Oceanography and Marine Biology: An Annual Review, Volume 45 (Oceanography and Marine Biology)

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Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Group, an informa business

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International Standard Serial Number: 0078-3218

CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2007 by R.N. Gibson, R.J.A. Atkinson and J.D.M. Gordon CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-1-4200-5093-6 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http:// www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

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Contents Preface Inherent optical properties of non-spherical marine-like particles — from theory to observation

vii

1

Wilhelmina R. Clavano, Emmanuel Boss & Lee Karp-Boss

Global ecology of the giant kelp Macrocystis: from ecotypes to ecosystems

39

Michael H. Graham, Julio A. Vásquez & Alejandro H. Buschmann

Habitat coupling by mid-latitude, subtidal, marine mysids: import-subsidised omnivores

89

Peter A. Jumars

Use of diversity estimations in the study of sedimentary benthic communities

139

Robert S. Carney

Coral reefs of the Andaman Sea — an integrated perspective

173

Barbara E. Brown

The Humboldt Current system of northern and central Chile — oceanographic processes, ecological interactions and socioeconomic feedback

195

Martin Thiel, Erasmo C. Macaya, Enzo Acuña, Wolf E. Arntz, Horacio Bastias, Katherina Brokordt, Patricio A. Camus, Juan Carlos Castilla, Leonardo R. Castro, Maritza Cortés, Clement P. Dumont, Ruben Escribano, Miriam Fernandez, Jhon A. Gajardo, Carlos F. Gaymer, Ivan Gomez, Andrés E. González, Humberto E. González, Pilar A. Haye, Juan-Enrique Illanes, Jose Luis Iriarte, Domingo A. Lancellotti, Guillermo Luna-Jorquera, Carolina Luxoro, Patricio H. Manriquez, Víctor Marín, Praxedes Muñoz, Sergio A. Navarrete, Eduardo Perez, Elie Poulin, Javier Sellanes, Hector Hito Sepúlveda, Wolfgang Stotz, Fadia Tala, Andrew Thomas, Cristian A. Vargas, Julio A. Vasquez & Alonso Vega

Loss, status and trends for coastal marine habitats of Europe

345

Laura Airoldi & Michael W. Beck

Climate change and Australian marine life

407

E.S. Poloczanska, R.C. Babcock, A. Butler, A.J. Hobday, O. Hoegh-Guldberg, T.J. Kunz, R. Matear, D. Milton, T.A. Okey & A.J. Richardson

Author Index

479

Systematic Index

535

Subject Index

541

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Preface The forty-fifth volume of this series contains eight reviews written by an international array of authors; as usual, the reviews range widely in subject and taxonomic and geographic coverage. The editors welcome suggestions from potential authors for topics they consider could form the basis of future appropriate contributions. Because an annual publication schedule necessarily places constraints on the timetable for submission, evaluation and acceptance of manuscripts, potential contributors are advised to make contact with the editors at an early stage of preparation. Contact details are listed on the title page of this volume. The editors gratefully acknowledge the willingness and speed with which authors complied with the editors’ suggestions, requests and questions and the efficiency of Taylor & Francis in ensuring the timely appearance of this volume.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 1-38 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES — FROM THEORY TO OBSERVATION WILHELMINA R. CLAVANO1, EMMANUEL BOSS2 & LEE KARP-BOSS2 1School of Civil and Environmental Engineering, Cornell University, 453 Hollister Hall, Ithaca, New York 14853, U.S. E-mail: [email protected] 2School of Marine Sciences, University of Maine, 5706 Aubert Hall, Orono, Maine 04469, U.S. E-mail: [email protected], [email protected] Abstract In situ measurements of inherent optical properties (IOPs) of aquatic particles show great promise in studies of particle dynamics. Successful application of such methods requires an understanding of the optical properties of particles. Most models of IOPs of marine particles assume that particles are spheres, yet most of the particles that contribute significantly to the IOPs are nonspherical. Only a few studies have examined optical properties of non-spherical aquatic particles. The state-of-the-art knowledge regarding IOPs of non-spherical particles is reviewed here and exact and approximate solutions are applied to model IOPs of marine-like particles. A comparison of model results for monodispersions of randomly oriented spheroids to results obtained for equalvolume spheres shows a strong dependence of the biases in the IOPs on particle size and shape, with the greater deviation occurring for particles much larger than the wavelength. Similarly, biases in the IOPs of polydispersions of spheroids are greater, and can be higher than a factor of two, when populations of particles are enriched with large particles. These results suggest that shape plays a significant role in determining the IOPs of marine particles, encouraging further laboratory and modelling studies on the effects of particle shape on their optical properties.

Introduction Recent advances in optical sensor technology have opened new opportunities to study biogeochemical processes in aquatic environments at spatial and temporal scales that were not possible before. Optical sensors are capable of sampling at frequencies that match the sub-metre and sub-second sampling scales of physical variables such as temperature and salinity and can be used in a variety of ocean-observing platforms including moorings, drifter buoys, and autonomous vehicles. In situ measurements of inherent optical properties (IOPs) such as absorption, scattering, attenuation and fluorescence reveal information on the presence, concentration and composition of particulate and dissolved material in the ocean. Variables such as organic carbon, chlorophyll-a, dissolved organic material, nitrate and total suspended matter, among others, are now estimated routinely from IOPs (e.g., Twardowski et al. 2005). Retrieval of seawater constituents from in situ (bulk) IOP measurements is not a straightforward problem — aquatic systems are complex mixtures of particulate and dissolved material, of which each component has specific absorption, scattering and fluorescence characteristics. In situ IOP measurements provide a measure of the sum of the different properties of all individual components present in the water column. Interpretation of optical data and its 1

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

successful application to studies of biogeochemical processes thus requires an understanding of the relationships between the different biogeochemical constituents, their optical characteristics and their contribution to bulk optical properties. Suspended organic and inorganic particles play an important role in mediating biogeochemical processes and significantly affect IOPs of aquatic environments, as can be attested from images taken from air- and space-borne platforms of the colour of lakes and oceans where phytoplankton blooms and suspended sediment have a strong impact (e.g., Pozdnyakov & Grassl 2003). Interactions of suspended particles with light largely depend on the physical characteristics of the particles, such as size, shape, composition and internal structure (e.g., presence of vacuoles). Optical characteristics of marine particles have been studied since the early 1940s (summarised by Jerlov 1968) and, with an increased pace, since the 1970s (e.g., Morel 1973, Jerlov 1976). In the past decade, development of commercial in situ optical sensors and the launch of several successful ocean-colour missions have accelerated the efforts to understand optical characteristics of marine particles, in particular the backscattering coefficient because of its direct application to remote sensing (e.g., Boss et al. 2004). These efforts, which have focused on both the theory and measurement of IOPs of particles, are summarised in books, book chapters and review articles on this topic (Shifrin 1988, Stramski & Kiefer 1991, Kirk 1994, Mobley 1994, Stramski et al. 2004, Jonasz & Fournier 2007, and others). Although considerable effort has been given to the subject of marine particles and their IOPs, there is still a gap between theory and the reality of measurement. Such a gap is attributed to both instrumental limitations (e.g., Jerlov 1976, Roesler & Boss 2007) and simplifying assumptions used in theoretical and empirical models (e.g., Stramski et al. 2001). The majority of theoretical investigations on the IOPs of marine particles assume that particles are homogeneous spheres. Optical properties of homogeneous spheres are well characterised (see Mie theory in, e.g., Kerker 1969, van de Hulst 1981) and there is good agreement between theory and measurement for such particles. Mie theory has been used to model IOPs of aquatic particles (e.g., Stramski et al. 2001) and in retrieving optical properties of oceanic particles (e.g., Bricaud & Morel 1986, Boss et al. 2001, Twardowski et al. 2001) with varying degrees of success. For example, while phytoplankton and bacteria dominate total scattering in the open ocean, based on Mie theory calculations for homogeneous spheres, they account for only a small fraction (<20%) of the measured backscattering (referred to as the ‘missing backscattering enigma’, Stramski et al. 2004). Uncertainties in the backscattering efficiencies of phytoplankton cells due to shape effects, however, are not well constrained and may account for a portion of this ‘missing’ backscattering. A sphere is not likely to be a good representative of the shape of the ‘average’ aquatic particle for two main reasons: (1) the majority of marine particles are not spherical, and (2) of all the convex shapes a sphere is rather an extreme shape: for a given particle volume it has the smallest surfacearea-to-volume ratio. Only a limited number of studies have examined the IOPs of non-spherical marine particles and results indicate a strong dependence of optical properties, in particular scattering, on shape (Aas 1984, Voss & Fry 1984, Jonasz 1987b, Volten et al. 1998, Gordon & Du 2001, Herring 2002, MacCallum et al. 2004, Quirantes & Bernard 2004, 2006, Gordon 2006). Unfortunately, with the exception of two, non-peer-reviewed publications (Aas 1984, Herring 2002) and a short book chapter (Jonasz 1991), there is no published methodical evaluation of shape effects on IOPs in the context of marine particles. The goal of this review is to provide a systematic evaluation of the effects of particle shape on the IOPs of marine particles, bringing together knowledge gained in ocean optics and other relevant fields. While it is recognised that marine particles (in particular, living cells) are not necessarily homogeneous, the focus in this article, for the sake of simplicity and due to limitations in available analytical and numerical solutions, is on the significance of the deviation from sphericity by homogeneous particles. A survey of theoretical and experimental studies on the IOPs of

2

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

s t s t = 0.25

s t = 0.5

s t =1

s t =2 s t =4

Figure 1 Illustration of spheroids of different aspect ratios, s/t; oblate spheroids (s/t < 1) and prolate spheroids (s/t > 1). A sphere is a spheroid with an aspect ratio of one.

non-spherical homogeneous particles addressing the wide range of particle sizes and indices of refraction relevant to aquatic systems is presented here. Exact analytical solutions are available for a limited number of shapes and physical characteristics (e.g., cylinders and concentric spheres larger than the wavelength and with an index of refraction similar to the medium, Aas 1984), but advances in computational power have enabled the growth of numerical and approximate techniques that permit calculations for a wider range of particle shapes and sizes (Mishchenko et al. 2000 and references therein). It is not realistic to develop a model for all possible shapes of marine particles but in order to cover the range of observed shapes, from elongated to squat geometries, a simple and smooth family of shapes — spheroids — is used here to model particles. Spheroids are ellipsoids with two equal equatorial axes and a third axis being the axis of rotation. The ratio of the axis of rotation, s, to an equatorial axis, t, is the aspect ratio, s/t, of a spheroid (Figure 1). The family of spheroids include oblate spheroids (s/t < 1; disc-like bodies), prolate spheroids (s/t > 1; cigar-shaped bodies), and spheres (s/t = 1). Spheroids provide a good approximation to the shape of phytoplankton and other planktonic organisms that often dominate the IOP signal. Furthermore, by choosing spheroids of varying aspect ratios as a model, solutions for elongated and squat shapes can easily be compared with solutions for spheres and the biases associated with optical models that are based on spheres can be quantified. This review focuses on marine particles because the vast majority of studies on IOPs of aquatic particles have been done in the marine context. However, the results presented here apply to particles in any other aquatic environment.

Bulk inherent optical properties (IOPs) Definitions Inherent optical properties (IOPs) refer to the optical properties of the aquatic medium and its dissolved and particulate constituents that are independent of ambient illumination. To set the stage for an IOP model of non-spherical particles, a brief description of the parameters that define the IOPs of particles is given here. For a more extensive elaboration on IOPs, the reader is referred to Jerlov (1976), van de Hulst (1981), Bohren & Huffman (1983) and Mobley (1994). Most of the notation used in this review follows closely that used by the ocean optics community (e.g., Mobley

3

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

1994). A summary of the notation along with their definitions and units of measure is provided in the Appendix (see p. 37). Light interacting with a suspension of particles can either be transmitted (remain unaffected) or attenuated due to absorption (transformed into other forms of energy, e.g., chemical energy in the case of photosynthesis) and due to scattering (redirected). Neglecting fluorescence, the two fundamental IOPs are the absorption coefficient, a(λ), and the volume scattering function (VSF), β(θ,λ), where λ is the incident wavelength and θ is the scattering angle. All other IOPs discussed here can be derived from these two IOPs. Other IOPs not discussed in the current review include the polarisation characteristics of scattering and fluorescence. While all quantities are wavelength dependent, the notation is henceforth ignored for compactness. The absorption coefficient, a, describes the rate of loss of light propagating as a plane wave due to absorption. According to the Beer-Lambert-Bouguer law (e.g., Kerker 1969, Shifrin 1988), the loss of light in a purely absorbing medium follows (Equation 11.1 in Bohren & Huffman 1983): E ( R ) = E (0 )e − aR [ W m −2 nm −1 ] ,

(1)

where E(R) is the incident irradiance at a distance R from the light source with irradiance E(0) [W m–2 nm–1]. The light source and detector are assumed to be small compared with the path length and the light is plane parallel and well collimated. The absorption coefficient, a, is thus computed from  1   E ( R )  −1 a = −   ln   [m ] .  R   E (0 ) 

(2)

This equation reveals that the loss of light due to absorption is a function of the path length and that the decay along that path is exponential. In a scattering and absorbing medium, such as natural waters, the measurement of absorption requires the collection of all the scattered light (e.g., using a reflecting sphere or tube). The volume scattering function (VSF), β(Ψ), describes the angular distribution of light scattered by a suspension of particles toward the direction Ψ [rad]. It is defined as the radiant intensity, dI(Ω) [W sr –1 nm–1] (Ω [sr] being the solid angle), emanating at an angle Ψ from an infinitesimal volume element dV [m3] for a given incident irradiant intensity, E(0): β(Ψ ) =

1 dI (Ω) [ m −1sr −1 ] . E (0 ) dV

(3)

It is often assumed that scattering is azimuthally symmetric so that β(Ψ ) = β(θ) , where θ [rad] is the angle between the initial direction of light propagation and that to which the light is scattered irrespective of azimuth. The assumption of azimuthal symmetry is valid for spherical particles or randomly oriented non-spherical particles. This assumption is most likely valid for the turbulent aquatic environment of interest here; it is assumed throughout this review and is further addressed in the following discussion. A measure of the overall magnitude of the scattered light, without regard to its angular distribution, is given by the scattering coefficient, b, which is the integral of the VSF over all (4π[sr]) angles:

4

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

b≡

∫

4π

β(Ψ )dΩ =

0

2π

∫ ∫ 0

π

β(θ, ϕ)sin θdθdϕ = 2π

0

∫

π

β(θ) sin θdθ [m −1 ] ,

(4)

0

where ϕ [rad] is the azimuth angle. Scattering is often described by the phase function, β
(θ) , which is the VSF normalised to the total scattering. It provides information on the shape of the VSF regardless of the intensity of the scattered light: β(θ) −1 [sr ] . β
θ ≡ b

()

(5)

Other parameters that define the scattered light include the backscattering coefficient, bb, which is defined as the total light scattered in the hemisphere from which light has originated (i.e., scattered in the backward direction): bb ≡

∫

2π

β(Ψ )dΩ = 2π

0

∫

π π 2

β(θ)sin θdθ [m −1 ] ,

(6)

and the backscattering ratio, which is defined as b b
≡ b [dimensionless]. b

(7)

Finally, the attenuation coefficient, c, describes the total rate of loss of a collimated, monochromatic light beam due to absorption and scattering: c = a + b [ m −1 ] ,

(8)

which is the coefficient of attenuation in the Beer-Lambert-Bouguer law (see Equation 1) in an absorbing and/or scattering medium (Bohren & Huffman 1983): E ( R ) = E (0 )e − cR [ W m −2 nm −1 ] .

(9)

When describing the interaction of light with individual particles it is convenient to express a quantity with dimensions of area known as the optical cross section. An optical cross section is the product of the geometric cross section of a particle and the ratio of the energy attenuated, absorbed, scattered or backscattered by that particle to the incident energy projected on an area that is equal to its cross-sectional area (denoted by Cc, Ca, Cb and C bb , respectively). For a nonspherical particle, the cross-sectional area perpendicular to the light beam, G [m2], depends on its orientation. In the case when particles are randomly oriented, as assumed here, it has been found that for convex particles (such as spheroids) the average cross-sectional area perpendicular to the beam of light (here denoted as 〈G 〉 ) is one-fourth of the surface area of the particle (Cauchy 1832). In analogy to the IOPs (Equation 8), the attenuation cross section is equal to the sum of the absorption and scattering cross sections: C c = C a + C b [m 2 ] .

5

(10)

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

Many theoretical texts on optics focus on optical efficiency factors, Qc,a,b,bb , in their treatment of light interaction with particles (e.g., van de Hulst 1981). Optical efficiency factors are the ratios of the optical cross sections to the particle cross-sectional area; their appeal is in that efficiency factors of compact particles are bounded (i.e., their values rarely exceed three) and their values for particles much larger than the wavelength are constant and independent of composition (see below). For non-spherical particles efficiency factors for attenuation, absorption, scattering and backscattering, respectively, are defined as (e.g., Mishchenko et al. 2002):

Qc,a,b,bb ≡

Cc,a,b,bb [dimensionless]. 〈G 〉

(11)

Other useful optical parameters are the volume-normalised cross sections defined as:

α c ,a ,b ,bb ≡

C c ,a ,b ,bb V

[ m −1 ] ,

(12)

where V [ m −3 ] is the particle volume; they provide insight into what size particle most effectively affects light per unit volume (or per unit mass, see Bohren & Huffman 1983, and Figure 6 in Boss et al. 2001). To relate IOPs to optical cross sections, efficiency factors and volume-normalised cross sections, information on particle concentration (and size distribution, see below) is required. For example, for N identical particles within a unit volume, the relations are given by: c, a, b, bb = NCc,a,b,bb = N 〈G 〉Qc,a,b,bb = NV α c,a,b,bb [m −1 ].

(13)

Characteristics of particles affecting their optical properties Three physical characteristics of homogeneous particles determine their optical properties: the complex index of refraction relative to the medium in which the particle is immersed, the size of the particle with respect to the wavelength of the incident light and the shape of the particle. For non-spherical particles, specifying the orientation of the particle in relation to the light beam is an additional requirement. To continue to set the stage for an optical model for non-spherical particles, the physical characteristics of marine particles are discussed in this section and the values that are used to parameterise them in the current study are provided. Index of refraction The complex index of refraction comprises real, n, and imaginary, k, parts: m = n + ik [dimensionless] .

(14)

The real part is proportional to the ratio of the speed of light within a reference medium to that within the particle. It is convenient to choose the reference medium to be that in which the particle is immersed, in which case the proportionality constant is one. The imaginary part of the index of refraction (referred to as the absorption index, e.g., Kirk 1994) represents the absorption of light

6

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

as it propagates through the particle. It is proportional to the absorption by the intra-particle material, α*[nm–1]: k=

α ∗λ [dimensionless]. 4π

(15)

These definitions are independent of particle shape. For purposes of biogeochemical and optical studies it is often convenient to group aquatic particles into organic and inorganic pools. Organic particles comprise living (viruses, bacteria, phytoplankton and zooplankton) and non-living material (faecal pellets, detritus; although these are likely to harbour bacteria). Inorganic particles consist of lithogenous minerals (quartz, clay and other minerals) and minerals associated with biogenic activity (calcite, aragonite and siliceous particles). Particles in each of these two main groups share similar characteristics with respect to their indices of refraction. Living organic particles often have a large water content (Aas 1996), making them less refractive than inorganic particles. The real part of the index of refraction of aquatic particles ranges from 1.02 to 1.2; the lower range is associated with organic particles while the upper range is associated with highly refractive inorganic materials (Jerlov 1968, Morel 1973, Carder et al. 1974, Aas 1996, Twardowski et al. 2001). The imaginary part of the index of refraction spans from nearly zero to 0.01, with the latter associated with strongly absorbing bands due to pigments (e.g., Morel & Bricaud 1981, Bricaud & Morel 1986). This review aims to primarily illustrate the effects of shape as it applies to two ‘representative’ particle types: phytoplankton with m = 1.05 + i0.01 and inorganic particles with m = 1.17 + i0.0001 (Stramski et al. 2001). Varying the real and imaginary parts of the index of refraction among the values of the two illustrative particles chosen here showed similar dependence on changes in index of refraction to those observed in spheres (van de Hulst 1981, Herring 2002) and was not found to provide additional insight into the effects of shape on IOPs. Size Size is a fundamental property of particles that determines sedimentation rates, mass transfer to and from the particle (e.g., nutrient fluxes and dissolution), encounter rates between particles and, most relevant to this review, their optical properties. Foremost, the ratio of particle size to wavelength determines the resonance characteristics of the VSF (its oscillatory pattern as a function of scattering angle) and the size for which maximum scattering per volume will occur (i.e., maximum αb). In addition, in general, the larger an absorbing particle is, the less efficient it becomes in absorbing light per unit volume (i.e., the volume-normalised absorption efficiency, αa, decreases with increasing size), often referred to as the package effect or self-shading (see Duysens 1956). In both marine and freshwater environments particles relevant to optics span at least eight orders of magnitude in size, ranging from sub-micron particles (colloids and viruses) to centimetresize aggregates and zooplankton (Figure 2). Numerically, small particles are much more abundant than larger particles. A partitioning of particles into logarithmic size bins shows that each bin includes approximately the same volume of particulate material (Sheldon et al. 1972). This observation is consistent with a Junge-like (power-law) particulate size distribution (PSD), where the differential particle number concentration is inversely proportional to the fourth power of size (Junge 1963, Morel 1973; see p. 22). Several other distribution functions have been used to represent size distributions of particles in the ocean, which include the log-normal distribution (Jonasz 1983, Shifrin 1988, Jonasz & Fournier 1996), the Weibull distribution (Carder et al. 1971), the gamma distribution (Shifrin 1988)

7

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

Rayleigh 0.1 nm

1 nm

Rayleigh−Gans−Debye 0.1 µm

10 nm

Van de Hulst 1 µm

10 µm

Geometric Optics 100 µm

1 mm

1 cm

Dissolved organic matter Water molecules

Suspended particulate matter Truly soluble substances Colloids Viruses Bacteria Phytoplankton: Pico-

Nano-

MicroZooplankton

Organic detritus, minerogenic particles Bubbles 10−10

10−9

10−8

10−7

10−6 10−5 Particle size (m)

10−4

10−3

10−2

Figure 2 Representative sizes of different constituents in sea-water, after Stramski et al (2004). Optical regions referred to in the text are denoted at the top axis (shading represents approximate boundaries between these regions). These boundaries vary with refractive index for a given particle size.

and sums of log-normal distributions (Risoviç 1993). Here, the focus is on particles ranging in diameter from 0.2 to 200 µm (diameter here is given by that of an equal-volume sphere). The lower bound is associated with a common operational cutoff between dissolved and particulate material — often set by a filter with that pore size — and the upper bound chosen arbitrarily to represent the upper bound of particles that can still be assumed to be distributed as a continuum in operational measurements (Siegel 1998). Two particulate size distributions are adopted (as in Twardowski et al. 2001) for the illustrative optical model used in this study: the power-law distribution and that described by Risoviç (1993). Shape Several measures have been used to characterise the shape of particles in nature; some focus on the overall shape while others concentrate on specific features such as roundness and compactness. An elementary measure of particle shape is the aspect ratio, which is the ratio of the principal axes of a particle. It describes the elongation or flatness of a particle and hence the deviation from a spherical shape (a sphere having an aspect ratio of one). Shape effects on optical properties are examined here by modelling the IOPs of spheroids of varying aspect ratios. Aquatic particles vary greatly in their shape; most notable is the striking diversity in cell shapes among phytoplankton. Hillebrand et al. (1999) provides a comprehensive survey of geometric models for phytoplankton species from 10 taxa. Two relevant results arise from their analysis: (1) the sphere is not a common shape among microphytoplankton taxa and (2) despite the apparent high diversity of cell geometries, the diverse morphologies represent variations on a smaller subset of geometric forms, primarily ellipsoids, spheroids and cylinders. Picoplankton, which are not included in the analysis of Hillebrand et al. (1999), tend to be more spherical in shape, although rod-like morphologies are also common.

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Number of cells per size bin (N)

The authors are not aware of any published paper that provides the range of values of aspect ratios of phytoplankton cells in natural assemblages. To demonstrate the deviation from a spherical shape among phytoplankton, field data on cell dimensions of different taxonomic groups (nanoand microphytoplankton) were used to calculate aspect ratios of phytoplankton (Figure 3; data available from the California State Department of Water Resources). Aspect ratios of phytoplankton span a wide range, varying between 0.4 and 72 (Figure 3). Diatom chains, which are not included in the analysis, can have even higher aspect ratios. The frequency distribution of the aspect ratios shows that elongated shapes are a more common form compared with spheres or squat shapes (Figure 3). Inorganic aquatic particles are very often non-spherical; clay mineral particles have plate-like crystalline structures with sizes on the order of D = 0.5 µm and have aspect ratios varying between 0.05 and 0.3 (Jonasz 1987b, Bickmore et al. 2002). In nature, clays tend to aggregate and form larger particles with reduced aspect ratios. It is not possible to generalise their shapes except to say that they are extremely variable and do not look like spheres. Larger sedimentary particles such as sand and silt have aspect ratios ranging between 0.04 and 11 (derived from Komar & Reimers 1978, Baba & Komar 1981). Consistent with these observations, spheroids with aspect ratios between 0.1 and 46 are used in the analysis of IOPs of non-spherical particles presented here (98% of the cells that constitute the data in Figure 3 are within this range). Finer-scale structures that may be found in each particle do not dominate scattering, in general, as much as the effect of the

3000 2500 2000 N = 8059

1500 1000 500 0

0.5

1

2

5 10 Aspect ratio

20

50

Figure 3 Frequency distribution of aspect ratios of phytoplankton. Data are provided by the California State Department of Water Resources and the U.S. Bureau of Reclamation and are available on the Bay-Delta and Tributaries (BDAT) project website at http://baydelta.water.ca.gov/. A subset of the data was randomly selected for the analysis here and includes data collected during the period 2002–2003 from a variety of aquatic habitats: from freshwater in the Sacramento-San Joaquin Delta to estuarine environments in the Suisun and San Pablo Bays (California, USA). The data include phytoplankton from five different classes, including Bacillariophyceae (diatoms), Chlorophyceae, Cryptophyceae, Dynophyceae, and Cyanophyceae (N = 8059 cells). Phytoplankton analyses (identification, counts, and measurements of cell dimensions) were conducted at the Bryte Chemical Laboratory (California Department of Water Resources). Further information on the methods used can be found at http://iep.water.ca.gov/emp/Metadata/Phytoplankton/. The aspect ratio is calculated as the ratio between the rotational and equatorial axes of a cell based on the three-dimensional shape associated with each species as provided in Hillebrand et al. (1999). The reader is cautioned on the fact that the phytoplankton data do not include picophytoplankton (i.e., cells smaller than 2 µm) that tend to be more spherical in shape.

9

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

‘gross’ shape of the particle (Gordon 2006). Furthermore, Gordon (2006) found that, in theory, the total scattering of any curved shape (that is not rotationally symmetric) will behave similarly for a given particle thickness and cross-sectional area. However, when a particle exhibits sharp edges, smooth shapes are not able to reproduce the sharp spikes observed in the forward scattering (Macke & Mishchenko 1996). To allow comparisons between spheroids and spheres, particle size is used as a reference. The definition of size is often ambiguous when dealing with non-spherical particles; here the size of a spheroid is defined as the diameter of an equal-volume sphere ( D = 2 3 st 2 ). This was chosen for two main reasons: (1) popular particle sizers such as the Coulter counter are sensitive to particle volume and (2) mass, which is most often the property of interest in studies of particles, is proportional to particle volume. Size and shape, however, may not be independent attributes for aquatic particles. There appears to be a tendency for particles in ocean samples to deviate from a spherical shape as particle size increases (Jonasz 1987b). This trend has been observed for particles in both coastal (Baltic Sea) and offshore areas (Kadyshevich 1977, Jonasz 1987a). Shape effects on IOPs are examined here for two types of particulate populations: monodispersions (comprising particles with one size and one shape) and polydispersions (comprising particles with varying sizes and shapes) and are quantified by defining a bias, γ c ,a ,b ,bb, which is the ratio of the IOPs (attenuation, absorption, scattering and backscattering, respectively) of spheroids to that of spheres with the same particle volume distribution. Orientation In this review particles are assumed to be randomly oriented. IOPs of non-spherical particles, however, are strongly dependent on particle orientation (e.g., Latimer et al. 1978, Asano 1979) but data on the orientation of particles found in the natural marine environment are practically nonexistent. There are certain cases for which the assumption of random orientation may not apply because of methodological issues or because environmental conditions cause particles to align in a preferred orientation. Non-random orientation associated with methodology will be encountered when: (1) the instrument used to measure an IOP causes particles to orient themselves relative to the probing light beam (e.g., the flow cytometer in which particles are aligned one at a time within the flow chamber) and (2) when the existence of particles of a given sub-population (e.g., big diatom chains) is rare enough in the sample volume such that not all orientations are realised in a given measurement. In the latter case, averaging over many samples is necessary to randomise orientations. In the natural environment, shear flows can result in the alignment of particles with respect to the flow (e.g., Karp-Boss & Jumars 1998). When the environment is quiescent enough, large aggregates are oriented by the force of gravity as can be seen in photographs of in situ long stringers and teardrop-shape flocs (e.g., Syvitski et al. 1995). The following optical characteristics can be used to assess whether or not an ensemble of particles is randomly oriented (Mishchenko et al. 2002): (1) the attenuation, scattering and absorption coefficients are independent of polarisation and instrument orientation; (2) the polarised scattering matrix is block diagonal; and (3) the emitted blackbody radiation is unpolarised. Note that care should be applied so that the measurement procedures have minimal effect on the orientation of the particles investigated. Given that the orientation of aquatic particles is currently unconstrained we proceed in this review by assuming random orientation. Future studies, however, may find orientation effects to be important under certain conditions as was found in atmospheric studies due, for example, to orientation of particles under gravity (e.g., Aydin 2000).

10

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

Optical regimes A century and a half of theoretical studies on the interaction of light and particles has taught us that this interaction is strongly dependent on several parameters. First among them is the size parameter, x, which is defined as the ratio of the particle size to the wavelength: x=π

D [dimensionless], λ

(16)

where D is the particle size and λ is the wavelength of light within the medium (both with the same units), in this case water. An additional important parameter is the ratio of the speed of light within the particle to that in the medium (it is the reciprocal of the real part of the index of refraction of the particle to that of water, n). Marine particles are mostly considered to be ‘soft’; their index of refraction is close to that of water, that is, m − 1 ≈ n − 1  1. Finally, another important parameter is the phase shift parameter, ρ, which describes the shift in phase between the wave travelling within the particle and the wave travelling in the medium surrounding it and is a function of both the size parameter and the index of refraction of that particle:

(

)

ρ = 2 x n − 1 [dimensionless].

(17)

These parameters are useful to delineate optical regimes for which analytical approximations that apply to soft particles have been developed (see below). The material in this section borrows heavily from Bohren & Huffman (1983), Mishchenko et al. (2002) and Kokhanovsky (2003), where more details can be found. Many of the approximations discussed in these references are applicable to randomly oriented non-spherical particles (as in the case of marine particles) and help establish an intuition for their optical characteristics when compared with spheres. The characteristics of particles (size and index of refraction) most emphasised in Bohren & Huffman (1983), Mishchenko et al. (2002) and Kokhanovsky (2003), however, are significantly different from those of marine particles.

Particles much smaller than the wavelength The Rayleigh region (RAY) ( x  1, ρ  1, D  λ ) In this optical region shape does not contribute to the optical properties of particles; for a given wavelength, the IOPs are only dependent on particle volume and its index of refraction (e.g., Kerker 1969, Bohren & Huffman 1983, Kokhanovsky 2003): 3 1 + cos 2 (θ) 
β θ =  [dimensionless], 4

()

Cc =

k 2V 2 m 2 − 1

Ca =

6π

2

[m 2 ],

4 πkV [m 2 ], λ 11

(18)

(19)

(20)

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

Cb = Cc − Ca [m 2 ], Cbb =

Cb [m 2 ], 2

(21) (22)

where k = 2π/λ [nm–1] is the wave number. Since the IOPs are a function of only particle volume, incident wavelength and index of refraction (Equations 18–22), there is no difference between the IOPs of non-spherical particles and equal-volume spheres. In the marine environment, small organic and inorganic dissolved molecules fall within this regime.

Particles of size much larger than the wavelength The geometric optics (GO) region ( x  1, ρ  100, D  λ ) In this optical region scattering is dominated by diffraction although refraction effects introduce a necessary correction for intermediate values of the size parameter (known as ‘edge effects’, e.g., Kokhanovsky & Zege 1997). An analytical solution has been derived for the attenuation cross section of absorbing particles of random shape in this region (e.g., Kokhanovsky & Zege 1997) and is given by: 

Cc = 2  1 + x 

−2  3 

〈G 〉 [m 2 ].

(23)

The absorption cross section, Ca, can also be derived analytically. In general, it is a complex function of both parts of the index of refraction and x (e.g., Kokhanovsky & Zege 1997). For sizes where kx  1, it simplifies to C a = 〈G 〉. Within the GO region, these analytical solutions imply that the attenuation, absorption, and scattering (but not the VSF) of a randomly oriented non-spherical particle will be the same as that of a sphere of the same cross-sectional area, that is, it will approach the geometric optics limit (Kerker 1969): lim γ c ,a ,b =

ρ→∞

〈G 〉 ≥ 1. G

(24)

Given that the average cross-sectional area of a sphere is always the smallest of any convex shape of the same volume, an equal-volume sphere will always underestimate the IOPs of particles much larger than the wavelength. The VSF in this regime for known shapes (including spheroids) can be obtained from ray tracing computations (see below). Particles that fall in this region in the marine environment include large diatom chains, large heterotrophs (e.g., Noctiluca sp.), mesoand macrozooplankton and macrosize aggregates, including faecal pellets.

Particles of size comparable to or larger than the wavelength The Rayleigh-Gans-Debye (RGD) (x < 1, ρ < 1, D ≈ λ) and the van de Hulst (VDH) (x > 1, 1 < ρ < 100, D > λ) regions The RGD and VDH optical regions are of particular interest because many optically relevant marine particles (e.g., phytoplankton and sediments) fall within them. However, no simple closed-form analytical solution exists for randomly oriented non-spherical particles in these regions (Aas 1984). 12

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

Scattering by soft particles in the RGD and VDH regions is dominated by diffraction although contributions from reflection and refraction need to be taken into account. Absorption is assumed to be independent of the real part of the index of refraction, although more recent approximations have included n effects on absorption (Kokhanovsky & Zege 1997). Simple analytical solutions for Cc, Ca and Cb have been derived for spheres and for some simple shapes by van de Hulst (1981) and Aas (1984). Shepelevich et al. (2001), following Paramonov (1994a,b), derive Cc, Ca and Cb for randomly oriented monodispersed spheroids from a polydispersed population of spheres having the same volume and cross-sectional area. A similar approach is used here to examine the IOPs of non-spherical marine-like particles but, rather than follow Shepelevich et al. (2001) who used the approximation given by van de Hulst (1981) to obtain the optical values for spheres, values for spheres are derived here directly from Mie theory. Size ranges of aquatic constituents and optical regions are provided in Figure 2 for the particular wavelength (λ = 676 nm) and the specific refractive indices (n = 1.05, 1.17) used in this review. Results for other visible wavelengths are not expected to be very different and can be deduced from the results presented here by changing the diameter while keeping x constant. Similarly, the indices of refraction used here span the range of those of marine particles thus bounding the likely results for all relevant marine particles. The sizes associated with the different optical size regions are provided in Table 1.

IOPs of monodispersions of randomly oriented spheroids Exact and approximate methods Since the 1908 paper by Mie there is now an exact solution (in the form of a series expansion) providing the optical properties of a homogeneous sphere of any size and index of refraction relevant to aquatic optics. Unfortunately, there is no equivalent converging solution for non-spherical particles for all relevant sizes. Asano & Yamamoto (1975) obtained an exact series solution for scattering by spheroids of arbitrary orientation but their solution did not converge for size parameters >30. Obtaining optical properties of non-spherical particles for the wide range of sizes exhibited by marine particles requires the use of several methods, each valid within a specific optical region. The appropriate application of each of these approaches depends on the combination of sizes, shapes and refractive indices of the particles of interest. For small particles the T-matrix method (Waterman 1971, cf. Mishchenko et al. 2000), which is an exact solution to Maxwell’s equations for light scattering, applies. This method is limited to particles with a phase shift parameter that is smaller than approximately 10 (it covers particles with phase shift parameters as large as those in the RGD region, see Table 1). As particles deviate from a spherical shape the phase shift parameter for which this method is valid decreases. For larger particles, a variety of methods that provide approximate solutions for optical properties have been used (see Mishchenko et al. 2002 for a review of the state of the art). Table 1 Size ranges roughly corresponding to the size regions defined for two different refractive indices given λ = 676 nm Size region RAY RGD VDH GO

n = 1.05

n = 1.17

Equivalent ρ

D  0.2 µm D < 5 µm 5 < D < 200 µm D  200 µm

D  0.2 µm D < 2 µm 2 < D < 65 µm D  65 µm

ρ  0.1 ρ<3 3 < ρ < 100 ρ  100

13

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

One such approximation is the Paramonov (1994b) method for obtaining the attenuation, absorption and scattering of optically soft spheroids (Shepelevich et al. 2001). In this approach, a polydispersion of spheres with the same volume and average cross section (given an appropriate size distribution) is used to provide the attenuation, absorption and scattering coefficients of a monodispersion of randomly oriented spheroids. A comparison of absorption and attenuation efficiencies obtained by this method with T-matrix results (for the largest sizes possible) reveals that the differences are <0.2% for Qa and <3% for Qc when m = 1.05 + i0.01 (i.e., an organic-like particle). When m = 1.17 + i0.0001 (i.e., an inorganic-like particle), differences between the two methods are <4% for Qa and <5% for Qc. Another method is the ray tracing technique (the implementation by Macke et al. 1995 is used here), which provides solutions for the IOPs in the geometric optics region (good for soft particles with a phase shift parameter greater than ρ = 400 (n – 1) (based on Mishchenko et al. 2002) and applies to particles such as large zooplankton and aggregates; Table 1 and Figure 2). Using this approach, the phase function, β
(θ) , for which there is no solution in the relevant intermediate sizes, can be approximated. In addition, it provides both the VSF, β(θ) , and the backscattering coefficient, bb, for this size range. This method agrees well with the Paramonov method described above,with a difference of 3% for Qc, 5% for Qa and 0.2% for Qb, for m = 1.05 + i0.01; and of 3% for Qc, 40% for Qa and 3% for Qb, for m = 1.17 + i0.0001, thus increasing the confidence in the former approach as well. The relatively larger difference in the absorption efficiency is due to the fact that the absorption index is too small to bring even the largest particles considered here to approach the geometric optics limit, that is, the condition kx  1 is not satisfied. The ray tracing method is therefore used here only for computing the VSF in the GO limit while the Paramonov approach is used to obtain c, a and b at that limit. Two other approaches were evaluated: (1) an analytical approximation method developed by Fournier & Evans (1991) to obtain the attenuation efficiency of randomly oriented spheroids (this approach works extremely well for a wide range of particles) and (2) an analytical approximation method developed by Kirk (1976) to obtain the absorption cross section of randomly oriented spheroids. The agreement between these two methods and the T-matrix method was not as good as the agreement with the Paramonov method and therefore these two methods are not used here. The data used in this review can be found at http://misclab.umeoce.maine.edu/research/research10_ data.php. Numerical codes used in this review can be found at http://misclab.umeoce.maine.edu/ software.php.

Results: IOPs of a monodispersion Application of the methods described above to a wide range of particle sizes and aspect ratios (across all optical regions) reveals the potential biases associated with the use of spheres as models to obtain optical properties of monodispersed non-spherical particles (which may apply, for example, to single species blooms and laboratory studies of phytoplankton cultures). The volume scattering function The VSFs of monodispersed, non-spherical particles do not have the resonance structure (expressed as oscillations in the VSF as a function of scattering angle) observed for monodispersed spheres, much like polydispersions of spheres (Ch´ylek et al. 1976; see also Figure 4 in Mishchenko et al. Figure 4 (see facing page) (See also Colour Figure 4 in the insert following page 344.) The volume scattering function for spheres, β  (θ) (A, D), and for equal-volume spheroids, β
(θ) with aspect ratio s/t = 2 (B, E). The ratio between the two (i.e., the bias denoted as γβ(θ) is presented in panels C and F. The primary y-axis for each plot represents variation in particle size, D[µm], while the secondary y-axis represents variation in the phase shift parameter, ρ (scale found on C and F). Results are for two different types of particles: phytoplankton-like particles with m = 1.05 + i0.01 (A, B, C) and inorganic-like particles with m = 1.17 + i0.0001 (D, E, F). Values for spheroids have been obtained using the T-matrix method for D ≤ 10 µm and by the ray tracing method for D ≥ 40 µm. No solution is available for 10 < D < 40 µm (white regions in B, C, E and F).

14

Particle size D (µm)

15

0.2

0

60

90 120 150 180

Scattering angle θ (deg)

30

10−5 0

60

90 120 150 180

Scattering angle θ (deg)

30

10−3

10−1

101

103

10−4

10−2

100

102

104

0

m = 1.17 + i0.0001

F

m = 1.05 + i0.01

C

5

10

20

50

100

300 200

0.2

0.5

1

2

5

10

20

50

100

60

0.5 90 120 150 180 Scattering angle θ (deg)

30

1

m = 1.17 + i0.0001

E

m = 1.05 + i0.01

B

2

10−2

102

105

10−5

10−2

102

105

β (θ) β (θ)

1

m = 1.17 + i0.0001

D

m = 1.05 + i0.01

A

γ β (θ) =

0.5

2

5

10

20

50

200

0.2

0.5

1

2

5

10

20

50

200

s β (θ) (m−1sr−1); t = 2

Phase shift parameter ρ

Figure 4

Particle size D (µm)

β (θ) (m−1sr−1)

10−1

100

101

102

10−1

100

101

102

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

Phase shift parameter ρ

50931_C001.fm Page 16 Thursday, May 10, 2007 8:38 PM

WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

2002). Because the VSF is smoother for spheroids (Figure 4B,E, see also Colour Figure 4 in the insert following p. 344), the anomalous diffraction peaks inherent in spheres determine the pattern of the biases (Figure 4C,F). Internal transmission and refraction cause the number of peaks in the VSF for spheres to increase with particle size; however, the magnitudes are dampened and so is the general trend in the bias. For both large non-spherical organic-like and inorganic-like particles, forward scattering is stronger compared with that of equal-volume spheres (Figure 4). In the backward and side-scattering directions, however, there are differences in the biases in the VSF between the two types of particles; for organic-like particles, the largest biases are in the backward direction and are associated with small particles (in particular, particles on the order of the wavelength of light, e.g., D ≈ 0.5 µm; Figure 4C). For inorganic-like particles the largest differences are in the side-scattering direction and are associated with large particles (Figure 4F). Attenuation, absorption and scattering: efficiency factors and biases Efficiency factors for attenuation, Qc, as a function of particle size, show a similar trend of variation for spheres and spheroids (Figures 5 and 6), approaching an asymptotic value of two when the GO limit is reached (Figure 6A,B). The size, D, however, at which Qc reaches its maximal value increases with increased departure from a spherical shape (Figure 6A,B). In general, a sphere will overestimate the attenuation (γc < 1) of an equal-volume spheroid (up to 50% for the most extreme shapes) but will underestimate the attenuation (γc > 1) of an equalvolume spheroid for particles larger than the wavelength (Figures 7A,C and 8A,B). Scattering dominates attenuation; the efficiency factors and biases for scattering are very similar to those of attenuation (Figures 6E,F, 8E,F, 9A,C and 10A,C). The trend in the change of the efficiency factors for absorption, Qa, as a function of particle size is similar for spheres and spheroids, approaching an asymptotic value of one at the GO limit (Figures 5B,D and 6C,D). The absorption efficiency factor of spheroids, however, is always lower than or equal to that of an equal-volume sphere, regardless of particle size and aspect ratio (Figure 6C,D). Absorption efficiency factors of inorganic-like particles are low (Figure 6D) and the biases in absorption between spheres and spheroids are small (Figure 8D). Biases in absorption are also small for small organic-like particles (γa ≈ 1; Figure 8C), but increase with increasing particle size and deviation from sphericity. For large organic-like particles, absorption by a spheroid is always larger than that of a sphere of the same volume (Figures 7B and 8C). That is because the absorbing material in a randomly oriented spheroid is less packaged compared with that in a sphere, exposing more absorbing material to the incident light. However, Qa is smaller for a randomly oriented spheroid (Figures 5B,D and 6C,D), as it is derived from Ca by dividing by the average cross-sectional area, which is always smaller for spheres. The backscattering bias can be very large (by a factor of 16, Figure 10B), especially in the RGD region and for particles much larger than the wavelength (Figures 8G,H and 10B,D). For the largest particles, the backscattering does not reach the asymptotic value of the other IOPs, at least in the range of sizes examined here. By applying an unrealistically large absorption value, however, the backscattering bias does approach the same asymptotic value as total scattering (by using the T-matrix method, Herring 2002). The volume-normalised cross sections for attenuation and scattering, αc and αb, respectively, illustrate that the size contributing most to attenuation and scattering (per unit volume or per unit mass) is larger for spheroids than for equal-volume spheres (Figure 11A,B,E,F; consistent with the findings by Jonasz (1987a) that there is as much as a 300% difference between spheres and spheroids in the volume-normalised attenuation cross section). In general, the magnitude of the volume-normalised cross sections for attenuation and scattering decreases with departure from sphericity, suggesting 16

50931_C001.fm Page 17 Thursday, May 10, 2007 8:38 PM

INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 100 Qa

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 100 Qc 20

A

2.5

Aspect ratio ts

10

B

0.8

2

5 2 1

1

1.5

0.6

1

0.4

0.5

0.2

0.5 0.2

m = 1.05 + i0.01

m = 1.05 + i0.01

0.1 0.5 1 20

2

5 10 20

50 100 200

Qc

C

Aspect ratio ts

5 10 20

50 100 200

Qa 0.3

D

0.25

2.5

5

0.2

2

2

0.15

1.5

1

0.1

1

0.5

0.1 0.2 0.5 1

2

3

10

0.2

0.5 1 3.5

m = 1.17 + i0.0001

0.05

0.5

2 5 10 20 50 100 200 Particle size D (µm)

m = 1.17 + i0.0001 0.2 0.5 1

2 5 10 20 50 100 200 Particle size D (µm)

Figure 5 Efficiency factors for attenuation, Qc (A, C), and absorption, Qa (B, D), for spheroids as a function of size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top), and aspect ratio, s/t. Results were derived using the T-matrix method for small particles (area within the white line to the left of each plot), and the Paramonov (1994b) method for intermediate and larger particles (rest of the plot), for two different types of particles: phytoplankton-like particles with refractive index m = 1.05 + i0.01 (A, B) and inorganic-like particles with m = 1.17 + i0.0001 (C, D).

that spheres interact (resonate) better, per unit volume, with the impinging radiation compared with other shapes. Similar to attenuation and scattering, model results for the volume-normalised cross section for backscattering, α bb , show that the size contributing most to backscattering is larger for spheroids than for equal-volume spheres (Figure 11G,H). Unfortunately, the lack of solutions for intermediate regions limits the ability here to discuss α bb any further. The volume-normalised absorption cross section, αa, is higher for all strongly absorbing spheroids with low indices of refraction, consistent with the idea that in a randomly oriented monodispersion of homogeneous spheroids more material can interact with the incident light than in a monodispersion of spheres of the same volume, which is better ‘packaged’ or ‘self-shaded’ (Figure 11C,D). This is not the case for weakly absorbing particles that are smaller than a few microns — probably due to scattering within the particle that increases the average path length of a light ray — hence increasing the probability of absorption. This effect is slightly larger for spheres given that they are more effective scatterers (Figure 11D). 17

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

3 2.5

Phase shift parameter ρ

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50

4

A

Qc

Qc

1.5 1

2

m = 1.17 + i0.0001

0 0.4

C

0.3 Qa

0.8 Qa

200

B

m = 1.05 + i0.01

0

0.6 0.4

0.2 0.1

0.2

m = 1.05 + i0.01

0

D

m = 1.17 + i0.0001

Aspect ratio st 10 2 1 0.5 0.1

0 4

2.5 E

F

2

3

1.5

Qb

Qb

5 10 20 50

1

0.5

1

2

3

2

1.2

0.5 1

2

1 1

0.5 m = 1.05 + i0.01

0 0.004 G

0.1

m = 1.05 + i0.01

H 0.08 Q bb

0.003 Q bb

m = 1.17 + i0.0001

0

0.002

0.06 0.04

0.001 0.000 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

0.02 200

m = 1.17 + i0.0001 0 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

200

Figure 6 Efficiency factors for attenuation, Qc (A, B), absorption, Qa (C, D), scattering, Qb (E, F), and backscattering, Qbb (G, H), for spheroids as a function of size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top), and aspect ratio, s/t. Results were derived using the T-matrix method for small particle sizes and the Paramonov (1994b) method for intermediate sizes, while the ray tracing method was used to obtain Qbb for large sizes. Results are presented for two different types of particles: a phytoplankton-like particle with refractive index m = 1.05 + i0.01 (A, C, E, G) and an inorganic-like particle with m = 1.17 + i0.0001 (B, D, F, H). The lines represent aspect ratios (legend is shown in D): oblate spheroids with s/t = 0.5 (grey solid line) and s/t = 0.1 (grey dashed line), prolate spheroids with s/t = 2 (dark solid line) and s/t = 10 (dark dashed line), and spheres with s/t = 1 (solid line with dots).

18

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

0.2

Phase shift parameter ρ 0.5 1 2 5 10 20

50 100 γc

A 20

0.2 3.5

Phase shift parameter ρ 0.5 1 2 5 10 20

50 100 γa 2.75

B

3

2.5

5

2.5

2.25

2

2

Aspect ratio st

10

2 1.75

1 1.5

0.5 0.2

1.5 1.25

1

m = 1.05 + i0.01

m = 1.05 + i0.01

1

0.1 0.5 1

2

5

10 20

50 100 200

γc

C

4.5

20

2

5

10 20

50 100 200

γa

D

2 1.8

3.5

5

3

2

2.5

1

2

1.6 1.4

1.5

0.5

1.2

1

0.2 0.1 0.2

0.5 1

4

10 Aspect ratio st

5

m = 1.17 + i0.0001 0.5 1

2

5

10 20

m = 1.17 + i0.0001

0.5

50 100 200

0.2

Particle size D (µm)

0.5 1

2

5

10 20

1

50 100 200

Particle size D (µm)

Figure 7 Bias in attenuation, γc (A, C), and absorption, γa (B, D). Results were derived as in Figure 5. Thick grey lines indicate where γ = 1.

The smallest particles (in the Rayleigh limit) have the highest backscattering ratios, b˜ ≈ 0.5 (Figure 12A,C). For particles in the RGD region, the backscattering ratio of non-spherical particles is largely underestimated by spheres (γ b
> 1; Figure 12B,D). The backscattering ratio is lowest in the transition from the RGD to the VDH regions reaching a constant value for spheres in the midVDH region; b˜ ≈ 0.0005 for organic-like particles and b˜ ≈ 0.0042 for inorganic-like particles. For large inorganic-like particles, a spherical particle overestimates the backscattering ratio of nonspherical particles (Figure 12D), though generalisations do not seem possible. The available results for spheroids, however, are not sufficient to predict how the backscattering ratio of non-spheres will behave in the intermediate region.

Optical properties of polydispersions Obtaining the IOPs of polydispersions of particles When modelling natural waters, it is impractical to account for the contribution of each individual particle because bulk IOPs are the sums of the IOPs of an assembly of particles varying in size, composition and shape. In order to model the optical properties of natural populations, assumptions regarding their size distribution as well as their optical properties need to be made. An advantage 19

50931_C001.fm Page 20 Thursday, May 10, 2007 8:38 PM

WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

3

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50

4

A

2.5

0.5 1

Phase shift parameter ρ 2 5 10 20 50 200

B

3 γc

γc

2 2

1.5 1

1

m = 1.05 + i0.01

1.8

2.6

D

m = 1.05 + i0.01

C 2.2

1.6

1.8

1.4

Aspect ratio st

γa

γa

m = 1.17 + i0.0001

0

0.5

1.2

1.4

10 2 1 0.5 0.1

1 1

m = 1.17 + i0.0001

0.8 4

4 F

3

3

2

2

γb

γb

E

1

1 m = 1.05 + i0.01

0 7 6

2.5 G

m = 1.05 + i0.01

H

2

5

1.5

4

γbb

γbb

m = 1.17 + i0.0001

0

3

1

2

0.5

1 0 0.2 0.5 1

2

5 10 20 50

m = 1.17 + i0.0001

0 0.2 0.5 1

200

Particle size D (µm)

2

5 10 20 50

200

Particle size D (µm)

Figure 8 Biases for attenuation, γc (A, B), absorption, γa (C, D), scattering, γb (E, F), and backscattering, γbb (G, H), for spheroids as a function of size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top). Each line represents a different aspect ratio, s/t (legend is shown in panel D). Results were derived as in Figure 6 for two different types of particles: a phytoplankton-like particle with refractive index m = 1.05 + i0.01 (A, C, E, G) and an inorganic-like particle with m = 1.17 + i0.0001 (B, D, F, H).

20

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

0.2

Phase shift parameter ρ 0.5 1 2 5 10 20 50 100 Qb

A

0.2

2

Phase shift parameter ρ 0.5 1 2 5 10 20 50 100 Qbb

B

20

0.005

10 Aspect ratio s t

0.006

1.5 0.004

5 1

2

0.003

1 0.5

0.002

0.5

0.2

0.001

m = 1.05 + i0.01

m = 1.05 + i0.01

0.1 0.5 1

2

5 10 20

50 100 200

Qb

C 20 10 Aspect ratio s t

0.5 1

3.5

5

2

5 10 20

50 100 200

Qbb

0.09

D

3

0.08

2.5

0.07 0.06

2

0.05

2 1 0.5 0.2 0.1 0.2

0.04

1

0.03 0.02

0.5

m = 1.17 + i0.0001 0.5 1

1.5

m = 1.17 + i0.0001

2 5 10 20 50 100 200 Particle size D (µm)

0.2

0.5 1

0.01

2 5 10 20 50 100 200 Particle size D (µm)

Figure 9 Efficiency factors for scattering, Qb (A, C), and backscattering, Qbb (B, D), for spheroids as a function of size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top), and aspect ratio, s/t. Results were derived as described in Figure 5. Only the T-matrix and ray tracing methods were used for Qbb, however, as no other approximation is currently available for intermediate sizes.

of modelling polydispersions is that the results provide more realistic values of IOPs that better mimic natural populations by eliminating the extreme characteristics of monodispersions that are averaged out and smoothed in the IOPs for polydispersions. Particles are distributed according to a particulate size distribution (PSD) that describes how their number concentration varies with size. Most often the PSD, f (D) [# m–3 µm–1], is given in its differential form in number of particles per unit volume per unit bin length, such that the number concentration, N, between two size classes, D1 and D2, is computed as: N  ∆D = D2 − D1  =

∫ f ( D ) dD [ # m D2

−3

].

(25)

D1

For a population of particles with varied composition, the IOPs are computed from the PSD as: c, a, b, bb =

∫

Dmax

Dmin

( ) ( )

Cc,a,b,bb D f D dD [m −1 ],

21

(26)

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 100 γbb

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 100 γb 20

A

4.5

Aspect ratio st

14

4

10 5

3.5

12

3

10

2

2.5

8

1

2

6

1.5

0.5

m = 1.05 + i0.01

0.5 1

2

5 10 20

50 100 200

γb

C

10 5 2 1 0.5 0.2 0.1 0.2 0.5 1

m = 1.17 + i0.0001

0.5 1 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5

2 5 10 20 50 100 200 Particle size D (µm)

2

m = 1.05 + i0.01

0.5

0.1

20

4

1

0.2

Aspect ratio st

16

B

2

5 10 20

50 100 200

γbb

D

3.5 3 2.5 2 1.5 1 m = 1.17 + i0.0001

0.2 0.5 1

0.5

2 5 10 20 50 100 200 Particle size D (µm)

Figure 10 Bias in scattering, γb (A, C), and backscattering, γbb (B, D). Results were derived as in Figure 9. Thick grey lines indicate where γ = 1.

For the analysis conducted here two common PSDs previously used in other studies of IOPs are employed: 1. The power-law PSD (also referred to as the Junge-like PSD) is given by:  0, if D < Dmin or D > Dmax ;  f D = [ # m −3µm −1 ], −ξ D   n0  D0  , if Dmin ≤ D ≤ Dmax

( )

(27)

where D0 [µm] is a reference diameter and n0 [ # m −3 µm −1 ] is the differential number concentration at the reference diameter. ξ is the slope of the differential PSD (values in aquatic environments are within the range 2.5 < ξ < 5.0; Morel 1973, Jonasz 1983, Stramski & Kiefer 1991). When ξ = 4.0 the PSD is known as the Junge PSD for which an equal volume of particulate material is distributed in logarithmically increasing size bins. The smaller the value of the power-law slope, ξ, the smaller is the relative contribution of small particles to the PSD. In the analysis presented here, ξ is allowed to vary

22

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

1

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 A

3.5

m = 1.05 + i0.01

3

0.8

αc

αc 0.4

0 C

m = 1.05 + i0.01

0.25

αa

αa

0.15 0.1

H

m = 1.17 + i0.0001

0.0020

0

3.5

0.7 E

m = 1.05 + i0.01

3 2.5

0.4

2

αb

0.5 0.3

1.5

0.2

1

0.1

0.5

0

0

0.012

0.12

G

m = 1.05 + i0.01 Aspect ratio st 10 2 1 0.5 0.1

0 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

0.1 0.08

αbb

αb

m = 1.17 + i0.0001

0.0030 0.0025

0.05

αbb

F

0.0035

0.2

0.002

m = 1.17 + i0.0001

0.5 0.0040

0.004

D

2

0

0.006

m = 1.17 + i0.0001

1.5

0.3

0.008

B

1

0.2

0.01

Phase shift parameter ρ 200 2 5 10 20 50

2.5

0.6

0.6

0.5 1

0.06 0.04 0.02 0 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

200

200

Figure 11 Volume-normalised cross sections for attenuation, αc (A, B), absorption, αa (C, D), scattering, αb (E, F), and backscattering, αbb (G, H), for spheroids as a function of size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top). Each line represents a different aspect ratio, s/t (legend is shown in panel G). Results were derived as in Figure 6 for two different types of particles: a phytoplankton-like particle with refractive index m = 1.05 + i0.01 (A, C, E, G) and an inorganic-like particle with m = 1.17 + i0.0001 (B, D, F, H).

23

50931_C001.fm Page 24 Thursday, May 10, 2007 8:38 PM

WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

A Aspect ratio st

˜b

10−1 10−2 10−3

8

m = 1.05 + i0.01

6

m = 1.05 + i0.01

4 2

10−4

100

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50 B

10 2 1 0.5 0.1

γb˜

100

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50

0 0.5 1

2

5 10 20 50

200

5

C

0.5 1

2

5 10 20 50

200

D 4

10−1

m = 1.17 + i0.0001

γb˜

˜b

3 2

10−2

1 m = 1.17 + i0.0001

0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

200

0 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

200

b Figure 12 Backscattering ratios, b
= bb (A, C), and biases in the backscattering ratio, γ b
b (B, D), as a function of particle size, D [µm] (primary x-axis, bottom), with corresponding phase shift parameter, ρ (secondary x-axis, top). Results are derived as in Figure 9 for two different types of particles: a phytoplankton-like particle with m = 1.05 + i0.01 (A, B) and an inorganic-like particle with m = 1.17 + i0.0001 (C, D). Each line represents a different aspect ratio, s/t (legend is shown in panel A).

(representing the variations in the natural environment) to examine how changes in the relative concentration of small to large particles affects biases between spherical and non-spherical populations of particles. 2. A more elaborate PSD based on generalised gamma functions was introduced by Risoviç (1993):  0, if D < Dmin or D > Dmax ;  µL µS f ( D) =   D  [# m −3µm −1 ], D νS νL nS   exp(− τ S D ) + nL   exp(− τ L D ), if Dmin ≤ D ≤ Dmax  D0    D0  (28) where nS and nL are the number concentrations of small and large particles [# m–3 µm–1], respectively, and D0 [µm] is the reference diameter. The other parameters, µS,L , τS,L and υS,L, help to generalise the gamma functions that express the distributions of the small and large particles, respectively, and are site-specific with values provided by Risoviç (1993) (parametric values of a ‘typical’ water body are µS = 2, τS = 52 µm–1, υS = 0.157; and µL = 2, τL = 17 µm–1 and υL = 0.226). In the analysis that follows, the ratio of the number of small to large particles, nS : nL, is likewise varied, as with the power-law 24

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

distribution earlier, to examine how changes in the relative concentration of small to large particles affects the bias between spherical and non-spherical particles. The smaller the value of nS : nL , the smaller is the relative contribution of small particles to the PSD. Two types of comparisons between the IOPs of a polydispersion of spheroids are performed here: 1. A constant aspect ratio is assumed for the whole population and only the slope of the PSD (ξ or nS : nL) is allowed to vary. 2. The slope of the PSD and the aspect ratio are varied as a function of size following the observations of Jonasz (1987b) who, utilising scanning electron microscopy, derived the following shape distribution: 〈G 〉 = 1.28 D 0.22 . G

(29)

The implication of Equation 29 is that the smaller the particles are the more sphere-like they become. Jonasz (1987b) also found that the larger particles resembled elongated cylinders with aspect ratios >1. The geometric cross section of an elongated cylinder, however, is very similar to that of a prolate spheroid and so prolate spheroids are used here to model larger particles. Thus, the deviation from sphericity of a particle can be expressed in terms of its aspect ratio, s/t, and diameter of its equal-volume sphere, D, and Equation 29 becomes:  −2 1  s  3 + 2  t   

()

1

s 3 t

sin −1 1 − 1−

() s t

()

−2

s t

−2

  0.22  = 1.28 D .  

(30)

Given a size D, this equation is solved to obtain s/t, which is used in the population model with aspect ratios varying as a function of size (see also Figures 2 and 3 in Jonasz 1987b).

Results for polydispersions In the following section, the modelled IOPs (c, a and b) of polydispersions of spheroids are presented. Due to the inability to obtain the VSF of spheroids throughout the size range of interest, results regarding either the VSF or the backscattering coefficient, bb, are not presented here. For polydispersions of spheroids, shape effects depend on the relative contributions of small and large particles to the population and the degree to which particles deviate from a spherical shape (as indicated by the aspect ratio). In both the power-law and Risoviç (1993) PSD simulations, with constant and varying aspect ratios, the biases of all the IOPs increase with increasing proportion of large particles in the population (i.e., as ξ → 3 or as nS : nL → 1012, Figures 13 and 14). This is a direct consequence of the nearly monotonic change in the bias as a function of size for a monodispersion (Figure 8). As expected from the results for monodispersions of spheroids, the biases in attenuation and scattering increase as the aspect ratio departs from one, the absorption bias also increases with departure from sphericity and with increasing absorption index. In most cases the biases are >1 (i.e., a spherical model will underestimate a population of spheroids), being 25

50931_C001.fm Page 26 Thursday, May 10, 2007 8:38 PM

WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

2

A

1.8

1.6

1.6

1.4

1.4

γc

γc

1.8

2

m = 1.05 + i0.01

m = 1.17 + i0.0001

D

m = 1.17 + i0.0001

F

1

1

0.8

0.8 m = 1.05 + i0.01

C

1.4

1.6

1.3 γa

γa

B

1.2

1.2

1.8

m = 1.17 + i0.0001

1.4

1.2 1.1

1.2

1 1 2

2

m = 1.05 + i0.01

E

1.8

1.6

1.6

1.4

1.4

γb

γb

1.8

1.2

1.2

1

1

0.8 0.6

0.8 3.5

3.75

4

4.25 4.5

3.5

4

4.25 4.5

ξ

ξ

x

3.75

10

Aspect ratio st 2

1

0.5

0.1

Figure 13 The bias in attenuation, γc (A, B), absorption, γa (C, D), scattering, γb (E, F), and backscattering, γbb (G, H), for a power-law polydispersion of spheroids relative to a power-law polydispersion of spheres with the same volume as a function of the power-law exponent, ξ. Each line represents a different aspect ratio, s/t (legend below the plot). The grey line with dots (legend: ‘x’) denotes the polydispersions of spheroids where the shape co-varies with size following Jonasz (1983; see text). The dotted vertical lines are used to compare equivalent size distributions in Figure 14.

<1 only for attenuation and scattering by populations dominated by small particles (i.e., as ξ → 4.5 or as nS : nL → 1017, Figures 13 and 14) and for absorption when small cells dominate and the aspect ratio is significantly different from one (Figure 13D). Biases of the Risoviç (1993) PSD are similar to those of the power-law PSD (Figures 13 and 14). Changes in the bias as a function of the PSD parameter (Figures 13 and 14) are smooth due to the averaging over particles of many different sizes, as well as to random orientation. The more realistic case of a population varying in both size and shape exhibits, in general, a larger bias than populations with a constant shape (Figures 13 and 14) because for all the particles in this population the bias is one or larger while for those with constant shape the smallest particles very often have biases smaller than one. 26

50931_C001.fm Page 27 Thursday, May 10, 2007 8:38 PM

INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

A

2.2

1.8

1.9

1.6 1.4

B

2.5

2 γc

γc

2.2

m = 1.05 + i0.01

1.6 1.3 m = 1.17 + i0.0001

1.2

1

1

0.7

1.8

1.25 C

D

1.2

1.6 γa

γa

1.15 1.4 1.2

1.1

m = 1.05 + i0.01

1

1 E

2.2

1.9

1.9

1.6

1.6 1.3 m = 1.17 + i0.0001

m = 1.05 + i0.01

1 0.7

F

2.5

2.2 γb

γb

2.5

1.3

m = 1.17 + i0.0001

1.05

1 1013

1014

x

1015 nS : nL

1016

10

0.7

1017

Aspect ratio st 2

1013

1

1014

1015 n S : nL

0.5

1016

1017

0.1

Figure 14 The biases in attenuation, γc (A, B), absorption, γa (C, D), and scattering, γb (E, F), for a Risoviç (1993) polydispersion of spheroids relative to a Risoviç polydispersion of spheres with the same volume as a function of the relative numbers of small to large particles, nS : nL . Each line represents a different aspect ratio, s/t (legend below the plot). The grey line with dots (legend: ‘x’) denotes the polydispersions of spheroids where the shape co-varies with size following Jonasz (1983; see text). The dotted vertical lines indicate the ratios where the size distributions having approximately a power-law slope of ξ = 3.5 and ξ = 4.0, from left to right respectively, as shown on Figure 13.

The results here are consistent with those of Herring (2002) who investigated the attenuation bias of a population of particles with a power-law PSD with varying shape as well as varying refractive index (using the model of the dependence of the index of refraction on size by Zaneveld et al. 1974). Variations in the attenuation bias were slightly larger in the study by Herring (2002) than the results obtained here (Figure 13), varying from 2.2 to 1.1 as the power-law slope varied between 3 ≤ ξ ≤ 5. Varying the imaginary part of the index of refraction between 0.0015 ≤ k ≤ 0.01 results in a difference of up to 10% in the attenuation bias, most pronounced for a steeper PSD (Herring 2002). 27

50931_C001.fm Page 28 Thursday, May 10, 2007 8:38 PM

WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

In general, for the populations of particles modelled here with particle sizes ranging from D = 0.2 to 200 µm, at least 50% of the contribution to c, a and b comes from particles smaller than D = 10 µm (Figure 15). However, the strongest contribution, as much as 65% (indicated by the steepness of the curves in the plots), comes from the contribution made by particles of intermediate sizes belonging to the VDH region. Because in this region the biases are large (Figure 8), models based on spherical particles will underestimate the IOPs (lines with dots in Figure 15).

1

Phase shift parameter ρ 0.2 0.5 1 2 5 10 20 50

1

0.6

0.8 0.6 0.4

n

0.4 0.2

0.2

m = 1.05 + i0.01 1

1 C

D

0.8

Σi=1 ai/ ΣN aN

0.6 0.4

0.8 0.6

Power-law

0.4

Risoviç

n

n N Σi=1 ai/ Σ aN

m = 1.17 + i0.0001

0

0

0.2

0.2

m = 1.05 + i0.01

m = 1.17 + i0.0001 0

0

1

1 E

F

0.8

Σi=1 bi/ ΣN bN

0.6 0.4

0.8 0.6 0.4

n

n N Σi=1 bi/ Σ bN

Phase shift parameter ρ 2 5 10 20 50 200

B

0.8

Σi=1 ci/ ΣN cN

n N Σi=1 ci/ Σ cN

A

0.5 1

0.2

0.2

m = 1.05 + i0.01

0 0.2 0.5 1 2 5 10 20 50 Particle size D (µm)

10

m = 1.17 + i0.0001 0 0.2 0.5 1 2 5 10 20 50 200 Particle size D (µm) Aspect ratio st 2 1 0.5 0.1 200

Figure 15 The normalised cumulative contribution to attenuation (c) (A, B), absorption (a) (C, D), and scattering (b) (E, F), for both the Risoviç (nS : nL = 1016 ) and power-law (ξ = 4) polydispersions. Each line represents a different aspect ratio, s/t (legend below the plot). The uppermost curves in each panel represent populations with a power-law size distribution (compare with Figure 13) and the lowermost curves represent populations with a Risoviç size and shape distribution (compare with Figure 14). In all cases, the greater the deviation from sphericity (as indicated by the aspect ratio, s/t) the greater is the contribution by larger particles to the IOPs of the polydispersion.

28

50931_C001.fm Page 29 Thursday, May 10, 2007 8:38 PM

INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

The reader is cautioned that the shapes chosen here, the specific choices for size distribution (including the size range from Dmin to Dmax), the index of refraction and the internal structure are all idealisations and may differ from natural environmental conditions. The general trends in the results, however, are expected to hold true for the natural environment as has been found in many past studies where idealised optical theory has been used to interpret and invert in situ observations. In addition, model results presented here provide an order of magnitude estimate for the likely bias resulting when spherical particles are used to model natural assemblages of particles. Two conclusions can be drawn from the results here and from Herring (2002): (1) biases in IOPs are expected to be greatest in populations enriched with large particles similar to those in coastal assemblies of phytoplankton and those in benthic environments and (2) these biases are likely to be smaller than a factor of three (the biases are likely to be <30% when a population is enriched with small particles as in the near-surface layer of an oligotrophic ocean).

Observations on the effects of particle shape on IOPs There are relatively few direct observations on the effects of shape on the IOPs of aquatic particles (e.g., Volten et al. 1998). Size determination and hence volume are often ambiguous. For example, when size fractionation is used (i.e., using filters or sieves of increasingly smaller pore sizes) information on only two of the three dimensions (possibly the largest) of the particles can be estimated. Similarly, when microscopy is used in sizing, it is difficult to estimate the third (usually smaller) dimension. Thus, there are uncertainties in both measurements and modelling of IOPs of non-spherical particles. Several studies provide evidence that aquatic particles in general, and nonspherical particles in particular, are not optically equivalent to spheres. Kadyshevich (1977), Voss & Fry (1984) and Volten et al. (1998) measured the VSF and polarised scattering characteristics of oceanic samples and phytoplankton cultures, respectively, and found that the polarisation characteristics of scattering are not consistent with spherical particles. Hodkinson (1963), Proctor & Barker (1974) and Proctor & Harris (1974) have found that the attenuation efficiency factor (Qc ) as a function of size of sorted nonspherical particles did not exhibit the oscillatory behaviour seen for monodispersed spheres and, similar to spheres, attained an asymptotic value for large particles. This behaviour is similar to Qc for a polydispersion of spheres. However, the asymptotic value found in those studies was not always two, probably a consequence of the variety of means by which the ‘size’ of the particles of interest has been determined in the various studies (Aas 1984). An example of recent measurements of the near-forward VSF of natural particles from the Satluj River in India (Figure 16) exhibits two features that are similar to those suggested by the theoretical analysis presented in this review (Figure 4) and in previous theoretical papers (e.g., Kerker 1969). The resonance pattern in the VSF associated with a monodispersion of spheres disappears for even tightly sorted natural particles, in a similar manner as a polydispersion of spheres (Figure 16A,C). Associated with a larger cross-sectional area, non-spherical particles exhibit stronger (diffraction-dominated) forward-peaked VSFs (Figure 16A,C). These results are consistent with the theoretical results showing no resonance pattern in the VSF of monodispersed spheroids as a function of angle (Figure 4) and a scattering bias >1 for large particles compared with wavelength (Figure 8F) due to a higher VSF in the near-forward direction. Similar results have been recorded by MacCallum et al. (2004) for phytoplankton cultures where the best agreement in the near-forward VSF was found for spheres with a volume larger by a factor of 1.5. When Mie-based size inversions are applied to non-spherical and complex particles such as phytoplankton, unexpected results are produced. For example, inversion of VSF measurements conducted on a culture of Ceratium longipes suggests a multi-modal population (Figure 17). The

29

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS

104

104 Glass spheres Sediment

102

102

101

101 75–90 µm 100

Sediment

103 β (θ) (unscaled)

103 β (θ) (unscaled)

Glass spheres

0

25–30 µm

100 µm

1 2 3 4 5 Scattering angle θ (deg) A

100 Satluj River sediment

1 2 3 4 5 Scattering angle θ (deg)

B

C

6

0

6

Figure 16 Measurements of near-forward scattering. A is a comparison of the shape of the near-forward scattering between sorted particles (Satluj River sediment; solid line) and glass spheres (line with dots) 75–90 µm in size. An image of the particles used in the measurement of the sediment in A is presented in B. C is a comparison between sediment (solid line) and glass spheres (line with dots) 25–30 µm in size. Note the narrowing of the scattering pattern and absence of a secondary maximum for the non-spherical natural particles (solid lines) compared to polydispersions of spheres sieved similarly (lines with dots). Scattering measurements were performed with the LISST-100 instrument (data courtesy of Briggs-Whitmire and Agrawal at Sequoia Scientific, Inc.).

peaks in the volume size distribution, however, are found to correspond to the outer boundary of the cell, the core part of the cell and the thickness of the appendages (Figure 17).

Summary and future prospect Together with size, composition and internal structure (not addressed here, however, the reader is referred to Kitchen et al. 1982, Quirantes & Bernard 2004, 2006), shape has important effects on IOPs. For a monodispersion of particles, the biases between spheroids and equal-volume spheres can be larger than a factor of three, while for more realistic polydispersions biases in attenuation, absorption and scattering are smaller than a factor of three. The size of the particles having the maximal IOP per unit volume is larger for spheroids than for spheres for all IOPs; this size increases with non-sphericity. Many studies have attempted to solve the problem of optical properties of non-spherical particles by looking for a spherical equivalent. While for certain optical properties and size ranges a single sphere can provide an adequate model for a non-spherical particle, it has been found that other properties cannot be modelled with spheres; of these, the degree of polarisation and the VSF in the backward direction are inherently different for non-spherical geometries (Bohren & Singham 1991). In this survey, following Paramonov (1994b), a polydispersion of spheres with the same volume and cross-sectional area as a monodispersion of spheroids is used to model the attenuation, absorption and scattering for the size range in which no ‘exact’ solutions are available (the T-matrix approach or the ray tracing method). This approximation works well in that it merges into the T-matrix and ray tracing solutions with very little difference. This method, however, does not provide an accurate estimate for the VSF or the backscattering coefficient of non-spherical particles. For the smallest particles, such as viruses in aquatic environments, shape is not likely to affect the IOPs and hence these particles can be modelled as spheres. Particles with sizes comparable 30

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES

20 µm

Volume concentration[ µl ] l

1.2 1 0.8 0.6 0.4 0.2 0

0

50 100 150 200 Mean particle diameter (µm)

250

Figure 17 Volume concentration (assuming spherical particles) inverted from VSF measurements of the dinoflagellate Ceratium longipes using the Sequoia Scientific LISST-100. The peaks in the size distribution correspond to different length scales associated with the individual cell.

with the wavelength (e.g., bacteria) have attenuation and scattering biases that are <1. This bias becomes greater than one as particle size increases (e.g., for microphytoplankton) until it reaches an asymptote: the ratio of the average cross-sectional area of the spheroid to that of an equalvolume sphere (Equation 24), which is always >1. For absorption, the bias generally increases with size until an asymptotic value is reached, as a randomly oriented spheroidal particle is less ‘packaged’ than a sphere. Backscattering by non-spherical particles is still largely unexplored due to the lack of computational methods covering much of the range of interest (Figures 9B,D, 10B,D, and 12). The backscattering bias is, in general, >1 and can be greater by as much as a factor of seven (95% of the time in Figure 9B) for specific sizes of phytoplankton-like particles. For particles with a very large absorption coefficient (unrealistic for marine particles), an asymptotic value similar to the other IOPs is reached (Herring 2002), suggesting that in general, for particles larger than the wavelength, the backscattering should be more enhanced compared with that of equal-volume spheres. Despite the complexity observed, it seems sensible to conclude that the backscattering of spheroids is likely to be significantly larger than that of equal-volume spheres for the sizes relevant to phytoplankton (Figure 8G,H). In this respect, shape may be a factor contributing to the inability to account for the bulk backscattering coefficient in the ocean, when spheres are used as a model for natural particles (e.g., Stramski et al. 2004). Indeed, Morel et al. (2002) used a mixture of prolate and oblate spheroidal particles (using the T-matrix method) to generate the phase function 31

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of small phytoplankton-like particles that was more realistic in the backward directions compared with that derived from spheres. For polydispersions of particles with constant or varying shape as a function of size, the biases in attenuation, absorption and scattering have been found here to be bounded, reaching high values (270%) only for extreme shapes and size distribution parameters but generally being within about 50% of that of spheres (Figures 13 and 14). While not as large as for monodispersions, these biases are significant and most often >1, implying that populations of spherical particles perform poorly as an average, unbiased model. Diffraction-based instruments provide an opportunity to measure particle size in situ. Given that measurements are made for angular scattering and that inversions from optical measurements to obtain particle size are based on Mie theory, shape may cause significant biases for the sizing of particles. A population of non-spherical particles will appear, on average, larger (and more dispersed) than a population of equal-volume spheres (Figure 11). In addition, such an inversion will ‘create’ populations at the tail ends of the size distribution due to the fact that the non-spherical particles have no resonance pattern in the near-forward scattering as a function of angle (in contrast to spheres, see Figures 4, 16 and 17; see also Heffels et al. 1996). Shape is likely to have some effect on optical inversions that are based on Mie theory. In such inversions, IOPs are used to predict the physical characteristics of the underlying bulk particulate population. For example, the imaginary part of the index of refraction of phytoplankton has been found by inverting absorption data using measured size distributions and Mie theory (Bricaud & Morel 1986). Based on the results of this paper, the inverted k is likely to be an overestimate, with the bias increasing with increasing phytoplankton size and departure from sphericity. Similarly, an inversion of the backscattering ratio was used to obtain the real part of the index of refraction for populations of particles with a power-law size distribution, assuming spherical particles (Twardowski et al. 2001, Boss et al. 2004). Results of this work suggest that a spherical model is likely to underestimate the index of refraction as deviations from sphericity will enhance the backscattering ratio, thus increasing the bias of the inverted index of refraction. Shape effects, on the other hand, were not found to significantly change the spectral slope of the beam attenuation (Boss et al. 2001) and thus are not likely to significantly affect the inversion of this parameter to obtain information on the particulate size distribution. Given the inherent biases associated with using spheres as models for natural particles, it is sensible to predict that inversions that include nonspherical characteristics should provide an improvement compared to those based on Mie theory. This has been the case in several atmospheric studies (e.g., Dubovik et al. 2002, Zhao et al. 2003, Kocifaj & Horvath 2005). Shape has important effects on the polarisation of light scattered by marine particles but is a topic which is beyond the focus of this review. Nevertheless, it is one of the future frontiers in ocean optics, as currently there is no in situ commercial instrumentation able to measure polarised scattering. The aquatic community has largely neglected polarisation when studying particulate suspensions (with a few exceptions, e.g., Quinby-Hunt et al. 2000 and references therein). Studies by Geller et al. (1985) and Hoovenier et al. (2003) suggest that there is promise in obtaining information regarding some aspects of particle shape (e.g., departure from sphericity) by analysing certain elements of the polarised scattering matrix. For example, theoretical shape indices have been derived based on both linear (Kokhanovsky & Jones 2002) and circular (Hu et al. 2003) polarisation measurements. In particular, the latter was found to be less sensitive to multiple scattering. Both were found to be most sensitive at scattering angles in the backward hemisphere. Polarimetry shows promise especially for extreme shapes and larger particles (Macke & Mishchenko 1996). Both organic and inorganic aquatic particles are not randomly distributed among shapes but rather tend to span a limited and non-uniform range of aspect ratios, with spheres being relatively 32

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rare. Given the limited amount of data available regarding shape distributions of natural particles, more measurements of shape parameters are needed; in particular, these are needed as input to improve inversion models that currently assume spherical particles. Laboratory experiments designed to measure the effects of shape on optical properties and their consistency with the predictions presented here and elsewhere are also required so that a more complete picture of the effect of shape on IOPs can be established.

Acknowledgements We are indebted to J.R.V. Zaneveld, G. Dall’Olmo and H. Gordon for helpful discussions and constructive comments on earlier drafts of this manuscript; D. Risoviç for the delight in sharing the pragmatism of representing particle size distributions; Y.C. Agrawal and A. Briggs-Whitmire for the scattering measurements and pictures of river sediment; G.R. Fournier for insight into analytical solutions to ‘the problem’; J.T.O. Kirk for resurrecting the absorption cross section triple integral that was done on a hand calculator and M.I. Mishchenko for a lifetime of T-matrix code. This project is supported by the Ocean Optics and Biology programme of the Office of Naval Research (Contract No. N00014-04-1-0710) to E. Boss and by NASA’s Ocean Biology and Biogeochemistry research programme (Contract No. NAG5-12393) to L. Karp-Boss.

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS Cauchy, A.L. 1832. Mémoire sur la rectification des courbes et la quadrature des surfaces courbes. Paris: Académie des Sciences. Ch´ylek, P., Grams, G.W. & Pinnick, R.G. 1976. Light scattering by irregular randomly oriented particles. Science 193, 480–482. Dubovik, O., Holben, B.N., Lapyonok, T., Sinyuk, A., Mishchenko, M.I., Yang, P. & Slutsker, I. 2002. Nonspherical aerosol retrieval method employing light scattering by spheroids. Geophysical Research Letters 29, 1415–1418. Duysens, L.M.N. 1956. The flattening of the absorption spectrum of suspensions, as compared to that of solutions. Biochimica et Biophysica Acta 19, 1–12. Fournier, G.R. & Evans, B.T.N. 1991. Approximation to extinction efficiency for randomly oriented spheroids. Applied Optics 30, 2042–2048. Geller, P.E., Tsuei, T.G. & Barber, P.W. 1985. Information content of the scattering matrix for spheroidal particles. Applied Optics 24, 2391–2396. Gordon, H.R. 2006. Backscattering of light from disklike particles: is fine-scale structure or gross morphology more important? Applied Optics 45, 7166–7173. Gordon, H.R. & Du, T. 2001. Light scattering by nonspherical particles: application to coccoliths detached from Emiliania huxleyi. Limnology and Oceanography 46, 1438–1454. Heffels, C.M.G., Verheijen, P.J.T., Heitzmann, D. & Scarlett, B. 1996. Correction of the effect of particle shape on the size distribution measured with a laser diffraction instrument. Particle and Particle Systems Characterization 13, 271–279. Herring, S.G. 2002. A systematic survey of the modeled optical properties of nonspherical marine-like particles. MS thesis, Oregon State University, Corvallis, Oregon. Hillebrand, H., Dürselen, C.-D., Kirschtel, D., Pollingher, U. & Zohary, T. 1999. Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology 35, 403–424. Hodkinson, J.R. 1963. Light scattering and extinction by irregular particles larger than the wavelength. In Electromagnetic Scattering, M. Kerker (ed.). New York: Macmillan, 87–100. Hoovenier, J.W., Volten, H., Muñoz, O., van der Zande, W.J. & Waters, L.B.F.M. 2003. Laboratory studies of scattering matrices for randomly oriented particles: potentials, problems, and perspectives. Journal of Quantitative Spectroscopy and Radiative Transfer 79–80, 741–755. Hu, Y.-X., Yang, P., Lin, B., Gibson, G. & Hostetler, C. 2003. Discriminating between spherical and nonspherical scatterers with lidar using circular polarization: a theoretical study. Journal of Quantitative Spectroscopy and Radiative Transfer 79–80, 757–764. Jerlov, N.G. 1968. Optical Oceanography. Amsterdam: Elsevier. Jerlov, N.G. 1976. Marine Optics. Amsterdam: Elsevier Scientific Publishing Company, Elsevier Oceanography Series 14. 2nd edition. Jonasz, M. 1983. Particle-size distributions in the Baltic. Tellus 35B, 346–358. Jonasz, M. 1987a. Nonspherical sediment particles: comparison of size and volume distributions obtained with an optical and resistive particle counter. Marine Geology 78, 137–142. Jonasz, M. 1987b. Nonsphericity of suspended marine particles and its influence on light scattering. Limnology and Oceanography 32, 1059–1065. Jonasz, M. 1991. Size, shape, composition, and structure of microparticles from light scattering. In Principles, Methods, and Application of Particle Size Analysis, J.P.M. Syvitski (ed.). Cambridge: Cambridge University Press, 143–162. Jonasz, M. & Fournier, G.F. 1996. Approximation of the size distribution of marine particles by a sum of lognormal functions. Limnology and Oceanography 41, 744–754. Errata published 1999, Limnology and Oceanography 44, 1358. Jonasz, M. & Fournier, G. 2007. Light Scattering by Particles in Water: Theoretical and Experimental Foundations. Amsterdam: Elsevier Science. Junge, C.E. 1963. Air Chemistry and Radioactivity. New York: Academic Press. Kadyshevich, Ye. A. 1977. Light-scattering matrices of inshore waters of the Baltic Sea. Izvestiya, Atmospheric and Oceanic Physics 13, 77–78. Translated by the American Geophysical Union from Izvestiia Akademii nauk SSSR. Fizika atmosfery i okeana.

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INHERENT OPTICAL PROPERTIES OF NON-SPHERICAL MARINE-LIKE PARTICLES Karp-Boss, L. & Jumars, P.A. 1998. Motion of diatom chains in steady shear flow. Limnology and Oceanography 43, 1767–1773. Kerker, M. 1969. The Scattering of Light and Other Electromagnetic Radiation. San Diego, California: Academic Press. Kirk, J.T.O. 1976. A theoretical analysis of the contribution of algal cells to the attenuation of light within natural waters. III. Cylindrical and spheroidal cells. New Phytologist 77, 341–358. Kirk, J.T.O. 1994. Light and Photosynthesis in Aquatic Environments. Cambridge: Cambridge University Press. 2nd edition. Kitchen, J.C., Zaneveld, J.R.V. & Pak, H. 1982. Effect of particle size distribution and chlorophyll content on bean attenuation spectra. Applied Optics 21, 3913–3918. Kocifaj, M. & Horvath, H. 2005. Retrieval of size distribution for urban aerosols using multispectral optical data. Journal of Physics: Conference Series 6, 97–102. Kokhanovsky, A.A. 2003. Optical properties of irregularly shaped particles. Journal of Physics D: Applied Physics 36, 915–923. Kokhanovsky, A.A. & Jones, A.R. 2002. The cross-polarization of light by large non-spherical particles. Journal of Physics D: Applied Physics 35, 1903–1906. Kokhanovsky, A.A. & Zege, E.P. 1997. Optical properties of aerosol particles: a review of approximate analytical solutions. Journal of Aerosol Science 28, 1–21. Komar, P.D. & Reimers, C.E. 1978. Grain shape effects on settling rates. Journal of Geology 86, 193–209. Latimer, P., Brunsting, A., Pyle, B.E. & Moore, C. 1978. Effects of asphericity on single particle scattering. Applied Optics 17, 3152–3158. MacCallum, I., Cunningham, A. & McKee, D. 2004. The measurement and modelling of light scattering by phytoplankton cells at narrow forward angles. Journal of Optics A: Pure and Applied Optics 6, 698–702. Macke, A. & Mishchenko, M.I. 1996. Applicability of regular particle shapes in light scattering calculations for atmospheric ice crystals. Applied Optics 35, 4291–4296. Macke, A., Mishchenko, M.I., Muinonen, K. & Carlson, B.E. 1995. Scattering of light by large nonspherical particles: ray-tracing approximation versus T-matrix method. Optics Letters 20, 1934–1936. Mie, G. 1908. Beiträge zur Optik trüber Medien, speziell kolloidaler Metallösungen. Annalen der Physik 25, 377–445. Mishchenko, M.I., Hoovenier, J.W. & Travis, L.D. (eds). 2000. Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications. San Diego, California: Academic Press. Mishchenko, M.I., Travis, L.D. & Lacis, A.A. 2002. Scattering, Absorption and Emission of Light by Small Particles. New York: Cambridge University Press. Mobley, C.D. 1994. Light and Water: Radiative Transfer in Natural Waters. San Diego, California: Academic Press. Morel, A. 1973. Diffusion de la lumière par les eaux de mer: résultats expérimentaux et approche theorique. AGARD Lecture Series 61, 3.1.1–3.1.76. Morel, A., Antoine, D. & Gentili, B. 2002. Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function. Applied Optics 41, 6289–6306. Morel, A. & Bricaud, A. 1981. Theoretical results concerning light absorption in a discrete medium, and application to specific absorption of phytoplankton. Deep-Sea Research 28A, 1375–1393. Paramonov, L.E. 1994a. A simple formula for estimation of the absorption cross section of biological suspensions. Optics and Spectroscopy 77, 506–512. Translated from Optika I Spektroskopiya. Paramonov, L.E. 1994b. On optical equivalence of randomly oriented ellipsoidal and polydisperse spherical particles. The extinction, scattering and absorption cross sections. Optics and Spectroscopy 77, 589–592. Translated from Optika i Spektroskopiya. Pozdnyakov, D. & Grassl, H. 2003. Colour of Inland and Coastal Waters: A Methodology for Its Interpretation. Chichester, U.K.: Praxis. Proctor, T.D. & Barker, D. 1974. The turbidity of suspensions of irregularly shaped diamond particles. Journal of Aerosol Science 5, 91–99. Proctor, T.D. & Harris, G.W. 1974. The turbidity of suspensions of irregular quartz particles. Journal of Aerosol Science 5, 81–90.

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WILHELMINA R. CLAVANO, EMMANUEL BOSS & LEE KARP-BOSS Quinby-Hunt, M.S., Hull, P.G. & Hunt, A.J. 2000. Polarized light scattering in the marine environment. In Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications, M.I. Mishchenko et al. (eds). San Diego, California: Academic Press, 525–554. Quirantes, A. & Bernard, S. 2004. Light scattering by marine algae: two-layer spherical and nonspherical models. Journal of Quantitative Spectroscopy and Radiative Transfer 89, 311–321. Quirantes, A. & Bernard, S. 2006. Light-scattering methods for modelling algal particles as a collection of coated and/or nonspherical particles. Journal of Quantitative Spectroscopy and Radiative Transfer 100, 315–324. Risoviç, D. 1993. Two-component model of sea particle size distribution. Deep-Sea Research I 40, 1459–1473. Roesler, C.S. & Boss, E. 2007. In situ measurement of the inherent optical properties (IOPs) and potential for harmful algal bloom detection and coastal ecosystem observations. In Real-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms, M. Babin et al. (eds). Paris: UNESCO Publishing, in press. Sheldon, R.W., Prakash, A. & Sutcliffe, W.H. Jr. 1972. The size distribution of particles in the ocean. Limnology and Oceanography 17, 327–340. Shepelevich, N.V., Prostakova, I.V. & Lopatin, V.N. 2001. Light-scattering by optically soft randomly oriented spheroids. Journal of Quantitative Spectroscopy and Radiative Transfer 70, 375–381. Shifrin, K.S. 1988. Physical Optics of Ocean Water. New York: American Institute of Physics, AIP translation series. Originally published as Vvedenie v optiku morya 1983. Siegel, D.A. 1998. Resource competition in a discrete environment: Why are plankton distributions paradoxical? Limnology and Oceanography 43, 1133–1146. Stramski, D., Boss, E., Bogucki, D. & Voss, K.J. 2004. The role of seawater constituents in light backscattering in the ocean. Progress in Oceanography 61, 27–56. Stramski, D., Bricaud, A. & Morel, A. 2001. Modeling the inherent optical properties of the ocean based on the detailed comparison of the planktonic community. Applied Optics 40, 2929–2945. Stramski, D. & Kiefer, D.A. 1991. Light scattering by microorganisms in the open ocean. Progress in Oceanography 28, 343–383. Syvitski, J.P.M., Asprey, K.W. & Leblanc, K.W.G. 1995. In-situ characteristics of particles settling within a deep-water estuary. Deep-Sea Research Part II: Topical Studies in Oceanography 42, 223–256. Twardowski, M.S., Boss, E., MacDonald, J.B., Pegau, W.S., Barnard, A.H. & Zaneveld, J.R. 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in Case I and Case II waters. Journal of Geophysical Research 106, 14129–14142. Twardowski, M.S., Lewis, M.R., Barnard, A.H. & Zaneveld, J.R. 2005. In-water instrumentation and platforms for ocean color remote sensing applications. In Remote Sensing of Coastal Aquatic Environments: Technologies, Techniques and Applications, R.L. Miller et al. (eds). Dordrecht: Springer, 69–100. van de Hulst, H.C. 1981. Light Scattering by Small Particles. New York: Dover. Volten, H., de Haan, J.F., Hoovenier, J.W., Schreurs, R. & Vassen, W. 1998. Laboratory measurements of angular distributions of light scattered by phytoplankton and silt. Limnology and Oceanography 43, 1180–1197. Voss, K.J. & Fry, E.S. 1984. Measurement of the Mueller matrix for ocean water. Applied Optics 23, 4427–4439. Waterman, P.C. 1971. Symmetry, unitarity, and geometry in electromagnetic scattering. Physical Review D 3, 825–839. Zaneveld, J.R.V., Roach, D.M. & Pak, H. 1974. The determination of the index of refraction distribution of oceanic particles. Journal of Geophysical Research 79, 4091–4095. Zhao, T.X.-P., Laszlo, I., Dubovik, O., Holben, B.N., Sapper, J., Tanré, D. & Pietras, C. 2003. A study of the effect of non-spherical dust particles on the AVHRR aerosol optical thickness retrievals. Geophysical Research Letters 30, 1317–1320.

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APPENDIX: NOTATION Notation used following Mobley (1994) closely. The actual units used are given in the text, however, only the dimensions are provided in this table for mass, M, length, L, and time, T, or angular measure as indicated. Symbol

Definition

Dimension

a b b˜ bb Ca Cb C bb Cc c D D0 E(0) E(R) f (D) G 〈G〉 I k k m N n n0 nS nL Qa Qb Qbb Qc R s s/t t V x α* αa αb αbb αc β(θ) ˜ β(θ) γa γb

Absorption coefficient Scattering coefficient Backscattering ratio Backscattering coefficient Absorption cross section of a particle Scattering cross section of a particle Backscattering cross section of a particle Attenuation cross section of a particle Attenuation coefficient Particle size represented by diameter of an equal-volume sphere Reference diameter of size range Irradiance at the light source Irradiance at distance R from the light source Particulate size distribution Geometrical cross-sectional area of a sphere Average geometrical cross-sectional area of a non-sphere Radiant intensity Imaginary part of the relative index of refraction Wave number of the incident light Complex relative index of refraction Number of particles per unit volume Real part of the relative index of refraction Number concentration of particles at the reference diameter D0 Number concentration of small particles Number concentration of large particles Absorption efficiency factor of a particle Scattering efficiency factor of a particle Backscattering efficiency factor of a particle Attenuation efficiency factor of a particle Arbitrary path length of light Rotational axis of a spheroid Aspect ratio of a spheroid Equatorial axis of a spheroid Particle volume Size parameter Specific absorption coefficient of a particle Volume-normalised absorption cross section Volume-normalised scattering cross section Volume-normalised backscattering cross section Volume-normalised attenuation cross section Volume scattering function (VSF) Volume scattering phase function Absorption bias Scattering bias

L–1 L–1 dimensionless L–1 L2 L2 L2 L2 L–1 L L M L–1 T –3 M L–1 T –3 # L–4 L2 L2 M L–1 T –3 sr –1 dimensionless L–1 dimensionless # L–3 dimensionless # L–4 # L–4 # L–4 dimensionless dimensionless dimensionless dimensionless L L dimensionless L L3 dimensionless L–1 L–1 L–1 L–1 L–1 L–1sr –1 sr –1 dimensionless dimensionless

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Symbol

Definition

Dimension

γbb γc θ λ µS µL ξ ρ τS τL υS υL ϕ Ψ Ω

Backscattering bias Attenuation bias Scattering angle Wavelength of the incident light Small-particle generalised gamma distribution parameter Large-particle generalised gamma distribution parameter Slope of the power-law size distribution Phase shift parameter Small-particle generalised gamma distribution parameter Large-particle generalised gamma distribution parameter Small-particle generalised gamma distribution parameter Large-particle generalised gamma distribution parameter Azimuth angle Angular direction into which light is scattered Solid angle into which light is scattered

dimensionless dimensionless radians (rad) L dimensionless dimensionless dimensionless dimensionless L–1 L–1 dimensionless dimensionless radians (rad) radians (rad) steradians (sr)

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 39-88 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS MICHAEL H. GRAHAM1,2, JULIO A. VÁSQUEZ2,3 & ALEJANDRO H. BUSCHMANN4 1Moss Landing Marine Laboratories, 8272 Moss Landing Road, Moss Landing, California 95039, U.S. E-mail: [email protected] 2Centro de Estudios Avanzados de Zonas Aridas (CEAZA - www.ceaza.cl) 3Departamento Biología Marina, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile 4Centro de Investigación y Desarrollo en Ambientes y Recursos Costeros (i~mar), Universidad de Los Lagos, Casilla 557, Puerto Montt, Chile Abstract The giant kelp Macrocystis is the world’s largest benthic organism and most widely distributed kelp taxon, serving as the foundation for diverse and energy-rich habitats that are of great ecological and economical importance. Although the basic and applied literature on Macrocystis is extensive and multinational, studies of large Macrocystis forests in the northeastern Pacific have received the greatest attention. This review synthesises the existing Macrocystis literature into a more global perspective. During the last 20 yr, the primary literature has shifted from descriptive and experimental studies of local Macrocystis distribution, abundance and population and community structure (e.g., competition and herbivory) to comprehensive investigations of Macrocystis life history, dispersal, recruitment, physiology and broad-scale variability in population and community processes. Ample evidence now suggests that the genus is monospecific. Due to its highly variable physiology and life history, Macrocystis occupies a wide variety of environments (intertidal to 60+ m, boreal to warm temperate) and sporophytes take on a variety of morphological forms. Macrocystis sporophytes are highly responsive to environmental variability, resulting in differential population dynamics and effects of Macrocystis on its local environment. Within the large subtidal giant kelp forests of southern California, Macrocystis sporophytes live long, form extensive surface canopies that shade the substratum and dampen currents, and produce and retain copious amounts of reproductive propagules. The majority of subtidal Macrocystis populations worldwide, however, are small, narrow, fringing forests that are productive and modify environmental resources (e.g., light), yet are more dynamic than their large southern California counterparts with local recruitment probably resulting from remote propagule production. When intertidal, Macrocystis populations exhibit vegetative propagation. Growth of high-latitude Macrocystis sporophytes is seasonal, coincident with temporal variability in insolation, whereas growth at low latitudes tracks more episodic variability in nutrient delivery. Although Macrocystis habitat and energy provision varies with such ecotypic variability in morphology and productivity, the few available studies indicate that Macrocystis-associated communities are universally diverse and productive. Furthermore, temporal and spatial variability in the structure and dynamics of these systems appears to be driven by processes that regulate Macrocystis distribution, abundance and productivity, rather than the consumptive processes that make some other kelp systems vulnerable to overexploitation. This global synthesis suggests that the great plasticity in Macrocystis form and function is a key determinant of the great global ecological success of Macrocystis.

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Introduction Kelp beds and forests represent some of the most conspicuous and well-studied marine habitats. As might be expected, these diverse and productive systems derive most of their habitat structure and available energy (fixed carbon) from the kelps, a relatively diverse order of large brown algae (Laminariales, Phaeophyceae; ~100 species). Kelps and their associated communities are conspicuous features of temperate coasts worldwide (Lüning 1990), including all of the continents except Antarctica (Moe & Silva 1977), and the proximity of such species-rich marine systems to large coastal human populations has subsequently resulted in substantial extractive and non-extractive industries (e.g., Leet et al. 2001). It is therefore not surprising that the basic and applied scientific literature on kelps is extensive. Our present understanding of the ecology of kelp taxa is not uniform, as the giant kelp Macrocystis has received the greatest attention. Macrocystis is the most widely distributed kelp genus in the world, forming dense forests in both the Northern and Southern hemispheres (Figure 1). The floating canopies of Macrocystis adult sporophytes also have great structural complexity and high rates of primary productivity (Mann 1973, Towle & Pearse 1973, Jackson 1977, North 1994). Furthermore, although Macrocystis primary production can fuel secondary productivity through direct grazing, most fixed carbon probably enters the food web through detrital pathways or is exported from the system (e.g., Gerard 1976, Pearse & Hines 1976, Castilla & Moreno 1982, Castilla 1985, Inglis 1989, Harrold et al. 1998, Graham 2004). In some regions, such habitat and energy provision can support from 40 to over 275 common species (Beckley & Branch 1992, Vásquez et al. 2001, Graham 2004). Venerated by Darwin (1839), the ecological importance of Macrocystis has long been recognised. The genus, however, did not receive thorough ecological attention until the 1960s when various Macrocystis research programmes began in California, and later in British Columbia, Chile, México, and elsewhere. Since that time, several books and reviews and hundreds of research papers have appeared in both the primary and secondary literature, primarily emphasising the physical and biotic factors that regulate Macrocystis distribution and abundance, recruitment, reproductive strategies and the structure and organisation of Macrocystis communities (see reviews by North & Hubbs 1968, North 1971, 1994, Dayton 1985a, Foster & Schiel 1985, North et al. 1986, Vásquez & Buschmann 1997). This review synthesises this rich literature into a global perspective of Macrocystis ecology and such a review is timely for three reasons. First, the last review of Macrocystis ecology was done by North (1994) and thoroughly covered the literature until 1990, yet there has been significant progress on many aspects of Macrocystis ecology since that time. Second, during the last 15–20 yr the general focus of Macrocystis research (and that of kelps in general) has shifted from descriptive and experimental studies of local Macrocystis distribution, abundance and population and community structure (e.g., competition and herbivory) to comprehensive investigations of Macrocystis life history, dispersal, recruitment, physiology and broad-scale variability in population and community processes. Finally, previous reviews of Macrocystis ecology have been from an inherently regional perspective (e.g., California or Chile) and there is currently no truly global synthesis. This last aspect is of great concern because it effectively partitions kelp forest researchers into provincial programmes and limits cross-fertilisation of ideas. Such a limitation is compounded by the great worldwide scientific and economic importance of this genus, the acclimatisation of Macrocystis to regional environments, and the recent finding that gene flow occurs among the most geographically distant regions over ecological timescales (Coyer et al. 2001). Therefore, the goal here is not to review the existing Macrocystis literature in its entirety, but rather to (1) focus on progress made during the last 15 yr, (2) discuss the achievements of Macrocystis research programmes worldwide and (3) identify deficiencies in the understanding of Macrocystis ecology that warrant future investigation. 40

Washington Oregon

41 Chile

Peru

Falkland Is.

Argentina

South Georgia Is.

Gough Is.

Crozet Is. Prince Edward Is.

Tristan de Cunha Is.

South Africa

Heard Is.

Kerguelen Is.

Amsterdam/St.Paul Is.

New Zealand Bounty Is.

Chatham Is.

Antipodes Is. Campbell Is.

Tasmania Auckland Is.

South Australia

Figure 1 Global distribution of the giant kelp Macrocystis. Locations are given for distinct Macrocystis mainland and island populations determined directly from citations herein.

Baja California Mexico

California

British Columbia

Alaska

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In particular, it is now recognised that great variability exists in Macrocystis morphology, physiology, population dynamics and community interactions at the global scale and it is considered that such ecotypic variability is key to understanding the role of Macrocystis in kelp systems worldwide.

Organismal biology of Macrocystis Most of the biological processes that ultimately prove to be important in regulating the dynamics and structure of Macrocystis populations and communities (e.g., morphological complexity, photosynthesis, growth, reproductive output, gene flow) operate primarily at the scale of individual organisms. The standard means of studying Macrocystis organismal biology continues to be through laboratory studies. Clearly, laboratory studies allow researchers to address various processes under controlled environmental conditions, but in many cases the reliance on laboratory studies has been due to technical limitations in collecting organismal data in situ. Various technological advances since the 1960s (most occurring in the last two decades), however, have resulted in a surge of studies of Macrocystis evolutionary history, distribution, life history, growth, productivity and reproduction.

Evolutionary history The order Laminariales has traditionally included five families (Chordaceae, Pseudochordaceae, Alariaceae, Laminariaceae, Lessoniaceae) but various ultrastructural and molecular data suggest that subordinal classification (i.e., families, genera, and species) is in need of significant revision (Druehl et al. 1997, Yoon et al. 2001, Lane et al. 2006). For example, the Chordaceae and Pseudochordaceae should not be included in the Laminariales (Saunders & Druehl 1992, 1993, Druehl et al. 1997) and a new family has been proposed (Costariaceae; Lane et al. 2006). The order is presumed to have originated in the northeast Pacific (Estes & Steinberg 1988, Lüning 1990) and molecular studies have estimated the date of origin to be between 15 and 35 million yr ago (Saunders & Druehl 1992). Within the order, the genus Macrocystis was formerly assigned to the family Lessoniaceae (including Lessonia, Lessoniopsis, Dictyoneurum, Dictyoneuropsis, Nereocystis, Postelsia and Pelagophycus; Setchell & Gardner 1925), which was considered paraphyletic to the Laminariaceae (Druehl et al. 1997, Yoon et al. 2001). Recent molecular studies, however, have found that Lessonia, Lessoniopsis, Dictyoneurum and Dictyoneuropsis are actually in phylogenetic clades that do not include Macrocystis, and that Macrocystis, Nereocystis, Postelsia and Pelagophycus group together in a derived clade that is nested well within the Laminariaceae (Lane et al. 2006), with Pelagophycus porra being the most closely related taxon to Macrocystis. Species classification within the genus Macrocystis was originally based on blade morphology yielding over 17 species (see review by North (1971)). Blade morphology was then considered a plastic trait strongly affected by environmental conditions and subsequently all 17 Macrocystis species were synonymised with Macrocystis pyrifera (Hooker 1847). Macrocystis species were later described based on holdfast morphology ultimately leading to the current recognition of three species: M. pyrifera (conical holdfast; Figure 2A), M. integrifolia (rhizomatous holdfast; Figure 2B), and M. angustifolia (mounding rhizomatous holdfast) (Howe 1914, Setchell 1932, Womersley 1954, Neushul 1971). The fourth currently recognised species, M. laevis, was described by Hay (1986), again based on blade morphology (M. laevis has smooth fleshy blades and a M. pyriferatype conical holdfast). Four lines of evidence, however, suggest that this current classification of Macrocystis is also in need of revision: (1) M. pyrifera, M. integrifolia and M. angustifolia are interfertile (Lewis et al. 1986, Lewis & Neushul 1994; interfertility with M. laevis has not been 42

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A

B

C

D

Figure 2 Macrocystis holdfast morphologies and sporophyte spacing. (A) Holdfast of pyrifera-form sporophyte from La Jolla, southern California. (Published with permission of Scott Rumsey.) (B) Holdfast of integrifolia-form sporophyte from Huasco, northern Chile. (Photograph by Michael Graham.) (C) Vertical structure of pyrifera-form population from San Clemente Island (15 m depth), southern California; note average sporophyte spacing is 3–7 m. (Published with permission of Enric Sala.) (D) Vertical structure of angustifoliaform population from Soberanes Point (3 m depth), central California; note average sporophyte spacing is 10–50 cm. (Published with permission of Aurora Alifano.)

tested); (2) intermediate morphologies have been observed in the field (Setchell 1932, Neushul 1959, Womersley 1987, Brostoff 1988); (3) in addition to blade morphology (Hurd et al. 1997), holdfast morphology is phenotypically plastic (Setchell 1932, M.H. Graham, unpublished data); and most importantly, (4) patterns of genetic relatedness among all four species are not in concordance with current morphological classification (Coyer et al. 2001). This evidence strongly supports the recognition of the genus Macrocystis as a single morphologically plastic species, with global populations linked by non-trivial gene flow. For the purpose of this review, therefore, the four currently recognised species are referred to simply as giant kelp, Macrocystis. Biogeographic studies of extant kelp in the north Pacific suggest that the bi-hemispheric (antitropical) global distribution of Macrocystis developed as the genus arose in the Northern Hemisphere and subsequently colonised the Southern Hemisphere (North 1971, Nicholson 1978, Estes & Steinberg 1988, Lüning 1990, Lindberg 1991). Alternatively, North (1971) and Chin et al. (1991) proposed a Southern Hemisphere origin of the genus, the latter via vicariant processes that have been questioned (Lindberg 1991). Recently, Coyer et al. (2001) studied the global phylogeography of Macrocystis using recombinant DNA internal transcribed spacer (ITS1 and ITS2) regions. In addition to suggesting that the morphological species description of M. pyrifera, M. integrifolia, M. angustifolia and M. laevis has no systematic support, Coyer et al. (2001) described a wellresolved phylogeographic pattern in which Southern Hemisphere Macrocystis populations nested within Northern Hemisphere populations, linked by Macrocystis populations on the Baja California Peninsula, Mexico. This pattern, and the greater genetic diversity among Macrocystis populations in the Northern Hemisphere (within-region sequence divergences 1.7% and 1.2% for ITS1 and ITS2, respectively) relative to their Southern Hemisphere counterparts (within-region sequence

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divergences 0.8% and 0.6% for ITS1 and ITS2, respectively), supports a northern origin of the genus with subsequent range expansion to include the Southern Hemisphere (Coyer et al. 2001); Coyer et al. (2001) suggested that gene flow across the equator may have occurred as recently as 10,000 yr ago. Despite such progress, however, many questions remain regarding the evolutionary history of Macrocystis. Most importantly, how can this single, globally distributed species maintain gene flow throughout its range, yet at a regional scale exhibit relatively high geographic uniformity in such seemingly important characters as blade and holdfast morphology (i.e., ecotypes or forms)? The data of Coyer et al. (2001) suggest that simple founder effects may have resulted in the unique morphologies of the laevis form at the Prince Edward Islands (including Marion Island) and angustifolia form in Australia. The smooth-bladed laevis form has been found occasionally at the Falkland Islands (van Tüssenbroek 1989a) and a recent description from Chiloé Island, Chile (Aguilar-Rosas et al. 2003), is probably a misidentification of sporophylls as vegetative blades (Gutierrez et al. 2006). Still, despite the apparently high gene flow and morphological plasticity, the distinct forms with distinct ecologies can dominate different habitats often adjacent to each other (e.g., integrifolia form in shallow water vs. pyrifera form in deep water). The identification of which Macrocystis form is present within a region will aid in the understanding of the region’s ecology (see ‘Population’ section, p. 54). In this context, it is hypothesised that the great plasticity in Macrocystis form and function may, in fact, be an adaptive trait resulting in its great global ecological success. Studies testing this hypothesis will require a better understanding of the nature of Macrocystis morphological plasticity, including biomechanics, structural biochemistry and quantitative genetics studies of genes regulating Macrocystis form.

Distribution Macrocystis distributional patterns have been well described (especially in the Northern Hemisphere) due primarily to the large stature of Macrocystis sporophytes and ability to sense their surface canopies remotely from aircraft or satellites (Jensen et al. 1980, Hernández-Carmona et al. 1989a,b, 1991, Augenstein et al. 1991, Belsher and Mouchot 1992, Deysher 1993, North et al. 1993, Donnellan 2004). Macrocystis typically grows on rocky substrata between the low intertidal and ~25 m depth (Figure 3; Rigg 1913, Crandall 1915, Baardseth 1941, Papenfuss 1942, Scagel 1947, Guiler 1952, 1960, Cribb 1954, Chamberlain 1965, Neushul 1971, Foster & Schiel 1985, Westermeier & Möller 1990, van Tüssenbroek 1993, Schiel et al. 1995, Graham 1997, Spalding et al. 2003, Vega et al. 2005) and is distributed in the northeast Pacific from Alaska to México, along the west and southeast coasts of South America from Perú to Argentina, in isolated regions of South Africa, Australia and New Zealand and around most of the sub-Antarctic islands to 60°S (Figure 1; Crandall 1915, Baardseth 1941, Cribb 1954, Papenfuss 1964, Chamberlain 1965, Neushul 1971, Hay 1986, Stegenga et al. 1997). In unique circumstances, sexually reproducing populations can exist in deep water (50–60 m; Neushul 1971 (Argentina), Perissinotto & McQuaid 1992 (Prince Edward Islands)), in sandy habitats (Neushul 1971) and unattached populations that reproduce vegetatively can exist in the water column (North 1971) or shallow basins (Moore 1943, Gerard & Kirkmann 1984, van Tüssenbroek 1989b). High latitudinal limits appear to be set by increased wave action (Foster & Schiel 1985, Graham 1997) and decreased insolation (Arnold & Manley 1985, Jackson 1987), whereas low latitudinal limits appear to be set by low nutrients associated with warmer (non-upwelling) waters (Ladah et al. 1999, Hernández-Carmona et al. 2000, 2001, Edwards 2004) or competition with warm-tolerant species (e.g., Eisenia arborea on the Baja California Peninsula, Mexico; Edwards & Hernández-Carmona 2005). The upper shallow limits of Macrocystis populations are ultimately regulated by the increased desiccation and high ultraviolet and/or photosynthetically active radiation (PAR) of the intertidal zone (Graham 1996, Huovinen et al. 2000, Swanson & Druehl 2000), 44

45

E

B

F

C

Figure 3 Photographs of various Macrocystis populations. (A) Infrared aerial canopy photo of subtidal pyrifera-form population at La Jolla, southern California. (Published with permission of Larry Deysher/Ocean Imaging.) (B) Shallow subtidal pyrifera-form population at Mar Brava, central Chile. (Photograph by Michael Graham.) (C) Subtidal pyrifera-form population at Nightingale Island near Tristan da Cunha Island, South Atlantic Ocean. (Published with permission of Juanita Brock.) (D) Intertidal integrifolia-form population at Van Damme State Park, northern California. (Photograph by Michael Graham.) (E) Intertidal integrifolia-form population at Strait of Juan de Fuca, Washington. (Photograph by Michael Graham.) (F) Intertidal integrifolia-form population at Huasco, northern Chile. (Photograph by Michael Graham.)

D

A

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although wave activity, grazing and competition with other macroalgae in shallow subtidal areas can also be important (Santelices & Ojeda 1984a, Foster & Schiel 1992, Graham 1997). At local scales, decreased availability of light and rocky substratum, and occasionally sea urchin grazing, appear to set the lower off-shore limits of Macrocystis populations (Pearse & Hines 1979, Lüning 1990, Spalding et al. 2003, Vega et al. 2005). Finally, within these upper and lower limits, the lateral distribution of Macrocystis populations typically corresponds with abrupt changes in bathymetry or substratum composition (e.g., sand channels or harbour mouths; North & Hubbs 1968, Dayton et al. 1992, Kinlan et al. 2005). There is an interesting pattern within the global distribution of Macrocystis whereby different regions may have large Macrocystis populations of one morphological form or another (Neushul 1971, Womersley 1987). For example, the integrifolia and angustifolia forms of Macrocystis are generally found in shallow waters (low intertidal zone to 10 m depth), whereas the pyrifera form is generally found in intermediate-to-deep waters (4–70 m depth) (Table 1). In the Northern Hemisphere, the integrifolia form is most commonly observed at higher latitudes north of San Francisco Bay with scattered populations found as far south as southern California (Abbott & Hollenberg 1976, M.H. Graham, personal observations), whereas the pyrifera form is most common at lower latitudes south of San Francisco Bay with scattered populations found as far north as southeast Alaska (Gabrielson et al. 2000). In South America, the integrifolia and pyrifera forms also appear to occupy shallow and deep habitats, respectively (Howe 1914, Neushul 1971). Latitudinally, however, the Southern Hemisphere Macrocystis distribution is opposite that of the Northern Hemisphere: the integrifolia form is generally found at lower latitudes, restricted to Perú México, and northern Chile (Howe 1914, Neushul 1971), whereas the pyrifera form dominates the higher latitudes of central and southern Chile (and Argentina; Barrales & Lobban 1975), but can also be found far north in Perú (Howe 1914, Neushul 1971). The pyrifera form also appears to be Table 1 Maximum depths of worldwide populations of Macrocystis ecotypes Macrocystis form

Location

angustifolia

South Australia South Africa British Columbia Northern Chile Perú Southern Chile Tasmania New Zealand St. Paul/Amsterdam Is. Crozet Is. Falkland Is. South Georgia Is. Southern California Central California Tristan da Cunha Is. Baja California Perú Southern Argentina Kerguelen Is. Gough Is. Prince Edward Is.

integrifolia

pyrifera

laevis

Depth (m) 6 8 10 8, 14 20 10 15 16 20 25 25 25 30 30 30 40 40 55 40 55 68

* Depths interpreted by Perissinotto & McQuaid (1992).

46

Reference Womersley 1954 Isaac 1937 Druehl 1978 Neushul 1971, Vega et al. 2005 Juhl-Noodt 1958* Dayton et al. 1973 Cribb 1954 Hay 1990 Delépine 1966* Delépine 1966* Powell 1981 Skottsberg 1941 Neushul & Haxo 1963 Spalding et al. 2003 Baardseth 1941 North 1971 Juhl-Noodt 1958* Neushul 1971 Grua 1964* Chamberlain 1965 Perissinotto & McQuaid 1992

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most common where Macrocystis is found elsewhere in the Southern Hemisphere (e.g., Tasmania, New Zealand, various sub-Antarctic islands), except in South Australia and South Africa where the angustifolia form is common (Cribb 1954, Womersley 1954, 1987, Hay 1986, Stegenga et al. 1997). Jackson’s (1987) analyses suggested that high latitude Macrocystis sporophytes would be light limited in subtidal waters, forcing a shift in distribution to shallower water above 53° latitude. This may explain the Northern Hemisphere distributional pattern, but cannot explain why shallow-water Macrocystis is the most common form in northern Chile. Furthermore, exceptions to these patterns clearly exist. For example, pyrifera-form individuals can be found in the intertidal zone (e.g., Guiler 1952, 1960 (Tasmania), Chamberlain 1965 (Gough Island), Westermeier and Möller 1990 (southern Chile), van Tüssenbroek 1993 (Falkland Islands)), sometimes even side by side with integrifoliaform individuals (M.H. Graham, personal observations in California; J.A. Vásquez, personal observations in northern Chile). Intermediate morphologies similar to the angustifolia form of South Australia-South Africa can also be observed at intermediate depths (2–6 m) between adjacent pyrifera-form and integrifolia-form populations in central California (M.H. Graham, personal observations). Still, these global distribution patterns support the general consideration of the integrifolia and angustifolia forms as having more shallow-water affinities than the pyrifera form. Another interesting global distributional pattern is the apparent restriction of large Macrocystis forests (>1 km2) to the southwest coast of North America (Point Conception in southern California to Punta Eugenia in Baja California, Mexico; Hernández-Carmona et al. 1991, North et al. 1993), although Macrocystis forests on most of the sub-Antarctic islands have not been explored. The southwest coast of North America has broad shallow-sloping subtidal rocky platforms to support wide Macrocystis populations (up to 1 km width), whereas the regions north to Alaska and south to Patagonia have steep shores and typically support very narrow Macrocystis populations (<100 m width); in some cases, narrow Macrocystis populations can fringe entire islands in the Pacific Northwest (Scagel 1947), southern Chile (Santelices & Ojeda 1984b) and many sub-Antarctic islands (e.g., Crandall 1915, Cribb 1954, van Tüssenbroek 1993). Thus, several key unanswered questions remain: (1) does the geological restriction of Macrocystis to small forests outside southern California affect the ecology of these systems (see ‘Population’ section, p. 54), (2) why are the shallow-water forms found poleward in the Northern Hemisphere and equatorward in the Southern Hemisphere, (3) does the recruitment of Macrocystis individuals to different depths or regions determine their ultimate morphological form or (4) does variability in Macrocystis morphological form determine the depth or region in which sporophyte recruitment and survival will be successful?

Life history As with all kelps, Macrocystis exhibits a biphasic life cycle in which the generations alternate (Sauvageau 1915), and the general life history is well understood (Figure 4; see review by North (1994)). Macroscopic sporophytes attach to substrata by a holdfast consisting of a mass of branched and tactile haptera. Dichotomously branched stipes arise from the holdfast and are topped by apical meristems that split off laminae (blades) as they grow to the surface; gas-filled pneumatocysts join laminae to the stipes and buoy them. The resulting fronds consisting of stipes, laminae and pneumatocysts can form extensive surface canopies and represent the bulk of photosynthetic biomass (North 1994). Other, shorter stipes give rise to profusely and dichotomously branched specialised laminae near the base of the sporophyte (sporophylls) that bear sporangia aggregated in sori (Neushul 1963); occasionally sori are observed on laminae in the canopy (A.H. Buschmann, personal observations in southern Chile) and sporophylls can bear pneumatocysts (Neushul 1963). Each sporangium contains 32 haploid biflagellate pyriform zoospores produced through meiosis and subsequent mitoses (Fritsch 1945). Haplogenetic sex determination apparently results in a 1:1 male-to-female zoospore sex ratio (Fritsch 1945, Reed 1990, North 1994), although the two 47

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Germlings (drifting)

Female gametophytes

Adults (drifting)

Male gametophytes

Embronic sporophytes

Zoospores

Adults (reproductive)

Juveniles (recruits)

Adults (attached) Adults (sterile)

Local population

Remote populations

Figure 4 Macrocystis life cycle depicting various life-history stages important in regulating local Macrocystis population dynamics. Ovals represent benthic stages and rectangles represent pelagic stages; white stages are microscopic and shaded stages are macroscopic. Circular arrows represent potential for retention within particular stages for unknown durations.

sexes cannot be distinguished easily at the zoospore stage (Druehl et al. 1989). Zoospores (~6–8 µm length) are released into the water column where they disperse via currents until they reach suitable substrata where they settle, germinate and develop into microscopic male or female gametophytes. As gametophytes mature, the females extrude oogonia (eggs) accompanied by the pheromone lamoxirene (Maier et al. 1987, 2001). Upon sensing the pheromone, male gametophytes release biflagellate non-photosynthetic antherozoids (sperm) that track the pheromone to the extruded egg. Subsequent fertilisation gives rise to microscopic diploid sporophytes, which ultimately grow to macroscopic (adult) size and complete the life cycle. Although these steps necessary for Macrocystis to progress through its life cycle are straightforward, specific resources are necessary for gametogenesis, fertilisation, and growth of microscopic stages. As a result, variability in environmental factors can greatly affect Macrocystis recruitment success and completion of its life cycle. The experiments of Lüning & Neushul (1978) clearly identified light quality and quantity as important in regulating female gametogenesis in Macrocystis, and kelps in general. Deysher & Dean (1984, 1986a) quantified gross light (PAR), temperature and nutrient (nitrate) requirements of Macrocystis gametogenesis and fertilisation, with embryonic sporophyte formation limited to PAR above 0.4 µM photons (µEinsteins) m−2 s−1, temperatures from 11 to 19°C and nitrate concentrations of >1 µM. Such critical irradiance, temperature and nutrient thresholds were further supported by field experiments (Deysher & Dean 1986b). Although these studies did not provide data amenable to the development of probability density functions for predicting Macrocystis recruitment success as a function of variable environmental conditions, the research was vital to the development of the concept of temporal ‘recruitment windows’, during 48

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which environmental factors exceeded minimum levels for successful gametogenesis and fertilisation. Deysher & Dean (1986a) also found that the growth of embryonic sporophytes to macroscopic size was inhibited at low PAR and nitrate concentrations, but these PAR levels were higher than the threshold for gametogenesis and fertilisation. This suggests that the growth of embryonic sporophytes to macroscopic size may be a stronger bottleneck in the Macrocystis life history than gametogenesis and fertilisation. The photosynthesis studies of Fain & Murray (1982) similarly identified differences in physiology between Macrocystis gametophytes and embryonic sporophytes. The process leading to Macrocystis recruitment from gametophytes can thus be divided into two functionally different stages: (1) sporophyte production (gametogenesis and fertilisation, with relatively lower light requirements) and (2) growth of sporophytes to macroscopic size (with relatively higher light requirements). It follows that the timing and success of Macrocystis recruitment will depend on both the duration of each stage and whether such durations can be extended to allow for delayed recruitment (Figure 4) similar to the concept of seed banks for terrestrial plants (Hoffmann & Santelices 1991). Laboratory and field studies indicate that the sporophyte production stage is relatively short (1–2 months) and rigid in its duration, suggesting limited potential for delayed Macrocystis recruitment via gametophytes. In California, female Macrocystis gametophytes appear to have an initial competency period of 7–10 days prior to gametogenesis (North 1987) and lose fertility after ~30 days (Deysher & Dean 1984, Kinlan et al. 2003), whereas in Chile, laboratory culture studies under ample light and nutrient conditions suggest that Macrocystis female gametophytes may remain fertile for up to 75 days (Muñoz et al. 2004). However, Macrocystis gametophytes can apparently survive indefinitely under ‘unnatural’ artificial light-quality conditions (i.e., red light only; Lüning & Neushul 1978). In California, unfertilised female gametophytes older than ~30 days have limited potential for fertilisation (Deysher & Dean 1986b) and thus recruitment, which was supported by the laboratory studies of Kinlan et al. (2003). As indicated by Kinlan et al. (2003), however, the necessary studies have not been done to determine whether this lack of fertilisation success is due to senescence of female gametophytes or of their male counterparts. Also, it has been demonstrated that zoospore swimming ability is correlated with germination success (Amsler & Neushul 1990) and a similar mechanism may affect fertilisation of oogonia by antherozoids. The demonstration of a shorter life-span (period of fertility) for Macrocystis male gametophytes relative to females would suggest the potential for cross-fertilisation among different zoospore settlements via perennial females. Another well-known aspect of sporophyte production is the minimum density of settled zoospores necessary for recruitment. Specifically, the reliance of kelps on the presence of lamoxirene as a trigger for antherozoid release (Maier et al. 1987, 2001) and the dilution of this sexual pheromone over short distances from the oogonia inherently require sufficient zoospore settlement densities (and survivorship to maturation) to ensure that males and females are close enough for fertilisation to be successful. Such ‘critical settlement densities’ were demonstrated in a series of laboratory and field experiments by Reed and his colleagues (Reed 1990, Reed et al. 1991). Specifically, Reed et al. (1991) identified 1 settled zoospore mm−2 (vs. 0.1 or 10 settled zoospores mm–2) as the minimum Macrocystis (and Pterygophora) zoospore settlement density above which fertilisation and sporophyte production could be expected. These experiments focused on recruitment from single zoospore settlement cohorts and cross-fertilisation among different zoospore settlements may result in fertilisation even if cohort settlement densities are <1 settled zoospore mm−2. It has recently been demonstrated that Macrocystis sporophytes can be produced from unfertilised gametes through apogamy (Druehl et al. 2005). Although the frequency of parthenogenic sporophyte production in the field has not been tested, parthenogenesis may obviate the need for >1 settled zoospore to yield an adult sporophyte. Reed (1990) also demonstrated that speciesdependent female maturation rates combined with species-independent pheromone activity might 49

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result in chemically mediated competition among microscopic stages of kelp species, although this was only suggested for Macrocystis and Pterygophora in southern California. In addition to producing valuable life-history data, these studies clearly demonstrated the utility of combining laboratory and field experiments of kelp recruitment and resulted in a surge in studies of the ecology of kelp microscopic stages. Nevertheless, several key issues regarding the Macrocystis life history remain to be resolved. Most importantly, Macrocystis microscopic life-history stages have not been observed in the field. Microphotometric techniques have recently been developed for identifying Macrocystis zoospores based on species-specific zoospore absorption spectra (Graham 1999, Graham & Mitchell 1999). Subsequent determination of Macrocystis zoospore concentrations from in situ plankton samples led to direct studies of Macrocystis zoospore planktonic processes (e.g., Graham 2003). However, upon settlement, Macrocystis zoospores germinate into gametophytes of variable cell number and pigment concentration, negating the use of microphotometric techniques for studying postsettlement processes (Graham 2000). Fluorescently labelled monoclonal antibodies have been developed for distinguishing between Macrocystis and Pterygophora gametophytes based on cell surface antigens (Hempel et al. 1989, Eardley et al. 1990). However, the effectiveness of these tags diminishes when applied to field samples, in which kelp cells are universally coated with bacteria (D.C. Reed, personal communication). Additionally, although Kinlan et al. (2003) observed plasticity in growth of laboratory-cultured Macrocystis embryonic sporophytes under realistic environmental conditions (light and nutrients), and thus the potential for arrested development in this stage, their experiments provided no evidence of arrested development of gametophytes. This study demonstrated (1) that delayed recruitment of Macrocystis post-settlement stages is possible and (2) the general lack of understanding of the physiological processes that regulate the growth, maturation and senescence of Macrocystis microscopic stages. For example, it is considered that kelp female gametophytes living under adequate environmental conditions will have only one or very few cells, one oogonium per gametophyte, and become reproductive in the shortest period possible (e.g., Lüning & Neushul 1978, Kain 1979). In the absence of light and nutrients, female gametophytes are typically sterile and multicellular (e.g., Lüning & Neushul 1978, Kain 1979, Hoffmann & Santelices 1982, Hoffmann et al. 1984, Avila et al. 1985, Reed et al. 1991), suggesting a trade-off or antagonistic relationship between gametophyte growth and fertility. In some Chilean populations, however, female Macrocystis gametophytes grown under standard laboratory conditions (1) were multicellular, (2) produced multiple viable oogonia per gametophyte, (3) often resulted in numerous sporophytes per gametophyte and (4) took longer to mature than Californian populations (Muñoz et al. 2004). These results must be validated by additional laboratory and field studies but they did demonstrate the highly plastic physiology of Macrocystis life-history stages. Our lack of understanding of variability in the biology of Macrocystis microscopic stages, especially at the global level, is an important constraint on future progress in Macrocystis population dynamics (see ‘Population’ section, p. 54).

Growth, productivity and reproduction Recruitment processes are the main determinant of when and where Macrocystis sporophytes might occur, yet it is the survival and growth of established sporophytes that constrain sporophyte size, self-thinning, population cycles and the primary productivity and canopy structure that ultimately provide energy and habitat for Macrocystis communities. The maximum age of Macrocystis sporophytes is unknown. Individual fronds generally senesce after 6–8 months (North 1994) although van Tüssenbroek (1989c) observed maximum frond survival of 1 yr and Macrocystis sporophytes can produce new fronds from apical meristems (frond initials) retained above the holdfasts near the sporophylls (Lobban 1978a,b, van Tüssenbroek 1989c, North 50

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1994). As such, the sporophytes may survive as long as they remain attached to the substratum and environmental conditions are adequate for growth. In some regions of central California and Argentina, most Macrocystis sporophytes die within a year due to high wave activity (Barrales & Lobban 1975, Graham et al. 1997), whereas in southern California, sporophytes can live up to 4–7 yr (Rosenthal et al. 1974, Dayton et al. 1984, 1999), a life-span that coincides with the periodicity of the El Niño Southern Oscillation (ENSO); in southern Chile, the life-span of Macrocystis sporophytes often exceeds 2 yr (Santelices & Ojeda 1984b, Westermeier & Möller 1990). Interestingly, the only Macrocystis populations known to recruit and senesce on an annual cycle occur in the protected waters around 42°S in Chilean fjords (Buschmann et al. 2004a). The life-span of vegetatively reproducing Macrocystis sporophytes (e.g., angustifolia and integrifolia forms) has never been determined in the field, although integrifolia-form sporophytes have been shown to survive very high levels of rhizome fragmentation (Druehl & Kemp 1982, Graham 1996) and cultivated sporophytes can live 2–3 yr (Druehl & Wheeler 1986). In any case, the life-span of Macrocystis sporophytes appears to be far less than that of other perennial kelp genera (Reed et al. 1996, Schiel & Foster 2006), for example, Pterygophora and Eisenia, which can live for 10+ yr (Dayton et al. 1984). The relatively high turnover of Macrocystis sporophytes is probably due to their massive size (up to 400 fronds per pyrifera-form sporophyte; North 1994) and the almost strict reliance of sporophyte growth and productivity on the biomass of the surface canopy (Reed 1987, North 1994, Graham 2002). Shallow-water Macrocystis sporophytes typically have lower frond numbers than deeper sporophytes (North 1994). Numerous studies have demonstrated high Macrocystis frond productivity rates with estimates of 2–15 g fixed carbon m−2 day−1 in the Northern Hemisphere (reviewed by North 1994), and values that vary between 7 and 11 g C m−2 day−1 in the southern Indian Ocean (Attwood et al. 1991). Delille et al. (2000) also observed a significant ‘draw-down’ of pCO2 when off-shore water entered a dense Macrocystis bed at the Kerguelen Islands, suggesting that the productivity of Macrocystis fronds was high enough to decrease inorganic carbon concentrations in the water column. Furthermore, Schmitz & Lobban (1976) determined that Macrocystis sporophytes can translocate photosynthates from production sources in the surface canopy to energy sinks (meristems, holdfasts, sporophylls) at rates of 55 to 570 mm h−1; the canopy typically represents the greatest contribution to total sporophyte biomass (Nyman et al. 1993, North 1994). Such high rates of productivity and translocation appear to be necessary to maintain sporophyte growth in the face of high metabolic demands (Jackson 1987) because, unlike other perennial kelp genera (e.g., Pterygophora), Macrocystis sporophytes have very limited nutrient and photosynthate storage capabilities (2 wk; Gerard 1982, Brown et al. 1997). The subsequent reliance on the surface canopy, and the vulnerability of surface canopy fronds to both physical and biological disturbance, results in considerable spatial and temporal variability in Macrocystis productivity potential, size structure and overall health. The linkage between Macrocystis sporophyte growth, productivity and biomass therefore results in a plastic response of sporophyte condition to temporal and spatial variability in resource availability (Kain 1982, Reed et al. 1996). The low storage capabilities are clearly disadvantageous during periods of suboptimal environmental conditions, such as occur seasonally in southern California (Zimmerman & Kremer 1986) and the inland waters of southern Chile (Buschmann et al. 2004a). Again, other perennial kelp genera either possess greater storage capabilities or exhibit seasonally offset periods of growth and photosynthesis in order to weather periods of low resource availability (e.g., light or nutrients; Chapman & Craigie 1977, Gerard & Mann 1979, Dunton & Jodwalis 1988, Dunton 1990). At high latitudes, like British Columbia, southeast Alaska, and the Kerguelen and Falkland Islands, Macrocystis sporophyte growth follows distinctly seasonal patterns in insolation, with frond elongation ranging from 2 to 4.7 cm day−1 during the summer maximum (Lobban 1978b, Asensi et al. 1981, Druehl & Wheeler 1986, Wheeler & Druehl 1986, Jackson 51

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1987, van Tüssenbroek 1989d). At lower latitudes, like California, distinct seasonal growth patterns due to variability in insolation were not apparent (North 1971, Wheeler & North 1981, Jackson 1987, Gonzalez-Fragoso et al. 1991, Hernández-Carmona 1996). Instead, Zimmerman & Kremer (1986) described seasonal frond growth rates that corresponded with variability in ambient nutrient concentrations (nitrate), in which frond growth was maximised during winter-spring (12–14 cm day−1; upwelling periods) and minimised during summer-fall (6–10 cm day−1; non-upwelling periods). In New Zealand, minimum Macrocystis frond growth rates also occurred during summer, but were relatively high throughout the remainder of the year (Brown et al. 1997), whereas in northern Chile frond growth rates of 5–10 cm day−1 were observed with no seasonal variability (Vega et al. 2005). In many regions, light and nutrients can be present well above limiting levels throughout the year (e.g., central California or central Chile) thereby permitting continuously high Macrocystis sporophyte productivity (Jackson 1987). The reliance of Macrocystis sporophyte growth and productivity on the biomass and health of the canopy also helps to explain much of the sensitivity of Macrocystis to ENSOs, relative to that of other kelp genera (Dayton et al. 1999). There is a strong inverse relationship between water column nitrate concentrations and water temperature (Zimmerman & Robertson 1985, Tegner et al. 1996, 1997, Dayton et al. 1999, Hernández-Carmona et al. 2001). Kelp growth becomes nutrient limited below approximately 1 µM nitrate, which typically occurs in southern California when water temperatures rise above 16°C (Jackson 1977, Zimmerman & Robertson 1985, Dayton et al. 1999); the same threshold appears to occur around 18°C in Baja California, Mexico (HernándezCarmona et al. 2001). During ENSOs, depression of the thermocline shuts down nutrient replenishment via coastal upwelling and decreases the propagation of nutrients via internal waves (Jackson 1977, Zimmerman & Robertson 1985, Tegner et al. 1996, 1997). Due to its limited nutrient storage capabilities, Macrocystis canopy biomass begins to deteriorate when tissue nitrogen drops below 1.1% dry weight (Gerard 1982). When frond losses exceed frond initiation, the biomass necessary to sustain meristems is lost and the sporophytes die. Sporophyte mortality was 100% in many Macrocystis forests in southern and Baja California following the 1983 and 1997 ENSOs (Dayton et al. 1984, 1992, 1999, Tegner & Dayton 1987, Dayton & Tegner 1989, Hernández-Carmona et al. 1991, Ladah et al. 1999, Edwards 2004), although sporophytes may find refuge in deep water (Ladah & Zertuche-Gonzalez 2004) or within the benthic boundary layer (Schroeter et al. 1995). Finally, during ENSOs, regulatory control over growth of juvenile Macrocystis sporophytes shifts from light inhibition under Macrocystis surface canopies (Dean & Jacobsen 1984) to nutrient limitation (Dean & Jacobsen 1986). Extensive plasticity in sporophyte growth is by no means restricted to Macrocystis adults. Due to the high temporal variability in sporophyte growth potential and the striking differences in biomass among small and large Macrocystis sporophytes, the transition among different size classes can also be delayed in time similar to the arrested development described above for embryonic sporophytes. Santelices & Ojeda (1984a) and Graham et al. (1997) observed that Macrocystis juveniles could survive for many months under adult canopies, growing rapidly to adult size when adult densities decreased and light became available. Presumably, light levels under the canopy were adequate to meet the metabolic demands of the juveniles, but inadequate to sustain growth (Dean & Jacobsen 1984). It is unknown, however, how long juveniles or subadults can survive such conditions. Another important feature of Macrocystis growth potential is that frond initiation is indeterminate because sporophytes can tolerate sublethal biomass loss (loss of fronds) as long as meristems are present and abiotic conditions are conducive to survival (North 1994). Subsequently, sporophyte age is decoupled from sporophyte size, which can be advantageous for both young and old individuals, but disadvantageous to researchers trying to use size as a proxy of age (Santelices & Ojeda 1984b). Graham (1997) found that large Macrocystis sporophytes living in the surf zone suffered greater mortality due to wave action than those that survived sublethal loss 52

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of canopy biomass, which presumably decreased overall sporophyte drag and the likelihood of detachment by waves. Finally, it has been demonstrated that the response of Macrocystis juvenile growth to variable nutrient concentrations is under genotypic control (Kopczak et al. 1991), resulting in broad latitudinal variability in sporophyte growth and recruitment potential. Again, it is interesting that such genotypic variation can occur in spite of non-trivial gene flow among Macrocystis populations (Coyer et al. 2001). The reliance of sporophyte growth on surface canopy biomass also constrains reproductive output. Unlike most other kelp genera, Macrocystis sporophyll and sorus production can occur continuously given adequate translocation of photosynthates from the surface canopy (Neushul 1963, McPeak 1981, Reed 1987, Dayton et al. 1999, Graham 2002, Buschmann et al. 2006). The number of sporophylls per fertile Macrocystis sporophyte varies from 1 to 100+ (Lobban 1978a, Reed 1987, Reed et al. 1997, Buschmann et al. 2004a, 2006), although sporophyll growth rates have yet to be determined. In Macrocystis, two processes lead to turnover of reproductive material: growth of sporophylls and production of sori on the sporophylls (Neushul 1963). Both processes decrease in magnitude following either natural or experimental loss of canopy biomass (Reed 1987, Graham 2002), although the cessation of sorus production appears to be more sensitive than sporophyll growth to biomass loss and can result in complete sporophyte sterility within 9 days of disturbance to the canopy (Graham 2002). It is unknown whether sublethal biomass loss also affects the quantity or quality of zoospores in sori or the timing of their ultimate release into the water column. Due to the continuous reliance of Macrocystis reproduction on canopy biomass, however, variability in environmental factors can also greatly affect reproductive output. Reed et al. (1996) demonstrated that nitrogen content of Macrocystis zoospores varied as a function of in situ water temperature (and presumably water column nutrient concentrations) and nitrogen content of adults, whereas the nitrogen content of Pterygophora zoospores remained relatively constant. Reed et al. (1996) argued that the ability of Macrocystis sporophytes to respond to favourable environmental conditions allowed them to be reproductively successful despite their relatively short life-span. Again, such plasticity in reproductive timing can be adaptive, especially given the apparently low cost of reproduction in kelps (DeWreede & Klinger 1988, Pfister 1992). For example, Macrocystis sporophytes living in waveexposed locations in southern Chile reproduce year-round and produce high numbers of sporophylls, whereas Macrocystis sporophytes living in nearby wave-protected populations are annuals, have increased zoospore production per sorus area and are fertile for only a few months, presumably to ensure successful zoospore settlement and fertilisation prior to the disappearance of adult plants every autumn (Buschmann et al. 2004a, 2006). Overall, Macrocystis sporophyte growth, productivity and reproduction are very responsive to variability in environmental conditions. This response differs from that of most known kelps and other algae (see review by Santelices 1990) and is probably essential to the success of Macrocystis as a competitive dominant throughout much of its global distribution. What remains to be determined, however, is how this variable physiology is expressed among the different morphological forms of Macrocystis and across the variety of habitats in which Macrocystis populations are present. For example, the integrifolia and pyrifera forms inhabit low intertidal and deeper subtidal environments, respectively, which differ strikingly in factors known to regulate Macrocystis growth, productivity and reproduction (e.g., water motion, water quality and light availability). Consequently, it is expected that these two forms will respond differently to environmental perturbations (e.g., van Tüssenbroek 1989c,e), with potentially significant consequences at the population and community levels. This scenario is further complicated by the vegetative growth capabilities of the integrifolia form, absent in the pyrifera form, because the relative contribution of vegetative growth to sexual reproduction in maintaining integrifolia-form giant kelp populations is unknown. Furthermore, kelp physiological studies presently focus on measurements of physiological processes for 53

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specific structures (e.g., photosynthesis, growth, or nutrient uptake of excised laminae), and few have integrated these processes across entire sporophyte thalli (but see the translocation studies of Schmitz & Lobban (1976)). For example, translocation elements (sieve tubes and trumpet hyphae) run through the rhizomes of integrifolia-form sporophytes, which may spread over greater lengths of substratum than pyrifera-form holdfasts, potentially providing a physiological connectivity among fronds over the scale of metres. This limitation has inhibited the development of realistic carbon and nitrogen budgets for kelps and thus constrained our understanding of the physiology of entire sporophytes. This limitation is critical because it is at the level of individual sporophytes, not individual laminae, that mortality, growth and reproduction have consequences for population biology.

Population biology of Macrocystis Most of the work on Macrocystis population dynamics prior to 1990 focused on processes regulating seasonal-to-annual variability in adult sporophyte mortality (see review by North 1994), including competition (Reed & Foster 1984, Santelices & Ojeda 1984a), herbivory (Harris et al. 1984, Ebeling et al. 1985, Harrold & Reed 1985) and physical disturbance (Rosenthal et al. 1974, Dayton et al. 1984). Stimulated by the research of Reed and his colleagues (Reed 1990, Reed et al. 1988, 1991, 1992, 1996, 1997, 2004), a more population-based approach to Macrocystis biology and ecology has recently emerged in which studies have shifted to focus on reproduction, dispersal and recruitment and the consequences of these processes to the persistence of Macrocystis populations. Subsequently researchers have developed a more integrated view of Macrocystis population dynamics that unites variability in mortality agents with recruitment processes to provide a better understanding of local and global differences in Macrocystis population cycles.

Stage- and size-specific mortality Macrocystis populations do not exhibit unbounded growth (Dayton 1985a, Foster & Schiel 1985, North 1994). Although Macrocystis populations are probably never at equilibrium, Macrocystis populations often reach an apparent maximum in abundance or biomass per unit area (carrying capacity) that is determined by the availability of environmental resources (e.g., space, light and nutrients; Nisbet & Bence 1989, Burgman & Gerard 1990, Graham et al. 1997, Tegner et al. 1997). Furthermore, it has been well established that a variety of density-dependent and density-independent processes result in stage- and size-specific sporophyte mortality (reviewed by Schiel & Foster 2006) and retain Macrocystis at a population level below carrying capacity and initiate population cycling. Due to their large size and high drag, Macrocystis adult sporophytes are extremely vulnerable to removal by high water motion, and wave-induced sporophyte loss is considered the primary factor resulting in Macrocystis mortality (Foster 1982, Dayton et al. 1984, Seymour et al. 1989, Schiel et al. 1995, Graham 1997, Graham et al. 1997, Edwards 2004). The probability of a sporophyte being removed from the substratum by passing or breaking waves increases when the force (drag) experienced by the sporophyte due to water motion (related to both water velocity and the cross-sectional area of the sporophyte exposed to the flow; Seymour et al. 1989, Utter & Denny 1996) exceeds the attachment strength of the sporophyte holdfast (for whole sporophyte mortalities) or the breaking strength of individual fronds (for sublethal frond mortality; Utter & Denny 1996). High seasonal and year-to-year variability in wave intensity and sporophyte biomass therefore results in highly variable sporophyte mortality throughout the year. For example, in California, most sporophyte mortalities occur during the first large fall-winter storms (Zobell 1971, Gerard 1976, Graham et al. 1997), when adult biomass is high following long periods of low wave activity (spring to fall). It appears that sporophytes that survive these storms, but shed fronds and canopy 54

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biomass, decrease their overall drag and increase the probability of surviving subsequent and often more severe storms (Graham et al. 1997). On the Chatham Islands, Macrocystis populations are only found at protected sites (Schiel et al. 1995) and never attain large sporophyte or population sizes. In southern California, uprooted sporophytes are often observed entangled with attached sporophytes, further increasing the attached sporophytes’ drag and probability of detachment (Rosenthal et al. 1974, Dayton et al. 1984) and resulting in a ‘snowball effect’ that can clear large swaths in the local population (Dayton et al. 1984). Such massive entanglements, however, appear to be rare in central California (Graham 1997), possibly due to more rapid transport of detached sporophytes out of and away from the local population. Increased sporophyte biomass, therefore, simultaneously increases both Macrocystis growth and reproductive potential (described in the Organismal biology section) and the probability of wave-induced mortality. This trade-off between fitness and survival is probably viable because of the temporal and spatial unpredictability in wave intensity experienced throughout the alga’s global distribution and its ability to survive and quickly recover from sublethal loss of biomass. Exceptions are the wave-protected annual Macrocystis populations in southern Chile in which there seems to be no trade-off between reproductive output and survival (Buschmann et al. 2006). In this case, synchronous growth, reproduction and senescence occur in the near absence of water motion. Despite the high temporal variability in wave-induced mortality, Macrocystis sporophytes exhibit distinct spatial patterns in survivorship. Wave-induced mortality of all size classes of adult sporophytes increases with both increasing wave exposure (Foster & Schiel 1985, Graham et al. 1997) and decreasing depth (Seymour et al. 1989, van Tüssenbroek 1989c, Dayton et al. 1992, Graham 1997). These patterns are primarily due to spatial variability in water motion because wave activity increases toward shallow water, the tips of rocky headlands and regions of high storm production (e.g., the relatively stable winter Aleutian low-pressure system in the Northern Hemisphere). Graham et al. (1997), however, also observed that Macrocystis holdfast growth decreased significantly along a gradient of increasing wave exposure, possibly due to greater disturbance to the Macrocystis surface canopy, which reduces translocation to haptera and thereby reduces holdfast growth (Barilotti et al. 1985, McCleneghan & Houk 1985). Thus, increased wave forces and decreased strengths of holdfast attachment can act in combination to decrease Macrocystis sporophyte survival; Graham et al. (1997) observed that Macrocystis sporophyte life-spans rarely exceeded 1 yr at their most wave-exposed sites. Although all of these described patterns may possibly exist for any Macrocystis life stage, the likelihood of wave-induced mortalities will be much lower for the smaller life stages due to both decreasing thallus size and decreasing water velocities within the benthic boundary layer. Additionally, other hydrographic factors can result in high sporophyte mortalities in relatively wave-protected regions (e.g., tidal surge, nutrient limitation, temperature and salinity stress; Buschmann et al. 2004a, 2006). Biological processes also clearly play a role in mortality of Macrocystis sporophytes. During sea urchin population outbreaks, sea urchin grazing of Macrocystis holdfasts can result in (1) detachment of adult sporophytes and their removal from the population (Dayton 1985a, Tegner et al. 1995a), (2) modification of sporophyte morphology (Vásquez & Buschmann 1997) and (3) removal of entire recruits and juvenile sporophytes (Dean et al. 1984, 1988, Buschmann et al. 2004b, Vásquez et al. 2006). Unlike some locations (e.g., the Aleutian Islands; Estes & Duggins 1995), widespread destruction of Californian and Chilean Macrocystis populations by sea urchin grazing is rare (Castilla & Moreno 1982, Foster & Schiel 1988, Steneck et al. 2002, Graham 2004). Still, sea urchin outbreaks can result in episodic deforestation of Macrocystis populations up to a scale of a few kilometres (Dayton 1985a). In healthy southern California systems, sea urchins can live in Macrocystis holdfasts and result in holdfast cavitation and thus a decrease in sporophyte attachment strength (Tegner et al. 1995a). Although episodic and small scale, the prevalence of holdfast cavitation by sea urchins increases with increasing sporophyte age, thereby increasing the vulnerability of 55

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large, older sporophytes to wave-induced mortality (Tegner et al. 1995a). Infestations of Macrocystis sporophytes by epizoites and small herbivorous crustaceans (amphipods and isopods) have also been observed worldwide (North & Schaeffer 1964, Dayton 1985b). Most outbreaks of herbivorous crustaceans simply result in sublethal biomass loss (Graham 2002), which will effectively decrease sporophyte drag and thus possibly wave-induced mortality. Crustacean infestations can also occur in the holdfasts and result in increased mortality due to decreased sporophyte attachment strength (North & Schaeffer 1964, Ojeda & Santelices 1984). When carnivorous ‘picker’ fishes are absent from the water column in both California and Chile, outbreaks of epiphytic sessile invertebrates (bryozoans, kelp Pecten spp., spirorbids) often result (Bernstein & Jung 1979, Dayton 1985b), weighing down Macrocystis sporophyte canopies and either (1) increasing the likelihood of detachment due to water motion or (2) bringing surface canopy biomass into contact with grazing activities of benthic herbivores (Dayton 1985b). Although seemingly important, there are very few data concerning the importance of these processes in regulating Macrocystis mortality worldwide. Finally, although not a natural biological disturbance, human harvesting of Macrocystis canopies does not appear to have significant effects on sporophyte survival (Kimura & Foster 1984, Barilotti et al. 1985, Druehl & Breen 1986). Inter- and intraspecific competition for space and light are important in regulating the survival of Macrocystis microscopic stages (gametophytes and embryonic sporophytes) to macroscopic size (juveniles; less than tens of centimetres), and growth of Macrocystis juveniles to adult size (Schiel & Foster 2006). Smaller Macrocystis thalli are vulnerable to overgrowth by seaweeds and other kelps (Santelices & Ojeda 1984a, Vega et al. 2005), and even by conspecifics in monospecific stands (Schroeter et al. 1995, Graham et al. 1997). Intraspecific competition for space is likely to be most severe at the smaller size classes because critical zoospore settlement densities will result in high densities of microscopic embryonic sporophytes following fertilisation and the large size of adult Macrocystis holdfasts (up to 1 m diameter) necessitates that many recruits and juveniles will be smothered as nearby sporophytes grow in size. After Macrocystis sporophyte densities are initially thinned by competition for space, competition for light increases as sporophytes begin to grow to the water surface (Dean & Jacobsen 1984). Sporophytes that reach the surface will have enhanced photosynthetic rates and be able to translocate more photosynthates to basal meristems for new frond initiation (North 1994). As such, sporophytes that gain the competitive edge of a surface canopy may become even larger, increasing their likelihood of outcompeting neighbours. Water column nutrients further constrain the maximum amount of surface canopy biomass, apparently regulating the total number of Macrocystis fronds per square meter (the frond carrying capacity; North 1994, Tegner et al. 1997). The ontogenetic development of a Macrocystis cohort is, therefore, dominated by self-thinning (Schiel & Foster 2006), in which high densities of small individuals ultimately yield much lower densities of very large individuals (North 1994). The applicability of this self-thinning model in Macrocystis populations, however, has not been tested directly. North (1994) estimated the frond carrying capacity of a typical Macrocystis population to be 10 fronds m−2, whereas Tegner et al. (1997) found frond carrying capacity to vary according to oceanographic climate, being higher during cooler, nutrient-rich conditions (La Niña) and lower during warmer, nutrient-poor conditions (El Niño). Schiel et al. (1995) also observed at the Chatham Islands that a site with larger Macrocystis sporophytes had lower population densities than a site dominated by smaller Macrocystis sporophytes. Many researchers have estimated that self-thinning ultimately results in adult sporophyte densities of 1 per 10 m2 (Dayton et al. 1984, 1992, Graham et al. 1997), although the accuracy of this value has never been assessed experimentally. Furthermore, these studies have been restricted to pyrifera form populations in central, southern and Baja California. In other systems (e.g., Chile, New Zealand), pyrifera form individuals do not grow to large sizes or form large populations (Schiel et al. 1995) and conspicuous selfthinning of these populations has not been observed (Buschmann et al. 2004a, 2006). Similarly, 56

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shallow-water integrifolia-form sporophytes exhibit vegetative propagation, resulting in coalescent holdfasts, and the concept of sporophyte self-thinning may be irrelevant to these populations (A. Vega & J.A. Vásquez, unpublished data). As previously described, Macrocystis microscopic stages have high light requirements and are thus highly vulnerable to inter- and intraspecific competition for light (Schiel & Foster 2006). Due to their small size, Macrocystis gametophytes and embryonic sporophytes are also highly vulnerable to sand scour (Dayton et al. 1984) and smothering by sediments (Devinny & Volse 1978) and by macro- (Dean et al. 1989, Leonard 1994) and mesograzers (Sala & Graham 2002). Finally, it should be noted that all of the above mortality agents typically result in small- to mesoscale variability in the stage and size structure of Macrocystis populations. During normal conditions, many factors are typically acting to regulate sporophyte survival in a probabilistic fashion, resulting in high variability in sporophyte abundance and size structure at the scale of tens to hundreds of metres (Edwards 2004). During episodic storms and ENSOs, however, multiple factors (e.g., wave intensity and nutrient limitation) may act simultaneously to produce massive stageand size-dependent mortalities homogeneously over broad spatial scales of 10s to 100s of km (Edwards 2004).

Dispersal, recruitment and population connectivity The field ecology of microscopic life-history stages is perhaps the most dynamic and least understood aspect of Macrocystis population biology (North 1994), and that of seaweeds in general (Santelices 1990, Amsler et al. 1992, Norton 1992). Previous life-history studies for Macrocystis indicate the potential for a wide variety of temporal and spatial variability in the time an individual remains within a life-history stage, or the time necessary to proceed to subsequent stages (Figure 4). This temporal flexibility in the life history begins with dispersal and ultimately results in variability in recruitment and thus demographic interactions within a population (Santelices 1990). Adult Macrocystis sporophytes typically produce zoospores with limited dispersal abilities (e.g., Anderson & North 1966, Dayton et al. 1984, Gaylord et al. 2002, Raimondi et al. 2004), suggesting a tight coupling between zoospore output, dispersal and recruitment (Graham 2003). Recent studies, however, have indicated that the supply of propagules of marine organisms can be decoupled from the adult demographic and genetic patterns, as propagules are dispersed far from their natal site (e.g., Roughgarden et al. 1988, Downes & Keough 1998, Wing et al. 1998, Shanks et al. 2000). This decoupling also seems to apply to Macrocystis (Reed et al. 1988, 2004, 2006, Gaylord et al. 2002), especially when the populations are not large enough for modification of currents by the canopy (Jackson & Winant 1983, Jackson 1998, Graham 2003). Because of their small size, Macrocystis zoospores will clearly be transported as far as available currents advect them (Gaylord et al. 2002). However, if adult sporophytes modify current directions and velocities, effective zoospore dispersal can be decreased, coupling zoospore supply to relative changes in the density and size structure of the adult sporophytes (Graham 2003). Subsequently, Macrocystis forests can vary between ‘open’ and ‘closed’ populations, depending on their size, isolation and geographic location (Graham 2003, Reed et al. 2004, 2006). Furthermore, Macrocystis zoospore dispersal can be enhanced by episodic periods of high zoospore production that coincide with storms (Reed et al. 1988, 1997), large population sizes (and thus high source zoospore concentrations; Reed et al. 2004, 2006) and turbulent resuspension of zoospores within the benthic boundary layer (Gaylord et al. 2002). Together, spatial and temporal variability in water motion, zoospore output and Macrocystis forest size results in high variability in the effective ranges of zoospore dispersal (Reed et al. 2006). Nevertheless, it is likely that the dispersal dynamics described for a few large Macrocystis forests in southern California are unique to this region (e.g., Point La Jolla and Point Loma at 1–8 km2; Dayton et al. 1984, Graham 2003, Reed et al. 2006) because most Macrocystis forests 57

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worldwide are relatively small (<1 km2) and consist of narrow belts that fringe coastlines and nearshore islands. In these cases, the retention of zoospores within the small natal adult populations will be decreased, potentially reducing the probability of self-seeding of the populations and thus increasing the reliance of the population on external propagule sources (Reed et al. 2004, 2006). The potential for long-distance dispersal to effectively connect these small populations that occur over broad regions (e.g., in central California, Chile, Australia, New Zealand) has not been tested but models suggest that regional population connectivity via zoospore dispersal is likely (Reed et al. 2006). Furthermore, alternative mechanisms for colonisation and population persistence should be explored in these systems. For example, long-distance dispersal by means of drifting sporophytes or reproductive fragments has been suggested as an important mechanism for Macrocystis colonisation (Figure 5; Anderson & North 1966, Dayton et al. 1984, Macaya et al. 2005, Hernández-Carmona et al. 2006). Drifting reproductive sporophytes have been shown to be abundant along broad regions of the Chilean and Californian coasts (Macaya et al. 2005, Thiel & Gutow 2005a, Hernández-Carmona et al. 2006), and drifting sporophytes can remain reproductively viable in central California for over 125 days (Hernández-Carmona et al. 2006). Clearly, dispersal distance alone cannot explain variability in local or remote recruitment, including the colonisation of new substrata (Reed et al. 1988, 2004, 2006). Critical zoospore settlement densities necessary for Macrocystis recruitment will inherently limit effective dispersal distance to much less than the distance travelled by individual zoospores (Gaylord et al. 2002, Reed et al. 2006). The key to long-distance colonisation, therefore, is not the arrival of a kelp propagule to new substrata, but rather the arrival of two propagules (of opposite sex) within millimetres of each other and their ultimate survival to sexual maturity. As such, new colonisations are rarely

A

B Figure 5 (A) Drifting Macrocystis sporophyte, southern California. (Published with permission of Phillip Colla/Oceanlight.com.) (B) Epi-fluorescent micrograph of drifting Macrocystis sporangia observed in water sample (15 m depth) from Point Loma kelp forest, southern California (note individual zoospores with plastids). (Photograph by Michael Graham.) Macrocystis identification based on species-specific spectrophotometric signature (Graham 1999).

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observed farther than tens of metres from individual Macrocystis sporophytes (Anderson & North 1966, Dayton et al. 1984, Reed et al. 2004, 2006) or hundreds of metres from Macrocystis populations (Anderson & North 1966, Reed et al. 2004, 2006). Physical and biological processes that promote the arrival of zoospore aggregations to suitable substrata will, however, enhance the frequency of long-distance colonisation. For example, Reed et al. (1997) observed a synchronous decline in Macrocystis sorus area that was correlated with increased storm-induced water motion, potentially indicating a synchronous bout of reproductive output. The locally increased density of zoospores in the water column, and the high along-shore advection that occurs during such storms, may help to extend the colonisation distance (Gaylord et al. 2002). Similarly, annual Macrocystis populations in southern Chile exhibit increased zoospore production per soral area over short reproductive periods, potentially increasing the temporal aggregation of settled zoospores (Buschmann et al. 2006). Other kelps also synchronise reproductive output (McConnico & Foster 2005), increasing the likelihood that critical zoospore settlement densities will be exceeded, if only for a short time. Drifting Macrocystis sporophytes may provide an additional aggregation mechanism because reproductive sporophylls will travel together (Hernández-Carmona et al. 2006) and Dayton et al. (1984) observed a path of recruitment in the trail of a drifting reproductive Macrocystis sporophyte. Additionally, the detachment and dispersal of reproductive sporophylls, or even intact sporangia (Figure 5), during periods of high reproductive output may also increase colonisation distances as long as a high density of zoospores is released and they gain attachment to the substratum. Benthic invertebrates that catch and eat such drifting reproductive fragments may facilitate this process (Dayton 1985a). In order to reach suitable settlement substratum, Macrocystis zoospores must enter the benthic boundary layer where they respond to a chemically, physically and biologically heterogeneous microenvironment (Amsler et al. 1992). At this microscale, zoospores can orient their movement relative to nutrient gradients (Amsler & Neushul 1989) and settle preferentially in regions of high micronutrient concentrations (Amsler & Neushul 1990); all kelp zoospores lack eyespots (Henry & Cole 1982) and therefore are not phototactic (Müller et al. 1987). Energetic resources to support zoospore swimming appear to come from a combination of zoospore photosynthesis and lipid reserves (Reed et al. 1992, 1999). These experiments suggest an adaptation that enhances the probabilities for settlement in suitable microenvironments for growth and reproduction of gametophytes (Amsler et al. 1992). Upon settlement, the survival of Macrocystis gametophytes is low, with <0.1% of the female gametophytes being fertilised (Deysher & Dean 1986a). Microscopic stages, however, should not be considered simply an obstacle in the Macrocystis life history that must be overcome in order for populations to persist. In fact, recent studies have suggested that the microscopic stages may play a key role in population persistence by allowing Macrocystis to survive environmental conditions that are unfavourable to macroscopic sporophytes. Ladah et al. (1999) observed rapid and widespread Macrocystis recruitment following ENSO 1997–1998, which completely destroyed Macrocystis sporophytes over a 500-km region. The lack of nearby reproductive adults and homogeneity in recruitment over this broad region suggested that long-distance zoospore dispersal or individual drifting sporophytes were not the source of recovery (although deep-water refuges were possible; Ladah & Zertuche-Gonzalez 2004). Ladah et al. (1999) concluded that recruitment from persistent microscopic stages must have fuelled the recovery, similar to the assumption by Buschmann (1992) that over-wintering microscopic stages must link consecutive annual Macrocystis populations in southern Chile. Clearly, microscopic stages of many kelp taxa can persist through adverse environmental conditions, although field studies by Deysher & Dean (1986b) and Reed et al. (1997) have suggested that this is not true for Macrocystis. Kinlan et al. (2003) recently demonstrated that the development of Macrocystis embryonic sporophytes could be delayed under limited light and nutrients for at least 1 month. When resources

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were restored, the surviving embryonic sporophytes grew quicker and reached larger sizes than their ‘well-fed’ controls. Durations of arrested development >1 month were not explored, yet the identification of Macrocystis embryonic sporophytes (rather than gametophytes) as a potentially persistent stage may be important because high zoospore settlement densities are no longer necessary for recruitment. In any case, the arrested development of Macrocystis microscopic stages probably results from negligible growth due to inadequate resources (e.g., light or nutrients) rather than a true physiological state of dormancy as in many terrestrial seed plants. Numerous studies have identified low benthic irradiance as a key environmental factor limiting Macrocystis recruitment (e.g., Dean & Jacobsen 1984, Reed & Foster 1984, Santelices & Ojeda 1984a, Deysher & Dean 1986b, Schroeter et al. 1995, Kinlan et al. 2003). In the field, such light limitation along the deep limit of Macrocystis is typically due to poor water quality and high light extinction with depth (e.g., Spalding et al. 2003). Between the shallow and deep limits, overlying canopies of kelp, foliose and coralline algae regulate light available for Macrocystis recruitment (e.g., Dean & Jacobsen 1984, Reed & Foster 1984, Santelices & Ojeda 1984a). Macrocystis sporophytes that recruit to turf algae are typically removed by water motion before becoming firmly attached to the substratum (Leonard 1994, Graham 1997). In fact, one of the few patterns to emerge clearly for Macrocystis populations worldwide is that disturbances to Macrocystis canopies are typically followed by Macrocystis recruitment (Dayton & Tegner 1984, Dayton et al. 1984, 1992, 1999, Reed & Foster 1984, Santelices & Ojeda 1984a, Graham et al. 1997). However, in annual Macrocystis populations present in southern Chile, there is a time lag of 3–5 months between the disappearance of the canopy and subsequent recruitment (Buschmann et al. 2006). This population is also unique in that most Macrocystis sporophytes recruit to and grow upon the shells of large filter-feeding slipper limpets (Crepidula; Buschmann 1992). Finally, Raimondi et al. (2004) have recently demonstrated inbreeding depression (reduced growth) of Macrocystis recruits due to selfseeding in close proximity to adult sporophytes. Thus, although most zoospores may only travel short distances, inbreeding depression may select for cross-seeded recruits and enhance the effectiveness of long-distance zoospore dispersal in driving within-population recruitment. The population consequences of this intriguing result await exploration. The vegetative propagation of integrifolia-form sporophytes following sporophyte recruitment may enhance the persistence of Macrocystis populations, especially in the absence of consistent zoospore supply. Buschmann et al. (2004a) observed low sporophyte fecundity in small and narrow northern Chilean integrifolia-form populations relative to the larger central Chilean and pyriferaform populations, suggesting that sexual reproduction is less effective in these shallow-water populations. Therefore, the role of dispersal in Macrocystis population dynamics must be considered relative to the specific environmental and demographic contexts within which the populations exist, especially with regard to population size and isolation, near-shore hydrodynamics, regeneration capacity and differences in sexual and vegetative reproductive potential among Macrocystis forms. It is important to note that recruitment to integrifolia-form populations is noticeably absent in California (Setchell 1932, Graham 1996) but relatively common in British Columbia (Druehl & Wheeler 1986) and northern Chile (Vega et al. 2005). The ultimate consequence of 20+ yr of research on Macrocystis sporophyte mortality, propagule dispersal and population recruitment has been the integration of available data to support the functioning of regional Macrocystis forests as metapopulations (Reed et al. 2006). Reed et al. (2006) estimated that the frequency of local extinctions and recolonisations for Macrocystis populations in southern California occurred over broad temporal scales (months to 10+ yr). Local extinction rates decreased with increasing population size and decreasing population isolation, with extinction durations rarely exceeding 2 yr. Reed et al. (2006) also identified a broad spectrum of interpopulation distances (hundreds of metres to tens of kilometres). It is suggested here that the broad array of Macrocystis dispersal vectors, effects of local hydrodynamics, coupling of dispersal distances 60

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to forest size and the potential persistence of microscopic life-history stages may again be advantageous to maintaining demographic and genetic connectivity with Macrocystis metapopulations.

Demography and population cycles Temporal variability in Macrocystis sporophyte abundance ranges from highly predictable to chaotic, depending on the spatiotemporal scales of interest. In some locations, sporophyte mortality can been synchronised over broad spatial scales, typically driven by predictable seasonal mortalities, such as in the wave-exposed regions of South America (Barrales & Lobban 1975, Dayton 1985b) and California (Foster 1982, Dayton et al. 1984, Graham et al. 1997). Given the potential for continuous Macrocystis recruitment, recruitment suppression by surface canopies, and the potential for delayed recruitment, the response to these synchronised mortalities can be rapid and massive (Dayton & Tegner 1984, Dayton et al. 1984) or delayed (Graham et al. 1997). Graham et al. (1997) found that recruitment to adult size following winter mortalities was often delayed for many months at wave-exposed sites on the Monterey Peninsula in California, due presumably to a lack of recruits present to exploit the canopy opening. Although the cause of the recruitment delay was not identified, Graham et al. (1997) suggested that production of new adults actually occurs in two stages: first, the recruitment of macroscopic sporophytes (requiring both fertilisation and growth to macroscopic size), and second, sporophyte growth to adult size. Nevertheless, recruitment appears to drive Macrocystis population dynamics (Dayton et al. 1992, Graham et al. 1997, Buschmann et al. 2006). Graham et al. (1997) further suggested that the timing and magnitude of the disturbance determined whether the recruitment stages occur in rapid succession or are separated by a delay. For example, in the Point Loma kelp forest in southern California, Dayton et al. (1984, 1992, 1999) have repeatedly observed massive recruitment to adult size following ENSOs (4- to 7-yr frequency). In this case, pre-ENSO adult populations hover around carrying capacity with ENSOs typically removing entire sporophytes from the majority of the population and allowing recruits to grow quickly to adult size. In central California, however, the primary disturbance is caused by annual storms that produce a mosaic of both lethal and sublethal mortalities (Graham et al. 1997, Edwards 2004), and the populations never truly reach carrying capacity. Individual sporophytes may be lost, but canopies often recover quickly, decreasing the likelihood that recruits can grow directly to adult size. As such, the massive synchronised recruitment that drives long-term cycles in Macrocystis population dynamics in southern California (Dayton et al. 1984, 1992, 1999) may be typical of regions that experience large, yet episodic disturbances (e.g., ENSO in California and Chile; Edwards 2004, Vega et al. 2005), whereas regions that experience more chronic annual disturbances may experience more unpredictable population cycling, such as in California (Graham et al. 1997) and Chile (Buschmann et al. 2004a). Such a generalisation is consistent with the population modelling studies of Nisbet & Bence (1989) and Burgman & Gerard (1990). The effect of ENSO on Macrocystis population cycling also appears to vary among ENSOs. Both ENSO-induced storms and nutrient deprivation are major sources of Macrocystis mortality (Dayton et al. 1984, 1992, 1999, North 1994, Edwards 2004). During the 1982–1983 ENSO in California, large storms preceded the period of anomalously warm temperature and high nutrient stress (Dayton & Tegner 1984, Dayton et al. 1984), decimating Macrocystis populations throughout their range (Tegner & Dayton 1987). During the 1997–1998 ENSO, however, southern and Baja California kelp populations deteriorated in anomalously warm temperature prior to the massive winter storms of 1998 (Edwards 2004). As a result, some sporophytes survived in deeper water (Dayton et al. 1999, Edwards 2004, Ladah & Zertuche-Gonzalez 2004), potentially due to the decreased drag of sublethal loss of canopy biomass. Again, in both cases, the combination of open space cleared by storms, reduced canopy shading and subsequent La Niña conditions led to intense 61

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recruitment in the spring (Dayton et al. 1984, 1992, 1999). Increased abundance of understory kelps (e.g., Pterygophora californica, Laminaria farlowii and Eisenia arborea), usually inferior competitors to Macrocystis, became well established during ENSO, persisted for many years post-ENSO (Dayton & Tegner 1984, Dayton et al. 1984, 1999) and was shown to suppress Macrocystis recruitment in local areas (e.g., Edwards & Hernández-Carmona 2005). In the southeast Pacific, Soto (1985) also reported a massive mortality of Macrocystis from 18 to 30°S during ENSO 1982–1983, resulting in a collapse of the kelp harvest from 1983 to 1986 in northern Chile (National Fishery Service, SERNAPESCA 1980–1990). No such mortalities were witnessed, however, in northern Chile Macrocystis populations during ENSO 1997–1998 (Vega et al. 2005) where Macrocystis abundances were reduced but soon replaced by high recruitment. The absence of an ENSO-induced Macrocystis collapse in northern Chile suggested (1) differential effects of various ENSOs at different localities along the coastline; (2) presence of ‘source’ localities (Camus 1994), which, due to certain attributes of the habitat, were able to maintain Macrocystis populations that provided reproductive propagules to disturbed populations (‘sink’ localities); (3) the existence of persistent microscopic life-history stages (Santelices et al. 1995) and (4) differential effects of ENSO on intertidal versus subtidal Macrocystis populations. Unpredictably, Macrocystis populations in northern Chile began to decrease following ENSO 1997–1998, apparently as a result of La Niña 1999 (Vega et al. 2005). The direct cause remains unknown but is linked to Macrocystis recruitment failure.

Ecology of Macrocystis communities One of the most interesting aspects of any Macrocystis-dominated system is the linkage between the dynamics and productivity of Macrocystis populations and the diversity and structure of their associated floral and faunal communities. Indeed, the functional importance of Macrocystis within giant kelp communities was apparent to even the earliest kelp forest ecologists (see, e.g., Darwin 1839). Here, recent advances in Macrocystis community ecology are explored through a discussion of the structural role of Macrocystis within the system, resulting predator-prey interactions and food web dynamics, and the effects of exploitation and global climate changes on the biodiversity and stability of these coastal systems on global scales. The focus is on a mechanistic understanding of Macrocystis systems; a more comprehensive treatment of Macrocystis community ecology can be found in Foster & Schiel (1985).

Macrocystis as a foundation species Macrocystis is the tallest benthic organism (Steneck et al. 2002). Due to their complex morphology, Macrocystis sporophytes can alter abiotic and biotic conditions by dampening water motion (Jackson & Winant 1983, Jackson 1998), altering sedimentation (North 1971), shading the sea floor (Reed & Foster 1984, Edwards 1998, Dayton et al. 1999, Clark et al. 2004), scrubbing nutrients from the water column (Jackson 1977, 1998), stabilising substrata (Neushul 1971, North 1971), providing physical habitat for organisms both above and below the benthic boundary layer (reviewed by Foster & Schiel 1985) and providing fixed carbon (from drift kelp to particulate and dissolved organic carbon) within Macrocystis forests (Gerard 1976) and to surrounding habitats (reviewed by Graham et al. 2003). The irony for Macrocystis community ecologists is that this complex role of Macrocystis as the foundation of its associated community is both the impetus for mechanistic community ecology studies and yet is the primary impediment to such studies. There are three primary components to direct provision of habitat by Macrocystis sporophytes: the holdfast, the mid-water fronds, and the surface canopy (Foster & Schiel 1985). Macrocystis holdfasts are complex structures comprising numerous dichotomously branched and intertwined 62

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haptera and are colonised by a highly diverse assemblage of algae, invertebrates and fishes (Figure 2A,B; Fosberg 1929, Andrews 1945, Cribb 1954, Ghelardi 1971, Jones 1971, Beckley & Branch 1992, Vásquez 1993, Thiel & Vásquez 2000). Haptera typically initiate from the primary stipe dichotomy, with new haptera forming above older ones. The haptera generally grow until they reach the substratum, thereby forming holdfasts that are initially 2-dimensional structures, and depending on age, may ultimately become large 3-dimensional mounds. As the holdfasts grow, new biomass accumulates along the outer surface, whereas the older biomass in the centre of the holdfast becomes necrotic and cavitates (Cribb 1954, Ghelardi 1971, Tegner et al. 1995a). As such, large holdfasts can provide different quantities and qualities of available habitat than smaller ones; large holdfasts are generally restricted to angustifolia-, laevis- and pyrifera-form sporophytes (Figure 2A), whereas the flat strap-like rhizomes of integrifolia-form sporophytes offer little habitat to kelp forest organisms (Figure 2B; Scagel 1947). Most work on Macrocystis holdfast communities has focused simply on species enumeration (Ghelardi 1971, Jones 1971, Beckley & Branch 1992, Vásquez et al. 2001) and patterns of faunal abundance and diversity as a function of holdfast size (Andrews 1945, Thiel & Vásquez 2000) or time since dislodgement of holdfasts from the substratum (Vásquez 1993). Large holdfasts are often encrusted with bryozoans and sponges and serve as refuges for crustaceans (e.g., amphipods), molluscs, brittlestars and sea urchins, especially in the large cavitated centres of older holdfasts; small holdfasts typically house the more mobile invertebrates (e.g., amphipods). Occasional herbivore outbreaks within Macrocystis holdfasts may contribute to sporophyte mortalities, especially for large sporophytes (Jones 1971, Tegner et al. 1995a). Due to the dynamic nature of Macrocystis populations, high variability in sporophyte size and intersporophyte distances may be of primary importance in driving the abundance and diversity of holdfast communities within a population, as predicted by ‘island biogeography’ theory (Thiel & Vásquez 2000). Nevertheless, it has not been determined whether Macrocystis holdfast communities are of functional importance within the larger kelp forest system. The mid-water fronds and surface canopies are also host to a variety of fishes, sessile and mobile invertebrates, and even birds and pinnipeds (reviewed by Graham 2004, Graham et al. 2007). Encrusting bryozoans, hydroids and occasionally bivalves (Pecten) may cover large portions of mid-water fronds (Scagel 1947, Wing & Clendenning 1971, Bernstein & Jung 1979, Dixon et al. 1981, Dayton 1985a,b, Hurd et al. 1994), which are inherently older than their surface-water counterparts. The bulk of the faunal biomass in the mid-water, however, is locked up in crustaceans, grazing molluscs (e.g., top and turban snails; Watanabe 1984a,b, Coyer 1985, 1987, Stebbins 1986) and juvenile and adult fishes, which use the habitat as refuge, for foraging or as a focus of aggregations (Bray & Ebeling 1975, Moreno & Jara 1984, Ebeling & Laur 1985, Hallacher & Roberts 1985, DeMartini & Roberts 1990, Holbrook et al. 1990, Stephens et al. 2006). The Macrocystis-fish association may be weaker, however, in areas with high relief (Stephens et al. 1984). Again, the importance of these faunal components to the system as a whole has not been addressed. The functional importance of Macrocystis canopies to the dynamics of the kelp forest community, however, is well established. Macrocystis canopies are important recruitment sites for many species of near-shore fishes (Carr 1989, 1991, 1994, Anderson 1994, Stephens et al. 2006), and the direct link between canopy biomass, frond density or sporophyte density and fish abundance has been demonstrated (Carr 1989, 1991, 1994, DeMartini & Roberts 1990, Holbrook et al. 1990, Anderson 1994, 2001). These fish assemblages are important in controlling canopy herbivore outbreaks (Bray & Ebeling 1975, Bernstein & Jung 1979, Dayton 1985a,b, Tegner & Dayton 1987, Graham 2002), except in South America where canopy ‘picker-fish’ assemblages are apparently absent (Dayton 1985b, Vásquez et al. 2006). Nevertheless, the Macrocystis-fish relationship is complex. Some kelp forest fish taxa show a negative relationship with Macrocystis abundance 63

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(e.g., Embiotoca lateralis), apparently due to the negative effect of Macrocystis on subsurface algal assemblages that are important fish foraging habitats (Ebeling & Laur 1985, Holbrook et al. 1990). It remains to be seen, however, whether such conspicuous habitat associations are specific to the relatively benign regions in which they have been tested (e.g., southern California) or may also be general to regions with higher spatial and temporal variability in Macrocystis population dynamics. Furthermore, there appear to be no studies of fish-Macrocystis associations that have focused on the shallow-water angustifolia or integrifolia forms. Macrocystis sporophytes continue to provide habitat resources after detachment from the substratum. Holdfast, mid-water fronds and canopies can retain epifaunal fishes and mobile and sessile invertebrates even when drifting sporophytes travel long distances (Edgar 1987, Vásquez 1993, Helmuth et al. 1994, Hobday 2000a,b,c, Smith 2002, Macaya et al. 2005, Thiel & Gutow 2005a,b). In some cases, new species are added from the plankton to the communities on the Macrocystis drifters (Hobday 2000c, Thiel & Gutow 2005b). Eventually the drifters (1) are deposited onto coastal beaches where they can be buried or the pneumatocysts may break causing sporophytes that are resuspended by high tides to be transported to deep water habitats (Zobell 1971), (2) lose their buoyancy at sea and sink directly to deep-water habitats (Harrold & Lisin 1989), (3) aggregate at convergence zones where they may grow vegetatively for undetermined durations (North 1971, van Tüssenbroek 1989b, Thiel & Gutow 2005a) or (4) reconnect with coastal Macrocystis populations (Hobday 2000a, Thiel & Gutow 2005b). Additional habitat and trophic associations become apparent at the scale of Macrocystis populations rather than individuals, probably due to the variety of ways that kelp forests affect the near-shore environment. Kelp forests tend to be darker, less hydrodynamic habitats than adjacent rocky reefs (Dayton 1985a, Foster & Schiel 1985) and it has been hypothesised that large kelp forests may be sites where fixed carbon accumulates in the form of detritus (from drift kelp to small particulates) (Gerard 1976, Harrold & Reed 1985, Graham et al. 2007). It is therefore not surprising that up to 35% of 275 common kelp forest taxa (flora and fauna) in the southern California Channel Islands were found to be associated with the presence of Macrocystis (Graham 2004), 25% of which were obligate associates; >90% of the taxa were more common in forested areas than deforested areas. Many of these associates had either clear trophic linkages with Macrocystis (e.g., abalones) or the associations were driven by habitat provision (e.g., kelp surfperch Brachyistius frenatus). Similar forestwide associations are found for Macrocystis populations in northern Chile, although species richness is much less than in California (Figure 6). Interestingly, the Chilean data show first that the presence of other kelp taxa (e.g., Lessonia) can also drive changes in kelp forest assemblage structure, and second that different species of kelp (e.g., Macrocystis vs. Lessonia) may differ in the quality and quantity of habitat that they provision. Furthermore, Vega et al. (2005) recently demonstrated that the morphology of the understory subtidal kelp Lessonia trabeculata varies in the presence/absence of Macrocystis, potentially resulting in additional effects of Macrocystis distribution on community structure. Still, these studies have relied on natural kelp deforestations, for example due to sea urchin overgrazing, which can produce various factors that confound variability in kelp presence. As such, the direct isolation of the importance of Macrocystis energy and habitat provision relative to that of other kelps or non-kelp macroalgae species remains elusive (Graham et al. 2007). Finally, due to the different growth rates and distribution of canopy biomass among the different forms of Macrocystis (e.g., pyrifera vs. integrifolia forms), shallow- and deepwater Macrocystis populations may also provide trophic and habitat resources in different ways. For example, interfrond distances among shallow integrifolia- and angustifolia-form sporophytes (Figure 2D) are much more homogeneous than their deeper pyrifera-form counterparts (Figure 2C), where high stipe densities are aggregated around individual sporophytes that are widely spaced. Such ecotypic variability in the spatial distribution of suitable habitat (i.e., canopy fronds) may 64

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affect the nature and strength of species associations in shallow versus deep water, especially among fish taxa that preferentially use the canopy, mid-water fronds or water column spaces.

Trophic interactions and food webs During his initial observations of Macrocystis forests in southern Chile, Darwin (1839) was struck by the high diversity of species that appeared to be trophically linked to energy provision by Macrocystis. He professed “The number of living creatures of all orders, whose existence intimately depends on the kelp, is wonderful”. Indeed, all described Macrocystis forests harbour tens to hundreds of species, most of which feed either on Macrocystis-derived fixed carbon (from direct grazing to filter-feeding on Macrocystis detritus) or within some predatory trophic subweb founded upon Macrocystis-based herbivores (Graham et al. 2007). Although food web studies are rare (reviewed by Graham et al. in press), most species lists from within Macrocystis forests contain taxa from multiple trophic levels, often with numerous taxa within each level, and typically a wide variety of generalist and specialist species. It therefore seems unnecessary to review here the nature of trophic interactions within Macrocystis forests. Instead, the focus is specifically on recent studies of the fate of Macrocystis-based primary productivity and the importance of trophic interactions in the dynamics and stability of Macrocystis forests because these are topics of global interest. Gerard (1976) and Pearse & Hines (1976) estimated that although central Californian Macrocystis sporophytes had very high standing stock, most Macrocystis-based productivity entered the food web through detrital pathways. Storm waves rip entire sporophytes from the substratum, break fronds and erode senescent blades, sending detrital material of a wide size range to either the kelp forest floor or out of the forest to other systems. Large detrital pieces (i.e., drift) collect near the bottom where they are heavily grazed by asteroids, crustaceans (crabs, amphipods, isopods), snails and fishes (Leighton 1966, Feder et al. 1974, Gerard 1976, Pearse & Hines 1976, Beckley & Branch 1992, Kenner 1992, Hobson & Chess 2001; see also reviews by Castilla 1985, Foster & Schiel 1985, Graham et al. 2007). When present, large pieces of Macrocystis drift make up the primary diet of sea urchins (Leighton 1966, Castilla & Moreno 1982, Dayton et al. 1984, Vásquez et al. 1984, Castilla 1985, Ebeling et al. 1985, Harrold & Reed 1985). In Chile, Tetrapygus niger and Loxechinus albus can catch drift in Macrocystis forests (Castilla 1985, Rodriguez 2003) but to a lesser extent than Strongylocentrotus franciscanus or S. purpuratus in the northeast Pacific (Harrold & Reed 1985, Harrold & Pearse 1987). When deprived of drift, S. franciscanus or S. purpuratus abandon their normal ‘sit and catch drift’ strategy in search of attached algae (Mattison et al. 1977, Ebeling et al. 1985, Harrold & Reed 1985, Harrold & Pearse 1987), a behavioural switch not observed for other sea urchin taxa (Vásquez & Buschmann 1997, Steneck et al. 2002). Macrocystis drift is also the main component of the diet of abalone in California (Leighton 1966, Tutschulte & Connell 1988) and sea urchins and abalone are thought to compete strongly when Macrocystis drift is in short supply (Tegner & Levin 1982). In the absence of drift, abalones often decrease in abundance or disappear from the local system entirely (e.g., Graham 2004). Smaller detrital pieces (i.e., particulate organ carbon, POC) make Macrocystis-based productivity accessible to many more taxa (e.g., polychaetes, bivalves, sponges, crustaceans, ophiuroids, mysids or basically any kelp forest detrital or filter feeder; Clarke 1971, Foster & Schiel 1985, Beckley & Branch 1992, Kim 1992, Graham 2004, Graham et al. 2007). Therefore, it is not surprising that sessile filter feeders and mobile herbivores can be extremely diverse in Macrocystis forests (100+ taxa), with many taxa disappearing during local Macrocystis deforestation (Graham 2004). The direct grazing pathway is also utilised by a high diversity of kelp forest herbivores (Rosenthal et al. 1974, Gerard 1976, Pearse & Hines 1976, Moreno & Sutherland 1982, Castilla 1985, Foster & Schiel 1985, Graham 2004, Graham et al. 2007). Snails, crustaceans, asteroids and fishes can graze the benthic and water column biomass of Macrocystis sporophytes. These herbivores 65

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Porifera Phragmatopoma Spionidae Balanus laevis Austromegabalanus sp. Bugula sp. Pyura chilensis Vermetidae

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Figure 6 (continued) (C) density of mobile invertebrates (no. m−2); (D) abundance (no. 20 min−1 of visual survey) of fishes. Data are means ± SD; sample sizes range from 34 to 136. Data are from Nuñez & Vásquez (1987), Vásquez et al. (1998), Salinas (2000) and W. Stotz, J. Aburto & L. Cailleaux, unpublished data.

