ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY
LAGOONS: BIOLOGY, MANAGEMENT AND ENVIRONMENTAL IMPACT
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ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY
LAGOONS: BIOLOGY, MANAGEMENT AND ENVIRONMENTAL IMPACT
ADAM G. FRIEDMAN EDITOR
Nova Science Publishers, Inc. New York
Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com
NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Lagoons : biology, management, and environmental impact / editor, Adam G. Friedman. p. cm. Includes index. ISBN 978-1-61122-086-5 (eBook) 1. Lagoons. I. Friedman, Adam G. GB2203.2.L34 2010 551.46'18--dc22 2010033077
Published by Nova Science Publishers, Inc. † New York
CONTENTS
Preface Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
vii Metabolic and Structural Role of Major Fish Organs as an Early Warning System in Population Assessment C. Fernandes , A. Afonso and M.A. Salgado Benthic Foraminifera in Coastal Lagoons: Distributional Patterns and Biomonitoring Implications F. Frontalini, E. Armynot du Châtelet, J.P. Debenay, R. Coccioni and G. Bancalà
1
39
Coastweb, a Foodweb Model Based on Functional Groups for Coastal Areas Including a Mass-Balance Model for Phosphorus Lars Håkanson and Dan Lindgren
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Form and Functioning of Micro Size Intermittent Closed Open Lake Lagoons (ICOLLs) in NSW, Australia W. Maher, K. M. Mikac, S. Foster, D. Spooner and D. Williams
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Waterbirds as Bioindicators in Coastal Lagoons: Background, Potential Value and Recent Research in Mediterranean Areas Francisco Robledano Aymerich and Pablo Farinós Celdrán
153
How Important are Local Nutrient Emissions to Eutrophication in Coastal Areas Compared to Fluxes from the Outside Sea? A CaseStudy Using Data from the Himmerfjärden Bay in the Baltic Proper Lars Håkanson and Maria I. Stenström-Khalili Environmental Consequences of Innovative Dredging in Coastal Lagoon for Beach Restoration Emmanuel Lamptey
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vi Chapter 8
Contents State of Knowledge of the Trophic State of Worldwide Lagoon Ecosystems: Leading Fields and Perspectives Monia Renzi, Antonietta Specchiulli, Raffaele D’Adamo and Silvano E. Focardi
Chapter 9
Treatment of Contaminated Sediments by Chemical Oxidation Sabrina Saponaro, Alessandro Careghini, Kevin Gardner and Scott Greenwood
Chapter 10
Reconstruction of the Eutrophication in the Gulf of Finland Using a Dynamic Process-Based Mass-Balance Model Lars Håkanson
Chapter 11
Chapter 12
Chapter 13
Environmental Management and Sustainable Use of Coastal Lagoons Ecosystems Rutger de Wit, Behzad Mostajir, Marc Troussellier and Thang Do Chi Involvement of Local Users is the Overlooked Background Information for Improving Implementation of Conservation Solutions in Coastal Lagoon Management: The Case of the Ichkeul National Park (Tunisia) Caterina Casagranda Birth, Evolution and Death of a Lagoon: Late Pleistocene to Holocene Palaeoenvironmental Reconstruction of the Doñana National Park (SW Spain) F. Ruiz,, M. Pozo, M. I. Carretero, M. Abad M. L. González-Regalado, J. M. Muñoz, J. Rodríguez-Vidal, L. M. Cáceres, J. G. Pendón, M. I. Prudêncio and M. I. Dias
Chapter 14
The Alvarado Lagoon – Environment, Impact, and Conservation Jane L. Guentzel, Enrique Portilla-Ochoa, Alejandro Ortega-Argueta, Blanca E. Cortina-Julio and Edward O. Keith
Chapter 15
Adaptive Lagoon Fishery Development through Sustainable Livelihoods Approach: A Case Study of Chilika Lagoon, India Shimpei Iwasaki
Chapter 16
Vertical Flux of Ice Algae in a Shallow Lagoon, Hokkaido, Japan Yoko Niimura, Hiroaki Saito, and Satoru Taguchi
Chapter 17
The Evaluation of Some Limnological Features of the Lagoon Lakes in European Part of Turkey Belgin Çamur-Elipek and Timur Kırgız
Index
249
279
301
333
351
371
397
417 435
457 475
PREFACE Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. This book presents current research from across the globe in the study of lagoons, their biology, management and environmental impact. Chapter 1- There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they also support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. In many cases, even in sub-lethal concentrations, aquatic pollutants affect structure and normal functioning of natural populations as they can cause impacts at multiple levels of organization, including cells, tissues, organs, individuals and community level. Several aquatic species can be used to study these issues and fish has been proved to be a suitable test-organism. Fish organs, such as liver, spleen and kidney can be very helpful to understand the response mechanisms to pollutant exposure. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, the anterior part of kidney supports the main pool of several fish leukocyte types. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of these relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the abundance and diversity of wildlife and increased need for water quality. Fish are relatively sensitive to changes in the environment and toxic effects of
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pollutants may start to occur in the cell and in metabolic pathways, before significant alterations in behaviour or morphology can be identified. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the wealth of a fish population and their natural environment. Chapter 2- Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. Moreover, these ecosystems are often subjected to a great deal of anthropogenic impact, which further complicates our understanding of these habitats. Comparative studies of lagoonal environments essentially require the utilization of organisms that are distributed worldwide and occur in high density populations in most of the benthic niches. This is certainly the case for foraminifers which, as lower trophic level members, are crucial to the biological community and ideal candidates for comprehensive habitat assessment. Some widespread paralic benthic foraminiferal species are present from temperate macrotidal estuaries to tropical microtidal lagoons, thus enabling comparative studies of environmental conditions to be conducted. Since lagoons are increasingly affected by environmental stress and degradation due to pollution and other anthropogenic factors, there is a pressing need to develop a set of indicators and monitoring approaches with which to assess their health. A large number of research programs have addressed these issues within various regions, and studies of foraminiferal assemblages have produced very useful, comprehensive datasets on environmental and biotic conditions. This paper is a review of what is known about the foraminiferal assemblages living in lagoons, including their distribution according to environmental parameters and their value when it comes to assessing environmental quality in these ecosystems. Chapter 3- It is important to develop tools to get realistic predictions of how, e.g., the loading of contaminants and future climate changes may affect the structure and function of aquatic ecosystems. The CoastWeb-model presented in this work in meant as such a tool. CoastWeb is a process-based mechanistic foodweb model for coastal areas (the ecosystem scale) and includes a mass-balance model (CoastMab) for phosphorus. The model is based on ordinary differential equations and gives monthly calculations of production and biomasses for ten functional groups (phytoplankton, benthic algae, macrophytes, bacterioplankton, herbivorous and predatory zooplankton, zoobenthos, jellyfish, prey and predatory fish). CoastMab calculates in- and outflow, sedimentation, diffusion, resuspension, up- and downward mixing, biouptake and retention of phosphorus in biota. There are algorithms for, e.g., migration of fish and plankton between the given coastal area and the sea and the influence of exposure on macrophyte cover . The paper presents case-studies on eutrophication, overfishing and toxic contamination illustrating the potential of CoastWeb as a tool for sustainable coastal management. Increased nutrient loading will cause several changes to the foodweb characteristics of the studied coastal area. Some of these could be expected without a model, but here they have been quantified using a general foodweb model. The model accounts for different compensatory effects that are difficult to quantify without a
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model. The case-study on overfishing indicates that increased fishing will likely affect the studied coastal system marginally because the migration of fish from the sea is large in the studied coastal area. The case-study on toxic contamination shows that a reduction of zoobenthos biomass will have clear effects of fish production and biomass in the studied coastal area. Chapter 4- ICOLLs are considered to be one of the most ecologically productive ecosystems on earth. Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters. ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea. Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. The focus for this chapter is micro size ICOLLs, classified as any coastal water body that has: (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels. ICOLLs can be viewed in a hierarchical manner, with the ocean and catchment influencing other smaller scale processes. Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and seston within an ICOLL. Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions. In turn, these attributes determine the biological diversity and functioning of these systems. Chapter 5- Among the biological components of estuarine systems and other transitional coastal waters, waterbirds are probably the group that has been monitored more intensively and throughout longer time series, especially due to the use of citizen science. Moreover, several authors have reviewed, organized and analyzed critically the role and potential use of waterbirds as bioindicators. Recently, academic research has encouraged more intensive monitoring of waterbirds in the context of bioindication in wetlands and coastal waters. However, in the particular case of coastal lagoons, birds have received little attention compared to research efforts directed to other taxa, ignoring their important role as top predators and underestimating their contribution to various ecological processes. Few studies have included waterbirds as integral components of the food webs in lagoons, relating them to other biota. However, recent studies show that waterbirds respond to changes imposed by a variety of stressors, constituting warning signals against undesirable changes. Waterbirds can be used as bioindicators both at suborganismic and at population-community-ecosystem levels. Either approach requires that the relationships birds establish with habitats and with
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the ensemble of the lagoon‘s biocoenosis are clarified. As these relationships and the bioindicator role of waterbirds are established in more detail, stands out their usefulness as indicators of impairment in coastal lagoons of similar characteristics, subject to similar impacts with time lags. Studies on the waterbird community of the Mar Menor Lagoon (SE Spain) show the long-term response of populations to variables related to eutrophication and biological changes (proliferations of jellyfish and changes in fish stocks). Studies based on community variation in relation to internal environmental gradients of the lagoon, show spatial responses that can be mapped, and provide a basis for building indices of integrity. This is a relevant issue given the paucity of studies that explore and apply the indicator value of birds in conservation and environmental evaluation, particularly in the Mediterranean and elsewhere in temperate latitudes. Recent studies that integrate the monitoring of different physico-chemical and biotic variables of the lagoon with waterbird numbers and distribution, and research on waterbird trophic ecology based on stable isotope analysis, aim at clarifying the role of waterbirds as top-down controllers in the food webs of coastal lagoons. A role whose monitoring is also important from an applied perspective, given the potential of some waterbirds like cormorants to become conflicting species (through their interaction with fisheries). The application of these monitoring schemes to other Mediterranean lagoons emerges as a valuable tool for assessing and preventing changes in the ecological status of these systems with respect to relatively undisturbed, reference conditions. Chapter 6- The basic aim of this work has been to present a general approach to quantify how coastal systems are likely to respond to changes in nutrient loading. The conditions in most coastal areas depend on nutrients emissions from points sources, diffuse sources, river input and the exchange of nutrients and water between the given coast and the outside sea, but all these fluxes can not be of equal importance to the conditions in the given coastal area, e.g., for the water clarity, primary production and concentration of harmfull algae (such as cyanobacteria). This work describes how a general process-based mass-balance model (CoastMab) has been applied for the case-study area, the Himmerfjärden Bay on the Swedish side of the Baltic Proper. The model has previously been extensively tested and validated for salt, phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the transport processes (sedimentation, resuspension, diffusion, mixing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural variations and anthropogenic reductions of water pollutants. The results presented in this work indicate that the conditions in the Himmerfjärden Bay are dominated by the water exchange between the bay and the outside sea. The theoretical surface-water retention time is about 19 days, as determined using the mass-balance model for salt, which is based on comprehensive and reliable empirical data. This means that although this bay is quite enclosed, it is still dominated by the water exchange towards the sea. Local emissions of nutrients to the Himmerfjärden Bay are small compared to the nutrient fluxes from the sea. If the conditions in this, and many similar bays, are to be improved, it is very important to lower the nutrient concentrations in the outside sea.
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Chapter 7- Evidence suggests that hydraulic dredging is accompanied by considerable adverse environmental impacts on the receiving ecosystem especially on the benthos and water quality. Recently, innovative dredging is designed to minimise environmental impacts and enhance the ecological settings. Evaluations of environmental consequences of such innovative dredging are essential to quantify the ecological benefits and the associated impacts to ensure good environmental management. Congruently, innovative dredging (‗design with nature‘ principle) in a large tropical coastal lagoon in Ghana (Keta lagoon), West Africa, was assessed Before, During and After dredging operations on spatio-temporal scales to ascertain the environmental impacts on the macrobenthic fauna, shorebirds and water quality. A total of 9091 million cubic meter of sediment was removed from the 8m stretch of the lagoon for beach nourishment, land reclamation and creation of habitat islands. The macrobenthic fauna was sampled once in 2000 (Before), 2001 (During) and 2002 (After) along seven stations (A-0 to G-0 of 1-km interval) in the dredged channel. Water quality was assessed at the subsurface and bottom layers quarterly from June, 2001 to September, 2002. The shorebirds community abundance were quantified monthly from August 2000 to 2002, but only parallel data from August-December (peak periods of shorebirds abundance) of each year (2000-2002) was used for statistical analyses. The results demonstrate that dredging had initial adverse effects on numerical abundance of macrobenthic fauna but with evidence of recovery a year after the dredging (2002). Species recorded in 2001(During Dredging) and 2002 (After Dredging) were very similar in terms of composition particularly in the wet periods, suggesting the influence of seasonal environmental factors. The abundance of the species showed significant spatio-temporal variations (p<0.05). The macrobenthic fauna was dominated by opportunistic species of the family Capitellidae. Although, Nepthys lyrochaeta revealed higher frequency of occurrence (52%), there was significant (p<0.05) decrease in abundance after dredging (2002). Conversely, Notomastus cf. latericeus depicted significant (p<0.05) increase (recovery) after dredging (2002). There was no apparent impact on coastal avifauna although numerical abundance of wader group decreased from 78% in 2000; 69% in 2001 to 51% in 2002. Conversely, terns showed increased abundance from 17% in 2000, 21% in 2001 and 47% in 2002 indicating positive impact. The shorebirds placed in the ‗others‘ category experienced peak and trough between the period (6% in 2000; 10% in 2001, and 2% in 2002). In general mean numerical abundance of the shorebirds increased from 8.8% in 2000 (Before) to 81.5% in 2002 (After) of the periods. Temporal and spatial variability occurred in the physicochemical parameters measured (e.g., salinity, total dissolved solids, total suspended solids and sulfate). However, elevated turbidity occurred in localised areas along the fetch during the dredging operation. The results of the analysis presented are pertinent to several questions, such as what are the expected ecological benefits of innovative dredging and adverse impacts on the receiving ecosystem. Chapter 8- In the latest years, the environmental research has focused on studying the water quality of marine-coastal ecosystems and on the main consequences of human activities within these environments, their surroundings and catchments. Among aquatic water systems, coastal lagoons are particularly vulnerable to water-quality deterioration, due to their restricted water exchange. In addition, they are used as nursery areas for aquaculture and fisheries exploitations, which represent the main economic relevance for local inhabitants. Protection of the ecological status of worldwide lagoons has to be the key purpose of the
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International directives, as coastal lagoons are naturally stressed ecosystems which suffer from frequent environmental disturbances and fluctuations related to their geomorphologic characteristics, general hydrodynamics, abiotic and biological parameters. The main keys of ecological research studies in coastal lagoons are represented by the need to improve the general knowledge on system dynamics focusing on the leading aspects useful to develop eco-compatible management plans which allow us to preserve their productivity avoiding losses of biodiversity related to the increase of bioavailabile nutrients. The increasing number of ecosystems exhibiting frequently a progressive decline of water quality has led environmental researchers and managers to identify eutrophication as a major worldwide problem. The development of simple and not expensive well calibrated indices of eutrophication represents one of the most actual ecological fields in which researchers are involved. Many European countries have developed within the Water Framework Directive (CE 2000/60), an environmental quality classification scheme in order to assess the trophic state and water quality through the use of specific indices based on environmental factors. Our aim is to evaluate nowadays the state of knowledge related to eutrophication of worldwide lagoon ecosystems, highlighting the main fields of interest and major problems. Leading problems are related to the choise of useful indices, their calibration, their efficiency in describing dynamics of lagoons characterized by different trophic levels and the selection of the opportune pristine ecosystem as reference for lagoon classifications related to water quality. Chapter 9- A number of different approaches can be used when managing contaminated sediments depending on site-specific conditions, sediment characteristics, mix of contaminants in the sediment and local regulations. Ex situ management options can include landfill disposal or, more generally, the application of remediation treatments for beneficial reuse, which may improve the economics of management and/or be required to meet regulatory requirements. Chemical oxidation involves the use of chemical additives to remediate sediments contaminated by organic compounds. Due to electron transfers between two (or more) compounds, pollutants are degraded into less toxic or biologically available chemical forms. Chemical oxidation also changes the pH and redox conditions of the treated system, which may also alter the mobility of the target and other compounds and elements. Several different oxidizing agents are available that result in different effectiveness on different pollutants. The most commonly used oxidants are Fenton-like reagents (hydrogen peroxide catalyzed by bivalent iron ions), ozone, permanganate, and persulfate. Recent laboratory studies have also shown good results in peroxy-acid systems (an organic acid mixed with hydrogen peroxide) to degrade compounds such as Polycyclic Aromatic Hydrocarbons (PAHs). Oxidation is a non-selective process. Therefore, the oxidizable material within the sediment (natural organic matter, detritus, etc.), which may be a significant percentage of the sediment mass, can consume the oxidizing agent. Moreover, many different reactions can occur (acid/base reactions, sorption/desorption, dissolution, hydrolysis, ion exchange, oxidation/reduction, precipitation, etc.). Pollutant removal efficiency strictly depends on the contamination (pollutants, concentrations) and the sediment being treated (physical-chemical properties and composition). Laboratory tests are always necessary to evaluate the feasibility of the treatment to select the best oxidizer and the proper treatment configuration.
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This chapter reports on laboratory batch tests conducted on sediments from Porto Marghera (Italy) and New York/New Jersey Harbor (NY, USA). Porto Marghera sediments were treated with Fenton-like reagents to remove total petroleum hydrocarbons, PAHs, and polychlorinated biphenyls. Different oxidizers (Fenton-like reagents, persulfate, and peroxyacid) were used for the New York City sediments polluted by PAHs. For the latter sediments, the leachability of metals in the treated sediments and filtration resistance were also assessed to understand potential unintended consequences of treatment on metal availability and sediment dewatering operations. Chapter 10- The Gulf of Finland is a large bay in the Baltic Sea where major changes have taken place during the last 100 years. The Secchi depth has, for example, decreased from more than 7 m to about 5 m. The basic aim of this work has been to try to reconstruct the development that has taken place in this bay during the last 100 years. Since the conditions in the Gulf of Finland depend very much on both the river input of nutrients directly to the bay and the exchange of nutrients and water between the bay and the Baltic Proper, this work has focused on such interactions. The work describes how a general process-based mass-balance model (CoastMab) has been applied for the Baltic Proper and the Gulf of Finland. The model has previously been extensively tested and validated for phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the monthly transport processes (sedimentation, resuspension, diffusion, missing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural changes and anthropogenic reductions of water pollutants. The results presented in this work indicate that it is possible to remediate the Gulf of Finland and the Baltic Proper to the conditions that characterized the system 100 years ago. About 7000 tons of phosphorus (including 1800 tons from the tributaries to the Gulf of Finland) must then be removed on an annual basis from the present annual tributary load of about 30000 tons to the Baltic Proper. The trophic conditions in the Baltic Proper have varied relatively little during the last 25-30 years. The most marked changes in Secchi depth in the Gulf of Finland took place between 1920 and 1980. Chapter 11- This chapter illustrates some of the major issues for the management and use of coastal lagoons using two examples from the South of France. These are the mesotidal Bassin d‘Arcachon on the Atlantic coast and the microtidal Etang de Thau on the Mediterranean (see Figure 1). Oyster-farming is a major use in both lagoons. Coastal lagoons are part of a coastal landscape and are therefore typical transition zones between the continent and the sea, characterised by gradients and ecotones. Thus, it is most important to consider the coastal lagoon ecosystems in the context of the coastal zone and consider their links both with the ocean as well as with the hinterland. The latter requests a thorough knowledge of the watershed of the lagoon. Coastal areas, which are commonly defined as the interface or the transition area between land and sea, are diverse in function, form and dynamics. In general, these systems are not well defined by strict spatial boundaries and include low lands, intertidal zones, salt marshes, wetlands, lagoons and their watersheds. From the development and management point of view, the coastal areas are characterised by the economical
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activities that they support and by the impact of these activities on the environment. Accordingly, the coastal areas are characterised by i) the production of living resources, ii) highly diverse human uses including urban development, exploitation of sediments, shipping and harbours, commercial and sport fishing, aquaculture, tourism, and as a receptacle of industrial and agricultural waste, iii) their role in providing protection against flooding and by iv) their biodiversity and role in the functioning of the ecosystems at different spatial levels. Chapter 12- The Garaet El Ichkeul in Northern Tunisia has long been recognized as one of the four major wetland areas in the Western Mediterranean basin (MAB Reserve in 1977, World Heritage and Ramsar site in 1980). The Ichkeul lagoon and its marshes perform essential ecological functions which are the basis of multiple services that contribute to the wellbeing and economy of the local community. The villagers living within the core area and the buffer zone have used to make a living off the land that did not seem to pose any threat to the functions and services of these ecosystems. However, the construction of dams on the rivers which provide water for the lake and marshes, as planned by the Tunisian Ministry of Agriculture for the purposes of agricultural, urban and industrial development, has had an impact on the ecological character of the site. The Tunisian authorities, aware of the impact of these dams on the natural environment at Ichkeul, founded a National Park. Unfortunately, the Park regulations were introduced without taking properly into account the reality of the socio-economic conditions of local residents. The lack of rehabilitation measures forced the villagers to exploit the resources in a non-selective way, which in turn further aggravated the existing pressure on the Park and the precarious social conditions in which the families survive. An international multidisciplinary study of all biotic and non-biotic aspects of the National Park drew up an integrated management plan which was designed to take into account the socio-economic development of the region. Since then, a number of conservation measures have been adopted by the Tunisian authorities. They mainly take into account the flora and fauna but without consultation of the people affected by these measures – a fact that possibly explains the limited implementation of the management plan proposed by the multidisciplinary study. The question is of more than local interest, since similar problems arise throughout the Mediterranean and elsewhere, i.e. conservation measures have been introduced but the legislation is not respected in practice. When stakeholders are not involved initially or are brought into the process at a later date, without the opportunity to provide input, they are seldom supportive of the policy outcome. This is due in large part to the continued reluctance of natural scientists and developers to learn from local community practices, as opposed to management systems established on the basis of scientific facts. However, recent studies on traditional ways of living off the land claim that the local communities have developed elaborate processes for sustainably exploiting their resources. Such practices can provide an important information base for integrated resource management. The goal is: (1) to promote recognition of the traditional resource practices and the accumulated wisdom as important features within ecological research, and (2) to stimulate debate about whether their input will have significance for improving environmental management policy. Chapter 13- A multidisciplinary study of sediment cores from Doñana National Park (SW Spain), a broad region of wetlands in SW Spain, provides the base for the reconstruction of the main palaeoenvironmental changes that occurred in the Guadalquivir estuary since OIS 3. The facies analysis differentiates six main facies, deposited in freshwater pond and marsh
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(FA-1: laminated silt), brackish marsh or the periphery of a brackish lagoon (FA-2: greyish silt), a shallow lagoon (FA-3: green silt and clay), the marine connection of this lagoon (FA4: yellow silt) or sandy spit (FA-6: yellow sand), whereas FA-5 includes bioclastic silt and sand with a tsunamigenic origin. The vertical arrangement of these facies, their dates and a detailed comparison with previous works permit to delimitate ten phases in the Late Pleistocene to Holocene evolution of this lowland. In the oldest phase (OIS 3), this area was occupied by freshwater marshes. Phase 2 (OIS 2) was characterized by the alternation of freshwater and brackish marshes, partly enclosed by aeolian units. During the third phase (Early Holocene), the brackish marshes constituted the northern limit of a broad lagoon that extended along the present-day inner shelf. The sea-level highstand of the Present Interglacial (Flandrian transgression, phase 4: ~6.5 cal BP) caused the inundation of this area, occupied by an open lagoon. Between 6.5 and 4.6 cal ka (phase 5), incipient brackish marshes emerged along the margins of this lagoon and a first tsunamigenic event (5100-4800 cal BP) eroded partially the Doñana spit. The following phase (4.6-3.7 cal ka) was relatively quiet, with predominance of infilling processes. This calm scenario was interrupted by a new period of instability (phase 7: 3.7-3 cal ka), with two new high-energy events. The progressive infilling is the main feature of phase 8 (3-2.2 cal ka), with the emersion of new brackish marshes and a decreasing depth in the adjacent lagoon. The first historical tsunamis (phase 9: 2.2-1.9 cal ka) induced the creation of washover fans and bioclastic ridges overlying the previous marshes. Since 1.9 cal ka (phase 10), the growing of the Doñana spit and the fluvial-tidal sediment inputs caused an important filling of the Guadalquivir estuary (Doñana National Park), only interrupted by new tsunami records (~1.8-1.5 cal ka). Chapter 14- The Alvarado Lagoon System (ALS) in south-central Veracruz State, Mexico, is a mangrove dominated coastal wetland formed by the confluence of the Acula, Blanco, Limon and Papaloapan rivers. The ALS has a maximum width of 4.5 km, a mean surface area of 62 km2, and is connected to the Camaronera Lagoon by a narrow channel and to the Gulf of Mexico (GOM) via a 0.4 km wide sea channel. Water samples were collected during the wet (September 2005) and dry (March 2003 and 2005) seasons. Salinity ranged from 1-25.5 psu and pH was slightly alkaline (7.6-8.6). Levels of total organic carbon (TOC), total mercury (Hg), and total suspended solids (TSS) ranged from 3.9-20.9 mg C/L, 0.92-26.1 ng Hg/L, and 1-39.2 mg TSS/L, respectively. The strong correlation (R2=0.71; P=0.001) between total mercury and TSS in the water column suggests that particulate matter is a carrier phase for mercury within the Alvarado and Camaronera Lagoons. The ALS is one of the most productive estuarine-lagoon systems in the Mexican GOM. Model studies suggest that primary production by sea grasses provides more energy input to the ecosystem than detritus, which is contrary to most other Mexican GOM lagoons and estuaries. In 2004 the ALS was nominated Ramsar site no. 1355 because of its important biodiversity, ecological attributes, and high resource production. Over 100 fish species have been collected from the ALS, representing four ecological guilds: marine stenohaline, marine euryhaline, estuarine, and freshwater fishes. These assemblages have not experienced significant changes over the past 40 years, but there has been a recent decline in diversity. Antillean manatees (Trichechus manatus manatus) historically have occurred in the ALS but were reduced in the 1970s and 1980s by hunting and are now considered endangered. The rescue of 6 orphan calves between 1998 and 2000 suggests that manatees are reinhabiting the ALS as a result of conservation measures. Manatees are most commonly sighted in the
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Alvarado Lagoon, Acula River and adjacent lagoons, and are rarely sighted in the Limon River and adjacent lagoons. To protect the manatees and their habitat an educational program was developed in 1998 and an assessment of their current status and critical habitat in the ALS was conducted. Our manatee conservation efforts were recognized in 2001 when September 7th was officially declared the ―National Day of the Manatee‖ in Mexico. Almost 350 species of birds occur in the ALS, including the Mexican Duck (Anas diazi), which is undergoing a slow but marked decline due to habitat destruction and overhunting. The largest threats to the ALS include unsustainable sugar cane cultivation, cattle-ranching, coastal urban development, oil and gas exploration and exploitation, water pollution by urban waste and agricultural runoff, and increases in port and tourism industries. Despite the establishment of government policy and measures to protect the coastal wetlands of ALS, the identified threats continue to menace the important biodiversity and human well-being of the region. Chapter 15- Fishery resource in the lagoon environment is the primary form of livelihood for survival and affects lives in different ways. For centuries, fishermen used to keep a certain harmony with fishery resources in a traditional manner but they have been faced with various vulnerabilities in managing fishery resources and their related livelihoods. This chapter presents a case study of fishing communities in Chilika Lagoon (India) with emphasis on adaptive capacity to respond to changes in the lagoon environment. It explores pressing constraints and positive strengths of lagoon fishery development by applying the concept of Sustainable Livelihoods Approach (SLA). The research is based on five livelihood assets analysis developed by DFID with due consideration of vulnerability assessment and institutional contexts. Drawing on Chilika Lagoon experience, the study revealed that vulnerabilities to fishery livelihoods are affected by climatic and environmental dimensions as well as by socio-economic and cultural values. The range of pressing constraints for fishing communities covers not just fishing but also marketing, schooling, social relations, social infrastructure and environmental and disaster prevention awareness. This exposure posed grave threats in lowering the capability of people in the choice of lagoon fishery development, leading to less income generation and its associated byproducts. In contrast, the study identified several attempts to cope with the underlying root causes of failure in resource-based development. The Chilika Development Authority (CDA), for instance, implemented hydrological interventions in 2000, resulting to fisheries enhancement with a spectacular increase in fish landings. The elaborations undertaken by CDA also made great contributions to institutional arrangements for watershed management with a concept of participatory micro-watershed management that has enabled the upper communities to upgrade their socio-economic status as well as mitigate the impacts of siltation. Importantly, innovative activities which are considered to be positive strengths of lagoon fishery development have been commonly associated with the involvement of various stakeholders to adjust to the ecological-social-economic system in response to actual or expected impacts. Finally, this chapter draws some suggestions on adaptive strategies for fishery development in Chilika Lagoon and potential implications to other lagoons all over the world. The findings in Chilika Lagoon fisheries provide answers to the enquiry on holistic and integrated measures to sustain lagoon fisheries by putting forward the principle of SLA. Chapter 16- A seasonal variability in the vertical flux of ice algae was examined with a multiple sediment trap during seasonal ice coverage in SaromaKo Lagoon, Hokkaido, Japan. The multiple sediment traps were moored at 4 m below the water surface and 5 m above the
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bottom to collect suspended materials at 7 dayintervals for 64 days from February 4 to April 8, 1999. Community structure of ice algae and water column phytoplankton collected with the sediment traps was determined in terms of both cell abundance and cell volume. For the ice algal community, Odontella aurita was the most dominant in cell volume, followed by Pleurosigma spp., Achnanthes spp., Detonula confervacea, Bacteriaosira fagilis, Fragilariopsis spp., and Navicula spp. while Fragilariopsis spp. and Achnanthes spp. were dominant numerically. Water column phytoplankton were dominant in descending order of cell volume by Membraneis spp. Thalassiosira spp. Campylodiscus sp., Chaetoceros spp., Amphora spp., and Dictyocha speculum, and Alexandrium sp. Mean cell volume ratio of ice algae to total algae with one standard deviation was 0.30 ± 0.28 and highly variable although a similar ratio based on cell number was 0.72 ± 0.06. The vertical fluxes of chlorophyll a (Chl a) was estimated from the volume ratio, and the mean with one standard deviation was 0.90 ± 0.42 mg Chl a m−2 d−1. This suggests that the ecological role of ice algae in a small embayment should be considered separately from ecosystem in the high latitudes although a total release of ice algal carbon from the sea ice into a water column could be similar to one in the high latitudes and only 3 g C m2 in 65 day ice season. Even during the ice coverage, due to a lateral transport of phytoplankton through two channels from the Sea of Okhotsk, where ice coverage was always incomplete, the community structure of released ice algae under the sea ice was modified significantly. A combination of laterally transported water column phytoplankton and vertically released ice algae into the underlying water column may play a significant role in the energy transfer to the successful aquaculture of scallops and oysters as well as other benthos in the shallow coastal water ecosystem. Chapter 17- Lagoons have perfect hydrodynamic perspective and very sensitive structures. First of all, the human activities on lagoons have become a major environmental concern. Any artificial influence to these sensitive areas may cause the destruction of the natural balance of them. Turkish coasts have more than 70 lagoon lakes which are formed on about 60 000 ha. area. European part of Turkey which is also named as ―Turkish Thrace‖ is surrounded by three different seas: The Marmara Sea, The Black Sea, and The Aegean Sea. The region has a lot of lagoon lakes (such as Lakes Mert and Erikli are located on the coasts of The Black Sea in Kırklareli province; Lakes Terkos, Küçükçekmece, and Büyükçekmece are located on the coasts of The Marmara Sea in İstanbul province; and Lakes Gala, Dalyan, Taşaltı, Işık, Vakıf, and Tuzla are located on the coasts of The Aegean Sea in Edirne province) which are formed at different types. Therefore, Turkish Thrace may be considered as a rich area in terms of lagoon lakes. Furthermore, some lakes are important parts of some National Parks in Turkey. In this chapter, some limnological features of some lagoon lakes located in European part of Turkey were evaluated. With this aim, both the results of the previous limnological studies performed by different researchers (by the authors and/or the others) since 1987 in some lagoons in the region and the results of the present data on the lakes which were visited on different dates by the authors at the years 2008 and 2009 for sampling were evaluated. According to the all data (both from the previous studies and from the present study) some physicochemical features, salinity levels, some biological data of the lagoons were gathered in this chapter. Furthermore, rather roughly trophy levels of the lagoons were determined by the available features which are used to determine the trophy level of the lakes. In conclusion, this study aimed to gather all data on the lagoons in European part of Turkey by making a comparison of their former and present status.
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Consequently, the results from the previous limnological studies performed in some lagoons in the region (a review); the results from the present data on some features of some lagoons (a research); limnological evaluation on all of the lagoons in the region (an evaluation) were provided in the present chapter. Thus, it was provided the whole limnological documents which have been gathered from the lakes at separate times since 1987.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 1-38 © 2011 Nova Science Publishers, Inc.
Chapter 1
METABOLIC AND STRUCTURAL ROLE OF MAJOR FISH ORGANS AS AN EARLY WARNING SYSTEM IN POPULATION ASSESSMENT 1
C. Fernandes 1*, A. Afonso 2 and M.A. Salgado 2
IPB - Instituto Politécnico de Bragança, CIMO - Centro de Investigação de Montanha, Campus de Santa Apolónia, Apartado 1038, 5301-854 Bragança, Portugal 2 ICBAS - Instituto de Ciências Biomédicas de Abel Salazar, CIIMAR - Centro Interdisciplinar de Investigação Marinha e Ambiental, Rua dos Bragas, 289, 4050-123, Porto, Portugal
ABSTRACT There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they also support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. In many cases, even in sub-lethal concentrations, aquatic pollutants affect structure and normal functioning of natural populations as they can cause impacts at multiple levels of organization, including cells, tissues, organs, individuals and community level. Several aquatic species can be used to study these issues and fish has been proved to be a suitable test-organism. Fish organs, such as liver, spleen and kidney can be very helpful to understand the response mechanisms to pollutant exposure. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms * Corresponding author: E-mail:
[email protected]. Fax: +351 273 325 405.
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C. Fernandes, A. Afonso and M. A. Salgado occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, the anterior part of kidney supports the main pool of several fish leukocyte types. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of these relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the abundance and diversity of wildlife and increased need for water quality. Fish are relatively sensitive to changes in the environment and toxic effects of pollutants may start to occur in the cell and in metabolic pathways, before significant alterations in behaviour or morphology can be identified. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the wealth of a fish population and their natural environment.
1. INTRODUCTION There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the total and the diversity of wildlife and increased need for water quality. Fish, compared with invertebrates, are more sensitive to many toxicants and are the convenient test-objects for water quality assessment and toxicological effects. They are exposed to pollutants via two main routes, waterborne and dietary and, fish can develop early signs of toxic effects, even with low contamination levels. Depending on time of exposure, bioavailability and chemical speciation of pollutants in water, as well as several biotic and abiotic factors, and synergistic or antagonistic effects, aquatic pollutants can cause impacts on natural fish populations at multiple levels of organization, including cells, tissues, organs, individuals and community. Several biomarker evaluations can be used to monitor environmental activities. Toxicants body burden in fish tissues can be a helpful indicator of contaminant exposure however it depends on chemical type and speciation, and metabolic processes such as absorption, redistribution and compartmentalization into specific tissues and it is not easy to interpret,
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when there are several contaminants involved. On the other hand, the variety of highly sensitive physiologic mechanisms in fish, together with multiple contaminants exposure, may lead to an integrated stress response, beyond to their toxic effects at the cell and tissue levels. The ideal bioaccumulation marker of exposure is one that is chemical-specific, accurately measurable in trace quantities, measurable in easily sampled biological tissues or by noninvasive techniques, and correlates well with exposure history (Van der Ost, 2003). However several biomarker responses have been tested on limited number of compounds, ecosystems, and for relatively short periods of time. The complementary use of non-specific biomarkers could bring a wider range of application on environmental monitoring, related to broadspectrum of contamination. Fish organs, such as liver, spleen and kidney can be helpful to evaluate the impact and understand the response mechanisms to toxic exposure and so can be used as useful biomarkers in monitoring environmental quality. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, kidney is the major hematopoietic organ and its anterior part (pronefros) supports the main pool of several fish leukocyte types. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the quality of aquatic environment and fish population wealth. Biochemical responses to contaminant exposure can include changes in hematologic parameters and in plasma electrolytes concentrations, as well as histopathologic alterations in several organs including liver, kidney and spleen. It is also useful, from both economic and public health points of view, to assess the effect of chemical pollutants on the fish immune system, and on their vulnerability to infection.
2. LIVER, ITS ROLE IN METABOLISM, ACCUMULATION AND REGULATION OF XENOBIOTIC COMPOUNDS Fish liver, the largest visceral organ, plays a major role in metabolism, namely detoxification, protein and hormone synthesis, glycogen storage and lipid metabolism. It produces bile, an alkaline compound which aids in digestion, via the emulsification of lipids. It also performs and regulates a wide variety of biochemical reactions requiring highly specialized tissues, including the synthesis and breakdown of small and complex molecules, many of which are necessary for normal vital functions (Wolf and Wolfe, 2005). Liver has also a key role in regulating vertebrate homeostasis, including reproductive cycle (Rocha et al., 2003). There are two general basic types of livers: those that contain pancreatic tissue vs. those that do not. Fish livers with exocrine pancreatic tissue are often called ―hepatopancreas‖ (Bruslé and Anadon, 1996; Rocha and Monteiro, 1999). Reports on the morphology of fish liver reflect the structural non-lobulation of the hepatic parenchyma, quite different from traditional lobulation as reported in the mammalian liver.
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The liver major vascular organization consist of afferent blood vessels entering by the hilum – hepatic artery and portal vein – and efferent veins - hepatic vein(s) - emerging at the anterior surface of the organ, which is not always a single vessel. It is consensual that hepatocytes are the main component of the fish liver and the most important structural element of the hepatic parenchyma. Covering the liver, there is a thin (Glisson) capsule that can bridge through the submesothelial connective tissue with the intrahepatic interstitial one. The more numerous liver cells are hepatocytes and usually 3 structures appear evidenced: dense bodies - that include primary and secondary lysosomes and residual bodies -, lipid droplets and glycogen. Hepatocyte morphology depends on the quantity of storage products, such as lipid and glycogen, and also on the reproductive cycle, in particular the estrogeninduced state of vitellogenesis in spawning females (Vethaak, 1993). Hepatic organization is not exactly the same in all fish species (Robertson and Bradley, 1992) and variations with age, nutritional status, temperature and sexual maturation normally occurs (Van Bohemen et al., 1981; Storch et al., 1984; Barni et al., 1985). The endocrine influences, which are strongly connected with the environmental regulation breeding status, also affect hepatic structure (Rocha and Monteiro, 1999).
Histopathology Histopathology of fish liver is a monitoring tool that can provide an assessment of the effects of environmental stressors on fish populations, and it has been considered one of the most reliable indicators of health impairment on aquatic animals due to anthropogenic activities (Hinton and Laurén 1990; Stentiford et al. 2003). Despite some morphological differences among species, liver is essentially similar in all vertebrates. There are more similarities than differences between fish and mammals in terms of their macro- and microanatomy, physiological and biochemical characteristics, and pathologic responses to hepatotoxic substances (Wolf and Wolfe, 2005). In terms of anatomical differences, fish have a relatively lower liver to body weight ratio, they have 1/4 to 1/2 less liver perfusion than mammals (Klassen and Plaa, 1967; Gingerich, 1984). But it is however, the hepatocyte architecture one of the relevant features of fish liver anatomy. The relation of hepatocytes and the blood ductules and canaliculi draining into them, make the basal and basolateral aspects of hepatocytes the only ones to be directly exposed to sinusoidal perfusion. Consequently the uptake of some chemicals may be lower. On the other hand, the blood flow through fish hepatic sinusoids is relatively slower, increasing the time of uptake, which may partially compensate for the reduced hepatocyte exposure (Hinton, et al. 2001, Gingerich, 1982). Liver histopathology has been used as an indicator of environmental stress since it provides a definite biological end-point of historical exposure (Stentiford et al. 2003), and the kind of injury is often dependent upon time of exposure to pollutants, such as metals (Yang and Chen 2003; Au 2004; Olojo et al. 2005). Although, liver histopathological alterations are not specific to pollutants, several studies have established a causal relationship between metal concentrations and fish liver lesions (Au 2004). Because the liver is so important in detoxification, exposure to contaminants can lead to an increase in liver size from hypertrophy (an increase in size), hyperplasia (an increase in
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number) of hepatocytes (Goede and Barton 1990; Hinton and Lauren 1990), or both. Significant higher Zn- and Cu-liver content associated with extensive hepatic heterogeneous parenchyma, with large spectrum of vacuolization, observed in mullet (Liza saliens) suggest that these abnormalities could be a response to metal chronic exposure (Fernandes et al., 2008c). Ultrastructural changes induced by toxicant exposure may include increased numbers of organelles such as myelinated bodies, mitochondria, glycogenosomes, peroxisomes, and lysosomes, and changes in rough endoplasmic reticulum (increased amount, vesiculation, and dilatation). Physiologic hypertrophy of hepatocytes can be observed in reproductively active female fish, or in male fish that have been exposed to exogenous estrogenic compounds, since estrogens stimulate hepatocyte metabolism for vitellogenin (yolk lipoprotein) production (Wester et al., 2003). These phenomena however can have a physiologic or toxicologic cause. Cytoplasmic and nuclear enlargement (megalocytosis), are others histologic alterations observed in cases of algal toxicity in farmed Atlantic salmon (Kent et al., 1988; Andersen et al., 1993; Stephen et al., 1993). Other types of nuclear changes, such as enlarged, binucleate, or bizarre nuclei, are seen occasionally, most often in the repair stages of toxicosis (Ferguson, 1989). A common and certainly pathologic, response of the fish liver to toxins is hepatocyte necrosis. The most characteristic reaction to toxicity is an apoptotic type of single cell death (Ferguson, 1989; Boorman et al., 1997). Typically, a random pattern of necrosis rather than a zonal pattern can be seen in fish liver, although occasionally a perivenous distribution of necrosis is observed (Casillas, et al., 1983). Necrosis of the biliary epithelium can also be induced in rainbow trout experimentally exposed to the toxin alpha-naphthylisothiocyanate (Metcalfe, 1998). Unlike mammals, cirrhosis is rarely seen in the fish liver as a sequel to hepatocellular necrosis (Ferguson, 1989). Piscine cholangiofibrosis may be accompanied by bile duct hyperplasia, increased numbers of bile ductule and/or oval cells, and nonneoplastic proliferation of the biliary epithelium (Boorman et al., 1997). Neoplasia, in fish liver collected from natural waters, has been one of the histologic biomarkers used in many research studies, to assess the hepatotoxicity of pollutants. There is now solid evidence, however, that fish should also be recognised as valid models for assessing other nonneoplastic biomarkers, in terms of both field and laboratory-based research (Wolf and Wolfe, 2005).
Glycogen and Lipid Reserves A common morphologic response of the fish liver to toxicity is a loss of hepatic glycogen and/or lipid (Ferguson, 1989). Macroscopically, affected fish have small, dark livers; microscopically, decrease of hepatocellular vacuolization, and size alterations of hepatocytes. Loss of glycogen or lipid can occur as a direct effect of intoxication, or it may occur secondary to decreased body condition, caused by inanition, stress, or concurrent disease. The latter is probably more typical. However, accumulation of fat or glycogen in the liver has also been observed in Japanese medaka (Oryzias latipes) (Wester et al., 1988) and guppies (Poecilia reticulate) (Wester and
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Canton, 1987), as a result of organotins exposure. The hypothesis to explain such results was that glycogen accumulation was due to decreased glycogen breakdown in consequence of hepatocellular toxicity. Liver of fish stores large amounts of lipids (triglyceride), but unfortunately this feature can hardly be used as a biomarker of hepatotoxicity since there are no accepted criteria for the diagnosis of hepatic lipidosis. Different percentages of lipid concentrations can be accumulated by different fish species (McLelland et al., 1995), so that the concentration above which lipid accumulation would be pathologic, would rather vary, however there are several reasons to use this alteration with some precaution as a reliable biomarker of contamination. Hepatic lipidosis in extreme may result in the fusion of the fat globules from neighbouring hepatocytes, but even though may not be detrimental or irreversible in all fish. In addition it may be nutritionally induced (Penrith et al., 1994) by an excessively energy-rich diet or caused by lipid peroxidation associated with diets rich in polyunsaturated fats and/or by the suppression of vitamin E (Ferguson, 1989). Lipid peroxidation in fish may also be toxicant-induced. The induction of hepatic lipid peroxidation caused by chronic dietary exposure to Cu was confirmed in grey mullet (Chelon labrosus) (Baker et al., 1998) and in mullet (Liza saliens) chronically exposed to Cu (Fernandes et al., 2008b). Sediment contaminated with polyaromatic hydrocarbons, polychlorinated biphenyls (PCBs), and metals have been described as lipid peroxidation inducters in channel catfish (Di Gulio et al., 1993) and in juvenile grey mullet Liza ramada exposed to atrazine (Biagianti-Risbourg and Bastide, 1995). Lipid or glycogen vacuolization can cause an increase in the size of hepatocytes; however, Hinton et al., (1992) identified 3 additional potential causes of hepatocellular enlargement: organelle proliferation (hypertrophy); the failure of sublethally-injured hepatocytes to mitotically divide (megalocytosis); and vacuolar swelling of the endoplasmic reticulum cisternae (hydropic degeneration). Hepatocyte hypertrophy was observed in rainbow trout that was simultaneously exposed to endosulfan and disulfoton (Arnold et al., 1995).
Biotransformation System of Xenobiotics In terms of physiology, the liver of fish, as the liver of mammals, is responsible for the same basic metabolic functions: processing, and storage of nutrients, enzyme and cofactors synthesis, bile formation and excretion, and the metabolism of xenobiotic compounds. A complex multienzyme family, normally referred as the biotransformation system, accomplishes the biotransformation of xenobiotics in fish. This system metabolizes both, endogenous and foreign compounds, through a series of reactions, which can be divided in two steps: Phase I that often produces reactive or toxic metabolites, and phase II where larger groups are conjugated with the oxygenated xenobiotic into polar, water-soluble and lessreactive end-products and thus can be excreted from the organism. Fish have many of the same microsomal and cytosolic enzymes as mammals (Cowey and Walton, 1989). The cytochrome P450 (CYP) monooxygenase system comprise a family of enzymes that catalyse phase I monooxygenation reactions and among them, the CYP1A,
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which can be found in hepatocytes, biliary epithelial cells, and endothelial cells (Stegeman et al., 1979; Stegeman and Hahn, 1994; Hinton et al., 2001). The activity of this enzyme has been demonstrated to vary according to the type of inducer, the exposure route, and the fish species (Hinton et al., 2001). Fish also have an enterohepatic cycling mechanism (Gingerich, 1982) to process the substances that were not metabolized during their first pass through the liver. This enterohepatic cycling may increase the efficacy of xenobiotic removal (Gingerich, 1982; deBethizy and Hayes, 2001). The induction of the CYP1A system has become an important tool for monitoring environmental exposure of fish to organic compounds (Hodson et al., 1991) and has been extensively used as a biomarker of aquatic contamination by different pollutants in freshwater as well as in marine environments (Narbonne et al., 1991; Parente et al., 2004). The CYP1A is a sensitive indicator to different environmental contaminants, such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and pesticides, in mammalian as well as in fish (Haasch et al., 1993). In this context, the cytochrome P450-dependent monooxygenase induction, measured as ethoxyresorufin O-deethylase (EROD) activity, has been used as an indicator of exposure to pollutants (Setegman and Lech, 1991; Stegeman and Hahn, 1994; Whyte et al., 2000; Pacheco and Santos, 2002; Ferreira et al., 2004). The expression of hepatic CYP1A and its evaluation by increases in EROD activity has been used in field and laboratory studies to assess the pollutants exposure in different fish species (Narbonne et al., 1991; Goksøyr and Förlin, 1992; Ferreira et al., 2004; Miller et. al 2004; Lee and Anderson, 2005; Bacanskas et. al, 2005). Nevertheless, there are a number of essential physiologic differences between mammalian and fish livers, some of which may affect the rate, pattern, and/or extent of toxicity that occurs in a fish following chemical exposure. One of the most important differences is that fish appear to have a relatively homogenous distribution of biotransforming enzymes in their livers (Gingerich, 1982; Schar et al., 1985; Metcalfe, 1998; Hinton et al., 2001) that is, there is generally no preferential location for these enzymes within anatomical structures, such as central veins. The significance of this dissimilarity will be addressed shortly. Another difference is that fish monooxygenases like CYP1A may be refractory to some classic cytochrome inducers such as phenobarbital (Ferguson, 1989), or variably responsive to other inducers such as 3-methylcholanthrene (Di Gulio et al., 1995) or resistant in cases where fish has been chronically exposed to heavy pollution. A PAH-resistant population of killifish has been identified in a creosoto contaminated site (Van Veld and Westbrook, 1995) However in the same site, CYP1A was environmental induced on both hepatic and extrahepatic tissues at certain times of the year. The variability in resistance among different populations of chemically impacted killifish suggests that such a resistance can occur through different mechanisms depending on the type of toxicant, and the genetic variability of the population (Bello et al., 2001). Fish liver is more tolerant to hepatotoxins than the liver of mammals, which means that the same hepatic changes are only observed in fish exposed to greater concentrations of toxicant (Gingerich, 1984). This tolerance of fish to hepatotoxins could be attributed to some of the mentioned above factors, such as the lower perfusion rate of the fish liver, the
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limitation of toxic exposure to the basal hepatocyte membrane, the homogenous distribution of biotransforming enzymes, and the fact that some enzymes are not readily inducible. Another important propensity of the fish liver is that the lesion distribution, following toxic exposure, tends to be random, without the zonal pattern that is common to sublethal intoxications in mammals (Ferguson, 1989; Boorman et al., 1997; Hinton et al., 2001). Again, this trait has been attributed to the homogenous distribution of biotransforming enzymes in the fish liver, and the fact that the zonal architecture is not apparent.
Transaminases Many enzymes of intermediary metabolism of fish as plasma transaminases are affected by exposure to chemicals. Alanine aminotransferase (AlaAT) and aspartate aminotransferase (AspAT) are indicators of liver damage. They are both mitochondrial and cytosolic and are a very sensitive measure of hepatotoxicity and histophathalogic changes that can be assessed within a shorter time (Balint et al., 1997). These intracellular enzymes are involved in catabolism of amino acids, transferring amino groups to α-keto acids. Usually they are present at very low amounts in serum or plasma. Their increase in plasma may mean liver damage, resulting in their liberation and raising plasma levels (Rao, 2006). For this reason transaminases have been used as indicators of tissue damage (Oluah, 1998, 1999; De la Torre et al. 2000; Das et al., 2004). The increase in (AlaAT), and (AspAT) activities has been observed in fish experimentally exposed to various chemicals including phenols (Hori et al., 2006), organophosphorus insecticide (Rao, 2006) and metals (Varanka et al., 2001) resulting in metabolic alterations at various levels and tissues and hepatic ultrastructure changes. In field studies, where fish has been chronically exposed to environmental metals (Cu and Zn) an increase of plasma AspAT was found suggesting a change in protein metabolism (Fernandes et al. 2008c).
Metal-Binding Proteins Metallothioneins (MTs), are cysteine-rich metal-binding proteins which are believed to play an essential role in regulating the intracellular concentration of the ionic forms of zinc and copper and in protecting cells from the deleterious effects of harmful heavy metals, such as cadmium and mercury (Kaegi et al. 1981; Kaegi and Schaffer 1988; Kaegi 1993). They have an additional role in reducing the toxicity of other metals such as Ag, Cd and Hg in contaminated environments since they also bind elements from groups Ib and IIb of the periodic table (Livingstone, 1993). The relationship between metal levels in the environment and MTs concentrations in animal tissues has led to their use for monitoring the biological effects of metal exposure (Hylland et al., 1992; Livingstone, 1993). The mechanism of metal detoxification by MTs occurs via metal-initiated transcriptional activation of MT genes, resulting in an increase in MT synthesis, and subsequent binding to the free metals (Hogstrand and Haux, 1991)
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In teleost fish, there are marked variations in the inductive response between different species and there are a number of environmental and animal conditions that influence MTs synthesis, as season, temperature, salinity, dietary status and reproductive steroids (Olsson et al., 1995, 1996; Hylland et al., 1998). Interpretation of the results and consequently its use as biomarker of environmental contamination is therefore limited (Rotchell et al., 2001).
3. THE LYMPHOHEMOPOIETIC TISSUES IN FISH In vertebrates, the hemopoietic system is one of the primary targets to several insults. As fish do not have bone marrow or lymph nodes, the hematopoiesis and lymphopoiesis must occur in different fish organs (Agius and Roberts, 2003). In teleosts, hemopoiesis is mainly located within the stroma of the spleen and in the kidney interstitium (Kranz and Peters, 1984; Fänge and Nilsson, 1985; Agius and Roberts, 2003). To a lesser extent, hemopoiesis may also occur in the peri-portal areas of the liver, in the intestinal sub-mucosa and in the thymus (Kranz and Peters, 1984; Agius and Roberts, 2003; Tort et al., 2003) and there are also reports of their occasional occurrence in gills, brain and gonads (Agius and Roberts, 2003). Teleost fish species do not have lymph nodes, thus mature lymphocytes are dependent of hemopoietic tissues, such as the spleen. The thymus, kidney and spleen are the major lymphoid organs in fish (Fänge and Nilsson, 1985; Agius and Roberts, 2003; Tort et al., 2003; Zapata et al., 2006) and, to a lesser extent, mucosa-associated lymphoid tissues can occur, including in the skin and gills (Tort et al., 2003; Huttenhius et. al., 2006). The amount of lymphoid tissue in spleen of distinct vertebrates reflects the pattern of blood circulation and/or occurrence of other peripheral lymphoid organs (Zapata et al., 1996; Agius and Roberts, 2003). Therefore, teleosts splenic lymphoid tissue is poorly developed (Zapata et al., 1996); Fänge and Nilsson, 1985), with diffuse layers of lymphoid tissue showing a tendency to accumulate around blood vessels and macrophage aggregates, as well as scattered lymphocytes within the whole spleen parenchyma (Lamers and De Haas, 1985; Fänge and Nilsson, 1985). On the contrary elasmobranchs, because they loose their renal lymphoid tissue in adult life, show an important splenic lymphoid contribution (Zapata et al., 1996). The major teleost lymphoid organs appeared in the following sequence: kidney, spleen, and thymus, as it has been earlier observed in fish, like Senegalese sole (Solea senegalensis), turbot (Scophthalmus maximus) and Japanese flounder (Paralichthys olivaceus) (Padrós and Crespo, 1996; Cunha et al., 2003), becoming soon the spleen rich in blood capillaries, red blood cells and thrombocytes (Padrós and Crespo, 1996). In freshwater species, but not in marine teleosts, the spleen is the last organ to become lymphoid (Zapata et al., 2006).
3.1. The Spleen Fish spleen is an organ with multiplicity of functions and, depending on fish species, can present high structural complexity. Spleen is surrounded by a connective tissue capsule, which is frequently a thin structure, as it has been shown in rainbow trout (Kita and Itazawa, 1994) and carp (Lamers and De
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Haas, 1985). Blood vessels organization in the spleen showed that visceral arteries originate the arterial blood supply and the hepatic portal system comprises the splenic veins (Fänge and Nilsson, 1985). The parenchyma includes grossly: blood vessels, ellipsoids, macrophages and white pulp that correspond to lymphoid tissue, showing a reticular area without definite lymphoid centers, and red pulp, showing predominantly erythrocytes (Fänge and Nilsson, 1985; Sailendri and Muthukkaruppan, 2005). However, red and white pulp is less clearly defined in poikilothermics than in the homeothermic vertebrates (Fänge and Nilsson, 1985). The ellipsoids are the terminal arterial capillaries and in carp they are surrounded by a cuff of cells (mainly macrophages) (Lamers and De Haas, 1985). Ellipsoids have been suggested to be involved in immune response, by trapping antigens, or through formation of antigenantibody complexes (Fänge and Nilsson, 1985; Lamers and De Haas, 1985). Within the spleen, macrophage aggregates usually occur close to the blood vessels and, in certain species, they are surrounded by a lymphoid sheath (Kranz and Peters, 1984; De Vico et al., 2008). The spleen of teleost fish, compared with those of elasmobranchs, is usually smaller. In teleosts spleen weight ranges 0,05-0,86 % of the body weight comparing with elasmobranchs that could range between 0,1 to 4,0 % (Fänge and Nilsson, 1985). In fish, the spleen is involved in the development of circulating blood cells, as well as immunity. Functions of fish spleen comprise blood cell formation, their storage and release, and also destruction of aged or defective blood cells and foreign agents by cells of the nonspecific immune response (Fänge and Nilsson, 1985; Spazier et al., 1992). Rapid expulsion of stored blood cells by contraction of the fish spleen can occur after severe exercise (Franklin et al., 1993; Kita and Itazawa, 1994). The spleen also serves as a filter, retaining and eliminating effete or aged blood cells and foreign particles (Fänge and Nilsson, 1985; Kita and Itazawa, 1994). The white pulp, lymphoid tissue, is mainly related to immune response, by processes involving macrophages and lymphocytes, and although species differences may exist, it has been suggested that the spleen is also involved in anti-body production. Along with other lymphohemopoietic tissues, such as the pronephros, the spleen probably is an important source of immunoglobulins in elasmobranchs and teleosts (Fänge and Nilsson, 1985).
3.2. The Kidney Fish is the oldest, largest and most variable group of vertebrates on Hearth. So, it is not surprising that this obligate aquatic animal has a multifunctional kidney, which is reflected on its complex tissue organization. Originated from mesoderm, development of kidney is a gradual process that occurs during the embryonic period and reaches various degrees of differentiation in different groups. That differentiation happens always from the head to the caudal region in a concept of a kidney triplicate organization (i.e. pronefros, mesomefros and metanefros). Because it forms within the intermediate mesoderm located in the dorsal and posterior body wall, modern fish kidney is a retroperitoneal organ (Hildebrand and Goslow, 2001; Kardong, 2002). The kidney ontogenetic development in teleost species stops at the opistonefros phase. This organ has two distinct segments: an anterior pronefretic segment (the head kidney) and a
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posterior segment mesonefretic, with contribution of some metanefros components (the trunk kidney). Although both segments hare lymphoemopoietic, it is more intense in the anterior part because this part is not involved in excretory function. The head kidney parenchyma is dispersed between the sinusoid system that is supported by the stroma. The stroma supports the hemopoietic tissue and has an important role in nonspecific immunity traping and clearance of debris and damaged cells mainly from blood (reviewed by Press and Evensen, 1999). It appears, from studies in various teleost species, that the anterior kidney is the first lymphoid organ to possess Ig+ cells during ontogenesis (Kaattari and Irwin, 1985; Castillo et al., 1993; Koumans-van Diepen et al., 1994; Breuil et al., 1997; Romano et al., 1997; Schroder et al., 1998). Moreover, Kaattari and Irwin (1985) suggested that this organ also serves as a secondary lymphoid organ. The functions assigned to each part of the organ, throughout its development, will vary and, in some cases, after a transient development, a complete regression can happen, or other function can be assigned to the remaining structures. For example, in several bony fishes the archinefretic ducts are shared in urine and sperm release. In other cases they have testicular ducts. (Hildebrand and Goslow, 2001; Kardong, 2002). Fish kidney shows morphological and physiological variations between and within groups. For example, Chondrichthyes have particular arrangements - i.e. Leydig organ(Zapata et al., 1996) and within teleosts there are aglomerular species (McDonald and Grosell, 2006). Furthermore, in contrast to higher vertebrates, most fish species hatch these organs at embryonic stage, so becoming free-living organisms. The adult fish kidney, often situated along the dorsal wall of the body cavity, is for most species an opistonefros divided into anterior pronefric region (head or cranial) and posterior (trunk or caudal) sections (Kardong 2002). The anterior kidney is one of the primary hemopoietic organ in adult teleosts (Press and Evensen, 1999). Together with the blood, anterior kidney has the largest amount and the greatest variety of fish leucocytes. In fact, anterior kidney is the larger lymphomieloid organ in most teleosts (Zapata and Cooper, 1990; Zapata et al., 1996). So, it is usually the supplier of leukocytes for in vitro studies. The interest seen over the recent few decades by the fish kidney functions is not surprising. In fact, all vertebrates have that retroperitoneal organ (the kidney) that is responsible for several vital functions. Removal of nitrogenous waste products and other circulating harmful substances is the most commonly known, because this function is general through all vertebrate groups. Osmoregulation and water balance are also vertebrate kidney general functions (Varsamos et al., 2005; Evans, 2008). The other two functions of fish kidney are reflected in the endocrine tissues, that include medullar and cortical adrenal homologs, the chromaffin tissue, or chromaffin bodies, and the interregnal tissue, or interregnal bodies, that produce catecholamines (Reid et al., 1998) and corticosteroid hormones (McCormick, 2001; Martinez-Porchas, 2009), respectively; and the last to be addressed, but not least important, is an hemopoiesis and immunological functions (Ellis 1977; 1999; Secombes 1993). Kidney plays a key role in maintaining body homeostasis, by blood filtration and critical electrolyte and acid–base balance and maintenance of intracellular fluid volume. As part of its blood filtering function, kidney remove wastes and toxicants from blood and discharges those through urine, while conserving essential ions, amino acids, and glucose. Other kidney crucial
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function is the absorption and deposition of calcium. The kidney also produces essential hormones, including renin and erythropoietin (Bernier et al., 1999).
Kidney and Its Role in Electrolyte Balance The knowledge on osmoregulation and its implications in growth is vital to understand fish survival. The water salinity has great impact in fish physiology, namely the various salinity regimes that occur in estuaries where it is of particular importance to several fish species. Freshwater environments display a diversity of low ionic types and ratios and typically have substantially lower levels of total dissolved electric charged particles (ions) than marine or brackish waters. On the other hand, in marine environment, ions occur in stable ratios, comparatively with absolute concentrations. Even though, teleosts may live in waters which exhibit wide ranges of salinity, since they are capable of maintaining relatively stable plasma and tissue ion concentrations (Evans et al., 2004; Evans, 2008). Osmoregulation is the mechanism for maintaining constant internal ionic concentrations relative to external or environmental ionic concentrations. The osmoregulatory mechanisms maintain at almost constant or only slightly variable blood osmolality, between 280 and 360 mOsm kg -1 (Varsamos et al., 2005). From the point of view of hydromineral regulation, the main function of kidney, in freshwater fish, is the excretion of large volumes of osmotically accumulated water and the elimination of surplus ions extracted from the food, mainly K+, sulfate, and phosphate. In the limit, if renal losses of valuable ions via urine occurs, intensive reabsorption of Na+, Cl–, Mg2+ and Ca2+ takes place, by transporting enzymes and exchangers in epithelial cells lining the nephronic tubules, collective tubules, and bladder (Beyenbach, 1995), depending on the external salinity. In marine environments loss of water from fish tissues is dramatic as exposure occurs over the entire body surface and the major function of fish kidney is excretion of divalent ions taken up by drinking. Water excretion has to be reduced as much as possible in a hyperosmotic environment, and this is achieved mainly by reduction of the glomerular filtration rate (Beyenbach, 1995). Few studies are available on the physiological aspects of renal hydromineral function, such as urine flow and renal ion excretion rates. Technical drawbacks as collection of such fluids require cannulation that is complicated and extremely stressful to fish, often interfering with results. Thus, a proper evaluation of the effects of toxic chemicals on the kidney is even more complicated than in others organs.
4. THE IMPACT OF WATER CONTAMINATION ON RENAL FUNCTION Because it is the main route of elimination of hydrophilic toxicant metabolites, kidney is also an important organ in toxicology. The high volumes processed in kidney lead to high levels of exposure particularly toxicants, with concomitant deposition of these toxic substances and eventual damage.
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A number of substances have been implicated in kidney damage. As Au (2004), mentioned, histochemical techniques can be used as biomarkers, of general health condition of fish and of toxic organic contaminant exposure. However, both histopathological and morphological analysis showed moderate sensitivity to pollution when compared with other techniques (Van der Oost et al., 2003). Toxicological studies have revealed extensive histopathological alterations in kidney as a result of fish exposure to heavy metals and organic chemicals. Generally, proximal tubules appear to be the first affected, but damage progresses to the posterior segments and glomeruli, following both, chronic exposure, or high concentration of the toxicant (Au, 2004; Wendelaar Bonga and Lock, 2008). Some metals, including cadmium, lead, mercury, nickel, and chromium, particularly abundant in some contaminated aquatic environments, are severely nephrotoxic. Also, halogenated hydrocarbons, including bromobenzene, chloroform, carbon tetrachloride and tetrafluoroethylene, that are transported to the kidney as cysteine S-conjugate, have nephrotoxic action (Wendelaar Bonga and Lock, 2008). The herbicide paraquat, diquat, and 2,4,5-trichlorophenoxyacetate have also toxic effects on the kidney (Parvez and Raisuddin, 2006). Histopathological effects vary from slight disruption of the proximal tubular cells, increased numbers of phagosomes and lysosomes, and abnormal mitochondria, to rupture of cell membranes, swelling and vacuolization, increased cell death by necrosis and apoptosis, and large lesions in the tubular epithelia (Hisar et al., 2009; Kosai et al., 2009; Vinodhini and Narayanan, 2009). Although kidney has been used as nonspecific cellular biomarker, for cadmium it is well known its affinity for renal tissue, as a site of accumulation, here the highest concentrations of this metal are usually found, after exposure (Bentley, 1991; McCoy et al., 1995; Van Campenhout et al., 2009). As a consequence, cadmium is able to produce severe histopathological alterations (Gill et al., 1989; Hallare et al., 2005). Copper has no specific affinity for the kidneys, but it can also produce significant structural damage to both glomeruli and renal tubules (Vinodhini and Narayanan, 2009). A study on mercury chloride effects on head kidney macrophage function and integrity of sea bass (Dicentrarchus labrax) and their dependence on macrophage activating factor(s) (MAF) for the production of reactive oxygen species (ROS), showed a decrease in ROS production as compared to cells incubated with medium alone. MAF activation of the macrophages phagocytic activity was also impaired by HgCl2 addition. Mercury chloride induced macrophages apoptosis and MAF addition prevented this effect (Sarmento et al., 2005). Among the many organic chemicals producing similar effects are paraquat (Molck and Friis, 1997), TCDD (Henry et al., 1997) and atrazine (Fischer-Scherl et al., 1991). It is clear that the lesion severity of renal functions, including hydromineral regulation, is affected by the concentration and length of exposure. Relatively few studies deals with renal functions, however inhibitory effects of silver on K+- dependent of p-nitrophenol phosphatase (Bury, 2005), of cadmium and chromium (Venugopal and Reddy, 1993), of copper and mercury (Singh and Sivalingam, 1982; Lan et al., 1993), as well as on renal tubular Na+/K+ATPase, Ca2+-ATPase, and Na+/Ca+ exchange activity were reported (Wright and Welbourn, 1993). Most organic pollutants may be responsible for a reduced activity of renal ion transport, in a less specific way. The reduction of Na+/K+-ATPase activity induced by paraquat has been
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related to the disruption of this chemical on mitochondrial electron chain transfer (Molck and Friis, 1997). Decrease in renal Na+ efflux was found in freshwater rainbow trout following exposure to waterborne copper (Li et al., 1996). As copper has a strong inhibitory action upon Na+/K+ATPase activity, the opposite effect was expected, i.e. an increased tubular reabsorption of Na+, for which Na+/K+-ATPase is a driving force. A physiological response of the kidney to compensate the impairment of branchial Na+ uptake was the explanation for this phenomenon (Grosell et al., 1998).
Endocrine Kidney Response to Stressors Fish kidney participates also through several endocrine mechanisms, during exposure to a wide range of internal and environmental stress factors. Cortisol is the principal corticoid secreted by the interrenal tissue located in the head-kidney of teleost fish. It is released by the activation of the hypothalamus-pituitary-interrenal axis (Mommsen et al., 1999). The hypothalamus releases corticotropin-releasing factor (CRF) toward blood circulation and this polypeptide further stimulates secretion of adrenocorticotropic hormone (ACTH) from the anterior pituitary gland (Fryer and Lederis, 1986), which induces the release of cortisol by the kidney interrenal tissue (Balm and Pottinger, 1995; Mommsen et al., 1999). More important in freshwater fish is prolactin, the hormone controlling the permeability to water and ions in the gills, intestine, and renal tubules (Sakamoto and McCormick, 2006). The interference of toxic agents with neuroendocrine control processes in fish involving osmoregulation has been documented (Hontela et al., 1992). Prolactin cells, adrenocorticotropic hormone (ACTH) cells and the interrenal cortisol producing cells were those that received major attention in order to investigate the potential use as biomarkers (Ramesh et al., 2009). Activation of prolactin cells has been frequently observed in fish exposed to toxic agents and has been generally interpreted as a compensatory response to the disturbance in the permeability of these epithelia by toxicants (reviewed by Wendelaar Bonga and Pang, 1989). Cortisol is one of the primary stress hormones in fish and also an important stimulator of Na+/K+- ATPase activity in gills, intestine, and kidney. The multiple functions of this hormone clearly demonstrate the intimate relationship between the stress response and osmoregulation in fish (Wendelaar Bonga, 1997; Reid et al., 1998; Barton, 2002). Endocrine dysfunction was also found in fish from water naturally contaminated with a mixture of pollutants, including heavy metals and PCBs, when compared with fish from an unpolluted reference site (Hontela et al., 1992; Hontela et al., 1997; Wendelaar Bonga and Lock, 2008). Hypothalamo–pituitary–interrenal (HPI) axis of wild brown trout is activated in fish from sites contaminated with cadmium and zinc. Histological analyses revealed that interrenal cells are more stimulated, exhibiting both hypertrophy and hyperplasia (Norris et al., 1997). These results suggest that the hypothalamo-pituitary-interrenal (HPI) axis of fish living in metal-contaminated water may be susceptible to chronic stimulation. A study of effects of endosulfan, an organochlorine pesticide, on cortisol secretion in vitro revealed that the head kidney cells of rainbow trout, (Oncorhynchus mykiss) exposed to endosulfan, decreased ACTH- or dbcAMP-stimulated cortisol secretion and cell viability in a
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concentration-dependent pattern and the doses required to disrupt cortisol secretion were significantly lower than lethal doses to the head kidney cells (Leblond et al., 2001). The interrenal tissue of yellow perch, from a site contaminated by a mixture of heavy metals and organic contaminants, secreted significantly less cortisol in response to a standardized pulse of ACTH than those from an unpolluted site (Brodeur et al., 1998) . Given the cortisol importance for osmoregulation in fish, any interference with the secretion of cortisol and its stimulant hormone (ACTH) may be expected to have an effect on osmoregulation (McDonald and Milligan, 1997); however, the actual impact of the disruptive effects of some toxic chemicals on this process remains to be established. Currently, the use of cortisol as a biomarker has to be done carefully. For proper use of cortisol as biomarker, an evaluation has to be done in each case (species, contaminant compounds and environmental conditions).
5. IMMUNE SYSTEM IN FISH The main source of pollution in aquatic environment is the growing human population and their demanding needs that may affect both, fish and human health. Degradation of environmental conditions, due to pollution, can disturb fish immune process and consequently fish health. Consequences of exposure to pollutants on fish immune system can range from suppression/inhibition or even enhancement of a specific immune response. According to Agius and Roberts (2003), fish inhabiting polluted environments can respond to environmental conditions altering the nonspecific defence activities. In fact, toxic effects on the immune system may serve as an excellent biomarker to monitor pollution and water quality, since most environmental pollutants are known to alter immune system function, even at doses that do not cause histopathological toxicity (Agbede et al., 2005).
5.1. Non-Specific Defence Mechanisms As in all jawed vertebrates, fish species possess a complex mechanisms system that provide homeostasis and fight against infection. The complexity and the type of these mechanisms led to a division in innate (non-specific) and an acquired (adaptive or specific) immunity. Indeed, the system is unique and their parts are interdependent, with several molecules and cells working together in both, innate and acquired system. Both types have the participation of both, cellular and humoral factors. However, as the term humoral was first applied to activities involving antibodies, humoral innate components are just referred as soluble components. As previously stated, the innate immunity is generally subdivided into two parts, the cellular and humoral defense responses (Köllner et al, 2002; Aoki et al., 2008). Cellular responses include physical barriers, such as mucus and epithelial tissues in skin, gills and stomach (Aoki et al., 2008), and cells, like monocytes/macrophages, and granulocytes, mainly involved in phagocytosis (Agbede et al., 2005; Aoki et al., 2008). Humoral responses involve
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a variety of proteins and glycoproteins capable of destroying or inhibiting growth of infectious microorganisms (Aoki et al., 2008). The non-specific immunity, in fish, is the primary line of defence and represents a considerable part of the immune response, since activation of leucocytes is one of the first reactions in every immune response (Agbede et al., 2005; Aoki et al., 2008). This mechanism is characterised by being non-specific and therefore not depending upon previous recognition of the invader (Tort et al., 2003). Depending on the antigen leukocyte, certain subpopulations are activated and proliferate. However, it has been shown in different fish species that some circulating sub-populations are able to act in immune defence without prior activation (Köllner et al, 2002). The nonspecific immunity in fish primarily depends on the phagocytic activity of sub-populations of monocytes/macrophages and neutrophilic granulocytes (Köllner et al, 2002; Agbede et al., 2005). Phagocytosis, killing and degradation of invading microorganisms by professional phagocytes, is a crucial process in the mechanisms of defense of vertebrates against some infections (Mackaness, 1969; Ellis, 1977; Adams and Hamilton, 1984; Edwards and Kilkpatrick, 1986; Lehrer et al., 1988; Hine, 1992; Brown, 1995). It is interesting that mammals, teleosts and other higher eukaryotes utilize two types of professional phagocytic cells -neutrophils and macrophages- in the defense against infection (Rowley and Ratcliffe, 1988; Secombes and Fletcher, 1992; Brown, 1995). Data from studies conducted on the behavior of each of the two professional mammals phagocytes in inflammation, including that due to infectious situations, can be summarized as follows (Lehrer et al., 1988; Haslett et al., 1989; Silva et al., 1989; Densen et al., 1995; Kubicka et al., 1996; van Furth 1992). Macrophages are present in all body compartments being in a quiescent state. Therefore, when superficial barriers are breached by an invading microorganism, it encounters this phagocyte. Neutrophils are present in large numbers in blood and hemopoietic organ pools as a reserve, and, under normal conditions, are rare in the tissues and body cavities. These granulocytes migrate to the infection focus just when mobilized by chemotactic molecules, including those released by macrophages (Afonso et al., 1998a; Afonso et al., 1998b). Although phagocytic system in fish involves resident macrophages present in all organs and tissues of the body (Agbede et al., 2005), spleen has an important role in this mechanism, developed by macrophages and granular leucocytes inside parenchyma. This is not surprising since it is known that phagocytosis is the principal function of macrophages in teleosts fish (Agius and Roberts, 2003; Agbede et al., 2005), and the response of splenic macrophages to foreign substances is the subsequent elimination by phagolysosomes. Therefore macrophages aggregates have been considered as metabolic dumps (Kranz and Peters, 1984).
Macrophage Aggregates Macrophages are mononuclear cells derived from circulating blood monocytes, terminally differentiated, that have been studied in a variety of fish species (Secombes and Fletcher, 1992; Enane et al., 1993; Secombes, 1993). Several distinct macrophages subpopulations seem to exist in fish (Afonso et al., 1998a; Neumann et al., 2000). Described long ago by Metchnikoff (1887), phagocytosis is one of the most ancient cellular immune mechanisms and the term ―macrophage‖ came first of these observations. Several
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immunoregulatory molecules such as macrophage-activating factor (MAF), TNF-, TGF-, -glucans, growth hormone, and neurotransmitters have been implicated in the modulation of fish macrophage phagocytosis (Secombes, 1994; Secombes et al., 1996). Temperature can affect nonspecific immune responses in fish. Studies on the effect of environmental temperature, on fish nonspecific defences, revealed greater effectiveness of phagocytosis at low environmental temperature in several species (Morvan et al., 1998). Dispersed or aggregated, macrophages are pigmented populations with particular interest. Macrophage aggregates (MAs), or melanomacrophage centers, are structures normally located in the stroma of the hemopoietic tissue of spleen and kidney, although in some fish, they are also found in liver (Fringe and Nilsson, 1985; Kranz, 1989; Montero et al., 1999; Agius and Roberts, 2003). MAs vary between the different hemopoietic organs. Splenic MAs exist in all teleosts fish (Lamers and De Haas, 1985) and for most fish species they are more abundant and larger than those in the liver (Kranz and Peters, 1984), and compared to kidney, they are more variable in pigmentation and show a closer degree of aggregation (Kranz, 1989). As stated before, polluted environments may induce changes in fish nonspecific defence activity. Macrophage aggregates have been used as nonspecific cellular biomarkers of physiological stress following exposure to chemical pollutants. Changes in MAs number and structure could be a sensitive biomarker, which could be of great value as an early sign of environmental contamination (Montero et al., 1999; Fournie et al., 2001; Agius and Roberts, 2003; Facey et al., 2005; Jordanova et al., 2006). General functions of these centres have been described as storage, destruction or detoxification of exogenous and endogenous substances, and iron metabolism and recycling (Montero et al., 1999; Agius and Roberts, 2003; Jordanova et al., 2006). They have also been implicated in the immune response, including inflammatory and humoral responses (Montero et al., 1999). MAs often exist as complex discrete centres, containing lymphocytes and macrophages, and may be primitive analogues of the germinal centres of lymph nodes of higher vertebrates (Kranz and Peters, 1984; Kranz, 1989; Agius and Roberts, 2003). It is thought that the MAs might be involved in the response of fish to infectious agents, by acting as focal depositories of resistant pathogens and also as antigen processors in immune responses (Lamers and De Haas, 1985; Agius and Roberts, 2003). Different types of pigments have been identified, frequently even within the same cell (Agius and Roberts, 2003), which seems to be species-specific (Jordanova et al., 2006). Melanin is not observed in MAs of carp, being the, hemosiderin and lipofuscin the main pigments (Lamers and De Haas, 1985). At least 3 types of pigments have been identified in the macrophages aggregates e.g. melanin, lipofuscin/ceroid and the hematogenous pigment hemosiderin (Fringe and Nilsson, 1985; Agius and Roberts, 2003; Jordanova et al., 2006). These pigments are associated to different biochemical roles, and their levels could be indicative of fish unbalance physiology.
Splenic MAs Macrophage aggregates increase in size, frequency or in pigment patterns in conditions of environmental stress and have been suggested as reliable biomarkers of water quality (Agius
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and Roberts, 2003). Furthermore, Hinton et al. (1992) have suggested MAs as histologic biomakers of contaminant exposure or environmental stress. Histochemical properties of splenic MAs vary considerably between healthy and diseased fish and increases in pigment content are suggestive of catabolic, infectious or toxic exposure (Agius and Roberts, 2003; De Vico et al., 2008). The accumulation of iron appears to be a characteristic feature of splenic MAs, but not of those in the liver, leading to conclude that one of their main functions is the digestion of degraded red blood cells (Kranz and Peters, 1984). Hemosiderin, related with iron storage and recycling (Fringe and Nilsson, 1985; Montero et al., 1999), is usually detectable in little amounts in the MAs of spleen and increased storage should be considered as a pathological event (De Vico et al., 2008). The increase hemosiderin in splenic MAs, in some infectious diseases, occurs manly due to high rates of erythrocyte destruction or/and high iron sequestering in centers to prevent them from bacterial growth (Kranz, 1989). Also Khan and Nag (1993), reported an increase in splenic hemosiderin in fish exposed to crude oil. According Agius and Roberts (2003) lipofuscin is the pigment that accumulates with age and tissue destruction and is the most widespread pigment in the MAs of many fish species. Increase of lipofuscin is derived from cell peroxidation (Kranz, 1989; Agius and Roberts, 2003). Lipofuscin in splenic MAs, has been predominantly related to high levels of tissue catabolism and degenerative chronic disorders (De Vico et al., 2008). Although changes in splenic MAs can be considered in toxicological studies as a sensitive biomarker, since they are nonspecific, their abundance and structure can be affected by many factors and so these etiologies must be considered in toxicological studies. Increase of splenic MAs has been associated with starvation (Agius and Roberts, 1981; Fänge and Nilsson, 1985), with ulcerous infection (Kranz, 1989), with parasitic infection (De Vico et al., 2008), with nutritional imbalances and high fish stocking density (Montero et al., 1999). It has also been observed that these centres increase in size and number, at least in a number of fish species, as fish grow older and tissues degenerate (Agius and Roberts, 2003). In addition, normal fluctuations occur, since MAs could undergo seasonal and breeding dependent variations. It is established that the amount of pigmented MAs in spleen was significantly increased in wild Ohrid trout females, during and/or after spawning (Jordanova et al., 2006). Thus, for biomonitoring purposes, normal fluctuations of a pollution biomarker must be excluded to achieve reliable responses. Data control could be made by comparisons between contaminated and reference sites, with fish of similar age and captured at the same season. Besides, a quantitative study, an assessment of spleen and liver MAs in broun trout (Salmo truta) during an entire gonadal cycle performed by Jordanova et al. (2006), was required since it provides a basis for future evaluation of normal versus altered levels of MAs induced by pollution, to be applied at least in the same group of fish. Although non-specific, MAs in fish has been proven to be a sensitive indicator of exposure to environmental contaminants (Au, 2004). Splenic MAs are effective biotic indicators for discrimination between fish exposed to degraded and non-degraded environments. However comparative studies, on the incidence of MAs in the spleen, kidneys and liver of fish exposed to toxic chemicals, have shown an opposite trend. A reduction in number and size of these structures in fish living in polluted water is probably due to a pollutant-induced immunosuppression (De Vico et al., 2008). The spleen of the eel (Anguilla anguilla), exposed to a chemical spill, showed alterations such as necrosis, lacking of MAs and a reduced number of macrophages dispersed throughout the reticulum, compared to
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controls (Spazier et al., 1992). Normally, the phagocytic capacity of the spleen in eel and other species is mainly associated with number and extent of MAs (Spazier et al., 1992), and according to these authors a decreased ability of macrophages phagocytic function, is possibly due to a toxicant-induced reduction of chemotactic activity. Metals may disturb ionic metabolic, balance and cell division of immunocompetent cells. It was found in vivo that copper causes, in a dose-dependent manner, a depressed phagocytic activity of catfish spleen macrophages (Saxena and Saxena, 2008). The utility of splenic MAs has been assumed as a general indicator of fish exposure to contaminated environments and has been used in monitoring programs, such as the Environmental Monitoring and Assessment Program–Estuaries (EMAP-E). This study, using image analysis, has proved that MAs densities greater than 40/mm2 can be correlated with exposure, to hypoxic conditions or chemical contamination in sediments (Fournie et al., 2001). Also, utilizing image analysis, an increase in splenic hemosiderin was observed in longhorn sculpin (Myoxocephalus octodecemspinosus), yellowfin sole (Limanda aspersa), quillback rockfish (Sebastes maliger) and kelp greenling (Hexagrammos decagrammus) exposed to crude oil (Khan and Nag, 1993). An environmental study in Calcasieu Estuary, Louisiana, showed that the frequency of MAs in spotted trout (Cynoscion nebulosus) spleen was significantly higher in contaminated sites, than reference sites (Jenkins, 2004). According to Kranz and Peters (1984), the MAs in spleen and liver of ruffe (Gymnocephalus cernua) from the polluted Elbe River, augmented during the development of several histopathological abnormalities of these organs. It also is well established an association between erythrocyte damage and spleen toxicity, after exposure to aniline and other aromatic amines. According to Monteiro et al. (2006) after 96 h of exposure to aromatic amine 3,4-dichloroaniline spleen histological alterations and deposition of hemosiderin granules, in a dose-dependent manner, were observed in juveniles of common goby (Pomatoschistus microps), compared to control groups. Besides, splenic MAs hyperplasia was generally reported in a variety of fish species inhabiting degraded environments, such as exposed to pulp mill effluent and areas with elevated levels of xenobiotic chemicals (Au, 2004). It has been shown that heavy metals exposure cause significant pathological changes in fish lymphoid organs and fish mortality. Histopathology of spleen tissues of common carp (Cyprinus carpio carpio) after metals exposure revealed congestion, haemorrhage, lymphocytic infiltration and degenerative changes with loss of cellular architecture (Saxena and Saxena, 2008). In laboratory conditions, frequency and size of splenic MAs were significantly increased in Tilapia mossambica after median lethal exposure to heavy metal cadmium chloride (Suresh, 2009). Osman et al. (2009), found splenic histopathological changes in Oreochromis nilotica under copper sulfate and lead acetate laboratory exposure. Fish spleen showed congestion of vessels, depletion of lymphoid follicles, excessive hemosiderosis and hyper activation of MAs, associated with increase of pollutants concentration and time of exposure. Also MAs sizes, in male pike (Esox lucius) and longnose sucker (Catostomus catostomus), have increased with mercury contamination (Hinck et al., 2004). A long-term effect of small concentrations of the dioxin TCDD introduced in the diet of rainbow trout (Oncorhynchus mykiss), was evaluated by Walter et al. (2000). The increased numbers of macrophages and pigmented macrophages with intracytoplasmic hemosiderin
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observed suggested a link with increased degeneration of lymphocytes and, possibly also, erythrocytes. Chronic (32 weeks) exposure of rainbow trout (O. mykiss) to sewage treatment plant (STP) effluent showed effects on spleen leucocytes and on the integrity of spleen tissue. Spleen tissue of exposed fish appeared to have less structural integrity and infiltration of stimulated monocytes/macrophages, as compared to control (Hoeger et al., 2004). These results are in agreement with the general idea that the increase in size, frequency and pigments variation on MAs of fish spleen, in conditions of environmental stress, is a reliable biomarker for water chemical pollution. In addition, utility of splenic MAs as biomarkers could be extended to evaluation of ecosystems recovery. Significant decreases in splenic MAs area were also used to suggest decreased exposure to contaminants on a fish population (Facey et al., 2005). Results of rainbow trout (O. mykiss) exposure to sublethal concentrations of the pesticide endosulfan showed splenic abnormalities, after 21 days of exposure, including exudate, necrosis and scattered MAs throughout the spleen, compared to control; whereas after 30 days of recovery, lesions were no longer seen (Altinok and Capkin, 2007). According to Jordanova et al. (2006), changes in MAs relative volume can be a nonexpensive and sensitive biomarker, which should be of great value as a first-line evaluator of early signs of aquatic environmental degradation. The histologic analyses of spleen could include the assessment of morphometric parameters, such as mean MAs profile area and number per square millimetre of spleen tissue (De Vico et al., 2008). Also, image analyses that select and quantify pigmented area are proved to be an objective way of MAs evaluation in salmonid spleen (Schwindt et al., 2006). This method is less time-consuming and was shown to be very accurate. Other studies that have used area occupied by MAs, noted increased splenic hemosiderin in several fish exposed to crude oil (Khan and Nag, 1993) and in dab with ulcers (Kranz, 1989). Using image analysis of splenic MA Fournie et al. (2001) also proved the utility of this technique as effective discriminator between fish exposed to degraded and nondegraded environments. These approaches can provide data that is easily analysed statistically, resulting in less controversial conclusions and reinforces the importance of using splenic MAs as histologic biomarker of contaminant exposure.
6. ORGANO-SOMATIC INDICES Organo-somatic indices reflect the status of organs within the whole body, which may change in size due to environmental factors more rapidly than organism weights and lengths increase or decrease. Although several factors could increase or decrease the sizes of a few organs, the organo-somatic indices have been used widely in fish health and population assessments.
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The Splenosomatic Index (SSI) Spleen size is considered a useful diagnostic factor because, as previously seen, this organ plays a highly important role in hemopoiesis and immune reactivity of fish and the use of relative spleen weight could provide information about fish health. The splenosomatic index (SSI) is the weight of the spleen expressed as a percentage of total body weight, and alterations in this index could indicate an abnormal condition in the spleen (Dethloff and Schmitt, 2000). Commitment in immune defence could be measured by spleen size, moreover the use of spleen size is also recommended in ecotoxicological studies as a standard measure of immunocompetence on fish (Šimková et al., 2008; Van der Ost et al., 2003). There is evidence that immune system of fish reacts to various environmental factors, including anthropogenic ones, and, therefore, the immune responses (either stimulation or suppression) have to be considered as an unspecific indicator of environmental stress. Phagocytic activity is an important immunological function in the study of bacterial infections in fish and contaminants can affect spleen directly and change their normal function within the immune system. These facts, together with contaminant exposure, could facilitate development of infectious and/or non-infectious diseases and in this way resulting in different disease prevalence and incidence. Pollution of the natural aquatic environment, with industrial or agricultural sewage, is an important immuno-suppressing factor, resulting in higher susceptibility of fish to infectious diseases (Köllner et al, 2002). For that reason, this issue is also of relevance for environmental monitoring programmes and useful, from both points of view, economic and public health. Enlargement of the spleen is considered to be indicative of disease or immune system problems (Dethloff and Schmitt, 2000). Parasitic infections, can lead to an increase in spleen volume (Durborow, 2003; Khan, 2009), usually by development of leucocyte reactions (Lizama et al., 2006). However, when relative spleen size is used as reflecting an immune investment against parasites or pathogens, large spleen can be interpreted either as an improving ability to respond to parasite exposure or an indication of high immunological activity from already established infection. (Šimková et al., 2008). Often the occurrence of MAs mainly around parasite larvae has been noticed in infected liver and spleen (Dezfuli et al., 2007). In rainbow trout (O. mykiss) a positive association between spleen size and resistance to bacterial disease was also found (Hadidi et al., 2008). Histological, and morphometric modifications of splenic macrophage aggregates in sea breams (Sparus aurata), infected by an ectoparasite in the gills, revealed a dramatic increase in the size and number of MAs in fish (De Vico et al., 2008). Increase splenosomatic index could be dependent on parasitic load. According to Lizama et al. (2006), the infestations in fish Prochilodus lineatus, by acantocephalan, increase SSI, while the infestation with metacercariae, due to the lower intensity of this infection, resulted in SSI decrease. Environmental alterations, due to contamination can also alter the SSI. Fish chronically exposed to a bleached Kraft mill effluent (BKME) showed a tendency for high SSI (Adams et al., 1992). Jenkins (2004) also found in black drum (Pogonias cromis), a splenosomatic index significantly higher in fish from contaminated sites than in fish from reference sites. Decrease in SSI is commonly found following contaminants exposure. Fish exposed to organic contaminants, alone or in combination with metal, have shown decrease SSI (Hinck
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et al., 2004). Exposure of fish to lead for up to 183 days was reported to produce a reduction in spleen size, with an increase in leukocyte number (Saxena and Saxena , 2008). Decreased SSI was also recorded in fish exposed to petroleum and polluted waters, with PCBs, PAHs, metals (Dethloff and Schmitt, 2000). These findings are consistent with the use of SSI as a sensitive end point biomarker. A complex pattern of effects of paper mill effluents in fish physiology was observed. Some results indicate that in-stream exposure to elemental-chlorine-free pulp and paper mill effluents the SSI decreases. An experiment of 35 days exposure to surface water of up- and downstream, from a pulp and paper mill treatment-effluent discharge, showed that SSI was significantly decreased in fish downstream, compared to fish upstream, along with a transfer from lymphocytes to neutrophils in peripheral blood (Baer et al., 2009). The effects of paper mill effluents on free-ranging and captive largemouth bass (Micropterus salmoides) were assessed by Sepúlveda et al., (2004). Fish in outdoor tank, exposed to increasing full strength effluent for 28 or 56 days, showed that SSI was not affected; whereas free-ranging bass sampled from effluent-dominated sites showed a decreased in both SSI and number of splenic macrophage aggregates, in relation to reference streams. Besides a decline on the weight of the spleen, results also showed hematological changes, such as reductions in the number of red blood cells, probably caused by alterations in the hemopoietic capacity of the spleen and/or head kidney. These authors also suggested that the decrease number of splenic MAs is due to the decreased spleen weights since bass with larger spleens and livers tend to have more MAs. Also an important issue addressed in this study is that, although many of the physiological parameters measured were statistically different from control or reference fish, they fell within normal physiological ranges when compared to reports on largemouth bass and other freshwater species. Based on that, it is evident that different responses could arise between laboratory and field biomarker assessments, and also conclusions about significant trends observed must be distinguished from normal physiological ranges. As an unspecific indicator, also certain endogenous factors are known to affect the SSI. The range of spleen sizes varies among fishes and populations of the same species. Relative spleen weight may also differ with age, gender and gonad development (Dethloff and Schmitt, 2000). Seasonal changes of the spleen size have long been known to occur in the salmon (Salmo salar) and other salmonids. Before and after spawning the spleen is large and hyperemic, but at spawning it shrinks and becomes anemic, maybe related to blood storage rather than lymphoid or hemopoietic activities (Fänge and Nilsson, 1985). However, in BEST fish monitoring program, in the Yukon River Basin, the SSI of longnose sucker (C. catostomus), was not influenced by gender (Hinck et al., 2004). Nonspecific stressors can also ending into altered spleen morphology. Several studies have shown that fish under hypoxic conditions or severe exercise, reveals spleen contraction and then decrease in size (Fänge and Nilsson, 1985; Dethloff and Schmitt, 2000). Rainbow trout, generally considered to be a hypoxia-sensitive species, showed, during hypoxia exposure, a decrease in SSI and an increase in blood hemoglobin. Splenic contraction and the subsequent red blood cell release, accounts for decrease in SSI (Lai et al., 2006). Exercise at a speed great enough to cause exhaustion also contributed to the increase in hematocrit of Pagothenia borchgrevinki (Franklin et al., 1993). Based on these considerations and according to Dethloff and Schmitt (2000), in addition to histological data, that show a relation between cellular changes in the spleen and exposure
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to contaminants, the SSI is a relevant indicator of spleen dysfunction and a useful biomarker of fish health.
The Hepato-Somatic Index (HSI) Alterations in liver size due to environmental stressors are of interest since liver plays vital functions such as energy storage and metabolism. Evaluation of the hepato-somatic index (HIS) must consider the endogenous, sometimes cyclic variations as well as the exogenous factors associated with toxicant exposure. The HSI varies with seasonal cycles (Delahunty and de Vlaming, 1980; Slooff et al., 1983; Beamish et al., 1996; Saborowski and Buchholz, 1996). Nutritional quality and regimes are main factors that affect relative liver size (Daniels and Robinson, 1986; Heidinger and Crawford, 1977; Foster et al., 1993). Gonadal development and sex of fish make the HSI to vary along the reproductive cycle (Fabacher and Baumann, 1985; Förlin and Haux, 1990; Grady et al., 1992). In females, the HSI may change due to the synthesis of vitellogenin in liver (Scott and Pankhurst, 1992). Nevertheless, the HSI is the organo-somatic index most measured to assess pollution exposure (Adams and McLean, 1985; Goede and Barton, 1990). Several investigators have suggested that relative liver enlargement in fish indicates exposure to environmental carcinogens or other toxic chemicals. Studies evaluating the relative liver size of fish from contaminated and reference sites often utilize the HSI, which expresses liver size as a percentage of total body weight (Facey et al., 1999). The rock bass Ambloplites rupestris collected from a sediment contaminated harbor showed a significant increase of splenic tissue occupied by macrophage aggregates and greater HSI than fish from reference sites (Facey, 2005). In this study macrophage aggregates and HIS were also used to evaluate the recovery of the fish population in a 7-year period after remediation has been implemented. An increase of HSI in brown bullheads (Ameiurus nebulosus) has been reported associated with polycyclic aromatic hydrocarbons (PAHs) contamination (Fabacher and Baumann, 1985; Gallagher and Di Giulio, 1989). Several other species (Atlantic cod, winter flounder, redbreast sunfish, striped bass, hard-head catfish and European plaice) exposed to different chemicals or mixtures of chemicals PAHs, PCBs, in natural or industrial waters, all had enlarged livers (Poels et al., 1980; Fletcher et al., 1982; Buckley et al., 1985; Kiceniuk and Khan, 1987; Adams et al., 1989; Everaarts et al., 1993; Secombes et al., 1995). This enlargement of fish liver seems to be due to the increase of xenobiotic metabolism rather than the increase of detoxification enzyme activities (Fabacher and Baumann, 1985; Gallagher and Di Guilio, 1989). In a coastal lagoon, contaminated with metals, condition indices (K and HSI) of mullets (Liza saliens) that bioaccumulated high concentrations of Cu and Zn in their liver were higher compared to mullets from the sea, suggesting abnormal condition in the lagoon population (Fernandes, 2008a). In contrast with these results several other studies described a decrease of liver size following exposure to contaminants (Chambers, 1979; Larsson et al., 1984; Hickie and Dixon 1987; Ruby et al., 1987; Hoque et al., 1998). The decrease of HSI may reflect glycogen loss to produce energy (Barton et al., 1987) but histopathological alterations including hepatocyte
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damage and degeneration may also result in decrease of liver size (Ram and Singh, 1988). Other explanations attribute lower HSI to altered carbohydrate metabolism (Adams et al., 1992a). The use of SSI and HSI is very challenging since they respond to several affecting factors that need to be recognized and avoided or accounted for, when possible. Organo-somatic indices should only be compared within species, or at least between similar species, of the same classes of age. In addition it is preferable a separation by gender, to avoid gender effect. The sampling procedure must be quick and effective to avoid fish handling stress that can provoke recruitment of erythrocytes from the spleen, and tissue alterations. Comparisons between polluted and natural environments must be performed with fish caught at same season. And finally, according to Dethloff and Schmitt (2000), organ size is better expressed relative to fish size excluding the gonads weight.
CONCLUSION Aquatic toxicology is part of a general trend in a world of increasing contaminant risks and it is clear that confined waters are among great concern. Coastal and shallow lagoon waters are still ecological and economical relevant resources that justify the study and development of early warning systems for evaluation of aquatic environment and fish population health. They are vital for implementation of effective recovery measures. This chapter contributes to the knowledge of liver, kidney and spleen metabolic processes and their alterations induced by pollutants exposure. The fact that contaminants usually appear in the environment as complex mixtures that can cause interactive effects, underlines the necessity of using a range of different biomarkers when attempting to evaluate environmental impact. The use of liver, kidney and spleen as an early warning system in population assessment, has the advantage of looking at different metabolic and anatomic biomarkers levels and thus offering an integrated approach of toxic effects. Biochemical responses to contaminant exposure can include changes in neuroendocrine control of osmoregulation, plasma electrolytes concentrations, EROD and plasmatic transaminases activities, metallothioneins synthesis in liver and hematologic parameters in spleen. Ultrastructural changes induced by toxicant exposure also occur in liver, kidney and spleen depending on the concentration and length of exposure. Changes in histochemical properties of splenic MAs are linked to fish exposure to contaminated environments. Besides, organo-somatic indices variations, as a measure of immune defence and as well as energy storage and metabolism, they reflect well fish toxic exposure.
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Figure 1. Diagram of the major fish organs involved in the regulation, hemopoietic, immune and detoxification processes, and the evaluation of their responses to be used as fish biomarkers of stress/injury.
The suite of methods that should be applied to each organ depends on sensitivity, costeffectiveness, the ability of the methods to detect the contaminants and requires expertise. In addition, the experimental design should take into account the potential confounding factors that may occur for each of the described biomarkers. Regarding structural aspects, the knowledge of the normal organ microanatomy is fundamental to properly evaluate abnormal physiologic and histological changes. The fact that toxic agents can act as stressors also implies that their effects are partially additive with those of other stressors. As outlined in this manuscript, the structure of the organs normally varies in direct connection with gender, age, nutritional status, or temperature. Moreover, a solid baseline data on the normal morphology and physiologic range is essential to establish associations with toxic induced changes. Concerning fish, long-term toxic exposure can instigate several adaptive responses therefore is essential to know such variations for correct discrimination between structural adaptations and lesions caused by pollutants. The weight-of-evidence for the utility of analysing these organs, as an early warning system, is that it can be useful for detecting toxic diffuse effects, such as those arising from poor accumulation in fish. Similarly, more than one autochthon fish species is useful for accurately assess the presence of environmental contaminants, given that metabolic pathways in different species can show diverse sensitivity and behavior to respond against toxic exposure. This approach contributes to a realistic understanding of the implications and extent of aquatic pollution and thus to choose wisely remediation strategies to achieve a sustainable management.
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Balint, T., Ferenczy, J., Katai, F., Kiss, I., Kraczer, L., Kufcsak, O., Lang, G., Polyhos, C., Szabó, I., Szegletes, T. & Nemcsok, J. (1997). Similarities and differences between the massive eel (Anguilla anguilla L.) devastations that occurred in lake Ablation in 1991 and 1995. Ecotoxicol Environ Saf., 37, 17-23. Balm, P. H. M. & Pottinger, T. G. (1995). Corticotrope and melanotrope pomc-derived peptides in relation to interrenal function during stress in rainbow-trout (Oncorhynchusmykiss). Gen Comp Endocrinol, 98, 279-288. Barni, S., Bernocchi, G. & Gerzelli, G. (1985). Morphohistochemical changes in hepatocytes during the life cycle of the European eel. Tissue Cell, 17, 97-109. Barton, B. A. (2002). Stress in fishes: A diversity of responses with particular reference to changes in circulating corticosteroids. Integrative and Comparative Biology, 42, 517-525. Bello, S. M., Franks, D. G., Stegeman, J. J. & Hahn, M. E. (2001). Acquired resistance to Ah receptor agonists in a population of Atlantic killifish (Fundulus heteroclitus) inhabiting a marine Superfund site: in vivo and in vitro studies on the inducibility of xenobiotic metabolizing enzymes. Toxicol Sci., 60(1), 77-91. Bentley, P. J. (1991). Accumulation of cadmium by channel catfish (Ictalurus punctatus) influx from environmental solutions. Comp Biochem Physiol C Pharmcol Toxicol Endocrinol, 99, 527-529. Bernier, N. J., McKendry, J. E. & Perry, S. F. (1999). Blood pressure regulation during hypotension in two teleost species: Differential involvement of the renin-angiotensin and adrenergic systems. J Exp Biol., 202, 1677-1690 Beyenbach, K. W. (1995). Secretory electrolyte transport in renal proximal tubules of fish. In: Cellular and molecular aproaches to fish ionic regulation. C. M. Wood, & T. J. Shuttleworth, (eds.). Academic Press, New York, 85-103. Biagianti-Risbourg, S. & Bastide, J. (1995). Hepatic perturbations induced by a herbicide (atrazine) in juvenile grey mullet Liza ramada (Mugilidae, Teleostei): an ultrastructural study. Aquat Toxicol, 31, 217-29. Boorman, G. A., Botts, S., Bunton, T. E., Fournie, J. W., Harshbarger, J. C., Hawkins, W. E., Hinton, D. E., Jokinen, M. P., Okihiro, M. S. & Wolfe, M. J. (1997). Diagnostic criteria for degenerative, inflammatory, proliferative nonneoplastic and neoplastic liver lesions in medaka (Oryzias latipes): consensus of a National Toxicology Program Pathology Working Group. Toxicol Pathol, 25, 202-10. Breuil, G., Vassiloglou, B., Pepin, J. F. & Romestand, B. (1997). Ontogeny of IgM-bearing cells and changes in the immunoglobulin M-like protein level (IgM) during larval stages in sea bass (Dicentrarchus labrax). Fish Shellfish Immunol, 7, 29-43. Brodeur, J. C., Daniel, C., Ricard, A. C. & Hontela, A. (1998). In vitro response to ACTH of the interrenal tissue of rainbow trout (Oncorhynchus mykiss) exposed to cadmium. Aquat Toxicol, 42, 103-113. Brown, E. J. (1995). Phagocytosis. BioEssays, 17, 109-117. Bruslé, J. & Anadon, G. G. (1996). The structure and function of fish liver. In Fish Morphology - Horizon of New Research. J. S. D. Munshi, & H. M. Dutta, (eds). New Delhi and Calcutta, India: Oxford & IBH Publishing, 77-93. Bury, N. R. (2005). The changes to apical silver membrane uptake, and basolateral membrane silver export in the gills of rainbow trout (Oncorhynchus mykiss) on exposure to sublethal silver concentrations. Aquat Toxicol, 72, 135-145.
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Press, C. M. & Evensen, O. (1999). The morphology of the immune system in teleost fishes. Fish Shellfish Immunol, 9, 309-318. Rao, J. V. (2006). Sublethal effects of an organophosphorus insecticide (RPR-II) on biochemical parameters of tilapia, Oreochromis mossambicus. Comp Biochem Physiol, Part C, 143, 492-498. Ramesh, M., Saravanan, M. & Kavitha, C. (2009). Hormonal responses of the fish, Cyprinus carpio, to environmental lead exposure. Afr J Biotechnol, 8, 4154-4158. Reid, S. G., Bernier, N. J. & Perry, S. F. (1998). The adrenergic stress response in fish: control of catecholamine storage and release. Comp Biochem Physiol Part C Toxicol Pharmcol, 120, 1-27. Robertson, J. C. & Bradley, T. M. (1992). Liver ultrastructure of juvenile Atlantic salmon (Salmo salar). J Morph, 21, 41-54. Rocha, E. & Monteiro, R. A. F. (1999). Histology and Cytology of Fish Liver: A Review. Ichthyology: Recent Research Advances. D. N. Saksena, (eds), New Delhi, India: Oxford & IBH Publishing Co. Pvt. Ltd. and Enfield, New Hampshire, USA: Science Publishers, Inc. 321-344. Rocha, E., Rocha, M. J. & Monteiro, R. A. F. (2003). Seasonal changes in fish hepatocytes and correlations with the endocrine system. In Fish Adaptations. B. G. Kapoor, & A. L. Val, (eds). Enfield, New Hampshire, USA, Science Publishers, Inc., Plymouth, UK, Plymbridge Distributors Ltd., 383-403. Romano, N., Abelli, L., Mastrolia, L. & Scapigliati, G. (1997). Immunocytochemical detection and cytomorphology of lymphocyte subpopulations in a teleost fish Dicentrarchus labrax. Cell Tissue Res., 289, 163-171. Rotchell, J. M., Clarke, K. R., Newton, L. C. & Bird, D. J. (2001). Hepatic metallothionein as a biomarker for metal contamination: age effects and seasonal variation in European flounders Pleuronectes flesus from the Severn estuary and Bristol Channel. Mar Environ Res., 52, 151-171. Rowley, A. F. & Ratcliffe, N.A. (1988). Vertebrate blood cells. Cambridge University Press, Cambridge - Great Britain. Sakamoto, T. & McCormick, S. D. (2006). Prolactin and growth hormone in fish osmoregulation. Gen Comp Endocrinol, 147, 24-30. Sarmento, A., Guilhermino, L. & Afonso, A. (2005). Mercury chloride effects on the function and cellular integrity of sea bass (Dicentrarchus labrax) head kidney macrophages. Fish Shellfish Immunol, 17, 489-498. Saxena, M. P. & Saxena, H. M. (2008). Histopathological changes in lymphoid organs of fish after exposure to water polluted with heavy metals. The Internet Journal of Veterinary Medicine, 5(1), ISSN: 1937-8165. Schar, M., Maly, I. P. & Sasse, D. (1985). Histochemical studies on metabolic zonation of the liver in the trout (Salmo gairdneri). Histochemistry, 83, 147-51. Schroder, M. B., Villena, A. J. & Jorgensen, T. O. (1998). Ontogeny of lymphoid organs and immunoglobulin producing cells in Atlantic cod (Gadus morhua L.). Dev Comp Immunol, 22, 507-517. Schwindt, A. R., Truelove, N., Schreck, C. B., Fournie, J. W., Landers, D. H. & Kent, M. L. (2006). Quantitative evaluation of macrophage aggregates in brook trout (Salvelinus fontinalis) and rainbow trout (Oncorhynchus mykiss). Dis Aquat Org., 68(2), 101-113.
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Secombes, C. J. (1993). Phagocytes and immunity in fish. The Nordic Symposium on Fish Immunology. The Nordic Society for Fish Immunology, Lysekil - Denmark, 9-11. Secombes, C. J. (1994). Enhancement of fish phagocyte activity. Fish Shellfish Immunol, 4, 421-436. Secombes, C. J. & Fletcher, T. C. (1992). The role of phagocytes in the protective mechanisms of fish. Ann Rev Fish Dis, 2, 73-51. Secombes, C. J., Hardie, L. J. & Daniels, G. (1996). Cytokines in fish: an update. Fish Shellfish Immunol, 6, 291-304. Segner, H., Dölle, A. & Böhm, R. (1997). Ketone body metabolism in the carp Carpinus carpio: biochemical and IH-HMR spectroscopical analysis. Comp Biochem Physiol, 116B, 257-62. Sepúlveda, M. S., Gallagher, E. P. & Gross, T. S. (2004). Physiological changes in largemouth bass exposed to paper mill effluents under laboratory and field conditions. Ecotoxicology, 13, 291-301. Singh, S.M. & Sivalingam, P. M. (1982). In vitro study on the interactive effects of heavy metals on catalase activity of Sarotherodon mossambicus (Peters). J Fish Biol., 20, 683688. Šimková, A., Lafond, T., Ondračková, M., Jurajda, P., Ottová, E. & Morand, S. (2008). Parasitism, life history traits and immune defence in cyprinid fish from Central Europe. BMC Evol Biol., 8(29). Spazier, E., Storch, V. & Braunbeck, T. (1992). Cytopathology of spleen in eel Anguilla anguilla exposed to a chemical spill in the Rhine River. Diseases of Aquatic Organisms, 14, 1-22. Stegeman, J. J., Binder, R. L. & Orren, A. (1979). Hepatic and extrahepatic microsomal electron transport components and mixed function oxidases in the marine fish (Stenotomus versicolor). Biochem Pharmacol, 28, 3431-9. Stegeman, J. J. & Lech, J. J. (1991). Cytochrome P-450 monooxygenase systems in aquatic species: Carcinogen metabolism and biomarkers for carcinogen and pollutant exposure. Environ Health Perspect, 90, 101-109. Stegema,n, J. J. & Hahn, M. E. (1994). Biochemistry and molecular biology of monooxygenases: current perspectives on forms, functions and regulation of cytochrome P450 in aquatic species. In Aquatic Toxicology (D. C. Malins, & G. K. Ostrander, eds.), 87-203. Lewis Publishers, Boca Raton. Stentiford, G. D., Longshaw, M., Lyons, B. P., Jones, G., Green, M. & Feist, S. W. (2003). Histopathological biomarkers in estuarine fish species for the assessment of biological effects of contaminants. Mar Environ Res., 55, 137-159. Stephen, C., Kent, M. L. & Dawe, S. C. (1993). Hepatic megalocytosis in wild and farmed chinook salmon Oncorhynchus tshawytscha in British Columbia, Canada. Dis Aquat Org., 16, 35-9. Storch, V., Segner, H., Juario, J. & Duray, M. (1984). Influence of nutrition on the hepatocytes of Chanos chanos (Chanidae, Teleostei). Zool Anz., 213, 151-160. Suresh, N. (2009). Effect of cadmium chloride on liver, spleen and kidney melano macrophage centres in Tilapia mossambica. J Environ Biol, 30(4), 505-508. Tort, L., Balasch, J. C. & Mackenzie, S. (2003). Fish immune system. A crossroads between innate and adaptive responses. Immunologiya, 22(3), 277-286.
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Van Bohemen, C., Lambert, J. & Peute, J. (1981). Annual changes in plasma and liver in relation to vitellogenesis in the female rainbow trout, Salmo gairdineri. Gen Comp Endocrinol, 44, 94-107. Van Campenhout, K., Bervoets, L., Redeker, E. S. & Blust, R. (2009). A kinetic model for the relative contribution of waterborne and dietary cadmium and zinc in the common carp (Cyprinus carpio). Environ Toxicol Chem., 28, 209-219. Van der Oost, R., Beyer, J. & Vermeulen, N. P. E. (2003) Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharmacol, 13, 57-/149. Van Veld, P. A. & Westbrook, D. J. (1995). Evidence for depression of cytochrome P4501A in a population of chemicallyresistant mummichog (Fundulus heteroclitus) from a creosote- contaminated environment. Environ Sci., 3, 221-224. Varsamos, S., Nebel, C. & Charmantier, G. (2005). Ontogeny of osmoregulation in postembryonic fish: A review. Comp Biochem Physiol Part A Mol Integr Physiol, 141, 401-429. Venugopal, N. & Reddy, S. L. N. (1993). In-vivo effects of trivalent and hexavalent chromium on renal and hepatic ATPases of a fresh-water teleost Anabas-scandens. Environ Monit Assess, 28, 131-136. Vethaak, D. (1993). Diseases of flounder (Platichtys flesus) in Dutch coastal and estuarine waters, with particular reference to environmental stress factors: part 2, liver histopathology. PhD thesis, 59-81. Vinodhini, R. & Narayanan, M. (2009). Heavy metal induced histopathological alterations in selected organs of the Cyprinus carpio L. (Common Carp). International Journal of Environmental Health Research, 3, 95-100. Walter, G. L., Jones, P. D. & Giesy, J. P. (2000). Pathologic alterations in adult rainbow trout, Oncorhynchus mykiss, exposed to dietary 2,3,7,8-tetrachlorodibenzo-p-dioxin. Aquat Toxicol, 50, 287-299. Wendelaar Bonga, S. E. (1997). The stress response in fish. Physiol Rev., 77, 591-625. Wendelaar Bonga, S. E. & Lock, R. A. C. (2008). The osmoregulatory system. In The toxicology in fishes. R. T. Di Giulio, (eds). CRC Press, New York. 401-415. Wester, P. W. & Canton, J. H. (1987). Histopathological study of Poecilia reticulata (guppy) after long term exposure to bis(tri-n-butyltin)oxide (TBTO) and di-n-butyltindichloride (DBTC). Aquat Toxicol, 10, 143-65. Wester, P. W., Canton, J. H., Van Iersel, A. A. J., Kranjnc, E. I. & Vaessen, H. A. M. G. (1988). The toxicity of bis(tri-n-butyltin)oxide (TBTO) and di-n-butyltindichloride (DBTC) in the small fish species Oryzias latipes (medaka) and Poecilia reticulata (guppy). In Toxicological Pathology in Fish: An Evaluation with Two Species and Various Environmental Contaminants, 107-28. Door, The Netherlands. Wester, P. W., van der Ven, L. T. M., Brandhof, E. J. & Vos, J. H. (2003). Identification of endocrine disruptive effects in the aquatic environment: a partial life cycle assay in zebrafish. RIVM Report 6409200001/2003, 31-9. Wright, D. A. & Welbourn, P. M. (1993). Effects of mercury exposure on ionic regulation in the crayfish Orconectes propinquus. Environmental Pollution, 82, 139-142. Wyte, J. J., Jung, R. E., Schmitt, C. J. & Tillitt, D. E. (2000). Ethoxyresorufin-o-deethylase (EROD) activity in fish as a biomarker of chemical exposure. Critical Rev. Toxicol, 30 (4), 347-570.
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Wolf, J. C. & Wolfe, M. J. (2005). A Brief Overview of Nonneoplastic Hepatic Toxicity in Fish Toxicologic Pathology, 33, 75-85. Zapata, A., Diez, B., Cejalvo, T., Gutiérrez-de Frías, C. & Cortés, A. (2006). Ontogeny of the immune system of fish. Fish Shellfish Immunol, 20(2), 126-136. Zapata, A. G., Chibá, K. & Varas, A. (1996) Cells and tissues of the immune system of fish. In The fish immune system: organism, pathogen and environment. G. Iwama, T. & Nakanishi, (eds). Academic Press, USA. Zapata, A., Chibá, A. & Varas, A. (1996). Cells and tissues of the immune system of fish. In The fish immune system. G. K. Iwama, & Nakanishi, T. (eds.). Academic Press, USA, 153. Zapata, A. G. & Cooper, E. L. (1990). The immune system: Comparative histophysiology. John Wiley & Sons, Chichester.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 39-72 © 2011 Nova Science Publishers, Inc.
Chapter 2
BENTHIC FORAMINIFERA IN COASTAL LAGOONS: DISTRIBUTIONAL PATTERNS AND BIOMONITORING IMPLICATIONS F. Frontalini,1 E. Armynot du Châtelet2, J.P. Debenay3, R. Coccioni1 and G. Bancalà1
1
DiSUAN, Urbino University, Campus Scientifico, Localita' Crocicchia, 61029, Urbino, Italy 2 CNRS, UMR 8157, UFR des Sciences de la Terre, Laboratoire Géosystèmes, Université de Lille-1, bâtiment SN5, 59655 Villeneuve d‘Ascq cedex, France 3 IRD, Unité 182 LOCEAN, BP A5, 98848 Nouméa cedex, Nouvelle-Calédonie, France
ABSTRACT Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. Moreover, these ecosystems are often subjected to a great deal of anthropogenic impact, which further complicates our understanding of these habitats. Comparative studies of lagoonal environments essentially require the utilization of organisms that are distributed worldwide and occur in high density populations in most of the benthic niches. This is certainly the case for foraminifers which, as lower trophic level members, are crucial to the biological community and ideal candidates for comprehensive habitat assessment. Some widespread paralic benthic foraminiferal species are present from temperate macrotidal estuaries to tropical microtidal lagoons, thus enabling comparative studies of environmental conditions to be conducted.
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F. Frontalini, E. Armynot du Châtelet, J.P. Debenay et al. Since lagoons are increasingly affected by environmental stress and degradation due to pollution and other anthropogenic factors, there is a pressing need to develop a set of indicators and monitoring approaches with which to assess their health. A large number of research programs have addressed these issues within various regions, and studies of foraminiferal assemblages have produced very useful, comprehensive datasets on environmental and biotic conditions. This paper is a review of what is known about the foraminiferal assemblages living in lagoons, including their distribution according to environmental parameters and their value when it comes to assessing environmental quality in these ecosystems.
1. INTRODUCTION A lagoon is ‗a body of shallow sea water or brackish water separated from the sea by some form of barrier‘, which excludes isolated inland saline water bodies. In reality, lagoons are complex ecotones located between continental and marine systems. They are also highly heterogeneous due to: 1) strong variations in physical, chemical and biological characteristics over space and time, and 2) multiple exchanges with the limiting continental and marine systems, the atmosphere, and sediments. Located at the transition between the continental and the marine realms, lagoons belong to paralic habitats. The term paralic was defined by Naumann (1854) for fossil environments and was first used by a sedimentary geologist. Later, the notion was adapted to apply to recent ecosystems comprising estuaries, coastal lagoons, marshes, and coastal zones under high freshwater input (Guélorget and Perthuisot, 1983, 1992). This term is more precise than the traditional phrase ‗margino marine‘ and is increasingly used to refer to modern environments. For the purpose of this study, we restricted our survey to clastic lagoons separated from the ocean by a depositional land barrier, excluding coral reef lagoons. We also used the physiography of clastic lagoons as clarified by Kjerfve (1986), who distinguished between restricted, choked and leaky lagoons (Figure 1). In particular, restricted lagoons are characterized by two or more entrance channels or inlets as well as well-defined tidal circulation.
Figure 1. Schematic representations of restricted, choked and leaky lagoons, after Kjerfve (1986)
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Like other paralic environments (e.g. marsh, mangrove, estuary, fjord and delta), lagoons exhibit a balance between an enhanced freshwater input and an evaporation loss, which determines a salinity gradient within the continuity of the aquatic habitat. Transition processes are much more complex in sheltered lagoons with high water retention times than in large well-flushed estuaries. On the basis of the triple influence of fluvial input, exchanges with the sea, and climate, the gradation can be either horizontal and/or vertical, and moves from brackish to hypersaline environments. These general conditions are complicated by a complex interplay of an array of parameters that include: (1) local climatic conditions (i.e. temperature, insolation, evaporation-rainfall balance); (2) horizontal salinity distribution, which also controls plant distribution; (3) vertical mixing between hypo- and hypersaline water, thus affecting water stratification; (4) hydrodynamic turnover time; (5) the energy of wind-forced currents and wave action; (6) the nature of the bottom; (7) the occurrence of seaweed or seagrass meadows; (8) the quality and quantity of suspended sediment (turbidity), nutrients, and dissolved and particulate organic matter; (9) the physical-chemical characteristics of the water (mainly oxygen content and pH); and (10) aperiodic crises, such as anoxia, drought, storms, or frost (Debenay et al., 2000; Debenay and Guillou, 2002). These multiple factors lead to a major internal patchiness and heterogeneity, as well as environmental fluctuations which occur at a variety of time scales ranging from daily to seasonal to years/decades, and which are further influenced by multiple impacts of anthropogenic activities. These can be the result of: pollution from industrial, domestic, agricultural, and mining work; dredging and spoil dumping; salinization; siltation and sedimentation from land clearance; forestry; and the destruction of habitat. Agricultural runoffs may be enriched in nutrients and pesticide residues, the former of which can lead to eutrophication, the deterioration of water quality and, ultimately, anoxic conditions (Wilson et al., 1993; Moss, 1996). However, nutrients are not the only chemicals affecting the ecosystems; trace elements and other organic and inorganic chemicals are also ubiquitous contaminants of the aquatic environment. There is, therefore, a need to develop a set of indicators and monitoring approaches for use in these shallow transitional waters which are increasingly affected by environmental stress that is naturally and, above all, anthropogenically induced. This requirement is made more difficult by the complexity of these environments, which can often influence and complicate the application of the most common indicators and indices of environmental quality and health status. A large number of research programs have addressed these problems within various coastal regions, and have produced extremely valuable and comprehensive datasets on the environmental and biotic conditions within these systems. A growing number of new tools and methods for assessing the health of these systems have thus emerged, and of these foraminifera are of primary importance. Foraminifera (class Foraminifera: d‘Orbigny, 1826; phylum Granuloreticulata) are single-celled organisms (protists), which play a significant role in global, biogeochemical cycles of inorganic and organic compounds, making them one of the most important animal groups on earth (Haynes, 1981; Lee and Anderson, 1991; Yanko et al., 1999). Furthermore, many foraminiferal taxa secrete a carbonate shell, which is readily preserved and so records evidence of environmental stresses and changes over time. They are commonly small and abundant compared to other hard-shelled taxa and are easy to collect, meaning that a highly reliable database for statistical analysis can be obtained, even when only small sample
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volumes are available. Because of their: widespread distribution; short life and reproductive cycles (from a few weeks for small taxa to one year for some larger forms: Boltovskoy, 1965, and Murray, 1991, 2006); high biodiversity; and specific ecological requirements, foraminifera respond rapidly to environmental changes. Benthic foraminifera are particularly sensitive, and can be successfully utilized for their value as bio-indicators of environmental change in a wide range of marine environments (e.g. Alve, 1991, 1995; Yanko et al., 1999; Coccioni, 2000; Debenay et al., 2001, 2005; Murray and Alve, 2002; Armynot du Châtelet et al., 2004; Frontalini and Coccioni, 2008; Frontalini et al., 2009, 2010; Coccioni et al., 2009; Debenay et al., 2009a; Armynot du Châtelet and Debenay, 2010). The aim of this paper is to review the recent advances and achievements when it comes to understanding the processes controlling the distribution of foraminiferal assemblages within lagoons. The main findings in relation to an array of parameters will also be summarized and emphasized. The article will also discuss the significance and influence of anthropogenic activities on benthic foraminifera in these sensitive, but environmentally valuable, areas.
2. MATERIAL AND METHODS Samples were collected either with a grab sampler or by snorkelling in subtidal environments. At intertidal stations, the samples were obtained by scraping off the upper five millimeters of sediment. The collections were made at several points over a surface of about 1 m2 using a pseudoreplication strategy (Hurlbert, 1984) to limit the bias due to patchy distribution. In such heterogeneous environments, field experience shows that the standard collection of samples over a 10 cm2 surface (e.g. Wells, 1971) does not provide reliable data, while the time consuming study of replicates (e.g. Murray, 2006) is justified only for detailed studies of living assemblages. Samples can be preserved in alcohol (ethanol), which allows Rose Bengal staining (Walton, 1952) to be used to help identify living individuals. Only superficial samples are considered because, even though foraminifera can live at depths of 30 cm in the sediment (e.g. Goldstein et al., 1995; Ozarko et al., 1997), the greatest numbers of living creatures, which produce the accumulation of living and empty tests, are found in the surface layer <1 cm (review in Alve and Murray, 2001). Collecting sediment from greater depths would also include tests deposited over a long period of time. At the laboratory, a subsample of 50 cm3 was extracted from each sample after homogenization and then washed through 315 and 50/63 μm sieves. After drying, the microfauna were separated from sand grains by flotation on trichloroethylene (d=1.465) or carbon tetrachloride (d=1.594). Observations were carried out under a stereo microscope and: (1) the total number of tests in 50 cm3 of sediment was examined; (2) 100 to 300 individuals, depending on the total number of species, were counted (Fatela and Taborda, 2002); and (3) whole samples were checked for rare species which were not found during counting. When the population density was lower than 100, all of the individuals were counted. Rose Bengal stained (living?) individuals were noted separately to provide information on living, dead and total (stained + empty tests) assemblages. However, the reliability of Rose Bengal staining for determining living individuals is still the subject of some debate (discussion in Debenay et al., 2009b, p. 253-254), and the study of living assemblages in highly dynamic environments, such as lagoons, might be more appropriate for time series studies.
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3. FORAMINIFERA LIVING IN LAGOONAL ENVIRONMENTS Complicated by tidal and seasonal cycles, the physicochemical characteristics of lagoonal environments can change drastically in relation to hydrodynamic turnover time (itself a function of freshwater input), tidal currents, wind forced currents, and volume lost by evaporation and gravitational circulation. Benthic organisms living in such environments must adapt to this instability and are generally euryhaline and eurythermal. For example, the cosmopolitan Ammonia tepida tolerates salinities ranging from 0.2 to 100 (Bradshaw, 1957; Reddy and Rao, 1984; Debenay, 1990; Almogi-Labin et al., 1992; Wennrich et al., 2007). However, only a few species can tolerate such ecological conditions, and the foraminiferal assemblages in lagoons are poorly diversified and display high levels of dominance. Despite the fact that endemic species which characterize specific areas can be found, there is an overall species similarity in lagoonal environments. The foraminiferal assemblages are generally dominated by Rotaliina in moderately restricted environments, the most cosmopolitan species being Ammonia parkinsoniana (d‘Orbigny, 1839), Ammonia tepida (Cushman, 1826), Elphidium gunteri (Cole, 1931), Haynesina germanica (Herenberg, 1840), and Quinqueloculina seminula (Linné, 1758) (Figure 2). On the other hand, the agglutinated species Ammobaculites exiguus Cushman and Brönnimann, 1984, Ammotium salsum (Cushman and Brönnimann, 1984), Arenoparella mexicana (Kornfeld, 1931), Gaudryna exilis Cushman Brönnimann, 1984, Haplophragmodes wilberti Andersen, 1953, Pseudoclavulina sp. and Trochammina spp. are the dominant species in restricted to highly restricted environments (Figure 2). Low salinity habitats are dominated by Miliammina fusca (Brady, 1870), Astrammina sphaerica (Heron-Allen and Earland, 1932) and Polysaccammina ipohalina Scott, 1976 (Figure 2). Ammonia tepida and Q. seminula are considered to be quite tolerant of environmental stress (Debenay et al., 2000; Debenay and Guillou, 2002), and these two species have been regarded as the primary pioneers in several paralic environments (Debenay et al., 2009b). For example, in the hypersaline Araruama Lagoon (Brazil) and Lake Qarun (Egypt), they comprise 70% of the total foraminiferal assemblage (Debenay et al., 2001; Abu-Zied et al., 2007). Ammonia beccarii (tepida?), which is associated with Cribroelphidium articulatum, was also reported as being present in the hypersaline Coorong Lagoon (Cann et al., 2000). It is also well represented in the Santo André Lagoon, Portugal, in association with H. germanica, Elphidium oceanensis and Q. seminula (Cearreta et al., 2002); in Lake lllawarra, Australia, where it is associated with Cribrononion sydneyensis (Yassini and Jones, 1989) and in small coastal lagoons located along the coast of West Africa (Debenay, 1990). In Croatia, A. tepida lives in low-oxygen, slightly hypersaline lagoons, typically in association with Haynesina depressula Walker and Jacob, 1798, Elphidium crispum (Linné, 1758), and Quinqueloculina spp. (Vanicek et al., 2000). However, a great deal of confusion still exists about the variety of forms and the taxonomy of the genus, despite numerous attempts to clarify these issues (e.g. Hayward et al., 2004). It is, therefore, highly probable that several different species are present in lagoons.
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Figure 2. Benthic foraminiferal species in lagoon environments: 1. Polysaccammina ipohalina, 2. Trochammina inflata, 3. Pseudoclavulina sp., 4. Ammobaculites exiguus, 5. Ammotium salsum lateral and apertural views, 6. Miliammina earlandi apertural and lateral views, 7. Miliammina fusca lateral and apertural views, 8. Caronia exilis lateral and apertural views, 9. Quinqueloculina seminula, 10. Arenoparrella mexicana spiral, apertural, and umbilical views, 11. Haplophragmoides wilberti lateral and apertural views, 12. Eponides repandus apertural and spiral views, 13. Discorbinella bertheloti spiral, umbilical, and lateral views, 14. Bolivina striatula, 15. Porosononion granosum, 16. Nonionella turgida, 17. Discorinopsis agayoi umbilical and spiral views, 18. Pararotalia cananeiaensis spiral, lateral and umbilical views, 19. Ammonia parkinsoniana umbilical view, 20. Ammonia tepida umbilical views, 21. Elphidium gunteri, 22. Cribroelphidium excavatum, 23. Haynesina germanica, 24. Haynesina depressula, 25. Elphidium crispum. Scale bars are 100µm
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The geographic distribution of these paralic species covers spectacularly wide latitudinal and longitudinal ranges (e.g. Sen Gupta, 1999; Debenay and Guillou, 2002), and their worldwide distribution supposes powerful dispersion processes. Aerial transport, over short or great distances, is often mentioned, since foraminifera may occasionally survive on the muddy feet or feathers of migratory seabirds, whose landfalls are mostly intertidal mud and sand flats (e.g. Resig, 1974; Lessard, 1980; Patterson et al., 1997; Hayward and Hollis, 1994; Almogi-Labin et al., 1995; Wennrich et al., 2007). Transport by fish is also possible if they move from one area to another during feeding and defecation (Daniels and Lipps, 1978; Langer and Lipps, 2006; Debenay et al., in press). The transplantation of marine fish or shellfish may also play a part in the introduction of new foraminifera (Arnal, 1954; Bouchet et al., 2007). Travel over short distances may similarly affect embryonic juveniles, which are easily transported thanks to a density that is similar to that of seawater (Goubert, 1997; Alve, 1999; Hayward et al., 1999). Accordingly, incoming tidal currents probably introduce many coastal species to the lagoons, but only those that can adapt, grow and reproduce in the new environment survive. In shallow paralic environments, the most successful colonizer is A. tepida in both brackish (Wennrich et al., 2007) and hypersaline (Almogi- Labin et al., 1992) waters. Indeed, during interglacial intervals in the Quaternary, it colonized lakes along the Mediterranean (Usera et al., 2002). It also populated shrimp ponds, which are associated with Q. seminula, with its fast reproduction rates rapidly increasing the density of live specimens and the accumulation of empty tests (Debenay et al., 2009b).
