Whales, Seals, Fish and Man

Developments in Marine Biology 4

Whales, seals, fish and man

Developments in Marine Biology 1.

Toxic dinoflagellate blooms edited by D.L. Taylor and H.H. Seliger, 1979 (out of print)

2.

Phytoflagellates edited by E.R. Cox, 1980 (out of print)

3.

Toxic phytoplanktonblooms in the sea edited by T.J. Smayda and Y. Shimizu, 1993

Developments in Marine Biology 4

Whales, seals, fish and man Proceedings of the International Symposium on the Biology Marine Mammals in the North East Atlantic Tromsg, Norway, 29 November-1 December 1994

Editors:

Arnoldus Schytte Blix Department of Arctic Biology, University of Tromse, Tromse, Norway Lars Wallge Institute of Physiology, University of Oslo, Blindern, Oslo, Norway 0yvind Ulltang Institute of Marine Research, Nordnes, Bergen, Norway

1995

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0 1995 Elsevier Science B.V. All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher, Elsevier Science B.V., Permissions Department. P.O. Box 521, lo00 AM Amsterdam, The Netherlands. No responsibility is assumed by the Publisher for any injury andor damage to persons or property as a matter of products liability, negligence or otherwise, or from use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, the Publisher recommends that independent verification of diagnoses and drug dosages should be made. Special regulations for readers in the USA - This publication has been registered with the Copyright Clearance Center Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, USA. Information can be obtained from the CCC about conditions under which photocopies of parts of this publication may be made in the USA. All other copyright questions, including photocopying outside the USA, should be referred to the copyright owner, Elsevier Science B.V., unless otherwise specified. Developments in Marine Biology 4 ISBN 0 444 82070 1 This book is printed on acid-free paper. Published by: Elsevier Science B.V. P.O. Box 21 1 lo00 AE Amsterdam The Netherlands

Library of Congress Cataloging in Publication Data: I n t e r n a t i o n a l S y m p o s i u m on t h e B i o l o g y o f M a r i n e M a m m a l s in t h e N o r t h E a s t A t l a n t i c (1994 T r o m s s , N o r w a y ) Whales. seals. fish, and man proceedings o f the International S y m p o s i u m on t h e B i o l o g y o f M a r i n e M a m m a l s i n t h e N o r t h E a s t A t l a n t i c . T r o m s c . N o r n a y . 29 N o v e m b e r - 1 D e c e m b e r 1994 / e d l t o r s . A r n o l d u s S c h y t t e - B I i x . L a r s WalIcre. 0 1 v i n d U l t a n g . p. c m . -- ( D e v e l o p m e n t s i n m a r i n e b i o l o g y 4) I n c l u d e s indexes. I S B N 0-444-82070-1 1. M a r i n e m a m m a l s - - N o r t h A t l a n t l c O c e a n - - C o n g r e s s e s . 2. F i s h e r i e s - - N o r t h A t l a n t i c O c e a n - - C o n g r e s s e s . I. S c h y t t e - B l l x . Arnoldus. 11. Wallse. Lars. 111. Ultang. Oivind. IV. Title. V. S e r i e s . 0~713.25.157 1994 599.5'09163'3--dC20 95-91 10 CIP

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In order to ensure rapid publication this volume was prepared using a method of electronic text processing known as Optical Character Recognition (OCR). Scientific accuracy and consistency of style were handled by the author. Time did not allow for the usual extensive editing process of the Publisher. Printed in the Netherlands

Preface In February 1988, the Board of the Norwegian Fisheries Research Council agreed to establish an integrated research programme on whales and seals in Norwegian waters. A planning group was appointed to draw up the framework for the programme and recommend how it should be organised. Members of the planning group were Professor Lars WallCe, University of Oslo; (chairman) Professor Amoldus S. Blix, University of Tromsr (senior lecturer) Per Grotnes, Norwegian College of Fishery Science, Tromsr (research officer) Morten Ryg, University of Oslo; (research director) Oyvind Ulltang, Institute of Marine Research, Bergen. A plan was presented in June 1988 and approved by both the Board of the Norwegian Fisheries Research Council, and the two relevant ministries (Environment and Fisheries). The planning group was supplemented by one representative from each of the two ministries, and was appointed as the steering group for the research programme. Dr. Nina H. Markussen later replaced Dr. Morten Ryg, Dr. Ame J. BjCrge and Mr. Helge Lorentzen were representatives of the ministries for most of the programme period, but were temporarily replaced by others. Ms. Sidsel GrCnvik was employed as secretary to the steering group. In 1988, there were two main reasons for the establishment of an extensive research programme on marine mammals. Firstly, in the preceding few years there had been considerable scientific disagreement concerning the information on which Norwegian minke whaling was based. In particular, there had been controversy over the size of the north-east Atlantic minke whale stock, and disagreement as to whether continued harvesting of the stock could be justified. In 1986, the International Whaling Commission decided to classify the northeast Atlantic minke whale stock as a "protection stock", and the Norwegian government subsequently appointed an independent group of scientists to assess the state of our knowledge and review the scientific controversy (Roy M. Anderson, UK; Raymond J.H. Beverton, UK; Ame Semb-Johansson, Norway; and Lars WallCe, Norway). The group concluded that our knowledge of the biology, population structure, and stock sizes of this species was inadequate and recommended a number of research activities designed to provide more data. Secondly, during the winter of 1986-1987 large numbers of harp seals appeared along the Norwegian coast. Altogether, about 60,000 animals were caught in fishing gear. The same happened on a somewhat smaller scale in the winter of 1987-1988. These migrations resulted in heavy economic losses for fishermen. The reasons for the mass migrations were not clear, although many hypotheses were put forward. The steering group gave highest priority to research activities which could provide more information on the questions mentioned above, but funding was also provided for research proposals related to other aspects of the management of marine mammals. The research programme was originally planned to last for five years, but was later extended for another two years until the end of 1994. The total research council

vi spending on the programme added up to more than NOK 100 million (approximately 15 million US$). We believe that the programme has resulted in significant advances in our understanding of marine mammals both in Norwegian waters and elsewhere. Since marine mammal research is a topic of international interest, the steering group decided to arrange an international symposium to mark the conclusion of the programme, to present the results and to provide an opportunity for criticism and discussion. The symposium was organised in Tromsr Norway, at 70~ in the middle of the Arctic winter (November 29 to December 1, 1994), when snow and darkness prevail, but it nevertheless attracted 150 participants from no less than 17 countries. This volume presents the proceedings of the symposium. It outlines the major findings from the Norwegian programme, and in addition contains invited contributions from international authorities on specific relevant topics as well as other communications by non-Norwegian participants. We hope that this volume will be of interest to scientists and managers as well as to the environmentally aware members of the general public.

Arnoldus Schytte Blix Lars WallOe Oyvind Ulltang

vii

Acknowledgements The editorial committee gratefully acknowledges the work of the organising committee for the symposium: Ame J. BjCrge (convener), Oyvind Ulltang, Erling S. NordCy, Sidsel Grcnvik (secretary), and the many helpers from the Department of Arctic Biology, the Norwegian College for Fishery Science, and the Norwegian Institute of Fisheries and Aquaculture, as well as the financial contributions from the Research Council of Norway and the many sponsors, all of whom contributed to a successful symposium. We would also like to express our appreciation of the secretarial assistance provided by Ms. Elin Giaever during the production of this volume.

viii

Sponsors The Research Council of Norway, Oslo The University of Tromsr The Roam Amundsen Centre for Arctic Research, University of Tromsr The Norwegian Institute of Fisheries and Aquaculture, Tromsr TromsO Kommune Norges Fiskarlag, Trondheim Norges R&fisklag, Tromsr Sildemelfabrikkenes Landsforening, Oslo Nord-Norges Sildolje- og Sildemelfabrikkers Forening, Vadsr G.C. Rieber & Co., A/S, Bergen L. Macks Olbryggeri og Mineralvandsfabrik A/S, Tromsr Odd Berg Gruppen, Tromsr

ix

Contents Preface Acknowledgements Sponsors

V

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Stock assessment Estimating the abundance of marine mammals: a North Atlantic perspective P.S. Hammond Effective search width in shipboard surveys of minke whales in the northeastern Atlantic: concepts and methods T. Schweder and G. Hagen Point clustering of minke whales in the northeastern Atlantic G. Hagen and T.Schweder Use of mark-recapture experiments to monitor seal populations subject to catching N. @en and T. @-itsland Estimation of grey seal Halichoerus grypus pup production from one or more censuses S.-H. Lorentsen and Bakke Increased accuracy in the estimation of harp seal (Phoca groenlandica) abundance in whelping patches V.I. Chernook, V.A. Potelov and N. V. Kuznetsov Haul-out behaviour of the Norwegian harbour seal during summer R. Roen and A. Bj@rge Influences on spatial patterns of Gulf of Maine harbor porpoises D. Palka Aerial surveys of harp and hooded seal pups in the Greenland Sea pack-ice T.@itsland and N. @en

a.

Stock identity and social organization Genetic markers and whale stocks in the North Atlantic ocean: a review A. Arnason Genetic variation in northeastern Atlantic minke whales (Balaenoptera acutorostrata) A. K. Danielsddttir, S. D. Hallddrsson, S. Gudlaugsddttir and A. Arnason Preliminary results of a DNA-microsatellite study of the population and social structure of the harbour porpoise L. W. Andersen, L.-E. Holm, B. Clausen and C.C. Kinze Photo-identification of the minke whale Balaenoptera acutorostrata off the Isle of Mull, Scotland A. Gill and R.S. Fairbairns

3

13 27

35 47

53 61 69 77

91 105

119 129

X

Parasites as indicators of social structure and stock identity of marine mammals J.A. Balbuena, F.J. Aznar, M. Ferndndez and J.A. Raga Marine mammalian fatty acids: a source of information 0. Grahl-Nielsen and 0. Mjaavatten Fatty acid composition in blubber, heart and brain from phocid seals B. Fredheim, S. Holen, K.I. Ugland and 0. Grahl-Nielsen Studies of the social ecology of Norwegian killer whales (Orcinus orca) A. Bisther and D. Vongraven Possible effects of previous catch on the present population of Norwegian killer whales (Orcinus orca) D. Vongraven and A. Bisther

Distribution, diet and feeding ecology New approaches to studying the foraging ecology of small cetaceans A.J. Read Distribution and diving behaviour of hooded seals L.P. Folkow and A.S. Blix Distribution and abundance of walruses (Odobenus rosmarus) in Svalbard I. Gjertz and @. Wiig Habitat use and diving behaviour of harbour seals in a coastal archipelago in Norway A. Bjorge, D. Thompson, P. Hammond, M. Fedak, E. Bryant, H. Aarefjord, R. Roen and M. Olsen Spatial and temporal variations in northeast Atlantic minke whale Balaenoptera acutorostrata feeding habits T. Haug, H. Gj@sa?ter,U. LindstrGm, K.T. Nilssen and I. Rottingen Seasonal distribution, condition and feeding habits of Barents Sea harp seals (Phoca groenlandica) K.T. Nilssen Food consumption of the Northeast Atlantic stock of harp seals E.S. Nordoy, P-.E. Mirtensson, A.R. Lager, L.P. Folkow and A.S. Blix Historic variation in the diet of harp seals (Phoca groenlandica) in the northwest Atlantic J. W. Lawson and G.B. Stenson Seasonal and regional variations in the diet of harbour seal in Norwegian waters M. Olsen and A. Bjorge Feeding ecology of harp and hooded seals in the Davis Strait - Baffin Bay region F. 0. Kapel

133 141 153 169

177

183 193 203

21 1

225

24 1 255

26 1

27 1

287

xi

Energetics and other physiological aspects Food requirements of Northeast Atlantic minke whales E.S. Nordgy, L.P. Folkow, P.-E. MGrtensson and A.S. Blix Energetics of pregnancy, lactation and neonatal development in ringed seals (Phoca hispida) C. Lyde rsen Harp and hooded seals - a case study in the determinants of mating systems in pinnipeds K.M. Kovacs Consumption of cod by the Northwest Atlantic grey seal in Eastern Canada M.O. Hammill, M.S. Ryg and B. Mohn Digestive physiology of minke whales S.D. Mathiesen, T.H. Aagnes, W. Sgrmo, E.S. Nordgy, A.S. Blix and M.A. Olsen Body condition of fin whales during summer off Iceland G.A. Vikingsson Seal adaptations for long dives: recent studies of ischemia and oxygen radicals R. Elsner, S. Qyaseter, O.D. Saugstad and A.S. Blix Pineal functions in newborn seals K.-A. Stokkan Changes in metabolic rate and body composition during starvation and semistarvation in harbour seals N.H. Markussen Variation in the metabolic rates of captive harbour seals D. Rosen and D. Renouf Population dynamics Population dynamics: species traits and environmental influence C.W. Fowler Interpretation of growth layers in the periosteal zone of tympanic bulla from minke whales Balaenoptera acutorostrata I. Christensen On the life history and autecology of North Atlantic rorquals J. Sigurjdnsson Aspects of the biology of the harbour porpoise, Phocoena phocoena, from British waters C. Lockyer Aspects of reproduction and seasonality in the harbour porpoise from Dutch waters M.J. Addink, T.B. Sgrensen and M. Garcia Hartmann Migration strategy of southern minke whales to maintain high reproductive rate H. Kato

307 319 329 337

35 1 36 1 37 1 377 383 393

403 413 425 443 459 465

xii Overview of cetacean life histories: an essay in their evolution T. Kasuya Modelling the school structure of pilot whales in the Faroe Islands, 18321994 D. Bloch and L. Lustein Harp seals as indicators of the Bqrents Sea ecosystem Y.K. Timoshenko

Interactions with fisheries Interactions between marine mammals and fisheries: an unresolved problem for fisheries research T.D. Smith Strategies to reduce the incidental capture of marine mammals and other species in fisheries M.A. Hall Ecological implications of harp seal Phoca groenlandica invasions in northern Norway T. Haug and K.T. Nilssen Aspects of the sealworm Pseudoterranova decipiens life-cycle and sealfisheries interactions along the Norwegian coast K. Andersen, S. des Clers and T. Jensen Grey seal (Halichoerus grypus Fabr.), population biology, food and feeding habits, and importance as a final host for the life-cycle of sealworm (Pseudoterranova decipiens Krabbe) in Icelandic Waters E. Hauksson and D. Olafsddttir Pollutants, toxicology and epizootics Toxicological and epidemiological significance of pollutants in marine mammals P.J.H. Reijnders and E.M. de Ruiter-Dijkman Organochlorine contaminants in marine mammals from the Norwegian Arctic J.U. Skaare Seasonal variation of organochlorine concentrations in harp seal (Phoca groenlandica) L. Kleivane, 0. Espeland, K.I. Ugland and J. U.Skaare Biomarkers in blood to assess effects of polychlorinated biphenyls in freeliving grey seal pups B.M. Jenssen, J. U.Skaare, S. Woldstad, A.T. Nastad, 0. Haugen, B. Kloven and E.G. Sormo Toxic, essential and non-essential metals in harbour porpoises of the Polish Baltic Sea P. Szefer, M. Malinga, W. Czarnowski and K. Skdra

48 1 499 509

527 537 545 557

565

575

5 89 599

607 617

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Assessment of the vulnerability of grey seals to oil contamination at Froan, Norway M.Ekker, D. Vongraven, B.M. Jenssen and M. Silverstone Cytochrome P450 in marine mammals: isozyme forms, catalytic functions, and physiological regulations A. GoksQyr Serological investigation of morbillivirus infections in minke whales (Balaenoptera acutorostrata) S. Stuen and P. Have

Management and cultural, social and economic aspects of exploitation The International Whaling Commission’s Revised Management Procedure as an example of a new approach to fishery management J.G. Cooke Multispecies modelling and management with reference to the Institute of Marine Research’s multispecies model for the Barents Sea 0.Ulltang The management of Irish waters as a whale and dolphin sanctuary E. Rogan and S. D. Berrow The scientific background for the management of monodontids in West Greenland M.P. Heide-JQrgensen Marine mammals in the culture of Norwegian coastal communities A. Kalland Management of whaling in coastal communities R. Gambell Impacts of modern seal invasions S. Eikeland

623 629 64 1

647 659 671 683 689 699 709

Index of authors

715

Keyword index

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Stock assessment

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9 1995 ElsevierScienceB.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. Ulltang,editors

Estimating the abundance of marine mammals: a North Atlantic perspective P.S. H a m m o n d Sea Mammal Research Unit, Natural Environment Research Council, Cambridge, UK Abstract. This paper investigates how studies to estimate the abundance of marine mammals have used the characteristics and behaviour of the target population to help determine the most appropriate method for any specific study. It also addresses how these studies have attempted to overcome the problems associated with ensuring that important assumptions of the method are not violated. Three basic methods used for estimating marine mammal abundance are described: extrapolating counts; mark-recapture analyses of photo-identification data; and sightings surveys. Recent studies in the North Atlantic to estimate abundance include: harbour seals and bottlenose dolphins in the Moray Firth, Scotland; grey seals in the North Sea and the breeding population in Britain; North Atlantic humpback whales; and the NASS and SCANS sightings surveys for whales and small cetaceans in the North Atlantic and North Sea, respectively. The paper demonstrates the wide range of applicability of the available methods, the way that the example studies addressed and (in some cases) overcame potential problems, and the modification or extension of "standard" methodology to fit particular circumstances. Key words: population size, extrapolating counts, sightings surveys, line transect, photo-identification, mark-recapture, model assumptions, North Atlantic

Introduction There are a number of ways to estimate animal abundance that are applicable to marine mammals. But any application of these methods must take into account the inconvenient fact that pinnipeds and cetaceans spend most (or all) of their time at sea and a large proportion of that time underwater. However, studies to estimate marine mammal abundance can take advantage of the variation in the physical and behavioural characteristics of species to arrive at the most appropriate method for a particular case. In this context, pinnipeds spend a proportion of their time on land (or ice) and some of these haulout periods are predictable, particularly during the pupping season. Being out of the water avoids the complication of animals diving out of sight. This means that they can actually be counted. Methods for estimating seal numbers make use of haulout behaviour thus avoiding the problems of sampling at sea. In contrast, cetaceans spend their entire lives at sea. Direct counts are not possible and methods for estimating their abundance must rely on sampling. This has received increasing attention during the last 15 years, particularly through the forum of the IWC Scientific Committee [1,2]. This paper investigates how studies to estimate the abundance of marine mammals have used the characteristics and behaviour of the target population to help deAddress for correspondence: Sea Mammal Research Unit, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB3 0ET, UK.

termine the most appropriate method for any specific study. But even the most appropriate method will have its drawbacks, particularly the difficulties in ensuring that important assumptions of the estimation model are not violated. This paper also addresses, therefore, how these studies have attempted to overcome these difficulties. The examples chosen are all drawn from the North Atlantic, reflecting the focus of this Symposium and the experience of the author. This paper is not a review but, in describing these example studies, it is also intended to give the reader an idea of the range of work undertaken in the North Atlantic in recent years.

Methods for estimating abundance A fundamental assumption of any method of estimating abundance is that the data must be representative of the study population or area. This applies to all the methods described below.

Extrapolation of counts Rarely, if ever, can it be possible to enumerate an entire population of animals. This is certainly true for marine mammals which are effectively invisible for a large proportion of their lives. However, seals give birth and wean their pups on land or ice, and also haul out during their annual moult and on other occasions, and it is possible during these periods to count the number of animals present in an area. But all the animals in the population will not be hauled out at the same time so it is necessary to extrapolate the number of seals counted to obtain an estimate of the entire population. There are a number of ways of doing this. One is to choose a class of animal which can be counted (pups of the year, for example) and to use those numbers as input to an age- or stage-structured population model which calculates total abundance. An example of this method is given below. For a reliable estimate the population model must be realistic with parameter values estimated from relevant data. Another method of extrapolation is to count all the animals hauled within a given period and to divide this number by an estimate of the proportion of the population which is hauled out during this time. One way that this proportion can be estimated is by using telemetry data. An example of this method is given below. Assuming accurate counts can be made, these methods are most sensitive to the quality of data used to extrapolate counts to total abundance.

Mark-recapture and photo-identification Mark-recapture methods use data on the number of animals marked and the proportion of marked animals in samples of recaptured animals to estimate population size. They makes several basic assumptions about the data including:

marks are unique, cannot be lost and are always reported on recovery; and marking does not affect the subsequent catchability of an animal. In the past, mark-recapture analyses have been used to estimate the population size of marine mammals using data from artificially applied marks. More recently, studies have concentrated on populations of animals in which unique individual natural markings can be photographed and identified. Records of re-identifications from a series of photographic samples (capture histories) can then be used as data for mark-recapture analyses to estimate population size. Three examples of this are given below. Photo-identification has some advantages over the use of artificial marks [1] but obviously cannot be used for those populations whose individuals do not possess recognisable natural markings. In mark-recapture analyses, the assumption most likely to be violated is that each animal must have the same probability of being captured within a sampling occasion. It is very likely that the behaviour of individual animals will lead to heterogeneity of capture probabilities resulting in population estimates which are biased downwards. In the extreme, some animals may never be available to be sampled and will not be included in the population estimate. There are ways to account for this analytically if closed population models can be used but it is clearly better to minimise the problem during data collection. This means designing a study which gives every animal a chance of being captured, and capturing as many animals as possible. This can be achieved more easily if the distribution of the study population is concentrated in a limited area for a period during the year.

Sightings surveys Line transect methods [2,3] were first developed for terrestrial animals but are now widely used to estimate the abundance of cetacean populations via shipboard or aerial surveys. In these sightings surveys, the study area is sampled by the survey platform searching along predetermined transects, placed so that the whole area is representatively sampled. When sightings are made, data are collected which allow the calculation of perpendicular distance from the sighting to the transect line. These data are used to estimate the effective width of the strip searched so that sample density can be estimated and extrapolated to give an estimate of abundance in the whole study area. Sighting surveys thus provide an estimate of the number of animals in an area at a given time, not an estimate of the size of a biological population unless the whole of that population was in the study area during the survey period. The most important assumption made by the line transect sampling method is that every animal (or group of animals if groups are the sighting target) on the transect line itself is seen. That is, the probability of detecting an animal at zero perpendicular distance is unity. Clearly, this can never be the case for cetaceans, which are underwater most of the time. In order to arrive at an unbiased estimate of abundance, therefore, it is necessary to estimate this probability (known as g(0) in the literature). The best way to do this is through the analysis of duplicate sightings data collected

from independent sightings platforms. However, sightings surveys do not always collect data for estimating g(0) and in these cases, abundance will be negatively biased by an unknown amount, notwithstanding other potential biases. An alternative method of data collection and analysis for sightings surveys is that of "cue counting" [4]. This method involves estimating the density of cues (whale blows, for example) per unit area searched per unit time and dividing by an estimate of the rate at which animals of the study species provide cues. This approach can only be used for species which exhibit clear cues. But it has the advantage that the equivalent of g(0) is the probability that all cues at zero (radial) distance from the survey platform will be seen, which is far more likely to be satisfied. Cue counting works best from aerial platforms.

Studies to estimate abundance in the North Atlantic

Harbour seals in the Moray Firth The Moray Firth in northeast Scotland is home to a population of harbour seals which regularly haul out on inter-tidal sandbanks, particularly during the June/July pupping season. This has made it possible to count seals at all known sites in the area during this period of the year with the aim of estimating population size (personal communication). Sex-specific estimates of the proportion of seals hauled out during this time were estimated from VHF telemetry data collected from 26 seals of a range of sizes. Pups were not included in the estimate because they were being born throughout the counting period. The estimate of the average number of seals hauled out of 1007 was extrapolated to an estimate of population size (excluding pups) of 1651 (CV = 0.104). The important factors which had to be taken into account in this study were" the timing of the counts with respect to time of year, time of day and stage of tide; the need to ensure that double counting was not occurring; and the representativeness of the telemetry data. Peak haulout counts were made during the pupping season and 2 h either side of low tide. There was no diurnal pattern. This was in contrast to a similar study in Orkney where peak haulout counts were made during the moult, there was no tidal relationship but time of day had to be taken into account [5]. Double counting was judged minimal based on the movement patterns of individuals. The telemetry data were collected over a number of years and the data for females was biased towards pregnant females so there is a possibility that they were not representative and that the population estimate may be biased. Obtaining representative telemetry data for any study is often difficult and is, perhaps, the major drawback of this method of estimating abundance.

The British grey seal breeding population The number of grey seals breeding around the coasts of Britain is estimated each

year based on counts of pups born during autumn [6]. High resolution aerial photography is used to record all the pups on land at all known major breeding sites, several times during the pupping season. Pup production is estimated by fitting a model, with parameters defining birth, death and time of leaving the site, to the pup counts for each site. The number of females in the population is estimated by feeding the annual pup production figures into an age-structured population model. Total population size is obtained via a simple sex ratio calculation. The most important factors affecting this study are: the quality of the aerial photographs; the adequacy of the model used to estimate pup production from the pup counts (including the number of counts made each year at each site); and the adequacy of the data in the population model. The development of a purpose-built camera system including image-motion compensation [7] has resulted in excellent quality aerial photographs. The model to estimate pup production is sensitive to the timing and length of the pupping season. These vary from site to site, and so pup production is estimated separately for each site. Estimates of population size from the model are sensitive to the fecundity rate data and the sex ratio. The fecundity data were collected from one area in 1981 and it is not known how representative they are to other areas and the present day. There are few data on the sex ratio, which is assumed to be 1:1. Grey seals in the North Sea

The method described above estimates the size of the grey seal population breeding around Britain. But the distribution of seals outside the pupping season, when they are building up energy reserves for the next season, may be different. And it is the number of seals foraging in an area which is of most relevance to concerns about interactions with fisheries. To address this, a study using photo-identification methods to obtain data for mark-recapture analyses has been conducted to estimate the number of seals associated with haulouts along the central North Sea coast of Britain [8]. The pelage patterns of grey seals (Fig. l a) were photographed at 2-week intervals during the summer months at three major haulout areas in 1991-1993. Normally, only adult female grey seals are well enough marked to be recognisable in a subsequent photograph. This is an extreme form of heterogeneity of capture probabilities and to account for it the proportion of well-marked animals present was recorded during each sampling occasion. The pelage pattern was extracted from a standard area of the seal's head and neck by specifically developed image processing software which compensates for differences in the viewpoint of the photograph and the posture of the seal [9]. These standard images served as "marks". All pairs of photographs were compared by another computer program which generated a set of similarity measures, the highest of which were compared by eye to determine genuine matches. In this way, capture histories were established for all individually recognisable seals. A mark-recapture model was developed specifically for these data, structured to

Fig. 1. Examples of natural markings used for photo-identification studies in the North Atlantic: (a) grey seal (photo: Lex Hiby, Sea Mammal Research Unit); (b) bottlenose dolphin (photo: Ben Wilson, University of Aberdeen); (c) humpback whale (photo: Tony Martin, Sea Mammal Research Unit).

allow for movement between the three sampling areas and to account for animals identified from the left or right side [8]. The data showed that mixing of animals in the population occurred rapidly so that it was possible to estimate population size within each year using a model ignoring births and deaths. The estimates were corrected by an estimate of the proportion of well-marked seals in the population. This assumes that males and immature seals spend the same proportion of their time at haulout sites as do adult females. Limited telemetry data on grey seals indicate that this is the case but if it is not, the estimate will be biased. Heterogeneity of capture probabilities within the well-marked part of the population was probably not a problem because sampling covered all major haulout sites in the area and over 50% of this class of animals were identified. In addition, data collected outside the study area indicated little exchange of animals.

Bottlenose dolphins in the Moray Firth In the Moray Firth, one of the aims of a study of a small and isolated population of bottlenose dolphins is to estimate population size. The dolphins can be identified by nicks on the dorsal fin and/or by pigmentation patterns on the skin (Fig. l b) [10]. This is thus an ideal situation for mark-recapture analysis of photo-identification data. As in the case of grey seals described above, left and right sides of an animal are different and were sampled separately. Not all animals have natural markings so data were collected to estimate the proportion which do. The population was sampled twice each month during the summers of 1990-1992 and matches were determined by eye. The first population estimates have recently been calculated (personal communication). Analysis was via a multi-sample closed population model applied to the data for each summer. This allowed the use of identifying marks which were known to last longer than a summer but not necessarily more than a year, thus increasing sample sizes, and allowed heterogeneity of capture probabilities to be taken into account using the program, CAPTURE [11 ]. The model allowing heterogeneity gave consistently higher estimates indicating that this did need to be accounted for. The estimate in 1992, when sampling was extended to cover a larger proportion of the known range, was higher indicating that there were some site preferences within the study area and that results from this year should be used. The estimate for the right side (lower CV than left side) for 1992 using the heterogeneity model was selected as the best estimate. This study is a good example of the use of an extensive and detailed data set to address and take account of some of the potential problems of applying mark-recapture methods of photo-identification data.

North Atlantic humpback whales At the other extreme of scale is an ongoing multi-national study of humpback whales in the North Atlantic. One aim of project YoNAH (Years of the North Atlantic Humpback) is to estimate the size of the whole population via mark-recapture

10 analyses of data from photo-identification of fluke patterns (Fig. l c). Humpbacks breed in winter in the West Indies, migrating to summer feeding areas in high latitudes. There is known to be a high degree of fidelity of an animal to a particular feeding area [ 12]. Project YoNAH sampled whales in the breeding areas and again in all known major feeding areas (Gulf of Maine, Canada, West Greenland, Iceland and Norway) in 1992 and 1993. Although humpback whales occur across the whole North Atlantic, the chosen abundance estimation method is the most appropriate because all animals are well-marked and available to be sampled in relatively discrete and accessible areas. The photographs are currently being processed by eye. In 1992, 819 whales were identified in the West Indies and 855 in feeding areas. In 1993, there were 773 identifications from the West Indies and over 1000 are expected from the feeding areas. Next, the most appropriate mark-recapture model to analyze this particular data set will be developed. The options are limited by the number of sampling occasions but there is a large amount of detailed data which it is hoped can be used to test whether some of the standard assumptions have been violated and to take account of this, if necessary. For example, sampling in the feeding areas was unbalanced; how important was this? In addition, it is expected that analyses of data in the breeding areas may be affected by different behavioural characteristics of animals in different social groups, a form of heterogeneity of capture probabilities. North Atlantic sightings surveys

In 1987 and 1989, several countries in the North Atlantic collaborated in the NASS (North Atlantic Sightings Survey) projects, and a third is planned for 1995. The area covered by the 1987 and 1989 surveys is shown in Fig. 2. Ships were the main survey platform but some areas were covered by aerial survey to estimate the abundance of the target species: fin, minke, sei and pilot whales. The ship surveys used line transect sampling and the aerial surveys used cue-counting methods. On the ships, no data were collected to allow the estimation of g(0) in 1987, but in 1989 duplicate sightings data were collected on some vessels. A new "maximum simulated likelihood" method of analysis was developed to estimate g(0) for minke whales by integrating experimental and survey data [13]. NASS is a good example of one way to enable a large area of ocean to be surveyed in order to estimate cetacean abundance. Estimates of the target species could only be obtained from sightings surveys and a collaborative effort was important in order to cover as much of the North Atlantic as possible. Estimates of abundance for all the target species have been accepted by the IWC Scientific Committee although there is currently a debate about the estimate of g(0) for minke whales. For the other species, g(0) was not estimated and was assumed to be equal to one. Small cetacean abundance in the North Sea

Another, recently conducted, multi-national sightings survey in the North Atlantic

11

% % .

@

O'o/. zr \

6~'~

20.t,/

I 20"~ o* Fig. 2. Areas covered by the 1987 and 1989 NASS sightings surveys in the central and eastern North Atlantic and the 1994 SCANS sightings survey in the North Sea and adjacent waters. was SCANS (Small Cetacean Abundance in the North Sea). SCANS targeted harbour porpoises and other small cetaceans (and including minke whales) in the North Sea and adjacent waters in summer 1994. The area surveyed (shown in Fig. 2) was sampled by nine ships and two aircraft. Harbour porpoises are difficult to detect and it was expected that the probability of detecting them on the transect line would be small, so it was important to obtain good estimates of g(0). Duplicate sightings data were, therefore, collected on all ships. The two searching platforms operated all the time; one searched in "normal" mode, the other tracked sightings detected further ahead. The two aircraft flew in tandem (one directly behind the other) for much of the time, allowing duplicate sightings data to be collected during the aerial survey. New methodology was developed to analyze the duplicate sightings data from the ships and the aircraft. At the time of writing, the data are still being analyzed. It is hoped that the intensive coverage of the survey area and the extensive duplicate sightings data collected will allow the calculation of abundance estimates of higher than usual precision and accuracy.

Concluding remarks

The studies described above demonstrate the range of and variation within the methods available to estimate the abundance of marine mammal populations. In each example, the method was chosen which was most appropriate to the physical and

12

behavioural characteristics of the study population. In all cases, those conducting the research were aware of the particular difficulties of the chosen method and in some cases were able to investigate potential violations of the assumptions. And in several examples, "standard" methods were modified to adapt existing techniques to fit the particular situation. The studies described also demonstrate that there has been much work in recent years to increase our knowledge of marine mammal abundance in the North Atlantic. And the examples given, although important ones, are not exhaustive. Future attempts to estimate pinniped or cetacean population size should take note of the successes, and problems, detailed in the work described above.

References 1. Hammond PS. Estimating the size of naturally marked whale populations using capture-recapture techniques. Rep Int Whal Commn 1986;(Special Issue 8):253-282. 2. Hiby AR, Hammond PS. Survey techniques for estimating abundance of cetaceans. Rep Int Whal Commn 1989;(Special Issue 11):47-80. 3. Buckland ST, Anderson DR, Burnham KP, Laake JL. Distance Sampling: Estimating Abundance of Animal Populations. London: Chapman and Hall, 1993. 4. Hiby AR. An approach to estimating population densities of great whales from sightings surveys. IMA J Math Appl Med Biol 1985;2:201-220. 5. Thompson PM, Harwood J. Methods for estimating the population size of common seals (Phoca vitulina). J Appl Ecol 1990;217:281-294. 6. Ward AJ, Thompson D, Hiby AR. Census techniques for grey seal populations. Symp Zool Soc London 1987;58:181-191. 7. Hiby AR, Thompson D, Ward AJ. Census of grey seals by aerial photography. Photogram Rec 1988;12:589-594. 8. Hiby AR. Abundance estimates for grey seals in summer based on photo-identification data. In: Hammond PS (ed.) Grey Seals in the North Sea and their Interactions with Fisheries. Report to UK Ministry of Agriculture, Fisheries and Food under contract MF 0503, 1994. 9. Hiby AR, Lovell, P. Computer-aided matching of natural markings: a prototype system for grey seals. Rep Int Whal Commn 1990;(Special Issue 12):57-61. 10. Thompson PM, Hammond PS. The use of photography to monitor dermal disease in wild bottlenose dolphins (Tursiops truncatus). Ambio 1992;21:135-137. 11. White GC, Anderson DR, Burnham KP, Otis DL. Capture-recapture and removal methods for sampling closed populations. Los Alamos, NM: Los Alamos National Laboratory, 1982. 12. Katona SK, Beard JA. Population size, migrations and feeding aggregations of the humpback whale (Megaptera novaeangliae) in the western North Atlantic Ocean. Rep Int Whal Commn 1990;(Special Issue 12):295-305. 13. Schweder T, HCst G. Integrating experimental data and survey data to estimate g(0): a first approach. Rep Int Whal Commn 1992;42:575-582.

9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang,editors

13

Effective search width in shipboard surveys of minke whales in the northeastern Atlantic: concepts and methods Tore Schweder ~ and Gro Hagen 2

_

1University of Oslo, Blindern, Oslo, Norway; and 2Norwegian Computing Center, Blindern, Oslo,

Norway

A b s t r a c t . Concepts and methods for estimating the effective search width from survey data of the line

transect type, independent observer data, dive time data and other data sources are reviewed and further developed. It is argued that effective search width is the primary parameter, which should not be estimated by separate estimates of g(0) and f(0) in cases where the hazard of sighting has been estimated. To estimate the hazard probability of sighting in complex models, systematic simulation is used. Occurrence exposure data for estimating the hazard probability of sighting are obtained from independent observer experiments by an automatic identification rule based on measurement error data. To remove bias introduced by imperfections in the chosen rule, the independent observer experiments are simulated for spatially distributed whales with density and clustering estimated from the survey data. Measurement errors are included in the model when estimating the hazard probability of sighting. The effective search width is calculated as the sighting rate in the fitted simulation model. Emphasis is on methodology for future surveys. Key words: baleen whales, abundance estimation, sighting, line transect survey

Introduction

Shipborne surveys of whales are cases of line transect experiments (see [1,2]). In standard line transect theory, the assumptions are that (i) objects on the line are detected with certainty; (ii) objects are detected at their initial location, and (iii) measurements of time and positions are exact. An additional assumption is: (iv) cues are, with certainty, identified with individual objects. When the objects are minke whales in the north Atlantic, and when the survey is carried out by ship, none of the four assumptions are likely to be completely satisfied. A whale is only available for sighting in the brief moments it breaks the surface for breathing. Observations are made from the barrel, some 16 m above sea surface, with two trained observers using the naked eye. In the Norwegian surveys, the vessels move at a speed of 10 knots, when the sighting condition is satisfactory (ca. 25% of the time). The northern minke whale does not show itself by a visible blow, and it is not easy to see the black back of a surfacing whale. Whales dive, and it is quite possible to pass a whale which is submerged during the period of possible sighting. With g(y) being the probability of detecting a whale at perpendicular distance y from the transect, assumption (i) is that g(0) = 1. When this assumption fails, g(0) must be estimated. Data, concepts and methods for estimating g(0) are discussed in some detail. We argue, however, that the effective search width, 2w, is the parameter of

Address for correspondence: T. Schweder, University of Oslo, Box 1095 Blindern, 0317 Oslo, Norway.

14 primary interest, and this parameter should rather be estimated directly than through separate estimates of g(0) and the probability density at zero of observed perpendicular distances, f(0) = g(O)/w. The basic concept in our model is the hazard probability of sighting. This is the conditional probability of successfully sighting a surfacing whale, given that the whale was not previously sighted. Having estimated this probability as a function of surfacing position, and possibly other observables, the effective search width is estimated by counting the successes in a simulation experiment. Here, whales scattered over the area are surfacing according to observed dive time data, and they are sighted according to the estimated hazard probability of sighting. Whales are moving about. Assumption (ii) is essentially that their movements are random, with no specific directional drift, or without being affected by the observer. If whales are attracted by the approaching vessel, or if they try to avoid it, assumption (ii) is broken. This problem is not further discussed. When a whale has been sighted, the observer presses a button connected to a computer to record the time of the sighting. He then measures the radial distance to the surfacing by eye, and he measures the angle between the sighting line and the transect line with the help of an angle board fixed at the barrel rim. None of these measurements are taken without error. Separate experiments are needed to estimate the error distribution, with sighting of radar buoys or other objects similar to a surfacing minke whale at known positions, and under conditions similar to the survey. In the experiment reported in [3], the vessel moved towards radar buoys at a speed of 10 knots, and the observer was allowed to observe the buoys at discrete points in time. Such experiments serve the additional purpose of training the observers. We use data from Ref. [3] for various purposes, but we do not discuss measurement error experiments any further. We do, however, stress the importance of consistency: if measurement errors are present, substantial errors can occur if it is switched inconsistently between measured and true coordinates for relative whale positions throughout the analysis. In our case, the cues are visible surfacings of minke whales. Cues might be misinterpreted. The problem is not that other species of whales are mistaken for minke whales, but rather that series of minke whale cues erroneously might be linked together as tracks for individual whales. The identification of tracks of cues is done online, and it is based on whale behaviour, direction of movement, size and other visual aspects of the cue. This identification might be affected by two types of errors: the series of sighted cues belonging to one whale is broken into several tracks; and the series of more than one whale are linked together in one track. It is possible to develop a cue counting method which will help to remove bias introduced by erroneous track identification. Space does not, however, allow this to be done in the present paper. The primary purpose of this paper is to present concepts and methods for the shipborn survey of minke whales in Norwegian water, planned for the summer of 1995, and for similar surveys. The plan is to cover the complete northeastern Atlantic management area. We go a bit further than in Ref. [4], where the independent ob-

15 server experiments in 1989 and 1990 were analysed, and an estimate of abundance was presented. In the 1995 survey, the plan is to have two barrels in place on each vessel. This will allow the independent observer experiments to be concurrent with the survey. Heterogeneity in observational conditions, and in sighting efficiency between vessels and teams, will thus be less of a concern than assumed in Ref. [ 11 ]. Due to the criticism raised in Ref. [6], the interpretation of data from independent observer experiments is discussed in extra detail. We present an automated procedure for so-called duplicate identification. This procedure is used on the observed data from the 1990 independent observer experiment (see [5]). The classification found by using the automated rule agrees well with the classification actually used in Ref. [4]. To remove bias due to subjectivity in the classification rule, simulation based estimation is required. This approach is explained, but not carried out. The method to use is that of maximum simulated likelihood [7], which was used in Ref. [4] to estimate g(0).