Aplodactylus punctatus Scarthichthys viridis Doydixodon laevifrons Cheilodactylus variegatus Helcogrammoides cunninghami Pinguipes chilensis Hypsoblennius sordidus Graus nigra Chromis chrusma Paralabrax humeralis Trachurus murphyi Isacia conceptionis Prolatilus jugularis Auchenionchus microcirrhis Hemilutjanus macropthalmos Mugil cephalus Anisotremus scapularis Calliclinus genicuttatus Austromenidia laticlavia

Tetrapygus niger Tegula atra Tegula tridentata Allopetrolisthes sp. Nassarius gayi Crassilabrum crassilabrum Calyptraea trochiformis Mitrella unisfasciata Xantochorus cassidiformis Prisogaster niger Scurria sp. Pagurus sp. Ophiaycthis kroyerii Taliepus sp. Tricolia mcleani

Density (no. m−2)

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generally have low per capita consumption rates (e.g., Jones 1971, Sala & Graham 2002) and probably have little impact on Macrocystis standing stock, except during population explosions (Jones 1971, Tegner & Dayton 1987, Graham 2002) or when Macrocystis sporophytes are small in size (e.g., during recruitment or recovery following disturbance; Moreno & Sutherland 1982, Harris et al. 1984, Castilla 1985, Sala & Graham 2002, Buschmann et al. 2004b). It is unknown whether the diversity of these herbivores within Macrocystis forests may enhance or lessen the effects of herbivory on Macrocystis survival and population dynamics, through complementarity or competition, respectively. It is well known, however, that sea urchins can have a great impact on Macrocystis standing stock through direct grazing (Lawrence 1975, Pearse & Hines 1979, Schiel & Foster 1986, Harrold & Pearse 1987, Vásquez & Buschmann 1997, Steneck et al. 2002, Vásquez et al. 2006). In some systems (e.g., southern Chile), Macrocystis fronds can be weighted down by epizoites and sea urchins can heavily graze water column biomass directly (Dayton 1985b). In most cases, however, the greatest impact of sea urchin grazing on Macrocystis biomass is when sea urchins aggregate on holdfasts and detach entire sporophytes, which then drift out of the system (North 1971, Foster & Schiel 1985); sea urchins (and potentially other herbivores) may then keep the system in a deforested state by grazing directly on Macrocystis recruits. Again, such overgrazing by Strongylocentrotus is apparently limited to periods of low drift availability (Ebeling et al. 1985, Harrold & Reed 1985), which occur episodically at local scales within southern California (Foster & Schiel 1988, Steneck et al. 2002, Graham 2004). Sea otters (Enhydra lutris) inhibit sea urchin overgrazing throughout the otter’s range (McLean 1962, Harrold & Pearse 1987, Foster & Schiel 1988, Watanabe & Harrold 1991), which at present is limited mostly to the Northern Hemisphere north of Point Conception (Laidre et al. 2001). Cowen et al. (1982) also observed that high wave action in central California curtailed sea urchin foraging and allowed algal recovery. In this region, seasonal variability in wave intensity was suggested as the most important factor regulating the abundance and structure of macroalgal assemblages (Cowen et al. 1982, Foster 1982). The mechanisms controlling sea urchin overgrazing in southern California (south of Point Conception), however, are controversial. In the absence of sea otters, various forms of abiotic and biotic regulation of sea urchin populations have been proposed (see Foster & Schiel 1988, Steneck et al. 2002). For example, storms and/or disease can wipe out large sea urchin aggregations over relatively broad spatial scales (Ebeling et al. 1985, Tegner & Dayton 1991, Lafferty 2004), whereas recruitment failure can limit replenishment of local sea urchin populations (Pearse & Hines 1987). Nevertheless, the most popular explanation for the lack of large-scale sea urchin barrens in the absence of sea otters in southern California is that other predators are controlling sea urchin abundance. Various kelp forest predators eat sea urchins (see review by Graham et al. 2007), although most only eat small sea urchins that are incapable of inflicting significant damage to Macrocystis holdfasts. Sheephead (Semicossyphus), lobsters (Panulirus) and the sunflower stars (Pycnopodia) appear to be the only Californian kelp forest predators other than sea otters that can feed on adult sea urchins. In some southern California kelp forests, data suggest that sheephead and lobster predation are important in controlling urchin abundance (e.g., Cowen 1983, Lafferty 2004) although the diets of these species are highly variable in space and may not include sea urchins even when sea urchins are present (e.g., Cowen 1986). Furthermore, in most cases the predation hypothesis is invoked in the absence of field experimentation (but see Cowen 1983), which is problematic since sheephead and lobsters have become relatively rare in southern California kelp forests (Dayton et al. 1998), yet deforested areas are also relatively rare (Foster & Schiel 1988). Sea urchin populations in southern California, therefore, are clearly regulated by multiple abiotic and biotic processes, probably resulting in the low frequency of sea urchin barrens in the Southern California Bight.

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The only other Macrocystis systems for which sea urchin overgrazing has been observed are in South America, although like California, large-scale overgrazing is rare (Vásquez & Buschmann 1997, Steneck et al. 2002). In northern Chile, large-scale overgrazing of Macrocystis by Tetrapygus niger appears to be limited by high water motion in the region where Tetrapygus and Macrocystis distributions overlap (Vásquez & Buschmann 1997). Sea urchin overgrazing in northern Chile is subsequently restricted to particular depth zones. Also, the asteroids Luidia and Meyenaster are solitary hunters within subtidal habitats and are important predators on Tetrapygus niger and other echinoids and asteroids (Viviani 1979, Vásquez & Buschmann 1997, Vásquez et al. 2006). Again, as in California, the role of sea urchin grazing in regulating Macrocystis populations in southern Chile is more controversial. Initial experimental results detected no effect of Loxechinus albus grazing on Macrocystis populations in the Beagle Channel (Castilla & Moreno 1982). On the other hand, Dayton (1985b) argued that Loxechinus albus grazing should significantly affect Macrocystis abundance along the protected coast of southern Chile where large asteroid predators could serve as a controlling factor and further suggested that the results of Castilla & Moreno (1982) were only relevant to the southernmost subpolar area (Beagle Channel). Additionally, density of an annual Macrocystis population in the archipelago region of southern Chile was significantly reduced from 24 to 2 sporophytes m−2 when Loxechinus albus densities exceeded 20 m−2 (Buschmann et al. 2004b). These contradictions have developed into an unresolved controversy about the ecological role of sea urchins in structuring Chilean Macrocystis populations (Vásquez & Buschmann 1997). Based on these numerous field studies spanning the global range of Macrocystis, simple trophic cascades do not seem to exist in Macrocystis-based systems. Various instances of overgrazing have been described (Steneck et al. 2002) but they are generally short-lived, observed at local scales and are often the result of overgrazing by particular trophic groups (e.g., sea urchins and amphipods). Nevertheless, due to the high diversity and productivity of Macrocystis-based food webs (Rosenthal et al. 1974, Pearse & Hines 1976, Castilla 1985, Foster & Schiel 1985, Graham 2004, Graham et al. 2007), these rare overgrazing events can have conspicuous ecological consequences (e.g., Graham 2004). The question still remains, however, as to why overgrazing is less frequent in Macrocystisbased systems than in other kelp-based systems (e.g., Aleutians, North Atlantic, Japan; Steneck et al. 2002). Three striking features are common to Macrocystis systems worldwide and may be important in buffering Macrocystis communities from overexploitation. The first is that all Macrocystis-based food webs are relatively diverse. Such high diversity, especially when it occurs at higher-order trophic levels, may provide a wider range of trophic interactions than less-diverse systems, minimising the impact of grazing by any given herbivore species. Such ecological effects of high diversity are supported by the field and experimental mesocosm studies of Byrnes et al. (2006), who found that increased predator diversity decreased the impact of an assemblage of grazers on Macrocystis biomass. In addition to the highly diverse systems of California, Beckley & Branch (1992) enumerated 200+ taxa in a Macrocystis system at the Prince Edwards Islands. Castilla (1985) identified 30+ herbivores and primary predators for the Macrocystis-based food web in the Beagle Channel, culminating with the generalist asteroid Cosmarestias lurida; Adami & Gordillo (1999) observed a similar system on the other side of the channel, although Loxechinus albus was conspicuously absent. Vásquez et al. (1998) observed similar trophic diversity in the Macrocystis system of northern Chile, which can include the Southern Hemisphere sea otter Lontra felina. Although L. felina does not feed on sea urchins (Ebensperger & Botto-Mahan 1997, Villegas 2002), these sea otters do forage on fishes, crustaceans and molluscs and may represent a diversifying component in these systems (Castilla & Bahamondes 1979). A poleward decrease in the diversity of Macrocystis systems appears to be present in both the Northern (Graham 2004, Graham et al. 2007) and Southern Hemispheres (Castilla 1985, Vásquez et al. 1998). The second commonality

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among Macrocystis systems is that they are all imbedded within high-productivity systems necessary to support Macrocystis survival, growth and reproduction. Therefore, the inherently high delivery of nutrients to global Macrocystis populations may simply override consumptive processes in regulating community structure and ecosystem processes over broad temporal and spatial scales. Finally, sea urchin recruitment appears to be more variable in space and time at low latitudes compared with high latitudes (Castilla & Moreno 1982, Foster & Schiel 1988, Buschmann et al. 2004b, Vega et al. 2005), potentially destabilising sea urchin population dynamics and decreasing the likelihood of large-scale sea urchin population explosions (Foster & Schiel 1988). Despite the numerous trophic studies of kelp forest organisms, however, there is a dearth of research on communitywide patterns of energy flow. Stable isotope methods have demonstrated the important role of detrital pathways in Macrocystis forests (e.g., Kaehler et al. 2000) and other systems (Duggins et al. 1989, Bustamante & Branch 1996, Fredriksen 2003). Macrocystis productivity is also exported to other systems (e.g., sandy beaches, deep-sea basins, coastal islands) where it may contribute greatly as an allochthonous energy source (Lavoie 1985, Inglis 1989, Vetter 1994, Harrold et al. 1998, Orr et al. 2005). The trophic consequences of Macrocystis production, however, have rarely been considered beyond the finite boundaries of the kelp forest. Clearly, Macrocystis systems are energy rich. Trophic interactions among kelp forest organisms can be conspicuous and are interesting avenues for ecological research. Yet, the emerging pattern over the last 150 yr of research is that at the community or ecosystem level, the diversity and productivity of Macrocystis systems are driven primarily by oceanographic processes that regulate the distribution, abundance and standing stock of the main foundation species, Macrocystis. It has recently been proposed, however, that the primary structural force for Macrocystis-based systems in southern California (Channel Islands National Park) is ‘top-down’ consumption (Halpern et al. 2006). Halpern et al. (2006) used satellite-derived chlorophyll-a data to estimate nutrient delivery to kelp beds as a proxy for ‘bottom-up’ processes. The effect of nutrients on algal abundance (primarily that of Macrocystis) was then determined to be significantly lower than consumptive effects. Off-shore chlorophyll-a concentrations, however, are not indicative of processes acting in the near shore (Blanchette et al. 2006) and nutrient delivery to off-shore plankton assemblages and near-shore kelp beds are two fundamentally different and negatively correlated processes (Broitman & Kinlan 2006). Additionally, it is well established that variability in Macrocystis sporophyte density (the abundance variable used by Halpern et al. 2006) is driven primarily by self-thinning and is unrelated to nutrient supply (North 1994), whereas nutrient supply and Macrocystis biomass are tightly coupled (North 1994, Tegner et al. 1996, 1997, Dayton et al. 1999). It would be interesting to know whether Halpern et al. (2006) would have obtained different results if they had used Macrocystis canopy biomass data available for the same region (Reed et al. 2006) and conducted their study beyond 1999–2002, which was the most ‘nutrient benign’ period of the last 50 yr. In fact, their study period did not include any of the conspicuous El Niño or La Niña events known to drive maxima and minima in community structure and energy flow within these systems (Dayton et al. 1999, Edwards 2004). A final concern with the approach of Halpern et al. (2006) is the inability of their correlative analyses to disentangle the confounding effects of habitat versus trophic associations. For example, one of their four conspicuous species that was correlated with Macrocystis abundance, and thus identified as a key consumer, was the striped surfperch (Embiotoca lateralis). Previous studies have repeatedly observed a negative association between E. lateralis and Macrocystis (Ebeling & Laur 1985, Holbrook et al. 1990). The mechanism underlying the association, however, is not a topdown trophic interaction but rather the negative effect of Macrocystis surface canopies on preferred foraging habitat (foliose algae) of Embiotoca lateralis. Another of the conspicuous species, the scavenger Kelletia kelletii, was found previously to be associated with sea urchin barrens rather than kelp forests (Behrens & Lafferty 2004), the exact opposite pattern from that predicted by the 70

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top-down hypothesis. The confounding nature of habitat versus trophic interactions in driving kelp forest associations is probably ubiquitous among Macrocystis systems due to this species simultaneous provision of primary habitat and energy throughout much of its range (see ‘Macrocystis as a foundation species,’ p. 62). This criticism of the results of Halpern et al. (2006) does not mean that predation is unimportant in regulating the structure and dynamics of Macrocystis systems, but simply argues for greater caution when using correlative data to understand regulatory processes in this complex system.

Community consequences of climate change and kelp forest exploitation Climate change and human exploitation can affect the diversity and productivity of Macrocystis systems either by indirect modification of Macrocystis distribution, abundance and productivity or by directly modifying distribution, abundance and productivity of the flora and fauna that inhabit Macrocystis forests. Macrocystis productivity and distributional limits are largely constrained by environmental processes (see ‘Organismal biology’ section, p. 42). Studies of environmental control on Macrocystis systems, however, have been limited entirely to ecological timescales (e.g., Dayton et al. 1999). Over periods of years to decades, temporal changes in nutrient availability (as measured through sea-surface temperature proxies), sedimentation and substratum composition, storms and light have all been shown to modify the living space and carrying capacity of Macrocystis (e.g., North & Schaeffer 1964, Zimmerman & Robertson 1985, Seymour et al. 1989, North 1994, Tegner et al. 1996, 1997, Dayton et al. 1999, Edwards 2004). Such responses to short-term climate change have typically been associated with ENSOs (4- to 7-yr frequency; Dayton et al. 1999, Edwards 2004) and cycles in the Pacific Decadal Oscillation (PDO, 10- to 20-yr frequency; Dayton et al. 1999). In California, strong ENSOs affect Macrocystis populations in two primary ways: nutrient stress associated with deepening of the thermocline and destructive storm waves. The relative impacts of each of these processes, however, vary latitudinally (Edwards 2004). Conspicuous second-order community responses often result, for example, from reduction in the availability of Macrocystis standing stock and drift and subsequent overgrazing by sea urchins or crustaceans (Ebeling et al. 1985, Harrold & Reed 1985, Tegner & Dayton 1987, Graham 2002, Behrens & Lafferty 2004). Ecologically important echinoderms (e.g., sea urchins and seastars) often suffer mass mortalities that may also be associated with ENSOs (Tegner & Dayton 1987, Dayton & Tegner 1989, Dayton et al. 1992, Behrens & Lafferty 2004, Lafferty 2004). These high-frequency ENSO cycles are overlaid on longer-frequency PDO cycles, with warm PDO periods exacerbating ENSO cycles (Dayton et al. 1999); the two most destructive ENSOs on record (1982–1983 and 1997–1998) occurred during the most recent warm PDO period. Nevertheless, the most wellestablished effect of PDO cycling on Macrocystis systems is the correlation between larger Macrocystis sporophyte sizes during PDO cold periods relative to warm periods (Tegner et al. 1996, 1997). The importance of short-term oceanographic phenomena (e.g., ENSO) in regulating other Macrocystis systems is essentially unknown. During the 1997–1998 El Niño, northern Chilean Macrocystis populations increased, while black sea urchins (Tetrapygus niger) decreased (Vega et al. 2005), a pattern opposite to that observed in southern California. The 1997–1998 El Niño devastated Macrocystis populations in central Perú, decreasing sporophyte density and the diversity of associated species (Lleellish et al. 2001). The subsequent 1998–1999 La Niña, however, triggered high Tetrapygus niger recruitment and a significant increase in T. niger adult populations (Vásquez et al. 2006), which corresponded with a crash in Macrocystis populations (Vega et al. 2005). The 1997–1998 El Niño also affected northern Chilean asteroid populations. Luidia and Meyenaster are considered to be top predators in littoral benthic food chains of northern Chile, and both species prey upon Heliaster and Stichaster (Viviani 1979). Luidia and Meyenaster coexist and restrict the 71

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bathymetric distribution of Stichaster and Heliaster in the intertidal and subtidal zones (Viviani 1979). Meyenaster and Luidia decreased significantly within Macrocystis populations during the 1997–1998 El Niño, potentially migrating to deeper water, whereas Heliaster and Stichaster increased in abundance during the same period (Vásquez et al. 2006). It remains to be determined whether the ENSO-driven decreases in Luidia and Meyenaster abundances, both important predators on Tetrapygus (Viviani 1979, Vásquez 1993, Vásquez & Buschmann 1997), were the ultimate causes of the 1998–1999 T. niger population explosion (Vega et al. 2005, Vásquez et al. 2006). Although nutrient deprivation is the most conspicuous intra- and interdecadal oceanographic stressor on Macrocystis physiology and survival, it has recently been shown that temperature shifts alone can have rapid impacts on Macrocystis systems from the organismal to community levels. Schiel et al. (2004) used an 18-yr dataset to study changes in the structure of a local Nereocystis kelp bed after 10 yr of increased ocean temperature (+3.5°C) due to the thermal outfall of a powergenerating station. Similar to the changes observed following deforestation in southern California (Graham 2004), Schiel et al. (2004) detected significant communitywide changes in 150 species of algae and invertebrates since the initiation of the thermal outfall. These community changes, however, were not consistent with a northern shift in the distribution of southern species, but rather a shift in the dominant canopy-forming kelp from Nereocystis to Macrocystis, and the potential shading effect of the Macrocystis surface canopy. These data demonstrate the difficulty in disentangling the direct effect of climate change on giant kelp communities from the indirect effect of climate change on the distribution, abundance and productivity of key habitat-forming and energyproducing species, like Macrocystis. Studies of the effects of natural and anthropogenic climate change on Macrocystis systems have been limited to the last few decades. The frequency and severity of ENSOs have been highly variable over geological timescales (Rosenthal & Broccoli 2004) and it has been suggested that their frequency is increasing (Diaz et al. 2001). Still, the ecological consequences of such longterm climate change to Macrocystis systems seem obvious; Schimmelmann & Tegner (1991) detected an ENSO signal in the flux of Macrocystis-derived organic carbon to the floor of the Santa Barbara Basin over 1500 yr. Less obvious, however, are interactions between long-term changes in ocean temperature, near-shore sedimentation, light and sea level that are driven by glacialinterglacial cycling (Graham et al. 2003). Macrocystis has limited depth, substratum composition and nutrient ranges, and ice age redistribution and modification of environmental conditions may have had massive impacts on Macrocystis distribution, abundance and productivity. For example, late-Quaternary sea-level rise probably led to large changes in inhabitable Macrocystis reef area around the Californian Channel Islands and mainland as broad near-shore rocky platforms became exposed, shrank and even fragmented (Graham et al. 2003, Kinlan et al. 2005). A recent study predicted that southern Californian Macrocystis kelp forest area and biomass increased up to 3-fold from the last glacial maximum to the mid-Holocene, but then rapidly declined by 40–70% during the late Holocene to current area and biomass levels (M.H. Graham, B.P. Kinlan, R.K. Grossberg, unpublished data). Furthermore, the early Holocene peak in Macrocystis distribution and abundance coincided with highly productive palaeo-oceanographic conditions, probably yielding a subsequent peak in Macrocystis productivity during that period. This shift overlapped with conspicuous changes in total biomass of kelp-associated species, such as abalone, sea urchins and turban snails in native American shell middens on the Channel Islands (Erlandson et al. 2005). The community and ecosystem consequences of such long-term climate change on Macrocystis systems can be predicted but critical tests of such predictions will require application of contemporary palaeo-ecological tools (e.g., stable isotopes) because Macrocystis sporophytes do not fossilise (Graham et al. 2003). Poor strategies of sewage discharge in the 1950s and 1960s were associated with the decimation of a few very large Macrocystis forests in southern California (North & Schaeffer 1964, North & Hubbs 1968, North 1971, Tegner & Dayton 1991). Stringent regulations, however, quickly remedied 72

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the impacts. Tegner et al. (1995b) later found that nitrogenous wastes originating from breakage in sewage outfalls can actually have positive effects on Macrocystis recruitment, especially during periods of nutrient deprivation. It was also noted by Dawson et al. (1960) that an oil spill in Baja California, Mexico, had no direct impacts on Macrocystis physiology, yet positively affected Macrocystis survival by causing high local mortality of sea urchins. Effects of other pollutants, such as some metals and aqueous petroleum waste, on Macrocystis microscopic stages can inhibit microtubule dynamics, DNA replication, photosynthetic processes and overall physiology (Anderson et al. 1990, Garman et al. 1994, 1995, Reed & Lewis 1994). Despite these localised impacts, there is little evidence that chemical pollution currently restricts Macrocystis distribution, abundance and productivity over broad spatial and temporal scales. Finally, Macrocystis systems have been subjected to long-term anthropogenic exploitation, spanning a period of at least 11,000 yr (Erlandson et al. 2005). Recent attention has focused on direct exploitation of Macrocystis populations and Macrocystis-associated organisms, especially in southern California where Macrocystis has been harvested for algin extraction since the 1920s (North 1994). Californian harvests are limited to the upper 1–2 m of the water column and have been shown to have minimal impacts on sporophyte survival (see p. 56). Indeed, while there is considerable temporal variability in Macrocystis populations due to physical and biological factors, the long-term stability of the Macrocystis harvest suggests that it is one of the best-managed marine harvests of wild populations worldwide (Dayton et al. 1998). Nevertheless, in southern Chile, Macrocystis is harvested by abalone farmers who require biomass all year round and Macrocystis cultivation is now required to offset heavy exploitation of natural Macrocystis populations (Gutierrez et al. 2006). Due to the patchy distribution of integrifolia-form populations in northern Chile, Macrocystis harvesting near abalone farms has had a great impact on the dynamics of local Macrocystis populations, with subsequent effects on Macrocystis-associated communities (J.A. Vásquez, unpublished data). Although Macrocystis populations themselves appear to be relatively immune to episodic harvesting of the surface canopy, Macrocystis-associated organisms are not. Overfishing has resulted in virtual elimination of large predators in southern California Macrocystis forests (Dayton et al. 1998). The ecological impacts of overfishing on Macrocystis populations are unclear because some correlative studies suggest cascading impacts whereas others do not (Foster & Schiel 1988, Dayton et al. 1998, Steneck et al. 2002, Behrens & Lafferty 2004, Lafferty 2004, Graham et al. 2007). Although predators may or may not be more common within marine reserves (Paddack & Estes 2000, Behrens & Lafferty 2004, Lafferty 2004), predators within reserves are typically larger in size (Paddack & Estes 2000). Again, the problem lies in deciphering the various types and strengths of species interactions operating in Macrocystis forests (e.g., Macrocystis-derived habitat and energy provision compared with predation). One thing is clear, however, despite the ubiquitous role of Macrocystis-derived habitat and energy provision in enhancing kelp forest diversity and productivity worldwide, kelp forest organisms cannot survive targeted exploitation over large temporal and spatial scales (Dayton et al. 1998).

Conclusion The global scientific literature indicates that Macrocystis is an important provider of habitat and energy to its associated communities wherever it is present. It is also clear that, despite non-trivial gene flow among global Macrocystis populations, Macrocystis morphology and physiology are highly variable in response to the environmental conditions within which sporophytes recruit, grow and reproduce. These conspicuous ecotypic differences have generally led researchers to study Macrocystis population dynamics and community interactions from a regional perspective. Patterns observed for some large conspicuous giant kelp forests in southern California have subsequently 73

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dominated the literature and become the paradigms against which the ecologies of other Macrocystis systems are compared. When viewed from a global perspective, however, regional differences in the results of prior descriptive and experimental studies can be reconciled by an appreciation of great plasticity in Macrocystis form and function. The origin, nature and potential restriction of such plasticity to Macrocystis are appealing paths for future research.

Acknowledgements We greatly appreciate the support of our funding agencies: J.A.V. and A.H.B. acknowledge FONDECYT (grants 1010706, 1000044 and 1040425) and the Universidad de Los Lagos; M.H.G. acknowledges the National Science Foundation (NSF 0351778 and 0407937), San Jose State University, and the Moss Landing Marine Laboratories. We also acknowledge Alonso Vega, Mariam Hernández, Pirjo Huovenin, René Espinoza, Lara Ferry-Graham, David Schiel, Sean Connell, Louis Druehl and Michael Foster for various levels of support and comments during production of this review.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Druehl, L.D. & Kemp, L. 1982. Morphological and growth responses of geographically isolated Macrocystis integrifolia populations when grown in a common environment. Canadian Journal of Botany 60, 1409–1413. Druehl, L.D., Mayes, C., Tan, I.H. & Saunders, G.W. 1997. Molecular and morphological phylogenies of kelp and associated brown algae. In Plant Systematics and Evolution Supplement 11: Origins of Algae and their Plastids, D. Bhattacharya (ed.). Vienna: Springer-Verlag, 221–235. Druehl, L.D., Robertson, B.R. & Button, D.K. 1989. Characterizing and sexing Laminarialean meiospores by flow cytometry. Marine Biology 101, 451–456. Druehl, L.D. & Wheeler, W.N. 1986. Population biology of Macrocystis integrifolia from British Columbia, Canada. Marine Biology 90, 173–179. Duggins, D.O., Simenstad, C.A. & Estes, J.A. 1989. Magnification of secondary production by kelp detritus in coastal marine ecosystems. Science 245, 170–173. Dunton, K.H. 1990. Growth and production in Laminaria solidungula: relation to continuous underwater light levels in the Alaskan high Arctic. Marine Biology 106, 297–304. Dunton, K.H. & Jodwalis, C.M. 1988. Photosynthetic performance of Laminaria solidungula measured in situ in the Alaskan high Arctic. Marine Biology 98, 277–286. Eardley, D.D., Sutton, C.W., Hempel, W.M., Reed, D.C. & Ebeling, A.W. 1990. Monoclonal antibodies specific for sulfated polysaccharides on the surface of Macrocystis pyrifera (Phaeophyceae). Journal of Phycology 26, 54–62. Ebeling, A.W. & Laur, D.R. 1985. The influence of plant cover on surfperch abundance at an offshore temperate reef. Environmental Biology of Fishes 12, 169–180. Ebeling, A.W., Laur, D.R. & Rowley, R.J. 1985. Severe storm disturbances and reversal of community structure in a southern California kelp forest. Marine Biology 84, 287–294. Ebensperger, L.A. & Botto-Mahan, C. 1997. Use of habitat, size of prey, and food-niche relationships of two sympatric otters in southernmost Chile. Journal of Mammalogy 78, 222–227. Edgar, G.J. 1987. Dispersal of faunal and floral propagules associated with drifting Macrocystis pyrifera plants. Marine Biology 95, 599–610. Edwards, M.S. 1998. Effects of long-term kelp canopy exclusion on the abundance of the annual alga Desmarestia ligulata (Light F). Journal of Experimental Marine Biology and Ecology 228, 309–326. Edwards, M.S. 2004. Estimating scale-dependency in disturbance impacts: El Niños and giant kelp forests in the northeast Pacific. Oecologia 138, 436–447. Edwards, M.S. & Hernández-Carmona, G. 2005. Delayed recovery of giant kelp near its southern range limit in the North Pacific following El Niño. Marine Biology 147, 273–279. Erlandson, J.M., Rick, T.C., Estes, J.A., Graham, M.H., Braje, T.J. & Vellanoweth, R.L. 2005. Sea otters, shellfish, and humans: a 10,000 year record from San Miguel island, California Proceedings of the California Islands Symposium 6, 56–68. Estes, J.A. & Duggins, D.O. 1995. Sea otters and kelp forests in Alaska: generality and variation in a community ecological paradigm. Journal of Phycology 65, 75–100. Estes, J.A. & Steinberg, P.D. 1988. Predation, herbivory, and kelp evolution. Paleobiology 14, 19–36. Fain, S.R. & Murray, S.N. 1982. Effects of light and temperature on net photosynthesis and dark respiration of gametophytes and embryonic sporophytes of Macrocystis pyrifera. Journal of Phycology 18, 92–98. Feder, H.M., Turner, C.H. & Limbaugh, C. 1974. Observations on fishes associated with kelp beds in southern California. California Department of Fish and Game, Fish Bulletin 160, 1–144. Fosberg, F.R. 1929. Preliminary notes on the fauna of the giant kelp. Journal of Entolomological Zoology 21, 133–135. Foster, M.S. 1982. The regulation of macroalgal associations in kelp forests. In Synthetic and Degradative Processes in Marine Macrophytes, L. Srivastava (ed.). Berlin: Walter de Gruyter & Co., 185–205. Foster, M.S. & Schiel, D.R. 1985. The ecology of giant kelp forests in California: a community profile. United States Fish and Wildlife Service Biological Report 85, 1–152. Foster, M.S. & Schiel, D.R. 1988. Kelp communities and sea otters: keystone species or just another brick in the wall? In The Community Ecology of Sea Otters, G.R. VanBlaricom & J.A. Estes (eds). Berlin: Springer-Verlag, 92–115.

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GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS Foster, M.S. & Schiel, D.R. 1992. Zonation, El Niño disturbance, and the dynamics of subtidal vegetation along a 30 m depth gradient in two giant kelp forests. Proceedings of the International Temperate Reef Symposium 2, 151–162. Fredriksen, S. 2003. Food web studies in a Norwegian kelp forest based on stable isotope (d13C and d15N) analysis. Marine Ecology Progress Series 260, 71–81. Fritsch, F.E. 1945. The Structure and Reproduction of the Algae. Volume 2. Cambridge: Cambridge University Press. Gabrielson, P.W., Widdowson, T.B., Lindstrom, S.C., Hawkes, M.W. & Scagel, R.F. 2000. Keys to the Benthic Marine Algae and Seagrasses of British Columbia, Southeast Alaska, Washington and Oregon: Phycological Contribution #5. Vancouver: University of British Columbia Department of Botany. Garman, G.D., Pillai, M.C. & Cherr, G.N. 1994. Inhibition of cellular events during algal gametophyte development: effects of select metals and an aqueous petroleum waste. Aquatic Toxicology 28, 127–144. Garman, G.D., Pillai, M.C., Goff, L.J. & Cherr, G.N. 1995. Nuclear events during early development in Macrocystis pyrifera gametophytes and the temporal effects of a marine contaminant. Marine Biology 121, 355–362. Gaylord, B., Reed, D.C., Raimondi, P.T., Washburn, L. & McLean, S.R. 2002. A physically based model of macroalgal spore dispersal in the wave and current-dominated nearshore. Ecology 83, 1239–1251. Gerard, V.A. 1976. Some aspects of material dynamics and energy flow in a kelp forest in Monterey Bay, California. Ph.D. dissertation, University of California Santa Cruz, Santa Cruz, California. Gerard, V.A. 1982. Growth and utilization of internal nitrogen reserves by the giant kelp Macrocystis pyrifera in a low-nitrogen environment. Marine Biology 66, 27–35. Gerard, V.A. & Kirkmann, H. 1984. Ecological observations on a branched, loose-lying form of Macrocystis pyrifera (L) C. Agardh in New Zealand. Botanica Marina 27, 105–109. Gerard, V.A. and Mann, K.H. 1979. Growth and production of Laminaria longicruris (Phaeophyta) populations exposed to different intensities of water movement. Journal of Phycology 14, 195–198. Ghelardi, R.J. 1971. The biology of giant kelp beds (Macrocystis) in California: species structure of the holdfast community. Nova Hedwigia 32, 381–420. Gonzalez-Fragoso, J., Ibarra-Obando, S.E. & North, W.J. 1991. Frond elongation rates of shallow water Macrocystis pyrifera (L.) Ag. in northern Baja California, México. Journal of Applied Phycology 3, 311–318. Graham, M.H. 1996. Effect of high irradiance on recruitment of giant kelp Macrocystis (Phaeophyta) in shallow water. Journal of Phycology 32, 903–906. Graham, M.H. 1997. Factors determining the upper limit of giant kelp, Macrocystis pyrifera Agardh, along the Monterey Peninsula, central California, U.S.A. Journal of Experimental Marine Biology and Ecology 218, 127–149. Graham, M.H. 1999. Identification of kelp zoospores from in situ plankton samples. Marine Biology 135, 709–720. Graham, M.H. 2000. Planktonic patterns and processes in the giant kelp Macrocystis pyrifera. Ph.D. dissertation, University of California San Diego, La Jolla, California. Graham, M.H. 2002. Prolonged reproductive consequences of short-term biomass loss in seaweeds. Marine Biology 140, 901–911. Graham, M.H. 2003. Coupling propagule output to supply at the edge and interior of a giant kelp forest. Ecology 84, 1250–1264. Graham, M.H. 2004. Effects of local deforestation on the diversity and structure of southern California giant kelp forest food webs. Ecosystems 7, 341–357. Graham, M.H., Dayton, P.K. & Erlandson, J.M. 2003. Ice ages and ecological transitions on temperate coasts. Trends in Ecology and Evolution 18, 33–40. Graham, M.H., Halpern, B.S. & Carr, M.H. 2007. Diversity and dynamics of Californian subtidal kelp forests. In Food Webs and the Dynamics of Marine Benthic Ecosystems, T.R. McClanahan & G.R. Branch (eds). Oxford: Oxford University Press, in press. Graham, M.H., Harrold, C., Lisin, S., Light, K., Watanabe, J.M. & Foster, M.S. 1997. Population dynamics of giant kelp Macrocystis pyrifera along a wave exposure gradient. Marine Ecology Progress Series 148, 269–279.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Graham, M.H. & Mitchell, B.G. 1999. Obtaining absorption spectra from individual macroalgal spores using microphotometry. Hydrobiologia 398/399, 231–239. Grua, P. 1964. Sur la structure des peuplements de Macrocystis pyrifera (L.) C. Ag. observés en plongée à Kerguelen et Crozet. Comptes Rendus Hebdomadaires des Séances de l’Académie des Sciences Paris 259, 1541–1543. Guiler, E.R. 1952. The intertidal ecology of Eaglehawk Neck area. Papers and Proceedings of the Royal Society of Tasmania 86, 13–29. Guiler, E.R. 1960. Notes on the intertidal ecology of Trial Harbour, Tasmania. Papers and Proceedings of the Royal Society of Tasmania 94, 57–62. Gutierrez, A., Correa, T., Muñoz, V., Santibañez, A., Marcos, R., Caceres, C. & Buschmann, A.H. 2006. Farming of the giant kelp Macrocystis pyrifera in southern Chile for development of novel food products. Journal of Applied Phycology 18, 259–267. Hallacher, L.E. & Roberts, D.A. 1985. Differential utilization of space and food by the inshore rockfishes (Scorpaenidae: Sebastes) of Carmel Bay, California [U.S.A.]. Environmental Biology of Fishes 12, 91–110. Halpern, B.S., Cottenie, K. & Broitman, B.R. 2006. Strong top-down control in southern California kelp forest ecosystems. Science 312, 1230–1232. Harris, L.G., Ebeling, A.W., Laur, D.R. & Rowley, R.J. 1984. Community recovery after storm damage: a case of facilitation in primary succession. Science 224, 1339–1338. Harrold, C., Light, K. & Lisin, S. 1998. Organic enrichment of submarine-canyon and continental shelf benthic communities by macroalgal drift imported from nearshore kelp forests. Limnology and Oceanography 43, 669–678. Harrold, C. & Lisin, S. 1989. Radio-tracking rafts of giant kelp: Local production and regional transport. Journal of Experimental Marine Biology and Ecology 130, 237–251. Harrold, C. & Pearse, J.S. 1987. The ecological role of echinoderms in kelp forests. Echinoderm Studies 2, 137–233. Harrold, C. & Reed, D.C. 1985. Food availability, sea urchin grazing, and kelp forest community structure. Ecology 66, 1160–1169. Hay, C.H. 1986. A new species of Macrocystis C. Ag. (Phaeophyta) from Marion Island, southern Indian Ocean. Phycologia 25, 241–252. Hay, C.H. 1990. The distribution of Macrocystis C. Ag. (Phaeophyta, Laminariales) as a biological indicator of cool sea surface temperatures, with special reference to New Zealand water. Journal of the Royal Society of New Zealand 20, 313–336. Helmuth, B.S., Veit, R.R. & Holberton, R. 1994. Long-distance dispersal of subantarctic brooding bivalve (Gaimardia trapesina) by kelp rafting. Marine Biology 120, 421–6. Hempel, W.M., Sutton, C.W., Kaska, D., Ord, D.C., Reed, D.C., Laur, D.R., Ebeling, A.W. & Eardley, D.D. 1989. Purification of species-specific antibodies to carbohydrate components of Macrocystis pyrifera (Phaeophyta). Journal of Phycology 25, 144–149. Henry, E.C. & Cole, D.W. 1982. Ultrastructure of swarmers in the Laminariales (Phaeophyceae). I. Zoospores. Journal of Phycology 18, 550–569. Hernández-Carmona, G. 1996. Frond elongation rates of Macrocystis pyrifera (L.) Ag. at Bahia Tortugas, Baja California sur, México. Ciencias Marinas 22, 57–72. Hernández-Carmona, G., Garcia, O., Robledo, D. & Foster, M.S. 2000. Restoration techniques for Macrocystis pyrifera (Phaeophyceae) populations at the southern limit of their distribution in México. Botanica Marina 43, 273–284. Hernández-Carmona, G., Hughes, B. & Graham, M.H. 2006. Reproductive longevity of drifting kelp Macrocystis pyrifera (Phaeophyceae) in Monterey Bay, U.S.A. Journal of Phycology 42, 1199–1207. Hernández-Carmona, G., Robledo, D. & Serviere-Zaragoza, E. 2001. Effect of nutrient availability on Macrocystis pyrifera recruitment and survival near its southern limit off Baja California. Botanica Marina 44, 221–229. Hernández-Carmona, G., Rodriguez-Montesinos, Y.E., Casas-Valdez, M.M., Vilchis, M.A. & Sanchez-Rodriguez, I. 1991. Evaluation of the beds of Macrocystis pyrifera (Phaeophyta, Laminariales) in the Baja California peninsula, México. III. Summer 1986 and seasonal variation. Ciencias Marinas 17, 121–145.

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GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS Hernández-Carmona, G., Rodriguez-Montesinos, Y.E., Torres-Villegas, J.R., Sanchez-Rodriguez, I. & Vilchis, M.A. 1989a. Evaluation of Macrocystis pyrifera (Phaeophyta, Laminariales) kelp beds in Baja California, México. I. Winter 1985–1986. Ciencias Marinas 15, 1–27. Hernández-Carmona, G., Rodriguez-Montesinos, Y.E., Torres-Villegas, J.R., Sanchez-Rodriguez, I., Vilchis, M.A. & Garcia-de la Rosa, O. 1989b. Evaluation of Macrocystis pyrifera (Phaeophyta, Laminariales) kelp beds in Baja California, México. II. Spring 1986. Ciencias Marinas 15, 117–140. Hobday, A.J. 2000a. Abundance and dispersal of drifting kelp Macrocystis pyrifera rafts in the Southern California Bight. Marine Ecology Progress Series 195, 101–116. Hobday, A.J. 2000b. Age of drifting Macrocystis pyrifera (L.) C. Agardh rafts in the Southern California Bight. Journal of Experimental Marine Biology and Ecology 253, 97–114. Hobday, A.J. 2000c. Persistence and transport of fauna on drifting kelp (Macrocystis pyrifera (L.) C. Agardh) rafts in the Southern California Bight. Journal of Experimental Marine Biology and Ecology 253, 75–96. Hobson, E.S. & Chess, J.R. 2001. Influence of trophic relations on form and behavior among fishes and benthic invertebrates in some California marine communities. Environmental Biology of Fishes 60, 411–457. Hoffmann, A.J., Avila, M. & Santelices, B. 1984. Interactions of nitrate and phosphate on the development of microscopic stages of Lessonia nigrescens Bory (Phaeophyta). Journal of Experimental Marine Biology and Ecology 78, 177–186. Hoffmann, A.J. & Santelices, B. 1982. Effects of light intensity and nutrients on gametophytes and gametogenesis of Lessonia nigrescens Bory (Phaeophyta). Journal of Experimental Marine Biology and Ecology 60, 77–89. Hoffmann, A.J. & Santelices, B. 1991. Banks of algal microscopic forms: hypotheses on their functioning and comparisons with seed banks. Marine Ecology Progress Series 79, 185–194. Holbrook, S.J., Carr, M.H., Schmitt, R.J. & Coyer, J.A. 1990. Effect of giant kelp on local abundance of reef fishes: the importance of ontogenetic resource requirements. Bulletin of Marine Science 47, 104–114. Hooker, J.D. 1847. The Botany of the Antarctic Voyage of H.M. Discovery Ships Erebus and Terror. I. Flora Antarctica. London: Reeve Brothers. Howe, M.A. 1914. The marine algae of Perú. Memoirs of the Torrey Botanical Club 15, 1–185. Huovinen, P.J., Oikari, A.O.J., Soimasuo, M.R. & Cherr, G.N. 2000. Impact of UV radiation on the early development of giant kelp (Macrocystis pyrifera) gametophytes. Photochemistry and Photobiology 72, 308–313. Hurd, C.L., Durante, K.M., Chia, F.S. & Harrison, P.J. 1994. Effect of bryozoan colonization on inorganic nitrogen acquisition by the kelps Agarum fimbriatum and Macrocystis integrifolia. Marine Biology 121, 167–173. Hurd, C.L., Stevens, C.L., Laval, B.E., Lawrence, G.A. & Harrison, P.J. 1997. Visualization of seawater flow around morphologically distinct forms of the giant kelp Macrocystis integrifolia from wave-sheltered and exposed sites. Limnology and Oceanography 42, 156–163. Inglis, G. 1989. The colonization and degradation of stranded Macrocystis pyrifera (L.) C. Ag. by the macrofauna of a New Zealand sandy beach. Journal of Experimental Marine Biology and Ecology 125, 203–218. Isaac, W.E. 1937. Studies of South African seaweed vegetation. I. West coast from Lamberts Bay to the Cape of Good Hope. Transactions of the Royal Society of South Africa 25, 115–151. Jackson, G.A. 1977. Nutrients and production of giant kelp, Macrocystis pyrifera, southern California. Limnology and Oceanography 22, 979–995. Jackson, G.A. 1987. Modeling the growth and harvest yield of the giant kelp Macrocystis pyrifera. Marine Biology 95, 611–624. Jackson, G.A. 1998. Currents in the high drag environment of a coastal kelp stand off California. Continental Shelf Research 17, 1913–1928. Jackson, G.A. & Winant, C.D. 1983. Effect of a kelp forest on coastal currents. Continental Shelf Research 2, 75–80. Jensen, J.R., Estes, J.E. & Tinney, L. 1980. Remote sensing techniques for kelp surveys. Photogrammetric Engineering and Remote Sensing 46, 743–755.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Jones, L.G. 1971. The biology of giant kelp beds (Macrocystis) in California: Studies on selected small herbivorous invertebrates inhabiting Macrocystis canopies and holdfasts in southern Californian kelp beds. Nova Hedwigia 32, 343–367. Juhl-Noodt, H. 1958. Beiträge zur Kenntnis der Perúanischen Meeresalgen. I. Kieler Meeresforschungen 14, 167–174. Kaehler, S., Pakhomov, E.A. & McQuaid, C.D. 2000. Trophic structure of the marine food web at the Prince Edward Islands (Southern Ocean) determined by delta13C and delta15N analysis. Marine Ecology Progress Series 208, 13–20. Kain, J.M. 1979. A view of the genus Laminaria. Oceanography and Marine Biology: An Annual Review 17, 101–161. Kain, J.M. 1982. Morphology and growth of the giant kelp Macrocystis pyrifera in New Zealand and California. Marine Biology 67, 143–157. Kenner, M.C. 1992. Population dynamics of the sea urchin Strongylocentrotus purpuratus in a central California kelp forest: recruitment, mortality, growth and diet. Marine Biology 112, 107–118. Kim, S.L. 1992. The role of drift kelp in the population ecology of a Diopatra ornata Moore (Polychaeta: Onuphidae) ecotone. Journal of Experimental Marine Biology and Ecology 156, 253–272. Kimura, R.S. & Foster, M.S. 1984. The effects of harvesting Macrocystis pyrifera on the algal assemblage in a giant kelp forest. Hydrobiologia 116/117, 425–428. Kinlan, B.P., Graham, M.H. & Erlandson, J.M. 2005. Late-quaternary changes in the size and shape of the California Channel Islands: implications for marine subsidies to terrestrial communities. Proceedings of the California Islands Symposium 6, 119–130. Kinlan, B.P., Graham, M.H., Sala, E. & Dayton, P.K. 2003. Arrested development of giant kelp (Macrocystis pyrifera, Phaeophyceae) embryonic sporophytes: a mechanism for delayed recruitment in perennial kelps? Journal of Phycology 39, 47–57. Kopczak, C.D., Zimmerman, R.C. & Kremer, J.N. 1991. Variation in nitrogen physiology and growth among geographically isolated populations of the giant kelp, Macrocystis pyrifera (Phaeophyta). Journal of Phycology 27, 149–158. Ladah, L.B. & Zertuche-Gonzalez, J.A. 2004. Giant kelp (Macrocystis pyrifera) survival in deep water (25–40 m) during El Niño of 1997–1998 in Baja California, México. Botanica Marina 47, 367–372. Ladah, L.B., Zertuche-Gonzalez, J.A. & Hernández-Carmona, G. 1999. Giant kelp (Macrocystis pyrifera, Phaeophyceae) recruitment near its southern limit in Baja California after mass disappearance during ENSO 1997–1998. Journal of Phycology 35, 1106–1112. Lafferty, K.D. 2004. Fishing for lobsters indirectly increases epidemics in sea urchins. Ecological Applications 14, 1566–1573. Laidre, K.L., Jameson, R.J. & DeMaster, D.P. 2001. An estimation of carrying capacity for sea otters along the California coast. Marine Mammal Science 17, 294–309. Lane, C.E., Mayes, C., Druehl, L.D. & Saunders, G.W. 2006. A multi-gene molecular investigation of the kelp (Laminariales, Phaeophyceae) supports substantial taxonomic re-organization. Journal of Phycology 42, 493–512. Lavoie, D.R. 1985. Population dynamics and ecology of beach wrack macroinvertebrates of the central California [U.S.A.] coast. Bulletin of the Southern California Academy of Sciences 84, 1–22. Lawrence, J.M. 1975. On the relationships between marine plants and sea urchins. Oceanography and Marine Biology: An Annual Review 13, 213–286. Leet, W.S., Dewees, C.M., Klingbeil, R. & Johnson, E.J. (eds) 2001. California’s living marine resources: a status report. State of California Resources Agency and Fish and Game, Sacramento, California. Leighton, D.L. 1966. Studies of food preference in algivorous invertebrates of southern California kelp beds. Pacific Science 20, 104–113. Leonard, G.H. 1994. Effect of the bat star Asterina miniata (Brandt) on recruitment of the giant kelp Macrocystis pyrifera C. Agardh. Journal of Experimental Marine Biology and Ecology 179, 81–98. Lewis, R. & Neushul, M. 1994. Northern and Southern Hemisphere hybrids of Macrocystis (Phaeophyceae). Journal of Phycology 30, 346–353. Lewis, R.J., Neushul, M. & Harger, B.W.W. 1986. Interspecific hybridization of the species of Macrocystis in California. Aquaculture 57, 203–210.

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GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS Lindberg, D.R. 1991. Marine biotic interchange between the Northern and Southern Hemispheres. Paleobiology 17, 308–324. Lleellish, M., Fernández, E. & Hooker, Y. 2001. Disturbancia del bosque submareal de Macrocystis pyrifera durante El Niño 1997–1998 en la bahía de Pucusana. In Sustentabilidad de la Biosiversidad: Un problema actual, bases científico-técnicas, teorizaciones y perspectivas, K. Alveal & T. Antezana (eds). Concepción, Chile: Universidad de Concepción, 331–350. Lobban, C.S. 1978a. The growth and death of the Macrocystis sporophyte (Phaeophyceae, Laminariales). Phycologia 17, 196–212. Lobban, C.S. 1978b. Growth of Macrocystis integrifolia in Barkley Sound, Vancouver Island, B.C. Canadian Journal of Botany 56, 2707–2711. Lüning, K. 1990. Seaweeds. Their Environment, Biogeography and Ecophysiology. New York: John Wiley & Sons. Lüning, K. & Neushul, M. 1978. Light and temperature demands for growth and reproduction of Laminarian gametophytes in southern and central California. Marine Biology 45, 297–310. Macaya, E.C., Boltaña, S., Hinojosa, I.A., Macchiavello J.E., Valdivia, N.E., Vásquez N.R., Buschmann A.H., Vásquez, J.A., Vega, J.M.A. & Thiel, M. 2005. Presence of sporophylls in floating kelp rafts of Macrocystis spp. (Phaeophyceae) along the Chilean Pacific Coast. Journal of Phycology 41, 913–922. Maier, I., Hertweck, C. & Boland, W. 2001. Stereochemical specificity of lamoxirene the sperm-releasing pheromone in kelp (Laminariales, Phaeophyceae). Biological Bulletin (Woods Hole) 201, 121–125. Maier, I., Müller, D.G., Gassmann, G., Boland, W. & Jaenicke, L. 1987. Sexual pheromones and related egg secretions in Laminariales (Phaeophyta). Zeitschrift Naturforschung Section C Biosciences 42, 948–954. Mann, K.H. 1973. Seaweeds: their productivity and strategy for growth. Science 182, 975–981. Mattison, J.E., Trent, J.D., Shanks, A.L., Akin, T.B. & Pearse, J.S. 1977. Movement and feeding activity of red sea urchins (Strongylocentrotus franciscanus) adjacent to a kelp forest. Marine Biology 39, 25–30. McCleneghan, K. & Houk, J.L. 1985. The effects of canopy removal on holdfast growth in Macrocystis pyrifera (Phaeophyta; Laminariales). California Fish and Game 71, 21–27. McConnico, L. & Foster, M.S. 2005. Population biology of the intertidal kelp, Alaria marginata Postels and Ruprecht: a non-fugitive annual. Journal of Experimental Marine Biology and Ecology 324, 61–75. McLean, J.H. 1962. Sublittoral ecology of kelp beds of the open coast near Carmel, California. Biological Bulletin (Woods Hole) 122, 95–114. McPeak, R.H. 1981. Fruiting in several species of Laminariales from southern California. Proceedings of the International Seaweed Symposium 8, 404–409. Moe, R.L. & Silva, P.C. 1977. Antarctic marine flora: uniquely devoid of kelps. Science 196, 1206–1208. Moore, L.B. 1943. Observations on the growth of Macrocystis in New Zealand, with a description of a freeliving form. Transactions of the Royal Society of New Zealand 72, 333–340. Moreno C.A. & Jara H.F. 1984. Ecological studies of fish fauna associated with Macrocystis pyrifera belts in the south of Feuguian Islands, Chile. Marine Ecology Progress Series 15, 99–107. Moreno, C.A. & Sutherland, J.P. 1982. Physical and biological processes in a Macrocystis pyrifera community near Valdivia, Chile. Oecologia 55, 1–6. Müller, D.G., Maier, I. & Müller H. 1987. Flagellum autofluorescence and photoaccumulation in heterokont algae. Photochemistry and Photobiology 46, 1003–1008. Muñoz, V., Hernandez-Gonzalez, M.C., Buschmann, A.H., Graham, M.H. & Vásquez, J.A. 2004. Variability in per capita oogonia and sporophyte production from giant kelp gametophytes (Macrocystis pyrifera, Phaeophyceae). Revista Chilena de Historia Natural 77, 639–647. Neushul, M. 1959. Studies on the growth and reproduction of the giant kelp Macrocystis. Ph.D. dissertation, University of California, Los Angeles, California. Neushul, M. 1963. Studies on the giant kelp Macrocystis. II. Reproduction. American Journal of Botany 50, 354–359. Neushul, M. 1971. The biology of giant kelp beds (Macrocystis) in California: the species of Macrocystis. Nova Hedwigia 32, 211–222. Neushul, M. & Haxo, F.T. 1963. Studies on the giant kelp, Macrocystis. I. Growth of young plants. American Journal of Botany 50, 349–353.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Nicholson, N.L. 1978. Evolution within Macrocystis: Northern and Southern Hemisphere taxa. Proceedings of the International Symposium on Marine Biogeography and Evolution in the Southern Hemisphere 2, 433–441. Nisbet, R.M. & Bence, J.R. 1989. Alternative dynamic regimes for canopy-forming kelp: a variant on densityvague population regulation. American Naturalist 134, 377–408. North, W.J. 1971. The biology of giant kelp beds (Macrocystis) in California: introduction and background. Nova Hedwigia 32, 1–68. North, W.J. 1987. Biology of the Macrocystis resource in North America. In Case Studies of Seven Commercial Seaweed Resources, M.S. Doty et al. (eds). San Francisco, California: FAO. North, W.J. 1994. Review of Macrocystis biology. In Biology of Economic Algae, I. Akatsuka (ed.). Hague: Academic Publishing, 447–527. North, W.J. & Hubbs, C.L. (eds) 1968. Utilization of kelp-bed resources in southern California. State of California Resources Agency and Fish and Game, Sacramento, California. North, W.J., Jackson, G.A. & Manley S.L. 1986. Macrocystis and its environment: knowns and unknowns. Aquatic Botany 26, 9–26. North, W.J., James, D.E. & Jones, L.G. 1993. History of kelp beds (Macrocystis) in Orange and San Diego Counties, California. Hydrobiologia 260/261, 277–283. North, W.J. & Schaeffer, M.B. (eds) 1964. An investigation of the effects of discharged wastes on kelp. Resource Agency of California, State Water Quality Control Board, Publication 26. Norton, T.A. 1992. Dispersal by macroalgae. British Phycological Journal 27, 293–301. Nuñez, L. & Vásquez, J.A. 1987. Amplitud trófica y utilización de microhábitat de 4 especies de peces asociados a un bosque submareal de Lessonia trabeculata Villouta Santelices. Estudios Oceanológicos (Chile) 6, 78–85. Nyman, M.A., Brown, M.T., Neushul, M., Harger, B.W.W. & Keogh, J.A. 1993. Mass distribution in the fronds of Macrocystis pyrifera from New Zealand and California. Hydrobiologia 260/261, 57–65. Ojeda, F.P. & Santelices, B. 1984. Ecological dominance of Lessonia nigrescens (Phaeophyta) in central Chile. Marine Ecology Progress Series 19, 83–91. Orr, M., Zimmer, M., Jelinski, D.E. & Mews, M. 2005. Wrack deposition on different beach types: spatial and temporal variation in the pattern of subsidy. Ecology 86, 1496–1507. Paddack, M.J. & Estes, J.A. 2000. Kelp forest fish populations in marine reserves and adjacent exploited areas of central California. Ecological Applications 10, 855–870. Papenfuss, G.F. 1942. Studies of South African Phaeophyceae. I. Ecklonia maxima, Laminaria, pallida, Macrocystis pyrifera. American Journal of Botany 29, 15–24. Papenfuss, G.F. 1964. Catalogue and bibliography of Antarctic and sub-Antarctic benthic marine algae. In Biology of the Antarctic Seas, M.O. Lee (ed.). Washington, D.C.: American Geophysical Union, 1–70. Pearse, J.S. & Hines, A.H. 1976. Kelp forest ecology of the central California coast. University of California, Sea Grant College Program Annual Report 1975–76: Sea Grant Publication 57, 56–58. Pearse, J.S. & Hines, A.H. 1979. Expansion of a central California kelp forest following the mass mortality of sea urchins. Marine Biology 51, 83–91. Pearse, J.S. & Hines, A.H. 1987. Long-term population dynamics of sea urchins in a central California kelp forest: rare recruitment and rapid decline. Marine Ecology Progress Series 39, 275–283. Perissinotto, R. & McQuaid, C.D. 1992. Deep occurrence of the giant kelp Macrocystis laevis in the Southern Ocean. Marine Ecology Progress Series 81, 89–95. Pfister, C.A. 1992. Costs of reproduction in an intertidal kelp: patterns of allocation and life history consequences. Ecology 73, 1586–1596. Powell, H.T. 1981. The ecology of Macrocystis and other kelps around the Falkland Islands (South Atlantic). Proceedings of the International Seaweed Symposium 8, A48 only. Raimondi, P.T., Reed, D.C., Gaylord, B. & Washburn, L. 2004. Effects of self-fertilization in the giant kelp, Macrocystis pyrifera. Ecology 85, 3267–3276. Reed, D.C. 1987. Factors affecting sporophyll production in the giant kelp Macrocystis pyrifera. Journal of Experimental Marine Biology and Ecology 113, 60–69. Reed, D.C. 1990. The effects of variable settlement and early recruitment on patterns of kelp recruitment. Ecology 71, 776–787.

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GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS Reed, D.C., Amsler, C.D. & Ebeling, A.W. 1992. Dispersal in kelps: factors affecting spore swimming and competency. Ecology 73, 1577–1585. Reed, D.C., Anderson, T.W., Ebeling, A.W. & Anghera, M. 1997. The role of reproductive synchrony in the colonization potential of kelp. Ecology 78, 2443–2457. Reed, D.C., Brzezinski, M.A., Coury, D.A., Graham, W.M. & Petty, R.L. 1999. Neutral lipids in macroalgal spores and their role in swimming. Marine Biology 133, 737–744. Reed, D.C., Ebeling, A.W., Anderson, T.W. & Anghera, M. 1996. Differential reproductive responses to fluctuating resources in two seaweeds with different reproductive strategies. Ecology 77, 300–316. Reed, D.C. & Foster, M.S. 1984. The effects of canopy shading on algal recruitment and growth of a giant kelp (Macrocystis pyrifera) forest. Ecology 65, 937–948. Reed, D.C., Kinlan, B.P., Raimondi, P.T., Washburn, L., Gaylord, B. & Drake, P.T. 2006. A metapopulation perspective on patch dynamics and connectivity of giant kelp. In Marine Metapopulations, J.P. Kritzer & P.F. Sale (eds). San Diego, California: Academic Press, 353–386. Reed, D.C., Laur, D.R. & Ebeling, A.W. 1988. Variation in algal dispersal and recruitment: the importance of episodic events. Ecological Monographs 58, 321–335. Reed, D.C. & Lewis, R.J. 1994. Effects of an oil and gas-production effluent on the colonization potential of giant kelp (Macrocystis pyrifera) zoospores. Marine Biology 119, 277–283. Reed, D.C., Neushul, M. & Ebeling, A.W. 1991. Role of settlement density on gametophyte growth and reproduction in the kelps Pterygophora californica and Macrocystis pyrifera (Phaeophyceae). Journal of Phycology 27, 361–366. Reed, D.C., Schroeter, S.C. & Raimondi, P.T. 2004. Spore supply and habitat availability as sources of recruitment limitation in the giant kelp Macrocystis pyrifera. Journal of Phycology 40, 275–284. Rigg, G.B. 1913. The distribution of Macrocystis pyrifera along the American shore of the Strait of Juan de Fuca. Torreya 13, 158–159. Rodriguez, S.R. 2003. Consumption of drift kelp by intertidal populations of the sea urchin Tetrapygus niger on the central Chilean coast: possible consequences at different ecological levels. Marine Ecology Progress Series 251, 141–151. Rosenthal, R.J., Clarke, W.D. & Dayton, P.K. 1974. Ecology and natural history of a stand of giant kelp, Macrocystis pyrifera, off Del Mar, California. Fishery Bulletin 72, 670–684. Rosenthal, Y. & Broccoli, A.J. 2004. In search of paleo-ENSO. Science 304, 219–221. Roughgarden, J., Gaines, S. & Possingham, H. 1988. Recruitment dynamics in complex life cycles. Science 241, 1460–1466. Sala, E. & Graham, M.H. 2002. Community-wide distribution of predator-prey interaction strength in kelp forests. Proceedings of the National Academy of Sciences of the United States of America 99, 3678–3683. Salinas, N. 2000. Macrocystis integrifolia (Laminariales: Phaeophyta) en el norte de Chile: distribución espacio-temporal y fauna asociada. M.S. thesis, Universidad Católica del Norte, Coquimbo, Chile. Santelices, B. 1990. Patterns of reproduction, dispersal and recruitment in seaweeds. Oceanography and Marine Biology: An Annual Review 28, 177–276. Santelices, B., Hoffman, A.J., Aedo, D., Bobadilla, M. & Otaiza, R. 1995. A bank of microscopic forms on disturbed boulders and stones in tide pools. Marine Ecology Progress Series 129, 215–228. Santelices, B. & Ojeda, F.P. 1984a. Effects of canopy removal on the understory algal community structure of coastal forests of Macrocystis pyrifera from southern South America. Marine Ecology Progress Series 14, 165–173. Santelices, B. & Ojeda, F.P. 1984b. Population dynamics of coastal forests of Macrocystis pyrifera in Puerto Toro, Isla Navarino, southern Chile. Marine Ecology Progress Series 14, 175–183. Saunders, G.W. & Druehl, L.D. 1992. Nucleotide sequences of the small-subunit ribosomal RNA genes from selected Laminariales (Phaeophyta): implications for kelp evolution. Journal of Phycology 28, 544–549. Saunders, G.W. & Druehl, L.D. 1993. Revision of the kelp family Alariaceae and the taxonomic affinities of Lessoniopsis Reinke (Laminariales, Phaeophyta). Hydrobiologia 260/261, 689–697. Sauvageau, C. 1915. Sur la sexualité heterogamique d’une Laminaire (Saccorhiza bulbosa). Comptes Rendus de l’Académie des Sciences Paris 161, 796–799.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Scagel, R.F. 1947. An investigation on marine plants near Hardy Bay, B.C. Provincial Department of Fisheries Report 1, Victoria, British Columbia, Canada. Schiel, D.R., Andrew, N.L. & Foster, M.S. 1995. The structure of subtidal algal and invertebrate assemblages at the Chatham Islands, New Zealand. Marine Biology 123, 355–367. Schiel, D.R. & Foster, M.S. 1986. The structure of subtidal algal stands in temperate waters. Oceanography and Marine Biology: An Annual Review 24, 265–307. Schiel, D.R. & Foster, M.S. 2006. The population biology of large brown algae: ecological consequences of multiphase life histories in dynamic coastal environments. Annual Review of Ecology Evolution and Systematics 37, 343–372. Schiel, D.R., Steinbeck, J.R. and Foster, M.S. 2004. Ten years of induced ocean warming causes comprehensive changes in marine benthic communities. Ecology 85, 1833–1839. Schimmelmann, A. & Tegner, M.J. 1991. Historical oceanographic events reflected in carbon13 to carbon12 ratio of total organic carbon in laminated Santa Barbara [California, U.S.A.] Basin sediment. Global Biogeochemical Cycles 5, 173–188. Schmitz, K. & Lobban, C.S. 1976. A survey of translocation in Laminariales (Phaeophyta). Marine Biology 36, 207–216. Schroeter, S.C., Dean, T.A., Thies, K. & Dixon, J.D. 1995. Effects of shading by adults on the growth of blade-stage Macrocystis pyrifera (Phaeophyta) during and after the 1982–1984 El Niño. Journal of Phycology 31, 697–702. Setchell, W.A. 1932. Macrocystis and its holdfasts. University of California Publications in Botany 16, 445–492. Setchell, W.A. & Gardner, N.L. 1925. The marine algae of the Pacific Coast of North America. III. Melanophyceae. University of California Publications in Botany 8, 383–898. Seymour, R.J., Tegner, M.J., Dayton, P.K. & Parnell, P.E. 1989. Storm wave induced mortality of giant kelp Macrocystis pyrifera in southern California. Estuarine Coastal and Shelf Science 28, 277–292. Shanks, A.L, Largier, J.L., Brink, L., Brubaker, J. & Hooff, R. 2000. Demonstration of the onshore transport of larval invertebrates by the shoreward movement of an upwelling front. Limnology and Oceanography 45, 230–236. Skottsberg, C. 1941. Communities of marine algae in subantarctic and Antarctic waters. Kungliga Svenska Vetenskapsakademien Handlingar 19, 1–95. Smith, S.D.A. 2002. Kelp rafts in the Southern Ocean. Global Ecology and Biogeography 11, 67–69. Soto, R. 1985. Efectos del fenómeno El Niño 1982–83 en ecosistemas de la I Región. Investigación Pesquera (Chile) 32, 199–206. Spalding, H., Foster, M.S. & Heine, J.N. 2003. Composition, distribution, and abundance of deep-water (>30 m) macroalgae in central California. Journal of Phycology 39, 273–284. Stebbins, T.D. 1986. Density, distribution, and feeding of the marine snail Norrisia norrisi (Mollusca: Gastropoda) on the kelp Macrocystis pyrifera (Phaeophyta: Laminariales). Bulletin of the Southern California Academy of Sciences 85, 69–73. Stegenga, H., Bolton, J.J. & Anderson, R.J. 1997. Seaweeds of the South African west coast. Contributions from the Bolus Herbarium, Number 18, 1–655. Steneck, R.S., Graham, M.H., Bourque, B.J., Corbett, D., Erlandson, J.M., Estes, J. & Tegner, M.J. 2002. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environmental Conservation 29, 436–459. Stephens, J.S., Jr., Larson, R.J. & Pondella, D.J., Jr. 2006. Rocky reefs and kelp beds. In The Ecology of Marine Fishes: California and Adjacent Waters, L.G. Allen et al. (eds). Berkeley, California: University of California Press. Stephens, J.S., Jr., Morris, P.M., Zerba, K. & Love, M. 1984. Factors affecting fish diversity on a temperature reef: the fish assemblage of Palos Verdes Point [California, U.S.A.], 1974–1981. Environmental Biology of Fishes 11, 259–275. Swanson, A.K. & Druehl, L.D. 2000. Differential meiospore size and tolerance of ultraviolet light stress within and among kelp species along a depth gradient. Marine Biology 136, 657–664. Tegner, M.J. & Dayton, P.K. 1987. El Niño effects on southern California kelp forest communities. Advances in Ecological Research 17, 243–279.

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GLOBAL ECOLOGY OF THE GIANT KELP MACROCYSTIS: FROM ECOTYPES TO ECOSYSTEMS Tegner, M.J. & Dayton, P.K. 1991. Sea urchins, El Niños, and the long-term stability of southern California kelp forest communities. Marine Ecology Progress Series 77, 49–63. Tegner, M.J., Dayton, P.K., Edwards, P.B. & Riser, K.L. 1995a. Sea urchin cavitation of giant kelp (Macrocystis pyrifera) holdfasts and its effects on kelp mortality. Journal of Experimental Marine Biology and Ecology 191, 82–99. Tegner, M.J., Dayton, P.K., Edwards, P.B. & Riser, K.L. 1996. Is there evidence for long-term climatic change in southern California kelp forests? CalCofi Reports 37, 111–126. Tegner, M.J., Dayton, P.K., Edwards, P.B. & Riser, K.L. 1997. Large-scale, low-frequency oceanographic effects on kelp forest succession: a tale of two cohorts. Marine Ecology Progress Series 146, 117–134. Tegner, M.J., Dayton, P.K., Edwards, P.B., Riser, K.L., Chadwick, D.B., Dean, T.A. & Deysher, L.E. 1995b. Effects of a large sewage spill on a kelp forest community: catastrophe or disturbance? Marine Environmental Research 40, 181–224. Tegner, M.J. & Levin, L.A. 1982. Do sea urchins and abalones compete in California kelp forest communities? In International Echinoderms Conference, A.A. Balkema (ed.). Rotterdam: Tampa Bay, 265–271. Thiel, M. & Gutow, L. 2005a. The ecology of rafting in the marine environment. I: The floating substrata. Oceanography and Marine Biology: An Annual Review 42, 181–264. Thiel, M. & Gutow, L. 2005b. The ecology of rafting in the marine environment. II: The rafting organisms and community. Oceanography and Marine Biology: An Annual Review 43, 279–418. Thiel, M. & Vásquez, J.A. 2000. Are kelp holdfasts islands on the ocean floor? Indication for temporarily closed aggregations of peracarid crustaceans. Hydrobiologia 440, 45–54. Towle, D.W. & Pearse, J.S. 1973. Production of the giant kelp, Macrocystis, estimated by in situ incorporation of 14C in polyethylene bags. Limnology and Oceanography 18, 155–159. Tutschulte, T.C. & Connell, J.H. 1988. Feeding behavior and algal food of three species of abalones (Haliotis) in southern California. Marine Ecology Progress Series 49, 57–64. Utter, B.D. & Denny, M.W. 1996. Wave-induced forces on the giant kelp Macrocystis pyrifera (Agardh): field test of a computational model. Journal of Experimental Biology 199, 2645–2654. van Tüssenbroek, B.I. 1989a. Smooth-bladed Macrocystis (Laminariales, Phaeophyta) from the Falkland Islands. Phycologia 28, 520–523. van Tüssenbroek, B.I. 1989b. Observations on branched Macrocystis pyrifera (L.) C. Agardh (Laminariales, Phaeophyta) in the Falkland Islands. Phycologia 28, 169–180. van Tüssenbroek, B.I. 1989c. The life span and survival of fronds of Macrocystis pyrifera (Laminariales, Phaeophyta) in the Falkland Islands. British Phycology Journal 24, 137–141. van Tüssenbroek, B.I. 1989d. Seasonal growth and composition of fronds of Macrocystis pyrifera in the Falkland Islands. Marine Biology 100, 419–430. van Tüssenbroek, B.I. 1989e. Morphological variations of Macrocystis pyrifera in the Falkland Islands in relation to environment and season. Marine Biology 102, 545–556. van Tüssenbroek, B.I. 1993. Plant and frond dynamics of the giant kelp, Macrocystis pyrifera, forming a fringing zone in the Falkland Islands. European Journal of Phycology 28, 161–165. Vásquez, J.A. 1993. Effects on the animal community of dislodgement of holdfasts of Macrocystis pyrifera. Pacific Science 47, 180–184. Vásquez, J.A. & Buschmann, A.H. 1997. Herbivore-kelp interactions in Chilean subtidal communities: a review. Revista Chilena de Historia Natural 70, 41–52. Vásquez, J.A., Camus, P.A. & Ojeda, F.P. 1998. Diversidad, estructura y funcionamiento de ecosistemas costeros rocosos del norte de Chile. Revista Chilena de Historia Natural 71, 479–499. Vásquez, J.A., Castilla, J.C. & Santelices, B. 1984. Distributional patterns and diets of four species of sea urchins in giant kelp forest (Macrocystis pyrifera) of Puerto Toro, Navarino Island, Chile. Marine Ecology Progress Series 19, 55–63. Vásquez, J.A, Vega, J.M.A. & Buschmann, A.H. 2006. Long term studies on El Niño-La Niña in northern Chile: effects on the structure and organization of subtidal kelp assemblages. Journal of Applied Phycology 18, 505–519. Vásquez, J.A., Véliz, D. & Pardo, L.M. 2001. Biodiversidad bajo las grandes algas. In Sustentabilidad de la Biosiversidad: Un problema actual, bases científico-técnicas, teorizaciones y perspectivas, K. Alveal & T. Antezana (eds). Concepción, Chile: Universidad de Concepción, 293–308.

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MICHAEL H. GRAHAM, JULIO A. VÁSQUEZ & ALEJANDRO H. BUSCHMANN Vega, J.M.A., Vásquez, J.A. & Buschmann, A.H. 2005. Population biology of the subtidal kelps Macrocystis integrifolia and Lessonia trabeculata (Laminariales, Phaeophyceae) in an upwelling ecosystem of northern Chile: interannual variability and El Niño 1997–1998. Revista Chilena de Historia Natural 78, 33–50. Vetter, E.W. 1994. Hotspots of benthic production. Nature 372, 47–47. Villegas, M.J. 2002. Utilización de hábitat por parte de Lontra felina (Molina, 1782) (Carnívora, Mustelidae) en Isla Choros (Cuarta Región de Chile) en relación con la abundancia y distribución de presas. M.S. thesis, Universidad Católica del Norte, Coquimbo, Chile. Viviani, C.A. 1979. Ecogeografía del litoral Chileno. Studies on Neotropical Fauna and Environment 14, 65–123. Watanabe, J.M. 1984a. Food preference, food quality and diets of three herbivorous gastropods (Trochidae: Tegula) in a temperate kelp forest habitat. Oecologia 62, 47–52. Watanabe, J.M. 1984b. The influence of recruitment, competition, and benthic predation on spatial distributions of three species of kelp forest gastropods (Trochidae: Tegula). Ecology 65, 920–936. Watanabe, J.M. & Harrold, C. 1991. Destructive grazing by sea urchins Strongylocentrotus spp. in a central California kelp forest: potential roles of recruitment, depth, and predation. Marine Ecology Progress Series 71, 125–141. Westermeier, R. & Möller, P. 1990. Population dynamics of Macrocystis pyrifera (L.) C. Agardh in the rocky intertidal of southern Chile. Botanica Marina 33, 363–367. Wheeler, P.A. & North, W.J. 1981. Nitrogen supply, tissue composition and frond growth rates for Macrocystis pyrifera off the coast of southern California. Marine Biology 64, 59–69. Wheeler, W.N. & Druehl, L.D. 1986. Seasonal growth and productivity of Macrocystis integrifolia in British Columbia, Canada. Marine Biology 90, 181–186. Wing, B.L. & Clendenning, K.A. 1971. The biology of giant kelp beds (Macrocystis) in California: kelp surfaces and associated invertebrates. Nova Hedwigia 32, 319–341. Wing, S.R., Botsford, L.W., Ralston, S.V. & Largier, J.L. 1998. Meroplanktonic distribution and circulation in a coastal retention zone of the northern California upwelling system. Limnology and Oceanography 43, 1710–1721. Womersley, H.B.S. 1954. The species of Macrocystis with special reference to those on southern Australian coasts. University of California Publications in Botany 27, 109–132. Womersley, H.B.S. 1987. The Marine Benthic Flora of Southeastern Australia. II. Phaeophyta. Adelaide: South Australian Government Printing Division. Yoon, H.S., Lee, J.Y., Boo, S.M. & Bhattacharya, D. 2001. Phylogeny of Alariaceae, Laminariaceae, and Lessoniaceae (Phaeophyceae) based on plastid-encoded RuBisCo spacer and nuclear-encoded ITS sequence comparisons. Molecular Phylogenetics and Evolution 21, 231–243. Zimmerman, R.C. & Kremer, J.N. 1986. In situ growth and chemical composition of the giant kelp, Macrocystis pyrifera: response to temporal changes in ambient nutrient availability. Marine Ecology Progress Series 27, 277–285. Zimmerman, R.C. & Robertson, D.L. 1985. Effects of El Niño on local hydrography and growth of the giant kelp, Macrocystis pyrifera, at Santa Catalina Island, California. Limnology and Oceanography 30, 1298–1302. Zobell, C.E. 1971. The biology of giant kelp beds (Macrocystis) in California: drift seaweeds on San Diego County beaches. Nova Hedwigia 32, 269–315.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 89-138 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

HABITAT COUPLING BY MID-LATITUDE, SUBTIDAL, MARINE MYSIDS: IMPORT-SUBSIDISED OMNIVORES PETER A. JUMARS School of Marine Sciences & Darling Marine Center, University of Maine, 193 Clark’s Cove Road, Walpole, Maine 04573, U.S. E-mail: [email protected] Abstract Mysids often dominate mobile benthic epifaunas of mid-latitude continental shelves. Macquart-Moulin & Ribera Maycas (1995) reported that the six most abundant species on western and southern European shelves are all strong diel migrators. Published daytime epibenthic sledge (sled) data from the surf zone to the shelf edge matched with published behavioural data on the most abundant species were used to test, confirm and extend that relationship to other coastal regions and to identify an association of abundant migrators with species that are important in fish diets. They also reveal another pattern: a correspondence between abundant surf-zone species and species that dominate estuarine faunas seasonally. Population concentrations at estuary mouths, sills of fjords and in the surf zone suggest a lifestyle dependent upon horizontal fluxes. Marine mysids that migrate between habitats are chronically undersampled in the field, however, and are underrepresented in food-web models. Unfortunately, no single methodology samples both pelagic and benthic individuals well and nearly all shelf measurements so far reported must be considered underestimates of local abundance. Mysids are major dietary components for many benthic and pelagic fishes, mammals, cephalopods and decapods, often for key life stages, and often because mysid migrations result in encounters with predators. Mysids can be extraordinarily omnivorous, with demonstrated capabilities to digest cellulose and diets spanning macrophyte detritus, more labile detritus, large microalgae, and smaller animals and heterotrophic protists. They can be sufficiently abundant and active to play roles in sediment transport. Contributing factors to their underappreciation have been the lack of fidelity of mysids to single habitats, coupled with higher fidelity of investigators to the study of single habitats. Sampling with classical methods has been problematic because of effective evasion by mysids, compounded by extreme patchiness associated with mysid schooling. Their frequent absence from coastal and even estuarine food-web models has not been more conspicuous because the combination of their migration and omnivory spreads their feeding impacts and because they are subsidised by horizontally imported plankton and seston and are themselves horizontally exported in the form of predator gut contents and biomass. They clearly link pelagic and benthic food webs in two important and ecosystem-stabilising ways, however, by feeding in both habitats and by succumbing in both habitats to both cruising and sitand-wait predators. Consideration of resource and predation gradients and limited data implicate horizontal, diel migrations as well, extending these linkages, especially in the onshore–offshore direction. Somewhat paradoxically, the same features that have made them difficult to study by classical means, in particular schooling, diet breadth, ontogenetic change in diet and migration between habitats, suit migrating mysids well to new, individual- or agent-based modelling approaches. Moreover, benthic observatories deploying acoustic technologies with spatial and temporal resolution sufficient to resolve individual migratory behaviours promise powerful tests of such models.

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Introduction For nearly two centuries, observations of zooplankton vertical migrations have aroused curiosity and elicited alternative and compound explanations (Pearre 2003). Selective forces evoking and altering these migrations include vertical gradients in resources, in predation risks and in environmental drivers of physiological rates (i.e., temperature and salinity). Such gradients in risks and benefits can be even steeper within the bottom boundary layer, including its upper layers of sediment (Boudreau & Jørgensen 2001), and laterally across fronts, than they are in the overlying water column. The focus of this review is on migrations between benthic and pelagic habitats by a subset of the animal community that may also move horizontally, both across and along isobaths, connecting more than two habitats. For that reason, in this review the more general term ‘habitat coupling’ is used rather than benthic-pelagic coupling (Schindler & Scheuerell 2002). Widespread use of echo sounders after the rapid advance of underwater acoustics in World War II brought attention to the ubiquity of vertical migrations and specifically to the oceanic deep scattering layer. Echo-sounder frequencies near 12 kHz that were useful for locating the bottom proved sensitive to air bladders of fishes and siphonophores. Based partly on such observations, Vinogradov (1962) developed a conceptual scheme subsequently dubbed ‘Vinogradov’s ladder’: although diel migrations from deeper than 600 m are rare, many deeper-dwelling species migrate part of the way to the surface, so that predatory interactions provide a chain or ladder for vertical redistribution of energy and materials that daily extends to depths in excess of 1000 m in the open ocean. The proliferation of acoustic Doppler current profilers (ADCPs, operating typically at 300–600 kHz; Brierly et al. 1998) and of bioacoustic instruments designed to detect zooplankton at acoustic frequencies typically ranging from 250 kHz to a few megahertz (e.g., Gal et al. 1999) is revealing the ubiquity and intensity in shallow waters of an inherently more complicated phenomenon that has been dubbed the shallow scattering layer (Kringel et al. 2003). In waters too shallow to hold a deep scattering layer, animals from many taxa have evolved foraging patterns and morphologies compatible with living in or on the bottom, usually during the day, and rising into the water column, usually at night. Although there is no need for a vertical ladder where the water is a single rung deep, early data already show the outlines of a horizontal or oblique, onshore–offshore ladder in the coastal zone. Though still quite limited in number, deliberate, multifrequency acoustic studies of shallowwater migrators suggest that water-column abundances (depth-integrated biomasses) of these migrants may frequently exceed those of the holoplankton. This suggestion led to a systematic examination of corroborative evidence for the ecological importance of these migrants. For pragmatic reasons, in this review analysis is limited to a single large taxon, the Mysidacea (commonly known as opossum shrimp), that appears in shallow, mid-latitude seas and often dominates such migrations. Similarly, the focus is limited to subtidal, coastal habitats of mid-latitudes and to species that occur outside estuaries during at least some seasons of the year. Work in other marine, estuarine and freshwater environments is cited selectively when comparable information was not at hand for mid-latitude marine systems. Literature on freshwater species or (oligohaline and mesohaline) estuarine endemics has not been reviewed for the simple reason that the importance of vertically migrating mysids in these systems is widely appreciated (e.g., Rudstam et al. 1989, Kotta & Kotta 2001a, Viitasalo et al. 2001). To avoid inflation of inferred importance by selective extraction of conspicuous examples of migration and to give some insight into migrations of individual species, a two-step process was used. The first step was to identify a few regional studies of mysids notable for the spatial or temporal extent (or both) of their epibenthic sledge sampling. Thus, this review is also focused away from hard bottoms, caves and vegetation, all habitats well exploited by mysids but ones requiring different census methods. The second step was to review characteristics of migrations in the mysid species that dominated samples in these studies. In both steps emphasis 90

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has been on studies published after the major review by Mauchline (1980), citing prior literature primarily when a particular citation was omitted by Mauchline (1980) or when focusing on information that was not summarised by Mauchline (1980). Additional information was then reviewed, substantiating the importance of mysids to coastal and estuarine ecosystems. Confluence of multiple lines of evidence for the importance of migrating mysids to both benthic and pelagic systems proved compelling. They often dominate diets of both pelagic and benthic fishes in coastal waters and estuaries, highlighting the multiple risks inherent in the migratory lifestyle. Mysids also appear to be important to the population abundances of some of their prey species, but for the most part mysids are remarkable dietary generalists when all life stages and habitat phases are included, and so are underappreciated stabilisers of the communities that they inhabit and transit (McCann & Hastings 1997). Recently, their migrations have been implicated as an important factor in sediment dynamics (Roast et al. 2004). Major habitat changes due to climate, introduced species or human intervention have often produced major changes in mysid populations that resonate through the food web. Despite underlying differences between mysid-containing food webs in fresh and marine waters, analogy with lake systems takes advantage of their closed boundaries to assess effects of mysid introduction, which are detected both up and down the food web. Another indicator of potential importance is the latitudinal range and habitat diversity over which high abundances of even single species are found; Neomysis americana (S.I. Smith, 1873) is abundant from Nova Scotia to Florida and from shelf habitats 100 m deep to salt marshes; in the last century it was introduced to the Atlantic coast of South America, where it has become an important food-web component. The importance of N. americana as food for both benthic and pelagic fishes over a broad geographic range was recognised in its original species description (Smith 1873). The question naturally arises as to why, despite engaging, comprehensive treatments of their capabilities and roles (e.g., Mauchline 1980) and intense and sustained interest among the specialists cited in this review, mysids do not figure more prominently in fisheries and oceanographic models and texts. The most direct comparison is with the largely holoplanktonic euphausiids, a group of similar body size and also large dietary breadth (but less expansion into detritivory) as a group. The summary by Mauchline (1980) of both groups followed a parallel structure for each. Tellingly, his chapter on “Mysids in the marine economy” is half as long as its counterpart for euphausiids, and only a small portion is devoted to shallow-water species that migrate. Biological oceanographic textbooks in general give an even more lopsided treatment. Reasons for this shortage of information are manifold. Shallow-water migrations are fundamentally more complicated than better-studied migrations in the open ocean or in coastal holoplankton because component populations in benthic and pelagic habitats cannot be studied by the same means and often are not sampled by a single investigator. Their natural reference frame shifts back and forth between an Eulerian fixed reference frame and a Lagrangian, water-mass-following reference frame with the change between benthic and pelagic habitats, respectively, seriously complicating description and analysis. Even when they stay within the pelagic or benthic habitat, mysids are notoriously poorly captured because of their effective evasive behaviours. More subtly, their lack of freely released eggs or larvae leaves no evidence of large mysid populations in lowflow or small-aperture capture devices, such as continuous plankton recorders, that efficiently recover those non- or weakly swimming life stages in euphausiids, decapods and fishes. Extreme patchiness of mysid populations, reinforced by schooling behaviours, make precise abundance estimates even more difficult to achieve than they are for non-schooling animals. The migratory lifestyle gives mysids access to horizontally imported pelagic food sources and leads through encounter to their local export as gut contents and assimilated biomass of fishes and decapods, effectively camouflaging their importance to local food webs and energy budgets; a large net import or export would be far more conspicuous. 91

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Migrations between the sea bed and the water column also generate semantic difficulties. Mees & Jones (1997) took a habitat point of view and defined the hyperbenthos as those animals living in the water layer immediately above the bottom. In this sense, migratory mysids spend part of their time as hyperbenthos. The term fails, however, to capture the range of habitats occupied by migratory mysids because in clear, shallow waters without bottom cover in the form of crevices or vegetation, mysids often bury themselves during daylight, disappearing from the hyperbenthos. Mysid migrations also exhibit considerable plasticity, varying in timing, intensity and vertical extent seasonally, night to night and with tides (e.g., Abello et al. 2005, Taylor et al. 2005). To pursue these migrations further from a habitat perspective thus would require more elaborate terminology than even the refinements proposed recently by Dauvin & Vallet (2006). Instead, in the present review an alternative approach is adopted that may lead more readily to quantitative models and predictions by taking the perspective of an individual migrating through habitats. It is noted that, because mysids swim actively when pelagic and may do so at times during their benthic phases, this perspective is not truly Lagrangian (in the normal physical oceanographic sense of tracking a parcel of water), although it follows that same spirit of following the entity of interest. Seeking the simplest terminology that has this behavioural focus, the term ‘emergence’ is used herein to describe the overall vertical migration behaviour between habitats and more specifically the upward component of the migration (leaving the distinction to context). This usage follows precedent for those who have focused on the migratory behaviour rather than on community structure in the hyperbenthic habitat (Saigusa 2001). When the shift is from pelagic to benthic, the term ‘re-entry’ is used in the current review, reflecting the author’s benthic background. Two recent developments promise accelerated understanding of the role of migratory mysids. One development is the continued evolution of bioacoustic instrumentation and its deployment methods, particularly in the context of high-power, high-bandwidth ocean observatories. The second advance is the rapid development of flexible, individual-based models (IBMs). Many of the same features that have made mysids difficult to study make them excellent subjects for applications and tests of IBMs (i.e., their schooling behaviours, their occupation of multiple habitats, their use of multiple food resources and their shifts in behaviour during development) (Grimm & Railsback 2005, Grimm et al. 2005). The combination of new technologies and models promises accelerated advances in understanding of the extents, causes and consequences of mysid migrations through tests of predictions about habitat usage.

Migratory capabilities, schooling and their consequences Credibility of evidence for migrations rests in some measure on the sensitivities of sensory mechanisms to guide them and on swimming capabilities. Mysids as a group are well endowed in both of these categories (Mauchline 1980). The earliest (Carboniferous to Jurassic) mysids appear to have been holopelagic, and the transition to emergence to have been marked by the evolution of statocysts with mineralised statoliths (Ariani et al. 1993), likely associated with the fitness enhancement of directional guidance in emergence and re-entry. Marine species generally (including Neomysis americana) secrete fluorite (CaF2), whereas low-salinity estuarine and freshwater species generally secrete vaterite (a CaCO3 polymorph of calcite and aragonite), although particular species provide exceptions to each generalisation that reflect their lineages (Ariani et al. 1993). Mysids have major impact on the marine fluorine cycle (Wittman & Ariani 1996), and their statoliths may be abundant enough in some fossil marine strata to warrant extraction (Voicu 1981). Likewise, calcite (transformed vaterite) from statocysts represents a substantial fraction of some Miocene Paratethys deposits in the Ponto-Caspian region, where use of calcium carbonate minerals appears to have first evolved in mysids (Ariani et al. 1993). Emergent mysids thus appear to have been very abundant in coastal ecosystems for a very long time, and they are still abundant enough to leave 92

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detectable statoliths in modern shelf sediments (Enbysk & Linger 1966). In addition to a pair of statocysts for vertical orientation, a less well-identified mechanism for sensing depth is present (Rice 1961, 1964) that is sensitive to pressure changes equivalent to less than 1 m of water and that probably enables observed tidal rhythms in activity cycles (Mauchline 1980, Saigusa 2001, Gibson 2003, Taylor et al. 2005). In terms of horizontal navigation, mysids have long been known to utilise polarised light (Bainbridge & Waterman 1957, 1958), and movements of their stalked eyes are co-ordinated with information from the statocysts (Neil 1975a,b,c). Contrary to opinion in many recent references, polarisation (specifically e-vector orientation) is a useful indicator of solar azimuth throughout continental shelf depths and through most of the day, with the highest information content near dusk and dawn because of high inclination of the e-vector with respect to the horizontal (Waterman 2005). Seasonal onshore–offshore migrations have been inferred from asynchronous seasonal changes in abundance across habitats (e.g., Bamber & Henderson 1994), and polarised light probably provides the directional cue, although it often is not clear to what extent the asynchrony in local abundance is due to migration versus seasonally changing, local differences in population growth and mortality (Mees et al. 1993). For reasons that also are not yet clear, a majority of onshore–offshore migrators show winter maxima offshore, extending in high abundance into shallower water and estuaries during some or much of the period from spring to fall (Mauchline 1980). Diel homing to the same location over smaller scales has been documented experimentally in reef mysids (Twining et al. 2000). Utilisation of estuarine circulations to help maintain horizontal position on intermediate scales has also been observed (i.e., either an interaction of horizontal and vertical bias or directed navigation) (e.g., Orsi 1986, Moffat & Jones 1993, Schlacher & Wooldridge 1994, Kimmerer et al. 1998a,b), although variation in such behaviours with local conditions from year to year can be considerable (Kimmerer 2002), as can differences among mysid species at the same estuarine location (Sutherland & Closs 2001). Retention-assisting, horizontal migrations also have been observed during slack tides (Köpcke & Kausch 1996). Many mysid species are documented to be strong swimmers. Sustained swimming at 10 body lengths s−1 is not unusual, with bursts in some species exceeding 20 body lengths s−1 (Mauchline 1980). At these sustained speeds, diel vertical, diagonal or horizontal excursions on the order of 1 km would be feasible, depending on local flow velocities, so diel vertical migrations to the shelf edge are well within mysid capabilities. Habitats with flow speeds in excess of sustainable swimming speeds appear to be avoided, however, and mysids shelter behind flow obstructions and in the most slowly moving water layer directly over the bottom (Roast et al. 1998, Lawrie et al. 1999). Perhaps the most important point to emphasise in this introduction is the reason to focus on both abundance and migration. A point forgotten all too easily is that ecological importance to individuals of another species is usually a function of interspecific encounter rates (Hurlbert 1971), themselves a product of areal or volumetric abundance times relative velocity (e.g., Jumars 1993). The combination of good sensory guiding mechanisms and strong swimming capabilities would tend toward ballistic encounter during organised migrations, an advantage in feeding but a disadvantage when being preyed upon (Visser & Kiørboe 2006). Encounters in mysids are often modulated by schooling behaviours. Mysids use visual and tactile senses to form and maintain both highly polarised schools and less polarised aggregations or swarms (Ritz 1994). Very large aggregations of varying local density and orientation are termed shoals (Clutter 1969). Typical mysid schools range from 1–10 m in linear dimensions and 1–15 m3 in volume (Ritz 1994). Near the bottom, school shapes often become planar, typically with more than one layer of mysids and sometimes differing in vertical structure by sex and life stage. Moving schools tend to be elongate, whereas stationary swarms (albeit containing milling individuals) are more circular (when near the sea bed) or spherical (Clutter 1969, Wittman 1977, Ohtsuka et al. 1995). Schooling is typical of animals out from the cover of vegetation and swimming off the 93

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bottom (i.e., in the pelagic phase), even when only a few centimetres from the bottom, but schools may maintain oriented, evenly spaced formation while on the bottom. Mysids on or near the bottom typically orient into the current (Mauchline 1980). Densities in swarms are often near 105 of individuals (ind.) m−3, with mean interindividual separation distances near 2 cm; for a single layer, that spacing yields about 2500 ind. m−2 (Mauchline 1980). The first emergence event of the night shows clear schooling and a constant ascent velocity dependent on depth and local light conditions, but later emergence does not appear to be as organised; schooling may not be maintained through the night (Kringel et al. 2003, Abello et al. 2005, Taylor et al. 2005). One function of schooling is to reduce average risk per individual (Ritz 1994) to individual predators, although schooling predators or large individual predators (e.g., whales) may be quite effective in the presence of mysid schooling. It is clear from gut contents of benthic and pelagic fishes that migrating mysids still incur fatal risk and that fitness loss must be counterbalanced by even greater gain from migrations if the migrations persist. Hence, the observations made by Macquart-Moulin & Ribera Maycas (1995) in an exhaustive sampling programme of the pelagic phase of mysids throughout the water column in the northwestern Mediterranean take on particular significance: they observed that the most abundant mysids found on the continental shelves of Europe are diel migrators between the sea bed and the pelagic environment. Based on the integration of a large number of studies with varying types of sampling gear over a long period, Macquart-Moulin & Ribera Maycas (1995) concluded that six species showed high benthic abundance on the shelf: Gastrosaccus sanctus (Van Beneden, 1861), G. spinifer (Goës, 1863), Anchialina agilis (G.O. Sars, 1877), Haplostylus lobatus (Nouvel, 1951), H. lobatus var. armata (Nouvel, 1951), and H. normani (G.O. Sars, 1877). They provided compelling new data from the region near Marseille of migration to the surface in all six of these taxa. Deprez et al. (2005) regard Gastrosaccus sanctus as a synonym of G. spinifer and Haplostylus normani as a synonym of H. lobatus. Macquart-Moulin & Ribera Maycas (1995) also found strong evidence of offshore migration or transport of Anchialina agilis and Haplostylus lobatus, both captured over bottoms 700–1000 m deep, where individuals are not known to occur on the bottom. They captured pelagic Anchialina agilis in bathyal waters during the day and collected a high percentage of dead animals, suggesting that occurrence in waters deeper than 500 m is an extension beyond suitable habitat.

Methods of data collection To identify recent published records of mysid abundance, three sources have been used in this review: the Food and Agriculture Organisation of the United Nations’ Aquatic Sciences and Fisheries Abstracts (ASFA), Thomson Scientific’s Web of Science and Google Scholar. The first two sources are limited primarily to citations later than those in the review of Mauchline (1980), but the third source is expanding rapidly into older literature. Into the search fields of the first two databases, ‘mysi*’ was entered and a country name that has a continental shelf, or in the case of the United States or Canada, a state or province name, respectively. For Google Scholar ‘mysid’ was used and the place name. For ASFA and the Web of Science, the ‘and’ is a Boolean operator. For Google Scholar, it was omitted (as Google in general ignores small, common words unless they are within explicit quotation marks). From the references returned, selected were those that documented mysid abundance either over an extensive period (a year or more) or a broad geographic area or both during daytime on the basis of epibenthic sledge samples. Many of these sledge studies used multiple, vertically arrayed nets (e.g., Zouhiri et al. 1998) to get information on near-bottom vertical distributions, biased to an unknown degree by species-specific escape responses. Such samples are referred to as ‘vertically resolved, epibenthic-sledge samples’. From the data provided, mysids have been ranked in terms of their abundances, selecting the one to five abundant and 94

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frequent species, using a smaller number when a natural break point in abundance occurred (a difference of an order of magnitude or more in absolute abundance), and using the largest number when a long study over a large area showed consistent dominance of one species in at least one location and season. In each case, the choices of taxa are explained. Species names in quotation marks were then used as search terms in the same three databases to determine the migratory behaviour of the most abundant species. In addition, species names were searched in the NeMys database (Deprez et al. 2004, 2005) using the inclusive list of species names (valid and invalid) for references on behaviour and as a further check for inclusivity of publications with extensive sampling of field abundance and publications on migratory behaviour. The NeMys database was also used as one source of taxonomic authority, indicated on first use of the species name in the body of this review, and for some information (especially for European species) about geographic and depth ranges. For brevity, depth ranges of the species are summarised only in tabular form (Table 1). For consistency, only benthic capture records were used. Where taxonomic ambiguities or disputes over synonymy might affect conclusions, all databases were searched under both names. Table 1 Mysid species identified as abundant in epibenthic sledge samples, along with their known depth ranges, diel migratory behaviours and the study that established their high abundance Species Mesopodopsis slabberi Schistomysis spiritus Schistomysis kervillei

Depth limits (m) (respective citations) 1–42 (Buhl-Jensen & Fosså 1991, Beyst et al. 2001) 1–116 (Buhl-Jensen & Fosså 1991, Beyst et al. 2001) 1–25 (Cornet et al. 1983, Beyst et al. 2001)

Anchialina agilis

2–493 (Bacescu 1941, Cartes & Sorbe 1995)

Gastrosaccus spinifer

1–260 (Lagardère & Nouvel 1980, San Vicente & Munilla 2000) 17–420 (Lagardère & Nouvel 1980, Dauvin et al. 2000) 10–150 (Lagardère & Nouvel 1980, Dauvin et al. 2000) 1–125 (Bacescu & Schiecke 1974, Cunha et al. 1997) 6–407 (Brattegard & Meland 1997) 5–512 (Elizalde et al. 1991, San Vicente & Munilla 2000)

Haplostylus lobatus Haplostylus normani Erythrops elegans

Schistomysis ornata Leptomysis gracilis

Diel migratory behaviour (citations) Very strong swimmer, extends vertical distribution at night (Apel 1992, Wang & Dauvin 1994) Moderately strong swimmer, extends vertical distribution at night (Apel 1992, Wang & Dauvin 1994) Weaker swimmer, extends vertical distribution at night (Apel 1992, Wang & Dauvin 1994) Strongest swimmer and migrator to limits of its benthic depth distribution; most of the population leaves the bottom every night (Macquart-Moulin & Ribera Maycas 1995) Strong swimmers and migrators (MacquartMoulin & Ribera Maycas 1995)

Source of information on abundance Beyst et al. 2001

Beyst et al. 2001

Beyst et al. 2001

Dauvin et al. 2000

Dauvin et al. 2000

Strong swimmers and migrators (MacquartMoulin & Ribera Maycas 1995)

Dauvin et al. 2000

Strong swimmers and migrators (MacquartMoulin & Ribera Maycas 1995)

Dauvin et al. 2000

May be a diel migrator (Vallet et al. 1995)

Zouhiri et al. 1998

Collected in nighttime surface samples in some seasons; may be a diel migrator (Sorbe 1991) Strong migrator (Mauchline 1980, Kaarvedt 1989)

Zouhiri et al. 1998 Cornet et al. 1983, Cunha et al. 1997 (continued on next page)

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Table 1 (continued) Mysid species identified as abundant in epibenthic sledge samples, along with their known depth ranges, diel migratory behaviours and the study that established their high abundance Species Mysideis parva

Neomysis americana

Americamysis bigelowi Erythrops erythrophthalma Metamysidopsis elongata Neomysis kadiakensis Xenacanthomysis pseudomacropsis Neomysis rayii Acanthomysis stelleri Archaeomysis kokuboi Archaeomysis japonica Iiella ohshimai Nipponomysis ornata

Depth limits (m) (respective citations) 120–519 (Bacescu & Schiecke 1974, Elizalde et al. 1991) 1–232 (Wigley & Burns 1971)

4–179 (Wigley & Burns 1971, Allen 1984) 16–450 (Petryashev 2002a) 1–14 (Clutter 1967) 1–210 (Petryashev 2005) 1–104 (Petryashev 2005) 1–79 (Petryashev 2005) 1–104 (Petryashev 2005) 0–2 (Petryashev 2005) 1–50 (Hanamura 1997) 1–5 (Takahashi & Kawaguchi 1995) 1–5 (Yamamoto & Tominaga 2005)

Diel migratory behaviour (citations)

Source of information on abundance

Non-migrator (Elizalde et al. 1991). No description found.

Cornet et al. 1983, Cunha et al. 1997

Strong diel, tidally modulated migrator, but perhaps not to the full extent of its depth range (Herman 1963, Brown et al. 2005, Taylor et al. 2005) Strong diel migrator (Williams 1972)

Wigley & Burns 1971

Migrates at least in some environments (Brunel 1979) Slight upward shift of population mode at night (Clutter 1969) Strong diel migrator (Kringel et al. 2003) Caught in mid-water trawls (Wing & Barr 1977) Caught in mid-water trawls (Wing & Barr 1977) Poorly known Strong diel migrators (Takahashi & Kawaguchi 1997) Strong diel migrators (Takahashi & Kawaguchi 1997) Strong diel migrators (Takahashi & Kawaguchi 1997) Undescribed?

Wigley & Burns 1971 Wigley & Burns 1971 Clutter 1967 Clutter 1967 Kim & Oliver 1989 Kim & Oliver 1989 Kim & Oliver 1989 Takahashi & Kawaguchi 1997 Takahashi & Kawaguchi 1997 Takahashi & Kawaguchi 1997 Hanamura & Matsuoka 2003, Yamamoto & Tominaga 2005

Given demonstrated mysid capabilities for social aggregation and movement, reported maximal local abundances per unit of volume of water are not very informative regarding typical regional abundances, and documentation of consistently high abundance over a long time or broad region is a better indicator of consistent importance. This review therefore focused on a subset of those references that provide abundance estimates from epibenthic sledge samples taken during the benthic phase (i.e., when individuals are most susceptible to capture by a sledge). Drawbacks are that these studies varied widely in the geometries of the net mouth openings used and that many of these papers reported only numbers per unit of volume filtered (as determined by flow meter). No attempt was made to express abundances per unit of volume or per unit of area when the original author did not do so. For ease of comparison, however, all areal or volumetric abundance estimates given per total area or volume of tow were converted to numbers per square or cubic metre.

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Regionally abundant mysids and their migration habits European shelves One of the most challenging environments to sample with respect to abundance and emergence behaviours is the shallow subtidal and in particular the surf zone. In 15 monthly samples with a bottom sledge hauled by hand from four sites in the Belgian surf zone, Beyst et al. (2001) found average animal densities to exceed 15 ind. m−2 and to vary in ash-free dry weight (AFDW) from 3 to >30 mg m−2. Three quarters of individuals overall were mysids, primarily of three dominant species (Mesopodopsis slabberi (Van Beneden, 1861), Schistomysis spiritus (Norman, 1860) and S. kervillei (G.O. Sars, 1885)), and mysids dominated AFDW in some seasons. As is typical of such estimates, sampling efficiency is unknown for this sledge with these species and is assumed to be 100% for purposes of the calculation, so true densities must be higher. The three-species group also dominates the Voor delta, where Gastrosaccus spinifer is also abundant (Mees et al. 1993). Patterns of diel migration in Mesopodopsis slabberi are not as well known as might be expected. The species was described from in situ observations (Wittman 1977) as active and colourless during the day, showing no visible substrata preferences and changing leadership within schools spontaneously. Wittman (1977) also noted that schools did not appear to return to the same location and that predator-evading swarms veered horizontally without changing depth unless the predator attacked from above, a behaviour that should aid in capture by an epibenthic sledge. Daytime schools swam up to 50 cm above the substratum. Although Wittman (1977) did not specifically name M. slabberi in that context, he implied that nocturnal expansion among the mysids he studied was the norm. Wang & Dauvin (1994) found M. slabberi in epibenthic sledge samples both night and day and concluded from its upward skewed distribution among vertically resolved samples that it is an active swimmer, consistent with the observations of Wittman (1977). Wang & Dauvin (1994) caught more individuals in nighttime sledge samples but remarked that it might have been because of increased capture efficiency (less evasion in the dark). Zouhiri et al. (1998) in another series of epibenthic sledge samples found crepuscular peaks in capture of M. slabberi, consistent with the idea of distribution broadening above the bottom at night (and perhaps net evasion in the light). An inference consistent with most observations and directly supported by paired benthic and pelagic samples in the Jade estuary is that M. slabberi is concentrated near the bottom during the day but spreads into the water column at night (Apel 1992). This spreading includes a horizontal component, into the intertidal zone of at least one estuary during the night (Colman & Segrove 1955). It is worth noting that whether a seaward expansion also occurs in surface waters is unknown. In a long-term study of the polyhaline zone of the very turbid Gironde estuary, however, M. slabberi was captured abundantly in surface waters during daylight (Castel 1993, David et al. 2005). In addition, in the region of South African surf-zone diatom blooms M. wooldridgei Wittman, 1992 (closely enough related that it was previously identified as M. slabberi) also migrated onshore at night to take advantage of sinking surf-zone diatoms carried offshore in rip currents (Webb & Wooldridge 1990) at the same time that another mysid species, Gastrosaccus psammodytes Tattersall, 1958, migrated offshore from its inner surf-zone, daytime habitat to take advantage of that same resource (Webb et al. 1988). Mesopodopsis slabberi appears to migrate offshore in winter but to include vertical migrations in its repertoire there at 20 m water depth (van der Baan & Holthuis 1971). Even in winter, however, this species is observed inside but near the mouths of some estuaries (Mees & Hamerlynck 1992), so the entire population does not migrate offshore seasonally, and both migration and site-dependent mortality need to be examined as components of the distributional shift. Seasonally, M. slabberi also enters tidal creeks of salt marshes at high tides in sufficient abundance to be important as a prey species there (Hampel et al. 2003a), but it 97

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is unclear to what extent active behaviour versus passive advection is responsible (Hampel et al. 2003b). Recent molecular genetic work shows some genetic differentiation among populations in the northeast Atlantic and Mediterranean and Black Seas (Remerie et al. 2006) and also shows what may be an important mysid trait allowing rapid adaptation (i.e., high intrapopulation genetic diversity). Schistomysis spiritus and S. kervillei show similar migration patterns to Mesopodopsis slabberi, including nocturnal vertical spreading (van der Baan & Holthuis 1971, Apel 1992, Wang & Dauvin 1994). Of these two congeners, nighttime expansion into very shallow water has been reported for Schistomysis spiritus (Colman & Segrove 1955). Wang & Dauvin (1994) documented near-bottom, daytime vertical distributions and near-bottom, nighttime spreading patterns in vertically resolved sledge samples that allowed them to rank swimming activity as Mesopodopsis slabberi > Schistomysis spiritus > S. kervillei, with Gastrosaccus spinifer in the same category as Schistomysis kervillei and none of these mysids in their lowest activity category. Mesopodopsis slabberi is the most widely distributed of the three species geographically, ranging from Iceland in the Atlantic to North Africa, widely through the Baltic and Mediterranean and into the Black Sea (Deprez et al. 2005). Both Schistomysis congeners have somewhat more restricted geographic distributions than Mesopodopsis slabberi, with Schistomysis spiritus ranging from the Baltic to northern France and S. kervillei ranging from the North Sea to the southern Atlantic coast of France (with a report from northwest Africa), but its habitat distribution is comparable, ranging from shallow estuarine to shelf depths (Deprez et al. 2005). Within the North Sea, S. spiritus, S. kervillei and Mesopodopsis slabberi peaked in abundance near shore (Dewicke et al. 2003). Late-summer abundances (all mysids combined) averaged near 30 m−3 and 30 mg AFDW m−3 in sledge samples from the nearshore zone. All three species, however, reached even higher densities in the polyhaline and mesohaline zones of estuaries (e.g., Castel 1993, Wang & Dauvin 1994, Delgado et al. 1997, Azeiteiro et al. 1999, Lock & Mees 1999, Dauvin et al. 2000, Mouny et al. 2000, Wittman 2001, Drake et al. 2002, Dewicke et al. 2003). In terms of winter distributions, all three species are known to occur inside estuaries (near the mouth of the Schelde; cf. Mees & Hamerlynck 1992), in shallow coastal waters of warm regions (e.g., Lock & Mees 1999) and also offshore (van der Baan & Holthuis 1971). In deeper waters of the English Channel and the European shelf, other mysid species become dominant. Dauvin et al. (2000) presented a summary of 432 epibenthic sledge samples taken at 15 stations in the English Channel, including 3 stations within the Seine estuary, and covering the years 1988–1996. Those three stations have been excluded from the analysis in this review, except to note that they support the habitat pattern observed elsewhere for M. slabberi (i.e., shallow-water marine plus polyhaline-mesohaline estuarine water). The indisputable dominant in terms of abundance and frequency of occurrence outside the Seine estuary is Anchialina agilis, with mean abundances >1 ind. m−3 at both of the deepest stations, a coarse sand off Roscoff and a medium sand off Plymouth, both at 75 m depth. The species occurred at all the stations outside the Seine. Four other species occurred at over one half of the non-estuarine stations and reached mean abundances of at least 1 ind. m−3 at a minimum of one station: Gastrosaccus spinifer, Haplostylus lobatus, H. normani and Schistomysis ornata (G.O. Sars, 1864). Other studies in the same region by the same group of investigators appear consonant with these broad conclusions (e.g., Vallet et al. 1995, Vallet & Dauvin 1998, 2001), although Zouhiri et al. (1998) clearly showed Erythrops elegans (G.O. Sars, 1863) to be co-dominant with Anchialina agilis and Schistomysis ornata in autumn samples from the 75-m station near Plymouth, so Erythrops elegans has been added to the list of species for investigation of migratory habits in this review. Samples off Arcachon, France (Cornet et al. 1983), and off Aveiro, Portugal (Cunha et al. 1997), support the ubiquity and abundance of Anchialina agilis at shelf depths ≤125 m and the inclusion of Erythrops elegans as a frequent and abundantly caught mysid. They also support adding Leptomysis gracilis (G.O. Sars, 1864) as a 98

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frequent co-dominant and occasional dominant at 52–125 m depth. Both of these sampling efforts also found relatively high abundances of Mysideis parva Zimmer, 1915 at 85–120 m depth, so this species has been added to the list of abundant species (Table 1). Anchialina agilis, Gastrosaccus spinifer, Haplostylus lobatus and H. normani are included in the list of six species provided by Macquart-Moulin & Ribera Maycas (1995), along with incontrovertible evidence of their emergence at night. As its specific name implies, Anchialina agilis is an exceptionally strong swimmer. As for most shelf mysids, direct observations are rare. Wittman (1977) described A. agilis during the day in diving depths to be inactive and colourless and to cling to leaves of Zostera without showing any reaction to natural predators or to touch by a diver. This description is incompatible with inferences from vertically resolved epibenthic sledge samples, where Anchialina agilis is usually nearly uniformly distributed among vertically arrayed nets near the bottom (e.g., Zouhiri & Dauvin 1996). Either the behaviour of this species varies spatially or they show an eventual escape response to the sledge that is strong enough to randomise their vertical distribution at the sledge mouth. Given their ubiquity, observations with a remote underwater vehicle or other camera system should be feasible to resolve their daytime behaviours beyond comfortable depths for divers. Both A. agilis and Haplostylus normani showed decreases of abundance in bottom trawls (Zouhiri & Dauvin 1996) and increases in surface plankton tows (Macquart-Moulin & Ribera Maycas 1995) at night, when Anchialina agilis showed remarkable concentration in the very surface 10 cm of the water column (Champalbert & Macquart-Moulin 1970). Few other species are so reduced in abundance in nighttime epibenthic sledge samples (Zouhiri & Dauvin 1996), prompting the conclusion that most of the A. agilis and Haplostylus normani populations undergo diel migration (Macquart-Moulin & Ribera Maycas 1995, Vallet et al. 1995). Anchialina agilis has been caught at the surface in water columns 1000 m deep, likely due to cross-isobath advection of surface waters during emergence (Macquart-Moulin & Patriti 1993, Macquart-Moulin & Ribera Maycas 1995), yet it is difficult from extant data to exclude the possibility of an active horizontal component to the migration as a contributor (Macquart-Moulin & Ribera Maycas 1995). Suggestive of accidental expatriation is the capture in bathyal waters during the day of dead specimens (MacquartMoulin & Ribera Maycas 1995). Macquart-Moulin & Ribera Maycas (1995) also concluded that the whole population of Gastrosaccus spinifer became pelagic at night. Of the migrators discussed by Macquart-Moulin & Ribera Maycas (1995) and included under the abundance criteria in this review, Anchialinja agilis is distributed from the North Sea to the northern Mediterranean and is captured in estuaries only as stray specimens. Haplostylus lobatus and H. normani, with synonymy that has been disputed (Deprez et al. 2005), together cover a range from the Porcupine Bight to the northern Mediterranean and also are rare in estuaries. Gastrosaccus spinifer ranges from Norway, in all the seas surrounding the British Isles and into the northern Mediterranean and along the adjacent North African coast, with disjunct reports from Ivory Coast and the South Shetland Islands in the Southern Ocean (Deprez et al. 2005). It is found further into estuaries than the others but generally in reduced numbers compared with the nearby shelf (e.g., Buhl-Jensen & Fosså 1991). Macquart-Moulin & Ribera Maycas (1995) did not list Erythrops elegans, Schistomysis ornata, Leptomysis gracilis or Mysideis parva among the most abundant shelf mysids and thus did not assess their migratory capabilities. Little published information is available on migration in Erythrops elegans. Zouhiri et al. (1998) on the basis of vertically resolved epibenthic sledge samples listed it as a weak swimmer, along with Gastrosaccus spinifer and Schistomysis ornata, because it tended to be caught in the lower nets. Vallet et al. (1995), quoted in Zouhiri & Dauvin (1996), suggested that Erythrops elegans migrates on a diel cycle (up at night) from the bottom boundary layer to the surface. Mauchline (1980) found negative evidence in the Clyde Sea and Loch Etive for diel migration of S. ornata and in the Clyde for Erythrops elegans. He did not comment on migration of Mysideis 99

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parva. In an extensive series of vertical plankton tows from the continental shelf of western France over the span of 2 yr, Beaudouin (1979) reported Schistomysis ornata only from February tows near the Gironde. Sorbe (1991) reported this species to be abundant from 91 to 179 m depth off Arcachon in southwest France. Based on qualitative plankton tows over the 91-m station, he reported vertical migration in this species and suggested based on size-frequency data that the species migrates seasonally across isobaths. Zouhiri et al. (1998) found S. ornata and Erythrops elegans in high abundance in the western English Channel, but their data showing nighttime disappearance of mysids as a group from sledge samples (with crepuscular peaks in abundance) came from a station in the eastern channel. They captured both Schistomysis ornata and Erythrops elegans primarily in the lower two sampling nets of their epibenthic sledge, prompting the classification of these two species in the group of weakest swimmers. Dauvin et al. (2000) captured Schistomysis ornata only in nighttime sledge tows. Vallet & Dauvin (2001), however, captured roughly equal biomasses of this species in day and night tows with peak autumn abundances reaching 21 ind. m–2. Vallet et al. (1995), quoted in Zouhiri & Dauvin (1996), suggested that S. ornata remained planktonic all day. Kaartvedt (1989) in the abstract of his study on mysid migration in Masfjorden, Norway, listed S. ornata as a vertical migrator, but in that paper reported capture in 57 mostly nighttime Isaacs-Kidd mid-water trawls of only 10 individuals (7 in the shallowest region sampled, above a bottom 35–40 m deep and 3 singletons elsewhere) but made reference to unpublished data from Kaartvedt et al. (1988) to support the conclusion of frequent migration. Earlier observations, summarised by Tattersall (1938), suggested that a small subset of breeding individuals enters the water column at night. Also supporting a case for reduced migration in this species compared with the others already explored is its reported occurrence in the guts of relatively few fish species in the three databases queried (i.e., Gibson & Ezzi 1980, Mauchline 1980, Astthorsson, 1985), but Mauchline (1980) included several more predators, including herring (Clupea harengus), so the issue of the degree of diel migration is not well settled in terms of the fraction of the population participating, the seasonality of the phenomenon, its short-term frequency or the height above bottom at which potentially enhanced swimming activity occurs. Schistomysis ornata also appears to be able seasonally to congregate at a coastal front, presumably via horizontal migration, to take advantage of the concentrated food resources there (Dewicke et al. 2002). Mauchline (1980) cited abundant evidence of diel vertical migration in Leptomysis gracilis, a highly mobile swarmer. Subsequent observations underscore the diel migratory activities of L. gracilis (into the water column at night; e.g., Kaartvedt 1985, 1989). Zouhiri & Dauvin (1996), however, captured more individuals in epibenthic sledges at night than during the day, suggesting that part of the population stays on or returns to the bottom and that it may be more easily captured at night. They also observed this species to be concentrated in the lower nets of vertically resolved tows, nominally indicating lower activity but perhaps indicating a species-specific escape response. Very little information is available on the migratory behaviour of Mysideis parva. Elizalde et al. (1991) reported that the species was concentrated in the lower nets of their sledge samples, indicating weak swimming ability, though nocturnal activity cycles have not been ruled out. In terms of predator gut contents, it has been reported only from thornback rays (Raja clavata) (see Mauchline 1980), lending some support to the conclusion that little migration occurs. Erythrops elegans is somewhat narrowly distributed latitudinally in the North Atlantic (not reported from northern Norway, Iceland or Morocco) but it is found broadly in the northern Mediterranean. Although it is found in some fjords, it has not been reported from shallower estuaries or from salinities much below that of sea water. Schistomysis ornata occurs in the North Atlantic off Iceland, from Norway to France along the European west coast and in coastal seas surrounding the British Isles. To the east it extends into the Baltic. It is also reported from Morocco, but not from the Mediterranean. Like Leptomysis gracilis, it occurs frequently in fjords. Leptomysis gracilis is distributed from Norway south around the British Isles, through the Baltic and broadly in the 100

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northern Mediterranean. It occurs frequently in fjords and in some shallower estuaries. Mysideis parva has been reported on only a few occasions and only at strictly marine sites stretching from southern Ireland to the Ionian Sea. Erythrops elegans, Schistomysis ornata and Leptomysis gracilis co-occur in western Norwegian fjords, where their depth ranges are generally narrower and shallower than the inclusive ones quoted in Table 1 (Fosså & Brattegard 1990). Erythrops elegans was collected by Fosså & Brattegard (1990) at 32–100 m depth and had a median depth of occurrence of 40 m. In the fjords, Schistomysis ornata and Leptomysis gracilis had depth ranges of 32–350 m and 32–166 m and median depths of occurrence of 66 and 89 m, respectively. The four shallowest stations in this wide-area survey were at 32, 40, 74 and 100 m depth. Even more interesting is the horizontal distribution in detailed studies of a single fjord of western Sweden (Buhl-Jensen & Fosså 1991). Erythrops elegans, Leptomysis gracilis, Mesopodopsis slabberi, Schistomysis ornata and S. spiritus all reached high abundances on one or both of the sill stations. Erythrops elegans and Mesopodopsis slabberi occurred only on the sill. Leptomysis gracilis had highest abundance on the sill but also occurred throughout the fjord. Schistomysis ornata peaked on the shelf just beyond the sill (with secondand third-ranked abundances on the sill) but was distributed across all stations except the shallowest, most upstream station (depth 33 m). Erythrops erythrophthalma (Goës, 1864) showed a similar pattern, with high abundance just outside the sill, at the inner sill station, and the highest abundance shown by any mysid (11 ind. m−2) just inshore of the sill at 72 m depth.

Northwest Atlantic shelves Regrettably, systematic, intensive epibenthic sledge sampling has not been practised so frequently on other shelves. On the west side of the Atlantic, the collection of the U.S. National Marine Fisheries Service (NMFS) from the U.S. Atlantic coast remains indisputably the most comprehensive (Wigley & Burns 1971). It includes samples with an epibenthic sledge (‘bottom skimmer’) and 11 other kinds of samplers. Although this study and a follow-up analysis (Wigley & Theroux 1981) included abundant core samples from areas further south, sledge samples were limited to the region between Nova Scotia and Long Island. The NMFS survey left no room for doubt about the single most dominant species (Wigley & Burns 1971): “N[eomysis]. americana is the most common mysid inhabiting the northeastern coastal waters of the United States and undoubtedly the most abundant mysid in the western North Atlantic Ocean. …The NMFS [National Marine Fisheries Service] collection originally contained over 2 million specimens…”. The next most abundant mysids in the NMFS collection were Erythrops erythrophthalma, with 4573 specimens, and Americamysis bigelowi (Tattersall, 1926), with 2031 specimens (Wigley & Burns 1971). No other species yielded >382 specimens. No areal or volumetric abundance estimates were attempted by Wigley & Burns (1971), who were quite sensitive to issues of sampling bias (e.g., Wigley 1967). Mauchline (1980) cited abundant evidence that Neomysis americana is a frequent migrator in shallow water but noted (p. 74) that Whiteley (1948) “found no evidence of a regular diel migration in Neomysis americana on Georges Bank where the depth at which they were living, as deep as 75 m, was greater than in the coastal regions where this species is known to migrate fairly regularly”. Brown et al. (2005) from an extensive collection of zooplankton samples documented seasonal emergence, peaking in April and May, over the period from 1995 to 1989. In most years, peak abundances captured in these plankton samples were 0.1–1 ind. m−3. The present author and coworkers have been collecting emergence-trap and acoustic data on this species in the Damariscotta River estuary, in the U.S. mid-coast region of Maine for over 5 yr and at depth ranges of 10–20 m; it undergoes diel, tidally modulated emergence from approximately late June until early November, although emergence may be weak or absent on any particular day (Abello et al. 2005, Taylor et al. 2005, P.A. Jumars, unpublished observations). Neomysis americana appears to be a strongly diel 101

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migrator in some seasons in most habitats from which it has been reported (e.g., Calliari et al. 2001). Neomysis americana also shows spectacular ability to aggregate (up to 2500 ind. m−2) in bottom-water salinity fronts of estuaries (Schiariti et al. 2006). Mauchline (1980) did not comment on migration in Americamysis bigelowi. The 10-year study of Williams (1972) left no doubt, however, that A. bigelowi migrates above the bottom in large numbers. Further support comes from its presence in the guts of Atlantic silversides (Menidia menidia) in 20 m of water off New York (Warkentine & Rachlin 1989). Mauchline (1980) cited Brunel (1979) for documentation of vertical migration of Erythrops erythrophthalma in the Gulf of St. Lawrence. More recently, Carter & Dadswell (1983) reported planktonic capture of E. erythrophthalma in the very turbid Saint John River estuary, New Brunswick, year-round, including all life stages, but they took no benthic samples. Beaudouin (1979) reported it from only three of her vertical plankton hauls off Gascogne during one winter. It is among the species reported by Astthorsson (1985) from cod (Gadus morhua) guts, but the small number of observations leaves the regularity and depth limits of its diel migratory status uncertain. When this review was written, Deprez et al. (2005) had not entered many geographic data on mid-latitude mysids outside Europe and Africa so, herein, original reports are cited instead. The natural range of Neomysis americana is from the Gulf of St. Lawrence to northeastern Florida (Williams et al. 1974). Such a broad geographic range that includes high abundances at both its extremes of latitude strongly suggests a very successful opportunist or generalist, a conclusion supported by its invasion of coastal waters and estuaries of South America, where it was first reported from Uruguay (González 1974), but has spread south at least as far as San Blas, Argentina (Orensanz et al. 2002). Some fishes have come to depend on this resource (e.g., Sardiña & Lopez Cazorla 2005a,b), and some sympatric copepod populations have declined (Hoffmeyer 2004, although she does not attribute the effect to N. americana; M.S. Hoffmeyer, personal communication). Americamysis bigelowi is known from Georges Bank southward to Florida (Wigley & Burns 1971). The species frequently co-occurs with, but in substantially lower abundance than, Neomysis americana (e.g., Allen 1984). These two species are capable of substantial carnivory (Fulton 1982). Americamysis bigelowi (as Mysidopsis bigelowi) was thought to range into the Gulf of Mexico to the Texas coast, but is replaced by a pair of closely related species in the Gulf of Mexico (Price et al. 1994): Americamysis alleni Price, Heard & Stuck, 1994 and A. stucki Price, Heard & Stuck, 1994. The former species is found in poly- and mesohaline estuaries and the surf zone to 15 m, whereas the latter species has a deeper distribution out to the shelf edge (Price et al. 1994). Deprez et al. (2005) give distributional data for European Erythrops erythrophthalma, which is found off Greenland and Svalbard, down the Norwegian coast and around the British Isles, off western France and along the shelf and slope of the northern Mediterranean. The species is found southward along the U.S. east coast as far as Delaware, peaking in abundance at 60–100 m depth in evidence from the NMFS collection (Wigley & Burns 1971), and is widespread in the Arctic basin (Petryashev 2002a,b). All three of the most abundant mysid species in the NMFS collection showed high abundance on Georges Bank, with E. erythrophthalma most abundant on its southern flank, just above the 100-m isobath. Erythrops erythrophthalma is found primarily on the middle and outer shelf (Wigley & Burns 1971, Petryashev 2002a). Both Neomysis americana and Americamysis bigelowi are abundant in estuaries (e.g., Herman 1963, Allen 1984). In the NMFS survey, peak abundances on the shelf for A. bigelowi were at 30–60 m depth (Wigley & Burns 1971). The bathymetric distribution of Neomysis americana is unusual. In grab samples from the Gulf of Maine, Wigley and Burns (1971) found this species at highest abundance from 30 to 60 m depth, noting its more common presence in grabs taken during daylight. Within Cape Cod Bay, however, N. americana apparently has a shallower abundance peak at 10–29 m depth (Maurer & Wigley 1982). In the southern United States, the species rarely is captured in benthic samples offshore (Wigley & Burns

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1971), occurring more frequently in the lower, middle and upper reaches of estuaries (e.g., Williams 1972, Zagursky & Feller 1985). This onshore shift, opposite in direction to that of many other species with temperature or latitude, led Williams et al. (1974) to suspect (sub)speciation, but morphological evidence did not support this interpretation, although the issue now merits reexamination with molecular methods (Audzijonyte & Väinölä 2005, Remerie et al. 2006). Over both the shelf and offshore shoals, within coastal embayments and near inlets, abundance peaks of N. americana are reported in winter-spring, consistent with an overwintering generation breeding then, although overwintering is not excluded as a possibility within estuaries as well (Carter & Dadswell 1983). Estuarine abundance of N. americana generally peaks in summer from the midAtlantic states northward, and the number of generations per year can increase to three in the southern part of the species range (Cowles 1930, Whiteley 1948, Hulbert 1957, Herman 1963, Hopkins 1965, Williams 1972). In South Carolina, N. americana is found year-round in subtidal estuary channels and in shallow ocean waters, and its peak populations in estuaries are shifted earlier in the year (DeLancey 1987, Johnson & Allen 2005, D.M. Allen, personal communication).

Northeast Pacific shelves Elsewhere, information is much more fragmentary. In his classic study of nearshore mysids in the surf zone of southern California, Clutter (1967) found the two most abundant mysids to be Metamysidopsis elongata Holmes, 1900 (up to about 2000 ind. m−3 at 6 m below MLLW (mean lower low water)) and Neomysis kadiakensis Ortmann, 1908 (up to about 180 ind. m−3 at 8 m below MLLW); both are swarming species. Clutter (1969) reported only a subtle upward shift in median population position of Metamysidopsis elongata at night, and he reported no observations on Neomysis kadiakensis at night. Little more has been written after Clutter’s studies about the behaviour and distribution of Metamysidopsis elongata except its essential fatty acid requirements (Kreeger et al. 1991) and its role as a prey species for juvenile white seabass (Atractoscion nobilis) (Donahoe 1997). A few observations on abundance patterns and laboratory culture of its Atlantic subspecies have appeared (Tararam et al. 1996, Gama et al. 2002, and references therein). Neomysis kadiakensis appears to follow an analogous pattern to the European Mesopodopsis slabberi in abundance along the west coast of the United States. Clutter described Neomysis kadiakensis as occurring in kelp beds as well as over open sand. This species can reach higher abundances in estuaries. Dean et al. (2005) in a salt marsh within the San Francisco estuary noted that it dominated mysid abundance there over the full year, with a spring peak in abundance at 244 ind. m−3. They measured a large net import of N. kadiakensis into the salt marsh, where instantaneous mortality was calculated as 0.29 day−1. Kringel et al. (2003) in northern Puget Sound over a muddy bottom at 20 m water depth observed coherent emergence and re-entry events of N. kadiakensis associated with estimated biovolumes of 4–5 × 103 mm3 m−3. Moreover, these nocturnal emergence events appear to have dominated the holoplankton in abundance (Kringel et al. 2003). Vertical migration of this species is widespread in Puget Sound, but in the deeper reaches individuals do not appear to migrate all the way to the sea bed (Thorne 1968). It seems unlikely that Clutter (1969) could have missed such strong nocturnal emergence, so N. kadiakensis likely differs in diel migration patterns along its range. Neomysis kadiakensis is distributed from the Gulf of Alaska to southern California (Petryashev 2005). Kim & Oliver (1989) specifically studied schooling crustaceans in regions where gray whales (Eschrichtius robustus) fed in the Bering and Chukchi Seas. In diving observations concentrated in the Bering Sea, they reported swarms of Xenacanthomysis pseudomacropsis Tattersall, 1933, Neomysis rayii Murdoch, 1885 and Exacanthomysis arctopacifica Holmquist, 1981 and sampled them with various means at depths from 3 to 24 m. Petryashev (1992) regarded E. arctopacifica

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as a junior synonym of Acanthomysis stelleri Derzhavin, 1913. In Kim & Oliver’s study, Xenacanthomysis pseudomacropsis usually dominated and reached abundances of 600 ind. m−3. Acanthomysis stelleri was one to two orders of magnitude less abundant, and Neomysis rayii was reported only from two sites at the southeast extreme of the Bering Sea, where it reached intermediate abundances between those of the other two species. Direct observations of diel migration apparently are lacking, but Wing & Bar (1977, quoted in Mauchline 1980) captured Xenacanthomysis pseudomacropsis, Acanthomysis sp. and Neomysis rayii in mid-water trawls from the Chukchi Sea. Neomysis rayii is a known winter diet component in common murres (Uria aalge) and marbled murrelets (Brachyramphus marmoratus) off southeast Alaska (Sanger 1987, DeGange 1996) and Acanthomysis spp. are listed as additional diet components of the latter (DeGange 1996), although it is not clear how far the birds make excursions toward the bottom or mysids make excursions off the bottom to effect their encounters. Neomysis rayii and Acanthomysis spp. are also taken by gray whales (Eschrichtius robustus) further to the south, off Vancouver Island (Darling et al. 1998). Neomysis rayii must have been caught often enough in plankton samples to be considered a pelagic crustacean by some (McConnaughey & McRoy 1979), but simultaneous benthic and pelagic samples over diel cycles would do much to clarify these issues for all three of the Alaskan species. Xenacanthomysis pseudomacropsis occurs from central Japan to British Columbia, Neomysis rayii shares that range and extends it to southern California, and Acanthomysis stelleri has the narrowest geographic range from northern Japan to the easternmost portion of the Aleutian peninsula. All three species extend into the Chukchi Sea but not above the latitude of Wrangel Island (Petryashev 2002a).

Northwest Pacific shelves Takahashi & Kawaguchi (1995, 1997) on the Pacific coast of northern Honshu, Japan, took isobathparallel, epibenthic sledge samples from the shallowest submerged station they could sample at the lowest level of the spring tide out to 100 m from the tide line, to about 5 m water depth. Tows were stratified by distance from shore in 10-m increments and were repeated monthly between March 1992 and January 1993. Three species clearly dominated, with the dominant varying with season and depth: Archaeomysis kokuboi Ii, 1964, A. japonica Hanamura, Jo & Murano, 1996 and Iiella ohshimai (Ii, 1964). Archaeomysis kokuboi moved with the tide to stay in the shallowest position, barely immersed, and showed a peak abundance of 511 ind. m−2 in 31 July in the 0- to 10-m range from the water’s edge. (The areal abundance estimate in the present review includes no correction for sampling efficiency but simply divides the number in the tow by its 60-m2 area.) Archaeomysis kokuboi emerged at night, expanding its distribution offshore, with the reproductively most valuable members of the population showing less tendency to do so. Archaeomysis japonica occupied the next depth stratum and did not migrate with the tides but also emerged at night. The species reached peak abundance in the 10- to 20-m interval from the tide line in June at 60 ind. m–2. Iiella ohshimai was found primarily in the deepest samples as juvenile stages but showed some shoaling of its distribution in summer and also emerged at night. Iiella ohshimai reached peak abundance of 1.3 ind. m−2 in the 20- to 30-m distance from the shoreline in August, but in other months more than half of the captured individuals were found further offshore. All three species spent daytime hours buried in the sand, and all three species showed depth segregation of life stages. The Archaeomysis kokuboi population had breeding females as its shallowest members, whereas the other two species’ populations had juveniles as their shallowest members. Archaeomysis kokuboi and A. japonica are extensively exploited as food by surf-zone fishes and, as expected from their burrowing behaviour during the day, are taken mostly at night by both benthic and pelagic fishes that converge on this environment (Takahashi et al. 1999). Moreover, adult females of A. kokuboi find spatial refuge in the extremes of shallow water (Takahashi et al. 2004).

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Yamamoto & Tominaga (2005) took epibenthic sledge samples by boat from the shallow surf zone of the Seto Inland Sea three times a month from May to August in three successive years. Iiella ohshimai and Nipponomysis ornata Ii, 1964 co-dominated, with mean densities of 1.38 and 1.28 ind. m−2, respectively. One of the three dominant fish species fed primarily on the (daytime) epibenthic species N. ornata, whereas the other two ingested Iiella ohshimai more frequently, based on gut contents of daytime-collected fishes (Yamamoto & Tominaga 2005). In a separate study of Japanese flounder (Paralichthys olivaceus) from the same region, Yamamoto et al. (2004) found them to prefer the epifaunal Nipponomysis ornata. In another site in the same general region of the Seto Inland Sea, sampled monthly by epibenthic sledge between May and October for two of the same years, N. ornata showed much greater dominance over Iiella ohshimai, and mysid abundance peaked at 250 ind. m−2 in May–June (Hanamura & Matsuoka 2003). Of the four mysid species that dominated the nearshore subtidal in these Japanese studies, only Archaeomysis kokuboi is listed by Petryashev (2005) in his biogeographic summary. He listed it as being West Pacific, low boreal. Hanamura (1997) described its geographic limits as being from central Hokkaido to Honshu in northern Japan and those of A. japonica as being shallow subtidal to 50 m from Kyushu to Hokkaido. Suh et al. (1995) described an offshore migration in A. kukuboi in eastern Korea in the afternoon, with onshore migration in the morning, but their study was done before Hanamura (1997) resolved differences between some closely related species of Archaeomysis. Hanamura et al. (1996) also confirmed the emergence of Archaeomysis japonica at night. It appears that no information on diel migration of Nipponomysis ornata is available.

Other regions In other regions, it was not possible to attempt the two-step methodology for lack of comparable abundance estimates or information on migratory behaviour or lack of both, but it is clear that mysids are ubiquitous at and beyond the range of latitudes considered here. Patagonian fjords, as but one example, contain a rich mysid fauna (Brandt et al. 1997), with evidence of diel migrations (Antezana 1999), and merit more intensive study. In many cases, neuston or plankton samples confirm a pelagic phase, but neither the connection to benthic populations nor phasing of migrations is known (e.g., Sawamto 1987). A few more of these geographically scattered reports are mentioned in the following discussions of particular issues of ecological roles of mysids and drivers of their vertical migrations. Mysid ‘umwelt’ Information in the three databases used is clearly biased geographically toward Europe and North America, but where data are available on all three aspects, there is strong association among diel migration by a mysid species, its high relative abundance among mysids in the same habitat and its use as food by fishes and other animals. There is no reason to doubt that additional data would add additional species to this list or that it could already be enlarged through other databases, but some trends already are apparent. The clear risk during migration in species with this syndrome must clearly be accompanied and outweighed by substantial fitness gains in nutrition, dispersal, reproductive encounter and other aspects of life in order for these species to be among the most abundant mysids. As but one example of these ‘other’ potential gains or reduced losses, mysids living in macrophyte beds or over dense diatom mats may be driven out by low oxygen concentrations at night (Ledoyer 1969). One other pattern is apparent immediately from the data: many of the abundant shelf species of mysids show even higher abundances in the convergence zones at estuary mouths (Figure 1) than they do on shelves, with varying seasonal penetrations and population irruptions into polyhaline, mesohaline and even oligohaline reaches of estuaries.

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Erythrops elegans Erythrops erythrophthalma Gastrosaccus spinifer Leptomysis gracilis Neomysis americana Schistomysis ornata

Coastal plains estuary with an inlet

Fjord with a sill

Americamysis alleni Mesopodopsis slabberi Neomysis americana Neomysis kadiakensis Schistomysis kervillei Schistomysis spiritus

Mesopodopsis slabberi Isobath Americamysis bigelowi

Shelf edge Increasing latitude

Figure 1 Species that meet abundance criteria in the text and that occur either in the surf zone and estuaries or on the mid-shelf and in fjords or show both patterns (Neomysis americana). Mesopodopsis slabberi apparently also invades fjords from the surf zone, whereas Americamysis bigelowi apparently invades estuaries from the mid-shelf as surmised from seasonal abundance patterns.

Multiple drivers of emergence and their differing relative importance among species, locations and times are as certain for mysids as they are for holoplankton (Pearre 2003), but strong involvement of visual predators is clear from the characteristic pattern of emergence near dusk and re-entry near dawn. What makes the emergent lifestyle unique is relative, Eulerian immobility during the benthic phase, during which overlying waters are replaced. Holoplankton arguably can get a similar subsidy in regions of high vertical shear, and euphausiids are routinely captured in epibenthic sledge samples from mid-shelf depths and deeper (e.g., Cunha et al. 1997), but it will take a particular combination of vertical shear and migration timing to remain in a region of high horizontal velocity (e.g., Barber & Smith 1981). Daytime location of mysids under the surf zone, under inlets, on sills (Figure 1) and under particular portions of estuaries (e.g., Kaartvedt 1989, Cunha et al. 1999) attests to mysid virtuosity in utilising horizontal fluxes and resisting displacement. Horizontal subsidy has been easiest to visualise over abrupt changes in topography such as seamounts (reviewed by Genin 2004). The zooplankters that happen to occur over seamounts and shoals as their downward diel migrations begin are subject to intense predation. In the mysid case, the topography can be less steep, but the process is analogous and it is the mysids rather than their food taxa that do the migrating; the large phytoplankton, other protists and small zooplankton that chance to be advected above a mysid-rich area at night are subject to intense predation. Just as predators resident on seamounts can produce patches of reduced zooplankton abundance in those waters that passed over a seamount at night (Haury et al. 2000), nocturnal, pelagic patches of high mysid abundance of diel migrators can be predicted to produce patches of reduced abundance in their holoplanktonic prey. Preferred daytime mysid habitat underlies wave-driven currents, coastal currents, tidal currents, buoyancy-driven currents and topographically driven flow convergences over shoals, narrows and sills, where resultant flows replace overlying waters at high frequency. The contrast between mysids and euphausiids in fjords (Kaartvedt et al. 1988, Kaartvedt 1989) illuminates the benefits of the mysid lifestyle. Euphausiids are clearly less capable of maintaining or returning to horizontal

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co-ordinates of high horizontal flux or of high utility as refuge from predators and so are less able to profit from them than are mysids. Mysids thus fit into a broader pattern of horizontal import subsidy but have some special adaptations that enhance their gains. Genin (2004, his ‘feed-rest’ hypothesis) noted that fishes on seamounts can rest in the bottom boundary layer or behind flow obstructions when they are not feeding. Mysids as omnivores can improve on feed-rest by feeding in the pelagic environment and both feeding and resting on the bottom. They can cause ‘trophic focusing’ (Genin 2004) even where topography is not steep. The reason that this focusing is not as evident as it could be, in turn, is that mysids clearly suffer extensive mortality from mobile decapod and fish predators that horizontally export much of the horizontal import subsidy that they gather. If mysids fed only on locally produced prey and on a narrower range of resources, or if they were not fed on as heavily, their impacts would be far easier to detect but they would be less important as stabilisers in the context of new food-web theory (Montoya et al. 2006, Rooney et al. 2006). The likelihood that they return to similar habitat but not the same location when they re-enter the benthic habitat suggests that they also lend dynamic stability to benthic community structure; a local disturbance in terms of mortality of mysids can recover literally overnight compared with the need in many other benthic species for larval recruitment to occur. Besides the typical pattern of daytime re-entry and nighttime emergence, a second indication of the importance of visual predation as a driver of emergence is release from re-entry in especially turbid waters (Carter & Dadswell 1983, Castel 1993) and association of high mysid abundances with high turbidity zones of estuaries (e.g., Kimmerer et al. 1998b, Roast et al. 2004, Schiariti et al. 2006), which often leads to shoaling of populations in upper, more turbid reaches (e.g., Hulbert 1957). This association with and benefit from turbidity may underlie the paradoxical southward shoaling of peak abundances of Neomysis americana on the continental shelf. South of Cape Cod, particularly where barrier bars and islands develop along this passive continental margin, most fine material delivered by rivers is trapped inside estuaries, and what little does get delivered has a short residence time on the shelf. Dependence by juveniles on macrophyte detritus (either algal or angiosperm) may also contribute to this southward shoaling because macroalgal substrata become scarcer southward and plant and macroalgal fragments are among the particles largely trapped in estuaries. Mysids are not absent from shallow or clear waters, but generally adopt one or more of three strategies where they cannot hide within or below turbid waters: burying themselves in the bottom, hiding in vegetation or other cover or schooling. If the reaction is to visual predation and not turbidity per se, other optical phenomena that impede image formation will also benefit mysids (e.g., image distortion through salinity or thermal microstructure) (suggested by M.J. Perry, personal communication) and wave speckle and bubble clouds in the surf zone. Some mysids do congregate at salinity fronts (Kotta & Kotta 2001b, Schiariti et al. 2006). Of course there are other potential reasons, such as enhanced resource concentrations from electrostatically induced coagulation, from salting out of organics or from frontal circulation patterns. Day-night shifts in activity level (frequency and duration of movement) and height above the bottom occur even in those species not known to migrate to surface waters, with increases typical of nighttime (Fosså 1986). In the lowermost bottom boundary layer, because of the rapidly increasing horizontal velocity and hence fluxes with increasing distance from the sea bed, even modest changes in height above the bottom can yield large differences in exposure to resources. Coming out of the sediments (for the mysid species that bury) as well as activity and height changes can also produce major changes in encounter rates with predators. Saigusa (2001) provided a highresolution method for examining activity cycles, that is, by pump sampling from a depth 50 cm below the water surface simultaneously with pump sampling 50 cm above the bottom and collecting sequential 30-min samples from both streams. Saigusa (2001), at Akkeshi on the Pacific Coast of

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Hokkaido in water ~3 m deep at high tide, Nipponomyis toriumi (Murano, 1977), in 25 days of continuous sampling, showed a strong nocturnal periodicity in capture 0.5 m off the bottom, whereas the surface pump showed weak or no diel periodicity. Both sampling streams showed tidal periodicity in capture rates. At Ushimado on the Seto Inland Sea, in water of similar depth, where only surface water was sampled, an 18-day time series showed Siriella japonica Ii, 1964 to have distinct nocturnal periodicity in capture, again modulated by tides. A great deal of diversity in tidal and diel periodicity and height of emergence above the bottom is expected of mysids across species, locations and times as there is ample modulation of both risks and benefits on diverse scales. Particularly striking in the time series analysis by Saigusa (2001) is the ubiquity of periodicity in pump capture of potential prey of mysids and thus, in potential, for their capture by mysids.

An appreciation of mysids Further evidence of mysid importance in the coastal marine economy Food-web roles Roles that mysids play in feeding their predators are increasingly recognised. A search on ‘mysi*’ and ‘feeding’ in ASFA currently returns about 900 citations of which >90% concern mysids in diets of other animals. Mysids constitute particularly large fractions in the diets of many fishes in the 3–15 cm length category. In a collection of nearly 500 beam trawl samples from the Westerschelde estuary (Hostens & Mees 1999), mysids occurred in >50% of the (mostly juvenile) fish stomachs analysed and constituted >10% of the diets of two goby species (Pomatoschistus lozanoi and P. minutus), garfish (Belone belone), two gadids (bib, Trisopterus luscus, and whiting, Merlangius merlangus), two flatfish species (Pleuronectes platessa and Platichthys flesus), herring (Clupea harengus), seabass (Dicentrarchus labrax), sea snail (Liparis liparis), hook-nose (Agonus cataphractus) and tub gurnard (Trigla lucerna). Beach seining in the southern Sea of Japan produced similar dietary prominence in the 19 fish species recovered, with 67% of individuals feeding on mysids (Inoue et al. 2003). As other prominent examples of mysid dominance in gut contents, juvenile cod (Gadus morhua) <10 cm long in one study from the northwest Atlantic feed almost exclusively on mysids (Link & Garrison 2002), and European hake (Merluccius merluccius) show similar dietary preference (Papaconstantinou & Caragitsou 1987, Bozzano et al. 1997). Plummer et al. (1983) examined gut contents of California halibut (Paralichthys californicus) trawled from 6–30 m depths off southern California and found Neomysis kadiakensis to dominate the diets of fish <25 cm long. Patterns inside estuaries are similar (e.g., Nemerson & Able 2004). Particularly when locally dominant mysid species bury themselves during the day and the water column is shallow, bottom fishes may show higher feeding rates on mysids at night for simple encounter-rate reasons (e.g., Hirota et al. 1990, Takahashi et al. 1999). Even mysids that stay near the bottom in deeper water may become more active at night than during the day (Fosså 1986), increasing their encounter rates with demersal fishes. As an example of pelagic fish diets, mysids are important items in the nighttime diets of European anchovies (Engraulis encrasicholus) (see Tudela & Palomera 1997), emphasising the role of migration in encounter. In the Baltic, where the interaction of mysids and herring (Clupea harengus) has been studied most extensively, herring feed on mysids primarily as medium to large fish during winter (Möllmann et al. 2004). Whereas herring are widely regarded to be primarily visual feeders and thus unlikely to eat nocturnally emerging mysids (Flinkman et al. 1992), other clupeids do not necessarily follow this pattern. Alewives (Alosa pseudoharengus) use the lateral line to locate mysid prey in the dark (Janssen et al. 1995) and in their sometimes-turbid marine and estuarine habitats, specialise on mysids, crangonids and amphipods (Stone & Daborn 1987). 108

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Moreover, gut contents analysis underestimates mysid contribution to assimilation because mysids are more digestible than are many other taxa (Lankford & Targett 1997). The high dietary value of mysids, based on richness in polyunsaturated fats (Navarro & Villanueva 2000, Richoux et al. 2004), has also been recognised in aquaculture feeds (e.g., Takeuchi et al. 2001). A particularly clever application of stable carbon and nitrogen isotopic methods to flounders that eat mysids permits estimation of their cumulative food consumption after release from a hatchery and documentation of their competition with natural stocks (Tominaga et al. 2003, Tanaka et al. 2005). Another line of evidence for food-web significance comes from estuarine and coastal habitat changes that have gone beyond their ‘normal’ limits through interannual variability (e.g., in freshwater runoff) or through habitat expansion of invasive species. A notable example is invasion of the San Francisco Bay estuary system by the overbite clam (Potamocorbula amurensis), which appears to have greatly reduced phytoplankton and small zooplankton stocks available to benthos and plankton alike. Mysid stocks have plummeted to 10% of previous levels (Kimmerer & Orsi 1996), apparently as a result of food limitation (Orsi & Mecum 1986, Kimmerer 2002). Eight of 13 fish species showed declines in apparent response to this reduction, and only striped bass (Morone saxatilis) contained more than traces of mysid remains (Feyrer et al. 2003) after the invasion. Other vertebrates also utilise mysid prey. Notably, gray whales (Eschrichtius robustus) are observed to feed on mysids both on shallow shelf feeding grounds (Kim & Oliver 1989) and along the coast of British Columbia (Darling et al. 1998, Dunham & Duffus 2002, Stelle 2002, Patterson 2004). Bowhead whales (Balaena mysticetus) also take mysids (Lowry & Burns 1980). Seabirds also utilise mysid populations (e.g., Moran & Fishelson 1971, Divoky 1978, Sanger 1987, DeGange 1996), and some species of polar seals (i.e., crabeater seals, Lobodon carcinophagus, and Weddell seals, Leptonychotes weddellii) also have been found to eat mysids (Green & Williams 1986, Lake et al. 2003). Seals at lower latitudes appear more commonly to have a less-direct dietary interaction with mysids, experiencing parasitism by nematodes that use mysids and the fish predators of mysids as intermediate hosts (Jackson et al. 1997). Humans also harvest mysids and do so on a commercial scale (2000–3000 tons of one species per year) in Japan (Omori 1978). Mysids are also substantial dietary components of many invertebrates. They appear critical, for example, to diets of the smallest juvenile cuttlefish (Sepia officinalis) <2 cm long (Le Mao 1985) and are substantial components in diets of many cephalopods (e.g., Aronson 1989, Huang 2004). Many decapod shrimp species routinely prey on mysids, but among the most interesting couplings is the frequent association of species of Crangon with vertically migrating mysids. Although it is clear that Crangon spp. are not obligate feeders on mysids, where mysids are abundant local Crangon species appear to specialise on them (e.g., Price 1962, Sitts & Knight 1979, Siegfried 1982, Pihl & Rosenberg 1984, Wahle 1985, Hong & Oh 1989, Oh et al. 2001, Hanamura & Matsuoka 2003). Crangon septemspinosa emerges on a diel cycle with or shortly after Neomysis americana according to Taylor et al. (2005) and broadly overlaps its habitat and geographic ranges. On Georges Bank, catches of the two species in macrozooplankton samples are highly correlated (Brown et al. 2005). Taylor et al. (2005) pointed out that mysid emergence in their system is also associated with copepod emergence. This copepod-mysid-crangonid emergence combination (Figure 2) greatly expands the size spectrum of prey available in this movable feast, and some fish species use a substantial fraction of the total range at one time or ontogenetically (e.g., Stone & Daborn 1987, Gatlin 1997, St.-Hilaire et al. 2002, Yamamoto et al. 2004, Yamamoto & Tominaga 2005). Other invertebrates may also follow the migration (e.g., Matsumoto 1995). It is also clear that the depth limits and sensory postures of some benthic invertebrate predators are tuned to the arrival of vertical migrants (Lagardère 1977). Mysids are both preyed upon and parasitised by protists (Buchanan & Hedley 1960, Shields 1994). Mysids may also be eaten by other mysids of the same (Johnston & Ritz 2001, Quirt & Lasenby 2002) or different species (Jerling & Wooldridge 1995). Mysid-mysid predation

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Pelagic fishes

Pelagic by night

Crangon septemspinosa

Emergent meiofauna

Emergence

Mesozooplankton Large phytoplankton Benthic by day

Re-entry

Neomysis americana

Demersal fishes Crangon septemspinosa Neomysis americana

Other meiofauna

Emergent meiofauna

Microphytobenthos

Detritus

Figure 2 The immediate food web of Neomysis americana, showing changes and some surprising constancy over the diel cycle. The components within the dotted line all migrate, providing a much larger size spectrum for encounter by larger decapods and fishes than would a single migrant. Mysids are extremely omnivorous and are consumed by many species; the non-migrating part of this web is highly aggregated in the diagram.

is a function not only of size, but also of behaviours and abundances of the predator and prey mysids as well as of alternative prey (Winkler & Greve 2004). Because mysid diets have recently been reviewed by Takahashi (2004), present comments are limited to a short summary. He pointed out that carnivory on holozooplankton is typical of later juvenile and adult stages of mysids. In coastal and poly- to mesohaline estuarine environments, prey are often copepods ingested at roughly 3–30% of mysid body carbon day−1. In oligohaline and freshwater environments, cladocerans are often preyed upon heavily, probably because they can be filtered in bulk (Viitasalo et al. 2001) and digested readily, and are ingested at 24–300% of mysid body carbon day−1. The carnivorous component of the diet appears to be especially important for growth and reproduction (Viherluoto et al. 2000). Smaller, younger juveniles that migrate eat smaller holozooplankton, detritus and phytoplankton, but rarely ingest cells or chains <10 mm long, often selecting diatoms in preference to other phytoplankton taxa. When large diatoms are scarce, diets of juveniles may shift to microzooplankton (Jerling & Wooldridge 1995). The smallest mysid individuals often do not migrate off the bottom and thereby may focus even more strongly on a detrital or microphytobenthic diet. The potential dietary role of benthic diatoms for multiple life stages of mysids bears emphasis (Mauchline 1968, Perissinotto et al. 2003). Takahashi (2004) usefully described the trend of increasing carnivory with size and maturity as life-history omnivory, supporting the generality of the stable isotope-based conclusions and terminology of Branstrator (2000) for Mysis relicta Loven, 1862. The same term has been applied to fishes (Montoya et al. 2006), but mysid omnivory brackets a larger range of food types closer to the base of the food web, yet spans more than one habitat. Mysid life-history omnivory is particularly well documented by analysis of fatty acids (Richoux et al. 2005), and lipid accumulation in mysids from nighttime predation on holozooplankton is probably enhanced by post-feeding migration to cooler waters (Chess & Stanford 1999). Benthic phases may also span the entire gamut of diets from detritus to microphytobenthos to heterotrophic protists and rotifers to larger meiofauna and even macrofauna 110

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(Johannsson et al. 2001, Albertsson 2004), but all sizes of many species are more prone to ingest detritus during the benthic phase than during the pelagic (Table 2 of Takahashi 2004). It seems very likely that benthic-phase mysids are able to take advantage of the much greater food value of suspended detritus (Mayer et al. 1993) either by direct suspension feeding from material already suspended in the bottom boundary layer or by resuspending it from the bottom and then filtering it (Mauchline 1980, Viherluoto et al. 2000). Cellulases that are apparently endogenous have been reported in Mysis stenolepis S.I. Smith, 1873 by Friesen et al. (1986), and macrophyte detritus appears to be particularly important in the winter diet of Neomysis americana in salt marshes in the southern part of its range (Zagursky & Feller 1985). Stable isotopic data also support a winter shift toward a greater contribution from refractory terrestrial, angiosperm detritus to mysid diets in coastal British Columbia (Mulkins et al. 2002). Froneman (2001), however, found no seasonality in the isotopic signature of Mesopodopsis wooldridgei Wittman, 1992 in the temperate Kareiega estuary of South Africa but did find evidence of likely contribution to its nutrition from eelgrass. All these studies contrast with the stable isotopic results of Dauby (1995) for four species of Leptomysis that, contrary to the diel migrators focused on in this review, school near the bottom during the day, remaining largely immobile relative to the bottom and not feeding, and migrate down to feed on detritus at night; he found only minor dietary influence from seagrass, with much greater reliance on micro- and macroalgae. Dauby’s results, in turn, are compatible with those of Metillo & Ritz (2001), who found seasonal laminarinase activity cycles in three Tasmanian mysid species, which imply a winter reliance on macroalgal detritus. In summary, reliance on detritus of varied sources depends on species and perhaps on location. One point to emphasise is that most species of mysids, although they tend toward carnivory as late juveniles and adults, do not appear to become exclusively carnivorous in the field (Hansson et al. 1997, Branstrator 2000). Adults of some species, however, move very much toward that extreme (Jerling & Wooldridge 1995, Kouassi et al. 2006). The vertically migrating species tend to show increases in the fraction of detritus and sediments as gut contents during their benthic phases (e.g., Lasenby & Shi 2004). On a diel timescale, they are sequential omnivores, alternating between daytime diets rich in nitrogen and worth substantial digestive time and detrital diets that yield higher net rate of gain at higher throughput rates (Zagursky & Feller 1985, Penry & Jumars 1987, Jumars 2000). Eating food of different qualities in sequence allows tailoring of gut retention time to day-night change in diet quality (Penry & Jumars 1987, Jumars 2000), which can provide much higher assimilation efficiency than optimising retention time on a complete mixture of daytime with nighttime diets. Mysids in general have complex masticatory and digestive structures that not only admit broad diets but also make ingestion of organisms that have no hard parts (e.g., many protists and larval stages) difficult to identify (e.g., Brunet et al. 1994, De Jong-Moreau et al. 2001). Mysids can be sufficiently abundant to influence prey community structure (e.g., Fulton 1983). Both in the surf zone and in the plankton, larger diatom cells and chains experience the greatest grazing pressure from mysids (e.g., Webb et al. 1987, 1988, Linden & Kuosa 2004). In a particular interesting migratory role reversal from the typical offshore or estuarine scenario, Gastrosaccus psammodytes Tattersall, 1958 feeds on surf-zone diatoms during the nighttime, benthic phase of the diatoms (Webb et al. 1988), and Mysidopsis wooldridgei may consume up to 70% of surf-zone diatom primary production (Webb & Wooldridge 1990). David et al. (2006b) found that juvenile Mesopodopsis slabberi could account for the vast majority of herbivory in some settings. In fresh water, daphnid populations can be severely reduced by mysids, defeating the purpose of mysid introductions into lakes as food for salmonids (Spencer et al. 1999). In one shallow, tropical lagoon, a population of mysids appeared to explain the low zooplankton:phytoplankton biomass ratio and potentially could have consumed the entire holozooplankton production (Kouassi et al. 2006). In that particularly carnivorous role, mysids can contribute substantially to phytoplankton nitrogen 111

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requirements through excretion (Kouassi et al. 2006), but more typically the effect of feeding on a combination of phytoplankton and zooplankton is expected to produce subtle shifts in size structure of phytoplankton with little net effect on standing stocks (e.g., Linden & Kuosa 2004). In estuaries, grazing pressure by mysids on holozooplankton varies among locations and seasons but can be substantial (e.g., Fulton 1983, Aaser et al. 1995, Kibirige et al. 2003, Winkler et al. 2003). Early results with Americamysis bigelowi showed substantially reduced feeding on copepods in the dark versus the light (Fulton 1982). Contrary to expectations from their well-developed eyes, from the results of Fulton (1982) and from the observation by Clutter (1969) of more polarised schooling in the light, more recent experimental data do not support the idea that most mysids are primarily visual feeders. One migrating species showed higher ingestion rates on copepods in the dark, whereas a non-migrating species showed no difference in light versus dark (Viherluoto & Viitasalo 2001). Different mysid species apparently rely to differing degrees on tactile and visual cues, and likely on chemical ones as well. It seems likely that species risking vertical migration will have means to feed efficiently in the dark, that is, to obtain net gain during that migration risk by ingesting large, lipid- and protein-rich prey. Moreover, mysids are capable of predation on relatively large prey on the bottom as well (e.g., Wilhelm et al. 2002). One particularly interesting observation is that, given a choice, some mysid species prefer meroplankton (David et al. 2006a). Mysids thus have the potential to cause large mortality of meroplanktonic recruits in the plankton or when they are settling. This potential coastal filter of larvae in both habitats (pelagic and benthic) merits attention. Habitat alteration and coupling Roast et al. (2004) documented a significant role for mysids in resuspension of sediments underlying the turbidity maximum of an estuary. Acoustic experiments with artificially emplaced sediments (C.D. Jones & P.A. Jumars in preparation) in 20 m water depth off the Friday Harbor Laboratories pier in the San Juan Islands, Washington, strongly implicated emergent Neomysis kadiakensis in rapid microtopographic roughening of the sediment-water interface. Because the sediment surface at steady state is already rough, this interaction of mysids is normally difficult to detect but likely contributes to the erodibility effects documented by Roast et al. (2004), and attacks by predators of mysids add further to it. Less obviously, mysids also have the potential to alter the lowermost chemical boundary layer above the sediment-water interface, both through this roughening (e.g., Figure 1 of Jumars & Nowell 1984) as well as through movement over the bottom. The diffusive sublayer in smooth-turbulent flow over the sea bed is typically on the order of 1 mm thick. Diffusion time over that distance, calculated at time = distance2/(2D), where D is the molecular diffusion coefficient (typically ≥ 2 × 10−9 m2 s−1), is 4 min. Thus disruption of the lowermost 1 mm every 4 min or less by mobile animals could appreciably increase benthic-pelagic fluxes by producing unsteady diffusion through frequent sharpening of the diffusion gradient. In terms of habitat coupling, diel migrations of holoplankton that feed closer to the surface than where they spend other parts of the day result in net downward fluxes of nitrogen in the form of excretion and carbon as respired dioxide (Longhurst & Harrison 1988, Longhurst et al. 1990) in addition to the downward advection of particles as gut contents and faeces. Mysids returning toward the seabed transport materials downward in all these ways. Unlike holoplankton, however, emergent mysids also transfer material upward by feeding on the bottom and excreting and respiring in surface waters. Net nitrogen flux is almost certainly downward because of the generally high C:N ratios in benthic detrital foods, but where most carbon is obtained and carbon dioxide released is less clear because swimming activity and temperature on average are both higher during the pelagic phase. For materials highly concentrated in sediments, such as hydrophobic contaminants and certain valence states and compounds of rare-earth elements and metals, mysid migrations and 112

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food-web concentration conceivably could result in net upward transport (Evans et al. 1989, Neff 1997, Song & Breslin 1999). Interesting potential exists for an interaction of habitat coupling and habitat modification by dense, migratory swarms of mysids. Kunze et al. (2006) have documented a significant contribution to turbulence and water-column mixing by coastal euphausiids during periods of stratification; similar effects can be expected from mysids. One reason that diel migrants may be especially effective at cross-isopycnal mixing is that, unlike shear-driven turbulence in the stratified ocean, swimming is directed in the vertical, causing downward inertial jets during the upmigration and vice versa. A particularly tractable system for estimating, through daytime-collected egesta, the mysid contribution to habitat coupling was identified by Carola et al. (1993), who worked with mysids that migrate horizontally out of a submarine cave at night and return during the day, allowing collection of faecal pellets in simple sediment traps set in the cave. Such submarine caves are shut off from normal vertical particulate fluxes as well as being sheltered from normal horizontal particulate fluxes through the obvious flow obstruction. They are generally considered oligotrophic. Coma et al. (1997) estimated that the 756-m3 cave during the day housed 1–12 million mysids over the seasons of their year-long study (peaking in spring). They estimated that the population’s daily import to the cave through faecal deposition varied seasonally between 20 and 407 g dry wt of particulate organic matter, 2–21 g C and 0.5–2.7 g N. Most pellets were released within 4.5 h after the mysids’ sunrise return. The pellets are remarkably labile, with 20–50% of both C and N released in dissolved form within 2 h after egestion, and they account for previous inabilities to reconcile biological oxidation demand in such caves. Although it is a wonderful demonstration of intense habitat coupling between the pelagic environment of the nearshore Mediterranean and a cave environment, the results are difficult to generalise to sediment-dwelling mysids and their benthicpelagic coupling. The cave dwellers apparently do not feed during the day, and their nightly diet remains obscure. Scanning electron microscopic examination of the pellets revealed no animal and few phytoplankton remains, prompting Coma et al. (1997) to consider them to be detritivores, but the lability of the pellets is then particularly puzzling. Possibilities compatible with the observed detrital remains in the pellets are a diet rich in soft-bodied protists captured by feeding on marine snow or rich in soft-bodied meroplankton (David et al. 2006b). Dominating the holoplankton Recent acoustic estimates of abundance call for renewed attention to mysid migrations. Two geographically widely separated studies (Kringel et al. 2003, Taylor et al. 2005) found that the water column during emergence was completely dominated by mysids, that is, that the mysid contribution to nighttime standing stock exceeded daytime standing stocks of macrozooplankton by an order of magnitude (Figure 3). Although widely separated, the environments share many similarities. Both are in productive, shallow (10- to 20-m) regions of fjords that experience little dilution by freshwater runoff, so whether and how deep these kinds of abundances extend over the continental shelf is an obvious question. Another issue is whether acoustic methods would reveal much higher abundances in those estuarine environments where high mysid abundances are already known. Midnight sinking was noted in many of the contour plots of abundance versus depth and time made by Macquart-Moulin & Ribera Maycas (1995) for pelagic mysids. Midnight sinking in mysids has been observed at least since the classic study of Neomysis americana in Narragansett Bay by Herman (1963). Often but not always, mysids that emerge tend to be less abundant in near-surface layers near the middle of the night than just after sunset or just before dawn. In some cases, a clear mid-depth concentration accounts at least in part for this change (e.g., Herman 1963, the second 113

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Figure 3 Changes in integrated water-column abundance derived from acoustic backscatter showing overwhelming dominance by emergent animals. (A) Column scattering strength at 265 kHz from West Sound, Orcas Island, Washington, in ~20 m of water. (From Kringel et al. 2003. With permission from the American Society of Limnology and Oceanography, Inc.) Horizontal dotted lines connect median column scattering strengths between and during emergence events, showing a 14-fold increase during emergence. The dashed oval shows apparent midnight sinking (higher scattering strengths on both sides of a local minimum during emergence. The first full day of the data record was 27 August 1995. (B) Column-integrated biovolumes derived by acoustic inversion for the Damariscotta River estuary, mid-coast Maine, a shallow fjord. Bottom depth is approximately 10 m, and the large emergence events that begin at the vertical dashed lines are cued by the tides. (From Taylor et al. 2005, their Figure 3. With permission of the Estuarine Research Federation.) Column-integrated standing stocks here also often display the molar- (tooth-) shaped structure with a local minimum (dashed oval) and are 6-fold higher during emergence than during the day (Taylor et al. 2005). The first full day of this record was 15 August 2002.

depth interval in the 4–5 April samples of his Figure 7; Macquart-Moulin & Ribera Maycas 1995, bottom panel of their Figure 5 for Anchialina agilis). Anchialina agilis generally shows dusk and dawn capture peaks in epibenthic sledge samples as well, but no evidence of a midnight return all the way to the sea bed (Dauvin et al. 2000). Drivers of midnight sinking in mysids are not well known, but satiety and predator evasion have been suggested in other taxa, and more recently midnight sinking has been shown to promote retention of Calanus spp. in model results for one inland sea 114

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(Emsley et al. 2005). It is worth remarking again that navigation through use of the polarised light field should be most reliable both near the surface and near dawn and dusk, as one potential contributor to surface congregation at those times. Lending trophic and dynamic stability Although they once were thought to have a destabilising effect on communities, recent and more realistic, non-linear, non-equilibrium theory suggests an important stabilising role for omnivores (McCann & Hastings 1997, Emmerson & Yearsley 2004) that has been confirmed in experiments (Holyoak & Sachdev 1998). Omnivory is an obvious advantage when a favoured resource becomes scarce, and multiple advantages accrue from eating one’s competitors for limiting resources. Less obviously and more paradoxically, species that are eaten by many predators may suffer lower total predation intensity (Montoya et al. 2006). The shelf ecosystems in which mysids participate have high connectance (Link 2002, Dunne et al. 2004), but mysids have more connections over more trophic levels than does the average member of even those highly connected food webs. In shallow water, mysids contribute in a major way to multichain omnivory, linking organic matter that originates from benthic and pelagic primary production; theory originally developed for lakes suggests that this linkage is particularly stabilising (Vadeboncoeur et al. 2005). By being food for pelagic as well as benthic fishes and by consuming both planktonic and benthic primary and secondary production and detritus, mysids not only link benthic and pelagic food webs but also link resources with different inherent timescales. The latter linkages reduce synchrony and overshoot in the populations constituting those resources, identifying another of the mechanisms through which omnivores stabilise food webs (Rooney et al. 2006). The northwest Atlantic shelf ecosystem has been disturbed at such high frequency and high intensity for so long that it has not remained stable, with the notable crash of the groundfish fishery (Link 2002, Choi et al. 2004). Although offshore banks have shown recovery of herring (Clupea harengus) from about 1993 (Fogarty & Murawski 1998), some coastal spawning stocks have not recovered from overfishing or environmental degradation (Smedbol & Stephenson 2001). Cascading trophic effects from the groundfish collapse have been observed, with northern shrimp (Pandalus borealis) and snow crab (Chionoecetes opilio) apparently experiencing release from predation (Frank et al. 2005). A hint of the potentially stabilising effect of mysids comes from the conjecture that they likely experienced a release from predation by benthic predators during the infamous cod (Gadus morhua) crash in 1993 (Choi et al. 2004) and may have experienced some release from herring predation as well. Juvenile cod captured in the southern Gulf of St. Lawrence shifted after 1990 from feeding on euphausiids to feeding on mysids, perhaps reflecting population expansion in mysids, and as of 2000 had not shifted back (Hanson & Chouinard 2002).

Reasons why mysids have been underappreciated Problems of sampling The most obvious reason why mysids are not better understood is the difficulty of making total areal (m−2) abundance estimates. It is a problem greatly compounded by simultaneous and (or) sequential occupation of multiple habitats by mysids. Clutter & Anraku (1968) published a photograph showing that information can be transmitted through a mysid school to turn it away from an approaching plankton net. Lasenby & Sherman (1991) invoked the same explanation for greater capture in vertically operated traps than in trawls. Fleminger & Clutter (1965) took oblique plankton tows through a laboratory tank containing mysids (≥95% Metamysidopsis elongata) and captured significantly more individuals in the dark than in the light. They noted, however, that they lacked 115

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observations to distinguish whether the difference was due to visual avoidance by the mysids or to their potentially broader vertical distribution in the dark (the latter documented by Clutter 1969 in the field). Eleftheriou & Holme (1984) suggested that a 10% sampling efficiency is a reasonable estimate for total macrofauna captured by epibenthic sledges. Emergence traps (e.g., Kringel et al. 2003) may also be biased to an unknown degree. Traps designed to catch emergent individuals alter cues and may induce greater or lesser emergence than would occur in the absence of the trap. Capture efficiency of emergent individuals is also unknown. Ribes et al. (1996) compared abundance estimates based on faecal recovery in the aforementioned cave setting with net tows by divers and found a 10-fold difference, with the net-based estimates being lower. A rare estimate of mysid sampling efficiency based on independent sampling with several methods was that of Carlton & Hamner (1987) from a coral reef lagoon. They found epibenthic sledge efficiency (relative to the most efficient sampler, a trap operated by divers) for mysids to be between 1% and 10%. Because nocturnally emerging mysids in coastal waters stay in the relative dark around the clock, often in turbid waters, it is difficult to imagine how to undertake a complete census of a population analogous to that carried out by Carlton & Hamner (1987). Capture efficiency is certain to vary with life stage and species of mysid and likely with whether they are schooling at the time of sampling, so the purpose of this short review of net and trap sampling clearly is not to find or endorse a fixed estimate of sampling efficiency but rather to indicate that most mysid sampling based on nets is likely to provide gross underestimates. One underlying reason is high burst-swimming speed (caridoid escape reaction) and intermediate size (order of 1 cm): fast nets in order to achieve reasonable filtration efficiencies typically use meshes too large to capture mysids, whereas fine-meshed nets to achieve reasonable filtration efficiencies are typically towed too slowly to capture mysids efficiently. For species that release eggs or weakly swimming larvae into the plankton, slowly towed nets or plankton recorders will still reveal the presence of large populations (e.g., Sameoto 2001). For mysids and other peracarids that brood young, such gear will not sample adequately, especially if newly released juveniles initially are benthic. When most places contain few individuals and a few places contain many mysids, a small number of samples is unlikely to encounter the high concentrations of mysids. Although precise estimates of mysid mean areal abundance would still be useful in evaluating their importance in the ocean economy (e.g., in determining whether they must be included in estimates of secondary production, nutrient regeneration and vertical fluxes), the more aggregated a population is, the less relevance mean abundances have to issues such as encounter rates and behaviours (Omori & Hamner 1982). Direct observations by divers find mysid swarms up to densities of nearly 600 l−1 (6 × 105 m–3). Such dense swarms are usually dominated by a single species but may be joined by several (Ohtsuka et al. 1995). Instead of focusing on mean abundance it may make more sense to be concerned about the fraction of space occupied by swarms and the frequency with which any given place is occupied by a swarm. A simple exercise demonstrates several aspects of the mysid-sampling problem. For Anchialina agilis, because the entire population appears to emerge at night, it would appear to be feasible to estimate total areal abundance by vertically integrating depth-specific abundance estimates. For the points near 2020 h on 11 December for male A. agilis in the 60-m water column as depicted by Macquart-Moulin & Ribera Maycas (1995, their Figure 4) integrating by linear interpolation between the four depths sampled yields an areal abundance of ~15.4 males m−2. For females plus juveniles on the same night, two sections are plotted (their Figure 5) that show peak abundances at about 0500 h of ~3 and ~15.4 ind. m−2, respectively, for an average areal estimate for females and juveniles of ~9 ind. m−2. The sum (total of males plus females and juveniles) exceeds typical, sledge-estimated abundances for the species, and itself is likely an underestimate because of net avoidance by pelagic A. agilis, but could be an overestimate of local benthic areal abundance during the day if there is significant local horizontal convergence during emergence. 116

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Acoustic estimates of abundance based on vertically integrated biovolumes and of migration rates based on changes in vertically resolved biovolumes are also underestimates of unknown severities. A continuing issue with acoustic estimates of organism abundance is individual target strength, particularly for elongate organisms with complex morphologies, because their target strengths vary with orientation relative to the transducer, greatly increasing the uncertainty of abundance estimates made through acoustic inversion (e.g., Amakasu & Furusawa 2005, Lawson et al. 2006). Timevarying polarizations and direction changes of swarms and schools clearly compound this problem, but acoustic methods are more robust in biological application than some of the complexities in acoustic inversion might suggest (Benoit-Bird & Au 2002). A more fundamental problem, often opined (Pearre 2003), is that methods that infer migration from changes in spatial distributions are unable to detect migrations that do not cause net change (Figure 4). Thus it is not known to what extent acoustic observations of Neomysis kadiakensis (e.g., Kringel et al. 2003) or N. americana (e.g., Abello et al. 2005, Taylor et al. 2005) reflect individuals staying in the water column for hours at a time versus frequently exchanging places with benthic members of the same population, and it is not known what fraction of the total population fails to migrate at all. Mysid species and life stages differ in this regard, as reflected in near-surface and near-bottom or nearshore and offshore samples taken at different times of day. Acoustic methods based on backscatter intensity in principle could be used to obtain data fairly close to the bottom by burying an upward-looking device. Besides the logistical problems, however, most transducers have non-ideal near-field effects, and TAPS (Tracor Acoustic Profiling System, now under the auspices of BAE Systems, San Diego, California) on this account does not collect data closer than 37.5 cm from its transducers. Conversely, down-looking geometries (e.g., Greenlaw et al. 2004) are effectively ‘blinded’ in the lowermost one or two range bins by the high backscatter intensity from the bottom. Use of split-beam, dual-beam and multibeam acoustics, generating the acoustic equivalent of binocular vision and giving some capability of tracking individuals, promises at long last to reveal individual zooplankton behaviours (Smith et al. 1992, Kaufmann et al. 1993, De Robertis et al. 2003). These methods do not overcome interference from strong bottom scattering, but they should allow individual acoustic target strengths and trajectories of individuals to be determined from stable bottom platforms, at least when current speeds are small and acoustic sampling intervals are short. Each sampling method will need to be used for its strengths and to remedy the weaknesses of others. Acoustics have the clear advantage in spatial and temporal resolution (e.g., Figure 5), but have the generic problem of being poor at resolving identities. When species diversity is low, however, acoustic methods can be sufficient for discrimination (David et al. 1999), and shape and biomechanical properties that are detectable acoustically show promise of providing better discrimination in the future. Acoustic methods excel with their high resolution in both space and time at pinpointing locations and times of interest for sampling by other means (e.g., Figure 6). Difficulty in modelling Whereas high, flow-driven horizontal flux over the bottoms they inhabit is an important component of the ‘umwelt’ of mysids that emerge in coastal environments, it compounds the difficulties of simulation. It is no accident that many of the citations given here are for studies done in closed systems (lakes) and semi-enclosed systems (estuaries) where effects are much easier to calculate and model, rather than the nominal coastal environments of primary interest. Open-shelf systems are more difficult to constrain in both measurements and models. Further, the same infidelity to habitat that makes abundance estimates difficult also complicates study in analog laboratory systems. Although smaller tanks have yielded valuable observational data on taxa without extensive migrations (Fosså 1986), a much larger system (e.g., Conover & Paranjape 1977) would be needed to 117

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Figure 4 A simple demonstration of the potential for radically different mysid behaviours to produce similar patterns of vertical change in abundance over large regions of the habitat and the consequent need to develop methods for tracking individuals during migration. Simple, heuristic Markov models (cf. Kemeny & Snell 1960, Jumars et al. 1981) were set up under two different sets of hypothetical behaviours. The boxes in panels A and B represent a 2-dimensional section in the onshore–offshore direction, shoaling to the right. Greyed boxes (A, B) represent a hyperbenthic environment, with white boxes being in the water column. In both model runs (see also next page), all animals began in the box labelled 0 in panel B. Time steps were 10 min. In the first run, all transition probabilities were set to 1/8; that fraction of individuals in each box moved to the adjacent box, and the fractions in (A) represent the proportion that stayed in the box during one time step. After a long time with this transition matrix, individuals would become uniformly distributed. At T = 6 h, however, the original source box became an absorbing state (transitions out were prohibited) representing recognition of the habitat by the model animals. In addition, all transition probabilities that reduced the number of steps back to the original source box were made five times larger than those leading away. (Continued on next page.)

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Figure 4 (continued) That process led to the return of 95% of all individuals in 6 h. This first scenario can be construed as a broadening of the depth distribution through very active random transfer among compartments, with a biased random walk bringing the animals back. Arrows in panel C represent the cycle that emergence would follow from start to finish. If the cycle is repeated (dashed arrow), results of the slightly different starting condition are not perceptibly different. In the second scenario (D) the same fractions remained in each compartment as shown in (A). Initially, all transitions moving a greater number of steps away from the same source box were set at 1/20 (with zero probability of moving toward the source), except that downward transitions were ruled out (also set at zero) and the model was run for 6 h before reversal of behaviour (moving away from the original source set to zero probability and moving toward set to 4/25). In this phase, the initial source compartment was again made perfectly absorbing. The second scenario can be construed as much slower, deliberate navigation to and from nighttime feeding areas. Because net movement among boxes is not radically different between the two scenarios (except for deep regions in panel D that are effectively unreachable), neither is the depth-time distribution of individuals. Again 95% of individuals returned after 72 time steps, and running the cycle again with this starting condition produces results that are not perceptibly different from starting all individuals in the original source compartment. Animals in the first scenario do a great deal more moving among locations per unit of time and therefore would likely have much higher encounter rates with predators. Future methods need to differentiate net from gross migration rates. Note that while neither scenario includes any sinking at all, the pattern of abundance in the surface compartment above the source shows what might be interpreted as midnight sinking, that is, higher abundances early and late in the migration cycle than in its middle.

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Figure 5 (See also Colour Figure 5 in the insert following page 344.) Resolution achievable acoustically without resolving individual mysids, showing some of the diversity that can be encountered in emergence. The two time series have been aligned so that midnight occurs in both at the same location on the abscissa. Regularity of nightly emergence in the West Sound time series (formed from data taken every 2 min in 25-cm range bins; top panel from Kringel et al. 2003. With permission of the American Society of Limnology and Oceanography, Inc.) is stunning, and the descents are often more organised than the initial ascent, a phenomenon herein called the Dracula effect (Abello et al. 2005). The data from the Damariscotta estuary have even higher resolution (taken every minute with 12.5-cm spatial resolution). Low tides occurred near noon in the West Sound series, and the reflection from the water surface is evident as bright red patches of high backscatter. The Damariscotta time series shows both low tides of the day, with the red extensions from the surface being a combination of fish aggregations and bubbles injected by breaking wavelets from the afternoon sea breeze. The Damariscotta series shows multiple emergence events per night. The first emergence events after dark are light cued (Abello et al. 2005), whereas the largest events begin at peak tidal flow speed after dark (Taylor et al. 2005). (Bottom panel from Taylor et al. 2005. With permission of the Estuarine Research Federation.)

Figure 6 (opposite page; see also Colour Figure 6 in the insert.) Acoustic methods that do not resolve individual mysids can also be used to gather information on group ascent and descent velocities and times of departure from and return to the sea bed. (After Kringel et al. 2003, from the same 1995 dataset presented at the top of Figure 5. With permission of the American Society of Limnology and Oceanography.) Leading edges of the ascent can be recognised as the first and the last pixels above background backscattering levels at each height above bottom (white circles). Slopes of the linear regressions yield ascent and descent velocities, and intercepts provide objective start and stop times of emergence. Modal abundance values (blue X marks, colour version) represent the behaviours of a larger fraction of the emergent population, but again only net migration rates can be visualised from measures of total backscatter.

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provide realistic prey distributions and allow migration. Moreover, mysids are notoriously sensitive to light exposure and take considerable time to recover physiologically, and presumably behaviourally, from unnatural levels (e.g., Attramadai et al. 1985, Lindström et al. 1988). Red-light viewing to avoid light-induced artifacts (e.g., Fosså 1986) rapidly becomes less practical at long range because red light has a high absorption coefficient in water.

Challenges and opportunities A continuing challenge is to produce an effective, convincing census of shelf mysid populations (abundance versus location versus time) that misses neither migrating nor non-migrating members. No one method yet attempted appears to be a panacea in this regard because different methods have different strengths and weaknesses in different habitats. In this review, emphasis has been placed on the challenges in measuring the vertical component of migration and the coupling of benthic with pelagic habitats because enough data can be gathered to review them. The horizontal component provides many additional challenges and opportunities. It is obviously a key feature of mysid migrations in and out of caves (e.g., Carola et al. 1993, David et al. 1999) and vegetation (e.g., Wittman 1977, Mattila et al. 1999). Whereas organisms with clear structural, spatial refuges from predation can return to them when risk is high, organisms without a structural spatial refuge adopt other means of reducing risk. Besides the obvious tactic of staying in the dark, emergent mysids can alter schooling patterns and (or) reduce their feeding rates to reduce risk by evading pursuit or detection, respectively (Ritz 1994, Hamren & Hansson 1999). Mysids are documented to change behaviour via both visual and chemical cues from predators (Hamren & Hansson 1999, Cohen & Ritz 2003, Linden et al. 2003). Schooling for mysids that have evolved schooling behaviours may be more effective at predator evasion than is their entry into vegetation because such entry breaks up schools into more easily taken, smaller groups (Flynn & Ritz 1999), and swarm-formers versus species using structural refugia show the expected responses (Linden et al. 2003). Burrowing or burying during the day by emergent mysids appears to be an intermediate solution, providing mechanical, optical and perhaps chemical refuge from sensory detection by predators, but it probably has costs of reduced feeding capabilities relative to mysids feeding at the sediment-water interface. Mysid schooling may be less effective against predators that themselves school (Foster et al. 2001) and may incur greater risk from suspensionfeeding animals that do not pursue individual prey but filter them in bulk, such as gray whales (Eschrichtius robustus). School size appears to depend on a dynamic optimum solution between reduction of risk and enhancement of feeding success (Ritz 1994). Among questions that merit attention are whether mysids by schooling during emergence and re-entry enhance their mean individual rates of capture of emergent and holoplanktonic copepods and whether those in poorest nutritional status take greater risks by emerging earlier in the night as has been demonstrated for some diel migrators among the holoplankton (Hays et al. 2001). Near shore, where physical gradients in nearly all directions and over time are usually strong, gradients in risk and potential gain run in all directions but certainly covary strongly with distance from shore, water depth and time of day (e.g., Takahashi et al. 2004). Diel horizontal migration has not received much recent attention in shallow-water biological oceanography, whereas diel horizontal differences in abundance are so commonly documented among freshwater crustaceans and rotifers that the term ‘shore avoidance’ was coined when the behaviour of swimming toward open water in the morning and a putative orientation mechanism in the form of polarised light were reported (Siebeck 1968a,b). Curiously, marine mysid capability to detect polarisation was documented a decade earlier (Bainbridge & Waterman 1957), but early marine work focused more on physiology than on ecological implications. More recently, Goddard & Forward (1991) documented

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grass shrimp orientation mediated by polarisation and aiming them away from shore during daylight, likely avoiding littoral predators. Test results are consistent with several predictions based on predator avoidance in fresh waters (e.g., Wicklum 1999). Recent experimental verification of homing capabilities in marine mysids (Twining et al. 2000) and clarification of submarine polarisation showing potential utility for orientation to >200 m depth (Waterman 2005) promise renewed interest. Notably, horizontal tilt of the polarisation e-vector is greatest near dawn and dusk, giving the best onshore–offshore information then. Benefits of homing to particular reef, cave or macrophyte sites are obvious, but information on relocation of mysids from horizontally (alongshore) more uniform environments is scarce. Wittman (1977), however, painted mysids in his diving study and remarked that he could find them up to 12 days later (the intermolt period for one of the dominant species). Further mark-recapture results might be particularly informative about homing and might also be revealing about population sizes if the relevant parameters can be estimated. In terms of risks, many also vary over timescales beyond the diel. Over 6 yr of observation, we have observed Neomysis americana to be present in our local, shallow fjord (Damariscotta River estuary, with little freshwater input) weeks before any appreciable vertical migration begins. Nocturnal emergence does not start until late May or early June, coincident with the termination of the annual alewife (Alosa pseudoharengus) run upstream (P.A. Jumars, personal observations). A mechanistic relationship remains to be established, but a time-varying predation risk at midlatitudes from seasonal cycles of clupeids is nearly universal. In terms of spatiotemporal gradients of predators, recent acoustic results document that, in a setting with a narrow shelf, many mid-water animals migrate strikingly close to shore at night, with onshore–offshore speeds exceeding those of their vertical excursions by three orders of magnitude (Benoit-Bird et al. 2001, Benoit-Bird & Au 2004). Although wider shelves will impede mid-water participants in diel migration, analogous phenomena in diel predator movemements are expected even on broad shelves. For emergent mysids that time-share food resources and predation risks between pelagic and benthic habitats, the likelihood that optimal benthic and pelagic habitats occur in the same depth of water seems remote. What is perhaps the greatest animal migration on the planet has recently been revealed acoustically and comprises horizontal movements of great shoals of fishes over the continental shelf (Makris et al. 2006); diel patterns are not yet established. It is easy to predict with confidence that the horizontal and coastal equivalent of Vinogradov’s ladder (Vinogradov 1962) will be documented in the observatory era of oceanography and that mysids will constitute several rungs. Combined gradients in predation risk and resources can produce confusing patterns of resource use when interpreted according to resource availability alone, particularly for omnivores that have multiple feeding options (Morris 2005). In an innovative and ambitious contribution, Speirs et al. (2002) predicted and dissected the movements of intertidal mysids as functions of both resource and predator effects and time, through population-level modelling of distributions. It could be useful to repeat their measurements of response to sediment organic quality using a method more sensitive to the labile, digestible component of sediments (Mayer et al. 1995), which in general is not well correlated with total organic carbon (Dauwe et al. 1999) and using only the surficial and resuspendable materials (Mayer et al. 1993) to which epibenthic mysids are exposed. A quickly advancing, alternative approach to modelling organisms that use multiple habitats also appears to merit closer examination for potential application to mysids. Given the long history of research on diel vertical migration in zooplankton, prospects for rapid advance to predictive understanding of emergence by reductionist testing of the same or variant collections of hypotheses on mysids or other emergers appear bleak. As an alternative, IBM is a subset of agent-based modelling within complexity theory (Auyang 1998) and has several characteristics that distinguish it from classical reductionist or holistic approaches (Grimm & Railsback 2005, p. 55):

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•

•

•

“Theory is neither holist (system-level) nor reductionist (individual-level). We do not assume that ecological systems can be understood from only the system level, but we also do not assume that a system is simply the sum of its individual parts. Systems have properties of completely different types than the properties of individuals, and theory must explain these system properties. Theory must therefore be multilevel, linking traits of individuals to properties of the system. We are not interested in understanding all aspects of individual behavior but instead are interested in developing models of individuals that explain important system properties. Observational and experimental science at both the individual and system level is the basis for theory development. Such empirical science is important both for discovering the phenomena driving the system and for testing theories.”

IBM is also an obvious approach toward understanding of emergence because the constellation of traits associated with emergent mysids overlaps so broadly with published success stories of IBM in explaining and predicting schooling and foraging behaviours under varying risks, dispersal, habitat usage and local reproductive success (Grimm & Railsback 2005, Chapter 6). What is particularly promising about this approach is that it frequently predicts very different consequences in different environments, as would appear necessary in the case of Neomysis americana. IBMs have already been used in other marine applications (Miller et al. 1998, Grimm et al. 1999, Crain & Miller 2001, Leising 2001). The variety of IBM that would appear appropriate to mysids assumes that individuals choose behaviours that on average enhance their fitness, and those behaviours are termed ‘adaptive traits’ (Zhivotovsky et al. 1996). A successful IBM is generally recognised through correct prediction of often-subtle spatial patterns of distribution and habitat usage (Dieckmann et al. 2000, Grimm & Railsback 2005). Both from the standpoint of understanding observations and making models, the words of Pearre (2003) resonate: “Without knowing the actual movements of individuals it seems unlikely that we will be able to understand their causes, nor the effects of vertical migrations on the environment or on the migrators themselves”.

Acknowledgements I am grateful to the Office of Naval Research (grant N00014-03-1-0776) for generous funding of my acoustic research on mysid migrations and to Van Holliday and Charles Greenlaw of BAE Systems for perpetual help and encouragement with acoustic approaches. Much of this synthesis comes from the work of four master of science students: Kelly Kringel, Heather Abello, Leslie Taylor and Mei Sato. The manuscript benefitted considerably from comments by K. Dorgan and careful editing by Prof. R.J.A. Atkinson. I thank Dennis Allen and Harmon Brown for sharing their data and ideas about Neomysis americana in South Carolina and on Georges Bank, respectively.

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HABITAT COUPLING BY MID-LATITUDE, SUBTIDAL, MARINE MYSIDS Tararam, A.S., Wakabara, Y. & Flynn, M.N. 1996. Suprabenthic community of the Cananeia lagoon estuarine region, southeastern Brazil. Cahiers de Biologie Marine 37, 295–308. Tattersall, W.M. 1938. The seasonal occurrence of mysids off Plymouth. Journal of the Marine Biological Association of the United Kingdom 23, 43–56. Taylor, L.H., Shellito, S.M., Abello, H.U. & Jumars, P.A. 2005. Tidally cued emergence events in a strongly tidal estuary. Estuaries 28, 500–509. Thorne, R.E. 1968. Diel variations in distribution and feeding behavior of Mysidacea in Puget Sound. M.S. thesis, University of Washington, Seattle. Tominaga, O., Uno, N. & Seikai, T. 2003. Influence of diet shift from formulated feed to live mysids on the carbon and nitrogen stable isotope ratio (∂13C and ∂15N). Aquaculture 218, 265–276. Tudela, S. & Palomera, I. 1997. Trophic ecology of the European anchovy Engraulis encrasicolus in the Catalan Sea (northwest Mediterranean). Marine Ecology Progress Series 160, 121–134. Twining, B.S., Gilbert, J.J. & Fisher, N.S. 2000. Evidence of homing behavior in the coral reef mysid Mysidium gracile. Limnology and Oceanography 45, 1845–1849. Vadeboncoeur, Y., McCann, K.S., Vander Zanden, M.J. & Rasmussen, J.B. 2005. Effects of multi-chain omnivory on the strength of trophic control in lakes. Ecosystems 8, 682–693. Vallet, C. & Dauvin, J.-C. 1998. Composition and diversity of the benthic boundary layer macrofauna from the English Channel. Journal of the Marine Biological Association of the United Kingdom 78, 387–409. Vallet, C. & Dauvin, J.-C. 2001. Biomass changes and bentho-pelagic transfers in the English Channel. Journal of Plankton Research 23, 903–922. Vallet, C., Zouhiri, S., Dauvin, J.-C. & Wang, Z. 1995. Variations nycthémérales de l’abondance de la faune démersal en Manche. Journal de Recherches Océanographiques 20, 94–102. van der Baan, S.M. & Holthuis, L.B. 1971. Seasonal occurrence of Mysidacea in the surface plankton of the southern North Sea near the ‘Texel’ lightship. Netherlands Journal of Sea Research 5, 227–239. Viherluoto, M., Kuosa, H., Flinkman, J. & Viitasalo, M. 2000. Food utilisation of pelagic mysids, Mysis mixta and M. relicta, during their growing season in the northern Baltic Sea. Marine Biology 136, 553–559. Viherluoto, M. & Viitasalo, M. 2001. Effect of light on the feeding rates of pelagic and littoral mysid shrimps: a trade-off between feeding success and predation avoidance. Journal of Experimental Marine Biology and Ecology 261, 237–244. Viitasalo, M., Flinkman, J. & Viherluoto, M. 2001. Zooplanktivory in the Baltic Sea: a comparison of prey selectivity by Clupea harengus and Mysis mixta, with reference to prey escape reactions. Marine Ecology Progress Series 216, 191–200. Vinogradov, M.E. 1962. Feeding of the deep-sea zooplankton. Rapports et Procès-Verbaux des Réunions du Conseil International pour l’Exploration de la Mer 153, 114–119. Visser, A.W. & Kiørboe, T. 2006. Plankton motility patterns and encounter rates. Oecologia 148, 538–546. Voicu, G. 1981. Upper Miocene and recent mysid statoliths in central and eastern Paratethys. Micropaleontology 27, 227–247. Wahle, R.A. 1985. The feeding ecology of Crangon franciscorum and Crangon nigricauda in San Francisco Bay, California. Journal of Crustacean Biology 5, 311–326. Wang, Z. & Dauvin, J.-C. 1994. The suprabenthic fauna of the infralittoral fine sand community from the Bay of Seine (eastern English Channel) — composition, swimming activity and diurnal variation. Cahiers de Biologie Marine 35, 135–155. Warkentine, B.E. & Rachlin, J.W. 1989. Winter offshore diet of the Atlantic silverside, Menidia menidia. Copeia 1989, 195–198. Waterman, T.H. 2005. Reviving a neglected celestial underwater polarization compass for aquatic animals. Biological Reviews 81, 1–5. Webb, P., Perissinotto, R. & Wooldridge, T.H. 1987. Feeding of Mesopodopsis slabberi (Crustacea, Mysidacea) on naturally occurring phytoplankton. Marine Ecology Progress Series 38, 115–123. Webb, P., Perissinotto, R. & Wooldridge, T.H. 1988. Diet and feeding of Gastrosaccus psammodytes (Crustacea, Mysidacea) with special reference to the surf zone diatom Anaulus birostratus. Marine Ecology Progress Series 45, 255–261. Webb, P. & Wooldridge, T.H. 1990. Diel horizontal migration of Mesopodopsis slabberi (Crustacea: Mysidacea) in Algoa Bay, southern Africa. Marine Ecology Progress Series 62, 73–77.