4. DISTRIBUTION OF FORAMINIFERA IN LAGOONAL ENVIRONMENTS 4.1. Common Pattern Numerous studies of benthic foraminiferal assemblages have been carried out in lagoons, (e.g. Closs, 1963; Closs and Madeira, 1968; Schafer and Sen Gupta, 1969; Murray, 1971; Madeira-Falceta, 1974; Suguio et al., 1975; Scott, 1976a,b; Zaninetti et al., 1977, 1979; Scott and Medioli, 1980; Zaninetti, 1982; Beurlen and Hilterman, 1983; Boltovskoy and Martinez, 1983; Debenay, 1990, 1991; Albani et al., 1991; Debenay et al., 1993; Alve and Murray, 1994a; Hayward et al., 1996; Redois and Debenay, 1996; Vanicek et al., 2000; Coccioni, 2000; Cearreta et al., 2002; Serandrei Barbero et al., 2004). A common pattern is their general distribution along a marine-continental gradient, with diverse assemblages, including calcareous forms closest to the ocean, changing landwards into oligospecific-to-monospecific assemblages in both hyposaline and hypersaline environments (Debenay et al., 2000; Debenay and Guillou, 2002). Low diversity assemblages present in the areas closest to freshwater input contain only agglutinated species (e.g. Serandrei Barbero et al., 1997; Lloyd and Evans, 2002) As stated by Nichols (1974) and reported in numerous studies, this pattern suggests that salinity is the major controlling factor for the presence of foraminiferal assemblages in paralic environments. However, their distribution is often more complex, reflecting multiple interactions between the distance to the sea, water depth, the nature of the sediment,
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hydrodynamic turnover time, tidal currents, wind forced currents, and gravitational circulation etc. It also depends on the great variety of foraminiferal behaviour, namely mode of nutrition, tolerance to oxygen depletion, steno- or euryhalinity, steno- or eurythermy, epior endofaunal mode of life, and free or attached mode of life. Among the major parameters identified as having a strong influence on foraminiferal distribution are: exposure during tidal cycles (Hayward and Hollis, 1994; De Rijk, 1995; Horton et al., 1999); pH (Wang, 1992); organic matter content; and grain size of the sediment (Scott et al., 1979; Zaninetti, 1982; Petrucci et al., 1983; Albani et al., 1991; Jennings and Nelson, 1992; Coccioni 2000). Consequently, foraminiferal assemblages may change considerably from one lagoon to another, depending on local characteristics. As a result of the complexity of interpreting entire assemblages, biocenotic indices, such as the diversity index or the dominance index, are often used for the characterization of the community structure and, subsequently, environmental conditions. However, attempts to use the Fisher diversity index revealed that values vary irregularly between 2 and 8 inside the lagoons, without any clear ecological significance (Zaninetti et al., 1977; Debenay, 1990; Debenay et al., 1998). This is probably the result of a replacement of fauna (hyaline species replaced by agglutinated ones), rather than a simple faunal change. Moreover, biocenotic indices neither take into account the role of the species in the community, nor their potential interest as bioindicators. Accordingly, they are of lesser value than the methods based on the presence/absence of bioindicator species (Caquet and Lagadic, 1998). Instead of such biocenotic indices, the ―Confinement Index‖, or Ic, which is based on the relative abundance of species identified as being characteristic of environmental conditions, has been defined in the estuaries and lagoons of West Africa (Debenay, 1990). It was later adapted, with slight modifications, for utilization in Brazilian lagoons (Debenay et al., 1996), a Mediterranean lagoon (Debenay et al., 2005), and in the Mekong estuary (Debenay and Luan, 2006). The species used for the calculation of the Ic are listed in Table 1. The following selected examples were studied separately by one of us. They are grouped together here to illustrate the particular conditions that can prevail in some representative lagoonal environments.
Figure 3. Locations map of some of the presented lagoons
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Table 1. The Confinement Index and the species considered for its calculation in different worldwide areas Group A, species related to strong marine influence: Mediterranean (Kalloni)
Vietnam (Mekong delta)
Elphidium crispum, Gavelinopsis praegeri, Lobatula lobatula, Nonionella turgida, Quinqueloculina stelligera, Rosalina bradyi, R. floridensis, R. globularis, Triloculina adriatica Asterorotalia dentata, Asterorotalia pulchella, Brizalina striatula, Cribroelphidium cf. incertum, Rosalina sp.
Group B, species from paralic environments subjected to noticeable marine influence: Aubignyna planidorso, Brizalina striatula, B. variabilis, Eggerelloides scaber, Elphidium jenseni, Porosononion granosum Ammonia spp., Brizalina cf. variabilis, Haynesina sp., Miliammina spp., Quinqueloculina seminula
Brazil (coastal lagoons)
Bolivina striatula, Elphidium gunteri, Pararotalia sp., Rosalina spp.
Ammonia spp., Bolivina variabilis, Elphidium galvestonense, Haynesina germanica, Quinqueloculina seminula, Quinqueloculina poeyana
Africa (coastal lagoons and estuaries)
Elphidium fichtelianum, Pararotalia sp., Bolivina striatula, Rosalina spp.
Eggerelloides scaber, Quinqueloculina poeyana, Q. seminula, Haynesina germanica, Elphidium gunteri, E. limosum, Bolivina variabilis, Ammonia spp.
Western coast of France
Brizalina strialula, Brizalina variabilis, Cribroelphidium excavatum, Elphidium pulvereum, Quinqueloculina stelligera, Rosalina spp.
Ammonia tepida, Elphidium gunteri, Haynesina germanica, Quinqueloculina seminula
Group C, euryhaline species living in more restricted areas: Ammonia tepida, A. convexa, Cribroelphidium translucens, Haynesina depressula simplex, Haynesina sp., Quinqueloculina seminula
Ammobaculites formosensis, Ammotium cf. salsum, Arenoparrella asiatica, Haplophragmoides wilberti, Jadammina macrescens, Siphotrochammina lobata, Trochammina spp. Ammobaculites exiguus, Ammotiumsalsum, Arenoparrella mexicana, Gaudryina exilis, Haplophragmoides wilberti, Miliammina spp., Trochammina spp., Siphotrochammina spp. Ammobaculites exiguus, Ammotium salsum, Arenoparella mexicana, Gaudryina exilis, Haplophragmoides wilberti, Miliammina spp., Trochammina spp., Siphotrochammina lobata Jadammina macrescens, Miliammina spp., Paratrochammina spp., Trochammina spp.
Ic = (C /(B + C) - A /(A + B) + 1)/2Ic = 1 if assemblage III is the only one represented (A + B = 0); Ic = 0 if assemblage I is the only one represented (B + C = 0). Ic<0.4 indicates low confinement; 0.4
0.9 indicates an extreme confinement
4.2. Choked Stratified Lagoon Example: Lagoa da Conceição, Brazil, latitude ≈ 27°3 S (Debenay et al., 1998; Figures 3 and 4).
Morphology The lagoon is elongated, about 13.5 km in length, with a total surface area of about 19 km2 (Knoppers et al., 1984; Muehe and Caruso-Gomes, 1989). It communicates with the sea via a narrow, 2 m deep and 2 km long channel (Odebrecht and Caruso-Gomes, 1987; Sierra de Ledo and Klingebiel, 1993). The lagoon is longitudinally divided into three zones, with a maximum water depth of about 8 m, and is separated by shallows and/or narrowings. The
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dunes extend into shallow sandbanks on the east side, while a deep channel is present on the west side (Figure 4).
Hydrodynamics The long and shallow entrance channel reduces water exchanges with the ocean, while fresh water enters the lagoon through runoff from the western granitic reliefs, the João Gualberto River discharge in the northern zone, and groundwater seepage from the sand dunes in the southern zone (Odebrecht and Caruso-Gomes, 1987). During the rainy season, the high freshwater input is responsible for strong water stratification, with brackish superficial water (≈18‰) and saline bottom waters (> 30‰) being trapped in the depressions and becoming anoxic. During the dry season, the stratification is weakened and the bottom waters can be renewed. Sediments The sediments in the depressions are organic-rich muds, while fine to medium grained sands, with numerous fragments of euryhaline Pelecypods, make up the sand banks.
Figure 4. Conceição Lagoon on Santa Catarina island. A. Horizontal distribution of the main foraminiferal species showing the dominance of agglutinated species on sand banks while hyaline species dominate in deeper areas; B. Vertical distribution of the main foraminiferal species showing the impact of the halocline on the dominant species. C. Distribution of Ic values with depth showing the impact of the halocline on foraminiferal assemblages (after Debenay et al., 1998)
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Foraminiferal Assemblages The density of tests in 50 cm3 of sediment (D50) varies from zero to 800 inside the lagoon, reaching 5000 in the outer part of the entrance channel. Thirty-three species are found. The assemblages reveal little horizontal change, except for a higher percentage of Miliammina (70%), which is under the direct influence of freshwater input. Vertically, they change abruptly at about the halocline: shallow sand banks (<1.5 m) are dominated by agglutinated species, mainly Ammotium salsum, which is associated with A. exiguus, Pseudoclavulina sp., G. exilis, and Miliammina earlandi. Depressions, on the other hand, are characterized by less restricted foraminiferal taxa, such as A. tepida and E. gunteri (Figure 4 A-B). This deeper microfauna only develops during periods of bottom water renewal (dry season), while only empty tests are found during anoxic conditions (rainy season). Pararotalia cananeiaensis, which is characteristic of a stronger marine influence, is found only in the outer part of the channel. The diagram of the Ic vs. depth clearly shows the distribution of the two assemblages, which are separated from each other at the depth corresponding to the halocline (Figure 4C). The Ic index, which is between 0.4 and 0.7 in most parts of the depressions, indicates a moderate confinement, while a strong confinement is suggested in the shallow areas. Stratification is also observed in the choked, hyposaline Ebrie Lagoon (Ivory Coast; Debenay et al., 1987). Ammotium salsum is the dominant species, and is associated with A. tepida near the entrance channel. A high proportion of Miliammina spp. occurs near the mouth of the main tributary. Neither foraminifera nor other microorganisms are found in the deep anoxic depressions.
4.3. Restricted Lagoon with Salt Wedge Example: Cananéia-Iguape Lagoon, Brazil, latitude ≈ 25° S (Eichler et al., 1995; Debenay et al., 1998; Figures 3 and 5)
Morphology The Cananéia-Iguape Lagoon is made up of channels that run parallel to the coastline and are separated from the sea by a sand spit, which is more than 70 km long. The study area in the south-eastern part of the lagoon consists of two channels that are 6 to 10 m deep (Mar de Cubatão and Mar de Cananéia), and are connected southwards with the Baia de Trapandé (10 m deep), which is wide open to the sea through a 13 m deep inlet (Figure 5). Mangroves are well developed on the edges of the lagoon. Hydrodynamics The characteristics of the mixohaline waters depend on sea-water inputs during semidiurnal microtidal tides (mean amplitude about 0.8 m) and seasonal cycles of freshwater input from small coastal rivers (Miyao et al., 1986). The resulting pattern is an inclined salinity gradient (salt wedge), which is related to gravitational circulation (Kjerfve, 1986; Kjerfve and Magill, 1989) (Figure 5B).
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Figure 5. Cananéia-Iguape Lagoon. A. Horizontal distribution of the main foraminiferal species showing changes from hyaline species near the inlet to agglutinated species landward. B. Distribution of salinity values with depth and distance to the sea showing the salt wedge. B. Distribution of Ic values with depth and distance to the sea where the influence of the salt wedge can be seen. Anomalous values of Ic are found in areas subjected to pollution (after Eichler et al., 1995; Debenay et al., 1998)
Sediments The sediments are mostly muddy sands, with mud in restricted areas, sand near the inlet where the tidal currents are stronger, and coarse sand and gravel in estuaries where there are strong currents during the rainy season. Foraminiferal Assemblages The density (D50) varies from 20 to 3000, reaching a maximum at Baia de Trapandé. The microfauna are comprised of about 100 species. Near the lagoon entrance, under marine influence, the assemblage is dominated by calcareous species, particularly P. cananeiaensis, which is associated with Brizalina striatula, E. gunteri, and Pseudononion atlanticum (Figure 5A). This assemblage progressively changes landwards, with an increasing proportion of agglutinated species, such as A. salsum and G. exilis, becoming dominant in restricted areas. In low salinity areas, the assemblages become oligospecific, with the M. earlandi predominating. The progressiveness in the transition means that it is not possible to subdivide the lagoon into clearly distinct zones.
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The Ic index increases progressively landwards, reflecting the gradual transition in foraminiferal assemblages. It increases more rapidly in the shallow waters (Ic D 0:4 about 10 km from the sea) than in the deep bottom waters of the channel (Ic D 0:4 about 18 km from the sea), revealing a weaker marine influence in the shallower areas in relation to the salt wedge (Figure 5C).
4.4. Choked Non-Stratified Hypersaline Lagoon Example: the Lagoon of Araruama, Brazil, latitude ≈ 23° S (Debenay et al., 2001, Figures 3 and 6)
Morphology The Lagoon of Araruama is one of the largest hypersaline lagoons in the world (Kjerfve et al., 1996). It is about 47 km long, with a surface area of 210 km2 and an additional 65 km2 of adjacent salt-producing ponds. Its average depth is about 3 m up to a maximum of 17 m. It has only limited water exchanges with the sea through a narrow and shallow entrance channel (less than 4 m deep) located at its eastern extremity. Sand spits, constructed by wind driven circulation cells, extend into sand banks and partially divide the lagoon into several basins. Hydrodynamics The deficit in the water balance: average rainfall ≈700 mm/y, average evaporation ≈1400 mm/y (Kjerfve et al., 1996), results in permanently hypersaline conditions. The mean salinity may exceed 65‰ (average 52‰; André et al., 1979), lowering only in the entrance channel and the eastern-most basin. In the salt-producing ponds it exceeds 100‰. Only two tributaries, located in the north-western part of the lagoon, have permanent runoffs. Other freshwater inputs result from rainfall, runoffs, small river occasional discharges, and domestic sewage, which are estimated to be 0.7 m3/s (Kjerfve et al., 1996). The increase in the superficial water density, which results from intense evaporation, induces mixing in the water column and prevents water stratification. The tidal range (0.8 m to 1.3 m in the open ocean) rapidly weakens in the lagoon, where it becomes negligible (14 km inside) (Lessa, 1990). The circulation processes are dominated by clockwise wind driven circulation cells. Sediments The input of fluvial sediments is noticeable in the western part of the lagoon where fine organic rich sediments accumulate (Azevedo, 1984; Barroso, 1987). The finest sediments, which are comprised of up to 98% of silt and clay, are mainly present in the deepest, central part of the lagoon and in the shallow, eastern-most lagoon cell. They are black and reduced, except for a thin surface layer. The sediments of the shallower northern and southern parts of the lagoon are shelly sands with a thick oxidized layer. The western-most lagoon cell often has accumulations of organic remains (plant fragments, dead fish or various domestic effluents). The maximum concentrations of organic carbon, phosphorus, and nitrogen are found near to human activities (Campos et al., 1979; Debenay et al., 2001).
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Figure 6. Araruama Lagoon. The dominance of Ammonia tepida is related to enrichment in anthropogenic nutrients along the northern shore and eastern part of the lagoon assemblages (after Debenay et al., 2001)
Foraminiferal Assemblages The density (D50) varies from 50 to about 50,000 inside the lagoon, reaching 500,000 in adjacent areas. A total of seventy-four species are found, with the species richness of the samples ranging between 5 and 27. Very few specimens were alive. The D50 is highest along the northern coast and in the central part of the lagoon, while it is less than 1000 near to the main urban areas, Araruama City and Cabo Frio. In the entire lagoon, the assemblages are dominated by three species: A. tepida, Q. seminula (first identified as Triloculina oblonga) and the less abundant Cribroelphidium excavatum var. selseyense. Ammonia tepida is dominant (50%-92% of the assemblages) along the northern shore and at the eastern end of the lagoon, while Q. seminula is dominant at the other stations (Figure 6). This has been attributed to the input of wastewaters and the enrichment in anthropogenic nutrients along the northern shore and eastern part of the lagoon. Only a few species that are indicative of marine influence are present in the outermost stations of the entrance channel (e.g. Eponides repandus, Discorbinella bertheloti, Pseudononion atlanticum, Quinqueloculina lamarckiana and P. cananeiaensis). In adjacent areas, Q. seminula is frequently dominant, and is associated with A. tepida and species that are absent or rare in the lagoon, such as Discorinopsis aguayoi. Textulariidae are nearly absent, even in the hyposaline estuaries of the tributaries. No correlation was observed between the abundance of common species and any of the sedimentary parameters. The Ic index is about 0.5 in almost the entire lagoon, except near the entrance and in the estuaries of the tributaries.
4.5. Restricted, Non-Stratified Lagoon, with Roughly Normal Saline Waters Example: Gulf of Kalloni, Lesvos Island, Greece, latitude ≈ 39°05‘ N, longitude ≈ 26°10‘ E (Debenay et al., 2005; Figures 3 and 7)
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Morphology The Gulf of Kalloni is essentially a lagoon that is about 20 km long, with a surface area of about 130 km2. It communicates with the sea through a narrow inlet, which is less than 2 km wide, at its south-western end. The depth of about 25 m at the inlet decreases steadily north-eastwards, while the gulf progressively widens, ending up in a wider and shallower north-eastern part. Hydrodynamics During the dry season (May-September), weak freshwater input and strong wind-induced evaporation lead to higher salinity (38‰) in the north-eastern end of the gulf. During the rainy season (October-April), freshwater input from small intermittent rivers lowers the salinity, the seasonal range being about 5‰ (Lefebvre, 1993). No vertical salinity stratification was observed, other than temporary stratification during strong rainfalls. According to Kjerfve and Magill (1989), the horizontal salinity gradient demonstrates that the flushing rate is relatively long in the north-eastern part of the gulf. Water exchange with the Aegean Sea depends on tidal flow (maximum tidal range of 23 cm) and wind-forced currents (Millet and Lamy, 2002; Debenay et al., 2005). When northern winds dominate (June to September), the marine waters penetrate through the central part of the gulf, reaching its north-east end in less than five days; the ebb tidal flow moves along the shores. In contrast, when the southern winds blow (October to March), the marine waters penetrate along the shores, particularly the southern shore. The seawards ebb tidal flow moves through the central part of the gulf. North-westerly and south-easterly winds, which only blow for limited periods, induce clockwise gyratory currents that limit the inflow of marine water to the south-western part of the gulf and enhance the confinement in the northeastern part (Millet and Lamy, 2002). Sediments The bottom sediments are sand, muddy sand or sandy mud, with a greater proportion of mud (up to 93%) in the low energy, deepest areas. These are mostly of terrigenous origin, with a greater contribution of carbonate biogenic production in the shallower sandy areas. They are enriched in organic matter near a fish farm and a small town to the south. The concentration of Cu is low in most of the gulf (around 14 ng/g), revealing the absence of noticeable chemical contamination, except in the vicinity of the town of Skala Kalloni (53 ng/g) (Angelidis et al., 2001). Foraminiferal Assemblages The density (D50) varies from 160 to about 40,000, with the maximum being near the inlet. The lower values are in the central axis of the gulf and in two areas of high organic input near a fish farm and a town. A total of 147 species is found, which is quite high compared to the shallow choked lagoons of the western Mediterranean (69 in the Thau Lagoon, France (Kurk, 1961) and 47 in the Prévost Lagoon, France) (Favry et al., 1998), but considerably lower than in Mediterranean open gulfs: 222 species in the Gulf of Policastro, Italy (Sgarrella et al., 1985) and 366 in the Gulf of Naples (Sgarrella and Moncharmont-Zei, 1993). With respect to foraminiferal assemblages, the Gulf of Kalloni has an intermediate position between choked lagoons and the gulfs that are wide open to the sea. The species
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richness ranges between 11 and 81, with decreasing values from the inlet towards the northeastern end of the gulf and from the shores towards the deeper, central part. The six dominant species are Haynesina sp., Aubignyna planidorso, A. beccarii, A. tepida, Porosononion granosum and Nonionella turgida. Ammonia tepida and Haynesina sp. achieve their maximum relative abundances in the north-eastern part of the gulf and in the two areas of high organic input. A. planidorso and P. granosum reach their highest relative abundance along the central axis of the gulf, where water energy is lower in the depression of the southern axial zone, and in the centre of the gyratory currents affecting the north-eastern part of the gulf. The lower density and species richness in the two areas of high organic input may result from low-oxygen stress. At these two stations the dominant species A. tepida and Haynesina sp. Owing to the weak freshwater influence, the agglutinated species used for calculating the Ic in previous studies are extremely rare or are not found in the Gulf of Kalloni The distribution of the Ic reflects the decreasing marine influence north-eastwards; values are higher than 6.5 in the north-eastern part of the gulf (Figure 7), indicating more restricted conditions. The values of the Ic are also high in the two areas of high organic input, highlighting that organic matter accumulation can have the same impact on this index as decreasing marine influence does.
Figure 7. Gulf of Kalloni. Values indicated on this figure were measured in September 1993. The Ic values show increasing confinement with distance to the sea and the impact of both the fish farm and the town of Skala Polychnitos. The density of foraminiferal assemblages shows a decrease with increasing distance to the sea, mainly in the central part of the gulf. The species diversity is higher along the southeastern shore of the lagoon indicating the penetration of marine water along the shore during most of the year (after Debenay et al., 2005)
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4.6. Choked Hyposaline Lagoon Example: Lake Nokoué, Bénin, latitude ≈ 6°26‘ N, longitude ≈ 2°27‘ E (Debenay et al., 1993; Figures. 3 and 8)
Morphology This coastal lagoon extends over about 160 km2 (20 km long from west to east). It is closed by a sand spit, which is about 5 km wide, and is directly connected to the sea via a narrow channel through Cotonou. Another connection to the sea exists to the east of the lagoon, through a channel and the lagoons of Nigeria. The Cotonou channel can close during low-water periods. The south coast is sandy while the north coast, where the main tributaries flow into the lagoon, is marshy. The lagoon is shallow (<3 m) except near the entrance channel (9 m). Hydrodynamics The main water circulation pattern is a general clockwise, wind driven current around the lagoon, with several smaller circulation cells (Colleuil, 1984; Millet et al., 1991). Tidal currents are sensitive only during low water periods, and are mainly located near the entrance channel. Freshwater inputs are generally produced by rain and runoffs during the great rainy season (March - July) and by the main tributary, the Oueme River, during the small rainy season (September – November). When the Oueme River is in spate (September – December), almost the entire lagoon is filled with fresh water, with a salinity of about 0.2‰. At the beginning of the low water period, oceanic waters penetrate the lagoon through the Cotonou channel and are pushed westwards by the clockwise current, inducing a west-east zonation. Maximum salinity can then reach 33‰. Later, the entrance channel closes naturally, due to long-shore sediment input, and the salinity lowers, with a gradient from 10‰ (west) to 5‰ (east). No vertical water stratification was observed. Sediments The sediments are of terrigenous origin, and are typically organic rich muds, with some sand banks deposited by the wind driven currents. Foraminiferal Assemblages The foraminiferal assemblages collected in Lake Nokoué are poor and dominated by the euryhaline A. salsum. However, near the Cotonou channel, and under oceanic influence, they are more diversified, with A. parkinsoniana, A. tepida and E. gunteri present. The samples collected from the organic-rich-sediment in the estuaries of the tributaries contain A. mexicana and H. wilberti, while the brackish eastern area contains M. earlandi and M. fusca. The distribution of the confinement index, the Ic, fit well with the hydrological characteristics of the area (Figure 8). Values lower than 0.4 are limited to the vicinity of the Cotonou channel, highlighting the weakness of the marine influence. Both the westwards extension of the area, where the Ic is less than 0.7, and its north-eastern extension are the result of the combined effects of: i) freshwater input from the Ouémé River; and ii) the clockwise rotation of the water masses. The south-eastern extension of this area is probably due to the influence of the eastern channel.
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Figure 8. Lake Nokoué. The distribution of the confinement index Ic is related to the input of marine water through the entrance channel and to the circulation of these waters pushed by wind-forced currents assemblages (after Debenay et al., 1993)
4.7. Generalization Living at the bottom of areas of water, benthic foraminifera are subjected to all kinds of changes in the characteristics of water masses, ranging from the scale of the tidal to seasonal cycles. They therefore represent the average conditions prevailing at the site of sampling, which is of primary interest in these highly changing environments. The selected examples of coastal clastic lagoons reveal that the main distribution pattern of foraminiferal assemblages is primarily related to the balance between marine and continental influence, thus reflecting the various water masses. The sensitivity of foraminifera is such that they can indicate the influence of salt wedges, such as in the Cananéia-Iguape Lagoon. The impact of marine water has often been emphasized in the literature, and a good example is the Santo André coastal lagoon, where Cearreta et al. (2002) reported that the absolute abundance of foraminiferal assemblages greatly increases when the inlet periodically opens. Salinity certainly plays a prominent role in the impact of the balance between marine and continental water masses, as is attested to by the presence of foraminifera in inland saline lakes. The selected examples also reveal that the gradient of marine influence is not necessarily a direct function of the distance to the inlet, and that this primary distributional pattern may be complicated by secondary parameters, such as water stratification. Consequently, a simple horizontal mapping of foraminiferal assemblages has no significance in a stratified lagoon, such as the Lagoa da Conceiçao, and could lead to misinterpretations. In areas of almost stable salinity, the assemblages are controlled by secondary parameters, which are no longer obscured by the marine/continental balance. In the Araruama Lagoon, for example, local conditions, such as anthropogenic inputs, clearly affect the foraminiferal assemblages. Albani (1978) reported the same phenomenon in estuarine environments, where assemblages reflected the marine and fluvial water masses in areas of
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variable conditions, while in areas of more stable salinity the major parameters became water depth and tidal activity. In the study examples, no clear relationship could be established between foraminiferal assemblages and the nature of the sediment. However, such a link could be evidenced in Lake lllawarra, Australia (Yassini and Jones, 1989), and in the Bassin d'Arcachon, a restricted lagoon on the Atlantic coast of France, where Le Campion (1970) recognized a number of sub-environments with different foraminiferal assemblages related to the nature of the sediment. Generally, muddier sediments, usually accompanied by higher nutrient conditions, tend to contain a greater density of foraminifera than sandier sediments, as seen in the Gippsland Lakes, Australia (Apthorpe, 1980) and the Goro Lagoon, Italy (Coccioni, 2000). The agglutinated species collected in the selected lagoons are always related to low salinity and are always associated with low pH conditions. However, when considering these species and their significance for environmental conditions, it is necessary to make the distinction between organic-cemented species, which mainly live in low salinity and low pH conditions, and calcite-cemented species, which are abundant in fully marine reefal environments and coral reef lagoons. The species that lives in the less saline areas is M. fusca, and is always found near fluvial input sites. This species is often reported to be present in the same type of environments and also seems to prefer the quieter conditions prevailing in shallow, subtidal sheltered waters (Lewis, 2006). The great variety of lagoonal functioning illustrated by the selected examples reveals that it is impossible to establish a universal model for foraminiferal distribution in lagoons. However, these assemblages may be used as a key indicator in lagoonal environments, either for understanding the functioning of the lagoon, as was the case in Lagoa da Conceiçao (Debenay et al., 1998), or for exploring the favourable, average conditions for man‘s activity, such as aquaculture. For example, it was demonstrated in the Nokoue Lagoon that the distribution of the confinement index, the Ic, fits well with macrobenthic zonation (Debenay et al., 1993). The Ic index is also a powerful tool for comparing various lagoonal environments and other paralic habitats, typically estuaries. Moreover, the Ic also gives a helpful indication of organic matter input and serves as a useful tool for a quick characterization of the environment, including the detection of any anthropogenic impact.
5. USING FORAMINIFERA FOR ASSESSING WATER AND SEDIMENT QUALITY IN LAGOONS 5.1. Use of Foraminifera Coastal areas have traditionally been places of human settlement, with the accompanying development of cities, industries and other human-related activities possibly having an impact on aquatic ecosystems and modifying their health quality and local biota. Although humaninduced disturbances may take many forms, the most deleterious impact typically occurs in paralic environments, where the effects generally overlap with the stress conditions which tend to be induced by drastic changes in water characteristics. At present, there is clearly an increasing need to monitor the ecosystem response to different types of disturbance. Despite the complex interplay of natural vs. anthropogenic induced stress, biological organisms like
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foraminifera can be used to provide an early warning of the presence or absence of pollution (biological monitoring). Like the biotic indices that have already been developed for macrofaunal organisms, foraminiferal monitoring procedures are also beginning to be formalized, and considerable effort has been made to develop new methodologies for the biological monitoring of different contaminants. Moreover, because of our increased knowledge of the biology of foraminifera, it is clear that benthic foraminifera have great potential as indicators of stress, thereby providing one of the most sensitive and inexpensive markers of environmental strain in both naturally and anthropogenically stressed locations (Murray and Alve, 2002). Benthic foraminifera generally respond to adverse ecological conditions, mainly by undergoing: i) local extinctions; ii) compositional biocenosis changes; iii) assemblage modifications, which include changes in abundance and diversity; iv) dwarfism (Lilliput effect); v) prolocular morphology; vi) reproduction capability; and vii) the development of test abnormalities (e.g. Alve 1991, 1995; Yanko et al., 1994; Geslin, 1999; Frontalini et al., 2009). Over the last few years, many studies of benthic foraminiferal assemblages have been carried out in different parts of the world in areas exposed to different kinds of marine pollution, which has generally included a) increased organic matter, b) hydrocarbons-oil and c) trace elements.
5.2. The Effect of Organic Matter on Benthic Foraminifera The input of organic matter has deleterious effects on marine ecosystems and their benthic community by inducing high nutrient levels which can ultimately lead to oxygen deficiency. The influence of organic material on the benthic community is not only controlled by its quantity, but also by its quality. Although organic matter is composed of a wide range of compounds, it can be divided into two main groups. The first includes the material that is more easily biodegradable and ―naturally‖ produced. This encompasses organic compounds from agriculture (e.g. fertilizers) and aquaculture, as well as domestic sewage, which is readily metabolized by marine organisms. In contrast, the effluents of pulp/paper mills, which are composed primarily of cellulose, lignin and other wood fibers, are rather resistant and difficult to metabolize. According to Alve (1995), the increase in organic matter from both sources in the socalled defined ―hyper-trophic‖ zone may stimulate the growth of large populations of benthic foraminifera. However, an excess of organic material may negatively influence the benthic community. In fact, most studies have revealed that around areas of organic matter supply (e.g. outfall and pipe), an abiotic zone might occur in response to the development of anoxic conditions. Changes in density are not the only response by benthic foraminifera to organic matter, with a lowering in species diversification also being documented in the vicinity of many outfalls (e.g. Resig, 1960; Schafer, 1973). Although the Index of confinement (Ic) is used to define a marine-to-confined water gradient, it can be also utilized to unravel the influence of freshwater discharges and detect anthropogenic impact (Debenay et al., 1998, 2005). This is the case in the Cananéia-Iguape Lagoon, which exhibits salinity gradients due to the mixing of freshwater input from local
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rivers with marine waters, and where anomalous values of the Ic and the dominance of Miliammina spp., in correspondence with freshwater input, have been documented by Debenay et al. (1998). Although the environmental quality of the Gulf of Kalloni has been reported as good, higher organic matter contents have been noted in the vicinity of a fish farm and in correspondence to the town of Skala Polychnitos (Figure 7). This is due to local pollution sources, which include urban effluents and agricultural land runoffs (Panayotidis et al., 1999). The enhanced organic matter input appears to be responsible for a lowering in density and species diversity as well as a higher Ic index and abundances of A. tepida and Haynesina sp. (Debenay et al., 2005). In the hypersaline Lagoon of Araruama, the strong contrast of foraminiferal assemblage distributions between the north-eastern part of the lagoon, which is dominated by A. tepida, and the southern part, where T. oblonga dominates (Figure 6), has been related to organic-rich wastewater input along the north-eastern coast of the lagoon (Debenay et al., 2001). Ammonia tepida has usually been found in shallow marine environments, lagoons and deltaic zones (Jorissen, 1988; Almogi-Labin et al., 1992; Coccioni, 2000; Abu-Zied et al., 2007; Frontalini et al., 2009), and is known for its great tolerance to chemical and thermal pollution, fertilizing products, and hydrocarbons (e.g. Yanko and Flexer, 1991; Coccioni, 2000). It was even capable of supporting very polluted environments and high concentrations of trace elements (e.g. Ferraro et al., 2006). Yanko et al. (1994) found that megalospheric forms of A. tepida were dominant at stations where toxic trace metal pollution was prevalent. Similarly, H. germanica has been regarded by Stubbles (1993) and Armynot du Châtelet et al. (2004) as a species that is tolerant to pollution, and its increasing dominance is an indicator of stressed environmental conditions. Enrichments of organic matters have also been considered to be responsible for increasing the proportions of abnormal tests (FAI). In particular, in shrimp ponds in New Caledonia, Debenay et al. (2009a) documented a strongly positive correlation between the FAI and (1) the quantity of easily oxidized material (EOM) deposited at the bottom of the ponds, and (2) the sediment oxygen demand. This is corroborated by the poorly diversified assemblages that are mainly dominated by A. tepida and Q. seminula, indicating very restricted conditions and major environmental stress. It has also been suggested that a very high FAI could be a potential indicator of great accumulations of native organic matter, leading to a high sediment oxygen demand. In their multi-proxy study on intertidal estuaries in New Zealand, Hayward et al. (2004, 2006) found that stepwise shifts in dominance from calcareous to agglutinated forms, which are usually related to increasing continental influence, were also associated with the arrival and establishment in the area of humans. These major faunal changes probably resulted from the increased freshwater runoffs associated with forest clearance and an increase of nutrient inputs. Clear foraminiferal faunal zones have been documented by Takata et al. (2006) in the organic-rich brackish-water Lagoon of Saroma (Japan). This faunal distribution appears to be controlled by the dissolved oxygen content of the bottom water and a combination of organic enrichment and mud content in the substrate in front of river mouths. In particular, these authors reported a river-mouth fauna dominated by Elphidium excavatum, which is probably adapted to organic-rich sediment. Previous studies have reported the presence of E. excavatum in highly organic substrates; Schafer (1973) noted that the Elphidium incertum/Elphidium clavatum Group (probably related to E. excavatum) was particularly abundant around sewage outfalls in Chaleur Bay, Canada, while Alve and Murray (1999) inferred that E. excavatum can live in substrates characterized by highly variable grain size
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and TOC content. Major changes in foraminiferal assemblages over both time and space have also been reported in the Osaka Bay (which can be regarded as a restricted lagoon) by Tsujimoto et al. (2006a, b). Using living foraminiferal assemblages, these researchers documented an inner area of the bay which was mainly related to eutrophication and dominated by agglutinated forms (Trochammina hadai and Eggerella advena). Moreover, they also highlighted marked foraminiferal assemblages present over the past 50 years, where the dominance of agglutinants, which was linked to the increase of eutrophication from the 1960s to the 1970s, was followed by a decrease of these forms in response to the imposition of improved environmental regulations. A similar approach has been used in the northern sector of the Lagoon of Venice by Albani et al. (2007), who compared foraminiferal assemblages from samples collected in 1983 and 2001, thus documenting unchanged conditions for 50% of the lagoon. On the basis of these results, these authors have been able to document both the effectiveness of the purification plant, which has been operating since 1980s, and improvements in the water quality in the area near Porto Marghera.
5.3. The Effect of Hydrocarbon-Oil on Benthic Foraminifera The effect of hydrocarbons on benthic foraminiferal assemblages in field and experimental studies has been the subject of only a few papers (e.g. Vénec-Peyre, 1981; Yanko et al., 1994; Alve, 1995; Bernhard et al., 2001; Morvan et al., 2004; Ernst et al., 2006; Sabean et al., 2009). Increased mortality and abnormality and decreased density and diversity are among the effects on benthic foraminiferal assemblages induced by hydrocarbon pollution. In particular, and in order to address the response of benthic foraminifera to pollution as a result of the ―Erika‖ oil spill, Morvan et al. (2004) evaluated a site situated on the tidal mudflat along the southern Bay of Bourgneuf (France) at monthly/bimonthly intervals. Although a clear link between FAI and oil pollution was not found, impoverished fauna in terms of density and species richness was highlighted, confirming the potential sensitivity of foraminifera to this pollutant, and suggesting a direct impact either by the oil spill itself or by the strong disturbance of the environment resulting from cleaning activities.
5.4. The Effect of Trace Elements on Benthic Foraminifera Although most trace elements are biologically essential at very low concentrations, they become potentially toxic to marine and estuarine organisms above a specific threshold (Kennish, 1992). Over the last four decades, many studies from different environmental settings have focused on the response of benthic foraminifera to pollution by trace elements (Alve, 1991, 1995; Sharifi et al., 1991; Yanko et al., 1994 1998, 1999; Coccioni, 2000; Geslin et al., 2000, 2002; Samir, 2000; Samir and El-Din, 2001; Elberling et al., 2003; Armynot du Châtelet et al., 2004; Coccioni et al., 2003, 2005, 2009; Coccioni and Marsili, 2005; Ferraro et al., 2006; Frontalini and Coccioni, 2008; Frontalini et al., 2009, 2010). Most of these studies documented a lowering in species diversity and density, and a high incidence of abnormality, megalospheric and dwarfed forms, and changes in assemblage composition.
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The benthic foraminiferal response to trace element pollution was investigated by Samir (2000) in two Egyptian Nile Delta lagoons (Manzalah and Edku). The high level of pollution reported in the Manzalah was believed to be lethal to foraminifera and, indeed, only one species of Ostracoda (Cyprideis torosa) was found to be able to survive in this environment. On the other hand, the Edku Lagoon, which had trace element concentrations close to the natural baseline level, yielded living foraminifera. On the basis of total assemblages, the Manzalah Lagoon exhibited lower foraminiferal diversification and higher percentages of both megalospheric forms of A. tepida and abnormality. A similar response, in terms of very impoverished foraminiferal assemblages, has been documented in different Italian lagoons (e.g. Santa Gilla, Venice, Orbetello and Lesina) by Frontalini et al. (2009, 2010) and Coccioni et al. (2009). In particular, reduced foraminiferal diversification and high percentages of abnormal forms have been reported close to the most polluted industrial zone of Porto Marghera (Coccioni et al., 2009). The same authors reported a biocenosis (living assemblages) dominated by A. tepida, H. germanica and E. oceanensis. These assemblages are comparable to the Ammonia associations with H. germanica that are characteristic of lagoons along the Mediterranean coast (see Murray, 1991, 2006). High concentrations of trace elements (e.g. Hg values up to 10 times higher than the background level) were found in the Santa Gilla lagoon, the innermost part of which is comprised of the industrial complex at Macchiareddu. Indeed, the trace element concentration values were generally higher than the USEPA ER–L and ER-M levels (Frontalini et al., 2009). The same authors documented an oligotipic assemblage and the occurrence of abnormalities, particularly in the innermost part of the lagoon, testifying to an important chemical stress in this area. In contrast, higher diversity values and lower percentages of abnormalities were recognized in the outermost part, which is probably favoured by faster water renewal and the reduced influence of urban discharge. This reflects a limited influence of trace element concentrations in the sediment. On the basis of trace element analysis of the biogenic carbonate of porcelanaceous foraminifera, Frontalini et al. (2009) also found higher concentrations than those reported in unpolluted environments. The same results were achieved by Madkour and Youssef Ali (2008), who found high concentrations of Fe and Mn in benthic foraminiferal tests from several Egyptian Red Sea lagoons (e.g. Umm al-Huwayat).
7. CONCLUSION Lagoons, like other transitional marine environments, are areas where biological, chemical, and physical processes overlap over both time and space. Our understanding of them might be improved by knowledge of the behaviour of the organisms evolving and living in these complex systems. Benthic foraminifera are highly suitable and sensitive biological organisms through which our comprehension of lagoon environments can be further explored. Since the early 1900s, plenty of studies have documented the ability of benthic foraminifera to synthetically reflect a great variety of complex processes. Despite of the general conditions are complicated by a complex interplay of an array of parameters in lagoon environments, this work highlights that foraminiferal assemblages are distributed along major gradients (i.e., salinity). Benthic foraminifera have been also proven to be particularly sensitive
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microrganisms and they have been successfully utilized for their value as bio-indicators of environmental change in a wide range of marine environments including lagoon ecosystems. In this context, the ―Confinement Index‖ gives a helpful indication of organic matter input and serves as a useful tool for a quick characterization of the environment, including the detection of any anthropogenic impact. Although the separation of natural and anthropogenically-induced stress is sometimes hampered by environmental complexity, benthic foraminifera are ideal and reliable candidate for environmental monitoring program and management of lagoonal ecosystems.
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 73-117 © 2011 Nova Science Publishers, Inc.
Chapter 3
COASTWEB, A FOODWEB MODEL BASED ON FUNCTIONAL GROUPS FOR COASTAL AREAS INCLUDING A MASS-BALANCE MODEL FOR PHOSPHORUS Lars Håkanson* and Dan Lindgren Department of Earth Sciences, Uppsala University, Uppsala, Sweden
ABSTRACT It is important to develop tools to get realistic predictions of how, e.g., the loading of contaminants and future climate changes may affect the structure and function of aquatic ecosystems. The CoastWeb-model presented in this work in meant as such a tool. CoastWeb is a process-based mechanistic foodweb model for coastal areas (the ecosystem scale) and includes a mass-balance model (CoastMab) for phosphorus. The model is based on ordinary differential equations and gives monthly calculations of production and biomasses for ten functional groups (phytoplankton, benthic algae, macrophytes, bacterioplankton, herbivorous and predatory zooplankton, zoobenthos, jellyfish, prey and predatory fish). CoastMab calculates in- and outflow, sedimentation, diffusion, resuspension, up- and downward mixing, biouptake and retention of phosphorus in biota. There are algorithms for, e.g., migration of fish and plankton between the given coastal area and the sea and the influence of exposure on macrophyte cover . The paper presents case-studies on eutrophication, overfishing and toxic contamination illustrating the potential of CoastWeb as a tool for sustainable coastal management. Increased nutrient loading will cause several changes to the foodweb characteristics of the studied coastal area. Some of these could be expected without a model, but here they have been quantified using a general foodweb model. The model accounts for different compensatory effects that are difficult to quantify without a model. The case-study on overfishing indicates that increased fishing will likely affect the studied coastal system marginally because the migration of fish from the sea is large in the studied coastal area. The case-study on toxic contamination shows that a reduction of *
Corresponding author: Email: [email protected]., tel: +46 184713897; fax: +46 184712737.
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Lars Håkanson and Dan Lindgren zoobenthos biomass will have clear effects of fish production and biomass in the studied coastal area.
Keywords: coastal areas, eutrophication, foodweb modelling, functional groups, massbalance modelling, overfishing, phosphorus, toxic contamination, climate change
INTRODUCTION At any modelling scale, the complexity of natural ecosystems always exceeds the complexity and size of any model, so simplifications are always needed. The ultimate goal in achieving predictive power and general validity for a model is to find the most appropriate simplifications (Monte, 1995, 1996; Monte et al., 1999; Peters, 1991). Different models for biota focus on different targets and scales. Fundamentally different approaches may be used in, e.g., physiological models, models for individual species and models for functional groups, approaches using different time scales (hours to years), different spatial scales (from sites to ecosystems), different driving variables (climatological data or map parameters) and approaches using statistical methods or models based on ordinary differential equations (box models) or partial differential equations (2- or 3-dimensional models), see Monte (1996), Mace (2001). The CoastWeb-model presented in this work is meant as a tool for coastal sciences and management to study how changes in nutrient inflow, fishing, water temperature and contamination by toxins could influence the structure and function of coastal ecosystems. CoastWeb is basically a combination of a foodweb model for lakes (LakeWeb, Håkanson and Boulion, 2002), a process-based dynamic mass-balance model for phosphorus (CoastMab, Håkanson and Eklund, 2007) and several adjustments needed to bring these two models together into a comprehensive unit. An important feature of this model, and a pre-requisite for its practical use, is that it can be run by a few driving variables readily accessible from standard maps and monitoring programs. CoastWeb is based on ordinary differential equations, works at the ecosystem scale and gives monthly predictions, but it does not address the finer details related to individual species or changes among sites within coastal systems. LakeWeb, has been positively tested against comprehensive empirical data for lakes and by sensitivity and uncertainty analyses (Håkanson and Boulion, 2002). LakeWeb was used for the Baltic Sea as a tool to set fish quotas (Håkanson and Gyllenhammar, 2005) by calculating the fish production potential and how it depends on environmental conditions (salinity, temperature and phosphorus loading) as well as on fishing and overfishing. Håkanson and Gyllenhammar (2005) compared LakeWeb with other models, e.g., Ecopath/Ecosim (Christensen et al., 2000; Walters et al., 1997, 2000; Sandberg et al., 2000; Harvey et al., 2003) and that comparison will not be repeated here. However, it should be stressed that CoastWeb provides a new dimension to understand and simulate the factors regulating aquatic ecosystem structure, including the fish production. Ecopath/Ecosim and CoastWeb/LakeWeb are complementary and both can calculate production and biomasses, but CoastWeb/LakeWeb has a separate sub-model to calculate inflow, outflow and internal processes (sedimentation, resuspension, etc.) of nutrients so that the nutrient concentration can be related to the nutrient loading and used to
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calculate chlorophyll (phytoplankton biomass). Ecopath/Ecosim is designed to handle more detailed foodweb interactions than CoastWeb/LakeWeb. Most of the algorithms used in the mass-balance model for phosphorus (CoastMab) have been critically tested and shown to predict well, but only for coastal areas within a fairly limited salinity range. It would be very interesting to test CoastWeb/CoastMab for more saline systems, e.g., in the Mediterranean, along the Atlantic coast or in the Black Sea. The case-studies presented here merely illustrate the potential use of this modelling related to eutrophication, toxic contamination and overfishing – each case-study could easily grow into a large book. So, this paper is ―not the end, nor the beginning of the end, but rather the end of the beginning‖.
Figure 1. Illustration of the steps to define the boundary lines of a coastal area (step 1) at the topographical bottlenecks defined by the ratio between the section area (At) and the enclosed coastal area (A) where the exposure (Ex) attains a minimum value. Once the boundary lines for the coastal area are defined, steps 2 and 3 illustrate how to calculate important coastal parameters (such as morphometric size, form and special parameters, the theoretical surface and deep water retention times and where areas of fine sediment accumulation prevails)
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Lars Håkanson and Dan Lindgren The text has been divided into the following parts: First, the basic structure of the foodweb model is described, including the approach to define the geographical boundary conditions for coastal areas, the approach to define ―normal‖ biomasses for the functional groups, migration into and out from coastal areas and an outline of the new sub-model for jellyfish. Then, there is a section related to the different roles of macrophytes in coastal systems and how these roles and functions can be modelled using CoastWeb. The third main part gives results related to the three case-studies and how CoastWeb may be used as a tool to analyse how very complicated and important environmental problems may be handled in a structured and quantitative manner. The appendix gives a list of minor modifications done to transform the lake model into a model for coastal areas.
METHODS – THE MODELLING APPROACH Coastal Ecosystem Boundaries It is easy to define what a lake is or a stretch of river. It is more difficult to draw the borderlines toward the sea and/or adjacent coast to define a given coastal area. The positions of such borders are essential for mass-balance calculations since arbitrary borderlines generate arbitrary volumes, which reduce the predictive power of the mass-balance model (Håkanson, 1999). CoastWeb requires that the coastal area is defined according to the topographical bottleneck approach (Figure 1). The boundaries should be drawn at the topographical bottlenecks using Geographical Information Systems (GIS) techniques so that the exposure (Ex = 100·At/A) attains a minimum value when different alternatives for defining the boundary lines are tested (At = section area; A = enclosed coastal area; Pilesjö et al., 1991). Once the coastal area is defined, other key variables for mass-balance calculations may also be defined, such as the water volume. This method also makes it possible to use simple models to estimate the theoretical surface-water retention time (Persson et al., 1994), the deep-water exchange (Håkanson and Karlsson, 2004) and the bottom dynamic conditions (Håkanson, 2006) from morphometrical parameters. Such simple models are important since establishing an empirical value of the theoretical water retention time from field measurements can be costly. CoastWeb may be used for the main coast types, tidal coasts, open coasts, archipelago coasts and bays (Håkanson, 2000).
The Foodweb Model The main aim of the LakeWeb-model is to quantitatively describe characteristic foodweb interactions so that production, biomasses and predation can be determined for the functional groups in the model: the three primary producers, phytoplankton, benthic algae and macrophytes, the five secondary producers, herbivorous zooplankton, predatory zooplankton, zoobenthos, prey fish and predatory fish, and one decomposer, bacterioplankton. Jellyfish is
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added as a functional group to adapt the model to coastal conditions. The group ―predatory fish‖ does the work of eating ―prey fish‖, which in turn eats zooplankton (herbivorous and predatory) and zoobenthos. Other organisms, like benthic bacteria and fungi are not treated individually but are included in the flux called ―zoobenthos production from other sediment sources‖. Such simplifications are necessary to keep the model as small as possible, to keep the driving variables as few and as accessible as possible and to be able to critically test the model using empirical data. The idea is not to include everything, but to focus on key functional groups and fundamental abiotic/biotic relationships (see Figure 2 for an overview of the LakeWeb model). CoastWeb is meant to cover a wide range in temperature, water basin morphometry, trophic state and salinity. Since the model can be run from few and readily accessible driving variables (see Table 1), it is evident that the aim is to model general conditions. This modelling is intended to handle feedbacks among the functional groups, but biotic/abiotic feedbacks also are included. Table 1. Data needed to run the CoastWeb-model for the studied coastal areas (data from Wallin et al., 1992 and Håkanson et al., 2007). The water exchange between Ringkobing Fjord and the sea is regulated by a sluice Area
Country
Lati- Water CatchDmax Dm At Chl SalCaCTP Sec tude area ment area inity conc. # (°N) (km2) (km2) (m) (m) (km2) (µg/l) (mg/l) (µg/l) (m) Ringkobing Denmark 56 300 3 500 5.1 1.9 sluice 52/9,1* 7.8/9.6 30 130/56 0.6/1.6 Ronneby S. Swed. 56 11.0 633 17.6 4.3 0.0176 2.1 6.5 25 21 4 Gräsmarö C. Swed. 58 13.8 0 46.9 14 0.0825 2.6 6.6 15 17 4.3 Haverö Finland 61 2.3 0 22.5 8.6 0.0172 2.1 6.5 15 27 3.4 Gävle N. Swed. 61 17.1 2 600 17.0 8.4 0.0063 3.5 4.2 9 23 3.6
Dmax = maximum depth; Dm = mean depth; At = section area; Chl = concentration of chlorophyll-a; CTP = TP-concentration; Sec = Secchi depth; *) mean values from all existing data 1990/93 and 2000/2003, respectively; #) estimated values Predatory fish
Secondary producers
Prey fish
Jellyfish Predatory zooplankton
Zoobenthos Herbivorous zooplankton Sediments Benthic algae Macrophytes
Primary producers
Phytoplankton
Bacterioplankton
Decomposer Figure 2. Illustration of a coastal foodweb including ten groups of organisms (phytoplankton, bacterioplankton, benthic algae, macrophytes, herbivorous zooplankton, predatory zooplankton, jellyfish, zoobenthos, prey fish and predatory fish)
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Figure 3. Illustration of general and fundamental transport processes to, within and from coastal systems used in the mass-balance model for phosphorus in the CoastWeb-model. ―ET-sediments‖ in the figure refer to erosion and transportation areas where fine sediments and particulate forms of nutrients are resuspended. ―Active A-sediments‖ are biologically active sediment areas where fine sediments are continuously being deposited (accumulation areas)
Mass-balance modelling of nutrients is important in aquatic ecology (Vollenweider, 1968; OECD, 1982) and by including a mass-balance model for nutrients in the foodweb model, it is possible to calculate the uptake and retention of phosphorus in biota. Basically, CoastWeb consists of two parts: the foodweb model, which is driven by chlorophyll and calculates production (kg ww/month) and biomass (kg ww) of the functional groups, and the mass-balance model for phosphorus (CoastMab; Håkanson and Eklund, 2007) based on transport processes that appear in most systems (Figure 3) and apply to most substances (nutrients, suspended particulate matter (= SPM), radionuclides, etc.). Key concepts in this modelling are (Table 2): (1) Consumption rates - ―how large a fraction of the prey biomass is consumed per time unit by the predator?‖ (2) Metabolic efficiency ratios for each compartment - ―how much of the food consumed will increase the biomass of the consumer?‖ (3) Turnover or retention rates for each compartment - ―how long is the mean, characteristic lifespan of the group?‖ (4) Food choices - ―if there is a food choice, how much is consumed of each food type?‖ (5) Migration rates - ―how large a fraction of the group will leave and enter the system per unit of time?‖ These concepts will be described briefly below for jellyfish. Håkanson and Boulion (2002) give more information on the different concepts. This modelling uses a simple general system to assign weights to food choices and adjust the consumption to the number of food choices. Figure 4 gives an overview of the food choice panel. If there are more than two food choices, they are first differentiated by a distribution coefficient (DC1) that separates between the primary and the other food types. A second distribution coefficient (DC2) separates the second most popular food type from the rest, etc.
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Table 2. Metabolic efficiency ratios for key functional groups (MER = PR/CON, dimensionless). The MER-value is calculated from the mass-balance equation, CON = PR + RES + FAE, where CON = consumption, PR = production, RES = respiration, FAE = unassimilated food (faeces), all dimensionless, and T = turnover time (= BM/PR, days; BM = biomass). The actual consumption rate constant, CR, expresses reduction of prey organism biomass per unit of time. The jellyfish values on PR, RES and FAE are from Schneider (1989) while the corresponding values for the other functional groups mainly are from Winberg (1985) and Håkanson and Boulion (2002) Zooherb
CON 100
PR 24
RES 36
FAE 40
MER 0.24
T 6.0
CR 0.17
Zoopred
100
32
48
20
0.32
11.0
0.091
Zoobenthos
100
15
35
50
0.15
65
0.015
Prey fish
100
16
64
20
0.16
300
0.016
Predatory fish Jellyfish
100
25
55
20
0.25
450
100
22
56
20
0.22
120
0.00130.02 0.008
Consumes Phytopl., Bacteriopl.Zoo pred, Zooherb Macrophytes, Benthic algae Zoobent., Zooherb, Zoopred Prey fish Zoopred, Zooherb
DC = 1
Zoobenthos DC = 0.5 Benthic plants DC = DC = 0.25 0.75 Benthic Macroalgae phytes
Secchi depth and morphometry
DC = 0.5 Organic sediments
Prey fish
DC = 0.5·Ysec Zooplankton
DC = 0.75 Pred. zooplankton
DC = 0.25 Herb. zooplankton
DC = 0.5 Phytoplankton
Phosphorus
Jellyfish
DC = 0.5
DC = 0.5
DC = 0.5 Bacterioplankton
SPM
Figure 4. Food choice panel for the default set-up used for the CoastWeb-model
Table 3. Gives a compilation of abbreviations used in this modelling.
Prey fish, Jellyfish Prey fish Pred. fish Pred. fish None
Predatory fish
DC = 1-0.5·Ysec
Consumed by Prey fish, Jellyfish
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Table 3. Abbreviations and dimensions of the most commonly used concepts and variables in this modelling. Note that we have tried to use as simple and self-explanatory abbreviations as possible. Greek letters have been banned A. Organisms BA = Benthic algae BE = Zoobenthos BP = Bacterioplankton JE = Jellyfish MA = Macrophytes PD = Predatory fish PH = Phytoplankton PY = Prey fish ZH = Zooplankton, herbivours ZP = Zooplankton, predators B. Driving variables Area = Coastal area (m2) Dm = Mean depth (m) Dmax = Maximum depth (m) SWT = Surface-water temperature (°C) TP = Total phosphorus (μg/l) C. Foodweb interactions BM = Biomass (kg ww), e.g., BMBP CON = Consumption (kg ww/week), e.g., CONPHZH (of PH eaten by ZH) CR = Actual consumption rate (1/week), e.g., CRZPPY (ZP eaten by PY) EL = Elimination (kg ww/week), e.g., ELZP IPR = Initial production (kg ww/week), e.g., IPRZHZP (ZH eaten by ZP) NBM = Normal biomass (kg ww), e.g., NBMBE NCR = Normal consumption rate (1/week), e.g., NCRPY MER = Metabolic efficiency ratio (dim. less), e.g., MERPYPD (PY eaten by PD) NR = Number of first order food choices (dim. less), e.g., NRZH PR = Production (kg ww/week), e.g., PRPD (PR defined by the ratio BM/T) T = Turnover time (weeks), e.g., TPH D. Mass-balance for phosphorus (= CoastMab) ASec = Area above Secchi depth (m2) BL = Biota with long turnover times BS = Biota with short turnover times C = Concentration, e.g., of phosphorus CTP (μg/l) DF = Dissolved fraction of phosphorus (dim. less) DP = Dissolved phosphorus (μg/l) DR = Dynamic ratio (dim. less) ET = Areas of fine sediment erosion and transport (dim. less) F = Flux of phosphorus (g/week), e.g., FETA (from ET to A) M = Mass of phosphorus (g), e.g., MET PF = Particulate fraction of phosphorus (dim. less) R = Rate (1/week) SW = Surface water Vd = Volume development (= form factor, dim. less)
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Table 3. (Continued) Y = Dimensionless moderator E. Other abbreviations Chl = Chlorophyll-a concentration (μg/l) dw = Dry weight IG = Sediment organic content (= loss on ignition, % dw) PrimP = Primary phytoplankton production Prec = Mean annual precipitation (mm/yr) SPM = Suspended particulate matter (mg/l) Sec = Secchi depth (m) W = Sediment water content (% ww) ww = Wet weight
Table 4. Many biological variables, whose determination normally require extensive and expensive field and laboratory work, may be estimated from lake TP (in µg/l = mg/m3). From Håkanson and Peters (1995) and Håkanson and Boulion (2002). PrimP = primary production (in g ww / m2 yr), Maccov = Macrophyte cover of lake bed (in % lake area), SecMV = mean annual Secchi depth (in m), Dm = mean lake depth (in m), Col = lake colour (mg Pt/l), DC = distribution coefficient (dimensionless), n = number of lakes used in the regression, ww = wet weight and dw = dry weight y-value
Equation
Equations based on phosphorus used as norms in LakeWeb: Chlorophyll =0.28·TP0.96 (summer mean) Chlorophyll =0.64·TP1.05 (summer max.) Max. prim. prod. =20·TP-71 (TP>10) Max. prim. prod. =0.85·TP1.4 (TP<10) Mean prim. prod. =10·TP-79 (TP>10) Mean prim. prod. =0.85·TP1.4 (TP<10) Phytoplankton =30·TP1.4 Bacterioplankton =0.90·TP0.66 Zooplankton, =0.77·38·TP0.64 herbivores Zooplankton, =0.23·38·TP0.64(the distr. coeff. is predators 0.77) Zoobenthos =810·TP0.71 Fish =590·TP0.71 Fish yield =7.1·TP Other equations used as norms in LakeWeb: Bacterioplankton =10(0.973·(0.27·log(Chl)+0.19)-0.438)
r2
n
Units
2.5-100
0.77
77
mg ww/m3
2.5-100
0.81
50
mg ww/m3
7-200
0.95
38
mg C/m3·d
Range for x
mg C/m3·d 7-200
0.94
38
m C/m3·d
0.88 0.83 0.86
27 12 12
mg ww/m3 mill./ml mg ww/m3
mg C/m3·d 3-80 3-100 3-80
mg ww/m3 3-100 10-550 8-550
0.48 0.75 0.87
38 18 21
mg ww/m2 mg ww/m2 mg ww/m2·yr mg ww/m3
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Equation =0.0023·PrimP0.9
Range for x 170-14 000
r2
n
Units
0.64
66
mg ww/m2·yr mg ww/m2 mg ww/m2 %
Prey fish =DC·fish biomass (default DC=0.73) Predatory fish =(1-DC)·fish biomass Macrophyte = 0.50·( SecMV/Dm) 229 cover Macrophytes =1.37·log(Maccov)+3.58 g ww/m2·yr 0.86 Zooplankton, =0.15·(PrimP·1000) 13-15 000 0.61 42 g ww/m2·yr herbivores Zooplankton, =0.076·(PrimP·1000)0.84 2-3 000 0.43 42 g ww/m2·yr predators Examples of local, regional and general relationships that may be used in the CoastWeb-model to predict chlorophyll-a concentrations from TP Local (for Chl = Ringkobing SMTH(((SWT+0.1)/9),12,60)·10^(Fjord): 1.86+1.72·log(CTP)) Regional (Baltic Chl = ((SWT+0.1)/20)·10^(coastal areas): 1.59+1.56·log(CTP)) General: Chl = (1/YCa)·YDRchl·Ytemp·Ysal·(0.28·CTP·0.56 /PF)0.96
Predictions of Normal Biomasses In LakeWeb and CoastWeb ―normal‖ (= norms = characteristic) biomasses of all functional groups are needed for calculations of consumption and migration. All normal biomasses and production values for the functional groups should ideally be calculated from empirical regressions yielding a high coefficient of determination (r2). Such general regressions are not, to the best of our knowledge, available for coastal areas, but many such empirical regressions are available for lakes (see Table 4). This is a major problem, not just to obtain good predictive power using CoastWeb, but also more generally in coastal ecology, to know what the ―normal‖ conditions are, given a set of standard abiotic regulating variables, such as TP-concentration for lakes. For coastal areas, the salinity is important for the Secchi depth (see Håkanson, 2006) and also for the relationship between chlorophyll and nutrient concentrations (Figure 5). Since there are no empirical relationships available for coastal areas that predict normal biomasses (norms), and since normal biomasses are essential in this modelling, the approach here is to modify and adjust the normal biomasses used in the LakeWeb-model and given in Table 4. Salinity influences the relationship between Chl and TP – the higher the salinity the lower chlorophyll relative to TP (Figure 5). If the primary production becomes lower at higher salinities, so will the secondary production. Hence, the first step in the approach to estimate coastal norms is to calculate a correction factor (Ychl) that describes the difference between chlorophyll in lakes (Chllake) and in coastal areas (Chlcoast) at the same TP, eq. 1.
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50 45
Chlorophyll-a concentration (µg/l)
40 35 30 25
1. Lakes, mean summer values; salinity = 0 2. Brackish coastal areas, salinities 2- 20; mean salinity - 11 3. Marine coastal areas, mean salinity - 23.5 4. Marine sites, mean salinity - 36 Chl=(1/YCa)·YDRchl·Ytemp·Ysal·(0.28·TP·0.56/PF)^0.96 If Ca-conc. < 10 mg/l then YCa =1 else YCa = (1+0.23·(Ca/10-1)) If DR > 2.45 then YDRchl=1 else YDRchl=DR/2.45 Ytemp = ((SWT+0.1)/20); SWT = surface-water temperature; °C Ysal = (1-0.75·Sal/36); Sal = salinity PF = the particulate fraction of P (calculated in the CoastWeb-model)
20
1
2
15
3 10
4
5 0 0
10
20
30
40
50
60
TP-concentration (µg/l)
70
80
90
100
Figure 5. The relationship between median total phosphorus concentrations (TP) in surface water and median concentrations of chlorophyll-a from the summer period (months 6, 7 and 8) for lakes, brackish water systems, marine coastal areas and open marine sites covering a salinity range from 0 to 36. DR is the dynamic ratio = √Area/Dm (Area = coastal area in km2; Dm = mean depth in m) (modified from Håkanson et al., 2005)
Ychl = Chlcoast/Chllake
(1)
Chlcoast may be calculated from a regression between TP and Chl as explained in Figure 5; Chllake is derived from Table 4. Hence, Ychl is 1 for lakes and less than 1 for coastal areas that have lower Chl-values than lakes at the same TP. To get the norms for the different functional groups, the corresponding norms in LakeWeb (Table 4) are multiplied with this correction factor. The normal biomasses for herbivorous zooplankton (NBMZH), predatory zooplankton (NBMZP), prey fish (NBMPY) and predatory fish (NBMPD) are calculated as: NBMZH = Ychl·(DCZHZP)·10-6·Vol·38·CTP0.64
(2)
DCZHZP is set to 0.77 as a default value (Håkanson and Boulion, 2002); Vol is the coastal volume (m3). NBMZP = Ychl·(1-DCZHZP)·10-6·Vol·38·CTP0.64 The normal biomass for fish (prey plus predatory fish) is given by:
(3)
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(4)
NBMPY = (DCPYPD)·SMTH(NBMfish,TPY,NBMfish)
(5)
NBMPD = (1-DCPYPD)·SMTH(NBMfish,TPD,NBMfish)
(6)
TPY and TPD are the turnover times for prey and predatory fish. The smoothing function (SMTH; see Håkanson, 1999, for more information on smoothing function) is used to adjust the temporal variability in TP to the turnover time of prey fish. The distribution coefficient regulating the fraction of prey fish is given by eq. 7. The more eutrophic the system, the higher the fraction of prey fish. This means that in relatively low-productive systems with TP = CTP = 15 µg/l, DCPYPD = (15/(15+22))0.4 = 0.70; and 70% of the fish biomass would be prey fish. DCPYPD = (CTP/(CTP +22))0.4
(7)
In LakeWeb, the normal biomass of zoobenthos (NBMZB) is calculated from Table 4 as 810·(CTP0.71). In CoastWeb, this has been modified to take into account that the biomass of zoobenthos primarily should depend on the sedimentation of organic matter and the bottom area above the Secchi depth, which regulate the production of benthic algae and macrophytes. The approach to predict NBMZB in CoastWeb is: If CTP < 100 µg/l then NBMZB = YChlZB·10-6·Area·810·(CTP0.71) else NBMZB = YChlZB·10-6·Area·810·(CTP0.71)·(1-0.5·(CTP/100-1))
(8)
Area is the coastal area (m2), CTP is the modelled TP-concentration. The normal biomass of phytoplankton is given by: NBMPH = Ychl·(10-6)·Vsec·(30·CTP1.4)
(9)
(30·TP1.4) is the normal biomass of phytoplankton in lakes (Table 4) and Vsec (or VsecSW) the water volume above the Secchi depth (Sec), calculated from: Vsec = V-(A-Asec)·Vd·(Dmax-Sec)/3
(10)
Vd is the form factor (Vd = 3·Dm/Dmax) and Asec is the bottom area shallower than the Secchi depth. The normal biomass of benthic algae (NBMBA) is calculated from the normal production of benthic algae (NPRBA) and the turnover time of benthic algae (TBA) by: NBMBA = NPRBA·TBA
(11)
NPRBA = 0.63·(Asec/A)·PRPH·(YsalSW)
(12)
Where
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Asec/A is the part of the bottom area shallower than the Secchi depth; PRPH is the production of phytoplankton (PRPH = BMPH/TPH). The equation in CoastWeb is the same as in LakeWeb, except for YsalSW, which is a salinity moderator for how the salinity influences the water clarity, which in turn influences the production of benthic algae (if SalSW < 1 then YsalSW = 1 else YsalSW = SalSW/1). The normal biomass of bacterioplankton (NBMBP) is estimated from a lake regression based on TP and Chl (Table 4), and modified by a moderator for SPM (YSPMBP) – the higher the amount of degradable organic suspended matter, the higher the normal biomass of bacterioplankton. NBMBP =YSPMBP·0.001·Vol·10(0.973·(0.27·log(Chl)+0.19)-0.438)
(13)
YSPMBP is given by: YSPMBP = SPMSWcoast/SPMSWlake
(14)
So, if there is a difference in SPM between a coast and a similar lake, this would influence the normal biomass of bacterioplankton in the coast. The SPM-concentrations in the surface water in the coast (SPMSWcoast) and in a corresponding lake (SPMSWlake) are calculated from the respective TP-concentrations and the regression between TP and SPM (from Håkanson, 2006). The same approach is used to estimate normal biomasses of the functional groups in the sea outside the given coastal area (NBMsea), which are used to calculate immigration. NBMsea is estimated from: NBMsea = NBMcoast·Ychlsea
(15)
Ychlsea is Chlsea/Chlcoast. For phytoplankton in the sea outside the given coastal area, the normal biomass is: NBMPHsea = Ychlsea·(30·CTPsea1.4)
(16)
For herbivorous and predatory zooplankton, the normal biomasses in the sea (NBMZHsea and NBMZPsea) are calculated as Ychlsea·NBMZH and Ychlsea·NBMZP. This is also the case for the normal biomasses for prey and predatory fish (Ychlsea·NBMPY and Ychlsea·NBMPD). For bacterioplankton, we have: NBMBPsea = NBMBP·YSPMsea
(17)
YSPMsea is SPMsea/SPMcoast and SPMsea is calculated from (SPMsea = 10(1.56·log(TPsea)-1.64)). The TP-concentration in the sea outside the given coast (TPsea = CTPsea in µg/l) is an obligatory driving variable. Immigration and emigration are not calculated for benthic algae, macrophytes and zoobenthos since these groups are assumed to be largely stationary. Migration of the other functional groups is described in the following section. We will be show how these algorithms work using data from real coastal areas.
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Table 5. Compilation of equations used to quantify immigration and emigration of predatory fish, prey fish, jellyfish, predatory zooplankton, herbivorous zooplankton, phytoplankton and bacterioplankton. There is no in- and emigration for benthic algae or zoobenthos (or macrophytes) in the model Ychlsea = Chlsea/Chlcoast The chlorophyll concentration in the sea and the coast may be given either by empirical data or by local, regional or global regressions based on TP and SWT (SWT = surface-water temp, °C) Predatory fish (PD); immigration: If BMPD/NBMPD < 1 then FinmigPD = Yseason ·RmigPD·NBMPDsea else FinmigPD = 0.5·Yseason ·RmigPD·NBMPDsea Migration rate: RmigPD = (1/TSW) [this is the theoretical surface water retention rate] Dimensionless seasonal moderator for migration: Yseason If (YseasonA -YseasonB) ≥ 0 then Yseason = ((YseasonA+YseasonB)/2)·(Lat/63) else Yseason = ((YseasonA+YseasonB)/2)·(63/Lat, where YseasonB = SMTH(YsaeasonA, AV, 0.12) NBMPDsea = NBMPDlake ·Ychlsea Ychlsea = Chlsea/Chlcoast Predatory fish (PD); emigration If BMPD/NBMPD < 1 then FoutmigPD = 0.5·Yseason ·RmigPD·BMPD else FoutmigPD = Yseason ·RmigPD·BMPD Prey fish (PY) immigration: If BMPDY/NBMPY < 1 then FinmigPY = Yseason ·RmigPY·NBMPYsea else FinmigPY = 0.5·Yseason ·RmigPY·NBMPYsea Migration rate: RmigPY = (0.33·1/TSW) NBMPYsea = NBMPYlake ·Ychlsea Prey fish (PY); emigration If BMPY/NBMPY < 1 then FoutmigPY = 0.5·Yseason ·RmigPY·BMPY else FoutmigPD = Yseason ·RmigPD·BMPD Jellyfish (JE) Migration rate: RmigJE = RmigPY Immigration: FinmigJE = RmigJE·NBMJEsea NBMJEsea = NBMJE ·Ychlsea NBMJE (kg ww) is assumed to be 10 times the normal biomass of predatory zooplankton (NBMZP, see below). Emigration: FoutmigJE = RmigJE·BMJE Predatory zooplankton (ZP) Migration rate: RmigZP = 1/TSW Immigration: FinmigZP = RmigZP·NBMZPsea NBMZPsea = NBMZPlake ·Ychlsea Emigration: FoutmigZP = RmigZP·BMZP Herbivorous zooplankton (ZH) Migration rate: RmigZH = RmigZP Immigration: FinmigZH = RmigZH·NBMZH
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Table 5. (Continued) NBMZHsea = NBMZHlake ·Ychlsea Emigration: FoutmigZH = RmigZH·BMZH Phytoplankton (PH) Migration rate: RmigPH = 0.5·RmigZP Immigration: FinmigPH = RmigPH·NBMPHsea NBMPHsea = NBMPHlake ·Ychlsea Emigration: FoutmigPH = RmigPH·BMPH Bacterioplankton (BP) Migration rate: RmigBP = RmigPH Immigration: FinmigBP = RmigBP·NBMBPsea NBMBPsea = NBMBPlake ·Ychlsea Emigration: FoutmigBP = RmigBP·BMBP
Migration LakeWeb accounts for immigration and emigration of fish. Coastal areas have a much more dynamic exchange of water than lakes (a typical theoretical surface-water retention time for Baltic Sea coastal areas is 4-6 days; and a typical water retention time for a lake is about 1 year; see Håkanson, 2000), which affects the immigration and emigration of fish to and from the area. Migration of fish is a complicated issue (Levinton, 2001), but it has to be quantified in CoastWeb where the aim is to obtain realistic predictions of fish biomass. Not only prey and predatory fish migrate, but also jellyfish, zooplankton, bacterioplankton and phytoplankton. New algorithms for immigration and emigration are used for all these functional groups (Table 5). They are based on the following principles: 1. The migration rate (Rmig, per month) in LakeWeb is related to the surface water (SW) retention rate (Rmig =1/TSW). This is meant to account for the physical possibilities for the organisms to migrate: if there is no inflow or outflow of water, no organisms will migrate in and out of the system. This approach is also used in CoastWeb for plankton that travel with the water rather than in the water, but not for fish and jellyfish. Plankton is mainly transported by water currents, as given by the SWexchange (TSW). The deep-water (DW) exchange is generally smaller than the SWexchange and the focus here is on the water exchange for the productive SW-layer. 2. It is assumed that big predatory fish will move more than smaller prey fish (the default assumption is that the migration rate is a factor of 3 lower for prey fish than for predatory fish, all else being constant); jellyfish and prey fish are assumed to have similar migration rates but jellyfish is likely to drift more passively in the water than prey fish. Vertical movements of jellyfish are achieved through contraction of the bell (Moen and Svensen, 2004). 3. Fish can migrate in and out of coastal areas for a number of reasons: as a part of their life cycle, to spawn, mate, etc. (Levinton, 2001) or more seasonally in search for food. This behaviour is different for different species. Knowledge of the dominating species in a region should be used to define an optimum migration behaviour for the
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Lars Håkanson and Dan Lindgren prey and predatory fish in the given region. For example, in Baltic Sea systems, Baltic herring (Clupea harengus) is likely to migrate into the coast in great numbers during the spawning in the spring (Axenrot and Hansson, 2004), which implies that the predatory fish feeding on herring also will migrate into the coast, and that the fish biomass in the coast will increase. To account for such regional migration patterns, CoastWeb uses a dimensionless moderator (Yseason), which could be adjusted to the prevailing conditions in different regions. This moderator is multiplied with the default migration rate (Rmig). As in LakeWeb, it is also assumed that the immigration or emigration of fish depend on the relationship between the actual biomass in the coastal area and the normal biomass (the BM/NBM-ratio). The migration may also sometimes be temperature dependent. Fish eat and grow faster in species-specific temperature ranges (Larsson and Berglund, 2005). This temperature influence could also be accounted for in the Yseason-moderator. An algorithm has been added to take into account that the latitude (Lat in °N) probably influences the seasonal migration patterns for fish. One should expect a more pronounced seasonal variation in light and temperature at high latitudes than at low latitudes and hence also in migration of fish searching for food. This has been handled in the following manner: If Lat > 63°N then AV = 1 else AV = (63-Lat); AV is an averaging function used in the smoothing function (SMTH) below: YseasonB = SMTH(YsaeasonA, AV, 0.12)
(18)
YseasonA is the seasonal moderator used for all coasts at latitudes ≥ 63°N (for which AV = 1; this is an assumed boundary latitude for the given algorithm). At lower latitudes, the function will smooth this curve (Figure 6A). The general moderator for migration is given by: If (YseasonA -YseasonB) ≥ 0 then Yseason = ((YseasonA+YseasonB)/2)·(Lat/63) else Yseason = ((YseasonA+YseasonB)/2)·(63/Lat)
(19)
Yseason is the default dimensionless moderator. It is shown in Figure 6A for four different latitudes (≥ 63, 56, 45 and 35°N). With this setup, the moderator attains high values in the spring at high latitudes reflecting regions with strong migrations related to the spawning and feeding of the dominating fish species. This is a suggestion for a general approach that can be used if no information is available on regional migratory patterns of fish. If such information is available, it should preferably be used. 4. It would require a very extensive sea-model (similar to and compatible with CoastWeb) to predict the amount of fish or plankton available for immigration outside any given coastal area. CoastWeb estimates the potentially available fish biomass for immigration using an estimated normal fish biomass in the sea outside the given coastal area, which is calculated from chlorophyll in the sea outside the coastal area. The immigration of predatory fish is then calculated as: If BMPD/NBMPD < 1 then FinmigPD = Yseason·RmigPD·NBMPDsea else FinmigPD = 0.5·Yseason·RmigPD·NBMPDsea
(20)
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RmigPD is the default migration rate for predatory fish (= 1/TSW). If the theoretical SW-retention time, TSW, is 6 days, the surface water is exchanged 5 times each month. Since there are no general migration rates to/from coastal areas available in the literature (to the best of our knowledge), the value of the default migration rate is our estimate based on calibrations using information from the studied coastal areas. To quantify this more accurately is an important task for the future. NBMPDsea is the normal biomass of predatory fish in the sea outside the given coastal area calculated from the normal biomass of predatory fish in lakes, NBMPDlake (Table 4) and a chlorophyll moderator, Ychlsea. Figure 6B illustrates the migration rate (Rmig) for predatory and prey fish for the Ronneby coastal area (latitude 56°N; Table 1). An Rmig-value of 0.75 means that 75% of the fish biomass may migrate either in or out of the coastal area. 5. Emigration of predatory fish is calculated in a similar way, i.e.: If BMPD/NBMPD < 1 then FoutmigPD = 0.5·Yseason·RmigPD·BMPD else FoutmigPD = Yseason·RmigPD·BMPD
(21)
Figure 6. A. Illustration of the seasonal moderator for immigration and emigration, Yseason, for four different latitudes (≥ 63, 56, 45 and 35 °N) and B. The default migration rates for prey and predatory fish (RmigPY and RmigPD, respectively) using data for the Ronneby coastal area (latitude 56 °N)
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Table 5 gives a compilation of all equations quantifying immigration and emigration. It shows that the basic set-up is applied to all functional groups. Note that CoastWeb does not account for cannibalism (feeding within the functional group). Cannibalism exists in aquatic systems among fish (Menshutkin, 1971), but to gain simplicity, the model calculates net production of fish (and zooplankton and zoobenthos). Table 6 gives all calculated monthly fluxes of predatory fish, i.e., immigration and emigration, initial production (IPR), production (BM/T), fishing and elimination, for the Ronneby coastal area (Table 1). Table 6 and the following four tables give results exemplifying the magnitude of these fluxes. Evidently, uncertainties in major fluxes are more decisive for the predictions than uncertainties in minor fluxes. So, it is important to identify the major fluxes and use algorithms that quantify these as correctly as possible. One can note: The biomass of predatory fish in this coast varies between 2.5 and 4 t wet weight during the year. The initial production is relatively high during summer and fall with a yearly total of 3.2 t/y; the production values are about 3 t/y. Immigration and emigration are significant; immigration 16 t/y and emigration 10 t/y. So, there is a net immigration of predatory fish to this area. The annual fishing of predatory fish under default conditions is 5 t/y. The loss of predatory fish (death, etc.) is 4 t/y. Table 7. gives the corresponding values for prey fish. The biomass of prey fish is about a factor 5 times higher than for predatory fish; the biomass varies between 12 and 20 t during the year. The initial production is 63 t/y and the production about 20 t/y. Immigration is 12 t/y and emigration 25 t/y, which means a significant net outflow of prey fish. Table 6. Calculated monthly and annual values of predatory fish biomass and fluxes of predatory fish in the Ronneby coastal area (southern Baltic Proper) Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Biomass (BMPD) (kg ww) 3 811 3 646 3 187 2 647 3 426 3 606 3 828 4 030 4 155 3 977 4 002 3 977 Annual values:
IPRPD (kg ww/m)
ElimPD (kg ww/m)
294 277 240 166 178 229 264 308 329 319 306 304 3 214
365 348 318 260 285 332 347 369 383 381 374 375 4 137
FishingPD (kg ww/m) 128 283 653 1 442 1 010 303 121 91 385 331 139 147 5 033
InmigPD (kg ww/m)
OutmigPD (kg ww/m)
513 622 798 2 096 3 329 2 056 1 422 1 222 1 798 1 060 772 661 16 349
480 432 525 1 100 1 434 1 470 995 869 1 234 846 539 468 10 392
Production (BMPD/TPD) (kg ww/m) 258 246 215 179 231 244 259 272 281 269 270 269 2 993
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3 906 3 946 4 063 3 907 4 573 5 902 7 147 7 502 6 767 5 912 5 172 4 291 63 088
17 29 43 52 95 150 151 130 102 67 36 14 886
12 18 24 28 56 94 100 84 65 37 21 10 549
1 177 1 107 960 663 713 916 1 056 1 233 1 315 1 278 1 222 1 216 12 856
2 447 2 316 2 136 1 776 1 752 1 911 2 198 2 566 2 738 2 696 2 644 2 569 27 749
287 627 1 460 3 282 2 088 582 256 211 916 783 326 336 11 154
318 341 438 1 782 3 236 1 586 1 041 882 1 241 676 457 379 12 377
1 161 1 252 1 552 2 539 2 533 2 887 2 288 2 179 3 230 2 479 1 673 1 372 25 145
Production (BMPY/TPY) (kg ww/m)
OutmigPY (kg ww/m)
InmigPY (kg ww/m)
FishingPY (kg ww/m)
ElimPY (kg ww/m)
From PY to PD (kg ww/m)
IPRZPPY (kg ww/m)
17 024 16 057 14 516 12 025 12 900 14 338 16 979 19 388 19 366 18 823 18 643 17 845 Annual values:
IPRZHPY (kg ww/m)
Biomass (BMPY) (kg ww)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
IPRZBPY (kg ww/m)
Month
Table 7. Calculated monthly and annual values of prey fish biomass and fluxes in the Ronneby coastal area
1 727 1 628 1 472 1 220 1 308 1 454 1 722 1 966 1 964 1 909 1 891 1 810 20 071
Zoobenthos is the most dominating and important food for prey fish. The prey fish production from zoobenthos consumption is 63 t/y, compared to 1 t/y from consumption of herbivorous zooplankton and 0.5 t/yr from consumption of predatory zooplankton. The annual fishing of prey fish is 11 t/y. The loss of prey fish (death, etc.) is 28 t/y. Table 8. gives the results for predatory zooplankton. The biomass varies very much during the year, from 120 kg ww during the winter to almost 1.6 t during the summer. The initial production from eating herbivorous zooplankton is over 27 t/yr and the production about 21 t/yr. Immigration is 49 t/y and emigration 40 t/y, i.e., a net inflow from the sea. The elimination is 29 t/y. Table 9 shows the same results for zoobenthos, which feed on benthic algae (430 t/y), macrophytes (24 t/y), but most of all on ―sediments‖ (1000 t/y) since zoobenthos mainly are detrivores. The biomass of zoobenthos varies between 45 and 100 t during the year and is about a factor of 6 higher than the biomass of prey fish. Immigration and emigration are zero (zoobenthos are largely stationary within the given coastal area). The elimination of zoobenthos is about 1000 t/y.
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Lars Håkanson and Dan Lindgren Table 8. Calculated monthly and annual values of biomass and fluxes for predatory zooplankton in the Ronneby coastal area Month
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Biomass (BMZP) (kg ww) 117 160 252 340 607 1 159 1 594 1 285 917 681 347 146 Annual values:
IPRZP (kg ww/m)
ElimZP (kg ww/m)
135 150 300 527 933 3 224 6 769 6 676 4 399 2 787 1 051 464 27 415
456 501 790 1 134 1 569 3 309 5 568 5 617 4 182 3 037 1 750 987 28 900
From ZP to JE (kg ww/m) 0 0 0 0 0 0 0 0 0 0 0 0 0
From ZP to PY (kg ww/m) 147 165 259 350 399 814 1 375 1 466 1 222 944 540 306 7 987
InmigZP (kg ww/m) 1 066 1 248 1 926 2 600 3 455 5 994 8 249 7 808 6 376 5 125 3 307 1 983 49 137
OutmigZP (kg ww/m) 626 688 1 084 1 556 2 153 4 542 7 641 7 709 5 739 4 168 2 402 1 355 39 663
Production (BMZP/TZP) (kg ww/m) 323 442 696 940 1 678 3 203 4 405 3 551 2 534 1 882 959 403 21 017
Table 9. Calculated monthly and annual values of biomass and fluxes for zoobenthos in the Ronneby coastal area Month Biomass (BMZB) (kg ww) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
45 501 48 373 53 841 64 705 80 396 100 518 103 515 90 509 77 495 69 738 57 531 47 569 Annual values:
IPRBAZB (kg ww/m) 6 284 10 099 15 137 22 908 49 432 78 805 84 256 68 794 49 825 28 632 15 390 6 157 435 719
IPRsedZB (kg ww/m) 73 156 75 203 76 514 77 983 84 312 91 251 95 216 96 027 94 897 89 079 81 274 73 798 1 008 710
IPRMAZB (kg ww/m) 1 034 1 001 1 069 1 260 1 723 2 510 3 247 3 298 2 876 2 371 1 862 1 280 23 531
From ZB to PY (kg ww/m)
ElimZB (kg ww/m)
24 374 24 720 26 935 33 436 52 251 66 358 75 697 71 336 60 968 40 650 34 077 27 314 538 116
58 168 58 711 60 316 57 851 67 525 86 086 104 025 109 788 99 645 87 189 76 656 63 882 929 844
Production (BMZB/TZB) (kg ww/m) 10 808 11 490 12 789 15 369 19 096 23 876 24 588 21 499 18 407 16 565 13 665 11 299 199 451
These simulations indicate that zoobenthos is an important food for fish in this coastal area and that threats to the production of zoobenthos would be serious to the fish production. Immigration and emigration of fish and zooplankton are important processes. There is generally no jellyfish in the Ronneby coastal area. The next section focuses on jellyfish.
An Outline of the Sub-Model for Jellyfish Jellyfish (JE) can appear in great numbers and are able to consume substantial amounts of mainly zooplankton, which can influence on fish production (Schneider and Behrends, 1994;
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Brodeur et al., 2002; Purcell, 2003). This makes them an important part of coastal foodwebs and they have been included as a secondary production unit in CoastWeb for areas where the salinity is high enough (the default threshold value in this model is set to 10; Lucas (2001) gave a value of 14 for a common jellyfish, Aurelia aurita). Jellyfish is a predatory zooplankton and could belong to the predatory zooplankton group in the model. However, the medusae-stage, i.e., what we generally mean by jellyfish, is so different compared to other predatory zooplankton concerning size, abundance, etc. that it has been assigned its own group in CoastWeb. Figure 7 illustrates the jellyfish sub-model and Table 10 gives all equations. Although this is a new sub-model, it is built in the same way as all other sub-models. This section will give an outline of this building block. Since jellyfish mainly eat zooplankton (Larson, 1987; Mills, 1995; Hansson, 2006), there is only one food choice between predatory and herbivorous zooplankton. So, the number of first order food choices for jellyfish is NRJE = 2, separated by DCZPZH. Jellyfish are also known to consume ichthyoplankton (fish eggs and larvae; Cowan et al., 1996; Suchman and Brodeur, 2005). However, this is not considered in the model since ichthyoplankton is not included as a functional group. Table 10. Basic differential equation for production and biomass of jellyfish (JE) BMJE(t) IPRZHJE IPRZPJE InmigJE ElimJE OutmigJE FZHJE FZPJE Ychlsea CRJE DCZPZH MERZP RmigJE NJE NBMJE NCRJE SalSW TJE YsalJE Ytemp
= BMJE(t - dt) + (IPRZHJE + IPRZPJE + InmigJE - ElimJE - OutmigJE)·dt = YsalJE· (1- DCZPZH)·FZHJE· MERZP·Ytemp0.5 [initial production of JE from eating ZH] = YsalJE· DCZPZH·FZPJE· MERZP·Ytemp0.5 [initial production of JE from eating ZP] = RmigJE·NBMJEsea [immigration of JE] = BMJE·1.386/TJE [elimination of JE] = RmigJE·BMJE [emigration of JE] = BMJE·CRJE [flux from ZH to JE] = BMJE·CRJE [flux from ZP to JE] = Chlsea/Chlcoast [correction factor for biomasses in the sea and in the coast related to chlorophyll] = (NCRJE+NCRJE·(BMJE/NBMJE-1)) [consumption rate for JE; if NBMJE = 0, then CRJE = 0] = 0.5 [distribution coefficient for JE eating ZP or ZH] = 0.32 [metabolic efficiency ratio for JE eating ZP or ZH] = RmigPY = RmigPD·0.33 [basic migration rates for PY, JE and PD] = 2 [number of first order food choices] = 10·NBMZP = 50·Ychlsea·(1-DCZHZP)·10-6·SMTH((V·38·CTP 0.64),TZP,(V·38·CTP 0.64)) [normal biomass of JE] = NJE/TJE [normal consumption rate for JE] = Surface-water salinity [= 6.5 in the Ronneby coastal area] = 120/30.42 [turnover time for JE in months] = if SalSW < 10 then 0 else 1 [assumed threshold salinity for JE production] = (SWT+0.1)/9 [dimensionless moderator for temperature influences on bioproduction]
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Lars Håkanson and Dan Lindgren Outline of the sub-model for jellyfish From ZH to JE, FZHJE MERZP
YSWT
T JE
IPR ZHJE
InmigJE
Jellyfish biomass BMJE Elim JE
RmigJE IPR ZPJE
From ZP to JE, FZPJE
OutmigJE CRJE
DCZPZH NCR JE
YsalJE
NJE NBM ZP
NBM JE
SalSW
Figure 7. An outline of the new sub-model for jellyfish
The consumption of biomass from grazing is calculated in kg ww/month. The total consumption is given by FZPJE = BMZP·CRJE. BMZP is the available biomass of predatory zooplankton and CRJE is the actual consumption rate (jellyfish eating its prey): CRJE = (NCRJE+NCRJE·(BMJE/NBMJE-1))
(22)
NCRJE is the normal consumption rate, BMJE is the actual biomass of jellyfish and NBMJE is the normal biomass. This means that the model quantifies changes in the actual consumption of the prey unit related to changes in the biomass of the consumer: more animals in the secondary unit (higher BMJE) means a higher actual consumption rate, CRJE. If the actual biomass of the predator is equal to the normal biomass of the predator, BMJE/NBMJE = 1, and CRJE = NCRJE. If the actual biomass of the predator is twice the normal biomass, then CRJE = 2·NCRJE. So, the model gives a linear increase in consumption with increase in biomass of the secondary unit. Lacking reliable empirical data, it is assumed that NBMJE may be set to be 10 times higher than the normal biomass of predatory zooplankton and depend on salinity. This gives: NBMJE = 10·NBMZP·YsalJE
(23)
By using a boundary condition, NBMJE can never be less than 0. The normal consumption rate, NCRJE, is NCRJE = 2/TJE. TJE is the turnover time of jellyfish (i.e., of the medusae stage). According to Lucas (2001), medusae of the common jellyfish, Aurelia aurita,
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generally live for 4 to 8 months. In the model, 120 days is used as a default value of turnover time for Jellyfish. The initial production (IPR) of jellyfish (JE) from eating predatory zooplankton (ZP) is given by: IPRJE = YsalJE·DCZPZH·FZPJE·MERZP·Ytemp0.5
(24)
The distribution coefficient, DCZPZH, gives the fraction of predatory zooplankton versus herbivorous zooplankton consumed by jellyfish. The MER-value is the amount of the total consumption (FZPJE) that will increase the biomass of the consumer, here jellyfish. The jellyfish digestion/consumption of its prey is temperature dependent (Martinussen and Båmstedt, 1999). This is accounted for by a dimensionless moderator Ytemp0.5 (Ytemp = ((SWT+0.1)/9); SWT = the SW-temperature in °C). YsalJE is a salinity moderator, which works in the following way: If the SW-salinity (salSW) is lower than 10, then YsalJE = 0 else YsalJE = salSW/10. Jellyfish can in some cases be consumed by fish and turtles (Legović, 1987) and they can also be consumed by other jellyfish (Martinussen and Båmstedt, 1999). However, this is not accounted for in the default set-up of the model. Jellyfish are removed from the coastal system by two processes: elimination, related to the turnover time of jellyfish and emigration. Immigration and emigration of jellyfish are calculated from: FinmigJE = RmigPY·NBMJEsea·YsalJE
(25)
FoutmigJE = RmigPY·BMJE
(26)
The migration rate for jellyfish is set equal to the migration rate for prey fish and the normal biomass of jellyfish in the sea outside the given coastal area is calculated from NBMJEsea = NBMJE·Ychl. The actual biomass of jellyfish in the coastal area, BMJE, is calculated automatically in the model and Ychl is defined by eq. 1. Elimination, i.e. the loss of biomass (ELJE) is given as: ELJE = BMJE·1.386/TJE
(27)
Where 1.386 is the halflife constant (-ln(0.5)/0.5 = (0.693/0.5; see Håkanson and Peters, 1995).
THE ROLE OF MACROPHYTES Macrophyte Cover The sub-model used in LakeWeb to predict the macrophyte cover is shown in eq. 28. MAcovlake = (10.49+1.502·(Sec /Dm)-1.993·(90/(90-Lat))-0. 422·(√Dmax)+0.490·log(A1·10-6))2
(28)
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In CoastWeb, it has been modified by an energy factor (Yex1) taking into account that coasts are open and affected by wind/wave action from the sea. This moderator quantifies that in coasts, where the wind/wave energy is high and the water exchange fast, it would be more difficult for the roots of the macrophytes to develop which would lower the macrophyte cover (MAcov in % of the coastal area). The macrophyte cover is calculated as: MAcov = MAcovlake· (1/Yex10.75)
(29)
If Ex < 0.003 (lower boundary condition for the exposure; see Figure 1) then Yex1 = 1 else Yex1 = (Ex/0.003)0.25 If Ex > 10 (upper boundary condition for the exposure) then Yex1 = 10 else Yex1 = (Ex/0.003)0.25 So, if the exposure (Ex) is very limited (< 0.003), the equation will calculate the same macrophyte cover as for a lake. If Ex is very high (> 10) for open coasts, (1/Yex10.75) will be 0.18 and the macrophyte cover will be only 18% of the corresponding value for a lake. A typical Ex-value for Baltic coastal areas is about 0.1 (Håkanson, 2006) which gives Yex = 0.52 and a macrophyte cover that is 52% of what would be expected in a lake with the same Secchi depth (Sec in m), the same area above a water depth of one meter (A1 in km2), the same mean depth (Dm in m) and maximum depth (Dmax in m). The macrophyte cover is used to calculate macrophyte production and biomass; the higher the macrophyte cover, the higher the fish biomass (if everything else is constant), since the macrophytes provide a protected environment for small fish (Sogard and Able, 1991). Different macrophyte species prefer different salinities (Boston et al., 1989; King and Garey, 1999) and have different tolerance to changes in salinity (Rout and Shaw, 1998, 2001). A relatively constant salinity is desirable for the macrophytes to abound. Figure 8 shows that the increase in salinity in the middle of the 1990s in Ringkobing Fjord (see Table 1) likely caused the observed reduction in macrophyte cover. There has been a slight change in dominance from sago pondweed Potemogeton pectinatus towards the more salt tolerant ditch grass Ruppia cirrhosa in recent years. This example is included to stress that Coast Web does not include any consideration to the fact that there can be changes in the abundance of single macrophyte species with a higher or lower tolerance to changes in salinity. The overall correspondence between the predicted values for the macrophyte cover during the period when the salinity was lower than 9.5 is good (see Håkanson, 2006), but when the salinity reached a threshold value of 9.5 (Håkanson et al., 2007), there was an initial reduction in macrophytes, which is not captured by the model. This is because when the salinity increases, the Secchi depth will also iincrease, which means that the model will predict an increased macrophyte cover. However, Figure 8 shows that the opposite has happened in Ringkobing Fjord. This indicates that the effect of the changes in salinity on single macrophyte species is even more pronounced than indicated by looking just at the macrophyte cover for the initial period. The actual change should be related to the curve predicted by CoastWeb since these predictions describe what would normally be expected under given conditions related to the factors accounted for in CoastWeb (eq. 28).
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Figure 8. Illustration of how the mean annual macrophyte cover and the mean annual salinity have varied in Rinkobing Fjord between 1980 and 2004, and how the macrophyte cover is predicted by the modified CoastWeb-model
Macrophytes and Macroalgae and Their Influence on Fish Production Macrophytes and macroalgae constitute a good environment for some species of predatory fish, e.g., for pike to make an ambush (Savino and Stein, 1989). The beds of macrophytes constitute a ―nursery‖ for young fish (Sogard and Able, 1991), which help to sustain a high fish biomass. Macrophytes and macroalgae are generally not important food for most fish (Barnes and Hughes, 1988; except for herbivores), but they provide shelter (Persson and Eklöv, 1995; Duarte, 2000) and can reduce the predation pressure (Nelson and Bonsdorff, 1990; Winfield, 2004), especially on small fish. In LakeWeb, this is handled by a dimensionless moderator, YMA: YMA = (1-0.2·(Maccov/25-1))
(30)
Maccov is the macrophyte cover (%). Macroalgae are expected to play a larger role in saline systems than in lakes for two reasons. Firstly, when the water clarity increases, the depth of the photic zone increases. This increases the production of benthic algae and macrophytes, which can cause a shift from a dominance of pelagic primary production to benthic primary production. Secondly, in marine systems such a shift would likely lead to a higher percentage of large macroalgae compared to smaller benthic algae. These macroalgae will influence the structure of the coastal ecosystem in ways similar to the macrophytes. In LakeWeb, the macrophytes influence the fish production mainly by providing a safe haven for the small fish. This is accounted for by lowering the predation pressure (from man, mammals or birds) on the fish. In CoastWeb, the influence of macroalgae and macrophytes on production and survival of prey and predatory fish is accounted for by a modification of the dimensionless moderator (YMA) in eq. 30. This gives a new moderator YMAcoast, eq. 31, that should reduce the predation pressure on prey and predatory fish in the same manner as YMA does in LakeWeb.
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(31)
YBAmacro is the ratio between the actual biomass of benthic algae in coastal areas and the normal biomass of benthic algae in lakes (YBAmacro = BMBA/NBMBAlake). This ratio reflects the prevalence of macroalgae in coastal areas compared to lakes and is generally higher than 1. In LakeWeb, the loss of prey fish from fishing and predation, is given by a constant default rate. In CoastWeb, the corresponding default rate is modified by two dimensionless moderators meant to make the loss of prey fish from fishing more realistic. The loss of prey fish from fishing is given by FfishPY (in kg ww/month): FfishPY = YMAcoast·BMPY·RfishPY
(32)
BMPY is the biomass of prey fish and RfishPY is the fishing rate of the prey fish. RfishPY is defined as: RfishPY =Ysec·Yseason ·0.5
(33)
0.5 (1/month) is a default fishing rate used in LakeWeb (derived from extensive calibrations), which is affected by two dimensionless moderators that account for influence of Secchi depth (Ysec) and seasonal migration pattern to and from the coastal area (Yseason). If empirical data are available on fishing of prey fish, such data should be used instead of the default fishing rate of 0.5. If the Secchi depth in a corresponding lake (Seclake) is larger than the Secchi depth in the coast (Seccoast = Sec), then Ysec =1 else Ysec = Sec/Seclake. So, if the water clarity in the coast is larger than in a corresponding lake, the predation pressure on prey fish is assumed to be higher than in a lake. This is quantified by this simple dimensionless moderator. Yseason is the dimensionless moderator for seasonal migration (see eq. 19). The loss from all types of predation on predatory fish (FfishPD in kg ww/month) is given in a similar way by: FfishPD = YMAcoast·BMPD·2·RfishPY
(34)
The default assumption is that the rate for fishing and predation is higher for predatory fish than for prey fish based on the fact that large fish are more attractive for professional and recreational fishermen (given by the factor 2). Figure 9 illustrates how the prey fish biomass, the predatory fish biomass and the elimination of prey fish depend on the new algorithm given in eq. 31. In these simulations, the new algorithm was used after month 26, before the algorithm in eq. 30 was used. One should note the effects that the macroalgae would have on the predation of prey fish (Figure 9C). The effect is due to an increase in prey fish biomass, which is compensated for by a significant increase in the food available for predatory fish and hence also in predation pressure of predatory fish on prey fish. The net effect is a relatively small change in prey fish biomass (Figure 9B) and in predatory fish biomass (Figure 9A).
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Figure 9. Simulations to illustrate the role of macroalgae for the fish production and biomass in coastal areas. In these simulations, the dimensionless moderator expressing how macroalgae influence elimination of prey fish was used from month 26 (the curves ―Accounting for macroalgae‖) compared to a situation when this moderator is not used. Using data from the Ronneby coastal area, S. Sweden, (A) gives the results for predatory fish, (B) for prey fish and (C) for the predation/fishing of prey fish
RESULTS This section presents case-studies to illustrate the potential use of CoastWeb to quantify how three major threats to coastal systems are likely to influence the structure and function of coastal foodwebs and this section will also give results from sensitivity analyses to illustrate how the model works along a latitude/temperature gradient and a salinity gradient. The first case-study focuses on eutrophication, the second on overfishing and the third on toxic contamination.
Eutrophication The idea here is to study how hypothetical stepwise (3-year steps) increases in TP in the sea outside a coast would likely influence the coast. Here, data from the Haverö coastal area are used (Finland; Table 1). The results are presented in Figure 10. The actual (default) TPconcentration in the sea is 24 µg/l, and tests have been done of how values of 0.75·24, 24, 1.5·24 and 2·24 would change modelled values of TP in the coastal water (A), chlorophyll (B), Secchi depth (C), the oxygen saturation in the deep-water zone, O2Sat (D), the normal and actual biomasses of zoobenthos (E), herbivorous zooplankton (F), prey fish (G) and predatory fish (H). Modelled values of TP, chlorophyll, Secchi depth and O2Sat are also
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compared with empirical data and uncertainty bands for the empirical data. The main results and conclusions of the simulations are: There is generally good correspondence between modelled and empirical data for the TPconcentration (Figure 10A), chlorophyll (Figure 10B), Secchi depth (Figure 10C) and O2Sat (Figure 10D). Note that the empirical chlorophyll value is a mean value for the entire summer period. There is also a close and logical correspondence between the actual and normal biomasses for zoobenthos, herbivorous zooplankton, prey fish and predatory fish. Note that the actual biomasses accounts for seasonal variations and predation more realistically than the normal biomasses, which are basically empirical reference values. The increased hypothetical eutrophication of the sea outside the coastal area will drastically increase TP also in the coast (which is logical because the water retention time in this area is 3-5 days, Persson et al., 1994) (Figure 10E). This leads to higher Chl-values (Figure 10B), reduced Secchi depths (Figure 10C) and lower O2Sat (Figure 10D), which will influence zoobenthos (Figure 10E) living in the sediments more than zooplankton in the more oxygenated surface water (Figure 10F). Since there is much more zoobenthos in the system than zooplankton (about 50 t ww compared to about 3-5 t ww), zoobenthos is an important source of food for omnivorous prey fish and changes in zoobenthos will have clear effects on the prey fish (Figure 10G), and changes in prey fish biomass will in turn influence the predatory fish who feed on prey fish (Figure 10H). The zoobenthos within the accumulation areas (A-areas) will die if O2Sat is lower than 20%, but the oxygenation of the sediments on the erosion and transport areas (ETareas) will maintain a low biomass of zoobenthos in the more shallow parts of the coastal area. To conclude: The increased eutrophication in the sea will imply several changes to the water quality and foodweb characteristics of the studied coastal area. Many of these changes could be expected without a model, but the point here is that they have been quantitatively predicted using a general comprehensive foodweb model which includes a dynamic massbalance model for phosphorus. This modelling accounts for many abiotic and biotic interactions and feedbacks and it is meant to give the ―normal‖ response of the system to the given change in the TP-concentration in the sea. The model accounts for different types of compensatory effects (such as increasing eutrophication leading to a higher primary phytoplankton production, which leads to more suspended particulate matter in the water and a lower Secchi depth, which leads to a smaller depth of the photic zone, which leads to a lower primary phytoplankton production). Such effects are difficult to quantify without a model. As stated, CoastWeb simulates functional groups and hence does not include responses related to single species.
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Figure 10. Case-study on coastal eutrophication using data from the Haverö coastal area. There are changes in 3-year steps in the TP-concentration in the sea adjacent to the coastal area. The default TPconcentration in the sea is 24 µg l-1 and this value has been set to 0.75·24, 24, 1.5·24 and 2·24 (i.e., 18, 24, 36 and 48 µg l-1) and the consequences calculated for (A) the TP-concentration in the given coastal area, (B) chlorophyll, (C) Secchi depth, (D) oxygen saturation in the deep-water zone (all compared to empirical mean values and inherent uncertainties in the mean values; the chlorophyll mean value is for the summer period) and actual and normal biomasses of (E) zoobenthos (F) herbivorous zooplankton, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
Overfishing Extensive fishing or fishing more than the permitted quota, is, unfortunately, a common practice in most parts of the world and an issue of intensive debate in many countries (Eagle
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and Thompson Jr., 2003; Hilborn et al., 2003). The idea with this case study is to illustrate how CoastWeb can be used to address this issue. Here, data from the Gävle coastal area (northern Sweden; Table 1) have been used. We will show how changes in fishing would influence the structure of this coastal ecosystem. The scenario is defined in Figure 11A. First, there is a ―normal‖ period of three years, then a period of one year when ten times the normal amount of prey and predatory fish is taken out of the system, followed by a recovery period of two years, then another period of intensive fishing with 20 times the default fishing for a period of two years, followed by a recovery period. Note that this is also a sensitivity analysis since no other changes than fishing have been made. In Figure 11, the consequences for TP-concentration (A), Secchi depth (B), chlorophyll (C) and the actual biomasses with and without this extensive fishing for herbivorous and predatory zooplankton (D, E), zoobenthos (F), prey fish (G) and predatory fish (H) are presented. The main results and conclusions of the simulation are: Also for this coastal area, there is generally a good correspondence between modelled and empirical data for TP (Figure 11A), Secchi depth (Figure 11B) and chlorophyll (Figure 11C). One can also note from these three figures that the changes in fishing in this coastal area would not affect the three water variables very much. There are no clear changes for herbivorous zoolankton (Figure 11D), but increases in the biomass of predatory zooplankton as a response to the lower predatory pressure from a declining biomass of prey fish related to the extensive fishing (Figure 11E and 11G). The lower predation pressure on zoobenthos from a reduced biomass of benthivorous prey fish is evident (Figure 11F). Note that this coastal system will recover quickly. As long as there is fish in the sea outside the coast, immigration of fish will continue, and the system will return to a dynamic steady state, as given by the algorithms for migration in the model. To conclude: The increased fishing will likely only affect the given coastal system marginally and mostly so during the period of the intensive fishing. The immigration of fish from the sea, especially in the springtime, is very large. However, if this kind of fishing were done also in the outside sea, the results would be different. This scenario also shows that it is essential to use as accurate values as possible on immigration and emigration in the model.
Toxic Contamination The final case-study concerns the effects of toxic substances. Our aim is to demonstrate the potential of CoastWeb for making calculations to obtain realistic expectations of the consequences that contaminants can have on the coastal foodweb. We will examine what might happen if a hypothetical contaminant would drastically reduce the biomass of a functional group. Large ecosystem effects should be expected if there are major changes in groups with large biomasses. For that reason, zoobenthos have been selected and data from the Ronneby coastal area have been used. There is also another reason to focus on zoobenthos, related to the fact that many toxic substances show a high affinity for particles in
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aquatic systems (Håkanson, 1999; Mackay, 2001). This means that high concentrations of such substances may appear in sediments, the habitat for zoobenthos.
Figure 11. Case-study on extensive fishing (or overfishing) using data from the Gävle coastal area. First there is a tenfold increase in the default fishing/predation rate on prey and predatory fish for one year, and then the fishing rate is increased by a factor of 20 for two consecutive years (see Figure A). The consequences of these events are calculated for (A) TP-concentration, (B) Secchi depth and (C) chlorophyll (all compared to empirical data, mean values and uncertainties in the mean values; the chlorophyll mean value is for the summer period). Figures D to H gives a comparison of how this extensive fishing would influence the actual biomasses of (D) herbivorous zooplankton, (E) predatory zooplankton, (F) zoobenthos, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
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Figure 12. Case-study on toxic contamination using data from the Ronneby coastal area. It is assumed that there is first a contamination that eliminates 90% of the zoobenthos months 7 and 8, then a contamination that kills 99% of the zoobenthos for a whole year, and, finally, total extinction of zoobenthos (see Figure A). The consequences of these events are calculated for the actual and normal biomasses of (B) phytoplankton, (C) benthic algae, (D) bacterioplankton, (E) herbivorous zooplankton, (F) predatory zooplankton, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
Figure 12A presents the scenario. First, 90% of the zoobenthos biomass is reduced (killed by contamination) months 7 and 8, year 4. Then, after a two year recovery period, 99% of the zoobenthos biomass is reduced for an entire year. Finally, after another period of recovery, all zoobenthos are killed. Figure 12 shows how this would influence the actual and normal biomasses of zoobenthos (A), phytoplankton (B), benthic algae (C), bacterioplankton (D), herbivorous zooplankton (E), predatory zooplankton (F), prey fish (G) and predatory fish (H).
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Initially, there is a good correspondence between actual and normal biomasses also in this area for all the eight functional groups shown in Figure 12. The changes in zoobenthos (Figure 12A) will not affect phytoplankton (Figure 12B), benthic algae (Figure 12C) and bacterioplankton (Figure 12D). Since there is much more zoobenthos in the system than herbivorous and predatory zooplankton (about 100 t ww compared to about 5 and 1 t ww, respectively), zoobenthos is an important food source for omnivorous prey fish and reductions or changes in zoobenthos will have clear effects on prey fish and hence also on predatory fish (compare Figure 12A to Figure 12G and H). To conclude: This case-study shows that a reduction of zoobenthos biomass will have clear effects of fish production and biomass in the given coastal area. This scenario may not be realistic in the sense that nothing but zoobenthos has been affected by the contamination. However, more realistic simulations can be made with the model. The model can, e.g., also be used to simulate non-lethal effects of toxic substances, such as reduced production. The idea here is just to briefly demonstrate its potential.
Sensitivity Analysis – Latitude/Temperature This section first presents a sensitivity analysis along a latitude (temperature) gradient. The latitude for the Gräsmarö coastal area (see Table 1; latitude = 58°N) has been changed in 3-year steps to 40, 50, 58 and 70°N. Results are given in Figure 13 for Secchi depth, TP, O2Sat, chlorophyll (using the general approach in Table 4) and actual and normal biomasses of benthic algae, zoobenthos, prey fish and predatory fish. Figure 13A gives the driving variable, the latitude gradient. The main results and conclusions of the simulation are: The change in latitude will cause clear changes in predicted surface-water temperatures (Figure 13A). There is a good correspondence between modelled and empirical chlorophyll (Figure 13B); the figure gives empirical mean values (MV) and MV plus two standard deviations (SD). There is a good correspondence also between modelled values for sedimentation on accumulation areas and empirical data, as determined from sediment traps (Figure 13C). Figure 14D to H give values of the actual and normal biomasses for phytoplankton, benthic algae, bacterioplankton, zoobenthos and predatory fish. The actual biomasses should give representative values since these values account for predation and several factors that are not included in the calculation of the normal biomasses. In general, however, there is a good correspondence between the two measures indicating that the model works as expected. It is also interesting to compare the biomasses: in this test, the biomass of benthic algae (Figure 13E) is higher than the biomass of bacterioplankton (Figure 13F), which is higher than the biomass of phytoplankton (Figure 13D); the biomass of zoobenthos
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Figure 13. Testing the model along a latitude gradient using data from the Gräsmarö coastal area. The default latitude (58°N) has been changed in 3-year steps by 40, 50, 58 and 70°N and the consequences have been calculated for (A) the surface-water temperature, (B) chlorophyll-a, (C) sedimentation on accumulation areas (as compared to empirical maximum and minimum data from sediment traps), and modelled actual and normal biomasses of (D) phytoplankton, (E) benthic algae, (F) bacterioplankton, (G) zoobenthos and (H) predatory fish. MV: Mean values, SD: Standard deviation
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Sensitivity Analysis - Salinity This section presents a sensitivity analysis along a salinity gradient. Figure 14 uses data from the Ronneby coastal area (see Table 1). The default salinity inside and outside this area has been increased in 3-year steps from 6.5 to 13, 19.5 and 26 and the consequences calculated for all functional groups and bioindicators while all other factors have been kept constant at the default conditions. Figure 14 gives results for Secchi depth, TP, O2Sat, chlorophyll (using the general approach in Table 4) and actual and normal biomasses of benthic algae, jellyfish, prey fish and predatory fish. Figure 14A gives the driving variable, the salinity gradient. The main results and conclusions are: The increase in salinity will cause a distinct increase in Secchi depth and in water clarity (Figure 14A). There is a good correspondence between modelled and empirical Secchi depths also in this coastal area. Whenever data are available, Figure 14 also gives empirical mean values (MV) and standard deviations for the empirical data (SD) as a measure of the inherent uncertainty in the empirical data. There is a good correspondence between modelled and empirical TP. TP will decrease somewhat along the salinity gradient (Figure 14B). There is also a fine correspondence between modelled and empirical O2Sat, which will decrease with increasing salinity because a high salinity will increase flocculation and sedimentation of suspended particulate matter and particulate phosphoprus. In this open and shallow area, the deep-water turnover time is about 6 days and the deep-water volume is small. This means that the coastal area is well oxygenated (Figure 14C). There is also a relatively good correspondence between modelled and empirical chlorophyll (Figure 14D). Chlorophyll decreases with increasing salinity (see Figure 5) and with lower TP. The biomass of benthic algae (Figure 14E) increases along the salinity gradient because a higher salinity means an increased water clarity and therefore photosynthetic activity. Also the Jellyfish biomass increases (Figure 14F). However, there are no empirical data on biomasses available for comparison. Also the biomass of zoobenthos increases, meaning more food for prey fish and a higher biomass of prey fish along the salinity gradient. More prey fish also means more food for the predatory fish and an increase in predatory fish biomass (Figure 14G and H). The changes in salinity would also influence the migration of fish and the consumption rates since the salinity influences the normal biomasses of both prey and predatory fish. In reality, individual species can be sensitive to changes in salinity and would not survive the big changes in salinity that was used in this example. However, the model does not simulate individual species, but functional groups and a salinity that is non-optimal for one species may be optimal for another species in the same functional group.
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Figure 14. Testing the CoastWeb-model using data from the Ronneby coastal area along a salinity gradient. The default salinity (6.5) has been increased in 3-year steps by a factor of 1, 2, 3 and 4 and the consequences calculated for (A) Secchi depth, (B) TP-concentration, (C) oxygen saturation in the deepwater zone, (D) chlorophyll-a concentration using the general model (all compared to empirical mean values and inherent uncertainties in the mean values; the chlorophyll mean value is for the summer period) and actual and normal biomasses of (E) benthic algae, (F) jellyfish, (G) prey fish and (H) predatory fish
DISCUSSION AND COMMENTS The overall framework for this modelling is that science and management need practical, operational tools to predict how coastal ecosystems would likely respond to
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different threats so that the best possible remedial actions can be taken. The model presented in this work in meant as a tool to address such issues. This is exemplified by the case-studies and sensitivity analyses discussed in this paper We have presented a first version of CoastWeb, a coastal foodweb model that simulates ten functional groups and includes a mass-balance model for phosphorus. CoastWeb is an adaptation of a foodweb model for lakes and its underlying structure and main algorithms have been extensively tested. However, this is a first adaptation of the model to coastal conditions and there are several parts that could and should be improved if, and when, better data become available from more coastal areas covering a wide functional domain. At present, the lack of data is most evident for more saline coastal areas. A major deficiency in CoastWeb compared to LakeWeb concerns the empirical models to predict normal biomasses for the functional groups. In this respect, limnology, where good empirical models exist for almost all functional groups, is ahead of coastal ecology. This highlights the importance of getting better data and knowledge on the role of the salinity to predict chlorophyll from phosphorus and/or nitrogen in costal areas. It is also important to seek better knowledge on the processes regulating nitrogen fluxes in marine systems to be able to include a mass-balance model of nitrogen in CoastWeb in the future. In CoastWeb, jellyfish has been introduced as a functional group. The model structure for this group is the same as for all other functional groups. Empirical data have been used for jellyfish model parameterisation, when available. However, in this first version, several estimates have been used that may need to be changed when more and better data become available in the future. Mass occurrence (blooms) of jellyfish also needs to be addressed in future versions of CoastWeb. Due to the high variability that coastal fish show concerning food habits, migratory patterns, etc., it is difficult to develop general algorithms for fish that give good predictions over a wide range of areas. The regional seasonal moderator (Yseason) that handles migration of fish used in this work is only meant as a template and is mainly intended to reflect prevailing conditions in Baltic Sea coastal areas. Similar regional moderators should be developed for other coastal regions. This is especially important since the performed tests show that migration of fish is of major importance for coastal fish biomasses. It is essential to stress that the model simulates functional groups and not individual species. In the presented sensitivity analyses and case-studies, several water variables show good correspondence with existing and available empirical data. The calculated biomasses seem reasonable, but no or few empirical biomasses data have been available to perform independent validations. This is desirable for the future, although it is very hard to get comprehensive, time- and area compatible data on biomasses and abiotic variables from the same area for functional groups of organisms.
ACKNOWLEDGMENTS This work has been carried out within the framework of the Thresholds-project, an integrated EU project (no., 003933-2), and we would like to acknowledge the financial support from EU and the constructive cooperation within the project. Special thanks to prof. Carlos Duarte, the scientific coordinator of the project.
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APPENDIX: MINOR MODIFICATIONS 1. Salinity is of paramount importance for the number of different species: freshwater species dominate at salinities lower than 5 (psu), brackish water species at salinities from 5 to 20 and saltwater species at higher salinities than 20 (Remane, 1934). The salinity also influences the settling velocity of SPM, and hence water clarity (Secchi depth): the higher the salinity, the greater the aggregation, and the higher the sedimentation (Kranck, 1973, 1979). In CoastMab, this is expressed by a dimensionless moderator for salinity (Ysal) operating on the settling velocity. The effect of salinity is of special importance in estuaries where fresh and saltwater meet and a zone of maximum turbidity occurs (Gebhardt et al., 2005). A new algorithm relating the Secchi depth to SPM and salinity (from Håkanson, 2006) has also been incorporated into CoastWeb. 2. SPM-values are used to calculate the Secchi depth, which in turn is important to predict macrophyte cover and production of benthic algae. In the original CoastMabmodel for total phosphorus (TP) (Håkanson and Eklund, 2007), SPM is calculated by a dynamic SPM-model. For simplicity, and because there is a close relationship between SPM and TP, this version of CoastWeb has omitted the dynamic SPMmodel and uses a regression to predict SPM from dynamically modelled TPconcentrations (Figure 15). It is based on annual data from 51 systems (data from Lindström et al., 1999; Håkanson, 2006) and gives a high coefficient of determination (r2 = 0.895). However, this regression is based on data from systems with salinities lower than 15 so it may provide limited predictive power for systems with higher salinities. y = 1.561x - 1.639; r2 = 0.895; n = 51; p < 0.001 1.75 1.5 1.25
log(SPM) [mg l-1]
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log(TP) [µg l-1] Figure 15. The regression between annual SPM and TP-concentrations based on data from 51 coastal areas and lakes
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3. The chlorophyll-a concentration (Chl) is important in CoastWeb since Chl is needed to predict phytoplankton biomass. If the aim is to use only CoastWeb, the simplest approach is to use empirical data of Chl. However, if the aim is to study how changes in phosphorus loading affect the foodweb, CoastMab should be linked to CoastWeb. Calculating chlorophyll from nutrients is a fundamental concern in aquatic sciences. Generally, Chl-values are predicted from temperature or light and nutrient concentrations (Dillon and Rigler, 1974; Smith, 1979; Riley and Prepas, 1985; Evans et al., 1996). In this work, regressions relating monthly TP to monthly chlorophyll are used. A local relationship (Håkanson et al., 2007) between chlorophyll and TP has been used for Ringkobing Fjord, Denmark (see Table 4 and Figure 16, with and without a smoothing function SMTH; see Håkanson, 1999). Note that modelled values are not compared to the empirical mean values, but to uncertainty bands calculated as median monthly values ± the uncertainty in the mean empirical value. The regional regression in Table 4 is from Håkanson and Eklund (2007); (SWT+0.1)/20) is the temperature moderator where 20°C is the summer mean temperature for this regression. If no local or regional relationships are available, the general approach in Table 4 may be used. This is an adaptation of a basic regression for lakes [(0.28·CTP)0.96; from OECD (1982)], which is modified by a four moderators. The calcium moderator (YCa) takes into account that systems with Caconcentrations > 10 mg/l are likely to have lower Chl-values relative to TP than systems with lower Ca-concentrations (Håkanson et al., 2005). The morphometry moderator, YDRchl, quantifies how the dynamic ratio (DR = √Area/Dm; Area in km2 and mean depth, Dm, in m) influences the relationship between TP and Chl. Systems with DR > 2.45, are dominated by resuspension events of fine sediments (Håkanson and Jansson, 1983). In such systems, benthic algae may be resuspended and included in the water sample used for the chlorophyll analysis. YDRchl is given by: If DR < 2.45 then YDRchl = 1 else YDRchl = DR/2.45
(35)
The temperature moderator [Ytemp= ((SWT+0.1)/20)] has already been mentioned. The salinity moderator, Ysal, takes into account that the salinity influences the distribution coefficient between dissolved and particulate P in a similar way as calcium: the higher the salinity the lower the slope of the regression line between TP and chlorophyll (Figure 5; Håkanson et al., 2007). The relationship between Chl and phosphorus is also affected by the particulate fraction of phosphorus (PF). In LakeWeb, monthly PF was set to 0.56 as a reference value (Håkanson and Eklund, 2007), but in CoastWeb PF is affected by the biouptake and retention of phosphorus in functional groups, eq. 36. If SWT > 9 °C then PF = 0.56·(MSW + Mshort + Mlong)/MSW else PF = 0.56·MSW/(MSW+ Mshort + Mlong)
(36)
MSW, Mshort, Mlong are the amounts of TP [g] in the surface water, in functional groups with short turnover times and with long turnover times. So, in CoastWeb,
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The previous expression works well for systems where the DW-zone has the form of a cone, but for systems that are more U-shaped with Vd-values higher than 1, the correction using the form factor (Vd = 3·Dm/Dmax) will provide a more realistic estimate of VDW. 5. The moderator, YEh1, is used to express the oxygen stress on zoobenthos in LakeWeb. In CoastWeb, it has been replaced by a more tested approach, which is also used to quantify diffusion of phosphorus from sediments (Håkanson and Eklund, 2007): If O2Sat > 50% then YEh1 = (2-1·(O2Sat/50-1)) else YEh1 = (2-3000·(CTPA/1)·(O2Sat/50-1))
(38)
Figure 16. Modelling chlorophyll in Ringkobing Fjord, from modelled monthly TP-concentrations (actual data and smoothed data) using the CoastMab-model (within CoastWeb) and the regression given in eq. 2, compared to uncertainty bands based on median monthly values ± the uncertainty in the empirical annual mean values (see Håkanson et al., 2007)
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CTPA is the modelled TP-concentration is accumulation-area (A) sediments. If CTPA is higher than 1 mg/g dw, the dimensionless amplitude value (3000) increases, and hence also the diffusion; if CTPA is lower than 1, the amplitude value decreases. The following smoothing function has also been applied to provide realistic temporal changes in the moderator for zoobenthos: YEh = SMTH(1/YEh1, TZB, 1/YEh1)
(39)
TZB is the turnover time for zoobenthos (Table 2). YEh is never permitted to attain values < 0. 6. The dimensionless moderator expressing how low oxygen saturation in the DW-zone (O2Sat in %) would influence the survival of zoobenthos in areas of erosion and transport (ET-areas) has been modified from YEh10.25 to YEh10.5. This means that a low O2Sat will more clearly reflect lower oxygen conditions also in the surface water. 7. The distribution coefficient regulating the prey fish consumption of either zooplankton or zoobenthos has been changed from 0.5 in LakeWeb to DCZPZB = 0.5·Ysec0.2. For coasts, which generally have a higher water clarity than lakes, the basic DC-value is modified by a Secchi depth moderator (Ysec;, eq. 40), that compares the Secchi depth in the coast Secchicoast with that of a corresponding lake, Secchilake. If Secchilake > Secchicoast then Ysec = 1 else Ysec = Secchicoast/Secchilake
(40)
Which, e.g., gives 0.5·20.2 = 0.57 (a diet of 57% zooplankton and 43% zoobenthos consumed by prey fish) if Ysec is 2. The power (0.2) has been derived by calibration. 8. The moderator used in LakeWeb to reduce the predation pressure in very turbid lakes (Yfish) has been set to 1, since Secchi depths lower than 1 m are rare in coastal areas on a monthly basis (the ecosystem scale). 9. The amount of food (―sediment pool‖, FsedZB in kg ww/month) available for the zoobenthos is not calculated in the same manner as in LakeWeb, but from sedimentation of particulate phosphorus recalculated into sedimentation of organic matter as food for the zoobenthos. This is done accordingly: FsedZB = FAET·(1000/2)·1000·(100/(1-W))·0.67
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FAET is the sedimentation of TP on ET- and A-areas in g dw/month (calculated automatically in CoastMab from eq. 42). FAET is calculated from a function which gives an annual smoothing of the monthly sedimentation on ET-areas and A-areas (FSWET and FDWA in g TP/month): FAET = SMTH((FSWET+FDWA), 12, (FSWET+FDWA))
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From Håkanson (2006) it is assumed that SPM deposited on ET- and A-areas on average has a TP-concentration of 2 mg/g dw. Multiplication with 1000 gives SPM in kg dw/month. W is the water content of SPM (= 100·(g ww-g dw)/g ww) of SPM
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(43)
When the fraction of ET-areas is 15%, W is 75% which is used as the default water content of ET- and A-sediments in coastal areas (Håkanson et al., 1984). If the fraction of ET-areas (with coarser materials), is higher, the calculated water content of the SPM should be lower, which is given by eq. 43. If ET is 0.9, W is 61%.
REFERENCES Axenrot, T. & Hansson, S. (2004). Seasonal dynamics in pelagic fish abundance in a Baltic Sea coastal area. Estuar. Coast. Shelf Sci., 60, 541-547. Barnes, R. S. K. & Hughes, R. N. (1988). An introduction to marine ecology, 2nd ed. Blackwell Scientific Publications, Oxford, 351. Boston, H. L., Adams, M. S. & Madsen, J. D. (1989). Photosynthetic strategies and productivity in aquatic systems. Aquat. Bot., 34, 27-57. Brodeur, R. D., Sugisaki, H. & Hunt, G. L. Jr., (2002). Increases in jellyfish biomass in the Bering Sea: implications for the ecosystem. Mar. Ecol. Prog. Ser., 233, 89-103. Christensen, V., Walters, C. J. & Pauly, D. (2000). Ecopath with Ecosim: A User‘s Guide. Fisheries Centre, Univ. of British Columbia, Vancouver, 130. Cowan, J. H., Jr, Houde, E. D. & Rose, K. A. (1996). Size-dependent vulnerability of marine fish larvae to predation: an individual-based numerical experiment. ICES J. Mar. Sci., 53, 23-37. Dillon, P. J. & Rigler, F. H. (1974). The phosphorus-chlorophyll relationship in lakes. Limnol. Oceanogr, 19, 767-773. Duarte, C. M. (2000). Marine biodiversity and ecosystem services: an elusive link. J. Exp. Mar. Biol. Ecol., 250, 117-131. Eagle, J. & Thompson Jr., B. H. (2003). Answering Lord Perry‘s question: dissecting regulatory overfishing. Ocean Coast. Manag., 46, 649-679. Evans, M. S., Arts, M. T. & Robarts, R. D. (1996). Algal productivity, algal biomass, and zooplankton biomass in a phosphorus-rich, saline lake: deviations from regression model predictions. Can. J. Fish. Aquat. Sci., 53, 1048-1060. Gebhardt, A. C., Schoster, F., Gaye-Haake, B., Beeskow, B., Rachold, V., Unger, D. & Ittekkot, V. (2005). The turbidity maximum zone of the Yenisei River (Siberia) and its impact on organic and inorganic proxies. Estuar. Coast. Shelf Sci., 65, 61-73. Hansson, L. J. (2006). A method for in situ estimation of prey selectivity and predation rate in large plankton, exemplified with the jellyfish Aurelia aurita (L.). J. Exp. Mar. Biol. Ecol., 328, 113-126. Harvey, C. J., Cox, S. P., Essington, T. E., Hansson, S. & Kitchell, J. F. (2003). An ecosystem model of food web and fisheries interactions in the Baltic Sea. ICES J. Mar. Sci., 60, 939-950.
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Håkanson, L. (1999). Water pollution - methods and criteria to rank, model and remediate chemical threats to aquatic ecosystems. Backhuys Publishers, Leiden, 299. Håkanson, L. (2000). Modelling radiocesium in lakes and coastal areas - new approaches for ecosystem modelers. A textbook with Internet support. Kluwer Academic Publishers, Dordrecht, 215. Håkanson, L. (2006). Suspended particulate matter in lakes, rivers and marine systems. The Blackburn Press, New Jersey, 331. Håkanson, L., Blenckner, T., Bryhn, A. C. & Hellström, S. S. (2005). The influence of calcium on the chlorophyll-phosphorus relationship and lake Secchi depths. Hydrobiologia, 537, 111-123. Håkanson, L. & Boulion, V. V. (2002). The Lake Foodweb - modelling predation and abiotic/biotic interactions. Backhuys Publishers, Leiden, 344. Håkanson, L., Bryhn, A. C. & Eklund, J. M. (2007). Modelling phosphorus and suspended particulate matter in Ringkobing Fjord in order to understand regime shifts. J. Mar. Syst., 68, 65-90. Håkanson, L. & Eklund, J. M. (2007). A dynamic mass balance model for phosphorus fluxes and concentrations in coastal areas. Ecol. Res., 22, 296-320. Håkanson, L. & Gyllenhammar, A. (2005). Setting fish quotas based on holistic ecosystem modelling including environmental factors and foodweb interactions – a new approach. Aquat. Ecol., 39, 325-351. Håkanson, L. & Jansson, M. (1983). Principles of lake Sedimentology, Springer, Berlin, 316. Håkanson, L. & Karlsson, M. (2004). A dynamic model to predict phosphorus fluxes, concentrations and eutropications effects in Baltic coastal areas. In: M. Karlsson, Predictive modelling – a tool for aquatic environmental management. Thesis, Department of Earth Sciences, Uppsala University, 108. Håkanson, L., Kulinski, I. & Kvarnäs, H. (1984). Vattendynamik och bottendynamik i kustzonen. SNV PM 1905, Solna, 228. (in Swedish). Håkanson, L. & Peters, R. H. (1995). Predictive limnology. Methods for predictive modelling. SPB Academic Publishing, Amsterdam, 464. Hilborn, R., Branch, T. A., Ernst, B., Magnusson, A., Minte-Vera, C. V., Scheuerell, M. D. & Valero, J. L. (2003). State of the Worlds Fisheries. Annu. Rev. Environ. Resour., 28, 359399. King, G. M. & Garey, M. A. (1999). Ferric Iron Reduction by Bacteria Associated with the Roots of Freshwater and Marine Macrophytes. Appl. Environ. Microbiol, 65, 4393-4398. Kranck, K. (1973). Flocculation of suspended sediment in the sea. Nature, 246, 348-350. Kranck, K. (1979). Particle matter grain-size characteristics and flocculation in a partially mixed estuary. Sedimentology, 28, 107-114. Larson, R. J. (1987). Daily ration and predation by medusae and ctenophores in Saanich inlet, B.C., Canada. Neth. J. Sea Res., 21, 35-44. Larsson, S. & Berglund, I. (2005). The effect of temperature on the energetic growth efficiency of Arctic charr (Salvelinus alpinus L.) from four Swedish populations. J. Therm. Biol., 30, 29-36. Legović, T. (1987). A recent increase in Jellyfish populations: A predator-prey model and its implications. Ecol. Model., 38, 243-256. Levinton, J. S. (2001). Marine biology: function, biodiversity, ecology, 2nd Ed. Oxford University Press, New York, USA, 515.