The search width problem The detection curve, g(y), represents the conditional probabilities of detecting a whale, given that it is at perpendicular distance y _> 0 from the line. The effective search width, 2w, is that width for which the strip of area a = 2wL contains the same expected number of objects as is observed during a transect of length L. When the transect line is randomly placed in the area, and D is the average whale density per unit area, the expected number of sightings is

DL2~g(y) dy The effective half-width is therefore W--

~g(y) dy

If n whales are observed during a transect of length L through an area of size A, and an estimate ff is available for w, the abundance of whales in the area is estimated by ^

An

NA = 2~L

(1)

Perpendicular distances between observed whales and the line has probability density, f(y), which is proportional to the detection curve, f ( y ) = g(y)/w. The effective half-width therefore satisfies g(0) w = ~ f(0)

(2)

16 This relation has been used to estimate w, by first estimating f(0) by fitting a parametric probability density to the observed perpendicular distances in the survey, and then separately to estimate g(0) from data gathered in an independent observer experiment [1,2,4]. The effective search width is, however, a more fundamental concept than g(0). If a direct estimate of w is available, as is the case when the spatial hazard probability of sighting has been estimated, this estimate should be used in density or abundance estimation. There are two main reasons for not estimating f(0) and g(0) separately, and then computing w: (i) it is notoriously difficult to estimate the density at the extreme end, 0, of the range. Erroneous model specification for the observed perpendicular distances can actually introduce quite severe bias in the estimate of f(0). The second reason is (ii) that extra variability is introduced in the abundance estimate. If the hazard probability has to be estimated, both w, f(0) and g(0) are implicitly determined. To estimate f(0) separately from the positions of initial observations, which already have been used when estimating the hazard probability, amounts to adding variability, and it will make the estimation of uncertainty more difficult. In Ref. [4], we were in partial breach with this advice (see section 7). The abundance estimate is sensitive to the estimation of g(0). For the previous surveys of minke whales in the northeastern Atlantic, g(0) was estimated to 0.36 [4]. The abundance estimate not corrected for g(0) (setting g(0)= 1, as assumed in the standard theory) was therefore increased by a factor of 1/0.36 = 2.78.

Hazard

probability

and simulation

Minke whales are available for sighting only at the discrete points in time when they are up breathing. The concept of hazard probability is therefore appropriate when modelling the observational process. Let Q(p) be the conditional probability that a whale surfacing at position p relative to the observer platform is sighted, given that the whale was not previously sighted from the platform. If Pi is the relative position of the whale at its ith surfacing, I I ( 1 - Q(Pi)) is the probability that the whale is passed without being sighted at any of its surfacings. If the whale stays at a fixed absolute position, the relative positions a r e Pi=(Xo-vTi,y), where the first coordinate is its position along the transect direction and the second coordinate is the perpendicular position. Here, Xo is the forward distance at time 0, Ti is the time of the ith surfacing and v is the speed of the observer platform. If the surfacings follow a Poisson process in time, with surfacing rate a, the probability generating functional of the Poisson point process yields (E is the expectation operator)

g(y) =

1 - Eli

(1 -

Q(x o -

vT/, y)) = 1 - e x p ( - c t v

IoQ(X,y) dx)

(3)

It is here assumed that no whale is sighted behind the observer platform, Q (x,y) = 0, x<0.

17 There is a distinct rhythm in the surfacings of a minke whale, and the Poisson process provides only an approximation to its surfacing pattern. By simulation one obtains a better estimate than eq. (3) of the detection curve and the effective search width. The method is to scatter points representing whales over an area. Each whale is given a surfacing pattern, which might be a random selection of dive time data obtained from observing radio tagged whales (see [8]). An observer platform is simulated to move at speed v through the middle of the area, and each time a hitherto unobserved whale at relative position p, at visible range, is simulated to surface, a pseudo random experiment is carried out to determine whether the whale is observed at this exposure. The success probability is Q (p). The effective search width is calculated from the number of sighted whales and the transect length in a simulation where the spatial density of whales is set to 1. This is done as follows. Let n be the number of sighted whales in a simulated transect of length L through an area of size A containing N whales. The direct estimate of the effective search width is, by inverting eq. (1), given by An =~ 2LN

(4)

By eq. (2), a count-estimate of g(0) is found as

~(0) = ~ ( 0 )

(5)

where an appropriate distance model is used for estimating the probability density at the origin, f(0), of the perpendicular distances for sighted objects in the simulation. The simulation approach has several advantages. The simulation model can, for example, be expanded to embody measurement errors, whale movement, heterogeneity in sighting conditions, etc., when data allow valid specifications of such elements. Since the effective search width simply is estimated by counting the number of successful sightings in the simulation experiments, such modifications of the model will not make the calculation of w difficult.

Independent observer experiments In the North Sea experiment in 1990, two barrels were mounted on the mast of the vessel, one above the other [5]. The observer teams in the two barrels could not communicate, but both were linked to a common computer for coherent time measurements, and to the coordinator at the bridge. This will also be the setup for all the vessels participating in the survey in 1995. Independently of each other, the observations of surfacing minke whales are made from the two platforms, both with respect to time and relative position. These cues are linked together in tracks, supposedly belonging to individual whales. This is done on the spot, and the track identification is based on all "information" available to the

18 observer at the time. Platform A produces one set of observations, and so does platform B. At the stage of analysis, the two independent, but concurrent, sets of observed cue-tracks are converted to two sets of spatial occurrence/exposure data, one for each platform. An exposure for platform A is a surfacing seen by B of a whale which A had not sighted before. This exposure is an occurrence if A successfully sights the cue. The occurrence/exposure data for B are defined in the same way, but now with A as the control platform. The identification of occurrence/exposure data in Ref. [4] was done by visual inspection of graphical representation of the data from the two platforms. This was done independently by several scientists. For the 1990 data, the four judgements were in good agreement. This was taken as evidence for the agreed occurrence/ exposure identification to be close to correct. It has, however, been argued that the judgements could be wrong, in spite of the agreement. A different occurrence/ exposure identification was, in fact, presented in Ref. [6]. This identification was more explicitly based on observed error distributions in measurements of times and relative positions, but a substantial subjective element remained in the judgements.

Duplicate identification To avoid subjectivity in the analysis, the following approach is possible. An automated rule for identifying exposures and occurrences from the parallel stream of observations in the independent observer experiment is developed. The procedure should be consistent with information on errors in time and spatial measurements. The aim should be to have the true exposures and occurrences identified, without contaminating the data with false identifications. To prevent possible classification errors to introduce bias in the estimated hazard probability function, the automated rule is applied both to the observed data and to data obtained from simulation of the independent observer experiment. This is explained in some detail below. In the 1990 independent observer data, some positions were not recorded, but could be inferred by interpolation from other positions in the track of cues. Another problem was that some time measurements were accurate only to the minute, while other were accurate to the second. The less accurate times are given in rounded minutes, with 0 s, but it is unknown which of the time measurements with 0 s are rounded and which are accurate. From the frequency of 0 s, one finds that about 7% of the time measurements are in rounded minutes. From the measurement error experiment reported in Ref. [3], we estimated the expected value,/z, and the standard deviation, a, of the distance AP = IP,- P2l between two independently recorded positions, P~ and P2, for a duplicate sighting. These values are represented as two spatial functions of the mean of the two observed positions, P and they are used in the automated identification rule given below.

19 1.

Cues from platform A and B are matched with respect to time. The track of an A-cue and that of a B-cue are classified as a possible duplicate pair if the time difference between the two cues is less than 30 s. For a possible duplicate pair of tracks, the A-cue and B-cue closest in time are classified as a possible pair of duplicate sightings. If this pair is not unique, choose arbitrarily one of the pairs. The cues for the two tracks of a possible duplicate pair are matched in serial order, with the possible duplicate sighting as the reference. If all the matched cues have time difference less than 30 s, and if at least some of those with non-zero seconds are closer than e seconds (e = 8, 10 or 15 s), the pair remains a possible duplicate pair of tracks. 2. A pair of tracks remains a possible duplicate pair if A P < I* ( P ) + a a ( P ) for at least one matched pair of cues. The coefficient a is set to 1 if position is recorded for both cues, to 2 if position is recorded for one of the cues, while the other position is found by interpolation, and to a = 3 if both positions are found by interpolation. To further remain a possible duplicate pair of tracks, none of the matched pairs of cues must have one of its cues more than 0.2 nm away to the port side of the track line while the other is more than 0.2 nm away to the starboard side. 3. If an A-track is paired with more than one B-track as possible duplicates, the following pruning is done. Pair the A-track with that or those B-tracks which minimize the minimal time difference in matched pairs of cues. If multiple pairs remain, choose that or those which minimize the maximum time difference in matched pairs. If there still are multiples, choose that or those with minimum minimal spatial distance within matched pairs. If multiples remain, choose that with minimum maximal spatial distance within matched pairs. If the pruning is not complete at this stage, make an arbitrary choice. The remaining pairs of tracks are classified as duplicate observations of the same whale. 4. A-tracks not a member of any duplicate pair provide exposures for B. The exposures have spatial coordinates from the A-cues, and they are all classified as failures (non-occurrences). An A-track which is a member of a duplicate pair provides failure exposures for B if it has cues before those matched with Bcues. If the first B-cue in the pair is matched with an A-cue, this is classified as a duplicate sighting or an occurrence for B. The position of this successful exposure is that of the A-cue. Exposures and occurrences for A are found in the same way, with A and B interchanged. This duplicate rule applied to the 1990 data identified all exposures and occurrences used in Ref. [4], except one. Table 1 displays the result of using the above automatic role as compared to the classification used in Ref. [4]. The classification used is well characterised by the role, with e = 15 s.

Simulation-based parameter estimation The basic idea of statistical estimation is to fit a model so that its predictions are in

20 Table 1. Classification of the 1990 independent observer data by the automated rule for three critical levels Limit

Exposures

8s

+5

10 s

+5

15 s

+2

Occurrences -0 -0 -0

+0 +0 +0

-3 -3

-1

The classifications are compared to that based on visual inspection, with 219 exposures and 44 occurrences. The positive (negative) numbers indicate how many of the category have been added (missed).

the best possible agreement with observed data. In nice statistical models, it is possible to find an explicit formula for computing the estimate from the data. In more complex models, one might be able to find the estimate by numerical optimization. When, for example the parameters tr and b of the popular model

])

(6)

are estimated by the program distance [1], this is usually done by numerical maximum likelihood estimation on appropriately grouped data. In many cases, however, the model is too complex to allow the likelihood function, or some other appropriate criterion function, to be analytically or numerically maximized. In such cases, one might find an acceptable estimate of the parameter of the model by systematic simulation. The idea is to simulate the model for many different values of the parameter in a region of high simulated likelihood. The simulated likelihood of the observed data is calculated from a descriptive statistical model applied to both the observed data and the simulated data for a given value of the parameter. After having found the region of high simulated likelihood, and having computed the simulated likelihood for sufficiently many parameter points in this region, the likelihood surface is estimated by quadratic regression, possibly in a generalized linear model framework. The maximum simulated likelihood estimate is then computed by maximizing this fitted likelihood surface. Theory and methodology of maximum simulated likelihood is discussed in Ref. [9]. A version of this method was used to estimate the hazard probability of sighting minke whales in the Norwegian shipborne survey in 1989, Q = 1 - exp(- exp(flo + fl x log(x)+

fl rr))

(7)

in forward track distance x and radial distance r (see [4,7]). The maximum simulated likelihood method was actually developed for this particular problem, because the "true" likelihood was unavailable since the data consisted both of occurrence/ exposure data from independent observer experiments and positions of initial sightings in the survey.

21 When measurement errors are included in the model (see below) and an automatic classification rule is used to process the data from the independent observer experiment, the simulation based estimation goes as follows. From the observed data, one has positions of initial sightings Pj = (Xj, Yj), j = 1 ..... J. The occurrence/exposure data are (Ei,Di), i= 1 ..... I, where Ei = (Xi, Yi) is the relative position of the ith exposure, and D i is 1 if the object was successfully sighted at the ith exposure, and 0 if it was missed. Writing Q(x,y Ifl) for the hazard probability of sighting at relative position (x,y) when the hazard parameter has value fl, one might use as descriptive log likelihood I

L(fl) -" ~_~ [O i log(Q( X i , Y/lfl) + (1- D i ) log(1- Q(X i , Y/]fl))] i=1

+ ~ [log(Q(Xj, Yj Ifl))- a--v~~ Q(x / y j) dz]- 7 log(w) j=l

(8)

The first likelihood component is the binomial likelihood of the occurrence/exposure data. The second component is obtained by the Poisson approximation, eq. (3), as explained in Ref. [6]. This last component is due to the positions of initial sightings, and is preferable to the likelihood component L1(fl), which was used in Ref. [4]. The maximum simulated likelihood approach is to estimate the independent observer experiment and the survey for a number of values b for the hazard probability parameter ft. In the formulation of the log likelihood eq. (8), the coordinates are taken to be measured and are not true coordinates. The simulation is therefore done by adding a randomly drawn measurement error to the simulated surfacing position before the pseudo random experiment is carried out to see whether the surfacing leads to a successful sighting. This is elaborated in the next section. Each simulation yields data of the same format as the observed data. After having classified the simulated independent observer data into occurrences and exposures by the chosen rule, the maximum likelihood estimator fl(b) is calculated by maximizing eq. (8), but with simulated data in place of observed data. When this has been done for sufficiently many values, b, in the parameter region of high likelihood, a quadratic surface in b is fitted to the responses L(fl(b)) by generalized linear regression. Generalized linear regression [10] is used since log likelihood is known to be F-distributed and not normally distributed. Finally, the fitted log likelihood is maximized, and the maximizing value of b is taken as the maximum simulated likelihood estimate ft. The covariance matrix of this estimate is calculated from the curvature of the fitted log likelihood in the usual way. More complicated models than that indicated above, or that used in Ref. [4], are probably needed to satisfy the Scientific Committee of the 1WC. In models based on observed dive-time data, measurement errors in the observed relative positions, automated occurrence/exposure identification from independent observer experimental data, and errors in cue track identification, simulation based estimation seems indispensable.

22 Measurement

errors

Errors in radial sighting distance and angle measurements were identified as a potential source of bias in the Norwegian independent observer experiments (see [11]). An experiment [3] revealed that substantial variability was present in these measurements, and also some bias. The structure of these measurement errors is summarized as follows [3,4] (where typos occur in the formula for errors in the angles): Let A be the measured angle, and a the true angle between the sighting line and the track line, and let R and r be the measured and true radial distance from the observer to the whale, respectively. Then, given a and r, R = 0.815r + 0.301(0.05 - 0.05 e x p ( - r / 0.05)) + 0.117(r + 0.01) TMZ 1 and A = s i g n ( a ) ( 1 . 1 4 4 7 x ~ - 0.1892 + 0.761Z 2 + 3 ( 1 - I)Z 3 )2 where Zl, Z 2 and Z3 are independent standard normal variates, independent of the mixing indicator, I, Pr (I = 1) = 1 - Pr(l = 0) = 0.98. The hazard probability (eq. (7)) in Ref. [4] was estimated on occurrence/exposure data and positional data for initial sightings. These data are given in observed coordinates. In the simulation, one keeps to observed coordinates as follows. Each time a hitherto unobserved whale is simulated to surface at visible range, a positional error vector, e, is drawn from the above error distribution and added to the true relative position vector, p. The relative position in measured coordinates is then P = p + e. The Bernoulli experiment to determine whether this surfacing is sighted has success probability Q(P). It is also possible to work with true coordinates instead of observed ones. Then, the success probability in the simulation is Q(p), and measurement errors are added to positions where sightings are made, but after the sighting. If the measurement errors are added after the sighting, the hazard probability parameter, fl, relates to the true position of the surfacing. When estimating this parameter by way of simulation, the log likelihood (eq. (8)) for simulated data must be computed in measured coordinates, exactly in the same way as when the hazard parameter relates to measured coordinates. The estimate of fl will depend on whether it relates to true or measured coordinates. The resulting estimate of the effective search width should, however, not differ substantially between the two approaches - provided one keeps consistently to either measured or true coordinates in the analysis consisting both of parameter estimation and calculation of effective search width. When the hazard model has been fitted in true coordinates, a direct estimate of g(0) is available through eq. (3) or by simulating the sighting process for whales located on the track line. If, however, the hazard probability parameter relates to measured coordinates, only the count estimate (eq. (5)) makes sense.

23 Figure 1 shows the distribution of perpendicular distances from the track line of initial sightings during the 1989 survey. The dotted line is the distance model (eq. (6)) fitted to data with y < 0.5 nm, and the other curve is the exponential density f(y) = a e x p ( - a y ) fitted to y < 0.3 nm. Figure 2 shows the same for the simulated perpendicular distances in the fitted model including measurement errors. This model was fitted by maximum simulated likelihood, as described in Ref. [4]. The shape of the simulated distribution is somewhat different from the observed one close to 0. The exponential distribution fits actually slightly better than the distance model (eq. (6)). The numbers inserted on the graphs are estimates off(0) for the two models. In Ref. [4] we used the model (eq. (6)) when calculating the count estimate of g(0). The discrepancy in distributional shape near 0 was not noticed in Ref. [4]. It is probably due to imperfections in the measurement error model, which was estimated separately. This lack of fit illustrates the importance of combining all elements of the analysis in one model, in order to ensure consistency in the analysis. The above difficulty also illustrates the sensitivity of the abundance estimate on the model chosen for the perpendicular distance distribution. Since estimation of a probability density at the extreme end of the range is notoriously difficult, it should be avoided if possible. When the hazard model has been fitted, the count estimate (eq. (4)) of the effective search width is available, and there is in fact no need for any estimation off(0). In the 1995 survey, it is planned to have two barrels on each vessel, to allow independent observations to be made concurrently with the survey for each vessel and

Observed

1989

CO

r~

-4.88 4.55

'I\L~ .....13

i.

iiii 0'.0 Fig. 1.

[Inn

i

012

014 016 Perpendicular distance

n nn

018

n

1'.0

24

Simulated

i

4.91

--...

r]m•

O

olo

012

014

016

Perpendicular distance

m r v . v . - ~ FI

o'.8

,-1

1'.o

Fig. 2.

each stratum. It will then be possible to estimate the hazard probability function for each stratum. Thus, the effective search width can be estimated by counting the sightings in simulation models for each stratum. This will allow the abundance estimates to be less hampered with bias introduced by choosing the wrong distance model, and it will allow the variability of the abundance estimates to be less - and more easily understood. More systematic measurement error experiments are also needed, both for the purpose of training the observers, and for obtaining a better model for measurement errors.

Conclusion The standard assumptions in line transect analysis are not always satisfied. When surveying minke whales by ship in the northeastern Atlantic, it is clear that the probability is less than 1 of observing an object on the track line, and positions are measured with error. To tackle these difficulties, models formulated in terms of the hazard probability of sighting have been useful for this type of discrete line transect experiments. To estimate the parameters of these models, methods based on systematic simulation have been developed. Independent observer experiments and experiments for gathering data on the errors in positional data provide an empirical basis for the abundance estimate. To calculate this estimate, the effective search width should be estimated directly through the hazard probability model, and not

25

indirectly through g(0) and f(0). To remove subjectivity, an automated rule to identify exposures and occurrences is needed, and this rule should be applied to both the observed data from the independent observer experiment, and to simulated data in the course of the estimation. Statistical uncertainty in the estimate of effective search width can be studied by a parametric bootstrap approach, as in Ref. [4]. The methodology developed for discrete line transect experiments is essentially applicable also for the more usual continuous time experiments. Here, the concept of hazard rate replaces the hazard probability of sighting [1,13]. To estimate the hazard rate from independent observer experiments, one will need models of censored survival times: the time one observer is aware of an object until the other observer sights the object. In the continuous case, the detection curve is exactly determined by eq. (3).

References 1. Buckland ST, Anderson DR, Burnham KP, Laake JL. Distance Sampling: Estimating Abundance of Biological Populations. London: Chapman and Hall, 1993. 2. Hiby AR, Hammond PS. Survey techniques for estimating current abundance of cetateans. Rep Int Whal Commn 1989;(Special Issue 11):47-80. 3. ~ien N, Schweder T. Estimates of bias and variability in visual distance measurements made by observers during shipboard surveys of northeastern Atlantic minke whales. Rep Int Whal Commn 1992;42:407-412. 4. Schweder T, Oien N, HCst G. Estimates of abundance of northeastern Atlantic minke whales in 1989. Rep Int Whal Commn 1993;43:323-331. 5. Schweder T, Oien N, H~st G. Estimates of g(0) for the northeastern Atlantic minke whales based on independent observer experiments in 1989 and 1990, found by the hazard probability approach. Rep Int Whal Commn 1992;42:399-405. 6. Cooke, J. A re-analysis of experimental data to estimate G(0) for shipboard surveys of minke whales in the North Atlantic. Paper SC/46/NA8 presented to the Scientific Committee of the International Whaling Commission, 1994 (unpublished). 7. Schweder T, HCst G. Integrating experimental data and survey data to estimate g(0): a first approach. Rep Int Whal Commn 1992;42:557-582. 8. Folkow LP, Blix AS. Daily changes in surfacing rates of minke whales (Balaneoptera acutostrata) in Norwegian waters. Rep Int Whal Commn 1993;43:311-314. 9. Schweder T. Maximum simulated likelihood, 1994 (unpublished). 10. McCullagh P, Nelder JA. Generalized Linear Models. London: Chapman and Hall, 1983. 11. International Whaling Commission. Report of the Scientific Committee, Annex L. Report of the ad-hoc working group on g(0). Rep Int Whal Commn 1992;42:252-258. 12. Oien N. Abundance of the northeastern Atlantic stock of minke whales based on shipboard surveys conducted in July 1989. Rep Int Whal Commn 1991;41:499-511. 13. Schweder T. Transformations of point processes: applications to animal sighting and catch problems, with special emphasis on whales. Dissertation, University of California, Berkeley, CA, USA, 1974 (unpublished).

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9 1995 ElsevierScience B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand D. Ulltang,editors

27

Point clustering of minke whales in the northeastern Atlantic G r o H a g e n 1 and T o r e S c h w e d e r 2 1Norwegian Computing Center, Blindern, Oslo, Norway; and 2University of Oslo, Blindern, Oslo, Norway A b s t r a c t . A statistical model for spatial whale distribution in the Northeastern Atlantic is presented.

The model, a Neyman-Scott cluster process, is fitted separately for 12 strata, based on data from the Norwegian shipborn survey in 1989. The spatial distribution differs considerably between areas, with respect to both cluster size, intensity of clusters and density of whales within clusters. It seems obvious that information about the clustering is relevant when planning new surveys, and when analyzing survey data. K e y w o r d s : survey data, spatial distribution, cluster process

Introduction

The spatial distribution of minke whales is of interest for various reasons. The degree of clustering is of independent biological interest, with respect to both behaviour and feeding. The variability in the line transect surveys will depend on the degree of clustering, and the interpretation of survey data will be facilitated if a spatial point process model has been fitted. We will use transect data from the Norwegian shipborne survey in 1989 [6] to fit a Neyman-Scott cluster process, separately for each stratum. The estimation is done by fitting the theoretical K-function [ 1] to its empirical counterpart by numerical optimization. The K-function summarizes the interpoint distances in the point process.

Statistical model for whale distribution

The point process model for spatial whale distribution in the Northeastern Atlantic is a Neyman-Scott cluster model. When defining such a model, we need to specify a statistical model that covers both the cluster units and the individual whales belonging to each cluster. Separate models are fitted to each of the survey blocks used in Dien [6]. The model, and simulation, is based on: a. Cluster units: the clusters form a stationary Poisson process with intensity 2 per unit area. This means that the number of clusters in a region A, with area v(A) is Poisson distributed with parameter (and expected value) m = 2 . v(A). The clusters' positions inside the region, represented by the positions of cluster centers, are randomly distributed over the total region according to a uniform probability distribution. Address for correspondence: G. Hagen, Norwegian Computing Center, Box 114, Blindern, N-0314 Oslo, Norway.

28 b~

Individual whales belonging to a cluster: the individual whales of a given cluster is a Poisson process, but with intensity decreasing as the distance from the cluster center increases. The Poisson intensity of whales in a cluster is

/texp -

X2

+y2]

2p z

(1)

where x is the distance from the center in the x-direction and y is the distance in the y-direction. The intensity model (1) specifies that the number of points in a cluster is Poisson distributed with parameter M =/t2arp 2

(2)

The points are independently scattered around the cluster center, according to the spherical bivariate normal distribution with variance in both x- and ydirection p2. The parameter p might be interpreted as the radius of the cluster, and the parameter/~ is the whale intensity in the center. If p is small relative to the size of the area, the method of simulation indicated above works well. If, however, p is large, edge effects come into play. Poisson cluster processes are described in Diggle [1 ] and Ripley [3]. The process consists of parent events (cluster centers), and to each parent there are a number of offspring (individual whales) with relative positions independently and identically distributed according to a probability distribution (bivariate normal).The intensity of parent events is 2, and the number of offspring for each parent is a Poisson variable with parameter M, given in eq. (2). To summarize the interpoint distances in a Poisson cluster process, one introduces the so-called K-function, defined by yK(t) = expected number of further points within distance t from an arbitrary point in the process where y is the overall intensity of points, y = 2M = 2/t2~p 2

(3)

In the present model, "points" are the individual whales, and yK(t) thus is defined as the expected number of further whales within an interpoint distance not exceeding t from a randomly chosen whale. From the theory in Diggle [1] we find that in the present model, K(t) = art 2

4-

"~- 1 -- exp - 4P 2

and so the kt-parameter disappears.

(4)

29 Estimation To estimate the model parameters we will use the K-function, and we therefore need an empirical point estimate for K(t) based on observed data. The estimator R ( t ) is described in Diggle [1] and Ripley [3], and we only include a short summary. The function ~,K(t) is the expected number of points (whales) within a distance t from a randomly chosen point (whale). For a general region A with area v(A), the expected number of points is w(A). The expected number of ordered pairs of points, with the first point being inside A thus become Np (t) = ~ v ( A ) . ~,K(t) = ~ , 2 v ( A ) K ( t )

(5)

The method for estimating K(t) is to estimate Np(t), and then to combine eq. (5) with the common estimator for overall intensity p = n/v(A), to obtain an estimator for the K-function: K ( t ) = v ( A ) IVp (t) n 2

where n is the total number of points observed inside the region A. Let P~ ..... Pz be the process points inside the region A, and let u U be the distance between Pi and Pj. Following Ripley [3], we estimate Np as a weighted sum of ordered pairs, with weights being the inverse of the probability that a point at distance u U from the point Pi will be observed (i.e. is inside the region A). When the process is stationary and isotropic, as is the case in our model, this probability is the proportion of the circumference with radius u U and center at Pi that lies inside the observed region A. Our observed points are from line transects through relatively large areas. It seems realistic to define the observed region (region A in the text above) to be a small strip of width b around the transect line. The total observed area in a block (stratum) is v(A) = hTb

where h = intended vessel speed during transect, T = transect duration inside the actual block and b is the effective search width on the transect. In 1989 the intended vessel speed was h = 10 knots, and the effective search width has been estimated to be approximately 0.18 nautical miles [4]. When estimating the model parameters, we therefore use these values in all formulas. In several of the blocks, the data consist of observations from more than one continuous transect. We have chosen to regard these as independent observation series from the same model. They are therefore linked together in one continuous transect, covering the actual block. The only relevant parameters are block identification and relative time of observation. From these we can compute a theoretical position of each observation, and perform the estimation. For one specific block, let the relative points of time for whale observations be 0 < rl < ra < "'" < rn < T. Relative forward

30 positions in the observed strip will then be 0 < hrl < hr2 < "'" < hrn < hT, and these can also be regarded as the observed absolute positions along the transect strip. The reason for this is that the effective search width is very small compared to the forward distances between observations. The K-function and its estimator R(t) thus become

K(t) = K(hr)= zc(hr) 2 + ~ 1-

exp/h,242// (6)

n2

i=1

E['gi-'gJ j~i

(uij

where It(u) = 1 if u < t, and zero else. To stabilize the variance, Ripley [3] suggests using L(t)= ~l(K(t)/z~) when estimation is done by least squares. For a given survey block, the estimates of 2 and p are those values which minimize the squared error:

Z (L(t) -/~(t)) 2 t
z + W(2lt2gp2hTb- n) 2

(7)

t
31

Table 1. Blockwise parameter estimates based on observations from the Norwegian survey in 1989, see Oien [6] for block identification Block

~t

VSN VSS SV BJ BA GA KO FI LO NO SN NS Median value

jb

3.131 5.951 0.292 1.630 9.765 2.351 6.446 1.363 1.642 2.024 0.932 0.762 1.833

~.

1.230 1.244 133.979 2.161 5.815 2.617 5.720 1.886 2.156 2.861 2.667 16.684 2.642

8.896 6.539 5.074 2.569 1.181 9.951 6.601 5.327 4.425 6.966 2.479 1.049 1.737

x x x x x x x x x x x x x

10 -3 10-3 10 -6 10-3 10 -4 10-4 10-4 10- 3 10-3 10 --4 10 -3 10-4 10-3

Discussion

The model parameters (U, P, 2) were estimated by numerical minimization of eq. (7), separately for each of the 12 blocks. The parameter estimates are presented in Table 1, and from this table we observe that the parameter estimates differ a lot. Figure 1 shows that the L-functions are well fitted to the empirical estimates, and it also illustrates the dilemma when deciding the actual window size At. In the upper tail of

Estimated and fitted L-functi0n o

.j

0

.-I

0.0

0.2

0.4 0.6 time (hours)

0.8

1.0

O v.-

0.0

0.2

0.4 0.6 time (hours)

0.8

1.0

Fig. 1. Empirical L-function (dots) and fitted L-function (smooth curve), from the blocks VSS (west of Spitsbergen, south) and KO (Kola).

32 VSS-estimated model, simulated (no

{Do

E

.~..

o .l=.,

.,.

~-':

~t--00 o ......

...,,-

/~~

,;:~.,~

..r

.~...... .

:~".

~ .~.

@..-.

.r

-.~-

,~;:

:!~,,,

~ ~r .~.

-

~'

-~

",":

...~...:

~:~..

%'r.:

~176

r~.~.. 9 .

"- ~~ . .,

.,~.'..,

"(~,"

...... ".~.'o 9

0

20

40

6'0

80

100

nautical miles

KO-estimated model, simulated ~ 0 ~ 0

E

. . ;;~' :'":'".

- " ":9." ~L~ f~ f' ~" ' ~, ":i ' ~ " ;'. ;" _:,-'7. :, " .

. " :,~:

.o_ ,r

9

~

"~

":

"~.,~..':(,'::'.....~.:.rff,,,,~

.~, .....

9

~0 r-"00

9

.. . . . . .

.

.

.

.

.

9

9

.......;.,.-,.,. ~r 9

.

..

....

.. ,,:~.o.,~ ~ ; 7 : - . ":..~.-.~:,~ -..., . . . . .

9 .

.

" ~ ...... ." ".~.~,~"..';

"

.

~-

::~..

,

. ....

..

.

......,~.,-..,,.o~...o~.... , . , .-.. . . . . . ...

~ '~-,-:.~~:,.- .-

,...~%-..,

..-,

' : .~,~=.': ~~4.~~::;,..'.:-... 9 9

0 {.o

..

: . "...'.:.?:~r

. . . . 2"..:-.~.'...."

~~ ::='.~;.Z

0 ',:3"

:~,: .--.

9 %.. . . . s .~ 9 .','.. ""

"" ...

9

:.'

.....: :..,.,.:...: 9

"

"

"'..

.

..

"

9 :...,-.,,..:

~.~,'-,',.'0 ,'r . ",-.: :.-,:.~~' .... "!i.i,:, . ". 9

,-.,...-...'~9*':'-T~": -;.,,,: 9

0 o,,I

"

9

"~'" "i.

:';"'~i,'._" 9

0

,".

20

40

60

.

80 100 nautical miles

2 . Two regions of 10,000 square nautical miles simulated according to the estimated model from block VSS (west of Spitsbergen, south) and KO (Kola), respectively. Fig.

33 the left figure there is a substantial increase in the empirical values, which is not reflected in the fitted function. This sudden increase can be interpreted as an inclusion of points from different clusters in the sum defining the empirical Lfunction, and is therefore of minor interest when investigating the individual clusters. The different sets of parameter estimates give rise to varying spatial whale distributions. The model estimated for block VSS (west of Spitsbergen, south) is an example of a model with many small clusters of high whale intensity, while the KOmodel (Kola block) is an example of a model with relatively few and large clusters in terms of radius, and of high whale intensity. Block SV (Svalbard area, southwest of the Spitsbergen blocks) has parameter estimates very different from the other blocks. The fitted model for this block has very few clusters of enormous radius but with very small whale density. When the models are to be interpreted, one must have in mind that the estimated whale distribution is a theoretical model for regions of unlimited area. The actual blocks then must be regarded as a smaller region, randomly placed in the infinite area of the theoretical model. However, the result is clearly that the whale distribution in the Northeastern Atlantic can be modelled as a Neyman-Scott process, with substantial clustering. Information on degree of clustering within the various survey blocks will be of help when designing future surveys. It is important to optimize the design in order to obtain abundance estimates of minimal variance, given total costs. Since variability depends on the degree of clustering, such information is helpful. From data gathered in a new survey, the Neyman-Scott model should be estimated for the individual survey blocks. These fitted models will be useful when the survey process is to be simulated, in order to estimate hazard probability parameters and effective search width [5].

References 1. 2. 3. 4.

Diggle PJ. Statistical Analysis of Spatial Point Patterns. London: Academic Press, 1983. Neyman J, Scott EL. A theory of spatial distribution of galaxies. Astrophys J 1952;116:144-163. Ripley BD. Spatial Statistics. New York: Wiley, 1981. Schweder T, Oien N, Hr G. Estimates of abundance of northeastern Atlantic minke whales in 1989. Rep Int Whal Commn 1993;43:323-331. 5. Schweder T, Hagen G. Effective search width in shipborne surveys of minke whales in the northeastern Atlantic: concepts and methods. Contribution to the International Symposium on the Biology of Marine Mammals in the Northeast Atlantic, Tromsr 1994. 6. Oien N. Abundance of the northeastern Atlantic stock of minke whales based on shipboard surveys conducted in July 1989. Rep Int Whal Commn 1991;41:499-511.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand t3. Ulltang, editors

35

Use of mark-recapture experiments to monitor seal populations subject to catching Nils Oien and Torger Oritsland Institute of Marine Research, Nordnes, Bergen, Norway Abstract. During the period 1977-1994 about 17,000 harp seal pups have been tagged in the Greenland Sea and about 18,000 in the White Sea. The numbers of recoveries since 1977 have been approximately 870 and 50, respectively, from the two tagging operations. The recaptures indicate that Greenland Sea harp seals share common feeding grounds with both Northwest Atlantic and White Sea harp seals, albeit not breeding grounds. Recaptures made 1 year or more after tagging during the commercial catch operations in the Greenland Sea have been used to estimate pup production for several years during the period 1977-1991. It is evident from the analyses that the assumptions of mark-recaptUre estimates are violated, probably most seriously so by violations of the randomness assumption and non-uniform distribution of tagged animals. A mechanism of non-permanent emigration is suggested to explain the source of the bias, but no data are available to correct it although a truncation of recapture data assuming that temporary emigrated seals have returned to the population upon reaching sexual maturity might prove useful. Although mark-recapture experiments as a tool to estimate pup production certainly involve many problems which need to be accounted for, they should at least be considered as valuable supplements to other direct methods such as aerial surveys. In the case of ice-breeding seals in the Greenland Sea, the logistics and operational constraints on aerial surveys might even leave markrecaptures experiments the only feasible alternative at present. Key words: harp seals, mark-recapture, distribution, pup production, Greenland Sea, White Sea

Background Mark-recapture experiments might be useful in studying several aspects of the monitoring of seal populations subject to catching. When such experiments were introduced into the studies of ice-breeding seals in the North Atlantic long ago, the main purpose was to gain knowledge on migrations and distributions to resolve questions on population structure and stock identity. Norwegian taggings of harp (Phoca groenlandica) and hooded (Cystophora cristata) seals in the North Atlantic performed during the years 1951-1963 have been summarized by Rasmussen and Oritsland [ 1]. Moreover, known-age teeth from recaptured animals have been used to establish age reading procedures, for example the relationship between growth layer groups in dentine and absolute age in harp seals [2]. More recently, mark-recapture experiments have also been used for estimating pup production (e.g. [3]). Harp seals in the northern North Atlantic are separated into three populations based on the location of their breeding sites, namely the Northwest Atlantic, the Greenland Sea (traditionally known as the West Ice) and the White Sea (East Ice) populations. Pup production of the Northwest Atlantic population has successfully Address for correspondence: N. Oien, Institute of Marine Research, P.O. Box 1870 Nordnes, N-5024 Bergen, Norway.

36 been estimated from aerial surveys [4]. In the White Sea, regular surveys have been conducted over a long period of years to estimate the number of females in the breeding lairs there. In recent years, aerial surveys have also been conducted to estimate pup production of harp and hooded seals in the Greenland Sea [5] but with limited success due to the very difficult logistics associated with operations in that remote area as well as unfavourable weather and ice conditions in past years. A survey estimate of harp seal pup production in 1991 has been presented [6], but the status for the West Ice hooded seal population is still unknown. As part of the studies of harp and hooded seals in the northeast Atlantic extensive efforts have been made through the years to tag pups in the breeding lairs in the Greenland Sea, and since 1987 also as a collaborative effort with Russian scientists in the White Sea. Relatively little information has been returned from the hooded seal taggings, but for harp seals the marking programme has been most informative. This has motivated the use of the mark-recapture data from the Greenland Sea to try to estimate harp seal pup production in that area. In this paper we present a summary of earlier presentations [6-8] on the markrecapture experiments conducted on harp seals in the northeastern Atlantic, in some cases including updated information.

Tagging of harp seals in the Greenland and White Seas Since the late 1970s, Norwegian tagging efforts have concentrated on the breeding lairs in the Greenland Sea area and then mainly on harp seals. In the Greenland Sea, tagging has been conducted in breeding patches which are usually found within an area broadly delimited by the latitudes 70~ and 75~ and longitudes 20~ and 0~ Through most years, tagging has been carried out on an opportunistic basis as part of the research activities on board commercial vessels during their catch operations. This has restricted the possibilities of distributing tagging effort throughout the breeding season and area. During the years 1983-1988, governmental subsidies, partly allocated to facilitate research, made it easier to tag a larger number of pups. During the years 1989-1991, tagging was carried out from research vessels as part of the Sea Mammal Research Programme, mainly by using helicopters to distribute marking effort. In the White Sea a cooperative project with Russia on tagging harp seals started in 1987, and especially since 1989 a considerable number of pups have been tagged annually. The number of harp seal pups tagged in the Greenland Sea and the White Sea over the period 1977-1994 is shown in Fig. 1. The total numbers tagged within this period are about 17,000 and 18,000 for the two areas, respectively. However, while the last large tagging operation in the Greenland Sea took place in 1991, tagging has continued on an annual basis in the White Sea breeding lairs. As is seen in Fig. 2, the overwhelming number of recaptures have come from the Greenland Sea taggings, despite the fact that about the same total numbers of pups

37

45OO

I

4OOO

West Ice

r--1 East Ice

lo 350O O}

oo~, 3000 D. :3

2500

~20[~ i 15oo 1000 500

,,,, ,, , ,I,I i r-. r..

co ,-.. O,

o,-..

o co

O,

,co

O,

e~ co

O,

O,

co co ~

~ co

(~.

to co

,o co

C~,

O,

,I..,.,II,I .. v... co O-

co co ~

o, co O,

Year

o

,

,

,

8:

Fig. 1. Numbers of harp seal pups tagged in the Greenland Sea area (the West Ice) and in the White Sea (the East Ice) over the period 1977-1994.

have been tagged. Until now, a total of 870 recoveries has been obtained from the Greenland Sea taggings after 1977, and approximately 50 from the White Sea taggings. As a specific example, in 1991 approximately 3300 and 4200 pups were tagged in the Greenland and White Seas, respectively, but during the next catching season in 1992, 71 recaptures were made in the West Ice and only one in the East Ice. The difference is therefore only partly related to the fact that the West Ice tags have been available for recapture over a longer period; the most important factor is the very different age structure in catches of moulting harps from the two areas. While there is typically about 50% immatures in the moulting catches in the West Ice, this percentage is much lower in the East Ice.

180

.IdO '~ 140 :3

m West Ice East Ice

~. 120 0 U

I00

0

8O

.n c 13 =i... 0

60

6

,-

40 20 0

CO

C~

~-"

CO

~

CO

u') co

O,

,0

co

O-

co

co

~1"

(3-

Year

Fig. 2. Accumulated numbers since 1977 of recaptured harp seals by cohort tagged in the West Ice and in the East Ice.

38

Distribution patterns Most of the recoveries have been made during catch operations in moulting patches in the West and East Ices. The recoveries from outside these areas predominantly comprise very young seals (0 and 1 age groups). Although young animals are inexperienced and may be more prone to getting caught in fishing gear, they may also have other migration patterns and feeding ground preferences than the older harp seals. In particular, several seals have been recaptured off the northern coasts of Iceland 1-2 months after tagging in the Greenland Sea. As discussed by Rasmussen and Oritsland [1], this probably reflects a passive drift of pups with prevailing currents. Further evidence for distribution dependence on prevailing weather conditions during the pupping season is found in the recoveries from the 1984 cohort tagging in the Greenland Sea (Fig. 3). There have been five recaptures north of 65~ at West Greenland. One was tagged in 1985, the others were tagged in 1984, and all recaptured from 6 months to 3 years and 9 months after tagging. Moreover, a harp seal from the 1984 tagging was recaptured in 1990 at Newfoundland. Bad weather conditions with heavy storms from the northeast were reported during the pupping season in 1984, and five tagged pups were caught in fishing gear north of Iceland during May and early June that year. However, recoveries of 1 year or even older seals might indicate that they also actively migrate to areas not commonly thought to be part of their normal distributional range, and that they might stay in these areas for a while.

6000 80oo

4500 ,

3000 . ,

.

15oo ,,..., t .

00oo .. '

.

15oo 3000 .,.,,), . . . . z

4500 '

700o

6000 . .

80oo

70oo

o

6000

6000

5000

lrJ ~ 6000

....

i

4 500

'l 3000

......

I 1 500

5000 00oo

1 500

3000

4 5oo

6000

Fig. 3. Recapture sites of harp seals tagged as pups in the West Ice area in 1984 and recaptured outside the tagging area.

39

6000 8000 ......

4500

t

,,

3000 n

1 500 i ,

00oo i

1 500 ,,

3000 i

9

Q

}

4500

t

.,

6000

8000

~

O 7000

70oo

6000

6000

50oo~ 600o

I

45oo

I

3000

'

I

15oo

j.,...~_r" I 00oo

I

15oo

I

30oo

I

45oo

'500o I

6000

Fig. 4. Recapture sites of harp seals tagged as pups in the White Sea in the period 1987-1994. Recaptures outside the tagging area only.