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PETER A. JUMARS Whiteley, G.C., Jr. 1948. The distribution of larger planktonic Crustacea on Georges Bank. Ecological Monographs 18, 233–264. Wicklum, D. 1999. Variation in horizontal zooplankton abundance in mountain lakes: shore avoidance or fish predation? Journal of Plankton Research 21, 1957–1975. Wigley, R.L. 1967. Comparative efficiencies of Van Veen and Smith-McIntyre grab samplers as revealed by motion pictures. Ecology 48, 168–169. Wigley, R.L. & Burns, B.R. 1971. Distribution and biology of mysids (Crustacea, Mysidacea) from the Atlantic coast of the United States in the NMFS Woods Hole collection. Fishery Bulletin, National Oceanic and Atmospheric Administration of the United States 69, 717–746. Wigley, R.L. & Theroux, R.B. 1981. Atlantic continental shelf and slope of the United States — macrobenthic invertebrate fauna of the Middle Atlantic Bight Region — faunal composition and quantitative distribution. Geological Survey Professional Paper 529-N, N1–N198. Wilhelm, F.M., Hamann, J. & Burns, C.W. 2002. Mysid predation on amphipods and Daphnia in a shallow coastal lake: prey selection and effects of macrophytes. Canadian Journal of Fisheries and Aquatic Sciences 59, 1901–1907. Williams, A.B. 1972. A 10-year study of meroplankton in North Carolina estuaries: mysid shrimps. Chesapeake Science 13, 254–262. Williams, A.B., Bowman, T.E. & Damkaer, D.M. 1974. Distribution, variation and supplemental description of the opossum shrimp Neomysis americana (Crustacea: Mysidacea). Fishery Bulletin, National Oceanic and Atmospheric Administration of the United States 72, 835–842. Wing, B.L. & Barr, N. 1977. Midwater invertebrates from the southeastern Chukchi Sea: species and abundance in catches incidental to midwater trawling survey of fishes, September–October, 1970. National Oceanic and Atmospheric Administration of the United States, Technical Report NMFS SSRF-710, 1–43. Winkler, G., Dodson, J.J., Bertrand, N., Thivierge, D. & Vincent, W.F. 2003. Trophic coupling across the St. Lawrence River estuarine transition zone. Marine Ecology Progress Series 251, 59–73. Winkler, G. & Greve, W. 2004. Trophodynamics of two interacting species of estuarine mysids, Praunus flexuosus and Neomysis integer, and their predation on the calanoid copepod Eurytemora affinis. Journal of Experimental Biology and Ecology 308, 127–146. Wittman, K.J. 1977. Modifications of association and swarming in North Adriatic Mysidacea in relation to habitat and interacting species. In Biology of Benthic Organisms, B.F. Keegan et al. (eds). Oxford: Pergamon Press, 605–612. Wittman, K.J. 2001. Centennial changes in the near-shore mysid fauna of the Gulf of Naples (Mediterranean Sea), with description of Heteromysis riedli sp. n. (Crustacea, Mysidacea). Pubblicazioni della Stazione Zoologica di Napoli I: Marine Ecology 22, 85–109. Wittman, K.J. & Ariani, A.P. 1996. Some aspects of fluorite and vaterite precipitation in marine environments. Pubblicazioni della Stazione Zoologica di Napoli I: Marine Ecology 17, 213–219. Yamamoto, M., Makino, H., Kobayashi, J.-I. & Tominaga, O. 2004. Food organisms and feeding habits of larval and juvenile Japanese flounder Paralichthys olivaceus at Ohama Beach in Hiuchi-Nada, the central Seto Inland Sea, Japan. Fisheries Science 70, 1098–1105. Yamamoto, M. & Tominaga, O. 2005. Feeding ecology of dominant demersal fish species Favonigobius gymnauchen, Repomucenus spp. and Tarphops oligolepis at a sandy beach where larval Japanese flounder settle in the Seto Inland Sea, Japan. Fisheries Science 71, 1332–1340. Zagursky, G. & Feller, R.J. 1985. Macrophyte detritus in the winter diet of the estuarine mysid Neomysis americana. Estuaries 8, 355–362. Zhivotovsky, L.A., Bergman, A. & Feldman, M.W. 1996. A model of individual adaptive behavior in a fluctuating environment. In Adaptive Individuals in Evolving Populations, R.K. Belew & M. Mitchell (eds). Santa Fe, New Mexico: Santa Fe Institute, 131–153 (Santa Fe Institute Studies in the Sciences of Complexity 26). Zouhiri, S. & Dauvin, J.-C. 1996. Diel changes of the Benthic Boundary Layer macrofauna over coarse sand sediment in the western English Channel. Oceanologica Acta 19, 141–153. Zouhiri, S., Vallet, C., Mouny, P. & Dauvin, J.-C. 1998. Spatial distribution of suprabenthic mysids from the English Channel. Journal of the Marine Biological Association of the United Kingdom 78, 1181–1202.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 139-172 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES ROBERT S. CARNEY Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, Louisiana, U.S.A. 70803 E-mail: [email protected] Abstract The soft-bottom benthos covers most of the sea floor. Measurement and analysis of the species richness of these habitats are increasingly needed for studies of community regulation and for providing scientific criteria for the conservation of the ocean bottom at all depths. Diversity measures provide an evolving suite of tools that allow benthic ecologists to meet both basic and applied needs. While species diversity is now considered a fundamental aspect of communities and ecosystems, the measurement of benthic diversity did not become commonplace until the late 1960s. Prior to that communities were characterised by representative species with the implicit assumption that minor species components did not warrant detailed analysis. Use of diversity measures in benthic ecology has largely parallelled studies in other ecosystems with an emphasis upon measures that are informative when applied to large amounts of data with high species numbers. Non-parametric indices such as Simpson’s and Shannon’s are widely used along with simple species richness. Logseries and log-normal distributions have been advocated as general neutral models but receive less use. Current research is especially focused upon extrapolation of unsampled species richness and diversity relationships across spatial scales. Major contributions from benthic ecology include the rarefaction of samples to a uniform size, the development of indices that include phylogenetic relationships in diversity estimation and the extrapolation of full species richness from observed values. In meeting scientific and societal needs, benthic ecologists must apply methods that are insightful yet can be simply explained within the resource-policy arena.

Introduction Justification Estimation of diversity has become an integral part of benthic ecology. There is so much recent literature and software available that review may seem unneeded. Benthic ecology is, however, now experiencing a change in the ways that species data are accessed and analytical results used that is both scientific and societal in origin. Both origins require that concepts and estimation of diversity be reconsidered. The greatest scientific change is the increasing accessibility of survey data through open Internet databases. This allows the search for geographic and temporal patterns not anticipated in the original study designs and a search across multiple studies by experts in analysis and theory who may be largely unfamiliar with benthic ecology and the taxonomy of benthic organisms. The second change is societal in the sense that international regulatory policies increasingly mandate the preservation of biological diversity in both marine and terrestrial systems. Benthic ecologists must provide regulators with estimates of diversity that can be explained and defended if these estimates are to serve agencies as the basis for conservation decisions. Thus, the intent of this review is to provide users of databases an explanation of what benthic ecologists have 139

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found and provide benthic ecologists a guide to the changes associated with the shift in terminology from diversity to biodiversity. Contraction of the term biological diversity to biodiversity seems to have originated within the U.S. government environmental management structure and was then progressively used by those ecologists especially interested in conservation biology (Harper & Hawksworth 1994). Along with development of conservation biology, biodiversity began to encompass a much broader concept than species diversity alone and now may be considered a distinct concept or suite of concepts (Hamilton 2005). One marine definition of biodiversity included the variety of genomes, species and ecosystems occurring in a defined region (National Research Council 1995) and followed a similar combination of genetic and ecological perspectives used by Norse and his colleagues (Norse et al. 1986). The official definition of biodiversity as contained in Article 2 of the Convention on Biological Diversity included “variability among living organisms from all sources … within species, between species, and of ecosystems” (United Nations Conference on Environment and Development, 1992). The view adopted in this review is that biodiversity is largely a policy term rather than scientific and its use should be avoided. Efforts to better define biodiversity from a scientific standpoint are needed and reflect conservation biologists’ duty to provide objective tools to managers faced with mandates to preserve biodiversity in marine as well as terrestrial systems (Lubchenco et al. 2003). Presently, however, policy usage of ‘biodiversity’ carries with it many assumptions that have not been proven scientifically such as a link between diversity of ecosystem health (Norse 1993) and ecosystem stability. Notable efforts in ecology to provide management tools were the adoption in benthic ecology of taxonomic indices that weight diversity by phylogenetic differences (Warwick & Clarke 2001) and the search for indicator species to be used in place of more comprehensive diversity assessment. As discussed in the historical review, selection of indicator species bears a strong similarity to the selection of characteristic species during the decades of benthic ecology research prior to any interest in the diversity of bottom communities. ‘Biodiversity informatics’ is the term applied to the growing development and use of databases for diversity studies and is very broadly defined to include biogeography and certain aspects of systematics. Progress and challenges for systems that will provide marine data have been outlined by Costello & Berghe (2006). There is already progress for deep-sea studies starting with data compiled by many French cruises (Fabri et al. 2006) and by many studies conducted in shallow European seas (Costello et al. 2006). Initially, these marine databases can most confidently be used for determining geographic and bathymetric ranges of individual species. As problems of inconsistent and incorrect taxonomy are solved, however, the datasets will be extremely useful for estimating benthic diversity over a wide range of scales.

Structure of the review This review takes a broad historical perspective to examine how benthic ecology has treated diversity from approximately 1870 until the present time with special attention to soft bottoms. Benthic ecologists carried out surveys as early as the 1900s that were similar to the projects of today, but lacked both the modern concepts of diversity and the computational tools to compute indices. However, there are strong similarities between the struggle of early benthic ecologists to simplify discussion of species-rich systems and the search of contemporary conservation biologists for indicator taxa that can be used in the estimation of overall community diversity (Pearson 1994). The mathematics of diversity estimation are treated herein only in sufficient detail to indicate what benthic ecologists do and have done with respect to concepts and data analysis. Only those approaches widely used in or originating in benthic ecology are considered. Texts by Hayek & 140

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Buzas (1997) and Magurran (2004) do an excellent job of focusing upon the major concepts and methods. The former text has somewhat greater mathematical detail, while the latter text provides more information about concept development. Even these recent books are quickly outdated. Methods, concepts and large-scale patterns of diversity with respect to mud bottoms have been considered in highly informative reviews of Gray (2000, 2001, 2002). The information presented herein is intended to compliment these works by taking a broader historical perspective and tracing the use of analytical tools more than by discussing details of many individual results. Unfortunately, all reviews must choose to omit something. The two serious omissions here are (1) the use of evenness measures to compliment diversity and (2) the effect of pollution stress on benthic diversity. Both topics warrant separate treatment in the future. In concluding, recommendations are made as to a future course in benthic ecology that will allow both a better understanding of diversity and an ability to provide managers with useful information.

Basics To avoid contributing to additional confusion, it is necessary to state the concept of diversity used in this review. According to a simple view of systems ecology, there are three types of information about a benthic community (Figure 1). First, an ‘inventory’ is a list of all species and their abundance. Second, a set of interactions among the component species is often represented by a matrix. Third, a set of relationships exists between the fauna and the physical environment. Sampling, identification and enumeration produce the inventory. Determination of fauna-environment relationships can be made through sampling designs that capture variation in sediment type, salinity, temperature, and so on. Assessment of species interactions is the most difficult information to obtain. Certainly, soft-bottom communities are impractical locations to determine the population interaction parameters required by theoretical community matrices (Levins 1968). In some cases, however, associations such as dependence on biogenic structure are obvious and a variety of tools can be used to determine at least a trophic position. The assumption is that the abundance of each species in the inventory can be explained to some extent by the interactions among species and the interactions with the environment. Of these three sets of information, diversity is an attribute of the inventory (Peet 1974). When given a mathematical definition, diversity should afford a parsimonious means of comparing the inventories of different systems. The underlying assumption is that differences in diversity reflect differences in species interactions. Common questions in benthic ecology have been directed to whether ubiquitous gradients of diversity exist with depth, with latitude and with anthropogenic stress. In each case, diversity is a convenient indicator of ecosystem differences. Terminology varies greatly in the larger ecological literature, but most authors take the position advocated by Hill (1973) and Hurlbert (1971). Measures of species diversity (the variety of the inventory) are based on two simple attributes: the number of species (species richness) and the proportional abundances. An effective means of describing the variability of proportional abundance is evenness (i.e.,departure from equal proportions). Using these two attributes, indices can be calculated and used as an overall measure of heterogeneity (Magurran 2004). A somewhat unsettling aspect about species diversity is that all species are treated equally, making no use of additional knowledge about biotic or abiotic interactions and life histories. Failure to treat some species as more important would seem to make a traditional species diversity measure poorly suited to be used for conservation decisions about which communities should be afforded special protections. A partial solution is seen in a recent development in benthic ecology, use of indices of taxonomic distinctness (Warwick & Clarke 2001). Still an attribute of the inventory, these indices make use of additional information about taxonomic position of the component species. The adoption of these indices marks a major change in benthic community analysis. 141

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Sample 8

Sample 9

Sample 10

x1,8 x2,8 x3,8 x4,8 x5,8 x6,8

x1,9 x2,9 x3,9 x4,9 x5,9 x6,9

x1,10 x2,10 x3,10 x4,10 x5,10 x6,10

…

xi,1

Species i

xi,3

xi,2

xi,4

xi,7

xi,6

…

…

…

…

xi,5

xi,9

xi,8

… … … … … …

xi,10 …

x1,k x2,k x3,k x4,k x5,k x6,k …

Sample 7

x1,7 x2,7 x3,7 x4,7 x5,7 x6,7

…

Sample 6

x1,6 x2,6 x3,6 x4,6 x5,6 x6,6

…

Sample 5

x1,5 x2,5 x3,5 x4,5 x5,5 x6,5 …

Sample 4

x1,4 x2,4 x3,4 x4,4 x5,4 x6,4 …

Sample 3

x1,3 x2,3 x3,3 x4,3 x5,3 x6,3 …

Sample 2

x1,2 x2,2 x3,2 x4,2 x5,2 x6,2

Species 1 Species 2 Species 3 Species 4 Species 5 Species 6

Sample k

Sample 1

x1,1 x2,1 x3,1 x4,1 x5,1 x6,1 …

Species-by-sample quantitative data

xi,k

Speciesenvironment factor interactions

Species i

xi,1

xi,2

xi,3

xi,4

xi,5

xi,6

xi,7

xi,8

…

ρ1,m ρ2,m ρ3,m ρ4,m ρ5,m ρ6,m …

… … … … … … …

…

ρ1,8 ρ2,8 ρ3,8 ρ4,8 ρ5,8 ρ6,8

…

ρ1,7 ρ2,7 ρ3,7 ρ4,7 ρ5,7 ρ6,7

…

Factor 8

ρ1,6 ρ2,6 ρ3,6 ρ4,6 ρ5,6 ρ6,6

…

Factor 7

ρ1,5 ρ2,5 ρ3,5 ρ4,5 ρ5,5 ρ6,5

…

Factor 6

ρ1,4 ρ2,4 ρ3,4 ρ4,4 ρ5,4 ρ6,4

…

Factor 5

ρ1,3 ρ2,3 ρ3,3 ρ4,3 ρ5,3 ρ6,3

…

Temperature

ρ1,2 ρ2,2 ρ3,2 ρ4,2 ρ5,2 ρ6,2

…

Salinity

ρ1,1 ρ2,1 ρ3,1 ρ4,1 ρ5,1 ρ6,1

Factor m

Sediment

Species i

Species 6

Species 5

Species 4

Species 3

Species 2

Species 1

Species 1 1 α1,2 α1,3 α1,4 α1,5 α1,6 … α1,j Species 2 α2,1 1 α2,3 α2,4 α2,5 α2,6 … α2,j Species 3 α3,1 α3,2 1 α3,4 α3,5 α3,6 … α3,j Species 4 α4,1 α4,2 α4,3 1 α4,5 α4,6 … α4,j

Species 1 Species 2 Species 3 Species 4 Species 5 Species 6

Depth

Speciespair relation matrix

xi,m

…

…

…

…

…

…

…

…

Species 5 α5,1 α5,2 α5,3 α5,4 1 α5,6 … α5,j Species 6 α6,1 α6,2 α6,3 α6,4 α6,5 1 … α6,j Species i αi,1 αi,2 αi,3 αi,4 αi,5 αi,6 … 1

Figure 1 Basic nature of soft-bottom benthic survey data. Ecology theory takes the position that population levels of individual species in a community are influenced by interactions with the environment, including resource utilisation, and pairwise relationships among species. In application, benthic surveys produce quantitative species-by-sample data according to designs that nest replicates with stations within larger ocean areas. Interactions of species with the environment are often expressed as correlation coefficients and are limited to the few factors included in the sampling design. An actual matrix of the relationships among pairs of species is rarely known, but statistical associations are sometimes developed as substitutes from the species-sample data. Traditionally, species diversity has been seen as a property of the species-by-sample data alone, ignoring the other two types of data.

History From Forbes zones to Petersen communities When benthic studies from the late 1800s through the mid-1900s are reviewed a peculiar situation emerges about use of species diversity. Early hints of interest in diversity existed prior to the advent 142

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of community ecology, but then there was surprisingly little interest during early formative years of community ecology. Finally tremendous new interest began in the 1950s as niche theory and easy computation facilitated inquiry. Certainly, benthic surveys produced inventories in which a few species were common and many more rare, but comments as to this fact are largely absent from about 1900 to 1960. With so much emphasis upon diversity today, it is informative to consider a historical period of very active benthic surveying when the concept seems to have been missing or unimportant. Estimation of species diversity is now associated with quantitative benthic sampling. Toward the end of the 1800s, seafloor studies began the transition from the description of faunal zones based upon qualitative trawl and dredge sampling (Forbes 1859, Mills 1978, Carney 2005) to more quantitative grab and core surveys. Interest in species diversity during qualitative sampling can be seen from the criticism of the CHALLENGER Expedition (1872–1876) by Anton Stuxburg (1883). Stuxburg complained about the lack of synthesis in the largely taxonomic works and specifically suggested that the number of species and the proportions of each be presented trawl by trawl. Possibly accepting these suggestions, the summary of the expedition issued 12 yr later carefully noted that deep samples contained a greater variety of megafauna species that showed lower numerical dominance than shallow samples in spite of the numerically smaller catch (Murray 1895). No explanation of this higher deep diversity was presented, and the observation was largely forgotten, possibly due to the much greater emphasis upon quantitative shallow water studies that soon followed. Contemporary surveys of soft bottom benthic communities are distinguished by a strong emphasis on numerical analysis of truly quantitative samples of the fauna in a known volume of sediment lying under a similarly known area of the sea floor. The origin of this type of surveying is generally attributed to the work of pioneering fisheries ecologist, C.G.J. Petersen (Petersen 1918), The method was developed during the course of ecologically comprehensive fish stock assessment begun in the late 1880s. Petersen-type surveys producing species inventories were widely adopted. Local surveys were conducted around Great Britain at such locations as in the vicinity of the Plymouth Marine Laboratory (Ford 1923, Smith 1932) and Scotland (Stephen 1928, 1934, Clark & Milne 1955). Numerous surveys took place along other west European coasts such as off Iceland and in the Mediterranean. By the 1900s larger scale surveys were conducted in the English Channel (Holme 1966). In North America, Allee (1923) surveyed the benthos in the vicinity of Woods Hole. Possibly most influential were benthic surveys in Puget Sound on the Pacific coast by Shelford (1935) who was a strong proponent of the super-organism view of community structure and function. Similar surveys were spread across the Arctic from the 1920s onward, and were summarised in English by Zenkevitch (1963). The techniques were also adopted along the Japanese coast in the 1930s and 1940s by Miyada (cited by Thorson 1957). These many Petersen-type surveys were all quite similar although sampling gear and sediment processing evolved over the course of the studies (Spärck 1935, Thorson 1955). The general trend was towards larger areas of sampling and more reliable penetration of the bottom. Statistical analyses were minimal, and results were often presented as a map of both faunal assemblages and oceanographic conditions. Assemblages were inventoried in detail, then described and named on the basis of the two characteristic species. Graphics were used to portray the relative abundance of dominant species. Diversity, as an aspect of the species inventories, was neither discussed nor analyzed in studies into the 1960s. This was despite the availability of useful indices since the 1940s, and their widespread use terrestrially for both plant and insect surveys. In addition these early workers considered themselves to be studying communities as interacting systems. However, hints exist that questions about species diversity were beginning to be formulated. In the survey by Smith (1932) of the Eddystone grounds species richness was presented with singletons and more abundant species 143

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carefully noted. Possibly reflecting growing ideas and better calculators, more sophisticated analyses began to appear such as the dispersion of species across samples (Clarke & Milne 1955). By the time of the English Channel survey (Holme 1966), the Petersen tradition of naming assemblages after two characteristic species had been dropped due to the finding that species composition varied greatly within such assemblages. The surprisingly little interest in species diversity or in any related characterisation of species inventories probably had several causes. The three most likely are a lack of practical utility, a lack of relevant concepts, and a lack of computational tools. With respect to utility, many of these benthic surveys were associated with fisheries studies making community productivity the parameter of interest. The apparent lack of ideas about species diversity may be related to the immaturity of the community concept. In the early 1900s, mapping of communities and characterisation of their component species was the major activity, and not a careful investigation of community structure and function that might be implied from the species inventory. Jones (1950) reviewed the status of benthic studies in the context of community theory and concluded that many workers accepted the idea that they were studying integrated systems in which biological interactions were important. Few, however, seemed to fully embrace the idea that benthic communities were superorganisms passing through biologically controlled successive states until a certain climax was reached. Indeed, the distribution of benthic assemblages was always explained in terms of control by physical conditions such as depth, sediment type, salinity, etc. One notable exception was Shelford, who was one of the framers of the climax community and biome concepts (Clements & Shelford 1939). He divided the oceans into a series of biomes largely associated with depth and geographic position without reference to species richness. Another ecology pioneer was Allee (1934), a strong proponent of benthic communities functioning as superorganisms, tracing the idea back to Verrill.

At the end of Petersen era In 1957, the state of knowledge about benthic ecology was compiled by international experts in a twenty nine-chapter memoir and published by the Committee on Marine Ecology and Paleoecology of the Geological Society of America (Hedgepeth 1957). Of particular relevance to the concept of diversity was the paper on bottom communities by Thorson (1957). This paper clearly marks a transition from the era of naming communities to one of discussing diversity patterns. The level mud bottom was correctly seen as one of the largest, and apparently homogenous, environments on Earth. Due to the strong dependence upon oceanographic conditions, bottom communities with similar taxonomic structure should be found over very large areas. These parallel communities were viewed as having relatively minor differences around the world. More importantly, Thorson compiled species richness data on selected taxa and found an increase from pole to tropics for epifauna and no gradient for infauna. Strongly influenced by physiological explanations, the increase was attributed to greater thermal stability in the tropics. A different view of benthic community stability emerged based upon ‘Thorson’s Rule’, a generalisation about increased occurrence of pelagic larvae in the tropics seen as having many exceptions but some general validity (Laptikhovsky 2006). It was then suggested that the tropical benthos would show greater spatial and temporal variation in species composition because of a large variation in survival to settlement in the plankton. Higher latitudes should have a more stable community structure due to the prevalence of direct development. The strong emphasis on parsimoniously characterising multispecies communities in a manner suitable for mapping without actual mathematical analyses lead early benthic ecologists to depend on nomenclature, or the naming of communities. A reading of the very detailed “ideal rules” of Thorson (1957) indicates how subjective the process actually was. Recommendations on how to 144

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select characteristic species would be of only historical interest if a similar need did not exist today to simply describe benthic communities for conservation planning. Later in this review it will be shown that naming Petersen communities is similar to picking indicator species and assigning greater importance to some species than others. The primary task of naming communities was to identify within the collected fauna those species that are ‘characteristic’ of the community. The five rules of Thorson paraphrased here were. First, more than one such species should be selected. Second, short life-span species should be avoided because their numbers fluctuate too much to be consistently characteristic. Third, highly mobile animals and predators should be avoided as being be too transient. Fourth, characteristic species should be big enough and abundant enough to be immediately conspicuous and have good identification traits without consultation with a specialist. Fifth, biomass and/or density can be used an indicator of abundance as long as they are not misleading due to large brood sizes or very large specimens. Even within the mundane task of picking names for communities, an interest in diversity can be seen. Thorson divided the species inventory into four categories or orders based on abundance and fidelity of association with a particular community. A first-order characteristic species should be conspicuous, found throughout the range of the community in at least 50% of the samples, and at least 5% of the biomass and restricted to that community. A second-order characteristic species should have a similar frequency of occurrence and biomass dominance, but limited to only portions of the range. A third-order species would be found in other communities as well as in at least 70% of the units and at least 10% biomass. A fourth-order of ‘associated animals or influents’ would be in at least 25% of the units and as much as 2% of the biomass but of little diagnostic value due to a wide distribution crossing other communities.

Beginning of a new era While formative elements of modern ecological theory may be found in many lines of early population research, ecological questions about niche filling, resource utilisation, and competitive exclusion were first expressed by G.E. Hutchinson and his students and colleagues in the 1960s (Maurer 1999). The “diversity of a species inventory” was modelled as a balance achieved through competition, resource specialisation, habitat complexity, resource availability, and history (MacArthur 1972). The details of community structure and function were being examined with mathematical tools, and species diversity was a parameter of great interest. The transition to the new view is most evident in a series of benthic studies begun in shallow estuaries (Sanders 1960) and then extended to abyssal depths (Sanders et al. 1965). Initially, communities were still named on the basis of characteristic species such as the Nephthys incisa – Nucula proxima community, and diversity indices were not calculated (Sanders 1960). By 1965, descriptive habitat names were used in place of characteristic species, and new diversity tools were proposed. There was obvious interest in species richness and proportions, the large number of rarer species, and the quantitative analysis of recurrent groups using trellis diagrams. Sanders’ benchmark comparative study of marine benthic diversity (Sanders 1968) marked the beginning of an adoption of niche theory and analytical methods by benthic ecologists worldwide that persists to this day. This comprehensive paper by Sanders made four major contributions. First, it objectively examined the use of several diversity measures, and found that the information-based Shannon’s index was adequate, but species richness was preferred. Secondly, rarefaction, a procedure for estimating species richness in computationally reduced samples was presented to reduce the effect of sample size. Third, Thorson’s infauna versus epifauna latitude gradients were challenged and regional oceanographic conditions considered to be of greater importance in controlling diversity highs and lows. Fourth, the high diversity of deep-sea macrofauna was noted for the first time since 145

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the CHALLENGER Expedition and proposed as a general ocean feature. A stability-time hypothesis was proposed as a general model for all benthic environments. In this explanation physical instability was predicted to cause low diversity and biological accommodation would cause high diversity where physical conditions were stable. Sanders was extremely careful about making a distinction between measurements of diversity that are reflective of species number (species diversity) and those reflective of proportional abundance (dominance diversity). Although categorising several indices as being of one or the other category, Sanders employed his own method of using species number per sample size for species diversity. His method of calculating dominance diversity was to first plot a species accumulation curve for each sample. He then compared that curve at reduced sample sizes (arrived at by rarefaction) with a baseline curve representing maximum equitability with all species having the same proportional abundance. Unfortunately, full details of the method were omitted. Sanders proceeded to examine the behaviour of species diversity versus dominance diversity in eight benthic habitats reducing the sample size artificially through rarefaction. A graphical means was employed to track changes in rank of diversity as samples were rarefied. The ranks determined by species number were found to be fairly consistent upon rarefaction, while ranks determined by dominance were very inconsistent. He concluded that species number was the more conservative measure of diversity while dominance was more variable due to the physical environment.

Influx of indices The 1960s and 1970s saw a rapid adoption of diversity measures and multivariate approaches to the analysis of benthic data. This adoption was due to a more fully developed niche theory, a better access to computers, and a dissatisfaction with the subjectivity of Petersen-like community description (Lie personal communication). The origins of the indices, however, preceded adoption by benthic ecologists by a decade or more. The inventories, lists and counts of species, found in benthic or any other type of survey sampling are categorical data in which individual specimens are assigned to a species category. Linguists also deal with categorical data, and pioneers like Zipf (1935) and Yule (1944) developed quantitative methods of comparing texts. They counted the frequency of words in various texts, ordered those frequencies by rank and noted recurrent curves reflecting the fact that a few words were very common and many rare. At roughly the same time period, R.A. Fisher (Fisher et al. 1943) proposed the use of a logarithmic series for examination of species categorical data. Influenced by the linguistic indices, Simpson (1949) proposed use of a ‘concentration’ index, and Shannon (1948) developed Information Theory that would be embraced by ecologists following a suggestion by Margalef (1958). The literature on how diversity should be measured continues to grow rapidly. Works in general ecology published in the 1960s through 1980s tend to fall into a either a category dealing with niche-theory models or a more practical category trying to improve the utility of indices. Benthic studies of diversity fit into both categories, but place emphasis on practical aspects. The emphasis on practical aspects stems from the increased number of surveys required to address environmental problems. Both theoretical and practical works are now on an upsurge. Increased theoretical interest has been generated by the proposal by Hubbell (2001) of the “unified theory of biodiversity and biogeography” and by multinational interest in the preservation of the European coastal seas. The ‘unified theory’ has inspired considerable controversy (Whitfield 2002) and renewed examination of diversity models (Pueyo 2006). Preservation of the coastal seas of many European nations requires standardised measures of diversity that are both scientifically meaningful and useful for policy and management decisions.

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Compared with terrestrial studies, the use of diversity measures by benthic ecologists has been relatively conservative in terms of restricting the types of indices proposed and applied. This can be attributed to the nature of benthic survey data, that is, a collection of many thousands of individuals and several hundred species. The taxonomy for many of the benthic groups is poorly developed and often in need of revision. Many species are rare. Compounding these problems, attempts at larger-scale syntheses are hindered by inconsistent sampling methods and great natural variation in sample size. Therefore, benthic ecologists have always needed measures that were robust when data were not ideal and which simplified the task of interpretation. Most studies have made use of just a few diversity measures based either upon fitting abundance distribution models or calculating an index. Most of these measures were well described by Gray (1981a) in benthic terms. In the context of this review, use of a distribution means fitting and calculation of the parameters that generate the distribution. Use of an index means the combining of two or more characteristics of species-abundance distributions to produce a single value on a scale that allows comparison among communities. Indices make no assumptions about the underlying distribution, but carry with them implicit definitions of diversity. Use of distributions always allows for significance testing. For all common indices statistical properties have been developed and formal testing is also possible.

Traditional approaches Diversity measures are so widely applied and improved measures are so actively sought that a division into traditional versus newer approaches is somewhat artificial. Old approaches are constantly being reconsidered. That acknowledged, there are some approaches that have been in use a long time and have been quite extensively discussed. These shall be presented first. Then some of the more recent developments are considered. Log-series and log-normal abundance distributions From a statistical perspective the most parsimonious means of describing diversity and conducting rigorous comparisons among communities is to first identify the underlying species abundance distribution, and fit the model and estimate the parameters that characterise the distribution. Several such distributions have been used in diversity studies (Hayek & Buzas 1997, Magurran 2004), but the two oldest have had the greatest usage in benthic ecology. These are the log-series (Fisher et al. 1943) and log-normal (Preston 1948) distributions. The finding that either one or the other of these distributions fitted a wide variety of terrestrial and marine data was once considered to reflect profound aspects about ecosystem structure (Odum et al. 1960), and that studies of pattern alone could definitively identify the causative processes. It has now been realised, however, that such distributions may simply reflect the outcome of many complex processes, especially when there are a large number of species and individuals are present (May 1975, Pueyo 2006). Indeed, information on species abundance alone is insufficient to select among alternate ecological theories of causation (McGill 2003). Many different processes can generate the same distribution. Explanation of distributions, the process of fitting, and the determination of parameters is substantially more complex than a discussion of diversity indices. Hayek & Buzas (1997) provide an excellent detailed account, but these authors are strong advocates for the wide application of the log-series. The log-series can be characterised using only a single parameter Fisher’s α. Computing α requires an interactive computation. When data actually fit the log-series, α is approximately the number of species represented by a single specimen (singletons).

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An especially successful use of the log-series in benthic systems was an application to archived foraminiferan data from five coastal regions ranging from the Arctic into the Caribbean (Buzas & Culver 1989). Fisher’s α provided a highly useful measure of diversity and indicated a strong geographic trend with the highest diversities in the tropical Caribbean and lowest in the Arctic. An unusual aspect of that analysis was that log-series rarefaction was used (Hayek & Buzas 1997) to produce equivalency, and that occurrence among samples was used as a measure of abundance rather than counts within a sample. The log-normal refers to abundances that are normally distributed about a mean once the data have been log transformed. As for any normal distribution, it is characterised by two parameters — mean and variance, which can be used as indicators of diversity. The log-normal has a rich history of usage in ecology since first recognised as a widespread pattern (Preston 1948). An early application in benthic ecology was the re-examination by Gage & Tett (1973) of benthic data from two lochs that had been previously analyzed using rarefacted species richness (Gage 1972). The log-normal distribution was fitted, and resulting means and variances used to search for patterns associated with the salinity differences of two lochs, salinity gradient within each loch, and sediment type. In the authors’ opinion, the two log-normal parameters provided a more informative picture than rarefacted species richness. The actual goodness of fit, however, can be questioned since singletons were excluded before analysis. The complete data may have been better fitted with the log-series. The most extensive use of the log-normal distribution in benthic ecology can be found in the studies of John Gray and his colleagues. Gray (1981a) noted that benthic assemblages containing many singletons generally fit the log-series distribution, but the common assemblage in which most species were represented by a few individuals fit the log-normal. The log-normal distribution has proven useful in identifying pollution impacts on benthic diversity (Gray 1981b, 1983, 1985). The log-normal has been proposed as a neutral model for soft bottom macrofauna assemblages in the sense that it is the expected outcome of certain ubiquitous processes of immigration, emigration, and resources partitioning (Ugland & Gray 1982, 1983). In a renewed discussion about the generation of species abundance patterns by neutral models, the appropriateness of the log-normal has been criticised (Williamson & Gaston 2005). Grey et al. (2006a), however, considered both a terrestrial and a marine system, and argue that many systems may be effectively modelled as compound log-normals in which two or more distributions are mixed. Ecologically, it seems quite feasible that benthic samples will include several suites of species for which the abundances reflect separate and distinct histories. Additional investigation is required. Species richness and its rarefaction Species richness is defined as the number of species in the samples of interest. Those samples may represent replicates from a single location or from larger spatial scales. The notation and nomenclature of Gray (2000) serves to avoid confusion with other symbols and ambiguity as to scale. ‘SR’ denotes species richness with subscripts applied to indicate spatial extent. It is the most easily explained of all measures of diversity, and for a large segment of the concerned community it is synonymous with biodiversity. In his classification of indices (Hill 1973), “SR” is viewed as giving equal weight to species of any abundance since it ignores those abundances completely. Recognising that SR is a function of sample size N, SR is often normalised through division by N or area sampled. Additionally, relationships of SR with sample size and abundance can be examined through regression with the slope of a regression serving as a index of diversity. These approaches are well covered by Hayek & Buzas (1997) and Magurran (2004). Species richness is often plotted against sampling effort represented by counts, number of samples, or area sampled as an indication of the completeness of the species inventory. In the case of a complete inventory, the curve becomes asymptotic. 148

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An important advancement in examination of species-effort and species-area curves was the generation of multiple plots of subsets of the data selected at random by computer (Colwell 2005). This produced both means and variances rather than single points along a curve. Renewed interest in such relationships is based upon the potential to extrapolate species richness beyond the actual level of sampling to be discussed below (Colwell & Coddington 1994, Ugland et al. 2003). Analytical approaches have, however, replaced randomisation. The best application of species richness as a diversity measure is in a situation where the biota has been fully inventoried with all species collected and recognised. This seldom if ever occurs in benthic ecology. Rare species go unsampled due to insufficient sample size, and fine distinctions between similar-appearing species can be easily overlooked. The problem of taxonomic error is quite hard to overcome, but an adjustment can be made for differences in SR arising from unequal sample size. Rarefaction originated in benthic studies (Sanders 1968) and has been widely adopted throughout ecology. Its purpose is to reduce multiple samples to a common N, and then estimate the number of species that should be present. Sanders also noted that the curves generated by rarefaction proceeding through a range of N’s could also be used to rank samples by diversity. Sanders use of rarefaction was not intended as a rigorous exercise in probabilities, and is best considered as an instruction set for reducing sample size. Hurlbert (1971) and Simberloff (1972) recognised the estimation of SR as a problem that could be solved by making use of the hypergeometric distribution and introduced the term expected species E(Sn) where Sn denotes species richness at the reduced sample size. Rarefaction is no longer limited just to estimating SR, but to other diversity measures as well using the hypergeometric and other distributions. Hayek & Buzas (1997) compared four rarefaction methods using tree survey data. The hypergeometric produced the best results, but Sander’s methods still proved both useful and simple. Simpson’s λ Simpson’s λ is an index based upon the probabilities encountered when comparing any two individuals in a set of species. These probabilities are estimated from the proportional abundance of each species in an assemblage. When two individuals are drawn, they may either be the same or a different species. All possible outcomes can be displayed as a square matrix (Figure 2). The diagonal of the matrix contains the probability of all possible ways in which the individuals drawn are in the same species. The values above and below the diagonal are all the possible ways that dissimilar species could be drawn. Since the order in which the species is found is unimportant, the probabilities above and below the diagonal are equal. The sum of all terms in the matrix are equal to one since no other combinations for two individuals exist. Simpson’s λ is the sum of all the elements on the diagonal where S equals the number of species (Equation 1). S

Simpson’s index

λ=

∑p

2

(1)

i =1

Simpson’s λ was proposed (Simpson 1949) as a measure of the concentration of the classification of individuals into species. The index has great conceptual appeal since it is the likelihood that two individuals drawn at random without replacement from a community or sample of a community belong to the same species. Terminology varies somewhat among users with Simpson’s D usually refering to the form 1 – λ which has the preferred property of increasing with greater diversity. The index can also be expressed expressed as 1/ λ , 1 – λ , and ln(λ) (Magurran 2004). The form 1 – λ is the probability of drawing two individuals that are not the same species (Equation 2). The double summation indicates that summing of the elements excludes the diagonal. Only half the matrix 149

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ROBERT S. CARNEY

0.25 Proportional abundances for index calculation

0.20

10

20 300 Rank of abundance

S

p2 p3 p2 p4 p2 p5 p2 p6 … p2 pj

Species 2 Species 3

p3 p1 p3 p2 p23

Species 4

p4 p1 p4 p2 p4 p3 p24

Species 5

p5 p1 p5 p2 p5 p3 p5 p4 p52

Species 6

p6 p1 p6 p2 p6 p3 p6 p4 p6 p5 p62

50 Species i Species number

p1 p2 p1 p3 p1 p4 p1 p5 p1 p6 … p1 pj

p2 p1 p22

…

40

Species j

1

Species 6

.....

2

p1

Species 5

Species 1

0.05

Species 4

Log-series? 0.10

Species 3

0.15

Species 2

Species 1

Proportional abundance

Species abundance plots

…

p3 p4 p3 p5 p3 p6 … p3 pj

p5 p6 … p5 pj

…

… pi2

…

…

… p6 pj

pi p1 pi p2 pi p3 pi p4 pi p5 pi pj …

…

…

p4 p5 p4 p6 … p4 pj

Species × species probability of all pairs

30 Log-normal?

20 10 1 1

10 50 100 Specimen count (logn scale)

Figure 2 Distributions or calculation of indices. Two common means of plotting species abundance, rank of abundance versus proportion of sample and number of species versus number of individuals have led to the suggestion that either the log-series or log-normal distribution could parsimoniously describe the data. Alternately indices can be calculated, most often using the proportion of abundance. Proportions provide an estimate of the probabilities that pairs of individuals drawn from the data will be the same (values on the diagonal) or different (off the diagonal) species.

is summed according to this notation, requiring that the result be multiplied by two to get the actual probability. It has come into renewed application as a component of taxonomic distinctiveness discussed below. The index is sometimes referred to as the Gini-Simpson index in recognition of development of the same function by the economist C. Gini in 1912 (Gorelick 2006). S −1

S

∑∑ p p

1− λ = 2

i

j

(2)

j=2 i< j

In his classification of indices (Hill 1973), λ gives greatest weight to abundant species. This behaviour has reduced its popularity in benthic ecology and other fields that commonly encounter numerous species with low abundances. For example, the index goes unmentioned in Gray (1981a). The emphasis on abundant species is a property of squaring the proportions. Proportions are always equal to or less than one. When proportions are squared the product is an even smaller fraction.

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USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES

Thus, if the most dominant species in a sample has a p = 0.30, p2 = 0.090. A species with half that abundance, p = 0.15 will contribute p2 = 0.023 to the summed index, or only a fourth as much. The positive side of λ’s insensitivity to rare species is that it is minimally influenced by sample size because abundant species are usually sampled with low effort. Therefore, λ produces relatively consistent rankings of the least to the most diverse assemblages Lande et al. (2000). It has also been effectively used to show latitude gradients in intertidal mudflats (Attrill et al. 2001), and warrants greater consideration for similar comparisons across multiple studies. The abundant species that most influence λ are most likely to be the best surveyed and most consistently and correctly identified Information theory and Shannon’s H′ Shannon’s index is the summation of plog(p) for all S species (Equations 3a,b). S

Shannon’s H′ = −

∑ p log p i

i

(3a)

i =1

S

H′ = −

∑ p ln( p ) i

i

(3b)

i =1

Unlike the conceptually simple Simpson’s λ , Shannon’s H′ is based on the more abstract field of information theory and systems entropy (Shannon 1948). The formula appeared much earlier in Boltzman’s 1872 work in entropy (Gorelick 2006) and simultaneously in the cybernetics work of Weiner (1948). The index is sometimes termed the Shannon-Weiner index or incorrectly ShannonWeaver due to citation confusion (Magurran 2004). In spite of unclear conceptual relevance to ecology, it continues in widespread use due to its mathematical properties and history of application. Information theory provides a means to quantify the complexity of information that can be used in the design of communication systems (Shannon 1948). It originated during World War II as a tool for assuring the successful transmission and reception of encoded messages through noisy radio channels. Its use in systems ecology for the quantification of diversity was first advocated by Margalef (1958) on the basis of an analogy between transmission systems and temporal changes in ecosystems. Very simplified, temporal changes are like a noisy channel between the structure of an ecosystem at one time and another time. Pielou (1966) was very influential in the adoption of information diversity measures, but specifically rejected the underlying analogy (Pielou 1969). Margalef (1995) continued to advocate the utility of the analogy. H′ is a fundamentally different way of envisioning diversity, and is related to the complexity of the task of sorting the specimens into correct species groups through a series of decisions. Compared to other measures of diversity, information has two very important distinguishing features associated with the summed term plog(p), most often calculated as the natural logarithm pln(p). First, pln(p) is modal reaching a maximum of 0.3679 for a proportion of p = 0.3678. Higher and lower proportions contribute less to the summed index. Illustrating this point with an unlikely assemblage of two species with proportions of 0.999994 and 0.000006, both the very common and the very rare would contribute roughly equally to H′, approximately 0.000006 for both. Second, H′ increases linearly with geometric increase of species richness under conditions of full evenness. For example, if there are three assemblages with 10, 20 and 40 equally abundant species, the

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ROBERT S. CARNEY

respective H′ will be 2.303, 2.996 and 3.689. The increment in H′ is a consistent 0.693 even though the species richness doubles. Depending upon one’s concept of diversity, these are either good or bad properties. Use of information theory for diversity quantification in benthic studies had been initiated by the late 1960s (Lie and Kelly 1970, Lie 1974). Its popularity in benthic studies can be seen from the fact that it is the only diversity index presented in Gray’s (1981a) succinct text on benthic ecology. This popularity continues to the present (Gobin and Warwick 2006, Warwick et al. 2006). A variety of diversity specialists have found the properties of H′ poorly suited for specific tasks (May 1975, Lande 1996), and Magurran (2004) attributes its continued use largely to tradition. H′ does, however, have properties very useful in diversity analysis. Specifically, it supports additive formulations of diversity across scales from sample to large area (Lande 1996, Veech et al. 2002), and identification of the underlying distribution of proportions can be made through examining the changes in species richness, Equitability, and H′ during subsampling of data (SHE analysis, Hayek & Buzas 1997).

Newer developments New developments in the measure of benthic diversity still fall into both theoretical and practical categories, although there is greater merger of the two than previously. When sedimentary habitats are sampled, the process of developing high quality species count data is far more time and effort consuming than parallel activities such as chemical and granulometric analyses. Once the benthic data are available, confusion can exist in explaining the data analyses applied. In the real situation when both time and money are critical, there is a great emphasis upon doing things more expediently and providing more informative results. The use of surrogates to estimate diversity is an approach seeking to reduce effort. The use of new taxonomic diversities is an effort to improve results. A bit closer to theory are attempts to extrapolate from small samples to larger areas, and to gain knowledge over larger spatial scales by compiling local studies. Surrogates The intent of the surrogate approach is to replace the hard and expensive task of compiling a multispecies inventory with an easier and less costly survey of indicator species, coarser taxonomic level, or restricted size class. Proof that any of these surrogates are useful rests in demonstrating that they allow for an accurate estimation of the diversity of unsampled species. Weaker proof is that the surrogate produces a similar diversity ranking of assemblages as that obtained by more comprehensive methods. Benthic ecologists are largely accepting that such approaches might work if proven, since surrogacy is almost always applied to some extent. Benthic systems like most others are complex, and benthic ecologists have traditionally met the need to adopt a practical focus by dealing with a restricted size range or taxonomic category. The concept of an indicator or surrogate for full diversity measurement has been widely examined for terrestrial systems (Gaston & Williams 1993, Williams & Gaston 1994, Anderson 1995, Andelman & Fagan 2000). Unfortunately, approaches from the use of single species to more inclusive groupings have shown little utility for reflecting diversity of the unsurveyed species (Eduardo & Grelle 2002, MacNally et al. 2002, Su et al. 2004). When the criteria for indicator species developed by Pearson and associates (Pearson 1994) for conservation biology are critically examined, they seem intended to produce simple descriptors of a community rather than to serve as a surrogate for diversity. Indeed, they are similar to rules for identifying characteristic species in Petersen-type communities (Thorson 1957). Indicator criteria can be rephrased as:

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USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES

1. The taxonomy should be well known, stable, and suitable for correct and consistent identification by a non-specialist; 2. The biology and general life history should be well understood so as to make ecological roles known and sources of variation understood; 3. The populations should be readily surveyed and manipulated; 4. Higher taxa (i.e., genera, family) of the indicators should occupy a breadth of habitats and a broad geographic range so that wide application is possible; 5. At lower taxonomic levels (populations, subspecies, species, etc.), there should be narrow habitat specialisation so that the ability to detect small geographic differences is provided; 6. The patterns observed in the indicator should actually be an indicator of similar patterns in other related or unrelated taxa; and 7. A species with potential economic impact may be especially useful for policy purposes even though it fails to meet other criteria. While the possibility exists that some indicator species might reliably replace more comprehensive species in special cases, the wider application of simple species surrogates seems unlikely. Taxonomic surrogacy or taxonomic sufficiency (Ellis 1985, Quijón & Snelgrove 2006) is a an alternative. Taxonomic surrogacy has been effectively treated from a taxonomic perspective by Bertrand et al. (2006). Irish Sea polychaete data (Mackie et al. 1995) were re-examined at different taxonomic resolutions employing three equally acceptable phylogenies ranging from splitter influenced to lumper influenced. Good regressions between species richness and family richness existed for each phylogeny, but slopes were dramatically different. Therefore, the phylogeny used greatly influences species richness estimates. For most benthic marine fauna, phylogenies are not well developed. Field results also suggest caution in the adoption of taxonomic surrogates. Only in the case of hydrothermal vent fauna have genus, family, and order all been well correlated with species patterns (Doerries &Van Dover 2003). In deep sediments family-species correlations were poor (Narayanaswamy et al. 2003). Quijón & Snelgrove (2006) examined taxonomic surrogacy in a reexamination of seafloor predator exclusion and found that the family level was effective only when families contained three or fewer species. They concluded, as with many others, that species-level investigation should be the norm. Following methods used in terrestrial systems (Su et al. 2004), Karakassis et al. (2006) compared similarity analyses of benthic samples in the eastern Mediterranean with community diversity measured by a broad range of indices. The indicator taxa were multispecies groups of macrofauna collected by grab, ciliates collected similarly, and megafauna and fish colleted by trawl. The measures of diversity based on the different indicator groups were poorly correlated. Most studies examining taxonomic surrogacy in marine systems have been primarily concerned with the use of similarity analysis to detect differences rather than estimation of diversity per se. Warwick (1988) re-examined macrobenthic data from five sites at a coarser resolution, and found that the family level provided adequate results. Similar sufficiency at the family level has been found in impacted benthic systems (Olsgard et al. 1998a,b) with the caveat that the level of resolution should be limited to impacted systems containing steep gradients of impact. Additionally, family-level studies should only be used following development of a species-level baseline. The question as to whether one size class can be used to determine diversity trends in another is especially relevant in benthic ecology due to the traditional separation of macrofauna and meiofauna studies. Warwick et al. (2006) carried out a carefully designed study across both size groups with interesting results. Sieve-size fractions of the benthos showed similar diversities when sampled over a set range of spatial scales. The Shannon Index and Expected Species at a sample

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size of 50 were used as diversity measures. Diversity of the 63, 125 and 250 µm fractions were quite similar. Diversities of the 500 and 1000 µm sizes were lower by a factor of about two, but were similar to one another. No one size fraction could be used as a surrogate for the whole, but the diversity pattern in the larger and the smaller could possibly be studied at only two sieve sizes. Taxonomic diversity The incorporation of taxonomic information into a diversity-like index represents a truly novel development. Indeed, when the indices that form the taxonomic distinctness approach are examined, they both stretch and then depart from the traditional view that diversity combines species richness and proportional abundance. Initially viewed as a need in conservation biology (May 1990, Crozier 1997), the approach has been extensively developed in benthic studies (Clark & Warwick 1998, 1999, 2001, Warwick & Clarke 1998, 2001). Although in use a relatively short time, the approach is gaining wider acceptance. It has already been reviewed in this journal (Warwick & Clarke 2001), and is widely available through the PRIMER-5 package of computer analysis routines. Combination of species diversity measures and numerical taxonomy into a more informative index was proposed in passing by Sneath & Sokal (1973), but the idea seems to have gone largely unexplored until conservation biologists sought a means of better assessing diversity (Faith 1992, Posadas et al. 2001, Mace et al. 2003). In addition to the utility in conservation planning, the concept is also ecologically appealing as nicely presented by Purvis & Hector (2000). When developing a operational definition of diversity, three factors rather than two should be included. In addition to species richness and proportional abundance, we should consider the inherent differences among the taxa present. Giving a benthic example, we might judge that an assemblage of vermiform animals consisting solely of polychaetes was in some way less diverse than an assemblage consisting of burrowing anemones, phoronids, sipunculids, echiurans, holothuroids, and a few polychaetes. At this time, five descriptors for taxonomic distinctness have been developed (Clark & Warwick 2001; Warwick & Clarke 2001): Taxonomic Diversity ∆, Taxonomic Distinctness ∆*, Average Taxonomic Distinctness for presence/absence data ∆+, Variation in Taxonomic Distinctness Λ+, and Total Taxonomic Distinctness s∆+. The first two can be considered three-component diversity indices combining species richness, proportional abundance, and taxonomic information. The latter three omit a consideration of abundance. These importance differences are best seen through an examination of how the measures are calculated. As introduced in the discussion of Simpson’s λ , the relationship between all pairs of species can be represented by a symmetrical square matrix (Figure 3). The heart of taxonomic distinctness is such a matrix of taxonomic distinctness values ωij between each pair. The matrix of distinctness values is effectively similar to a dendrogram or cladogram. Ideally, ωij values should be based on carefully developed phylogenies (e.g., Bertrand et al. 2006), but Warwick & Clarke (2001) have effectively made the case for starting with the Linnaean hierarchy until better values are available. Unlike phylogenies, the Linnaean hierarchy has fixed ranks. Two individuals in the same species (i = j) would have a ωij of zero. Two individuals from separate congeneric species (i ≠ j) would have a ωij of one. If the pair were in confamilial genera, ωij would be two and so on. These increments can be rescaled to allow for taxonomies with many additional subdivisions such as tribes, superfamilies, subclasses, etc. (Warwick & Clarke 2001). The calculation of Taxonomic Diversity and Distinctness combine the values of taxonomic distinctness with abundance (Equation 4a). For these calculations, each element in the taxonomic distinctness matrix is weighted by the product of the abundances of each pair of species (xi xj ). The somewhat more familiar form of ∆ can be made by converting xi xj values to the probability of encountering the species pair (pij ) simply by dividing each element by N 2 (Equation 4b). The

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USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES

ω1,j

ω2,3 ω2,4 ω2,5 ω2,6 …

ω2 ,j

ω3,4 ω3,5 ω3,6 …

ω3 ,j

ω4,5 ω4,6 …

ω4 ,j

ω5,6 …

ω5 ,j

0

…

ω6 ,j

0 …

0

0

ω3,1 ω3,2

0

ω4,1 ω4,2 ω4,3

0

ω5,1 ω5,2 ω5,3 ω5,4

0

ω6,1 ω6,2 ω6,3 ω6,4 ω6,5 …

…

…

…

…

…

Species 3

Species 4 Species 5

ω1,2 ω1,3 ω1,4 ω1,5 ω1,6 …

ω2,1 Class

Family

0

Phylum

Species 2

Order

Species 1

Genus

Taxonomic hierarchy and distinctness paths

…

Species × species taxonomic distinctness weights ωi,j = ωj,i

ωi,1

ωi,2

ωi,3

ωi,4

ωi,5

ωi,6

ω3,4 = 5

Species × species probability of pair

ω6,7 = 3

pi pj = pj pi

Species 6 p1 p6

…

p1 pj

p2

p2 p3

p2 p4

p 2 p5

p2 p6

…

p2 pj

p 3 p1

p3 p2

p3

p3 p4

p 3 p5

p3 p6

…

p3 pj

p 4 p1

p4 p2

p4 p3

p4

p 4 p5

p4 p6

…

p4 pj

p 5 p1

p5 p2

p5 p3

p5 p4

p5

2

p5 p5

…

p5 pj

p 6 p1

p6 p2

p6 p3

p6 p4

p 6 p5

p62

…

p6 pj

…

…

…

…

…

Species 9

p 1 p5

…

Species 8

p1 p4

…

Species 7

p1 p3

…

2

pi p1

pi p2

pi p3

pi p4

pi p5

pi pj

…

pi

p1

p1 p2

p 2 p1

2

2

2

Species 10

Species i

2

Figure 3 Taxonomic distinctness measures. The taxonomic distinctness suite of indices is based upon determining distinctness between all pairs of species collected by sampling. As an initial approximation of phylogenetic relationships, distinctness weight (ω) is half the path length linking a species pair in the taxonomic hierarchy. The properties of the resulting distinctness matrix can be analyzed and expressed as a purely taxonomic-distinctness index like ∆*. When combined with a matrix of probabilities of drawing species pairs, an index of taxonomic diversity (∆) can be obtained that combines species richness, relative abundance and interspecies evolutionary relationships. This is a major extension of the species diversity concept.

relationship with 1 – λ (Equation 2) explained by Warwick & Clarke (1998) is more obvious in this presentation. It can also be noted that as N becomes large its effect on the calculated value quickly becomes small. Seen as an extension of Simpson’s λ , ∆ is the expected or average taxonomic difference between any pair of specimens drawn from the assemblage on the condition that they are not the same species.

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ROBERT S. CARNEY

S −1

S

∑∑ω x x

2 Taxonomic Diversity

ij i

j=2 i< j

∆=

(

)

(4a)

N N −1 S −1

S

∑∑ω p p

2 ∆=

ij

i

(4b)

(1 − N −1 ) S

∑∑ω x x ij i

∆* =

j

j=2 i< j

S −1

Taxonomic Distinctness

j

j

j=2 i< j S S

∑∑ x x i

(5a) j

j=2 i< j

S −1

S

∑∑ω p p ij i

∆* =

j

j=2 i< j

(5b)

1− λ

Taxonomic distinctness, ∆*, is an extension of Taxonomic Diversity based on the ratio of the product of taxonomic distance and species pair abundances to the same product when all ωij have been set equal to 1 (Equation 5a). This ratio has the effect of comparing actual weighted taxonomic distinctness to a reference distance based on all specimens being in the same genus. The relationship with Simpson’s λ is again more obvious when proportions are used (Equation 5b). Two important attributes of ∆* are that the ratio eliminates the effects of any scaling that has taken place on the abundance data, and the direct influence of sample size, n, is eliminated. When only presence/absence data are available, Taxonomic Diversity and Distinctness reduce to Average Taxonomic Distinctness. This index is based entirely upon the taxonomic weights and species richness. Thus, it represents a different definition of diversity than either the index combining richness with abundance or the three-component definition of Taxonomic Diversity and Distinctness. S −1

S

∑∑ω

2 Average Taxonomic Distinctness

+

∆ =

j=2 i< j

S ( S − 1)

ij

(6)

Excluding studies used in developing the approach, application of the taxonomic distinctiveness approach is still in the early phases, and much remains to be learned about its utility for answering a range of questions. Ellingsen et al. (2005) examined its ecological utility by applying the qualitative form, ∆+, to soft-sediment macrobenthos at 101 sites along the Norwegian continental shelf (Ellingsen & Gray 2002). To examine the possibility of surrogacy, annelids, molluscs, and crustaceans were treated separately and then combined for an overall pattern. A distinct gradient of decreasing values of ∆+ with depth and latitude was found when all taxa were combined, but three separate groups showed different relationships indicating that no group could serve as a surrogate 156

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USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES

for the overall pattern. The traditional measure, species richness, showed a modal relationship to depth and a gradient with latitude and sediment grain size. While ∆+ produced results from the Norwegian data that warrant additional investigation, these workers concluded that the inconsistencies among taxa may have been an artifact of differences in taxonomic hierarchy rather than ecology. Aside from ecological applications, conclusions about the applied utility of taxonomic diversity measures for assessing environmental quality also vary among studies. In the initial application to a North Sea oil field, the measures showed greater sensitivity than other indices and were monotonic with the degree of degradation (Warwick & Clarke 1995). Somerfield et al. (1997) found less clear gradients of impact in a similar system. Applied to three different coastal habitats in Spain and Portugal (Salas et al. 2006), the measures lacked greater utility than other diversity or habitatquality measures. The data from these coastal studies combined grab with hand-collected specimens and mixed soft bottom, hard bottom, subtidal, and intertidal habitats. There needs to be more application of the approach across comparable benthic datasets and habitats. This wider application should be accompanied with refinement by systematists in the method of determining taxonomic weights before a full critical evaluation is possible. An unresolved problem with taxonomic distinctness indices is exactly how to interpret them in the context of diversity theories that largely ignore the phylogenetic aspect of species diversity. For example, a carefully designed mesocosm experiment examined the combined effects of nutrient enrichment and physical disturbance on both macrofauna and meiobenthic nematodes (Widdicombe & Austen 2001, Austen & Widdicombe 2006). Diversity was measured using Total Taxonomic Distinctness s∆+ (Warwick & Clarke 2001), a measure entirely dependent upon the matrix of taxonomic distinctness values and species richness. The results for both macrofauna and nematodes were interpreted as being consistent with the dynamic equilibrium hypothesis of Huston (1979). It is not clear at this point in the development of taxonomic distinctiveness what Huston’s model would predict if modified to consider phylogenies. Indeed, it is not obvious how such a modification should be made other than to accept the unlikely assumptions about generic and familiar competition and dispersal abilities. Extrapolation Benthic surveys typically sample a very small area of bottom and try to characterise the diversity of a much larger area of sea floor. Collector’s curves of number of species found versus effort (individuals or samples) seldom approach an asymptote indicating that the complete species inventory has been poorly sampled. Traditionally, benthic ecologists avoided the temptation of extrapolating beyond the actual observed species richness. Conservation biology has, however, driven the need to extrapolate from samples to much larger areas or to a larger number of samples than actually taken. Reviews of the methods employed have been written by Bunge & Fitzpatrick (1993) and Colwell & Coddington (1994) who point out that determining the number of unobserved things is a statistical challenge in many different fields. The methods are available through the EstimateS software distributed by Colwell (2005). Extrapolation in soft-bottom systems has been addressed employing different methods by Karakassis (1995), Rumohr et al. (2001), Ugland et al. (2003) and Ugland & Gray (2004). Karakassis employed a method developed from catch statistics identical to earlier work by DeLury (Ugland & Gray 2003). This method is sample based and plots the observed species at one level of effort, k, against k + 1. The curve is extrapolated until the two terms are equal. Foggo et al. (2003) applied the Karakassis method and Rumohr’s modification to beach macrofauna, estuarine oligochaetes and reef fish. These datasets were modest with the largest for reef fish having 109 samples and only 33 species. Using the criteria that the predicted species richness should equal the total observed species richness at 75% sampling effort, it was concluded that different methods gave best estimates 157

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at different levels of effort. The Karakassis method always produced low estimates. At high sampling efforts, the modified Karakassis method gave estimates closer to the actual value. In addition to Karakassis methods, methods derived from the work of Chao (1984) were employed in the same comparison. These are non-parametric techniques made popular by the review of Colwell & Coddington (1994), and are succinctly treated in Magurran (2004). Chao1 and Chao2 are individual-based and sample-based versions of the same relationship (Equations 7a,b). The ˆ and the actually observed species richness is S . For estimated species richness is denoted by S, obs the individual-based case when abundances are known, F1 and F2 denote the number of singleton and doubleton species. For the sample-based case when only number of occurrences are known; Q1 and Q2 are the number of species found in just one and two samples.

Chao1

F2 S
= Sobs + 1 F2

(7a)

Chao2

Q2 S
= Sobs + 1 Q2

(7b)

Concerned that subtidal macrobenthic surveys are typically much more extensive and collect many more species, Ugland & Gray (2004) carried out a comparison of the Karakassis and Chao methods using extensive Norwegian shelf data from two regions. One dataset contained 68,298 individuals and 809 species collected in 101 samples (Ellingsen 2001). The second contains more than three million individuals and 2186 species found in 124 aggregated samples (Ellingsen & Gray 2002). The first region could be subdivided into five subregions and the second into six based on various oceanographic factors. Both the Chao and Karakassis methods were found to seriously underestimate species richness when applied to subsets of data. Ugland and associates have been pursuing a new application of species accumulation curves for extrapolation of species richness and bottom heterogeneity. An important advancement was an independent derivation by Ugland et al. (2003) and Colwell et al. (2004) of an analytical method of calculating the mean and variance of a sample-based accumulation curve without resorting to randomisations (Gotelli & Colwell 2001). Ugland et al. (2003) further treated inherent heterogeneity of the shelf-depth benthos partitioned macrofauna data from Hong Kong and the Norwegian shelf into subareas and nested the species accumulation curve. Seeking explanations for differences between the two regions that could be due to bottom heterogeneity, similar nested analyses were applied to data generated by Arrhenius null models (Ugland et al. 2005) with very good results. Progress in measurement of diversity over scales: α, β, and γ One of the most active and interesting areas of diversity research today focuses on the diversity changes observed when progressing from small to larger spatial scales. These changes are of special interest because they should reflect the processes through which regional (larger area) dynamics influence local (smaller area) communities. From a systems perspective, it is a matter of assemblage: how do smaller units such as communities fit together hierarchically to make a larger unit such as an ecosystem? When ecologists examine differences in diversity across increasing scales or nested sets of samples, three general approaches have been taken (Magurran 2004). A value β can be developed describing the relationship between diversity at one scale α and a larger scale γ. Diversities can be compared using similarity indices that consider species by species differences. Finally the species-area relationship can be considered as the area increases. 158

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The concept of β diversity was introduced by Whittaker (1960, 1972) who needed a means to quantify changes in plant diversity along gradients. A scheme was introduced employing ‘inventory’ diversity at four spatial scales and three ‘differentiation’ diversities between adjacent scales. On the smallest scale is point diversity for a single sampling unit followed by α (habitat), γ (landscape) and ε (province). The change in diversity between point and α was termed ‘pattern’ diversity. The most familiar is the difference between α diversity and γ diversity termed β. A simple relationship between the two is Whittaker’s multiplicative relationship shown in Equation 8 where the denominator is the average α of all components combined to make γ (Magurran 2004).

Whittaker

βW =

γ α

(8)

A certain amount of confusion persists surrounding α, β and γ. Most critical confusion is the distinction between inventory and differentiation diversities. β is not a diversity but is a relationship between diversities. Since α and γ have the units species, β must be a unitless ratio when the Whittaker multiplicative approach is used. A related approach is to express β as the slope of species richness when area sampled or sample number increases (Rosenzweig 1995). In which case β has the units of species per area or sample number. Wilson & Shumida (1984) evaluated six β diversity indices, most following the multiplicative tradition, and found the simple Whittaker multiplicative relationship to most closely meet their criteria, results that were accepted in later reviews (Gray 2000, Magurran 2004). The second source of confusion is a general inconsistency of terminology in describing scale. The symbol α is used to describe the diversity of everything from a single sample up to a large geographic region. In an effort to reduce confusion, Gray (2000) dropped the use of γ and proposed a nomenclature that built upon a review of benthic system scaling (Thrush et al. 1999). The key distinction of the system is between the terms habitat and assemblage that should not have restricted scales versus diversity of points, samples, large areas, and provinces which can be given convenient set scales. Unfortunately, confusion will be hard to eliminate especially between point and sample diversity. In oceanographic data archiving the smallest unit, a single core is often recorded as being a sample rather than the statistical usage in which several cores taken according to a specified design would comprise a sample. Following the influential evaluation by Lande (1996) of diversity measures, Crist & Veech (2006) proposed simply using αi to denote diversity at all levels with the actual level specified by the subscript. Further each level αi is composed of a set of lower level values. Effectively, no fixed scales are used, and it is the burden of the investigator to specify the scales over which αi values are nested. As part of the renewed interest in the scales of diversity and how large ecosystems fit together, it has become appreciated that there is no one right way of envisioning β diversity. A most important recent development is the use of additive rather than multiplicative measures, i.e., γ is the sum of α and β rather than their product. The general relationship attributed to Lande (1996) is shown in Equation 9. Development of an actual computational form is more complicated. Veech et al. (2002) traced the origins of additive diversity partitioning to MacArthur (1966) and Levins (1968), noting that these initial works did not apply the same α, β and γ symbols and terminology as Whittaker (1960), whereas Lande (1996) did. Adopting additive partitioning, β diversity can be seen as the difference between the average diversity of sub units and the overall diversity of the set they are in (Loreau 2000). Additive Diversity

159

γ = α+β

(9)

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The first application of additive diversity partitioning to the benthos was not actually presented as such. Ugland et al. (2003) developed an approach to accumulation curve analysis — the analytical species accumulation (ASA) approach, which is based upon accumulation within subsets of samples and a novel analytical expression for the accumulation curve rather than Monte Carlo simulations. The method was used to extrapolate total species richness in areas of the Norwegian shelf and Hong Kong harbour. Crist & Veech (2006) recognised, however, the additive nature of the relationship in ASA between observed species richness in a combined set and the average species richness of the members of the subset. On further investigation of the additive and multiplicative models of β diversity, Kiflawi & Spencer (2004) established the interrelationship βM = βA/α and explored the statistical properties of both approaches. No evidence of the benefit of one over the other was presented. The analysis of similarity to investigate β and for other purposes is so extensively used in benthic studies (Gray 2000) that it is beyond the scope of this review. The partitioning of a similarity matrix to study β diversity has been compared to the use of the variance of a raw species by a sample array (Legendre et al. 2005). As previously noted a goal of assessing diversity changes across scales and across system hierarchies is to gain information about processes. A seminal work of this kind was based on a study of West Indian bird communities (Terborgh & Faaborg 1980). A simple relationship was proposed that distinguished between species saturated and unsaturated communities. Saturated communities were those having such strong species interactions that no new species from the regional pool could successfully enter. Unsaturated communities lacked similarly intense interaction allowing additional species to enter from the larger pool. The difference between saturated and unsaturated communities should be detected by simple plots from many localities and regions of local (α) versus regional species richness (γ). Saturated communities would show an asymptote while unsaturated would show a linear relationship. Unfortunately, this simple scheme has failed in a large number of terrestrial and marine studies (Russell et al. 2006). The determination of local versus regional diversity is, however, seen as an important task in diversity studies assuming adequate attention is paid to designs that make appropriate comparisons (Ricklefs 2004). Ellingsen & Gray (2002) carried out an examination of diversity at different scales that employed four approaches to β and examined the relationship between local (α) and regional (γ) diversities. The smallest scale was represented by five pooled van Veen grabs taken at 101 sites along the length of the Norwegian continental shelf. Whittaker’s βw, number of species shared between all pairs, biotic distinctness and Bray-Curtis similarity were calculated. Regional pooling of data produced γ diversities. While the results were discussed in the context of lacking a latitudinal gradient, other points were equally important. β values were found to vary with taxa such that no group could serve as a surrogate for the whole. α was found to bear no clear relationship with γ that would indicate strong regional control of local diversity. The Bray-Curtis values and biotic distinctness, both similarity measures, reflected γ diversity changes more than βw . Biogeographic studies that compare diversity across large scales can differ in the manner in which diversity at the largest scale (γ) is determined. It can be arrived at by pooling data into larger and larger composites. When this is done there may be relationships between α and λ diversities that reflect the pooling process rather than ecology. Therefore an independent estimate of largescale diversity is desirable. To accomplish this a list of regional species can be compiled independent of the smaller-scale sampling by using published lists, biogeographic archives, museum collections, etc. In the case of well-studied areas such as the Norwegian shelf the regional pool of macrofaunal species should be especially well known. Unfortunately, few similarly well-known regions exist. Developing regional pools from multiple sources of taxonomic knowledge also has problems associated with it. Such regional species lists may fail to draw important distinctions between

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habitats in heterogenous regions, overestimating the number of species available for colonisation and survival at small-scale sites (Russell et al. 2006). Traditional information may be expressed only in terms of depth and geographic ranges. The limits of observed occurrence set the boundaries, and it is implicit that the species is in the regional pool throughout the range when discontinuous distribution is more often the actual case (Hurlbert & White 2005). Compiled ranges when strong boundaries exist such as the surface and the maximum depth of the ocean can be expected to produce maxima in diversity that may have no ecological relevance, the Mid-Domain effect (Colwell et al. 2005, Connolly 2005). Pineda & Caswell (1998) examined species richness and ranges on the Gay Head-Bermuda data and found elements of agreement and disagreement between model and observed diversity.

Examining large-scale patterns Study of large-scale patterns is an extremely active area of benthic diversity research (Gray 2002). The global latitude gradient is the primary focus due to the large number of taxonomists and systematists addressing that question. A smaller number of experts continue to study species distribution and diversity on the continental margins over the transition from shallow to abyssal depths. These gradients are being examined from both a local and a regional perspective. The much shorter spatial scale of the bathymetric gradient makes small-scale analysis easier with diversity being first measured sample-by-sample. The great expanse of latitude makes large-scale range compilations taxa-by-taxa based on sampling and archived records the most common approach. Simple species richness is the most often used measure of diversity.

Global latitude gradient There has been important progress in synthesising the accumulated knowledge about distributions in the ocean. In a meta-analysis of 232 published studies including 102 of coastal benthos and 34 of the deep-sea, it was established that marine species richness increases towards the equator (Hillebrand 2004a,b). Marine diversity shows this latitude effect as strongly as terrestrial. Regional (γ) diversity shows the effect more strongly than local (α). Furthermore, the actual measure of diversity used did not influence the correlation between diversity and latitude. It did, however, influence the slope of the gradient, being steepest when species richness was used. Within this global pattern, particular habitats and faunal groups did vary. Among the faunal categories considered, epibenthic and endobenthic gradients were significant but weaker than others. Within marine habitats, the correlation between diversity and latitude is stronger for the deep-sea than coastal waters. The slope of the gradient was steeper for coastal habitats, but the shallow/deep difference was not statistically significant. These generalities about the marine latitude gradient may prove valid with additional investigation, but should be considered with caution. They were generated from such a large and diverse literature by means of meta-analysis, a procedure for combining results from multiple studies widely used in medicine, education, and social research (Hedges & Olkin 1985), that is being applied to ecological research (Gurevitch & Hedges 1993, Rosenberg et al. 2000). Meta-analysis can be a powerful tool when seeking consensus from an extensive body of literature with contradictory findings. Unfortunately, in meta-analysis the individual studies become anonymous along with all their assumptions, incompatibilities, and possible errors (Slavin 1986). Given the weakness of the latitudinal effect for epi- and endobenthos, more information about the contributing studies would be informative. The actual latitudinal patterns of the soft bottom still seem poorly studied. So much so that the observation by Clarke & Crame (1997) of a lack of convincing evidence of a soft bottom 161

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(α) diversity cline may still be valid. As noted by Hillebrand, many individual studies did not find significant gradients. A persistent problem with the assessment of global diversity patterns is that the spatial scale of the underlying data is often unknown and most likely mixed. This was a problem even in the earliest conflicting findings. When Thorson (1957) first proposed the pattern of a benthic epifauna diversity maximum in the tropics contrasted by a more geographically uniform infauna diversity, he was speaking mainly in terms of regional (γ) diversity compiled from large studies. When Sanders (1968) countered that infauna also show highest diversities on the tropical shelf, his supporting data were based on sample (α) diversity. Global comparisons of sample (α) diversity based on compilations of multiple studies are quite difficult due to lack of habitat comparability, non-standard methods, and inconsistent taxonomy. All of these factors may bias meta-analysis results. A narrower and more refined analysis was undertaken by Attrill et al. (2001) making appropriate comparisons by a careful screening of studies of intertidal mudflats. Twenty such studies were selected based upon a restricted salinity and median grain size range, comparable samplers, and use of a 500-µm sieve. Diversity was measured with Simpson’s index based on performance criteria suggested by Rozenweig (1995). Fisher’s (α) was rejected due to a lack of fit of the log-series for many of the datasets. Based on this high-quality data, an increase in diversity was found from high latitudes towards the equator. A similar approach could be applied to other habitats if datasets become available. Ideally, global gradients would best be determined through co-ordinated global sampling designed to examine a range of scales. An example of what can be accomplished is seen in the survey of subtidal rock wall epibiota by Witman et al. (2004). Smallest-scale species richness, extrapolated richness, and Choa2 estimates of full species richness were determined from photo transects on subtidal rock walls at twelve global sites. This meets the criteria that similar habitats be studied and scales be specified. Regional diversity was independently estimated on the basis of local species lists and experts. Both local and regional diversity increased toward the equator with higher latitudes having a greater per cent of the regional pool found in local samples. A more modest approach that controlled the uniformity of habitat to some degree was taken by Gobin & Warwick (2006) by putting artificial substrate at four regions from 10°N to 63°S. Shannon’s index and others were measured. Place to place differences were found, but neither polychaetes nor nematodes conformed to a latitudinal gradient. Similar global sampling could be conducted for infauna. Many large-scale studies are taxonomically restricted. While these studies seldom claim that the targeted taxon serves as a surrogate for total community diversity, surrogacy is often implied in the discussion of the theoretical consequences of the results. One of the best-examined components of global-scale diversity are the molluscs (Rex et al. 2004), and have the added benefit of speciation and extinction rates estimated from the fossil record (Jablonski et al. 2006). Many taxarestricted studies omit fine-scale assessment and determine larger-species richness from range compilations. A good example is the study by Roy et al. (2000) of 930 marine bivalves distributed on the eastern Pacific continental shelf between 71°N and 5°S. A strong latitudinal gradient with maximum species richness at about 10°N latitude was found. There was a good correlation between diversity and surface temperature. Taxa-restricted studies are often in conflict when different habitats and regions are studied. When Valdovinos et al. (2003) extended the molluscs study southward, a poleward increase in species richness was found but no correlation with surface temperature. Similarly, the infaunal protobranchs that showed no latitude gradient on the northeast Pacific shelf were shown to have such a gradient in the deep Atlantic (Allen & Sanders 1996, Rex et al. 1997, 2004).

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Deep-sea diversity Studies of large-scale diversity patterns in the deep sea continue to be hampered by a relative paucity of samples and a large backlog of undescribed species. Sampling is increasing, however, with the advent of deep-sea resource development, and a core of taxonomists who continue to make progress in species description. There are actually three benefits of the paucity of samples. First, diversity is usually measured on a fine-scale sample-by-sample basis, and then compiled for largerscale analysis. Second, so few sampling devices have been used that scales are well known. Third, the same experts have often been able to study many separate studies, assuring a high level of taxonomic comparability. The main large-scale gradients of interest are latitude and depth. There is also an interest in estimating the total species richness of this vast region. A variety of diversity tools have been used. Species richness is usually rarefied, and indices such as Simpson’s and Shannon’s are often used. A latitude gradient with increased tropical diversity has been reported for isopods (Poore & Wilson 1993), Foraminifera (Culver & Buzas 2000), polychaetes (Paterson & Lambshead 1995), bivalve molluscs (Rex et al. 2000) and cumaceans (Gage et al. 2004). Local and regionally compiled species richness combined with a regression was used to reach these conclusions. The analysis of Culver & Buzas (2000) was distinct and used species count data from more than 110 samples in published studies. Species richness, and Fisher’s α were calculated. Clear gradients were significant in a regression of these parameters against latitude for both measures of diversity. Wilson (1998) carried out isopod work restricted to the Atlantic, using Expected Species with rarefaction to 200 individuals on 66 samples. The isopods were partitioned into the Flabellifera and Asellota. The former showed negative correlation with depth and latitude. The latter showed positive correlation with only depth. Evolutionary history was thought to still exert a strong control over broad-scale patterns. The idea that the deep sea is species rich with a maximum diversity at some middle depth on the continental margin originated with Sander’s (1968) observation and is now reasonably well demonstrated around the north Atlantic (Rex et al. 1997). The generality of the pattern in the global ocean and across taxa is still open to valid questions (Gray 2001). In effect, there will have to be many better-designed shelf to abyss sampling programmes around the world to settle the matter. The mid-slope modal pattern can be viewed as unexpected from two perspectives. First, population sizes decrease progressively with depth due to loss of nutrient value of detritus as it sinks from its photosynthetic origins. Second the deep-sea bottom appears to become progressively more homogenous and possibly niche poorer with depth. The subject has received extensive recent review (Gray 2001, Levin et al. 2001, Snelgrove & Smith 2002, Tyler 2003) and a comprehensive book is in progress (Rex personal communication). Most analyses have been based on rarefacted species richness of samples and focus questions on diversity maintenance on small scales. Rex et al. (2005) examined compiled mollusc depth ranges assessing both species richness within depth bands and noting the range widths and end points. This approach to diversity analysis lead to the hypothesis that the abyssal region is a sink largely populated by species with larger populations at shallower depths on the slope. Deep-sea diversity has also been controversial with respect to global extrapolation of total marine species richness. Extrapolating the species accumulation curve generated from samples collected on the Atlantic continental slope of the United States, Grassle & Maciolek (1992) predicted a global marine species richness of the order of 108 species with most residing in deep water. This hyper diversity was quickly challenged on grounds of methodology (May 1992), and in light of contrary benthic diversity data (Gage & May 1993, Poore & Wilson 1993, Gray 1994). The notion

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has persisted, however, that the deep sea may be exceptionally diverse especially if poorly resolved groups like the nematodes were better studied. The issue of deep hyperdiversity has been specifically addressed and rejected in the case of nematodes by Lambshead & Boucher (2003) employing extrapolation methods. As a caution against extrapolating far beyond a region of sampling, it was shown that the extrapolation based on northsouth accumulation gave different results than accumulation East-West. Having established the tentative nature of the conclusions, accumulation curves and Chao methods were used to estimate total nematode diversity in 16 ocean regions over a wide depth range. The deep regions did not have an exceptionally high estimated diversity of nematode fauna. The question then revolves around the issue of local versus regional diversity and whether the deep sea substantially differed from shallower depths. At depth α diversity may be high while γ is comparably low due to a widespread but very patchy species pool across the great expanse of the abyssal plain.

Conclusions In undertaking the historical review I expected that early benthic ecologists would have expressed an interest in the variety of animals only to be hindered by a lack of analytical tools. Except for the mention of higher variety in deep water CHALLENGER samples (Murray 1895) and a criticism of the lack of relative abundance data (Stuxburg 1883), there was limited interest. Subsequent adoption of the rigid early community concept reduced the interest even more. As wrongly noted by Allee (1934), characterisation of the representative species was such a sufficent approach that details about the minor constituents were unnecessary; in effect total diversity was seen as irrelevant! There are, however, at least two lessons to be learned from history about species distributions and the parsimonious description of a community or assemblage. Thorson’s (1957) criteria for the selection of characteristic species and the four types of characteristic species that could be considered. First, the nature of the four types (first order, second order, third order, and influent) makes it clear that early workers recognised the relationship between geographic range and occurance in samples. The first-order species in a community were common but geographically restricted. The influents (fourth order) were common but found over too large a range to be useful in characterising a specific community found within that range. This is quite similar to the suggestion by Ugland et al. (2005) that benthic assemblages might be best considered a combination of a widely and narrowly distributed species. In future investigations small-scale diversity should be partitioned according to the larger ranges of the contributing species. Second, is the matter of parsimony. Historically characteristic species were used to name and map assemblages. Scientifically, there may be little value in the naming of assemblages. Much of the demand for biodiversity information, however, falls into the area of policy and political science. In this arena, it may be best to return to a system of assemblage nomenclature that first describes and maps assemblages in terms of characteristic species. Then, when greater scientific characterisation is needed, composition and diversity can be appropriately quantified. Certainly some improvement over “Maldane sarsi-Ophiura sarsi community” (Thorson 1957) is now possible, but equally simple and descriptive nomenclature should be of great utility when conservation is debated. Benthic ecologists face the issue of which diversity measure to use. Lande’s (1996) criteria that good measures of diversity should be non-parametric is widely accepted throughout ecology. Judging by the most common choice of methods, most benthic ecologists prefer to use non-parametric indices rather than fit a distribution to species abundance data. Nevertheless, the log-series has proven effective in application to benthic foraminiferans and is strongly advocated as a null model (Buzas & Hayek 2005). Similarly, the log-normal has proven effective in the study of macrobenthos and has been effectively advocated as a null model (Gray et al. 2006a,b). The great advantage of using a parametric distribution is that the full complexity of the data may be most parsimoniously 164

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described without the ambiguity of an index that combines two or more aspects of the sample. Therefore, it is valuable to retain the use of distributions especially when previous work on the same faunal components and in the same region have shown there to be a good and consistent fit. Non-parametric indices should be the preferable means of describing diversity when the data considered are from previously unstudied areas or faunal components. Similarly, when the spatial and temporal scale of sampling are so great as to include more than a single assemblage type, nonparametric indices are preferred. In his influential book Huston (1994) gave a brief but adequate discussion of diversity measures and offered the suggestion that a lot of exploration of these tools produced more mathematics than understanding of actual biological diversity. This may have seemed the case at the time, but some developments with origins in benthic ecology are truly innovative. Taxonomic distinctness and the associated measures of phylogenetic variability are the primary example. When the measure combines phylogenetic information with species richness and abundance as in the case of taxonomic diversity, it becomes an extension of how biological diversity is conceptualised. Once abundance is removed, however, it is probably best that these measures should not be treated as diversity in order to minimise confusion. The study of taxonomic distinctness is an endeavour in itself, and determining patterns across many marine habitats and taxa is an exciting new undertaking. Similarly, extrapolation from a small area of sea floor actually sampled to areas being considered for conservation management is an important advancement. The impact of computer technology on the study of diversity patterns cannot be overstated. However, this calls into question why ecologists still employ diversity analyses developed prior to easy access to digital computers? Indices like Simpson’s and Shannon’s are products of the mechanical calculator age when characterising fauna samples with more than a single value was a lengthy process. When patterns are found, they have to be dissected to be understood. How did species richness and relative abundance change? Scientifically, multiple measures should be used beginning with species richness, rarefacted values to allow for better comparisons, and then indices giving different weights to different fractions. In effect, ease of computation has already made this the standard approach in benthic ecology. In the policy area, however, only one or very few measures should be used. Species richness with an adjustment for sample size is the easiest to explain to a non-scientific audience. While the term informatics may seem like unnecessary jargon, having access to vast amounts of information through networked data sources is an extremely powerful tool. This is seen in Hillebrand’s succinct summation of latitudinal trend in the ocean and on land through the use of literature keyword searches and meta-analysis. A traditional scholarly review could only have produced a list of contradictory findings. There is, however, a limit to the utility of reviews, traditional or otherwise. Access to real data is preferable. Currently, there are several international efforts to create open data archives. Many databases are best suited for species-by-species investigation of occurrences, and will require additional development to be useful in diversity analyses that begin core by core. Once suitable formats are available, it can be hoped that complete regional surveys will be made available for re-examination. The importance of the assessment of diversity across multiple scales will continue to increase. Conservation policy needs information on the location of diversity hot spots and the spatial extent of relatively homogenous assemblages. Theoretical and applied ecology needs information on how regional species pools influence assemblages on local scales. Development of new cross-scale diversity measures is an active and needed area of research. Unfortunately, ambiguity as to what scales α and γ precisely refer to has made published results hard to interpret. Adhering to the niche theory view that local diversity must be influenced by competition and partitioning of resources, species count data should be collected, analyzed and initially reported on a consistently small scale. Benthic ecologists have a great advantage in this regard as grabs and corers are limited to less than 165

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0.5 m2. These point measurements can then be pooled into the larger sets allowed by sampling design to cover larger scales. Rather than depend too much on nomenclature, the scales should always be specified. As a final observation, there must be more large-scale studies conducted at locations carefully selected to test the effects of ocean processes upon diversity across a wide range of scales. Standard methods must be used and comparable taxonomy assured. Such well-designed studies will provide for a better understanding than re-examination of old archived data far beyond the level of inquiry anticipated in the original sampling designs. Ideally, scientific questions about ocean diversity are adequate to drive such ambitious new sampling and analysis. More realistically, monetary support is more likely to be mandated by resource mangers in the policy arena if diversity studies can be shown to be an indispensable management tool providing readily understood results.

References Allee, W.C. 1923. Studies in marine ecology. I. The distribution of common littoral invertebrates of the Woods Hole region. Biological Bulletin 36, 96–104. Allee, W.C. 1934. Concerning the organization of marine communities. Ecological Monographs 4, 541–554. Allen, J.A. & Sanders, H.L. 1996. The zoogeography, diversity and origin of the deep-sea protobranch bivalves of the Atlantic: the epilog. Progress in Oceanography 38, 95–153. Andelman, S.J. & Fagan, W.F. 2000. Umbrellas and flagships: efficient conservation surrogates or expensive mistakes? Proceedings of the National Academy of Sciences U.S.A. 97, 5954–5959. Anderson, A.N. 1995. Measuring more of biodiversity: genus richness as a surrogate for species richness in Australian ant faunas. Biological Conservation 73, 39–43. Attrill, M.J., Stafford, R. & Rowden, A. 2001. Latitudinal diversity patterns in estuarine tidal flats: indications of a global cline. Ecography 24, 318–324. Austen, M.C. & Widdicombe, S. 2006. Comparison of the response of meio- and macrobenthos to disturbance and organic enrichment. Journal of Experimental Marine Biology and Ecology 330, 96–104. Bertrand, Y., Pleijel, F. & Rouse, G.W. 2006. Taxonomic surrogacy in biodiversity assessments, and the meaning of Linnean ranks. Systematics and Biodiversity 4, 149–159. Bunge, J. & Fitzpatrick, M. 1993. Estimating the number of species: a review. Journal of the American Statistical Association 88, 364–372. Buzas, M.A. & Culver, S.J. 1989. Biogeographic and evolutionary patterns of continental-margin benthic foraminifera. Paleobiology 15, 11–19. Buzas, M.A. & Hayek, L.C. 2005. On richness and evenness within and between communities. Paleobiology 31, 199–220. Carney, R.S. 2005. Zonation of deep-sea biota on continental margins. Oceanography and Marine Biology: An Annual Review 43, 211–278. Chao, A. 1984. Non-parametric estimation of the number of classes in a population. Scandinavian Journal of Statistics 11, 265–270. Clarke, A. & Crame, J.A. 1997. Diversity, latitude and time: patterns in the shallow sea. In Marine Biodiversity: Patterns and Processes, R.F.G. Ormond et al. (eds). Cambridge: Cambridge University Press, 122–147. Clarke, K.R. & Warwick, R.M. 1998. A taxonomic distinctness index and its statistical properties. Journal of Applied Ecology 35, 523–531. Clarke, K.R. & Warwick, R.M. 1999. The taxonomic distinctness measure of biodiversity: weighting the step lengths between hierarchical level. Marine Ecology Progress Series 184, 21–29. Clarke, K.R. & Warwick, R.M. 2001. A further biodiversity index applicable to species lists: variation in taxonomic distinctness. Marine Ecology Progress Series 216, 265–278. Clarke, R.B. & Milne, A. 1955. The sublittoral fauna of two sandy bays on the isle of Cumbrae, Firth of Clyde. Journal of the Marine Biological Association of the United Kingdom 34, 161–180. Clements, F.E. & Shelford, V.E. 1939. Bio-ecology. New York: John Wiley and Sons.

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USE OF DIVERSITY ESTIMATIONS IN THE STUDY OF SEDIMENTARY BENTHIC COMMUNITIES Colwell, R.K. 2005. EstimateS Users Guide. Online. Available HTTP: http://purl.oclc.org/estimates (accessed 31 October 2006). Colwell, R.K. & Coddington, J.A. 1994. Estimating the terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London Series B 345, 101–118. Colwell, R.K., Mao, C.X. & Chang, J. 2004. Interpolating, extrapolating and comparing incidence-based species accumulation curves. Ecology 85, 2717–2727. Colwell, R.K., Rahbek, C. & Gotelli, N.J. 2005. The mid-domain effect: there’s a baby in the bathwater. American Naturalist 166, 149–154. Connolly, S.R. 2005. Process-based models of species distributions and the mid-domain effect. American Naturalist 166, 1–11. Costello, M.J. & Berghe, E.V. 2006. ‘Ocean biodiversity informatics’: a new era in marine biology research and management. Marine Ecology Progress Series 316, 203–214. Costello, M.J., Bouchet, P., Emblow, C.S. & Legakis, A. 2006. European marine biodiversity inventory and taxonomic resources: state of the art and gaps in knowledge. Marine Ecology Progress Series 316, 257–268. Crist, T.O. & Veech, J.A. 2006. Additive partitioning of rarefaction curves and species-area relationships: unifying α-, β-, and γ-diversity with sample size and habitat area. Ecology Letters 9, 923–932. Crozier, R.H. 1997. Preserving the information content of species: genetic diversity, phylogeny, and conservation worth. Annual Review of Ecology and Systematics 28, 243–268. Culver, S.J. & Buzas, M.A. 2000. Global latitudinal species diversity gradient in deep-sea benthic Foraminifera. Deep-Sea Research I 47, 259–275. Doerries, M.B. & Van Dover, C.L. 2003. Higher-taxon richness as a surrogate for species richness in chemosynthetic communities. Deep-Sea Research I 50, 749–755. Eduardo, C. & Grelle, V. 2002. Is higher-taxon analysis a useful surrogate for species richness in studies of neotropical mammal diversity? Biological Conservation 108, 101–106. Ellingsen, K.E. 2001. Biodiversity of a continental shelf soft-sediment macrobenthic community. Marine Ecology Progress Series 218, 1–15. Ellingsen, K.E., Clarke, K.R., Somerfield, P.J. & Warwick, R.M. 2005. Taxonomic distinctness as a measure of diversity applied over a large scale: the benthos of the Norwegian continental shelf. Journal of Animal Ecology 74, 1069–1079. Ellingsen, K.E. & Gray, J.S. 2002. Spatial patterns of benthic diversity: is there a latitudinal gradient on the Norwegian continental shelf? Journal of Animal Ecology 71, 373–389. Ellis, D. 1985. Taxonomic sufficiency in pollution assessment. Marine Pollution Bulletin 16, 459–459. Fabri, M.C., Galeron, J., Larour, M. & Maudire, G. 2006. Combining the Biocean database for deep-sea benthic data with the online Ocean Biogeographic Information System. Marine Ecology Progress Series 316, 215–224. Faith, D.P. 1992. Conservation evaluation and phylogenetic diversity. Biological Conservation 61, 1–10. Fisher, A.A., Corbert, A.S. & Williams, C.B. 1943. The relationship between the number of species and the number of individuals in a random sample of an animal population. Journal of Animal Ecology 12, 42–58. Foggo, A., Attrill, M.J., Frost, M.T. & Rowden, A.A. 2003. Estimating marine species richness: an evaluation of six extrapolative techniques. Marine Ecology Progress Series 248, 15–26. Forbes, E. 1859. Map of the distribution of marine life, illustrated chiefly by fishes, molluscs and radiata showing also the extended limits of the homoiozoic belts. In The Physical Atlas of Natural Phenomena, A.K. Johnson (ed.). Edinburgh: W. & A.K. Johnson. Ford, E. 1923. Animal communities of the level sea bottom in the waters adjacent to Plymouth. Journal of the Marine Biological Association of the United Kingdom 13, 165–224. Gage, J. 1972. Community structure of benthos in Scottish sea-lochs. 1. Introduction and species diversity. Marine Biology 14, 281–297. Gage, J., Lambshead, P.J.D., Bishop, J.D.D., Stuart, C.T. & Jones, N.S. 2004. Large-scale biodiversity patterns of Cumacea (Peracarida: Crustacea) in the deep Atlantic. Marine Ecology Progress Series 277, 181–196. Gage, J. & May, R.M. 1993 Biodiversity — a dip into the deep-seas. Nature 365, 609–610. Gage, J. & Tett, P.B. 1973. Use of log-normal statistics to describe benthos of lochs Etive and Creran. Journal of Animal Ecology 42, 373–382.

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ROBERT S. CARNEY Gaston, K.J. & Williams, P.H. 1993. Mapping the world’s species — the higher taxon approach. Biodiversity Letters 1, 2–8. Gobin, J.F. & Warwick, R.M. 2006. Geographical variation in species diversity: a comparison of marine polychaetes and nematodes. Journal of Experimental Marine Biology and Ecology 330, 234–244. Gorelick, R. 2006. Combining richness and abundance into a single diversity index using matrix analogues of Shannon’s and Simpson’s indices. Ecography 29, 525–530. Gotelli, N.J. & Colwell, R.K. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecological Letters 4, 379–391. Grassle, J.F. & Maciolek, N.J. 1992. Deep-sea species richness: regional and local diversity estimates from quantitative bottom samples. American Naturalist 139, 313–341. Gray, J.S. 1981a. The Ecology of Marine Sediments: An Introduction to the Structure and Function of Benthic Communities. Cambridge: Cambridge University Press. Gray, J.S. 1981b. Detecting pollution induced changes in communities using the log-normal distribution of individuals among species. Marine Pollution Bulletin 12, 173–176. Gray, J.S. 1983. Use and misuse of the log-normal plotting method for detection of effects of pollution — a reply. Marine Ecology Progress Series 11, 203–204. Gray, J.S. 1985. Ecological theory and marine pollution monitoring. Marine Pollution Bulletin 16, 224–227. Gray, J.S. 1994. Is deep-sea species-diversity really so high: species-diversity of the Norwegian continental shelf. Marine Ecology Progress Series 112, 205–209. Gray, J.S. 2000. The measurement of marine species diversity, with an application to the benthic fauna of the Norwegian continental shelf. Journal of Experimental Marine Biology and Ecology 250, 23–49. Gray, J.S. 2001. Marine diversity: the paradigms in patterns of species richness examined. Scientia Marina 65 (Suppl. 2), 41–56. Gray, J.S. 2002. Species richness in marine sediments. Marine Ecology Progress Series 244, 285–297. Gray, J.S., Bjørgesæter, A., Ugland, K.I. & Frank, K. 2006a. Are there differences in structure between marine and terrestrial assemblages. Journal of Experimental Marine Biology and Ecology 330, 19–26. Gray, J.S., Bjørgesæter, A., Ugland, K.I. & Frank, K. 2006b. On plotting species abundance distributions. Journal of Animal Ecology 75, 752–756. Gurevitch, J. & Hedges, L.V. 1993. Meta-analysis: combining the results of independent experiments. In Design and Analysis of Ecological Experiments, S.M. Scheiner & J. Gurevitch (eds). New York: Chapman Hall, 378–398. Hamilton, A.J. 2005. Species diversity or biodiversity? Journal of Environmental Management 75, 89–92. Harper, J.L. & Hawskworth, D.L. 1994. Biodiversity: measurement and estimation, preface. Philosophical Transactions of the Royal Society London Series B 345, 5–12. Hayek, L.C. & Buzas, M.A. 1997. Surveying Natural Populations. New York: Columbia University Press. Hedgepeth, J.W. 1957. Concepts of marine ecology. In Treatise on Marine Ecology and Paleoecology, J.W. Hedgepeth (ed.). The Geological Society of America Memoir 67, 29–52. Hedges, L.V. & Olkin, I. 1985. Statistical Methods for Meta-Analysis: Orlando, Florida: Academic Press. Hill, M. 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54, 427–432. Hillebrand, H. 2004a. Strength. Slope and variability of marine latitudinal gradients. Marine Ecology Progress Series 273, 251–267. Hillebrand, H. 2004b. On the generality of the latitudinal diversity gradient. American Naturalist 163, 192–211. Holme, N.A. 1966. Bottom fauna of the English Channel. 2. Journal of the Marine Biological Association of the United Kingdom 46, 401–493. Hubbell, S.P. 2001. The Unified Neutral Theory of Biodiversity and Biogeography. Princeton, New Jersey: Princeton University Press. Hurlbert, A.H. & White, E.P. 2005. Disparity between range map- and survey-based analyses of species richness: patterns, processes and implications. Ecology Letters 8, 319–327. Hurlbert, S. 1971. The non-concept of species diversity: a critique and alternative parameters. Ecology 52, 577–586. Huston, M.A. 1979. A general hypothesis of species diversity. American Naturalist 113, 81–101. Huston, M.A. 1994. Biological Diversity: The Coexistence of Species on Changing Landscapes. Cambridge: Cambridge University Press.

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ROBERT S. CARNEY Tyler, P.A. (ed.) 2003. Ecosystems of the Deep Oceans. Amsterdam: Elsevier. Ugland, K.I. & Gray, J.S. 1982. Lognormal distributions and the concept of community equilibrium. Oikos 39, 171–178. Ugland, K.I. & Gray, J.S. 1983. Reanalysis of Caswell neutral models. Ecology 64, 603–605. Ugland, K.I. & Gray, J.S. 2003. The species accumulation curve and estimation of species richness. Journal of Animal Ecology 72, 888–897. Ugland, K.I. & Gray, J.S. 2004. Estimation of species richness: analysis of the methods developed by Chao and Karakassis. Marine Ecology Progress Series 284, 1–8. Ugland, K.I., Gray, J.S. & Ellingsen, K.E. 2003. The species-accumulation curve and estimation of species richness. Journal of Animal Ecology 72, 888–897. Ugland, K.I., Gray, J.S. & Lambshead, P.J.D. 2005. Species accumulation curves analyzed by a class of null models discovered by Arrhenius. Oikos 108, 263–274. United Nations Conference on Environment and Development. 1992. Convention on Biological Diversity. Secretariat at the Convention on Biological Diversity. United Nations Environmental Program. Available HTTP: http://www.biodiv.org/convention/articles.shtml?a=cbd-02.html. Acessed 11 February 2007. Valdovinos, C., Navanete, S.S. & Marquet, P.A. 2003. Mollusk species diversity in the Southeast Pacific: why are there more species towards the pole? Ecography 26, 139–144. Veech, J.A., Summerville, K.S., Crist, T.O. & Gering, J.C. 2002. The additive partitioning of species diversity: recent revival of an old idea. Oikos 99, 3–9. Warwick, R.M. 1988. The level of taxonomic discrimination required to detect pollution effects on marine benthic communities. Marine Pollution Bulletin 19, 259–268. Warwick, R.M. & Clarke, K.R. 1995. New ‘biodiversity’ measures reveal a decrease in taxonomic distinctness with increasing stress. Marine Ecology Progress Series 129, 301–305. Warwick, R.M. & Clarke, K.R. 1998. A taxonomic distinctness index and its statistical properties. Journal of Applied Ecology 35, 523–531. Warwick, R.M. & Clarke, K.R. 2001. Practical measures of marine biodiversity based on relatedness of species. Oceanography and Marine Biology: An Annual Review 39, 207–231. Warwick, R.M., Dashfield, S.L. & Somerfield, P.J. 2006. The integral structure of a benthic infaunal assemblage. Journal of Experimental Marine Biology and Ecology 330, 12–18. Whitakker, R.H. 1960. Vegetation of the Siskiyou Mountains Oregon and California. Ecological Monographs 30, 279–338. Whitakker, R.H. 1972. Evolution and measurement of species diversity. Taxon 21, 213–251. Whitfield, J. 2002. Ecology: neutrality versus the niche. Nature 417, 480–481. Widdicombe, S. & Austen, M.C. 2001. The interaction between physical disturbance and organic enrichment: an important element in structuring benthic communities. Limnology and Oceanography 46, 1720–1733. Weiner, N. 1948. Cybernetics, or Control and Communication in the Animal and the Machine. Cambridge, Massachusetts: The Technology Press. Williams, P.H. & Gaston, K.J. 1994. Measuring more of biodiversity — can higher-taxon richness predict wholesale species richness? Biological Conservation 67, 211–217. Williamson, M. & Gaston, K.J. 2005. The lognormal distribution is not an applicable null hypothesis for the species-abundance distribution. Journal of Animal Ecology 74, 409–422. Wilson, G.D.F. 1998. Historical influences on deep-sea isopod diversity in the Atlantic Ocean. Deep-Sea Research Part II: Topical Studies in Oceanography 45, 279–301. Wilson, M. & Shumida, A. 1984. Measuring beta diversity with presence-absence data. Journal of Ecology 72, 1055–1064. Witman, J.D., Etter, R.J. & Smith, F. 2004. The relationship between regional and local species diversity in marine benthic communities: a global perspective. Proceedings National Academy of Sciences U.S.A. 1001, 15,664–15,669. Yule, G.U. 1944. Statistical Study of Literary Vocabulary. Cambridge: Cambridge University Press. Zenkevitch, L. 1963. Biology of the Seas of the USSR. London: Wiley Interscience. Zipf, G.K. 1935. Psycho-Biology of Languages. Boston: Houghton-Mifflin.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 173-194 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

CORAL REEFS OF THE ANDAMAN SEA — AN INTEGRATED PERSPECTIVE BARBARA E. BROWN School of Biology, University of Newcastle, Newcastle upon Tyne NE1 7RU, U.K. E-mail: [email protected] Abstract The Andaman Sea lies on the eastern edge of the Indian Ocean, bordered to the west by an arc of islands stretching from northern Sumatra to the Irrawaddy delta. Fringing reefs are abundant in the Andaman and Nicobar Islands (India), Mergui Archipelago (Myanmar), west coasts of Thailand and Malaysia and northwest Sumatra (Indonesia). Most have never been visited by scientists because of political constraints; consequently the region is one of the least studied coral reef areas in the world. Many inshore reefs are intertidal and occur in turbid settings, while offshore reefs exist in clearer waters. Regardless of physical rigours, reefs generally display high cover and high coral diversity. The Andaman Sea has a complex geological history, a varied seafloor topography, a highly dynamic oceanography and a large tidal range (2–5 m) coupled with periodic sea-level depressions. It is also a major sink for sediments from the Irrawaddy, the world’s fifth largest river in terms of suspended sediment load. Human-made influences are limited; sedimentation from land reclamation and dredging are a principal negative factor though rising sea temperatures present a major threat. Natural damage results from aerial exposure on low tides, negative sea-level anomalies, earthquakes and tsunamis. The dynamic nature of the Andaman Sea and the in-built stress resistance of many shallow water corals could result in the region being an important ‘refuge’ during an era of global warming.

Introduction Charles Darwin first described the extent of reef building in the eastern Indian Ocean in his book The Structure and Distribution of Coral Reefs published in 1842. He wrote: “The coast of Malacca, Tanasserim, and the coasts northward, appear in the greater part to be low and muddy: where reefs occur, as in parts of the Malacca Straits, and near Singapore, they are of the fringing kind; but the water is so shoal, that I have not coloured them” referring latterly to his shading of reef types on his map of worldwide reef distribution (his Appendix, p. 226). Similarly he dismissed reefs of the Andamans where recent publications of the day led him to doubt their existence (citing Asiatic Researches 4, 402). He acknowledged fringing reefs in the Nicobars which extended between 200 and 300 yards (185–277 m) from the shore, while for west Sumatra he commented on numerous reefs and banks. Since publication of Darwin’s book there have been several European-based expeditions to the region (Rao & Griffiths 1998) with much significant marine biology being done by the British surgeon-naturalists Alcock and Sewell. By 1933, some 90 yr after Darwin’s first mention of reefs in the region, it was recognised that extensive fringing reefs were indeed present throughout the Andaman Sea. They are particularly well developed in the Andaman and Nicobars, along the coastline of Myanmar and Thailand and the northwest tip of Sumatra and to a limited extent around the off-shore islands of Malaysia and along the Malacca Straits (Figure 1).

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95° East

100°

Irrawaddy Delta MYANMAR 15°

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10°

Ten Degree Channel

THAILAND

Phuket

Nicobar Islands

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0

5°

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200 km

95°

100°

Figure 1 Distribution of fringing reefs in Andaman Sea, based on information held in Reef Base (www.reefbase. org). Bold lines along shorelines represent fringing reefs.

Unfortunately up to the present day the Andaman Sea has never been viewed as an integrated entity and so the full biological significance of its fringing coral reefs has never been recognised. One reason for this is that major international initiatives under the aegis of the United Nations Environment Programme (UNEP: Regional Seas Programme), the International Union for Conservation of Nature and Natural Resources (IUCN) and the Global Coral Reef Monitoring Network (GCRMN) have followed political boundaries. Such demarcations divide the Andaman Sea in half partitioning the Andaman and Nicobar Islands to South Asia programmes and Sumatra, Thailand and Myanmar to southeast Asia. Yet, as this review will explore, the reefs within the region experience many common and unique characteristics.

Geological history, seafloor topography and related coral biogeography of the Andaman Sea The geology and plate tectonics of the Andaman Sea are extremely complex and the geological history of the region is inextricably linked to the tectonics and geological history of Myanmar, the Andaman and Nicobar Islands, Sumatra and the Malay peninsula (Curray 2005). Figure 2 outlines the tectonic setting of the Andaman Sea, its islands and the mainland of southeast Asia. The Andaman Sea extends some 1200 km from Myanmar to Sumatra and 650 km from the Malay 174

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Fault

100° 20° EURASIA PLATE

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f

o Banda Aceh

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al

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ac

ca

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at ra

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Figure 2 Tectonic structure of Andaman Sea. The naming of faults follows Pubellier et al. (2003).

peninsula to the Andaman and Nicobar Islands. Major tectonic features affecting the present appearance of the area include collision between the Indian and Eurasian plates, coupling and decoupling of platelets, crustal movement along fault lines, rotation of continental blocks and opening of marginal basins, such as the Andaman Sea (Khan & Chakraborty 2005). Where the two major 175

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plates meet, the oceanic (Indian) plate subducts beneath the continental Eurasia plate, causing clockwise rotation of the subduction zone and an increase in obliquity of the convergence (Curray 2005). The Indian plate begins its descent into the Earth’s mantle at the Sunda trench, which is a surface expression of the plate interface between the Australian and Indian plates situated to the southwest of the trench, and the Burma and Sunda plates, located to the northeast. Spencer (in press) describes the convergence as being partitioned into two components comprising both trench-normal subduction and forces parallel to the trench which generate strike-slip motions along major fault systems. As a result a sliver plate, the Burma plate, has sheared off parallel to the subduction zone and is located between the convergent margin to the west and the great fault systems (the Sumatra fault, West Andaman Fault, and Sagaing Fault to the east). In terms of timing of this tectonic activity the region has been significantly affected by at least three major geological events over the last 50 million yr. According to reconstructions by Hall (1998) the first major event occurred 50 million yr ago (Mya) with changes in the plate boundaries from the collision of India with Eurasia. At this time resultant mountain building led to major changes in both habitats and climates and was accompanied by significant changes in drainage systems. Huge volumes of sediment moved south from central Asia to the sedimentary basins of the Sunda Shelf. Approximately 25 Mya plate boundaries and motions changed once more due to the collision between the north Australian margin and arcs to the north. This tectonic event was probably very important, in terms of biogeography, because it led to new links between Australia and Southeast Asia across areas which included many shallow marine habitats. Approximately 5 Mya the positions and boundaries of the tectonic plates changed again with the rotation of north Sumatra and the partial coupling of the Burmese plate with the northeast-moving India plate. The Burma plate began to move north on the Sagaing fault, leading to the stretching of the Sunda continental margin north of Sumatra and to ocean crust formation in the Andaman Sea. While many workers have concluded that the Andaman Sea showed active spreading only during the past 4–5 Mya, others argue that spreading took place in two phases, one in the middle Miocene (~11 Mya) and another in the late Miocene–early Pliocene (4–5 Mya) (see Khan & Chakraborty 2005 for review). In terms of rate of spreading Guzman-Speziale & Ni (1993) estimated the spreading rate to be 3–5 cm yr−1 but more recent estimates (Curray 2005) put the value at 12 mm yr−1. Such physical upheaval over the last 50 million yr in this part of Southeast Asia is reflected in an active seismic history with records of earthquakes, uplift and subsidence in the Andaman and Nicobar Islands from the mid-1800s onward (Bilham 2005, Bilham et al. 2005). Large earthquakes have been recorded in these islands in 1847, 1881 and 1941 and most recently in nearby Sumatra in 2004 and 2005 and the Nicobars in 2005. Geological evidence for vertical motion of the islands dates back to Oldham (1884) who observed extensive uplifted marine terraces (2–2.6 m above sea level) throughout the coast of South Andaman Island (Bilham et al. 2005). The Andaman and Nicobar Island chain represent the peaks of a prominent ocean rise extending from eastern Myanmar to Sumatra. Geology of the islands has been reviewed by Madhaven et al. (1997), Pal et al. (2003) and Curray (2005). In brief, the assemblage of rocks found on the islands include the ophiolite complex of the late Cretaceous era, comprising a periotite, mafic and acidic suite of rocks; basaltic pillow lavas of the Upper Cretaceous to Palaeocene eras; massive silty stones, thinly bedded chert, pale yellow- and green-coloured limestone of the Palaeocene-Oligocene era and shelly limestones, fossil coral reefs and beach sand of recent age (Madhaven et al. 1977). The only active volcano in the Andaman Basin is Barren Island in the Andamans which last erupted in 1803 (Rodolfo 1969). Recent geological history suggests that the Pliocene-Pleistocene glaciations, which resulted in pronounced regressions and alternating transgressions of sea water, have also had an effect upon the region. About 18,000 yr ago sea level was about 120 m lower than today (Haneburth et al. 2000). In the Indo-Malaysian region land replaced much of the seas and bays and created an almostcomplete barrier between the Indian and Pacific Oceans — the emergence of this area, known as 176

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the northern Sunda Shelf, saw the extermination of extensive fringing coral reefs now evident as fossils along relicts of the Malaysian coastline (Tija 1980). Subsequent sea-level rise about 14,000 yr ago was rapid (16 m in 300 yr) due to a major melting event in polar regions (Haneburth et al. 2000). A sea-level curve derived from Singapore (Hesp et al. 1998) indicates that present sea level was reached between 6500 and 7000 yr ago; it then rose to +3 m before falling to present mean sea level about 3000 yr ago. The Singapore sea-level curve is supported by work of Tudhope & Scoffin (1994) and Scoffin & Le Tissier (1998) for Phuket, Thailand, in the Andaman Sea which showed that reef growth began here about 6000 yr ago when the low spring tide level was at least 1 m above its present height. The geological history of the region ultimately shapes the topography of the Andaman Sea floor (Figure 3). The major features have been summarised by Rodolfo (1969) and Curray (2005). The eastern portion of this marginal sea is dominated by the Malay continental margin, a 250-km wide shelf. An inner shelf, less than 100 m deep, encloses the Mergui Archipelago off Myanmar; the shelf gradually narrowing toward the south where it terminates in a minor slope with 100 m relief. Off Phuket the inner shelf is only 35 km wide, merging to the south and east with the Sunda Shelf and the Malacca Strait. Another major feature is the continental slope off the Malay peninsula with an outer shelf break that occurs at increasing depth southward to a maximum at 7°N latitude; pinnacles (200 m relief) mark the shelf break. The continental slope ends abruptly in a deep terrace 2435 m deep between the Sewell Rise and Martaban Canyon. This deep terrace slopes gently westward for 60 km to a depth of 2670 m where the sea floor drops steeply to 3075 m in the Central Andaman Trough. The Andaman-Nicobar Ridge is another significant feature which bounds the western portion of the Andaman Sea. The western coastlines of the Andaman and Nicobar Islands show little indentation and coastal plains are found only on these shores. The eastern shores are more indented and steep and in many places coral reefs and beaches are raised as high as 20 m above sea level (Sewell 1925). Major channels cross the Andaman-Nicobar Ridge divide the islands into four groups which are fringed by coral shelves 10–50 km wide west of the islands and less than 10 km wide on the east. It has been reported by Alcock (1902), Sewell (1925, 1935) and Rodolfo (1969) that the Andaman Islands are parallelled 22 km off their western coasts by a series of coral banks that have been described as a discontinuous barrier reef but these reports remain unconfirmed. The major channels between the islands include the Great Passage between Great Nicobar and Sumatra and the Ten Degree Channel between Car Nicobar and Little Andaman. To the west and northeast, Bay of Bengal and Andaman Sea waters interconnect through narrow channels 1000–2000 m deep. Coral biogeography of the region is closely linked to the geological and tectonic history of the area. Some of the earliest global records of scleractinian corals are found in the Andaman Sea region (Wilson & Rosen 1998) with upper Triassic (~180 Mya) scleractinian coral recorded on the Myanmar/Thailand border and in the Indonesian Archipelago (Stanley 1988). Other records include Upper Jurassic (~140 Mya) known from Sumatra, Myanmar and Thailand (Beauvais 1983) and a few corals from the Upper Cretaceous (~80 Mya) in northern Sumatra (Wilson & Rosen 1998). Generally corals were most common throughout Southeast Asia in the Upper Triassic and Upper Jurassic, reflecting times when corals flourished globally. Wilson & Rosen (1998) concluded that diversity of recent corals in the region has ultimately been controlled by plate tectonics. At the beginning of the Tertiary (~70 Mya) Australia was separated from mainland Southeast Asia by ~3000 km of ocean creating an ‘Indo-Pacific gateway’ which narrowed over the next 70 Mya as Australia moved northward. This fact combined with the emergence of new islands and shallowwater carbonate areas gave rise to potential for exchange of coral larvae with other regions and the establishment of coral communities. At the same time, during India’s drift northward suitable habitats for coral development may have occurred on narrow shelves with limited sediment input in the eastern Indian Ocean. Wilson & Rosen (1998) commented that the large deltas of the Irrawaddy 177

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East

100°

an C anyo n

95°

15° MYANMAR

2000 m

Mar tab

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Inner Shelf

Sewell Rise

10°

10°

200 m

South

500 m

0m 300 Central Andaman Trough

2000 m

Alcock Rise

2000 m

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5° SUMATRA

95°

100°

Figure 3 Seafloor topography of Andaman Sea. Bathymetry reproduced from GEBCO Sheet G.08 compiled by R.L. Fisher of Scripps Institution of Oceanography and extracted from GEBCO Digital Atlas published by British Oceanographic Data Centre for IOC and IHO, 2003.

and Ganges currently inhibit coral growth in their immediate vicinity, forming coastal barriers to biogeographical exchange of many shallow-water organisms in the northern Andaman Sea. The Pliocene-Pleistocene glaciations and the exposure of the Sunda Shelf would also have significant implications for coral biogeography (Potts 1983, Myers 1991). The Andaman Sea was probably bounded at this time by the Andaman and Nicobar Island bridges which may have promoted speciation and endemism in the Andaman Sea (Satapoomin 2002). Several endemic reef fishes have been identified (McManus 1985, Satapoomin 2002) though no corals specific to the Andaman Sea have yet been described. Two Acropora species are endemic to India/Sri Lanka and the Andaman Sea (Wallace & Muir 2005). The authors warn that present identifications underrepresent the overall species composition of the region and, as a result, potential endemicity. 178

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A recurrent feature of papers dealing with the biogeography of the region is that it has been an area where the scope to develop diverse communities has been controlled by the way suitable habitats have been continually created, reorganised and lost through tectonic movements (Wilson & Rosen, 1998) and natural events such as volcanism, sediment influx and storm damage (McManus 1985).

Physical influences affecting coral reefs Oceanography Circulation of the Indian Ocean is strongly influenced by the seasonal reversal of the monsoon winds and their effect on ocean currents in the Northern Hemisphere as described in Tomczak & Godfrey (1994). When the northeast monsoon is established the North Equatorial Current runs as a narrow current of about 0.3 m s−1 from the Malacca straits to southern Sri Lanka passing through the Andaman Sea en route. The transition from northeast to southwest monsoon is characterised by the easterly moving, intense Indian Equatorial Jet first described by Wyrtki (1973) with velocities of 0.7 m s−1 or more. When the southwest monsoon is fully established, during July–September, the northern Indian Ocean is dominated by the eastern flow of the South West Monsoon Current which enters the Andaman Sea via the Bay of Bengal. The transition before the onset of the northeast monsoon is also characterised by the equatorial jet which concentrates eastward flow in a 600-km wide band along the equator. It reaches its peak in November with velocities of 1.0–1.3 m s−1 and disappears in early January when the cycle is repeated (Tomczak & Godfrey 1994). A comprehensive review of oceanography of the Bay of Bengal and Andaman Sea is provided by Varkey et al. (1996) and combines actual observations by Varkey (1986) with results of a simulation model driven by climatological monthly mean winds (Potemra et al. 1991). Potemra’s model was a four-layer isopycnal model that used the 200-m contour as the land boundary. Both Varkey et al. (1996) and Potemra et al. (1991) described surface circulation in the Andaman Sea as a double gyre with anticlockwise flow during the northeast monsoon and clockwise flow in the southwest monsoon. Earlier work by Soegiarto & Birowo (1975) and Soegiarto (1985) and simulations using the Ocean Circulation and Climate Advanced Model (OCCAM) by P. Hyder (personal communication) do not reflect these gyres but do broadly agree on the predominant direction of current flow throughout the year as shown in Figure 4. This figure is probably an overly simplistic representation of current flow but is the best available at the present time. The earlier model used by Potemra et al. (1991) suggests surface flow enters the Andaman Sea south of the Nicobar Islands during the northeast monsoon and exits south of the Andamans. During the southwest monsoon flow enters from the Bay of Bengal, circulates clockwise and exits via the southern Andaman Sea. Khokiattiwong (1991) found that off the west coast of Thailand shallow-water currents were strongly influenced by tidal currents during the northeast monsoon. In later work S. Khokiattiwong (personal communication) suggested that there are two major water masses influencing flow around Phuket on the west coast of Thailand. One, a northern water mass, is described as flowing clockwise from the Bay of Bengal along the Andaman Sea coast of Thailand to Phuket where it meets a southern water mass flowing from the Malacca Strait northward in a counterclockwise direction before it flows east to the Indian Ocean. Between the two water masses there is a mixing zone which shifts further to the north or south of Phuket depending on the effects of the reversing monsoon. Such interpretations are based on salinity and temperature distributions and measurements of sea-level height. The highly dynamic nature of the Andaman Sea is reflected in current flow at depth (>200 m) where Potemra et al. (1991) suggested that flow changes direction three times a year. In January, February and March flow is clockwise; between April and July it is anticlockwise; from August to October it becomes clockwise before reverting to anticlockwise in November and December. 179

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East 95°

100°

Myanmar 15°

15° Andaman Islands

South 10°

10° Thailand Nicobar Islands

5°

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75 cm/sec

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Myanmar 15°

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South 10°

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Figure 4 Predominant surface currents in the Andaman Sea in the northeast monsoon (December–May) and the southwest monsoon (June–November) after Soegiarto & Birowo (1975) and Soegiarto (1985). Arrows depict current strength. (Data reproduced with the permission of the United Nations Environment Programme. UNEP Regional Seas Reports and Studies No. 69 (1985).)

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While precise details of water movements within the Andaman Sea remain speculative other hydrographic features have received considerable attention. Large-amplitude, long-interval waves, with associated surface waves (‘rips’), have been observed in the Andaman Basin (Osborne & Burch 1980, Osborne 1990, Hyder et al. 2005). These internal waves, which are apparently due to non-linear internal tides (or solitons), have been observed as surface rips in satellite imagery of the Andaman Sea (Alpers et al. 1997). The waves propagate within subsurface layers of the sea that are stratified because of temperature and salinity variations and appear to result from tidal interaction with tidal sills and seamounts, spreading radially from the source. The length of the wave becomes longer as the waves spread out from the source. In the southern Andaman Sea the waves occur in packets of 4–10 and propagate several hundred kilometres before encountering the Thai coastline. The waves are normally rank ordered by amplitude (crest-to-trough distance) with the largest wave leading the rest. In one event, the amplitude of the foremost wave was estimated to be 60 m with the warm water from above being pushed down by the internal soliton by 60 m (Alpers et al. 1997). Bands of surface rips accompany the internal waves; these bands are 600–1200 m wide, stretch 10–100 km across the sea surface and can be observed in satellite photographs. In the northern Andaman Sea the waves only occurred on spring tides when the tidal range exceeded 1.5 m and the probability of their occurrence increased with tidal range (Hyder et al. 2005). Internal waves represent a significant mechanism for the transport of momentum and energy within the ocean (Osborne & Burch 1980) and possibly lead to increased mixing, perturbation of temperature and salinity gradients and potential increases in primary and secondary production in coastal waters (Nielsen et al. 2004). In addition to internal waves, a longer-period internal oscillation has been observed in the northern Andaman Sea resulting in a downward perturbation of the pycnocline (the density gradient caused by the thermocline) by 80 m in a survey period between January and April 1998 (P. Hyder personal communication). These observations have been attributed to eastward-propagating Kelvin-like waves which propagate parallel to the continental slope. Such waves also have considerable implications for mixing processes in the Andaman Sea. Upwelling is another significant feature of the Andaman Sea. Yesaki & Jantarapagdee (1981) suggested that coastal upwelling on the west coast of Thailand is a recurrent phenomenon generated by the monsoon system. In recent work Nielsen et al. (2004) argued that the shelf area of the Andaman Sea has the potential of being a productivity ‘hot spot’ with stratified water meeting mixed coastal water in combination with very dynamic oceanography. While high production was not noted at the shelf break in this study the site of particularly high production was at the midshelf front where breaking of the shoaling waves introduced cold, nutrient-rich water to the euphotic zone.

Tidal influences and sea-level fluctuations Most coral reefs in the Andaman Sea are subject to semi-diurnal tides. Mesotidal areas with a spring tide range of 1–2 m are found in the Andaman and Nicobar Islands and along the north/northwest coast of Sumatra while macrotidal ranges are found along the coast of Thailand (~3 m) and the Mergui Archipelago (>5 m) of Myanmar. Sea levels in the region show high annual variability (Figure 5) with considerable anomalies in some years (Dunne & Brown 2001). Both in situ and remote satellite measurements of sea level along the Thai coastline are well matched over the period shown, apart from two periods of pronounced positive anomalies reflected in the in situ data in early 1994 and 1997 (which are probably the result of Kelvin waves moving along inshore areas) but not in the off-shore altimeter record. Large negative sea-level anomalies of −21 and −27 cm are obvious in late 1994 and late 1997, respectively. A period of negative sea-level anomalies in 1994–1995 extended over 9 months from May 1994 181

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N7.777 E97.05 N7.83 E97.07 Ko Taphao Noi

40

Sea level anomalies (cm)

30 20 10 0 −10 −20 −30 −40

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Figure 5 Sea-level anomalies for Ko Taphai Noi tide station, Phuket, Thailand (shown as monthly means) and from TOPEX/POSEIDON satellite altimeter records at two off-shore stations. (From Dunne & Brown 2001. With permission of Springer Science and Business Media.)

to January 1995 whereas the more pronounced negative anomalies of 1997–1998 persisted over 11 months from July 1997 to May 1998. Such negative sea-level anomalies are a regular feature in the Andaman Sea and Indian Ocean and were first described by Webster et al. (1999). These authors described the anomalies as the result of ocean-atmosphere-land interactions in the Indian Ocean which occur primarily as a result of a reversal in sea temperature gradient between east and west basins of the Indian Ocean. During this process there is substantial warming in the western basin of the Indian Ocean with higher sea levels, lowered thermocline and reduced upwelling. In contrast, sea level is depressed in the eastern Indian Ocean and the position of the thermocline is raised with resultant enhanced upwelling. This phenomenon is known as the Indian Ocean Dipole, and although Webster et al. (1999) considered the phenomenon internally forced others believe that the anomalies are externally forced by connection with the Pacific El Niño Southern Oscillation (ENSO) (Allan et al. 2001). The resultant sea-level depressions may cause significant mortality on shallow coral reefs throughout the Andaman Sea (Brown & Phongsuwan 2004). Not only are low tides much lower than normal, involving greater exposure of reef flat organisms for longer periods, but the times of exposure are also altered. Marine organisms may, as a result, find themselves exposed at mid-day under maximum solar radiation rather than early morning and evening when solar radiation is minimal.

Sea temperatures and salinity Monthly sea temperatures in the Andaman Islands range from 28.1°C in January to a maximum of 29.8°C in May while on the Thai coast temperatures range from 27.8°C in January to a maximum of 29.5°C in May (Brown et al. 1996). Recent analyses of historical sea temperature data and contemporary continuous sea-surface measurements in the Andaman Sea at Phuket show an interesting trend for the eastern Indian Ocean (Figure 6) where there has been a significant increase in sea-surface temperatures over the last 50 yr of at least 0.126°C decade−1 (Brown et al. 1996). This is consistent with positive trends in the Indian Ocean area demonstrated by others (Hoegh Guldberg 182

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1997 1998 1991 1995

30.1°C

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Figure 6 Monthly mean sea-surface temperatures (SST) 1945–2004 from the Meteorological Office Historical Sea Surface Temperature (MOHSST 6) dataset for Andaman Sea area off Phuket. Regression line for all points shown (p < 0.001). The 30.1°C line represents an approximate coral bleaching threshold since solar radiation levels, as well as sea temperature, have a significant part to play in bleaching.

1999) and with current predictions of the Intergovernmental Panel on Climate Change (IPCC 2001). Such trends have major implications for all marine fauna, particularly many corals which have been shown to be extremely sensitive to increases in temperature, bleaching (losing colour through loss of essential algae and/or their pigments) when temperatures exceed their seasonal maxima by only 1°C. Salinity measurements in the Andaman Sea are limited. According to Varkey et al. (1996) surface salinity varies between 32 in the northern Andaman Sea to 33 in the south during the northeast monsoon. In support of these values Janekarn & Hylleberg (1989) found surface salinities of between 32.1 and 33.6 in coastal waters of Phuket in the southern Andaman Sea and Desai et al. (1988) values ranging from 31 to 32.8 in the northern Andaman Sea. Varkey et al. (1996) provided no salinity data for the Andaman Sea in the southwest monsoon though Tomczak & Godfrey (1994) reported salinities below 25 in the central Andaman Basin at this time. Desai et al. (1988) described very low salinities (but give no values) due to river discharge during the southwest monsoon in the northern Andaman Sea, noting that below the surface salinity increases rapidly with a strong halocline developing at 10–60 m after the southwest monsoon period.

Sedimentation Major rivers discharge into the Bay of Bengal, north of the Andaman Sea and directly into the Andaman Basin and have done so for thousands of years. The Ganges/Brahmaputra delta is the largest estuarine system in the world with an estimated average annual suspended load of 2,179,000 × 103 tonnes (mt) and an average discharge of 31.5 × 103 m3 s−1 (Rao & Griffiths 1998). Sediments, sourced from the Himalayas, are discharged into the Bay of Bengal where they contribute to the Bengal Fan, which is the world’s largest accumulation of sediments. The Irrawaddy in Myanmar also makes a significant sedimentary contribution directly into the Andaman Sea with an average annual suspended load of 300,000 × 103 mt and an average discharge at the mouth of 13.6 × 103 m3 s−1. Ramaswamy et al. (2004) gave a comprehensive account of the fate of the Irrawaddy 183

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discharge providing turbidity profiles that show transport of sediments into the deep Andaman Sea via the Martaban Canyon. While sedimentation limits reef growth in the vicinity of these enormous river discharges coral reefs do flourish in inshore turbid settings on all islands and mainland areas bordering the Andaman Sea where they receive considerable local drainage from mangrove forests. Indeed these waters, enriched in particulate and dissolved organic matter, may be of considerable benefit to the corals of the region as described in later sections of this review.

Biological characteristics of coral reefs in the Andaman Sea Reef type and coral diversity Fringing reefs dominate all sites within the Andaman Sea with the only ‘barrier’ reef reported by Sewell (1935) on the west coast of the Andaman Islands. This observation remains to be confirmed though Turner et al. (2001) also noted off-shore reef structures on the west side of the Andamans in a recent survey using satellite imagery. Throughout the Andaman Sea fringing reefs tend to be better developed on the eastern sides of islands (Phongsuwan & Chansang 1992, Spalding et al. 2001) where they are not exposed to the southwest monsoon influence. In northern Aceh, Sumatra reef development is mainly on the west side of the mainland and on off-shore islands to the north (A.H. Baird personal communication). Extensive intertidal reefs flats are found throughout the region (Figure 7). Sheltered reefs are dominated by a high cover of Porites species and faviids while those receiving more wave exposure are dominated by the branching corals Acropora spp., Pocillopora damicornis and Montipora digitata. Such a distribution pattern associated with wave exposure is common throughout the whole Indo-Pacific (Rosen 1975) although A.H. Baird (personal communication) noted very little M. digitata on reefs in Aceh, in northern Sumatra. In the Andamans and Nicobars the width of reef flats is considerable, ranging from 200 to 500 m (UNEP/IUCN, 1988). Many of these reefs support significant growth of alcyonarians as well as stony corals. Extensive reef flats may also be found on the mainland coast of Thailand and occasionally in Aceh. Generally, reefs along the coast of mainland Thailand are found at depths of 5–15 m whereas those on off-shore islands are found in depths down to 30 m. A detailed mapping of Thailand’s reefs in the Andaman Sea has been carried out and the results are published in Chansang et al. (1999). The most abundant species in deeper water are Porites lutea, Acropora intermedia, A. muricata (formally formosa) and Porites (synaraea) rus (Phongsuwan & Chansang 1992). These authors also noted that coral communities on off-shore islands are usually formed of a single species on the reef slope, while those on near-shore islands comprise mixed species. As a result, diversity is higher at near-shore sites than at off-shore locations. In addition to fringing reefs, the reefs of some off-shore islands develop principally in bays as scattered isolated coral heads, clumps and thickets of coral which have a high percentage of living coral. An array of reef types has been described in the Andamans and Nicobars by Reddiah (1977) and in the Andamans by Turner et al. (2001). These include channel reefs, which are found on shorelines between islands where wind and wave influences are less severe with slopes down to 20 m depth, and knoll reefs which occur in channels and patch reefs. Where sediment levels are high and calm conditions prevail, inshore reefs are dominated by poritid and faviid corals similar to those described on the west coast of Thailand (Reddiah 1977). In more wave-exposed situations reef edges are dominated by Acropora, Pocillopora and Montipora. On the northwest coast of Sumatra the outer reef edges of off-shore islands also support high-energy coral reef associations of Acropora and Pocillopora (A. Kunzmann personal communication). In the Nicobars, seaward edges of reefs on the west side of the islands have well-developed spurs and grooves with surge channels about 1 m deep and 1 m wide and dominated by calcareous red algae (Reddiah 1977). 184

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A

B

C

Figure 7 Fringing intertidal reefs in the Andaman Sea. (A) Havelock Island Andamans; reef is dominated by alcyonarians. (Photograph courtesy Jason Reubens.) (B) Southeast Phuket; reef is dominated by Acropora aspera, A. pulchra and Montipora ramosa. (Photograph courtesy Barbara Brown.) (C) Paway Island, Mergui Archipelago, Myanmar; reef is a mixture of massive (Porites sp.) and branching corals. (Photograph courtesy R.B.S. Sewell.)

Unfortunately very little ecological information is available for the reefs of the Mergui Archipelago in Myanmar although the southernmost reefs appear to resemble, in terms of coral communities, those of the Surin Islands in Thai waters to the south. Initial surveys suggest that the majority of reefs visited in the southern Mergui have >50% cover (Wilkinson 2004). 185

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Table 1 The number of zooxanthellate corals recorded to date at selected locations in the Andaman Sea Location Andaman Islands Andaman Islands Andaman Islands Andaman and Nicobar Islands Andaman and Nicobar Islands Nicobar Islands Nicobar Islands Mergui Archipelago Mergui Archipelago West coast of Thailand West coast of Thailand

No. of coral species

No. of coral genera

57 49 187 110 203 64 ND 51 65 268 353

23 15 56 45 ND 19 40 26 ND 66 69

Reference Pillai 1972 Reddiah 1977 Turner et al. 2001 Pillai 1983 Wilkinson 2004 Reddiah 1977 Scheer 1971 Summarised by Pillai 1972 Wilkinson 2004 Phongsuwan in press Turak et al. 2005

Note: ND, not described.

Table 1 summarises the level of diversity of corals throughout the region. The values are very variable even for a single region and reflect, in the Andaman Islands for example, limited sampling in earlier studies. In several of the publications cited, corals have been designated variously as hermatypes or non-hermatypes, zooxanthellate or non-zooxanthellate and scleractinian or nonscleractinian which makes cross-comparison between studies very difficult In addition, it is likely that figures given for the Mergui Archipelago and the Nicobars are underestimates because no comprehensive surveys have been carried out here or on the northwest tip of Sumatra. While Andaman Sea reefs are some of the most diverse in the Indian Ocean they have previously been reported as being less diverse than those in the Philippines and Indonesia. Recent surveys in western Thailand, however, now report 353 coral species (Turak et al. 2005) which brings the Andaman Sea into the Indo-Pacific ‘coral triangle’ of high biodiversity centred on Indonesia to the east. Interestingly, a number of these newly recorded coral species were previously known only from the Pacific. Despite limited sampling Wallace (1999) noted at least 55 species of Acropora in the Andaman Sea, a figure which is exceeded in the Indian Ocean only in the ‘eastern Indian Ocean’ which boasts 71 species and ranks alongside the most diverse areas of the world. Of Acropora species recorded in the Andaman Sea, 51 are regarded as widespread and are present in 12 of the 29 biogeographic areas described in the Indo-Pacific.

Physiological attributes of reef corals in the Andaman Sea Early work on zooxanthellae densities in corals suggested that they were remarkably constant, ranging from 1 × 106 to 2.5 × 106 algae cm−2 (Drew 1972). Subsequent work has shown more variability particularly in corals from turbid waters such as those which characterise shallow inshore areas of the Andaman Sea. In reef-flat corals from Phuket, algal densities per square centimetre of coral tissue ranged from 0. 6 × 107 to 1.4 × 107 in Porites lutea, 0.4 × 107 to 1.8 × 107 in the faviid Goniastrea retiformis and 0.8 × 107 to 2.6 × 107 in the faviid G. aspera and agaricid Coeloseris mayeri (Brown et al. 1999). Massive corals from inshore turbid waters around Singapore (B. Goh personal communication) and Java (Suharsono & Soekarno 1983) have similar high algal densities. Non-massive reef-slope corals at Phuket also show relatively high algal densities ranging from 186

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5 × 106 cm−2 (Psammocora digitifera) to 6 × 106 cm−2 (Mycedium elephantotus) (Satapoomin 1993). A potential influence on algal density is the nutrient content of surrounding sea water because experimental studies have shown that the density of algae increases on exposure to elevated nutrient concentrations (Stambler et al. 1991). The concentration of dissolved nutrients at Phuket is high all year round due to drainage from extensive mangrove areas to the north and oceanic upwelling off shore (Janekarn & Hylleberg 1989). Brown et al. (1999) compared levels of dissolved nutrients at Phuket with other reef sites worldwide and showed that values of nitrate, nitrite and phosphate recorded at Phuket were high, ranking alongside other inshore locations in the Florida Keys and Barbados which experienced eutrophication. In addition, particulate load is elevated in inshore waters, frequently reaching 20–40 mg l−1 (Scoffin et al. 1992, Panutrakul 1996). Particulates are derived from fine terrigeneous sediments composed of clay minerals. It is likely that these particulates, coated with bacteria and microalgae, present added potential nutrients to particulate-feeding corals in the region (Anthony 1999). As a result corals have the potential to benefit from both autotrophic and heterotrophic feeding. The algal genus Symbiodinium, which forms a symbiotic relationship with corals, is diverse and molecular analyses have shown that there is considerable variation at the level of the ribosomal RNA genes. It comprises two clades, one known as phylotype A and the other which includes phylotypes B–F (LaJeunesse 2001). Of all the phylotypes so far evaluated phylotype D appears to be the most thermotolerant (Rowan 2004). Interestingly, phylotype D is present in many shallowwater corals and zoanthids throughout the Indian Ocean (Goodson 2000, Burnett 2002) whereas this phylotype is relatively rare on the southern Great Barrier Reef and in the Caribbean (LaJeunesse et al. 2003). On extensive reef flats of the east coast of Phuket, Thailand phylotype D was identified in all six species (four genera) sampled. In most cases D was present to the exclusion of all other phylotypes apart from Acropora pulchra which contained a mixture of C and D. Interestingly, in Goniastrea aspera, which is a cosmopolitan intertidal reef species throughout the Indo-Pacific, colonies from the southern Great Barrier Reef contained phylotype C (LaJeunesse et al. 2003) although only phylotype D has been found in this species at Phuket (Goodson 2000). Since the rigours of intertidal living are similar on the Great Barrier Reef to those in Thailand it appears that something other than environmental constraints might be acting to produce this distribution pattern. Burnett (2002) believes that biogeography may play a major role in the distribution of symbionts in the zoanthid Palythoa in the Indian Ocean. If this is also true for corals, then the presence in a wide variety of coral species of the most thermotolerant algal symbiont known could have important implications for the impacts of global warming. Another noteworthy feature of corals in the Andaman Sea (in this case specifically massive corals from the west coast of Thailand) is their rate of skeletal extension, which appears to be higher than any other recorded in the Indo-Pacific. Buddemeier & Kinzie (1976) described extension rates for massive corals in optimal settings around the world as 10–15 mm yr−1 with the rate for Porites spp. being slightly higher. Lough & Barnes (2000) compared the extension rates of P. lutea from 44 Indo-Pacific reefs (29 on the Great Barrier Reef; 14 in the Hawaiian Archipelago and 1 close to Phuket, Thailand). The Thai study was carried out by Scoffin et al. (1992). Skeletal extension and calcification was significantly higher in corals from Phuket compared with those from other Indo-Pacific sites, being two to three times higher than corals from the Great Barrier Reef and at least a third higher than Hawaiian corals. According to Lough & Barnes (2000) such differences were strongly linked to sea temperature with the highest sea temperature being found in the Andaman Sea. In the original study of Thai corals Scoffin et al. (1992) showed that skeletal extension rates in P. lutea ranged from 1.35 cm yr−1 at off-shore sites to 3.25 cm yr−1 at inshore locations. The significant difference in extension rates between sites was attributed to wave energy, with linear extension decreasing along a gradient of increased hydraulic energy. Clearly environmental factors are important in controlling coral skeletogenesis but one factor which has not been 187

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taken into account above is the nutrient content of sea water. Earlier descriptions in this review of sites in the Andaman Sea have highlighted the extent of turbid, high-nutrient, sheltered inshore reef settings which may have a bearing on the remarkably high zooxanthellae densities recorded in shallow-water corals. If the synthesis of organic matrix (upon which crystals of calcium carbonate are deposited in the coral skeleton) is a product of the zooxanthellae, as earlier work on calcification suggests (Johnstone 1980), then the observed rapid skeletal extension of corals in the Andaman Sea may be a result not only of high sea temperature and reduced wave energy but also of high nutrients. It is not clear how universal these growth characteristics might be in the Andaman Sea but it is likely that, because of the similarity of environmental conditions throughout the region, it is more widespread than the west coast of Thailand. The high tidal range (2–5 m) at many sites in the Andaman Sea, which favours extensive intertidal reefs in the region, results in many coral species being exposed to rigorous environmental conditions during low spring tides. During these periods, corals will be exposed to extremely high sea temperatures, high solar radiation, and reduced salinities. To survive in these settings the corals have developed remarkable environmental tolerances to temperature, light, desiccation and salinity. Protective mechanisms range from behavioural responses which induce rapid tissue retraction (Brown et al. 2002a) to photoprotective mechanisms such as xanthophyll interconversion and biochemical defences that include antioxidant enzyme and heat-shock protein production in both coral host and symbiotic alga (Brown et al. 2002b). Not surprisingly all these mechanisms are particularly well developed in intertidal corals in the region which are capable of withstanding up to 3-h aerial exposure at low spring tides. Relatively few assays of such defences have been monitored worldwide, but in the few studies that have been carried out production of stress responses by intertidal corals from the Andaman Sea (e.g., Goniastrea aspera) are many-fold higher than subtidal species such as Montastraea faveolata from the Caribbean when exposed to similar stress levels (Downs et al. 2000, Brown et al. 2002b). It is interesting to note that although there has been marked coral bleaching in years with anomalous sea temperatures such as 1991, 1995 and 2003, the intertidal reefs around Phuket, Thailand, have shown no significant mortality (Brown & Phongsuwan 2004) — a result which is testimony to the fact that these corals are well endowed with effective environmental defences and have the potential to acclimatise and adapt to varied environments.

Natural and human influences on coral reefs in the Andaman Sea The coral reefs of the Andaman Sea have been described as some of the most diverse, extensive and least disturbed by human intervention in the Indian Ocean (Wallace & Muir 2005) particularly with respect to the Andamans and Nicobars and Myanmar (Wilkinson 2004). There is generally a low level of human interference in the region apart from Aceh in Sumatra, where damaging fishing practices have negatively affected reefs (A.H. Baird personal communication). Thai reef scientists report very few incidences of damaging fish practices in their waters (U. Satapoomin personal communication) but highlight the establishment of marine protected areas as a factor which minimises such activities. Within the Andaman Sea there are at least 100 nominated marine protected areas in the Andamans and Nicobars, 2 in Myanmar, 13 in Thailand, 2 on the northwest coast of peninsular Malaysia and 1 on the northwest tip of Sumatra (Spalding et al. 2001). Enforcement procedures, however, are not rigorous in the majority of these designated areas. Despite a low level of human influences shallow reefs are subject to natural disturbances which include exposure to high solar radiation during aerial exposure, lowered sea level during Indian Ocean Dipole events, decreased salinity from heavy rain at low tide, tsunami-related damage and volcanic uplift. There is evidence of marked partial mortality as a result of exposure of faviid 188

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colonies to high solar radiation at low tide on reefs in the Andamans, west coast of Thailand and Malaysia (Brown et al. 1994) and this phenomenon, which is induced by solar bleaching, is probably widespread throughout the region. Unusually low spring tides also cause coral mortality with sealevel depressions of 1994 and 1997–1998 (>20 cm experienced over 8–10 months) resulting in considerable coral mortality on shallow reefs of western Thailand (Brown & Phongsuwan 2004). Again, these events affect reefs throughout the region, particularly those on the northwest coast of Sumatra where the sea-level depression of 1997–1998 exceeded 30 cm for several months (Webster et al. 1999). This review has already highlighted the fact that earthquakes and resultant tsunamis have been a recurrent historic feature of the Andaman Sea although the 26 December 2004 earthquake was unprecedented in scale. Uplifted reef flats (raised by 1–2 m) were reported as a result of the earthquake on the southwest coast of Simeulue, off the west coast of Sumatra (Sieh 2005) and also in the Andaman Islands (Searle 2006). Reefs uplifted by the earthquake on the west coast of islands along the 1000-km arc from Sumatra to the northern most Andamans represent a significant loss to the gene pool of physiologically resistant corals in this area with many thousands of colonies now well above the high-tide mark. A rapid assessment survey of the 700-km coastline of west Thailand (Department of Marine and Coastal Resources 2005) 4 days after the earthquake revealed very little damage to coral reefs as a result of tsunami waves. Of the 174 sites visited up to 105 were unaffected or showed very little damage, with 30 sites displaying low-level damage (11% of coral cover affected). A further 16 sites showed moderate damage (31–50% cover affected) while 23 sites were severely damaged (>50% coral cover affected). The type of damage fell into three categories: (1) overturned massive corals, (2) broken branching corals and (3) sedimentation effects. The northernmost coastline and its off-shore islands were more severely impacted than the south — apart from Phi Phi Island, with shallow reefs on wave-exposed islands and shorelines that are most vulnerable to wave-induced damage. Similar results were obtained in Aceh although at this location deeper-living massive Porites corals, with poor attachment to the substratum, were dislodged while many shallow-living colonies were unaffected (Baird et al. 2005). At damaged locations in Thailand it is predicted that recovery will be relatively rapid (5–10 yr) based on monitoring of reefs affected by storm surges in 1986 (Phongsuwan 1991, Satapoomin et al. 2006). Reports of human damage to reefs are restricted to the Thai coastline because the majority of research has been carried out here. They include the effects of tin-smelting operations (Brown & Holley 1982), tin dredging (Chansang et al. 1992), land reclamation and associated dredging (Brown et al. 1990, Clarke et al. 1993) and tourism-related activities. While all these perturbations may cause localised damage, from which coral reefs may recover once the environmental stressor is removed, global warming represents a much more serious threat to all reefs in the Andaman Sea. Already a significant increase in sea temperature has been noted in the Andaman Sea over the last 50 yr (Brown et al. 1996), leading to claims that by the late 1990s coral bleaching might be seen on an annual basis in the region (Hoegh Guldberg 1999). In fact, this has not been the case because the two most severe bleaching events were in 1991 and 1995 in Thai waters. While the effects of global warming cannot be underestimated there seems to be little evidence at present to support so gloomy a prognosis. Not only has there been no annual bleaching of corals but also there has been limited mortality on both off-shore and inshore reefs. Presently the coral reefs of the Andaman Sea are in very good condition with inshore corals displaying remarkable physical tolerances. These in-built tolerances will, however, be severely tested if sea temperatures continue to rise. Rather than being the first reefs to succumb to global warming inshore reefs in the region may be protected by both turbid waters and their broad array of environmental defences acquired over centuries. Offshore reefs in clearer waters are likely to be more susceptible to global warming, at least initially,

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because they live in a much more benign environment and have not acquired the same level of physiological defences as their inshore counterparts.

Conclusions The coral reefs of the Andaman Sea are not only extensive and largely undisturbed but also boast a relatively high diversity of corals — the levels of which are likely to be revised upward in the future because of the present limited surveillance. Such high diversity is probably a consequence of the complex geological history of the area which has led to habitat disturbance that promoted increased species diversity over time. Features highlighted in this review, such as the dynamic and complicated hydrography, the marked tidal ranges and regular sea-level anomalies, will also have resulted in corals and symbiotic algae developing remarkable environmental tolerances. It is now abundantly clear that corals thrive in turbid settings such as those in the Andaman Sea and nearby Java (Bak & Meesters 2000) where they appear to have acclimatised/adapted to living under high sediment loads. Indeed Potts & Jacobs (2000) suggested that success in turbid habitats allowed corals to radiate out to more ‘typical’ oceanic habitats. They further proposed that a variety of turbid inshore habitats have been continuously available through geological time providing ecological and evolutionary continuity as well as refugia for corals during non-optimal periods of reef growth. The Andaman Sea could well have been such a refuge in the past and indeed may act as such in the future if sea temperatures continue to rise.

Acknowledgements I acknowledge the support of staff at Phuket Marine Biological Center over the last 26 years. Thanks are given to the Natural Environment Research Council (NERC), United Kingdom, the Leverhulme Trust, United Kingdom, the Royal Society, United Kingdom, and the U.K. Department for International Development for research support. Thanks also to Peter Hunter at the National Oceanographic Centre, Southampton, for compilation of Figure 3 and to Dr. Patrick Hyder of the Meteorological Office for discussion of the oceanography of the Andaman Sea.

References Alcock, A. 1902. A Naturalist in Indian Seas. London: John Murray. Allan, R., Chambers, D., Drosdowsky, W., Hendon, H., Latif, M., Nicholls, N., Smith, I., Stone, R. & Tourre, Y. 2001. Is there an Indian Ocean dipole, and is it independent of the El Nino-Southern Oscillation? CLIVAR Exchanges 6, 18–21. Alpers, W., Wang Chen, H. & Hock, L. 1997. Observation of internal waves in the Andaman Sea by ERS SAR. International Geosciences and Remote Sensing Symposium, Singapore 4, 03–08. Anthony, K.R.N. 1999. Coral suspension feeding on fine particulate matter. Journal of Experimental Marine Biology and Ecology 232, 85–106. Baird, A.H., Campbell, S.J., Anggoro, A.W., Ardiwijaya, R.L., Fadii, N., Herdiana, Y., Kartawijaya, T., Mahyiddin, D., Mukminin, A., Pardede, S.T., Ptrachett, M.S., Rudi, E. & Siregar, A.M. 2005. Acehnese reefs in the wake of the Asian tsunami. Current Biology 15, 1926–1930. Bak, R.P.M. & Meesters, E.H. 2000. Acclimatization/adaptation in a marginal environment. Proceedings of the Ninth International Coral Reef Symposium, Bali, Indonesia 1, 265–271. Beauvais, L. 1983. Jurassic Cnidaria from the Philippines and Sumatra. Economic and social commission for Asia and the Pacific. Committee for Co-Ordination Joint Prospecting for Mineral Resources in Asian Offshore Areas (CCOP) Technical Bulletin 16, 39–67.

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CORAL REEFS OF THE ANDAMAN SEA — AN INTEGRATED PERSPECTIVE Bilham, R. 2005. A flying start, then a slow slip. Science 308, 1126–1127. Bilham, R., Engdhal, E.R., Feld, N. & Satyabalam, S.P. 2005. Partial and complete rupture of the IndoAndaman plate boundary 1847–2004. Seisomological Research Letters 76, 299–311. Brown, B.E., Downs, C.A., Dunne, R.P. & Gibb, S.W. 2002a. Preliminary evidence for tissue retraction as a factor in photoprotection of corals incapable of xanthophyll cycling. Journal of Experimental Marine Biology and Ecology 277, 129–144. Brown, B.E., Downs, C.A., Dunne, R.P. & Gibb, S.W. 2002b. Exploring the basis of thermotolerance in the reef coral Goniastrea aspera. Marine Ecology Progress Series 242, 119–129. Brown, B.E., Dunne, R.P., Ambarsari, I., Le Tissier, M.D.A. & Satapoomin, U. 1999. Seasonal fluctuations in environmental factors and their influence on photophysiological parameters in four Indo-Pacific coral species from the Andaman Sea, Indian Ocean. Marine Ecology Progress Series 191, 53–69. Brown, B.E., Dunne, R.P. & Chansang, H. 1996. Coral bleaching relative to elevated seawater temperature in the Andaman Sea (Indian Ocean) over the last 50 years. Coral Reefs 15, 151–152. Brown, B.E., Dunne, R.P., Scoffin, T.P. & Le Tissier, M.D.A. 1994. Solar damage in intertidal corals. Marine Ecology Progress Series 105, 219–230. Brown, B.E. & Holley, M.C. 1982. Metal levels associated with tin dredging and smelting and their effect upon intertidal reef flats at Ko Phuket, Thailand. Coral Reefs 1, 131–139. Brown, B.E., Le Tissier, M.D.A., Scoffin, T.P. & Tudhope, A.W. 1990. Evaluation of the environmental impact of dredging on intertidal coral reefs at Ko Phuket, Thailand, using ecological and physiological parameters. Marine Ecology Progress Series 65, 273–281. Brown, B.E. & Phongsuwan, N. 2004. Constancy and change on shallow reefs around Laem Pan Wa, Phuket, Thailand over a 20-year period. Phuket Marine Biological Center Research Bulletin 65, 61–73. Buddemeier, R.W. & Kinzie, R.A. 1976. Coral growth. Oceanography and Marine Biology: An Annual Review 14, 183–225. Burnett, W.J. 2002. Longitudinal variation in algal symbionts (zooxanthellae) from the Indian Ocean zoanthid Palythoa caesia. Marine Ecology Progress Series 234, 105–109. Chansang, H., Phongsuwan, N. & Boonyanate, P. 1992. Growth of corals under effect of sedimentation along the northwest coast of Phuket Island, Thailand. Proceedings of the Seventh International Coral Reef Symposium, Guam 1, 241–248. Chansang, H., Satapoomin, U. & Poovachiranon, S. (eds) 1999. Maps of Coral Reefs in Thai waters: Volume 2, Andaman Sea. Bangkok: Coral Reef Resource Management Project, Department of Fisheries. Clarke, K.R., Warwick, R.M. & Brown, B.E. 1993. An index showing breakdown of seriation, related to disturbance, in a coral-reef assemblage. Marine Ecology Progress Series 102, 153–160. Curray, J.R. 2005. Tectonics and history of the Andaman Sea region. Journal of Asian Earth Sciences 25, 187–232. Darwin, C. 1842. The Structure and Distribution of Coral Reefs. London: Smith, Elder and Co. Department of Marine and Coastal Resources, Thailand. 2005. Report on the Effects of the Indian Ocean Tsunami in Thai Waters [in Thai]. Bangkok: Department of Marine and Coastal Resources. Desai, B.N., Bhargava, R.M.S., Sarupia, J.S. & Pankajakshan, T. 1988. Oceanographic coverage of the Andaman and Nicobar Seas. Indian Association for Advancement of Science, Island Development Technology Options, 86–102. Downs, C.A., Mueller, E., Phillips, S., Fauth, J.E. & Woodley, C.M. 2000. A molecular biomarker system for assessing the health of a coral (Montastraea faveolata) during heat stress. Marine Biotechnology 2, 533–544. Drew, E.A. 1972. The biology and physiology of algal invertebrate symbiosis. II. The density of algal cells in a number of hermatypic hard corals and alcyonarians from various depths. Journal of Experimental Marine Biology and Ecology 9, 71–75. Dunne, R.P. & Brown, B.E. 2001. The influence of solar radiation on bleaching of shallow water reef corals in the Andaman Sea, 1993–1998. Coral Reefs 20, 201–210. Goodson, M.S. 2000. Symbiotic algae: molecular diversity in marginal coral reef habitat. Ph.D. thesis, University of York, U.K. Guzman-Speziale, M. & Ni, J.F. 1993 The opening of the Andaman Sea: where is the short term displacement being taken up? Geophysical Research Letters 20, 2949–2952.

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BARBARA E. BROWN Hall, R. 1998. The plate tectonics of Cenozoic SE Asia and the distribution of land and sea. In Biogeography and Evolution of SE Asia, R. Hall & J.D. Holloway (eds). Leiden, The Netherlands: Backhuys Publishers, 99–131. Haneburth, T., Stattegger, K. & Grootes, P.M. 2000. Rapid flooding of the Sunda Shelf: a late-glacial sealevel record. Science 288, 1033–1035. Hesp, P.A., Hung, C.C., Hilton, M., Loke Ming,C. & Turner, I.M. 1998. A first tentative Holocene sea level curve for Singapore. Journal of Coastal Research, 14, 308–314. Hoegh Guldberg, O. 1999 Climate change: coral bleaching and the future of the world’s coral reefs. Marine and Freshwater Research 50, 839–866. Hyder, P., Jeans, D.R.G., Cauquil, E.& Nerzic, R. 2005. Observations and predictability of internal solitons in the northern Andaman Sea. Applied Ocean Research, 27, 1–11. IPCC. 2001. Climate Change 2001 Synthesis report. R.T. Watson and Core Writing Team (eds). Geneva, Switzerland: Intergovernmental Panel on Climate Change. Janekarn, V. & Hylleberg, J. 1989. Coastal and offshore production along the west coast of Thailand (Andaman Sea) with notes on physical-chemical variables. Phuket Marine Biological Center Research Bulletin 51, 1–20. Johnstone, I. 1980. The ultrastructure of skeletogenesis in hermatypic corals. International Reviews of Cytology 67, 171–214. Khan, P.K. & Chakraborty, P.P. 2005. Two-phase opening of Andaman Sea: a new seismotectonic insight. Earth and Planetary Science Letters 229, 259–271. Khokiattiwong, S. 1991. Coastal hydrography of the southern Andaman Sea of Thailand, Trang to Satun province. In Proceedings of the First Workshop of the Tropical Marine Mollusc Programme (TMMP). Phuket: Phuket Marine Biological Center, 87–93. LaJeunesse, T.C. 2001. Investigating the biodiversity, ecology and phylogeny of endosymbiotic dinoflagellates in the genus Symbiodinium using the ITS region: in search of a ‘species’ level marker. Journal of Phycology 37, 866–880. LaJeunesse, T.C., Loh, W.K.W., van Woesik, R., Hoegh-Guldberg, O., Schmidt, G.W. & Fitt, W.K. 2003. Low symbiont diversity in southern Great Barrier Reef corals, relative to those of the Caribbean. Limnology and Oceanography 48, 2046–2054. Lough, J.M. & Barnes, D.J. 2000. Environmental controls on growth of the massive coral Porites. Journal of Experimental Marine Biology and Ecology 245, 225–243. Madhaven, B.B., Venkataraman, G., Shah, D. & Mohan, B.K. 1997. Revealing geology of the Great Nicobar Island, Indian Ocean, by interpretation of airborne synthetic aperture radar images. International Journal of Remote Sensing 18, 2723–2742. McManus, J.W. 1985. Marine speciation, tectonics and sea-level changes in Southeast Asia. Proceedings of the Fifth International Coral Reef Congress, Tahiti 4, 133–138. Myers, R.F. 1991. Micronesian Reef Fishes: A Practical Guide to the Identification of Inshore Fishes of the Tropical and Western Pacific. Guam: Coral Graphics, 2nd edition. Nielsen, T.G., Bjornsen, P.K., Boonruang, P., Fryd, M., Hansen, P.J., Janekarn, V., Limtrakulvong, V., Munk, P., Hansen, O.S., Satapoomin, S., Sawangarreruks, S., Thomsen, H.A. & Ostergaard, J.B. 2004. Hydrography, bacteria and protist communities across the continental shelf and shelf slope of the Andaman Sea (NE Indian Ocean). Marine Ecology Progress Series 274, 69–86. Oldham, R.D. 1884. Note on the earthquake of 31 December 1881. Records of the Geological Survey of India 17, 45–53. Osborne, A.R. 1990. The generation and propagation of internal solitons in the Andaman Sea. In Soliton Theory: A Survey of Results, A.P. Fordy (ed.). Manchester: Manchester University Press, 152–173. Osborne, A.R. & Burch, T.L. 1980. Internal solitons in the Andaman Sea. Science 208, 451–460. Pal, T., Chakraborty, P.P., Gupta, T.D. & Singh, C.D. 2003. Geodynamic evolution of the outer-arc-forearc belt in the Andaman Islands, the central part of the Burma-Java subduction complex. Geological Magazine 140, 289–307. Panutrakul, S. 1996. Water quality in Phuket Bay. Phuket Marine Biological Research Center Research Bulletin 61, 67–81.

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CORAL REEFS OF THE ANDAMAN SEA — AN INTEGRATED PERSPECTIVE Phongsuwan, N. 1991. Recolonization of a coral reef damaged by a storm on Phuket Island, Thailand. Phuket Marine Biological Center Research Bulletin 56, 75–83. Phongsuwan, N. Geographic Maps of Natural Resources in Southern Thailand [in Thai]. Bangkok: Department of Marine and Coastal Resources (in press). Phongsuwan, N. & Chansang, H. 1992. Assessment of coral communities in the Andaman Sea (Thailand). Proceedings of the Seventh International Coral Reef Symposium 1, 114–121. Pillai, C.S.G. 1972. Stony corals of the seas around India. Proceedings of a Symposium on Corals and Coral Reefs. Marine Biological Association of India, 191–216. Pillai, C.S.G. 1983. Coral reefs and their environs. In Mariculture Potential of Andaman and Nicobar Islands — An Indicative Survey. Central Marine Fisheries Research Institute Bulletin, Cochin, India, 34, 36–43. Potemra, J.T., Luther, M.E. & O’Brien, J.J. 1991. The seasonal circulation of the upper ocean in the Bay of Bengal. Journal of Geophysical Research 96, 12,667–12,683. Potts, D.C. 1983. Evolutionary disequilibrium among Indo-Pacific corals. Bulletin of Marine Science 33, 619–632. Potts, D.C. & Jacobs, J.R. 2000. Evolution of reef-building scleractinian corals in turbid environments: a paleo-ecological hypothesis. Proceedings of the Ninth International Coral Reef Symposium, Bali 1, 249–254. Pubellier, M., Ego, F., Chamot-Rooke, N. & Rangin, C. 2003. The building of pericratonic mountain ranges: structural and kinematic constraints applied to GIS-based reconstruction of SE Asia. Bulletin de la Societé Geologique de France 174, 561–584. Ramaswamy, V., Rao, P.S., Rao, K.H., Thwin, S., Rao, N.S. & Raiker, V. 2004. Tidal influence on suspended sediment distribution and dispersal in the northern Andaman Sea and Gulf of Martaban. Marine Geology 208, 33–42. Rao, T.S.S. & Griffiths, R.C. 1998. Understanding the Indian Ocean. Perspectives on Oceanography Series. Paris: UNESCO Publishing. Reddiah, K. 1977. The coral reefs of the Andaman and Nicobar Islands. Records of the Zoological Survey of India 72, 315–324. Rodolfo, K.S. 1969. Bathymetry and marine geology of the Andaman Basin and tectonic implications for Southeast Asia. Geological Society of America Bulletin 80, 1203–1230. Rosen, B.R. 1975. The distribution of reef corals. Report of the Underwater Association 1, 1–16. Rowan, R. 2004. Thermal adaptation in reef coral symbionts. Nature 430, 742. Satapoomin, U. 1993. Responses of corals and coral reef to the 1991 coral reef bleaching event in the Andaman Sea, Thailand. M.Sc. thesis, Chulalongkorn University, Thailand. Satapoomin, U. 2002. Comparative Study of Reef Fish Fauna in Thai Waters: The Gulf of Thailand versus the Andaman Sea. Technical Paper Phuket Marine Biological Center. Satapoomin, U., Phongsuwan, N. & Brown, B.E. 2006. A preliminary synopsis of the effects of the Indian Ocean tsunami on the coral reefs of western Thailand. Phuket Marine Biological Center Research Bulletin 67, 77–80. Scheer, G. 1971. Coral reefs and coral genera in the Red Sea and Indian Ocean. Symposium of the Zoological Society of London 28, 329–367. Scoffin, T.P. & Le Tissier, M.D.A. 1998. Late Holocene sea level and reef-flat progradation, Phuket, South Thailand. Coral Reefs 17, 273–276. Scoffin, T.P., Tudhope, A.W., Brown, B.E., Chansang, H. & Cheeney, R.F. (1992) Patterns and possible environmental controls of skeletogenesis of Porites lutea, South Thailand. Coral Reefs 11, 1–11. Searle, M. 2006. Co-seismic uplift of coral reefs along the western Andaman Islands during the December 26, 2004 earthquake. Coral Reefs, 25, 2. Sewell, R.B.S. 1925. The geography of the Andaman Sea basin. Memoirs of the Asiatic Society of Bengal 9, 1–26. Sewell, R.B.S. 1935. Studies on coral and coral formations in Indian waters. Memoirs of the Asiatic Society of Bengal 9, 461–540. Sieh, K. 2005. What happened and what’s next? Nature 434, 573–574. Soegiarto, A. 1985. Oceanographic assessment of the East Asian Seas. Environment and Resources in the Pacific, UNEP Regional Seas Reports and Studies 69, 173–184.

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BARBARA E. BROWN Soegiarto, A. & Birowo, A.T. 1975. Oceanologic Atlas of the Indonesian and Adjacent Waters. Volume 1. Jakarta, Indonesia: National Institute of Oceanology. Spalding, M.D., Ravilious, C. & Green, E.P. 2001. World Atlas of Coral Reefs. Berkeley: University of California Press. Spencer, T. Coral reefs and the tsunami of 26 December 2004: generating processes and ocean-wide patterns of impact. Atoll Research Bulletin (in press). Stambler, N., Popper, N., Dubinsky, Z. & Stimson, J. 1991. Effects of nutrient enrichment and water motion on the coral Pocillopora damicornis. Pacific Science 45, 299–307. Stanley, G.D. 1988. The history of early Mesozoic reef communities: a three step process. Palaios 3, 170–183. Suharsono & Soekarno. 1983. Kandungan zooxanthella pada karang batu di terumbu karang Pulau Pari. Oseanologi Indonesia 16, 1–7. Tija, H.D. 1980. The Sunda Shelf, Southeast Asia. Zeitchrift fur Geomorphologie 24, 405–427. Tomczak, M. & Godfrey, J.S. 1994. Regional Oceanography: An Introduction. Oxford, U.K.: Pergamon. Tudhope, A.W. & Scoffin, T.P. 1994. Growth and structure of fringing reefs in a muddy environment, South Thailand. Journal of Sedimentary Research A64, 752–764. Turak, E., Veron, C. & Sanpanich, K. 2005. Coral reef status after 26 December 2004 tsunami. In Final Technical Report Rapid Assessment Survey of Tsunami-Affected Reefs of Thailand, R.A. Allen & G.S. Stone (eds). Boston: New England Aquarium, 16–30. Turner, J.R., Vousden, D., Klaus, R., Satyanarayan, C., Fenner, D., Venkataraman, K., Rajan, P.T. & Subba Rao, N.V. 2001. Report of Phase 1: Remote Sensing and Rapid Site Assessment Survey April 2001. Coral Reef Systems of the Andaman Islands, Government of India and United Nations Development Programme, Global Environment Facility, New Delhi, India. UNEP/IUCN. 1988. Coral Reefs of the World Volume 2: Indian Ocean, Red Sea and Gulf. UNEP Regional Seas Directories and Bibliographies. Gland, Switzerland: IUCN and Nairobi, Kenya: UNEP. Varkey, M.J. 1986. Salt balance and mixing in the Bay of Bengal. Ph.D. thesis, University of Kerala, India. Varkey, M.J., Murty, V.S.N. & Suryanarayana, A. 1996. Physical oceanography of the Bay of Bengal and Andaman Sea. Oceanography and Marine Biology: An Annual Review 34, 1–70. Wallace, C.C. 1999. Staghorn Corals of the World: A Revision of the Coral Genus Acropora. Collingwood, Australia: CSIRO Publishing. Wallace, C.C. & Muir, P.R. 2005. Biodiversity of the Indian Ocean from the perspective of staghorn corals (Acropora spp.). Indian Journal of Marine Science 31, 42–49. Webster, P.J, Moore, A.M., Loschnigg, J.P. & Lebel, R.R. 1999. Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997–1998. Nature 401, 356–360. Wilkinson, C. 2004. Status of Coral Reefs of the World 2004. Townsville: Australian Institute of Marine Science. Wilson, M.E.J. & Rosen, B.R. 1998. Implications of paucity of corals in the Paeogene of SE Asia: plate tectonics or centre of origin? In Biogeography and Geological Evolution of SE Asia, R. Hall & J.D. Holloway (eds). Leiden, The Netherlands: Backhuys Publishers, 165–195. Wyrtki, K. 1973. An equatorial jet in the Indian Ocean. Science 181, 262–264. Yesaki, M. & Jantarapagdee, P. 1981. Wind stress and sea temperature changes off the west coast of Thailand. In Special Publication on the Occasion of the 10th Anniversary of Phuket Marine Biological Centre. Phuket, Thailand: Phuket Marine Biological Center, 27–42.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 195-344 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE OCEANOGRAPHIC PROCESSES, ECOLOGICAL INTERACTIONS AND SOCIOECONOMIC FEEDBACK MARTIN THIEL1,2, ERASMO C. MACAYA1, ENZO ACUÑA1, WOLF E. ARNTZ3, HORACIO BASTIAS1, KATHERINA BROKORDT1,2, PATRICIO A. CAMUS4,5, JUAN CARLOS CASTILLA5,6, LEONARDO R. CASTRO7, MARITZA CORTÉS1, CLEMENT P. DUMONT1,2, RUBEN ESCRIBANO8, MIRIAM FERNANDEZ5,9, JHON A. GAJARDO1, CARLOS F. GAYMER1,2, IVAN GOMEZ10, ANDRÉS E. GONZÁLEZ1, HUMBERTO E. GONZÁLEZ10, PILAR A. HAYE1,2, JUAN-ENRIQUE ILLANES1, JOSE LUIS IRIARTE11, DOMINGO A. LANCELLOTTI1, GUILLERMO LUNA-JORQUERA1,2, CAROLINA LUXORO1, PATRICIO H. MANRIQUEZ10, VÍCTOR MARÍN12, PRAXEDES MUÑOZ1, SERGIO A. NAVARRETE5,9, EDUARDO PEREZ1,2, ELIE POULIN12, JAVIER SELLANES1,8, HECTOR HITO SEPÚLVEDA13, WOLFGANG STOTZ1, FADIA TALA1, ANDREW THOMAS14, CRISTIAN A. VARGAS15, JULIO A. VASQUEZ1,2 & J.M. ALONSO VEGA1,2 1

Facultad de Ciencias del Mar, Universidad Católica del Norte, Larrondo 1281, Coquimbo, Chile E-mail: [email protected] 2Centro de Estudios Avanzados en Zonas Áridas (CEAZA), Coquimbo, Chile 3Alfred Wegener Institute for Polar and Marine Research, Columbusstrasse, 27568 Bremerhaven, Germany 4Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Casilla 297, Concepción, Chile 5Center for Advanced Studies in Ecology and Biodiversity (CASEB), Santiago, Chile 6Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Casilla 114-D, Santiago, Chile 7Laboratorio de Oceanografía Pesquera y Ecología Larval (LOPEL), Departamento de Oceanografía, Universidad de Concepción, Concepción, Chile 8Center for Oceanographic Research in the Eastern South Pacific (COPAS), Departamento de Oceanografía, Facultad de Recursos Naturales y Oceanografía, Universidad de Concepción, Estación de Biología Marina, PO Box 42, Dichato, Chile 9Coastal Marine Research Station, Departamento de Ecología, Pontificia Universidad Católica de Chile, Casilla 114D, Santiago, Chile 10Instituto de Biología Marina, Universidad Austral de Chile, PO Box 567, Campus Isla Teja, Valdivia, Chile 11Instituto de Acuicultura, Universidad Austral de Chile, PO Box 1327, Puerto Montt, Chile 12Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Casilla 653, Nuñoa, Santiago, Chile 13Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Casilla 160-C, Concepción, Chile 14School of Marine Sciences, University of Maine, Orono, Maine 04469-5741, U.S. 15Unidad de Sistemas Acuáticos, Centro de Ciencias Ambientales EULA, Universidad de Concepción, Concepción, Chile 195

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Abstract The Humboldt Current System (HCS) is one of the most productive marine ecosystems on earth. It extends along the west coast of South America from southern Chile (~42°S) up to Ecuador and the Galapagos Islands near the equator. The general oceanography of the HCS is characterised by a predominant northward flow of surface waters of subantarctic origin and by strong upwelling of cool nutrient-rich subsurface waters of equatorial origin. Along the coast of northern and central Chile, upwelling is localised and its occurrence changes from being mostly continuous (aseasonal) in northern Chile to a more seasonal pattern in southern-central Chile. Several important upwelling centres along the Chilean coast are interspersed with long stretches of coast without or with sporadic and less intense upwelling. Large-scale climatic phenomena (El Niño Southern Oscillation, ENSO) are superimposed onto this regional pattern, which results in a high spatiotemporal heterogeneity, complicating the prediction of ecological processes along the Chilean coast. This limited predictability becomes particularly critical in light of increasing human activities during the past decades, at present mainly in the form of exploitation of renewable resources (fish, invertebrates and macroalgae). This review examines current knowledge of ecological processes in the HCS of northern and central Chile, with a particular focus on oceanographic factors and the influence of human activities, and further suggests conservation strategies for this high-priority large marine ecosystem. Along the Chilean coast, the injection of nutrients into surface waters through upwelling events results in extremely high primary production. This fuels zooplankton and fish production over extensive areas, which also supports higher trophic levels, including large populations of seabirds and marine mammals. Pelagic fisheries, typically concentrated near main upwelling centres (20–22°S, 32–34°S, 36–38°S), take an important share of the fish production, thereby affecting trophic interactions in the HCS. Interestingly, El Niño (EN) events in northern Chile do not appear to cause a dramatic decline in primary or zooplankton production but rather a shift in species composition, which affects trophic efficiency of and interactions among higher-level consumers. The low oxygen concentrations in subsurface waters of the HCS (oxygenminimum zone, OMZ) influence predator-prey interactions in the plankton by preventing some species from migrating to deeper waters. The OMZ also has a strong effect on the bathymetric distribution of sublittoral soft-bottom communities along the Chilean coast. The few long-term studies available from sublittoral soft-bottom communities in northern and central Chile suggest that temporal dynamics in abundance and community composition are driven by interannual phenomena (EN and the extent and intensity of the OMZ) rather than by intra-annual (seasonal) patterns. Macrobenthic communities within the OMZ are often dominated in biomass by sulphide-oxidising, mat-forming bacteria. Though the contribution of these microbial communities to the total primary production of the system and their function in structuring OMZ communities is still scarcely known, they presumably play a key role, also in sustaining large populations of economically valuable crustaceans. Sublittoral hard bottoms in shallow waters are dominated by macroalgae and suspension-feeder reefs, which concentrate planktonic resources (nutrients and suspended matter) and channel them into benthic food webs. These communities persist for many years and local extinctions appear to be mainly driven by large-scale events such as EN, which causes direct mortality of benthic organisms due to lack of nutrients/food, high water temperatures, or burial under terrigenous sediments from river runoff. Historic extinctions in combination with local conditions (e.g., vicinity to upwelling centres or substratum availability) produce a heterogeneous distribution pattern of benthic communities, which is also reflected in the diffuse biogeographic limits along the coast of northern-central Chile. Studies of population connectivity suggest that species with highly mobile planktonic dispersal stages maintain relatively continuous populations throughout most of the HCS, while populations of species with limited planktonic dispersal appear to feature high genetic structure over small spatial scales. The population dynamics of most species in the HCS are further influenced by geographic variation in propagule production (apparently caused by local differences in primary production), by temporal variation in recruit supply (caused by upwelling 196

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events, frontal systems and eddies), and topographically driven propagule retention (behind headlands, in bay systems and upwelling shadows). Adults as well as larval stages show a wide range of different physiological, ecological and reproductive adaptations. This diversity in life-history strategies in combination with the high variability in environmental conditions (currents, food availability, predation risk, environmental stress) causes strong fluctuations in stocks of both planktonic and benthic resources. At present, it remains difficult to predict many of these fluctuations, which poses particular challenges for the management of exploited resources and the conservation of biodiversity in the HCS. The high spatiotemporal variability in factors affecting ecological processes and the often-unpredictable outcome call for fine-scale monitoring of recruitment and stock dynamics. In order to translate this ecological information into sustainable use of resources, adaptive and co-participative management plans are recommended. Identification of areas with high biodiversity, source and sink regions for propagules and connectivity among local populations together with developing a systematic conservation planning, which incorporates decision support systems, are important tasks that need to be resolved in order to create an efficient network of Marine Protected Areas along the coast of northern-central Chile. Farther offshore, the continental shelf and the deep-sea trenches off the Chilean coast play an important role in biogeochemical cycles, which may be highly sensitive to climatic change. Research in this area should be intensified, for which modern research vessels are required. Biodiversity inventories must be accompanied by efforts to foster taxonomic expertise and museum collections (which should integrate morphological and molecular information). Conservation goals set for the next decade can only be achieved with the incorporation of local stakeholders and the establishment of efficient administrative structures. The dynamic system of the HCS in northern-central Chile can only be understood and managed efficiently if a fluent communication between stakeholders, administrators, scientists and politicians is guaranteed.

Introduction The deep-blue colour of the water observed for a long time past gave place to a green colour, and on the whole there was a great change in the general character of the surface fauna, pointing to the nearness of a great continent, similar to what was observed off Japan and elsewhere. On November 18 [1875], the water was very green in colour, and the ship occasionally passed through large red or brown patches, which the tow-net showed to be due to immense numbers of red copepods, hyperids, and other Crustacea. Murray (1895), on approaching Valparaíso aboard H.M.S. Challenger

Such a vivid language was rarely used by John Murray to refer to the abundance of planktonic organisms in surface waters. Only for the surface plankton from the Agulhas Bank off South Africa did he employ similar colourful language, referring to “myriads of Zoeae and a few larger Megalopae”. Scientists studying the plankton ecology of the Eastern Boundary Currents (EBCs) are used to the sight of these dense accumulations of zooplankton, which are often found in sharply defined patches. It is the intense upwelling of nutrient-rich waters in the EBCs that fuels the extraordinary high primary production (PP) in the EBCs, which forms the basis of the food web supporting some of the largest fisheries of the world. However, the frequency and intensity of upwelling within the EBCs varies, mainly depending on large-scale climatic forcing, latitudinal/seasonal signals and local factors, such as the width of the shelf, coastal topography, and sources of upwelled waters (Thomas et al. 2004). Although the overall importance of upwelling in these large marine ecosystems is relatively well known, the effects of temporal and spatial variability of upwelling on the ecology and productivity of the planktonic and benthic communities remain poorly understood. Herein these effects are explored, using the Humboldt Current System (HCS), one of the most 197

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productive EBCs (Halpin et al. 2004, Montecino et al. 2005), as a model system. In the present paper knowledge on the HCS in northern-central Chile is reviewed because this area is characterised by a complex set of temporally changing and geographically variable conditions that represent a particular challenge to science and management (see also Artisanal benthic fisheries and following sections, p. 278ff). The aims of this review are 4-fold: to (1) review current knowledge, (2) reveal gaps in information, (3) indicate conservation priorities, and (4) propose future research avenues. The HCS, by some authors named the Peru-Chile Current System, extends from ~42°S up to about the equator (Montecino et al. 2005). The main oceanographic features of this system are often described as cold nutrient-rich waters being transported northward and nutrient-enriched subsurface waters upwelled along the shorelines of Ecuador, Peru and northern Chile. Occasionally the nutrient-supply engine of the HCS is interrupted by influx of warm and nutrient-depleted equatorial waters; during such events (El Niño, EN) the northward flow of cool nutrient-rich waters is suppressed and upwelling intensity is often reduced (W. Palma et al. 2006). Individual cycles of this El Niño Southern Oscillation (ENSO) last for several years, but predictability of EN events is still very limited. On shorter temporal scales, there is a seasonal (predictable) pattern of climate and oceanography at high latitudes, which becomes aseasonal (and less predictable) at mid- and low latitudes (Blanco et al. 2001, Carr et al. 2002). It can be argued that the predictability of oceanographic conditions is lowest in the mid-region of the HCS (from 18°S to about 32°S; see also Thomas et al. 2001a) because here the seasonal variations are occasionally overshadowed by the interannual ENSO cycles, whereas at low latitudes (<18°S) the conditions may remain relatively stable for several years in a row, only being disturbed, but then severely, by EN events. To add to this variability, the HCS between 18°S and ~40°S features a complex coastal oceanography, where the main equatorward current is enveloped by a set of counter- and undercurrents, the width, location and intensity of which also vary in time. Herein we focus on this area between 18°S and ~40°S because the interaction between seasonal and interannual (ENSO) signals results in high temporal variability, which affects the ecological processes in this region. Overall, the coastline of northern and central Chile (18° to ~40°S) is relatively straight (Figure 1), but in the nearshore region small-scale geographic features produce a high spatial heterogeneity, which also influences oceanographic conditions in this area. Several bay systems are found along the coast of northern-central Chile. Circulation in these bays is complex with counterrotating gyres (Valle-Levinson et al. 2000) affecting larval transport and settlement patterns (A.T. Palma et al. 2006), most likely related to depth- and site-dependent retention or export scenarios (Yannicelli et al. 2006a). Headlands favour the generation of powerful coastal flow structures (squirts) transporting surface waters up to 100 km offshore (Marín et al. 2003a). In contrast, long stretches of exposed outer coast without headlands or bays, as found for example in northern Chile between 20° and 22°S, favour alongshore currents leading to relatively homogeneous conditions and downstream transport (W. Palma et al. 2006). Numerous studies have examined the effects of oceanographic conditions on a variety of ecological processes in the HCS (e.g., Carrasco & Santander 1987, Tarazona et al. 1988a,b, Alheit & Niquen 2004, Arntz et al. 2006). Upwelling or ENSO-related conditions affect PP (Wieters et al. 2003, Iriarte & González 2004), zooplankton community composition (Escribano et al. 2004a), fish population dynamics (Halpin et al. 2004), dispersal of larvae (Poulin et al. 2002a,b), growth of benthic algae (Wieters 2005), benthic-pelagic coupling (Graco et al. 2006), population dynamics of benthos organisms (Castilla & Camus 1992), and a variety of other processes. Most of these studies have focused on direct cause-effect relationships between oceanographic factors and ecological responses. Recent studies in central Chile indicate complex interactions between upwelling, supply of recruits, and grazers or predators (Nielsen & Navarrete 2004, Wieters 2005). These studies show the importance of bottom-up and top-down processes, which may vary on small temporal and spatial scales, making predictions difficult. In this context, Navarrete et al. (2002) emphasised 198

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Fishery unit

CHILE

18° Iquique/Rio Loa

Iquique

Mejillones Antofagasta

Antofagasta

25°

X - XII

Southern

45°

RREN T SYSTEM

Chiloé

T

CU

Valdivia

40°

D

L

V - IX

BO

35°

M

30°

Isla Choros Coquimbo Coquimbo (Lengua de Vaca) Punta Curaumilla Valparaíso central Chile Concepcin Concepción Golfo Arauco

HU

Caldera

III - IV

Northern

I - II

Central

20°

Arica

50°

55°

Figure 1 Study region in northern Chile with the main upwelling regions and localities mentioned throughout the text. Principal upwelling centers in black dots, other sites with frequent upwelling indicated with grey dots, coastal stretches with occasional upwelling shown as thick black line.

that “lack of consistent trends among sites … shows that El Niño effects on interannual recruitment variation are not predictable”. Not only marine biologists but above all the organisms inhabiting the HCS are grappling with this limited predictability. How do these organisms deal with the difficulty of foreseeing the availability of dispersal windows, food, competitors or predators in the near future? Many of the following sections will explicitly or implicitly address this question. The main focus, though, will be on the outcomes of ecological processes in the HCS, the processes that govern them and their relevance in a socioeconomic and conservation context. Variable distribution patterns and species interactions in the HCS are not only due to oceanographic processes but are also increasingly affected by human activities that reduce the abundance of some species while favouring others. When humans first started to use the natural resources of the HCS, they opportunistically reacted to the system and exploited natural resources where these were available and accessible. When a particular resource became scarce or inaccessible they either searched for the resource in other places or shifted to alternative resources (e.g., Llagostera 1979, Méndez & Jackson 2004). With increasing population pressure and technological advances, human pressure on the HCS has intensified. Wave-sheltered bays along the coast with dense human populations are impacted by intense shipping traffic, artificial coastline constructions and wastewater influx (Fernández et al. 2000). Mining and agriculture activities have resulted in severe contamination of some coastal areas, fishing pressure has intensified and extended into previously inaccessible regions and zones and finally climate change (increased ultraviolet (UV) radiation, global warming) has also reached the HCS. From being opportunistic users who responded to natural variations in resource abundance, humans have now become important actors who directly affect many of the 199

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natural processes in the HCS. Recognition of this impact has called increasingly for planning and regulation of human activities. The limited predictability of oceanographic conditions and the ecological processes in the HCS, however, represents an enormous challenge for efficient management of this large marine ecosystem. Herein we strive to describe those aspects of the system that are comparatively predictable and to identify those that will require additional knowledge before they can be reliably predicted. In order to achieve this goal, this review provides (1) a brief overview of historic research activities, (2) a description of the main oceanographic conditions in the HCS of northern and central Chile, (3) an analysis of the pelagic environment and top consumers, (4) an introduction to benthic systems and nearshore biogeography, (5) a discussion of biological adaptations of organisms, (6) a portrayal of socioeconomic aspects related to the exploitation of natural resources, and finally (7) a scenario for marine conservation and an outlook identifying some of the main administrative and scientific tasks for the future.

A brief history of research on the Humboldt current system First reports on a cool current in the southeastern Pacific First written accounts of a cold current along the western coast of South America come from the European explorers. According to Gunther (1936), the history of the Humboldt Current began in 1515 when Vasco Nuñez de Balboa first sighted the South Sea. The knowledge of this oceanic current dates to the sixteenth century when several Europeans carried out observations suggesting that waters were cool: Pascual de Andagoya in 1522 was the first Spaniard to explore to the south of the Panamanian coast, Agustin de Zarate published in 1555 his Historia del descubrimiento y Conquista de la Provincia del Peru, and the Jesuit José de Acosta described in his Historia Natural y Moral de Indias (1591) the temperature conditions and their influence on the climate (Santibáñez 1944). Other travellers carried out additional observations (for details see Gunther 1936), but it was the German naturalist Alexander von Humboldt who took the first temperature measurements (Gunther 1936, Santibáñez 1944). Humboldt (1846), in his book Cosmos, wrote on page 301: “in the Southern Pacific Ocean, … a current the effect of whose low temperature on the climate of the adjacent coast was first brought into notice by myself in the autumn of 1802. This current brings the cold water of high southern latitudes to the coast of Chile, and follows its shores and those of Peru northward”. Additionally, Humboldt also was the first to describe EN temperature anomalies in coastal waters (Kortum 2002).

From natural history to ecology to marine conservation The first Chilean naturalist was Abate Juan Ignacio Molina. He published the following works in Italy: Compendio della storia geografica, naturale, e civili del regno del Chile (1776) and Saggio sulla storia naturale del Chili (1782), which include detailed descriptions of the mineral wealth and native flora and fauna based on the Linnaean system of classification (Ronan 2002). Claudio Gay, a French naturalist who arrived in Chile in 1828, as a result of 12 yr of exploring Chile under government contract, wrote his Historia fisica y política de Chile. In 29 volumes Gay described the history, botany and zoology of the country, including detailed descriptions of the marine fauna (e.g., 79 species of decapod crustaceans) (Jara 1997). Rodulfo Amando Philippi, who emigrated from Germany to Chile in 1851, was a physician by profession but a naturalist by inclination, and he is considered one of the most recognised and influential scientists in the development of natural sciences in Chile (Castro et al. 2006). He contributed numerous taxonomic descriptions to the knowledge of biological diversity of Chile. In a recent article, Castro et al. (2006) conclude that in comparison with other taxonomists, Philippi was the author of the largest number of presently 200

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valid species in the Chilean biota. Other scientists who contributed enormously to the knowledge of the fauna and flora from the HCS of northern-central Chile included Alcide D’Orbigny, Eduard Friedrich Poeppig and Carlos Emilio Porter Mosso. Most expeditions during the eighteenth and nineteenth centuries produced observations and collections that were gathered by individual scientists or ‘naturalists’ aboard global voyages of exploration and discovery. These voyages often had political, military and economic purposes, with science being a secondary or even incidental activity (Fiedler & Lavín 2006). After Humboldt’s travels, several pioneer expeditions were carried out in the southern Pacific, but most of them rounded Cape Horn on their way into the Pacific, stopped in Concepción or more commonly in Valparaíso, and then turned off to Juan Fernández and from there progressed further into the southwest Pacific. The coasts of northern Chile were rarely visited by these expeditions. Also the U.S. Exploring Expedition (1838–1842), the main objective of which was to facilitate American commerce (Johnson 1995), left the coast of northern Chile untouched on its way from Valparaíso to Callao. Other expeditions took the same route on their return trips. For example, the Novara Expedition passed through Valparaíso in April 1859, coming from Tahiti. The corvette H.M.S. Challenger reached Valparaíso in November 1875 coming from Juan Fernández and then continued to the south. Later expeditions, such as the Fisheries Commission Steamer Albatross, with Alexander Agassiz on board, explored the northern parts of the HCS, but rarely reached farther south than Callao, Peru. A notable exception to this general pattern was the H.M.S. Beagle (1831–1836), with Charles Darwin aboard, which after leaving Valparaíso made stopovers in Coquimbo (30°S), Caldera (27°S) and Iquique (20°S) before continuing directly to Callao (Peru) (Darwin 1851, 1854). Expeditions conducted during the first half of the twentieth century were mainly dedicated to the study of the local biodiversity. One of the most important expeditions during that time, the Lund University Chile Expedition in 1948–1949, explored the Chilean coast between Iquique and the Magellan Straits, but of the 277 stations visited, only 79 were located in northern and central Chile (Brattström & Dahl 1951). Only during the last half of the twentieth century have concentrated research efforts been directed toward the oceanography and ecology of the HCS in northern Chile (e.g., Gallardo 1963 and many others). While those initial studies have provided important information on the description of species distribution and abundance in the HCS along the coast of Chile, research during the last quarter of the twentieth century became much more process oriented (Castilla & Largier 2002, Escribano et al. 2004a,b, Montecino et al. 2005 and citations therein). In particular during the past decade, marine conservation has become an important topic in the marine sciences literature of Chile (see, e.g., Castilla 1996, 2000, Fernández et al. 2000, Fernández & Castilla 2000, 2005, Moreno 2001). Thus, as in other regions of the HCS (e.g., Pauly et al. 1989), research in the HCS along the Chilean coast has shifted from a description of taxonomy and patterns to the examination of processes, which has also resulted in an increasing trend of interdisciplinary studies, in particular between ecologists and oceanographers.