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indström, M., Håkanson, L., Abrahamsson, O. & Johansson, H. (1999). An empirical model for prediction of lake water suspended matter. Ecol. Model, 121, 185-198. Lucas, C. H. (2001). Reproduction and life history strategies of the common jellyfish, Aurelia aurita, in relation to its ambient environment. Hydrobiologia, 451, 229-246. Mace, P. M. (2001). A new role for MSY in single-species and ecosystem approaches to fisheries stock assessment and management. Fish and Fisheries, 2, 2-32. Mackay, D. (2001). Multimedia Environmental Models. The Fugacity Approach, 2nd ed. Lewis Publishers, Boca Raton, FL, USA, 272. Martinussen, M. B. & Båmstedt, U. (1999). Nutritional ecology of gelatinous planktonic predators. Digestion rate in relation to type and amount of prey. J. Exp. Mar. Biol. Ecol., 232, 61-84. Menshutkin, V. V. (1971). Mathematical modelling of populations and communities of aquatic animals. Leningrad (in Russian). Mills, C. E. (1995). Medusae, siphonophores, and ctenophores as planktivorous predators in changing global ecosystems. ICES J. Mar. Sci., 52, 575-581. Moen, F. E. & Svensen, E. (2004). Marine fish and invertebrates. AquaPress, Essex, 608. Monte, L. (1995). A simple formula to predict approximate initial contamination of lake water following a pulse deposition of radionuclide. Health Phys., 68, 397-400. Monte, L. (1996). Collective models in environmental science. Sci. Total Env., 192, 41-47. Monte, L., Brittain, J. E., Håkanson, L. & Gallego, E. (1999). MOIRA models and methodologies for assessing the effectiveness of countermeasures in complex aquatic systems contaminated by radionuclides. ENEA, RT/AMP, 150. Nelson, W. G. & Bonsdorff, E. (1990). Fish predation and habitat complexity: are complexity thresholds real? J. Exp. Mar. Biol. Ecol., 141, 183-194. OECD. (1982). Eutrophication of waters. Monitoring, assessment and control. OECD, Paris, 154. Persson, J., Håkanson, L. & Pilesjö, P. (1994). Prediction of surface water turnover time in coastal waters using digital bathymetric information. Environmetrics, 5, 433-449. Persson, L. & Eklöv, P. (1995). Prey refuges affecting interactions between piscivorous perch and juvenile perch and roach. Ecology, 76, 70-81. Peters, R. H. (1991). A Critique for Ecology. Cambridge Univ. Press, Cambridge, 366. Pilesjö, P., Persson, J. & Håkanson, L. (1991). Digital sjökortsinformation för beräkningar av kustmorfometriska parametrar och ytvattnets utbytestid. National Swedish Environmental Protection Agency (SNV) Report no. 3916, Solna, Sweden, 76. (in Swedish). Purcell, J. E. (2003). Predation on zooplankton by large jellyfish, Aurelia labiata, Cyanea capillata and Aequorea aequorea, in Prince William Sound, Alaska. Mar. Ecol. Prog. Ser., 246, 137-152. Remane, A. (1934). Die Brackwasserfauna. Verh. Dtsch. Zool. Ges., 36, 34-74. Riley, E. T. & Prepas, E. E. (1985). Comparison of the phosphorus-chlorophyll relationships in mixed and stratified lakes. Can. J. Fish. Aquat. Sci., 42, 831-835. Rout, N. P. & Shaw, B. P. (1998). Salinity tolerance in aquatic macrophytes: probable role of proline, the enzymes involved in its synthesis and C4 type of metabolism. Plant Sci., 136, 121-130. Rout, N. P. & Shaw, B. P. (2001). Salt tolerance in aquatic macrophytes: possible involvement of the antioxidative enzymes. Plant Sci., 160, 415-423.
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Sandberg, J., Elmgren, R. & Wulff, F. (2000). Carbon flows in Baltic Sea food webs – a reevaluation using a mass balance approach. J. Mar. Syst., 25, 249-260. Savino, J. F. & Stein, R. A. (1989). Behavioural interactions between fish predators and their prey: effects of plant density. Animal Behav, 37, 311-321. Schneider, G. (1989). Estimation of food demands of Aurelia Aurita medusae populations in the Kiel Bight/Western Baltic. Ophelia, 31, 17-27. Schneider, G. & Behrends, G. (1994). Population dynamics and the trophic role of Aurelia aurita medusae in the Kiel Bight and western Baltic. J. Mar. Sci., 51, 359-367. Smith, V. H. (1979). Nutrient dependence of primary productivity in lakes. Limnol. Oceanogr, 24, 1051-1064. Sogard, S. M. & Able, W. (1991). A comparison of eelgrass, sea lettuce macroalgae, and marsh creeks as habitats for epibenthic fishes and decapods. Estuar. Coast. Shelf Sci., 33, 501-519. Suchman, C. L. & Brodeur, R. D. (2005). Abundance and distribution of large medusae in surface waters of the northern California Current. Deep-Sea Res., II 52, 51-72. Vollenweider, R. A. (1968). The scientific basis of lake eutrophication, with particular reference to phosphorus and nitrogen as eutrophication factors. Tech. Rep., DAS/DSI/68.27, OECD, Paris, 159. Wallin, M., Håkanson, L. & Persson, J. (1992). Belastningsmodeller för närsaltutslepp i kustvatten – speciellt fiskodlingars miljöpåverkan. Nordiska ministerrådet, 1992, 502, Copenhagen, 207 (in Swedish). Walters, C. J., Christersen, V. & Pauly, D. (1997). Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Rev. Fish Biol. Fish., 7, 139-172. Walters, C. J., Christersen, V., Pauly, D. & Kitchell, J. F. (2000). Representing density dependent consequences of life history strategies in aquatic ecosystems: Ecosim II. Ecosystems, 3, 70-83. Winberg, G. G. 1985). Main features of production process in the Naroch lakes. Ecological system of Naroch lakes. Minsk, 269-284 (in Russian). Winfield, I. J. (2004). Fish in the littoral zone: ecology, threats and management. Limnologica, 34, 124-131.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 119-151 © 2011 Nova Science Publishers, Inc.
Chapter 4
FORM AND FUNCTIONING OF MICRO SIZE INTERMITTENT CLOSED OPEN LAKE LAGOONS (ICOLLS) IN NSW, AUSTRALIA
1
W. Maher1, K. M. Mikac2, S. Foster1, D. Spooner1 and D. Williams1
Ecochemistry Laboratory, Institute for Appled Ecolgy, University of Canberra, Bruce, ACT, Australia. 2 Institute for Conservation Biology and Environmental Management, University of Wollongong, Wollongong, NSW, Australia.
ABSTRACT ICOLLs are considered to be one of the most ecologically productive ecosystems on earth. Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters. ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea. Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. The focus for this chapter is micro size ICOLLs, classified as any coastal water body that has: (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels.
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W. Maher, K. M. Mikac, S. Foster et al. ICOLLs can be viewed in a hierarchical manner, with the ocean and catchment influencing other smaller scale processes. Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and seston within an ICOLL. Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions. In turn, these attributes determine the biological diversity and functioning of these systems.
1. INTRODUCTION AND DEFINITION Intermittently Closed and Open Lake Lagoons (ICOLLs) are a common feature of the NSW coastline, occupying approximately 92 % of all New South Wales estuarine waters (Williams et al., 1998). ICOLLs are coastal bodies of saline water (Figure 1), either wholly or partially separated from the adjacent sea, by one or more restricted inlets (Bird, 1967a, b, 1994; Mee, 1978). They are characterised as having largely varying salinities e.g. hyposaline to hypersaline (Kjerfve, 1986, 1994; Bamber, 1998), and often as being stagnant and brackish (ie: 5-20ppt) in nature (Ward and Ashley, 1989; Tagliapietra et al., 2009). ICOLLs are considered to be one of the most ecologically productive ecosystems on earth (Boynton et al., 1996). Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters (Edgar and Barrett, 2000). ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea (Kjerfve and Magill, 1989; Cognetti and Maltagliati, 2000). Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. On the south eastern coast of NSW they provide a habitat for commercially important fish stocks (Griffiths, 2001), and are sanctuaries for many migrating demersal nektonic species (e.g. shrimps, crabs, spots, flounders) that depend on shallow lagoonal habitats as nursery areas for early development (Boynton et al., 1996). Of all the systems that are inherent to the coastal environments, ICOLLs have the greatest potential to become eutrophic (Comin and Valiela, 1993; Boynton et al., 1996; Menendez and Comin, 2000). Reduced flushing, shallow waters, and often silt/clay sediment composition all contribute to accelerate eutrophication. NSW coastal lakes are under immense pressure, and almost all have been modified with approximately 60% classified as degraded and in need of comprehensive or significant protection (HRC, 2002). One of the main problems associated with this assessment was the lack of data for micro size ICOLLs along the south coast of NSW, which highlight the requirement for future research priority. To provide the focus for this chapter a micro size ICOLL will be classified as any coastal water body that has:
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 121 (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels.
Figure 1. Morphology and sediment facies of micro-size ICOLLs. A: Brackish Creeks (Wimbie Creek); B: Broad Basins (Kianga Lake); C: Floodplain brackish creeks (Congo Creek)
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Figure 2. Hierarchical effects in ICOLLs
ICOLLs can be viewed in a hierarchical manner; with the ocean and catchment influencing other smaller scale processes (see Figure 2). Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and plankton within an ICOLL (Kench 1999; Loneragan and Bunn 1999; Roshanka and Pattiaratchi 1999; Cooper 2001; Roy et al. 2001). Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition (Harris 2001b). In turn, these attributes determine the biological diversity and functioning of these systems. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions (Cooper 2001).
2. PHYSICAL FEATURES ICOLLs are located at the transitional zone between rivers and oceans and often act as net sinks of land derived sediment and nutrient inputs (Kennish, 1986; Kjerfve, 1994). ICOLLs may have one or multiple entrances to the sea that are intermittently open or closed to the ocean (Kench, 1999). These shallow systems are often found behind barrier islands and sand spits and are conspicuous physiographic features of continental land margin around the world (Boynton et al., 1996). The movement of sediment into these water bodies is part of an evolutionary process and changes the morphology and bathometry of the ICOLL basin (Kennish, 1986). Accelerated
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 123 infilling caused by increased catchment sediment loads can sometimes ‗in fill‘ coastal ICOLLs, although the isolation of the water body from the ocean is the true cause of their demise (Hodgkin, 1998). The different stages of isolation of ICOLLs to the ocean have also been attributed to differences in ICOLL volume and varying catchment discharges (i.e. sporadic or consistent) (Hodgkin, 1998). The location of the ICOLL entrance in relation to the inherent coastal features that shelter them from prevailing wind and ocean waves is also an important physical aspect of ICOLLs (Hodgkin, 1998). The formation of the barrier that restricts oceanic exchange is reliant on shoreline drift of marine sands that accumulate at the entrance of the ICOLL (Kennish, 1986). During high river discharges the barrier can be breached allowing tidal inflow and exchange. Understanding of the ecological and hydrological consequences of these breaches within south eastern Australian ICOLLs are limited (Pollard, 1994; Wiecek and Floyd, 2006; Gale et al., 2007). In Australia, ICOLLs are found where high wave energy, microtides (ie: tidal amplitude <2 m), low fluvial discharge and low coastal relief dominate (Bayly, 1971; Digby et al., 1999). These oceanographic and terrestrial forces act synchronously to produce ICOLLs (Bird, 1967a, 1994; Digby et al., 1999). In Australia, ICOLLs are noticeably absent on coastlines characterised by high retreating cliffs e.g. Great Australian Bight, and where macrotides dominate e.g. Northern Australia (Bird, 1994; Digby et al., 1999). Bird (1967a) demonstrated that ICOLLs are well represented throughout the southern seaboard of Australia, and although a great variation in lagoon morphology occurs, similar general physico-chemical and biological processes operate in most south eastern Australian ICOLLs.
3. MORPHOLOGY ICOLLs display high morphological variability (Figure 1 and 3), and have been previously described as either brackish creeks (Stanton et al. 1999), or barrier lagoons (Bird 1994; Kjerfve 1994; Cooper 2001). Brackish creeks are typically narrow creeks with a single entrance to the ocean, usually with a sand bar built up to around the high tide level (Stanton et al. 1999). Brackish creeks are also usually narrow shallow channels that have a small surface area (Stanton et al. 1999; Mikac et al. 2007). Barrier lagoons on the other hand can have single or multiple entrances with a narrow entrance opening out to a larger shallow lagoon/lake (Kjerfve 1994). Digby et al. (1999) and Gregory and Petrie (1994) described numerous physical characteristics that can be easily measured to define the morphology of estuaries, some of which are pertinent to ICOLLs (e.g. Haines et al. 2006). The morphological features that best classify micro sized ICOLLs on the south east coast of New South Wales are: Cross sectional ratio – ratio of average width of the ICOLL to the average width of the mouth. Describes the general shape of the lagoon i.e. values <1 indicate a narrow entrance opening out into a wide lagoon, whereas values >1 indicate a wide entrance narrowing toward the back. ICOLLs with a value <1 would tend to restrict tidal flow when open while ICOLLs with values >1 would facilitate tidal flushing (Gregory and Petrie 1994).
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W. Maher, K. M. Mikac, S. Foster et al. ICOLL surface area (km2) – Measurement of the surface area of the ICOLL (Digby et al. 1999). Length to width ratio – length to width ratio is an indicator of the geometry of the ICOLL i.e. long and narrow to short and wide (Gregory and Petrie 1994). Fluvial flow – Fluvial flow is a ratio of mean annual rainfall runoff to the volume of the lagoon. Fluvial flow is an indication of the ICOLLs buffering capacity i.e. ICOLLs with low fluvial flow have smaller volumes of water entering from the catchment in comparison with the ICOLLs volume therefore, expected changes in the water characteristics (salinity) would be attenuated (Digby et al. 1999). Fluvial flow is calculated using the equation: FF = (P × A × Ceff) ÷ V
Figure 3. Cross sections of the berm (entrance channel), middle and basin in ICOLLs. A: Brackish Creeks (Wimbie Creek); B: Broad Basins (Kianga Lake); C: Floodplain brackish creeks (Congo Creek).
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 125 Where FF is fluvial flow; P is the mean annual precipitation; A is the area of the catchment under a single land use; Ceff is the rainfall runoff coefficient for the land use; V is the volume of the ICOLL. Three main morphologies are present in ICOLLs of the southeastern coast of NSW, and have been classified based on their physical features as brackish creeks, lake lagoons and floodplain lagoons (Figure 1). The morphology of ICOLLs is a reflection of the topography of the catchment. Brackish creeks characteristically have high cross sectional ratios and high fluvial flows, which together with their small water volumes have little capacity to attenuate inputs from the catchment or the ocean. Brackish creeks have pronounced boom bust cycles and are highly variable environments in respect to their water quality (Foster, 2002; Mikac et al. 2007). Brackish creeks tend to occur in coastal environments with steep catchments with little to no flood plain, these are the most common type of ICOLL occurring on the south east coast of NSW. Lake lagoons characteristically have large surface areas and high length to width ratios and low fluvial flows. Lake lagoons are the most stable type of small ICOLL (i.e. <0.5 km2) in respect to their water quality as they have greater buffering capacity due to their large water volumes, which acts to attenuate inputs (i.e. smaller oceanward openings in relation to their body and low fluvial inputs in relation to their volume). Lake lagoons typically occur in moderately sloped catchments with some flood plain development. Floodplain lagoons occur in large catchments with low catchment slopes and moderate fluvial flows. These ICOLLs are long and sinuous along their length and have well defined floodplains. Floodplain lagoons tend to be flanged with the seaward opening larger than the ICOLL body, causing greater tidal influence when the ICOLL is open to the ocean. Many of the processes involved in the geomorphological evolution of ICOLLs are similar to the processes involved in river systems (i.e. floodplain development) (Vannote et al. 1980). Lake lagoon ICOLLs would be classified as being in the early to middle stages of geomorphological evolution and flood plain ICOLLs in the latter stages (Digby et al. 1999). It would be difficult to place brackish creeks into a geomorphological class due the lack of floodplain development and depositional features (Digby et al. 1999). Cooper (2001), agues that scouring during flood events would result in the removal of much of the accumulated sediments “thus resetting the evolutionary clock”. It can be expected that flood events will occur with more frequency in steeper catchments (i.e. greater fluvial flow), it would be anticipated that brackish creeks would tend not to follow the accepted hypothesis of shallowing with age (Roy et al. 2001).
4. CATCHMENT CHARACTERISTICS AND HYDROLOGICAL PROCESSES 4.1. The Influence of Catchment Characteristics on ICOLLs Catchments can be viewed as functional geographic units that integrate a variety of environmental processes and anthropogenic effects on the landscape (Post and Jakeman 1996; Aspinall and Pearson 2000). Both Edgar and Barrett (2000) and Harris (2001b) found that changes in land-use within coastal catchments affected both the quantity and quality of material entering estuaries. Estuaries form the terminal point in a catchment where all water
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leaves the river system and enters the ocean (Frissell et al. 1986). In this respect estuaries form the interface between the terrestrial and oceanic environments (Edgar and Barrett 2000; Cooper 2001). ICOLLs are often separated from the ocean by a barrier of sand, and during periods of freshwater input from the catchment, act as sinks for all the products exported (e.g. sediment, organic matter, nutrients and pollutants) (Kench 1999). As such, catchment exports play a vital role in the health and function of ICOLLs (Heap and Harris 2002). Changes in the amount of sediment, organic matter and nutrients will affect the functioning of these ecosystems, by altering their physical, chemical and biological nature (Hopkinson Jr and Vallino 1995; Harris 2001a, b; Cooper 2001). The physical features of a catchment such as slope, land cover, soils types, drainage density, shape and size of the catchment, as well as urban infrastructure govern the movement of water and associated constitutes (i.e. sediment, nutrients and organic matter) through the catchment (Calow and Petts 1994; Post and Jakeman 1996; Harris 2001b; Jennings and Jarnagin 2002). The volume and velocity of water through the catchment is crucial in determining the morphology of ICOLLs, such as the shape of the water body, entrance morphology, internal depositional characteristics and the opening and closing regimes of the ICOLL (Bell and Edwards 1980; Sklar and Browder 1998; Cooper 2001, Roy et al. 2001).
4.2. Catchment Hydrology Australia is the driest inhabited continent, with a large variation in runoff compared to the rest of the world. Many of Australia‘s rivers and streams are ephemeral. Hydrographs often show a rapid rise in stream level followed by a sharp decline with long periods of little or no flow (Croke and Jakemen 2001). ICOLLs receive most of their freshwater input during high rainfall events (Pollard 1994). As a result of their small catchment areas, ICOLL inlets are often blocked for extended periods by sand deposited by wave action. They are only open when there is a sufficiently large storm where storm water inflow raises the water level such that the berm is breached or when there are large waves overtopping the berm. The unpredictable nature of rainfall on the South Coast of NSW results in erratic opening of ICOLLs. The frequency and magnitude of rainfall events determines the frequency of entrance opening. Under low stream flow conditions, water inputs are balanced by water losses through evaporation and seepage and the entrance remains closed (Figure 4a). Wave energy will maintain the berm and over washing will top up lagoons and maintain brackish water conditions. Storm events of sufficient magnitude will incise a channel and cause the berm to breach (Figure 4b). The depth of incision will determine how much of the ICOLL is drained. Wave action will normally re-establish the berm within 1-2 weeks and the lagoon water level will remain low unless refilled by runoff or tidal exchange (Figure 4c). Streams and rivers serve as rapid conduits for water and anthropogenic nutrients to estuarine and coastal marine environments (McMahon, 1998; Smith, 1999). Slope determines the velocity of the surface runoff that governs the erosive potential and the transport capacity of the flow (Lepisto et al., 1995; Croke and Jakeman, 2001). Hill slope erosion across Australia has increased 100-fold in historical times as a result of catchment clearing and agricultural land use (Prosser, 2001). Smaller catchments are often steeper which tends to
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 127 induce greater sediment movement and subsequent sediment yield. During periods of high rainfall and runoff, exports of sediment, nutrients and organic matter tend to be higher (Harris 2001a, b). This often causes characteristic sediment plumes from the river into the ocean from estuaries, however, as ICOLLs are closed for the majority of the time, these sediments and associated material are trapped within the ICOLL and can have a great affect upon the water quality and sediment composition within the ICOLL.
Figure 4. ICOLL hydrology. A: ICOLL full; B: Berm breeched; C: Berm rebuilt, ICOLL drained (Wimbie Creek)
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5. PHYSIOCHEMICAL FEATURES The physicochemical composition of ICOLLs is highly variable (Figure 4) depending on runoff, wave action and whether the ICOLL entrance is open or closed (Mikac, 2001; Foster, 2002). The period of closure will also influence water composition (Wiecek and Floyd, 2006; Scanes et al., 2007).
5.1. Salinity and pH Salinity regimes within ICOLLs depend on the ratio of fresh water inflow, overtopping, tidal exchange and evaporation. If the entrance is closed and stream flow is low, ICOLLs are generally brackish (15-25 % S) and increase in salinity over time if evaporation exceeds the fresh water input. ICOLLs can also be stratified with a denser saline layer (36 % S) in deeper areas. Increased stream flow can result in a surface layer of fresh water or a reduction in salinity. It is common to find a lens of nearly fresh water (8-10 % S) over a deeper layer of brackish water (16-25 % S). Once the berm is breached, the ICOLL can become completely fresh although saline layers in deeper areas will persist. Depending on how long the entrance is open, tide height and storm activity, salinity can vary from brackish to sea water due to over washing and tidal exchange. pH will also change with variations in storm water inflows and salinity. Fresh water pH varies between 5.5-6.5 while brackish water tends to have a similar pH to sea water (pH 8).
5.2. Temperature The temperature of the bulk of ICOLL water generally reflects the ambient air temperature and varies seasonally from 5 - 40 oC. However, overtopping or filling by seawater can substantially modify water temperature depending on the ambient seawater temperature. Seawater temperature along the South Coast varies from to 11 -21 oC and doesn‘t follow a seasonal pattern. Thus ICOLL water temperature will be highly dependent on if the ICOLL is open or closed. the period of closure and prevailing sea water temperature. Similarly, water temperature of the deep saline layer, if present, will be also depend on the ambient seawater temperature. These deep saline layers can be warmer than the overlying water depending on the seawater temperature, ambient air temperature and decomposition of organic matter, which generates heat.
5.3. Dissolved Oxygen Dissolved oxygen concentration is also highly variable depending on the source of the water, ambient temperature, water stratification and biological activity. Normally if ICOLLs are open or surface flow is occurring, dissolved oxygen concentrations are 40-100% saturation. Over washing of seawater raises the oxygen levels, as seawater is generally 100% saturated with oxygen. Catchment runoff brings water in that is oxygen saturated but also
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 129 brings in organic matter that through respiration lowers oxygen concentrations. On closure, ICOLLs oxygen concentrations can vary from 0-140 % saturation. Over a 24 hour period, oxygen concentrations can drop to 0 % saturation at night especially if a deep stratified saline layer is present, and depending on the presence of algae recover to 50-80 % saturation during day light hours. Prolonged deoxygenation will led to the mortality of organisms while hypoxia (< 10% saturation) will effect growth, feeding and metabolic rates (Gray et al. 2002). Many ICOLLs have extensive mats of benthic attached algae during summer. In shallow, non turbid ICOLLs, oxygen concentrations can become supersaturated (100-140%) due to algae photosynthesis.
5.4. Nutrients As most nutrients enter ICOLLs bound to suspended particulates, the concentration of dissolved phosphorus (< 1 g/l), dissolved nitrogen (5-10 g/L) and ammonia (2-10 g/L) are normally low (Mikac, 2001; Foster, 2002; Mikac et al., 2007). Inputs of dissolved nutrients from septic sewage systems and sewer overflows during periods of high rainfall can result in short lived elevation of nutrient concentrations (P: 3-5 g/L; N: 20-30 g/L) especially ammonia (20-90 g/L). Low water column nutrient concentrations limit phytoplankton growth such that attached benthic algae are the most common algae growth (Nozais et al. 2001).
5.5. Colour During periods of low flow, ICOLLs are generally non-turbid and highly coloured from the release of tannins from decomposing organic litter. Together with the low soluble nutrient concentrations, tannins may limit phytoplankton growth. We have shown in our laboratory that the growth of algae species such as Chaetamorpha, Oscillatoria and E. ralfsii are inhibited by highly coloured water derived from tannins (Dalton et al. unpublished).
6. SEDIMENT COMPOSITION 6.1. Grain Size Patterns of sedimentation in coastal water bodies are highly heterogeneous and vary according to hydrological processes e.g. river discharge, tidal flow and catchment inputs (Dyer, 1979). Bird (1994) proposed a general sedimentation model for ICOLLs. This model suggested that coarser material e.g. sand and gravel, is deposited as the river/creek enters the lagoon, while the finer sediment e.g. silt/ clay, is carried out into the lagoon and deposited throughout the central basin. Sediments enter coastal lagoons from oceanic and fluvial sources (Bird 1967b; Kennish 1986). The terrestrial and coastal geology influence the types of sediments available for transport (Thornton et al. 1995). A number of factors can affect the transport and spatial
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distribution of sediments in ICOLLs e.g. salinity, surface runoff, tidal influence (Dyer 1979; Thornton et al. 1995; Kench 1999). In general, coarse sediments of fluvial sands and gravel are deposited where the river meets the lagoon, the finer sediments of silt and clay are carried further and, through the process of flocculation, deposited within the central basin, with wave action carrying oceanic sand into the mouth of the lagoon (Dyer 1979; Bird 1994). Sediments are a depository for organic matter, nutrients and contaminants (Thornton et al. 1995). The sediments in microsize ICOLLs consisted mainly of sand at the seaward end with increasing silt upstream (Figure 1). This is typical of south eastern Australian coastal lagoons (e.g. Allan et al., 1985) from which marine sand is transported (and eventually deposited) into ICOLLs by ocean currents and wave action (Owen, 1978). However, Mikac et al. (2007) found that the ICOLLs in catchments dominated by urban development had greater % silt/clay. Silt/clay is a covariate of urbanisation, where % silt/clay increases as urbanisation increases (Edgar and Barrett, 2000). Hume and McGlone (1986) have shown that the deforestation of catchments for urban development increases the peakedness and frequency of catchment high flows and results in an increase in the loads of fine sediment deposited into coastal water bodies. Once the catchment is developed the soil is stabilised, however, the peakedness of flows increases further because of the development of sealed areas and stormwater systems (Hume and McGlone, 1986). Stormwater systems, of urbanised areas in particular, are known to carry large quantities of fine sediment, organic material, nutrients and contaminants to coastal water bodies (Dennison and Abal, 1999). In addition, Mikac et al. (2007) found that an increase in the % silt/clay of sediments was associated with an increase in sediment total organic carbon, nutrient (total nitrogen and phosphorus) and trace metal concentrations (lead, copper, cadmium and zinc). It should be noted that concentrations of these nutrients and trace metals did not exceed benchmark levels as recommended by Australian water and sediment quality guidelines (ANZECC/ARMCANZ, 2000). Rather, silt and clay have a large sorption capacity and thus locations with greater % silt/clay have a greater potential to bind and scavenge organic matter, nutrients and trace metals (Kennish, 1986; Arakel, 1995). In particular, fine sediments have an immense sorption capacity because of their large surface area to volume ratio and high surface charge to mass ratio (Arakel, 1995). The effects of ICOLL opening and closing on the sediments of the system are vast. If an ICOLL is closed for extended periods, the system will be subjected to greater influence of land derived sediments (usually fine sediments) that accumulate in the absence of diurnal tidal scouring and near coast sand deposition.
6.2. Nitrogen and Phosphorus Phosphorus and nitrogen are considered macronutrients, as they are essential for biological processes (Deeley and Paling 1999). Typically in uncontaminated ICOLLs, nitrogen and phosphorus concentrations vary from 20-100 and 5-80 g/g respectively with higher concentrations in silt than sand. Nutrients enter ICOLLs attached to sediments, humic material or in organic matter, either through catchment runoff, inputs from the ocean, precipitation or the decomposition of biota (Kennish 1986; Thornton et al. 1995). Most nutrients entering ICOLLs are found in the finer sediments of silt and clay (Thornton et al. 1995; Harris 2001b). Nutrients can be reintroduced into the water column by chemical,
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 131 physical and biological processes such as changes in pH and redox, bioturbation and bioirrigation (See Section 6.4; Thornton et al. 1995). Under oxic conditions, phosphorus is usually bound with iron (Fe) in the sediments and nitrate converted to nitrogen gas through the process of denitrification (Aston 1980; Heggie et al. 1999). Under low pH and/or anoxic conditions phosphorus can be liberated from sediments and nitrogen released into the water column as ammonia (Figure 5 and 6) (Aston 1980; Hatcher 1994; Thornton et al. 1995; Heggie et al. 1999). ICOLLs are generally nitrogen limited, with increases in nitrogen shown to stimulate algal growth (Harris 2001b). Nutrient concentrations within ICOLLs sediments have been shown to be highly seasonal and ICOLL specific (e.g. Schallenberg et al., 2010).
6.3. Organic Matter Organic matter enters estuaries both internally through the decay of fauna and fauna and externally through inputs from the catchment (leaf litter fall, leaching of soils) and ocean (seaweed, biota) (Kennish 1986). Typically in uncontaminated ICOLLs, organic carbon concentrations vary from <0.01-10 % respectively with higher concentrations in silt relative to sand. Large quantities of organic matter can enter ICOLLs during periods of high fluvial inputs (Day 1981) and in some ICOLLs the extensive accumulation of dead seaweed also occurs. Within estuaries organic matter is the primary food source for many benthic organisms (Morrisey 1995). Large quantities of organic matter can adversely affect water quality by producing anoxic conditions leading to sulphate reduction and the production of hydrogen sulphide gas (H2S) (Burton 1976). Hydrogen sulphide per se, should not be viewed as a problem as some polychaete species eg Capitella sp. require hydrogen sulphide as a settlement cue (Cuomo, 1985).
6.4. Biogeochemical Nutrient Cycles Benthic sediments in shallow coastal embayments (i.e. ICOLLs) are the primary site for the mineralisation of organic matter (Fisher et al., 1982; Jorgensen and Revsbech, 1989; Heggie, 1999). These processes are primarily mediated by bacteria and contribute, together with catchment discharges, to the nutrient concentrations in the water column.
6.4.1. Nitrogen Inorganic nitrogen species NO3- and NH3+ are the most important because they are readily available for biological uptake (Herbert, 1999). Currently, the consensus is that denitrification ie the release of nitrogen as nitrogen gas, in closed systems with restricted oceanic exchange, plays a vital role in regulating, or removing, nitrogen out of the aquatic cycle (Figure 5). This is especially apparent in shallow Australian coastal systems where denitrification is primarily a sedimentary based process (Heggie et al., 1999).
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Figure 5. Nitrogen cycling in response to organic carbon loading
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Figure 6. Phosphorus cycling in response to organic carbon loading
During the cooler months of the year, or when labile organic matter is unavailable, bacterial metabolic activity is low, and the water column is well oxygenated. This situation promotes deep penetration of oxygen into benthic sediments that is utilised by bacteria to oxidize organic matter (ammonification), which is then oxidized further by nitrifying bacteria
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to nitrate (nitrification). In the anoxic microzones, which are vertically and horizontally distributed throughout the sediment profile, denitrifying bacteria reduce the nitrate to nitrogen gas that is released to the atmosphere (denitrification) (Figure 5a). Under these conditions biologically available nitrogen concentrations in the water column remain stable, and often limit phytoplankton and microphyte production. Once water temperatures increase and a source of organic carbon is available, the metabolic activity of heterotrophic bacteria increases and oxygen in the sediment profile is restricted to the surficial zone. Under these conditions, ammonification and nitrification is reduced and denitrification ceases (Figure 5b). Alternate electron acceptors are employed by the bacteria to mineralize the organic matter, and sulphate is the most likely source. Sulphate reduction of organic matter releases ammonia to the water column, which is directly available for biological uptake (Figure 5c). Large fluxes of ammonia to the overlying water column occur that support algal blooms and cause fish kills.
6.4.2. Phosphorus Organic carbon inputs also control the mobilisation of phosphorus from ICOLL sediments into overlying water. During the cooler months of the year, or when labile organic matter is unavailable, bacterial activity is low, and the water column is well oxygenated and little phosphorus is released. Sediments are oxidised and phosphorus complexes with iron. Thus phosphorus is effectively trapped in sediments (Figure 6a). When ‗fresh‘ labile organic matter is deposited to marine sediments oxygen is consumed and phosphorus is released from organic matter and iron oxide phases (Figure 6b). Under anoxic conditions H2S is formed and reacts with iron-phosphorus complexes. The capacity of the sediment to retain the phosphorus is drastically reduced and a larger phosphate fluxes occurs (Figure 6c). The mineralisation of organic matter and desorption from inorganic complexes have been identified as major sources of phosphorus for phytoplankton production in coastal marine environments (Nixon, 1981; McComb, 1998).
7. BIOLOGICAL FEATURES 7.1. Food Webs The biota of brackish ICOLLs comprises relatively few species when compared to stable marine habitats (Hammond and Synnot, 1994). Salinity is the prime factor in determining the types of organisms within ICOLLS. Organisms within ICOLLs need to cope with varying salinity and usually are opportunists such as polychaetes and shrimps, adapted to exploit space and resources following disturbances ie opening and closing regimes (Boesch, 1977). Generally, food webs in micro size ICOLLs are detritus based relying on allochthonous inputs from both terrestrial and marine sources (Hadwen and Arthington, 2006), as phytoplankton abundance is low because of low water column nutrient concentrations and tannins (see Section 5.4 and 5.5). Benthic communities dominate micro size ICOLLs with attached algae, microphytobenthos (Figure 7) and meso- and macro invertebrates being the dominant organisms (Figure 8). Fish that are mobile and efficient osmoregulators also thrive in ICOLLs (Figure 9) (Hadwen and Arthington, 2006).
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Figure 7. Typical algae and plants in ICOLLs
7.2. Algae and Plants As ICOLLs are relatively unstable environments and considerable redistribution of sand and sediment occurs, it is rare to find extensive seagrass beds or mangroves within microsize ICOLLs. Where these do occur in ICOLLs, it is in stable areas in which sand or sediment has accumulated and not remobilised. Fringing vegetation tends to be salt tolerant terrestrial species such as sedge, Juncus and Salt Bush (Atriplex). As mentioned in Section 5, phytoplankton abundance is normally low because of the low water column nutrient concentrations (Nozais et al. 2001) and the presence of tannins. Phytoplankton abundance tends to be higher in winter months than in summer months. Phytoplankton species abundance will be a function of ICOLL pH. Although some species grow well over a wide range of pH (6-10), some species growth rates are significantly
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influenced by pH (Hinga, 2002) with pH changes of 0.1 units causing observable changes in phytoplankton community structure. Any freshwater phytoplankton carried into ICOLLs die at salinities greater than 8% S (McLusky, 1989). Also in some ICOLLs it has been found that phytoplankton growth is governed by the opening and closing regimes of the system, with some ICOLLs experiencing greater phytoplankton chlorophyll a concentrations during closure with the opposite being found for others (Schallenberg et al., 2010). Nitrogen and phosphorus limitation and/or light limitation were other factors that were found to alter phytoplankton growth in ICOLLs (Everett et al., 2007; Schallenberg et al., 2010). Benthic attached filamentous algae such as Enteromorpha sp. form extensive mats in warmer months and decline in autumn. Microphytobenthos have been reported in the literature to exhibit strong seasonal fluctuations and not to be inhibited by low water column nutrient concentrations or light availability (Nozais et al 2001). Large populations of microphytobenthos (diatoms and other micro algae) also occur in silty-sandy sediments up to depths of 20 cm. These algae play an important role in maintaining the surface of sediments and overlying water in an oxygenated state (Peckol and Rivers, 1996) and are an important food source for macroinvertebrates. Little information is known about algal recruitment, competition or predation, the effects of disturbances and changes in pH, salinity and temperature in micro size ICOLLs. All of these factors are known to cause changes in the distribution and abundance of phytoplankton, filamentous algae and microphytobenthos (Hamilton et al. 2000). Processes are likely to be different in different ICOLLs.
7.3. Soft Sediment Macrofauna Soft-sediment macrofauna are marine invertebrates that live within the sediment bed that are retained on 1 or 0.5 mm sieves (Snelgrove and Butman, 1994). It has been suggested that the soft-sediment macrofauna when coupled with an assessment of their habitat parameters may be used as reliable indicators of anthropogenic or natural disturbance (e.g. Warwick, 1986, 1993; Deeley and Paling, 1999). In the microsize ICOLLs of southeastern Australia, Mikac et al. (2007) found a total of 20, 253 individuals belonging to 12 marine invertebrate families (Figure 8). The macrofaunal communities of the five ICOLLs examined consisted of polychaetes (Capitellidae, Nereididae, Sabellidae, Spionidae and Serpulidae), gastropods (Haminoeidae and Hydrobiidae), bivalve molluscs (Galeommatidae and Mytilidae) an amphipod (Melitidae) and isopod crustaceans (Cirolanidae and Sphaeromatidae). The macrofaunal assemblages of the microsize ICOLLs examined by Mikac et al. (2007) were typical of meso and macrosize ICOLLs in Australia (e.g. Hodgkin and Clark, 1988; Platell and Potter, 1996; Edgar et al., 2000b). The soft-sediment macrofaunal abundance and composition of an ICOLL is usually a function of its size and opening and closing regime (Hutchings, 1999). Although not directly examined by Mikac et al. (2007), opening and closing regimes are acknowledged as having a significant effect on overall taxa richness and assemblage composition. In that, the opening and closing regime is known to affect the habitat parameters (salinity, dissolved oxygen, sediment grain size and organic carbon content) of the macrofauna and therefore have an indirect effect. This is supported by Platell and Potter (1996) who show that not only does the
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 137 closure of Wilson‘s Inlet (a mesosize ICOLL in south-western Western Australia) prevent recruitment of macrofaunal larvae into the system but also determines the salinity regime of the water body.
Figure 8. Typical benthic macrofauna in ICOLLs
It is difficult to determine which specific abiotic variable is responsible for the pattern of macrofaunal assemblages in micro size ICOLLs, however, the habitat parameters found to best explain soft-sediment macrofaunal composition in large south eastern Australian ICOLLs include water quality (salinity, dissolved oxygen) and physico-chemical sediment variables (grain size, organic carbon content) (Weate and Hutchings, 1977; Hutchings et al., 1978; Powis and Robinson, 1980; Atkinson et al., 1981; Poore, 1982; Robinson et al., 1982; Gibbs, 1986). More recent work conducted by Platell and Potter (1996) and Mikac et al. (2007) have attempted to single out the habitat parameters of the macrofauna in micro- and meso- sizel ICOLLs. Platell and Potter (1996) found that a greater number of macrofaunal species were associated with sediment composition and also the biomass of an aquatic macrophyte Ruppia megacarpa. In turn, Mikac et al. (2007) found that the macrofauna of five microsize ICOLLs examined was largely a function of sediment composition. Where fine sediment and sandy substrata dominated, opportunistic polychaete taxa e.g. spionids, capitellids, nereids, and
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mollusc taxa e.g. hydrobiids and mytilids were numerically dominant. It is possible that these opportunistic macrofaunal taxa occur in disturbed locations because of their ability to reproduce quickly in unrestricted conditions afforded by new unexploited environments (Grassle and Grassle, 1974; Pearson and Rosenburg, 1978; Barnes, 1989). In ICOLLs, where large variability in abiotic variables is common, usually due to unpredictable opening and closing regimes, it is not surprising to find taxa that have life history characteristics e.g. rselected species, that enable them to exploit such environments. Mikac et al. (2007) demonstrated that microsize ICOLLs in NSW have similar macrofaunal taxanomic assemblages as larger Australian ICOLLs. The macrofaunal assemblages are also governed by opening and closing regimes, either directly, through macrofaunal recruitment when ICOLLs are connected to the sea or indirectly, through the effect opening and closing exerts on abiotic variables (i.e. water quality and physico-sediment quality) or macrofaunal habitat parameters within these systems.
7.4. Fish To date there are no publications on the ichthyofauna of micro size ICOLLs in south eastern Australia. However, the ichthyofauna of meso size ICOLLs have been investigated by Pollard (1994) and Griffiths (1999) and (2000). Both Pollard (1994) and Griffiths (1999) found similar species in the six ICOLLs examined by the authors. Both authors show that greater taxa richness and abundance of fishes occurred in the larger and more open of the ICOLLs examined. Pollard (1994) studied Lake Conjola, Swan lake and Lake Wollumboola (meso sized coastal lagoons) and found that the larger of these and the ICOLL that was open the most (i.e. Lake Conjola) had the most species and also the greatest abundance of these species. Pollard (1994) found species composition in the ICOLLs examined were similar to permanently open estuaries in eastern Australia. Griffiths (1999) found that fish abundance and taxa richness was a function of size and opening and closing regimes. In addition, the larger of the ICOLLs examined by Griffith (1999; i.e. Lake Illawarra), which was connected to the ocean more often, had a greater abundance of commercial and non-commercial species than the smaller and less frequently open ICOLL examined. The most common fish found by Griffiths (1999) in the three ICOLLs examined were Ambassis jacksoniensis (Lake Illawarra); Pseudogobius olosium (Shellharbour Lagoon); and Atherinosoma microstoma (Werri Lagoon). In addition, the commercially important species Mugil cephalus, Acanthopognus autralis and Myxus elongatus were also found. As well, both Pollard (1994); Griffiths (1999; 2001) showed that ICOLLs are important nursery areas for juvenile fish of both commercial and non-commercial significance. ICOLLs are also refugia as juvenile fish are protected from open ocean predators during ICOLL closure. Griffiths (1999) discusses the consequences of opening and closing of ICOLLs and suggests that although the consequences of such events are poorly documented in Australian ICOLLs (regardless of size), there is evidence that species composition and abundance are a function of the duration, frequency and time of ICOLL opening that may coincide with the recruitment period of a wide range of species and randomly increase the chance of other species entering the ICOLLs. As discussed in section 1.1, near shore and land based coastal processes determine the opening /closing regimes of ICOLLs. If these processes coincide
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 139 with recruitment periods of various fish species then ICOLLs that are connected to the sea are available to be recruited into. This is supported by Griffiths (2001) who found that the recruitment of Acanthopagrus australis occurred in marked phases when the ICOLL examined was connected to the adjacent sea.
Figure 9. Typical fish species in ICOLLs
Consequently the spatial and temporal variability of fish assemblages and their abundances within ICOLLs is often large because the patterns of assemblages in ICOLLs are a function of the opening and closing regimes. Not only does an intermittent opening and closing regime effect recruitment into the lagoon itself but also effects the general water quality of the lagoon. That is, when the ICOLL is closed from the adjacent sea for extended periods and freshwater versus saltwater inputs are greater, the resulting changed salinity
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profile of the ICOLL will favour euryhaline species and be detrimental to stenohaline species. The inherent variability in opening and closing regimes in ICOLLs is recognised as the driving force that determines the fish assemblages of ICOLLs, regardless of size, in south eastern Australia.
8. ANTHROPOGENIC CHANGES ICOLLs are not isolated ecosystems but intimately connected or nested within adjacent or larger systems (e.g. Frissell et al., 1986, See Section 4). ICOLLs represent systems that form part of a continuum from rivers and creeks to lagoons; from lagoons to the sea; and from the sea to the ocean (e.g. Vannote et al., 1980). These systems are inherently linked and thus a natural or anthropogenic disturbance or perturbation at one level inevitably has an effect at various other temporal and spatial scales within the system (Glasby and Underwood, 1996). Human activity in coastal catchments has been directly correlated with increased rainfall runoff and sediment loads (Hume and McGlone 1986; Harris 2001b; Jennings and Jarnagin 2002). Water carries particulate and soluble material through the catchment, into the coastal zone (Petts 1984). Alterations in the physical nature of the catchment can increase or decrease the amount of particulate and soluble material moving through the catchment, however, increased movement of material normally occurs (Petts 1984). The physical variability in ICOLLs is influenced by numerous factors whose effects coincide with different catchment characteristics that drive this variability (Cooper 2001). The morphology of ICOLLs increases the susceptibility of ICOLLs to changes in land-use (Heap and Harris 2002). Due to the presence of a barrier, ICOLLs lack tidal flushing (Cooper 2001; Heap and Harris 2002). This can lead to the build up of nutrients, sediments and other contaminants, which in turn can affect the ecological function of the ICOLLs through reduced sediment and water quality (Heap and Harris 2002). The morphology of an ICOLL can have a profound effect on the symptoms associated with eutrophication. The position of the entrance in relation to the shoreline drift can influence the opening regime; the estero can influence the exchange kinetics between the ICOLL and the adjacent ocean. Water residence time within the ICOLL influences the accumulation of organic matter, high water residence time often correspond to increased potential for eutrophication symptoms. Unlike permanently open estuaries which are flushed diurnally (Kennish, 1986), ICOLLs are usually closed off from the adjacent sea and thus susceptible to changes in land use practices in their catchments (Zann, 1995; Inglis and Cross, 2000; Mikac et al., 2007). It is widely accepted that anthropogenic activities effect estuarine ecosystems and in numerous instances have resulted in large-scale alterations of their natural communities (Edgar et al., 1998; Edgar and Barrett, 2000). Bucher and Saenger (1991) showed that 70 % of the 738 coastal water bodies dominating the Australian coastline have deforested catchments and associated poor water quality, yet they represent habitats with moderate to high fisheries and conservation value. More alarming is the recent trend in ICOLL degradation (Edgar et al., 2000; Edgar and Barrett, 2000). Zann (1995) and Hutchings (1999) reported that mesosized ICOLLs of the densely populated south eastern and western Australian coastlines are under immense threat from the adverse effects of urbanisation.
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8.1. Changes in Catchment Land-Use, Hydrology and Water Quality It is well established that deforestation associated with urban or commercial development increases the peakedness and frequency of catchment high flows and fine sediment runoff to estuaries (Hume and McGlone, 1986). Once the catchment is developed the soil is stabilised and although sediment runoff decreases, the peakedness of flows increases further because of the development of sealed areas and stormwater systems (Hume and McGlone, 1986). This is supported by numerous authors who have demonstrated that changes in land use have effects, usually considered to be adverse, on the receiving system‘s physical, chemical and biological components (Loughran et al., 1986; Hogg and Norris, 1991; Arakel, 1995; Zann, 1995; Stromberg et al., 1998; Dennison and Abal, 1999; Foster and Lees, 1999; Harris, 1999). Stormwater and sewage discharges from urbanised catchments contain fine sediments, nutrients, organic material, heavy metals, pesticides, oils and hydrocarbons (Deeley and Paling, 1999). Elevated concentrations of trace metals, toxic to fauna, are readily stored in the sediments and act as an intermittent source of contamination (Arakel, 1995; Birch, 1996, 2000). Trace metals such as cadmium, lead, copper and zinc have become serious contaminants throughout Australian coastal water bodies (Birch, 2000). Physical alterations to catchments as a result of commercial, urban or industrial development e.g. impervious surfaces, drainage systems etc., are exacerbated by urban non-point source discharges which aid in the rapid deterioration of water and physico-chemical sediment quality (Aelion et al., 1997; Corbett et al., 1997; Wahl et al., 1997; Dennison and Abal, 1999).
8.2. Changes in Biological Communities Both natural and anthropogenic disturbances may affect the overall pattern of macrofaunal assemblages temporally and spatially in an ICOLL. The habitat parameters found to explain soft-sediment macrofaunal composition in south eastern Australian ICOLLs include a combination of water quality and physico-chemical sediment variables (Weate and Hutchings, 1977; Hutchings et al., 1978; Powis and Robinson, 1980; Atkinson et al., 1981; Poore, 1982; Robinson et al., 1982; Gibbs, 1986; Mikac et al., 2007). As indicated in previous sections of this chapter, the water quality and physico-chemical sediment variables of ICOLLs are a function of opening and closing regimes and catchment activities i.e. land use. Numerous biotic indices may be used to summarise the response of organisms to anthropogenic/natural disturbance and stress. Biotic indicators of anthropogenic or natural stress or disturbance include ecological measures such as taxa richness, relative taxa abundance, taxa diversity, biomass and size strata (Deeley and Paling, 1999). Indices of biotic integrity are most popular for assessing anthropogenic disturbance/stress or ecosystem health and three biotic metrics are commonly used: (1) taxa richness and composition including indicator taxa e.g. capitellids, nereids and spionids are usually indicative of disturbed/ contaminated locations; (2) trophic composition or the proportion of taxa belonging to different feeding groups e.g. the proportion of suspension feeders compared to deposit feeders; and (3) mean abundance of individuals belonging to a particular taxonomic grouping or feeding guild (Deeley and Paling, 1999). In microsized ICOLLs in southeastern Australia,
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Mikac et al. (2007) reported a significant increase in spatial heterogeneity/variability of macrofauna between control and impact (urban) locations. The author found that in impacted locations there was a shift towards more opportunistic taxa e.g. polychaetes, compared to the less opportunistic/conservative taxa found at control locations. Others have found that in anthropogenically disturbed locations opportunistic polychaete e.g. spionids, capitellids, nereids, mollusc e.g. hydrobiids (Pearson and Rosenburg, 1978) and mytilid taxa (Grassle and Grassle, 1974; Desrosiers et al., 1990), numerically dominate. The combined effects of urban/commercial/industrial development on the macrofauna of coastal water bodies have been difficult to determine (Edgar and Barrett, 2000; Inglis and Kross, 2000). However, numerous correlative and descriptive publications have provided convincing evidence to demonstrate a direct link between changes in community composition e.g. increase in opportunists usually deposit feeding polychaetes, and reduced water and physico-chemical sediment quality e.g. organic contamination (Grassle and Grassle, 1974; Pearson and Rosenburg, 1978) and trace metal contamination (Inglis and Kross, 2000). The observed decline in suspension feeders and the increase of deposit feeders in organic and/or contaminant rich sediments is widely accepted (Pearson and Rosenburg, 1978; Warwick, 1986; Clarke and Warwick, 1994; Inglis and Kross, 2000). That is, there is a change from large bodied, long-lived, iteroparous k- selected species to r-selected species (MacArthur and Wilson, 1967; Pianka, 1970). The later are characteristically small bodied, short-lived species that are able to reproduce quickly and readily colonise disturbed locations (MacArthur and Wilson, 1967; Pianka, 1970). The spatial distribution of environmental variables and contaminants within coastal water bodies is variable, with the foci of accumulation occurring near major sources of contamination or in depositional environments where fine sediments and organic matter accumulate (Morrisey et al., 1994; Inglis and Kross, 2000). Inglis and Kross, (2000) proposed that if contaminants are haphazardly distributed, changes in the soft-sediment macrofauna will be characterised by an increase in the spatial variability of assemblages from degraded sites. This tenet is based on work conducted by Caswell and Cohen (1991) who demonstrated that in patchy environments, disturbance can generate heterogeneity both spatially and temporally in local macrofaunal community structure (Caswell and Cohen, 1991). In the absence of disturbance the once patchy and heterogeneous habitats converge to form a uniform landscape (Caswell and Cohen, 1991). This is supported by Warwick and Clarke (1993) who found a marked increase in variability among macrofaunal samples from disturbed/stressed treatments. Therefore, the possible detection of habitat degradation, identified as increased spatial variability, may be achieved using spatially nested experimental designs that incorporate measures of variance within and among the effected locations or habitats (Underwood, 1997, 2000; Krebs, 1999).
9. MANAGEMENT 9.1. Flood Management Many ICOLLs are surrounded by urban areas and when development was approved often no consideration of possible inundation during extreme rainfall events was considered.
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 143 Consequently some ICOLLS are artificially opened to prevent flooding of houses and infrastructure such as roads and sewage pumping stations (Wiecek and Floyd, 2006). In these situations, ICOLLs would probably have opened naturally, thus artificial opening will make little difference to the ecology of ICOLLs. As well, flora and fauna found in ICOLLs are often species that can tolerate natural or anthropogenic disturbances (artificial openings).
9.2. Water Quality Changed land use in catchments will inevitably lead to increases in suspended solids, nutrients and altered carbon inputs (see section 8 and 9.3). Most nutrients (excluding sewage inputs) will be attached to or incorporated into particles and deposited in sediments. Micro sized ICOLLs, even after severe storm events have low water column dissolved nutrient concentrations and do not experience many phytoplankton blooms. Sediments are already relatively rich in nutrients, thus the addition of nutrient rich sediment is unlikely to alter the natural ecosystem balance. Potentially the greatest threat to ICOLLs is nutrient and reactive carbon inputs from untreated sewage from leaking septic tanks and sewage overflows. Reactive organic matter will interfere with the natural nutrient cycling processes in ICOLLs. Denitrification (see Section 6.4.1) can cease and ammonia released to the water column. As well, phosphorus can also be released to the water column (see Section 6.4.2). Consequently dissolved nutrient concentrations will be increased and phytoplankton growth favoured over the growth of benthic attached algae (Schallenberg et al., 2010). Ammonia is also toxic to marine organisms especially fish. Deoxygenation caused by decomposition of reactive organic matter can also lead to fish kills. Most ICOLLs have periods of being odorous due to hydrogen sulphide production. This is a natural phenomenon, a result of naturally high sulphide concentrations from sea water inputs and periods of anoxia. Sewage inputs would lead to longer periods of anoxia and longer periods of excessive hydrogen sulphide production. Erosion in catchments and mobilisation of sediment is also a threat to ICOLLs as smothering of habitats and infilling may occur. However, as scouring of ICOLLs often occurs when ICOLLs open, sediments are probably not as greater a threat as in poorly flushed marine lake and barrier estuaries. ICOLLs are highly variable in their water quality even when they are the same type of ICOLL and located in the same geographic area/region, therefore it is imperative that each ICOLL be managed as a single entity rather than a series of lagoons from a particular location (Scanes et al., 2007; Chuwen et al., 2009; Schallenberg et al., 2010).
9.3. Conservation A potential problem of deforestation of catchments and urbanisation is that the amount and composition (from eucalypts to introduced grasses and other plant species) of organic matter entering ICOLLs changes. Detritus based ecosystems such as ICOLLs are adapted to specific types of organic matter thus fundamental changes in ecology may occur. Broad scale clearing in catchments should be avoided and revegetation with native species encouraged preventing drastic changes in organic carbon inputs and composition. Riparian vegetation
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forms an important habitat in ICOLLs. Urbanisation leads to loss of riparian vegetation with many ICOLLs having houses built within 5-10 metres of the water body. Reestablishment and restoration of riparian buffer strips would aid in conserving biodiversity and prevent erosion of banks and channel widening. As ICOLLs are breeding grounds and refugia for fish, artificial opening of ICOLLs should be avoided as protection from open water marine predators is a feature of ICOLLs. Fish seem to survive and thrive in closed ICOLLs as long as ICOLLs do not become totally devoid of oxygen.
9.4. Amenity As described in Section 9.2, odours due to hydrogen sulphide formation are often a problem in ICOLLs. Odours are a natural phenomenon and exacerbated by anoxic conditions. However, some hydrogen sulphide is required as a settlement cue for polychaetes (Cuomo, 1985). Opening the mouth of ICOLLs to allow flushing to occur can alleviate odours. However, as mentioned above ICOLLs as refugia can be compromised. The community probably should be educated as to why odours occur and the trade off between alleviating odours and compromising biodiversity and breeding habitats. While ICOLLs are closed they may look like they are in poor condition because of scum build up and algae growth. This is a natural phenomenon and not a symptom of deterioration. Again, education is needed as to what the natural states of ICOLLs are.
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Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 151 Stanton, R., Mackenzie, D., O'Loughlin, E. & Smith, G. (1999). Water Quality Management in Urban Coastal Creeks: Objective Data for Rational In Management Decisions. In 'Second Australian Stream Management Conference': Adelaide. Stromberg, H., Pettersson, C. & Johnstone, R. (1998). Spatial variations in benthic macrofauna and nutrient dynamics in a mangrove forest subject to intense deforestation: Zanzibar, Tanzania. Ambio, 27, 734-739. Suzuki, M. S., Ovalle, A. R. C. & Pereira, E. A. (1998). Effects of sand bar openings on some limnological variables in a hypertrophic tropical coastal Lagoon of Brazil. Hydrobiologia, 368, 111-122. Tagliapietra, D., Sigovini, M. & Volpi Ghirardini, A. (2009). A review of terms and definitions to categorise estuaries, lagoons and associated environments. Marine and Freshwater Research, 60(6), 497-509. Thornton, J. A., McComb, A. J. & Ryding, S. O. (1995). The role of sediments. In 'Eutrophic shallow estuaries and lagoons'. (Ed. AJ McComb) CRC Press Florida, 206-221. Underwood, A. J. (1997). Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance, Cambridge University Press, Cambridge. Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R. & Cushing, C. E. (1980). The river continuum concept. Canadian Journal of Fisheries and Aquatic Science, 37, 130137. Wahl, M. H., McKellar, H. N. & Williams, T. M. (1997). Patterns of nutrient loading in forested and urbanized coastal streams. Journal of Experimental Marine Biology and Ecology, 213, 111-131. Ward, L. G. & Ashley, G. M. (1989). Introduction: coastal lagoonal systems. Marine Geology, 88, 181-185. Warwick, R. M. (1986). A new method for detecting pollution effects on marine macrobenthic communities. Marine Biology, 92, 557-562. Warwick, R. M. (1993). Environmental impact studies on marine communities: pragmatical considerations. Australian Journal of Ecology, 18, 63-80. Warwick, R. M. & Clarke, K. R. (1993). Increased variability as a symptom of stress in marine communities. Journal of Experimental Biology and Ecology, 172, 215-226. Weate, P. B. & Hutchings, P. A. (1977). Gosford lagoons environmental study- the benthos. Operculum, 1977, 137-143. Wiecek, D. & Floyd, J. (2007). Does dredging in ICOLL entrances improve tidal flushing? 16th NSW Coastal Conference, 7 - 9 November, Yamba, Australia. Williams, R. J., Watford, M. A., Taylor, M. A. & Button, M. L. (1998). New South Wales Coastal Estate. Wetlands (Australia), 18, 25-47. Zann, L. P. (1995). State Of the Marine Environment Report, Great Barrier Reef Marine Park Authority, Townsville.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 153-183 © 2011 Nova Science Publishers, Inc.
Chapter 5
WATERBIRDS AS BIOINDICATORS IN COASTAL LAGOONS: BACKGROUND, POTENTIAL VALUE AND RECENT RESEARCH IN MEDITERRANEAN AREAS Francisco Robledano Aymerich* and Pablo Farinós Celdrán Department of Ecology and Hidrology, University of Murcia, Espinardo, Spain
ABSTRACT Among the biological components of estuarine systems and other transitional coastal waters, waterbirds are probably the group that has been monitored more intensively and throughout longer time series, especially due to the use of citizen science. Moreover, several authors have reviewed, organized and analyzed critically the role and potential use of waterbirds as bioindicators. Recently, academic research has encouraged more intensive monitoring of waterbirds in the context of bioindication in wetlands and coastal waters. However, in the particular case of coastal lagoons, birds have received little attention compared to research efforts directed to other taxa, ignoring their important role as top predators and underestimating their contribution to various ecological processes. Few studies have included waterbirds as integral components of the food webs in lagoons, relating them to other biota. However, recent studies show that waterbirds respond to changes imposed by a variety of stressors, constituting warning signals against undesirable changes. Waterbirds can be used as bioindicators both at suborganismic and at population-community-ecosystem levels. Either approach requires that the relationships birds establish with habitats and with the ensemble of the lagoon‘s biocoenosis are clarified. As these relationships and the bioindicator role of waterbirds are established in more detail, stands out their usefulness as indicators of impairment in coastal lagoons of similar characteristics, subject to similar impacts with time lags. Studies on the waterbird community of the Mar Menor Lagoon (SE Spain) show the long-term response of populations to variables related to eutrophication and biological *
Corresponding author: E-mail: [email protected]
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Francisco Robledano Aymerich and Pablo Farinós Celdrán changes (proliferations of jellyfish and changes in fish stocks). Studies based on community variation in relation to internal environmental gradients of the lagoon, show spatial responses that can be mapped, and provide a basis for building indices of integrity. This is a relevant issue given the paucity of studies that explore and apply the indicator value of birds in conservation and environmental evaluation, particularly in the Mediterranean and elsewhere in temperate latitudes. Recent studies that integrate the monitoring of different physico-chemical and biotic variables of the lagoon with waterbird numbers and distribution, and research on waterbird trophic ecology based on stable isotope analysis, aim at clarifying the role of waterbirds as top-down controllers in the food webs of coastal lagoons. A role whose monitoring is also important from an applied perspective, given the potential of some waterbirds like cormorants to become conflicting species (through their interaction with fisheries). The application of these monitoring schemes to other Mediterranean lagoons emerges as a valuable tool for assessing and preventing changes in the ecological status of these systems with respect to relatively undisturbed, reference conditions.
1. INTRODUCTION Among the biota of estuarine systems and other transitional coastal waters (TW), waterbirds are probably the group that has been monitored more intensively and throughout longer time series (Crivelli et al., 1996; Delany et al., 1999; Gilissen et al., 2002; Wetlands International, 2008). The use of citizen science has been crucial in this respect (Kushlan, 1993). However, the application of such datasets to ecological monitoring or bioindication has been much more limited. Waterbirds have been the main criterion -and for a long time, virtually the only available- for the designation of internationally important wetlands, with a prominent role in the implementation of the Ramsar Convention (Morgan, 1982; Green et al., 2002; Jackson et al., 2004). But quite often, once wetlands have been awarded the label of Ramsar Sites, waterbird monitoring data have become mere ―success indicators‖ of the type of management focused at bird populations and their preferred habitats. In most cases, this success has been measured only in quantitative terms (number of birds). Or, at best, the monitoring of some specialized bird species has lead to some form of biodiversity and environmental health indication (Máñez et al., 2010). Several authors have reviewed, organized and analyzed critically the role and potential use of waterbirds as bioindicators (e.g. Peakall and Boyd 1987; Adamus 1996; Green and Figuerola 2003; Gregory et al. 2003; Stolen et al. 2004; Rönkä et al. 2005; Amat and Green, 2010). Recently, academic research has encouraged more intensive monitoring of waterbirds in the context of bioindication in wetlands and coastal waters (Hubina, 2008; Rönkä et al. 2008). However, in the particular case of coastal lagoons (CLs, hereafter), birds have received little attention compared to research efforts directed to other taxa, ignoring their important role as top predators and underestimating their contribution to various ecological processes (Daborn et al., 1993; Comín and Hernández, 1997; Glassom and Branch, 1997; Steinmetz, 2003; Hahn et al., 2007; Rodríguez-Villafañe et al., 2007). Few studies have included waterbirds as integral components of the food webs in lagoons, relating them to other biota (Acuna et al., 1994; Žyydelis and Kontautas, 2008). Recent studies show that waterbirds respond to changes imposed by a variety of stressors, constituting warning signals against undesirable changes (Amat and Green, 2010; Mallory et
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al., 2010). Waterbirds can be used as bioindicators both at suborganismic and at populationcommunity-ecosystem level (Kushlan, 1993). Either approach requires that the relationships birds establish with habitats and with the ensemble of the lagoon‘s biocoenosis are clarified. As these relationships and the bioindicator role of waterbirds are established in more detail in the best studied lagoons, so will improve their usefulness for detecting impairment trends in other lagoons of similar characteristics, subjected to similar impacts with different time lags. Among the basic questions to which studies of waterbirds should respond, we will try to examine to what extent current knowledge and studies in progress in Mediterranean CLs, shed some light on the following: Do waterbird metrics or indexes respond in a predictable manner to long-term changes in the ecological conditions of CLs? Do such metrics or indices track spatial gradients of ecological impairment inside CLs? What is the spatial scale (habitat, site, landscape) at which species respond to environmental changes affecting CLs? Which combination of suborganismical and population-community-ecosystem level bioindicators (sensu Kushlan, 1993) will produce the best scheme for waterbirdbased bioindication in CLs?
2. WATERBIRDS AS INDICATORS: POTENTIAL USES AND RESTRICTIONS The potential for using of waterbirds for assessing wetland quality is based on several attributes which allow them to fulfil the properties of good indicators (Roomen et al., 2006; Everard, 2008). Waterbirds are sensitive to changes in the composition and structure of the wide range of habitats and landscapes they use; they occupy a high trophic position; they are conspicuous and easily identifiable to species in the field and hence can be monitored without greater methodological limitations; they enjoy a wide coverage through routine schemes of coordinated monitoring (U.S. EPA, 2002; DeLuca et al., 2004; Stolen et al., 2004; Bryce et al., 2005; Brazner et al., 2007). In particular, waterbirds show a close relationship with the abiotic characteristics and food webs of inland aquatic ecosystems (Paszkowski and Tonn, 2006), which has spurred their integration in the studies of such systems (Kerekes and Pollard, 1994 ). Attributes of waterbird populations or communities (species composition, abundance, reproductive success, habitat use) can provide information about other ecosystem characteristics (trophic structure, hidrology, organic or chemical contaminants…) that are more difficult to monitor (Stolen et al., 2004; Roomen et al., 2006). The use of waterbirds as biological indicators has been often questioned by the lack of a measurable direct response to changes in limnological variables (Adamus, 1996; Green and Figuerola, 2003). However, monitoring waterbird populations, at least in a regional system or a wetland compex (Adamus, 1996), provides a good signal of environmental change (Martínez et al., 2005). For instance, several authors have observed a response of waterbird populations to changes in the supply of nutrients from multiple sources, to both inland and coastal waters (Nilsson, 1985; Raffaelli, 1999). The interpretation of such changes is complicated because waterbird
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responses change depending on the stage within the process of eutrophication (Van Impe, 1985; Raffaelli, 1999; Van Eerden et al., 2005), and sometimes also in a taxon-specific way (Rönkä et al., 2005). Among other major limitations for the use of waterbirds as indicators, it can also be mentioned the frequent lack of concordance or similarity between the diversity of waterbirds and that of other organisms living in the same aquatic habitats (Amat and Green, 2010), for which they are expected to act as surrogates (Stolen et al., 2004). High mobility and instability in numbers within sites at different temporal scales (interanual to daily) can lead to misleading conclusions about relationships of waterbirds with environmental conditions if monitoring work does not account for this variability (Dodd and Colwell, 1996; Johnson and Krohn, 2001; Roomen et al., 2006; Bolduc and Afton, 2008; Amat and Green, 2010). Despite the limitations exposed, waterbirds have been shown to track environmental changes at different temporal scales, and at different levels or organization (species, communities) within ecological systems (Amat and Green, 2010). Basically ornithological studies searching for trends in waterbird numbers and inferring local habitat changes as explanatory factors (e.g. Lopes et al., 2005), while coming closer to the indicator approach, usually lack the environmental dataset needed to support these inferences (Stolen et al., 2004).
3. THE PARTICULAR CASE OF MEDITERRANEAN COASTAL LAGOONS As mentioned earlier, waterbirds have received little attention in CLs compared to research efforts directed to other taxa (see e.g. Bachelet et al., 2000; Pérez-Ruzafa et al., 2004; Arvanitidis et al., 2005; Basset et al., 2008), ignoring their important ecological role and the relevant influence they can exert on ecosystem processes. Mediterranean CLs are not an exception. This is surprising since Mediterranean wetlands, and especially lagoons, meet several characteristics that make them particularly suitable for testing the response of waterbirds to environmental pressures, due to the concentration of human activities and population along its shores (De Stefano, 2004; Viaroli et al., 2005). Mediterranean CLs receive through their watersheds the influence of intensively farmed and densely populated areas, especially during the summer months when this semi-enclosed sea becomes the major world‘s tourism hotspot (Vogiatzakis et al., 2006). Although bird-based Indices of Biotic Integrity (IBIs) for terrestrial and aquatic ecosystems have been developed worldwide during the last decades (O‘Connell et al., 1998, 2000; Canterbury et al., 2000; Bryce et al., 2002; DeLuca et al., 2004; Bishop and Myers, 2005; DeLuca et al., 2004), their application to Mediterranean TWs has been very limited, and only Paracuellos et al. (2002) get close to the concept of bird-based assessment of wetland condition, comparing the situation before and after the abandonment of Mediterranean Salinas. The European Union (EU) Water Framework Directive (WFD) proposes an indicator system based on hydromorphological, physico-chemical and biological elements (flora, invertebrates, fish) but ignores birds, despite being an important macroscopic component of aquatic ecosystems, for: i) their contribution to their ecological integrity, in terms of
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composition, structure, and functioning; and ii) their role as integrators and detectors of ecological change. Composite bird indexes of integrity can also help to harmonize the WFD‘s water-quality objectives with the biodiversity conservation objectives set by other EU Directives (Birds and Habitats). Such assessment tools can be especially useful in complex Mediterranean TW areas like CLs and their associated wetlands, where many conservation and protection regulations overlap. Moreover, multispecies assessments of protected areas can be a valuable tool, not only for its own zoning or management, but for the investigation of human impacts on biodiversity at a wide array of scales (Devictor et al., 2007).
4. A TYPICAL MEDITERRANEAN EXAMPLE: THE MAR MENOR CASE STUDY Research carried out up to date on the waterbird community of the Mar Menor Lagoon (SE Spain) shows the long-term response of populations and guilds, to proximate variables related to eutrophication and other apparent biological changes (proliferations of jellyfish and changes in fish stocks) whose ultimate causes are the intensification of agriculture and urbanization (Pérez-Ruzafa et al., 2002; Alvarez-Rogel et al., 2006; García-Pintado et al., 2007). Besides, recent studies based on community variation in relation to internal environmental gradients of the lagoon (Farinós and Robledano, in press), display spatial responses that can be mapped and provide a basis for building indices of integrity. In this section we report on the main results, whether published or not, of such studies. The issues dealt with in are relevant, given the scarcity of studies that explore and apply the indicator value of birds to the conservation and environmental assessment of CLs, particularly in the Mediterranean and elsewhere in temperate latitudes (some exceptions being, e.g.: Tamisier and Boudouresque, 1994; Green, 1998; Ntiamoa-Baidu, 1998; Green et al., 2002; Paracuellos et al., 2002; Hubina, 2008). Let us first draw an outline of the environmental characteristics of the case study site (Mar Menor CL), a hypersaline lagoon located in the coast of Murcia Region (Figure 1). At 135 km2, it is the largest CL of the western Mediterranean (Pérez Ruzafa and Marcos, 2003) and has an average depth of 4 m. It is separated from the Mediterranean Sea by a narrow sand strip (La Manga) almost completely reclaimed for tourism, and surrounded by an irrigated agricultural plain of 480 km2 inside a total watershed area of 1.275 km2 also with dense urban settlements (Figure 1). The waterbird community is one of the most important biological components of the Mar Menor CL, included in the Ramsar List of Wetlands since 1994 (Robledano, 1998), and designated as EU Bird Specially Protected Area (SPA) and as Barcelona Convention‘s Specially Protected Area of Mediterranean Importance (SPAMI) since 2001. The lagoon experienced major physical and hydrological changes in the decade of 1970‘s due to the dredging of one of the inlts (Estacio) communicating it with the sea. This increased the marine influence, starting a process of ―mediterraneization‖, i.e. smoothing the sharp differences between the lagoon (hypersalinity, higher temperature, greater confinement) and the open sea. Until mid 1980‘s the lagoon lacked any permanent watercourses flowing into, but since then the Albujón Channel started to discharge a permanent flow of agricultural drainage water, refuse from desalination and untreated urban wastewater (García-Pintado et al., 2007). Total yearly flow has been recently estimated in 20 Hm3 of water whose
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conductivity is usually between 8-11 mS/cm2, a brackish input into the hypersaline (33.6-46.2 p.s.u) main water mass (Lloret et al., 2005). There are also low-salinity inputs through several minor channels, below-ground seepages and diffuse drainage. Environmental datasets (predictors) were obtained from several official data, modelling studies and intensive monitoring campaigns performed by different institutions and research groups (see e.g. Rodríguez et al., 2005; Martínez et al., 2007). For more detailed information on sampling procedures and statistical methods we refer to these papers and reports. The basis of this research work are the winter waterbird census made between 1972 and 2005 in the framework of the International Waterbird Census (IWC), compiled for the Region of Murcia by Hernández and Robledano (1991), Martínez et al. (2005) and Hernández et al., 2006), and on more recent waterbird monitoring campaigns running along shorter periods but with a more intensive coverage (Robledano et al., 2008; Farinós and Robledano, in press). These datasets represent the source for the main ornithological response variables. Tables 1 and 2 present the most important species, in terms of abundance, included in such studies.
Figure 1. Geographical location of the Mar Menor CL
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Table 1. Wintering species studied in the Mar Menor CL classified “a priori” on the basis of their taxonomic, habitat and trophic characteristics. “Habitat specialization” refers to the degree of restriction of each species to the lagoon main water mass; “Feeding specialization” summarizes the variety of food types and foraging methods used by each species. The characterization is based on personal work in the area plus literature sources (Cramp, 1980). “Trophic guild” follows Ysebaert et al. (2000) Familiy
Species
Gruidae
Common Coot Fulica atra
Phalacrocoracidae
Cormorant Phalacrocorax carbo Great Crested Grebe Podiceps cristatus
Podicipedidae
Anatidae
Black-necked Grebe Podiceps nigricollis Red-breasted Merganser Mergus serrator
Habitat specialization Restricted (rarely outside lagoon) Oportunistic (moves around widely to terrestrial, aquatic and marine habitats) Restricted (rarely outside lagoon) Facultative (occasional movements to nearby wetlands) Restricted (rarely outside the lagoon)
Feeding specialization Generalist
Trophic guild Herbivore
Generalist Specialist
Piscivores
Generalist Specialist
Table 2. Species of the Mar Menor CL offshore waterbird community recorded in the studies covering at least one complete year cycle (occasional species, i.e. those with abundances ≤ 1 individual in any census, have been excluded). Main phenological status is also indicated (W= species of the winter community; S=species of the summer community) Family Podicipedidae Phalacrocoracidae Laridae
Sternidae Anatidae Ardeidae
Species‘ scientific name Podiceps cristatus Podiceps nigricollis Phalacrocorax carbo Larus michahellis Larus ridibundus Larus genei Larus audouinii Sterna sandvicensis Sterna hirundo Mergus serrator Egretta garzetta
Species‘ common name Great-crested Grebe Black-necked Grebe Great Cormorant Yellow-legged Gull Black-headed Gull Slender-billed Gull Audouin‘s Gull Sandwich Tern Common Tern Red-breasted Merganser Little Egret
Phenology W W W W+S W+S W+S W+S W W+S W W+S
In the most recent work (Farinós et al., 2009), three groups of environmental variables were used: descriptors of physico-chemical conditions (nutrients), biological conditions (ichthyoplankton species composition, total ichthyoplankton abundance and chlorophyll ―a‖), and variables expressing distances to shelter or disturbance elements (mainly islands and airports, respectively).
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4.1. Long Term Response of Waterbirds to Environmental Changes Eutrophication is one of the main problems confronted by coastal ecosystems (Caddy and Bakun, 1995). In the Mar Menor Lagoon, many research initiatives have attempted to gauge the contribution of various causes and pathways to this process (Esteve and Martínez, 2003; Delbaere and Nieto-Serradilla, 2004; Jiménez-Cárceles et al., 2005; García Pintado et al., 2007), but most of them have been carried out on a short time or small spatial scale, and there is a lack of studies on the long term responses of biodiversity to the biotic changes imposed by eutrophication. Martínez et al. (2005), Esteve et al. (2008) and Robledano et al. (in press) analysed the relationship of waterbirds with locally measured or estimated environmental variables (nutrient load, fish production, jellyfish blooms) related with the process of eutrophication, and discussed the potential value of birds as indicators of the trophic status of the wetland. They used linear regression and GLMs to relate the biomass of the five waterbird species that compose the bulk of the lagoon‘s waterbird community to these variables. Since local changes in waterbird numbers can obviously be linked to external influences, affecting their populations globally, there was a need to collect information on the status of wintering populations in higher-level biogeographical divisions (Lopes et al., 2005; Roomen et al., 2006), an important issue when interpreting local trends in waterbird data (see e.g. Rendón et al., 2008). In the Mar Menor studies, such influences were controlled through the use of a biogeographical (Western Mediterranean) population index as a predictor, and by comparing population trends at national and local scales (Martínez et al., 2005, Robledano et al., in press). The Red-breasted Merganser was the dominant piscivore during most of the decade of 1970. The Great Cormorant dominated the community most years since then, representing ca. 50% of the biomass except between 1988 and 1996 when other piscivores, including the two Grebe species (Podiceps cristatus and nigricollis), dominate (Figure 2). Only the Great Cormorant showed a significant relationship with its Western Mediterranean population index (explaining almost 50% of the variation in local biomass), an effect that biased the global positive response of the piscivore guild to nutrient load (NLD). Red-breasted Merganser appeared relatively insensitive to nutrient enrichment, although it declined in the long-term. The remaining species responded positively. NLD was a significant predictor of their biomass when a 2-year lag was allowed, although this variable alone had a low explanatory power, except for the Coot, for which it accounted for up to 59.5% of the variance. When temporal phases were defined within the study period (Table 3), grebes (Podicipedidae) could be identified as early warners of eutrophication, and herbivores (Coot) as a late-stage indicators (Figure 2). Although eutrophication often causes a marked deterioration of seagrass and macroalgal communities, apparently not beneficial for herbivores (Noordhuis et al., 2002), it also can favour opportunistic macroalgae (Krause-Jensen et al., 2008), a source of food for generalist herbivores like Coot (Perrow et al., 1997; Yallop et al., 2004). The proliferation of such algae is already observed in some stretches of the lagoon‘s shoreline.
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Figure 2. Top: Changes in the environmental variables that describe changes experienced by the Mar Menor CL: estimated nutrient load (NLD-2, 2 year lagged), jellyfish numbers (JFGS-2, 2 year lagged) and fish catch (FISH). The last variable is used as a surrogate index for fish productivity. Bottom: variation of the relative contribution of different species and guilds to total biomass
Table 3. Main phases identified by the response of waterbirds to environmental changes in the Mar Menor CL (modified from Robledano et al., in press)
Nutrient inputs Fishing catches
1 1972-79 Start and stabilization High but declining at the end of period (overfishing?)
Jellyfish
Absent
Water birds
2 1980-87 Regular loading Very few data (probably fluctuant at intermediate levels) Absent
Dominance of Dominance of Mergus serrator Phalacrocorax+ Low piscivore Mergus diversity
3 1988-1995 Moderate increase Fluctuant at intermediate levels
4 1996-(97)-? Sharp increase
Absent
Incipient populations
Increase of Podicipedidae (maximum relative contribution) Maximum piscivore diversity
Decrease of Podicipedidae Dominance of Phalacrocorax
Sharp decline
5 ?-(1999)-2005 Higher loading (fluctuant) Stable or fluctuant at low levels Dramatic increase and peak numbers Increase of herbivores (Fulica) Partial recovery of Podicipedidae
The increase of piscivores along a period of declining fish catches could reflect a shift in fish community composition or structure that favours their feeding preferences. It is possible
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that piscivores select prey types or size classes other than those commercially exploited (Liordos and Goutner, 2007), which in the long term seem to be negatively affected by eutrophication. This decrease in fish yield can also be a consequence of overfishing, leading to a dominance of small fish (Van Rijn and Van Eerden, 2003), which creates good feeding conditions for species like the Great Crested Grebe and the Great Cormorant (Gwiazda, 1997; Smit et al., 1997; Van Rijn and Van Eerden, 2003). Other species can survive entirely on prey different than fish (invertebrates), like Black-necked Grebe (Jehl, 2001; Fjeldså, 2004). Jellyfish, the main top-down agent controlling the food web in the Mar Menor lagoon (Pérez Ruzafa et al., 2002), seemed to modify the response of waterbirds to nitrogen load during the years when the surplus of nutrients triggered a bloom of this gelatinous component of zooplankton (mainly two species of allochtonous scyphomedusae, Rhyzostoma pulmo and Cotylorhyza tuberculata, recent colonisers of the lagoon). It has also been suggested that jellyfish not only affect birds through nutrient removal, but also qualitatively modifying the structure of the food web.
4.2. Spatial Response of Waterbirds along Coastal Lagoon Gradients From October 2006 to March 2008, Farinós and Robledano (in press) studied the spatiotemporal structure of the offshore waterbird community of the Mar Menor CL in relation with environmental gradients, in order to assess the role of waterbirds as integrative indicators of the lagoon‘s bio-ecological status. Waterbirds were censused in 20 sampling stations distributed according to an established zonation scheme based on the degree of confinement (as defined by Guelorget and Perthuisot, 1983) and primary production (Pérez-Ruzafa et al. 2005), which was subsequently modified to match bird use at the landscape level. Multivariate classification and ordination techniques (MDS and SIMPER) allowed to identify indicator species and to display their association with relevant environmental vectors. Total abundance of waterbirds increased latitudinally, southward in winter and vice versa in summer. Greater abundance and diversity were found in the southern half of the lagoon in winter, where grebes (62.8%), gulls (22%) and cormorants (15.1%) , and in the northern half in summer, where gulls (80.1%) and terns (9.3%) where the dominant species. Taking the sampling sections of figure 3 as an expression of its internal heterogeneity, the MDS ordination of the samples showed that changes in community structure poorly reflected the zonation established by Pérez-Ruzafa et al. (2005). A new spatial aggregation of samples was derived from a ―waterbird zoning‖ classification, based on the level of similarity which had a more coherent spatial expression (80-85% similarity). The new zones (Figure 3) can be characterized from a combination of terrestrial influence (direct or indirect, depending on their relative position regarding incoming channels and internal circulation), marine influence (inner or outer, in relation to the open sea) and latitudinal position (north or south): IIIN (indirect influence inner north), DII (direct influence inner), IIIS (indirect influence inner south), IIOS (indirect influence outer south), IION (indirect influence outer north) and ODS (other dispersed sampling stations). ―Indirect influence‖ refers to the effect of nutrient inputs through internal circulation.
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Figure 3. Map of the Mar Menor CL showing the original zonation of Pérez-Ruzafa et al. (2005), and the sampling stations for the study of the offshore waterbird community and related environmental characteristics (left). The map on the right displays the zonation based on the level of similarity of the waterbird community among sampling stations (―waterbirds zoning‖), and the most representative species of each zone . Modified from Farinós and Robledano (in press)
A distinct latitudinal distribution of particular species was observed (Figure 3), the northern half of the lagoon‘s basin being characterized by Black-headed Gull (Larus ridibundus) and the southern half by Great-crested Grebe (Podiceps cristatus) and Great Cormorant (Phalacrocorax carbo). Such distribution patterns seem to respond to internal functional gradients of the lagoon, but also to the physical structure of the habitat (e.g. sheltered areas) and to the influence of human activities (direct disturbance or landscape modification). Both internal and external factors related with waterbird abundance and distribution are affected by human activity, as has been shown in other wetland ecosystems, both at local and landscape scales (Kerekes and Pollard 1994; Noordhuis, et al. 2002; Paracuellos, 2006; Paszkowski and Tonn, 2006; Hebert et al. 2009). While at community level winter abundance and diversity seem to respond to gross levels of productivity, individual species‘ responses are indicative of internal gradients in these and other factors. The Great-creasted Grebe favours areas indirectly influenced by nutrient inputs over direct discharge zones, which supports its role of early warner about eutrophication (already recognized as such in the 1980s; see Hernández and Robledano 1997). The same preference is shown by the Great Cormorant, proposed as an indicator of waters of intermediate turbidity (Van Rijn and Van Eerden 2003; Rönkä et al. 2005). However, in the Mar Menor CL the Great Cormorant should preferably be considered a background indicator of eutrophication, given its mobility and landscape-scale response to increased productivity and complementary food sources (irrigation ponds, fish farms). Compared with earlier work in the area (Hernandez and Robledano, 1997), the main difference revealed by this study, apart from the
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decrease of Anatidae, is precisely the increase of cormorants in the winter waterbird assemblage. The physical structure and geomorphology of the lagoon can help to explain the differential use of the water mass by some species, e.g. Great Cormorants, which feed mainly in the area with more islands where they can perch on small emergent rocky outcrops (Reymond and Zuchuat 1995; Roycroft et al. 2007). Also, restricted to the island-rich part of the lagoon is the Red-breasted Merganser, once a characteristic species of the Mar Menor CL but now undergoing a steady decline in numbers (Martínez et al., 2005). The positive numerical response of other piscivores in some phases of eutrophication suggests that changes in the type and quality of food resources might explain the Merganser‘s opposing trend. The species favouring the northern, island-free part of the lagoon, seem to be more dependent on the influence of the Mediterranean Sea than on increased productivity of terrestrial origin. An example is the Black-headed Gull, strictly favouring the more open and oligotrophic waters of the north basin. This species has increased notably in the Mediterranean during the last century in response to the increased variety and quantity of resources offered by man, although this process has occurred at a landscape level (Blondel and Aronson, 1999). In the Mar Menor CL, the zones favoured by Black-headed gulls do also display the greatest diversity of trophic resources and are the most suitable for the species‘ foraging techniques (Lewis et al., 2003).
Figure 4. Density distribution of Sandwich Tern (Sterna sandvicensis) in July 2007 (left graph) and November 2007 (right graph)
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Figure 5. Density distribution of grebes during 2006-2007 wintering season (left, December; right, January): upper graphs, Great-creasted Grebe (Podiceps cristatus); lower graphs, Black-necked Grebe (Podiceps nigricollis)
The results show that waterbirds can be incorporated in a monitoring scheme of the lagoon, as integrative indicators of spatial gradients of environmental deterioration. As shown by figures 4 and 5, mapping the densities of waterbird indicator species is a promising tool to detect changes in the direction and/or intensity of the pressures (whether originated in the mainland or in the seaward side of the lagoon), since these changes make themselves evident along the main spatial gradients identified within the water mass. Coastal lagoons are dynamic, wide open systems, and highly dependent on adjacent terrestrial and marine systems with which a continuous exchange of materials and energy occurs (Pérez Ruzafa and Marcos 2003). A multitude of anthropogenic changes can modify the natural inputs from their
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watersheds (Menéndez and Comín 2000; 2001; Herrera-Silveira et al. 2002; Contreras and Warner, 2004). The ecological status of CLs is determined, among other factors, by the confluence of these opposing forces (terrestrial vs marine influence, natural processes vs anthropogenic modifiying factors) that explain their heterogeneity, biodiversity and productivity (Tamisier and Bouduresque 1994; Pérez Ruzafa et al. 2002). A landscape perspective is essential to build sound conservation programs for waterbird assemblages (Guadagnin, et al., 2005), but also to assess waterbird indicator potential and to devise associated monitoring schemes. Hidrology, nutrient status, disturbance levels and other relevant features of the CL, can be severely modified by actions carried out at the watershed level, in the watercourses and hydraulic connections of the lagoon with adjacent ecosystems, in the shoreline habitats or its immediate landscape surroundings, as well as by those occurring in the lagoon‘s littoral and benthic communities. The diversity of waterbirds in the Mar Menor lagoon increases with proximity to the Mediterranean Sea, a trend already found for other animal groups (Rosique 2000) and that can be attributed to an increased diversity of food resources and feeding habitats. In a comparative analysis of 40 Atlanto-Mediterranean coastal lagoons Pérez-Ruzafa et al. (2007) found that fish species richness increased with lagoon volume and the openness parameter, which characterizes the potential influence of the sea on general lagoon hydrology and is related to the total transversal area of the inlets connecting the lagoon to the sea. On the other hand, the number of species decreased exponentially with the phosphate concentration in water, and fishing yield increased with the chlorophyll a concentration in the water column and exponentially with shoreline development. Since waterbirds seem to respond well to changes in these parameters within the lagoon, processes of such importance for the system as the increase in marine influence (the so-called "mediterraneization") or the eutrophication caused by discharges of urban origin, can be traced through waterbird monitoring. In contrast to other biota of these transitional water ecosystems, birds have the capacity to integrate in their responses the combined effects of purely physical and/or trophic influences, plus human deterioration of habitats by direct disturbance or through the modification of the landscape setting (Rosa et al. 2003; McKinney et al. 2006; De Luca et al., 2008). Since anthropogenic impacts on the lagoon from different spatial scales (watershed, immediate landscape, shoreline, lagoon sections) act through relatively discrete and well-referenced paths, the distribution of waterbirds within the lagoon emerges as a potential barometer of the system‘s internal response to these pressures. Although biologically meaningful and statistically supported (Erwin and Custer, 2000; Van Strien et al., 2009) such a distributional response to a complex syndrome of ecological changes can still be regarded as too general or vague if our interest is to develop a scientifically sound and practical wildlife indicator (Stolen et al., 2004). The next step needed is thus to discern the specific CL attributes to be indicated (e.g., nutrient status, habitat structure, biodiversity), and to state a model of how the proposed waterbird indicator will respond to perturbations of the lagoon ecological status or functioning. This will allow to upgrade indicators based on waterbird abundance distribution, or indexes built upon it, to the types -among those distinguished by Van Strien et al. (2009)- with more strength in the detection of anthropogenic impacts on the biodiversity of CLs (Figure 6).
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Strong TYPE 3
TYPE 4
¿How are specific taxa responding to a driving force?
¿How is biodiversity responding to a driving force?
Waterbird abundance distribution
Strength of link to a driver
Multispecies conservation value indexes
Long term trends in waterbird populations and guilds ¿How are specific taxa doing?
TYPE 1
Weak
Weak
¿How is biodiversity doing?
TYPE 2
Ability to generalise findings to trends in biodiversty
Strong
Figure 6. Judgements of the examples of bird-based indicators studied in the Mar Menor CL, in the framework of the tipology sketched by Van Strien et al. (2009). Arrows show the potential for upgrading indicator types currently under development, along the scales of increasing strength depicted by the axes
The decisions about urban planning and land arrangement for different uses (agricultural, residential...), and about the spatial allocation of typical lagoon uses (recreation, transport, fishing...) have also a direct influence in the levels of potential damage and disturbance to biological communities (birds being in this sense particularly reactive), and indirectly through an increased risk of nutrient and contaminants release. In this sense, watebirds ability to respond quickly to changes in the levels of disturbance (Davidson and Rothwell, 1993; Burton, 2007), to the spread of potentially harmful structures (fishing nets), to bioaccumulate toxins or pollutants (Kushlan, 1993; Konstantinou et al., 2000), or to show symptoms of disease (Newman et al., 2007), makes them irreplaceable monitoring tools. The use of multispecies and multimetric indexes is another promising application of research on indicators, to assess both ecological integrity and the interest for conservation of discrete areas subjected to different levels of disturbance. In a first attempt to apply waterbird-based indexes to assess the ecological integrity of different sections of the Mar Menor shoreline, Robledano and Farinós (2007) selected bird metrics through a guild-based approach, on the basis of shared characteristics of waterbirds‘ life history, distribution, demography or behaviour. As a first test, composite Waterbird IBIs were calculated in two contexts: i) an ensemble of littoral sites within a large coastal lagoon, representing a spatial disturbance gradient; and ii) a series of waterbird records in this same wetland complex, covering a temporal disturbance gradient. Bird data used were: i) mean waterbird density calculated from 5 winter counts in 14 sites (500 m of shoreline x 1000 m towards the centre of the Mar Menor lagoon, Figure 7); ii) winter waterbird census (made in january within the International Waterbird Census, IWC).
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Figure 7. Location of the sampling stations of the Mar Menor CL shoreline compared through the calculation of waterbird-based Indices of Biotic Integrity (IBIs)
The spatial gradient of disturbance was described through a subjective index (DI-S) created from a combination of stress factors (artificial/natural uses in the immediate land and water surroundings, hidrological and/or hidrochemical alterations, presence of mitigation factors like vegetation buffer zones). To validate it, an independent index of disturbance (DIECELS) was calculated using a procedure adapted from the ECELS index of hidromorphological and vegetation quality (ACA, 2006), which takes inverse values and is scaled in the same terms than the DI-S index. The correlation between both indexes was relatively high and significant (r Spearman = 0.76; p < 0.01). Waterbird metrics were selected on the basis of the procedures established by Bryce et al. (2002) and DeLuca et al. (2004). The first authors give scores to the species according to their vulnerability to disturbance, classifying them as specialists or generalists in different attributes (feeding habitat, foraging methods, breadth of diet, distribution range, migratory character) - equaling specialization to greater sensitivity to changes in the wetland. The second authors test the response of a quartet of metrics (number of species, number of individuals, % species and % individuals) for each of these same attributes. A metrics is selected when its response matches the hypothetical ―expected‖ response (i.e., metric values decrease significantly as the level of disturbance increases. Two separate indices were calculated based on each of these reference papers. (a) The Bird IBIBRYCE was calculated from the scores of the selected metrics, multiplied by 10 and divided by the total number of metrics, to keep it within a scale from 0 to 100. (b) The Bird IBIDELUCA was obtained from a modification of the author‘s original formula:
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Table 4. Values of waterbird-based IBIs for different sampling stations of the Mar Menor CL shoreline IMBCDELUCA IBIBRYCE IBIBRYCE (1-6) IBIDELUCA (1-6)
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 17.75 17.00 17.19 17.14 17.00 17.83 17.19 16.79 16.40 17.50 15.75 15.75 15.75 19.63 56.05 50.1 42.1 65 52.8 87.6 60.1 44.3 58.56 53.2 46.3 36.2 36.5 90.08 4 2 3 3 2 4 3 2 1 2 1 1 1 6 3 2 1 4 2 6 3 1 3 3 2 1 1 6
WIMBCI =
Σ [(S
IMBCI
] –4
/ SN)
Where SN is the total number of species detected in the wetland. The equation represents the mean score of all the species present. Four is subtracted to ensure a scale that starts at zero and is constant. The values obtained for the two Bird IBIS in the different sampling stations shown in Figure 7 are shown in Table 4. In the two last rows of the table, the values of the indices have been scaled between 1-6, considering the total range of variation, and shades of grey used to highlight those stations better (darker) and negatively rated (lighter). Although not completely concordant, the results can be interpreted in relation to the characteristics of the sampling stations, particularly the habitat and landscape characteristics. The results are neither entirely consistent with those obtained from the study of the community within the water mass of the lagoon (the so-called "offshore" community). However, some similarities are evident, especially the high value that reach the sectors most influenced by the connection to the Mediterranean. Sectors which, as seen in the previous sections, must be considered of great importance for the overall bird diversity of the lagoon. When these same indices are applied at a long-term scale to the whole lagoon, the indexes do not respond to known degradation processes (e.g. increase in nutrient loads or decrease in fishing yields) that have affected the lagoon during the period in which they were obtained. In the long run, none of the metrics that make them up seems to show a clear trend of change, unlike to what happens when the same assessment procedure is applied at the spatial scale. It seems that an individual species or taxonomic guild approach like that presented in section 4.1 is best suited to the nature of the waterbird community of the main water mass of a Mediterranean CL. Although not implemented in the lagoon, multispecies indexes based in the conservation value for birds (Pons et al, 2003; Paquet et al, 2006), have proved very useful when applied to peripheral wetlands of the Mar Menor inner shore (Robledano et al., 2010). Also, a recent test of such indices in restored coastal salt ponds (Farinós et al., 2009 a) has proven useful to detect changes in bird conservation value along a process of nutrient enrichment. These indexes, and some other bird metrics (abundance, diversity) fit bell-shaped response curves, in apparent response to the initial improvement and subsequent deterioration of ecological characteristics relevant to birds and other biodiversity of coastal saline habitats. The fact that these relationships emerge in restored ponds equivalent to the low-salinity compartments of solar saltworks (from which they have originated), is remarkable. The latter are aquatic ecosystems sharing common characteristics with natural transitional waters ecosystems (like CLs), whose study is of special interest to the WFD (Evangelopoulos et al., 2008). Therefore,
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coastal lagoons seem an ideal field for the application of these assessment indices, already tested in small-scale replicates.
4.3. New Approaches: Coupling Waterbird Studies with Other Biological Monitoring Schemes Recent studies that integrate the monitoring of different physico-chemical and biotic variables of the Mar Menor with waterbird numbers and distribution, and research on waterbird trophic ecology based on stable isotope analyses, are helping to clarify the links between these top consumers and other trophic components of CLs. The firs studies also point to the search of concordance among indicators, as a necessary step for the selection of a suite of indicators to be incorporated into a multi-metric/multi-assemblage index of coastal wetland condition (Brazner et al., 2007). The second ones will help to clarify the strength of association of waterbirds with the CL basin versus their use of alternative or complementary habitats. In multivariate analyses relating waterbird community metrics (abundance, diversity) calculated from spatially and temporally segregated counts (monthly census in discrete sectors), with environmental variables recorded in the same sampling stations (Farinós et al., 2009 b), some relevant relationships emerged, which deserve further study. In multiple regression analyses (Table 5), total abundance of waterbirds showed a dependence on seasonality and on the spatial gradient (positive coefficient with salinity and negative with temperature). Nitrite had a positive effect on the wintering community diversity. The winter community abundance showed also a negative relationship with ichthyoplankton (its increase was associated with a reduction in the density of fish larvae), which indicates that waterbird populations could regulate this throphic component in the lagoon (top-down control of the food web). These results were concordant, in global terms, with the species associations displayed by a Canonical Correspondence Analysis (CCA) whose first axis (40% explained variance) seemed to differentiate species based on their foraging and seasonal general preferences (with piscivorous birds associated with frecuency of fishing nets). The second axis of this same analysis (20% explained variance) differentiated species based on their specific preferred prey and the tolerance to disturbance activities or elements. The waterbird community shows a strong dependence on the seasonal and spatial variation in the physicochemical properties of the lagoon‘s water mass, which determines its response to the gradient of continental influence (in combination with the spatially heterogeneous influence of the surrounding landscape structure and the extent of direct human disturbance). This is mediated by specific food preferences, as waterbird abundance seems not to respond directly to primary or secondary productivity (see also Farinós and Robledano, in press), and waterbird populations could even exert a top-down control of the food web.
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Table 5. Summary of multiple regression models with waterbird metrics (total abundance, species diversity) as response variable, and environmental or landscape variables -recorded in the stations sampled by boat- as predictors Dependent variable: SHANNON-WIENER DIVERSITY Waterbird assemblage: All year Multiple adj. R2: Predictors: Coef Distance to the nearest village -0.027 Salinity 0.030 Temperature -0.043 Waterbird assemblage: Winter Multiple adj. R2: Predictors: Coef Stress (Mean weighted record of disturbance events) 0.415 Nitrite 0.052 Waterbird assemblage: Summer Multiple adj. R2: Predictors: Coef Distance to main communication channel 0.025 Waterbird assemblage: All year Multiple adj. R2: Predictors: Coef Nitrite 1.452 Salinity 0.601 Temperature -0.921 Waterbird assemblage: Winter Multiple adj. R2: Predictors: Coef Stress 6.685 Nitrite 1.042 Ichthyoplankton -0.003 Waterbird assemblage: Summer Multiple adj. R2: Predictors: Coef Mean frequency of fishing nets at each sampling -0.901 station Distance to the nearest harbour 1.011 Distance to the nearest village -0.847 Salinity 0.055
0.630 p-value 0.078 0.000 0.000 0.685 p-value 0.000 0.025 0.240 p-value 0.000 0.550 p-value 0.017 0.000 0.000 0.544 p-value 0.000 0.000 0.000 0.450 p-value 0.000 0.001 0.024 0.000
4.4. Towards a Better Understanding of Waterbird Trophic Ecology in CL Research on waterbird trophic ecology based on stable isotope analyses, aim at clarifying the role of waterbirds as top-down controllers suggested by the preliminary research results outlined in the previous section. Monitoring of such effects of top predators is also important from an applied perspective, given the potential of piscivorous birds to become conflicting species, through their interaction with fisheries (Engström, 2001; Carss, 2003; Liordos and Goutner, 2007). This new approach also intends to determine how the feeding dispersion of
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the species studied around the Mar Menor CL and other habitat types, can affect their indicator value. In this regard, current work (P. Farinós et al., in preparation) attempts to explore, through the application of newly standardized methodologies like circular statistics (Post, 2002, Schmidt et al., 2007) or niche interactions and trophic diversity measures (Layman et al. 2007), the feeding dispersion patterns of cormorants in the Region of Murcia throughout its potential habitats distributed along the continental-marine gradient (with the Mar Menor lagoon as ―typical‖ TW habitat). These studies are primarily focused at three groups of wintering cormorants settled in three habitat types (freshwater bodies, coastal lagoon and open marine water), and their potential prey, and are based on detecting trends of change in the isotopic signature of C13 and N15 among the three areas, exploring the breadth, overlap and packing of food niche occupied by each group and clarifying the predator-prey relationships. As preliminary results, in Figure 8 is shown the biplot representing the mean and standard deviation of the signal of C13 and N15 of each trophic group studied. At a first glance, the representation depicts a strong affinity -from the point of view of the trophic niche and feeding habitats-, between two groups of wintering birds as distant as freshwater and marine cormorants (the position of the latter suggesting that their feeding extends to freshwater bodies as well). In any case, several aspects and issues expressed through circular and other statistical techniques described above, are still under discussion with regard to other research works that explore the isotopic signature of different elements in the food webs of the Mar Menor CL (Marín-Guirao et al. 2008, Lloret and Marín, 2009).
22,00
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Lake cormorants Marine cormorants
δ 15 N
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Lake fish
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δ
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C
Figure 8. Biplot representing the mean and standard deviation of the signal of C13 and N15 of each trophic group of Great Cormorants studied. ―Lake cormorants (and fish) refer to the group whose samples were collected in an inland freshwater reservoir; ―Marine‖, to those sampled in open sea islands; and ―Lagoon‖, to those from the Mar Menor CL
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Finally, eco-toxicological studies have been launched in order to explore the role of the Great Cormorant as bio-indicator of heavy metals pollution (Burger and Gochfeld, 2001 a), a process also present in the lagoon as a result of decades of opencast mining in the southern part of its watershed. These studies draw on the growing number of dead specimens beached in the lagoon shoreline, as a result of an increasing number of individuals drowned in fishing nets. The collection of fresh corpses is already yielding further data on the feeding ecology of this species (stomach contents), in addition to the tissues in which to base the toxicological analyses. The sampling of various elements of live and dead specimens for monitoring purposes, will help in future studies on the community of waterbirds and the whole lagoon ecosystem. Most of the species studied are top predators that integrate food web processes over time. A feature which, combined with new techniques to conduct retrospective measurement of chemical and/or biochemical indicators in archived tissue samples, can inform about temporal changes in food webs (Hebert et al., 2009).
5. SYNTHESIS AND PERSPECTIVES A main conclusion of this review is that waterbird monitoring activities in CLs should make a qualitative leap from routine accounting of population changes, towards a more accurate record of bird metrics, and their combination in meaningful indexes. While the former has an indisputable value for the compilation of indicators at national or international scales, studies of regional or local levels are of most interest to detect and, where appropriate, prevent, trends in habitat degradation. Austin et al. (2000) states that a regional breakdown of winter indices (based in wader census) increases understanding of national trends and can potentially act as an early warning system, highlighting possible declines before they become apparent at a national level. These declines may be indicators of changes in habitat quality that could have important consequences for conservation. In analogy, local monitoring of waterbird indicator species in CLs would help to better understand how the processes operating on this scale are combined and integrated to generate emerging trends. Ornithological monitoring data are recognized by various authors as cost-effective components of indicator systems for assessing habitat quality in wetlands (Brazner et al., 2007; Everard, 2008), and therefore should be investigated further on their consistency with other metrics and indices developed for the internal assessment of alteration gradients in CLs (e.g. Salas et al., 2006). At this point, it seems also indisputable the convenience of a multispecies/multi-metric system of ecological and biological monitoring of CLs based on waterbirds (Brazner et al., 2007). This system needs to combine the population-communityecosystem indicators dealt with in sections 4.1 to 4.3, the suborganismical ones outlined at the end of section 4.3, and whatever other relevant biological data generated by monitoring programs. Schemes like wildlife disease surveillance programs, beached-bird surveys, rehabilitation center data, and waterbird monitoring programs, all can supply information about a number of parameters (morbidity and mortality, breeding effort, breeding success, changes in population sizes) which combined, will provide a potentially robust early warning system for larger scale perturbations. This has remarkable implications, not only for aquatic bird health, but also for human health, as aquatic birds are used as sentinels for the alteration of ecosystems (wetlands,
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coastal areas) from which people obtain important goods and services (Burger and Gochfeld, 2001 b; Newman et al. 2007). Ongoing studies will allow in the near future to address key issues raised in the introduction to this chapter, but they are also opening new questions to be answered by posing new hypotheses, leading to the correct formulation of indicators (Stolen et al., 2004; Amat and Green, 2010). From a practical point of view, there remains the question of how to transfer the knowledge generated to ecologically and geographically related areas, as are other coastal lagoons in early stages of impairment and/or under still less intense pressures. Previous studies in closely related CL complexes (e.g. Tamisier and Boudouresque, 1994; Charco-García et al., 1995; Hernández and Robledano, 1997) show differences in the composition of their communities of waterbirds, which could be related to a lagged expression of similar alteration processes (as a consequence of different socio-economic development contexts, like those found in Northern versus Southern Mediterranean shores). It is possible, in any case, that waterbird responses found in the Mar Menor CL are sitespecific, as it seems to happen in other Mediterranean sites (Tamisier and Boudouresque, 1994), so comparative studies in similar ecosystems and in other habitat types are urgently needed. Once tested in Northern Mediterranean CLs, the application of bird bioindication schemes to less impacted wetlands of the Southern shores (taken as relatively undisturbed reference sites) appears as a valuable tool for assessing and preventing changes in the ecological status of these systems. Such comparative studies, coupled with the long term monitoring data available from CLs of developed countries, will also help to establish restoration objectives for the latter, with the reference undisturbed stages as most desirable (though not always achievable) targets.
ACKNOWLEDGMENTS The studies on which this chapter is based were funded, until 2006, by the European Union through EC ―Energy, Environment & Sustainable Development Programme‖ (DITTY Project, Contract EVK3-CT-2002-0084 DITTY). Between 2007-2009 financial support came from the Spanish Ministry of Education and Science through Project IBISMED- ESTADO ECOLÓGICO DE LOS HUMEDALES DEL MEDITERRÁNEO SEMIÁRIDO: PROPUESTA DE INDICADORES PARA SU EVALUACIÓN (CGL 2006-08134). We thank Asociación de Naturalistas del Sureste (ANSE) for coordinating waterbird censuses in the Mar Menor Lagoon during the years without public support to this scheme, and many volunteer ornithologists for carrying them out. Recent work on the offshore waterbird community of the Mar Menor CL would not have been possible without the logistical support of Angel Perez Ruzafa and Research Group of Marine Ecology (in particular, Mari Carmen Mompeán, Victoria Fernández, Jhoni I. Quispe, Marta García, Mercedes González and Oscar Esparza). The study was supported by the University of Murcia and Consejería de Agricultura y Agua de la Región de Murcia through the Agreement ―Red de Control y Vigilancia de la Calidad de las Aguas Litorales de la Región de Murcia‖. M. Francisca Carreño assisted in the calculation of some environmental variables with GRASS and in graphical representations. Jhoni I. Quispe also collaborated in the creation of
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distribution maps, and J. Miñano in the figures. Part of the content of this chapter comes from the work done by the first author during a stay in 2007 in the ―Unitat d'Ecosistemes Aquatics‖ del IRTA (Centre d'Aqüicultura de Sant Carles de la Ràpita, Catalonia, Spain).
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Rönkä, M., Tolvanen, H., Lehikoinen, E., von Numers, M. & Rautkari, M. (2008). Breeding habitat preferences of 15 bird species on south-western Finnish archipelago coast: Applicability of digital spatial data archives to habitat assessment. Biological Conservation, 141, 402-416. Roomen, M. van, Koffijberg, K., Noordhuis, R. & Soldaat, L. (2006). Long-term waterbird monitoring in The Netherlands: a tool for policy and management, 463-470, in: Boere, G. C., Galbraith, C. A. & Stroud, D. A. (Eds). Waterbirds around the world. The Stationery Office, Edinburgh. Rosa, S., Palmeirim, J. M. & Moreira, F. (2003). Factors Affecting Waterbird Abundance and Species Richness in an Increasingly Urbanized Area of the Tagus Estuary in Portugal. Waterbirds, 26, 226-232. Rosique, M. J. (2000). Recopilación y análisis de los trabajos existentes sobre el Mar Menor. Unpublished Technical Document, Centro Oceanográfico de Murcia (IEO), Murcia. Roycroft, D., Kelly, T. C. & Lewis, L. J. (2007). Behavioural interactions of seabirds with suspended mussel longlines. Aquaculture International, 15, 25-36. Salas, F., Marcos, C., Neto, J. M., Patrício, J., Pérez-Ruzafa, A. & Marques, J. C. (2006). User-friendly guide for using benthic ecological indicators in coastal and marine quality assessment. Ocean and Coastal Management, 49, 308-331. Schmidt, S. N., Olden, J. D., Solomon, C. T. & Vander-Zanden, M. J. (2007). Quantitative approaches to the analysis of stable isotope food web data. Ecology, 88, 2793-2802. Smit, H., Van der Velde, G., Smits, R. & Coops, H. (1997). Ecosystem responses in the Rhine-Meuse Delta during two decades alter enclosure and stops towards estuary restoration. Estuaries, 20, 504-520. Steinmetz, J., Kohler S. L. & Soluk, D. A. (2003). Birds Are Overlooked Top Predators in Aquatic Food Webs. Ecology, 84(5), 1324-1328. Stolen, E. D., Breininger, D. R. & Frederick, P. C. (2004). Using waterbirds as indicators in estuarine systems: successes and perils, 409-422 in: Bortone, S. A. (Ed.). Estuarine Indicators. CRC Press, Boca Raton, Florida. Tamisier, A. & Boudouresque, C. (1994). Aquatic birds populations as possible indicators of seasonal nutrient flow at Ichkehul Lake, Tunisia. Hydrobiologia, 278/280, 149-156. U.S. EPA. (2002). Methods for Evaluating Wetland Condition: Biological Assessment Methods for Birds. Office of Water, U.S. Environmental Protection Agency, Washington, DC. EPA-822-R-02-023. Van Eerden, M. R., Drent, R. H., Stahl, J. & Bakker, J. P. (2005). Connecting seas: western Palearctic continental flyway for water birds in the perspective of changing land use and climate. Global Change Biology, 11, 894-908. Van Impe, J. (1985). Estuarine pollution as a problable cause of increase of estuarine birds. Marine Pollution Bulletin, 16, 271-76. Van Rijn, S. & Van Eerden, M. R. (2003). Cormorants in the Ijsselmeer area: competitor or indicator?. Cormorant Research Bulletin, 5, 31-32. Van Strien, A. J., van Duuren, L., Foppen, R. P. B. & Soldaat, L. L. (2009). A typology of indicators of biodiversity change as a tool to make better indicators. Ecological Indicators, 9, 1041-1048. Viaroli, P., Mistri, M., Troussellier, M., Guerzoni, S. & Cardoso, A. C. (2005). Structure, functions and ecosystems alterations in Southern European coastal lagoons: preface. Hydrobiologia, 550, vii–ix.
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Vogiatzakis, I. N., Mannion, A. M. & Griffiths, G. H. (2006). Mediterranean ecosystems: problems and tools for conservation. Progress in Physical Geography, 30, 175-200. Wetlands International, (2008). Waterbird trends in Europe 1974-2002. Wageningen, The Netherlands. URL: http://www.wetlands. Yallop, M. L., O‘Connell, M. J. & Bullock, R. (2003). Waterbird herbivory on a newly created wetland complex: potential implications for site management and habitat creation. Wetlands Ecology and Management, 12, 395-408. Ysebaert, T., Meininger, P. L., Meire, P., Devos, K., Berrevoets, C. M., Strucker, R. C. W. & Kuijken, E. (2000). Waterbird communities along the estuarine salinity gradient of the Schelde estuary, NW-Europe. Biodiversity and Conservation, 9, 1275-1296. Žyydelis, R. & Kontautas, A. (2008). Piscivorous birds as top predators and fishery competitors in the lagoon ecosystem. Hydrobiologia, 611, 45-54.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 185-217 © 2011 Nova Science Publishers, Inc.
Chapter 6
HOW IMPORTANT ARE LOCAL NUTRIENT EMISSIONS TO EUTROPHICATION IN COASTAL AREAS COMPARED TO FLUXES FROM THE OUTSIDE SEA? A CASE-STUDY USING DATA FROM THE HIMMERFJÄRDEN BAY IN THE BALTIC PROPER Lars Håkanson* and Maria I. Stenström-Khalili Dept. of Earth Sciences, Uppsala University, Uppsala, Sweden
ABSTRACT The basic aim of this work has been to present a general approach to quantify how coastal systems are likely to respond to changes in nutrient loading. The conditions in most coastal areas depend on nutrients emissions from points sources, diffuse sources, river input and the exchange of nutrients and water between the given coast and the outside sea, but all these fluxes can not be of equal importance to the conditions in the given coastal area, e.g., for the water clarity, primary production and concentration of harmfull algae (such as cyanobacteria). This work describes how a general process-based mass-balance model (CoastMab) has been applied for the case-study area, the Himmerfjärden Bay on the Swedish side of the Baltic Proper. The model has previously been extensively tested and validated for salt, phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the transport processes (sedimentation, resuspension, diffusion, mixing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural variations and anthropogenic reductions of water pollutants. The results *
Corresponding author: E-mail: [email protected], Fax: +46-18-471-2737, Phone: +46-18-471-3897.
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Lars Håkanson and Maria I. Stenström-Khalili presented in this work indicate that the conditions in the Himmerfjärden Bay are dominated by the water exchange between the bay and the outside sea. The theoretical surface-water retention time is about 19 days, as determined using the mass-balance model for salt, which is based on comprehensive and reliable empirical data. This means that although this bay is quite enclosed, it is still dominated by the water exchange towards the sea. Local emissions of nutrients to the Himmerfjärden Bay are small compared to the nutrient fluxes from the sea. If the conditions in this, and many similar bays, are to be improved, it is very important to lower the nutrient concentrations in the outside sea.
Keywords: coastal waters; nutrients; eutrophication; Baltic Sea; Himmerfjärden Bay; massbalance modeling; Secchi depth; chlorophyll, cyanobacteria
1. INTRODUCTION AND AIM The title of this paper addresses a key issue in coastal management: If investments are being made to reduce local nutrient emissions to coastal areas, e.g., from industries and other point sources (such as fish farms), from diffuse sources, by means of changing agricultural practices, what are the benefits for the local receiving water system? And how much of the local emissions would be transported out of the local coastal system and contaminate the outside sea? To answer such questions, it is evident that one needs to quantify all major fluxes of water and nutrients/contaminants to, within and from the given coastal area to put the planned reductions into the proper context. This work will use a general mass-balance model (CoastMab; see Håkanson and Eklund, 2007, for a more thorough model description) in three different forms: (1) CoastMab for salt will provide water fluxes to, within and from the given coastal area and also the basic algorithms for (a) the theoretical water retention times (which influence the turbulence of the system and hence also sedimentation of particulate matter), (b) the mixing transport between the surface and the deep-water layers and (c) diffusion fluxes of dissolved substances (such as salt and dissolved forms of nutrients). (2) CoastMab for phosphorus will provide the requested nutrient fluxes and put the nutrient fluxes from the tributaries and from local emissions into a framework where also the exchange of nutrients between the given coastal area and the outside sea are calculated. The main difference between CoastMab for salt and CoastMab for phosphorus relate to the fact that phosphorus may appear in two different forms, the particulate fraction (PF), which is subject to gravitational sedimentation, and the dissolved fraction (DF = 1 – PF), which is subject to biouptake and also that the phosphorus deposited in the sediments may return to the water phase by means of advective and diffusive transport processes. The advective fluxes are mainly caused by wind-induced wave action and slope processes and the diffusive internal loading mainly by high sedimentation of organic material leading to high oxygen consumption, low oxygen concentrations and low redox potential in the sediments, which favors the formation of high levels of dissolved phosphorus in the sediments,
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 187 which trigger a high diffusion of phosphorus from the sediments. These processes are well known and included in textbooks in recent sedimentology (see, e.g., Håkanson and Jansson, 1983) and these processes are also included in the CoastMab-model. (3) CoastMab for suspended particulate matter (see Håkanson, 2006), which also predicts water clarity (Secchi depth) and sedimentation of matter and how these factors relate to nutrient fluxes (how the nutrient concentrations regulate the internal production of suspended particles) and the salinity (which regulates the aggregation of suspended particles and hence also sedimentation and water clarity). A central question in coastal management is how a given system would respond to suggested measures. How long would it take to reach a new steady state? What are the characteristic new nutrient concentrations in the water? And how would key bioindicators for eutrophication (see, e.g., Nixon, 1990; Livingston, 2001; Schernewski and Schiewer, 2002; Schernewski and Neumann, 2005; Moldan and Billharz, 1997; Bortone, 2005), such as chlorophyll-a concentration, concentration of cyanobacteria, oxygen concentration in the deep-water zone or Secchi depth change? In short, what is the environmental benefit related to the remedial costs? Such questions are addressed in this work using a general processbased quantitative approach which could also be used for other coastal areas than the casestudy area discussed here, the Himmerfjärden Bay in the Baltic Sea. Eutrophication is ranked as the most severe threat to the Baltic Sea (Savage et al., 2002; Bernes, 2005). Himmerfjärden was chosen as study area because it has been investigated intensively since 1976 and long data series on nutrient levels and water quality variables are available. There has been no proper mass-balance modeling of the bay before this study but Elmgren and Larsson (1997) and Larsson et al. (2006) stressed the importance of performing a mass-balance modeling study of Himmerfjärden to determine flows and water retention times in the bay. Khalili (2007) has presented a literature study on previous eutrophication research in Himmerfjärden. The research in the bay includes four large-scale nutrient regulation tests related to the discharges from a water treatment plant, Himmerfjärdsverket. The results from Himmerfjärden are often cited and used to motivate the benefits of nitrogen emission reductions. This has been questioned and the debate has been lively (Rabalais, 2002; Rönnberg and Bonsdorff, 2004; Howarth and Marino, 2006; Boesch et al., 2006). The following section will present the data used in the mass-balance calculations for salt, phosphorus and suspended particulate matter (SPM). A central part of this work is to compare modeled data on the target variables (salinity, phosphorus and nitrogen concentrations, Secchi depth, chlorophyll and oxygen concentrations) with empirical data. We will also present model predictions of cyanobacteria, SPM-concentrations, phosphorus concentration in sediments and sedimentation but in those cases there are no comparable reliable empirical data accessible to us. The main results concern the dynamic response of the system to reductions in nutrient loading and the analyses and interpretations of those results. It should be stresses that the CoastMab-model has previously been extensively tested and validated with good results for phosphorus from over 20 different coastal areas and more than 40 lakes, for suspended particulate matter in over 20 coastal areas and more than 10 lakes and for toxic substances (radionuclides and metals) in several lakes and coastal areas.
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2. INFORMATION ON THE HIMMERFJÄRDEN BAY 2.1. Previous Tests and Studies Himmerfjärden Bay (see Figure 1), situated about 60 km south of Stockholm at 59° 00‘ N, 17° 45‘, is a narrow bay divided into four sub-basins (Boesch et al., 2006). The basins are separated by thresholds, and just outside the outer basin, to the south, is the area Hållsfjärden. Hållsfjärden is commonly used as a reference area for Himmerfjärden and holds a reference station called B1. There are five sampling stations in Himmerfjärden, H2 to H6. Himmerfjärden is connected to Lake Mälaren in the north but the freshwater inflow to the bay is limited to a few short periods when the water levels in the lake are high (Elmgren and Larsson, 1997). Himmerfjärden has been monitored since the middle of the 1970s when sewage water from the area southwest of Stockholm was redirected from Lake Mälaren to Himmerfjärden. In 1974, the treatment plant in Himmerfjärden began to remove phosphorus and 96% of the phosphorus is, on average, removed today. The treatment plant initially served about 90 000 people but the population increased rapidly, causing an increase in primarily nitrogen fluxes. Today, the plant serves 240 000 people (Boesch et al., 2006). Extensive nitrogen removal has been implemented since the late 1990‘s reaching about 90 percent in 1998 (Larsson and Elmgren, 2001).
Figure 1. Himmerfjärden with the locations of sampling stations and treatment plant
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 189 It must be stressed that it has been assumed that the emissions from the sewage treatment plant contributes with flows of nitrogen of such significance that the regulation of emissions would have a clear effect on the eutrophication status in Himmerfjärden. This assumption was mainly based on the fact that total nitrogen concentration and inorganic concentrations of nitrogen before the spring bloom at station H4 correlated (r2 = 0.69, n = 16) with the load from the sewage treatment plant. Changes in eutrophication status have consequently been interpreted mainly as results of treatment plant regulatory measures (Elmgren and Larsson, 1997; Elmgren and Larsson, 2001; Larsson and Elmgren, 2001). The first large-scale experiment in Himmerfjärden was performed in 1983 when the concentration of phosphorus in the treatment plant discharge was allowed to increase to about fourfold (or twofold as compared to the amount discharged annually in 1983, i.e., 31 tons). According to Elmgren and Larsson (1997), no increase in primary production was observed following this increase in phosphorus loading but a slight increase in heterocytes (the nitrogen fixing cells in cyanobacteria) was noted and this increase occurred mainly at station B1 in the reference area possibly implying that the growth of cyanobacteria in Himmerfjärden reflects the growth in the adjacent sea. The second large-scale experiment started in 1985 when the treatment plant increased its capacity and began receiving sewage from Eolshälls treatment plant resulting in increased emissions of nitrogen to Himmerfjärden. The increase was followed by a successive decrease when nitrogen reduction processes were introduced and became more and more efficient reaching about 50 percent in 1992. As in the case with the first experiment, no increase in primary production occurred following increasing nitrogen inputs to the bay. Elmgren and Larsson (1997) suggested that phosphorus at this time was the main limiting nutrient in Himmerfjärden and that the excess nitrogen was exported to the adjacent sea causing increased eutrophication in the outside sea. As mentioned, Elmgren and Larsson (1997) found no significant correlation between eutrophication indicators, such as chlorophyll, phytoplankton production (biomass) or Secchi depth, and varying loads of nitrogen and phosphorus from the sewage treatment plant following the two first large-scale experiments. They concluded that further removal of phosphorus would not be meaningful since the emissions from the treatment plant constitute a small fraction of total loading of phosphorus. They recommended to increase nitrogen removal efficiency from treatment plant discharge. Following the recommendations from Elmgren and Larsson (1997) extensive nitrogen removal (about 90 percent) began in 1998. A third large-scale experiment was performed in 2001-2002 when emissions of nitrogen were deliberately doubled. As in the previous cases, no increase in chlorophyll a levels was observed by the increase in nitrogen from the sewage treatment plant (Boesch et al. 2006). According to Boesch et al. (2006) both the experiment in 1983 and the two experiments with increased nitrogen emissions may have been too small and or to short to result in clear changes in primary production in the bay. From this background, we will present several scenarios where the phosphorus emissions from the plant are increased and also the TP-fluxes from the sea. The idea is to quantify all key transport processes (see Figure 2) and see how the given changes, and potential remedial strategies, would influence not just the phosphorus concentrations in the bay but also key bioindicators (the Secchi depth, and concentrations of cyanobacteria and chlorophyll).
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Point source emissions Precipitation Inflow from catchment Surface water
Biouptake and retention in biota Water and TP exchange between the coast and the sea
Mixing
ET-sediments
Resuspension
Wave base Deep water
Sedimentation
Diffusion
Diffusion
Compaction
Active A-sediments Bioturbation
Burial
Biopassive A-sediments (geosphere)
Figure 2. An outline of transport processes (= fluxes) and the structure of the dynamic coastal model for phosphorus (CoastMab)
2.2. Data and Methods This work will use morphometric data from Khalili (2007) who made an analysis of the Himmerfjärden Bay using geographical information systems (GIS). Basin-specific data are compiled in table 1, which gives information on, e.g., total area; volume; mean depth; maximum depth; the volume of the surface-water layer and the deep-water layer; the section area, which defines the cross-sectional area that separates the given coastal area from the outside sea (Figure 3); the tributary water discharge to the bay; the discharge of water and phosphorus from the plant; the catchment area; latitude; and mean annual precipitation. Figure 3 shows the limiting section area which constitutes the boundary between the bay and the open sea, as determined using the topographical bottleneck method, i.e., so that the exposure attains a minimum value. From this figure, one can note that the deepest part of the section area is at 19 m, and this is also the reason for setting the theoretical wave base at 19 m in the Himmerfjärden Bay; above the theoretical wave base, there should be discontinuous sedimentation of fine sediments and particulate phosphorus, and areas of fine sediment erosion and transport; at larger water depths, there should be areas of fine sediment accumulation. So, the theoretical wave base separates the transportation areas (T), with discontinuous sedimentation of fine materials, from the accumulation areas (A), with continuous sedimentation of fine suspended particles (see Håkanson and Jansson, 1983). The Himmerfjärden Bay has been divided into two depth intervals: (1) The surface-water layer (SW), i.e., the water above the theoretical wave base at 19 m. (2) The deep-water layer (DW) is defined as the volume of water beneath the theoretical wave base (see table 1). It should be noted that the theoretical wave base is meant to describe average conditions. During storm events, the wave base will likely be at greater water depths (see Jönsson, 2005) and during calm periods at shallower depths. Khalili (2007) has presented a new
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 191 hypsographic curve and a corresponding volume curve for Himmerfjäden and those curves have been used in this work to calculate the volumes given in table 1. One can note that the area below the theoretical wave base (Dwb) is 46 km2 and that the SW-volume is 2.6 km3, the volume of the DW-layers is small (only 0.24 km3) and the entire volume is 2.88 km3. The boundary lines for the Himmerfjärden Bay used in this work are from Khalili (2007); the total section area (At), which provides a minimum value of the exposure (Ex=100·At/A; see Pilesjö et al., 1991, for more information regarding the topographical bottlerneck method to objectively define the boundary lines for coastal areas) is 45310 m2, which gives an exposure (Ex) of 0.0194, indicating the enclosed character of the bay. Table 1. Data on Himmerfjärden Bay (see Kahlili, 2007, for more information) Catchment area (ADA in km2) Annual precipitation (Prec, mm/yr) Area (A in km2) Area below wave base at 19 m (ADwb in km2) Maximum depth (Dmax in m) Wave base (Dwb in m) Dynamic ratio (DR=√A/Dm) Areas of fine sediment erosion and transport (ET, dim. less) Exposure (Ex=100·At/A) Form factor (Vd=3·Dm/Dmax) Land rise (LR, mm/yr) Latitude (Lat, °N) Mean depth (Dm=V/A, m) Water flow from plant (Qplant, m3/yr) Water flow from rivers (Qtrib, m3/yr) Section area (At, m2) TP-emissions from plant (FTPplant, kg/yr) Volume of DW-layer (VSW, km3) Volume of SW-layer (VDW, km3) Total volume (V, km3)
1 268 460 234 46 52 19 1.24 0.80 0.0194 0.71 4 59 12.3 35 000 000 491 600 000 45 310 1 632 0.236 2.642 2.878
Water depth (m)
5 0
1000
2000
3000
4000
5000
Section length (m)
-5 -10 -15 -20
Figure 3. Limiting section area profile between Askö-Torö in the Himmerfjärden Bay
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Lars Håkanson and Maria I. Stenström-Khalili Table 2. Monthly data on driving variables (mean monthly number of hours with daylight), surface-water (SW) salinity in the sea outside of Himmerfjärden Bay (the Baltic proper, BP), Secchi depth outside the bay, TP in SW and DW-water outside the bay and SW and DW-temperatures in the bay. MV = mean value; M50 = median; SD = standard deviation Month 1 2 3 4 5 6 7 8 9 10 11 12 MV M50 SD
Daylight hr/month 9.1 11.8 14.3 17.1 18.5 18.1 15.8 13.0 10.1 7.3 6.4 6.4 12.3 12.4 4.5
SalinitySWBP psu 7.18 7.12 7.01 7.01 7.06 6.96 6.96 6.93 6.92 7.00 7.09 7.09 7.03 7.01 0.08
SecchiBP psu 8.5 8.5 7.0 9.0 7.6 5.3 5.5 6.7 8.5 9.5 7.8 7.8 7.7 7.8 1.3
TPSWBP µg/l 30.1 27.2 22.1 18.2 18.1 16.6 17.9 19.3 23.1 25.9 30.9 30.9 23.4 22.6 5.5
TPDWBP µg/l 31.2 29.3 24.3 21.2 22.4 24.5 24.8 26.0 27.1 26.9 33.3 33.3 27.0 26.5 4.0
TempSW °C 0.7 1.1 3.0 8.0 12.6 16.1 18.0 14.6 10.8 7.6 1.3 1.3 7.9 7.8 6.4
TempDW °C 1.3 1.2 2.3 4.0 5.9 7.5 8.3 8.0 8.1 7.1 2.1 2.1 4.8 4.9 2.9
Table 2 shows the driving variables used in this work (calculated from the ongoing monitoring program for the period 1997 to 2007). This table gives monthly mean values for the number of hours with daylight (needed to calculate chlorophyll concentration), salinity in the surface water outside the Himmerfjärden Bay in the Baltic Proper (needed in the massbalance calculation of salt inflow from the Baltic Proper), the Secchi depth in the area outside of Himmerfjärden (needed to calculate the inflow of SPM from the Baltic Proper), the total phosphorus (TP) concentrations in the SW and DW-layers in the area outside of Himmerfjärden (needed to calculate the inflow of TP from the Baltic Proper), and the empirical monthly SW and DW-temperatures in the Himmerfjärden (needed to quantify mixing). In the following modeling, we will compare the modeled values for the target variables mainly to the confidence intervals related to ± 1 standard deviation of the mean monthly empirical data accessible to us from the bay.