Recoveries from outside the East Ice of harp seals tagged in the White Sea have above all been made along the Norwegian coastline, but also at East Greenland (Fig. 4). Most of these seals have been in their first year at the date of recapture. Several recaptures are worthy of further comment. In 1994 two harp seals tagged in the White Sea, one in 1990 and one in 1991, were caught in a moulting patch in the West Ice northwest of Jan Mayen. In 1993, a 2-year-old was caught late in the season southwest of Spitsbergen. Three young harps were also caught at East/Southern Greenland during the autumn of 1992. In Fig. 5 are shown recoveries of harp seals tagged in the Greenland Sea but recovered outside the breeding and moulting patches there. Most of the recoveries are located within a band from the Ammasalik area at East Greenland, passing through the coastal areas of Iceland, especially the northern coastline, and ending off the coast of northern Norway. Thus this might be considered a southern limit of their distribution although it might well be that also the southern part of East Greenland, extending into the Nanortalik area west of Cape Farewell, should be considered part of the normal range. The areas at East Greenland (generally the Denmark Strait) are apparently important feeding grounds both for harp seals breeding in the West Ice and at Newfoundland, and as mentioned above, even stragglers from the East Ice occur. Many recaptures, most of them young immature seals, have been reported from the Nanortalik and Ammasalik districts of seals tagged at the Front, Gulf and Davis Strait breeding patches. Similarly, frequent recaptures of young seals along the

40 6000 8000 t

45oo

30oo

,

,

1 5o0 ,., = ~,

00oo !

1 50o

30oo I

45oo !

60oo

8000

70oo

60oo-

EI

q~

- 6000

, i

50oo~ 6000

, 4 500

'

, 30oo

, ~ 1 500

i 00oo

, 1 500

i 30oo

, 4 500

5000 6000

Fig. 5. Recapture sites of harp seals tagged as pups in the West Ice area in the period 1977-199]. Rec a p t u r e s o u t s i d e the t a g g i n g a r e a only.

Norwegian coast, tagged in the Greenland Sea as well as in the White Sea, indicate that those two breeding units share common feeding grounds off northern Norway. The management implications are, however, unclear but do not seem to call for changes in current practice. There is no hard evidence from the mark-recapture experiments that the three North Atlantic harp seal populations (Northwest Atlantic, Greenland Sea and White Sea) intermingle at the breeding grounds, as we do not have recaptures of breeding animals. But there are records from the moulting season indicating that intermixing is probable: (1) in late May 1990 a seal tagged in the West Ice in 1984 was shot 40 miles southeast of Gray Islands, Newfoundland; (2) a seal tagged in the West Ice in 1977 was recaptured in late April in 1983 in the White Sea, presumably during moulting; (3) three harps tagged in the Greenland Sea, one in each of the years 1989-1991, were caught in 1992 during moulting in the East Ice; (4) the two harp seals tagged in the White Sea and recaptured in the West Ice (mentioned above). In addition, Rasmussen and Oritsland [ 1] report on a seal tagged in the West Ice in 1952 and recaptured in the White Sea in late April 1953. That there is little positive evidence of breeding mixing does not mean that exchanges do not occur at all, and we also know that very small migration rates are sufficient to erase genetic differences between populations. So far, studies of genetic variation of enzymes have not been able to reveal differences between West Ice and East Ice animals [9], while a study of underwater vocalizations of harp seals [10] concluded that harps of the northwest Atlantic population breeding in the Gulf of St. Lawrence were reproductively isolated from harps breeding in the Greenland Sea.

41 The large seal invasions in 1986-1988 were correlated with an increase in reported recaptures off the Norwegian coastline. All the 13 recaptures of current interest were of seals tagged in 1985 and 1987 (no seals were tagged in 1986). Of these, 11 were recaptured in winter (one in December, four each in January and February and two in March) and two in May. A rough calculation indicates that these recaptures would mean that West Ice harp seals would account for at most a few percent of the total catches of some 100,000 animals caught in fishing gear on the Norwegian coast. It is, however, difficult to be too specific about numbers of recaptures as indicators of availability of harp seals in different areas. Along the Norwegian coast, for example, some fishing effort is distributed throughout the year, but there are peaks in effort corresponding to spawning migrations of cod, saithe and haddock. These species seem to spawn from winter to early summer, with the most intense periods being from mid-March to May [ 11 ].

Pup production estimates By considering each marked cohort over the years as a separate entity from which catches and recaptures are removed, an estimate of the original pup production can be made based on a Petersen mark-recapture estimator. In addition to a series of assumptions underlying such an estimator [12], this approach also requires that the age distributions in the moulting catches are known, which introduces the question of whether the age samples are representative and whether errors associated with age determinations are negligible. Over the period relevant to the pup production estimates (i.e. from 1978 onwards), age samples have usually been collected annually onboard one or two commercially operating vessels. The absolute sample sizes have varied as have the catches, but usually the age samples have comprised 25% to

1613[]03 140000 0

o

1[x3[x30

o

8OOOO

:3 "13 c~

a. 6[XX~

a=

I I

F

4 ~ 20000 r'-.. r',.. (3".

I

co r~. O-

I

oo co O-

I

~ co O-

I

u~ co O,

I

l'.,. ao (3'.

I

ao ao (3-

I

Oao O-

I

(~

I

,.-

8:

Cohort

Fig. 6. Pup production estimates by year based on accumulated data up to and including 1993. The bars illustrate the 95 % confidence regions around the point estimates.

42 more than 90% of the Norwegian catches of 1-year-old and older seals. Evaluations of age determinations [13] based on dental annuli indicate that they might be subject to both measurement and systematic errors. Such errors have not been accounted for in the estimates presented here, but it is certain that measurement errors would add to the uncertainty in the pup production estimates, while it is not at all clear in which direction estimates would be biased if there are systematic errors of the kind mentioned above. Pup production estimates for harp seals in the Greenland Sea from recoveries accumulated over the years since tagging are summarized in Fig. 6 together with their associated 95% confidence intervals. The coefficients of variation for the estimates are typically less than 0.15 (range 0.10--0.27 [8]). Although the estimates span a wide range, they can hardly be told apart by their 95% confidence intervals with the possible exception of the highest estimates. A striking feature of these pup production estimates is that they seem to fall into two broad categories; one with estimates around 40,000-55,000 (seven cohort estimates) and one with estimates two to three times that, i.e. 100,000-115,000 (three cohort estimates). In Fig. 7, the cohort estimates have been plotted as a function of number of years with accumulated data. An apparent feature of the point estimates is that they tend to either increase or decrease for a specific cohort as years pass, while the ratio of marked to unmarked animals within a cohort should be constant if the underlying assumptions hold. There is reason to believe that the underlying assumptions of mark-recapture estimates are all undoubtedly violated to some extent. However, some of the assumptions, like those on population closure and that marking does not affect catchability, do not seem to influence the estimates. It might be suggested that tag loss could explain why we observe an increasing trend in most of the cohort estimates as data accumulate over the years. Unfortunately, double tagging experiments have not been carried out routinely to check the

--"--

250000

o

r-

._o 2[][][][]O 0 ::3 "13

o

15OOOO

\

--*--

O.

u9 l [ ] [ ] [ x ~ d'

E

..,,.,.,---"

I ,--

0,,I

I ~

I ~

a

~

D-'---o---o

o

I

I

I

I

I

I

I

I

I

I

i

I

t.O

',0

I'~

CO

0'.

0 ,,.-.

'-,,=-

0,I ,,=-

~ ,.-

~ i=.-

~ ,...

,,0 ,=-

Years

after lagging

1977

1978 1983

<>

1984

J'

1985

"9

1987

-"

1988

----o

1989

--x--

1990

--~:--

1991

Fig. 7. Cohort pup production estimates plotted as a function of years with accumulated data.

43 tag loss assumption. Bowen and Sergeant [3] made the conclusion from their data that loss of Rototags in harp seals occurs shortly after the tags are applied and subsequent losses are negligible, at least until the tags become worn or brittle. If the tags are lost only during the first year after application and at a probability of 0.25, all the serial estimates of, say, the 1978 cohort are positively biased, although this should not induce a trend in the series. The bias in the final 1978 estimate would then be about +20%. Bowen and Sergeant [3], who conducted a double-tagging experiment for Rototags on harp seals living under similar conditions in the Northwest Atlantic, estimated a tag loss rate of 0.051_ 0.0081 (SE) from data pooled over the first 3 months after tag application, with no evidence of increasing tag loss with time. If tag loss is to account for increasing serial trends in estimates, there has to be further tag losses as years pass. A topic closely related to tag loss is non-reporting of recoveries. During the period covered by this study, only a few vessels have participated in the catching operations. Institute personnel have often been on board these vessels, and the crew members have been well aware of the tagging programme. If not detected at an earlier stage, the tag is usually recognized when the seals are skinned. However, tags might occasionally be overlooked. During the catching season in 1989 we received reports on two occasions and in 1990 on one occasion that the remains of processed seal had been thrown overboard when it was recognized that it had a tag, however, too late to identify it. We therefore have to realize that some unknown positive bias is introduced to the estimates from such losses. Segregational behaviour and non-random mixing would be detrimental to markrecapture estimates. It is, however, unavoidable that the tagging process itself is a clustered operation thereby implying that each pup does not have the same probability of being marked. This is something which could be remedied if uniform mixing took place before recapture. Although the pooled recapture rates are similar for the different vessels operating within the same year, there are examples of clustering of recaptures, thus questioning the randomness assumption. While the discussions so far have failed to explain the observed results entirely satisfactorily, a mechanism that could possibly explain both serial trends (positive and negative) as well as large variations in estimates might be suggested. The basis for these speculations is that recoveries of harp seals tagged in the Greenland Sea have been reported from a vast area extending from Newfoundland to the Barents Sea, most of them young immature animals. Tagged animals from some of the cohorts (for example 1984) seem to have been more prone to go to other areas, depending on ice and prevailing weather conditions, as discussed earlier. For simplicity, we will assume that the pup production in any year can be divided into two components, one "normal" component and one "emigrating" component. The normal component is supposed to follow a normal migration cycle, whatever that might be, but at any rate returning to the West Ice next year for moulting. We suggest that the emigrating component at least temporarily (>1 year) leaves the normal cycle, and its members are therefore not available for the next year's moulting season. The assignment of a pup to either of these components takes place at birth, for example determined by

44 location in a breeding patch, where those at the outskirts might be more prone to be taken away by prevailing weather and ice conditions. It can then be shown [8] that: (i) the return rate of temporarily emigrated animals will determine how fast the mark-recapture estimates approach the true value over years; and (ii) the proportional distribution of tags on emigrants and non-emigrants during tagging determines whether the true estimate will be approached from below or above. This motivates the following procedures for alternative estimations of pup production: (1) given that the first year after tagging generally is the more sensitive to the assumptions of uniform mixing, estimates might be calculated by deleting data from the first year after tagging; (2) by the assumption that all emigrants will return to the population when sexually mature, estimates might be calculated by deleting data from all the 5 years following a tagging. Although with a scanty data series, such tentative estimates were presented by Oien and Oritsland [8] and indicate that the return rate is rather small the first year, but increasing with the years, giving some merit to the suggested method (2). Unfortunately, several years will pass until the cohorts arrive at the truncation point, and thereafter several years are needed to obtain reasonable sample sizes for the estimates. This procedure might of course be of limited value for management questions in the short term, but in a longer time perspective might prove to be the only way of monitoring on a regular basis such remote seal populations as the harp seals breeding in the Greenland Sea.

Acknowledgements The tagging of harp seals during the Sea Mammal Research Programme has been funded by the Norwegian Council of Fisheries Research (NFFR), project number 4001-701.304.

References 1. RasmussenB, Oritsland T. Norwegian tagging of harp and hooded seals in North Atlantic waters. Fiskeridir Skr 1964;13(7):43-55. 2. BowenWD, Sergeant DE, Oritsland T. Validation of age estimation in the harp seal, Phoca groenlandica, using dentinal annuli. Can J Fish Aquat Sci 1983;40:1430-1441. 3. Bowen WD, Sergeant DE. Mark-recapture estimates of harp seal pup (Phoca groenlandica) production in the Northwest Atlantic. Can J Fish Aquat Sci 1983;40:728-742. 4. Stenson GB, Myers RA, Hammill MO, Ni I-H, Warren WG, Kingsley MCS. Pup production of harp seals, Phoca groenlandica, in the northwest Atlantic. Can J Fish Aquat Sci 1993;50:24292439. 5. Oritsland T, Oien N. Aerial surveys of harp and hooded seal pups in the Greenland Sea pack-ice. In: Blix AS, WallOe L, Ulltang 0 (eds) Whales, Seals, Fish and Man. Amsterdam: Elsevier, 1995;77-83. 6. Oien N. Update of mark-recapture estimates of harp seal pup production in the Greenland Sea. Working paper to the Joint ICES/NAFO Working group on harp and hooded seals, WP SEA-47, Copenhagen, September, 1993.

45 7. Oien N, Oritsland T. Recaptures of harp seals (Phoca groenlandica) tagged as pups in the Greenland Sea; pup production and dispersion patterns. Working paper to the Joint ICES/NAFO Working group on harp and hooded seals, WP SEA-33, Copenhagen, October, 1991. 8. Oien N, Oritsland T. Using mark-recapture methods to estimate pup production of harp seals (Phoca groenlandica) in the Greenland Sea. ICES CM 1992/N:10- Ref.D. 9. Meisfjord J, Fyllingen I, N~evdal, G. A study of genetic variation in Northeast Atlantic harp seals (Pagophilus groenlandicus). ICES CM 1991/N:5. 10. Terhune JM. Geographical variation of harp seal underwater vocalizations. Can J Zool 1994;72:892-897. 11. Bergstad OA, Jr T, Dragesund O. Life history and ecology of the Gadoid resources of the Barents Sea. Fish Res 1987;5:119-161. 12. Seber GAF. The Estimation of Animal Abundance and Related Parameters. London: Charles Griffin, 1982. 13. Oien N. Age compositions in 1982 to 1984 samples from breeding and moulting harp seals in the West Ice, with an evaluation of the age determinations. Working paper to the ICES Working group on harp and hooded seals in the Greenland Sea, SGS WP 12, Copenhagen, October, 1987.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCe and ~. Ulltang, editors

47

E s t i m a t i o n of grey seal Halichoerus grypus p u p p r o d u c t i o n f r o m o n e or m o r e c e n s u s e s Svein-HS.kon Lorentsen and O y v i n d B a k k e Norwegian Institute for Nature Research, Tungasletta, Trondheim, Norway Halichoerus grypus~ the spread of pupping dates exceeds the length of the stay ashore of individual pups. Thus, no single census will include all pups born. To cover the whole pupping season is time consuming and expensive. We therefore developed a method, based on maximum likelihood estimation, to estimate annual pup production from one or more censuses in which the pups are classified according to age. The results of using this method on single censuses in the 1993 breeding season in the Froan Nature Reserve, Central Norway, are presented. The total pup production estimates are within 20% of the estimate based on all 8 censuses, except for those based on single censuses, which deviated more. A b s t r a c t . In the grey seal

K e y w o r d s : maximum likelihood, age group duration, stage structure

Introduction

Proper management of animal populations requires rational methods for monitoring population development. The methods used should give a confident estimate of the population size, or of the fraction that is being monitored, and should be easy to carry out, cheap, and not too time consuming. For seals the only fraction of the population that can be accurately counted is the number of pups born. Seals use the same pupping grounds annually and the number of pups born each year can be accurately counted, and compared with previous counts. However, in the grey seal Halichoerus grypus, the spread of pupping dates exceeds the length of the stay ashore of individual pups, and thus, no single census will include all pups born. To cover the whole pupping season is time consuming and expensive. We therefore developed a method for estimating annual pup production from a limited number of censuses in which the pups are classified according to age. After birth grey seal pups go through five age groups defined by external morphology [ 1]. They typically migrate to sea at 3-4 weeks old. A procedure for estimating grey seal pup production from a single census was given by Radford et al. [2] who assumed deterministic age group durations. We wanted to develop a procedure where the number of censuses may be greater than one, as the breeding season seems to be too long at Froan to obtain sensible estimates from one census. We also wanted to take into account the variation in age group durations and take advantage of today's computing power, which makes maximum likelihood estimation possible.

Address for correspondence: S.-H. Lorentsen, Norwegian Institute for Nature Research, Tungasletta 2, N-7005 Trondheim, Norway. Tel: (+47) 73 580500. Fax: (+47) 73 915433. Emaih [email protected].

48 Ward et al. [3] gave a similar estimation procedure, but without going into detail about how to utilize knowledge of age group durations or applying the estimation procedure to data.

Materials and Methods Data were collected in Froan Nature Reserve (64~ 9~ Central Norway, during the breeding seasons of 1990--1993. Froan is one of the main grey seal pupping grounds in Norway and each year about 300 females gather to give birth to their single pup [4]. The whole area used by breeding grey seals was searched approximately every 5 days. All pups encountered were identified by a Rototag mark in their hind flipper and were aged according to Kovacs and Lavigne [1]. In addition, the number of days since birth was determined for pups that were less than 3 days old. We used a procedure for estimating the total grey seal pup production during a breeding season based on one or more censuses in each of which counts of pups of each defined age group are obtained [5]. The procedure resembles the Bellow and B irley model described by Manly [6]. Estimates were obtained for the peak time for pup production, the spread of the breeding season, the observability (invisibility due to stay at sea or death), and the total number of pups produced. We needed to know the distribution and parameters for the duration of the first four age groups. Parameter estimates were obtained by a method described by Bakke and Lorentsen [5]. It is based on repeated counts of marked pups throughout the breeding season, and thus requires a great deal of field work. It seems reasonable to assume that the duration of stay in each age group varies less from season to season than the four parameters mentioned in the preceding paragraph, so that these estimates may also be used in other years. The age group duration parameters of the fifth age group are not used because it is difficult to obtain estimates for the duration of this age group since pups have migrated to sea and are not easily observable when this age group ends. However, the first observation of a pup in the fifth age group is used when estimating the parameters of the fourth age group. We have assumed that the time of birth To is normally distributed with expected value # and standard deviation or. Thus # may be thought of as the "time of peak pup production" and cr as the "spread of the breeding season". Further, we have assumed that the probability of a pup being observable t days after birth is qt, where q is a parameter that may be less than 1 because the pup is at sea or dead. The motivation for choosing this probability is that the probability of being observed t days after birth would be qt if all live pups are observed and they have a constant probability q of surviving from one day to the next, and it is also reasonable to believe that invisibility due to pups entering the sea increases as they get older. The age group durations Tj, 1 < j < 4 were assumed to be log-normally distributed with parameters as estimated in the Results using the method of Bakke and Lorentsen [5].

49 The uncertainty of the estimates may be assessed by bootstrap analysis [7]. For each census, a new census is then simulated by drawing the same number of pups as in the original census. Each pup is assigned a specific age group with probability equal to the ratio of pups in this age group to the total number of pups in the original census. Then the parameters are estimated again on the basis of this simulated data set. This procedure is repeated a number of times, so that a number of bootstrap estimates of the parameters are obtained. The sample standard deviations of those parameters are estimates of the standard deviations of the original ones.

Results

Pup production The data from the 1993 breeding season were organized into 8 census data sets (Table 1). Information on single pups obtained by marking was thus lost. Several subsets of the censuses were used to estimate pup production parameters (Table 2). When all 8 censuses were used to obtain estimates, a total production of 306 pups was estimated. We simulated birth, aging and observability according to the model (Table 1) to see if deviation from the model in the original data had any effect on the estimates (Table 2).

Age group durations The age group durations were assumed to be log-normally distributed. The expected values and standard deviations were estimated to 4.4 _+ 0.8, 2.4 _+ 1.4, 4.5 _+ 4.0 and 6.5 _ 2.5 days for age groups 1, 2, 3 and 4, respectively, using data from 465 pups.

Table 1. Results of eight censuses made during 45 days (with the last count on day 0) at Froan in 1993 Census no.

Day no.

No. of pups in age group 1

2

1

-45

8 (20)

2 3 4 5 6 7 8

-41 -37 -31 -25 -14 -8 0

16 (22) 39 (24) 48 (41) 21 (37) 9 (12) 4 (3) 3 (1)

Numbers in parentheses were simulated by the model.

14 (2)

10 (10) 15 (13) 19 (11) 31 (13) 14 (11) 4 (2) 2 (1)

3

4 0 (4)

5 (7) 15 (7) 18 (10) 19 (16) 18 (9) 9 (10) 4(2)

0 (1) 0(3) 4 (5) 5(8) 21 (13) 18(17) 22 (9) 8 (5)

50 Table 2. Estimates of expected time of birth (/z), standard deviation of this (a), observability parameter (q) and total pup production (N) for various subsets of counts made at Froan in 1993 (Table 1)

No. of censuses

Censuses included

Parameterestimates /z

a

q

N

All real All simulated 2, 4, 6, 8 1, 4, 7 3, 6

-32.2 -33.0 -30.9 -31.8 _ 0.4 -33.5

10.6 11.3 10.5 9.9 _+0.4 9.9

0.93 0.90 0.91 0.93 _ 0.01 0.92

1

3

-41.3

3.4

1.00

1 1 1

4 5 6

-35.2 -32.3 -22.7

3.4 3.3 3.6

1.00 1.00 1.00

306 312 348 328 _ 39 366 84 105 95 61

8 8 4 3 2

An estimate based on the simulated counts is also included. Bootstrapping was used to estimate the standard deviation for the estimate based on 3 censuses.

Discussion

In 1993, a total of 226 pups were found in the Froan Nature Reserve. However, due to a long period of bad weather during the peak of the pup production, it is highly likely that we missed several pups which probably were washed into the sea and drifted out of the study area. Also taking into consideration the probability of failing to see a pup during its stay ashore, the estimated total production of 306 pups using all 8 censuses seems reasonable. All estimates based on more than one census are within 20% of the estimate based on all 8 censuses. In contrast, the mean for the single census estimates (86 pups) is only one-fourth of the total estimate and no single census estimate is more than onethird of the total estimate. This may be due to both the extended spread of pupping dates at Froan, and/or inaccuracies in our model. Nevertheless, these results clearly indicate that total pup production estimates based on a single census should be avoided. To obtain more accurate estimates, it is necessary to know more about the distribution of births and the observability of pups, although the closeness of the estimates derived from the simulated censuses to those from the original data indicates that the estimates are quite robust. No assessment of the age group duration parameters has been made, and more accurate information on the distribution of the age group durations should be acquired before using the pup production estimates for management purposes. The procedure used for age group parameter estimation is extremely computer intensive. The duration of age groups could, thus, be better determined by following individual pups, e.g. by radiotelemetry. The observability q is influenced by mortality, invisibility when the pups are at sea and when being overlooked by the observer. Clearly it would have been desir-

51 able to have separated the first factor from the last two. Again, more information could be obtained by studying individual pups.

Acknowledgements This study was financed by the Norwegian Research Council through grant no. 4001.713.030. We want to thank Steinar Engen for helpful discussions. We are thankful to T. Anker-Nilssen who made helpful comments on the manuscript and to R. Binns who improved the English language. Thanks are also due to the field personnel G. Dahl, H. Hoel, J.M. Meland, M. Olsen, T. Opdahl, T. Rodahl, P.T. Smiseth, O. Vie, and I.J. Oyen. Part of the data was collected by M. Ekker, B.M. Jenssen and D. Vongraven from SINTEF/UNIMED and the University of Trondheim.

References 1. Kovacs KM, Lavigne DM. Growth of Grey seal Halichoerus grypus neonates: differential maternal investment. Can J Zool 1986;64:1937-1943. 2. Radford PJ, Summers CF, Young KM. A statistical procedure for estimating grey seal pup production from a single census. Mammal Rev 1978;8:35--42. 3. Ward AJ, Thompson D, Hiby AR. Census techniques for grey seal populations. Symp Zool Soc London 1987;58:181-191. 4. Wiig 0, Ekker M, Ekker T, RCv N. Trends in the pup production of grey seals Halichoerus grypus in Froan, Norway, from 1974 to 1987. Holarctic Ecol 1990;13:173-175. 5. Bakke 0, Lorentsen S-H. Estimation of offspring production from a limited number of stage structured censuses. Manuscript. 6. Manly BFJ. Stage-structured Populations: Sampling, Analysis and Simulation. London: Chapman and Hall, 1990. 7. Efron B, Tibshirani RJ. An Introduction to the Bootstrap. New York: Chapman and Hall, 1993.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang,editors

53

Increased accuracy in the estimation of harp seal (Phoca groenlandica) abundance in whelping patches V.I. Chernook, V.A. Potelov and N.V. Kuznetsov Knipovich Polar Research Institute of Marine Fishery and Oceanography (PINRO), Murmansk, Russian Federation A b s t r a c t . The course and results of experimental aerial surveys of harp seal whelping patches con-

ducted in March 1993-1994 in the White Sea u s i n g an MI-8 helicopter are presented. Recommendations concerning improvements of the on-board equipment, the method of aerial survey and possible automation of the aerial counting work are given. Key words: seal, white coat pup, air survey, infrared, transect

Introduction

Aerial surveys of harp seal whelping patches are part of the complex research which also includes the distribution and migration analysis (geographical aspects) and biological aspects, and which leads to a rational use of the stocks of this animal. Aerial surveys have been used to estimate the number of harp seals in the White Sea since the middle 1920s. Since the early 1960s scientists have surveyed only suckling females, while estimations of the number of pups themselves, the main indication of the seals' stock condition, have not been made. While suckling their pups the females need to feed themselves and must occasionally leave their pups. According to observations made by Popov [1] in early March (when the patches are formed and the suckling begins) 70-80% of females are in the water in the early morning hours on bright sunny days. During the second part of the day no more than 30--40% stay in the water. After 1 or 2 weeks of suckling, the time the females spend in the water increases greatly. This may cause aerial surveys when only females are counted to err by 50% or more. The number of females on the ice also decreases during snow-storms, or when the ice breaks up [1], but increases during ice compressions. Taking into account that the number of suckling females varies greatly both during a 24-h daily cycle and during the whelping period, the harp seal researchers in the White Sea have introduced a correction factor [2]. Thus it is assumed that 80% of females are on the ice and 20% are in the water during aerial surveys conducted in early March. The validity of the correction factor has not yet been confirmed. Estimates based on aerial surveys of harp seal whelping patches during the first days of suckling have some advantages compared to estimates made at other periods of their life (e.g. when the suckling period is over or on the moulting grounds). Then

Address for correspondence: V.I. Chernook, Knipovich st. 6, Murmansk 183763, Russian Federation.

54 the density of the seals' patch is at its highest; furthermore, the age and sex structures of the patch are stable for a long time (females + pups + males). After approximately 3 weeks the whelping patches break up leaving only the pups on the ice. Because of the ice drift, however, the density of pups in the patch greatly decreases, thus resulting in increases in the cost of flights designed to survey them. For that reason we set out to improve the method of aerial surveys of seals in the suckling period. The main point of the work was to improve the accuracy in the methods used to estimate harp seal pup numbers. The means was a survey where the seals were synchronously recorded visually and in the IR part of the spectrum. The stages of the work were: data collection; determination of optimal survey conditions by considering the technical specifications of the on-board equipment; improving the methods for a synchronous survey using the visual and IR part of the spectrum; simultaneous processing of the shots and images obtained from the two parts of spectrum.

Methods

and

Equipment

In March 1993 and 1994 experimental aerial surveys of harp seal whelping patches were carded out using an MI-8 helicopter in the entrance of the White Sea. Technical facilities used in 1993 included (see Table 1): "Vulkan" thermovision set; aerial photo camera AFA-TES- 10; video set JVC GF-500. It is necessary to emphasize that, unlike photo and video cameras, the thermovision set surveys the space by linear scanning with a narrow momentary sighting angle perpendicular to the flight direction. Therefore the given combined survey may be considered as a "quasisynchronous" one.

Table 1.

Specifications of the equipment used in the 1993 survey

Sensor

Thermovisiona Video Photo

Sight angle

Track width

Ground resolution (m)b

(~

(km)

Across

Along

80 40 84

0.72 1.34

1.29

0.40 0.33 0.15

0.4 0.4 0.2

aThermovision-scanner with scanning frequency of 180 lines/s, sensitivity 0.3~ bGround resolutions are given for a flight altitude of 200 m.

55

Table 2. Specifications of the equipment used in the 1994 survey. Sensor

Thermovisiona Video Photo

Sight angle

Track width

Ground resolution (m)b

(o)

(km)

Across

Along

20 40 44

0.35 0.72 0.80

0.26 0.33 0.08

0.3 0.4 0.1

aThermovision sensitivity is 0.2~ bGround resolutions are given for a flight altitude of 200 m.

Technical facilities used in 1994 included (see Table 2): "Insight 80" series thermal imager; video camera JVC TK-880; videocassette recorders JVC; aerial photo camera PA-39; lap-top computer Toshiba; GPS positioning system Raytheon R-900. To determine the number of whitecoats reliably, the survey should be conducted when the majority of the females have whelped. The experiments were conducted when the number of whelped females exceeded 95%. The experiments both in 1993 and in 1994 were carried out using the following design: 1st flight: searching for the whelping patch and choosing the optimum flight parameters (height and speed; synchronous surveys were carried out successively from 400, 200 and 100 m height, speeds ranging between 100 and 180 km/h). 2ndflight: surveying the seal patch along a net of transects at a predetermined height and speed. In 1993 the flights were carried out on 5 and 7 March, and in 1994 on 8 and 9 March. With the equipment used in 1993, the optimum height and speed was 100 m and 180 km/h. The corresponding values in 1994 were 200 m and 130 km/h. The essence of the method is synchronous surveying of the harp seal whelping patches in the visual and IR parts of the spectrum followed by joint processing of the images, when the number of whitecoat pups lying on the ice is determined. Interpretation of the visual images was unproblematic because this information is the same as obtained through the human eye. Thermal images were formed by three main objects: snow-and-ice cover, water and seals. Snow-and-ice cover and water were hardly distinguishable on IR images and served as background for the surveyed seals. These objects had a temperature close to that of the air which at the beginning of March is usually - 3 to -5~ It is known that the temperature of adult seals and whitecoat pups substantially exceeds 0~ Such thermal contrast is quite enough to image them distinctly by means of thermovision techniques (Fig. 1). -

-

-

-

56

a).

b).

Fig. 1. Computer image processing of an IR frame (there are 3 harp seals on the frame) (a) incoming IR frame; (b) IR frame (a) after image processing. 1, Water; 2, ice; 3, harp seals.

-

-

-

-

The succession of analyses of the photographs obtained was as follows: general analysis of images, sorting of the films according to tracks and heights; selection of image areas and ice-floes surveyed in both the visual and IR parts of the spectrum; identification and calculation of seals on the photos in the visual part of the spectrum; joint analysis and calculation of seals in both the visual and IR parts of the spectrum (Fig. 2);

Fig. 2. (1) Video image; (2) processed IR image; bright (warm) spots on IR image are seals; clark (cold) background is ice and water.

57 studies of spatial distribution and determination of errors in seal calculations; In the 1993 experiment, the number of seals was determined by counting the animals on the same ice floes on visual and IR images. The seal count was made in the following order: counts of adult seals on the photos; counts of total number of seals on the IR images; counts of adult seals and whitecoat pups while analysing both photo and IR images. To ensure the reliability of the survey results, video films were also used. The 1994 results have not yet been analysed, so that the following only presents the 1993 results. -

Results

In Table 3 the results of aerial survey of seals on three tracks from a height of 100 m are presented. On these tracks some ice-floes with clearly visible edges were selected and on these ice-floes seals were counted on photos and IR images. A total 272 females and 60 males (332 in total) were counted on the three tracks. According to presently used methods of estimation of seal numbers in aerial surveys, these data correspond to 272 whitecoat pups, 272 females and 60 males (totally 604 seals). Use of a correction factor of 20% [2] yields a corrected number of seals of 340 females, 60 males and 340 pups; in total 740 animals. On IR images 522 seals were counted. Thus the results obtained by one method alone may include large errors. Combination of the two methods, however, may help to increase the accuracy. As can be seen from Table 4, the number of adults remained the same, 332, but the distribution among males and females was altered when the photos and IR images were analysed in combination. In particular, two new groups of seals appeared: single ones (without pups), which were classified as "females with pups" according to Table 3, and dead ones (no spots on IR image). The number of females with pups decreased from 272 to 188 (by 31%), the number of males increased from 60 to 72 (by 20%). In the combined analysis of the images, 69 pups lying on ice-floes without Number of harp seals detected during photo and IR surveys on whelping patches in the White Sea, 6.03.93, 100 m height (corrected numbers include a surplus of 20% [2]) Table 3.

No. of track 10

Visual survey Females 96

11

109

12 Total Corrected

67 272 340

IR survey total no. of seals

Males

Total

9 27 24 60 60

105

194

136

194

91 332 (604) 400 (740)

134 522

58 Table 4. Results of harp seal numbers estimated on whelping patches in the White Sea obtained by combined analysis of the photo and IR images obtained 6.03.93, 100 m height No. of track

10 11 12 Total

Adults

Pups

Total number

Females with pups

Single seals

Males

Dead or ice-floes

With mothers

Single

88 62 38 188

6 47 17 70

9 27 36 72

2 2

88 62 38 188

28 28 13 69

221 226 142 589

mothers were detected. The total number of pups established by the visual and IR method of survey on the three tracks equalled 257 which was 6.5% less than in Table 3 (or 32% less if the correction factor is taken into consideration). The data of Table 4 also let one determine the number of females in the water, which is equal to the number of single pups. On track 10 they amount to 24.1%, on track 11, 31.1% and on track 12, 25.5%.

Discussion When conducting such surveys, the spatial resolution of the survey equipment is of utmost importance. The ground resolution depends on the angle of view, the equipment's angular resolution and the altitude of the flight. Due to some technical problems the resolution of the thermovision equipment obtained during the present survey was less than that of the video camera and included 200-250 lines in the frame. The technical characteristics of the infrared imager are determined when conducting the survey (video + IR). An infrared imager temperature sensitivity of 0.1 o, a spatial resolution of 300-400 elements in the line, and an angle of view of 15-20 ~ are desirable. The following errors appear in processing of the infrared images: a seal scared away from the ice in the patch can be seen as a luminous spot (heated ice), which may be erroneously interpreted as a second seal; a seal only observed in the water has a very weak infrared contrast and may be not detected in the infrared image, but may be observed in the video image; pup and female lying together may be seen as a large spot; pups lying under standing ice-floes are not observed in the infrared still pictures. The main shortcoming of the infrared equipment (infrared imager "Vulkan") used in 1993 was that the film recording the infrared information was not suitable for operational analysis and correction of the survey results in situ. Furthermore, its sensitivity was insufficient. The infrared equipment used in 1994 had better sensitivity, with an output signal of television standard, making it possible to observe the results

59 of the survey during the flight at once. Additionally, the use of a satellite navigational system made it possible to have a precise spatial attachment of all the data from the survey and to show the route of the flight on the monitor screen. The 1994 results will be published at a later stage. Synchronous video and IR surveys of harp seals whelping patches allow the determination of the number of seals on the ice. A combined image analysis in the visible and IR parts of spectrum increases the accuracy of the number of adult seals determined. Using this method, the pupless females (sterile and non-pregnant), separate males, females moving inside the patch, dead animals (or spots resembling animals) and pups separated from their mothers may be detected on the photos.

Acknowledgements The authors thank the on-board operator V.Yu. Bogomolov for his participation in the experimental survey of the seals. We also thank A.B. Gvozd for his aid in data processing and forming the present report.

References 1. Popov LA. On biological substantiation of aerial photography of harp seals' whelping patches in the White Sea (in Russian). In: IV All-Union Conference on Studying of Sea Animals, Kaliningrad, Moscow, 1969;102-105. 2. Timoshenko Yu K. Observations on harp seal females' behaviour on whelping patches. In: Coil "Sea mammals". Moscow: USSR Academy of Science, 1978;323-324 (in Russian).

This Page Intentionally Left Blank

9 1995 ElsevierScience B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. Wallce and O. Ulltang,editors

61

Haul-out behaviour of the Norwegian harbour seal during summer Randi R o e n and Arne BjCrge Norwegian Institute for Nature Research, Blindern, Oslo, Norway Abstract. Background: the haul-out behaviour of the Norwegian harbour seals had previously not been studied thoroughly. Methods: the intent was to examine the haul-out behaviour in relation to three factors: (1) the diel light cycle, (2) the tidal cycle and (3) the interaction between these two cycles. Observations were therefore made on days with low tide around noon, and later repeated on days with high tide around noon. The number of hauled-out seals was counted every hour, day and night. Three places were selected on the basis of their differing characteristics in diel light and tidal variation during summer. Results: the diel light cycle, the tidal cycle, and the interaction between the two cycles, all showed a significant relation with the haul-out behaviour both at Froan and in Kongsfjord. At Hvaler, the haulout pattern was very inconsistent, with large fluctuations from day to day. Conclusions: the higher numbers of hauled-out seals in the daytime, especially in Froan but to a certain degree also in Kongsfjord, may indicate that most seals feed at night. Similarly, the higher numbers hauled out at low tide, especially in Kongsfjord but also in Froan, may indicate that most seals feed around high tides. At Hvaler, the seals may be less at ease by the great deal of commercial and recreational boat traffic. K e y w o r d s : seals, diurnal activity, time series, haul-out pattern

Introduction

Tide is often thought to be a highly important factor influencing the haul-out behaviour of harbour seals [1-3]. Others, however, have found time of day to be the most significant factor [4,5]. Prior to this study, only occasional observations of the haul-out behaviour of harbour seals have been made in Norway. These observations suggest that harbour seals in the Oslofjord haul out in the very early morning, while the seals in West- and North-Norway haul out at low tide [6].

Materials and Methods Three harbour seal colonies at three different locations were selected for the study. At all three locations, haul-out sites are accessible throughout the tidal cycle. Hvaler (59~ 10~ has the smallest tidal amplitude, on average <30 cm, but a large variation in the diel light during summer; the sun is down for about 5 h. Kongsfjord (70~ 29~ has the opposite characteristics, 24 h daylight and an average tidal amplitude around 200 cm, while Froan (63~ 9~ comparably has a moderate tidal amplitude, on average about 130 cm, as well as a moderate variation in the diel light; the sun is down for about 3 h. At Froan a maximum of 100 hauledAddress for correspondence: R. Roen, Norwegian Institute for Nature Research, P.O. Box 1037, Blindern, N-0315 Oslo, Norway.

62 out harbour seals was observed; at Kongsfjord the maximum was 45, and at Hvaler it was 42. According to the principles described by Heide-JCrgensen [7] and Calambokidis et al. [8], the harbour seals were monitored from an elevated view point and counted more than once, before a mean was made. The variation from this mean was generally found to be +_1 seal. The diel light and tidal cycles may interact, so that different combinations of these cycles may influence the haul-out behaviour differently. In order to assess possible interactions, each harbour seal colony was monitored for 2 x 24 h on two occasions with low tide around noon (later referred to as "out of phase" sequences, since the tide falls as the sun rises in the daytime), and similarly on two other occasions with high tide around these hours ("in phase" sequences). The tidal state was recorded, in addition to the time of day, as a measure for the diel light cycle. The seals were viewed with Hartmann Wetzlai 25 x 80 binoculars on a tripod, Fuji 7 x 50 binoculars and a Mirador 60m/m spotting scope with a 20--45 x zoom lens. The official tide tables for the Norwegian coast for 1991 (produced by Norges SjCkartverk) were used to find the high and low tides. Times of sunset and sunrise were obtained from the tables for 1991 of the sun's height and azimuth (produced by Department of Astrophysics, University of Oslo). An analysis of discrete time series by searching for hidden periodicities with periodogram analyses was applied according to Wei [9]. A regression estimation technique was used to assess the deterministic periodic components "diel light" with frequency 1/24 day -~ and "tidal height" with frequency 2/24 day -~. The significance of the contribution of a given frequency to the total variability was tested by an ordinary F-test by comparing with the variability not accounted for by the model, i.e. the residual variability.

Results

The diel light cycle The diel light cycle did show a significant effect on the haul-out behaviour of the harbour seals both at Froan (P < 0.05, r2=0.38) and in Kongsfjord (P < 0.05, r 2 = 0.09) (Fig. 1). At Froan the mean number of hauled-out seals peaked around midday (1000-1700 h; 39-49 seals) and was lowest at night (2300-0500 h; 4-9 seals) (Fig. l a). In Kongsfjord the mean number was slightly larger in the morning (0500-1000 h; 17-21 seals), than in the evening and night (6-13 seals) (Fig. lb). The r 2 for Kongsfjord is conspicuously low. However, by applying hourly means based on observations from all days instead of the individual hourly observations, one finds that r 2 rises to 0.97 for Froan and 0.72 for Kongsfjord. The variance connected with these hourly means, however, conceals both a tidal and a stochastic component. At Hvaler, the diel light cycle did not show a significant effect on the haul-out behaviour of the harbour seals (P = 0.12). There were great fluctuations in the daily haul-out pattern.

63 a

b 80

.

Ill

~o

Sea,, ,o

20 . . . . . . o ~~.~.a~

l

~

'"

ii II

II

'l

h~.t.

sea,s

8~t

60

I

401 20

I ,,llllll~l,

.

.

.

.

,,

0

Time

Time

Fig. 1. Mean numbers of hauled-out seals ( , ) , 1 standard deviation, a n d the numbers predicted by the model of the diel light cycle ( - - ) , in relation to time of day, for Froan (a) and Kongsfjord (b). For Froan Ypred. = 25.5 + 22.1 cos 211/24 (t - 14), r 2 = 0.38; for Kongsfjord Ypred. = 14.1 + 5.1 cos 2H/24(t 8), r 2 = 0,09.