Oceanographic conditions in the southeastern Pacific The HCS is the equatorward-flowing, eastern portion of the basin-scale southeast Pacific anticyclonic gyre, bounded to the north by the equatorial current system and to the south by the West Wind Drift (WWD). The HCS is one of the four major global EBCs, characterised by dominant equatorward alongshore wind stress, offshore Ekman transport, coastal upwelling of cold, nutrientrich subsurface water and highly productive fisheries (Hill et al. 1998). The narrow continental shelf and meridionally oriented coastline of South America allow efficient transmittal of atmospheric and oceanographic signals imposed from both lower latitudes through the equatorial current system and from higher latitudes where increasing seasonality in both wind forcing and oceanic response 201

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is seen with increasing latitude. The coast can be divided into general zones based on physical characteristics. The shelf (200 m) off Peru is up to 100 km wide. Along the Chilean coast, four zones (Figueroa 2002) include the northern region (north of ~32°S) with little freshwater influence and an extremely narrow shelf (<10 km), a widening shelf from 32°S to 36°S, a wider shelf (~70 km) from 36°S to 42°S with increased freshwater influence, especially in winter, and a high-latitude region (>42°S) with a wider topographically complex, fjord-indented coastline and with strong freshwater influence. Wind forcing in the southeast Pacific is dominated by the influence of the southeast Pacific subtropical anticyclone that creates equatorward, upwelling-favourable winds along most of the South American Pacific coast with latitudinally varying seasonality. Between 5°S and ~35°S, monthly mean winds remain upwelling favourable throughout the year and are weakest along the northern Chilean coast ~17–23°S (Shaffer et al. 1999, Thomas et al. 2001a). Distinct phase differences in the annual maxima are evident as a function of latitude (Thomas et al. 2001a), where maximum upwelling strength shifts from austral autumn–winter off Peru (Bakun & Nelson 1991, Carr et al. 2002), to austral spring–summer off northern Chile (Blanco et al. 2001) and austral summer south of ~30°S (Shaffer et al. 1999). Upwelling is augmented by a decrease in alongshore wind stress near shore that creates a region of cyclonic (negative) wind stress curl in the coastal zone, lifting isotherms. Two regions of maximum alongshore wind stress are evident, centred at ~15°S and ~30°S (Shaffer et al. 1999, Thomas et al. 2001a, Hormazábal et al. 2004). North of 30°S, strong land–sea thermal contrast in austral summer enhances upwelling-favourable alongshore wind stress (Rutllant et al. 2004a). At the very lowest latitudes (north of ~5°S), the annual meridional migration of the Inter-Tropical Convergence Zone (ITCZ) creates both wind and precipitation (and therefore stratification) seasonality. Beginning at ~35°S and extending poleward, seasonality in the strength of the subtropical anticyclone creates seasonal reversals between an austral summer upwelling maximum and mean winter conditions of poleward, downwelling-favourable winds driven by winter storms associated with the polar front (Shaffer et al. 1999, Rutllant et al. 2004a). The strength and duration of these winter conditions increases with latitude. South of ~45°S, events associated with polar front activity create poleward alongshore monthly mean winds, downwelling conditions and strong precipitation in coastal regions throughout the year. The large-scale equatorward surface flow of the HCS within the basin-scale gyre belies a complicated and still relatively poorly sampled flow structure closer to the coast. The following description is a general overview of commonly observed characteristics reviewed in more detail by Strub et al. (1998). The northern latitude at which the WWD approaches the continent shifts seasonally from 35°S to 40°S in austral winter to ~45°S in austral summer. Flow from the WWD branches north and south (Figure 2). The southern arm joins poleward coastal flow of the Cape Horn Current, a buoyancy-driven coastal current with input from local river runoff, which is strongest during austral winter. The northern arm forms the main flow of the Humboldt Current that proceeds equatorward along the basin margin and joins the westward-flowing South Equatorial Current at lowest latitudes, off northern Peru-Ecuador. This main flow of the Humboldt Current is located seaward (~75–85°W) of a system of narrower coastal flows. Closest to the coast and coupled to local wind forcing and coastal upwelling, the Chile Coastal Current (CCC) flows predominantly equatorward. In summer, equatorward flow is most latitudinally extensive, traceable to 35–40°S (Atkinson et al. 2002) and flowing along the entire central and northern Chilean coast, continuous with the equatorward flowing Peru Coastal Current (PCC), also forced by local winds, as far as ~5°S. In winter, the PCC strengthens in association with the winter maximum in alongshore wind stress. Off northern Chile (18–24°S) the seasonal maximum of the CCC is in the autumn (Blanco et al. 2001), while south of ~25°S the CCC becomes increasingly seasonally variable. South of ~35°S, in association with the seasonal reversal in alongshore wind stress, the CCC is predominantly

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−92° −88° −84° −80° −76° −72° W

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Figure 2 Overview of the surface currents in the eastern South Pacific that influence the north-central Chilean coast, showing the West Wind Drift (WWD), the main flow of the Humbolt Current (HC), the Cape Horn Current (CHC), the Chile Coastal Current (CCC), the Peru Coastal Current (PCC), the Peru-Chile Countercurrent (PCCC) and the South Equatorial Current (SEC).

poleward in winter. Between these seasonal coastal currents and the more continuous equatorward flow of the main Peru-Chile Current is the poleward-flowing Peru-Chile Countercurrent located ~100–300 km offshore, originating in equatorial regions likely as Equatorial Undercurrent water and continues to ~35°S. This flow is poorly resolved in drifter data (Chaigneau & Pizarro, 2005) but evident in altimeter data (Strub et al. 1995) and temperature-salinity characteristics (Strub et al. 1998). Beneath the coastal surface currents, a Poleward Undercurrent is continuous from northern Peru to latitudes as high as 45–50°S (Silva & Neshyba 1979). This undercurrent, located over the continental slope (Zuta & Guillén 1970, Shaffer et al. 1995, Leth et al. 2004), delivers relatively saline, nutrient-rich, low-oxygen water (equatorial subsurface water, ESSW) to coastal regions; it

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is a primary contributor to upwelling off Peru and northern Chile (Huyer et al. 1987) and in Chilean coastal regions at least as far as 35°S (Fonseca 1989). From 5°S to ~40°S, the primary coastal oceanographic characteristics are isotherms and isohalines of the upper ~100 m tilted upward toward the coast and associated with upwelling. Off Peru, the seasonally maximum winter winds and the small Coriolis term combine to create strong offshore Ekman transport with upwelling effects evident at least as far as 400 km offshore. Along the Chilean coast, four regions are recognised for especially strong upwelling, most likely due to topographic enhancement by headlands, at Antofagasta (23°S), Coquimbo (30°S), Valparaíso (33°S) and Concepción (37°S) (Figueroa & Moffat 2000, Mesías et al. 2003). Off southern-central Chile (36–40°S), coastal stratification imposed by freshwater runoff becomes important even during summer upwelling conditions (Atkinson et al. 2002). Strong interannual variability is superimposed on mean seasonal patterns by ENSO signals propagating poleward along the coast from their equatorial source. These impose elevated sea levels, a deeper thermocline, positive sea-surface temperature (SST) anomalies and either a decrease or episodic reversal of coastal equatorward flow in the PCC and CCC (Figure 2) during the EN (warm) phase. Decreased coastal sea levels, shallower thermoclines, colder SST conditions and strengthened coastal equatorward flow occur during the La Niña (LN; cold) phase. Satellite data show that EN anomalies can extend south of 40°S to include the entire coast of South America (Carr et al. 2002, Strub & James 2002), but anomalies decrease with increasing latitude (Strub & James 2002, Montecinos et al. 2003, Escribano et al. 2004a). EN conditions can also be imposed by local anomalous winds, likely modulated via atmospheric teleconnections (Shaffer et al. 1999). Oceanic ENSO signals originate as eastward-propagating equatorial Kelvin waves that propagate poleward as coastally trapped waves (CTWs). Alongshore wind stress and offshore Ekman transport persist, or even strengthen during EN periods (Carr et al. 2002, Escribano et al. 2004a), but upwell warm, nutrient-poor water from above the deepened thermocline. Mesoscale variability is evident as eddies and filaments that advect cold, high-pigment coastal water for hundreds of kilometres offshore, often originating at headlands (Thomas 1999, Sobarzo & Figueroa 2001, Mesías et al. 2003). Along the coast of central Chile, a transition zone of elevated eddy kinetic energy is observed (Hormazábal et al. 2004). A wide zone (800–1000 km) of relatively diffuse and low eddy kinetic energy is observed north of ~30°S where winds are weak but are persistently favourable to upwelling. Eddy kinetic energy is stronger and more closely associated with the coast (~600 km) in the region between ~30°S and 38°S where the winds, though stronger, are more variable (Hormazábal et al. 2004). Away from the coast (>300 km), altimeter and drifter data show two regions of maximum eddy kinetic energy, one along the Peru coast and another centred at ~30°S off Chile. This is consistent with patterns of surface temperature and satellitemeasured ocean colour that show cold waters with high pigment concentrations associated with the upwelling extending furthest offshore off Peru and off central Chile (Montecino et al. 2005), while being restricted to an extremely narrow coastal band off northern Chile (Morales et al. 1999, Thomas et al. 2001b). CTWs propagate poleward along the entire Peru and Chile coastlines, traceable to wind fluctuations in equatorial regions (Hormazábal et al. 2001). CTWs raise and lower the pycnocline/ nutricline, influencing the effectiveness of upwelling, with dominant frequencies of days to weeks off Peru (Enfield et al. 1987) and ~50-day periods off northern and central Chile (Shaffer et al. 1997, Hormazábal et al. 2001, Rutllant et al. 2004b). Ramos et al. (2006) show that variability of equatorial origin at both annual and semi-annual periods impose strong modulation on isotherm depth along the coast. CTWs appear especially energetic during EN periods and weaker during LN periods and austral winter (Shaffer et al. 1999). At the shorter time-/space scales, diurnal cycles in wind stress are important contributors to forcing along the arid northern Chilean coast, especially in summer (Rutllant et al. 1998), but become less important with increasing latitude, where

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storm-mediated variability on 3- to 7-day cycles increases (Strub et al. 1998), with a maximum in austral winter.

Coastal oceanography Coastal waters have been defined in many different ways depending upon the reason (e.g., scientific, geopolitical, international conventions, etc.) for their usage. Bowden (1983) defines them, from an oceanographic perspective, as “those on the continental shelf and the adjoining seas”. If such a definition would be used for the HCS, then the coastal strip would be rather narrow. Bottom depth in some areas of the HCS (i.e., Antofagasta) goes from less than 100 m at distances of 10 km from shore to more than 1000 m at 30 km. However, many characteristics of the plankton assemblages at those distances show that they are still largely influenced by the proximity of the coast. Thus, for the purposes of this analysis an alternative definition for coastal ocean is used: that part of the ocean where the proximity of the continents affects the circulation and ecological processes. This definition then includes coastal waters as defined by Bowden and the coastal transition zone defined by Hormazábal et al. (2004). The analysis of any oceanographic system is scale dependent (Haury et al. 1978, Rutllant & Montecino 2002). Thus, if space–time is considered as a continuum, then isolating parts of it is an observer decision, which may be influenced by its epistemological background (Ramírez 2005a) and the characteristics of the ecosystem to be studied (Marín 2000). Haury et al. (1978), in a classical article on scales of analysis in oceanography, propose two terms (mesoscale and gross scale) to refer to those scales where the effects of flow structures such as filaments, squirts, meanders and eddies (1–102 km) are dominant and where ecosystem patterns are advective (influenced by the physics of the system) and biological. Coastal upwelling is one of the main mesoscale oceanographic processes affecting the dynamics and the spatial and temporal structure of coastal ecosystems along the EBCs (Strub et al. 1998, Montecino et al. 2005). Upwelling flow structures such as filaments (Sobarzo & Figueroa 2001), squirts (Marín et al. 2003a, Marín & Delgado 2007) and shadows (Castilla et al. 2002a, Marín et al. 2003b) have been described for the Chilean coast. Herein, information about those structures is succinctly reviewed and the potential effects on the ecology of the coastal ocean in the HCS are discussed. The HCS, from the standpoint of coastal wind forcing, can be divided in two latitudinal areas near 26°S (Figueroa 2002). From 26°S to the north, meridional, upwelling-favourable winds are rather constant throughout the year; south of this latitude greater seasonality is observed. One important upwelling focus in the northern zone is the Mejillones Peninsula (23°S). Observational (Marín et al. 1993, Escribano et al. 2000, Marín et al. 2001, Olivares 2001, Sobarzo & Figueroa 2001, Escribano et al. 2002, Rojas et al. 2002, Marín et al. 2003b) and modelling studies (Escribano et al. 2004b) have shown that the dynamics of the coastal ecosystems in that area largely depend on the generation of upwelling filaments at Mejillones Peninsula. Indeed, the generation of filaments in the northern tip of the peninsula (Punta Angamos) has been identified as the main mechanism of nutrient enrichment in the surface layers (Marín & Olivares 1999). Furthermore, ‘upwelling shadows’ within Mejillones Bay, an equator-facing bay located in the northern end of the peninsula, have been dynamically linked to the generation of bifurcated filaments at Punta Angamos (Marín et al. 2003b). This shadow is an important physical structure within the bay, affecting PP (Marín et al. 2003b) and the retention of planktonic organisms (Olivares 2001). An alternative mechanism, described as an ‘upwelling trap’ by Castilla et al. (2002a) and also related to the coastal upwelling dynamics, generates higher temperatures inside Antofagasta Bay, a pole-facing bay at the southern end of the peninsula. In this case also the physically generated structure contributes to the retention of planktonic organisms. Thus, mesoscale flow features (upwelling shadows and upwelling traps),

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associated with cold-water filaments, seem to play an important role not only in relation to the biological productivity of coastal upwelling regions but also as mechanisms for the retention of coastal planktonic species. If account is taken of the fact that Mejillones Peninsula is located in the area where upwelling-favourable winds occur year-round, then those areas may constitute recurrent retention zones. Farther south, within the HCS area where upwelling is more seasonal, the Coquimbo Bay System (30°S) is another important coastal upwelling centre. This system is located within two coastal points (Punta Lengua de Vaca and Punta Pájaros) and is the site of intensive fisheries and eco-tourism (Ramírez 2005b). Filaments, including bifurcated upwelling filaments (Moraga et al. 2001), are known to generate at Punta Lengua de Vaca, contributing with cold, nutrient-high waters to the coastal system (Montecino & Quiroz 2000, Montecino et al. 2005). A recent Lagrangian study conducted within the bay (Marín & Delgado 2007) shows that the dominant equatorward flow is modulated at quasi-inertial frequencies, enhancing the coastal retention times. Furthermore, Marín et al. (2003a) have shown that cold-water squirts generate at the northern end of the bay system (near Punta Pájaros). Squirts seem to be geographically anchored to locations meeting the requirements for their generation (Strub et al. 1991). Thus, it is highly likely that indeed the squirts observed in the vicinity of Punta Pájaros are normally generated within the same area, making them a recurrent mesoscale flow feature. As a test of this idea a simple model was built using the ROMS model (Shchepetkin & McWilliams 2005) and initialised with the ROMSTOOLS package (Penven 2003). The study area was defined by longitudinal boundaries set at 74°W and 70°W and latitudinal boundaries at 32°S and 24°S (see also Figure 3). This model has been run for 2 yr in other eastern boundary systems such as the California Current System (Marchesiello et al. 2003) to obtain a statistical equilibrium condition. However, in the present test case a squirt was generated just after 17 days of integration, which closely resembles the squirt observed in an SST image obtained in January 2005 in shape, size and location (Figure 3). The interesting, and indeed serendipitous, observation resulting from this numerical exercise is that transient modes developed as perturbations (e.g., baroclinic instabilities) from climatological mean conditions generate coastal flow structures (squirts) which are recurrently found within the HCS. Satellite observations and Lagrangian drifter data (Marín & Delgado 2007) have in fact shown that this squirt is a recurrent feature in the area, reaching distances on the order of 140 km offshore. Squirt speeds, estimated both through feature-tracking analysis (Marín et al. 2003a) and Lagrangian drifters (Marín & Delgado 2007), range between 0.2 and 0.3 m s−1. Thus, considering that the lifetime of a single squirt is related to the active period of equatorward wind events, which for the area range between 3 and 7 days (Rutllant et al. 2004a), coastal organisms trapped within the squirt are likely to reach 100–200 km offshore in a period of less than a week. The conclusions that may be offered as a result of this brief, and highly condensed, analysis of the prevailing mesoscale coastal features of the HCS are nevertheless far reaching. In the first place, if these features are intrinsic to the HCS (generated as a result of coastline geometry, bottom topography and prevailing flow conditions including perturbations) and not dependent on largescale, low-frequency forcing (e.g., ENSO), then a whole new array of multiscale (nested) models are necessary to generate predictable bio-oceanographic coastal patterns for the HCS. Second, coastal upwelling areas can be described as a dynamic mosaic of nearshore retention/offshore expatriation patches or sectors. Thus, for a planktonic organism, remaining in a specific location (i.e., local populations) within the HCS coastal zone becomes a probabilistic process. If, for example, larvae are entrained within an upwelling shadow then there is a high chance that they will remain in the same sector for a period close to a week. If, on the other hand, the larvae are entrained within a squirt, then in a period close to 24 h they will be expatriated offshore. However, since the seascape is dynamic and depends upon the upwelling condition, it is not possible to ensure that a given geographic location will always act as a retention or expatriation locality. 206

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26°S

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Figure 3 (See also Colour Figure 3 in the insert following page 344.) Result of the squirt simulation by means of the Regional Oceanic Modeling System (coloured image) for 17 January in comparison to the thermal squirt (NOAA satellite, black-and-white image) observed on 15 January 2005. Temperature coding of the coloured image goes from blue (lower temperature) to red (higher temperature) while for the NOAA image it goes from lighter to darker tones of grey. White areas in the NOAA image correspond to clouds. The study area in the model was defined by longitudinal boundaries set at 74°W and 70°W and latitudinal boundaries at 32°S and 24°S. The resolution was 1/10°, approximately 10 km, with 20 vertical levels, a minimum depth of 50 m and a smoothed bathymetry. The baroclinic time step was set to 900 s. Surface forcing (wind stress, heat fluxes, freshwater flux, SST, sea-surface salinity, and short-wave radiation) was derived from the monthly climatology found in the COADS dataset (Da Silva et al. 1994) and interpolated into the model grid. The temperature and salinity initial conditions for the model were obtained for the month of January from the ‘World Ocean Atlas 2001’ (Conkright et al. 2002). The Ekman and geostrophic velocities at the boundary were obtained combining these data with COADS winds, following Marchesiello et al. (2001), with level of no motion defined at 500 m (Marchesiello et al. 2003).

The water column chemistry The northern Chilean ocean margin (~18–30°S) presents distinctive characteristics in topography, climatic and oceanographic conditions, which modulate PP and water column chemistry. It features a comparatively low PP (for the HCS), and despite semi-permanent wind-driven upwelling some areas are considered as high-nutrient low-chlorophyll (HNLC) environments (Torres 1995, Daneri et al. 2000). These observations are in contrast to the localised prominent upwelling cells with relatively high PP, such as off Iquique (21°S), Antofagasta (23°S) and Coquimbo (30°S) (0.5–9.3 g C m−2 d−1; González et al. 1998, Daneri et al. 2000, Thomas et al. 2001a). Studies carried out in the main upwelling centres indicate that highest PP foci occur close to the coast over the narrow continental shelf and fuel major fisheries, with catches that represent 207

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40% of the annual landings of the HCS (Escribano et al. 2003 and references therein). This production also constitutes an important way of sequestering CO2 and supports a high rate of particulate organic matter (POM) exported to depth (González et al. 2000a, Pantoja et al. 2004). This material, which is partly remineralised in the water column, strengthens the oxygen-minimum zone (OMZ) and promotes biogeochemical anaerobic processes. In this sense, a sequence of mechanisms that are determined by the oceanographic conditions is regulating the chemistry of the water column and the sea bottom. These processes gain relevance in several aspects of material exchange (i.e., gas fluxes as CO2 and N2O), implying that this area could play a key role in the main global cycles (i.e., oceanic productivity, global warming, authigenic carbonatic and phosphorite mineral formation, etc.).

Oxygen distribution and relevance in organic carbon remineralisation Most research efforts have focused on specific areas where high productivity cells are recognised, but the interactions with biogeochemical processes are still poorly understood. Along the northern margin of Chile, a well-developed OMZ is observed between 100 and 500 m water depth (Blanco et al. 2001). This zone is basically a mid-water feature since the topography of the margin precludes the OMZ to impinge on a large area of the bottom, except off Antofagasta (Mejillones) where it touches the bottom from 50 m to 300 m depth. Normally the shelf is extremely narrow from southern Peru to northern Chile (10–15 km) in comparison with central Peru and southern-central Chile (40–60 km; Strub et al. 1998), where the OMZ extends over a wide area of the shelf, promoting distinct biogeochemical processes (Gutiérrez 2000, Neira et al. 2001). This characteristic of northern areas could thus affect pathways (i.e., aerobic or anaerobic) associated with organic matter (OM) degradation in the sediments, which is an important source of regenerated nutrients to the water column. Off Mejillones, a high percentage (86%) of photosynthetically produced particulated protein is being degraded within the upper 30 m of the water column (Pantoja et al. 2004), coinciding with oxygenated waters. In consequence, OM reaching the sediments at greater depths is depleted of proteins. Over the shallower shelf sediments, where also preserved fish debris and bones are found (Milessi et al. 2005), high pigment concentrations have been reported (42–100 µg g−1 of chloroplastic pigment equivalents in surface sediments; P. Muñoz et al. 2004a, 2005). Thus, there is a narrow band of inshore sediments that are enriched in fresh OM coming from the water column. The remineralisation of this material could generate an important flux of nutrients contributing to fertilisation of the water column. Similar predictions can be made for other areas of high PP along the coast of northern Chile, where upwelled waters containing preformed nutrients are enriched with recycled nutrients derived from the OM degradation in shelf sediments. The relevance of the sea floor in water column fertilisation and biological productivity as well as its relevance in the global carbon cycle has not been well examined. Some information is available for the role of sediments near the main upwelling centres, but nothing is known about the biogeochemical processes along the large extent of the margin between the main upwelling centres mentioned here. The high OM degradation rates result in CO2 supersaturated waters that, in combination with the CO2 input from upwelled waters, favour the CO2 flux from the ocean to the atmosphere. Some studies off Antofagasta (23–24°S) and Coquimbo (30°S) have measured a saturation of >200% in upwelled waters, an f CO2 up to 1000 µatm and CO2 flux ~3.9–4.0 mol C m−2 yr−1 (Torres et al. 2003 and references therein). These authors concluded that CO2 outflux is a highly variable shortterm process, depending on the intensity of the wind-driven upwelling, the depth of the upwelled waters, the OM degradation (positively correlated with the apparent oxygen utilisation, AOU) and the biological uptake. Furthermore, the high degradation rates of organic carbon by the microplankton community (dissolved organic carbon-, DOC; 1.1–21.6 µM h−1; G. Daneri unpublished data) and high respiration rates (81–481 mmol O2 m−2 d−1; R.A. Quiñones unpublished data) indicate 208

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that nutrient recycling in the water column is an important process in the CO2 production, resulting in high concentrations of CO2 and outgassing when upwelled waters are warming up at the sea surface. A substantial proportion of the carbon assimilated by primary producers is reaching the bottoms via biogenic CaCO3 flux, as has been observed off Coquimbo (30°S) where sediment traps located at 2300 m water depth (~180 km off the coast) revealed that almost 40–90% of carbonate flux is associated with some species of foraminiferans characteristic of upwelling areas (H.E. González et al. 2004a, Marchant et al. 2004). These authors suggest that biogenic CaCO3 is the main pathway by which carbon is removed from the upper ocean, controlled by autochthonous and allochthonous foraminiferans, that is, large-size organisms with high sinking rates (1.5 days) and smaller organisms that are laterally advected. Therefore, part of this carbon is exported offshore, sequestered from the water column and preserved in the sediments (Hebbeln et al. 2000a,b), but it has not been clearly established what percentage of the total CO2 assimilated by primary producers this CaCO3 flux represents.

Macro- and micronutrient distribution The distribution of nutrients shows a high variability in the water column associated with upwelling pulses and mixing. High concentrations occur inshore and usually decrease in the offshore direction, followed by decreasing pigment concentrations (Escribano et al. 2003, Marín et al. 2003a, 2004a, Peñalver 2004). Off 30°S, high surface concentrations of nitrate, phosphate and silicate have been reported (~5–15, 0.5–1 and 5–8 µM, respectively; Peñalver 2004). The nutrient distribution at this latitude is also affected by the topography of the area, where several islands reduce the circulation and mixing of the water column (Peñalver 2004). In northern Chile, between 20°S and 22°S, high concentrations of nitrate were also observed near shore at <100 m water depth (0–20 µM; Escribano et al. 2004b, Pantoja et al. 2004, Herrera & Escribano 2006). In general, the distribution of nitrate showed low subsurface concentrations (Pantoja et al. 2004, Peñalver 2004) associated with high nitrite concentrations (>2 µM; Morales et al. 1996) and coincident with low oxygen concentrations (<0.5 ml L−1). This implies that denitrification is an important process in the nitrogen recycling, as has been recognised for other OMZ regions (Codispoti & Christensen 1985, Codispoti et al. 1986, Cornejo et al. 2006). Another important aspect that controls the biogeochemistry of the water column is the hydrological regime. Northern Chile, with the Atacama Desert, is an extremely arid zone without relevant fluvial inputs into the ocean. The maximum amount of precipitation is ~0.5–78 mm yr−1, which is significantly lower than in central and southern Chile (300 to >1000 mm yr−1; www.meteochile.cl). In general, rivers play an important role in the fluxes of trace metals, nutrient and particulate matter to coastal waters, and some of these components are considered to be important factors determining PP in the water column. For example, Fe has been proposed as a factor limiting PP in waters enriched with other macronutrients but low in pigment concentrations (Martin & Gordon 1988, Martin et al. 1993, Coale et al. 1998). Some recent studies suggest that this element should be relevant in PP off northern Chile, where low dissolved Fe concentrations have been measured (0.6–1.4 nM; R. Torres unpublished data). Additionally, other elements such as Cd and Co may also play an important role in biological processes. The concentration of dissolved Co in the water column shows a similar vertical distribution as macronutrients in an upwelling region off Peru (8–10°S), apparently controlled by biological uptake and remineralisation (Saito 2005). In the same sense, dissolved Cd in the water column for Mejillones Bay shows a typical micronutrient-like distribution (23°S; J. Valdés unpublished data). Low values of dissolved Cd (~0.4–1.6 nM) were found in the water column, while very high concentrations were measured in surface sediments (~60 µg g–1; Valdés et al. 2003). In other coastal waters of northern-central Chile, high Cd values in sediments are probably associated with biological uptake and subsequent deposition in the 209

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sediments (~30°S; <6.6 µg g−1; P. Muñoz unpublished data). Therefore the uptake of trace elements by primary producers and subsequent export to sediments appears to be another important factor controlling the concentrations of metals and nutrients in the water column.

Dominant primary producers and their role in the pelagic food web The HCS off Chile demonstrates high PP associated with wind-driven upwelling events of different intensities and frequencies along the South American coast (Strub et al. 1998). In northern Chile (21–23°S, off Iquique and Antofagasta), a permanent upwelling sustains high PP throughout the entire year (3–9 g C m−2 d−1; Daneri et al. 2000, Montecino & Quiroz 2000, Iriarte & González 2004) while in the central-southern area (i.e., Concepción at 36°S) the upwelling events are mainly concentrated in the spring–summer period (Strub et al. 1998). In the above coastal areas intense upwelling of nutrient-replete waters fertilise the euphotic zone (e.g., NO3−: 10–25 µM) (Escribano et al. 2004b) creating suitable conditions for large-size primary producers, and in turn causing profound effects on the water column processes such as carbon flow through the pelagic food web and carbon export toward deeper layers of the ocean. Off northern Chile a weak seasonality in chlorophyll-a (chl-a) concentration showed slightly higher values during the winter and early spring, whereas in central southern Chile (30–40°S), the annual maximum in chl-a concentration occurred during the summer (Thomas et al. 2001a). In the northern coastal area off Chile (18–24°S) the highest chl-a concentrations (15–20 mg m−3) were mostly restricted to a narrow inshore zone (<37 km) and were associated mostly with microphytoplankton (>20 µm), whereas pico- and nanophytoplankton (pico: 0.7–2.0 µm; nano: 2.0–20 µm) predominate in the offshore, mostly oligotrophic zone (Morales et al. 1996, Iriarte & González 2004). Off central Chile (33–37°S) upwelling-favourable south-southwest winds predominate during the austral spring and summer months when chl-a ranged between 3.8 and 26 mg m−3 compared with 1.0–2.5 mg m−3 recorded during winter (González et al. 1989, Montecino et al. 2004). The permanent and seasonal upwelling off Antofagasta (Mejillones Bay) and Concepción (Concepción Bay), respectively, produce a highly productive phytoplankton assemblage, dominated by no more than 10 species of chain-forming diatoms, such as Chaetoceros spp., Thalassiosira spp., Guinardia delicatula, Rhizosolenia spp., Detonula pumila, and Eucampia cornuta (Rodríguez et al. 1996). The cell sizes of the phytoplankton species along the northern coast of Chile generally are >20 µm (Morales et al. 1996, Iriarte & González 2004), and high microphytoplankton abundances in the sediment record correlate positively with intense/more frequent upwelling events (higher PP) in waters of Mejillones Bay (Ortlieb et al. 2000). In contrast, small-size phytoplankton (<20 µm) predominate in oligotrophic regimes, associated with the intrusion of subtropical, nutrientdepleted, warmer subtropical waters (STW) (Iriarte et al. 2000, Iriarte & González 2004). In such cases, small dinoflagellates (Gymnodinium spp., 5–25 µm) and autotrophic flagellates dominated the phytoplankton assemblages (Iriarte et al. 2000). In Concepción Bay (37°S), few numerically dominant diatom species represented >80% of the total diatom abundance during upwelling events (González et al. 1987), and in correspondence with this, the highest biomass was concentrated in the microphytoplankton fraction (>20 µm) from winter through spring (González et al. 1989). The first studies that considered several trophic levels of the pelagic system (Peterson et al. 1988) and trophic models of carbon flux (Bernal et al. 1989) were conducted in the coastal area off Concepción during the late 1980s. These original studies supported the classical view that the upwelling areas are characterised by short food chains dominated by large chain-forming diatoms and few small clupeiform fish species or the ‘traditional food chain’ (Ryther 1969). This view has recently been challenged, highlighting the relevance of the microbial loop (Troncoso et al. 2003, 210

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Vargas & González 2004) and gelatinous food web (H.E. González et al. 2004b). These trophic flows are important throughout the whole year in oceanic areas and are highly relevant during the non-productive periods (including EN events) in coastal upwelling areas. The carbon budget of the photosynthetically generated OM in the coastal areas of the HCS has been under debate for many years (Bernal et al. 1989, González et al. 1998). It is accepted nowadays that the fraction of the PP removed from the photic zone, which is highly variable on an annual basis (Hebbeln et al. 2000a), strongly depends on the various biological (internal metabolism), physical (stratification/mixing), and chemical (nutrient rich/poor waters) processes involved as well as the time of year. However, the sources of this variability, both in space and time, have been poorly analysed until recently (Morales & Lange 2004), mainly because of the lack of long-term time-series studies. In Figure 4 the main pathways of the photosynthetically generated organic carbon are depicted. Very high bacterial secondary production (BSP) has been reported in the coastal area of northern-central Chile (Troncoso et al. 2003, Cuevas et al. 2004), suggesting a tight coupling between PP and BSP. The pivotal role of bacteria is supported by the exceptionally high

Primary production 5700 Microplankton respiration

Zooplankton grazing 455 Iquique

1513

−20°

Bacterial secondary production 1106

Antofagasta −25°

114

A Coastal area off Antofagasta Coquimbo

−30°

Primary production 4570 Microplankton respiration

Zooplankton grazing −35°

321

1400

Concepción

Bacterial secondary production 2300

Export production

Southern latitude

Export production

−40°

336

B Coastal area off Concepción

Figure 4 Photosynthetically generated carbon and its flows (rate estimates in mgC m–2 d–1) through the more relevant biological processes in the upwelling system off Antofagasta (23°S) and Concepción (37°S).

211

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degradation rates of dissolved organic carbon in Concepción Bay (1–21 µM h−1; G. Daneri unpublished data) and the high BSP rates (range of 1100–2300 mg C m−2 d−1 or 19–50% of PP). Microbial community respiration rates (Eissler & Quiñones 1999) are also very high along the HCS, reaching average values of 1450 mg C m−2 d−1 (~28% of PP). Finally, both zooplankton grazing and export production (González et al. 2000b, Grünewald et al. 2002) gave values between 100 and 500 mg C m−2 d−1 (or mean values between 2% and 10% of PP). These carbon flows are more representative of the coastal upwelling systems of Antofagasta and Concepción because they are the most studied areas (from an oceanographic point of view) along the Chilean coast. Estimations of PP for the HCS along the Chilean coast are similar to those of the Peru (4000 mg C m−2 d−1; Walsh 1981) and about 2-fold higher than those of the California (1000–2500 mg C m−2 d−1; Olivieri & Chavez 2000) upwelling systems. In addition, typical upwelling values for the flow of OM through bacteria in the HCS (19–50% of PP) are well within the range (3–55% of PP) of those described for other upwelling systems in the world oceans (Ducklow 2000).

Processes affecting primary production and export processes In coastal areas of central and southern Chile there is a distinctive seasonal pattern involving the development of maxima (spring) and minima (winter) in phytoplankton biomass and PP during an annual cycle (Ahumada 1989, González et al. 1989). In contrast, high and more constant phytoplanktonic biomass and PP has been observed during an annual cycle along the northern coast off Chile (Marín et al. 1993, Rodríguez et al. 1996, Marín & Olivares 1999). Among the factors that might control the PP, light limitation (P. Montero & G. Daneri unpublished data) and Fe availability (Hutchins et al. 2002, R. Torres unpublished data) have been suggested for the Concepción and Coquimbo upwelling systems, respectively. In addition, high microzooplankton grazing might control the PP during non-upwelling conditions (i.e., winter) in Concepción Bay upwelling (Böttjer & Morales 2005). The understanding of the factors that regulate the magnitude and the variability of phytoplankton PP is quite complex in the HCS due to the geographically distinctive upwelling areas (wind stress, topography), seasonal changes (winter vs. spring) and coastal–oceanic gradients. Integrated values in Table 1 indicate that the variation in chlorophyll concentration is coherent with changes in PP; that is, estimates are lowest in the Coquimbo upwelling system and highest in Antofagasta and Concepción coastal upwelling areas. Higher chlorophyll-specific productivity at Coquimbo and Antofagasta during EN 1997–1998 (2.5–2.8 vs. 1.0–2.0) indicates that the increase in specific productivity did not result solely from a biomass decrease, but from a change in the phytoplankton size distribution (therefore in species composition), from the larger size class (microphytoplankton) to smaller size classes (pico- and nanoplankton). The intrusion of oligotrophic oceanic waters into the coastal area off Coquimbo (Shaffer et al. 1995) and Antofagasta (Iriarte & González 2004) during an EN could be a possible explanation for the low productivity and the dominance of smaller phytoplankton size fractions and their large contribution to total PP. This feature suggests that biological and physiological shifts occur at the phytoplankton species level in order to counteract the change in prevailing physical and chemical conditions in those areas (Montecino & Quiroz 2000, Pizarro et al. 2002). On the other hand, in the permanent/seasonal coastal upwelling of cold nutrient-rich waters in enclosed areas like Concepción Bay and Mejillones Bay, PP estimates increase up to 12 g C m−2 d−1. In the above-mentioned areas, the microphytoplankton fraction accounted for >50% for the total autotrophic biomass and PP. In general, the range of specific rate of productivity in the three upwelling areas could indicate that physiological factors such as nutrient supply and/or light availability may regulate the seasonal signal of productivity in those areas, whereas top-down processes such as grazing and production export might be important in removing a fraction of the generated photosynthetic carbon (Figure 4, Table 1). Furthermore, high biological 212

213

Las Cruces (33°S) 1999–2000 Concepción Bay and Gulf of Arauco (36–37°S) Total: 200–21,000 Winter: 481–1600 Spring: 1770–16,670 Spring: 208–544

1–13.5 (mg m–3)

53–141

8.0–92.5

Total: 140–2955 Summer: 605–2224 Winter: 602–1012

Humboldt Current System (19–22°S)

47–695

1100–8100

Antofagasta (22–23°S) Non El Niño 2000–2002 Coquimbo-Valparaíso (30-33°S) 1992–1994, 1995

11.7–175.4

338–6063

Chl. a (mg m–2)

Antofagasta (22–2°S) El Niño 1997-1998

Study area

PP (mg C m–2 d–1)

Spring: 2.0

2.5

1.0

2.8

PB (mmol C mg Chl. a–1 d–1)

Winter: 48% nanoplankton Spring: 84% microphytoplankton

Spring: 65% microphytoplankton

Winter: >50%

Winter: 59% nanoplankton

60–86% microphytoplankton

48–68% nanoplankton

Dominant size class (as % of the total Chl. a)

Thalassiosira spp., Detonula pumila, Chaetoceros socialis, Chaetoceros curvisetus, Skeletonema costatum, Leptocylindrus danicus, Guinardia delicatula

Coast: Pseudo-nitzschia pseudoseriata, Chaetoceros compressus, Leptocylindrus danicus, Rhizosolenia imbricata, Ceratium tripos, Diplopsalis lenticula Oceanic: Chaetoceros coarctatus, Ch. dadayi, Ceratium contortum, C. gibberum, C. macroceros, Dinophysis rapa, Ornithocercus magnificus

Detonula pumila, Leptocylindrus danicus, Pseudo-nitzschia pseudoseriata, Prorocentrum micans

Chaetoceros spp., Thalassiosira spp., Rhisozolenia spp., Detonula pumila, Guinardia delicatula, Eucampia cornuta

Gymnodinium sp., Pseudo-nitzschia cf. delicatissima Autotrophic flagellates

Main phytoplankton taxa

González et al. 1989 Iriarte & Bernal 1990 Ahumada 1989 Daneri et al. 2000 Troncoso et al. 2003 Montecino et al. 2004 Cuevas et al. 2004

Narvaez et al. 2004

Montecino et al. 1996 Montecino & Pizarro 1995 Avaria & Muñoz 1982 Montecino & Quiroz 2000 Troncoso et al. 2003 Morales et al. 1996 Avaria et al. 1982

Pizarro et al. 2002 Iriarte et al. 2000 Ulloa et al. 2001 Troncoso et al. 2003 Iriarte & González 2004

Reference

Table 1 Range of primary productivity, chlorophyll, chlorophyll specific primary productivity rate and main phytoplankton taxa between the 22° to 37°S Humboldt Current System. Primary productivity and chlorophyll estimates are integrated to the 1% light penetration depth

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productivity observed along the northern and central coast of the HCS (23–37°S) is probably fertilising oceanic and oligotrophic areas through the formation of eddies and filaments that transport coastal water offshore (Marín et al. 2003a, Hormazábal et al. 2004, Letelier et al. 2004). Finally, much of what is known about upwelling dynamics, phytoplankton ecology and their role in biogeochemical cycles along the Chilean coast has been mainly gathered from selected upwelling areas (i.e., Antofagasta, Coquimbo, Concepción, Valparaíso) with scarce or no information from areas in-between.

Zooplankton consumers Zooplankton consumers are considered the link between primary producers and higher trophic levels in the pelagic realm of the world ocean. This function also implies a role to regulate the rate at which phytoplankton-C can be transferred through the food web or retained as zooplankton biomass. This rate greatly depends on population turnover rates, which vary widely among zooplankton taxa. Thus, the knowledge of the population biology of dominant species, the community structure and its variation, become key issues in understanding the ecological and biogeochemical role of zooplankton. In the HCS substantial progress has been made in the last decades about some of these issues. In the following sections we summarise the major advances in understanding population, community and ecosystem processes involving zooplankton in the upwelling region off northern Chile. Much less progress is being made in molecular, genomic and genetic biology of zooplankton in this region. However, the need for a better understanding of zooplankton ecology in the region will most likely motivate the use of molecular tools in the near future.

Biogeographic and biodiversity issues In the upwelling region off northern Chile most species or species assemblages are considered to be part of the subantarctic fauna. This fauna originates in the Austral region, but it is then advected northward. In northern Chile and off Peru, it mixes with some species of tropical and equatorial origin. The most studied taxa are Copepoda (Heinrich 1973, Vidal 1976, Hidalgo & Escribano 2001) and Euphausiacea (Antezana 1978, D. Fernández et al. 2002). Nearly 60 species of copepods have been identified, of which the dominant in the coastal zone are Calanus chilensis, Centropages brachiatus, Paracalanus parvus, Acartia tonsa, Eucalanus inermis, Oithona similis, Oncaea conifera and Corycaeus typicus. Calanus chilensis is an endemic species of the HCS (Marín et al. 1994), whereas Centropages brachiatus, Paracalanus parvus, Acartia tonsa and Oithona similis are cosmopolites and widely distributed along the Chilean coast. Eucalanus inermis is a typical tropical species, although the genus Eucalanus may contain about six species, which have not yet been clearly defined. Among euphausiids, the most abundant and endemic species of the HCS is Euphausia mucronata (Antezana 1978). This species is closely associated with upwelling centres off northern Chile (Escribano et al. 2000) and performs an extensive vertical migration into the OMZ. Euphausia eximia is another abundant species, which increases in number during EN (Antezana 1978, González et al. 2000b). Gelatinous zooplankton, on the other hand, has received much less attention, although it may form dense aggregations at times of the year in the coastal upwelling zone (Pagès et al. 2001), and it can exert a strong predation pressure on copepods (Giesecke & González 2004, H.E. González et al. 2004b, Pavez et al. 2006) and possibly on fish larvae. Species replacements seem to occur in the zooplankton associated with EN versus LN regimes (Hidalgo & Escribano 2001). Dominant species alternate between copepods (mainly Calanus and Eucalanus genera) and euphausiids during upwelling conditions and cyclopoid copepods, Paracalanus 214

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and Acartia during EN events (González et al. 2002). Warm conditions during an EN may also cause reduced size of copepods at maturity (Ulloa et al. 2001). All these changes in structure of the pelagic system may have profound implications on the functioning and productivity of this region (see, e.g., Alheit & Niquen 2004) and should also be considered in future ecosystem studies.

Zooplankton and coastal upwelling in northern Chile In the coastal zone off northern Chile, wind-driven upwelling is the principal driver of biological productivity. Pelagic organisms benefit by high productivity in upwelling sites. However, upwelling zones comprise strongly variable environments and zooplankton must cope with changing conditions in this zone. The understanding of these physical and biological interactions in the water column of upwelling systems may give much insight into the key processes that control production and biological diversity of pelagic assemblages. In northern Chile, examples of physical–biological interactions taking place during coastal upwelling are restricted to particular conditions and sites (e.g., Escribano & Hidalgo 2000a, Escribano et al. 2001, 2002, Giraldo et al. 2002). Other studies (Marín et al. 2001) have shown some relevant findings that may help understanding mechanisms through which pelagic populations are able to maintain their populations in the food-rich coastal zone. Off Mejillones Peninsula (23°S), the interaction between a poleward flow and cold upwelling plumes may generate large eddies by which non-migrant plankton can be maintained nearshore. This type of circulation may act as a retention mechanism to avoid offshore advection of zooplankton (Giraldo et al. 2002). Thus, most species maintain their population in the food-rich upwelling centres being recirculated by near-surface currents. In other upwelling systems, such as the Benguela Current, zooplankton is maintained nearshore by vertical migration behaviour (Verheye et al. 1992, Roy 1998). Organisms advected offshore migrate to deep water and then are returned to shore by a compensatory flow. In northern Chile, however, vertical migration does not seem to be an important or widely used behaviour. In fact, most dominant species appear strongly constrained to the upper layer (<100 m) (Escribano & Hidalgo 2000a) because of oxygen-depleted waters in the OMZ, which come close to the surface (<50 m) during upwelling (Morales et al. 1999). Upwelling in the coastal zone off northern Chile may exhibit much spatial variation characterised by discrete upwelling centres, such as those usually observed off Iquique (20°S), the river Loa (21°S), Mejillones (23°S) and Coquimbo (30°S) (Fonseca & Farías 1987). Zooplankton populations tend to aggregate in these upwelling centres and hence they are also very patchily distributed (González & Marín 1998, Escribano & Hidalgo 2000a). Spatial heterogeneity in plankton distribution linked to variability in oceanographic conditions, such as temperature and food quantity and quality, may be one of the major causes of variability in population growth and secondary production along the coast off northern Chile (Giraldo et al. 2002).

Zooplankton and the oxygen minimum zone The OMZ system is a prominent feature in northern Chile closely related to the ESSW. This oxygendepleted water mass is also strongly linked to wind-driven upwelling in the coastal area. The ESSW, which normally occupies the intermediate (200- to 500-m) layer (Blanco et al. 2001), may ascend to shallow waters (<50 m) near the coast due to upwelling (Morales et al. 1999). The influence of this low-oxygen water on pelagic communities of the coastal zone is not well understood. Dominant zooplankton, which usually aggregates near the upwelling centres in this region (Escribano & Hidalgo 2000b), must cope with such low-oxygen conditions. The options are either avoiding the OMZ and restricting the population to the upper oxygenated layer, as earlier reported for some dominant copepods (e.g., Escribano 1998), or evolving some metabolic adaptations to withstand 215

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poor oxygen conditions, such as those described in González & Quiñones (2002). It has been observed that several abundant epipelagic species concentrate in the upper 50 m without exhibiting diel vertical migration (DVM) (Escribano 1998, Escribano & Hidalgo 2000a), although some euphausiids, such as Euphausia mucronata, may temporarily enter the OMZ (Antezana 2002), or some others like the copepod Eucalanus inermis may even reside in it (Hidalgo et al. 2005a). Thus, the OMZ cannot be considered as just a constraint for vertical distribution because several species may use it as their habitat, either temporarily or permanently. The ecological and biogeochemical consequences of entering and living within the OMZ should be considered as relevant issues. Future studies of species life cycles and behavioural or metabolic adaptations may provide novel findings for life under low oxygen, as described for benthic organisms inhabiting these systems (Helly & Levin 2004). Cycling and vertical fluxes of C and N mediated by zooplankton migration and vertical distribution may be substantially modified by the low-oxygen and highly reduced environment. These issues have received little attention for marine zooplankton associated with OMZ systems (e.g., Wishner et al. 1998). In the upwelling region off northern Chile, the most abundant species are usually closely related to coastal upwelling plumes (Escribano et al. 2000, Giraldo et al. 2002). These species have been well identified (Heinrich 1973, Hidalgo & Escribano 2001). Among dominant ones, the studies of horizontal and vertical distribution have been focused on the calanoids Calanus chilensis (Escribano 1998), Centropages brachiatus (González & Marín 1998) and Eucalanus inermis (Hidalgo et al. 2005a) and on the euphausiid Euphausia mucronata (Escribano et al. 2000, Antezana 2002). The available information indicates that Calanus chilensis and Centropages brachiatus are mostly restricted to the upper layer without performing substantial DVM (Escribano 1998, Escribano & Hidalgo 2000a). By contrast, Eucalanus inermis, the dominant species among a complex of four to five species of the genus Eucalanus that coexist in this region, may remain in the upper boundary of the OMZ with limited excursion into surface waters (Hidalgo et al. 2005a). Meantime, Euphausia mucronata has been suggested as actively and daily migrating into the OMZ (Antezana 2002). A summary of the vertical extent of species habitats for zooplankton in this region has been recently constructed from several cruises (Escribano et al. accepted) and is illustrated in Figure 5. Zooplankton can indeed occupy the entire water column despite the presence of an intense OMZ. Occurrence and vertical movements of various species may ensure a substantial contribution of zooplankton to the vertical export of OM.

Zooplankton life cycles and population dynamics Life cycles and population dynamics are certainly important issues for understanding the biogeochemical and ecological role of zooplankton in this region. When examining annual life cycles there are some important factors to consider. Since the entire upwelling region is subjected to interannual variability due to the ENSO cycle, different years might induce changes in populations. Water column warming, an abrupt thermocline and oxycline deepening characterises the EN conditions in northern Chile (Ulloa et al. 2001, Escribano et al. 2004a), in contrast to a typically shallow thermocline and OMZ indicating a ‘normal’ (LN condition) upwelling situation. However, despite oceanographic variability some species, such as Calanus chilensis, seem to have a rather stable annual cycle from year to year independent of ENSO variation (Escribano & Hidalgo 2000b). Dominant zooplankton species have been suggested to be strongly associated with upwelling centres (González & Marín 1998, Escribano & Hidalgo 2000b), and they can thus complete their life cycles within the upwelling zone, growing at temperature-dependent rates under non-limiting conditions of food (Escribano & McLaren 1999, Giraldo et al. 2002). Lack of food shortage has even been suggested during EN conditions (Ulloa et al. 2001). Continuous reproduction and multiple generations throughout seasons characterise life cycles of copepods in this region (Escribano & Rodríguez 216

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Nematoscelis flexipes

? ? Euphausia sp.

Nematoscelis megalops

Stylocheiron affinis

Euphausia tenera

Euphausia recurva

Euphausia eximia (3)

Euphausia mucronata

Euphausia distinguenda

Euchaeta sp.

Candacia rostrata

Candacia sp.

Centropages brachiatus (1)

Pleuromamma gracilis (3)

Acartia tonsa (2)

Euaetideus bradyi

Scolecithrichella bradyi

Calanus chilensis (1)

Corycaeus typicus (1)

Oithona similis

Oncaea conifera (2)

Eucalanus inermis (1)

Paracalanus parvus (1)

Eucalanus attenuatus

Eucalanus subtenuis

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420

Subeucalanus crassus

Depth (m)

THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

Figure 5 Dominant habitat and daily movements of zooplankton species in and out of the main core of the oxygen minimum zone (OMZ) (shaded area) during coastal upwelling at northern Chile. Day (white dots) and night (black dots) positions represent the depth distribution of each one of the species listed and the arrow the extent of their vertical movement. These positions were estimated from depth-weighed averages of abundances. Data are from MinOx cruise carried out in March 2000 (modified from Escribano et al. accepted). (1) Dominant species found in upwelling centers, (2) inshore species, (3) species associated with El Niño events.

1994, Hidalgo et al. 2005b). However, strong variation in population size can be observed at some times of the year (Escribano 1998, Ulloa et al. 2001, Hidalgo et al. 2005b). The populations of annual species typically show a sudden collapse that tends to occur by the end of the summer. This pattern has been described for Eucalanus inermis (Hidalgo et al. 2005b), Calanus chilensis and Centropages brachiatus (Hidalgo & Escribano submitted) and Euphausia mucronata (Escribano et al. accepted). The conceptual model of population dynamics for these species (Figure 6) considers a two-stage population, which may grow exponentially during the spring and early summer at low mortality rate and then exhibit an abrupt decay at high mortality rate due to increased predation. In this model the increase in predation pressure coincides with the rise of the OMZ, which produces a habitat that is vertically constrained to surface waters by low oxygen concentrations, thereby resulting in increased interactions among prey and predators. This model does not preclude the possibility that changing food quality associated with the rise of the OMZ, either through deleterious effects of diatoms on copepods (Ianora et al. 2004) or by low nutrition, might negatively impact the population. Indeed, a recent study (Vargas et al. 2006b) has shown that available food resources may strongly affect reproduction and recruitment of zooplankton in the coastal zone of the HCS.

Future perspectives in zooplankton research Much of the current research devoted to understanding the ecological and biogeochemical role of zooplankton consumers in the upwelling region off northern Chile is focused on establishing 217

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Growth rate

Mortality rate

Co

p pe

o

e dr

cr u

itm

t en

Po p

ula tio

nd

Population size

e ca y

Maximum bloom TEMPERATURE DIATOMS OMZ SpringSummer

AutumnWinter

Figure 6 A conceptual model to describe the annual cycle of dominant zooplankton species at the coastal upwelling off Chile. The model proposes a life cycle in two phases. The first phase (left side) shows a positive growth of the population (growth rate is stable as well as mortality rate: bottom-up control). The population reaches a maximum size coinciding with the maximal diatom bloom and then it suddenly collapses. The second phase (right side) describes the population decay under increased mortality rate of early stages (topdown control) and a slight decrease of growth rate. The panel below describes the environmental conditions upon which both phases take place. Temperature has a weak signal, diatoms reach a maximum, but remain stable, and a key feature is the rise of the oxygen minimum zone (OMZ) coinciding with the population collapse.

quantitative relationships between species and trophic levels or functional groups (e.g., H.E. González et al. 2004b). It is expected that trophic relationships may provide insights on the functional role of zooplankton for recycling C and N in the ocean (Morales 1999, Hidalgo et al. 2005a, Vargas et al. 2007). This should be considered as baseline information for zooplankton modelling in the region. At population level, modelling approaches have rarely been applied to zooplankton in this area (Marín 1997). Nevertheless, biogeochemical modelling incorporating zooplankton is an expected issue for coming years. At any level, however, key oceanographic processes interacting with zooplankton populations need to be identified and understood. Among such processes coastal upwelling, OMZ distribution, ENSO variability and changing food quantity and quality are to be considered crucial.

Fish consumers The pelagic food webs in the HCS, as in other upwelling systems, feature relatively short trophic pathways. In general, besides zooplankton (mainly copepods and euphausids) three trophic levels of consumers can be distinguished: small-size planktivorous fish, larger fish predators and top predators (Neira et al. 2004). The dominant species among the small-size fish consumers are anchovy (Engraulis ringens) and Pacific sardine (Sardinops sagax); large predators include the jack 218

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

mackerel (Trachurus murphyi), hake (Merluccius gayi) and cephalopods (Neira & Arancibia 2004). Top predators in the HCS are large pelagic fish such as tuna (Thunnus orientalis) and swordfish (Xiphias gladius), southern sea lions (Otaria flavescens) and seabirds. Most fish predators in the HCS appear to be non-specialists, which feed opportunistically on a wide range of different prey items. Sardines and anchovy consume small food particles (mainly phytoplankton and copepods), with the anchovy able to consume larger food items than sardines (Balbontín et al. 1979). Anchovy are more specialised on large zooplankton, while sardines consume a wide range of food items from phytoplankton to small zooplankton (Alheit & Niquen 2004). Jack mackerel prey on copepods, euphausids, sardines and anchovies and benthic resources (Medina & Arancibia 2002). Jumbo squids (Dosidicus gigas) feed cannibalistically and on fish, including jack mackerel and anchovy (Chong et al. 2005). Some of the main fish consumers themselves are prey to larger predators, for example, swordfish (Ibáñez et al. 2004) and sea lions (Sielfeld 1999). A generalised scheme of the pelagic food web off central Chile shows the short trophic pathways and the predominance of relatively few main fish consumers (Figure 7A). While the food spectra of most pelagic consumers are relatively well known, information about consumption rates, intra- and interspecific competition or intraguild predation is limited. Similarly, relatively little is known about prey preferences and feeding strategies of the pelagic fish consumers in the HCS. This knowledge is particularly important in light of variable oceanographic conditions, which may modify availability of preferred food items or produce a spatial segregation of predators and prey (e.g., Bakun 2001, Alheit & Niquen 2004). A review by Cury et al. (2000) suggested that the availability of small pelagic fish in the HCS off Peru determines the population size of higher trophic levels. Bakun (2001) pointed out that the interaction between small pelagic fish and their predators is highly dynamic, depending on multiple environmental (oceanic fronts, climate-driven changes in oceanography), biological (reproductive strategies) and behavioural (schooling behaviour) factors. Small fish consumers may temporarily escape from predation in this dynamic system, and if their reproductive and behavioural strategies permit them to find a refuge from predation these species may build up and maintain huge populations (Bakun 2001). Once this dynamic balance is interrupted (e.g., by climatic factors), regime shifts may occur (Alheit & Niquen 2004). It has been proposed that the regime shift from a sardine-dominated system to an anchovydominated system (or vice-versa), which is related to long-term variations in oceanographic conditions (Chavez et al. 2003), may ultimately be mediated by trophic feedbacks (Alheit & Niquen 2004). During warm periods, the preferred prey items of anchovy (large copepods and euphausids) become less available (see also Zooplankton consumers, p. 214ff.) while predation pressure on adult anchovies increases, due to invasions of jack mackerel into coastal waters (Alheit & Niquen 2004). Simultaneously, sardines, which are also important predators on anchovy eggs (Alheit 1987), may be favoured because they have a wide prey spectrum including phytoplankton. The consequences of these regime shifts, which have been analysed for Peru and northern Chile (Alheit & Niquen 2004), also extend to central Chile. Future studies need to examine to which degree bottom-up or top-down mechanisms are involved, and whether EN impacts and fisheries may accelerate these regime shifts. Both prey and predator behaviour also affects trophic interactions in the HCS. In a recent study, Bertrand et al. (2006) suggested that the feeding behaviour of jack mackerel is closely linked to the OMZ and DVM of their prey. These authors discussed that during the day, when prey are hiding in deeper waters, jack mackerel rest near the upper limit of the OMZ. At night, when prey migrate into upper oxygenated waters, jack mackerel become active (Figure 7B). If this model is confirmed in future studies, interannual variation in oceanographic conditions (e.g., the intensity and depth of the OMZ) may also affect the trophic efficiency of jack mackerel. This hypothetical scenario underscores the importance of better knowledge of predator–prey behaviour and interactions in order to better understand the pelagic food webs in the HCS. 219

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A

pelagic fish predators

FISHERY

sea lions

jack mackerel cephalopods

seabirds

euphausids

anchovy sardines

gelatinous zooplankton

copepods

phytoplankton B

Day

100m

Night

jack mackerel Resting Hydrologically driven

200m

−

+ Concentration

Foraging Trophically driven

Zooplankton 300m

400m

Mesopelagic fish

Depth Oxygen

Figure 7 (A) Simplified pelagic food web in the HCS off northern and central Chile; size of boxes indicates relative proportions; grey arrows show mortality due to fishing. (B) Conceptual model of feeding behaviour of jack mackerel (Trachurus murphyi) in response to diel vertical migration of prey into the OMZ; position of jack mackerel shown as grey patches, position of prey organisms shown as continuous grey band. (Modified after Bertrand et al. 2006)

Interannual fluctuations in fish stocks do not seem to affect the general characteristics of the food web off central Chile (Neira et al. 2004). However, fisheries appear to have a long-term impact on the pelagic food web in this area. Fisheries are acting on several trophic levels of the pelagic food web (Figure 7A). Off central Chile, a decrease in the trophic level of the principal fisheries resources has been observed during recent decades (Arancibia & Neira 2005). It needs to be taken into account, however, that populations of some top predators that have experienced severe exploitation in the past (whales) may still be at very low levels, which may be reflected in the structure of present-day food webs. The interpretation of trophic relationships in the different parts of the

220

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

HCS (and in other EBCs) requires detailed understanding of the different components of the respective system (Moloney et al. 2005).

Seabirds and marine mammals In marine environments seabirds and partially marine mammals are highly visible wide-ranging, upper trophic-level consumers. Upwelling systems are generally characterised by high production and relatively short food chains/webs, enabling massive energy transfer to the higher trophic levels (Cushing 1971, Arntz & Fahrbach 1991). The upwelling system of the Humboldt Current is particularly well suited for studying the effects of the marine environment on the biology and ecology of seabirds and marine mammals.

Seabirds In the HCS there is a rich diversity of seabirds, comprising at least 14 breeding species, 9 of which are endemic (Table 2). According to available information, along the coast of Chile the most important breeding colonies are found on islands of northern-central Chile, near upwelling areas. The grey gull (Larus modestus), which nests inland in the Atacama Desert, travels to the coast on a daily basis to forage in the upwelling zones off Antofagasta (~23°S). Although proximity to a feeding ground is relevant in endemic seabirds, it seems that inaccessibility to predators and human intrusion strongly determines the distribution of breeding populations. Despite some protective status, most islands in the HCS are subject to human disturbance. In the past, this was caused mainly by guano harvesting and egg collecting. At present, introduced mammals and unregulated tourism (Ellenberg et al. 2006) are a major problem. The majority of the endemic seabirds breed once a year. However, in their northernmost breeding areas (Peru), species such as the Humboldt penguin (Spheniscus humboldti) nest throughout the year. Apparently, the two-peak breeding strategy has evolved in response to more favourable oceanographic and climatic conditions off Peru, and this behaviour is preserved in northern-central Chile providing additional offspring to those produced during the spring event (Simeone et al. 2002). Furthermore, differences in food availability along its breeding range (~4000 km) might induce lower breeding performance in southern colonies of this species (Hennicke & Culik 2005). These birds feed on the main pelagic fish species from the HCS, mainly anchovy and jack mackerel. The proportion of fish stocks taken by endemic seabirds is not well known, but most likely does not exceed 10%. Incidental mortality of endemic seabirds due to fisheries is mainly caused by gill nets (Simeone et al. 1999, see also Majluf et al. 2002). The HCS is visited regularly by a number of migrant species. Among the Procelariiformes, whitechinned petrels (Procellaria aequinoctialis), Buller’s albatrosses (Thalassarche bulleri), Antarctic prions (Pachyptila desolata) and Juan-Fernández petrels (Pterodroma externa) are the most abundant species during austral summer (Weichler et al. 2004). There is evidence that the HCS is also frequented by other remarkable visitors such as the Chatham, wandering and royal albatrosses (Thalassarche eremita, Diomedea exulans, and D. epomophora, respectively). Apparently the presence of these species at such a distance from their colonies is related to the food abundance in the HCS, which in summer also attracts species like the black-browed albatross (Thalassarche melanophris) from southern islands (56°S) (Arata & Xavier 2003) and during winter species like the white-chinned petrels from South Georgia (Phillips et al. 2006). The abundances of some of these visitors during austral summer may reach 2.5–5 birds km−2, but at present it is not known which proportion of the entire population of these visitors may at times use the HCS as a feeding ground. The large albatrosses mainly feed on cephalopods and pelagic fishes (resulting in deadly interactions with long-line fisheries), 221

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Table 2 Breeding abundance and conservation status of seabirds (number of pairs) and mammals (individuals) on the coast of northern-central Chile. The geographic divisions correspond approximately to the limit of political division of Chile. Data for cetaceans (ψ) correspond to systematic counts during oceanographic trips conducted every January (1999, 2002, 2003 and 2004) surveying an area of ~420 km2. The other data for cetaceans are mainly from sightings made from the land. Species Seabirds Order Sphenisciformes Humboldt penguin Spheniscus humboldti φ Magellanic penguin Spheniscus magellanicus Order Procellariiformes Peruvian diving-petrel Pelecanoides garnotii φ Wedge rumped storm petrel Oceanodroma tethys Order Pelecaniformes Peruvian booby Sula variegata φ Peruvian pelican Pelecanus thagus φ Neotropic cormorant Hypoleucos brasiliensis Guanay cormorant Leucocarbo bougainvillii φ Red legged cormorant Stictocarbo gaimardi φ Order Charadriiformes Band tailed gull Larus belcheri φ Grey gull Larus modestus φ Kelp gull Larus dominicanus Inca tern Larosterna inca φ Peruvian tern Sterna lorata φ Marine mammals Order Carnivora Family Otariidae South american fur seal Arctocephalus australis South american sea lion Otaria flavescens Family Mustelidae Marine otter Lontra felina (ind./km of coast)

18–21°59′S

22–26°59′S

27–29°59′S

30–32°59′S

8120

122

85

33–34°S

8930

5

5

6132

1.5

Order Cetacea (numbers come from sightings) Family Balaenidae Southern right whale Eubalaena australis

9

9

LC

15,560 1400

LC LC

305

—

162

NT

150

440

NT

450

1 10,000 3250 10 2499

LC LC LC NT E

1860

LR

21,656

LR

15,560 400

1000

200

50

12

150

60

23

55

129

100 10

1598

1.0–2.5

21

222

NT

4170

2700

13,797

V

4170

1

1205

CS*

810

10,000

655

Total

E

E

21

LR

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

Table 2 (continued) Breeding abundance and conservation status of seabirds (number of pairs) and mammals (individuals) on the coast of northern-central Chile. The geographic divisions correspond approximately to the limit of political division of Chile. Data for cetaceans (ψ) correspond to systematic counts during oceanographic trips conducted every January (1999, 2002, 2003 and 2004) surveying an area of ~420 km2. The other data for cetaceans are mainly from sightings made from the land. Species Family Balaenopteridae Humpback whale Megaptera novaeangliae Balaenoptera sp. Fin whale Balaenoptera physalus Minke whale Balaenoptera acutorostrata Blue whale Balaenoptera musculus Family Kogiidae Dwarf sperm whale Kogia simus Family Physeteridae Sperm whale Physeter macrocephalus Family Ziphiidae Cuvier’s beaked whale Ziphius cavirostris Family Delphinidae Bottlenose dolphin Tursiops truncatus Short-finned pilot w. Globicephala macrorhynchus Long finned pilot whale Globicephala melas Globicephala sp. Killed whale Orcinus orca False killer whale Pseudorca crassidens Common dolphin Delphinus delphis Southern rightwhale dolphin Lissodelphis peronii Risso’s dolphin Grampus griseus Dusky dolphin Lagenorhynchus obscurus Family Phocoenidae Harbour porpoise Phocoena spinipinnis

18–21°59′S

22–26°59′S

30–32°59′S

33–34°S

Total

CS*

1

17 ψ

18

V

25

9ψ 63 ψ 4ψ

34 63 5

E LR

1ψ

1

3ψ

3

19 ψ

20

V

5

5

—

1

1

27–29°59′S

1

301 ψ

301

n.d.

E

DD LR

101

101

LR

11 11 5

LR LR

200

200

LR

450

450

DD

11 ψ 11 ψ 5ψ

456

30 ψ 1404 ψ

30 1860

DD DD

72

10 ψ

82

DD

Notes: *CS: Conservation status was extracted from IUCN (2006). E: Endangered, V: vulnerable, NT: near threatened, LC: least concern, DD: data deficient, LR: lower risk. φ Endemic species of the Humboldt Current System. Data from Guerra et al. 1987, 1988, Sielfeld et al. 1997, van Waerebeek et al. 1998, Capella et al. 1999, Sielfeld & Castilla 1999, Rendell et al. 2004, Simeone et al. 2003, Frere et al. 2004, Jiménez 2005, Bernal et al. 2006, and G. Luna-Jorquera unpublished data.

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while the smaller petrels consume mainly planktonic crustaceans (e.g., Euphausia mucronata). Although available information shows that incidental mortality in the artisanal Patagonian toothfish (Dissostichus eleginoides) fisheries in southern Chile is low (0.047 birds per 1000 hooks; C.A. Moreno et al. 2006), incidental mortality of petrels and albatrosses in industrial long-line fisheries has not yet been assessed for northern Chile, where most of the Chilean swordfish vessels are based.

Marine mammals Species of mammals listed in Table 2 are those that mainly occur over the continental shelf in the HCS. Although there are no endemic species, the total species richness reaches at least 22 species, most of them being cetaceans. The number of species and abundance of individual sightings in Table 2 suggest that the upwelling regions between 18°S and 30°S are important feeding stations on the migration routes of whales (see also Rendell et al. 2004). For the sea otter (Lontra felina), available information shows that this species feeds mainly in areas dominated by macroalgae (Ebensperger & Castilla 1992, Ebensperger & Botto-Mahan 1997, Villegas 2002), where refuges on land are available (Sielfeld & Castilla 1999). The diet of this species is principally composed of coastal fishes, crabs and seabirds (Sielfeld & Castilla 1999, Mattern et al. 2002) and foraging success is higher at wave-protected sites than at exposed sites (Villegas et al. 2007). The biology and ecology of otariids at both sea and land has been investigated in Peru (Majluf et al. 2002) and Ecuador (e.g., Dellinger & Trillmich 1999), but studies from northern-central Chile mostly focus on population size or demography (e.g., Guerra et al. 1987). Interaction between sea lions (Otaria flavescens) and fisheries is an important issue in Chile (Hückstädt & Krautz 2003). Their traditional foraging behaviour (search and pursuit of prey) has changed to one of ‘sit and wait’ for food captured by fishing vessels (Hückstädt & Antezana 2003), a strategy that appears to be exploited by killer whales (Orcinus orca) preying on sea lions near fishing vessels (Hückstädt & Antezana 2004). While it is well known that sea lions destroy nets and consume pelagic fish, the extent of this problem has not yet been systematically examined in northern Chile. Although there is a lack of information, it appears that there exists an inverse relationship between the breeding distribution of sea lions and endemic seabirds in northern-central Chile (Table 2). Sea lions are most abundant between 18°S and 26°S, while seabirds seem to be more abundant between 27°S and 33°S. The reasons for this spatial separation are not well known, but one possibility might be that sea lions are common in northern Chile where they can successfully breed on small rocky outcrops, while seabirds may be most abundant between 27°S and 33°S, where they form huge breeding colonies on undisturbed islands. Additionally, maternal care might impose higher restrictions (duration and distance of foraging trips) on female sea lions (e.g., Trillmich 1990) than on female seabirds, which share parental care with their male partners and thus can afford longer absence from the nest and farther foraging trips during breeding. The apparent lower productivity of pelagic fish between 27°S and 33°S (see also Pelagic fisheries and fisheries management 1980–2005, p. 288ff.) might affect female sea lions (which usually forage close to the breeding sites; e.g., Trillmich 1986) to a higher degree than seabirds (which may travel >30 km from breeding colonies during individual foraging trips, as observed in Humboldt penguins; Luna-Jorquera & Culik 1999). Future studies should examine the causes for the inverse abundance patterns of sea lions and seabirds along the coast of northern Chile.

Effects of ENSO on seabirds In the upwelling area of Coquimbo (Region IV), the species composition of seabirds at sea fluctuates among different sites, and distribution patterns are linked to variation in SST and chlorophyll 224

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concentration. Dense swarms of pelagic fishes attract high numbers of piscivorous birds, which is the most important factor to explain their distribution patterns. Usually, only 3% of all birds recorded in a given area are seen directly attending fishing vessels (Weichler et al. 2004). Life-history theory predicts that seabirds will respond to reduction in food availability by changing their behaviour and/or breeding effort, thus buffering adult survival. Data of Peruvian boobies (Sula variegata) are in agreement with this prediction (G. Luna-Jorquera unpublished data). In January 2002, about 3000 breeding pairs of this species were registered in a colony off Coquimbo, but 1 month later there were only 10 pairs, coinciding with a positive SST anomaly (Figure 8). Counts of birds at sea conducted in ~420 km2 around the colony showed that the numbers of boobies were lower than in a ‘normal’ year, indicating that boobies left the area probably due to a reduction in food availability. This caused both a reduction in the total numbers of all seabirds foraging in feeding flocks and a simultaneous increase of seabirds attending fishing vessels. During cooler LN years, large concentrations of seabirds were seen in feeding flocks and few birds followed fishing boats (Figure 8). The apparent change in food availability is also reflected in the high number of breeding pairs of boobies during LN years (Figure 8). Endemic seabirds have evolved in the upwelling area of the HCS, where historically their populations are subjected to large fluctuations, ENSO being an important selective force for the evolution of their breeding biology and life-history patterns. During EN, some species abruptly leave their eggs and young to undertake eruptive movements away from the usual breeding and feeding sites in apparent search for food; total or partial breeding failure then often occurs (Simeone et al. 2002). Seabirds are generally characterised by longevity, high age of first breeding, slow reproductive rate and intense offspring care and are thus typical K-strategists. However, it has been hypothesised that, compared with related species, Peruvian boobies and Guanay cormorants (Leucocarbo bougainvilli) have larger clutches, may attempt to breed more than once within 1 yr and reach sexual maturity at an unusually early age (Luna-Jorquera et al. 2003). This enables them to build up populations rapidly in the years after EN events because even young, unexperienced adults are able to raise large broods because the food supply per bird is much greater than it would be in a population in equilibrium with the environment (Furness & Monaghan 1987). However, since the establishment of the anchovy fishery, the dynamics of the seabird populations have changed (Duffy et al. 1984). Instead of rapidly increasing populations by raising large broods at least once per year, endemic seabirds failed to respond to the reduced competition brought about by their reduction in numbers. It seems that the anchovy fishery has taken up the superabundance of food, which in the past permitted the seabirds from the HCS to cope with the recurring crashes induced by oceanographic perturbations (Jahncke et al. 2004). In fact, data available for Peruvian seabird colonies (Tovar & Cabrera 1985) show that the EN 1957–1958 caused a mortality of 39% of the estimated populations of 28 million adult birds. Mortality increased to 57% (of 6.54 million adult birds) due to EN 1972–1973, after 1970 when anchovy landings had reached 12 million t (metric tons). The extreme EN 1982–1983 caused a decrease from 6 million birds to only 0.3 million birds in Peru. After that, the populations showed an increase in numbers, reaching ~6 million birds, but the EN 1997–1998 reduced it again to less than 0.4 million birds. In 2000, the size of the Peruvian seabird population was estimated to be 1.93 million adult birds, showing a slight recovery (IMARPE 2006). No comparable datasets are available for the coast of northern-central Chile, where only infrequent surveys of breeding colonies have been conducted so far (e.g., Simeone et al. 2003).

Food resources or breeding sites? Seabirds and sea lions feed on fish and population crashes during EN years have been explained with the disappearance of fish stocks. Which proportion of the fish stocks do seabirds and seals consume? And how are they affected by variable food supply? Bioenergetic modelling provides 225

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Figure 8 Abundance of breeding and foraging seabirds in the vicinity of Coquimbo, Chile (30°S), and the relationship with sea-surface temperature (SST) anomalies in the southeast Pacific. Upper panel shows SST anomalies during the study period; middle panel shows nesting pairs of Peruvian boobies in a breeding colony on Pájaros Island (29°35′S), and boobies counted during censuses at sea in the Upwelling system of Coquimbo, between 29°08′ and 30°11′ (see Weichler et al. 2004 for more details); lower panel shows total number of all seabirds counted in the study area in January of each year, and the percentage of birds foraging in feeding flocks or attending fishing vessels in search of food.

useful quantitative assessment of the impact of marine vertebrates on fish stocks and may serve to predict changes in fishery practices or effects of fish stock sizes on seabird and seal numbers. Simple predictions would be that species with specialised feeding methods and a high dependence on specific diets, which have been reduced in availability (due to fisheries or oceanographic 226

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conditions), would be most likely to decline in numbers. In order to develop the models to test these predictions, a long-term research programme is necessary to assess (1) breeding populations, (2) feeding ecology, (3) reproductive biology and (4) energy budgets, under different environmental conditions. In particular, it appears to be important to examine the breeding biology of seabirds. There is an indication that populations of seabirds in northern and central Chile may be limited by the availability of undisturbed breeding islands (see Schlatter 1984, 1987, Schlatter & Simeone 1999). While additional research is necessary, present knowledge already identifies the protection of undisturbed breeding sites as one of the highest priorities for seabird conservation in the HCS of northern and central Chile.

Sandy beaches Sandy beaches are a common feature of the Chilean coast between 18°S and 41°S (Figure 9), where they offer breeding habitats and important food resources for migrating shorebirds. The extent and distribution of sandy beaches offers unique opportunities for studying the factors driving the population dynamics of invertebrate consumers along the coast of northern and central Chile. Beaches are found along exposed shorelines, sheltered bays and coastal islands and their total extent and average length show a clear latitudinal trend, increasing toward southern-central Chile (Figure 9). Sandy beaches of the coast of Chile show a general zonation pattern of three zones that differ both in their physical characteristics and biological communities (Figure 10) (Jaramillo 1987, Average distance between beaches (km) 6 4 2 0

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Figure 10 Zonation scheme of sandy beach community along the coast of Chile during winter and summer; shaded background areas represent intertidal gradients in food supply (FS, dotted area) and habitat harshness (HH, grey area), showing both latitudinal and seasonal variation in these physical factors; size of boxes with animal sketches represents proportional abundances of the respective species; note the latitudinal difference in species composition in the upper intertidal zone; species shown are 1, Ocypode gaudichaudii; 2, Phalerisida maculata; 3, Orchestoidea tuberculata; 4, Tylos spinulosus; 5, Excirolana braziliensis; 6, E. hirsuticauda; 7, E. monodi; 8, Emerita analoga; 9, Nephtys impressa; 10, Mesodesma donacium. (Figure inspired by a drawing from Jaramillo 1987.)

McLachlan & Jaramillo 1995, Jaramillo et al. 2001). The lower and middle shore have similar species composition (i.e., Emerita analoga, Mesodesma donacium, Nephtys impressa, Excirolana braziliensis, E. hirsuticauda and E. monodi) along the continental coast of Chile, while the upper shore has species-composition differences between northern, central and southern Chile (Jaramillo 1987) (Figure 10). The upper zone, extending from the drift line up to the dunes, is a very dry environment, occasionally moistened by sea mist. Inhabitants of this zone, such as tenebrionid beetles (Phalerisida maculata), talitrid amphipods (Orchestoidea tuberculata) and oniscoid isopods (Tylos spinulosus) feed on plant and animal remains washed up on the beach (Jaramillo 1987). In the northern zone (18–25°S) and off Peru, the amphipod and isopod species are replaced by the ghost crab Ocypode gaudichaudii (Quijón et al. 2001), which together with Phalerisida maculata inhabits the upper shore (Figure 10). To which degree species replacement is due to physical factors or to species interactions is not well known at present. However, the fact that these faunal changes in the supralittoral zone are accompanied by a gradient in burrowing depth and proximity to the drift line of the main organisms suggests that physical factors (in particular desiccation risk) may play an important role. Guppy (1906) expressed that “the beaches are of dry loose sand in which the hand fails to find on scooping below the surface that refreshing coolness which is the character of beaches in all latitudes where the land is vegetated”. 228

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Within the beach, there are differences not only in the interspecific but also in the intraspecific zonation patterns, which may be accompanied by behavioural differences. In particular, locomotor activity and position on the beach varies depending on the developmental stage and on the time of the day. For example, juvenile Orchestoidea tuberculata and Phalerisida maculata are most active during the day, while adults show highest activities at night (Jaramillo et al. 1980, 2000). This has been suggested as a strategy to avoid intraspecific competition for food and additionally the risk of intraspecific predation. Furthermore, Orchestoidea tuberculata shows an aggregated distribution on kelp patches stranded in the supralittoral zone (Duarte et al. 2004), which is related mainly to feeding behaviours. For Emerita analoga and Mesodesma donacium, similar ontogenetic differences in activity or habitat use have been reported. Juvenile Emerita analoga typically occur in highest abundances in the low intertidal zone slightly above the adults (Contreras et al. 2000). Similarly, juvenile Mesodesma donacium inhabit the lowest intertidal zone of the beach (in the swash zone), while adults live in permanently water-covered sediments of the subtidal zone (mainly in the surf zone) (Jaramillo 1994). Most sandy beach studies have centred on the effect of physical factors, in particular wave exposure, grain size and tides, on the community structure. Species richness, biomass and abundance decrease from dissipative to reflective beaches (Jaramillo 1994, McLachlan & Jaramillo 1995). Biological interactions are more intense on dissipative beaches than on reflective beaches, where the population dynamics are mainly controlled by physical factors (Defeo & McLachlan 2005). Strong competition between mole crabs Emerita and surf clams Donax has been suggested as the cause for the aggregated distribution of the surf clams (Leber 1982), and negative interactions between Emerita analoga and Mesodesma donacium were observed along the Chilean coast (Dugan et al. 2004), but aggregations may also be a response to sediment characteristics (i.e., grain size). On the other hand, organisms inhabiting the upper shore (i.e., talitrid amphipods) are not associated to one particular beach type (Defeo & McLachlan 2005), which suggests that their populations are not influenced by beach morphodynamics but rather by other physical factors or food availability. To which degree resource or interference competition (or direct predation) is responsible for the latitudinal changes in the species composition of this zone remains to be explored. The species that inhabit sandy beaches have diverse reproductive strategies, which can be related to the habitat characteristics. For example, most of the species of the upper and middle shore (i.e., Orchestoidea tuberculata, Tylos spinulosus and Excirolana spp.) have direct development, which might suggest that the connectivity between populations is low. In northern-central Chile (29°S) the reproductive peak of Excirolana hirsuticauda is in spring–summer (Contreras & Jaramillo 2003), and it is suggested that the other species from the upper/middle shore follow a similar pattern. The lower intertidal and subtidal zone is inhabited by organisms with indirect development (Emerita analoga, Mesodesma donacium, Nephtys impressa), which have planktonic larvae possibly permitting higher connectivity between local populations. For Emerita analoga, distinct recruitment peaks (see also Arntz et al. 1987 for Peru) have been reported for autumn, spring or early summer in northern (22°S) and southern-central Chile (39°S), but ovigerous females are usually found throughout the year (Contreras et al. 1999, Contreras et al. 2000). In northern-central Chile (30°S) the surf clam Mesodesma donacium has two spawning peaks during the year (usually during the early summer and autumn), but females with mature gonads have been observed throughout most of the year (Alarcón & Navea 1992, Stotz et al. 1999). These observations suggest continuous reproductive activity, but spawning or successful recruitment seems to occur only infrequently, possibly depending on particular environmental factors (triggering gamete release) and oceanographic conditions (affecting larval survival and supply). There is also a high temporal variability of faunal abundance throughout the year. For example, Orchestoidea tuberculata reach highest abundances during the winter months, both in central (30°S) and southern Chile (40°S) (Sánchez et al. 1982, McLachlan & Jaramillo 1995). Furthermore, during 229

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the winter, these amphipods live higher up on the beach, mainly to avoid being washed out by higher wave activity. During summer, the abundances of O. tuberculata decrease and they are found closer to the flotsam (Sánchez et al. 1982, McLachlan & Jaramillo 1995), possibly to avoid desiccation risk in the supralittoral zone or to get close to their food. The cirolanid isopods (Excirolana spp.) have similar abundances in summer and winter, but they shift their position in the intertidal zone, moving higher during the winter months (Sánchez et al. 1982). On the other hand, Emerita analoga in the northern (22°S) and Mesodesma donacium in northern-central Chile (30°S) reach highest abundances in summer (Sánchez et al. 1982, Contreras et al. 2000). At present, the reasons for the apparent inverse population dynamics of species from the upper versus those from the lower intertidal zone are speculative, and seasonally varying offspring (larval) survival or food supply could be invoked. One very interesting species from the supralittoral zone, Tylos spinulosus, which has a restricted distribution in northern-central Chile (17°–30°S) (Schmalfuss & Vergara 2000), is little known aside from a few data on its population density (Sánchez et al. 1982, Jaramillo et al. 2003), and it appears a promising enterprise to examine its population dynamics. The vicinity to upwelling centres plays an important role in the succession and structure of hard-bottom communities (Broitman et al. 2001, Narváez et al. 2006), but there is no clear indication that the macrofauna composition of sandy beaches is influenced by their proximity to upwelling areas (Jaramillo et al. 1998). Contreras et al. (2000) concluded that growth rates of Emerita analoga from a beach near the upwelling centre of Mejillones (22°S) were within values reported for other areas, suggesting only limited or no direct effects of upwelling on sandy beach inhabitants. Community dynamics of sandy beaches may be influenced by upwelling to a lesser degree than those pertaining to hard-bottom communities. For example, higher nutrient availability near upwelling areas positively influences growth rates of seaweeds on hard bottoms (Camus & Andrade 1999, Wieters 2005) and thereby the community succession (Nielsen & Navarrete 2004), which clearly is of no importance on exposed sandy beaches where algae are usually imported from neighbouring (or distant) hard-bottom habitats. Furthermore, the interplay between upwelling and subsequent relaxation events strongly affects the recruitment of hard-bottom organisms with planktonic larvae (Narváez et al. 2006), but seems to be of minor importance on sandy beaches, where the most common organisms feature direct development. The effect of ENSO has been intensively studied in hard-bottom environments, but its role in the dynamics of sandy beach communities is not well known (Arntz et al. 1987). EN events may have deleterious effects on the organisms from the lower intertidal zone of sandy beaches (e.g., Mesodesma donacium; see also Artisanal benthic fisheries, p. 278ff.). On the other hand, it is known that EN provokes mass mortalities of seaweeds and animals, many of which eventually will strand on sandy beaches (Arntz 1986). This high supply of OM may represent an important food source for scavenging animals of the supralittoral zone of sandy beaches (e.g., Orchestoidea tuberculata). In this way, it can be suggested that intertidal organisms are distinctly affected by EN: species from the lower shore (suspension feeders with planktonic larvae) may be negatively affected by EN, while those from the supralittoral zone (scavenging animals with direct development) might benefit from the higher food supply and more benign climate (lower desiccation risk) during EN.

Subtidal soft-bottom communities Zonation patterns Recent studies suggest that the bathymetric distribution of subtidal benthic communities off the Chilean margin seems to be controlled mainly by bottom water oxygen conditions and sediment organic loading. OMZs are significant mid-water features in the eastern Pacific Ocean (Wyrtki 1973, Kamykowski & Zentara 1990) that strongly influence the distribution and diversity of 230

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planktonic and benthic marine communities. Where OMZs intercept the continental margin (bottomwater dissolved oxygen < 0.5 ml L−1), strong gradients are formed in both bottom-water oxygen concentration and OM input (Levin et al. 1991, Levin et al. 2000). These gradients influence the biogeochemical properties of sediments (Cowie et al. 1999) and the distribution and diversity of bacteria, meio-, macro- and megabenthic organisms (Sanders 1969, Mullins et al. 1985, Wishner et al. 1990, Tyson & Pearson 1991). Off Chile, oxygen-deficient waters are in general associated with the ESSW, which partially covers the continental shelf and upper bathyal area. The intensity and vertical extent of the OMZ suggest a latitudinal gradient, the effect disappearing at about 41°S (Brandhorst 1971). Off northern Chile, sediments affected by the OMZ extend from a few tens of metres below the surface to 300–400 m water depth. Between Huasco and Valparaíso (~28–32°S), the OMZ seems to intercept the sea floor deeper than 100 m (D. Lancellotti & W. Stotz unpublished data), and due to the narrowness of the shelf and steepness of the slope, there are zones that probably are not severely affected. This is also corroborated by the presence of a fauna atypical for oxygendeficient areas (e.g., diverse species of gastropods) and the absence of bacterial mats (Lancellotti & Stotz 2004). The shelf widens southward and when upwelling prevails, during spring–summer, the OMZ again can be found only a few metres from the surface even in southern-central Chile (~36°S), within Concepción Bay (Ahumada et al. 1983), and extending down to 200–300 m (see also Arntz et al. 2006). However, the OMZ intensity here is probably the result of many local factors (e.g., the high PP that leads to high remineralisation rates in the water column and sea floor, consuming oxygen and generating sulphidic conditions within the sediment) (P. Muñoz et al. 2004b). In this way, it is probably possible to visualise the OMZ impinged sea floor, from northern to central Chile, as a wedge-shaped band, getting narrower southward, but with two foci of most intense oxygen-deficient conditions, one off northern Chile and the other at the shelf off Concepción. The continuity between these two foci may be interrupted by better-oxygenated sediments, at comparable depths, off central Chile. Reports of low bivalve abundances between 80 and 120 m depth in Valparaíso Bay (31°S) are suggestive of OMZ effects (Ramorino 1968), but additional data are required to resolve the intensity and extent of the OMZ and its effect on benthic communities between 25°S and 35°S. Considering the general effect of the OMZ on benthic communities, and based on the limited amount of biological sampling available at that time, Gallardo (1963) proposed the existence of basically three main benthic zones for the local eukaryotic communities: (1) an upper sublittoral zone, up to 50 m depth, with favourable conditions for the development of ‘normal’ benthic communities, (2) a lower sublittoral zone, from 50 to 300–400 m (varying with latitude and coinciding with the extent of the OMZ), in which only those organisms highly adapted to cope with oxygen deficiency and high organic loadings are able to thrive (basically small polychaetes, oligochaetes, nematodes and a few molluscs), and (3) a bathyal area, associated mainly with Antarctic Intermediate Waters, with a diverse and rich fauna (dominated by annelids, crustaceans, molluscs and echinoderms) that benefits from enhanced oxygen and good quality and quantity of sediment OM. How this general pattern differs in southern areas (>41°S) where the OMZ dissipates is still poorly known. One of the most distinguishing features of benthic shelf communities within OMZ-impinged sediments is the presence of extensive mats of the filamentous, sulphide-oxidising bacteria Thioploca and Beggiatoa (Gallardo 1963, 1977, Schulz et al. 2000, Arntz et al. 2006). These bacteria are the most conspicuous component of the benthos also in the central and southern Peruvian shelf (Rosenberg et al. 1983). Bacterial biomasses of up to 1 kg m−2 wet wt have been reported from shelf sediments off Iquique (~21°S) (Gallardo 1963) and off Concepción (~37°S) (Gallardo 1977) at depths between 50 and 100 m. On the other hand, within the OMZ eukaryotes are in general small-size forms, like meiofauna, calcareous foraminiferans and nematodes (Gooday et al. 2000, Neira et al. 2001, Levin 2003). Very high densities, on the order of 10,000 individuals (ind.) 10 cm–2, 231

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of meiobenthic organisms, mostly nematodes, have been recorded on the shelf off Concepción (Neira et al. 2001, Sellanes et al. 2003). OMZ macrofaunal assemblages thus have low diversity and are typically composed of organisms with morphological and metabolic adaptations and feeding strategies suited to these conditions. A good example is the locally abundant polychaete Paraprionospio pinnata, an interface feeder organism, which is also able to switch to suspension feeding (Gutiérrez et al. 2000), with a complete set of enzymes for anaerobic metabolism (González & Quiñones 2002), and also bearing a set of highly branched and complex gills. Paraprionospio pinnata comprises about half of the ~14,000 macrofauna individuals m−2 reported from off Concepción within the OMZ (Palma et al. 2005). Below the OMZ, the total abundance of macrobenthos decreases while biomass and diversity increase in parallel with increases in oxygen and decreases in organic carbon (Levin 2003). In the bathyal area off Chile, important crustacean assemblages, mainly of commercially valuable galatheid decapods (e.g., Pleuroncodes monodon and Cervimunida johni), thrive at the slope within and below the lower boundary of the OMZ. Below the OMZ, groups that are favoured by increased oxygen concentrations are decapod crustaceans, gastropods and at greater depths echinoderms (mainly ophiuroids, asteroids and irregular echinoids). The large tubiculous onuphid polychaete Hyalinoecia sp. (tubes 10–20 cm in length) is particularly abundant at mid-slope depths off Concepción and Chiloé (J. Sellanes personal observations). Scleractinian corals and many species of gorgonarians are common on the slope off Chiloé, below 500 m water depth. Finally, though the three-layer scheme for benthic zonation is the general rule, another type of chemosynthetic community, methane seep areas, has been reported from off Concepción at 700–1400 m water depth (Stuardo & Valdovinos 1988, Sellanes et al. 2004, Sellanes & Krylova 2005). In these reducing systems, C is fixed locally by both free-living and symbiotic chemosynthetic bacteria. Seepage areas thus provide a suitable environment for the development of singular communities consisting of sulphide oxidising bacteria (e.g., Beggiatoa), highly endemic endosymbiont-bearing clams (e.g., Vesicomyidae, Lucinidae, Thyasiridae and Solemyidae) and tubeworms (e.g., Lamellibrachia sp.). In addition, non-chemosymbiotic megafauna (e.g., crustaceans, gastropods, cephalopods, fish) are massively attracted to these deep-sea hot spots of biological activity. The attraction of these areas is due to both the abundance of locally produced organic material and the presence of authigenic carbonate reefs (generated by microbial and chemical processes), which are avidly colonised by a diverse benthic fauna (J. Sellanes unpublished data).

Latitudinal and bathymetric patterns In general, for the available data of macrofaunal species richness on the Chilean shelf, no clear latitudinal pattern emerges. Published reports of species numbers range from 18 to 56 species at northern Chile (~23°S, 15–65 m water depth) (Jaramillo et al. 1998), 42 to 85 species at Huasco (~28°S, 20–50 m water depth) (Lancellotti & Stotz 2004), 10 to 41 species at Concepción (~36°S, 15–65 m water depth) (Carrasco et al. 1988), and 24 to 34 species further south (~45°S) (D. Lancellotti & W. Stotz unpublished data). Highest abundances reported are for the shelf off Concepción (36,290–38,590 ind. m−2; Carrasco et al. 1988) and biomass values of almost 900 g wet wt m−2 are reported for south of Chiloé (D. Lancellotti & W. Stotz unpublished data). A crude comparison among the few available deeper studies (>100 m water depth) suggests higher macrofaunal standing stocks and abundances also at the shelf off central and southern areas, both for macro- (body size 0.3–2 cm) and megafauna (body size >2 cm), compared with northern Chile (Figure 11). Palma et al. (2005) reported macrofaunal biomass values for three transects covering a depth range from about 100 m to 2000 m at Antofagasta, Concepción and Chiloé (about 22°S, 36°S and 42°S, respectively). Though biomass trends with depth, beyond the OMZ, are in general unimodal at all transects, with higher values at intermediate depths and lowest within the 232

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OMZ and beyond 1350 m, average biomasses are lower off Antofagasta. Maximum values for this transect (6.9 g wet wt m−2) are reported at 518 m water depth, while values about an order of magnitude higher (60.7 g wet wt m−2) are reported off Concepción at 784 m depth. For southern Chile (~42°S) intermediate values (39.2 g wet wt m−2) are reported for a station located at 1250 m depth. This also indicates a deepening of macrofaunal biomass maxima with latitude (Figure 11). For the megafauna observed at the same three transects, though biomass values are not available, abundances in general exhibited a similar pattern to that previously explained for macrofaunal 233

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biomass (Palma et al. 2005). On average, pooling the data for the three transects, abundance (~500 ind. m−2) and species number (~25) peaks were located between 1000 and 1500 m depth.

Temporal patterns of variability in shelf communities As explained in previous sections of this review, the coastal zone off northern and central Chile is strongly influenced by seasonal wind-driven upwelling, giving rise to one of the areas with the highest PP rates known worldwide (Fossing et al. 1995, Daneri et al. 2000). Since water column oxygen conditions and sediment organic loadings fluctuate at both intra- (i.e., seasonal) and interannual scales (i.e., ENSO cycle), some degree of coupling with the dynamics of benthic communities is expected (Tomicic 1985, Arntz & Fahrbach 1991). This has been demonstrated for southern-central Chile (~36°S), where seasonal and interannual changes in upwelling intensity can lead to changes in bottom-water dissolved oxygen concentration, in the amount of OM reaching the bottom (Gutiérrez et al. 2000), in the quality and lability of deposited OM (Neira et al. 2001, Sellanes & Neira 2006) and in the sediment nitrogen fluxes (P. Muñoz et al. 2004b). During the last strong EN event (1997–1998), important insights were gained by examining the effects of changing environmental conditions on local bacterial, meiofaunal (Neira et al. 2001, Sellanes et al. 2003) and macrofaunal (Gutiérrez et al. 2000) communities off central Chile. The largest biomasses of the bacterial component have been observed after several years of upwelling-favourable conditions, which are associated with cold LN phases of the ENSO (V.A. Gallardo et al. unpublished data), while the bacterial biomass is effectively depressed during warm EN phases. A decreasing trend in macrofaunal density, as well as the presence of deeper-burrowing infauna, evolved toward the end of EN 1997–1998, mainly due to the decrease of the polychaete Paraprionospio pinnata (Gutiérrez et al. 2000). It appears that more oxygenated bottom waters and oxidised sediment during EN caused P. pinnata to fail in its summer recruitment. In addition, it is probable that increased competition and predation by other species have contributed to its decline. Indeed, it has been reported that during EN, many subtropical predators invade the coastal areas (Arntz et al. 1991), negatively affecting the surface-feeding polychaetes (Tarazona et al. 1996). In central Chile, P. pinnata recovered its numerical dominance only in summer 2003, i.e., 5 yr after the end of EN. Severe hypoxic and sulphidic conditions that developed during summer 2003 probably eliminated or precluded possible competitors and/or predators, triggering the explosive increase of the P. pinnata population during this period (Sellanes et al. 2007). In northern Chile (20–30°S) few datasets extending over at least 12 months are available from shallow benthic communities (20–80 m). For the time period 1990–1995, relatively high abundances of polychaetes have been reported from several stations in northern Chile (23°50′S) at water depths of 50–60 m (Carrasco 1997). This author remarked on the absence of a clear seasonal signal in abundance changes of the main polychaete species, and he suggested that the observed variations rather reflected long-term patterns. At a long-term monitoring station near 28°S, abundances of polychaetes were high in 1995 (Figure 12), comparable to those found by Carrasco (1997). High abundance, biomass and species diversity at 28°S were associated with the warm period 1993–1995 and followed by a strong decline in 1996, coincident with LN conditions, which continued during the EN 1997–1998 (Lancellotti 2002, D. Lancellotti & W. Stotz unpublished data). Gradual disappearance of spionids, as observed in Huasco in 1996 during LN (Figure 12), was also observed during the same time period in Iquique (20°S) between 9 and 30 m depth (Quiroga et al. 1999). In northern-central Chile, during EN events, increased wave activity and freshwater runoff are frequent, in contrast to calmer periods recorded during LN events. Turbulence and runoff, in a zone where rains and strong storms are uncommon, probably oxygenate the water column, resuspend OM and/or provide terrigenous material, thus favouring reproduction and settlement of macrobenthic species living below the zone of direct wave and sediment deposition impact (>20 m 234

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

6000

60 Upper sublittoral zone 28°S

50

4000

40

3000

30

2000

20

1000

10 0

0

60

6000 5000

Lower sublittoral zone (OMZ) 36°S

50

4000

40

3000

30

2000

20

1000

10

0

93 94 95 96 97 98 99 2000 01 02 03 04 05 Years

Species richness

Abundance (ind m−2)

5000

0

Figure 12 Temporal variations in the abundance of soft-bottom macrofauna in the upper sublittoral zone (northern Chile, 28°S) and the lower sublittoral zone (central Chile, 36°S); average abundance and species richness (S) are given; data from the upper littoral zone are taken by Smith-MacIntyre grab (1995–1996) or with sediment cores by divers (1997–2005) (D.A. Lancellotti & W. Stotz unpublished data); data from the lower sublittoral zone are taken with a multicorer, and several samples from each year were pooled, thus not allowing intra-annual variation to be seen (J. Sellanes unpublished data).

water depths). Effects of EN (and other) events on the temporal variability of benthic soft-bottom communities at present are difficult to evaluate because very few long-term datasets from benthic habitats are available from the HCS along the Chilean coast. It is herein suggested that long-term monitoring programmes should be implemented, sampling on a seasonal or bimontly basis, following examples in Peru (Tarazona et al. 2003, Arntz et al. 2006, Peña et al. 2006) and the Northern Hemisphere (Frid et al. 1996, Kroencke et al. 1998, Salen-Picard et al. 2002).

Intertidal and subtidal hard-bottom communities Hard bottoms along the coast of northern-central Chile are generally restricted to a narrow fringe extending from the intertidal zone to shallow sublittoral waters. The rock substratum is composed of rock of volcanic, granitic or sedimentary origin (Fariña et al. in press). The extensive rocky shores between 18°S and 40°S are mostly exposed to strong wave action, and they are only interrupted by short stretches of sandy beaches, which increase in extent toward the south (see Sandy beaches, p. 227, Figure 9), thereby leading to a wider separation of neighbouring hardbottom environments. Communities on intertidal and subtidal hard bottoms are dominated by macroalgae and suspension-feeding animals that form large patches (occasionally extending over to neighbouring soft bottoms) or belt-like stretches (running parallel to the shore at a certain tidal level). Most intertidal and subtidal hard bottoms are covered by one or a few dominating habitatforming organisms. Patches may persist for many years at a given location (Durán & Castilla 1989, Fernández et al. 2000, Vega et al. 2005), and they offer abundant microhabitat and food for associated organisms (Moreno & Jara 1984, Vásquez et al. 1984, Núñez & Vásquez 1987, Buschmann 1990, Vásquez 1993a, López & Stotz 1997, Sepúlveda et al. 2003a,b). Here these habitat-forming 235

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species, their spatial and geographic extent, their temporal dynamics and their role as ecosystem engineers (EEs) will be described. Further, it will be briefly discussed how the spatiotemporal distribution of these EEs may influence local biodiversity, population dynamics and trophic interactions in hard-bottom communities along the HCS.

Habitat-forming species on hard bottoms Large kelps (Lessonia nigrescens, L. trabeculata, Macrocystis integrifolia, M. pyrifera and Durvillaea antarctica), which grow abundantly in the low intertidal and shallow subtidal zone of the HCS, have compact and complex holdfasts that offer abundant and diverse microhabitats on the rock substratum itself. Their stipes and blades reach lengths of 2.5 m (Lessonia trabeculata) up to 30 m (Macrocystis pyrifera), and they have an important effect on local hydrodynamics because they act as wave breakers and slow down currents (Graham 2004). Smaller macroalgae with shorther thalli of 5–50 cm (such as Halopteris funicularis, Glossophora kunthii, Asparagopsis armata, Corallina officinalis and Gelidium chilense) form dense carpets (turfs) that offer primary and secondary microhabitats because they act as sediment traps retaining sand and shell fragments between their thalli and stolons (López & Stotz 1997, Kelaher & Castilla 2005). A diverse group of suspension-feeding EEs on hard bottoms include polychaetes (Phragmatopoma moerchi), barnacles (Austromegabalanus psittacus), bivalves (Perumytilus purpuratus, Semimytilus algosus, Choromytilus chorus and Aulacomya ater), and ascidians (Pyura chilensis and P. praeputialis). Their matrices reach heights of 2–40 cm, offering abundant space between living individuals (Cerda & Castilla 2001) or in remaining tubes or shells of dead individuals. Matrices of these suspension feeders may also retain considerable amounts of sediments (Prado & Castilla 2006), thereby providing secondary substratum for associated organisms. Habitat-forming species compete among themselves for space on hard-bottom substrata. Several studies indicate that mussels are competitively superior over barnacles (Navarrete & Castilla 1990, 2003, Tokeshi & Romero 1995a) and can also overgrow turf algae (Wieters 2005), ascidians may outcompete mussels (Castilla et al. 2004a) or barnacles (Valdivia et al. 2005), and large kelp may recruit in and then overgrow turf algae (Camus 1994a). Superior competitors themselves may be suppressed by predators (e.g., mussels and ascidians by gastropod and seastar predators; Paine et al. 1985, Castilla 1999, Castilla et al. 2004b) and grazers (Vásquez & Buschmann 1997, Buschmann et al. 2004a). Humans, acting as top predators by removing intermediate consumers, also strongly influence the structure of hard-bottom communities in northern and central Chile (Moreno et al. 1986, Castilla 1999). Furthermore, recruitment and growth of habitat-forming species are controlled by a variety of processes (e.g., upwelling) that drive larval and food supply (Navarrete et al. 2002, Nielsen & Navarrete 2004, Wieters 2005). Following disturbances and detachment, open space on hard bottoms is quickly recolonised, starting with ephemeral algae, which subsequently are replaced by large and long-lived turf or kelp algae and suspension feeders (Durán & Castilla 1989; Valdivia et al. 2005).

Spatial and temporal dynamics of ecosystem engineers The geographic range of most macroalgae and suspension-feeding EEs extends throughout northerncentral Chile (into Peru), but not all of them have a continuous latitudinal distribution (Table 3). All EEs from hard bottoms have pelagic dispersal stages, but in the case of the macroalgae the planktonic phase is of short duration (minutes to hours). Kelps of the genera Lessonia and Macrocystis extend from southern Chile to north of 18°S, but EN events may provoke large-scale extinctions in northern Chile (see also Kelp forests, 236

237

0–15 0–30 0 0–8 0–8 0–8 0–8 0–2 0 0 0 10–20 0–20 1–20 0–10

Macrocystis integrifolia

Macrocystis pyrifera

Durvillaea antarctica

Glossophora kunthii

Halopteris funicularis

Asparagopsis armata Corallina officinalis Gelidium chilense Phragmatopoma moerchi Perumytilus purpuratus

Semimytilus algosus

Aulacomya ater

Austromegabalanus psittacus

Pyura chilensis

Pyura praeputialis

E,S,P

E,S,P

E,S,P

E,S

E

E

S,P E,S,P E,S,P E E

E,S,P

E,S,P

E

S,P

S,P

E,S

2.5

0.6

0.2

0.2

0.2

0.1

0.12 0.15 0.06 0.2 0.05

0.1

0.25

15

30

10

6

<1 x

x

x x

x

x

1 to 10 x

x

x

x x x x x

x

x

x

x

x

10 to 1000 x

x

x

x

x

x

x

> 1000 x

x

x

x

x

x

x

<1 x

x

x

x

x

x

x x x

x

x

x

x

x

1 to 10 x

x

x

x

x

x

x x x

x

x

x

x

x

x

x x

x

x

10 to 1000

36,37

34,35

32,33

30,31

28,29

26,27

24,25

22,23

20,21

18,19

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x x x x x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

Information obtained from Hoffmann & Santelices 1997, Santelices 1989, Castilla et al. 2000, Zagal & Hermosilla 2001, Sepúlveda et al. 2003a,b and Hernández et al. 2001.

absent

rare

present, but patchy

common and widespread

temporally extinct

0

Lessonia nigrescens

Notes:

0–30

Lessonia trabeculata

> 1000

Patch persistence (years)

<1

Distance between patches (km) 1 to 10

Zonation Wave- Height of (m) exp. patches (m) Size of patches (m2) Latitudinal extent (°)

>10

Ecosystem engineer

38,39

Table 3 Main ecosystem engineer species from intertidal and subtidal hard bottoms along the Humboldt Current System of northern and central Chile

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p. 240ff.). Durvillaea antarctica does not extend further north than 32°S. Patches or belts formed in the low intertidal zone by Lessonia nigrescens and Durvillaea antarctica generally have extents of several square metres up to >100 m2. Subtidal kelp forests of Lessonia trabeculata and Macrocystis spp. may extend over >1000 m2, comprising some of the largest habitat patches formed by EEs. Distances between neighbouring patches are small in the case of Lessonia spp. and Durvillaea antarctica but individual forests of Macrocystis spp. can be separated by several hundred kilometres (see also Kelp forests, p. 240ff.). Persistence of patches over time may be favoured by recruitment of new sporophytes into existing kelp patches (Santelices & Ojeda 1984). Turf algae generally form smaller patches, with individual patches rarely exceeding an area of a few square metres. Corallina officinalis and Gelidium chilense (and other turf algae, e.g., Montemaria horridula, Rhodymenia skottsbergii) form long-lived patches in the intertidal zone (López & Stotz 1997, Vásquez & Vega 2004a, Wieters 2005), and distances between neighbouring patches are relatively small (Table 3). Glossophora kunthii, Halopteris funicularis, Asparagopsis armata (and others, including Corallina officinalis) occur mainly on shallow subtidal hard bottoms where they form patches of several square metres and, while thalli may disappear during the winter, the stolons persist over several years (Vásquez et al. 2001a). Patches may extend their size or renew thalli via asexual proliferation. The polychaete Phragmatopoma moerchi forms patches of several square metres in extent in the low intertidal and shallow subtidal zone in areas with a high supply of sand and shell fragments (Sepúlveda et al. 2003b). These patches persist over several years, but disappear if renewal is reduced, either due to low larval supply or high postsettlement mortality (Zamorano et al. 1995). The barnacle Austromegabalanus psittacus forms aggregations in the low intertidal and shallow subtidal zone; patches generally are small, rarely exceeding more than a few square metres in area. This species occurs all along the coast of northern and central Chile and little is known about the temporal dynamics of individual patches. Bivalves form extensive patches of a few square metres up to >1000 m2 in area in the mid-intertidal (Perumytilus purpuratus), low intertidal (Semimytilus algosus) and subtidal zones (Choromytilus chorus, Aulacomya ater). In the absence of predators patches can persist over many years (Durán & Castilla 1989), facilitated by regular recruitment into adult patches (Alvarado & Castilla 1996). Most bivalve species have a wide latitudinal distribution, but Perumytilus purpuratus and Aulacomya ater are almost entirely absent over an extensive area in northern Chile between 23°S and 32°S (Fernández et al. 2000, personal observations), which appears to be mainly due to limited larval supply in that region (for Perumytilus purpuratus see Navarrete et al. 2005). The ascidian Pyura chilensis occurs in small patches in the shallow subtidal zone (e.g., Vásquez & Vega 2004b), while the congener P. praeputialis forms extensive belts in the low intertidal zone (Table 3). Patches of P. chilensis persist over many years at the same location (personal observations), but little is known about the population dynamics within patches. In P. praeputialis, recruitment may be most successful in the vicinity of adults (Clarke et al. 1999), thereby favouring the long-term persistence of patches. While P. chilensis has a wide geographic distribution, P. praeputialis is restricted to a small range of 70 km along the Bay of Antofagasta (23°S) in northern Chile (Castilla et al. 2000).

Macrofauna associated with ecosystem engineers on hard bottoms A wide diversity of organisms is associated with habitat-forming species on hard bottoms of northern and central Chile. Highest species richness is found in the kelp holdfasts, intermediate numbers of associated species are reported from ascidian and bivalve reefs, and turf algae harbour fewest species of associated macrofauna (Figure 13A). This relationship appears to be related to

238

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

140

120

120

100

100

80

80

60 60 40

40

Pyrua praeputialis

Perumytilus purpuratus

Perumytilus purpuratus

Turf algae

Phragmatopoma moerchi

Gelidium chilense

Corallina officinalis

Halopteris funicularis

Durvillaea antarctica

Kelps

Macrocystis integrifolia

0

Macrocystis integrifolia

0

Lessonia nigrescens

20

Lessonia trabeculata

20

1 to 10 10 to 1000 >1000 Patch size (m2) B

Suspension feeders

A

Figure 13 (A) Species richness of macroinvertebrates associated with habitat-forming macroalgae or suspension feeders from intertidal and subtidal hard bottoms of the northern and central coast of Chile; for reasons of comparability only studies that reported at least seven phyla of associated macrofauna were considered. (B) Average species richness in biotic habitats of different patch sizes; information obtained from López & Stotz 1997, Gelcich 1999, Godoy 2000, Thiel & Vásquez 2000, Cáceres 2001, Cerda & Castilla 2001, Hernández et al. 2001, Vásquez et al. 2001b, Thiel & Ullrich 2002, Sepúlveda et al. 2003a,b, Prado & Castilla 2006.

the fact that kelp beds and ascidian and bivalve reefs have a comparatively large spatial extent while patches of turf algae rarely cover more than a few square metres (Figure 13B). A positive relationship between patch size and number of associated species has been revealed for most habitatforming species (Vásquez & Santelices 1984, Villouta & Santelices 1984, Thiel & Vásquez 2000, Hernández et al. 2001, Sepúlveda et al. 2003a,b). Several macrofauna species have been reported from a variety of different biotic habitats. Of 251 species identified from biotic substrata (see references in Figure 13), 11.6% have been found in all three types of main biotic habitats (kelps, turf algae and suspension feeder reefs), 23.5% have been found in two types and 64.9% are only reported from one type of habitat. It must be emphasised that so far no single study has compared the associated fauna among the three main types of EEs, and there is little indication that there are habitat specialists that only occur in one type of biotic substratum. For example, Hernández et al. (2001) emphasise that several of the polychaetes found in patches of the barnacle Austromegabalanus psittacus also occur in other habitats. Similarly, Sepúlveda et al. (2003b) mention that many species from surrounding habitats associate with the reef-building polychaetes Phragmatopoma moerchi. They also emphasise that these biotic substrata may serve as recruitment habitat for some organisms. Similar observations led López & Stotz (1997), who found juvenile stages of many crustaceans and molluscs in Corallina officinalis, to

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speak of a ‘transitory fauna’ in biotic substrata (see also Vásquez & Santelices 1984, Cerda & Castilla 2001). EEs may thus favour many mobile organisms that temporarily find shelter in these habitats (e.g., Vásquez et al. 2001b). In this context, Castilla et al. (2004b) reported that the intertidal ascidian Pyura praeputialis facilitates the extension of mobile macrofauna from the subtidal into the mid-intertidal zone, thereby enhancing local species richness. The main functional groups of the organisms associated with biotic habitats are suspension feeders (32.4% of all species), grazers (25.2%) and predators (23.4%) (H. Bastias & M. Thiel unpublished data). Vásquez et al. (2001b) found very similar proportions of functional groups both in kelp holdfasts and on the surrounding hard bottoms. By offering structural protection, EEs are considered to mediate species interactions and buffer the effect of physical stress, often favouring suspension feeders (Wieters 2005, Valdivia & Thiel 2006). While the role of EEs in sustaining and promoting local biodiversity on intertidal and subtidal hard bottoms has been elucidated in numerous studies during the past decades (Vásquez & Santelices 1984, Villouta & Santelices 1984, Cerda & Castilla 2001, Sepúlveda et al. 2003a,b, Castilla et al. 2004b, Prado & Castilla 2006), relatively little is known about their trophic role on exposed rocky shores of northern-central Chile. Several studies have underlined the role of kelp forests as contributors of algal biomass to neighbouring habitats (Rodríguez 2003) and as feeding grounds for fish predators that consume understory algae and kelps (Angel & Ojeda 2001) or associated fauna (Núñez & Vásquez 1987, Palma & Ojeda 2002). Fish consumers are known to play an important role in kelp food webs of northern-central Chile (Angel & Ojeda 2001, Fariña et al. in press) but little is known about the food webs in other EEs. While most studies acknowledge the importance of EEs as habitat for associated organisms, their trophic efficiency (uptake of nutrients and suspended matter, release of dissolved and particulate organic matter) and the role of associated macrofauna in the tropho-dynamics of communities on intertidal and subtidal hard bottoms have not been thoroughly studied (see also Graham et al. 2007). The high biomass and diverse assemblage of associated consumers suggest that EEs are energetic power plants that concentrate and convert food resources in a similar way to kelp, seagrass or suspension feeder reefs in other parts of the world (e.g., Asmus & Asmus 1991, Lemmens et al. 1996, Wild et al. 2004).

Kelp forests Giant kelp dominate shallow, subtidal rocky-bottom areas in temperate and cold seas down to a depth of ~40 m (Dayton et al. 1984, Harrold & Pearse 1987, Vásquez 1992, Graham et al. 2007). Kelp distribution from south Peru to central Chile is as follows: (1) intertidal rocky areas are dominated by Lessonia nigrescens, which forms belts along exposed coasts; (2) rocky subtidal environments are dominated by Lessonia trabeculata until 40 m in depth; (3) Macrocystis integrifolia forms shallow kelp beds from the intertidal zone to depths of about 15 m. In southern-central Chile, these species are gradually replaced by Durvillaea antarctica, which dominates the intertidal zone in wave-exposed areas (Hoffmann & Santelices 1997), and in subtidal areas by Macrocystis pyrifera, which occurs in both wave-exposed and –protected habitats (Buschmann et al. 2006a). While the two species from the genus Lessonia have an almost-continuous distribution along the entire Chilean continental coast, Macrocystis integrifolia has a fragmented distribution, forming patchy populations in northern Chile. In this zone Lessonia trabeculata and Macrocystis integrifolia coexist, but mixed kelp populations have segregated patterns of bathymetric distribution, M. integrifolia being more abundant in shallow areas (Vega et al. 2005). Local populations may vary from hundreds of metres to hundreds of kilometres in extent. The observed distribution patterns are the result of complex life-history strategies that interact with environmental factors such as spatial and temporal variation in water movement, nutrient availability and temperature (Buschmann et al. 2004b, V. Muñoz et al. 2004, Vega et al. 2005). 240

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The kelp forest community Kelp communities are highly productive (Dayton 1985), and they harbour a high diversity and abundance of invertebrates and fishes. Kelps, especially their holdfasts, constitute feeding areas, refuges against predation and bottom currents, spawning, settlement areas and nursery sites (Vásquez & Santelices 1984, Vásquez et al. 2001c, Vásquez & Vega 2005). Below the kelp canopy a wide diversity of turf algae exists, including several Corallinales, Asparagopsis armata, Halopteris paniculata and Gelidium spp.; several species of barnacles and other sessile invertebrates (Pyura chilensis, Phragmatopoma moerchi, Aulacomya ater) are also part of the associated species sheltered by the kelp canopy (Vásquez et al. 2001b,c, Vásquez & Vega 2004a). In contrast to the Northern Hemisphere, no large predators have been reported for southeastern Pacific kelp beds (Graham et al. 2007). Instead, invertebrate predators such as the muricid snail Concholepas concholepas, seastars (Meyenaster gelatinosus, Stichaster striatus, Heliaster helianthus and Luidia magellanica), and intermediate-size coastal fishes (Cheilodactylus variegatus, Semicossyphus maculatus and Pinguipes chilensis) dominate the predator guild in kelp forests from northern-central Chile (Vásquez 1993b, Vásquez et al. 1998, 2006). These predators feed on a diverse guild of herbivores, including sea urchins (Tetrapygus niger and Loxechinus albus), gastropods (Tegula spp. and Fissurella spp.), as well as fishes (Aplodactylus punctatus, Girella laevifrons and Kyphosus analogus) (e.g., Medina et al. 2004). These herbivore species graze on kelp and associated algae, regulating their abundance and distribution (Vásquez & Buschmann 1997, Vega et al. 2005, Vásquez et al. 2006). Marine mammals widely distributed in the coastal zone of the HCS, such as sea lions Otaria flavescens and sea otters Lontra felina, also use kelp beds as feeding areas.

Population dynamics and spatial distribution of kelps in northern-central Chile The kelp species from northern and central Chile belong to the Laminariales, which have a complex life cycle with two morphologically different stages: one conspicuous stage, recognisable as kelp that produces spores (the sporophytes), and a microscopic stage comprising independent female and male plants (the gametophytes) that lead a hidden life in the benthos. Sporophytes are the product of gametic reproduction, which is triggered by environmental factors (temperature, irradiance, photoperiod, and nutrient concentrations). The sporophytes themselves are reproductive year-round, but peak spore release has been observed during winter. Since spore survival in Laminariales is short, the dispersal range of kelps is generally assumed to be quite reduced (Graham et al. 2007); if spores do not settle within a relatively short period they die (Santelices 1990a). However, spores may survive in the guts of different herbivores (Santelices & Correa 1985, Santelices & Payá 1989) or as filaments in darkness (Santelices et al. 2002). Furthermore, fertile floating plants may act as spore carriers and thereby contribute to dispersal (Macaya et al. 2005). Juvenile sporophytes of Lessonia recruit onto hard-bottom substrata during late winter–spring, and in the field are capable of producing spores after 6–8 months (Santelices & Ojeda 1984; see review by Edding et al. 1994). Interference by adult plants inhibits the intertidal recruitment of juvenile L. nigrescens in exposed habitats. Nevertheless, water movements produce whiplash effects (sensu Dayton et al. 1984) that gives protection against grazers, thereby promoting successful recruitment of sporophytes (Santelices & Ojeda 1984). In subtidal habitats abundance of grazers, currents and reproductive behaviour of two species of elasmobranchs (Schroederichthys chilensis and Psammobatis scobina) affect Lessonia trabeculata populations. Grazing modifies algal morphology, producing two morphotypes: shrub-like and tree-like morphs. Water movement affects these differentially and generates higher mortality on tree-like morphs (Vásquez 1992). Short distances between plants (or high densities) reduce the access of grazers to the holdfasts. The 241

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whiplash effect of fronds and stipes pushes herbivores away from the plants, reducing grazing pressure. On the other hand, spawning of egg cases of elasmobranchs on L. trabeculata ties the stipes together, thereby reducing the whiplash effect and thus permitting grazers to approach kelp plants. Additionally, this ‘tie effect’ modifies plant shape toward the tree-like morph, and plants are more easily dislodged by water movement (Vásquez 1992). Longevity of kelps from northern Chile in the field is not well known since they do not show any evident age-related structure. Nevertheless, individual Lessonia plants can survive in the field for as long as 5 yr (J.A. Vásquez personal observations), and Macrocystis integrifolia has been reported as a perennial species in northern Chile (Buschmann et al. 2004b). Several factors generate significant biomass loss in the field: grazing pressure, wave impact, and spore release, which takes place mainly during summer (Santelices & Ojeda 1984, Edding et al. 1994). Lessonia and Macrocystis populations in northern-central Chile grow throughout the year but exhibit growth peaks during spring–summer (Buschmann et al. 2004b, Tala et al. 2004). Growth patterns are modified by wave impact, quantity and quality of light, water temperature and nutrient concentration (Buschmann et al. 2004b, Vega 2005). Local factors such as intraspecific interactions (Santelices & Ojeda 1984), herbivory (Vásquez & Buschmann 1997, Vásquez et al. 2006) and coastal upwelling events (González et al. 1998, Vásquez et al. 1998) can modify seasonal patterns of abundance and distribution (see also Graham et al. 2007). Large-scale phenomena such as ENSO produce interannual variability in abundance and could eventually generate local extinctions, as observed after the EN events of 1982–1983 and 1997–1998 (Soto 1985, Tomicic 1985, Vega 2005, Vásquez et al. 2006). Major impacts of EN were observed in kelp beds from lower latitudes (18–21°S). For example, a kelp bed occupying an area of ~40 ha at 18°S during the 1970s (IFOP 1977) disappeared as a consequence of EN 1982–1983 (Soto 1985) and has not recovered since. Similarly, during EN 1997–1998, the density of adult sporophytes on subtidal hard bottoms at 21°S decreased rapidly and linearly with increasing positive thermal anomalies (Figure 14). Six months later the site remained completely devoid of adult sporophytes, and no recolonisation occurred in the subtidal zone during the study period. In areas south of 23°S positive thermal anomalies registered during EN 1997–1998 had only limited effects on kelp beds (Figure 14). As a result, the spatiotemporal abundance patterns of M. integrifolia sporophytes in northern-central Chile is highly variable (Figure 14).

Kelp conservation and human activities Many of the diverse kelp-associated species have significant socioeconomic importance for human populations along the coast in north-central Chile and have been subject to harvesting by local human communities since pre-Columbian times (Jerardino et al. 1992, Vásquez et al. 1996). Spatial and temporal dynamics of kelp beds are significantly affected by anthropogenic impacts produced by both intense harvesting and severe pollution with organic as well as mining waste (Faugeron et al. 2005; Vásquez & Vega 2005). Lessonia nigrescens, L. trabeculata and Macrocystis integrifolia are commercially exploited between 18°S and 32°S. These species account for >95% of landings of macroalgae and basically are used for alginic acid extraction. Until 2002, collected biomass in dry weight (dry wt) amounted to ~200,000 t, almost exclusively based on stranded kelps, resulting from natural mortality of plants with holdfasts that are weakened by grazing and then detached by strong bottom currents and waves. Since 2003, however, due to international needs for raw (dry) materials and also due to increasing demands for fresh algae (to sustain aquaculture of herbivorous invertebrates in northern Chile), harvesting of natural kelp increased to ~300,000 t dry wt per year. This has led to the recent implementation of new administrative rules in order to mitigate the impact on natural kelp populations. Regulations aim at the establishment of a sustainable kelp fishery, applying the following strategies: (1) harvest management (Vásquez 1995, 1999, 2006), (2) stock 242

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Intertidal kelp

5

San Marcos (21°S)

4

Camarones (18°S)

3

1998 1

2

−1

1

−3

0 5

−5 5

4

1996

1997

Constitución (23°S)

1

2

−1

1

−3

0 5

−5 5

Playa Blanca (28°S)

3

3

1

2

−1

1

−3

0

−5 5

5 4

Los Choros (29°S)

3

3

1

2

−1

1

−3

0

−5 5

5 4

San Lorenzo (30°S)

3

3

1

2

−1

1

−3

0

−5 5

5 4

2000

3

3

4

1999

5 3 1 −1 −3 −5

Thermal anomalies (°C)

Abundance of adult sporophytes (ind m−2)

5 4 3 2 1 0

Thermal anomalies (°C)

Subtidal kelp

Abundance of adult sporophytes (ind m−2)

THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE

Los Vilos (32°S)

3

3

1

2

−1

1

−3 −5

0 1996

1997

1998

1999

2000

Figure 14 Temporal variation (between 1996 and 2000) of abundances of adult sporophytes of M. integrifolia (●) and thermal anomalies estimated in situ (line) over a latitudinal gradient in northern Chile. Note: At San Marcos, an intertidal kelp population appeared after the El Niño event (▫), while the subtidal kelp bed did not recover. At Camarones (top) no sporophytes were observed during the study period. (Modified from Vega 2005)

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enhancement (Vásquez & Tala 1995), (3) cultivation (Edding & Tala 2003, Westermeier et al. 2006, Gutierrez et al. 2006), and (4) conservation programmes including Marine Protected Areas (MPAs; CONAMA 2006). Considering the high variability of kelp populations in northern Chile, the limited dispersal capability of Lessonia species, and in particular the patchy distribution of beds of Macrocystis integrifolia, sustainable exploitation of natural kelp forests requires integrated management plans with continuous monitoring of standing stocks.

Export and import processes within the HCS Kelp forests, as other EEs, strongly influence trophic fluxes in benthic environments (e.g., Graham et al. 2007). In the HCS, some of the most important trophic connections occur in the vertical direction, such as dissolved nutrients released from sediments into the water column, upwelling of nutrient-rich waters from subsurface layers to the sea surface, or POM sinking from the euphotic zone toward deeper water layers and finally to the sea floor. In addition, there exist numerous types of horizontal transfer of particulate or dissolved components between the marine and the terrestrial realm, between the benthic and the pelagic environment, or between benthic habitats. In the following section the importance, intensity and frequency of these exchange processes in the HCS of northern-central Chile are considered, with a focus on coastal habitats.

Exchange between realms Exchange between the marine and the terrestrial environment occurs in both directions. Flux of materials toward the sea is via rivers, which (due to limited freshwater flow) is usually only of minor importance between 18°S and 30°S. In some areas in northern-central Chile, dissolved and solid components from human activities are continuously supplied to the marine environment, impacting local intertidal and subtidal communities (Vásquez et al. 1999, Gutiérrez et al. 2000, Lancellotti & Stotz 2004). During certain time periods (EN events or summer rains in the Andes highlands), river flow increases dramatically, transporting mainly sediments but also large quantities of terrestrial vegetation to nearshore coastal waters (Vásquez et al. 2001a). Shallow subtidal habitats along the coast of northern-central Chile are infrequently impacted by these mud flows (Miranda 2001, Vásquez et al. 2001a, Lancellotti & Stotz 2004), and it is considered likely that these impacts occur in parallel over a large geographic range. In the reverse direction, several natural exchange mechanisms are relevant in the HCS, namely, energy transfer by seabirds and marine mammals from offshore waters to coastal habitats, which occurs in a highly concentrated manner on breeding or roosting sites. Additionally, some terrestrial vertebrates (rodents, lizards, songbirds) from coastal environments forage along the drift line or in the intertidal zone (Navarrete & Castilla 1993, Fariña et al. 2003a, Sabat et al. 2003). Most of these organisms maintain relatively stable territories along the coastline, and thus material transfer from the intertidal to the upper supralittoral zone is dispersed in space, but relatively continuous in time. The same process has been reported from coastal habitats in California, where populations of insects, spiders, lizards, rodents and coyotes are mainly maintained and modulated by the food subsidy from the marine environment (Polis & Hurd 1995, 1996, Polis et al. 1997). Under certain conditions, marine resources are also transported toward the shore without the aid of biotic agents (invertebrate or vertebrate consumers defecating on land). Mortality of seabirds and marine mammals during EN events results in large numbers of animal carcasses accumulating on local beaches (e.g., Guppy 1906, Arntz & Fahrbach 1991). Similarly, during storm events, algae or benthic invertebrates are detached and cast onto the shore (González et al. 2001). These food bounties attract large numbers of terrestrial vertebrate scavengers but since supply is highly infrequent (e.g., Moore 2002), no quantitative estimates of material transfer during these events are available. 244

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Fisheries also contribute to the transfer of OM from the marine toward the terrestrial realm. This not only includes direct (extraction) but also indirect forms of transfer, such as by scavenging seabirds around fishing vessels at sea (Weichler et al. 2004) or in fishing ports (Ludynia et al. 2005). Populations of kelp gulls (Larus dominicanus) near main population centres in northern-central Chile depend to a large extent on these human-derived food sources, and they then distribute remains in terrestrial environments (Ludynia et al. 2005).

Exchange between environments There is a wide range of exchange processes between the pelagic and the benthic environments. This includes, for example, supply of POM from the water column to soft bottoms where microand macroorganisms remineralise this POM, returning dissolved materials to the water column (Graf 1989, Marcus & Boero 1998, Dunton et al. 2005). Suspension feeders are important agents, which aid in transfer of suspended material (e.g., phytoplankton and kelp detritus) from the water column to the benthic system (Wolff & Alarcón 1993). In some of the bays of northern-central Chile dense stocks of natural or culture beds may significantly affect these fluxes (Uribe & Blanco 2001, Avendaño & Cantillánez 2005). The intensity and direction of transfer can be affected by regional discontinuities in the oceanographic conditions (e.g., distance from upwelling areas), which influence the transport and flux of POM and nutrients (Graco et al. 2006). These processes are also exposed to large-scale temporal variations in oceanographic conditions (e.g., ENSO cycles) (Farías et al. 2004, P. Muñoz et al. 2004b). Fisheries in small fishing ports contribute POM in the form of fish remains to soft bottoms (Sahli 2006). On hard bottoms, macroalgae and suspension feeders take up nutrients and suspended POM from the water column, returning algal remains, repackaged faeces or dissolved excretions to the water column. Most large kelps are continuously shedding senescent parts (e.g., Tala & Edding 2005). These authors estimated that annual export of shed plant detritus from a kelp forest of Lessonia trabeculata may amount to 18 kg wet wt m−2. What proportion of this detritus remains suspended in the water column or sinks immediately to the bottom is not known at present. Kelp productivity shows some seasonal variation, but kelp detritus is supplied throughout the year, at least in northern-central Chile (Tala & Edding 2005). This suspended kelp detritus may also sustain the large proportion of suspension-feeding organisms on intertidal and subtidal hard bottoms (see also Intertidal and subtidal hard-bottom communities, p. 235ff. and Bustamante & Branch 1996). Little is known about the role of DOC released by kelp forests. It enhances bacterial populations (Delille et al. 1997) and contributes to foam lines at the sea surface, which are thought to play a role in propagule dispersal and survival (Meneses 1993, Shanks et al. 2003a). Foam lines are frequently observed along the coast of northern-central Chile. Fish consumers also have an important role in energy transfer from benthic toward pelagic environments (Angel & Ojeda 2001). This transfer includes all feeding guilds of fishes from herbivores to omnivores and carnivores (Angel & Ojeda 2001). Studies of trophic coupling between hard bottoms and the water column have mainly focused on kelp forests and little is known about these trophic interactions in other hard-bottom communities (see also Intertidal and subtidal hardbottom communities, p. 235ff.).

Exchange between benthic habitats Exchange between neighbouring communities (NCs) occurs throughout the shallow subtidal zone. The form of materials exchanged between NCs and the direction of transport can be highly variable. Algal detritus exported from kelp forests contributes an important food source for animal communities on intertidal hard bottoms (Bustamante et al. 1995, Bustamante & Branch 1996, Rodríguez-Graña 245

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Table 4 Different types of material transfer between communities within the HCS of northern Chile. Distances of transport increase with increasing length of line, intensity of transfer increases with increasing size, and frequency augments with increasing number of dots. Material type

Agent

Distance

Intensity

Frequency

●

●●●●●

Lancellotti & Stotz 2004

●

●●●●●

Vásquez et al. 1999 Vásquez et al. 2000



●



●

●

●●●●●

●

●●●●●

●

●●●

Uribe & Blanco 2001

●

●●●

Bustamante & Branch 1996 Tala & Edding 2005

●

●●●●●

●

●●●●●

Between Realms TERRESTRIAL (T) –MARINE (M) Particulate inorganic matter River (T to M) (mining discharge) Dissolved metals River (T to M) (mining discharge) Particulate inorganic matter River (T to M) (river floods) Organic matter Currents (carcasses and algae) Organic matter Terrestrial vertebrates (M to T) Nutrients and dead biomass Seabirds (food) (M to T) Between Environments PELAGIC-BENTHIC POM & phytoplankton Suspension feeders POM (algal detritus)

Currents

Between Benthic Habitats NEIGHBOURING COMMUNITIES POM (detached algae) Currents Shell remains

Waves and currents

Reference

Miranda 2001 Guppy 1906 Arntz & Fahrbach 1991 Navarrete & Castilla 1993 Fariña et al. 2003a Sabat et al. 2003 Sanchez-Pinero & Polis 2000 Ludynia et al. 2005

Rodríguez 2003 Tala & Edding 2005 Bomkamp et al. 2004 Personal observations

Note: POM = particulate organic matter.

& Castro 2003). The transfer of large amounts of algal fragments from subtidal kelp forests toward the shore has been considered as a principal food source, structuring and maintaining macrofauna communities on sandy beaches (Colombini et al. 2000, Dugan et al. 2003). Transport of detached kelp plants or parts to aggregations of sea urchins in tide pools is considered to be an important trophic subsidy for these grazers (Rodríguez 2003). Arrival of kelp in the intertidal zone of northerncentral Chile continues throughout the year, but highest quantities arrive from late spring until early autumn, also depending on the proximity to source habitats (Rodríguez 2003). The importance of kelp transfer to deeper subtidal habitats (for the Californian coast see, e.g., Kim 1992, Harrold et al. 1998, Vetter & Dayton 1998, 1999) or to the rocky subtidal zone has not been evaluated in the HCS, but given that the main kelp species are non-buoyant (Lessonia spp.), it is assumed that large fractions of detached kelp may be accumulating on deeper or wave-sheltered subtidal bottoms. In addition to kelp detritus, hard-bottom communities also export large quantities of shell remains to NCs (Bomkamp et al. 2004). Along the coast of northern-central Chile, shell gravel is relatively common near exposed headlands (Ramorino & Muñiz 1970). These sediments are mainly composed of shell fragments from barnacles, sea urchins and bivalves, but source habitats, fluxes of these materials from hard bottoms to sediments and the relevance of local hydrography have not been examined.

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Frequency and intensity of exchange processes Exchange of nutrients or particulate matter among marine communities in northern-central Chile varies in frequency and intensity (Table 4). Some of the most important and frequent exchange processes in northern Chile occur in the vertical direction (sedimentation of POM, release of nutrients into the water column, upwelling of nutrient-rich waters). Horizontal transfer processes appear to be most intense and frequent in coastal habitats, such as, for example, supply of kelp detritus to NCs. In contrast to this relatively continuous exchange of material, depositions of terrestrial sediments to coastal waters or of dead plants and animals to local beaches appear to be some of the least frequent and unpredictable transfer events. When these events occur, their intensity is often so high (e.g., Arntz 1986) that they exceed the escape or ingestion capacity of the organisms in the receiving habitats. This can result in the destruction of local communities and the incorporation of materials to deeper sediment layers. Transfer of marine-derived materials in colonies of seabirds and sea lions is also very intense (and frequent), but in northern-central Chile cannot be utilised by terrestrial organisms due to lack of water. A similar effect is observed in the water column and sediments of the OMZ where recycling processes are suppressed due to the lack of oxygen (Graco et al. 2006). Thus the intensity of the fluxes, which overcome the recycling capacity of receiving communities, may favour the long-term storage of POM not only in shelf sediments (H.E. González et al. 2004a), but also in terrestrial, intertidal and subtidal habitats of the HCS (islands with seabird and sea lion colonies, sandy beaches, subtidal kelp accumulations). It appears to be important to estimate carbon and nutrient export (and storage) not only to shelf sediments but also to terrestrial soils and intertidal and subtidal bottoms along the HCS.

Propagule supply, dispersal and recruitment variability Exchange of biological information (i.e., gene flow) depends on the dispersal ability of the organisms in question. Dispersal of individuals determines the scale at which species interact with the physical environment, the nature and consequences of the interaction with other species, the way in which they respond to perturbations and ultimately the selective forces and rates to evolve, speciate or go extinct. Because in most benthic habitats there is a predominance of species with complex life cycles, which include a free-swimming larval stage (Thorson 1950, Strathmann 1990), high dispersal capabilities are intuitively associated with most marine organisms. However, this is not a rule since coexisting with species with planktonic larvae there always exists a myriad of species with very limited dispersal potential, such as most macroalgae and direct developers or brooding species (Reed et al. 1992, Kinlan & Gaines 2003, Shanks et al. 2003b). Moreover and to further complicate things, many species use rafting as an alternative method of long-distance dispersal (Santelices 1990a, Thiel & Gutow 2005). Despite the early realisation of the high diversity of life cycles found in every marine habitat, the ecological consequences of such diversity on species interactions and on the structure and dynamics of benthic communities are only beginning to be unveiled (Kinlan & Gaines 2003, Leibold et al. 2004, Velázquez et al. 2005).

Methodological approaches to the study of dispersal The study of dispersal in the ocean is fraught with methodological problems imposed by the difficulty of following the usually microscopic propagules over extended time. Indirect methods to estimate aspects of dispersal have been developed. For instance, the use of highly variable neutral DNA markers offers an unprecedented opportunity to estimate realised dispersal distances (Palumbi

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1995, Kinlan & Gaines 2003, Palumbi 2003, Sotka & Palumbi 2006). Similarly, trace element microchemistry (elemental fingerprinting) (Swearer et al. 1999, DiBacco & Levin 2000, Zacherl et al. 2003) or stable isotope ratios (Herzka et al. 2002, Levin 2006) hold promise for identifying larval origin under specific environmental conditions. However, these techniques do not yet provide a quantitative measure of the fate of all propagules released from a focal location (i.e., the ‘dispersal kernel’). Therefore, spatially explicit connectivity among local populations, the type of information needed regarding the location of MPAs (Botsford et al. 1994, Lockwood et al. 2002, Kaplan 2006), remains tractable only through the combination of biophysical models linking larval attributes with advection-diffusion physical processes (Marín & Moreno 2002, Largier 2003, Siegel et al. 2003, Guizien et al. 2006, Kaplan 2006, Levin 2006, Aiken et al. 2007).

Studies of dispersal in HCS Studies of dispersal within the HCS are scarce at best. Santelices (1990a) provides a review of dispersal in marine seaweeds and points out that most information comes from laboratory studies conducted under idealised hydrographic conditions or from rather anecdotal evidence of colonisation of new habitats. Studies conducted by incubating seawater samples have demonstrated the existence of a multispecific ‘spore cloud’ which is present year-round in coastal waters of central Chile (Hoffmann & Ugarte 1985, Hoffmann 1987). These studies showed the patchy and temporally variable nature of the spore cloud, but the dispersal distances and mechanisms involved are unclear. Considering the small size of spores (5–150 µm) and their short duration (a few hours, but it can be up to few days; Santelices, 1990a), stochastic turbulence diffusion probably plays a major role in shaping the dispersal kernels in algal dispersal. Nearshore advective currents within the dispersal scale of spores (e.g., tidal currents, breaking waves, internal tidal bores) cannot be ruled out, however. Recent studies by Bobadilla & Santelices (2005) conducted by sampling the water column with a semi-automated sampling device (Bobadilla & Santelices 2004), illustrate the great temporal variability in multispecific dispersal kernels for major algal groups and dispersal distances exceeding 100 m. The most direct studies of dispersal of invertebrates in the HCS are restricted to species with short larval duration, such as tunicates (Castilla et al. 2002a,b, 2004a). These studies sampled larval distribution at distances from a unique adult population source. Quantitative aspects of dispersal for species with long-lived larval stages are virtually unknown for any invertebrate or coastal fish species in the HCS. Several physical processes that can increase offshore and alongshore advection, or instead increase retention of larvae near shore, have been described for the coast of Chile, such as upwelling filaments, cyclonic circulation in embayments, topographically controlled eddies and upwelling shadows and traps (Vargas et al. 1997, Marín et al. 2001, Castilla et al. 2002a, Escribano et al. 2002, Wieters et al. 2003, Narváez et al. 2004). These features undoubtedly influence dispersal of coastal species, potentially increasing self-recruitment (Swearer et al. 2002), but their effect on connectivity among adult populations of any species is hard to demonstrate. A few high-resolution 3-dimensional numerical models of currents in the coastal ocean have been developed and tested against physical data for different sections of the coast of Chile (Mesías et al. 2001, Aiken et al. 2007). Coupled with Lagrangian larval-tracking techniques these biophysical models can generate testable hypotheses about dispersal and connectivity in real biological systems (e.g., Aiken et al. 2007). There is an urgent requirement to develop highly variable, neutral molecular markers such as microsatellites for algal and invertebrate species inhabiting the HCS system to improve the ability to infer dispersal distances over ecological timescales and to test hypotheses about connectivity (see also Population connectivity, p. 252ff.) derived from theoretical models.

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Settlement studies in the HSC A more tractable and directly related problem is the settlement and recruitment of species to a given habitat. Settlement is the process through which a spore or larva makes permanent contact with the benthic habitat (Keough & Downes 1982). Since most adults of benthic organisms are sessile or have limited movement, settlement marks the end of the effective dispersal phase. For brooding organisms with mobile adults or those that use rafting as a secondary dispersal mechanism this is of course not the case (Thiel & Haye 2006). Recruitment is the input of new individuals to the benthic population measured at some arbitrary time after settlement. Therefore, while settlement is expected to reflect the arrival or supply of propagules, recruitment can be substantially modified by postsettlement mortality. Of the considerable number of studies of supply ecology conducted in the HCS over the past decades, very few have come close to measuring settlement (Hoffmann & Ugarte 1985, Hoffmann 1987, Moreno et al. 1993a, 1998, Martínez & Navarrete 2002, Vargas et al. 2004, Lagos et al. 2005, Narváez et al. 2006), and most have actually examined recruitment at varying time intervals after settlement. The paucity of studies of settlement of marine algae, due largely to the enormous difficulties of identifying sporelings to species level (Hoffmann 1987, Santelices 1990a), has not permitted the identification of mechanisms involved in algal settlement patterns. On the other hand, using intertidal barnacles, mussels and several gastropod species as model organisms, a few larval transport mechanisms have been demonstrated in the central and southern HCS. At the locality of Las Cruces in central Chile, which has been characterised as an upwelling shadow (Kaplan et al. 2003, Wieters et al. 2003, Narváez et al. 2004), the onshore daily settlement of several invertebrate species is associated with conditions that favour the occurrence of internal tidal bores, which appear to be common in the area when the water column is well stratified (Vargas et al. 2004). These results suggest that, for a number of intertidal invertebrates, internal tidal bores (Pineda 1991, 1994a) can be an important mechanism of onshore transport. In contrast with results at some sites in the California upwelling ecosystem (e.g., Farrell et al. 1991, Wing et al. 1995a), studies at Las Cruces showed that settlement of invertebrates was not directly associated with upwelling-relaxation events, which occur throughout spring and summer over synoptic timescales. The suggestion here is not that the upwelling-relaxation transport model (e.g., Roughgarden et al. 1988, 1991, Wing et al. 1995a,b) plays no role in settlement and recruitment in central Chile, but rather that at Las Cruces larval transport toward the shore does not seem to be dominated by these mechanisms. Indeed, spatially intensive studies over a region of about 120 km around Las Cruces showed a clear mesoscale spatial pattern in barnacle settlement, apparently imposed by the topographic variability in upwelling intensity (Lagos et al. 2005). Thus, the spatial variability in upwelling intensity typical of central Chile (Strub et al. 1998, Broitman et al. 2001, Halpin et al. 2004) might influence the spatial position of the larval pool and probably affects the scales of dispersal of invertebrates, as suggested also by the study of spatial synchrony in recruitment of species with contrasting dispersal potential (Lagos et al. in review). Topographic effects on patterns of settlement and recruitment have also been reported for a variety of brachyuran crab species (A.T. Palma et al. 2006). Buoyancy fronts produced by river plumes, common from about 30°S to the south in the HCS, in conjunction with wind stress can also play a role in delivering larvae to shore (Vargas et al. 2006c). Narváez et al. (2006) also report on the effect of what they called ‘large warming events’, which occurred a few times in spring–summer in association with downwelling-favourable (northerly) winds. During these specific large warming events these authors observed significant synchrony in recruitment of several invertebrate taxa (decapods, gastropods, polychaetes, mussels and sea urchins), suggesting that larvae could be entrained in these advective fronts and delivered onshore. A roughly similar phenomenon has been observed around Valdivia in southern Chile, where southward and onshore movement of warm waters produced by winter

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storms delivered larvae of several gastropod species to the shore (Marín & Moreno 2002, C.A. Moreno in a personal communication to S.A. Navarrete). Few studies have directly and simultaneously examined the distribution of larvae in the plankton, physical processes and settlement onshore in the HCS. Even fewer have examined larval behaviour under field or laboratory conditions (Poulin et al. 2002a,b, Manríquez et al. 2004, Vargas et al. 2006a).

Patterns of recruitment and benthic communities Systematic studies of recruitment of species in the HCS have focused on (1) characterising spatial and temporal variation in the arrival of new individuals for intertidal and a few subtidal species (e.g., Jara & Moreno 1983, Hoffmann & Santelices 1991, Stotz et al. 1991a, Camus & Lagos 1996, Martínez & Navarrete 2002); (2) relating these patterns with large-scale oceanographic anomalies, such as El Niño events (e.g., Moreno et al. 1998, Navarrete et al. 2002); (3) examining the effects of recruitment variability on population dynamics and recovery of local populations from physical, biological or human-induced disturbance (e.g., Santelices & Ojeda 1984, Moreno et al. 1993b, Duarte et al. 1996, Alvarado et al. 2001); (4) determining the consequences of recruitment variation on the nature and intensity of species interactions in the adult habitat (e.g., Navarrete & Castilla 1990, Moreno 1995, Navarrete et al. 2005, Wieters 2005); and (5) characterising the effects on the processes that regulate the dynamics of entire intertidal communities over large spatial scales (Navarrete et al. 2005). The far-reaching ramifications of persistent variation in recruitment have been most amply demonstrated in recent studies that quantify patterns of recruitment over large temporal (years) and spatial (tens to hundreds of kilometres) scales. These studies are starting to shed light on, and find recurrent patterns in, the causes of the typically large, baffling and usually ‘unpredictable’ variation in coastal ecosystems. Studies along the California coast have found large-scale regularities in patterns of recruitment of sessile species that can help reconcile odd experimental results (Menge et al. 1994, Connolly et al. 2001, Menge et al. 2003). Studies in the HCS conducted by Navarrete et al. (2002, 2005) have evaluated the effects of variation in wind-driven upwelling on community regulation along 900 km of coastline between 29°S and 35°S during 72 months. Sharp discontinuities in upwelling regimes around 30–32°S produced abrupt and persistent breaks in the dynamics of benthic and pelagic communities over hundreds of kilometres (regional scales) (Figure 15A,B). Rates of mussel and barnacle recruitment changed sharply at 32°S, determining a geographic break in adult abundance of these competitively dominant species. Analyses of satellite images also corroborate the existence of regional-scale discontinuities in dynamics and concentration of offshore surface chl-a that had been previously described at coarser resolution (Thomas 1999, Thomas et al. 2001b). Intertidal field experiments showed that the paradigm of top-down control of intertidal benthic communities (Castilla & Durán 1985, Paine et al. 1985, Castilla 1999, Navarrete & Castilla 2003) holds only south of this geographic discontinuity. To the north, populations seem recruitment limited, and predators have negligible effects, despite attaining similarly high abundances. Thus, geographically discontinuous oceanographic regimes set bounds to the strength of species interactions and define distinct regions for the design and implementation of sustainable management and conservation policies along the HCS. Further ecological studies using molecular markers are needed to define the consequences of this variation for the genetic population structure of mussels and barnacles, as well as for other components of intertidal communities, many of which do not experience such a discontinuity in recruitment, despite having similar life histories and general biology (Figure 15C,D).

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3.5

A Chthamalid barnacles, high zone

3.0 2.5 2.0 1.5 1.0 0.5 0.0 3.0

B Perumytilus purpuratus, mid zone

2.5 2.0 1.5 Recruits day−1 collector−1

1.0 0.5 0.0 2.5

C Semimytilus algosus, mid zone

2.0 1.5 1.0 0.5 0.0 TE

70

M

A

RR

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Figure 15 Average recruitment of intertidal invertebrates along the coast of central Chile at sites ordered from north to south, from ~29°S to 35°S. Data correspond to long-term (3–7 yr) averages per site of individuals found in replicated collectors that replaced monthly. The arrow in panels (A) and (B) indicates approximate position of regional discontinuity in intertidal chthamalid barnacles in the high intertidal zone and the dominant mussel Perumytilus purpuratus in the mid-zone. See Navarrete et al. (2005) for further details.

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Population connectivity Connectivity can be defined as the extent to which populations in different parts of a species’ range are linked by exchange of larvae, recruits, juveniles or adults (Palumbi 2003) and determines the degree of cohesion of its genetic pool and the geographic structure of its genetic diversity. The intensity and geographical scale of connectivity within a species is given by the realised dispersal through active and passive mechanisms, which depend on species life-history traits and environmental characteristics. Among the numerous dispersal mechanisms reported in marine organisms, active swimming/crawling and planktonic larval transport, together with rafting and anthropogenic dispersal, are considered as the most relevant to achieve connectivity among local populations (Thiel & Haye 2006). Of particular relevance for connectivity of marine species are the temporal and spatial oceanographic characteristics such as currents, upwelling, water masses and gyres. For example, even though a species may have long-lived planktonic larvae, in a particular bay the larvae may not effectively disperse due to local larval retention (e.g., Swearer et al. 1999, Poulin et al. 2002a, Baums et al. 2005). In contrast, benthic species lacking dispersive larval stages can achieve long-distance dispersal by rafting or anthropogenic transport (Thiel & Haye 2006). Indeed, a recent study demonstrated that biogeographic patterns along the coast of South Africa are reflected in the genetic population structure of littoral organisms regardless of their dispersal stages (i.e., with or without planktonic larvae) (Teske et al. 2006). It seems particularly interesting to pursue this avenue in the HCS of northern-central Chile where no distinct biogeographic barriers but rather taxondependent breaks exist (see section on biogeography). Moreover, the unique characteristics of the HCS make it an interesting system to study the genetic connectivity of marine populations. Important characteristics of the system for genetic connectivity are its wide geographic extent and the oceanographic cyclic variations that lead to temporal and spatial changes in population size and distribution. It is expected that both life-history traits and oceanography play crucial roles in determining the realised dispersal of marine populations and thus their connectivity and the extent of their geographic ranges. Few population genetic studies have been published on marine species of the HCS, although there are several currently being developed on pelagic fishes, marine invertebrates and algae. Nevertheless, some predictions may be formulated and, where possible, validated through existing examples. The pattern of genetic connectivity among local populations of a species determines the geographic structure of its genetic diversity (Figure 16). The frequency, intensity and geographical scale of dispersal within a species shape the resulting gene flow that counteracts the action of genetic drift and local selection. In this context, the intensity of genetic drift is principally determined by population dynamic processes such as population size variation, local extinction, recolonisation and founder effects, all intimately related to connectivity among populations. Therefore, acting both on gene flow and genetic drift, the different patterns of connectivity should result in different geographic structuring of the genetic diversity. Very high gene flow (at the scale of the geographic distribution of the species) leads to genetic homogeneity among local populations independently of the geographic distance. With lower levels of gene flow, different patterns of population genetic structure may result depending on the association between gene flow and geographic distance. If the magnitude of the gene flow is associated with geographic distance, which may be the case for many organisms with planktonic larvae, a genetic cline may form through the range of distribution, characterised by genetic differentiation being proportional to geographic distance, a pattern known as isolation by distance (IBD). This pattern will also be influenced by the direction and strength of the currents. If the magnitude of the gene flow is not strongly associated with geographic distance, which may be the case for organisms that disperse through passive mechanisms, the resulting pattern may be chaotic patchiness. So far two parameters have been

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considered: amount of gene flow and association with geographic distance. A third relevant parameter is the geographic and temporal continuity of the gene flow, from very continuous to a highly discontinuous gene flow that will lead to a break in the geographic structure of the genetic diversity. However, because the amount of time required to reach equilibrium between migration and drift is at least hundreds of times the generation time of a species, the genetic structuring may also reflect historic connectivity. Moreover, such equilibrium cannot be reached under high temporal variability in the pattern of connectivity.

Population connectivity studies in the HCS A first and very general prediction for the HCS is associated with the long and continuous extent of the southeastern Pacific coast, without apparent geographic breaks. In this context, IBD and genetic homogeneity should be the prevalent patterns of geographic structure of the genetic diversity, particularly for organisms that achieve high gene flow through long-lived planktonic larvae or frequent rafting routes. The hairy edible crab Cancer setosus, which is of commercial interest, may represent an example of the above scenario. Gomez-Uchida et al. (2003), using allozymes and AFLPs (amplified fragment length polymorphisms), show genetic homogeneity over 2500 km of the Chilean coast for this species. The authors propose that this pattern may reflect the long-lived larvae (60 days) of C. setosus, the absence of geographic barriers and the oceanographic conditions (north and southward currents) of the area that allow effective mixing of larvae. A similar pattern of genetic homogeneity has been observed in pelagic fishes such as Chilean hake (Merluccius gayi gayi) between 29°S and 41°S (Galleguillos et al. 2000) and Chilean jack mackerel (Trachurus murphyi) between 20°S and 40°S (E. Poulin unpublished data). It is predicted that species with high connectivity and extensive geographic ranges may appear less affected by the oceanographic cyclic variations of the HCS, either because they suffer less population reduction or because they have a relatively rapid recovery after a disruptive event. Overall, these taxa may lose less genetic variability and show a faster ecological recovery after ENSO events.

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Conversely, it is predicted that taxa with low dispersal potential will exhibit pronounced genetic structure and will be the most affected by the oceanographic variations. Genetic studies of the macroalga Lessonia nigrescens show that gene flow is limited among nearby populations (Martínez et al. 2003, Faugeron et al. 2005). Additionally, these authors found that 20 yr after the EN 1982–1983 event, which caused a massive mortality of L. nigrescens on 600 km of the coastline, northward recolonisation had only advanced 60 km (Martínez et al. 2003). Lessonia nigrescens is a good example of a species very vulnerable to oceanographic changes, specifically EN, and that may be continuously recovering from drastic population reductions and local extinction, never reaching migration–drift equilibrium. The genetic structure found for L. nigrescens corresponds to chaotic patchiness at a small geographical scale (tens of metres), reflecting recent population dynamic processes (years to tens of years) and life-history traits such as very low distance dispersal of propagules (Faugeron et al. 2005). Other species that show genetic differentiation at a small spatial scale are the alga Mazzaella laminarioides (Faugeron et al. 2001) and the edible and overexploited snail Chorus giganteus that has a low larval dispersal potential (Gajardo et al. 2002). For the edible and also overexploited scallop Argopecten purpuratus, Moragat et al. (2001) found both genetic and morphological differentiation between populations at the two protected sides of the Mejillones Peninsula (50 km apart) and discuss that it is probably due to currents that restrict the gene flow between the two localities. It can further be predicted that biogeographic breaks will reflect strong barriers to dispersal and thus gene flow for species with low dispersal potential, leading to breaks in the geographic structure of the genetic diversity of species. It has been shown that along the northern Chilean coasts, habitat discontinuities can cause gene flow interruptions (e.g., Faugeron et al. 2001, 2005). Species with lower dispersal potential will be more vulnerable to breaks, while species with high potential of dispersal may not show evidence of a genetic break associated with a biogeographic break, as is the case of Cancer setosus (Gomez-Uchida et al. 2003). Even though for the HCS it has not yet been demonstrated that recognised biogeographic breaks correspond with the geographic distribution of the genetic diversity, it has been shown to be the case for other biogeographic regions such as Point Conception in the California Current System (e.g., Burton 1998, Wares et al. 2001). Rafting may be a very advantageous dispersal mechanism for populations that suffer recurrent extinctions and recolonisations, mostly in the extent of the HCS where macroalgae with high floatability are very abundant. Once organisms are in a raft that has the potential to be in voyage for weeks or months, the rafting-mediated gene flow resulting may not be strictly associated with geographic distance and the resulting pattern of connectivity will depend on the intensity of gene flow, that is, if the rafting route is frequent, intermittent or episodic (see Thiel & Haye 2006). We predict that given the abundance of floating macroalgae, rafting routes along the Chilean coast may be intermittent or frequent, leading to patterns of genetic diversity ranging from chaotic patchiness to homogeneity. Ongoing studies of the isopod Limnoria chilensis may contribute to the validation of this prediction. These organisms have the potential to persist in rafts for long periods of time because they are brooders, have local recruitment and feed on the raft. It is interesting to mention that even though Lessonia nigrescens shows high genetic differentiation even at small spatial scales, the geographic distribution of the genetic diversity does not follow an IBD pattern, suggesting that some long-distance dispersal may occur, although it is not known whether it could be via freeliving spores or on drifting fragments of mature thalli (Faugeron et al. 2005). The HCS appears to be an interesting model for studying marine connectivity patterns in variable environments. Despite the general lack of such studies, recent and still unpublished results on pelagic fishes such as anchovies and sardines, and commercially exploited benthic marine invertebrates like the gastropod Concholepas concholepas and the bivalve Mesodesma donacium, support the existence of genetic homogeneity at large geographical scales as a consequence of the absence of contemporary biogeographical barriers along the HCS for species with high dispersal 254

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potential. In general, it is expected that further studies of different biological systems will show that all the patterns of connectivity (Figure 16) are present along the HCS as a result of the interaction of present and past environmental conditions with species life-history traits.

Biogeography Large-scale patterns in the HCS The pioneer work by S.P. Woodward in 1856, which is probably the earliest biogeographical classification involving the southeast Pacific (Camus 2001, Harzhauser et al. 2002), was followed by a series of foundational studies (e.g., Dall 1909, Ekman 1953, Stuardo 1964, Viviani 1979, Santelices 1980, Brattström & Johanssen 1983, among others) that provided a consistent view of the major biogeographic features of the HCS temperate area (south of the tropical Panamian Province), based on physical gradients and patterns of endemism, richness and spatial turnover of species, and supported by subsequent studies (see reviews by Fernández et al. 2000 and Camus 2001). Overall, two main biotic replacements along the coast differentiate three biogeographical units (see Brattström & Johanssen 1983 and Camus 2001 for reviews on available classifications): (1) a warm-temperate biota extending from northern Peru (4–6°S) toward a variable, taxondependent limit in northern Chile (usually 30–36°S), often designated as Peruvian Province, and dominated by subtropical and temperate species; (2) a cold-temperate biota (also present in southern Argentina) extending along the fragmented coast of the Chilean archipelago from 54°S to about 41–43°S, corresponding to the Magellanic Province dominated by subantarctic and temperate species, exhibiting reduced wave exposure and an estuarine condition due to the dilution caused by high rainfall levels, glaciers and rivers (Ahumada et al. 2000); and (3) a transition zone between both provinces, characterised by strong numerical reduction of subtropical and subantarctic species at its southern and northern borders, respectively, rather than by diffusive overlap of biotas. However, many species occurring throughout this transition zone have a subantarctic affinity and a wide distribution in Chile (e.g., Menzies 1962, Castillo 1968, Alveal et al. 1973, Santelices 1980), probably facilitated by the HCS transporting cool water masses toward the north, which is also considered to be the main reason why the area lacks a definite biogeographic character. Traditionally, the important physical changes around 42°S are considered to be external forcings that act as effective filters for dispersal, and with few exceptions, this zone represents the steepest induced transition along the HCS coast. Contrastingly, the northern limit of the transition zone is remarkably diffuse for the whole coastal biota (Figure 17) and highly variable depending on the taxon examined (Camus 2001), which has been attributed so far to the apparent absence of major physical discontinuities between northern Peru and Chiloé Island (e.g., Brattström & Johanssen 1983, Jaramillo 1987). Such variation mirrors a typical pattern of transitions (Brown & Lomolino 1998), due to differential attenuation rates among taxa related with their different dispersal ability and physiological tolerance. In fact, some particular taxa (e.g., peracarid crustaceans; Thiel 2002) show a well-defined overlap of northern and southern species with a gradual replacement pattern. On a wider taxonomic basis, however, the breaking points for different taxa do exhibit some latitudinal scattering throughout northern Chile, but they are significantly concentrated around 30°S and 33°S (see comparative analyses of animal and macroalgal taxa in Brattström & Johanssen 1983, Lancellotti & Vásquez 2000, Meneses & Santelices 2000, Santelices & Meneses 2000, Camus 2001). Notably, these multiphyletic breaks include southern and northern limits of species with very different life forms and ecological requirements, even involving pelagic groups (e.g., Antezana 1981, Hinojosa et al. 2006). This information strongly suggests that such breaks are not a passive outcome of dispersal and tracking of key environmental variables. For instance, recent work shows that latitudinal patterns of SST (the main causal factor invoked in most studies) fail to explain 255

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Figure 17 Break points of distribution along the north-central Chilean coast documented in 29 biogeographical classifications published between 1951 and 2006 (breaks outside the range 17–38°S are not shown). The figure includes a wide spectrum of animal and macroalgal taxa of varying hierarchical levels, life forms and habitats, and some classifications may partially overlap in one or more of these categories. Each classification is represented along an imaginary vertical axis in correspondence with the numbers at the bottom, where dashed lines denote the zones in which break points were found (each one marked by a thick horizontal dash), ranging from one to three break points per study. Horizontal lines highlight the latitudes 30°S and 33°S where break points tend to concentrate. Classifications (for numbers 1–10 and 11–22, see references in compilations by Brattström & Johanssen 1983 and Camus 2001, respectively): 1, Mollusca (Carcelles & Williamson 1951); 2, Foraminifera (Boltovskoy 1964); 3, Mollusca (Marincovich 1973); 4, several animal taxa (Knox 1960); 5, eulittoral organisms (Hartmann-Schröder & Hartmann 1962); 6, intertidal Mollusca (Dell 1971); 7, benthic animals (Semenov 1977); 8, several animal taxa (Viviani 1979); 9, Anthozoa (Sebens & Paine 1979); 10, several animal taxa (Brattström & Johanssen 1983); 11, benthic macroalgae (Santelices 1980); 12, Bryozoa (Moyano 1991); 13, fishes (Mann 1954); 14, Isopoda (Menzies 1962); 15, several animal taxa (Ekman 1953); 16, several animal taxa (Balech 1954); 17, planktonic Euphausiids (Antezana 1981); 18, Asteroidea (Madsen 1956); 19, macroalgae (Alveal et al. 1973); 20, sandy beach Isopoda (Jaramillo 1982); 21, Porifera Demospongiae (Desqueyroux & Moyano 1987); 22, several invertebrate taxa (Lancellotti & Vásquez 1999); 23, demersal fishes (Sielfeld & Vargas 1996); 24, littoral Teleostei (Ojeda et al. 2000); 25, Phaeophyta (Meneses & Santelices 2000); 26, Rhodophyta (Meneses & Santelices 2000); 27, several animal and algal taxa (Camus 2001); 28, Peracarid crustaceans (Thiel 2002); 29, benthic Polychaeta (Hernández et al. 2005); 30, pelagic barnacles (Hinojosa et al. 2006).

variations of mollusc diversity along the HCS, which would be determined by shelf area (Valdovinos et al. 2003), while the distribution of some littoral species appears more related to regional variations in temperature trends (Rivadeneira & Fernández 2005). Thus, the transitions in northern Chile are

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not readily explained simply by the contact between warm and cold biotas, and proper explanations will require a multivariate, integrative approach and an exploration of possible external forcings.

The role of past and present processes in northern-central Chile (18–35°S) Different lines of historical and ecological evidence suggest that northern-central Chile constitutes a very complex and dynamical biogeographic scenario. Clearly, present-day patterns are not divorced from physical changes related to the origin and installation of the cold HCS during the Tertiary or from subsequent Quaternary fluctuations (e.g., see Villagrán 1995, Hinojosa & Villagrán 1997, Villa-Martínez & Villagrán 1997, Maldonado & Villagrán 2002). The establishment of the HCS had involved both the northward advance of the subantarctic biota and the northward retraction of a former tropical/subtropical biota (Brattström & Johanssen 1983, Camus 2001), with consequences that may persist until the present, reflected in the heterogeneous character of the northern biota. For instance, 10 of the nowadays most common bivalves in northern Chile exhibit upper thermal tolerances exceeding the highest temperatures recorded during EN events in the past century (Urban 1994), which is unexpected for species evolving in a cold upwelling system. At least one of them (Argopecten purpuratus) is thought to be a relict of the Miocene tropical/subtropical fauna (Wolff 1987). Such physiological ‘anomalies’ suggest the presence of an inertial faunistic component within the modern northern biota (i.e., remnants of the former warm fauna that escaped the forced retraction to lower latitudes, and maintained their warm-water characteristics facilitated by recurrent post-Miocene warming events such as EN) (Wolff 1987). In comparison, the marine flora appears more homogeneous and dominated mainly by subantarctic species, while tropical/subtropical species are virtually absent (Santelices & Meneses 2000). For instance, some common and ecologically important kelp species are not only more sensitive to warming episodes but also their upper thermal tolerance varies in accordance with the thermal latitudinal gradient (Martínez 1999). In this regard, the northern fauna underwent repeated distributional alterations in the past associated with climatic fluctuations. Some of them involved the simultaneous range retraction and expansion of different species (e.g., Ortlieb et al. 1994), but more often the occurrence of tropical/ subtropical fauna related to warming (EN-like) events in the Pleistocene (e.g., Ortlieb 1995) and Holocene (e.g., Llagostera 1979). Moreover, Neogene processes related to the establishment of the modern upwelling system in the HCS (e.g., shallowing of the OMZ) provoked a mass extinction of bivalve molluscs (>75% of species), with lasting impacts on their current distribution patterns and biological characteristics (Rivadeneira 2005), and similar effects have been suggested for the polychaete fauna (R.A. Moreno et al. 2006a). Notwithstanding, the causal relationships between historical events and current distribution patterns in northern Chilean waters remain largely unexplored, although their importance may be overwhelming. On the other hand, modern processes also have strong influences in northern Chile, particularly interannual fluctuations related to ENSO, which, however, should be looked at retrospectively, acknowledging the frequency and importance of EN-like events throughout the Holocene (e.g, see Maldonado & Villagrán 2002). Strong EN events can modify the taxonomic composition of littoral communities (e.g., Arntz 1986, Castilla & Camus 1992, Camus et al. 1994, Vega et al. 2005, Vásquez et al. 2006) and the geographical occurrence of many species including key structural components such as intertidal and subtidal kelps (e.g., Lessonia nigrescens, L. trabeculata and Macrocystis pyrifera). Short-term modifications of community composition during EN occur through local extinctions and invasions, depending also on local conditions, which either favour or prevent their occurrence (Arntz 1986, Camus et al. 1994, Martínez et al. 2003, Castilla et al. 2005a). Moreover, the impacts on key species may scale up to produce long-term biogeographic changes, as exemplified by the dramatic effects of the 1982–1983 EN event on the intertidal kelp Lessonia

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nigrescens (for similar cases in subtidal kelp beds see Vega et al. 2005, Vásquez et al. 2006 and the discussion of EN effects here). Lessonia nigrescens plays a key role in Chilean rocky shores (e.g., Ojeda & Santelices 1984, Castilla 1988, Santelices 1990b), and its presence/absence has direct effects on community organisation and diversity. The kelp suffered a regionally correlated local extinction (also involving the loss of its rich holdfast fauna) along 600 km of coastline, which left a few and highly isolated patches, provoking a strong alteration of its geographical population structure (Camus 1994b, Martínez et al. 2003). The regional recovery process of L. nigrescens was slow, more effective toward higher latitudes, and only partial as it failed to re-establish populations in northernmost Chile (Castilla & Camus 1992). Twenty years later, northward recolonisation advanced less than 60 km, and some recovered populations lost >50% of their genetic diversity exhibiting significant IBD (Martínez et al. 2003). These extinctions also lead to transient changes in biotic interactions within the community (see El Niño section), which had negative effects on local kelp recruitment and contributed to its slow recovery (Camus 1994a). Additionally, Scurria scurra, a limpet living on the stipes and holdfasts of Lessonia nigrescens (Muñoz & Santelices 1989), suffered a concomitant extinction. In southernmost localities, Scurria scurra recolonised and re-established its association with the kelp within 1 yr following the EN event, but in some northernmost localities it failed to do so for at least 11 yr (Camus 1994b) (and remains absent in some places until now; P.A. Camus unpublished data). Overall, the ecological, biogeographical and evolutionary consequences derived from the recurrent extinction-recolonisation dynamics undergone by different species in northern Chile are not yet fully understood. However, it may be argued that they promote changes in spatial patterns of genetic diversity and gene flow, increase betweencommunity diversity, and affect the dynamics of endpoints of distribution, leading to unstable biogeographical limits (Camus 2001, Thiel 2002). This last effect can be reinforced by the transient or permanent invasion of warm-water species favoured by EN episodes (e.g., Soto 1985, Tomicic 1985, Arntz 1986, Castilla et al. 2005a, Coloma et al. 2005, Arntz et al. 2006), thus contributing to the mixed biogeographic character of the northern Chilean biota. However, while some general conclusions can be drawn at this level, a proper understanding of large-scale patterns will need to distinguish their historical and ecological components and consider the physical-biological coupling generating differential responses among taxa. In this regard, the factors affecting dispersal and recruitment deserve special attention. Even though EN is known to be related in varied ways to the recruitment of coastal species (e.g., Soto 1985, Glynn 1988, Vega et al. 2005), in northern Chile its effects on dominant littoral species may be negligible or highly specific, with no clear association with interannual variations (Navarrete et al. 2002). Both mesoscale and regional factors related to the spatial structure of upwelling dynamics seem promising to explain such recruitment variations (e.g., Lagos et al. 2005, Navarrete et al. 2005). Additionally, the spatiotemporal dynamics of the OMZ (e.g., Morales et al. 1999, Palma et al. 2005) and the mesoscale eddy activity bounding coastal ecosystems (Hormazábal et al. 2004) may both play a significant role in understanding the dynamic connection between oceanographic processes and biogeographic patterns.

El Niño-La Niña in coastal marine communities The El Niño Southern Oscillation (ENSO) is the largest modern source of interannual variability in the ocean–atmosphere system (e.g., Wang et al. 1999) and, even though its effects are stronger in the tropics, it significantly affects marine life in northern Chile. The ENSO cycle has been a crucial factor in the global climate for at least the past 130,000 yr (Cane 2005), showing continuous, although variable, activity during the last 12,000 yr (Moy et al. 2002); regionally, it has had a major influence on the Chilean coast since the Holocene (e.g., see Ortlieb et al. 2000, Maldonado & Villagrán 2002; see also Biogeography, p. 255ff.). This suggests that coastal communities in northern Chile have continuously been shaped by impacts of EN events (Camus 1990, 2001). 258

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Properties of coastal waters in northern Chile are primarily driven by remote equatorial forcing, which can provoke strong changes in PP due to the availability of nutrients and essential trace elements, corresponding to ENSO cycles (Takesue et al. 2004). Such alterations can trigger a complex chain of biological effects derived from bottom-up controls and physiological constraints, which may involve several levels of biological organisation at different spatial scales, during and between EN. The dramatic and widespread impacts of EN 1982–1983 on coastal communities of northern Chile allowed the identification of biological changes associated with ENSO such as bathymetric or latitudinal migrations, invasion by exotic species, behavioural alterations, reproductive and recruitment failures, increasing population abundance, population decrease due to mass mortality, and in the most severe cases local population extinctions (e.g., see Soto 1985, Tomicic 1985, Arntz 1986, Glynn 1988, Camus 1990, Castilla & Camus 1992, Sielfeld et al. 2002, Vega et al. 2005, Arntz et al. 2006, Vásquez et al. 2006). As a whole, these impacts affect all kinds of taxa and environments, although with clear species- or site-specific components (e.g., in northern Chile none of these effects involves either an entire taxonomic group or the whole suite of species from a given place; e.g., see Soto 1985, Tomicic 1985). Moreover, the type and magnitude of impacts, as well as the range of affected taxa, may vary from one event to another, depending both on the strength of the event and the type of physical-biological couplings that may take place (e.g., see Navarrete et al. 2005). On the other hand, some biotic modifications may occur, or have simultaneous effects, at both local and regional scales (Camus 1994a, 2001, Vega et al. 2005, Vásquez et al. 2006), as observed also in the northeast Pacific (Edwards 2004). Additionally, from a socioeconomic perspective, the increase or decrease in abundance or diversity of fisheries resources at some places may be certainly interpreted as positive or negative effects, respectively (e.g., Arntz 1986). However, from an ecological point of view, it would be as yet uncertain to qualify such changes in the same terms, even for species with no recognisable importance with variations that may have unknown or unpredictable consequences for the community. Thus, simple generalisations on the ecological impacts of EN in northern Chile may still be inappropriate, except at very specific levels. This situation is mainly because of (1) the lack of long-term and systematic biological observations encompassing several events, preventing robust comparisons before, during and after EN conditions, and (2) the irregularity of ENSO itself (e.g., Wang et al. 1999) and the lack of correlation between EN and LN in their strength and duration (e.g., Kerr 1999). Nonetheless, ENSO impacts are indisputably relevant in the ecology of coastal communities in northern Chile. One of the key aspects needed to understand EN effects is its recurrent impact on ‘engineer species’ (sensu Jones et al. 1994) such as kelps, which play a crucial role for the diversity, complexity, structure and functioning of coastal communities along the southeast Pacific (Graham 2004, Vega et al. 2005, Vásquez et al. 2006). Local extinction of kelps is frequent during strong EN events (Camus 1994a,b) such as the 1982–1983 episode, when intertidal populations of Lessonia nigrescens and Macrocystis integrifolia disappeared from the area between 10°S and 21°S and so did the invertebrate community associated with their holdfasts (Soto 1985; see also Biogeography, p. 225 ff.). Concurrent and dramatic impacts were reported during the same event (Soto 1985), affecting ecologically important species of ascidians (e.g., Pyura chilensis), seastars (e.g., Stichaster striatus, Heliaster helianthus) and several fish species, most of them associated with kelp beds. However, the implications of these impacts, both at population and community levels, remain largely unknown. A long-term series of subtidal community dynamics during variable ENSO conditions (1996–2005) has been recently published (Vásquez et al. 2006). Although the EN 1997–1998 was catastrophic and produced local kelp extinctions on the coasts of Chile and Peru (Fernández et al. 1999, Godoy 2000, Martínez et al. 2003), site-dependent conditions allowed the persistence of 259

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some kelp assemblages of Macrocystis integrifolia and Lessonia trabeculata around 24°S (Martínez et al. 2003, Vega et al. 2005). These effects would be related to the frequency and intensity of local coastal upwelling (González et al. 1998, Lagos et al. 2002), which minimised the impact of warming and retained high concentrations of nutrients within the coastal environment (Takesue et al. 2004). A long-term analysis of the structure and organisation of kelp communities in northern Chile (Vásquez & Vega 2004b, Vásquez et al. 2006), which included EN and LN events, showed that the abundance of Macrocystis integrifolia (1) increased significantly during EN 1997–1998, (2) decreased during LN 1999–2001, dropping nearly to zero in 2000, and (3) became reestablished and recovered during a period of positive thermal anomalies in 2002–2003 (Figure 18). This pattern

Figure 18 (A) Upwelling index (Offshore Ekman Transport OET), (B) ENSO index (Southern Oscillation Index SOI-grey line and Multivariate ENSO Index MEI-black line), (C) temporal variability of Macrocystis integrifolia, (D) Lessonia trabeculata, (E) benthic grazers, and (F) benthic predator densities, including El Niño 1997–1998 and La Niña 1999–2000.

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was different from that recorded on the California coast, where the rapid recovery of M. pyrifera following EN 1997–1998 was favoured by the establishment of a cold period (1998–2000) and the survival of sporophytes in deep environments (Ladah et al. 1999; Edwards 2004). In northern Chile, the recolonisation rate of kelp assemblages occurred comparatively slowly (Martínez et al. 2003; see also Population connectivity, p. 252ff. and Biogeography, p. 255ff.), even though cold conditions prevailing during 1998–2000 enhanced the upwelling effect. In this regard, the slow recovery of Lessonia nigrescens after EN 1982–1983 (Castilla & Camus 1992) appeared more related to biotic constraints: recruitment was strongly reduced by a combination of postsettlement grazing and inhibition by encrusting coralline algae, while erect coralline algae played a key role as facilitators, allowing the kelp some escape from grazers and space competitors (Camus 1994a). On the other hand, the decreased abundance of Macrocystis integrifolia was caused by a significant reduction in the adult plant population and the lack of recruitment of juvenile sporophytes (Figure 18). Thus, the disappearance of the M. integrifolia population occurred 2 yr after EN 1997–1998 and was inversely correlated with a population increase of the sea urchin Tetrapygus niger (Figure 18). In contrast, information from other areas of the southeastern Pacific during EN 1997–1998 showed that superficial warming decreased the abundance of kelp on shallow bottoms, inducing migrations of grazers to deeper zones (Fernández et al. 1999, Godoy 2000, Lleellish et al. 2001). In northern Chile, during EN 1997–1998 and LN 1998–2000, different events favoured the increase of sea urchin populations during the cold phase, including (1) induction of mass spawning due to increases in SST and persistence of upwelling events, (2) reduction in density of adult seastars, and (3) changes in the feeding behaviour of the seastar Heliaster helianthus, one of the most important benthic predators on Chilean and Peruvian coasts (Tokeshi & Romero 1995b, Vásquez et al. 2006) (Figure 18). Thus, the long-term study of subtidal communities suggests that different bottom-up and top-down factors might control ecosystem changes in northern Chile, including (1) the intensity and frequency of upwelling, which may buffer the positive thermal anomalies of SST and maintain high nutrient levels, favouring kelp persistence during EN events; (2) site-dependent oceanographic conditions, which may generate optimal conditions for spawning, larval development, and recruitment of echinoderms during and/or after EN events; (3) an overall abundance increase of carnivores which is correlated with an abundance decline of the most conspicuous grazers; (4) population dynamics of adult seastars and sea urchins which may become decoupled during EN events; (5) species-specific population dynamics of some predator species (e.g., Luidia magellanica), and changes in dietary composition in others (e.g., H. helianthus), which may promote population increase of its prey, the urchin Tetrapygus niger, during EN events; and (6) changes in abundance of T. niger, which might be a key factor controlling the development of two alternate states: environments dominated by kelp beds versus barren ground areas. In a wider context involving both subtidal and intertidal environments, EN impacts can be summarised as a large-scale bottom-up effect influencing various (and as yet difficult-to-predict) levels of marine food webs. However, this is just the initial path for most impacts, and top-down effects should not be neglected (e.g., see Nielsen & Navarrete 2004). Future research on EN impacts could consider at least five aspects related to the variability of biological effects, which may serve as guidelines or study framework: (1) the southward intensity attenuation of EN signals produces a latitudinal impact gradient, with reduced effects toward higher latitudes (e.g., Castilla & Camus 1992, Martínez et al. 2003); (2) in the spatiotemporal context, many effects are episodic and/or local (e.g., abundance variability), and some others may propagate their effects to larger spatial scales (e.g., distribution changes, local extinctions), being highly persistent over time (e.g., see Camus et al. 1994); (3) on a taxonomic basis, some taxa are recurrently affected (e.g., kelps), others exhibit no significant impacts (e.g., chlorophytes), and some taxa can be more affected in their reproduction while others in their recruitment (e.g., Camus 1994a, Navarrete et al. 2005, Vásquez et al. 2006); (4) the genetic and evolutionary consequences of recurrent phenomena such as mass 261

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mortalities, extinction-recolonisation processes, and variations in population connectivity are presumably of critical significance, but they are just beginning to be explored (e.g., see Martínez et al. 2003; see also Population connectivity on p. 252ff. and Biogeography, p. 255ff.); and (5) interannual variations related to EN and LN may be strongly related to both small-scale processes such as the Madden-Julian Oscillation (Madden & Julian 1971) and large-scale processes such as the Pacific Decadal Oscillation (PDO; e.g., Trenberth & Hurrel 1994, Zhang et al. 1997) or the Antarctic Oscillation (e.g., Gong & Wang 1999), with possible biological implications for benthic community dynamics that are virtually unknown. Up to now, the ecological knowledge of EN impacts on the marine communities from northern Chile continues to be mainly descriptive, focused on a reduced number of species and places. Nonetheless, prior studies have shed some light on the wide biological scope and geographical extent of such impacts and the need for comparative, multiscale and long-term approaches to obtain meaningful results.

Physiological adaptations of marine invertebrates Physiological variation is the result of genetic, developmental and/or environmental influences (Spicer & Gaston 1999). Thus, physiological diversity and adaptations are linked to environmental characteristics and variability. The understanding of how living organisms function (i.e., their physiology) is aided by comparing the way different animals deal with environmental constraints (Schmidt-Nielsen 1997). Major environmental factors affecting the animal’s physiology are temperature, oxygen and energy (food) availability. The HCS in northern-central Chile is an interesting scenario for running physiological studies due to changing environmental characteristics, such as (1) the occurrence of a latitudinal temperature gradient, (2) extended zones with permanent and/or seasonal upwelling (cold seawater temperature and low oxygen content), (3) some closed bays with relatively high temperatures (e.g., Antofagasta Bay) compared with the surrounding areas and (4) the occurrence of thermal anomalies like ENSO. The HCS is characterised also by the occurrence of oxygenminimum waters, where physiological adaptations of organisms should be expected, even of species from shallower (10–50 m) waters, which may occasionally be confronted with low oxygen concentrations (when there is upwelling of oxygen-deficient waters). Surprisingly few studies are available on physiological adaptations to hypoxic conditions of benthic organisms from the HCS. One of these studies was the characterisation of the pyruvate oxidoreductase enzymes involved in the biochemical adaptation to low oxygen conditions in nine benthic polychaetes from the HCS (González & Quiñones 2000). Pyruvate oxidoreductase enzymes permit the metabolism to produce adenosine triphosphate (ATP) at high rates under environmental or physiological hypoxic conditions (Livingstone 1983). Interestingly, these enzymes were found to be more numerous and with different pyruvate consumption rates in the most abundant and worldwide distributed polychaete species (Paraprionospio pinnata) (González & Quiñones 2000). Another study of biochemical adaptations to hypoxic conditions in the HCS was done on two key species (in terms of trophodynamics and abundance) of this system, the euphausiid Euphausia mucronata and the copepod Calanus chilensis (González & Quiñones 2002). The enzyme lactate dehydrogenase (LDH, a key enzyme of the anaerobic pathway) from Euphausia mucronata was two orders of magnitude higher than that of Calanus chilensis. Higher activities of the LDH indicate higher anaerobic capacities, and this may enable Euphausia mucronata to conduct daily vertical migration through the oxygen-minimum layer (see also Zooplankton consumers, p. 214ff). In contrast, low LDH activities restrict Calanus chilensis to oxygenated waters (González & Quiñones 2002). The importance of the interaction between oxygen and temperature has been explored in recent studies of the brooding behaviour of decapod crabs (Baeza & Fernández 2002, Fernández et al. 2006b). 262

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Closed bays with relatively high temperatures and productivity in the HCS offer suitable conditions for the permanence and reproduction of the scallop Argopecten purpuratus, a species more characteristic of warm waters. An increment of 2.5°C in bottom temperatures (normally 15.5°C) during EN 1982–1983 in Tongoy Bay (30°S) augmented dramatically gonad mass and spawning, and as a consequence spat (juvenile) collection exceeded levels from previous years by 300% (Illanes et al. 1985). However, total gonadal levels of lipids and proteins increased markedly in A. purpuratus conditioned for reproduction at 16°C, but these increases were less pronounced at 20°C (Martínez et al. 2000). Moreover, during gonad maturation muscle carbohydrate levels dropped considerably, as well as the activity of a pyruvate oxidoreductase, the enzyme octopine dehydrogenase (Martínez et al. 2000). Muscle carbohydrate (i.e., glycogen) and glycolytic enzymes have been shown to decrease greatly in other scallop species such as Chlamys islandica and Euvola ziczac (Brokordt et al. 2000a,b). This leads to a decrease in muscle metabolic capacity and thus in escape capacities, which is facilitated by muscle contractions. A reduction of escape capacities during reproduction has been observed in Argopecten purpuratus as well as in Chlamys islandica and Euvola ziczac (Brokordt et al. 2000a,b, 2006). In the intertidal and shallow subtidal zones of the HCS, temperature is the main variable changing over various spatial and temporal scales, with unpredictable interannual patterns. Under normal conditions, physical environmental conditions are relatively stable in the shallow subtidal between 18°S and 35°S (HCS), where salinity typically ranges between 34 and 35 and temperature may vary from 12°C to 22°C. However, due to terrestrial influence, the temperature conditions in the intertidal are different along this latitudinal gradient. For example, the range of mean temperatures registered in high intertidal pools during the summer is ~13–33°C in Antofagasta (23°S), ~13–30°C in Carrizal Bajo (28°S), and ~11–25°C in Las Cruces (33°S) (Pulgar et al. 2006). During EN, these differences in thermal conditions may be enhanced. To evaluate phenotypic plasticity or evolutionary responses of organisms to different habitat temperatures, comparative studies have typically focused on species distributed along latitudinal gradients (Vernberg 1962, Graves & Somero 1982, Stillman & Somero 2000, Pulgar et al. 2006). However, local thermal gradients (TGRs) can be formed by fine-scale variation in, for example, the marine intertidal vertical zones. The intertidal zone is characterised by important spatial and temporal gradients of temperatures, which may be equivalent to those found over a large latitudinal gradient. Intertidal organisms have evolved physiological tolerance adaptations that are important in determining the upper vertical distribution of the species. Studies of congeners or conspecifics allow adaptive variation to be clearly demarcated, independent of effects of phylogeny (Stillman & Somero 2000). Crabs of the genus Petrolisthes (Anomura: Porcellanidae) are widely distributed not only along the intertidal zone of the HCS, but also worldwide, covering huge latitudinal gradients. One of the few studies of physiological adaptations of marine invertebrates in the HSC (Las Cruces, 33°S) was done in five species of the genus Petrolisthes (P. granulosus, P. laevigatus, P. violaceus, P. tuberculatus and P. tuberculosus) (Stillman & Somero 2000). Each species is found at different vertical levels, from the low (P. tuberculosus), mid-low (P. tuberculatus), middle (P. violaceus), mid-high (P. laevigatus) to the high (P. granulosus) intertidal. The limits of thermal tolerance (LT50) were strongly correlated with the vertical position of the species in the intertidal zone (y = 36.02 − 1.88x, r 2 = 0.97) and with the maximal habitat temperature (Table 5) (Stillman & Somero 2000). Thus, species have adapted their upper thermal tolerance limits to coincide with microhabitat conditions. Interestingly, mid-high and high intertidal species (P. laevigatus and P. granulosus, respectively) live near their limits of thermal tolerance. While these LT50 values offer some hints, it may be extremely interesting to explore at which temperatures these organisms enter suboptimal ranges, that is, where they may be able to survive but where growth and reproduction may be compromised. Petrolisthes laevigatus from southern-central Chile dramatically reduces oxygen consumption between 18°C and 20°C (maximal average temperature range found in its 263

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Table 5 Thermal tolerance limits (LT50), and spring maximal habitat temperature of Petrolisthes along intertidal vertical gradient in a locality at the HCS (33°S) Species of Petrolisthes P. P. P. P. P.

tuberculosus tuberculatus violaceus laevigatus granulosus

Vertical position in the intertidal

~ Limit of thermal tolerance (LT50, °C)

~ Maximal habitat temperature (°C)

Low Mid-low Middle Mid-high High

27.5 28.5 30.5 31.5 35.0

14 18 18 28 33

Note: Data from Stillman & Somero (2000).

habitat), which suggests the beginning of the organism’s decompensation, or the commencement of another homeostatic mechanism independent of oxygen consumption (Yaikin et al. 2002). Higher thermal stress or having thermal limits close to actual maximal habitat temperatures might increase the ‘cost of living’ of the species in the upper intertidal (Somero 2002, Stillman 2002). This higher cost of living would be associated with the cost of repairing thermal damage (heat-shock proteins, Hsp) and adapting systems through acclimatisation (Somero 2002). Although tropical Petrolisthes species have higher thermal limits than HCS species, the latter show a wider range of thermal tolerance between low and high intertidal species (Stillman & Somero 2000). Moreover, low intertidal HCS species show greater phenotypic plasticity in their thermal tolerance than high intertidal species (Stillman & Somero 2000). Considering global warming, species inhabiting the upper intertidal zone, living at the ‘edge’ of their thermal limits, would be more affected than species from the lower intertidal, which live far from their thermal limit and with a greater thermal phenotypic plasticity. These physiological traits may have an important effect on the borders in the latitudinal distribution of a species and consequently also on biogeographic limits. Thermal effects that occur outside the normal physiological range involve deleterious changes at the cellular level, especially in systems involved with oxygen uptake, delivery and utilisation (Stillman 2002), such as the cardiac system (Frederich & Pörtner 2000). The heart of a crab species living in the upper intertidal has an Arrhenius break temperature (ABT, temperature at which a break occurs in the slope in an Arrhenius plot, i.e., log rate vs. reciprocal of absolute temperature, K) that is 5°C higher than in a crab species from the low intertidal (Stillman & Somero 1996). These differences were associated with the Na+ K+ ATPase (adenosine triphosphatase) activity, which is necessary for the establishment of the membrane action potential that permits the heartbeat (Stillman 2002). Similar to the rate of heartbeat, oxygen consumption by isolated mitochondria exhibits a ‘break’ at some high temperatures (Dahlhoff & Somero 1993). Phenotypic plasticity in the ABT of mitochondrial respiration has been observed in abalone Haliotis congeners from different thermal habitats (latitude and vertical positions along subtidal-to-intertidal gradient) (Dahlhoff & Somero 1993). Protein synthesis and heat-shock response has been shown to change spatially among gastropod (Tegula) congeners from the temperate subtidal to the low intertidal zones (Tomanek 2001) and seasonally in the bivalve Mytilus trossulus (Hofmann & Somero 1995). Hsp have the function of refolding and ‘rescuing’ proteins damaged by thermal denaturation (Becker & Craig 1994, Hofmann & Somero 1995). Intertidal species of Tegula showed greater expression of Hsp70 than the subtidal species when temperature increases (Tomanek 2001). The energy cost associated with replacing damaged proteins and maintaining Hsp may be an important proportion of cellular energy demands (Hofmann & Somero 1995, Somero 2002). Intertidal and shallow subtidal invertebrates present a ‘cascade’ of physiological responses that enable them to adapt and finally survive changes in environmental conditions. Despite the important 264

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latitudinal and vertical environmental conditions gradient of the HCS, there are few studies of physiological responses of invertebrates living in this ecosystem. The range of temperatures registered in the intertidal (rocky pools) along this latitudinal gradient (Pulgar et al. 2006) is very similar to the TGR from the low-to-high intertidal zone observed in central Chile (Table 5). Therefore, it could be expected to find similar thermal physiological variability and local adaptations of congeners or conspecifics in the latitudinal gradient to those found in the intertidal vertical gradient. Because in this area the pattern of environmental variability shifts from a relatively predictable seasonal pattern to a more unpredictable pattern of high interannual variability (i.e., ENSO), physiological characterisation of congeners or conspecific organisms inhabiting the intertidal and shallow subtidal zones along the latitudinal gradient of the HCS would be particularly interesting. Moreover, since algal availability increases from northern to southern Chile (Santelices & Marquet 1998), and physiological compensation associated with environmental stress increases cost of living (Somero 2002, Stillman 2002), latitudinal changes in food availability should also be considered in future studies. It appears particularly interesting to examine how increased costs of living near the distribution limit of a species influences its reproductive potential.