3. THE DYNAMIC COASTWEB-MODEL The model consists of five compartments: surface water (SW), deep water (DW), erosion/transportation areas for fine sediments (ET), accumulation areas for fine sediments below the theoretical wave base (A) and biota with short turnover times (BS; plankton). There are algorithms for all major internal fluxes of salt, TP and SPM (outflow, TP and SPM from land uplift, sedimentation of particulate TP and SPM, resuspension of TP and SPM, diffusion
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 193 of salt and dissolved phosphorus, mixing, biouptake of dissolved phosphorus and burial of TP and SPM and mineralization of the organic fraction of SPM; see Håkanson and Eklund, 2007 and Håkanson, 2006 which give and motivate all equations and model variables). Table 3 gives a compilation of all equations and model variables related to the CoastMab-model for salt. Table 3. A compilation of all equations and model variables in the mass-balance model for salt (CoastMab). Abbreviations: F for flow (kg/month), R for rate (1/month), C or Sal for concentration (‰ = psu = kg/m3), DC for distribution coefficients (dimensionless), M for mass (kg salt), D for depth in m, A for area in m2, V for volume in m3; ET stands for areas with erosion and resuspension (advection) of fine sediments above the theoretical wave base; T is the theoretical retention time (years); flow from one compartment (e.g., SW) to another compartment (e.g., DW) is written as FSWDW; mixing flow is abbreviated as FxDWMW; Q is water discharge (m3/month) Surface-water layer (SW) MSW(t) = MSW(t - dt) + (FxMWSW + Ftrib + Fprec + FdDWSW + FInSW +FplantSW - FoutSW - FxSWDW – Feva)·dt INFLOWS: FxDWSW = MDW·RxSWDW·VSW/VDW; mixing from DW to SW (kg/month) Ftrib = Qtrib·Saltrib; tributary inflow of salt (kg/month) Fprec = Qprec·Salprec; precipitation of salt (kg/month) FdDWSW = Qprec·Salprec; precipitation of salt (kg/month) FdDWSW= MDW·Diffcoeff ·Diffconst; diffusion from DW to SW (kg/month) FinSW = Qin·SalSWBP; inflow of salt to SW (kg/month) FplantSW = QplantSW·Salplant; inflow of salt to SW from water purification plant (kg/month) OUTFLOWS: FoutSW = QoutSW·SalSW; outflow of salt from SW (kg/month) FxSWDW = MSW·RxSWDW; mixing from SW to DW (kg/month) Feva = Qeva·Saleva; evaporation of salt from SW (kg/month) Deep-water layer (DW) MDW(t) = MDW(t - dt) + (FxSWDW + FinDW - FxMWSW - FdDWSW – FoutDW)·dt INFLOWS: FxSWDW = MSW·RxSWDW; mixing from SW to DW (kg/month) FinDW = QinDW·SalDWBP; inflow of salt to DW (kg/month) OUTFLOWS: FxDWSW = MDW··RxSWDW·VSW/VDW; mixing from DW to SW (kg/month) FdDWSW = MDW·Diffcoeff ·Diffconst; diffusion from DW to SW (kg/month) FoutDW = SalDW·QoutDW; outflow of salt from DW (kg/month) Model variables Area = 234·106; coastal area (m2) Area below wave base (AWB) = 46·106; (m2) Saleva = 0; salinity in evaporating water (psu) Salplant = 0; salinity in water from plant (psu) Salprec = 0; salinity in precipitation (psu) Saltrib= 0; salinity in tributary water (psu)
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Table 3. (Continued) Diffconst = 0.05/12; diffusion rate (1/month) DCSWDW = 0.9; distribution coefficient regulating water inflow from the sea to the SW and DW layers in the bay DCSWDWplant = 0.99; distribution coefficient regulating water inflow from the plant to the SW and DW layers in the bay Diffcoeff = if SalSW > SalDW then 0 else (SalDW-SalSW); diffusion coefficient ET = (Area-AWB)/Area; distribution coefficient (fraction of ET-areas) Exposure (Ex) = (100·At·10-6)/(Area·10-6) Mean depth (dm) = 12.3: (m) Rxdef = Strat·ET/12; default mixing rate (1/month) Rxexp = 2; mixing rate expotent RxSWDW = if SalDW > SalSW then Rxdef·(1/(1+SalDW-SalSW))^ Rxexp else Rxdef; mixing rate (1/month) Prec = 460; mean annual precipitation (mm/yr) Qemp = if SWT < 5 °C then 491.6·106 else (491.6·106-Qplant); annual empirical freshwater inflow (m3/yr) Qeva = 0.9·Qprec; water transport related to evaporation (m3/month) QinSW = DCSWMW·Qin; water inflow to SW from the sea (m3/month) Qin = 4500·106; total water inflow from the sea (m3/month) QinDW = Qin·(1-DCSWMW); water inflow to DW from the sea (m3/month) QmixDWSW = FxDWSW/SalDW; mixing water flow (m3/month) QoutDW = (QinSW+QinDW+Qtrib+Qprec)-(QoutSW+Qeva)+Qplant/12; outflow of water from DW (m3/month) QoutSW = /QinSW+Qprec+Qtrib-Qeva); outflow of water from SW (m3/month) Qprec = Area·Prec·0.001/12; water flow from precipitation (m3/month) QplantDW = (1-DCSWDWplant)·35·10^6 QplantSW = DCSWDWplant·35·10^6 Qtrib = (Qemp/12)·YQ SalDW = MDW/VDW; DW salinity (psu) SalSW = MSW/VSW; SW salinity (psu) Section area(At) = 45310 (m2) Strat = if ABS(SWT- DWT) < 4 °C then Strat = (1+1/(1+ABS(SWT- DWT)) else 1/ABS(SWT- DWT; temperature dependent stratification SWT = surface water temperatire (°C) TDW = VDW/(QinDW+QmixMWSW); theoretical deep water retention time (months) VDW = 0.236·10^9; DW volume (m3) V = Area·Mean_depth; volume (m3) VSW = (V-VDW); SW volume (m3) Wave base = 19 m To calculate the inflow of salt, TP and SPM to the Himmerfjärden Bay (HI) from the Baltic Proper (BP), data on the concentrations in the SW and DW-layers in the Baltic Proper from table 2 have been used. The inflows to the two layers from the Baltic Proper are given by the water discharges in table 4 (QSWBPHI and QDWBPHI) and the given concentrations. The empirical Secchi depths in table 2 have been recalculated into SPM-values (the suspended particles regulate the light scattering in the water and the Secchi depth) by eq. 1 (from Håkanson, 2006): SPMSW = 10^(-0.3-2·(log(Sec)-(10^(0.15·log(1+SalSW)+0.3)-1))/
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 195 Table 4. Compilation of calculated monthly data (using the mass-balance for salt) for water transport (Q in million m3/yr) related to evaporation (Qeva), surface water (SW) inflow from the Baltic Proper (BP) to Himmersfjärden Bay (HI), deep-water (DW) inflow from BP to HI, mixing from DW to SW in HI, DW outflow from HI to BP, SW outflow from HI to BP, water flow related to direct precipitation onto the surface area of HI (Qprec), inflow of water to SW and DW from the water treatment plant (QSWplant and QDWplant) and freshwater inflow from tributaries (Qtrib). MV = mean value; M50 = median; SD = standard deviation. Month 1 2 3 4 5 6 7 8 9 10 11 12 MV M50 SD
Qeva 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 8.1 0
QSWBPHI 4050 4050 4050 4050 4050 4050 4050 4050 4050 4050 4050 4050 4050 4050 0
QDWBPHI 450 450 450 450 450 450 450 450 450 450 450 450 450 450 0
QDWSWx 278 303 248 37 18 13 10 13 151 276 243 256 154 197 125
QDWHIBP 453 453 453 453 453 453 453 453 453 453 453 453 453 453 0
QSWHIBP 4104 4095 4099 4110 4110 4084 4078 4076 4078 4081 4097 4097 4092 4096 13
Qprec 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9 9 0
((10^(0.15·log(1+ SalSW)+0.3)-1)+0.5))
QSWplant 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 0
QDWplant 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0
Qtrib 52.9 44.3 47.9 59.1 59.4 33.2 27.1 25.0 26.7 30.3 46.4 46.4 42 45 13
(1)
So, SPM-values (in mg/l) are calculated from measured Secchi depths (in m) and the salinity of the SW-layer in the area outside Himmerfjärden (SalSW in psu). The higher the salinity, the higher the aggregation and the higher the Secchi depth. Figure 4 A and B give comparisons between modeled salinities and measured values (instead of using the mean or median empirical data, we prefer to give the uncertainty bands related to ± 1 standard deviation). The idea is that the modeled values should lie in-between these uncertainty bands. This is one main way of controlling the model predictions, another way is shown in table 5. From extensive measurements in many coastal areas (see Håkanson et al., 1986), one can conclude that typical water velocities in limiting section areas generally range between 1 and 15 cm/s for coastal areas in the Baltic Sea. Lower mean velocities than 1 cm/s would be rather unrealistic on a monthly basis. The water velocity in the section area has been calculated for the total outflow (m3/yr) divided by half the section area since there is also inflow of water to maintain a given water level ((m3/yr)·(1/(0.5·m2). These calculations give an average velocity in the section area of 7.7 cm/s, which is in the middle of the expected range. Another way to check the modeled water fluxes between the coast and the sea is to compare these model predictions from the mass-balance for salt with data from an empirically-tested model for the theoretical water retention time. It has been shown (Persson et al., 1994) that TSW can be predicted very well (r2 = 0.95) with the regression in eq. 2, which is based on the exposure (Ex), which, in turn is a function of section area (At) and coastal area (Area). The range of this model for TSW is given by the minimum and maximum values for
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Ex of 0.002 < Ex < 1.3; Ex = 0.0194 for Himmerfjärden Bay is well within this range. The model should not be used without complementary algorithms if the tidal range is > 20 cm/day or for coastal areas dominated by fresh water discharges. For open coasts, i.e., when Ex > 1.3, TSW may be calculated not by this equation but from a model based on coastal currents (Håkanson, 2006) . ln(TSW) = (-4.33·(√Ex) + 3.49)
(2)
From table 5, one can note the good correspondence between TSW-values calculated using the mass-balance for salt (mean value = 0.62 months) and with eq. 2 (mean value = 0.59 months). One can also see from table 5 that the theoretical deep-water retention time, TDW, is short (0.41 months on average) because the volume of the DW-layer is small and TDW is defined from the ratio between the volume of the DW-layer and the total water flux to the DW-layer. Table 5. Modeled monthly values the flow velocity of water in the section area, the theoretical surface-water (SW) retention time calculated from the mass-balance for salt (TSW), and from the empirical morphometrical formula based on the exposure (Ex) (TSWEx) and for the deep-water (DW) according to the mass-balance for salt (TDW). MV = mean value; M50 = median; SD = standard deviation Month
1 2 3 4 5 6 7 8 9 10 11 12 MV M50 SD
Monthly flow velocity uAt, cm/s 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 7.66 0
Theor. wat. Theor. wat. Theor. wat. ret. time ret. time ret. time TSWEx, months TSW, months TDW, months 0.59 0.60 0.32 0.59 0.59 0.31 0.59 0.60 0.34 0.59 0.63 0.48 0.59 0.63 0.50 0.59 0.64 0.51 0.59 0.64 0.51 0.59 0.64 0.51 0.59 0.62 0.39 0.59 0.60 0.33 0.59 0.60 0.34 0.59 0.60 0.33 0.59 0.62 0.41 0.59 0.62 0.39 0 0.02 0.09
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 197
Figure 4. Comparison between modeled values and uncertainty bands for the empirical mean values representing ± 1 standard deviation for A. SW-salinity, B. DW-salinity, C. TP-concentration in SW, D. TP-concentration in DW, E. Chlorophyll, F. Secchi depth, G. O2-concentration in DW, H. modeled TPconcentration in accumulation area sediments in relation to minimum and maximum reference values, I. modeled TN-concentration in relation to ±1 standard deviations for the empirical mean values, J. modeled TN/TP-ratios in relation to the Redfield ratio (7.2 in g) and the Threshold ratio (15 in g), K. modeled values of cyanobacteria, and L. modeled SPM-concentrations in the SW and DW-layers
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Also note that there has been no calibration or tuning regarding the water fluxes given in table 4 and that these fluxes are used also to calculate the TP and SPM-fluxes. The monthly data on tributary water discharge used in the modeling have been calculated from the empirical average annual value using the dimensionless moderator for this purpose (from Abrahamsson and Håkanson, 1998). When empirical data from 119 rivers were compared to modeled values, the r2-value was 0.84. This model has also been described and successfully used in many previous contexts (see, e.g., Håkanson, 2006).This moderator is based on data on the size of the catchment area, mean annual precipitation and latitude (see table 1). Since we do not have access to reliable empirical monthly data on tributary water discharge for the study period (1997 to 2007), it should be stressed that this modeling concerns average, characteristic conditions on a monthly basis for this period of time and not the actual sequence of months. The theoretical water retention times in the two layers from the basic mass-balance for salt (see table 4) are used together with the temperature-dependent mixing rate in the massbalance model as indicators of how the turbulent mixing influences the settling velocity for particulate phosphorus and SPM – the faster the water renewal, the more turbulence, the lower the settling velocity. The mixing rate regulating the monthly transport of water, salt and nutrients between the surface and the deep-water layers depends on the difference in temperature and salinity between the two layers and the form of the basin, as given by the areas of fine sediment erosion and transport (ET) (see Table 3). The small TP-input from precipitation onto the water surface of the Himmerfjärden Bay has been estimated from the characteristic annual precipitation of 460 mm and a TP-concentration in the rain of 5 µg/l (see Håkanson and Eklund, 2007). The internal processes are: sedimentation of particulate phosphorus from surface water to deep water (FTPSWDW), sedimentation from SW to areas of erosion and transportation (FTPSWET), sedimentation from DW to accumulation areas (FTPDWA), resuspension (advection) from ET-areas (including TP from land uplift, FTPLU) either back to the surface water (FTPETSW) or to the deep water (FTPETDW), diffusion of dissolved phosphorus from accumulation area sediments to the DW-layer (FTPADWd), diffusion from DW-water to SWwater (FTPDWSWd), upward and downward mixing between SW and DW (FTPDWSWx and FTPSWDWx) and biouptake and elimination of phosphorus from biota (FTPSWBS and FTPBSSW). When there is a partitioning of a flux from one compartment to two compartments, this is handled by a distribution coefficient (DC). 1. The DCs regulating the amount of phosphorus in particulate and dissolved fractions in the SW and DW-layers. These DCs are called particulate fractions (PF). By definition, only the particulate fraction of a substance is subject to gravitational sedimentation and only the dissolved fraction (DF = 1 – PF) may be taken up by biota. Table 6 gives a compilation of calculated PF-values for the SW and DWcompartments. The CoastMab-model uses an algorithm to calculate the PF-value for phosphorus in the surface-water layer based on the biouptake of dissolved P (the higher the biouptake of dissolved P, the higher the PF-value) and the resuspension of particulate P (which depends on the stratification; the more homothermal the water, the more resuspension and the higher the PF-value). The default PF-value is 0.56, which is a general, average empirical value based on extensive data from many aquatic systems (see Håkanson and Boulion, 2002; Håkanson and Bryhn, 2008a, b).
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 199 So, the default PF-value is modified by the two dimensionless moderators for biouptake and stratification/resuspension, as explained in Håkanson and Eklund (2007). The PF-value for the deep-water layer is also calculated from resuspension/stratification, the resuspended fraction of phosphorus in the deep-water layer (which is calculated automatically in the model) and the monthly temperature of the deep-water layer, which regulates the bacterial decomposition of organic material, and hence also the oxygen consumption and the dissolved fraction of phosphorus (see Håkanson and Eklund (2007). One can note that the PF-values in the SW-compartment vary between 0.2 and 0.87 depending on season of the year (and how much TP is bound in biota) and that the PF-values in the DW-compartment are low during stratified conditions (when most phosphorus appear in dissolved form). The mean PFSW-value is 0.51 (see table 6). 2. The DC regulating sedimentation of particulate phosphorus either to areas of fine sediment erosion and transport (FTPSWET) or to the DW-areas beneath the theoretical wave base (FTPSWDW). The ET-value is 0.80 (i.e., 80% of the total area of the bay are dominated by areas with fine sediment erosion and transport). 3. The DC describing the resuspension flux from ET-areas back either to the surface water (FTPETSW) or to the DW-compartment (FTPETDW), as regulated by the form factor (Vd, where DC=Vd/3, Vd = 3·Dm/Dmax, Dm = the mean depth, Dmax = the maximum depth). 4. The DC describing how much of the TP in the water that has been resuspended (DCres) and how much that has never been deposited and resuspended (1-DCres) in the SW and DW-layers. The resuspended fraction settles out faster than the materials that have not been deposited. Table 6. Modeled monthly values related to accumulation area sediments 0-10 cm; bulk density, organic content (= loss on ignition), water content, sedimentation and fall velocities of suspended particulate matter and particulate phosphorus. MV = mean value; M50 = median; SD = standard deviation Month
1 2 3 4 5 6 7 8 9 10 11 12 MV M50 SD
Bulk Organic Water Sedimentation Sedimentation Fall Fall Particulate Particulate density content content velocity velocity fraction fraction bg IG W SedDW SedDW vSW vDW PFDW PFSW g ww/cm3 g/g dw % ww µg/cm2·d cm/yr m/month m/month 1.17 6.3 75 12.1 0.01 2.4 2.3 0.22 0.22 1.17 6.3 75 11.2 0.01 2.4 2.3 0.23 0.20 1.17 6.3 75 10.8 0.01 2.4 2.2 0.23 0.26 1.17 6.3 75 14.6 0.02 2.5 2.2 0.02 0.81 1.17 6.3 75 17.8 0.02 2.4 2.2 0.01 0.82 1.17 6.3 75 19.5 0.02 2.4 2.3 0.01 0.86 1.17 6.3 75 21.6 0.03 2.4 2.3 0.01 0.87 1.17 6.3 75 18.6 0.02 2.4 2.3 0.02 0.80 1.17 6.3 75 11.8 0.01 2.5 2.3 0.53 0.46 1.17 6.3 75 12.3 0.02 2.5 2.2 0.37 0.31 1.17 6.3 75 13.2 0.02 2.5 2.3 0.18 0.27 1.17 6.3 75 12.6 0.02 2.5 2.3 0.20 0.23 1.17 6.3 75 14.7 0.018 2.4 2.3 0.17 0.51 1.17 6.3 75 12.9 0.020 2.4 2.3 0.19 0.39 0 0 0 3.7 0.0062 0.051 0.036 0.17 0.29
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Land uplift (FLU) is a special case. Land uplift is a main contributor of TP to the Baltic Proper (Håkanson and Bryhn, 2008b). From the map illustrating the spatial variation in land uplift (see Voipio, 1981), one can calculate that the mean land uplift in the Himmerfjärden Bay is about 4 mm/yr and this value has been used in these calculations. Land uplift has been discussed in many contexts (Voipio, 1981; Jonsson et al., 1990; Jonsson, 1992) and the algorithm to quantify how land uplift influences the fluxes of TP and SPM has been given by Håkanson and Bryhn (2008b). The total area above the theoretical wave base in the Himmerfjärden is about 188 km2 and the sediments in this area will be exposed to increased erosion by wind/wave action due to the land uplift. The sediments in the shallower parts, which may have been deposited more than 1000 years ago, will be more consolidated than the recent materials close to the theoretical wave base. The calculation of the TP-flux from land uplift uses (1) modeled data on the TP-concentration in the accumulation area sediments from the DW-zone, (2) a water content of the sediments exposed to increased erosion set to be 15% lower than the modeled water content of the recent sediments and (3) the total volume of sediments above the theoretical wave base lifted each year. To calculate the TP-uptake and retention in biota, this modeling uses a similar approach as presented by Håkanson and Boulion (2002). This means that the uptake and retention in biota depends on concentration of dissolved P, daylight, temperature and the turnover time of the modeled organisms. It is given by: MBSTP(t) = MBSTP(t - dt) + (FTPbioup - FTPbioret)·dt
(3)
MBSTP(t) = The mass (amount) of TP in biota with short turnover times (plankton) (g). FTPbioup = MSWTP·YSWT·(30/TBL)·(DayL/12.3)·(DFSW/0.44); the biouptake of TP in biota (g/month). FTPbiore = MBLTP·30/TBL; the retention (= outflow) of TP from biota (g/month). YSWT = (SWT/11.85); the dimensionless moderator regulating the temperature dependent biouptake of TP. TBS = the average turnover time for the functional groups included in biota (phytoplankton 3.2 days, bacterioplankton = 2.8 days and herbivorous zooplankton = 6 days). SWT = The surface water temperature (°C); 11.85 = the mean surface water temperature for the growing season (°C). DFSW = the dissolved particulate fraction of phosphorus in surface water (dim. less); 0.44 is a standard reference value for DF (see Håkanson and Boulion, 2002). DayL= the number of days with daylight (see table 2); 12.3 is the mean annual value; so, this is a dimensionless moderator for the influence of light on the primary production.
3.1. Regressions between Modeled TP-Values versus Total-N and Different Bioindicators It is well established (Redfield et al., 1963) that plankton cells have a typical atomic composition of C106N16P, which means that 16 times as many atoms (and 7.2 times as many grams) are needed of N than of P to produce phytoplankton. This means that one generally
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 201 finds a marked co-variation between phosphorus and nitrogen concentrations in aquatic systems (see Wallin et al., 1992) and in this work total nitrogen (TN) concentrations have been predicted from dynamically modeled monthly TP-concentrations using a regression from Håkanson and Eklund, 2007). The regression is: log(TN) = 0.70·log(TP) + 1.61
(4)
(r2 = 0.88; n = 58 coastal systems) There are several reasons why we have not done any dynamic, process-based massbalance modeling for nitrogen. To the best of our knowledge, there are no general algorithms, which could be used within the framework of existing general mass-balance models that can quantify nitrogen fixation either from the atmosphere or from sources within a given aquatic systems in a reliable manner. The main reason for this is the lack of well-tested, practically useful approaches to predict the concentration of nitrogen fixing bluegreen algae. Studies have shown (Rahm et al., 2000) that atmospheric nitrogen fixation may be very important in contexts of mass-balance calculations for nitrogen in the Baltic Sea. Lacking empirically well-tested algorithms to quantify atmospheric and internal nitrogen fixation, crucial questions related to the effectiveness of remedial measures to reduce nutrient discharges to aquatic systems cannot be properly evaluated. It also means that it is generally very difficult to understand, model and predict changes in measured TN-concentrations in the water phase, since such changes in concentrations are always mechanistically governed by mass-balances, i.e., the quantification of the most important transport processes regulating the given concentrations. The problem to understand and predict TN-concentrations in marine systems is accentuated by the fact that there are no (to the best of our knowledge) practically useful models to quantify the particulate fraction for nitrogen in saltwater systems (but such approaches are available for phosphorus in lakes and brackish systems, see Håkanson and Eklund, 2007). In mass-balance modeling, it is imperative to have a reliable algorithm for the particulate fraction of nitrogen, since the particulate fraction (PF) is the only fraction that by definition can settle out due to gravity. From previous modeling work (see, e.g., Floderus, 1989), one can conclude that it is also very difficult to quantify denitrification. Denitrification depends on sediment red-ox conditions, i.e., on sedimentation of degradable organic matter and the oxygen concentration in the deep-water zone, but also on the frequency of resuspension events, on the presence of mucus-binding bacteria, on the conditions for zoobenthos and bioturbation. Given this complexity, it is easy to understand why empirically well-tested algorithms to quantify denitrification on a monthly basis do not exist to the best of our knowledge. The atmospheric wet and dry deposition of nitrogen may be very large (in the same order as the tributary inflow) and patchy (Wulff et al., 2001), which means that for, e.g., large coastal areas and relatively smaller systems far away from measurement stations, the uncertainty in the value for the atmospheric deposition is also generally very large. Total phosphorus is since long recognized as generally the most crucial limiting nutrient for lake primary production (Schindler, 1977, 1978; Chapra, 1980; Boers et al., 1993; Wetzel, 2001). Nitrogen is regarded as a key nutrient in some marine areas (Redfield, 1958; Ryther and Dunstan, 1971; Nixon and Pilson, 1983; Howarth and Cole, 1985; Howarth, 1988; Hecky and Kilham, 1988; Ambio, 1990; Nixon, 1990). Håkanson et al. (2007) demonstrated from a very comprehensive comparative study that only 9 systems out of 533 covering a very wide size and salinity domain were nitrogen limited in the sense that the TN/TP-ratios were lower
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than 7.2 for the growing season and 34% of the systems had TN/TP-ratios lower than 15. They also demonstrated that there is an increasing risk for harmful algal blooms (of cyanobacteria) when the TN/TP-ratio is below 15. One should note that also Guildford and Hecky (2000) stressed that long-term nutrient limitation is generally governed by phosphorus and not by nitrogen in both lakes and marine systems. This is a good reason for the massbalance modeling for phosphorus discussed in this work. There are also clearly increasing risks of harmful algal blooms if the water temperature is above 15 °C (Edler, 1979; Wasmund, 1997; Håkanson et al., 2007). In this work, the modeling is done on a monthly basis and in the CoastMab-model there is information on the dissolved fraction of phosphorus. This means that the basic approach for the mean conditions during the growing season (ChlGS in µg/l; eq. 5) has been modified to predict the requested mean monthly chlorophyll values (Chl). These calculations use simple dimensionless moderators to account for seasonal/monthly changes in the light conditions (DayL; mean monthly number of hours with daylight in the Himmerfjärden Bay; from standard tables) and in the amount of bioavailable/dissolved phosphorus (DFSW). This means the chlorophyll-a concentration are predicted from: Chl = (DayL/12.3)·(DFSW/0.44)·ChlGS
(5)
Where the basic model between the TP-concentration in the SW-layer (TPSW in µg/l, modeled), the salinity in the SW-layer (SalSW, modeled) and ChlGS is given in table 7A. (DayL/12.3) is a dimensionless moderator based on the ratio between the monthly DayLvalues divided by the mean annual number of hours with daylight (12.3) at this latitude (59 °N). The modeled monthly values of the dissolved fraction in the SW-layer (DFSW) have been transformed into a dimensionless moderator by division with the average DF-value of 0.44 for phosphorus in surface water conditions. This means that the predicted chlorophyll values are low if DF is low, the number of hours with daylight low and the modeled TP-values low. The small variations in salinity (see Figure 4A and B) will not influence the predicted Chl-values very much, but such variations are also accounted for. The basic model to predict mean chlorophyll-a concentrations for the growing season from TP-concentrations was tested by Håkanson and Eklund (2007) and gave an average error when empirical data were compared to modeled data of 0.06; the standard deviation for the 21 tested coastal areas was 0.55, which corresponds to the 95% confidence interval for the uncertainty in the empirical data. This means that it is probably not possible to predict better than this. However, the range in the empirical data only covered coastal areas from the Baltic Sea. The empirically-based model to predict the total concentration of cyanobacteria (Håkanson et al., 2007) is given in table 7B. The following simulations will use dynamically modeled monthly TP-concentrations in the SW-layer, empirical mean monthly SWtemperatures, dynamically modeled SW-salinities and modeled monthly TN-concentrations in the SW-layer (see eq. 4) to predict monthly values of cyanobacteria in the SW-layer. Note that there are no empirical data available to us to test the predicted values for cyanobacteria, but these values are basically predicted from an empirical approach which yielded an r2-value of 0.78 (coefficient of determination), which is close to the maximum possible predictive power for cyanobacteria because of the inherently very high coefficient of variation (CV) for cyanobacteria (see Håkanson et al., 2007). Nitrogen fixation by different species of
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 203 cyanobacteria counteracts long-term nitrogen deficits, and the N-fixation rate depends on the TP-concentration, water temperature and the TN/TP-ratio (see Figure 4). When the mean O2-concentration is lower than about 2 mg/l, and the mean oxygen saturation (O2Sat in %) lower than about 20%, many key functional benthic groups are extinct (Pearson and Rosenber, 1976). Empirical data on the amount of material deposited in deepwater sediment traps (1 m above the bottom; SedDW in g dw/m2·day) were used in deriving the model for oxygen used in this modeling (see eq. 6, from Håkanson, 2006). This empirical model for oxygen is put into the dynamic SPM-model and the empirical data on sedimentation in the deep-water zone (SedDW) will be replaced by modeled values of SedDW from the dynamic SPM-model. The values for the O2-concentration (mg/l) calculated in this manner for the growing season will be compared to empirical oxygen data from the Himmerfjärden Bay. O2=0.1·(101-10^(0.47+0.643·log(SedDW)+0.323·Dm^0.50.118·(100·ET)^0.5+(1/QFS)·0.301·log(1+TDW))))
(6)
Of all the many factors that could, potentially, influence the O2-concentration in the DWzone, the following were shown (using stepwise multiple regression analysis using data from 23 Baltic Sea coastal areas) to be most important: 1. Sedimentation in the deep-water layer (SedDW); the more oxygen-consuming matter in the deep-water zone, the lower O2. 2. The prevailing bottom dynamic conditions in the coastal area (ET, i.e., the erosion and transport areas). If variations among coastal areas in ET are accounted for. If ET is high (say 0.95), the oxygenation is also likely high and O2 high, and vice versa. 3. The theoretical deep-water retention time (TDW); variations in mean O2 among coastal areas can also be statistically related to variations in TDW; the longer TDW, the lower O2. This is logical and mechanistically understandable. 4. The mean depth (Dm); the mechanistic reason for this is not so easy to disclose since Dm influences different factors, e.g., (1) resuspension, (2) the volume and hence all SPM-concentrations, (3) stratification and mixing, and (4) the depth of the photic zone and, hence, primary production. However, coastal areas with small mean depths generally have clear water, little SPM, low sedimentation and high O2. Fine suspended particles in open coastal areas will be transported out of the area and not be entrapped in the same manner as in closed lagoons or lakes. If variations among coastal areas in Dm are accounted for, the r2 value was 0.80 when tested for 23 Baltic coastal areas (data from Wallin et al., 1992). 5. The oxygen model was basically derived using data from coastal areas without freshwater inflow. For coastal areas with freshwater inflow, the factor QFS will account for tributary influences (Qtrib) in the following way: If Qtrib = 0 then QFS = 1 else QFS = ((Qtrib+Qsalt)/Qsalt)^(120/(1+TDW)))
(6)
Where the theoretical deep-water retention time (TDW) is given in days. Dimictic coastal areas in the Baltic Sea (i.e., coastal areas which become homothermal in the
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Lars Håkanson and Maria I. Stenström-Khalili spring and in the fall) rarely have longer characteristics TDW-values than 120 days. Qsalt is the total inflow (QSW plus QDW) of saline water from the outside sea. This means that if TDW is 12.3 days as it is in the Himmerfjärden Bay, if Qtrib is 1% of Qsalt (see table 4), QFS is 2.2 and the predicted O2-concentration 7.3 mg/l and not 6.5 mg/l as it would have been expected if the coastal area did not have any tributary inflow. This oxygen model should not be used for coastal areas dominated by tides.
The following section will demonstrate how this modeling predicts the salinities in the two layers, the TP-concentrations, Secchi depths, cyanobacteria and nitrogen concentrations and also other variables of interest, such as TP-concentrations in sediments (0-10 cm) below the theoretical wave base (the accumulation-area sediments), sedimentation in the two layers, settling velocities for particulate phosphorus (and suspended particulate matter) and the particulate fractions (PF = 1-DF). Whenever possible, the modeled values will be compared to empirical data and to the uncertainty bands related to the empirical data. All calculated TPfluxes in Himmerfjärden Bay and all calculated TP-amounts (= where would one find the TP?) will be given. Table 7A. The model for chlorophyll-a (from Håkanson and Eklund, 2007). The model predicts median summer values for chlorophyll in surface water from total phosphorus and salinity Chl = Ysal·TP Ysal = if Y3 <0.012 then 0.012 elseY3 Y1 = if salinity < 2.5 then (0.20-0.1·(salinity/2.5-1)) else (0.20+0.02·(salinity/2.5-1)) Y2 = if salinity< 12.5 then Y1 else (0.28-0.1·(salinity/12.5-1)) Y3 = if salinity> 40 then (0.06-0.1·(salinity/40-1)) else Y2 Chl = chlorophyll-a concentration in μg/l; TP = TP-concentration in surface water in μg/l; salinity in psu Ysal = dimensionless moderator for the influence of salinity on chlorophyll B. The model for cyanobacteria (from Håkanson et al., 2007). The model predicts median summer values for total cyanobacteria in surface water from total phosphorus, total nitrogen, salinity and surface-water temperatures. CB = ((5.85·log(TP)-4.01)4)·YTNTP·YSWT·Ysal YTNTP = if TN/TP < 15 then (1-3·(TN/TP/15-1)) else 1 YSWT = if SWT ≥ 15 then (0.86+0.63·((SWT/15)1.5-1)) else (1+1·((SWT/15)3-1)) Ysal = if salinity <10 then (2.1+1.1·((salinity/10)2-1)) else (2.1-115·((salinity/10)0.01-1)) CB in μg ww/l; salinity in psu; SWT= Surface water temperature in °C; Total-N (TN) in μg/l; Total-P (TP) in μg/l Model domain: 4 < TP < 1300; 165 < TN < 6830; 0 < salinity < 40; 8 < SWT < 25
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 205
4. RESULTS 4.1. Modeled Values versus Empirical Data Figure 4 shows modeled values compared to the standard deviations for the mean empirical values monthly data for the period 1997 to 2007. If the model yields values close to the empirical mean value and in-between these two uncertainty bands, the predictions should be regarded as good. For all these comparisons between modeled and empirical data, it should be noted that: 1. The monthly tributary inflows of water, phosphorus and SPM have not been calculated using actual monthly inflow data (since no such data are available to us). This will explain some of the differences between the modeled and the measures monthly values. 2. The monthly calculations of the inflow of water, salt, SPM and phosphorus from the Baltic Proper use mean values for the SW and the DW-compartments not in the inflowing water from the area outside the Himmerfjärden Bay, which would have been more appropriate, but values from a single station meant to reflect the conditions outside the bay in the Baltic Proper (see Figure 1). This likely also further explains some of the differences between the modeled and the measured monthly values. With these reservations, one can note from Figure 4 that: The TP-concentrations in the SW and DW-layer (Figure 4C and D) are within the defined uncertainty bands of the empirical data. 1. The modeled chlorophyll concentrations give the ―twin-peak pattern‖ as indicated by the empirical data but the predicted values are somewhat higher than the measured data in connection to the two peaks but within the given uncertainty bands for the main part of the growing season and for the winter period. It should be stressed that the chlorophyll concentrations are predicted from a regression based on dynamically modeled TP-concentrations in the surface water, the predicted salinities in the SWlayer and a dimensionless moderator for the average light conditions at this latitude. A simple and typical form of a dimensionless moderator is, e.g., the ratio between a mean monthly value, MM, and a mean annual value, AM. In traditional mass-balance models, one would multiply an amount (kg) by a rate (1/month) to get a flux (i.e., amount·rate or amount·rate·1). In this model, one multiplies kg·(1/month)·Y (= amount·rate·mod), where Y is a dimensionless moderator quantifying how an environmental variable influences the given flux (e.g., sedimentation of particulate phosphorus). Instead of building a large mechanistic sub-model for how environmental factors influence given rates, this technique uses a simple, general algorithm for the moderator. Empirical data can be used for the calibration of the moderator. The modeled values also account for biouptake in biota with short turnover times, but they do not include any considerations to the biouptake and retention of phosphorus in biota with long turnover times (such as fish, zoobenthos,
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2. 3. 4.
5. 6.
7.
8.
macrophytes). Given the limitations of the modeling for chlorophyll, one can conclude that the overall correspondence is relatively good. The predicted Secchi depths are also quite close to the empirical values and the temporal patterns agree quite well. The oxygen concentrations in the DW-layer (Figure 4G) are within the defined uncertainty bands of the empirical data for the growing season. The predicted TP-concentrations in the accumulation areas sediments (0-10 cm; 0.61 mg/g dw; dw = dry weight) below the wave base of 19 m (Figure 4H) are within the minimum and maximum lines defined for Baltic Sea coastal sediments (see Håkanson and Eklund, 2007) of 0.5 to 2.5 mg/g dw. The TN-concentrations are predicted from a regression (eq. 4) using dynamically modeled TP-concentrations in the SW-compartment. There is a relatively good correspondence between modeled and measured TN-concentrations (Figure 4I). The TN/TP-ratios based on modeld values are given in Figure 4J in relation to the Redfield-ratio of 7.2 (in g) and the Threshold-ratio of 15 for cyanobacterial (see Håkanson et al., 2007). The monthly TN/TP-ratios are clearly higher than 7.2 all months, and higher than 15 most summer months. Given the situation in the Himmerfjärden Bay, as revealed by these data, a lowering of the TN/TP-ratio will imply greater risks for blooming of cyanobacteria. So, to reduce the nitrogen concentration is useless when the TN/TP-ratio is higher than 15, and harmful when the TN/TP-ratio is lower than 15, since this would stimulated the growth of cyanobacteria, which should be avoided. The focus should instead be set on reductions of the major anthropogenic fluxes of phosphorus to the Baltic Proper. The predicted concentrations of cyanobacteria in Himmerfjärden under default conditions are given in Figure 4K. Under calm conditions when these algae will float to the surface, the concentrations in the upper meter of water may be many times higher than the mean values for the entire SW-layer shown in Figure 4K. The modeled SPM-concentrations in the SW and DW-compartments are shown in Figure 4L. These values will, together with the modeled salinities in Figure 4A and D, determine the values for the Secchi depth given in Figure 4F. For the open Baltic Sea, a default value of 3 mg/l (from Pustelnikov, 1977) has often been used. Håkanson and Eckhell (2005) have presented more data on SPM-concentrations in the Baltic Proper and those data also indicate that typical values in the SW-layer are between 0.1 and 14 mg/l with a mean value of about 2 mg/l. The predicted values in Himmerfjärden Bay agree quite well with the empirical data from those studies.
From Figure 4, one can conclude that the CoastMab-model predicts the target variables quite well given the factual limitations in the seasonal patterns in the driving variables for tributary water discharge (since this pattern in the modeling is not based on measured data for the modeled period) and in the seasonal pattern for the TP and SPM-concentrations outside Himmersfjärden Bay. Note that there has been no tuning of the model to achieve these predictions and that the basic model has been shown to describe the transport processes for phosphorus very well for many other coastal areas (see Håkanson and Eklund, 2007). This should lend credibility to the following simulations.
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 207 Table 8. A ranking of the annual fluxes (t/yr), as calculated using the CoastMab-model based on the monthly fluxes (t/month) of TP to, in and out of the Himmerfjärden Bay. The key fluxes for remedial measures are bolded. F = flux, SW = surface water, DW = deep water, HI = Himmerfjärden Bay, BP = Baltic Proper, trib = tributary, d = diffusive flux, x = mixing flux, LU = land uplift, ET = erosion and transport areas for fine sediments, A = accumulation areas for fine sediments, BS = biota with short turnover times, bur = burial Month 1 2 3 4 5 6 7 8 9 10 11 12 Annual FTPBSSW 13.6 26.3 99.2 216.2 151.9 142.9 139.9 141.8 249.1 209.8 109.7 20.0 1521 FTPSWBS 12.3 28.8 109.1 67.5 151.5 141.5 140.5 142.1 260.1 197.7 96.1 20.0 1367 FTPSWHIBP 136.3 130.0 114.2 95.8 77.9 70.2 69.2 74.2 111.5 128.4 126.5 135.1 1269 FTPSWBPHI 122.1 110.4 89.7 73.8 73.2 67.1 72.6 78.2 93.4 104.9 109.6 125.0 1120 FTPETSW 14.1 14.1 12.1 2.5 3.9 4.8 5.8 10.3 61.7 28.0 15.7 13.5 187 FTPDWHIBP 15.5 14.8 13.0 11.4 11.3 12.2 12.8 14.0 19.3 15.6 14.3 15.6 170 FTPDWBPHI 14.0 13.2 11.0 9.6 10.1 11.0 11.2 11.7 12.2 12.1 13.7 15.0 145 FTPLU 10.4 10.3 10.3 10.3 10.3 10.3 10.2 10.2 10.2 10.3 10.4 10.4 124 FTPSWET 7.5 6.7 6.8 8.0 8.5 9.6 10.3 12.8 17.8 10.7 7.0 7.7 113 FTPDWSWx 9.5 9.9 7.1 0.9 0.5 0.3 0.3 0.4 6.4 9.4 10.1 8.8 64 FTPETDW 4.4 4.4 3.8 0.8 1.2 1.5 1.8 3.2 19.1 8.7 4.9 4.2 58 FTPSWDWx 9.0 9.2 5.7 0.5 0.2 0.1 0.1 0.1 2.2 5.7 8.1 8.2 49 FTPMWSWd 3.8 3.4 2.3 1.5 1.5 1.9 2.2 2.9 7.5 3.9 3.1 4.0 38 FTPSWDW 1.8 1.6 1.7 2.0 2.1 2.3 2.5 3.1 4.3 2.6 1.7 1.9 28 FTPtrib 2.8 2.3 2.5 3.1 3.1 1.8 1.4 1.3 1.4 1.6 2.1 2.5 26 FTPplantSW 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 19 FTPDWA 0.7 0.8 0.7 0.0 0.0 0.0 0.0 0.1 4.6 1.8 0.8 0.7 10.3 FTPbur 1.0 1.0 0.8 0.7 0.8 0.7 0.7 0.8 0.7 0.7 0.8 0.9 9.6 FTPprec 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.54 FTPplantDW 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.20 FTPADWd 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.06
4.2. Fluxes and Amounts of Phosphorus Which are the large and the small TP-fluxes? And where is the phosphorus stored? Table 8 gives a compilation of all monthly TP-fluxes and a ranking of the annual fluxes. One can note that the two largest fluxes are biouptake and retention (=outflow) of phosphorus to and from biota. These fluxes are significantly larger than the fluxes related to in and outflow of TP between the Baltic Proper and the Himmerfjärden Bay. The fluxes that may be reduced by remedial measures are bolded in table 8 - the SW-inflow from the Baltic Proper (FTPSWBPHI = 1120 t/yr), inflow to the DW-layer from the Baltic Proper (FTPDWBPHI = 170 t/yr, tributary inflow (FTPtrib = 26 t/yr) and TP from the purification plant (FTPplant = 19 t/yr). From this, it is evident that smaller reductions of the TP-emissions (say a factor of 2-4) from the plant will have small effects on the conditions in the bay. The phosphorus fluxes are dominated by the exchange processes between the coast and the sea. The diffusive flux from the accumulation areas sediment (below the theoretical wave base at 19 m) is very small (<1 t/yr). The modeled TP-concentration in these sediments (0-10 cm) is 0.61 mg/g dw. This model provides values based on the total TP-inventory in the entire
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area below the theoretical wave base down to 10 cm of sediments. The biologically passive sediments below 10 cm are expected to have a TP-concentration of about 0.45 in the Baltic Proper (Jonsson et al., 1990) and this value is also used in this modeling for the Himmerfjärden Bay. This means that only a small fraction (related to the difference between 0.61 and 0.45) of the phosphorus in the accumulation area sediments could be available for diffusive transport from these sediments. But the diffusion also depends on the redoxconditions in the sediments, which depend on the sedimentation of organic matter. The average values for total sedimentation calculated by the model vary between 0.1 and 0.3 mm/yr or between 10 and 20 µg/cm2·d on the accumulation areas. The modeled water content (W) of the accumulation area sediments (0-10 cm) is 75% ww, the modeled organic content (loss on ignition, IG) is 6.3 %dw and the bulk density (d) 1.17 g/cm3. Table 4 gave modeled values for the SW and DW-water inflow from the Baltic Proper (QSWBPGE = 4050·106 m3/month and QDWBPGR = 450·106 m3/month); modeled monthly tributary inflow (Qtrib); theoretical water retention times in the SW and DW-layers (TSW = 0.62 months and TDW = 0.41 months, since the DW-volume is small), as calculated from the mass-balance for salt; fall velocities for particulate phosphorus and suspended particulate matter in the SW and DW-layers (vSW 2.4 m/month and vDW 2.3 m/month); the particulate TP-fractions in the SW and DW-layers (PFSW 0.20 to 0.87 and PFDW 0.01 to 0.53; see table 6). It should also be stressed that land uplift (FLU) is a rather important individual input of TP to the bay (124 t/yr). It is interesting to note the difference between fluxes and amounts (compare the results in table 8 with the data in table 9). The largest TP-fluxes are to and from biota, but the total TPinventory in biota is only 16.8 t TP or 6% of the total inventory. By far most TP is found in the accumulation area sediments (191 t or 66% of the total amount). Table 9. Amounts of TP (t) in the different compartments; accumulation areas in the DW-compartment (A-areas), in biota with short turnover times (Biota), in the DWlayer, in areas of fine sediment erosion and transport (ET) and in the SW-layer. MV = mean value; M50 = median; SD = standard deviation Month 1 2 3 4 5 6 7 8 9 10 11 12 MV % M50 SD
A-areas 192 192 192 191 191 190 189 189 190 192 192 192 191 66 191 1.2
Biota 1.8 3.5 13.3 27.3 20.2 19.0 18.7 18.9 33.3 27.9 14.5 2.7 16.8 6 18.8 3.6
DW 8.1 7.7 6.8 5.9 5.9 6.4 6.7 7.3 10.1 8.1 7.5 8.1 7.4 3 7.4 7.8
ET-areas 7.5 6.5 6.6 9.0 23.1 36.6 49.7 61.1 42.4 14.3 6.9 7.7 22.6 8 11.7 6.7
SW 85.9 80.3 60.2 34.0 29.8 26.3 26.2 29.2 39.3 55.3 67.2 84.5 51.5 18 47.3 82.3
Sum 289 100
How Important Are Local Nutrient Emissions to Eutrophication in Coastal Areas… 209
5. PREDICTING THE DYNAMIC RESPONSE OF THE SYSTEM TO CHANGES IN NUTRIENT LOADING The simulations to estimate a realistic response to changes in nutrient loading will be presented in four steps. The first step concerns a two-fold increase in the direct emissions from the plant to mimic the experiment of 1983. The next example concerns a 10-fold increase in these direct emissions of TP from the plan. The third case concerns a 10% increase in the TP and SPM-concentrations in the sea outside of Himmerfjärden Bay. The fourth test concerns a 10% reduction in TN-concentrations in the SW-layer in the bay. These four cases will be compared to the default values representing the conditions today (19972007). We will also show the dynamic response of the system to sudden changes in the nutrient loading. The results are complied in table 10: Table 10. Results related to how changes in phosphorus loading to Himmerfjärden Bay would likely influence TP-concentrations in SW, TP in DW, Secchi depth, chlorophyll, cyanobacteria and oxygen concentrations if the default TP input from the plant is increased by a factor of 2, by a factor of 10, if the TP-inflow from the Baltic Proper is increased by 10% or if the TN-concentration in the bay is decreased by 10% TPSW (µg/l) Month Default 2·plant 10·plant 1.1·TPsea 1 33.2 33.6 36.5 36.3 2 31.7 32.1 35.0 34.7 3 27.8 28.2 31.1 30.4 4 23.2 23.6 26.5 25.4 5 18.9 19.3 22.0 20.7 6 17.2 17.5 20.3 18.8 7 17.0 17.3 20.1 18.6 8 18.2 18.5 21.3 20.0 9 27.4 27.8 31.0 29.8 10 31.5 31.9 35.1 34.2 11 30.9 31.3 34.4 33.7 12 32.9 33.3 36.3 36.0 25.8 26.2 29.1 28.2 MV 0.4 3.3 2.4 Diff. 27.6 28.0 31.0 30.1 M50 6.5 6.6 6.7 7.1 SD TPDW (µg/l) 1 34.3 34.6 36.7 36.7 2 32.9 33.2 35.6 35.2 3 28.9 29.2 31.4 31.0 4 25.3 25.6 27.8 27.1 5 25.2 25.5 27.8 27.0 6 27.2 27.5 29.9 29.2 7 28.6 28.9 31.2 30.6 8 31.1 31.4 33.8 33.2 9 43.0 43.3 45.9 45.3 10 34.6 34.9 37.6 36.7 11 31.9 32.2 34.4 34.1
0.9·TN 33.2 31.7 27.8 23.2 18.9 17.2 17.0 18.2 27.4 31.5 30.9 32.9 25.8 0.0 27.6 6.5 34.3 32.9 28.9 25.3 25.2 27.2 28.6 31.1 43.0 34.6 31.9
Chlorophyll (µg/l) Month Default 2·plant 10·plant 1.1·TPsea 0.9·TN 1 2.0 2.0 2.2 2.2 2.0 2 3.7 3.8 4.1 4.1 3.7 3 9.4 9.5 10.5 10.2 9.4 4 2.6 2.6 3.0 2.8 2.6 5 2.7 2.7 3.1 3.0 2.7 6 1.8 1.8 2.1 2.0 1.8 7 1.5 1.5 1.8 1.6 1.5 8 2.0 2.0 2.3 2.2 2.0 9 6.4 6.5 7.3 7.0 6.4 10 6.8 6.9 7.6 7.4 6.8 11 6.1 6.2 6.8 6.7 6.1 12 2.3 2.4 2.6 2.6 2.3 3.9 4.0 4.4 4.3 3.9 MV 0.1 0.5 0.4 0.0 Diff. 2.6 2.7 3.1 2.9 2.6 M50 2.6 2.6 2.9 2.8 2.6 SD Cyanobacteria (µg/l) 1 0.2 0.2 0.2 0.2 0.2 2 0.5 0.5 0.7 0.7 0.6 3 7.0 7.4 10.4 9.6 8.1 4 76 81 130 109 90 5 118 125 208 153 119 6 138 147 227 183 138 7 151 160 249 201 151 8 162 172 255 213 162 9 356 375 535 473 400 10 191 198 264 245 209 11 32 34 45 43 36
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Month Default 12 34.7 31.5 MV Diff. 31.5 M50 5.0 SD 1 2 3 4 5 6 7 8 9 10 11 12 MV Diff. M50 SD
9.1 9.1 6.9 5.6 6.7 6.3 6.3 6.6 5.9 6.0 6.4 8.5 6.9 6.5 1.2
TPDW (µg/l) 2·plant 10·plant 1.1·TPsea 34.9 37.1 37.1 31.8 34.1 33.6 0.3 2.6 2.1 31.8 34.1 33.6 5.0 5.1 5.1 Secchi (m) 9.1 9.1 8.3 9.1 9.1 8.3 6.9 6.8 6.4 5.5 5.4 5.2 6.7 6.5 6.3 6.3 6.1 5.8 6.3 6.1 5.8 6.6 6.4 6.1 5.8 5.6 5.5 6.0 5.8 5.7 6.3 6.2 5.9 8.5 8.4 7.7 6.9 6.8 6.4 0.0 -0.1 -0.5 6.5 6.3 6.0 1.3 1.3 1.1
0.9·TN 34.7 31.5 0.0 31.5 5.0 9.1 9.1 6.9 5.6 6.7 6.3 6.3 6.6 5.9 6.0 6.4 8.5 6.9 0.0 6.5 1.2
Cyanobacteria (µg/l) Month Default 2·plant 10·plant 1.1·TPsea 0.9·TN 12 0.9 0.9 1.2 1.2 1.0 103 108 160 136 110 MV 5.4 57.5 32.9 6.7 Diff. 97 103 169 131 105 M50 107 112 162 141 117 SD Oxygen concentration (mg/l) 1 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 5 7.0 7.0 7.0 6.9 7.0 6 6.5 6.5 6.5 6.4 6.5 7 6.2 6.2 6.1 6.0 6.2 8 6.5 6.5 6.4 6.3 6.5 9 7.5 7.5 7.4 7.3 7.5 10 0 0 0 0 0 11 0 0 0 0 0 12 0 0 0 0 0 6.8 6.7 6.7 6.6 6.8 MV -0.06 -0.13 -0.23 -0.05 Diff. 6.5 6.5 6.5 6.4 6.5 M50 0.50 0.50 0.51 0.53 0.50 SD
The predicted values for TP-concentrations in the SW-layer, TP-concentrations in the DW-layer, Secchi depths, chlorophyll-a concentrations, concentrations of cyanobacteria and the oxygen concentrations in the deep-water layer at steady-state are given for the four cases and the results are compared to the default conditions. Case 1 (a 2-fold increase of TPemissions from the plant) would influence the system very little, e.g., the mean annual TPconcentration would increase from 25.8 µg/l to 26.2 µg/l and the Secchi depth would not change at all. Case 2 (a 10-fold increase in TP-emission from the plant) would, influence the system markedly. The TP-concentrations in the SW-later would increase by 3.3 µg/l, the average chlorophyll concentration would increase by 4.4 µg/l, the maximum concentration of cyanobacteria would increase from 360 to 540 µg/l. Case 3 (a 10% increase in TP and SPM-inflow from the sea) would also create substantial changes corresponding to the changes in case 2. Case 4 (a 10% reduction in TN-concentrations in the bay) would only change the predicted concentration of cyanobacteria, which would increase from a maximum value of 360 to a maximum monthly value of 400 µg/l. Note that, as explained, we have not modeled the TN-concentrations dynamically. The dynamic response of the system related to sudden 2-fold and 10-fold increases in the TP-emissions from the plant month 25 are shown in Figure 5. One can see from Figure 5, that the system will reach a new steady-state within a year. The main reason for this quick adjustment is related to the relatively fast water turnover of the system. The theoretical surface-water retention time is about 19 days, i.e., about 19 total water exchanges per year with the outside sea.
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Figure 5. Illustration of the dynamic response of the system (Himmerfjärden Bay) to sudden 2-fold and 10-fold increases in phosphorus loading from the treatment plant in the bay month 25 (January) for A. TP-concentrations in the SW-layer, B. chlorophyll-a concentrations and C. concentrations of cyanobacteria
We also believe that these results largely explain important aspects of previous results related to the experiments carried out during the last 25 years (see the background given in section 2.1) and that, since these results are based on a general process-based modeling approach, which may be applied to most coastal areas, one would also hope that this type of analysis could be more widely used. The results given in the tables for the phosphorus fluxes and in Figure 5 indicate that for this, and many other coastal bays, it seems very important to lower the nutrient concentrations in the outside sea. This will be shown in the next scenario. The background for this scenario is as follows: Today HELCOM has adopted a new strategy (HELCOM, 2007) to lower the eutrophication in the Baltic Sea by suggesting that 133,000 tons of nitrogen and 15,000 tons of phosphorus should be reduced from the present annual nutrient loading to the system. One can safely assume that it is practically impossible to remediate all human emissions of TP to the Baltic Sea. The 15,000 t/yr suggested by HELCOM (2007) represent a reduction of 50% of the 30,000 t/yr of TP transported via rivers/countries to the Baltic Sea. From Sweden and other countries or regions, which have already carried out costly measures to reduce nutrient discharges to the Baltic Sea, one can assume that only a smaller part of the remaining
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anthropogenic nutrient fluxes can be reduced, as suggested by HELCOM (e.g., 290 t/yr from Sweden). In the following scenario, TP will be cut off a given month, month 25 (i.e., in January). How would the Baltic Sea system react to such a hypothetical sudden change? This has been discussed in great detail by Håkanson and Bryhn (2008b) and in this scenario we will use results from those simulations and apply the results for the conditions in the Himmerfjärden Bay. Note that HELCOM (2007) did not suggest that one should reduce the nutrient loading suddenly, as this scenario simulates, only gradually. In this scenario, we will also give predicted monthly data on Secchi depths, chlorophyll, cyanobacteria and phosphorus concentrations. Håkanson and Bryhn (2008b) challenged HELCOM‘s strategy and motivated and presented a scenario (called the ―optimal‖ scenario) with a total reduction of 9775 t/yr of phosphorus (and no reductions in nitrogen emissions) and of these reductions 6625 t/yr (48% of anthropogenic emissions) are removed from the countries/rivers adding nutrients to the Baltic Proper, 2725 t/yr from the Gulf of Finland (corresponding to 60% of the anthropogenic input) and 425 t/yr of TP to the Gulf of Riga (or 46% of the anthropogenic input to this basin). This would give a Secchi depth of 7 m in the Gulf of Finland on an average annual basis, a Secchi depth of almost 10 m (9.7 m) in the Bothnian Sea, of about 8 m in the Bothnian Bay, 5.6 m in the Gulf of Riga and almost 8 m (7.9 m) in the Baltic Proper. These conditions would be close to the situation in the Baltic Sea as it was before the main eutrophication started in 1920. After 1980 trend analyses based on comprehensive data show that the Baltic Sea system is slowly recovering (Håkanson and Bryhn, 2008b).
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Figure 6. Simulation results for the TP-concentrations in the surface and middle-water layers in the Baltic Proper to illustrate how the system of connected sub-basins forming the Baltic Sea would likely react to reductions in phosphorus loading. The ―optimal‖ remedial strategy means that 6625 t TP to the Baltic Proper, 2725 t TP to the Gulf of Finland and 425 t TP to the Gulf of Riga, would be reduced month 25. Data from Håkanson and Bryhn (2008b)
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Figure 7. Illustration of the dynamic response of the system (Himmerfjärden Bay) to sudden total reductions (month 25) of all phosphorus emissions from the local treatment plant (curves 2) and to the ―optimal‖ remedial scenario for the Baltic Sea (from Håkanson and Bryhn, 2008) with a reduction of 6625 t phosphorus to the Baltic Proper, 2725 t phosphorus to the Gulf of Finland and 425 t phosphorus to the Gulf of Riga (curves 3) for A. TP-concentrations in the SW-layer, B. chlorophyll-a concentrations, C. concentrations of cyanobacteria and D: Secchi depths
Figure 6 gives results where the consequences of nutrient reductions have been simulated using the CoastMab-model for the entire Baltic Sea (from Håkanson, and Bryhn, 2008b). Figure 6 gives the results for the surface water (0-44 m) and middle-water layers (44 to 75 m) in the entire Baltic Proper. In the following simulations, we have used the data given in Figure 6, but since these values are close to but not identical with the data from the reference site just outside the Himmerfjärden Bay, we have adjusted these vector files to the mean monthly values from the reference site outside the bay. This means that, e.g., the average annual surface-water concentration for TP for the Baltic Proper is a factor of 1.083 higher than the data given in Figure 6. This ―optimal‖ scenario would imply that the primary phytoplankton production would go down by, on average, 35-40% in the Baltic Proper. Furthermore, the risks of harmful algal blooms (of cyanobacteria) would be significantly reduced, by a factor of 3 to 5 in the Baltic Proper. It is also interesting to note the dynamic response of the system. In these scenarios with the hypothetical sudden reduction a given month (month 25), there are two response phases related to TP-concentrations in water, first an initial quick response of about 6 years (72 months) and then a much slower response and that after about 10 years, the system has almost reached a new steady state. To reach a new steady-state takes longer in the sediments. To see how these changes in the Baltic Proper would influence the Himmerfjärden Bay compared to reductions in direct TP-loading to the bay, we have set all TP-emissions from the treatment plant to zero month 25. The results are given in Figure 7 for the TP-concentrations (A), the chlorophyll-a concentrations (B), the concentrations of cyanobacteria (C) and the Secchi depths (D). One can note very small improvements indeed if the direct TP-emissions from the plant are removed (curve 2 as compared to curve 1, which gives the default condition), but significant
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changes when 9775 t of TP are removed according to the ―optimal‖ scenario: The average annual TP-concentration would go down from almost 26 µg/l to 17.4 µg/l, the concentrations of chlorophyll and cyanobacrteria would follow the reduction in TP and the Secchi depth would likely increase from about 7 to about 7.5 m.
6. CONCLUDING REMARKS This work has presented a general method to calculate how a given coastal area would likely respond to changes in nutrient loading. This approach makes it possible to carry out structured analyses of the costs and environmental benefits of remedial actions designed to reduce nutrient input to coastal areas and to put such reductions or changes into a processbased holistic context where all important transport processes to, within and from the given coastal area are accounted for on a monthly basis to achieve seasonal variations, which is essential for most biological variables and key bioindicators of coastal eutrophication. The dynamic modeling also provides quantitative values of the time-dependent response of the system. The method discussed here may be applied to most coastal systems and the data necessary for this analysis have also been discussed. These results demonstrate that the conditions in the case-study area, the Himmerfjärden Bay, are dominated by the water exchange between the bay and the outside sea (the Baltic Proper). The theoretical surface-water retention time is 19 as days, as determined using the mass-balance model for salt, which is based on comprehensive and reliable empirical data. This means that although this bay is quite enclosed, with an exposure of 0.0194, it is still dominated by the water exchange towards the sea. Local emissions of nutrients to the Himmerfjärden Bay are small compared to the nutrient fluxes from the sea. If the conditions in this, and many similar bays, are to be improved, it is very important to lower the nutrient concentrations in the outside sea. To do that in the best possible manner, one must apply the same process-based mass-balance principles for the larger system as discussed in this work for a coastal bay. This means that the major phosphorus fluxes to the sea, in this case the Baltic Proper, should be reduced in the most cost-efficient manner. That remedial strategy has not penetrated fully into management decisions neither for the Himmerfjärden Bay nor for the Baltic Proper or the Baltic Sea.
ACKNOWLEDGMENTS This work has been carried out within the framework of the Thresholds-project, an integrated EU project coordinated by Prof. Carlos M. Duarte, CSIC-Univ. Illes Balears, Spain, and we would like to acknowledge the financial support from the EU.
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Håkanson, L. & Eklund, J. M. (2007). A dynamic mass-balance model for phosphorus fluxes and concentrations in coastal areas. Ecol Res., 22, 296-320. Håkanson, L. & Jansson, M. (1983). Principles of Lake Sedimentology. - Springer-Verlag, Berlin, Heidelberg, New York, Tokyo, 316. Håkanson, L., Kvarnäs, H. & Karlsson, B. (1986). Coastal morphometry as regulator of water exchange - a Swedish example. Estuarine, Coastal and Shelf Science, 23, 1-15. Hecky, R. E. & Kilham, P. (1988). Nutrient limitation of phytoplancton in freshwater and marine environments: A rewiew of recent evidence on the effects of enrichment. Limnology and Oceanography, 33, 796-822. Howarth, R. W. (1988). Nutrient limitation of net primary production in marine ecosystems. Ann. Rev. Ecol., 19, 89-110. Howarth, R. W. & Cole, J. J. (1985). Molybdenum availability, nitrogen limitation, and phypoplankton growth in natural waters. Science, 229, 653-655. Howarth, R. W. & Marino, R. (2006). Nitrogen as the limiting nutrient for eutrophication in coastal marine ecosystems: Evolving views over three decades. Limnol. Oceanogr, 51, 364-376. Jonsson, P. (1992). Large-scale changes of contaminants in Baltic Sea sediments during the twentieth century. Dr. Thesis, Uppsala Univ., Sweden. Jonsson, P, Carman, R. & Wulff, F. (1990). Laminated sedments in the Baltic – a tool for evaluating nutrient mass balances. Ambio, 19, 152-158. Jönsson, A. (2005). Model studies of surface waves and sediment resuspension in the Baltic Sea. Dr. thesis No. 332, Linköping Univ. Khalili, M. (2007). Salt, water and nutrient fluxes to Himmerfjärden bay. Master thesis, Dept. of Earth sciences, Uppsala Univ. Larsson, U. & Elmgren, R. (2001). Eutrophication in the Baltic Sea area. Integrated coastal management issues. Sci. Int. Coast. Man., 15-35. Dahlem University Press, Berlin. Larsson, U., Hajdu, S., Walve, J., Andersson, A., Larsson, P. & Edler, L. (2006). Bedömningsgrunder för kust och hav. Växtplankton, näringsämnen, klorofyll och siktdjup. Livingston, R. J. (2001). Eutrophication processes in coastal systems. CRC Press, Boca Raton, 327. B. Moldan, & S. Billharz, (eds.), (1997). Sustainability indicators. Wiley, see http://www.icsu-scope.org/downloadpubs/scope58/. Nixon, S. W. (1990). Marine eutrophication: a growing international problem. Ambio, 3, 101. Nixon, S. W. & Pilson, (1983). Nitrogen in estuarine and coastal marine ecosystems. In: E. J. Carpenter, & D. G. Capone, (eds.), Nitrogen in the marine environment. Academic Press, New York, 565-648. Pearson, T. H. & Rosenberg, R. (1976). A comparative study on the effects on the marine environment of wastes from cellulose industries in Scotland and Sweden. Ambio, 5, 7779. Persson, J., Håkanson, L. & Pilesjö, P. (1994). Prediction of surface water turnover time in coastal waters using digital bathymetric information. Environmentrics, 5, 433-449. Pilesjö, P., Persson, J. & Håkanson, L. (1991). Digital bathymetric information for calculations of morphometrical parameters and surface water retention time for coastal
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 219-247 © 2011 Nova Science Publishers, Inc.
Chapter 7
ENVIRONMENTAL CONSEQUENCES OF INNOVATIVE DREDGING IN COASTAL LAGOON FOR BEACH RESTORATION Emmanuel Lamptey* Department of Oceanography and Fisheries, University of Ghana, Legon, Ghana
ABSTRACT Evidence suggests that hydraulic dredging is accompanied by considerable adverse environmental impacts on the receiving ecosystem especially on the benthos and water quality. Recently, innovative dredging is designed to minimise environmental impacts and enhance the ecological settings. Evaluations of environmental consequences of such innovative dredging are essential to quantify the ecological benefits and the associated impacts to ensure good environmental management. Congruently, innovative dredging (‗design with nature‘ principle) in a large tropical coastal lagoon in Ghana (Keta lagoon), West Africa, was assessed Before, During and After dredging operations on spatiotemporal scales to ascertain the environmental impacts on the macrobenthic fauna, shorebirds and water quality. A total of 9091 million cubic meter of sediment was removed from the 8m stretch of the lagoon for beach nourishment, land reclamation and creation of habitat islands. The macrobenthic fauna was sampled once in 2000 (Before), 2001 (During) and 2002 (After) along seven stations (A-0 to G-0 of 1-km interval) in the dredged channel. Water quality was assessed at the subsurface and bottom layers quarterly from June, 2001 to September, 2002. The shorebirds community abundance were quantified monthly from August 2000 to 2002, but only parallel data from AugustDecember (peak periods of shorebirds abundance) of each year (2000-2002) was used for statistical analyses. The results demonstrate that dredging had initial adverse effects on numerical abundance of macrobenthic fauna but with evidence of recovery a year after the dredging (2002). Species recorded in 2001(During Dredging) and 2002 (After Dredging) were very similar in terms of composition particularly in the wet periods, suggesting the influence of seasonal environmental factors. The abundance of the species showed significant *
Corresponding author: [email protected], Tel: +233 24 483 1455, Fax: +233 21 520298
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Emmanuel Lamptey spatio-temporal variations (p<0.05). The macrobenthic fauna was dominated by opportunistic species of the family Capitellidae. Although, Nepthys lyrochaeta revealed higher frequency of occurrence (52%), there was significant (p<0.05) decrease in abundance after dredging (2002). Conversely, Notomastus cf. latericeus depicted significant (p<0.05) increase (recovery) after dredging (2002). There was no apparent impact on coastal avifauna although numerical abundance of wader group decreased from 78% in 2000; 69% in 2001 to 51% in 2002. Conversely, terns showed increased abundance from 17% in 2000, 21% in 2001 and 47% in 2002 indicating positive impact. The shorebirds placed in the ‗others‘ category experienced peak and trough between the period (6% in 2000; 10% in 2001, and 2% in 2002). In general mean numerical abundance of the shorebirds increased from 8.8% in 2000 (Before) to 81.5% in 2002 (After) of the periods. Temporal and spatial variability occurred in the physicochemical parameters measured (e.g., salinity, total dissolved solids, total suspended solids and sulfate). However, elevated turbidity occurred in localised areas along the fetch during the dredging operation. The results of the analysis presented are pertinent to several questions, such as what are the expected ecological benefits of innovative dredging and adverse impacts on the receiving ecosystem.
Keywords: Innovative Dredging, Environmental Impacts, Ecological Benefits, Coastal Lagoon, Macrobenthic Fauna, Coastal Avifauna, Water Quality
1.0. INTRODUCTION Coastal lagoons are fragile ecosystems but accounts for 13-15% of the world‘s littoral zone [Kjerfve, 1994, Marcovecchio et al. 2005]. They are highly productive than several riverine and estuarine ecosystems in terms of fisheries yield [Kapetsky, 1984], attributable to high primary production as a sequel of nutrients inflow from land drainages [Nixon, 1982]. Coastal lagoons constitute an essential environmental reservoir for fluvial sediments due to their capacity to retain them and therefore accompanied elemental pollutants. In recent times it has been a common practice to redistribute large amount of coastal sediments for beach nourishment projects to combat shoreline retreat. The problem of beach/coastline recession/erosion are as a result escalating impacts of emerging global geophysical changes, such as rising sea levels, and coastal development [Rakocinski, 1996]. Engineered solutions of massive dredge-and-fill methods have increasingly been adopted worldwide. But the activities accompanying dredge-and-fill projects such as the dredging itself, transportation and disposal of dredged materials result in adverse environment impacts to the ecology and economy of the receiving ecosystem. There is a huge body of literature that have documented adverse environmental impacts of dredging on the benthos, and water quality characteristics [ICES 1992, 2000; Kenny, 1995; Newell et al., 1998; Bemvenuti et al., 2005] with relatively few on aquatic shorebirds (Grippo et al., 2007). Other reports nonetheless have indicated beneficial uses of the dredged materials for beach nourishment, land reclamation, berm creation, replacement fill, capping and habitat creation for wildlife utilization leading to increased biodiversity and economic improvement [Krause and McDonnel, 2000]. However, evidence of benefits of restoration to wildlife is still somewhat ambiguous [Simenstad et al., 2005]. It is uncertain if restoration projects increased habitat use by wildlife or not. Therefore monitoring and assessment of environmental consequences of
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dredge-and-fill projects is a fundamental step towards understanding the associated impacts in particular biological resource responses. Relatively very few studies have addressed the environmental consequences (adverse impacts & beneficial uses) of dredging. The extent of dredging impacts on the environment may depend on a number of factors including location, characteristics of the bottom sediment and surface water, the methods of dredging and timing, sensitivity of the ecosystem, and ecological objective. The difficulty in predicting the type of response from organisms in ecosystem subjected to dredging requires that studies and analyses of such effects be conducted on a case-by-case basis [Harvey et al., 1998]. As such, environmental studies investigating impacts of dredging (physical disturbance) on the biological resource and water quality are essential requirements for biodiversity resource management. When an impact causes complete loss of biological community and deterioration of water quality, studies of environmental impacts are useful in assessing recovery/amelioration and also an empowering tool for sustainable development. A variety of study designs existed to detect and assess effects of impacts of general anthropogenic activities in aquatic systems. Green‘s [1979] BACI (Before-After-Control Impacts) design have been extensively used in such impact studies where samples are taken before and after a planned impact. It is believed that such design may confound the effects of the impacts with other types of unique natural fluctuations that occur at one site but not at the other [Osenberg and Schmitt, 1996; Hurlbert, 1984; Stewart-Oaten et al., 1986]. This is because anthropogenic sources of stress, often interact with natural processes [Gaston and Edds, 1994; Gaston, 1985; Parker et al., 1980]. A recent design suggests sampling before and after the impacts, at several control sites temporally [Underwood, 1992, 1994].
1.1. Geomorphology and Sedimentation of Coastal Lagoon A coastal lagoon is a shallow water body separated from the ocean by a barrier, connected at least intermittently to the ocean by one or more restricted inlets, and usually oriented parallel to the shore [Kjerfve, 1994]. All coastal lagoons are recent and transitional geological happenings. The fundamental processes that contributed to their formation took place in the Holocene and were due to changes in (eustatic) sea level about 6000 to 7000 years ago [Emery and Stevenson, 1957; Phleger, 1969] together with the rise and fall of the coastal area [Zenkovitch, 1969]. In the case of an emergent coastline, the shallowness of the water and the plain may give rise to a submerged beach that contributes to the formation of a barrier, which isolates interior water and, thus, forms a lagoon. In the case of sinking coastline the mechanism that operates is a continual and gradual rise in sea level forming a barrier [Zenkovitch, 1969] or with regard to a slight sloping coast, the coastal water from the sea may flood a coastal depression, in a process that under certain circumstances may form a barrier that encloses the depressions and forms a lagoon [Lankford, 1977]. In geomorphologic terms, coastal lagoons usually occur where valley mouths or lowlands have been submerged by the sea during the later stages of the Late Quaternary marine transgression, which on tectonically stable coasts brought the sea up to approximately its present level about 6000 years ago [Bird, 1994]. Once formed, coastal lagoons are modified by erosion and deposition. Infilling by accumulation of in-washed sediment, organic deposits
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such as peat or shells, precipitated material, results in shallowing and shrinkage of lagoons [Bird, 1994]. Contrasting sea-level histories have exerted a fundamental control on coastal sedimentation [Dominguez, 1984]. Under conditions of sea-level rise, Barrier Island/lagoonal systems become important environments of sedimentation. Barrier islands form preferentially under conditions of sea-level rise. According to Bruun‘s rule [Bruun, 1962], if the coastal profile is accepted as an equilibrium response of the sea floor to the coastal fluid power expenditure, then the effects of a sea-level rise could be deduced as a landward and upward translation of the profile. Thus, as sea level rises along a low-relief coastal plain, the beach and dune are nourished by the longshore drift and grow upwards at the same rate of sea-level rise following Bruun‘s rule. The swale behind the dune, however, remains at the same altitude and, as sea level rises, becomes a lagoon [Martin and Dominguez, 1994]. When sea level falls, the inverse of Bruun‘s rule applies, resulting in a seaward and downward translation of the coastal profile, and shallow back-barrier lagoons eventually become emergent [Martin and Dominguez, 1994]. Because lagoons are generally shallow, they are very sensitive to fluctuations of sea level, small rises and falls translate respectively into widespread inundation and emergence of coastal lagoons. Thus, coastal lagoons during their geological history may be affected by multiple episodes of invasion and emergence. Ecological conditions, particularly water salinity and temperature, are important in the geomorphological evolution of coastal lagoons. They control the extent to which vegetation can colonize lagoon shores, impeding erosion, promoting pattern of sedimentation and generating organic deposits [Bird, 1994]. Coastal lagoons around the world show great contrasts, but the same processes have operated in similar situations. In general, coastal lagoons are formed and maintained through sediment transport processes. Sediments are carried by rivers, waves, currents, wind, and tides (Nichols and Boons, 1994). Lagoons fed by rivers receive sediments ranging from coarse sand to silt and clay. The coarser material is deposited as the river enters the lagoon, and may be added to lagoon beaches and spread around the shore by wave action; the finer sediment is carried out into the lagoon and deposited on the floor, progressively reducing the depth. Rates of fluvial sediment yield to lagoons may be accelerated by the reduction of vegetation cover and the onset of soil erosion in the river catchments [Bird, 1994]. Studies have also indicated that higher energy conditions are responsible for the composition and distribution of sediments in a lagoon (Hubbard, 1992; Kalbfleisch and Jone, 1998; Kench, 1998). The development of these sediments is attributed to short-lived, storm-induced high energy conditions (Beanish and Jone, 2002).
1.2. Value of Coastal Lagoons Coastal lagoons present many ecological and socio-economic values, albeit the debate as to whether natural systems usurp an intrinsic value of their own that lies outside human determination (Rolston, 1994; Williams, 1994). Coastal lagoons support a wide range of natural services that are highly valued by society including fisheries, storm protection and tourism. They are important as nursery grounds for a variety of marine fishes and shrimps [Day and Yanez-Arancibia, 1985; De Wit, 2003]. Significant fisheries of oyster, shrimp and bony fish exist within many lagoons. Migrating birds make extensive use of lagoons, where they feed, roost and may spend most, or all of their lives there (Armah, 1993). Lagoons serve
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as sanctuaries in certain areas for endangered species such as crocodiles and hippopotami [Day and Yanez-Arancibia, 1985]. Many of the coastal lagoons serve as important harbors, navigation routes and also for recreation. They therefore, constitute important sites for industries that are connected with tourism. The shores of certain coastal lagoons are preferred locations for construction of residences owing to its numerous benefits. Lagoon reefs made of molluscs are extensively used for concrete aggregate in low coastal areas, which are far from source hard rock. Some lagoons are dumping areas for disposal of waste from urban and industrial areas. They constitute areas for the production of significant amount of salt from local techniques of evaporated pans (e.g., Keta lagoon in Ghana). In some places, their water is used for the cooling of generators of electric power plants, which return effluent of warmed water to the lagoon. Coastal lagoons are economically important in their use for aquaculture facilities [Day and Yanez-Arancibia, 1985; De Wit, 2003]. Coastal lagoons facilitate processes, particularly those resulting in loss or accretion of natural wetland. They provide numerous ecosystem goods and services.
1.3. Environemntal Impact Studies The environment is the sum total of all causal factors that show actual interactions, and comprises the input and output components, with resources and conditions constituting the input environment. Environmental conditions are all things outside an organism that affect it but, in contrast to resources, are not consumed by it [Begon et al., 1990]. Impact is defined as any effect caused by human activity (activity is basic element of a project that has potential to affect any aspect of the environment, see EIA for developing countries) on the environment including flora, fauna, sediment, air, water, climate, landscape or other physical structures or the interactions among these factors [Convention on Environmental Impact Assessment, 1991]. Environmental Impact Assessments (EIAs) is a requirement for any project that may have the potential to result in significant impacts to the environment. A principal objective of the EIA (Ghana perspective) is to provide enough relevant information to the Environmental Protection Agency (EPA) to enable the Agency to set an appropriate level of assessment for a proposed project. The information collected through the EIA may be presented in one of several forms, but for larger projects, the most common is an EIS. Environmental impact studies are composed of two distinct phases (i) impacts analysis phase, which is meant to identify, predict, quantify and evaluate the effects of expected impacts before a project occurs and (ii) a monitoring and assessment phase, which is meant to measure and interpret environmental effects during the project and after it has been completed. Impact hypothesis draws on the results of earlier studies of environmental characteristics and their variability [British Geological Survey, 1999]. Impacts whether they are significant or not, can be direct or indirect. Direct impacts to biological resources result when biological resources or critical habitats are altered, destroyed, or removed during the course of project implementation. Indirect impacts to biological resources may occur when project activities result in environmental change that directly influence the survival, distribution, or abundance of native species (or increase the abundance of undesired nonnative species). It is also possible to have beneficial
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impacts, directly or indirectly. Impacts may also be short- or long term. Short-term impacts are generally not considered significant, by definition. Impact thresholds are based on factual evidence of physical disturbance of habitat, and the loss or disturbance of recorded species. Impact thresholds could have significant impacts on biological resources (i.e., plankton and benthos) through (i) loss in substantial number of individual of species or loss that could affect abundance, (ii) a substantial adverse effect on species, natural community, or habitat which is recognised as biologically significant, (iii) significant degradation of pelagic or benthic habitats for rare species and/or native species, and (iv) disruption of the trophic structure of the biological communities. In assessing the impacts on biological resources, the temporal and spatial variability of the benthic assemblages along with predicted area and rate of recolonization constitute a good consideration. Biological communities exhibit complex interacting behaviours among themselves and with the non-living abiotic environment [Lamptey and Armah 2008]. These communities play multiple ecological roles within an ecosystem and therefore, are a critical part in monitoring and evaluation of project impacts. Changes in soft bottom zoobenthic communities in response to the environmental impact have been successfully implemented world-wide in pollution assessment studies and monitoring programs [Pearson and Rosenberg, 1978].
1.4. Environmental Impacts of Dredging The principal biological impacts of dredging include disturbance and removal of benthos and alteration of the substrate upon which colonization depends [British Geological Survey, 1999]. The environmental impacts of dredging have been well documented, with general reviews of the topic provided by ICES [1992, 2001]; Kenny et al., [1998] and Newell et al., [1998]. It was clear from such reviews that most studies have been concerned with impacts of dredging soft sediments or those associated with beach nourishment projects. A direct impact of dredging would come from loss of invertebrates via mortality and removal of sediment. Physical removal of substratum and associated plants and animals from the seabed, and burial due to subsequent deposition of material are the most likely direct effects of dredging and reclamation projects [Newell et al., 1998]. New habitats may also be created as a result of the operation, either directly in the dredged area or by introduction of new habitats on the slopes of a reclaimed area (e.g. hard substratum in the form of breakwaters and revetments). Dredged material may come into suspension during dredging itself as a result of disturbance of the substratum, but also during transport to the surface, overflow from barges or leakage of pipelines, during transport between dredging and disposal sites, and during disposal of dredged material [Jensen and Mogensen, 2000]. Dredging may change the physical environment and could directly impact on macrobenthic organisms through (i) compaction of sediment, (ii) burial of organisms, or (iii) smothering through increased turbidity and siltation [Goldberg, 1989]. Dredging has effects at two locations, the site of removal and the site where the material is dumped [Hall, 1994]. The natural processes of sedimentation in coastal lagoons are significantly altered by dredging activities. The consequence changes in sediment composition as a result, affect the associated macrobenthic fauna. Bonsdorf [1983] examined recolonization after dredging at three shallow brackish sites
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in Finland. The study showed that the pool of available colonists is important in determining the dynamics of disturbed patches. At one site dredging occurred to below the thermocline and the benthos at this level were exposed to deoxygenation events every year which defaunated the sediment. Deoxygenation took approximately two months to kill the fauna and this was followed by a gradual recovery with the peak in species richness occurring after about 10 months. In contrast, just above the thermocline a stable community developed over the six years of the study and this region provided colonists for deeper parts. With the progressive recovery of the upper region, a more diverse and abundant pool of colonists was available to recolonise the deeper parts, which led to successively higher peaks in species richness each year. At a second site at 8-9m depth in a channel, it took 4-5 years for the community to return to a background level, despite the area containing only about three species. Interestingly, early in the colonization sequence, three species established which had not occurred in the area before dredging. Species richness declined after five years and these three species were not found in the final community which itself contained only three species. Maurer et al., [1986] reviewed studies of burial effects and concluded that the pattern of susceptibilities can be reversed when sediments containing silt/clay are compared with those comprising sand. This was based on earlier experimental studies, which indicated that atypical sediments for the area caused the highest mortalities in estuarine bivalve species following burial in natural and exotic sediments [Maurer et al., 1986]. Maurer et al., [1986] cited Kranz [1972] who studied the burrowing of 30 species of bivalves showed that the life habits of the taxa affected the susceptibility of the fauna to mortality. Mucous tube feeders and labial palp deposit feeders were most susceptible, followed by epifaunal suspension feeders, boring species and deep burrowing siphonate suspension feeders, none of which could cope with more than 1 cm of sediment overburden. Infaunal non-siphonate suspension feeders were able to escape 5 cm of their native sediment, but normally less than 10 cm. One potentially complicating factor, when considering the effects of dumping dredge spoil, is that many types of sediment will be contaminated [Hall, 1994]. Indeed, much of the motivation for studies on dumping dredge spoil effects stems from concern over chemical pollutants rather than dumping per se. Flemer et al., [1997] concluded that there was no apparent consistent gross effects of dredged material disposal on macrobenthic community structure at coastal Louisiana and suggested that some long-term unidentified factor (e.g. sediment toxicity) maintained differences in macrobenthic community structure in the three different study areas. A number of factors influence the effects of dredging on local populations including the types of organisms which remain in the vicinity [Thrust et al., 1992], the life histories and mechanisms of dispersal in different fauna [Levin, 1984], the patchiness of the environment [Hall et al., 1994], the spatial and temporal variability of dredging disturbance, the effects of existing or new residents on the substratum [Rhoads and Boyer 1982, Davoult and Richard, 1990] and the potential interactions between dredging disturbance and other perturbations [Jewett et al., 1999]. Dredging activities is also usually associated with profound changes in water quality as a result of alterations to natural suspended sediment loads and localized sedimentation resulting in clouding and colouring of the surface water. Impacts associated with increased suspended particles in the water column include high turbidity levels, reduced light transmittance and reduction or loss of benthic habitats. The intensity and duration of sediment re-suspension
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from dredging and disposal operations highly dependent on the type of equipment, operator, characteristics of sediment, and the hydrodynamic conditions [Collins 1995; Clark and Wilber, 2000]. Elevated suspended sediments have also been shown to adversely affect the respiration of fishes, reduce egg buoyancy, disrupt icthyoplankton development and reduce filtering activities of benthic organisms [Messieh et. al., 1991; Barr, 1993]. Other forms of dredging like aggregate mining can reduce localized current strength, resulting in lowered dissolved oxygen concentrations. Reduced oxygen levels adversely affect the ability of fish and invertebrates to utilize specific areas for spawning, feeding and development [Pacheco, 1984]. The release of material into the water column during dredging can alter water quality, especially if excavated material is high in organic matter. The effects of mixing in the water column are likely to increase the demand of oxygen by decomposing organic matter and the release of nutrients [ICES, 1992]. Furthermore, dredging could increase or decrease the exchange rate of nutrients between the sediments and water column and introduce pulses of productivity during nutrient recycling. Dredging activities therefore affect certain physical and chemical conditions of the water such as degree of oxygenation and mineralization, temperature, salinity, water flow, depth and water level fluctuations. The actual impact of dredging operation will be a function of the spatial extent and degree to which the post-construction environment differs from pre-construction conditions.
1.5. Overview of the Keta Restoration Project The Keta Lagoon area is an ecologically important wetland in West Africa and has been recognized as a designated Ramsar site (a wetland of international importance especially as a habitat for waterbirds). Ghana has ratified both the Ramsar and Bonn (which addresses the conservation of migratory species of wild animals) Conventions in 1988. Due to the high population density of people in the Keta Lagoon area, the Ramsar Convention is particularly applicable because it promotes the conservation and preservation of wetlands through sustainable and ―wise-use‖, as opposed to outright protection through ―non-use‖. The Keta lagoon covers an estimated area of 340 km2 with water depths ranging from 0.47 to 0.94 m in the wet season and 0.14 to 0.56 m in the dry season [Lamptey and Armah, 2008]. The lagoon has a maximum coastal length (east–west) and width (north–south) of 25 and 13.5 km, respectively [Lamptey and Armah, 2008]. It is separated from the sea by a narrow sand bar (Figure 1) and, therefore, receives sea water only through spillover during periods of high tide. The Keta basin was formed by coastal subsidence during the Precambrian [Akpati, 1975]. The upper geologic strata (about 24 m) are composed of coarse, unconsolidated beach sand and gravels both of fluviatile and shallow marine to estuarine origin [Akpati, 1975]. Most areas in the lagoon are typically muddy in the upper 10 cm. The sea grass Ruppia maritima used to occur in the northeastern part of the lagoon and portions of the southern part until disappeared in 2004. The macrophytic flora in the lagoon is dominated by Typha domingensis and Paspalum vaginatum in the northwestern and southwestern portions in the freshwater tributaries of the lagoon. The southwestern part is dominated by Paspalum vaginatum.
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Figure 1. Aerial view of the created habitat island using dredged material (Source: GLDD/ESL/EPA
The lagoon receives fresh water from a large catchment area including (1) runoff from the Tordzie river, which originates from the Akwapim–Togo ranges; (2) runoff from the Aka and Belikpa catchments, which enters the lagoon from the north; and (3) inflows from the Volta estuary through Anyanui creek [Entsua-Mensah and Dankwa, 1997]. The Tordzie river has a catchment area of 2,200 km2 and a mean annual flow of 11 m3 s−1; Aka and Belikpa have catchment areas of 280 and 420 km2, respectively; the total drainage area of the Volta estuary is 37,900 km2 [Finlayson et al., 2000]. Nevertheless, the volume of water (84,446 m3) transferred to the lagoon during one flood period in January 2001 from the Volta estuary via Anyanui creek resulted in a tidal excursion of 5.4 km [Sørensen et al., 2003], indicating that the fresh water that flows from the Volta estuary into the lagoon is not substantial. The estimated static capacity of Keta lagoon is 360×106 m3 when there is no flow of water into it [Finlayson et al., 2000]. The area lies within the dry equatorial region of Ghana, which has two wet seasons, one from May to July (major rainy season) and from September to November (minor rainy season). The mean annual rainfall is 750 mm [Dickson and Benneh, 1988]. The dry season begins in January and ends in March. Annual mean air temperatures range between 24°C and 32°C. Evaporation in the area far exceeds annual rainfall. It is only during the major wet season that monthly rainfall may exceed evapotranspiration and temporary streams flow [Biney, 1986]. The prevailing wind direction is from the southwest (the southwest monsoon), which is a feature of the entire coastal belt of the country [Finlayson et al., 2000]. The mean monthly averages of daily wind speeds range from 5.86 to 8.06 m s−1 [Finlayson et al., 2000]. Restoration project of the Keta beach was driven by episodes of erosion threats dated back 1920s. The project tarried until in 2000 after a definitive study in 1996 and engineering solution recommended [ESL/RPI/GLDD, 2004]. Prior to the restoration project, flooding from the Keta lagoon following torrential rains displacing immediate inhabitants was a perennial characteristics feature. The restoration project was initiated in 2000 by Great Lakes Dredge & Dock (GLDD). The project had four principal components: i) sea defense, ii) land reclamation via beach nourishment; iii) construction of a road along the lagoon; and iv) construction of a flood relief structure. As a complement to the specific objectives of each component, an overall objective of the project was to minimize impact to, or even improve the general environmental conditions and enhance the ecological setting against the background a designated Ramsar site. Restoration science, and its recent manifestation,
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sustainability science (Kates et al., 2001], are partly rooted in ecological fidelity; i.e., those restoration goals characterized by structural replication, functional success, and durability (self-sustainability) [Higgs, 1997]. To give impetus for the project, dredging of the Keta lagoon to obtain appropriate sediment materials for road construction, beach nourishment, and infilling the reclaimable land became a viable option. However, aware of the adverse impacts associated with dredging, innovative dredging was designed to ensure beneficial uses of the dredged material.
1.6. Objectives The main aim of the study was assess the dredging impacts on the receiving environment on spatial and temporal scales. The potential environmental impacts can be positive (beneficial) or negative, direct or indirect and short-term or long-term. This assessment is focused primarily on the biological habitats, species and water quality conditions. The goal was to assess the effect on a soft bottom community resulting from the removal of approximately 9,091,000 m3 of sediment during the dredging of the channel.
MATERIALS AND METHODS 2.0. Field Sampling The sampling was designed to provide a sound monitoring plan that assessed the potential impacts of the dredging on the lagoon ecology especially biological resources and water quality. The sampling strategy/design followed Underwood‘s (1994) BACI; (beforeafter control-impact) approach but included in it aspect during the dredging phase. Following the design seven impacted sites were located in the dredged channel (1-km interval) labelled alpha-numerically (A-0 to G-0), and also a control non-impacted site. Quantitative sampling of macrobenthic fauna was carried out using Orange-peel grab at each location September 2000 (Before Dredging), September 2001 (During Dredging) and September, 2002 (After Dredging) of dredging operations. Four replicate samples were taken at each site. A grab sample constituted a sediment volume of 2.036 x 10-3 m3. The samples were processed by passing through a 0.5mm sieve, processed and fixed with 10% borax prebuffered formaldehyde solution. Water quality parameters were collected quarterly at the surface and bottom (during and after dredging period) using a Van Dorn water sampler. In-situ measurements of dissolved oxygen, temperature, pH, water depth, salinity, transparency were carried out. Additional water samples were collected for laboratory analyses of nutrients (nitrate, phosphate, silicate, sulfate), turbidity, suspended solids, and dissolved solids. Avifauna observations were made using a 60 mm, 15-60x zoom spotting scope mounted on a tripod (Figure 1) and 7 x 50 binoculars. Observations of the shorebirds were made in the morning (6:00 AM) and early evening (6:00 PM). Five monitoring stations within the sphere of the project site were visited in each survey session to quantify shorebirds abundance.
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2.1. Laboratory Sample Processing Macrobenthic faunal samples were washed thoroughly with fresh water in 450-µm stainless sieves to get rid of the formaldehyde solution and excess mud. The washed sediment samples were separately placed in 50 x 40m sorting tray with a white background thinly spread and the organisms picked into storage vials with the aid of hand lens and preserved in 70% ethanol mixed with glycerol. During sorting the organisms were grouped into broad taxonomic units such as polychaetes, mollusks, crustaceans etc. These broad taxa were identified to genus or species levels as possible and counted. Identifications were based on taxonomic guides and manuals [e.g., Day, 1967a, b; Edmund, 1978] as well as voucher specimens in the Zoological Museum of the University of Ghana. Voucher specimens are available for examination. Sediment samples collected for physical and chemical analyses were taken at each sample location at 20-cm deep core. The samples were homogenized, air-dried, and used for granulometric analysis (i.e., sand, silt, and clay fractions) following Bouyoucos‘ [1934] method and also percent organic carbon and percent sulfur contents using the ELTRA 500 CS determinator after pretreatment of the sediment with hydrochloric acid to remove inorganic carbon. Water samples collected at the subsurface and bottom were analyzed in the laboratory for nitrate, phosphate, silicate, sulfate, conductivity, turbidity, suspended solids, and dissolved solids using the HACH DR/2010 spectrophotometer following the methods in A.P.H.A. et al. [1998].
2.2. Data Analyses The data set was analysed using both univariate and multivariate statistics. Spatial and temporal distributional trends were plotted to indicate the impacts of the project on the macrobethic fauna, shorebirds and water quality. To test for differences in community structure between the study shores; one-way Analysis of Similarity (ANOSIM) was utilized [Clark and Warwick, 1994]. This program computes r-statistics as a measure of discrimination. First, a global R-value was computed to indicate the overall effect of similarity between the study shores. Values of R=1 are obtained when all replicates (sites) within the groups (zones) are more similar. The p-value for the statistics was obtained by simulating all possible permutations of assigning replicates (sites) to study zones. In this study, a random sample of 999 permutations was used in each calculation. The species that contributed the most and discriminated one study zone from another were investigated using non-metric similarity percentage procedure (SIMPER) [Clark and Warwick, 1994]. These results assisted in interpretation of the community changes responsible for the observed pattern in the ordination [Clarke, 1993]. The group of species with cumulative contribution above the 50% (dis)similarity threshold were considered important in controlling the taxa assemblages in the studied area.
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3.0. RESULTS 3.1. Distribution of Dredged Materials on Restoration Sites Two hydraulic cutter dredges were used to remove varied quantities of sediments in two burrow pits and access channel (Figure 2). The average depths of the burrow pits were approximately 9.6 m and 11.1 m for pits 1 and 2 respectively (Figure 2). The depths for the access channels ranged from 2-4 m. The burrow pits were approximately 300 m wide while the access channels were 40 m wide. Table 1 presents the quantity of sedimentary materials deposited at each construction site. The total sedimentary material deposited on each constructional site was 2,861 million cubic meter for beach restoration with a daily average production of approximately 11,800 cubic meters. The total dredged material production to the avifauna habitat islands was 2,010 million cubic metres with average daily production of approximately 9,050 cubic meters of sedimentary material. At the site for reclamation, a total of 4,220 million cubic metres and a daily production of approximately 10,300 m3 were deposited. The water to solids ratios were 10–16% in medium sand and 12–20% in cohesive soils [ESL/RPI/GLDD, 2001-2004]. The dredging activities in the lagoon varied throughout the period according to actual sand requirements, but it was estimated that on average 300,000-350,000 m3 of sediment were dredged monthly.
Figure 2. Schematic diagram of relative locations of burrow pits and access channels and their approximate lengths and sampling stations of the dredged channel
Table 1. Average and total dredged sediment deposited at the project specific area Project Component Beach restoration Land reclamation Habitat island Total
Average daily Production (m3) 11,800 10,300 9,050 31,150
Total material deposited (m3) 2,861,000 4,220,000 2,010,000 9,091,000
No. of days for deposition 242 410 222 874
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3.2. Impacts of Dredging Operations on Shorebirds‟ Abundance The total shorebirds abundance increase considerably from 12346 (2000), 13643 (2001) to 114, 398 (2002). Averagely shorebirds‘ abundance indicated significant (p<0.05) increase after dredging (Figure 3) suggesting a positive impact of the project. Nonetheless, the numerical abundance of wader bird group decreased after the dredging operations in 2002 (Figure 4). Conversely, terns showed increased trends from 2000 to 2002, whereas ‗other‘ category fluctuated between the periods (Figure 4).
Figure 3. Mean total abundance of shorebirds before, during and after the dredging periodicity (composite abundance was from August to December of each year)
Figure 4. Percent abundance of shorebirds groups before, during and after the dredging periodicity (composite abundance was from August to December of each year)
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3.3. Dredging Impacts on Macrobenthic Fuanal Community Structure The macrobenthic community of the dredged channel showed significant reduction in abundance (using one-way ANOSIM) between 2000 (Before) and during (2001) (r=0.205, p<0.05), as well as 2000 (Before) and 2000 (After) the dredging (r=0.166, p<0.05) periodicity. The species that contributed to significant difference in the periods were Ischyroceros sp., Nereis operta, Notomastus cf. latericeus, Nephtys lyrochaeta, Tellina nymphalis, Capitella capitata (Table 2). The first four species contributed greater than 50% for the average dissimilarities of 85.29% and 83.57% realized respectively between 2000 and 2001, also between 2000 and 2002. However, three species namely Nepthys lyrocheata, Tellina nymphalis and Notomastus cf. latericeus contributed greater than 50% to the average dissimilarity of 87.71% between 2001 (During) and 2002 (After). The differing abundances of these species largely influenced the macrobenthic assemblage structure of the dredged channel. Table 2. SIMPER analysis results: species contributing to the average Bray–Curtis dissimilarity between the 2000 (Before), 2001 (During) and 2002 (After) dredging based on simultaneous analysis of taxa abundance data. δi: contribution of the i-th faunistic group to the average Bray-Curtis dissimilarity (δ) between the project periods , also expressed as a cumulative percentage (∑δi%). Diss/SD is the ratio of dissimilarity to standard deviation and F is the frequency of occurrence of the 7 sites. For brevity, only species that contributed to ≥ 5.0% and cumulative percentage of ≥70% are listed. The codes in the parenthesis after the species name indicate: „C‟ crustacean, „P‟ Polychate, „B‟ Bivalve Species Ave. Diss Diss./SD Average dissimilarity between year 2000 and 2001 =85.29 Ischyroceros sp. (C) 14.84 1.36 Nereis operta (P) 13.96 0.97 Notomastus cf. latericeus (P) 10.20 1.14 Nepthys lyrochaeta (P) 10.17 1.12 Tellina nymphalis (B) 8.15 0.75 Capitella spp. (P) 6.22 0.59 Average dissimilarity between year 2000 and 2002 =83.57 Ischyroceros sp. (C) 15.84 1.29 Nereis operta (P) 14.55 0.94 Notomastus cf. latericeus(P) 11.16 1.10 Nepthys lyrochaeta (P) 9.68 1.00 Capitella spp. (P) 7.21 0.64 Tellina nymphalis (B) 5.37 0.76 Average dissimilarity between year 2001 and 2002 =87.71 Nepthys lyrochaeta (P) 23.16 0.73 Tellina nymphalis (B) 20.51 0.70 Notomastus cf. latericeus (P) 15.96 0.69 Capitella spp. (P) 7.33 0.78 Ischyroceros sp. (C) 6.48 0.46
(δi)
∑δi%)
(F%)
17.40 16.37 11.96 11.93 9.55 7.41
17.40 33.77 45.72 57.65 67.20 74.62
38 29 43 52 33 24
18.95 17.41 13.36 11.58 8.62 6.42
18.95 36.36 49.72 61.30 69.93 76.35
38 29 43 52 24 33
26.40 23.38 18.20 8.35 7.38
26.40 49.79 67.98 76.34 83.72
52 33 43 24 38
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Figure 5. Temporal distribution of macrobenthic faunal abundance before, during and after dreding
Individual macrobenthic faunal species showed spatio-temporal differences (Figures 6 &7) in numerical abundance such that higher numbers occurred at Stations C-0 (Tellina nymphalis) and G-0 (Nephtys lyrochaeta, Notomastus cf. latericeus and Capitella spp.) during September 2001. Stations F-0 and G-0 were freshly dredged during this period. A notable feature was the absence of mactra nitida at any of the stations before dredging but occurred in appreciable numbers in 2001 (During dredging) (Figure 7). Capitella capitata was also abundant at station D-0 in 2002 (After).
Figure 6. Spatial abundance of macrobenthic fauna before, during and after dredging. Error bars indicate 95% confidence interval
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Figure 7. Temporal distribution of macrobenthic taxa before, during and after dredging periods
The effect of spatial declension in species abundance after dredging was significantly pronounced at Stations A-0, B-0, E-0, F-0 and G-0 (Figure 6). Conversely, Stations C-0 showed significant increased in taxa abundance after dredging. Station D-0 depicted evidence of community recovery. Certain stations notably Stations A-0, B-0, E-0 and F-0 recorded no species after dredging. Probably, the dredged material mainly smothered the species.
3.4. Dredging Impacts on Water Quality 3.4.1. Spatial Pattern Of Water Quality The water quality parameters showed both temporal and spatial variation during the periods of the study (Figure 8). Spatio-temporally, parameters such as total dissolved solids, sulfate and salinity showed a trend. Higher values of these parameters were observed at Stations E-0 and F-0 during May 2002. The lowest values occurred at stations A-0 and D-0. Turbidity did not show any trend, however higher turbidity was recorded at Stations D-0 (Sept. 2001), which could possibly be due to the movement of dredged plume from stations F-0 and G-0 eastward. Levels of turbidity and suspended solids were extremely low at Station G-0 throughout the study period due possibly to the direction of the fetch carrying the dredged plume eastward. The distribution of variables such as dissolved solids, sulphate and salinity seemed to mimic each other spatially. Stations E-0 and F-0 recorded the highest values for these parameters. The other stations recorded values within very narrow range to each other.
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Figure 8a. Spatial distribution of water quality variables at the surface of sampling stations
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Figure 8b. Spatial distribution of water quality variables at the bottom of sampling stations
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3.4.2. Temporal Patterns Of Water Quality Regimes Temporal distribution of water quality variables in the dredged channel are presented in figure 9. The surface waters always stayed well oxygenated and generally saturated. The oxygen concentrations between the surface and bottom waters were significantly different throughout the period except in September 2001. There was no existence of channel prior to this period and hence reference could not be made to pre-dredging periods of differences in surface and bottom oxygen content The pH measurements showed that the dredged channel water was moderately basic with slight increases in June. The surface waters were moderately basic than bottom. Water temperatures during the period ranged from 27 to 31ºC. Temperatures fluctuated between the periods possibly reflecting the prevailing seasonal climatic conditions. Understandably, surface temperatures were moderately higher than the bottom except in Jun02 where the contrast occurred. Nonetheless, the no significant differences existed between the surface and bottom waters. Temperature changes due to dredging are not much of importance. No abnormal thermal regimes were noticed in the dredged channel. Generally, temperature influences molecular diffusion and metabolic rates. The salinity generally mimicked the pattern of water temperature, but showed direct positive relationship with nitrate. The salinity influences many important processes and functions in aquatic systems. For example, the aggregation and flocculation of suspended particles increase with increasing salinity, meaning that water clarity increases [Håkanson, 2006] leading to increasing primary production of benthic algae and phytoplankton [Preisendorfer, 1986]. It is likely salinity spews from the sediment occurred as a result of dredging operations. Turbidity is an important parameter which influenced water quality during dredging. Turbidity was generally low except September 2001 during the peak of the dredging when it increased sharply in the bottom waters. Ostensibly, the bottom waters experienced higher turbidity than the surface throughout the period. The prevalence of moderately higher turbidity at the bottom waters indicates impacts of dredging operations. Water depth showed increased moderately after January 2002 after the dredging. However, the temporal pattern did not any significant difference. Nutrient incursions into the coastal lagoons are routed through land drainages and often in sinks/sources. All the nutrients (nitrate, phosphate, silicate and sulfate) measured were generally higher at bottom waters. This indicates the likelihood of bottom sediments releasing quantitative amounts of nutrients into the water column as sequel of the dredging operations. The highest concentrations of phosphate and silicate were recorded in September during dredging operations (Figure 9). Frequent resusupension episodes decreases phosphorus content in the sediment [Sørensen et al., 2003] resulting in increased concentration in the water column [Watts 2000]. The importance of sediments as a potential source of phosphorus has also been reported in shallow coastal areas [Fisher et al., 1982]. Further, the strong positive correlations of salinity and nutrients lend credence to the efflux of saline nutrient-rich water from the sediment due to the dredging. Sediments constitute an essential environmental reservoir in coastal systems due to their capacity to retain and release different compounds from or to the water column.
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Figure 9. Temporal variations of water quality variables at the surface and bottom of the dredged channel of Keta lagoon
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Surface
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Bottom
Phosphate (mg/L)
0.4 0.3 0.2 0.1 0.0
Figure 9. Temporal variations of water quality variables at the surface and bottom of the dredged channel of Keta lagoon
4.0. CONCLUSION 4.1. Distribution Pattern of Avifauna Community The coastal water bodies of Ghana constitute important habitats for both resident and migratory shorebirds from the East Atlantic and the Mediterranean flyways [Ntiamoa-Baidu & Hepburn, 1988; van de Kam et al., 2004]. The shorebirds use these coastal areas for food, resting and breeding. The Keta lagoon complex is one of the five Ramsar sites being managed [Willoughby et al., 2001; Ryan, 2005], with Songor, Sakumo, Densu and Muni-Pomadze are the other four. Management of these Ramsar sites mainly includes implementation of civil works to minimize the impact of identified problems amongst others. This management objective was considered in the implementation of the KSDPW. As such, the dredged materials were used for birds‘ habitats creation. The positive impact of the habitats creations for shorebirds was evident in the abundance of reported after the project (Figure 3). Notably, the impact was positive for the terns (Figure 4). Possibly, the dredging materials used to create the birds islands not only provide habitat refuge for the shorebirds but also exposed benthic invertebrates serving as reliable source of food.
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Rapid exposure of wetland substrate [e.g. Velasquez, 1992] could lead to rapid exposure of fresh patches of unexploited feeding areas which would consequently attract foraging birds. According to Jan et al. [2003], foraging waterbirds are uncertain about their chances of success on arrival at a patch and therefore sample their environment to get information on the presence of food so as to ‗make decisions‘. Since the decision on whether to keep on feeding or leave a patch depends largely on prey encounter rates. The increased abundance of the shorebirds after the project suggests that they had found reliable patch with increased encounter rate as a result of the project. The waders and ‗others‘ shorebirds categories were negatively impacted by the project as were substantial reduction in their abundance after the dredging operation in 2002 (Figure 4). These shorebirds probably moved away from the noise generated as a result of the project activities and human presence in the vicinity.
4.2. Impact of Dredging on Macrobenthic Fauna The dredged material (approx. 9091,000 m3), mainly peat smothered the macrobenthic fauna in area where the sediment were deposited (habitat islands). It however, exposed new area (burrow pit) for colonization. The rate and period of recovery for the macrofauna would be indicators for assessing the enormity of the impacts. Disturbance likely leads to a nonequilibrium state in community structure where communities are continually recovering the last disturbance [Reice, 1994] as occurred during the dredging phase of the KSDWP. Disturbance of coastal macrobenthic communities induced through experimental manipulation suggest that colonization may be relatively rapid, but time to recovery is variable and depends on the timing of disturbance, nature of the habitat, reproductive periodicity of macrobenthos, and abiotic and biotic factors [e.g. Probert, 1984; Zajac and Whitlatch, 1982]. In this study, macrobenthic faunal community showed a good deal of dominance and diversity 2001 (During Dredging) and 2002 (After Dredging) dredging. In fact, during the periods of dredging the dominant species encountered in the channel was Tellina nymphalis, which possibly survived the low oxygen at the bottom of 9m water depth. This is possibly due to their long siphons, which enable them to filter the water column for food. Gradually, however this species disappear and could not be recorded in the subsequent samples. Exactly a year later colonization by similar species, which were recorded during the dredging and few months after dredging, showed signs of recovery with appreciable numbers recorded. This probably was due to the more favorable conditions that existed in the channel at the time. It must be noted that the species recorded during dredging and a year after were very similar in terms of composition during the wet periods where environmental condition were in the tolerable ranges of the organisms. The abundance of the species showed both spatial and temporal variation. In the 2001 (During Dredging) samples, the abundance of Tellina nymphalis was high at station C-0 and Capitella capitata and other Capitellids were high in Station G-0 (where highest species richness and diversity was recorded). This was due to the fact that sampling was done few days after dredging where most of the recorded species were still surviving. However, in 2002 (After Dredging), the abundant of species occurred in Stations C-0 (though numbers and diversity varied with the previous year‘s results) and D-0.
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In this case, dominant species were Notomastus sp. Capitella capitata and Tellina nymphalis but Station G-0 did not record many species. It could also be realized that the dominant species in each instance were opportunistic species, able to tolerate stressful environments. This corroborates findings by Hall, et al., [1994] that a common consequence of high physical disturbance is a numerical reduction in non-opportunistic taxa. The only exception being the dredge spoils which created a very high turbid environment. Nevertheless, the impact of the dredging on the macrobenthic fauna was measurably felt within the few months as the substrates that served as habitats and on which colonization depends were continuously removed and palpably the first 8 months saw no colonization process in place. However, with the emergence of those species that were decimated, a year after, the channel is expected to fully recover to climax in a year or two. The re-colonization of the macrobenthic fauna was dependent on local hydrodynamic regimes and sediment characteristic, which showed spatial and temporal variations.
4.3. Impacts of Dredging on Water Quality Temporal and spatial variability were observed in the physico-chemical parameters measured (e.g. salinity, total dissolved solids, total suspended solids and sulfate) in the channel (Figures. 8 & 9). Turbidity and salinity were the most commonly observed changes in the water during the dredging operations. Higher turbidity may have ecological consequences not only adversely affect the production of phytoplankton as it interferes with primary production by limiting light penetration [Jonhston Jn. 1981], but affect fish gills its clogging action and can also clog the membranes of filter feeding organisms [Bray 1979]. Many of the water quality variables fluctuated between the periods possibly reflecting natural conditions. Ostensibly, estuaries and coastal lagoons are characterized by variability and low predictability of their environmental conditions. Consequently, their physicochemical parameters exhibit large variation (e.g. seasonal), with the highest concentration generally found following a rainy period. It is therefore sometimes maze decoupling natural phenomenon from human-induced activities such as dredging.
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 249-277 ©2011 Nova Science Publishers, Inc.
Chapter 8
STATE OF KNOWLEDGE OF THE TROPHIC STATE OF WORLDWIDE LAGOON ECOSYSTEMS: LEADING FIELDS AND PERSPECTIVES Monia Renzi*1, Antonietta Specchiulli2, Raffaele D’Adamo2 and Silvano E. Focardi3 1
Research Centre in Ecology, aquaculture and fishery (Ecolab), Polo Universitario Grossetano, University of Siena, Orbetello (GR), Italy 2 National Research Council - Institute of Marine Science, Department of Lesina (FG), Lesina (FG), Italy 3 Department of Environmental Science, University of Siena, Siena, Italy
ABSTRACT In the latest years, the environmental research has focused on studying the water quality of marine-coastal ecosystems and on the main consequences of human activities within these environments, their surroundings and catchments. Among aquatic water systems, coastal lagoons are particularly vulnerable to water-quality deterioration, due to their restricted water exchange. In addition, they are used as nursery areas for aquaculture and fisheries exploitations, which represent the main economic relevance for local inhabitants. Protection of the ecological status of worldwide lagoons has to be the key purpose of the International directives, as coastal lagoons are naturally stressed ecosystems which suffer from frequent environmental disturbances and fluctuations related to their geomorphologic characteristics, general hydrodynamics, abiotic and biological parameters. The main keys of ecological research studies in coastal lagoons are represented by the need to improve the general knowledge on system dynamics focusing on the leading aspects useful to develop eco-compatible management plans which allow us to preserve their productivity avoiding losses of biodiversity related to the increase of bioavailabile nutrients. The increasing number of ecosystems exhibiting frequently a progressive decline of water quality has led environmental researchers and managers to * Corresponding author: [email protected], Research Centre in Ecology, aquaculture and fishery (Ecolab) Polo Universitario Grossetano, University of Siena, via Lungolago dei pescatori s.n.; 58015, Orbetello (GR), Italy.
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Monia Renzi, Antonietta Specchiulli, Raffaele D‘Adamo et al. identify eutrophication as a major worldwide problem. The development of simple and not expensive well calibrated indices of eutrophication represents one of the most actual ecological fields in which researchers are involved. Many European countries have developed within the Water Framework Directive (CE 2000/60), an environmental quality classification scheme in order to assess the trophic state and water quality through the use of specific indices based on environmental factors. Our aim is to evaluate nowadays the state of knowledge related to eutrophication of worldwide lagoon ecosystems, highlighting the main fields of interest and major problems. Leading problems are related to the choise of useful indices, their calibration, their efficiency in describing dynamics of lagoons characterized by different trophic levels and the selection of the opportune pristine ecosystem as reference for lagoon classifications related to water quality.
8.1. INTRODUCTION Coastal lagoons represent ecosystems of particular ecological, social and economic interest. Compared to the sea, they are able to sustain higher fish production rates, representing an important economic relevance for local inhabitants and helping aquaculture and fisheries exploitation. This efficiency is directly related to the fact that coastal lagoons are a natural sink for nutrients, supporting primary producers and, subsequently, other species of the lagoon trophic web. Nevertheless, nutrient enrichments represent the major problem for these systems. Ecological dynamics of coastal lagoons are regulated on the basis of preypredator complex relationships. If the growth of primary producers is excessive and not balanced by herbivores, nutrient increases determine changes in community structure that could, also, evolve towards a dramatic reduction of the ecosystem biodiversity and fish productivity. Lower nutrient levels (low trophism) are associated with lower primary production rates; on the contrary, higher levels of available nutrients (high trophism) could determine hyper-proliferations of macro and microphyto communities (Perez-Ruzafa et al., 2005). Following an increasing concentration of available nutrients in water, aquatic ecosystems could be classified within four trophic classes: oligotrophic, mesotrophic, eutrophic and hypertrophic (Nixon, 1995). A trophic level is not a fixed characteristic but represents the equilibrium reached by a specific aquatic ecosystem as sum of multiple different factors just at the moment when the observations are occurring. This means that it could rapidly and reversibly evolve as a response to specific natural or human-mediated stressors. For the exposed reasons, it is evident that the regulation of lagoon dynamics, directly or indirectly related to nutrient loads, represents the most important target to develop sustainable management plans in coastal lagoons. Unfortunately, ecosystem processes are controlled by complex interactions among natural and human-mediated stressors and fluxes of materials between land, ocean and atmosphere, making coastal lagoons the most changeable and vulnerable environments worldwide (Viaroli et al., 2007). Due to their morphologic, geomorphologic and hydrologic characteristics, which favour nutrient accumulation and reduce contextually their potential dilution potential and carrying capacity, lagoons are naturally stressed ecosystems characterized by frequent environmental disturbances and fluctuations. Furthermore, additive interferences due to human activities increase complexity of system dynamics, modify ecological equilibrium and reduce, as final effect, system resistance and resilience. If ecological relationships are not balanced, systems
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could highlight successive cycles characterized by alternative crises and partial community recoveries with a progressive deterioration of the ecosystem quality. The increasing number of ecosystems which exhibit a progressive decline of water quality has led environmental researchers and managers to identify the eutrophication as the major problem for coastal lagoons worldwide. Briefly, eutrophication could be described as a well-known ecological phenomenon supported by nutrient enrichments causing a significant increase of primary productivity, which could determine a notable reduction of the secondary ones (Kjerfve, 1994). In order to allow the conservation and natural productivity of these ecosystems, the protection of the ecological status of lagoons has to be the key purpose of the International directives. From 1980 to date, significant progress has been made in the development of regulations designed for the coastal lagoon protection and management. The interest from the governments for these systems has led to an exponential enhancement of specific scientific research studies (Basset, 2010). In the latest years, the main target of ecological studies is represented by the need to improve the general knowledge on system complex dynamics focusing on the leading aspects useful to develop eco-compatible management plans which allow us to preserve their productivity avoiding losses of biodiversity related to the increase of bioavailable nutrients. Research worldwide has focused on the complex relationships between human pressure and ecosystem response (eutrophication). The development of simple, not expensive, and well calibrated indices of eutrophication represents one of the most actual ecological fields in which research studies are involved. Many European countries have developed within the Water Framework Directive CE 2000/60 (European Commission, 2000) an environmental quality classification scheme for the water quality assessment, through the use of specific indices based on environmental factors. In this chapter an evaluation of the eutrophication state of lagoon ecosystems worldwide is reported, highlighting the main fields of interest, major problems, international regulations that aim to contrast this phenomenon and major scientific research perspectives. Leading problems are related to the choice of useful indices, their calibration, their efficiency in describing lagoons dynamics characterized by different trophic levels and the selection of the opportune pristine ecosystem as reference for water quality classifications of the lagoons.
8.2. COASTAL LAGOON PRODUCTIVITY: AN ECONOMIC VALUE LINKED TO THE TROPHIC LEVEL It is well known by the literature that coastal lagoons represent peculiar ecosystems for primary and secondary productivity (Nixon, 1995). The net primary production estimated for these ecosystems and calculated over 70 lagoons ranges from 10 to 7000 g of C m-2y-1 (Troussellier and Gattuso, 2007). Relationships between available nutrients and ecosystem metabolism have been highlighted (Viaroli et al., 2008). In particular, oligo and mesotrophic systems show values <300 g C m-2y-1, while 300–500 g C m-2y-1 are associated with eutrophic lagoons. Hypertrophism (>500 g C m-2y-1) could determine a rapid evolution towards the ecological status of dystrophy. Primary productivity could be characterized by a dominance of phytoplankton, macroalgae or phanerogams. For macroalgae productivity, data acquired in 1996 by Morand and Briand highlighted that the seaweed annual productivity was notably high in Italian lagoons (1,000,000 t wet weight, w.w.), while lower values were reported for
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French (100,000–200,000 t w.w.) and Australian areas (100,000–600,000 t w.w.) with densities ranging from 0.2–400 kgm-2 and mat thicknesses included within 2–100 cm. Species dominances are linked to the ecological values of the system and population shifts are reliable to changes of trophism (Knoppers, 1994; Zaldivar et al., 2008a). Unfortunately, prediction models based on simple relationships among nutrient levels and abundance or distributions of different primary producers are not applicable to shallow coastal lagoons because of the wide variability and the overlapping of the boundaries (Nixon et al., 2001). Nevertheless, additions of nutrients could produce cascade effects on trophic webs with significant variation of abundances and biomasses also in upper predators (Zaldivar et al., 2008a). Relationships linking water physico-chemical properties, primary productivity levels, and trophic status of coastal lagoons are summarized in figure 8.2.1.
Figure 8.2.1 Relationships linking water physico-chemical properties, primary productivity levels, and trophic status of coastal lagoons.
Numerous factors could affect water trophism in coastal lagoons, but human activities represent important direct or indirect stressors. For this reason, the evaluation of sustainability of human activities in these ecosystems becomes a main and not a secondary aspect. The sustainability of human activities in the biosphere is a widely discussed problem (UNWCED, 1987). Early discussions between ecologists and economists have stressed limits imposed by the physical environment to the economic development, concluding that humans should utilize species and ecosystems in such a way to allow them to go on renewing indefinitely (Anand and Sen, 2000). As result of the anxieties expressed by environmental scientists and ecologists, policymakers and economists have attempted to formulate the concept of
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sustainable development. The main problem derived from the need to translate ecosystem properties and their value for the human development into an economic and political language. For this reason, ecosystem services are considered in terms of benefits for human populations directly or indirectly derivable from different ecosystem functions (Costanza et al., 1997). On the basis of this approach, the determination of total economic value of any ecosystem is performable, calculating single value of market and non-market components derived from it. Even if the evaluation of the non-market values of ecosystems represents the major target of the economists, this procedure is affected by severe methodological limits (Pimm, 1998). Despite prices are simple to define for market objects, the calculation of value assignable to different world‘s ecosystems could produce severe mistakes. Nevertheless, this strategy could represent an useful universal language of communication among politicians, populations and scientists making ecological values comparable, on an economic point of view, to economic services and manufactured capitals (Costanza et al., 1997). On these bases, wetlands economic values per hectare was estimated to be 165 US$y-1 (Schuyt and Brander, 2004). Due to the fact that the world surface covered by wetlands is about 320,000 km2 (Troussellier and Gattuso, 2007), their total value is about of 5.3 109 US$y-1. Obtained estimations by Costanza and colleagues (1997) reported a total value of 20,070 US$ ha -1y-1 (average) for tidal marshes, while Mangroves habitats were evaluated 11,029 US$ ha-1y-1. The values of different ecological functions could be evaluated considering both the economic damages derivable from their losses and/or advantages from their preservation. As example, wetlands produce a climate regulation function due to the carbon sequestration, evaluable in terms of 265 US$ ha-1y-1, a positive effect on the regulation of disturbance (mainly due to the flood control and storm protection) of 1,839 US$ ha-1y-1. Considering only coastal wetlands, advantages derived from nutrient cycling and waste treatment were estimated to be 4,500 US$ ha-1y-1. The nursery value was calculated to be 170 US$ ha-1y-1, while the habitat value for the protection of migratory species was considered to be of 439 US$ ha-1y-1. The economic value related to the food production and the collection of raw material derived from the productivity of these systems, ranged from 1,142-2,752 US$ ha-1y-1 (Costanza et al., 1997). On these bases, it is clear as the conservation of these ecosystems represents an economic relevance. It is to notice that if the evaluation of the economic values derived from some functions of these ecosystems, such as the primary and secondary production is reasonable; on the contrary evaluations concerning not-marketable benefits are very difficult to perform and could produce questionable results. In fact, these ecosystems constitute an invaluable historical and cultural heritage of not simple conversion into economic terms (Viaroli et al., 2007). As example, it could be quite impossible to evaluate in economic terms the possible losses which could be derived from the ecological deterioration of the Venice lagoon (Italy) listed in 1987 by the UNESCO as world heritage site.
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8.3. NATURAL AND HUMAN-CONTROLLED FACTORS THAT AFFECT TROPHIC LEVEL Trophic level in coastal lagoons is a result of different synergic factors acting both to global and local scales and deriving from natural dynamics or human activities. In relation to natural factors, the main forcing feature on a global scale is represented by the geographical localization, while geomorphology, tidal effects, and salinity are more related to local component. Geographical localization is the first factor able to determine some effects on lagoon trophic level. In fact, it defines the general environmental context forcing the main physico-chemical and ecological characteristics. For instance, water renewal is the process characterizing the reduction of nutrient levels inside the lagoon by dilution with the surrounding sea water. The trophic level of the near sea water represents the minimum base value for the lagoon ecosystems. Seas characterized by high nutrient levels show a low dilution efficiency compared to oligotrophic ones. Recent studies have shown that the Mediterranean sea is characterized by different trophic status. Generally, it is oligotrophic (Fogg, 1995), but the Adriatic Sea is mesotrophic, because of the Po River inputs (Crispi et al., 2001), while the Aegean Sea is mostly eutrophic for the discharges from the Black Sea (Crispi et al., 2001). Climate represents an aspect linked to both global and local dynamics. Local and occasional climatic events could determine significant effects on lagoon structure. As example, tropical coastal areas are frequently subjected to hurricanes which could affect the lagoon structure (Medina-Gómez and Herreira-Silveira, 2003), producing significant differences among systems. Meteorological factors have also impacts on lagoon morphology and related physico-chemical characteristics. Rainfall and the runoff could determine significant changes in rapidly responding variables such as nutrients, phytoplankton and zooplankton biomass and composition (Rissik et al., 2009). Hydrological balance depends on different co-occurring global and local-driven phenomena such as evaporation, water inflows, rains and water losses due to outflows. When evaporation exceedes freshwater supplies volumes, a hyper saline character is usually highlighted (Moreira-Turcq, 2000). Winds are the main factor responsible of natural hydrodynamics in coastal lagoons scarcely affected by tides. Winds enhance water exchanges and fluxes, favouring oxygenation; on the contrary they could produce sediment resuspention (Medina-Gómez and Herrera-Silveira, 2003). The resuspension of steady soft sediments raises organic particulate and dissolved organic matter towards the surface (Hopkinson, 1985) increasing phosphorous levels (Søndergaard et al., 1992), activating bacterial oxidative mineralization (Fanning et al., 1982) and increasing the remineralisation rates (Wainright, 1987; Wainright, 1990). Resuspension also activates nutrient release in interstitial water from sediment particles (Wainright and Hopkinson, 1997). Geomorphologic features are important aspects in system classifications, able to influence lagoon dynamics. In fact, they could determine differences in sunlight exposure and water exchanges (McLusky and Elliot, 2007), helping nutrient accumulation and high primary productivity rates. On a general basis, coastal lagoons are usually oriented shore-parallel (Bossard et al., 2000) and the width of the connections with the adjacent sea are less than 20% of the barrier length during high tide (Bird, 1994). Barriers are constituted by sand or single banks, bars, or coral (McLusky and Elliot, 2007) depending on both local geomorphology and geographical localization. In fact, temperate coastal lagoons are typically characterized by sandbars, while tropical and sub-tropical lagoons are mainly characterized
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by the presence of coral reef barriers originated shore parallel or circularly around islands derived from volcanic activities. Both barriers nature of the barriers and dimensions of the communicating channels (width, length and depth) affect water exchanges between lagoons and the surrounding sea. The morphology of the communicating channels is strictly related to the geomorphology of the region and general marine and climatic features. A recent study performed on 40 Atlantic-Mediterranean coastal lagoons have shown that the geomorphologic features (volume, sea influence and shoreline development) explained alone the 22% of the variance in the canonical analysis and an additional 75% in conjunction with the hydrographical and trophic characteristics (Perez-Ruzafa et al., 2007). For these reasons, human management of barriers could determine significant effects on trophic level, diversity or assessment of biological communities as observed during occasional artificial openings of sandbars (Kozlowsky-Suzuki and Bozelli, 2004). Geological structure of bottom sediments could significantly affect nutrient dynamics. Nutrient release from sediments is a process strictly related to grain-size structure. Chemical composition of sediments could determine different releasing processes during resuspension. In fact, sediments resuspension may lead to the oxidation of the iron into its ferric forms (oxides) which adsorb orthophosphates removing them from the water column (Golterman, 1995; 2001). Also, lagoon soil geology could determine significant difference in nutrient fluxes; karstic substrates determine the absence of river or stream inflows, favouring the presence of spring water (Medina-Gómez and HerreraSilveira, 2003) and reducing notably the nutrient inputs coming from agriculture and soil drainage. Evolutionary trends in lagoon systems could be extremely rapid. As example, changes of the geomorphologic structure occurred in Tindari lagoons (Sicily, Italy) have produced a net migration of the whole sandbar system in the NW-SE direction and a significant natural decrease of the lagoon surface (about 54.000 m2 from 1997 to 2009). This constant evolve of the system has produced, as consequence, significant effects on water chemism (Ruta et al., 2009), trophic levels and biological communities (Leonardi and Giacobbe, 2001). This behaviour does not represent an exception, the Illa de Buda area (Ebro delta) showed the same evolutionary trend with a net reduction of the total surface area of 150 ha from 1957-2000 at a rate of 2 hay-1 (Valdemoro et al., 2007). It is well known that tidal effects differentiate substantially worldwide. Related to the geographical localization of the lagoon systems, water volumes exchangeable between lagoon and sea and the potential dilution effect exercised by the water flux on nutrient levels vary significantly. In fact, the Mediterranean sea, except the Northern Adriatic area, is characterized by lower tidal effects compared to the ocean coastal areas. According to the tide influence, lagoons could be classified in three different groups: lentic non-tidal lagoon (tidal range <50 cm), lentic microtidal lagoon (tidal range >50 cm) (McLusky and Elliot, 2007) and mesotidal lagoon (wide tidal in the range of 1-2 m), as highlighted for the Atlantic Ocean (Zaldivar et al., 2008a). Systems characterized by wide and significant tidal inlets could represent a source of nutrients and suspended solids for the surrounding coastal area. As example, fluxes of suspended solids related to the tide of 13-15 t per tidal cycle were recorded in the Tapong lagoon (WeiChun et al., 2010). Due to their location, between the land and sea, coastal lagoons are characterized by a mixing area between saline and fresh water. Based on hydrological balance within the lagoon (Kjerfve, 1994) and meteorological events, water salinity may vary from fresh water (<3‰) to hyposaline/brackish (3–30 ‰), to marine (30–35 ‰) or hypersaline (>35 ‰). Changes of salinity related to changes of the morphological components (Valdemoro et al., 2007),
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phytoplankton (i.e. diatoms, Saunders et al., 2007), zooplankton (Kozdowsky-Suzuki and Bozelli, 2004) and vegetation assessment (Valdemoro et al., 2007) have been observed. A study performed on 42 fish species in the Koycegiz Lagoon Estuarine System, located on the north-western Turkish coast showed that salinity and turbidity were the most important environmental parameters affecting secondary productivity and determining changes in the fishes assemblage structure (Akin et al., 2005). Relationships between zooplankton and abiotic variables (temperature, precipitations, pH, and duration of ice cover) have been reported by Feike and colleagues (2007). It has been observed that, in temperate systems salinity changes have caused the dominance of Daphnia spp., while fluctuations occurring at species level in tropical lagoons have to be better explored (Kozlowsky-Suzuki and Bozelli, 2004). Approximately 60% of the world‘s population is concentrated in settlements within the coastal zone, i.e. areas that extend 50 km inland from the coastline (Crossland et al., 2005). However, coastal areas have consistently been neglected, poorly understood and exploited, and are under increasing pressure from rapid human population growth and over-exploitation of resources. Humans could affect these ecosystems with great pressures (Aliaume et al., 2007) even if it is to notice that human management and regulation strategies performed throughout the history have allowed some systems to be conserved until nowadays (Carrada, 2007). As result of recent human activities, many coastal lagoon in the eastern Australia have evidently changed. In the Orielton Lagoon (south-east Tasmania, Australia) recent anthropogenic hydrological modifications have influenced water salinity, affecting the lagoon ecology (Saunders et al., 2007). Human activities could strongly influence trophic level by acceleration of natural processes increasing significantly nutrient levels for the primary producers. Man-made pressure has been dramatically increased over the last several decades as a consequence of uncontrolled agricultural, industrial and tourist development. Mediterranean area is a suitable zone for agriculture and tourism. In tropical and sub-tropical systems, the occurrence of acid sulphate soils determines high drainage rates of soil nutrients and fertilizers into the reef (Sammut et al., 1996). These land use practices led to an accelerated soil erosion and a related increasing in fertiliser and pesticide leakage to the aquatic system (Anon, 2003). Effluents from municipal waste water treatment plants (Renzi et al., 2009), industrial activities and human settlements, directly or indirectly collected into coastal lagoons, determine a significant increase of bioavailable nutrients in water (Ibrekk et al., 1991), enhancing the micro and macrophytes proliferations (Perez-Ruzafa et al., 2005). On the basis of the consideration exposed, it is evident that many studies on coastal lagoon have to be necessarily included. During monitoring studies, a critical and preliminary consideration on factors affecting these ecosystems could allow researchers and politicians to evaluate the relative weight of single variables and perform well-sized sampling campaigns, monitoring and management programmes. A summarize of major natural and humanmediated factors affecting lagoon trophism is represented in figure 8.3.1.
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Figure 8.3.1. Summary of major natural and human-mediated factors affecting lagoon trophism.
8.4. WHEN THE IMBALANCE OCCURS: EUTROPHICATION, MAIN FEATURES AND ECOLOGICAL EFFECTS During the last thirty years several coastal environments have shown the occurrence of eutrophication, particularly enhanced in lagoons and estuaries. The eutrophication represents a natural human-enhanced phenomenon which could compromise the ecosystem productivity because of an increase in the rate of supply of organic matter (Nixon, 1995). The ecological characteristics of all organisms living in coastal lagoon are related to environmental stress due to the alternating inputs of marine and freshwaters, in addition to the increased nutrient inputs related to human activities (Sfriso et al., 1992). Dynamics occurring in abiotic matrices (water and sediment) and biological populations (plankton, benthos, nekton) have been widely documented by literature (Zaldivar et al., 2008a and all citations within the paper). The main ecological effect produced by nutrient enrichment is represented by an acceleration in the growth of micro and macroalgae species, causing a loss of water quality (European Commission, 1991). Eutrophication involves a reduction of the available light in the water column, due to the increase of phytoplankton mass, the growth of epiphytes on the seagrass and reduction of their photosynthetic powers. Under conditions of eutrophication, seagrasses are less competitive than opportunistic macroalgae. An increase in organic matter and sulphide concentration in sediments could cause a reduction of seagrass biomasses, allowing opportunistic macroalgae to replace them (Goodman et al., 1995). This phenomenon is reversible and a reduction in nutrient concentrations could lead to seagrass recovery (Ben Charrada, 1995; Lenzi et al., 2003; Plus et al., 2003). Sediment characteristics as pH, Eh (redox-potential), grain-size, nutrient and trace elements concentrations are key factors for seagrass establishment and presence in an eutrophic ecosystem (Ben Charrada, 1995; Plus et al., 2003; Renzi et al., 2007). Many eutrophic coastal lagoons and estuaries produce excessive macroalgal biomass during warmer months (Morand and Briand, 1996). These conditions lead to a settlement of organic matter in sediments and an increase in sulphate-reduction. In these ecosystems more than 50% of organic matter is degraded by sulphate-reduction (sulphate respiration) bacterial processes (Jørgensen, 1983). High decomposition rates of organic matter involve toxic gases such as CO2 and H2S. Dissolved sulphides have a toxic
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effect on biota, producing a relevant impact on the system (Heijs et al., 1999). In this condition, pH values in sediments decrease at levels of greater acidity (for marine ecosystems) and Eh can reach very low values (about -400 mV), leading to a build-up of both reduced and reducing components. Low values of Eh and pH induce to ammonium production (Marty et al., 1990) and nitrite increase by ammonification of organic matter, causing a toxic effect on biota (Torres-Beristain et al., 2006) and stimulating production of nitrophilic algal species. This is particularly evident for rooted plants, whose development is curbed by bacterial and chemical conditions in the sediment, leaves epiphytes development, phytoplankton shielding out light and floating macroalgae masses that can suffocate seagrass meadows (Den Hartog, 1994; Raffaelli et al., 1998). High levels of eutrophication could induce changes from seagrass to seaweed and, if the conditions worsen, to opportunistic microphytes characterized by an higher turnover (Duarte, 1995). Lenzi and colleagues (2003) have observed a macroalgal distribution gradient with phosphorophilic macroalgae near the human nutrient source and nitrophilic macroalgae farer. The anoxia and bacteria associated with the sulphur cycle could mobilise pollutants stored in sediments such as mercury (cinnabar) and methylmercury (CH3Hg+) (Wood and Wang, 1983; Kim et al., 2006). These mechanisms are not yet well known and require further researches. In order to face the effects produced by the eutrophication in coastal lagoons, human control measures are mainly based on engineering approaches (creation of underwater canals, use of pumping stations to increase sea water inflows, use of flow accelerators). Often excesses of macroalgae biomasses are removed using harvesting boats to avoid the occurrence of decomposition processes. These approaches require expansive maintenance which frequently can not be sustained. A not expensive strategy could be represented by human induced sediment disturbance, which could induce oxidative mineralising activities (Logan and Kirchman, 1991), increase of biodiversity (Widdicombe and Austen, 2001), development of phanerogam meadows with reduction on phosphorus limited macroalgae (Lenzi et al., 2003). Nevertheless, the application of this techniques requires the absence of significant pollution of sediments. In fact, pollutants are released from sediment to the water column when oxidation of the organic matter occurs and could be transferred towards the food chain (Kim et al., 2006), producing ecotoxicological risks for biota.