The tidal cycle The tidal cycle also showed a significant effect on the haul-out behaviour of the harbour seals both at Froan (P < 0.05, r 2 = 0.26) and in Kongsfjord (P < 0.05, r 2 = 0.33) (Fig. 2). At Froan the mean number of hauled-out seals was lowest around high tide (7.9 seals) and peaked at low tide (41.2 seals) (Fig. 2a). The same was true for Kongsfjord (high tide 3.2 seals; low tide 23.9 seals) (Fig. 2b). When applying the hourly means, one finds that r 2 rises to 0.94 for Froan and 0.87 for Kongsfjord. The variance connected with these hourly means conceals both a diel light and a stochastic component. At Hvaler, the tidal cycle did not show a significant effect on the haul-out behaviour of the harbour seals (P = 0.08). There was no distinct haulout pattern related to the tidal cycle.

Analysis combining the diel light and tidal cycles Both at Froan and in Kongsfjord, the diel light and tidal cycles did show a significant coupled effect on the haul-out behaviour of the harbour seals, both in the "out of

a

80

b

I

60

80 60

Seals 40

Seals 40

20

20

0

1

2

3 4 h.t.

5

6

7

Tidal state

8

9 10 11 12 I.t.

l

t

0

l/_/-_c 1

2

3 4 h.t.

5

6

7

Tidal state

8

9 10 11 12 I.t.

Fig. 2. Mean numbers of hauled-out seals ( , ) , 1 standard deviation, and the numbers predicted by the model of the tidal cycle ( - - ) , in relation to tidal state, for Froan (a) and Kongsfjord (b). For Froan Ypred. = 25.2 + 18.5 cos 2 H / 1 2 ( t - 8), r 2 = 0 . 2 6 ; for Kongsfjord Ypred. = t3.9 + 10.1 cos 2 I I t 1 2 ( t - 9), r 2 = 0.33. (h.t., high tide; l.t., low tide.)

64

Seals

100

100~

80

80=

60

Seals

40

i

601

40 !

i

20

ol

0 l.t.

h.t.

Tim~.t.

h.t.

h.t.

Seals

I.t.

Timeh.t.

c~

I.t.

4 0 1 ~

40 30

o

. . . . . . . . . .

I

20

Seals

30 20

10 o

o

I.t.

o

o

o

h.t.

.o..~..~..o..~.

Time

I.t.

.~..o. c~

h.t.

I

0

c~

h.t.

I.t.

Time

h.t.

I.t.

Fig. 3. Mean numbers of hauled-out seals ( , ) , 1 standard deviation, and the numbers predicted by the model combining the diel light and tidal cycles (m), in relation to time of day and high and low tides, for the "in phase" sequence (a,c) and the "out of phase" sequence (b,d) at Froan (a,b) and in Kongsfjord (c,d). In (a) Ypred. = 31.3 + 35.1 cos 2 I I / 2 4 ( t - 13) + 18.1 cos 2I'I/24(2t), r 2 = 0.86; in (b) Ypred. = 21.7 + 17.0 cos 2 I I / 2 4 ( t - 16) + 16.0 cos 2 I I / 2 4 ( 2 t - 13), r 2 = 0.69. In (c) Ypred. = 10.6 + 4.2 cos 2 F l / 2 4 ( t - 10) + 6.9 cos 2 I I / 2 4 ( 2 t - 2), r 2 = 0.32; in (d) Ypred. = 17.7 + 6.6 cos 2 F l / 2 4 ( t - 7) + 11.5 cos 2 F l / 2 4 ( 2 t - 14), r 2 = 0.56.

phase" sequences (Froan, P < 0.05, r 2 = 0.86; Kongsfjord, P < 0.05, r z = 0.32) and in the "in phase" sequences (Froan, P < 0.05; r 2 = 0.69; Kongsfjord, P < 0.05, r 2 = 0.56) (Fig. 3). At Froan, the highest numbers of hauled-out seals were always observed in the "out of phase" sequences, at which time they occurred around noon (Fig. 3a). The lowest numbers in the "out of phase" sequences could be found at the high tides and at night (2000-0500 h). The diel light component explained 68% of the total variation in the observed number of hauled-out seals, while the tidal component explained 18%. Utilisation of hourly means raises the r 2 for the diel light component to about 0.77, and the r 2 for the tidal component slightly to about 0.20. In the "in phase" sequences, the number of hauled-out seals peaked around the afternoon low tide, with fewer seals hauling out around the morning low tide (Fig. 3b). The lowest mean numbers could be found at night (2300-0300 h). The diel light component explained 36% of the total variation in the observed data, and the tidal component explained 33%. Again, employment of hourly means increases the r 2 for the diel light component to about 0.51, and the r 2 for the tidal component to about 0.46. In Kongsfjord, the number of hauled-out seals generally peaked at or around the two low tides in the "out of phase" sequences (Fig. 3c). However, the noon low tide peak was much larger and more distinct than the midnight one. The diel light component only explained 9% of the total variation in the observed data, while the tidal

65 component explained 23%. Utilisation of hourly means increases the r 2 for the diel light component to about 0.23, and the r 2 for the tidal component to about 0.62. In the "in phase" sequences, the morning low tide peak was somewhat larger than the aftemoon low tide peak (Fig. 3d). The diel light component explained only 13% of the total variation in the observed data, while the tidal component explained 43%. Usage of hourly means increases the r 2 for the diel light component to about 0.21, and the r 2 for the tidal component to about 0.74. The largest numbers of hauled-out seals always occurred in the "in phase" sequences, most often around a morning low tide. At Hvaler, only the tidal component showed a significant influence on the haulout behaviour in the "out of phase" sequences (P < 0.05, r 2 = 0.16), and only the diel light component showed a significant influence in the "in phase" sequences (P < 0.05, r 2 = 0.19).

Discussion The harbour seals at Froan preferred to haul out during the day (Fig. l a). The diel light cycle is therefore important for the seal's haul-out behaviour in this area. In Kongsfjord, there are only very small variations in the diel light during summer, due to the midnight sun. The diel light cycle may therefore only have a very weak effect on the haul-out behaviour in Kongsfjord, as indicated by the almost negligible higher numbers of hauled-out seals in the early morning (Fig. l b). At Hvaler, the diel light cycle seemed to be of no importance for the haul-out behaviour of the harbour seal colony. The tidal cycle is of importance for the haul-out behaviour of the harbour seals both at Froan and in Kongsfjord (Fig. 2). At Hvaler, however, there are only very small differences in tidal height. The tidal cycle, therefore, does not seem to have any influence on the haul-out behaviour of the harbour seals in this area. In the analysis of the interaction between the diel light and tidal cycles, the diel light seemed to be the most important component at Froan, since maximum numbers of hauled-out seals always occurred in the daytime (Fig. 3a,b). The tidal component, however, was important for the size and timing of this daily maximum. Thus, most seals hauled out around the noon low tide in the "out of phase" sequences (Fig. 3a), and around the afternoon low tide in the "in phase" sequences (Fig. 3b). The results may indicate that most seals at Froan probably feed primarily during the night, and secondly also around the high tides. In Kongsfjord, however, the tide seemed to be the most important component, since maximum numbers always occurred at low tides (Fig. 3c,d). Yet, the time at which a tidal stage occurred was also of some importance. Thus, a somewhat larger number of hauled-out seals occurred around the noon low tide in the "out of phase" sequences (Fig. 3c), and around the morning low tide in the "in phase" sequences (Fig. 3d). The results may suggest that most seals in Kongsfjord primarily feed around high tides. At Hvaler, the haul-out behaviour of. the harbour seals was very inconsistent. Only the diel light component was of impor-

66 tance for the haul-out pattern in the "in phase" sequences, and only the tidal component was of importance in the "out of phase" sequences. The diel haul-out pattern observed in Froan is in accordance with the patterns found in other studies of the harbour seal [e.g. 4,10,11 ]. Harbour seals at Hvaler and Froan feed on several species of fish (e.g. Trisopterus esmarkii, Pollachius virens, Clupea harengus [ 12]) which are considered to be either nocturnally active fishes, or have vertical migrations at night [13-16], and may therefore occur closer to the surface during these hours. The fishes may thereby be more available to the harbour seals at night, resulting in a higher nocturnal activity in the seals. Similarly, the pattern of higher numbers of hauled-out seals at or around high tides observed both at Froan and in Kongsfjord is in agreement with the results found in other studies of harbour seals [e.g. 3,11,17]. Harbour seals may respond to increased local food availability as the high tide enters [ 11 ]. Some of the fishes that migrate in and out of the intertidal zone with the tide [18] are known to be among the prey of harbour seals, e.g. Pleuronectidae, Clupeidae and Salmonidae [e.g. 12,19,20]. The Salmonidae, however, are especially interesting in the case of Kongsfjord, where there is a river with populations of salmon, sea trout and sea char. In addition, extensive intertidal fiats in Kongsfjord may impede high tide haul-out at sites available further up on the fjord banks, since harbour seals often prefer to haul out at places where a swift flee to deeper water is possible [ 1,21 ]. Seals in Kongsfjord moved during haulout and remained close to the tide line as it fell, a type of behaviour reported for hunted and disturbed populations of harbour seals elsewhere [21 ]. At Hvaler the tidal range is very small. In such areas, the activity patterns of the fish may be synchronised with the diel light cycle, rather than with the tides [24]. The lack of a distinct daily haul-out pattern at Hvaler was unexpected, considering the large variations in diel light. However, it may be a consequence of the seals not being at ease, possibly as a result of a combination of the very open topography and the boat traffic in the area. Hvaler has a heavier traffic burden than either of the other two locations, due both to commercial shipping and to recreational utilisation. Generally, however, seals that haul out on smooth sandy beaches or continuous ice [e.g. 1,22,23] do not seem to be influenced by the states of the tide. On the other hand, seals hauling out in habitats consisting of rocks and intertidal ledges do appear to be influenced by the tide [e.g. 2,3,17]. The habitats at Hvaler, Froan and in Kongsfjord belong to the latter group. The haul-out behaviour of the harbour seals in Kongsfjord and at Froan may therefore be expected to be influenced by the tide, whereas the tidal range at Hvaler is too small to have an effect on the haul-out behaviour.

Acknowledgements This study has been a part of the project "Comparative feeding ecology of marine mammals in Norwegian waters" under the Norwegian Marine Mammal Research Program. Financial support was provided by the Norwegian Council for Fisheries Research and WWF.

67

References 1. Sullivan RM. Seasonal occurrence and haul-out use in pinnipeds along Humboldt county, California. J Mammal 1980;61:754-760. 2. Thompson PM, Miller D. Summer foraging activity and movements of radio-tagged common seals (Phoca vitulina) in the Moray Firth, Scotland. J Appl Ecol 1990;27:492-501. 3. Terhune JM, Albon M. Variability in harbour seal numbers on haul-out sites. Aquat Mammal 1983;10:71-78. 4. Stewart BS. Diurnal hauling patterns of harbor seals at San Miguel Island, California. J Wildlife Manage 1984;48:1459-1461. 5. Thompson PM, Harwood J. Methods for estimating the population size of common seals, Phoca vitulina. J Appl Ecol 1990;27:924-938. 6. BjCrge A. Ecology of common seal, Phoca vitulina, in Norway. In: Proceedings, Coastal Seal Symposium, Oslo. Paris: International Council for Game and Wildlife Conservation, 1987;159161. 7. Heide-Jr M-P. Sp~ettet s~el (Phoca vitulina vitulina L.) ph Anholt 1977-78. Flora Fauna 1979;85:59-70. 8. Calambokidis J, Taylor BL, Carter SD, Steiger GH, Dawson PK, Antrim LD. Distribution and haul-out behavior of harbor seals in Glacier Bay, Alaska. Can J Zool 1987;65:1391-1396. 9. Wei WWS. Time Series Analysis. Sec. 12-1. Reading, MA: Addison-Wesley, 1990;i-xv, 478 pp. 10. Yochem PK, Stewart BS, DeLong RL, DeMaster DP. Diel haul-out patterns and site fidelity of harbor seals (Phoca vitulina richardsi) on San Miguel Island, California, in autumn. Mar Mammal Sci 1987;3:323-332. 11. Thompson PM, Fedak MA, McConnell B J, Nicholas KS. Seasonal and sex-related variation in the activity patterns of common seals (Phoca vitulina). J Appl Ecol 1989;26:521-535. 12. Olsen M. N~eringsvalg og n~eringsstrategi hos steinkobber (Phoca vitulina). Cand. Scient.-oppgave i marin zoologi. Biologisk Institutt, Universitetet i Oslo, 1993. 13. Albert OT. Oyephl i Norskerenna: Utbredelse, biologi og n~eringsCkologi. Hovedfagsoppgave i fiskeribiologi. Institutt for fiskeribiologi, Univeristetet i Bergen, 1989, 80 pp. 14. Gordon JDM. The fish populations in inshore waters of the west of Scotland. The Biology of the Norway Pout (Trisopterus esmarkii). J Fish Biol 1977;10:417--430. 15. Woodhead, PMJ. The behaviour of fish in relation to light in the sea. Oceanogr Mar Biol Annu Rev 1966;4:337--403. 16. Helfman GS. Fish behaviour by day, night and twilight. In: Pitcher TJ (ed) Behaviour of Teleost Fishes. London: Chapman and Hall, 1993;479-512. 17. Schneider DC, Payne PM. Factors affecting haul-out of harbor seals at a site in south-eastern Massachusetts. J Mammal 1983;64:518-520. 18. Gibson RN. Intertidal teleosts: life in a fluctuating environment. In: Pitcher TJ (ed) Behaviour of Teleost Fishes. London: Chapman and Hall, 1993;513-536. 19. Bigg MA. Harbour seal Phoca vitulina Linnaeus, 1758 and Phoca largha Pallas, 1811. In: Ridgway SH, Harrison RJ (eds) Handbook of Marine Mammals, Vol 2. Seals. London: Academic Press, 1993; 1-27. 20. Brown RF, Mate BR. Abundance, movements and feeding habits of harbor seals, Phoca vitulina, at Netarts and Tillamook Bays, Oregon. Fish Bull 1983;81:291-301. 21. Vaughan RW. A study of common seals in the Wash. Mammal Rev 1978;8:25-34. 22. Finley KJ. Haul-out behaviour and densities of ringed seals (Phoca hispida) in the Barrow Strait area, NWT. Can J Zool 1979;57:1985-1997. 23. Smith MSR. Seasonal movements of the Weddell seal in McMurdo Sound, Antarctica. J Wildlife Manage 1965;29:464--470. 24. Koppel VH. Habitat selection and space partitioning among two Mediterranean Blenniid species. Mar Ecol Publ Stazione Zool Napoli 1988;9:329-346.

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69

Influences on spatial patterns of Gulf of Maine harbor porpoises Debra Palka National Marine Fisheries Service, Woods Hole, MA, USA Abstract. Background: inter-annual spatial and temporal differences in the sighting rates of harbor porpoises in the Gulf of Maine/Bay of Fundy region have been documented since 1970. This paper explores a possible reason for these differences. Methods: using data collected in 1991 and 1992, harbor porpoise densities adjusted for sea state were related to environmental factors (surface temperature, water depth, density index of prey species, and spatial location) by inspecting contour maps of kriged values of each factor and by fitting generalized additive models (GAMs) to all the factors simultaneously. Results: on a large spatial scale, high density aggregations of harbor porpoises were located in the same general regions during both years. However, on a smaller spatial scale, exact location and magnitude of the aggregations were correlated with the small scale distributions of environmental factors. High densities of harbor porpoises were associated with waters that had surface temperatures of 10-13.5~ contained fish densities of 1.5-11 fish caught per minute of trawling, and were 30-70 fathoms deep. Conclusions: inter-annual changes in surface temperature and fish density may be a reason for changes in the distribution and abundance of harbor porpoises. Key words: habitat description, generalized additive models

Introduction

Line transect surveys conducted in the summers of 1991 and 1992 revealed differences in the small spatial scale distribution and abundance of harbor porpoises (Phocoena phocoena) in the Gulf of Maine/Bay of Fundy/Scotian slope region (GOM/BOF). These surveys used the same ship in nearly the same region, at the same time of the year, and used the same sighting procedures, analysis methods, and half the same observers. Yet, in addition to small scale distribution differences, the estimated abundance for 1992 was nearly twice that for 1991 [1,2]. Such differences may not be abnormal. During 1970-1978, Gaskin and Watson [3] documented interannual and spatial differences in sighting rates in part of the Bay of Fundy. To explain these inter-annual differences, this study expands a previous Bay of Fundy habitat study [4] to the entire GOM/BOF. In this larger region, small scale densities of harbor porpoises were examined relative to small scale environmental and physical factors: water temperature, depth, index of density of herring and silver hake, and spatial location.

Materials and Methods

Harbor porpoise density and most of the environmental data were obtained during Address for correspondence: National Marine Fisheries Service, 166 Water Street, Woods Hole, MA 02543, USA.

70 line transect sighting surveys conducted in the GOM/BOF region during 22 July-30 August, 1991 and 29 July-6 September, 1992. During both years, the two "independent" team methodology was used to estimate density corrected for g(0) [ 1]. Environmental data were collected at the beginning of "legs of effort", which were defined as a period in which all sighting conditions were the same. A leg usually lasted 30 min and was about 5 nautical miles (nmi) long. Depth was not collected in 1991. Therefore, using the software package SURFER [5], depths measured in 1992 were kriged and used to predict the depths at the beginning of legs surveyed in 1991. Simple kriging was used with a spherical variogram model, no drift or nugget, and anisotropy was at a 45 ~ angle tilted NE-SW, which followed the coastline. The predicted depths were validated by inspection of a nautical chart. Density indices of a combination of several fish species were estimated from data collected on research trawl surveys conducted by the National Marine Fisheries Service (NMFS) and Canadian Department of Fisheries and Oceans (DFO). Trawl surveys were conducted during 23 July-1 August, 1991 (NMFS), 5-10 July, 1991 (DFO), 27 July-10 August, 1992 (NMFS), and 24 June-2 July, 1992 (DFO). Fish species that were investigated are primary harbor porpoise prey species: Atlantic herring (Clupea harengus), alewife herring (Alosa pseudoharngus), blueback herring (A. aestivalis), and silver hake (Merluccius bilinearis). Fish density indices were calculated as the ratio of total number of fish of the above species that were caught in a trawl to the length (in minutes) of that trawl. Fish density indices at the beginning of each leg of effort of the harbor porpoise sighting survey were predicted from kriged spatial distributions of the fish density index from the trawl surveys. Simple kriging was used with the same conditions as for depth: a spherical variogram model, no drift or nugget, and anisotropy at a 45 ~ angle tilted NE-SW. Sighting rates from a leg of a line transect survey depend not only on the true local density, but also on sightability of harbor porpoises, which may be affected by observers (i.e. year of survey), sea state or size of harbor porpoise groups. Size bias was checked for by using DISTANCE [6] and was not significant. Density along a leg of effort was, therefore, estimated by multiplying the following factors: sighting rate of groups from a leg of effort, average group size from that leg, and the sightability corresponding to the year and sea state experienced during that leg. Sightability was expressed as f(O)/g(O), where f(0) is the probability density of observed perpendicular distances at perpendicular distance zero, and g(0) is the probability of detecting a group on the track line. These parameters were estimated independently for each combination of sea state and year using DISTANCE to estimate f(0) and the direct duplicate method [1 ] to estimate g(0). The resulting adjusted estimates of local density were fitted to environmental factors (water depth, surface temperature, latitude, longitude, and fish density index) using generalized additive models (GAMs) [7] in SPLUS [8] and by visual inspection of contour plots of the spatial distribution of an environmental factor overlaid with harbor porpoise density for each leg of effort. Smooth contour plots were generated by kriging values of one environmental factor, which was collected on the irregularly spaced beginning of legs of sighting survey effort. Simple kriging was

71 used under the same conditions as was used for depth. These contour plots were also used to measure the amount of planar area which was covered by a range of values of a particular factor. Planar area was computed by projecting the desired portions of the predicted surface onto a plane and calculating the area of the projection. An assumption of GAMs is that the dependent variable is distributed according to a distribution from the exponential family which includes the Normal, Poisson, Binomial and Gamma distributions. The dependent variable in this study, density of harbor porpoises, is always greater than or equal to zero, but may not be an integer. Distributions of normalized residuals (Anscombe residuals) were used to determine which distribution was most appropriate. Because no harbor porpoises were observed on some legs of effort (65% and 52% in 1991 and 1992, respectively), only those legs with positive densities were used. To assess goodness-of-fit and compare GAM models, the F-test, AIC [7] and a pseudo-R 2 [9] were used. The pseudo-R 2 was 1.0 minus the ratio of deviance of the model to deviance for the model with just the overall mean.

Results

During 1991, 472 and 375 groups of harbor porpoises were seen by the two "independent" teams while surveying 1,962 nmi of track line. During 1992, there were 726 and 599 groups observed by the two teams on 2,003 nmi of track line. There was no evidence of size bias in either year. The estimates of f(0) and g(0) differed by year and sea state, although not significantly (ANOVA, P > 0.05). To insure an assumption of GAMs, the dependent variable, harbor porpoise density, was log transformed and the gaussian link was used because log(density) was more closely normally distributed than were the Gamma or Poisson normalized (Anscombe) residuals of density. Fish density indices were transformed to log(fish density index + 1) for the same reason. Adding one to the fish density index allowed the areas of zero fish density (which were infrequent) to be used. Using the F-test and AIC for each separate year, the following GAM model was chosen which used the lowest possible order smoothed functions while still capturing the shape of the relationship: log(density) = s(temperature,2) + s(depth, 2) + s(log(fish + 1),2) +/o(latitude,longitude, 1/3) where s(factor, df) indicates a smoothed function of the factor with df degrees of freedom, and/o(factorl,factor2,span) indicates a lowest smoothed fit of factorl and factor2, where the span is the fraction of data used to compute the local regression. Separate smoothed functions of latitude and longitude were investigated but did not fit as well as the bivariate relationship, indicating an interaction between latitude and longitude. The pseudo-R 2 for 1991 and 1992 were 0.25 and 0.32, respectively.

72

Fig. 1. Plots of CAM smooth fits of the environmental factors: temperature (temp), depth and log transformed fish density index (logcalcallnum) for 1991 (top line) and 1992 (bottom line). Solid line is best fit, dashed lines are 2 standard error confidence limits, hash lines on x-axis are the observed values of that factor.

73 GAM models suggested that high densities of harbor porpoises were in waters that were between 10 ~ and 13.5~ especially between 10 ~ and 12 ~ in 1991 (Fig. 1). Spatial contour plots of temperature overlaid with harbor porpoise density (Fig. 2) illustrated that 1992 harbor porpoise density was higher than that in 1991, as was the percentage of the planar area that was covered with water temperatures of 10-13.5 ~ (41% in 1991 versus 59% in 1992). GAMs demonstrated that harbor porpoises were most often found in waters that were between 30 and 70 fathoms deep. Also, more animals were found in shallower waters (down to 10 fathoms) and in deeper waters (out to 100 fathoms) in 1992 than in 1991 (Fig. 1). The relationship between harbor porpoise and fish density is less clear. The GAM models indicated that, for both years, high densities of harbor porpoises were associated with intermediate levels of the fish density indices (1.5-11.0 fish/min; Fig. 1), even though harbor porpoises were distributed in waters with a larger range of fish density indices in 1992 than in 1991 (0-53 fish/min in 1991 versus 0-244 in 1992). In fact, legs with very high fish density indices were in hot waters, generally in temperatures higher than the "preferred" surface temperatures described above. The planar area of the study region that was covered with waters containing the "preferred" fish index values was greater in 1992 than in 1991 (10% in 1991 versus 16% in 1992; Fig. 2). The bivariate relationship of latitude and longitude in the GAM indicated that highest densities during both years were found around Grand Manan Island and offshore of Penobscot and Frenchmans Bays of central Maine (Fig. 1). The Maine area had lower harbor porpoise densities in 1991 than in 1992.

Discussion

The GAM models of harbor porpoise density did predict small scale patterns; however, the magnitude was underestimated. For example, when using environmental data from 1991 in the 1992 model, the density in 1991 was correctly predicted to be lower than that predicted for 1992. However, the predicted 1991 densities were also lower than the actual 1991 densities. This may be due to several possibilities, such as: the smoothing procedure was too smooth; zero density legs should have been incorporated; data should have been collected on a finer spatial scale; there were additional factors influencing density and/or sightability of harbor porpoises that were not incorporated; or density in the summer depends not only on concurrent small scale environmental factors, but also on events which occurred in regions where harbor porpoises spent the winter. Some of these factors can be investigated in the future. Even though the GAM models provided very smooth surfaces, these data indicated that on a large spatial scale, harbor porpoise aggregations were in the same general vicinity during both years. On a smaller scale, the exact location and magnitude of those aggregations were correlated to small scale distributions of water tem-

74 Fig. 2. Contour plots of spatial distribution of temperature and log transformed fish density index for 1991 and 1992. Dark areas of contour plots are warmer ternperatures. Black dots and + marks are the locations of the beginning of legs of effort from the harbor porpoise line transect survey. + indicates no observed harbor porpoises. Size of black dot indicates magnitude of harbor porpoise density; the larger the dot size the greater the density. Total black areas are either land or water that was not surveyed.

75

perature and fish density indices. This can be seen by a close inspection of the two highest density areas. The Maine aggregation extended farther offshore and south in 1992 than in 1991. However, in both years, the aggregation coincided with a finger of water that was 13~ and contained intermediate fish density indices of 2 - 1 0 or more fish per minute. The same trends can be seen in the Grand Manan Island area, although not as clearly. South of the island (along 44.3~ from 67.5~ to 66.5~ temperature, harbor porpoise and fish densities were higher in 1991 than in 1992. Inter-annual changes in the surface temperature and fish density patterns may be a reason for the inter-annual changes in harbor porpoise abundance. Although it is difficult to demonstrate a cause-and-effect relationship, it can be noted that the abundance of the region for 1992 was estimated to be 1.8 times higher than that for 1991 [2], which coincides with a similar magnitude of increase in the planar area covered by "preferred" water temperatures (1.5 x ) and fish density indices (1.6 x ).

References 1. Palka D. Abundance estimate of the Gulf of Maine harbor porpoise. Rep Int Whal Commn 1994;(Special Issue 16) (in press). 2. Smith T, Palka D, Bisack K. Biological significant of bycatch of harbor porpoise in the Gulf of Maine demersal groundfish fishery. NOAA/NMFS/NEFSC Ref Doc 1993;23:1-15. 3. Gaskin DE, Watson AP. The harbor porpoise, Phocoena phocoena, in Fish Harbour, New Brunswick, Canada: occupance, distribution and movements. Fish Bull 1985;83:427-442. 4. Watts P, Gaskin DE. Habitat index analysis of the harbor porpoise (Phocoena phocoena) in the southern coastal Bay of Fundy, Canada. J Mammal 1985;66:733-744. 5. Keckler D. SURFER for Windows User Guide. Golden, CO, USA: Golden Software Inc, 1994. 6. Buckland S, Anderson DR, Burnham KP, Laake JL. Distance Sampling. Estimating Abundance of Biological Populations. New York: Chapman and Hall, 1993. 7. Hastie TJ, Tibshirani RJ. Generalized Additive Models. New York: Chapman and Hall, 1991. 8. SPLUS. Seattle, WA, USA: Statistical Sciences, 1991. 9. Swartzman G, Huang C. Spatial analysis of Bering Sea groundfish survey data using generalized additive models. Can J Fish Aquat Sci 1992;49:1366--1378.

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77

Aerial surveys of harp and hooded seal pups in the Greenland Sea pack-ice Torger Oritsland and Nils Oien Institute of Marine Research, Nordnes, Bergen, Norway A b s t r a c t . After experimental surveys by ship-borne helicopter and fixed-wing aircraft in 1990, harp

seal breeding patches were surveyed in the Greenland Sea pack-ice (the West Ice) in the spring of 1991. Combined estimates based on data from visual helicopter transects and aerial photographic transect surveys indicate a minimum total production in excess of 55,000 harp seal pups in the West Ice in 1991. Extreme weather conditions and an exceptional westerly distribution of the pack-ice impeded attempts to survey West Ice hooded seal pups in 1994. Classified counts suggest late births of harp seal pups in 1990 when compared to 1991. Less precise data suggest comparable timing of peak pupping but a wider temporal distribution of hooded seal births in 1994 than in 1991. Published results from analyses of still-camera and video material confirm that image-analysis may be used to obtain useful information on environmental conditions and the spatial distribution and sizes of seals in pack-ice breeding patches. Key words: visual, video and photographic transects, pup development, production

Introduction Harp and hooded seals, Phoca groenlandica and Cystophora cristata, were selected as key species for studies under the Norwegian Marine Mammal Research Programme 1989-1993, and surveys of pups in the West Ice, the breeding grounds in the Greenland Sea pack-ice, were among the chosen priority projects planned for the programme. Experience in the operation of a ship-based helicopter was obtained on an expedition to tag harp seal pups in the West Ice during the breeding season of 1989 [1,2]. The project was continued on an expedition to pursue the tagging programme and to test alternative techniques and select methods for aerial transect surveys of pups in the West Ice breeding lairs in 1990 [3]. Harp seal pups were then surveyed and tagged during the breeding season in 1991 [4,5]. Further efforts were delayed by a temporary scarcity of funds, and a postponed expedition dedicated to surveys of hooded seal pups was organized by the Institute of Marine Research in prolongation of the Marine Mammal Research Programme in 1994. Activities and results related to the surveys in 1990, 1991 and 1994 are summarized in this report. Results from the tagging programme [6] are reported separately to this symposium [7].

Logistics The mutually trustful relationship established between the Institute of Marine ReAddress for correspondence: T. Dritsland, Institute of Marine Research, P.O. Box 1870, Nordnes, N5024 Bergen, Norway.

78 search and the companies and crews during the tagging expedition in 1989, formed the basis for further cooperation with Rieber Shipping A/S, Bergen, and Helikopterteneste a.s., Kinsarvik, for the use of the same ship and helicopter on the expeditions in 1990, 1991 and 1994. The "Polarsyssel" is a 50-m long vessel of 499 gross tonnes with reinforced hull for navigation in ice and fitted with a 2,500 hp main engine. She is fully classified as an icebreaker-sealer (DnV + 1AJ). Large flush hatches over the aft shelterdeck are particularly useful because they permit sheltered stowage of the helicopter during crossings in rough seas to and from the ice, as well as sheltered instalment of a container lab. The Ecureuil AS 350 B 1 helicopter proved to be well suited for our purpose, both with regard to ease of handling and stowage on board the ship and because of capacity and range. Both the ship and the helicopter were fitted with satellite navigation systems. The global positioning system (GPS) in the helicopter proved to be useful both for positioning of observations during search flights and for navigation along preplanned transect lines during visual and video surveys. A fixed-wing twin-engine Partenavia P68TC Observer aircraft, operated by Fotonor A.S., Oslo, was based on Jan Mayen Island to be used for search flights and photographic transect surveys of seal patches in all the 3 years covered by this report. For navigation, the Partenavia was fitted with Loran C in 1990 and 1991 and with GPS in 1994, and carded a mounted Wild RC 20 camera with a 15 cm lens for vertical photography. In 1994 an additional fixed-wing twin-engined aircraft operated by the same company, a Piper PA31 fitted with GPS and a vertically mounted Zeiss LMK camera with a 15 cm lens, was based at Longyearbyen airport, Svalbard, to improve the efficiency of search and photographic surveys during the expected brief spells of acceptable weather conditions.

Field work 1990

The primary purpose of the expedition in 1990 was to test alternative techniques for selection of methods for transect surveys of harp and hooded seal pups in the West Ice breeding lairs. A secondary objective was to continue the tagging program for harp seal pups which was started in 1989. "Polarsyssel", with the helicopter on board, spent 20 days (20 March to 9 April) in the ice in 1990. Continued northerly winds prior to and during the breeding season dispersed the pack-ice and also caused a rapid southerly drift of the floes. This drift continued throughout the season. Except for three early days with strong winds and poor visibility, the weather conditions were tolerable or good during the period in the ice. The Partenavia aircraft was available for search and survey flights for 13 days, but

79 the operations were restricted by local weather conditions at Jan Mayen, and flying was limited to a total of 29.5 h. However, the pack-ice between 71~ and 75~ was searched on three flights before the end of March, and another search with intervallic photography from 1,000 ft (305 m) was carded out from 70~ to 75~ during the first few days of April (Fig. 1). Short intervallic and overlapping photo-transects from 500 ft (152 m) and 1,000 ft were also obtained over two small harp seal breeding lairs. Additional information on ice conditions was supplied from two search flights by a Soviet aircraft which covered the area between 72~ and 74~ on 21 March and 23 March. Breeding seals were not discovered during the Soviet flights. "Polarsyssel", in the meantime, worked its way from about 71~ up to 75~ using available time on helicopter search and tagging of harp seal pups. Scattered breeding harp seals were recorded throughout the area from 70~ to 74~ with two small patches of breeding harps which were located around 73~ 12~ in late March. Widely dispersed families of hoods were found all over the open pack-ice from 70~ to 75~ with only one minor concentration of some 300 families at 73~ 13~ on 25 March. In addition to search flights, the helicopter was also used to deploy personnel for tagging and for experimental transect surveys. Seven series of video transects were carried out over the two patches of harps at 100 ft (30 m) altitude intervals between 200 ft and 600 ft (61 and 183 m). A special Dage MTI camera, selected for maximum resolution, proved to be hopelessly inadequate for the purpose, but good images were obtained by an off-the-shelf Sony 8 mm handycam, provisionally mounted for vertical recording through a front-bottom window in the helicopter cockpit [8]. In 1990 the helicopter was also used for visual transects with two observers at 200 ft (61 m) and a series of age (developmental stage) determinations of harp seal pups from altitudes around 50 ft (15 m) in breeding patches between 31 March and 8 April. 1991

In 1991 the Partenavia aircraft was available on Jan Mayen Island for 26 days from 15 March. Operations were impeded by unsuitable or unstable weather for 16 days, but a total of seven search flights and three photosurveys were completed over the pack-ice between 71~ 18~ and 74~ 03~ "Polarsyssel", with the helicopter onboard, was engaged in search, taggings and surveys in the ice between 71 ~ 18'W and 75~ 03'W for 28 days from 16 March. Again the weather was highly variable and less than ideal with winds at gale force or stronger for 11 days, and moderate or poor visibility for 16 days through the period "Polarsyssel" was working in the pack-ice (Fig. 2). Young ice covered extensive areas between strips and patches of consolidated older ice. Currents and changing winds led to frequent rearrangements of the ice with an unexpected easterly drift in late March and a resultant fairly fast drift towards SSW in early April. Scattered harp seals with pups were recorded throughout the area between 71 ~ and 75~ a distance of about 350 nautical miles (650 km), with the largest concen-

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Fig. 2. Ice edges and the distribution of breeding harp and hooded seals, recorded by ship-borne helicopter and spotting aircraft in the West Ice 16 March to 12 April, 1991" (1) hooded seal breeding patch; (2) harp seal breeding patch; (3) scattered breeding hooded seals; (4) drift; (5) ice edge.

Table 1. Estimates of harp seal pup production in four separate breeding patches in the Greenland Sea pack-ice in 1991, based on visual transect counts from helicopter and photographic transect surveys by fixed-wing aircraft, uncorrected for bias

Patch No. 01 02 03 04 Total over all patches 95% confidence interval

Visual 7,100 (0.075) 3,800 52,500 (0.159)

Photographic 2,021 (0.128) 5,905 31,917 (0.271)

Combined 2,991 (0.078) 3,800 5,905 (0.195) 42,574 (0.141) 55,270 (0.141) 44,500-68,500

The estimate for patch No 2 was provided from visual shipboard transects by the Soviet research vessel "Varzuga" without information on uncertainties. Available visual and photographic data were combined for each patch by weighting of variances. Coefficients of variation are given in parentheses.

82 trations towards the north. Four separate harp seal breeding patches were found and three of them were covered by aerial still photo transects and two of these three patches also by visual and video helicopter transects (Table 1). The fourth and smallest patch (No. 02) was covered only by visual shipboard transects carried out by the Soviet research vessel "Varzuga". Age or developmental stages were determined for a total of 4,711 harp seal pups in two of the breeding patches. An additional 20 dead pups (0.4% of the total sum) were recorded during these low-altitude helicopter flights. 1994

As mentioned under logistics, the expedition in 1994 included an extra fixed-wing aircraft stationed at Longyearbyen airport, Svalbard. "Polarsyssel", with the helicopter on board, had 19 days in the ice from 16 March, and both aircraft were available for 18 days from the same date. However, boisterous weather was even more restrictive this year than during any of the previous expeditions. Northerly winds prevailed with strengths from strong breeze (Beaufort 6) to violent storm (B.11) with occasional hour-long gusts of hurricane force (B.12). Visibility was poor to moderate for 16 days through the time spent in the ice. Also the ice conditions were extreme with the ice edge far to the west of the expected position and with a rapid drift of the pack-ice towards SSW-SW (Fig. 3). An Argos satellite buoy deployed on a large floe on 26 March drifted at an average speed of 1.3 knots until it was resighted 116 nautical miles further to the SSW 4 days later, and continued roughly in the same direction along the East Greenland coast until the last signals were received in early June. Because of the ice conditions, the expedition in 1994 operated under special permit from Greenlandic authorities. "Polarsysser' operated south of 72~ towards 68~ throughout the period in the ice and was unable to proceed further north. The helicopter was used on 12 search flights between 68~ and 73~ and two attempts at visual transect surveys of hooded seals with pups on 26 March and 30 March. An attempt to use the helicopter for tagging of harp seal pups at 69~ 20~ on 3 April was discontinued because of icing and poor visibility. The difficult weather conditions and the westerly location of the pack-ice also impeded the operation of the two fixed-wing aircraft. They needed about 1 and up to 3 h to reach the ice from their bases on Jan Mayen and at Longyearbyen, respectively, and therefore required exceptionally stable weather and reliable forecasts. However, three search flights from Jan Mayen covered the ice from 68~ 23~ to 74~ 10~ and the area from 74~ 15~ to 76~ 09~ was searched on four flights from Longyearbyen. Only small numbers of scattered breeding harps and hoods were found north of 74~ A total of 395 photographs were taken at intervals from 800 ft (245 m) during these seven search flights. The Partenavia from Jan Mayen also obtained 180 images from the same altitude in four transects over scattered weaned hooded seal pups around 68~ 23~ on 26 March. On the same date scattered female hoods

83 76 ~

_

74 o

72 ~

'~176 Lf -

6B o -/--

. . . . . .

03,26~ /

Y

=

3

ooo

/-,,

::x

5

--'03.25-03.26

2 "0 o

-

'

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'

Fig. 3. Ice edges and the distribution of breeding harp and hooded seals recorded by spotting aircraft

and ship-borne helicopter in the West Ice 20 March to 4 April, 1994: (1) hooded seal breeding patch; (2) harp seal breeding patch; (3) scattered weaned hooded seal pups; (4) scattered weaned harp seal pups; (5) ice edge. with relatively young pups were recorded around 74~ 14~ Another hooded seal breeding patch with newly born pups unevenly distributed over an area of about 5 x 10 nautical miles (170 km 2) was discovered the next day at 71~ 18~ A few pictures were obtained but the available flight-time did not permit coverage by transects.

Results and Discussion

Still-camera and video images obtained during the exploratory survey in 1990 have been used in image analyses to assess ice-conditions and measure sizes of seals [8].

84

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Fig, 4. The relative distribution of harp seal pups by developmental stage and date (] = newborn; 5 = moulted beater), recorded by classified counts in the West Ice 28 March to 8 April, 1990 (upper graph) and 22 March to 12 April, 1991 (lower graph). Sample sizes for each count are given along the upper horizontal axis of each graph. The vertical stippled line in the lower graph divides between counts in two separate breeding patches.

85 108 100

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I

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.

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x

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148

306

6O

U ~ e,.

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0 40

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Fig. 5. The relative distribution of hooded seal pups by developmental stage and date (0 = unborn/ parturient females; 5 = weaned), recorded by classified counts in the West Ice 22 March to 7 April, 1991 (upper graph) and 16 March to 31 March, 1994 (lower graph). Sample sizes for each count are given along the upper horizontal axis of each graph.

86 Results indicate that seals prefer medium-sized floes, ranging from 13 to 38 rn in diameter, compared to the size range 0.2--49 rn for all ice floes. Floe shape was also characteristic of occupied floes: seals selected more rounded floes rather than elongated floes. The presence of seals was also related to the ice conditions over a larger area. In the transects that were analysed seals were always found in areas with greater than 60% ice coverage. Data from videos resulted in values of 1.32-2.40 m for lengths of adult and subadult seals, and 1.02 m for pup length. No attempt was made to distinguish between species, but these measurements fall within the combined range of lengths for harp and hooded seals obtained from previous studies [8]. Abundance estimates of harp seal pups calculated from the basic transect data obtained in 1991 are listed in Table 1, with a provisional best estimate of total production exceeding 55,000 pups. For each patch the available estimates have been combined by weighting of variances. The variance associated with the Soviet count of patch No. 02 is not known, and has therefore not been accounted for in the confidence interval for the combined total. Both the visual and the photographic survey estimates have an inherent negative bias caused by the fact that no correction has been made for scattered pups between the patches, nor for the temporal distribution of births. A specific problem with the photographic surveys is caused by errors in the interpretation and reading of the photographic material. Experimental reading of subsamples by alternative techniques indicates that the adopted procedure may underestimate the true counts of pups by about 9% [5]. The results from low altitude developmental stage determinations of harp seal pups in 1991 [4] are compared to corresponding data collected in 1990 in Fig. 4. These graphs suggest that breeding may have occurred earlier by 5-7 days in 1991 than in 1990. To accommodate the sealers' lore, it may be mentioned that the moon occurred in its first quarter on 23 March in 1991 and 10 days later, on 2 April, in 1990. Developmental stages of hooded seal pups [4] were not determined on dedicated flights in 1994, but classified counts recorded on helicopter search flights suggest an exceptionally wide temporal spacing of births; centered roughly around the same dates as in 1991 when stage determinations were recorded on three dedicated low altitude helicopter flights and from the ship in passing through the ice (Fig. 5). Because they covered only limited areas with unevenly distributed hooded seals, representing a minor but unknown proportion of the total, the visual helicopter transects of hooded seal pups in 1994 were methodological exercises rather than surveys which could be applied in assessments. Data from the expedition in 1994 are indicative of possible distributions of breeding hooded seals under extreme conditions in the Greenland Sea. They are, however, totally inadequate for any assessment of production.