Reproductive patterns of selected marine invertebrates in the HCS Some of the factors that vary with upwelling intensity and persistence, such as temperature and PP, are known to critically affect per capita reproductive investment of marine invertebrates (e.g., MacDonald & Thompson 1985, 1988, Clarke 1987, Brey 1995, Phillips 2002). In the northeastern Pacific, reproductive hot spots coincide with regions exhibiting high PP, which suggests not only that bottom-up processes play a central role in explaining reproductive output, but also that spatial heterogeneity in reproduction needs to be considered in conservation and management plans (Leslie et al. 2005). The clear break in eddy kinetic energy and equatorward wind stress reported at 30°S in the southeastern Pacific (Hormazábal et al. 2004) coincides with two contrasting regimes in chl-a concentration both in coastal areas and offshore (Yuras et al. 2005). Chl-a concentration is negatively correlated with seawater temperature along the HCS (Strub et al. 1991, Thomas et al. 2001b). The effects of small- and large-scale variation in environmental conditions related to upwelling persistence and strength on reproductive patterns along the HCS have recently been analysed.

Primary productivity and gonad production Gonad and egg production of marine invertebrates do not exhibit a clear latitudinal cline in investment in reproduction along the HCS in central Chile (Fernández et al. 2007). However, gonad production shows variable patterns throughout the study region, which extends from 28°S to 36°S, and this variability appears related to the trophic level of the species being investigated and the proximity of the study sites to upwelling centres. Carnivores such as Concholepas concholepas and Acanthina monodon do not show variation in gonad investment between 28°S and 36°S (Figure 19). In contrast, some of the dominant intertidal suspension-feeding species, Perumytilus purpuratus and Nothochthamalus scabrosus, and one of the most abundant herbivores, Chiton granosus, exhibit strong variation in gonad production among sites, even between adjacent locations (Fernández et al. 2007). Investment in reproduction of suspension-feeding and herbivore species is constantly higher in some sites (e.g., Los Molles 32°24′S, Consistorial 33°49′S) and lower in others (e.g., Montemar 32°96′S, Matanzas 33°96′S). Furthermore, there is a positive and significant correlation between investment in gonads among Perumytilus purpuratus, Nothochthamalus scabrosus and Chiton granosus (p always < 0.05; P. purpuratus-N. scabrosus: R = 0.89, P. purpuratus-Ch. granosus: 265

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30°S

28°S 0.15

32°S

34°S

36°S

A

0.1 0.05 0 0.03

B

0.01

D

Pichilemu

El Quisco

Consistorial Matanza

Montemar Quintay

Los Molles

Guanaqueros

Arrayan

Totoralillo

Temblador

Cta. Hornos

E

Huasco

400 300 200 100 0

C

Pta. Choros

0 0.125 0.02 0.075 0.05 0.025 0 0.5 0.4 0.3 0.2 0.1 0 500

Brood size n/basal area

Reproductive output

0.02

Figure 19 Reproductive output of (A) Concholepas concholepas, (B) Acanthina monodon, (C) Chiton granosus, (D) Perumytilus purpuratus, and (E) brood size (number of embryos per unit of basal area) of Nothochthamalus scabrosus, along the study site which ranges from 28°S to 36°S in the eastern South Pacific Ocean. The white bars are used for carnivore species, the black bars for herbivore or filter-feeding species. The white arrows indicate upwelling centers, the black arrows point to sites not influenced by upwelling along the HCS.

R = 0.64, N. scabrosus-Ch. granosus: R = 0.73; Fernández et al. 2007). Investment in gonads of carnivore species does not show any correlation with the reproductive patterns exhibited by herbivores or suspension-feeding species. The patterns reported were consistent over the 3-yr study (coefficient of variation = 1.3%). These results suggest that the small-scale variation in environmental conditions along the upwelling-favourable region of the HCS seems to affect gonad production and consequently larval production, and therefore that some locations potentially serve as source populations of propagules. Transplant experiments support the hypothesis that local environmental conditions determine reproductive output. Suspension feeders (e.g., Perumytilus purpuratus) 266

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and herbivores (e.g., Chiton granosus) transplanted between the most and least suitable sites for reproduction in central Chile showed that reproductive output was strongly determined by the site to which the animals were transplanted while the site of origin showed a negligible effect (Fernández et al. 2007). Organisms transplanted to Los Molles showed high reproductive output and organisms transplanted to Matanzas showed low reproductive output, regardless of the site of origin (Fernández et al. 2007). These contrasting results suggest that environmental variables, such as PP, may affect investment in gonads of lower trophic level benthic invertebrates. These environmental conditions seem to be related to the spatial variation of upwelling conditions. The central coast of Chile is dominated by seasonal wind-driven upwelling that forces cold, nutrient-rich water into the upper water column (Wieters et al. 2003). However, it is remarkable that the well-documented relationship between cold upwelled water and high chl-a concentration over large spatial scales off the coasts of Chile and California (Strub et al. 1991, Thomas et al. 2001a) is not observed at smaller spatial scales (Wieters et al. 2003). Between 28°S and 36°S, the lowest chl-a concentrations are associated with coldest upwelled waters (Wieters et al. 2003). Matanzas and Montemar are sites influenced by upwelling centres, in contrast with the lower influence of upwelling in areas such as Los Molles or Consistorial (Broitman et al. 2001, Wieters et al. 2003). Upwelling centres also show higher growth rate of corticated algae, which are not consumed by herbivores, and low growth of ephemeral algae (Nielsen & Navarrete 2004). Although temperature decreased from 28°S to 36°S and is lower in upwelling centres, gonad production is not correlated with seawater temperature (Fernández et al. 2006a). Most likely, the low chl-a concentration associated with upwelling conditions (Wieters et al. 2003) and low abundance of benthic ephemeral algae (Nielsen & Navarrete 2004) are the main factors affecting reproductive output of lower trophic level, intertidal species along the HCS. Evidence from other geographic regions supports the hypothesis that patterns of PP associated with upwelling conditions determine reproductive output (Leslie et al. 2005). However, more information is necessary to clearly identify the set of environmental variables affecting reproductive investment.

Temperature and brooding requirements Although the effect of temperature on gonad production is not evident along the upwelling region associated with the HCS between 28°S and 36°S, studies conducted over larger spatial scales (and wider temperature ranges) suggest that temperature can affect egg production in species that aggregate embryos. Oxygen is a limiting factor in embryo aggregations of marine invertebrates (Cohen & Strathmann 1996, Lee & Strathmann 1998, Fernández et al. 2003) and temperature affects oxygen availability in different types of embryo packing (Brante et al. 2003, Fernández et al. 2006a). Studies of the brachyuran crab Cancer setosus show that brooding females respond to the increased oxygen demand of the embryos at higher temperatures by increasing abdominal flapping frequency, a behaviour that supplies oxygen to the brood (Brante et al. 2003). Similar patterns of female response to embryo oxygen demand have been reported throughout embryo development in other crab species (Baeza & Fernández 2002, M. Fernández et al. 2002). The change in female brooding behaviour (abdominal flapping frequency) produces a higher rate of oxygen supply, dramatically affecting the costs of brooding. Between 10°C and 18°C, a 45% increase in brooding costs was estimated for large-size crabs, such as C. setosus (Brante et al. 2003). This substantial increase in brooding behaviour and cost seems to affect egg production and survival (Fernández et al. 2003). Field data showed that gonad investment (or reproductive output) in C. setosus is lower in northern Chile (approximately 20°S) than in central (30–33°S) and southern (40°S) Chile. Lardies & Castilla (2001) reported a similar latitudinal trend in reproductive output for Pinnaxodes chilensis. Moreover, embryo loss in Cancer setosus increases with temperature (Brante et al. 2003), suggesting that temperature also affects embryo survival throughout the brooding period. Reproductive output of most brachyuran crab species does not vary south of 30°S 267

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(Brante et al. 2004). The contrasting pattern in reproduction between populations of brachyuran crabs north and south of 30°S seems also to occur in other species that aggregate embryos. It is interesting that despite the lack of difference in reproductive output of Concholepas concholepas between 28°S and 36°S (Figure 19), embryo packing shows a clear break that coincides with the break exhibited by brachyuran crabs (north and south of 29–30°S). The mean number of embryos per unit of capsule area was significantly lower in capsules from sites north of 29°S than south thereof (20.6 vs. 31.8, respectively), over a range of study sites located between 30°S and 42°S. Although there is no dramatic break in temperature at 30°S (Broitman et al. 2001), the pattern of embryo packing is explained by the mean temperature at the study site shortly before egg deposition. The evidence accumulated to date suggests that the higher brooding costs north of 30°S seem to affect reproductive output and that the effect is consistent across the brooding modes and taxa studied so far. This finding suggests that environmental conditions are less favourable for brooding species in the northern part of the HCS. In fact, large-scale studies of the patterns of species distribution in relation to larval developmental mode support the hypothesis that the spatial distribution of brooding species is explained by the cost of brooding, which is associated with the cost of oxygen provision (Astorga et al. 2003, Marquet et al. 2004). It is less clear if the impact of the cost of brooding on reproductive output may change with adult body size. Recent studies have shown that small crab species perform the same active brooding behaviours as large species (e.g., Pisoides edwardsi, Acanthocyclus gayi; Fernández et al. 2006b). However, mean oxygen consumption of brooding females, which is a proxy of brooding cost, is not significantly different from oxygen consumption of non-brooding females (Fernández et al. 2006b). These results contrast with previous studies of large species, showing a 2- to 3-fold increase in oxygen consumption by females carrying later-stage embryos over non-brooding females (e.g., Cancer setosus: Baeza & Fernández 2002; Homalaspis plana: Ruiz-Tagle et al. 2002; Ovalipes trimaculatus: Fernández & Brante 2003). Therefore, the patterns described for brooding species may be dependent on adult body size. In fact, the small crab species Acanthocyclus gayi and A. hassleri do not show any pattern in reproductive output along the region extending from 28°S to 36°S (Espinoza 2006). Although existing evidence on reproductive output along the HCS suggests that the behaviour of populations north and south of 30°S depend on the cost of oxygen provision in larger-size species, more studies are needed in order to generalise the findings on the effects of temperature on brooding costs, the link between adult size and brooding mode, and the consequences on species distribution, especially in regions influenced by upwelling where low oxygen conditions cover extended regions of the ocean (Fuenzalida et al. accepted).

Larval life in the HCS Oceanographic conditions in the HCS ecosystem expose planktonic larval forms to environmental conditions in which they do not behave simply as a passive particle. Therefore, morphological, physiological and behavioural characteristics present in fish and benthic invertebrate larval forms inhabiting any particular habitat can be interpreted as effective local adaptations evolved to face this unique ecosystem. Herein, the aim is to give a brief overview of some behavioural and feeding traits together with transport processes described in larval forms of benthic invertebrates and fishes inhabiting the HCS.

Behavioural traits Larvae of many marine benthic invertebrates, differing from lecitotrophic short-lived larvae, spend extended periods in the plankton prior to settlement and metamorphosis (Thorson 1950, Pechenik 1986, 1999). Usually, during their pelagic phase, planktotrophic larvae (PL) of marine benthic 268

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invertebrates must remain suspended, locate and gather food, avoid predators and unfavourable conditions, disperse to new areas and select sites for settlement (Strathmann 1974, Palmer & Strathmann 1981, Scheltema 1986). The importance of larval behaviour has been recognised as an important subject in marine ecology and the recent focus on the role of nearshore oceanographic processes controlling larval dispersal and recruitment of benthic organisms has revived interest in the behaviour of larvae in the plankton (reviewed in Le Fèvre & Bourget 1992). Although larval transport seems to be mainly controlled by hydrographic factors (Thorson 1950), larval behaviour may influence their final destination (e.g., Butman 1987, Pineda 1994a,b). In general, sources of mortality in the dispersal phase for PL are food limitation, extreme conditions of temperature and salinity, low dissolved oxygen, UV radiation and pollution (Pechenik 1986). However, because of the difficulties associated with larval tracking in the field, the relative importance of each potential source of larval mortality in nature is still largely unknown. Field and laboratory experiments have revealed a number of behavioural mechanisms that allow larvae to contend with these selective pressures on mortality. However, specific studies of characteristics displayed by PL throughout the HCS are largely absent. Few published studies regarding larval characteristics linked with ecological importance have been conducted in Chile (e.g., Manríquez & Castilla 2007). Field evidence of a DVM pattern in competent larvae has been described for the muricid gastropod Concholepas concholepas (Poulin et al. 2002a,b). It has been suggested that the behaviour of competent larvae of this species may help them to avoid offshore transport during upwelling events. Studies with several crustacean species have shown clear synchronisation between reproduction and the hydrodynamic processes promoting larval transport or retention (Yannicelli et al. 2006a). Similar studies with other PL in the HCS incorporating behavioural or physiological responses to environmental variables such as currents, temperature and salinity are urgently needed. However, along the HCS those studies are precluded by the absence of basic knowledge such as larval identification in many species of Chilean invertebrates. Work to investigate the scale of the source–sink dynamics of PL in the temporally heterogeneous HCS ecosystem is also largely absent. More recent techniques involving chemical tags in calcified structures of PL have been successfully used to identify potential larval source and sink areas, and larval trajectories in the HCS (Zacherl et al. 2003).

Feeding and larval food environment in the HCS Recruitment is recognised as the leading determinant of population dynamics of benthic invertebrate and fish species and it strongly adjusts the importance and intensity of species interactions in the HCS (see above). Since PL rely on food to grow and develop, availability and quality of food particles during larval development are important factors influencing larval recruitment (Vargas et al. 2006a). Despite the high variability in larval food composition, there are well-documented, persistent, temporal and spatial differences in plankton structure and abundance along the HCS. For instance, large and geographically persistent heterogeneity in chl-a has been documented along the Chilean coast (Thomas et al. 2001b, Yuras et al. 2005; and see Dominant primary producers and their role in the pelagic food web, p. 210ff.). The general pattern indicates that a large percentage of chl-a is found in the large phytoplankton fraction in permanent coastal upwelling areas off northern Chile (Iriarte & González 2004; see also Dominant primary producers and their role in the pelagic food web, p. 210ff.), as well as during spring/summer at seasonal upwelling sites in central Chile (González et al. 1989, Vargas et al. 2006b). Similarly, a large and geographically persistent heterogeneity in chl-a levels has been observed to the north of latitude 32°S (Yuras et al. 2005). The scarcity of available published data on larval fish and invertebrate feeding makes it difficult to evaluate potential larval survival and recruitment along the HCS. Currently, the largest body of literature is available for larval fish of commercially exploited species. Because of their seasonal 269

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Diatoms

Heterotrophic nanoflagellates Microprotozoa

Copepod stages

mid-size prey

Physical processes Affecting both food and larvae Turbulence Internal waves, tides River plume motion Frontal structures Filaments Upwelling/downwelling

large prey small prey

Diatoms

Microprotozoa

Autotrophic nanoflagellates

Heterotrophic nanoflagellates

Picoautotrophs

Bacteria

Autotrophs

+

Food size

Spatial/temporal heterogeneity

Autotrophic nanoflagellates

Bacteria

+

Low chlorophyll

Picoautotrophs

Food size

High chlorophyll

Heterotrophs

−

Autotrophs

−

Heterotrophs

Figure 20 Conceptual scheme of main pathways of interaction in coastal food webs involving invertebrate (i.e., veliger competent larvae and barnacle nauplii) and fish larvae under spatial/temporal variation in chlorophyll levels in the Humboldt Current System. The thickness of the arrows represents main predator-prey interactions. The sizes of the boxes or circles represent the dominance in terms of biomass of a specific food item (both autotrophic and heterotrophic prey) during each condition. Physical processes discussed in this chapter, which affect both larvae and food distribution, are also included. Arrows directed to food items at top or bottom boxes were included for convenience.

nature, in the coastal upwelling area off central Chile (36–37°S), the changes in the phytoplankton protozoan and microplankton community that constitute the food supply for larval fish also occur on a seasonal basis (Vargas et al. 2006b). Accordingly, larvae produced in the middle of winter in the HCS, when PP and seawater temperatures are low and wind-induced turbulence in the upper part of the water column is high, are probably not going to face the same prey as those produced in summer, when upwelling and PP are at maximum (Figure 20). Most of the studies of larval fish feeding have focused on changes in prey field, diet overlap, and their influence on larval feeding over short timescales, between adjacent areas, or have attempted to investigate whether evidence of starvation occurred in wild-collected larvae (Llanos et al. 1996, Balbontín et al. 1997, Pizarro et al. 1998, Llanos-Rivera et al. 2004). For the anchovy, Engraulis ringens, in northern Chile (20–21°S), scarce incidence of starvation was even observed during autumn, a season of reduced 270

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plankton production (Pizarro et al. 1998). In northern Chile, the diet of the myctophids Diogenichthys laternatus and Triphoturus oculeus, which feed diurnally and share the upper water column (0–200 m depth), was shown to vary according to prey availability in the field. The diets of both species overlap in periods and areas where food is more abundant (e.g., copepods, copepodids, nauplii, invertebrate eggs and ostracods), but differ under conditions of low prey availability (RodríguezGraña et al. 2005). Other studies in central Chile have shown that either microplankton concentrations did not appear limiting in winter (Castro et al. 2000, Hernández & Castro 2000, Castro 2001) or larval diet overlap occurred among several species but during periods of high food abundance (Llanos et al. 1996, Balbontín et al. 1997, Llanos-Rivera et al. 2004). Hence, the few studies carried out on feeding of larval fish along the HCS in Chile suggest that, although the larval food abundance may vary among seasons and localities, starvation due to limiting food availability alone does not seem to be such a common feature, even in seasons of lower production (autumn and winter). For starvation to occur, other factors may be necessary, such as increased turbulence, which may play a concomitant role during the low productivity seasons, at least in southern Chile (Cury & Roy 1989, Castro et al. 2002). Scarce dietary overlap and local morphological and physiological adaptations (i.e., increased reserves in fish eggs and larger yolk size in fish larvae; Llanos-Rivera & Castro 2004, 2006) seem to exist in larval periods when ontogenetically food is highly necessary (i.e., onset of feeding) or when food becomes less abundant in the environment (Balbontín et al. 1997, Llanos-Rivera et al. 2004, Rodríguez-Graña et al. 2005). For benthic invertebrates, sharp spatial transition in phytoplankton biomass associated with upwelling dynamics has been assumed to have important effects on larval condition (Wieters et al. 2003). This assumption is based on the idea that phytoplankton is the most important food item for PL. A major impediment to understanding how food quantity and quality influence larval life under natural conditions is that virtually all published information comes from laboratory rearing studies in which larvae are offered a monospecific or controlled-mix algal culture. One of the first studies done in the HCS analysing feeding preferences in larval invertebrates, by Vargas et al. (2006a), found evidence that barnacle nauplii (Jehlius cirratus and Notobalanus flosculus) and veligers (Concholepas concholepas) exhibited high consumption of heterotrophs (i.e., ciliates and dinoflagellates), but the size spectrum of food particles removed by barnacle nauplii was in contrast with those for C. concholepas veligers. Barnacle nauplii preyed heavily on small picophytoplankton (<2 µm), whereas competent C. concholepas veliger larvae were mechanically unable to feed on small cells, and the highest removal rates were of nano- and microphytoplankton (>20 µm). The ability of barnacle nauplii to feed on small prey hinges on the small spaces between their limb setules (Stone 1989). This important finding indicates that omnivorous larval feeding should be the norm in the pelagic ecosystem and might explain why larvae maintain positive growth in environments where phytoplankton is thought to be limiting (Crisp et al. 1985). Therefore, the scarce published information for the HCS suggests that the inference of patterns of larval condition and recruitment over large scales from chl-a biomass, now easily measured from satellite images (e.g., Thomas et al. 2001b), has to be regarded with caution. The scenario suggests that a large spectrum of food particles is available for larval feeding, and species may adapt their feeding preferences in relation to temporal/spatial food distribution along the HCS as well as their physiology and energetic reserves to counteract the spatial and temporal variations in food quality and quantity (Vargas et al. 2006b) (Figure 20).

Upwelling and larval transport processes The wind-driven seasonal upwelling, besides its paramount effect on PP in the coastal zone, induces profound changes in the dynamics of coastal waters that directly affect the distribution and abundance of organisms in the nearshore areas as well as over the continental shelf and slope. To reside 271

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in these hydrodynamically variable but highly productive environments, coastal and offshore organisms have developed a series of reproductive strategies that enable them to counteract the effects of offshore advection in the surface Ekman layer or take advantage of other oceanographic processes to return to the coastal zone (see also Coastal oceanography, p. 205ff.). For instance, on a seasonal timescale, small pelagic clupeiform fish tend to synchronise their reproductive timing with processes that induce shoreward transport and coastal retention. Probably the best-documented species in the HCS of central Chile are the anchovy (Engraulis ringens) and common sardine (Strangomera bentincki) that reproduce during winter, when the wind-driven Ekman layer is directed shoreward and thus eggs and larvae are retained in the coastal area (Castro et al. 2000, Castro 2001, Cubillos et al. 2001, Hernández-Miranda et al. 2003). Shelf-break, slope-demersal and mid-water fish species, such as Chilean hake (Merluccius gayi), big eye flounder (Hippoglossina macrops), and the mesopelagic Maurolicus parvipinnis, instead seem to prefer early spring reproduction when subsurface waters drive their eggs and larvae to the coast during the upwelling season, where they develop in the season of higher production (Vargas et al. 1997, Vargas & Castro 2001, Landaeta & Castro 2002, Landaeta et al. 2006). This strategy, originally described for some large offshore copepods such as Rhincalanus nasutus, and more recently observed also in the galatheid Pleuroncodes monodon and the majid Libidoclaea granaria, is currently accepted as a common feature among several types of organisms that have in common larvae inhabiting subsurface waters in central Chile (Castro et al. 1993, Yannicelli et al. 2006a,b). Other species of decapod crustaceans also synchronise their reproduction with the seasonal changes in hydrodynamics for their transport or retention (Yannicelli et al. 2006b). In this group, however, several species reproduce during the upwelling season in spring and summer and their horizontal distribution seems to be associated with their behavioural ability for vertical migration (i.e., Neotrypaea uncinata, Pagurus sp.). Other species with protracted larval periods such as Emerita analoga and Blepharipoda spinimana, which reproduce late in summer and early spring and then reside in the upper water column without signs of vertical migration, probably use more than a single retention process, as yet unknown, because their reproduction occurs over periods of contrasting hydrographic processes (Yannicelli et al. 2006b). Among molluscs, there is scarce information; for instance, the larval retention and shoreward transport mechanism of the gastropod Concholepas concholepas are the only information reported for the HCS. In this case, avoidance of the surface Ekman layer by competent larvae appears to be accomplished by an inverse vertical migration that reduces their time exposed to seaward flow and keeps the larvae between the coast and an upwelling front (Poulin et al. 2002a,b). Coastal oceanographic processes such as upwelling shadows have also been reported (Escribano et al. 2002) as larvae retention mechanisms and such might constitute an understudied coastal larval retention system along the HCS. Tidal transport of larvae, associated with frontal structures near the coast, the entrance of estuaries or large bays, has also been reported recently for central and southern Chile. Internal tidal bores associated with semi-diurnal temperature changes coincided with bivalve, gastropod and crustacean settlement, suggesting that coastward larval transport occurred during these events in summer (Vargas et al. 2004). In Corral Bay (~40°S), changes in larval fish distributions coincident with changes in the estuarine front position in different tidal phases have been reported by Vargas et al. (2003) as an indication of potential larval tidal transport. More recently, with the aid of fineresolution current profiles and stratified larval collections over 24-h cycles, semi-diurnal changes in water flow patterns and of decapod and larval fish fluxes in and out of the Gulf of Arauco have been estimated (Yannicelli et al. 2006a, R. Veas unpublished data). The overall larval fluxes were modified by their vertical position in the water column, the diurnal vertical migration patterns and the tidal cycle. Interestingly, although clearly associated with tidal phases, the larval fluxes experienced by these decapod and fish larvae in the Gulf of Arauco did not correspond exactly to selective tidal stream transport (STST) as it has been reported at the entrance of other bays and estuaries in other coasts of the world (Forward et al. 1998). 272

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Seaward and alongshore exportation of larvae in river plumes, filaments and eddies seems to be a common feature along the HCS. In northern Chile, a mixture of coastal and offshore larval fishes, both in the coastal and adjacent offshore areas, has been repeatedly reported in different seasons and years (Loeb & Rojas 1988, Rojas et al. 2002, Rodríguez-Graña et al. 2005). Besides the existence of a narrow continental shelf, at least three oceanographic processes involving larval transport have been advocated to explain such patterns: (1) seaward surface Ekman transport and upwelling plumes, (2) the presence of filaments, and (3) warm-water intrusion during EN years, all well-documented processes in northern Chile (González et al. 2000b, Sobarzo & Figueroa 2001). In central Chile, surface Ekman transport and cold-water filaments have also been reported to export chl-a, meroplankton and ichthyoplankton from the coastal zone (Cáceres 1992, Morales et al. in review) and they have been used to explain part of the larval mortality rate estimations in the coastal zone (Castro & Hernández 2000, Landaeta & Castro 2006). Larval transport associated with river plumes, mesoscale processes not occurring in northern Chile, has also been proposed as a determinant of barnacle larval transport (Vargas et al. 2006c). Such plumes are also potential areas of increased larval food availability at the frontal area. Other still-unknown oceanographic processes capable of transporting larval forms alongshore probably occur in the HCS. In fact, it is worth noting that almost no reports exist on the role of the Humboldt Current itself or the Chile-Peru poleward undercurrent as a means of alongshore latitudinal larval transport (except for potential transport of larval Pleuroncodes monodon in subsurface waters off central Chile; Yannicelli 2005). In summary, a number of larval transport processes have been described along the central and southern part of HCS. Three of them seem particularly important when considered from an ecological perspective: (1) larval transport (seaward and shoreward) in the surface Ekman layer, (2) exportation from the coast in filaments (especially off the Mejillones Peninsula in northern Chile and off the Talcahuano area of central Chile) and (3) the coastward subsurface larval transport in upwelling waters in spring and summer with the concomitant mixing of offshore and coastal species near shore. Examples of important differences between northern and central Chile are the influence of oceanographic processes such as EN events (much stronger in northern Chile) and of river plumes (absent in northern Chile). Overall, populations of invertebrates and fishes along the HCS develop multiple strategies to cope with the intense periods of transport during early life stages. Timing the reproductive seasons with specific oceanographic events is most common. However, specific reproductive timing depends on the local sites of reproduction, capability of larvae to move vertically in the water column, length of larval life history/cycle and other not so well studied processes (i.e., retention in upwelling shadows) or those occurring during the adult life stage (seasonal growth, energy accumulation, oogenesis) that may finally affect the larval characteristics mentioned above.

Life-history adaptations of macroalgae The macroalgal flora along the HCS is characterised by the presence of endemic species (32%) mixed with species of different biogeographical affinities, including subantarctic (34%), widely distributed (23%), tropical (3.5%) and amphi-equatorial (7%) species (Santelices 1980). In general, this species composition, which is comparatively poorer than that reported for other regions and increases in number toward higher latitudes (Lüning 1990, Santelices & Marquet 1998), responds to the relative biogeographic isolation as a consequence of the predominant direction of the water circulation regime in the HCS (Santelices et al. 1980, Meneses & Santelices 2000). However, an increasing number of invasive species as a result of human activities (ship transport, aquaculture, etc.) has recently been reported with concern about their impact on indigenous species (Castilla et al. 2005a). For example, recent surveys indicate an increase of subtropical elements, a decrease in endemic species and two break points in species composition at 12°S and 42°S (Meneses & Santelices 2000). 273

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Environmental gradients and strategies of resistance, recovery and recolonisation Although benthic algae are not in direct contact with the main stream of the HCS, subsystems such as the Arica-Mejillones Current or Gunther Undercurrent are located close to the coast (<100 km) (Strub et al. 1998) and hence strongly influence macroalgal assemblages. On the other hand, the biogeographic patterns and ecology of macroalgae of northern-central Chile may be affected by upwelling events and by changes in the oceanographic conditions due to EN episodes. Both processes can interact on local and temporal scales: the permanent coastal upwelling can buffer and moderate superficial warming of the sea and depletion of nutrients during EN (Vega et al. 2005). The first factor has not been well studied for the case of the macroalgae; however, the effects of EN have received much attention in the last decades (Camus 1990, Vásquez & Vega 2004b). Over the last 30 yr, studies of seaweed ecology have traditionally focused on conspicuous genera such as Lessonia, Durvillaea and Macrocystis. Their distribution, reproductive phenology and recruitment patterns as well as ecological functions on the rocky shores have been well documented for communities between 40°S and 20°S (Santelices et al. 1980, Moreno & Sutherland 1982, Santelices & Ojeda 1984, Vásquez 1992, Westermeier et al. 1994, Tala et al. 2004 and references therein). These brown algae represent the major biotic factors structuring the intertidal and subtidal communities, directly affecting coastal processes through changes in species diversity, biomass and PP (Ojeda & Santelices 1984, Santelices & Ojeda 1984, Vásquez & Santelices 1990, Santelices 1991, Vásquez 1992, Camus 1994a, Ortiz 2003, Tala & Edding 2005, Vega et al. 2005). Because the coastal scenarios along this region are relatively similar in terms of prevailing oceanographic conditions, it may be argued that most macroalgae are exposed to the same environmental factors and thus show similar adaptations. However, considering the phenology, algae respond to environmental variability basically in two ways (sensu Kain 1989): (1) ‘season anticipators’ can grow and reproduce in a strategic annual rhythm suitable for the species, which does not necessarily require suitable environmental conditions but rather an environmental trigger (e.g., day length, nutrient level; Lüning & tom Dieck 1989); and (2) ‘season responders’, by contrast, grow and reproduce when environmental conditions are favourable (e.g., suitable light conditions). Whether these two life-strategy mechanisms operate in algae along the HCS has not been well addressed; however, some patterns of abundance and reproduction as summarised in Figure 21, based on large geographic distributional scales (described, e.g., for Lessonia, Durvillaea, Macrocystis and some genera of Rhodophyta) may be associated with ‘season anticipation’ or ‘season responses’. However, taking into account that upwelling processes, ENSO or human activities (e.g., pollution due to mining discharges) modify local environmental conditions, the existence of other adaptive mechanisms to withstand these perturbations cannot be ruled out. With the exception of the well-documented consequences of EN on population dynamics of the dominant kelp Lessonia (Camus 1994b, Martínez et al. 2003, Vega et al. 2005), questions related to functional strategies of other macroalgal assemblages during and after mass extinction events within the HCS have been less addressed. A latitudinal asynchrony in biological processes would be related to different climatic regimes affecting life-history traits (Mediterranean vs. desert climate in southern-central and northern Chile, respectively). However, local environmental conditions exert a strong pressure on the observed patterns and the later recruitment, mainly related to seasonal grazing intensity, habitat distribution (intertidal versus subtidal) and water movement (Santelices & Ojeda 1984, Camus 1994a, González et al. 1997, Buschmann et al. 2004b, Tala et al. 2004, Vega et al. 2005). In this sense, species that reproduce continuously may show advantages in unpredictable environments compared with strictly seasonal species. Thus, the knowledge about environmental thresholds for life-history adaptations (expression of functional responses to optimise resource use, e.g., light, temperature and nutrients, or to withstand environmental stress) is crucial in understanding the biogeographical patterns of macroalgae. 274

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Phaeophyceae

Rhodophyta

L.n. (∼20°S) −20° C.ch. (∼30°S)

L.t. (∼30°S)

G.ch. (∼30°S) M.i. (∼30°S) G.p. (∼30°S) G.k. (∼30°S)

−30°

D.a. (∼32°S)

L.n. (∼32-33°S) D.a. (∼32-33°S)

M.I. (∼35°S) −40°

Southern latitude

C.c. (∼30°S) Intertidal Subtidal

M.I. (∼39°S)

L.n. (∼39°S)

D.a. (∼39°S)

−50°

M.p. (∼41°S)

100% 50% Sp Sm A W

Figure 21 Seasonal patterns of reproductive phenology in macroalgae along latitudinal gradients in Chile. Small inserts show seasonal phenology: Sp, Spring; Sm, Summer; A, Autumn; and W, Winter. Information was adapted from: Lessonia nigrescens (L.n.) (Camus 1994a, Westermeier et al. 1994); L. trabeculata (L.t.) (Tala et al. 2004); Macrocystis integrifolia (M.i.) (Buschmann et al. 2004b); Glossophora kunthii (G.k.) (García 1996); Durvillaea antarctica (D.a.) (Santelices et al. 1980, Westermeier et al. 1994, Collantes et al. 2002); Macrocystis pyrifera (M.p.) (Buschmann et al. 2004b); Chondrus canaliculatus (C.c.) (Vega & Meneses 2001); Chondracanthus chamissoi (C.ch.) (González et al. 1997); Gelidium chilense (G.ch.) (Dantagnan 1993); Gastroclonium parvum (G.p) (Rivera 1992); Mazzaella laminarioides (M.l.) (Santelices & Norambuena 1987, Westermeier et al. 1987).

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Temperature tolerance Thermal adaptations of the life-history stages, mainly for growth, reproduction and survival requirements, are key factors explaining the geographic distribution of benthic algae. In general, two major aspects characterise temperature demands of macroalgae distributed along the HCS: (1) there is a close correlation between the upper survival temperature of gametophytes and the northern distribution limits of the species and (2) algae occurring between 18°S and 40°S show higher temperature tolerance (18–28°C) than algae south of 40°S (17–23°C), coinciding with the latitudinal influence of the HCS and the boundaries of the two traditionally recognised biogeographic regions (ChileanPeruvian and Magellan provinces) (Santelices 1980, Wiencke & tom Dieck 1990, Peters & Breeman 1993, Santelices & Marquet 1998, Martínez 1999). For example, brown algae with Antarctic/ subantarctic distribution commonly found between 18°S and 40°S (e.g., Adenocystis utricularis and Scytothamnus fasciculatus) have maximal survival temperatures close to 18°C and 24°C (Wiencke & tom Dieck 1990). These lethal values are above the mean monthly temperatures measured around 18°S (14–19.5°C) and 37°S (11.7–15.5°C) (Gorshkov 1985). However, when the upper limit for gametogenesis is regarded, these species do not reproduce at temperatures >13–15°C (Peters & Breeman 1993). Such thermal requirements suggest that they may survive moderate EN episodes, but probably a recovery through sexual reproduction may become limited. In the case of species restricted to the HCS (e.g., the red alga Chondracanthus chamissoi), the growth of both gametophytes and sporophytes increases at temperatures of 25°C, which is 5–6°C higher than water temperature in northern Chile (Bulboa & Macchiavello 2001). This is a known phenomenon in macroalgae and may reflect a reasonable safety limit to survive unpredictable increases of temperature for a long time (e.g., months during EN) or may represent a potential for shifting the distribution boundaries northward. It must be emphasised that most of the macroalgae from northern-central Chile studied so far show a capability of growth at very low temperatures (>10°C), indicating clearly an adaptation to the cooling effect of the HCS and reflecting their subantarctic affinities (Wiencke & tom Dieck 1990, Peters & Breeman 1993, Santelices & Marquet 1998). Physiological and morphofunctional adaptations In general, there are only a few ecophysiological studies addressing adaptations of the life history of macroalgae to varying light and nutrient conditions and they have normally been restricted to the genera of commercial importance (e.g., Lessonia, Gracilaria, Gelidium, Mazzaella and Porphyra) (Oliger & Santelices 1981, Hoffmann & Santelices 1982, Hoffmann et al. 1984, Correa et al. 1985, Hannach & Santelices 1985, Avila et al. 1986, Bulboa & Macchiavello 2001, Véliz et al. 2006). Although physiological performances (measured as growth or photosynthesis) are comparable to those of species from other biogeographical regions, much of the existing information is site-specific and has been gathered from individual species, indicating adaptations to narrow ranges of environmental variability. However, in genera such as Gracilaria and Porphyra, which are exposed to highly changing environmental conditions in enclosed bays, estuaries or upper littoral zones, broader ranges of environmental tolerance may be expected (Gómez et al. 2004, 2005a). Due to its physical configuration, the coast along the HCS is characterised by high energy, and hence physical perturbations such as wave action or sand erosion/accretion fluctuations are important and often govern the population dynamics of various infralittoral algae such as Lessonia, Mazzaella and Gymnogongrus. Thus, algae have developed a suite of morphofunctional adaptations such as alternation of crustose and erect morphs, large size and seasonal regulation of abundance (Santelices et al. 1980, Jara & Moreno 1984, Santelices & Ojeda 1984, Santelices & Norambuena 1987, Gómez & Westermeier 1991, Westermeier et al. 1994, Vega & Meneses 2001). In many cases, these adaptive strategies operate in the early development of the life cycle and in both isomorphic 276

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and heteromorphic phase expressions. Processes such as coalescence of spores (Santelices et al. 1999, 2003), regrowth from crusts or vegetative propagation (Hannach & Santelices 1985, Gómez & Westermeier 1991, Macchiavello et al. 2003), selective mortality of early developmental stages (Martínez & Santelices 1998), differential phase ratios (Vega & Meneses 2001) and synchronisation of spore release (Edding et al. 1993, Tala et al. 2004) have been described in algae from northerncentral Chile, which are related to potential selection under changing environmental conditions. While the seasonal and latitudinal gradients in environmental conditions along the HCS are recognisable, the magnitude of their impact on the physiological and reproductive biogeography of benthic algae remains diffuse. Therefore, comparative studies focused on assemblages from different sites along the HCS are needed in order to define, for example, the environmental thresholds involved in reproductive fitness, physiological adaptation and recovery capacity. A special case: enhanced solar radiation Ozone depletion (with the concomitant increase of UV-B radiation) over the Antarctic region, which in spring can reach areas as far north as 36°S, has opened the debate about its consequences on the marine biota of cold and temperate regions (Madronich et al. 1995, Sobolev 2000). Short wavelengths (UV-B) affect photosynthesis in different ways and have detrimental effects on DNA and other key cell components (Bischof et al. 2006). Recent studies indicate a potential impact of current solar UV radiation on photosynthesis of intertidal macroalgae from the southern limit of HCS (39°S; Gómez et al. 2004, Huovinen et al. 2006). In northern Chile (30°S), zoospores, gametophytes and embryonic sporophytes of subtidal Lessonia trabeculata and the intertidal L. nigrescens show elevated sensitivity to UV exposure, leading to high spore mortalities and decreases in germination under current UV doses (Véliz et al. 2006). In general, UV sensibility of early stages correlates with the depth-distribution patterns of the parental sporophytes, suggesting that this factor may play a relevant role in depth zonation of benthic algae in this region (Gómez et al. 2005b). Recent surveys indicate that intertidal species display various photoprotective mechanisms, in particular the ‘dynamic photoinhibition’, regarded as a down-regulation of the photosynthetic apparatus to quench the impact of excess energy (Gómez et al. 2004). Some intertidal algae also have noticeably high contents of UV-absorbing substances (e.g., mycosporine-like amino acids) (Huovinen et al. 2004). Whether algae from different latitudes exhibit a differential susceptibility to UV radiation in the context of the HCS remains unclear and future work should give new insights into the ecophysiological strategies of macroalgal assemblages in scenarios of climate change.

A brief history of exploitation of natural resources in the HCS First coastal settlers Evidence of coastline occupation off Peru and Chile may date from as early as 11,000 yr ago (Llagostera 1979, Muñoz 1982, Báez et al. 1994, Keefer et al. 1998, Sandweiss et al. 1998, Méndez 2002, Méndez & Jackson 2004, Santoro et al. 2005). One of the first studies of the earliest human habitation along the coast of northern-central Chile (Arica to Coquimbo) was carried out by Junius Bird in 1941 during excavations of shell middens. This author (Bird 1943, 1946) showed that the earliest evidence of human settlements on this coast went back to ~6000 yr before present (BP) and people used highly specialised artifacts with an efficient maritime adaptation. According to Santoro et al. (2005) evidence of the earliest inhabitants (~11,000 yr BP) is difficult to find since most prehistoric sites are now on drowned landscapes. However, there is clear evidence that coastal populations in northern-central Chile used marine natural resources during the Holocene (Llagostera 1979). It is thought that early fishermen dived in subtidal waters to collect molluscs and they also 277

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speared large fish and marine mammals such as sea lions (Otaria juvata and O. flavescens) (Santoro et al. 2005). A report on the navigation off the west coast of South America carried out by Lothrop (1932) showed artifacts used by aboriginal people of northern Chile. Most remarkable was a raft composed of two cylinders of seal hides tied together to support a small platform on top, and while voyages out of sight of land were rarely attempted, it was not uncommon to remain at sea for 2 or 3 days (Lothrop 1932). Llagostera (1979), working between 21°S and 25°S, found evidence of groups of people with the ability to exploit natural resources from coastal waters ~10,000 yr BP, and he found remains of molluscan species such as Concholepas concholepas, Fissurella spp., Tegula atra, Choromytilus chorus, several species of fishes (e.g., Isacia conceptionis and Trachurus murphyi), and semifossilised bones of sea lions and dolphins. Reports from southern Peru suggest specific sites where mainly fish and seabird resources were exploited (Keefer et al. 1998), while at other (more ephemeral) sites they processed mainly molluscs (Sandweiss 2003). Studies from southern Peru and northern Chile demonstrated that the resources exploited by early coastal settlers of the HCS changed with time (Llagostera 1979, Sandweiss et al. 2001), which is taken as an indication of climate change and EN events, causing gradual or abrupt changes in available resources. Similar observations were made in central Chile near 32°S (Báez et al. 2004). For the late Holocene (4000–2000 BP) Méndez & Jackson (2004) reported a high degree of mobility of coastal people in central Chile, who apparently moved between different sites in a region, exploiting the accessible resources at a given site in an opportunistic manner. A systematic study of remains of marine invertebrate fauna from central Chile (Curaumilla, 33°S) defined the ecological role of early inhabitants as shellfish gatherers (Jerardino et al. 1992). According to these authors, they probably modified areas of the rocky intertidal, causing decreases in mean sizes of Concholepas and Fissurella. Interestingly, Llagostera (1979) suggested that the appearance of larger shells of Concholepas in shell heaps is indication of an increasing radius of action and the exploitation of new fishing grounds. This author also remarked that the appearance of some fish species (e.g., cusk eels, locally called ‘congrio’, from the genus Genypterus, which can only be fished at greater depths) around 3000 BP is indication that coastal fishermen started to venture farther out to sea during that time period. In general, prehistoric people used littoral resources in an opportunistic manner, and during the past millennia they increasingly widened their radius of action, improved their navigating skills (rafts) and developed their fishing techniques (fishing nets, hooks). Extraction of marine resources was not only for subsistence of local groups, but also for an intensive transfer of fish toward inland sites (Briones et al. 2005). Local people persisted and exploited marine resources until well after the appearance of the Spanish (Llagostera 1979). The resources collected and captured by prehistoric people are the same that still today play an important role in the fisheries of northern and central Chile.

Artisanal benthic fisheries The present artisanal fisheries in the HCS between 18°S and 35°S are very diverse, comprising ~13 species of algae, ~45 species of invertebrates (molluscs, crustaceans, echinoderms, tunicates) and ~68 fish species (SERNAPESCA 2005). Before the 1980s, fisheries in general were of low level and stable since products only went to local markets and the intensity of exploitation was comparatively moderate (Stotz 1997, González et al. 2006). During the mid-1980s the export of most of the resources was initiated, producing increases in captures, and once the accumulated biomass was used up, the resources remained at low and fluctuating levels (Figure 22). In general, these fluctuations have been interpreted as the classical signs of a badly regulated fishery, as

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described by Hilborn & Walters (1992): discovery of a stock, development of its fishery and subsequent overexploitation and eventually collapse. In order to improve the management status of benthic fisheries (mainly dive fisheries for invertebrates and algae), Chile has established a system of Territorial User Rights for Fisheries (TURF), called Areas de Manejo y Explotación de Recursos Bentónicos (AMERB or Management and Exploitation Areas for Benthic Resources MEABR, which are the diverse names and shortcuts under which they have been described in the literature) (Castilla 1997, Stotz 1997, Castilla & Fernández 1998, Aviléz & Jerez 1999, Bernal et al. 1999, Meltzoff et al. 2002, González et al. 2006). This management tool grants exclusive fishing rights over a defined coastal area to legally established organisations of local fishermen. These areas are exploited according to a management plan, developed by professionals, approved by authority, and then worked by fishermen under the permanent supervision of the administrative authority. This system was initiated in practice by fishermen at the beginning of the 1990s, but legally established in 1997 (Stotz 1997). In general, it has proven to be a good tool to increase stocks and recover depleted fisheries (Stotz 1997, Castilla

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& Fernández 1998, González et al. 2006), albeit it appears to be deficient in particular situations (e.g., Gelcich et al. 2006). Since resource stocks are continuously monitored in management areas, with captures well controlled and registered, it has been possible to begin to understand the underlying nature of fluctuating landings. Contrary to the above-described classical pattern of a badly managed fishery, it has often turned out to reflect the natural variability of the environment of the HCS. Global-scale phenomena, such as EN events, which produce an outburst of some resources and disappearance of others, together with more localised processes of upwelling and current systems, generate a complex, spatially and temporally changing, mosaic of conditions. Fluctuating fisheries are mainly the consequence of this, the fishermen following (and suffering) natural variations, but not always causing them, as generally assumed. The following description of the four most valuable resources fished by artisanal fishermen illustrate this.

Case studies Scallop fishery The scallop fishery can be considered as a ‘boom-and-bust’ fishery, where the ‘boom’ is caused mainly by EN events (Wolff 1987, Stotz 2000, Wolff & Mendo 2000, Stotz & Mendo 2001, von Brand et al. 2006). During EN, recruitment of Argopecten purpuratus is intense, and during following years, given the normal fast growth of the species (Stotz & González 1997), huge stocks of scallops build up, with fluctuations of several orders of magnitude between years (Figure 22A, stock increased with EN 1982–1983; Figure 23A stock increased with EN 1997–1998) (Stotz & Mendo 2001). However, following the increased scallop stocks, the development of similar predator populations and/or the shift of prey preference of predators in response to increased scallop abundance (Ortiz et al. 2003), together with the fishery, leads to an increasing mortality, which finally generates the ‘bust’ (Figure 23A) (Wolff 1987, Jesse & Stotz 2002, León & Stotz 2004). Fishermen are just able to take advantage of part of the EN production before the natural mortality, caused mainly by predation (e.g., by Octopus mimus), but also by mass strandings (González et al. 2001), takes most of the scallops away (Figure 23B). Normal (LN) years are characterised by small and, due to spatially (Aguilar & Stotz 2000) and temporally variable recruitment, fluctuating scallop stocks, which supply a low-level fishery (Figure 22A). Taking advantage mainly of natural recruitment while preventing predation, in northern Chile aquaculture has been able to build up stocks and harvest at levels several times above fishery production (Figure 22A) (Stotz 2000). Surf clam fishery The ‘macha’ Mesodesma donacium fishery also shows boom and bust fisheries along the coast (Figure 22B). In the past, on most sites a relatively stable low-level fishery existed, produced by fishermen working in the intertidal zone. During the mid-1970s fishermen learned also to dive for this resource, which means putting the boat behind the breakers (‘rompiente’), diving, loaded with at least 40–50 kg of lead, through the surge and then working underneath the breakers. This began in Region V (32–35°S). After having depleted the local stocks in Region V, some fishermen came over to Region IV (29–32°S), where the local fishermen quickly learned the same technique. This has generated a tradition of divers, mainly from Regions IV and V, working on the macha along the entire Chilean coast, making use of and depleting macha stocks throughout the country (Figure 22A). However, after the establishment of AMERBs for this resource, other reasons for the depletion became apparent. With the EN 1997–1998 all the macha beds between Arica and Coquimbo, managed conservatively within AMERBs, died off within a few days. The beds in Coquimbo were smothered by mud, washed into the bay by a river flood due to heavy rainfall (Miranda 2001). For 280

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Figure 23 (A) Stock size of the scallop Argopecten purpuratus in an AMERB, (B) the impact of the harvest on the decrease of the same scallop stock, and (C) of a Mesodesma donacium stock in another AMERB, ‘Area de Manejo y Explotación de Recursos Bentónicos’ (MEABR, Management and Exploitation Area for Benthic Resources).

Arica no specific reason was identified, but increased temperatures have been mentioned as a cause of mortality for the same species in Peru (Arntz et al. 1987, 1988). In the Coquimbo area, the only beds left were in Tongoy Bay, which were exploited according to what was considered then a very conservative strategy. However, despite dynamic (and apparently conservative) management, these beds also disappeared (Figure 23C) (Aburto & Stotz 2003). Captures were almost irrelevant compared with the natural decrease (Figure 23C), which was not renewed by recruitment, because larval supply is spatially (Ortiz & Stotz 1996) and temporally very irregular or absent during many years. A similar situation was shown for macha beds managed within management areas in Region VIII, where, due to the almost complete lack of recruitment, the stocks within the AMERBs collapsed by 2004 (Figure 22B) (Stotz et al. 2004). Following their disappearance during or after 281

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EN events, the recovery of local macha beds can be extremely slow, as observed in Peru (Arntz et al. 2006). The ‘loco’ fishery (sold as ‘Chilean abalone’ in international markets) The loco fishery makes use of the muricid gastropod, Concholepas concholepas, described as a top predator in the intertidal systems (Castilla & Paine 1987), but with its fished populations mainly occurring in the subtidal zone (Stotz 1997). In such areas and given that its main prey items are suspension feeders (barnacles, tunicates), the species appears more as a browser, through its prey taking advantage of high PP in the water column near upwelling areas (Stotz 1997, Stotz et al. 2003). Thus, production and consequently fishery landings vary greatly along the coast, with main landing sites coinciding with the most important upwelling areas (Figure 24) (Stotz 1997). Given

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Figure 24 Concholepas concholepas: Variability of larval retention and recruitment along the coast of Regions III and IV, production (average of the period 1985–1995) along the coast of Region IV and harvests of three AMERBs located at coastal areas differing in production (note the scale of y-axis). (Figure adapted from J. González et al. (2004) and Stotz (1997)) Harvest data of AMERB obtained from SERNAPESCA (www. sernapesca.cl); stars show for Region IV the approximate locations of the AMERBs, ‘Area de Manejo y Explotación de Recursos Bentónicos’ (MEABR, Management and Exploitation Area for Benthic Resources).

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its complex reproductive biology, which starts with reproductive aggregations for copula, the laying of egg capsules in which the larvae develop for about 30 days, then followed by a 3-month period of pelagic life, the result is high recruitment variability at temporal and spatial scales, depending on coastal oceanography and topography, and the potential for retention areas (Stotz 1997, J. González et al. 2004) (Figure 24). Larvae settle and metamorphose mainly on adult barnacles covering adult shells (Manríquez et al. 2004) or in association with recently settled barnacles (Stotz et al. 1991b), which may vary greatly between years and sites (Stotz et al. 1991a). This produces a very complex metapopulation structure (J. González et al. 2004, 2006). However, given its long life, with individual growth varying greatly (depending on food availability), fluctuations become partly attenuated when the individuals finally recruit to fisheries at an age between 3 and 4 yr with a size of 10 cm of peristomal opening length (Pérez & Stotz 1992, Stotz & Pérez 1992, Stotz 1997). Thus, while spatial variability of the fisheries is great, the temporal variability at each site becomes partially attenuated (Figure 22C after 1996), with fluctuations at the level of two to three times, which nevertheless means significant changes in the income for fishermen (Figure 24, harvest in AMERBs). The establishment of AMERBs, which was mainly motivated by the closure of the loco fishery at the same time (1989–1992), coincided with a period of increased loco stocks along most parts of the central Chilean coast, probably favoured by the closure and a short period in which fishermen agreed to strictly obey that measure (Stotz 1997). The relationship of the number of fishermen to the size of the management area was at that time generating an acceptable income, but this situation has mostly changed drastically in the following years. At present, many fishermen located at coastal areas with low production are dissatisfied and willing to abandon their AMERBs (compare magnitudes of harvest of AMERBs and number of fishermen in the organisation, shown in Figure 24). Sea urchin fishery The urchin Loxechinus albus fishery in the HCS between 18°S and 35°S is perhaps one of the most variable ones, in this case natural variability probably being increased as a consequence of captures. In central Chile (Regions IV–VIII), urchins are restricted to shallow areas with great surge on the exposed coast, in which the species is partly safe from the predation of the rock shrimp Rhynchocinetes typus (Stotz 2004), a species with abundance and distribution pattern that responds to the variable existence of refuges from its own predators (Caillaux & Stotz 2003). This produces a very patchy distribution of sea urchins. Recruitment occurs mainly inside the adult aggregations, where recruits are protected by the spine canopy (Stotz et al. 1992). Thus, when fishermen, taking advantage of calm weather conditions, reduce the stocks, subsequent recruitment is probably heavily affected. The observation is that once a site is fished for this species, it only recovers about 10 yr later (Stotz 2004). Further north (Regions I–III, mainly between 20°S and 23°S), the fluctuations attenuate slightly and landings increase, as large Macrocystis beds appear (Stotz 2004). There, a more conservative exploitation is carried out inside the AMERBs, conserving patches, and this strategy has allowed an increase in numbers, the sustainable exploitation of which nevertheless still needs to be demonstrated (Figure 22D).

Resource dynamics and management of artisanal benthic fisheries The great natural spatial and temporal variability of resources, and hence fishery production, which characterises the HCS between 18°S and 35°S, poses a great challenge to management. Fishermen, through AMERBs and legal restrictions, are not allowed to move away when a resource goes through a low cycle, as they used to do in the past. Illegal movement, though still occurring, is also increasingly prevented in practice by conflicts with the respective local fishers. This produces 283

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the risk that fishermen continue fishing on a weakened population, perhaps producing its collapse to a degree where recovery is severely compromised. Additionally, the distribution of fishermen along the coast within each region in general is not well adjusted to its spatial productive variability, thus creating great differences of income along the coast, with fishermen’s organisations located at productive sites getting increasingly richer, and others at unproductive sites (as shown with harvest in AMERBs in Figure 24) getting increasingly poorer, which could be a source of conflicts (Gelcich et al. 2005, Stotz & Aburto 2006). The challenge is to advance to an integral management strategy in which fishermen, instead of rotating between fishing zones along the coast, rotate between fisheries of different resources or among other related activities (processing, tourism, etc.) in order to produce income during years or months of poor production. This means a change from a specialist to a generalist strategy, but with very strict control of their numbers, such that they are well adjusted to local production levels. Complementary stock enhancement, using biological and ecological knowledge and aquaculture experience, might help to mitigate natural fluctuations (Stotz et al. 1992, Zamora & Stotz 1994, Pacheco & Stotz 2006). In order to avoid the risk of increased fishing pressure (caused by restricting movements of fishermen) on already weakened populations, the establishment of a network of small reserves along the coast should be considered, which should also aid in reducing natural recruitment variability (see also Stotz & Aburto 2006).

Bioeconomic aspects of industrial crustacean fisheries An important crustacean bottom-trawl fishery exists in northern and central Chile, particularly between Regions II and IV. This fishery, which includes the nylon shrimp (Heterocarpus reedi), yellow squat lobster (Cervimunida johni) and the red squat lobster (Pleuroncodes monodon), is conducted on the continental shelf at depths ranging from ~100 to 600 m. The exploitation of these resources began in the 1950s as fauna accompanying catches of hake Merluccius gayi and was subsequently developed into a fishery specific for these crustaceans (Arana & Nakanishi 1971, SUBPESCA 1999a,b). A growth phase for these fisheries occurred between 1958 and 1968, during which annual landings of nylon shrimp reached 11,000 t. Subsequently, landings declined to less than 3000 t in 1979. Between 1980 and 1986 landings remained below 4000 t, except for 1983, when landings exceeded 6000 t. The last period is interesting in its analysis since it coincided with three fundamental factors: (1) from 1979 to 1982 the exchange rate (Chilean peso/U.S. dollar) was 39 Chilean pesos/U.S. dollar, which produced a depressive economic effect, resulting in the collapse of fisheries companies; (2) in 1983 the occupation of new fishing grounds south of Region IV increased the catch levels above those previously obtained; and (3) from 1984 to 1986 a reorganisation of the fishing fleet occurred due to the opening of the fishery for the red squat lobster (Pleuroncodes monodon) along with an increase in world prices for this resource. Between 1989 and 1991 the fishery was closed in Regions V and VIII, but it remained open in northern Chile. In this northern area after 1986 there was an increase in landings of squat lobster reaching 10,620 t in 1995. After this year there was a clear decrease in these landings, reaching 4000 t in 2000. Since 1995, the three species are subject to catch quotas per boat owner, based on a total allowable catch (TAC), which is determined annually, following direct resource evaluations. A period of difficulty in the crustacean fisheries due to decreasing stocks began in 1999 in northerncentral Chile (SUBPESCA 2005a,b). The TAC per Fisheries Unit of nylon shrimp (Regions II–VIII) dropped over four subsequent years from 10,000 t in 1997 to only 4000 t in 2000 (i.e., a 60% decline). The TAC of the fishery for the yellow squat lobster in Regions III and IV dropped from 6000 t in 1998 to 4000 t in 2000, representing a reduction of 33% during that time period. This substantial reduction in landings caused a major decline in the activities of the fishing fleet and the packing plants. During 2002, some companies closed, with important losses in employment producing socioeconomic impacts in the regions affected (Pérez 2003, 2005). This brief overview 284

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underscores that the fishery of these benthic crustaceans is highly dynamic, driven not only by biological factors, but also by administrative decisions and economic considerations. In the following section some relevant information on the biology of these three species is provided before presenting a case study highlighting the relationship between catch-based stock estimates and species biology.

Basic biology of nylon shrimp and squat lobsters The main bathymetric distribution of these species shows a strong overlap with the OMZ between ~50 and ~600 m, where they occur on gravel and mud bottoms (SUBPESCA 1999a,b). Their latitudinal distribution ranges from 25°S to 39°S (Heterocarpus reedi), from 6°S to 40°S (Pleuroncodes monodon), and from 29°S to 38°S (Cervimunida johni) (Acuña et al. 1997, 1998, Quiroz et al. 2005). Little is known about their food resources. All three species themselves are important prey organisms for demersal fish predators (e.g., flounders and hake), and it has been discussed that the OMZ may represent a refuge from predation (Villarroel et al. 2001). Most information about the biology of these crustacean species is based on analysis of specimens obtained from commercial or research catches. Heterocarpus reedi Available data suggest seasonal migrations with the main concentrations of shrimp found at great depths (>400 m) in austral summer, at shallow depths during austral winter (<200 m), and at intermediate depths in autumn and spring (SUBPESCA 1999a). During austral summer/early autumn, a comparatively large proportion of individuals has a soft carapace, which indicates that moulting is frequent during this time period (SUBPESCA 1999a), possibly accompanied by mating. Following this period, ovigerous females are found throughout winter and early spring (May–November) with a peak abundance in July–August (SUBPESCA 1999a). Larval release is initiated in September. Fecundity has been estimated at 1000–10,000 eggs, and it is generally assumed that each female produces one clutch per year (SUBPESCA 1999a). Catches have consistently shown higher proportions of females than males, with males smaller in size than females. Cervimunida johni Moulting and copulation are thought to occur mainly during the summer months (SUBPESCA 1999b). Embryo incubation extends from May to November, with the highest proportion of ovigerous females observed in July–August (in September–October in the northern zone) (SUBPESCA 1999a,b). Larvae are released during the spring months. Fecundity has been estimated at 500–14,000 eggs in Regions III and IV, although some females in these and other regions have been found with >20,000 embryos. Males reach substantially greater sizes and weights than females, and average size at first maturity (of females) varies substantially among years (Acuña et al. 2005). It is generally assumed that each female produces only one clutch per year, and Arancibia et al. (2005) suggested that C. johni is a slow-growing species, with individuals living up to 11 yr. Pleuroncodes monodon Based on the main occurrence of ovigerous females it has been suggested that mating occurs mainly in late summer/early autumn (Palma & Arana 1997). Embryo incubation extends from April to November, with the highest proportion of ovigerous females observed in July–August (Palma & Arana 1997). All embryonic developmental stages were found between June and October (Palma & Arana 1997), suggesting that not all females mate at the same time. The first planktonic larvae 285

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appeared in June, and early developmental stages were found in the plankton until December (Palma 1994), supporting the suggestion that reproduction is not synchronised among females. Gallardo et al. (1994) reported the first benthic stages in March with very high densities of recently settled squat lobsters in April. Roa et al. (1995) identified nursery areas in places with very low oxygen concentrations from where juveniles migrate to nearby adult habitats. It is generally assumed that females produce only one clutch per year, but the extended reproductive period and the apparently short incubation period of 2–3 months (Palma & Arana 1997) could allow some females to produce more than one clutch per year. Fecundity has been estimated at 1800–34,000 eggs in Region VIII (Palma & Arana 1997), and most females reach sexual maturity at carapace lengths of ~25 mm. Red squat lobsters are estimated to live from 5 to 10 yr (Roa & Tapia 1998).

Biology and stock estimates As can be seen from the preceding section, information on the biology of the nylon shrimp and the squat lobsters is mainly based on demographic data (size at first reproduction, fecundity, sex ratio, per cent ovigerous females, embryo developmental stages), but little information is available on their behaviour. A close analysis of monthly landings suggests possible seasonal changes in behaviour during the year and indicates that it is important to incorporate this information in stock estimates (Pérez 2005). Pérez (2005) proposed that the biomass of the nylon shrimp showed well-defined cycles of availability (sensu Menge 1972), which were not related to its true abundance in biomass (sensu Menge 1972). The first cycle (termed the ‘short cycle’) occurs from September to December and is characterised by a decrease in availability (minimum in October), followed by a recovery (maximum availability in December). This leads to a cycle of greater length (termed the ‘long cycle’), characterised by a decline in available biomass, reaching a minimum in April and followed by an increase again reaching a maximum in August. Reasons for these cycles are not clear, but it has been suggested that they are related to the moult and reproduction. In this sense, a sudden decrease in availability could be due to recently moulted individuals hiding from predators (Pérez 2005). The total biomass of Heterocarpus reedi in Region IV in September 1997 was estimated to be about 5000 t, but not all of these shrimp were susceptible to fishing gear, resulting in an available biomass (to the fishery) of 4200 t (for details see Pérez 2005). The estimated total biomass decreased to 2000 t in August 2000 (Week 143), representing a decline of 60% from that estimated at the initiation of the simulation (Figure 25A). However, the percentage variation in the catch per unit effort (CPUE) was not proportional to the decrease in abundance within periods of maximum availability (Figure 25A). At the beginning of the study period, the CPUE was 0.59 t haul−1, and in August 2000 this decreased to 0.45 t haul−1, representing a decrease of only 24%. In recruitment, at each fishing station in 1997–1998 and 1998–1999 the difference between the control curves and availability allowed the identification of two time windows for recruitment, one of lesser intensity in December and one of greater intensity extending through June and July. This seasonal variation in the availability of the resource to the fishing gear has a direct influence on the population estimates and consequently the determination of TACs. Therefore it was recommended to include this biological information in stock evaluation and to conduct the corresponding research cruises during periods of maximum availability of the resource (Pérez 2005).

Crustacean fisheries and economic considerations Fisheries respond not only to fluctuations in stock abundance but also to economic considerations. From the economic perspective, the annual TAC system has produced an increase in the fishing 286

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effort, measured in terms of hauls, resulting in a decrease in the expected economic benefit based on administrative measures. Pérez (2003) explored the bioeconomic effect produced by the decrease in CPUE in the nylon shrimp and yellow squat lobster fisheries in northern Chile during 1997–2000. A biological-technological simulation model was used by Pérez (2005), which took both physical and biological variables into account. An economic submodel was incorporated into this model in order to carry out an integrated analysis of the crustacean fisheries, which included the subsector involving catches and their processing. The economic results obtained, when integrated with the catch results and size of the stocks, allowed the dynamics of this fishery to be explained in Regions III and IV during 1997–2000, when the catch increased by 21%, and final production increased by 24% (measured as frozen tails), although the variable costs increased by only 11% (Figure 25B). In this same period the fisheries costs increased by 117% and the total production cost increased by 93%. The results showed that part of the economic benefit was lost due to the effect of a decrease in the biomasses of both resources and an excessive increase in the average production costs (due to increased costs of fishing and extraction). This example underscores the importance of incorporating economic reference points in addition to biological (biomass) and fishery variables (CPUE and catch). Furthermore, basic biological data (larval ecology, settlement biology, habitat requirements, seasonal migrations, and mating behaviour) still need to be revealed for these three crustacean species. At present, very little is

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known about the influence of oceanographic factors on recruitment success and stock dynamics of crustaceans from the continental shelf off northern-central Chile. Most current information suggests that their life history is driven by seasonal factors, and presently available data do not permit an examination of the effects of interannual variability in oceanographic conditions (e.g., ENSO) on their population dynamics. Future studies should address these questions in order to achieve a sustainable fishery.

Pelagic fisheries and fisheries management, 1980–2005 The Chilean purse seine fleet mainly exploits five pelagic fish species: anchovy (Engraulis ringens), jack mackerel (Trachurus murphyi), chub mackerel (Scomber japonicus), and Pacific sardine or pilchard (Sardinops sagax) and common sardine (Strangomera bentincki). There were doubts about the taxonomic status of jack mackerel (Stepien & Rosenblatt 1996, Oyarzún 1998), but a recent molecular study revealed that the name Trachurus murphyi should be conserved (Poulin et al. 2004). In the official landing statistics it is also recorded as T. murphyi, but the Technical Reports of the Undersecretary of Fisheries refer to it as T. symmetricus.

History of the catches Aguilar et al. (2000) described the development of the Chilean pelagic fisheries based on the landings of anchovy, jack mackerel and pilchard from 1970 to 1995. Herein the period from 1995 to 2005 (also known as the ‘regulated’ period) is included, which adds two additional species: chub mackerel and common sardine, and their landings since 1980. The total annual landings captured by the Chilean purse seine fleet during the study period showed a steadily increasing tendency from 1980 until 1995, from 3.4 million t to almost 6.9 million t, driven mainly by the increase in jack mackerel landings and secondarily by anchovy landings, which replaced the Pacific sardine, the most important species during the early 1980s (Figure 26). After that, the total annual catch decreased to around the same level found at the beginning of the study period, with the exception of 1998, when both species simultaneously showed a sharp decline in their landings. However, as stated, these are ‘regulated’ landings since catches are the result of fixed total annual quotas and therefore not necessarily representative of resource availability. Administratively, four of the five species included in this analysis are latitudinally assigned to fisheries units, each of which comprises two to five administrative zones: Regions I–II (18°25′S–26°06′S), Regions III–IV (26°06′S–32°18′S), Regions V–IX (32°18′S–39°37′S) and Regions X–XII (39°37′S–56°30′S), and there is a strong difference in landings between the respective fishery units (Figure 26). Therefore, annual landings are analysed by species and these latitudinal fisheries units to visualise their importance in each of them. In the following text each Fisheries Unit is defined by the Regions it contains, e.g., Fisheries Unit I-II. Landing statistics of anchovy show the typical characteristics of engraulids, with successive increases and decreases, attaining highest landings of 2.7 million t in 1994, but landings usually do not surpass 1.5 million t. Anchovy landings are most important in northern Chile (Fisheries Unit I–II) (Figure 27). In contrast to all other species, jack mackerel showed a continuous increase until 1995, when annual landings reached 4.4 million t, after which catches continuously decreased again. Throughout this period, catches in central-southern Chile (Fisheries Unit V–IX) had overriding importance (Figure 27). The highest landings of chub mackerel were attained in 2003 with 0.5 million t. This species has shown a steady increase in landings during the study period. At the beginning of the period, landings of chub mackerel were mainly in northern Chile (Fisheries Unit I–II) but since the year 2000 also increased in central-southern Chile (Fisheries Unit V–IX) 288

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Figure 26 Total annual landings for the five most important pelagic species caught by the Chilean purse seine fleet during the period 1980–2005; left panel shows SST anomaly, total landings and landings of the five species; right panel shows average landings per latitude and year in each of the four fisheries units, calculated for the time period 1980–2005.

(Figure 27). The highest landings of Pacific sardine were attained in 1985 with almost 2.9 million t. During the 1980s this species was the most important small pelagic fish captured in Chilean waters but catches continuously decreased during the late 1980s, reaching very low levels in the mid1990s. The Pacific sardine was most important in northern Chile (Fisheries Unit I–II) but gained proportionally in importance in central-southern Chile (Fisheries Unit V–IX) during the early 1990s (Figure 27). The highest landings of common sardine were attained in 1999 with 0.75 million t. During the 1980s this species was very scarcely captured in Chilean waters but from then on showed a steady increase (Figure 27). Landings of the common sardine were most important in the centralsouthern Chile (Fisheries Unit V–IX).

Relationships with oceanographic variations The coastal areas off the Chilean coast are known for being typical of an EBC system, where upwelling is a characteristic oceanographic feature. Fonseca & Farías (1987) and other authors described the presence of active upwelling centres in several areas of the Chilean coast, like Iquique (Fuenzalida 1990) and Antofagasta in Fisheries Unit I–II (Blanco et al. 2001), Caldera and Coquimbo (Acuña et al. 1989) in Fisheries Unit III–IV, Valparaíso (Johnson et al. 1980) and Concepción (Cáceres & Arcos 1991) in Fisheries Unit V–IX. 289

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Yáñez et al. (1996) conducted a survey to assess the possibility of introducing the use of SST, obtained from NOAA (National Oceanic & Atmospheric Administration) satellite data, for the small pelagic fisheries resources and found significant relationships between species yields and TGRs. Jack mackerel yields were largely related to strong TGRs next to oceanic waters, while anchovy and common sardine yields were mainly associated with the development of coastal upwelling events. Comparison with the SST anomalies shows that landings of anchovy negatively correlate 290

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with SST anomalies (Yáñez et al. 2001); also chub mackerel landings seem to correlate with SST (Figure 27). In contrast, interannual variations in the landings of the other three species seem to be largely independent of variations in SST (Figure 27). The stabilisation of maximum anchovy landings between 1.5 and 2.7 million t during the 1990s and the parallel decline of the landings of the Pacific sardine in the HCS (and the entire southeastern Pacific) reflects another regime shift from the warm ‘sardine regime’ to a cool ‘anchovy regime’ (Chavez et al. 2003, Alheit & Niquen 2004, Halpin et al. 2004). These regime shifts occur on multidecadal scales and are probably related to the PDO, but the mechanisms driving these changes are not yet well understood. Silva et al. (2003) studied the relationship between chl-a concentration, SST, and fishing yields of anchovy, Pacific sardine and jack mackerel in northern Chile during summer and autumn 1999. CPUE superimposed over SST images confirmed that the anchovy has a more coastal distribution than Pacific sardine and jack mackerel, being found in the frontal zone of coastal areas. In the southeastern Pacific, the jack mackerel is a heavily exploited pelagic species, and its presence in the HCS in autumn and winter is assumed to be mainly due to an inshore feeding migration (Bertrand et al. 2004). During warmer years, jack mackerel may immigrate into coastal waters where they are thought to exert high predation pressure on anchovy (Alheit & Niquen 2004). Changes in SST associated with EN events may also affect the migration pattern of jack mackerel, which needs to be taken into account in stock assessment and management plans (Arcos et al. 2001).

Management of pelagic fisheries According to Aguilar et al. (2000) the traditional method used to conserve fish stocks and prevent overfishing is to set a TAC for the fishery. Typically, TACs aim to restrict fishing effort to its MSY (maximum sustainable yield) level. Once these ‘safe biological limits’ are reached, fishing is prohibited. But TACs do not, by themselves, address the overcapitalisation issue. Consequently, many fisheries economists recommend that the designated TAC is distributed to industry participants in the form of individual transferable quotas (ITQs), quasi property rights that restrict additional access to the fishery. Under these rules, failure to acquire an ITQ effectively forces vessels out of the fishery, thereby reducing fishing effort and increasing harvesting efficiency. The Chilean General Law of Fisheries and Aquaculture considers three types of access to the fishery: (1) Full Exploitation Regime, which includes setting an annual quota or TAC by fishing unit, which can be temporally divided during the year and also modified once during that same period (once the full exploitation regime is assigned to a given species no more fishing vessels are allowed to enter the fishery); (2) Recovering Fishery Regime is the fishery under a state of overexploitation, subject to a capture ban of at least 3 yr, to obtain its recovery and where an annual quota (or TAC) can be established; and (3) Early Developing Fishery Regime, which is a demersal or benthonic fishery with open access where an annual quota can be established and where no fishing effort is applied or if it is done it is less than 10% of this quota. In 1993 the first pelagic fisheries in Fisheries Unit I–II were assigned the status of Full Exploitation Regime, and by 2000 this had extended to four of the five fisheries (anchovy, jack mackerel, Pacific sardine and common sardine) and to all fisheries units. The chub mackerel is one of the few commercial species that is still under ‘open access’, with no regulation to date. Alternative management tools have been developed and used in the last years: in 1998, the use of a geographical positioning system for the industrial and artisanal fleets was established; later in 2001 the Límite Máximo de Captura por Armador (LMCA, maximum capture limit per owner) was introduced for the industrial fleet in the fisheries for the small pelagics anchovy, sardines and jack mackerel in all fishery units, which is essentially an ITQ, and at least had the effect of reducing the fishing fleet. The LMCAs are determined using captures (1997–2001) and corrected hold capacity (authorised hold capacity in cubic metres times authorised area length divided by total 291

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length of fishery unit, Law 19.173). This action was set to last until 2002, but was later extended until 2012 (Law 19.849). Finally, in 2004 a similar management tool was established for the artisanal fleet, the Regimen Artesanal de Extracción (RAE, Artisanal Capture Regime), which in this case assigns the artisanal fraction of the Annual Global Quota to one or more artisanal fishermen’s organisations in each fishery unit, which in turn divide it between members. As becomes evident from the preceding paragraphs the currently valid management rules (full exploitation, Global Annual Quota, LMCA, etc.) have been implemented when landings started to decrease or stocks had already dramatically declined. Therefore, fisheries of small pelagic fisheries in the HCS off Chile are presently managed at much lower population levels than they used to be in previous decades. In fact, stocks of anchovy and common sardine in central Chile are considered to be overfished (Cubillos et al. 2002). The interaction between administrative effects on landings and fishery-induced impacts on stocks complicate the detection of direct relationships between environmental factors and fish stocks. In addition to fishery-independent stock surveys, studies of the basic biology of individual species, of biological interactions (predators, competitors, food), and of the role of climatic and coastal oceanography are required in order to improve our understanding of the factors driving the population dynamics and distribution in northern-central Chile.

Aquaculture According to the latest reports published by the Food and Agriculture Organization of the United Nations (FAO 2006), the contribution of aquaculture to the world supply of fish and shellfish “continues to grow faster than any other productive sector of animal food origin”. The world production of aquaculture registered in 2002 rose to 51.4 million t (including aquatic plants), with Asian countries producing 91.2% of this. In 2002, Chile contributed only 1.4% of the world’s total production, but it is among the 10 countries showing the fastest growth in aquaculture production. Fisheries and aquaculture are for Chile one of the most important economic activities with a total income of U.S. $2,246 million in 2003, of which aquaculture contributed U.S. $1600 million. The largest share of the Chilean aquaculture production (80%) is from southern Chile (41–46°S), with salmon and mussels and to a lesser extent oysters, seaweeds and more recently red abalones (Haliotis rufescens) being the most important resources (FAO 2006). Aquaculture activities along the coast of northern-central Chile (18–35°S), although not reaching the same levels as in southern Chile, have been continuously growing during the past two decades (FAO 2006). Given that the shorelines of northern-central Chile are relatively exposed to wave action and fully subjected to the effects of ENSO, it is particularly important to take these factors and interannual variability in oceanographic conditions into account. In fact, all aquaculture centres in northern and central Chile are located in relatively sheltered bays. The main natural resources cultured in northern-central Chile are scallops (Argopecten purpuratus) and seaweeds (Gracilaria chilensis), and their natural populations are also exposed to strong seasonal and interannual variations. Small-scale culture of some other species (bivalves Mesodesma donacium and Tagelus dombeii, gastropods Concholepas concholepas and Fissurella spp., sea urchins Loxechinus albus) has also been attempted but has not reached a commercial stage, mainly due to biological (long larval periods) and logistic (food supply) reasons. Several introduced species are also cultured in northern Chile, namely the Pacific oyster (Crassostrea gigas), which has been cultured on a small scale since 1970, and during recent years increasingly abalones (Haliotis rufescens and H. discus hannai). The main resource cultured during the past two decades in northern Chile is the scallop Argopecten purpuratus. Culture centres are located in bays, namely Isla Santa Maria and Bahía Mejillones (22°S), Bahías Caldera, Calderilla and Inglesa (27°S), and Bahías Guanaqueros and Tongoy (30°S). Standing stocks and productivity in these bays are below those of similar bays in 292

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Peru (Uribe & Blanco 2001). It has long been recognised that natural scallop stocks vary together with ENSO variations, mainly because settlement of small settlers (spat) is strongly favoured during EN events (Narvarte et al. 2001). Due to this relationship, the local scallop industry is affected in a positive way by EN, which can lead to an increase in spat collection by >300% (Illanes et al. 1985). In a research project on the effect of environmental factors on scallop culture, data of water temperature, gonad indices, larval abundance and recruitment (spat collection) were gathered between 1981 and 1984 in Tongoy Bay (Illanes et al. 1985). The EN event led to a temperature increase of 2°C above the pre- or post-EN levels at the sea surface and of 2.5°C at the bottom (20 m). During the EN period, the Gonad Index of adults registered a maximum (25) and a minimum (6.8) with a massive evacuation of gametes, a situation never observed during normal years (Illanes et al. 1985). Similar observations were made in southern Peru by Wolff (1988), who concluded that A. purpuratus is a continuous spawner with spawning peaks during late austral summer and autumn (February–March). Under the unusually high water temperatures during EN 1982–1983 (2–2.5°C above the normal temperatures), the recuperation time between two spawnings was shortened, indicating that maturation was accelerated and spawning probably intensified under these conditions. This interpretation was confirmed by the highest larval concentration found within the period. Wolff (1988) stated that it is not clear along the Peruvian coast that past EN favoured the scallops stocks. The EN 1972 apparently did favour stocks, as catches were significantly higher than during the 3 yr before and after this event, but the weaker EN 1976 did not have the same effect. In 1979, which was a ‘normal’ year, the catches still exceeded the catches of 1972. Limo (in a personal communication to M. Wolff) reported enormous numbers of A. purpuratus during the strong EN 1925 in Ancon Bay, north of Lima. In order to reduce the dependency on natural variations in supply of small recruits, intense efforts have been undertaken to produce settlers in the laboratory (Uriarte et al. 2001), but this only satisfies part of the requirements for scallop spat. The fact that natural spat is still obtained at much lower costs than spat produced in the laboratory may have led to the strong increase in spat collectors observed during recent years in Tongoy Bay (Figure 28). Possibly, the decreasing spat collection efficiency between 1998 and 2001 (when the total number of spat collectors in the bay exceeded 2.5 million bags) is indication that the carrying capacity is reached and that spat collectors are starting to compete for the available settlers. Culture of Gracilaria chilensis in northern Chile is mainly developed on shallow soft bottoms in sheltered parts of the bays (e.g., Pizarro & Santelices 1993). Since sheltered bays are relatively scarce along the cost of northern and central Chile, aquaculture of this seaweed in this area does not reach the amounts harvested in southern Chile. Edding & Blanco (2001) observed a decrease in productivity and yield of ‘agar’ from G. chilensis cultured in Region IV (29°59′S) during EN 1997–1998. This may be more related to the decrease in nutrient concentrations and increase of visibility instead of the higher water temperatures. Furthermore, these authors cited González (1998), who reported that increased wave action during EN resulted in an important reduction of biomass. Growers of G. chilensis in Region IV also reported heavy damage to culture fields on shallow subtidal soft bottoms caused by storms during EN (R. Rojas personal communication). However, Santelices et al. (1984) stated that recovery of Gracilaria sp. after storms is unexpectedly fast due to regrowth of thalli from the portions buried in the sand. Overall, the production of G. chilensis in northern Chile does not seem to be severely affected by ENSO, but is rather determined by stock density and harvesting frequency (Pizarro & Santelices 1993). The relatively limited interannual variability in extracted and cultured biomass (Figure 28) further supports the suggestion that management rather than environmental conditions drive the production of G. chilensis in northern Chile. During recent years first attempts have been made to culture large kelps from northern and central Chile (e.g., Edding et al. 1990, Edding & Tala 2003) in order to satisfy the growing needs of the abalone culture. This is considered particularly important since EN can have dramatic impacts 293

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on the populations of large kelps and other macroalgae in northern Chile (Vásquez 1999). Kelp aquaculture is presently in a developmental phase and has not yet achieved economic importance. Other resources currently being investigated for aquaculture in northern Chile are bivalves from sandy beaches (Mesodesma donacium, Tagelus dombeii). Culture of these bivalves is aiming at stock repopulations after extinction of local stocks (see also Artisanal benthic fisheries, p. 278ff.). Additionally, there are several introduced species that are presently cultured in northern Chile. The Pacific oyster (Crassostrea gigas) was originally introduced in northern Chile in the 1970s, and despite fast growth rates, aquaculture activities then moved to southern Chile because there culture costs are cheaper (bottom culture vs. suspended culture in northern Chile). The production in northern Chile is marginal, and there are only two oyster companies remaining. During the first half of 2004 these produced only 935 t, which represents a 46.8% decrease compared with the production during the first half of 2003. The influence of ENSO on the production of oysters is not well known, but since Pacific oysters have a wide range of temperature tolerance EN effects may be minor (or positive). 294

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Other species introduced to the coast of Chile are abalone, originating from California and Japan. These have been mainly cultured in land-based facilities, but due to an increasing production and limited holding capacities on land, sea-based culture (as already established in southern Chile) is also considered for northern-central Chile. The production of abalones increased from 1 t in 1998 to 342 t in 2005, and for the year 2006 it is expected that the Chilean abalone industry will produce >500 t. Only in Region IV, currently five abalone production centres are established and an additional five centres have solicited permits to initiate new aquaculture activities during 2006. The present abalone production in Chile is mainly based on the red abalone (Haliotis rufescens). However, the Japanese abalone (H. discus hannai), which has a better market value, is also raised, but to a lesser degree since culture technology has higher requirements (and costs) than those for red abalone. Although the land-based abalone culture is not directly affected by variations in environmental conditions, ENs may have severe effects on abalone culture because they can produce strong impacts on the population of large kelp, the main food resource presently used in abalone culture. The lack in supply of fresh food algae may produce serious bottlenecks in the culture of abalone. Some of these problems are occurring presently and the National Fisheries Service (SERNAPESCA) is concerned with the overexploitation of kelp, restricting the extraction from natural kelp beds and promoting research for cultivation and management of seaweeds. This scenario presents important challenges for applied research in the near future. In general, aquaculture in northern and central Chile does not reach the levels it has in southern Chile. Some of the main reasons for this are related to the fact that the coast of northern Chile is (1) mostly exposed to wave action and (2) is strongly affected by important interannual variations in oceanographic conditions. Future efforts should probably focus on the development of landbased culture facilities and integrated systems where animals and algae are produced in combination (Chopin et al. 2001).

Conservation of marine biodiversity and Marine Protected Areas The HCS extending from Ecuador to southern Chile is considered as one of the large marine ecosystems for high-priority attention (Boersma et al. 2004). The growing use of coastal areas by human activities is also increasingly threatening marine biodiversity in the HCS. The most important threats are overfishing, aquaculture, pollution by sewage and mining activities, runoffs of chemicals used for agriculture, oil spills and tourism activities (Vásquez et al. 1999, Fernández et al. 2000). All countries, including Chile, that have ratified the Convention on Biological Diversity (CBD) treaty agreed to develop a network of Marine Protected Areas (MPAs, as defined by IUCN 1994) to ultimately protect 10% of the marine environments by 2012, based on an ecosystem approach (Wood 2006). However, the actual establishment rate of MPAs (4.5% annual increase) reveals that the work plan is unrealistic and will not be achieved before the second half of this century (Wood 2006). The Chilean case is a paradox as its economic exclusive zone (EEZ) corresponds to 17.8% of the Latin-American EEZ and is three times larger than its terrestrial territory (~18% of which is already protected; Pauchard & Villarroel 2002). However, only 0.03% of the Chilean EEZ (0.67% of the territorial sea) is protected as MPAs (CONAMA personal communication). Further, only 14% of the surface area of these MPAs are located within the HCS of northern and central Chile (18°S to 41°S). Considering that ~95% of the Chilean population is located between 18°S and 41°S and the growing human impact in coastal areas, this zone represents one of the greatest challenges for marine conservation. The Chilean fisheries management policy, through creation of Management and Exploitation Areas (AMERBs) for benthic resources from coastal habitats, is focusing on economically important 295

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target species, largely ignoring habitats, ecological interactions and other important ecosystem components (e.g., species dispersal). Although management areas can provide nursery grounds for target species (e.g., the Chilean abalone, Concholepas concholepas, keyhole limpets Fissurella spp. and the red sea urchin Loxechinus albus), this approach is often criticised for its weakness in providing a long-term ecological and economic viability and uncertainty in its efficiency (NRC 2001). The establishment of MPAs has proven to be a useful tool to achieve conservation and preservation goals (e.g., resources, communities, habitats), either as no-take MPAs or multiple-use MPAs (MUMPAs) (NRC 2001). Among the different tools existing in the Chilean legislation for protecting coastal areas, two types of no-take MPAs (marine reserves and parks) were foreseen in the law since 1989 but have only recently been established (Morales & Ponce 1997, Fernández & Castilla 2005). According to the Chilean laws, marine reserves are not focused on ecosystem protection but rather on exploited resources and their habitats and eventually may allow partial extractions if stocks reach very high levels of abundance. Three marine reserves are located between 18°S and 41°S (Table 6): La Rinconada to preserve a genetic stock of the scallop Argopecten purpuratus and Isla Choros-Damas and Isla Chañaral for allowing the recovery of several overexploited benthic invertebrates (and their habitats). Furthermore, two MUMPAs, Isla Grande de Atacama and Lafken Mapu Lahual, have been created by the National Environmental Agency (CONAMA) with international private funding (GEF) as two of the three Chilean MUMPAs. In contrast to the marine reserves, these MUMPAs aim at the conservation of biodiversity integrating socioeconomic interests by creating not only no-take areas, but also areas where fishery and outdoor activities (e.g., diving, ecotourism) are permitted. While no-take zones have not yet been established in the MUMPA Isla Grande de Atacama, they have recently been identified (C. Gaymer et al. unpublished data) and will be declared in the near future. Finally, a small no-take MPA is located at Las Cruces, mainly for scientific purposes. Although very few MPAs exist in Chile, initiatives for conservation are facilitated by the Chilean law, which established an exclusive zone for artisanal fisheries within 5 nautical miles from the shore (e.g., prohibits trawling). The MPAs Isla Choros-Damas, Isla Chañaral and Isla Grande de Atacama in northern Chile have been subjectively chosen through the use of expert criteria, based on the presence of some important ecological communities representing the HCS. The subtidal zone of these three MPAs is characterised by kelp beds of Lessonia trabeculata, L. nigrescens and Macrocystis integrifolia and several invertebrate populations overexploited during decades, and now vulnerable, such as the Chilean abalone Concholepas concholepas and the red sea urchin Loxechinus albus (i.e., extraction prohibited). Moreover, these MPAs are the habitat of some emblematic and/or endangered species, such as the bottlenose dolphin Tursiops truncatus, the sea otter Lontra felina, the Humboldt penguin Spheniscus humboldti and the Peruvian diving petrel Pelecanoides garnotii, and Isla Grande de Atacama is the southernmost site where the wedge-rumped storm-petrel Oceanodroma tethys kelsalli occurs. Biological corridors (Kaufman et al. 2004) permitting those species along with other seabirds to travel between these three MPAs are not included in the present MPA design. Additional MPAs between the marine reserves and the MUMPA would help to ensure undisturbed migration of marine birds and mammals. Ultimately, given the use of both terrestrial and marine environments by some species (e.g., Humboldt penguins) (Fariña et al. 2003b, Ellis et al. 2006), the selection of priority sites for conservation/preservation should integrate both environments, looking for common hot spots that would increase efficiency and reduce conservation costs. MPAs offer a management tool to preserve hot spots of native species diversity; however, these hot spots can be strongly affected by invasion of exotic species which could compromise the effectiveness of MPAs (Byers 2005, Klinger et al. 2006). Introduction of invasive species in Chile becomes a serious concern with the increase of aquaculture (Castilla et al. 2005a). The Isla Grande de Atacama MPA is south of a bay (Bahia Inglesa) where intense scallop culture takes place and where the highest density of the exotic seaweed Codium fragile for the Chilean coast has been 296

Marine Reserve MUMPA

La Rinconada

297 Marine Reserve No-take MPA MUMPA

Isla Choros-Damas

Las Cruces

Lafken Mapu Lahual

Marine Reserve

Isla Chañaral

Isla Grande de Atacama

Status

Name

2005

2005

2005

2005

2004

1997

Establishment year

33°30′ S 40°43′ S

29°15′ S

29°02′ S

23°28′ S 27°10′ S

Mean latitude

44.6

0.15

25

4.3

35.5

3.4

Size (km2)

791

470

20

213

404

Distance to next MPA (km) to south

Scientific research Biodiversity protection

Overexploited species recovery

Overexploited species recovery

Biodiversity protection

Genetic reserve

Main conservation goals

Conflicts with indigenous people

Illegal extractions

Illegal extractions

Illegal extractions

Invasive species

Illegal extractions

Major threats

Kelp beds, marine mammals and birds

Kelp beds, barrens, marine mammals and birds Kelp beds, barrens, marine mammals and birds Kelp beds, barrens, sea grass, marine mammals and birds Kelp beds, barrens

Scallop bed

Main communities and target groups

Table 6 Main characteristics of marine protected areas (MPAs) in the Humboldt Current System (HCS) between 18° and 41°S

Every year since 1982 1 in 2006

1 in 1999

1 in 1999

Every year since 1997 1 in 2002

Biological survey

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reported (Neill et al. 2006). Recently, patches of C. fragile have been observed within the MPA (R. Villablanca personal observations), highlighting the importance of considering connectivity with surrounding areas and the constraints of aquaculture sites for selecting location of MPAs (Micheli et al. 2004). The establishment of MPAs in Chile has so far been based on anecdotal recommendations (e.g., resource management, tourist attractions) rather than scientific criteria. This approach is considered inadequate to effectively protect biodiversity (Meir et al. 2004, Sutherland et al. 2004). Current strategies for implementing MPA networks require a systematic planning conservation method to identify optimal sites for protection of biodiversity (Sayre et al. 2000, Beck & Odaya 2001). The first step in planning an MPA is the assessment and mapping (Geographic Information System — GIS) of the coastal marine biodiversity, the physical environment and major threats (e.g., human uses) and then the identification of priority sites using Decision Support Systems (DSS) based on algorithms (Sala et al. 2002, Leslie et al. 2003). A DSS based on species richness has been used to identify priority areas for marine vertebrate conservation along the Chilean coast (Tognelli et al. 2005). Habitat classification is generally considered as the conservation goal in the DSS (Roberts et al. 2003). However, benthic surveys along the Chilean coast (C. Gaymer & C. Dumont unpublished data) revealed that communities are probably more appropriate to characterise the benthic environment and consider the ecosystem processes (e.g., trophic cascades; Shears & Babcock 2003), ecological interactions (e.g., predator-prey; Micheli et al. 2004) and population connectivity (e.g., larval dispersal; Palumbi 2003). Moreover, there is an urgent need for more scientific information in Chilean marine biodiversity (e.g., there is a lack of taxonomic expertise), population connectivity (e.g., identifying source and sink populations) and ecological processes (in particular species interactions in subtidal habitats are poorly studied). Although ecological knowledge is a key component in developing MPAs, the management effectiveness is the most important challenge for the success of an MPA (Mascia 2004, Pomeroy et al. 2004). A major difficulty arises from the way in which marine reserves and MUMPAs have been established in Chile. The former were created by an imposition from the central authority (fisheries ministry) without consulting the stakeholders, who are mostly in disagreement with this new status. This establishment strategy has turned enforcement into a complicated task for the fisheries authority, and this may turn into a major threat for the success of present and future MPAs. For example, since its creation in 1997, the marine reserve La Rinconada has been affected by frequent illegal extractions of scallops (M. Avendaño personal observations). Social conflicts due to lack of communication between the authority and the stakeholders are also present within the recently created marine reserves Isla Choros-Damas and Isla Chañaral. In contrast, a participative process took place in the establishment of the MUMPA Isla Grande de Atacama, incorporating most of the relevant actors (i.e., administrative authorities, stakeholders, managers, scientists and fishermen), offering the opportunity to evaluate contrasting interests in order to reduce potential conflicts. Social costs should be evaluated before the establishment of MPAs and a formal educational process should be implemented by the authorities to teach the importance of MPAs in developing sustainable exploitation of resources (Mascia 2004). The government should also negotiate compensations and propose alternative activities (e.g., tourism) to fishermen, who are the ancestral users of the MPA areas, and avoid creating high expectations (Mascia 2004, Sobel & Dahlgren 2004). Ideally, an international MPA network (from Ecuador to Chile) including the connectivity among MPAs should be implemented to effectively preserve biodiversity in the HCS. This should be achieved using the support of international tools and agreements, and international non-governmental organisations (NGOs) in order to co-ordinate and improve the quality of scientific information and reduce the costs (Balmford et al. 2004). Moreover, the Chilean government must contribute to funding for implementation and functioning of MPAs as successful conservation experiences from all over the

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world have demonstrated that self-funding (e.g., through tourism business) is not feasible (Balmford et al. 2004).

Outlook, long-term research vision and future research frontiers An outlook of the pressing scientific questions and tasks to be addressed in the short/mid-term future (during the next decade) within the HCS of northern and central Chile should, as a minimum, include (1) studies of ocean–atmosphere interactions and offshore oceanography, (2) research in inshore and offshore oxygen-minimum ecosystems, (3) research on inner inshore coastal oceanography and benthic-pelagic linkages, (4) development of an ecosystem-based adaptive resource management approach to fisheries that integrates socioeconomic aspects, (5) implementation of a coastal overarching network system for marine conservation-management, (6) novel approaches in coastal mariculture, (7) studies of marine non-indigenous species (NIS), (8) marine molecular biology, particularly on genomics, and (9) training of Chilean marine taxonomists. A long-term HCS vision (during the coming two decades) should also, as a minimum, include (1) intensification of precautionary and integrative ecosystem management; (2) implementation of a high-sea conservation policy; (3) intensification of research on the continental slope, deep-sea and abyssal ecosystems; (4) scientific and technological research on deep-sea gas (methane) hydrates; and (5) evaluations of the effects of future climate change.

Short/mid-term scientific outlook Research on ocean–atmosphere interactions and offshore oceanography The HCS offers unique opportunities for offshore oceanographic studies (e.g., Strub et al. 1998) and considered as a whole, Chile and Peru represent between 15% and 20% of the world’s fishery landings. Large-scale fluctuations in ocean climate (ENSO and the PDO) dominate interannual and interdecadal variability in the ocean, which in turn are linked to upwelling and climate changes (Chavez et al. 2003) and are considered key elements in the HCS functioning. Upwelling systems presently are experiencing ‘anomalous changes’ such as profound changes in the physical and biogeochemical properties in the California Current Systems (Freeland et al. 2003, Grantham et al. 2004), massive nitrogen loss in the Benguela upwelling system (Kuypers et al. 2005), and hydrogen sulphide eruptions in the Atlantic Ocean off southern Africa and linked abrupt degradation of upwelling systems (Bakun & Weeks 2004, Weeks et al. 2004, Arntz et al. 2006). Such interannual and decadal variability and anomalous changes may intensify due to global climate changes, which will also affect the HCS, causing important changes in productivity, biogeochemical cycling and fisheries. Research on these and related oceanographic topics is urgently needed for the HCS. Research on inshore and offshore oxygen-minimum ecosystems Oxygen-minimum zones (OMZs) in the ocean generally form along the EBCs. The decomposition of upwelling-derived biomass in combination with sluggish circulation of mid-water masses strongly enhance the hypoxia conditions, as is the case in the HCS (Levin & Gage 1998, Morales et al. 1999, Levin 2002, Helly & Levin 2004, Ulloa & De Pol 2004). The HCS is characterised by the relative shallowness of the oxygen-minimum layer. The OMZ produces peculiar environments with organisms highly resistant to low oxygen concentrations (Levin et al. 2001, Gallardo et al. 2004). These environments are unique in the HCS and quite different from those off California (Arntz et al. 2006). They offer diverse opportunities to develop frontier research, ranging from

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evolutionary adaptability, primary and secondary production, biodiversity, and species invasions (Castilla & Neill 2007) to impacts on fisheries. Research on nearshore coastal oceanography and benthic-pelagic coupling The nearshore oceanography (coastal border to about 2–3 km offshore) is one of the least-known areas of the world’s oceans. In this regard, during the past 5 yr several lines of research have been developed in central Chile (e.g., Poulin et al. 2002a,b, Kaplan et al. 2003, Wieters et al. 2003, Narváez et al. 2004, Vargas et al. 2004, Piñones et al. 2005) and further research efforts are needed. Unless improvements in the knowledge of nearshore oceanography are achieved, coastal ecology cannot be properly understood. This includes topics such as dispersal of nearshore propagules, benthic resource fisheries and sustainability issues, coastal conservation and pollution impacts. Linking nearshore oceanography and the coastal benthic-pelagic systems remains as a challenge, not only along the HCS (Castilla et al. 2002a, Escribano et al. 2002, Lagos et al. 2002, Marín & Moreno 2002), but also around the world (Shanks 1983, 1995, 2002, Largier 2002). Development of an integrative and adaptive resource management approach to fisheries Pelagic, benthic and demersal marine resource management in Chile is regulated by the Ley de Pesca y Acuicultura 1991 (Fishery and Aquaculture Law, FAL 1991), under the responsibility of the Subsecretary of Fisheries, Ministry of Economy. For the management and administration of fisheries, among other regulations, the law (1) defines the ‘artisanal fishery’ referring to vessels/boats <50 t and <18 m long, separating fishers into four major categories and distinguishing them from the ‘industrial fisheries’; (2) establishes the allocation of a 5-mile wide coastal stretch from 18°20′S to 41°28′S exclusively for the operation of the artisanal fishery fleet; (3) includes an artisanal and industrial National Register Fisher System restricting the spatial movements of fleets; (4) promotes co-management and allocates exclusive AMERBs and TURFs (for artisanal fishery associations); and (5) regulates overexploited stocks via area closure systems and allocation of transferable and non-transferable quotas (Defeo & Castilla 2005, Castilla & Gelcich 2006, Castilla et al. 2007). Hence, it is herein suggested that the 1991 Chilean FAL contains modern and advanced fishery regulation concepts and management tools to potentially promote the rationalisation of Chilean fisheries. An important step forward in this direction must be the introduction of an integrated socio-biophysical ecosystem fishery approach (FAO 2003, Castilla & Defeo 2005). To promote this approach at least three elements need to be considered: (1) the proactive participation of stakeholders (artisanal and industrial) in the co-evaluation of stocks, (2) a proactive government approach to adaptive co-management (e.g., artisanal fisheries, AMERBs and TURFs) via the use of experimental fisheries and further socioeconomic studies, and (3) an increase in the number of Chilean scientists engaged in fishery biology and modelling of resource dynamics. In particular, this last point is considered critical in achieving the stakeholder participation in stock evaluation and management because well-trained scientists and communicators are needed to make information available transparently, while simultaneously consulting and incorporating the perceptions of fishermen. Fostering fisheries sciences would probably also enhance international collaboration, thereby also promoting refereed frontier publications (which presently are extremely scant; Castilla et al. 2005b). Implementation of a coastal overarching network system for marine conservation management A novel and overarching integrative approach to jointly address coastal conservation and management issues along the Chilean coast needs to be implemented in the next decade. The aim will be 300

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to build a coastal conservation management network, including no-take and multiple-use MPAs, sanctuaries, marine concessions and AMERBs (Castilla 2000, Secretariat of the Convention on Biological Diversity SCBD 2004, Fernández & Castilla 2005, Castilla & Gelcich 2006). The present authors believe that, based on present progress, this overarching framework can be achieved in Chile (following guidelines given by the SCBD 2004). In fact, along ~18–41°S at present there are already established >300 AMERBs, two main MPAs for multiple uses (Isla Grande de Atacama and Lafken Mapu Lahual; see CONAMA-PNUD 2006), four declared and active marine reserves and several other categories of protected areas (Fernández & Castilla 2005). Connecting these areas and providing them with one unified administrative umbrella will furthermore meet the goals of the Chilean National Biodiversity Strategy Plan, which attempts to protect 10% of relevant marine Chilean ecosystems by 2012 (Rovira 2006). This overarching network system must also consider external threats such as pollution, which is an important issue in Chile due to pollution resulting from mining activities, agriculture and ship paints (Correa et al. 1999). Novel approaches in coastal mariculture The Chilean coastline along the HCS is very exposed to the open ocean, generally lacking waveprotected embayment, and is thus not particularly suitable for the development of mariculture activities. Exceptions are the bays or bay systems of Mejillones, Antofagasta, Caldera, Coquimbo and Dichato, where scallops, oysters, mussels and Gracilaria are cultured on a limited scale. Inland mariculture has also been developed, particularly for introduced species of the genus Haliotis. If further progress for mariculture in the HCS will occur, the challenge remains in the development of novel technologies for sea bottom or raft culture systems in exposed and offshore systems. Research on marine non-indigenous species The number of NIS along the HCS is surprisingly low when compared with similar upwelling or non-upwelling systems around the world (Castilla et al. 2005a). It has been suggested that this results from a combination of factors such as less-stressed coastal environments or the scarcity of estuaries, gulfs and enclosed bays. Furthermore, it has been hypothesised that it might be linked to the existence of the coastal shallow oxygen-minimum zones (Castilla & Neill 2007). These aspects need further research. Moreover, the rate at which NIS are presently being introduced for aquaculture purposes (e.g., salmon, abalone, algae) needs to be carefully monitored since, for instance, escapees (e.g., salmon) from culture pens may impact native species and communities (Buschmann et al. 2006b). The potential for the introduction of diseases and pests into HCS coastal environments, linked to the development of aquaculture (e.g., Radashevsky & Olivares 2005, R.A. Moreno et al. 2006b, Neill et al. 2006), must also be monitored. Research in marine molecular biology, particularly on genomics The use of molecular biology techniques in marine organisms is seen for Chile as a new research frontier (Castilla et al. 2005b), allowing a range of questions to be addressed, covering evolutionary biology, taxonomy and phylogeny (e.g., Letelier et al. 2003, Véliz et al. 2003, Thiel et al. 2004), ecology and invasive species (Castilla et al. 2002b) and above all population aspects linked to fisheries (Cárdenas et al. 2005). We anticipate that during the next decade this research, particularly on marine genomics, should substantially increase. Training of Chilean marine taxonomists In Chile the training of marine taxonomists must increase. For this the establishment of specific programmes is needed that support the formation and hiring of taxonomic experts, publication of 301

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monographs and field guides, visiting taxonomist programmes with the objective to tackle certain groups and provide publications that allow easy identification of the HCS species, visiting scholarships for national scientists to foreign institutions and museums, increased support for functioning species collections, and an innovative programme to link specimen collections and molecular information. The enhancement of marine taxonomic research in Chile embodies the vision that biodiversity and ecological functioning are key components of the HCS. If this ecosystem is going to be fully understood, and fishery, environmental sustainability and conservation programmes are to be implemented, then the improvement of taxonomic expertise is seen as crucial.

HCS long-term scientific vision Intensification of precautionary and integrative ecosystem management A consideration of the research needs for the HCS indicates that fishery sustainability (subsistence, small-scale and industrial fisheries) will continue for a long time to play a critical role in the economy and human well-being of Chile. Presently, the FAO Code of Conduct Fishery Precautionary Principles and the socio-biophysical ecosystems fishery management approach (FAO 1995, 2003) are the two most novel management tools regarding sustainability of world fisheries. Following the failure of traditional single-species approaches (Defeo et al. 2007), the present authors consider these tools as key elements for an efficient fisheries management in the HCS, and scientists in Chile need to be trained and prepared to properly use them. Therefore, an intensification of scientific research in these areas with respect to the HCS is foreseen. There is a particular need for communication between scientists, users, administrators and politicians. Due to the overriding importance of the HCS for the Chilean society (fisheries, aquaculture, shipping, tourism), integrative management requires one unifying administrative body that oversees, monitors and evaluates all activities within the HCS of Chile. This entity should incorporate representatives of all interest groups and co-ordinate communication among them on both the national and international levels. Implementation of a high-sea conservation policy So far, Chile has not developed a high-sea conservation policy, and there is no policy for unique offshore oceanic realms, such as sea mountains and deep-sea environments, or populations of migratory mammals, birds and fishes. Extensive and international protection measures for highly mobile, migratory marine vertebrates in the dynamic high sea of the HCS are needed. The implementation of such policies remains an important challenge for Chile. Intensification of the research on continental slope, deep-sea and abyssal ecosystems The Chilean portion of the continental slope, deep-sea and abyssal realm of the HCS continue to be some of the least-known oceanographic ecosystems. Aside from isolated studies (e.g., Glud et al. 1999, Thurston et al. 2002), little is known about the OM accumulation, benthic ecology or species diversity in the unique deep trenches off the Chilean coast. During the next two decades or so Chile has to make an effort to improve the understanding of the HCS trenches and also to increase research in offshore oceanography. In order to achieve this goal, the country urgently needs to improve access to oceanic work platforms, including modern research vessels (Castilla et al. 2005b). Scientific and technological research on deep-sea gas (methane) hydrates Gas hydrates are solid crystals formed by a cell of water molecules containing methane, ethane, CO2 or H2S and are found inside pores of sedimentary rocks. Methane hydrates are considered to 302

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be one of the strategic energy compounds for the future (they commonly occur below the permafrost shield and in sediments of ocean margins). Gas methane hydrates are abundant on the continental margins between Papudo (central Chile) to Valdivia (southern Chile). First evaluations in this area indicate gas methane hydrate reserves for 1013 m3 (Morales 2003). The technology to access these hydrates is developing fast, and Chile must be part of the advance and innovation processes. Geological oceanography in Chile is poorly developed (although the number of geologists in the country is high). Therefore the training of marine geologists and the substantial increase of marine geological research in Chile remains an important task (and opportunity) for the future (Castilla et al. 2005b). Evaluation of the effects of future climate change It is known that greenhouse warming and other human alterations may increase the possibility of large and abrupt regional or global changes in climatic events, oceanic circulation (especially related to deep-water formation), sea–ice dynamics (Smith et al. 2006), and wind velocity (Bakun & Weeks 2004). Future wind increases, due to greenhouse effects, may eventually affect one of the HCS key characteristics, such as the rate of upwelling events (Bakun 1990, Bakun & Weeks 2004). For instance, an increase of 15% in wind would represent an increase of ~40% in the typical rate (late twentieth century) of sea upper layer volume replaced per day (water renewal). In the Benguela Current System off Namibia, the present atmospheric greenhouse-related intensification of coastal upwelling appears to be causing the abrupt degradation of the ecosystem (Weeks et al. 2004). Therefore, in a scenario with concentrations of greenhouse gases increasing, climate change (e.g., pattern of wind increase and intensification of upwelling) along the HCS needs to be surveyed under a long-term monitoring scheme.

HCS frontier research opportunities As pointed out there are several research opportunities along the HCS, such as studies of the OMZ and related ecosystems, upwelling and climate change, fishery productivity, co-management, conservation and socio-biophysical approaches to fisheries. In addition there are other very exciting and novel frontier lines of research such as studies of the biogeochemical role of Archaea (Woese & Fox 1977) in the HCS. These organisms are also linked to the OMZ and appear to be particularly abundant in this system. This line of research has recently started in Chile and needs to be strengthened. Further topics that extend far beyond the scope of the present review but that appear to be relevant in the present context are linked to socioecology, anthropology and paleo-oceanography. For example, how do the processes occurring in coastal waters of the HCS affect the terrestrial environments and human populations along the Pacific coast of South America (past, present and future)? Palaeo-oceanography and anthropology can offer exciting insights from the past that will also help to master future challenges.

Conclusions Upwelling is the major driving force of ecological processes in the HCS by promoting high PP both in the plankton and in the nearshore benthos. Additional processes influenced by upwelling are transport of propagules and biogeochemical processes. Besides their high nutrient concentrations, one main feature of the upwelled waters from the HCS along the Chilean coast is that they have low concentrations of dissolved oxygen. This restricts vertical migration of most zooplankters, including of larvae, thereby affecting dispersal. Furthermore, the low oxygen concentrations drive 303

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the dynamics of the benthos communities along the continental shelf and also the remineralisation of OM. There is indication that the upper depth limits of the low-oxygen fauna oscillates with upwelling strength (and EN). In parallel with these oscillations, the lower depth limit of benthos communities from the upper sublittoral zone shifts up and down. This community experiences at its upper depth limit the impact of EN events, where individual species or the whole community may temporarily disappear (due to water temperature, wave action or burial under terrigenous sediments). These extinction events affect the shallow sublittoral and intertidal biota along the HCS in northern and central Chile, but their intensity varies between events, often resulting in differential elimination of particular species, while leaving others unaffected or favouring them. Similar variation in effect size is seen along the latitudinal gradient, where EN impacts (which may occur at all trophic levels) attenuate toward higher latitudes. This leads to different constellations in the interaction webs found in pelagic and benthic communities. Spatial variability in upwelling, which mitigates EN effects, further enhances the variability in the ecological responses. The diffuse pattern of biogeographic limits observed in northern-central Chile is expression of this high variability. Studies of individual growth, reproductive potential, dispersal, recruitment, physiology and population connectivity of organisms from the HCS demonstrate the importance of life-history traits for improving predictability of ecological processes in this area. The high temporal and spatial variability in oceanographic conditions and ecological processes in the HCS of northern-central Chile complicates management and conservation decisions (such as calculation of catch quotas or identification of important areas for recruitment or growth). Recent studies have revealed small-scale variability in reproductive potential, larval supply, recruitment and growth. This indicates that spatially explicit conservation measures (e.g., MPAs) require information of high temporal and spatial resolution. For most parts of the coast of northern and central Chile such data are not available. Given this present gap in information and the urgent need for efficient conservation of this large marine ecosystem, a large-scale approach is proposed. Future conservation measures should also include terrestrial environments such as seabird breeding sites, dune fields and estuarine habitats. Research and administration activities along the HCS face important challenges that require substantial efforts, in particular a continuous and fluent communication among all involved parties. In order to achieve this, a common umbrella organisation that co-ordinates all these activities (and permits rapid exchange of opinion and information) appears to be highly desirable.

Acknowledgements We acknowledge the continuing financial support from FONDECYT, FONDAP, FONDEF, FIP, SHOA, MECESUP and DAAD. We are especially grateful to Jim Atkinson for his patience and careful editing of the manuscript. We also would like to thank all our colleagues who allowed us to refer to their unpublished data and manuscripts.

References Aburto, J. & Stotz, W. 2003. Una experiencia de co-manejo de bivalvos en el marco de una nueva herramienta de administración pesquera en Chile: las áreas de manejo. Policy Matters 12, 200–204. Acuña, E., Arancibia, A., Mujica, A., Cid, L. & Roa, R. 1998. Análisis de la pesquería y evaluación indirecta del stock de langostino amarillo en la III y IV Regiones. Informe Final FIP No. 96-08. Coquimbo, Chile. Acuña, E., Arancibia, A., Roa, R., Alarcón, R., Díaz, C., Mujica, A., Winkler, F.M. & Lépez, I. 1997. Análisis de la pesquería y evaluación indirecta del stock del camarón nailon (II a VIII Regiones). Informe Final FIP No. 95-06. Coquimbo, Chile.

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THE HUMBOLDT CURRENT SYSTEM OF NORTHERN AND CENTRAL CHILE Vidal, J. 1976. Copépodos calanoideos epipelágicos de la expedición Marchile II. Gayana (Zoología) 15, 1–98. Villagrán, C. 1995. El cuaternario en Chile: evidencias de cambio climático. In Cambios Cuaternarios en América del Sur, J. Argollo & P. Mourguiart (eds). La Paz, Bolivia: ORSTOM, 191–214. Villa-Martínez, R. & Villagrán, C. 1997. Vegetational history of the swamp forests of the central Chilean coast during the mid and late Holocene. Revista Chilena de Historia Natural 70, 391–401. Villarroel, J.C., Acuña, E.H. & Andrade, M.J. 2001. Feeding and distribution of the bigeye flounder Hippoglossina macrops off northern Chile. Marine and Freshwater Research 52, 833–841. Villegas, M.J. 2002. Utilización del hábitat por parte de Lontra felina (Molina, 1782) (Carnivora, Mustelidae) en isla Choros (IV Región de Chile) en relación con la abundancia y distribución de presas. Honors thesis, Universidad Católica del Norte, Coquimbo, Chile. Villegas, M.J., Aron, A. & Ebensperger, L.A. 2007. The influence of wave exposure on the foraging activity of the marine otter, Lontra felina (Molina, 1782) (Carnivora: Mustelidae) in northern Chile. Journal of Ethology DOI 10.1007/s10164-006-0024-x. Villouta, E. & Santelices, B. 1984. Estructura de la comunidad submareal de Lessonia (Phaeophyta, Laminariales) en Chile norte y central. Revista Chilena de Historia Natural 57, 111–122. Viviani, C.A. 1979. Ecogeografía del litoral chileno. Studies on Neotropical Fauna and Environment 14, 65–123. von Brand, E., Merino, G.E., Abarca, A. & Stotz, W. 2006. Scallop fishery and aquaculture in Chile. In Scallops: Biology, Ecology and Aquaculture, 2nd edition. S.E. Shumway & G.J. Parsons (eds). Amsterdam: Elsevier Science Publishers, 1293–1314. Walsh, J.J. 1981. A carbon budget for overfishing off Perú. Nature 290, 300–304. Wang, H.J., Zhang, R.H., Cole, J. & Chavez, F. 1999. El Niño and the related phenomenon Southern Oscillation (ENSO): the largest signal in interannual climate variation. Proceedings of the National Academy of Sciences USA 96, 11,071–11,072. Wares, J.P., Gaines, S.D. & Cunningham, C.W. 2001. A comparative study of asymmetric migration events across a marine biogeographic boundary. Evolution 55, 295–306. Weeks, S.J., Currie, B., Bakun, A. & Peard, K.R. 2004. Hydrogen sulphide eruptions in the Atlantic Ocean off southern Africa: implications of a new view based on SeaWiFS satellite imagery. Deep-Sea Research I 51, 153–172. Weichler, T., Garthe, S., Luna-Jorquera, G. & Moraga, J. 2004. Seabird distribution on the Humboldt Current in northern Chile in relation to hydrography, productivity, and fisheries. Ices Journal of Marine Science 61, 148–154. Westermeier, R., Müller, D.G., Gómez, I., Rivera, P. & Wenzel, H. 1994. Population biology of Durvillaea antarctica and Lessonia nigrescens (Phaeophyta) on the rocky shores of southern Chile. Marine Ecology Progress Series 110, 187–194. Westermeier, R., Patino, D., Piel, M.I., Maier, I. & Müller, D.G. 2006. A new approach to kelp mariculture in Chile: production of free-floating sporophyte seedlings from gametophyte cultures of Lessonia trabeculata and Macrocystis pyrifera. Aquaculture Research 37, 164–171. Westermeier, R., Rivera, P.J., Chacana, M. & Gómez, I. 1987. Biological bases for management of Iridaea laminarioides Bory in southern Chile. Hydrobiologia 151/152, 313–328. Wiencke, C. & tom Dieck, I. 1990. Temperature requirements for growth and survival of macroalgae from Antarctica and southern Chile. Marine Ecology Progress Series 59, 157–170. Wieters, E.A. 2005. Upwelling control of positive interactions over mesoscales: a new link between bottomup and top-down processes on rocky shores. Marine Ecology Progress Series 301, 43–54. Wieters, E.A., Kaplan, D.M., Navarrete, S.A., Sotomayor, A., Largier, J., Nielsen, K.J. & Véliz, F. 2003. Alongshore and temporal variability in chlorophyll a concentration in Chilean nearshore waters. Marine Ecology Progress Series 249, 93–105. Wild, C., Hüttel, M., Klueter, A., Kremb, S., Rasheed, M. & Jorgensen, B. 2004. Coral mucus functions as an energy carrier and particle trap in the reef ecosystem. Nature 428, 66–70. Wing, S.R., Botsford, L.W., Largier, J.L. & Morgan, L.E. 1995a. Spatial structure of relaxation events and crab settlement in the northern California upwelling system. Marine Ecology Progress Series 128, 199–211. Wing, S.R., Largier, J.L., Botsford, L.W. & Quinn, J.F. 1995b. Settlement and transport of benthic invertebrates in an intermittent upwelling region. Limnology and Oceanography 40, 316–329.

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MARTIN THIEL ET AL. Wishner, K.F., Gowing, M.M. & Gelfman, C. 1998. Mesozooplankton biomass in the upper 1000 m in the Arabian Sea: overall seasonal and geographic patterns, and relationship to oxygen gradients. DeepSea Research II 45, 2405–2432. Wishner, K.F., Levin, L., Gowing, M.M. & Mullineaux, L. 1990. Involvement of the oxygen minimum in benthic zonation on a deep seamount. Nature 346, 57–59. Woese, C.R. & Fox, G.E. 1977. Phylogenetic structure of the prokaryotic domain: the primary kingdoms. Proceedings of the National Academy of Sciences USA 74, 5088–5090. Wolff, M. 1987. Population dynamics of the Peruvian scallop Argopecten purpuratus during the El Niño phenomenon of 1983. Canadian Journal of Fisheries and Aquatic Science 44, 1684–1691. Wolff, M. 1988. Spawning and recruitment in the Peruvian scallop Argopecten purpuratus. Marine Ecology Progress Series 42, 213–217. Wolff, M. & Alarcón, E. 1993. Structure of a scallop Argopecten purpuratus (Lamarck, 1819) dominated subtidal macro-invertebrate assemblage in northern Chile. Journal of Shellfish Research 12, 295–304. Wolff, M. & Mendo, J. 2000. Management of the Peruvian bay scallop (Argopecten purpuratus) metapopulation with regard to environmental change. Aquatic Conservation-Marine and Freshwater Ecosystems 10, 117–126. Wood, L.J. 2006. Summary report of the current status of the global Marine Protected Area network, and of progress monitoring capabilities. Information document provided to the Eighth Ordinaty Meeting of the Conference of the Parties to the Convention on Biological Diversity. Curitiba, Brazil: UNEP/CBD/COP/8/INF/4. Wyrtki, K. 1973. Physical oceanography of the Indian Ocean. In The Biology of the Indian Ocean, B. Zeitzschel (ed.). Berlin: Springer-Verlag, 18–36. Yaikin, J., Quiñones, R.A. & González, R.R. 2002. Aerobic respiration rate and anaerobic enzymatic activity of Petrolisthes laevigatus (Anomura, Porcellanidae) under laboratory conditions. Journal of Crustacean Biology 22, 345–352. Yannicelli, B. 2005. Distribución y transporte de larvas de crustáceos decápodos en la zona de surgencia costera de Chile central: interacciones entre el comportamiento, tolerancias fisiológicas y períodos de liberación. Ph.D. thesis, Universidad de Concepción, Concepción, Chile. Yannicelli, B., Castro, L.R., Schneider, W. & Sobarzo, M. 2006b. Crustacean larvae distribution in the coastal upwelling zone off central Chile. Marine Ecology Progress Series 319, 175–189. Yannicelli, B., Castro, L.R., Valle-Levinson, A., Atkinson, L. & Figueroa, D. 2006a. Vertical distribution of decapod larvae in the entrance of an equatorward facing bay of central Chile: implications for transport. Journal of Plankton Research 28, 19–37. Yáñez, E., Barbieri, M.A., Silva, C., Nieto, K. & Espíndola, F. 2001. Climate variability and pelagic fisheries in northern Chile. Progress in Oceanography 49, 581–596. Yáñez, E., Catasti, V., Barbieri, M. & Bohm, G. 1996. Relationships between the small pelagic resources distribution and the sea surface temperatures recorded by NOAA satellites from Chile central zone. Investigaciones Marinas, Valparaíso 24, 107–122. Yuras, G., Ulloa, O. & Hormazábal, S. 2005. On the annual cycle of coastal and open ocean satellite chlorophyll off Chile (18–40°S). Geophysical Research Letters 32, L23604, DOI:10.1029/2005GL023946. Zacherl, D.C., Manríquez, P.H., Paradis, G., Day, R.W., Castilla, J.C., Warner, R.R., Lea, D.W. & Gaines, S.D. 2003. Trace elemental fingerprinting of gastropod statoliths to study larval dispersal trajectories. Marine Ecology Progress Series 248, 297–303. Zagal, C. & Hermosilla, C. 2001. Guide to Marine Invertebrates of Valdivia. Valdivia: Universidad Austral de Chile. Zamora, S. & Stotz, W. 1994. Cultivo y producción masiva de juveniles de erizo rojo chileno Loxechinus albus (Molina, 1782) en laboratorio. Investigaciones Pesqueras 38, 37–54. Zamorano, J.H., Moreno, C.A. & Duarte, W.E. 1995. Postsettlement mortality in Phragmatopoma virgini (Polychaeta, Sabellariidae) at the Mehuin marine reserve, Chile. Marine Ecology Progress Series 127, 149–155. Zhang, Y., Wallace, J.M. & Battisti, D.S. 1997. ENSO-like interdecadal variability: 1900–1993. Journal of Climate 10, 1004–1020. Zuta, S. & Guillén, O. 1970. Oceanografía da las aguas costeras del Perú. Boletín Instituto del Mar de Perú 2, 157–324.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 345-405 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE LAURA AIROLDI1 & MICHAEL W. BECK2 1Dipartimento di Biologia Evoluzionistica Sperimentale and Centro Interdipartimentale di Ricerca per le Scienze Ambientali in Ravenna, University of Bologna, Via S. Alberto 163, 48100 Ravenna, Italy E-mail: [email protected] 2The Nature Conservancy and Institute of Marine Sciences, 100 Shaffer Road–LML, University of California, Santa Cruz, California 95060, U.S. Abstract Over the centuries, land reclamation, coastal development, overfishing and pollution have nearly eliminated European wetlands, seagrass meadows, shellfish beds, biogenic reefs and other productive and diverse coastal habitats. It is estimated that every day between 1960 and 1995, a kilometre of European coastline was developed. Most countries have estimated losses of coastal wetlands and seagrasses exceeding 50% of the original area with peaks above 80% for many regions. Conspicuous declines, sometimes to virtual local disappearance of kelps and other complex macroalgae, have been observed in several countries. A few dominant threats have led to these losses over time. The greatest impacts to wetlands have consistently been land claim and coastal development. The greatest impacts to seagrasses and macroalgae are presently associated with degraded water quality while in the past there have been more effects from destructive fishing and diseases. Coastal development remains an important threat to seagrasses. For biogenic habitats, such as oyster reefs and maerls, some of the greatest impacts have been from destructive fishing and overexploitation with additional impacts of disease, particularly to native oysters. Coastal development and defence have had the greatest known impacts on soft-sediment habitats with a high likelihood that trawling has affected vast areas. The concept of ‘shifting baselines’, which has been applied mostly to the inadequate historical perspective of fishery losses, is extremely relevant for habitat loss more generally. Most habitat loss estimates refer to a relatively short time span primarily within the last century. However, in some regions, most estuarine and near-shore coastal habitats were already severely degraded or driven to virtual extinction well before 1900. Native oyster reefs were ecologically extinct by the 1950s along most European coastlines and in many bays well before that. These shellfish reefs are among the most endangered coastal habitats, but they receive some of the least protection. Nowadays less than 15% of the European coastline is considered in ‘good’ condition. Those fragments of native habitats that remain are under continued threat, and their management is not generally informed by adequate knowledge of their distribution and status. There are many policies and directives aimed at reducing and reversing these losses but their overall positive benefits have been low. Further neglecting this long history of habitat loss and transformation may ultimately compromise the successful management and future sustainability of those few fragments of native and semi-native coastal habitats that remain in Europe.

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Introduction Habitat modification, fragmentation and loss are widely considered some of the most serious threats to diversity globally (Sih et al. 2000). In terrestrial environments, understanding and abating the effects of habitat loss and fragmentation are a huge focus in science, conservation and management (Wilcove et al. 1998, Brooks et al. 2002). It has been estimated that, throughout history, humans have severely modified or exploited to complete loss >70% of natural habitats in the habitable portion of the planet (Hannah et al. 1994) and that we are still losing somewhere between 0.5% and 1.5% of wild nature each year (Balmford et al. 2003). Habitat loss is also well recognised as an important threat in the marine environment (Suchanek 1994, Gray 1997, Wolff 2000) but has not been as much a focus of science and conservation as in terrestrial environments. Habitat loss is particularly severe in coastal marine ecosystems, where human activities have been historically concentrated (Suchanek 1994, Lotze 2004, Knottnerus 2005, Lotze et al. 2006, Valiela 2006). Coastal zones occupy <15% of the Earth’s land surface, but they accommodate >60% of the world’s population (EEA 1999a). Globally, the number of people living within 100 km of the coast increased from roughly 2 billion in 1990 to 2.2 billion in 1995 (Burke et al. 2001), and the population living on the coast is projected to double in the next 30 yr with an expected 75% of the world’s population residing in coastal areas by 2025 (EEA 1999a). As human population has increased in coastal areas, so has the pressure on coastal ecosystems through habitat conversion, increased pollution, and demand for coastal resources. Coastal systems provide many important services to humans such as nutrient cycling, food production, provision of habitat/refugia, disturbance regulation, natural barriers to erosion, control of water quality, and nursery grounds. Indeed the global value of services from seagrasses, estuaries and coastal wetlands is estimated to be 10 times higher than that of any terrestrial ecosystems (Costanza et al. 1997). Recent reviews have examined the extent of habitat loss and fragmentation in tropical environments across large regions for coral reefs (e.g., Sebens 1994, Spalding et al. 2001, Pandolfi et al. 2003, Wilkinson 2004) and mangroves (e.g., Burke et al. 2001, Valiela et al. 2001, Alongi 2002, Wilkie & Fortuna 2003). These studies have done much to advance our understanding of the status and trends of tropical marine ecosystems at multinational and global levels and have been influential in galvanising support for tropical science, conservation and management. Our understanding of the status and trends of temperate marine habitats is surprisingly further behind. Few scientific institutions, organisations or agencies have programmes that focus on temperate marine environments beyond a regional level, and almost no non-governmental organisations (NGOs) or agencies have multinational or global programmes that focus particularly on temperate ecosystems such as seagrasses, salt marshes or oyster reefs or the issue of habitat loss. There have been a few broad reviews of the condition of key temperate habitats (e.g., Kennish 2002, Steneck et al. 2002, Thompson et al. 2002, Lotze et al. 2006) and some recent exemplary efforts to pull together global distribution data on seagrasses (Short & Wyllie-Echeverria 1996, Duarte 2002, Green & Short 2003). Nonetheless, huge gaps still remain in our knowledge of habitat loss on temperate coasts and estuaries. This gap is particularly disturbing because these coasts contain some of the most productive, diverse and, at the same time, degraded ecosystems on Earth (Suchanek 1994, Edgar et al. 2000). In Europe, there has been increasing awareness and concern about the degradation of natural habitats (e.g., Laffoley 2000). Many European coastal habitats have been lost or severely degraded, and it is estimated that only a small percentage of the European coastline (<15%) is in ‘good’ condition (EEA 1999a). Unfortunately, there are no comprehensive summaries of the current distribution and status of marine habitats along European coastlines and even less information is available about long-term trends of habitat loss or degradation.

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Aim of the review The aim of the present work is to review up-to-date estimates of large-scale trends in habitat extent, status and loss along European coastlines. Some of the major causes of these losses and some of the E.U.-wide policies aimed at slowing these losses are also discussed. Knowledge of the loss of coastal habitats and the drivers of this change is critical for identifying future directions in the sustainable conservation and management of Europe’s coastlines (Dayton et al. 1998, Jackson et al. 2001, Lotze 2004). The review is organised into three major sections: (1) an overview of the historical use of coastal resources and general impacts to European coastlines; (2) a compilation of data on the current distribution, historical loss, threats and protection measures of coastal habitats within bays, estuaries and near-shore shelf environments of Europe; (3) a discussion of gaps in the data, ecological knowledge and protection measures for these coastal habitats and recommendations for how to address these gaps. The information on the coastal habitats of Europe is widely disparate in its availability and quality. The review of information focuses first and foremost on information that was consistent and comparable at the Europe-wide level. This information was augmented with data from countrywide and within-country surveys and occasionally with information from individual bays, estuaries or sections of country coastlines. The information from these finer levels of resolution mostly provides key and in-depth examples of coastal change and its causes; it was not possible to collect this site-specific information for most areas. When possible, information was collected from the primary literature but much of this information exists in agency reports and online databases and these were often the most common sources of information.

Definitions ‘Habitat’ and ‘ecosystem’ are terms that have often been used inconsistently and interchangeably (e.g., Beck et al. 2001). In this review, ‘habitat’ indicates a focus on the predominant features that create structural complexity in the environment, such as plants (e.g., seagrass meadows, kelp forests), animals (oyster reefs) or other geological features (e.g., rocky reefs, mudflats). ‘Ecosystem’ indicates a focus on the many other plants, animals, natural processes and services associated with the predominant features. These definitions are consistent with those commonly used in European policy (e.g., E.U. Habitats Directive, EC 2003). ‘Habitat loss’ and ‘habitat conversion’ are treated as representations of similar impacts, that is, a reduction in the distribution of natural habitats. Habitat degradation and fragmentation also represent serious impacts but they are not often treated as habitat loss because of difficulties in measurement. Loss clearly occurs when natural habitats such as salt marshes are filled with sediments and blocked from the sea to form agricultural fields. Habitat conversion often occurs when more structurally complex natural habitats are converted to less-complex habitats (e.g., oyster reefs are dredged and mudflats are left). These converted habitats (e.g., dredged mudflats) may still have some natural value, but they exist for artificial reasons, and less structurally complex habitats usually have lower diversity and productivity (e.g., Heck & Crowder 1991, Beck et al. 2001). Areas are rarely converted from less-complex to more complex natural habitats unless there is active habitat restoration, which is treated as habitat gain. Structurally complex habitats are clearly becoming rarer across Europe and the world, and that is recognised in their common treatment in policy, conservation and management. Habitat degradation, such as the invasion of non-native algae into seagrass meadows or ditching in marshes, is also a serious issue that has ecosystem implications and often is a precursor to loss

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Dike 100 m Creek

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Figure 1 Morphology of a natural salt marsh (left) and an artificial salt marsh (right) functioning as foreland to protect a dyke in the Wadden Sea. (From Reise 2005. With permission.) Compared with natural ones, artificial salt marshes are smaller, fragmented, truncated at the landward side and of a simplified structure, although the halophytic vegetation may be similar.

of natural habitats. Degradation is, however, difficult to measure because it represents a decrease in condition, not a change in distribution (i.e., habitat loss). Degradation is particularly difficult to measure at the regional, national and multinational levels considered in this review. Nonetheless it is clear that present-day salt marshes in Europe, for example, are much different from salt marshes of the past, not only because they are smaller (habitat loss), but also because they are much less complex with fewer channels and straighter, less-fractal edges (Figure 1). This degradation results in much less efficient transfer of nutrients and species at this critical terrestrial/marine interface (Minello et al. 1994). Habitat fragmentation falls between loss and degradation. Fragmentation occurs when previously continuous habitats become patchier (e.g., loss of patches of seagrass within a larger bed). In this review, these changes in the habitat are treated as loss when it can be measured, which is generally an issue associated with monitoring resolution because many large-scale surveys and spatial imagery do not capture increases or decreases in patchiness.

General European context European estuaries and coastal areas have a long history of intense human impacts and urbanisation and are among the most severely degraded coastal temperate systems worldwide (Lotze et al. 2006). Europeans have exploited near-shore marine resources since at least the Palaeolithic (e.g., Knottnerus 2005), and during the Roman times European coastal landscapes were far from pristine (Rippon 2000). To improve the habitability of coastal areas and exploit their resources humans 348

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D B

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Figure 2 Native coastal habitats such as oyster reefs (A), salt marshes (B), and seagrass meadows (C) are being squeezed out of coastal zones by many factors including coastal development and defence (D), diking and ditching (E), dredging (F), pollution and excess sedimentation (D, E, F), non-native species (G) and destructive fishing and overfishing (H).

have altered the fluvial sedimentation patterns, controlled the river networks, reclaimed marsh lands and developed agriculture and fishing (Cencini 1998). Heavy exploitation, modification and deterioration of coastal habitats increased significantly during the Middle Ages, when coastal areas became more populated and humans started to systematically transform the coastal environment and commercially exploit its resources (Wolff 1992, Hoffmann 2005), and assumed dramatic proportions during the nineteenth and twentieth centuries, when uncontrolled coastal development, industry and tourism destroyed near-shore habitats and assemblages and deeply modified coastal landscapes and seascapes (Cencini 1998, Reise 2005). This section does not intend to give detailed information on the history of human exploitation of coastal resources or provide an extensive review of every type of impact. Rather, it provides baseline information and some key examples of the major past and present human pressures to European coastlines (Figure 2). This information is relevant to an understanding of how the concentration of population, settlements and economic interests in near-shore coastal areas and bays has produced, and still produces, drastic and probably irreversible changes to native habitats and assemblages (e.g., Lotze et al. 2005). The section also provides a broad overview of the main E.U. and trans-national agreements and policies that have been developed to rectify or reduce damage to European natural habitats and associated species.

Threats to European coastlines The exponential growth of European populations over time (McEvedy & Jones 1978) has driven the historical intensification and multiplication of human impacts on coastal habitats. Since ancient epochs, human densities have peaked along European estuaries and coasts, reflecting their importance for settlement, trade and transport. Many of Europe’s capital cities are on or close to the coast, and altogether there are 280 coastal cities with populations above 50,000 (Figure 3). In the 1990s, approximately 200 million Europeans lived within 50 km of coastal waters (Stanners & Bourdeau 1995; see also EEA 1999a, Frid et al. 2003). Today the coasts of many European countries are among the fastest-growing areas in terms of social and economic development and it is expected 349

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that European coastal areas will face increasing pressures from population growth (EEA 2005, 2006a). The coasts of the Mediterranean Sea, in particular, have always been among the most densely populated regions on Earth, with an estimated 5700–6600 people km−1 of coastline in 2000 (UNEP/MAP/PAP 2001). Along Mediterranean coasts, the population increased by 46% between 1980 (84.5 million) and 2000 (123.7 million), and it is projected to nearly double between 2000 and 2025 (UNEP/MAP/PAP 2001). Increased land use and development of settlements, agriculture, industries, ports, military installations, mines, power plants and other infrastructures has accompanied population growth in European coastal areas. Their development has posed and still poses severe threats to coastal areas (EEA 2006a). Estuarine and coastal landscapes have been deeply modified and transformed in a process that in some regions, such as the western Netherlands, dates as far back as late prehistoric periods, when the first attempts were made to control the flow of water through the construction of dams and sluices (Rippon 2000). During the Roman times, reclamation of coastal marshes became intensive in some regions (e.g., the Severn Estuary; Rippon 1997), and after the tenth to twelfth centuries, large-scale transformations and reclamations took place systematically around Europe (Wolff 1992, Cencini 1998, Rippon 2000, Reise 2005). In the Wadden Sea region, about 350

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15,000 km2 of wetland, lagoons, coastal lakes and tidal flats have been embanked, drained and converted into arable land and pasture over the centuries (Figure 4; see also Wolff 1992, 1997). In the United Kingdom land reclamation has affected at least 85% of the estuaries since Roman times, with losses of intertidal areas ranging between 25 and up to >80% (Davidson et al. 1991); such widespread claim of estuarine land is continuing at rates of 0.2–0.7% yr−1 and affects also estuaries of recognised international wildlife importance included in the Ramsar/Special Protection Area (SPA) network. Data from the CORINE project indicate that 22,000 km2 of the coastal zone in Europe are covered in concrete or asphalt (EEA 2005), and that artificial surfaces increased by almost 1900 km2 between 1990 and 2000 alone (EEA 2006a). The greatest urban developments occur along the Euro-Mediterranean coasts. At present about two thirds of the Mediterranean coastline is urbanised, with this fraction exceeding 75% in the regions with the most developed industries (UNEP/MAP/PAP 2001). More than 50% of the Mediterranean coasts are dominated by concrete with >1500 km of artificial coasts, of which about 1250 km are developed for harbours and ports (EEA 1999c). Growth of cities (particularly tourist developments) and development of industry in some regions (including the French Riviera, Athens, Barcelona, Marseille, Naples, the north Adriatic shorelines) have taken up to 90% of the coastline (Jeftic et al. 1990, Meinesz et al. 1991, Cencini 1998). In Italy, a survey carried out by World Wildlife Fund (WWF) showed that, in 1996, 42.6% of the entire Italian coast was subject to intensive human occupation (areas completely occupied by built-up centres and infrastructures), 13% had extensive occupation (free zones occupied only by extensive building and infrastructures) and only 29% was free from buildings and infrastructures (EEA 1999c). Coastal zone urbanisation will further increase in the near future, with projected increases of 10–20% for most Mediterranean countries (EEA 2006a). Severe decreases of water quality have generally followed population growth with organic pollution as a major driving factor (Jansson & Dahlberg 1999, Diaz 2001, van Beusekom 2005). Excessive nutrient enrichment has been a problem in European waters historically (Islam & Tanaka 2004). Hoffman (2005) reports that archaeological signs of eutrophication from dense, mainly urban populations were detected on the Bodensee shore at Konstanz (Germany) in late-mediaeval times, and that in 1415 a royal ordinance tried to mitigate the low water quality of the Seine below Paris. Nutrient loads started to rise probably around 1700–1800, increased significantly in the early 1900s and steeply accelerated after the 1950s (Lotze et al. 2006). It is estimated that in the Baltic and North Sea regions nitrogen (N) and phosphorus (P) loads from land and atmosphere have increased about 2–4 and 4–8 times, respectively, since the 1940s (Nehring 1992, EEA 2001, Karlson et al. 2002). Historical reconstructions of the preindustrial trophic status in the Wadden Sea suggest about 5-fold greater organic matter turnovers nowadays compared with preindustrial conditions (van Beusekom 2005). The historical development in nutrient loads to the Mediterranean and Black Seas is unknown, but is probably of the same magnitude (UNEP/FAO/WHO 1996, EEA 1999c). For example, in the north Adriatic Sea nutrient load has been increasing since at least 1900 and it markedly intensified after 1930 (Barmawidjaja et al. 1995, Sangiorgi & Donders 2004), with a doubling of nutrient loads in the Po river between 1968 and 1980 (Marchetti et al. 1989). In the Black Sea, concentrations of nitrate have increased 5 times and phosphate 20 times from the 1960s to 1980s (Gomoiu 1992). The increased eutrophication has, as a secondary effect, led to increased oxygen consumption on the sea bed and expansion of areas with hypoxia and anoxia (Diaz 2001, Karlson et al. 2002). In the Black Sea up to 90% of the waters are anoxic. The Kattegat has been affected by seasonal hypoxia since the beginning of the 1980s, which has followed a more than 3-fold increase in N input in the 1960s and 1970s (Rosenberg et al. 1990). Similarly, in the north Adriatic Sea the first signs of hypoxia started around 1960 and developed into severe anoxic events over the past 20 yr (Barmawidjaja et al. 1995, Diaz 2001). Since the middle of the 1980s the phosphorus load has 351

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Figure 4 Maps of about 20 km of coasts in Nordfriesland circa 1500 (top) and in 1965 (bottom). (From Reise 2005. With permission.) Shown is the massive loss of coastal habitats due to land claim. In 1500 Dagebüll and Fahretoft islands were surrounded by low summer dykes. All the area was subsequently embanked (years of progressive diking are indicated in the 1965 map), and tidal flats and salt marshes were drained and converted to arable land and pasture. Pleistocene elevations are hatched, salt marshes stippled, tidal flats dotted, former creeks narrowly dotted and arrows point to sites of shore erosion.

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generally levelled off or declined locally. In some areas such as the North Sea there have been declines in P up to 50% due to improved sewage treatment, reduced industrial discharges and a change to phosphorus-free detergents (Frid et al. 2003). However, there do not yet seem to be discernible European-scale reduction of nitrogen inputs, marine eutrophication or extent of anoxic areas (Karlson et al. 2002). Increased loads of sediments have followed changes in land use both inland and along the coasts of Europe, but long-term data on water turbidity and sediment load are limited even at local scales (Lumb 1990). The greatest impacts were felt when forests were extensively cleared for timber, agriculture or urban developments, which together with interferences in the natural course of rivers caused dramatic acceleration of natural soil erosion (Airoldi 2003). In Europe clearing of forested catchments for agriculture commenced several thousand years ago (e.g., see the historical reconstruction by Cencini 1998). Episodes of accelerated erosion following phases of expansion of arable lands were common during mediaeval times (Hoffmann 2005) and became particularly severe during the nineteenth century (Pukaric & Jorissen 1990, Barmawidjaja et al. 1995). Chemical pollution has also affected European estuaries and coastal waters since ancient times (Islam & Tanaka 2004), particularly in the Mediterranean Sea, where overall 101 pollution ‘hot spots’ have been identified, generally located in semi-enclosed gulfs and bays near important harbours, big cities and industrial areas (UNEP/MAP/PAP 2001, EEA 2006b). Pollution from shipping, oil spill traffic, drilling activities and related accidents is particularly severe in Europe (EEA 1998, 1999c, 2006a, Thompson et al. 2002). Some of the busiest shipping lanes in the world are found in the Baltic Sea, North Sea and Mediterranean Sea (Frid et al. 2003), and about 22% of the total world petroleum traffic passes through the Mediterranean Sea (Jeftic et al. 1990). Marine pollution has become a major concern in Europe, and many E.U., trans-national and national initiatives (see next section, p. 356) have helped to control the disposal of urban and industrial pollutants in coastal areas. Even so, there are still large pollution loads, and long-term contamination of sediments is a major problem. Marine food resources have been used by Europeans since prehistory. At some heavily populated localities, particularly along the Mediterranean shores, the most valued species had severely declined in abundance and size by the end of the Roman era (Hoffmann 2005) with detectable effects on coastal systems (Sala 2004). Exploitation increased during late-mediaeval times, when fisheries became subject to market exploitation, and in subsequent centuries growing food demand and technological progress led to almost unrestricted overexploitation of coastal resources (Hoffmann 2005, Wolff 2005, Lotze et al. 2006). The total fish landings in European sea regions peaked at 12 million t in 1997, but have decreased since in both quantity and quality, down to 7.6 million t in 2002 (EEA 2006a). Disruptive fishing techniques are considered among the major causes of physical destruction of marine coastal habitats at global scales (Watling & Norse 1998, Turner et al. 1999, Thrush & Dayton 2002). In Europe, bottom trawls, bivalve dredging, pneumatic hammering of date mussels, explosives and other disruptive fishing techniques have a long history of use, mainly in estuaries, bays and continental shelf waters (Fanelli et al. 1994, Bavestrello et al. 1997, Lindeboom & de Groot 1998, Cicogna et al. 1999, EEA 1999c, Johnson 2002, Hall-Spencer et al. 2003, Tudela 2004). In Britain, concern about the adverse effects of fishing on marine habitats and wildlife populations dates back to the fourteenth century when it was noted in a petition presented to Parliament in the year 1376–1377 (quoted in Hore & Jex 1880) that “the hard and long iron of the said ‘wondyrchoun’, [an oyster dredge] … destroys the spawn and brood of the fish beneath the said water, and also destroys the spat of oysters, muscles [sic], and other fish by which large fish are accustomed to live and be supported”. The use of trawls and other mobile fishing gears accelerated sharply with the introduction of diesel engines in the 1920s (Watling & Norse 1998). The sea bed in Europe

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has been trawled to a depth of over 1000 m since the 1970s, affecting extensive areas of benthic habitats. Aquaculture, which can have some benefits, has had increasingly adverse effects on coastal habitats. World aquaculture production has increased by >300% since 1984, with growth of about 10% a year in the 1990s, making it the fastest-growing food production activity (Mock et al. 1998). In Europe the culture of fish, shrimp, shellfish and seaweeds has been used as an alternative source of marine food at least since Roman times (Hoffmann 2005), and in regions such as the Po delta area salt marshes were transformed centuries ago into artificial fishing lagoons (Cencini 1998). Unprecedented growth in production has occurred in the last decades (Váradi 2001, EEA 2006a), with significant impacts on bottom habitats and assemblages (e.g., Holmer et al. 2001, EEA 2006b). In 1998, total marine aquaculture production in Europe was >1.3 million t, with most production concentrated in Norway, France, Spain and Italy (Váradi 2001). In the Mediterranean region, marine aquaculture production has increased from 19,997 t in 1970 to 339,185 t in 2002 (EEA 2006b), and the total production of salmon in fish farms (mainly in Norway and Scotland) has increased from 70,000 t in 1990 to 148,000 t in 1996 (EEA 2002) up to 540,000 t in Norway alone in 2003 (EEA 2006a). More recent pressure and threats to European coastlines are from tourism and development of recreational infrastructures, particularly in the Mediterranean region. Before the 1930s, tourism was a relatively minor phenomenon, although it did lead to the beginning of urbanisation in seaside areas (EEA 1999c). From the 1930s onward and especially after World War II, mass tourism started to grow, and the phenomenon was amplified by the development of transport facilities (e.g., Cencini 1998). Nowadays, the Mediterranean coast is the world’s leading holiday destination, accounting for 30% of the world’s tourism, and in some countries coastal tourism represents up to 90% of all tourism. In 1990 alone, 135 million vacationers flocked to the Mediterranean coast, and by 2025 the annual crowd is projected to increase to 235–350 million tourists (EEA 1999c). Effects on coastal habitats have been devastating. In Spain, tourist developments occupy 42% of the entire coast (Jeftic et al. 1990), with peaks in areas such as the Catalonia coast, where tourist developments make up 337 km of the total 580 km. Similarly, buildings, roads, bathing establishments and other recreational facilities located directly over the beaches and sand dunes almost entirely occupy the Italian coast of the north Adriatic Sea (Cencini 1998). The demand for marinas and yacht harbours has been growing all over the Mediterranean coasts, with an estimated growth for France of 1.5–2.6% yr−1 (EEA 2006a). Increased coastal erosion and flooding (often indirectly related to human activities) also pose serious threats to European coastlines (EC 2004). A recent inventory of coastal evolution in Europe undertaken within the CORINE programme showed 55% of the coastline to be stable, 19% to be suffering from erosion problems and 8% to be depositional (Stanners & Bourdeau 1995). Some coastal regions are also gradually subsiding (Bondesan et al. 1995, EEA 2006a), with subsidence sometimes enhanced by groundwater or petrochemical extraction (Bird 1993), while land lift up to 9 mm yr−1 is occurring in areas of the Baltic Sea (HELCOM 1998). Erosion mitigation schemes have been put in place to respond to the problem of coastal erosion, which affected about 7600 km of coasts in 2001 (EC 2004). Defence measures include a variety of hard defence structures (e.g., breakwaters, groynes, seawalls, dykes or other rock-armoured structures), which have proliferated in the second half of the twentieth century, leading to severe hardening of coastal areas and changes in sediment structure (Airoldi et al. 2005). In the north Adriatic Sea, >190 km of artificial structures, mainly groynes and breakwaters, seawalls and jetties (Figure 5), have been built along 300 km of naturally low sedimentary shores (Bondesan et al. 1995, Cencini 1998). This hardening has caused severe losses and alterations of shallow sedimentary habitats (e.g., Martin et al. 2005) and has introduced new artificial habitats, with dramatic effects on native habitats and assemblages (Bacchiocchi & Airoldi 2003, Bulleri & Airoldi 2005). Similar 354

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Figure 5 Coastal defence structures along the highly urbanised Italian shores of the north Adriatic Sea. (Photo by Giorgio Benelli. With permission.)

examples occur in many other European coasts (e.g., Davidson et al. 1991, Anthony 1994, Reise 2005), presumably affecting an overlooked enormous amount of benthic habitats. Overall >15,000 km of coasts in Europe are now actively retreating, some of them in spite of coastal protection works (2900 km), and another 4700 km are artificially stabilised (EC 2004). Globally the problem of erosion and flooding is becoming much more serious because of rising sea levels and an increased storm frequency as a result of global climate change (Bray & Hooke 1997, Valiela 2006). During the past century, the mean global sea level has risen between 10 and 25 cm (Burke et al. 2001). The Intergovernmental Panel on Climate Change (IPCC) Working Group 355

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has projected a global sea-level rise of 15–95 cm by the year 2100. The recession of coastlines is expected to continue even in the absence of new human activities (Bondesan et al. 1995). Approximately 450–600 non-indigenous marine species have been added to European coastal fauna and flora, often facilitated by human-mediated processes such as shipping, aquaculture and aquaria (Reise et al. 2006 and references therein). Some introductions occurred hundreds of years ago, as is the case of the sand-gaper, Mya arenaria, which was probably transported as food from North America to Europe by the Vikings (Petersen et al. 1992). Rates of introduction rose dramatically in the past century, probably in relation to increased shipping and aquaculture. In the Mediterranean Sea, the number of introduced species has nearly doubled every 20 yr since the beginning of the twentieth century (Boudouresque & Verlaque 2002). The number of introduced species is often greatest in estuaries, lagoons, embayments, closed seas, canals and harbours, probably because of low species richness combined with strong anthropogenic change (OcchipintiAmbrogi 2001, Reise et al. 2006). They have profoundly altered European coastal ecosystems and are displacing some native species. One notorious example is the invasion of Caulerpa taxifolia along the coastlines of Spain, France, Monaco, Italy, Croatia and Tunisia (Meinesz et al. 2001) although there is debate about the area of benthos affected (Jaubert et al. 2003). Nevertheless, these invasions do not seem to have caused large-scale extinctions in recipient biota and losses of native coastal habitats (Wolff 2000).

E.U. coastal policies and trans-national agreements The European Union has been involved in efforts to protect the European natural heritage for the past 30 yr (Table 1). At the international level, the European Union has signed a number of important conventions aimed at nature protection, including the Ramsar Convention on the Conservation of Wetlands, the Bonn Convention on Migratory Species, and the Rio Convention on Biological Diversity (CBD), and shares the international commitment of the World Summit for Sustainable Development to establish a globally representative system of marine and coastal protected areas by 2012 (Kelleher et al. 1995, Green & Paine 1997). At the European level, the Bern Convention has led the development of policy and action in nature conservation in Europe. It lists protected species, including a number of marine plants and invertebrates, and requires its parties to prevent the disappearance of endangered natural habitats. The Sixth Environmental Action Plan, setting the European Union’s environmental policy agenda until 2012, highlighted nature and biodiversity as a top priority, and the E.U. leaders in Gothenburg in 2001 launched the E.U. Sustainable Development Strategy to halt the loss of biodiversity in the European Union by 2010. The European Union has adopted a Biodiversity Strategy and Action Plans (currently under review), and Member States have developed — or are developing — their own national strategies and action plans (e.g., U.K. Biodiversity Group 1999). Other policies, in particular the Birds Directive and the Habitats Directive, have been promoted to rectify or reduce damage to European natural habitats and associated species. Following the criteria set out in the directives, each Member State must draw up a list of sites hosting wild fauna and natural habitats and put in place a special management plan to protect them, combining longterm preservation with economic and social activities, as part of a sustainable development strategy. The final aims are the creation of a European Ecological Network of Special Protection Areas (SPAs) and Special Areas of Conservation (SACs), called NATURA 2000, and the integration of nature protection into other E.U. policy areas, such as agriculture, fishery, industry, regional development and transport. Indirect protection to a variety of habitats also comes from a number of E.U. Directives that regulate water quality, including the Dangerous Substances, Shellfish Waters, Integrated Pollution

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Table 1 Summary of main protection initiatives adopted by the European Union and State Members that directly or indirectly address issues related to the protection of European marine coastal habitats and associated assemblages Initiative

Description

Web site

Ramsar Convention

Ramsar Convention on Wetlands, Ramsar (1971). Provides the framework for the conservation and wise use of wetlands of international importance especially as waterfowl habitat. Includes salt marshes and some lagoon systems and marine waters to a depth of 6 m. Convention on the Conservation of Migratory Species of Wild Animals, Bonn (1979). Intergovernmental treaty, aiming to conserve terrestrial, marine and avian migratory species throughout their range. Convention on Biological Diversity, Rio de Janeiro (1992). Provides legal framework for biodiversity conservation and sustainable development. The Jakarta Mandate (1995) leads activity in marine biodiversity management and conservation. Convention on the Conservation of European Wildlife and Natural Habitats, Bern (1979). Aims at preserving wild flora and fauna (including some marine species) and their natural habitats through national programmes using the co-operation between European States. Convention for the International Council for the Exploration of the Sea, Copenhagen (1964). Coordinates and promotes marine research in the North Atlantic, including the Baltic Sea and North Sea, and the Common Fisheries Policy on the protection of the marine environment and the regulation of fisheries. Convention for the Protection of the Marine Environment of the northeast Atlantic, Paris (1992). Merged the 1972 Oslo Convention on dumping waste at sea and the 1974 Paris Convention on land-based sources of marine pollution. It guides the protection of the marine environment of the northeast Atlantic and the identification of priority habitats and species. Six declarations produced at as many International Conferences on the Protection of the North Sea (first in Bremen, 1984). Political commitments to the protection of the North Sea environment, addressing, e.g., species and habitats issues, pollution and fisheries. Convention on the Protection of the Marine Environment of the Baltic Sea Area, Helsinki (1992). Guides the protection of the marine environment of the Baltic Sea from pollution and the identification of priority habitats and species for protection. Joint Declaration of The Netherlands, Denmark and Germany, Copenhagen (1982). Aimed at co-ordinating the protection of the Wadden Sea National Park. In 1997, a Trilateral Wadden Sea Plan was adopted.

www.ramsar.org

Bonn Convention

Rio Convention

Bern Convention

ICES Convention

OSPAR Convention

North Sea Conference Declarations

Helsinki Convention

Trilateral Wadden Sea Cooperation

www.cms.int

www.biodiv.org/convention/default.shtml

www.coe.int/T/E/Cultural_Co-operation/ Environment/Nature_and_biological_ diversity/Nature_protection/

www.ices.dk/aboutus/convention.asp

www.ospar.org

www.sweden.gov.se/sb/d/6363/a/57475; jsessionid=abPgelqjfxJ8

www.helcom.fi

www.waddensea-secretariat.org

(continued on next page)

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Table 1 (continued) Summary of main protection initiatives adopted by the European Union and State Members that directly or indirectly address issues related to the protection of European marine coastal habitats and associated assemblages Initiative

Description

Web site

Barcelona Convention/ Mediterranean Action Plan (MAP)

Amended in 1995 as the Convention for the Protection of the Marine Environment and the Coastal Region of the Mediterranean, Barcelona (1976). Provides legal framework to MAP (1975), under UNEP Regional Seas Programme. Aims to control human impacts (e.g., marine pollution, tourism) and protect the marine and coastal Mediterranean environments. Convention on the Protection of the Black Sea against Pollution, Bucharest (1992). Aims to control and prevent pollution and preserve biodiversity in the Black Sea. Council Directive on the Conservation of Wild Birds. Identifies 194 endangered species and subspecies of birds for which the E.U. Member States are required to designate Special Protection Areas (SPAs). Over 4000 SPAs have been designated to date, covering 8% of E.U. territory. Council Directive on the Conservation of Natural Habitats and of Wild Fauna and Flora. Aims to protect wildlife species and habitats which have conservation that requires the designation of Special Areas of Conservation (SACs). These sites, together with the SPAs of the Birds Directive, make up the NATURA 2000 network, currently covering about 15% of E.U. coasts. Marine habitats broadly defined, and few marine species listed. Council Directive on the Quality Required of Shellfish Waters. Aims to ensure a suitable environment for shellfish harvest. Member States are required to designate coastal and brackish waters that need improvement to support shellfish fisheries. Integrates and updates existing E.U. water legislations (e.g., Discharges of Dangerous Substances, Urban Waste Water Treatment, Nitrates Directive) and provides for water management. Complemented by the recently revised Bathing Water Directive (2006/7/EC). The proposed directive aims to define common objectives and principles at E.U. level to achieve good environmental status of the European marine environments by 2021. It will establish European Marine Regions as management units for implementation.

www.unepmap.org

Bucharest Convention

Birds Directive (79/409/EEC)

Habitats Directive (92/43/EEC)

Shellfish Waters Directive (79/923/EEC)

Water Framework Directive (2000/60/EC) Marine Strategy Directive

Note: All web sites last accessed 8 August 2006.

358

www.blacksea-commission.org

www.ec.europa.eu/environment/nature/ nature_conservation/eu_nature_legislation/ birds_directive/index_en.htm

www.ec.europa.eu/environment/nature/ nature_conservation/eu_nature_legislation/ habitats_directive/index_en.htm

www.europa.eu.int/eur-lex/en/consleg/pdf/ 1979/en_1979L0923_do_001.pdf

www.europa.eu.int/comm/environment/ water

www.ec.europa.eu/environment/water/ marine.htm

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Control, Urban Waste Waters, Bathing Waters and the Water Framework (Table 1). These commitments provide for the regulation of discharges to the sea and have set targets and quality standards covering many metals, pesticides and other toxic substances. In addition to E.U. initiatives, a number of trans-national agreements have been developed to address some conservation issues within the main European seas, including the OSPAR Convention, the North Sea Conference Declarations, the Helsinki Convention, the Trilateral Cooperation on the Protection of the Wadden Sea, the Mediterranean Action Plan and the Black Sea Environmental Programme (Table 1). These programmes generally address water quality and fishery concerns and are not specifically focused on habitat loss and protection, although initiatives have also included commitments toward establishing an integrated network of Marine Protected Areas (MPAs). A more focused initiative for the Atlantic Ocean and Baltic Sea is the commitment of the Joint Ministerial Meeting of the Helsinki and OSPAR Commissions to complete by 2010 a joint network of MPAs that, together with the NATURA 2000 network, would be ecologically coherent. In recent years there has been increasing awareness that past efforts to protect European marine coastal habitats and associated species have been marginal relative to terrestrial environments and that there is limited co-ordination of national and transnational initiatives at a European level. The global MPA database indicates that there are 1129 MPAs in Europe (Figure 6) covering 236,000 km2 (MPA Global 2006). Most of these MPAs are small, and they often lack adequate political and

N

0

250 500

1,000 Km

Figure 6 Marine Protected Areas in Europe (UNEP/WCMC 2006; data extracted August 2006). These MPAs include, for example, nature reserves, national parks, habitat/species management areas, RAMSAR Wetlands of International Importance and World Heritage Sites. The map should be considered indicative of general distribution not areal extent of MPAs.

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financial support and effective enforcement (an extensive review of MPAs in Europe is offered in Kelleher et al. 1995, and specifically for the Mediterranean Sea in Badalamenti et al. 2000). The application of the Birds and Habitats Directives to the marine environment is also presenting major challenges, with significant delays in the selection and designation of the marine sites of the NATURA 2000 network. In response the European Union has set the protection of the marine environment as a major priority and has launched the Marine Strategy Directive, specifically aimed at protecting and conserving marine ecosystems and promoting the sustainable use of marine resources through the development of an integrated, coherent policy for the marine environment. A 2004 conference in Malahide (Ireland) has also set the necessary steps to complete the selection of the marine NATURA 2000 sites by the end of 2008.

Coastal habitats in Europe Despite its relatively small geographic size, Europe has a very long coastline, approximating 325,892 km, including islands (Pruett & Cimino 2000). It comprises the main marine regions of the northeast Atlantic, part of the Arctic, the Baltic Sea, the North Sea, the Mediterranean Sea and the Black Sea (Frid et al. 2003, EEA 2006a). It includes primarily temperate environments as well as some Arctic and subtropical climate environments and covers a variety of geomorphological features (EEA 2002). There are a large variety of extremely productive, diverse and valuable natural coastal habitats, including sea-bed communities of macroalgae and seagrasses, tidal mudflats, salt marshes and biogenic reefs (Stanners & Bourdeau 1995). However, there does not seem to be any comprehensive summary of the current distribution and status of native habitats along European coastlines as a whole. Databases are available or are being prepared for some habitats (e.g., wetlands (Nivet & Frazier 2004) and seagrasses (Green & Short 2003)), countries (e.g., the United Kingdom; Hiscock & Tyler-Walters 2006), and regions (e.g., northwest Europe, the OSPAR regions and the Baltic Sea; ICES 2006a). However, for most European coasts information, if any, is scattered, fragmented and not easily accessible. Even less information is available about long-term trends of habitat loss or degradation. With some notable exceptions (e.g., the Wadden Sea; Lotze & Reise 2005), there is little comprehensive historical information on coastal habitats prior to about 1900 (e.g., Hiscock & Kimmance 2003). In this section published information, from both the scientific and grey (reports, web sites) literature is critically documented for major coastal habitats. The aim was not to reconstruct trends from local historical sources, maps or databases but to cover the most pertinent literature that reported data and information at regional, national, trans-national or European levels. The data summarised in this section are of variable quality and it should not be inferred that they provide a complete picture of the status of European coastal habitats.

Coastal wetlands and salt marshes Current distribution and status Much of the European coastline consists of a chain of extensive estuaries, lagoons and intertidal bays interspersed through stretches of rocky shore and sandy beaches. These coastal wetlands represent some of the most productive and biologically diverse components of near-shore ecosystems (Dugan 1993, Keddy 2000). They provide nursery grounds for commercially important fishes, habitat for shellfish, birds and a variety of biota and play a fundamental role in flood control, nutrient cycling and sediment dynamics. These coastal wetlands are patchworks of sand, mud flats

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and salt marshes. Salt marshes, with their vegetated complex surfaces, form one of the most important components of these wetlands (Adam 1990). Coastal salt marshes are distinctive habitats that can be delineated relatively easily on remotely sensed images (e.g., Ekebom & Erkkilä 2003). In Europe, they have been the target of studies for a long time (see, among others, Dijkema 1984, Allen & Pye 1992, Jones & Hughes 1993, Rippon 2000, Adam 2002). However, quantitative information on their distribution and status is limited even at local scales. Information is often available for the more general category of ‘coastal wetlands’ and here the focus is mainly on this broader habitat type. Accounts exist at regional and local scales but most European countries lack comprehensive inventories of the extent and status of coastal wetlands, with numerous countries lacking almost any organised information on these conspicuous habitats (Table 2). One of the greatest difficulties in completing such inventories is in identifying intact wetlands, that is those wetlands that are not so severely transformed or deteriorated as to be functionally extinct (Allen 2000, Nivet & Frazier 2004). In the Severn Estuary, England, for example, there are a total of about 14 km2 of intact marshes and about 840 km2 of enclosed marshes, and this ratio of intact to enclosed coastal marshes may be common across Ireland, France, the Netherlands, northwest Germany and Denmark (Allen 2000). Other difficulties in estimating coverage include incompatible information (e.g., inconsistent classifications and methodologies) and the lack of co-ordination between different studies or for different wetland types (Nivet & Frazier 2004). A European-scale review of the current distribution and coverage of coastal wetlands has been recently completed by Nivet & Frazier (2004) that integrates and updates previous inventories by Jones & Hughes (1993) and Finlayson & Spiers (1999). According to this inventory, the total cover of marine/coastal wetlands in Europe is around 51,910 km2, and detailed information for individual countries is summarised in Table 2. An inventory of the distribution of European wetlands, including coastal wetlands, is also available in the CORINE database (EEA 1999b). A broad map of the distribution of salt marshes in Europe is given in Figure 7. There is little comprehensive information on the status of coastal wetlands and salt marshes in Europe but there are clear indications that the historical concentration of human activities in European coastal wetlands has deeply modified their structure and function (Dijkema 1984, U.K. Biodiversity Group 1999, Allen & Pye 1992). Adam (2002) points out that nowadays minerogenic sedimentation prevails over autogenic (organic matter) sedimentation in the majority of European marshes. Most wetlands have deeply altered flow regimes (e.g., Cencini 1998, Reise 2005) with associated important effects on sediment dynamics as well as nutrient and salinity regimes (e.g., Allen 2003) and often are heavily polluted (e.g., Trombini et al. 2003). Their vegetation composition is the product of centuries of use and management (e.g., Wolff 2000) and their fauna and flora have been deeply transformed by introduced species (Reise et al. 2006). Historical losses and causes Coastal wetlands have suffered some of the most serious habitat loss rates (Dugan 1993, Suchanek 1994, Rippon 2000, Valiela 2006) and some estimates suggest that over time temperate estuaries and coastal areas may have lost approximately 67% of the wetlands that existed (Lotze et al. 2006). Even when wetlands have not been completely lost, significant degradation of their environment has often occurred, impairing their functions (Dugan 1993, Wolff 2000). Exploitation of coastal wetlands and salt marshes in Europe dates back to at least the Neolithic, when salt marshes were used for salt production (e.g., Rippon 2000). Since then, these habitats have been increasingly exploited, providing location for settlement, agriculture and harbours; source of food, water and raw materials; and a focus for transport, trade and exploration (Rippon 1997,

361

362

n.a. n.a. n.a. 60% ^ since 1870 n.a 50% ^ 86% in twentieth century

8.3 n.a.

n.a. n.a. n.a 8851* n.a. 501 3 813

n.a. 6809*

1011

n.a. n.a.

n.a. <1000 of salt marshes

Belgium BosniaHerzegovina Bulgaria Croatia Cyprus Denmark Estonia Finland France

Georgia Germany

Greece

Iceland Ireland

Italy

25,000 km2 ^ since Roman times 6000 km2 of salt marshes in twentieth century

73% salt marshes in twentieth century n.a. n.a.

n.a. 56.6% ^ in 1950s to 1984

>550–600 km since mid-1900s n.a. n.a.

150

2

Albania

Loss

Cover (km2)

Country

D, S, U, A

D

WQ, D

D, U

2500

>250 salt marshes are located/mapped; 65 km2 of estuarine area reclaimed in the Shannon estuary and 20 km2 in the Wexford Harbour mainly in nineteenth century 60% of the estimated losses occurred in 1938–1984; on the Po river delta, >70% of salt marshes reclaimed in 1870s–1960s; in Friuli Venezia Giulia 631 km2 lost in 1877–1990

In the Wadden Sea, 200 km2 of salt marshes lost during 1950–1984, and only 400 km2 remain today; in the whole Wadden Sea (not only Germany) 14,650 km2 of coastal wetlands lost since the eleventh century (33% of salt marshes in 1930–1987)

Losses of 22.8% ^ between 1950 and 1985 In Bretagne, 40% of coastal wetlands lost since 1960, and 66% of the remaining seriously affected by drainage; ongoing losses in the Languedoc Roussillon wetlands

D D, U

Limited settlement during Iron Age

Regional data/additional information

Country’s coastline shortened by 1168 km (14%)

2000

2000

Exploitation history (yr)

D

D

Cause of loss

Stanners & Bourdeau 1995, Cencini 1998

Curtis & Skeffington 1998, Healy & Hickey 2002

EEA 2006a

Dugan 1993, Rippon 2000, Reise 2005

EEA 2006a

Rippon 2000

Additional references

Table 2 Estimates of actual cover and historical losses of coastal wetlands (and when possible salt marshes) for European countries (and eventual additional regional information), main attributed causes of loss and known history of exploitation

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363

n.a. n.a. n.a. 4043 (85 of salt marshes)

n.a. n.a. 795 5297 5786* n.a. 1041 6000

n.a. n.a. 5966 (450 of salt marshes)

Malta Monaco Montenegro Netherlands

Norway Poland Portugal Romania Russiaa Slovenia Spain Sweden

Turkey Ukraine United Kingdom

n.a. 70% ^ during the past 30 yr n.a. n.a. n.a. 4000 km2 of salt marshes between twelfth century and second half twentieth century n.a. 89.8% ^ n.a. 4000–6600 km2 ^ n.a. n.a. 60% 23% ^ since early 1800s n.a. n.a. >50% of salt marshes since Roman times; 38 lagoons in the latter half of 1980s; >913 km2 of estuary area D, U, E

Coastal/marine wetlands comprise (in km2) 14 sand dune slack, 2658 estuarine waters, 2793 intertidal flats, 450 salt marsh and 50 saline lagoons; salt marsh loss most significant in the 1800s but still ongoing (100 ha yr−1).

Most of the losses occurred in 1965–1990 >50% degraded since early 1800s; in some areas losses up to 80–90%

D, U D

Humans affected salt marshes since at least the Iron Age; earliest dam dates 175 B.C.

70% of salt marshes in the western Algarve lost before 1988

2500

>2500

D D, S, E

D, WQ, U

D

Rippon 1997, 2000, Davidson et al. 1991, Boorman 2003

EEA 2006a

Allen 2003

Wolff 1992, 1997, 2000, Rippon 2000

a

Including Asian Russia.

Note: If not otherwise specified in the reference column, information is derived from Nivet & Frazier (2004) and references therein, while information about history of exploitation is generally derived from Rippon (2000). A = aquaculture, D = drainage/embankment/land claim/conversion (e.g., to agriculture), E = erosion/sea-level rise/coastal squeeze, n.a. = not available, S = altered sediment loads (e.g., from inland deforestation), U = urban/harbour developments, WQ = water quality degradation. Note that the definition of coastal wetland is vague for most countries, and in many cases (indicated as *) only important or large marine wetlands were included. Concerning habitat loss, in many cases (indicated as ^) estimates refer to total wetlands because no distinction was made between coastal and inland wetlands, and often no time span is indicated. Overall, estimates should be considered as broad indications.

1426 413

Latvia Lithuania

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Major complexes Isolated sites >500 ha Small <500 ha, frequent Small <500 ha, scattered

Figure 7 Distribution of salt marshes along European coastlines. (From Boorman 2003. With permission.)

2000, Knottnerus 2005, Wolff 2005). European estuaries support major cities and harbours and have an enormous economical and social importance. This long history of human exploitation has deeply altered these habitats in extent and ecological characteristics. Although historical information exists for some regions or localities (Table 2), knowledge of the extent of loss of coastal wetlands is generally limited. A first overview of E.U. wetlands and their loss was provided by Jones & Hughes (1993), and more recently by Nivet & Frazier (2004), but they could not produce a European-wide estimate because of the scarcity and poor quality of most data available. Denmark, the Netherlands, Germany, Finland, Lithuania, the United Kingdom, Spain, Greece, Italy, France, Poland, Romania and parts of Portugal and Sweden have reported losses of wetland exceeding 50% of original area, with peaks above 80% for some regions (Table 2). These estimates sometimes refer to whole wetlands (without distinction between coastal and inland) and most often cover a relatively small time span (over the last century). However, when historical and archaeological documentation are available, it is evident that significant losses of coastal wetlands started in Roman times and locally even earlier than that (e.g., Wolff 1992, Allen 1997, Cencini 1998, Rippon 2000). Overall, it has been suggested that in the Mediterranean Sea 28,000 km2 (>90%) of coastal wetlands have been lost since Roman times (UNEP/MAP/PAP 2001). Recent estimates have also suggested that approximately two thirds of all European coastal wetlands that existed at the beginning of the twentieth century have now been lost (EEA 2006a). 364

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Some of the best historical records of the loss of coastal wetlands are from the estuaries around the United Kingdom, the Wadden Sea and the Po river delta in the north Adriatic Sea. In the United Kingdom, coastal wetlands were already used in prehistoric times for salt production, pasture and collection of wild resources (Rippon 2000). During Roman times a more systematic modification of coastal marshes began, with documented reclamation of some areas around the Severn estuary (Rippon 1997). Since mediaeval times, the use of coastal wetlands (e.g., for settlement, agriculture and food) has increased continuously in intensity; salt marshes were systematically enclosed, drained, settled and used for agriculture and pasture, leading to large-scale claims throughout much of British estuaries (detailed historical reconstructions of these developments are given by Rippon 2000). Overall, in the United Kingdom it is estimated that about 913 km2 of estuary area and 550 km2 of salt marshes have been claimed since Roman times for agricultural, urban, harbour and industrial developments (Davidson et al. 1991, Nivet & Frazier 2004). Decline was most significant in the 1800s but it has continued until today. For example, in the Wash, 858 ha of salt marshes were converted to agricultural use between 1970 and 1980 (U.K. Biodiversity Group 1999). Similarly, average losses of 20–25% of salt marshes, with individual sites suffering losses of 10–44%, occurred between 1973 and 1998 in Kent and Essex (Cooper et al. 2001, Adam 2002), where many salt marshes are ‘squeezed’ between an eroding seaward edge and fixed flood defence walls (U.K. Biodiversity Group 1999, but see Wolters et al. 2005 for debate about the causes of salt marsh erosion in southeast England). Overall, in England and Wales it is estimated that 15% of salt marshes were lost between the 1940s and the 1970s (Nivet & Frazier 2004). The history of human transformation of the Wadden Sea ecosystems has been recently reviewed (Lotze et al. 2005). Similar to estuaries in the United Kingdom, exploitation of the wetlands in this region started in prehistory, when people collected wild fauna and flora for subsistence, grazed cattle and sheep and made the first attempts to transform the coastal landscape and control the flow of water (Rippon 2000, Knottnerus 2005). Although these activities did not result in the disappearance of salt marshes, they changed the composition of their vegetation considerably (Wolff 2000). The conversion of coastal wetlands into arable land and freshwater lakes became systematic before the eleventh century (Reise 2005), and after the introduction of windmill technology, in the sixteenth century, it also became possible to drain shallow lakes (Wolff 2000). Embankments continued until the second half of the twentieth century (e.g., Figure 4), supported by improved building technologies, and it was only after the 1960s that exploitation slowed and there was a growing focus on conservation (Wolff 1997). Overall about 15,000 km2 of coastal wetlands have been lost during this long history of progressive embankments (Reise 2005) and the whole Wadden Sea has been reduced to nearly half of its primordial size. Massive loss of coastal wetlands has also occurred in Italy. It is estimated that there were about 7000 km2 of coastal marshes remaining at the end of the nineteenth century, no more than 1920 km2 in 1972 and <1000 km2 today (Stanners & Bourdeau 1995). Compiled historical information is limited to a few areas (e.g., the river Tevere; Keddy 2000). Cencini (1998) recently reconstructed the evolution of the Po river delta in the north Adriatic Sea and the effects of human transformation on coastal wetlands. Ancient sources and maps (e.g., from Pliny the Elder, Polybius and Strabo) described the deltaic coastland as a continuous, almost impassable sequence of lagoon, marshes and rivers. Since the Greco-Etruscan times, and more so after the consolidation of the Roman Empire, the area was heavily inhabited and exploited, and important urban settlements, roads and commercial ports were developed. Over the centuries, the main causes of transformation of the delta were altered sedimentation patterns and direct land claim. Sediment loads were enhanced by extensive inland deforestation carried out already by the Celts and Romans (Bondesan et al. 1995, Barmawidjaja et al. 1995). Since the seventeenth and eighteenth centuries, hydraulic works of river diversions, embankment and drainage took place, and after 1870 wetland drainage occurred systematically over large scales not only to improve hygiene conditions and eradicate malaria but also 365

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Po River (main stream) 3 Km

EL TA

0

D

PO

a

RN

1969

c noc di G Po

1872

Po di Goro

GRANDE BONIFICAZIONE FERRARESE

MO DE

1930

1872

Po di Volano R.

1878 Valli Bertuzzi

Valle del Mezzano 1929

COMACCHIO

1958 Valli di Comacchio 1964 Valle Santa

Vene di Bellocchio

1931

R . - Reno R .

Punte Alberete

Sillaro

R.

Po di Primar o

Pialasse ravennati

1940

RAVENNA

Reclaimed saltwater marshes

N

R.

Reclaimed freshwater

Savio

Existing freshwater marshes

C. Cencini, 1998

Existing saltwater marshes

Figure 8 Reclaimed (with indication of year of reclamation) and existing fresh- and saltwater marshlands in the southern part of the Po river delta. (From Cencini 1998. With permission.) Overall 98% of the freshwater marshes and >70% of the salt marshes were reclaimed between the 1870s and 1960s.

to claim new farmland. Reclamation ended by the 1960s with an almost-complete elimination of marshes and irreversible changes to the hydrological and agricultural asset of the coastal plains. Overall in the Po delta, 98% of the freshwater marshes and more than 70% of the salt marsh that existed at the beginning of the twentieth century have been claimed (Figure 8). The ancient delta (until the twelfth century A.D.) covered about 1300 km2, while the modern delta covers only 730 km2.

366

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Trends and threats Pollution, eutrophication, drainage, conversion to agriculture and aquaculture, changes in sedimentation and hydraulic regimes, changes in sea levels, global warming, invasive species, fishery overexploitation and disruptive fishing techniques, urban development, shipping, tourism and water sports are generally considered the most serious threats to present-day coastal wetlands (e.g., Dugan 1993, Cencini 1998, Jansson & Dahlberg 1999, Wolff 2000, Kennish 2002, Hiscock et al. 2005). However, limited information is available on the extent to which these activities affect and impair specific coastal wetlands and thus the general importance in causing further habitat loss is difficult to rate. Although in some regions embankments and drainage have been stopped or even reversed (e.g., Wolff 1997, Cencini 1998), land loss still continues to be the most pervasive threat to coastal wetlands and salt marshes. Between 1990 and 2000 there has been a total net loss of 390 km2 of coastal wetlands around European coastlines, a significant proportion of which was lost as a result of drainage to reclaim land for development and afforestation (EEA 2006a). Expanding aquaculture and tourist infrastructures (e.g., marinas) are also making intensive use of estuaries and wetlands, with limited consideration of the consequences on these systems (EEA 2006a). Global changes in sea levels are beginning to pose severe threats to salt marshes, coastal wetlands and river deltas because of the strong dependence of these habitats on water-level fluctuations and tidal regimes (Adam 2002, Morris et al. 2002). It has been suggested that the projected sea-level rise could cause the loss of up to half of European current coastal wetlands (EC 2004), with some of the largest losses expected to occur around the Mediterranean and Baltic Seas (Nicholls et al. 1999). When combined with other losses directly or indirectly due to human action up to 70% of the world’s remaining coastal wetlands could be lost within the next 100 yr (Nicholls et al. 1999), although there is considerable uncertainty. In the United Kingdom, for example, it has been predicted that there could be a loss of freshwater and brackish habitats of around 4000 ha as a consequence of the combined effects of sea-level rise and a temperature increase of 3–4°C (Lee 2001). Such habitat losses from sea-level rise could naturally be compensated for by the habitat regressing or developing inland. However, these inland areas are often developed and this coastal infrastructure is defended by building barriers; marshes are thus caught in a ‘coastal squeeze’ between rising seas and expanding development (Doody 2004). In the United Kingdom, for example, current ongoing losses of 100 ha yr−1 of coastal salt marsh have been estimated, due to erosion/reduced sediment inputs/land subsidence and coastal defence measures to counteract erosion (U.K. Biodiversity Group 1999, Hughes & Paramor 2004). Fortunately, since the 1990s a new approach has been developed to address coastal erosion in Europe, and increasingly the sea is being allowed to break through barriers and to re-create fringing habitats including salt marshes and lagoons (e.g., EC 2004, Hughes & Paramor 2004, Kabat et al. 2005). Protection measures The importance of preserving coastal wetlands is being increasingly recognised in Europe (Jones & Hughes 1993), where wetlands are now the target of numerous international and national initiatives and regulations for conservation, wise use and restoration. Government commitments have been encouraged though various initiatives, such as the Ramsar Convention and the Rio CBD (Table 1). Atlantic, Mediterranean and Baltic salt marshes are specifically listed as habitats in Annex I of the Habitats Directive, with some types of marshes identified as priority habitats for conservation, and wetlands in general fall into several broad habitats of the directive, such as ‘Coastal lagoons’,

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‘Estuaries’ and ‘Large shallow inlets and bays’. Many coastal wetlands are also recognised as SPAs according to the Birds Directive. As a response to these initiatives, European states have developed their own national strategies and action plans. As an example, in the United Kingdom approximately 80% of present salt marshes (50% in northwest Scotland) are currently designated as Sites of Special Scientific Interest (SSSIs), and in Northern Ireland five out of seven estuaries containing salt marshes have been designated as Areas of Special Scientific Interest (ASSIs) (U.K. Biodiversity Group 1999). Ten areas in the United Kingdom have been proposed as SACs (Habitats Directive), and 27 major salt marshes and many smaller sites are included in SPAs (Birds Directive) and Ramsar sites: the target goal is to stop further net loss of coastal wetlands, and restore 40 ha of salt marsh yr−1, to replace the 600 ha lost between 1992 and 1998 (U.K. Biodiversity Group 1999).

Seagrass meadows Current distribution and status Seagrasses are rhizomatous, clonal, marine plants that form some of the most valuable and productive coastal ecosystems in the biosphere (Costanza et al. 1997). They provide food and habitat for a variety of biota and play a fundamental role in carbon and nutrient cycling, control of water quality and sediment dynamics (Duarte 2002). Seagrasses can colonise a variety of coastal habitats from estuarine to marine, subtidal to intertidal, sedimentary to rocky. Global area estimates for seagrasses are beginning to be developed but at present there is no comprehensive dataset of actual seagrass distribution, and even regional datasets can be limited. The World Atlas of Seagrasses (Green & Short 2003) provides the most current and comprehensive compilation of information, documenting some 177,000 km2 of seagrass and suggesting a tentative global acreage estimate of 500,000 km2. Several seagrass species occur along the European coastline, including the natives Zostera marina, Z. noltii, Ruppia maritima, R. cirrhosa, Cymodocea nodosa and Posidonia oceanica (endemic to the Mediterranean Sea) plus Halophila stipulacea, which was recently introduced in the Mediterranean Sea. Seagrasses around European coastlines are now increasingly well monitored and published accounts exist for many sites and regions (Table 3). National inventories of seagrass distribution are available (e.g., Davison & Hughes 1998 for the United Kingdom) or are being prepared (e.g., REBENT programme for France). There is not, however, an organised comprehensive inventory of the distribution and coverage of seagrasses in Europe, and records for some regions are very incomplete. Furthermore, although in some regions or countries most seagrass beds are known and located, their actual coverage has not been determined. The World Atlas of Seagrasses (Green & Short 2003) documents a coverage of seagrasses of 1850 km2 in Scandinavia and the Baltic Sea, 338 km2 in western Europe (United Kingdom, Wadden Sea, Portugal and Atlantic France and Spain), 4152 km2 in western Mediterranean countries (Italy, France and Spain), and 950 km2 in the northwest Black Sea (Figure 9). It has been conjectured that seagrasses could be much more abundant in the Mediterranean, covering from 25,000 to 45,000 km2 (Pasqualini et al. 1998). Present-day seagrasses along European coasts are often described as in a degraded state (Green & Short 2003), with low shoot densities, high mortality rates, and high fragmentation. This is the case, for example, of seagrasses along the Mediterranean coasts of Spain (e.g., Table 3; Duarte 2002, Marbà et al. 1996, Delgado et al. 1997), including some deeper ones along the southeastern coasts, where trawling damages up to 40% of the total Posidonia oceanica surface (Tudela 2004). Along the Ligurian coast of Italy, P. oceanica meadows (50 beds covering 48 km2) have been severely degraded due to coastal modification and town developments (Bianchi & Peirano 1995). Some of these beds were severely damaged in the early 1990s by the wreck of the oil tanker Haven 368

369

n.a. 1150 km2 of P. oceanica

France

n.a. 1380–1710

Cyprus Denmark

n.a. <10

n.a. n.a.

n.a. n.a.

Estonia Finland

n.a.

n.a. No losses since 1968 n.a. 30–40% of P. oceanica in recent decades

n.a. 75–80% in 1900–1990s

n.a

n.a. Not present n.a.

Albania Belgium BosniaHerzegovina Bulgaria Croatia

Loss

Cover (km2)

Country

WD, LC, P, I, F, T

WD, Sa, EU, MG

I

Cause of loss

Along the Atlantic coasts >70 sites mapped and coverage of many known (most beds are 1–5 ha, but at least 10 beds cover 10 to >100 ha). South of Arcachon there is the largest Zostera nolti bed in Europe (70 km2 in 1984) and a large bed of Z. marina (4 km2 in 1984). The Glenan Archipelago lost 6 km2 of seagrasses during 1932–1992. In the Mediterranean many local documented losses of P. oceanica (e.g., close to Marseille, 5–6% per decade between 1900 and 1970, nowadays 90% is deteriorated; along the French Riviera, 30.57 km2 lost since 1800; seagrasses virtually extinct from the region of Toulon). 3184 ha affected by the invasion of C. taxifolia.

Seagrasses presumably not affected by the wasting disease.

Considered as widespread; severe declines of Posidonia oceanica in Istria between 1938–1998. Local invasions by Caulerpa taxifolia. Considered as widespread. Total cover is the sum of 30 km2 in the Wadden Sea and 1350–1680 km2 on the eastern coasts; vertical depth distribution reduced by 50% between 1900 and 1996–1997 (from 5–6 to 2–3 m in estuaries and from 7–8 to 4–5 m in open waters); 261 km2 lost in Limfjiorden between 1900 and 1994 and 559 km2 lost in Oresund between 1900 and 1996–2000; local losses continue nowadays (e.g., in 1994 eelgrass temporarily lost at Funen Island due to summer anoxia).

Regional data/additional information

(continued on next page)

Meinesz et al. 1991, 2001, Glemarèc et al. 1997, Duarte 2002, EEA 2002

Reise 1994, Rask et al. 1999

Zavodnik & Jaklin 1990, Meinesz et al. 2001

Additional references

Table 3 Estimates of actual cover and historical losses of seagrasses for European countries (and eventual additional regional information) and main attributed causes of loss

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370

n.a.

n.a.

n.a.

Norway

Poland

Portugal

n.a. n.a. n.a. n.a.

Greece Iceland Ireland Italy

n.a. Extinct? n.a. n.a. n.a. 200

n.a. 170

Georgia Germany

Latvia Lithuania Malta Monaco Montenegro Netherlands

Cover (km2)

Country

n.a.

No losses since 1930 n.a.

n.a. 100%? n.a. n.a. n.a. n.a. Virtually extinct in Wadden Sea

n.a. n.a. n.a. 30–40% of P. oceanica in recent decades

n.a. n.a.

Loss

Most seagrasses are in southwest estuaries; in the Grevelingen estuary, the construction of two dams facilitated the growth of Z marina (from 12 km2 in 1964 to 34 km2 in 1985) and the disappearance of Z. noltii, which before was the most common seagrass (large-scale, unexplained die-off of Z. marina since 1986–1987). In the Wadden Sea 145 km2 lost in 1919–1971 and 3 km2 since) and only 1–2 km2 are left nowadays.

WD, Ec, S, EU, Fd

Virtually extinct in Puck Lagoon in 1957–1987, with subsequent recolonisation in some areas.

Severe invasion by C. taxifolia.

I

MGc, EU

Considered abundant over thousands of hectares in the past.