8.5. AN OVERVIEW ON RECENT DATA RELATED TO THE TROPHISM OF LAGOONS WORLDWIDE A review of recent literature reporting trophic levels and specific characteristics of coastal lagoon worldwide is explained. All data have been acquired from major databases of literature, but also public reports of international interest have been considered and included. Despite the great number of coastal lagoon worldwide, not all world‘s area have been well documented by a recent literature. As example, tropical sedimentary lagoon systems are poorly studied (Gordon, 2000). Explanation for this occurrence is mainly related to local, political, economic and social troubles and lack of resources to perform ecological studies. Often, data are acquired on a local basis to allow management plans, but they are not efficiently diffuse throughout international databases or scientific publications. Actually, scientific researches performed in European Countries are the most represented in
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international papers, as the application in the European Community of the Water Framework Directive has enhanced these researches and a large economic support has been given to develop suitable monitoring programs. The geographical localization of recent studied lagoons worldwide is summarized in Figure 8.5.1 Only papers reporting information concerning trophic levels have been included.
Figure 8.5.1. The geographical localization of recent studied lagoons worldwide.
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Water exchanges with the surrounding sea are naturally regulated in tropical and subtropical lagoons. In fact, the occurrence of a long rainy season determines notably an increase of lagoon volume which could also produce flooded of communicating channels. During the dry season the evaporation exceeds freshwater supplies and the trophic level generally increases in these systems. Desert areas, lying in dry equatorial regions, are characterized by high evaporation rates and wide depth excursions (Lamptey and Armah, 2008), which could also produce the complete desiccation of the lagoon during dry seasons and determine a temporary behaviour. In high evaporative systems the exploitation for the production of salt has acquired a notable importance (Lamptey and Armah, 2008). Coastal lagoons located in not developed Countries are particularly subjected to humanderived pollution. As example, about 3.6 billion people live in Asia exploiting natural resources along the coasts (Jennerjahn et al., 2009). The agriculture consumes about 81% of Asia‘s annual water withdrawal overstressing coastal lagoon systems (World Resources Institute, 2005). It has been highlighted by some studies that tropical Asia represents the area with maximum nutrient and sediment inputs to the seawater (Elvidge et al., 1997). Overpopulation could determine a significant nutrient charge also for coastal ecosystems characterized by rapid water exchanges with the ocean. An example is represented by Tapong lagoon (Taiwan, Asia), characterized by wide tidal excursions (2.2-6.0 m), with the strongest tidal current reaching about 75 cms-1 over a spring-ebb tidal cycle (WeiChun et al., 2010). Nevertheless, the lagoon is subjected to eutrophication phenomena, as its surroundings are overpopulated and over-exploited by aquaculture and fish farming. Loading rates of nutrients (N and P) have been reported to be about 1.87 and 0.51 mol m-2y-1, with a residence time of about 10 days (Hung and Hung, 2003). In this system, aquaculture is mainly addressed to the oyster cultures. A recent study in Tapong lagoon has shown that, oysters may increase nutrient levels in the water column via recycling from excretion and remineralisation of feces and pseudofeces (Lin et al., 2006). The application of not well sized management plans can determine not desired effects in lagoon systems. During 2002, all of the oyster culture racks were removed from Tapong lagoon, as it was designated a National Scenic Area, with the aim to reduce nutrient loads. Removal of oyster culture racks resulted in phytoplankton blooms and increasing of eutrophication only in the inner region, which was subject to poor flushing (Huang et al., 2008). Some studies (Lin et al., 2006; WeiChun et al., 2010) have shown that in many tropical lagoons (e.g. Chiku, Terminos, Tampamachoco, Celestun, HuizacheCaimanero) the food web is dependent on the accumulation of detritus in sediments, while in Tapong lagoon the trophic web is mainly supported by herbivores. Researches performed in the eutrophic Lake Nakaumi (Japan) have highlighted that the first biological response to the water eutrophication is related to the benthic community, occurring after 20 years from the first evidence of phenomenon, on a longer temporal-scale if compared to that of the water (Katsuki et al., 2008). In tropical lagoon systems the major control on nutrients, during dry season, is exerted by natural processes such as recycling in mangroves (Jennerjahn et al., 2009). As reported by Jennerjahn and colleagues, the eutrophication in the Segara Anakan lagoon (Indonesia) ranges from low to moderate because of the rapid exportation of nutrient towards the Ocean and the strong control exercised by natural processes in nutrient regulation dynamics. Chilika lagoon (India) represents a Ramsar site of particular interest for its high biodiversity. The lagoon has shown environmental and anthropogenic impacts over the last several decades, such as environmental degradation, siltation, changes in salinity gradients, extensive growth of invasive species, depletion of fishery resources, shifting of the lagoon
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inlet, choking of the lagoon-sea channel. From a previous study, performed for six years from 1999 to 2004, it has been determined that the lagoon was slightly eutrophicated and that the water quality was largely determined by salinity changes (Jeong et al., 2008). Management strategies performed to enhance sea-water exchanges in these ecosystems have led no suitable effect on salinity and turbidity which affect fish catchments and total biodiversity (Mohapatra et al., 2007). Effects related to wars, poverty and the lack of a technological development represent the major problems to face off in many Nations. Countries affected by socio-political problems and human health diseases show a lack of knowledge on coastal areas. An example is represented by Africa whose economic and political assessment do not allow to allocate national resources for studying critical areas and widely characterizing coastal lagoons, but they are mainly aimed to face social problems related to the absence of food, drinkable water for local populations and human diseases. The reconciliation among environmental sustainability, humans needs and economic development represents a challenging problem. In order to favour scientific knowledge and support these Countries, the European Commission has developed numerous multidisciplinary projects including the MELMARINA which was established to monitor and model coastal lagoons in Morocco, Tunisia, and Egypt with the aim to evaluate environmental changes in the Southern Mediterranean Region linked to sealevel rise changes (Flower and Thompson, 2009). Recent studies have showed as in this Mediterranean area water resources are under extreme and growing pressure and water pollution, land reclamation are the main causes of wetland losses around the Mediterranean (Flower and Thompson, 2009). In addition, studies related to the MELMARINA project have deduced that excess nutrients and discharge of waste or agricultural return water together with land reclamation are probably the most serious current and common problems confronting sustainability of the North African lagoons (Ramdani et al., 2009). Many data are available by literature from Burullus, Edku, Manzala, Maryut lagoons located in the Nile Delta, Egypt (Oczkowski and Nixon, 2008). These systems support alone the 60% of the Egypt‘s fish production. Egypt‘s fertilizer consumption hasincreased steadily from 3.4 x 105 t in 1965 to 1.3 x 106 t in 2002 (FAO, 2006). Given the dramatic increase in human-derived nutrient loads on the Nile Delta, a considerable eutrophication in lagoon waters during the last decades has been observed (Okbah and Hussein, 2006), threatening fish productivity. Despite inorganic nitrogen changed from 1 µM (1957) to over 1000 µM (1995), primary production in these systems was dissolved inorganic nitrogen limited (Oczkowski and Nixon, 2008). In relation to Tunisia, researches performed in Slimane lagoon have highlighted the occurrence of a constant enrichment in phosphorous compounds due to human activities, with nitrogen as the limiting factor (Hadj Amor et al., 2008). Bizerte lagoon represents a highly human impacted ecosystem for the presence of urban, agricultural, industrial activities, fisheries and aquaculture farms. Nevertheless, on the basis of the chlorophyll a levels, it could be classified in lower range of eutrophicated systems (Grami et al., 2008). Studies performed on the Ghar El Mehl lagoon (Northern Tunisia), characterized by an eutrophic behaviour, have shown that in this system loads of human origin produced 182 ty-1 of total nitrogen and 26 ty-1 of total phosphorous (Rasmussen et al., 2009). Keta lagoon (Ghana, West Africa) represents the largest of more than 90 lagoons along the 550 km coastline of Ghana (Lamptey and Armah, 2008). In this system high evaporation rates, induced by solar exposition, cause a natural increase of nutrients during summer (Hadj Amor et al., 2008) and presence of permanent hypersaline nutrient enriched waters, which involve osmotic stress for aquatic organisms and
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significant changes of populations along the environmental gradient (Lamptey and Armah, 2008). Salinity changes have a clear control on spatial and temporal variations of zooplankton communities, while the role of the trophic status could be not clearly highlighted as in GrandLahou Lagoon, Cote d‘Ivoire (N‘doua Etilé et al., 2009). Ebrié Lagoon represents the largest coastal ecosystems in the Western Africa. In this system nutrient loads are mainly due to the river inputs and land runoff phenomena. Total annual nitrogen loads in 2000 were estimated to be 33 kt, of which 45% from urban sources, 42% from runoff and 13% from atmospheric deposition. In this system domestic loads are responsible of the 95% of the urban nutrient load (Scheren et al., 2004). Although the Australian continent is characterized by many transitional ecosystems (more than 200 lagoons and estuaries considering only the New South Wales), there are few detailed site-specific studies (Sanderson and Coade, 2010). Consequently, conservation and restoration programmes have been difficult to implement (Saunders et al., 2007). As reported by some studies, Tasmania‘s coastal lagoon waters (ranged in size from 0.02-40 km2) are characterized by a clear nitrogen limitation (Harris, 2001). Many Australian estuaries and lagoons are shallow and the growth of benthic macrophytes would not be limited by the availability of photo-synthetically active radiation under natural sediment and nutrient loads (Sanderson and Coade, 2010). In these systems, which directly exchange water with the open ocean, eutrophic levels during the year could be influenced by the regulation of water volumes inside the lagoon. In fact, a study performed on Dee Why Lagoon (northern beaches of Sydney) has shown that after a prolonged summer dry period, the lagoon filled up over 5 weeks of continuing rainfall until it broke open to the sea, transporting a substantial flux of nutrients and carbon towards the ocean, which, with the subsequent tidal flushing (>60% of volume each tidal cycle) until the lagoon closed, would assist in maintaining mesotrophic conditions within the lagoon (Rissik et al., 2009). The lagoon of the Great Barrier Reef, located off the Queensland coast of Australia, is an area where tourism represents the major economic source (Productivity Commission, 2003). Such a system is characterized by a great surface, over than 1,500 km from Bundaberg (in the south) to the tip of Cape York (in the north). This extention justifies ecological changes from typicaly tropics to typicaly subtropics, with related changes in rainfall patterns (Gordon, 2007). In this lagoon systems major threats are represented by human pressure associated with land use practices (agricultural activities and urbanization) and harbour activities (Gordon, 2007). Further studies have shown that urban waters are responsible of nutrient input for the whole reef lagoon area, while other human activities, such as effluents from urban sewerage treatment plants and aquaculture facilities, contribute less than 3% to the overall nutrient load (Anon, 2003) and are able to affect lagoon dynamics only on a local basis. Nevertheless, the quick expansion of the aquaculture along the Great Barrier Reef coast could represent a potential source in the near future (Boyd, 2003). In such a system, rivers represent a notable source of nutrients. Dissolved inorganic nitrogen measured in river plumes are reported to be typically 10–50 times the concentrations exceeding the trigger levels for environmental harm on corals, seagrasses and algae (Furnas, 2003). Notable effects on inshore coral reefs produced by eutrofication have been described by Fabricious (2005). In relation to American coastal lagoons, tropical and sub-tropical regions, such as the Caribbean Sea and the Gulf of Mexico, are particularly studied. In these areas hurricanes frequently occurs and pristine ecosystems are characterized by low trophic levels (chlorophyll a, chla, ranging from 0.71 to 7.00 mgm-3) as reported by recent literature in Celestun,
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Chelem, and Dzilam lagoons (Herreira-Silveira et al., 2002; Medina-Gómez and HerreiraSilveira, 2003; 2006; Tapia Gonzalez et al., 2008). In these ecosystems, groundwater inputs could represent an important source of silicates, phosphorous (Puerto Morelos Reef lagoon) and nitrogen compounds (Nichupte lagoon system) (Carruthers et al., 2005). Nutrient shifts, causing phytoplankton growth limitation, occur following natural cycles (Herreira-Silveira, 1998). A large part of lagoons are characterized by high pollution levels mainly related to agricultural and urban activities. As example, Indian River lagoon, Florida, is affected by human-related sources of nitrogen (832,645 kgy-1) and phosphorous (94,476 kgy-1) compounds (Sigua and Tweedale, 2003; Philips et al., 2010) and Ciénaga de Tesca lagoon (Colombia) collects the 60% of waste domestic waters from the Cartagena City. In this last ecosystem, eutrophication levels are very high with a phytoplankton biomass ranging from 110 to 160 mgm-3 of chla and ammonium concentrations in water from 0.3 to 1.0 mgL-1 of N (Lonin and Tuchkovenko, 2001). Coastal lagoons in Southern America are generally characterized by higher salinities, related to high evaporation rates, and significant fluctuations during the year related to the climate dynamics, with considerable effects on trophic level and local biota (Moreira-Turcq, 2000; Souza et al., 2003). The knowledge of coastal lagoons in European countries has been remarkably improved by the introduction of the Water Framework Directive and, actually, scientific researches on European lagoons are the most represented in literature. Furthermore, the European Community has also encouraged and financed long term researches in Mediterranean areas not only in Europe, but also in the Northern part of Africa, the Middle-Est, and Southern America. On a general basis, in Mediterranean and Temperate areas, exchanges between lagoons and sea are mainly regulated by humans, because of minor effect of climatic phenomena. Most of physical and environmental variability of Atlantic-Mediterranean coastal lagoons is related to its size, salinity differences compared to the open sea and the trophic status (Perez-Ruzafa et al., 2007). A large lagoon perimeter with shoreline development helps nutrient inputs; for this reason the fishing yield increases with increasing of the perimeter/surface ratios. In these systems the increase of primary productivity involves the abundance of some species at expense of species richness (Perez-Ruzafa et al., 2007). Lagoons located in the Baltic Sea (Northern Europe) are characterized by low values of salinity during the whole year and presence of iced surface during winter (Schumann et al., 2006). In Kursu Marius (Curonian) lagoon, the eutrophication (83-103 mgm-3 of chl a) is associated to the blue-green algae bloom (Aleksandrov and Dmitrieva, 2006). Toxic proliferations are probably due to nitrogen reduction unbalanced than that of phosphorous (Schernewski et al., 2008). Long term monitoring programs performed on both freshwater Curonian (Kursu Marius) and brackish Vistula lagoons have highlighted a general increasing of nutrients in the Baltic Sea waters during the 20th century. In the late 1980s, in Curonian lagoon, the input of N ranged from 60.8 to 109.6 gm-2y-1, while the P ranged from 3.7 to 8.5 gm-2y-1. The crisis in industry and agriculture in 1990s resulted in a nutrient loading under the permissible level leading to eutrophication, but an associated reduction of eutrophication was not observed (Aleksandrov, 2009; 2010). Climate warming and an increase in the number of ―warm‖ years in the 1990s and 2000s have been regarded as possible causes for the continuing eutrophication of the Curonian Lagoon despite a significant reduction of anthropogenic impact. In contrast, the trophic state of Vistula lagoon has not attained high levels, because hydrodynamic activity and brackish waters of this lagoon have prevented a high primary production. In Mediterranean coastal wetlands, highly affected by agricultural
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activities, external freshwater inputs are considered the main driver of nutrient supplies (mainly as inorganic nitrogen) causing a fertilization effect (Chapelle et al., 2000; Lucena et al., 2002; Perez-Ruzafa et al., 2005). The trophic level of lagoons could significantly influence the structure of the trophic web. Although the food web length is conserved in high eutrophic lagoon, some researches performed in French Mediterranean lagoons (Canet and Lapalme) have pinpointed that several consumers occupied a lower trophic level in eutrophic basins (Canet) than in mesotrophic ones (Lapalme), because of a more omnivorous feeding regime in Canet (Carlier et al., 2008). Links between global climate and dystrophic events have been highlighted in the eutrophic Thau lagoon, France (Harzallah and Chapelle, 2002). The Mar Menor lagoon is a well studied ecosystem, characterized by a high touristic impact, hypersaline feature but nutrient levels under the limit of the eutrophication risk. Urban effluents represent a notable source of nutrients and the presence of coastal marshes effectively involves a reduction of water eutrophication, as highlighted by Alvarez-Rogel and colleagues (2006), because they act as a filter to reduce nutrient concentrations before the polluted water flows into the Mar Menor lagoon. Nevertheless, the canalization of urban effluents, performed as management strategy, could determine a lower efficiency in nutrient reduction and an increase of eutrophication. Other studies made on this basin have shown a link between nutrient inputs and not-point agricultural sources, with maxima values of nitrates observed after heavy rains in autumn (Velasco et al., 2006). Furthermore, benthic communities play an important role in regulating the resistance capacity of lagoon ecosystems (Lloret and Martin, 2009). In fact, Caulerpa prolifera represents an important organism able to increase system resistance towards eutrophication processes (Lloret et al., 2008). In this ecosystem relationships between chla levels and fish larvae density suggests the occurrence of a top-down control of the trophic web (Perez-Ruzafa et al., 2005). A large quantity of scientific papers describes the trophic level of coastal lagoons in Portugal, and Ria de Aveiro (Figueiredo da Silva et al., 2002; Lopes et al., 2005; Lopes and Silva, 2006; Rodrigues et al., 2009), Ria Formosa (Edwards et al., 2005; Nobre et al., 2005; Newton et al., 2003; Newton and Mudge, 2005; Gamito and Erzini, 2005; Gamito, 2008; Mudge et al., 2008), Obidos (Pereira et al., 2009a, b) and Algarve (Coelho et al., 2007; Cartaxana et al., 2009) lagoons are the most studied coastal systems. Ria the Aveiro lagoon is estimated to receive 6,118 ty-1 of total N and 779 ty-1 of total P from rivers. In this system sewage effluents contribute for the 5% (yearly basis) of the total charge, with an increase to 65% during summer (Figueiredo da Silva et al., 2002). Nevertheless, further studies have stressed that eutrophication is not frequent in this area (Lopes and Silva, 2006). Researches performed on Obidos lagoon have shown that the system is subjected to time-spatial fluctuations of nutrient levels (Pereira et al., 2009a). It is therefore necessary to perform observations at different time scales in eutrophic coastal lagoons, because of great differences observed in daily/night cycles related to the nutrient availability in water column (Pereira et al., 2009b). Ria Formosa lagoon has shown an enrichment in phosphorous during the observation year, while nitrogen enrichments have been observed in autumn during the rainy season (Newton et al., 2003; Newton and Mudge, 2005). In this last system a significant tidal effect has been highlighted, determining an important additive factor which produces the land-ocean gradient stressor (Gamito, 2008). In Italy, ecosystems studied in detail are Venice (Carrer and Optiz, 1999; Bendoricchio and De Boni, 2005) and Orbetello lagoons (Benedetti-Cecchi et al., 2001; Brando et al.,
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2004; Specchiulli et al., 2008) due to their social, economic and ecological relevance and to the occurrence of frequent dystrophic crises.
8.6. INTERNATIONAL DIRECTIVES: THE NEED FOR ORGANIZING A STRATEGIC REGULATION The progressive decreasing of the surface occupied by wetlands and, in particular, by estuaries and lagoons, is a phenomenon occurring worldwide, probably related to different natural and human-mediated factors (Boesch et al., 1994). These systems are not stable and affected by littoral processes along the shoreline (Valdemoro et al., 2007), currents and relative sea level rise (McFadden et al., 2007) linked to the vertical accretion (Day et al., 1997). Recent projections performed by McFadden and colleagues (2007) have stressed that the increasing of only 38 cm of sea-level will determine in 2080 the loss of 22% of the total surface actually covered, on a world basis. Human mediated factors, such as the increase of urban settlements along the coastal area and land use, directly and indirectly affect the reduction of coastal lagoon surface, producing changes in the natural land cover assessment (Ruiz-Luna and Berlanga-Robles, 2003). Also, reclaiming processes of land, out of necessary of agricultural activities, and planned remediation of wetlands, performed worldwide to face the health disease because of malarial infections, represent a significant human impact. Health diseases are not a secondary cause with that human communities have been face during the last century. Moreover, the occurrence of infections caused by the Plasmodium spp. represents an actual widespread endemic health problem (Leder et al., 2004). These parasites are transmitted to humans throughout the puncture of about a thirty of different types of female mosquito species functioning as vectors (Collins and Jeffrey, 2007). From a standpoint of human health, wetlands represent areas to remediate rather than ecosystems to protect and to study, although they are systems of particular ecological, for their great variety of environments and flora and fauna richness, and clear economic interest (Costanza et al., 1997). It is considerable to notice that human perception of social and economic values deriving from wetland protection strategies is a function which varies depending on the geographic and economic situation of the country, because of different market values of commercial products and local populations needs (Costanza et al., 1997). In the Mediterranean basin it has been estimated that there still are 28,500 km2 of wetlands and about two-thirds of wetlands in Spain, France, Italy and Greece have been drained during the last two generations (Diamantopoulou et al., 2008). The consciousness of the ecological and economic importance of these ecosystems is a quite recent and not totally completed process. Policies finalized to protect transitional ecosystems have been originated from the Ramsar Convention on wetlands hold in Ramsar (1971), Iran. Although this event has been thought to preserve important habitats for birds migrating species protection, it focused for the first time the importance of wetlands for biodiversity conservation, performing a classification system for wetland types (Christian and Mazzilli, 2007) and stimulating further initiatives. Later, at the United Nation Conference on Environment and Development (UNCED) occurred in 1992 at Rio the Janeiro, the Agenda 21 document was adopted. It was a document related to the coastal area integrated management and structured to allow successive agreements and legal instruments. An increasing interest in
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wetlands has been recording since then (Carlsson et al., 2003). This tendency had led to the development of directives and guide lines for the preservation of these ecosystems worldwide. National regulations for managing and protecting coastal water have been developed worldwide; nevertheless, the management of eutrophication-related problems often needs to plan programs on a wider scale than political one. Kursiu Marus/Curonian lagoon is connected to the Baltic sea only throughone channel, whose northern part is under the jurisdiction of Lithuania and the southern part is under the Russia‘s jurisdiction (Aleksandrov and Dmitrieva, 2006; Zelmys et al., 2008). This example shows as national legislations could be inefficient to protect and manage coastal ecosystems. In European Countries the introduction of the Water Framework Directive represents the first important step towards the environmental protection of aquatic habitats, integrating the EU political strategies aimed at management and conservation. It came into force in December 2000 and was aimed at attaining in all Member States good ecological status (Annex V) for all surface waters by 2015. Due to its innovative structure, the WFD focuses on the quantification of the ecological status of aquatic ecosystems rather than on the external pressures, the response of the biological components rather than on the physical and chemical context. The WFD in the Article 5 define that Member States have to characterize their River Basin Districts by the identification of surface water types and anthropogenic pressures. This innovative structure has changed the study approach of ecosystems, focusing the main attention on the role of biological indicators of ecosystem quality. In the WFD there are not explicit requirements related to monitoring criteria and variable selection on hydromorphological quality elements, even if these represent an important element to define system behaviour related to eutrophication. European commission has enhanced multidisciplinary researches projects in not-European countries. As example, the DGXII project was finalized to the development and management tools for wetland resources in Latin America (Loiselle et al., 2001). The National Estuarine Eutrophication Assessment (NEEA) represents in the USA a tool to evaluate actual eutrophic conditions and the effectiveness of the management actions performed by locals to reduce water eutrophication (Bricker et al., 2007). The integrated methodology for the Assessment of Estuarine Trophic Status (ASSETS) has been applied to 138 estuaries, but it may be comparatively applied to rank the eutrophication status of estuaries and coastal areas and to address management options. It includes quantitative and semi-quantitative components and uses field data, models and expert knowledge to provide Pressure-State-Response (PSR) indicators. ASSETS additionally aims to contribute to the EU Water Framework Directive classification system, regarding a subset of water quality and ecological parameters in transitional and coastal waters, including in its model three diagnostic tools: a heuristic index of pressure (Overall Human Influence), a symptoms-based evaluation of state (Overall Eutrophic Conditions) and an indicator of management response (Definition of Future Outlook) (Bricker et al., 2003).
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8.7. ACTUAL PERSPECTIVES: IMPROVE THE KNOWLEDGE THROUGHOUT SCIENTIFIC RESEARCH A detailed knowledge of coastal lagoons was overlooked by the scientific community untill the last twenty years, when an increasing interest towards these ecosystems was highlighted. The first international event, organized in 1981 by the UNESCO/SCOR Consultative committee on coastal systems, focused on the need of an improvement of the scientific researches on these environmnets (Lasserre and Postma, 1982). From this event, researches focused on transitional waters as confirmed by the rapid increase of published papers on these observed from 1986 to 2007 (Basset, 2010). The need to define reference conditions is conceptually questionable since pristine conditions of aquatic ecosystems must incorporate human society. Coastal ecosystems characterized by the presence of international networks could represent potential sentinel ecosystems for coastal observations on global changes (Christian and Mazzilli, 2007). The assessment of the trophic state in aquatic ecosystems generally includes the determination of nutrient levels (ammonium, nitrites, nitrates, soluble reactive phosphorous), the quantification of algal development (chlorophyll a), fluctuations of dissolved oxygen, pH, levels of organic matter (Newton et al., 2003; Dell‘Anno et al., 2002). The concentration limit approaches (CLA) defines limits of chemicals, such as nutrients, in waters and represents an interesting jurisdictional tool due to the relatively easiness to define out layers and critical sites. Nevertheless, it evidences structural limits related to the definition of significant pollution and biological effects related to this occurrence. Due to the transitional water quality paradox described for estuaries by Elliot and Quintino (2007), the definition of pristine conditions related to eutrophication is difficult. For this reason, techniques developed for freshwater and coastal areas should be carefully evaluated and tested before being applied in transitional ecosystems as coastal lagoons (Zaldivar et al., 2008a,b). Palaeoecological approach using diatoms were developed to reconstruct recent changes of physico-chemical variables in a water column (such as salinity) and discriminate human impacts over the time (Saunders et al., 2007). This approach has been successfully applied to evaluate changes of numerous aquatic environmental variables such as salinity (Gell et al., 2002; Tibby et al., 2007), pH (Tibby et al., 2003) and nutrients (Weckstròm et al., 2004). Modelling methods represent a complex but promising strategy to evaluate the eutrophication risk in lagoon ecosystems. Recent models allow us to estimate the coverage of lagoons with benthic macrophytes and how sensitive this coverage is to the effective total nitrogen load per unit area of waterway (Sanderson and Coade, 2010). Furthermore, models could integrate different self-regulating dynamics in coastal ecosystems linking physicochemical and morphological features to biological effects and aim for developing well-sized management strategies (Pinazo et al., 2004). The major goal is represented by the ability to link, through evaluation models, potential modifications in wetlands, due to the local functions, and regional socio-economic context. Useful tools could be represented by the analysis of energetic fluxes through the trophic web (Loiselle et al., 2001). Recently, some authors have suggested that approaches based on the life cycle impact assessment (LCIA) modelization could represent a tool to evaluate the environmental impact derived from human activities on aquatic ecosystems (Hadj Amor et al., 2008).
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The increase of knowledge on transitional water environements (lagoons, wetlands and saltmash systems) needs the development of strategies allowing a rapid diffusion of significant advances. For this reason, worldwide, a groving number of no-profit scientific associations are instituted with the aim to promote rapid cultural exchanges among researchers working on these ecosystems. In Europe among the associations that are actually working to support and encourage co-operation of research groups are avialable on-line the international organisation ECSA (Estuarine & Coastal Sciences Association) and the Italian observational network LaguNet.
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Chapter 9
TREATMENT OF CONTAMINATED SEDIMENTS BY CHEMICAL OXIDATION Sabrina Saponaro*1, Alessandro Careghini1, Kevin Gardner≠2 and Scott Greenwood2 1
Politecnico di Milano, Dipartimento di Ingegneria Idraulica, Ambientale, Rilevamento, Infrastrutture Viarie – Sezione Ambientale, Milano Italy 2 University of New Hampshire, Environmental Research Group, Durham, NH (USA)
ABSTRACT A number of different approaches can be used when managing contaminated sediments depending on site-specific conditions, sediment characteristics, mix of contaminants in the sediment and local regulations. Ex situ management options can include landfill disposal or, more generally, the application of remediation treatments for beneficial reuse, which may improve the economics of management and/or be required to meet regulatory requirements. Chemical oxidation involves the use of chemical additives to remediate sediments contaminated by organic compounds. Due to electron transfers between two (or more) compounds, pollutants are degraded into less toxic or biologically available chemical forms. Chemical oxidation also changes the pH and redox conditions of the treated system, which may also alter the mobility of the target and other compounds and elements. Several different oxidizing agents are available that result in different effectiveness on different pollutants. The most commonly used oxidants are Fenton-like reagents (hydrogen peroxide catalyzed by bivalent iron ions), ozone, permanganate, and persulfate. Recent laboratory studies have also shown good results in peroxy-acid
* Politecnico di Milano, Dipartimento di Ingegneria Idraulica, Ambientale, Rilevamento, Infrastrutture Viarie – Sezione Ambientale, Piazza Leonardo da Vinci 32 – 20133 Milano (Italy), [email protected] ≠ University of New Hampshire, Environmental Research Group, Gregg Hall – 03824 Durham, NH (USA), [email protected]
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Sabrina Saponaro, Alessandro Careghini, Kevin Gardner et al. systems (an organic acid mixed with hydrogen peroxide) to degrade compounds such as Polycyclic Aromatic Hydrocarbons (PAHs). Oxidation is a non-selective process. Therefore, the oxidizable material within the sediment (natural organic matter, detritus, etc.), which may be a significant percentage of the sediment mass, can consume the oxidizing agent. Moreover, many different reactions can occur (acid/base reactions, sorption/desorption, dissolution, hydrolysis, ion exchange, oxidation/reduction, precipitation, etc.). Pollutant removal efficiency strictly depends on the contamination (pollutants, concentrations) and the sediment being treated (physicalchemical properties and composition). Laboratory tests are always necessary to evaluate the feasibility of the treatment to select the best oxidizer and the proper treatment configuration. This chapter reports on laboratory batch tests conducted on sediments from Porto Marghera (Italy) and New York/New Jersey Harbor (NY, USA). Porto Marghera sediments were treated with Fenton-like reagents to remove total petroleum hydrocarbons, PAHs, and polychlorinated biphenyls. Different oxidizers (Fenton-like reagents, persulfate, and peroxy-acid) were used for the New York City sediments polluted by PAHs. For the latter sediments, the leachability of metals in the treated sediments and filtration resistance were also assessed to understand potential unintended consequences of treatment on metal availability and sediment dewatering operations.
INTRODUCTION A large quantity of sediments is dredged all over the industrialized countries, mainly for the maintenance of commercial functions of lagoons, harbors, and waterways. In the USA about 200-300 Mm3 of sediments are dredged every year. About 2.3-4 Mm3 of sediments are dredged for maintenance purposes in the NY/NJ harbor area [Jones et al., 1998; U.S. EPA 2004; U.S. EPA, 2005; Wargo, 2002]. In Europe, the amount is estimated to be 200 Mm3 a year, with very different situations among the countries: 0.1 Mm3 in Norway, 28 Mm3 in The Netherlands, 46 Mm3 in Germany, 56 Mm3 in France [Palumbo, 2007]. In Italy, 6 Mm3 a year were dredged in the period 1988-1997, but no data are available about the current situation [Palumbo, 2007]. The final destination of the dredged material is one of the key points in the sediment management system. Only a small percentage of the volumes mentioned above is contaminated, but the management can be a serious issue especially for areas with severe disposal limitations [Dubois et al., 2008; Hamer et al., 2005]. Among the options, there are relocation in water, when the pollutant concentration is low enough, disposal to landfill, or treatment to accomplish cleanup goals [Reis et al., 2007; Rulkens, 2005]. Local situations can be critical; for instance, about 70-80% by weight of the NY/NJ dredged materials can not be disposed of in the ocean due the high concentrations of organic and inorganic pollutants [Jones et al., 1998; Wargo, 2002]. In the case of disposal or treatment, pre-treatments are usually applied to reduce the volume/weight of sediments and/or reduce salinity [Hakstege et al., 2007; Hamer et al., 2005]. Chemical oxidation involves the use of additives to induce electron transfers between two (or more) species, theoretically resulting in the degradation of organic pollutants to carbon dioxide and water. Inorganic pollutants can change their chemical form, also due to changes in the pH and redox conditions of the system [Reis et al., 2007].
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The chemistry in the oxidative systems is very complex because of the many different kinds of reactions that can occur (oxidations/reductions, acid/base reactions, hydrolysis, sorption/desorption, ion exchange, precipitation, etc.). The reaction pathway is strongly affected by the reactants being used. Moreover, very unstable and reactive radical species can be produced during the primary oxidation pathway, which in turn induce other oxidative reactions [Ferrarese et al., 2008; N‘Guessan et al., 2004a]. Common oxidants used in this kind of treatments are Fenton-like reagents (hydrogen peroxide catalyzed by bivalent iron ions), ozone, permanganate, and persulfate [Ferrarese et al., 2008; Huling et al., 2006]. Recent studies also report the degradation of polycyclic aromatic hydrocarbons (PAHs) in peroxy-acid systems (organic acid mixed with hydrogen peroxide) [Alderman et al., 2007; N‘Guessan et al., 2004b]. The strength of oxidants is usually expressed by the Oxidation Standard Potential (OSP): the higher its value, the stronger being the oxidant. Table 1 reports the OSP for the most common oxidants and radical species. To date, no OSP values are available for peroxy-acids. Table 1. Oxidation Standard Potential (OSP) for the most common oxidants and radical species [Huling et al., 2006]. Oxidant Permanganate (sodium/potassium) Hydrogen Peroxide Persulfate (sodium) Ozone Sulfate free radicals Hydroxyl radical
OSP (V) 1.7 1.8 2.0 2.1 2.6 2.8
FENTON-LIKE REAGENTS Hydrogen peroxide (H2O2) is a strong oxidizer. However, when used without a catalyzer, the decomposition of hydrogen peroxide to water and molecular oxygen tends to be faster than the oxidation reaction on many common pollutants. In the classic Fenton‘s treatment, hydrogen peroxide at low concentration is mixed with bivalent iron ions (Fe2+) in an acidic solution (pH between 2 and 4). Iron ions catalyze the production of hydroxyl radicals (•OH), hydroxyl ions (OH–) and trivalent iron ions (Fe3+), according to the starting reaction: H2O2 + Fe2+ •OH + OH– + Fe3+
(1)
Strong acidic conditions are necessary to enhance the electron transfer between Fe2+ and H2O2 and keep the iron ions dissolved. This seems the major problem when treating soils and sediments, due to the large quantity of acid necessary to consume the buffer capacity of the solid matrix. This, in turn, often results in irreversible damages to the mineral structure of the matrix being treated [Huling et al., 2006; Suthersan et al., 2005]. In order to overcome these points, different treatments have been developed, based on Fenton-like reactants (or modified Fenton‘s reactants). One or more of the following options
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are applied: a) hydrogen peroxide is used at high concentrations; b) chelating agents are used to keep iron dissolved under neutral pH conditions; c) oxides/oxyhydroxides/iron (II or III) minerals in the solid matrix are used as the catalyzer [Ferrarese et al., 2008; Suthersan et al., 2005]. When high H2O2 concentrations are used, many other reactions develop besides reaction (1). These result in the production of additional reactive species, such as hydroperoxide radical (•HO2), superoxide anion (•O2–), and hydroperoxide anion (HO2–). These radical forms are very reactive and can degrade most recalcitrant compounds sorbed on the solid particles. However, excessive oxidant concentrations tend to enhance hydrogen peroxide selfconsumption [Ferrarese et al., 2008; Huling et al., 2006]. Fenton‘s treatments on soils and sediments have proved effective in treating total petroleum hydrocarbons (TPHs), monoaromatic solvents, methyl tert-butyl ether, tert-butyl alcohol, PAHs, phenols, chlorophenols, chlorinated ethenes, chlorobenzene, and explosives. Poor abatements have been obtained on carbon tetrachloride, chloroform, methylene chloride, and dichloroethanes. Site-specific effectiveness has been reported for trichloroethane, polychlorinated biphenyls (PCBs), and pesticides [Huling et al., 2006; ITRC, 2005]. Due to their high reactivity and non-specificity, hydroxyl radicals are consumed in reactions not involving the target pollutants. Therefore, the H2O2 dosage should take into consideration the amount of radicals reacting with natural organic matter, carbonates, and bicarbonates [Di Palma, 2005; Flotron et al., 2005; Suthersan et al., 2005]. Fenton‘s reactions are strongly exothermic. The heat developed during the treatment can enhance pollutant dissolution and volatilization, with potential release in the environment [Ferrarese et al., 2008; Huling et al., 2006].
OZONE Ozone is a strong oxidant widely used for both ex situ and in situ applications. It can oxidize contaminants directly or by the induced hydroxyl radicals, being the prevailing mechanism dependent on the matrix being treated, and the environmental conditions (temperature, pH). Radical attack is favored under alkaline conditions [Di Palma, 2005; Haapea et al., 2006]. Addition of hydrogen peroxide promotes the generation of hydroxyl radicals [Huling et al., 2006]. Non-halogen substituted olefins, phenols, PAHs, non-protonated amino-compounds, and thio-compounds can be easily oxidized by ozone directly. Hydroxyl radicals are necessary to degrade aliphatic hydrocarbons, trichloroethene, tetrachloroethene, benzene, chlorobenzene, and PCBs. Ozone can rapidly react with both electron-rich olefins and aromatic compounds. With olefins, the reaction rate decreases as the number of chloride substitutions increases. With aromatic compounds, the reaction rate increases as the number of functional groups increases [Cassidiy et al., 2002; O‘Mahony et al., 2006]. Ozone has a short retention time in the environment, as it reacts with a wide range of naturally-occurring substances [Huling et al., 2006; Rivas, 2006].
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PERMANGANATE Permanganate salts (usually potassium or sodium permanganate) in an aqueous system generate permanganate ions MnO4–. Equation (2) shows the reaction occurring at pH values between 3.5 and 12: MnO4– + 2 H2O + 3e– MnO2 (s) + 4 OH–
(2)
MnO4– ions do not generate radical species and oxidize pollutants by direct electron transfer. Compared to Fenton‘s systems, permanganate has slower reaction rates and persists in the environment longer, which can be an advantage for in situ applications [Huling et al., 2006]. Despite the relatively low OSP value, permanganate has proved effective on a wide range of organic compounds, including molecules with carbon-carbon bounds, aldehyde groups or hydroxyl groups. It is recommended for in-situ and ex-situ applications for many petroleum hydrocarbons. Some pollutants, such as 1,1,1-trichloroethane, 1,1-dichloroethane, carbon tetrachloride, chloroform, methylene chloride, chlorobenzene, benzene, some pesticides, and PCBs, seem to be recalcitrant to degradation with permanganate [Dash et al., 2009; Huling et al., 2006, Ferrarese et al., 2008]. A wide range of natural compounds (above all, natural organic matter and reduced chemical species) can react with MnO4–, resulting in a high oxidant demand. Metal oxidation can increase their leachability, and this is the case of chromium and nickel [Al et al., 2006; Huling et al., 2006]. The reaction product MnO2 is poorly soluble in the pH range 3.5-12. Its deposition on the solid matrix can negatively affect pollutant removal efficiency due to mass transfer limitations. However, MnO2(s) behaves as a sorbent for many heavy metals (Cd, Co, Cr, Cu, Ni, Pb, Zn), especially at high pH values. Moreover, it has the role of primary electron acceptor in the oxidation of As(III) to the less soluble As(V) [Huling et al., 2006].
PERSULFATE Persulfate salts dissociate in aqueous solution to create persulfate anion S2O8–, which is a strong oxidant. Persulfate anion, in turn, can produce the sulphate radical •SO4–, more powerful than S2O8– itself and the hydroxyl radical. The production of •SO4– can be achieved by "activating" the system as follows: i) heating to temperatures of about 35-40 °C; ii) adding transition metal ions (such as bivalent iron ions); iii) by UV irradiation; iv) rising the pH value above 10; v) by H2O2 [Ferrarese et al., 2008; Huling et al., 2006; Liang et al., 2008]. Equation (3) shows the chemical activation reaction based on Fe2+: S2O8– + Fe2+ Fe3+ + •SO4– + SO42–
(3)
Persulfate is effective on a wide range of organic contaminants, including mono- and poly-aromatic compounds [Cuypers et al., 2000].
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Beside reactions with the target contaminants, sulphate radicals react with a wide range of species in the sediment. An excessive use of activating Fe2+ results in unwanted consumption of the oxidant as well. Usually, the amount of persulfate dosed in the treatments widely exceeds the stoichiometric requirements [Huling et al., 2006; Liang et al., 2008].
PEROXY-ACIDS A peroxy-acid system is based on using hydrogen peroxide and an organic acid produce a peroxy-acid compound. This can react directly with the organic pollutants, produce hydroxyl cations that in turn react with the pollutants [N‘Gussan et al., 2004b]. N‘Gusussan et al. [2004a], the acetic acid was used to induce a cyclical catalytic process, shown in Figure 1.
to or In as
Figure 1. Peroxy-acid cyclical catalytic process obtained with acetic acid [modified from N‘Guessan et al., 2004a].
Peroxy-acids are relatively selective oxidizing agents. They act on aromatic rings, double and triple bonds, whereas they do not react in unwanted competing reactions with molecules such as sugars [N‘Guessan et al., 2004b]. On the other hand, the additions of large amounts of acetic acid to sediments have significant environmental implications, in particular due to the drastic decrease of the system pH [N‘Guessan et al., 2004a]. Peroxy-acid oxidation is a well-known technology in pulping industry. Its use for the remediation of contaminated soils and sediments is a recent application [Ciotti et al., 2008; Levitt et al., 2003]. In literature, some works are reported on the use of peroxy-acid systems for the degradation of PAHs, but information is not available yet about the effectiveness on other organic pollutants. In N‘Guessan et al. [2004b], α-methylnaphthalene and benzo[a]pyrene on artificially contaminated sediments were degraded at laboratory scale with acetic acid or propionic acid in peroxy-acid systems. Although the reaction rates with the
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propionic acid were faster than with the acetic acid, the latter provided a higher removal efficiency of the target pollutants. Alderman et al. [2007] used a PAH-contaminated soil from a U.S. Superfund site to evaluate the effectiveness of peroxy-acid oxidation at lab scale. No significant difference was found in the removal rate of low and high molecular weight PAHs. Ciotti et al. [2008] carried out laboratory tests using different acetic acid to hydrogen peroxide mole ratios on two sediments spiked with anthracene and pyrene. The highest removal efficiency (>95% in 24 hours) was reached with an acetic acid to H2O2 mole ratio of 3.
CASE STUDIES The oxidizers mentioned above show different effectiveness in treating sediments, according to the pollutants, the sediment and the environmental conditions involved. Experimental tests are recommended to assess site-specific feasibility of chemical oxidation and to select the most appropriate treatment conditions [Huling et al., 2006; Rivas, 2006]. Two case studies are discussed in this chapter, for which chemical oxidation was tested at lab scale on polluted sediments from Porto Marghera (Venice, Italy) and New York/New Jersey Harbor (NY, USA). In the first case, Fenton-like reagents were used to treat total petroleum hydrocarbons (TPHs), PAHs, and PCBs. In the second case, different oxidizers (Fenton-like reagents, chemically activated persulfate, and peroxy-acid) were tested on sediments with high PAH concentrations, also assessing under selected conditions changes in metal leachability and Specific Resistance to Filtration (SRF) of the treated sediments.
MATERIALS AND METHODS Sediments Porto Marghera Sediments Located next to Venice lagoon, Porto Marghera is one of the most important industrial/commercial harbors in Italy. From the 1950s to 1980s, many chemical and petrochemical industries have settled at the site, but after this period, the recognition of human health hazards due to pollution brought to the progressive reduction of industrial activities. In 1993, a protocol was signed by the local authorities and the Italian Environmental Ministry, establishing specific limit values for the sediments dredged in the lagoon. According to this protocol, the final destination of the dredged sediments must take into account pollutant concentrations. In 1998, Porto Marghera was recognized as a National Priority Site (NPS) by the Italian Law n° 426. An official agreement was signed between different public institutions and private companies to remediate the site [Carlon et al., 2005]. The sediments used for this study were dredged in the Northern canal. To ensure the stability of their physical-chemical properties over the duration of the research program (2 years), after dredging the material has been air-dried for 72 hours, sieved to less than 4 mm to remove wood and shells, homogenized, and stored under controlled conditions.
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The sediment was composed of sand (39 2 % w./w.) and particles <63 μm (61 3 % w./w.); particles <45 μm accounted for more than 50% on weight basis. The residual moisture was 2.8 % 0.3 w./d.w. The organic carbon content was 2.0 0.2 w./d.w. pH was 8.6 0.3. As far as the elemental composition is concerned, the sediment contained about 15% Si, 12% Ca, 4.5% Al, 3.5% Mg and Fe, about 2% Na and K, and 1% Cl. Pollutant concentrations are reported in Table 2, and compared to the concentration limits in the Venice protocol. Light PAHs (2- to 3- aromatic ring PAHs) and heavy PAHs (4- to 6- aromatic ring PAHs) were approximately 8.0% and 92% (on weight basis) of total PAHs. Table 3 reports the concentrations of selected PCB congeners. Table 2. Pollutants measured in Porto Marghera sediments and classification based on Venice protocol. “Light PAHs” refers to the 2- and 3- aromatic ring PAHs, “heavy PAHs” refers to 4- to 6- aromatic ring PAHs. Pollutant
Unit
Measured value
As Cd Cr (total) Cu Pb Zn TPHs PAHs (total) Light PAHs Heavy PAHs PCBs (total)
mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. mg/kg d.w. μg/kg d.w.
23 ± 2 6.0 ± 0.6 661 ± 186 101 ± 31 144 ± 13 826 ± 28 213 ± 38 90 ± 5 7.0 ± 1.5 83 ± 5 202 ± 98
Venice protocol limits A B 15 25 1 5 20 100 40 50 45 100 200 400 30 500 1 10 10 200
C 50 20 500 400 500 3000 4000 20 2000
Classification B C Above C C C C B Above C C
Table3. PCB congeners measured in Porto Marghera sediments. Congener BZ-8 BZ-18 BZ-28 BZ-52 BZ-101 BZ-81 BZ-77 BZ-123 BZ-118 BZ-114 BZ-105 BZ-138 BZ-126 BZ-167 BZ-156 BZ-157 BZ-180 BZ-169 BZ-198 BZ-189 BZ-206 BZ-209
IUPAC Name 2,4‘-dichlorobiphenyl 2,2‘,5-trichlorobiphenyl 2,4,4‘-trichlorobiphenyl 2,2‘,5,5‘-tetrachlorobiphenyl 2,2‘,4,5,5‘ -pentachlorobiphenyl 3,4,4‘,5-tetrachlorobiphenyl 3,3‘,4,4‘-tetrachlorobiphenyl 2,3‘,4,4‘,5‘ -pentachlorobiphenyl 2,3‘,4,4‘,5 -pentachlorobiphenyl 2,3,4,4‘,5 -pentachlorobiphenyl 2,3,3‘,4,4‘-pentachlorobiphenyl 2,2‘,3,,4,4‘,5‘-hexachlorobiphenyl 3,3‘,4,4‘,5-pentachlorobiphenyl 2,3‘,4,4‘,5,5‘-hexachlorobiphenyl 2,3,3‘,4,4‘,5-hexachlorobiphenyl 2,3,3‘,4,4‘,5‘-hexachlorobiphenyl 2,2‘,3,4,4‘,5,5‘-heptachlorobiphenyl 3,3‘,4,4‘,5,5‘-hexachlorobiphenyl 2,2‘,3,3‘,4,5,5‘,6-octachlorobiphenyl 2,3,3‘,4,4‘,5,5‘-heptachlorobiphenyl 2,2‘,3,3‘,4,4‘,5,5‘,6-nonachlorobiphenyl Decachlorobiphenyl
Value (μg/kg d.w.) 10.1 ± 3.9 11.3 ± 4.8 2.8 ± 1.0 3.7 ± 1.4 6.8 ± 2.6 11.6 ± 1.4 9.4 ± 5.9 13.2 ± 3.3 7.0 ± 2.4 9.0 ± 3.5 1.8 ± 0.2 9.9 ± 4.4 9.4 ± 2.8 2.4 ± 0.3 1.7 ± 0.2 1.7 ± 0.3 8.7 ± 4.3 2.3 ± 1.5 1.6 ± 0.0 1.6 ± 0.0 2.3 ± 0.7 9.4 ± 2.7
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Gowanus Canal Sediments Located in Kings County (Brooklyn), New York City (NY, USA), Gowanus canal is an industrial waterway constructed in the mid-19th century. Its banks became the site of intensive industrial activities (such as refining, coal gasification, soap making and tanning). Today many of these industrial activities have ceased, but sediments remain contaminated by inorganic and organic pollutants. In particular, PAHs are a critical group of contaminants. The canal area remains densely populated and community pressure is providing an impetus for remediation and redevelopment [U.S. ACE, 2004]. The sediments were dredged, mixed and characterized. The pre-treatment described for Porto Marghera sediments was not applied in this case, as the duration of the study was shorter (6 months). The sediment was composed of sand (79 4 % w./w.), a small amount of silt (17.0 0.9 % w./w.), and a negligible amount of clay (2.5 0.1 % w./w.). The moisture content was 55 2 % w./w. The organic carbon content was 6.1 0.4 % w./w. Iron content was 2.2 0.8 % w./w. pH was 7.9 0.2. The SRF value was 3.1 ( 0.4) · 1012 m/kg; according to the literature, this value suggests a medium to high filterability of the sludge [Guangwei et al., 2009]. Table 4 reports pollutant concentrations measured in the sediment and two classes of values reported in the National Oceanic and Atmospheric Administration Screening Quick Reference Tables (NOAA SQuiRTs) for marine sediments [Buchman, 2008]. Sediments were heavily polluted by PAHs; light PAHs and heavy PAHs were 39% and 61% (on weight basis) of total PAHs respectively. Cd, Cu, Pb, and Zn concentrations were high based on the screening values in the NOAA tables. Table 4. Concentration measured in Gowanus canal sediments. Probable Effect Level (PEL) and Effect Range Median (ERM) values reported in NOAA SQuiRT (National Oceanic and Atmospheric Administration Screening Quick Reference Tables) are also shown. “Light PAHs” refers to the 2- and 3- aromatic ring PAHs, “heavy PAHs” refers to 4- to 6- aromatic ring PAHs. Pollutant
Value (mg/kg d.w.)
As Cd Cr (total) Cu Pb Zn PAHs (total) Light PAHs Heavy PAHs
8.8 ± 1.3 8.4 ± 1.4 91 ± 14 218 ± 25 346 ± 35 473 ± 55 1340 ± 265 525 ± 120 815 ± 140
NOAA SQuiRT – Marine Sediments (mg/kg d.w.) PEL ERM 41.6 70 4.2 9.6 160.0 370 108.0 270 112.0 218 271 410 16.7 44.8 1.4 3.2 6.7 9.6
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Oxidation Tests Porto Marghera Sediments For Porto Marghera sediments, Fenton-like reagents were selected for the oxidation treatment. Each test was carried out in batch, using 5 g d.w. of sediment and a Liquid to Solid ratio (L/S) of 10: v./w. Different suspending solutions were prepared by mixing:
deionized water or tap water; a commercial solution of hydrogen peroxide; ferrous sulphate (FeSO4) as the Fe2+ supplier; acidifying agents and buffer solutions: hydrochloric acid (37 % by volume) and acetic acid (1 M), or phosphoric acid (0.4 % by volume), or acetic acid (1 M).
Table 5 summarizes the experimental conditions; each condition was tested at least in duplicate. Tests duration varied from 2 to 24 hours. The test designated K* (see Table 5) was carried out in two steps with different duration (6 h and 18 h respectively): hydrogen peroxide and phosphoric acid were added in the first one, whereas FeSO4 was added in the second one. Tests were done in 200 ml glass vessels, sealed with a PTFE-covered gasket. During the test duration, mixing was ensured by a horizontal-axis shaking table (Tecnovetro, I) operating at 200 oscillations per minute. At the end, samples were centrifuged at 2000 rpm to separate solids from the liquid phase. The liquid phase was filtered (0.45 μm) and used to measure residual hydrogen peroxide, dissolved Fe2+ and Fe3+, and pH. Measurements of organic pollutants in the liquid phase were occasionally carried out, resulting in a negligible contribution to the pollutant mass balance. Based on the residual hydrogen peroxide measured in the liquid phase, sodium sulphite was added stoichiometrically to stop the oxidation reactions in the solid phase. Then the solid phase was analyzed to quantify TPHs, PAHs and PCBs. Table 5. Oxidation tests carried out on Porto Marghera sediments (5 g d.w. sediment, L/S = 10:1 v./w.) Test
(1)
A and A* B C D E F and F* G* H* I* K*
Duration (h) 2 24 24 24 24 24 6 and 24 6 and 24 6 and 24 6 / 18
H2O2 (mmol H2O2/ g d.w. sed.) 16.2 16.2 16.2 16.2 32.4 32.4 16.2 16.2 16.2 16.2 / 2.74
Fe2+ added (mmol Fe2+/ mmol H2O2)
HCl + CH3COOH H3PO4 (ml) (ml)
CH3COOH (ml)
2.4 + 2
1:990 1:123 1:966
- / 1:96
20 0.3 + 20
20 / -
(1) * indicates that the test was performed with tap water instead of deionized water.
10
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Gowanus Canal Sediments Three different kinds of oxidizer were selected for Gowanus canal sediments: Fenton-like reagents (FEN tests), persulfate (SUL tests), and peroxy-acid (ACI tests). Tests were carried out in batch, using 5 g d.w. sediment and the L/S reported in Table 6. Different suspending solutions were prepared by mixing:
deionized water; a commercial solution of hydrogen peroxide for Fenton-like and peroxy-acid tests; Na2S2O8 as the oxidant in persulfate tests; FeSO4 as the Fe2+ supplier for Fenton-like and persulfate tests; acetic acid for peroxy-acid tests,
dosed according to Table 6. The duration of each test was 24 h. Each configuration was carried out at least in duplicate. Tests were done in 200 ml glass flasks without cap. Mixing was ensured by a shaking platform (Innova, NJ-USA) operating at 180 rpm. At the end, samples were centrifuged at 2000 rpm to separate solids from the liquid phase. The liquid phase was filtered (0.45 μm) before acid digestion for metal analyses. In order to measure the PAH concentration on the sediment after treatment, the solid material on the filter was joined to the centrifuged solid phase and quenched with sodium sulphite; the quantity of sodium sulphite was calculated stoichiometrically on the amount of oxidizer added in the test. Some solid samples, which were not quenched, were used for SRF measurements, according to the Buchner Funnel test described in U.S. EPA [1987]. Table 6. Oxidation tests on Gowanus canal sediments. Test FEN-1 FEN-2 FEN-3 FEN-4 FEN-5 FEN-6 SUL-1 SUL-2 ACI-1 ACI-2 ACI-3
L/S (ml/g d.w. sed) 1.7 1.9 1.7 1.9 5.0 5.0 5.0 5.0 3.7 3.7 5.0
Oxidizer (mmol oxid./ g d.w. sed.) 6.7 6.7 3.3 3.3 3.3 3.3 6.7 3.3 15.7 H2O2 + 15.7 CH3COOH 10.5 H2O2 + 15.7 CH3COOH 10.5 H2O2 + 15.7 CH3COOH
Fe2+ added (mmol Fe2+/ mmol oxid.) 1:50 1:50 1:50 1:25 1:25 -
Chemicals and Analytical Methods All chemicals were reagent-grade commercial products. Particle size distribution of sediments was measured according to ASTM D422 – 63 [ASTM, 2008]. Sediment pH was measured according to ISO 10390 [ISO, 2005]. The
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Buchner Funnel test described in U.S. EPA [1987] was carried out operating at 64 kPa for 40 min. Organic carbon content was assessed through loss on ignition at 550°C [EN, 2007]. The following chemical methods were used for Porto Marghera sediments: i) EPA 3541 for the extraction of organics [U.S. EPA, 2007]; ii) EPA 3630C for clean-up [U.S. EPA, 2007]; iii) EN 14039 by GC/MS (CV: 20%) for TPHs [EN, 2004]; iv) EPA 8260 B by GC/MS (CV: 20%) for PAHs [U.S. EPA, 2007]; v) EN 12766-1 by GC/ECD for PCBs [EN, 2000]. Inorganics were measured by X-ray spectrophotometry (internal method). Hydrogen peroxide concentration was measured by spectrophotometry using the Lange LCW 058 kit. The concentration of dissolved iron was spectrophotometrically measured according to ISO 6332 [ISO, 1988]. The following chemical methods were used on Gowanus canal sediments: i) EPA 3545A for the extraction of PAHs [U.S. EPA, 2007]; ii) EPA 3630C for clean-up [U.S. EPA, 2007]; iii) EPA 8260 B by GC/MS (CV: 20%) for PAHs [U.S. EPA, 2007]. Inorganics were measured by microwave oven acid digestion (EPA 3051 A [U.S. EPA, 2007] and ICP analyses by EPA 6010C [U.S. EPA, 2007].
RESULTS AND DISCUSSION Porto Marghera Sediments Table 7 reports the measured concentrations of H2O2, Fe(II) and Fe(III) in the aqueous phase normalized to the slurry weight and the pH values at the beginning and at the end of the tests. In G*, H*, I* and K*, results obtained after 6 hours of treatment are also reported in parentheses. Hydrogen peroxide was completely consumed in most 24 hour-tests; residual concentrations of H2O2 were measured only where phosphoric acid was added (G* and K*) due to its stabilizing effect on hydrogen peroxide [Charlot, 1977]. A limited consumption of hydrogen peroxide was achieved after 2 or 6 hours of treatment. Table 7. H2O2, Fe(II) and Fe(III) in the aqueous phase and pH values. For K*, results in parentheses refer to 6 hours of treatment. Test A A* B C D E F F* G* H* I* K*
H2O2 (% w. H2O2/ w. slurry) start end 5 3.7 5 2.5 5 <0.09 5 <0.09 5 <0.09 10 <0.09 10 <0.09 10 0.5 5 (3.9) 2.5 5 (1.5) <0.09 5 (0.8) <0.09 5 (3.9) 2.1
Fe(II) (% w. Fe2+/ w. slurry) start end 3.9E-4 7.7E-4 4.6E-4 3.5E-4 1.8E-5 7.3E-6 1.2E-3 4.6E-6 6.7E-3 2.2E-5 1.1E-5 5.1E-6 4.7E-3 7.6E-6 1.1E-7 5.3E-6 1.2E-7 (2.6E-7) 3.1E-7 2.0E-6 (2.5E-7) 1.1E-7 1.1E-6 (5.0E-7) 1.8E-7 1.2E-7 (2.6E-7) 2.2E-7
Fe(III) (% w. Fe3+/ w. slurry) start end 3.6E-4 2.2E-4 3.9E-4 1.4E-4 7.5E-6 2.5E-6 4.0E-5 4.9E-6 5.8E-4 1.0E-6 2.0E-5 3.6E-6 2.2E-5 7.9E-6 2.2E-5 2.5E-6 1.6E-7 (3.1E-8) 4.7E-8 3.1E-8 (<1.0E-9) 4.7E-8 4.7E-8 (<1.0E-9) 6.2E-8 1.6E-7 (3.1E-8) <1.0E-9
pH start 3.6 3.6 7.1 7.0 6.8 7.1 6.5 6.5 5.0 5.0 5.0 5.0
end 3.7 3.5 7.7 8.0 7.8 7.9 8.0 7.6 (4.9) 4.6 (5.8) 7.7 (5.9) 7.2 (4.9) 4.7
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Fe(II) dissolved concentration at the beginning of the treatments without acidification (tests B to F* in Table 7) was high where FeSO4 and deionized water had been added (C, D, and F). Comparison between F (deionized water) and F* (tap water) suggests that tap water negatively affected FeSO4 dissolution. This could be related to the presence of major species in tap water (22 mg NO3−/l, 65 mg SO42−/l, 284 mg CaCO3/l) interfering with the dissolution kinetics and chemical equilibria in the slurry system [Greenberg et al. 1992]. In C, D and F, Fe(II) dissolved concentration at the end of tests was about three orders of magnitude lower than the starting value and similar to the ending value in F*. The pH values were quite stable during the treatments, but in H* and I* the pH increased more than 2 units at the end of the treatment, with stable values within the first six hours. Figure 2 shows the TPH concentration measured in the sediment after the oxidation treatments. The removal efficiency was high (>80%) for all the configurations tested. The highest abatement (95%) was achieved in G*. Treatments A*, G*, H* and I* were effective in downgrading the classification of the sediment (from class B to class A) for TPHs. Total PAH concentrations are shown in Figure 3. The highest abatement (50%) was achieved in A*. A 40% removal efficiency was reached in H*, whereas no significant removals were observed in the other tests. No treatments were able to downgrade the classification of the sediment for total PAHs. Figure 4 shows results for light and heavy PAHs. Abatements between 34 and 45% were obtained A*, F, K* and I* for light PAHs. For heavy PAHs, the highest removal efficiencies were achieved in A* (50%) and H* (35%). According to these results, treatment A* exhibited the highest effectiveness for PAHs. Total PCBs in the sediment after the oxidation treatments are shown in Figure 5. No significant differences between SED and the treated samples was observed due to the high standard deviation in results. However, in terms of average value, tests A*, F* and G* resulted in the lowest residual concentration. The highest removal efficiencies (>99%) were achieved in A* for BZ-77, BZ-123, BZ-105, BZ-126, BZ-198, BZ-189, BZ-206, and BZ-209, and in A for BZ-198, BZ-189, BZ-206, and BZ-209. BZ-8 congener concentration increased in all the configurations tested; moreover, PCB chromatograms of the treated samples indicated the presence of unidentified non-PCB chlorinated by-products. These results might be related to free-radical chlorination of alkanes or alkyl-substituted aromatics, as reported in Manion [2000] and Poerschmann et al. [2009]. Actually, the lagoon sediment contains free chlorine atoms and alkanes, and the presence of non-investigated compounds such as phenols, chlorophenols or biphenyl cannot be excluded. In general, tests with tap water resulted in higher removal efficiencies than with deionized water. This might be related to a slower kinetics of iron dissolution, in turn reducing hydroxyl radical scavenging [Watts et al. 1996]. Fe(II) additions did not significantly modify the pollutant removal efficiencies. Time was not a key factor, as no significant difference in the residual pollutant concentration was measured after 6 and 24 hours of treatment in G*, H* and I*. The best results were obtained in A*, in spite of the short contact time (2 h). This test was characterized by strong acidic conditions, which could have heavily modified the solid matrix. The production of unidentified by-products seems to be a critical point in the oxidation treatments, due to their potential toxicity and/or bioavailability.
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mg/kg d.w.
200 150 100 50 0 A*
A
B
C
D
E
F*
F
G*
H*
I*
K*
SED
Figure 2. TPH concentration after oxidation treatments compared to the untreated sample (SED). The horizontal line represents the limit for "class A" sediments according to the Venice protocol. Results for G*, H*, and I* are reported as the mean value after 6 and 24 h, as no significant differences were observed in the values. 140 120 mg/kg d.w.
100 80 60 40 20 0 A*
A
B
C
D
E
F*
F
G*
H*
I*
K*
SED
Figure 3. Total PAH concentration after oxidation treatments compared to the untreated sample (SED). The horizontal line represents the limit for "class C" sediments according to the Venice protocol. Results for G*, H*, and I* are reported as the mean value after 6 and 24 h, as no significant differences were observed in the values. Light PAHs
120
Heavy PAHs
mg/kg d.w.
100 80 60 40 20 0 A*
A
B
C
D
E
F*
F
G*
H*
I*
K*
SED
Figure 4. Light PAH (2- to 3- aromatic rings) and heavy PAH (4- to 6- aromatic rings) concentrations after oxidation treatments compared to the untreated sample (SED). Results for G*, H*, and I* are reported as the mean value after 6 and 24 h, as no significant differences were observed in the values.
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Figure 5. Total PCB concentrations after oxidation treatments compared to the untreated sample (SED). The horizontal line represents the limit for "class B" sediments according to the Venice protocol. Results for G*, H*, and I* are reported as the mean value after 6 and 24 h, as no significant differences were observed in the values.
Gowanus Canal Sediments Figure 6 shows the concentration of total PAHs measured after oxidation compared to the untreated sediment (SED). A significant removal was achieved in all tests. In terms of average abatement, the highest value (54%) was achieved in ACI-1, where the highest amount of oxidizer was used. This trend was observed also in FEN tests (FEN-1 vs. FEN-3 and FEN-5; FEN-2 vs. FEN-4 and FEN-6), but not in SUL tests. In Fenton-like treatments, the addition of Fe(II) improved the average abatement of total PAHs (FEN-1 vs. FEN-2, FEN-3 vs. FEN-4, FEN-5 vs. FEN-6). The liquid to solid ratio did not affect the total PAH removal in any of the systems in which this factor was investigated (FEN-3 vs. FEN-5, FEN4 vs. FEN-6; ACI-2 vs. ACI-3). 1600 1400
mg/kg d.w.
1200 1000 800 600 400 200 0 FEN-1 FEN-2 FEN-3 FEN-4 FEN-5 FEN-6 SUL-1 SUL-2 ACI-1 ACI-2 ACI-3
SED
Figure 6. Concentration of total PAHs at the end of the oxidation tests and in the sediment.
The concentration of light and heavy PAHs is shown in Figure 7. In general, the lowest residual concentrations of light PAHs were observed for the treatments in which the highest amount of oxidizer was used (FEN-1, FEN-2, and ACI-1). No significant difference could be
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pointed out in the residual concentration of light PAHs for the different liquid to solid ratios applied (FEN-3 vs. FEN-5, FEN-4 vs. FEN-6; ACI-2 vs. ACI-3). On the contrary, the residual concentration of heavy PAHs was not significantly affected by the oxidant dosage (FEN-1 vs. FEN-3 and FEN-5; FEN-2 vs. FEN-4 and FEN-6; SUL-1 vs. SUL-2; ACI-1 vs. ACI-2 and ACI-3). Peroxy-acid was the most effective oxidant on heavy PAHs. As reported in Valderrama et al. [2009], light PAHs were better removed than heavy PAHs in all Fentonlike reagent tests and persulfate. Chemical oxidation effectiveness strongly depends on the matrix and the experimental set-up; difference in results between this study and the literature can be ascribed to these factors. The experimental removal efficiencies for Fenton-like reagents and persulfate for Gowanus canal sediment were lower than in Ferrarese et al. [2008], in which the best remediation performance was reported for an oxidant dosage of about 100 mmols for 30 g of sediment. However, the organic carbon in the sediment of Ferrarese et al. [2008] was 190 mg/kg d.w., more than two orders of magnitude lower than in Porto Marghera and Gowanus canal sediments. The abatement in peroxy-acid tests in the present study was close to that reported in Alderman et al. [2007] for the experiment on Bedford LT soil with ratios of hydrogen peroxide to acetic acid and water similar to those used in the present study. The high organic content in the Bedford LT soil (up to three times higher than in the sediment used in the present study) is supposed not to have negatively affected the treatment due to the peroxy-acid selectivity. Anyhow, the measured removal efficiencies for PAHs in this study were consistent with those reported for matrices that were not artificially spiked with contaminant in the laboratory [Brown et al., 2009; Jonsson et al., 2007; Vanderrama et al., 2009]. 1050
Light PAHs
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750 600 450 300 150 0 FEN-1 FEN-2 FEN-3 FEN-4 FEN-5 FEN-6 SUL-1 SUL-2 ACI-1 ACI-2 ACI-3
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Figure 7. Light (2- to 3- aromatic rings) and heavy (4- to 6- aromatic rings) PAHs after oxidation compared to the untreated sediment.
Figure 8 and 9 show metals dissolved in the liquid phase and the pH values after filtration for some selected tests. Negligible quantities of metals were recovered in the liquid phase for Fenton-like tests, except for cadmium in FEN-4 and FEN-6. On the contrary, sediments treated with persulfate and peroxy-acid showed a high amount of metals in the liquid phase, suggesting increase in their leachability. Changes in metal speciation could occur due to pH and redox variations compared to the untreated sediment and from addition or organic compounds that complex metals; in fact, ACI and SUL tests had the lowest pH values at the
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end of treatment. Oxidation of sulphide-metal species may also contribute to mobilize inorganic pollutants [Di Palma, 2005; Sparrevik et al., 2009]. Moreover, organic-based structures in the sediment might degrade when these two oxidants are used, resulting in metal release and dissolved complexing agent formation. These results underline the need of proper control (and treatment before discharge) of the liquid phase at full-scale application. They also underline the potential risk associated with different metal species in the treated sediments, for either leachability or toxicity [Martin et al., 1998]. As
Cd
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% (w./w.) in liquid phase
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FEN-1 FEN-2 FEN-3 FEN-4 FEN-5 FEN-6 SUL-1 SUL-2 ACI-1 ACI-2 ACI-3 SED
Figure 8. Metals in the liquid phase. Percentage is referred to the amount of metal in the untreated sediment. 8 7 6
pH
5 4 3 2 1 0 FEN-1 FEN-2 FEN-3 FEN-4 SUL-1 SUL-2 ACI-1 ACI-2 SED
Figure 9. pH values measured in the liquid phase after filtration.
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Figure 10 shows the SRF values measured in selected tests and Figure 11 shows the residual moisture in the oxidized sediment after the filtration test. Results indicate that the different oxidation treatments did not significantly change the SRF value compared to the filtered untreated sediment. Significant decreases of residual moisture were measured in FEN3, SUL-1 and ACI-1 tests compared to the filtered untreated sediment, but these changes seem too low for practical interest.
SRF (m/kg)
1.00E+13
1.00E+12
1.00E+11
1.00E+10 FEN-1 FEN-2 FEN-3 FEN-4 SUL-1 SUL-2 ACI-1 ACI-2 SED Figure 10. SRF values by filtration tests.
Moisure content (% w./w.)
40 35 30 25 20 15 10 5 0 FEN-1 FEN-2 FEN-3 FEN-4 SUL-1 SUL-2 ACI-1 ACI-2 SED Figure 11. Residual moisture after filtration tests.
Comparison Between the Two Sediments Comparison between results obtained with the two sediments investigated is hard, due to the differences in terms of sediment physical-chemical properties, contamination, and pollutant concentrations, as well as not completely homogeneous test conditions. Tests B and D on Porto Marghera sediments, and FEN-1 and FEN-2 on Gowanus canal sediments are the most similar in treatment conditions. Comparison is reported in Table 8.
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Table 8. PAH results for tests B and D on Porto Marghera sediments and tests FEN-1 and FEN-2 on Gowanus canal sediments.
Tests B D FEN-1 FEN-2
Total PAHs Total PAH (mg/kg d.w.) removal (%) Start End 90 67 26 90 97 0 1340 898 33 1340 718 46
Light PAHs Light PAH (mg/kg d.w.) removal (%) Start End 7 6.3 10 7 9.6 0 523 212 59 523 119 77
Heavy PAHs Heavy PAH (mg/kg d.w.) removal (%) Start End 83 61 27 83 88 0 816 687 16 816 599 27
Based on total PAH removal efficiency, oxidation was more effective on Gowanus canal sediment, despite of the lower amount of oxidizer added (6.7 mmol H2O2/g d.w. Gowanus canal sediment, compared to 16.2 mmol H2O2/g d.w. Porto Marghera sediment). The presence of many different oxidizable chemical species in Porto Marghera sediments has probably limited the efficiency towards PAHs. The removal trend of light PAHs agrees with that of total PAHs. For heavy PAHs, the removal efficiency was higher in test B than in FEN-1, and as equal as in FEN-2. Iron addition improved PAH removal in Gowanus canal tests, but had no effect for Porto Marghera sediments; the lower iron content in the Gowanus canal sediment or different iron species in the sediments could explain this behavior. In addition, the Gowanus canal sediments had significantly higher total PAH concentrations; availability of PAH in easily exchangeable form may be a prerequisite to effective oxidation and excess PAH (i.e. not tightly bound in the sediment matrix) may yield higher degradation in general.
CONCLUSION Chemical oxidation tests resulted in some positive results, but also highlighted some complexities that need further investigation. With Porto Marghera sediments, high removal efficiencies for TPHs were observed in the oxidation experiments (Fenton-like reagents). The majority of the conditions tested downgraded sediment classification for this parameter. On the contrary, changes in the classification were not obtained for PAHs and PCBs. Concerning the investigated process parameters, tap water and strong acidic conditions resulted in the highest pollutant abatement. The addition of Fe2+ did not seem a key factor in gaining better abatements. Unidentified byproducts were found in the oxidized sediments. Tests conducted on Gowanus canal sediments resulted in significant decreases of total PAHs in all the configurations tested. The maximum removal efficiency (54%) was achieved in the peroxy-acid system. The oxidation reactions with persulfate and peroxy-acid resulted in high metal leachability. Based on total PAH removal efficiency, oxidation was more effective on the Gowanus canal sediment, despite the lower amount of oxidizer added. The presence of more types of oxidazable chemical species in Porto Marghera sediments may have limited the efficiency on PAHs, and the significantly higher total PAH burden in the Gowanus canal sediments may have increased the contaminant availability for oxidation. Iron addition improved PAH removal in Gowanus canal tests, but had no effect on Porto Marghera sediments; the lower
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content of iron in the Gowanus canal sediment or different iron species in the sediments could explain this behavior. For ex-situ application, the treatment of water used in the process seems to be mandatory before discharge. Moreover, mineralization of the target organic compounds does not seem certain. Many by-products could be produced, with doubts about toxicity and environmental behavior. Ecotoxicological tests should be performed on the treated material prior to its fullscale use. The use of a bioslurry post-treatment could be a possible step to remove the intermediates or reduce toxicity [Palmroth et al., 2006]. Moreover, the sequential treatment (chemical oxidation + biodegradation) could improve the overall removal of organic pollutants [Kulik et al., 2006; Vanderrama et al., 2009]. No effect of chemical oxidation was observed on specific resistance to filtration in all tests. Small changes occurred on residual moisture in the sediment after filtration for three tests, but the extent of changes were not of practical interest.
ACKNOWLEDGMENTS This work was supported by the Italian Ministry of Education, University and Research (PRIN 2005 Project) and the Cooperative Institute for Coastal and Estuarine Environmental Technology.
REFERENCES Al T.A.; Banks V.; Loomer D.; Parker B.L.; Mayer K.U. J Contam Hydrol 2006, 88, 137152. Alderman N.S.; N‘Guessan A.L.; Nymana M.C. J Hazard Mater 2007, 146, 652-660. APHA; AWWA; WEF Standard Methods for the Examination of Water and Wastewater; XX Ed.; APHA: Washington (DC, USA), 1998. ASTM Annual book of ASTM standards; ASTM International: Philadelphia (PA, USA), 2008. Brown R.A.; Raines D.; Butler W. Proceedings of the Fifth International Conference on Remediation of Contaminated Sediments; Battelle Memorial Institute: Columbus (OH, USA), 2009; paper J-51. Buchman M.F. NOAA Screening Quick Reference Tables. NOAA OR&R Report 08-1; Office of Response and Restoration Division, National Oceanic and Atmospheric Administration: Seattle (WA, USA), 2008; 34 pages. Carlon C.; Marcomini A. In Soil and Sediment Remediation. Mechanisms, technologies and applications; Lens P.; Grotenhuis T.; Malina G.; Tabak H. (eds.); IWA Publishing: London (UK), 2005; pp 478-489. Cassidy D.; Hampton D.; Kohler S. J Chem Technol Biotechnol 2002, 77, 663-670. Charlot G. Analisi chimica qualitativa; Piccin Editore: Padova (IT), 1977. Ciotti C.; Baciocchi R.; Cleriti G.; Chiavola A. Proceedings of CONSOIL 2008: Theme E – Remediation Concepts & Technologies, 2008, pp 24-33.
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Cuypers C.; Grotenhuis T.; Joziasse J.; Rulkens W. Environ Sci Technol 2000, 34, 20572063. Dash S.; Patel S., Mishra B.K. Tetrahedron 2009, 65, 707-739. Di Palma L. In Soil and Sediment Remediation. Mechanisms, technologies and applications; Lens P.; Grotenhuis T.; Malina G.; Tabak H. (eds.); IWA Publishing: London (UK), 2005; pp 200-222. Dubois V.; Zentar R.; Abriak N.E. Proceedings of the International Symposium on Sediment Management; Abriak N.E.; Damidot D.; Zentar R. (eds.); Lille (FR), 2008; pp 429-436. EN 14039, Characterization of waste. Determination of hydrocarbon content in the range of C10 to C40 by gas chromatography, 2004. EN 12766-1, Methods of test for petroleum and its products. Petroleum products and used oils. Determination of PCBs and related products. Separation and determination of selected PCB congeners by gas chromatography (GC) using an electron capture detector (ECD), 2000. EN 15169, Characterization of waste. Determination of loss on ignition in waste, sludge and sediments, 2007. Ferrarese E., Andreottola G., Oprea I.A. J Hazard Mater 2008, 152, 128-139. Greenberg J.; Tomson M. Applied Geochemistry 1992, 7, 85-190 Guangwei Y., Hengyi L., Tao B., Zhong L., Qiang Y., Xianqiang S. J Environ Sci 2009, 21, 877-883. Hakstege A.L. In Sustainable Management of sediment resources. Volume 2: Sediment and Dredged Material Treatment; Bortone G.; Palumbo L. (eds.); Elsevier: Amsterdam (NL), 2007; pp 68-118. Hamer K.; Hakstege P.; Arevalo E. In Soil and Sediment Remediation. Mechanisms, technologies and applications; Lens P.; Grotenhuis T.; Malina G.; Tabak H. (eds.); IWA Publishing: London (UK), 2005; pp 345-369. Haapea P.; Tuhkanen T. J Hazard Mater 2006, 136(2), 244-250. Huling S.G.; Pivetz B.E. In Situ Chemical Oxidation; Engineering Issue Paper, EPA/600/R06/072; United States Environmental Protection Agency: Cincinnati (OH, USA); 2006. ISO 6332, Water quality. Determination of iron. Spectrometric method using 1,10phenanthroline, 1988. ISO 10390, Soil quality. Determination of pH, 2005. Jones K.W.; Stern E.A.; Donato K.R.; Clesceri N.L. Proceedings of the5th International Petroleum Environmental Conference; Albuquerque (NM, USA); 1998. Jonsson S.; Persson Y.; Frankki S.; van Bavel B.; Lundstedt S.; Haglund P.; Tysklind M. J Hazard Mater 2007, 149, 86-96. Kulik N.; Goi A.; Trapido M.; Tuhkanen T. J Environ Manage 2006, 78, 382-391. Levitt J.S.; N‘Guessan A.L.; Rapp K.L.; Nyman M.C. Water Res 2003, 37, 3016-3022. Liang C.; Lee I.L.; Hsu I.Y.; Liang C.P.; Lin Y.L. Chemosphere 2008, 70, 426-435. Manion J. Free-radical chlorination; Jeffers J. (ed.); Neidig H.A. Publisher: Palmyra (PA), 2000, pp 1-12 Martins C.P.S.; Zanardi E.; Buratini S.V.; Lamparelli M.C.; Martins M.C. Water Res 1998, 32(1), 193-199. N‘Guessan A.L.; Carignan T.; Nyman M.C. Environ Sci Technol 2004a, 38, 1554-1560. N‘Guessan A.L.; Levitt J.S.; Nyman M.C. Chemosphere 2004b, 55, 1413-1420.
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O‘Mahony M.M.; Dobson A.D.W.; Barnes J.D.; Singleton I. Chemosphere 2006, 63(2), 307314. Palmroth M.R.T.; Langwaldt J.H.; Aunola T.A.; Goi A.; Puhakka J.A.; Tuhkanen T.A. J Chem Technol Biot 2006, 81, 598-607. Palumbo L. In Sustainable Management of sediment resources. Volume 2: Sediment and Dredged Material Treatment; Bortone G.; Palumbo L. (eds.); Elsevier: Amsterdam (NL), 2007; pp 11-58. Poerschmann J.; Trommler U.; Górecki T.; Kopinkea F.-D. Chemosphere 2009, 75, 772-780 Reis E.; Lodolo A.; Miertus S. Survey Of Sediment Remediation Technologies; International Centre for Science and High Technology, 2007. http://www.ics.trieste.it/Portal/Publication.aspx?id=883 Rivas F.J. J Hazard Mater 2006, 138(2), 234-251. Rulkens W. Reviews in Environmental Science and Bio/Technology 2005, 4, 213-221. Sparrevik M.; Eek E.; Grini R.S. Environ Technol 2009, 30 (8), 831-840. Suthersan S.S.; Payne F.C. In situ remediation engineering; CRC Press: Boca Raton (FL, USA), 2005. ITRC Technical and regulatory guidance for In Situ Chemical Oxidation of contaminated soil and groundwater; 2° ed; The Interstate Technology & Regulatory Council; 2005. U.S. ACE Sediment quality evaluation report Gowanus Canal and bay ecological restoration project. U.S. Army Corps of Engineers: New York (NY, USA); 2004; 37 pages. U.S. EPA Design Manual. Dewatering Municipal Wastewater Sludges; EPA number: 625187014; United States Environmental Protection Agency: Cincinnati (OH, USA); 1987. U.S. EPA The Incidence and Severity of Sediment Contamination in Surface Waters of the United States, National Sediment Quality Survey: Second Edition; EPA-823-R-04-007; United States Environmental Protection Agency: Washington (DC, USA); 2004. U.S. EPA Contaminated Sediment Remediation Guidance for Hazardous Waste Sites; EPA540-R-05-012. United States Environmental Protection Agency: Washington (DC, USA); 2005. U.S. EPA Test Methods for Evaluating Solid Waste, Physical/Chemical Methods; SW-846; United States Environmental Protection Agency: Washington (DC, USA); 2007. http://www.epa.gov/epawaste/hazard/testmethods/sw846/online/index.htm Valderrama C., Alessandri R., Aunola T., Cortina J.L., Gamisans X., Tuhkanen T. J Hazard Mater 2009, 166 (2-3), 594-602 . Wargo J.L. New York/ New Jersey Harbor: Alternative Methods for Ex-Situ Sediment Decontamination and Environmental Manufacturing; Report prepared for U.S. Environmental Protection Agency; Washington (DC, USA); 2002. Watts R.J.; Dilly S.E. Journal of Hazardous Materials 1996, 31, 209-224
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 301-332 © 2011 Nova Science Publishers, Inc.
Chapter 10
RECONSTRUCTION OF THE EUTROPHICATION IN THE GULF OF FINLAND USING A DYNAMIC PROCESS-BASED MASS-BALANCE MODEL Lars Håkanson* Dept. of Earth Sciences, Uppsala University, Uppsala, Sweden
ABSTRACT The Gulf of Finland is a large bay in the Baltic Sea where major changes have taken place during the last 100 years. The Secchi depth has, for example, decreased from more than 7 m to about 5 m. The basic aim of this work has been to try to reconstruct the development that has taken place in this bay during the last 100 years. Since the conditions in the Gulf of Finland depend very much on both the river input of nutrients directly to the bay and the exchange of nutrients and water between the bay and the Baltic Proper, this work has focused on such interactions. The work describes how a general process-based mass-balance model (CoastMab) has been applied for the Baltic Proper and the Gulf of Finland. The model has previously been extensively tested and validated for phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the monthly transport processes (sedimentation, resuspension, diffusion, missing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural changes and anthropogenic reductions of water pollutants. The results presented in this work indicate that it is possible to remediate the Gulf of Finland and the Baltic Proper to the conditions that characterized the system 100 years ago. About 7000 tons of phosphorus (including 1800 tons from the tributaries to the Gulf of Finland) must then be removed on an annual basis from the present annual tributary load of about 30000 tons to the Baltic Proper. The *
Corresponding author: E-mail: [email protected], Fax: +46-18-471-2737, Phone: +46-18-471-3897.
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Lars Håkanson trophic conditions in the Baltic Proper have varied relatively little during the last 25-30 years. The most marked changes in Secchi depth in the Gulf of Finland took place between 1920 and 1980.
Keywords: coastal waters; nutrients; eutrophication; Baltic Sea; Gulf of Finland; massbalance modeling; Secchi depth; chlorophyll, cyanobacteria.
1. INTRODUCTION AND AIM The conditions in the Baltic Sea, and specifically in the Baltic Proper and the Gulf of Finland, have been discussed in many papers and books (see recent compilations by Pitkänen and Tallberg, 2007; and also Ambio, 2001, 2007; Schernewski and Schiewer, 2002; Schernewski and Neumann, 2005; Wulff et al., 2001). The aim of this work is to focus on the conditions in the Gulf of Finland, since this is one of most heavily eutrophicated, major subbasins in the Baltic Sea (see Figure 1 and the HELCOM website), and to try to reconstruct the development that has taken place in this bay between the years 1900 and 2000. The eutrophication in the Gulf of Finland has been discussed in many papers and reports (see, e.g., Kiirikki et al., 2001; SYKE, 2003, 2006; HELCOM, 2006). Since the Gulf of Finland is open to the Baltic Proper, the conditions in the Baltic Proper will influence the conditions in the Gulf of Finland beside the direct discharges to the Gulf (see, e.g., Savchuk and Wulff, 1999).
Figure 1. Average annual Secchi depths in the Baltic Sea and parts of the North Sea in the upper 10 m water column based on HELCOM data for the period from 1990 to 2005 (from Lindgren and Håkanson, 2007)
The main objective of this work can be illustrated by the data on Secchi depth given in Figure 2 (see also Aarup, 2002). These data come from the HELCOM database and concern
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how the water clarity (the Secchi depth) has changed in the period from 1900 to 1991. An initial trend analysis, a linear regression between measured Secchi depths and time (month 1 is January of 1900), indicates the negative development: The Secchi depth has decreased from about 7-8 m 100 years ago to about 5 m today. One can also note the large scatter in the data from the individual sampling sites. The aim of this work is to try to explain the development shown in Figure 2 by using: 1. a process-based dynamic mass-balance model for salt (CoastMab for salt; see Håkanson et al., 2007) to get realistic and reliable data on the water fluxes to, within and from the Gulf of Finland; 2. a process-based dynamic mass-balance model for phosphorus (CoastMab for phosphorus; see Håkanson and Eklund, 2007a; Håkanson and Bryhn, 2007a) to quantify how the system would react to changes in nutrient loading; 3. linked to the mass-balance model for phosphorus, there are empirically-based submodels for Secchi depth, chlorophyll-a concentration, concentration of cyanobacteria, sedimentation, total nitrogen and suspended particulate matter (which will be discussed later); and 4. linked to these models, there is also a more comprehensive dynamic foodweb model for 10 functional groups (CoastWeb, see Håkanson and Gyllenhammar, 2005; Håkanson and Bryhn, 2007b; Håkanson and Lindgren, 2007), which is used in this work to calculate biouptake and retention of phosphorus in biota. The CoastMab-model has previously been extensively tested and validated for phosphorus from over 20 different coastal areas and more than 40 lakes, for suspended particulate matter in over 20 coastal areas and more than 10 lakes and for toxic substances (radionuclides and metals) in several lakes and coastal areas.
Figure 2. HELCOM data on the Secchi depth in the Gulf of Finland 1990 to 1991 and a trend analysis; regression line, coefficient of determination (r2), number of data (n) and statistical certainty (p)
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The basic idea is to demonstrate (A) how this modeling works and how well modeled phosphorus concentrations, Secchi depths and chlorophyll values agree to empirical data, (B) how reductions in nutrient loading to the Gulf of Finland and to the Baltic Proper would influence the conditions for these target variables in the Gulf of Finland, and (C) how a reconstruction of the development could be made so the that the changes in the Gulf of Finland shown by the data in Figure 2 may be explained and understood. This would also imply that important information to reverse the development in the Gulf of Finland and the Baltic Proper could be gained. To reduce nutrient inputs from urban areas, industries, catchments or diffuse sources involves complex and often expensive remedial measures (see, e.g., Nixon, 1990; Moldan and Billharz, 1997; Livingston, 2001; Bortone, 2005). A central question is then how a given system would respond to the suggested measures? How long would it take to reach a new steady state? What are the characteristic new nutrient concentrations in the water? How would key bioindicators for eutrophication, such as chlorophyll-a concentration, concentration of cyanobacteria or Secchi depth change? In short, what is the environmental benefit related to the remedial costs? To address such questions, two important issues must be dealt with: 1. A validated process-based dynamic model, which has proven to predict the target variables well, must be at hand to provide realistic values for the dynamic (timedependent) response of a reduced nutrient loading since this can not generally be done by static empirical regression models? One aim of this work is to use such a dynamic model, the CoastMab-model. This model has been presented and critically tested with good results for many aquatic systems (see Håkanson and Eklund, 2007a) and it will be used in this work for the Gulf of Finland and also for the Baltic Proper, since the condition in the Baltic Proper influence the Gulf of Finland very much. 2. The dynamic model must quantify all important fluxes to, within and from the system and include information on the natural load and the anthropogenic load and, preferably also, information on how much of the anthropogenic load from different sources that can, realistically, be reduced. An important reason for selecting the Gulf of Finland as a case-study is that for this bay the author can access the necessary data: First, data on the salinity inside and outside the bay, and the tributary water fluxes to the bay, must be available so that a reliable mass-balance for salt can be established, so that the water exchange with the outside sea (the Baltic Proper) can be quantified realistically and also the theoretical water retention time in the bay, which influence important internal processes, such as stratification, mixing and diffusion. The CoastMab-model also includes a mass-balance model for salt structured in the same way as the model for phosphorus except that the mass-balance model for phosphorus also calculates sedimentation, resuspension, burial and biouptake of dissolved phosphorus. By definition, total phosphorus (TP) in the water generally includes living and dead plankton, but not larger animals such as zoobenthos and fish. A new aspect of this version of the CoastMab-model (as compared to the basic version from Håkanson and Eklund, 2007a) is that this model calculates phosphorus uptake and retention in biota with short turnover times (phytoplankton, bacterioplankton, herbivorous zooplankton and benthic algae) and long turnover times (predatory
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zooplankton, prey and predatory fish, macrophytes, zoobenthos and jellyfish) using the CoastWeb-model. Second, data on the TP-concentration in the water outside the bay must be at hand so that the inflow from the Baltic Proper can be calculated. Data on the TP-transport from different sources on land are also needed and such data are available for the Gulf of Finland from the HELCOM data base. HELCOM also gives information on the natural background losses, the diffuse losses and the point sources discharges of TP to the Gulf of Finland and from this one can use the CoastMab-model to estimate how various reductions in the anthropogenic load would influence the system. This is essential information for the reconstruction requested in this work. Even though the focus is on the changes in Secchi depth, this work will also discuss changes in other bioindicators of eutrophication, mainly the chlorophyll-a concentration, as a standard measure of phytoplankton biomass, and the concentration of cyanobacteria, as a measure of the mass of ―harmful‖ algae.
2. DATA FROM THE GULF OF FINLAND AND INFORMATION ON THE MODEL STRUCTURE 2.1. Data and Methods Figure 1 shows that the Gulf of Finland today generally has a relatively low Secchi depth compared to other basins in the Baltic Sea. Table 1 gives background data from the Gulf of Finland and the Baltic Proper and shows that the limiting section area towards the Baltic Proper is 3.74 km2. This means that the Gulf of Finland is quite open to the Baltic Proper. Table 1 also gives information on, e.g., total area, volume, mean depth, maximum depth, the depth of the theoretical wave base. Table 2 gives data on the volume of the surface-water layer and the middle-water layer separated by the theoretical wave base and the deep-water layer separated from the middle-water layer by the depth of the average halocline. The annual fresh-water flux to Gulf of Finland used in this work is the average annual value from Savchuk (2000; 3552 m3/s), Myrberg (1998; 3615 m3/s) and Stålnacke et al. (1999; 3875; m3/s). The monthly data on water discharge used in the modeling have been calculated from the average annual value using the dimensionless moderator for this purpose (from Abrahamsson and Håkanson, 1998). This moderator is based on data on the size of the catchment area, mean annual precipitation and latitude (see table 1). Since the author does not have access to reliable monthly data on water discharge for the study period (1990 to 1998), it should be stressed that this modeling concerns average, characteristic conditions on a monthly base for this period of time and not the actual sequence of months. The results from 19901998 concerning the processes and fluxes will then be put into a wider time frame (1990 to 2000).
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Area Max. depth Volume Mean depth Wave base Section area Halocline depth ET-areas Water discharge Catchment area Latitude Precipitation
(km2) (m) (km3) (m) (m) (km2) (m) (%) (km3/yr) (km2) (°N) (mm/yr)
Gulf of Finland (GF) 29600 105 1073.2 36.3 41 3.74 75 63 29.0 421000 60 593
Baltic Proper (BP) 211100 459 13054.6 61.8 43.8 75 47 250 568973 58 750
Table 2. Data on volumes and areas (below the given depths) based on new hypsographic curves (from Håkanson and Lindgren, 2007) Basin
Level
Gulf of Finland
SW MW DW SW MW DW
Baltic Proper
Volume (km3) 851.2 202.0 20.0 7315 3050 2690
Area below the given level (km2) 29600 10900 2400 211100 123500 73000
Also note that the values presented in this work relate to the definitions of the surfacewater, the middle-water and the deep-water layers, the given time period (1990 to 1998) and the given hypsographic curves (from Håkanson and Lindgren, 2007). This means that although these data correspond quite well with other values (see, e.g., Voipio, 1981; Mikulski, 1985; Monitor, 1988), they are not directly comparable. The theoretical wave base is defined from the ETA-diagram (erosion-transportaccumulation; from Håkanson, 1977), which gives the relationship between the effective fetch, as an indicator of the free water surface over which the winds can influence the wave characteristics (speed, height, length and orbital velocity). The theoretical wave base separates the transportation areas (T), with discontinuous sedimentation of fine materials, from the accumulation areas (A), with continuous sedimentation of fine suspended particles. The theoretical wave base (Dwb in m) is at a water depth of 41 m in the Gulf of Finland. This is calculated from eq. 1 (A = area in km2): Dwb= (45.7·√A)/(√A+21.4)
(1)
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This approach gives one value for the theoretical wave base related to the area of the system. So, the Gulf of Finland has been divided into three depth intervals: 1. The surface-water layer (SW), i.e., the water above the theoretical wave base at 41 m. 2. The middle-water layer (MW) between the theoretical wave base and the average depth of the halocline at 75 m. 3. The deep-water layer (DW) is defined as the volume of water beneath the average depth of the halocline at 75 m. It should be noted that the theoretical wave base describes average conditions. The actual wave base varies around 41 m. During storm events, the wave base will be at greater water depths (see Jönsson, 2005) and during calm periods at shallower depths. Håkanson and Lindgren (2007) have presented new hypsographic curves for the Gulf of Finland calculated using GIS (Geographical Information System) and bathymetric data provided by Seifert et al. (2001). Those values have been used in these calculations. One can note from table 2 that the area below the theoretical wave base (Dwb) at 41 m is 10900 km2 and that the volumes of the SW, MW and DW-layers are 851.2, 202.0 and 20.0 km3 and the entire volume is 1073.2 km3. The Gulf of Finland is also relatively shallow and 63% of its bottom area is dominated by resuspension processes of fine materials (these are the erosion and transportation areas, ET; as calculated by the CoastMab-model; see table 1). Figure 3 illustrates the number of sampling sites for the Secchi depth data from the HELCOM data base used in this work. Empirical data on salinities, Secchi depth, chlorophyll and nutrient concentrations will be given later and compared to modeled values. There are no corresponding empirical data on cyanobacteria available to the author from the Gulf of Finland. The empirical temperature data from the HELCOM data base (from 1990 to 1998) have been used to model stratification and mixing. The standard deviations (SD) for the monthly mean empirical values are very important in the sense that the variables with the high inherent SD-values cannot be expected to be predicted as well as variables with comparatively low SD-values (such as salinity).
Figure 3. Sampling sites for Secchi depth in the Gulf of Finland (from HELCOM)
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Table 3. Calculated monthly values for the theoretical SW, MW and DW water retention times (TSW, TMW and TDW), the water fluxes (Q) from the Baltic Proper (BP) to the Gulf of Finland (GF) in the three layers (SW, MW and DW), the mixing transport (abbreviated with an x) between the MW and SW and the DW and MW layers and the water velocity in the section area (uAt) from the mass-balance model for salt. These values are used in the mass-balance model for phosphorus Mont h 1 2 3 4 5 6 7 8 9 10 11 12
TSW
TMW
TDW
QSWBPGF
QMWBPGF
QDWBPGF
QMWSWx
QDWMWx
uAt
months 8.6 8.6 8.7 8.6 8.1 8.1 8.0 7.8 10.3 10.4 8.5 8.2
months 7.6 7.8 7.8 7.5 6.6 6.8 6.1 5.5 19.0 20.4 7.1 6.3
months 2.5 2.6 2.5 2.5 2.7 2.8 2.5 2.4 2.7 2.7 2.4 2.4
km3/month 69.6 68.4 69.5 69.8 63.5 60.6 67.7 69.5 70.6 70.6 71.7 70.5
km3/month 7.1 7.0 7.1 7.1 6.5 6.2 6.9 7.1 7.2 7.2 7.3 7.2
km3/month 7.1 7.0 7.1 7.1 6.5 6.2 6.9 7.1 7.2 7.2 7.3 7.2
km3/month 19.5 18.8 18.8 19.8 23.9 23.7 26.2 29.7 3.4 2.6 21.0 24.6
km3/month 0.8 0.7 0.8 0.8 1.0 1.0 1.1 1.2 0.1 0.1 0.9 1.0
cm/s 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0
2.2. The Dynamic Coastmab-Model The model consists of seven compartments: surface water (SW), middle water (MW), deep water (DW), erosion/transportation areas for fine sediments (ET-areas), accumulation areas for fine sediments below the theoretical wave base (A-areas), biota with short turnover times (BS) and biota with long turnover times (BL). There are algorithms for all major internal TP-fluxes (outflow, TP from land uplift, sedimentation, resuspension, diffusion, mixing, biouptake and retention in biota and burial; see Håkanson and Eklund, 2007a, for a more detailed model description). To calculate the inflow of TP to the Gulf of Finland (GF) from the Baltic Proper (BP), modeled data on the TP-concentrations in the surface, middle and deep-water layers in the Baltic Proper from Håkanson and Bryhn (2007a) have been used. The water fluxes between the Gulf of Riga and the Baltic Proper are calculated from the mass-balance for salt. So, the inflows to the three layers (SW, MW and DW) from the Baltic Proper are given by the water discharges in table 3 (QSWBPGR, QDWBPGR and QDWBPGR) and the modeled TP-concentrations. The transport of TP from the catchment area to the Gulf of Finland uses data from HELCOM: 1191 t TP/yr from natural background losses, 2112 t TP/yr from diffuse losses and 2431 t TP/yr from point source discharges. These annual TP-fluxes have been transformed into monthly values by division with 12 and by applying a seasonal moderator for water discharge (characteristic mean monthly Q-values divided by the annual mean water discharge). From extensive measurements in many coastal areas (see Håkanson et al., 1986), one can conclude that typical water velocities in limiting section areas range between 0.5 and 20 cm/s for coastal areas in the Baltic Sea. Lower velocities that 0.5 cm/s would be rather unrealistic on a monthly or annual basis. Typical velocities in the coastal jet zone in the Baltic Sea are in
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the range 15-25 cm/s (see FRP, 1978). The water velocity in the section area has been calculated for the total outflow (km3/yr) divided by half the section area since there is also inflow of water to maintain a given water level ((km3/yr)·(1/(0.5·km2). Savchuk (2006) gave a total water outflow from the Gulf of Finland of 554 km3/yr, which is a factor of 2 lower than the value obtained in this work (990 km3/yr) and 554 seems a less likely value since it would imply that the average water velocity in the section area would be lower than 1 cm/s. These calculations give an average velocity in the section area of 1.9 cm/s. Some key questions for this work are: How will the system react if the diffuse losses and the point source discharges of TP to the Gulf are reduced? How would the system respond if similar reductions to the entire Baltic Proper are also done? To calculate the changes in the concentrations of TP in the SW, MW and DW-layers, the CoastMab-model has also been applied to the entire Baltic Proper (see Håkanson and Bryhn, 2007a). The theoretical water retention times in the three layers (see table 3) from the basic massbalance for salt are used together with the temperature dependent mixing rate in the massbalance model as indicators of how the turbulent mixing influences the settling velocity for particulate phosphorus – the faster the water renewal, the more turbulence, the slower the settling velocity. The small TP-input from precipitation onto the water surface of the Gulf of Finland has been estimated from the characteristic annual precipitation of 593 mm and a TPconcentration in the rain of 5 µg/l (see Håkanson and Eklund, 2007a). The internal processes are: sedimentation of particulate phosphorus from surface water to middle water and deep water (FSWMW and FSWDW), sedimentation from the SW-layer to areas of erosion and transportation (FSWET), sedimentation from the MW and DW-layers to the respective accumulation areas (FMWAMW and FDWADW), resuspension (advection) from ETareas (including TP from land uplift, FLU) either back to the surface water (FETSW) or to the middle water (FETMW), diffusion of dissolved phosphorus from accumulation area sediments in the MW and DW-layers to water in the MW and DW-layers (FAMWMW and FADWDW), diffusion from MW and DW-water layers to the SW and MW-layers, respectively (FMWSWd and FDWMWd), upward and downward mixing between the water layers (FSWMWx, FMWSWx, FDWMWx and FMWDWx) and biouptake and elimination of phosphorus from biota with short and long turnover times (FbioupBS and FretbioBS and FbioupBL and FretbioBL). When there is a partitioning of a flux from one compartment to two compartments, this is handled by a distribution coefficient (DC). 1. The DCs regulating the amount of phosphorus in particulate and dissolved fractions in the SW, MW and DW-layers. These DCs are called particulate fractions (PF). By definition, only the particulate fraction of a substance is subject to gravitational sedimentation and only the dissolved fraction (DF = 1 – PF) may be taken up by biota. 2. The DC regulating sedimentation of particulate phosphorus either to areas of fine sediment erosion and transport (FSWET) or to the areas beneath the theoretical wave base (FSWMW). The ET-value is 0.63 (i.e., 63% of the total area should function as areas of fine sediment erosion and transport). 3. The DC describing the resuspension flux from ET-areas back either to the surface water (FETSW) or to the MW-compartment (FETMW), as regulated by the form factor (Vd, where DC=Vd/3, Vd = 3·Dm/Dmax, Dm = the mean depth, Dmax = the maximum depth).
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Lars Håkanson 4. The DC describing how much of the TP in the water that has been resuspended (DCres) and how much that has never been deposited and resuspended (1-DCres) in the layers. The resuspended fraction settles out faster than the materials that have not been deposited.
Land uplift (FLU) is a special case. Land uplift is a main contributor of TP to the Baltic Proper (Håkanson and Bryhn, 2007a). From the map illustrating the spatial variation in land uplift (see Voipio, 1981), one can estimate that the mean land uplift in the Gulf of Finland is about 1.2 mm/yr and this value has been used in these calculations. Land uplift has been discussed in many contexts (Voipio, 1981; Jonsson et al., 1990; Jonsson, 1992) and the algorithm to quantify how land uplift influences the concentration of TP has been given by Håkanson and Bryhn (2007a). The total area above the theoretical wave base in the Gulf of Finland is about 18700 km2 and the sediments in this area will be exposed to increased erosion by wind/wave action due to land uplift. The sediments in the shallower parts, which may have been deposited more than 1000 years ago, will be more consolidated than the recent materials close to the theoretical wave base. The calculation of the TP-flux from land uplift uses (1) modeled data on the TP-concentration in the accumulation area sediments from the MW-zone, (2) a water content of the sediments exposed to increased erosion set to be 15% lower than the modeled water content of the recent sediments and (3) the total volume of sediments above the theoretical wave base lifted each year.
2.3. Regressions between Modeled TP-Values versus Total-N and Bioindicators The Secchi depth (Sec in m) is a target bioindicator in this study and it is calculated from a model illustrated in Figure 4 relating Secchi depth to the concentration of suspended particulate matter in the SW-layer (SPMSW in mg/l) and the salinity of the SW-layer (SalSW) according to eq. 2 (from Håkanson, 2006). SPMSW = 10^(-0.3-2·(log(Sec)-(10^(0.15·log (1+SalSW)+0.3)-1))/((10^(0.15·log(1+ SalSW)+0.3)-1)+0.5))
(2)
One can note from Figure 4 that for the Gulf of Finland with a SW-salinity of about 6 psu, one should expect a fairly rapid (non-linear) improvement in Secchi depths if the SPMconcentration is lowered from 4 to 3 mg/l. SPMSW, in turn, is calculated from dynamically modeled TP-concentrations in the SW-layer using the following regression (from Håkanson and Bryhn, 2007b): SPM = 0.0235·TP1.56 (r2 = 0.895; n = 51)
(3)
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Figure 4. The relationship between Secchi depth, concentration of suspended particulate matter (SPM) and the surface-water salinity (from Håkanson, 2006)
Eq. 3 will translate modeled TP (in µg/l) into SPM-values (in mg/l) and together with modeled data on the salinity, translate those values into Secchi depths using eq. 2. The Secchi depth is important for predictions not just of water clarity and the depth of the photic zone but also of, e.g., macrophyte cover and biomass of benthic algae using the CoastWeb-model. It should be noted that eq. 3 is based on data from systems with salinities ≤ 15‰. This means that it may provide more limited predictive power for coastal systems with salinities ≥ 15‰. In this work, mean concentrations of chlorophyll-a (Chl in µg/l) for the growing season are first predicted from modeled TP-concentrations and from modeled SW-salinities using an approach presented by Håkanson and Eklund (2007b). In this work, the modeling is done on a monthly basis and in the CoastMab-model there is information on the dissolved fraction of phosphorus. This mean that the basic approach for the mean conditions during the growing season (ChlGS in µg/l) has been modified to predict the requested mean monthly chlorophyll values (Chl). These calculations use simple dimensionless moderators to account for seasonal/monthly changes in the light conditions (DayL; mean monthly number of hours with daylight in the Gulf of Finland; from standard tables) and in the amount of bioavailable/dissolved phosphorus (DFSW). This means the chlorophyll-a concentration are predicted from: Chl = (DayL/12.3)·(DFSW/0.44)·ChlGS
(4)
Where the basic model between the TP-concentration in the SW-layer (TPSW in µg/l, modeled), the salinity in the SW-layer (SalSW, modeled) and ChlGS is shown in Figure 5. (DayL/12.3) is a dimensionless moderator based on the ratio between the monthly DayLvalues divided by the mean annual number of hours with daylight (12.3) in the Gulf of Finland. The modeled monthly values of the dissolved fraction in the SW-layer (DFSW) have been transformed into a dimensionless moderator by division with the average DF-value of 0.44 for phosphorus in surface water conditions (see Håkanson, 2006). This means that the
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predicted chlorophyll-values are low if the DF is low, the number of hours with daylight low and the modeled TP-values low. The small variations in salinity (see table 4) will not influence the predicted Chl-values very much, but such variations are also accounted for. Table 4. A comparison between measured (empirical; data from HELCOM for 1990 to 1998) data and modeled values on the salinity in the SW, MW and DW-layers in the Gulf of Finland. Note that there are no reliable mean monthly data accessible from the MW and DW-layers and the data given for these layers (7.0 and 10.0) should be regarded as the “best possible” estimates based on few and scattered data from the Gulf of Finland and from the area of the Baltic Proper outside the Gulf of Finland Month
1 2 3 4 5 6 7 8 9 10 11 12 Mean Median SD for emp Diff. 1 2 3 4 5 6 7 8 9 10 11 12 Mean diff. SD for diff.
SalSW psu mod 6.20 6.20 6.20 6.21 6.19 6.14 6.10 6.12 6.13 6.14 6.16 6.19 6.17 6.18
0.33 0.05 -0.17 -0.11 -0.11 -0.10 -0.30 -0.02 -0.25 -0.39 0.01 0.39 -0.06 0.23
SalSW psu emp 5.87 6.15 6.37 6.32 6.30 6.24 6.40 6.14 6.38 6.53 6.15 5.80 6.22 6.27
SalMW psu mod 6.91 6.91 6.91 6.92 6.91 6.88 6.86 6.84 6.84 6.89 6.91 6.91 6.89 6.91 0.22 -0.09 -0.09 -0.09 -0.08 -0.09 -0.12 -0.14 -0.16 -0.16 -0.11 -0.09 -0.09 -0.11 0.03
SalMW psu emp 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00
SalDW psu mod 10.10 10.09 10.09 10.08 10.06 10.01 9.98 9.95 9.99 10.11 10.14 10.10 10.06 10.09 0.00 0.10 0.09 0.09 0.08 0.06 0.01 -0.02 -0.05 -0.01 0.11 0.14 0.10 0.06 0.06
SalDW psu emp 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 0.00
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Figure 5. Illustration of the model for how salinity influences the Chl/TP-ratio (the Ysal-moderator) and the equations (from Håkanson and Eklund, 2007b)
Figure 6. Outline of the model to predict median summer values of cyanobacteria from total phosphorus, total nitrogen, salinity and surface-water temperatures. From Håkanson et al. (2007b)
The empirically-based model to predict the total concentration of cyanobacteria (Håkanson et al., 2007b) is given in Figure 6. The following simulations will use dynamically
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modeled monthly TP-concentrations in the SW-layer, empirical mean monthly SWtemperatures, dynamically modeled SW-salinities and modeled monthly TN-concentrations in the SW-layer (see eq. 5) to predict monthly values of cyanobacteria in the SW-layer. Note that there are no empirical data available to the author to test the predicted values for cyanobacteria, but these values are basically predicted from an empirical approach which yielded an r2-value of 0.78 (coefficient of determination), which is close to the maximum possible predictive power for cyanobacteria because of the inherently very high coefficient of variation (CV) for cyanobacteria (see Håkanson et al., 2007b). Nitrogen fixation by cyanobacteria counteracts long-term nitrogen deficits, and the N-fixation rate depends on the TP-concentration, water temperature and the TN/TP-ratio (see Figure 6). The mechanisms showing that phosphorus is generally the long-term controlling nutrient for the primary production were first demonstrated in whole-lake experiments by Schindler (1977, 1978). The same mechanisms have also been used to explain primary production and nutrient concentrations in the Baltic Proper, e.g., in modeling work by Savchuk and Wulff (1999), and have been tested globally by Tyrrell (1999) (see also Hecky and Kilham, 1988; Howarth, 1988; Guildford and Hecky. 2000). However, these results demonstrating the role of phosphorus as a long-term limiting nutrient have not yet been rooted in management policies for the Baltic Sea. Reductions of nitrogen favor the production of cyanobacteria. It is well established (Redfield, 1958; Redfield et al., 1963) that plankton cells have a typical atomic composition of C106N16P, which means that 16 times as many atoms (and 7.2 times as many grams) are needed of N than of P to produce phytoplankton. This means that one generally finds a marked co-variation between phosphorus and nitrogen concentrations in aquatic systems (see Wallin et al., 1992) and in this work total nitrogen (TN) concentrations have been predicted from dynamically modeled monthly TP-concentrations using a regression from Håkanson and Eklund, 2007b): log(TN) = 0.70·log(TP) + 1.61 (r2 = 0.88; n = 58 coastal systems)
(5)
The following section will demonstrate how this modeling predicts first the salinities in the three layers, then the TP-concentrations, Secchi depths, cyanobacteria and nitrogen and also other variables of interest, such as TP-concentrations in sediments (0-10 cm) below the theoretical wave base (the accumulation-area sediments) in the MW and DW-zones, sedimentation in the three layers, settling velocities for particulate phosphorus (and suspended particulate matter) and the dissolved fractions of phosphorus in the three layers (and hence also the particulate fractions, PF = 1-DF). Whenever possible, the modeled values will be compared to empirical data and to the uncertainty bands related to the empirical data and all calculated TP-fluxes in the Gulf of Finland and all calculated TP-amounts (= where would one find the TP?)
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3. RESULTS 3.1. Modeled Values versus Empirical Data Table 4 gives modeled values for the salinity compared to the mean empirical monthly data for the period 1990 to 1998 and also to the standard deviations (SD) for the mean empirical values. If the model yields values close to the empirical mean values and inbetween the uncertainty bands given by ± one standard deviation, the predictions should be regarded as good. For all these comparisons between modeled and empirical data, it should be noted that: The monthly inflows of water and phosphorus have not been calculated using data for this period of time (1990-1998) but using a general model for water discharge (see Abrahamsson and Håkanson, 1998). This will explains some of the differences between the modeled and the measures monthly values for salinity, TP and other variables. The monthly calculations of the inflow of water, salt and phosphorus from the Baltic Proper use mean values for the SW and MW-compartments not in the inflowing water from the area just outside the Gulf of Finland, which would have been more appropriate, but for the entire Baltic Proper. For the inflow to the DW-compartment, a value of 70.9 µg TP/l (from Karlsson, 2007) has been used. The reason why the more appropriate data have not been used is simply that it has been difficult to find such data. This likely also further explains some of the differences between the modeled and the measured monthly values. With these reservations, one can note from table 4 that the predicted monthly salinities in the SW-layer are generally close to the empirical data and within the defined uncertainty bands of the empirical data (± 1SD = 0.22). The average error (the mean difference for the 12 months) is 0.02 psu. It should be noted that the available data from the MW and DW-layers are few and the values 7 and 10 for the two layers are uncertain. The CoastMab-model gives a value of 6.75 psu for the mean salinity in the MW-layer and of 10.02 psu in the DW-layer. The water fluxes between the Gulf of Finland and the Baltic Proper calculated from the massbalance model for salt and the corresponding fluxes for mixing and for molecular diffusion are used without any changes also in the mass-balance calculations for phosphorus, except, of course, that phosphorus has a particulate fraction. The main message here is that there should be no ―tuning‖ of the mass-balance calculations and the same algorithms and values have been used for mixing, diffusion and water fluxes for salt and phosphorus. There are substance-specific parts in the CoastMab-model and they mainly concern the algorithms for the particulate fraction and for diffusion. The results for phosphorus are given in table 5. (A) The TP-concentrations in the SW-layer are generally close to the empirical data and (mean difference 0.5 and median difference 0.2 µg/l) well within the uncertainty bands of the empirical data (±1SD).
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Lars Håkanson (B) Also the average TP-concentrations in the MW-layer are close to the empirical average value (the mean difference between the mean values is 2.9 µg/l), which is a small difference compared to the relatively high standard deviation for the empirical data (18.6 µg/l). (B) The average TP-concentrations in the DW-layer differ more (mean difference 25.4) but also this is close to the inherent uncertainty in the empirical data (SD = 22.0 µg/l). (C and D) The target variables, the two bioindicators Secchi depth and chlorophyll-a concentration in the SW-layer, are close to the empirical values (the mean error for Secchi depth is 0.2 m and for chlorophyll 2.3 µg/l) and within the uncertainty bands defined by one standard deviation of the empirical mean value. The modeled chlorophyll concentrations also give the ―twin-peak pattern‖ as indicated by the empirical data. It should be stressed that the chlorophyll concentrations are predicted from a regression including dynamically modeled TP-concentrations in the surface water and a dimensionless moderator for the light conditions (eq. 4) and the calculated dissolved fraction of phosphorus. These calculations also include considerations to the biouptake of dissolved phosphorus in all types of biota (functional groups) included in the CoastWeb-model. However, the temporal patterns are calculated in the standardized pattern to reveal the most typical, characteristic condition in the Gulf of Finland, and the given presuppositions including the relatively high uncertainties in the empirical data, one cannot hope to obtain very much better predictions than these. (F) The TN-concentrations are predicted from a simple regression using dynamically modeled TP-concentrations in the SW-compartment. There is a relatively good correspondence between modeled and measured TN-concentrations (the mean error is 1.3 µg/l).
The TN/TP-ratios based on modeled values, modeled salinities in the SW-layer and empirical temperature data for the SW-layer will be used to calculate the concentration of cyanobacteria (see later). From this, one can conclude that the model predicts the target variables quite well given the factual limitations in the seasonal patterns in the driving variables for tributary water discharge (since this pattern in the modeling is not based on measured data for the modeled period) and in the seasonal pattern for the TP-concentrations outside the Gulf of Finland (since these data for the SW and MW-layers emanate not from the area outside of the Gulf but from the entire Baltic Proper and since the empirical value for the TP-concentration in the Baltic Proper outside the Gulf of Finland is uncertain). Note that there has been no tuning of the model to achieve these predictions and that the basic model has been shown to describe the transport processes for phosphorus very well for many other coastal areas (see Håkanson and Eklund, 2007a). This should lend some credibility to the following simulations.
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Table 5. A comparison between empirical data (data from HELCOM from 1990 to 1998) and modeled values on TP-concentrations, Secchi depths, chlorophyll-a concentrations and total-N concentrations (TN) in the three layers (SW, MW and DW) in the Gulf of Finland. The lower part of the table gives the differences between modeled and measured values Month
1 2 3 4 5 6 7 8 9 10 11 12 Mean Median SD for emp. Diff. 1 2 3 4 5 6 7 8 9 10 11 12 Mean diff. Median diff. SD for diff.
TPSW µg/l mod 23.0 24.0 24.8 25.3 25.6 26.5 26.8 27.0 25.6 22.7 21.2 22.1 24.5 25.1
TPSW µg/l emp 34.1 32.2 30.1 30.1 22.5 24.0 16.2 17.5 16.6 16.9 24.2 24.2 24.1 24.1 ±8.9 -11.1 -8.3 -5.3 -4.8 3.1 2.5 10.6 9.5 9.0 5.8 -3.0 -2.1 0.5 0.2 7.3
TPMW µg/l mod 37.0 35.0 32.7 32.0 32.8 35.0 36.5 38.0 38.1 36.2 38.0 39.0 35.8 36.3
TPMW µg/l emp 37.7 35.1 33.9 35.6 32.3 40.9 39.1 38.2 39.6 51.5 40.7 40.7 38.8 38.7 ±18.6
TPDW µg/l mod 90.4 90.5 89.3 86.9 85.1 84.7 85.4 85.0 87.6 85.3 79.2 86.2 86.3 85.8
-0.7 -0.1 -1.2 -3.7 0.5 -5.9 -2.7 -0.2 -1.5 -15.3 -2.7 -1.7 -2.9 -1.6 4.3
TPDW µg/l emp 71.7 43.2 31.3 57.2 47.8 69.2 69.5 50.6 68.0 126.1 47.8 47.8 60.9 53.9 ±22.0 18.7 47.3 58.0 29.7 37.3 15.5 15.9 34.4 19.6 -40.8 31.4 38.4 25.4 30.5 24.6
Sec m mod 6.1 5.6 5.4 5.3 4.7 4.2 4.6 4.6 5.2 6.4 7.3 6.7 5.5 5.3
Sec m emp 6.3 5.1 5.1 5.4 5.6 5.5 5.0 5.8 5.3 4.8 3.3 6.3 5.3 5.3 ±1.6 -0.2 0.5 0.3 -0.1 -0.9 -1.3 -0.4 -1.2 -0.1 1.6 4.0 0.4 0.2 -0.1 1.4
Chl µg/l mod 3.1 5.9 7.9 8.3 7.5 7.2 6.8 5.9 7.5 5.1 1.5 2.3 5.7 6.3
Chl µg/l emp 0.5 1.3 2.2 10.5 7.3 2.4 3.5 3.0 5.8 3.6 0.4 0.5 3.4 2.7 ±2.6 2.6 4.6 5.7 -2.2 0.3 4.8 3.3 2.9 1.7 1.5 1.1 1.8 2.3 2.2 2.2
TN µg/l mod 366 376 386 391 394 403 407 409 394 362 345 356 382 388
TN µg/l emp 439 422 410 394 394 458 352 329 291 294 375 447 384 394 ±41 -73.0 -45.7 -24.0 -3.4 0.2 -54.5 54.8 80.4 102.8 68.1 -29.8 -91.5 -1.3 13.7 63.9
3.2. Fluxes and Amounts of Phosphorus Which are the large and the small TP-fluxes? And where is the phosphorus stored? Table 6 gives a compilation of the monthly TP-fluxes and a ranking based on the annual fluxes. One can note that the two largest fluxes are biouptake and retention (=outflow) of phosphorus to and from biota with short turnover times (BS). These fluxes (about 500000 t/yr) are 25 times larger than the fluxes related to the following fluxes because the organisms in this group have very short turnover times (about 3-6 days). The following fluxes are: sedimentation from the MW-layer to accumulation areas within the MW-zone (FTPMWAMW = 28000 t/yr),
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resuspension from ET-sediments to the SW-layer (27500 t/yr), outflow of TP from the Gulf of Finland (GF) to the Baltic Proper (BP) in the SW-compartment (21000 t/yr). The fluxes that may be reduced by remedial measures are bolded in table 6: the SW-inflow from the Baltic Proper (FSWBPGF = 14000 t/yr), total tributary inflow (Ftrib = 5735 t/yr) and inflow to the DW and MW-layers from the Baltic Proper (FDWBPGR = 8880 and FMWBPGR = 4100 t/yr, respectively). The diffusive flux from the accumulation areas sediment (below the halocline at 75 m) is rather small (10 t/yr). The modeled TP-concentration in the accumulation area sediments (0-10 cm) in the MW-layer is 2.4 mg/g dw and in the DW-layer 0.63 mg/g dw (see table 7), which agrees with measured values for the Baltic Proper (see Carman et al., 1996). This model provides values based on the total TP-inventory in the entire area below the theoretical wave base and below the average halocline down to 10 cm of sediments. The biologically passive sediments below 10 cm are expected to have a TP-concentration of about 0.45 in the Baltic Proper (Jonsson et al., 1990) and this value is also used in this modeling for the Gulf of Finland. This means that only a minor part (reflecting the difference between the calculated value of 0.63 and 0.45) of the phosphorus in the accumulation area sediments in the DW-zone could be available for diffusive transport from these sediments. The diffusion rate depends on the redox-conditions in the sediments, which depend on the calculated sedimentation of matter. The average values for total sedimentation calculated by the model is about between 0.7 and 1.5 mm/yr in the MW-layer and less than 1 mm/yr in the DW-layer or between 4 and 131 µg/cm2·d on the accumulation areas. The predicted water content (W) of the accumulation area sediments (0-10 cm) is 75% ww, the organic content (loss on ignition, IG) 6.3 %dw and the bulk density (d) 1.17 g/cm3. Table 7 also gives modeled values for the dissolved fraction in the three layers and these values vary between 0.8 and 0.99 in the DWzone, between 0.64 and 0.98 in the MW-layer and between 0.22 and 0.64 in the SW-layer. It should also be stressed that land uplift (FLU) is a very important individual input of TP to the system (18000 t/yr). It is interesting to note the difference between fluxes and amounts (compare the results in table 6 with the data in table 8). The largest TP-fluxes are to and from biota with short turnover times, but the total TP-inventory in biota with short turnover times is only between 1 and 5 kt (on a monthly basis). By far most TP is found in the accumulation area sediments in the MW-zone (about 590 kt), and a significant part of this is potentially available for diffusion.
3.3. Changes in the Gulf of Finland during the Last 100 Years Figure 1 shows measured Secchi depths from the Gulf of Finland during the last 100 years and table 9 gives selected results from statistical analyses of the data. One can note that: 1. The changes in Secchi depth are small and/or not statistically significant for the periods between 1900 to 1945 and 1980 to 19991. 2. The most pronounced changes in terms of significance and slope of regression line appears for the data from 1920 to 1980.
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Table 6. A ranking of the annual fluxes (t/yr), as calculated using the CoastMab-model from the monthly fluxes (t/month) of TP to, in and from the Gulf of Finland. The key fluxes for remedial measures are bolded. F = flux, SW = surface water, MW = middle water, DW = deep water, GF = Gulf of Finland, BP = Baltic Proper, trib = tributary, d = diffusive flux, x = mixing flux, LU = land uplift, ET = erosion and transport areas, A = accumulation areas, BS = biota with short turnover times, BL = biota with long turnover times, bur = burial Month 1 2 3 4 5 6 7 8 9 10 11 12 Annual FTPbioupBS 33010 42102 56886 57493 49979 38693 37909 37807 38434 54519 40518 17391 504740 FTPbioretBS 31491 41569 54658 56791 49823 39015 37506 37506 38036 52083 41010 16860 496349 FTPMWAMW 2798 2620 2641 2461 2281 2174 2371 2240 2189 3040 1350 1832 27998 FTPETSW 2549 2464 2335 2300 2351 2840 2793 3060 3209 376 351 2941 27568 FTPSWGFBP 1569 1642 1718 1773 1800 1872 1958 1923 1926 1813 1606 1494 21094 FTPSWET 1694 1487 1031 1116 1412 1795 1982 2106 2120 1676 1751 2302 20472 FTPLU 1535 1535 1535 1536 1536 1537 1537 1538 1538 1538 1536 1535 18438 FTPburAMW 1420 1398 1379 1369 1365 1343 1326 1341 1343 1364 1410 1448 16507 FTPETMW 1344 1300 1232 1213 1240 1498 1473 1614 1693 198 185 1551 14540 FTPSWBPGF 1036 1153 1238 1352 1449 1381 1303 1292 1126 959 818 880 13987 FTPSWMW 988 867 601 650 823 1046 1155 1228 1236 977 1021 1342 11933 FTPMWSWx 965 920 857 831 870 1083 1134 1297 1522 172 125 1018 10792 FTPAMWMWd 1021 1253 1187 1040 878 754 717 762 732 976 942 488 10748 FTPDWGFBP 917 949 933 936 915 815 774 872 892 932 909 856 10700 FTPDWBPGF 752 743 730 742 745 678 647 723 742 753 754 765 8775 FTPMWDW 790 740 746 695 644 614 670 632 618 858 381 517 7905 FTPSWMWx 473 477 463 493 551 710 736 820 933 93 64 522 6336 FTPtrib 361 414 486 417 400 774 948 526 416 355 349 288 5735 FTPMWSWd 666 497 354 217 196 260 362 450 517 628 677 751 5574 FTPbioupBL 234 331 460 511 472 379 358 354 356 445 316 116 4331 FTPbioretBL 295 309 330 365 388 388 381 373 365 357 352 310 4212 FTPDWMWd 313 374 381 379 359 339 337 322 307 431 373 213 4128 FTPMWBPGF 358 345 334 335 339 314 302 338 356 368 366 367 4123 FTPburADW 107 105 104 103 103 101 100 101 101 103 106 109 1245 FTPDWADW 113 113 120 121 117 117 110 118 120 6 5 120 1180 FTPprec 7.3 7.3 7.3 7.3 7.3 7.3 7.3 7.3 7.3 7.3 7.3 7.3 88 FTPADWDWd 0.9 0.9 1.0 1.0 0.9 1.0 0.9 1.0 1.0 0.2 0.2 1.0 10
Table 10 gives a statistical compilation of data (mean values, medians, standard deviations, coefficients of variation and number of data) for three interesting periods, 19001920, 1920-1980 and 1980-1991. One should note the high CV-values (about 0.35) and that the mean Secchi depths have decreased from 7.1 to 4.8 m. This is a significant change influencing the entire ecosystem since it influences the depth of the photic zone and the benthic production, which is highly dependent of water clarity. If there are major changes in primary phytoplankton and benthic algae production, one should also expect major changes in secondary production (of zooplankton, zoobenthos and fish). To discuss such changes is outside the scope of this paper, but such changes will be addressed in a coming paper using the CoastWeb-model. The question here is if it is possible to reconstruct the changes in Secchi depth shown in Figure 1 and tables 9 and 10.
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Table 7. Compilation of monthly data for modeled TP-concentrations in A-sediments (in mg/g dw) from the AW and DW-layers, water content (%ww) and loss on ignition (IG) of A-sediments (%dw), sedimentation (Sed) in the the MW and DW-layers (cm/yr and µg/cm2·yr), settling velocities (v) in the three layers (m/month) and dissolved fractions (DF) in the three layers (dim. less). Month CTPAMW CTPADW W IG SedAMW SedADW SedDW SedMW vSW vMW vDW DFDW DFMW DFSW 1 2.4 0.63 75 6.3 0.14 0.10 113 79 0.61 0.78 2.00 0.83 0.7 0.49 2 2.4 0.63 75 6.3 0.14 0.10 114 83 0.62 0.77 2.03 0.83 0.68 0.64 3 2.4 0.63 75 6.3 0.13 0. 10 106 84 0.62 0.76 2.04 0.82 0.68 0.63 4 2.4 0.63 75 6.3 0.12 0. 10 98 81 0.63 0.75 2.04 0.82 0.68 0.54 5 2.4 0.63 75 6.3 0.13 0. 10 94 82 0.63 0.74 2.02 0.82 0.66 0.40 6 2.4 0.63 75 6.3 0.12 0. 10 102 76 0.63 0.74 2.00 0.83 0.67 0.34 7 2.4 0.63 75 6.3 0.12 0. 10 97 82 0.63 0.74 1.99 0.81 0.67 0.33 8 2.4 0.63 75 6.3 0.16 0. 10 95 83 0.63 0.75 1.99 0.81 0.66 0.33 9 2.4 0.63 75 6.3 0.07 0.01 131 4 0.62 0.75 2.00 0.99 0.98 0.53 10 2.4 0.63 75 6.3 0.24 0.00 58 4 0.60 0.76 2.04 0.99 0.98 0.52 11 2.4 0.63 75 6.3 0.10 0. 10 79 84 0.59 0.77 2.01 0.79 0.64 0.22 12 2.4 0.63 75 6.3 0.15 0. 10 121 78 0.60 0.77 1.98 0.82 0.68 0.41
Table 8. Amounts of TP (1000·t) in the different compartments, i.e., accumulation areas in the DW-compartment (ADW), accumulation areas in the MW-compartment (AMW), the DW-layer, areas of fine sediment erosion and transport (ET), the MW-layer, the SW-layer, in biota with long turnover times (BL) and in biota with short turnover times (BS). Month 1 2 3 4 5 6 7 8 9 10 11 12
MTPADW 44.3 44.3 44.3 44.4 44.4 44.4 44.4 44.4 44.4 44.4 44.3 44.3
MTPAMW 588 588 588 588 588 588 589 589 589 589 588 588
MTPDW 1.7 1.8 1.8 1.8 1.7 1.7 1.7 1.7 1.7 1.8 1.7 1.6
MTPET 25.9 25.4 24.9 24.3 23.9 23.6 22.7 22.2 21.5 22.4 25.4 26.8
MTPMW 7.9 7.5 7.1 6.6 6.5 6.6 7.1 7.4 7.7 7.7 7.3 7.7
MTPSW 16.3 16.4 16.1 16.6 17.3 18.3 19.4 19.7 19.8 17.6 15.9 16.6
MTPBL 1.2 1.2 1.3 1.5 1.6 1.6 1.6 1.6 1.5 1.5 1.5 1.4
MTPBS 2.5 3.2 4.3 4.6 4.2 3.4 3.1 3.1 3.1 4.1 3.4 1.4
Table 9. Changes in Secchi depths in the Gulf of Finland during different periods of time 1900-1991 Sec = -0.0025·month + 7.84; r2 = 0.141; n = 738; p < 0.0001 1900-1945 Sec = +0.0005·month + 7.10; r2 = 0.0008; n = 352; p = 0.61; not significant 1945-1991 Sec = -0.0024·month + 7.67; r2 = 0.010; n = 386; p = 0.048 1980-1991 Sec = -0.0068·month + 11.69; r2 = 0.019; n = 60; p = 0.29; not significant 1920-1980 Sec = -0.0031·month + 8.38; r2 = 0.141; n = 555; p < 0.0001
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Table 10. Statistics of Secchi depth measurements from different periods from the Gulf of Finland
Mean (MV) Median (M50) Standard deviation (SD) Coefficient of variation (CV) Number of data (n)
1900-1920 7.1 7.0 2.45 0.35 123
1920-1980 6.3 6.1 2.2 0.35 556
1980-1991 4.8 4.5 1.6 0.33 60
Figure 7. Trend analysis of chlorophyll-a changes in the Baltic Proper from 1974 to 2005 for surfacewater samples (based on HELCOM data)
The changes in the Baltic Proper between the years 1974 to 2006 for the chlorophyll-a concentrations in the SW-layer provide a complementary picture and are shown in Figure 7. In this period, there is a weak and continuous decline in the chlorophyll values, which demonstrates that the eutrophication is not getting worse in the Baltic Proper, but rather the opposite. It is also interesting to note that the individual data in the surface water of the Baltic Proper cover all trophic classes from oligotrophic to hypertrophic. The median chlorophyll-a value in the surface-water is at the class limit between mesotrophic and oligotrophic, i.e., at 2 µg Chl/l. Figure 8 gives chlorophyll data from the Gulf of Finland relative to water depth. All these data emanate from the SW-layer, as this is defined in this work from the theoretical wave base. One can see from Figure 8 that there is only a weak correlation between the measured chlorophyll values and the water depth. This indicates that the SW-zone is relatively well mixed. That conclusion is supported by the data in Figure 9 showing measured TPconcentrations in the entire water column. Some important depth intervals are also shown in this Figure The mean depth of the Gulf of Finland is 36 m, the theoretical wave base is at 41 m and the average depth of the halocline at 75 m. One can see from Figure 9 and from table 11, which gives a statistical compilation of monthly TP-data, that there are important differences between the three zones discussed in this work (see table 5 for data).