Acknowledgements We acknowledge with gratitude the assistance of the crews on the "Polarsyssel" and

87 the crews manning the helicopter and fixed-wing aircraft, and appreciate the support of Rieber Shipping A/S, Helikopterteneste a.s. and Fotonor AS. We also extend our thanks to BjCrn Bergflcdt, Kjell Arne Fagerheim and Karl Tellnes of the Institute of Marine Research, and to Tore Haug, Kjell T. Nilssen and Nils-Erik Skavberg of the Norwegian Institute of Fisheries and Aquaculture in Tromsr who all contributed by enthusiastic participation in the field work. Kjell Arne Fagerheim also handled all visual analyses of the photographic material and Siri Hartvedt provided assistance with the punching and analysis of data. Visitors who joined individual expeditions to pursue independent studies and contributed to activities in the field included Jonny Beyer, University of Bergen, Robert Eisner, University of Alaska, Lars Folkow and Per-Erik MArtensson, University of Tromsr V.A. Potelov and V.F. Prishchemikhin, sevPINRO, Arkhangelsk and Jack Terhune, University of New Brunswick. The project was funded by the Norwegian Fisheries Research Council (NFFR No. 4001701.304) and in 1994 by the Norwegian Research Council (NFR No. 104.500/110).

References 1. Oritsland T, Folkow L. Selmerking i Vesterisen. Rapport Fiskeridirektoratets havforskningsinstitutt, SPS 8904. Bergen: 1989; 1-4. 2. Folkow LP, Blix AS. Tracking harp and hooded seals in the Greenland and Barents Seas. Working Paper ICES Working Group on Harp and Hooded Seals, 16-18 October. SEA- 17. Bergen: 1989; 16. 3. ~ritsland T, Haug T, Oien N, BergflCdt B. Telling, merking og undersCkelser av sel i Vesterisen. Rapport Havforskningsinstituttet, SPS 9004. Bergen: 1990;1-11. 4. IDritsland T, Fagerheim KA, Oien N. West Ice seal survey and tagging in 1991. Working Paper Joint ICES/NAFO Working Group on Harp and Hooded Seals, 14-18 October, SEA-23. Copenhagen: 1991;1-13. 5. Oien N, Oritsland T. Aerial and visual surveys to estimate harp seal pup production in the Greenland Sea. ICES Coun Meet 1993; N9:1-9. 6. ~ien N, 13ritsland T. Recaptures of harp seals (Phoca groenlandica) tagged as pups in the Greenland S e a - pup production and dispersion patterns. Working Paper Joint ICES/NAFO Working Group on Harp and Hooded Seals, 14-18 October, SEA-33. Copenhagen: 1991 ;1-21. 7. Oien N. Use of mark-recapture experiments to monitor seal populations subject to catching. In: Blix AS, WallCe L, Ulltang 13 (eds) Whales, Seals, Fish and Man. Amsterdam: Elsevier, 1995;3545. 8. Estep KW, Maclntyre F, Noji TT, Stensholt B, Oritsland T. Seal sizes and habitat conditions assessed from aerial photography and video analysis. ICES J Mar Sci 1994;51:253-261.

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Stock identity and social organization

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© 1995 ElsevierScienceB.V. All rightsreserved Whales, seals, fish and man A.S. Blix, L. Wallceand 0. Ulltang,editors

Genetic markers

91

and whale stocks in the North Atlantic ocean:

a review

Alfrec3 Arnason lmmunogenetics Unit, Department of Pathology, University Hospital, Reykjavfk, Iceland Abstract. The discovery of protein electrophoresis and later of applying electrophoresis to DNA fragments is a powerful tool in comparing animals from different areas. We discuss our experience of using these techniques in comparing stocks of whales. The emphasis is laid on fin (Balaenoptera physalus), sei (B. borealis) and minke whales (B. acutorostrata). Of 31 enzyme systems encoded by 40 loci in fin whale liver samples from Iceland and Spain, 11 loci were found to be polymorphic. The average heterozygosity for these two stocks of fin whales was 0.074 and 0.083, respectively. There were between years differences observed in the fin whales suggesting substructures of the populations. The Nei's genetic distance between Icelandic and Spanish fins was 0.016. In a limited study of fin whale samples from Norway, Iceland and Canada there were statistical differences between enzyme loci tested. No between years differences were found in seis that came only from Iceland. The isozyme study of minke whales revealed genetic differentiation between Norway, Iceland and West Greenland. DNA fingerprinting showed similar differentiation. Earlier morphometric comparisons and tagging experiments pointed in the same direction. Immunogenetical studies of the MHC region of fin and sei show lack of polymorphism in these species. The C4 is more similar to terrestrial animals regarding polymorphism. The C4 typing revealed hybridisation between blue and fin whales; three hybrids were found, one fertile female in her second pregnancy and two males. This demonstrates how closely related these two species are. The conclusion from our study is that fin whales from Norway, Iceland, Canada and Spain are separate stocks. The same applies to minke whales from Norway, Iceland and West Greenland; they represent different populations. Key words: fin, sei, minke, isozymes, DNA, MHC, hybrids

Introduction In this short review we concentrate mainly on our investigation over the past 18 years or so. This is bound to reflect the technical advances during the period. The advent of electrophoresis made possible the separation of different proteins and later of DNA fragments. The patterns acquired give the picture of different genes or their products, the proteins; these are the so-called genetic markers. We have applied a variety of these techniques to study several species of whales from different areas of the North-Atlantic Ocean. R/Srvik and Jonsgaard [1] divide fin whales in the North Atlantic Ocean into six stocks: 1. North Norway and Arctic Eastern North-Atlantic; 2. East Greenland and Iceland; 3. West-Norway and the Faroes; 4. British Isles, Spain and Portugal; Address for correspondence: Immunogenetics Unit, Department of Pathology, University Hospital, Reykjav~, Iceland.

92 5. 6.

West Greenland; Nova Scotia, Newfoundland and Labrador. The IWC divides the fin whales of the North Atlantic into seven management stocks, the divisions the same as above, except stock 6 is further subdivided into two stocks: Newfoundland-Labrador and Nova Scotia stocks [2]. Other ideas have been put forward, e.g. that the fin whales in the North Atlantic form a patchy continuum [3]. The sei whales are divided into three management stocks by the IWC [2]: 1. Iceland-Denmark Strait; 2. Eastern stock (Norway, Scottish Isles, Spain and Portugal); 3. Nova Scotia. The IWC division of minke whales into four management stocks is as follows [2]: 1. the Canadian East Coast stock; 2. West Greenland stock; 3. Central stock (Iceland); 4. Northeastern stock (Norway). The IWC stock divisions are mainly based on catch statistics, and some biological characters such as morphometry and tag returns. The aim of the present study was to use genetic marker systems in order to clarify, if possible, the stock identity of the above-mentioned whale species in the North Atlantic Ocean. This review also deals with some comparative immunogenetical markers in the major histocompatibility complex (MHC region) as well as complement factor 4 (C4).We also discuss species hybridization between the blue and the fin whale and how this reflects the close genetic relationship between these species.

Material and Methods

Electrophoresis was the separation method used, adjusted to each marker system. The proteins investigated were mostly isozymes, each locus recognized by specific substrates. The DNA fragments were recognized by specific probes and restriction enzymes and in some cases by PCR magnification. Otherwise we refer to the original papers cited in the text. The samples came from the following areas: fin whales (Balaenoptera physalus) mainly from Icelandic and Spanish waters, but smaller numbers for a pilot study from Canadian and Norwegian waters; sei whales (Balaenoptera borealis) only from Icelandic waters; minke whales (Balaenoptera acutorostrata) from Norway, Iceland and West Greenland. Only a few individuals from various other whale species were studied for the purpose of species comparison.

Results

The results presented here are a compilation from our earlier publications from dif-

93 ferent times thus being a review of what we know today about the whale stocks in the North Atlantic The fin whale

Both protein and DNA markers were used in the study. Protein markers

We started investigating esterases of fin whale blood in 1971, concentrating on carbonic anhydrases of the erythrocytes [4]. The total of 1,099 fin whales caught off Iceland were studied in the years 1971, 1981-1989. This system was in HardyWeinberg equilibrium all years except 1985 and 1986. Young males seemed to be responsible for this deviation from the Hardy-Weinberg equilibrium [4,5]. Liver esterases. The liver esterases gave a complex pattern and only the fast moving esterases were of use in this respect. No significant differences were observed between years or locations [4,6]. Liver esterase patterns were on the other hand useful for species comparison. Cardiac esterases. The electrophoretic esterase patterns of cardiac muscle homogenates of fin whales are highly polymorphic. This is discussed in detail in our earlier reports [4,7]. There is a highly significant difference between Iceland and Spain in frequencies of some fractions [4]. If we use the most frequent phenotypes as markers shown in Fig. 1, differences between Iceland and Spain seem obvious and are statistically significant. The differences between years could probably reflect herd structure. It should be borne in mind that we do not know the genetics behind the cardiac esterase patterns, so we are only using these as markers. Genetic variation at 40 enzyme loci in fin whales. Fin whale samples taken in 1985 and under special permit in 1986-1989 were used for an extensive study of isozymes and other markers [4,8]. A total of 31 out of the 38 enzyme systems examined gave adequate staining and resolution. The zymograms have been described

Phenotypes iI

0,8 0,7

II III

0,6 % 0,5 0,4

0,3

i~ !iiiii

0,2 0,1

!.

Fig.

1981 n=169

1982 1983 n=72 n=71 Iceland

1984 n=129

I

I

1983 n=29

1984 n=12 Spain

I

1. A bar chart demonstrating the frequencies of cardiac esterase phenotypes in fin whales caught off Iceland in the years 1981-1984 and in fin whales caught off Spain 1983-1984 [4].

94 Table 1. Allele frequencies of 11 polymorphic enzymes in fin whales caught off Iceland and Spain Locus

Subunit number

Alleles

Allele frequencies Spain 1985

Sample size Ada

(n) 1

Ak-I

(n) 1

Ca

(n) 1

Gpd

(n) 2

Ldh-A

(n) 4

Mdh-S

(n) 2

Mpi

(n) 1

Pep-A

(n) 1

Pgm-1

(n) 1

Pgi

(n) 2

Sod-A

(n) 2

1 2 3 4 1 2 F S 1 2 A A' 1 2 1 2 3 1 2 3 1 2 1 2 3 1 2

46 0.098 0.293 0.152 0.457 33 0.636 0.364** 24 0.187 0.813 46 0.533 0.467 46 0.674 0.326** 40 0.562 0.438 0.000 45 0.611 0.389 0.000 45 0.100 0.900 46 0.858 0.109 0.033 46 0.315 0.685

Iceland 1985

Iceland 1986

65 49 0.085 0.069 0.231 0.139 0.330 0.271 0.354*** 0.521"** 64 67 0.164 0.172 0.836*** 0.828*** 145 0.276 0.724* 65 0.138 0.862 65 72 0.531 0.729 0.469 0.271 65 72 0.669 0.299 0.331 0.701"* 60 62 0.133 0.113 0.867 0.887 0.000 0.000 20 71 0.725 0.676 0.275 0.317 0.000 0.007*** 65 59 0.108 0.153 0.892 0.847 63 70 0.937 0.915 0.063 0.064 0.000 0.021 65 72 0.208 0.312 0.792 0.688

Iceland 1987

78 0.032 0.346 0.109 0.513"** 73 0.192 0.808*** 78 0.814 0.186 78 0.147 0.853 78 0.038 0.949 0.013 73 0.610 0.370 0.020*** 74 0.101 0.899* 78 0.911 0.051 0.038 78 0.391 0.609

Iceland 1988

68 0.081 0.279 0.051 0.588** 61 0.492 0.508*** 68 0.801 0.198 68 0.044 0.956 68 0.140 0.838 0.022 58 0.715 0.241 0.430** 65 0.262 0.738 68 0.919 0.037 0.044 68 0.140 0.860

Danfelsd6ttir et al. [8]. Significant deviations in genotypic frequency from Hardy-Weinberg I (*) and the sample size (n). *0.01 < P < 0.05; **0.001 < P < 0.01; ***P < 0.001; -, not screened.

p r e v i o u s l y . I n fin w h a l e s a m p l e s c a u g h t o f f I c e l a n d a n d S p a i n , t h e 31 e n z y m e s r e p r e s e n t 4 0 l o c i o f w h i c h 11 ( 2 7 . 5 % ) w e r e p o l y m o r p h i c b y t h e 0 . 9 5 c r i t e r i o n f o r p o l y m o r p h i s m , i.e. t h e r a r e a l l e l e h a d a f r e q u e n c y o f at l e a s t 0.05. A l l e l e f r e q u e n c i e s f o r t h e p o l y m o r p h i c loci in fin w h a l e s a m p l e s are l i s t e d in T a b l e 1. In f i n w h a l e s , t h e

95 loci suitable for the chi-square goodness-of-fit test for the Hardy-Weinberg equilibrium were: Ada, Ak-1, Ca, Gpd, Ldh-A, Mdh-S, Mpi-1, Pep-A, Pgm-1, Pgi and Sod-A. Where the expected number of a given genotypic frequency was <5 and df = 1, the Yates correction was applied. In cases where the expected number was ~<3 and df > 1, the frequency values for certain genotypes were pooled [9]. Most of the chi-square values were found to be non-significant, indicating no deviation from the Hardy-Weinberg equilibrium. There were, however, significant differences between observed proportions and Hardy-Weinberg expectations in 16 of the 48 comparisons. It can be seen from Table 1 that the majority of these differences were observed at the Ada, Ak-1 and Pep-A loci. Some deviations between expected and observed values were also noted at the Ca, Pgm-1 and Mdh-S loci. All the significant deviations from the expected proportions are due to an excess of homozygotes. The amount of genetic variation found at the enzyme loci in fin whales is shown in Table 2. The observed average heterozygosity values were calculated for 12 variable enzyme loci plus 28 invariant loci and ranged from 0.064 to 0.077 in fin whales caught in different years off Iceland (1985-1988) with a mean of 0.071 (SD = 0.005). The average heterozygosity was 0.089 in those caught off Spain in the year 1985. The genetic differences between the samples were calculated using the genetic distance coefficient (D) of Nei [10] based on allele frequencies at all loci examined. The mean genetic distance between Icelandic fin whale samples from the years 1985-1988 was 0.010. The genetic distance between the Icelandic and the Spanish samples caught in 1985 was 0.013. When comparing Icelandic samples from all the years (1985-1988) with the Spanish samples from 1985, the mean D value was higher at 0.020. An unweighted pair group arithmetic average (UPGMA) cluster analysis [11] of the D values gave the dendrogram in Fig. 2.

Spain 1985 Iceland 1985 Iceland 1986 Iceland 1987 Iceland 1988 I

,

0.03

,

,

,

I

,

0.02

i

i

i

I

0.01

. . . .

t

0.00

Genetic distance Fig. 2. An UPGMAdendogramshowingthe relationships of North Atlantic fin whale samples based on Nei's unbiased geneticdistance coefficient(D) of 39 loci [8].

96 A pilot study was carried out on samples from Nova Scotia, Newfoundland (kept frozen since 1972), Iceland (scientific catch 1988) and from the Barents Sea (biopsy samples, 1991). These preliminary results indicate that the fin whales from these areas are different populations (Danfelsd6ttir, personal communication) judged from the statistical analysis using the BIOSYS-1, Fortran-77 computer program by Swofford and Selander [12]. DNA markers The M H C genes. We have demonstrated limited polymorphism of MHC genes of

two cetacean species [13]. Human class I and class II probes were used to study major histocompatability complex (MHC) genes from fin and sei whales. Stronger signals were obtained on whale than on an equivalent concentration of mouse DNA. Evidence was obtained for several DRB-related genes, a DNA gene, one DQA gene and multiple class I genes in the two species. The whale genes were less polymorphic than those of human and mice. No difference was found between the few samples from fins caught off Spain and those caught off Iceland. The sample size was too small for a population study. The importance of this system is mainly related to immunogenetics, and this may reflect the lack of polymorphism in fins and seis due to different immunological stimulus in the sea compared with terrestrial mammals. The C4 genes. We used human C4 cDNA probes to investigate the complement component C4 gene in fin, sei and minke [14]. Restriction mapping of genomic DNA shows the presence of only one gene (locus) in these species. The C4 gene is polymorphic in fin and sei, which could be used in population studies. Only 31 fins and 22 seis were investigated for the same restriction enzyme. The study of DNA samples available from mother-foetus pairs from the two polymorphic species showed a simple two allele transmission. Sei whales

We could only study sei whales from Icelandic waters. In our first investigation in 1981-1984 we found less variation in cardiac esterases in sei whales than fin whales [7]. In another study [8] of 40 isozyme loci from 101 animals caught in the years 1985-1988, seven loci proved to be polymorphic or 17.5%. There was less heterozygosity than in fins, H = 0.047 (see Table 2). No significant differences in Table 2. The average heterozygosity in fin whales caught and Spain and in sei whales caught off Iceland

Fin whales Sei whales

Spain

Iceland

Iceland

Iceland

Iceland

Iceland

1985

1985

1986

1987

1988

Mean

SD

0.089 -

0.077 0.039

0.070 0.049

0.064 0.042

0.071 0.036

0.071 0.047

0.005 0.011

Danfelsd6ttir et al. [8]. - , no data available.

97 Table 3. The multilocus G-test values for the pairwise comparison of all frequencies between Icelandic sei whale samples from different sample years Locus

1985-1986

Ldh-A Ada Mdh-S Mpi Pep-A Pgm-1 Total

1986-1987

1987-1988

1985-1988

G

df

G

df

G

df

G

df

5.15 2.72 1.15 0.19 7.02 1.12 17.35

2 2 2 2 2 5 15

0.30 0.59 0.62 9.43 4.88 1.64 17.46

2 2 2 2 2 5 15

1.57 1.22 1.44 1.68 1.10 0.03 7.04

2 2 2 2 2 5 15

6.83 9.70 11.37 15.42 10.33 2.13 55.78

6 6 6 6 6 15 45

Danfelsddttir et al. [8]. No significant differences between sample years were observed.

allele frequencies between years were observed nor any deviation from HardyWeinberg equilibrium as shown in Table 3. The sei whale population is very uniform. Minke whales

This species is discussed only briefly in this review as this is dealt with in this volume by Danfelsd6ttir. The isozyme studies [15] indicate that the minke whales from West Greenland, Iceland and Norway represent different populations (Fig. 3). We used human hypervariable region probe and Alu I endonuclease to study variability in minke whales from these regions. The fingerprinting results are shown in Table 4 and support the existence of separate populations in those areas [16].

W. Greenland

Iceland

Norway

I

i

0.020

.

,

.

r

.

0.015

.

.

.

t

.

0.010

.

.

.

I

.

0.005

.

.

.

I

0.000

Genetic distance Fig. 3. An U P G M A dendogram showing the relationships of North Atlantic minke whale samples based on Nei's unbiased genetic distance coefficient (D) of 27 loci [15].

98

Table 4. DNA fingerprinting of minke whales using Alu I endonuclease alpha-globin 3'HVR probe (range 4.3-24kb) Country

Plate No.

No. of f animals

x

q

h

p

Iceland

45 43 46 46

19 10 7 36 11

1.79 _+0.42 1.90 _+0.32 2.00 _+0 1.86 _+0.35 1.54 _+0.50

0.15 0.16 0.21 0.16 0.18

0.0724 0.0770 0.1000 0.0789 0.0863

0.9624 0.9600 0.9470 0.9589 0.9549

0.0335 0.0307 0.0441 0.0346 0.0713

48

20

1.85 _+0.37

0.027

0.0134

0.9935

0.0013

Iceland total Norway (Barent Sea) West Greenland (Davis Strait)

,/~rnason and Spilliaert [ 16]. f, mean number of resolvable fragments obtained after digestion of minke whale genomic DNA with Alu I + SD. x, probability that a fragment present in one individual is also present in a randomly chosen individual. q, calculated mean population frequency of the resolvable alleles, assuming x = 2q - q2 h, mean probability for a fragment to be in heterozygous state, h = 2q(1 - q)/(2q q 2 ) = 2(lq)/(2 - q). p, mean probability that all fragments detected in an individual A are also present in another individual B,p =xf. -

Hybridization between blue and fin whale W h a l e r s have c l a i m e d for a long time that there existed h y b r i d s b e t w e e n blue and fin w h a l e s [17]. In the scientific catch under special p e r m i t in 1986 was a f e m a l e b a l a e n o p t e r i d w h a l e with external characteristics o f both blue and fin whale. This a n i m a l carried a foetus. It was also clear that this was its second p r e g n a n c y as j u d g e d f r o m the status o f the ovary. M o l e c u l a r analysis o f c o m p l e m e n t factor 4 (C4) and several other m a r k e r s d e m o n s t r a t e d clearly that the animal was indeed a h y b r i d b e t w e e n the two largest animals on earth, the blue and the fin w h a l e (Fig. 4), and m t D N A analysis s h o w e d that the father o f the foetus was a blue w h a l e [18]. T w o b a l a e n o p t e r i d males caught in 1983 and 1989 p r o v e d to b e h y b r i d s b e t w e e n the t w o a b o v e - m e n t i o n e d species. O n e o f these had a blue w h a l e m o t h e r and a fin w h a l e father, the other had a fin w h a l e m o t h e r and a blue w h a l e father j u d g e d f r o m the m t D N A which is u s u a l l y inherited f r o m the m o t h e r only. T h e difference b e t w e e n the m i t o c h o n d r i a l c y t o c h r o m e b gene o f the blue and fin suggests that the two species s e p a r a t e d / > 3 . 5 million y e a r s ago. The sequences o f the m i t o c h o n d r i a l control region o f blue and fin w h a l e s differ b y 7%. The difference in the m t D N A control r e g i o n b e t w e e n three blue w h a l e m t D N A h a p l o t y p e s was ~< 1%, about one-tenth o f the difference b e t w e e n the two species [19]. F i g u r e s 5 and 6 show the ventral side of male blue/fin h y b r i d and a m a l e fin, respectively.

DNA fingerprinting of fin whales in the North Atlantic Ocean using human hypervariable region probe, alpha-globin 3 'HVR A s d e m o n s t r a t e d earlier [20], the h u m a n a l p h a - g l o b i n 3 ' H V R p r o b e was useful for D N A fingerprinting fin and sei. The e n d o n u c l e a s e H i n f I gave the highest n u m b e r o f

99

kb 3.5 3.0 2.7 2.5

1.8 1

2

3

4

Fig. 4. Southern blot assay of DNA, digested with the restriction endonuclease Taq I, and probed with a C4 cDNA of human origin: 1, fin whale; 2, blue/fin hybrid; 3, blue whale; 4, foetus of the hybrid whale.

DNA fractions in fin whales, Alu I and Rsa I in sei whales. It can be deduced from this that the probability of finding two identical fins is 1:1.3 x 106 and for sei 1:6,250, when the endonucleases Hinf I and Alu I were used, respectively. This demonstrates great genetic variation in fins, which is also found in the enzyme systems [8].

Discussion

It can be seen from Fig. 2 that the different sample years of Icelandic fin whales show more genetic similarities than the Icelandic and Spanish fin whale samples. The genetic variation observed in fin whales caught off Iceland and off Spain is higher than that described in general for other mammals. Ayala [21] has summarised the genetic variation in 30 mammalian species and finds the average heterozygosity H = 0.051 and the average proportion of polymorphic loci P = 0.206. In fin whales caught off Iceland, H = 0.071 and for fin whales caught off Spain the value is higher at H = 0.089. The proportion of loci polymorphic is the same for both groups at P = 0.275 (40 loci investigated). Our H-values for fin whales are also higher than previously reported values by Wada and Numachi [22] for the North Pacific and the Antarctic fin whale stocks (H=0.017 and P=0.138, 13 loci investigated). The

100

Fig. 5. The ventral side of a male blue/fin hybrid whale caught in Icelandic waters in 1989. Compare the ventral coloration with that of the fin whale in Fig. 6 (photo by ,~rni Alfre~sson, 1989).

Fig. 6. A male fin whale in the same position as the hybrid whale in Fig. 5 (photo by Sveinn GuSmundsson, 1989).

101 observed genotypic frequencies at most of the loci revealed non-significant deviations from those expected by the Hardy-Weinberg equilibrium in Icelandic and Spanish fin whales. However, at three loci the observed genotypic frequencies between years in Icelandic fin whales differed significantly from that expected in most of the comparisons which were made. The deviations from the HardyWeinberg expectations were all due to deficiency in heterozygotes, which could point to substructure in the population. The G-values of the genetic homogeneity tests show significant differences between all the sample years in fin whales from Iceland and also between the samples from Iceland 1985 and Spain 1985. The G-values between the sample years 1985-1986 and 1986-1987 in fin whales from Iceland, show less difference than the G-value between samples from Iceland 1985 and Spain 1985, although the sample years 1987-1988 show a greater difference. This is hard to interpret at the population level, but may indicate that some variation exists in sampling of different breeding herds between whaling seasons. The genetic distance between samples of fin whales from Iceland 1985 and Spain 1985 (D = 0.013) is greater than the mean D value calculated between Icelandic sample years 1985-1988 (D = 0.010). The D value (D = 0.013) between the Icelandic and Spanish fin whales is smaller than that found between geographically isolated populations in other mammalian species, D = 0.058 [21], but within the range of previously reported values between populations of Cetacea [22], the values ranging from 0.0003 to 0.0885. The finding that the genetic distance between samples from the two areas (Iceland 1985 and Spain 1985) is greater that that found between Icelandic sample years, suggests that the Icelandic and Spanish samples represent two different stocks. Most population genetic studies involve only a single year comparison between populations. Nevo [24] reports that marine vertebrates have significantly higher average heterozygosity (H=0.061, 21 species) than terrestrial vertebrate species ( H = 0.041, 70 species) but that they share similar polymorphism, P = 0.203 (15 species) and P = 0.180 (74 species), respectively. The amount of genetic variation in fin and sei whales in Danfelsd6ttir et al. [8] (H = 0.069 and P = 0.225) agrees with Nevo' s findings and the large value of H implies that the fin and the sei whales have an unbroken history in the Northeast Atlantic. The value of genetic distance between fin and sei whales (D = 0.098) is lower than the mean value reported on species of mammals in general, D = 0.232 [23] but higher than the smallest genetic distance found between two whale species, striped dolphin (Stenella coeruleoalba) and spotted dolphin (Stenella attenuata), D = 0.026 and also higher than the D value between sei and Bryde's whales, D = 0.047 [23]. The genetic distance between cetacean species, as demonstrated by this review and other studies [8,22,23] appears to be less than the genetic distances previously reported between other mammalian species. The above-mentioned results support that fin whales and minke whales from the sample areas represent different populations; this is also supported by morphometric studies [25,26] and tagging experiments [27].

102

Conclusions The genetic marker studies indicate that: 1. fin whales from Canada, Iceland, Norway and Spain are different populations with substructures; 2. sei whales in Icelandic waters are a homogenous population; 3. minke whales from West Greenland, Iceland and Norway are separate populations; 4. heterogeneity is high in the three species in protein as well as DNA markers indicating an unbroken history in the area; 5. genetical relationship is close between the three species; 6. hybridization between blue whales and fin whales occurs and the hybrid can be fertile; 7. MHC genes are less polymorphic in fin and sei whales than in most terrestrial mammals reflecting a different immunogenic environment in the sea.

Acknowledgements I wish to thank all my co-authors over the years who have made this review possible. I also want to thank those working on the flencing platform for their assistance as well as the crews of the whaling boats for their help. Grants from Hvalur Ltd. over the years, which made these studies possible, are gratefully acknowledged.

References 1. R6rvik C J, Jonsgard A. Review of balaenopterids in the North Atlantic Ocean. FAO Fish Ser (Mammals in the Seas) (5) 1981 ;3:269-286. 2. Donovan GP. A review of IWC stock boundaries. Rep Int Whal Commn 1991;(Special Issue 13):39~58. 3. Sergeant DE. Stocks of fin whales Balaenopteraphysalus L. in the North Atlantic Ocean. Rep Int Whal Commn 1977;27:460-473. 4. Arnason A, Danielsd6ttir AK, Spilliaert R, SigurSsson JH, J6nsd6ttir S, P~ilsd6ttir A, Duke EJ, Joyce P, Groves V, Trowsdale J. A brief review of protein and DNA marker studies in relation to the stock identity of fin whales (Balaenoptera physalus) from Iceland and Spain (SC/F91/F16). Rep Int Whal Commn 1992;42:701-705. 5. Arnason A, Spilliaert R. Study of carbonic anhydrase polymorphism in fin whales (Balaenoptera physalus) caught off Iceland and comparison with five other species of whales: Sei (B. borealis), minke (B. acutorostrata), sperm (Physeter catodon), killer whale (Orcinus orca) and pilot whale (Globicephala melaena) (SC/39/O18). Rep Int Whal Commn 1988;38:514. 6. Spilliaert R, Arnason A. A progress report on an electrophoretic study of liver esterases in fin whales from Icelandic and Spanish waters (SC/40/Ball). Rep Int Whal Commn 1989;39: 463. 7. Arnason A, J6nsd6ttir S. An electrophoretic study of cardiac esterases and proteins of fin whales (Balaenoptera physalus) from Icelandic and Spanish waters and sei whales (Balaenoptera borealis) caught off Iceland (SC/39/Ba6). Rep Int Whal Commn 1988;38:507.

103 8. Danfelsd6ttir AK, Duke EJ, Joyce P,/trnason A. Preliminary studies on genetic variation at enzyme loci in fin whales (Balaenoptera physalus) and sei whales (B. borealis) from the North Atlantic. Rep Int Whal Commn 1991;(Special Issue 13):115-124. 9. Sokal PR, Rohlf FJ. Biometry, 2nd edn. San Francisco, CA: Freeman, 1981 ;859 pp. 10. Nei M. Genetic distance between populations. Am Nat 1972;106:283-292. 1 I. Sneath PHA, Sokal RR. Numerical Taxonomy. San Francisco, CA: Freeman, 1973;573 pp. 12. Swofford DL, Selander RB. BIOSYS-1. A computer program for the analysis of allelic variation in population genetics and biochemical systematics. Champaign, IL: Illinois Natural History Survey, 1989;43 pp. 13. Trowsdale J, Groves V, /~rnason A. Limited MHC polymorphism in whales. Immunogenetics 1989;29:19-24. 14. Spilliaert R, P~lsd6ttir ,/~, Arnason A. Analysis of the C4 genes in baleen whales using a human cDNA probe. Immunogenetics 1990;32:73-76. 15. Danfelsd6ttir AK, Duke EJ, ,~rnason A. Genetic variation at enzyme loci in North Atlantic minke whales (Balaenoptera acutorostrata). Biochem Genet 1992;30:189-202. 16. ,~rnason A, Spilliaert R. A study of variability in minke whales (Balaenoptera acutorostrata) in the North Atlantic using a human hypervariable region probe, a-globin 3'HVR. Rep Int Whal Commn 1991 ;41:439-443. 17. Cocks AH. The fin whale fishery of 1886 on the Lapland coast. The Zoologist 1887;11:207-222. 18. Spilliaert R, Vfkingsson G, ,~rnason lJ, P~ilsd6ttir A, Sigurj6nsson J,/~rnason A. Species hybridization between a female blue whale (Balaenoptera musculus) and a male fin whale (B. physalus): molecular and morphological documentation. J Hered 1991;82:269-274. 19. Arnason 0, Spilliaert R, P~ilsd6ttir A, Arnason A. Molecular identification of hybrids between the two largest whale species, the blue and the fin whale. Hereditas 1991 ;115:183-189. 20. Arnason A. Hvalastofnar og erf6amork. Landvernd: Hi6 fslenska n~ittfirufr~eOif61ag, 1993;351 pp. 21. Ayala FJ. Population and Evolutionary Genetics. Menlo Park, CA: Benjamin/Cumming, 1982;268 PP. 22. Wada S, Numachi K. Allozyme analysis of genetic differentiation among the populations and species in Balaenoptera. Rep Int Whal Commn 1991 ;(Special issue 13): 125-154. 23. Wada S. Genetic differentiation between two forms of short-finned pilot whales off the Pacific coast of Japan. Sci Rep Whal Res Inst 1988;39:91-101. 24. Nevo E. Genetic variation in natural populations: patterns and theory. Theoret Popul Biol 1978;13:121-177. 25. Jover L. Biometrical discrimination between Icelandic and Spanish stocks of fin whales (Balaenoptera physalus). Rep Int Whal Commn 1987;37:394. 26. Christensen I, Haug T, Wiig O. Morphometric comparison of minke whales Balaenoptera acutorostrata from different areas of the North Atlantic. Mar Mammal Sci 1990;6:327-338. 27. Gunnlaugsson Th, Sigurj6nsson J. Analysis of the North-Atlantic fin whale marking data from 1979-1988 with special reference to Iceland. Rep Int Whal Commn 1989;39:383-388.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

105

Genetic variation in northeastern Atlantic minke whales (Balaenoptera ac utorostrata ) Anna K. Danfelsd6ttir l, Sverrir D. Halld6rsson ~, Sigfrf6ur Gu61augsd6ttir 1 and Alfre6/krnason 2 1Marine Research Institute, Reykjavfk, Iceland; and 21mmunogenetics Unit, Department of Pathology, University Hospital, Reykjavfk, Iceland Abstract. Background: the population structure of North Atlantic minke whales (Balaenoptera acutorostrata) was studied in a previous study by Danfelsd6ttir et al. [1]. It was concluded that bigger sample sizes were needed in order to determine if whales from the northeastern Atlantic represent a different population to the West Greenland and Icelandic whales, respectively. Methods: genetic variation within northeastern Atlantic (Norwegian) minke whales was investigated and compared with genetic variation in minke whales from West Greenland and Iceland using isozyme analysis. Results: in the Norwegian minke whale liver samples, 37 enzyme loci were examined, of which eight were found to be polymorphic. The average heterozygosity was 0.060 (SE = 0.021). Significant deviations from the Hardy-Weinberg genotypic frequencies were observed at two loci in the liver samples. In gonad samples, 28 enzyme loci were examined and significant deviations from expected frequencies were observed at two loci, which could be due to small sample size of the gonads. Contingency Z2 analysis revealed significant differences in allele frequencies between the Norwegian minke whales and minke whales from West Greenland and Iceland, respectively. Wright's FST value was 0.111 and the genetic distance was 0.015 between minke whale liver samples from West Greenland and Norway. The FST value was 0.149 and the genetic distance was 0.028 between minke whale gonad samples from Iceland and Norway. Conclusions: the genetic differences between minke whales from Norway, West Greenland and Iceland indicated that the Norwegian minke whales represent a different breeding population from the West Greenland population and the Icelandic population, respectively. Key words: population genetics, isozyme analysis, population structure, stocks, genetic variability, genetic distance

Introduction

The minke whale (Balaenoptera acutorostrata) is widely distributed in the North Atlantic but their division into populations is unclear. Their northern geographical range is limited by the polar ice and their southern limit is thought to reach as far as the Mediterranean on the eastern side of the North Atlantic and south of the coast of Florida on the western side [2]. They migrate north in the spring and early summer to their feeding grounds and south again in the autumn to their breeding grounds. The North Atlantic minke whales have been divided into four management stocks by the International Whaling Commission [3]: (1) the Canadian East coast stock, (2) the West Greenland stock, (3) the Central stock (Icelandic whales) and (4) the

Address for correspondence: A.K. Danfelsd6ttir, Marine Research Institute, c/o Biotechnology IceTec, Keldnaholt, IS-112 Reykjav~, Iceland.

106 northeastern stock (Norwegian whales). This division is based on methods such as catch statistics, studies on biological characteristics and tagging. A study by Christensen et al. [4] using statistical analysis of morphometric data to identify North Atlantic minke whale populations revealed some differences in parameters measured between minke whales from West Greenland, Icelandic and Norwegian waters. However, it was considered that no clear stock division could be identified because of the high degree of overlapping characters between the groups. An isozyme study of the genetic variation in North Atlantic minke whales, including samples from West Greenland (West Greenland stock), Icelandic (Central stock) and Norwegian waters (northeastern stock) indicated that the genetic differences between samples from the three areas represented different breeding populations. However, due to small sample size of Norwegian minke whales, it was noted that more extensive study using larger sample sizes was needed, and that possible tissue specificity of zymograms could result in larger deviation of the relative genetic distances between Icelandic samples and samples from the other areas [ 1]. Differences in variability in DNA fingerprinting of minke whale samples from West Greenland, Iceland and Norway (Barents Sea) using human a-globin 3'HVR probe, supported the existence of three different populations in these areas [5]. Population genetic studies of minke whales using electrophoretic analysis of isozymes have been carried out on North Atlantic minke whales by S imonsen et al. [6] and Arnason et al. [7], on Antarctic minke whales by Wada and Numachi [8], on Japanese coastal minke whales by Wada [9] and on Pacific and Antarctic minke whales by Wada and Numachi [ 10]. Other population genetic studies on minke whales include methods such as mtDNA D-loop sequencing, mtDNA restriction fragment analysis (mtDNA RFLP), ribosomal DNA RFLP, repetitive satellite DNA and single locus DNA variation [ 11-

15]. The present study describes the genetic variation in minke whale samples from Norway (northeastern stock) using electrophoretic analysis of isozymes. The Norwegian samples came from four main areas, along the west of Spitsbergen and Bear Island (ES area), Barents Sea (EB area), Norwegian coast (EC area) and the North Sea (EN area). The genetic variation in Norwegian minke whales is compared with the isozyme data of North Atlantic minke whales (West Greenland and Central stock) contained in Danfelsd6ttir et al. [ 1]. The genetic variation in liver and kidney samples from West Greenland and Norway and gonad samples from Iceland and Norway were examined in order to investigate the genetic variation and population structure of North Atlantic minke whale samples.

Materials and Methods

Minke whale samples were collected during the Norwegian scientific catch 1988 (EB and EC areas), 1989 (ES and EC areas), 1990 (EB and EC areas), 1992 (ES, EB and EC areas), 1993 (ES, EB, EC and EN areas) and 1994 (EN area). The samples

107 f r o m the 1985 w h a l i n g season in N o r w a y , Barents Sea (EB) w e r e supplied b y Ivar Christensen, Institute of M a r i n e Research, B e r g e n , N o r w a y . S a m p l e s w e r e stored at - 2 0 ~ in N o r w a y , transported to Iceland by air on dry ice and stored a t - 2 0 ~ until analysed. A total of 279 N o r w e g i a n m i n k e w h a l e tissue s a m p l e s o f liver, k i d n e y and g o n a d f r o m 220 individuals were analysed (Table 1). T h e i s o z y m e data on W e s t G r e e n l a n d / D a v i s strait and Icelandic coastal m i n k e whales w e r e obtained f r o m Danielsd6ttir et al. [ 1]. A total of 40 individuals of m i n k e w h a l e s a m p l e s f r o m W e s t G r e e n l a n d and Iceland w e r e also r e - a n a l y s e d in this study, as a control for the c o m p a r i s o n of the i s o z y m e data c o n t a i n e d in Danfelsd6ttir et al. [1]. T h e s a m e m e t h o d s as described in Danfelsd6ttir et al. [1 ] and Danfelsd6ttir [16] w e r e used for p r e p a r i n g the samples for electrophoresis and c a r r y i n g out the i s o z y m e analysis. Table 2 lists the 29 e n z y m e s y s t e m s e x a m i n e d , the a b b r e v i a t i o n s used, the

Table 1. The location, tissue type and number of North Atlantic minke whale samples

Location

Year

Tissue type Liver

West Greenland b

1980 1982 1983 Total

Iceland b

1981 1982 1983 1984 1985 Total

28 22 50

Kidney

Gonads a

8 2 19 29 18 22 25 41 8 114

Norway

Barent's Sea EB

Spitsbergen ES Coastal EC

North Sea EN

1985 1988 1990 1992 1993 1989 1992 1993 1988 1989 1990 1992 1993 1993 1994 Total

12 1 2 39 12 15 35 27 25 1 3 18 18 5 7 220

2 12 24 1 2 41

aNumbers in parentheses are samples that are being analysed at present. bSamples analysed in the study by Danfelsd6ttir et al. [ 1]

(39) (12) (35) (27) 15 3 (18) (18) 167

108

Table 2. Enzymes screened for in North Atlantic minke whales (Balaenoptera acutorostrata), their Enzyme Commission numbers (EC No.), minimum number of loci, the optimal electrophoresis methods employed and the staining method references Enzyme

Abbrev.

EC No.