Most beds are mapped, and coverage of many is known (estimated 2350 km2 in Liguria, Lazio, Sardinia, Veneto and Friuli). Estimate of loss is derived from estimates from France. P. oceanica virtually extinct in the north Adriatic Sea, in some areas since earlier than 1850s. Z. marina disappeared from areas of the Venice lagoon. 9414 ha affected by the invasion of C. taxifolia.

S, EU, P, I, T

MGc

Most seagrasses occur in Wadden Sea; only present on eastern coasts. Baltic Sea: in Kiel Bight decreased from 6 to 2 m in depth between 1960 and end of 1980. No losses in Greisvald Lagoon between 1930 and 1988. North Sea: Z. marina extinct at Helgoland island as early as 1928. Considered as widespread.

Regional data/additional information

WD, EU, S, MGb, LC

Cause of loss

Reise 1994, Short & Wyllie-Echeverria 1996, Wolff 2000, 2005

Meinesz et al. 2001

Barmawidjaja et al. 1995, Piazzi et al. 2000a,b, Guidetti 2001, Meinesz et al. 2001, Milazzo et al. 2004

Reise 1994, Bartsch & Tittley 2004

Additional references

Table 3 (continued) Estimates of actual cover and historical losses of seagrasses for European countries (and eventual additional regional information) and main attributed causes of loss

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371

n.a.

n.a. n.a. n.a.

Sweden

Turkey Ukraine United Kingdom n.a. n.a. n.a.

n.a.

n.a. n.a. n.a. 30–40% of P. oceanica in recent decades

WD

EU, MG

S, F, I, A, T Estimate of loss is derived from estimates from France. In the Mediterranean, 57% of P. oceanica beds were under regression in 1996 along 1000 km of coasts, and some are now extinct, with losses concentrated over 400 km of coasts. 58% of P. oceanica beds and 52% of seagrasses are degraded along the Catalan coasts and near Alicante, respectively. Local invasions by C. taxifolia. At least 60–130 km2 along the southern Baltic coasts. Losses of 58% (10.61 km2) of seagrasses in the Skagerrak in 1980s–2000. Considered as widespread. 950 km2 in the northwestern bays. Most beds mapped, and coverage of many known. About 140 sites of Z. marina and about 70 sites of Z. noltii, covering from 12 km2 (Cromarty Firth) to 20–40 hae. The Maplin Sands hosts one of the largest surviving population of Z. noltii in Europe (325 ha). Before 1900s, seagrasses were common; they severely declined in 1920s–1930s and have not recovered yet, particularly in southern and eastern England.

Davison & Hughes 1998, U.K. Biodiversity Group 1999

Baden et al. 2003

Marbà et al 1996, Meinesz et al. 2001, Duarte 2002, EEA 2002

b

Decrease of maximum Secchi depth from 12 m in 1900 to 6 m in the 1990s. Seagrasses replaced by filamentous algae. This may not necessarily be the cause of seagrass loss. c Including the closure of the Zuidersee in 1932. d Eelgrass harvesting until 1930, shell fisheries after 1970. e Other important sites are the Exe Estuary, the Solents marshes and the Isles of Scilly, Morfa Nefyn, Milford Haven, the Moray Firth, Carlingford Lough, Dundrum Bay, Strangford Lough and Lough Foyle.

a

Note: If not otherwise specified in the reference column, information is derived from the World Atlas of Seagrasses (Green & Short 2003) and references therein. A = aquaculture, E = engineering works and embankments, EU = eutrophication, F = fisheries, I = invasive species, MG = growth of ephemeral macroalgae (often a consequence of eutrophication), LC = land claim/waterfront development, n.a. = no comprehensive estimate available, P = urban and/or industrial pollution, S = increased water turbidity/load of sediment, beach replenishments, T = tourism, WD = wasting disease. Note that the estimates of covers should be regarded as minimal representation of the actual coverage in most cases. Also note that most often time span is not indicated.

n.a. n.a. n.a. n.a. >1000 in Mediterranean

Romania Russia Slovenia Spain

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N

0

250 500

1,000 Km

Figure 9 Map of the distribution of seagrasses in Europe. (Data courtesy of UNEP World Conservation Monitoring Centre.) The map should be considered indicative of general distribution not areal extent.

(Sandulli et al. 1994). The extent of seagrass degradation is, however, difficult to quantify even locally. Historical losses and causes There is increasing awareness about the severe degradation of seagrass meadows (e.g., see, among others, the reviews by Short & Wyllie-Echeverria 1996, Hemminga & Duarte 2000, Duarte 2002). Reports consistently identify a long-term trend of worldwide seagrass decline, about 70% of which can be probably attributed to direct human-induced disturbance (Short & Wyllie-Echeverria 1996). Less information is available concerning the degradation caused by indirect impacts (Duarte 2002). It has been estimated that a global loss of 12,000 km2 occurred during the 1990s alone (Short & Wyllie-Echeverria 1996), which represents about 7% of the known distribution of seagrasses (Green & Short 2003). Data covering longer time spans are rare. Based on data from 12 temperate estuaries around the world, it has been estimated that over time these systems may have lost approximately 65% of their seagrasses (Lotze et al. 2006). No comprehensive organised historical information seems to be available for Europe and information is limited to restricted areas (Table 3). There are different trends for seagrass losses in northern and Mediterranean European countries (Green & Short 2003). In northern Europe, before the early 1900s, several seagrass species, including Zostera marina, were common. They were harvested for a variety of uses, including use for fuel, packing, upholstery, insulation, roof material, filling of mattresses and cushions, feeding and bedding for domestic livestock, fertiliser and as resource to obtain salt. Their abundance was, however, severely reduced in the 1930s by a ‘wasting disease’, caused by the pathogenic slime mould Labyrinthula zosterae (e.g., Den Hartog 1987). The disease led to the catastrophic die-back 372

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of eelgrass (Zostera marina) meadows along the north Atlantic coasts, with loss of almost 90% of the Zostera populations in north Atlantic western Europe. Some beds progressively recovered, but substantial areas remain lost from most beds. There is uncertainty about the causes of this disease outbreak and there has been much debate about whether concomitant human impacts that already weakened the plants contributed to the outbreak (Den Hartog 1987). The decline particularly affected sublitoral beds, while intertidal populations were less affected. Probably the best records of the disruptive effects of the wasting disease are from Denmark, where records of eelgrass distribution date back to 1900 (Boström et al. 2003). In 1900 eelgrass covered about 6726 km2 (Figure 10); by 1940, 93% of the distribution of vegetated areas was lost. Since 1960, there has been a slow recolonisation. Currently, there is approximately 20–25% of the distribution recorded in 1900 (i.e., a total loss of 75–80%). The greatest loss has been in deep Zostera populations and in Denmark the vertical depth distribution of Z. marina was reduced by about 50% during the twentieth century, from a historical depth limit of 5.6–11 m to a recent limit of 2.5–8 m in sheltered and exposed areas, respectively (Hemminga & Duarte 2000, Baden et al. 2003). Similar dramatic losses are described for the United Kingdom (Davison & Hughes 1998 and references therein) and the Wadden Sea (Reise 1994, Wolff 2000, Lotze 2005). The distribution of seagrasses in the United Kingdom was only systematically described in the 1930s after the outbreak of wasting disease, when Z. marina was already scarce and restricted to few sheltered lagoons but there are indications that seagrasses were widespread until 1917 (Davison & Hughes 1998). There is some uncertainty about when recovery started. According to some, recovery began in 1933 and was quite rapid, with some beds fully recovering within a few years of the 1930s epidemic, while according to others the disease continued to affect Zostera populations until the mid-1940s and recovery did not really begin until the 1950s. Nowadays, most Zostera beds have not fully recovered, particularly in southern and eastern England where the species was once abundant, and only 20 of Britain’s 155 estuaries have eelgrass meadows >1 ha in extent (Davison & Hughes 1998). Before the 1930s the Wadden Sea also contained large subtidal, seagrass beds. These have been exploited since historical times for construction and insulating material and to fill mattresses and cushions. In the Dutch Wadden Sea, from the thirteenth century to 1825, eelgrass was used to build dykes. The construction of 1 m of seawall required about 8–20 m3 of compacted eelgrass, equivalent to about 40–100 m3 of fresh eelgrass, which in some years corresponded to about 1–10% of the annual production (Wolff 2005). Decline of seagrasses appears to have occurred over two phases (Reise 1994): one acute in the 1930s, caused by the wasting disease, after which most subtidal eelgrass beds did not recover, and one more gradual that began in the 1960s, mostly driven by eutrophication. These declines first affected subtidal eelgrass beds, and subsequently also intertidal ones, leading to the almost extinction of seagrasses in some regions of the Wadden Sea (e.g., the Dutch Wadden Sea, where cover dropped from 150 to 1–2 km2; see Table 3), and to the disappearance of numerous species associated with seagrasses (Wolff 2000). Along Mediterranean coasts, reliable estimates made by direct observation of the area of seagrass lost or degraded are limited (Green & Short 2003). It is estimated that in the past Posidonia oceanica meadows may have covered 50,000 km2 in the whole basin (Duarte 2002), which considering present estimated covers of seagrasses in the Mediterranean and Euro-Asian Seas (Green & Short 2003) would make an overall loss >85% (but probably many existing seagrass meadows are not presently documented). Rapid local regression (up to complete disappearance) of P. oceanica meadows is known to have occurred at numerous localities in France, Italy and Spain (Table 3). It is estimated that shoot density of P. oceanica in the western Mediterranean has decreased by up to 50% over a few decades, with major losses between 10 and 20 m depth (EUCC 1998). For the French mainland coast, overall habitat loss is estimated as about 10–15%, which would increase up to 30–40% if the decline in shoot density is also taken into account. Overall, these figures are 373

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North Sea

1901

Sweden

Kattegat Denmark ∅resund

Baltic Sea Germany

North Sea

1941

Sweden

Kattegat Denmark ∅resund

Baltic Sea

Germany North Sea

1994

Sweden

Kattegat Denmark ∅resund

Baltic Sea

Germany

Figure 10 Area distribution of eelgrass Zostera marina (in dark grey) along Danish coasts in 1901, 1941 and 1994. (Modified after Boström et al. 2003. With permission.) In the 1930s, eelgrass populations were severely affected by a wasting disease, and in 1941 they covered only 7% of the areas occupied in 1901. Recolonisation took place after the 1960s, but in 1994 cover was still only 20–25% of that in 1901.

374

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considered a good estimate for most western Mediterranean coastlines, with notable exceptions around the islands and in the eastern Mediterranean (EUCC 1998). There have been clear losses of seagrasses on the Italian coast of the north Adriatic Sea. Geological data have shown that seagrass beds were probably common before the 1800s and experienced dramatic regressions to virtual extinction in the last two centuries (Barmawidjaja et al. 1995, Caressa et al. 1995, Rismondo et al. 1997). For example, faunal changes and the sudden disappearance of epiphytic foraminiferans in a sediment core in front of the Po river delta suggest that seagrass beds were present up to 1840 in this area, and that increased load of fine sediment and nutrients between 1840 and 1870, due to substantial changes to the main outflow canals of the Po river, was probably the main cause of their sudden disappearance (Barmawidjaja et al. 1995). Similarly, dead beds of P. oceanica have been found at several sites about 8 miles offshore from the Venice lagoon, indicating the likely past presence of P. oceanica (Rismondo et al. 1997). In the Gulf of Trieste the regression has been more recent and there has been some direct documentation. P. oceanica was reported as common in the Gulf of Trieste at the beginning of the 1900s (Caressa et al. 1995). In 1938 the species had declined but was still present all over the coastlines of the Istrian peninsula, while just about 30 yr later only the Koper meadow was detected. Nowadays, P. oceanica is present only in a fragmented meadow along the coastline of Koper (Slovenia, at the southern side of the Gulf of Trieste) and in a very small area along the coasts of Grado (on the Italian side of the Gulf of Trieste). This drastic reduction has been attributed to a steep increase in water pollution during the last 50 yr as a consequence of industrial and harbour development in the Gulf of Trieste (Caressa et al. 1995). Another case of rapid regression of P. oceanica meadows is in the French Riviera, from Menton to the Rhône delta (Meinesz et al. 1991). Intensive waterfront development started around 1800 covering natural coastal habitats with recreational harbours, artificial beaches, landfills (for the tourist industry) and large commercial and military complexes, ports and airports. A total of 185 reclamation projects ‘occupied’ 106 km (16.2%) of the coastline, directly removing 30.57 km2 of bottom substrata and greatly affecting surrounding areas (by modifying water movements and sedimentation patterns). Overall a total of 9.7% of the shallow water zone between 0 and −20 m and 14.5% of the zone between 0 and −10 m were irreversibly destroyed. The vast majority of this area was occupied by P. oceanica meadows, which were estimated to originally cover a total of 200 km2. Trends and threats Many anthropogenic factors are considered responsible for the ongoing degradation and decline of seagrasses in Europe as well as globally (e.g., see, among others, the reviews by Short & WyllieEcheverria 1996, Davison & Hughes 1998, Hemminga & Duarte 2000, Duarte 2002, Green & Short 2003). The most important of these threats is likely to be poor water quality from pollution, eutrophication and excess sedimentation. These impacts are associated with, and enhanced by, urban and tourist waterfront developments, port constructions, beach replenishments and other interventions for shoreline stabilisation. Severe seagrass loss is still in progress in Europe, as evident along 200 km of the Skagerrak Swedish coast (Baden et al. 2003). Here, 50 of 69 mapped meadows of Zostera marina have shown average declines of 58% between the 1980s and 2000, corresponding to a lost surface of about 1061 ha. Most declines are related to a reduction of the upper and the lower depth distribution of seagrasses, resulting in narrower meadows, but in some areas seagrass meadows have disappeared completely, with dramatic effects on the fish assemblages (Pihl et al. 2006). The reasons for this continuing loss of seagrasses are not known but could be related to an excess growth of phytoplankton and filamentous or other ephemeral macroalgae as a consequence of eutrophication. These micro- and macroalgae outcompete seagrasses (Hauxwell et al. 2001) and decompose on the bottom, 375

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favouring anoxia events like those that caused the recent temporary disappearance of Z. marina in 1994 around the island of Funen in Denmark (Rask et al. 1999). There is also current seagrass loss in the Mediterranean Sea as a consequence of the invasion of Caulerpa taxifolia (Meinesz et al. 2001, but see Jaubert et al. 2003). This species competes for space and resources with the seagrass Cymodocea nodosa (Ceccherelli & Cinelli 1997) and is thought to be able to damage Posidonia oceanica beds, particularly when these are already under stress (e.g., de Villèle & Verlaque 1995). Protection measures Green & Short (2003) report that worldwide there are only some 247 MPAs that are known to include seagrasses, spread in 72 countries and territories. This estimate may be conservative but these authors note that this is far smaller than the number of MPAs with coral reefs (more than 660) or mangrove forests (over 1800). Even for these 247 MPAs, there are questions about their effectiveness in protecting seagrass ecosystems particularly from threats such as poor water quality (e.g., Marbà et al. 2002, Milazzo et al. 2004). In Europe, numerous initiatives arising from the Rio CBD, the Habitats Directive and the Birds Directive (Table 1) have led to seagrass meadows being specifically targeted for conservation and restoration. Seagrasses are a named component of several habitats in the Habitats Directive, including ‘Coastal lagoons’ (a priority habitat), ‘Sandbanks slightly covered by seawater all of the time’, ‘Large shallow inlets and bays’, ‘Estuaries’ and ‘Mudflats and sandflats not covered by seawater at low tide’ (EC 2003). Furthermore, Posidonia oceanica beds are a priority habitat in Annex I of the Habitats Directive. International concern about the conservation of seagrass beds has also led to the banning of trawling on seagrasses in EC waters (Tudela 2004). As a response to these initiatives, European States have also developed national strategies and initiatives. The U.K. Biodiversity Action Plan, for example, includes a Habitat Action Plan for seagrass beds (U.K. Biodiversity Group 1999). Accordingly, areas of seagrass are included in some coastal ASSIs/SSSIs, Ramsar sites, SPAs and voluntary MPAs. Two of the three U.K. Marine Nature Reserves have seagrass beds and the habitat occurs in a number of areas proposed as SACs.

Macroalgal beds Current distribution and status For the purpose of this review ‘macroalgal beds’ refer to kelps, fucoids and other complex, erect brown and red macroalgae that produce relatively large biogenic habitats. Macroalgal beds form diverse, productive and valuable temperate coastal ecosystems (Steneck et al. 2002). They are widespread on shallow hard substrata around Europe (Birkett et al. 1998b, Steneck et al. 2002, Thibaut et al. 2005 and references therein), including rock, boulders, cobbles and human-made structures from the intertidal down to more than 30 m in depth. Laminaria and Fucus are the main genera along the coasts of northwest Europe, while Cystoseira and Sargassum are the main genera in the Mediterranean Sea. The macroalgal flora of the European coasts are among the best known and studied. Furthermore, large macroalgae have been the target of ecological studies for over a century and there is extensive literature on physical and biological factors operating in these habitats (see, among many, Lüning 1990, Ballesteros 1992). Surprisingly, however, quantitative information on the distribution of macroalgal beds is limited and their extent is unknown. At present, there do not appear to be comprehensive inventories for the macroalgae of any European country and it is difficult to estimate the areal coverage even at regional or local scales. Distribution maps of rocky coast biotopes, 376

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including kelps, are available for the United Kingdom (Connor et al. 2004), and ongoing inventories by the Joint Nature Conservation Committee (JNCC) are likely to result in estimates of the cover of macroalgal beds for this country, at least for intertidal habitats, while little information is available for the subtidal. Intensive research on kelp distribution, ecology and effects of human harvesting has also been carried out along Norwegian coasts, where it is estimated that the dominant kelp Laminaria hyperborea might cover between 5,000 and 10,000 km2 (Jensen 1998). Limited quantitative information on the distribution of macroalgal beds is available at a few regional or local scales (e.g., the Albères coast, Thibaut et al. 2005; Kiel Bay, Vogt & Schramm 1991; the Öregrund archipelago, Eriksson et al. 1998; the Gullmar Fjord, Johansson et al. 1998). Historical losses and causes A perceived worldwide decline of macroalgal beds has been reported during the last decades (Steneck et al. 2002, Airoldi 2003). Such decrease most often appears to be parallelled by a trend of increasing abundance of turf-forming, filamentous or other ephemeral algae (e.g., Munda 1993, Eriksson et al. 1998, Benedetti-Cecchi et al. 2001, Lotze 2005) that, once established, often inhibit recolonisation of canopy-forming algae and other organisms (Airoldi 1998). Canopy-forming algae and turfs have been suggested to represent alternative states in shallow temperate rocky reefs under different disturbance and stress regimes (Worm et al. 1999, Airoldi 2003, Connell 2005). Macroalgal beds have also been replaced by coralline dominated ‘urchin barrens’, where outbreaks of urchins may have been the primary cause of macraolgal extirpation (Hagen 1995, Steneck et al. 2002, Guidetti et al. 2003), or by mussel beds (Thibaut et al. 2005). In Europe, almost no information on trends in abundance of macroalgae is available before the 1900s. In the twentieth century, conspicuous losses, sometimes to virtual local disappearance, of complex macroalgae have been documented for coastal areas in several countries, including Iceland, Norway, Britain and Ireland (Hagen 1995, Steneck et al. 2002 and references therein); Sweden (Lundälv et al. 1986, Eriksson et al. 1998, 2002, Johansson et al. 1998, Nilsson et al. 2004); Denmark (Middelboe & Sand-Jensen 2000); Finland and Germany (Kangas et al. 1982, Messner & von Oertzen 1991, Vogt & Schramm 1991, Schories et al. 1997); Lithuania (Olenin & Klovaité 1998); Italy (Sfriso 1987, Cormaci & Furnari 1999, Benedetti-Cecchi et al. 2001, Guidetti et al. 2003, L. Airoldi unpublished data); France and Spain (Rodríguez-Prieto & Polo 1996, Thibaut et al. 2005 and references therein); Croatia (Munda 1993, 2000) and Romania (Zaitsev 2006). The causes of these losses are various but mainly include outbreaks of sea urchins and decreased water quality as a consequence of pollution and/or enhanced sediment loads. These trends have been generally traced through comparisons with historic floristic records, which are difficult to translate into an estimate of the extent of habitat loss. Furthermore, complex native species were often replaced by simpler macroalgae or non-native species, possibly affecting the status and functioning of the systems but not their extent. Frequently, the declines of macroalgae have been greater at depth so that their depth range has become shallower (Lumb 1990, Messner & von Oertzen 1991, Bokn et al. 1992, Munda 1993, Eriksson et al. 1998, 2002, Pedersén & Snoeijs 2001, Thibaut et al. 2005). In Kiel Bay (Germany, western Baltic), for example, there has been a >90% decline in the biomass of Fucus spp. between 1950 and 1988, from about 40,000–45,000 t wet wt down to only 2400 t wet wt (Vogt & Schramm 1991). In the 1950s, Fucus spp. were the dominant macrophytes down to 6 m in depth and were still frequent in the 1970s, whereas at the end of the 1980s, the species were not found at depths >2 m. In the Öregrund archipelago (Sweden) the average depth penetration of F. vesiculosus decreased significantly by 2 m between 1943 and 1996 and this species had completely disappeared at depths >8 m (Figure 11). The amount of macroalgal habitat lost as a consequence of this depth reduction has not been estimated (B.K. Eriksson personal communication) but it must have been 377

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0

Max. depth

Mean depth

∗ 2

Depth (m)

4 6 8 1943–44 10

1984 1996

12

Figure 11 Changes in the depth (maximum and mean) distribution of Fucus vesiculosus in 1943–1944, 1984 and 1996 in the Öregrund archipelago. (From Eriksson 2002, based on Kautsky et al. 1986, Eriksson et al. 1998 and Eriksson & Bergstrom 2005; courtesy B.K. Eriksson.) *No mean depth data were available for 1984. Data are averages ± 1 standard error. Maximum and mean depth penetration of F. vesiculosus decreased significantly both between 1943–1944 and 1984 and between 1943–1944 and 1996 (t-test, n = 5 sites, p < .05).

considerable because quantitative measures of the distribution of F. vesiculosus indicated that this species covered on average 20–50% of the substrata. Similarly, at Stora Bornö Island, on the Swedish Skaggerak coast, the depth distribution of macroalgae declined on average by 2.8 m between 1941 and 1998 (Eriksson et al. 2002). This loss was particularly severe for large, complex macroalgae (>50 cm), which showed up to 8-m reductions in their depth distribution (Figure 12). These complex macroalgae were replaced by simpler, thin filamentous and sheet-like forms. Losses to virtual extinction of macroalgal species have been reported from other regions in the Wadden Sea, southern France, the Venice lagoon and the Black Sea, for example. In the Wadden Sea, at least 10 species of macroalgae have become extinct during the past 2000 yr, probably because of the transformation of brackish waters into fresh waters and the destruction of native eelgrass beds and oyster reefs that provided solid surfaces for attachment (Wolff 2000). Along the 1941

1998

2

Depth (m)

4 6 8 10 12 14 16 300

200

100 0 100 200 Estimate of cover (%)

300

Figure 12 Depth distributions of macroalgae with different thallus shape (thin filamentous and sheet-like = white bars; coarse filamentous and thick, leathery algae = dotted bars) in 1941 and 1998 at Stora Bornö Island. (Based on data from Eriksson et al. 2002. Courtesy B.K. Eriksson.) Bars are mean percentage cover in each depth interval pooled for two vertical profiles (error lines are not shown for clarity).

378

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Albéres coasts (southern France) dramatic reductions in abundance to extinction of populations of Fucales (Cystoseira spp. and Sargassum spp.) occurred between the early 1900s and 2003 (Thibaut et al. 2005). Only 9 of 14 species of Fucales documented in 1912 were present in 1978, with the genus Sargassum entirely lost, and only 5 species were found in 2003. Seven of the extinct species were considered frequent to abundant in 1937. Of the 5 species remaining in 2003, only 1 did not show signs of regression. In the Venice lagoon, some 141 algal species were documented in 1938, 116 in 1962, 107 in 1987 and 96 in 1991 (Sfriso 1987, Sfriso & La Rocca 2005). Some of the most damaged species in the lagoon were previously dominant large brown algae, including species of Cystoseira, Fucus virsoides, and Sargassum hornschuchii. These algae were adversely affected when channel excavations limited water exchange, leading to an increase of nutrient levels and eutrophication within the lagoon, and in the 1980s their abundance dramatically decreased, sometimes to complete and permanent disappearance. These complex macroalgae were replaced by ephemeral species, mainly green algae, and invasive species. In the last 10 yr, water quality has improved in the Venice lagoon, and recent sampling detected an increase in the number of macroalgae (Sfriso & La Rocca 2005), in part also linked to the introduction of several invasive species, including the now-abundant large brown algae Undaria pinnatifida and Sargassum muticum. Along the coasts of the Black Sea, several complex macroalgae (including brown algae of the genera Cystoseira and Phyllophora) have virtually disappeared during the past 30 yr (Zaitsev 2006). Estimates at some Romanian localities indicate that in 1971 these species attained considerable biomasses (about >10,000 t fresh wt). Trends and threats Several factors are thought to be responsible for the continuing decline of kelps and canopy-forming macroalgae and to pose serious threats to the future of rocky reefs in general (Steneck et al. 2002, Thompson et al. 2002). Urbanisation is thought to have the most disrupting effects on kelps and other canopy-forming algae, particularly by affecting water clarity and quality as well as other habitat-related changes (e.g., Vogt & Schramm 1991, Munda 1993, Eriksson et al. 1998, 2002, Benedetti-Cecchi et al. 2001). In some northern European regions, including the west coast of Norway, the French channel coast and parts of the U.K. coast, harvesting is also an issue (e.g., Christie et al. 1998). Kelps washed up on the shore have been traditionally collected for centuries in some regions, for use as an agricultural fertiliser and to improve the soil structure. Nowadays kelps and fucoids are harvested from living beds to be used as basic resource in the alginate industry to produce emulsifying and gelling agents. The most commonly harvested species include Laminaria hyperborea, L. digitata, Ascophyllum nodosum and Fucus spp. with 70,000–80,000 t of seaweeds collected each year around the coasts of both Brittany (Birkett et al. 1998b) and Norway (EEA 2002). Modern methods of kelp harvesting (e.g., by trawling) seem to have a significant direct influence on kelp biotopes (Birkett et al. 1998b, Christie et al. 1998). Reef habitats and associated macroalgal beds are also severely damaged by disruptive fishing techniques. For example, the collection of the date mussel Lithophaga lithophaga by use of hammers and chisels, pneumatic hammers and explosives is still a widespread practice in most Mediterranean countries, despite its legal ban. This practice directly and irreversibly destroys the rocky environment, causing the loss of canopy-forming seaweeds and the formation of barrens (Fanelli et al. 1994, Guidetti et al. 2003). The introduction of harbour piers, jetties, dykes, seawalls, coastal defences and other armoured artificial structures has in some regions led to an expansion in the distribution of native and nonnative macroalgae and other rocky-bottom species (Moschella et al. 2005). In the Wadden Sea, for example, where hard substrata were naturally scarce, about 730 km of artificial structures have 379

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introduced about 2–4 km2 of hard substrata, providing new habitats for a variety of rocky-bottom species, including Laminaria saccharina (Reise 2005). Along the north Adriatic shores, which are naturally devoid of rocky substrata, >190 km of rock-armoured structures (Figure 5), built mainly in the past 40 yr (Bondesan et al. 1995), have introduced about 1 km2 of artificial hard substrata within natural sandy depositional environments, which are now extensively colonised by the nonindigenous, invasive canopy-forming macroalga Codium fragile ssp. tomentosoides (Bulleri & Airoldi 2005). The extent of hard coastal structures is expected to increase in the future, with profound but overlooked ecological consequences on native coastal environments (Airoldi et al. 2005). Protection measures Although kelp beds and other macroalgal habitats are not specifically targeted in the Habitats Directive, species of the genus Fucus, Laminaria and Cystoseira and other macroalgae are named components of ‘Reefs’ habitat (EC 2003). Other European initiatives also include the protection of some species of complex macroalgae. For example, six Mediterranean species of the genus Cystoseira and two species of Laminaria are listed in Annex I of the Bern Convention. The Action Plan for the Conservation of Marine Vegetation in the Mediterranean Sea, adopted within the framework of the Barcelona Convention, identifies the conservation of Cystoseira belts as a priority. Several complex brown macroalgae are listed in the Red Books of Mediterranean and Black Seas as endangered (e.g., Boudouresque et al. 1990, Zaitsev 2006). Furthermore, Lithophaga lithophaga is included in Annex IV of the Habitats Directive and its collection is banned in most Mediterranean countries to protect rocky reefs and associated macroalgal beds from the destructive consequences of the fishery for this rather abundant date mussel (Russo & Cicogna 1991). There are also national initiatives. For example, the commercial harvesting of kelps is strictly regulated in Norway and in Brittany (Birkett et al. 1998b), including a system of rotation of harvested areas introduced by the Norwegian government to ensure that each area of kelp forest is harvested only once every 4 yr.

Biogenic reefs: oyster reefs Current distribution and status The native European flat oyster (Ostrea edulis) is a sessile, filter-feeding, bivalve mollusc that used to be very abundant throughout its range (Korringa 1952). It is associated with highly productive estuarine and shallow coastal water habitats with sediments ranging from mud to gravel. The natural distribution of O. edulis is along the European Atlantic coasts from Norway to Morocco and across the coasts of the Mediterranean and Black Seas. Their abundance declined significantly during the nineteenth and twentieth centuries and wild native beds were considered scarce in Europe as early as the 1950s (Korringa 1952, Yonge 1966, Mackenzie et al. 1997). Remains of wild native oyster beds still occur in various regions, including the rivers and flats bordering the Thames Estuary, the Solent, River Fal, the west coasts of Scotland and Ireland (Kennedy & Roberts 1999, U.K. Biodiversity Group 1999, Tyler-Walters 2001, Jackson 2003), the western part of the Swedish Kattegat region of the Baltic (Lozan 1996), the Limfjord region of Denmark (Korringa 1952), the Adriatic Sea, where O. edulis is still captured in the wild (Barnabe & Doumenge 2001), the Mar Menor (Spain), where a large flat oyster population, estimated at over 100 million individuals, still produces large amounts of spat (Cano & Rocamora 1996), and areas of the Black Sea, where the species was still valuable commercially until the 1970s (Zaitsev 2006). Limited information, however, is available about the current status of these oyster reefs and there 380

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is debate about whether the fragmented patches of wild oyster habitats are self-sustaining or owe their survival to the inputs of larvae from cultivated oysters (Korringa 1952). Nowadays, aquaculture provides the main supply of native oysters in most European countries (Mackenzie et al. 1997, Ocean Studies Board 2004). This industry has also been seriously affected by epidemic diseases in recent decades, with documented losses of commercial stocks above 80% in France (Kennedy & Roberts 1999, Ocean Studies Board 2004), and most Mediterranean native oyster beds are in such poor conditions that they are unable to support intensive culture (Barnabe & Doumenge 2001). Although marketplace demand for native oysters remains strong, the introduced Pacific oyster Crassostrea gigas, which is easier to cultivate than the native oyster, now provides the major share of oyster production in Europe (Cano & Rocamora 1996, Kennedy & Roberts 1999, Lotze 2005; see Figure 13C). Historical losses and causes There is some documentation on the declines and loss of native oyster reefs, mostly from fishery landing records; direct quantitative data are uncommon. In Europe oysters have been an extremely popular food for centuries (Jackson 2003). Both ancient Greeks and Romans highly valued oysters. Romans fished and imported them from all over European and Mediterranean coastlines and extensively cultivated them (Günther 1897), and in some British estuaries there are archaeological signs of overexploitation of native oyster beds since the first century (Rippon 2000). For centuries, Ostrea edulis reefs supported a productive commercial fishery (Mackenzie et al. 1997). In the eighteenth and nineteenth centuries, large offshore oyster grounds in the southern North Sea and the English Channel produced up to 100 times more than today’s 100–200 t (U.K. Biodiversity Group 1999, Berghahn & Ruth 2005). The richest natural oyster beds in Europe until the nineteenth century were probably around Britain, from Stornoway to the Solway in the west and from the Orkney Islands to the Firth of Forth in the east (Berghahn & Ruth 2005). In the mid-nineteenth century these were heavily exploited; dredging of the oyster beds was one of the largest fisheries, employing about 120,000 men around the coast in the 1880s (Tyler-Walters 2001), with an annual yield of >50 million oysters (Berghahn & Ruth 2005). Oyster reefs at Strangford Lough, in Ireland, once supported up to 20 boats employed in oyster dredging (Kennedy & Roberts 1999). In the Wadden Sea, the commercial fishery for oysters started in the eleventh century and flourished in the eighteenth century (Figure 13): in 1765 large oyster beds between Texel and Wieringen supported profitable fishery by 145 vessels, with catches over 100,000 oysters yr−1 vessel−1 (Wolff 2005). By the late nineteenth century, beds of O. edulis were already severely depleted or physically destroyed around most European coasts (Ocean Studies Board 2004). Regulations and fishery closures were imposed in some regions. In the Wadden Sea, for example, management strategies including minimum landing size, fishery closures, a licence system and maximum yield per year have been applied since the seventeenth century (Berghahn & Ruth 2005). Similar initiatives were taken in France. The decline could not, however, be halted and in the twentieth century catches collapsed (e.g., Figure 13A,B). Overfishing and wasteful exploitation, combined with outbreaks of diseases, habitat loss and change or destruction, reduction in water quality and other large-scale environmental alterations, adverse weather conditions, and the introduction of non-native oysters (and associated parasites and diseases, such as the protozoan Bonamia ostreae) for aquaculture and other non-native species (e.g., the invasive gastropod Crepidula fornicata) were blamed for the decline (Korringa 1952, Mackenzie et al. 1997, Wolff 2000, Jackson 2003, Berghahn & Ruth 2005). Virtual extinction of native oyster beds has been documented in the Wadden Sea, where wild oysters largely disappeared by 1950 (Wolff 2000, 2005, Lotze 2005); in Helgoland (Germany), where beds largely disappeared by the mid-1900s (Korringa 1952, Franke & Gutow 2004, OSPAR Commission 2005); in the Dutch Easter Scheldt (van den Berg et al. 2005); in Belgium (OSPAR Commission 381

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A

0.3 0.2 0.1 0.0

1770 1780 1790 1800 1810 1820 1830 Oysters harvested (× 106)

6 B

5 4 3 2 1 0

1870 1880 1890 1900 1910 1920 1930 25 C 20 15 10 5 0 1970 1975 1980 1985 1990 1995 2000 Figure 13 Annual landings of native European oysters, Ostrea edulis, (A) in the east Frisian Wadden Sea during 1770–1830, (B) in the north Frisian Wadden Sea during 1868–1930 and (C) landings of cultured Pacific oysters, Crassostrea gigas, in the Netherlands during 1970–2000. (From Lotze 2005. With permission.)

2005); in all deeper waters of the southern North Sea, such as in the Oyster Grounds (OSPAR Commission 2005); in most areas of Galicia (Cano & Rocamora 1996) and in some bays in the Black Sea (Zaitsev 2006). In the Firth of Forth (Scotland), which in past centuries had hosted one of the most famous oyster banks, no oysters were found in 1957 (Dodd 2005). Dramatic stock decreases have been reported as well on the Atlantic coasts in French Brittany, the Netherlands, Denmark, Norway, Ireland and England and in the Mediterranean Sea (Korringa 1952, Mackenzie et al. 1997, U.K. Biodiversity Group 1999, Barnabe & Doumenge 2001). In the United Kingdom, where 700 million oysters were consumed in London alone in 1864, the catch fell from 40 million in 1920 to 3 million in the 1960s and has not recovered (Tyler-Walters 2001). In Archachon Basin (France), 382

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wild oysters, which had been exploited for ages, were nearly commercially exhausted in the mid1800s, leading to the introduction first of the Portuguese hollow oyster (Crassostrea angulata) and then of the Pacific oyster (Crassostrea gigas). Trends and threats There is limited information about current trends and threats to remaining native oyster reefs in Europe. Ostrea edulis is a relatively long-lived species and reproduces sporadically (Korringa 1952). Thus, presumably, times of recovery from overexploitation or other causes of damage are very long and are estimated to take up to 20 yr (Jackson 2003). O. edulis is considered to be highly sensitive to substratum loss, smothering, contamination by synthetic compounds (particularly tributyltin (TBT) antifouling paints used on ships and leisure craft, which, in the early 1980s, caused stunted growth of oysters and probably affected reproductive capacity), oxygen depletion, reduced freshwater inputs, introduction of microbial pathogens/parasites, introduction of non-native species and direct extraction (U.K. Biodiversity Group 1999, Jackson 2003, Hiscock et al. 2005). All these factors impair recovery as well as restoration efforts. The main factors that probably threaten native oyster reefs nowadays include illegal fishing as well as by-catch in trawling targeting other species, poor water quality and pollution, changes to the environment (e.g., habitat loss due to coastal development) and the introduction of non-native competitors, predators and diseases (Jackson 2003, OSPAR Commission 2005). Protection measures Nowadays, the sparse remains of wild native oyster beds are probably one of the most endangered marine habitats in Europe. Ostrea edulis, however, does not seem to be the target of any specific protection measure, conservation legislation or convention at a European level. ‘Reefs’, including biogenic reefs, are listed as a conservation feature in Annex I of the Habitats Directive; however, native oyster reefs are not mentioned as a component (EC 2003). Since 2003, O. edulis beds are included in the OSPAR list of threatened and/or declining species and habitats for all OSPAR areas (OSPAR Commission 2005). Ostrea edulis is also included in the ‘Red’ lists of some regions (e.g., Wadden Sea, Black Sea). Indirect protection to native oyster reefs may also come from a number of EC Directives related to shellfish, such as the 95/70/EC, which sets community-wide rules to prevent the introduction and spread of the most serious diseases affecting bivalve molluscs, and the Shellfish Waters Directive (Table 1). Fisheries for native oysters are regulated (sometimes prohibited) at a national level (e.g., Hiscock et al. 2005, Zaitsev 2006) but other national or regional conservation initiatives seem to be rare. There is little evidence that this management is leading to recovery of stocks. In the United Kingdom, O. edulis is included in a Species Action Plan under the U.K. Biodiversity Action Plan (U.K. Biodiversity Group 1999) and naturally occurring native oyster beds are considered a nationally scarce habitat (Jackson 2003), although complex regulations still allow some harvesting.

Biogenic habitats: maerls Current distribution and status Maerls (also known as rhodolith beds) comprise several species of crust-forming, free-living (i.e., unattached), calcareous red algae (Donnan & Moore 2003). Over time, they can become abundant enough to form substantial banks of live and dead material, with some European beds dated as older than 5500 yr (Grall & Hall-Spencer 2003). The major maerl-forming species in European waters are Phymatolithon calcareum, Lithothamnion corrallioides and L. glaciale. They can occur 383

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in exposed and sheltered environments, from the surface down to 100 m in depth (e.g., near Corsica and Malta), but most typically occur at 20–30 m (OSPAR Commission 2005). Maerl beds are structurally and functionally complex habitats that support rich and diverse assemblages and host many species unique to those habitats. There is also growing evidence that maerl beds have considerable value as nursery grounds for species of commercial interest (Barbera et al. 2003). Records of the presence or absence of maerl biotopes on European coasts are patchy (Birkett et al. 1998a). Detailed studies of maerl habitats have been undertaken only in the past 40 yr and at only a few locations, mainly in France, Norway and Ireland. Large, historically accessible maerl banks are relatively well recorded as a result of commercial interests. The locations of other maerl sites are known from the results of grab-and-dredge sampling during scientific research cruises. In more recent times, scuba divers have reported maerl banks. However, the extent of a maerl bed at any given location, its species composition and the species associated with it remain largely unknown (Birkett et al. 1998a). The most recent and comprehensive overview of maerl beds in Europe was compiled under the EC MAST-funded BIOMAERL project (Donnan & Moore 2003). Unpublished databases are expanding for the United Kingdom and France but an overall inventory has not been attempted. In Europe maerl beds are patchily distributed and relatively restricted in size (Donnan & Moore 2003). They are found throughout the Mediterranean Sea, with important beds in Algeria, at Marseilles, in Corsica and Sardinia and in the Aegean (Birkett et al. 1998a). Maerl beds are also common on the Atlantic coasts, from Norway to Portugal. Spanish maerl deposits are confined mainly to the Ria de Vigo and Ria de Arosa (Galicia, northwest Spain). Maerl beds are relatively rare in the eastern English Channel, Irish Sea, North Sea and Baltic Sea (Barbera et al. 2003), whereas they are particularly abundant in Brittany, with more that 70 beds >1 km2 and some of the largest and thickest beds in Europe and the world (Grall & Hall-Spencer 2003). In Ireland, maerl is widely distributed in the south and southwest (e.g., Galway Bay, Bantry Bay, Roaringwater Bay; De Grave & Whitaker 1999), and Scotland is home to some of the most extensive maerl beds in Europe (Birkett et al. 1998a). Information on the status of present maerl beds in Europe is limited. Most Breton maerl beds are affected by human activities and the only pristine grounds remaining are small compared with the extensive maerl beds that covered several square kilometres in the 1960s (Grall & Hall-Spencer 2003). In 1999, surveys at one of the largest maerl beds in Brittany (Glenan), which was covered with living maerl until extraction started some 35 yr ago, showed that live maerl was rare over most of this bank while species-poor assemblages on muddy bottoms prevailed (Grall & HallSpencer 2003). Even maerl beds included in Breton NATURA 2000 sites are far from pristine and many are severely degraded. Historical losses and causes Information on historical losses of maerl beds in Europe as a consequence of human activities is virtually absent. Maerl has been harvested on a small scale in Europe for thousands of years for use in animal food additives, water filtration systems, acid lake and pond treatment, biological denitrification, toxin elimination, surfacing garden paths and in the pharmaceutical, cosmetics, medical and nuclear industries, but mostly as a cost-effective source of calcium/magnesium soil additive in agriculture and horticulture (Barbera et al. 2003, Grall & Hall-Spencer 2003). Initially, the quantities extracted were small, being dug by hand from intertidal banks, but in the 1970s about 600,000 t of maerl were extracted per year in France alone (Birkett et al. 1998a). Maerl extraction still forms a major part of the French seaweed industry, both in terms of tonnage and value of harvest, although amounts have declined to about 500,000 t yr−1 (Grall & Hall-Spencer 2003). In the United Kingdom and Ireland maerl has been harvested since the seventeenth century (De Grave 384

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& Whitaker 1999) with up to 30,000 t yr−1of maerl harvested commercially in the River Fal from 1975 to 1991 (Birkett et al. 1998a). Currently only limited extraction of maerl takes place in the United Kingdom and Ireland (De Grave & Whitaker 1999). The extent to which this historical extraction has affected maerl beds is not known. Comparisons between museum collections made in 1885–1891 and again in 1995–1997 at maerl beds in the Firth of Clyde (Scotland) showed extensive changes, with substantial reduction in size and number of living thalli of Phymatolithon calcareum (Hall-Spencer & Moore 2000). Such changes have been attributed to mechanical impacts of scallop dredging, which started in that area in the 1930s and became particularly intensive in the 1960s through the advent of more powerful boats, more efficient dredges and better processing facilities. The wholesale removal of maerl habitats and significant reductions in diversity and abundance to adjacent areas at five sites around the coasts of Brittany have also been reported (Barbera et al. 2003) and attributed to commercial extraction (Grall & Hall-Spencer 2003). Trends and threats Maerl habitats are considered highly sensitive to overexploitation and other human activities that result in physical disturbance or deterioration in water quality (Barbera et al. 2003), particularly smothering by fine sediments (Wilson et al. 2004). This sensitivity is compounded by long recovery times due to the slow growth (approximately 1 mm yr−1) and accumulation characteristics of maerl beds. The coralline algae that form the maerl are among the slowest-growing species, and substantial deposits take centuries to millennia to accumulate (Hall-Spencer et al. 2003) so that any effects of habitat removal are irreversible over timescales relevant to humans. The major threats to maerl habitats have been recently reviewed (Barbera et al. 2003). The most obvious threats are from the ongoing commercial extraction. The three main areas of commercial exploitation in Europe have been Brittany, Cornwall and the west of Ireland. Nowadays, only limited extraction takes place in Ireland and the United Kingdom (De Grave & Whitaker 1999) but maerl extraction still forms a major part of the French seaweed industry (Grall & Hall-Spencer 2003). It has been predicted that if extraction rates persist at current levels the large Glenan deposit (Britttany) could be exhausted within 50–100 yr (Grall & Hall-Spencer 2003). In addition to the direct effects of harvesting, other direct and indirect impacts on maerl beds have been noted. Damage to the surface of the beds is caused by towed demersal fishing gear, such as scallop dredges, which significantly reduce bed complexity, biodiversity and long-term viability (Hall-Spencer & Moore 2000, Barbera et al. 2003, Hall-Spencer et al. 2003). Hall-Spencer & Moore (2000) found that scallop (Pecten maximus) dredging in the Clyde Sea led to a 70% reduction of live maerl on a previously unexploited bed with no signs of recovery over the subsequent 4 yr. Permanent moorings for pleasure boats can have similar, more localised, effects (Birkett et al. 1998a). The negative effects of increased eutrophication and turbidity in coastal waters both from silt loads and nutrient runoff from agricultural land and aquaculture have been documented in Galicia and in the Bay of Brest (Birkett et al. 1998a, Barbera et al. 2003). Smothering of maerl beds as a consequence of the invasion of the gastropod Crepidula fornicata has been observed in Breton bays (Grall & Hall-Spencer 2003). Maerl beds are also threatened by land reclamation and proliferation of coastal structures that alter circulation patterns (Birkett et al. 1998a, Barbera et al. 2003). Protection measures Although maerl is confined to a relatively small proportion of European shallow sublittoral waters, their conservation importance is being increasingly recognised (Birkett et al. 1998a, Donnan & 385

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Moore 2003). Two of the most common maerl-forming species, Phymatolithon calcareum and Lithothamnion corallioides, are now the only algal species specified as requiring appropriate management measures under the Habitats Directive (Annex V). Free-living Corallinaceae are also a named component of the habitat ‘Sandbanks which are slightly covered by sea water all of the time’ (EC 2003). Maerl beds are also included in the OSPAR list and Mediterranean Red Book of threatened habitats (Boudouresque et al. 1990, OSPAR Commission 2005). In the United Kingdom, maerl is the subject of a Habitat Action Plan (U.K. Biodiversity Group 1999) and both L. corallioides and Phymatolithon calcareum are on the long list of species in the U.K. Biodiversity Steering Group Report (U.K. Steering Group 1995). Furthermore, in the JNCC interpretation of the EC Habitats Directive, maerl is identified as a key habitat within the Annex I category ‘Sand banks which are slightly covered by seawater at all times’. This means that a number of SACs being designated under the directive will provide protection to the maerl that they contain. Maerl beds occur in three of 12 demonstration SACs within the United Kingdom, while the Fal and Helford (Cornwall) candidate SAC includes the largest maerl bed in England. Recently, the Board of Falmouth Harbour Commissioners in Cornwall has decided to cease licensing maerl extraction (Hall-Spencer 2005). France has also recognised biogenic reefs, such as maerls, as vulnerable habitats, and some maerl grounds in Brittany lie within SACs (Grall & Hall-Spencer 2003). However, many of these are already severely degraded and are affected by dredge fishing, eutrophication and the spread of Crepidula fornicata. Maerl extraction in Brittany is under the control of the French mining management scheme, with quota schemes (80,000 t in 2001 on the Glenan bank) and regular environmental surveys. However, such quotas are considered not compatible with regeneration of the resource (Grall & Hall-Spencer 2003).

Biogenic formations There are other examples of biogenic habitats that are severely affected and presumably have been subject to massive losses over the centuries. However, most of these losses have probably passed unnoticed and the information is scattered and mainly anecdotal. For example, off-shore rocky formations in the north Adriatic Sea, both organogenic and fossil in nature, have been flattened and reduced in size by trawling or other destructive forms of fisheries (Bombace 2001), sometimes to virtual extinction. Mediterranean ‘coralligenous’ reefs, which are considered one of the most valuable and diverse habitats in the Mediterranean Sea, are degraded and highly threatened by a variety of human activities (Ballesteros 2006) but how much coralligenous habitat might have been lost in the past as a consequence of these activities is not known. Significant declines in the extent of wild intertidal mussel beds have been reported from large coastal areas of Germany, the Netherlands and Denmark, and Mytilus edulis beds are now rare in the Wadden Sea (OSPAR Commission 2005, Wolff 2005) and are considered under threat in the United Kingdom (Hiscock et al. 2005). Large subtidal Sabellaria spinulosa reefs in the German Wadden Sea, which provided an important habitat for a wide range of associated species, have been completely lost since the 1920s (U.K. Biodiversity Group 1999, Wolff 2000) and similar losses have been reported also from areas of the northeast Atlantic and the United Kingdom (OSPAR Commission 2005). A significant contraction in the range of S. alveolata reefs on the south coast of England has occurred over a period of at least 20 yr until 1984. Declines have also been reported in the western part of the north Cornish coast, the upper parts of the Bristol Channel and in North Wales and the Dee Estuary but the causes of this regression are not known (U.K. Biodiversity Group 1999). The scarcity of information probably underlies the lack of adequate policies and protection measures for these biogenic habitats. Biogenic reefs and concretions are all broadly covered as ‘Reef’ by the Habitats Directive but most are not specifically mentioned (EC 2003) and even 386

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national and regional initiatives are limited. Coralligenous assemblages are listed in the Red Book of Mediterranean assemblages (Boudouresque et al. 1990) and S. spinulosa reefs are included in the Red List of Macrofaunal Benthic Invertebrates of the Wadden Sea and the OSPAR list of threatened habitats (OSPAR Commission 2005). In the United Kingdom, both S. spinulosa and S. alveolata are the subject of Habitat Action Plans (U.K. Biodiversity Group 1999).

Sedimentary habitats (mudflats, sandflats and subtidal soft bottoms) Current distribution and status Coastal areas are dominated by soft-sediment habitats. The marine biotope classification for Britain and Ireland identifies a number of littoral and sublittoral sediment biotopes (U.K. Biodiversity Group 1999). These are grouped into several major categories (gravels and sands, muddy sands, muds and mixed sediments) and subdivided further according to depth (littoral, infralittoral or circalittoral) and sediment size. Muddy habitats usually occur in sheltered areas, such as sea lochs, enclosed bays and estuaries, whereas sandflats and coarser sediments tend to develop in more exposed situations on the open coast. Distinctions are also sometimes made between estuarine and marine habitats (e.g., OSPAR Commission 2005). Despite the importance of these highly productive soft-sediment habitats, which support large numbers of predatory birds and fishes, providing nursery, feeding and resting areas, and the long history of studies on many aspects of their ecology, no comprehensive inventory of their extent and status is available at a European level, and even regional or local initiatives are rare. The only habitat for which there are some rough estimates of the amount and distribution are intertidal mudflats. In the OSPAR region, the largest continuous area of intertidal mudflats borders the north coasts of Denmark, Germany and the Netherlands in the Wadden Sea, covering around 4990 km2 (OSPAR Commission 2005). In the United Kingdom, intertidal mudflats are widespread, with significant examples in the Wash, the Solway Firth, Mersey Estuary, Bridgwater Bay and Strangford Lough; overall they are estimated to cover about 2700 km2 (U.K. Biodiversity Group 1999). Historical losses and causes The extent of historical losses of soft-bottom habitats is virtually unknown for any country and even regional or local information is scarce. Available information suggests that loss or deep alteration of these types of habitats may have been extremely high, particularly in estuaries and enclosed bays but there is also the possibility that unvegetated soft bottoms have increased their area at the expense of losses in other more structurally complex habitats (e.g., seagrass beds). Past losses are likely to have been related mainly to land claim for agriculture, ports and industrial and urban developments. In the United Kingdom, for example, it is estimated that at least 88% of estuaries have lost intertidal habitats and about 25% of overall estuarine intertidal flats have been removed with peaks of up to 80% in some estuaries such as the Tees (U.K. Biodiversity Group 1999, OSPAR Commission 2005). The amount of intertidal mudflats and sandflats may have also changed significantly over time in relation to coastal erosion, changes in sea levels and human interventions to control these factors (e.g., Lee 2001). Most often, however, these habitats have probably been deeply altered in their fundamental characteristics, including sediment structure and composition, accretion or erosion rates, and inhabiting fauna. As an example, in Europe the massive use of hard defence structures and beach replenishment schemes has deeply changed the structure of shallow surf-zone sediments along whole coastlines in past decades (Airoldi et al. 2005, Martin et al. 2005), as is the case of the north Adriatic Sea (e.g., Figure 5), presumably affecting an enormous and overlooked amount of shallow 387

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soft-bottom habitats. Similarly, most sedimentary benthic systems on the continental shelf of Europe have been modified by fishing activities, particularly bottom trawls and dredging, in the last 100 yr (Ball et al. 2000, Frid et al. 2000). In the southern North Sea fishing is thought to have long been the main ecological structuring force on the benthos, to an extent that makes it difficult even to design robust field experiments due to the virtual lack of control areas (Hall-Spencer & Moore 2000). How much of this transformation should be considered as habitat loss or degradation is difficult to quantify. Trends and threats There is limited organised information on the current trends and threats to sedimentary environments (Brown & Mclachlan 2002). Today the major threats to sedimentary habitats are more likely to be linked to further land claim, construction of marinas and slip ways, the widening and dredging of channels for navigation, pipe and cable laying, oil and gas extraction, tourist developments and infrastructures and the construction of sea defences. Some of these threats have slowed considerably in recent years, at least in some European countries, but they have not stopped. In the United Kingdom, many coastal areas, including estuaries, are now either licensed or available for exploration and development (U.K. Biodiversity Group 1999). Pollution from sewage discharge, aquaculture activities, industries and shipping are also important threats to sedimentary environments and associated fauna, leading to anoxic conditions particularly in estuaries and enclosed basins, as observed in Scandinavian and Baltic waters (Karlson et al. 2002), and to long-term accumulation of contaminants (Islam & Tanaka 2004). Physical disturbance by fishing and aggregate dredging activities also represents a major threat to Europe’s sedimentary habitats and associated biota (Lindeboom & de Groot 1998, Tudela 2004), although nowadays highly disturbed seabeds may appear to be relatively unaffected by fishing activities or other physical disturbances (e.g., Hall-Spencer & Moore 2000). On the Dutch continental shelf, the fisheries are now so intensive that every square metre is trawled, on an average, once to twice a year (Lindeboom 1995), and this broadly applies to the entire sea bed of the North Sea (Gray 1997). Direct extraction of sands and gravels for coastal developments, use in the construction industry and beach nourishments are also major, increasing threats for sedimentary habitats (Newell et al. 1998, van Dalfsen et al. 2000). Extraction of sands has steadily increased in most north European countries during the past few decades (ICES 2006b). In the Netherlands, for example, extraction of sands has increased from <5 million m3 yr−1 in 1974 to >35 million m3 yr−1 in 2001, and in the coming decades an average request of 19–43 million m3 yr−1 is expected. Much of the extracted sand is used for beach recharges and coastal defence. Beach nourishments are being increasingly used along European coasts as a ‘soft’ measure to counteract erosion (Hamm et al. 2002), but the consequences of both the extraction and the disposal of sands on sedimentary habitats and biota have received limited attention (Desprez 2000, van Dalfsen et al. 2000, Simonini et al. 2005). Some projections of loss are available for intertidal areas in relation to possible future changes in sea level, recession of coastlines and coastal ‘squeeze’. For example, sea-level rise is projected to cause a loss of 80–100 km2 of intertidal flats in England between 1993 and 2013 (U.K. Biodiversity Group 1999), particularly in southern and southeast regions; the major firths in Scotland will probably also be affected. Protection measures Protection for intertidal and shallow mudflats and sandflats is provided by various international and E.U. agreements, including the Ramsar Convention, the Bonn Convention, the Bern Convention, 388

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and the Birds and Habitats Directives (Table 1). In particular, ‘Mudflats and sandflats not covered by seawater at low tide’ and ‘Sandbanks which are slightly covered by sea water all the time’ are listed in Annex I of the Habitats Directive. Mudflats are also included within several other designated Annex I Habitats: ‘Estuaries’, ‘Lagoons’ and ‘Large shallow inlets and bays’. Mudflats are also in the list of OSPAR threatened habitats (OSPAR Commission 2005). Some countries also have national protection measures. For example, in the United Kingdom mudflats are the subject of a Habitat Action Plan (U.K. Biodiversity Group 1999); furthermore, over 300 SSSIs including mudflats have been designated in estuaries and 10 coastal ASSIs in Northern Ireland contain significant areas of mudflats. Soft bottoms deeper than 30 m do not seem to be the target of any specific protection measure at a European level (Hiscock et al. 2005), although a number of EC Directives that regulate water quality provide indirect protection from some types of impacts (Table 1). There are, however, national initiatives. For example, in the United Kingdom ‘Sublitoral sands and gravels’ and ‘Mud habitats in deep waters’ are the subjects of Habitat Action Plans (U.K. Biodiversity Group 1999). Commercial fishing activities are excluded from a number of estuaries and bays around the coast of the United Kingdom, which are important nursery areas for juvenile commercial species (e.g., River Exe, River Conwy and Filey Bay). Fishing activities are prohibited within 500 m of gas and oil platforms, from firing ranges and in close proximity to certain military installations (U.K. Biodiversity Group 1999).

Discussion Population density along European coasts has been growing since ancient times. There are increasingly greater demands and impacts on the habitats and resources in coastal environments. The present review has shown that such intensive exploitation has caused dramatic losses and severe deterioration of native coastal habitats (e.g., Tables 2–4). There are many policies and directives Table 4 Summary of main characteristics of European coastlines and habitats based on reviewed sources Characteristic

Value

Main references

Coastline length Population within 50 kmb Degraded coastlines Years of impactc Artificial coastlines Defended/eroding coastlines Increase in N/P loads 1940s–1980s

325,892 km 200 × 106 85% 2500 yr 22,000 km2 7,600/20,000 km 2- to 4-/4- to 8-fold

Number of invasive species MPAs (Number/Total surface) Present coastal wetlands/loss since 1900s Present seagrasses/historical lossesd Present wild native oyster reefs/historical lossesd Present macroalgal beds/historical lossesd

450–600 1,129/ 236,000 km2 51,910 km2/>65% 7290 km2/>65% Scarce/>90% Unknown/2–4 m in depth

Pruett & Cimino 2000 Stanners & Bourdeau 1995 EEA 1999a Rippon 2006, Lotze et al. 2006 EEA 2005 EC 2004 Nehring 1992, EEA 2001, Karlson et al. 2002 Reise et al. 2006 UNEP/WCMC 2006, MPA Global 2006 Nivet & Frazier 2004, EEA 2006a Duarte 2002, Green & Short 2003 Mackenzie et al. 1997 Vogt & Schramm 1991, Eriksson 2002

a

a b c d

Including islands. In the 1990s. Since beginning of modification and transformation of coastal landscapes. Estimate based on reviewed local to regional sources.

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Table 5 Past (earlier than 1900 = P), recent (twentieth century = R) and present (N) main drivers of habitat loss along European coasts based on reviewed sources Wetlands Impact Claim/conversion Coastal development Coastal defence Exploitation Water quality Diseases/pests/predators Destructive fishing Aquaculture

Seagrasses

Macroalgae

P

R

N

P

R

N

P

*** ***

*** *** **

** *** ***

** ***

** *** *

* *** **

?

**

** *

** *

*

**

*** *** *** *

*** ** * **

** ** *

? ? ?

R

N

* ** g * *** ** **

** *ga * *** ** *

Biogenic habitats P

R

*

*

*** ** ** ** *

*** ** *** *** **

N

*** ** *** *** ***

Sediments P

R

N

*** ***

*** *** ** *

** *** *** **

?b

?b

Note: Habitats are coastal wetlands (including salt marshes); seagrass meadows; macroalgal beds (kelps, fucoids and other complex macroalgae); biogenic habitats (including oyster reefs and maerls); and sedimentary habitats (mudflats, sandflats and subtidal soft bottoms). Impacts are drainage, embankment, land claim and habitat conversion (e.g., into agriculture land or into freshwater lake); coastal development including urban and industrial developments, ports and infrastructures, marinas and tourist and recreational developments; coastal defence which includes hard structures, beach nourishments and other measures associated with impacts from erosion, storms and sea-level rise; direct exploitation or harvesting; water quality including organic and chemical pollution and altered sedimentation regimes; outbreaks of diseases, introduced species, competitors or predators; destructive fishing techniques (e.g., trawling); aquaculture. Blank cells = nil or modest, * = low, ** = moderate/locally high, *** = high and widespread, g = habitat gain, ? = not known. a b

Negative effects of beach nourishments, enhancement of substratum availability from hard structures. Fishing affects soft bottoms extensively, but it is difficult to evaluate how many soft sediment habitats are lost.

aimed at reducing and reversing these losses (e.g., Table 1) but their overall positive benefits have been low. Coastal habitats are affected by many threats with a few dominant threats that vary somewhat by habitat and over time (Table 5). The greatest impacts to wetlands have been land claim and coastal development with the latter rising in importance over time. The greatest impacts to seagrasses and macroalgae are presently associated with degraded water quality whereas in the past there have been more effects from destructive fishing and diseases. Coastal development remains an important threat to seagrasses in particular. For biogenic habitats, some of the greatest impacts have been from destructive fishing and overexploitation with additional impacts of disease, particularly to native oysters. Coastal development and defence have had the greatest known impacts on soft-sediment habitats with a high likelihood that trawling has impacted vast areas while not causing loss of soft-sediment habitats per se. Shellfish, oyster reefs in particular, have been among the most severely affected of all coastal habitats by overexploitation and other human-driven changes to the environment. By the late nineteenth century, overfishing combined with outbreaks of diseases, habitat transformation, and the introduction of non-native competitors and parasites, had already wiped out wild Ostrea edulis reefs around much of the European coastline. Where documentation is available, it is evident that the loss of shellfish habitat is a major cause of species extirpation and declines in biodiversity (Wolff 2000, Lotze et al. 2005). Currently most native oyster reefs are functionally or entirely extinct in most coastal areas of Europe and they are probably one of the most endangered marine habitats. However, loss and threats to these habitats are largely overlooked and shellfish beds do not seem to be covered by adequate protection measures, conservation legislation or convention at a European level. Oyster reefs are not mentioned specifically in the Habitats Directive, which sets the present framework for habitat protection in Europe. Although less documented and more 390

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localised, similar losses seem to have occurred also to other types of shellfish reefs and biogenic formations, such as maerl beds, intertidal mussels beds, Sabellaria spp. reefs and coralligenous formations. The current losses in European coastal habitats are alarming; even worse is the fact that these losses are only measured against recent distributions with little recognition of the compounding impact of centuries and millennia of habitat loss. This historical short-sightedness has been referred to as ‘shifting baselines’, where we only recognise declines in the natural environment relative to the baseline of recent memory in each generation (sensu Dayton et al. 1998, Jackson et al. 2001). At present, there seems to be limited public, political and even scientific awareness of the extent, importance and consequences of such a long history of coastal habitat loss (Lotze 2004). The evidence reviewed in the present work clearly indicates that in some European regions most estuarine and near-shore coastal habitats were probably already severely degraded or driven to virtual extinction well before 1900 and sometimes much earlier than that. Ecological descriptions of coastal marine habitats are rather recent (mid-1900s), and long-term documentation of habitat declines and losses are virtually missing for most systems. Even when documentation is available, evidence tends to be overlooked. For example, Wolff (2000) points out how most Dutch people are inclined to ignore the profound habitat changes and losses that occurred during the past 2000 yr in the Wadden Sea, and they tend to consider present-day systems to be in a ‘natural’ state. Nowadays only a small percentage of the European coastline is considered in ‘good’ condition (EEA 1999c). The degradation has continued at high rates over the past few decades. In France, for example, it is estimated that 15% of natural areas on the coast have disappeared since 1976 and are continuing to do so at the rate of 1% a year (Stanners & Bourdeau 1995). In Italy, around 7000 km2 of coastal marshes were present at the beginning of the 1900s, no more than 1920 km2 in 1972 and fewer than 1000 km2 today (Stanners & Bourdeau 1995). Losses of coastal wetlands and seagrasses exceeding 50% of original area have been documented for most countries where long-term data were available, with peaks above 80% for many regions. Beds of complex macroalgae have been under severe recession since at least the early 1900s. An impressive number of local to regional extinctions of habitats have been documented. Overall, it is estimated that every day between 1960 and 1995, a kilometre of ‘unspoilt’ European coastline has been developed (EUCC 1998). Those fragments of native habitats that remain are under continued threat.

Recommendations for conservation and management Fortunately there is recognition at the European level that the current management and conservation of marine diversity and habitats is insufficient. In particular, there have been recent and significant E.U. policies to identify the coastal and marine habitats of Europe and to develop networks of MPAs around them. These efforts have been inspired in part by the international commitments developed as part of the Rio CBD and the World Summit for Sustainable Development. The development of E.U. MPAs is included in the Habitats Directive and the Birds Directive and embodied in particular in the development of protected areas in the NATURA 2000 network. There are also other regional (e.g., OSPAR) and national initiatives with similar aims for protection of endangered habitats and species (Table 1). These policies are necessary but not sufficient. Indeed MPAs alone have limited use for addressing threats such as poor water quality, disease or even coastal development. Some key needs and opportunities for enhancing the overall conservation and management of coastal and marine habitats in Europe are suggested below. Currently, there is no comprehensive summary of the distribution of habitats along European coastlines and their management is not well informed by adequate knowledge of their distribution and status. Despite millennia of reliance on the resources from coastal and marine ecosystems, we cannot accurately describe the distribution of even the shallowest habitats. Detailed habitat mapping 391

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should therefore be given high priority to promote conservation and sustainable management practices. Some databases are available or are being prepared for some countries or habitats but most information is scattered, fragmented or limited to few case studies. At least there has been good progress in developing a consistent habitat classification as part of the European Union Nature Information System (EUNIS) (Davies et al. 2004), which is a necessary precursor to developing a consistent database of habitat distribution. These habitat distributions then need to be compared with the existing protected areas to identify gaps in protection. To fill these gaps, there should be systematic planning for placement of new protected areas and other management measures. Increasingly scientists, agencies and organisations are using systematic planning approaches to target the placement of their protection and management efforts particularly at regional levels (e.g., Beck & Odaya 2001, Possingham et al. 2002, Airamè et al. 2003, Leslie et al. 2003, Beck et al. 2004). These approaches enable decision makers to develop a range of solutions for protection and management and to examine how changes in decisions can affect solutions. The values of these coastal habitats also need to be better assessed to provide real estimates of the ecosystem services that they provide such as pollution regulation, storm hazard reduction, productivity of nurseries for fisheries and recreation (Agardy & Alder 2005). Better valuations of these services will illustrate for communities and governments the real costs of this habitat loss and should provide impetus and economic incentives for their protection and restoration. There are still reasonable opportunities for conservation of coastal habitats in key areas throughout Europe. This protection should be put in place quickly because conservation is cheaper than restoration. The current EC policies are mostly aimed at these protections but they do need to be implemented. Given the extent of damage to coastal habitats, restoration will be required in many places to meet any reasonable goals for conservation and management. Information on historical distributions and loss is extremely important because management goals for these habitats should be based on historical estimates of the distributions of these habitats, not the vastly reduced current distributions (Beck 2003). Even extremely modest goals of 10% protection of the historical distributions of European coastal habitats will require some restoration for many habitats. To meet these goals for conservation and restoration there should be greater involvement by nongovernmental organisations and community groups and there are tools that they can use to contribute directly to conservation and management. These groups have often been involved in efforts to develop MPAs and restore coastal habitats and these efforts should be encouraged and expanded. There are also new tools, such as the private leasing and ownership of marine lands and resources that can be employed more often by private groups to help protect and restore these coastal habitats (Beck et al. 2004). For example, the National Trust in the United Kingdom leases intertidal lands and sea beds from the government along some 180 km of the coast for conservation and restoration. Recently there has been new policy adopted by the French government that allows private groups also to lease subtidal lands as is commonly done by many business interests (e.g., aquaculture industry). Most coastal habitats lie within the exclusive economic zones of individual countries and thus the individual coastal zone management of these countries must be strengthened to protect and manage these habitats. The European Union and member nations have been dedicated to developing better Integrated Coastal Zone Management (ICZM) for some time. The development of strong and effective ICZM programmes has been slow for most nations. These programmes need to advance further to slow and reverse coastal habitat loss. There is much academic and agency interest in developing a more ecosystem-based management (E-BM) approach for managing the many marine resources and the overlapping stakeholder needs for access to these resources (e.g., Browman & Stergiou 2005). E-BM has been incorporated 392

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as a central goal of the European Union’s emerging ‘Marine Strategy’ (Table 1). While this approach is needed and sensible, it will take many years to develop and its development should not be allowed to slow efforts to protect and restore habitats now.

Conclusions Europe has seen decades, centuries, even millennia of coastal habitat loss and it continues today. Estuaries, enclosed bays and near-shore shelf habitats around the European coasts are some of the most degraded environments on Earth as they have been used intensively for thousands of years. These functionally valuable coastal ecosystems are still a focal point for human colonisation and use. Before all the services from these ecosystems are lost, efforts should be redoubled to protect the remaining habitats, slow and stop future losses and restore some of these habitats. Recent efforts toward a more sustainable use of these coastal resources have not reversed the trend. There is no single best strategy for addressing these losses and there are many approaches that can help. Many of these are commonsense recommendations that are common in policies within and between nations, but the progress toward them has been slow with a few exceptions. The United Kingdom clearly has made more progress than most nations in the European Union and internationally. If the long history of physical destruction, fragmentation and transformation is further neglected, and if significant, irreversible thresholds are passed, the future sustainability of those few fragments of native or semi-native habitats that remain may ultimately and finally be compromised.

Acknowledgements The work was supported by a grant from The Nature Conservancy. L.A. was further supported by an Assegno di Ricerca of the University of Bologna. We are grateful to Heike Lotze and Keith Hiscock for valuable input and for comments on an earlier draft of the work and to Robin Gibson for his unfailing support. Many other people stimulated our work and gave useful input/references, including Claudio Battelli, Erik Bonsdorff, Paolo Guidetti, Fiorenza Micheli, Karsten Reise and Enric Sala. We are grateful to all the authors who provided figures from their work and the publishers who agreed to their publication. We thank particularly Klemens Erikkson, who kindly prepared original figures for this work, and Sandy Beck for lending her artistry to Figure 2. We also wish to thank Giovanna Branca, Kendra Karr, Caitlyn Toropova, Dan Dorfman, Chris Shepard and Marco Abbiati for their support at various stages of the work. L.A. is particularly grateful to Elena Fuschini for her invaluable assistance with library searches. This publication is contribution number MPS07016 of the E.U. network of Excellence MarBEF.

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE Beck, M.W., Marsh, T.D., Reisewitz, S.E. & Bortman, M.L. 2004. New tools for marine conservation: the leasing and ownership of submerged lands. Conservation Biology 18, 1214–1223. Beck, M.W. & Odaya, M. 2001. Ecoregional planning in marine environments: identifying priority sites for conservation in the northern Gulf of Mexico. Aquatic Conservation-Marine and Freshwater Ecosystems 11, 235–242. Benedetti-Cecchi, L., Pannacciulli, F., Bulleri, F., Moschella, P.S., Airoldi, L., Relini, G. & Cinelli, F. 2001. Predicting the consequences of anthropogenic disturbance: large-scale effects of loss of canopy algae on rocky shores. Marine Ecology Progress Series 214, 137–150. Berghahn, R. & Ruth, M. 2005. The disappearance of oysters from the Wadden Sea: a cautionary tale for notake zones. Aquatic Conservation: Marine and Freshwater Ecosystems 15, 91–104. Bianchi, C.N. & Peirano, A. 1995. Atlante delle Fanerogame Marine della Liguria. Posidonia oceanica e Cymodocea nodosa. La Spezia: ENEA CRAM, Segraf. Bird, E.C.F. 1993. Submerging Coasts. The Effects of a Rising Sea Level on Coastal Environments. Chichester, U.K.: John Wiley & Sons. Birkett, D.A., Maggs, C.A. & Dring, M.J. 1998a. Maerl (Volume 5). An Overview of Dynamic and Sensitivity Characteristics for Conservation Management of Marine SACs. Scottish Association for Marine Science (U.K. Marine SACs Project). Online. Available HTTP: http://www.ukmarinesac.org.uk/pdfs/ maerl.pdf (accessed 2 August 2006). Birkett, D.A., Maggs, C.A., Dring, M.J., Boaden, P.J.S. & Seed, R. 1998b. Infralittoral Reef Biotopes with Kelp Species (Volume 7). An Overview of Dynamic and Sensitivity Characteristics for Conservation Management of Marine SACs. Scottish Association for Marine Science (U.K. Marine SACs Project). Online. Available HTTP: http://www.ukmarinesac.org.uk/pdfs/reefkelp.pdf (accessed 6 August 2006). Bokn, T.L., Moy, F.E., Magnusson, J.B. & Murray, S.N. 1992. Changes in fucoid distributions and abundances in the Inner Oslofjord, Norway: 1974–1980 versus 1988–1990. Acta Phytogeographica Suecica 78, 117–124. Bombace, G. 2001. Influence of climatic changes on stocks, fish species and marine ecosystems in the Mediterranean sea. Archivio di Oceanografia e Limnologia 22, 67–72. Bondesan, M., Castiglioni, G.B., Elmi, C., Gabbbianelli, G., Marocco, R., Pirazzoli, P.A. & Tomasin, A. 1995. Coastal areas at risk from storm surges and sea-level rise in northeastern Italy. Journal of Coastal Research 11, 1354–1379. Boorman, L.A. 2003. Saltmarsh Review. An Overview of Coastal Saltmarshes, Their Dynamic and Sensitivity Characteristics for Conservation and Management. JNCC Report, No. 334. Peterborough, U.K.: JNCC. Online. Available HTTP: http://www.jncc.gov.uk/page-2347 (accessed 27 July 2006). Boström, C., Baden, S.P. & Krause-Jensen, D. 2003. The seagrasses of Scandinavia and the Baltic Sea. In World Atlas of Seagrasses, E.P. Green & F.T. Short (eds). Berkeley: University of California Press, UNEP-WCMC, 27–37. Boudouresque, C.F., Meinesz, A., Ballesteros, E., Ben Maiz, N., Boisset, F., Cinelli, F., Cirik, S., Cormaci, M., Jeudy de Grissac, A., Laborel, J., Lanfranco, E., Lundberg, B., Mayhoub, H., Panayotidis, O., Semroud, R., Sinnassamy, J.M. & Span, A. 1990. Livre Rouge “Gérard Vuignier” des Végétaux, Peuplements et Paysages Marins Menacés de Méditerranée. Map Technical Report Series, 43. Athens: UNEP/IUCN/GIS Posidonie. Boudouresque, C.F. & Verlaque, M. 2002. Biological pollution in the Mediterranean Sea: invasive versus introduced macrophytes. Marine Pollution Bulletin 44, 32–38. Bray, M.J. & Hooke, J.M. 1997. Prediction of soft-cliff retreat with accelerating sea-level rise. Journal of Coastal Research 13, 453–467. Brooks, T.M., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B., Rylands, A.B., Konstant, W.R., Flick, P., Pilgrim, J., Oldfield, S., Magin, G. & Hilton-Taylors, C. 2002. Habitat loss and extinction in the hotspots of biodiversity. Conservation Biology 16, 909–923. Browman, H.I. & Stergiou, K.I. 2005. Introduction: politics and socio-economics of ecosystem-based management of marine resources. Marine Ecology Progress Series 300, 241 only. Brown, A.C. & Mclachlan, A. 2002. Sandy shore ecosystems and the threats facing them: some predictions for the year 2025. Environmental Conservation 29, 62–77.

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LAURA AIROLDI & MICHAEL W. BECK Bulleri, F. & Airoldi, L. 2005. Artificial marine structures facilitate the spread of a non-indigenous green alga, Codium fragile ssp. tomentosoides, in the north Adriatic Sea. Journal of Applied Ecology 42, 1063–1072. Burke, L., Kura, Y., Kassem, K., Revenga, C., Spalding, M. & Mc Allister, D. 2001. Pilot Analysis of Global Ecosystems. Coastal Ecosystems. Washington, D.C.: WRI. Online. Available HTTP: http://pdf.wri.org/ page_coastal.pdf (accessed 4 August 2006). Cano, J. & Rocamora, J. 1996. Growth of the European flat oyster in the Mediterranean Sea (Murcia, SE Spain). Aquaculture International 4, 67–84. Caressa, S., Ceschia, C., Orel, G. & Treleani, R. 1995. Present and former populations in the Gulf of Trieste between Punta Salvatore and Punta Tagliamento (upper Adriatic). In Posidonia Oceanica. A Contribution to the Preservation of a Major Mediterranean Marine Ecosystem, F. Cinelli et al. (eds). Rivista Maritima 12 (Suppl.), 174–187. Ceccherelli, G. & Cinelli, F. 1997. Short-term effects of nutrient enrichment of the sediment and interactions between the seagrass Cymodocea nodosa and the introduced green alga Caulerpa taxifolia in a Mediterranean bay. Journal of Experimental Marine Biology and Ecology 217, 165–177. Cencini, C. 1998. Physical processes and human activities in the evolution of the Po delta, Italy. Journal of Coastal Research 14, 774–793. Christie, H., Fredriksen, S. & Rinde, E. 1998. Regrowth of kelp and colonization of epiphyte and fauna community after kelp trawling at the coast of Norway. Hydrobiologia 375–376, 49–58. Cicogna, F., Bavestrello, G. & Cattaneo-Vietti, R. (eds). 1999. Red Coral and Other Mediterranean Octocorals: Biology and Protection. Rome: Ministero Politiche Agricole. Connell, S.D. 2005. Assembly and maintenance of subtidal habitat heterogeneity: synergistic effects of light penetration and sedimentation. Marine Ecology Progress Series 289, 53–61. Connor, D.W., Allen, J.H., Golding, N., Howell, K.L., Lieberknecht, L.M., Northen, K.O. & Beker, J.B. 2004. The Marine Habitat Classification for Britain and Ireland. Version 04.05. Peterborough: JNCC. Online. Available HTTP: http://www.jncc.gov.uk/MarineHabitatClassification (accessed 8 June 2006). Cooper, N.J., Cooper, T. & Burd, F. 2001. Twenty-five years of salt marsh erosion in Essex: implications for coastal defence and nature conservation. Journal of Coastal Conservation 7, 31–40. Cormaci, M. & Furnari, G. 1999. Changes of the benthic algal flora of the Tremiti islands (southern Adriatic) Italy. Hydrobiologia 398/399, 75–79. Costanza, R., d’Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Neill, R.V., Paruelo, J., Raskin, R.G., Sutton, P. & van den Belt, M. 1997. The value of the world’s ecosystem services and natural capital. Nature 387, 253–260. Curtis, T.G.F. & Skeffington, M.J.S. 1998. The salt marshes of Ireland: an inventory and account of their geographical variation. Biology and Environment: Proceedings of the Royal Irish Academy 98B, 87–104. Davidson, N.C., Laffoley, D.d., Doody, J.P., Way, L.S., Gordon, J., Key, R., Drake, C.M., Pienkowski, M.W., Mitchell, R. & Duff, K.L. 1991. Nature Conservation and Estuaries in Great Britain. Peterborough, U.K.: Nature Conservancy Council. Davies, C.E., Moss, D. & Hill, M.O. 2004. EUNIS Habitat Classification Revised 2004. Report to EEA and European Topic Centre on Nature Protection and Biodiversity. October 2004. Online. Available HTTP: http://eunis.eea.europa.eu/upload/EUNIS_2004_report.pdf (accessed 1 August 2006). Davison, D.M. & Hughes, D.J. 1998. Zostera Biotopes (Volume 1). An Overview of Dynamics and Sensitivity Characteristics for Conservation Management of Marine SACs. Scottish Association for Marine Science (U.K. Marine SACs Project). Online. Available HTTP: http://www.ukmarinesac.org.uk/ zostera.htm (accessed 15 July 2006). Dayton, P.K., Tegner, M.J., Edwards, P.B. & Riser, K.L. 1998. Sliding baselines, ghosts, and reduced expectations in kelp forest communities. Ecological Applications 8, 309–322. De Grave, S. & Whitaker, A. 1999. A census of maerl beds in Irish waters. Aquatic Conservation: Marine and Freshwater Ecosystems 9, 303–311. Delgado, O., Grau, A., Pou, S., Riera, F., Massuti, C., Zabala, M. & Ballesteros, E. 1997. Seagrass regression caused by fish cultures in Fornells Bay (Menorca, western Mediterranean). Oceanologica Acta 20, 557–563.

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE Den Hartog, C. 1987. ‘Wasting disease’ and other dynamic phenomena in Zostera beds. Aquatic Botany 27, 3–14. Desprez, M. 2000. Physical and biological impact of marine aggregate extraction along the French coast of the Eastern English Channel: short- and long-term post-dredging restoration. ICES Journal of Marine Science 57, 1428–1438. de Villèle, X. & Verlaque, M. 1995. Changes and degradation in a Posidonia oceanica bed invaded by the introduced tropical alga Caulerpa taxifolia in the northwestern Mediterranean. Botanica Marina 38, 79–87. Diaz, R.J. 2001. Overview of hypoxia around the world. Journal of Environmental Quality 30, 275–280. Dijkema, K.S. (ed.) 1984. Saltmarshes in Europe. Nature and Environment Series 30. Strasbourg, France: Council of Europe. Dodd, J. 2005. Native Oysters. Argyll, U.K.: Scottish Natural Heritage. Online. Available HTTP: http://www.snh.org.uk (accessed 19 July 2006). Donnan, D.W. & Moore, P.G. 2003. Introduction. Aquatic Conservation: Marine and Freshwater Ecosystems 13 (Suppl.), 1–3. Doody, J.P. 2004. Coastal squeeze: a historical perspective. Journal of Coastal Conservation 10, 138 only. Duarte, C.M. 2002. The future of seagrass meadows. Environmental Conservation 29, 192–206. Dugan, P. (ed.) 1993. Wetlands in Danger. A World Conservation Atlas. New York: Oxford University Press. EC. 2003. Interpretation Manual of European Union Habitats, Version EUR25. Brussels: EC, DG Environment. Online. Available HTTP: http://ec.europa.eu/environment/nature/nature_conservation/eu_enlargement/ 2004/pdf/habitats_im_en.pdf#search=‘interpretation%20manual%20Habitats%20directive’ (accessed 2 August 2006). EC. 2004. Living with Coastal Erosion in Europe — Sediment and Space for Sustainability. Luxembourg: OPOCE. Online. Available HTTP: http://www.eurosion.org/project/eurosion_en.pdf (accessed 11 September 2006). Edgar, G.J., Barrett, N.S., Graddon, D.J. & Last, P.R. 2000. The conservation significance of estuaries: a classification of Tasmanian estuaries using ecological, physical and demographic attributes as a case study. Biological Conservation 92, 383–397. EEA. 1998. Europe’s Environment: the Second Assessment. State of Environment report No 1/1998. Copenhagen: EEA. Online (summary). Available HTTP: http://reports.eea.europa.eu/92–828–3351–8/en (accessed 24 June 2006). EEA. 1999a. Coastal and marine zones. Chapter 3.14. Environment in the European Union at the Turn of the Century. State of Environment report No 1/1999. Copenhagen: EEA. Online. Available HTTP: http://reports.eea.eu.int/92–9157–202–0/en (accessed 4 August 2006). EEA. 1999b. Corine Land Cover (CLC1990) 250 m - Version 06/1999. Online. Available HTTP: http://dataservice. eea.europa.eu/atlas/viewdata/viewpub.asp?id=65 (accessed 4 August 2006). EEA. 1999c. State and Pressures of the Marine and Coastal Mediterranean Environment. Environmental Issues Series 5. Luxembourg: OPOCE. Online. Available HTTP: http://reports.eea.europa.eu/ ENVSERIES05/en/envissue05.pdf (accessed 4 August 2006). EEA. 2001. Eutrophication in Europe’s Coastal Waters. Topic Report 7. Copenhagen: EEA. Online. Available HTTP: http://reports.eea.eu.int/topic_report_2001_7 (accessed 4 August 2006). EEA. 2002. Europe’s Biodiversity — Biogeographical Regions and Seas. Online. Available HTTP: http://reports.eea.eu.int/report_2002_0524_154909/en (accessed 4 August 2006). EEA. 2005. The European Environment — State and Outlook 2005. Copenhagen: EEA. Online. Available HTTP: http://reports.eea.europa.eu/state_of_environment_report_2005_1/en/SOER2005_all.pdf (accessed 4 August 2006). EEA. 2006a. The Changing Faces of Europe’s Coastal Areas. EEA Report 6/2006. Luxembourg: OPOCE. Online. Available HTTP: http://reports.eea.europa.eu/eea_report_2006_6/en/eea_report_6_2006.pdf (accessed 7 August 2006). EEA. 2006b. Priority Issues in the Mediterranean Environment. EEA Report 4/2006. Luxembourg: OPOCE. Online. Available HTTP: http://reports.eea.europa.eu/eea_report_2006_4/en/medsea_4_2006.pdf (accessed 7 August 2006).

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LAURA AIROLDI & MICHAEL W. BECK Ekebom, J. & Erkkilä, A. 2003. Using aerial photography for identification of marine and coastal habitats under the E.U.’s Habitats Directive. Aquatic Conservation — Marine and Freshwater Ecosystems 13, 287–304. Eriksson, B.K. 2002. Long-Term Changes in Macroalgal Vegetation on the Swedish Coast. An Evaluation of Eutrophication Effects with Special Emphasis on Increased Organic Sedimentation. Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, Upsala University. Uppsala, Sweden: Tryck & Medier. Eriksson, B.K. & Bergstrom, L. 2005. Local distribution patterns of macroalgae in relation to environmental variables in the northern Baltic Proper. Estuarine Coastal and Shelf Science 62, 109–117. Eriksson, B.K., Johansson, G. & Snoeijs, P. 1998. Long-term changes in the sublitoral zonation of brown algae in the southern Bothnian Sea. European Journal of Phycology 33, 241–249. Eriksson, B.K., Johansson, G. & Snoeijs, P. 2002. Long-term changes in the macroalgal vegetation of the inner Gullmar Fjord, Swedish Skagerrak coast. Journal of Phycology 38, 284–296. EUCC — The Coastal Union. 1998. Posidonia beds. In Facts and Figures on Europe’s Biodiversity: State and Trends 1998–1999, B. Delbaere (ed.). Technical Report Series. Tilburg: ECNC. Online. Available HTTP: http://www.coastalguide.org/dune/posidi.html (accessed 7 August 2006). Fanelli, G., Piraino, S., Belmonte, G., Geraci, S. & Boero, F. 1994. Human predation along Apulian rocky coasts (SE Italy): desertification caused by Lithophaga lithophaga (Mollusca) fisheries. Marine Ecology Progress Series 110, 1–8. Finlayson, C.M. & Spiers, A.G. (eds) 1999. Global Review of Wetland Resources and Priorities for Wetland Inventory. Supervising Scientist Report 144. Canberra: Supervising Scientist. Franke, H.D. & Gutow, L. 2004. Long-term changes in the macrozoobenthos around the rocky island of Helgoland (German Bight, North Sea). Helgoland Marine Research 58, 303–310. Frid, C., Hammer, C., Law, R., Loeng, H., Pawlak, J.F., Reid, P.C. & Tasker, M. 2003. Environmental Status of the European Seas. Copenhagen: ICES. Online. Available HTTP: http://www.bmu.de/files/pdfs/ allgemein/application/pdf/ices_report.pdf (accessed 7 August 2006). Frid, C.L.J., Harwood, K.G., Hall, S.J. & Hall, J.A. 2000. Long-term changes in the benthic communities on North Sea fishing grounds. ICES Journal of Marine Science 57, 1303–1309. Glemaréc, M., LeFaou, Y. & Cuq, F. 1997. Long-term changes of seagrass beds in the Glenan Archipelago (South Brittany). Oceanologica Acta 20, 217–227. Gomoiu, M.-T. 1992. Marine eutrophication syndrome in the north-western part of the Black Sea. In Marine Coastal Eutrophication, R.A. Vollenweider et al. (eds). Amsterdam: Elsevier, 683–692. Grall, J. & Hall-Spencer, J.M. 2003. Problems facing maerl conservation in Brittany. Aquatic ConservationMarine and Freshwater Ecosystems 13(Suppl.), 55–64. Gray, J.S. 1997. Marine biodiversity: patterns, threats and conservation needs. Biodiversity and Conservation 6, 153–175. Green, E.P. & Short, F.T. 2003. World Atlas of Seagrasses. Berkeley, California: UNEP-WCMC, University of California Press. Green, M.J.B. & Paine, J. 1997. State of the world’s protected areas at the end of the twentieth century. Paper presented at IUCN World Commission on Protected Areas Symposium on ‘Protected Areas in the Twenty-First Century: From Islands to Networks’. Cambridge, U.K.: WCMC. Online. Available HTTP: http://ariiprotejate.ngo.ro/docs/worldsap.pdf (accessed 28 July 2006). Guidetti, P. 2001. Detecting environmental impacts on the Mediterranean seagrass Posidonia oceanica (L.) Delile: the use of reconstructive methods in combination with ‘beyond BACI’ designs. Journal of Experimental Marine Biology and Ecology 260, 27–39. Guidetti, P., Fraschetti, S., Terlizzi, A. & Boero, F. 2003. Distribution patterns of sea urchins and barrens in shallow Mediterranean rocky reefs impacted by the illegal fishery of the rock-boring mollusc Lithophaga lithophaga. Marine Biology 143, 1135–1142. Günther, R.T. 1897. The oyster culture of the ancient Romans. Journal of the Marine Biological Association of the United Kingdom 4, 360–365. Hagen, N.T. 1995. Recurrent destructive grazing of successionally immature kelp forests by green sea-urchins in Vestfjorden, northern Norway. Marine Ecology Progress Series 123, 95–106. Hall-Spencer, J. 2005. Ban on maerl extraction. Marine Pollution Bulletin 50, 121 only.

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE Hall-Spencer, J.M., Grall, J., Moore, P.G. & Atkinson, R.J.A. 2003. Bivalve fishing and maerl-bed conservation in France and the U.K. — retrospect and prospect. Aquatic Conservation: Marine and Freshwater Ecosystems 13 (Suppl.), 33–41. Hall-Spencer, J.M. & Moore, P.G. 2000. Scallop dredging has profound, long-term impacts on maerl habitats. ICES Journal of Marine Science 57, 1407–1415. Hamm, L., Capobianco, M., Dette, H.H., Lechuga, A., Spanhoff, R. & Stive, M.J.F. 2002. A summary of European experience with shore nourishment. Coastal Engineering 47, 237–264. Hannah, L., Lohse, D., Hutchinson, C., Carr, J.J. & Lankerani, A. 1994. A preliminary inventory of human disturbance of world ecosystems. Ambio 23, 246–250. Hauxwell, J., Cebrián, J., Furlong, C. & Valiela, I. 2001. Macroalgal canopies contribute to eelgrass (Zostera marina) decline in temperate estuarine ecosystems. Ecology 82, 1007–1022. Healy, M.G. & Hickey, K.R. 2002. Historic land reclamation in the intertidal wetlands of the Shannon estuary, western Ireland. Journal of Coastal Research SI 36, 365–373. Heck, K.L., Jr. & Crowder, L.B. 1991. Habitat structure and predator-prey interactions in vegetated aquatic systems. In Habitat Structure: the Physical Arrangement of Objects in Space, S.S. Bell et al. (eds). London: Chapman & Hall, 282–299. HELCOM. 1998. Red List of Marine and Coastal Biotopes and Biotope Complexes of the Baltic Sea, Belt Sea and Kattegat. Baltic Sea Environment Proceedings 75. Helsinki: HELCOM. Online. Available HTTP: http://www.helcom.fi/stc/files/Publications/Proceedings/bsep75.pdf (accessed 7 August 2006). Hemminga, M.A. & Duarte, C.M. 2000. Seagrass Ecology. Cambridge: Cambridge University Press. Hiscock, K. & Kimmance, S. 2003. Review of Current and Historical Time-Series Seabed Biological Studies in the U.K. and Near Europe. JNCC Report 336. Peterborough: JNCC. Online. Available HTTP: http://www.jncc.gov.uk/pdf/jncc336.pdf (accessed 19 July 2006). Hiscock, K., Sewell, J. & Oakley, J. 2005. Marine Health Check 2005. A Report to Gauge the Health of the U.K.’s Sea-Life. Godalming: WWF-UK. Online. Available HTTP: http://www.wwf.org.uk/filelibrary/ pdf/marine_healthcheck05.pdf (accessed 7 August 2006). Hiscock, K. & Tyler-Walters, H. 2006. Assessing the sensitivity of seabed species and biotopes — the Marine Life Information Network (Marlin). Hydrobiologia 555, 309–320. Hoffmann, R.C. 2005. A brief history of aquatic resource use in medieval Europe. Helgoland Marine Research 59, 22–30. Holmer, M., Lassus, P., Stewart, J.E. & Wildish, D.J. 2001. ICES symposium on environmental effects of mariculture. Introduction. ICES Journal of Marine Science 58, 363–368. Hore, J.P. & Jex, E. 1880. The Deterioration of Oyster and Trawl Fisheries of England: Its Causes and Remedy. London: Elliot Stock. Hughes, R.G. & Paramor, O.A.L. 2004. On the loss of saltmarshes in south-east England and methods for their restoration. Journal of Applied Ecology 41, 440–448. ICES. 2006a. Report of the Working Group on Marine Habitat Mapping (WGMHM), 4–7 April, 2006, Galway, Ireland. ICES CM 2006/MHC:05. Copenhagen: ICES. Online. Available HTTP: http://www.ices.dk/ reports/MHC/2006/WGMHM06.pdf (accessed 7 August 2006). ICES. 2006b. Report of the Working Group on the Effects of Extraction of Marine Sediments on the Marine Ecosystems (WGEXT), 4–7 April, 2006, Cork, Ireland. ICES CM 2006/MHC:07. Copenhagen: ICES. Online. Available HTTP: http://www.ices.dk/reports/MHC/2006/WGMHM06.pdf (accessed 7 August 2006). Islam, M.S. & Tanaka, M. 2004. Impacts of pollution on coastal and marine ecosystems including coastal and marine fisheries and approach for management: a review and synthesis. Marine Pollution Bulletin 48, 624–649. Jackson, A. 2003. Ostrea Edulis. Native Oyster. Marine Life Information Network: Biology and Sensitivity Key Information Sub-programme. Plymouth, U.K.: Marine Biological Association of the United Kingdom. Online. Available HTTP: http://www.marlin.ac.uk/species/Ostreaedulis.htm (accessed 7 August 2006). Jackson, J.B.C., Kirby, M.X., Berger, W.H., Bjorndal, K.A., Botsford, L.W., Bourque, B.J., Bradbury, R.H., Cooke, R., Erlandson, J., Estes, J.A., Huges, T.P., Kidwell, S., Lange, C.B., Lenhian, H.S., Pandolfi, J.M., Peterson, C.H., Steneck, R.S., Tegner, M.J. & Warner, R.R. 2001. Historical overfishing and the recent collapse of coastal ecosystems. Science 293, 629–638.

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE Lindeboom, H.J. 1995. Protected areas in the North Sea: an absolute need for future marine research. Helgoland Marine Research 49, 591–602. Lindeboom, H.J. & de Groot, S.J. (eds) 1998. IMPACT-II. The Effects of Different Types of Fisheries on the North Sea and Irish Sea Benthic Ecosystems. Texel, The Netherlands: Netherlands Institute for Sea Research. Lotze, H.K. 2004. Repetitive history of resource depletion and mismanagement: the need for a shift in perspective. Marine Ecology Progress Series 274, 269–303. Lotze, H.K. 2005. Radical changes in the Wadden Sea fauna and flora over the last 2000 years. Helgoland Marine Research 59, 71–83. Lotze, H.K., Lenihan, H.S., Bourque, B.J., Bradbury, R.H., Cooke, R.G., Kay, M.C., Kidwell, S.M., Kirby, M.X., Peterson, C.H. & Jackson, J.B.C. 2006. Depletion, degradation, and recovery potential of estuaries and coastal seas. Science 312, 1806–1809. Lotze, H.K. & Reise, K. 2005. Ecological history of the Wadden Sea. Helgoland Marine Research 59, 1 only. Lotze, H.K., Reise, K., Worm, B., Van Beusekom, J., Busch, M., Ehlers, A., Heinrich, D., Hoffmann, R.C., Holm, P., Jensen, C., Knottnerus, O.S., Langhanki, N., Prummel, W., Vollmer, M. & Wolff, W.J. 2005. Human transformations of the Wadden Sea ecosystem through time: a synthesis. Helgoland Marine Research 59, 84–95. Lozan, J.L. 1996. Nutzung und Veraenderungen von Mollusken und Krebsen der Ostsee. In Warnsignale aus der Ostsee, J.L. Lozan et al. (eds). Berlin: Parey, 197–201. Lumb, C.M. 1990. Algal depth distributions and long-term turbidity changes in the Menai Strait, North Wales. Progress in Underwater Science 15, 85–99. Lundälv, T., Larsson, C.S. & Axelsson, L. 1986. Long-term trends in algal-dominated rocky subtidal communities on the Swedish west coast — a transitional system? Hydrobiologia 142, 81–95. Lüning, K. 1990. Seaweeds, Their Environment, Biogeography and Ecophysiology. New York: John Wiley & Sons. Mackenzie, C.L., Jr., Burrell, V.G., Jr., Rosenfield, A. & Hobart, W.L. (eds). 1997. The History, Present Condition and Future of the Molluscan Fisheries of North and Central America and Europe. Volume 3, Europe. NOAA Technical Report NMFS, 129. Seattle, Washington: U.S. Department of Commerce. Marbà, N., Duarte, C.M., Cebrian, J., Enríquez, S., Gallegos, M.E., Olesen, B. & Sand-Jensen, K. 1996. Growth and population dynamics of Posidonia oceanica on the Spanish Mediterranean coast: elucidating seagrass decline. Marine Ecology Progress Series 137, 203–213. Marbà, N., Duarte, C.M., Holmer, M., Martínez, R., Basterretxea, G., Orfila, A., Jordi, A. & Tintore, J. 2002. Effectiveness of protection of seagrass (Posidonia oceanica) populations in Cabrera National Park. Environmental Conservation 29, 509–518. Marchetti, R., Provini, A. & Crosa, G. 1989. Nutrient load carried by the river Po into the Adriatic Sea. Marine Pollution Bulletin 20, 168–172. Martin, D., Bertasi, F., Colangelo, M.A., de Vries, M., Frost, M., Hawkins, S.J., Macpherson, E., Moschella, P.S., Satta, M.P., Thompson, R.C. & Ceccherelli, V.U. 2005. Ecological impact of coastal defence structures on sediments and mobile infauna: evaluating and forecasting consequences of unavoidable modifications of native habitats. Coastal Engineering 52, 1027–1051. McEvedy, C. & Jones, R. 1978. Atlas of World Population History. New York: Penguin. Meinesz, A., Belsher, T., Thibaut, T., Antolic, B., Mustapha, K.B., Boudouresque, C.-F., Chiaverini, D., Cinelli, F., Cottalorda, J.-M., Djellouli, A., El Abed, A., Orestano, C., Grau, A.M., Ivesa, L., Jaklin, A., Langar, H., Massuti-Pascual, E., Peirano, A., Tunesi, L., de Vaugelas, J., Zavodnik, N. & Zuljevic, A. 2001. The introduced green alga Caulerpa taxifolia continues to spread in the Mediterranean. Biological Invasions 3, 201–210. Meinesz, A., Lefevre, J.R. & Astier, J.M. 1991. Impact of coastal development on the infralittoral zone along the southeastern Mediterranean shore of continental France. Marine Pollution Bulletin 23, 343–347. Messner, U. & von Oertzen, J.A. 1991. Long-term changes in the vertical distribution of macrophytobenthic communities in the Greifswalder Bodden. Acta Ichthyologica et Piscatoria 21(Suppl.), 135–143. Middelboe, A.L. & Sand-Jensen, K. 2000. Long-term changes in macroalgal communities in a Danish estuary. Phycologia 39, 245–257.

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LAURA AIROLDI & MICHAEL W. BECK Milazzo, M., Badalamenti, F., Ceccherelli, G. & Chemello, R. 2004. Boat anchoring on Posidonia oceanica beds in a Marine Protected Area (Italy, western Mediterranean): effect of anchor types in different anchoring stages. Journal of Experimental Marine Biology and Ecology 299, 51–62. Minello, T., Zimmerman, R. & Medina, R. 1994. The importance of edge for natant macrofauna in a created salt marsh. Wetlands 14, 184–198. Mock, G., White, R. & Wagener, A. 1998. Farming Fish: the Aquaculture Boom, W. Vanasselt (ed.). Originally written for World Resources 1998–1999, updated for EarthTrends (July 2001). Online. Available HTTP: http://earthtrends.wri.org/features/view_feature.cfm?theme=1&fid=20 (accessed 20 July 2006). Morris, J.T., Sundareshwar, P.V., Nietch, C.T. & Kjerfve, B.C.D.R. 2002. Responses of coastal wetlands to rising sea level. Ecology 83, 2869–2877. Moschella, P.S., Abbiati, M., Åberg, P., Airoldi, L., Anderson, J.M., Bacchiocchi, F., Bulleri, F., Dinesen, G.E., Frost, M., Gacia, E., Granhag, L., Jonsson, P.R., Satta, M.P., Sundelof, A., Thompson, R.C. & Hawkins, S.J. 2005. Low-crested coastal defence structures as artificial habitats for marine life: using ecological criteria in design. Coastal Engineering 52, 1053–1071. MPA Global. 2006. A database of the world’s Marine Protected Areas. University of British Columbia. Online. Available HTTP: http//www.mpaglobal.org (accessed 9 August 2006). Munda, I.M. 1993. Changes and degradation of seaweed stands in the northern Adriatic. Hydrobiologia 260/261, 239–253. Munda, I.M. 2000. Long-term marine floristic changes around Rovinj (Istrian coast, north Adriatic) estimated on the basis of historical data from Paul Kuckuck’s field diaries from the end of the nineteenth century. Nova Hedwigia 71, 1–36. Nehring, D. 1992. Eutrophication in the Baltic Sea. In Marine Coastal Eutrophication, R.A. Vollenweider et al. (eds). Amsterdam: Elsevier, 673–682. Newell, R.C., Seiderer, L.J. & Hitchcock, D.R. 1998. The impact of dredging works in coastal waters: a review of the sensitivity to disturbance and subsequent recovery of biological resources on the seabed. Oceanography and Marine Biology: An Annual Review 36, 127–178. Nicholls, R.J., Hoozemans, F.M.J. & Marchand, M. 1999. Increasing flood risk and wetland losses due to global sea-level rise: regional and global analyses. Global Environmental Change — Human and Policy Dimensions 9 (Suppl.), 69–87. Nilsson, J., Engkvist, R. & Persson, L.E. 2004. Long-term decline and recent recovery of Fucus populations along the rocky shores of southeast Sweden, Baltic Sea. Aquatic Ecology 38, 587–598. Nivet, C. & Frazier, S. 2004. A Review of European Wetland Inventory Information. Almere The Netherlands: RIZA, Evers Litho en Druk. Occhipinti-Ambrogi, A. 2001. Transfer of marine organisms: a challenge to the conservation of coastal biocenoses. Aquatic Conservation: Marine and Freshwater Ecosystems 11, 243–251. Ocean Studies Board. 2004. Nonnative Oysters in the Chesapeake Bay. Washington, D.C.: National Academy Press. Olenin, S. & Klovaité, K. 1998. Introduction to the marine and coastal environments of Lithuania. In Red List of Marine and Coastal Biotopes and Biotope Complexes of the Baltic Sea, Belt Sea and Kattegat. Baltic Sea Environment Proceedings 75. Helsinki: HELCOM. Online. Available HTTP: http://www.helcom.fi/ stc/files/Publications/Proceedings/bsep75.pdf (accessed 7 August 2006). OSPAR Commission. 2005. Case Reports for the Initial List of Threatened and/or Declining Species and Habitats in the OSPAR Maritime Area. Biodiversity Series: OSPAR Commission. Online. Available HTTP: http://www.ospar.org/documents/dbase/publications/p00198_Case%20reports%20for%20Initial%20list %20of%20species%20and%20habitats%202005%20version.pdf (accessed 8 August 2006). Pandolfi, J.M., Bradbury, R.H., Sala, E., Hughes, T.P., Bjorndal, K.A., Cooke, R.G., McArdle, D., McClenachan, L., Newman, M.J.H., Paredes, G., Warner, R.R. & Jackson, J.B.C. 2003. Global trajectories of the long-term decline of coral reef ecosystems. Science 301, 955–958. Pasqualini, V., Pergent-Martini, C., Clabaut, P. & Pergent, G. 1998. Mapping of Posidonia oceanica using aerial photographs and side scan sonar: application off the island of Corsica (France). Estuarine Coastal and Shelf Science 47, 359–367. Pedersén, M. & Snoeijs, P. 2001. Patterns of macroalgal diversity, community composition and long-term changes along the Swedish west coast. Hydrobiologia 459, 83–102.

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE Petersen, K.S., Rasmussen, K.L., Heinemeier, J. & Rud, N. 1992. Clams before Columbus? Nature 359, 679 only. Piazzi, L., Acunto, S. & Cinelli, F. 2000a. Mapping of Posidonia oceanica beds around Elba Island (western Mediterranean) with integration of direct and indirect methods. Oceanologica Acta 23, 339–346. Piazzi, L., Acunto, S., Papi, I., Pardi, G. & Cinelli, F. 2000b. Mapping of the seagrasses beds in Tuscany (Italy): situation in 1998. Biologia Marina Mediterranea 7, 594–596. Pihl, L., Baden, S., Kautsky, N., Ronnback, P., Soderqvist, T., Troell, M. & Wennhage, H. 2006. Shift in fish assemblage structure due to loss of seagrass Zostera marina habitats in Sweden. Estuarine Coastal and Shelf Science 67, 123–132. Possingham, H., Ball, I. & Andelman, S. 2002. Mathematical models for identifying representative reserve networks. In Quantitative Methods in Conservation Biology, S. Ferson & M.A. Burgman (eds). New York: Springer-Verlag, second edition, 291–306. Pruett, L. & Cimino, J. 2000. Global Maritime Boundaries Database (GMBD). Fairfax, Virginia, U.S.: Veridian — MRJ Technology Solutions. Online. Available HTTP: http://earthtrends.wri.org/text/ coastal-marine/variable-61.html (accessed 13 July 2006). Pukaric, S.B.G.W. & Jorissen, F.J. 1990. Successive appearance of subfossil phytoplankton species in Holocene sediments of the northern Adriatic and its relation to the increased eutrophication pressure. Estuarine Coastal and Shelf Science 31, 177–187. Rask, N., Pedersen, S.E. & Jensen, M.H. 1999. Response to lowered nutrient discharge in coastal waters around the island of Funen, Denmark. Hydrobiologia 393, 69–81. Reise, K. 1994. Changing life under the tides of the Wadden Sea during the twentieth century. Ophelia Suppl. 6, 117–125. Reise, K. 2005. Coast of change: habitat loss and transformations in the Wadden Sea. Helgoland Marine Research 59, 9–21. Reise, K., Olenin, S. & Thieltges, D.W. 2006. Are aliens threatening European aquatic coastal ecosystems? Helgoland Marine Research 60, 77–83. Rippon, S. 1997. The Severn Estuary: Landscape Evolution and Wetland Reclamation. London: Leicester University Press. Rippon, S. 2000. The Transformation of Coastal Wetlands: Exploitation and Management of Marshland Landscapes in North West Europe During the Roman and Medieval Periods. London: British Academy. Rismondo, A., Guidetti, P. & Curiel, D. 1997. Presenza delle fanerogame marine nel Golfo di Venezia: un aggiornamento. Bollettino del Museo Civico di Storia Naturale di Venezia 47, 317–328. Rodríguez-Prieto, C. & Polo, L. 1996. Effects of sewage pollution in the structure and dynamics of the community of Cystoseira mediterranea (Fucales, Phaeophyceae). Scientia Marina 60, 253–263. Rosenberg, R., Elmgren, R., Fleischer, S., Jonsson, P., Persson, G. & Dahlin, H. 1990. Marine eutrophication case studies in Sweden. Ambio 19, 102–108. Russo, G.F. & Cicogna, F. 1991. The date mussel (Lithophaga lithophaga), a ‘case’ in the Gulf of Naples. In Les Espèces Marines à Protéger en Méditérranée, C.F. Boudouresque et al. (eds). Marseille: GIS Posidonie, 141–150. Sala, E. 2004. The past and present topology and structure of Mediterranean subtidal rocky-shore food webs. Ecosystems 7, 333–340. Sandulli, R., Bianchi, C.N., Cocito, S., Morgigni, M., Sgorbini, S., Silvestri, C., Morri, C. & Peirano, A. 1994. Status of some Posidonia oceanica meadows on the Ligurian coast influenced by the Haven oil spill. In Atti Del 10° Congresso AIOL (Associazione Italiana Oceanologia e Linmologia), G. Albertelli et al. (eds). Genova, Italy: AIOL, 277–286. Sangiorgi, F. & Donders, T.H. 2004. Reconstructing 150 years of eutrophication in the north-western Adriatic Sea (Italy) using dinoflagellate cysts, pollen and spores. Estuarine Coastal and Shelf Science 60, 69–79. Schories, D., Albrecht, A. & Lotze, H. 1997. Historical changes and inventory of macroalgae from Königshafen Bay in the northern Wadden Sea. Helgoländer Meeresuntersuntersuchungen 51, 321–341. Sebens, K.P. 1994. Biodiversity of coral reefs: what are we loosing and why? American Zoologist 34, 115–133. Sfriso, A. 1987. Flora and vertical distribution of macroalgae in the lagoon of Venice: a comparison with previous studies. Giornale Botanico Italiano 121, 69–85.

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LAURA AIROLDI & MICHAEL W. BECK Sfriso, A. & La Rocca, B. 2005. Aggiornamento sulle macroalghe presenti lungo i litorali e sui bassofondali della laguna di Venezia. Lavori della Società Veneziana di Scienze Naturali 30, 45–56. Short, F.T. & Wyllie-Echeverria, S. 1996. Natural and human-induced disturbance of seagrasses. Environmental Conservation 23, 17–27. Sih, A., Jonsson, B.G. & Luikart, G. 2000. Habitat loss: ecological, evolutionary and genetic consequences. Trends in Ecology and Evolution 15, 132–134. Simonini, R., Ansaloni, I., Bonvicini Pagliai, A.M., Cavallini, F., Iotti, M., Mauri, M., Montanari, G., Preti, M., Rinaldi, A. & Prevedelli, D. 2005. The effects of sand extraction on the macrobenthos of a relict sands area (northern Adriatic Sea): results 12 months post-extraction. Marine Pollution Bulletin 50, 768–777. Spalding, M.D., Green, E.P. & Rvilious, C. 2001. World Atlas of Coral Reefs. Berkeley, California: UNEPWCMC, University of California Press. Stanners, D. & Bourdeau, P. (eds) 1995. Europe’s Environment. The DOBRIS Assessment. State of Environment Report 1/1995. Copenhagen: EEA. Online. Available HTTP: http://reports.eea.eu.int/92–826–5409–5/en (accessed 4 August 2006). Steneck, R.S., Graham, M.H., Bourque, B.J., Corbett, D., Erlandson, J.M., Estes, J.A. & Tegner, M.J. 2002. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environmental Conservation 29, 436–459. Suchanek, T.H. 1994. Temperate coastal marine communities: biodiversity and threats. American Zoologist 34, 100–114. Thibaut, T., Pinedo, S., Torras, X. & Ballesteros, E. 2005. Long-term decline of the populations of Fucales (Cystoseira spp. and Sargassum spp.) in the Alberes coast (France, north-western Mediterranean). Marine Pollution Bulletin 50, 1472–1489. Thompson, R.C., Crowe, T.P. & Hawkins, S.J. 2002. Rocky intertidal communities: past environmental changes, present status and predictions for the next 25 years. Environmental Conservation 29, 168–191. Thrush, S.F. & Dayton, P.K. 2002. Disturbance to marine benthic habitats by trawling and dredging: implications for marine biodiversity. Annual Reviews of Ecology and Systematics 33, 449–473. Trombini, C., Fabbri, D., Lombardo, M., Vassura, I., Zavoli, E. & Horvat, M. 2003. Mercury and methylmercury contamination in surficial sediments and clams of a coastal lagoon (Pialassa Baiona, Ravenna, Italy). Continental Shelf Research 23, 1821–1831. Tudela, S. 2004. Ecosystem Effects of Fishing in the Mediterranean: An Analysis of the Major Threats of Fishing Gear and Practices to Biodiversity and Marine Habitats. Studies and Reviews. General Fisheries Commission for the Mediterranean 74. Rome: FAO. Online. Available HTTP: http://www. fao.org/docrep/007/y5594e/y5594e00.htm (accessed 1 August 2006). Turner, S.J., Thrush, S.F., Hewitt, J.E., Cummings, V.J. & Funnell, G. 1999. Fishing impacts and the degradation or loss of habitat structure. Fisheries Management and Ecology 6, 401–420. Tyler-Walters, H. 2001. Ostrea Edulis Beds on Shallow Sublittoral Muddy Sediment. Marine Life Information Network: Biology and Sensitivity Key Information Sub-programme. Plymouth, U.K.: Marine Biological Association of the United Kingdom. Online. Available HTTP: http://www.marlin.ac.uk/biotopes/ Bio_BasicInfo_IMX.Ost.htm (accessed 8 August 2006). U.K. Biodiversity Group. 1999. U.K. Biodiversity Group Tranche 2 Action Plans — Volume 5: Maritime Species and Habitats. Peterborough, U.K.: English Nature. Online. Available HTTP: http://www. ukbap.org.uk/Library/Tranche2_Vol5.pdf (accessed 2 August 2006). U.K. Steering Group. 1995. Biodiversity: The U.K. Steering Group Report — Volume 2: Action Plans (Annex F: Lists of Key Species, Key Habitats and Broad Habitats). London: HMSO. Online. Available HTTP: http://www.ukbap.org.uk/Library/Tranche1_Ann_f.pdf (accessed 2 August 2006). UNEP/FAO/WHO. 1996. Assessment of the State of Eutrophication in the Mediterranean Sea. MAP Technical Series 106. Athens: UNEP. UNEP/MAP/PAP. 2001. White Paper: Coastal Zone Management in the Mediterranean. Split: Priority Actions Programme. Online. Available HTTP: http://www.pap-thecoastcentre.org/pdfs/ICAM%20in %20Mediterranean%20%20White%20Paper.pdf#search=‘White%20paper%3A%20coastal%20zon% 20management%20in%20the%20Mediterranean’ (accessed 8 August 2006).

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LOSS, STATUS AND TRENDS FOR COASTAL MARINE HABITATS OF EUROPE UNEP/WCMC. 2006. 2006 World Database on Protected Areas: UNEP-WCMC. Online. Available HTTP: http://sea.unep-wcmc.org/wdpa/ (accessed 8 August 2006). Valiela, I. 2006. Global Coastal Change. Singapore: Blackwell. Valiela, I., Bowen, J.L. & York, J.K. 2001. Mangrove forests: one of the world’s threatened major tropical environments. BioScience 51, 807–815. van Beusekom, J.E.E. 2005. A historic perspective on Wadden Sea eutrophication. Helgoland Marine Research 59, 45–54. van Dalfsen, J.A., Essink, K., Madsen, H.T., Birklund, J., Romero, J. & Manzanera, M. 2000. Differential response of macrozoobenthos to marine sand extraction in the North Sea and the western Mediterranean. ICES Journal of Marine Science, 57, 1439–1445. van den Berg, J.B., Kozyreff, G., Lin, H.-X., McDarby, J., Peletier, M.A., Planqué, R. & Wilson, P.L. 2005. Japanese oysters in Dutch waters. Nieuw Archief voor Wiskunde 5/6, 130–141. Vogt, H. & Schramm, W. 1991. Conspicuous decline of Fucus in Kiel Bay (western Baltic): what are the causes? Marine Ecology Progress Series 69, 189–194. Váradi, L. 2001. Review of trends in the development of European inland aquaculture linkages with fisheries. Fisheries Management and Ecology 8, 453–462. Watling, L. & Norse, E.A. 1998. Disturbance of the seabed by mobile fishing gear: a comparison to forest clearcutting. Conservation Biology 12, 1180–1197. Wilcove, D.S., Rothstein, D., Dobow, J., Phillips, A. & Losos, E. 1998. Quantifying threats to imperiled species in the United States. BioScience 48, 607–615. Wilkie, M.L. & Fortuna, S. 2003. Status and Trends in Mangrove Area Extent Worldwide. Forest Resources Assessment Working Paper 63. Rome: Forest Resources Division, FAO. Online. Available HTTP: http://www.fao.org/docrep/007/j1533e/j1533e00.HTM (accessed 4 August 2006). Wilkinson, C.R. (ed.) 2004. Status of Coral Reefs of the World: 2004. Volumes 1 and 2. Townsville, Australia: Australian Institute of Marine Science. Online. Available HTTP: http://www.aims.gov.au/pages/ research/coral-bleaching/scr2004/index.html (accessed 4 August 2006). Wilson, S., Blake, C., Berges, J.A. & Maggs, C.A. 2004. Environmental tolerances of free-living coralline algae (maerl): implications for European marine conservation. Biological Conservation, 120, 283–293. Wolff, W.J. 1992. The end of a tradition: 1000 years of embankment and reclamation of wetlands in the Netherlands. Ambio 21, 287–291. Wolff, W.J. 1997. Development of the conservation of Dutch coastal waters. Aquatic Conservation: Marine and Freshwater Ecosystems 7, 165–177. Wolff, W.J. 2000. Causes of extirpations in the Wadden Sea, an estuarine area in the Netherlands. Conservation Biology 14, 876–885. Wolff, W.J. 2005. The exploitation of living resources in the Dutch Wadden Sea: a historical overview. Helgoland Marine Research 59, 31–38. Wolters, M., Bakker, J.P., Bertness, M.D., Jefferies, R.L. & Moller, I. 2005. Saltmarsh erosion and restoration in south-east England: squeezing the evidence requires realignment. Journal of Applied Ecology 42, 844–851. Worm, B., Lotze, H.K., Boström, C., Engkvist, R., Labanauskas, V. & Sommer, U. 1999. Marine diversity shift linked to interactions among grazers, nutrients and propagule banks. Marine Ecology Progress Series 185, 309–314. Yonge, C.M. 1966. Oysters. London: Collins. Zaitsev, Y.P. (ed.) 2006. Black Sea Red Data Book. Online. Available HTTP: http://www.grid.unep.ch/bsein/ redbook/index.htm (accessed 11 July 2006). Zavodnik, N. & Jaklin, A. 1990. Long-term changes in the northern Adriatic marine phanerogam beds. Rapport de la Commission Internationale pour l’Exploration Scientifique de la Mer Méditerranée 32, 15 only.

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Oceanography and Marine Biology: An Annual Review, 2007, 45, 407-478 © R. N. Gibson, R. J. A. Atkinson, and J. D. M. Gordon, Editors Taylor & Francis

CLIMATE CHANGE AND AUSTRALIAN MARINE LIFE E.S. POLOCZANSKA1, R.C. BABCOCK2, A. BUTLER1, A.J. HOBDAY3,6, O. HOEGH-GULDBERG4, T.J. KUNZ3, R. MATEAR3, D.A. MILTON1, T.A. OKEY1 & A.J. RICHARDSON1,5 1Wealth from Oceans Flagship — CSIRO Marine & Atmospheric Research, PO Box 120, Cleveland, Queensland 4163, Australia E-mail: [email protected] 2Wealth from Oceans Flagship — CSIRO Marine & Atmospheric Research, Private Bag 5, Floreat, Western Australia 6913, Australia 3Wealth from Oceans Flagship — CSIRO Marine & Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia 4University of Queensland, Centre for Marine Studies, St Lucia, Queensland 4072, Australia 5University of Queensland, Department of Mathematics, St Lucia, Queensland 4072, Australia 6University of Tasmania, School of Zoology, Private Bag 5, Hobart, Tasmania 7001, Australia Abstract Australia’s marine life is highly diverse and endemic. Here we describe projections of climate change in Australian waters and examine from the literature likely impacts of these changes on Australian marine biodiversity. For the Australian region, climate model simulations project oceanic warming, an increase in ocean stratification and decrease in mixing depth, a strengthening of the East Australian Current, increased ocean acidification, a rise in sea level, alterations in cloud cover and ozone levels altering the levels of solar radiation reaching the ocean surface, and altered storm and rainfall regimes. Evidence of climate change impacts on biological systems are generally scarce in Australia compared to the Northern Hemisphere. The poor observational records in Australia are attributed to a lack of studies of climate impacts on natural systems and species at regional or national scales. However, there are notable exceptions such as widespread bleaching of corals on the Great Barrier Reef and poleward shifts in temperate fish populations. Biological changes are likely to be considerable and to have economic and broad ecological consequences, especially in climate-change ‘hot spots’ such as the Tasman Sea and the Great Barrier Reef.

Introduction The global climate is changing and is projected to continue changing at a rapid rate for the next 100 yr (IPCC 2001, 2007). Average global temperatures have risen by 0.6 ± 0.2°C over the twentieth century and this warming is likely to have been greater than for any other century in the last millennium. The 1990s were the warmest decade globally of the past century; and the present decade may be warmest yet (Hansen et al. 2006). Most of the warming observed during the last 50 yr is attributable to anthropogenic forcing by greenhouse gas emissions (Karoly & Stott 2006). The increase in global temperature is likely to be accompanied by alterations in patterns and strength of winds and ocean currents, atmospheric and ocean stratification, a rise in sea levels, acidification of the oceans and changes in rainfall, storm patterns and intensity. Evidence is mounting that the

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changing climate is already impacting terrestrial, marine and freshwater ecosystems (HoeghGuldberg 1999, Walther et al. 2002, Parmesan & Yohe 2003, Root et al. 2003, Walther et al. 2005). Species’ distributions are shifting poleward (Parmesan et al. 1999, Thomas & Lennon 1999, Beaugrand et al. 2002, Hickling et al. 2006), plants are flowering earlier and growing seasons are lengthening (Edwards & Richardson 2004, Wolfe et al. 2005, Linderholm 2006, Schwartz et al. 2006) and timing of peak breeding and migrations of animals are altering (Both et al. 2004, Lehikoinen et al. 2004, Weishampel et al. 2004, Jonzén et al. 2006, Menzel et al. 2006). Most of this evidence, however, is from the Northern Hemisphere, with few examples from the Southern Hemisphere and only a handful from Australia (Chambers 2006). The lack of observations in Australia is attributed to a lack of studies of climate impacts on natural systems and species at regional or national scales. Further, the extent of historical biological datasets in Australia is largely unknown, many are held by small organisations or by individuals and the value of these datasets may not be recognised (Chambers 2006). Because of the unique geological, oceanographic and biological characteristics of Australia, conclusions from climate impact studies in the Northern Hemisphere are not easily transferable to Australian systems. Including fringing islands, Australia has a coastline of almost 60,000 km (Figure 1) that spans from southern temperate waters of Tasmania and Victoria (~45°S) to northern tropical waters of Cape York, Queensland (~10°S). Australia is truly a maritime country with over 90% of the population living within 120 km of the coast. Most of Australia’s population of 20 million live in the southeast with the west and north coasts being sparsely populated. Around 40% of Australia’s population live in the cities of Sydney and Melbourne alone (Australian Bureau of Statistics 2006).

10° Indian Ocean

Exmouth Gulf

Scott Reef

Torres Strait Darwin Gulf of Carpentaria

Cape York

Great Barrier Reef

20° Hervey Bay Shark Bay

30°

Pacific Ocean

Australia Brisbane Moreton Bay

Houtman Abrolhos Islands Perth

Adelaide

Albany

Sydney

Hawkesbury Estuary Botany Bay

Melbourne Corner Inlet Bass Strait Tasman Sea

40°

Tasmania

Southern Ocean

New Zealand

Hobart

Tasmanian Seamounts Marine Reserve

50° 110°

120°

130°

140°

150°

160°

170°

180°

190°

Figure 1 (See also Colour Figure 1 in the insert following page 344.) Map of Australia indicating the locations discussed in the text. The 200 nm EEZ for Australia is marked by the dashed line, and the 200 m depth contour by the solid line.

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Australia has sovereign rights over ~8.1 million km2 of ocean and this area generates considerable economic wealth estimated as $A52 billion per year or about 8% of gross domestic product (CSIRO 2006). Fisheries and aquaculture are important industries in Australia, both economically (gross value over $A2.5 billion) and socially. Marine life and ecosystems also provide invaluable services including coastal defence, nutrient recycling and greenhouse gas regulation valued globally at $US 22 trillion ($A27 trillion) per annum (Costanza et al. 1997). The annual economic values of Australian marine biomes have been estimated: open ocean $A464.7 billion, seagrass/algal beds $A175.1 billion, coral reefs $A53.5 billion, shelf system $A597.9 billion and tidal marsh/mangroves $A39.1 billion (Blackwell 2005). This assessment assumes Australian marine ecosystems are unstressed so actual values may be lower for degraded systems. Compared to other countries, relatively little is known about the biology and ecology of Australia’s maritime realm, mainly due to the inaccessibility and remoteness of much of the coast as highlighted by the discovery of living stromatolites (representing the one of the oldest known forms of life on Earth) in Western Australia in the 1950s (Logan 1961). Australia is unique among continents in that both the west and east coasts are bounded by major poleward-flowing warm currents (Figure 2), which have considerable influence on marine flora and fauna. The East Australian Current (EAC) originates in the Coral Sea and flows southward before separating from the continental margin to flow northeast and eastward into the Tasman Sea (Ridgway & Godfrey 1997, Ridgway & Dunn 2003). Eddies spawned by the EAC continue southward into the Tasman Sea bringing episodic incursions of warm water to temperate eastern Australia and Tasmanian waters (Ridgway & Godfrey 1997). The Leeuwin Current flows southward along the Western Australian coast and continues eastward into and across the Great Australian Bight reaching the west of Tasmania in austral winter (Ridgway & Condie 2004). The influence of these currents is evident from the occurrence of tropical fauna and flora in southern Australian waters at normally temperate latitudes (Maxwell & Cresswell 1981, Wells 1985, Dunlop & Wooller 1990, O’Hara & Poore 2000, Griffiths 2003). The importance of these major currents in structuring marine communities can be seen in the biogeographic distributions of many species, functional

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Figure 2 Major currents and circulation patterns around Australia. The continent is bounded by the Pacific Ocean to the east, the Indian Ocean to the west and the Southern Ocean to the south. Figure courtesy of S. Condie/CSIRO.

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Figure 3 (See also Colour Figure 3 in the insert.) Phytoplankton provinces around Australia. In northern shelf waters westwards from Torres Strait tropical diatom species dominate, with slight regional differences in relative abundances and absolute biomass (1a-c). The shallow waters of the Great Barrier Reef region (3) are dominated by fast-growing nano-sized diatoms. The deeper waters of the Indian Ocean and the Coral Sea are characterised by a tropical oceanic flora (2a and 2c, respectively) that is dominated by dinoflagellates and follows the Leeuwin Current (2b) and the East Australia Current and its eddies (2d). South-eastern coastal waters harbour a temperate phytoplankton flora (4) with seasonal succession of different diatom and dinoflagellate communities. Waters south of the tropical and temperate phytoplankton provinces are characterised by an oceanic transition flora (5a,b) that communicates to the subantarctic phytoplankton province (6) and is highly variable in extent. The phytoplankton provinces are associated with surface water masses and the zooplankton fauna likely shows a similar pattern (Figure prepared by G.M. Hallegraeff for CSIRO and National Oceans Office).

groups and communities. For example, there is broad agreement between phytoplankton community distributions and water masses (Figure 3). Australian waters are generally nutrient poor (oligotrophic), particularly with respect to nitrate and phosphate because the boundary currents are largely of tropical and subtropical origins and there is little input from terrestrial sources. In general, Australia has a low average annual rainfall and this rainfall is highly variable. Much of the interior is desert and in the west the aridity extends to the coast. Monsoonal rains fall in the tropical north during the wet season (December to March) with cyclones common at this time, but there is little or no rainfall during the rest of the year. Australian soil is generally low in nutrients and this, together with the high variability in rainfall, results in little terrestrial nutrient input into the surrounding sea. The generally oligotrophic status of Australian marine waters contrasts with many mid-latitude productive coastal areas around the world. This distinction is particularly strong on the western coast of Australia where the Leeuwin Current replaces the upwelling systems produced by the highly productive eastern boundary currents characteristic of all other major ocean basins. The impact of changing productivity on marine oligotrophic systems is largely unknown; they may not be as resilient to stress and disturbance, including climate change, as more productive 410

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systems that commonly experience considerable interannual variability. Changes in the terrestrial climate also impact Australia’s marine ecosystems to a greater degree than other parts of the world, so it may not be possible to generalise easily from knowledge elsewhere. Aeolian dust input may be an important regulator of coastal primary production. In regions south of Tasmania, where macronutrient concentrations are always high, iron availability influences growth, biomass and composition of phytoplankton (Sedwick et al. 1999, Boyd et al. 2000). In the macronutrient-limited regions more typical of the waters around continental Australia, the atmospheric supply of iron may stimulate nitrogen-fixing phytoplankton, which have a higher iron requirement than other phytoplankton and therefore influence phytoplankton community composition (Jickells et al. 2005). Climate-induced changes in wind or rainfall may thus have disproportionately large consequences for waters around Australia. Climate change will influence physiology, abundance, distribution and phenology of species both directly and indirectly, although impacts will usually become most apparent at an ecosystem level. Given the intrinsic complexity of ecosystems and the uncertainties in future climate projections, predicting consequences for biodiversity is difficult and highly speculative. Response rates will depend on the magnitude of changes and on longevity of the species involved in a particular system. Plankton systems will therefore respond quickly (Hays et al. 2005), whereas a lag might generally be expected in responses of long-lived species. The ability for adaptation to change will also vary among species but the rapid rate of present climate change coupled with high exploitation and destruction or alteration of habitats will compromise the resilience of many populations and ecosystems (Travis 2002). Strategies for adaptation and mitigation of climate change impacts must begin with the identification of ecosystems or populations that are most vulnerable to change and those most vulnerable to other anthropogenic stressors. In this review, we address the potential impacts of climate variability and climate change on Australian marine life from the intertidal zone through pelagic waters and into the deep sea. We provide a synopsis of climate change projections for Australia of key climate variables known to regulate marine ecosystems from the only IPCC (Intergovernmental Panel of Climate Change) climate system model constructed in the Southern Hemisphere, the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk3.5 model. Our focus is on the critical variables that regulate processes in marine ecosystems, namely, temperature, winds, currents, solar radiation, mixed-layer depth and stratification, pH and calcium carbonate saturation state, storms and precipitation, and sea level. We review the expected impacts on species and communities of changes in each of these variables based on laboratory, modelling and field work and concentrate on biological groups found in three broad ecosystems: coastal, pelagic and offshore benthic.

Australian marine biodiversity Australia has highly diverse and unique marine flora and fauna, ranging from spectacular coral reefs in the tropics to giant kelp forests in Tasmanian waters. The biodiversity of tropical Australia is high because it is a continuation of the Indo-Pacific biodiversity hot spot, but much of this fauna is threatened by overharvesting and unregulated development in this region including countries to the north of Australia. The species diversity of seagrasses and mangroves is among the world’s highest, particularly in tropical Australia (Walker & Prince 1987, Kirkman 1997, Walker et al. 1999). Temperate Australian waters contain high numbers of endemic organisms due to their long history of geographic isolation from other temperate regions (Poore 2001). Australian waters also harbour species and ecosystems that are of international importance. The best-known example is the Great Barrier Reef, which is the world’s largest World Heritage Area and extends some 2100 km along the coast of northeast Australia.

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Although Australian temperate waters have lower species diversity than the northern tropical waters, they harbour much higher numbers of endemic species (Poore 2001). Approximately 85% of fish species, 90% of echinoderm species and 95% of mollusc species in these southern waters are endemic (Poore 2001). This high endemism is also documented in Australia’s temperate macroalgae (Bolton 1996, Phillips 2001). High endemism along the southern coastline is partly the result of low dispersal abilities of species and the presence of ecological barriers to dispersal along the southern coastal waters such as a sharp temperature gradient near the cessation of the Leeuwin Current and the absence of near-shore rocky reefs in the centre of the Great Australian Bight and at other locations along the southern Australian coastline. Australia’s fish fauna is extremely diverse and endemic by world standards due to a high diversity of tropical and temperate habitats and due to the geographic isolation of the temperate regions. Pelagic fish found around Australia include iconic species such as tuna, billfish (swordfish and marlin) and sharks. The continental shelf waters off southern Queensland have been identified as a biodiversity hot-spot for large pelagic fishes (Worm et al. 2003). In contrast to the pattern elsewhere, this Australian pelagic fish hot spot is located in an area of high catch rates and fishing effort (Campbell & Hobday 2003). Valuable fisheries exist, despite the generally low productivity of Australian marine waters; these include the Northern Prawn Fishery, the Southern Bluefin Tuna Fishery, the Eastern Tuna and Billfish Fishery and the Western Rock Lobster Fishery. Small pelagic species, such as sardines, jack mackerel, redbait and squid are captured in lower-value but highvolume coastal fisheries operating from a number of Australian ports. For many of these, there are well-known correlations between environmental factors and the productivity of the fishery. For example, the size of the Western Rock Lobster Panulirus cygnus Fishery, which is Australia’s most important single-species fishery and the world’s largest rock lobster fishery, varies in a predictable manner with the strength of the Leeuwin Current (Caputi et al. 2001). Similarly, size of banana prawn Penaeus merguiensis catches in some areas of northern Australia is correlated with wet season rainfall (Staples et al. 1982, Vance et al. 1985). These variables are likely to change as climate changes. Further offshore, cold-water corals are found on seamounts and the continental rise, particularly within the Tasmanian Seamounts Marine Reserve. Cold-water corals are hot spots for biodiversity, comparable to shallow tropical coral reefs, although little is known of their ecology, population dynamics or distribution in Australian waters. Over 850 macro- and megafaunal species were recently found on seamounts in the Tasman and southeast Coral Seas, of which 29–34% were potential endemics or new to science (Richer de Forges et al. 2000, Williams et al. 2006). Globally significant populations of many other groups occur in Australia including populations of marine turtles, marine mammals and seabirds. Six of the seven living species of marine turtle forage and breed in Australian tropical waters. Marine turtles home to their natal area to breed and large rookeries used by tens to hundreds of thousands of turtles occur along the northern Australian coastline and the southern Great Barrier Reef area (Marsh et al. 2001). The flatback turtle Natator depressus nest only on Australian beaches so can be considered endemic to Australia. The dugong Dugong dugon forages on seagrasses in tropical Australasian waters. This species is highly threatened in much of its range and a large proportion of global dugong stock is believed to be in Moreton Bay in eastern Australia and Shark Bay in Western Australia (Marsh et al. 2001). Australian fur seals Arctocephalus pusillus doriferus, the world’s fourth rarest seal species, and the endemic Australian sea lion Neophoca cinerea, one of the most endangered pinnipeds in the world, breed at sites along the southern coast of Australia. These non-migratory pinniped species remain in southern Australian waters for their entire lives. Around 45 species of whales, dolphins and porpoises are found in Australian waters including large baleen whales such as the southern right whale Eubalaena australis and the humpback whale Megaptera novaeangliae, which migrate from their Southern Ocean feeding grounds to temperate waters around the southern parts of Africa, South America and Australia and to the tropical waters of the Pacific to breed. 412

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A diverse seabird fauna breeds on mainland and island coastlines around Australia; for example the Houtman Abrolhos Islands on the west coast are an important nesting area for Australian seabirds in terms of biomass and species diversity (Ross et al. 2001). One of the largest documented colonies of crested terns Sterna bergii globally (13,000–15,000 nesting pairs) occurs in the Gulf of Carpentaria in Australia’s tropical north (Walker 1992). Planktivorous seabirds occur in high numbers in Australia’s southern temperate waters. For example an estimated 23 million short-tailed shearwaters Puffinus tenuirostris nest in southeast Australia (Ross et al. 2001).

Climate change projections for Australia A number of climate models have been used to investigate the response of the ocean-atmosphere system to increased levels of greenhouse gases and aerosols (Cubasch et al. 2001). This review examines aspects of climate simulations that are relevant to determining how marine ecosystems will respond to global climate change. In general, climate model simulations using future greenhouse gas emission scenarios project oceanic warming, an increase in oceanic stratification and alteration of mixing depth, changes in circulation, increased pH and rise in sea level, alterations in cloud cover and ozone levels and thus solar radiation reaching the ocean surface and altered storm and rainfall regimes (Figure 4). It is very likely that such changes will cause considerable alterations in marine biological communities (Bopp et al. 2001, Boyd & Doney 2002, Sarmiento et al. 2004). We use future climate projections over the next century from the CSIRO Mk3.5 climate model (hereafter called the CSIRO climate model; Appendix 1) using the IS92a future emissions scenario, often referred to as the ‘business-as-usual’ scenario. Although there are subtle differences between the CSIRO climate model and other international models, many of the general trends in these fields are similar and we use the CSIRO climate model to suggest the magnitude of the projected changes in the set of variables that follow. HUMAN ACTIVITIES Increased greenhouse gas concentration

Change in UV radiation levels

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ff Rise in sea-level Altered nutrient supply and stratification (mixed layer depth)

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Figure 4 Important physical and chemical changes in the atmosphere and oceans as a result of climate change.

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Ocean temperature Waters around Australia are projected to warm by 1–2°C by the 2030s and 2–3°C by the 2070s (Figure 5). The CSIRO climate model projects the greatest warming off southeast Australia and this is the area of greatest warming this century in the entire Southern Hemisphere. This Tasman Sea warming is associated with systematic changes in the surface currents on the east coast of Australia; including a strengthening of the EAC and increased southward flow as far south as Tasmania (Figure 5). This feature is present in all IPCC climate model simulations, with only the magnitude of the change differing among models. Changes in currents leading to the Tasman Sea warming observed to date is driven by a southward migration of the high-latitude westerly wind belt south of Australia, and this is expected to continue in the future (Cai et al. 2005, Cai 2006).

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Winds Under global warming scenarios, the southeasterly trade winds strengthen east of northern Australia, but weaken to the west of the continent (Figure 5). Westerly winds in southern Australian waters will weaken. In the Australian coastal region, downwelling will prevail due to the dominating winds and density structure of the upper ocean. Increasing wind intensity may suppress localised upwelling in the northeast. However, decreasing wind intensity in southern waters may facilitate localised upwelling there.

Ocean currents Surface currents on the east coast will show a systematic change (Figure 5) including EAC strengthening and increased southward flow as far south as Tasmania. On the west coast there will be no obvious strengthening of the Leeuwin Current. In the south, the Great Australian Bight region will experience more westward transport as global temperatures rise. Along the northwest and northeast coasts there will be an increase in the northward flow.

Mixed-layer depth and stratification The Australian coastal region is generally a downwelling region due to prevailing winds and density structure of the ocean. In oligotrophic marine regions of Australia, the dominant mechanism of nutrient supply to the upper ocean is winter convective mixing due to cooling of surface waters. Under these conditions the seasonal evolution of the mixed-layer depth and density differences between this layer and the water below play an important role in the supply of nutrients to the upper ocean. Surface ocean warming will stabilise the upper ocean and reduce the supply of nutrients to the surface. The CSIRO climate model simulations project a decline in the annual mean mixedlayer depth by the 2070s (Figure 5).

CO2, pH and calcium carbonate saturation state Over the last 200 years, oceans have absorbed 40–50% of the anthropogenic CO2 released into the atmosphere (Raven et al. 2005). Rising atmospheric CO2 concentrations via fossil fuel emissions will lead to enhanced oceanic CO2 as the ocean re-equilibrates with the perturbed atmosphere (McNeil et al. 2003). Elevated CO2 in the upper ocean will alter the chemical speciation of the oceanic carbon system. As CO2 enters the ocean it undergoes the following equilibrium reactions: CO 2 + H 2O ⇔ H 2CO3 ⇔ HCO3− + H + ⇔ CO32− + 2H + Two important parameters of the oceanic carbon system are the pH and the calcium carbonate (CaCO3) saturation state of sea water (Ω). Ω expresses the stability of the two different forms of CaCO3 (calcite and aragonite) in sea water. Increasing CO2 concentration in the surface ocean via uptake of anthropogenic CO2 will have two effects. First, it decreases the surface ocean carbonate ion concentration (CO32−) and decreases Ω. Using an ocean-only model forced with atmospheric CO2 projections (IS92a), Kleypas et al. (1999) predicted a 40% reduction in aragonite saturation (Ωarag) by 2100. Laboratory experiments

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have shown that some species of corals and calcifying plankton (Gattuso et al. 1998, Langdon et al. 2000, Orr et al. 2005) are highly sensitive to changes in Ω, which has led to the hypothesis of large decreases in future calcification rates under elevated atmospheric CO2 (Kleypas et al. 1999). Second, when CO2 dissolves in water it forms a weak acid (H2CO3) that dissociates to bicarbonate, generating hydrogen ions (H+), which makes the ocean more acidic (pH decreases). Using an ocean-only model forced with atmospheric CO2 projections (IS92a), Caldeira & Wickett (2003) predicted a pH drop of 0.4 units by the year 2100 and a further decline of 0.7 by the year 2300. They argued that the oceanic absorption of anthropogenic CO2 over the next several centuries may result in a pH decrease greater than inferred from the geological record over the past 300 million years, with the possible exception of those resulting from rare, extreme events such as meteor impacts. Changes in surface pH and in Ωarag reflect changes in the speciation of carbon within the ocean and are a function of temperature, salinity, alkalinity and dissolved inorganic carbon concentrations. McNeil & Matear (2006) showed that climate change does not alter the projected change in surface pH. The projected pH decrease is controlled by the future levels of atmospheric CO2. However, the decline in Ωarag due to rising CO2 levels in the ocean is slightly reduced (~15%) because of the increase in Ωarag due to the increase in surface temperature. For the Australian region, the pH and Ωarag for the 1990s are shown along with the corresponding change in these values relative to 1990s (Figure 6). We see significant declines in these parameters but with the greatest declines occurring off northeast Australia. A major unknown in this region is whether any dissolution of the tropical coral reefs would buffer the pH decreases. Because of the enhanced levels of CO2 in the atmosphere and rates of fossil fuel burning, the process of ocean acidification is essentially irreversible over the next century. It will take thousands of years for ocean chemistry to return to a condition similar to that of preindustrial times.

Solar radiation Highly energetic ultraviolet radiation (UVR) penetrates the ocean surface and is known to have detrimental effects on marine organisms. UVR penetration to the earth’s surface increased during the last quarter of the twentieth century as stratospheric ozone was depleted by chlorofluorocarbons (CFCs), halons, hydrochlorofluorocarbons and other compounds. Stratospheric ozone levels appear to have stabilised, however, due to the 1989 implementation of the Montreal Protocol designed to phase out the production of CFCs and other compounds that deplete the ozone layer (de Jager et al. 2005). Most climate models predict that the ozone layer will recover and thicken throughout the twenty-first century (de Jager et al. 2005), so UVR penetration should decline (McKenzie et al. 2003). However, these predictions are somewhat uncertain, especially in the timing of the rethickening, due to uncertainties in projections of greenhouse gas emissions and degradation and due to the complex ways that chemical, radiative and dynamic processes will affect stratospheric ozone. For example, chemical reactions of some greenhouse gases (such as methane) can reduce total ozone in the stratosphere but the level of methane emissions is difficult to predict. Climate change will also affect UVR penetration indirectly by influencing other factors such as aerosols, clouds and snow cover. Aerosols can scatter more than 50% of the UV-B — the biologically important component of UVR — and aerosols increased in the atmosphere during most of the twentieth century, although they have shown declines since 1990 (Schiermeier 2005). Clouds can attenuate 15–30% of the UV-B, and cloud reflectance measured by satellite has shown a long-term increase in some regions of the world (McKenzie et al. 2003). All these factors introduce considerable uncertainty in future levels of UVR at the ocean surface, and it has been suggested that climate warming will slow the recovery of the ozone layer by up to 20 yr (Kelfkens et al. 2002). 416

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Precipitation and storms Changes in the amount or timing of rainfall and the associated river runoff affect the salinity regimes of estuaries and adjacent coastal waters, while in comparison salinity is relatively constant throughout the year in most oceanic waters. Despite the high uncertainty of rainfall projections in Australia, there is a tendency for decreased rainfall over most of Australia and over the oceans in climate model simulations (Figure 7). This general reduction in rainfall may be offset by an increase in the frequency of intense storms (Emanuel 2005, Webster et al. 2005), which will increase rainfall intensity and the associated runoff of freshwater and suspended sediments. In northern Australia, tropical cyclones are important extreme rainfall events. A recent study under 3 times the baseline levels of CO2 conditions based on levels prior to the industrial revolution in the mid-1800s, projected a 56% increase in the number of simulated tropical cyclones over northeastern Australia with peak winds greater than 30 ms−1 (Walsh et al. 2004). However, the behaviour of tropical cyclones under 417

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Figure 7 (See also Colour Figure 7 in the insert.) Simulated annual means of downward solar radiation at the ocean surface (W/m2) (left), precipitation minus evaporation (mm/d) (middle), and sea-level height anomaly due to upper ocean stratification relative to 2000 m (cm) (right). Top row: 1990s, bottom row: difference between 1990s and 2070s.

global warming is uncertain because they are not currently well resolved by global or regional climate models (Pittock et al. 1996, Walsh & Pittock 1998).

Sea level Rising sea level around Australia will flood existing coastal environments and alter their marine habitats. With global warming, the CSIRO climate model projects a doubling in the rate of sealevel rise from the observed 1.44 mm yr−1 for the twentieth century (Church et al. 2001). By the 2080s, sea level is projected to rise by 0.06–0.74 m above the 1990 value (Gregory et al. 2001). These projections take into account both the mean global projections from the IPCC scenarios and the non-uniform spatial distributions of sea-level change related to thermal expansion produced by the climate simulations. However, they do not include vertical land movement, which can be locally important. Sea-level rise projected by the CSIRO model for just the thermal expansion shows an increase in the entire Australian region but with large spatial variability (Figure 7). The variability in sea-level rise reflects how the excess heating of the planet due to global warming is stored in 418

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the oceans, and this large variability is supported by reconstructed sea-level estimates from the past decade (Willis et al. 2003). Therefore, over this century the local impact of sea-level rise may substantially deviate from the global averaged value. For the Australian region, much greater sealevel rise is projected on the east coast than the west coast due to the increased southward penetration of the warm EAC, which causes water here to expand more than in other regions.

Climate impacts on Australian marine life In this section we describe the impacts of climate variables on marine life in coastal, pelagic and offshore benthic systems. We consider the climate variables that have greatest impact on structuring marine communities within these systems and for which projections over the next 100 yr are available from global climate models. Where applicable, we review impacts on physiology, distributions and abundance, and phenology of marine organisms. Studies of climate impacts from both field and experimental research from Australia are discussed and supplemented with studies and observations from international research. Results of this section are summarised in Table 1.

Ocean temperature Elevated water temperatures stress plants and animals already near the upper limits of their optimal temperature range, slowing growth and impairing reproductive capacity (Philippart et al. 2003, Roessig et al. 2004, Helmuth et al. 2005, Keser et al. 2005). This is because most biological processes have an optimal temperature range and outside this range physiological efficiency declines. Coastal systems Physiology Extreme temperatures, both warm and cool, if severe or prolonged can lead to irreparable damage and death of coastal organisms as well as photosynthetic inhibition in marine plants (Bruhn & Gerard 1996, Ralph 1998, Davenport & Davenport 2005, Campbell et al. 2006). Large diebacks of marine fauna and flora in the intertidal and shallow subtidal occur on very hot days particularly when these coincide with low tides during the middle of the day (Tsuchiya 1983, Perez et al. 2000). Such a situation may have been responsible for the major dieback of seagrass beds in southern Australia during early 1993 when over 12,000 hectares were lost (Seddon et al. 2000). Probably the most widely publicised mass mortalities induced by warmer-than-average temperatures are those resulting from tropical coral reef bleaching events (Hoegh-Guldberg 1999). During bleaching events, the symbiosis between the coral and the unicellular algae (dineflagellates from the genus Symbiodium) that live within the coral tissues disintegrates. Bleached corals may recover their symbiotic populations of Symbiodium in the weeks and months after a bleaching event if the conditions triggering the event are mild and short-lived, but mortality has reached 100% in bleached corals when stressful conditions have persisted for days to weeks. Recent warming throughout tropical oceans has led to repeated coral bleaching events, not seen anywhere in the world before 1979, affecting hundreds to thousands of square kilometres of coral reefs in almost every region of the world where coral reefs occur. In the most severe global episode of mass coral bleaching (1998), 16% of corals that were surveyed before that event had died by the end of the year (Hoegh-Guldberg 1999, Knowlton 2001). Mass bleaching events over large sections of the Great Barrier Reef have occurred six times during the past 30 years: in 1983, 1987, 1991, 1998, 2002 and 2006. Mortality rates in this region were relatively low however, primarily because warming on the Great Barrier Reef was less severe than in other parts of Australia and the world. For example, in 1998 a very warm pool of water sat 419

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Table 1 Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Expected climate impact in Australia

Observations in Australia

Increasing temperature

Seagrasses and mangroves

Poleward shift in species ranges and a shift in abundance toward species tolerant of warmer waters Earlier flowering and fruiting

Seagrass

Increased frequency and intensity of large-scale diebacks with increase in frequency and intensity of extreme temperatures Poleward shift in species ranges and a shift in abundance toward species tolerant of warmer waters

Seagrass distributional limits linked to temperature1 Flowering of seagrasses in temperate Australia linked to water temperature2 Southern Australia early 1993 (>12,000 hectares)3

Rocky shore, fauna and macroalgae

Kelp communities

Phytoplankton

Zooplankton

Increased frequency and intensity of large-scale diebacks with increase in frequency and intensity of extreme temperatures Contraction of kelp ranges, declines in abundance, local extinctions, particularly in Tasmania Poleward shift in species ranges and a shift in abundance toward warm-water species

A decline where warming enhances stratification Earlier appearance of plankton in summer in temperate waters Increase in frequency and intensity of harmful and nuisance blooms Poleward shift in species ranges and a shift in abundance toward warm-water species A decline where warming enhances stratification

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Diebacks in Tasmania and South Australian hot days5

Observations elsewhere or experimental evidence

Rocky shores in Europe, United States and South America over past 50 yr4 European and Japanese coasts6

Decline of kelp in Tasmanian waters over past 50 yr7

Loss of kelp in east Pacific following El Niño8

Southward extension of a coccolithophore and a dinoflagellate in southeast Australia9

Poleward shift in North Atlantic10

North Atlantic11 North Sea12 Norwegian coast13

Large poleward range shifts (>1000 km) in North Atlantic14 North Atlantic15

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Coral reefs

Demersal and pelagic fish

Seabirds and wetland birds

Marine turtles and mammals

Expected climate impact in Australia Earlier appearance of zooplankton in summer in temperate waters Increase in frequency and severity of coral bleaching and mortality Increase in local extinctions of coral-associated fauna with bleaching events Poleward shift in species ranges and a shift in abundance toward species tolerant of warmer waters

Earlier dates of mean migration and spawning in temperate and subtropical species Poleward shifts in species ranges and a shift in abundance toward species tolerant of warmer waters Earlier arrival in migratory species in temperate and subtropical regions Earlier nesting and laying and protracted breeding seasons in temperate and subtropical species Poleward shift in species foraging ranges

Earlier breeding

Skewing of turtle sex ratios toward females

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Observations elsewhere or experimental evidence

Observations in Australia

North Sea16

Six severe bleaching events in past 30 yr (Great Barrier Reef, Ningaloo Reef)17

Coral reefs globally18

Coral reefs globally19 Tasmanian fish distributions shifting south with increase in fish that prefer warmer waters20

North Atlantic fish shifting northward21

Earlier migrations in northeast Atlantic fish22 Southward shift of seabird distributions in Western Australia and increase in abundance23 Southern Australian wetland birds24

Terrestrial, wetland and seabirds globally25

Western and southern Australian seabirds26 Northward shift of cetaceans and turtles in northeast Atlantic27 Earlier nesting in marine turtles in United States28 Experimental and modelling evidence that warmer temperatures produce more females29 (continued on next page)

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Expected climate impact in Australia

Observations in Australia

Alteration of winds

Phyto- and zooplankton

Increased productivity where wind mixing is enhanced and a reduction where wind strength declines

Coastal fish

Recruitment strength linked to wind strength Reduction of breeding success with prolonged periods of strong winds Local extinctions of cold-water species in southeastern Australia with increased flow of EAC, appearance of tropical species further south on east coast

Production pulses correlated with peaks in wind oscillation in Tasmanian shelf waters30 Rocky reef fish32

Seabirds

Alteration of currents including strengthening of EAC

Seagrasses & mangroves

Rocky shore, fauna and macroalgae

Kelp communities

Phyto- and zooplankton

Local extinctions of cold-water species in southeastern Australia with increased flow of EAC, appearance of tropical species further south on east coast Local extinctions of cold-water species in southeastern Australia with increased flow of EAC, appearance of tropical species further south on east coast Poleward extension of warm currents will transport tropical plankton more southward

Decline in mixed-layer depth/increasing stratification

Phyto- and zooplankton

Decrease in abundance

Increased CO2 and decrease in pH and aragonite saturation state

Mangroves

Increase in productivity with rising atmospheric CO2

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Observations elsewhere or experimental evidence Decreased production in central North Pacific during low-wind regimes31

Breeding colonies on Great Barrier Reef33 Seagrass distributional limits further south on west coast than east coast due to influence of warmwater Leeuwin Current34 Tropical species already found at temperate latitudes on east coast35

Expansion of longspined urchin to Tasmania facilitated by larval transport by EAC36 High abundance of a tropical coccolithophore off southeast Australia37 Phytoplankton productivity in central North Pacific declines as mixed-layer depth decreases38 Experimental evidence39

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Expected climate impact in Australia

Seagrasses

Increase in productivity with increase dissolved CO2 and deepening of depth limits Impaired growth in calcifying fauna and macroalgae and increase in mortality of early life stages Changes in growth and community composition; longterm decline in abundance and distribution of calcifying species Impaired growth in calcifying species, particularly pteropods; midterm decline in abundance and distribution Impaired growth rates and possible dissolution

Rocky shore, fauna and macroalgae Phytoplankton

Zooplankton

Coral reefs

Possible increase in UV

Cold-water corals Seagrasses

Mangroves

Rocky shore fauna and macroalgae Kelp and subtidal macroalgae Phytoplankton

Zooplankton

Coral reefs

High threat of impaired growth rates and possible dissolution Reduction of growth rates and biomass in UV-sensitive species Reduction of growth rates and biomass in UV-sensitive species Increase mortality of early life stages and reduction of growth rates in UV-sensitive species Increase mortality of early life stages Reduction of growth rates and biomass in UV-sensitive species and of nutritional value to zooplankton Changes in community composition Increased mortality of early life stages and reduction of growth rates in UV-sensitive species Increase in mortality during bleaching events through synergistic effects with temperature

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Observations in Australia

Observations elsewhere or experimental evidence Experimental evidence40 Experimental evidence41

Experimental evidence42

Experimental evidence43

Experimental and modelling evidence44 Evidence from modelling work45 Experimental evidence46 Experimental evidence47 Experimental evidence48 Experimental evidence49 Evidence from field and laboratory experiments50

Evidence from laboratory experiments51 Evidence from laboratory experiments52 (continued on next page)

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Demersal and pelagic fish

Increase in frequency or intensity of severe storms and extreme rainfall events and a decrease in average rainfall

Mangroves

Expected climate impact in Australia Increase mortality of early life stages and reduction of growth rates Damage to epidermis and ocular components in pelagic species and increased mortality in egg and larval stages in shallow water and upper ocean Shifts in community abundance as coastal salinity regimes are altered and nutrient and sediment loading changes

Seagrasses

Destruction of seagrass beds

Kelp communities and subtidal macroalgae

Shifts in community abundance and increased local mass mortality events associated with storms and flood events

Benthic macrofauna

Shifts in community abundance and increased local mass mortality events associated with storms and flood events

Alteration of peak timing of life cycle events

Coral reefs

Mass mortality events associated with storms and flood events

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Observations in Australia

Observations elsewhere or experimental evidence Evidence from laboratory experiments53 Evidence from laboratory experiments54

Increase in mangrove area in southeast Australia may be indirectly linked to changes in rainfall although changes in land use likely to be overriding factor55 Loss of >1000 km2 in Harvey Bay after severe storms and flooding56 Switch from canopyforming macroalgae to turf-forming algae in South Australia linked to enhanced nutrient supply from coastal runoff58 Mass mortality of grazing urchins after freshwater pulse60

High rainfall may decrease salinity in estuaries so triggering prawn emigration in northern Australia62 Mass mortality of corals on Great Barrier Reef after cyclones and flood events64

Large-scale destruction in United States after cyclones57 Range shifts of macroalgae in New Zealand and California associated with storms and wave exposure59 Field experiments revealed shift in community composition with increased sedimentation61 High rainfall may decrease salinity in estuaries so triggering prawn emigration in the United States63 Mass mortality of corals in Caribbean after cyclones65

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia

Expected change in climate

Species group/ natural system

Phytoplankton

Marine turtles and mammals

Rise in sea level

Mangroves

Seagrass

Seabirds

Marine turtles and mammals

Expected climate impact in Australia

Observations in Australia

Community structure influenced by rainfall regime and runoff

Lower coral diversity on Great Barrier Reef in wet tropics66

Diatoms may decline with decreasing average runoff and nutrient input while dinoflagellates (including harmful algae) may profit from stormassociated runoff and humic substances in coastal waters Increased mortality events

Alteration of hydrological or tidal regimes leads to mortality of mangroves Mangrove retreat with rising sea level Reduction in growth of seagrass and distributional shifts

Loss of breeding sites for species that nest on low-lying coastal areas through increased flooding and erosion Loss of breeding and haul-out sites for species through increased flooding and erosion

Observations elsewhere or experimental evidence

Evidence from field experiment and time series67

High mortalities of turtles and seal pups associated with cyclones and storms68 Mangroves in Africa and Asia69 Caribbean70 50 cm rise in sea level expected to result in 30–40% reduction of seagrass growth71 Evidence from modelling work72

50 cm rise in sea level expected to lead to a 32% loss of turtle nesting beaches in the Caribbean73

Notes: 1Walker & Prince 1987; 2West & Larkum 1979, Cambridge & Hocking 1997, Inglis & Smith 1998; 3Seddon et al. 2000; 4Barry et al. 1995, Southward et al. 1995, Sagarin et al. 1999, Zacherl et al. 2003, Mieszkowska et al. 2005, Rivadeneira & Fernandez 2005, Simkanin et al. 2005, Smith et al. 2006; 5Valentine & Johnson 2004, Womersley & Edwards 1958; 6Tsuchiya 1983, Perez et al. 2000; 7Edyvane 2003, Edgar et al. 2005; 8Dayton & Tegner 1984, Zimmerman & Robertson 1985, Dayton et al. 1998, 1999, Adey & Steneck 2001; 9Blackburn & Creswell 1993, Blackburn 2005, G. Hallegraef pers. com.; 10M. Edwards 2005; 11Richardson & Schoeman 2004; 12Edwards & Richardson 2004; 13Edwards et al. 2006; 14Beaugrand et al. 2002, Bonnet et al. 2005; 15Richardson & Schoeman 2004; 16Greve et al. 2004, Edwards & Richardson 2004, Kirby et al. 2007; 17Hoegh-Guldberg 1999, Wilkinson 2004; 18Hoegh-Guldberg 1999, Knowlton 2001; 19Dulvy et al. 2003; 20Welsford & Lyle 2003, P. Last pers. com.; 21Beare et al. 2004, Byrkjedal et al. 2004, Perry et al. 2005, (continued on next page)

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Table 1 (continued) Expected and observed impacts of climate change on Australian marine life and field or experimental evidence from outside Australia Notes (continued): Rose 2005a, 2005b; 22Sims et al. 2001; 23Dunlop & Wooller 1986, Dunlop et al. 2001, Bancroft et al. 2004; 24Beaumont et al. 2006; 25Mason 1995, Crick et al. 1997, Archaux 2003, Both et al. 2004, Lehikoinen et al. 2004, Both et al. 2005, Marra et al. 2005, Jonzén et al. 2006, Moller et al. 2006; 26Dunlop & Wooller 1986, Chambers 2004; 27Robinson et al. 2005, MacLeod et al. 2005, McMahon & Hays 2006; 28Weishampel et al. 2004; 29Yntema & Mrosovsky 1982, Godfrey et al. 1999, Booth & Astill 2001, Glen & Mrosovsky 2004; 30Harris et al. 1991; 31Polovina et al. 1994; 32Thresher et al. 1989; 33King et al. 1992; 34Walker & Prince 1987; 35Griffiths 2003; 36Johnson et al. 2005; 37Blackburn & Cresswell 1993, Blackburn 2005; 38Venrick et al. 1987, Polovina et al. 1994, 1995; 39Polovina et al. 1995, Roemmich & McGowan 1995, Farnsworth et al. 1996, Ainsworth & Long 2005; 40Invers et al. 1997, 2002, Zimmerman et al. 1997; 41Gao et al. 1993, Kurihara et al. 2004, Michaelidis et al. 2005, Berge et al. 2006; 42Riebesell et al. 2000, Antia et al. 2001, Tortell et al. 2002, Engel et al. 2005; 43Orr et al. 2005; 44See Hoegh-Guldberg 2004; 45Guinotte et al. 2006, Raven et al. 2005; 46Dawson & Dennison 1996; 47Moorthy & Kathiresan 1997, 1998; 48Graham 1996, Rijstenbil et al. 2000, Cordi et al. 2001, Lesser et al. 2003, Przeslawski et al. 2004, 2005, Bonaventura et al. 2006; 49Graham 1996, Bischof et al. 1998, Swanson & Druehl 2000, Wiencke et al. 2006; 50Behrenfeld et al. 1993, Keller et al. 1997, Wilhelm et al. 1997, Wängberg et al. 1999, Garde & Cailliau 2000, Barbieri et al. 2002, Litchman & Neale 2005; 51Karanas et al. 1979, Damkaer & Dey 1983; 52Lesser 1996, 1997, Baruch et al. 2005, Drohan et al. 2005; 53Shick et al. 1996, Wellington & Fitt 2003; 54Hunter et al. 1982, Keller et al. 1997, Zagarese & Williamson 2001, Markkula et al. 2005; 55Saintilan & Williams 1999, Harty 2004, Rogers et al. 2006; 56Preen et al. 1995; 57Thomas et al. 1961; 58Gorgula & Connell 2004; 59Graham 1997, Cole et al. 2001; 60Andrew 1991; 61Norkko et al. 2002, Thrush et al. 2003a, 2003b, Lohrer et al. 2004; 62Staples 1980, Vance et al. 1985, Staples & Vance 1986, Vance et al. 1998; 63Zein-Eldin & Renaud 1986; 64Alongi & Robertson 1995, Alongi & MacKinnon 2005; 65Porter & Meier 1992, Gardner et al. 2005; 66De Vantier et al. 2006; 67Carlsson et al. 1995, Goffart et al. 2002; 68Limpus & Reed 1985, Pemberton & Gale 2004; 69Blasco et al. 1996; 70Ellison 1993, Parkinson et al. 1994; 71Short & Neckles 1999; 72Galbraith et al. 2002, Smart & Gill 2003; 73Fish et al. 2005.

above Scott Reef off northwest Australia for several months, resulting in an almost total bleaching of these offshore reefs and mortality of corals down to 30 m depth. The recovery of Scott Reef has been very slow (Wilkinson 2004). By the middle of this century, temperature thresholds for coral bleaching will be exceeded every year in Australia if sea temperatures increase as projected by global climate models (HoeghGuldberg 1999). Based on the current responses of corals, it is estimated that an increase of 2°C in tropical and subtropical Australia would result in annual bleaching and quite possibly regular, large-scale mortalities (Hoegh-Guldberg 1999, 2004, Lough 2000). A geographic analysis of risk to the Great Barrier Reef associated with these changes in sea temperature indicated that the projected succession of devastating mass coral bleaching events will severely compromise the ability of reefs to recover, no matter where they are found along the Queensland coastline (Done et al. 2003). This analysis indicated that deterioration of coral populations is likely in most of the scenarios examined and this is reinforced by findings from other studies (Hoegh-Guldberg 1999, Donner et al. 2005). For large, mobile animals that may be transient visitors to coastal waters, oceanic warming may impact particular life stages such as juveniles or embryos. For example, gender in all turtles is determined by ambient nest temperatures during embryonic development (Mrosovsky et al. 1992, Godfrey et al. 1999, Hewavisenthi & Parmenter 2002a). Small changes in temperature close to the pivotal temperature at which a 50:50 sex ratio is produced (~29°C for marine turtles) skew the sex ratio of hatchlings, with warmer temperatures producing more females (Yntema & Mrosovsky 1982, Godfrey et al. 1999, Booth & Astill 2001, Glen & Mrosovsky 2004). Many nesting beaches around the world, including most Australian beaches, already have a strong female bias (Limpus

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1992, Loop et al. 1995, Godfrey et al. 1996, Binckley et al. 1998, Hewavisenthi & Parmenter 2002b, Hays et al. 2003, Glen & Mrosovsky 2004) so if temperatures rise, the proportion of eggs developing as males may be further reduced. However, light-coloured (thus cooler) beaches within nesting regions produce more males (Hays et al. 2003). In Queensland beaches on offshore coral cays and islands have lighter-coloured sand than mainland beaches, thus maintaining sex ratios (Environment Australia 1998). Therefore if temperatures warm on these beaches, the gross skewing in sex bias may have serious implications for local breeding population persistence. On a global scale outbreaks of disease have increased over the last three decades in many marine groups including corals, echinoderms, mammals, molluscs and turtles (Ward & Lafferty 2004). Causes for increases in diseases of many groups remain uncertain, although temperature is one factor that has been implicated in corals, molluscs and turtles (Harvell et al. 2002). Previously unseen diseases have also emerged in new areas through shifts in distribution of hosts or pathogens, many of these shifts are in response to climate change (Harvell et al. 1999). A consequence of climate-mediated physiological stress is that host resistance to pathogens or parasites can be compromised (Scheibling & Hennigar 1997, Garrabou et al. 2001, Lee et al. 2001, Harvell et al. 2002, Mouritsen et al. 2005). Temperature-induced disease outbreaks in corals on the Great Barrier Reef have occurred at the same time as bleaching events, resulting in increased coral mortality rates (Jones et al. 2004). A large-scale mortality of greenlip abalone, Haliotis laevigata, along the south Australian coast in 1985 and 1986 due to infection by Perkinsus parasites may have been aggravated by warmer water temperatures predisposing the abalone to this disease (Goggin & Lester 1995). Population declines due to temperature-related disease susceptibility have also been reported in several Californian abalone species through both observational and experimental studies (Davis et al. 1996, Vilchis et al. 2005). Fibropapillomatosis, a disease that causes tumours, is now common in green turtles Chelonia mydas and olive ridley turtles Lepidochelys olivacea (Adnyana et al. 1997, Jones 2004). This disease was first documented in the 1930s and was rare until the early 1980s but has since reached epidemic proportions in many turtle populations worldwide (Jones 2004). The prevalence of the tumours in young turtles suggests prolonged exposure to anthropogenic pollutants may be responsible (Adnyana et al. 1997, Herbst et al. 2004, Jones 2004, Ene et al. 2005, Foley et al. 2005). However, the increase of this disease in recent decades coincides with rapidly rising temperatures so it may also be indirectly related to climate change (Robinson et al. 2005). Distribution and abundance Temperature influences the abundance and distribution of coastal marine life such as macroalgae, seagrasses and molluscs (McMillan 1984, Walker & Prince 1987, Jernakoff et al. 1996, Steneck et al. 2002, Hiscock et al. 2004). Fluctuations in species abundances and community composition have been linked to variations in temperature (Southward et al. 1995, Tegner et al. 1996, Dayton et al. 1999, Grove et al. 2002, M.S. Edwards 2004, Schiel et al. 2004, Smith et al. 2006). Shifts in species distributions associated with ocean warming are documented from rocky shores in Europe, the United States and South America (Barry et al. 1995, Sagarin et al. 1999, Zacherl et al. 2003, Mieszkowska et al. 2005, Rivadeneira & Fernandez 2005, Simkanin et al. 2005). For example, a recent comprehensive resurvey of rocky intertidal shores around the United Kingdom found range extensions in the northern (high-latitude) limits of some warm-water species over the past 50 yr and a retraction in the southern limits of fewer cold-water species although rates of recession were not as fast as rates of advancement in warm-water species (Mieszkowska et al. 2005). The high levels of endemism along Australia’s southern coastline could increase vulnerability to temperature increases compared to temperate rocky shores elsewhere; many endemic species may have more stringent temperature limits and so may be particularly susceptible to warming (Beardall et al. 1998).

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There are interactive effects between the impacts of warming and availability of nutrients on distribution and abundance of macroalgae. Declines of giant kelp forest communities in Tasmanian coastal waters have been associated with thermal and nutrient stress (Edyvane 2003, Edgar et al. 2005). Macrocystis kelp forests in Australia are found predominantly in the southeast where water conditions are cool and relatively nutrient rich. There has been a considerable decline in Tasmanian kelp forests over the past 50 yr associated with rising temperatures (Edyvane 2003). Further, an unusual dieback of the shallow sublittoral brown macroalga Phyllospora comosa along the east coast of Tasmania in 2001 has also been attributed to above-average seawater temperatures coupled with nutrient stress (Valentine & Johnson 2004). If the EAC strengthens as projected by climate models, warm, nutrient-poor water will impinge more frequently on Tasmanian giant kelp communities, potentially leading to local extinction and a shift of macroalgal communities to understoreydominated forms (Kennelly 1987a,b, Dayton et al. 1999). Globally, mangrove distribution is generally constrained by the 20°C winter sea isotherm; there are a few exceptions, such as the more southerly distribution of mangroves in eastern Australia (Duke 1992). It has been suggested that this distribution is the result of small-scale extensions of warmer currents, such as the EAC, or that the southern populations are a relict representing refuges of more poleward distributions in the past (Duke 1992). As mangrove species show considerable variation in their sensitivity to temperature, species composition of mangrove forests will alter as temperatures rise and species distributions are expected to shift poleward (Field 1995). Evidence suggests that some benthic and demersal fish species may be able to move as oceans warm, regardless of whether there is a shift in associated habitats such as coral reefs, kelp forests or rocky reef communities. Certain fishes associated with coral reefs appear to be able to populate reefs that do not have corals, as shown by the appearance of coral reef fishes in southern New South Wales and Victoria during the summer (Hoegh-Guldberg 2004). These fishes recruit into coastal areas and grow for several months, disappearing when cold conditions return. Many coral reef fish may be able to move southward as oceans warm, although obligate corallivorous species would presumably be missing (Hoegh-Guldberg 2004). This has already been observed in other parts of the world such as California, where the composition of near-shore rocky reef fish communities shifted in dominance from cold-water northern species to warm-water southern species as temperatures warmed (Holbrook et al. 1997). However, coral bleaching has already led to local extinctions of a few coral-associated fish (Dulvy et al. 2003) and doubtless many more could disappear as coral bleaching episodes increase. Other mobile groups such as seabirds and marine mammals may be able to rapidly shift their distributions with climate change, although many are restricted to coastal habitats during breeding seasons. Warmer waters may allow marine turtles and dugongs to extend their foraging distributions in Australian inshore waters further south. However, green turtles Chelonia mydas and dugongs Dugong dugon selectively feed on seagrasses while hawksbill turtles Eretmochelys imbricata forage on coral reefs, so their ability to shift distributions are likely to be limited by changes in the distribution of their food sources. Range expansions have already been observed in seabird species along the west coast of Australia, with tropical species extending their breeding and foraging ranges southward (Dunlop & Wooller 1986, Dunlop et al. 2001). The recent growth of nesting colonies of wedge-tailed shearwaters Puffinus pacificus in southwestern Australia may be due to a southerly movement from more northerly colonies as temperatures rise (Bancroft et al. 2004). Wedge-tailed shearwaters are found only over waters with surface temperatures exceeding 20°C (Surman & Wooller 2000). The population of Australasian gannets Morus serrator that breed in southeast Australia has increased by approximately 6% per year since 1980, with new breeding sites being established as nesting space becomes limited (Bunce et al. 2002). This increase appears to be associated with a long-term

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warming trend and a concurrent increase in the abundance of small pelagic prey fish, principally pilchards Sardinops sagax. Phenology Water temperature and day length are the principal triggers or correlates for the timing of biological events such as breeding or migration in marine animals and flowering and seed germination in marine plants (Parmesan & Yohe 2003). Synchrony in reproduction of widely distributed seagrass beds and mangroves (Clarke & Myerscough 1991, Inglis & Smith 1998, DiazAlmela et al. 2006) suggests control by these environmental variables. Such synchronies of biological events in distant populations may be regulated by a large-scale independent factor such as temperature or day length. Regular flowering of the seagrass Posidonia australis occurs between April and June in southwestern Australia, probably induced by a seasonal decline in water temperatures (West & Larkum 1979, Cambridge & Hocking 1997). However, further north in Shark Bay P. australis meadows do not flower every year (Larkum 1976). Widespread flowering P. australis is also rare off central New South Wales on the east coast (Walker et al. 1988). Shark Bay and central New South Wales are near the northern limits for this temperate seagrass species so the threshold decline in water temperature required to trigger flowering may begin to occur less frequently. As a warming of coastal waters is projected, particularly off southeast Australia, episodes of flowering of P. australis may become even rarer in northern meadows. The deposition of seed banks after flowering is an important process that allows seagrass beds to recover rapidly from catastrophic disturbances such as storms or floods (Preen et al. 1995). Temperature has also been correlated with the timing of mass spawning in tropical reef corals on the Great Barrier Reef (Babcock et al. 1986) and on the tropical west coast (Simpson 1991). However, the physiological and evolutionary mechanisms that underlie the timing of reproduction in corals and in most marine invertebrates are far from clear; thus it is difficult to speculate on the consequences of any change in the timing of spawning. There is global evidence that climate change is influencing the phenology of larger marine fauna. Marine turtles in Florida in the United States are nesting earlier in response to warmer ocean temperatures (Weishampel et al. 2004). Warmer waters also reduce the interval length between the multiple clutches laid within a nesting season (Sato et al. 1998, Hays et al. 2002). Not all adult turtles will breed each year, but the relative numbers arriving annually at widely separated rookeries in Australia and the Indo-Pacific are similar, suggesting large-scale environmental forcing on reproductive success (Limpus & Nicholls 1988, Chaloupka 2001). Variation in winter sea-surface temperature anomalies partly explains internesting intervals of a Costa Rican population of green turtles Chelonia mydas, with 2-yr remigration probabilities increasing in warmer years (Solow et al. 2002). In Australia, interannual fluctuations in numbers of green turtles nesting at rookeries within the Great Barrier Reef are positively correlated with the Southern Oscillation Index, also with a 2-yr lag (Limpus & Nicholls 1988). Modelling studies suggest breeding intervals (time between nesting years) are determined by resource provisioning on adult feeding grounds and the 2-yr lag represents the time required for physiological provisioning for reproduction and migration (Hays 2000, Rivalan et al. 2005). Green turtles are herbivorous so are likely to be tightly coupled to productivity in coastal waters (Broderick et al. 2001). Mean egg-laying dates of many terrestrial bird species around the world have advanced considerably in response to increasing temperatures (Archaux 2003, Both et al. 2004, 2005, Moller et al. 2006). Migratory species are arriving earlier and leaving later (Mason 1995, Crick et al. 1997, Lehikoinen et al. 2004, Marra et al. 2005, Jonzén et al. 2006). Most evidence is from the Northern Hemisphere, but a similar pattern has recently been found in Australian migratory wetland birds such as the curlew sandpiper Calidris ferruginea and the double-banded plover Charadrius bicinctus (Beaumont et al. 2006). It is assumed that such changes are also occurring in Australian seabirds. Protracted breeding seasons observed in seabird species in Western Australia are likely to be a 429

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response to changing climate (Dunlop & Wooller 1986, Chambers et al. 2005). Breeding success of little penguins Eudyptula minor in Bass Strait is correlated with sea temperatures and mean laying dates are earlier in warmer years (Chambers 2004). Pelagic systems Physiology All plankton are poikilothermic and thus physiological rate processes and rates of overall growth are highly sensitive to temperature (Eppley 1972, Peters 1983, Huntley & Lopez 1992), with many plankton having a Q10 between 2 and 3 (i.e., a doubling to tripling in the speed of rate processes for a 10°C temperature rise). Species have a thermal optimum where growth is maximal and thermal limits beyond which net growth ceases or becomes negative. Basal metabolic losses increase with increasing temperature so that zooplankton fitness and, subsequently, abundance and distribution may be adversely affected. Little information is available on temperature ranges for Australian plankton, and in most cases experiments have been carried out with temperate plankton strains. Culture studies do give some indication (e.g., Smayda 1976) and suggest that species with tropical and subtropical distributions have growth optima <30°C. Optimal growth for the dominant picophytoplankton species Synechococcus and Prochlorococcus in the Great Barrier Reef is in the range 20–30°C (Furnas & Crosbie 1999), and in the Atlantic Ocean growth of Synechococcus peaks at 28°C and growth of Prochlorococcus at a cooler temperature of 24°C (Moore et al. 1995). As individual plankton strains have their own thermal optimum and limits for growth, warming will have differential effects on the growth of individual species and changes in phytoplankton and zooplankton community composition. Although direct effects of temperature changes are fundamentally important to plankton rate processes, indirect effects are also critical to plankton growth rates because zooplankton grow at temperature-dependent maximal rates only when they are food saturated (Kleppel et al. 1996, Hirst & Lampitt 1998, Richardson & Verheye 1998). Available evidence from tropical Australia indicates that copepod growth and egg production rates are regulated primarily by food availability rather than temperature (McKinnon & Thorrold 1993, McKinnon 1996, McKinnon & Ayukai 1996, McKinnon et al. 2005). For example, generation times of the common coastal tropical copepod Acrocalanus gibber decreased by 25% with a 5°C rise in temperature because of food limitation (McKinnon 1996). Therefore, zooplankton growth rates appear to be severely food limited in the warm, oligotrophic waters of tropical Australia (McKinnon & Duggan 2001, 2003). Climate impacts on nutrient enrichment processes are thus likely to be at least as important in Australia as local and direct temperature effects. Temperature also has an effect on the body size of individual species of zooplankton. Copepod body length typically decreases with increasing temperature (McKinnon 1996). Effects of temperature on upper trophic levels may be strongly mediated by zooplankton size, which is a key determinant of food quality for planktivorous fish. Warming of ocean waters will impact the physiology or morphology of demersal and pelagic fish populations directly and indirectly, but too little is known to speculate how these might be driven by climate change. Warming temperatures will affect all life stages of these fish but egg and larval stages may be the most sensitive. Distribution and abundance Plankton respond rapidly to ocean warming and have exhibited some of the largest range shifts of any marine group (Hays et al. 2005). Members of the warm temperate copepod communities in the northeast Atlantic have moved more than 1000 km poleward over the last 50 yr (Beaugrand et al. 2002, Bonnet et al. 2005), although this may be more associated with changing currents than warming. Concurrently, cooler water copepod assemblages have retracted further toward the North Pole. It is likely that similar expansions have also occurred in warm

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temperate and tropical dinoflagellates in the North Atlantic (M. Edwards 2004). Unfortunately, plankton observations are rare in Australian waters. The only examples of plankton range extensions are for the coccolithophorid Gephyrocapsa oceanica and the dinoflagellate Noctiluca scintillans. Since the early 1990s this species has begun to appear in high densities off southeastern Australia, with the likely cause being warmer sea temperatures (Blackburn & Cresswell 1993, Blackburn 2005, G. Hallegraef personal communication). Range expansions of other plankton species may have considerable social and economic consequences. The box jellyfish Chironex fleckerii is currently at the southern limit of its range on North Queensland beaches where it causes problems for bathers during summer; it may also expand its range further south as waters warm. It is well recognised that sea temperature is a principal determinant of fish species abundance and distribution (Lehodey et al. 1997, Roessig et al. 2004, Perry et al. 2005), biomass (Ware 1995, O’Brien et al. 2000, Drinkwater 2005), and other critical life-history and physiological processes (Burkett et al. 2001). Poleward shifts in distribution over the last century have been documented for fish in the North Atlantic and the North Sea (Beare et al. 2004, Byrkjedal et al. 2004, Perry et al. 2005, Rose 2005a,b), but observations from Australian waters are again few. Changes in the distribution of large pelagic fishes, such as tunas and billfish, have been observed in response to climate variability both seasonally (Zagaglia & Stech 2004) and interannually in terms of El Niño Southern Oscillation (ENSO) (Lehodey 2001) and Rossby waves (White et al. 2004). Seasonal distributions may be impacted if the timing of expansion or contraction of currents, such as the Leeuwin or EAC, alters. For example, southern bluefin tuna Thunnus maccoyii are restricted to the cooler waters south of the EAC and range further north when the current contracts up the New South Wales coast (Majkowski et al. 1981). This response to climate variation has allowed realtime spatial management to be used to restrict catches of southern bluefin tuna by non-quota holders in the east coast fishery by restricting access to ocean regions believed to contain southern bluefin tuna habitat (Hobday & Hartmann 2006). The seasonal presence of these fish along the east coast of Australia may be reduced further if Tasman Sea warming continues. Preliminary analyses indicate that changes may have already occurred, with fewer fish moving to the east coast in the Austral winter (Polacheck et al. 2006). Species from intermediate trophic levels (such as sardines and anchovies) are also crucial to maintenance of biodiversity in the pelagic realm. These are particularly sensitive to climate impacts based on studies elsewhere in the world (Chavez et al. 2003). A rare example from Australia is the replacement in eastern Tasmania of cold-water jack mackerel Trachurus declivis with warm-water redbait Emmelichthys nitidus from the EAC (Welsford & Lyle 2003), consistent with a warming trend on the east coast of Australia and Tasmania. Most species of marine turtles (except flatback turtles) move between coastal habitats and open oceans, being distributed in waters generally warmer than 15–20°C (Davenport 1997), although leatherbacks and loggerheads do penetrate into colder waters. Large leatherbacks are reported from waters as cool as 8°C but juvenile leatherbacks (<100 cm carapace length) are rarely found in waters <26°C (Eckert 2002). Reports from the Northern Hemisphere indicate that turtle populations may already be responding to warmer temperatures. Most sightings of marine turtles in U.K. waters over the past century are from the last 40 yr and sightings are increasing, suggesting a poleward shift or expansion in distributions but may also be a result of better reporting (Robinson et al. 2005, McMahon & Hays 2006). Global ranges of marine mammals are often related to water temperature (Learmonth et al. 2006). However, climate-induced changes in prey availability will strongly influence distributions of marine mammals. A recent increase of warm-water cetaceans recorded in the northeast Atlantic is likely to be the result of northward expansions linked to shifts of lower trophic levels in response to warming temperatures (MacLeod et al. 2005).

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Phenology There are insufficient data to assess changes in timing of plankton blooms in Australia, but overseas studies show that timing is sensitive to climate warming and this can have effects that resonate to higher trophic levels. In the plankton ecosystem of the North Sea, the timing of taxa associated with low turbulent conditions in summer advanced with warming of 0.9°C from 1958 to 2002, with meroplankton moving forward by 27 days, dinoflagellates by 23 days, diatoms by 22 days, copepods by 10 days and non-copepod holozooplankton by 10 days (Edwards & Richardson 2004). These changes in phenology were greater than those observed in terrestrial communities (Root et al. 2003). Some groups such as dinoflagellates may not only be responding physiologically to temperature, but may also react to temperature indirectly through earlier onset or intensity of stratification. Others such as meroplankton are temperature sensitive because they are dependent on temperature to stimulate physiological developments and larval release (Kirby et al. 2007). Important gelatinous meroplankton species that may display such tendencies include the medusa stages of box jellyfish and the small highly poisonous Irukandji jellyfish, which has stings that can be fatal to bathers. Only one species, Carukia barnesi, has been demonstrated to cause Irukandji syndrome but at least six other, mostly undescribed, species may also be responsible in Australian waters (Barnes 1964, Gershwin 2005, Little et al. 2006). Although many plankton species are responding to climate warming, the magnitude of the response differs throughout the community, having profound implications for the assembly, structure and functioning of the pelagic communities and the entire pelagic ecosystem (Edwards & Richardson 2004). The different extent to which functional groups are moving forward in time in response to warming (e.g., phytoplankton responding more than zooplankton) may lead to a mismatch between successive trophic levels and a change in the synchrony of timing between primary, secondary and tertiary production. Efficient transfer of marine primary and secondary production to higher trophic levels such as commercially important fish species is largely dependent on the temporal synchrony between successive trophic production peaks in temperate systems (Cushing 1990). Thus, marine trophodynamics may have already been radically altered by ocean warming and the extent to which this is happening in Australian temperate waters is unknown. Phenology of migrations and spawning of many other marine species is also expected to alter. For example, squid Loligo forbesi in the northeast Atlantic migrate to inshore spawning grounds earlier in warmer years (Sims et al. 2001) while flounder Platichthys flesus migrate later (Sims et al. 2004). Offshore benthic systems Physiology Cold-water corals have been recorded from all the oceans and differ from shallow, tropical, reef-forming species in that they lack symbiotic algae and are found at depths of several hundred metres below sea level. Cold-water corals are restricted largely to temperatures between 4°C and 12°C (Roberts et al. 2003, Roberts et al. 2006). As these corals have evolved to be adapted to this narrow yet stable temperature range, any rapid warming or cooling of temperatures is likely to impact negatively on coral physiology. For example, rising temperatures will influence their calcification rates, physiology and biochemistry. Distribution and abundance Much of the relationship between temperature and benthic and demersal fish populations is likely to be a consequence of temperature-related productivity in pelagic layers of the ocean, in addition to physiological dependencies. This relationship between temperature and fish production and distribution is apparent over the decadal timescale where oceanographic (temperature and productivity) regime shifts regulate zooplankton biomass, fisheries catches and seabird abundances (Beamish et al. 1997, Mantua et al. 1997, McGowan et al. 1998, Beamish et al. 1999, Koslow et al. 2002). Range shifts of benthic and demersal fish species have already been observed in response to warming of Australian waters. Most of these observations are from eastern or southeastern Australia, 432

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although some such changes have been observed in Western Australia and it is not known whether these differences are a reflection of differences in observation effort. Distributions of at least 36 species of Tasmanian marine fish have shifted poleward during the last decade (P. Last, personal communication, CSIRO). Many of these are warm temperate reef species historically distributed adjacent to the coast of New South Wales that have now become established south of Bass Strait. Still others have shifted their ranges further south along the Tasmanian coast. Phenology The benthic larval component of the zooplankton has shown large shifts in timing compared with the holozooplankton in Northern Hemisphere temperate waters (Edwards & Richardson 2004, Greve et al. 2004). Evidence from the North Sea has shown that larvae of benthic echinoderms are now appearing in the plankton about 6 wk earlier than 50 yr ago in response to warmer temperatures. If Australian benthic systems responded similarly, peak larval abundances of crown-of-thorns starfish could appear much earlier in the year, perhaps before the presence of their normal predators (a potential positive feedback) or before wet season pulses in nutrients originating from early wet season rains (a negative feedback).