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Figure 8. Chlorophyll data from the Gulf of Finland (1990-98) collected at different water depths (based on HELCOM data)
Figure 9. Total phosphorus concentrations in the Gulf of Finland (1990-98) collected at different water depths (based on HELCOM data)
For the reconstruction of the development in the Gulf of Finland, one can conclude that (1) there were likely no or only small changes in the nutrient loading and eutrophication in the Gulf of Finland from 1900 to about 1920, (2) the most significant changes occurred between 1920 and 1980 and (3) after that the system has not changed very much (and there may even be a slight improvement, at least in the Baltic Proper which would also reflect on the conditions in the Gulf of Finland).
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Table 11. Statistical compilation (means values, standard deviations and number of data) of empirical monthly data on TP-concentrations in the three layers (SW, MW and DW) from the Gulf of Finland (data from HELCOM from 1990 to 1998) Month 1
2
3
4
5
6
7
8
9
10
11
12
MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n MV SD n
SW 34.1 11.4 138 32.2 6.7 286 30.1 5.7 117 30.1 7.1 204 22.5 8.5 149 24.0 15.0 51 16.2 7.2 377 17.5 7.8 846 16.6 8.0 79 16.9 9.4 59 24.2 7.6 282 33.3 17.4 65
MW 37.7 18.2 53 35.1 12.4 91 33.9 10.1 45 35.6 15.5 77 32.3 16.6 63 40.9 18.5 22 39.1 18.3 81 38.2 21.7 168 39.6 23.7 37 51.5 38.3 26 40.7 11.4 92 54.1 24.5 30
DW 71.7 21.8 7 43.2 20.0 10 31.3 0.0 1 57.2 22.1 12 47.8 16.9 11 69.2 21.2 4 69.5 19.7 12 50.6 25.1 32 68.0 14.6 6 126.1 50.1 4 47.8 8.9 14 58.6 37.5 3
3.4. Reconstruction the Conditions in the Gulf of Finland The simulations to estimate the changes that have taken place during the last 100 years in the Gulf of Finland will be presented in two steps. The first step concerns substantial but realistic reductions of the direct anthropogenic emissions of TP to the Gulf of Finland from diffuse sources and point sources. The values given by HELCOM (2000) are 2112 t/yr and 2431 t/yr, respectively, and the natural loading is 1191 t/yr. It is not realistic to assume that all the anthropogenic emissions can be removed, and at the first step, it will be assumed that 40% of these emissions are eliminated (i.e., 1817 t phosphorus so that the annual loading would be
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reduced from 5734 to 3917 t TP). In reality, this would require major investments. It would also take a long time to implement such actions. In the following, it will be assumed these emissions are suddenly removed (month 31, i.e., in July). The aim is also to demonstrate the dynamic response of the system to such a sudden change in nutrient loading. At the next step, it will be assumed that also the conditions in the Baltic Proper will be altered. An overall budget for nitrogen and phosphorus fluxes to the Baltic Proper (including the Gulf of Riga and the Gulf of Finland) is given in table 12. On average, the total tributary load of phosphorus to the Baltic Proper is about 30000 t/yr. Values of the proportion between natural load, load from diffuse sources and from point source emission for the nutrient to the entire Baltic Proper are given by HELCOM (2006) and here it will be assumed that in total 7200 t TP/yr of the total transport of 30000 t TP/yr will be removed. There have been several tests and the following results mainly concern this particular reduction. Table 12. Transport of nitrogen and phosphorus to and from the Baltic Proper (tons/yr). The data from SNV (1993) concern mean values for the period between 1982 and 1989; the data from HELCOM (2000) concerns year 2000 (from Håkanson and Lindgren, 2007) Total-N SNV A. From countries Sweden Baltic states Finland Russia Poland Germany Denmark Sum inflow from countries:
44 300 72 600 35 981 90 229 109 900 20 000 51 000 297 800 ≈ 500 000 B. From processes and water inflow from adjacent basins Precipitation 289 900 Nitrogen fixation 130 000 Land uplift 480 000 Inflow from Kattegat 120 000 Inflow from Bothnian Sea 340 000 Sum from processes: 1 261 000 – 1 359 000 ≈ 1 300 000 Total inflow: ≈ 1 800 000 C. Water outflows to adjacent basins To the Bothnian Sea 340 000 To Kattegat 260 000 Total outflow: ≈ 600 000 D. Rest terms Burial in sediments (3·180 000)* = 540 000 Denitrification
(1 800 000 - 600 000 – 540 000) = 660 000
Total-P HELCOM
HL07
SNV
46 636 145 697 1874 5863 191 521 20 602 27 664 558 046 ≈ 30 000
1780 1890
1219 5408
19 100 2750 7860 33 380
12 698 512 1193 28 767
192 400
3420
HELCOM
HL07
160 000 14 000 14 000 191 420 ≈ 190 000 220 000 24 000 18 000 40 000 (220 000 – 40 000) = 180 000
* the nitrogen concentration is 3 times higher than the phosphorus concentration in these sediments
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Steady-state results are first shown in table 13. This table gives the predicted values today for the Secchi depth (mean value = 5.5 m), the monthly maximum concentration of chlorophyll-a (8.3 µg/l; since the maximum value is of great interest in contexts of algal blooms), the monthly maximum concentration of cyanobacteria in the SW-layer (86 µg/l), the mean predicted TP-concentrations in the SW, MW and DW-layers (24.5, 36 and 86 µg/l, respectively). The second column gives the corresponding steady-state values if 1871 t TP from the direct tributary inflow to the Gulf of Finland are reduced. Then, the Secchi depth would be 6.7 m, which is lower than the value 100 years ago (7.1 m, see table 10). So, it is not enough to reduce anthropogenuous TP-inflow via the rivers to the Gulf of Finland by 40%. If 7200 t TP are removed from the present TP-inflow via rivers to the Baltic Proper (including 1817 t to the Gulf of Finland), then the requested mean annual Secchi depth of 7.1 m in the Gulf of Finland will be reached and there are also major changes in the chlorophyll-a concentration and the maximum concentration of cyanobacteria. Figure 10 shows the dynamic response of the system. In these simulations, 7200 t of TP to the Baltic Proper (including 1871 t to the Gulf of Finland) have been removed month 31 and the response of the Gulf of Finland is shown for (A) the Secchi depth, (B) chlorophyll concentrations, (C) cyanobacteria, (E) TP in surface water, (E) TP in surface water in the Baltic Proper and (F) predicted SPM-concentrations in the SW, MW and DW-layers in the Gulf of Finland. Whenever possible, this figure are compares the modeled values during the initial 31 months, corresponding to the conditions prevailing today, to the uncertainty bands in the empirical data. From Figure 10A, one can see that during the initial period there is a very good correspondence between the modeled values and the empirical data given by the uncertainty band related to ± 1 standard deviation of the measured mean Secchi depth. There is also a good correspondence between measured and modeled values for chlorophyll (Figure 10B) and for TP in the SW-layer in the Gulf of Finland (Figure 10D). It is interesting to note that under these hypothetical presuppositions (that 7200 t TP would suddenly be removed month 31), there is an initial phase with a relatively fast recovery of about 7 years and then a phase with a slow recovery related to the fact that the steady-state adjustment to changes is very slow for the sediments in the MW and DW-zones (the accumulation area sediments). Table 13. How would mean annual Secchi depths, maximum monthly chlorophyll-a concentrations, maximum concentrations of cyanobacteria and mean annual TPconcentrations in the three layers (SW, MW and DW) change from today if, first, 1817 tons of TP to the Gulf of Finland and, secondly a total of 7200 tons of TP from river inflow to the Baltic Proper (including 1817 tons to the Gulf of Finland) were reduced? The table gives steady-state values Today Mean Secchi (m) Max. chlorophyll-a (µg/l) Max. cyanobacteria (µg/l) Mean TPSW (µg/l) Mean TPMW (µg/l) Mean TPDW (µg/l)
5.5 8.3 86 24.5 36 86
1817 t TP reduced from trib. to GF 6.7 7.7 63 21.9 32 80
7200 t TP reduced to BP 7.2 7.5 55 18.7 30 79
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Figure 10. The dynamic response of the Gulf of Finland if 7200 tons of phosphorus (including 1817 tons from tributaries to the Gulf of Finland) were hypothetically reduced month 31 for (A) Secchi depth, (B) chlorophyll, (C) cyanobacteria, (D) TP-concentrations in the SW-layer, (E) TPconcentrations in the SW-layer in the Baltic Proper and (F) concentrations of suspended particulate matter (SPM) in the SW, MW and DW-layers in the Gulf of Finland. This figure also gives uncertainty bands for the empirical data (± 1 standard deviation) valid for the initial period (the first 31 months) for Secchi depth, chlorophyll and TP in the SW-layer in the Gulf of Finland
Reconstruction of Secchi depths in the Gulf of Finland 14
Empirical data (o) Modeled values (x)
12
Secchi M)
10
8
6
4
2
0 0
1900
200
400
1917
1933
600
Month 1950
800
1000
1200
1967
1983
2000
Figure 11. Reconstruction of Secchi depths in the Gulf of Finland when 7200 tons of phosphorus (including 1817 tons from tributaries to the Gulf of Finland) have been reduced between the years from 1920 to 1980 compared to measured data (from HELCOM)
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The reconstruction results are given in Figure 11. The measured data on Secchi depth (from Figure 1) have been compared to the modeled values, first when there were no changes in the TP-inflow to the Baltic Proper and the Gulf of Finland in the years 1900 to 1920 (3917 t via tributaries to the Gulf of Finland; 22800 via tributaries to the Baltic Proper including the tributaries to the Gulf of Finland). Then, in the period 1920 to 1980 7200 t (including 1817 t from the tributaries to the Gulf of Finland) have successively been reduced (7200/60·12 = 10 t per month). Finally, the discharges of today have been used in the period from 1980. From Figure 11, one can see that this will reflect the measured Secchi depths in the Gulf of Finland quite well. There are several individual Secchi depth measurements higher and lower than the predicted mean monthly values, but the general correspondence between the measure and the modeled Secchi depths is good. This also means that one can run this scenario in the other direction and conclude that if the present tributary TP-load could be reduced by 7200 t, the Baltic Proper and the Gulf of Finland would return to the conditions as they were 100 years ago. If the reductions are done as in Figure 11, it would take 60-70 years to get a new steady-state condition. If the reductions are implemented slower, it takes longer, and vice versa.
3.5. Sensitivity Tests In the following sensitivity tests, one variable has been changed (reduced by 50% as compared to the default situation) and all else in the model kept at the initial default conditions. The results will be presented for two target variables, the dynamically modeled TP-concentrations in the SW-layer and the Secchi depths. The first column in table 14 gives the default conditions (today), the second column the results when the TP-flow from land uplift has been reduced by 50%. Then, one can note that the modeled TP-concentration would be 19.8 µg/l, which is significantly lower than the reference value (24.5 µg/l) and also the empirical mean annual value (24.1 µg/l, see table 5). The Secchi depth would be 7.9 m, which is markedly higher than the empirical mean value (7.1 m) a hundred years ago. In the next sensitivity test, the two diffusive TP-fluxes from the sediments (from accumulation area sediments in the MW and DW-layers) have been reduced by 50%. Since these diffusive fluxes are relatively small, the changes are not great: annual mean TP has been reduced from 24.5 to 23.4 µg/l, and the Secchi depth increased from 5.5 to 6 m. Also the diffuse TP-fluxes in the water have been reduced by 50%, and the results are close to the results for the diffusive sediment fluxes: mean annual TP has decreased to 23.2 µg/l and the Secchi depth increased to 6.1 m. Since it is fairly complicated to calculate the production and biomasses of functional groups or species of organisms and since most mass-balance models for nutrients would not do this, it is also interesting to see what would happen of 50% of the biouptake to organisms with short turnover times would be changed. The results show that this would neither alter the predicted TP-concentrations very must (from 24.5 to 24.9 µg/l) nor the predicted Secchi depths (5.5 to 5.4 m). This is also the result if 50% of the biouptake to organisms with long turnover times are being reduced.
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Table 14. Steady state results from 8 sensitivity analyses where the influence from (1) land uplift, (2) diffusion from sediments, (3) diffusion in water, (4) biouptake and retention in biota with short turnover times and (5) in biota with long turnover times, (6) the particulate fraction of phosphorus in the deep-water zone, in (7) the middlewater zone and (8) the surface-water zone were reduced by 50%. This has been calculated for (A) TP-concentrations (µg/l) and (B) Secchi depths (m) A. TP-concentrations in the surface-water layer Month Today Landup. Diff sed Diff wat 1 23.0 18.5 21.8 21.3 2 23.9 19.0 22.7 22.4 3 24.8 19.6 23.7 23.5 4 25.2 20.0 24.1 24.1 5 25.6 20.4 24.5 24.5 6 26.4 21.1 25.3 25.3 7 26.7 21.5 25.7 25.5 8 27.0 21.5 25.9 25.7 9 25.5 20.7 24.4 24.1 10 22.6 19.2 21.4 20.8 11 21.1 18.0 19.8 19.2 12 22.0 18.1 20.9 20.2 MV 24.5 19.8 23.4 23.1 B. Secchi depth 1 6.1 8.9 6.7 .0 2 5.6 8.3 6.2 6.3 3 5.4 8.1 5.8 5.9 4 5.3 7.9 5.7 5.7 5 4.7 6.9 5.0 5.0 6 4.2 6.1 4.5 4.5 7 4.6 6.7 4.9 5.0 8 4.7 6.8 5.0 5.1 9 5.2 7.4 5.6 5.7 10 6.4 8.5 7.0 7.4 11 7.3 9.6 8.1 8.6 12 6.6 9.2 7.2 7.6 MV 5.5 7.9 6.0 6.1
BioS 23.3 24.2 25.2 25.7 26.0 26.8 27.0 27.2 25.8 23.2 21.6 22.3 24.9
BioL 23.3 24.2 25.2 25.7 26.1 26.9 27.2 27.4 26.0 23.3 21.7 22.4 24.9
PFDW 22.5 23.4 24.3 24.7 25.1 25.9 26.2 26.4 25.1 22.3 20.8 21.6 24.0
PFMW 23.0 23.9 24.8 25.2 25.6 26.4 26.7 27.0 25.5 22.6 21.1 22.1 24.5
PFSW 24.3 24.9 25.6 26.1 26.6 27.6 27.9 28.1 26.8 24.0 22.8 23.6 25.7
6.0 5.5 5.2 5.1 4.5 4.1 4.5 4.6 5.1 6.1 7.0 6.5 5.4
6.0 5.5 5.3 5.1 4.5 4.1 4.5 4.5 5.0 6.1 7.0 6.4 5.3
6.4 5.9 5.6 5.5 4.8 4.4 4.8 4.8 5.4 6.5 7.5 6.8 5.7
6.1 5.6 5.4 5.3 4.7 4.2 4.6 4.7 5.2 6.4 7.3 6.6 5.5
5.6 5.3 5.1 5.0 4.4 3.9 4.3 4.3 4.8 5.8 6.4 5.9 5.1
There are also uncertainties regarding the distribution of phosphorus in dissolved and particulate forms. Only the dissolved forms can be taken of by biota and only the particulate forms can settle out due to gravity. If one would first decrease the particulate fraction for phosphorus in the DW-zone, this could be a reflection of lower oxygen concentrations in the DW-layer and it would increase the dissolved fraction in the DW-layer, reduce sedimentation in the DW-layer, increase diffusion to the MW-layer but not influence the TP-concentration in the SW-layer much since this change would mainly influence relatively small TP-fluxes in the Gulf of FInland. If the particulate fraction in the MW-layer is reduced by 50%, it would influence the predicted TP-concentrations in the SW-layer even less and hence also the
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Secchi depth. If, however, the particulate fraction in the SW-layer itself is reduced by 50%, this would lower the sedimentation more and also increase the predicted TP-concentration (from 24.5 to 25.7 µg/l) and also decrease the Secchi depth (from 5.5 to 5.1 m).
4. CONCLUDING REMARKS These results indicate that it is possible to remediate the Gulf of Finland to the conditions that characterized the system 100 years ago. About 7000 tons of phosphorus must be removed on an annual basis. This should be done in the most cost-efficient manner so that the largest fluxes of phosphorus are removed per euro or dollar. The trophic conditions in the Baltic Proper have varied very little during the last 30 years. The most marked changes in Secchi depth in the Gulf of Finland took place between 1920 and 1980. Process-based mass-balance models are - categorically - the only tool to quantify fluxes, concentrations and amounts and to make predictions of how the concentrations would change in response to reductions in loading. Evidently, this modeling could and should be expanded and it would be very interesting to link all major sub-basins of the Baltic Sea into one system of communicating basins. It would also be interesting to expand such modeling to include also key functional groups (e.g., the CoastWeb-model, see Håkanson and Gyllenhammar, 2005). This would imply that it may be possible to predict how future climate changes would likely influence the structure and function of the Baltic Sea ecosystem more realistically and holistically. However, those expansions are certainly outside the scope of this work.
ACKNOWLEDGMENTS This work has been carried out within the framework of the Thresholds-project, an integrated EU project coordinated by Prof. Carlos M. Duarte, CSIC-Univ. Illes Balears, Spain, and I would like to acknowledge the financial support from the EU and to Dan Lindgren for valuable help and comments concerning the GIS-data, and to Andreas Bryhn for valuable discussions.
REFERENCES Aarup, T. (2002). Transparency of the North Sea and Baltic Sea – a Secchi depth data mining study. Oceanologica, 44, 323-337. Abrahamsson, O. & Håkanson, L. (1998). Modelling seasonal flow variability of European rivers. Ecological Modelling, 114, 49-58. Ambio, (1990). Special issue. Marine eutrophication, 19, 102-176. Ambio, (2007). Special issue. Science and governance of the Baltic Sea, 2-3, 117286-176. S. A. Bortone, ed. (2005). Estuarine indicators. CRC Press, Boca Raton, 531.
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Carman, R., Aigars, J. & Larsen, B. (1996). Carbon and nutrient geochemistry of the surface sediments of the Gulf of Riga, Baltic Sea. Mar. Geol., 134, 57-76. FRP. (1978). The sea; natural conditions and use (in Swedish, Havet; naturförhållanden och utnyttjande). Fysisk riksplanering (FRP), Bostadsdepartementet, Nr 7, 303. Guildford, S. J. & Hecky. R. E. (2000). Total nitrogen, total phosphorus, and nutrient limitation in lakes and oceans: Is there a common relationship? Limnology and Oceanography, 45, 1213-1223. Håkanson, L. (1977). The influence of wind, fetch, and water depth on the distribution of sediments in Lake Vänern, Sweden. Canadian Journal of Earth Sciences, 14, 397-412. Håkanson, L. (2006). Suspended particulate matter in lakes, rivers and marine systems. The Blackburn Press, New Jersey, 319. Håkanson, L. & Bryhn, A. C. (2007a). A process-based mass-balance model for phosphorus/eutrophication including a climate change scenario, as exemplified for the Baltic Proper. Manuscript, Inst. of Earth Sci., Uppsala Univ. Håkanson, L. & Bryhn, A. C. (2007b). Modeling the foodweb in coastal areas – a case study of Ringkobing Fjord, Denmark. Ecol Res., (in press). Håkanson, L., Bryhn, A. C. & Hytteborn, J. A. (2007b). On the issue of limiting nutrient and predictions of bluegreen algae in aquatic systems. Science of the Total Environment, 379, 89-108. Håkanson, L. & Eklund, J. M. (2007a). A dynamic mass-balance model for phosphorus fluxes and concentrations in coastal areas. Ecol Res., 22, 296-320. Håkanson, L. & Eklund, J. M. (2007b). Relationships between chlorophyll, salinity, phosphorus and nitrogen in lakes and marine areas. Manuscript, Uppsala Univ. Håkanson, L. & Gyllenhammar, A. (2005). Setting fish quotas based on holistic ecosystem modelling including environmental factors and foodweb interactions – a new approach. Aquatic Ecology, 39, 325-351. Håkanson, L., Kvarnäs, H. & Karlsson, B. (1986). Coastal morphometry as regulator of water exchange - a Swedish example. Estuarine, Coastal and Shelf Science, 23, 1-15. Håkanson, L. & Lindgren, D. (2007). The CoastWeb-model, a foodweb model based on functional groups for coastal areas including a mass-balance model for phosphorus. Manuscript, Inst. of Earth Sci., Uppsala Univ. Håkanson, L., Lindgren, D. & Omstedt, A. (2007a). Water fluxes to, within and from a coastal system using a general mass-balance model for salt as exemplified using data for the Baltic Sea. Manuscript, Inst. of Earth Sci., Uppsala Univ. Hecky, R. E. & Kilham, P. (1988). Nutrient limitation of phytoplancton in freshwater and marine environments: A rewiew of recent evidence on the effects of enrichment. Limnology and Oceanography, 33, 796-822. HELCOM, (2000). Baltic Sea Environment Proceedings No. 100 from the HELCOM website. HELCOM, (2006). Development of tools for assessment of eutrophication in the Baltic Sea. Baltic Sea Environment Proceedings nr. 104, Helsinki. Howarth, R. W. (1988). Nutrient limitation of net primary production in marine ecosystems. Ann. Rev. Ecol., 19, 89-110. Jonsson, P. (1992). Large-scale changes of contaminants in Baltic Sea sediments during the twentieth century. Thesis, Uppsala Univ., Sweden.
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Jonsson, P, Carman, R. & Wulff, F. (1990). Laminated sedments in the Baltic – a tool for evaluating nutrient mass balances. Ambio, 19, 152-158. Jönsson, A. (2005). Model studies of surface waves and sediment resuspension in the Baltic Sea. Dr. thesis No. 332, Linköping Univ. Karlsson, M. (2007). Dynamic mass-balance modeling of phosphorus in the Baltic Sea. Master thesis, Dept. of Earth Sciences, Uppsala Univ. 79 (in Swedish). Kiirikki, M., Inkala, A., Kuosa, H., Pitkänen, H., Kuusisto, M. & Sarkkula, J. (2001). Evaluating the effects of nutrient load reductions on the biomass of toxic nitrogen-fixing cyanobacteria in the Gulf of Finland, Baltic Sea. Boreal Environment Research, 6, 1-16. Lindgren, D. & Håkanson, L. (2007). Functional classification of coastal areas as a tool in ecosystem modeling and management. Manuscript, Inst. of Earth Sci., Uppsala Univ. Livingston, R. J. (2001). Eutrophication processes in coastal systems. CRC Press, Boca Raton, 327. B. Moldan, & S. Billharz, Eds. (1997). Sustainability indicators. Wiley, see http://www.icsuscope.org/downloadpubs/scope58/. Mikulski, Z. (1985). Water Balance of the Baltic Sea. Baltic Sea Environment, Proceedings No. 16, Helsinki Commision, Helsinki, 174. Monitor, (1988). Sweden´s Marine Environment - Eosystem under Pressure. Swedish Environmental Protection Agency, 207. Myrberg, K. (1998). Analysing and modelling the physical processes of the Gulf of Finland in the Baltic Sea. Monographs of the Boreal Environment research. Nr 10, Helsinki. Nixon, S. W. (1990). Marine eutrophication: a growing international problem. Ambio, 3, 101. H. Pitkänen, & P. Tallberg, (2007) (eds.). Searching efficient protection strategies for the wutrophied Gulf of Finland: the integrated use of experimental and modeling tools (SEGUE), Finnish Environment Institute, Helsinki, 15, 89. Redfield, A. C. (1958). The biological control of chemical factors in the environment. Am. Sci., 46, 205-222. Redfield, A. C., Ketchum, B. H. & Richards, F. A. (1963). The influence of organisms on the composition of sea-water. In: N. Hill, (Ed.), The Sea 2. Interscience, New York, 26-77. Savchuk, O. P. (2000). Studies of the assimilation capacity and effects of nutrient load reductions in the eastern Gulf of Finland with a biogeochemical model. Boreal Environment Research, 5, 147-163. Savchuk, O. P. (2006). SANBaLTS - Simple as Necessary Long-Term large-Scale simulation model of the nitrogen and phosphorus biogeochemical cycles in the Baltic Sea, version 3. http://www.mare.su.se/nest/docs/SANBalTS_QAv3.pdf (2007-01-15). Savchuk, O. P. & Swaney, D. P. (2000). Water and Nutrient Budget of the Gulf of Riga. http://data.ecology (2006-04-19). Savchuk, O. & Wulff, F. (1999). Modelling regional and large-scale response of Baltic Sea ecosystems to nutrient reductions. Hydrobiologia, 393, 35-43. Schernewski, G. & Neumann, T. (2005). The trophic state of the Baltic Sea a century ago: a model simulation study. Journal of Marine Systems, 53, 109-124. G. Schernewski, & U. Schiewer, (2002) (eds.). Baltic coastal ecosystems. Springer, Berlin, 397. Schindler, D. W. (1977). Evolution of phosphorus limitation in lakes. Science, 195, 260-262. Schindler, D. W. (1978). Factors regulating phytoplankton production and standing crop in the world's freshwaters. Limnology and Oceanography, 23, 478-486.
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Seifert, T., Tauber, F. & Kayser, B. (2001). A high resolution spherical grid topography of the Baltic Sea – 2nd edition. Baltic Sea Science Congress, Stockholm 25-29. November 2001. Poster #147. http//www.iowarnemuende.de/iowtopo/. SNV, (1993). Eutrophication of land, freshwater and the Sea (in Swedish, Eutrofiering av mark, sötvatten och hav). Swedish Environmental Protection Agency, Report 4134, Stockholm, 199. Stålnacke, P., Grimvall, A., Sundblad, K. & Tonderski, A. (1999). Estimation of riverine loads of nitrogen and phosphorus to the Baltic Sea, 1970-1993. Environmental Monitoring and Assessment, 58, 173-200. SYKE, (2006). Syrebristen i Finska viken exceptionellt omfattande, tillståndet i havsbottnen sämre än tidigare på 2000-talet. Finlands miljöcentral Pressmeddelande, 2006-08-17. SYKE, (2003). Intern belastning reglerar kraftigt algblomningen i Finska viken. Finlands miljöcentral Pressmeddelande, 2003-06-11. Tyrrell, T. (1999). The relative influences of nitrogen and phosphorus on oceanic primary production. Nature, 400, 525-531. A. Voipio, (ed.), (1981). The Baltic Sea. Elsevier Oceanographic Series, Amsterdam, 418. Wallin, M., Håkanson, L. & Persson, J. (1992). Load models for nutrients in coastal areas, especially from fish farms (in Swedish with English summary). Nordiska ministerrådet, 1992,502, Copenhagen, 207. Wulff, F., Rahm, L., Hallin, A. K. & Sandberg, J. (2001). A nutrient budget model of the Baltic Sea. In: F. Wulff, et al., (Eds.), A Systems Analysis of the Baltic Sea, Ecological Studies, vol. 148, Springer, Berlin, 353-372.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 333-350 © 2011 Nova Science Publishers, Inc.
Chapter 11
ENVIRONMENTAL MANAGEMENT AND SUSTAINABLE USE OF COASTAL LAGOONS ECOSYSTEMS Rutger de Wit, Behzad Mostajir, Marc Troussellier and Thang Do Chi Unité Mixte De Recherche ―Ecosystèmes Lagunaires‖, Université Montpellier 2, Centre National de la Recherche Scientifique (CNRS), IRD & Ifremer, Montpellier, France
1. INTRODUCTION This chapter illustrates some of the major issues for the management and use of coastal lagoons using two examples from the South of France. These are the mesotidal Bassin d‘Arcachon on the Atlantic coast and the microtidal Etang de Thau on the Mediterranean (see Figure 1). Oyster-farming is a major use in both lagoons. Coastal lagoons are part of a coastal landscape and are therefore typical transition zones between the continent and the sea, characterised by gradients and ecotones. Thus, it is most important to consider the coastal lagoon ecosystems in the context of the coastal zone and consider their links both with the ocean as well as with the hinterland. The latter requests a thorough knowledge of the watershed of the lagoon. Coastal areas, which are commonly defined as the interface or the transition area between land and sea, are diverse in function, form and dynamics. In general, these systems are not well defined by strict spatial boundaries and include low lands, intertidal zones, salt marshes, wetlands, lagoons and their watersheds. From the development and management point of view, the coastal areas are characterised by the economical activities that they support and by the impact of these activities on the environment. Accordingly, the coastal areas are characterised by i) the production of living resources, ii) highly diverse human uses including urban development, exploitation of sediments, shipping and harbours, commercial and sport fishing, aquaculture, tourism, and as a receptacle of industrial and agricultural waste, iii) their role in providing protection against flooding and by iv) their biodiversity and role in the functioning of the ecosystems at different spatial levels.
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Figure 1. Localisation in France of the Bassin d‘Arcachon (Atlantic coast) and the Etang de Thau (Mediterranean coast). Below both lagoons are depicted on the same scale (cf bar indicating 10 km
However, biodiversity and ecosystem functioning may be impaired or negatively affected by economic use of lagoons. Coastal lagoons represent an important natural heritage and are noticeably important habitats for waterfowl, marine wildlife, algae and halophytic plant species. The objective of sustainable use of coastal ecosystems, therefore, is to conserve the natural heritage and guarantee the living resources for future generations and develop management schemes that allow an acceptable degree of human exploitation that does not impair the functioning of the ecosystem in the long term. Population densities are usually very high in coastal areas, which results in a concentration of economic activities. Thus, the consequences on the natural environment and on the living resources may be particularly strong, which points out to some extent the incompatibility between the development process and the ecosystems conservation requirements. Coastal lagoons were early sites for human settlement and are becoming increasingly important areas for human economic, social and cultural development. Some lagoons have disappeared as the consequence of land-reclamation programmes, particularly in densely populated countries as Japan and in the Netherlands. Tourism started in the 19th century in some lagoons, with the Bassin d‘Arcachon as a historical example in France. Many other lagoons, as e.g. in the Languedoc-Roussillon region, were long-time considered as unattractive as seaside resorts and have been developed for tourism only during the second half of the 20th century. Tourism has grown into a real industry in Southern Europe, implying that population densities during holiday periods may exceed local population by several factors. The urbanisation of these attractive areas has been further reinforced by suburban developments. Thus, the surroundings of the Etang de Thau and the Bassin d‘Arcachon increasingly serve as suburban areas for the cities of Montpellier and Bordeaux, respectively. This has resulted in increasing pressures on these coastal ecosystems and spatial planning and proactive environmental management are requested for sustainable use. Management schemes depend on identifying the spatial area that needs to be managed in a coherent way. This is difficult in the coastal zone, because of the openness of the coastal ecosystems that depend on
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their continental watersheds and interact with the coastal sea and because of the traditional administrative boundaries which often do not follow the natural boundaries. Hence, we first describe the scientific definition of coastal lagoons. Second we describe some definitions of operational units which have been proposed from the point of view of the managers and we pay particular attention to the definitions used in the European Water Framework Directive.
Definitions of Coastal Lagoons, Transitional Waters and Coastal Waters In 1980, Barnes published a classical book titled ―Coastal Lagoons; the natural history of a neglected habitat‖. He indicated that in English language (Oxford English Dictionary) the word ―lagoon‖ allows two meanings, i.e. ―an area of salt or brackish water separated from the adjacent sea by a low-lying sand or shingle barrier‖, and ―a stretch of water enclosed in a coral atoll‖. For the latter, French language uses a specific word, i.e. ―lagon‖ as opposed to ―lagune côtière‖ that corresponds to the first definition, i.e. a coastal lagoon. Hence, coastal lagoon is a typical geomorphological term. We recommend the use of the definition proposed by Kjerfve (1994, adapted from earlier definitions by Pritchard and Phleger); accordingly, coastal lagoons are shallow water bodies separated from the ocean by a barrier, connected at least intermittently to the ocean by one or more restricted inlets, and usually oriented shoreparallel. Nevertheless, you may find some scientific publications where some coastal lagoons are actually described as bar-built estuaries (for a discussion see Kjerfve, 1994). In the socio-historical context of South-western Europe, lagoons are well recognised and distinguished from estuaries as is shown by the vernacular languages that contain specific words for the coastal lagoons, their barriers and inlets. Thus, coastal lagoons are named ―laguna‖ in Spanish and Italian, ―lagoa‖ in Portuguese and ―lagune côtière‖ in French. However, in the Languedoc-Roussillon region in Mediterranean France the coastal lagoons are called ―Etangs‖, i.e. the Etang de Thau. For coastal zone management, coastal areas are delimited based on a compromise between political, administrative, ecological and pragmatic considerations. A general definition of the coastal zone would include the coastline and the coastal ocean extending for legal reasons up to the 12 nautical miles (national jurisdiction) or up to the 200 nautical miles (EEZ: economic exclusive zone) and on the continent to the boundaries of the watershed. However, such an area is far too wide and too diverse for most management purposes and it is often better to delimit specific coastal ecosystems as subsystems where the highest levels of interactions and conflicts are observed. A narrow coastal zone is often sufficient if the intertidal zone and the coast line have to be managed. However, the watershed of the coastal ecosystem needs to be considered for the control of water quality, because the coastal ecosystems are the receptacle for contaminants and nutrients that may cause eutrophication. The Large Marine Ecosystem concept (LME) (Sherman et al., 1990) should be considered in case of interactions between the coastal zone and the high sea, as e.g., for migratory species. The latter support sequential fisheries based on the exploitation of juveniles in lagoons and estuaries and of the adults off shore.
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BOX 1. TERMINOLOGY INTRODUCED BY THE EUROPEAN WATER FRAMEWORK DIRECTIVE The European Water Framework Directive (2000/60/EC of 23 October 2000), abbreviated as WFD, establishes a new framework for European Community action in the field of water policy (http://europa.eu.int/comm/environment). The WFD has introduced new terminology for aquatic systems, according this terminology coastal lagoons are either classified as Transitional Waters or as Coastal Waters. According WFD, Transitional Waters are defined as ―Bodies of surface water in the vicinity of river mouths which are partly saline in character as a result of their proximity to coastal waters, but, which are substantially influenced by freshwater flows‖. Therefore, many of the coastal lagoons could be characterised without problems as Transitional Waters, since most of them receive freshwater inputs. Nonetheless, national working groups have interpreted the ―substantially influenced by freshwater flows‖ rather strictly and decided that many lagoons on the Atlantic coast that are even more substantially influenced by seawater tidal flushing should be considered as ―coastal waters‖ (http://www.ecowin.org/TICOR/, Bettencourt et al., 2003. The WFD uses a very complicated bureaucratic definition for Coastal Waters, i.e., ―surface water on the landward side of a line, every point of which is at a distance of one nautical mile on the seaward side from the nearest point of the baseline from which the breadth of territorial waters is measured, extending where appropriate up to the outer limit of transitional waters‖. To say it in other words, this means that one should first use the coastline as it has been used for defining the breadth of the territorial waters, and secondly draw an imaginary line in the coastal sea at one nautical mile distance from this coastline. All marine saline waters between the coastline and this imaginary line at one nautical mile distance are unambiguously recognised as coastal waters. However, a problem of interpretation arises for some bays and lagoons where saline waters may extent inland from the defined coastline. The Portuguese and French national working groups have thus classified some of their Atlantic lagoons as coastal waters, while the Italian approach is to consider these waters on the inland side of the coastline by definition not as coastal waters. The one nautical mile limitation means that on average about 20 % of the European coastal ocean with a depth less than 200 m is taken into account as Coastal Waters in the frame of the WFD Borja (2005). The term of Transitional Waters has been adopted as an interesting and useful typology by the scientific community and recently two new scientific journals have been founded that are dedicated to studies on these ecosystems, which are called Transitional Waters Bulletin (TWB) and transitional Waters Monographs (TWM), respectively. These journals have defined the Transitional Waters simply as river mouth ecosystems, lagoons, coastal lakes and brackish wetlands. No reference was made to the definition in the WFD, because it was considered that when this definition is taken alone it is actually quite confusing and becomes clear only when compared with the definition of coastal waters.
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Glossary of Terms Provided by the European Environment Agency We found the multilingual Glossary of terms (http://glossary.eea.eu.int/EEAGlossary) provided by the European Environment Agency a very helpful on-line tool for looking after the definitions of the different environmental terms used in the context of European Environmental Policies and Legislations. The European Environment Agency (EEA) is located in Copenhague (Denmark) and currently has 31 member countries, which include all the 27 member states of the European Union as well as Turkey, Iceland, Norway and Liechtenstein. Its main task is task is to provide decision-makers with the information needed for making sound and effective policies to protect the environment and support sustainable development. The Agency also ensures this information is available to the general public through its publications and website (http://www.eea.eu.int/ ). The European Water Framework Directive has introduced a specific typology (see Box 1). Accordingly, the transitional waters include both the majority of the lagoons as well as the estuaries and river deltas. The coastal waters have been limited on the seaside by a baseline that is located at one nautical mile distance from the coastline. Within the frame of implementation of the WFD, the coastal lagoons on the Mediterranean shore in LanguedocRoussillon, including the Etang de Thau, are all considered transitional waters, while the mesotidal lagoons on the Atlantic as Ria Formosa (Faro, Portugal) and the Bassin d‘Arcachon (S.W. France) are being considered as coastal waters (see Box. 1).
2. ECOLOGICAL AND ECONOMICAL IMPORTANCE OF THE COASTAL LAGOONS; ENVIRONMENTAL ISSUES AND CONFLICTS Coastal lagoons were originally clear water systems, characterised by the presence of extensive seagrass meadows. Seagrasses are rooted phanerogamms and flowering plants (Magnioliophyta) that belong to the Zosteraceae, Potamogetonaceae and Ruppiaceae families. In the mesotidal Bassin d‘Arcachon (Atlantic coast of France) 30,000 to 45,000 brent geese (Brenta bernicla bernicla) overwinter, which represent 10 to 20 % of the world population of this species. These species use the seagrass Zostera noltii as their food source. Primary production rates of seagrass communities range from 0.2 to 1.5 kg C m-2 yr-1, which are higher than most coastal phytoplankton but lower than most salt marshes (Valiela, 1995). Nonetheless, over the last decades, many of these coastal lagoons in Western Europe have suffered dramatic losses of their seagrass populations. The loss of the seagrass communities has been related to increasing eutrophication (De Wit et al., 2001 and references cited therein). The replacement of the seagrass communities by floating algae or dense phytoplankton blooms has often occurred suddenly and the change can be characterised as a drastic shift. This shows that while seagrass communities have some inbuilt resistance towards change at low forcing levels when these are exceeded, dramatic non-linear changes occur. The ROBUST project, a EU research programme that run from 1996-2000 (De Wit et
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al., 2001) has focused on the study of mechanisms that provide these inherent resistances, which have been invoked as buffering capacities (Box 3). Coastal lagoons and estuaries are ecosystems that play a major role in the life cycles of economically important finfish and shellfish species by providing feeding, spawning grounds, breeding, and nursery habitat. For example, over 90 percent of all fish caught in the Gulf of Mexico are reported to be estuarine dependant to some degree. Many of these ecosystems have been exploited for aquaculture e.g. oyster farming is the main aquaculture both in the non-tidal Etang de Thau (Mediterranean coast of France) and in the Bassin d‘Arcachon (Box 2). Oysters are filter-feeding organisms that consume phytoplankton, bacteria and detritus from the water column. Therefore, the aquaculture in the lagoon is particularly sensitive to environmental quality as a degradation of the habitat and inappropriate food will result in low quality products. Hence, by accumulating micro-organisms, viruses, heavy metals and persistent organic pollutants from the water column shell fish farming may present a risk factor for human health. A major source of degradation of estuaries and lagoons is their continued use as pollutant discharge areas. Besides the outright fish kills and other dramatic effects, pollution causes pervasive and continuous degradation, shown by the gradual disappearance of fish, shellfish, and waterfowl and of plant and algal species, as well as by a general decline in the natural carrying capacity of the system. The most likely sources of pollution are agricultural and industrial chemical and organic wastes. Such contaminants tend to accumulate in coastal lagoons due to long residence times and restricted water exchange. Above certain threshold concentrations these create a hostile environment that drives away fish, prevents shellfish from reproducing or undermines the food chain (Clark, 1992). Tributyltin (TBT) is a specific tin (Sn)-containing persistent organic pollutant that has been used as an anti-fouling paint in shipping. As early as 1975, repeated severe disturbances were observed in the Crassostrea gigas oyster farms of the Bassin d‘Arcachon, which were attributed to TBT. As a precautionary principle, the use of TBT for ships of less than 15 m has been banned in France since 1982. Since then it has been shown that TBT is extremely toxic for marine animals in general and for gastropods and bivalves in particular (Alzieu, 2000). Alteration in the functioning of coastal lagoons as e.g. the algal blooms in the Mediterranea, in the Carribean, in the North Sea, Western Pacific and other areas are often linked to the pollution and eutrofication and its consequences are of sanitary concern as well as for the food safety. In the Thau lagoon (Southern France) bacterial contaminants are the major environmental and sanitary issue (see below) as this area is supporting the main shellfish farming production of the French Mediterranea. The proliferation of human and animal pathogens in coastal lagoons needs to be prevented, particularly for sanitary reasons in those environments where fish and shellfish are farmed and/or harvested. Within the EU shellfish farming and shellfish harvesting areas are classified depending on the degree of faecal pollution, which is based on the monitoring of the gut-bacterium Escherichia coli. The highest quality, i.e. sanitary class A requires that
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BOX 2. LIFE-CYCLE OF THE JAPANESE OYSTERS CRASSOSTREA GIGAS, WHICH ARE FARMED IN THE BASSIN D‟ARCACHON AND THE ETANG DE THAU
Figure 2. Life cycle of Japanese oysters Crassostrea gigas (Thunberg, 1793)
Both in the Bassin d‘Arcachon and in the Etang de Thau, nowadays Japanese oysters Crassostrea gigas (Thunberg, 1793) are the main oyster species used for oyster farming. In the Etang de Thau, most often oysters of small size are imported from other regions in France. These small oysters are cemented to a rope and immerged into the microtidal lagoon in places where water depths is about 5 to 8 m. These small oysters are grown to adult sizes (6 – 12 cm) in about 1.5 year and show high growth rates because of high water temperatures and quite eutrophic conditions in the Etang de Thau. In the mesotidal Bassin d‘Arcachon, traditionally since the mid 19th century oysters have been cultured directly on the intertidal mudflats. To facilitate the harvesting, nowadays, the oysters are often grown in bags of black plastic mesh that are placed as trays on metallic supports some 10-20 cm above the surface of the tidal flat. The conditions in the Bassin d‘Arcachon are particularly favourable for the reproduction of the oysters. The oyster farmers exploit these favourable conditions and many of them have specialised on capturing the larvae from the water column by facilitating the settlement on artificial structures and growing them subsequently in about 8 months into juvenile oysters (3-4 cm), a size suitable for exportation to the other oyster farming regions in France. This technique called ―captage‖ in French was developed in the 1860‘s by the naturalist Costes and the mason Michelet who designed the collectors comprising tiles coated with a
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mixture of chalk and sand. These collectors are placed along the intertidal channels and have proven particularly good in facilitating the settlement of the larvae. To understand and manage this process, knowledge of the life-cycle of the oysters is essential. The Japanese oysters are hermaphrodites showing irregular sexuality. This means that the sexually mature individuals are either male or female, but can change gender in between reproductive seasons. There is a certain tendency to protandry, which means that younger individuals are males and become females later in their lives. Sexual differentiation takes place in autumn. They have simple reproductive systems consisting of gonads where the gamets are formed. Gametogenesis becomes very active in March and April and sexual maturity reaches its optimum between May and July. The outer part of the gonads become creamy-white and very rich in lipids, in vernacular language the local people say that oysters have become ―laiteuses‖ i.e. creamy-milky. Spawning, i.e. the release of the gametes into the water column is induced by temperature (requiring temperatures > 22.5 °C) and other physical-chemical factors, and takes place in the Bassin d‘Arcachon from early June to mid September. A fertilised oocyte develops within 24 h through different developmental stages into a D-hinged larvae of 50-100 µm size, provided that the water temperature is between 22 and 24 °C. It owns its name to its typical shape resembling the letter D. The concentration of larvae in the water column during the summer periods ranges from 100 – 500,000 ind. m-3. The larvae mainly feed on bacteria, small uni-cellular phytoplankton, so-called pico-phytoplancton < 3 µm and nano-phytoplancton < 20 µm and enter in competition with other zooplancton. In 15-18 days the larvae grow in size to about 250 µM and develop an appendix (pediveliger larvae). This is the last stage of the pelagic phase of the life cycle. The pediveliger larvae is cable to settle on hard surfaces and the appendix is involved in motility and finally in cementing the oyster on the surface. Thereafter, the oyster larvae metamorphose and start making their shells. In Arcachon this phenomenon is facilitated by introducing the characteristic collectors developed in the mid 19th century. The juveniles growing on the tiles are called ―naissain‖ in vernacular language. These need to be thinned regularly to avoid intraspecific competition and are thus grown for a 8 month period to a size of about 3-4 cm. These juveniles are used for growth on the intertidal flats in the lagoon or exported to other regions (transportation in refrigerated trucks). It has been estimated that 60 to 70 % of the oyster production in France is raised from the juveniles grown in the Bassin d‘Arcachon. Therefore, a high success of capturing larvae on the collectors is most important for the local aquaculture economy as well as for the well-being of entire oyster farming branch in France. Success rate is variable in between years. After a particularly bad year was 1998, when the number of metamorphosed larvae settled on the collectors was below 50 per tile, while in normal years it ranges from several hundreds to 20,000. This raised a lot of concern in this economic branch and IFREMER, the French Institute for the study and exploitation of the Sea, was asked to perform a specific study to find out whether the low success rate was due to natural variability or caused by structurally changed environmental factors and a final report was delivered in 2004 (Auby and Maurer, 2004). Auby, Maurer and their coworkers checked several hypothetical possibilities and developed a study comprising both the factors determining the health status of adult oysters as well as the aquatic ecology of the system to understand the survival rate of veliger larvae. Although, it could not be fully excluded that there was some negative effect of organic pollutants from agriculture and maritime activities (i.e. anti-fouling paints as TBT and Cu-containing
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organics) it was concluded that most of the variation of reproductive success of oysters was explained by food availability in spring (the intensity of the spring phytoplankton blooms expressed as chlorophyll concentrations) and of the temperature during the summer period of spawning and veliger larvae development (Auby and Maurer, 2004). The juvenile and adult oysters are filter feeders, which potentially consume a variety of species of phytoplankton, bacteria, detritus and viruses from the surrounding water. The adult oysters may filter up to 10 L of water per hour and they perform best when their diet comprises diatoms and chrysophytes.
100% of shell samples contain less than 230 Echerichia coli per 100 g of shellfish flesh. Sanitary class B requires that 90% of shell samples contain less than 4600 E. coli per 100 g of shellfish flesh and the remaining 10% less than 46,000 E. coli per 100 g of shellfish flesh.. Class A can be sold directly for consumption. For class B, self-purification (depuration) in tanks of clean seawater is requested. Because of recurrent problems with water quality in the Etang de Thau due to fecal polution, this lagoon has been classified as B-quality for oyster farming activities. In addition, phytoplankton communities need to be monitored to check for possible occurrence of toxic algae. Although it remains sometimes enigmatic what are the factors that trigger the occurrence of the so-called harmful algal blooms; it is without doubt that human pressure has increased the importance of this phenomenon. A major objective of the European Water Framework Directive (WFD – see Box 1) is to achieve good ecological status for all the European waters in 2015. Hence, the WFD can be a very good policy aim to achieve the good water quality requested for sustaining the use of coastal lagoons in the long term. However, WFD is much more ambituous in scope than the abovementioned policies aiming at protecting the human populations against consumption of unhealthy fisheries and aquaculture products. Therefore, WFD request a more elaborate assesment scheme for describing the ecological status (see chapter 2) than provided by the sanitary classes mentioned before. Monitoring based on use of ecological indicators is therefore an essential methodology. So far (2006), the EU countries have not yet fully approved the indicators that should be used for assessing the ecological status of transitional and coastal waters. Therefore, some basic scientific research is still needed to understand the meaning of the different indicators and finally the application and interpretation needs to be homogenised among the member states by an intercallibration excercise. Nonetheless, the monitoring programme of coastal lagoons in the Languedoc-Roussillon region is a very good example of how policies in the regions and counties of the E.U. are currently providing the tools for the implementation of the WFD. For the Bassin d‘Arcachon the implementation of criteria for WFD are still preliminary (see Box 1). At the local level it is realised that all measurements aimed at improving the water quality in the Etang de Thau will also allow to decrease the faecal pollution and finally allow to class this environment as A for shellfish farming. Such a classification has an immediate impact on the commercial value of the oysters and therefore, policies to improve water quality receive strong support from the shellfish farming branch and a ―réconquête‖ of class A classification is now a strong political objective in the Région Languedoc-Rousillon. The Bassin d‘Arcachon lagoon is favourable for the reproduction of oysters and the oyster farming branch has taken advantage of this phenomenon to specialise in breeding the juveniles for other oyster-farming regions (see Box 2). For example, 1998 was a particularly bad year for the reproduction of the oysters. This
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raised a lot of public concern and environmental degradation was invoked as a possible explanation (see Box 2). Thus, water quality management is paramount in the context of environmental management for sustainable use. However, this needs to be completed with sustained action to ensure the conservation of different habitats or to allow for the development of ecological potential. This combined approach is the objective of WFD and in this chapter we will focus on the different aspects. Primary producer communities have been particularly proposed for elaborating ecological evaluation index (Orfanidis et al., 2003). This is based on the observation that ecosystem shifts can be evaluated from primary producer communities (see above cf. Figure 2, De Wit et al., 2001 and references cited therein). Accordingly, all seagrasses and a selection of seaweeds were considered as indicators for the pristine ecological status, while opportunistic algae mainly those including with sheet-like (e.g. Ulva and Monostroma spp.) and filamentous thalli, were considered as indicative of a degraded environmental status. The monitoring programme of coastal lagoons in the Languedoc-Roussillon region (S. France), which is coordinated by Ifremer, Sète and includes the Etang de Thau, uses a combination of different characteristics to classify the ecological status of the lagoons (website: http://rsl.cepralmar.com/intro_01.html in French). In addition to primary producers (macrophytes and phytoplankton), this programme takes into account the biogeochemistry of the sediments, physicochemical features of the water column and macrofaunal assemblages. Accordingly, most of the Etang de Thau including those where are located the oysterparks has been classified as moderate and a small part in the center as good.
3. WATER FLOWS IN COASTAL LAGOONS AND MANAGEMENT OF THE WATERSHED The marine connection between the coastal lagoon is maintained by inlets or tidal channels, which are called grau on the Mediterranean coast and les passes for the Bassin d‘Arcachon. The Etang de Thau is connected to the sea by the canal of Sète (90% of exchanges) and by the Grau de Pisse Saumes (10% of exchanges), located in the northern and southern parts, respectively (see Figure 1). Tidal movements of the coastal sea will propagate through the tidal channels into the lagoon. Tidal amplitude has been used to characterize coastal lagoons viz. macrotidal lagoons have a tidal range between 4 and 6 m, while mesotidal and microtidal lagoons have amplitudes ranging between 2-4 and 0-2 m, respectively. The Bassin d‘Arcachon is a mesotidal lagoon (mean tidal range 3 m) and the Etang de Thau is microtidal, but considered as ―non-tidal‖ in the frame of the WFD, because the tidal difference is less than 0.25 m. In the Mediterranean, microtidal lagoons, with a tidal range close to 1 m, are only found in the North Adriatic. Flushing is the process by which a certain volume of water leaves the lagoon and is replaced by water from another source. Tidal flushing is the predominant flushing mechanism in the Bassin d‘Arcachon. However, flushing can also be induced by other mechanisms as for example it can be driven by wind or the consequence of freshwater inputs from the catchment. Understanding of flushing phenomena together with the knowledge of what is delivered to the lagoon from the watershed is most essential for water quality management in coastal lagoons. A first practical approach is provided by the Land Ocean Interaction in Coastal Zone (LOICZ) procedure. However,
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coastal lagoons do not behave as continuously stirred homogeneous reactors and the extent of freshwater inputs and flushing phenomena are very variable in space and in time. Therefore, a more detailed knowledge of water movements and dilution of water masses requires detailed hydrodynamic modelling. Detailed 3-D hydrodynamic models do exist for the Etang de Thau (MARS 3D) and have recently been developed for the Bassin d‘Arcachon. Due to these heterogeneities, the distribution of nutrient loading from the watershed into the Bassin d‘Arcachon is very different due to hydrodynamics and accordingly three hydrological sectors have been distinguished. The W sector and the center of the lagoon are most strongly influenced by tidal flushing. The SE sector of the lagoon directly receives the highest nutrient loadings and is characterised by relatively long residence times (up to 3 weeks) and therefore most prone to eutrophication phenomena. Indeed this sector was characterised by dense blooming of the macroalga Monostroma obscurum in 1992 and 1993. This macroalgae is notoriously nitrophilous (nitrogen loving), which reflects that since the end of the 1970‘s the N/P ratio has strongly deviated from the Redfield ratio in favour of N. Nowadays, total nitrogen inputs into the lagoon fluctuate among years corresponding to average loadings of 60 to 120 kg N ha-1 year-1. The 3000 km2 watershed of the Bassin d’Arcachon is dominated by sand soils of pleistocene origin which are typical for the Les Landes system. The average slope is as low as 0.25 % and land-use is dominated by forestry (84 % of the surface), mainly pine trees. While intensive agriculture occupies only 11 % of the surface in the watershed, this activity contributes more than 65 % of the nitrogen input into the lagoon. In total ninety percent of the nitrogen input into the lagoon comes from runoff, while 9 % corresponds to atmospheric deposition and about 1 % enters through ground water flow. Agricultural inputs are dominated by nitrate (90 % of total nitrogen), while forestry releases mainly organic nitrogen (70 % of total nitrogen). Nitrogen abatement is very low in the surface fresh water systems, because of short residence times, and low aquatic primary production due to acidity and humic substances of the water. In contrast, the freatic environment has the capacity to denitrify provided that organic matter input is sufficient. Hence, nitrogen abatement has been observed in waterlogged sand soils in buffer zones surrounding some of the agricultural areas (De Wit et al., 2005). In conclusion, this watershed is extremely sensitive to land use changes. Therefore, local policies have arrested the increase of agricultural area for the time-being, since it can be expected that an increase in agricultural surface will proportionally increase the N-loading to the lagoon thus increasing risk of eutrophication. One hundred percent of the urban wastewater from the entire urban zone encircling the Bassin d‘Arcachon is nowadays collected in a collectively operated wastewater collection system and directly diverted to the open ocean after treatment. Thus, household and industrial wastewater from this zone stopped contributing to contamination and nutrient loading of the lagoon since the early 1980‘s. In the remaining rural area (6,000 inhabitants) wastewater is treated in different autonomous wastewater treatment plants, which constitute point sources of N and P and faecal bacteria in the watershed. The wastewater treatment resulted in a strong reduction both of the phosphorus loadings and of the faecal contamination. Until 2002, there were no problems with faecal contaminations in the Bassin d‘Arcachon, but in 2003 higher levels were detected and the Bassin d‘Arcachon was even provisionally placed in category B for shellfish farming. In contrast to P, N delivery was not significantly reduced after the introduction of urban wastewater collection and treatment around the lagoon, because it mostly comes from agricultural diffuse sources. This resulted in an increase of the N/P ratio
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since the end of the 1970‘s largely above the Redfield ratio. Such phenomena favour the proliferation of nitrophilous (nitrogen loving) algae and could induce a shift towards phosphorus limitation of primary production. However, sediments may present a significant source of P and therefore exchanges of nutrients along the sediment water interface need to be studied in concert with the direct nutrient loading from the tributaries to characterise the limiting nutrients for primary productivity (see Box 3). The watershed of the Etang de Thau is about 280 km2. It is drained by numerous small streams which flows are intermittent due to the Mediterranean climate. The geology of this watershed is very contrasted: the northeast is mainly formed by karstic limestone while clay marls dominate the southwest. Land use in the watershed is mainly agriculture (vineyards). There are also industrial activities (agro-food and fertilizer industries) and increasing urbanisation. Approximately 80,000 people live around the lagoon, half of them in the town of Sète. However the population doubles during the summer. A strong demographic increase is still expected for the coming years, because this area develops as a suburban area for Montpellier. The urban wastewater is treated in different autonomous wastewater treatment plants, which constitute point sources of N and P and faecal bacteria in the watershed. Within the frame of the E.U. project DITTY a Decision Support System has been developed (http://www.dittyproject.org/etangDeThauPresentation.asp) to determine how investments can be optimized to get the highest increase in environmental quality. These are based on confronting the loss of income due to insufficient quality of oysters with the costs of improving the waste water treatment plants and finding their optimal locations.
4. IMPORTANCE OF INTERNAL PROCESSES IN THE LAGOON FOR MAINTAINING WATER QUALITY AND FOR PROVIDING HABITATS Figure 3 compares the link between primary producer communities in coastal lagoons with their impact on biogeochemical cycling and water quality. Rooted phanerogamms are perennials with slow growth rates. The growth rates peak during spring and early summer and the plants form continuously new leaves during that period. Some of the older leaves are shed, but before these are shed from the plants such leaves are impoverished in elements like N and P by translocation processes. Therefore, degradation of such leaves in the environment are slow. Standing biomass varies between 100 and to 200-400 g DW m-2 in winter and summer, respectively, with Ruppia attaining higher biomass densities than Zostera noltii (De Wit et al., 2001). Moreover, about half of the biomass of the plants occurs belowground as rhizomes and roots. The rhizosphere of these plants is an area of intense microbial activities showing important plant-microbe interactions. In the Bassin d‘Arcachon, nitrogen fixing bacteria are present in the rhizosphere, which seems to indicate an plant-microbe association particularly well adapted to N- deficient environments (De Wit et al, 2001 and references cited therein). Oxygen is released from these roots, which contributes to oxidation of the sediment. The moribund parts of the root system are an additional input of organic matter to the sediments, which occurs at depth. Due to the autotrophy of the plants, oxygen release
Environmental Management and Sustainable Use of Coastal… Rooted Phanerogamms high water column transparencies
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Planktonic microalgae and cyanobacteria
oxic well mixed fluctuating O2 decomposing anoxic
sediment oxygenation from roots
PO4 3- sequestered in the sediment
thalli
HS-, NH4+, organic N, PO4 3-
HS-, NH4+, organic N, PO4 3-
perennial life cycle low growth rates
seasonal life cycle high growth rates
short generation times high growth rates
high biodiversity shelter habitats for meiofauna
low biodiversity
low biodiversity
high pulsed input of OM at the sediment surface sulfate reduction
high pulsed input of OM at the sediment surface sulfate reduction
deep regular input OM sulfate reduction - trapping of sulfide with iron
Figure 3. Different communities of primary producers in coastal lagoons and their differential impacts on biogeochemical cycling and on water quality
from their root systems, the fact that half of the dead plant debris into the sediment is at depth and because of the nature of the plant debris, the surface sediments remain well oxidised. As a result, PO43-, HS- and NH4+ do not diffuse out of the sediment (see Box. 3). The highly structured plant canopies therefore have a strong positive impact on ecosystem functioning and can be considered as ecosystem engineers. They also create shelter habitats for meiofauna and small gastropods and thus contribute to maintaining high biodiversity. Floating macroalgae with sheet-like (e.g. Ulva and Monostroma spp.) and filamentous thalli (e.g. Enteromorpha clathrata) are capable of high specific growth rates and often show a clear seasonal dynamics. Thus for Ulva and Monostroma spp., growth rates are high during the end of the winter and in spring and as a result standing biomass may built up to values of 1,000 g DW m-2 or higher. In contrast to the phanerogamms, all their biomass is suspended in the water column or deposited at the sediment surface at low tides in intertidal areas. Within such dense beds extreme variations of oxygen occur during day and night time. Selfshading may become important and algae that are at the bottom may start to die off resulting in hypoxic or anoxic conditions in the lower part of the bed. This process finally provokes the death of the macroalgae and massive consumption of oxygen leading to a dystrophic crisis (see Box 3). The dead material settles on the top of the sediment surface. Therefore, microbial degradation processes are particularly intense in the surficial layers. This may result in diffusive transfer of PO43-, Mn2+, HS- and NH4+ from the sediment into the water column (see Box 3) with both toxic effects on biota (Mn2+, HS- and NH4+ ) as well as enhanced remobilisation of N and P (PO43-, and NH4+, respectively) for growth of primary producers. That latter phenomenon is an example of positive feedback which reinforces the maintenance of the macroalgal state of the ecosystem and makes a move (back) to the phanerogamm dominated state less likely. In addition, macroalgal dominated systems generally seem to have a lower biodiversity than the rooted phanerogamm dominated system, although this is not always the case.
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BOX 3. ROLE OF SEDIMENT PROCESSES AND RISKS OF DYSTROPHIC CRISES The sediments are an important biogeochemical compartment in coastal lagoons. Densities of microbes within sediments exceed the densities of pelagic (water column) microbes by orders of magnitude (i.e., typically 104). The organic matter inputs into lagoons and organic matter production in coastal lagoons is reminerilised mainly within the sediment compartment. This creates a high oxygen demand for the sediment, which drives a flux of oxygen from the water column to the sediment. Muddy sediments are almost impermeable, meaning that interstitial water does not move. Hence, soluble compounds, like dissolved oxygen, are transported by molecular diffusion only, which is a slow process. In contrast, sandy sediments are permeable and the interstitial water can move through the pores when it is forced by hydrodynamic pumping. This creates a convective movement in the sediment. In these systems the dissolved compounds are transported both by molecular difusion and by the convective currents, the latter may enhance the transport rates by orders of magnitude. At a certain depth in the sediment, the delivery of oxygen is insufficient to supply the oxygen for mineralization processes and the sediment becomes anoxic. In the muddy sediments of the Etang de Thau and the Bassin d‘Arcachon, oxygen penetration depths, which have been measured with oxygen micro-electrodes, typically ranges from 1 mm to 4 mm depth. A suite of compounds including NO3-, Fe3+, MnO2, SO42- and CO2 can be used as electron acceptors for bacterial mineralization as an alternative for oxygen, which are reduced to N2 or NH4+, Fe2+, Mn2+, HS- and CH4, respectively. Because sulfate concentrations are very high in marine systems (i.e. 28 mM at 37 salinity), the process of sulfate reduction (see Figure 4) is quantitatively very important and may represent 50 % or more of the total organic carbon remineralisation. The reduced compounds NH4+, Mn2+, and HS- are noxious for most of the water colum biota and their efflux into the water column is therefore undesirable. A high efflux of HS- and H2S into the water column will create a so-called dystrophic crisis that is characterised by fish and mollusc mortality. Fortunately, under balanced conditions, these reduced compounds are oxidised in the superficial layers of the sediments. Such balanced conditions are typical for the phanerogamm beds due to a combination of factors (see Figure 3). First of all, growth of phanerogamms is slow and more spread out in time than the seasonal growth of the nitrophilous macroalgae; as a result detritus inputs (organic matter) occurs at a lower rate than during the collaps of an macroalgal bloom. Secondly, phanerogamms often have about 50 % of their biomass below ground as roots and rizomes and dead parts of these organs contribute to organic matter input deeper into the sediment thus not impacting the superficial layer. Thirdly, many phanerogamms may excrete oxygen from their roots systems and thus contribute to increase the transport of oxygen into the sediment. It is also most important to consider how the sulfide (HS- and H2S) interact with the rest of the sediment microbiology and geochemistry. HS- and H2S can be oxidised as mentioned before in the superficial layers by sulfur-oxidising bacteria that consume oxygen; however, in addition specialised sulfur-oxidising bacteria can oxidise these compounds in a chemical reaction with nitrate as the electron acceptor and others in a
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Binds phosphates
Iron III + O2 or + NO3-
sulfur oxidation + O2 or + NO3-
S sulfur
SO42-
Fe 2+ + O2 or + NO3-
photons : h. H S <-> HS-+H+ 2 free sulfides
sulfate
Sulfate reduction
Iron II
FeS iron sulfide
FeS2 pyrite
Figure 4. Interactions between sulfur cycling and iron chemistry in the sediment. From De Wit et al., 2001, reproduced with permission of Elsevier
photosynthetic reaction using light. HS- and H2S can also be sequestered in the sediment by reaction with iron forming ironsulfide (FeS) and pyrite (FeS2). However, iron is also important for sequestering phosphates by a reaction that occurs in the aerobic part (see Figure 4). Hence, through redox conversion, sulfide and phosphate may compete for binding with iron and as a result under highly reducing conditions with a high amount of HS- and H2S in the sediment, the phosphate can be liberated from the iron complexes and flux as ortho-phosphate into the water column. Such a phenomenon will enhance the eutrophication of the water column, that might induce a shift in the primary producer communities (see Figure 3). Hence, excessive reduction of sediments followed by a dystrophic crisis may induce dangerous postive feedback loops that stabilise the system in a undesired state characterised by a high level of eutrophication, loss of phanerogamm species and frequently occurring dystrophic crises. In this respect, systems that are poor in iron are more sensitive towards this phenomenon campared to iron rich systems. In general for understanding the water quality it is necessary to gain some insight into the functioning of the sediments.
Another possible state of the ecosystem is a turbid water column dominated by phytoplankton species. In hypertrophic freshwater systems and in some brackish lagoons on the Baltic coast filamentous cyanobacteria are forming dense blooms in the water column and present a nuisance. This represents a particular risk factor for ecosystem health since many of these planktonic cyanobacterial species produce toxins. Fortunately, these species do not resist salt concentrations above 10. In some hypertrophic lagoons, small Chlorophycean phytoplankton may develop very high biomass densities as e.g. in the Etang de Maugio located to the East of the Etang de Thau. The high turbidity of the water column is strongly detrimental to the phanerogamms. Oxygen concentrations may change significantly between
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day and night time. The dying algae are an important input of organic matter to the ecosystem and their degradation may take place in the water column or in the very surficial layers of the sediment. The abovementioned shows that an antagonistic relationship may exist between phytoplankton and rooted phanerogamms and that the community dominated by the rooted phanerogamms represents a more-appreciated ecosystem state. However, one should realise that the oyster farming activity drives on the use of natural phytoplankton as a food source for the oysters. Hence, while it is absolutely necessary to prevent the phytoplankton dominated state of the ecosystem, a certain level of productivity of the lagoonal phytoplankton needs to be guaranteed to sustain the productivity and reproduction of the oysters (see Box 2). It is not unlikely that under fully pristine conditions, i.e. the reference state for the WFD, phytoplankton productivity was insufficient for sustaining the oysterfarming yields obtained nowadays in both lagoons. Therefore, coastal zone management needs to find a balance between favouring sufficient phytoplankton growth for sustaining the productivity of the oyster farming and the conservation and restoration measures aimed to restore good ecological state for the ecosystem close to the reference state. Unfortunately, little research has been performed on the direct interactions between seagrasses and phytoplankton. This contrasts with the study of the interactions between seagrasses and macroalgae where a large body of information is available nowadays (Valiela et al., 1997). Sediments represent a particularly important ecosystem compartment in coastal lagoons. These represent the habitat for the benthic community, are chemically enriched and capable to store both the elements which are essential for primary productivity as well as the noxious compounds. Sediments are real biogeochemical reactors responsible for the mayor part of the remineralisation of organic matter. In addition, several of the material cycles interact within sediments. Therefore, the sediment processes are dealt with in a special Box (i.e. Box 3)
5. EFFECTS OF THE CLIMATE CHANGE ON THE COASTAL LAGOONS The coastal lagoons as well as the other aquatic ecosystems are submitted to the global change however, regarding their geographic position between land and sea and their confinement and shallowness water, the coastal lagoons could be more sensitive than the adjacent sea. The changes of several variables issues of global change such as temperature, wind direction and precipitation regime, ultraviolet-B radiation, sea level, CO2 concentration can drastically modify the functioning of the coastal lagoons. For example, increasing CO2 concentration results in proton addition to the water (dissociation of the weak acid H2CO3) and may therefore induce a decrease of pH with a negative impact on biocalcification. Sealevel rise in coastal areas will have a dramatic negative effect on intertidal areas and particularly the morphometry of the coastal lagoons will be strongly affected. Colectively, these changes influence primary production rates, bacterial growth rates, biogeochemical cycles, structure of food web and finally the exploitable resources of the lagoons. Water temperature increase is probably one of the most important variable that can be affected the functioning of the coastal lagoons. The lagoon species are adapted to a high variation of water temperature especially in the Mediterranean climate, however if the water
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temperature increases more than the optimal level of tolerance by these species, the food web structure will be modified. Any changes of food web structure can significantly modify the exploitable resources of the coastal lagoons. Economic activities as e.g. oysterfarming depend directly on the ressources of the lagoon. In general, all socioeconomic activities are directly or indirectly related to these resources and to the biological components of lagoons. It should be noted that the increase of water temperature during a short period (several years) can be beneficial for the exploitable resources in the lagoons; however, the prevision (quantification) of combined effects of several variable changes is very difficult consisting a challenge for researchers working on. These potential changes and complexity of the ecosystem responses should be considered in the management of the coastal lagoons. This can be addressed with reference to an integrated coastal zone management (ICZM) approach (Clark, 1992).
6. CONCLUSION AND PERSPECTIVE Water quality management is paramount for sustainable use of coastal lagoons and particularly crucial for aquaculture activities as oyster farming. The water quality management should, however, not be limited to sectorial policies, but rather be elaborated as an integrated approach considering the entire ecosystem. This is most important because causes and effects are coupled at different spatial and temporal scales, as e.g. demonstrated by the coupling between land use in the watershed and nutrient loadings into the lagoon. In addition, internal processes in the lagoon ecosystem have a large impact on water quality. In this respect, measures to protect seagrass meadows are particularly important for ecosystem health. The European Water Framework Directive appears as a very good framework to achieve these goals, particularly because it requires an integrated approach and focuses on ecosystem functioning for water quality management. However, these developments should also be considered with respect to climate change and sealevel rise. Ecological and socioeconomic spatial consideration should be taken into account to define the boundaries of the coastal lagoons ecosystems. However, historically, the administative and political boundaries (municipalities, counties, regions and countries) do often not concur with the natural boundaries needed to manage lagoons in an efficient way and complicated interadministrative collaborations are often requested. Due to the diversity of the ―exploitation patterns‖ of the coastal lagoons, the boundaries of the management unit (or for the conservation of Transitional and Coastal waters in the frame of WFD) should be ideally that of the area wher the conflicts and interactions levels are the highest. For example, on one hand, the management area of a lagoon includes also the related watershed. On the other hand, if the coastal lagoon shows evidence of interaction with resources from the oceans and/or the EEZ (Exclusive Economical Zone) (e.g. migratory species such as snapers or seabream, the LME concept (large marine ecosystem) (Sherman et.al., 1990) should be applied.
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REFERENCES Alzieu, C. (2000). Impact of Tributyltin on marine invertebrates. Ecotoxicology, 9, 71-76. Auby, I. & Maurer, D. (2004). Etude de la reproduction de l'huître creuse dans le Bassin d'Arcachon- Rapport final. R.INT.DEL/AR 04.03, 201, + Annexes. Barnes, R. S. K. (1980). Coastal lagoons; the natural history of a neglected habitat. 106. Cambridge University Press, Cambridge. Bettencourt, A., Bricker, S. B., Ferreira, J. G., Franco, A., Marques, J. C., Melo, J. J., Nobre, A., Ramos, L., Reis, C. S., Salas, F., Silva, M. C., Simas, T. & Wolff, W. (2003). Typology and reference conditions for Portuguese transitional and coastal waters, Development of Guidelines for the Application of the European Union Water Framework Directive, INAG/IMAR (2003) 98 pp.. Borja, A. (2005). The European water framework directive: a challenge for nearshore, coastal and continental shelf research, Continental Shelf Research, 25, 1768-1783. Clark, J. R. (1992). Integrated management of coastal zones. FAO Fish. Tech. Report, 327, 167. De Wit, R. Stal, L. J., Lomstein, B. Aa., Herbert, R. A., Van Gemerden, H., Viaroli, P., Cecherelli, V. U., Rodríguez-Valera, F., Bartoli, B., Giordani, G., Azzoni, R., Schaub, B., Welsh, D. T., Donelly, A., Cifuentes, A., Antón, J., Finster, K., Nielsen, L. B., Underlien Pedersen, A. G., Turi Neubeurer, A., Colangelo, M. A. & Heijs, S. K. (2001). "ROBUST: The ROle of BUffering capacities in STabilising coastal lagoon ecosystems. Continental Shelf Research, 21, 2021-2041. De Wit, R., Leibreich, J., Vernier, F., Delmas, F., Beuffe, Ph. Maison, H., Chossat, J. C., Laplace-Treyture, C., Laplana, R., Clavé, V., Torre, M., Auby, I., Trut, G., Maurer, D. & Capdeville, P. (2005). Relationship between land-use in the agro-forestry system of les Landes, nitrogen loading to and risk of macro-algal blooming in the Bassin d'Arcachon coastal lagoon (SW France). Estuarine, Coastal and Shelf Science, 62, 453-465. Kjerfve, B. (1994). Coastal Lagoons, chapter 1. In: B. Kjerfve, (ed.) Coastal lagoon processes. 1-8. Elsevier Oceanography Series, Amsterdam. Orfanidis, S., Panayotidisb, P. & Stamatisa, N. (2003). An insight to the ecological evaluation index (EEI). Ecological Indicators, 3, 27-33. Sherman, K., Alexander, L. M. & Gold, B. D. (1990). Large marine ecosystem : Patterns, processes and yields. American Association for the Advancement of Science, 242. Valiela, I. (1995). Marine ecological processes. Springer-Verlag, Berlin (ISBN: 3540943218) Valiela, I., McClelland, J., Hauxwell, J., Behr, P. J., Hersh, D. & Foreman, K. (1997a). Macroalgal blooms in shallow estuaries: Control and ecophysiological and ecosystem consequences. Limnology & Oceanography, 42, 1105-1118.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editors: Adam G. Friedman, pp. 351-370 ©2011 Nova Science Publishers, Inc.
Chapter 12
INVOLVEMENT OF LOCAL USERS IS THE OVERLOOKED BACKGROUND INFORMATION FOR IMPROVING IMPLEMENTATION OF CONSERVATION SOLUTIONS IN COASTAL LAGOON MANAGEMENT: THE CASE OF THE ICHKEUL NATIONAL PARK (TUNISIA) Caterina Casagranda* Marine Biologist Formerly of the UMR 6540 CNRS Dimar "Diversité, Evolution et Ecologie fonctionnelle marine", Centre d‘Océanologie de Marseille.
ABSTRACT The Garaet El Ichkeul in Northern Tunisia has long been recognized as one of the four major wetland areas in the Western Mediterranean basin (MAB Reserve in 1977, World Heritage and Ramsar site in 1980). The Ichkeul lagoon and its marshes perform essential ecological functions which are the basis of multiple services that contribute to the wellbeing and economy of the local community. The villagers living within the core area and the buffer zone have used to make a living off the land that did not seem to pose any threat to the functions and services of these ecosystems. However, the construction of dams on the rivers which provide water for the lake and marshes, as planned by the Tunisian Ministry of Agriculture for the purposes of agricultural, urban and industrial development, has had an impact on the ecological character of the site. The Tunisian authorities, aware of the impact of these dams on the natural environment at Ichkeul, founded a National Park. Unfortunately, the Park regulations were introduced without taking properly into account the reality of the socio-economic conditions of local residents. The lack of rehabilitation measures forced the villagers to
* 6a, rue Crudère, F-13006 Marseille (France), e-mail: [email protected]
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Caterina Casagranda exploit the resources in a non-selective way, which in turn further aggravated the existing pressure on the Park and the precarious social conditions in which the families survive. An international multidisciplinary study of all biotic and non-biotic aspects of the National Park drew up an integrated management plan which was designed to take into account the socio-economic development of the region. Since then, a number of conservation measures have been adopted by the Tunisian authorities. They mainly take into account the flora and fauna but without consultation of the people affected by these measures – a fact that possibly explains the limited implementation of the management plan proposed by the multidisciplinary study. The question is of more than local interest, since similar problems arise throughout the Mediterranean and elsewhere, i.e. conservation measures have been introduced but the legislation is not respected in practice. When stakeholders are not involved initially or are brought into the process at a later date, without the opportunity to provide input, they are seldom supportive of the policy outcome. This is due in large part to the continued reluctance of natural scientists and developers to learn from local community practices, as opposed to management systems established on the basis of scientific facts. However, recent studies on traditional ways of living off the land claim that the local communities have developed elaborate processes for sustainably exploiting their resources. Such practices can provide an important information base for integrated resource management. The goal is: (1) to promote recognition of the traditional resource practices and the accumulated wisdom as important features within ecological research, and (2) to stimulate debate about whether their input will have significance for improving environmental management policy.
1. INTRODUCTION Historically, agriculture and urbanization have been the chief destroyers of ―useless‖ swamps and lagoons since these ―dirty‖ and ―smelly‖ places full of ―snakes‖ (i.e. eel) and mosquitoes are impossible to plow or build upon. So why not get rid of them ? The Mediterranean countries are characterized by their high attractiveness for tourism and many governmental programs have encouraged the transformation of coastal lagoons and wetlands into exploitable land or waters. As a consequence, many Mediterranean shores have suffered from draining, dredging, dike building, mining for sand and gravel, ditching, road building for the extension and development of seaside resorts (marinas, artificial beaches) (Meinesz et al. 1991) because they had been seen as having little value. Human communities, which rely directly on lagoonal resources for subsistence, do not necessarily share this view and often have a detailed understanding of the goods and services such areas may provide. Since the mid-twentieth century, scientific research on the functioning of lagoons has led to a change of attitude. These literally ―wet lands‖ are transitional zones between terrestrial and aquatic systems. They perform far-reaching functions within the ecosystem itself and as pathways between land, freshwater habitats and sea (Levin et al. 2001). These essential ecological functions provide services which contribute to human wellbeing and the economy. Scientific acknowledgement of their value has led to an intensification of impact assessments in the Mediterranean and elsewhere, but broader application of mitigation and restoration plans remains difficult. At Ichkeul (Tunisia) (Fig. 1), the most spectacular illustration of its natural functions and services are the 150 000 - 250 000 wintering Palaearctic waterfowl present there at one time
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(Tamisier et al. 1987). The high identified value of Ichkeul is reflected in its exclusive listing in three international conventions: (1) Biosphere Reserve in 1977 (UNESCO 2010); (2) World Heritage Convention in 1980 (UNESCO World Heritage Centre 2010) and (3) Ramsar Convention in 1980 (Ramsar Convention & Wetlands International 2010). The documents presented at the time of Ichkeul‘s inclusion in these international conventions noted that the construction of 6 dams on the wadis (i.e. temporary rivers) which provide freshwater for the lake and marshes, as planned in the ―Master Plan for the Waters of Northern Tunisia‖, was likely to have an impact on the ecological character of the site. The Ichkeul National Park was formally founded in 1980 by presidential decree and an international multidisciplinary research programme entitled ―Etude pour la Sauvegarde du Parc National d‘Ichkeul‖ (BCEOM et al. 1994, 1995) drew up an integrated management plan. A number of measures have been adopted by the Tunisian authorities which are essentially a response to the primary concern of the MAB-Programme, i.e. the objective of conservation of the flora and fauna. However, the wider implementation of the management plan still remains difficult (Baccar et al. 2000).
Figure 1. The Ichkeul National Park (Tunisia) and its catchment.
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About 350 people live within the core area of the reserve who made a living off the land in a way that did not seem to pose any threat to the integrity of the ecosystem (Muller 1976, Hollis 1977, Hollis 1986, BCEOM et al. 1994). Nevertheless, the local population affected by the conservation measures has not been involved in the process of identifying problem areas a fact that possibly explains the limited implementation of the management plan proposed by the Safeguard study. The National Park regulations have been imposed on local communities from above and the lack of rehabilitation measures forced the villagers to exploit the resources in a non-selective way, which in turn further aggravated the existing pressure on the Park and the precarious social conditions in which the families survive (BCEOM et al. 1994). The question that arises is: Is traditional resource use the overlooked management tool for improving coastal lagoon conservation ? The Park is still perceived by the local residents and stakeholders as a burdensome collection of prohibitions. Rural communities and their knowledge of the resource, which receive little attention in management planning, will be the focus of this presentation. The question is of more than local interest, since similar problems arise throughout the Mediterranean and elsewhere, i.e. conservation measures have been introduced but the legislation is not respected in practice. In this presentation, I describe the natural functions and services of the Ichkeul ecosystem, with particular reference to local resident communities, and their social and practical usefulness. I then examine the economic, ideological and institutional factors that combine to perpetuate the marginalisation and neglect of local knowledge, and discuss some of the requirements for applying local knowledge in modern management. The paper brings together a fair amount of hitherto dispersed and unpublished information which is not easily available to international readers.
2. GEOGRAPHICAL CONTEXT The designation ―Biosphere Reserves‖ refers to a mosaic of habitats. The Ichkeul National Park is made up of three major landscape units that include a particularly diverse variety of habitats: [1] A permanent shallow brackish water lake in northern Tunisia, with an area of 90 km² , connected to the marine lagoon of Bizerte by a small winding channel, improperly referred to as Tinja wadi (i.e. temporary river) Fig. (1). [2] Temporarily flooded marshes of an area of about 36 km². The region has a typically Mediterranean semi-arid climate which leads to a temporary drying out of the marshes during the summer (Fig. 2). [3] The isolated and wooded djebel (mountain in Arabic) rising on the southern shore of the permanent lake.
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Potamogeton pectinatus meadow Ruppia cirrhosa meadow Phragmites australis reed
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Scirpus maritimus rush Bare bottom
National Park limit
Figure 2. Schematic annual alternation of surface and water level at Ichkeul lagoon (Tunisia) under predammed conditions. Maximum water depth in winter: 2-3 m with all marshes inundated, in summer 1m with all marshes dried up.
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3. ECOSYSTEM FUNCTIONS Ecosystem functions refer variously to the habitat, biological or system properties or processes of ecosystems. Coastal lagoons and wetlands are critical transition zones (CTZ) that link terrestrial and aquatic systems (Levin et al. 2001). They perform essential ecological functions, including decomposition, nutrient cycling and production, regulation of fluxes of nutrients, water, particles, and organisms to and from land, freshwater habitats and sea. Ecological functions at each wetland depend on its location, size, and relationship to adjacent land and water areas. By analogy to Levin et al. (2001), functions at Ichkeul are performed as follows:
3.1. Within the Ecosystem Itself Primary and secondary production.- Coastal wetlands and lagoons are among the most productive natural systems in the world. Global contributions are proportionally much greater than might be expected from their small coverage area (Costanza et al. 1997). At Ichkeul, phytoplankton density was found to be remarkably low, with < 1.5·106 cells/l (BCEOM et al. 1995). Macroalgae were locally and temporally limited to the north-eastern border in autumn (BCEOM et al. 1995). Both groups were considered negligible as primary producers. The primary producer that fuels secondary and higher order production at Ichkeul are seagrasses (Casagranda & Boudouresque 2007). The western and southern areas, supplied with freshwater from the wadis, are covered by extensive monospecific beds of Potamogeton pectinatus L., 3050 and 690 ha respectively (Casagranda & Boudouresque 2007). The eastern area close to the Tinja channel and supplied with seawater is covered by a meadow of Ruppia cirrhosa (Petagna) Grande (300 ha). The central area (4960 ha) is completely free of vegetation (Casagranda & Boudouresque 2007). The mean primary production was very high (Table 1), at 203 g dry mass (DM)/m² (Casagranda & Boudouresque 2007). The total primary production extrapolated over the whole lagoon surface (9 000 ha) would amount to 18 233 tDM. The keystone process that channels the energy fixed in the biomass through the ecosystem is the primary consumption, i.e. it determines how much of this energy enters the herbivore and/or the detritivore pathway. By analogy to Asmus (1987), the macroinvertebrate consumers can be divided into 2 functional compartments at Ichkeul: [1] a ―turnover compartment‖ that consists of shredders and epibenthic deposit feeders. The species are characterized by relatively low production, high P/B ratio (Table 1) and are subject to strong predation. The production is mainly transferred to higher trophic levels. This compartment governs the decomposition and nutrient transfer in the community. [2] A ―storage compartment‖ that consists in the case of Ichkeul of endobenthic deposit feeders. These species are characterized by high production, low P/B ratio (Table 1) and are subject to only little predation. The production is mainly sequestrated within the ecosystem leading to further biomass increase. This compartment governs the nutrient and oxygen conditions for the community.
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Table 1. Mean primary producer and macroinvertebrate consumer biomasses of the Ichkeul aquatic ecosystem. DM = dry mass, AFDM = ash-free dry mass. Functional group
Mean biomass
Mean production
Seagrass
125 gDM/m²
203 gDM/m²
Shredders <1 gAFDM/m² 1 gAFDM/m² Epibenthic deposit 4 gAFDM/m² 12 gAFDM/m² feeders Endobenthic deposit 20 gAFDM/m² 8 gAFDM/m² feeders
Turnover Lagoonwide P/B production 2 2 3 <1
Data source Casagranda & Boudouresque 18 233 tDM 2007 96 tAFDM Casagranda et al. 2006 1 067 Casagranda et al. 2005 tAFDM Casagranda & Boudouresque 741 tAFDM 2005
Decomposition and nutrient recycling.- Seagrass beds produce large amounts of dead plant material (litter). In autumn, thick layers of dead vegetation pile up all along the southern shores after collapsing and becoming detached. The mean litter biomass buried in the sediments ranges between 92 and 138 g DM/m² (Casagranda & Boudouresque 2007). The organic matter is rapidly incorporated into a complex decomposer food web. A significant proportion (10-25 %) of the plant material leaches out of plants as dissolved organic matter during the first few weeks after death (Fenchel 1977). The senescent plant parts are rapidly colonized by microscopicalgae, aquatic microbes and microfauna (Fenchel 1977). Shredder species which graze on the leaf surface ―fouling‖ (Graça et al. 2000), facilitate the mechanical breakdown by scraping and shredding (Newell & Bärlocher 1993) and enhance the nutrient transfer to higher trophic levels (Lillebo et al. 1999). Litter bag experiments by Verhoeven (1980) showed how important shredding and grazing invertebrates were for macrophyte decomposition. He found that half of the material had decomposed within two months and that after a year practically no plant material was left. High rates of decomposition are critical to the sustained functioning of coastal lagoons. No accumulation of organic matter, algal blooms or summer anoxia characteristic for eutrophic lagoons have ever been reported from Ichkeul (Chaumont 1956, Zaouali 19974, Dridi 1977, Hollis 1986, Tamisier et al. 1987, Ben Rejeb-Jenhani 1989, BCEOM et al. 1994, 1995, Casagranda 2005 and many other unpublished reports).
3.2. Pathway Functions that Connect and Transfer Water, Material, and Organisms between Land and Sea Mixing of water and salt.- Garaet El Ichkeul was a freshwater lake (―garaet‖ means freshwater basin in Arabic) before the deepening and widening in 1881 of the canal linking Bizerte lagoon to the sea (Fig. 1). It has been characterized since then by the alternation of fresh water in winter and brackish water in summer. Until the early 1990s, it was filled up in winter with freshwater from direct precipitation and from the drainage basin by 7 wadis (i.e. temporary rivers) that overflowed into the Bizerte Lagoon. In summer, high evaporation lowered the water level and allowed saline water to enter the lake. Its surface varied considerably between summer and winter: from 80 to 90 km² in summer to 110 to 130 km² in winter with all marshes inundated. The freshwater output through the Tinja channel was 47 to 955·106 m3/a, the mean saltwater input was about 60·106 m3/a (Chaumont 1956, Hollis 1977,
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Lemoalle 1983a, BCEOM et al. 1995). The salinity displayed considerable seasonal changes from 3 in the innermost parts in spring to over 38 at the mouth of the Tinja channel in autumn (Lemoalle 1983b, Ben Rejeb-Jenhani 1989, BCEOM et al. 1995). Three dams have been constructed on the wadis providing Ichkeul with freshwater (Joumine in 1983, Ghezala in 1984 and Sejnene in 1994) while three more are planned on Douimiss, Melah and Tine (Fig. 1) in the ―Master Plan for the Waters of Northern Tunisia‖. The filling period of the Sejnene dam 1994 to 1998 fell unfortunately within a ten-year period of low rainfall. In addition to the reduced inflow from the catchment, there was also an increased backflow of saline water from the Bizerte Lagoon. As a result, the salinity of the lake in summer sharply increased sometimes reaching values over 60, hence twice the salinity of sea water (Dridi pers. com., ANPE 2010). The increased salinity caused the extirpation of P. pectinatus and a serious loss of biological diversity, especially of migrant waterfowl and fish (Shili pers. com., Shili et al. 2007). Reedfringe and freshwater macrophytes disappeared and rush beds were replaced by halophytic plants with a significant reduction of breeding birds that no longer had any nesting cover in the vegetation (Shili et al. 2007). By a stroke of good luck, the winters of both 2002/03 and 2003/04 were exceptionally wet for Tunisia, filling the dams to the extent that they overflowed into Ichkeul. These releases were in addition to inflow from the undammed rivers and direct precipitation. As a result, practically all the salt that had accumulated in the lake over the previous decade was leached out via the Tinja channel. The low salinity levels have allowed Potamogeton pectinatus to reappear in the lake, while rush stands have begun to grow again in the marshes (Shili et al. 2007). Nutrient transfer and transformation.- According to the eutrophication study of the OECD (Organisation for Economic Cooperation and Development) (Vollenweider & Kerekes 1982), Ichkeul can be considered as ultraoligotrophic in mean total nitrogen terms (Ntot , 21 μmoles/l) and hypertrophic in mean total phosphorous terms (Ptot , 4 μmoles/l) (BCEOM et al. 1995). BCEOM et al. (1995) reported low inputs from the western catchment and the Tinja channel, but high inputs from the southern catchment and internal supply. High organic N (Norg) values in the water column during autumn (156 mol/l) indicate inputs from seagrass meadow senescence. The water column of the southern basin is subject to high pollution-induced turbidity from municipal sewage from the town of Mateur through the Joumine wadi (Secchi depth less than 10 cm), essentially soluble reactive phosphorous (P-PO4, 102 mol/l) and ammonium (N-NH4, 1131 mol/l), i.e. the assimilable N and P fractions by plants. However, P-PO4 and N-NH4 levels in the water column of the lake were low (0.2 mol/l and 5.8 mol/l respectively) (BCEOM et al. 1995). Low P-PO4 and N-NH4 levels in the water column indicate macrophyte uptake; however, most P-PO4 and N-NH4 is supposed to be concentrated in the sediments. At Ichkeul, rapid elimination of P-PO4 from the water column by sediments has been demonstrated. Ben Rejeb-Jenhani (1989) showed that the Ichkeul sediments have high P-PO4 adsorption capacity. As the dissolved oxygen is in the range of 83-117 % of saturation, the BOD5 low (1.5-2.8 mg/l) and the redox potential high (370-400 mV) (BCEOM et al. 1995), P-PO4 storage in the sediments and N fixation rather than denitrification would be more likely. Under aerobic conditions and lack of assimilable N and P in the water column, sediments are the major nutrient source for seagrasses. Moreover, BCEOM et al. (1995) reported high outputs of organic N and N-NH4 through the Tinja channel, a factor that
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further aggravates the impoverishment of the lake water in nitrogen. Under pre-dam conditions, it can be postulated that seagrasses controlled P availability and suppressed lightlimiting phytoplankton blooms. Particle flows and pollutant transport.- According to Chaumont (1956), around 1 000 000 t of sediment can be transported into Ichkeul via wadi inflow and runoff from land, of which around 100 000 t would be evacuated via the Tinja channel (Lemoalle, in Ben RejebJenhani, 1989). In Roman times, the extension of the permanent lake was likely to be much greater than nowadays and the Djebel must have been an island (Chaumont 1956). Hollis (1986) reported a sedimentation rate of about 6 mm/a. Seagrass beds slow water flow, and enhance the deposition of fine particles and the trapping and transformation of pollutants (Fonseca 1996). The decline of the seagrass meadows in the 1990s and the construction and operation of the Tinja sluice in the summers to maintain fresh water in the lake may have had an impact on sedimentation patterns in the lake. Sediments, which would formerly have been carried away through the Tinja channel, may have been held back in Ichkeul by the sluice. It may be therefore that the depth of the lake is decreasing more rapidly, which might induce changes in the distribution and species composition of vascular plants and animals, water regime or flooding (Shili et al. 2007). The closing of the Tinja sluice is far from being a cheap solution in water quota terms since its operating is triggered by the water salinity and the levels measured. Organism movements.- Animals moving within or through CTZs are vectors that transport nutrients and organic matter across terrestrial, freshwater, and marine interfaces (Levin et al. 2001). The most spectacular illustration of this pathway function are the 150 000 - 250 000 wintering Palaearctic waterbirds present at one time which use the lake and marshes at Ichkeul. The high records of migratory birds, in particular ducks, coot, geese, storks and flamingos, indicate that Ichkeul is the most important wintering station in North Africa, i.e. 5 to 7 times more than any other site in the Western Mediterranean offering similar wintering conditions, such as the Camargue (France), the El Kala (Algeria) or the Coto Doñana (Spain) (Tamisier et al. 1987, Tamisier 1992, BirdLife International 2010). They use it in conjunction with other wintering or staging areas in the Mediterranean (Ramsar criteria 1, 3, 5 and 6). Extensive stands of rushes (Bolboschoenus maritimus (L.) Palla and Schoenoplectus lacustris (L.) Palla) in the surrounding marshes provide the major food source for a large population of greylag geese (Anser anser (L.)) (3 000). The annual trophic impact derived from migratory fish comes almost entirely from 3 euryhaline migrant species, the European eel Anguilla anguilla (L.) (―Anguille‖) and the mullet Liza ramada (Risso) (―Bitoum‖ in Tunisian) and Mugil cephalus L. (―Bouri‖). Other species such as Dicentrarchus labrax (L.), Belone belone (L.), Solea vulgaris (L.), Sparus aurata L. and Alosa fallax (Lacepède) account for this impact to a far lesser extent (BCEOM et al. 1995). Mullet fry and eel elver enter Ichkeul from the Tinja channel in spring, mainly in February and March, and feed and grow for a variable number of years, ranging from 3 to 5 years for the mullet and around 4 years for the eel (Casagranda & Boudouresque 2010) until sexual maturation, whereupon the fish leave the lake for spawning. In the macrophyte meadows there occur small sized eurybiont fish of short life and early sexual maturation such as Atherina boyeri Risso, Pomatoschistus microps (Krøyer), Aphanius fasciatus (Valenciennes), Syngnathus acus L. and Gambusia affinis (Baird & Girard), which do not migrate but spend their entire life cycle in Ichkeul. The species constitute the main
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prey of eel and seabass, and thus hold a significant position in the flow of organic material into and out of the ecosystem.
4. ECOSYSTEM SERVICES According to Costanza et al. (1997), coastal lagoons and wetlands cover less than one percent of the earth's surface, but are the source of one-6th of the world's productivity in monetary terms. Ecosystem goods (such as food) and services (such as waste assimilation) represent the benefits that human populations derive, directly or indirectly, from ecosystem functions. It is important to emphasize the interdependent nature of many ecosystem functions. In addition, ecosystem functions and services do not necessarily show a one-to-one correspondence. A single ecosystem service can be the product of two or more ecosystem functions whereas a single ecosystem function can contribute to two or more ecosystem services. Ichkeul has - in addition to its birds - numerous goods and values, marketed and non-marketed ones, that are given too little weight in policy decisions. The problem with nonmarketed ecosystem services is that the costs of degrading these resources are hidden. In the following section, I attempt to make the range of potential values of services more apparent. The goal is to help ensure that the absence of market value does not mean that the valuable services these resources provide are taken for granted since many ecosystem services are literally irreplaceable. Hydrological values.- The wetland is the last remaining site of a chain of freshwater lakes which once extended across North Africa (World Heritage‘s criterion iv). Lake Ichkeul acts as a waste water purifier, erosion control and sediment retention system, water storage basin, including mitigating the impact of floods and drought, and supply of groundwater reserves. The winter inflows flood the surrounding marshes, sediment and pollutants are trapped; soil particles bind with pollutants. The water slowly soaks into the ground. Bacteria in the water and soil neutralize wastes. This natural cleansing capacity performs entirely free of charge what engineers perform in exchange for thousands of dollars. The dense seagrass beds absorb nutrients and form the base of the food web. The slowed-down, cleansed water flows out through the Tinja channel but much of it percolates into the ground and recharges the groundwater that provides most of the drinking water. Economic resource.- The Ichkeul fishery, which is based on fish traps at the mouth of the Tinja channel linking Ichkeul to the Bizerte lagoon, is of some national importance. Mullet (M. cephalus, L. ramada) and eel (A. anguilla), making up 97 % of the catches, are easily captured on their leaving the lagoon for spawning via the Tinja channel (BCEOM et al. 1994). While the mullet are sold at the local market, the eel are not consumed in Tunisia (―snakes‖); the fishing rights are sold every winter to an Italian company. During winter 1993/94, the income from the eel alone was 763 000 TD ($ 586 000), and from the mullet another 381 000 TD ($ 293 000) (BCEOM et al. 1995). Biological reservoir.- The present aquatic and terrestrial flora and fauna of the area is recognized as being particularly diverse largely due to the wide variety of habitats. 500 plant species have been counted in the park. The main vertebrate and invertebrate fauna is typical of brackish water areas although on the edge of the salt marsh there are freshwater species. More than 185 bird species have been recorded (Tamsier et al. 1987). Waterbirds using Lake
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Ichkeul include grebe, cormorant, heron, ibis and spoonbills, stork, geese and duck, rail and coot, shorebirds, gulls and terns, and two raptors that are functionally linked to wetlands (the Western Marsh-Harrier Circus aeruginosus (L.) and the Osprey Pandion haliaetus (L.)) (Hollis 1986, Tamisier et al. 1987, Tamisier 1992). Total numbers were much higher in winter than during the breeding season and made up principally by three phytophageous waterfowl species, the Eurasian wigeon Anas penelope L., the common pochard Aythya ferina (L.) and the common coot Fulica atra L. In addition to these long-distance migrants, threatened and endangered species such as Marbled Teal (Marmaronetta angustirostris (Ménétriés)) rely directly on Ichkeul for their survival. The Purple Gallinule (Porphyrio porphyrio (L.)) breed at Ichkeul and up to 600 of the threatened White-headed Duck (Oxyura leucocephala (Scopoli)) (4 % of the known world population) have been recorded (Hollis 1977). Many species of raptor breed on the Djebel. The herpetofauna Rana ribibunda Pallas and Clemmys leprosa Schweigger can be found in the marshes and lake (Morgan 1982). One of the most notable of the mammals recorded at Ichkeul is the otter Lutra lutra L. (Hollis 1977). The site has internationally important mammal fossil deposits including late Tertiary and early Quaternary outcrops (Arambourg & Arnould 1949). The Djebel is composed of Triassic and Jurassic formations (Hollis 1986), mainly as metamorphosed limestone with pseudodolomitic marble correspondence including features of botanical interest and remaining a geological enigma since it bears little relation to other surrounding geological features. Cultural heritage.- Since antiquity, the lake, marshes and mountain have been settled and influenced by man, providing food (game, fish), and raw materials (reeds, peat). It is at the root of very strong cultural and social traditions. Native people at the djebel have traditionally raised cattle, sheep and goats, fished in the lake and worked in the quarries on the mountainside, exploited since Roman times. The hot springs at the foot of the Djebel attract many Tunisian visitors during spring. In Punic times, the site was a reserve for state hunting and the wild Asiatic water buffalo (Bubalus bubalis Kerr) is claimed to descend from herds kept as game animals (Müller 1970). Living laboratory.- An impressive number and diversity of studies have been carried out on Ichkeul: Heldt (1948), Chaumont (1956), Massin (1967), Jaeger (1971), Zaouali (1974), Dridi (1977), Ouakad (1982), Vidy (1983), Ben Rejeb-Jenhani (1989), Casagranda (2005) are only a few among many others. Some of the earliest scientific studies resulted from the palaeontological excavations in 1947-49 (Arambourg & Arnould 1949). A programme of waterfowl observational research has been under way since 1963 in collaboration with University College London (UCL) (UK), The International Waterfowl Research Bureau (IWRB) (UK) and the Tour du Valat Biological Station, Camargue (France). During the 1980s, a number of international research projects were carried out at Ichkeul in order to investigate the impact of the two dams and predict the likely impact of all six dams (Hollis 1986). The aim of these projects was to complement existing ornithological data with hydrological and macrophyte data. In 1993, the Safeguard Study, more thorough than the previous ones, of all biotic and non-biotic aspects of the National Park was launched to summarize the existing data, to model the functioning of the whole ecosystem and to devise an integrated management plan (BCEOM et al. 1995). An on-site technical team, based in the reception centre on the mountain, has since 1997 been monitoring a number of different parameters, both abiotic and biotic.
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Recreation.- The tourist potential of the National Park is high as the isolated and wooded djebel rising from the lake gives the site a singular natural beauty. It is very rare to find a rocky mountain rising from the middle of a wetland (World Heritage criterion iii). According to Lavauden (1937), ―Ichkeul‖ is probably derived from the Italian word for rock, ―il scoglio‖. Moreover, the presence of some 200 000 waterfowl during the winter is very spectacular even for visitors unfamiliar with bird watching. The number of annual visitors is estimated at 60 000, 90% of them Tunisians. An ecomuseum and a reception centre have been constructed with assistance from the British Museum of Natural History and the WWF to inform visitors about the values that explain its inclusion in three International Conventions. According to Costanza et al. (1997), non-extractive values of ecosystem resources, which range from the tangible (e.g., water buffalo as a lure for tourists) to the more abstract (e.g., the value of simply knowing that migrating birds exist, even if one does not ever expect to go bird-watching), can exceed the value of extractive uses like fishing.
5. IMPROVING REGIONAL EFFORTS IN LAGOON PROTECTION 5.1. Conflicts of Interest Human use of ecosystem services may or may not leave the original capital stock intact. At present, Ichkeul National Park is the focus of a number of different interests which come into conflict: water supply, conservation, agriculture, local residents and stakeholders. At site level.- The villagers living within the core area and the buffer zone of the Ichkeul National Park used to make a living off the land that did not seem to pose any threat to the ecosystem‘s functions and services (Muller 1976, Hollis 1977, Hollis 1986, BCEOM et al. 1994). The people traditionally used the marshes for grazing, fished in the lake and worked in the marble quarries on the south-eastern slopes of the Djebel, which have been exploited since Roman times. After the creation of the National Park in 1980, the regulations have unfortunately been imposed on the local residents from above without giving them the opportunity to find alternative ways of earning their livelihood or raising awareness of the need for conservation of the natural resource. The lack of alternative socio-economic proposals for the villagers directly affected by the Park regulations has led to the overexploitation of grazing on the Djebel and the marshes, and greater dependence on - prohibited - fishing and duck hunting within the reserve (Hollis 1986, BCEOM et al. 1994). The number of sheep and cattle on the Joumine marsh has increased very substantially since the 1980‘s and this area now is seriously threatened, although grazing of domestic stock did not appear to pose any threat to the ecological functions and services until then. Livestock not only consume the vegetation, they also tend to remain in the same area for an extended period of time. Their movements to and from riversides can create gullies and otherwise undermine the banks. While fishing seems to be limited in intensity and relatively few birds are killed, significant disturbance to the feeding waterfowl and destruction of surrounding vegetation occurs through repeated use of trails. The park director has watched that all households have at least one person in full time employment. Although the park wardens consider themselves fortunate to have a steady paying job, the low pay and the lack of equipment, status and social
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benefits has been frustrating (Yousef M. pers. com.). After writing appeals to the Ministry of Agriculture, their status has improved as the guards are no longer considered as ―day workers‖ and are eligible for social security benefits. Ironically, the activity of the quarries on the southern slopes of the Djebel, although well within the Park, did not seem to come into conflict with the Park status until the 1990s. Their extension and the intensification of quarrying seriously threatened the relatively luxuriant flora and fauna of the Djebel. Moreover, the dust and dumping caused pollution of the maquis and the marshes, and the fleet of heavy lorries had an adverse impact on the landscape and wilderness appeal of the Park for tourists. The political decision to close the marble quarries was only put into practice in 1994, some 14 years after the Park was founded. The call for restoration has been met by spraying of the surfaces of outcrops with green paint (Casagranda et al. pers. obs.). At government level.- In a country such as Tunisia, situated on the northern edge of the Sahara desert, water is a natural resource of prime importance for economic and social development. The need to obtain control over surface water resources and to move water around the country to wherever it is needed has been a national development priority since independence in 1956 (BCEOM et al. 1994). Another reason for developing the water control system was to reduce the impact of flash flooding. In September 1969, torrential rain in central Tunisia caused flash flooding in the plains downstream leading to loss of human lives and catastrophic damage to transport systems and other infrastructure. The massive downpour in Algiers (Algeria) in 2001 served as a reminder of this ever-present risk. The General Directorate for Hydraulic Studies and Works of the Tunisian Ministry of Agriculture developed ambitious plans, finalized in 1975, to build a series of interlinked dams on rivers in the well-watered north, six of them dams on rivers flowing into Ichkeul. These dams are the key element of the so-called ―Master Plan for the Waters of Northern Tunisia‖, i.e. a national water network which will provide water for agriculture, urban development and industry. Two of these 6 dams are of considerable size, the Sejnene dam and the Joumine dam, and the other four rather smaller (Fig. 1). During the 10-year period of natural and anthropogenic shortage of freshwater input to Ichkeul, the only possible solutions would have been water releases from the Sejnene and Joumine dams (Fig. 1). However, it would have been difficult to release water when farmers themselves are short of water, i.e. for ducks. - The Tunisian authorities decided to suspend the construction of the remaining dams on the other wadis Douimiss, Melah and Tine until the Sidi El Barrak dam, situated in a neighbouring catchment, became operational (Shili pers. com., ANPE 2010). It has further been decided to grant Ichkeul an annual water quota and to ensure this supply from the Sidi El Barrak dam as soon as it is linked to the Sejnene dam and from the three remaining dams once they have been built. However, no clear indication has been made regarding the amount of water to be supplied (Shili pers. com., ANPE 2010). As a practical measure, a sluice was built on the Tinja channel which would make it possible to maintain fresh water in the lake or to prevent the flow of saline water into the lake in summer (BCEOM et al. 1995). Another concern for the long term conservation of Ichkeul is the saga of the drainage canal on the Joumine marsh in the southern catchment (Fig. 2). The Ministry of Agriculture‘s General Directorate of Rural Engineering developed an agricultural improvement scheme in the Plain of Mateur adjacent to the Park that would involve irrigation of the higher fields of the Plain and the drainage of the low lying lands adjacent to the marshes of the National Park
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(Fig. 1). In addition, the plan involved the substantial use of agrochemicals that would be carried towards the lake. The Joumine drainage canal (Fig. 1) was formerly a winding wadi through the Mateur Plain, which was diverted and canalised for the last 200 m before the marsh fringes in the early 1950‘s. The canal fed into the Joumine marsh and spread its water over most of the marsh. This was subsequently incorporated into the National Park in 1980 (Tamisier pers. com., Hollis 1977). In the autumn of 1981, i.e. one year after the foundation of the Park, the existing canal was extended for 2 km to the very edge of the lake. This was done without consultation with the Park authorities (Tamisier pers. com., Hollis 1986). The reduced water level led to the drying out of the marshes while the lack of freshwater flooding restricted vegetation to salt tolerant plants. Before the digging of the drainage canal, the grazing of the cattle did not appear to be a threat to the ecological ―health‖ of the marsh since the previously existing reed beds made it inaccessible to domestic livestock (Tamisier pers. com.). The filling of this drainage canal has been agreed to by all parties in the Ichkeul Coordinating Committee since 1984 (Hollis 1986) but no action has been taken by the General Directorate of Rural Engineering because the filling of the canal may interfere with the drainage for the Plain of Mateur. The interest of General Directorate of Rural Engineering as a land drainage organisation is to keep the lake level as low as possible throughout the winter months. A step towards closer collaboration between different arms of decision has been taken with the merging of the Ministries of Agriculture and Environment into a single Ministry of Agriculture, Environment and Water Resources. At international level.- The Safeguard Study (BCEOM et al. 1995) identified a number of measures and drew up an integrated management plan for the Park, taking account of its regional economic context. Studies of this kind, i.e. where both biotic and abiotic data are assessed simultaneously in a single survey, are very rare in scientific literature. The study clearly demonstrated that water releases from the dams would be required if the main elements of the ecosystem were to be conserved and drew particular attention to the filling of the drainage canal at Joumine to ensure the effectiveness of the water releases. Despite a certain number of policy decisions taken by the Tunisian authorities (e.g., the decision to grant Ichkeul an annual water quota, supplied from the Sidi El Barrak dam) and some practical measures introduced by the ANPE (National Agency for the Protection of the Environment) (e.g., operating of the Tinja sluice, a monitoring programme), wider implementation of the management plan drawn up by the Safeguard Study remained difficult. A World Heritage/Ramsar mission in 2000 (Baccar et al. 2000) took note of the efforts made on site and at government level, and again stressed the need for the updating and implementation of the management plan with the involvement of all concerned interest groups and the restoration of the Joumine marsh. During summer 2008, the lower part of the drainage canal at Joumine has been filled and autumn rainfall flooded the marsh through additional small side channels (ANPE 2010) thus restoring the conditions that existed when the National Park was created 28 years ago.
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5.2. Underlying Causes of the Conflict Effective implementation of a management strategy requires the involvement of the main stakeholders, who must be made aware of the need for the conservation of the natural resource as a guarantee for their current and continued future wellbeing. The Ramsar Convention has provided guidelines for encouraging and strengthening the participation of the human users affected by the policy outcome. When stakeholders are not involved or are brought into the policy formulation and planning process at a later date, without the opportunity to provide input, they are seldom supportive of the policy outcome. Compliance with policy, together with requisite monitoring and enforcement, greatly suffers in consequence, and the policy can even fail outright. The designation ‗Biosphere Reserves‘ under the UNESCO MAB-Programme requires a balance between conservation of biological diversity, sustainable human exploitation and scientific research. The measures adopted by the Tunisian authorities took account of the primary concern of the MAB-Programme, i.e. the objective of conservation of the flora and fauna of the Park. However, they failed to meet the objective defined as ―sustainable development‖ in Agenda 21 of the UN Earth Summit held in Rio de Janeiro in 1992, i.e. ―incorporating care of the environment, living off the land without depleting its capital, with greater social equity, including respect for rural communities and their accumulated wisdom‖. It is clearly stated that government agencies, charged with coastal zone protection (e.g., the ANPE in Tunisia), must integrate traditional ecological knowledge and socio-cultural values with management agendas. Traditional ecological knowledge is now more specifically defined as Traditional Ecological Knowledge and Wisdom (TEKW), a concept that combines the worldview of a people with their use of resources over time (Ford & Martinez 2000). In addition, Nazarea (1998) reminds us that this knowledge, as well as the preservation of threatened taxa, is critical for the preservation of biodiversity. Because biotic diversity in coastal lagoons is inherently low, whereas their functional significance is great, shifts in diversity are likely to be particularly important. Ecological modelling of the Ichkeul ecosystem (Casagranda in prep.) provides evidence that single species changes from anthropogenic influences (e.g., eutrophication, non-nutrient pollutants, habitat alteration, climate change) have overt, sweeping effects on ecosystem structure, with negative consequences for functions and services. Beyond the ethical duty to respect rural communities and their accumulated wisdom, I hypothesize that traditional resource use is from the ecological point of view important for lagoon management because its sustainable approach maintains positive interactions among species, promoting stability and resistance to disturbance. The complexity of interactions between man and species, together with feedback for ecosystem functions, suggests that social science-based approaches will be required to gather biological data and to elucidate the role of man in sustaining lagoon functions and services. Humans are also components of ecosystem functions, and it is similarly necessary to identify the individuals, groups of individuals, and institutions that are most critical in this regard. In this sense, the local users and residents are critical stakeholders in the process of establishing management plans, which can support its implementation and respect in practice.
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5.3. Lessons from Ethno-Science and Fishery Management The extent of marginalisation and neglect of local knowledge among scientists during the Safeguard Study and afterwards came as a surprise and is worth pointing out. The personal experience that alternative resource practices are often denigrated as backward, inefficient and founded on myth and ignorance is in keeping with Poizat & Baran (1997) who observed that scientists and environmental managers have generally disregarded the possibilities of learning from the local communities. It is, however, evident that identifying conservation priorities based on the best available science alone will not solve conservation problems. - I agree with Huntington (2000) that this is due to continued inertia in recognising that such practices can provide an important information base for integrated resource management, especially in the southern countries, where biological data are usually scarce to non-existent (Johannes 1981, Dieges 1999, Valbo-Jorgensen & Poulsen 2001). Human communities which rely directly on their natural resources for subsistence have often developed elaborate processes for protecting and managing their resources (Gadgil et al. 1993, Berkes 1999). Furthermore, traditional knowledge benefits from its low cost, both in time and material, and from the integrative nature of the source which potentially allows the acquisition of information at several temporal and spatial scales (Mackinson 2001, Valbo-Jorgensen & Poulsen 2001). To be useful for resource management, however, it must be systematically collected and scientifically verified. The main difficulty for natural scientists is accessing traditional ecological knowledge, which is rarely written down and which makes social science-based approaches necessary (Berkes & Folke 1998). But, the alternative approach for using the local resource practice as a source of information on lagoon ecology is by recognizing that villager‘s daily observation of their own ecological system, together with traditional knowledge learned from elders, could be beneficial to ecological studies and can also be used as a preliminary stage of an ecological investigation (Valbo-Jorgensen & Poulsen 2001).
5.4. A New Old Approach Recent studies on traditional knowledge (Aswani & Hamilton 2004, Wiber et al. 2004, Silvano & Begossi 2005, Aliaume et al. 2007) confirm that these ―diachronic‖ observations can complement the ―synchronic‖ observations on which scientifically achieved management practices are based. This knowledge has accumulated through a long series of observations transmitted from generation to generation in a constantly evolving adaptation to risk, based on empirical and practical experience. In addition, it provides a way of checking whether scientific recommendations are implementable and provides a shortcut to pinpoint essential scientific research needs (Mackinson 2001). Although I acknowledge that there are many conceptual and empirical problems inherent in improving management planning, I think this exercise is essential in order: (1) to establish at least a first approximation of the relative magnitude of global lagoon functions and services in the case of Ichkeul; (2) to make the range of potential values of traditional lagoon knowledge more apparent; (3) to highlight the role that traditional knowledge can and should
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play in regional efforts for conservation; (4) to point out the need to overcome practical and methodological barriers; and (5) to stimulate additional research and debate.
ACKNOWLEDGMENTS The author is grateful to Frank Columbus, Nova Science Publishers, for the invitation to contribute to this book. In preparing this chapter, the author thanks the participants in the Safeguard Study for discussions of their views on Ichkeul and for providing access to many of the unpublished works and reports which are not easily available to international readers. Thanks are due to the Centre d‘Océanologie de Marseille for work facilities. The work would not have been possible without the support of Prof. Charles François Boudouresque. The author is of course solely responsible for the views expressed in this presentation. Finally, thanks are due to Michael Paul for improving the English text. For Mabrouka and her sons, and all the children of their generation who will have to deal with all that my generation has bequeathed to the 21st century.
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Nazarea, V. D. (1998): Cultural memory and biodiversity.- Univ. Arizona Press, Tucson, Arizona (USA). Newel, S.Y. & Bärlocher, F. (1993): Removal of fungal and total organic matter from decaying cordgrass leaves by shredder snails.- J. Exp. Mar. Biol. Ecol. 171: 39-49. Ouakad, M. (1982): Evolution sédimentologiue et caractère géochimique des dépôts récents de la Garaet el Ichkeul (Tunisie septentrionale).- Ph.D. Thesis, Univ. Perpignan (France). Poizat, G. & Baran, E. (1997): Fishermen‘s knowledge as background information in tropical fish ecology: a quantitative comparison with fish sampling results.- Environ. Biol.Fish. 50: 435-449. Ramsar Convention & Wetlands International (2010): Information Sheet on Ramsar Wetlands, Tunisia, Ichkeul. Ramsar Sites Information Service.- Available at: http://ramsar.wetlands.org/Database/Searchforsites/tabid/765/Default.aspx. Shili, A., Ben Maïz, N., Boudouresque, C.F. & Trabelsi, E.B. (2007): Abrupt changes in Potamogeton and Ruppia beds in a Mediterranean lagoon.- Aquat. Bot. 87: 181–188. Silvano, R. & Begossi, A. (2005): Local knowledge on a cosmopolitan fish Ethnoecology of Pomatomus saltatrix (Pomatomidae) in Brazil and Australia.- Fish. Res. 71: 43-59. Tamisier, A., (1992): Programme national de recherche sur l‘écosystème Ichkeul. Saison 1991-92. La communauté des oiseaux aquatiques.- Rapport ANPE (Agence Nationale pour la Protection de l‘Environnement)/FNR (Fond National de la Recherche) (Tunisia). Tamisier, A., Bonnet, P., Bredin, D., Dervieux, A., Rehfish, M., Rocamora, G. & Skinner, J. (1987): L‘Ichkeul (Tunisie), quartier d‘hiver exceptionnel d‘Anatidés et de foulques. Importance, fonctionnement et originalité.- Revue Française d’Ornithologie 57: 296-306. UNESCO (2010): Biosphere Reserve Information Tunisia, Ichkeul. UNESCO-MAB Biosphere Reserves Directory.- Available at: http://www.unesco.org/mabdb/br/brdir/directory/biores.asp?code=TUN?03&mode=all. UNESCO World Heritage Centre (2010): Ichkeul National Park.- Available at: http://whc.unesco.org/en/list/8/. Valbo-Jorgensen,J. & Poulsen, A.F. (2001): Using local knowledge as a research tool in the study of river fish biology: experiences from the Mekong.- Environ. Dev. Sust. 2: 253276. Verhoeven, J.T.A. (1980): The ecology of Ruppia-dominated communities in western Europe. III. Aspects of production, consumption and decomposition.- Aquat. Bot. 8: 209253. Vidy, G. (1983): Organisation de la pêche et statistiques de production du lac Ichkeul. Rapp. Doc. Inst. Natl. Sci. Techn. Océanogr. Pêche Salammbô (Tunisia) 1: 34-45. Vollenweider, R. & Kerekes, J. (1982): Eutrophication of waters, monitoring, assesment and control.- OECD (Organisation for Economic Cooperation and Development) publ. Paris (France). Wiber, M., Berkes, F., Charles, A. & Kearney, J. (2004): Participatory research supporting community-based fishery management.- Mar. Policy 28: 459-468. Zaouali, J. (1974): Les peuplements malacologiques dans les biocénoses lagunaires tunisiennes. Etudes de la biologie de l'espèce pionnière Cerastoderma glaucum Poiret.Ph.D. Thesis, Univ. Caen (France).
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 371-396 © 2011 Nova Science Publishers, Inc.
Chapter 13
BIRTH, EVOLUTION AND DEATH OF A LAGOON: LATE PLEISTOCENE TO HOLOCENE PALAEOENVIRONMENTAL RECONSTRUCTION OF THE DOÑANA NATIONAL PARK (SW SPAIN) F. Ruiz1, *, M. Pozo2, M. I. Carretero3, M. Abad1, M. L. González-Regalado1, J. M. Muñoz4, J. Rodríguez-Vidal1, L. M. Cáceres1, J. G. Pendón5, M. I. Prudêncio6 and M. I. Dias6 1
Departamento de Geodinámica y Paleontología, Universidad de Huelva, Avda.Tres de Marzo, s/n, 21071-Huelva, Spain 2 Departamento de Geología y Geoquímica, Universidad Autónoma de Madrid, 28049-Madrid, Spain 3 Departamento de Cristalografía, Mineralogía y Química Agrícola, Universidad de Sevilla, Apdo. 553, Sevilla, Spain 4 Departamento de Estadística e Investigación Operativa, Universidad de Sevilla. 41071- Sevilla, Spain 5 Departamento de Geología, Universidad de Huelva, Avda. Tres de Marzo, s/n, 21071-Huelva, Spain 6 Instituto Tecnologico e Nuclear. EN-10, 2686-953-Sacavém, Portugal
ABSTRACT A multidisciplinary study of sediment cores from Doñana National Park (SW Spain), a broad region of wetlands in SW Spain, provides the base for the reconstruction of the main palaeoenvironmental changes that occurred in the Guadalquivir estuary since OIS 3. The facies analysis differentiates six main facies, deposited in freshwater pond and marsh (FA-1: laminated silt), brackish marsh or the periphery of a brackish lagoon (FA-2: greyish silt), a shallow lagoon (FA-3: green silt and clay), the marine connection of this *
Corresponding author: Email: [email protected]
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F. Ruiz, M. Pozo, M. I. Carretero et al. lagoon (FA-4: yellow silt) or sandy spit (FA-6: yellow sand), whereas FA-5 includes bioclastic silt and sand with a tsunamigenic origin. The vertical arrangement of these facies, their dates and a detailed comparison with previous works permit to delimitate ten phases in the Late Pleistocene to Holocene evolution of this lowland. In the oldest phase (OIS 3), this area was occupied by freshwater marshes. Phase 2 (OIS 2) was characterized by the alternation of freshwater and brackish marshes, partly enclosed by aeolian units. During the third phase (Early Holocene), the brackish marshes constituted the northern limit of a broad lagoon that extended along the present-day inner shelf. The sea-level highstand of the Present Interglacial (Flandrian transgression, phase 4: ~6.5 cal BP) caused the inundation of this area, occupied by an open lagoon. Between 6.5 and 4.6 cal ka (phase 5), incipient brackish marshes emerged along the margins of this lagoon and a first tsunamigenic event (5100-4800 cal BP) eroded partially the Doñana spit. The following phase (4.6-3.7 cal ka) was relatively quiet, with predominance of infilling processes. This calm scenario was interrupted by a new period of instability (phase 7: 3.7-3 cal ka), with two new highenergy events. The progressive infilling is the main feature of phase 8 (3-2.2 cal ka), with the emersion of new brackish marshes and a decreasing depth in the adjacent lagoon. The first historical tsunamis (phase 9: 2.2-1.9 cal ka) induced the creation of washover fans and bioclastic ridges overlying the previous marshes. Since 1.9 cal ka (phase 10), the growing of the Doñana spit and the fluvial-tidal sediment inputs caused an important filling of the Guadalquivir estuary (Doñana National Park), only interrupted by new tsunami records (~1.8-1.5 cal ka).
1. INTRODUCTION The Pleistocene-Holocene geological record of littoral areas has received an increasing attention in the last decades. The multidisciplinary analysis of cores collected in lagoons, estuaries, salt marshes or deltas has revealed a broad information about the palaeoenvironmental evolution of these environments, global or regional sea-level changes, palaeoclimatology or the effects of anthropogenic actions during this period (Borrego et al., 2004; Vilanova et al., 2006; Selby and Smith, 2007). In this scenario, the mineralogical composition is an important tool to infer the origin of sediments, the variations of some physical-chemical water parameters or even palaeoclimatic oscillations (Chamley, 1989; Carretero et al., 2002; Mackie et al., 2007). This record includes distinctive sedimentary layers that have been attributed to storms, cyclones, hurricanes or tsunamis. These high-energy events cause the deposition of sedimentary layers with characteristic textural and mineralogical features (Clague et al., 2000; Singarasubramanian et al., 2006; Babu et al., 2007). In most cases, these investigations are concentrated on a single event (Dawson and Smith, 2000; Wagner et al., 2007), although even six tsunamis have been recognized in a single section (e.g., Cisternas et al., 2005). The southwestern Spanish coast is a low-probability tsunamigenic area (Galbis, 1932, Campos, 1991; Reicherter, 2001), with sixteen documented tsunamis between 218 BC and 1900 AC. Nevertheless, its geological record is poorly known at present (e.g., Luque et al., 2001; 2002; Ruiz et al., 2004; 2005a; Scheffers and Kelletat, 2005). The aim of this chapter is to delimitate the main sedimentary facies deposited in the Doñana National Park (SW Spain) during the Late Pleistocene-Late Holocene period, with special attention to their textural, mineralogical and palaeontological features. Its vertical and
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lateral dispositions, together with radiometric datings, will permit to reconstruct the palaeoenvironmental evolution of this area in relation with climatic changes and sea level oscillations.
2. STUDY AREA The Doñana National Park (SW Spain) is located on the western bank of the Guadalquivir estuary, with an extension of 50,720 ha (Figure 1). This area constitutes one of the largest wetlands in Europe, composed mainly of salt and freshwater marshes that include temporary ponds and have a modest topographic gradient (0-1 m). These marshes are drained by two main tributaries (Guadiamar River and Madre de las Marismas Creek) and numerous ebb-tide channels, with recent and former banks occupied by clayey levees and both bioclastic and beach-morphology ridges (Figure 1: Veta la Arena, Las Nuevas). In addition, they are locally covered by sandy ridges located very close to the Doñana spit and disposed in a NE-SW direction (Figure 1: Carrizosa, Vetalengua). These inner zones are partly protected by two sandy spits (Doñana and Algaida; 0-30 m height). They include active dune systems disposed in narrow (< 100 m) and elongated (1–2 km) alignments. The main hydrodynamic processes are controlled by the fluvial regime, tidal inputs, the southwestern dominant wave action and the southeastern drift currents. The Guadalquivir River has a very irregular regime, with an annual mean of 185 m3s-1 and a maximum up to 1000 m3h-1 (Vanney, 1970; Menanteau, 1979). The tidal regime is mesotidal and semidiurnal, with an average tidal range of approximately 3.6 m (Borrego et al., 1993).
3. MATERIALS AND METHODS 3.1. Textural, Mineralogical and Paleontological Analyses Two long cores (Figure 1: PLN -93 m-; CM –31 m-) were collected by the Geological Survey of Spain in the southern part of the Doñana National Park. Additional samples were obtained from seven short cores included by Ruiz et al. (2004; 2005a) in previous works. The main facies were established from lithological descriptions complemented with the grain-size analysis of seventy representative samples, owing the predominance of detrital facies (Figures 2-3-4). Grain-size distribution was determined by wet sieving for the coarser fractions (>100 μm). Fractions lesser than 100 μm were analyzed by photosedimentation (MicromeriticsR SediGraph 5100 ET). Na-hexametaphosphate has been used as a dispersing agent. The mineralogical analysis of samples was carried out by means of X-ray diffraction (XRD) using a Siemens D-5000 equipment with a scanning speed of 102θ/min and Cu-kα radiation. XRD studies were performed both on randomly oriented samples (total fraction) and clay fraction samples (< 2 µm), the last prepared from cation-saturated, ultrasonic treated suspensions oriented on glass slides. The identification of the clay fraction minerals was carried out on oriented Mg2+-saturated samples with ethylene glycol salvation, and also after
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heating at 5500C following K+ saturation. When required, carbonates were eliminated using 0.6 N acetic acid. Quantitative estimation of the mineral content was carried out using the intensity factors calculated by Schultz (1964) and Barahona (1974). Results from 65 bulk samples and 41 oriented clay samples are shown in Tables 1 and 2, respectively.
Figure 1. Geographical setting and geomorphology of the Doñana National Park, with location of the cores
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Figure 2. Long Cores. Distribution of facies and mineralogical samples
Figure 3. Short cores. Distribution of facies and mineralogical samples
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In addition, the >63 µm fraction was revised under stereoscopic microscope, in order to effectuate a general revision of the palaeontological record. This revision includes the taxonomical determination and the estimation of both densities and diversities of bivalves, gastropods, ostracods and foraminiferids. In addition, the presence and relative abundance of other groups (scaphopods, barnacles, bryozoans, crabs) have been also detailed.
3.2. Mathematical Procedures A multivariate analysis was applied to determine the mineralogical sample groups based on the percentages computed of the main minerals (quartz, calcite, phyllosilicates, feldspars and dolomite). An initial clustering procedure is applied using a hierarchical agglomerative technique with the application of the Euclidean distance and the Ward linkage. Results are contrasted by discriminant analysis, by determining both the dimensions and variables on which the groups differ. In addition, a stepwise selection procedure was computed and the contribution of each of the predictor variables to the overall discrimination was determined. The error rate estimation was obtained by a final cross-validation method. These statistical techniques were carried out using several subprograms of the Statistical Package for the Social Sciences (SPSS™). Further details of these techniques may be consulted in Dillon and Goldstein (1984).
3.3. Radiocarbon Chronology Two new dates were produced at the Beta Analytic Laboratory (Miami, USA) by radiocarbon analysis of mollusc shell (Figure 6. core CM), whereas the remaining twelve dates were obtained from Ruiz et al. (2004; 2005 a, b) and Pozo et al. (2010). All data were calibrated using CALIB version 5.0.2 (Stuiver and Reimer, 1993) and the Stuiver et al. (1998) calibration dataset. The final results correspond to calibrated ages (ca.) using 2σ intervals, with the reservoir corrections suggested by Soares and Dias (2006 a, b) and Soares (2008) for this area. For the time interval 4500-4000 yr BP, more future results are necessary to determine a mean value to be used with the marine calibration curve (Soares, personal communication). Ages discussed below are expressed as the highest probable age of the 2σ calibrated range (e.g., Van der Kaars et al., 2001). In addition, the calibrated age of the maximum of the Flandrian transgression has been used (Zazo et al., 1994; Figure 6: **) and the sedimentation rates (1.5-2.5 mm/yr) deduced from Spanish Holocene estuarine sequences (Lario et al., 2002; Zazo et al., 2008) for the interval 10,000-7000 yr BP have been applied to core PLN (see Figure 6: ***)
3.4. Palaeogeographical Reconstruction The palaeogeographical evolution of this area has been possible with: a) the inclusion of numerous data obtained by Lario (1996), Zazo et al. (1999) and Yll et al. (2003) in other cores of the Doñana National Park; b) the analysis of several boreholes drilled near the
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Guadiamar River mouth by Salvany et al. (2001); c) the palaeogeographical interpretation of numerous seismic profiles effectuated in the Cádiz Gulf (Lobo et al., 2001; 2002); and d) previous analyses of short cores (Figure 3) by Ruiz et al. (2004; 2005a).
4. RESULTS AND DISCUSSION 4.1. Facies and Palaeoenvironmental Interpretation Six main facies have been differentiated: Facies FA-1. Laminated silt.This facies occupies the lowest 30 m of core PLN and the upper 32 cm of core GR. It consists mainly of clayey silt (Figure 2: Facies FA-1-a), with up to 65 % of sediments included in the 40 µm-4 µm grain size interval. These sediments show a fine parallel lamination, with alternation of greyish to greenish (colour 6/1; Munsell scale) and blackish (colour 4/1) layers. Some layers of sandy-clayey silt (Facies FA-1-b: sand ~1015 %) are also interbedded within this general pattern. Phyllosilicates (42-73 %) are clearly dominant over calcite (11-21%), quartz (8-13 %) and feldspars (2-27 %) in the clayey-silty layers, whereas quartz increases remarkably (20-40%) in the sandier laminae. The clay mineral contents are very variable (smectites: 25-56 %; illite: 25-56 %; kaolinite: 4-27 %). The microscopical analysis reveals the presence of numerous reddish, oxidized fragments of roots and phanerogams, scarce gyrogonites of characeans (Chara sp., Nitella sp.) and isolated fragments of undifferentiated bivalves. A freshwater ostracod assemblage (Cyprinotus salinus, Cyprideis torosa, Ilyocypris gibba, Cyprideis torosa, Herpetocypris chevreuxi, Cypris bispinosa) is very abundant in core GR, whereas only scarce specimens of the two first species have been found in core PLN. Interpretation. The main features of Facies FA-1-a have been observed in temporary ponds and the surrounding freshwater marshes of the Doñana National Park, with similar ostracod and characean assemblages (Ruiz et al., 1996; Santos et al., 2006). These ponds are very shallow (< 1 m in most cases) and contain alkaline, fresh to oligohaline waters (Serrano and Toja, 1995). Fine laminations will indicate a calm environment with a cyclic sedimentation suggested by the alternating color shades, probably due to alternating dry or wet periods, pulses from small tributaries or the vegetation distribution (Whittecar et al., 2001; Harter and Mitsch, 2003). The almost absence of microfauna in the oldest sediments may be due to the dissolution of the thin carapaces of the freshwater species (e.g., ostracods), a process very usual in similar (paleo-)environments during the oxidation of organic matter (Hoge, 1994; Smith, 1997). The higher grain size of Facies FA-1-b and the absence of faunal remains are attributed to increasing fluvial inputs. Facies FA-2. Greyish silt. This facies is widely represented in almost all cores and is constituted by silt and clay (silt: 55-70 %; clay: 26-43 %) with greyish to greenish colours (colour 5Y 4/2). Up to 70 % of sediment is comprised between 15 and 2 µm (Figure 4), with high percentages of fine and very fine silt. They are massive or show a very tenuous lamination. Phyllosilicates are the main mineral components (24-73 %; mean 48 %), although
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both quartz (8-34 %; mean 14 %) and calcite (8-35 %; mean 23.3 %) increase in relation to FA-1. Smectites (> 44 % in most cases) are dominant over illite (mean: 37.2%) and kaolinite (11.7 %).