No. of loci

Optimum buffer system (%)a

Staining Tissue method reference T O L K

Adenosine deaminase Adenylate kinase Alcohol dehydrogenase Aspartate aminotransferase Creatine kinase Esterase Fructose- 1.6-diphosphatase Fumarase Glucose dehydrogenase Glucose-6-Ph. dehydrogenase Glutamate dehydrogenase Glyceraldehyde phosph, deh. a-Glycerophosphate dehydrog. Hexokinase Isocitric dehydrogenase Lactate dehydrogenase Malate dehydrogenase Malic enzyme Mannose phosphate isomerase Nucleoside phosphorylase Peptidase A Peptidase B Peptidase C Phosphoglucomutase 6-Phosphogluconate dehydrog. Phosphoglucose isomerase Sorbitol dehydrogenase Superoxide dismutase Xanthine oxidase

ADA AK ADH AAT CK EST F16DP FH GDH G6PD GLUD GAPDH GPD HK IDH LDH MDH ME MPI NP PEPA PEPB PEPC PGM 6PGDH PGI SDH SOD XO

3.5.4.4 2.7.4.3 1.1.1.1 2.6.1.1 2.7.3.2 3.1.1.1 3.1.3.11 4.2.1.2 1.1.1.47 1.1.1.49 1.4.1.3 1.2.1.12 1.1.1.8 2.7.1.1 1.1.1.42 1.1.1.27 1.1.1.37 1.1.1.40 5.3.1.8 2.4.2.1 3.4.11 .* 3.4.11 3.4.11 2.7.5.1 1.1.1.44 5.3.1.9 1.1.1.14 1.15.1.1 1.2.3.2

1 2 1 2 2 1

PAGE(15) PAGE(12) PAGE(5) PAGE(4) AM PAGE(7)

[21] [22] [22] [22] [24] [22]

+ + + -+ -

+ + + + + + + + + + + + + + - + +

1

AM

[22]

-

-

+

+

1 1 1 1

PAGE (3) TCB PAGE(7) TVB

[20] [22] [20] [23]

+ + + +

w + + +

+ + + +

+ + w +

1

AM

[22]

+

+

+

w

1

AM

[24]

+

+ -

1

AM

[22]

+

+

+

+

2 2 2 2 1

AM PAGE(5) PAGE(5) AM PAGE(12)

[22] [25] [20] [20] [21]

+ + + + +

+ + + + +

+ + + + +

+ + + + +

1

AM

[21]

+

+

+

+

1 1 1 1

PAGE(7) PAGE(9) PAGE(9) PAGE(9)

[22] [22] [22] [22]

+ + + +

+ + + +

+ + + +

+ + + w

1

AM

[22]

+

+

+

+

1

PAGE(4)

[22]

+ + + +

1

AM

[22]

- -

4 1

PAGE(7) PAGE (5)

[26] [27]

+ + + + - - + -

+

+

w

aoptimum buffer system: AM, citrate-aminopropylmorpholine (pH 6.3), modified from [17]; PAGE, polyacrylamide gel electrophoresis; Tris-glycine (pH 8.9) [ 18]; TCB, Tris-citrate-borate (pH 8.6) [ 19]; TVB, Tris-versene-borate (pH 8.0) [20]. Tissues: T, testis; O, ovaries; L, liver; K, kidney. Staining appearance: +, staining,-, no staining; w, weak staining. o p t i m a l e l e c t r o p h o r e t i c m e t h o d s a n d r e f e r e n c e s f o r t h e s t a i n i n g m e t h o d s . A l l t h e statistical a n a l y s i s o f t h e e l e c t r o p h o r e t i c d a t a w a s c a r r i e d o u t u s i n g B I O S Y S - 1 ,

Fortran-

7 7 c o m p u t e r p r o g r a m b y S w o f f o r d a n d S e l a n d e r [28].

Results

Genetic variation within samples T h e 29 e n z y m e s y s t e m s e x a m i n e d in t h e N o r w e g i a n m i n k e w h a l e s a m p l e s r e p r e s e n t 3 9 loci. S o m e o f t h e e n z y m e s y s t e m s f a i l e d to g i v e a d e q u a t e s t a i n i n g a n d r e s o l u t i o n

109 required in this study. They were a-glycerophosphatase (GPD) and peptidase C (PEPC) in liver samples, 6-phosphogluconate dehydrogenase (6PGDH) and xanthin oxidase (XO) in kidney samples and aspartate aminotransferase (AAT), esterase (EST), fructose-l,6-diphosphatase (F16DP), sorbitol dehydrogenase (SDH) and XO in gonad samples. In the Norwegian liver, kidney and gonad samples 27, 27 and 24 enzyme systems represent 37, 37 and 28 loci, respectively. The following six loci were found to be polymorphic in all three tissue types of the Norwegian minke whales: Ada, Ak-1, Mdh-S, Mpi and Pep-B. In addition, the liver samples were polymorphic at Adh, AatS and Ldh-A loci (eight loci in all) and variable at three loci: Est, Pep-A and Pgi. The kidney samples, in addition, were polymorphic at Aat-S, Ldh-A and Pep-A (eight loci in all) and the gonad samples at Pep-A (six loci in all). Two of the loci (Ldh-A and Mdh-S) were excluded from statistical analyses of minke whale liver samples, as the readings of these loci were ambiguous in some of the Norwegian samples and their analysis needs to be repeated. Table 3 summarises the amount of genetic variation found at the enzyme loci in the West Greenland, Icelandic and Norwegian liver, kidney and gonad samples. The mean sample size per locus, the mean number of alleles per locus, number of loci examined, the percentage of polymorphic loci by the 0.95 criterion for polymorphism and the average heterozygosity, both average observed (direct count) and the Table 3. The average heterozygosity at enzyme loci in North Atlantic minke whales

Tissue

Mean sample size per locus

West Greenland Liver 49.9 (0.1) Kidney 28.2 (0.6) Iceland Gonads

112.0 (1.1)

Norway Liver

216.0

Kidney

43.5

Gonads

15.0

(1.0)

Mean no. of alleles per locus

No. of loci

1.2 (0.1) 1.2 (0.1)

37

Percent of polymorphic loci, pa

Average heterozygosity (H) H (SE) direct count

H (SE) H-W expected b

16.2

0.061 (0.025)

0.057 (0.023)

29

17.2

0.045 (0.023)

0.044 (0.019)

1.3 (0.1)

29

20.7

0.074 (0.027)

0.076 (0.028)

1.4

37

21.6

0.053 (0.018)

0.060 (0.021)

1.3

35

22.9

0.081 (0.029)

0.083 (0.028)

1.3

28

21.4

0.086 (0.038)

0.074 (0.029)

(0.1)

(0.3)

(0.1)

(o.o)

(o.1)

P, polymorphism by the 0.95 criterion; H, average heterozygosity (including invariant loci); SE, standard error. aA locus is considered polymorphic if the frequency of the most common allele does not exceed 0.95. b Hardy-Weinberg expected: unbiased estimate [29].

110

Table 4. Allele frequencies at variable loci in North Atlantic minke whales and x2-values (df = 1) for deviation from Hardy-Weinberg equilibrium Locus

Subunit no.

Alleles

Ada

1

(n)

Ak-1

1

~ d h

2

Aar-S

1

Est

1

West Greenland liver Obs. freq.

I 2 3 (n) 1 2 3

(4 I

2 (n) 1 2 3

(4

1 2 3

50 0.3 10 0.610 0.080 50 0.210 0.780 0.010 50 0.040 0.960 50 0.060 0.940 0.000 50 0.000 1.000 0.000

X2

P

2.19

0.14

0.31

0.58

0.06

0.08

0.17

0.68

Iceland gonadsa Obs. freq.

x2

111 0.113 0.887 0.000 0.12 109 0.500 0.500 0.000 1.21 87 0.236 0.764 0.20 87#

114#

Norway gonads

Norway liver

P

0.73

0.27 0.66

Obs. freq. 213 0.042 0.484 0.474 215 0.126 0.874 0.000 211 0.066 0.934 208 0.065 0.933 0.002 207 0.022 0.973 0.005

X2

P

1.17

0.28

6.95

0.008**

0.24

0.62

0.25

0.61

Obs. freq15 0.033 0.333 0.633 15 0.067 0.933 0.000 15 0.000 1.OOO 15#

15# 0.00

I.00

x2

P

1.01

0.20

0.04

0.84

Ldh-A

4

(n)

Mdh-S

2

(n) 1

Mpi

1

Pep-A

1

Pep4

1

A A*

2 (n) 1 2 3 (n) 1 2 (n) 1

Pgi

NP

2

2

2

(4

1 2 8 (4 1

2

df, degrees of freedom. n, number of individuals analysed. #, Aat-S and Est did not stain in gonad samples; !, Samples need to be re-analysed for Ldh-A and Mdh-S loci. *0.01 < P < 0.05, **0.001 < P < 0.01, ***P < 0.001. aData from DanielsdBttir et al. [I].

111

112 average calculated heterozygosity according to the unbiased H by Nei [29]) are listed. In the Norwegian minke whales, the average percentage of polymorphic loci was 21.6% in liver, 22.9% in kidney and 21.4% in gonad samples. The average heterozygosity for the Norwegian samples was 0.060 (0.021) in liver, 0.083 (0.028) in kidney and 0.074 (0.029) in gonad samples. The contingency Z2 statistical analyses of sex heterogeneity of allele frequencies were carried out. Significant differences were observed between males and females in the Norwegian liver samples, at the Ada and Ak-1 loci (Z2 at 34 loci = 45.52, df = 12, P < 0.001). The locus Pep-B was not in H-W equilibrium within the male sample group and was therefore excluded from this comparison. The sex ratio was 0.491 for females. The variable loci in liver and gonad samples from West Greenland, Iceland and Norway, their allele frequencies and the Z2 goodness of fit test for the HardyWeinberg equilibrium are listed in Table 4. Kidney samples were also analysed but the data are not represented here. The liver samples were chosen for the comparison between West Greenland and Norwegian areas on the grounds of bigger sample size. Significant differences in observed frequencies from those expected by the HardyWeinberg equilibrium were detected at Ak-1 and Pep-B loci (P < 0.01) in Norwegian liver samples both due to heterozygote deficiency and at Mdh-S and Pep-A locus (P < 0.05) due to heterozygote excess and deficiency, respectively, in Norwegian gonad samples (Table 4). The Norwegian liver samples (n = 220) had seven unique alleles at the Aat-S, Est, Pep-A, Pep-B and Pgi loci, not found in the West Greenland liver samples (n = 50). The Norwegian gonad samples (n = 15) had three unique alleles at the Ada, Pep-A and Pep-B loci not found in the Icelandic gonad samples (n = 114).

Genetic differentiation The heterogeneities in allele frequencies between liver samples from West Greenland and Norway and gonad samples from Iceland and Norway were tested using the contingency Z2 table and the Wright's F-statistics (Fsx) analyses [28]. The heterogeneities of Z2 values between areas are presented in Table 5. The total Z2 values for the differences in allele frequencies between samples were highly significant (P < 0.001) both between liver samples from West Greenland and Norway (Z2= 105.15, d f - 11) and between gonad samples from Iceland and Norway (Z2= 289.46, d f - 11) (Table 5). No contingency Z2 analysis was done between West Greenland and Icelandic samples as common tissue types were not available. Wright's Fsv values for the polymorphic loci in the West Greenland-Norwegian comparison varied between 0.000 and 0.241 and the mean value was 0.111 which means that 11.1% of the total gene diversity (HT = 0.106) is attributed to differences between sample areas and 88.9% of the genetic variation is due to within total sample variability. In the Icelandic-Norwegian comparison, the FsT values for the polymorphic loci varied between 0.009 and 0.342 and the mean value was 0.149. The total gene diversity was HT = 0.135.

113 Table 5. Contingency ~2 analysis of allele frequencies at enzyme loci between North Atlantic minke whale samples

Locus

Minke whale samples West Greenland and Norway liver

Ada Ak-1 Adh

Aat-S Est Ldh-A Mdh-S Mpi Np Pep-A Pep-B Pgi

Total for all loci

)(;2 df )(;2 df ~2 df )(;2 df )(;2 df )~2

df Z2 df )~2 df ~2 df ~2 df )C2 df ~2 df ~2 df

96.40"** 2 _ 0.97 1 0.27 2 2.71 2 _

_ 0.04 1 _ 3.82 1 0.93 2 105.15"** 11

Iceland and Norway gonads 152.09" 2 20.03*** 1 8.85* 1 _

0.99 1 4.76 2 1.51 1 50.03*** 1 46.69*** 1 289.46*** 11

df, degrees of freedom. * 0.01 < P < 0.05, ** 0.001 < P < 0.01, *** P < 0.001. T h e g e n e t i c differentiations b e t w e e n the s a m p l e s f r o m W e s t G r e e n l a n d a n d N o r w a y and also b e t w e e n I c e l a n d and N o r w a y w e r e c a l c u l a t e d u s i n g the u n b i a s e d genetic d i s t a n c e c o e f f i c i e n t (D) of Nei [29] b a s e d on the allele f r e q u e n c y o f 37 a n d 27 c o m m o n loci, r e s p e c t i v e l y . T h e D v a l u e c a l c u l a t e d b e t w e e n s a m p l e s f r o m W e s t G r e e n l a n d a n d N o r w a y was 0.015. T h e D v a l u e b e t w e e n s a m p l e s f r o m I c e l a n d a n d N o r w a y w a s 0.028. T h e U P G M A d e n d r o g r a m in Fig. 1 w a s b a s e d on the a b o v e listed D values.

Discussion Genetic variation within samples

T h e g e n e t i c variation in the N o r w e g i a n m i n k e w h a l e s , H = 0 . 0 6 0 ( S E = 0 . 0 2 1 ) a n d

114

0.03 I

0.02 i

I

0.01

I

I

0.00

I

I

I

West Greenland (liver)

Norway (liver) Norway (gonads)

Iceland (gonads)

i

0.03

i

i

0.02

I

I

0.01

I

I

0.00

Nei's genetic distance (D).

Fig. 1. A UPGMA dendrogram showing the relationships of North Atlantic minke whale samples from West-Greenland, Iceland and Norway, based on Nei's [29] unbiased genetic distance coefficient (D).

P = 0 . 2 1 6 is within the range of previously reported values in minke whale populations (Table 6). The average H of North Atlantic minke whales from this study and Danfelsd6ttir et al. [1] is H = 0.064 (SE = 0.023). Wada and Numachi [10] reported a range from H = 0.020 to 0.087 in three minke whale populations and Simonsen et al. [6] reported H = 0 . 0 4 6 ( S E = 0 . 0 1 0 ) in West Greenland minke whales. The average heterozygosity in 19 baleen whale populations ranged from H = 0.003 to 0.087 (mean average H = 0.042, SE = 0.029) (Table 6). The low H value for the small form minke whale, H = 0.003 [10] could be due to the small sample size (n = 8). Table 6 summarises the average heterozygosity for four baleen whale species, H = 0.043 [1,6,10,16,30] and for 13 toothed whale species, H = 0.056 [31-35]. The genetic variation in marine mammals is H = 0.041 (30 species) and P = 0.150 (26 species) [ 1,6,10,16,30-44], which is similar to what Nevo et al. [45] summarised for mammals in general, H = 0.041, SD = 0.035 (184 species) and P = 0.191 (181 species). The amount of genetic variation in North Atlantic minke whales is within the range of previously reported average values for H and P in marine mammals and mammals. The range of heterozygosity values appears to be broad in whale populations which agrees with Nevo et al. [45] who report that the intraspecific and interspecific H and P values range widely in mammals (184 species) and that the level of genetic variation may differ more within than between taxa.

115 Table 6. Summary of the genetic variation in mammalian species and populations

Groups

No. of species

No. of loci

P0.95

H (SE)

References

0.191 0.150 0.175 0.179 0.171

0.041 0.041 0.049 0.056 0.043

(0.035) (0.035) (0.038) (0.046) (0.029)

[1,6,10,16,30--44] [1,6,10,16,30-35] [31-35] [1,6,10,16,30]

0.222 0.044 0.179 0.095 a 0.162 0.207 0.216 0.204

0.087 0.020 0.052 0.046 0.057 0.074 0.060 0.057

(0.024) (0.011) (0.018) (0.010) b (0.023) (0.028) (0.021) (0.021)

[ 10] [ 10] [10] [6] [1] [ 1] This study [1,6,10 and this study]

P/H

Mammals Marine mammals Whales Toothed whales Baleen whales Minke whales Antarctic ocean Japan coastal Korean coastal West Greenland West Greenland Iceland Norway Mean

181/184 26/30 17 13 4 45 45 39 21 37 29 37

[45]

P, polymorphism by the 0.95 criterion; H, average heterozygosity, unbiased estimate [29]" SE, standard error. a By the 0.99 criterion. b By direct count method.

The observed significant deviations in observed genotypic frequencies from those expected by the Hardy-Weinberg equilibrium were detected at two of the eight polymorphic loci in Norwegian liver samples and were due to heterozygote deficiency, suggesting that the samples are not taken from a homogeneous population. Samples were taken in different areas in the Northeast Atlantic, in different seasons and years and might contribute to the observed heterogeneity within the Norwegian samples. Further statistical analyses on the subdivided samples are needed, in order to study the observed heterogeneity. Deviations from the H-W equilibrium at the Mdh-S and Pep-A loci in gonad samples could be explained by a small sample size (n = 15).

Genetic differentiation The contingency Z2 analyses revealed highly significant differences in allele frequencies between liver samples from West Greenland and Norway and between gonad samples from Iceland and Norway. This indicates that the samples from Norway are from a different population than the samples from West Greenland and Iceland, respectively. The degree of heterogeneity between samples of minke whales measured by Wright's FST indicated restricted gene flow between the samples. The FST was similar to fin whale samples from two locations (Iceland and Spain, FST = 0.10) and higher than found between fin whale sample years (FsT = 0.07) [ 16]. This is similar to the findings of Arnason and Spilliaert [5]. They examined the variability in the North Atlantic minke whales by using the human a-globin 3'HVR (hypervariable region) probe. Morphological studies on minke whales from these

116 three areas [4] also revealed some differences in samples between areas. PalsbOll [12] used restriction fragment analysis of mtDNA and ribosomal DNA to identify samples of minke whales from West Greenland and the northeastern Atlantic (Norway). His findings revealed no significant difference between the two areas and he concluded that either there was a co-existence of two matemal lineages within one random mating population or an existence of two distinct breeding aggregations in one common feeding area. Our findings, however, do not indicate any mixing of breeding populations at the feeding areas. The genetic distance between minke whale liver samples from West Greenland and Norway, D = 0.015 was less than the genetic distance between gonad samples from Iceland and Norway, D = 0.028. The genetic distance between North Atlantic minke whale populations is within the lower range of what was reported between populations of Antarctic and Pacific minke whales, D = 0.0125 to D = 0.0885 by Wada and Numachi [ 10]. The distance between Icelandic and West Greenland minke whale samples was not calculated because no common tissue types were available. Only gonad samples were available from the Icelandic minke whales and liver and kidney samples from West Greenland. Deviations of the relative genetic distance between Norway and the other areas could occur since the tissue types are not the same between the two comparisons. Also it should be noted that only 15 gonad samples were available from Norway and more samples need to be examined for better evaluation of the genetic differences between minke whales from Iceland and Norway. The level of genetic differentiation between minke whales from Norway and both West Greenland and Iceland indicates that the Norwegian minke whale samples (northeastern stock) represent a different population from that of West Greenland and Icelandic (Central stock) minke whales, respectively. Study of the population structure of northeastem Atlantic minke whales is underway and further statistical analyses of the different sample areas, seasons and years are in process, as well as the study of more gonad samples from the northeastern area for comparisons with Icelandic gonad samples.

Acknowledgements We would like to thank Mr. Sverrir Sverrisson for assisting with the laboratory work and Dr. J6n M. Einarsson for professional support and encouragement. This research was supported by funding from the Norwegian Fisheries Research Council.

References 1. Danfelsd6ttirAK, Duke EJ, Arnason A. Genetic variation at enzyme loci in North Atlantic minke whales, Balaenoptera acutorostrata. Biochem Genet 1992;30:189-202. 2. ROrvikCJ, Jonsghrd A. Review of balaenopterids in the North Atlantic ocean. F.A.O. Fish Ser (5) Mammals in the Seas 1981;3:269-286.

117 3. Donovan GP. A review of IWC stock boundaries. Rep Int Whal Commn 1991;(Special Issue 13):39-68. 4. Christensen I, Haug T, Wiig 0. Morphometric comparison of minke whales (Balaenoptera acutorostrata) from different areas of the North Atlantic. Mar Mammal Sci 1990;6:327-338. 5. A,rnason A, Spilliaert R. A study of variability in minke whales (Balaenoptera acutorostrata) in the North Atlantic using a human hypervariable region probe, alpha-globin 3'HVR. Rep Int Whal Commn 1991;41:439-443. 6. Simonsen V, Kapel F, Larsen F. Electrophoretic variation in the minke whale, Balaenoptera acutorostrata Lacepede. Rep Int Whal Commn 1982;32:275-278. 7. Arnason A, Danfelsd6ttir AK, Spilliaert R, SigurOsson JH, J6nsd6ttir S, P~ilsd6ttir A, Duke EJ, Joyce P, Groves V, Trowsdale J. A brief review of protein and DNA marker studies in relation to the stock identity of fin whales (Balaenoptera physalus) from Iceland and Spain. Rep Int Whal Commn 1991 ;42:701-705. 8. Wada S, Numachi K. External and biochemical characters as an approach to stock identification for the Antarctic minke whale. Rep Int Whal Commn 1979;29:421-432. 9. Wada S. Genetic structure and taxonomic status of minke whales in the coastal waters of Japan. Rep Int Whal Commn 1983;33:361-363. 10. Wada S, Numachi K. Allozyme analyses of genetic differentiation among the populations and species of the Balaenoptera. Rep Int Whal Commn 1991;(Special Issue 13): 125-154. 11. Hoelzel AR, Dover GA. Mitochondrial D-loop DNA variation within and between populations of the minke whale (Balaenoptera acutorostrata). Rep Int Whal Commn 1991;(Special Issue 13):171-182. 12. PalsbOll PJ. Restriction fragment length polymorphism in the ribosomal genes of minke whales, Balaenoptera acutorostrata, from the Barents sea and West Greenland and restriction fragment pattern analysis of mitochondrial DNA in minke whales, Balaenoptera acutorostrata, from the Davis Strait and the Northeast Atlantic. Master Thesis, University of Copenhagen, 1989. 13. Wada S, Kobayashi T, Numachi KI. Genetic variability and differentiation of mitochondrial DNA in minke whales. Rep Int Whal Commn 1991;(Special Issue 13):203-216. 14. Amos B, Dover GA. The use of satellite DNA sequences in determining population differentiation in the minke whale. Rep Int Whal Commn 1991;(Special Issue 13):235-244. 15. vanPijlen I, Amos W, Dover GA. Multilocus DNA fingerprinting applied to population studies of the minke whale Balaenoptera acutorostrata. Rep Int Whal Commn 1991;(Special Issue 13):245254. 16. Danfelsd6ttir AK. Genetic variation among different species and populations of baleen whales from the North Atlantic Ocean. Ph.D. Thesis, University College Dublin, Ireland, 1994. 17. Clayton JW, Tretiak DN. Amine-citrate buffers for pH control in starch gel electrophoresis. J Fish Res Board Can 1972;29:1169-1172. 18. Davis BJ. Disk electrophoresis- II. Methods and application to human serum proteins. Ann NY Acad Sci 1964; 121:404--427. 19. Taggart J, Ferguson A, Mason FM. Genetic variation in Irish populations of brown trout (Salmo trutta L.): electrophoretic analysis of allozymes. Comp Biochem Physiol 1981;69B:393-4 12. 20. Siciliano MJ, Shaw SR. Separation and visualisation of enzymes on gels. In: Smith I (ed) Chromatographic and Electrophoretic Techniques, Vol. II. London: Heinemann, 1976; 185-209. 22. Harris H, Hopkinson DA. Handbook of Enzyme Electrophoresis in Human Genetics. Amsterdam: North-Holland, 1976. 23. Shaw CR, Prasad R. Starch gel electrophoresis of enzymes. A compilation of recipes. Biochem Genet 1970;4:297-320. 24. Brewer GJ. An Introduction to Isozyme Techniques. London: Academic Press, 1970. 21. Meera Khan P, Rijken H, Wijnen JT, Wijnen LMM, De Boer LEM. 4. Red cell enzyme variation in the orangutan: electrophoretic characterisation of 45 enzyme systems in cellogel. In: de Boer LEM, Junk W (eds) The Orang Utan. Its Biology and Conservation. The Hague, 1982;61-108.

118 25. Shaklee JB, Kepes KL, Whitt GS. Specialised lactate dehydrogenase isozymes: the molecular and genetic basis for the unique eye and liver LDHs of teleost fishes. J Exp Zool 1973;185:217-240. 26. Crouch R, Priest DG, Duke EJ. Superoxide dismutase activities of bovine ocular tissues. Exp Eye Res 1978;27:503-509. 27. Yen TTT, Glassman E. Electrophoretic variants of xanthine dehydrogenase in Drosophila melanogaster. Genetics 1965 ;52:977-981. 28. Swofford DL, Selander RB. BIOSYS-1. A computer program for the analysis of allelic variation in population genetics and biochemical systematics. Champaign, IL: Illinois Natural History Survey, 1989. 29. Nei M. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 1978;89:583-590. 30. Danfelsd6ttir AK, Duke EJ, Joyce P, /~rnason A. Preliminary studies on the genetic variation at enzyme loci in fin whales (Balaenoptera physalus) and sei whales (Balaenoptera borealis) from North-Eastern Atlantic. Rep Int Whal Commn 1991;(Special Issue 13): 115-124. 31. Shimura E, Numachi K. Genetic variability and differentiation in the toothed whales. Sci Rep Whales Res Inst 1987;38:141-163. 32. Andersen LW. Electrophoretic differentiation among local population of the long-finned pilot whale, Globicephala melaena, at the Faroe Islands. Can J Zool 1988;66:1884-1892. 33. Wada S. Genetic heterozygosity in the striped dolphin off Japan. Rep Int Whal Commn 1983;33:617-619. 34. Wada S. Genetic differentiation between two forms of short-finned pilot whales off the Pacific coast of Japan. Sci Rep Whales Res Inst Tokyo 1988;39:91-101. 35. Winans GA, Jones LL. Electrophoretic variability in Dall's porpoise (Phocoenoides dalli) in the North Pacific ocean and Bering Sea. J Mammal 1988;69:14-21. 36. Bonnell ML, Selander RK. Elephant seals: genetic variation and near extinction. Science 1974; 184:908-909. 37. Gales NJ, Adams M, Burton HR. Genetic retardness of two populations of the southern elephant seal, Mirounga leonina. Mar Mammal Sci 1989;5:57-67. 38. McDermid EM, Ananthakrishnan R, Agar NS. Electrophoretic investigation of plasma and red cell proteins and enzymes of Macquarie Island elephant seals. Anim Blood Groups Biochem Genet 1972;3:85-94. 39. Shaughnessy PD. An electrophoretic study of blood and milk proteins of the southern elephant seal, Mirounga leonina. J. Mammal 1974;55:796-808. 40. McDermid EM, Bonner WN. Red cell and serum protein systems of grey seals and harbour seals. Comp Biochem Physiol 1975;50B:97-101. 41. Testa JW. Electromorph variation in weddell seals (Leptonychotes weddelli). J Mammal 1986;67:606-610. 42. Lidicker WZ, Sage RD, Calkins DG. Biochemical variation in northern sea lions from Alaska. In: Smith MH, Joule J (eds) Mammalian Population Genetics. Athens, GA: University of Georgia Press, 1981 ;231-241. 43. Simonsen V, Allendorf FW, Eanes WF, Kapel FO. Electrophoretic variation in large mammals. III. The ringed seal, Pusa hispida, the harp seal, Pagophilus groenlandicus, and the hooded seal, Cystophra cristata. Hereditas 1982;97:87-90. 44. Simonsen V, Born EW, Kristensen T. Electrophoretic variation in large mammals. IV. The Atlantic walrus, Odobenus rosmarus rosmarus (L.). Hereditas 1982;97:91-94. 45. Nevo E, Beiles A, Ben-Shlomo R. The evolutionary significance of genetic diversity: ecological, demographic and life history correlates. In: Mani GS (ed) Evolutionary Dynamics of Genetic Diversity, Proceedings, Manchester, 1983. Berlin: Springer-Verlag, 1984; 13-213.

9 1995 ElsevierScience B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand ~. Ulltang, editors

119

Preliminary results of a DNA-microsatellite study of the population and social structure of the harbour porpoise Liselotte Wesley Andersen l, Lars-Erik Holm 2, Bjarne Clausen 3 and Carl C. K i n z e 4 l lnstitute of Biological Sciences, Department of Genetics and Ecology, University of Aarhus, Denmark; 2Department of Animal Physiology and Biochemistry, National Institute of Animal Science, Foulum, Denmark; 3Danish Environmental Research Institute, Denmark; and 4Zoological Museum, University of Copenhagen, Denmark Abstract. A total of 106 specimens were used in the analysis of the subdivision into genetically differentiated subpopulations of the harbour porpoise, Phocoena phocoena, occurring in inner Danish waters (IDW), North Sea and West Greenland using PCR amplified DNA microsatellites. To date, two polymorphic microsatellites, 417/418 and insulin-like growth factor-I (IGF-I), were detected, consisting respectively of 8 and 15 alleles. Deviations from the expected Hardy-Weinberg distribution were observed at the IGF locus in the North Sea sample and subsamples from the North Sea, and in the West Greenland male sample. All the North Sea samples showed a surplus of homozygotes which could be explained by a Wahlund effect; the mixing of several subpopulations or non-random mating illustrated by straying males from different breeding areas in the North Sea. The analysis of the genetical population structure performed by Monte-Carlo simulations showed that harbour porpoises from West Greenland are geographically differentiated from harbour porpoises in IDW and North Sea. It was not possible with the present sample size and number of microsatellite loci to differentiate between harbour porpoises in IDW and the North Sea. Key words: cetaceans, Danish waters, genetic structure, nuclear markers, polymerase chain reaction, 417/418 primer set, insulin-like growth factor-I, Monte Carlo simulations

Introduction Growing concern about the health of the porpoise populations in the Northeast Atlantic is accentuated by the apparently high incidental mortality of porpoises and by the lack of knowledge about the impact this may cause to the natural growth rates of the populations [1]. To evaluate the potential impact, it is at least necessary to estimate the magnitude of the incidental mortality and the pregnancy rate, to estimate the abundance and distribution of the harbour porpoise population in the given region and to estimate genetical differentiation among subpopulations and the gene flow between them. The only analysis available at present on the genetical population structure of the Danish harbour porpoises is that of Andersen [2], which was based on allozyme data. The present preliminary study concerns the above-mentioned estimate of the subdivision into genetically differentiated subpopulations and the processes that influence subdivision of the harbour porpoise occurring in inner Danish waters (IDW) Address for correspondence: L.W. Andersen, Institute of Biological Sciences, Department of Genetics and Ecology, University of Aarhus, Denmark.

120 and the North Sea using DNA microsatellites. Microsatellite loci vary in the number of repeats consisting of usually di-nucleotide sequences and are highly polymorphic, often with up to more than a dozen alleles per locus [3,4]. Because the array of microsatellite repeats is generally shorter than 300 base pairs [5], it is possible to use the polymerase chain reaction (PCR) to amplify a single locus.

Materials and Methods Muscle tissues from 106 stranded and incidentally caught harbour porpoises were used in the analysis representing three supposed populations/subpopulations, West Greenland, inner Danish waters and the North Sea. All the individuals in the Greenlandic sample, the North Sea sample and most of the individuals in the IDW sample were analyzed by allozyme electrophoresis by Andersen [2]. The additional individuals were collected by H.H. Dietz, National Veterinary Laboratory, Aarhus, Denmark. Mating in harbour porpoises takes place in July to August [6] suggesting that porpoises collected in summer represent an interbreeding subpopulation. Two microsatellite primers were used. One flanks the simple sequence locus 417/418 described by Schl0tterer et al. [7] and Amos et al. [8] in long-finned pilot whales (Globicephala melas) and the other is situated in the promoter region of the insulin-like growth factor I (IGF-1) in cattle and pigs, where it is polymorphic [9]. The microsatellites were fluorescently labelled and analyzed on a 6% denaturing polyacrylamide gel using the ALF TM DNA Sequencer (Pharmacia LKB) (Fig. 1). At the 417/418 locus, 8 alleles were detected ranging in size from 162 to 180 base pairs (upper fluorogramme, Fig. 1). This microsatellite was originally found to be polymorphic with 3 alleles in the long-finned pilot whales [8]. At the IGF-I locus 15 alleles were detected ranging in size from 94 to 154 base pairs (lower fluorogramme). Figure 1 gives an example of four different genotypes at each locus and the top indicated at 118 base pairs is one of the internal markers.

Statistical analysis The test for deviations from expected Hardy-Weinberg distributions was performed with a permutation test. The genes are distributed independently into genotypes by shuffling and the array found is one of several under the assumed Hardy-Weinberg equilibrium with allele frequencies of the array identical to the original sample. This test was conducted using a computer-package developed by H.R. Siegismund, The Arboretum, The Royal Veterinary and Agricultural University, HCrsholm, Denmark. Monte-Carlo simulations were also used in the analysis of the geographical differentiation to generate the expected Chi-square distribution if the homogeneity, Ho, was true for a given data set [10]. This was performed by using the MONTEprogram from the REAP-package on each locus [11 ] and testing the combined probability of the exact probabilities of the two loci. Where multiple tests were run, the sequential Bonferroni test was applied [ 12] to give table-wide significance levels.

121

locus 417/418

17/Oct/94

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0 8 ' 5 5 ' 37

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Data n Base Pa~r ]

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"

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120

160

140

180

2O0

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Genotypes: 33=8/9; 34=4/8; 35=6/8; 36=9/11 Fig. 1. Fluorogramme.

2OO

122 T h e g e o g r a p h i c d i f f e r e n t i a t i o n w a s a l s o a n a l y z e d w i t h W r i g h t ' s F - s t a t i s t i c s [13] f r o m w h i c h it is p o s s i b l e to o b t a i n a g e n e f l o w e s t i m a t e ( e f f e c t i v e n u m b e r o f m i grants

per

generation).

Fs.r--1/(1 + 4 N m )

in W r i g h t ' s

infinite

Island

model,

if

m < < 1. T h e F s x o v e r t h e t w o m i c r o s a t e l l i t e l o c i w a s e s t i m a t e d u s i n g W e i r a n d Cockerham's

[ 14] u n b i a s e d e s t i m a t o r , O . T h i s e s t i m a t o r g i v e s a r e a s o n a b l e m e a s u r e

f o r N m w i t h m o d e r a t e l e v e l s o f g e n e f l o w a n d r e a s o n a b l y l a r g e s a m p l e s i z e s [ 15].

Table 1. Tests for Hardy-Weinberg expectations based on permutation tests [18,19]. The observed and expected G-values from the goodness of fit to the Hardy-Weinberg distribution are compared to simulated values. N = sampler size, H o and H e = observed and expected heterozygosity, F = (H e Ho)IHe, P = probability of the goodness of fit after 1,000 simulations. Locality

Locus

N

Ho

He

Inner Danish waters (IDW)

IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418 IGF 417/418

57 57 49 49 45 45 54 54 32 32 23 23 34 34 18 18 25 25 21 21 33 33 10 10 16 16 106 106 37 37 11 11 17 17

0.8247 0.5263 0.7755 0.6122 0.7778 0.6444 0.8148 0.5185 0.7500 0.6563 0.7826 0.5217 0.8529 0.5294 1.0000 0.5556 0.6800 0.5600 0.7619 0.5238 0.8485 0.5152 1.0000 0.5000 0.6875 0.6250 0.8019 0.5660 0.7838 0.6757 0.7273 0.4545 0.8235 0.6471

0.8717 0.6131 0.8669 0.5891 0.8686 0.6062 0.8673 0.6118 0.8616 0.6255 0.8478 0.6219 0.8689 0.6051 0.8549 0.5664 0.8525 0.5808 0.8424 0.6145 0.8650 0.6070 0.8200 0.5700 0.8457 0.6230 0.8728 0.6053 0.8046 0.6775 0.7769 0.6116 0.7958 0.6765

North Sea North Sea a IDW summer North Sea summer IDW females IDW males North Sea females North Sea males IDW summer females IDW summer males North Sea summer females North Sea summer males Total IDW + North Sea Greenland summer W. Greenland summer females W. Greenland summer males

F 0.0540 0.1416 0.1055 -0.0392 0.1046 -0.0631 0.0605 0.1525 0.1297 -0.0492 0.0769 0.1611 0.0184 0.1251 -0.1697 0.0191 0.2026 0.0358 0.0956 0.1476 0.0191 0.1513 -0.2195 0.1228 0.1871 -0.0031 0.0813 0.0648 0.0259 0.0027 0.0638 0.2568 -0.0348 0.0435

P 0.1200 0.4180 0.0190" 0.4240 0.0590 0.4650 0.0930 0.5100 0.0240* 0.3280 0.2640 0.5560 0.1820 0.5330 0.9730 0.7010 0.0030* 0.2090 0.2470 0.6050 0.2110 0.4560 0.8530 0.5080 0.0080* 0.2000 0.2590 0.7330 0.0520 0.2020 0.7910 0.0770 0.0130* 0.4360

aNorth Sea sample minus 4 individuals landed on the same date (17 November 1980) and in the same harbour.

123 Results and Discussion

Table 1 shows the significant deviations from the Hardy-Weinberg expectations for the harbour porpoise in the North Sea, IDW and West Greenland as totals and when they are divided into locality, season and sex. Significant deviations from HardyWeinberg expectation were observed only at the IGF-I locus in 5 cases. In 4 cases, all subsamples of the North Sea total sample based either on season or sex, a clear Wahlund-effect was observed, as found by Andersen [2]. This observation could be explained by a mixing of several subpopulations in the North Sea or non-random mating. The homozygote excess is caused by males in the North Sea which also supports earlier findings. One hypothesis that explains this observation is that female harbour porpoises return to the same breeding area every year while males stray, returning to different breeding areas in the North Sea, indirectly suggesting the existence of several breeding areas and several subpopulations. Males in the IDW sample, on the contrary, seem to return to the breeding areas in the inner Danish waters indicating that this group is a reminiscence of a Baltic Sea subpopulation. Figure 2 pictures the distribution of the allele frequencies of the sample totals and when dividing into summer-samples for IDW and North Sea. At the IGF-I locus, one private allele was observed in the North Sea sample and one in the IDW sample. At the 417/418 locus, a private allele was found only in the IDW sample. Private alleles can be used to estimate gene flow in terms of Nm [ 16] in species with low to moderate gene flow (Nm < 10). Rare and private alleles might also imply population structure, i.e. the occurrence of allele 15 at the IGF-I locus and allele 8 at the 417/418 locus in the IDW sample might be diagnostic for an IDW subpopulation. Meanwhile since the frequencies of these alleles are equal to the probability of the occurrence of individuals carrying the alleles in the population (IDW) and the sample sizes are small, it is impossible to conclude that the allele does not also exist elsewhere. More polymorphic microsatellite loci and a larger sample size should be analyzed to evaluate this possibility. In Table 2 the geographical heterogeneity among the three assumed populations of harbour porpoises based on permutation tests [10,11] is given whenever allele counts could be used. In three incidences, genotypes were used because deviation from Hardy-Weinberg expectation was observed. The test for geographical heterogeneity between the West Greenland, IDW and North Sea samples was significant (P < 0.007) indicating the existence of geographical subpopulations. In Andersen [2], a seasonal effect influenced the genotypic distribution at the PGM locus, which corresponded well to a formerly described seasonal migration of harbour porpoises out of the Baltic and into the North Sea in winter [17]. As a result of this observation, the geographical differentiation was tested among summer samples giving a highly significant difference (P < 0.00009). A pairwise comparison between IDW, North Sea and West Greenland and the respective subgroups based on season showed that both total and summer samples of the IDW and North Sea are geographically differentiated from the West Greenland sample. This was expected but it was not possible to detect this differentiation in the allozyme study. In the pairwise

124

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125 Table 2. Tests for allele-frequency differences among the three supposed populations of harbour porpoise based on permutation tests [ 10] Locality

Chi-square

P

W. Greenland-IDW-North Sea a W.Greenland-IDWSU-North Sea summer genotypes North Sea a Inner Danish waters - W. Greenland summer Inner Danish waters North Sea a W. Greenland summer - W. Greenland summer I D W summer - North Sea summer genotypes I D W summer - W. Greenland summer genotypes North Sea summer North Sea female I D W female - W. Greenland summer female I D W summer female North Sea summer female - W. Greenland summer female I D W summer female - North Sea summer female

16.29 18.53 4.72 15.02 Undef. Undef. 10.11 18.28 3.13 9.10 5.39 2.68

0.0026* 0.00097** 0.3173 0.0046* 0.0000"** 0.0000"** 0.0386 0.00109** 0.5350 0.0580 0.2402 0.6127

-

-

-

The probability for each locus was combined and the Chi-square values are given along with the new P values (df = 4). a North Sea sample minus 4 individuals landed on the same date (17 November 1980) and in the same harbour. For table-wide significance ***P < 0.00009, **P < 0.0011, *P < 0.007.

comparison, on the other hand, it was not possible to differentiate between the IDW summer sample and the North Sea summer sample. Geographic differentiation of the three populations also was estimated in terms of Wright's F-statistics. An Fsx = 0.008 was found, which indicated a low degree of genetic substructure in the total sample of the three assumed subpopulations. The gene flow estimate was Nm = 31 which is high. One problem here is the high number of alleles at each locus and the following lack of some genotypes in many cases. This might require a larger sample size when Weir and Cockerham's estimator for Fsx is used. Another question is whether the harbour porpoise is capable of migrating over very long distances such as between West Greenland and IDW and the North Sea, so the estimated gene flow might only be between IDW and the North Sea.

Conclusion

The preliminary analysis of the genetic population structure of the harbour porpoise in Danish waters and West Greenland based on two microsatellite loci showed that harbour porpoises from West Greenland are geographically differentiated from harbour porpoises in inner Danish waters and the North Sea. It is not possible with the present sample size and number of microsatellite loci to differentiate between harbour porpoises in the IDW and North Sea. The allozyme study showed a significant deviation between the genotypic distribution of the IDW and North Sea sample. Excess of homozygotes was observed in both studies in the North Sea sample males indicating that the North Sea sample probably consists of several subpopulations figuratively illustrated by males straying from different breeding areas.