Winds Marine systems are influenced by wind fields, which drive major surface currents, and by episodic wind events ranging in strength from low to extreme. In shallow waters, these wind events create hydrodynamic disturbance whereas in deeper waters, wind fields and events contribute to hydrodynamic regimes that affect upwelling and hence productivity at different spatial and temporal scales and across different trophic levels (Harris et al. 1991). Coastal systems Physiology Hydrodynamic stress will affect growth forms and morphological adaptations of plants and animals (Denny & Gaylord 1996). For example, variation in the morphology of the kelp Ecklonia radiata along the southern Australian coastline is related to wave exposure, longitude, plant density and temperature at each site (Fowler-Walker et al. 2005, 2006). At sites with high wave exposure, plants have longer stipes and smaller surface areas so are better adapted to cope with high-energy water movement. Phenotypic responses to hydrodynamic stress are frequently a trade-off between reducing mechanical damage and risk of dislodgement and obtaining nutrients/ food (Sebens 2002, Marchinko & Palmer 2003, Stewart & Carpenter 2003, Li & Denny 2004). Populations cannot respond indefinitely to hydrodynamic stress so there are limits to the degree of plasticity in morphological characteristics in response to the environment. Barnacles on Northern Hemisphere exposed shores tend to have shorter cirri than those on sheltered shores (Arsenault et al. 2001, Marchinko & Palmer 2003, Li & Denny 2004, Chan & Hung 2005) but above a threshold current velocity barnacles cease to respond plastically to flow (Li & Denny 2004). Intertidal snails tend to have thicker and/or larger shells on shores with high wave exposure (Frid & Fordham 1994, Boulding et al. 1999). However, intertidal snails along the coast of southern Australia show no differences in morphology with wave exposure, and it is hypothesised that the generally homogeneous and wave-exposed nature of Australia’s southern coastline may have favoured generalist traits (Prowse & Pile 2005). Fauna and flora of Australia’s exposed southern coastline may be adapted to cope with high variability in wave exposure. Distribution and abundance Intertidal and shallow-water animal and plant communities are structured by wave exposure and local current velocity so species tolerant of high-energy hydrodynamic forces dominate at high wave-exposed sites (Edgar et al. 1997, Coates 1998, Fonseca & Bell 1998, Goldberg & Kendrick 2004, Fulton et al. 2005, Jonsson et al. 2006). An increase in wind strength 433

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may increase wave exposure and may result in a considerable reduction in algal and seagrass production or a shift in community composition in areas that are affected (Kendall et al. 2004, Cruz-Palacios & van Tussenbroek 2005). A general weakening of those winds is expected to hinder recruitment for coastal marine populations. Strong relationships between wind strength and recruitment have been shown, including in a coastal rocky reef fish (Heteroclinus sp.) for which enhanced settlement followed winddriven productivity boosts (Thresher et al. 1989). Prolonged periods of strong winds have impacted the breeding success of the sooty tern Sterna fuscata and common noddy Anous stolidus in the Great Barrier Reef region with large-scale desertion of nests and starvation of chicks (King et al. 1992). Environmental conditions associated with strong winds may have led to a reduction in prey availability or a reduction in the foraging success of adults. Nests were also lost through inundation by waves and shoreline erosion (King et al. 1992). Phenology Winds and waves have the potential to affect timing of the reproduction of algae. For example species of Fucus in the North Atlantic release spores only under calm conditions at low tide at certain times of the year (Brawley 1992, Serrão et al. 1996, Brawley et al. 1999). It is not clear whether this is an absolute condition for reproduction, or whether it is simply periods of relative calm that are required. It is also unknown whether any Australian species of marine plants have similar requirements for reproduction. It has also been suggested that the timing of mass spawning in tropical reef corals is related to seasonal wind and current fields, coinciding with times of the year when calm conditions are likely to occur (Babcock et al. 1994). It is thought that the fertilisation success of coral populations may be the ultimate factor responsible for this pattern (Oliver & Babcock 1992), so any change in the seasonal wind pattern may affect reproduction and recruitment. If climate change decouples factors such as seasonal wind patterns and seasonal temperature cues that may be important for mass spawning corals then the reproductive success of these species may be reduced. Pelagic systems Distribution and abundance Wind is one of the driving forces of currents and vertical mixing in the water column. Wind therefore affects mixing depth and intensity and may thus be seen as a proxy for mixing depth, mixing intensity, and light and nutrient supply to the surface layer. Climate models consistently project a poleward shift in the zonal winds that normally cross the southern part of Australia, and these projections are consistent with recent changes in the Antarctic Oscillation Index (Gillett & Thompson 2003; also see Jones & Widmann 2004). The projected general weakening of those winds following this shift may reduce recruitment to marine fish populations. Strong relationships between wind strength and recruitment exist for some species, such as the commercially exploited blue grenadier Macruronus novaezelandiae in outer continental shelf waters (Thresher et al. 1992). In southeastern Australia, Harris et al. (1992) found evidence that reduced production of the jack mackerel Trachurus declivis off Tasmania resulted from decreased wind stress and subsequent decreases in large zooplankton. Offshore benthic systems Distribution and abundance The variability in the annual frequency of strong zonal westerly winds has been related to catch rates and recruitment variability in several southeastern demersal fisheries (Harris et al. 1988). The collapse of the gemfish fishery Rexea solandri in that region was likely a consequence of the combination of weak recruitment due to declining winds and overfishing (Thresher et al. 1996). A variety of southeastern shelf teleosts exhibit a decadal-scale recruitment cycle, in several cases directly linked to regional wind fields (Thresher 2002, Jenkins 2005). 434

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Ocean currents Currents and ocean circulation systems strongly affect dispersal, migration and geographic distribution of species and therefore have implications for the connectivity of marine systems. Southwardmoving currents such as the EAC and Leeuwin Current interact with southern coastal and offshore waters, influencing temperature and regional productivity (Harris et al. 1987, Ridgeway & Dunn 2003, Ridgway & Condie 2004). Coastal systems Distribution and abundance Many marine plants and animals rely on water movement for dispersal, particularly for early life stages. Distributional patterns of marine populations often reflect connectivity of marine systems. Evidence is mounting that despite the potential for long-distance dispersal, actual dispersal distances for coastal fauna may be constrained by behavioural mechanisms such as vertical migration. Typical larval dispersal distances for coral reef fish in the Caribbean are on a scale of 10–100 km, with dispersal distances strongly determined by active movement of larvae (Cowen et al. 2006). Some coastal invertebrates have very short larval durations which will restrict dispersal distance (McShane et al. 1988, Sammarco & Andrews 1988, Davis & Butler 1989, Stoner 1992). Further, the viability of larvae and plant propagules may diminish over time. For example, propagules of the mangrove Avicennia marina may only be able to establish successfully within the first 4–5 days of dropping (de Lange & de Lange 1994). The southern limit of this species in New Zealand appears to be controlled by limited transport by coastal drift and lack of suitable habitat within the dispersal range of existing populations, rather than by climatic factors (de Lange & de Lange 1994). The most southerly mangroves globally are found at Corner Inlet in Victoria (de Lange & de Lange 1994). These may be relict populations from when favourable climate extended further south than at present. Projected global warming and strengthening of the EAC may facilitate further southerly expansion of mangrove species. Alternatively, this southerly limit may be set (and restricted) by eastward water movement through the Bass Strait (de Lange & de Lange 1994). Southward water movement through the Bass Strait by wind-induced drift is slow and is insufficient to transport the propagules to Tasmania within the 5-day period for viable establishment (de Lange & de Lange 1994, Clarke et al. 2001). Therefore, even if temperatures in Tasmania become warm enough to support Avicennia populations (conventional wisdom is that latitudinal range edges of mangroves are determined mainly by freezing temperatures) they are unlikely to become established there. Currents thus act as a barrier as well as an aid to dispersal for many marine organisms and therefore determine adult abundances as well as distributional limits (Gaylord & Gaines 2000). Incidentally, this means that a key consequence of future climate change will be influences on current patterns, often on a small scale and therefore dependent on fine-scale variations in weather and current patterns, which are still difficult to predict. In addition to affecting the range of species distributions, a change in the strength of currents may alter the overall strength of recruitment. One of the best examples of this comes from the correlation between the strength of the Leeuwin Current and recruitment of the western rock lobster Panulirus cygnus. The strength of the Leeuwin Current is highly correlated with ENSO and in El Niño years when the current is weak, rock lobster recruitment is also weak (Caputi et al. 2001). The mechanism underlying this is not well understood, but it is clearly more complex than simply a range extension and may be related to temperature or cross-shelf transport, mixing and productivity driven by the Leeuwin (Griffin et al. 2001). The establishment of long-spined sea urchins Centrostephanus rodgersii in Tasmania in the 1960s has been attributed to larval transport from northern populations by the EAC (Johnson et al. 2005). Populations have since expanded in Tasmania and have resulted in the elimination of 435

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macroalgae in some areas through intense grazing pressure. A reduction in the density of rock lobster Janus edwardsii and abalone Haliotis rubra in areas devoid of macroalgae has serious implications for fisheries targeting these species. It must be assumed that any major shift or strengthening of wind fields and major currents may have profound implications for Australian coastal organisms. Pelagic systems Distribution and abundance Transport by large ocean currents plays a major role in the movements of marine turtle hatchlings and early juveniles to ocean pelagic nursery habitats where young turtles remain for a number of years exploiting biologically rich environments linked to current systems and convergence zones (Carr 1987, Witherington 2002, Ferraroli et al. 2004). Juvenile and adult turtles undertake extensive migrations; juvenile loggerheads originating from Australian populations have been identified from feeding grounds off Baja California, representing a journey that crosses the entire Pacific Ocean aided by the North Pacific Current (Bowen et al. 1995). Adult loggerheads and leatherbacks forage at fronts and eddies and are associated with major currents (Ferraroli et al. 2004, Polovina et al. 2004). Turtles have also been tracked swimming against prevailing currents as well as with currents so may only use current flows opportunistically to facilitate transport (Luschi et al. 2003, Polovina et al. 2004). Alteration of major current systems will impact the navigational abilities of marine turtles and deflect turtle movements (Luschi et al. 2003, Robinson et al. 2005). Offshore benthic systems Distribution and abundance Cold-water corals are found in areas of fast currents and this is evident on Australian seamounts where corals occur in distinct depth zones (Koslow et al. 2001). Alteration of currents may make areas unfavourable for coral growth and, given the low growth rate, colonisation of newly available areas with optimal environmental conditions may be slow and may take many decades before a viable population size is reached. Fast flow may also be necessary for larval supply or retention to establish or maintain populations (Genin et al. 1986). Changes in local current regimes could alter the ‘stepping stone’ function of seamount chains, whereby the biology on distant seamounts is linked by intermediate ones, and have a considerable impact on coral distribution (Roberts et al. 2003). Survival of cold-water corals appears to be controlled by oceanographic conditions. Chemical analysis of deep-water corals off southern Australia has indicated a long-term deep cooling that commenced in the mid-eighteenth century and is a result of enhanced poleward flow of the warm EAC as it interacts with the colder subsurface countercurrents (Thresher et al. 2004). This strengthening of the EAC is predicted to continue as the global climate warms (Cai et al. 2005, Cai 2006) with considerable impacts for ocean circulation and marine biodiversity, including cold-water coral ecosystems.

Mixed-layer depth and stratification Mixing depth and mixing intensity in the surface ocean and the associated stratification are key factors for the production of phytoplankton and of higher trophic levels because they fundamentally affect the supply of nutrients (from below) and light (from above), and sinking losses of phytoplankton (Mitchell & Holm-Hansen 1991, Huisman & Weissing 1995, Diehl 2002) and because consumer biomass is positively related to the productivity of their food (Grover 1997).

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Pelagic systems Distribution and abundance Experimental manipulation of mixing depth has demonstrated the positive impact of decreasing mixing depth (increasing light supply) on the biomass of temperate phyto- and mesozooplankton when nutrients are relatively abundant (Kunz 2005). Flagellates profited from shallower mixing and the heterotroph-to-autotroph (mesozooplankton-to-phytoplankton) biomass ratio was higher at low mixing depth. Variability of mixing depth and change in stratification in several ocean regions since the 1950s provide striking examples of potential impacts on pelagic communities. In the central and subarctic North Pacific Ocean, large variability in plankton primary and secondary production has been linked to a decadal-scale climate change event between the mid-1970s and the late 1980s and associated changes in the depth of the winter and spring mixed layers (Venrick et al. 1987, Polovina et al. 1995, Hayward 1997). These impacts on lower trophic levels appear to have propagated to higher trophic levels with pelagic larvae, including squid, salmon and flying fishes with different mechanisms operating in different regions (Polovina et al. 1994, 1995). In the northwest Hawaiian Islands (situated in the North Pacific subtropical gyre), chlorophyll concentration and primary production were positively related to deepening of the mixed layer due to increased nutrient supply (Venrick et al. 1987, Polovina et al. 1995) while in the subarctic Gulf of Alaska copepod abundance and, likely, primary production were positively related to shallowing of the mixed layer due to increased light availability (Polovina et al. 1995). In the Northern California current, a decrease in macrozooplankton biomass by 80% since 1951 has been related to reduced nutrient transport across the thermocline due to warmer sea-surface temperatures and increased stratification (Roemmich & McGowan 1995). In the North Atlantic, large-scale northward shifts in the distribution of warm-water phyto- and zooplankton and changes in the abundance of plankton between 1958 and 2002 have been related to increasing water column stratification (Richardson & Schoeman 2004, Hays et al. 2005, Edwards et al. 2006). With the projected enhancement of stratification around most of continental Australia nutrient transport to the surface layer will be reduced over vast areas of the pelagic zone. Most Australian waters are therefore likely to become more depauperate in nutrients with repercussions for production and biomass of most pelagic (and benthic) food webs. Cyanobacteria, flagellates and dinoflagellates (including nuisance and harmful algal bloom species) may increase in abundance where vertical mixing decreases and the ‘microbial loop’ may be favoured over the relatively more productive ‘classic’ food web in affected areas. The productive temperate pelagic province may shrink considerably in area and potentially become restricted to west of Tasmania by 2100. In tropical surface waters where increasing stratification lifts the oxycline, the abundance of pelagic apex predators, such as skipjack and yellowfin tuna may decline. Phenology In the North Atlantic, earlier timing of dinoflagellate blooms in spring is partly attributed to earlier and enhanced stratification (Edwards & Richardson 2004, Richardson & Schoeman 2004). In Tasmanian waters, zonal westerly winds stimulate deeper and/or stronger vertical mixing and affect the timing and duration of phytoplankton blooms (Harris et al. 1988). Offshore benthic systems Distribution and abundance Deep seafloor habitats, with the exception of hydrothermal vents and cold seeps, are typically areas of low productivity, relying on the flux of detritus from surface waters which is partially regulated by mixed layer depth. Despite this, species diversity can locally be very high (Snelgrove & Smith 2002). Seamounts, with topographically enhanced currents are areas of high productivity (e.g., Koslow 1997) but are still sensitive to the flux of organic matter from surface waters, albeit over a wider area than that of the seamount itself. This coupling to

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surface productivity may mean the deep sea is particularly susceptible to climate change (Glover & Smith 2003). If surface productivity is reduced as climate warms then the reduction in organic carbon flux to the sea floor will lead to a reduction in benthic biomass.

CO2, pH and calcium carbonate saturation state Changes to the atmospheric concentration of CO2 and hence carbonate ions represents a serious threat to calcifying organisms such as corals, pteropods and coccolithophores (Raven et al. 2005), especially as calcification of most organisms appears linearly related to the carbonate ion concentration (Langdon et al. 2000). The level of calcification is significant in that it represents concentrations at which organisms such as tropical reef-building corals no longer calcify. Marine organisms differ in their susceptibility to acidification depending on whether the crystalline form of their calcium carbonate is calcite (calcifying phytoplankton, foraminiferans) or aragonite (pteropods, corals). Calcite is less soluble than aragonite, making it less susceptible to pH changes. Other effects of increased CO2 on the physiology of marine flora and fauna are less well understood. Experiments to determine the likely response of marine organisms to pH changes have explored large changes in pH (>1.0) under laboratory conditions (Kikkawa et al. 2003, Pedersen & Hansen 2003a,b, Pörtner et al. 2004, Engel et al. 2005) but little is known on what the gradual long-term effects of pH lowering will be on marine organisms. Coastal systems Physiology Marine plants vary in their degree of immersion in water, from mangroves that generally have their foliage and flowers above the water to macroalgae and seagrasses that are either fully submerged or submerged for part of the tidal cycle. Land plants, including mangroves, capture CO2 primarily by diffusion so that increasing atmospheric CO2 generally hastens photosynthesis, productivity and growth (Ainsworth & Long 2005). Seagrasses, although submerged, are of terrestrial origin and so rely primarily on dissolved CO2; thus they are photosynthetically inefficient in sea water (Invers et al. 1997, 2002, Short & Neckles 1999). By contrast, most marine phytoplankton and macroalgae have mechanisms that actively concentrate and take up inorganic carbon as CO2, bicarbonate ions (HCO3−) or both, so changes in dissolved CO2 have less effect on their rates of photosynthesis (Giordano et al. 2005). Carbon-concentrating mechanisms are not as common in benthic photosynthetic organisms (Giordano et al. 2005). Mangrove growth may be stimulated as CO2 levels increase. Seedlings of Rhizophora mangle grown under double ambient CO2 for a year exhibited increases in growth and photosynthetic rate (Farnsworth et al. 1996). The young plants also became reproductive a year earlier than in the field, so elevated CO2 may accelerate maturation as well as growth (Farnsworth et al. 1996). However, the long-term response of mature mangrove forests to elevated CO2 is unknown. A widespread thickening of terrestrial vegetation observed in parts of Australia may be induced by recent climate change although is more likely the result of changes in land use (Bowman et al. 2001, Australian Greenhouse Office 2003). Australian coastal waters are generally low in phosphate and nitrate but as seagrasses are rooted, they can take up these essential nutrients from the sediment. Therefore, seagrasses are primarily carbon limited. An increase in atmospheric CO2 will result in a higher proportion of dissolved CO2 in the oceans, potentially increasing seagrass biomass, deepening of seagrass depth limits and enhancing of the role of seagrass beds in carbon and nutrient cycles (Zimmerman et al. 1997, Invers et al. 2002). Intertidal macroalgae, which generally use bicarbonate when submerged, may only benefit from elevated CO2 during aerial exposure (Farnsworth et al. 1996, Beardall et al. 1998, Gao et al. 1999, Zou & Gao 2002, 2005). 438

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Coral reefs represent a balance between calcification and erosion, with 90% of what is laid down by calcifiers being removed by erosion. Ocean acidification could tip the balance from net calcification to erosion. If atmospheric CO2 levels reach 500 ppm, projected to occur by the end of this century, then coral viability will be severely compromised (Hoegh-Guldberg 2004). At low carbonate ion concentrations (<200 µmol kg−1), calcification of corals and many other calcifying organisms effectively becomes zero. The actual seriousness and time frame of these changes have yet to be properly assessed. There has been some debate about the significance of the threat of ocean acidification to the long-term viability of coral reefs (see McNeil et al. 2004 vs. Kleypas et al. 2005). Changes in calcification rates over recent centuries estimated from cores from long-lived corals such as Porites on the Great Barrier Reef show evidence of an increase in calcification rates over the 50 yr prior to 1982 (Lough & Barnes 2000). Calcification rates were highly correlated with average sea temperature, with an annual average increase in calcification of 0.3 g cm−2 yr−1 for each degree of ocean warming. Lough and Barnes (2000) suggested the increase in calcification was probably due to the 0.25°C warming of sea temperature on the Great Barrier Reef over the last 50 yr. Although calcification does increase with temperature, it does not increase indefinitely; several studies have shown that it increases up to the summer sea-temperature maximum, but declines rapidly at warmer temperatures. Interactions between temperature and decreasing pH are still largely unknown but are likely to be considerable given, for example, the linkages between metabolic rate (which is temperature sensitive) and calcification. Most authors have concluded that the combination of the two pressures on calcifying organisms such as corals will be largely negative and synergistic (Hoegh-Guldberg 2004). Acidification may be expected to increase physiological stress on other calcifiers. Metabolic efficiency and growth rates of bivalves and other molluscs will be impaired (Michaelidis et al. 2005, Berge et al. 2006). Experiments have also shown that under lowered pH conditions the fertilisation rate of eggs of intertidal echinoderms declined and larvae were severely malformed (Kurihara et al. 2004). Distribution and abundance Macroalgae take up primarily bicarbonate ions for photosynthesis. As only a small proportional change in bicarbonate concentration will occur as atmospheric CO2 levels rise, little enhancement of growth is expected (Beardall et al. 1998). However, increased acidification of the oceans may have severe consequences for coralline algae (Gao et al. 1993) therefore enhancing competitive advantages of non-calcifying species over calcifying species (Gao et al. 1993, Beardall et al. 1998). Potential range shifts in tropical corals with warming may be restricted by the future latitudinal gradient in the carbonate saturation state of sea water (Figure 6). The undersaturation of aragonite and calcite in sea water is likely to be more acute and happen earlier further south in the Southern Hemisphere and then move northward (Orr et al. 2005). This means that corals will not be able to move further south into cooler waters in response to warming seas because these waters are likely to be undersaturated in calcium carbonate. The additional problem of reduced light levels at higher latitudes is also probably an important limit in this respect. Pelagic systems Physiology Seawater pH affects phytoplankton via several processes. pH is an important determinant of the growth rate of phytoplankton species, with some growing consistently well over a wide range of pH and the growth rate of others varying considerably over a pH range of 7.5–8.5 (Hinga 2002). Both temperate and tropical coccolithophorids show reduced calcite production and an increased proportion of malformed liths at decreased pH (Riebesell et al. 2000, Engel et al. 2005).

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Declining pH may also alter the growth rates of photosynthetic organisms; in particular changes in pH will affect the kinetics of the uptake of nutrients. Nitrification in marine bacteria is negatively affected below a pH of ~8. Because nitrification is an important pathway of nitrate supply to phytoplankton, nitrate availability for phytoplankton is likely to be reduced at pH <8.0, with consequences for phytoplankton community composition and productivity (Huesemann et al. 2002). Decreasing pH has also been found to increase the availability of potentially toxic trace elements such as copper, which may affect phytoplankton survival (Kester 1986). Changes may also occur in cell composition, which could affect the nutritional value of the microorganisms to the animals that feed on them. As phytoplankton have carbon-concentrating mechanisms, photosynthesis is generally not carbon limited, even at present CO2 levels. In almost all phytoplankton species, doubling CO2 concentration only increases photosynthesis by <10% (Beardall & Raven 2004, Schippers et al. 2004, Giordano et al. 2005). The small number of studies that have investigated effects of CO2 on phytoplankton community composition suggested that elevated CO2 concentrations favour diatoms over flagellates and coccolithophores (Antia et al. 2001, Tortell et al. 2002). The physiology of larger animals such as fish and squid are likely to be influenced by increasing CO2 levels in the oceans, which influences tissue acid-base regulation and thus metabolism. Squid are acutely sensitive to even small changes in ambient CO2 due to their high metabolic oxygen demand for locomotion (jet propulsion) and a strong relationship between O2 binding in the blood and pH (see Pörtner et al. 2004 ). Pelagic fish generally have lower metabolic rates and some venous oxygen reserve so are only moderately sensitive to changes in ambient CO2. The projected increases in CO2 are below lethal threshold levels; synergistic effects of warmer temperatures and increased CO2 may influence growth and reproduction in large pelagic fauna. Distribution and abundance The direct effect of ocean acidification on calcifying zooplankton will be to increase shell maintenance costs and reduce growth. Pteropods with their aragonite shells are particularly vulnerable to ocean acidification (Orr et al. 2005). In the Southern Ocean, shelled pteropods are prominent components of the food web contributing to the diet of carnivorous zooplankton, myctophid and other fishes, and baleen whales, as well as forming the entire diet of gymnosome molluscs. Pteropods can also account for the majority of the annual export flux of both carbonate and organic carbon in the Southern Ocean. Shells from live pteropods dissolve rapidly when placed in water undersaturated with aragonite, similar to the levels that are likely to exist in 2100. If pteropods cannot grow their protective shell, then their populations are likely to decline and their range will contract toward lower-latitude surface waters that remain supersaturated in aragonite. In Australian waters, pteropods are relatively rare but can be locally common. For example, the pteropod Cavolinia longirostris can form dense aggregations on the Great Barrier Reef during summer (Russell & Colman 1935), occurring in such large numbers that their shells wash up on beaches (D. McKinnon, personal communication). Offshore benthic systems Distribution and abundance Decreases in ocean pH will directly impact offshore soft sediment organisms that rely on calcium carbonate structures such as molluscs and foraminiferans. Changes in pH will also impact benthic organisms by influencing the composition of sediment as a large fraction in Australia is calcium carbonate in origin. For example, foraminiferan remains constitute most of the sediments in sandy regions of the Great Barrier Reef and a decline in the abundances of pelagic and benthic foraminiferans is likely to reduce the sedimentation of their skeletons to the sea bottom (McKinnon et al. in press). The global distribution of cold-water corals is influenced by seawater carbonate chemistry with a clear relationship between the occurrence of cold-water scleractinian corals and depth of the 440

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aragonite saturation horizon (Guinotte et al. 2006). The aragonite saturation horizon represents the limit between the upper saturated and the deeper undersaturated waters; calcium carbonate can form above the horizon but dissolves below it (Raven et al. 2005). As atmospheric CO2 levels increase, the depth of the aragonite saturation horizon will rise closer to the ocean surface and the entire Southern Ocean water column could become undersaturated by 2100 (Caldeira & Wickett 2005, Orr et al. 2005). Cold-water corals are thus likely to be much more vulnerable to changes in ocean chemistry than shallow tropical reef-building corals (Raven et al. 2005). Over the next 100 years, the predicted decrease in the aragonite saturation horizon in the oceans will result in only 30% of known deep-sea coral reefs and mounds remaining in supersaturated waters compared to the present-day figure of >95% (Guinotte et al. 2006). Ocean waters south of Australia may become inhospitable for cold-water corals below a few hundred metres. The shallowest pinnacles in the Tasmanian Seamounts Marine Reserve peak at about 600 m below the surface so cold-water corals on these seamounts could simply disappear, along with their multitude of associated organisms.

Solar radiation Future changes in UVR are difficult to predict (see p. 416) but in the following sections we discuss the potential impacts of heightened UVR, while recognising that the possibility of ozone recovery is becoming more likely. The extent to which UVR affects marine organisms will depend on factors such as aerosol concentrations, cloud cover and the concentration of dissolved and particulate matter in the water column (Jerlov & Steeman-Nielsen 1974, Smith & Baker 1979, Erga et al. 2005). Coastal systems Physiology UVR damages DNA and causes photo-oxidative stress in plants and animals (Setlow & Setlow 1962). In the aquatic environment, UVR effects should be most intense near the water surface. Sessile species, such as intertidal fauna and corals, do not have the capacity to avoid UVR through evasive movements and so can be exposed to powerful solar irradiances, particularly in tropical waters (see Shick et al. 1996). Tropical reef corals with their symbiotic zooxanthellae need to be exposed to sunlight for photosynthesis, so they are adapted for a high-UVR environment. However, an increase in UV light may exacerbate the simultaneous stress of warmer temperatures on corals and thus contribute to coral bleaching (Lesser 1996, 1997, Baruch et al. 2005, Drohan et al. 2005). Sublethal effects of UVR include depressed calcification and skeletal growth in corals (see Shick et al. 1996). Increased UVR reduces plant photosynthetic efficiency and biomass (Dawson & Dennison 1996, El-Sayed et al. 1996, Moorthy & Kathiresan 1997, 1998). Excessive UVR can induce photoinhibition in dinoflagellates, macroalgae, seagrasses, and the symbiotic zooxanthellae of tropical corals and sea anemones, with tolerances varying among species and life stages (Dawson & Dennison 1996, Graham 1996, Bischof et al. 1998, Häder et al. 1998; also see Shick et al. 1996). For example, net photosynthesis of the mangrove Rhizophora apiculata seedlings increased by 45% for a 10% increase in UVR but a 59% decrease in net photosynthesis occurred with a 40% increase in UVR (Moorthy & Kathiresan 1997). Many tropical species may already be near their upper limits of UVR tolerance so any further increase may reduce the ability of vulnerable species to persist near the water surface, thus leading to a shift in community composition (Häder et al. 1998). Egg and larval stages of many marine invertebrates and fish are highly susceptible to UV damage, particularly those that are pelagic (Lesser et al. 2003, Wellington & Fitt 2003, Przeslawski et al. 2004, 2005, Bonaventura et al. 2006). Increased UVR is known to have a deleterious effect on some adult fish, damaging ocular components and the epidermis, depressing the immune system, 441

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and allowing invasion of pathogens (Zagarese & Williamson 2001, Markkula et al. 2005). Some coral reef fishes that are exposed to intense irradiance are able to sequester UV-absorbing compounds from prey and thus are less vulnerable to UV increases (Zamzow 2004). Distribution and abundance Intertidal and subtidal algae and seagrasses will generally be susceptible to changes in solar irradiance. Upper depth limits of many species in these groups may deepen or grow shallower with increased or decreased levels of UVR, respectively (Dawson & Dennison 1996). Early life stages may be more susceptible to UVR than mature plants, thus regulating depth limits of adults (Graham 1996, Rijstenbil et al. 2000, Swanson & Druehl 2000, Cordi et al. 2001). For example, the upper depth limit of some kelp species is determined by susceptibility of their zoospores to UVR (Swanson & Druehl 2000, Wiencke et al. 2006) or early post-settlement stages (gametophytes or embryonic sporophytes) to photosynthetically active radiation (Graham 1996). Plants produce UV-absorbing compounds found predominantly in the epidermis and there is some capacity for adaptation in certain species. Levels of UVR-blocking pigment in certain tropical seagrasses increase when plants are grown at higher irradiance (Abal et al. 1994, Detres et al. 2001). Unlike sessile plants and animals, mobile fauna can shift distributions or retreat to refugia during periods of high solar radiation. One example is that the settlement of coral larvae is influenced by UVR levels (Kuffner 2001, Gleason et al. 2006), so these larvae may have some choice in settlement locations. How alteration of solar radiation patterns will affect behavioural responses of other marine animals is, however, generally difficult to predict. Visual systems of some shallowwater fishes use UV wavelengths and allow con-specific communication during breeding, shoaling or territorial behaviour (Losey et al. 1999, 2003, Garcia & de Perera 2002, Losey 2003, Siebeck 2004, Modarressie et al. 2006). It is assumed there is large plasticity in behavioural responses so at least some populations may adapt rapidly. Interspecific variability in the capacity of marine plants and animals to adapt to UVR changes (Hanelt et al. 1997, Choo et al. 2005) may lead to shifts in shallow-water and coral reef community structure if solar irradiance changes. Effects on communities should be most pronounced where there is a strong differential sensitivity to UVR between species or where protection against UVR is metabolically expensive or juvenile stages are found near the water surface (Wahl et al. 2004). Pelagic systems Physiology In phytoplankton, UVR can negatively impact several physiological processes and cellular structures, including photosynthesis, carbon and nutrient uptake, the ratio of polyunsaturated to saturated fatty acids, cell motility and orientation, the DNA, and life-span (Behrenfeld et al. 1993, Goes et al. 1994, Hessen et al. 1997, Wilhelm et al. 1997, Garde & Cailliau 2000, Hogue et al. 2005, Litchman & Neale 2005). These effects not only reduce phytoplankton growth, production and biomass (Worrest et al. 1978, Döhler 1994, Hessen et al. 1997, Keller et al. 1997, Wängberg et al. 1999) but also compromise the ability of phytoplankton to adapt to changing environmental conditions and respond to possibly hazardous situations (Häder & Häder 1989, Häder & Liu 1990). Although some phytoplankton are capable of acclimating to UVR via increased pigmentation or capability to repair damaged DNA, this inevitably involves metabolic costs reducing the energy that would otherwise be available for cell growth and division (Häder et al. 1998, Garde & Cailliau 2000). Increases in the cellular carbon-to-nutrient ratio and cell size reduce the nutritional value of phytoplankton for grazers. Negative effects of altered food quality are known to propagate to higher trophic levels and have been related to reductions in the abundance of copepod nauplii in experimental mesocosms (Hessen et al. 1997, Keller et al. 1997). UVR may positively affect bacteria and phytoplankton production because it increases the photolysis of dissolved organic carbon and colloids thereby increasing the availability of essential 442

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plant macro- and micronutrients from such compounds (Rich & Morel 1990, Palenik et al. 1991, Wängberg et al. 1999). There have been relatively few studies on the effects of UVR on marine zooplankton, in comparison with studies on phytoplankton. UVR is also known to damage various life stages of zooplankton such as copepods and shrimp, as well as eggs and larvae of crabs and fish that are temporary members of the plankton (Hunter et al. 1982, Damkaer & Dey 1983, El-Sayed et al. 1996, Kouwenberg et al. 1999a,b). In copepods, UVR has been found to lower fecundity, increase mortality and affect the sex ratio (Karanas et al. 1979, 1981, Bollens & Frost 1990). Because UVR can have deleterious consequences for those organisms that lack photoprotective mechanisms, many of the permanent members of the neustonic copepod community which are common in Australia’s warmer waters have pigments to reduce such damage. The effects of UVR radiation on fish eggs or larvae have rarely been investigated (see Zagarese & Williamson 2001). The few existing studies found deleterious effects of UVR in clear waters and confirm the importance of dissolved organic carbon in ameliorating those effects (Hunter et al. 1982, Keller et al. 1997, Zagarese & Williamson 2001). Distribution and abundance The degree of water column stratification crucially affects the exposure to UVR of those plankton that do not migrate vertically. Shallowing of the mixed surface layer and more energetic turbulence both increase plankton exposure to UVR and, therefore, their chance to receive harmful doses (Keller et al. 1997, Garde & Cailliau 2000, Barbieri et al. 2002, Hernando & Ferreyra 2005). Differential sensitivities of individual plankton taxa are thus likely to cause or have caused shifts in community structure or even ecosystem integrity, depending on the magnitude of changes in UVR. It is questionable to what extent the observed short-term effects of UVR on individual organisms can be used to estimate long-term ecosystem response (Häder et al. 1998).

Precipitation and storms A 70-yr drying trend has occurred along the eastern seaboard of the Australian mainland (Australian Greenhouse Office 2003), and this has reduced vegetation and destabilised sediment in coastal watersheds. Following intense storms in temperate Australia and monsoonal rains in tropical Australia, runoff from rivers tends to carry high sediment loads. The increasing frequency of intense storms as a result of climate change (Emanuel 2005, Webster et al. 2005) is likely to increase extreme rainfall events, hence altering runoff of freshwater and suspended sediment loads. There are clearly numerous indirect impacts associated with changes in freshwater flux in addition to the direct potential for fresh water to have physiological effects on marine organisms. Coastal systems Physiology Changes in rainfall patterns, and associated changes in watershed geomorphological dynamics, will affect the dynamics of coastal marine ecosystems through the physiological effects of large-scale flooding, fluctuations in salinity, and increases in turbidity and nutrients on resident organisms such as mangroves and wetland flora. Mangroves are adapted for coastal areas with waterlogged and often anoxic soils but their tolerance of salinity stress varies among species. As salinity levels increase, mangroves are faced with increasing salt levels in the tissues (see Field 1995). A ‘zonation’ of mangrove species can generally be observed going from the sea to the land or upriver from the mouth of estuaries reflecting the ecophysiological response of the plants along these and other environmental gradients and disturbance regimes (Ellison & Farnsworth 1993). Rainfall directly influences the salinity of the intertidal waters and sediments but also influences salinity through freshwater runoff from the land and freshwater seepage into the soil (Twilley & Chen 1998). 443

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Hydrology of mangroves is complex; tidal inundation, rainfall, groundwater seepage and evaporation all influence soil salinity and have a profound effect on mangrove growth. Hydrology model simulations of mangrove systems in southwest Florida have demonstrated that mangroves in the upper intertidal are particularly sensitive to reductions in rainfall, even though these are areas with minor freshwater input (Twilley & Chen 1998). Animals and plants living in the upper intertidal are generally near the upper limits of environmental tolerance limits so small alterations in climate may have a greater impact on upper shore organisms than in the lower intertidal. For example, seedlings of the mangrove Rhizophora apiculata grew more rapidly in the lower intertidal than those in the upper intertidal, presumably reflecting the additional stresses in the upper intertidal (Kathiresan et al. 1996). Freshwater runoff can increase sediment loading of coastal waters thus imposing metabolic costs on corals and other organisms that can potentially reduce growth or lead to mortality in severe cases (see Fabricius 2005). Other effects of sediment on corals can occur at early life-history stages. Sediment has been shown to reduce coral fertilisation (Gilmour 1999), as well as settlement (Babcock and Davies 1991) and post-settlement survival of recruits (Babcock and Smith 2002). Pollutants that are carried with flood waters are also known to have detrimental effects on the early life-history stages of corals. For example the herbicide diuron, commonly used in catchments adjacent to the Great Barrier Reef, inhibits coral metamorphosis and settlement (Negri et al. 2005). Distribution and abundance Mangroves are considered highly susceptible to alteration in rainfall abundance or frequency. In southeast Australia mangroves are expanding as they migrate into saltmarsh areas (Saintilan & Williams 1999, Harty & Cheng 2003, Harty 2004, Rogers et al. 2006). At Botany Bay, New South Wales, mangrove area increased by 32.8% between 1956 and 1996 while saltmarsh coverage decreased by 78.7% (Evans & Williams 2001). Although no single factor is responsible, it has been suggested that increased rainfall associated with climate change has reduced salinity levels within salt marshes thereby allowing mangroves to migrate and outcompete saltmarsh plants (Harty & Cheng 2003, Harty 2004, Rogers et al. 2006). However, hydrodynamic modification related to urban and rural development is likely to be the overriding factor driving mangrove expansion in the present climate. Freshwater influx not only reduces the salinity of coastal waters but also enhances the stratification of the water column thereby decreasing nutrient resupply from below. Flood events are associated with an increase in productivity as nutrients are washed into the sea (McKinnon et al. in press). While diatoms seem to be negatively affected by increases in river discharge, dinoflagellates have been observed to profit from the increase in stratification and availability of humic substances associated with riverine freshwater input (Carlsson et al. 1995, Goffart et al. 2002, Edwards et al. 2006). Irrespective of the direction of change, modifications in rainwater runoff and accompanying changes in salinity and resource supply should therefore affect the composition and, potentially, the productivity of the phytoplankton community in coastal waters. River discharge is also a primary shaper of soft-bottom coastal communities, particularly in tropical areas where smaller watersheds produce more sediment (Rhoads et al. 1985, Milliman 1991, Alongi & Robertson 1995, Hall 2002). Coral reefs are well known to be susceptible to fresh water as well as the effects of turbidity and sedimentation that vary with coastal weather patterns. Numerous examples of coral communities being killed off or adversely affected purely as a result of extreme rainfall events have been reported (Endean 1973, Rogers 1990, Alongi & Robertson 1995, Wilkinson 1999, Alongi & McKinnon 2005, Fabricius 2005). Increases in rainfall, or extreme rainfall events, can increase upland erosion and sediment transport considerably, thus severely impacting estuarine and nearshore coastal ecosystems, especially along coastlines where development and other human land uses have degraded the integrity of watersheds (Norkko et al. 2002, Thrush et al. 2003a,b, 2004, 444

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2005, Lohrer et al. 2004). This is of particular concern for the Great Barrier Reef (Devlin & Brodie 2005). Flood events are also associated with an increase in productivity as nutrients are washed into the sea. These nutrients may also lead to undesirable effects, for example, producing ideal conditions for the larvae of species such as the crown-of-thorns starfish. Recently long-term trends of increasing nutrients and phytoplankton concentrations in the coastal waters of the Great Barrier Reef have been shown, and these have been linked to recurring outbreaks of these starfish on the reef (Brodie et al. 2005). These factors in combination appear to have resulted in large-scale trends in coral diversity and abundance patterns on the Great Barrier Reef. Coastal areas in the so-called wet tropics, characterised by higher rainfall, greater runoff, and the most intensive agriculture, have generally lower coral diversity and lower coral cover than those adjacent to dryer coastal areas (De Vantier et al. 2006). Light penetration is an important factor limiting the distribution of marine macroalgae, both in Australia (Kennelly 1989) and elsewhere (Reed & Foster 1984, Deysher & Dean 1986, Dayton et al. 1999, Spalding et al. 2003). Increases in turbidity associated with greater rainfall, coastal development or other human activities would thus be expected to degrade macroalgal communities by generally decreasing the light penetration, so reducing depth ranges (Vadas & Steneck 1988; also see review in Okey et al. 2004). Increases in turbidity can give competitive advantage to shadetolerant flora and non-photosynthetic organisms (Keough & Butler 1995). The ability of kelp to compete with algal turfs may be reduced by coastal runoff. Turfs may benefit from the interaction between sediment and nutrients (Gorgula & Connell 2004). Cyclones and storms can be highly destructive by uprooting coastal plants, killing coastal animals, and destabilising and eroding coastlines. These natural disturbance regimes may be important in maintaining biodiversity in coastal ecosystems; however an increased frequency or intensity of storms may reduce the resilience of coastal ecosystems (Dayton et al. 1992, Graham 1997, Carruthers et al. 2002, Fourqurean & Rutten 2004). Impacts on coral reefs can be severe; the Category 4 Hurricane Andrew (Porter & Meier 1992) in Florida and other parts of the Caribbean substantially damaged corals through intense wave impacts. Cyclones in Australia and elsewhere have caused large-scale loss of algal cover and seagrass beds and devastation of mangroves and coral reefs (Dayton et al. 1992, Preen et al. 1995, Rothlisberg et al. 1998, Gardner et al. 2005). Recovery after these events can be relatively quick, but prolonged increases in the frequency or intensity of storms and cyclones may increase the likelihood of severe perturbations and lead to pronounced changes in biodiversity and community structure. Cyclones and storms also kill marine animals such as turtles and seabirds and destroy breeding and feeding habitat (Limpus & Reed 1985). Destruction by cyclones is considered a major threat for breeding colonies of northern birds such as the lesser noddy Anous tenuirostris melanops and the sooty tern Sterna fuscata (King et al. 1992, Garnett & Crowley 2000). Storms also exert considerable damage in temperate ecosystems, for example through removal of habitat-forming kelps and associated fauna, and influence community structure (Dayton & Tegner 1989). For example, the large fucoid alga (Carpophyllum flexuosum) is characteristic of calm conditions and is now common in areas of northeastern New Zealand where it was once virtually absent (Cole et al. 2001). This range expansion coincides with a significant decrease in storm frequency and intensity in this part of New Zealand over the past 30 yr related to decadal-scale climate variation (de Lange & Gibb 2000). Pinnipeds and seabirds nesting along Australia’s southern shores are vulnerable to storm-induced mortality. Pup mortality in Australian fur seals is strongly influenced by summer storms, particularly in low-lying colonies (Pemberton & Gales 2004). Phenology The tropical wet season strongly influences life cycles of fauna and flora such as the flowering and fruiting patterns of trees and shrubs (Friedel et al. 1993, Bach 2002, Keatley et al. 445

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2002, Boulter et al. 2006) including mangroves (Ochieng & Erftemeijer 2002, Tyagi 2004). The wet season also stimulates breeding in insects (Kemp 2001) and birds (Garnett & Crowley 2000, Whitehead & Saalfeld 2000). Tropical rainfall may also trigger behavioural changes in estuarine animals such as banana prawns, Penaeus merguiensis. In common with many commercially important species of penaeid prawns, these have a life cycle that involves migrations between nursery areas in mangrove-lined creeks and estuaries and offshore coastal waters. Rainfall is highly correlated with offshore commercial catches of banana prawns in southern areas of the Gulf of Carpentaria (Vance et al. 1985). It is thought high rainfall leads to a decrease in salinity of estuarine waters, which triggers an increased emigration of prawns (Staples 1980, Staples & Vance 1986, Vance et al. 1998). This salinity trigger has been noted in other parts of the world (see Zein-Eldin & Renaud 1986). Pelagic systems Physiology Because coastal regions may receive considerable freshwater input, coastal phytoplankton is subject to more variation in salinity than oceanic phytoplankton. In general phytoplankton species are adapted for ambient salinity so coastal species such as Skeletonema costatum thrive over a wide range of salinities while offshore species grow well only within narrow salinity ranges. In addition, estuarine and coastal species exhibit optimal growth at low and intermediate salinities while offshore species thrive at high salinities (Brand 1984, McQuoid 2005, Thessen et al. 2005).

Sea level Coastal systems Physiology Different mangrove species are adapted for different tidal inundation regimes as apparent in the zonation patterns of coastal mangroves. Rising sea level will alter the tidal inundation regime experienced by mangroves and presumably increase environmental stress on individual plants. For example, laboratory experiments have shown increased tidal inundation reduced growth and photosynthetic rates in Rhizophora mangle seedlings (Ellison & Farnsworth 1997). At any particular site, the mangrove community is highly specialised for local environmental conditions so minor variations in hydrological or tidal regimes can result in high mortality (Blasco et al. 1996). Distribution and abundance Coastal marine habitats will be vulnerable to changes in sea level (Short & Neckles 1999). The increase in water depth and consequent reduction in light availability to the sea bed will impact subtidal marine plants and tropical corals. At any given location, the location of maximum depth limits will shift, depending on topography, directly affecting distributions and abundance. For example, it is estimated that a 50-cm increase in sea level could result in a 30–40% reduction in growth of Zostera marina, a widespread Northern Hemisphere seagrass (Short & Neckles 1999). In many places, the shoreward shift of plants and animals will be impeded by coastal development. Sea-level rise will also alter the magnitude of local tidal ranges, depending on interactions with coastal topography. An increase or decrease in tidal range will directly impact the ‘zonation’ of macroalgae and fauna in the intertidal and subtidal. An increase in tidal range will exacerbate effects of changing water depth on subtidal plant communities, resulting in a loss of biomass in deeper waters whereas a decrease in tidal range will reduce exposure stress at shallower depths (Short & Neckles 1999). Mangroves typically occur on low-profile, low-energy coastlines and are ecologically restricted to saline intertidal environments so are considered particularly susceptible to rapid changes in sea 446

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level (Woodroffe 1992, Ellison 1993, Parkinson et al. 1994, Field 1995). Mangrove areas around Australia with small tidal regimes such as Shark Bay and the Exmouth Gulf are likely to be inundated by the projected rise in sea level (see Hughes 2003). When sea levels rise, as projected over the next century, shorelines will move landward but if sedimentation is more rapid then sealevel rise, shorelines may actually move seaward. Mangroves trap suspended sediments, for example a field study in a mangrove swamp in Cairns found 80% of suspended sediment brought in from coastal waters at spring flood tide was trapped in the mangroves, resulting in a rise of the substratum of 1 mm per year and presumably reducing turbidity in coastal waters (Furukawa et al. 1997). If sediment accretion rates in mangroves are equal to or exceed sea-level rise then mangroves will persist. The ability to accrete sediments will depend on the availability of suspended sediments in coastal waters so in areas where suspended sediment load is low, mangroves may not be able to track rising sea levels (Ellison & Stoddart 1991, Parkinson et al. 1994). Modelling studies of the response of tropical Australian estuaries to sea-level rise reveal differing responses depending on hydrodynamics and channel morphology; in some estuaries mangroves will expand while in others mangroves will retreat (Wolanski & Chappell 1996). Mangroves growing on carbonate settings or low islands may be strongly threatened by sea-level rise over the next century (Ellison & Stoddart 1991, Ellison 1993). Rising sea level is also a threat to bird species that nest on low-lying coastal areas as valuable breeding sites are flooded or eroded (Galbraith et al. 2002). Examples are the little kingfisher Alcedo pusilla pusilla and spangled drongo Dicrurus bracteatus carbonarius nesting on low-lying islands in the Torres Strait and the lesser noddy Anous tenuirostris melanops that nests in mangroves (Garnett & Crowley 2000). Marine turtle breeding beaches will be impacted by sea-level rise. For example, 32% of current beach area on the island of Bonaire in the Caribbean could be lost if the sea level rises by 50 cm and the loss of potential turtle nesting habitat may be even higher particularly where land directly behind the beach system is developed (Fish et al. 2005). Pinniped haul-out sites for breeding and nurseries may also be reduced or eliminated by sea-level rise (Learmonth et al. 2006).

Community impacts Climate impacts on particular species or groups do not occur in isolation and can result in extensive cascading effects and complex interactions (Figure 8). Climatic impacts on a few leverage species, such as species considered foundation species or ecosystem engineers, may result in sweeping community-level changes (Coleman & Williams 2002). Foundation species such as corals support a diverse range of fauna and flora by providing complex architectures of living habitat while ecosystem engineers increase habitat complexity either morphologically or behaviourally. Species that are functionally unique play a distinct role, so loss of these species tends to result in severe impacts on the ecosystem (Fonseca & Ganade 2001). Others such as phytoplankton and zooplankton are found in great numbers and are the base of trophic webs. Most of these groups are primary or secondary producers and therefore support higher trophic levels such as pelagic and demersal fishes, seabirds, turtles and marine mammals. Keystone species have a disproportionate structuring effect on biological communities (large interaction strength relative to their own abundance or biomass), and they are often vulnerable to local extinction due to their small numbers or biomass. Models and analytical tools provide the capability to estimate climate change impacts in terms of diversity, community composition and species interactions in the context of both direct and indirect effects. Relatively little modelling work has been done on Australian marine species and communities, and there has been no large-scale investigation on the potential impacts of climate change on the diverse and unique fauna of the region. Corals of the Great Barrier Reef are the only group that has been investigated extensively in terms of potential impacts of climate change. 447

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Stressors

Low

Climate change (e.g. increased temperatures, increased storms, currents, acidification)

High

Non-climate change (e.g. fisheries, pollution, habitat degradation) Attributes of species that arrive or leave Net interaction strength Engineering/architecture-forming (foundational) High

Low Keystoneness Functional uniqueness

Small change

Community structure

Large change

Management strategies Mitigation by global emissions reductions Major

Adaptation by management of non-climate stressors

Minor

Figure 8 Species attributes, types of stressors and management strategies that influence the magnitude of climate change impacts on the structure and function of biological communities. Low levels of particular attributes of the species that invade an area or become locally extinct lead to minimal changes, as do low levels of climate and non-climate stressors that a community is exposed to. High levels of those attributes and stressors lead to large community changes. Major implementation of management strategies can reduce community impacts, whereas minor implementation in the context of major stressors can lead to large community changes.

Non-climate stressors Climate change is not the only stressor to impact ecosystems, either at present or into the future. Anthropogenic stressors, such as fishing, pollution, coastal development and exotic pests, will all decrease the resilience of marine life and ecosystems. Systems that are already highly stressed may be particularly vulnerable to further perturbations such as those induced by climate change (Hughes & Connell 1999, Steneck et al. 2002, Hughes et al. 2003). Most non-climate stressors can be managed faster than climate change by altering policy and management practices on national and regional scales. Although Australian fisheries are relatively small by international standards due to the generally oligotrophic waters, considerable tonnage is still extracted and many species and groups are overexploited or at high risk. Fisheries can have major impacts on marine systems through removal of large predators, substantial by-catch of non-target species and habitat destruction by dredges and trawls. Australian fisheries include various commercial (Caton & McLaughlin 2004), recreational and indigenous fisheries (Henry & Lyle 2003). Commercial fisheries harvest more than 130,000 tonnes of fish, squid and crustaceans annually, mostly from coastal, continental shelf and upper continental slope waters. Of 74 Australian stocks considered in 2004, 17 were overfished, 17 were not overfished and 40 were of uncertain status (Caton & McLaughlin 2004), but such 448

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statistics can underestimate the damage to non-target biota and habitat structure. Recreational fishers also remove a sizeable biomass of fish and crustaceans (>30,000 tonnes annually) from coastal and estuarine waters (Lyle et al. 2003). Virtually all of Australia’s population and industries are situated along the coastal fringe or rivers that drain into the sea, and so the effects of pollution and coastal development on marine species or ecosystems can be severe (Kirkman 1997, Duke et al. 2005, Votier et al. 2005). Modification of structure and function of coastal watersheds by agriculture, urban development, and deforestation can lead to considerable increases in erosion and nutrient runoff. Habitat modification and destruction through coastal development or activities such as dredging will all impact marine habitats such as estuaries, mangroves, seagrass beds and kelp forests. These habitats are integral features of marine ecosystems that provide a variety of critical ecosystem services such as nursery grounds, primary production and adult habitats for whole suites of marine organisms. Introduced species can also have severe consequences for marine ecosystems. For example in 1995 and 1998/1999, mass mortalities linked to exotic pathogens probably introduced from aquaculture feed spread rapidly throughout the Australian population of the sardine Sardinops sagax (Gaughan 2001, Ward et al. 2001). These mortality events represent two of the most extensive mass mortality events recorded for marine organisms (Gaughan 2001). Biological communities have adapted to various levels of natural disturbance and variability over evolutionary timescales. Shifts in these disturbance regimes increase stress to these systems and decrease the overall resilience of the system to other disturbances. However, the resilience principle also implies that reductions of the stressors that humans can control may partially ameliorate increasing climate change impacts (Figure 8). Thus easing the impacts of fisheries, pollution, habitat destruction and other non-climate anthropogenic-induced stressors on marine ecosystems may partly mitigate climate change impacts. Although immediate and conscientious international diplomacy to reduce greenhouse gas emissions is a critical mitigation strategy for addressing the long-term impacts of climate changes, adaptive and integrated management systems that focus on fisheries and pollution on regional levels are just as critical because these can address the near-term inevitable changes that will act synergistically with climate change to threaten Australia’s marine life.

Summary Rising temperatures will have a major influence on species distributions, although population responses will be modified by climate-induced changes in competitive ability, dispersive capacity and behaviour of organisms. However, a general shift in species distributions toward higher latitudes is expected and is already occurring in many parts of the world (Parmesan et al. 1999, Thomas & Lennon 1999, Beaugrand et al. 2002, Parmesan & Yohe 2003, Hickling et al. 2006). In Australian coastal waters, this shift may be facilitated by the major southward-flowing surface currents, particularly given the projected enhancement of the EAC. A concurrent alteration in phenology is expected, with longer growing seasons for marine plants (e.g., seagrasses) and earlier breeding seasons of marine animals. Higher sea level will alter coastline and island hydrography and topography, with potential loss of nesting or breeding areas for seabirds, turtles and seals. Acidification may become a major threat to tropical coral reefs and the cold-water corals found on the edge of the continental slope and on seamounts and to some plankton that are important for ecosystem functioning (Orr et al. 2005, Guinotte et al. 2006). A schematic of many of the expected impacts of future climate change on Australian marine systems is shown in Figure 9. In coastal waters, tropical species of seagrasses, mangroves and fish have shifted further south. Dugongs have also moved further south following the expansion of tropical seagrasses. However, cold-water kelp species have disappeared from higher latitudes with 449

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Figure 9 (See also Colour Figure 9 in the insert.) Hypothetical Southern Hemisphere marine coastline and coastal waters ranging from low latitudes in the north to high latitudes in the south under present climate (top) and in the future under global warming scenario (bottom). As temperatures rise, species’ distributions shift further south. The range of tropical and subtropical species extends to temperate latitudes while temperate species in the south decline. Rising temperatures and ocean acidification stress coral reefs leading to frequent coral bleaching and an increase in mortality while rapid sea level rise inundates the coral reefs. Ocean acidification also leads to the decline of calcifying plankton such as pteropods and coccolithophores. Rising sea-level encroaches on the mainland and on offshore islands. The sex ratio of marine turtle hatchlings, which is determined by ambient nest temperatures, is skewed in the future as warming produces more females.

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a warming climate and the occurrence and distribution of venomous jellyfish has increased. Further offshore corals have bleached and declined in response to warmer temperatures and ocean acidification. Tropical pteropods and coccolithophores have also declined as the oceans acidify. The sex ratio of turtle hatchlings is heavily skewed toward females as nesting beaches heat up. Finally, rapid sea-level rise has drowned the coastline, islands and barrier reefs. Monitoring and strategic planning is sorely needed for Australia because numerous other climate change effects might be already occurring in Australia’s marine realm.

Tropical and subtropical Australia Rising temperatures and ocean acidification are considered the major climate change threats to tropical coral reefs. Bleaching of coral reefs has occurred regularly over the last couple of decades and is projected to occur with increasing frequency over this century. Australian coral reefs are relatively healthy compared to many elsewhere in the world (Pandolfi et al. 2005). However, they are facing considerable pressures from changes to coastal water quality and overexploitation of key ecological functional groups, particularly in areas close to urban and agricultural developments. The role of coral reefs in underpinning coastal economies in Australia is becoming increasingly recognised. The pristine nature of Australian coral reefs attracts large numbers of tourists; the reefassociated tourist economy currently exceeds $A4 billion per annum. Hoegh-Guldberg & HoeghGuldberg (2004) analysed the potential effect of losing the competitive edge for tourism if the coral reefs on the Great Barrier Reef deteriorated as a result of climate change. The effects vary, depending on domestic and international trends in aspects such as markets and politics. However, if one uses the reef-associated component of these economies as a guide to how things might change if reefs continue to degrade, degradation would reduce international tourist income by as much as $A8 billion over 19 yr (Hoegh-Guldberg & Hoegh-Guldberg 2004). Seagrass beds and mangroves commonly co-occur with tropical coral reefs and there are strong interactions between them (Harborne et al. 2006). Coral reef crests dissipate wave energy thus ensuring the calm conditions required by seagrass beds and mangroves further inshore, while mangrove and seagrasses filter riverine sediments and nutrients that would otherwise impact coral reefs. Many fish are found in mangroves and seagrasses as juveniles before undertaking ontogenetic shifts in habitat use onto coral reefs (Mumby et al. 2004, Dorenbosch et al. 2005, Mumby 2006). Deterioration in one or more of these systems due to climate change or other impacts may have deleterious consequences for the entire coastal ecosystem with associated economic losses. A reduction in seagrass beds and mangroves will have an immediate impact on the economic value of associated fisheries (Loneragan et al. 2005, Manson et al. 2005, McArthur & Boland 2006). Mangroves and seagrasses provide a range of ecosystem services such as recycling of carbon and nutrients, shoreline protection and enriched coastal productivity (Costanza et al. 1997, Ewel et al. 1998, Kathiresan & Bingham 2001, Duarte et al. 2005, Bloomfield & Gillanders 2005). Coastal fringing mangroves are important for shoreline protection from storms and erosion (Ewel et al. 1998, Badola & Hussain 2005, Kathiresan & Rajendran 2005).

Temperate Australia Over 46% of Australian’s population live in the southeast (Zann 2000). Around Sydney, central New South Wales, the coastline is largely metropolitan with extensive industrial development (Zann 2000). The southeast is considered the most stressed from anthropogenic pressures, other than climate change, such as metal and sewage pollution (Hobday et al. 2006). Large demersal trawl fisheries operate in southeastern Australian waters. This region is also considered the most stressed

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by fishing pressure, with a highest proportion of overexploited stocks (Caton & McLoughlin 2004, Hobday et al. 2006). Marine ecosystems of southern Australia are strongly influenced by the Leeuwin Current and EAC (Maxwell & Cresswell 1981, Phillips 2001). The temperature difference between the EAC and surrounding waters can be more than 5°C (Zann 2000). The projected strengthening of the EAC and warming of the Tasman Sea as global climate warms will have detrimental effects for cold-temperate species in the southeast, particularly in Tasmanian waters. The shelf does not extend far south of Australia and the lack of alternative land mass until Antarctica means these species have no suitable habitat to occupy as global climate warms. The cold-water giant kelp is already in decline in this region and presumably other marine organisms in this region are also at high risk from climate change. All marine groups investigated are expected to show some southward movement of members. The coccolithophore Gephyrocapsa oceanica is a good example; a tropical strain of it has already expanded into temperate waters in eastern Australia. The relatively productive temperate pelagic zone may shrink considerably in area and potentially become restricted to west of Tasmania by the 2070s, while the food web in formerly productive regions may shift toward a much less productive subtropical regime. The recent expansion of G. oceanica and decreasing stock sizes of jack mackerel in southeastern shelf waters and southern bluefin tuna returning to the east coast in winter indicate that the pelagic ecosystem may have started to change (Welsford & Lyle 2003, Blackburn 2005, Polacheck et al. 2006). Venomous jellyfish and harmful algal blooms are a major threat to human health, but are largely phenomena associated with tropical waters or relatively warm and stratified waters, respectively. As a consequence of enhanced southward flow of warm currents such as the EAC and ocean warming these phenomena will likely extend into more southerly regions currently unaffected (jellyfish) or occur more frequently (in case of harmful algal blooms).

Critical knowledge gaps and a way forward In this review we have detailed the expected considerable and observed consequences of climate change for marine groups, some of which, such as bleaching of tropical corals, are already being observed in Australian waters. At present, it is impossible to determine if climate change is impacting many less-charismatic marine groups and habitats in Australia, despite compelling evidence from elsewhere in the world. Long-term datasets are key to documenting and understanding the response of species to climate change. Australian marine scientists have long claimed that the lack of observable climate signals is a consequence of the paucity of ecological time series in the region. This claim is not unique to Australia. Despite an exponential increase in the initiation of long-term monitoring programmes in the world’s oceans since World War II, 40% of these time series were discontinued during the 1980s because monitoring was viewed as poor science by administrators (Duarte et al. 1992). This negative perception began shifting during the late 1990s when the knowledge of consequences of climate change began emerging in scientific and political realms, and this has markedly improved the support for many monitoring programmes (Hays et al. 2005). The case of zooplankton sampling in Australia highlights gaps in the present monitoring system. Zooplankton may be the most abundant multicellular organisms on the planet, are the major source of food of many marine organisms, and are considered sentinels of climate change (Hays et al. 2005). Globally there are zooplankton time series spanning more than 15 yr in no fewer than 30 countries, including relatively small or developing nations such as Bulgaria, Chile, Estonia, Greece, Kazakhstan, Latvia, Faroe Islands, Namibia, Peru, Turkey and the Ukraine. However, the longest

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ongoing zooplankton time series in Australia is 2 yr and consists of a single cross-shelf transect off Perth. Given the diversity of marine habitats in Australia and the economic and social importance of fishing, Australia is clearly impoverished in long-term zooplankton and other datasets urgently required to assess climate change impacts (see Hobday et al. 2006). Without such datasets, Australia will be unaware of how its marine systems are altered by future climate change, continuing to rely on information gathered from systems elsewhere. This will make adaptation and mitigation strategies uncertain. This review indicates that we have a general understanding of some of the likely mechanisms of climate effects on a few particular species, but we have limited knowledge about how Australian marine ecosystems will respond to climate change. It is only when Australia focuses on the entirety of its marine resources will we be able to tackle rigorously the impacts of climate change. There are a number of critical questions that need to be addressed to allow managers tasked with conserving biodiversity, locating marine protected areas, managing eco-tourism associated with cetaceans and turtles, and implementing management plans for the sustainable use of marine resources and indigenous harvesting: • • • • • •

How will the distribution, abundance and phenology of marine species alter with climate change and how will these impact communities? Which species are candidate indicators to monitor climate change in Australian waters? Which areas are particularly sensitive to changing climate or are ‘hot spots’ of change? How will regional ocean productivity alter with climate change? How can ecosystem resilience to climate change be increased? How will climate change affect the socioeconomic productivity of marine ecosystems?

Acknowledgements This contribution was supported by the CSIRO Wealth from Oceans National Research Flagship and the Australian Greenhouse Office.

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CLIMATE CHANGE AND AUSTRALIAN MARINE LIFE Sammarco, P.W. & Andrews, J.C. 1988. Localised dispersal and recruitment in Great Barrier Reef Corals: the Helix experiment. Science 239, 1422–1424. Sarmiento, J.L., Slater, R., Barber, R., Bopp, L., Doney, S.C., Hirst, A.C., Kleypas, J., Matear, R., Mikolajewicz, U., Monfray, P., Soldatov, V., Spall, S.A. & Stouffer, R. 2004. Response of ocean ecosystems to climate warming. Global Biogeochemical Cycles 18, GB3003. Sato, K., Matsuzawa, Y., Tanaka, H., Bando, T., Minamikawa, S., Sakamoto, W. & Naito, Y. 1998. Internesting intervals for loggerhead turtles, Caretta caretta, and green turtles, Chelonia mydas, are affected by temperature. Canadian Journal of Zoology 76, 1651–1662. Scheibling, R.E. & Hennigar, A.W. 1997. Recurrent outbreaks of disease in sea urchins Strongylocentrotus droebachiensis in Nova Scotia: evidence for a link with large-scale meteorologic and oceanographic events. Marine Ecology Progress Series 152, 155–165. Schiel, D.R., Steinbeck, J.R. & Foster, M.S. 2004. Ten years of induced ocean warming causes comprehensive changes in marine benthic communities. Ecology 85, 1833–1839. Schiermeier, Q. 2005. Cleaner skies leave global warming forecasts uncertain. Nature 435, 135. Schippers, P., Lürling, M. & Scheffer, M. 2004. Increase of atmospheric CO2 promotes phytoplankton productivity. Ecology Letters 7, 446–451. Schwartz, M.D., Ahas, R. & Aasa, A. 2006. Onset of spring starting earlier across the Northern Hemisphere. Global Change Biology 12, 343–351. Sebens, K.P. 2002. Energetic constraints and size gradients in intertidal and subtidal marine invertebrates. Integrative and Comparative Biology 42, 853–861. Seddon, S., Connolly, R.M. & Edyvane, K.S. 2000. Large-scale seagrass dieback in northern Spencer Gulf, South Australia. Aquatic Botany 66, 297–310. Sedwick, P.N., DiTulliio, G.R., Hutchins, D.A., Boyd, P.W., Griffiths, F.B., Crossley, A.C., Trull, T.W. & Quéguiner, B. 1999. Limitation of algal production by iron and silicic acid deficiency in the Australian subantarctic region. Geophysical Research Letters 26, 2865–2868. Serrão, E.A., Pearson, G., Kautsky, L. & Brawley, S.H. 1996. Successful external fertilization in turbulent environments. Proceedings of the National Academy of Sciences of the United States of America 93, 5286–5290. Setlow, R.B. & Setlow, J.K. 1962. Evidence that ultraviolet-induced thymine dimers in DNA cause biological damage. Proceedings of the National Academy of Sciences of the United States of America 48, 1250–1257. Shick, J.M., Lesser, M.P. & Jokiel, P.L. 1996. Effects of ultraviolet radiation on corals and other coral reef organisms. Global Change Biology 2, 527–545. Short, F.T. & Neckles, H.A. 1999. The effects of global climate change on seagrasses. Aquatic Botany 63, 169–196. Siebeck, U.E. 2004. Communication in coral reef fish: the role of ultraviolet colour patterns in damselfish territorial behaviour. Animal Behaviour 68, 273–282. Simkanin, C., Power, A., Myers, A., McGrath, D., Southward, A.J., Mieszkowska, N., Leaper, R. & O’Riordan, R. 2005. Using historical data to detect temporal changes in the abundances of intertidal species on Irish shores. Journal of the Marine Biological Association of the United Kingdom 85, 1329–1340. Simpson, C.J. 1991. Mass spawning of corals on Western Australian reefs and comparisons with the Great Barrier Reef. Journal of the Royal Society of Western Australia 74, 85–92. Sims, D.W., Genner, M.J., Southward, A.J. & Hawkins, S.J. 2001. Timing of squid migration reflects North Atlantic climate variability. Proceedings of the Royal Society of London B 268, 2607–2611. Sims, D.W., Wearmouth, V.J., Genner, M.J., Southward, A.J. & Hawkins, S.J. 2004. Low-temperature-driven early spawning migration of a temperate marine fish. Journal of Animal Ecology 73, 333–341. Smart, J. & Gill, J.A. 2003. Climate change and the potential impact on breeding waders in the U.K. Wader Study Group Bulletin 100, 80–85. Smayda, T.J. 1976. Phytoplankton processes in mid-Atlantic nearshore and shelf waters and energy-related activities. In Effects of Energy-Related Activities on the Atlantic Continental Shelf, B Manowitz (ed.). Report No. 50484. Brookhaven National Laboratory, Upton, New York, U.S., 70–95. Smith, J.R., Fong, P. & Ambrose, R.F. 2006. Dramatic declines in mussel bed community diversity: response to climate change? Ecology 87, 1153–1161.

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CLIMATE CHANGE AND AUSTRALIAN MARINE LIFE Wolfe, D.W., Schwartz, M.D., Lakso, A.N., Otsuki, Y., Pool, R.M. & Shaulis, N.J. 2005. Climate change and shifts in spring phenology of three horticultural woody perennials in northeastern U.S.A. International Journal of Biometeorology 49, 303–309. Womersley, H.B.S. & Edmonds, S.J. 1958, A general account of the intertidal ecology of south Australian coasts. Australian Journal of Marine and Freshwater Research 9, 217-260. Woodroffe, C. 1992. Mangrove sediments and geomorphology. In Tropical Mangrove Ecosystems, Coastal and Estuarine Studies No. 41, A.I. Robertson & D.M. Alongi (eds), Coastal and Estuarine Studies 41, 7–42. Worm, B., Lotze, H.K. & Myers, R.A. 2003. Predator diversity hotspots in the blue ocean. Proceedings of the National Academy of Sciences of the United States of America 100, 9884–9888. Worrest, R.C., van Dyke, H. & Thomson, B.E. 1978. Impact of enhanced simulated solar ultraviolet radiation upon a marine community. Journal of Photochemistry and Photobiology B 27, 471–478. Yntema, C.L. & Mrosovsky, N. 1982. Critical periods and pivotal temperatures for sexual differentiation in loggerhead sea turtles. Canadian Journal of Zoology 60, 1012–1016. Zacherl, D., Gaines, S.D. & Lonhart, S.I. 2003. The limits to biogeographical distributions: insights from the northward range extension of the marine snail, Kelletia kelletii (Forbes, 1852). Journal of Biogeography 30, 913–924. Zagaglia, C.R. & Stech, J.L. 2004. Remote sensing data and longline catches of yellowfin tuna (Thunnus albacares) in the equatorial Atlantic. Remote Sensing of the Environment 93, 267–281. Zagarese, H.E. & Williamson, C.E. 2000. Impact of UV radiation on zooplankton and fish. In The Effects of UV Radiation in the Marine Environment. S.J. de Mora et al. (eds) Cambridge, UK: Cambridge University Press, 279-309. Zagarese, H.E. & Williamson, C.E. 2001. The implications of solar UV radiation exposure for fish and fisheries. Fish and Fisheries 2, 250–260. Zamzow, J.P. 2004. Effects of diet, ultraviolet exposure, and gender on the ultraviolet absorbance of fish mucus and ocular structures. Marine Biology 144, 1057–1064. Zann, L.P. 2000. The eastern Australian region: a dynamic tropical/temperate biotone. Marine Pollution Bulletin 41, 188–203. Zein-Eldin, Z.P. & Renaud, M.L. 1986. Inshore environmental effects on brown shrimp Penaeus aztecus and white shrimp P. setiferus populations in coastal waters, particularly of Texas. Marine Fisheries Review 48, 9–19. Zimmerman, R.C., Korhs, D.G., Steller, D.L. & Alberte, R.S. 1997. Impacts of CO2 enrichment on productivity and light requirements of eelgrass. Plant Physiology 115, 599–607. Zimmerman, R.C. & Robertson, D.L. 1985. Effects of El Niño on hydrography and growth of the giant kelp, Macrocystis pyrifera, at Santa Catalina Island, California. Limnology and Oceanography 30, 1298–1302. Zou, D.H. & Gao, K.S. 2002. Photosynthetic responses to inorganic carbon in Ulva lactuca under aquatic and aerial states. Acta Botanica Sinica 44, 1291–1296. Zou, D.H. & Gao, K.S. 2005. Ecophysiological characteristics of four intertidal marine macroalgae during emersion along Shantou coast of China, with a special reference to the relationship of photosynthesis and CO2. Acta Oceanologica Sinica 24, 105–113.

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APPENDIX: THE CSIRO MK3 CLIMATE SYSTEM MODEL The CSIRO Mk3 Climate System Model (CSIRO Mk3) is a state-of-the-art climate model that represents all the major components of the Earth’s climate system: atmosphere, land surface, sea ice and oceans. A detailed description of the CSIRO Mk3 is given in Gordon et al. (2002) and summarised below. The CSIRO Mk3 is ranked with the top international models. CSIRO Mk3 model simulations are included in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (IPCC 2007). The Fourth Assessment Report assesses scientific, technical and socioeconomic information relevant for the understanding of climate change, its potential impacts, and the options for adaptation and mitigation. An essential component of this report is climate change projections of the impact of various scenarios of future levels of greenhouse gases on the earth’s climate system. The CSIRO Mk3 simulations are an important contributor to these climate projections. For climate projection present in this study we use the IPCC SRES A2 greenhouse gas emission scenario, which projects atmospheric CO2 levels of 536 ppm by 2050. The CSIRO Mk3 atmospheric module has a spectral T63 horizontal grid (~1.875° latitude by 1.875° longitude) with 18 vertical levels (hybrid sigma-pressure vertical co-ordinate). The atmospheric model includes a comprehensive cloud microphysical parameterisation and convection parameterisation, which are linked via the detrainment of liquid and frozen water at the cloud top. Atmospheric moisture advection (vapour, liquid and frozen) is carried out by the semi-Lagrangian method. This module includes the direct radiative forcing of sulphate on atmospheric albedo. The CSIRO Mk3 land surface scheme uses six layers of moisture and temperature with a vegetation canopy. The scheme uses multiple soil (9) and vegetation (12) types and includes a three-layer snow model. The sea-ice module incorporates a dynamical-thermodynamic polar ice model that includes a variable fraction of leads. The CSIRO Mk3 ocean model is based upon the Modular Ocean Model version 2.2 (MOM2.2) of the Geophysical Fluid Dynamics Laboratory (GFDL) model. The oceanic component has horizontal resolution of ~0.9375° latitude by 1.875° longitude. For every atmospheric grid point there are two ocean points in the meridional direction, which allows for the atmospheric model and ocean model subcomponents to have matching land-sea masks. There are 31 levels in the vertical, with the spacing of the levels gradually increasing with depth, from 10 m at the surface to 400 m at depth. The ocean model includes a parameterisation of mixing of tracers based on the formulation of Griffies et al. (1998) and improved vertical mixing in the tropical Pacific. For the climate change projection in this manuscript we use the Mk 3.5 version of the climate system model which has a greatly improved simulation of the Southern Ocean from the original Mk 3 climate system model.

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Particle size D (µm)

0

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m = 1.17 + i0.0001

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Colour Figure 4 (Clavano, Boss & Karp-Boss) The volume scattering function for spheres, β
(θ) (A, D), and for equal-volume spheroids, β
(θ) with aspect ratio s/t = 2 (B, E). The ratio between the two (i.e., the bias denoted as γβ(θ) is presented in panels C and F. The primary y-axis for each plot represents variation in particle size, D[µm], while the secondary y-axis represents variation in the phase shift parameter, ρ (scale found on C and F). Results are for two different types of particles: phytoplankton-like particles with m = 1.05 + i0.01 (A, B, C) and inorganic-like particles with m = 1.17 + i0.0001 (D, E, F). Values for spheroids have been obtained using the T-matrix method for D ≤ 10 µm and by the ray tracing method for D ≥ 40 µm. No solution is available for 10 < D < 40 µm (white regions in B, C, E and F).

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Day of July 1995, West Sound, Orcas Island, Washington 27 28

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m−3)

Colour Figure 5 (Jumars) For legend see Jumars Figure 5 (p. 120).

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Colour Figure 3 (Thiel) For legend see Thiel Figure 3 (p. 207).

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10

10

5

5

5

6 27 July

2

8

4

6 28 July

20

20

15

15

15

10

10

10

5

5

5

4

6 30 July

8

2

4

6 31 July

−35

−45

8

Hour of day

Colour Figure 6 (Jumars) For legend see Jumars Figure 6 (p. 120).

−50

−55

−60

2

8

20

2

2

20 22 24 2 30 July–1 August

20

4

22 24 28–29 July

−40

2

20

2

−30

2

20

20

−25

4

6 29 July

8

−65

−70

−75

2

4 6 1 August

8

Volume backscattering strength (dB)

20

50931_C009.fm Page 552 Tuesday, May 1, 2007 6:09 PM

10° Indian Ocean

Exmouth Gulf

Scott Reef

Torres Strait Darwin Gulf of Carpentaria

Cape York

Great Barrier Reef

20° Hervey Bay

30°

Pacific Ocean

Australia

Shark Bay

Brisbane Moreton Bay

Houtman Abrolhos Islands Perth Albany

Hawkesbury Estuary Botany Bay

Sydney

Adelaide

Melbourne Corner Inlet Bass Strait Tasman Sea

40°

Tasmania

Southern Ocean

New Zealand

Hobart

Tasmanian Seamounts Marine Reserve

50° 110°

120°

130°

140°

150°

160°

170°

180°

190°

Colour Figure 1 (Poloczanska et al.) Map of Australia indicating the locations discussed in the text. The 200 nm EEZ for Australia is marked by the dashed line, and the 200 m depth contour by the solid line. 110°00’E

120°00’E

130°00’E

140°00’E

10°00’S

150°00’E N

1b Darwin 2a

20°00’S

1a

Kimberlays Northern Territory

Port Hedland

10°00’S

1c? 2c

Cairns Burketown Mackey Queensland

Australia

20°00’S

3

Western Australia Brisbane South Australia

30°00’S 5a

Perth Esperance 2b

40°00’S

New South Wales Sydney 2d Canberra ACT Victoria Melbourne 4 2d Tasmania Hobart

6 110°00’E

120°00’E

130°00’E

30°00’S

Ceduna Adelaide

140°00’E

5b 40°00’S

2d

150°00’E

Colour Figure 3 (Poloczanska et al.) Phytoplankton provinces around Australia. In northern shelf waters westwards from Torres Strait tropical diatom species dominate, with slight regional differences in relative abundances and absolute biomass (1a-c). The shallow waters of the Great Barrier Reef region (3) are dominated by fast-growing nano-sized diatoms. The deeper waters of the Indian Ocean and the Coral Sea are characterised by a tropical oceanic flora (2a and 2c, respectively) that is dominated by dinoflagellates and follows the Leeuwin Current (2b) and the East Australia Current and its eddies (2d). South-eastern coastal waters harbour a temperate phytoplankton flora (4) with seasonal succession of different diatom and dinoflagellate communities. Waters south of the tropical and temperate phytoplankton provinces are characterised by an oceanic transition flora (5a,b) that communicates to the subantarctic phytoplankton province (6) and is highly variable in extent. The phytoplankton provinces are associated with surface water masses and the zooplankton fauna likely shows a similar pattern (Figure prepared by G.M. Hallegraeff for CSIRO and National Oceans Office).

50931_C009.fm Page 553 Tuesday, May 1, 2007 6:09 PM

10°N

35

10°N

0°

30

0°

25

10°S

10 8

260

0°

220

240

6

200 10°S

10°S

180

4

20 20°S

10°N

160 20°S

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20°S

140

15 30°S

0

30°S

40°S

5

−2

80

40°S

40°S

60

−4

50°S

0

50°S

60°S

−5

60°S

60°E

120

30°S

100

10

80°E 100°E 120°E 140°E 160°E 180°

−6 −8 60°E

40

50°S

20 0

60°S

80°E 100°E 120°E 140°E 160°E 180°

60°E

80°E 100°E 120°E 140°E 160°E 180°

20.0 cm/s

2.6

10°N

6

10°N

0°

2.2

10°S

1.8

0°

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10°S

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1.6 1.4 1.2

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0 −1

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0 60°E

80°E 100°E 120°E 140°E 160°E 180°

0 −20 −30

10°S

−40 −50

20°S

−60 −70

30°S

−80 −90

40°S

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1 20°S

1 40°S

10

3

2

20°S

10°N

5

2.4

−100 −110

50°S

−6 −7

60°S 60°E

80°E 100°E 120°E 140°E 160°E 180°

−120 −130

60°S 60°E

80°E 100°E 120°E 140°E 160°E 180°

5.00 cm/s

Colour Figure 5 (Poloczanska et al.) Simulated annual means of SST (°C) with annual mean surface currents (cm/s) (left), annual mean zonal winds (m/s) (middle), and mixed layer depth (m) (right). In the middle panels, westerly wind direction is denoted by positive sign, easterly wind direction by negative sign. Top row: 1990s, bottom row: difference between 1990s and 2070s.

50931_C009.fm Page 554 Tuesday, May 1, 2007 6:09 PM

8.16 10ºN

10ºN

7

8.14 0º

8.12 8.1

10ºS

6.5

0º

6 10ºS 5.5

8.08 20ºS

8.06 8.04

30ºS

20ºS

5

30ºS

4.5

8.02 40ºS

8 7.98

50ºS

4

40ºS

3.5 50ºS

3

7.96 60ºS

7.94

60ºS

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10 ºE

ºE

0º

80

60

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10 ºE

80

ºE

60 10ºN

2.5

−0.09 10ºN

−0.5

−0.1

−0.6

0º

−0.11 10ºS

−0.12 −0.13

20ºS

−0.7 10ºS

−0.8 −0.9

20ºS

−1

−0.14 30ºS 40ºS

−0.15

30ºS

−1.1

−0.16

40ºS

−1.2

−0.17 50ºS

−0.18 −0.19

60ºS

−1.3 50ºS

−1.4 −1.5

60ºS

ºE

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10 ºE

80

60

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º

ºE

ºE

10

80

60

Colour Figure 6 (Poloczanska et al.) Simulated annual means of pH (left) and aragonite saturation state (right). Top row: 1990s, bottom row: difference between 1990s and 2070s.

50931_C009.fm Page 555 Tuesday, May 1, 2007 6:09 PM

10ºN

280 260

0º

10ºN

15

0º

12

240 10ºS 20ºS

220

10ºS

200

20ºS

10

160 140

40ºS

6 4

30ºS

100

60ºS

40ºS

0

−4

40

3

10ºN

20 0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10 ºE 80

30ºS

0.5

28 26 24 22 20 18 16 14 12 10 8 6 4 2

0º 10ºS

0

20ºS 30ºS

−0.5 40ºS

−1

−40

−80

60

1

0

60ºS

80

50ºS 60ºS

1.5

10ºS

30ºS

−60

100 40ºS

−6

2

20ºS

50ºS

120

ºE

ºE

E

0º

0º

20

40ºS

140 30ºS

2.5

20ºS

−20

160

60

10ºN

40

180

20ºS

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10 ºE

100

60

60ºS

60 10ºS

200

10ºS

80

80

80

0º

−2

50ºS

18

0º

16

E

0º

14

E

E

0º

0º

12

10

ºE

ºE

80

60

10ºN

220

2

120 50ºS

240 0º

8

180 30ºS

260

10ºN

14

−1.5

50ºS

−2 −2.5

60ºS

40ºS 50ºS 60ºS ºE

ºE

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º

10

80

60

0º 18 E 0º 16 E 0º 14 E 0º 12 E 0º 10

ºE

ºE

60

80

E

0º

18

E

0º

16

E

0º

14

E

0º

0º

12

ºE

10

ºE

80

60

Colour Figure 7 (Poloczanska et al.) Simulated annual means of downward solar radiation at the ocean surface (W/m2) (left), precipitation minus evaporation (mm/d) (middle), and sea-level height anomaly due to upper ocean stratification relative to 2000 m (cm) (right). Top row: 1990s, bottom row: difference between 1990s and 2070s.

50931_C009.fm Page 556 Tuesday, May 1, 2007 6:09 PM

Present

TEMPE

TROPIC

RATE

Future

TEMPE

AL

TROPIC

AL

RATE

beach

island

turtle – female

tropical fish

tropical coral

tropical mangroves

kelp forest

turtle – male

temperate fish

bleached coral

tropical seagrass

dugong

jellyfish

carbonate rock

calcifying plankton

Colour Figure 9 (Poloczanska et al.) Hypothetical Southern Hemisphere marine coastline and coastal waters ranging from low latitudes in the north to high latitudes in the south under present climate (top) and in the future under global warming scenario (bottom). As temperatures rise, species’ distributions shift further south. The range of tropical and subtropical species extends to temperate latitudes while temperate species in the south decline. Rising temperatures and ocean acidification stress coral reefs leading to frequent coral bleaching and an increase in mortality while rapid sea level rise inundates the coral reefs. Ocean acidification also leads to the decline of calcifying plankton such as pteropods and coccolithophores. Rising sea-level encroaches on the mainland and on offshore islands. The sex ratio of marine turtle hatchlings, which is determined by ambient nest temperatures, is skewed in the future as warming produces more females.

50931_Idx1.fm Page 479 Thursday, May 10, 2007 8:34 PM

AUTHOR INDEX References to complete articles are given in bold type, references to bibliographic lists are in regular type.

A

Aguilar, R. See Guerra, C., 318 See Luna-Jorquera, G., 325 Aguilar-Rosas, L.E., 74 Aguilar-Rosas, R. See Aguilar-Rosas, L.E., 74 Aguilera, C. See Martínez, G., 326 Aguirre, G. See Sielfeld, W., 337 Ahas, R. See Menzel, A., 469 See Schwartz, M.D., 473 Ahrens, M. See Lohrer, A.M., 467 Ahumada, R., 305 See Bernal, P.A., 307 See González, H.E., 317 Aiken, C., 305 Ainsworth, E.A., 453 Airamè, S., 393 Airoldi, L., 345–405, 393, 394 See Bacchiocchi, F., 394 See Benedetti-Cecchi, L., 395 See Bulleri, F., 396 See Moschella, P.S., 402 Akaboshi, S. See Illanes, J.E., 321 Akano, T. See Gao, K., 461 Akin, T.B. See Mattison, J.E., 83 Aksnes, D.L. See Kaartvedt, S., 131 Alarcón, E., 305 See Wolff, M., 344 Alarcón, G. See Montecino, V., 327 Alarcón, R. See Acuña, E., 304 Albaina, A. See Bonnet, D., 455 Alberte, R.S. See Zimmerman, R.C., 477 Albertsson, J., 124 Albrecht, A. See Schories, D., 403 Alcalde, O. See Neill, P.E., 329 Alcock, A., 190 Alder, J. See Agardy, T., 393 Alderete, W. See Majluf, P., 325 Alexander, S. See Roughgarden, J., 333 Alheit, J., 305 Aliaga, B. See Bernal, P.A., 307 Allan, R., 190 Allee, W.C., 166 Allen, D.M., 125 See Johnson, W.S., 130 Allen, H.D., 394 Allen, J.A., 166 See Rex, M.A., 170 Allen, J.H. See Connor, D.W., 396 Allen, J.R.L., 394 Allison, G., Russell, R., 171 Alm, M.B. See Hutchins, D.A., 321 Alm-Kübler, K. See Menzel, A., 469 Aloia, A. See Colombini, I., 311 Alongi, D.M., 394, 453 Alonso Vega, J.M. See Thiel, M., 199–344

Aadnesen, A. See Kaartvedt, S., 131 Aasa, A. See Menzel, A., 469 See Schwartz, M.D., 473 Aaser, H., 124 Abal, E.G., 453 See Carruthers, T.J.B., 457 Abarca, A. See Uriarte, I., 340 See von Brand, E., 343 Abbiati, M. See Airoldi, L., 394 See Moschella, P.S., 402 Abbott, I.A., 74 Abello, H.U., 124 See Taylor, L.H., 137 Aberg, P. See Jonsson, P.R., 465 See Airoldi, L., 394 See Moschella, P.S., 402 Able, K.W. See Beck, M.W., 394 See Nemerson, D.M., 133 Abraham, E.R. See Boyd, P.W., 456 Abreu-Grobois, F.A. See Bowen, B.W., 455 Aburto, J., 304 See Stotz, W., 338 Aburto-Oropeza, O. See Sala, E., 334 Aceves, H. See Langdon, C., 466 Acha, E.M. See Schiariti, A., 135 Acuña, E., 304, 305 See Arancibia, H., 305 See Castilla, J.C., 310 See Sielfeld, W., 336 See Thiel, M., 199–344 Acuña, E.H. See Villarroel, J.C., 343 Acunto, S. See Piazzi, L., 403 Adam, P., 393 Adami, M.L., 74 Adams, D.C. See Rosenberg, M.S., 171 Ades, P.K. See Keatley, M.R., 465 Adey, W.H., 453 Adkins, J. See Thresher, R., 474 Adnan, N.A. See Loneragan, N.R., 467 Adnyana, W., 453 Aedo, D. See Santelices, B., 85 See Santelices, B., 334, 335 Aerts, J. See Kabat, P.W., 400 Aerts, K. See Engel, A., 460 Afanasyev, V. See Phillips, R.A., 332 Agardy, T., 393 Agegian, C.R. See Cowen, R.K., 76 Aguayo, A. See Sielfeld, W., 336 Aguilar, A., 305 Aguilar, M., 305 See González, S.A., 318

479

50931_Idx1.fm Page 480 Thursday, May 10, 2007 8:34 PM

AUTHOR INDEX Alpers, W., 190 Althaus, F. See Williams, A., 476 Altizer, S. See Harvell, C.D., 463 Alvarado, J.L., 305 See Castilla, J.C., 310 Alvarez, E. See Diaz-Almela, E., 458 Alveal, K., 305 Amado, N. See Sielfeld, W., 336 Amakasu, K., 125 Amann, R. See Kuypers, M.M., 323 Amarasekare, P. See Leibold, M.A., 323 See Micheli, F., 327 Ambarsari, I. See Brown, B.E., 191 Ambrose, R.F. See Smith, J.R., 473 Amoureux, L. See Cornet, M., 127 Amsler, C.D., 74 See Reed, D.C., 85, 333 An, Z.S. See Jickells, T.D., 465 Anandrai, A. See Perissinotto, R., 134 Andelman, S. See Leslie, H., 324, 400 See Lubchenco J., 169 See Meir, E., 327 See Possingham, H., 403 Andelman, S.J., 166 Andersen, K.K. See Jickells, T.D., 465 Andersen, R.A. See Coyer, J.A., 76 Anderson, A.N., 166 Anderson, B.S., 74 Anderson, D.M. See Moy, C.M., 329 Anderson, E.K., 74 Anderson, J.M. See Moschella, P.S., 402 Anderson, R.J. See Stegenga, H., 86 Anderson, T.W., 74 See Reed, D.C., 85 Andersson, A. See Jonzén, N., 465 Andrade, M.J. See Acuña, E., 305 See Villarroel, J.C., 343 Andrade, Y.N. See Camus, P.A., 309 Andrew, N.L., 453 See Schiel, D.R., 86 Andrews, J.C. See Sammarco, P.W., 473 Andrews, N. See Thresher, R.E., 474 Andrews, N.L., 74 Angel, A., 305 Anggoro A.W. See Baird, A.H., 190 Anghera, M. See Reed, D.C., 85 Anraku, M. See Clutter, R.I., 126 Ansaloni, I. See Simonini, R., 404 Antezana, T., 125, 305 See Hückstädt, L.A., 320 Anthony, E.J., 394 Anthony, K.R.N., 190 Antia, A.N., 454 Antoine, D. See Morel, A., 35 Antolic, B. See Meinesz, A., 401 Antonov, J.I. See Conkright, M.E., 311 Apel, M., 125

Apostolaki, E.T. See Karakassis, I., 169 Arana, P., 305 See Palma, S., 331 Arancibia, A. See Acuña, E., 304 Arancibia, H., 305 See Medina, M., 326 See Moloney, C.L., 327 See Neira, S., 330 Araneda, A. See Escribano, R., 314 Araneda, S.E. See Vargas, C.A., 341 Arata, J., 305 See Báez, P., 306 See Moreno, C.A., 328 Araya, B. See Simeone, A., 337 Araya, M. See Medina, M., 326 Archaux, F., 454 Archer, D. See Kleypas, J.A., 466 Arcos, D. See Cáceres, M., 309 See Letelier, J., 324 Arcos, D.F. 305 See Cubillos, L.A., 312 See Peterson, W.T., 331 See Vargas, C.A., 341 Ardiwijaya, R.L. See Baird, A.H., 190 Argua, Y. See Gao, K., 461 Ariani, A.P., 125 See Wittman, K.J., 138 Arias, A.M. See Drake, P., 128 Arias-Gonzalez, J.E. See Mumby, P.J., 469 Arlhac, D. See Salen-Picard, C., 334 Armstrong, R.A. See Detres, Y., 458 Arnaud, J. See Brunet, M., 126 Arnold, K.E., 74 Arntz, W., 305, 306 See Brante, A., 308 See Fernández, M., 316 See Palma, M., 331 See Rosenberg, R., 333 See Thiel, M., 199–344 Arntz, W.E., 306 See Peña T.S., 331 See Tarazona, J., 339 Aro, E. See Flinkman, J., 128 Aron, A. See Villegas, A., 343 Aronson, R.B., 125 Arriaza, B.T. See Santoro, C.M., 335 Arsenault, D.J., 454 Artemyev, A.V. See Both, C., 455 Aruga, Y. See Gao, K.S., 461 Asada, K. See Gao, K., 461 Asano, E., 33 Asencio, G. See Duarte, W.E., 313 See Moreno, C.A., 328 Asensi, A., 74 Ashjian, C.J. See Lawson, G.L., 132 Asmus, H. See Asmus, R.M., 306 Asmus, R.M., 306

480

50931_Idx1.fm Page 481 Thursday, May 10, 2007 8:34 PM

AUTHOR INDEX Badalamenti, F., 394 See Milazzo, M., 402 Baden, S., 394 See Pihl, L., 403 Baden, S.P. See Boström, C., 395 Badola, R., 454 Báez, P., 306 Baeza, J.A., 306 See Fernández, M., 316 Bagley, D.A. See Weishampel, J.F., 476 Bahamonde, N. See Castilla, J.C., 310 Bahamondes, I. See Castilla, J.C., 76 Bainbridge, R., 125 Baird, A.H., 190 See Hughes, T.P., 464 Bairlein, F. See Walther, G.R., 476 Bais, A. See McKenzie, R.L., 468 Bak, R.P.M., 190 Baker, A.C. See Drohan, A.F., 459 Baker, A.R. See Jickells, T.D., 465 Baker, K. See Smith, R., 474 Bakker, D.C.E. See Boyd, P.W., 456 Bakker, J.P. See Wolters, M., 405 Bakker, T.C.M. See Modarressie, R., 469 Bakun, A., 306 See Cury, P., 312 See Weeks, S.J., 343 Balanda, M.J. See Thiel, M., 339 Balazs, G.H. See Bowen, B.W., 455 See Polovina, J.J., 471 Balbontín, F., 306 Baldó, F. See Drake, P., 128 Baldwin, R. See Kaufmann, R.S., 131 Balech, E., 307 Balestri, E. See Diaz-Almela, E., 458 Ball, B.J., 394 Ball, I. See Leslie, H., 400 See Possingham, H., 403 Ball, I.R. See Leslie, H., 324 Ballesteros, E., 394 See Boudouresque, C.F., 395 See Delgado, O., 396 See Thibaut, T., 404 Balmford, A., 307, 394 Baltazar, M. See Gallardo, V.A., 316 See Gutiérrez, D., 319 See Roa, R., 333 Bamber, R.N., 125 Bancroft, W.J., 454 Bando, T. See Sato, K., 473 Bannon, S.M. See MacLeod, C.D., 468 Barange M. See Porteiro C., 471 Barber, P.W. See Geller, P.E., 34 Barber, R. See Sarmiento, J.L., 473 Barber, R.T., 125 See Codispoti, L.A., 311 Barbera, C., 394

Asprey, K.W. See Syvitski, J.P.M., 36 Astier, J.M. See Meinesz, A., 401 Astill, K. See Booth, D.T., 455 Astoreca, R. See Montecino, V., 327 Astorga, A., 306 Astorga, M. See Galleguillos, R., 316 Astthorsson, O.S., 125 Atkinson, L. See Yannicelli, B., 344 Atkinson, L.P., 306 Atkinson, M.J. See Langdon, C., 466 Atkinson, R.J.A. See Hall-Spencer, J.M., 399 Attramadai, Y.G., 125 Attrill, M.J., 166 See Foggo, A., 167 Attwood, C.G., 74 Au, W.W.L. See Benoit-Bird, K.J., 125 Audzijonyte, A., 125 Augenstein, E.W., 74 Aumont, O. See Bopp, L., 455 See Orr, J.C., 470 Aure, J. See Erga, S.R., 460 Aursland, K. See Erga, S.R., 460 Austen, M.C., 166 See Widdicombe, S., 172 Australia Bureau of Statistics, 454 Australian Greenhouse Office, 454 Autio, H. See Kangas, P., 400 Auyang, S.Y., 125 Avaria S., 306 Avellanal, M.H. See Jaramillo, E., 321, 322 Avendaño, M., 306 See Moragat, D., 328 Avila, M., 75, 306 See Correa, J.A., 312 See Hoffmann, A.J., 81, 320 Aviléz, O., 306 Avishai, N. See Baruch, R., 454 Axelsson, L. See Lundälv, T., 401 Aydin, K., 33 Ayukai, T. See McKinnon, A.D., 468 Azeiteiro, U.M.M., 125 Azuma, N. See Takahashi, K., 136

B Baardseth, E., 75 Baba, J., 33 Babcock, E.A. See Majluf, P., 325 Babcock, R., 454 Babcock, R.C. See Cole, R.G., 457 See Poloczanska, E.S., 407–478, 454 See Shears, N.T., 336 See Oliver, J., 470 Bacchiocchi, F., 394 See Moschella, P.S., 402 Bacescu, M., 125 Bach, C.S., 454

481

50931_Idx1.fm Page 482 Thursday, May 10, 2007 8:34 PM

AUTHOR INDEX Barbieri, E.S., 454 Barbieri, M. See Yáñez, E., 344 Barbieri, M.A. See Bertrand, A., 307 See Silva, C., 337 See Yáñez, E., 344 Barilotti, D.C., 75 Barker, D. See Procter, T.D., 35 Barker, N.P. See Teske, P.R., 339 Barmawidjaja, D., 394 Barnabe, G., 394 Barnard, A.H. See Twardowski, M.S., 36 Barnes, D.J. See Lough, J.M., 192 See Lough, J.M., 467 See McNeil, B.I., 469 Barnes, J.H., 454 Barnett, H. See Langdon, C., 466 Baron, J. See Moragat, D., 328 Baron, N. See Pandolfi, J.M., 470 Barr, N. See Wing, B.L., 138 Barrales, H.L., 75 Barrera, J.C. See Sala, E., 334 Barreto, R. See Godfrey, M.H., 461 Barrett, N.S., 397 See Edgar, G.J., 459 Barria, I. See Lagos, N., 323 Barry, J.P., 454 See Sagarin, R.D., 472 Barry, T.M. See Lesser, M.P., 467 Barth, J.A. See Grantham, B.A., 318 Bartlett, K.P. See Kunze, E., 131 Barton, E.D. See Hill, A.E., 320 Bartsch, I., 394 Baruch, R., 454 Bascompte, J. See Micheli, F., 327 Bass, A. See Mrosovsky, N., 469 Basterretxea, G. See Marbà, N., 401 Bastias, H. See Thiel, M., 199–344 Bastreri, D. See Calliari, D., 126 Bathmann, U. See Antia, A.N., 454 Battisti, D.S. See Zhang, Y., 344 Baumgartner, T. See Montecino, V., 327 Baumgartner, T.R. See Halpin, P.M., 319 Baums, I.B., 307 Bavestrello, G., 394 See Cicogna, F., 396 Baxter, C.H. See Barry, J.P., 454 See Sagarin, R.D., 472 Baxter, J. See Mieszkowska, N., 469 Beamish, R.J., 454 See Burkett, V., 456 Beardall, J., 454 Beardsley, G.F. See Carder, K.L., 33 Beare, D.J., 454 Beaudouin, J., 125 Beaufort, L. See Engel, A., 460 Beaugrand, G., 454 See Bonnet, D., 455 See Kirby, R.R., 466 Beaumont, L.J., 454

Beauvais, L., 190 Beck, M.W., 307, 394, 395 See Airoldi, L., 345–405, 394 Becker, J., 307 Beckerman, A. See Votier, S.C., 475 Beckley, L.E., 75 Bedo, A.W. See Longhurst, A.R., 132 Beebee, T.J.C. See Walther, G.R., 476 Beer, S. See Beardall, J., 454 Behrenfeld, M., 455 Behrens, M.D., 75 Beker, J.B. See Connor, D.W., 396 Bell, A.M. See Duke, N.C., 459 Bell, S.S. See Fonseca, M.S., 460 Bellantoni, D. See Peterson, W.T., 331 Bellwood, D.R. See Hughes, T.P., 464 Belmonte, G. See Fanelli, G., 398 Belsher, T., 75 See Meinesz, A., 401 Bence, J.R. See Nisbet, R.M., 84 Benedetti-Cecchi, L., 395 Benkendorff, K. See Przeslawski, R., 471 Ben Maiz, N. See See Boudouresque, C.F., 395 Bennett, A.F. See MacNally, R., 169 Bennett, W.A. See Kimmerer, W.J., 131 Benninger, L.K. See Muñoz, P., 329 Benoit-Bird, K.J., 125 Benthien, A. See Engel, A., 460 Ben-Yosef, D.Z. See Wahl, M., 475 Berasategui, A.D. See Schiariti, A., 135 Bergametti, G. See Jickells, T.D., 465 Berge, J.A., 455 Berger, S. See Walther, G.R., 476 Berger, U. See Grimm, V., 129 Berger, W.H. See Jackson, J.B.C., 399 Berges, J. A. See Wilson, S., 405 Berghahn, R., 395 Berghe, E.V. See Costello, M.J., 167 Bergman, A. See Zhivotovsky, L.A., 138 Bergmann, T. See Boss, E., 33 Bergstrom, L. See Eriksson, B.K., 398 Berkelmans, R. See Done, T.J., 459 Berkenbusch, K. See Lohrer, A.M., 467 Berlow, E.L. See Menge, B.A., 327 Bernal, M., 307 See Simeone, A., 337 Bernal, P. See González, H.E., 317 See Iriarte, J.L., 321 See Llanos, A., 324 See Llanos-Rivera, A., 324 Bernal, P.A., 307 See Castro, L.R., 310 See González, H.E., 318 Bernard, S. See Quirantes, A., 36 Bernardes, C. See Cunha, M.R., 127 Bernhard, J.M. See Gooday, A.J., 318 Bernhard, M. See Jeftic, L., 400 Bernstein, B.L., 75 Berríos, V. See Sielfeld, W., 337

482

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AUTHOR INDEX Bertasi, F. See Martin, D., 401 Bertignac, M. See Lehodey, P., 467 Bertness, M.D. See Wolters, M., 405 Bertrán, C. See Jaramillo, E., 322 Bertrand, A., 307 Bertrand, N. See Winkler, G., 138 Bertrand, Y., 166 Bestley, S. See Polacheck, T., 471 Betts, H. See Walsh, K.J.E., 476 Betzer, P.R. See Carder, K.L., 33 Beucher, M. See Asensi, A., 74 Beukema, J.J. See Philippart, C.J.M., 470 Beveridge, I. See Kunze, E., 131 Beyst, B., 125 Bhargava, R.M.S. See Desai, B.N., 191 Bhattacharya, D. See Yoon, H.S., 88 Bi, D. See Cai, W., 456 Bianchi, C.N., 395 See Sandulli, R., 403 Bickmore, B.R., 33 Bida, J. See Wilhelm, C., 476 Bilham, R., 191 Billot, C. See Faugeron, S., 315 Binckley, C.A., 455 Bird, E.C.F., 395 Bird, J., 307 Birkett, D.A., 395 Birkhead, T.R. See Votier, S.C., 475 Birklund, J. See van Dalfsen, J. A., 405 Birowo, A.T. See Soegiarto, A., 194 Bischof, K., 307, 455 See Wiencke, C., 476 Bishop, J.D.D. See Gage, J., Bissolli, P. See Menzel, A., 469 Bjerkeng, B. See Berge, J.A., 455 Bjørgesæter, A. See Gray, J.S., 168 Bjorn, L.O. See Madronich, S., 325 See McKenzie, R.L., 468 Bjorndal, K.A. See Jackson, J.B.C., 399 See Pandolfi, J.M., 402 See Solow, A.R., 474 Bjornsen, P.K. See Nielsen, T.G., 192 Blaauw, B. See Both, C., 455 Black, K.P. See McShane, P.E., 469 Blackall, L.L. See Jones, R.J., 465 Blackburn, S., 455 Blackburn, S.I., 455 Blackwell, B., 455 Blackwell, P.G. See Mumby, P.J., 469 Blain, S.P. See Coale, K.H., 311 Blair, D., See Adnyana, W., 453 Blake, C. See Wilson, S., 405 Blanchette, C.A., 75 See Menge, B.A., 327 Blanco, J.L., 307 See Atkinson, L.P., 306 See Carr, M.E., 309 See Castro, L.R., 311 See Escribano, R., 315

See Morales, C.E., 328 See Thomas, A.C., 339 See Uribe, E., 340 See Valle-Levinson, A., 341 Blanco, M. See Edding, M., 313 Blanz, T. See Antia, A.N., 454 Blasco, F., 455 Bleakley, C. See Kelleher, G., 400 Bloomfield, A.L., 455 Boaden, P.J.S. See Birkett, D.A., 395 Bobadilla, M., 307 See Santelices, B., 85 Bodini, A. See Acuña, E., 305 Boehlert, G.W. See Koslow, J.A., 466 Boer, G.J. See Cubasch, U., 458 Gregory, J.M., 462 Boero, F. See Fanelli, G., 398 See Guidetti, P., 398 See Marcus, N.H., 325 Boersma, D., 307 Boesch, D.F. See Rhoads, D.C., 471 Boghen, A.D. See St-Hilaire, A., 136 Bogucki, D. See Stramski, D., 36 Bohm, G. See Yáñez, E., 344 Bohren, C.F., 33 Boisset, F. See Boudouresque, C.F., 395 Bokn, T.L., 395 Boland, J.W. See McArthur, L.C., 468 Boland, W. See Maier, I., 83 Bollens, S.M., 455 See Brown, H., 126 See Dean, A.F., 127 Boltaña, S. See Hinojosa, I., 320 See Macaya, E.C., 83, 325 Bolten, A.B. See Solow, A.R., 474 Bolton, J.J., 455 See Stegenga, H., 86 Boltovskoy, E., 307 Bolvaran, A. See Sielfeld, W., 336 Bombace, G., 395 Bomkamp, R.E., 307 Bonaventura, R., 455 Bondesan, M., 395 Boni, L. See Carlsson, P., 456 Bonnet, D., 455 Bonsdorff, E. See Karlson, K., 400 Bonvicini Pagliai, A.M. See Simonini, R., 404 Boo, S.M. See Yoon, H.S., 88 Boonruang, P. See Nielsen, T.G., 192 Boonyanate, P. See Chansang, H., 191 Boorman, L.A., 395 Booth, D.T., 455 Bopp, L., 455 See Orr, J.C., 470 See Sarmiento, J.L., 473 Borcard, D. See Legendre, P., 169 Bordehore, C. See Barbera, C., 394 Borg, J.A. See Barbera, C., 394 Bortman, M.L. See Beck, M.W., 395

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AUTHOR INDEX Bortolus, A. See Orensanz, J.M., 134 Bos, O.G. See Philippart, C.J.M., 470 Boschi, E.E. See Astorga, A., 306 Boss, E., 33 See Clavano, W.R., 1–38 See Roesler, C.S., 36 See Stramski, D., 36 See Twardowski, M.S., 36 Boström, C., 395 See Worm, B., 405 Both, C., 455 Botsford, L.W., 307 See Jackson, J.B.C., 399 See Lockwood, D.R., 324 See Wing, S.R., 88, 343 Böttjer, D., 307 Botto-Mahan, C. See Ebensperger, L.A., 78, 313 Boucher, G. See Lambshead, P.J.D, 169 Bouchet, J.-M. See Cornet, M., 127 Bouchet, P. See Costello, M.J., 167 See Rex, M.A., 170 Boudouresque, C.F., 395 See Meinesz, A., 401 Boudreau, B.P., 126 Boulding, E.G., 455 Boulter, S.L., 455 Bourdeau, P. See Stanners, D., 404 Bourge, I. See Gattuso, J.P., 461 Bourget, E. See Le Fèvre, J., 323 Bourgois, T. See Remerie, T., 134 Bourque, B.J. See Jackson, J.B.C., 399 See Lotze, H.K., 401, See Steneck, R.S., 86, 404, 474 Bowden, K.F., 307 Bowen, B.W., 455 Bowen, J.L. See Valiela, I., 405 Bowen, P. See Abal, E.G., 453 Bowie, A.R. See Boyd, P.W., 456 Bowman, D.M.J.S., 456 Bowman, T.E. See Williams, A.B., 138 Bowyer, J. See Jones, R.J., 465 Boyd, P.W., 456 See Jickells, T.D., 465 See Sedwick, P.N., 473 Boyer, T.P. See Conkright, M.E., 311 Bozec, Y.M. See Moloney, C.L., 327 Bozinovic, F. See Pulgar, J.M., 332 Bozzano, A., 126 Bracher, D. See Farrell, T.M., 315 Bracken, M.E.S. See Menge, B.A., 327 Bradbury, R.H. See Jackson, J.B.C., 399 See Lotze, H.K., 401 See Pandolfi, J.M., 402, 470 Brainard, R.E. See Benoit-Bird, K.J., 125 Braje, T.J. See Erlandson, J.M., 78 Branch, G. See Boersma, D., 307 See Roberts, C.M., 333 Branch, G.M. See Beckley, L.E., 75 See Bustamante, R.H., 75, 308

Brand, L.E., 456 Brandhorst, W., 307 Brandon M.A. See Brierley A.S., 126 Brandt, A., 126 Branstrator, D.K., 126 Brante, A., 308 See Fernández, M., 315 Braslavska, O. See Menzel, A., 469 Brattegard, T., 126 See Fosså, J.H., 129 Brattstöm, H., 308 Braun, M. See Escribano, R., 314 See Morales, C.E., 328 Bravo, L. See Fuenzalida, R., 316 See Ramos, M., 333 Brawley, S.H., 456 See Serrão, E.A., 473 Bray, M.J., 395 Bray, R.N., 75 Brearley, A. See Jernakoff, P., 465 Breck, E. See Leslie, H., 324 Breeman, A.M. See Peters, A.F., 331 Breen, P.A. See Druehl, L.D., 77 Bregman, A. See Kelfkens, G., 465 465 Breslin, V.T. See Song, K.-H., 136 Brey, L. See Bischof, K., 307 Brey, T., 308 See Arntz W.E., 306 Bricaud, A., 33 See Morel, A., 35 See Stramski, D., 36 Briede, A. See Menzel, A., 469 Brierley A.S., 126 Brinch, C. See Jonzén, N., 465 Brink, K.H. See Hill, A.E., 320 Brink, L. See Shanks, A.L., 86 Briones, L., 308 Britton-Simmons, K. See Klinger, T., 322 Broccoli, A.J. See Rosenthal, Y., 85 Brochier, T. See Guizien, K., 318 Broderick, A.C., 456 See Hays, G.C., 463 Brodie, J., 456 See Devlin, M.J., 458 Broitman, B. See Navarrete, S.A., 329 Broitman, B.R., 75, 308 See Blanchette, C.A., 75 See Halpern, B.S., 80 See Navarrete, S.A., 329 Brokordt, K. See Martínez, G., 326 See Thiel, M., 199–344 Brokordt, K.B., 308 Brooks, N. See Jickells, T.D., 465 Brooks, T.M., 395 Brostoff, W.N., 75 Brothers, N. See Bunce, A., 456 See Ross, G.J.B., 472 Browman, H.I., 395 See Kouwenberg, J.H.M., 466

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AUTHOR INDEX Brown, A.C., 395 Brown, B.E., 173–194, 191 See Clarke, K.R., 191 See Dunne, R.P., 191 See Satapoomin, U., 193 See Scoffin, T.P., 193 Brown, G.W. See MacNally, R., 169 Brown, H., 126 Brown, J.H., 308 Brown, M.T., 75 See Chin, N.K.M., 76 See Correa, J.A., 312 See Nyman, M.A., 84 Brubaker, J. See Shanks, A.L., 86 Bruce, B.D. See Thresher, R.E., Bruhn, J., 456 Bruland, K.W. See Hutchins, D.A., 321 Brumbaugh, D.R. See Harborne, A.R., 463 Brunel, P., 126 Brunet, M., 126 Brunsting, A. See Latimer, P., 35 Brzezinski, M.A. See Reed, D.C., 85 Bucarey, D.A. See Cubillos, L.A., 312 Buchanan, J.B., 126 See Frid, C.L., 316 Buddemeier, R.W., 191 See Gattuso, J.P., 461 See Kleypas, J.A., 466 Buesseler, K.O. See Boyd, P.W., 456 Buhl-Jensen, L., 126 Bukantis, R.T. See Spencer, C.N., 136 Bulboa, C.R., 308 See Macchiavello, J., 325 Bull, G.D. See Babcock, R.C., 454 Bulleri, F., 396 See Benedetti-Cecchi, L., 395 See Moschella, P.S., 402 Bullister, J.L. See McNeil, B.I., 469 Bunce, A., 456 Bunge, J., 166 Burau, J.R. See Kimmerer, W.J., 131 Burbidge, A.A. See Ross, G.J.B., 472 Burch, T.L. See Osborne, A.R., 192 Burd, F. See Cooper, N.J., 396 Burford, M.A. See McKinnon, A.D., 468 Burger, R.L. See Sandweiss, D.H., 334 Burgman, M.A., 75 Burke, L., 396 Burkett, V., 456 Burkholder, J.M. See Harvell, C.D., 463 Burnett, W.J., 191 Burns, B.R. See Wigley, R.L., 138 Burns, C.W. See Wilhelm, F.M., 138 Burns, F. See Beare, D.J., 454 Burns, J.J. See Lowry, L.F., 132 Burrell, V.G., Jr. See Mackenzie, C.L., Jr, 401 Burrows, M.T. See Emsley, S.M., 128 See Kendall, M.A., 465

See Mieszkowska, N., 469 See Southward, A.J., 474 Burt, M.D.B. See Jackson, C.J., 130 Burton, H. See Lake, S., 132 Burton, R.S., 308 Busch, M. See Lotze, H.K., 401 Buschmann, A.H., 75, 308 See Gutierrez, A., 80 See Castilla, J.C., 310 See Chopin, T., 311 See Graham, M.H., 39–88, 318 See Gutierrez, A., 319 See Macaya, E.C., 83, 325 See Munoz, V., 83, 329 See Vásquez, J.A., 87, 341, 342 See Vega, J.M.A., 88, 342 Bustamante, R.H., 75, 308 See Boersma, D., 307 See Roberts, C.M., 333 Bustos, C. See Landaeta, M.F., 323 Butler, A. See Poloczanska, E.S., 407–478 Butler, A.J. See Davis, A.R., 458 See Keough, M.J., 466 Butman, C.A., 308 Buttino, I. See Ianora, A., 321 Button, D.K. See Druehl, L.D., 78 Buysse, D. See Beyst, B., 125 Buzas, M.A., 166 See Culver, S.J., 167 See Hayek, L.C., 168 Byers, J.E., 308 Byrkjedal, I., 456 Byrnes, J., 75

C Cabrera, D. See Tovar, H., 340 Cáceres, C. See Gutierrez, A., 80, 319 Cáceres, H., 309 Cáceres, M., 309 Caceres-Rubio, C.F. See Aguilar-Rosas, L.E., 74 Cadee, G.C. See Philippart, C.J.M., 470 Cai, W., 456 Caillaux, L. See Stotz, W., 338 Caillaux, L.M., 309 Cailliau, C. See Garde, K., 461 Cairns, S. See Guinotte, J.M., 462 Caldeira, K., 456 See Raven, J., 471 Calderon, J. See Rutllant, J.A., 334 Calderon, R. See Fernández, M., 315 Caldwell, M. See Madronich, S., 325 Calliari, D., 126 See Rodríguez-Graña, L., 333 Calvert, S.E. See Cowie, G.L., 312 Cambridge, M.L., 456 Camousseight, A. See Castro, S.A., 311 Campbell, D. See Lyle, J.M., 468

485

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AUTHOR INDEX Campbell, R.A., 456 Campbell, S.J., 456 See Baird, A.H., 190 Camus, P. See Thiel, M., 199–344 Camus, P.A., 75, 309 See Ahumada, R., 305 See Castilla, J.C., 310 See Vásquez, J.A., 87, 341 Canahuire, E. See Tarazona, J., 339 Canales, M.T. See Cubillos, L.A., 312 Cancino, J. See Santelices, B., 335 Cancino, J.M. See Gajardo, G., 316 See Paine, R.T., 330 See Sepúlveda, R., 336 Candia, M. See Ortlieb, L., 330 Cane, M.A., 309 Cañete, J.I. See Gallardo, V.A., 316 See Roa, R., 333 Canfield, D.E. See Fossing, H., 316 Cano, A. See Sandweiss, D.H., 334 Cano, J., 396 CansemiSoullard, M. See Delille, D., 313 Cantillánez, M. See Avendaño, M., 306 Cantlon, J.E. See Odum, H.T., 170 Canty, P. See Ross, G.J.B., 472 Cao, J.J. See Jickells, T.D., 465 Capella, J., 309 Capobianco, M. See Hamm, L., 399 Caputi, N., 456 See Griffin, D.A., 462 Caraco, N. See Duarte, C.M., 459 Caragitsou, E. See Papaconstantinou, C., 134 Carbajal, G. See Rosenberg, R., 333 Carcelles, A., 309 Card, M. See Hughes, T.P., 464 Cárdenas, L., 309 See Martínez, E.A., 326 See Poulin, E., 332 Carder, K.L., 33 Caressa, S., 396 Carlotti, F. See Bonnet, D., 455 See Miller, C.B., 133 Carlson, B.E. See Macke, A., 35 Carlsson, P., 456 Carlton, J.H., 126 Carney, R.S., 139–172, 166 Caro, A.U. See Castilla, J.C., 310 Carola, M., 126 See Coma, R., 126 Carotenuto, Y. See Ianora, A., 321 Carpenter, R.C. See Stewart, H.L., 474 Carr, A., 457 See Mulkins, L.M., 133 Carr, J.J. See Hannah, L., 399 Carr, M.E., 309 See Blanco, J.L., 307 See Thomas, A.C., 339 Carr, M.H., 75, 76 See Graham, M.H., 79

See Holbrook, S.J., 81 See Shanks, A.L., 336 Carr, M.R. See Olsgard, F., 170 See Somerfield, P.J., 171 Carrasco, F. See Gutiérrez, D., 319 See Jaramillo, E., 322 Carrasco, F.D., 309 See Gallardo, V.A., 316 See Sepúlveda, R., 336 Carrasco, S., 309 Carreno, E. See Letelier, S., 324 Carrette, T. See Little, M., 467 Carrington, E. See Helmuth, B., 463 Carriquiry, J.D. See Takesue, R.K., 339 Carruthers, T.J.B., 457 Carter, J.H.C., 126 Carter, K. See Kleppel, G.S., 466 Cartes, C. See Palma, A.T., 331 See Vargas, C.A., 341 Cartes, J.E., 126 Cary, J. See Lemmens, J., 323 Casanova, B. See De Jong-Moreau, L., 127 Casanova, J.-P. See De Jong-Moreau, L., 127 Casas, G. See Orensanz, J.M., 134 Casas-Valdez, M.M. See Hernández-Carmona, G., 81 Caselle, J.E. See Swearer, S.E., 339 Casey, J. See O’Brien, C.M., 470 Casotti, R. See Ianora, A., 321 Castel, J., 126 Castiglioni, G.B. See Bondesan, M., 395 Castilla, A.C. See Prado, L., 332 Castilla, J.C., 76, 309, 310 See Aiken, C., 305 See Alvarado, J.L., 305 See Cerda, M., 311 See Clarke, M., 311 See Correa, J.A., 312 See Defeo, O., 313 See Durán, L.R., 313 See Ebensperger, L.A., 313 See Fariña, J.M., 315 See Fernández, M., 315 See Gelcich, S., 317 See Jerardino, A., 322 See Kaplan, D.M., 322 See Kelaher, B.P., 322 See Lagos, N.A., 323 See Lardies, M.A., 323 See Manríquez, P.H., 325 See Narváez, D.A., 329 See Navarrete, S.A., 329 See Paine, R.T., 330 See Piñones, A., 332 See Poulin, E., 332 See Roberts, C.M., 333 See Sánchez, M., 334 See Santelices, B., 335 See Sielfeld, W., 336 See Takesue, R.K., 339

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AUTHOR INDEX See Thiel, M., 199–344 See Vásquez, J.A., 87, 341 See Zacherl, D.C., 344 Castillo, J.G., 310 Castillo, M. See Aiken, C., 305 Castro, H. See Rodríguez, L., 333 Castro, L. See González, H.E., 317 See Grünewald A., 318 See Rodríguez-Graña, L., 333 Castro, L.R., 310, 311 See Hernández, E.H., 319 See Landaeta, M.F., 323 See Llanos-Rivera, A., 324 See Morales, C.E., 328 See Pavez, M.A., 331 See Rodríguez-Graña, L., 333 See Thiel, M., 199–344 See Vargas, C.A., 341 See Yannicelli, B., 344 Castro, S.A., 311 Caswell, H. See Pineda, J., 170 Catasti, V. See Yáñez, E., 344 Caton, A., 457 Catrilao, M. See González, J., 318 Cattaneo-Vietti, R. See Bavestrello, G., 394 See Cicogna, F., 396 Cattrijsse, A. See Dewicke, A., 128 See Hampel, H., 129 See Mees, J., 133 Cauchy, A.L., 34 Cauquil, E. See Hyder, P., 192 Cavallini, F. See Simonini, R., 404 Cayan, D.R. See McGowan, J.A., 468 468 See Venrick, E.L., 475 Ceballos, S. See Bonnet, D., 455 Cebrián, J. See Duarte, C.M., 459 See Hauxwell, J., 399 See Marbà, N., 401 Ceccherelli, G. 396 See Milazzo, M., 402 Ceccherelli, V.U. See Martin, D., 401 Cech, J.J., Jr. See Roessig, J.M., 472 Cencini, C., 396 Cerda, G. See Sielfeld, W., 336 Cerda, M., 311 See Castilla, J.C., 310 Cerrano, C. See Bavestrello, G., 394 Cervetto, G. See Calliari, D., 126 Ceschia, C. See Caressa, S., 396 Chacana, M. See Westermeier, R., 343 Chadwick, D.B. See Tegner, M.J., 87 Chaigneau, A., 311 Chakraborty, P.P. See Khan, P.K., 192 See Pal, T., 192 Chaloupka, M., 457 Chamberlain, Y.M., 76 Chambers, D. See Allan, R., 190 Chambers, L.E., 457 Chamot-Rooke, N. See Pubellier, M., 193

Champalbert, G., 126 Chan, B.K.K., 457 Chan, F. See Grantham, B.A., 318 See Leslie, H., 324 See Menge, B.A., 327 Chan, H.R. See Webster, P.J., 476 Chang, H. See Boyd, P.W., 456 Chang, J. See Colwell, R.K., 167 Chang Chew Hung. See Hesp, P.A., Chansang, H., 191 See Brown, B.E., 191 See Phongsuwan, N., 193 See Scoffin, T.P., 193 Chao, A., 166 Chaplin, G. See Makris, N.C., 132 Chapman, A.R.O., 76 Chappell, J. See Wolanski, E., 476 Chardy, P. See David, V., 127 Charette, M. See Boyd, P.W., 456 Chase, J.M. See Leibold, M.A., 323 Chavez, F. See Wang, H.J., 343 Chavez, F.P., 311, 457 See Montecino, V., 327 See Olivieri, R.A., 330 Checkley, D.M. See Jahncke, J., 321 Cheeney, R.F. See Scoffin, T.P., 193 Chelazzi, L. See Colombini, I., 311 Chemello, R. See Milazzo, M., 402 Chen, R. See Twilley, R.R., 475 Chen, Y.C. See Lee, K.K., 467 Cheng, D. See Harty, C., 463 Cherr, G.N. See Garman, G.D., 79 See Huovinen, P.J., 81 Chess, D.W., 126 Chess, J.R. See Hobson, E.S., 81 Chia, F.S. See Hurd, C.L., 81 Chiaverini, D. See Meinesz, A., 401 Childers, D.L. See Beck, M.W., 394 Chin, N.K.M., 76 See Brown, M.T., 75 Chipman, D. See Langdon, C., 466 Chisholm, J.R.M. See Jaubert, J.M., 400 Chisholm, S.W. See Moore, L.R., 469 Chisolm P. See Kaufman L., 322 Chmielewski, F.M. See Menzel, A., 469 Choi, J.S., 126 See Frank, K.T., 129 Chong, J., 311 Choo, K.S., 457 Chopin, T., 311 Choquet, R. See Rivalan, P., 472 Chou, L. See Engel, A., 460 Chou Loke Ming. See Hesp, P.A., Chouinard, G.A. See Hanson, J.M., 130 Christensen, J.P. See Codispoti, L.A., 311 Christianen, M.J.A. See Dorenbosch, M., 459 Christie, H., 396 Chu, D. See Lawson, G.L., 132 Chubb, C. See Caputi, N., 456

487

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AUTHOR INDEX Coles, R.G. See Preen, A.R., 471 Coley, T.L. See Coale, K.H., 311 Collantes, G., 311 Collier, M.A. See Gordon, H.B., 462 Collins, A.G. See Castilla, J.C., 310 Collins, J.D. See Druehl, L.D., 77 Colman, J.S., 126 See Russell, F.S., 472 Coloma, C., 311 See Marchant, M., 325 Colombini, I., 311 Colucci-D’Amato, L. See Ianora, A., 321 Colwell, R.K., 167 See Gotelli, N.J., 168 Colwell, R.R. See Harvell, C.D., 463 Coma, R., 126 See Carola, M., 126 See Ribes, M., 134 Compagna, C. See Boersma, D., 307 CONAMA-PNUD, 311 Condie, S.A. See Ridgway, K.R., 472 Conkright, M.E., 311 Conn, J. See Hutchins, D.A., 321 Connell, J.H. See Hughes, T.P., 464 See Tutschulte, T.C., 87 Connell, S.D., 396 See Fowler-Walker, M.J., 460 See Gorgula, S.K., 462 Connelly, X.M. See Detres, Y., 458 Connolly, R.M. See Loneragan, N.R., 467 See Seddon, S., 473 Connolly, S.R., 167, 311 See Hughes, T.P., 464 Connor, D.W., 396 Conover, R.J., 127 Conte, M. See Antia, A.N., 454 Contreras, H., 312 See Duarte, C., 313 See Dugan, J.E., 313 See Jaramillo, E., 322 See Quijón, P., 332 Contreras, M. See Simeone, A., 337 Convey, E. See Walther, G.R., 476 Cook, K. See Bonnet, D., 455 Cooke, R. See Jackson, J.B.C., 399 Cooke, R.G. See Lotze, H.K., 401 See Pandolfi, J.M., 402 Cooper, N.J., 396 Cooper, T. See Cooper, N.J., 396 Corbert, A.S. See Fisher, A.A., 167 Corbett, D. See Steneck, R.S., 86 See Steneck, R.S., 404, 474 Cordell, J. See Dean, A.F., 127 Cordi, B., 457 Córdova, C. See Fernández, E., 315 Cordova, J. See Bertrand, A., 307 Corkeron, P.J. See Marsh, H., 468 Corliss, L.A. See Mrosovsky, N., 469

Chubb, C.F. See Griffin, D.A., 462 Chumán de Flores, E. See Rosenberg, R., 333 Church, J. See Walsh, K.J.E., 476 Church, J.A., 457 See Gregory, J.M., 462 Ch´ylek, P., 34 Cicogna, F., 396 See Russo, G.F., 403 Cid, L. See Acuña, E., 304 Cifuentes, M. See Fernández, M., 315, 316 Cifuentes, S. See Brante, A., 308 Cimino, J. See Pruett, L., 403 Cinelli, F. See Benedetti-Cecchi, L., 395 See Boudouresque, C.F., 395 See Ceccherelli, G. 396 See Meinesz, A., 401 See Piazzi, L., 403 Cirik, S. See Boudouresque, C.F., 395 Cisneros-Mata M.A. See Porteiro C., 471 Clabaut P. See Pasqualini V., 402 Clapin, G. See Lemmens, J., 323 Clark, R.P., 76 Clarke, A., 166, 311 See Rex, M.A., 170 Clarke, K.R., 166, 191 See Ellingsen, K.E., 167 See Warwick, R.M., 172 Clarke, M., 311 See Castilla, J.C., 310 Clarke, P.J., 457 Clarke, R.B., 166 Clarke, W.D., 76 See Rosenthal, R.J., 85 Clavano, W.R., 1–38 Clayton, M.N. See Wiencke, C., 476 Clement, A. See Sandweiss, D.H., 334 Clements, F.E., 166 Clementson, L. See Harris, G., 463 Clementson, L.A. See Harris, G.P., 463 See Thresher, R.E., 474 Clendenning, K.A. See Wing, B.L., 88 Closs, G.P. See Sutherland, D.L., 136 Clough, J. See Galbraith, H., 461 Clutter, R.I., 126 See Fleminger, A., 128 Coale, K.H., 311 Coates, M., 457 Cocito, S. See Sandulli, R., 403 Coddington, J.A. See Colwell, R.K., 167 Codignotto, J.O. See Burkett, V., 456 Codispoti, L.A., 311 Coelho, S.M. See Rijstenbil, J.W., 472 Cohen, C.S., 311 Cohen, P.J., 126 Colangelo, M.A. See Martin, D., 401 Cole, D.W. See Henry, E.C., 80 Cole, J. See Wang, H.J., 343 Cole, R.G., 457 Coleman, F.C., 457

488

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AUTHOR INDEX Crowley, G.M. See Garnett, S.T., 461 Croxall, J.P. See Phillips, R.A., 332 Crozier, R.H., 167 Cruz-Palacios, V., 457 CSIRO, 457 Cubasch, U., 458 Cubillos, L. See Ibáñez, C.M., 321 See Neira, S., 330 Cubillos, L.A., 312 See Arancibia, H., 305 See Arcos D.F., 305 Cuesta, J.A. See Drake, P., 128 Cuevas, L.A., 312 See Troncoso, V.A., 340 See Vargas, C.A., 341 Culik, B.M. See Hennicke, J.C., 319 See Luna-Jorquera, G., 325 Cullen, J.J. See Kouwenberg, J.H.M., 466 Culver, S.J., 167 See Buzas, M.A., 166 Cummings, V. See Thrush, S.F., 474 Cummings, V.J. See Lohrer, A.M., 467 See Norkko, A., 470 See Thrush, S.F., 171, 475 See Turner, S.J., 404 Cunha, M.R., 127 Cunningham, A. See MacCallum, I., 35 Cunningham, C.W. See Wares, J.P., 343 Cuq, F. See Glemaréc, M., 398 Curiel, D. See Rismondo, A., 403 Curnel, Y. See Menzel, A., 469 Curray, J.R., 191 Currie, B. See Weeks, S.J., 343 Currie, V. See Dayton, P.K., 76 See Dayton, P.K., 313 Curry, J.A. See Webster, P.J., 476 Curtis, T.G.F., 396 Cury, P., 312 Cushing, D.H., 312, 458

Cormaci, M., 396 See Boudouresque, C.F., 395 Cornejo, M., 312 Cornejorodriguez, M.D. See Enfield, D.B., 314 Cornelius, J. See King, B.R., 466 Cornet, M., 127 Cornuelle, B. See Willis, J.K., 476 Correa, J.A., 312 See Neill, P.E., 329 See Faugeron, S., 315 See Santelices, B., 335 Correa, T., See Gutierrez, A., 80, 319 Cortés, M. See Thiel, M., 199–344 Costanza, R., 396, 457 Costello, M.J., 167 Côté, I.M. See Fish, M.R., 460 See Gardner, T.A., 461 Cottalorda, J.-M. See Meinesz, A., 401 Cottenie, K. See Halpern, B.S., 80 Coulon, A.R. See Anderson, B.S., 74 Courtenay, S.C. See St-Hilaire, A., 136 Coury, D.A. See Reed, D.C., 85 Cowan, T. See Cai, W., 456 Cowen, R.K., 76, 457 Cowie, G.L., 312 Cowie, R.J. See Both, C., 455 Cowles, R.P., 127 Coyer, J.A., 76 See Holbrook, S.J., 81 Coyne, G. See Rex, M.A., 170 Craig, E.A. See Becker, J., 307 Craig, M.G. See Polovina, J.J., 471 Craigie, J.S. See Chapman, A.R.O., 76 Crain, J.A., 127 Crame, J.A. See Clarke, A., 166 See Rex, M.A., 170 Crandall, W.C., 76 Crater, T.S. See Bickmore, B.R., 33 Crawford, R.J.M. See Cury, P., 312 Crecelius, E.A. See Huesemann, M.H., 464 Creese, R.G. See Cole, R.G., 457 Crepinsek, Z. See Menzel, A., 469 Cresswell, G. See Blackburn, S.I., 455 Cresswell, G.R. See Maxwell, J.G.H., 468 Cribb, A.B., 76 Crick, H.Q.P., 457 See Learmonth, J.A., 466 See Robinson, R.A., 472 Crisci, J.V. See Posadas, P., 170 Crisp, D.J., 312 Crist, T.O., 167 See Veech, J.A., 172 Cronin, T.W. See Losey, G.S., 467 Croot, P. See Boyd, P.W., 456 Crosa, G. See Marchetti, R., 401 Crosbie, N.D. See Furnas, M.J., 461 Crossley, A.C. See Sedwick, P.N., 473 Crowder, L.B. See Heck, K.L., Jr, 399 Crowe, T.P. See Thompson, R.C., 404

D Daborn, G.R. See Stone, H.H., 136 Dadswell, M.J. See Carter, J.H.C., 126 da Fonseca, G.A.B. See Brooks, T.M., 395 Dahl, E. See Brattstöm, H., 308 Dahlberg, K. See Jansson, B.-O., 400 Dahlgren, C.P. See Harborne, A.R., 463 See Sobarzo, M., 337 Dahlhoff, E., 312 Dahlin, H. See Rosenberg, R., 403 Dalh, A. See Menzel, A., 469 Dall, W. See Staples, D.J., 474 Dall, W.H., 312 Dam, H. See Peterson, W.T., 331 D’Amato, A.F. See Godfrey, M.H., 462 Damkaer, D.M., 458 See Williams, A.B., 138

489

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AUTHOR INDEX Daneri, G., 312 See Cuevas, L.A., 312 See Escribano, R., 314 See González, H.E., 317 See Troncoso, V.A., 340 See Vargas, C.A., 341 Danielsson, K. See Rudstam, L.G., 135 Dann, P. See Ross, G.J.B., 472 D’Anna, G. See Badalamenti, F., 394 Dantagnan, P., 312 d’Arge, R. See Costanza, R., 396, 457 Darling, J.D., 127 Darnaude, A.M. See Salen-Picard, C., 334 Darrigran, G. See Orensanz, J.M., 134 Darwin, C., 191 Darwin, C.R., 76, 312 Dashfield, S.L. See Warwick, R.M., 172 Da Silva, A.M., 312 Dauby, P.A., 127 Dauvin, J.-C., 127 See Elizalde, M., 128 See Mouny, P., 133 See Vallet, C., 137 See Wang, Z., 137 See Zouhiri, S., 138 Dauwe, B., 127 Davenport, J., 458 Davenport, J.L. See Davenport, J., 458 David, P.M., 127 David, V., 127 Davidson, N.C., 396 Davies, C.E., 396 Davies, P. See Babcock, R., 454 See Harris, G.P., 463 Davis, A. See Wahl, M., 475 Davis, A.R., 458 See Przeslawski, R., 471 Davis, C.S. See Kleppel, G.S., 466 Davis, G., 458 Davis, R.F. See Kouwenberg, J.H.M., 466 Davison, D.M., 396 Dawson, E.Y., 76 Dawson, S.P., 458 Day, R.W. See Zacherl, D.C., 344 Day-Lewis, A. See Keefer, D.K., 322 Dayton, P.K., 76, 77, 313, 396, 458 See Barilotti, D.C., 75 See Genin, A., 461 See Graham, M.H., 79 See Kinlan, B.P., 82 See Rosenthal, R.J., 85 See Sala, E., 334 See Seymour, R.J., 86 See Tegner, M.J., 86, 87, 474 See Thrush, S.F., 404 See Vetter, E.W., 342 See Vilchis, L.I., 475 De Amesti, P. See Stotz, W., 338 Dean, A.F., 127

Dean, T.A., 77 See Deysher, L.E., 77, 458 See Schroeter, S.C., 86 See Tegner, M.J., 87 DeAngelis, D.L. See Grimm, V., 129 De’ath, G. See Brodie, J., 456 See De Vantier, L.M., 458 See McKinnon, A.D., 468 Debinski, D.M. See Su, J.C., 171 Defeo, O., 313 See Castilla, J.C., 310 See Contreras, H., 312 Defile, C. See Menzel, A., 469 deFrance, S.D. See Keefer, D.K., 322 DeGange, A.R., 127 De Grave, S., 396 de Groot, R. See Costanza, R., 396, 457 de Groot, S.J. See Lindeboom, H.J., 401 de Gruijl, F.R. See Kelfkens, G., de Gusmao, L.L.F. See Gama, A.M. da S., 129 de Haan, J.F. See Volten, H., 36 Deibel, D. See Richoux, N.B., 135 de Jager, D., 458 De Jong-Moreau, L., 127 Dekhuijzen, A.J. See Both, C., 455 Dekker, R. See Philippart, C.J.M., 470 de la Huz, Ch. See Barbera, C., 394 DeLancey, L.B., 127 de Lange, H..J. See Hessen, D., 463 de Lange, P.J. See de Lange, W.P., 458 de Lange, W.P., 458 Delaune, R.D.,See Parkinson, R.W., 470 Delépine, R., 77 See Asensi, A., 74 Delgado, L., 127 Delgado, L.E. See Marín, V.H, 326 Delgado, O., 396 Delille, B., 77 See Engel, A., 460 Delille, D., 313 See Delille, B., 77 Dell, R.K., 313 Della Croce, N. See Thurston, M.H., 340 Dellarossa, V. See Daneri, G., 312 Dellinger, T., 313 DeMartini, E.E., 77 See Plummer, K.M., 134 See Polovina, J.J., 471 DeMaster, D.J. See Smith, C.R., 337 DeMaster, D.P. See Laidre, K.L., 82 Demetropulous, A. See Jeftic, L., 400 Den Hartog, C., 397 Dennison, W. See Walker, D., 475 Dennison, W.C. See Abal, E.G., 453 See Carruthers, T.J.B., 457 See Dawson, S.P., 458 Denny, M., 458 Denny, M.W. See Li, N.K., 467 See Utter, B.D., 87

490

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AUTHOR INDEX Dixon, J.D. See Dean, T.A., 77 See Schroeter, S.C., 86 Dixon, K.W. See Gregory, J.M., 462 Djellouli, A. See Meinesz, A., 401 Djurfeldt, L. See Shaffer, G., 336 Dobow, J. See Wilcove, D.S., 405 Dobretsov, S. See Wahl, M., 475 Dobson, A.P. See Harvell, C.D., 463 Dodd, J., 397 Dodson, J.J. See Winkler, G., 138 Doerries, M.B., 167 Döhler, G., 458 Dolman, P.M. See Sutherland, W.J., 338 Domin, A. See Wilhelm, C., 476 Donahoe, C.J., 128 Donders, T.H. See Sangiorgi, F., 403 Done, T.J., 459 See De Vantier, L.M., 458 See Orr, J.C., 470 Doney, S.C. See Boyd, P.W., 456 See Sarmiento, J.L., 473 Donkin, M.E. See Cordi, B., 457 Donnan, D.W., 397 Donnellan, M.D., 77 Donnelly, A. See Menzel, A., 469 Donner, S.D., 459 Doody, J.P., 397 See Davidson, N.C., 396 Dorenbosch, M., 459 Dorman, L.M. See McGowan, J.A., 468 Dortch, Q. See Thessen, A.E., 474 dos Santos, A. See Bonnet, D., 455 Doumenge, F. See Barnabe, G., 394 Dower, J.F. See Kunze, E., 131 Downes, B.J., 77 See Keough, M.J., 322 Downing, K. See Boyd, P.W., 456 Downs, C.A., 191 See Brown, B.E., 191 Drake, C.M. See Davidson, N.C., 396 Drake, P., 128 Drake, P.T. See Reed, D.C., 85 Drew, E.A., 191 Dring, M.J. See Birkett, D.A., 395 Drinkwater, K. See Choi, J.S., 126 Drinkwater, K.F., 459 Drohan, A.F., 459 Drosdowsky, W. See Allan, R., 190 Druehl, L.D., 77, 78 See Lane, C.E., 82 See Saunders, G.W., 85 See Swanson, A.K., 86, 474 See Wheeler, W.N., 88 Du, T. See Gordon, H.R., 34 Duarte, C., 313 See Dugan, J.E., 313 See Jaramillo, E., 322 Duarte, C.M., 397, 459

De Oliveira J.A.A. See Porteiro C., 471 Department of Marine and Coastal Resources, Thailand, 191 de Perera, T.B. See Garcia, C.M., 461 Depledge, M.H. See Cordi, B., 457 De Pol, R. See Ulloa, O., 340 De Pol-Holz, R. See Atkinson, L.P., 306 Deprez, T., 128 Dermott, R.M. See Johannsson, O.E., 130 De Robertis, A., 128 Desai, B.N., 191 Desalle, R. See Herbst, L., 463 Descimon, H. See Parmesan, C., 470 Desprez, M., 397 Desqueyroux, R., 313 Desqueyroux-Faúndez, R. See Castilla, J.C., 310 Destombe, C. See Faugeron, S., 315 Detres, Y., 458 Dette, H.H. See Hamm, L., 399 Devinny, J.S., 77 Devlin, M.J., 458 DeVried, P.J. See Lande, R., 169 De Vantier, L.M., 458 de Vaugelas, J. See Meinesz, A., 401 de Villèle, X., 397 de Vries, M. See Martin, D., 401 Dewees, C.M. See Leet W.S., 82 Dewey, R. See Kunze, E., 131 Dewicke, A., 128 See Beyst, B., 125 Dewitte, B. See Ramos, M., 333 DeWreede, R.E., 77 Dey, D.B. See Damkaer, D.M., 458 Deysher, L. See Grove, R.S., 462 Deysher, L.E., 77, 458 See Tegner, M.J., 87 Dezileau, L. See Muñoz, P., 329 Díaz, A. See Palma, A.T., 331 Díaz, C. See Acuña, E., 304 Diaz, H.F., 77 Diaz, R.J., 397 Diaz-Almela, E., 458 DiBacco, C., 313 Diebold, E.N. See Simeone, A., 337 Dieckmann, U., 128 Diehl, S., 458 Diekman, R. See Bonnet, D., 455 Dijkema, K.S., 397 Dimmlich, W.F. See Ward, T.M., 476 Dinesen, G.E. See Moschella, P.S., 402 Dippner, J.W. See Kroencke, I., 323 Dittmann, S. See Grimm, V., 129 DiTulliio, G.R. See Sedwick, P.N., 473 See Hutchins, D.A., 321 See Tortell, P.D., 475 Divoky, G.J., 128 Dix, M. See Cubasch, U., 458 Dix, M.R. See Gordon, H.B., 462 Dixon, J., 77

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AUTHOR INDEX See Hempel, W.M., 80 See Reed, D.C., 85, 333 Ebensperger, L.A., 78, 313 See Villegas, M.J., 343 EC, 397 Eckerle, L. See Brante, A., 308 Eckert, S.A., 459 Edding, M., 313, 314 See Macchiavello, J., 325 See Tala, F., 339 See Véliz, K., 342 Edgar, G. See Walker, D., 475 Edgar, G.J., 78, 397, 459 Edmonds, S.J. See Womersley, H.B.S., 477 Edmunds, P.J. See Gleason, D.F., 461 Eduardo, C., 167 Edvardsen, E. See Jonzén, N., Edwards, A.J. See Mumby, P.J., 469 Edwards, M., 459 See Beaugrand, G., 454 See Bonnet, D., 455 See Kirby, R.R., 466 Edwards, M.J., 459 Edwards, M.S., 78, 314, 459 See Clark, R.P., 76 Edwards, P.B. See Dayton, P.K., 77, 396, 458 See Tegner, M.J., 87, 474 Edwards-Jones, G. See Gelcich, S., 317 Edyvane, K.S., 459 See Seddon, S., 473 EEA., 397 Eekhout, S. See Bustamante, R.H., 308 Eeva, T. See Both, C., 455 Eggiman, D.W. See Carder, K.L., 33 Eggleston, D.B. See Beck, M.W., 394 Ego, F. See Pubellier, M., 193 Ehlers, A. See Lotze, H.K., 401 Ehrhart, L.M. See Weishampel, J.F., 476 Eijsackers, M. See Rijstenbil, J.W., 472 Eilers, M.R. See Matilla, J., 132 Eischeid, J.K. See Diaz, H.F., 77 Eissler, Y., 314 Ekebom, J., 398 Ekman, S., 314 El Abed, A. See Meinesz, A., 401 Elderfield, H. See Raven, J., 471 Eleftheriou, A., 128 Elías, R. See Orensanz, J.M., 134 Elizalde, M., 128 Elkins, J.W. See Codispoti, L.A., 311 Ellenberg, U., 314 See Mattern, T., 326 See Simeone, A., 337 Ellingsen, K.E., 167 See Ugland, K. I., 172 Elliott, T.I. See Gordon, H.B., 462 Ellis, D., 167 Ellis, J.C., 314 See Fariña, J.M., 315

See Diaz-Almela, E., 458 See Hemminga, M.A., 399 See Marbà, N., 401 Duarte, W.E., 313 See Moreno, C.A., 328 See Zamorano, J.H., 344 Dubinsky, Z. See Stambler, N., 194 Dubovik, O., 34 See Zhao, T.X.-P., 36 Duce, R.A. See Jickells, T.D., 465 Duchene, J.C. See Guizien, K., 318 Ducklow, H.W., 313 Dudley, C. See Crick, H.Q.P., 457 Duff, K.L. See Davidson, N.C., 396 Duffus, D.A. See Dunham, J.S., 128 Duffy, D., 313 Dufresne, J.L. See Bopp, L., 455 Dugan, J. See Roberts, C.M., 333 Dugan, J.E., 313 See Airamè, S., 393 See Bomkamp, R.E., 307 Dugan, P., 397 Dugdale, R.C. See Hogue, V.E., 464 Duggan, S. See McKinnon, A.D., 468 Duggins, D.O., 78 See Estes, J.A., 78 Duke, N.C., 459 Dukowicz, J.K. See Griffies, S.M., 462 Dulvy, N.K., 459 Dumont, C.P. See Thiel, M., 199–344 Dunham, J.S., 128 Dunlop, J.N., 459 Dunn, J.R. See Ridgway, K.R., 472 Dunne, J.A., 128 Dunne, R.P., 191 See Brown, B.E., 191 Dunton, K., 313 Dunton, K.H., 78 Dupont, F. See St-Hilaire, A., 136 Durán, L.R., 313 See Castilla, J.C., 310 Durán, R. See Sielfeld, W., 336 Durante, K.M., See Hurd, C.L., 81 Durr, S.T. See Wahl, M., 475 Dürselen, C.-D. See Hillebrand, H., 34 Dutton, P.H. See Polovina, J.J., 471 Duysens, L.M.N., 34

E Eaglesham, G. See Negri, A., 469 Eakin, C.M. See Kleypas, J.A., 466 Eardley, D.D., 78 See Hempel, W.M., 80 Ebeling, A.W., 78 See Bray, R.N., 75 See Eardley, D.D., 78 See Harris, L.G., 80

492

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AUTHOR INDEX Espíndola, F. See Yáñez, E., 344 Espinoza, F., 315 Espinoza, R. See Buschmann, A.H., 75 See Buschmann, A.H., 308 Espinoza, S. See Marín, V.H., 326 Essink, K. See van Dalfsen, J. A., 405 Estes, J. See Steneck, R.S., 86 Estes, J.A., 78 See Duggins, D.O., 78 See Erlandson, J.M., 78 See Jackson, J.B.C., 399 See Paddack, M.J., 84 See Steneck, R.S., 474 See Steneck, R.S., 404 Estes, J.E. See Jensen, J.R., 81 Estrella, N. See Menzel, A., 469 Etter, R.J. See Levin, L.A., 169, 324 See Rex, M.A., 170 See Witman, J.D., 172 EUCC — The Coastal Union, 398 Evans, B.T.N. See Fournier, G.R., 34 Evans, M.J., 460 Evans, M.S., 128 Ewel, K.C., 460 Ezzi, I.A. See Gibson, R.N., 129

Ellis, J.I. See Norkko, A., 470 See Thrush, S.F., 474 475 Ellis, J.R. See Perry, A.L., 470 Ellison, A.M., 459 See Farnsworth, E.J., 460 Ellison, J.C., 460 Elmgren, R. See Hansson, S., 130 See Rosenberg, R., 403 Elmi, C. See Bondesan, M., 395 El-Sayed, S., 459 Emanuel, K., 460 Emblow, C.S. See Costello, M.J., 167 Emes, C. See Speirs, D., 136 Emmerson, M., 128 Emsley, S.M., 128 Enbysk, B.J., 128 Endean, R., 460 Ene, A., 460 Ene, A. See Herbst, L., 463 Enemar, A. See Both, C., 455 Enfield, D.B., 314 Engdhal E.R. See Bilham, R., 191 Engel, A., 460 Engkvist, R. See Nilsson, J., 402 See Worm, B., 405 Enríquez, S. See Marbà, N., 401 Enríquez-Briones, S. See Gallardo, V.A., 316 See Roa, R., 333 Environment Australia, 460 Eppley, R.W., 460 Epstein, P.R. See Harvell, C.D., 463 Erftemeijer, P.L.A. See Ochieng, C.A., 470 Erga, S.R., 460 Eriksson, B.K., 398 See Johansson, G., 400 Erkkilä, A. See Ekebom, J., 398 Erlandson, J. See Jackson, J.B.C., 399 Erlandson, J.M., 78 See Graham, M.H., 79 See Kinlan, B.P., 82 See Steneck, R.S., 86, 404, 474 Ernst, B. See Roa, R., 333 Escribano, N. See Marín, V.H., 326 See Ulloa, O., 340 Escribano, R., 314, 315 See Castro, L.R., 311 See Fernández, D., 315 See Giraldo, A., 317 See González, H.E., 317, 318 See Herrera, L., 319 See Hidalgo, P., 320 See Ortlieb, L., 330 See Palma, W., 331 See Rendell, L., 333 See Rodríguez, L., 333 See Rojas, P.M., 333 See Takesue, R.K., 339 See Thiel, M., 199–344 See Vargas, C.A., 341

F Faaborg, J. See Terborgh, J.W., 171 Fabbri, D. See Trombini, C., 404 Fabri, M.C., 167 Fabricius, K. See Brodie, J., 456 See Negri, A., 469 Fabricius, K.E., 460 See De Vantier, L.M., 458 Fabry, V.J. See Orr, J.C., 470 Fadii, N. See Baird, A.H., 190 Fagan, W.F. See Andelman, S.J., 166 Fahrbach, E. See Arntz, W., 306 Fain, S.R., 78 Faith, D.P., 167 FAL, 315 Fallaci, M. See Colombini, I., 311 Fanelli, G., 398 FAO, 315 Farber, S. See Costanza, R., 457 See Costanza, R., 396 Farías, L., 315 See Cornejo, M., 312 See Escribano, R., 314 See Graco, M., 318 Farías, M. See Fonseca, T., 316 Fariña, J.M., 315 See Ellis, J.C., 314 See Sabat, P., 334 Farnsworth, E.J., 460 See Ellison, A.M., 459 Farrell, T.M., 315

493

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AUTHOR INDEX Fishelson, L. See Moran, S., 133 Fisher, A.A., 167 Fisher, N.S. See Twining, B.S., 137 Fitt, W.K. See LaJeunesse, T.C., 192 See Wellington, G.M., 476 Fitzpatrick, L. See Guerra, C., 318 Fitzpatrick, M. See Bunge, J., 166 Fitzwater, S.E. See Coale, K.H., 311 See Martin, J.H., 326 Flato, G.M. See Gregory, J.M., 462 Fleischer, S. See Rosenberg, R., 403 Fleminger, A.,128 See Marín, V.H., 326 Flensted-Jensen, E. See Moller, A.P., 469 Fletcher, T.D. See Keatley, M.R., 465 Flick, P. See Brooks, T.M., 395 Flinkman, J., 128 See Viherluoto, M., 137 See Viitasalo, M., 137 Flint, E.N. See Polovina, J.J., 471 Flores, C. See Pizarro, J., 332 Flores, L.A. See Rosenberg, R., 333 Flores, M. See Bernal, M., 307 Flores, V. See Santelices, B., 335 Flores, V.A. See Arntz, W., 306 Flynn, A.J., 128 Flynn, M.N. See Tararam, A.S., 137 Foertch, J.F. See Keser, M., 466 Fogarty, M.J., 129 Foggo, A., 167 Foley, A.M., 460 Foley, M.M. See Menge, B.A., 327 Folke, C. See Hughes, T.P., 464 Follegati, R. See Ortlieb, L., 330 Fonck, E. See Santelices, B., 335 Fonck, E.A. See Edding, M., 313, 314 See Vásquez, J.A., 341 Fong, P. See Smith, J.R., 473 Fonseca, C.R., 460 Fonseca, M.S., 460 Fonseca, T., 316 See Johnson, D.R., 322 Forbes, D.L. See Burkett, V., 456 Forbes, E., 167 Ford, E., 167 Ford, R. See Lawrie, S.M., 132 Fordham, E. See Frid, C.L.J., 460 Forster, S. See Fossing, H., 316 Fortuna, S. See Wilkie, M.L., 405 Forward, R.B., 316 See Goddard, S.M., 129 Fosberg, F.R., 78 Fosså, J.H., 129 See Attramadai, Y.G., 125 See Buhl-Jensen, L., 126 Fossing, H., 316 Foster, E.G., 129 Foster, M.S. 78, 79

Faugeron, S., 315 See Neill, P.E., 329 Fauth, J.E. See Downs, C.A., 191 Feder, H.M., 78 Feely, R.A. See Orr, J.C., 470 Fehner, U. See Antia, A.N., 454 Feld, N. See Bilham, R., 191 Feldman, M.W. See Zhivotovsky, L.A., 138 Félix-Pico, E. See Narvarte, M.E., 329 Félix-Uraga R. See Porteiro C., 471 Feller, R.J. See Zagursky, G., 138 Fengshan, X. See Rhoads, D.C., 471 Fenner, D. See Turner, J.R., 194 Ferl, R.J. See Bowen, B.W., 455 Fernández, D., 315 Fernández, E., 315 See Lleellish, J., 324 See Lleellish, M., 83 Fernández, M., 315, 316 See Astorga, A., 306 See Baeza, J.A., 306 See Brante, A., 308 See Brokordt, K.B., 308 See Castilla, J.C., 310 See Escribano, R., 314 See Marquet, P.A., 326 See Rivadeneira, M.M., 333, 472 See Ruiz-Tagle, N., 334 See Thiel, M., 199–344 Fernandez de Puelles, M.L. See Bonnet, D., 455 Fernández-Delgado, C. See Drake, P., 128 Fernex, F. See Jeftic, L., 400 Ferraroli, S., 460 Ferreyra, G.A. See Hernando, M.P., 463 Fetter, M. See Möllmann, C., 133 Fey, C. See Haury, L., 130 Feyrer, F., 128 Fiala, M. See Delille, B., 77 Fick-Child, K.J. See Foley, A.M., 460 Fiedler, P.C., 316 Field, C.D., 460 Fielding, P.J. See Attwood, C.G., 74 Figueroa, C. See Takesue, R.K., 339 Figueroa, D., 316 See Atkinson, L.P., 306 See González, H.E., 317, 318 See Rutllant, J.A., 334 See Sobarzo, M., 337 See Yannicelli, B., 344 Figueroa, F.L. See Gómez, I., 317 See Huovinen, P., 321 Filella, Y. See Menzel, A., 469 Filún, L. See Buschmann, A.H., 75, 308 Finger, I. See Rosenberg, R., 333 Finke, G.R. See Navarrete, S.A., 329 Finlayson, C.M., 398 Firme, G.F. See Hutchins, D.A., 321 Fischer, G. See Antia, A.N., 454 Fish, M.R., 460

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AUTHOR INDEX Frost, M.T. See Foggo, A., 167 Fry, B. See Hansson, S., 130 Fry, E.S. See Voss, K.J., 36 Fryd, M. See Nielsen, T.G., 192 Fuchs, B.M. See Kuypers, M.M., 323 Fuenteseca, J. See Marín, V.H., 326 Fuenzalida, H. See Rutllant, J.A., 334 Fuenzalida, R., 316 Fuller, P.J. See Ross, G.J.B., 472 Fulton, E.A., 461 Fulton, R.S., III, 129 Funnell, G. See Turner, S.J., 404 Funnell, G.A. See Norkko, A., 470 See Thrush, S.F., 475 Furlani, D.M. See Thresher, R.E., Furlong, C. See Hauxwell, J., 399 Furnari, G. See Cormaci, M., 396 Furnas, M.J., 461 See McKinnon, A.D., 468 Furness, R., 316 Furukawa, K., 461 Furusawa, M. See Amakasu, K., 125

See McConnico, L., 83 See Clark, R.P., 76 See Cowen, R.K., 76 See Graham, M.H., 79 See Hernández-Carmona, G., 80 See Kimura, R.S., 82 See Reed, D.C., 85, 471 See Schiel, D.R., 86, 473 See Spalding, H., 86, 474 Fournier, G. See Jonasz, M., 34 Fournier, G.F. See Jonasz, M., 34 Fournier, G.R., 34 Fourqurean, J.W., 460 460 Fowler-Walker, M.J., 460 Fox, C.J. See O’Brien, C.M., 470 Fox, D.S. See Grantham, B.A., 318 Fox, G. See Ball, B.J., 394 Fox, G.E. See Woese, C.R., 344 Fox, R. See Hickling, R., 463 Francis, C.M. See Marra, P.P., 468 Francis, R.C. See Mantua, N.J., 468 Franco, E. See Ariani, A.P., 125 Francour P. See Perez, T., 470 Frank, K. See Gray, J.S., 168 Frank, K.T., 129 See Choi, J.S., 126 Franke, H.D., 398 Frankignoulle, M. See Delille, B., 77 See Delille, D., 313 See Gattuso, J.P., 461 Fraschetti, S. See Guidetti, P., 398 Frazier, S. See Nivet, C., 402 Frederich, M., 316 Fredriksen, S., 79 See Christie, H., 396 Freeland, H.J., 316 Freidenburg, T.L. See Menge, B.A., 327 Freiwald, A. See Guinotte, J.M., 462 See Roberts, J.M., 472 Frere, E., 316 Frette, O. See Erga, S.R., 460 Freudenthal, T., 319 Frew, R. See Boyd, P.W., 456 Frid, C., 398 Frid, C.L., 316 Frid, C.L.J., 398, 460 Friedel, M.H., 461 Friederich, G.E. See Codispoti, L.A., 311 Friedman, C.S. See Vilchis, L.I., 475 Friedman, J.D. See Vilchis, L.I., 475 Friesen, J.A., 129 Fritsch, F.E., 79 Fromentin, J.M. See Walther, G.R., 476 Froneman, P.W., 129 See Teske, P.R., 339 Frost, B.W. See Bollens, S.M., 455 See Hays, G.C., 130 Frost, M. See Martin, D., 401 See Moschella, P.S., 402

G Gabbbianelli, G. See Bondesan, M., 395 Gabrielides, G.P. See Jeftic, L., 400 Gabrielson, P.W., 79 Gacia, E. See Moschella, P.S., 402 Gage, J., 167 See Levin, L.A., 324 See Narayanaswamy, B.E., 170 See Roberts, J.M., 472 Gaines, S. See Roughgarden, J., 85, 333 Gaines, S.D. See Broitman, B.R., 308 See Gaylord, B., 461 See Kinlan, B.P., 322 See Lubchenco J., 169 See Menge, B.A., 327 See Siegel, D.A., 336 See Wares, J.P., 343 See Zacherl, D., 477 See Zacherl, D.C., 344 See Blanchette, C.A., 75 Gajardo, G., 316 Gajardo, J.A. See Thiel, 199–344 Gal, G., 129 See Johannsson, O.E., 130 Galáz, J. See Sielfeld, W., 336 Galáz, L.E. See Camus, P.A., 309 Galbraith, H., 461 Galeron, J. See Fabri, M.C., 167 Gales, R. See Bunce, A., 456 See Pemberton, D., 470 Gall, A. See Mumby, P.J., 469 Gall, M. See Boyd, P.W., 456 Gallardo, V. See Milessi, A., 327

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AUTHOR INDEX Gallardo, V.A., 316 See Arntz, W., 306 See Atkinson, L.P., 306 See Carrasco, F.D., 309 See Escribano, R., 314 See Fossing, H., 316 See Gutiérrez, D., 319 See Neira, C., 329 See Palma, M., 331 See Roa, R., 333 See Schulz, H.N., 335 See Sellanes, J., 336 Gallegos, M.E. See Marbà, N., 401 Galleguillos, R., 316 See Chong, J., 311 See Gómez-Uchida, D., 317 Galois, R. See David, V., 127 Gama, A.M. da S., 129 Ganade, G. See Fonseca, C.R., 460 Gandini, P. See Frere, E., 316 Gao, K., 461 Gao, K.S., 461 Garcés-Vargas, J. See Fuenzalida, R., 316 García, C. See Buschmann, A.H., 75, 308 Garcia, C.M., 461 Garcia, H.E. See Conkright, M.E., 311 García, J.C., 317 Garcia, O. See Hernández-Carmona, G., 80 Garcia-de la Rosa, O. See Hernández-Carmona, G., 81 García-González, D. See Drake, P., 128 Garde, K., 461 See Wängberg, S.A., 476 Gardner, N.L. See Setchell, W.A., 86 Gardner, T.A., 461 Garkaklis, M.J. See Bancroft, W.J., 454 Garman, G.D., 79 Garnett, S.T., 461 Garrabou, J., 461 See Perez, T., 470 Garrido, J. See González, J., 318 Garrison, L.P. See Link, J.S., 132 Garthe, S. See Ludynia, K., 324 See Simeone, A., 337 See Weichler, T., 343 Garwood, P.R. See Frid, C.L., 316 Gaspar, P. See Ferraroli, S., 460 Gasparovic, F. See Jeftic, L., 400 Gassmann, G. See Maier, I., 83 Gaston, K.J., 168 See Spicer, J.L., 337 See Williams, P.H., 172 See Williamson, M., Gates, R.D. See Gleason, D.F., 461 Gatien, G. See Freeland, H.J., 316 Gatlin, D.M., III, 129 Gattuso, J.P., 461 See Engel, A., 460 See Kleypas, J.A., 466 Gaughan, D.J., 461

Gaylord, B., 79, 461 See Denny, M., 458 See Raimondi, P.T., 84 See Reed, D.C., 85 See Siegel, D.A., 336 Gaymer, C.F. See Brokordt, K.B., 308 See Thiel, M., 199–344 Geesey, M.E. See Hutchins, D.A., 321 Gelcich, S., 317 See Castilla, J.C., 310 Gelfman, C. See Wishner, K.F., 344 Geller, P.E., 34 Gellner, G. See Rooney, N., 135 Genin, A., 129, 461 See Haury, L., 130 Genner, M.J. See Sims, D.W., 473 Gentili, B. See Morel, A., 35 Gentleman, W. See Miller, C.B., 133 George, R. See Guinotte, J.M., 462 Georges, J.Y. See Ferraroli, S., 460 Geraci, S. See Fanelli, G., 398 Gerard, V.A., 79 See Bruhn, J., 456 See Burgman, M.A., 75 Gerber, L.R. See Micheli, F. 327 Gerdes, D. See Palma, M., 331 Gering, J.C. See Veech, J.A., 172 Gerlotto, F. See Bertrand, A., 307 Gerrodette, T. See Dayton, P.K., 76, 313 Gershwin, L.A., 461 Ghelardi, R.J., 79 Giannoulaki, M. See Karakassis, I., 169 Gibb, J.G. See de Lange, W.P., 458 Gibb, S.W. See Brown, B.E., 191 Gibbons, J. See Capella, J., 309 Giberto, D.A. See Schiariti, A., 135 Gibson, G. See Hu, Y.-X., 34 Gibson, R.N., 129 Giesecke, R., 317 See Escribano, R., 314 See González, H.E., 317 Gieskes, W.W.C. See Kelfkens, G., 465 Giglio, S. See Marchant, M., 325 Gilbert, J.J. See Twining, B.S., 137 Gili, J.M. See Pagès, F., 330 See Ribes, M., 134 Gill, J.A. See Fish, M.R., 460 See Gardner, T.A., 461 See Smart, J., 473 Gillanders, B.M. See Beck, M.W., 394 See Bloomfield, A.L., 455 See Fowler-Walker, M.J., 460 Gillett, N.P., 461 Gilman, S.E. See Barry, J.P., 454 See Sagarin, R.D., 472 Gilmour, J., 461 Giordano, M., 461 Giraldo, A., 317 Girondot, M. See Rivalan, P., 472

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AUTHOR INDEX Gittleman, J.L. See Mace, G.M., 169 Glascock, M.D. See Sandweiss, D.H., 334 Glatts, R.C. See Kaufmann, R.S., 131 Gleason, D.F., 461 Glemaréc, M., 398 See Barbera, C., 394 Glen, F., 461 See Hays, G.C., 463 Gloersen, K.A. See White, W.B., 476 Glover, A.G., 461 Glover, H.E. See Codispoti, L.A., 311 Glud, R.N., 317 See Fossing, H., 316 Glue, D.F. See Crick, H.Q.P., 457 Glynn, P.W., 317 Gnanadesikan, A. See Griffies, S.M., 462 See Orr, J.C., 470 Gobin, J.F., 168 Goddard, J. See Langdon, C., 466 Goddard, S.M., 129 Godfrey, J.S. See Ridgway, K.R., 472 See Tomczak, M., 194 Godfrey, M.H., 461462 Godínez-Orta, L. See Takesue, R.K., 339 Godley, B.J. See Broderick, A.C., 456 See Hays, G.C., 463 Godo, O.R. See Byrkjedal, I., 456 Godoy, N.E., 317 Goericke, R. See Moore, L.R., 469 Goes, J.I., 462 Goff, L.J. See Garman, G.D., 79 Goffart A, 462 Goggin, C.L., 462 Goldberg, N.A., 462 Golding, N. See Connor, D.W., 396 Goldsmith, T.H. See Losey, G.S., 467 Gomez, E.D. See Kaufman L., 322 Gómez, F. See Bertrand, A., 307 Gómez, I., 317 See Huovinen, P., 321 See Thiel, M., 199–344 See Véliz, K., 342 See Westermeier, R., 343 Gomez, M. See Calliari, D., 126 Gómez-Uchida, D., 317 Gomoiu, M.-T., 398 Gong, D.Y., 317 Gong, W.K. See Farnsworth, E.J., 460 González, A., 317 See Leibold, M.A., 323 González, A.E. See Thiel, M., 199–344 González, C., 317 See Fernández, M., 315 See Ibáñez, C.M., 321 González, E. See Thiel, M., 339 González, E.O. See Camus, P.A., 309 González, H. See Bernal, P.A., 307 González, H.E., 317, 318 See Escribano, R., 314

See Giesecke, R., 317 See Grünewald A., 318 See Iriarte, J.L., 321 See Marchant, M., 325 See Morales, C.E., 328 See Pagès, F., 330 See Pantoja, S., 331 See Pavez, M.A., 331 See Rodríguez-Graña, L., 333 See Thiel, M., 199–344 See Vargas, C.A., 341 González, J., 318 González, L.A., 129 González, M. See Jaramillo, E., 321 González, R.R., 318 See Ulloa, O., 340 See Yaikin, J., 344 González, S.A., 318 See Stotz, W., 338 Gonzalez-Fragoso, J., 79 Gonzalez-Rodas, G. See El-Sayed, S., 459 Goodall, J. See Dunton, K., 313 Gooday, A.J., 318 See Levin, L.A., 169, 324 Goodson, M.S., 191 Gorczynska, M.I. See Mumby, P.J., 469 Gordillo, S. See Adami, M.L., 74 Gordon, H.B., 462 Gordon, H.R., 34 Gordon, J. See Davidson, N.C., 396 Gordon, R.M. See Martin, J.H., 326 Gorelick, R. 168 Gorgula, S.K., 462 Gorshkov, S.G., 318 Gotelli, N.J., 168 See Colwell, R.K., 167 Gowing, M.M. See Wishner, K.F., 344 Gowlett-Holmes, K. See Koslow, J.A., 466 See Williams, A., 476 Graco, M., 318 See Farías, L., 315 Graddon, D.J. See Barrett, N.S., 397 Graf, G., 318 Graham, M.H., 39–88, 79, 80, 318, 462 See Erlandson, J.M., 78 See Hernández-Carmona, G., 80 See Kinlan, B.P., 82 See Munoz, V., 83, 329 See Muñoz, V., See Sala, E., 85 See Steneck, R.S., 86, 404, 474 Graham, N.E. See Polovina, J.J., 471 Graham, W.M. See Reed, D.C., 85 Grall, J., 398 See Barbera, C., 394 See Hall-Spencer, J.M., 398 Grams, G.W. See Ch´ylek, P., 34 Granados, I. See Takesue, R.K., 339 Graneli, E. See Carlsson, P., 456

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AUTHOR INDEX Guerrero, R.A. See Schiariti, A., 135 Guidetti, P., 398 See Rismondo, A., 403 Guiler, E.R., 80 Guillén, O. See Zuta, S., 344 Guinéz, R. See Buschmann, A.H., 308 See Castilla, J.C., 310 See Alvarado, J.L., 305 See Kaplan, D.M., 322 Guinotte, J. See Kleypas, J.A., 466 Guinotte, J.M., 462 Guisado, C. See Véliz, D., 342 Guizien, K., 318 Gullström, L.B. See Baden, S., 394 Gundersen, J.K. See Fossing, H., 316 See Glud, R.N., 317 Gunn, J. See Polacheck, T., 471 Gunn, J.S. See Thresher, R.E., 474 Gunther, E.R., 318 Günther, C.-P. See Grimm, V., 129 Günther, R.T., 398 Guppy, H.B., 319 Gupta, T.D. See Pal, T., 192 Gurevitch, J., 168 See Rosenberg, M.S., 171 Gurney, W. See Speirs, D., 136 Gurney, W.S.C. See Lawrie, S.M., 132 Gustafsson, L. See Both, C., 455 Gustavson, K. See Wängberg, S.A., 476 Gutierrez, A., 80, 319 Gutiérrez, D. See Arntz W.E., 306 See Escribano, R., 314 See Gallardo, V.A., 316 See Graco, M., 318 See Muñoz, P., 329 See Neira, C., 329 See Sellanes, J., 336 See Tarazona , J., 339 Gutow, L. See Franke, H.D., 398 See Thiel, M., 87, 339 Guzman, H.M. See Pandolfi, J.M., 470 Guzmán, N. See Ortlieb, L., 330 See Takesue, R.K., 339 Guzman-Speziale, M., 191 Gwak, W.-S. See Tanaka, Y., 136

Granhag, L. See Jonsson, P.R., 465 See Moschella, P.S., 402 Grant, A. See Gardner, T.A., 461 Grantham, B.A., 318 See Shanks, A.L., 336 Grassl, H. See Pozdnyakov, D., 35 Grassle, J.F., 168 Grasso, M. See Costanza, R., 396, 457 Grau, A. See Delgado, O., 396 Grau, A.M. See Meinesz, A., 401 Graves, J.E., 318 Gravestock, P. See Balmford, A., 307 Gray, J.S. 168, 398 See Ellingsen, K.E., 167 See Ugland, K. I., 172 Grebmeier, J. See Dunton, K., 313 Green, E.P., 398 See Spalding, M.D., 194, 404 Green, K., 129 Green, M.J.B., 398 Green, R.E. See Balmford, A., 394 Greene, C.H. See Gal, G., 129 See Smith, S.L., 136 Greenlaw, C.F., 129 Gregory, J.M., 462 See Church J.A., 457 Greig, A. See Beare, D.J., 454 Grelle, V. See Eduardo, C., 167 Greve, W., 462 See Bonnet, D., 455 See Winkler, G., 138 Griffies, S.M., 462 Griffin, D.A., 462 Griffiths, F.B. See Harris, G.P., 463 See Sedwick, P.N., 473 Griffiths, R.C. See Rao, T.S.S., 193 Griffiths, S.P., 462 Grimes, D.J. See Harvell, C.D., 463 Grimm, V., 129 See Peña T.S., 331 Grol, M.G.G. See Dorenbosch, M., 459 Grone, G. See Rodríguez, L., 333 Grootes, P.M. See Haneburth, T., 192 Grosberg, R. See Hughes, T.P., 464 Grove, R.S., 462 Grover, J. 462 Grua, P., 80 Gruber, A. See Wiencke, C., 476 Gruber, N. See Orr, J.C., 470 Grünewald A., 318 Grzybowski, K. See Simeone, A., 337 Gucinski, H. See Behrenfeld, M., 455 Guderley, H. See Martínez, G., 326 Guderley, H.E. See Brokordt, K.B., 308 Guerao, G. See Delgado, L., 127 Guerin-Ancey, O. See David, P.M., 127 Guerra, C., 318 See Sielfeld, W., 336 Guerra, Y. See Sielfeld, W., 336

H Haaker, P.L. See Davis, G., 458 Häder, D., 462 Häder, D.P., 462 Häder, M.A. See Häder, D., 462 Hadfield, M. See Boyd, P.W., 456 Hagen, N.T., 398 Haight, W.R. See Polovina, J.J., 471 Halim, Y. See Jeftic, L., 400 Hall, J. See Boyd, P.W., 456 Hall, J.A. See Frid, C.L.J., 398

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AUTHOR INDEX Hall, K.R. See Root, T.L., 472 Hall, R., 192 Hall, S.J., 462 See Frid, C.L.J., 398 Hallacher, L.E., 80 Hällfors, G. See Kangas, P., 400 Halling, C. See Chopin, T., 311 Hall-Spencer, J., 398 Hall-Spencer, J.M., 399 See Barbera, C., 394 See Grall, J., 398 Halpern, B. See Beck, M.W., 394 Halpern, B.S., 80 See Graham, M.H., 79 See Roberts, C.M., 333 Halpin, P.M., 319 Hama, T. See Goes, J.I., 462 Hamann, J. See Wilhelm, F.M., 138 Hamerlynck, O. See Mees, J., 133 Hamilton, A.J., 168 Hamm, L., 399 Hammer, C. See Frid, C., 398 Hamner, W.M. See Carlton, J.H., 126 See Omori, M., 134 Hampel, H., 129 Hampson, G.R. See Sanders, H.L., 171 Hampton, J. See Lehodey, P., 467 Hamre, B. See Erga, S.R., 460 Hamren, U., 130 Hanamura, Y., 130 Handa, N. See Goes, J.I., 462 Haneburth, T., 192 Hanelt, D., 462 See Bischof, K., 455 Hannach, G., 319 Hannah, L., 399 Hannemann, A. See Behrenfeld, M., 455 Hannon, B. See Costanza, R., 396, 457 Hansen, J., 462 Hansen, L.J. See Roessig, J.M., 472 Hansen, O.S. See Nielsen, T.G., 192 Hansen, P.J. See Nielsen, T.G., 192 See Pedersen, M.F., 470 Hanson, J.M., 130 Hansson, S., 130 See Hamren, U., 130 See Rudstam, L.G., 135 Harborne, A.R., 463 See Mumby, P.J., 469 Harch, B.D. See Manson, F.J., 468 Hardy, J. See Behrenfeld, M., 455 Hare, C.E. See Hutchins, D.A., 321 Hare, S.R. See Mantua, N.J., 468 Harger, B.W.W. See Lewis, R., 82 See Nyman, M.A., 84 Hargraves, P. See Keller, A.A., 465 Harlay, J. See Engel, A., 460 Harmelin, J.G. See Garrabou, J., 461 See Perez, T., 470

Harmelin-Vivien, M.L. See Salen-Picard, C., 334 Harper, J.L., 168 Harrington, B. See Galbraith, H., 461 Harris, G., 463 See Boersma, D., 307 Harris, G.P., 463 See Thresher, R.E., 474 Harris, G.W. See Procter, T.D., 35 Harris, L.G., 80 Harris, R. See Bonnet, D., 455 Harrison, P.J. See Hurd, C.L., 81 Harrison, P.L. See Babcock, R.C., 454 Harrison, W.G. See Longhurst, A.R., 132 Harrold, C., 80, 319 See Graham, M.H., 79 See Watanabe, J.M., 88 Hartmann, G. See Hartmann-Schröder, G., 319 Hartmann, K. See Hobday, A.J., 464 Hartmann-Schröder, G., 319 Hartnoll, R.G. See Oh, C.W., 133 Harty, C., 463 Harvell, C.D., 463 Harvey, M. See Boyd, P.W., 456 Harwood, K.G. See Frid, C.L.J., 398 Harzhauser, M., 319 Hastings, A. See Botsford, L.W., 307 See Lockwood, D.R., 324 See McCann, K., 133 Hatchwell, B.J. See Votier, S.C., 475 Hatton, C. See Thrush, S.F., 474 Haury, L., 130, 319 Hauser, L. See Gómez-Uchida, D., 317 Hauxwell, J., 399 Hawkes, M.W. See Gabrielson, P.W., 79 Hawkins, S. See Hiscock, K., 464 Hawkins, S.J., See Airoldi, L., 394 See Jonsson, P.R., 465 See Kendall, M.A., 465 See Martin, D., 401 See Mieszkowska, N., 469 See Moschella, P.S., 402 See Sims, D.W., 473 See Southward, A.J., 474 See Thompson, R.C., 404 Hawskworth, D.L. See Harper, J.L., 168 Haxo, F.T. See Neushul, M., 83 Hay, C.H., 80 Haye, P. See Thiel, M., 339 Haye, P.A. See Thiel, M., 199–344 Hayek, L.C., 168 See Buzas, M.A., 166 Hays, C. See Duffy, D., 313 Hays, C.G. See Beck, M.W., 394 Hays, G.C., 130, 463 See Broderick, A.C., 456 See Luschi, P., 467 See McMahon, C.R., 468 Hayward, T., 463

499

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AUTHOR INDEX Hayward, T.L. See Venrick, E.L., 475 Haywood, M.D.E. See Vance, D.J., 475 Head, E.J.H. See Longhurst, A.R., 132 Heads, M.J. See Chin, N.K.M., 76 Heales, D.S. See Vance, D.J., 475 Healy, M.G., 399 Heard, R. See Thiel, M., 339 Heard, R.W. See Price, W.W., 134 Hebbeln, D., .319 See Antia, A.N., 454 See Coloma, C., 311 See González, H.E., 317 See Marchant, M., 325 See Muñoz, P., 329 See Palma, M., 331 Heck, K.L., Jr, 399 See Beck, M.W., 394 See Mattila, J., 132 Hecq, J.H. See Goffart, A., 462 Hector, A. See Purvis, A., 170 Hedgepeth, J.W., 168 Hedges, L.V., 168 See Gurevitch, J., 168 Hedley, R.H. See Buchanan, J.B., 126 Heemann, C. See Engel, A., 460 Heffels, C.M.G., 34 Heidemann, A. See Valdivia, N., 340 Heine, J.N. See Spalding, H., 86 See Spalding, H., 474 Heinemeier, J. See Petersen, K.S., 403 Heino, M. See Byrkjedal, I., 456 Heinrich, A.K., 319 Heinrich, D. See Lotze, H.K., 401 Heip, C.H.R. See Dauwe, B., 127 Heitzmann, D. See Heffels, C.M.G., 34 Helbling, W. See Barbieri, E.S., 454 HELCOM, 399 Hell, R. See Giordano, M., 461 Hellberg, M.E. See Baums, I.B., 307 See Swearer, S.E., 339 Helly, J.J., 319 Helmuth, B., 463 Helmuth, B.S., 80 Hemminga, M.A., 399 Hempel, W.M., 80 See Eardley, D.D., 78 Henderson, P.A. See Bamber, R.N., 125 Hendon, H. See Allan, R., 190 Hennicke, J.C., 319 Hennigar, A.W. See Scheibling, R.E., 473 Henríquez, L.A. See Buschmann, A.H., 308 Henry, E.C., 80 Henry, G.W., 463 See Lyle, J.M., 468 Herbert, R.J. See Mieszkowska, N., 469 Herbold, B. See Feyrer, F., 128 Herbst, L., 463 Herbst, L.H. See Ene, A., 460 Herdiana, Y. See Baird, A.H., 190

Herman, J.S. See MacLeod, C.D., 468 Herman, P.M.J. See Dauwe, B., 127 See Thrush, S.F., 474 Herman, S.S., 130 Hermosilla, C. See Zagal, C., 344 Hermosilla, N. See Jerardino, A., 322 Hernández, C. See Bertrand, A., 307 Hernández, C.E., 319 See Cárdenas, L., 309 See Moreno, R.A., 328 See Poulin, E., 332 Hernández, E. See Narváez, D.A., 329 See Poulin, E., 332 Hernández, E.H., 319 See Castro, L.R., 311 Hernández-Carmona, G., 80, 81 See Edwards, M.S., 78 See Ladah, L.B., 82, 323 Hernández-González, M.C. See Buschmann, A.H., 75, 308 See Muñoz, V., 83, 329 Hernández-Miranda, E., 319 Hernando, M.P., 463 Herrera, G. See Llanos, A., 324 See Llanos-Rivera, A., 324 Herrera, G.A. See Landaeta, M.F., 323 Herrera, L., 319 Herring, S. See Boss, E., 33 Herring, S.G., 34 Herrod-Julius, S. See Galbraith, H., 461 Hertweck, C. See Maier, I., 83 Herzka, S.Z., 319 Hesp, P.A., 192 Hess, S. See Gómez, I., 317 Hessen, D., 463 Hesslein, R.H. See Johannsson, O.E., 130 Hessler, R.R. See Levin, L.A., 169, 324 See Sanders, H.L., 171 Hewavisenthi, S., 463 Hewitt, J.E. See Lohrer, A.M., 467 See Norkko, A., 470 See Thrush, S.F., 171, 474, 475 See Turner, S.J., 404 Heyen, H. See Kroencke, I., 323 Heyward, A. See Negri, A., 469 Heyward, A.J. See Babcock, R.C., 454 Hickey, B.M. See Hill, A.E., 320 Hickey, K.R. See Healy, M.G., 399 Hickling, R., 463 Hicks, J.T. See King, B.R., 466 Hidalgo, P., 320 See Escribano, R., 314 See Fernández, D., 315 See Marín, V.H., 326 Higgins, K. See Botsford, L.W., 307 Hilborn, R., 320 Hildebrandt, H. See Grimm, V., 129 Hill, A.E., 320 Hill, J.K. See Hickling, R., 463 See Parmesan, C., 470

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AUTHOR INDEX Hill, M., 168 Hill, M.O. See Davies, C.E., 396 Hillebrand, H., 34, 168 Hilse, C. See Wilhelm, C., 476 Hilton, M. See Hesp, P.A., 192 Hilton-Taylors, C. See Brooks, T.M., 395 Himmelman, J.H. See Brokordt, K.B., 308 Hines, A.H. See Pearse, J.S., 84 Hinga, K.R., 464 Hinkley, S. See MacNally, R., 169 Hinojosa, I., 320 Hinojosa, I.A. See Macaya, E.C., 83, 325 Hinojosa, L.F., 320 Hirose, T. See Takahashi, K., 136 Hirota, Y., 130 Hirst, A. See Bonnet, D., 455 Hirst, A.C. See Gordon, H.B., 462 See Sarmiento, J.L., 473 Hirst, A.G., 464 Hiscock, K., 399, 464 See Mieszkowska, N., 469 Hitchcock, D.R. See Newell, R.C., 402 Hobart, W.L. See Mackenzie, C.L., Jr, 401 Hobbie, J.E. See Hansson, S., 130 Hobday, A. See Campbell, R.A., 456 See Polacheck, T., 471 Hobday, A.J., 81 See Koslow, J.A., 466 See Poloczanska, E.S., 407–478, 464 Hobson, E.S., 81 Hock, L. See Alpers, W., 190 Hocking, P.J. See Cambridge, M.L., 456 Hockley, N. See Balmford, A., 307 Hodkinson, J. R., 34 Hoedt, F. See Ward, T.M., 476 Hoegh-Guldberg, H., 464 Hoegh-Guldberg, O., 192 See Donner, S.D., 459 See Hoegh-Guldberg, H., 464 See Hughes, T.P., 464 See Jones, R.J., 465 See Kleypas, J.A., 466 See LaJeunesse, T.C., 192 See Poloczanska, E.S., 407–478, 464 See Raven, J., 471 See Walther, G.R., 476 Hoerling, M.P. See Diaz, H.F., 77 Hoffmann, A., 320 See Santelices, B., 334 Hoffmann, A.J., 81, 320 See Avila, M., 75 See Santelices, B., 85 Hoffmann, L. See Engel, A., 460 Hoffmann, R.C., 399 See Lotze, H.K., 401 Hoffmann, S. See Greve, W., 462 Hoffmeyer, M.S., 130 Hofmann, E.E. See Harvell, C.D., 463 Hofmann, G.E., 320

Hogue, V.E., 464 Holben, B.N. See Dubovik, O., 34 See Zhao, T.X.-P., 36 Holberton, R. See Helmuth, B.S., 80 Holbrook, S.J., 81, 464 Holby, O. See Glud, R.N., 317 Holland, G.J. See Webster, P.J., 476 Hollenberg, G.J. See Abbott, I.A., 74 Holley, M.C. See Brown, B.E., 191 Holliday, D.V. See Greenlaw, C.F., 129 See Kringel, K., 131 Holm, P. See Lotze, H.K., 401 Holme, N.A., 168 See Eleftheriou, A., 128 Holmer, M., 399 See Marbà, N., 401 Holmes, K.E. See Harborne, A.R., 463 Holm-Hansen, O. See Mitchell, B.G., 469 Holst, M. See Boulding, E.G., 455 Holt, G.J. See Herzka, S.Z., 319 Holt, R.D. See Leibold, M.A., 323 Holt, S.A. See Herzka, S.Z., 319 Holthuis, L.B. See van der Baan, S.M., 137 Holyoak, M., 130 See Leibold, M.A., 323 Hong, S.Y., 130 Hooff, R. See Shanks, A.L., 86 Hooke, J.M. See Bray, M.J., 395 Hooker, J.D., 81 Hooker, Y. See Lleellish, J., 324 See Lleellish, M., 83 Hoopes, M.F. See Leibold, M.A., 323 Hoovenier, J.W., 34 See Mishchenko, M.I., 35 See Volten, H., 36 Hoozemans, F.M.J. See Nicholls, R.J., 402 Hope, A.S. See Augenstein, E.W., 74 Hopkins, T.L., 130 Hore, J.P., 399 Horgan, E.F. See Brown, H., 126 Hormazábal, S., 320 See Morales, C.E., 328 See Rutllant, J.A., 334 See Santelices, B., 335 See Shaffer, G., 336 See Ulloa, O., 340 See Yuras, G., 344 Horvat, M. See Trombini, C., 404 Horvath, H. See Kocifaj, M., 35 Hoschino, K. See Beck, M.W., 394 Hostens, K., 130 Hostetler, C. See Hu, Y.-X., 34 Houghton, J.D. See Hays, G.C., 463 Houk, J.L. See McCleneghan, K., 83 Howe, M.A., 81 Howell, E.A. See Polovina, J.J., 471 Howell, K.L. See Connor, D.W., 396 Howlett, B.G. See Boulter, S.L., 455 Hu, Y.-X., 34

501

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AUTHOR INDEX Huang, C.Y. See Lee, K.K., 467 Huang, M., 130 Hubbard, D.M. See Dugan, J.E., 313 Hubbell, S.P., 168 Hubbs, C.L. See North, W.J., 84 Hucke-Gaete, R. See Moreno, C.A., 328 Hückstädt, L.A., 320 Hudson, G. See Menge, B.A., 327 Hudson, I.L. See Keatley, M.R., 465 Huesemann, M.H., 464 Huettel, M. See Wild, C., 343 Huffman, D.R. See Bohren, C.F., 33 Huges, T.P. See Jackson, J.B.C., 399 Huggett, C.L. See Levin, L.A., 324 Huggett, J.A. See Verheye, H.M., 342 Hughes, A.R. See Byrnes, J., 75 Hughes, B. See Hernández-Carmona, G., 80 Hughes, D.J. See Davison, D.M., 396 Hughes, J.M.R. See Jones, T.A., 400 Hughes, L., 464 See Beaumont, L.J., 454 See Chambers, L.E., 457 Hughes, R.G., 399 Hughes, T.P., 464 See Pandolfi, J.M., 402, 470 Huisman, J., 464 Hulbert, E.M., 130 Hull, P.G. See Quinby-Hunt, M.S., 36 Hultgren, K.M. See Byrnes, J., 75 Humboldt, A., 320 Humphrey, C. See Negri, A., 469 Hung, C.C. See Hesp, P.A., 192 Hung, O.S. See Chan, B.K.K., 457 Hunt, A.J. See Quinby-Hunt, M.S., 36 Hunt, G.L. See Jahncke, J., 321 Hunt, J.W. See Anderson, B.S., 74 Hunter, C.N. See Martin, J.H., 326 Hunter, F.M. See Votier, S.C., 475 Hunter, J.R., 464 See Porteiro C., 471 Hunter, K.A. See Jickells, T.D., 465 Huntley, B. See Parmesan, C., 470 Huntley, M., 464 Huovinen, P., 321 See Gómez, I., 317 Huovinen, P.J., 81 Hurd, C.L., 81 Hurd, S.D. See Polis, G.A., 332 Hurlbert, A.H., 168 Hurlbert, S., 168 Hurlbert, S.N., 130 Hurrel, J.W. See Trenberth, K.E., 340 Hussain, S.A. See Badola, R., 454 Huston, M. A., 168 Hutchings, L. See Verheye, H.M., 342 Hutchins, D.A., 321 See Sedwick, P.N., 473 Hutchinson, C. See Hannah, L., 399 Hutson, A.M. See Robinson, R.A., 472

Hüttel, M. See Fossing, H., 316 Huybrechts, P. See Church J.A., 457 Huyer, A., 321 See Freeland, H.J., 316 See Grantham, B.A., 318 See Strub, P.T., 338 Hyde, D. See Losey, G.S., 467 Hyder, P., 192 Hylleberg, J. See Janekarn, V., 192

I Ianora, A., 321 Ibanez, F. See Beaugrand, G., 454 Ibáñez, C. See Chong, J., 311 Ibáñez, C.M., 321 Ibáñez, S. See Moreno, C.A., 328 Ibarra-Obando, S.E. See Gonzalez-Fragoso, J., 79 ICES, 399 IFOP, 321 Iglesias-Prieto, R. See Kleypas, J.A., 466 Illanes, J.E., 321 See Thiel, M., 199–344 Ilyasd, M. See McKenzie, R.L., 468 IMARPE, 321 Immonen, A.K. See Markkula, S.E., 468 Inagaki, H. See Ohtsuka, S., 134 Indacochea, A. See Tarazona, J., 339 Inglis, G., 81 Inglis, G.J., 464 Inoue, T., 130 Invers, O., 464 Iotti, M. See See Simonini, R., 404 IPCC, 192, 464 Iratchet, P. See Ortlieb, L., 330 Iriarte, J. See González, H.E., 317 Iriarte, J.L., 321 See González, H.E., 318 See Pizarro, G., 332 See Thiel, M., 199–344 Irribarren, C. See Escribano, R., 314 See Rodríguez, L., 333 Isaac, W.E., 81 Ishida, A. See Orr, J.C., 470 Ishihara, T. See Gao, K., 461 Ishimatsu, A. See Kikkawa, T., 466 Isla, E., 306 Islam, M.S., 399 Ittekkot, V. See Burkett, V., 456 IUCN, 321 Ivankina, E.V. See Both, C., 455 Ivanov, V.V. See Beamish, R.J., 454 Ivesa, L. See Meinesz, A., 401