Figure 4. Photosedimentation grain-size analyses of the six facies differentiated, expressed as mean percentages of each grain size interval in each facies. See differences between subfacies in the text
The palaeontological record includes low densities of a high brackish ostracod assemblage (mainly C. torosa, Loxoconcha elliptica, Leptocythere castanea), salt marsh foraminifers (Ammonia tepida, Jadammina macrescens, Haynesina germanica, Trochammina inflata), scarce pulmonate gastropods and undifferentiated fragments of stems and roots. Reworked specimens of planktonic foraminifers, spines of echinoderms, bryozoans and marine or brackish bivalves (Cardium edule, Venerupis decussatus) are frequent.
Birth, Evolution and Death of a Lagoon: Late Pleistocene to Holocene… Table 1. Bulk mineralogy of selected samples SAMPLES CM-9 CM-8 CM-6 CM-5 CM-3 PLN-28 PLN-27 PLN-26 PLN-25 PLN-24 PLN-23 PLN-22 PLN-21 PLN-20 PLN-19 PLN-18 PLN-17 PLN-16 PLN-15 PLN-14 PLN-13 PLN-12 PLN-11 PLN-10 PLN-9 PLN-8 PLN-7 PLN-6 PLN-5 PLN-4 PLN-3 PLN-2 PLN-1 AR2 AR1 BR3 BR2 BR1 CR5 CR4 CR3
Quartz 10 27 44 71 13 13 14 10 16 14 10 12 16 14 20 14 13 18 20 12 8 7 14 17 14 9 34 8 14 11 39 12 13 62 13 4 16 11 75 23 17
Calcite 22 24 20 4 23 28 31 19 26 28 22 12 21 28 20 31 24 24 32 33 23 31 34 28 21 27 8 18 16 11 15 21 32 2 15 40 21 20 21 24 34
Phyllosilicates 62 40 15 3 56 42 33 54 45 43 34 35 51 44 55 32 41 33 35 45 61 49 32 31 24 44 24 67 47 48 28 52 42 30 43 56 54 62 3 46 43
Feldspars 3 3 19 21 2 7 8 3 4 4 24 13 7 5 2 5 15 8 6 4 3 5 8 14 8 8 23 5 5 27 13 11 4 5 2 0 3 0 1 3 1
Dolomite 3 3 2 1 6 7 11 9 2 8 9 24 5 6 3 17 5 14 7 6 5 6 12 8 32 12 11 2 18 3 5 4 9 1 2 0 4 2 0 4 4
Others 0 3 0 0 0 3 3 5 7 3 1 4 0 3 0 1 2 3 0 0 0 2 0 2 1 0 0 0 0 0 0 0 0 0 25 (Gypsum) 0 2 5 0 0 1
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SAMPLES CR2 CR1 DR3 DR2 DR1 FR6 FR5 FR4 FR3 FR2 FR1 GR3 GR2 GR1 HR10 HR9 HR8 HR7 HR6 HR5 HR4 HR3 HR2 HR1
Quartz 20 41 88 75 12 42 45 37 14 36 18 8 11 13 18 10 9 9 11 10 12 13 16 16
Calcite 23 35 1 2 16 25 21 30 35 22 20 14 20 21 21 19 21 20 21 24 25 32 27 19
Table 1. (Continued) Phyllosilicates Feldspars 53 2 20 2 6 5 11 10 67 1 13 8 10 8 12 13 44 4 31 4 53 4 73 3 61 3 58 3 53 3 60 5 61 2 65 2 61 2 58 4 55 4 47 1 49 2 51 9
Dolomite 2 2 0 1 4 12 16 8 3 7 5 2 5 4 3 3 3 2 3 2 2 3 3 3
Others 0 0 0 1 0 0 0 0 0 0 0 0 0 1 2 3 4 2 2 2 2 4 3 2
Interpretation. This facies has intermediate characteristics between FA-1 and FA-3. The microfossil assemblages are characteristic of brackish marsh or the surrounding margins of a brackish lagoon. Tidal flows introduced marine faunas toward the more protected areas of this lagoon. Both mineralogical and palaeontological records are very similar to those observed in the inner areas of perimediterranean lagoons (Carbonel and Pujos, 1982; Montenegro and Pugliese, 1996; Ruiz et al., 2006b). Facies FA-3. Green silt and clay. It consists of greenish clayey silt or silty clay (colour 10YR 5/3), with up to 70 % of sediment (dry weight) comprised between 30 µm and 1 µm and very low sand contents (< 4 %). This facies exhibits a fine parallel lamination, with coarse laminae (5-10 cm thick) well defined and scarce evidence of bioturbation. The bulk mineralogy is dominated by phyllosilicates (32-62 %), reaching usually up to 41 %. Calcite (19-32 %; mean 24 %) and quartz (10-23 %; mean 15.5 %) have more homogeneous distributions than FA-2, although similar mean values. The highest contents of feldspars (1-15 %) and dolomite (2-17 %) were found in core PLN (20-25 m depth).
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Table 2. Clay mineralogy of selected samples SAMPLES CM-9 CM-3 PLN-26 PLN-25 PLN-21 PLN-17 PLN-14 PLN-12 PLN-11 PLN-6 PLN-4 PLN-2 PLN-1 AR2 AR1 BR3 BR1 CR5 CR4 CR3 CR2 CR1 DR3 DR2 DR1 FR6 FR4 FR1 GR3 GR2 GR1 HR10 HR9 HR8 HR7 HR6 HR5 HR4 HR3 HR2 HR1
Smectites 45 46 30 26 32 31 38 58 44 31 56 25 47 67 54 41 67 35 50 46 56 52 61 29 56 26 35 49 41 28 53 47 42 34 43 57 60 55 57 51 58
Illite 38 42 51 53 48 49 39 31 41 46 25 56 42 31 40 52 29 59 37 50 35 39 37 59 34 60 54 39 51 68 40 43 50 57 49 33 33 36 37 41 36
Kaolinite 17 12 19 21 20 20 23 11 15 23 19 19 11 2 6 7 4 6 13 4 9 9 2 12 10 5 11 12 8 4 7 10 8 9 8 10 7 9 6 8 6
Clay minerals show an interesting contrast between core PLN and the remaining ones. In the upper part of this core, illite is clearly dominant (48-53 %) over smectites (26-32 %), whereas these latter are more abundant (51-67 %) in the inner cores or near the protected, landward side of the Doñana spit.
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Macrofauna is composed of brackish (mainly Cardium edule) and marine (Venerupis decussatus, Chamelea gallina) bivalves, together with less frequent specimens of marine gastropods (Rissoa, Hinia). Ostracods (2-200 individuals/gram; C. torosa, L. elliptica, L. castanea) and foraminifers (10-1,000 individuals/gram; A. tepida, H. germanica) are frequent to very abundant in these sediments. The reworked marine faunas of ostracodes, planktonic foraminifers, spines of echinoderms, fragments of bryozoans or central diatoms may be locally abundant, composing 20-40 % of the paleontological record. Interpretation. The most representative species of both ostracodes and foraminifers are well represented in the deeper, subtidal areas of brackish lagoons (salinity up to 15-20 0/00), located near a river mouth. In these coastal areas, the tidal renewal is conditioned by the dimensions of outlets that cross the external, elongated sandy spits (Marocco et al., 1996; Samir, 2000; Ruiz et al., 2006a). This marine influence is contrasted by the presence of reworked faunas derived from the adjacent infralittoral zone (Pérez Quintero, 1989; Ruiz et al., 1997). The different clay mineralogy may be explained by the more open location of core PLN within this lagoon, with inputs of illite-rich, silty-clayey sediments from the shelf. In these shallow marine areas of southwestern Spain, illite is dominant over smectites (Gutiérrez-Mas et al., 1997). Facies FA-4. Yellow silt. It is constituted by off-white to pale yellow, sandy-clayey silt (colour 8/2 to 8/3), poorly sorted, with very low to moderate percentages of sand (4-20 %). They present a very tenuous low-angle cross stratification, parallel lamination or absence of patent sedimentary structures. These fine-grained sediments are characterized by moderate to high percentages of quartz (20-44 %) and low to moderate phyllosilicate contents (15-35 %), In addition, calcite exceeds 20 % and feldspars can be significant (~ 20 %) in the upper part of core CM. Smectites and illite show similar proportions (40-50 %). Macrofauna is abundant, with numerous valves and fragments of marine molluscs, including bivalves (C. gallina, V. decussatus, Acanthocardia tuberculata), gastropods (Rissoa spp., Hinia reticulata, Lemintina arenaria) and scaphopods (Dentalium vulgare, D. sexangulum). Benthic marine foraminifers (50-300 individuals/gram; Ammonia beccarii, Quiqueloculina spp., Elphidium crispum) and ostracodes (Palmoconcha turbida, Pontocythere elongata, Urocythereis oblonga) are dominant over brackish species. Fragments of bryozoans, plates of barnacles, claws of crabs, or planktonic foraminifers (Orbulina, Globigerina, Globigerinoides) are also abundant. Interpretation. The most abundant assemblages of molluscs, ostracodes and foraminifers of this facies characterize the shallow areas (< 40 m depth) of the southwestern Spanish shelf (Pérez Quintero, 1989; Ruiz et al., 1997; González-Regalado et al., 2000). These assemblages and some brackish specimens (C. torosa, L. castanea) are usually found in the marine zones of perimediterranean lagoons, very close to the natural or artificial inlets and subjected to moderate to high hydrodynamic gradients (Ruiz et al., 2000; 2006, a; b). Facies FA-5. Bioclastic silt and sand. This facies is the main constituent of several bioclastic ridges located in the margins of recent or former tidal channels (Figure 1: Veta la Arena, Las Nuevas). These sedimentary beds are characterized by a large lateral extension (3-
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6 km) and a narrow width (20–30 m). Thickness (5-70 cm in most cases) decreases landward, being disposed usually over FA-2 or FA-3. They display an erosive base, with vegetation remains and intraclasts of the underlying sediments in the lower centimetres. In the upper part, bioclasts were disposed in thick laminae (3-5 cm) or present a disorganized disposition, being fragmented in most cases. Texture permits to delimitate two subfacies, with a bimodal grain size distribution and a poor sorting in both cases: Subfacies FA-5-a. Bioclasts are included in a greenish, clayey-silty matrix (colour 5Y 8/3), with moderate sand contents (10-25 %). Phyllosilicates (43-65 %) are clearly dominant over calcite (19-40 %) and quartz (4-18 %). Illite is the main clay mineral (43-68%), with percentages slightly higher than smectites (28-47 %). This subfacies is dominant in Veta la Arena and the northeastern part of Las Nuevas. Subfacies FA-5-b. It is represented in the cores located near the Doñana spit. This subfacies will be transitional to FA-6, with bioclasts included in a greenish to greyish siltysandy matriz (colour 5Y 8/6). The mineralogical composition is very variable, ranking from quartz-rich samples (quartz up to 70 %) to others dominated by phyllosilicates (30-40 %) and calcite (12-31 %). Dolomite can be occasionally important (10-24 %). Illite ranges between 50% and 60% in all samples. This subfacies is well represented in Vetalengua and the southwestern part of Las Nuevas. In this last ridge, grain size seems diminish landward and easternward. In general, these ridges fines upward, passing from basal fine sands to very fine sands with important silty percentages near the top. Molluscs represent an important proportion (10-40 % dry weight) of the sediment. Shell debris and disarticulated bivalve shells of estuarine (mainly Cardium edule) and marine (mainly Acanthocardia tuberculata, Donax vittatus and Spisula solida) are abundant. Gastropods are represented by freshwater (Gyraulus laevis, Melanopsis) and marine (Rissoa, Lemintina, Hinia) specimens. Fragments of barnacles, scaphopods and bryozoans are also frequent. Microfauna is better represented in subfacies FA-5-a, with 50-500 individuals/gram of brackish ostracodes (C. torosa, L. elliptica) and foraminifers (A. tepida, H. germanica), together with marine specimens of both groups (Basslerites berchoni, Carinocythereis whitei, Urocythereis britannica, Ammonia beccarii, Elphidum crispum). Some marine miliolids are also abundant (Triloculina, Quinqueloculina), with a frequent loss or rupture of the last chambers. Brackish ostracodes present a high-energy population structure, with numerous individuals (>70 % in most of samples) belonging to adults or A-1 to A-3 moults. Only scarce specimens of brackish species were observed in the sandier samples of subfacies FA-5-b. Interpretation. These ridges show numerous features that have been described in tsunamigenic deposits (Bryant et al., 1992; Bryant, 2001; Costa et al., 2004; Dawson and Steward, 2007): a) an erosional base; b) presence of intraclasts plant remains near the base; c) finer sediments toward the top; d) finer sediments landward; e) presence of higher sand percentages (near the Doñana spit) in relation to the underlying sediments; f) changes in the clay mineral composition, with a general dominance of illite, probably derived from the adjacent shelf where this clay mineral is dominant (Gutierréz-Más et al., 1997); g) strong changes of fauna in relation to the underlying layers; h) presence of numerous marine species
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of both macrofauna and microfauna with evidence of reworking; or i) high-energy population structures on ostracodes. Consequently, a tsunamigenic origin has been attributed to these beds. Facies FA-6. Yellow sand. This facies is represented in the uppermost part of the sandy ridges (Carrizosa, Vetalengua) and the dune system of the Doñana spit (core CM). These layers consists of well sorted, fine to very fine sand with intense yellow shades (colour 10Y 8/6). Up to 60 % of sediment presents a grain size comprised between 500 µm and 80 µm. In the upper levels of core CM, this facies exhibits cross stratification, whereas sand is massive in cores AR and DR. Quartz (62-88 %) is dominant over phyllosilicates (3-30 %) and feldspars (5-21 %). Smectites (54-56 %) are the main clay minerals, with minor proportions of illite (34-40 %) and kaolinite (6-10 %). Both macrofauna and microfauna are virtually absent, with exception of some isolated and fragmented remains of the bivalve Corbula gibba. Interpretation. These sediments constitute the dune systems of the Doñana spit. The mineralogical records obtained coincide with those indicated by Flor (1990) and the Spanish Environmental Ministry (2005) in these aeolian beds. The sandy ridges of Carrizosa and Vetalengua show the same textural, mineralogical and faunal features. They occupy the margins of former meanders within the old lagoon system and are disposed at high angles in relation to the Doñana spit. The contact with this sandy bed coincides with the presence of an erosive surface within the dune systems of the spit (Rodríguez Ramírez et al., 1995) and a remarkable slimming of its width. The presence of these sand layers over FA-2 or FA-3 may be indicative of old tsunamis, with a partial rupture or erosion of the spit and the deposit of washover fans in its inner side. In a second episode, these washover fans would be reworked by the tidal fluxes and deposited in the margins of old tidal channels, constituting the sandy ridges of Carrizosa and Vetalengua. Simultaneously or in a later stage, a part of these washover fans would be dismantled and their almost azoic sands were introduced toward the inner areas of the lagoon, being deposited (as FA-5-b) over fluvial levees or marshes. The vertical facies disposition of core DR, with basal bioclastic layers below sandy beds, is very similar to that indicated in some washover fans of the southwestern Spanish coast and southeastern Asia, derived from recent and past tsunamis (Luque, 2002; Hori et al., 2007).
4.2. Statistical Analysis 4.2.1. Cluster groups Cluster analysis permits to separate two main groups (Figure 5, A). Group 1 (52 samples) is characterized by high percentages of phyllosilicates (mean 49.1 %) and calcite (> 23 % in most cases). A more detailed analysis defines three subgroups, with very high phyllosilicate contents (Subgroup 1.1), high to very high percentages of both feldspars and dolomite (Subgroup 1.2) and the highest mean percentages of calcite of all groups or subgroups (Subgroup 1.3). The clay mineral pattern of the two first subgroups is unclear, with variable
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percentages of smectites (25-67 %) and illite (25-68 %). Smectites are generally dominant over illite or both present similar contents in the third subgroup. Samples (13) of Group 2 consist mainly of quartz (mean 53 %), with phyllosilicates and calcite as secondary constituents. The quartz contents differentiate clearly two subgroups (Subgroup 2.1: mean ~ 40 %; Subgroup 2.2: mean ~ 74 %). Illite is dominant in subgroup 2.1, whereas subgroup 2.2 can be divided between azoic (Figure 5: 2.2.A: smectites: 61-67 %; illite: 31-37%) and bioclastic (2.2.B: smectites: 29-35%; illite ~ 59 %) layers.
4.2.2. Cross-validation In this final step, all samples are included in the same initial cluster, indicating a true separation between the two groups differentiated. In addition, 59 samples (up to 90 %) were included in the same subgroup, whereas the remaining six were relocated in a different subgroup within Group 1 and no changes were observed in Group 2. 4.2.3. Mineralogical Groups Vs Sedimentary Facies A comparison between these two variables permits to observe some remarkable coincidences (Figure 5, B). The `inner´ facies of this coastal palaeoenvironment (FA-1a: freshwater marsh and pond; FA-2: lagoon margin and brackish marsh; FA-3: subtidal lagoon; FA-5a: tsunamigenic, inner layers) are included in Group 1, whereas those related with `external´ inputs (FA-1-b: fluvial; FA-4: marine; FA-5-b: tsunamigenic, externe aeolian layers; and FA-6: aeolian) are more closely related with Group 2. The presence of some samples belonging to FA-5-b within Group 1 would be explained by the palaeotopograhy of the lagoon bottom, probably deeper in the central zone (upper part of core PLN).
4.3. Radiocarbon Datings The total dataset has seventeen datings, with calibrated ages ranking from ~44 ka to 1.4 ka (Figure 6). Additional data have been inferred in core PLN from: a) the lateral correlation with the adjacent, bioclastic ridge of Las Nuevas (Figure 6: *); b) the maximum of the Holocene transgression in this area (Figure 6: **) inferred by Zazo et al. (1994) and Lario et al. (1995); and c) the general sedimentation ratios (1.5-2.5 mm/yr) deduced between 7000 and 10,000 cal BP interval (Figure 6: ***) in different estuaries of the southern Spanish coast (Lario et al., 2002; Zazo et al., 2008).
5. LATE PLEISTOCENE-LATE HOLOCENE EVOLUTION OF THE DOÑANA NATIONAL PARK The comparison of these data with others obtained by different investigation teams in the Doñana National Park and the adjacent areas permits to drawn a tentative palaeogeographical evolution of this zone. Ten phases may be delimitated:
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Figure 5. A: Cluster analysis of the mineralogical data, B: Comparison between the mineralogical groups and the sedimentary facies
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Figure 6. Correlation of the cores, with inclusion of the vertical disposition of facies, the mineralogical groups and datings.
Phase 1 (OIS 3) Freshwater marsh (Facies FA-1) characterized the easternmost, inner areas of the Doñana National Park during OIS 3 (Figure 7, a-b), with an increasing hydric availability and a moister climate in relation to OIS 4 (Yll et al., 2003; Zazo et al., 2005). This general scenario is only interrupted by a marine input (> 45 ka) that inundated the inner areas and caused the deposition of Facies FA-4 in core PLN. This event may be related to short-lived warmer episodes of interstadial character (Behre, 1989), ice retreat phases (Duplessy et al., 1988), the final phase of a warm period in southern Europe (Van Andel, 2003), a sea level rise (Yokoyama et al., 2001) or a high-energy event. In the western sector, different aeolian units (~ FA-6) were deposited in the El Abalario area (Zazo et al., 2005). Sea level oscillated between -80 m and -100 m during this period (Siddall et al., 2003). Consequently, the larger part of the adjacent shelf was exposed, with coastal deposits located in the central area of the Cádiz Gulf (Lobo et al., 2002).
5.2. Phase 2 (OIS 2) During the Last Glacial Maximum (Figure 7, c), the eastern part of the Doñana National Park was occupied by alternating freshwater and brackish marshes (FA-1a and FA-2). These inner areas are partly enclosed by aeolian units (Zazo et al., 2005).
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This phase coincides with the lowest sea level (~ -125 m to -130 m) of the last 100,000 years (Yokoyama et al., 2000). Consequently, the palaeocoastline was located at ~ 40 km to the southwestern of its present-day position (Lobo et al., 2001).
Phase 3 (Early Holocene) Sea level reached -50 + 5 m at 10 ka in the Cádiz Gulf (Hernández-Molina et al., 1994; Lario, 1996), coinciding with a climatic amelioration between 10 ka and 5.4 ka in this area (Santos et al., 2003). In the inner shelf (Figure 7, d), the interpretation of high-resolution seismic profiles has permitted to recognize the presence of an elongate sandy barrier that protected an adjacent broad lagoon. Tidal channels of this lagoon had a NW-SE direction and were partially covered by overwash deposits (Lobo et al., 2001). The northeastern part of this lagoon was delimitated by aeolian systems (Zazo et al., 2005) and marshes (core PLN; Zazo et al., 1999).
Figure 7. Palaeoenvironmental evolution of the Doñana National Park during the last 65 ka. Left column: Late Pleistocene to Early Holocene sea level changes (modified from Siddall et al, 2003). ad: southwestern corner modified from Lobo et al. (2001; 2002). Additional data obtained from Goy et al., (1996), Zazo et al. (1999, 2005), Salvany et al. (2001), and Zazo et al. (2008)
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Phase 4 (maximum of the Flandrian transgression -6.5 cal ka BP-) In the Cádiz Gulf, river mouths were inundated around 6.5 cal ka (Zazo et al., 1994; Borrego et al., 1999; Dabrio et al., 2000). The Doñana National Park was occupied by an open lagoon (Figure 7, e), partially protected in its westernmost part by aeolian units (Zazo et al., 2008). The bottom sediments were constituted by silty sand with abundant remains of marine faunas (core PLN). After this maximum, the Doñana spit began to grow (Goy et al., 1996), with a progressive limitation of the tidal fluxes. In addition, the Guadiamar River caused the deposition of alluvial terraces at ~6300 yr BP in the northern part of the park (level T2; Salvany et al., 2001).
Phase 5 (6.5-4.6 cal ka BP) The first part of this phase is characterized by the growth of the Doñana spit, with the progressive emersion of the inner side of this incipient barrier (core AR). The bottom sediments of the adjacent, quiet lagoon were composed of clayey silt (FA-3) with variable bioclastic contents (Figure 7, f). Between 5100 and 4800 cal BP (Figure 7, g), a tsunami caused the erosion of this spit and the deposition of aeolian sand (FA-6) over the new salt marsh.
Phase 6 (4.6-3.7 cal ka BP) The central part of the Doñana National Park was still occupied by an open lagoon (cores CR and PLN), whereas the Doñana spit grew toward the southeast. This phase is dominated by the lagoon infilling, with the deposition of phyllosilicate-rich sediments (FA-3) in the lagoon bottom (Figure 7, h).
Phase 7 (3.7-3 cal ka) This area was subjected to arid conditions during this period (Zazo et al., 2008). One or two tsunami-like events (or very strong storms) caused the erosion of the Doñana spit (Figure 7, i) and the deposition of bioclastic, sandy-clayey silt over the lagoon bottom (core CR). In a latter period, new high-energy events induced the emersion of the very shallow, southwestern areas of the lagoon, with the deposits of FA-5 over intertidal sediments (core BR, CR and PLN).
Phase 8 (3-2.2 cal ka) During this phase (Figure 7, j), the southwestern part of the Doñana National area remained emerged (cores AR-BR-CR), whereas the central and southern ones were occupied
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by a very shallow lagoon (core PLN). The continuous growing of the Doñana spit and the progressive infilling induced the creation of new brackish marshes (cores DR-HR; core ML97, Zazo et al., 1999) or the transition from marine conditions to more restricted scenarios (core CM).
Phase 9 (2.2-1.9 cal ka) Several tsunamis eroded the Doñana spit in the following phase (Figure 7, k), with the creation of small washover fans constituted by aeolian sediments (core DR and CM) and the accumulation of bioclastic ridges over the lagoon borders (core HR). In addition, the subtidal palaeoenvironments of the central part are covered by bioclastic, silty-sandy sediments (core GR). Additional sedimentary evidence of these events include erosive surface in the Doñana spit (Rodríguez Ramírez et al., 1995), washover fans near the Gibraltar Strait (Luque et al., 2002), limestone boulders located at +4 to +15 m asl near Lisbon (Scheffers and Kelletat, 2005) or a turbiditic layer in the SW Portuguese Margin (Vizcaino et al., 2006a). These tsunamis may be assimilated to the historical tsunamis that devastated the southwestern Iberian coasts between 218-209 BC and 60 BC (Campos, 1991).
Phase 10 (1.9 cal ka-Present) The first period of this phase (Figure 7, l: 1900-1600 cal BP) is characterized by an increasing infilling of the lagoon (cores FR, GR and CM), with a progressive transition toward intertidal-supratidal conditions. This tendency was interrupted by a new introduction of marine sediments and, to a lesser extent, aeolian sediments in the southern part of the park (core FR and, probably, CM), owing to new high-energy events. Ages of these phenomena coincide with those of a historical tsunami (382 BC; Campos, 1991). The posterior palaeoenvironmental evolution of the Doñana National Park is marked by the creation of new wetlands with temporary ponds (core GR) and the growing of the Doñana and La Algaida spits, with aeolian sands covering intertidal sediments (core CM). At present, no evidence of the 1755 Lisbon earthquake-induced tsunamis have been found in this area, although some erosive surfaces located in the southeastermost part of the Doñana spit might be originated by this event. These tsunamis settled washover fans near the Gibraltar Strait, imbricated boulders around Lisbon or abyssal tempestites in the SW Portuguese margin (Luque et al., 2001; Scheffers and Kelletat, 2005; Whelan and Kelletat, 2005; Vizcaino et al., 2006b)
6. CONCLUSIONS A Late Pleistocene to Holocene evolution of the Doñana National Park has been proposed, based on the multidisciplinary analysis (texture, colour, geomorphology, paleontology, mineralogy, dating) of sediments present in two drill cores and seven short
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cores. This study permits to delimitate the geological features of five sedimentary facies deposited in distinctive palaeoenvironments (freshwater and brackish marshes, open lagoon, external lagoon and sandy spit) and a sixth, heterogeneous facies with a tsunamigenic origin. Ten phases have been distinguished since OIS 3, with a general scenario of progressive lagoon infilling conditioned temporary by sea level changes and high-energy events. These events caused the deposition of washover fans and bioclastic ridges over previous marshes or the lagoon bottom. This geological scenario was compared with climatic oscillations and sea level changes.
ACKNOWLEDGMENTS This work was funded by two Spanish DGYCIT Projects (CTM2006-06722 and CGL2006-01412) and three Research Groups of the Andalousia Board (RNM-349, RNM-238 and RNM-293). It is a contribution to IGCP-495 and 526.
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 397-415 © 2011 Nova Science Publishers, Inc.
Chapter 14
THE ALVARADO LAGOON – ENVIRONMENT, IMPACT, AND CONSERVATION
1
Jane L. Guentzel1*, Enrique Portilla-Ochoa2, Alejandro Ortega-Argueta2,3, Blanca E. Cortina-Julio2 and Edward O. Keith 4**
Department of Marine Science, Coastal Carolina University, Conway, SC, USA 2 Investigaciones Biologicas, Universidad Veracruzana, Xalapa, Ver., Mexico 3 Ambiente y Sustentabilidad, Instituto de Ecología, Xalapa, Ver., Mexico 4 Oceanographic Center, Nova Southeastern University, Ft. Lauderdale, FL , USA
ABSTRACT The Alvarado Lagoon System (ALS) in south-central Veracruz State, Mexico, is a mangrove dominated coastal wetland formed by the confluence of the Acula, Blanco, Limon and Papaloapan rivers. The ALS has a maximum width of 4.5 km, a mean surface area of 62 km2, and is connected to the Camaronera Lagoon by a narrow channel and to the Gulf of Mexico (GOM) via a 0.4 km wide sea channel. Water samples were collected during the wet (September 2005) and dry (March 2003 and 2005) seasons. Salinity ranged from 1-25.5 psu and pH was slightly alkaline (7.6-8.6). Levels of total organic carbon (TOC), total mercury (Hg), and total suspended solids (TSS) ranged from 3.9-20.9 mg C/L, 0.92-26.1 ng Hg/L, and 1-39.2 mg TSS/L, respectively. The strong correlation (R2=0.71; P=0.001) between total mercury and TSS in the water column suggests that particulate matter is a carrier phase for mercury within the Alvarado and Camaronera Lagoons. The ALS is one of the most productive estuarine-lagoon systems in the Mexican GOM. Model studies suggest that primary production by sea grasses provides more energy input to the ecosystem than detritus, which is contrary to most other Mexican GOM lagoons and estuaries. In 2004 the ALS was nominated Ramsar site no. 1355 because of its important biodiversity, ecological attributes, and high resource production. *
Corresponding authors: Email: [email protected] [email protected]
**
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Jane L. Guentzel, Enrique Portilla, Alejandro Ortega-Argueta et al. Over 100 fish species have been collected from the ALS, representing four ecological guilds: marine stenohaline, marine euryhaline, estuarine, and freshwater fishes. These assemblages have not experienced significant changes over the past 40 years, but there has been a recent decline in diversity. Antillean manatees (Trichechus manatus manatus) historically have occurred in the ALS but were reduced in the 1970s and 1980s by hunting and are now considered endangered. The rescue of 6 orphan calves between 1998 and 2000 suggests that manatees are reinhabiting the ALS as a result of conservation measures. Manatees are most commonly sighted in the Alvarado Lagoon, Acula River and adjacent lagoons, and are rarely sighted in the Limon River and adjacent lagoons. To protect the manatees and their habitat an educational program was developed in 1998 and an assessment of their current status and critical habitat in the ALS was conducted. Our manatee conservation efforts were recognized in 2001 when September 7th was officially declared the ―National Day of the Manatee‖ in Mexico. Almost 350 species of birds occur in the ALS, including the Mexican Duck (Anas diazi), which is undergoing a slow but marked decline due to habitat destruction and overhunting. The largest threats to the ALS include unsustainable sugar cane cultivation, cattle-ranching, coastal urban development, oil and gas exploration and exploitation, water pollution by urban waste and agricultural runoff, and increases in port and tourism industries. Despite the establishment of government policy and measures to protect the coastal wetlands of ALS, the identified threats continue to menace the important biodiversity and human wellbeing of the region.
INTRODUCTION The Alvarado Lagoon System (ALS) in south-central Veracruz state (Figure 1), Mexico, is a large mangrove dominated coastal wetland located 70 km southeast of the Port of Veracruz. It has a total area of 2800 km2 of which 258 km2 are covered by water. The Alvarado Lagoon (AL) is a shallow system (average depth 1.5 m) connected to the Camaronera Lagoon by a narrow channel and to the Gulf of Mexico (GOM) via a 0.4 km wide sea channel [Moran-Silva et al., 2005, Cruz-Escalona et al., 2007]. The AL has a maximum width of 4.5 km and a mean surface area of 62 km2. The ALS is mainly formed by the Alvarado, Buen Pais, Camaronera and Tlalixcoyan lagoons, but it is also associated with a great number of smaller aquatic bodies, flood zones, and parts of the Acula, Blanco, Limon and Papaloapan rivers. The Papaloapan River extends through the states of Oaxaca, Puebla and Veracruz and traverses a distance of 445 km, passing through the city of Tlacotalpan and finally emptying into the AL. The Papaloapan drainage basin covers an area of approximately 39,200 km2. The ALS is one of the most productive estuarine-lagoon systems in the Mexican GOM [Cruz-Escalona et al. 2007]. It is characterized by a large diversity of interactions with its adjacent systems, particularly an extensive marsh, which contributes greatly to its biological productivity. Seasonal changes are well pronounced and are mainly influenced by the precipitation-drought regime conditions associated with its ecosystem. The ALS has three separate zones based on physicochemical characteristics; Camaronera Lagoon, Buen Pais Lagoon and the urban zone of Alvarado Lagoon, and the river zone of Alvarado Lagoon [Moran-Silva et al., 2005]. Model studies suggest that primary production by sea grasses provides more energy input to the ecosystem than detritus, which is the opposite of most other Mexican GOM lagoons
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and estuaries. This may be a consequence of relatively rapid flushing (50 x 109 m3 of water each year), a short water exchange time (0.5 days), mangrove deforestation, and overfishing [Cruz-Escalona et al., 2007]. The increase of anthropogenic activities in the surrounding terrestrial areas coupled with limited waste management planning have contributed to both local and regional deterioration of the hydrological characteristics of the ALS [Cruz-Escalona et al., 2007].
Figure 1. Satellite photograph of the Alvarado Lagoon System showing the major lagoons and rivers of the area. Image courtesy of the Consejo de Desarrollo del Papaloapan (CODEPAP, 2003), Xalapa, Ver., Mexico
ENVIRONMENT AND IMPACT Mercury and Other Water Quality Parameters We collected sediment, fish, and unfiltered water samples from the Alvarado Lagoon, Lagoon Camaronera, and the Gulf of Mexico during the wet (September 2005) and dry (March 2003 and 2005) seasons (Table 1). Water column pH values were slightly alkaline (7.6-8.6) and the salinity ranged from 1-25.5 psu. Precipitation amounts for the dry season months of March 2003 and March 2005 were 0.23 cm, and 2.79 cm, respectively, and the wet season month of September 2005 was 272 cm. Salinity in the ALS was inversely correlated with rainfall, with highest levels occurring in the dry season samples (March 2003 and 2005) and lowest levels occurring in the wet season samples (September 2005) (Table 2). Our salinity values are similar to the salinity ranges (1-14 psu) reported for the lagoon during the 2000-2001 wet, dry, and storm seasons [Moran-Silva et al., 2005]. Levels of nitrate (NO3-N mg/L) during the 2000-2001 season ranged from 0.03-0.14 mg N/L [Moran-Silva et al., 2005]. Our values for nitrate (NO3-N mg/L) during the 2003 dry season ranged from 0.73-2.3
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mg NO3-N/L. These values are slightly higher than the 2000-2001 values and may be indicative of increasing anthropogenic stressors within the lagoon system. Estuaries are considered at medium risk for eutrophication when nitrate values range from 0.1-1 mg N/L and high euthrophic risk when the values are greater than 1 mg N/L [Bricker et al., 1999]. It has been noted that nutrient levels within the lagoon can vary seasonally and spatially as a result of river discharge, rainfall, resuspension of sediments, and biological activity [MoranSilva, et al. 2005]. Concentrations of total inorganic carbon (TIC) ranged from 14.4-22.1 mg C/L and did not vary seasonally. Levels of total organic carbon (TOC) ranged from 3.9-20.9 mg C/L, with the highest concentrations observed during the rainy season (Table 2). Total mercury and total suspended solids (TSS) ranged from 0.92-26.1 ng Hg/L and 139.2 mg TSS/L, respectively (Table 2). The strong correlation (R2=0.71; P=0.001) between total mercury and TSS in the water column suggests that particulate matter is a carrier phase for mercury within the Alvarado and Camaronera lagoons. A more comprehensive study of the Alvarado Lagoon, and the Limon, Acula, Blanco, and Papaloapan rivers conducted during the March 2003 and 2005 dry seasons and the September 2005 wet season found that mercury concentrations were significantly correlated with total suspended solids in the water column (R2=0.82; P<0.001) [Guentzel et al., 2007]. The mercury concentrations in the Alvarado Lagoon, and the Blanco, Acula, and Limon rivers during the March 2003 and 2005 dry seasons (0.9-4.9 ng Hg/L) were similar to the September 2005 wet season (1.9-4.9 ng Hg/L), with higher Hg levels associated with higher levels of TSS. Water samples collected from the Papaloapan River were higher in Hg (10.9-12.7 ng (Hg/L) and TSS (89.1-154.7 mg TSS/L) during the September 2005 wet season than the March 2003 and 2005 dry seasons (0.9-2.7 ng Hg/L; 4.8-39.7 mg TSS/L). The sites from the Papaloapan River were sampled within 12 hours of a nighttime rainfall (15cm) event during the September 2005 wet season. The elevated Hg concentrations from this site during the wet season are likely a result of increased particulate matter transport within the river during high flow conditions and or input of dissolved and particulate Hg from precipitation [Guentzel et al., 2007]. A Mercury Deposition Network (MDN) monitoring site (HD01) within this region reported a rainfall Hg concentration of 11.4 ng Hg/L during the time period that the samples were collected from the Papaloapan River [Mercury Deposition Network]. The water column values that we observed for total Hg (0.92-26.1 ng/L) are below the US EPA ambient surface water quality criteria for freshwater (0.77-1.4 µg/L) and saltwater (0.94-1.8 µg/L) (US EPA, 2006) and the Mexican marine aquatic life criteria of 0.02 µg/L [Jimenez et al., 1999]. Table 1. Station identifications and locations for mercury and other water quality parameters
Alvarado Lagoon
Lagoon Camaronera
Gulf of Mexico
Station Identification I T BB DD EE FF AA
Latitude (N) 18 46.132 18 45.955 18 44.995 18 51.178 18 51.589 18 51.716 18 48.422
Longitude (W) 095 47.333 095 48.607 095 44.966 095 54.654 095 55.187 095 54.412 095 44.420
Table 2. Water quality parameters measured during the March 2003 and 2005 dry season and the September 2005 wet season ,
Month
Station
Salinity (psu)
Nitrate NO3-N (mg/L)
pH
Total Inorganic Carbon (mg C/L)
Total Organic Carbon (mg C/L)
Total Suspended Solids (mg/L)
Total Mercury (ng/L)
Lagoon Camaronera
March 2003 March 2003 March 2003 March 2005 September 2005 March 2003
Gulf of Mexico
March 2003
I T BB T T DD EE FF AA
9.9 9.8 6.7 12.9 1 14.5 14 13.8 25.5
2.3±0.9 1.35 1.51 0.86 1.08 0.75 0.73±0.8
8.1 8.0 7.9 8.1 7.6 8.2 8.2 8.3 8.6
14.9±4.2 14.4 14.7 22.1±0.16 16.7 17.2 17.6 17.9 16.4±0.47
5.4±2.1a 4.7a 3.9a 9.5±0.98a 20.9a 7.3 7.8 7.6 6.5±0.04a
9.1±4.5a 1a 14.1a 9.1±5.6a 25a 39.2 18.6 20.5 1.13a
0.92±0.05a 1.78a 2.67a 0.92±0.03a 3.8a 26.1 5.2 10.3 1.27±0.01a
Alvarado Lagoon
The values for March 2003 stations I and AA, and March 2005 station T represent the mean and standard deviation of 2 replicate field samples. ―a‖ denotes that the total organic carbon, total suspended solids and total mercury data for the Alvarado Lagoon and Gulf of Mexico are taken from Guentzel et al., 2007. ―― denotes that there is no data for this parameter.
Table 3. Mercury concentrations in fish, crab, shrimp, and squid and log bioconcentration (BCF) factors from the Alvarado Lagoon system n Brown Shrimp (Peneus aztecus)* Bay Squid (Lolliguncula brevis)* Blue Crab (Callinectes rathbunae)* White Mullet (Mugil curema)* Sheepshead (Archosargus probatocephalus)* Big Mouth Sleeper (Gobimorus dormitor)* Fat Snook (Centropomus parallelus)* Spine Snook (Centropomus ensiferus)* Striped Moharra (Eugerres plumeri)* Catfish (Bagre marina)*
20, 20, 20 3 3 2 1 2 2 1 1, 2 1
Total Hg (ug Hg/g-wet) March March September 2003 2005 2005 0.008±0.001 0.065±0.01 0.008±0.001 0.024±0.002 0.026±0.002 0.057±0.026 0.082 0.106±0.02 0.152±0.034 0.35
0.301±0.117 0.291
0.184
March 2003 3.6 4.2 4.2 5.6 4.7
Log BCF March 2005 4.6
4.8 4.9 5.3
5.3 5.3
September 2005 3.6
5.1
*The data for mercury concentration is taken from Guentzel et al., 2007. The log BCF is calculated as Log 10([Hg in tissue]/[Hg in water]). The average water concentration of Hg was 1.6 ng/L. n=the number of samples.
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We collected sediment from the lagoons and nearby rivers within the ALS. Total mercury at station T in the AL ranged from 13-22 ng Hg/g-wet and the %C and %N ranged from 0.230.77% and 0.31-0.37%, respectively. Total Hg from sediments in the adjacent rivers (Acula, Limon, Blanco, and Papaloapan) ranged from 10-78 ng Hg/g wet and the %C and %N ranged from 05-8.9% and 0.31-0.9%, respectively. There was a moderate correlation (R2=0.435, p=0.020) between the total Hg and % carbon in the sediments from the ALS [Guentzel et al., 2007]. The total Hg values for the sediment we collected are below the threshold effects level of 130 ng Hg/g dry for marine sediments [Buchman 1999] and are within the US EPA background sediment criteria of 0-300 ng Hg/g dry (US EPA 1997). Aquatic biota that represent ~87% of the annual catch from the ALS [Cruz-Escalona et al., 2007] were collected and analyzed for total Hg (Table 3). The total Hg concentration in the invertebrate species (shrimp, squid, crab) ranged from 0.008-0.026 μg Hg/g wet and the vertebrate species ranged from 0.082-0.35 μg Hg/g wet. The levels of Hg in the piscivorous and omnivorous fish (catfish, moharra) are at or slightly above the recommended consumption level of 0.3 μg Hg/g wet [NAS, 2000]. The log bioconcentration factors for total Hg in the organisms we collected ranged from 3.9-5.3, with no observable seasonal difference (Table 3). Activities such as biomass burning for land clearing, mangrove deforestation, and urbanization are known stressors to the ALS. These activities are also associated with increased mercury mobilization in aquatic and terrestrial environments, which can result in an increase in the bioaccumulation of mercury in biota from these systems [Friedli et al., 2003; Porvari et al., 2003; Munthe et al., 2007]. There are a large number of indigenous riverbank communities within the ALS that rely on fishing for comestible and economic subsistence. Reported total Hg levels in hair samples from individuals that reside and consume fish from within the ALS ranged from 0.10-3.36 µg Hg/g (n=47) [Guentzel et al., 2007]. Of these values, 58% are above the recommended consumption limit of 0.1 µg Hg/kg body/day which corresponds to a hair level of 1.0 µg Hg/g [NAS, 2000]. Anthropogenic activities that mobilize Hg could result in an increase in the mercury content of the fish and seafood from the ALS which may ultimately lead to increased body burdens of mercury in the indigenous peoples that reside in this region.
Vegetation The ALS features representative and diverse ecosystems of Mexico´s Gulf coastal plain, such as coastal dunes, reed beds of Cyperus spp., cattail Typha spp., palm forests of Sabal mexicana, Scheelea liebmannii, and Acrocomia mexicana, oak forest of Quercus oleoides; apompales (Pachira aquatica), and a large mangrove forest dominated by Avicenia germinans, Laguncularia racemosa, and Rhizophora mangle [Vazques-Torres, 1998]. There are 15 distinguishable landscape units (LU) in the area [Portilla-Ochoa et al., 1998 and SilvaLópez and Portilla-Ochoa 1998]. The LU were first differentiated as areas disturbed by agricultural activities, areas disturbed by cattle ranching, and areas where human intervention is not yet considerable, such that natural vegetation remains the dominant landscape element. Each LU was described in terms of land use, seasonal flooding, vegetation cover (i.e. primary and secondary), predominant exploitation systems, the physical medium (i.e. substrate origin and soil type), hydrologic characteristics, and other data (e.g. human settlements, main roads,
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and observations on deforestation, urban and rural infrastructure, and industrial development) [Silva-López and Portilla-Ochoa 1998 ].
Fish There are 107 fish species that have been collected in the ALS which represent four ecological guilds: marine stenohaline, marine euryhaline, estuarine, and freshwater fishes. Fish assemblages of the Alvarado Lagoon Estuary have not experienced significant changes over 40 years, but there may have been a decline in fish biodiversity during that period [Chávez-López et al., 2005a]. A comprehensive study of Mayan cichlids conducted in the ALS, by Chavez-Lopez et al., 2005b, reports that there are three genera and seven species of cichlids (Cichlidae) with the Mayan cichlid (Cichlasoma urophthalmus) being the species with the highest abundance. The Mayan cichlid is distributed throughout southeastern Mexico where it inhabits rivers and coastal lagoons. In the ALS it is distributed towards the north in Camaronera Lagoon. The Mayan cichlid inhabits oligohaline to mesohaline sites that are well oxygenated and contain submerged vegetation and deep transparent water. The major abundance and biomass of this species was obtained during December to February. The diet of Mayan cichlids is primarily herbivorous and consists mainly of plant detrital material and algae. There are two size classes that occur during the dry and rainy seasons which correspond to young of the year and reproductive fish. There is only one modal size class of fish between 60–100 mm during the stormy season. Although individuals with developed gonads are found throughout the year, the most reproductive adults are found between April and December. The highest gonadosomatic index (GSI) values occurred during the May through July time period of peak reproductive activity [Chávez-López et al., 2005b]. Other families with numerous species reported within the ALS include the Eleotridae and the Gobiidae, and the species with the highest abundance and biomass were Gambusia affinis, Petenia splendida, Cathoropus melanopus, Diapterus auratus, and Bathygobius soporator [Shareet et al., 2009]. A study by Pelaez-Rodriguez et al., (2005) examined the diet of demersal piscivorous fishes captured as bycatch by the commercial shrimping fleet just ouside of the ALS . Nine collections distributed throughout the stormy, wet, and dry seasons from November 1993 to January 1995 yielded a total of 646 fishes which represented 10 families and 14 species. 44.9% of these collections had empty digestive tracts and were excluded from the study. The most abundant species of dermersal predators found were Trichiurus lepturus and Synodus foetens. Differences in food consumption of the seven most abundant predators were observed among the 3 seasons. The greatest variety of prey (20 species) occurred during the stormy season and the lowest variety (nine species) occurred during the dry season. Prey type and location of prey within the water column helped to determine the classification of five distinct trophic guilds based on an overall index of relative importance of prey. The occurrence of these different trophic guilds may contribute to decreased competition for food resources on the continental shelf off of Alvarado lagoon [Peláez-Rodríguez et al., 2005].
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River Otters A study of the neotropical river otter (Lontra longicaudis annectens) and its habitat based on personal observations and the information provided by fishermen of the ALS, yielded three observations of adult otters hunting and eating in lagoons and rivers, together with records of otter tracks and feces. In addition, an adult otter skin was found in a fisherman‘s house in November 2002, where residents of the ALS said the otter was killed that year. All of these records were collected in three of the most conserved LU of the system, which include an area of 607 km2, encompassing more than 22.7 % of the total area of the ALS [Silva-López, 2009]. These observations and records, along with comments made by other Alvarado fishermen, suggest the neotropical river otter occupies the ALS year-round, and emphasizes the need to conduct more detailed surveys and studies to determine the present status and ecology of the ―perro de agua‖ (as it is locally known) and its habitat [Silva-López, 2009].
Manatees Antillean manatees (Trichechus manatus manatus) have historically occurred in the ALS, representing one of the most important areas for manatees in the southern GOM. Overexploitation reduced their numbers in the 1970s and 1980s and they are now considered endangered throughout their range in Mexico. However, the rescue of six orphan calves suggests that manatees may be increasing in the ALS. Historically, the Antillean manatee was found from northern Veracruz state along the west coast of the GOM to the eastern coast of the Yucatan peninsula and the Mexico-Belize border [Lluch, 1965, Lefebvre et al., 2001, Morales-Vela et al., 2005]. However; hunting, water quality degradation, and the destruction of breeding habitat has caused a decline in the number of manatees [Campbell and Gicca, 1978, Colmenero and Hoz, 1986]. There is little information regarding the life history of manatees in the state of Veracruz. It is not known if they migrate, as the Florida subspecies (Trichechus manatus latirostris) does in the United States [Deutsch et al., 2003], or whether they are year-round residents of their local habitat, as is typical of Antillean manatees in the Yucatan Peninsula of Mexico and in Belize [Morales-Vela et al., 2000, Self-Sullivan et al., 2003]. Movements of Antillean manatees in Chetumal Bay, on the east coast of the Yucatan Peninsula, do not appear to be influenced by cloudiness, atmospheric pressure, or temperature, in contrast to the Florida manatee that migrates seasonally in response to intra-annual changes in water temperature [Axis-Arroyo et al., 1998, Deutsch et al., 2003]. However, movements of Antillean manatees in Chetumal Bay were moderately associated with water salinity (as in Florida), depth and group structure [Axis-Arroyo et al., 1998]. Manatees in Florida seem to prefer areas with access to freshwater that they require for osmoregulation. The salinity in the waters of the ALS decreases with distance from the ocean, and the potential influence of this salinity gradient on the movements of manatees in the ALS is unknown. Manatees in Nicaragua undergo seasonal migrations, and their daily movements appear to be influenced by tides, which may also influence water salinity [Jimenez, 2002]. In the ALS fishermen have reported that manatees were quite common in the region in the mid-1900s. Even though large scale
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hunting of manatees was not practiced in ALS, the sale of meat in the town market of Alvarado during the 1970‘s was common [Ortega-Argueta, 1999], and poaching continues to be an important threat to the species. Studies conducted in the mid 1980s reported the disappearance of manatees from the ALS [Colmenero, 1984]. Nevertheless, recent reports from local residents of the ALS, and the incidental capture of manatee calves, have confirmed their continued occurrence in the Alvarado region [Ortega-Argueta, 1999; Portilla-Ochoa et al., 1999]. A recent study assessing manatee distribution and habitat utilization found that manatees could potentially be found in 3150 km2 of lowlands and wetlands in the ALS (Figure 2) [Ortega-Argueta, 2002]. Habitats selected by manatees include estuaries, mangrove wetlands and unpopulated areas. The marine zone appears not to be utilized permanently by manatees, although they may move locally between rivers along the coast through the marine zone. Threats to the manatees in the ALS include the clearing of land for sugar cane cultivation, cattle-ranching, coastal urban development, mangrove deforestation, increases in port and tourism industries in the coastal zone, water pollution, and oil and gas exploration and exploitation [Ortega-Argueta, 1999, 2002]. Rodriguez-Ibañez [2004] investigated the knowledge, use, and cultural traditions of the inhabitants of the ALS with respect to the Antillean manatee using oral interviews. She found a large number of correlations between the inhabitants‘ oral history knowledge of manatee movements and habitat use with current scientific knowledge as determined by a review of the literature. Additionally, many inhabitants knew a lot about the hunting, butchering, and preparing of manatee meat for human consumption. Such hunting has reduced the manatee population in the ALS to very low levels [Ortega-Argueta et al., 2003].
Figure 2. Classification of manatee habitat within the Alvarado Lagoon System (from Ortega-Argueta, 2002). Most of the best habitat lies in the lagoons along the Limon river and in lagoons between the Limon and Acula rivers. The Papaloapan river is not good manatee habitat due to its rapid current and channelizing with dikes that prevent animals from entering and leaving the river easily.
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During several interview surveys conducted with local inhabitants and fishermen, besides boat and airplane surveys in 2000, 2005 and 2006 it was revealed that manatees are common in the ALS around the year [Ortega-Argueta, 2002, Portilla-Ochoa et al., 2006, 2007, Keith et al., 2009]. Manatees are most commonly sighted in the Acula River and adjacent lagoons, and are rarely sighted in the Limon River and adjacent lagoons (Figure 3). Most of the interviewees reported that manatees are not as abundant now as compared to three decades ago, but their numbers have increased in the past few years (Figure 4). Most of the sightings are of adult animals, although females and calves are infrequently seen (Figure 5). Most sightings occur in the rainy season (Figure 6), and most sightings are unique in the sense that an animal is usually only seen once, rather than frequently or repeatedly (Figure 6). Respondents thought that manatees predominantly feed on marsh plants and water hyacinth, with ―grasses‖ and other emergent plants also being important in the diet (Figure 7). A recent survey of the ALS using visual, acoustic, and side-scan sonar methods estimated the abundance of manatees in the ALS at 0.93 manatees/ha ± 0.39 (95% CI) [Serrano-Solis, N.D.].
Figure 3. Locations of manatee sightings (from both vessels and aircraft), interviews and evidence of manatee butchering (from Ortega-Argueta, 2002).
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Figure 4. Increase in the number of manatee sightings over the past decade as determined by interviews with residents of the ALS. Most of the interviewees reported that manatees are not as abundant now as compared to three decades ago, but their numbers have increased recently. This increment in observations may reflect a recovery of the manatee population; a more dedicated monitoring effort; or an increase of the appeal of the species as results of the education and awareness campaigns.
Figure 5. Age-class of manatees sighted in the ALS as determined by interviews with residents. Most of the sightings are of adult animals, although females and calves are infrequently seen
Figure 6. Seasonality and frequency of manatee sightings in the ALS as determined by interviews with the residents. Most of the sightings occur in the rainy season and most sightings are unique in the sense that an animal is usually only seen once, rather than frequently or repeatedly
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Figure 7. Foods of manatees as reported by residents of the ALS. Respondents thought that manatees predominantly ate marsh plants and water hyacinth, with ―grasses‖ and other things also being important in the diet
We also found that the inhabitants of the ALS maximized their use of the manatees killed in the distant past, including the medicinal use of powdered manatee bones and manatee fat, and the use of manatee bones and teeth in the production of artifacts. This suggests that manatees played a significant role in the culture of these riverbank communities in the past. A majority of those interviewed (82%) said they were interested in protecting animals liberated near their homes in the ALS. However, several respondents expressed concern that neighbors would kill released animals and/or that hunting would continue because of lack of enforcement of the laws [Portilla-Ochoa et al., 2006, 2007, Keith et al., 2009]. Manatee poaching continues in many areas despite official protection. This illegal activity is still practiced for a number of reasons: tradition; an appreciation of manatee meat, which is considered a delicacy; ignorance of national laws and sanctions in force to protect the manatee, and limited inspection and vigilance by Mexican environmental and regulatory authorities (Ortega-Argueta, 1999).
CONSERVATION The coastal wetland lagoon system of Alvarado is one of the most productive such systems in Veracruz and the third largest wetland in Mexico. A total 350 species of birds have been registered in the ALS, including the Mexican Duck (Anas diazi), which is undergoing a slow but marked decline due to habitat destruction and overhunting. The ALS has been considered a high priority region for conservation [Arriaga-Cabrera et al., 1998; CONABIO, 1998; Dugan, 1993], including recognition by the North American Wetlands Conservation Council (NWCCA), the International Council for Bird Preservation-Mexico Chapter (CIPAMEX), and Mexico‘s Commission on Biodiversity (CONABIO). Notable, too, are the threats, including agricultural encroachment and increasing levels of contamination from urban wastewater and pesticides. A newly funded program will enable the municipality of Alvarado and Pronatura Veracruz (local NGO) to strengthen the environmental education program in Alvarado schools; teach sustainable management techniques to local communities
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and train them to be conservation promoters; and develop wetland-conservation outreach materials for use by local authorities. A conservation easement will be pursued at a site of high importance to wetland-associated birds. Partners will work to reduce the effects of cattle ranching on wetland resources and will continue monitoring resident and migratory birds in the area. These activities will be coordinated with the newly formed Veracruz State Committee for Conservation of Wetlands. One of the most important achievements of our conservation activities in Veracruz was the nomination of Alvarado lagoon system as a Ramsar Site. On February 4th, 2004, the ALS was designated Ramsar Site No. 1355 through the efforts of the Institute for Biological Research (IBR) at the University of Veracruz, and other organizations such as the North American Wetlands Conservation Council. The area encompasses 2671 km2 that includes most of our proposed critical manatee habitats and other areas that are crucial to manatee survival. The ecological description of the site mentions the region‘s importance to this endangered species. The IBR is taking further actions with the collaboration of local authorities in order to assure the implementation of protective measures and to establish a Regional Management Plan for the area. Further information on the ALS Ramsar Site can be found on the following web page: http://www.ramsar.org/wwd2004_rpt_mexico1.htm. After several workshops involving specialists and governmental agencies, including the ―Technical Advisory Subcommittee for Manatee Recovery in Mexico‖, it was concluded that in order to protect the manatees in the ALS from continued poaching, the primary mortality factor, an education and awareness program should be developed throughout the ALS. Additional components included an assessment of the current status of manatees in the ALS and the identification of critical manatee habitats within the ALS [Ortega-Argueta, 1999, 2002, Portilla-Ochoa et al., 2002]. These efforts led to the preparation of a ―Regional Manatee Recovery Plan in the Wetlands of Alvarado, Veracruz, Mexico‖ [Ortega-Argueta et al., 2001, 2002, 2003], and culminated in 2001 when September 7th was officially declared the ―National Day of the Manatee‖ in Mexico. With the potential for the release of rehabilitated manatees from the Veracruz Aquarium into the ALS, there is need for continued educational and informational campaigns to further educate the local community about the need to protect and conserve manatees and their habitat. Over the intervening years our educational, conservation, and outreach activities have continued, including informative workshops for children and adults in the communities within and surrounding the ALS, boat surveys of the ALS for manatees, interviews with fishermen and others familiar with the ALS and putative manatee habitats there, and continued celebration of the ―National Day of the Manatee‖ [Ortega-Argueta et al., 2001, 2002, 2003, Portilla-Ochoa et al., 2002,]. The rescue of orphan manatees in the ALS suggested that the population of manatees might be rebounding, and this has motivated the conservation and education efforts of the past decade [Ortega-Argueta et al., 2002, 2003]. During this period, six orphan manatees have been rescued from the ALS and transported to the Veracruz Aquarium in the city of Veracruz, Mexico. A seventh animal was rescued but subsequently died from a gunshot wound. As the captive population in the aquarium has grown, they have constructed a new, larger, manatee pool and viewing area, sufficient to support 4-6 manatees. The possibility that more orphan manatee calves may be encountered in the future has raised the concern that the aquarium will no longer be able to continue to accept new orphans without some mechanism to decrease the total number of animals being cared for there. The ability to release some animals will increase the Aquarium‘s capability to foster new orphans if and when they should be found.
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Rehabilitation strategies and sites for release are being discussed in the Manatee Advisory Committee. An agency of the government of the state of Veracruz, the ―Papaloapan Development Council‖ (Consejo de Desarrollo del Papaloapan, CODEPAP) has recently constructed two concrete-lined tanks suitable for manatee husbandry along the banks of the Acula River in the central ALS. These tanks were designed and constructed to facilitate the reintroduction of captive manatees into the ALS. Plans are currently underway to transfer some of the manatees from the Veracruz Aquarium to these tanks and to begin their transition to a free-ranging existence. Once the manatees have become accustomed to feeding on the native vegetation, and have been weaned from their dependence on humans, it is anticipated that they will be released into an enclosure along the bank of the Acula River, and eventually into their native habitat. Such husbandry constitutes an opportunity to rehabilitate and release individuals of one of the most threatened species in Mexico.
CONCLUSION The Alvarado Lagoon System is a mangrove dominated coastal wetland formed by the confluence of the Acula, Blanco, Limon and Papaloapan rivers. The ALS is one of the most productive estuary-lagoon systems in the Mexican GOM. It has a total area of 2800 km2 of which 258 km2 are covered by water with an average depth of 1.5 m. Vegetation of the ALS includes diverse ecosystems representative of Mexico´s Gulf coastal plain. Salinity in the ALS was inversely correlated with rainfall, with highest levels occurring in the dry season samples (March 2003 and 2005) and lowest levels occurring in the wet season samples (September 2005). Concentrations of total inorganic carbon did not vary seasonally, while levels of total organic carbon were higher during the rainy season. A strong correlation between total mercury and total suspended solids in the water column suggests that particulate matter may be a carrier phase for mercury within this lagoon system. Historically, Antillean manatees were found in the ALS and along the west coast of the Gulf of Mexico to the eastern coast of the Yucatan peninsula and the Mexico-Belize border. However, hunting, water quality degradation, and the destruction of breeding habitat has caused a decline in the number of manatees and they are now considered endangered throughout their range in Mexico. Manatee habitat in the ALS includes estuaries, mangrove wetlands and unpopulated regions, with a total potential area of 3150 km2. Interviews with the inhabitants of the ALS reveal important correlations between their oral history knowledge of manatees with current scientific knowledge. They also knew a lot about the hunting, butchering, and preparing of manatee meat for human consumption. The inhabitants maximized their use of the manatee carcass, including the medicinal use of powdered manatee bones and manatee fat, and the use of manatee bones and teeth in the artisanal production of artifacts, suggesting that manatees played a significant role in their culture in the past. A majority of those interviewed said they were interested in protecting manatees, but several expressed concern that hunting would continue because of lack of enforcement of the laws. Manatee poaching continues for a number of reasons including tradition; an
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appreciation of manatee meat that is considered a delicacy; ignorance of national laws and, and limited vigilance by Mexican environmental and regulatory authorities. In 2001, September 7th was officially declared the ―National Day of the Manatee‖ in Mexico. Our educational and informational campaigns have continued in order to educate the local communities about the need to protect and conserve manatees and their habitat. In 2004, the ALS was designated Ramsar Site No. 1355 and a ―Regional Manatee Recovery Plan in the Wetlands of Alvarado‖ was prepared. Over the past decade, six orphan manatees have been rescued from the ALS and transported to the Veracruz Aquarium in the city of Veracruz. Two concrete-lined tanks suitable for manatee husbandry have recently been constructed along the banks of the Acula River in the central ALS. These tanks were designed and constructed to facilitate the reintroduction of captive manatees into the ALS. Such efforts constitute an important opportunity to rescue, rehabilitate, and release individuals of one of the most threatened species in Mexico. Continuing threats to the ALS include increasing anthropogenic activities both within the lagoon system and in its surrounding terrestrial areas. Limited waste management planning and practices have contributed to deterioration of its hydrological characteristics. Overfishing, manatee poaching, and loss of habitat have lead to a significant deterioration in the quality of ecosystem services provided by the ALS. Despite the establishment of government policy and measures to protect the coastal wetlands of ALS, the identified threats continue to menace the important biodiversity and human well-being of the region.
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Morán-Silva, A., Martínez- Franco, L. A., Chávez-López, R., Franco-López, J., M. BediaSánchez, C. M., Espinosa, F. C., Mendieta, F. G. Brown-Peterson, N. J. & Peterson, M. S. (2005). Seasonal and Spatial Patterns in Salinity, Nutrients, and Chlorophyll a in the Alvarado Lagoonal System, Veracruz, Mexico. Gulf and Caribbean Research, 17, 133143. Munthe, J., Hellsten, S. & Zetterberg, T. (2007). Mobilization of mercury and methymercury from forest soils after a severe storm-fell event. Ambio, 36, 111-113. National Academy of Sciences (NAS). (2000). Toxicological effects of methylmercury. National Academy Press, Washington, DC USA. 368. Ortega-Argueta, A. (1999). Situación actual y las perspectivas de conservación del manatí en el sistema lagunar de Alvarado, Veracruz, Mexico. Informe Técnico presentado a la Dirección General de Vida Silvestre, INE-SEMARNAP. Instituto de Ecología, A.C., Xalapa, Ver., México. Ortega-Argueta, A. (2002). Evaluación del Hábitat del Manatí (Trichechus manatus) en el Sistema Lagunar de Alvarado, Veracruz, México. M.Sc. Thesis. Wildlife Management Program, Instituto de Ecología, A. C. Xalapa, Ver., México. Ortega-Argueta, A., Portilla-Ochoa, E. & Keith, E. O. (2001). A Regional Manatee Recovery Plan for the Alvarado Lagoon System, Veracruz, Mexico. Poster presented at the XIV Biennial Conference on the Biology of Marine Mammals, Vancouver, BC, Canada. 28 November-3 December. Ortega-Argueta, A., Portilla-Ochoa, E. & Keith, E. O. (2002). Manatee recovery plans for wetlands of Alvarado, Veracruz, Mexico. Final Report to the Save the Manatee Club, 35. Ortega-Argueta, A., Portilla-Ochoa, E. & Keith, E. O. (2003). Manatee recovery plan for wetlands of Alvarado, Veracruz, Mexico. Annual Report to the Wildlife Trust, Ref. #0203-099. 32. Pelaez-Rodríguez, E., Franco-López, J., Matamoros, W. A., Chávez-López, R. & BrownPeterson, N. J. (2005). Trophic Relationships of Demersal Fishes in the Shrimping Zone off Alvarado Lagoon, Veracruz, Mexico. Gulf and Caribbean Research, 17, 157-167. Portilla-Ochoa, E., Silva-López, G., García Campos, H. & Ramírez-Salazar, M. (1998). Paisajes amenazados en el complejo lagunar de Alvarado. In: G., Silva-López, VargasG. Montero, & J. Velasco-Toro, (editors). De Padre Río y Madre Mar: Reflejos de la Cuenca Baja del Papaloapan, Veracruz. Editora del Gobierno del Estado de VeracruzLlave, Veracruz, México. Vol. II. 257-263. Portilla-Ochoa, E., Paradowska K. & Cortina-Julio, B. E. (1999). Educación ambiental y planeación participativa para la conservación del manatí en Alvarado, Veracruz, México. Informe Técnico presentado a la Dirección General de Vida Silvestre, INE-SEMARNAP. Instituto de Investigaciones Biológicas, Universidad Veracruzana. Portilla-Ochoa, E., Cortina-Julio, B. E., Ortega-Argueta, A., Keith, E. O. & Vanoye-Lara, F. (2002). Achievements of the manatee conservation program in Veracruz, Mexico. Manatee Conservation Workshop accompanying the XXVII International Annual Meeting for the Study of Marine Mammals, Veracruz, Ver., Mexico. Portilla, E., Hernández, J. R., Contreras, C., Cortina, B. E. & Keith, E. O. (2006). Status and recovery of the Antillean manatee (Trichechus manatus manatus) in the Alvarado Lagoon System, Veracruz, Mexico. Annual meeting of the Sociedad Mexicana de Mastozoología Marina and the Sociedad Latinoamericana de Especialistas de Mamíferos Acuáticos, Mérida, Yuc., México.
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Portilla-Ochoa, E., Ortega-Argueta, A., Cortina-Julio, B., Contreras-Torres, C., HernándezMontero J. & Keith, E. O. (2007). Status and recovery of the Antillean manatee (Trichechus manatus manatus) in the Alvarado Lagoon System, Veracruz, Mexico. Sirenews – Newsletter of the IUCN Sirenian Specialist Group, 49, 8. Porvari, P., Verta, M., Munthe, J. & Haapanen, M. (2003). Forestry practices increase mercury and methymercury output from boreal forest catchments. Environmental Science and Technology, 37, 2389-2393. Rodríguez-Ibañez, C. (2004). Conocimiento, uso, y manejo del manatí Trichechus manatus manatus del Sistema Lagunar de Alvarado, con énfasis en la historia oral. Tesis para el título de Licenciado en Biología, Universidad Veracruzana, Xalapa, Ver., 96. Self-Sullivan, C., Smith, G. W., Packard, J. M. & Lacommare, K. S. (2003). Seasonal occurrence of male Antillean manatees (Trichechus manatus manatus) on the Belize barrier reef. Aquatic Mammals, 29, 342-354. Silva-López, G. & Portilla-Ochoa, E. (1998). Conservación y Manejo Sustentable de Recursos Naturales en Unidades del Paisaje del Humedal de Alvarado, Veracruz, México. Reporte Académico al US Fish & Wildlife Service (14-48-98210-97-G082). Universidad Veracruzana, Xalapa, Ver., México. Silva-Lopez, G. (2009). Records For The neotropical river otter In landscapes of the Ramsar site Alvarado Lagoon System, México IUCN/SCC Otter Specialist Group Bulletin , 26,162. Serrano-Solis, A. Diagnostico de poblaciones de manaties: Monitorea ambiental en el sistema lagunar de Alvarado. Technical Report, Universidad Veracruzana, Tuxpan, Ver. N.D. 54. Shareet, C. F. Z., Jonathan, F. L., Escorcia, H. B., Arenas, L. G. A., Sanchez, C. B., Silva, A. M. & Vasquez-Lopez, H. (2009). Trophic Seasonal Behavior of the Ichthyofauna of Camaronera Lagoon, Veracruz. Journal of Fisheries and Aquatic Sciences, 4, 75-89. U.S. EPA Mercury study report to congress, (1997). http://www.epa.gov/mercury U.S. EPA National recommended water quality criteria, (2006). http://www.epa.gov/wa terscience/criteria/wqctable/ Vasquez-Torres, M., Humedal de Alvarado: diversidad vegetal. In Vazques-Torres, S.M. (editor). (1998) Biodiversidad y problematica en el humedal de Alvarado, Veracruz, Mexico. Editorial Universidad Veracruzana. Veracruz, Mexico. Pp 143-168.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 417-433 © 2011 Nova Science Publishers, Inc.
Chapter 15
ADAPTIVE LAGOON FISHERY DEVELOPMENT THROUGH SUSTAINABLE LIVELIHOODS APPROACH: A CASE STUDY OF CHILIKA LAGOON, INDIA Shimpei Iwasaki Research Fellow of Japan Society for the Promotion of Science, Research Institute for Humanity and Nature, Kyoto University, Japan
ABSTRACT Fishery resource in the lagoon environment is the primary form of livelihood for survival and affects lives in different ways. For centuries, fishermen used to keep a certain harmony with fishery resources in a traditional manner but they have been faced with various vulnerabilities in managing fishery resources and their related livelihoods. This chapter presents a case study of fishing communities in Chilika Lagoon (India) with emphasis on adaptive capacity to respond to changes in the lagoon environment. It explores pressing constraints and positive strengths of lagoon fishery development by applying the concept of Sustainable Livelihoods Approach (SLA). The research is based on five livelihood assets analysis developed by DFID with due consideration of vulnerability assessment and institutional contexts. Drawing on Chilika Lagoon experience, the study revealed that vulnerabilities to fishery livelihoods are affected by climatic and environmental dimensions as well as by socio-economic and cultural values. The range of pressing constraints for fishing communities covers not just fishing but also marketing, schooling, social relations, social infrastructure and environmental and disaster prevention awareness. This exposure posed grave threats in lowering the capability of people in the choice of lagoon fishery development, leading to less income generation and its associated byproducts. In contrast, the study identified several attempts to cope with the underlying root causes of failure in resource-based development. The Chilika Development Authority (CDA), for instance, implemented hydrological interventions in 2000, resulting to fisheries enhancement with a spectacular increase in fish landings. The elaborations undertaken by CDA also made great contributions to institutional arrangements for
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Shimpei Iwasaki watershed management with a concept of participatory micro-watershed management that has enabled the upper communities to upgrade their socio-economic status as well as mitigate the impacts of siltation. Importantly, innovative activities which are considered to be positive strengths of lagoon fishery development have been commonly associated with the involvement of various stakeholders to adjust to the ecological-social-economic system in response to actual or expected impacts. Finally, this chapter draws some suggestions on adaptive strategies for fishery development in Chilika Lagoon and potential implications to other lagoons all over the world. The findings in Chilika Lagoon fisheries provide answers to the enquiry on holistic and integrated measures to sustain lagoon fisheries by putting forward the principle of SLA.
INTRODUCTION Our planet‘s essential goods and services consist of the functions of biological diversity. An ecological sphere rich in variety and endowed with highly-productive ecosystem services in which fishery resources are present provides attractive benefits. Fishery resource is the primary form of people‘s livelihood for survival, especially in coastal and lagoon areas. It is a major source of food protein for human beings representing at least 15 per cent of the average per capita animal protein intake of more than 2.9 billion people [1]. Significant demands for fishery resources create employment opportunities for many people around the world [2]. Indeed, the number of fishers including aquaculturists has grown faster than the world‘s population, and faster than employment in traditional agriculture during the past three decades [1, 3]. In 2004, an estimated 51 million people were making their entire or partial living from fish production and capture [4], the great majority of these in Asian countries [1, 3]. The characteristic of fisheries varies to some extent from place to place. However, it is interesting to note that a significant proportion of fishing population comprises ‗small-scale fishermen‘, especially from developing countries. It is estimated that there are 51 million fishermen in the world of whom 50 million (around 98 per cent) are small-scale, subsistence, or artisanal fishermen [4]. In general, they are continuously living amidst severe poverty. India, for instance, is one of the best cases to illustrate this situation as the prominent presence of a ‗caste system‘ (a social structure in which classes are determined by heredity) is deeply entrenched in defining the societal status of the fishers [5]. In local caste hierarchies, fishing occupation is regarded low as Shudras or out-of-caste (untouchables) by other higher castes in different regions of the Indian subcontinent. On this account, the term ‗small-scale fishermen‘ has been traditionally referred to as a minority group due to its so-called low socio-economic status in most parts of the world. Prior to the modern era, it is interesting to note that small-scale fishermen used to keep a certain harmony with fishery resources as a whole. Many studies have shown that fishing communities conserved fishery resources in a good condition because of a complicated traditional system of partitioning fishing activities along low population density and poor fishing gears [6-10]. In India, a regulatory system of traditional fisheries in a niche space among the sympatric castes is commonly observed so that the differences in resource use patterns allowed the caste groups to avoid competitive exclusion [6]. These traditional
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customs at the community level played a great and important role in managing fishery resources in a sustainable manner. However, the present situation tends to break or weaken such good customs and practices in many parts of the world; fishing communities have been faced with difficulties in managing sound fishery resources due to a wide variety of vulnerabilities such as climate change, population growth, technological development, market fluctuations, institutional changes, among others. Revenue-oriented thoughts is a good example that often induce dominant persons/groups such as government officials and capitalists to apply for destructive fishing methods or gear practices, accounting for numerous losses of fishery resource stocks. Such practices destroy fish ecology and then undermine people‘s capacity to adapt to fishing activities especially for small-scale fishermen. Out of various geographical types of fishery domain, such situations are particularly applicable to lagoon fisheries. The lagoon is situated at both extremity of watersheds and sea marine, which are of a dynamic and complex environmental character: these are transitional ecosystems between land and sea and between fresh and marine water. With spatial and temporal changes in the lagoon environment, these areas are physically or climatically subject to various influences not only from their internal environment but also the adjacent marine and terrestrial places including watershed areas. In other words, the lagoon ecosystem being influenced by extra-local shocks combined with rapid anthropogenic pressures tends to increase vulnerable conditions in fish ecology. To ensure that small-scale fishers can achieve wise use of fishery resources sufficiently over time, there is a need to explore the vulnerability of lagoon fisheries and its associated livelihoods in the local context. Thus, this chapter sets out to identify the pressing constraints and positive strengths of lagoon fishery development through a case study of Chilika Lagoon, India.
Livelihood Assets In order to achieve
H
• Shocks • Trends • Seasonality
S
N Influence & Access P
F
Key H = Human capital N = Natural capital F = Financial capital S = Social capital P = Physical capital
Source: modified from DFID [16] Figure 1. Sustainable Livelihoods Framework
Transforming Structures& Processes
Livelihood Outcomes
STRUCTURES
• More income • Increased well-being • Reduced vulnerability • Improved food security • More sustainable use of natural resources
• Levels of Government • Private sector
••Laws • •Policies • Culture •Institutions
PROCESSES
Livelihood Strategies
Vulnerability Context
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SUSTAINABLE LIVELIHOODS APPROACH The term ‗vulnerability‘ is crucial to identify pressing constraints and positive strengths of fishery operation and related activities in the lagoon environment. The origin of this word ‗vulnerability‘ lies in the Latin vulnus, meaning ‗a wound‘, and vulnerare, ‗to wound‘ [11]. In particular, Kelly and Adger [11] pointed out that the word vulnerable derives from the late Latin vulnerabilis which is enlightening and vulnerabilis was the term used by the Romans to describe the state of a soldier lying wounded on the battlefield, i.e., already injured therefore at risk from further attack. On the whole, vulnerability can be portrayed in the degree to which a system is susceptible or unable to cope with negative effects of natural or man-made variability and extremes. Although a common conceptualization of vulnerability has never been shared among academic and development practitioners [12-14], it is usually characterized as some form of the characteristic, extent and frequency of exposures and sensitivity, and people‘s capacity to adapt to these hazards. Consistent with the characteristics, Smit and Wandel [13] depicted a basic vulnerability relationship that takes into account a broad scale of determinants corresponding to three components (exposure, sensitivity and adaptive capacity) of vulnerability. In the exposed lagoon environment and the people who are sensitive to varying influential sources of climatic and hydrological changes at multiple scales, small-scale fishermen need to adapt to the impacts of changes in the ecological-social-economic systems. Thus, the last third function (adaptive capacity) of vulnerability is a critical key in building people‘s resilience to the lagoon environment. With this recognition, this chapter applied the ‗Sustainable Livelihoods Approach (SLA)‘ in an effort to understand the vulnerable contexts of Chilika Lagoon fisheries. SLA represents a new paradigm of poverty reduction, and is an innovative tool originally developed by UNDP on the basis of the 1987 UN Environment Summit and Chambers and Conway[15]. SLA provides a way of thinking about livelihoods of poor people in the context of vulnerability [16]. The application of SLA helps researchers and practitioners identify pressing constraints and positive strengths of lagoon fishery development with overlaps between micro and macro links. According to the SLA model developed by DFID [16], the framework compromises three components: ‗livelihood assets (natural, financial, social, human and physical capital)‘, ‗vulnerability context (vulnerability analysis)‘ and ‗structure and process (institutional analysis)‘ (Figure 1). The SLA has been applied flexibly in various ways, but the framework places high emphasis on the linkages among the three components so that users are encouraged to draw up the best adaptive strategies called ‗livelihood strategy‘ with ‗livelihood outcomes‘. However, the SLA has seldom been applied to field situations especially in the sector of fisheries [17-18]. In this sense, this chapter makes an enquiry into addressing holistic and integrated measures to sustain lagoon fisheries by utilizing the principle of SLA. On the basis of SLA, field surveys were conducted in Chilika Lagoon twice: between November 2005 and February 2006 and in June 2009. The case study was carried out in eight fishing communities of Chilika Lagoon with two communities each located in the north, central south and the outer channel sectors of Chilika Lagoon. The research used both qualitative and quantitative data, including structural questionnaires, key informants interviews and secondary data. In this chapter, primary data from structural questionnaires were collected from 25 fishermen (N=195), 20 women (N=160) and 15 fisher-children
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(N=110) in each fishing community, although in some instances the survey failed to collect data samplings of 5 fishermen and 10 fisher-children because of the small population in certain communities. The questionnaires used a multiple-choice format and were compiled into three sections; general information (age, caste, education, literacy), fishing and marketing activities and livelihood conditions. In addition, semi-structured interviews with key informants (government officers, village leaders, NGOs, researchers) were carried out to validate and complement the information.
PROFILE OF FIELD STUDY SITE (CHILIKA LAGOON) Chilika Lagoon is the largest brackishwater lagoon in Indian sub-continent, situated at latitude 19°28‘ and 19°54‘ north and longitude 85°05 and 85°38‘ east (Figure 2). The lagoon extends from southwest corner of Puri and Khurdra districts to the adjoining Ganjam district of Orissa state. The pear-shaped lagoon is around 64.3 km long and its width varies from 18 km to 5 km and, is connected to the sea through irregular water channels with several small sandy and usually ephemeral islands [19]. The average lagoon area is 1,055 sq km which increases to 1,165 sq km during the rainy season and shrinks to 906 sq km during the summer season. Chilika Lagoon becomes less saline during the rainy season due to flood waters from 52 rivers and rivulets. It becomes more saline during the dry season as the supply of flood water is cut off when the south wind begins to blow and saline waters enter from the Bay of Bengal at high [20]. The lagoon has three hydrologic sub-systems (Mahanadi delta, western catchments, and the Bay of Bengal) influencing the hydrological regimes as shown in Figure 2. The total inflow of freshwater from the Mahanadi delta has been estimated to be 4,912 million cu.m., accounting for 80 per cent of the total water flow. The maximum discharge of 3,182 million cu.m. comes from Makara River, followed by Bhargavi River (1,108 million cu.m.) and Luna River (428 million cu.m.) [19]. Meanwhile, the western catchments account for 20 per cent of the total fresh water flow. Chilika Lagoon itself can be broadly divided into four sectors (northern, central, southern and outer channel) with distinctive ecological characteristics in water depth and salinity (see Figure 2). The lagoon having four distinctive ecological sectors is a unique assemblage of marine, brackish and freshwater ecosystems with estuarine characteristics. This mixed combination has endowed it with valuable biodiversity and highly productive ecosystem in which fishery resources present attractive benefits. The rich lagoon ecosystem supports the livelihood of more than 200,000 fishermen and thousands of local people who are engaged in allied fishery business activities including boat operators, food processors, fish merchants and fish delivery operators [19, 22]. This valuable ecosystem service provides fishery resources that cater to the needs of Orissa state and other states such as West Bengal, Bihar, Madhya Pradesh, Tamil Nadu and Kerala states [19]. There are reported to be 127 fishing villages in Chilika Lagoon with estimated fishery families of 12,363 (ibid). With regard to fishing occupation, traditional fishermen include seven sub-caste groups: Keuta, Niari, Kartia, Kandara, Gokha, Tiara and Nolia [23]. Most of them belong to Schedule Caste (SC) and their societal status is quite low as they belong to the poorest of society.
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Northern Sector
Chilika Lagoon Central Sector
Old Mouth Outer Channel New Mouth
Southern Sector
Catchment along the Sandbbar
Source: modified from Ghosh and Pattnaik [21] Figure 2. Map of Chilika Lagoon
VULNERABLITY ASSESSMENT THROUGH LIVELIHOOD ASSETS ANALYSIS This section sets out to assess fishery vulnerability through livelihood assets analysis (natural, human, financial, physical and social capital) on the basis of the SLA model developed by DFID. The research seeks to identify the vulnerable context of each capital with regard to fishery livelihoods in Chilika Lagoon. It provides better insight into understanding
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the underlying issues of Chilika Lagoon fisheries and then throws light on fishery adaptation in an appropriate manner.
Natural Capital More or less, fishery development depends on the availability of fishery resources. On the point of resource stocks, Chilika Lagoon has experienced severe environmental deterioration primarily from siltation since the 1980s. In combination with anthropogenic pressures such as deforestation, overgrazing and industrialization, seasonal climate forces such as cyclones and floods brought a lot of silt into the lagoon. This caused shutting of the sea mouth between the sea and lagoon, leading to adverse impacts on the availability of fishery resources. The closure of the sea mouth affected the salinity level of the lagoon and prevented exchange of migratory fish species, which account for nearly 80 per cent of lagoon fisheries catch [24]. In addition, the silt accumulation reduced the water spread area and hindered the exchange of water between the sea and river, resulting in decreased salinity and lower availability of fish species in the lagoon. Siltation into the lagoon also encouraged the prolific growth of freshwater invasive species. The area of Chilika Lagoon dominated by invasive plants increased 20 sq km in 1972 to 685 sq km in May 2000 [22]. The spread of the invasive species restricted the feeding as well as the breeding ground of many marketable aquatic species. As a result, these changes reduced the area of fishing grounds in Chilika Lagoon. This led to loss of income that renders fishermen more to the brink of poverty. The weed invasion presented physical difficulties for boat navigation, further undermining people‘s adaptive capacity to changes in the lagoon environment.
Financial Capital The livelihoods of fishing communities largely depend on the fisheries from Chilika Lagoon. Most of them have no secondary occupation, so fishing is the sole source of income. On the whole, members of fishing boats in Chilika Lagoon are limited to family or neighbours, and their profits are equally distributed among them. Household incomes per month in 2005 (N=195) are Indian Rupee (INR) 1,540 (approximately US$ 34) 1 in the lean season and INR 3,303 (approximately US$ 72) in the harvest season, respectively2. Their incomes are not sufficient to cover their living expenses in the lean season especially during the monsoon period because they often cannot go fishing due to extreme rainfall and strong winds. Maintenance of fishery livelihoods often requires the purchase or repair of fishing gears, these being high exhaustive goods. Due to this situation, most of the fishermen fall into indebtedness. The fishermen borrowed money from mahajans – dominant fish merchants (4 per cent) and commission agents (68 per cent) to purchase or repair fishing gears. On the 1 2
An exchange rate of US$1 = INR 45.85 is used in 2005. Seasonality was purposely divided into two seasons (lean and harvest seasons). The seasonal difference is derived from amounts and profits of fish and prawn landings; fishermen catch more fishery resources from March to August and less in the rest of the months.
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average, the aggregate indebtedness per fishermen amounted to INR 28,506 (approximate US$ 622) from those lenders in 2005. Fish merchants seeks to exploit the fishermen in the fish marketing process in combination with money lending with interest free. The loan provisions are addressed through purchasing or repairing fishing gears, instead of informal fish trade promises that debtors shall deal their entire catch with the merchants. This give-and-take system led to the dominant control of fish merchants resulting to the fishermen selling their catch at lower than market price. Consequently, the dependency between fishermen and specific fish merchants pushes fishery households to the brink of indebtedness and led to the nearly-defunct primary fishery cooperative societies (PFCSs) which stopped managing cooperative fish marketing and then weakened people‘s unity in lagoon fisheries management [25]. The exploitative marketing situation drives the fishermen to operate indiscriminate fish catch for survival which can bring about failures in resource-led development [26].
Social Capital Perpetual conflicts over fishery resources especially between fishermen and nonfishermen caste have been observed in Chilika Lagoon. Tracing back the history of Chilika Lagoon, the traditional fishermen caste has naturally enjoyed fishing as an exclusive legal right but this situation changed in response to the 1991 guideline which gave rights to nonfishermen caste as well. It meant legally allowing outsiders to enter the fisheries in limited areas of Chilika Lagoon while excluding the local fishermen to some extent. Furthermore, ambiguous demarcation of each fishing ground enabled others to encroach on exclusive fishing grounds. Many fishing grounds are encircled by trapping nets (khandas) that make it difficult to adopt multi-strata use of fishing activities in one spot as practiced by the traditional fishermen caste before. Meanwhile, the decrease in the water spread area due to siltation (corresponding to natural capital), extensive gherry operation3 and human population growth push traditional fishermen more to the brink. Those sensitivities and exposures to decreasing fishing grounds in terms of social and natural dimensions gave rise to perpetual resource-based conflicts especially between fishermen and non-fishermen caste plaguing human lives, livelihoods and dignity.
Physical Capital The physical environment surrounding the fishing communities of Chilika Lagoon is very poor. The fishermen are forced to make use of unreliable boat jetties attached to raised ground. Once tremendous climate hazards occur, social infrastructure including fish landing centers and community roads are easily damaged in part by fallen trees. Villagers stressed that their fishing equipment tend to be broken or lost. The losses or damages of fishing equipment lead to suspension of fishing activities as well as require enough money to
3
Gherry is made either of earthen embankment or bamboo and a net enclosure [27-28].
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purchase or repair those materials, which induce them to become more reliant on dominant fish merchants, in terms of indebtedness. On the other hand, poor housing conditions make them vulnerable to climatic and environmental hazards. Some housing with partially-stripped roof can be observed due to a lack of sufficient household income. In particular, there is no sanitary facility in many parts of the fishing communities in Chilika Lagoon so that the local people are prone to various waterborne diseases which are relevant to human capital. Moreover, many people in fishing communities have less access to medical support because of lack of income and the remoteness of their village.
Human Capital Educational status in fishing communities of Chilika Lagoon is low. Instead of attending school, the boys tend to start fishing to help their families survive. Around 26 per cent of fishermen including boat members (N=462) had no educational experience while only around 5 per cent fishermen had entered college or university. Most of the fishermen (55 per cent) dropped out before high school except those who had no educational experience. On this account, 60 per cent of the people can read and write in their native language (Oriya). Such characteristics are particularly prominent among women (95 per cent school dropout and 20 per cent literacy rates). The high illiterate population resulted to various constraints on alternative jobs, health care and formal credit taking that are largely linked to enhancement of other capital assets. Lower education limits alternative jobs except fishing and related industries so that there is an increasing trend of fishing population in Chilika Lagoon. It creates high competition over limited fishery resources and triggers disputes among the fishermen. Children who have started fishing are more vulnerable to climate variability and extreme events than the adults, but there is no choice for them but to engage in fisheries. The root cause for this is mainly attributed to the lack of household income, but also linked to affairs of formal schooling. Villagers argued that some of children were reluctant to go to high school because of caste discrimination. Most high school are situated in non-fishing villages where a sense of caste discrimination strongly prevails leading to one or more obstacles for entering high school.
ADAPTIVE STRATEGIES FOR LAGOON FISHERY DEVELOPMENT This section explores adaptive strategies for fishery development in Chilika Lagoon. The primary goal of SLA is to develop an understanding of the factors that lie behind people‘s choice of livelihood strategy and then to reinforce the positive aspects as well as mitigate the pressing constraints toward sustainability (DFID, 1999-16). On the basis of vulnerability assessment through livelihood assets analysis, Table 1 shows expected fisheries strategies, showing the impacts on vulnerability and institutional contexts. The key expected adaptive strategies can be compiled into three components: integrated lagoon fisheries management, wise use of fishery resources and resilient fishing communities.
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Shimpei Iwasaki Table 1. Adaptive Strategies for Fishery Development in Chilika Lagoon by SLA
Livelihood Assets Natural Capital
Major Problems Related to Fishery Livelihoods Decrease of fish species Decrease of fishing grounds Boat navigation trouble
Financial Capital
Lack of fishery income High rate of indebtedness
Social Capital
Inequitable fish trade Resource-based conflict
Physical Capital
Poor social infrastructure Loss or damage of fishing equipment
Human Capital
School dropouts Increase in fishing population Vulnerable health condition especially for fisher-children
Root Causes
Adaptive Countermeasures
Soil erosion from upstream Closure of sea mouth Proliferation of freshwater weeds Illegal and destructive fisheries Decrease of fish species Exploitative marketing structure Resource-based conflicts Loan dependency on fish merchants Lower capacity of primary fishery cooperative societies Ambiguous demarcation of fishing grounds Improper consensus building for resource allocation change of fishing rights Lack of political power Lack of unity for disaster prevention
Hydrological interventions Involvement of stakeholders in watershed management Enhancing environmental awareness
Less fishery income Caste discrimination in schooling
Strategic loan provision for fishing equipment
Revitalization of primary fishery cooperative societies Proper demarcation of fishing grounds with rapport building among relevant stakeholders
Promotion of disaster insurance scheme Enhancing disaster prevention awareness Strategic loan provision for education Eradication of racial discrimination
Integrated Lagoon Fisheries Management The domain of lagoon fishery development is largely corresponding to the availability of fishery resources. However, the ecosystem of Chilika Lagoon was under severe environmental threat. Importantly, siltation (soil erosion) is identified as among the most serious environmental problems in combination with climate variability and human pressures. Siltation from upstream leading to the shrinkage of the water spread area, decrease in salinity and prolific growth of weed infestation had adverse impacts on the habitat of wildlife including fishery resources. Indeed, fish landing statistics in several decades showed how fishing activities were hampered by rapid changes in the lagoon environment especially in the 1990s. In an effort to solve the serious situation, Chilika Development Authority (CDA), which was established in 1991, implemented hydrological interventions (e.g., opening of a new mouth and dredging of water channels) in the year 2000 (see Figure 2). The interventions were successful and contributed to the dramatic natural restoration. In particular, the opening of a new mouth exhibited positive impacts on lagoon ecosystem especially fisheries enhancement with a spectacular increase in fish landings (see Figure 3). Fish landing of 14,053 metric tons in 2003-04 was an all-time record high, compared to the all-time low of around 1,600 metric tons prior to the interventions. However, it should be kept in mind that
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the technical interventions can be just temporal end-of-pipe measures to cope with siltation. Together with the overexploitation of fishery resources, there has been a gradual decrease in fish landing quantities after the hydrological implementation, so additional elaboration was needed to take into account how to reduce the risk impacts of siltation in a proactive manner. Under the circumstances, CDA has further adopted and expanded participatory microwatershed management projects since 2001 that seek to involve local people in the projects, in order to mitigate the impacts of siltation caused by climate extreme events combined with anthropogenic pressures. Greater emphasis has been placed on community participation including women and the landless or the poor to enhance the win-win situation of livelihood improvement and soil conservation. On this account, a watershed association was established in each project site, where members are the local people. In collaboration with relevant stakeholders, the responsibility of project implementation has been entrusted to the association. Within the association, the watershed committee implements the day-to-day activities of the watershed development projects, leading to stronger and better participation of local residents in the watershed areas. It is responsible for coordination and liaison with the Gram Panchayat and government agencies concerned to ensure smooth implementation of the watershed development projects. In this way, CDA acted in a leading role in the coordination of environmental watershed governance between upstream and downstream communities. Practices regarded as lagoon fisheries management linking to watershed conservation help develop a pathway for strengthening adaptive capacity to changes in the lagoon environment. Trend of Fish Landing Quantity from 1929 to 2008
MT 16000
14000
Yearly Average Fish Landing Amounts 3 Years Average Fish Landing Amounts
12000 10000 8000
6000 4000 2000 0
1929 1934 1939 1944 1949 1954 1959 1964 1969 1974 1979 1984 1989 1994 1999 2004
Source. modified from DFGO [29], DFGO and CDA [30], CDA data Figure 3. Trend of Fish Landing Quantity from 1929 to 2008
Table 2. Total amount of loan availed by PFCSs from different financial sources (Unit: Indian Rupee)
Amount of Finance Amount of Demand Collection Balance
Source: ARCSCCB [33]
Bank 38,75,150 38,75,150 21,91,284 16,83,866
Government 11,27,500 11,27,500 5,50,696 5,76,804
NCDC 24,48,960 22,18,996 2,29,366 19,89,630
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In an effort to maintain (and preferably improve) fish stocks in Chilika Lagoon, there is a need, therefore, to incorporate fisheries management into sea mouth and watershed management. Elaborations are needed to enhance or maintain multiple linkages, horizontally (across space) and vertically (across levels of organization) [31-32]. In this sense, it is of use to introduce a notion of integrated lagoon fisheries management (ILFM) in which fisheries management, sea mouth management and lagoon watershed management have to be balanced towards sustainability.
Wise Use of Fishery Resources It needs to be mentioned that fishermen tend to operate indiscriminate fish catch. The underlying cause of illegal and destructive fisheries is partly linked to exploitative fish marketing structure combined with informal money lending. Thus, enhancing environmental awareness and strategic loan finance from formal banking institutions are strongly recommended to eradicate their illegal and destructive activities. In this regard, however, considerate efforts are required to solve the latter challenge because attempts had already failed in private and government banks. In the past, these banking institutions provided loans to the fishermen for the purpose of reducing dependency on fish merchants, but debtors could easily escape the duty for loan repayment from the lenders while continuing to lie about who were debtors [33]. Indeed, Table 2 shows that only 57 per cent, 49 per cent and 10 per cent of total loan amounts were repaid to private banks, government banks and National Cooperative Development Corporation, respectively [34]. On this account, the formal banking institutions were forced to withdraw the loan scheme for small-scale fishermen. It created more space for control of the fish economy by fish merchants combined with informal money lending, which catalyzed a greater incentive for the fishermen to operate fish catch indiscriminately. To address this issue, it is helpful to know that there is an innovative approach to loan finance and cooperative fish marketing developed by the South Indian Federation of Fishermen Society (SIFFS). SIFFS supported a large number of fishing communities in the south of India by providing loan finance from banks to each fisherman with due capacity assessment and introducing automatic deduction of loan repayment from pay through cooperative fish marketing. Instead of cutting off the loan dependency with fish merchants, SIFFS encouraged the fishermen to join cooperative fish marketing activities for economic improvement as well as solution for ‗loan waiver‘. This effort gives a great clue to solve the loan issue and then bridge the gap between controlled and actual price in Chilika Lagoon (see Iwasaki [35]). Furthermore, lagoon fishery development is also largely linked to people‘s access to fishery resources as well as the presence of resource stocks. Perpetual conflicts over fishery resources especially between fishermen and non-fishermen caste undermined people‘s security plaguing human lives, livelihoods and dignity. Except for the outer channel sector, most of the fishermen strive to stay on boats near their grounds for several days so as not to allow others to encroach on their fishing grounds4. A sense of insecurity is commonly observed in Chilika Lagoon [28, 35] that caused the fishermen to do unfavorable fish trade 4
In the outer channel area, fishing grounds were close to the villages because of the productive and eco-sensitive nature of this area in Chilika lagoon so they are able to monitor encroachments from their villages.
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with commission agents on the boat [36]. Aside from loan finance, it further strengthened fish transaction with specific commission agents who made adjustments to meet the multiple needs of fishermen: the commission business was combined with the sale of basic materials and favourable trade location by boat-to-boat transaction, which made a great contribution to not only ensuring that fishing grounds are not encroached upon but also saving on their work and fuel oil in the fish delivery process to buyers. However, the merchants could have a more incentive to demand exploitative fish trade with the fishermen, irrespective of debt, taking advantage of insecurity affairs. In an attempt to solve the resource-based conflicts, the realistic feasible approach may be to precisely define the ambiguous demarcation of leased grounds. The defective demarcation of each leased ground made by the Orissa government enabled non-fishermen caste to encroach on leased grounds owned by fishermen caste or to occupy unauthorized leased grounds inside Chilika Lagoon. Therefore, an appropriate demarcation of leased grounds is strongly recommended to remove the underlying cause of resource-based conflicts. Moreover, there is a strong need to develop rapport and consensus building among all fishermen through deliberate discussions with appropriate rules and management for common-pool resources in Chilika Lagoon.
Enhancing Resilient Fishing Communities The practice of fisheries itself is prone to be physically affected by various types of climate and environmental hazards. Destructive natural hazards that frequently occur in Chilika Lagoon cause serious damages to fishing communities. In particular, people such as the aged, disabled, women and children are highly vulnerable. Despite the early age, for instance, children forced to start fishing are being exposed to severe climate hazards including strong sunlight and cold winds. There is no alternative for them but to engage in fisheries; the entrance to schooling is disallowed due mainly to the lack of financial capital. Thus, a strategic loan provision undertaken by SIFFS may offer one way to improve their livelihoods and make sure that children are able to go to school and kept in a safe environment. In addition, another effort needs to be made to eradicate caste discrimination in formal schooling. Discrimination induces school children to join fisheries despite the fact that its lifestyle makes them physically vulnerable to climate hazards. Hence, deliberate discussions on castism among relevant stakeholders are of high importance to promote resilient fishery development in Chilika Lagoon. In addition, their physical capital is so low that it will be easily damaged or lost when disastrous events occur in Chilika Lagoon. On this account, promotion of natural calamity insurance supported by Department of Fisheries and Animal Resources Development has been implemented. The insurance scheme enables all people including the poor to mitigate the sudden shocks of climate variability and extreme events. It was promoted through primary fishery cooperative societies (PFCSs) which were able to mediate the insurance scheme between their associated members and the government effectively. Taking into account the increased intensity and frequency of natural disasters in Orissa state [37], the initiatives will play a greater role in responding to the direct and indirect effects of climate change in the long run. There is, of course, negative aspects to be considered. Fishermen do not tend to adjust themselves to changes in climate and environment variability, even though catastrophic
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climate extreme events such as cyclones and floods devastate their private and public property including fishing equipment. Therefore, enhancing disaster prevention awareness and the sense of unity among the local people is recommended to mitigate the impacts of climate and environmental hazards.
CONCLUSION Putting them all together, this chapter sought to put the principle of sustainable livelihoods approach (SLA) into fishery development in the case study of Chilika Lagoon. Livelihoods approach with an overlap between micro and macro links reflects a wide variety of poverty aspects that give a clue to figuring out pressing constraints and positive strengths of lagoon fisheries development. The findings revealed that the range of fishery improvements covers not just occupational activities but also multifaceted aspects of fishery livelihoods that determine the extent of their capacity to adapt to the lagoon environment. The domain of expected fishery strategies in Chilika Lagoon covers all encompassing aspects including fishing, marketing, schooling, social cohesion, social infrastructure and environmental and disaster prevention awareness. The increase in fish species, for instance, meets an important requirement of capability for lagoon fishery development but is not a necessary precondition. The dominant fish marketing structure by fish merchants undermines fishermen‘s capacity to adapt to the ecological-social-economic system while access to fishing grounds also affects them to a great extent. These vulnerabilities triggered dropouts in school and caused young people to enter the fishing industry, resulting in an increase in overfishing population and subsequent practice of illegal and destructive fisheries. These interactions may lead to a negative chain of lagoon fishery development unless considerable efforts are made. Furthermore, the people in fishing communities have been under severe threats of climate and environmental hazards. Each vulnerability factor among their livelihood assets influences the extent of their capacity to cope with the downside risks. On this account, it implies that issues that lie behind fishery development in Chilika Lagoon will defy any attempt at a quick and simple solution. In this regard, expected adaptive strategies in Chilika Lagoon fisheries are presented in Table 1. There are several positive strengths of lagoon fishery development in Chilika Lagoon. In particular, hydrological interventions and participatory micro watershed management can be of very significance in maintaining (and preferably improving) the lagoon environment and fishery resource. In addition, the promotion of disaster insurance and strategic loan financial schemes helps fishery households, which are largely dependent on fisheries, in mitigating the impacts of climate and environmental extreme events. Of particular note is that these innovative efforts are commonly associated with the involvement of various stakeholders. In this way, further collaborative and cooperative efforts among relevant stakeholders will be required towards resilient lagoon fishery development. Finally, the application of SLA is rather new and still evolving, so the research method has been applied flexibly in various ways by researchers and policy makers. In this chapter, the analysis related to lagoon fisheries requires more examination of the interaction among households on how to allocate their own resources and services to family members. In this
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way, a better understanding of lagoon fishery development and their related livelihoods in the community context can be developed.
ACKNOWLEDGMENT The author acknowledges the support of a JSPS grant. The author is extremely grateful to Dr. Ajit Kumar Pattnaik, Chief Executive Officer, CDA for offering his wholehearted support. He is also thankful to Mr. Durga Prasad Dash, Secretary, Pallishree, for kind assistance during his stay in Bhubaneswar and Chilika Lagoon.
REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14]
FAO, (2009). The state of world fisheries and aquaculture 2008. Rome: Food and Agriculture Organization. FAO, (1995). Code of conduct for responsible fisheries. Rome: Food and Agriculture Organization. FAO, (2007). The state of world fisheries and aquaculture 2006. Rome: Food and Agriculture Organization. Pomeroy, S. R. & Rivera-Guieb, R. (2006). Fishery co-management: a practical handbook. Ottawa, ON and Cambridge, MA: CABI Publishing and International Development Centre. Sekhar, U. N. (2004). Fisheries in Chilika lake: how community access and control impacts their management. Journal of Environmental Management, 73, 257-266. Deb, D. (1996). Of cast net and caste identity: memetic differentiation between two fishing communities of Karnataka. Human Ecology, 24, 1, 109-123. Iwakiri, S. (1974). Approaches to economic progress of rural fisheries in the developing countries. Mem. Fac. Fish., Kagoshima Univ., 23, 81-103. Iwakiri, S. & Neaz, M. (1982). Methodological study on fisheries planning in the developing countries. Mem. Fac. Fish., Kagoshima Univ., 31, 35-56. Matthews, E., Veitayaki, J. & Bidesi, R. V. (1998) Fisian villagers adapt to changes in local fisheries. Ocean & Coastal Management, 38, 207-224. Sekhar, U. N. (2007). Social capital and fisheries management: the case of Chilika lake in India. Environ Manage., 39, 497-505. Kelly, M. P. & Adger, N. W. (2000) Theory and practice in assessing vulnerability to climate change and facilitating adaptation. Climatic Change, 47, 325-352. Cannon, T. (1994). Vulnerability analysis and the explanation of ‗natural‘ disasters. In A. Varley, (Ed.), Disasters, development and the environment in disasters, Chichester, UK: Wiley. Smit, B. & Wandel, J. (2006). Adaptation, adaptive capacity and vulnerability. Global Environmental Change, 16, 282-292. Ziervogel, G., Bharwani, S. & Downing, E. T. (2006). Adapting to climate variability: pumpkins, people and policy. Natural Resources Forum, 30, 294-305.
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[15] Chambers, R. & Conway, R. G. (1992). Sustainable rural livelihoods: practical concepts for the 21st century. IDS Discussion Paper 296, Institute of Development Studies, University of Sussex, Brighton. [16] DFID, (1999). Sustainable livelihoods guidance sheets. Department for International Development, UK. [17] Allison, H. E. & Ellis, F. (2001) The livelihoods approach and management of smallscale fisheries. Marine Policy, 25, 377-388. [18] Allison, H. E. & Horemans, B. (2006). Putting the principles of the sustainable livelihoods approach into fisheries development policy and practice. Marine Policy, 30, 757-766. [19] CDA, (2008). Chilika: the atlas of Chilika. Bhubaneswar: Chilika Development Authority. [20] Patro, S. N. (2001). New challenges to Chilika. In Indian Environmental Society (Ed.), Proceedings of the 5th Asia Pacific NGOs Environmental Conference APNEC-5, 22-25 September 2000, Agra: Indian Environmental Society. [21] Ghosh, K. A. & Pattnaik, K. A. (2005). Chilika lagoon: experience and lessons learned brief. http://www.iwlearn.net/publications/ll/chilikalagoon_2005.pdf. [22] CDA, (2005). Achievement report 2005. Bhubaneswar: Chilika Development Authority. [23] Mitra, N. G. & Mahapatra, P. (1957). Bulletin on the development on the chilika lake of orissa survey report on the fishing industry. Cutack: 0rissa govt. press. [24] Pattnaik, K. A. (2005). Impact of unauthorised shrimp culture on fishery resources of Chilka lagoon. Mimeo. Bhubaneswar: Chilika Development Authority. [25] Iwasaki, S. (2008). Managing fishery cooperatives towards self-development: lessons from coastal India. Paper prepared for International Conference on Managing Wetlands for Sustainable Development: Innovative Research and Lessons Learned, Effective Partnerships, and the Need for Co-Management, Trang, Thailand, 9-11 January 2008. [26] Misra, M. P. (2002). Eco-development of Chilika lagoon to perpetuate the wonder in twenty first century. In Chilika Development Authority, Department of Water Resources (Orissa) (Eds.) Proceedings of the International Workshop in Sustainable Development of Chilika Lagoon, Bhubaneswar: Chilika Development Authority. [27] Samal, C. K. (2002). Aquaculture (shrimp) industry in and around Chilika lake: its impact on environment. In B., Mishra, C. G. Kar, & N. S. Misra, (Eds.) Agro-industries and economic development: a vision for the 21st Century. New Delhi: Deep and Deep Publications. [28] Samal, C. K. & Meher, S. (1999). Socio-economic survey of villages in and around Chilika. mimeo. Bhubaneswar: Nabakrushna Choundhury Centre For Development Studies. [29] DFGO, (1970). Tha Chilka lake. Cuttack: Directorate of Fisheries, Government of Orissa. [30] DFGO, CDA (eds) (2005). Collection and estimation of fish, prawn and crab landings statistics in the Chilika Lagoon, Annual Report – 2003-04. Bhubaneswar: A collaborative programme of Department of Fisheries, Government of Orissa and Chilika Development Authority. [31] Berkes, F. (2004). Rethinking community-based conservation. Conservation Biology, 18, 3, 621-630.
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[32] Berkes, F. (2005). Common theory for marine resource management in a complex world. Senri Ethnological Studies, 67, 13-31. [33] ARCSCC, (2005). Information on the working of fishery co-operatives in Chilika Circle, Balugaon, Assistant Register of Co-operative Societies (Fy) Chilika Circle Balugaon. Bhubaneswar: Assistant Register of Co-operative Societies Chilika Circle. [34] Iwasaki, S. (2007). Fishery resource allocation system in Chilika lagoon, India and its social impacts to fisherman villages. Dissertation. Graduate School of Kyoto University, Kyoto. [35] Pattnaik, S. (2007). Conservation of environment and protection of marginalized fishing communities of lake Chilika in Orissa, India. Journal of Human Ecology, 22, 4, 291302. [36] Iwasaki, S. & Shaw, R. (2008). Fishery resource management in Chilika lagoon: a study on coastal conservation in the Eastern Coast of India. Journal of Coastal Conservation, 12, 43-52. [37] Iwasaki, S., Razafindrabe, H. N. B. & Shaw, R. (2009). Fishery livelihoods and adaptation to climate change: a case study of Chilika lagoon, India. Mitigation and Adaptation Strategies for Global Change, 14, 339-355.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 435-455 © 2011 Nova Science Publishers, Inc.
Chapter 16
VERTICAL FLUX OF ICE ALGAE IN A SHALLOW LAGOON, HOKKAIDO, JAPAN Yoko Niimura1, Hiroaki Saito2, and Satoru Taguchi*3 1
2
Tokyo University of Fisheries, Tokyo, Japan Hokkaido National Fisheries Research Institute, Hokkaido, Japan 3 Soka University, Tokyo, Japan
ABSTRACT A seasonal variability in the vertical flux of ice algae was examined with a multiple sediment trap during seasonal ice coverage in SaromaKo Lagoon, Hokkaido, Japan. The multiple sediment traps were moored at 4 m below the water surface and 5 m above the bottom to collect suspended materials at 7 dayintervals for 64 days from February 4 to April 8, 1999. Community structure of ice algae and water column phytoplankton collected with the sediment traps was determined in terms of both cell abundance and cell volume. For the ice algal community, Odontella aurita was the most dominant in cell volume, followed by Pleurosigma spp., Achnanthes spp., Detonula confervacea, Bacteriaosira fagilis, Fragilariopsis spp., and Navicula spp. while Fragilariopsis spp. and Achnanthes spp. were dominant numerically. Water column phytoplankton were dominant in descending order of cell volume by Membraneis spp. Thalassiosira spp. Campylodiscus sp., Chaetoceros spp., Amphora spp., and Dictyocha speculum, and Alexandrium sp. Mean cell volume ratio of ice algae to total algae with one standard deviation was 0.30 ± 0.28 and highly variable although a similar ratio based on cell number was 0.72 ± 0.06. The vertical fluxes of chlorophyll a (Chl a) was estimated from the volume ratio, and the mean with one standard deviation was 0.90 ± 0.42 mg Chl a m−2 d−1. This suggests that the ecological role of ice algae in a small embayment should be considered separately from ecosystem in the high latitudes although a total release of ice algal carbon from the sea ice into a water column could be similar to one in the high latitudes and only 3 g C m2 in 65 day ice season. Even during the ice coverage, due to a lateral transport of phytoplankton through two channels from the Sea of Okhotsk, where ice coverage was always incomplete, the community structure of released ice algae under * Corresponding author: [email protected], Tel/Fax: +81-42-691-8002
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Yoko Niimura, Hiroaki Saito, and Satoru Taguchi the sea ice was modified significantly. A combination of laterally transported water column phytoplankton and vertically released ice algae into the underlying water column may play a significant role in the energy transfer to the successful aquaculture of scallops and oysters as well as other benthos in the shallow coastal water ecosystem.
Key words: cell volume ratio, Chl a, diatoms, resuspension, sediment trap, temporal variability
INTRODUCTION Ice Algal Community Dense algal assemblages are formed at the bottom surface of sea ice and they are generally called ―ice algal community‖ (e.g., Horner 1985). Ice algal community occupy a habitat in the brinefilled space between ice crystals, i.e., brine channels or brine pockets. Ice algal community faces highly variable fluctuations in the physical, chemical, and biological environment over different temporal and spatial scales. Ice algal biomass in the brine channels often exceeds biomass found in open water (Legendre et al. 1992). High accumulation of ice algal biomass is controlled by permeability of the ice that is a critical factor for supply of nutrients to the ice algal community (e.g., Cota et al. 1987; Smith et al. 1990). At the same time for the accumulation of algal cells in the sea ice, ice algal community is continuously released into an underlying water column from the sea ice (e.g., Taguchi et al. 1997b). The release is provided by physical factors such as brine expulsion (Weeks and Ackley 1986) and water exchange between brine channels and underlying water (Krembs et al. 2000). The physical factors are likely triggered by temperature change. The released algae could contribute often to algal biomass in underlying water (Reesburg 1984; Garrison et al. 1987; Michel et al. 1993). Sinking ice algal community transports energy without a significant loss during the sinking in a water column to benthic community particularly in high latitudes (e.g., Tremblay et al. 1989). This process is particularly significant for the shallow coastal waters where the influence of seasonal inputs of organic matters to the sediments including aquaculture systems could be highly significant (Gutt et al. 1998). In such regions when sea ice and ice algal community are developed, the sedimentation of ice algal community has received much attention (Carey 1987) in connection with carbon flow in the aquatic ecosystem (Vezina et al. 1997).
Sedimentation of Ice Algal Community Ice algal sedimentation has been recognized as one of the most difficult processes for quantitative estimation but critical information, particularly in coastal sea ice ecosystem. The origin of the difficulty is two-fold: (1) resuspension of bottom sediments and (2) mixture with pelagic phytoplankton. The former can be corrected by a chemical ratio method
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introduced by Gasith (1975), requiring quantitative chemical measurements of ice algal community, organic matters collected in the sediment trap, and bottom sediments. The latter has been merely attempted in the past (Leventer and Dunber 1987) because some ice algal cells are often found in a water column and some phytoplankton are also incorporated into the sea ice and possible differential dissolution of silica frustules occurs during sedimentation. Because a taxonomical identification can be employed to distinguish ice algal species from other epiphytic algae and pelagic phytoplankton in the present study area (e.g., Michell et al. 1997) and any significant dissolution does not occur in a shallow water column due to a shallow water column, it can provide a reasonable estimate for the vertical flux of ice algal community. It can be made as long as a significant relationship between cell volume and Chl a concentration is obtained. Once the relative contribution of ice algal community is estimated, vertical flux of Chl a related to ice algal community can be obtained by assuming that a portion of ice algal Chl a in the total Chl a trapped in the sediment traps is similar to the cell volume ratio of ice algae to total algal cells.
Saroma-Ko Lagoon The complete freezing of the surface area in Saroma-Ko Lagoon commences in late January and ice retreat occurs in early April every year (Taguchi and Takahashi 1993) although the Sea of Okhotsk has never been completely frozen. The winter community of pelagic phytoplankton prevails in the surface mixed layer in the Sea of Okhotsk. Natural assemblages of pelagic phytoplankton are extremely suppressed under the complete coverage by sea ice in Saroma-Ko Lagoon (Michel et a. 1887). Since Saroma-Ko Lagoon is semienclosed water and connected with the Sea of Okhotsk by two channels, the winter community of pelagic phytoplankton in the Sea of Okhotsk can be transferred by tidal current through the channels to a water column in Saroma-Ko Lagoon. The tidal current may invade from the North deep channel and overfill through the South shallow channel during the period of complete coverage by sea ice. This process may modify the community structure of phytoplankton assemblage under the sea ice in Saroma-Ko Lagoon. Runoff from Bekanbetsu River, which is the biggest supply of fresh water and inorganic matters (Nomura et al. 2008), can affect the current system and sedimentation of organic matters under the sea ice in the east basin although the maximum runoff occurs one month after the ice season (Takeuchi 1993). All these characteristics related with not only tidal transport of pelagic winter phytoplankton but also a seasonal sea ice provides a unique situation to study vertical flux of ice algae in a water column. Observation study with sediment traps has been made in the present study area in the past (e.g., Michell et al. 1993, Taguchi et al. 1997b), however the seasonal variability in the vertical flux of ice algal Chl a released from sea ice has remained clarified. Ice algal community includes several taxonomic groups of algae and is employed to estimate quantitatively a vertical flux of Chl a specific to ice algal community.
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Objectives Objectives of this study were (1) to quantify the vertical flux of ice algae based on the community structure of algae, (2) to determine the temporal variability in the vertical flux of Chl a during the period of complete coverage of sea ice, and (3) to estimate the annual vertical fluxes of organic matter related to ice algal community.
MATERIALS AND METHODS In order to assess the vertical flux of ice algae from sea ice during a complete ice coverage season of Saroma-Ko lagoon, a multiple sediment trap was moored at a trap station off the coast of Sakae-ura in Hokkaido (Fig. 1) on January 21 when there was some ice in the lagoon but before complete ice coverage. The trap held 12 cylinders (8.5 cm inside diameter and 25.5 cm deep), with each cylinder being open for seven days before the motor drive closed that cylinder and opened the next cylinder (Taguchi et al. 1997b). Prior to deployment, each cylinder was filled with a 4 % NaCl solution. The trap array was bottom-anchored, with the cylinders 4 m below the water surface and 5 m above the bottom as in the previous study (Taguchi et al. 1997b). The 12 cylinders were sequentially opened for seven days between January 21 and April 15, 1999. A
Latitude (N)
Saroma-ko Lagoon 44
Hokkaido Hokkaido 42
140
142
144
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Saroma-Ko Lagoon
Figure 1. A, Map of Hokkaido, showing the location of Saroma−Ko Lagoon (open circle) and Monbetsu Tide Gage Station (open square); B, Location of the sediment trap station (filled circle) in Saroma-Ko Lagoon and the rader station at Tokoro (filled square).
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The hourly data of air temperature was taken from the Radar AMeDAS at Tokoro (144o06‘E, 44o09‘N, Fig. 1B). The water temperature was continuously observed at the vicinity of sediment trap station as part of the monitoring system of Saromako Aquaculture Research Center. The hourly data of tide height was obtained from Monbetsu port, where is 60 km far from Saroma-Ko Lagoon (Fig 1A). Shortly after the lagoon was ice-free, the sediment trap array was retrieved and taken to the nearby laboratory. The samples from each cylinder of the sediment trap array were kept at 20oC until time of analysis, when each sample was melted in a cold room and split to four sub−samples by a Folsom splitter (Sell and Evans 1982). For the determination of chlorophyll a (Chl a), the first subsamples were filtered onto a Whatman glass fiber filter type GF/F. Chlorophyll a pigments were extracted by N, Ndimethylfolmamid in opaque vials (Suzuki and Ishimaru 1990). The concentration of Chl a was measured on a fluorometer (Turner Designs, Model 10AU) with the method recommended by Holm-Hansen et al. (1965). The second sub−samples for determination of biogenic silica (BSi) were filtered onto a Millipore polycarbonate filter with 0.2 µm of pore size. Concentration of BSI was determined spectrophotometrically by the method of Paasch (1980). All measurements were conducted in duplicate. The last subsamples were fixed with buffered formalin for microscopic analysis of the species composition. Taxonomical identification, enumeration, and size (volume) determination of species were carried out on an inverted light microscopy (Olympus IMT−2). The subsamples were settled for at least 24 h (Hasle 1978) and minimum of 400 cells was processed (Lund et al. 1958). In order to differentiate between ―ice algae‘ and ‗water column phytoplankton‘, on February 15 and 17, 1999, five ice cores were obtained using a CRREL core sampler (Rand and Mellor 1985) in addition to water samples at 1 m water depth (using Niskin bottles) in the vicinity of the sediment trap array. The bottom surface (03 cm) of each core was sectioned and melted in 3 % NaCl solution to avoid any breakage of cells due to osmotic pressure (Sime-Ugando et al 1997). The aliquots were processed for microscopic analysis as mentioned above. Ice algae and water column phytoplankton were identified by the taxonomic descriptions as provided by Hasle (1973; 1990), Hasle and Syversten (1988), Poulin and Cardinal (1982; 1983), Medlin and Priddle (1990), Round et al. (1990), Krammer and Lange-Berta lot (1991), and Tomas (1997). Cell volume of ice algae and phytoplankton cells were estimated by the methods described in Hillebrand et al. (1999). The following premises are made in the present study; (1) the allocation of cells as ‗ice algae‖ or ‗water column phytoplankton‘ as determined from the ice core and water column studies as described above can be used to separate two groups of algae as recovered in the cylinders of the seiment trap array; 2) the ratio of cell volumes to cellular Chl a and to BSi are similar in ‗ice algae‘ as compared to ‗water column phytoplankton‘; 3) daily vertical flux can calculated by dividing the measured amounts in each cylinder by the number of days each cylinder was open. Daily vertical flux during the eleventh trap was corrected to the actual length of ice coverage period because the trap was closed one day earlier than the end of complete ice coverage.
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A Air temperature (oC)
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Date Figure 2. Temporal changes in environmental conditions at Saroma−Ko Lagoon during the period of complete ice coverage (February 4 to April 8, 1999). A. Changes in air temperature, with regression line for the data shown by the solid line; B. Changes in water temperature. Vertical lines indicate the duration of the time period during which each trap-cylinder was open, with the number of the cylinder shown on the upper abscissa.
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RESULTS Environmental Conditions Before and After Trap Deployment Although some sea ice formation was sporadically observed from the end of December 1998, it was not until February 3, 1999, that sea ice completely covered the surface area of Saroma-Ko Lagoon. The air temperature in the period immediately preceeding deployment of the sediment trap array was below −10.0 oC during the period of complete ice coverage the air temperature fluctuated considerably from −15.0 oC to +5.0 oC, with the regression line showing the general increase from −8 oC on February 4 to −1 oC on April 8 (Fig. 2A). With increasing air temperature and a strong spring wind, the sea ice disappeared completely on April 9, 1999 (Kohno, per. comm.). Duration of the complete ice coverage was 65 days. Overlying snow depth was 10 cm on March 11with 40 cm ice thickness and a 2cmincrease of sea ice thickness was observed during the data logger deployment from February 10 to March 11 (Shirasawa, pers. comm.). Air temperature during the complete ice coverage period fluctuated almost weekly, which was frequently observed at the southern location in the sea ice ecosystem of Northern Hemisphere (Fig. 2). Air temperature higher than the mean of −5.0 oC during the ice season was observed during the forth, sixth, eighth, tenth, and eleventh sediment trap openings. The coldest air temperature was observed during the fifth sediment trap opening from February 19 to 25.
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Figure 3. Temporal changes in tide height at Monbetsu port. Hour 817 and 2161 correspond to the first hour (01:00 am) of February 4 (beginning of Trap 3) and to the last hour (24:00pm) of April 8 (closing of Trap 11), 1999, respectively.
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Water temperature changed from the positive to negative value on December 22, 1998 and continued to decrease to −1.8 oC on January 10, 1999. During the first three sediment trap openings from February 4 to 25, the water temperature fluctuated between −1.8 oC and −1.6 o C and thereafter gradually increased to −0.8oC when the last cylinder was closed on April 8 (Fig. 2B). The overlying snow depth on the ice was 10 cm on March 1. On March 11 the ice thickness was 40 cm (Shirasawa, pers. comm.). During the period from February 10 to March 11 the temperature of the ice at 20 cm below the ice surface showed a temporal change from −3.1 to −1.5 oC, which reflected the increase in air and water temperatures during that time period. During the period when the first four cylinders were closed the daily tide change was relatively large (generally > 100 cm) and variable. During the time of the second half of the trap deployment, the change in the daily tide showed less variability and was generally < 80 cm (Fig. 3). However, the difference between two periods was not significant. Table 1. Top seven species of ice algae and water column phytoplankton observed in the sediment traps in term of cell abundance and cell volume. Species Ice algae Fragilariopsis spp. Achnanthes spp. Odontella aurita Detonula confervacea Navicula spp. Bacterosira fragilis Pleurosigma spp. Water column phytoplankton Thalassiosira spp. Chaetoceros spp. Amphora spp. Dictyocha speculumn Membraneis spp. Alexandrium sp. Campylodiscus sp.
Maximum cell abundance (106 cells m−2 d−1)
Maximum cell volume (109 cell volume m−2 d−1)
101 83.0 13.9 8.88 3.54 5.73 0.143
10.6 25.4 116 20.7 9.83 13.3 33.5
47.0 3.41 1.66 1.50 1.15 0.29 0.29
392 19.8 4.81 3.04 969 3.17 389
Dominant Species of Ice Algae and Water Column Phytoplankton Prior to the complete ice coverage, in the first two sediment traps, Thalassiosira spp. were dominated more than 86 % of water column phytoplankton while Odontella aurita and Achnanthus spp. were dominated more than 60 % of ice algae. During the complete ice coverage, diatoms exclusively dominated the top seven species of the ice algal community with a different descending order between cell density and cell volume (Table 1). Fragilariopsis spp. were most abundant in term of cell density while in term of cell volume Odontella aurita was most abundant and followed by Pleurogima spp., Achnanthes spp.,
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Detonula confervacea, Bacterosigma fragilis, Fragilariopsis spp., and Navicula spp. All these diatom species were also found in the bottom 3-cm sea ice core collected on February 15 and 17, 1999. For water column phytoplankton, diatoms, dinoflagellates, and silicoflgellates were dominant groups in the top seven species with a different descending order based on either cell density or cell volume (Table 1). Within a group of diatoms, volumetrically Membraneis spp. and Thalassiosira spp. were dominated consistently throughout the complete ice coverage while Campylodiscus sp. was occurred as the second dominant species only in the tenth sediment trap. For other two groups, Alexandrium sp. was mainly occurred in the last three sediment traps during the complete ice coverage while Dictyocha speculumn were occurred throughout the complete ice coverage. Diatoms and silicoflagellates except for Alexandrium sp. were also observed at < 106 cells m−3 in the water samples collected 1 m below the bottom surface of sea ice on February 15 and 17, 1999.
Temporal Changes in Cell Volume Temporal changes in the total cell volume of ice algae and water column phytoplankton indicated the maximum of 1820 × 109 µm3 m−2 d−1 during the period from March 25 to April 1 (Trap 10) and the minimum of 54 × 109 µm3 m−2 d−1 during the period from March 19 to 25 (Trap 9, Table 2). Total cell volume of ice algae ranged from 148 × 109 µm3 m−2 d−1 during the period from April 1 to 8 (Trap 10) to 22 × 109 µm3 m−2 d−1 during the period from February 19 to 25 (Trap 5, Table 2). Temporal changes in cell volume of ice algae was mainly caused by Odontella aurita which occupied usually more than 50 % of total ice algal cell volume except for Trap 10 (Fig. 4). In Trap 10, Pleurosigma spp. and Achnanthes spp. were more abundant than Odontella aurita. Total cell volume of water column phytoplankton stayed between 250 and 470 × 109 µm3 m−2 d−1 from February 4 to March 11, and thereafter decreased to about 10 × 109µm3 m−2 d−1, and increased to one higher than 700 × 109 µm3 m−2 d−1 (Table 2). Table 2. Cell volume (x 109 µm3 m−2 d−1) and relative abundance (%) of ice algae and water column phytoplankton in Saroma-Ko Lagoon, Hokkaido, Japan. Mean and S.D. indicate annual mean and one standard deviation, respectively. Trap Number Duration
Cell volume Total Ice algae
3 Feb 4 to 11 4 Feb 12 to 18 5 Feb 19 to 25 6 Feb 26 to Mar 4 7 Mar 5 to 11 8 Mar 12 to 18 9 Mar 19 to 25 10 Mar 26 to Apr 1 11 Apr 2 to 8 Mean ± S.D.
470 544 276 527 557 55.5 53.5 1810 791 565 526
122 126 21.6 112 80.1 46.0 38.6 148 100 88.3 44.2
Water column phytoplankton 348 418 254 414 467 9.5 14.7 1660 691 475 494
Relative abundance Ice algae Water column phytoplankton 25.9 74.0 23.2 76.7 7.87 92.1 21.0 78.0 14.6 85.4 82.8 17.2 71.5 28.5 8.19 91.8 12.8 87.2 29.8 70.3 27.7 27.7
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The cell volume of water column phytoplankton ranged from 1660 × 109 µm3 m−2 d−1 during the period from March 25 to April 1 (Trap 10) to 9.5 × 109 µm3 d−1 during the period from March 12 to 18 (Trap 9, Table 2). The most striking feature was characterized by two major groups; Thalassiosira spp. and Membraneis spp. (Fig. 4). The former group always occurred throughout the observation and dominated at 75 % in Traps 8 and 9 whereas the latter group disappeared from Traps 8 and 9. Although the maximum and minimum total cell numbers collected in the sediment traps showed two magnitudes of order difference, relative abundance of ice algae in the total algae was stayed in a relatively narrow range from 62 % during the period from April 2 to 8 to 83 % during the period from March 12 to 18 (Fig. 5).
Relative abundance of cell volume (%)
100
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0 3
4
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6
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8
9
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Trap numbers Odontella Pleurosigma Achnannthes Detonera Melosira Pinnularia Bacterosira Navicula others
Figure 4. Temporal changes in species composition of ice algae based on cell volume during the period of complete ice coverage.
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Relative abundance of cell volume (%)
100
80
60
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0 3
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Trap numbers Membraneis spp. Thalassiosira spp. Campylodiscus sp. Amphora spp. Chaetoceros spp. Alexandrium sp. Dictyocha others
Figure 5. Temporal changes in species composition of water column phytoplankton based on cell volume during the period of complete ice coverage.
Relationship between Cell Volume and Chl A and BSi A significant relationship was obtained between total cell volume of ice algal community (× 1010 µm3 m−2 d−1) and water column phytoplankton assemblages and amounts of Chl a or BSi (mg m−2 d−1) in the sediment traps as Y = 8.6 × 10−11 X + 0.30, r2 = 0.9421, p < 0.01 or Y = 8.4 × 10−9 X + 39, r2 = 0.9654, p < 0.01, respectively (Fig. 6).
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100
Relative abundance (%)
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0 100
Relative abundance (%)
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Trap numbers Figure 6. Relative abundance of ice algal community and water column phytoplankton based on cell density (upper panel) and cell volume (lower panel) during the period of complete ice coverage.
Vertical Flux of Chl a and BSi A vertical flux of ice algal Chl a or BSi, which were calculated by applying a ratio of ice algal cell volume to total algal volume to total amounts of Chl a or BSi in the sediment traps, ranged from the maximum of 1.4 mg Chl a m−2 d−1 during the period from February 4 to 11
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(Trap 3) and 127 mg BSi m−2 d−1 during the period from March 26 to April 1 (Trap 10) to the minimum of 0.18 mg Chl a m−2 d−1 and 17 mg BSi m−2 d−1 during the period from February 19 to 25 (Trap 5), respectively (Fig. 7). A significant relationship was obtained between the vertical flux of Chl a and BSi as Y = 12.2 × X + 80.5, r2 = 0.8249, p < 0.01.
Amounts of Chl a in sediment trap
18 16 14 12 10 8 6 4 2 0
Amounts of BSi in sediment trap
1800 1600 1400 1200 1000 800 600 400 200 0 0
5.0x1010
1011
1.5x1011
2.0x1011
Total cell volume in sediment trap Figure 7. Relationship between cell volume of ice algae and other algae and chlorophyll a (upper panel) and BSi (lower panel).
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1.4
-2
-1
Ice algal Chl a flux (mg Chla m d )
1.6
1.2 1.0 0.8 0.6 0.4 0.2 0.0
120
-2
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Ice algal BSi flux (mg BSi m d )
140
100 80 60 40 20 0 3
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Trap numbers Figure 8. Temporal changes in vertical flux of ice algal chlorophyll a (upper panel) and BSi (lower panel) during the period of complete ice coverage.