126

Acknowledgements We thank all the people involved in collecting material from the harbour porpoises for this study. A special thanks to the staff in the laboratory at the National Institute of Animal Science, Department of Animal Physiology and Biochemistry, Foulum, Denmark for their help during the study. Thanks also to H.R. Siegismund, The Arboretum, Royal Veterinary and Agricultural University, HCrsholm, Denmark for invaluable advice with the statistical analysis, to V. Loeschcke, Department of Genetics and Ecology, University of Aarhus for use of the laboratory and help, to M.M. Hansen and M. Niclasson for constructive discussions and to R. Krebs for reviewing and editing the English. This study was funded by the Danish Natural Science Research Council, Jr.Nr. 11-0642-1. References 1. NMFS, National Marine Fisheries Service. Harbour porpoise in eastern North Atlantic: status and research needs. Northeast Fisheries Science Center Reference Document 92-06. NOAA/NMFS/ NEFSC, Woods Hole, USA: 1992. 2. Andersen LW. The population structure of the harbour porpoise, Phocoena phocoena, in Danish waters and part of the North Atlantic. Mar Biol 1993;116:1-7. 3. Tautz D. Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Res 1989;17:6463-6471. 4. Fornage M, Chan L, Siest G, Boerwinkle E. Allele frequency distribution of the (TG)n(AG)m microsatellite in the apolipoprotein C-II gene. Genomics 1992;12:6368. 5. Rassmann K, Schl6tterer C, Tautz D. Isolation of simple-sequence loci for use in polymerase chain reaction-based DNA fingerprinting. Electrophoresis 1991 ;12:113-118. 6. SCrensen TB, Kinze CC. Reproduction and reproductive seasonality in Danish harbour porpoises, Phocoena phocoena. Ophelia 1994;39:159-176. 7. Schl6tterer C, Amos B, Tautz D. Conservation of polymorphic simple sequence loci in cetaceans species. Nature 1991 ;354:5463-5467. 8. Amos B, Schl6tterer C, Tautz D. Social structure of pilot whales revealed by analytical DNAprofiling. Science 1993;260:670--672. 9. Kirkpatrick BW. Identification of a conserved microsatellite site in porcine and bovine insulin-like growth factor-I gene 5' flank. Anim Genet 1992;23:543-548. 10. Roff DA, Bentzen P. The statistical analysis of mitochondrial DNA polymorphism: chi-square and the problem of small samples. Mol Biol Evol 1989;6:539-545. 11. McElroy D, Moran P, Bermingham E, Kornfield I. REAP. The restriction enzyme analysis package, Version 4.0. Department of Zoology, Migratory Fish Research Institute, Center for Marine Studies, University of Maine, USA, 1991. 12. Rice WR. Analyzing tables of statistical tests. Evolution 1989;43:223-225. 13. Wright S. The genetical structure of populations. Ann Eugen 1951 ;15:323-354. 14. Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution 1984;38:1358-1370. 15. Slatkin M, Barton NH. A comparison of three indirect methods for estimating average levels of gene flow. Evolution 1989;43:1349-1368. 16. Slatkin, M. Rare alleles as indicators of gene flow. Evolution 1985;39:53-65. 17. MChl-Hansen, BU. Investigations on reproduction and growth of the harbour porpoise, Phocoena phocoena (L.), from the Baltic. Vidensk Meddr Dansk Naturh Foren 1954;116:369-396.

127 18. Chakraborty R, Fornage M, Gueguen R, Boerwinkle E. Population genetics of hypervariable loci: analysis of PCR based VNTR polymorphism within a population. In: Burke T, Doff G, Jeffreys AJ, Wolf R (eds) DNA Fingerprinting: Approaches and Applications. Basel, Switzerland: Birkh~iuser Verlag, 1991;127-143. 19. Guo SW, Thompson EA. Performing the exact test for Hardy-Weinberg proportion for multiple alleles. Biometrics 1992;48:361-372. 20. Gaskin, D.E. The harbour porpoise, Phocoena phocoena, (L.). regional populations, status and information on direct and indirect catches. Rep Int Whal Commn 1984;34:569-586.

This Page Intentionally Left Blank

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand ~. Ulltang,editors

129

Photo-identification of the minke whale Balaenoptera acutorostrata off the Isle of Mull, Scotland A. Gill 1 and R.S. Fairbairns 2 1Department of Zoology, Aberdeen University, Aberdeen, UK; and 2Sea Life Surveys, Dervaig, Isle of Mull UK Abstract. Sea Life Surveys, set up by Richard Fairbairns in 1990, conducts research and whale-

watching trips in the waters around the Isle of Mull on the West Coast of Scotland. The main focus of this research is the Minke Whale Balaenoptera acutorostrata and since 1990 a photographic database has been collected containing photographs and sightings information. This database was analysed to evaluate the potential of using photo-identification to identify individual minke whales. Twenty-eight minke whales have been identified using distinguishing features such as dorsal fin notches, scars to the body and lateral body pigmentation. Fifteen whales have been seen at least twice, eleven of which have been sighted in more than 1 year. This suggests that some minke whales show site fidelity in returning to the area in successive years. Ten of the identified whales have been sighted at least twice within 1 year, with eight of these sighted in at least two different months of that year. This suggests that some minke whales are seasonally resident in the waters around Mull. There appears to be no evidence of any exclusive ranges as shown by minke whales in the eastern North Pacific. However, the data suggest that the whales tend to move progressively northwards throughout the season. This could be explained by spatial changes in prey abundance or temporal changes in the whales' selection of diet. Key words: baleen whales, natural marking, fidelity, migration

Introduction The waters to the north and west of Mull in Scotland contain an ecologically diverse marine life. Regularly sighted cetaceans include the minke whale (Balaenoptera acutorostrata), harbour porpoise (Phocoena phocoena), Risso's dolphin (Grampus griseus), common dolphin (Delphinus delphis), and occasional sightings of the killer whale (Orcinus orca). "Sea Life Surveys" was set up in 1990 by Richard Fairbairns conducting research and whale-watching trips covering the waters between Mull, the Scottish mainland (Ardnamurchan Point), Coil, Tiree, Eigg, Muck, Rum and The Treshnish Isles. The main focus of this research is the minke whale and data collected on these trips include details of location, photographs, behavioural observations and details of environmental conditions. The aim of this study is to evaluate the potential for identifying individual minke whales using photographic techniques and to use this photo-identification as a tool to answer various questions about the ecology of the minke whale in the coastal waters around Mull. In particular the aim was to investigate whether individual whales are returning to the study area in successive years, whether they are seasonally resident or transient and to determine the ranges of individual whales in the survey area. Address for correspondence: A. Gill, Department of Zoology, Aberdeen University, Tillydrone Avenue, Aberdeen, UK.

130 Materials and Methods The photographic catalogue consisted of photographs taken during whale-watching seasons from May to October in 1990-1994 by Richard Fairbaims. The survey trips were conducted aboard the 10.5 m M.V. Alpha Beta, equipped with a flying bridge and a global positioning system (GPS). Photographs were taken with a Canon EOS10 35 mm single lens reflex camera equipped with a 300 mm f2.8 lens and a motor drive. Shutter speed was set at 1/1000 s. The film used was Fujicolour 200 ASA Print film and photographs were processed at a commercial photographic laboratory. Black and white prints were sometimes produced from the colour negatives to highlight certain features to aid individual identification, for example, by varying the contrast of the prin-ts, scars and pigmentation of the whale can be enhanced. All the photographs were examined and initially sorted by selecting those photographs which were of sufficient quality for identification purposes. A photograph is considered to be of good quality if the major axis of the whale in the photograph is perpendicular to the photographer and the image is large enough to show various distinguishing features such as fin shape, lateral body pigmentation (three distinct swaths of lighter pigmentation on each side of the minke's body) and body scars. These were then studied for various features in order to distinguish between individual whales and to match resightings. A catalogue of identified whales was established containing all the photographs from the identified sighting and any subsequent resightings. The locations of all the sightings for each identified whale were plotted to investigate the possibility of exclusive ranges and intraseasonal movements.

Results Twenty-eight whales were identified from a total of 671 sightings. The whales were identified by year (1990-1994), and the number of identified sightings per year and the total number of sightings per identified whale is shown in Table 1. Whale no. 11 had a calf with her in 1992 and they were seen together throughout this season. Of the 28 individually identified whales 16 were identified by dorsal fin characteristics, 7 identified by scarring and 5 identified from a combination of lateral body pigmentation patterns, fin shape and small white scars. Fifteen of the identified whales have been sighted at least twice, the greatest number of resightings for one whale is 11. Eleven of these whales have been sighted in more than 1 year and this illustrates that whales are returning to the same area in successive years showing temporal site fidelity. Ten of the identified whales have been sighted at least twice within one or more years, nine of which were sighted in at least two different months in any one year. This suggests that these whales maybe be resident at least seasonally in the waters surrounding Mull. The locations of the identified whales reveal that there is considerable overlap in the ranges of these whales and so there appears to be no evidence of any exclusive

131 Table 1. Whales identified by year, showing the year of sighting and the total number of sightings for each whale ID no.

1990

1991

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Total id/year a

1

3

1

3 1 1 1 1 1 2

1992 2 3 1 1 1 1 1

1993 4 2

1994 1 3

3 1 3 1

4 1 1 1

1

1 1

1 1

1 2

1 2 1 1

1 1 1 1

2

11

11

11

2 1 1 12

Total no. 11 8 1 1 4 5 3 4 1 1 5 3 2 2 1 2 1 2 1 3 2 1 1 1 1 2 1 1

aTotal number of individually identified whales seen in that year.

ranges as shown by minke whales in the eastern North Pacific [1 ]. However, the data suggest that some whales tend to move progressively northwards throughout the season (mean change in latitude from first sighting to last sighting of an individual whale within a year is +9.6404 min north (n = 10)). Discussion This study has shown that photo-identification is a feasible technique for the individual recognition of minke whales in the coastal waters around Mull. The data reveal that from using such techniques, some important aspects of life-history patterns can be understood. The individuals recognised in this study were mainly identified from dorsal fin characteristics such as notches or unusual fin shapes. Dorsey et al. [2] studying minke whales in the eastern north Pacific identified 40% of these whales from dorsal fin features compared to 57% of identified individuals in

132 this study. Dorsey et al. [2] in their study used a smaller boat with greater manoeuvrability than the boat used in our study. The higher percentage of whales thus identified from dorsal fin characteristics in this study may reflect the greater difficulty in obtaining the optimal position for taking photographs that will highlight other features such as lateral body pigmentation and body scarfing. In the eastern north Pacific, Dorsey [2] reports that minke whales have numerous oval scars, thought to be of biological origin. These scars proved to be very useful for identifying individuals in this eastern north Pacific population, but were less useful in this study as very few of the whales photographed in our survey area have these scars. Despite this, several resightings have been achieved allowing some aspects of the life history of the minke whale to be determined. It is very important that this photoidentification work is continued to maintain the photographic database and with further resightings, our knowledge of the life history of the minke whales will be enhanced. The possibility that minke whales show site fidelity may have important implications for the identification of stocks and for the setting of catch quotas because if whaling is resumed it could have a severe effect on local populations. The results from this study imply that a small population of minke whales are resident during the summer around Mull and some of these return year after year. There is a possibility that some of these whales may remain all year round and these whales will probably have different feeding strategies to that of migratory whales. Residency of such a large mobile predator would have important implications in terms of energy and material flow and material cycling in the local ecosystem. The distribution of minke whales throughout the survey area over the season is likely to be in relation to their prey species. The northward progression of the minke whales throughout the season could be explained by a shift in the abundance of prey species or temporal changes in the whale's selection of diet.

References 1. Dorsey EM. Exclusive adjoining ranges in individually identified minke whales (Balaenoptera acutorostrata) in Washington State. Can J Zool 1983;61:174-181. 2. Dorsey EM, Stern SJ, Hoelzel AR, Jacobsen J. Minke whales (Balaenoptera acutorostrata) from the West Coast of North America: individual recognition and small-scale site fidelity. SC/A88/ID21. Rep Int Whal Commn 1990;(Special Issue 12):357-368.

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. Ulltang, editors

133

Parasites as indicators of social structure and stock identity of marine m a m m a l s J.A. Balbuena, F.J. Aznar, M. Fernfindez and J.A. R a g a Department of Animal Biology, University of Valencia, Burjasot, Valencia, Spain A b s t r a c t . Introduction: the use of parasites as biological indicators of marine mammals has not yet received all the necessary attention. The aim of this review is to show the value of parasite data in studies of stock identity and social structure. Methods: the application of the technique to marine mammals is hampered by the lack of control over sampling conditions and the paucity of information about the biology of their parasites. Relevant criteria for suitable parasite tags are discussed. Case studies: previous work on marine mammals is presented to illustrate the usefulness and limitations of parasite data. A study of pilot whales revealed that differences in helminth infections between two groups of pods conformed with previous evidence suggesting separate stocks. Other investigations have provided valuable information about behavioural features of marine mammals. Studies of whale-lice exemplify the advantages of using directly transmitted ectoparasites. Conclusions: the technique has so far proven more successful in behavioural than in population studies. However, parasite analyses have yet to reach their full potential. Improved statistical rigour and the use of molecular techniques applied to the parasites may provide new tools for further studies.

Key words: parasitology, cetaceans, pinnipeds, wildlife, management, conservation

Introduction Parasites have been used successfully as indicators or "markers" of stocks, migrations and other biological aspects of aquatic animals [1 ]. Research in this area is increasing at a remarkable rate. Williams et al. [1] revealed over 140 relevant references from the 1980s versus about 50 from the 1970s, most studies being focussed on commercially important species. Nevertheless, the interest in parasites as biological indicators of marine mammals has experienced a comparable increase. We have found nine references published between 1990 and 1994, whereas there were five from the 1980s and two from previous years. Although these modest figures possibly show the logistic and methodological constraints on research on marine mammals, perhaps they also reflect the fact that this technique has not yet received all the necessary attention from marine mammalogists. Parasite data have been used to study a wide range of biological features of marine mammals, including phylogeny [2], local migrations [3], distribution [4], disease [5], stock identity [6-8] and social behaviour [8-10]. A thorough discussion of all these approaches would probably exceed the space available for this review. This paper is mainly concerned with studies of stock identity and social structure because a good knowledge of these two aspects is essential for management and conservation

Address for correspondence: Juan A. Balbuena, Department of Animal Biology, University of Valencia, Dr. Moliner 50, 46100-Burjassot, Valencia, Spain. Email: [email protected].

134 of wild populations. However, parasitologists are not often aware of this implication. Lester [11] noted that only few papers dealing with fish parasites as tags contained useful information for fisheries managers. Likewise, conservation biologists and wildlife managers frequently do not seem to understand the value of parasite data. The aim of this study is to bridge the gap between parasitologists, marine mammalogists and wildlife managers by showing the value of parasites as indicators of stock identity and social behaviour of sea mammals. We discuss some methodological problems, present previous work to illustrate the advantages and limitations of the technique and provide some guidelines for further work.

Methods

The technique consists basically of the comparison of infections with one or more parasite species between several host groups, which can be arranged according to ecological (stock identity studies) or behavioural (social structure studies) criteria. The analysis is usually based on prevalence (proportion of individuals infected with a particular parasite species [12]), intensity (number of individuals of a given parasite species in each infected host [12]), abundance (mean number of individuals of a particular parasite species per host examined [12]) or presence/absence of parasite species. Occasionally, biochemical or morphometrical differences in the parasites have also been used [ 1,13]. Although studies of parasites as biological indicators are now standard for fishes, caution should be taken in applying the same methods to marine mammals mainly because of sampling limitations and the paucity of information about the parasites' biology.

Sampling Unlike parasitological investigations of fish, there is often little control over sampling conditions. Generally researchers have to rely on unpredictable, occasional strandings or by-catches, which may result in severe sampling biases. For instance, comparisons of parasite infections between host groups might be unreliable if sampling is not simultaneous. There is a risk of mistaking spatial for temporal patterns because parasite infections can vary seasonally or annually. Fish parasitologists can partly overcome this problem by restricting the analysis to one cohort of hosts [ 14]. However, this might be impractical in marine mammal studies because of the usually low sample sizes. Perhaps a more realistic approach is to use data from several parasites simultaneously [11] or limit the study to qualitative (presence/ absence) rather than quantitative differences (e.g. [7]). Generally, parasite occurrences are less sensitive than prevalence and intensity of infection to temporal factors [15]. However, unless this assumption is supported by previous field evidence, the conclusions drawn from these studies are questionable. Variation between samples in sex, age or other host factors may also compromise

135 the analyses. Researchers should ensure that such factors either do not differ significantly between samples or do not affect parasite infections [8].

Parasite selection The success of the analyses depends to a great extend on choosing suitable parasite species as markers. In marine mammal studies, this can be difficult because data on the biology of most parasites are scarce. Different authors have provided the criteria for appropriate parasite tags [1,11,13,14], although in practice some might be too restrictive [11]. Here, we discuss those more relevant to studies of marine mammals.

Parasite life span This is probably the most important factor, particularly in stock identity studies, determining the aims, design and conclusions of the survey. Short-lived parasites can show short-term or seasonal segregation of stocks, while long-lived parasites can reveal long-term segregation or permanent stocks. Little is known about the longevity of marine mammal parasites. However, it can be assessed in different ways, such as experimental infections of laboratory animals [16] or captive marine mammals [ 17] or comparison with similar parasites in terrestrial hosts [ 18].

Source of infection The composition of the parasite fauna of a particular individual can give indications of the habitats previously occupied by the host. Data about the distribution of parasites of marine mammals are fragmentary, although there is evidence concerning some common species. For instance, the nematode Anisakis typica occurs in warm and tropical waters between 40~ and 36~ [19]. The finding of this species in a striped dolphin (Stenella coeruleoalba) stranded on the French Atlantic coast suggested that the animal was a vagrant from southern latitudes [4].

Parasite life cycles Parasites with complex life cycles should not be discarded as biological markers because many successful studies include parasites with more than one host in the life cycle [1,11]. However, directly transmitted parasites with one-host cycle, such as whale-lice in cetaceans or suckling lice in pinnipeds, are simpler to use. In this case, it is not necessary to consider potential fluctuations in environmental conditions influencing the abundance and distribution of both free-living stages and intermediate hosts essential to the completion of the cycles. In addition, directly transmitted parasites are especially appropriate in behavioural studies because their infections tend to reflect the social patterns of their hosts [9].

Recovery of parasites Parasites should be easily detected involving a minimum of dissection. This condition is not essential but might be limiting, especially in studies of large whales or

136 under restricted time or resources. In this case, the use of ectoparasites or epizoites is advantageous over that of endoparasites.

Case studies

We present some examples to illustrate the value and limitations of parasite analyses. In a recent study on intestinal helminths of pilot whales (Globicephala melas) off the Faroe Islands, abundance of intestinal helminths of 101 animals from seven pods was used to evaluate their potential as indicators of stock and social identity [8]. The study showed differences between a group of three pods and another formed by four pods (Fig. 1). These results might be interpreted as prima facie evidence for temporal or spatial segregation of whale stocks. The first group consisted of pods caught within a few days in July and August showing high abundance of the acanthocephalan Bolbosoma capitatum, whereas the second included pods from September to June with low abundance of this species. Since B. capitatum is presumably a short-lived parasite [8], the variation observed could also result from seasonal fluctuations of parasite abundance, or from the interaction of spatial and temporal factors. However, the pattern of pod differences con-

1

Q r C

1~I 6 ~

0

w "~ 41-

m

O.i

1

9

2

9

9

3

5

i

7

I

I

4

6

School No.

Fig. 1. Dendrogram based on Mahalanobis' distances between the centroids of seven pods of pilot whales. From Balbuena and Raga [8].

137 formed with previous evidence from pollutant load and genetic analyses, supporting the hypothesis of whale segregation. Nevertheless, parasites can provide more conclusive evidence, particularly about behavioural features of marine mammals. In the same study, resampling experiments revealed that adult males were more difficult to allocate into their pods than the remainder, suggesting male exchanges between pods. This agreed with genetic studies showing that adult males do not breed within their natal pods [8]. Similarly, studies of whale-lice have provided valuable insights into the social behaviour of cetaceans and exemplify the advantages of using directly transmitted ectoparasites. Best [10] revealed that differences in the relative frequencies of two whale-louse species on sperm whales were indicative of segregation of adult males. Based on these data, he suggested that male sperm whales attained puberty at a length of 39-40 ft (i.e. about 11.9-12.2 m), which proved a very good estimate. Rice [20] based on histological analyses of gonadal tissue reckoned that males reach sexual maturity at a body length of 11-12 m. A recent survey of the whale-louse, lsocyamus delphini on Faroese pilot whales also yielded some interesting results [9]. Mature male whales showed higher prevalence and abundance of whale-lice than the rest. These data conformed with the polygynous mating system proposed for the species. Social fights between sexually mature males would result in a higher incidence of wounds and scars, providing additional shelter for whale-lice. Mass infections consisting of thousands of whalelice always occurred on unhealed wounds on the bulls. Perhaps these infections can be used to identify dominant males in sighting surveys.

Conclusions

This review shows that despite methodological limitations, parasites can be useful as biological indicators of marine mammals. Contrary to other alternative methods (genetics, pollutant analyses, etc.), parasite studies have the advantage of being relatively cheap and easy to implement. They do not require sophisticated equipment and although a knowledge of parasite systematics is desirable, it is not essential. These features make them particularly suitable for studies in developing countries or in remote field stations. The technique has so far proven more conclusive in behavioural than in population studies of marine mammals. Apparently, parasite surveys lack the precision of genetic, morphometric or biochemical studies to establish stock boundaries. It is important to note, however, that the latter techniques usually reveal "true stocks" or populations with a genetic basis, while parasite surveys tend to indicate "ecological stocks" (i.e. spatial patterns of distribution or abundance in an ecological time scale [21]). This can explain some contradictions between genetic and parasite analyses. For instance, Lester [11] recently showed that parasite data showed distinct groups of the fish, Hoplostethus atlanticus off New Zealand, while previous genetic analyses suggested a single stock. Therefore, parasite surveys should not be considered as a surrogate but as a complement to other studies.

138 Parasite analyses of marine mammals have yet to reach full potential, both in development and application. Increased statistical rigour and the use of sophisticated multivariate methods can provide better evidence relevant to management and conservation of their hosts [8]. In addition, as molecular techniques are perfected and applied to parasites, new tools to separate marine mammal stocks or discover more about their activities will be available. We believe that further integrated studies combining host and parasite information are most necessary to meet the ever increasing demand for correct conservation and management policies of marine mammals.

Acknowledgement This study was funded by grants from the DGICYT (project Nos PB87-997 and PB92-875) and CICYT (projects Nos NAT 1254/90E and NAT91-1128-C04-01) of the Spanish Government.

References 1. Williams HH, MacKenzie K, McCarthy AM. Parasites as biological indicators of the population biology, migrations, diet, and phylogenetics of fish. Rev Fish Biol Fish 1992;2:144-176. 2. Hoberg EP, Adams AM. Phylogeny, historical biogeography, and ecology of Anophryocephalus spp. (Eucestoda: Tetrabothriidae) among pinnipeds of the Holarctic during the late Tertiary and Pleistocene. Can J Zool 1992;70:703-719. 3. Helle E, Valtonen ET. Comparison between spring and autumn infection by Corynosoma (Acanthocephala) in the ringed seal Pusa hispida in the Bothnian Bay of the Baltic Sea. Parasitol 1981 ;82:287-296. 4. Abril E, Almor P, Raga JA, Duguy R. Parasitisme par Anisakis typica (Diesing, 1860) chez le dauphin bleu et blanc (Stenella coeruleoalba) dans le Nord-Est Atlantique. Bull Soc Zool Fr 1986;111:131-133. 5. Aznar FJ, Balbuena JA, Raga JA. Are epizoites biological indicators of a western Mediterranean striped dolphin die-off? Dis Aquat Org 1994;18:159-163. 6. Delyamure SL, Yurakhno MV, Popov VN, Shults LM, Fay FH. Helminthological comparison of subpopulations of the Bering Sea spotted seals, Phoca largha Pallas. In: Fay FH, Fedoseev GA (eds) Soviet-American Cooperative Research on Marine Mammals. Vol 1 - Pinnipeds. NOAA Tech Rep NMFS, 1984;61-65. 7. Dailey MD, Vogelbein WK. Parasite fauna of three species of Antarctic whales with reference to their use as potential stock indicators. Fish Bull 1991;89:355-365. 8. Balbuena JA, Raga JA. Intestinal helminths as indicators of segregation and social structure of pods of long-finned pilot whales (Globicephala melas) off the Faeroe Islands. Can J Zool 1994;72:443-448. 9. Balbuena JA, Raga JA. Ecology and host relationships of the whale-louse Isocyamus delphini (Amphipoda: cyamidae) parasitizing long-finned pilot whales (Globicephala melas) off the Faroe Islands (Northeast Atlantic). Can J Zool 1991;69:141-145. 10. Best PB. The sperm whale (Physeter catodon) off the west coast of South Africa 3. Reproduction in the male. Invest Rep Div Fish S Afr 1969;72:1-20. 11. Lester RJG. Reappraisal of the use of parasites of fish stock identification. Aust J Mar Freshwater Res 1990;41:855-864.

139 12. Margolis L, Esch GW, Holmes JC, Kuris AM, Schad GA. The use of ecological terms in parasitology (report of an ad hoc committee of the American Society of Parasitologists). J Parasitol 1982;68:131-133. 13. Moser M. Parasites as biological tags. Parasitol Today 1991;7:182-185. 14. MacKenzie K. Parasites as indicators of host populations. Int J Parasitol 1987;17:345-352. 15. Pence DB. Helminth communities of mammalian hosts: concepts at the infracommunity, component and compound community levels. In: Esch GW, Bush AO, Aho JM (eds) Parasite Communities: Patterns and Processes. London: Chapman and Hall, 1990;233-260. 16. Valtonen ET, Helle E. Experimental infection of laboratory rats with Corynosoma semerme (Acanthocephala). Parasitology 1982;85:9-19. 17. McCleUand G. Phocanema decipiens: growth, reproduction, and survival in seals. Exp Parasitol 1980;49:175-187. 18. von Bonsdorff B. Diphyllobothriasis in Man. London: Academic Press, 1977. 19. Davey JT. A revision of the genus Anisakis Dujardin, 1845 (Nematoda: Ascaridata). J Helminthol 1971;14:51-72. 20. Rice DW. Sperm whale Physeter macrocephalus Linnaeus, 1758. In: Ridgway SH, Harrison RJ (eds) Handbook of Marine Mammals, Vol 4. London: Academic Press, 1989;177-233. 21. Spanakis E, Tsimedines N, Zouros E. Genetic differences between populations of sardine, Sardina pilchardus, and anchovy, Engraulis encrasicolus, in the Aegean and Ionian Seas. J Fish Biol 1989;35:417-437.

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9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand t3. Ulltang, editors

141

M a r i n e m a m m a l i a n fatty acids: a source of information Otto Grahl-Nielsen and Olav Mjaavatten Department of Chemistry, University of Bergen, Norway A b s t r a c t . Background: fatty acids have been determined in tissues, especially blubber, of seals and

whales in a large number of investigations. None of these investigations have used a sufficient number of animals, nor have they treated the data in a proper statistical manner to allow quantitative conclusions on the internal (such as species, age, reproduction) and external (such as dietary) effects on the composition of the fatty acids. With good availability of seal samples through the Norwegian research program on marine mammals, we have by way of a chemometric method determined the fatty acids in blubber, hair and heart tissue of harp seals, Phoca groenlandica, hooded seals, Cystophora cristata, and harbor seals, Phoca vitulina. Methods: carefully selected samples of tissue were methanolysed in anhydrous methanolic HC1, the fatty acid methyl esters formed were gas chromatographed and the results were treated with multivariate principal component analysis. Conclusions: we have demonstrated the advantages of multivariate analysis, not previously applied on data on fatty acids in marine mammals. By this method, species differences in fatty acid composition of blubber, hair and heart tissue can be detected despite considerable individual variation. Differences between pups and adults were also clear for all three tissues. It is not likely that these differences are caused by the diet; distinct differences were observed in the pattern of fatty acids in the blubber of harp seals caught near Svalbard and in their main prey, the amphipod Parathemisto libellula. The pattern in the hairs from hooded seals changed from the time the hairs were new until they were shed 1 year later. The fatty acids in the heart tissue of harp seals differed between the western and eastern populations of harp seals. It is thus apparent that the fatty acid profile may be used for identification purposes. Key words: seals, blubber, hair, heart, species, populations

Introduction

The fatty acid composition of marine mammalian tissue, blubber and milk in particular, has been the subject of many investigations [1]. Species, age and dietary effects appear to have influence on the composition. However, it is not possible to extract any general conclusions about the quantitative measures of these differences from the many publications. This is mainly due to the small number of individuals which have been analysed in each case. With large individual differences, it has been impossible to apply quantitative, statistical treatment on the analytical data. We have developed a chemometric method for analysis of fatty acid composition, based on direct methanolysis of the sample, gas chromatography of the methyl esters formed, followed by multivariate, statistical treatment of the gas chromatographic data. With good availability of samples of seals through the Norwegian research program on marine mammals, we wanted to apply our chernometric method to study the fatty acids of blubber, hair and heart tissue. The main goal was to search for dif-

Address for correspondence: 0. Grahl-Nielsen, Department of Chemistry, University of Bergen, N5007 Bergen, Norway.

142 ferences between populations within the same species, but in this context it was necessary to look for differences between species, the effect of the age of the seals, and also to consider if variation in the diet could influence the fatty acid composition.

Materials and Methods

Seals were shot at various locations in the Northern Atlantic and in the Barents Sea according to the map in Fig. 1. Selected tissues were wrapped in aluminum foil and frozen onboard. After thawing in the laboratory, smaller samples of tissue were retrieved for analysis" approximately 2 mg of liquid blubber were collected with the tip of a small spatula from 1 cm beneath the skin from the dorsal part of the animal and transferred to a thick-walled glass tube for methanolysis. For sampling of hair, the pelt was washed carefully with water and air-dried. Approximately 50 mg of hair were picked out. In the pelts from four of the hooded seals caught in June, old hairs could be distinguished from new hairs, and old and new hairs were sampled separately. The hair sample was left for 24 h in a mixture of chloroform and methanol (3:1) and thereafter washed repeatedly with methanol and dichloromethane in a filter to get rid of extraneous lipids. The integral fatty acids of the hair were then obtained by methanolysis. Samples of heart tissue were taken from the tip of the heart. The outer "skin" was removed, and approximately 20 mg were cut off, carefully rinsed in distilled water to

~:::::i:i:::i:i:i: ::::::::::::::::::::::::::::::::::::::::::::::::::: ...... .............................................. .................................................. .................................................. :::.:::.:.:::: :.: .. ::::::::::::::::::::::::::::::::: :.;::: ===========================================

Fig. 1. The seals were shot in the following areas" E, harp seals in April 1989; W, harp seals in April 1989; S, harp seals in September 1990; H, harbor seals in June and October 1990; 90, harp and hooded seals in March and April 1990, and hooded seals in July 1990.

143 remove blood, thereafter dried on filter paper and transferred to the glass tube for methanolysis. Methanolysis was achieved by 2 N HC1 in dry methanol at 100~ for 15 h. The fatty acid methyl esters formed were extracted into hexane and gas chromatographed as described earlier [2]. To obtain the combined information from all fatty acids simultaneously, they were subjected to multivariate treatment based on principal component analysis. Their relative values were logarithmically transformed, thereby levelling out differences among fatty acids present in large and small amounts. With each sample positioned in the multi-dimensional space described by the log-transformed variables (fatty acids), the two coordinates (principal components, PCs) that described the largest and second largest variance among the samples were computed using the program package SIRIUS [3]. In this manner the relationship between the samples was displayed in two dimensions without considerable loss of the total original variance. The original variables, i.e. the fatty acids, were also displayed in the PC coordinate system, resulting in so-called biplots. Fatty acids with high, positive or negative, values along a PC in a biplot have high importance for that PC, and consequently for the position of the samples in the plot. Close positioning of two fatty acids means that they are positively correlated, while two acids on opposite sides of the origin are negatively correlated. The more perpendicular the direction from the origin towards two fatty acids, the less they are correlated.

Results and Discussion

Due to the clear difference between pup and adult harp seals (Table 1), only adult seals were used for inter-species evaluation: 27 harp seals, 16 hooded seals and 17 harbor seals. Within the species there were large differences between the seals, resulting in high standard deviations of the averages of the fatty acids (Table 1). This was also observed in other investigations [4,5]. A discussion of inter-species differences in the fatty acid composition of seal blubber based on determinations from single animals, as has been the case in some investigations, is therefore futile. In comparison of the three species, one acid at a time, i.e. a univariate approach, clear differences were found: 13 acids were significantly different, on the 99% level, between the harp seals and the hooded seals (Table 1). The differences in four of these corresponded with differences found by Jangaard and Ke [5]: 16:1 and 22:5n3 were lower, and 18:1 and 20:1 were higher in hooded seals than in harp seals. Nine acids differed significantly between the harp seals and the harbor seals, and comparison of hooded and harbor seals also revealed nine fatty acids with significant differences in the relative amounts (Table 1). When all 18 fatty acids were taken into consideration simultaneously in a principal component analysis, the three species fell into three groups (Fig. 2). Large individual differences within each group are obvious. While the hooded and harbor seals are well separated in this plot, the group of harp seals falls between the other two

144 Table 1. Relative amounts (as % of sum) • SD of fatty acids in blubber fat of pups and adult harp seals, adult hooded seals and adult harbor seals Fatty acids

Harp

Pups

14:0 14:1n5 16:0 16:1n7

18:0 18:1n9 18:1n7 18:1n5

18:2n6 18:3n3

18:4n3 20:1n9 20:4n6 20:5n3 22:1nl 1 22:1n9 22:5n3 22:6n3 Saturated Monousaturated Polyunsaturated

N=9

Adults N = 27

5.4 _ 0.5 0.9 _+ 0.2 1 4 . 2 _ 1.3 16.3 _ 2.3 1.9 _ 0.4 25.3 _ 1.4 6.1 _ 0.7 0.5 • 0.1 2.0 + 0.3 0.8 _ 0.1 2.7 _ 0.6 5.8 _ 2.4 0.4 • 0.1 8.5 _ 1.3 0.6 _ 0.5 0.2 • 0.1 3.0 • 0.4 5.7 • 0.9 22 56 23

5.8 1.2 11.1 15.0 1.0 20.4 5.1 0.5 1.7 0.9 3.7 8.2 0.3 9.0 3.4 0.4 4.0 8.3 18 54 28

> > >

> < > < < < <

_ 0.7 _ 0.4 _ 2.5 _ 2.4 _ 0.2 __. 3.0 • 1.4 _ 0.1 _ 0.3 _ 0.2 +_.0.7 _ 3.1 • 0.1 _ 1.4 _ 2.3 • 0.2 • 0.7 • 2.7

< > > > < < >

> < > < < >

Hooded

Harbor

N = 15

N = 17

5.1 0.7 9.1 9.3 1.5 23.6 3.6 0.5 1.7 0.9 2.4 15.4 0.3 5.2 7.3 1.0 2.4 10.1 16 61 23

_ 0.6 _ 0.2 • 1.7 • 1.7 _ 0.3 _-4-2.2 _ 0.6 _ 0.1 _ 0.2 _ 0.2 • 0.5 _ 2.4 • 0.1 • 1.3 _ 1.5 • 0.3 • 0.5 • 1.8

> < >

< > < > > <

5.1 _ 0.4 2.0 _ 0.5 9 . 6 _ 1.6 18.2 _ 4.5 0.9 _ 0.2 22.1 _ 2.6 3.1 • 0.7 0.5 _ 0.1 1.8 _ 0.2 1.5 • 0.3 2.6 _ 0.5 9.5 _ 2.7 0.7 _ 0.3 4.8 +_ 0.7 3.0 _ 1.1 0.2 • 0.1 4.2 • 0.8 9.8 • 0.9 16 59 25

< > >

<

> < > < <

The cases in which the amounts of fatty acids were significantly (P < 0.01) different between the groups are marked with inequality signs. The signs to the far right indicate significant differences between harbor and harp seals (adults).

species and is partly overlapping those groups. However, this plot does not show the total variance between the samples, since the two first principal components represent 67% of the variance, and the samples are projected onto the plane made up of these two principal components. By computing the groups pairwise, and only using the fatty acids which discriminate best according to Table 1, a complete separation of the three species of seals was evident (the PC-plots are not shown). The three species of seals have different feeding habits. Of the two oceanic species, the hooded seals feed at greater depths than the harp seals. The harbor seal feeds in coastal areas. However, all have an opportunistic feeding nature, consuming the prey items which are available, from squid and crustacea to a wide variety of fish species [6-8]. Many of these prey species are consumed by all three species of seals. The fatty acid composition of the prey species vary widely [9]. With such a composite menu, which is partly overlapping among the three seal species, any dietary effect should be levelled out. Examination of the stomachs of the harp seals shot at Svalbard in September 1990 showed that their diet was dominated by the amphipod Parathemisto libellula [10]. This was also the most abundant prey organism in most water layers in the area. P.

145

PC 2 (25%)

PC 1 (42%) Fig. 2. PC plot of blubber samples from hooded seals shot in the West Ice in 1990 (K), from harp seals shot in the West ice in 1989 and 1990 and in the East Ice in 1989 and near Svalbard in 1990 (G), and from harbor seals shot on the Norwegian coast in 1990. Each letter represents one seal. Eight replicate samples from one hooded seal are shown with outlined Ks.

Table 2. Relative amounts (as % of sum) _+SD of fatty acids in blubber fat of harp seals shot near Svalbard in September 1990 and in the amphipod Parathemisto libellula, their dominating diet Fatty acids

Blubber

P. libellula

14:0 14:1n9 16:0 16:1n7 18:0 18:1n9 18:ln7 18:1 n5 18:2n6 18:3n3 18:4n3 20:1n9 20:5n3 22:1nl 1 22:1n9 22:5n3 22:6n3

5.3 1.6 7.8 14.6 0.8 19.1 3.9 0.6 1.9 1.0 3.4 10.8 8.5 5.2 0.6 4.3 10.9

5.7 0.1 12.4 10.3 0.9 11.6 2.9 1.0 2.7 1.4 5.1 12.4 13.9 3.6 1.8 0.4 13.9

_ 1.0 _ 0.7 _ 2.2 _ 2.3 _ 0.2 _+4.5 _+ 1.0 _-4-0.1 _+0.4 _ 0.1 -+ 0.5 -+ 2.8 _+ 1.1 _+3.2 _+0.3 _+0.8 _+ 1.6

_ 1.2 _ 0.03 _+ 1.9 _+2.9 _ 0.1 _+ 1.9 _+ 1.2 -+ 0.2 _ 0.4 _ 0.3 -+ 0.6 -+ 3.0 _+ 1.3 _+0.8 _+0.6 _+0.07 _+ 1.7

146

P C 2 2o%

S

S

P

S

Ppp P

P C 1 73~

Fig. 3. PC plot of blubber samples from harp seals from Svalbard in September 1990 (S), and from the amphipod Parathemisto libellula caught in the same area (P). The two outlined Ps are replicates from the same animal.

libellula was also found to dominate the diet of harp seals captured in the same area in 1987 [6]. The composition of fatty acids in four P. libeUula caught by trawl in the area was determined and compared with the pattern of fatty acids in the blubber of the harp seals (Table 2). Clear differences are obvious, particularly for the polyunsaturated acid 22:5n3, which has approximately a ten times higher relative abundance in the blubber than in the prey organism, and the monounsaturated acid 14: ln9, which is approximately 15 times more abundant in the blubber. A principal component analysis of the fatty acid composition of the blubber and of P. libellula confirms the large difference between the two sample types (Fig. 3). With P. libellula being a major food item during excessive feeding of the harp seals in late summer and early spring, increasing their average blubber thickness from less than 2 cm to 8 cm [10], the large difference in fatty acid composition is a strong argument against the dietary effect on the fatty acid composition of the blubber.

Table 3. Relative amounts (as % of sum) • SD of fatty acids in hairs from pups and adults of harp seals caught in March 1990 and from adult hooded seals caught in March and June 1990 Fatty acids

Harp

Hooded

Pups

14:0 16:0 16:ln7 ul u2 18:0 18:1n9 u3 20:0 21:0a

2.9 19.7 4.9 4.0 1.3 11.9 29.5 2.6 0.6 22.7

Adults _ 1.5 • 1.6 +_.2.5 _ 0.7 _ 0.3 • 1.3 _ 3.8 • 2.1 • 0.1 • 4.2

3.5 34.0 3.6 2.6 1.0 26.9 10.7 2.4 1.2 14.2

_ _ _ _ • _ • • • •

2.1 5.3 2.7 0.7 0.2 4.9 3.7 1.4 0.3 5.6

March

June: new

June: old

3.8 34.0 4.2 3.8 0.7 21.8 16.6 1.2 1.0 13.1

2.2 30.3 3.8 6.2 0.9 13.6 17.2 2.1 1.4 22.3

2.2 45.3 1.7 1.3 0.7 26.1 18.1 0.2 1.6 2.9

__. 1.2 __.5.7 __. 1.9 • 0.6 • 0.1 __.5.2 • 6.3 • 0.4 • 0.4 • 2.7

_ _ _ _ _ _ • • • •

0.4 2.3 0.4 1.8 0.1 1.8 3.2 0.5 0.2 2.0

New and old hairs were determined separately from the hooded seals caught in June.