J Jablonski, D., 169 See Roy, K., 171

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AUTHOR INDEX Jaubert, J.M., 400 Jeans, D.R.G. See Hyder, P., 192 Jefferies, R.L. See Wolters, M., 405 Jeftic, L., 400 Jelinski, D.E. See Mulkins, L.M., 133 See Orr, M., 84 Jeltsch, F. See Grimm, V., 129 Jenkins, G.P. 464 Jenkins, M. See Balmford, A., 394 Jeno, K. See Fernández, M., 315 Jensen, A., 400 Jensen, C. See Lotze, H.K., 401 Jensen, J.N. See Rumohr, H., 171 Jensen, J.R., 81 Jensen, M.H. See Rask, N., 403 Jeon, H. See Keller, A.A., 465 Jeppesen, E. See Aaser, H., 124 Jerardino, A., 322 Jerez, G. See Aviléz, O., 306 Jerling, H.L., 130 Jerlov, N.G., 34, 464 Jernakoff, P., 465 Jesse, S., 322 See Ortiz, M., 330 Jesus, L. See Azeiteiro, U.M.M., 125 Jetten, M.S.M. See Kuypers, M.M., 323 Jeudy de Grissac, A. See Boudouresque, C.F., 395 Jex, E. See Hore, J.P., 399 Ji, Y. See Gao, K.S., 461 Jickells, T.D., 465 Jiménez, J.E. See Buschmann, A.H., 308 Jiménez, M., 322 Jo, S.-G. See Hanamura, Y., 130 See Suh, H.-L., 136 Jodwalis, C.M. See Dunton, K.H., 78 Johannsson, O.E., 130 Johanssen, A. See Brattström, H., 308 Johansson, G., 400 See Eriksson, B.K., 398 Johansson, J. See Wahl, M., 475 Johansson, S. See Hansson, S., 130 See Rudstam, L.G., 135 Johns, D.G. See Edwards, M.J., 459 Johnson, C., 465 Johnson, C.R. See Valentine, J.P., 475 Johnson, D.D., 322 Johnson, D.R., 322 Johnson, E.J. See Leet W.S., 82 Johnson, K.A., 400 Johnson, K.S. See Coale, K.H., 311 Johnson, L.E. See Brawley, S.H., 456 Johnson, N.A. See Rex, M.A., 170 Johnson, T. See Peterson, W.T., 331 Johnson, W.S., 130 Johnston, D.W. See Norse, E.A., 170 Johnston, N.M., 130 Johnstone, I., 192 Johst, K. See Peña T.S., 331

Jackett, D.R. See Gregory, J.M., 462 See Walsh, K.J.E., 476 Jackson, A., 399 Jackson, C.J., 130 Jackson, C.T. See Polis, G.A., 332 Jackson, D. See Báez, P., 306 Jackson, D.G. See Méndez, C.A., 327 Jackson, G. See Ward, T.M., 476 Jackson, G.A., 81 See North, W.J., 84 Jackson, J.B. See Kaufman L., 322 See Pandolfi, J.M., 470 Jackson, J.B.C., 399 See Hughes, T.P., 464 See Lotze, H.K., 401 See Pandolfi, J.M., 402 Jacob, B. See Cuevas, L.A., 312 See Daneri, G., 312 See Troncoso, V.A., 340 Jacobs, J.R. See Potts, D.C., 193 Jacobsen, F.R. See Dean, T.A., 77 Jacobson L.D. See Porteiro C., 471 Jacquemin, B. See Rivalan, P., 472 Jacquet, S. See Engel, A., 460 Jaenicke, L. See Maier, I., 83 Jaffe, J.S. See De Robertis, A., 128 Jagannathan, S. See Makris, N.C., 132 Jahncke, J., 321 Jaklin, A. See Meinesz, A., 401 See Zavodnik, N., 405 Jaksic, F.M. See Castro, S.A., 311 Jakubauskas, M.E. See Su, J.C., 171 James, C. See Strub, P.T., 338 James, D.E. North, W.J., 84 Jameson, G. See Boyd, P.W., 456 Jameson, R.J. See Laidre, K.L., 82 Janekarn, V., 192 See Nielsen, T.G., 192 Janodet, E. See Blasco, F., 455 Janssen, J., 130 Jansson, B.-O., 400 Jantarapagdee, P. See Yesaki, M., 194 Jara, A.F. See Moreno, C.A., 328 Jara, C.G., 321 Jara, F., 321 Jara, H.F., 321 See Moreno C.A., 83 Jaramillo, E., 321, 322 See Contreras, H., 312 See Duarte, C., 313 See Dugan, J.E., 313 See Fernández, M., 315 See McLachlan, A., 326 See Quijón, P., 332 See Stotz, W., 338 Jarre, A. See Cury, P., 312 See Moloney, C.L., 327 Jarvinen, A. See Both, C., 455 Jatczak, K. See Menzel, A., 469

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AUTHOR INDEX Kadyshevich, Ye. A., 34 Kaehler, S., 82 Kaila, L. See Parmesan, C., 470 Kain, J., 322 Kain, J.M., 82 Kaiser, B. See Wilhelm, C., 476 Kaiser, M.J. See Gelcich, S., 317 Kamezaki, N. See Bowen, B.W., 455 Kamykowski, D., 322 Kangas, P., 400 Kaplan, D. See Velázquez, I., 342 Kaplan, D.M., 322 See Wieters, E.A., 343 Kappel, C.V. See Pandolfi, J.M., 470 Karagatzides, J.D. See Mulkins, L.M., 133 Karakassis, I., 169 See Rumohr, H., 171 Karanas, J.J., 465 Karlson, K., 400 Karlsson, L. See Jonzén, N., 465 Karoly, D.J., 465 Karp-Boss, L., 35 See Clavano, W.R., 1–38 Kartawijaya,T. See Baird, A.H., 190 Kaska, D. See Hempel, W.M., 80 Kassem, K. See Burke, L., 396 Kastendiek, J. See Dixon, J., 77 Kathiresan, K., 465 See Moorthy, P., 469 Kaufman L., 322 Kaufmann, R.S., 131 Kaupp, S.E. See Hunter, J.R., 464 Kausch, H. See Köpcke, B., 131 Kautsky, H. See Kautsky, N., 400 Kautsky, L. See Serrão, E.A., 473 Kautsky, N., 400 See Chopin, T., 311 See Pihl, L., 403 Kautsky, U. See Kautsky, N., 400 Kawaguchi, K. See Takahashi, K., 136 Kawahata, H. See Jickells, T.D., 465 Kay, M.C. See Lotze, H.K., 401 Keatley, M.R., 465 Keddy, P.A., 400 Keefer, D.K., 322 Keel, S. See Sayre, R., 335 Kelaher, B.P., 322 Kelfkens, G., 465 Kelleher, G., 400 Keller, A.A., 465 Keller, B.D. See Dayton, P.K., 76 See Dayton, P.K., 313 Kelly, J.C. See Lie, U., 169 Kelly, P.J. See Codispoti, L.A., 311 Kemeny, J.G., 131 Kemp, D.J., 465 Kemp, L. See Druehl, L.D., 78 Kendall, M.A., 465 See Mieszkowska, N., 469

Jokiel, P.L. See Kleypas, J.A., 466 See Shick, J.M., 473 Jokinen, E.M. See Markkula, S.E., 468 Jonasz, M., 34 Jones, A.G. 465 Jones, A.P. See Fish, M.R., 460 Jones, A.R. See Kokhanovsky, A.A., 35 Jones, C.G., 322 Jones, E.G. See Beare, D.J., 454 Jones, G.P. See Swearer, S.E., 339 Jones, J.M., 465 Jones, K. See Ward, T.M., 476 Jones, L.G., 82 See North, W.J., 84 Jones, M.B. See Mees, J., 133 See Moffat, A.M., 133 See Roast, S.D., 135 Jones, N.S. 169 See Gage, J., 167 Jones, R. See Done, T.J., 459 See Galbraith, H., 461 See McEvedy, C., 401 See Negri, A., 469 Jones, R.J., 465 Jones, T.A., 400 Jones, W.R. See Janssen, J., 130 Jonsson, B.G. See Sih, A., 404 Jonsson, P. See Rosenberg, R., 403 Jonsson, P.R., 465 See Airoldi, L., 394 See Moschella, P.S., 402 Jonzén, N., 465 Joos, F. See Orr, J.C., 470 Jordi, A. See Marbà, N., 401 Jorgensen, B. See Wild, C., 343 Jorgensen, B.B. See Fossing, H., 316 See Kuypers, M.M., 323 See Schulz, H.N., 335 Jørgensen, B.B., See Boudreau, B.P., 126 Jorissen, F. See Barmawidjaja, D., 394 Jorissen, F.J. See Pukaric, S.B.G.W., 403 Juhl-Noodt, H., 82 Julian, P.R. See Madden, R.A., 325 Jumars, P.A., 89–138, 131 See Abello, H.U., 124 See Karp-Boss, L., 35 See Kringel, K., 131 See Mayer, L.M., 133 See Penry, D.L., 134 See Taylor, L.H., 137 Jung N. See Bernstein, B.L., 75 Junge, C.E., 34

K Kaartvedt, S., 131 Kabat, P.W., 400

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AUTHOR INDEX Kendrick, G.A. See Goldberg, N.A., 462 See Walker, D.I., 475 Kennedy, F. See Jaramillo, E., 321 Kennedy, H. See Hays, G.C., 130 Kennedy, R.J., 400 Kennelly, S.J., 465 Kenner, M.C., 82 Kennish, M.J., 400 Kenyon, R.A. See Vance, D.J., 475 Keogh, J.A. See Brown, M.T., 75 See Nyman, M.A., 84 Keogh, K.E. See Darling, J.D., 127 Keough, M.J., 322, 466 See Downes, B.J., 77 Kerker, M., 35 Kerr, J. See Vance, D., 475 Kerr, R.A., 322 Kerrigan, R.A. See Clarke, P.J., 457 Kerry, K.R. See Ross, G.J.B., 472 Kerville, S.P. See Campbell, S.J., 456 Keser, M., 466 Kesselmeier, J. See Wilhelm, C., 476 Kester, D.R. 466 Key, R. See Davidson, N.C., 396 Key, R.M. See McNeil, B.I., 469 See Orr, J.C., 470 Khan, P.K., 192 Khokiattiwong, S., 192 Kibirige, I., 131 See Perissinotto, R., 134 Kidwell, S. See Jackson, J.B.C., 399 Kidwell, S.M. See Lotze, H.K., 401 Kiefer, D.A. See Stramski, D., 36 Kienzle, M. See Beare, D.J., 454 Kiflawi, M., 169 Kikkawa, T., 466 Kim, J.Y. See Porteiro C., 471 Kim, K. See Harvell, C.D., 463 Kim, K.-Y. See Suh, H.-L., 136 Kim, S.L., 82, 131, 322 Kimmance, S. See Hiscock, K., 399 Kimmerer, W.J., 131 Kimura, R.S., 82 Kindscher, K. See Su, J.C., 171 King, B.R., 466 Kingsolver, J.G.,See Helmuth, B., 463 Kinlan, B.P., 82, See Broitman B.R., 75 See Reed, D.C., 85 See Siegel, D.A., 336 Kinley, J. See Wahl, M., 475 Kinloch, J.E. See Friedel, M.H., 461 Kinloch, M. See Ward, T.M., 476 Kinzie, R.A. See Buddemeier, R.W., 191 Kiørboe, T. See Visser, A.W., 137 Kirby, M.X. See Jackson, J.B.C., 399 See Lotze, H.K., 401 Kirby, R.R., 466 Kirk, J.T.O., 35

Kirkman, H., 466 Kirkmann, H. See Gerard, V.A., 79 Kirschtel, D. See Hillebrand, H., 34 Kirugara, D. See Wahl, M., 475 Kita, J. See Kikkawa, T., 466 Kitchen, J.C., 35 Kitching, R.L. See Boulter, S.L., 455 Kiyohara, M. See Gao, K., 461 Kjerfve, B.C.D.R. See Morris, J.T., 402 Klaus, R. See Turner, J.R., 194 Klein-MacPhee, G. See Keller, A.A., 465 Kleppel, G.S., 466 Kleypas, J. See Hughes, T.P., 464 See Sarmiento, J.L., 473 Kleypas, J.A., 466 Klingbeil, R. See Leet W.S., 82 Klinger, T., 322 See DeWreede, R.E., 77 Klos, E. See Keller, A.A., 465 Klovaité, K. See Olenin, S., 402 Klueter, A. See Wild, C., 343 Klyashtorin, L. See Beamish, R.J., 454 Knight, A.W. See Sitts, R.M., 136 Knight, T.M. See Sutherland, W.J., 338 Knottnerus, O.S., 400 See Lotze, H.K., 401 Knowlton, N., 466 Knox, G.A., 322 Knudsen, E. See Jonzén, N., 465 Kobayashi, J.-I. See Yamamoto, M., 138 Koch, E. See Menzel, A., 469 Kocifaj, M., 35 Koeve, W. See Antia, A.N., 454 Koh, B.S. See Guizien, K., 318 Kokhanovsky, A.A., 35 Komar, P.D., 35 See Baba, J., 33 Kong, I. See Castilla, J.C., 310 See Ortlieb, L., 330 Konstant, W.R. See Brooks, T.M., 395 Köpcke, B., 131 Kopczak, C.D., 82 Korhs, D.G. See Zimmerman, R.C., 477 Kornfield, I. See Cárdenas, L., 309 See Poulin, E., 332 Kornicker, L.S. See Odum, H.T., 170 Kornilovs, G. See Möllmann, C., 133 Korringa, P., 400 Kortum, G., 322 Koshiishi, Y. See Hirota, Y., 130 Koslow, J.A., 466 See Richardson, A.J., 471 See Thresher, R., 474 Kosro, P.M. See Strub, P.T., 338 Köster, F.W. See Möllmann, C., 133 Kotta, I., 131 Kotta, J. See Kotta, I., 131 Kouassi, E., 131 Kouwenberg, J.H.M., 466

505

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AUTHOR INDEX See Castilla, J.C., 310 See Vargas, C.A., 341 Lagos, S.L. See Dean, T.A., 77 Lagos, V. See Collantes, G., 311 Laidre, K.L., 82 LaJeunesse, T.C., 192 Lake, S., 132 Lakso, A.N. See Wolfe, D.W., 477 Lambeck, K. See Church J.A., 457 Lambshead, P.J.D, 169 See Gage, J., See Paterson, G.L.J., 170 See Ugland, K. I., 172 Lammers, M.O. See Benoit-Bird, K.J., 125 Lamont, P.A. See Levin, L.A., 324 Lampitt, R.S. See Hirst, A.G., 464 Lancellotti, D. See Hinojosa, I., 320 Lancellotti, D.A., 323 See Stotz, W., 338 See Thiel, M., 199–344 Landaeta, M.F., 323 See Castro, L.R., 311 Lande, R., 169 Lane, C.D. See Druehl, L.D., 77 Lane, C.E., 82 Lanfranco, E. See Barbera, C., 394 See Boudouresque, C.F., 395 Langar, H. See Meinesz, A., 401 Langdon, C., 466 See Kleypas, J.A., 466 Langdon, C.J. See Kreeger, K.E., 131 Lange, C.B. See Escribano, R., 314 See Fuenzalida, R., 316 See Jackson, J.B.C., 399 See Milessi, A., 327 See Morales, C.E., 328 See Muñoz, P., 329 Langenbuch, M. See Pörtner, H.O., 471 Langer, M. See Wahl, M., 475 Langhanki, N. See Lotze, H.K., 401 Lankerani, A. See Hannah, L., 399 Lankford, T.E., 132 Laptikhovsky, V., 169 Lapyonok, T. See Dubovik, O., 34 La Rocca, B. See Sfriso, A., 404 Lardies, M.A., 323 Largier, J. See Castilla, J.C., 310 See Narváez, D.A., 329 See Wieters, E.A., 343 Largier, J.L., 323 See Botsford, L.W., 307 See Kaplan, D.M., 322 See Shanks, A.L., 86 See Wing, S.R., 88, 343 Larichev, V.D. See Griffies, S.M., 462 Larkum, A.W.D., 466 See West, R.J., 476 LaRoche, J. See Boyd, P.W., 456 See Jickells, T.D., 465

Kouysoubas, D. See Karakassis, I., 169 Kowalczyk, E.A. See Gordon, H.B., 462 Kozyreff, G. See See van Dalfsen, J. A., 405 Kraemer, G.P. See Chopin, T., 311 Krause-Jensen, D. See Boström, C., 395 Krautz, C. See Escribano, R., 314 Krautz, M.C. See Hückstädt, L.A., 320 Kreeger, D.A. See Kreeger, K.E., 131 Kreeger, K.E., 131 Kremb, S. See Wild, C., 343 Kremer, J.N. See Kopczak, C.D., 82 See Zimmerman, R.C., 88 Kremling, K. See Antia, A.N., 454 Krenz, C. See Menge, B.A., 327 Kringel, K., 131 Kroencke, I., 323 Kruse, V.A. See Lesser, M.P., 467 Krylova, E. See Sellanes, J., 335 Kubilay, N. See Jickells, T.D., 465 Kuffner, I.B., 466 Kuhn, M. See Church J.A., 457 Kuijpers, L. See de Jager, D., 458 Kullberg, J. See Parmesan, C., 470 Kumar, H.D. See Häder, D.P., 462 Kunz, T.J. See Hobday, A.J., 464 See Poloczanska, E.S., 407–478, 466 Kunze, E., 131 Kuosa, H. See Linden, E., 132 See Viherluoto, M., 137 Kura, Y. See Burke, L., 396 Kurashov, V. See Beamish, R.J., 454 Kurihara, H., 466 Kuss, J. See Antia, A.N., 454 Kuver, J. See Fossing, H., 316 Kuypers, M.M., 323

L Labanauskas, V. See Worm, B., 405 Laborel, J. See Boudouresque, C.F., 395 Labra, F.A. See Ojeda, F.P., 330 See Tognelli, M.F., 340 Lacis, A.A. See Mishchenko, M.I., 35 Ladah, L.B., 82, 323 Ladds, P.W. See Adnyana, W., 453 Lafferty, K.D., 82 See Airamè, S., 393 See Behrens, M.D., 75 See Roberts, C.M., 333 See Ward, J.R., 476 Laffoley, D. See Mieszkowska, N., 469 Laffoley, D.D., 400 See Davidson, N.C., 396 Lagardère. J.P., 131 Lagos, N. See Astorga, A., 306 See Correa, J.A., 312 Lagos, N.A., 323 See Camus, P.A., 309

506

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AUTHOR INDEX Larour, M. See Fabri, M.C., 167 Larson, R.J. See Stephens, J.S., Jr, 86 Larsson, C.S. See Lundälv, T., 401 Larsson, U. See Hansson, S., 130 Lasenby, D. See Quirt, J., 134 Lasenby, D.C., 132 Laslo, I. See Zhao, T.X.-P., 36 Lassus, P. See Holmer, M., 399 Last, P.R. See Barrett, N.S., 397 Lastra, M. See Barbera, C., 394 Latif, M. See Allan, R., 190 Latimer, P., 35 Laur, D.R. See Ebeling, A.W., 78 See Harris, L.G., 80 See Hempel, W.M., 80 See Reed, D.C., 85 Laval, B.E. See Hurd, C.L., 81 Lavery, P. See Lemmens, J., 323 Lavik, G. See Kuypers, M.M., 323 Lavín, M.F. See Fiedler, P.C., 316 Lavoie, D.R., 82 Law, C.S. See Boyd, P.W., 456 Law, R. See Dieckmann, U., 128 See Frid, C., 398 See Leibold, M.A., 323 Lawrence, G.A. See Hurd, C.L., 81 Lawrence, J.M., 82 Lawrie, S. See Speirs, D., 136 Lawrie, S.M., 132 See Thrush, S.F., 171 Lawson, G.L., 132 Lawton, J.H. See Jones, C.G., 322 Lea, D.W. See Hansen, J., 462 See Swearer, S.E., 339 See Zacherl, D.C., 344 Leaper, R. See Mieszkowska, N., 469 See Simkanin, C., 473 Lear, D. See Mieszkowska, N., 469 Learmonth, J.A., 466 See MacLeod, C.D., 468 See Robinson, R.A., 472 Lebel, R.R. See Webster, P.J, 194 Leber, K.M., 323 Leblanc, K.W.G. See Syvitski, J.P.M., 36 Lechuga, A. See Hamm, L., 399 Leconte, M. See David, V., 127 Ledoyer, M., 132 Lee, C.E., 323 Lee, H., II. See Behrenfeld, M., 455 Lee, J.Y. See Yoon, H.S., 88 Lee, K.K., 467 Lee, M., 400 Lee, S. See Makris, N.C., 132 Lee Long, W.J. See Carruthers, T.J.B., 457 Leech, D.I. See Robinson, R.A., 472 Leet W.S., 82 LeFaou, Y. See Glemaréc, M., 398 Le Fèvre, J., 323 Lefevre, J.R. See Meinesz, A., 401

Lefevre, N. See González, H.E., 317 See Torres, R., 340 Legakis, A. See Costello, M.J., 167 Legendre, L. See Goffart, A., 462 Legendre, P., 169 Leggett, M.F. See Johannsson, O.E., 130 Leggett, W.C. See Choi, J.S., 126 See Frank, K.T., 129 Lehikoinen, A. See Jonzén, N., 465 Lehikoinen, E., 467 Lehodey, P., 467 Lehtiniemi, M. See Linden, E., 132 Leibold, M.A., 323 Leighton, D.L., 82 Leising, A.W., 132 Leiva, F. See Bertrand, A., 307 Leiva, G. See Narváez, D.A., 329 See Poulin, E., 332 Le Maho, Y. See Ferraroli, S., 460 Lemaire, S. See Ene, A., 460 Le Mao, P., 132 Lemmens, J., 323 Lenhian, H.S. See Jackson, J.B.C., 399 See Lotze, H.K., 401 Lennon, J.J. See Thomas, C.D., 474 Lenz, J. See Ene, A., 460 See Herbst, L., 463 León, R.I., 324 Leonard, G.H., 82 Le Pennect, M. See Moragat, D., 328 Lépez, I. See Acuña, E., 304 Lépez, M.I. See Moreno, C.A., 328 Leslie, H., 324, 400 See Airamè, S., 393 See Menge, B.A., 327 See Roberts, C.M., 333 Lesser, M.P., 467 See Shick, J.M., 473 Lester, R.J.G. See Goggin, C.L., 462 Letelier, J., 324 See Hormazábal, S., 320 See Morales, C.E., 328 Letelier, S., 324 Leterme, S.C. See Edwards, M.J., 459 Leth, O., 324 See Hormazábal, S., 320 Le Tissier, M.D.A. See Brown, B.E., 191 See Scoffin, T.P., 193 Le Treut, H. See Bopp, L., 455 Levin, L. See Arntz, W.E., 306 See Muñoz, P., 329 See Wishner, K.F., 344 Levin, L.A., 169, 324 See DiBacco, C., 313 See Gallardo, V.A., 316 See Gooday, A.J., 318 See Helly, J.J., 319 See Tegner, M.J., 87 Levins, R., 169

507

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AUTHOR INDEX Levitus, S. See Da Silva, A.M., 312 Lewis, A. See Lehodey, P., 467 Lewis, C.V.W. See Miller, C.B., 133 Lewis, M. See Boss, E., 33 Lewis, M.R. See Twardowski, M.S., 36 Lewis, R., 82 Lewis, R.J. See Reed, D.C., 85 Li, N.K., 467 Li, R., See Brawley, S.H., 456 Lichtensztajn, Y.G. See Meltzoff, S.K., 327 Liddicoat, M. See Boyd, P.W., 456 Lie, U., 169 Lieberknecht, L.M. See Connor, D.W., 396 Light, K. See Graham, M.H., 79 See Harrold, C., 80, 319 Lillywhite, P. See MacNally, R., 169 Limbaugh, C. See Feder, H.M., 78 Limburg, K. See Costanza, R., 457 See Costanza, R., 396 Limpus, C.J., 467 See Bowen, B.W., 455 See Loop, K.A., 467 See Marsh, H., 468 Limtrakulvong, V. See Nielsen, T.G., 192 Lin, B. See Hu, Y.-X., 34 Lin, H.-X. See van Dalfsen, J. A., 405 Lindberg, D.R., 83 See Castilla, J.C., 310 Lindeboom, H.J., 401 Lindeman, K.C. See Mumby, P.J., 469 Lindén, A. See Jonzén, N., 465 Linden, E., 132 Linderholm, H.W. 467 Lindley, J.A. See Beaugrand, G., 454 See Kirby, R.R., 466 Lindsay, K. See Orr, J.C., 470 Lindstrom, S.C. See Gabrielson, P.W., 79 Lindström M., 132 Ling, R. See Boyd, P.W., 456 Ling, S. See Johnson, C., 465 Linger, F.I. See Enbysk, B.J., 128 Link, J.S., 132 Linse, K. See Brandt, A., 126 Lipp, E.K. See Harvell, C.D., 463 Lipschultz, F. See Codispoti, L.A., 311 Liqiang, H. See Rhoads, D.C., 471 Lisin, S. See Graham, M.H., 79 See Harrold, C., 80 See Harrold, C., 319 Liss, P, See Raven, J., 471 Liss, P.S. See Jickells, T.D., 465 Lissalde, J-P. See Cornet, M., 127 Litchman, E., 467 Little, C.M. See Donner, S.D., 459 Little, M., 467 Liu, P.C. See Lee, K.K., 467 Liu, S.L., Häder, D., 462 Livingstone, D.R., 324 Llagostera, A., 324

Llanos, A., 324 See Balbontín, F., 306 See Castro, L.R., 311 Llanos-Rivera, A., 324 Lleellish, J., 324 Lleellish, M., 83 Llewellyn, G. See Kaufman, L., 322 See Mumby, P.J., 469 Lluch-Cota, S.E. See Chávez, F.P., 311, 457 Lo, K. See Hansen, J., 462 Lobban, C.S., 83 See Barrales, H.L., 75 See Schmitz, K., 86 Locarnini, R.A. See Conkright, M.E., 311 Lock, K., 132 Lockwood, D.R., 324 Loeb, V.J., 324 Loeng, H. See Frid, C., 398 Loew, E.R. See Losey, G.S., 467 Logan, B.W., 467 Loh, W.K.W. See LaJeunesse, T.C., 192 Lohr, M. See Wilhelm, C., 476 Lohrer, A. See Thrush, S.F., 474 Lohrer, A.M., 467 Lohse, D. See Hannah, L., 399 Loke Ming, C. See Hesp, P.A., 192 Lombardo, M. See Trombini, C., 404 Lomolino, M.V. See Brown, J.H., 308 Loneragan, N. See Abal, E.G., 453 Loneragan, N.R., 467 See Manson, F.J., 468 See Vance, D.J., 475 Long, D. See Roberts, J.M., 472 Long, S.P. See Ainsworth, E.A., 453 Long, W.J.L. See Preen, A.R., 471 Longhurst, A.R., 132 Longstaff, B.J. See Carruthers, T.J.B., 457 Lonhart, S.I. See Zacherl, D., 477 Lonsdale, P.F. See Genin, A., 461 Loop, K.A., 467 Lopatin, V.N. See Shepelevich, N.V., 36 López, C. See Stotz, W., 338 López, C.A., 324 Lopez, M.D.G. See Huntley, M., 464 Lopez Cazorla, A.C. See Sardiña, P., 135 López Gappa, J.J. See Orensanz, J.M., 134 López-Urrutia, A. See Bonnet, D., 455 Loreau, M. See Leibold, M.A., 323 Loschnigg, J.P. See Webster, P.J, 194 Losey, G.S., 467 Losos, E. See Wilcove, D.S., 405 Lostaunau, N. See Codispoti, L.A., 311 Lothrop, S.K., 324 Lotsberg, J.K. See Erga, S.R., 460 Lotze, H. See Schories, D., 403 Lotze, H.K., 401 See Wahl, M., 475 See Worm, B., 405, 477 Lough, J. See Done, T.J., 459

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AUTHOR INDEX Macchiavello, J.E. See Bulboa, C.R., 308 See Edding, M., 313 See Macaya, E.C., 83, 325 MacDonald, B.A., 325 MacDonald, I. See Norkko, A., 470 MacDonald, J.B. See Twardowski, M.S., 36 Mace, G.M., 169 Machias, A. See Karakassis, I., 169 Maciolek, N.J. See Grassle, J.F., 168 Macke, A., 35 Mackenzie, C.L., Jr, 401 Mackie, A.S.Y., 169 Mackinson, S. See Okey, T.A., 470 Macko, S.A. See Mayer, L.M., 133 MacLeod, C.D., 468 See Learmonth, J.A., 466 See Robinson, R.A., 472 MacNally, R., 169 Maconochie, J.R. See Friedel, M.H., 461 Macpherson, E. See Martin, D., 401 Macquart-Moulin, C., 132 See Champalbert, G., 126 Madden, R.A., 325 Madec, G. See Bopp, L., 455 Madhaven, B.B., 192 Madin, L.P. See Brown, H., 126 Madronich, S., 325 Madsen, F.J., 325 Madsen, H. T. See van Dalfsen, J. A., 405 Måge, F. See Menzel, A., 469 Maggs, C.A. See Wilson, S., 405 See Birkett, D.A., 395 Magin, G. See Brooks, T.M., 395 Magnusson, J.B. See Bokn, T.L., 395 Magoulas, A. See Cárdenas, L., 309 Magurran, A.E., 169 Mahan, L.C. See Dayton, P.K., 76 Mahmoudi, B. See Okey, T.A., 470 Mahnken, C. See Beamish, R.J., 454 Mahowald, N. See Jickells, T.D., 465 Mahyiddin, D. See Baird, A.H., 190 Maidment, D. See Dunton, K., 313 Maier, I., 83 See Müller, D.G., 83 See Westermeier, R., 343 Maier-Reimer, E. See Orr, J.C., 470 Majkowski, J., 468 Majluf, P., 325 Makino, H. See Yamamoto, M., 138 Makris, N.C., 132 Maldonado, A., 325 Maldonado, M.T. See Boyd, P.W., 456 Malinarich, A. See Sielfeld, W., 336 Manley, S.L. See Arnold, K.E., 74 See North, W.J., 84 Mann, G., 325 Mann, K.H., 83 See Friesen, J.A., 129 See Gerard, V.A., 79

Lough, J.M., 192, 467 See Hughes, T.P., 464 Loureau, M., 169 Loureiro, M. See Rodríguez-Graña, L., 333 Love, M. See Stephens, J.S., Jr, 86 Lovengreen, C. See Gómez, I., See Huovinen, P., 321 Low, P.J. See Perry, A.L., 470 Lowe, J.A. See Gregory, J.M., 462 Lowry, J.K. See Koslow, J.A., 466 Lowry, L.F., 132 Lowry, R.R. See Kreeger, K.E., 131 Lozan J.L., 401 Lubchenco, J., 169 See Grantham, B.A., 318 See Leslie, H., 324 See Menge, J., 327 See Roberts, C.M., 333 Lucas, M.I. See Attwood, C.G., 74 Lucic, D. See Bonnet, D., 455 Ludynia, K., 324 Luikart, G. See Sih, A., 404 Lumb, C.M., 401 Lumsden, L.F. See MacNally, R., 169 Luna-Jorquera, G., 325 See Ellenberg, U., 314 See Guerra, C., 318 See Ludynia, K., 324 See Marín, V.H, 326 See Mattern, T., 326 See Simeone, A., 337 See Thiel, M., 199–344 See Weichler, T., 343 Lundälv, T., 401 Lundberg, B. See Boudouresque, C.F., 395 Lunecke, K.M. See Moreno, C.A., 328 Lüning, K., 83, 325, 401 Lürling, M. See Schippers, P., 473 Luschi, P., 467 Luther, H. See Kangas, P., 400 Luther, M.E. See Potemra, J.T., 193 Luxoro, C. G. See Thiel, M., 199–344 Lyle, J.M., 468 See Henry, G.W., 463 See Welsford, D.C., 476 Lynch, D.R. See Miller, C.B., 133 Lyne, V. See Harris, G.P., 463

M Maasch, K.A. See Sandweiss, D.H., 334 MacArthur, R.H., 169 Macaya, E. See Hinojosa, I., 320 See Thiel, M., 199–344 Macaya, E.C., 83, 325 MacCallum, I., 35 Macchiavello, J., 325 See Edding, M., 313

509

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AUTHOR INDEX Manning, M. See de Jager, D., 458 Manriquez, P.H., See Thiel, M., 199–344 Manríquez, K. See Palma, A.T., 331 Manríquez, P.H., 325 See Vargas, C.A., 341 See Zacherl, D.C., 344 Manríquez, R. See Escribano, R., 314 Manson, F.J., 468 See Loneragan, N.R., 467 Mantua, N.J., 468 Manzanera, M. See van Dalfsen, J. A., 405 Mao, C. X. See Colwell, R.K., 167 Marbà, N., 401 See Diaz-Almela, E., 458 See Duarte, C.M., 459 Marchand, M. See Nicholls, R.J., 402 Marchant, M., 325 See Coloma, C., 311 See González, H.E., 317 See Hebbeln, D., 319 Marchesiello, P., 325 Marchetti, R., 401 Marchinko, K.B., 468 See Arsenault, D.J., 454 Marchioretti, M. See Jaubert, J.M., 400 Marcogliese, D.J. See Jackson, C.J., 130 Marcos, C. See Salas, F., 171 Marcos, R. See Gutierrez, A., 80 See Gutierrez, A., 319 Marcos-Ramirez, R. See Aguilar-Rosas, L.E., 74 Marcovaldi, M.A. See Godfrey, M.H., 462 Marcus, N.H., 325 Mardal, W. See Moller, A.P., 469 Margalef, R., 169 Marin, V. See Giraldo, A., 317 See Moreno, C.A., 328 See Thiel, M., 199–344 Marín, V.H, 325, 326 See Escribano, R., 314 See González, A., 317 See Rojas, P.M., 333 Marincovich, L., Jr, 326 Mark, F. See Brante, A., 308 Markkula, S.E., 468 Marocco, R. See Bondesan, M., 395 Marques, J.C. See Azeiteiro, U.M.M., 125 See Salas, F., 171 Marquet, P. See Alvarado, J.L., 305 Marquet, P.A., 326 See Fernández, M., 315 See Santelices, B., 335 See Santoro, C.M., 335 See Tognelli, M.F., 340 See Valdovinos, C., 172, 340 Marra, P.P., 468 Marsac, F. See White, W.B., 476 Marsaleix, P. See Guizien, K., 318 Marsh, H., 468 Marsh, T.D. See Beck, M.W., 395

Marshall, N.J. See Losey, G.S., 467 Marshall, P. See Hughes, T.P., 464 Martens, P. See Kelfkens, G., 465 Martin, C. See Levin, L.A., 324 Martin, D., 401 See Airoldi, L., 394 Martin, J.H., 326 Martin, M. See Anderson, B.S., 74 Martínez, D. See Stotz, W., 338 Martínez, E.A., 326 See Faugeron, S., 315 Martínez, G., 326 Martinez, N.D. See Dunne, J.A., 128 Martínez, P., 326 See Poulin, E., 332 See Marbà, N., 401 See Vargas, C.A., 341 Martínez, V. See Ahumada, R., 305 Marty, G. See Delille, D., 313 Marubini, F. See Langdon, C., 466 Mas, J. See Badalamenti, F., 394 Mascia, M., 326 Mason, C.F., 468 Masotti, I. See Rutllant, J.A., 334 Massuti, C. See Delgado, O., 396 Massuti-Pascual, E. See Meinesz, A., 401 Masuero, A. See Lagos, N., 323 Matano, R.P. See See Mesías, J.M., 327 Matear, R. See Orr, J.C., 470 See Poloczanska, E.S., 407–478 See Sarmiento, J.L., 473 Matear, R.J. See McNeil, B.I., 469 Matern, S.A. See Feyrer, F., 128 Matranga, V. See Bonaventura, R., 455 Matsuhiro, B. See Vásquez, J.A., 341, 342 Matsumoto, G.I., 132 Matsuoka, M. See Hanamura, Y., 130 Matsuura Y. See Porteiro C., 471 Matsuzawa, Y. See Sato, K., 473 Mattern, T., 326 See Ellenberg, U., 314 Mattila, J., 132 Mattison, J.E., 83 Maucher, J.M. See Hutchins, D.A., 321 Mauchline, J., 132 Maudire, G. See Fabri, M.C., 167 Maurer, D., 133Maurer, B.A., 169 Mauri, M. See Simonini, R., 404 Maxwell, J.G.H., 468 May, R.M., 169 See Gage, J., 167 Mayer, L.M., 133 Mayes, C. See Druehl, L.D., 78 See Lane, C.E., 82 Mayhoub, H. See Boudouresque, C.F., 395 Mayor, S. See Gutiérrez, D., 319 Mazza, J. See Brunet, M., 126 McAllan, I.A. See Beaumont, L.J., 454 McAllister, D. See Burke, L., 396

510

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AUTHOR INDEX McArdle, D. See Pandolfi, J.M., 402 See Roberts, C.M., 333 See Airamè, S., 393 McArthur, L.C., 468 McCann, K., 133 See Rooney, N., 135 McCann, K.S. See Vadeboncoeur, Y., 137 McClain, C.R. See Rex, M.A., 170 McClanahan, T. See Defeo, O., 313 McClean, C.J. See Balmford, A., 307 McCleery, R.H. See Votier, S.C., 475 McClenachan, L. See Pandolfi, J.M., 402 McCleneghan, K., 83 McComb, A.J. See Walker, D.I., 475 McConnaughey, T., 133 McConnico, L., 83 McCrary, M.D. See Dugan, J.E., 313 McCulloch, A. See Shanks, A.L., 336 McDarby, J. See See van Dalfsen, J. A., 405 McDougall, K. See Mullins, H.T., 329 McDougall, T.J. See Walsh, K.J.E., 476 McEvedy, C., 401 McFarland, W.N. See Losey, G.S., 467 McFarlane, G.A. See Beamish, R.J., 454 McGarvey, R. See Ward, T.M., 476 McGehee, D.E. See Greenlaw, C.F., 129 McGill, H., 170 McGowan, J. See Roemmich, D., 472 McGowan, J.A., 468 See Haury, L.R., 319 See Venrick, E.L., 475 McGrath, D. See Simkanin, C., 473 McGregor, J.L. See Gordon, H.B., 462 McInnes, K. See Pittock, A.B., 470 McInnes, K.L. See Walsh, K.J.E., 476 McInnis, H. See Sandweiss, D.H., 334 McKay, R.M. See Boyd, P.W., 456 McKee, D. See MacCallum, I., 35 McKenzie, E. See Beare, D.J., 454 McKenzie, L.J. See Campbell, S.J., 456 See Carruthers, T.J.B., 457 McKenzie, R.L., 468 See Madronich, S., 325 McKinnon, A.D. 468 See Alongi, D.M., 453 McLachlan, A., 326 See Brown, A.C., 395 See Defeo, O., 313 McLachlan, J. See Avila, M., 306 McLaren, I. See Escribano, R., 314 McLean, J.H., 83 McLean, S.R. See Gaylord, B., 79 McLeay, L. See Ward, T.M., 476 McLoughlin, K. See Caton, A.., 457 McMahon, C.R., 468 McManus, G.B. See Peterson, W.T., 331 McManus, J.W., 192 McMillan, C., 469 McNeil, B.I., 469

McPeak, R.H., 83 See Aguilar-Rosas, L.E., 74 See Barilotti, D.C., 75 McQuaid, C.D. See Attwood, C.G., 74 See Kaehler, S., 82 See Perissinotto, R., 84 See Teske, P.R., 339 McQuoid, M., 469 McRoy, C.P. See McConnaughey, T., 133 McShane, P.E., 469 McWilliams, J.C. See Marchesiello, P., 325 See Shchepetkin, A.F., 336 Mecum, W. See Orsi, J.J., 134 Medina, M., 326 Medina, R. See Minello, T., 402 Medina-Elizade, M. See Hansen, J., 462 Medrano, S. See Carrasco, F.D., 309 Meehl, G.A. See Cubasch, U., 458 Mees, J., 133 See Beyst, B., 125 See Dewicke, A., 128 See Hostens, K., 130 See Lock, K., 132 Meesters, E.H. See Bak, R.P.M., 190 Meier, O.W. See Porter, J.W., 471 Meinesz, A., 401 See Boudouresque, C.F., 395 Meir, E., 327 Meland, K. See Brattegard, T., 126 Meltzoff, S.K., 327 Mena, O. See Sánchez, M., 334 Méndez, C.A., 327 Mendo, J. See Arntz, W.E., 306 See Pauly, D., 331 See Stotz, W., 338 See Wolff, M., 344 Meneses, I., 327 See González, J., 318 See Santelices, B., 335 See Vega, J.M.A., 342 Menge, B.A., 327 See Connolly, S.R., 311 See Grantham, B.A., 318 See Leslie, H., 324 See Russell, R., 171 Menge, D.N.L. See Menge, B.A., 327 Menkhorst, P.W. See Ross, G.J.B., 472 Menzel, A., 469 See Walther, G.R., 476 Menzies, R.J., 327 Merino, A. See Collantes, G., 311 Merino, G.E. See von Brand, E., 343 Mesías, J.M., 327 See Strub, P.T., 338 Messner, U., 401 Mestre, A. See Menzel, A., 469 Metcalfe, J.D. See Hays, G.C., 463 Metcalfe, N.B. See Both, C., 455 Metillo, E.B., 133

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AUTHOR INDEX Metz, J.A.J. See Dieckmann, U., 128 Mews, M. See Orr, M., 84 Meyer, C.A. See Okey, T.A., 470 Meyer, C.P. See Castilla, J.C., 310 Meyer-Rochow, V.B. See Lindström M., 132 Meyers, G. See Harris, G.P., 463 Meza, J. See Simeone, A., 337 Mianzan, H.W. See Schiariti, A., 135 Michaelidis, B., 469 Michaels, M. See Simeone, A., 337 Micheli, F., 327 See Harborne, A.R., 463 See Pandolfi, J.M., 470 Middelboe, A.L., 401 Middelburg, J.J. See Dauwe, B., 127 See Duarte, C.M., 459 Mie, G., 35 Mieszkowska, N., 469 See Simkanin, C., 473 Mikolajewicz, U. See Sarmiento, J.L., 473 Milazzo, M., 402 Milessi, A., 327 Miller, C.B., 133 See Crain, J.A., 127 Miller, J. See Shanks, A.L., 336 Miller, J.D. See Loop, K.A., 467 Miller, K. See Johnson, C., 465 See Roughgarden, J., 333 Miller, M.W. See Baums, I.B., 307 Milliman, J.D., 469 Mills, E.L., 170 Milne, A. See Clarke, R.B., 166 Milne, D.J. See Bowman, D.M.J.S., 456 Milton, D.A. See Poloczanska, E.S., 407–478 Mimura, N. See Burkett, V., 456 Minamikawa, S. See Sato, K., 473 Mincks, S. See Smith, C.R., 337 Minello, T., 402 Minello, T.J. See Beck, M.W., 394 Minghelli-Roman, A. See Jaubert, J.M., 400 Miralto, A. See Ianora, A., 321 Miranda, A. See Bonnet, D., 455 Miranda, C., 327 Miranda-Esquivel, D.R. See Posadas, P., 170 Mishchenko, M.I., 35 See Macke, A., 35 See Dubovik, O., 34 Mitchell, B.G., 469 See Graham, M.H., 80 Mitchell, C.E. See Harvell, C.D., 463 Mitchell, R. See Davidson, N.C., 396 Mitchum, G.T. See Polovina, J.J., 471 Mittermeier, C.G. See Brooks, T.M., 395 Mittermeier, R.A. See Brooks, T.M., 395 Mobley, C.D., 35 Mock, G., 402 Modarressie, R., 469

Moe, R.L., 83 Moenne, A. See Correa, J.A., 312 Moffat, A.M., 133 Moffat, C. See Figueroa, D., 316 Moffitt, R.B. See Polovina, J.J., 471 Mohammadian, M.A. See Johannsson, O.E., 130 Mohan, B.K. See Madhaven, B.B., 192 Molinero, J.C. See Bonnet, D., 455 Molis, M. See Valdivia, N., 340 See Wahl, M., 475 Moller, A.P., 469 Moller, I. See Wolters, M., 405 Möller, P. See Westermeier, R., 88 Möllmann, C., 133 Moloney, C.L., 327 See Botsford, L.W., 307 Monaghan, P. See Furness, R., 316 Monfray, P. See Bopp, L., 455 See Orr, J.C., 470 See Sarmiento, J.L., 473 Montanari, G. See Simonini, R., 404 Montecino, V., 327 See Pizarro, G., 332 See Rutllant, J.A., 334 See Strub, P.T., 338 Montecinos, A., 328 Montenegro, C. See Quiroz, J.C., 332 Montero, P. See Cuevas, L.A., 312 See Daneri, G., 312 See Troncoso, V.A., 340 Montoya, J.M., 133 Montu, M.A. See Gama, A.M. da S., 129 Mooj, W.M. See Grimm, V., 129 Moore, A.M. See Webster, P.J, 194 Moore, C. See Latimer, P., 35 Moore, D.R. See Thomas, L.P., 474 Moore, F.R. See Marra, P.P., 468 Moore, J.C. See Rooney, N., 135 Moore, J.D. See Vilchis, L.I., 475 Moore, L.B., 83 Moore, L.R., 469 Moore, M.V. See Smith, S.L., 136 Moore, P. See Mieszkowska, N., 469 Moore, P.G., 328 See Barbera, C., 394 See Donnan, D.W., 397 See Hall-Spencer, J.M., 399 Moorthy, P., 469 Mora, J. See Barbera, C., 394 Moraga, J., 328 See Acuña, E., 305 See Valle-Levinson, A., 341 See Weichler, T., 343 Moragat, D., 328 Morales, C. See Bernal, P.A., 307 See Grünewald A., 318

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AUTHOR INDEX Morales, C.E., 328 See Böttjer, D., 307 See Escribano, R., 314 See Hidalgo, P., 320 Morales, E.G., 328 Morales, V. See Gómez, I., 317 See Huovinen, P., 321 Moran, S., 133 Moreira, M.H. See Cunha, M.R., 127 Morel, A., 35 See Bricaud, A., 33 See Stramski, D., 36 Morel, F.M.M. See Palenik, B., 470 See Rich, H.W., 471 See Riebesell, U., 472 See Tortell, P.D., 475 Moreno, C. See Buschmann, A.H., 308 Moreno, C.A., 83, 328 See Buschmann, A.H., 75 See Castilla, J.C., 76 See Duarte, W.E., 313 See Fernández, M., 315 See Jara, F., 321 See Jara, H.F., 321 See Marín, V.H., 326 See Zamorano, J.H., 344 Moreno, R.A., 328, 329 See Hernández, C.E., 319 See Sepúlveda, R., 336 Moretti, R. See Ene, A., 460 Morgan, L. See Guinotte, J.M., 462 Morgan, L.E. See Wing, S.R., 343 Morgan, S.G. See Swearer, S.E., 339 Morgigni, M. See Sandulli, R., 403 Morri, C. See Sandulli, R., 403 Morris, D.W., 133 Morris, J.T., 402 Morris, P.M. See Stephens, J.S., Jr, 86 Morrison, W. See Thessen, A.E., 474 Morrow, J.H. See Jaubert, J.M., 400 Mortensen, P.B. See Roberts, J.M., 472 Moschella, P.S., 402 See Airoldi, L., 394 See Benedetti-Cecchi, L., 395 See Jonsson, P.R., 465 See Martin, D., 401 See Mieszkowska, N., 469 Moseley, M.E. See Keefer, D.K., 322 Moss, D. See Davies, C.E., 396 Mouchet, A. See Orr, J.C., 470 Mouchot, M.C. See Belsher, T., 75 Mouny, P., 133 See Dauvin, J.-C., 127 See Zouhiri, S., 138 Mouquet, N. See Leibold, M.A., 323 Mouritsen, K.N., 469 Moverley, J. See Edgar, G.J., 459

Moy, C.M., 329 Moy, F.E. See Bokn, T.L., 395 Moyano, H., 329 See Castilla, J.C., 310 See Desqueyroux, R., 313 Moyle, P.B. See Feyrer, F., 128 MPA Global, 402 Mrosovsky, N., 469 See Glen, F., 461 See Godfrey, M.H., 461 462 See Yntema, C.L., 477 Muck, P. See Pauly, D., 331 Mueller, E. See Downs, C.A., 191 Mueller, H. See Furukawa, K., 461 Muinonen, K. See Macke, A., 35 Muir, P.R. See Wallace, C.C., 194 Mujica, A. See Acuña, E., 304 Mukminin, A. See Baird, A.H., 190 Mulkins, L.M., 133 Müller, A.M. See Wilhelm, C., 476 Müller, D.G., 83 See Maier, I., 83 See Westermeier, R., 343 Müller, H. See Müller, D.G., 83 Mullineaux, L. See Wishner, K.F., 344 Mullins, H.T., 329 Mulvihill, R.S. See Marra, P.P., 468 Mumby, P.J., 469 See Harborne, A.R., 463 Munda, I.M., 402 Munday, B.W. See Ball, B.J., 394 Munilla, T. See San Vicente, C., 135 Muñiz, L. See Ramorino, L., 333 Munk, P. See Nielsen, T.G., 192 Muñoz, A.A. See Ojeda, F.P., 330 Muñoz, C. See Palma, A.T., 331 Muñoz, G. See Hernández, C.E., 319 Muñoz, I., 329 Muñoz, J. See Simeone, A., 337 Muñoz, M., 329 Muñoz, O. See Hoovenier, J.W., 34 Muñoz, P., 329 See Avaria S., 306 See Thiel, M., 199–344 Munoz, V., 83, 329 See Gutierrez, A., 80, 319 Munoz-Schick, M. See Castro, S.A., 311 Murano, M. See Hanamura, Y., 130 Murawski, S.A. See Fogarty, M.J., 129 Murdoch, R. See Boyd, P.W., 456 Murphy, G.I. See Majkowski, J., 468 Murphy, J.J. See Lyle, J.M., 468 Murray, J., 170, 329 Murray, S.N. See Bokn, T.L., 395 See Fain, S.R., 78 Murty, V.S.N. See Varkey, M.J., 194 Mustapha, K.B. See Meinesz, A., 401

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AUTHOR INDEX Neill, P.E., 329 See Castilla, J.C., 310 Neira, C., 329 See Arntz, W.E., 306 See Gutiérrez, D., 319 See Muñoz, P., 329 See Sellanes, J., 335, 336 Neira, S., 330 See Arancibia, H., 305 See Moloney, C.L., 327 Nejstgaard, J. See Engel, A., 460 Nelson, C.S. See Bakun, A., 306 Nelson, D.J. See Friedel, M.H., 461 Nelson, P.A. See Losey, G.S., 467 Nemerson, D.M., 133 Neori, A. See Chopin, T., 311 Nero, R.W. See Makris, N.C., 132 Nerzic, R. See Hyder, P., 192 Neshyba, S. See Silva, N., 337 Neuer, S. See Antia, A.N., 454 Neushul, M., 83 See Amsler, C.D., 74 See Dawson, E.Y., 76 See Lewis, R., 82 See Lüning, K., 83 See Nyman, M.A., 84 See Reed, D.C., 85 Neville, C.M. See Beamish, R.J., 454 Newberger, P.A. See Enfield, D.B., 314 Newell, R.C., 402 Newland, C. See Haury, L., 130 Newman, M.J.H. See Pandolfi, J.M., 402 Newman, W.A. See Hinojosa, I., 320 Nhuan, M.T. See Church J.A., 457 Ni, J.F. See Guzman-Speziale, M., 191 Nicholls, N. See Allan, R., 190 See Limpus, C.J., 467 Nicholls, P.E. See Thrush, S.F., 475 Nicholls, R.J., 402 Nichols, P.D. See Thresher, R.E., Nicholson, N.L., 84 Nickell, T.D. See Narayanaswamy, B.E., 170 Nielsen, J. See Jernakoff, P., 465 Nielsen, K.J., 330 See Grantham, B.A., 318 See Wieters, E.A., 343 Nielsen, L.P. See Fossing, H., 316 Nielsen, T.G., 192 Niemi, Å. See Kangas, P., 400 Nietch, C.T. See Morris, J.T., 402 Nieto, K. See Silva, C., 337 See Yáñez, E., 344 Nilsen, K.J. See Rhoads, D.C., 471 Nilsson, C. See Harris, G., 463 Nilsson, H.L. See Attramadai, Y.G., 125 See Lindström M., 132 Nilsson, J., 402 See Choo, K.S., 457

Myers, A. See Simkanin, C., 473 Myers, R.A. See Worm, B., 477 Myers, R.F., 192 Myerscough, P.J. See Clarke, P.J., 457

N Naeem, S. See Costanza, R., 396, 457 Naganuma, N. See Hirota, Y., 130 Nagelkerken, I. See Dorenbosch, M., 459 Nagy, K.L. See Bickmore, B.R., 33 Naito, Y. See Sato, K., 473 Najjar, R.G. See Orr, J.C., 470 Nakanishi, A. See Arana, P., 305 Narayanaswamy, B.E., 170 Narváez, D. See Poulin, E., 332 Narváez, D.A., 329 See Piñones, A., 332 See Vargas, C.A., 341 Narvarte, M.E., 329 Nash, R.D.M. See Oh, C.W., 133 Nash, S.B. See Duke, N.C., 459 Nast, J. See Greve, W., 462 National Research Council, 170 Navanete, S.S. See Valdovinos, C., 172 Navarrete, S. See Castilla, J.C., 310 See Kaplan, D.M., 322 See Marquet, P.A., 326 Navarrete, S.A., 329 See Aiken, C., 305 See Broitman, B.R., 308 See Fernández, M., 315 See Lagos, N.A., 323 See Manríquez, P.H., 325 See Martínez, P., 326 See Menge, B.A., 327 See Narváez, D.A., 329 See Neill, P.E., 329 See Nielsen, K.J., 330 See Piñones, A., 332 See Poulin, E., 332 See Thiel, M., 199–344 See Valdovinos, C., 340 See Vargas, C.A., 341 See Velázquez, I., 342 See Wieters, E.A., 343 Navarro, J. See Jaramillo, E., 322 Navarro, J.C., 133 Navarro, J.M. See Gajardo, G., 316 Navea, M. See Alarcón, E., 305 Neale, P.J. See Litchman, E., 467 Neckles, H.A. See Short, F.T., 473 Neefus, C. See Chopin, T., 311 Neff, J.M., 133 Negri, A., 469 Nehring, D., 402 Neil, D.M., 133 Neill, P.A. See Moreno, R.A., 329

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AUTHOR INDEX O’Farrell, S.P. See Gordon, H.B., 462 See Gregory, J.M., 462 Ogden, J. See Boersma, D., 307 Ogden, J.C. See Pandolfi, J.M., 470 Oh, C.W., 133 See Hong, S.Y., 130 O’Hara, T. See Koslow, J.A., 466 O’Hara, T.D., 470 Ohme, U. See Santelices, B., 335 Ohtsuka, S., 134 Oikari, A.O.J. See Huovinen, P.J., 81 Ojeda, B. See Sandweiss, D.H., 334 Ojeda, F.P., 84, 330 See Angel, A., 305 See Cárdenas, L., 309 See Fariña, J.M., 315 See Fernández, M., 315 See Hernández-Miranda, E., 319 See Palma, A.T., 330, 331 See Poulin, E., 332 See Pulgar, J.M., 332 See Santelices, B., 85, 335 See Vásquez, J.A., 87, 341 Okaji, K. See Brodie, J., 456 Okey, T.A. See Hobday, A.J., 464 See Poloczanska, E.S., 407–478, 470 Oldfield, S. See Brooks, T.M., 395 Oldham, R.D., 192 Olenin, S., 402 See Reise, K., 403 Olesen, B. See Marbà, N., 401 Oliger, P., 330 Oliva, D. See Bernal, P.A., 307 Olivares, C. See Radashevsky, V.I., 332 Olivares, G., 330 See Escribano, R., 314 See Marín, V.H., 326 Olivares, G.R. See Marín, V.H., 326 Olivares, J. See Valle-Levinson, A., 341 Oliver, J., 470 Oliver, J.K. See Babcock, R.C., 454 Oliver, J.S. See Kim, S.L., 131 Oliver, P.G. See Mackie, A.S.Y., 169 Olivieri, R.A., 330 Olkin, I. See Hedges, L.V., 168 Olsgard, F., 170 See Somerfield, P.J., 171 Olyarnik, S.V. See Byrnes, J., 75 Omori, M., 134 Onbe, T. See Ohtsuka, S., 134 O’Neal, J.P. See Mattila, J., 132 O’Neill, R.V. See Costanza, R., 396, 457 Ong, J.E. See Ewel, K.C., 460 Opdyke, B.N. See Kleypas, J.A., 466 Oppenheimer, M. See Donner, S.D., 459 Ord, D.C. See Hempel, W.M., 80 Orel, G. See Caressa, S., 396 Orensanz, J.M., 134 See González, J., 318

Niquen, M. See Alheit, J., 305 See Chavez, F.P., 311, 457 See Porteiro C., 471 Nisbet, R.M., 84 Nivet, C., 402 Noakes, D.J. See Beamish, R.J., 454 Noda, A. See Cubasch, U., 458 Nodder, S. See Boyd, P.W., 456 Noguchi, G.E. See Evans, M.S., 128 Norall, T. See Grove, R.S., 462 Norambuena, R. See Santelices, B., 335 Nordli, Ø. See Menzel, A., 469 Norici, A. See Giordano, M., 461 Norkko, A., 470 See Thrush, S.F., 474 475 Norkko, J. See Norkko, A., 470 Norman, F.I. See Bunce, A., 456 See Ross, G.J.B., 472 Norse, E.A., 170 See Watling, L., 405 North, W.J., 84 See Anderson, E.K., 74 See Gonzalez-Fragoso, J., 79 See Wheeler, P.A., 88 Northen, K.O. See Connor, D.W., 396 Norton, T.A., 84 Nothig, E.M. See González, H.E., 318 Nouvel, H. See Lagardère, J-P., 131 Novitsky, J.A. See Friesen, J.A., 129 Nowell, A.R.M. See Jumars, P.A., 131 Nozais, C. See Kibirige, I., 131 See Perissinotto, R., 134 NRC, 330 Nultsch, W. See Hanelt, D., 462 Nuñez, L., 84, 330 See Briones, L., 308 Nunez, M. See Harris, G.P., 463 Núñez, S. See Letelier, J., 324 Núñez, S.P. See Arcos., 305 See Vargas, C.A., 341 Nusetti, O.A. See Brokordt, K.B., 308 Nyholm, N.E.I. See Both, C., 455 Nyman, M.A., 84 See Brown, M.T., 75 Nystrom, M. See Hughes, T.P., 464

O Oakley, J. See Hiscock, K., 399 Obenat, S. See Orensanz, J.M., 134 O’Brien, C.M., 470 O’Brien, J.J. See Potemra, J.T., 193 O’Brien, T.D. See Conkright, M.E., 311 Occhipinti-Ambrogi, A., 402 Ocean Studies Board, 402 Ochieng, C.A., 470 Odaya, M. See Beck, M.W., 307, 395 Odum, H.T., 170

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AUTHOR INDEX See Castilla, J.C., 310 See Sebens, K.P., 335 Painting, S.J. See Verheye, H.M., 342 Pak, H. See Carder, K.L., 33 See Kitchen, J.C., 35 See Zaneveld, J.R.V., 36 Pakhomov, E.A. See Kaehler, S., 82 Pal, T., 192 Paladino, F.V. See Binckley, C.A., 455 Palenik, B., 470 Paleras, A. See Michaelidis, B., 469 Palma, A.T., 330, 331 See Fariña, J.M., 315 See Hernández-Miranda, E., 319 See Poulin, E., 332 Palma, F. See Sielfeld, W., 336 Palma, M., 331 See Gallardo, V.A., 316 See Muñoz, P., 329 Palma, S., 331 Palma, W., 331 See Pizarro, J., 332 Palmer, A.R., 331 See Arsenault, D.J., 454 See Marchinko, K.B., 468 Palomera, I. See Tudela, S., 137 Palumbi, S.R., 331 See Hughes, T.P., 464 See Lubchenco J., 169 See Sotka, E.E., 337 Paluszkiewicz, T. See Huyer, A., 321 Panayotidis, O. See Boudouresque, C.F., 395 Pandolfi, J.M., 402, 470 See Hughes, T.P., 464 See Jackson, J.B.C., 399 Pankajakshan, T. See Desai, B.N., 191 Pannacciulli, F. See Benedetti-Cecchi, L., 395 Pantoja, S., 331 See Bernal, P.A., 307 See González, H.E., 318 See Muñoz, P., 329 Panutrakul, S., 192 Paolini, P. See Lagos, N., 323 Papaconstantinou, C., 134 Papadopoulou, K.N. See Karakassis, I., 169 Papenfuss, G.F., 84 Papi, F. See Luschi, P., 467 Papi, I. See Piazzi, L., 403 Pappalardo, P. See Fernández, M., 315 Paradis, G. See Zacherl, D.C., 344 Paramonov, L.E., 35 Paramor, O.A.L. See Hughes, R.G., 399 Paranjape, M.A. See Conover, R.J., 127 Pardal, M.A. See Salas, F., 171 Pardede, S.T. See Baird, A.H., 190 Pardi, G. See Piazzi, L., 403 Pardo, L.M. See Fernández, M., 316 See Palma, A.T., 331 See Vásquez, J.A., 87, 341, 342

Orestano, C. See Meinesz, A., 401 Orfila, A. See Marbà, N., 401 Orhon, D. See Jeftic, L., 400 O’Riordan, R. See Simkanin, C., 473 Orostegui, M. See Gómez, I., 317 Orr, J. See Guinotte, J.M., 462 Orr, J.C., 470 See Bopp, L., 455 Orr, M., 84 Orrego, P. See Edding, M., 313, 314 Orsi, J.J., 134 See Kimmerer, W.J., 131 Orth, R.J. See Beck, M.W., 394 Ortiz, V. See Clarke, M., 311 Ortíz, E. See Takesue, R.K., 339 Ortíz, M., 330 Ortíz, V. See Castilla, J.C., 310 Ortíz, V.C. See González, H.E., 318 Ortlieb, L., 330 See Takesue, R.K., 339 See Valdés, J., 340 Osborn, J.E. See Foster, E.G., 129 Osborne, A.R., 192 Oshel, P.E. See Janssen, J., 130 Osorio, P. See Buschmann, A.H., 75, 308 OSPAR Commission, 402 Osses, J. See Thomas, A.C., 339 Ostergaard, J.B. See Nielsen, T.G., 192 Osterhaus, A.D.M.E. See Harvell, C.D., 463 Ostfeld, R.S. See Harvell, C.D., 463 Otaiza, R. See Santelices, B., 85 Otsuki, Y. See Wolfe, D.W., 477 Ouzounis, C. See Michaelidis, B., 469 Overstreet, R.M. See Harvell, C.D., 463 Oviatt, C. See Keller, A.A., 465 Oxnevad, S. See Berge, J.A., 455 Oyarce, E. See Marín, V.H., 326 Oyarzún, C., 330 See Chong, J., 311 See Galleguillos, R., 316

P Pacanowski, R.C. See Griffies, S.M., 462 Pacheco, A., 330 Pacheco, C. See Alvarado, J.L., 305 See Castilla, J.C., 310 Pacheco, R. See Poulin, E., 332 Packard, T.T. See Codispoti, L.A., 311 Paddack, M.J., 84 Padilla, D.K. See Klinger, T., 322 Pagano, M. See Kouassi, E., 131 Page, G. See Galbraith, H., 461 Page, H.M. See Bomkamp, R.E., 307 Pagès, F., 330 See González, H.E., 317, 318 Paine, J. See Green, M.J.B., 398 Paine, R.T., 330

516

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AUTHOR INDEX Paredes, C. See Tarazona, J., 339 See Pandolfi, J.M., 402 See Sala, E., 334 Paredes, R. See Sandweiss, D.H., 334 Paris, C.B. See Cowen, R.K., 457 Park, G.S. See Takeuchi, T., 136 Park, R. See Galbraith, H., 461 Parker, D.M. See Polovina, J.J., 471 Parker, D.O. See Davis, G., 458 Parkinson, R.W., 470 Parks, J.E. See Pomeroy, R.S., 332 Parma, A.M. See González, J., 318 Parmenter, C.J. See Hewavisenthi, S., 463 Parmesan, C., 470 See Walther, G.R., 476 Parnell, P.E. See Dayton, P.K., 77, 458 See Seymour, R.J., 86 Parra, I. See Sala, E., 334 Parrish, C.C. See Richoux, N.B., 135 Parrish, F.A. See Polovina, J.J., 471 Parsons, M.L. See Thessen, A.E., 474 Paruelo, J. See Costanza, R., 396, 457 Pascual, M. See Orensanz, J.M., 134 Pastorino, G. See Orensanz, J.M., 134 Pasqualini V., 402 Paterson, D.M. See Lawrie, S.M., 132 Paterson, G.L.J., 170 Patino, D. See Westermeier, R., 343 Patrico, J. See Salas, F., 171 Patriti, G. See Macquart-Moulin, C., 132 Patterson, H.M., 134 Pauchard, A., 331 Paulmier, A. See Cornejo, M., 312 Pauly, D., 331 Pávez, A. See González, H.E., 317 Pavéz, M. See Vargas, C.A., 341 Pavez, M.A., 331 Pawlak, J.F. See Frid, C., 398 Pawson, D. See Levin, L.A., 169, 324 Payá, I. See Santelices, B., 335 Peach, K. See Beare, D.J., 454 Pearce, A. See Caputi, N., 456 Pearce, A.F. See Griffin, D.A., 462 Peard, K.R. See Weeks, S.J., 343 Pearre, S., Jr, 134 Pearse, J.S., 84 See Harrold, C., 80, 319 See Mattison, J.E., 83 See Towle, D.W., 87 Pearson, D.L., 170 Pearson, G. See Serrão, E.A., 473 Pearson, G.A. See Brawley, S.H., 456 Pearson, T.H. See Tyson, R.V., 340 Pechenik, J.A., 331 Pedersén, M., 402 See Choo, K.S., 457 See Johansson, G., 400 Pedersen, M.F., 470 Pedersen, S.E. See Rask, N., 403

Pedersen, T.F. See Cowie, G.L., 312 Pederson, D.K. See Duke, N.C., 459 Pedraza, M. See Landaeta, M.F., 323 Peelaers, D. See Remerie, T., 134 Peet, R.K., 170 Pegau, W.S. See Boss, E., 33 Pegau, W.S. See Twardowski, M.S., 36 Peinert, R. See Antia, A.N., 454 Peirano, A. See Bianchi, C.N., 395 See Meinesz, A., 401 See Sandulli, R., 403 Peletier, M.A. See See van Dalfsen, J. A., 405 Pellatt, J. See Votier, S.C., 475 Peloquin, J. See Cordi, B., 457 Pemberton, D., 470 See Ross, G.J.B., 472 Peña, J. See Moragat, D., 328 Peña, T.S., 331 Peñaloza, M. See Galleguillos, R., 316 Peñalver, E., 331 Penchaszadeh, P. See Orensanz, J.M., 134 Pennington, J.T. See Roughgarden, J., 333 Penry, D.L., 134 Peñuelas, J. See Menzel, A., 469 Penven, P., 331 Peredo, R. See Sielfeld, W., 336 Pereira, P. See Little, M., 467 Pere-Neto P.R. See Legendre, P., 169 Perez, E. See Thiel, M., 199–344 Pérez, E.P., 331 See Stotz, W., 338 Pérez, M. See Invers, O., 464 Perez, T., See Garrabou, J., 461 Perez-Llorens, J.L.See Bischof, K., 307 Perez-Ruzafa, A. See Salas, F., 171 Pergent G. See Pasqualini V., 402 Pergent-Martini C. See Pasqualini V., 402 Perissinotto, R., 84, 134 See Kibirige, I., 131 See Webb, P., 137 Perry, A.L., 470 Perry, C.J. See Abal, E.G., 453 Perry, C.T. See Harborne, A.R., 463 Persson, G. See Rosenberg, R., 403 Persson, L.E. See Nilsson, J., 402 Pescod, C.L. See Mumby, P.J., 469 Peters, A.F., 331 Peters, D. See Edgar, G.J., 459 Peters, R.H., 470 Petersen, C.G.J., 170 Petersen, K.S., 403 Peterson, C. See Kaufman L., 322 Peterson, C.H. See Jackson, J.B.C., 399 See Lotze, H.K., 401 Peterson, W.T., 331 See Halpin, P.M., 319 Petrie, B. See Frank, K.T., 129 Petrillo, M. See Thurston, M., 340

517

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AUTHOR INDEX Petryashev, V.V., 134 Pettersen, O. See Berge, J.A., 455 Petty, R.L. See Reed, D.C., 85 Pezzoli, G. See Colombini, I., 311 Pfister, C.A., 84 Philippart, C.J.M., 470 Phillips, A. See Wilcove, D.S., 405 Phillips, J.A., 470 Phillips, N.E., 332 Phillips, R.A., 332 Phillips, S. See Downs, C.A., 191 Phongsuwan, N., 193 See Brown, B.E., 191 See Chansang, H., 191 See Satapoomin, U., 193 Piacentini, D. See Jonzén, N., 465 Piazzi, L., 403 Picaut, J. See Lehodey, P., 467 Pickmere, S. See Boyd, P.W., 456 Piel, M.I. See Westermeier, R., 343 Pielou, E.C., 170 Pienkowski, M.W. See Davidson, N.C., 396 Pieper, R.E. See Smith, S.L., 136 Pierce, G.J. See Learmonth, J.A., 466 See MacLeod, C.D., 468 See Robinson, R.A., 472 Piersma, T. See Both, C., 455 Pierson, M.O. See Dugan, J.E., 313 Pietras, C. See Zhao, T.X.-P., 36 Pihl, L., 134, 403 See Baden, S., 394 Pikitch, E.K. See Boersma, D., 307 Pile, A.J. See Prowse, T.A.A., 471 Pilgrim, J. See Brooks, T.M., 395 Pillai, C.S.G., 193 Pillai, M.C. See Garman, G.D., 79 Piller, W.E. See Harrold, C., 319 Pilon, V. See Boulding, E.G., 455 Pimm, S.L. See Montoya, J.M., 133 Pineda, J., 170, 332 See Levin, L.A., 169, 324 Pinedo, S. See Thibaut, T., 404 Pinero, F.S. See Polis, G.A., 332 Pinnick, R.G. See Ch∆lek, P., 34 Pino, M. See Jaramillo, E., 322 Piñones, A., 332 See Vargas, C.A., 341 Pinto, L. See Ahumada, R., 305 Pinto, R. See Alvarado, J.L., 305 See Martínez, E.A., 326 Pipitone, C. See Badalamenti, F., 394 Piquet, A. See Kelfkens, G., 465 Piraino, S. See Fanelli, G., 398 Pirazzoli, P.A. See Bondesan, M., 395 Pirinen, P. See Menzel, A., 469 Piriz M.L. See Orensanz, J.M., 134 Pita, M.E. See Barbera, C., 394 Pitta, P. See Karakassis, I., 169 Pittock, A.B., 470

See Walsh, K., 475 See Walsh, K.J.E., 476 Pizarro, A., 332 Pizarro, G. See González, H.E., 317 See Iriarte, J.L., 321 See Montecino, V., 327 Pizarro, J., 332 Pizarro, O. See Chaigneau, A., 311 See Escribano, R., 314 See Letelier, J., 324 See Montecinos, A., 328 See Ramos, M., 333 See Shaffer, G., 336 Pizay, M.D. See Engel, A., 460 Planque, B. See O’Brien, C.M., 470 Planqué, R. See See van Dalfsen, J. A., 405 Plante, C.J. See Mayer, L.M., 133 Plattner, G.K. See Orr, J.C., 470 Pleijel, F. See Bertrand, Y., 166 Plenge, M. See Duffy, D., 313 Plummer, K.M., 134 Pohnert, G. See Ianora, A., 321 Poiner, I. See Rothlisberg, P., 472 Polacheck, T., 471 Polis, G.A., 332 See Sanchez-Pinero, F., 334 Pollingher, U. See Hillebrand, H., 34 Polo, L. See Rodríguez-Prieto, C., 403 Poloczanska, E.S., 407–478 See Hobday, A.J., 464 See Mieszkowska, N., 469 Polovina, J.J., 471 Poma, V. See Bonaventura, R., 455 Pomeroy, R.S., 332 Ponce, F. See Morales, C.E., 328 Ponce, T. See Simeone, A., 337 Pondella, D.J., Jr. See Stephens, J.S., Jr, 86 Pool, R.M. See Wolfe, D.W., 477 Poore, G.C.B., 170, 471 See Koslow, J.A., 466 See O’Hara, T.D., 470 See Richardson, A.J., 471 Poovachiranon, S. See Chansang, H., 191 Pope, N. See Roast, S.D., 135 Popper, N. See Stambler, N., 194 Porflitt, G. See Guerra, C., 318 Porteiro C., 471 Porter, J.W., 471 See Harvell, C.D., 463 Pörtner, H.O., 471 See Brante, A., 308 See Fernández, M., 316 See Frederich, M., 316 See Michaelidis, B., 469 See Ruiz-Tagle, N., 334 Posadas, P., 170 Possingham, H., 403 See Leslie, H., 400 See Roughgarden, J., 85,

518

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AUTHOR INDEX See Leslie, H., 324 See Meir, E., 327 See Pandolfi, J.M., 470 Post, E. See Walther, G.R., 476 Potemra, J.T., 193 Potter, D.S. See Spencer, C.N., 136 Potti, J. See Both, C., 455 Potts, D.C., 193 Pou, S. See Delgado, O., 396 Poulet, S.A. See Ianora, A., 321 See Vargas, C.A., 341 Poulin, E., 332 See Cárdenas, L., 309 See Narváez, D.A., 329 See Thiel, M., 199–344 Poulin, R. See Mouritsen, K.N., 469 Pounds, J.A. See Root, T.L., 472 Powell, H.T., 84 Powell, T.M. See Botsford, L.W., 307 Power, A. See Simkanin, C., 473 Pozdnyakov, D., 35 Pradel, R. See Rivalan, P., 472 Prado, L., 332 Prakash, A. See Sheldon, R.W., 36 Preen, A.R., 471 Preston, F.W., 170 Preti, M. See Simonini, R., 404 Prevedelli, D. See Simonini, R., 404 Prevost, C. See Delille, B., 77 Prévot-Julliard, A.C. See Rivalan, P., 472 Price, D.N. See Cordi, B., 457 Price, J.T. See Root, T.L., 472 Price, K.S. Jr, 134 Price, N.M. See Palenik, B., 470 Price, W.W., 134 Pridmore, R. See Boyd, P.W., 456 Prince, R.I.T. See Walker, D.I., 475 Probyn, T.A. See Attwood, C.G., 74 Proctor, C. See Thresher, R., 474 Proctor, T.D., 35 Prospero, J.M. See Jickells, T.D., 465 Prostakova, I.V. See Shepelevich, N.V., 36 Provini, A. See Marchetti, R., 401 Prowse, T.A.A., 471 Pruett, L., 403 Prummel, W. See Lotze, H.K., 401 Przeslawski, R., 471 Ptrachett, M.S. See Baird, A.H., 190 Pubellier, M., 193 Pueyo, S., 170 Pukaric, S.B.G.W., 403 Pulgar, J.M., 332 Pullin, A.S. See Sutherland, W.J., 338 Punt, A.E. See Fulton, E.A., 461 Purca, S. See Montecinos, A., 328 Purvis, A., 170 See Mace, G.M., 169 Puskaric, S. See Barmawidjaja, D., 394

Pye, K. See Allen, J.R.L., 394 Pyle, B.E. See Latimer, P., 35

Q Qin, D. See Church J.A., 457 Quéguiner, B. See Sedwick, P.N., 473 Quijón, P., 332 See Contreras, H., 312 See Jaramillo, E., 322 Quijón, P.A., 170 Quinby-Hunt, M.S., 36 Quinn, J.F. See Botsford, L.W., 307 See Wing, S.R., 343 Quiñones, R. See Daneri, G., 312 See González, H.E., 317 Quiñones, R.A. See Cury, P., 312 See Eissler, Y., 314 See González, R.R., 318 See Ulloa, O., 340 See Yaikin, J., 344 Quirantes, A., 36 Quiroga, E., 332 See Palma, M., 331 See Sellanes, J., 336 Quiroz, D. See Báez, P., 306 See Montecino, V., 327 Quiroz, J.C., 332 Quirt, J., 134

R Rabinowitz, C. See Baruch, R., 454 Rachlin, J.W. See Warkentine, B.E., 137 Radashevsky, V.I., 332 Raffaelli, D. See Speirs, D., 136 Raffaelli, D.G. See Lawrie, S.M., 132 Rahbek, C. See Colwell, R.K., 167 Raiker, V. See Ramaswamy, V., 193 Railsback, S.F. See Grimm, V., 129 Raimondi, P.T., 84 See Gaylord, B., 79 See Reed, D.C., 85 Rajan, P.T. See Turner, J.R., 194 Rajendran, N. See Kathiresan, K., 465 Ralph, P.J., 471 Ralston, S.V. See Wing, S.R., 88 Ramaswamy, V., 193 Ramírez, A., 333 Ramírez, J.M. See Jerardino, A., 322 Ramírez, M. See Correa, J.A., 312 Ramon, M. See Pagès, F., 330 Ramorino, L., 333 Ramorino, L.M., 333 Ramos, A.A. See Badalamenti, F., 394 Ramos, A.M. See Letelier, S., 324 Ramos, M., 333 See Ulloa, O., 340

519

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AUTHOR INDEX Rex, M.A., 170 See Levin, L.A., 169, 324 Rey, F. See Erga, S.R., 460 Reyes, A. See Moreno, C.A., 328 Reyes, E. See Buschmann, A.H., 75, 308 Reyes, H. See Morales, C.E., 328 Reyes, J. See van Waerebeek, K., 341 Reynolds, J.D. See Perry, A.L., 470 See Dulvy, N.K., 459 Reyss, J.L. See Muñoz, P., 329 Rhoads, D.C., 471 Ribbe, J. See Cai, W., 456 Ribera, C. See Delgado, L., 127 Ribera Maycas, E. See Macquart-Moulin, C., 132 Ribes, M., 134 Rice, A.L., 135 Rice, C.P. See Evans, M.S., 128 Rich, H.W., 471 Richards, D.V. See Davis, G., 458 Richardson, A.J. See Bonnet, D., 455 See Edwards, M., 459 See Edwards, M.J., 459 See Hays, G.C., 463 See Hobday, A.J., 464 See Kirby, R.R., 466 See McKinnon, A.D., 468 See Poloczanska, E.S., 407–478, 471 Richardson, J.B. See Keefer, D.K., 322 See Sandweiss, D.H., 334 Richardson, J.I. See Mrosovsky, N., 469 Richardson, T.H. See Mrosovsky, N., 469 Richer de Forges, B., 471 Richoux, N.B., 135 Rick, I.P. See Modarressie, R., 469 Rick, T.C. See Erlandson, J.M., 78 Ricklefs, R.E., 171 Ridgway, K.R., 472 Ridgwell, A.J. See Jickells, T.D., 465 Riebesell, U., 472 See Engel, A., 460 See Raven, J., 471 Riera, F. See Delgado, O., 396 Riera, T. See Carola, M., 126 See Coma, R., 126 Rigg, G.B., 85 Riggio, S. See Badalamenti, F., 394 Rijstenbil, J.W., 472 Rinaldi, A. See Simonini, R., 404 Rinde, E. See Christie, H., 396 Rintoul, S. See Boyd, P.W., 456 Rintoul, S.R. See Thresher, R., 474 Ripley, H.T. See Jaubert, J.M., 400 Rippon, S., 403 Riquelme, V.A. See Buschmann, A.H., 308 Riseman, S.F. See Hutchins, D.A., 321 Riser, K.L. See Dayton, P.K., 77, 396 See Tegner, M.J., 87, 474 See Vilchis, L.I., 475

Ramos-Esplá, A.A. See Barbera, C., 394 Ramsing, N.B. See Fossing, H., 316 Rangin, C. See Pubellier, M., 193 Rao, K.H. See Ramaswamy, V., 193 Rao, N.S. See Ramaswamy, V., 193 Rao, P.S. See Ramaswamy, V., 193 Rao, T.S.S., 193 Raper, S. See Cubasch, U., 458 Rasheed, M. See Wild, C., 343 Rask, N., 403 Raskin, R.G. See Costanza, R., 396, 457 Rasmussen, J.B. See Vadeboncoeur, Y., 137 Rasmussen, K.L. See Petersen, K.S., 403 Ratilal, P. See Makris, N.C., 132 Rautenberger, R. See Bischof, K., 307 Raven, J., 471 Raven, J.A. See Beardall, J., 454 Ravilious, C. See Spalding, M.D., 194 Ravussin, P.A. See Both, C., 455 Recasens, L. See Bozzano, A., 126 Reddiah, K., 193 Redlow, A.E. See Foley, A.M., 460 Reed, C. See Edgar, G.J., 459 Reed, D.C., 84, 85, 333, 471 See Amsler, C.D., 74 See Eardley, D.D., 78 See Gaylord, B., 79 See Harrold, C., 80 See Hempel, W.M., 80 See Raimondi, P.T., 84 Reed, P.C. See Limpus, C.J., 467 Rees, E.L.S. See Mackie, A.S.Y., 169 Rehfisch, M.M. See Robinson, R.A., 472 Reid, C. See Aguilar, A., 305 Reid, D.D. See Lyle, J.M., 468 Reid, D.G. See Beare, D.J., 454 Reid, P.C. See Beaugrand, G., 454 See Frid, C., 398 See Kirby, R.R., 466 Reid, R.J. See MacLeod, C.D., 468 Reimers, C.E. See Komar, P.D., 35 Reiners, F. See Greve, W., 462 Reinsel, K.A. See Forward, R.B., 316 Reipschläger A. See Pörtner, H.O., 471 Reise, K., 403 See Lotze, H.K., 401 Reisenbichler, K.R. See Kaufmann, R.S., 131 Reisewitz, S.E. See Beck, M.W., 395 Relini, G. See Benedetti-Cecchi, L., 395 Remerie, T., 134 Remi˘sová, V. See Menzel, A., 469 Renaud, M.L. See Zein-Eldin, Z.P., 477 Rendell, L., 333 Renken, H. See Mumby, P.J., 469 Renshoff, S. See Fish, M.R., 460 Retamal, L. See Montecino, V., 327 Retamal, M. See Gómez-Uchida, D., 317 Revenga, C. See Burke, L., 396 Revilla, E. See Grimm, V., 129

520

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AUTHOR INDEX Roeckner, E. See Gregory, J.M., 462 Roelfsema, C.M. See Duke, N.C., 459 Roemmich, D., 472 See Willis, J.K., 476 Roesler, C.S., 36 Roessig, J.M., 472 Rogers, C.S., 472 Rogers, K., 472 Rogers, P.J. See Ward, T.M., 476 Rojas, O. See Loeb, V.J., 324 Rojas, P.M., 333 Roleda, M.Y. See Wiencke, C., 476 Rollins, H.B. See Sandweiss, D.H., 334 Romaine, S. See Gattuso, J.P., 461 Román, C. See Jaramillo, E., 322 Roman, D. See Correa, J.A., 312 Romano, G. See Ianora, A., 321 Romero, J. See Invers, O., 464 See van Dalfsen, J. A., 405 Romero, L. See Tokeshi, M., 340 Romme, W.H. See Norse, E.A., 170 Romo, H. See Alveal, K., 305 Ronan, C.E., 333 Ronnback, P. See Pihl, L., 403 Roodbergen, S.P. See Both, C., 455 Rooney, N., 135 Root, T.L., 472 Rosales, S.A. See Escribano, R., 315 See Palma, W., 331 Rose, C. See Ene, A., 460 Rose, G.A., 472 Rosen, B. See Hughes, T.P., 464 Rosen, B.R., 193 See Wilson, M.E.J., 194 Rosenbaum, K.L. See Norse, E.A., 170 Rosenberg, M.S., 171 Rosenberg, R., 333, 403 See Baden, S., 394 See Karlson, K., 400 See Pihl L., 134 Rosenblatt, R.H. See Stepien, C.A., 337 Rosenbluth, B. See Rutllant, J.A., 334 Rosenfield, A. See Mackenzie, C.L., Jr, 401 Rosenthal, R. See Dayton, P.K., 313 Rosenthal, R.J., 85 See Dayton, P.K., 76 Rosenthal, Y., 85 Rosenzweig, M.L., 171 Rosenzweigk, C. See Root, T.L., 472 Ross, G.J.B., 472 Ross, J. See Johnson, C., 465 Rosson, A. See Manríquez, P.H., 325 Rost, B. See Riebesell, U., 472 Rothlisberg, P., 472 Rothschild B. See Porteiro C., 471 Rothstein, D. See Wilcove, D.S., 405 Rotstayn, L.D. See Gordon, H.B., 462 Rottiers, V. See Dewicke, A., 128

Rismondo, A., 403 Risoviç, D., 36 Ritz, D.A., 135 See Cohen, P.J., 126 See Flynn, A.J., 128 See Foster, E.G., 129 See Johnston, N.M., 130 See Metillo, E.B., 133 Rivadeneira, M.M, 333, 472 See Moreno, R.A., 328 Rivalan, P., 472 Rivas, M. See Gutiérrez, D., 319 Rivera, G., 333 Rivera, P. See Westermeier, R., 343 Rivera, P.J. See Westermeier, R., 343 Riveros, J.C. See Majluf., 325 Rizzo, M. See Barbera, C., 394 Roa, R., 333 See Acuña, E., 304 See Gallardo, V.A., 316 Roach, D.M. See Zaneveld, J.R.V., 36 Roast, S.D., 135 Robbins, T.T. See Vilchis, L.I., 475 Roberts, C.M., 333 See Balmford, A., 307 Roberts, D. See Kennedy, R.J., Roberts, D.A. See DeMartini, E.E., 77 See Hallacher, L.E., 80 See Plummer, K.M., 134 Roberts, J.D. See Bancroft, W.J., Roberts, J.M., 472 Robertson, A.I. See Alongi, D.M., 453 Robertson, B.R. See Druehl, L.D., 78 Robertson, D.L. See Zimmerman, R.C., 88, 477 Robertson, D.R. See Swearer, S.E., 339 Robertson, G. See Moreno, C.A., 328 Robinson, C. See Hays, G.C., 463 Robinson, R.A., 472 See Learmonth, J.A., 466 Robinson, S. See Bonnet, D., 455 Robison, B.H. See Kaufmann, R.S., 131 Robledo, D. See Hernández-Carmona, G., 80 Robles, A. See Arntz, W.E., 306 Roca, E. See Sayre, R., 335 Rocamora, J. See Cano, J., 396 Rochelle-Newall, E. See Engel, A., 460 Rodbell, D.T. See Moy, C.M., 329 Rodgers, K.B. See Orr, J.C., 470 Rodolfo, K.S., 193 Rodríguez, A. See Drake, P., 128 Rodríguez, L., 333 See Escribano, R., 314 See Marín, V.H., 326 See Ortlieb, L., 330 Rodríguez, S.R., 85, 333 Rodríguez-Graña, L., 333 Rodriguez-Montesinos, Y.E. See Hernández-Carmona, G., 80, 81 Rodríguez-Prieto, C., 403

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AUTHOR INDEX Roughgarden, J., 85, 333 See Connolly, S.R., 311 See Farrell, T.M., 315 See Hughes, T.P., 464 Rouse, G.W. See Bertrand, Y., 166 Roux, J.P. See Moloney, C.L., 327 Rovira, J., 334 Rowan, R., 193 Rowden, A. See Attrill, M.J., 166 Rowden, A.A. See Foggo, A., 167 Rowe, G.T. See Arntz, W.E., 306 Rowley, R.J. See Ebeling, A.W., 78 See Harris, L.G., 80 Rowling, K. See Thresher, R.E., 474 Roy, C. See Cury, P., 312 Roy, D.B. See Hickling, R., 463 Roy, K., 171, 334 See Jablonski, D., 169 Rozbaczylo, N. See Castilla, J.C., 310 See Hernández, C.E., 319 See Moreno, R.A., 328, 329 See Quiroga, E., 332 Rubilar, P. See Moreno, C.A., 328 Rubolini, D. See Jonzén, N., 465 Ruckelshaus, M. See Leslie, H., 324 See Leslie, H., 400 See Roberts, C.M., 333 Rud, N. See Petersen, K.S., 403 Rudi, E. See Baird, A.H., 190 Rudolph, A. See Ahumada, R., 305 Rudstam, L.G., 135 See Gal, G., 129 See Johannsson, O.E., 130 See Smith, S.L., 136 Rue, E.L. See Hutchins, D.A., 321 Ruedy, R. See Hansen, J., 462 Ruiz, G.M. See Swearer, S.E., 339 Ruiz, J. See Frere, E., 316 Ruiz Fernandez, J.A. See Badalamenti, F., 394 Ruiz-Fernandez, J.M. See Diaz-Almela, E., 458 Ruiz-Tagle, N., 334 See Fernández, M., 316 Rumohr, H., 171 Runge, J.A. See Kouwenberg, J.H.M., 466 Rupp, G. See Uriarte, I., 340 Russell, F.S., 472 Russell, G.L. See Gregory, J.M., 462 Russell, R., 171 See Menge, B.A., 327 Russo, G.F., 403 Russo, R. See Bonaventura, R., 455 Ruth, M. See Berghahn, R., 395 Rutllant, J. See Moraga, J., 328 See Shaffer, G., 336 See Strub, P.T., 338 See Torres, R., 340 Rutllant, J.A., 334

Rutten, L.M. See Fourqurean, J.W., 460 Rvilious, C. See Spalding, M.D., 404 Ryan, J. See Chavez, F.P., 311, 457 Rylands, A.B. See Brooks, T.M., 395 Ryrholm, N. See Parmesan, C., 470 Ryther, J.H., 334

S Saalfeld, K. See Whitehead, P.J., 476 Sabat, P., 334 Sabine, C.L. See Orr, J.C., 470 Sachdev, S. See Holyoak, M., 130 Sadovy, Y. See Dulvy, N.K., 459 Saenger, P. See Blasco, F., 455 Safi, K. See Boyd, P.W., 456 Sagarin, R.D., 472 See Barry, J.P., 454 Sahli, J.M., 334 Saigusa, M., 135 Saintilan, N., 472 Rogers, K., 472 Saint-Jean, L. See Kouassi, E., 131 Saito, M., 334 Sakamoto, W. See Sato, K., 473 Sala, E., 85, 334, 403 See Kinlan, B.P., 82 See Pandolfi, J.M., 402, 470 See Kaufman L., 322 Salamanca, M. See Takesue, R.K., 339 Salamanca, M.A. See Muñoz, P., 329 Salamanca, S.A. See Muñoz, P., 329 Salas, F., 171 Salazar, S. See Fariña, J.M., 315 Saldívar, M. See Takesue, R.K., 339 Salemaa, H. See Kangas, P., 400 Salen-Picard, C., 334 Saliba, L.J. See Jeftic, L., 400 Salinas, G.R. See Castro, L.R., 311 Salinas, N., 85 Salinas, S. See Shaffer, G., 336 See Strub, P.T., 338 Salm, R.V. See Kaufman L., 322 Salo, H.M. See Markkula, S.E., 468 Salzwedel, H. See Arntz, W., 306 See Tarazona, J., 339 Sameoto, D., 135 Sameoto, D.D. See Longhurst, A.R., 132 Sammarco, P.W.,.473 Samson, C.R. See Edgar, G.J., 459 Samuel, M.D. See Harvell, C.D., 463 San Vicente, C., 135 Sánchez, M., 334 Sánchez, P. See Santelices, B., 335 Sanchez, R.P. See Porteiro C., 471 Sánchez Lizaso, J.L. See Badalamenti, F., 394 Sánchez-Mata, A. See Barbera, C., 394

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AUTHOR INDEX Sanchez-Pinero, F., 334 Sanchez-Rodriguez, I. See Hernández-Carmona, G., 80, 81 Sanders, H., 334 Sanders, H.L., 171 See Allen, J.A., 166 Sand-Jensen, K. See Marbà, N., 401 See Middelboe, A.L., 401 Sandlin, P.E. See Bickmore, B.R., 33 Sandulli, R., 403 Sandweiss, D.H., 334 Sandweiss, M.D. See Sandweiss, D.H., 334 Sanger, G.A., 135 Sangiorgi, F., 403 Sano, M. See Inoue, T., 130 Sanpanich, K. See Turak, E., 194 Santander, H. See Carrasco, S., 309 Santelices, B., 85, 334, 335 See Avila, M., 75, 306 See Bobadilla, M., 307 See Castilla, J.C., 310 See Correa, J.A., 312 See Hannach, G., 319 See Hoffmann, A., 320 See Hoffmann, A.J., 81, 320 See Martínez, E.A., 326 See Meneses, I., 327 See Muñoz, M., 329 See Ojeda, F.P., 84, 330 See Oliger, P., 330 See Pizarro, A., 332 See Vásquez, J.A., 87, 341, 342 See Villouta, E., 343 Santibañez, A. See Gutierrez, A., 80, 319 Santibáñez, J., 335 Santibáñez, P. See González, H.E., 317 Santoro, C.M., 335 Santos, M.B. See Learmonth, J.A., 466 Sanz, J.J. See Both, C., 455 Sapper, J. See Zhao, T.X.-P., 36 Sardiña, P., 135 Sarmiento, J.L., 473 See McNeil, B.I., 469 See Orr, J.C., 470 Sartor, P. See Bozzano, A., 126 See Perez, T., 470 Sartoretto, S. See Garrabou, J., 461 Sarupia, J.S. See Desai, B.N., 191 Satapoomin, S. See Nielsen, T.G., 192 Satapoomin, U., 193 See Brown, B.E., 191 See Chansang, H., 191 Sato, K., 473 Sato, M. See Hansen, J., 462 Satta, M.P. See Martin, D., 401 See Moschella, P.S., 402 Satterlee, D.R. See Keefer, D.K., 322 Satyabalam, S.P. See Bilham, R., 191

Satyanarayan, C. See Turner, J.R., 194 Saunders, G.W., 85 See Druehl, L.D., 77, 78 See Lane, C.E., 82 Sautour, B. See David, V., 127 Sauvageau, C., 85 Sawamto, S., 135 Sawangarreruks, S. See Nielsen, T.G., 192 Sawyer, T. See Mayer, L.M., 133 Sayre, R., 335 Scagel, R.F., 86 See Gabrielson, P.W., 79 Scarabino, F. See Orensanz, J.M., 134 Scarlett, B. See Heffels, C.M.G., 34 Schaanning, M.T. See Berge, J.A., 455 Schaeffer, M.B. North, W.J., 84 Schaff, S. See Ene, A., 460 Scheer, G., 193 Scheffer, M. See Schippers, P., 473 Scheibling, R.E., 473 Scheifinger, H. See Menzel, A., 469 Schell, C. See De Robertis, A., 128 Schell, P.A., Scheltema, R.S., 335 Schembri, P.J. See Barbera, C., 394 Scheridan, P.F. See Beck, M.W., 394 Scheuerell, M.D. See Schindler, D.E., 135 Schiariti, A., 135 Schick, L.L. See Mayer, L.M., 133 Schiecke, U. See Bacescu, M., 125 Schiel, D.R., 86, 473 See Foster, M.S., 78, 79 Schiermeier, Q., 473 Schimmelmann, A., 86 Schindler, D.E., 135 Schippers, P., 473 Schlacher, T.A., 135 Schlatter, R.P., 335 Schlitzer, R. See Orr, J.C., 470 Schmalfuss, H., 335 Schmid, M. See Kuypers, M.M., 323 Schmidt, G.W. See LaJeunesse, T.C., 192 Schmidt, M. See Atkinson, L.P., 306 Schmidt-Nielsen, K., 335 Schmiede, P. See Santelices, B., 335 Schmitt, R.J. See Holbrook, S.J., 81, 464 Schmitz, K., 86 Schneider, S.H. See Root, T.L., 472 Schneider, U. See Engel, A., 460 Schneider, W. See Atkinson, L.P., 306 See Fuenzalida, R., 316 See Palma, M., 331 See Yannicelli, B., 344 Schoeman, D.S. See Richardson, A.J., 471 Scholten, J. See Antia, A.N., 454 Schonberg, S. See Dunton, K., 313 Schories, D., 403

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AUTHOR INDEX Schramm, W. See Vogt, H., 405 Schreurs, R. See Volten, H., 36 Schrieber, M.A. See Majluf, P., 325 Schroeder, B.A. See Foley, A.M., 460 Schroeter, S.C., 86 See Dean, T.A., 77 See Dixon, J., 77 See Reed, D.C., 85 Schul-Bull, D. See Antia, A.N., 454 Schultz, D. See Norkko, A., 470 Schulz, H. See Cowie, G.L., 312 See Fossing, H., 316 Schulz, H.N., 335 Schwartz, M.D., 473 See Wolfe, D.W., 477 Schweder, C. See MacLeod, C.D., 468 Schwindt, E. See Orensanz, J.M., 134 Scoffin, T.P., 193 See Brown, B.E. 191 See Tudhope, A.W., 194 Searle, M., 193 Sebens, K.P., 335, 403, 473 Secretariat of the Convention on Biological Diversity., 335 Sedaghatkish, G. See Sayre, R., 335 Seddon, P. See Ellenberg, U., 314 Seddon, S., 473 Sedwick, P.N., 473 Seed, R. See Birkett, D.A., 395 Segrove, F. See Colman, J.S., 126 Seiderer, L.J. See Newell, R.C., 402 Seikai, T. See Takeuchi, T., 136 See Tominaga, O., 137 Seki, M.P. See Polovina, J.J., 471 Self, R.F.L. See Jumars, P.A., 131 Selkoe, K.A. See Swearer, S.E., 339 Sellanes, J., 335, 336 See Gutiérrez, D., 319 See Milessi, A., 327 See Muñoz, P., 329 See Neira, C., 329 See Thiel, M., 199–344 Selmer, J.S. See Wängberg, S.A., 476 Seltzer, G.O. See Moy, C.M., 329 Semenov, V.N., 336 Semroud, R. See Boudouresque, C.F., 395 Senior, C.A. See Cubasch, U., 458 Sepúlveda, F. See Simeone, A., 337 Sepúlveda, H.H. See Thiel, M., 199–344 Sepulveda, J. See Pantoja, S., 331 Sepúlveda, M. See Sielfeld, W., 336 Sepúlveda, R., 336 See Chong, J., 311 SERNAPESCA, 336 Serra, R. See Porteiro C., 471 Serrão, E. See Brawley, S.H., 456 Serrão, E.A., 473 Serviere-Zaragoza, E. See Hernández-Carmona, G., 80 Servos, M.R. See Johannsson, O.E., 130 Setchell, W.A., 86

Setlow, J.K. See Setlow, R.B., 473 Setlow, R.B., 473 Seva, A. See Barbera, C., 394 Sewell, J. See Hiscock, K., 399 Sewell, R.B.S., 193 Seymour, J. See Little, M., 467 Seymour, R.J., 86 Sfriso, A., 403, 404 Sgorbini, S. See Sandulli, R., 403 Shachak, M. See Jones, C.G., 322 Shaffer, G., 336 See Hormazábal, S., 320 See Leth, O., 324 Shah, D. See Madhaven, B.B., 192 Shanks, A.L., 86, 336 See Mattison, J.E., 83 Shannon, C.E., 171 Shannon, L.J. See Cury, P., 312 See Moloney, C.L., 327 Shaughnessy, G. See Ross, G.J.B., 472 Shaughnessy, P.D. See Marsh, H., 468 See Ross, G.J.B., 472 Shaulis, N.J. See Wolfe, D.W., 477 Shchepetkin, A. See Marchesiello, P., 325 Shchepetkin, A.F., 336 Shears, N.T., 336 Sheldon, R.W., 36 Shelford, V.E., 171 See Clements, F.E., 166 Shellito, S.M. See Abello, H.U., 124 See Taylor, L.H., 137 Shepelevich, N.V., 36 Shepherd, J. See Raven, J., 471 Shepherd, S. See Johnson, C., 465 See Sayre, R., 335 Sherman, R.K. See Lasenby, D.C., 132 Shi, G. See Cai, W., 456 Shi, Y. See Lasenby, D.C., 132 Shick, J.M., 473 Shields, J.D., 135 Shifrin, K.S., 36 Shillington, F.A. See Hill, A.E., 320 Shima, J.S. See Swearer, S.E., 339 Shimode, S. See Kurihara, H., 466 Shirayama, Y. See Kurihara, H., 466 Short, F.T., 404, 473 See Green, E.P., 398 Shulenberger, E. See Haury, L., Shumida, A. See Wilson, M., 172 Shurin, J.B. See Leibold, M.A., 323 Siebeck, O., 135 Siebeck, U.E., 473 Siegel, D.A., 36, 336 Siegfried, C.A., 136 Sieh, K., 193 Sielfeld, W., 336, 337 Sievers, H. See Johnson, D.R., 322 Sifeddine, A. See Valdés, J., 340 Sigman, D.M. See Tortell, P.D., 475

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AUTHOR INDEX Sih, A., 404 Silk, J.R. See Phillips, R.A., 332 Silva, C., 337 See Yáñez, E., 344 Silva, M. See Palma, A.T., 331 Silva, N., 337 See Morales, C.E., 328 Silva, P.C. See Moe, R.L., 83 Silva-García, A. See Drake, P., 128 Silva-García, C. See Tognelli, M.F., 340 Silverin, B. See Both, C., 455 Silvestri, C. See Sandulli, R., 403 Simberloff, D.S., 171 Simenstad, C. See Dean, A.F., 127 Simenstad, C.A. See Duggins, D.O., 78 Simeone, A., 337 See Bernal, M., 307 See Luna-Jorquera, G., 325 See Schlatter, R.P., 335 Simkanin, C., 473 Simonini, R., 404 Simpson, C.J., 473 See Babcock, R.C., 454 Simpson, E.H., 171 Sims, D.W., 473 Singh, C.D. See Pal, T., 192 Singham, S.B. See Bohren, C.F., 33 Sinke, J. See Dauwe, B., 127 Sinnassamy, J.M. See Boudouresque, C.F., 395 Sinyuk, A. See Dubovik, O., 34 Siregar, A.M. See Baird, A.H., 190 Sitts, R.M., 136 Skeffington, M.J.S. See Curtis, T.G.F., 396 Skilleter, G.A. See Manson, F.J., 468 Skillman, A.D. See Huesemann, M.H., 464 Skirving, W. See Done, T.J., 459 See Kleypas, J.A., 466 Skirving, W.J. See Donner, S.D., 459 Skottsberg, C., 86 Slaper, H. See Kelfkens, G., 465 Slater, F.M. See Both, C., 455 Slater, R. See Sarmiento, J.L., 473 Slater, R.D. See Orr, J.C., 470 Slavin, R.E., 171 Slutsker, I. See Dubovik, O., 34 Smart, J., 473 Smayda, T.J., 473 Smedbol, R.K., 136 Smetacek, V. See Ianora, A., 321 Smith, A.D.M. See Fulton, E.A., 461 Smith, C.J. See Karakassis, I., 169 Smith, C.R., 337 See Glover, A.G., 461 See Levin, L.A., 169, 324 See Snelgrove, P.V.R., 171, 474 Smith, F. See Broitman, B.R., 308 See Witman, J.D., 172 Smith, G.C. See Ross, G.J.B., 472

Smith, G.J. See Coyer, J.A., 76 See Hutchins, D.A., 321 Smith, G.W. See Harvell, C.D., 463 Smith, I. See Allan, R., 190 Smith, J.E., 171 Smith, J.R., 473 Smith, K.L., Jr. See Kaufmann, R.S., 131 Smith, L. See Babcock, R.C., 454 Smith, M.G. See McShane, P.E., 469 Smith, M.P.L. See Inglis, G.J., 464 Smith, R., 474 Smith, R.C. See Häder, D.P., 462 Smith, R.D. See Griffies, S.M., 462 Smith, R.L. See Enfield, D.B., 314 See Freeland, H.J., 316 See Huyer, A., 321 Smith, S.D.A., 86 Smith, S.I., 136 Smith, S.L., 136 Smith, W.O., Jr. See Barber, R.T., 125 Sneath, P.H.A., 171 Snelgrove, P.V.R., 171, 474 See Quijón, P.A., 170 Snell, J.L. See Kemeny, J.G., 131 Snoeijs, P. See Choo, K.S., 457 See Eriksson, B.K., 398 See Johansson, G., 400 See Pedersén, M., 402 Sobarzo, M., 337 See González, H.E., 317, 318 See Iriarte, J.L., 321 See Pagès, F., 330 See Yannicelli, B., 344 Sobel, J.A., 337 Sobolev, I., 337 Sobrino, I. See Drake, P., 128 Soderqvist, T. See Pihl, L., 403 Soegiarto, A., 193, 194 Soekarno, 194 Soimasuo, M.R. See Huovinen, P.J., 81 Sokal, R.R. See Sneath, P.H.A., 171 Sokolov, L.V. See Both, C., 455 Soldatov, V. See Sarmiento, J.L., 473 Solé, R.V. See Montoya, J.M., 133 Solow, A.R., 474 Solvang, R. See Jonzén, N., 465 Somarakis, S. See Karakassis, I., 169 Somerfield, P.J., 171 See Ellingsen, K.E., 167 See Olsgard, F., 170 See Warwick, R.M., 172 Somero, G.N., 337 See Dahlhoff, E., 312 See Graves, J.E., 318 See Hofmann, G.E., 320 See Stillman, J.H., 337 Sommer, U. See Worm, B., 405 Sondergaard, M. See Aaser, H., 124 Song, K.-H., 136

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AUTHOR INDEX Stanton, T.P. See Coale, K.H., 311 Staples, D. See Rothlisberg, P., 472 See Vance, D., 475 Staples, D.J., 474 Stattegger, K. See Haneburth, T., 192 Stebbins, T.D., 86 Stech, J.L. See Zagaglia, C.R., 477 Steeman-Nielsen, E. See Jerlov, N.G., Steeves, T.E. See Darling, J.D., 127 Stefanescu, C. See Parmesan, C., 470 Stegenga, H., 86 Steinbeck, J.R. See Schiel, D.R., 86 See Schiel, D.R., 473 Steinberg, P.D. See Estes, J.A., 78 Steininger, F.F. See Harzhauser, M., 319 Stelle, L.L., 136 Steller, D.L. See Zimmerman, R.C., 477 Steneck, R.S., 86, 404, 474 See Adey, W.H., 453 See Jackson, J.B.C., 399 See Vadas, R.L., 475 Stenseth, N.C. See Jonzén, N., 465 Stephen, A.C., 171 Stephens, J.S., Jr, 86 See Holbrook, S.J., 464 Stephenson, R. See Smedbol, R.K., 136 Stephensons, C. See Conkright, M.E., 311 Stepien, C.A., 337 Stergiou, K.I. See Browman, H.I., 395 Stervander, M. See Jonzén, N., 465 Stevens, C.L. See Hurd, C.L., 81 Stewart, H.L., 474 Stewart, J.E. See Holmer, M., 399 Steyaert, M. See Deprez, T., 128 St-Hilaire, A., 136 Stillman, J.H., 337 Stimson, J. See Stambler, N., 194 Stive, M.J.F. See Hamm, L., 399 Stoddart, D.R. See Ellison, J.C.,460 Stokes, T. See Ross, G.J.B., 472 Stone, C.J., 337 Stone, H.H., 136 Stone, R. See Allan, R., 190 Stoner, D. See Roughgarden, J., 333 Stoner, D.S., 474 Stott, P.A. See Karoly, D.J., 465 Stotz, L.M. See Caillaux, L.M. 309 Stotz, W., 337, 338 See Aburto, J., 304 See González, J., 318 See González, S.A., 318 See Jaramillo, E., 322 See Jesse, S., 322 See León, R.I., 324 See Meltzoff, S.K., 327 See Ortiz, M., 330 See Pérez, E.P., 331 See Thiel, M., 199–344

Sorbe, J.C., 136 See Cartes, J.E., 126 See Cornet, M., 127 See Cunha, M.R., 127 See Kouassi, E., 131 See Elizalde, M., 128 Sotka, E.E., 337 Soto, A. See Gutiérrez, D., 319 See Neira, C., 329 Soto, R., 86, 337 See Quiroga, E., 332 Soto, V. See Martínez, G., 326 Soto-Gamboa, M. See Sabat, P., 334 Sotomayor, A. See Navarrete, S.A., 329 See Wieters, E.A., 343 Southward, A. See Hiscock, K., 464 Southward, A.J., 474 See Kendall, M.A., 465 See Mieszkowska, N., 469 See Simkanin, C., 473 See Sims, D.W., 473 Spalding, H., 86, 474 Spalding, M. See Burke, L., 396 Spalding, M.D., 194, 404 Spall, S.A. See Sarmiento, J.L., 473 Span, A. See Boudouresque, C.F., 395 Spanhoff, R. See Hamm, L., 399 Spärck, R., 171 Sparks, T.H. See Lehikoinen, E., 467 See Menzel, A., 469 See Robinson, R.A., 472 Sparrow, A.D. See Friedel, M.H., 461 Speirs, D., 136 Speirs, D.C. See Lawrie, S.M., 132 Spencer, C.N., 136 Spencer, M. See Kiflawi, M., 169 Spencer, T., 194 Speransky, V. See Brawley, S.H., 456 Speybroeck, J. See Deprez, T., 128 Spicer, J.L., 337 Spiers, A.G. See Finlayson, C.M., 398 Spiess, F.N. See Genin, A., 461 Spina, F. See Jonzén, N., 465 Spinrad, R.W. See Codispoti, L.A., 311 Spivak, E.D. See Orensanz, J.M., 134 Spotila, J.R. See Binckley, C.A., 455 Srinivasan, A. See Cowen, R.K., 457 Stachowicz, J.J. See Byrnes, J., 75 Stafford, R. See Attrill, M.J., 166 Stambler, N., 194 Stamnes, J.J, See Erga, S.R., 460 Stamnes, K. See Erga, S.R., 460 Standen, V.G. See Briones, L., 308 See Santoro, C.M., 335 Standford, J.A. See Spencer, C.N., 136 Stanford, J.A. See Chess, D.W., 126 Stanley, G.D., 194 Stanners, D., 404 Stanton, T.K. See Lawson, G.L., 132

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AUTHOR INDEX Sutherland, W.J., 338 Sutton, C.W. See Eardley, D.D., 78 See Hempel, W.M., 80 Sutton, P. See Boyd, P.W., 456 See Costanza, R., 396, 457 Svendsen, E. See Edwards, M.J., 459 Swadling, K.M. See Foster, E.G., 129 Swanson, A.K., 86, 474 Swearer, S.E., 339 Sweeney, C. See Langdon, C., 466 Swenarton, J.T. See Keser, M., 466 Sykes, M.T. See Walther, G.R., 476 Sylvester, C. See Grünewald A., 318 Symonds, D.T. See Makris, N.C., 132 Syvitski, J.P.M., 36

See von Brand, E., 343 See Zamora, S., 344 Stotz, W.B. See Aguilar, M., 305 See Caillaux, L.M., 309 See Lancellotti, D.A., 323 See Lopez, C.A., 324 See Pacheco, A., 330 Stouffer, R. See Sarmiento, J.L., 473 Stouffer, R.J. See Cubasch, U., 458 See Gregory, J.M., 462 Stout, M.L. See Norse, E.A., 170 Stow, D.A. See Augenstein, E.W., 74 St-Pierre, J.F. See Kouwenberg, J.H.M., 466 Stramski, D., 36 See Boss, E., 33 Strathmann, R.R., 338 See Cohen, C.S., 311 See Lee, C.E., 323 See Palmer, A.R., 331 Striz, M. See Menzel, A., 469 Strong, A.E. See Kleypas, J.A., 466 Strotmann, B. See Schulz, H.N., 335 Strub, P.T., 338 See Blanco, J.L., 307 See Carr, M.E., 309 See Halpin, P.M., 319 See Hill, A.E., 320 See Mesías, J.M., 327 See Montecino, V., 327 See Thomas, A.C., 339 Strzepek, R. See Boyd, P.W., 456 Stuardo, J., 338 Stuart, C.T. See Gage, J.,167 See Levin, L.A., 169, 324 See Rex, M.A., 170 Stuck, L. See Price, W.W., 134 Stuxburg, A., 171 Su, J.C., 171 Su, M. See Ene, A., 460 See Herbst, L., 463 Subba Rao, N.V. See Turner, J.R., 194 SUBPESCA, 338 Suchanek, T.H., 404 Suda, Y. See Inoue, T., 130 Suh, H.-L., 136 Suharsono, 194 Suhr, S.B. See Gooday, A.J., 318 Summerville, K.S. See Veech, J.A., 172 Sundareshwar, P.V. See Morris, J.T., 402 Sundelof, A. See Moschella, P.S., 402 See Airoldi, L., 394 Surman, C.A., 474 See Dunlop, J.N., 459 Suryanarayana, A. See Varkey, M.J., 194 Susnik, A. See Menzel, A., 469 Sutcliffe, W.H., Jr. See Sheldon, R.W., 36 Sutherland, D.L., 136 Sutherland, J.P. See Moreno, C.A., 328 See Moreno C.A., 83

T Taghon, G.L. See Mayer, L.M., 133 Taguchi, S. See Goes, J.I., 462 Takahashi, K., 136 Takahashi, T. See Langdon, C., 466 Takesue, R.K., 339 Takeuchi, T., 136 Tala, F., 339 See Edding, M., 314 See Thiel, M., 199–344 See Vásquez, J.A., 342 See Véliz, K., 342 Tammaru, T. See Parmesan, C., 470 Tan, I.H. See Druehl, L.D., 78 Tanaka, H. See Sato, K., 473 Tanaka, M. See Islam, M.S., 399 See Tanaka, Y., 136 Tanaka, Y., 136 Tanguyt, A. See Moragat, D., 328 Tankersley, R.A. See Forward, R.B., 316 Tanneberger, K. See Boyd, P.W., 456 Tanner, S.J. See Martin, J.H., 326 Tanré, D. See Zhao, T.X.-P., 36 Tapia, C. See González, J., 318 Tapia, F. See Lagos, N.A., 323 See Roa, R., 333 Tararam, A.S., 137 Tarazona, J., 339 See Arntz, W., 306 See Fernández, E., 315 See Montecino, V., 327 See Peña T.S., 331 See Rosenberg, R., 333 Targett, T.E. See Lankford, T.E., 132 Tarifeño, E. See Castro, L.R., 311 See Chong, J., 311 Tarling, G.A. See Emsley, S.M., 128 Tasker, M. See Frid, C., 398 Tattersall, W.M., 137 Taylor, J.H. See Hunter, J.R., 464

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AUTHOR INDEX Taylor, L.H., 137 See Abello, H.U., 124 Teare, J.A. See Simeone, A., 337 Teas, W.G. See Foley, A.M., 460 Tegen, I. See Jickells, T.D., 465 Tegner, M.J., 86, 87, 474 See Dayton, P.K., 76, 77, 396, 458 See Jackson, J.B.C., 399 See Schimmelmann, A., 86 See Seymour, R.J., 86 See Steneck, R.S., 86, 404, 474 See Vilchis, L.I., 475 Tennent, W.J. See Parmesan, C., 470 Terborgh, J.W., 171 Terbrueggen, A. See Engel, A., 460 Terlizzi, A. See Guidetti, P., 398 Terrazzano, G. See Ianora, A., 321 Terreay, L. See Bopp, L., 455 Teske, A. See Fossing, H., 316 Teske, P.R., 339 Tester, P. See Carlsson, P., 456 Tett, P.B. See Gage, J., 167 Thamdrup, B. See Fossing, H., 316 Thangaduri, G. See Kathiresan, K., 465 Theroux, R.B. See Wigley, R.L., 138 Thessen, A.E., 474 Thibaut, T., 404 See Meinesz, A., 401 Thiel, M., 87, 199–344, 339 See Hinojosa, I., 320 See Macaya, E.C., 83, 325 See Sepúlveda, R., 336 See Valdivia, N., 340 See Wahl, M., 475 Thieltges, D.W. See Reise, K., 403 Thies, K. See Dean, T.A., 77 See Schroeter, S.C., 86 Thivierge, D. See Winkler, G., 138 Thomas, A. See Thiel, M., 199–344 Thomas, A.C., 339 See Blanco, J.L., 307 See Carr, M.E., 309 See Hill, A.E., 320 See Montecino, V., 327 Thomas, C.D., 474 See Hickling, R., 463 See Parmesan, C., 470 Thomas, D. See Harris, G., 463 Thomas, J.A. See Parmesan, C., 470 Thomas, L.P., 474 Thomason, J.C. See Wahl, M., 475 Thompson, D.W. See Gillett, N.P., 461 Thompson, J.B. See Mullins, H.T., 329 Thompson, R.C., 404 See Airoldi, L., 394 See Jonsson, P.R., 465 See Martin, D., 401 See Mieszkowska, N., 469 See Moschella, P.S., 402

Thompson, R.J. See MacDonald, B.A., 325 See Richoux, N.B., 135 Thomsen, H.A. See Nielsen, T.G., 192 Thomson, B.E. See Worrest, R.C., 477 Thomson, D.L. See Crick, H.Q.P., 457 Thoney, D.A. See Drohan, A.F., 459 Thornber, C.S. See Byrnes, J., 75 Thorne, R.E., 137 Thorpe, A. See Aguilar, A., 305 Thorrold, S.R. See McKinnon, A.D., 468 See Swearer, S.E., 339 Thorson, G. 171 Thorson, G.L., 339 Thresher, R., 474 Thresher, R.E., 474 Thrush, S.F., 171, 404, 474, 475 See Lohrer, A.M., 467 See Norkko, A., 470 See Turner, S.J., 404 Thulke, H.-H. See Grimm, V., 129 Thurston, M.H., 340 Thwin, S. See Ramaswamy, V., 193 Tija, H.D., 194 Tilman, D. See Leibold, M.A., 323 Tinney, L. See Jensen, J.R., 81 Tintore, J. See Marbà, N., 401 Tiselius, P. See Peterson, W.T., 331 Tittley, I. See Bartsch, I., 394 See Hiscock, K., 464 Tognelli, M.F., 340 Tokeshi, M., 340 tom Dieck, I. See Lüning, K., 325 See Wiencke, C., 343 Tomanek, L., 340 Tomas, F. See Invers, O., 464 Tomasin, A. See Bondesan, M., 395 Tomczak, M., 194 Tomicic, J.J., 340 Tominaga, O., 137 See Tanaka, Y., 136 See Yamamoto, M., 138 Tompkins, D.M. See Mouritsen, K.N., 469 Torbjørn, E. See Jonzén, N., 465 Torok, J. See Both, C., 455 Torras, X. See Thibaut, T., 404 Torres, R., 340 See Jickells, T.D., 465 See Rutllant, J.A., 334 Torres-Villegas, J.R. See Hernández-Carmona, G., 80, 81 Tortell, P.D., 475 See Riebesell, U., 472 Totterdell, I.J. See Orr, J.C., 470 Tourre, Y. See Allan, R., 190 Tourre, Y.M. See White, W.B., 476 Tovar, H., 340 Towle, D.W., 87 Tranter, J. See Ross, G.J.B., 472 Travers, V. See Cole, R.G., 457 Travis, J.M.J., 475

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AUTHOR INDEX UK Biodiversity Group, 404 UK Steering Group, 404 Ulloa, N. See Gómez, I., 317 See Huovinen, P., 321 Ulloa, O., 340 See Castilla, J.C., 310 See Daneri, G., 312 See Escribano, R., 314 See Farías, L., 315 See Fossing, H., 316 See Hormazábal, S., 320 See Leth, O., 324 See Yuras, G., 344 Ullrich, N. See Thiel, M., 339 Umani, S.F. See Bonnet, D., 455 UNEP/FAO/WHO, 404 UNEP/IUCN, 194 UNEP/MAP/PAP, 404 UNEP/WCMC, 405 United Nations Conference on Environment and Development, 172 Uno, N. See Tominaga, O., 137 Urban, H.J., 340 Uriarte, I., 340 Uribe, E., 340Uriarte A. See Porteiro C., 471 See Acuña, E., 305 See Avaria S., 306 See Illanes, J.E., 321 Uribe, M. See Castilla, J.C., 310 Urzua, C. See Vásquez, J.A., 342 Utter, B.D., 87

Travis, L.D. See Mishchenko, M.I., 35 Treleani, R. See Caressa, S., 396 Trenberth, K.E., 340 Trent, J.D. See Mattison, J.E., 83 Trick, C.G. See Hutchins, D.A., 321 Trillmich, F., 340 See Dellinger, T., 313 Trinder, M. See Votier, S.C., 475 Troell, M. See Chopin, T., 311 See Pihl, L., 403 Trombini, C., 404 Troncoso, A. See Bernal, P.A., 307 See González, H.E., 317 Troncoso, L. See Galleguillos, R., 316 Troncoso, V.A., 340 See Castro, L.R., 310 See Iriarte, J.L., 321 Trull, T. See Boyd, P.W., 456 Trull, T.W. See Sedwick, P.N., 473 Trumbore, S. See Mayer, L.M., 133 Tsuchiya, M., 475 Tsuei, T.G. See Geller, P.E., 34 Tsukayama, I. See Pauly, D., 331 Tsusaki, T. See Tanaka, Y., 136 Tudela, S., 137, 404 Tudhope, A.W., 194 See Brown, B.E., 191 See Scoffin, T.P., 193 Tunesi, L. See Meinesz, A., 401 Turak, E., 194 See De Vantier, L.M., 458 Turley, C. See Raven, J., 471 Turner, C.H. See Feder, H.M., 78 Turner, D.R. See Torres, R., 340 Turner, I.M. See Hesp, P.A., 192 Turner, J.R., 194 Turner, S. See Boyd, P.W., 456 Turner, S.J., 404 Turpen, S.L. See Anderson, B.S., 74 Tutschulte, T.C., 87 Twardowski, M.S., 36 See Boss, E., 33 Twilley, R.R., 475 See Ewel, K.C., 460 Twining, B.S., 137 Tyagi, A.P., 475 Tyler, P.A., 172 Tyler-Walters, H., 404 See Hiscock, K., 399 Tyson, R.V., 340

V Vacelet, J. See Perez, T., 470 Vadas, R.L., 475 Vadeboncoeur, Y., 137 Väinölä, R. See Audzijonyte, A., 125 Valdebenito, E. See Moraga, J., 328 Valdés, J., 340 Valdes, J. See Ortlieb, L., 330 Valdes, L. See Bonnet, D., 455 Valdivia, E. See Arntz, W.E., 306 Valdivia, N., 340 See Hinojosa, I., 320 Valdivia, N.A. See Macaya, E.C., 325 Valdivia, N.E. See Macaya, E.C., 83 Valdovinos, C., 172, 340 See Castilla, J.C., 310 See Marquet, P.A., 326 See Stuardo, J., 338 Valdovinos, C.R. See Fernández, M., 315 Valentine, J.F. See Mattila, J., 132 Valentine, J.P., 475 Valentine, J.W. See Jablonski, D., 169 Valentine, W.V. See Roy, K., 171 Valenzuela, G. See Vargas, C.A., 341 Valenzuela, G.S. See Vargas, C.A., 341

U Udy, J.W. See Abal, E.G., 453 Ugalde, P. See Hinojosa, I., 320 Ugarte, R. See Hoffmann, A.J., 320 Ugland, K. I., 172 See Gray, J.S., 168

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AUTHOR INDEX Valenzuela, J. See Alveal, K., 305 Valenzuela, V. See Balbontín, F., 306 Valero, J. See González, J., 318 Valero, M. See Faugeron, S., 315 Valiela, I., 405 See Hauxwell, J., 399 Vallarino, E.A. See Orensanz, J.M., 134 Valle, C. See Barbera, C., 394 Vallejo, L. See Marín, V.H., 326 Valle-Levinson, A., 341 See Atkinson, L.P., 306 See Piñones, A., 332 See Yannicelli, B., 344 Vallet, C., 137 See Dauvin, J.-C., 127 See Zouhiri, S., 138 van Aken, H.M. See Philippart, C.J.M., 470 Van Beusekom, J. See Lotze, H.K., 401 van Beusekom, J.E.E., 405 van Bressem, M. See van Waerebeek, K., 341 Vance, D., 475 Vance, D.J., 475 See Staples, D.J., 474 Van Cuyck, J.P. See David, P.M., 127 van Dalfsen, J. A., 405 van de Hulst, H.C., 36 van den Belt, M. See Costanza, R., 396, 457 van den Berg, J.B., 405 Vanden Berghe, E. See Deprez, T., 128 van den Hoff, J. See Lake, S., 132 van der Baan, S.M., 137 Vanderhoe, H. See Harris, G.P., 463 van der Leun, J.C. See Kelfkens, G., 465 van der Velde, G. See Dorenbosch, M., 459 van der Zande, W.J. See Hoovenier, J.W., 34 Vander Zanden, M.J. See Vadeboncoeur, Y., 137 van der Zwaan, G. See Barmawidjaja, D., 394 van Dijken, G.L. See El-Sayed, S., 459 van Donk, E. See Hessen, D., 463 Van Dover, C.L. See Doerries, M.B., 167 Van Dyke, H. See Karanas, J.J., 465 See Worrest, R.C., 477 Vanfleteren, J. See Remerie, T., 134 van Geen, A. See Takesue, R.K., 339 van Loveren, H. See Kelfkens, G., 465 van Oijen, T. See Kelfkens, G., 465 Vanreusel, A. See Remerie, T., 134 Van Rijswijk, P. See Dauwe, B., 127 Van Tresca, D. See Dayton, P.K., 76 Van Tüssenbroek, B.I., 87 See Cruz-Palacios, V., 457 van Vierssen, J. See Kabat, P.W., 400 van Vliet, A.J.H. See Menzel, A., 469 van Waerebeek, K., 341 See Guerra, C., 318 van Woesik, R. See LaJeunesse, T.C., 192 Váradi, L., 405

Varas, M. See Castilla, J.C., 310 See Correa, J.A., 312 See Takesue, R.K., 339 Varela, C. See Jaramillo, E., 322 Varela, D. See Buschmann, A.H., 308 Vargas, C.A., 341 See González, H.E., 317 See Narváez, D.A., 329 See Piñones, A., 332 See Thiel, M., 199–344 Vargas, M. See Sielfeld, W., 336, 337 Vargo, G.A. See Okey, T.A., 470 Varkey, M.J., 194 Vasconcellos, M. See Okey, T.A., 470 Vásquez, C. See Gutiérrez, D., 319 Vasquez, J.A. See Thiel, M., 87, 199–344, 339, 341, 342 See Buschmann, A.H., 75, 308 See Camus, P.A., 309 See Fernández, M., 315 See González, J., 318 See Graham, M.H., 39–88, 318 See Lancellotti, D.A., 323 See Macaya, E.C., 83, 325 See Munoz, V., 83, 329 See Nuñez, L., 84, 330 See Santelices, B., 335 See Tala, F., 339 See Thiel, M., 87 See Vega, J.M.A., 88, 342 Vásquez, N. See Hinojosa, I., 320 Vásquez, N.R. See Macaya, E.C., 83, 325 Vassen, W. See Volten, H., 36 Vassura, I. See Trombini, C., 404 Vasta, G.R. See Harvell, C.D., 463 Veas, R. See Palma, A.T., 331 Veech, J.A., 172 See Crist, T.O., 167 Vega, A. See Buschmann, A.H., 75 See Buschmann, A.H., 308 See Shaffer, G., 336 Vega, C. See Medina, M., 326 Vega, J.M.A., 88, 342 See Macaya, E.C., 83, 325 See Vásquez, J.A., 87, 341, 342 Vega, M.A. See Letelier, S., 324 See Vásquez, J.A., 341 Vega, S.A. See Rutllant, J.A., 334 Veit, R.R. See Helmuth, B.S., 80 Velasco-Hernández, J.X. See Velázquez, I., 342 Velázquez, I., 342 Velders, G.J.M. See Kelfkens, G., 465 Véliz, D., 342 See Vásquez, J.A., 87, 342 Véliz, F. See Lagos, N., 323 See Wieters, E.A., 343 Véliz, K., 342 Vellanoweth, R.L. See Erlandson, J.M., 78

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AUTHOR INDEX Vellinga, P. See Kabat, P.W., 400 Veloso, X. See Sielfeld, W., 336 Ven Tresca, D. See Dayton, P.K., 313 Venegas, M. See Edding, M., 313, 314 Venegas, R.M. See Navarrete, S.A., 329 See Vargas, C.A., 341 Venkataraman, G. See Madhaven, B.B., 192 Venkataraman, K. See Turner, J.R., 194 Venrick, E.L., 475 Veraart, J. See Kabat, P.W., 400 Vercoutere, T.L. See Mullins, H.T., 329 Vergara, K. See Schmalfuss, H., 335 Vergara, P.A. See Buschmann, A.H., 308 Vergara, S. See Correa, J.A., 312 Verheijen, P.J.T. See Heffels, C.M.G., 34 Verheye, H.M., 342 See Cury, P., 312 See Richardson, A.J., 471 Verlaque, M. See Boudouresque, C.F., 395 See de Villèle, X., 397 Vernberg, F.J., 342 Veron, C. See Turak, E., 194 Vetter, E.W., 88, 342 Vidal, J., 343 Vidal, M.A. See Moreno, R.A., 328 Vierstraete, A. See Remerie, T., 134 Viherluoto, M., 137 See Viitasalo, M., 137 Viitasalo, M., 137 See Linden, E., 132 See Viherluoto, M., 137 Vik, J.O. See Jonzén, N., 465 Vilchis, L.I., 475 Vilchis, M.A. See Hernández-Carmona, G., 80, 81 Vilina, Y. See Capella, J., 309 Vilina, Y.A. See Frere, E., 316 Villablanca, R. See Simeone, A., 337 Villafane, V.E. See Barbieri, E.S., 454 Villagrán, C., 343 See Hinojosa, L.F., 320 See Maldonado, A., 325 See VillaMartínez, R., 343 VillaMartínez, R., 343 Villanueva, R. See Navarro, J.C., 133 Villarroel, J.C., 343 See Acuña, E., 305 Villarroel, P. See Pauchard, A., 331 Villegas, M., 343 Villegas, M.J., 88 Villouta, E., 343 Vincent, W.F. See Winkler, G., 138 Vincx, M. See Deprez, T., 128 See Dewicke, A., 128 See Hampel, H., 129 Vinogradov, M.E., 137 Visser, A.W., 137 Visser, M.E. See Both, C., 455

Viviani, C.A., 88, 343 Vogt, H., 405 Voicu, G., 137 Volhardt, C. See Negri, A., 469 Vollmer, M. See Lotze, H.K., 401 Volse, L.A. See Devinny, J.S., 77 Volten, H., 36 See Hoovenier, J.W., 34 von Brand, E., 343 von Oertzen, J.A. See Messner, U., 401 von Rad, U. See Cowie, G.L., 312 Voss, K.J., 36 See Stramski, D., 36 Votier, S.C., 475 Voultsiadou, E. See Badalamenti, F., 394 Vousden, D. See Turner, J.R., 194 Vuorinen, I. See Flinkman, J., 128

W Wabnitz, C.C.C. See Mumby, P.J., 469 Wada, T. See Porteiro C., 471 Wærn, M. See Kautsky, N., 400 Wagener, A. See Mock, G., 402 Wahl, M., 475 See Valdivia, N., 340 Wahle, R.A., 137 Waite, A. See Boyd, P.W., 456 Wakabara, Y. See Tararam, A.S., 137 Waldenström, J. See Jonzén, N., 465 Walker, D., 475 Walker, D.I., 475 Walker, T.A., 475 Walla, T.R., Lande, R., 169 Wallace, C.C., 194 See Babcock, R.C., 454 Wallace, J.M. See Mantua, N.J., 468 See Zhang, Y., 344 Wallace, R.S. See Simeone, A., 337 Wallem, K.P. See Fariña, J.M., 315 Walsh, A. See Bowman, D.M.J.S., 456 Walsh, J.J., 343 Walsh, K., 475 See Pittock, A.B., 470 Walsh, K.J.E., 476 Walters, C.J. See Hilborn, R., 320 Walther, G.R., 476 Wang, H.J., 343 Wang, S.W. See Gong, D.Y., 317 Wang, Z., 137 See Vallet, C., 137 Wang Chen, H. See Alpers, W., 190 Wängberg, S.A., 476 Ward, B.B. See Codispoti, L.A., 311 Ward, D. See MacNally, R., 169 Ward, J.R., 476 See Harvell, C.D., 463

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AUTHOR INDEX Ward, T.M., 476 See Marsh, H., 468 Ware, D.M., 476 Waren, A. See Rex, M.A., 170 Wares, J.P., 343 Warkentine, B.E., 137 Warner, R.R. See Airamè, S., 393 See Jackson, J.B.C., 399 See Pandolfi, J.M., 402 See Roberts, C.M., 333 See Swearer, S.E., 339 See Zacherl, D.C., 344 Warren, M. See Parmesan, C., 470 Warwick, R.M., 172 See Clarke, K.R., 166, 191 See Ellingsen, K.E., 167 See Gobin, J.F., 168 Washburn, L. See Gaylord, B., 79 See Raimondi, P.T., 84 See Reed, D.C., 85 Watanabe, J.M., 88 See Graham, M.H., 79 Waterman, L.J. See Gordon, H.B., 462 Waterman, P.C., 36 Waterman, T.H., 137 See Bainbridge, R., 125 Waters, L.B.F.M. See Hoovenier, J.W., 34 Watkins J.L. See Brierley A.S., 126 Watkinson, A.R. See Fish, M.R., 460 See Gardner, T.A., 461 Watling, L., 405 See Thiel, M., 339 Watson, A. See Raven, J., 471 Watson, A.J. See Boyd, P.W., 456 Watson, E. See Gelcich, S., 317 Watson, L.M. See Pomeroy, R.S., 332 Watterson, I.G. See Gordon, H.B., 462 Way, L.S. See Davidson, N.C., 396 Waycott, M. See Carruthers, T.J.B., 457 Wearmouth, V.J. See Sims, D.W., 473 Weatherbee, R. See Thomas, A.C., 339 Weaver, R.S. See Hutchins, D.A., 321 Webb, P., 137 Weber, U. See Brandt, A., 126 Webster, M.S. See Menge, B.A., 327 Webster, P.J, 194, 476 Weeks, S.J., 343 See Bakun, A., 306 Weetman, D. See Gómez-Uchida, D., 317 Wefer, G., 319 Weichler, T., 343 Weidman, C. See Thresher, R., 474 Weikert, H. See Bonnet, D., 455 Weiner, J. See Grimm, V., 129 Weiner, N., 172 Weinstein, M.P. See Beck, M.W., 394 Weirig, M.F. See Orr, J.C., 470 Weishampel, J.F., 476 Weissing, F.J. See Huisman, J., 464

Weissner, R. See Vásquez, J.A., 342 Wellington, G.M., 476 Wells, F.W., 476 Wells, S. See Kelleher, G., 400 Welsford, D.C., 476 Wennhage, H. See Pihl, L., 403 Wenzel, H. See Westermeier, R., 343 Wernberg, T. See Fowler-Walker, M.J., 460 West, G. See Polacheck, T., 471 West, L.D. See Lyle, J.M., 468 West, R.J., 476 Westermeier, R., 88, 343 Westermeier, R.C. See Gómez, I., 317 Weston, M.A. See Chambers, L.E., 457 Westphal, C.J. See Clarke, P.J., 457 Whang, A. See Janssen, J., 130 Wheeler, A.J. See Roberts, J.M., 472 Wheeler, P.A., 88 Wheeler, W.N., 88 See Druehl, L.D., 78 Whetton, P. See Done, T.J., 459 Whitaker, A. See De Grave, S., 396 Whitakker, R.H., 172 White, E.P. See Hurlbert, A.H., 168 White, J.R. See Parkinson, R.W., 470 White, K.N. See Crisp, D.J., 312 White, R. See Mock, G., 402 White, W.B., 476 Whitehead, H. See Rendell, L., 333 Whitehead, P.J., 476 Whiteley, G.C., Jr, 138 Whitfield, J., 172 Whitmarsh, D. See Badalamenti, F., 394 Wichard, T. See Ianora, A., 321 Wickett, M.E. See Caldeira, K., 456 Wicklum, D., 138 Widdicombe, S., 172 See Austen, M.C., 166 Widdows, J. See Roast, S.D., 135 Widdowson, T.B. See Gabrielson, P.W., 79 Widmann, M. See Jones, J.M., 465 Wiebe, P.H. See Haury, L.R., 319 See Lawson, G.L., 132 Wiegand, T. See Grimm, V., 129 Wielgolaski, F-E. See Menzel, A., 469 Wiencke, C., 343, 476 See Bischof, K., 455 See Hanelt, D., 462 Wieters, E.A., 343 See Navarrete, S.A., 329 Wiff, R. See Quiroz, J.C., 332 Wigley, R.L., 138 See Maurer, D., 133 Wilcove, D.S., 405 See Norse, E.A., 170 Wilcox, B.A. See Norse, E.A., 170 Wild, C., 343 Wildish, D.J. See Holmer, M., 399 Wildman, R.D. See Dawson, E.Y., 76

532

50931_Idx1.fm Page 533 Thursday, May 10, 2007 8:34 PM

AUTHOR INDEX Wilhelm, C., 476 Wilhelm, F.M., 138 Wilkerson, F.P. See Hogue, V.E., 464 Wilkie, M.L., 405 Wilkin, J.L. See Griffin, D.A., 462 Wilkinson, C., 194, 476 Wilkinson, C.R., 405, 476 Williams, A., 476 See Koslow, J.A., 466 Williams, A.B., 138 Williams, C.B. See Fisher, A.A., 167 Williams, K. See Majkowski, J., 468 Williams, L. See Manson, F.J., 468 Williams, P.H., 172 See Gaston, K.J., 168 Williams, R. See Green, K., 129 Williams, R.J. See Dunne, J.A., 128 See Evans, M.J., 460 See Saintilan, N., 472 Williams, S.L. See Coleman, F.C., 457 Williamson, C.E. See Smith, S.L., 136 See Zagarese, H.E., 477 Williamson, M., Williamson, S. See Carcelles, A., 309 Willis, B.L. See Babcock, R.C., 454 Willis, J.K., 476 Willis, M.J. See Simeone, A., 337 Wilson, A. See González, J., 318 Wilson, G.D.F., 172 See Poore, G.C.B., 170 Wilson, J.B. See Roberts, J.M., 472 Wilson, K.S. See Binckley, C.A., 455 Wilson, M., 172 Wilson, M.E.J., 194 Wilson, P.L. See See van Dalfsen, J. A., 405 Wilson, S., 405 Wilson, S.G. See Gordon, H.B., 462 Wilton, K.M. See Rogers, K., 472 Winant, C.D. See Jackson, G.A., 81 Wing, B.L., 88, 138 Wing, S.R., 88, 343 Winkel, W. See Both, C., 455 Winkler, F.M. See Acuña, E., 304 See Véliz, D., 342 Winkler, G., 138 Winton, M. See Gregory, J.M., 462 Wishner, K.F., 344 See Levin, L.A., 324 Witherington, B.E., 476 Witman, J.D., 172 See Ellis, J.C., 314 See Fariña, J.M., 315 Wittman, K.J., 138 See Ariani, A.P., 125 Woebken, D. See Kuypers, M.M., 323 Woese, C.R., 344 Wolanski, E., 476 See Furukawa, K., 461 See Rothlisberg, P., 472

Wolfe, D.W., 477 Wolff, M., 344 See Ortiz, M., 330 Wolff, W.J., 405 See Lotze, H.K., 401 Wolters, M., 405 Womersley, H.B.S., 88, 477 Wones, A. See Behrenfeld, M., 455 Wood, L.J., 344 Wood, S.A. See Russell, R., 171 Woodle, C.M. See Roessig, J.M., 472 Woodley, C.M. See Downs, C.A., 191 Woodroffe, C., 477 Woodworth, P.L. See Church J.A., 457 Wooldridge, S. See Done, T.J., 459 Wooldridge, T.H. See Jerling, H.L., 130 See Schlacher, T.A., 135 See Webb, P., 137 Wooller, R.D. See Dunlop, J.N., 459 See Surman, C.A., 474 Work, R.C. See Thomas, L.P., 474 Worm, B., 405, 477 See Lotze, H.K., 401 See Wahl, M., 475 Worrest, R.C., 477 See Häder, D.P., 462 See Karanas, J.J., 465 Wright, J. See Both, C., 455 Wyllie-Echeverria, S. See Short, F.T., 404 Wyrtki, K., 194, 344

X Xavier, J.C. See Arata, J., 305

Y Yahia, N.D. See Bonnet, D., 455 Yaikin, J., 344 Yamada, S.B. See Menge, B.A., 327 Yamaguchi, H. See Tanaka, Y., 136 Yamamoto, G. See Asano, E., 33 Yamamoto, M., 138 Yamanaka, Y. See Orr, J.C., 470 Yáñez, E., 344 See Castilla, J.C., 310 See Silva, C., 337 Yang, P. See Dubovik, O., 34 See Hu, Y.-X., 34 Yannicelli, B., 344 Yap, K.S. See Cubasch, U., 458 Yarish, C. See Chopin, T., 311 Yearsley, J.M. See Emmerson, M., 128 Yen, A. See MacNally, R., 169 Yesaki, M., 194 Yntema, C.L., 477 Yohe, G. See Parmesan, C., 470

533

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AUTHOR INDEX Yokoyama, M. See Takeuchi, T., 136 Yonge, C.M., 405 Yool, A. See Orr, J.C., 470 Yoon, H.S., 88 Yoon, Y.H. See Ohtsuka, S., 134 York, J.K. See Valiela, I., 405 Young, B. See Sayre, R., 335 Young, C.C. See Da Silva, A.M., 312 Ysebaert, T. See Thrush, S.F., 474 Ysla-Chee, L.A. See Narvarte, M.E., 329 Yule, A.B. See Crisp, D.J., 312 Yule, G.U., 172 Yuras, G., 344 See Morales, C.E., 328 See Piñones, A., 332

Zavala, P. See Castilla, J.C., 310 Zavodnik, N., 405 See Meinesz, A., 401 Zavoli, E. See Trombini, C., 404 Zeballos, J. See Arntz, W.E., 306 Zeebe, R.E. See Riebesell, U., 472 Zege, E.P. See Kokhanovsky, A.A., 35 Zein-Eldin, Z.P., 477 Zeiss, B. See Kroencke, I., 323 Zeldis, J. See Boyd, P.W., 456 Zenkevitch, L., 172 Zentara, S.J. See Kamykowski, D., 322 Zerba, K. See Stephens, J.S., Jr, 86 Zertuche-Gonzalez, J.A. See Ladah, L.B., 82 See Chopin, T., 311 See Ladah, L.B., 323 Zhang, J. See Keller, A.A., 465 Zhang, R.H. See Wang, H.J., 343 Zhang, Y., 344 See Hutchins, D.A., 321 See Mantua, N.J., 468 Zhao, T.X.-P., 36 Zhican, T. See Rhoads, D.C., 471 Zhivotovsky, L.A., 138 Zimmer, M. See Orr, M., 84 Zimmerman, R. See Minello, T., 402 Zimmerman, R.C., 88, 477 See Kopczak, C.D., 82 Zipf, G.K., 172 Zito, F. See Bonaventura, R., 455 Zobell, C.E., 88 Zohary, T. See Hillebrand, H., 34 Zondervan, I. See Engel, A., 460 See Riebesell, U., 472 Zou, D.H. See Gao, K S., 477 Zouhiri, S., 138 See Dauvin, J.-C., 127 See Mouny, P., 133 See Vallet, C., 137 Zuleta, A. See González, J., 318 Zuljevic, A. See Meinesz, A., 401 Zuniga, O. See Ortlieb, L., 330 Zust, A. See Menzel, A., 469 Zuta, S., 344

Z Zabala, M. See Carola, M., 126 See Coma, R., 126 See Delgado, O., 396 See Ribes, M., 134 Zabloudil, K. See Grove, R.S., 462 Zach, S. See Menzel, A., 469 Zacherl, D., 477 Zacherl, D.C., 344 Zagaglia, C.R., 477 Zagal, C., 344 Zagarese, H.E., 477 Zagursky, G., 138 Zaitsev, Y.P., 405 Zalakevicius, M. See Lehikoinen, E., 467 Zamon, J.E. See Smith, S.L., 136 Zamora, S., 344 Zamorano, J.H., 344 Zamzow, J.P., 477 See Losey, G.S., 467 Zaneveld, J.R. See Twardowski, M.S., 36 Zaneveld, J.R.V., 36 See Kitchen, J.C., 35 Zang, H. See Both, C., 455 Zann, L.P., 477 Zanzi, D. See Bavestrello, G., 394

534

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SYSTEMATIC INDEX References to articles are given in bold type, references to text pages are given in regular type.

A

B Bacillariophyceae, 9 Balaena mysticetus, 109 Balaenidae, 222 Balaenoptera, 223 acutorostrata, 223 musculus, 223 physalus, 223 Balaenopteridae, 223 Balanus laevis, 66 Beggiatoa, 231, 232 Belone belone, 108 Blepharipoda spinimana, 272 Bonamia ostreae, 381 Brachyistius frenatus, 64 Brachyramphus marmoratus, 104 Bryozoa, 256 Bugula, 66

Acanthina monodon, 265, 266 Acanthocyclus gayi, 268 hassleri, 268 Acanthomysis, 104 stelleri, 96, 104 Acartia, 215 tonsa, 214, 217 Acrocalanus gibber, 430 Acropora, 178, 184 aspera, 185 formosa, 184 intermedia, 184 muricata, 184 pulchra, 185, 187 Adenocystis utricularis, 276 Agonus cataphractus, 108 Alariaceae, 42 Alcedo pusilla pusilla, 447 Allopetrolisthes, 67 Alosa pseudoharengus, 108, 123 Americamysis alleni, 102, 106 bigelowi, 96, 101, 102, 106 stucki, 102 Anchialina agilis, 94, 95, 98, Anisotremis scapularis, 67 Anomura, 263 Anous stolidus, 434 tenuirostris melanops, 445, 447 Anthozoa, 256 Aplodactylus punctatus, 67, 241 Archaea, 303 Archaeomysis, 105 japonica, 96, 104, 105 kokuboi, 96, 104, 105 Arctocephalus australis, 222 pusillus doriferus, 412 Argopecten purpuratus, 254, 257, 263, 279, 280, 281, 292, 293, 294, 296 Ascophyllum nodosum, 379 Asellota, 163 Asparagopsis armata, 66, 236, 237, 238, 241 Asteroidea, 256 Atractoscion nobilis, 103 Auchenionchus microcirrhis, 67 Aulacomya ater, 236, 237, 238, 241 Austromegabalanus, 66 psittacus, 236, 237, 238, 239 Austromenidia laticlavia, 67 Avicennia, 435 marina, 435

C Calanus, 214 chilensis, 214, 216, 217, 262 Calidris ferruginea, 429 Calliclinus genicuttatus, 67 Calyptraea trochiformis, 67 Cancer setosus, 253, 254, 267, 268 Candacia, 217 rostrata, 217 Carnivora, 222 Carpophyllum flexuosum, 445 Carukia barnesi, 432 Caulerpa taxifolia, 356, 369, 370, 371, 376 Cavolinia longirostris, 440 Centropages brachiatus, 214, 216, 217 Centrostephanus rodgersii, 435 Ceratium contortum, 213 gibberum, 213 longipes, 29 macroceros, 213 tripos, 213 Cervimunida johni, 232, 284, 285, 287 Cetacea, 222 Chaetoceros, 210, 213 coarctatus, 213 compressus, 213 curvisetus, 213 dadayi, 213 socialis, 213 Charadriiformes, 222 Charadrius bicinctus, 429 Cheilodactylus variegatus, 67, 241

535

50931_book.fm Page 536 Tuesday, May 1, 2007 4:43 PM

SYSTEMATIC INDEX Chelonia mydas, 427, 428, 429 Chionoecetes opilio, 115 Chironex fleckerii, 431 Chiton granosus, 265, 266, 267 Chlamys islandica, 263 Chlorophyceae, 9 Chondracanthus chamissoi, 275, 276 Chondrus canaliculatus, 275 Chordaceae, 42 Choromytilus chorus, 236, 238, 278 Chorus giganteus, 254 Chromis chrusma, 67 Clupea harengus, 115 Codium fragile, 296, 298 fragile ssp. tomentosoides, 380 Coeloseris mayerii, 186 Concholepas, 278 concholepas, 241, 254, 265, 266, 268, 269, 271, 272, 278, 279, 282, 292, 296 Copepoda, 214 Corallina officinalis, 236-239 Corallinaceae, 386 Corallinales, 241 Corycaeus typicus, 214, 217 Cosmarestias lurida, 69 Costariaceae, 42 Crangon, 109 septemspinosa, 109, 110 Crassilabrum crassilabrum, 67 Crassostrea angulata, 383 gigas, 292, 294, 381, 382, 383 Crepidula, 60 fornicata, 381, 385, 386 Crustacea, 197 Cryptophyceae, 9 Cyanophyceae, 9 Cymodocea nodosa, 368, 376 Cystoseira, 376, 379, 380

Durvillaea, 274 antarctica, 236-240, 275 Dynophyceae, 9

E Ecklonia radiata, 433 Eisenia, 51 arborea, 44, 62 Embiotoca lateralis, 64, 70 Emerita, 229 analoga, 228, 229, 230, 272 Emmelichthys nitidus, 431 Engraulis encrasicholus, 108 ringens, 218, 270, 272, 288 Enhydra lutris, 68 Eretmochelys imbricata, 428 Erythrops elegans, 95, 98, 99, 100, 101, 106 erythrophthalma, 98, 101, 102, 106 Eschrichtius robustus, 109, 122 Euaetideus bradyi, 217 Eubalaena australis, 222, 412 Eucalanus, 214, 216 attenuatus, 217 inermis, 214, 216, 217 subtenuis, 217 Eucampia cornuta, 210, 213 Euchaeta, 217 Eudyptula minor, 430 Euphausia, 217 distinguenda, 217 eximia, 214, 217 mucronata, 214, 216, 217, 224, 262 recurva, 217 tenera, 217 Euphausiacea, 214 Euvola ziczac, 263 Exacanthomysis arctopacifica, 103 Excirolana, 229, 230 braziliensis, 228 hirsuticauda, 228, 229 monodi, 228

D Delphinidae, 223 Delphinus delphis, 223 Demospongiae, 256 Detonula pumila, 210, 213 Dicentrarchus labrax, 108 Dicrurus bracteatus carbonarius, 447 Dictyoneuropsis, 42 Dictyoneurum, 42 Dinophysis rapa, 213 Diogenichthys laternatus, 271 Diomedea epomophora, 221 exulans, 221 Diplopsalis lenticula, 213 Donax, 229 Dosidicus gigas, 219 Doydixodon laevifrons, 67 Dugong dugon, 412, 428

F Fissurella, 241, 278, 292, 296 Flabellifera, 163 Foraminifera, 163, 256 Fucales, 379 Fucus, 376, 377, 379, 380, 434 vesiculosus 377, 378 virsoides, 379

G Gadus morhua, 108, 115 Gastroclonium parvum, 275

536

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SYSTEMATIC INDEX

J

Gastrosaccus psammodytes, 111 sanctus, 94 spinifer, 94, 95, 97, 98, 99, 106 Gelidiales, 66 Gelidium, 241, 276 chilense, 236-239, 275 Geophyrocapsa oceanica, 431, 452 Girella laevifrons, 241 Globicephala, 223 macrorhynchus, 223 melas, 223 Glossophora kunthii, 66, 236, 237, 238, 275 Goniastrea aspera, 186, 187, 188 retiformis, 186 Gracilaria, 276, 293, 301 chilensis, 292, 293, 294 Grampus griseus, 223 Graus nigra, 67 Griffithsia chilensis, 66 Guinardia delicatula, 210, 213 Gymnodinium, 210, 213 Gymnogongrus, 276

Janus edwardsii, 436 Jehlius cirratus, 271

K Kelletia kelletii, 70 Kogia simus, 223 Kogiidae, 223 Kyphosus analogus, 241

L Labyrinthula zosterae, 372 Lagenorhynchus obscurus, 223 Lamellibrachia, 232 Laminaria, 376, 380 digitata, 379 farlowii, 62 hyperborea, 377, 379 saccharina, 380 Laminariaceae, 42 Laminariales, 40, 42, 241 Larosterna inca, 222 Larus belcheri, 222 dominicanus, 222, 245 modestus, 221, 222 Lepidochelys olivacea, 427 Leptocylindrus danicus, 213 Leptomysis, 111 gracilis, 95, 98, 99, 100, 106, 111 Leptonychotes weddellii, 109 Lessonia, 42, 64, 236, 238, 240, 241, 242, 244, 246, 274, 276 nigrescens, 236-242, 254, 257-259, 261, 275, 277, 296 trabeculata, 66, 236-242, 245, 257, 260, 275, 277, 296 Lessoniaceae, 42 Lessoniopsis, 42 Leucocarbo bougainvilli, 222, 225 Libidoclaea granaria, 272 Limnoria chilensis, 254 Liparis liparis, 108 Lissodelphis peronii, 223 Lithophaga lithophaga, 379, 380 Lithothamnion corrallioides, 383, 386 glaciale, 383 Lobodon carcinophagus, 109 Loligo forbesi, 432 Lontra felina, 69, 222, 224, 241, 296 Loxechinus albus, 65, 69, 241, 260, 279, 283, 292, 296 Lucinidae, 232 Luidia, 69, 71, 72 magellanica, 241, 261

H Haliotis, 264, 301 discus hannai, 292, 295 laevigata, 427 rubra, 436 rufescens, 292, 295 Halophila stipulacea, 368 Halopteris funicularis, 236, 237, 238, 239 paniculata, 66, 241 Haplostylus lobatus, 94, 95, 98, 99 lobatus var. armata, 94 normani, 94, 95, 98, 99 Helcogrammoides cunninghami, 67 Heliaster, 71, 72 helianthus, 241, 259, 261 Hemilutjanus macrophthalmos, 67 Heterocarpus reedi, 284 -287 Heteroclinus, 434 Hildenbrandia, 66 Hippoglossina macrops, 272 Homalaspis plana, 268 Hypoleucos brasiliensis, 222 Hypsoblennius sordidus, 67

I Iiella ohshimai, 96, 104, 105 Isacia conceptionis, 67, 278 Isopoda, 256

537

50931_book.fm Page 538 Tuesday, May 1, 2007 4:43 PM

SYSTEMATIC INDEX

M

Neotrypaea uncinata, 272 Nephthys incisa, 145 impressa, 228, 229 Nereocystis, 42, 72 Nipponomysis ornata, 96, 105 toriumi, 108 Noctiluca, 12 scintillans, 431 Nothochthamalus scabrosus, 265, 266 Notobalanus flosculus, 251 Nucula proxima, 145

Macrocystis, 39-88, 236, 238, 242, 274, 283, 428 angustifolia, 42, 43, 44, 47, 51, 63 integrifolia, 42-46, 47, 51, 53, 54, 57, 60, 63, 64, 66, 67, 236, 237, 239, 240, 242, 243, 244, 259, 260, 261, 275, 296 laevis, 42, 43, 44, 46, 63 pyrifera, 42-47, 53, 54, 56, 60, 63, 64, 236, 237, 240, 257, 261, 275 Macruronus novaezelandiae, 434 Maldane sarsi, 164 Maurolicus parvipinnis, 272 Mazzaella, 276 laminarioides, 254, 275 Megaptera novaeangliae, 412, 223 Merlangius merlangus, 108 Merluccius gayi, 219, 272, 284 gayi gayi, 253 merluccius, 108 Mesodesma donacium, 228, 229, 230 230, 254, 279, 280, 281, 292, 294 Mesophyllum, 66 Mesopodopsis slabberi, 95, 97, 98, 101, 103, 106, 111 wooldridgei, 97, 111 Metamysidopsis elongata, 96, 103, 115 Meyenaster, 69, 71, 72 gelatinosus, 241 Mitrella unifasciata, 67 Mollusca, 256 Montastraea faveolata, 188 Montemaria horridula, 238 Montipora, 184 digitata, 184 ramosa, 185 Morus serrator, 428 Mugil cephalus, 67 Mustelidae, 222 Mya arenaria, 356 Mycedium elephantotus, 187 Mysidacea, 90 Mysideis parva, 96, 99, 100, 101 Mysidopsis bigelowi, 101, 102, 106, 112 Mysis relicta, 110 stenolepis, 111 Mytilus edulis, 386 trossulus, 264

O Oceanodroma tethys, 222 tethys kelsalli, 296 Ocypode gaudichaudii, 228 Oithona similis, 214, 217 Oncaea conifera, 214, 217 Ophiaycthis kroyerii, 67 Ophiura sarsi, 164 Orchestoidea tuberculata, 228-230 Orcinus orca, 223, 224 Ornithocercus magnificus, 213 Ostrea edulis, 380, 381, 382, 383, 390 Otaria flavescens, 219, 222, 224, 241, 278 juvata, 278 Otariidae, 222 Ovalipes trimaculatus, 268

P Pachyptila desolata, 221 Pagurus, 67, 272 Palythoa, 187 Pandalus borealis, 115 Panulirus, 68 cygnus, 412, 435 Paracalanus, 214 parvus, 214, 217 Paralabrax humeralis, 67 Paralichthys californicus, 108 olivaceus, 105 Paraprionospio pinnata, 232, 234, 262 Pecten, 56, 63 maximus, 385 Pelagophycus, 42 porra, 42 Pelecaniformes, 222 Pelecanoides garnotii, 222, 296 Pelecanus thagus, 222 Penaeus merguiensis, 412, 446 Perkinsus, 427 Perumytilus purpuratus, 236-239, 251, 265, 266 Petrolisthes, 263, 264 granulosus, 263, 264 laevigatus, 263, 264

N Nassarius gayi, 67 Natator depressus, 412 Nematoscelis flexipes, 217 megalops, 217 Neomysis americana, 111, 113, 117, 123, 124 kadiakensis, 96, 103, 106, 108, 112, 117 rayii, 96, 103, 104 Neophoca cinerea, 412

538

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SYSTEMATIC INDEX

R

tuberculatus, 263, 264 tuberculosus, 263, 264 violaceus, 263, 264 Phaeophyceae, 40, 275 Phaeophyta, 256 Phalerisida maculata, 228, 229 Phocoena spinipinnis, 223 Phocoenidae, 223 Phragmatopoma, 66 moerchi, 236-239, 241 Phyllophora, 379 Phyllospora comosa, 428 Phymatolithon calcareum, 383, 385, 386 Physeter macrocephalus, 223 Physeteridae, 223 Pinguipes chilensis, 67, 241 Pinnaxodes chilensis, 267 Pisoides edwardsi, 268 Platichthys flesus, 108, 432 Pleuromamma gracilis, 217 Pleuroncodes monodon, 232, 272, 273, 284, 285 Pleuronectes platessa, 108 Pocillopora, 184 damicornis, 184 Polychaeta, 256 Pomatoschistus lozanoi, 108 minutus, 108 Porcellanidae, 263 Porifera, 66, 256 Porites, 184, 185, 187, 189, 439 lutea, 184, 186 (synaraea) rusi, 184 Porphyra, 276 Posidonia australis, 429 oceanica, 368, 369, 370, 371, 373, 375, 376 Postelsia, 42 Potamocorbula amurensis, 109 Prisogaster niger, 67 Procellaria aequinoctialis, 221 Procellariiformes, 222 Prochlorococcus, 430 Prolatilus jugularis, 67 Prorocentrum micans, 213 Psammobatis scobina, 241 Psammocora digitifera, 187 Pseudochordaceae, 42 Pseudo-nitzschia cf. delicatissima, 213 pseudoseriata, 213 Pseudorca crassidens, 223 Pterodroma externa, 221 Pterygophora, 49, 50, 51, 53 californica, 62 Puffinus pacificus, 428 tenuirostris, 413, 428, Pycnopodia, 68 Pyura chilensis, 66, 236-238, 241, 259 praeputialis, 236-240

Raja clavata, 100 Rexea solandri, 434 Rhincalanus nasutus, 272 Rhizophora apiculata, 441, 444 mangle, 438, 446 Rhizosolenia, 210 imbricata, 213 Rhodophyta, 256, 274 Rhodymenia skottsbergii, 238 Rhynchocinetes typus, 283 Ruppia cirrhosa, 368 maritima, 368

S Sabellaria, 391 alveolata, 386, 387 spinulosa, 386, 387 Sardinops sagax, 218, 288, 429, 449 Sargassum, 376, 379 hornschuchii, 379 muticum, 379 Scartichthys viridis, 67 Schistomysis, 98 kervillei, 95, 98, 106 ornata, 95, 98-101, 106 spiritus, 95, 97, 98, 101, 106 Schroederichthys chilensis, 241 Scolecithrichella bradyi, 217 Scomber japonicus, 288 Scurria, 67 scurra, 258 Scytothamnus fasciculatus, 276 Semicossyphus, 68 maculatus, 241 Semimytilus algosus, 236, 237, 238, 251 Sepia officinalis, 109 Siriella japonica, 108 Skeletonema costatum, 213, 446 Solemyidae, 232 Sphenisciformes, 222 Spheniscus humboldti, 221, 222, 296 magellanicus, 222 Spionidae, 66 Sterna bergii, 413 fuscata, 434, 445 lorata, 222 Stichaster, 71,72 striatus, 241, 259 Stictocarbo gaimardi, 222 Strangomera bentincki, 272, 288 Strongylocentrotus, 68 franciscanus, 65 purpuratus, 65 Stylocheiron affinis, 217 Subeucalanus crassus, 217

539

50931_book.fm Page 540 Tuesday, May 1, 2007 4:43 PM

SYSTEMATIC INDEX Tursiops truncatus, 223, 296 Tylos spinulosus, 228, 229, 230

Sula variegata, 222, 225 Symbiodinium, 187, 419 Synechococcus, 430

U T

Undaria pinnatifida, 379 Uria aalge, 104

Tagelus dombeii, 292, 294 Taliepus, 67 Tegula, 241, 264 atra, 67, 278 tridentata, 67 Teleostei, 256 Tetrapygus, 69, 72 niger, 67, 69, 71, 241, 260, 261 Thalassarche bulleri, 221 eremita, 221 Thalassiosira, 210, 213 Thioploca, 231 Thunnus maccoyii, 431 Thyasiridae, 232 Trachurus declivis, 431, 434 murphyi, 67, 219, 220, 253, 278, 288 symmetricus, 288 Tricolia mcleani, 67 Trigla lucerna, 108 Triphoturus oculeus, 271 Trisopterus luscus, 108

V Vermetidae, 66 Vesicomyidae, 232

X Xantochorus cassidiformis, 67 Xenacanthomysis pseudomacropsis, 103, 104

Z Ziphiidae, 223 Ziphius cavirostris, 223 Zostera, 99, 373 marina, 368-376, 446 noltii, 368, 370, 371

540

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SUBJECT INDEX References to complete articles are given in bold type, references to sections of articles are given in italics, references to pages are given in regular type.

A

Cavitation, 55 CHALLENGER, 143, 146, 164, 197 Charles Darwin, 40, 173, 201 Chile Coastal Current, 202, 203, 204 Chlorophyll a, 1, 210, 250, 265, 267, 269, 271, 273, 291 Chlorophyll, 207, 212, 213, 224, 270, 437 Climate change and Australian marine life, 407–478 Australian marine biodiversity, 411–413 climate change projections for Australia, 413–419 CO2, pH and calcium carbonate saturation state, 415–416 mixed layer depth and stratification, 415 ocean currents, 415 ocean temperature, 414 precipitation and storms, 417–418 sea level, 418–419 solar radiation, 416 winds, 415 climate impacts on Australian marine life, 419–447 CO2, pH and aragonate saturation state, 438–441 currents, 435–436 mixed layer depth and stratification, 436–438 precipitation and storms, 443–446 sea level, 446–447 solar radiation, 441–443 temperature, 419–433 winds, 433–434 community impacts, 447–448 critical knowledge gaps and a way forward, 452–453 non-climate stressors, 448–449 summary, 449–452 temperate Australia, 451–452 tropical and subtropical Australia, 451 Climate change, 62, 71–73, 277, 278, 299, 303 Climate models, 407, 413, 414, 415, 416, 417, 418, 419, 426, 428, 434, 478 Coastal defence, 355, 367, 379, 388, 390 development, 345, 349, 383, 388, 390, 391 erosion, 354, 367, 387 flooding, 354 355 Coastal marine habitats in Europe, loss, status, trends, 345–405 conclusions, 393 definitions, 347–348 general European context, 348–360 EU coastal policies and trans-national agreements, 356–360 threats to coastlines, 349–356 habitats, 360–389 biogenic formations, 386–387 macroalgal beds, 376–380 maerls, 383–386 oyster reefs, 380–383

Absorption coefficient, 4, 10, 31, 37 Absorption, 1, 4, 5, 6, 7, 10, 12, 13, 14, 16–19, 20, 23, 25–28, 30, 31, 32, 37 Acoustic Doppler current profiler (ADCP), 90 Adriatic Sea, 351, 354, 355, 365, 370, 375, 380, 386, 387 Advection, 59 Aeolian dust, 411 Aerosols, 413, 416, 441 Altimeter, 181, 182 Analytical species accumulation (ASA), 160 Andaman Sea, coral reefs, 173–194 Apogamy, 49 Aquaculture, 242, 273, 279, 280, 284, 291, 292–295, 296, 298, 301, 302, 354, 356, 363, 367, 371, 381, 385, 388, 390, 392, 409, 449 Areas of Special Scientific Interest, (ASSI), 368, 376, 389 Attenuation, 1, 5, 6, 10, 12, 14, 16–19, 20, 23, 25–32

B Backscatter(ing), 5, 6, 10, 14, 16–26, 30, 31, 32, 37, 38, 114, 117, 120, 121 Bacteria, 2, 7, 8, 31, 50, 187, 196, 211, 212, 231, 232, 234, 245, 270, 440, 442 Baltic Sea, 351, 353, 354, 357, 359, 360, 367, 368, 370, 371, 374, 377, 380, 388 Benthic boundary layer, 52, 55, 57, 59, 62 Benthic-pelagic coupling, 90, 112, 198, 299, 300 Biodiversity informatics, 140, 165 Biodiversity, 62, 140, 146, 148, 164, 197, 201, 214–215, 236, 240, 295–299, 301, 302, 407, 411–413, 431, 436, 445, 453 Biogeography, 140, 146, 164, 174–179, 196, 200, 214–215, 252, 254, 255–262, 264, 273, 274, 276, 277, 304 Birds Directive, 356, 358, 368, 376, 391 Black Sea, 98, 351, 358, 359, 360, 368, 378, 379, 380, 382, 383 Bleaching of corals, 183, 188, 189, 407, 419, 421, 423, 426, 427, 428, 441, 450, 451, 452 Bonn Convention, 356, 357, 388 Bottom-up processes, 70, 198, 218, 219, 259, 261, 265 Brooding, 247, 249, 262, 267–268

C C:N ratios, 112 Calcification, 416, 432, 438, 439, 441 Carbon budget, 54

541

50931_book.fm Page 542 Tuesday, May 1, 2007 4:43 PM

SUBJECT INDEX seagrass meadows, 368–376 sedimentary habitats, 387–389 wetlands, salt marshes, 360–368 recommendations for conservation and management, 391–393 Colonisation, 58, 59, 60 Community structure, 92, 107, 111, 425, 442, 443, 445, 448 Competition, 39, 40, 44, 46, 50, 54, 56, 57, 68 Conservation and management, 391–393 Conservation, 139, 140, 141, 145, 152, 154, 157, 164, 165, 222, 223, 227, 242–244, 250, 265, 295–299, 300–301, 302, 303, 304 Coral reefs of the Andaman Sea, 173–194 biological characteristics of coral reefs, 184–188 physiological attributes of reef corals, 186–188 reef type and coral diversity, 184–186 conclusions, 190 geological history, sea floor topography and related coral biogeography, 174–179 natural and human influences, 188–190 physical influences affecting coral reefs, 179–184 oceanography, 179–181 sea temperatures and salinity, 182–183 sedimentation, 183–184 tidal influences and sea-level fluctuations, 181–182 Coral reefs, 409, 411, 412, 416, 419, 421, 423, 424, 428, 435, 439, 441, 442, 444, 445, 449, 450, 451 Coral Sea, 409, 410 CORINE project, 351, 354, 361 Coulter counter, 10

traditional approaches, 147–152 abundance distributions, 147–148 information theory and Shannon’s H′, 151–152 Simpson’s λ, 149–151 species richness and its rarefaction, 148–149 Diversity, 200, 215, 221, 230, 231, 232, 234, 237, 241, 252, 256, 258, 259, 274, 295, 296, 301, 302, 411, 412, 413, 425, 437, 445, 447 DNA, 43, 73 Downwelling, 202, 249, 270 Dredging, 173, 189 Drift, kelp, 62, 64, 65, 68, 71, 228, 244,

E Earthquakes, 173, 176, 189 East Australian Current (EAC), 407, 409, 414, 415, 419, 422, 428, 431, 435, 436, 449, 452 Echo sounders, 90 Ecology of giant kelp, 39–88 ecology of communities, 62–73 community consequences of climate change and kelp forest exploitation, 71–73 Macrocystis as a foundation species, 62–65 trophic interactions and food webs, 65–71 organismal biology, 42–54 distribution, 44–47 evolutionary history, 42–44 growth, productivity and reproduction, 50–54 life history, 47–50 population biology, 54–62 demography and population cycles, 61–62 dispersal, recruitment, population connectivity, 57–61 stage- and size-specific mortality, 54–57 Ecosystem engineers, 236–238, 238–240 Ecosystem-based management, 392 Ekman transport, 201, 204, 260, 273 El Niño (EN), 56, 70, 71, 72, 196, 198, 199, 200, 204, 211, 212, 215, 216, 217, 219, 225, 230, 235, 236, 242, 243, 244, 250, 254, 257, 258–262, 263, 273, 274, 276, 278, 280, 281, 282, 291, 293, 294, 304, 420, 431, 435 El Nino-Southern Oscillation (ENSO), 51, 52, 57, 59, 61, 62, 71, 72, 196, 198, 204, 206, 216, 218, 224–225, 230, 234, 242, 245, 253, 257, 258, 259, 260, 262, 265, 274, 288, 292, 293, 294, 299, 431, 435 Endemic species, 214, 221, 223, 224, 225, 232, 273 Endemism, 411, 412, 427 Energy budgets, 91 Eutrophication, 351, 353, 367, 371, 373, 375, 379, 385, 386 Evolutionary history, Macrocystis, 42–44 Exploitation, 39, 62, 69, 71–73 Extrapolation, in diversity, 139, 157–158, 163, 164, 165

D Deep sea, 411, 437, 438, 441 Deep-sea diversity, 163–164 Deforestation, kelp, 55, 64, 65, 72 Detritus, 7, 8, 89, 107, 110, 111, 115, 245, 246, 247 Dispersal, 39, 40, 54, 57–61, 196, 198, 199, 236, 241, 244, 245, 247–251, 252, 254, 255, 258, 269, 296, 298, 300, 303, 304, 412, 435 Disruptive fishing techniques, 353, 367, 379 Diversity estimations in sedimentary benthic communities, 139–172 conclusions, 164–166 examining large-scale patterns, 161–164 deep-sea diversity, 163–164 global latitude gradient, 161–162 history, 142–146 end of Petersen era, 144–145 Forbes zones to Petersen communities, 142–144 new era, 145–146 influx of indices, 146–152 newer developments, 152–161 extrapolation, 157–158 progress in measurement, 158–161 surrogates, 152–154 taxonomic diversity, 154–157

542

50931_book.fm Page 543 Tuesday, May 1, 2007 4:43 PM

SUBJECT INDEX

F

regionally abundant mysids and their migration habits, 97–108 European shelves, 97–101 mysid ‘umwelt’, 105–108 northeast Pacific shelves, 103–104 northwest Atlantic shelves, 101–103 northwest Pacific shelves, 104–105 other regions, 105–108 Habitat degradation, 346, 347, 348, 360, 361 363, 388, 391 fragmentation, 346, 347, 348, 368, 393 loss, Europe, 345–405 modification, 346, 349, 368, 389 Habitats Directive, 347, 356, 358, 360, 367, 368, 376, 380, 383, 386, 389, 390, 391 Herbivores, 241, 242, 245, 265, 266, 267 Humboldt Current System, 195–344 aquaculture, 292–295 artisanal benthic fisheries, 278–284 case studies, 280–283 Chilean abalone fishery, 282–283 scallop fishery, 280 sea urchin fishery, 283 surf clam fishery, 280–282 resource dynamics and management, 283–284 bio-economic aspects of industrial crustacean fisheries, 284–288 basic biology of nylon shrimp and squat lobsters, 285–286 biology and stock estimates, 286 crustacean fisheries and economic considerations, 286–288 biogeography, 255–262 El Niño-La Niña in coastal marine communities, 258–262 large-scale patterns, 255–257 role of past and present processes, 257–258 brief history of exploitation of natural resources, 277–278 first coastal settlers, 277–278 coastal oceanography, 205–208 conclusions, 303–304 conservation of marine biodiversity and Marine Protected Areas, 295–299 dominant primary producers and their role in the pelagic food web, 211–214 processes affecting primary production and export processes, 213–214 export and import processes, 244–246 between benthic habitats, 245–246 between environments, 245 between realms, 244–245 frequency and intensity, 246 fish consumers, 218–219 history of research, 200–211 first reports on a cool current in the SE Pacific, 200 from natural history to ecology to marine conservation, 200–201

Fisheries, 196, 197, 201, 206, 207, 219, 220, 221, 224, 226, 245, 278–284, 284–288, 288–292, 295, 296, 299, 353, 357, 358, 371, 381, 383, 386, 388 Fisher’s α, 147–148 Fishing, 412, 448, 452, 453 Fjords, 100, 101, 105, 106, 113, 114, 123 Fluorine cycle, 92 Fluxes, horizontal, 89, 106, 107, 113, 117 Food webs, 40, 62, 65–71, 89, 91, 107, 108–112, 113, 115, 196, 197, 210–214, 218, 219, 220, 240, 261, 269, 270 Forbes zones, 142–144 Founder effects, 44

G Gametogenesis, 48, 49 Gene flow, 40, 42, 43, 44, 53, 73, 247, 252, 253, 254, 258 Genetic diversity, 252, 253, 254, 258 relatedness, 43 Geometric optics region (GO), 8, 12, 13, 14, 16 Georges Bank, 101, 102, 109 Giant kelp, ecology, 39–88 GIS, 298 Glaciation, 176, 178 Global Coral Reef Monitoring Network (GCRMN), 174 Global warming, 173, 187, 189, 199, 208, 264, 367, 415, 418, 435, 450 Grazing, 40, 46, 55, 56, 63, 64, 65, 66, 68, 69, 71 Great Barrier Reef, 407, 408, 410, 411, 412, 419, 421, 422, 424–427, 429, 430, 434, 439, 440, 444, 445, 447, 451 Greenhouse gases, 407, 409, 413, 416, 449

H Habitat alteration, 112–113 conversion, 346, 347, 363, 365, 367, 390 Habitat coupling by marine mysids, 89–138 an appreciation of mysids, 108–122 mysid importance in the coastal marine economy, 108–115 dominating the holoplankton, 113–115 food-web roles, 108–112 108–112 habitat alteration and coupling, 112–113 lending trophic and dynamic stability, 115 reasons why mysids have been under-appreciated, 115–122 modelling difficulty, 117–122 sampling problems, 115–117 challenges and opportunities, 122–124 methods of data collection, 94–96 migratory capabilities, schooling and consequences, 92–94

543

50931_book.fm Page 544 Tuesday, May 1, 2007 4:43 PM

SUBJECT INDEX propagule supply, dispersal and recruitment variability, 246–252 dispersal, 248–249 methodological approaches to the study of dispersal, 247–248 patterns of recruitment and benthic communities, 250–252 settlement, 249–250 reproductive patterns of selected marine invertebrates, 265–268 primary productivity and gonad production, 265–267 temperature and brooding requirements, 267–268 sandy beaches, 227–230 seabirds and marine mammals, 219–227 effects of ENSO on seabirds, 224–225 food resources or breeding sites, 225–227 marine mammals, 224 seabirds, 219–224 subtidal soft-bottom communities, 230–235 latitudinal and bathymetric patterns, 232–234 temporal patterns of variability in shelf communities, 234–235 zonation patterns, 230–232 water column chemistry, 208–214 macro- and micronutrient distribution, 210–211 oxygen distribution and relevance in the organic carbon remineralization, 209–210 zooplankton consumers, 214–217 biogeographic and biodiversity issues, 214–215 future perspectives in zooplankton research, 217–218 coastal upwelling in northern Chile, 215 oxygen minimum zone, 215–216 life cycles and population dynamics, 216–217 Hydrothermal vents, 153 Hyperbenthos, 92

intertidal and subtidal hard-bottom communities, 235–240 habitat-forming species on hard bottoms, 236 macrofauna associated with ecosystem engineers on hard bottoms, 238–240 spatial and temporal dynamics of ecosystem engineers, 236–238 kelp forests, 240–244 conservation and human activities, 242–244 population dynamics and spatial distribution, 241–242 the community, 241 larval life, 268–273 behavioural traits, 268–269 feeding and larval food environment, 269–271 upwelling and larval transport processes, 271–273 life history adaptations of macroalgae, 273–277 environmental gradients and strategies of resistance, recovery and recolonisation, 274 enhanced solar radiation, 277 physiological and morpho-functional adaptations, 276–277 temperature tolerance, 276 oceanographic conditions in the SE Pacific, 201–205 outlook, long-term research vision and future research frontiers, 299–303 frontier research opportunities, 303 long-term scientific vision, 302–303 effects of future climate change, 303 high-sea conservation policy, 302 precautionary and integrative ecosystem management, 302 slope, deep-sea and abyssal ecosystems, 302 technological research on deep-sea hydrates, 302–303 short/mid-term scientific outlook, 299–302 coastal network system for marine conservation management, 301 inshore and offshore oxygen minimum ecosystems, 299–300 integrative and adaptive resource management approach to fisheries, 300 marine molecular biology, 301 marine non-indigenous species, 301 nearshore coastal oceanography and benthicpelagic coupling, 300 novel approaches in coastal mariculture, 301 ocean-atmosphere interactions and offshore oceanography, 299 training of Chilean marine taxonomists, 301–302 pelagic fisheries and fisheries management, 288–292 history of the catches, 288–289 management of pelagic fisheries, 291–292 relationships with oceanographic variations, 289–291 physiological adaptations of marine invertebrates, 262–265 population connectivity, 252–255 population connectivity studies, 253–255

I Index of refraction, 3, 6–7, 11, 12, 13, 27, 29, 32, 37 Indicator species, 140, 145, 152, 153 Individual-based models (IBM), 92, 123, 124 Information theory, 146, 151–152 Inherent optical properties (IOPs) of non-spherical marine particles, 1–38 bulk IOPs, 3–10 characteristics of particles affecting their optical properties, 6–10 index of refraction, 6–7 orientation, 10 shape, 8–10 size, 7–8 definitions, 3–6 effects of particle shape on IOPs, 29–30 IOPs of monodispersions of randomly oriented spheroids, 13–19

544

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SUBJECT INDEX

M

attenuation, absorption, and scattering: efficiency factors and biases, 16–19 exact and approximate methods, 13–14 results: IOPs of a monodispersion, 14–16 volume scattering function, 14–16 optical properties of polydispersions, 19–29 obtaining the IOPs of polydispersions of particles, 19–25 results for polydispersions, 25–29 optical regimes, 11–13 geometric optics region, 12 Rayleigh region, 11–12 Rayleigh-Gans-Debye and the van de Hulst regions, 12–13 summary and future prospect, 30–33 Integrated Coastal Zone Management (ICZM), 392 Intergovernmental Panel on Climate Change (IPCC), 183, 355, 407, 411, 414, 418 Internal waves, 181 International Union for Conservation of Nature and Resources (IUCN), 174 Intertidal zone, 44, 46, 47, 53, 72, 97, 173, 184, 185, 188, 228, 229, 230, 235, 238, 240, 244, 246, 251, 263, 264, 265, 280, 351, 360, 363, 368, 376, 384, 387, 388, 392, 411, 419, 427, 443, 444, 446 Introduced species, 356, 361, 390 Invasive species, 367, 379, 389 Island biogeography theory, 63

Macroalgae, 412, 420, 422, 423, 424, 427, 428, 436, 439, 441, 445, 446 Macroalgal beds, 376–380, 389, 390 Maerls, 383–386, 390, 391 Mangroves, 346, 376, 409, 411, 420, 422, 423, 424, 425, 428, 429, 435, 438, 441, 443–447, 449, 451 Marine Protected Areas (MPA), 197, 244, 295–299, 359, 360, 376, 389, 391, 392 Mediterranean Sea, 94, 98–102, 113, 350, 351, 353, 354, 356, 358, 359, 360, 364, 367, 368, 369, 371, 372 Meiofauna, 110 Meroplankton, 112, 113, 432 Meta-analysis, 161, 162, 165 Metapopulations, 60, 61 Microbial loop, 210, 437 Microphotometry, 50 Mie theory, 2, 13, 29, 32 Migration, 89, 90, 91, 92–94, 97–108, 109, 110, 112, 113, 117–120, 122, 123, 124, 216, 224, 253, 254, 259, 261, 285, 287, 291, 296, 408, 421, 424, 429, 432, 435, 436, 446 diel vertical (DVM), 216, 219, 220, 262, 269, 272 vertical, 90, 92, 93, 97, 100, 102, 103, 105, 109, 111, 112, 123, 124, 214, 215, 272, 303 Missing backscattering enigma, 2 Modelling, 89, 117–122, 123, 205, 218, 225, 300 Molecular biology, 299, 301 Monoclonal antibodies, 50 Monodispersions, 1, 10, 13–19, 21, 25, 29, 30, 32 Monsoon, 179, 180, 181, 183, 184, 410, 443 Mortality, stage and size specific, 54–57 Mudflats, 347, 360, 387–389, 390

K Kattegat, 351, 374, 380 Kelp, 41, 420, 433, 442, 445, 452 forests, 39, 40, 58, 61–65, 68, 70, 71–73, 238, 240–244, 245, 246, 428, 449 giant, ecology of, 39–88 Keystone species, 447, 448

N NATURA 2000, 356, 358, 359, 360, 373, 375, 376, 379, 380, 381, 382, 384, 386 Nitrogen budget, 54 North Sea, 98, 99, 351, 353, 357, 360, 374, 381, 382, 384, 388, 420, 421, 431, 432, 433 Nutrients, 196, 208, 209–210, 230, 240, 241, 242, 244, 245, 246, 247, 259, 260, 274

L La Niña (LN), 56, 61, 62, 70, 71, 204, 214, 216, 225, 234, 258–262, 280 Land reclamation, 173, 189, 345, 350, 351, 365, 366, 375, 385 Leeuwin Current, 409, 410, 412, 415, 422, 431, 435, 452 Life history, Macrocystis, 39, 40, 42, 47–50, 57, 59, 61, 62 Limitation, light, 60 nutrient, 52, 55, 57 Logarithmic series, 146, 150 Log-normal distribution, 7, 8, 147–148, 150, 164 Log-series distribution, 147–148, 150, 162, 164

O Ocean Circulation and Climate Advanced Model (OCCAM), 179 Oil spills, 73 Optical sensors, 1, 2 Overfishing, 345, 349, 381, 390, 434 Oxygen minimum zone (OMZ), 196, 208, 214, 215–216, 217–220, 230, 231, 232, 235, 247, 258, 285, 299, 301, 303 Oyster reefs, 345, 346, 347, 349, 378, 380–383, 389, 390 Ozone layer, 416

545

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SUBJECT INDEX

P

Sandy beaches, 227-230, 235, 246, 247, 256, 294 Sandflats, 376, 387-389, 390 Satellites, 181, 184, 204, 207, 250, 271, 290, 416 Scattering, 1, 2, 4-7, 9, 10, 12-18, 20-23, 25-32, 37, 38 Schooling, 89, 91, 92-94, 97, 103, 107, 111, 112, 115, 116, 117, 122, 124 Sea level, 173, 176, 177, 179, 181-182, 188, 189, 355, 356, 363, 367, 387, 388, 390, 407, 411, 413, 418419, 425, 432, 446-447, 449, 450, 451 Sea-level anomalies, 173, 181 Sea surface temperature (SST), 204, 206, 207, 224, 225, 226, 255, 261, 289, 290, 291, 294 Seagrasses, 409, 411, 412, 419, 420, 422-425, 427, 428, 429, 434, 438, 441, 442, 445, 446, 449, 451 Seagrass meadows, 345, 347, 349, 368-376, 390 Sediment dynamics, 89, 91 Sedimentary habitats, 387-389 Sedimentation, 7, 173, 183-184, 410, 444, 447 Seston, 89 Settlement, 198, 234, 241, 249-250, 261, 268, 269, 272, 277, 287 Sex determination, 47 Shannon's index, H′, 139, 145, 151-152, 153, 162, 163, 165 Shifting baselines, 345, 391 Shoaling, 104, 107, 118 Simpson's index, λ, 139, 146, 149-151, 154, 155, 156, 162, 163, 165 Solar radiation, 407, 411, 413, 416, 418, 441-443 Solitons, 181 Special Areas of Conservation (SAC), 356, 358, 368, 376, 386 Special Protection Area (SPA), 351, 356, 358 Species richness, 139, 141, 143, 144, 145, 148-149, 151, 152, 153, 155-163, 165 Stable isotopes, 70 Statoliths, 92, 93 Storm waves, 59, 65, 71 Storms, 407, 411, 413, 417-418, 424, 425, 429, 443-446, 448, 451 Surf zone, 52, 89, 97, 102-107, 111 Surrogates, for biodiversity, 152-154, 156, 160, 162

Pacific Decadal Oscillation (PDO), 71 Paramonov method, 13, 14, 17, 18, 30 Particulate size distribution (PSD), 7, 8, 21, 32, 37 Peru Coastal Current (PCC), 202, 203 Petersen communities, 142, 145, 146, 152 Phenology, 274, 275, 411, 419, 429–430, 432, 433, 434, 437, 445–446, 449, 453 Pheromones, 48, 49 Photosynthesis, 42, 49, 51, 54, 59, 73, 267, 277, 438–442, 446 Photosynthetically active radiation (PAR), 44, 48, 49 Phytoplankton, 2, 3, 7, 8, 9, 12, 14, 17, 18, 20, 23, 24, 29, 31, 32, 106, 109–113, 210, 212, 213, 214, 219, 220, 245, 269, 270, 271, 375, 410, 411, 420, 422, 425, 430, 432, 436–440, 442–447 Pneumatocysts, 47, 64 Polarised light, 93, 112, 115, 122 Pollution, 242, 269, 274, 295, 300, 301, 345, 346, 349, 351, 353, 356, 357, 358, 367, 375, 377, 383, 388, 390, 392, 448, 449, 451 Polydispersions,1, 10, 13, 14, 19–29, 30, 32 Population biology, Macrocystis, 54–62 connectivity, 57–61, 196, 248, 252–255, 261, 262, 298, 304 growth, 350, 351 Primary production (PP), 196, 197, 198, 205, 207, 208, 209, 210, 211, 212-214, 234, 259, 265, 267, 270, 271, 274, 282, 303 Protection initiatives, 357, 358 Pycnocline, 181

R Ramsar Convention on the Conservation of Wetlands, 356, 357, 367, 388 Rarefaction, 139, 145, 146, 148-149, 163, 165 Rayleigh region (RAY), 8, 11-12, 19 Rayleigh-Gans-Debye region (RGD), 8, 12-13 Recombinant DNA, 43 Recruitment, 39, 40, 47-50, 53, 54, 57-61, 62, 63, 68, 73, 197, 199, 217, 218, 229, 230, 234, 236, 238, 239, 241, 247-250, 250-251, 254, 258, 259, 261, 269, 271, 274, 280-284, 286, 293, 304, 422, 434, 435 windows, 48 Remote sensing, 44 Ribosomal RNA genes, 187 Rio Convention on Biological Diversity (CBD), 356, 357, 367, 376, 391 Rocky shores, 420, 422, 423, 427

T Tasman Sea, 407, 408, 409, 414, 431, 452 Taxonomic Distinctness, 154, 156, 157 Diversity, 154, 156 Tectonics, 174, 175, 176, 177, 179 Thermocline, 181, 182, 487 Thorson's rule, 144 Tidal transport, 272 T-matrix method, 13, 14, 16, 17, 18, 21, 30, 31 Top-down consumption, 70, 71 processes, 198, 212, 219, 250, 261 Total Allowable Catch (TAC), 284, 286, 291 Tourism, 206, 221, 284, 295, 296, 298, 299, 302, 349, 354, 358, 367, 371, 451, 453

S Salt marshes, 346-349, 352, 354, 357, 360-368, 390 Sampling efficiency, 97, 104, 116

546

50931_book.fm Page 547 Tuesday, May 1, 2007 4:43 PM

SUBJECT INDEX Trawling, 345, 368, 376, 379, 383, 386, 390 Trophic focusing, 107 interactions, 65-71 Tsunamis, 188, 189

Volcano, 175, 176 Volume scattering function (VSF), 4, 5, 7, 12, 14-16, 37

W U

Wadden Sea, 348, 350, 351, 357, 359, 360, 365, 368, 373, 378, 379, 381, 382, 383, 386, 387, 391 Wasting disease, 372, 373, 374 Waves, 44, 46, 51, 52, 54, 55, 57, 68 West Wind Drift (WWD), 201, 202, 203 Wetlands, 345, 346, 356, 357, 359, 360-368, 389, 390, 391 Winds, 407, 411, 413, 414, 415, 417, 422, 433-434, 436, 437 World Wildlife Fund (WWF), 351

Ultraviolet radiation (UV), 44, 199, 269, 277, 413, 416, 423, 441, 442, 443 Umwelt, of mysids, 105-108, 117 United Nations Environment Programme (UNEP), 174, 180 Upwelling, 181, 182, 187, 196-199, 201, 202, 204-214, 217, 218, 221, 224, 225, 230, 231, 234, 236, 242, 244, 245, 247, 248, 249, 250, 252, 257, 258, 260, 261, 262, 265-274, 280, 282, 289, 290, 299, 301, 303, 304, 410, 415, 433

Z V

Zooplankton, 7, 8, 12, 14, 90, 101, 106, 109-113, 117, 123, 196, 197, 198, 211, 212, 214-218, 219, 220, 410, 420-423, 430, 432, 433, 434, 437, 440, 443, 447, 452, 453 Zooxanthellae, 186, 188

Van de Hulst region (VDH), 8, 12-13 Vinogradov's ladder, 90, 123 Viruses, 7, 8, 30

547

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