DISCUSSION It has been one of the most difficult problems to estimate a vertical flux of organic matter in shallow water because resuspension of the organic matter from the bottom is easily occurred by tidal currents and/or riverine inflow. Although the effect of riverine inflow is at the minimum during the ice season in Saroma-Ko Lagoon (Takeuchi 1993), a contribution of water column phytoplankton to the total cell volume in the sediment traps is highly variable
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due to effect of horizontal transport of water from the Sea of Okhotsk. One of the methods to provide a possible separation of resuspended matter from the newly produced suspended matter is a chemical ratio method introduced by Gasith (1975). The chemical ratio method is only applicable to the present study area if the chemical composition of the material in ice algal layer, sediment trap, and the bottom sediments are significantly different. The eastern basin of SaromaKo Lagoon where the sediment trap array had been deployed was as shallow as 9 m although the western basin was deeper than 20 m. A physical structure of the water column at the present station has been known to have a feature of three layers; the sea ice layer at the top, pycnocline in the first few meters, and high saline deep water (Taguchi et al. 1997a). The sediment trap array was aimed to locate within this high saline water layer in the present study so that they were expected to catch the particles which sediment through the pycnocline. There was also a logistic reason for the deployment depth of sediment trap array at 4 m depth to avoid the damage caused by the ice floe from the Sea of Okhotsk. Because of the shallowness, ice algal cells released into a water column reach rapidly the bottom without any significant changes in the chemical composition as discussed by Michell et al. (1997). Thick layers of ice algal aggregates or mats are usually observed at the bottom by scuba divers under the sea ice (Fujiyoshi, pers. comm.) because ice algal aggregates are formed at a much faster rate than other algae (Riebesell et al. 1991) and a low temperature may slow a rate of degradation. This feature may explain why different chemical composition is unable to obtain among the ice algal layer, the sediment trap, and the bottom sediments. The chemical ratio method may be less applicable to the present unique situation. Identification of ice algae can be employed to follow the sedimentation process in sea ice ecosystems such as the present study area. Since a horizontal transport of water from the Sea of Okhotsk to the water column under the sea ice in Saroma-Ko Lagoon can be occurred by tidal currents, some pelagic water column phytoplankton but less possibility for ice algae from the outside of the present study water can be found in the sediment traps. The sedimentation process of ice algal community under the sea ice in the present study water can be identified by microscopic determination. This can be supported by the following reasons; the ice algae inhabited in the Sea of Okhotsk are most likely sunken out of a water column even they are present in the water column before they are transported to the present water due to a high sinking rate of ice algae (Levanter 2003) and pelagic water column phytoplankton can be distinguished positively from the ice algae inhabited in the sea ice of Saroma-Ko Lagoon. The temporal variability of water column phytoplankton in the sediment traps can be governed by the abundance and the horizontal transportation rate of pelagic winter phytoplankton in the Sea of Okhotsk. The species of ice algae identified in the present study are similar to those observed previously in the similar area (Takahashi 1981). Ice algal cells have been known to remain not suspended in the plankton biomass in the present study area (Michel et al. 1997). Certain ice algal species such as Fragilariopsis species might be able to survive in a water column under the sea ice (Leventer and Dunbar 1987) but the abundance in a water column was low as < 1 × 106 cells m−3 in the present study as observed by Michell et al. (1997). Once they are released into a water column, they reach rapidly the bottom, where they provide a large quantity of high quality food for the cultured scallops and oysters, which have a grazing pressure on ice algal cells (Kurata et al. 1991). Zooplankton community in Saroma-Ko Lagoon mainly consists of microzooplankton, which are too small to feed on ice algal cells
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(Saito and Hattori 1997). The high sinking speed of released ice algal cells without a significant loss due to zooplankton grazing in a water column also support the direct relationship between the ice algal community and benthos. A significant relationship between the total cell volume of both ice algal and water column phytoplankton and the amounts of balk chlorophyll a or BSi in the sediment trap in the present study may suggest that a portion of vertical flux of Chl a related with ice algal community can be estimated from the bulk materials collected in the sediment traps based on the assumption that a portion of ice algal Chl a or BSi in the bulk Chl a or BSi in the sediment traps is similar to the cell volume ratio in the present study area. This assumption is not necessarily relevant for other waters as discussed by Levanter (2003). Both relationships have a positive intercept on Y-axis which indicates possible bias due to the shrinkage of cell volume and degradation of Chl a and dissolution of silicate. The estimation of cell volume based on the preserved samples could be underestimated by 8 % even for diatoms (Montagnes et al. 1994). It took three months to process the sediment materials so that the latter processes would be possibly occurred even though the samples were kept frozen in a dark condition. Any temporal change in the relative abundance of diatoms in the total phytoplankton could be one of error sources for the cell volume ratio method if their contributions are extremely low. Although the average relative cell volume contribution of diatoms in the total algae was about 30 % in the present study area, as long as the relative cell volume contribution of ice algae is considered, the cell volume ratio method may be less biased by the temporal change in the relative abundance of ice algae in the total algae. A temporal change in the relative abundance of cell volume within ice algal cells may influence the sinking speed of ice algal community (Smayda 1970). However their sinking speed is faster than water column phytoplankton cells due to a tendency to form aggregate (Riebesell et al. 1991), the cell volume ratio method should be able to differentiate ice algal Chl a and BSi from the bulk of Chl a and BSi with a reasonable accuracy. A significant relationship between the estimated vertical flux of Chl a and BSi may also support the reasonable estimation in the present study. The high variability in the vertical flux of Chl a and BSi observed in the present study may indicate that growth condition and their trophic interaction within the ice algal community are highly variable during the ice season. Variability in the growth condition and their interaction can be related with air temperature. Higher than 100 × 109 µm3 m−2 d−1 was usually associated with the air temperature higher than −5 oC except for during the period from March 12 to18 (Trap 8). The least loss of algal cells from the sea ice observed during the period from February 9 to 25 (Trap 5) might be caused by the coldest air temperature in the present study. The coldest air provides a solid structure of the bottom portion of brine and the accumulation of Chl a and BSi in the growing cells within the sea ice are occurred with a decreasing available light. The decrease of light is caused by a steady thickening of sea ice and accumulation of snow on the sea ice and this situation enforces ice algal cells shade adapted (Obata and Taguchi 2009). This trend to shade adaptation is likely further enforced by the consistent appearance of large cells such as Odontella aurita because large diatoms in the ice algal community are subjective to a high package of Chl a per cell (Finkel 2001). When both air and water temperature are suddenly increased as observed during the period of last two trap openings, ice algal cells are easily released into a water column (Nomura et al. 2008) so that they cannot take advantage to remain in the brine to grow rigorously. When the frequent increase of water temperature warmer than −1.6oC is occurred, the sea ice starts melting and eventually disappeared.
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When the cell ratio method is applied to the trapped materials, which contain sediment materials associated with not only ice algal community but also non-ice algal community, the vertical flux of ice algal community can be estimated as long as the ice coverage is maintained in the present study area. Although a significant relationship between the vertical flux of ice algal Chl a and BSi estimated in the present study does not necessarily support a validity of cell ratio method, the slope between them is within a range of BSi:Chl a ratios observed for nutrient limited and saturate diatoms (Harrison et al. 1977). Although it is difficult to confirm the validity of our estimates of vertical flux, the comparison with the previous studies may suggest that our estimates are within their range (Sasaki and Fukichi 1993; Michell et al. 1997; Taguchi et al. 1997b). The high variability in the vertical flux of Chl a and BSi as indicated by 44-% of coefficient of variation can be related with air temperature as observed in the variability in the ratios discussed above. The increase in the vertical flux during the period from March 26 to April 8 (Trap 10) seems to be accompanied by the increase of air temperature, which subsequently causes the temperature of sea ice to increase. A laboratory experiment shows that a steady increase of water temperature weakens the bottom structure of sea ice and subsequently high salinity brines are dropped out due to the heavy density (Wakatsuchi and Ono 1983). The peak in the vertical flux was also related with significant increase of air temperature and spring wind at the end of the ice season (Meteorological Agency of Japan, 1999). On the scale of days a frequent release of brine has been also observed to be related with highly variable air and sea ice temperature in the present study area (Nomura et al. 2009). The unstable fluctuation of air temperature is directly related with the southern location of SaromaKo Lagoon in the sea ice ecosystem of Northern Hemisphere (Honda et al. 1994). Ice algal community is one of the most important primary producers in the sea ice ecosystem and a portion of those is continuously released into a water column even during the ice growing period as observed in the present study. The species composition of released ice algal community also varies as ice grows as observed under the high latitude sea ice (Ishikawa et al. 2001). The released ice algal community has also the important role being utilized by benthos because the abundance of phytoplankton is low during the duration of ice coverage. The long−term success in the aquaculture of scallops and oysters in the present study area may not be maintained without the supply of organic matters derived from the ice algal community. The ecological significance of the ice algal community in addition to the primary producer in the sea is the supplier of organic matters to the benthos due to a short distance from the sea ice at the surface water to the bottom in shallow, coastal water such as the present study area. In conclusion, the effects of the re−suspension of organic matters in a water column and the lateral transport of phytoplankton assemblages always occurs even during the complete ice coverage and is highly variable; 70 ± 28 % in the present study. Annual supply of ice algal cells, Chl a, and BSi from sea ice were 3.97 x 109 cells m−2, 58 mg Chl a, and 5.5 g BSi m−2 for 65 days of complete ice coverage duration, respectively. If we assume a plant carbon to chlorophyll a ratio of 54 (Taguchi et al. 2004), total amounts of plant carbon released from the sea ice could be about 3.2 g C m−2 per ice season. If about 3-% of organic carbon in total mass flux is assumed in the present study area (unpublished data), the present estimate is similar to those observed in high latitudes as summarized by Levanter (2003). The quality of organic matters related directly with the ice algal community might be highly variable due to the growth condition and trophic interaction which depend on temperature. When a temporal
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variation of the energy flow is considered in a shallow, coastal water of sea ice ecosystem, the re-suspension and lateral transport of phytoplankton should be considered in relation to air temperature and tide.
ACKNOWLEDGMENTS We thank H. Hattori and his colleague who helped the deployment of the multiple sediment traps in the field. This work would not have been completed without logistic support from Y. Fujiyoshi and N. Kohno. We deeply appreciate K Shirasawa and N. Kohno for providing data. All facilities for sample analysis were provided by Soka University. This work was partly supported by the Institute of Low Temperature Science in Hokkaido University. Critical comment provided by O. Holm-Hansen was extremely constructive and helpful. All assistance provided by the Scripps Institution of Oceanography, University of California, San Diego was greatly appreciated.
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Nagao N, Toda T, Takahashi K, Hamsaki K, Kikuchi T, Taguchi S (2001) High ash content in net−plankton samples from shallow coastal water: Possible source of errors in dry weight measurement of zooplankton biomass. J Oceangr 57: 105−107. Nomura D, Takatsuka T, Ishikawa M, Kawamura T, Shirasawa K, Yoshikawa−Inoue M (2009) Tranpsot of chemical components in sea ice and under−ice water during melting in the seasonally ice−covered Saroma−ko Lagoon, Hokkaido, Japan. Est Coast Shlf Sci 81: 201−209. Obata M, Taguchi S (2009) Photoadaptation of an ice algal community in thin sea ice, Saroma−Ko Lagoon, Hokkaido, Japan. Polar Biol (in press) Paasche E. (1980) Silicon content of five marine plankton diatom species measured with a rapid filter method. Limnol Oceanogr 25: 474480. Poulin M, Cardianal A (1982) Sea ice diatoms from Manitounuk Sound, southeastern Hudson Bay (Quebec, Canada). II. Naviculaceae, genera Navicula. Can J Bot 60: 28252845. Poulin M, Cardinal A (1983) Sea ice diatoms from Manitounuk Sound, southeastern Hudson Bay (Quebec, Canada). III. Cymbellaceae, Entomoneidacea, Gomphonemataceae, and Nitzschaceae. Ca J Bot 61: 107118. Rand J, Mellor M (1985) Icecore augers for shallow depth sampling. CRREL Rept 85: 122. Reesburgh W (1984) Fluxes associated with brine motion in growing sea ice. Pol Biol 3: 2933. Riebesell U, Schloss I, Smetakek V (1991) Aggregation of algae released from melting sea ice: implications for seeding and sedimentation. Pol Biol 11: 239−248. Round, FE, Crawford RM, Mann DG (1990) The diatoms, biology and morphology of the genera. Cambridge Univ, Cambridge, 747p. Sasaki H, Fukuchi F (1993) Production and sedimentation processes in the ice−covered Lake Sarima. Bull Plankt Soc Jap 39: 170−171. Sell DW, Evans MS (1982) A statistical analysis of sub−sampling and evaluation of the Folson plankton splitter. Hydobiol 94: 136141. Sime-Ugando T, Juniper KS, Demers S (1997) Icebrine and plank tonic microheterotrophs from SaromaKo Lagoon, Hokkaido (Japan): Quantitative importance and trophdynamics. J Mar Sys 11: 149161. Smayda TJ (1970) The suspension and sniking of phytoplankton in the sea. Ocenogr Mar Biol Ann Rev 39: 353−414. Smith REH, Harrison WG, Harris LR, Herman A (1990) Vertical fine structure of particulate matter and nutrients in sea ice of the High Arctic. Can J Fish Aquar Sci 47: 13481355. Suzuki R, Ishimaru T (1990) An improved method for the determination of phytoplankton chlorophyll using N, Ndimethylfolmamid. J Oceanogr Soc Jap 46: 190194. Taguchi S, Takahashi M (1993) Summary of the Plankton Colloquim Ecosystem of Lake Saroma under ice covered condition in winter. Bull Plankt Soc Jap 39: 152154. Taguchi S, Smith REH, Shrasawa K (1997a) Effect of silicate enrichment on ice algae at low salinity in Saroma−Ko Laggon, Hokkaido, Japan. J Mar Syst 11: 45−52. Taguchi S, Saito H, Hattori H, Shirasawa K (1997b) Vertical flux of ice algae during the ice melting and breaking periods in SaromaKo Lagoon, Hokkaido, Japan. Proc NIPR Symp Polar Biol 10: 5665. Tomas CR (1997) Identifying marine phytoplankton. Acd Press, San Diego, 858p.
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Takahashi E (1981) Floristic study of ice algae from the sea ice of a lagoon, Lake Saroma, Hokkaido. Mem Natl Inst Polar Res Ser E 34: 49−56. Tremblay C, Rounge JA, Legendre L (1989) Grazing and sedimentation of ice algae during and immediately after a bloom at the ice water in Resolute Passage (Canadian High Arctic). J Mar Sys 11: 173189. Vezina AF, Demers S, Laurion I, Sime-Ugndo T, Juniper SK, Devine L (1997) Carbon flows trough the microbial food web of first ice in Resolute Passage (Canadian High Arctic). J Mar Sys 11: 173189. Wakatsuchi M, Ono N (1983) Measurement of salinity and volume of brine excluded from growing sea ice. J Geophys Res 88: 29432851. Weeks WF, Ackley SF (1986) The growth, structure and properties of sea ice. In: Untersteiner N (ed) The Geophysics of Sea Ice, Plenum Press, New York, NATO ASI Ser B:Physics 146: 9−164.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 457-473 © 2011 Nova Science Publishers, Inc.
Chapter 17
THE EVALUATION OF SOME LIMNOLOGICAL FEATURES OF THE LAGOON LAKES IN EUROPEAN PART OF TURKEY Belgin Çamur-Elipek and Timur Kırgız Trakya University, Faculty of Science, Department of Biology, Edirne, Turkey
ABSTRACT Lagoons have perfect hydrodynamic perspective and very sensitive structures. First of all, the human activities on lagoons have become a major environmental concern. Any artificial influence to these sensitive areas may cause the destruction of the natural balance of them. Turkish coasts have more than 70 lagoon lakes which are formed on about 60 000 ha. area. European part of Turkey which is also named as ―Turkish Thrace‖ is surrounded by three different seas: The Marmara Sea, The Black Sea, and The Aegean Sea. The region has a lot of lagoon lakes (such as Lakes Mert and Erikli are located on the coasts of The Black Sea in Kırklareli province; Lakes Terkos, Küçükçekmece, and Büyükçekmece are located on the coasts of The Marmara Sea in İstanbul province; and Lakes Gala, Dalyan, Taşaltı, Işık, Vakıf, and Tuzla are located on the coasts of The Aegean Sea in Edirne province) which are formed at different types. Therefore, Turkish Thrace may be considered as a rich area in terms of lagoon lakes. Furthermore, some lakes are important parts of some National Parks in Turkey. In this chapter, some limnological features of some lagoon lakes located in European part of Turkey were evaluated. With this aim, both the results of the previous limnological studies performed by different researchers (by the authors and/or the others) since 1987 in some lagoons in the region and the results of the present data on the lakes which were visited on different dates by the authors at the years 2008 and 2009 for sampling were evaluated. According to the all data (both from the previous studies and from the present study) some physicochemical features, salinity levels, some biological data of the lagoons were gathered in this chapter. Furthermore, rather roughly trophy levels of the lagoons were determined by the available features which are used to determine the trophy level of the lakes. In conclusion, this study aimed to gather all data
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Belgin Çamur-Elipek and Timur Kırgız on the lagoons in European part of Turkey by making a comparison of their former and present status. Consequently, the results from the previous limnological studies performed in some lagoons in the region (a review); the results from the present data on some features of some lagoons (a research); limnological evaluation on all of the lagoons in the region (an evaluation) were provided in the present chapter. Thus, it was provided the whole limnological documents which have been gathered from the lakes at separate times since 1987.
1. INTRODUCTION Although they have different forming types, lagoons are generally known as aquatic ecosystems which are located on coastal areas of marine environments. There are a lot of factors determining the formation type of a lagoon: the connection type between the mouth of river and marine environment, amounts and types of the sediment which are carried by flow of river or tide zone of marine environments. A lagoon may be formed at mouth of a river (alluvial deposit from river may accumulate at the mouth of the river and settled to water or alluvial deposit from marine environments may accumulate and settled to the mouth of river), at delta of a river basin (wetland area may be formed as a lagoon), or at small bay in marine (alluvial deposit from marine environment may close the bay as a lagoon). Salinity of a lagoon is determined by both water amount from the river and changes of water from sea. The salinity of the lagoons ranges from nearly fresh to hyperhaline waters. Therefore lagoons have saline, brackish, or fresh water and their salinities may change seasonally. Lagoons and its surrounding areas are used both to provide the agricultural products, fisheries and other aquatic activities and also to serve to the tourism sector. Lagoons are very sensitive areas and they are affected by surrounding environments. The physical, chemical, and biological components of the lagoons differ from one other. Therefore, it is very important to keep their sustainable use management. With this aim, we have to learn their hydrobiological structures. Their biological productivities and carrying capacities may change and thus they do not sustain their specific functions. A lot of activities belonging to agricultural, industrial, urban, and tourism surrounding of lagoons may cause deterioration on natural balance of these sensitive areas. These environmental deteriorations can be observed as some changes in their physicochemical features. Lagoons are the most productive areas in the ecosphere. Their productivity amounts are the highest because of nutrients carried by rivers, and fish production is very high in these habitats [1]. Nutrient loadings coming from both intent and extent surrounds, they have a major impact on water quality and ecology. The high nutrient concentrations in the water can be pointed out that the lagoon has eutrophic character [2]. A lagoon can be considered as oligotrophic when it has low levels of nutrient concentrations in the water [2]. Mesotrophic lagoons have medium level of nutrient concentrations in the water [2]. Hydrodynamic parameters can change at each lagoon lake. But it should be monitored its hydrodynamic parameters to know the situation of yesterday, today, and future‘s of the lake. Each lake has its own features. It changes as time passes and therefore it should be monitored periodically.
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Flows, salinity, nutrients, temperature, and other physicochemical features of lagoon, and discharges, salinity, and water temperature from the rivers and artificial outlets to a lagoon must be monitored periodically. Some parameters such as water salinity, temperature, light permeability, conductivity may be necessary for some modelling aspects in the lagoon. Furthermore, the other some parameters such as dissolved oxygen, hydrogen sulphide, pH, nutrients, etc. are necessary to identify the trophy level of a lagoon. Biological parameters such as chlorophyll-a, phytoplankton, zooplankton, macrophytes, macrozoobenthos, and Ichthyofauna are also necessary to monitory the trophy level of a lagoon.
2. LAGOON LAKES IN TURKISH THRACE Turkish Thrace (23764 km2) is located in the north-west of Turkey that is geographically part of Europe. This part of Turkey is occupying the south-eastern tip of the Balkan Peninsula. It is surrounded by three different seas: Black Sea in the northeast and by the Sea of Marmara and the Aegean Sea in the south. It includes several lakes that have traditionally sustained Turkish coasts have more than 70 lagoon lakes which are formed different forming types. European part of Turkey which is named as Turkish Thrace has more than 10 lagoons or lagoon type forming lakes. In this chapter it is given the brief summaries on some hydrobiological features of the Turkish Thrace lagoons from the studies which have been performed since 1983 are given. Thus, it is presented a comparative analysis of the lagoon lakes in Turkish Thrace for the future studies.
2.1. General Knowledge on the Lagoons of Turkish Thrace (Location, Origin and Hidrography) A total of 11 lagoon lakes in the European part of Turkey are presented in this chapter (Figure 1). Some of them have freshwater while they had salty water before. The others have water range salty to freshwater characters. Furthermore, some field experiments were carried out in some lagoons in the years 2008 and 2009. Conductivity, pH, and temperature profiles were obtained at several locations in the lagoons. Depth of each studied lake was also measured and the light permeability of the lakes was recorded. The water samples which were sampled from the lagoons were availed by using Ruttner Water Sampler and carried to the laboratory to determine salinity, total hardness, Mg+2, Ca+2 profiles, some nutrients (NO2-N, NO3-N, SO4-2, PO4-3), dissolved oxygen, solid suspended material were measured by classical titrimetric and spectrophotometric methods [3].
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Figure 1. The locations of the lagoon lakes in Turkish Thrace (1:Erikli, 2:Mert, 3:Terkos, 4:Küçükçekmece, 5:Büyükçekmece, 6:Tuzla, 7:Vakıf, 8:Işık, 9:Dalyan, 10:Taşaltı, 11:Gala)
2.1.1. Lake Erikli This lagoon lake is located between 41˚52'55"N, 27˚59'11"E (Demirköy/Kırklareli) by length is about 1-1.5 km (Figure 2). It has 43 ha. (0.43 km2) area and most of this area (36.5 ha) is covered by Phragmites austrialis [4]. Its maximum depth is 1.5-1.8 meters [4, 5]. This lagoon lake is formed by alluvial deposit from Efendi stream. The Black Sea is located on east of the lake. The forest area behind the lake remains under water level when the water level rises after excessive flows from the rivers. This area is named as ―Erikli Longos area‖.
Figure 2. Erikli lagoon lake
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Table 1. Some physicochemical characters in Erikli Lake (İğneada/Kırklareli) (from Güher [4]) Parameters\Months May. Jun. Jul. Aug. Sep. Water temp.(0C) 19.7 17.7 20.9 13.8 17.46 DO. (mg·L-1) 5.56 8.53 6.56 9.00 8.26 pH 8.19 7.89 8.09 9.33 9.49 Depth (cm) 111.6 113.3 94.33 76.66 60.00 Turbidity(cm) 45.0 43.3 61.0 43.3 48.3 226 300 523 1307 1045 EC (mho·cm-1) Mg (mg·L-1) 26.3 31.0 - 91.9 148.6 Ca (mg·L-1) 66.1 47.4 - 67.6 74.8 T.H. (FS)0 33.8 36.6 - 71.8 98.8 Cl- (mg·L-1) 392 444 - 1771 3001 NO3-N (mg·L-1) - 0.017 0.077 NO2-N (mg·L-1) - 0.012 0.001 Phosphate (mg·L-1) rare 0.2
Oct. 19.0 7.75 9.06 73.3 56.6 1512 206.5 136.2 153.4 3083 0.056 0.001 0.19
Nov. Dec. Jan. Feb. Mar. Apr. 3.6 6.6 5.0 6.3 13.3 22.3 13.34 9.21 9.60 8.54 9.96 7.54 7.80 9.38 7.67 6.66 8.11 7.82 125.0 103.3 111.6 130.0 115.0 123.3 65.0 36.6 81.6 76.6 95.0 115.0 925 485 113 195 476 83 301.1 25.3 39.6 77.2 26.2 35.2 32.0 51.2 68.0 40.2 142.0 26.5 42.0 65.9 31.1 5034 2722 730 1612 383 0.05 0.05 - 0.0002 0.0001 0.37 0.001 0.003 - 0.0006 0.0008 0.015 0.19 0.19 - 0.004 0.007 absent
(DO: Dissolved oxygen; EC: conductivity; T.H.: Total hardness)
2.1.1.1. Some Limnological Characters Of Lake Erikli This lake was studied by Kırgız & Güher [6] and Güher [4] in previous studies to obtain the some physicochemical features. According to the obtained results by Güher [4], dissolved oxygen ranged between 5.56-13.34 mg/L, pH ranged between 6.6-9.4, turbidity (light permeability) ranged between 43-115 cm, conductivity ranged between 83-1512 mho/cm, magnesium ranged between 26-301 mg/L, calcium ranged between 32-136 mg/L, total hardness ranged between 31-153 FS0, chloride ranged between 383-5034 mg/L, nitrate ranged between 0.00018-0.37 mg/L, nitrite ranged between 0.0006-0.015 mg/L, phosphate ranged between 0.00-0.2 mg/L. The results were showed that in Table 1. Also, in the study by Güher [4], it was reported that 268105 zooplanktonik organisms in per m3 at average in the lake. In the study which is performed by Kırgız & Güher [6] in the lake, it was reported that 600 macrozoobenthic individuals in per m2 at average belonging to a total of 11 different taxa [6]. In the studies which were performed in the years 2008 and 2009 in Erikli Lake, it was found that the temperature 25 0C, pH 7.6, biological oxygen demand (BOD) 7.36 mg/L, dissolved oxygen 4 mg/L, light permeability 34 cm, conductivity 1300 S/cm, NO3-N 0.76 mg/L, salinity 7.709 ‰, HCO3 6.5 mg/L, H2S 0.213 mg/L, solid suspended material 0.92 mg/L at average. It was also measured the amounts of NO2-N, carbonate, PO4-2 in the lake during the sampling, but it was not found in any amount. 2.1.2. Lake Mert (Lake Koca) This lagoon lake is located between 41˚52'09"N, 27˚57'57"E (Demirköy/Kırklareli) by length is about 2 km (Figure 3). It has an area of 222 ha. area and a most of part of this area (178 ha.) is covered by Phragmites austrialis [4]. Its maximum depth is 1.5 meters [4]. This lagoon lake is formed by alluvial deposit from Deringeçit stream [4]. It is separated from the Black Sea by a little sand area. It is sometimes related with the Sea when the water level rises. Thus, this area is named as ―Mert (Koca) Longos area‖ when the water level rise and the woodland area remains under the water. Mert and Erikli longos area have been declared as ―National Park of Iğneada Longos Forests‖ since 2007. The Longos forests (flooded forests) cover a large area at Erikli and Mert lakes surroundings.
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Figure 3. Mert Lagoon Lake
2.1.2.1. Some Limnological Characters Of Lake Mert This lake was studied by Kırgız & Güher [6] and Güher [4] in pervious studies to obtain the some physicochemical features. According to the obtained results by Güher [4], dissolved oxygen ranged between 6.9-13 mg/L, pH ranged between 7.1-9.2, turbidity (light permeability) ranged between 40-110 cm, conductivity ranged between 296-2550 mho/cm, magnesium ranged between 71-903 mg/L, calcium ranged between 53-212 mg/L, total hardness ranged between 56-290 FS0, chloride ranged between 1285-41178 mg/L, nitrate ranged between 0.0002-0.55 mg/L, nitrite ranged between 0.0001-0.03 mg/L, phosphate ranged between 0.00-0.2 mg/L. The results have been showed that in Table 2. Also, in the study by Güher [4], it was reported that 271919 zooplanktonik organisms in per m3 at average in Mert lagoon. In the study which was performed by Kırgız & Güher [6], it was reported that 1624 macrozoobenthic individuals in per m2 at average in the lake. These individuals belong to a total of 10 different taxa [6]. Table 2. Some physicochemical characters in Mert Lake (İğneada/Kırklareli) (from Güher [4]) Parameters \ Months May. Jun. Water temp.(0C) 17.8 19.9 DO. (mg·L-1) 6.9 12.5 pH 8.1 8.7 Depth (cm) 125 113 Turbidity(cm) 60 48 296 900 EC (mho·cm-1) Mg+2 (mg·L-1) 71.8 903.5 Ca (mg·L-1) 53.2 136.4 T.H. (FS)0 56 196.4 Cl- (mg·L-1) 1285 5443 NO3-N (mg·L-1) NO2-N (mg·L-1) Phosphate (mg·L-1) -
Jul. 20.1 9.1 9.2 98 75 1023 -
Aug. Sep. Oct. Nov. Dec. Jan. 15.3 12.7 17.6 4 11.6 10 9.1 9.0 7.1 13.0 9.9 8.7 8.63 8.9 8.34 7.95 7.9 7.8 71 56 73 116 71 86 63 56 66 40 43 75 3525 1985 2550 1125 2235 1350 505.4 493.6 424.2 374 307.7 181.0 186.6 212.4 47.6 121.4 285.3 282.9 290.6 178.3 187.7 8927 10114 10346 6580 41178 0.064 0.073 0.056 0.050 0.050 0.01 0.001 0.001 0.001 0.003 rare 0.20 0.19 0.18 0.19 -
(DO: Dissolved oxygen; EC: conductivity; T.H.: Total hardness)
Feb. Mar. Apr. 6.3 13.6 18.3 9.5 9.5 8.1 7.17 8.01 7.89 108 115 100 79 110 100 925 678 586 132.8 274.0 135.4 70.9 116.2 81.3 90.3 171.2 96.6 2769 5536 3193 0.0002 0.0004 0.55 0.0001 0.0009 0.034 0.07 0.005 absent
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Figure 4. Terkos Lagoon Lake
In the studies which were performed in the years 2008 and 2009 in Mert Lake, it was found that the temperature is 26 0C, pH 8.6, biological oxygen demand (BOD) 7.06 mg/L, dissolved oxygen 3 mg/L, light permeability 103 cm, conductivity 2050 S/cm, salinity 9.55 ‰, HCO3 5 mg/L, H2S 0.426 mg/L, solid suspended material 1.42 mg/L at average. It was also measured the amount of NO3-N, NO2-N, carbonate, PO4-2 in the lake during the sampling, but it was not found.
2.1.3. Lake Terkos (Lake Durusu) This lagoon forming lake has a surface area of 25-32 km2 (Figure 4). It has a maximum depth of 11 meters [7]. Its maximum length is 14 km., and width is 6 km. It is located near the Black Sea coast of Turkey between 40˚19' N, 28˚32' E (Çatalca/İstanbul), and it is one of the six main drinking water reservoirs of the Istanbul metropolitan area, providing 25% of the water demand. The lake is fed by Istranca River so its waters are fresh and its salinity is low, with an average 0.02‰ [7]. Freshwater fish species predominate [8]. The largest river in the drainage area is Istranca River. This lagoon is formed at the end of Quaternary. Firstly, a bay has been formed in the Sea. And then, this bay has been separated from the Sea by alluvial deposit from Istranca River. This lagoon is surrounded by settlements, agricultural areas and by small forests. 2.1.3.1. Some Limnological Characters Of Lake Terkos This lake was studied by Çamur-Elipek [7] in pervious study to obtain the physicochemical features. According to her obtained results, dissolved oxygen ranged between 8.94-11 mg/L, pH ranged between 7.6-8.5, turbidity (light permeability) ranged between 65-204 cm, conductivity ranged between 188-309 mho/cm, magnesium ranged between 3.8-13.7 mg/L, calcium ranged between 41.5-58.1mg/L, total hardness ranged between 12-20 FS0, chloride ranged between 27.5-38.7 mg/L, nitrate ranged between 0.000.61 mg/L. The results were showed that in Table 3. Also, in the study by Çamur-Elipek [7], it was reported that 1278 benthic organisms in per m2 at average. These individuals are belong to a total of 41 different taxa [7]. 2.1.4. Lake Küçükçekmece This lagoon lake is situated at twenty-four kilometers (24 km) southwest away from the center of Istanbul and adjacent to the Marmara Sea (41º00' N-28º43' E) (Figure 5). It has a surface area of 15.22 km2 [9]. The lake is 10 km in length and 6 km in its widest part. The
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average depth of the lake is approximately 10 meters and the deepest part is 20 meters near the southern edge of the lake [10]. A narrow channel connects it to the Marmara Sea in the southeast and the lake is connected to the Marmara Sea via this channel, but besides sea water, the main water supply comes from fresh underground springs and several small streams [11]. Three stream systems feed the lake: Nakkaşdere, Sazlıdere and Ispartakule [12]. The Sazlıdere stream output into the lake is much less due to the damming of this stream in 1995, which formed Sazlıdere Lake [13]. The lack of fresh water which was comes from the Sazlıdere stream does not affect Küçükçekmece‘s water level due to its connection with the Marmara Sea [13]. Since the discharge of Nakkaşdere stream was stopped and diverted offshore to the Marmara Sea by a new pipeline system in 2005, the lake has been fed by the Ispartakule stream from the northwest, surface runoff from the surrounding areas and by the sea water from the south [13]. Formerly the water of the lake was saline then it turned to fresh water by the river discharges [9]. Although, it is separated from the sea by a set, the lake has brackish water [10].
Figure 5. Küçükçekmece Lagoon Lake
Table 3. Some physicochemical characters in Lake Terkos (Çatalca/İstanbul) (from Çamur-Elipek [7]) Parameters\Months Water temp.(0C) DO. (mg·L-1) pH Depth (cm) Turbidity(cm) EC (mho·cm-1) Mg (mg·L-1) Ca (mg·L-1) T.H. (FS)0 Cl- (mg·L-1) NO3-N (mg·L-1)
Apr. 15.1 10.2 8.04 899 165 244 4.30 42.7 12.4 27.5 0.12
May. 20.3 11.0 8.12 871 156 238 4.11 43.3 12.5 31.9 0.00
Jun. 22.6 10.2 8.09 839 118 283 3.86 44.4 12.7 30.3 0.00
Jul. 25.5 8.94 7.98 814 139 300 4.74 42.7 12.6 30.9 0.61
Aug. 25.3 9.36 8.27 749 113 309 7.06 42.4 13.5 37.5 0.00
(DO: Dissolved oxygen; EC: conductivity; T.H.: Total hardness)
Sep. 18.1 10.0 8.32 672 65 229 9.75 41.6 14.4 38.7 0.00
Oct. 12.3 10.7 8.14 834 204 188 6.96 41.5 13.2 36.5 0.04
Nov. 13.1 10.5 8.55 565 141 239 12.9 45.3 16.6 38.0 0.03
Dec. 8.52 11.0 8.39 584 178 260 13.0 58.1 19.9 35.8 0.00
Jan. 8.02 11.0 8.42 612 120 257 13.7 57.8 20.1 37.5 0.00
Feb. 7.3 11.1 7.75 724 136 217 9.87 52.4 17.1 32.4 0.00
Mar. 13.9 9.59 7.64 745 155 243 9.29 56.7 18 35.9 0.13
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Table 4. Some physicochemical characters in Lake Küçükçekmece (İstanbul) (from Topçuoğlu et al. [11] and Demirci et al. [13]) Parameters / Literatures Salinity (‰) Temperature(°C) Dissolved oxygen (mg/L) pH Secchi depth (m) Nitrate (mg/L) Nitrite(mg/L) Ammonium (mg/L) Phosphate (mg/L) Conductivity (mS) COD (mg/L)
Topçuoğlu et al. (1999) 5.96 (April) -10.20 (October) 6.6 - 25.8 6.30 (in July)-10.80 (in April) 7.00 - 8.36 0.3 - 4.0 0.2 - 1.9 0.002 - 0.136 0.10 - 1.30 0.73 - 6.60 -
Demirci et al. (2006). 5.5 - 21 8.7 0.9 – 9.8 11.4 4.4 - 732
2.1.4.1. Some Limnological Characters Of Lake Küçükçekmece This lake was studied by Topçuoğlu et al. [11] and Demirci et al. [13] in pervious studies to obtain the physicochemical features. According to Topçuoğlu et al [11] dissolved oxygen ranged between 6.3-10.8 mg/L, pH ranged between 7-8.3, turbidity (light permeability) ranged between 30-400 cm, nitrate ranged between 0.2-1.9 mg/L, nitrite ranged between 0.002-0.136 mg/L, phosphate ranged between 0.7-6.6 mg/L, ammonium ranged between 0.11.3 mg/L. Some results were showed that in Table 4. According to Demirci et al [13], the average pH value is 8.7 for the lake (this value is approximately the same as open sea pH, which indicates the intrusion of saline sea water from the southern part into the lake converts it to brackish one), the average high conductivity values (11.4 mS) (is further evidence of the intrusion of sea water), dissolved oxygen (DO) values are between 5.5 and 21 mg/L, phosphate concentrations range between 0.1-9.8 mg/L (are far exceeding and unpolluted surface water), chemical Oxygen Demand (COD) values in the lake show a large value spread (between 4.4 and 732 mg/l), the total coliform values are at average of 563 per 100 ml (too high for either drinking water or recreational waters), turbidity is widespread across the lower levels in the southwest portion and higher near some of the streams (Table 4). 2.1.5. Lake Büyükçekmece This lagoon lake which is located at north of the Marmara Sea coast (41˚04' N, 28˚34' E) of Turkey (Çatalca/İstanbul) is the third largest water resource among the six main reservoirs of a metrapolitan Istanbul, providing 17% water demand [14] (Figure 6). It is 30-35 kilometers to the southwest of Istanbul city center. The lake is formed at the point, where the river Karasudere flows into the Marmara Sea blocked by the sandbank it created. The lake has an area of 28.47 km2, it is 7 km long and 2 km wide, and the deepest section is about 8.6 meters. The lake is fed by Karasu stream. After Büyükçekmece Lake is separated from Marmara Sea by a dam and serve as a reservoir to the city.
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Figure 6. Büyükçekmece Lagoon Lake
Table 5. Some physicochemical characters in Lake Büyükçekmece (Istanbul) (from Koşal-Şahin [15]) Parameters\Months
DO. (mg·L-1) pH Turbidity(cm) EC (mho·cm-1) T.H. (FS)0 Salinity (‰) NO2-N (mg·L-1) NO3-N (mg·L-1) PO4-3(mg·L-1)
Jun. Jul. Aug. Sep. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May. 9.0 10.2 8.9 9.0 10.0 12.0 11.7 10.8 8.8 9.8 7.8 7.4 7.4 7.8 7.6 8.3 7.7 8.2 6.4 7.4 7.4 7.3 7.0 6.8 132 160 102 80 110 90 120 130 90 70 60 62 446 481 533 503 527 514 472 509 430 467 547 547 12 12 12 12 12 12 13 18 14 13 13 12 0.02 0.02 0.03 0.02 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 1.44 1.54 1.84 0.56 0 0 0 25.34 16.84 26.6 12.54 36.34 0.28 0.88 0.52 1.38 0 0.92 0 0 0.40 0 0 0 20.9 21.0 21.5 17.4 0.18 0 1.9 14.0 18.5 7.4 0.2 82.3
(DO: Dissolved oxygen; EC: conductivity; T.H.: Total hardness)
2.1.5.1. Some Limnological Characters Of Lake Büyükçekmece This lake was studied by Koşal-Şahin [15] in pervious study to obtain the physicochemical features. According to her obtained results, dissolved oxygen ranged between 7.4-11.7mg/L, pH ranged between 6.4-8.3, turbidity (light permeability) ranged between 60-132cm, conductivity ranged between 430-547 mho/cm, total hardness ranged between 12-18 FS0, nitrate ranged between 0.0-1.3 mg/L, nitrite ranged between 0.00-36.3 mg/L, phosphate ranged between 0.00-82.3 mg/L, salinity is 0.03‰ at average. The results were showed that in Table 5. 2.1.6. Tuzla (Erikli Salt) Lagoon This lagoon is situated at 40˚37' N, 26˚28' E (Erikli, Enez/Edirne) (Figure 7). It has an area of 2.2 km2, and 2.1 km length, 1.4 km width. Its maximum depth is about 500 cm. It is correlated with the Aegean Sea by a narrow channel. Therefore it has very saline water.
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Figure 7. Tuzla Lagoon Lake (Erikli Salt Lagoon)
2.1.6.1. Some Limnological Characters Of Tuzla Lagoon Up to now, there has been no study on physicochemical features of Erikli Tuzla lagoon. In this chapter, the first records are provided. It was observed in the studies which were performed in the years 2008 and 2009 in Tuzla lagoon, it the temperature is 18 0C, pH 7.9, dissolved oxygen (DO) 2.1 mg/L, light permeability 30 cm, conductivity 280 mho/cm, NO3N 11.3 mg/L, salinity 12‰, solid suspended material 2.5 mg/L, calcium 330 mg/L, total hardness 295 FS0, PO4-3 0.002 mg/L, sulphate 6.10 mg/L at average. It was also measured the amounts of NO2-N, and Magnesium in the lake during the sampling, but it was not found. 2.1.7. Vakıf Salt Lagoon This lagoon is situated at 40˚36' N, 26˚15' E (Vakıf, Enez/Edirne) (Figure 8). It has an area of 1.5 km2, and length of 2.2 km, width of 1 km. Its maximum depth is 100 cm. It is fed weakly by Balik stream. But, it has salty water.
Figure 8. Vakıf Salt Lagoon Lake
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2.1.7.1. Some Limnological Characters Of Vakıf Salt Lagoon Up to now, there has been no study on physicochemical features of Vakıf Tuzla lagoon. In this chapter, the first records are provided. It was observed in the studies which were performed in the years 2008 and 2009 in Tuzla lagoon, it the temperature 17 0C, pH 7.8, dissolved oxygen (DO) 2.2 mg/L, light permeability 30 cm, conductivity 270 mho/cm, NO3N 12.39 mg/L, salinity 11‰, solid suspended material 2.93 mg/L, calcium 344 mg/L, total hardness 290 FS0, PO4 0.003 mg/L, sulphate 6.52 mg/L at average. It was also measured the amount of NO2-N, and Magnesium in the lake during the sampling, but it was not found. 2.1.8. Işık (Bücürmene) Lagoon This lagoon is situated at 40˚42' N, 26˚03' E (Enez/Edirne) at the South of Dalyan Lagoon and it has 76 ha. area (about 1 km2) (Figure 9). Its length is 1 km., and width is 1 km. Maximum depth is 2 meters. It is a coastal lagoon. It has haline water. There is marches on its north and east portion. 2.1.8.1. Some Limnological Characters Of Işık Lagoon Up to now, there has been no study on physicochemical features of Işık lagoon. In this chapter, this is the first record that is provided. Some physicochemical features of the lagoon were showed at Table 6. 2.1.9. Dalyan lagoon This lagoon is situated at 40˚42' N, 26˚04' E (Enez/Edirne) (Figure 9). It is formed by aluvyonal flows from Meriç River. It has an area of 3.7 km2, 5 km. length, and 1.7 km. width with maximum 2 meters depth. It is a coastal lagoon and has hyperhaline water. The lake is surrounded by sandy area. It has no macrovegetation on its banks except north-west portion. 2.1.9.1. Some Limnological Characters Of Dalyan Lagoon Up to now, there has been no study on physicochemical features of Dalyan lagoon. In this chapter, the first records are provided. Some physicochemical features of the lagoon were showed at Table 6. 2.1.10. Taşaltı lagoon This lagoon is situated at 40˚42' N, 26˚05' E (Enez/Edirne) in the South of Dalyan Lagoon and it has an area of 70 ha. (about 1 km2) (Figure 9). Its length is 1.2 km., and width is 0.6 km. Maximum depth is 80 cm. It is a coastal lagoon. It has water with medium salty. It is surrounded by marches. Table 6. Some observed features of the Işık, Dalyan, and Taşaltı Lagoons at the years 2008 and 2009 Temp. pH 0 C Dalyan 14 8.3 Işık 13 8.4 Taşaltı 11 7.9
D.O. Ca Mg Sal. T.H. Turb PO4-3 NO2-N NO3-N SO4-2 SSM mg·L- mg·L- mg·L- ‰ (FS)0 cm mg·L- mg·L- mg·L- mg·L- mg·L150 3.4 320 0 7 228 10 0 0.0002 21.58 5.94 1.67 240 5.1 272 0 10 230 70 0 0 3.76 5.69 2.27 230 2.8 496 0 10 284 10 0.05 0.22 4.54 3.52 2.24
EC.
(EC: conductivity; DO: Dissolved oxygen; Sal.: Salinity; T.H.: Total hardness; SSM: Solid suspended material)
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Figure 9. Işık, Dalyan, and Taşaltı Lagoons
2.1.5.1. Some Limnological Characters Of Taşaltı Lagoon Up to now, there has been no study on physicochemical features of Taşaltı lagoon. In this chapter, this is the first record that is provided. Some physicochemical features of the lagoon were showed at Table 6. 2.1.11. Lake Gala Lake Gala is 5.6 km2 area, its depth changes between 0.4-2.2 meters and sea level is 2 meters (Figure 10). It is formed as alluvial setted lagoon lake by the Meriç River. Therefore, this lake has different forming type from the other lagoons which are located on the coasts of Aegean Sea. During summer, the lake is separeted into two sections because of drying. The bank of the Lake is accompained by macrovegetation consisting of Phragmites australis and Typha sp. There are a lot of agricultural areas (essential rice plant) around the lake [16].
Figure 10. Location of Lake Gala
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Belgin Çamur-Elipek and Timur Kırgız Table 7. Some physicochemical characters in Lake Gala (Edirne) (from Çamur-Elipek et al. [17]) pH EC. Temp Ch-a DO Depth Turb. Mg Ca TH NO3N NO2N SO3-3 PO4-2
Mar. 8.2 145 14.8 21.9 16.3 199 48 67.8 96.1 52 7.20 0.001 3.80 0.01
Apr. 8.4 143 17.8 15.8 14.4 111 48 41.4 86.0 40 4.04 0.00 3.00 0.01
May 8.7 187 19.3 20.0 17.8 126 56 52.7 81.6 42 1.80 0.00 2.80 0.01
Jun. 8.2 163 26.7 17.8 12.8 164 47 69.9 52.9 42 4.40 0.00 3.20 0.06
Jul. 8.3 270 27.6 16.2 12.9 128 76 78.8 57.7 47 1.19 0.00 3.60 0.03
Aug 8.2 250 25.6 4.8 11.4 131 91 78.0 54.3 46 1.88 0.00 2.50 0.03
Sep. 8.3 310 23.6 26.5 14.9 145 28 98.6 52.1 54 3.32 0.24 3.73 0.03
Oct. 8.4 320 19 20.2 16.3 109 51 88.4 105.8 63 0.00 0.02 4.43 0.06
Nov 8.6 209 8.3 58.3 12.8 121 29 85.7 78.1 55 0.01 0.01 2.53 0.00
Dec 8.5 250 9.1 65.5 8.6 106 24 87.8 69.7 49 0.00 0.00 0.06 0.01
Jan. 8.4 150 6.2 18.9 12.3 156 38 80.5 67.5 50 0.00 0.00 2.58 0.02
(EC: conductivity; DO: Dissolved oxygen; Turb.: turbidity; T.H.: Total hardness)
2.1.11.1. Some Limnological Characters Of Lake Gala This lake was studied by Çamur-Elipek et al. [17] in pervious study to obtain the physicochemical features. According to their obtained results, dissolved oxygen ranged between 8.6-17.8 mg/L, pH ranged between 8.2-8.7, turbidity (light permeability) ranged between 24-91cm, conductivity ranged between 143-320 mho/cm, magnesium ranged between 41.4-98.6 mg/L, calcium ranged between 52.1-96.1 mg/L, total hardness ranged between 40-63 FS0, nitrate ranged between 0.00-7.2 mg/L, nitrite ranged between 0.00-0.24 mg/L, sulphate ranged between 0.06-4.43 mg/L, phosphate ranged between 0.00-0.06 mg/L, Chlorophyll-a ranged between 4.8-65.5 mg/L. The salinity is 0.02 %0 at average in this lake. Some results have been showed that in Table 7. Furthermore, it was reported that zoobenthic organisms were found 1627 individuals in per m2 at average by Çamur-Elipek et al. [17].
2.3. Evaluation As a result of some studies which were performed in the lakes in the previous studies, some of them have showed haline and some of them have showed freshwater characteristics. It is observed that Erikli and Mert Lagoons which are located on Black Sea coasts have coastal lagoon features. Their salinity ranged between brackish to salty water (7.709‰ in Erikli Lagoon, and 9.55‰ in Mert Lagoon). Their vegetation type, shallow, and some physicochemical features showed that these lagoons have eutrophic-mesotrophic characters. Kırgız & Güher [6] also supports our findings. The Lake Terkos has freshwater because of the Istranca River flows. Its salinity is very low, with an average of 0.02‰ [7]. Freshwater fish species predominate [8]. Although, the lake was reported to have oligotrophic characters, in the latest study the lake has been indicated as mesotrophic character [7].
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Küçükçekmece lagoon has ranged brackish to salty waters between 5.96‰ and 10.20‰ salinity. The lagoon has shown some sign of eutrophication, such as cyanobacterial blooms and deterioration in water quality from late spring to mid-autumn [18]. At present, the lagoon is used only for fishing and for recreational purposes [9]. Some fishing is possible, but unfortunately it has been facing a dangerous pollution in the last 20 years because of the dense human habitat and uncontrolled industrial development [13]. The low Dissolved oxygen (DO) values would indicate areas where some fish species may be under stress. The DO supersaturated surface water (unpolluted water DO is about 8.6 mg/L) is a clear indication of level approaching eutrophication [13]. The Phosphates and Nitrates levels reported are excessive and it assists algal growth in freshwater lakes [13]. Thus, the lake‘s water does not even approach safe drinking water standards and can be regarded as a heavily polluted lake in terms of many parameters like total coliform, turbidity, temperature, phosphate, DO and COD significant amount of toxic chemicals in the stream [13]. Büyükçekmece is fed by Karasu Stream. Therefore, it has ranged freshwater to weak salty water between 0.02‰ and 0.03‰ salinity [15]. The lake has showed eutrophicmesotrophic characters with the high dissolved oxygen, high nutrient levels, and low light permeability. There is some fishing but lately the lake has been endangered by the pollution caused by human settlement and industrial zones. Tuzla and Vakıf Salt lagoons have showed haline character with 12‰ and 11‰ salinities, respectively. The Lagoons Işık, Dalyan, and Taşaltı have also saline water with 10‰, 7‰, and 10‰ salinity, respectively. Lake Gala has freshwater. The forming type of this lake is different from the others which are located on the Aegean Sea coasts in Turkish Thrace. It is estimated that this may explane the differences for some features of the lake from the others. It was also reported eutrophic characters with measured features [17]. Consequently, it was observed that almost all lagoons in Turkish Thrace are under treatments of settlements, industrialization, agricultural and other human activities. Therefore, overloaded nutrient flowing from these areas may affect these sensitive areas negatively.
3. CONCLUSION Lagoons are very sensitive structures and they are affected by surrounding environments. Any artificial influence to these sensitive areas and the activities belonging agricultural, industrial, urban, and tourism surrounding of lagoons may cause to the destruction of the natural balance of them. First of all, the human activities on lagoons have become a major environmental concern. To avoid the deformation of the lagoons, we have to learn their past‘s, today‘s and future‘s balance.
ACKNOWLEDGMENTS We would like to thank B.Öterler, M.Taş, P.Özkahya, and P.Altınoluk (Trakya University) for their help during some field studies.
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REFERENCES [1] Kocataş, A. (1994). Ekoloji ve Çevre Biyolojisi. Ege Ünversitesi Fen Fakültesi Ders Kitapları Serisi No: 142. İkinci baskı, İzmir. [2] Gamito, S., Gilabert, J., iego, C. M. & Perez-Ruzafa, A. (2005). Effects of changing environmental conditions on lagoon ecology. In: Coastal Lagoons, eds: I. E. Gönenç, & J. P. Wolflin, CRC Press, Boca Raton, London, New York, Washington, D.C. [3] Egemen, Ö. & Sunlu, Ö. (1999). Su Kalitesi (Ders Kitabı), Ege Üniversitesi Su Ürünleri Fakültesi, Yayın no 14, III. Baskı, 153 Sayfa, İzmir. [4] Güher, H. (1996). Mert, Erikli, Hamam ve Pedina (İğneada/Kırklareli) Zooplanktonik Organizmaları (Roıifera, Cladocera, Copepoda) ve Mevsimsel Dağılımları. T. Ü. Fen Bil. Enst. Doktora Tezi. [5] Seçmen, Ö. & Leblebici, E. (1997). Türkiye Sulak Alan Bitkileri ve Bitki Örtüsü. Ege Üniversitesi Fen Fakültesi Yayınları No:158, 870s. Bornova/İzmir. [6] Kırgız, T. & Güher, H. (1994). A study on Benthic macroinvertebrates of Mert and Erikli Lakes (Kırklareli/İğneada). XII. National Biology Congress, 6-8 July 1994, Edirne / Turkiye. [7] Çamur-Elipek, (2003). The Dynamics of Benthic Macroinvertebrates in a Mesotrophic Lake: Terkos, Turkey‖, Acta Biologica Iugoslavica - Serija D: Ekologija, 38(1-2), 3140 . [8] Yüce, R. & Kocakaplan, N. (1999). Terkos (Durusu) Gölü Balıkları ve Balıkçılığı, Maramara Üniversitesi Araştırma Fonu Projesi (1998/17). 1-28. [9] Polge, N., Sukatar, A., Soylu, E., N. & Gönülol, A. (2010). Epipelic Algal Flora in the Küçükçekmece Lagoon. Turkish Journal of Fisheries and Aquatic Sciences, 10, 39-45. [10] Tuncer, M. (1999). Doğal çevre koruma öncelikli bir eylem alanı İstanbul Küçükçekmece Gölü, Gebze İleri teknoloji Enstitüsü, Türkiye’deki çevre kirlenmesi öncelikleri sempozyumu, 18-19 Kasım. [11] Topcuoğlu, S., Güngör, N. & Kirbaşoğlu, Ç. (1999). 'Physical and chemical parameters of brackish water lagoon, Küçükçekmece Lake, in northwestern Turkey', Toxicological & Environmental Chemistry, 69, 1, 101-108. [12] Demirci, A. (2001). Types and distribution of landslides in the Eastern Part of Büyükçekmece Lake by Using GIS, unpublished graduate thesis, Fatih University, İstanbul, Turkey. [13] Demirci, A., Mcadams M., A., Alagha, O. & Karakuyu, M. (2006). The Relatıonshıp Between Land Use Change And Water Qualıty In Küçükçekmece Lake Watershed, 4th GIS days in Turkiye, September 13-16, 2006, Fatih University, İstanbul/Turkiye. [14] Guyer, G. T. & İlhan, E. G. (2010). Assessment of pollution profile in Buyukcekmece Watershed, Turkey. Environmental Monitoring and Assessment. [15] Koşal-Şahin, S. (2005). Büyükçekmece Gölü (İstanbul) Bentik Makroomurgasızlarının Nitel ve Nicel Dağılımları, İstanbul Üniversitesi Fen Bilimleri Enstitüsü, Doktora Tezi, 64. [16] DSİ, (1986). Gala Gölü Limnolojik Araştırma Raporu, T.C. Enerji ve Tabii Kaynaklar Bakanlığı, Ankara, 126. [17] Çamur-Elipek, B., Arslan, N., Kırgız, T., Öterler, B., Güher, H. & Özkan, N. (2010). Analysis of Benthic Macroinvertebrates in Relation to Environmental Variables of Lake
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Gala, a National Park of Turkey. Turkish Journal of Fisheries and Aquatic Sciences, 10 (2), 235-243. [18] Albay, M., Matthiensen, A. & Codd, G., A. (2005). Occurrence of toxic blue-green algae in the Kucukcekmece lagoon Environ. Toxicol., 20, 277-284. Istanbul, Turkey.
INDEX 2 20th century, 263, 334 21st century, 367, 432
A abatement, 291, 293, 294, 297, 343 abundance data, 232 access, 198, 230, 304, 305, 367, 405, 425, 428, 430, 431 accounting, 173, 419, 421 accumulation areas, 100, 105, 106, 190, 192, 198, 206, 207, 208, 306, 308, 309, 317, 320 acetic acid, 284, 288, 289, 294, 374 acid, vii, xii, xiii, 2, 3, 11, 33, 229, 256, 275, 279, 280, 281, 284, 285, 288, 289, 290, 294, 297, 348, 374 acidic, 281, 291, 297 acidity, 258, 343 ACTH, 14, 15, 27 ADA, 191 adaptation, 28, 109, 111, 366, 423, 431, 433, 450 adaptations, 25 additives, xii, 279, 280 adjustment, 210, 325 adrenocorticotropic hormone, 14 adults, 335, 383, 404, 410, 425 adverse effects, xi, 140, 219 Africa, xi, 43, 46, 47, 64, 146, 176, 180, 219, 226, 242, 245, 261, 262, 263, 271, 272, 276, 359, 360, 369 age, 4, 18, 22, 24, 25, 35, 125, 376, 395, 396, 410, 421, 429 agencies, 365, 410, 427 aggregation, 17, 110, 162, 187, 195, 237 agriculture, 58, 157, 255, 256, 260, 263, 340, 343, 344, 352, 362, 363, 418
air temperature, 128, 227, 439, 440, 441, 450, 451, 452, 453 algae, viii, x, xvi, 73, 76, 77, 79, 80, 84, 85, 86, 91, 97, 98, 104, 105, 106, 107, 108, 110, 111, 129, 134, 135, 136, 143, 144, 160, 185, 201, 206, 215, 237, 262, 263, 304, 305, 311, 319, 330, 334, 337, 341, 342, 344, 345, 348, 404, 435, 436, 437, 438, 439, 442, 443, 444, 447, 449, 450, 454, 455, 473 Algeria, 180, 359, 363, 369 algorithm, 88, 98, 110, 198, 200, 201, 205, 310 ALS, xv, 397, 398, 399, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412 Alvarado Lagoon System (ALS XE "ALS" ), xv, 397, 398 ambient air, 128 ambient air temperature, 128 amine, 19 amines, 19 amino, 8, 11, 282 amino acid, 8, 11 amino acids, 8, 11 amino groups, 8 ammonia, 129, 131, 134, 143 ammonium, 258, 263, 267, 358, 452, 465 amplitude, 49, 113, 123, 342 anoxia, 41, 143, 258, 275, 357 antibody, 10 antigen, 10, 16, 17 antioxidant, 30 apoptosis, 13 aquaculture, xi, xiv, xvii, 57, 58, 223, 249, 250, 260, 261, 262, 269, 276, 333, 338, 340, 341, 349, 431, 436, 451 aquarium, 410 aquatic environment, vii, 1, 2, 3, 13, 15, 20, 21, 24, 33, 37, 41, 115, 267 aquatic habitats, 156, 266 aquatic life, 400
476
Index
aquatic systems, x, xiii, 90, 103, 114, 116, 144, 185, 198, 201, 215, 221, 237, 301, 304, 314, 330, 336, 352, 356 Argentina, 245, 395 aromatic compounds, 32, 282, 283 aromatic hydrocarbons, 7, 23, 67, 281 aromatic rings, 284, 292, 294 aromatics, 291 Asia, 71, 176, 177, 242, 260, 384, 432 Asian countries, 418 aspartate, 8, 34 assessment, viii, xvi, 2, 4, 18, 20, 24, 26, 28, 30, 36, 37, 39, 65, 67, 116, 120, 136, 144, 146, 147, 156, 157, 169, 170, 173, 175, 182, 220, 223, 224, 228, 247, 251, 255, 256, 261, 265, 267, 269, 271, 274, 275, 276, 330, 398, 410, 417, 425, 428 assessment techniques, 175 assessment tools, 157 assets, xvi, 176, 417, 420, 422, 425, 430 assimilation, 275, 331, 360 atmosphere, 40, 134, 201, 250 atmospheric deposition, 201, 262, 343 atmospheric pressure, 405 atoms, 200, 291, 314 authorities, xiv, 285, 351, 352, 353, 363, 364, 365, 409, 410, 412 awareness, xvi, 362, 408, 410, 417, 426, 428, 430
B background information, 370 bacteria, 77, 131, 133, 134, 201, 258, 273, 338, 340, 343, 344, 346 bacterial infection, 21 bacterium, 338 Baltic states, 324 banking, 428 banks, 48, 49, 51, 55, 144, 254, 287, 362, 373, 411, 412, 428, 468 barriers, 15, 16, 255, 335, 367 base, vii, xii, xiv, 2, 3, 11, 30, 33, 65, 112, 173, 190, 191, 192, 193, 194, 199, 200, 204, 206, 207, 254, 266, 280, 281, 305, 306, 307, 308, 309, 310, 314, 318, 321, 352, 360, 365, 366, 370, 371, 383, 432 benefits, xi, 186, 187, 214, 219, 220, 223, 253, 360, 363, 366, 418, 421 benthic invertebrates, 179, 239 benzene, 282, 283 bias, 42, 450 bile, 3, 5, 6, 32 bile duct, 5 bioaccumulation, 3, 37, 403, 413 bioassay, 31 bioavailability, 2, 291
biodegradation, 298 biodiversity, xii, xiv, xv, 42, 114, 115, 144, 154, 157, 160, 166, 169, 175, 177, 178, 182, 220, 221, 249, 250, 258, 260, 265, 274, 333, 334, 345, 365, 368, 370, 397, 404, 412, 421 biogeography, 67, 413 bioindicators, ix, 31, 46, 64, 107, 153, 154, 155, 176, 179, 187, 189, 214, 304, 305, 316 biological activity, 128, 400 biological control, 217, 331 biological processes, 123, 130, 272 biomarkers, 3, 5, 13, 14, 17, 20, 24, 25, 26, 29, 30, 31, 33, 34, 36, 37 biomasses, viii, 73, 76, 82, 83, 85, 93, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 252, 258, 327, 357, 367 biomonitoring, 18, 33 bioremediation, 69 biosphere, 252 Biosphere Reserves, 370 biotic, viii, x, xiv, 2, 18, 40, 41, 58, 77, 100, 115, 141, 154, 160, 170, 178, 180, 181, 215, 240, 352, 361, 364, 365 biotic factor, 178, 240 birds, ix, xvi, 97, 153, 154, 155, 156, 157, 160, 161, 162, 166, 167, 169, 170, 171, 172, 173, 178, 179, 180, 181, 182, 183, 222, 239, 240, 265, 358, 359, 360, 362, 368, 398, 409 blood, vii, 2, 3, 4, 9, 10, 11, 12, 14, 16, 18, 22, 31, 35 blood circulation, 9, 14 blood flow, 4 blood monocytes, 16 blood supply, 10 blood vessels, 4, 9, 10 Boat, 426 body size, 246 body weight, 4, 10, 21, 23 bones, 409, 411 boreal forest, 415 Brazil, 33, 34, 43, 47, 49, 51, 64, 65, 67, 70, 151, 178, 242, 274, 276, 368, 370 breakdown, 3, 6, 173, 357 breeding, 4, 18, 144, 173, 181, 239, 338, 341, 358, 361, 405, 411, 423 brevis, 402 Britain, 35, 175, 243 Brittany, 66 buffalo, 361, 362 bulk materials, 450 butyl ether, 282 buyers, 429 by-products, 291, 297, 298
Index
C Ca2+, 12, 13 Cabinet, 268 cadmium, 8, 13, 14, 19, 27, 28, 30, 33, 34, 36, 37, 130, 141, 294 calcium, 12, 32, 111, 115, 461, 462, 463, 467, 468, 470 calibration, xii, 113, 198, 205, 250, 251, 376, 395 Cameroon, 243 campaigns, 158, 256, 408, 410, 412 canals, 258 candidates, viii, 39 capsule, 4, 9 carbohydrate, 24 carbohydrate metabolism, 24 carbon, xv, xvii, 13, 28, 42, 51, 130, 131, 132, 133, 134, 136, 137, 143, 148, 229, 246, 253, 262, 280, 282, 283, 286, 287, 290, 294, 346, 397, 400, 401, 403, 411, 435, 436, 451, 453 carbon dioxide, 280 carbon tetrachloride, 13, 28, 42, 282, 283 carcinogen, 36 Caribbean, 262, 269, 412, 413, 414 case studies, 285 case study, xvi, 64, 66, 68, 102, 146, 149, 157, 277, 330, 417, 419, 420, 430, 433 catabolism, 8, 18 catastrophes, 392 catchment, ix, 120, 122, 123, 124, 125, 126, 129, 130, 131, 140, 141, 146, 148, 149, 150, 177, 190, 198, 227, 276, 305, 308, 358, 363 catchments, ix, xi, 119, 120, 125, 126, 130, 140, 141, 143, 144, 147, 149, 222, 227, 249, 261, 268, 271, 304, 415, 421 catecholamines, 11 catfish, 6, 19, 23, 27, 28, 33, 34, 403 cation, 373 cattle, xvi, 361, 362, 364, 398, 403, 406, 410 causal relationship, 4 CCA, 170 cell biology, 26 cell death, 5, 13 cell division, 19 cell membranes, 13 cellulose, 58, 216 Census, 158, 167, 176, 177 Central Europe, 36 CGL, 174 CH3COOH, 288, 289 Chaetoceros, xvii, 435, 442 chain transfer, 14 challenges, 432
477
changing environment, 56, 472 chemical characteristics, 41, 243, 254 Chemical oxidation, xii, 279, 280, 294, 297 chemical properties, xii, 252, 280, 285, 296 chemicals, 4, 8, 12, 13, 15, 18, 19, 23, 41, 267, 289, 471 Chicago, 245 children, 367, 410, 420, 425, 426, 429 Chile, 392 Chilika Lagoon, xvi, 417, 418, 420, 421, 423, 424, 425, 426, 428, 429, 430 chlorination, 291, 299 chlorine, 22, 291 chlorobenzene, 282, 283 chloroform, 13, 282, 283 chromatograms, 291 chromatography, 299 chromium, 13, 37, 283 CIA, 267 circulation, vii, viii, 9, 14, 39, 40, 43, 46, 49, 51, 55, 56, 68, 147, 162, 392 cirrhosis, 5 cities, 57, 334 City, xiii, 52, 67, 263, 280, 287 clarity, x, 85, 97, 98, 107, 110, 113, 185, 187, 237, 303, 311, 319 classes, 24, 162, 250, 287, 321, 341, 404, 418 classification, xii, 69, 146, 147, 162, 245, 250, 251, 265, 266, 286, 291, 297, 331, 341, 404 clay minerals, 384, 391 cleaning, 60 cleanup, 280 climate, viii, 41, 73, 74, 182, 223, 253, 263, 264, 271, 273, 329, 330, 344, 348, 349, 354, 365, 387, 396, 419, 423, 424, 425, 426, 427, 429, 430, 431, 433 climate change, viii, 73, 74, 273, 329, 330, 349, 365, 396, 419, 429, 431, 433 climates, 395 climatic conditions, 41, 237 closure, 128, 129, 136, 137, 138, 423 clustering, 376 CO2, 257, 346 coal, 287 coastal ecosystems, xi, 74, 108, 160, 217, 249, 260, 262, 266, 267, 331, 334, 335 coastal management, viii, 73, 146, 186, 187, 216 coastal region, 41, 109 coastal zone management, 348, 349 CoastWeb, viii, 73, 74, 76, 77, 78, 82, 84, 85, 87, 88, 90, 93, 96, 99, 100, 102, 109, 110, 111 coefficient of variation, 202, 314, 451 collaboration, 361, 364, 410, 427
478
Index
Colombia, 63, 263 colonization, 69, 224, 225, 240, 241, 243, 247 combined effect, 55, 142, 166, 349 commercial, xiv, 138, 141, 142, 245, 265, 280, 285, 288, 289, 333, 341, 404 communication, 171, 253, 376 compaction, 224 comparative analysis, 145, 166, 459 compatibility, 275 compensatory effect, viii, 73, 100 competition, 136, 145, 340, 404, 425 competitors, 183 compilation, 79, 90, 173, 193, 198, 207, 317, 319, 321, 323 complement, 227, 361, 366, 421 complex interactions, 250 complexity, 9, 15, 41, 46, 62, 74, 116, 201, 250, 349, 365 composition, ix, xi, xii, 26, 33, 60, 120, 122, 127, 128, 136, 137, 138, 141, 142, 143, 144, 147, 149, 155, 157, 159, 161, 174, 200, 217, 219, 222, 224, 240, 244, 254, 270, 274, 275, 280, 286, 314, 331, 359, 372, 383, 395, 439, 444, 445, 449, 451, 452 compounds, vii, xii, 1, 2, 3, 5, 6, 7, 15, 32, 33, 41, 58, 237, 261, 263, 279, 280, 282, 283, 291, 294, 298, 346, 348 comprehension, 61 conceptualization, 420 concordance, 156, 170, 180 conductivity, 158, 229, 459, 461, 462, 463, 464, 465, 466, 467, 468, 470 conference, 269 configuration, xii, 280, 289 confinement, 47, 49, 53, 54, 55, 56, 57, 58, 65, 66, 69, 157, 162, 178, 348 conflict, 176, 362, 363, 426 connective tissue, 4, 9 consciousness, 265 consensus, 27, 131, 426, 429 construction, xiv, 223, 226, 227, 228, 230, 351, 353, 359, 363 consumers, 170, 264, 356 consumption, 78, 79, 80, 82, 91, 93, 94, 95, 107, 113, 186, 199, 261, 282, 284, 290, 341, 345, 356, 370, 403, 404, 406, 411 consumption rates, 107 contact time, 291 contaminant, 2, 3, 13, 15, 18, 20, 21, 24, 26, 102, 142, 294, 297 contaminants, viii, 3, 4, 18, 20, 21, 23, 24, 25, 28, 29, 30, 33, 34, 41, 73, 102, 130, 141, 142, 145, 167, 186, 216, 279, 282, 330, 335, 338 contaminated sites, 19, 21
contaminated soil, 284, 300 contaminated soils, 284 contaminated water, 14, 34 contamination, ix, xii, 2, 3, 6, 7, 9, 17, 19, 21, 23, 35, 53, 66, 73, 74, 75, 99, 104, 105, 116, 141, 142, 146, 147, 275, 280, 296, 343, 409 Continental, 69, 245, 273, 350 control group, 19 control measures, 258 controversial, 20 copper, 8, 13, 14, 19, 26, 32, 33, 34, 130, 141 coral reefs, 262, 270 correlation, xv, 52, 59, 168, 189, 321, 385, 397, 400, 403, 411 correlations, 35, 237, 406, 411 corticosteroids, 27 corticotropin, 14, 29 cortisol, 14, 15, 31, 32 cost, 25, 173, 214, 329, 366 covering, 83, 109, 159, 167, 201, 390 crabs, 120, 376, 382 creosote, 37 crises, 41, 251, 265, 271, 347, 394, 396 Croatia, 43, 71 crop, 217, 331 cross-validation, 376 crude oil, 18, 19, 20 crystals, 436 cultivation, xvi, 398, 406 cultural heritage, 253 cultural tradition, 406 cultural values, xvi, 365, 417 culture, 33, 260, 272, 409, 411, 432 cumulative percentage, 232 cycles, 23, 41, 43, 46, 49, 56, 125, 251, 263, 264, 276, 331, 338, 348 cycling, 7, 132, 133, 143, 147, 148, 149, 215, 253, 270, 344, 345, 347, 356 cyclones, 372, 423, 430 cysteine, 8, 13 cytochrome, 6, 7, 30, 31, 32, 36, 37
D damages, iv, 253, 281, 424, 429 data mining, 329 data set, 229 database, 41, 302 decomposition, 128, 130, 143, 199, 257, 281, 356, 357, 368, 370 decoupling, 241 deduction, 428 defecation, 45 defence, 15, 16, 17, 21, 24, 36
Index deficiency, 58, 109 deficit, 51 deforestation, 130, 141, 143, 151, 399, 403, 404, 406, 423 deformation, 471 degenerate, 18 degradation, viii, 16, 20, 40, 140, 142, 169, 173, 224, 260, 280, 281, 283, 284, 297, 338, 342, 344, 345, 348, 369, 405, 411, 449, 450 degradation process, 169, 345 Delta, 61, 149, 176, 178, 180, 182, 261, 274 demography, 167 denitrification, 131, 134, 144, 201, 358 denitrifying, 134, 148 Denmark, 36, 77, 111, 244, 276, 324, 330, 337 deposition, 12, 19, 116, 130, 149, 201, 221, 224, 230, 262, 283, 343, 359, 372, 387, 389, 391 deposits, 71, 221, 222, 245, 361, 383, 387, 388, 389, 392, 393, 394, 395, 396 depression, 37, 54, 221 desiccation, 260 desorption, xii, 134, 280, 281 destruction, xvi, xvii, 10, 17, 18, 41, 362, 398, 405, 409, 411, 457, 471 detectable, 18 detection, 35, 57, 62, 142, 166, 247, 277 detoxification, vii, 1, 3, 4, 8, 17, 23, 25, 31 developed countries, 174 developing countries, 223, 418, 431 development policy, 432 deviation, xvii, 101, 103, 104, 106, 172, 192, 195, 196, 197, 199, 202, 208, 232, 291, 315, 316, 321, 325, 326, 401, 435, 443 diatom assemblages, 271 diatoms, 136, 256, 267, 341, 382, 436, 442, 450, 451, 452, 453, 454 dichloroethane, 283 diet, 6, 19, 65, 113, 168, 341, 404, 407, 409 differential equations, viii, 73, 74 diffraction, 373 diffusion, viii, x, xiii, 73, 112, 113, 185, 186, 187, 192, 193, 194, 198, 208, 237, 268, 301, 304, 308, 309, 315, 318, 328, 346 digestion, 3, 18, 65, 95, 289, 290 dignity, 424, 428 dioxin, 19, 30, 37 directives, xii, 249, 251, 266 disaster, xvi, 417, 426, 430 discharges, 11, 51, 58, 123, 131, 141, 166, 178, 187, 194, 196, 201, 211, 246, 254, 272, 302, 305, 308, 309, 327, 459, 464 discriminant analysis, 376 discrimination, 18, 25, 229, 376, 425, 426, 429
479
diseases, 18, 21, 28, 261, 265, 425 dispersion, 45, 65, 171, 172 disposition, 383, 384, 387 dissociation, 348 dissolved oxygen, 59, 128, 136, 137, 226, 228, 267, 273, 346, 358, 459, 461, 462, 463, 465, 466, 467, 468, 470, 471 diversification, 58, 61 diversity, vii, ix, xv, 2, 12, 27, 30, 45, 46, 54, 58, 59, 60, 61, 120, 122, 141, 156, 161, 162, 163, 164, 166, 169, 170, 171, 172, 240, 255, 349, 358, 361, 365, 398, 418 DNA, 28 dominance, 43, 46, 48, 52, 59, 96, 97, 146, 162, 240, 251, 256, 383 Doñana National Park, vi, xiv, 371, 372, 373, 385, 387, 388, 389, 390, 394 dosage, 282, 294 drainage, 126, 141, 157, 227, 255, 256, 275, 357, 363, 364, 398, 463 drinking water, 360, 463, 465, 471 drought, 41, 360, 398 drying, 42, 354, 364, 469 dumping, 41, 223, 225, 245, 363 durability, 228 dwarfism, 58
E early warning, viii, 2, 3, 24, 25, 58, 65, 173 ecological indicators, 62, 176, 182, 341 ecological requirements, 42 ecological restoration, 244, 300 ecological roles, 224 ecological systems, 156, 271 ecology, x, 62, 67, 69, 78, 82, 109, 114, 115, 116, 117, 143, 144, 149, 154, 170, 171, 173, 178, 220, 228, 241, 256, 270, 271, 272, 331, 340, 366, 370, 394, 405, 419, 458, 472 economic damage, 253 economic damages, 253 economic development, vii, xiv, 1, 2, 174, 252, 261, 352, 432 economic progress, 431 economic status, xvi, 418 economic systems, 420 economic values, 222, 253, 265, 276 economics, xii, 279 ecosystems, vii, viii, ix, xi, xiii, 1, 2, 20, 39, 40, 57, 58, 74, 108, 117, 119, 120, 140, 143, 156, 160, 169, 173, 174, 182, 220, 249, 250, 251, 252, 253, 256, 257, 260, 262, 264, 265, 266, 267, 269, 331, 333, 334, 335, 338, 348, 403, 411, 419, 421, 449, 458
480
Index
editors, 29, 215, 246, 247, 413, 414 education, 144, 408, 409, 410, 421, 425, 426 educational experience, 425 EEA, 337 effluent, 19, 20, 21, 22, 26, 31, 223, 269 effluents, 22, 26, 36, 51, 58, 59, 262, 264, 268 Egypt, 43, 62, 68, 69, 261, 274, 394 elaboration, 427 electrolyte, vii, 2, 3, 11, 27 electron, xii, 14, 26, 32, 34, 36, 134, 279, 280, 281, 282, 283, 299, 346 e-mail, 351 emigration, 85, 86, 87, 88, 89, 90, 91, 92, 93, 95, 102 emission, 187, 210, 324 employment, 362, 418 employment opportunities, 418 endangered species, 223, 361, 410 endocrine, 4, 11, 14, 35, 37 endocrine system, 35 endothelial cells, 7 energy, xv, xvii, 6, 23, 24, 41, 53, 54, 96, 123, 126, 165, 222, 244, 356, 372, 383, 384, 387, 389, 390, 391, 394, 397, 398, 436, 452 energy input, xv, 397, 398 energy transfer, xvii, 436 enforcement, 365, 409, 411 engineering, 227, 258, 300 England, 62, 70, 150 enlargement, 5, 6, 23 environmental awareness, 426, 428 environmental change, 42, 62, 68, 155, 156, 223, 261, 394 environmental characteristics, 145, 157, 163, 223 environmental conditions, viii, 15, 39, 46, 57, 59, 64, 74, 156, 180, 217, 227, 241, 274, 282, 285, 440, 472 environmental contamination, 9, 17 environmental degradation, 20, 260, 342 environmental effects, 223 environmental factors, xi, xii, 20, 21, 115, 205, 219, 250, 251, 330, 340 environmental impact, iv, vii, xi, 24, 150, 219, 220, 221, 224, 228, 247, 267 environmental influences, 32 environmental management, xi, xiv, 115, 219, 269, 334, 342, 352, 368 environmental protection, 266 Environmental Protection Agency, 116, 175, 182, 217, 223, 243, 299, 300, 331, 332 environmental quality, viii, xii, 3, 29, 40, 41, 59, 250, 251, 338, 344 environmental regulations, 60
environmental stress, viii, 4, 14, 17, 20, 21, 23, 37, 40, 41, 43, 59, 64, 257 environmental stresses, 41 environmental sustainability, 261 environmental variables, 142, 159, 160, 161, 170, 174, 267 enzyme, 6, 7, 23, 30 enzymes, 6, 7, 8, 12, 27, 28, 34, 116 EPA, 155, 175, 182, 215, 223, 227, 280, 289, 290, 299, 300, 400, 403, 415 epithelia, 13, 14 epithelial cells, 7, 12 epithelium, 5 equilibrium, 222, 240, 250 equipment, 226, 362, 373, 424, 426, 430 equity, 365 erosion, 78, 80, 100, 113, 126, 144, 190, 191, 192, 193, 198, 199, 200, 203, 207, 208, 220, 221, 222, 227, 242, 256, 306, 307, 308, 309, 310, 319, 320, 360, 384, 389, 426 erythrocytes, 10, 20, 24 erythropoietin, 12, 32 estrogen, 4 estuarine environments, 56 estuarine systems, ix, 153, 154, 182 ETA, 306 ethanol, 42, 229 ethics, 246 ethylene, 282, 283, 373 ethylene glycol, 373 EU, 109, 156, 157, 214, 266, 329, 337, 338, 341 Europe, 36, 71, 176, 183, 263, 268, 280, 334, 335, 337, 367, 370, 373, 387, 391, 395, 459 European Commission, 251, 257, 261, 270 European Community, 259, 263, 336 European Union, 156, 174, 337, 350 eutrophic, 84, 120, 178, 250, 251, 254, 257, 260, 261, 262, 264, 266, 272, 273, 274, 276, 277, 339, 357, 452, 458, 471 evaporation, vii, viii, 39, 41, 43, 51, 53, 126, 128, 193, 194, 195, 254, 260, 261, 263, 357 evapotranspiration, 227 evidence, xi, 5, 21, 25, 26, 31, 41, 138, 142, 216, 219, 220, 224, 234, 260, 272, 330, 349, 365, 380, 384, 390, 393, 395, 396, 407, 465 evolution, xv, 125, 222, 241, 251, 273, 368, 372, 373, 376, 385, 388, 390, 393, 394, 395, 396 excavations, 361 exchange rate, 226, 423 exclusion, 418 excretion, vii, 2, 3, 6, 12, 29, 30, 260 exercise, 10, 22, 29, 366 experimental condition, 288
Index experimental design, 25, 142 expertise, 25 exploitation, xiv, xvi, 250, 256, 260, 333, 334, 335, 340, 349, 362, 365, 398, 403, 406 explosives, 282 exports, 126, 127 exposure, vii, viii, xvi, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 46, 73, 75, 76, 96, 190, 191, 195, 196, 214, 240, 254, 417, 420 expulsion, 10, 436 external influences, 160 extinction, 104 extraction, 244, 245, 290 exudate, 20
F facies, xiv, xv, 121, 371, 372, 373, 375, 377, 378, 380, 382, 384, 385, 386, 387, 391, 392 facilitators, 247 FAI, 59, 60 families, xiv, 136, 337, 352, 354, 404, 421, 425 family members, 430 farmers, 339, 363 farmland, 180 farms, 163, 186, 217, 261, 332, 338 fascia, 64 fat, 5, 6, 409, 411 fauna, vii, xi, xiv, 1, 2, 46, 59, 60, 70, 131, 141, 143, 145, 147, 148, 150, 177, 219, 223, 224, 225, 228, 229, 233, 240, 241, 245, 265, 272, 352, 353, 360, 363, 365, 383, 394 feces, 260, 405 fertilization, 264 fertilizers, 58, 256 fiber, 439 fibers, 58 fidelity, 181, 228, 413 filtration, xiii, 12, 280, 294, 295, 296, 298 financial, 109, 174, 214, 329, 420, 422, 427, 429, 430 financial capital, 429 financial support, 109, 174, 214, 329 fine suspended particles, 190 Finland, vi, xiii, 77, 99, 212, 213, 225, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 329, 331, 332 fish liver, 3, 4, 5, 7, 8, 23, 27, 31 fisheries, x, xi, xvi, 114, 116, 140, 149, 154, 171, 176, 220, 222, 243, 244, 245, 249, 250, 261, 335, 341, 369, 417, 418, 419, 420, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 458
481
fishing, vii, ix, xiv, xvi, 1, 2, 73, 74, 90, 91, 98, 99, 101, 102, 103, 166, 167, 169, 170, 171, 173, 263, 333, 360, 362, 403, 417, 418, 419, 420, 421, 423, 424, 425, 426, 428, 429, 430, 431, 432, 433, 471 fixation, 201, 202, 217, 314, 324, 358 flocculation, 107, 115, 130, 237 flooding, xiv, 143, 227, 333, 359, 363, 364, 403 floods, 360, 423, 430 flora, vii, xiv, 1, 2, 143, 150, 156, 223, 226, 265, 352, 353, 360, 363, 365 flora and fauna, vii, xiv, 1, 2, 143, 150, 265, 352, 353, 360, 363, 365 flotation, 42 fluctuant, 161 fluctuations, vii, viii, xii, 18, 31, 39, 41, 136, 221, 222, 226, 249, 250, 256, 263, 264, 267, 270, 395, 396, 419, 436 fluid, 222, 273 food chain, 258, 338 food habits, 109 food production, 253 food safety, 338 food web, ix, 114, 117, 134, 153, 154, 155, 162, 170, 172, 173, 179, 180, 181, 182, 260, 264, 271, 277, 348, 349, 357, 360, 455 force, 14, 140, 266, 409 Ford, 365, 368 formaldehyde, 228, 229 formation, 6, 10, 123, 144, 186, 221, 295, 441, 458 formula, 116, 168, 196 fouling, 338, 340, 357 fragments, 48, 51, 377, 378, 382 France, xiii, 39, 47, 53, 57, 60, 64, 66, 67, 71, 177, 242, 245, 264, 265, 271, 272, 280, 333, 334, 335, 337, 338, 339, 342, 350, 351, 359, 361, 369, 370, 391 free radicals, 281 freezing, 437 freshwater species, 9, 22, 110, 360, 377 frost, 41 fungi, 77 fusion, 6
G gasification, 287 general knowledge, xii, 249, 251 genes, 8 genus, 43, 229 geography, 243 geological history, 222 geology, 129, 255, 344 geometry, 124, 453 Georgia, 66, 272
482
Index
Germany, 71, 280, 324, 368 gill, 29, 34 gland, 14 global climate change, 273 global scale, 254 glucose, 11, 33 glycerol, 229 glycogen, 3, 4, 5, 6, 23 glycoproteins, 16 gonads, 9, 24, 340, 404 goods and services, 174, 223, 352, 418 governance, 329, 427 government policy, xvi, 398, 412 governments, 251 grain size, 46, 59, 136, 137, 377, 378, 383, 384 granules, 19 graph, 164 grass, 96, 226 grasses, xv, 143, 397, 398, 407, 409 grasslands, 395 gravity, 201, 328 grazing, 94, 181, 275, 357, 362, 364, 449 Great Britain, 35, 243 Greece, 52, 63, 65, 69, 70, 179, 265 green alga, 263, 473 groundwater, 48, 178, 263, 272, 273, 300, 360 grouping, 141 growth, 12, 16, 17, 18, 26, 31, 35, 58, 63, 115, 129, 131, 135, 143, 144, 189, 206, 216, 250, 256, 257, 260, 262, 263, 274, 275, 339, 344, 345, 346, 348, 389, 419, 423, 424, 426, 450, 451, 452, 455, 471 growth hormone, 17, 31, 35 growth rate, 135, 339, 344, 345, 348 GSA, 396 guidance, 300, 432 guidelines, 130, 144, 365 Guinea, 145, 242 Gulf Coast, 394 Gulf of Finland, vi, xiii, 212, 213, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 312, 314, 315, 316, 318, 320, 321, 322, 323, 325, 326, 327, 329, 331 Gulf of Mexico, xv, 150, 262, 338, 397, 398, 399, 400, 401, 411, 413
H habitat quality, 173 harbors, 223, 280, 285 hardness, 459, 461, 462, 463, 464, 466, 467, 468, 470 harmony, xvi, 417, 418 harvesting, 258, 338, 339 hazards, 285, 420, 424, 425, 429, 430
health, viii, 3, 4, 13, 15, 20, 21, 23, 24, 30, 31, 33, 40, 41, 57, 126, 141, 146, 154, 173, 176, 179, 180, 261, 265, 272, 285, 338, 340, 347, 349, 364, 425, 426 health care, 425 health condition, 13, 426 health status, 41, 340 heavy metals, 8, 13, 14, 15, 19, 31, 35, 36, 66, 71, 141, 149, 173, 277, 283, 338 height, 128, 306, 373, 439, 441 hematocrit, 22 hemoglobin, 22 Hepatic lipidosis, 6, 34 hepatic necrosis, 32 hepatic portal system, 10 hepatocytes, 4, 5, 6, 7, 26, 27, 35, 36 hepatotoxicity, 5, 6, 8 hepatotoxins, 7 herbicide, 13, 27 heredity, 418 heterogeneity, 41, 142, 145, 149, 162, 166, 276 heterotrophy, 2725 highlands, 180 Himmerfjärden Bay, v, x, 185, 187, 188, 190, 191, 192, 194, 196, 198, 200, 204, 206, 209, 213, 214 Histopathology, 4, 19, 26, 34 history, 3, 36, 67, 116, 117, 138, 167, 222, 243, 245, 256, 335, 350, 392, 405, 406, 411, 424 Holocene, vi, xv, 63, 69, 71, 221, 371, 372, 376, 385, 388, 390, 391, 392, 393, 394, 395, 396 homeostasis, 3, 11, 15 homes, 409 Hong Kong, 391 horizontal salinity distribution, 41 hormone, 3, 14, 15, 31, 35 hormones, 11, 12, 14 host, 33 hot springs, 361 household income, 425 human activity, 163, 223 human capital, 425 human development, 253 human health, 15, 173, 261, 265, 285, 338 human perception, 265 hunting, xv, 361, 362, 398, 405, 406, 409, 411 hurricanes, 254, 262, 372 husbandry, 411, 412 hyaline, 46, 48, 50 hydrocarbons, xiii, 6, 13, 58, 59, 60, 67, 141, 280, 282, 283, 285 hydrodynamic turnover XE "turnover" time, 43 hydrogen, xii, 131, 143, 144, 279, 281, 282, 284, 285, 288, 289, 290, 294, 459
Index hydrogen peroxide, xii, 279, 281, 282, 284, 285, 288, 289, 290, 294 hydrological conditions, 181, 274 hydrolysis, xii, 280, 281 hydroxide, 271 hydroxyl, 281, 282, 283, 284, 291 hydroxyl groups, 283 hyperplasia, 4, 5, 14, 19 Hypertrophism, 251 hypertrophy, 4, 5, 6, 14 hypotension, 27 hypothalamus, 14 hypothesis, 6, 125, 223 hypoxia, 22, 32, 129, 147, 243
I ICAM, 64 ice algal community, 436, 437, 442, 445, 446, 449, 450, 451, 454 Iceland, 337 ideal, viii, 3, 39, 62, 170 identification, 266, 373, 410, 437, 439 identity, 431 image, 19, 20 image analysis, 19, 20 imbalances, 18 imitation, 136, 149, 215, 216, 217, 262, 263, 330, 331, 452 immigration, 85, 86, 87, 88, 89, 90, 93, 102 immune function, 32 immune response, 10, 15, 16, 17, 21 immune system, 3, 15, 21, 28, 35, 36, 38 immunity, vii, 2, 3, 10, 11, 15, 16, 26, 36 immunocompetent cells, 19 immunoglobulin, 27, 32, 35 immunoglobulins, 10 immunosuppression, 18 impact assessment, 267, 271, 352 Impact Assessment, 223 improvements, 29, 60, 213, 430 in transition, 29, 266, 267, 277 in vitro, 11, 14, 27 in vivo, 19, 26, 27, 33 incidence, 18, 21, 60, 179 income, xvi, 344, 360, 417, 423, 425, 426 incompatibility, 334 independence, 363 India, vi, xvi, 27, 35, 69, 260, 272, 391, 395, 417, 418, 419, 428, 431, 432, 433 indigenous peoples, 403 indirect effect, 136, 429
483
individuals, vii, 1, 2, 42, 136, 141, 168, 173, 242, 340, 365, 382, 383, 403, 404, 411, 412, 461, 462, 463, 470 Indonesia, 260, 272, 395 inducer, 7 induction, 6, 7, 30 industrialization, 423, 471 industrialized countries, 280 industries, xvi, 57, 186, 216, 223, 285, 304, 344, 398, 406, 425, 432 industry, 263, 284, 334, 363, 430, 432 inertia, 366 infection, 3, 15, 16, 18, 21, 32 inferences, 156 infestations, 21 infilling, xv, 123, 143, 228, 372, 390, 391 inflammation, 16, 26 infrastructure, xvi, 126, 143, 363, 404, 417, 424, 426, 430 inland aquatic ecosystems, 155 innate immunity, 15, 26 insecticide, 8, 35 insecurity, 428 institutional change, 419 institutions, 158, 285, 365, 428 integration, 155, 243, 274 integrity, x, 13, 20, 28, 35, 141, 154, 156, 157, 167, 175, 176, 177, 180, 181, 354 interest groups, 364 interface, ix, xiii, 119, 120, 126, 333, 344 interference, 14, 15 Intermittently Closed and Open Lake Lagoons (ICOLLs), 120 internal environment, x, 154, 157, 419 internal processes, 74, 198, 304, 309, 349 intervention, 274, 403 intestine, 14 intoxication, 5 intrinsic value, 222 invertebrates, 2, 116, 134, 136, 148, 156, 162, 179, 224, 226, 239, 246, 350, 357, 369 investment, 21 investments, 186, 324, 344 ion transport, 13 ions, xii, 11, 12, 14, 34, 279, 281, 283 Iowa, 29 IPR, 80, 90, 95 Iran, 265 iron, xii, 17, 18, 131, 134, 255, 271, 279, 281, 282, 283, 290, 291, 297, 298, 299, 347 irradiation, 283 irrigation, 163, 363
484
Index
islands, ix, xi, 119, 121, 122, 159, 164, 172, 219, 222, 230, 239, 240, 255, 421 isolation, 68, 123, 393 isotope, x, 154, 170, 171, 179, 182 Israel, 62, 71 issues, vii, viii, xiii, 1, 2, 11, 12, 19, 34, 40, 43, 109, 157, 172, 174, 216, 304, 333, 348, 423, 430 Italy, xiii, 39, 53, 57, 62, 64, 66, 69, 70, 249, 253, 255, 264, 265, 268, 269, 273, 275, 276, 279, 280, 285, 393 Ivory Coast, 49
J Japan, vi, xvi, 32, 59, 70, 71, 260, 272, 334, 417, 435, 443, 451, 453, 454 Java, 272, 395 jurisdiction, 266, 335 juveniles, 19, 31, 33, 45, 335, 340, 341
K K+, 12, 13, 14, 33, 374 kidney, vii, 1, 3, 9, 10, 11, 12, 13, 14, 17, 22, 24, 28, 30, 31, 32, 33, 34, 35, 36 kidneys, 13, 18 kill, 225, 409 kinetic model, 37 kinetics, 140, 291
L laboratory studies, xii, 7, 279 laboratory tests, 285 Lake Mälaren, 188 lamination, 377, 380, 382 landings, xvi, 417, 423, 426, 432 landscape, ix, xiii, 119, 120, 125, 142, 144, 155, 162, 163, 164, 166, 169, 170, 171, 175, 180, 181, 223, 333, 354, 363, 403 landscapes, 155, 415 languages, 335 larvae, 21, 93, 114, 137, 170, 264, 339 larval stages, 27 Late Pleistocene, vi, xv, 371, 372, 385, 388, 390, 392 Latin America, 266 laws, 409, 411 leaching, 131 lead, 3, 4, 12, 13, 19, 21, 22, 34, 35, 41, 53, 56, 58, 97, 130, 140, 141, 143, 154, 156, 240, 255, 257, 403, 412, 424, 430 leakage, 224, 256 learning, 366 legislation, xiv, 352, 354 lending, 424, 428
lens, 128, 229 lesions, 4, 13, 20, 25, 27 leucocyte, 21 levees, 373, 384 liberation, 8 life cycle, 27, 37, 87, 267, 271, 338, 340, 359 light, 26, 34, 88, 111, 129, 136, 149, 155, 194, 200, 202, 205, 225, 241, 257, 271, 287, 291, 293, 297, 311, 316, 347, 359, 423, 439, 450, 452, 459, 461, 462, 463, 465, 466, 467, 468, 470, 471 light conditions, 202, 205, 311, 316 light scattering, 194 light transmittance, 225 lignin, 58 limestone, 344, 361, 390 lipid metabolism, 3 lipid peroxidation, 6, 26 Lipid peroxidation, 6 lipids, 3, 6, 340 liquid phase, 288, 289, 294, 295 literacy, 421, 425 literacy rates, 425 Lithuania, 266 liver, vii, 1, 3, 4, 5, 6, 7, 8, 9, 17, 18, 19, 21, 23, 24, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37 liver cells, 4 liver damage, 8 liver disease, 26 livestock, 364 loans, 428 local authorities, 285, 410 local community, xiv, 351, 352, 410 local conditions, 56 localization, 32, 254, 259 Louisiana, 19, 31, 225, 243, 246, 269 lying, 260, 335, 363, 420 lymph, 9, 17 lymph node, 9, 17 lymphocytes, 9, 10, 17, 20, 22, 31 lymphoid, 9, 10, 11, 19, 22, 32, 33, 34, 35 lymphoid organs, 9, 19, 32, 34, 35 lymphoid tissue, 9, 10
M macroalgae, 97, 98, 99, 117, 149, 150, 160, 180, 251, 257, 274, 343, 345, 346, 348 macrobenthos, 240, 243, 245, 247 macronutrients, 130 macrophages, 10, 13, 15, 16, 17, 18, 19, 20, 26, 31, 35 magnesium, 461, 462, 463, 470 magnitude, 90, 126, 291, 294, 346, 366 major issues, xiii, 333
Index majority, ix, 119, 121, 127, 297, 337, 409, 411, 418 mammal, 361 mammals, 4, 5, 6, 7, 8, 16, 97, 361 man, 57, 97, 148, 164, 361, 365, 420 mangroves, 67, 135, 260 manipulation, 240, 247 mapping, 56, 165 marches, 468 marginalisation, 354, 366 marine benthos, 245, 246 marine diatom, 452 marine environment, 7, 12, 42, 59, 61, 62, 64, 69, 70, 126, 134, 147, 150, 216, 217, 246, 330, 458 marine environments, 7, 12, 42, 62, 64, 126, 134, 458 marine fish, 36, 45, 114, 222 marine species, 383 marketing, xvi, 417, 421, 424, 426, 428, 430 marrow, 9 marsh, xiv, 41, 64, 66, 67, 69, 70, 117, 177, 360, 362, 363, 364, 369, 371, 378, 380, 385, 387, 389, 392, 398, 407, 409 Maryland, 30 mass XE "mass" -balance model, viii, x, xiii, 73, 74, 75, 76, 78, 100, 109, 185, 186, 193, 198, 214, 216, 301, 303, 304, 308, 309, 315, 330 materials, xvii, 114, 165, 190, 199, 200, 220, 228, 230, 239, 250, 280, 306, 307, 310, 361, 410, 425, 429, 435, 450, 451 matrix, 281, 282, 283, 291, 294, 297, 383 Mauritania, 392 measurement, 173, 201, 454 measurements, 76, 195, 228, 237, 289, 308, 321, 327, 341, 413, 437, 439 meat, 406, 409, 411, 412 median, 19, 83, 111, 112, 192, 195, 196, 199, 204, 208, 313, 315, 321 medical, 425 Mediterranean, v, x, xiii, xiv, 33, 34, 45, 46, 47, 53, 61, 69, 71, 75, 153, 154, 155, 156, 157, 160, 164, 166, 169, 174, 175, 176, 177, 180, 181, 183, 239, 254, 256, 261, 263, 264, 265, 269, 270, 271, 273, 274, 276, 333, 334, 335, 337, 338, 342, 344, 348, 351, 352, 354, 359, 368, 369, 370, 394, 396 Mediterranean climate, 344, 348 Mediterranean countries, 352 melanin, 17 melting, 450, 454 membranes, 13, 241 memory, 370 mercury, xv, 8, 13, 19, 31, 34, 37, 258, 272, 397, 400, 401, 402, 403, 411, 414, 415 Mercury, 13, 35, 399, 400, 401, 402, 413, 415
485
mesoderm, 10 Metabolic, v, 1, 78, 79, 80 metabolic pathways, viii, 2, 25 metabolism, 3, 5, 6, 8, 17, 23, 24, 28, 30, 36, 116, 148, 251, 272, 274 metabolites, 6, 12 metabolized, 7, 58 metabolizing, 27 metal ion, 283 metal ions, 283 metals, x, xiii, 4, 6, 8, 13, 14, 15, 19, 22, 23, 29, 31, 35, 36, 66, 68, 71, 130, 141, 149, 173, 185, 187, 277, 280, 283, 294, 301, 303, 338 meter, xi, 96, 206, 219, 230 methodology, 66, 266, 269, 341 methylene chloride, 282, 283 Mexico, xv, xvi, 150, 175, 176, 245, 246, 247, 262, 275, 338, 397, 398, 399, 400, 401, 403, 404, 405, 409, 410, 411, 412, 413, 414, 415 Mg2+, 12, 373 Miami, 376 microorganism, 16 microorganisms, 16, 49 microscope, 32, 34, 42, 376, 452, 453 microscopy, 439 Middle East, 176 migrants, 361 migration, viii, 73, 76, 82, 86, 87, 88, 89, 93, 95, 98, 102, 107, 109, 245, 255 mineralization, 193, 226, 254, 298, 346 Ministry of Education, 174, 298 mission, 364, 367 missions, x, 185, 186, 189, 211, 212, 213, 413 mitochondria, 5, 13 mitogen, 34 mixing, viii, x, 41, 51, 58, 73, 150, 185, 186, 192, 193, 194, 195, 198, 203, 207, 226, 255, 288, 289, 304, 307, 308, 309, 315, 319 modelling, 74, 75, 77, 78, 79, 80, 82, 100, 108, 115, 116, 144, 145, 158, 215, 268, 269, 271, 273, 276, 330, 331, 343, 365, 459 models, 5, 74, 76, 93, 109, 116, 117, 171, 181, 201, 205, 215, 217, 252, 266, 267, 269, 274, 276, 303, 304, 327, 329, 332, 343, 393 moderators, 98, 109, 111, 199, 202, 311 modifications, 21, 46, 58, 76, 110, 256, 267 moisture, 286, 287, 296, 298 moisture content, 287 molecular biology, 36 molecular oxygen, 281 molecular weight, 285 molecules, 3, 15, 16, 17, 283, 284 morbidity, 173
486
Index
Morocco, 261, 394 morphological abnormalities, 69 morphological variability, 123 morphology, viii, ix, 2, 3, 4, 22, 25, 35, 58, 66, 120, 122, 123, 125, 126, 140, 254, 373, 452, 454 morphometric, 20, 21, 28, 75, 190 mortality, 19, 60, 129, 173, 180, 224, 225, 245, 275, 346, 410 mosaic, 181, 354 mosquitoes, 352 motivation, 225 MSW, 111, 193, 194 mucosa, 9 mucus, 15, 201 multiple factors, 41 multiple regression, 170, 171, 203 multiple regression analyses, 170 multiple regression analysis, 203 multivariate analysis, 376 multivariate statistics, 229
N Na+, 12, 13, 14, 33 NaCl, 438, 439 Namibia, 176 NAS, 403, 414 native species, 143, 223 NATO, 455 natural compound, 283 natural disaster, 429 natural disasters, 429 natural disturbance, 136, 141 natural hazards, 429 natural resources, 260, 366 Navicula, xvii, 435, 442, 443, 454 necrosis, 5, 13, 18, 20, 32 Necrosis, 5 negative consequences, 365 negative effects, 420 negative relation, 170 neglect, 354, 366 nephropathy, 29 net migration, 255 Netherlands, 37, 175, 176, 177, 179, 180, 182, 183, 243, 247, 280, 334 neurotransmitters, 17 neutral, 282 neutrophils, 16, 22, 26 New South Wales, 62, 120, 123, 145, 147, 148, 149, 150, 151, 262 New Zealand, 59, 67, 144, 148 NGOs, 421, 432 Nicaragua, 405, 413
nickel, 13, 283 Nigeria, 55 Nile, 32, 61, 261, 274 nitrates, 264, 267 nitrification, 134 nitrifying bacteria, 133 nitrite, 258, 461, 462, 465, 466, 470 nitrogen, 29, 51, 109, 117, 129, 130, 131, 134, 147, 148, 149, 150, 162, 179, 187, 188, 189, 201, 203, 204, 206, 211, 212, 215, 216, 261, 262, 263, 264, 267, 268, 269, 270, 271, 276, 303, 313, 314, 324, 330, 331, 332, 343, 344, 350, 358, 359, 453 nitrogen compounds, 263 nitrogen fixation, 201 nitrogen gas, 131, 134 N-N, 358 nodes, 9, 17 North Africa, 176, 261, 271, 275, 359, 360 North America, 409, 410, 413 Norway, 28, 62, 280, 337 NPS, 285 nutrient concentrations, x, 82, 111, 129, 131, 134, 135, 136, 143, 186, 187, 211, 214, 257, 264, 274, 277, 304, 307, 314, 458 nutrient enrichment, 181, 257 nutrient transfer, 356, 357 nutrients, ix, x, xii, xiii, 6, 41, 52, 68, 74, 78, 111, 119, 120, 126, 129, 130, 140, 141, 143, 155, 159, 162, 181, 185, 186, 198, 212, 214, 217, 220, 226, 228, 237, 246, 249, 250, 251, 254, 256, 260, 261, 262, 263, 264, 267, 270, 272, 274, 301, 302, 327, 332, 335, 344, 356, 359, 360, 436, 454, 458, 459 nutrition, 36, 46 nutritional imbalance, 18 nutritional status, 4, 25
O obstacles, 425 oceans, 122, 215, 330, 349 ODS, 162 officials, 419 OH, 281, 283, 298, 299, 300 oil, xvi, 18, 19, 20, 32, 58, 60, 66, 68, 69, 398, 406, 429 oil spill, 32, 60, 68, 69 olefins, 282 oocyte, 340 openness, 166, 334 operations, xi, xiii, 219, 226, 228, 231, 237, 241, 242, 280 opportunities, 418 ordinary differential equations, viii, 73, 74 ores, xiv, 371
Index organ, vii, 1, 3, 4, 9, 10, 11, 12, 16, 21, 24, 25, 28 organelles, 5 organic chemicals, 13 organic compounds, xii, 7, 33, 41, 58, 279, 283, 294, 298 organism, vii, 1, 6, 20, 38, 79, 223, 264 organs, vii, viii, 1, 2, 3, 9, 11, 12, 16, 17, 19, 20, 25, 32, 34, 35, 37, 346 osmolality, 12 osmotic pressure, 439 osmotic stress, 261 outreach, 410 overgrazing, 423 overlap, 57, 61, 157, 172, 430 ox, 6, 74, 100, 107, 133, 134, 136, 201, 237, 404 oxidation, xii, 255, 258, 279, 280, 281, 283, 284, 285, 288, 291, 292, 293, 294, 296, 297, 298, 344, 377 oxidative reaction, 281 oxidative stress, 28 oxygen, 13, 41, 43, 46, 54, 58, 59, 99, 101, 108, 112, 113, 128, 133, 134, 136, 137, 144, 186, 187, 199, 201, 203, 204, 206, 209, 210, 226, 228, 237, 240, 267, 269, 273, 281, 328, 344, 345, 346, 356, 358, 459, 461, 462, 463, 464, 465, 466, 467, 468, 470, 471 oxygen consumption, 186, 199 oyster, 222, 260, 272, 338, 339, 341, 348, 349 oysters, xvii, 260, 269, 339, 341, 344, 348, 436, 449, 451 ozone, xii, 279, 281, 282
P Pacific, 68, 338, 432 paints, 340 paleontology, 390 parallel, xi, 49, 219, 221, 254, 335, 377, 380, 382 parasite, 21 parasites, 21, 265 parasitic infection, 18 parenchyma, 3, 4, 5, 9, 10, 11, 16 partial differential equations, 74 participants, 367 pathogens, 17, 21, 338 pathology, 26 pathways, viii, 2, 25, 160, 352 PCBs, 6, 7, 14, 22, 23, 31, 282, 283, 285, 286, 288, 290, 291, 297, 299 peat, 222, 240, 361 peptides, 27 percolation, ix, 119, 121 perfusion, 4, 7 periodicity, 231, 232, 240
487
peripheral blood, 22 peritoneal cavity, 26 permeability, 14, 436, 459, 461, 462, 463, 465, 466, 467, 468, 470, 471 permission, iv, 347 permit, xv, 372, 373 peroxidation, 6, 18, 26 peroxide, xii, 280, 281, 282, 284, 285, 288, 289, 290, 294 personal communication, 376 Perth, 148 pesticide, 14, 20, 32, 41, 179, 256 petroleum, xiii, 22, 32, 280, 282, 283, 285, 299 Petroleum, 299 pH, xii, xv, 29, 41, 46, 57, 128, 131, 135, 136, 148, 228, 237, 256, 257, 267, 276, 279, 280, 281, 282, 283, 284, 286, 287, 288, 289, 290, 291, 294, 295, 299, 348, 397, 399, 401, 459, 461, 462, 463, 464, 465, 466, 467, 468, 470 phagocyte, 16, 36 phagocytosis, 15, 16, 17 phenol, 31 Philadelphia, 28, 298, 368 phosphate, 12, 134, 166, 228, 229, 237, 271, 347, 461, 462, 465, 466, 470, 471 phosphates, 347 phosphorous, 254, 261, 263, 264, 267, 276, 358 photosynthesis, 129, 452 phylum, 41 physical characteristics, 123 physical environment, 224, 252, 424 physical features, 125, 126 physical properties, 246, 396 physical structure, 163, 164, 223, 449 physicochemical characteristics, 43, 398 physico-chemical parameters, 241 physicochemical properties, 170 Physiological, 29, 36 physiology, 6, 12, 17, 22 pituitary gland, 14 plankton, viii, 73, 87, 88, 114, 122, 192, 200, 224, 257, 271, 304, 314, 449, 452, 454 plants, 135, 223, 224, 256, 258, 262, 337, 343, 344, 357, 358, 359, 364, 407, 409, 423 plasma levels, 8 platform, 289 playing, vii, 1, 2 PM, 78, 115, 187, 215, 228, 311, 326 Poland, 324 polar, 453 policy, xiv, xvi, 182, 270, 336, 341, 352, 360, 364, 365, 398, 412, 430, 431, 432 policy makers, 430
488
Index
policymakers, 252 political power, 426 political problems, 261 pollutants, vii, viii, x, xii, xiii, 1, 2, 3, 4, 5, 7, 13, 14, 15, 17, 19, 24, 25, 126, 167, 185, 220, 225, 258, 276, 279, 280, 281, 282, 283, 284, 285, 287, 288, 295, 298, 301, 338, 340, 359, 360, 365 polycarbonate, 439 polychlorinated biphenyl, xiii, 6, 7, 179, 280, 282 polychlorinated biphenyls (PCBs), 6, 7, 282 polycyclic aromatic hydrocarbon, 7, 23, 281 polypeptide, 14 polyunsaturated fat, 6 ponds, 45, 51, 59, 65, 163, 169, 373, 377, 390, 395 pools, 16 population, viii, ix, 2, 3, 7, 15, 20, 23, 24, 27, 37, 42, 66, 146, 153, 155, 156, 160, 173, 181, 188, 226, 252, 256, 334, 337, 344, 354, 359, 361, 368, 383, 384, 406, 408, 410, 418, 419, 421, 424, 425, 426, 430 population densities, 334 population density, 42, 226, 418 population growth, 256, 419, 424 population size, 173 population structure, 368, 383, 384 Portugal, 1, 29, 43, 64, 179, 182, 264, 269, 270, 271, 273, 274, 275, 337, 371, 392, 394, 395 positive correlation, 59, 237 positive feedback, 345 positive interactions, 365 positive relationship, 237 potassium, 281, 283 poverty, 261, 418, 420, 423, 430 poverty reduction, 420 power plants, 223 precipitation, xii, 81, 125, 130, 148, 190, 191, 193, 194, 195, 198, 280, 281, 305, 309, 348, 357, 358, 398, 400 predation, 65, 76, 97, 98, 99, 100, 102, 103, 105, 113, 114, 115, 116, 136, 177, 215, 356 predators, ix, 80, 81, 82, 116, 117, 138, 144, 153, 154, 171, 173, 179, 183, 252, 404 predictability, 241 prediction models, 252 predictor variables, 376 preparation, iv, 172, 410 preservation, 226, 253, 266, 365 prevention, xvi, 417, 426, 430 primary data, 420 Prince William Sound, 116 principles, 87, 214, 432 private banks, 428 probability, 372
producers, 76, 178, 250, 252, 256, 272, 342, 345, 356, 451 productivity rates, 254 profit, 268 project, 109, 214, 223, 224, 227, 228, 229, 230, 231, 232, 239, 240, 247, 261, 266, 300, 329, 337, 344, 427 prolactin, 14, 31 proliferation, 5, 6, 149, 160, 180, 338, 344 proline, 116 protected areas, 157, 177, 380 protection, xiv, 120, 144, 157, 222, 226, 251, 253, 265, 266, 268, 331, 333, 365, 409, 433 protective mechanisms, 36 proteins, 8, 16 proximal tubules, 13, 27 PTFE, 288 public concern, 342 public health, 3, 21 public support, 174 publishing, 71 pulp, 10, 19, 22, 26, 58 purification, 60, 193, 207, 341 pyrite, 347
Q quantification, 201, 266, 267, 277, 349, 368 quantitative estimation, 436 quartz, 376, 377, 378, 380, 382, 383, 385 Quartz, 379, 380, 384 Queensland, 146, 149, 262, 268 quotas, 74, 115, 330
R radiation, 262, 348, 373 radicals, 281, 282, 284 rainfall, 41, 51, 124, 125, 126, 127, 129, 140, 142, 227, 262, 275, 358, 364, 399, 400, 411, 423 raw materials, 361 reactants, 281 reaction rate, 282, 283, 284 reactions, xii, 3, 6, 16, 21, 26, 280, 281, 282, 284, 288, 297 reactive oxygen, 13 reactivity, 21, 282 reagents, xii, xiii, 279, 280, 281, 285, 288, 289, 294, 297 reality, xiv, 40, 107, 324, 351 receptacle, xiv, 333, 335 reception, 361, 362 recession, 220 recognition, xiv, 16, 71, 285, 352, 409, 420
Index recommendations, iv, 189, 366 reconciliation, 261 reconstruction, xiv, 304, 305, 322, 327, 371 recovery, xi, 20, 23, 24, 102, 104, 161, 219, 221, 225, 234, 240, 245, 257, 325, 408, 413, 414, 415 recovery plan, 414 recreation, 167, 223 recreational, vii, 1, 2, 98, 465, 471 recycling, 17, 18, 226, 260, 357, 453 red blood cells, 9, 18, 22 regeneration, 146, 243 regression, 11, 81, 83, 85, 110, 111, 112, 114, 160, 170, 171, 195, 201, 203, 205, 206, 303, 304, 310, 314, 316, 318, 440, 441 regression analysis, 203 regression line, 111, 303, 318, 440, 441 regression model, 114, 171, 304 regulations, xii, xiv, 60, 157, 251, 266, 279, 351, 354, 362 regulatory requirements, xii, 279 rehabilitation, xiv, 173, 351, 354 reintroduction, 411, 412 relevance, xi, 21, 249, 250, 253, 265, 276 remedial actions, 109, 214 remediation, xii, 23, 25, 265, 279, 284, 287, 294, 300 renin, 12, 27 repair, 5, 423, 425 replication, 228 reproduction, 45, 58, 339, 341, 348, 350 requirements, xii, 42, 221, 230, 266, 279, 284, 334, 354 RES, 79 researchers, xii, xvii, 60, 249, 251, 256, 268, 349, 420, 421, 430, 457 reserves, 360 residues, 41, 179 resilience, 250, 420 resistance, xiii, 7, 21, 27, 30, 179, 250, 264, 273, 277, 280, 298, 337, 365 resolution, 332, 388, 392 resource allocation, 426, 433 resource management, xiv, 221, 352, 366, 369, 433 resources, vii, xiv, xvi, 2, 24, 134, 164, 166, 223, 224, 228, 245, 256, 258, 260, 261, 266, 268, 271, 299, 300, 333, 334, 348, 349, 352, 354, 360, 362, 363, 365, 366, 404, 410, 417, 418, 419, 421, 423, 424, 425, 426, 427, 428, 430, 432 restoration, 29, 144, 174, 181, 182, 220, 227, 230, 243, 244, 246, 262, 269, 300, 348, 352, 363, 364, 426 retention rate, 78, 86, 87 reticulum, 5, 6, 18 rights, iv, 360, 424, 426
489
rings, 284, 292, 294 risk, 37, 167, 202, 264, 267, 295, 338, 343, 347, 350, 363, 366, 400, 420, 427 risk assessment, 37 risks, 24, 202, 206, 213, 258, 430 river basins, 146 river systems, 125 root, xvi, 344, 345, 361, 417, 425 root system, 344, 345 roots, 96, 344, 346, 377, 378 routes, 2, 223 routines, 180 rowing, 340 Royal Society, 63, 145, 244 RPR, 35 rules, 429 runoff, xvi, 48, 124, 125, 126, 128, 130, 140, 141, 145, 148, 227, 254, 262, 270, 343, 359, 398, 437, 464 Russia, 266, 324
S safe haven, 97 safety, 338 saline water, 40, 120, 204, 336, 357, 358, 363, 421, 449, 466, 471 salinity levels, xvii, 358, 457 salmon, 5, 22, 26, 32, 35, 36 salt concentration, 347 salts, 283 saltwater, 110, 139, 201, 357, 400 samplings, 421 sanctions, 409 sanctuaries, 120, 223 saturation, 99, 101, 108, 113, 128, 203, 358, 374 scaling, 452 school, 409, 425, 429, 430 schooling, xvi, 417, 425, 426, 429, 430 science, ix, 29, 108, 116, 153, 154, 227, 243, 246, 268, 270, 273, 274, 365, 366, 367, 368, 369 scientific knowledge, 261, 369, 406, 411 scientific papers, 264 scientific publications, 258, 335 scope, 216, 228, 319, 329, 331, 341 sea level, 67, 69, 220, 221, 222, 265, 348, 373, 387, 388, 391, 469 seafood, 403 sea-level, xv, 67, 222, 261, 265, 372, 393, 395, 396 sea-level rise, 222, 261, 393 seasonal changes, 34, 270, 358 seasonal flu, 31, 136 seasonal growth, 346 seasonality, 170
490
Index
secondary data, 420 secrete, 41 secretion, 14, 15, 29, 32 security, 363, 428 sedimentation, viii, x, xiii, 41, 73, 74, 84, 105, 106, 107, 110, 113, 129, 146, 185, 186, 187, 190, 192, 198, 199, 201, 203, 204, 205, 208, 222, 224, 225, 242, 243, 301, 303, 304, 306, 308, 309, 314, 317, 320, 328, 359, 376, 377, 385, 391, 392, 393, 436, 437, 449, 452, 453, 454, 455 seeding, 454 selectivity, 114, 294 semantics, 273 semi-structured interviews, 421 Senegalese sole, 9, 28 senescence, 358 sensitivity, 13, 25, 56, 60, 74, 99, 102, 105, 107, 109, 168, 221, 245, 327, 328, 420 septic tank, 143 serum, 8, 28, 34 services, iv, xiv, 114, 174, 222, 223, 253, 270, 351, 352, 354, 360, 362, 365, 366, 368, 412, 418, 430 settlements, 157, 256, 265, 403, 463, 471 sewage, 20, 21, 31, 51, 58, 59, 129, 141, 143, 188, 189, 217, 264, 358 sex, 23 sexuality, 340 shade, 450 shape, 123, 126, 340 sheep, 361, 362 shellfish, 45, 338, 341, 343 shelter, 97, 123, 159, 345 shoreline, 123, 140, 160, 166, 167, 168, 169, 173, 220, 255, 263, 265 shores, 53, 54, 156, 174, 222, 223, 229, 352, 357, 368 shortage, 363 showing, 9, 10, 48, 50, 163, 314, 321, 340, 344, 399, 425, 438, 441 shrimp, 45, 59, 65, 222, 402, 403, 432 Siberia, 114 signals, ix, 153, 154 signs, 2, 20, 240 silica, 437, 439 silver, 13, 27 simulation, 102, 105, 217, 277, 331 simulations, 92, 98, 99, 100, 105, 202, 206, 209, 212, 213, 274, 313, 316, 323, 325 skin, 9, 15, 405 sludge, 287, 299 smoothing, 84, 88, 111, 113, 157 snakes, 352, 360 SO42-, 346
social benefits, 363 social capital, 422 social development, 363 social infrastructure, xvi, 417, 424, 426, 430 social problems, 261 social relations, xvi, 417 social security, 363 social structure, 418 society, 222, 267, 421 sodium, 281, 283, 288, 289 soil erosion, 222, 256, 426 soil particles, 360 soil pollution, 268 soil type, 403 Solea senegalensis, 9, 28 solid matrix, 281, 282, 283, 291 solid phase, 288, 289 Solomon I, 367 solution, 227, 228, 229, 281, 283, 288, 289, 359, 428, 430, 438, 439 solvents, 282 sorption, xii, 130, 280, 281 South Africa, 145, 149, 176 SPA, 157 Spain, vi, x, xiv, 149, 153, 157, 175, 176, 177, 179, 180, 181, 214, 265, 268, 273, 274, 277, 329, 359, 371, 372, 373, 382, 391, 392, 393, 394, 395, 396 specialists, 168, 410 specialization, 159, 168 species richness, 52, 54, 60, 166, 225, 240, 263 spectrophotometric method, 459 spectrophotometry, 290 sperm, 11 spleen, vii, 1, 3, 9, 10, 16, 17, 18, 19, 20, 21, 22, 24, 29, 31, 32, 33, 36 Spring, 149, 180, 269, 412 SSI, 21, 22, 23, 24 stability, 147, 246, 277, 285, 365 stabilization, 161 stakeholders, xiv, xvi, 352, 354, 362, 365, 418, 426, 427, 429, 430 standard deviation, xvii, 105, 107, 172, 192, 195, 196, 197, 199, 202, 205, 208, 232, 291, 307, 315, 316, 319, 323, 325, 326, 401, 435, 443 starvation, 18, 26 state, xii, 4, 16, 77, 102, 136, 166, 187, 210, 213, 217, 240, 250, 251, 263, 266, 267, 269, 270, 271, 275, 276, 304, 325, 327, 328, 331, 345, 347, 348, 361, 398, 405, 411, 420, 421, 429, 431 states, 144, 173, 277, 324, 337, 341, 398, 421 Statistical Package for the Social Sciences, 376 statistics, 172, 229, 426, 432 steroids, 9
Index stimulant, 15 stomach, 15, 173 storage, 3, 4, 6, 10, 17, 18, 22, 23, 24, 32, 35, 229, 356, 358, 360, 367 storms, 41, 372, 389 stormwater, 130, 141 stratification, 41, 48, 51, 53, 55, 56, 65, 128, 194, 198, 203, 304, 307, 382, 384 stress, viii, 3, 4, 5, 14, 17, 18, 20, 21, 24, 25, 26, 27, 28, 29, 30, 31, 33, 35, 37, 40, 41, 43, 54, 57, 59, 61, 62, 64, 65, 66, 96, 109, 112, 141, 151, 168, 221, 257, 261, 270, 271, 471 stress factors, 14, 37, 168 stressors, ix, 4, 22, 23, 25, 153, 154, 250, 252, 271, 400, 403 structuring, 277 style, 243 subgroups, 384, 385 subsistence, 352, 366, 403, 418 substitutions, 282 substrate, 59, 224, 240, 403 substrates, 59, 241, 255 success rate, 340 succession, 150, 215, 242, 246, 275 sulfate, xi, 12, 19, 220, 228, 229, 234, 237, 241, 275, 346 sulfur, 148, 229, 346, 347 sulphur, 258, 272 Superfund, 27, 285 supplier, 11, 288, 289, 451 suppression, 6, 15, 21 surface area, xv, 47, 51, 53, 123, 124, 125, 130, 195, 255, 397, 398, 437, 441, 453, 463 surface layer, 42, 51, 128 surplus, 12, 162 surrogates, 156 surveillance, 63, 173 survival, xvi, 12, 97, 113, 223, 340, 361, 410, 417, 418, 424 survival rate, 340 susceptibility, ix, 21, 120, 122, 140, 147, 225 suspensions, 373 sustainability, 228, 252, 261, 425, 428 sustainable development, 221, 253, 337, 365 Sweden, 73, 99, 102, 116, 185, 211, 216, 217, 301, 324, 330, 331 swelling, 6, 13 Switzerland, 32, 367 symptoms, 140, 167, 266 syndrome, 166 synthesis, 3, 6, 8, 9, 23, 24, 34, 116, 245, 270 systemic change, 148
491
T Taiwan, 260, 272, 273 tanks, 143, 341, 411, 412 tannins, 129, 134, 135 Tanzania, 151 taphonomy, 62 target, vii, xii, 1, 3, 28, 187, 192, 206, 250, 253, 279, 282, 284, 285, 298, 304, 310, 316, 327 target variables, 187, 192, 206, 304, 316, 327 taxa, ix, 41, 49, 136, 137, 138, 141, 153, 154, 156, 177, 225, 229, 232, 234, 241, 365, 461, 462, 463 taxonomic descriptions, 439 taxonomy, 43 teams, 385 techniques, 3, 13, 76, 162, 164, 172, 173, 175, 223, 258, 267, 376, 409 technologies, 275, 298, 299 technology, 243, 284 tenure, 367 terraces, 389, 396 territorial, 336 testing, 156 tetrachlorodibenzo-p-dioxin, 30, 37 textbook, 115 textbooks, 187 texture, 66, 390, 391 TGF, 17 Thailand, 393, 432 Thalassiosira, xvii, 435, 442, 444, 452 thoughts, 419 threats, xvi, 92, 99, 109, 115, 117, 147, 227, 262, 398, 409, 412, 417, 430 tidal range_ XE "tidal range" _ formula, 196 tides, 49, 204, 222, 254, 345, 405 time frame, 305 time lags, x, 153, 155 time series, ix, 42, 153, 154 tin, 338 tissue, 3, 4, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 20, 23, 24, 26, 27, 33, 173, 402 tonic, 452, 454 tourism, xiv, xvi, 156, 157, 176, 222, 256, 262, 333, 334, 352, 398, 406, 458, 471 toxic contamination, viii, 73, 74, 75, 99, 104 toxic effect, vii, 2, 3, 13, 15, 24, 258, 345 toxic gases, 257 toxic substances, 12, 102, 105, 187, 303 toxicity, 5, 6, 7, 8, 15, 19, 28, 30, 37, 225, 291, 295, 298 toxicology, 12, 24, 28, 29, 30, 37 toxin, 5 trace elements, 41, 58, 59, 60, 61, 257
492
Index
tracks, 405 trade, 144, 424, 426, 428 traditions, 361, 406 traits, 36 transaminases, 8, 24 transformation, 352, 358, 359, 393 transgression, xv, 221, 372, 376, 385, 389, 391, 392, 393 transition metal, 283 transition metal ions, 283 transitional coastal waters, 154 transport processes, x, xiii, 78, 185, 186, 189, 190, 201, 206, 214, 215, 222, 245, 301, 316 transportation, 78, 190, 192, 198, 220, 306, 307, 308, 309, 340, 449 transportation XE "transportation" areas, 78, 190, 192, 306, 308 treatment, xii, xiii, 20, 22, 187, 188, 189, 195, 211, 213, 253, 256, 262, 270, 280, 281, 282, 285, 287, 288, 289, 290, 291, 294, 295, 296, 298, 343, 344 triggers, 425 trophic classes, 321 trophic level, viii, 39, 250, 254, 256, 260, 263, 264 trophic state, xii, 77, 217, 250, 263, 267, 270, 276, 331 turbulence, 186, 198, 309 turbulent mixing, 198, 309 Turkey, vi, xvii, 178, 268, 337, 457, 459, 463, 465, 472, 473 turnover, vii, viii, 39, 41, 43, 46, 79, 80, 84, 93, 94, 95, 107, 111, 113, 116, 192, 200, 205, 207, 208, 210, 216, 258, 304, 308, 309, 317, 318, 319, 320, 327, 328, 356, 367
U U.S. Army Corps of Engineers, 300 U.S. Geological Survey, 28 UK, 33, 35, 177, 179, 242, 245, 298, 299, 361, 368, 369, 392, 394, 395, 431, 432 ulcer, 32 ultrastructure, 8, 28, 35, 63 UN, 247, 365, 420 UNESCO, 64, 245, 246, 247, 253, 267, 272, 353, 365, 370, 452 uniform, 142 United, 69, 145, 150, 265, 276, 277, 299, 300, 405, 413 United Kingdom, 145, 150 United Nations, 276, 277 United States, 69, 299, 300, 405, 413 updating, 364 urban, xiv, xvi, 52, 59, 61, 126, 130, 141, 142, 145, 146, 147, 157, 166, 167, 179, 223, 261, 262, 263,
264, 265, 268, 270, 275, 277, 304, 333, 343, 344, 351, 363, 398, 404, 406, 409, 458, 471 urban areas, 52, 142, 304 urban settlement, 157, 265 urbanisation, 130, 140, 143, 148, 334, 344 urbanization, 157, 177, 262, 352, 403 urine, 11, 12 USA, xiii, 32, 35, 38, 66, 115, 116, 246, 247, 266, 275, 279, 280, 285, 287, 289, 298, 299, 300, 368, 370, 376, 393, 397, 413, 414 UV, 283 UV irradiation, 283
V validation, 376, 385 valuation, 23 variables, ix, x, 74, 76, 77, 80, 81, 82, 102, 109, 119, 120, 137, 141, 142, 149, 151, 153, 155, 157, 158, 159, 160, 161, 170, 171, 174, 187, 192, 193, 204, 206, 214, 234, 235, 236, 237, 238, 239, 241, 245, 254, 256, 267, 304, 307, 314, 315, 316, 327, 348, 376, 385 variations, x, xi, 4, 9, 11, 18, 23, 24, 25, 33, 40, 64, 100, 128, 151, 181, 185, 202, 203, 214, 220, 238, 239, 241, 246, 262, 271, 274, 294, 312, 345, 372, 391, 392 vector, 213 vegetation, 69, 135, 143, 168, 179, 222, 256, 270, 356, 357, 358, 362, 364, 377, 383, 403, 404, 411, 470 vein, 4 velocity, 110, 126, 195, 196, 198, 199, 306, 308, 309 vertebrates, 4, 9, 10, 11, 15, 16, 17, 31 vessels, 4, 9, 10, 19, 288, 407 Vietnam, 47 viruses, 338, 341 vision, 432 vitamin E, 6 volatilization, 282 vulnerability, xvi, 3, 114, 168, 417, 419, 420, 422, 425, 430, 431
W waiver, 428 Wales, 62, 71, 120, 123, 145, 147, 148, 149, 150, 151, 262 warning systems, 24 Washington, 29, 32, 69, 182, 276, 298, 300, 414, 472 waste, xiv, xvi, 11, 223, 253, 256, 261, 263, 270, 299, 333, 344, 360, 398, 399, 412 waste management, 399, 412 waste treatment, 253
Index waste water, 256, 270, 344, 360 wastewater, 59, 157, 241, 269, 343, 344, 409 water ecosystems, 166 water policy, 270, 336 water quality, vii, ix, xi, 2, 15, 17, 41, 60, 100, 120, 122, 125, 127, 131, 137, 139, 140, 141, 143, 144, 148, 150, 187, 219, 220, 221, 225, 226, 228, 229, 234, 235, 236, 237, 238, 239, 241, 249, 251, 257, 261, 266, 267, 268, 269, 273, 274, 275, 335, 341, 342, 344, 345, 347, 349, 400, 405, 411, 413, 415, 458, 471 water resources, 261, 363 waterbirds, ix, 153, 154, 155, 156, 160, 161, 162, 163, 165, 166, 170, 171, 173, 176, 177, 178, 180, 181, 182, 240, 359 watershed, xiii, xvi, 145, 146, 157, 166, 173, 177, 269, 277, 333, 335, 342, 343, 344, 349, 418, 419, 426, 427, 428, 430 waterways, 147, 280 wave base, 112, 190, 191, 192, 193, 199, 200, 204, 206, 207, 305, 306, 307, 308, 309, 310, 314, 318, 321 weakness, 55, 175 wealth, viii, 2, 3 web, 114, 162, 170, 173, 177, 180, 181, 182, 250, 260, 264, 267, 269, 271, 277, 348, 349, 357, 360, 410, 455 weight ratio, 4 well-being, xvi, 340, 398, 412 West Africa, xi, 43, 46, 64, 180, 219, 226, 243, 245, 246, 261, 272, 274, 276, 369 West Indies, 242, 244, 413 Western Australia, 137, 147, 148 Western Europe, 337 wetlands, ix, xiii, xiv, xvi, 153, 154, 156, 157, 159, 169, 173, 174, 175, 176, 177, 178, 179, 181, 183,
493
226, 241, 247, 253, 263, 265, 267, 268, 269, 271, 273, 276, 333, 336, 352, 356, 360, 361, 368, 370, 371, 373, 390, 393, 398, 406, 411, 412, 414 wild animals, 226 wilderness, 363 wildlife, vii, 2, 32, 166, 173, 220, 334, 426 wind speeds, 227 woodland, 180, 461 workers, 363 working groups, 336 worldview, 365 worldwide, viii, xi, 39, 45, 47, 156, 220, 249, 250, 255, 258, 259, 265, 266, 268
X X-ray diffraction, 373 X-ray diffraction (XRD), 373 XRD, 373
Y Y-axis, 450 yield, 81, 82, 127, 162, 166, 220, 222, 245, 263, 270, 297 yolk, 5 young people, 430
Z zinc, 8, 14, 33, 34, 37, 130, 141 zooplankton, viii, 73, 76, 77, 83, 85, 86, 87, 90, 91, 92, 93, 94, 95, 99, 100, 101, 102, 103, 104, 105, 113, 114, 116, 162, 200, 254, 256, 262, 270, 272, 274, 275, 304, 319, 450, 454, 459