• _ • _ _ • • • • •

0.4 2.9 0.6 0.2 0.1 2.6 6.0 0.2 0.4 0.6

147

unid

21:0ap/./pS~77 p / 23/unid 18: l n 9 ~ a / / ~

unid 20:0 8:0

16:1n7

14:0

Fig. 4. Biplot of samples of hair from pup and adult harp seals shot in the West Ice in April 1990 and

the fatty acids in the samples. The composition of fatty acids in hairs also showed large individual differences (Table 3). Nevertheless, there were obvious systematic differences: the saturated acids were less abundant in the pups than in the adult harp seals, while the monounsaturated and the branched acids were higher in the pups. The composition of fatty acids in the hair of adult harp and hooded seals was less different; none of the acids differed on the 95% level due to the large individual deviation. The differences between new and old hairs from the hooded seal were large; the most prominent differences being the higher content of the saturated acids, 16:0 and 18:0 in particular, in the old hairs, and the much lower amount of the anteiso 21:0 in the old hairs. The relative amounts of fatty acids in the hairs from the hooded seals caught in March apparently fell between the amounts in the new and old hairs. With principal component analysis, the pups and adult harp seals formed two different groups even if the spread among the individuals within each group was substantial (Fig. 4). In this biplot the fatty acids are displayed together with the samples, showing how the fatty acids influence the distribution of the samples. The saturated acids, 16:0, 18:0 and 20:0 are associated with the adult seals, indicating higher relative values of these acids in adults than in the pups. This is in accordance with the values in Table 3. The two monoenic acids, 16:1n7 and 18:1n9 and the branched acid, anteiso 21"0, are associated with the pups on the left side of the plot, showing that they are negatively correlated with the three aforementioned saturated acids, with high relative values in the pups and small relative value in the adults. The remaining four acids are located between the two groups of samples and have less importance for the separation between the groups. The difference in the fatty acid pattern of the hairs from adults of the two seal species, harp seals and hooded seals, was less than the difference between adults and

148 pups of the harp seal (Table 1). However, multivariate computation revealed that the fatty acid pattern of the hairs of the seals is species specific. In an investigation on mammalian hair, Wertz and Downing [ 11 ] found fatty acid compositions in sheep, pig, dog, cow and human to be "nearly identical". However, the relative amounts reported by them differ more among the species than the differences between the two seal species (Table 1). Moreover, they have not sampled from different individuals, and are therefore precluded from the use of statistics in their comparisons. It is therefore impossible to compare the results of the two investigations. The new and 1-year-old hairs of hooded seals differed substantially in fatty acid patterns (Table 1). The new hairs were much richer in anteiso 21:0 and two branched acids, while the two saturated acids 16:0 and 18:0 were present in higher amounts in the old hairs. Wertz and Downing [12] have suggested that the function of the branched fatty acids in hair is to fluidize membranes, similar to the function of unsaturated fatty acids in other tissues. Since hair is exposed to air, unsaturated acids have been replaced by branched acids because they exhibit greater resistance towards oxidative damage. We have now observed that the relative abundance of the branched fatty acids decreases as the hairs are aging. By comparing the composition of fatty acids in the new and old hairs from the hooded seals caught in July with the composition in the hairs from the seals caught in March (Table 1), it was clear that the new hairs had a closer resemblance to the hairs from March than the old hairs. PC analysis of the samples from March together with the new and old hairs from July also showed that the March samples were more closely related to the new hairs than to the old (Fig. 5). Consequently, the change in fatty acid composition which occurs during the 1-year lifetime of hair is much larger during the last 3-4 months before the hairs are shed than during the preceding 8-9 months. Even if the fatty acid composition in blubber tissue and in hairs was species specific, discrimination on a population level appears not to be possible. We therefore considered heart tissue, which could be expected to contain a more specific fatty acid

.3 21 4 r

Fig. 5. PC plot of samples of new (left) and old (right) hairs from four hooded seals shot in July 1990 in

the West Ice, together with samples of hair from six hooded seals shot in late March 1990 in the same area.

149 Table 4. Relative amounts (as % of sum) • SD of fatty acids in heart tissue of pups and adult harp seals, adult hooded seals and adult harbor seals Fatty acids

Harp

14:0 14:1n5 16:0 16:ln7 18:0 18:1n9 18:1n7 18:1n5 18:2n6 18:3n3 20:0 20:1n9 20:4n6 20:5n3 22:0 22:1nl 1 22:1n9 22:6n3 24:1n9 Saturated Monounsaturated Polyunsaturated

Pups N = 19

Adults N = 37

0.9 0.1 16.3 4.8 20.7 23.9 6.4 0.3 5.1 0.3 1.3 1.8 9.6 4.9 0.5 0.3 0.2 2.0 0.6 39.7 38.4 21.9

1.1 0.1 15.9 5.0 16.5 23.0 4.7 0.2 7.4 0.4 1.1 3.7 6.0 9.9 0.4 1.4 0.2 2.1 0.7 35.1 39.1 25.8

_ 0.3 _ 0.04 _ 1.3 • 0.6 • 2.6 _ 1.6 • 0.6 __ 0.1 _ 0.8 • 0.1 • 0.3 _ 0.8 • 1.7 __. 1.5 • 0.1 • 0.2 • 0.09 • 1.1 • 0.1

• • • _ • • _ • _ • _ • • • • • • • •

0.4 0.06 1.1 0.9 1.7 3.0 0.9 0.09 1.2 0.1 0.2 1.7 1.4 2.2 0.1 1.1 0.18 0.7 0.1

>

< < > < < < >

Hooded

Harbor

N = 26

N = 17

1.1 0.1 15.1 3.2 15.8 24.4 4.5 0.2 7.3 0.5 1.1 4.9 6.9 7.6 0.5 3.1 0.4 2.6 0.6 33.6 41.5 24.9

• 0.2 __ 0.03 • 1.3 __. 1.2 • 2.6 __. 3.3 • 0.7 _.+0.07 • 1.5 • 0.2 __.0.2 • 2.1 • 2.6 • 1.7 • 0.1 • 2.0 • 0.3 • 1.3 • 0.1

>

>

< <

< >

>

1.0 _ 0.5 0.04 _ 0.02 14.8 • 0.7 2.7 _ 0.7 15.5 • 2.1 19.7 _ 2.4 4.5 • 0.9 0.2 • 0.03 8.8 _ 1.7 1.3 • 0.3 1.2 _ 0.2 4.2 • 1.7 12.3 • 3.3 6.2 • 1.7 0.5 • 0.1 3.0 • 2.1 0.2 • 0.11 3.1 • 1.0 0.7 • 0.1 33.0 35.3 31.7

< < <

> >

> < > > >

The cases in which the amounts of fatty acids were significantly (P < 0.01) different between the adult seals are marked with inequality signs. The signs to the far right indicate significant differences between harbor and harp seals.

PC2

13%

Q

~3

"~

. . . .

K I~_

~)

o/i I

G

PC 1 63%1

Fig. 6. PC plot of samples of heart tissue from hooded seals shot in the West Ice in 1990 (K), from harp seals shot in the West Ice in 1989 and 1990 and in the East Ice in 1989 and near Svalbard in 1990 (G), and from harbor seals shot on the Norwegian coast in 1990. Each letter represents one seal.

150

HOODED

\

HARP \

/

G

.,'~ ~

G/777

G

/

/

9

\.

/ r

Fig. 7. PC plot of samples of heart tissue from pups and adults of hooded (K) and harp (G) seals shot in the West Ice in 1990.

~ PC 2 (25%)

ADULTS

I

I

PUPS

(42%) , '

Fig. 8. PC plot of samples of heart tissue from adult (bold numbers on the left) and pups (numbers in italics on the right) of harp seals from the West Ice, 1-4, and the East Ice, 11-12 and 21-25. Two or three replicate samples were taken from each animal.

151 profile than the other two types of tissues due to a high proportion of phospholipids in the lipid fraction. As was the case for the two other tissues, a large individual variation in the composition of the fatty acids in the heart tissue was observed, giving high standard deviations of the mean values (Table 4) and a large spread in the PC plot (Fig. 6). It appears from the plot that the fatty acid profile of the harbor seals is distinct from the profile of the other two species, while there is an overlap between hooded and harp seals. However, a test of the two latter species shows a clear distinction for animals shot in the same area off Greenland in the spring of 1990 (Fig. 7). This plot not only shows a species difference, but also an age difference, in that pups are clearly different from the adults. When differences between the western and eastern populations of harp seals are considered, it turns out that the difference between the adults and pups is larger than the difference between the two populations. This is seen in the PC plot in Fig. 8, where the age difference is along PC 1, which describes 42% of the total variance, while the population difference is along the second principal component with 25% of the variance among the samples. Adults and pups therefore have to be treated separately. The two populations are then well distinguished (Fig. 9). As a control, pups and adults from the western population, shot in the West Ice in 1990, were compared with the seals from 1989 (Fig. 9). For both pups and adults, the

PUPS E

E

ADULTS

E

E

EE

X

X

X

I IS I I I I I

S

X

xs

Fig. 9. PC plots of the same samples as in Fig. 7, computed separately for pups and adults. E and W represent seals from the East and West Ice, respectively, from 1989, X represent seals from the West Ice in 1990, and S represent seals shot near Svalbard in September 1990.

152 samples f r o m the w e s t e m population from the 2 years overlap. This indicates that the fatty acid profile of the heart tissue is typical for the two populations of harp seals. Thus, the fatty acid profile may be regarded as an intrinsic marker which may be used to identify to which population a seal belongs. This was applied to 22 harp seals shot near Svalbard in September 1990. At this time of the year the harp seals are foraging far away from their breeding areas. Seals from the two populations are expected to mix in the n o r t h e m areas. The overlap of the Svalbard seals with the western seals suggest that they belong to this population (Fig. 8). Although our findings are based on a very restricted n u m b e r of seals, the corresponding results for adults and pups, and the successful test of the 1990 seals from the w e s t e m population, do strengthen the implications that the fatty acid profile m a y be used for identification purposes.

References 1. Ackman RG, Lamothe F. Marine mammals. In: Ackman RB (ed) Marine Biogenic Lipids, Fats and Oils II. Boca Raton, FL: CRC Press, 1989;179-381. 2. Viga A, Grahl-Nielsen O. Genotypic and phenotypic fatty acid composition in the tissues of salmon, Salmo salar. Comp Biochem Physiol 1990;96B:721-727. 3. Kvalheim OM, Karstang T. A general-purpose program for multivariate data analysis. Chemom Intel Lab Syst 1987;2:235-237. 4. Engelhardt FR, Walker BL. Fatty acid composition of the harp seal, Pagophilus groenlandicus (Phoca groenlandica). Comp Biochem Physiol 1974;47B: 169-179. 5. Jangaard PM, Ke PJ. Principal fatty acids of depot fat and milk lipids from harp seal (Pagophilus groenlandica) and hooded seal (Cystophora cristata). J Fish Res Bd Can 1968;25:2419-2426. 6. Lydersen C, Angantyr LA, Wiig O, Oritsland T. Feeding habits of northeast Atlantic harp seals Phoca groenlandica along summer ice edge of the Barents Sea. Can J Fish Aquat Sci 1991 ;48:2180-2183. 7. Wiig 0. Selenes n~eringsopptak og konsum. Fiskets Gang 1988;6/7:12-13. 8. Olsen M, BjCrge A. Diet of the harbor seal Phoca vitulina, in the Hvaler area in 1990 and 1991, compared to the abundance of fish in the area. ICES Coun Meet 1992/n:19:1-15. 9. Gunstone FD, Harwood JL, Padley FB. The Lipid Handbook, 2nd edn. London: Chapman and Hall, 1994:167-180. 10. Nilssen KT, Haug T, Potelov V, Timoshenko YK. Feeding habits of harp seals (Phoca groenlandica) during early summer and autumn in the northern Barents Sea. Polar Biol 1994;in press. 11. Wertz PW, Downing DT. Integral lipids of mammalian hair. Comp Biochem Physiol 1989;92B:759-761. 12. Wertz PW, Downing DT. Integral lipids of human hair. Lipids 1988;9:878-881.

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. Ulltang, editors

153

Fatty acid composition in blubber, heart and brain from phocid seals BjCrge Fredheim 1, Siv Holen 2, Karl Inne Ugland 3 and Otto Grahl-Nielsen 4 1Norsk Hydro a.s., Research Centre, Sectionfor Environmental Technology, Norway; 2Bergen College, Department of Construction and Engineering, Norway; 3Department of Biology, University of Oslo, Norway and 4Department of Chemistry, University of Bergen, Norway Abstract. The fatty acid composition of phocid seals was investigated in order to map the possible stratification of fatty acids in the depot fat and to detect possible differences between different tissues and between the four species grey seal (Halichoerus grypus), harbour seal (Phoca vitulina), ringed seal (Phoca hispida) and harp seal (Phoca groenlandica). We used a chemometric method in this analysis: the fatty acids were determined by gas chromatography, and the relative amounts of fatty acids were treated by principal component analysis. Analysis of the depot fat in the four species indicates that the fatty acid composition of the blubber varies along a gradient from the epidermis. We are able to distinguish between three distinct vertical layers. With increasing depth from the epidermis, the amount of saturated and long-chained monounsaturated fatty acids in the blubber fat increased, while the amount of short-chained monounsaturated fatty acids decreased. The four seal species exhibited differences in fatty acid composition in the outermost layer of the blubber. In contrast, the middle and inner layers did not show differences between species. We also analysed the fatty acid composition of heart and brain tissue from harp seals. The three tissues had distinctly different profiles.

Key words: grey seal, harbour seal, ringed seal, harp seal, fatty acids

Introduction The fatty acid composition of blubber fat from marine mammals has been thoroughly investigated considering the commercial value of their oils [1 ]. In baleen whales the fatty acid composition varies with the different cross-sectional areas sampled [2-5]. In contrast, most of the analyses of blubber fat from seals are based on the assumption that the blubber has a homogenous composition [6-8]. However, this assumption is based on the analysis of only one harp seal [9]. In this work we apply a chemometric method developed by Kvalheim [10] and Grahl-Nielsen [11] in an analysis of three layers in a cross-section of the blubber from four phocid seals: grey seal (Halichoerus grypus, Fabricius 1791), harbour seal (Phoca vitulina L.), harp seals (Phoca groenlandica, Erxleben 1777) and ringed seals (Phoca hispida, Schreber 1775), and in an analysis of differences in the fatty acid profile from blubber, heart and brain tissue from harp seals. This method consists of direct methanolysis of the samples, followed by high-resolution gas chromatography and multivariate analysis of the data. Thus, instead of using three steps, (i.e. extraction, saponification, and esterification) the methanolysis requires only a single

Address for correspondence: B. Fredheim, Norsk Hydro a.s., P.O. Box 2560, N-3901 Porsgrunn, Norway.

154 step. This technique allows a large number of samples to be analysed. The purpose of our study was to identify the individual and interspecific variation in the blubber composition. Harp seals for analysis of heart and brain tissue were sampled in the Greenland Sea and in the Barents Sea. For analysis of the blubber, seals were sampled in the Varangerfjord (Finnmark county in northern Norway). Both the coastal species (grey and harbour seal) are represented by a small population in this fjord. In addition, the two arctic species (ringed and harp seal) visit the area regularly during the winter. All four species are known to be opportunistic feeders, hence competing for the available food resources in the sampling area.

Materials and Methods

We analysed the blubber of eight grey seals, four harbour seals, four harp seals and four ringed seals. All seals were collected during a period of 6 months from November 1991 to April 1992 in the Varangerfjord area in the eastern part of Finnmark (70~ 30~ (Fig. 1) during the seal invasions [12]. We also analysed

~fjorden

~,.

Os

Fig. 1. Map showing the sampling localities for harbour seal, grey seal, harp seal and ringed seal off the Norwegian coast.

155 brain and heart tissue from 80 harp seals collected ultimo April and primo May in the breeding area north of Jan Mayen (74~ 11 ~ and ultimo March and primo April in the breeding area in the southern part of the Barents Sea (69~ 44~ The blubber sections (skin to muscle) were taken from the area immediately overlying the sternum. Heart tissue was taken from the apex, and brain tissue was taken from the area close to foramen magnum. All tissue-samples were carefully wrapped and subsequently frozen and stored (temperature <-20~ Samples were taken in a frozen or partially frozen state. The cross-section of the blubber was sectioned into three equal pieces; outer-, middle- and inner-layer. In order to avoid contact with skin and muscle and also to minimise the influence of autooxidation, we extracted approximately 2 mg of oil from inside each blubber section. For each of the samples of heart and brain, we used approximately 20 mg of tissue. The pericardium was removed from the heart before sampling and the sample was then rinsed in water to remove blood from the tissue. Samples from brain tissue were taken from the grey matter. All samples were transferred to thick-walled glass tubes for methanolysis (100~ in 15 h), followed by gas chromatography of the resuiting methyl esters as described by Grahl-Nielsen and Barnung [11 ]. Peaks in the chromatograms from all samples were identified by comparison with chromatograms of standards. The areas of well-defined peaks from the chromatograms were integrated and the total relative amounts of the fatty acids, as a percentage of the sum, were calculated. Differences between the tissues can be seen by comparing the relative values for the fatty acids. In order to separate the information from noise, the data matrix was simplified by a multivariate technique called principal component analysis (PCA) first described by Pearson [13]. PCA looks for a few linear correlations (principal components or PCs) which can be used to summarise the data, losing as little information in the process as possible. This attempt to reduce dimensionality can be described as "parsimonious summarisation" of the data. If the data can be summarised by two linear combinations, we say that the dimensionality is reduced from 23 (original number of fatty acids) to 2 (number of PCs). In this investigation PCA was used to extract the two coordinates (PCs) that described the largest and the second-largest variance among the samples, using the software package SIRIUS [14]. In this manner the relationship between the samples was displayed in two dimensions without considerable loss of the total original variance. Classification of the various groups of samples was achieved in the second multivariate step using SIMCA analysis [15,16] also available in the SIRIUS package. Principal components were fitted to each group of samples. The number of components used to describe each group was determined by cross-validation [ 17]. A tolerance interval, with 95% significance level, around the principal components, was then determined for each group. This is the maximum relative standard deviation (RSDmax). Each sample was then classified by determination of its relative standard deviation (RSD) from the principal components of the group. A lower RSD than RSDmaxfor a group indicates that the sample belongs to that group.

156

kPC 2 (17%t8:1 (o9 Blubber

18:1 (o7 20:1 (o9

ain ' 1

"~L~.'5 3

\~

rt

14:0 A/

16:1 ~

PC 1 (69%) ,jr

Fig. 2. Classification of all tissue samples by PCA based on 11 fatty acids. The importance of the various fatty acids is given by their position in the biplot.

Table 1. Relative amounts (as % of sum) • SD of fatty acids, and sum of saturated (SFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids in the samples from heart and brain (harp seals) and blubber (grey seal, harbour seal, ringed seal and harp seal) Fatty acids 14:0 14:1095 16:0 16:1o97 18:0 18:1o99 18:1097 18:1095 18:2096 18:3(o3 18:4o93 20:0 20:1099 20:3096 20:4w6 20:5093 22:0 22:10911 22:1099 22:5093 22:6093 24:0 24:1099 SFA MUFA PUFA

Heart (n = 80) 0.52 _ 0.20 11.74 0.88 16.76 22.89 4.14 0.13 0.15

• 2.46 • 0.43 • 2.54 • 1.68 • 1.05 _ 0.02 _+0.11

1.80 5.05 0.24 3.44 0.63 1.41 0.15 0.91 0.66 3.83 6.19 10.26 38 44 9

+_.0.60 • 2.13 • 0.05 +_0.86 +_.0.38 • 0.39 __.0.15 _ 0.39 +_0.24 _ 1.78 • 2.25 _ 2.40

Brain (n = 80)

Blubber (n = 20)

0.90 0.10 13.19 4.04 16.06 20.16 4.05 0.25 7.21 0.32

_+0.31 +_0.06 • 1.40 • 0.80 __.2.17 • 2.37 _ 0.60 _ 0.07 _ 1.42 _+0.09

5.16 1.39 9.83 15.73 1.14 20.80 4.67 0.60 2.15 1.35 2.37

1.06 3.30 0.19 8.44 8.29 0.36 1.03 0.17 0.44 2.42

+_.0.32 _ 1.38 _ 0.05 _ 1.78 +_2.12 _.+0.10 __.0.68 _ 0.08 _ 0.28 • 0.88

1.98 _ 6.67 32 35 27

The number of animals analysed (n) is given for each tissue.

_ 1.18 _ 0.59 • 2.26 • 6.00 _ 0.42 _+ 3.70 _ 1.19 • 0.11 +_0.39 _+0.47 +_.0.63

6.42 • 2.52 0.58 _+0.24 6.17 _ 1.62 2.63 0.35 4.92 12.55

16 53 30

__.2.19 _ 0.24 +_0.83 • 2.02

157 Results

For the multivariate treatment we used 23 fatty acids, ranging from 14:0 to 24: lo~9, and two unidentified peaks (noid2 and noid3) which were represented in detectable amounts in the samples. Analysis of the relative amounts of 11 fatty acids represented in detectable amounts in both heart, brain and blubber showed significant differences between the three tissues (Fig. 2). The total amount of saturated acids in heart and brain was found to be more than twice the amount of saturated acids found in blubber (Table 1). Of the total fatty acid content, heart and brain were found to contain 38% and 32% saturated acids, respectively, with 16:0 and 18:0 being the main contributors (Table 1). Blubber had a low relative amount of saturated fatty acids; in fact, the only saturated acids detected in the blubber were the short-chained acids 14:0, 16:0 and 18:0, while both short- and long-chained saturated acids were found in heart and brain. However, blubber had the highest amount of monounsaturated and polyunsaturated fatty acids. Heart and brain also had the highest number of detectable fatty acids, 20 and 21, respectively, while blubber only had 18. There was also a higher number of unidentified peaks in the heart and brain samples. Table 2. Relative amounts (as % of sum) of fatty acids, and the sum of saturated (SFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids in blubber samples from four seal species caught in Varangerfjorden in northern Norway (short MUFA have 18 or less carbon atoms and long MUFA have more than 18 carbon atoms in the chain) Fatty acids

14:0 14:1 095 16:0 16:1 ~o7 18:0 18:1 ~o9 18:1 co7 18:1 095 18:2 a~6 18:3 w3 18:4o93 20:1 ~o9 20:4 ~o6 noid2 20:5 a~3 22:1 ~oll 22:1 ~o9 noid3 22:5 ~o3 22:6 ~o3 SFA Short MUFA Long MUFA PUFA

Total blubber Grey seal

Harbour seal

Ringed seal

Harp seal

5.04 -+ 1.33 1.22 _ 0.48 9.65 _ 2.09 12.87 _ 3.44 1.18 __.0.42 23.35 _+ 3.29 4.71 _+ 1.12 0.60 _+0.08 2.33 _+0.32 1.61 -+ 0.51 2.36 _+0.55 6.76 _+2.33 0.65 _+0.29 1.07 _+0.16 5.41 _+0.72 2.52 _+2.18 0.36 _+0.26 0.35 _+0.06 4.93 _+0.88 13.00_+ 1.33 15.88 _+ 1.16 42.75 _+ 1.13 9.64 _+ 1.19 30.29 _+ 1.37

5.03 1.66 11.68 18.53 1.27 19.05 3.99 0.62 2.16 1.35 2.38 5.84 0.59 0.71 5.13 2.44 0.32 0.32 4.62 12.31 17.97 43.85 8.60 28.54

5.00 1.45 8.73 21.26 0.99 17.67 5.32 0.68 1.79 1.08 2.01 4.44 0.55 0.74 8.02 2.09 0.21 0.35 5.26 12.35 14.72 46.39 6.74 31.05

5.62 1.42 9.57 13.79 1.11 19.65 4.63 0.51 2.04 1.00 2.73 8.19 0.42 0.56 7.20 3.56 0.48 0.39 4.91 12.25 16.29 39.99 12.23 30.54

-+ 0.81 _+0.85 _ 1.28 _ 6.77 _+0.38 _+2.69 _+0.89 _+0.07 +_.0.42 -+ 0.31 _+0.53 _+ 1.97 _+0.16 _+0.13 _+0.99 _+ 1.84 _+0.18 _+0.06 _+0.92 _+2.25 _+ 1.17 _+ 1.07 _+ 1.19 _+ 1.19

_ 1.25 _ 0.43 -+ 2.69 _ 7.09 _+0.47 _+2.10 _ 1.44 _+0.16 -+ 0.28 _+0.28 _+0.63 _+2.30 _+0.14 _+0.29 _+ 1.32 _+2.38 _+0.19 _+0.09 _+0.61 _+2.84 _+ 1.22 _+ 1.11 _+ 1.42 _+ 1.30

_ 0.95 _ 0.59 _+2.13 _ 3.06 _+0.40 _+ 3.05 -+ 1.03 _+0.06 -+ 0.22 _+0.21 _+0.71 _+2.23 _+0.14 _+0.12 _+ 1.76 _+2.16 _+0.23 _+0.10 _+0.69 _+2.26 _+ 1.10 _+ 1.10 _+ 1.19 _+ 1.24

158

PC2 (28%)

14:10)5 16:10)7

Gray seal

Qs

~8

18:30)3

~7

~5 18:~

06

18:40)3

18:30)3"]1;~ m n~ 0 ~2 .~9 ~J: 1,r 3

20:40)6

"~q~l

PC2 (13%) noid2

14:10)5

~1,6:,=7 01

14:0 ~ll8:10)7~r'?tll ~22:50)3l!14~2__% ~ 2

Harbour seal

'PC2 (17%) . !8 : 4 o ~ 1~4

3

22:60)3 22:50)3 18:0

20:40)6

18:0 -PC1 (53~

PC1 (67=/o)

Ringed seal

4m

Im 18:3r ~2

~

14:0 r~Jd3 16:1~i10)5

20:1o)9

2

~/~

16:0

2~~ 18:0

01

22:60)3 20:40)6 0

Outer layer

noid3

1~

l..O

18:10)7

04

20:50)3 ~6:10)7 14:10)5

22:60)3

"~1 PC1 ( 6 6 % ) gg Middle layer

20:40)6 ~

PC1 (39%)

r

Inner layer

Fig. 3. Classification of blubber samples by PCA based on fatty acids (the importance of the various fatty acids is given by their position in the biplot) from (a) grey seal, (b) harbour seal, (c) ringed seal and (d) harp seal. Each number represents one individual seal and the symbols indicate the position of replicate samples from outer, middle and inner blubber layer (replicate samples from one individual indicates the low analytical variance).

Table 2 presents the total relative amount of the 18 fatty acids represented in all blubber samples (n = 40). A closer examination of Table 2 reveals several differences between the species. However, neither a univariate statistical test nor PCA was able to separate the species significantly at this level. By the use of direct methanolysis and PCA we were able to analyse accurate samples from three layers in a blubber cross-section from 20 animals. The biplots from the four species analysed are presented in Fig. 3. The plots indicate that both harbour, ringed, grey and harp seals exhibit interspecific and individual or intraspecific variation in the fatty acid composition of the blubber. The plots also show that the intraspecific variation displayed by PC1 accounts for most of the variance in the data; 67%, 66%, 53% and 39% of the total variation, respectively (Fig. 2). In addition, the intraspecific variation displayed by PC2 only accounts for 17%, 13%, 28% and 27%, respectively.

159

Table 3. Relative amounts (as % of sum) _ SD of fatty acids from three layers in a cross section of the blubber from four seal species caught in Varangerfjord in northern Norway Grey seal

14:0 14:1095 16:0 16:1097 18:0 18:1099 18:1097

18:1095 18:2to6 18:3093 18:4093 20:1o99 20:4096 noid2 20:5093 22:10911 22:1099 noid3 22:5093 22:6~3

Harbour seal

Middle

Inner

Outer

Middle

Inner

Outer

3.81 +- 039 1.60 +- 0.39 8.05 _ 1.34 16.89 _ 1.34 0.79 _ 0.15 25.80 +- 1.85 5.55 ---0.68 0.66 • 0.07 2.35 +- 0.30 1.42--.0.41 2.07 ---0.32 4.71 +- 0.84 0.83 _ 0.34 1.02 _ 0 . 1 0 5.67 _ 0.44 0.59---0.35 0.17 _ 0.09 0.34 _ 0.02 5.01 _ 0.71 12.66 _ 0.77

4.86 _ 082 1.21 _ 0.40 9.45 +- 1.41 12.44 +- 1.84 1.20 +- 0.29 23.37 +- 3.11 4.78 ---0.98 0.60 _ 0.08 2.41 +- 0.31 1.58--,0.50 2.41 ---0.54 6 . 7 2 _ 1.20 0.63 +- 0.24 1.11 • 5.49 +- 0.69 2.04--,1.13 0.38 +- 0.16 0.36 +- 0.04 5.28 +- 0.88 13.65 _ 1.42

6.33 _ 1.22 0.88 • 0.39 11.17 _ 2.22 9.40 +- 1.65 1.50 +- 0.41 21.60 • 3.31 4.04 _ 1.25 0.56 _ 0.09 2.26 _ 0.34 1.76--,0.62 2.53 --.0.71 8.86 +- 2.57 0.51 _ 0.25 1.08 --.0.19 4.88 +- 0.84 4.65---2.07 0.55 _ 0.32 0.37 +- 0.10 4.66 • 1.19 12.40 +- 1.22

4.81 _ 0.10 2.74 • 0.16 11.46 • 0.60 27.06 • 1.11 0.95 +- 0.05 17.75 +- 1.43 3.86---0.58 0.68 • 0.04 1.91 • 0.18 1.24• 2.28 • 4.31 _ 0.64 0.62 +- 0 . I 0 0.65 • 4.40 _ 0.10 1.02--,0.42 0.19 +- 0.04 0.29 +- 0.02 3.79 +- 0.24 9.99 +- 0.34

5.02 _ 0.54 1.39 • 0.31 11.63 • 0.87 16.85 +- 2.85 1.21 +- 0.15 19.70 +- 1.47 3.86---0.68 0.60 • 0.04 2.42 • 0.42 1.59--,0.23 2.73 ---0.44 6.07 _ 1.05 0.53 +- 0.08 0.78 • 5.42 +- 0.59 2.33--.1.16 0.29 _ 0.08 0.34 +- 0.03 4.68 +- 0.35 12.54 +- 0.93

5.00 _ 1.09 0.79 +_0.12 12.77 +- 0.99 12.05 +- 0.59 1.68 +- 0.37 19.86 +- 2.91 3.99--- 1.10 0.55 • 0.06 2.41 _ 0.51 1.40_+0.34 2.38 ---0.63 6.40 +- 1.10 0.54 +- 0.15 0.74 +_0.14 5.87 _ 1.27 3.53---0.89 0.39 +- 0.06 0.31 +- 0.05 4.95 +- 0.73 14.37 • 2.34

Ringed seal

14:0 14:1095 16:0 16:1097 18:0 18:1o99 18:1097 18:1095 18:2xo6 18:3093 18:4o93 20:1099 20:4096 noid2 20:5093 22:10911 22:1099 noid3 22:5093 22:6093

Harp seal

Middle

Inner

Outer

Middle

Inner

Outer

3.81 ---0.27 1.80--.0.16 6.26 +- 0.52 27.31 ---2.79 0.56 +- 0.09 1 9 . 0 7 _ 1.49 6.76 +- 0.40 0.80 +- 0.13 1.77 ---0.30 0.86 --,0.13 1.46--,0.25 2.64 +- 1.51 0.60 +- 0.13 0.87 +- 0.40 8.64 _ 1.06 0.14 +- 0.14 0.03 +- 0.05 0.37 _ 0.09 5.16 +- 0.39 11.09 _ 1.30

5.21 _ 1.11 1.60--.0.27 7.89 _ 1.49 23.90---4.04 0.88 _ 0.21 16.33 +-2.16 5.35 • 0.67 0.72 +- 0.14 1.68--,0.22 1.11 --.0.18 2.17 ---0.37 3.68 +- 1.14 0.49 _ 0.10 0.74 +- 0.21 8.90 _ 0.54 1.15 _ 0.55 0.18 _ 0.09 0.40 _ 0.06 5.81 +- 0.33 11.80 +- 2.65

6.19--,0.77 1.01 ---0.04 11.56 +- 0.77 12.42--. 1.50 1.56 _ 0.22 1 7 . 3 6 _ 1.28 3.57 +- 0.37 0.56 +- 0.06 1.76--.0.24 1.28 ---0.35 1.88 • 7.02 • 1.08 0.72 +- 0.06 0.55 +- 0.09 6.02 • 0.44 5 . 8 9 _ 1.02 0.45 +- 0.03 0.23 _ 0.04 4.82 +- 0.32 15.14 _ 2.43

4.76---0.60 2.11 --,0.41 7.21 __. 1.29 16.35 +- 1.92 0.72 • 0.14 21.73__. 1.46 4.81 +- 0.34 0.51 __.0.08 2.20__.0.19 1.14 • 3.13 • 7.25 __.0.88 0.39 +- 0.10 0.59 +- 0.07 8.47 __. 1.17 1.78 • 1.07 0.31 +- 0.09 0.46 +- 0.10 4.86 +- 0.85 11.21 +- 0.50

6.01 ---0.34 1.24 ---0.25 10.20 +- 0.86 13.40--.2.41 1.05 +- 0.12 18.72 +- 3.39 4.63 +- 1.24 0.49 +- 0.05 2.01 --,0.19 0.95 ---0.06 3.02• 8.12 +- 1.96 0.35 +- 0.05 0.55 +- 0.08 7.44 _ 1.62 3.67 _ 1.80 0.50 +- 0.17 0.41 +- 0.02 5.00 _ 0.64 12.22 +- 2.21

6.64 ---0.56 0.93 ---0.24 10.98 +- 1.34 11.47--,3.39 1.43 _ 0.32 18.16 • 2.32 4.58 __. 1.49 0.51 • 0.08 1.94 • 0.88 ---0.29 2.36---0.86 10.20 +- 2.86 0.41 +- 0.14 0.53 -4-_0.18 5.70 +- 1.52 5.51 _ 2.19 0.70 +- 0.29 0.33 +- 0.06 4.87 +- 0.80 11.86 +- 2.93

160 Table 4. Relative amounts (as % of sum) _+SD of saturated (SFA), monounsaturated ( M U F A ) and polyunsaturated (PUFA) fatty acids in the samples from three layers in a cross section of the blubber from four seal species caught in Varangerfiord in northern Norway Fatty acids

Blubber section Outer

Middle

Inner

Grey seal ZSFA ZShort M U F A ZLong M U F A ZPUFA

12.66_ 50.50 • 5.46 _ 30.00 •

1.04 0.74 1.08 1.45

15.51 42.40 9.14 31.46

_ 1.14 • 0.99 • 1.19 _+ 1 33

18.99 _+ 1.13 36.49 • 1.01 14.05 _+ 1.18 2 9 . 0 0 _ 1.44

17.21 52.08 5.53 24.23

_ 1.02 _+0.59 _ 1.15 • 1.39

17.86 42.40 8.69 29.92

• 1.15 • 0.91 • 1.19 _+ 1.34

19.45 37.25 10.32 31.91

_ 1.22 _+0.87 _+ 1.18 _ 1.21

10.63 55.73 2.81 29.57

_ • _ _

1.12 0.89 1.00 1.24

13.99 47.90 5.01 31.95

• 1.37 • 1.09 • 1.21 _+ 1.09

19.32 34.92 13.35 31.62

+ 1.47 • 0.39 • 1.41 _+ 1.12

12.70 45.51 9.34 31.40

_ _ _ •

1.09 0.75 1.18 1.26

17.26 38.48 12.29 31.00

• 1.08 _ 1.07 • 1.19 +_ 1.20

19.05 35.65 16.41 28.02

• 1.10 +_ 1.08 _+ 1.17 _ 1.18

Harbour seal ZSFA ZShort M U F A ZLong MUFA ZPUFA

Ringed seal YSFA ZShort M U F A ZLong MUFA ZPUFA

Harp seal ZSFA ZShort M U F A ZLong M U F A ZPUFA

In the biplots, the fatty acids (variables) are located in accordance with their influence on the distribution or grouping of the samples (objects). Only fatty acids with high loadings on both PC1 and PC2, and hence influence the distribution of the samples, are presented in the biplots. Fatty acids with low loadings (close to the origin in the biplots) have little or no influence on the distribution of the samples and are removed from the figure to simplify the plots. Fatty acids located adjacent to the samples from the outer blubber layer (Fig. 3) are those with significantly higher relative amount in these samples (Table 3). In the biplot from grey and ringed seals, these fatty acids are located farthest to the left (Fig. 3a,c). In the same manner, fatty acids located adjacent to the samples from the inner layer are found in significantly higher relative amount in the samples from this layer, and are located to the right in the same plots (Fig. 3a,c). The outermost layer displays a significantly higher level of 14:1~o5 and 16:1co7, while 20:1~o9 and 18:0 are found in significantly higher levels in the innermost layer (Table 3). These fatty acids thus discriminate between the outer and inner blubber layer in all four species. Table 4 summarises the amount of saturated (SFA), short-chained (18 carbon atoms or fewer) and long-chained (more than 18 carbon atoms) monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) for the three blubber-layers in each

161

I D Outerlayer [] Middlelayer []

Innerlayer I

Grey seal

60-

Harbour seal

-60

50-

-50

40-

-40

30-

-30

20-

-20 -10

c-

0

i

O

E >

-

i

Harp seal

50

0

-60

Ringed seal

-50 -40

4O

rr

-30 -20

20

10

1

v

I

I

I

I

i

I

I

I

0

Fig. 4. The relative amounts of different groups of fatty acids determined in the blubber cross section

from each of the four species (values are given in Table 4). of the four species. With increasing depth from the epidermis, the amount of SFA in the blubber fat increased, while the amount of MUFA decreased. The relative amount of SFA was found to range from 8.2 in the outermost layer, to 22.6 in the innermost layer, a difference of more than 14 in the cross-section. In the same matter relative values for unsaturated acids were found to range from 91.4 in the outermost layer, decreasing with depth. The lowest value found in the innermost layer was 78, a difference of 13.4 in the cross-section. However, by dividing the monounsaturated acids into short-chained and long-chained, nuances appear (Fig. 4). Long-chained monounsaturated acids increase while short-chained monounsaturated acids decrease with increasing depth in the blubber fat. The relative amount of PUFA shows no significant variation in the stratified blubber samples (Fig. 3).

162 Discussion and Conclusions

In this investigation we use the relative amounts of fatty acids to analyse inter- and intraspecific differences in fatty acid profiles. By using a chemometric method we were able to analyse a large number of samples. The interpretation of a large sample size calls for the use of multivariate techniques. This is in contrast with most earlier investigations of marine lipids which are based on a relatively small number of samples (i.e. one animal) using univariate techniques [5,7,9,18]. Interpretation of one fatty acid at a time does not give a total picture of how the different samples are related to each other. However, this can be obtained by taking all fatty acids into account simultaneously by a multivariate approach.

Tissue differences Considering the saturated acids, the difference between the heart and brain tissue is mainly caused by the lack of 24:0 in brain, while the amount of 24:0 was found to be 6% of the total fatty acid composition in the heart. Similar values have been found in heart and brain from harbour and grey seals [ 19] and from hooded seal (Crystophora cristae), harbour seal and harp seal [20]. However, Grahl-Nielsen and Mjaavatten [20] found a higher value of saturated acids in brain tissue. In fact, the total relative amount of saturated acids was found to be 45 mainly due to higher values of 16:0 and 18:0. This higher value could be due to samples taken from both the grey and white matter. White matter is higher in lipid content than grey matter used in our investigation. Samples from both grey and white matter would probably cause a great variance in the data. However, this variance was not examined. The importance for future examinations of sampling not only the same tissue but also the same part of the tissue should therefore be emphasised. The fatty acid composition of different tissues from marine mammals has been thoroughly investigated, and differences have been found in several species [18]. Ackman et al. [21] found differences between heart and lung tissue from harbour seal. Differences between heart, liver and blubber from grey and harbour seals have also been demonstrated [19]. Engelhardt and Walker [22] demonstrated differences in tissues like heart, brain, liver, aorta, muscles and testes from harp seal. However, an investigation of the black right whale (Eubalena glacialis) concluded that the blubber had the same fatty acid composition as other tissues [23]. All of the above investigations are based on a small sample size, mainly one or at most two animals, and were analysed using univariate methods. Only Grahl-Nielsen and Mjaavatten [20] used multivariate techniques (PCA) to analyse the differences in the fatty acid profile between heart, brain, blubber, jaw-bone, hair and eye-lens. By applying PCA on all the samples from heart, brain and blubber, the analysis shows that blubber has a greater variability than heart and brain (Fig. 2). This variability is possibly due to the function of the different tissues analysed. Blubber is used as the main storage of fat reserves, and in natural conditions synthesis and hydrolysis of fat occur continually [24]. This implies that the fatty acid composition of

163 the blubber possibly will be influenced by the diet. Schweigert et al. [25] assumed that the fatty acid composition in the blubber from grey seal is possibly related to the diet. The same conclusion was also proposed by Ackman and Hooper [19] by comparing fatty acids found in the blubber from harbour and grey seal, and by West et al. [7] by comparing blubber from ringed seal, largha seal (Phoca largha), baikal seal (Phoca fasciata) and bearded seal (Erignathus barbatus). The total relative amount of unsaturated fatty acids in blubber was found to be 82.7% in our investigation. This is in accordance with earlier investigations of blubber from harp seal [6], grey seal [25-27], harbour seal [19] and ringed and bearded seal [28]. The relative amounts of unsaturated fatty acids in prey organisms of grey seal and other marine mammals have also been found to be approximately 80% [25]. By monitoring the fatty acid composition in blubber from harbour and grey seals in captivity, Grahl-Nielsen and Mjaavatten [29] found no significant differences in the composition of the blubber when the diet was switched from herring to mackerel. In spite of the differences in the fatty acid composition of the two prey species, it did not alter the composition of the depot fat significantly. Investigations of subcutaneous adipose tissue from humans indicate that the fatty acid composition of adipose tissue is related to the composition of the diet [30], and that the turnover of fatty acids in humans is approximately 600 days [31]. The fatty acid profile from human adipose tissue will therefore give an indication of the mean fatty acid composition of the diet during the last 3 years [32]. During starvation caused by moulting, pupping and also periods with lack of food, marine mammals utilise the stored fat reserves [33-36]. Investigation of lactating grey seals shows that the mother loses as much as 40% of total body mass during lactation [34], and that approximately 94% of the weight loss is due to decline in blubber mass [37]. This implies that the turnover time of fatty acids in sea mammals is possibly different, being much faster in sea mammals than in humans. A shorter turnover time of the fatty acids implies that the composition of blubber fat in marine mammals could be more influenced by the composition of their diet, especially when the animals are encountering periods of starvation. The investigation done by Grahl-Nielsen and Mjaavatten [29] was based on animals living in captivity. These animals will not encounter natural conditions with periods of starvation, and will possibly have a much lower activity than seals living under more strenuous condition in their natural habitat. This work based on 120 animals concludes that there are significant differences in the fatty acid composition between heart, brain and blubber. The most obvious difference is the amount of polyunsaturated fatty acids of linolenic (o~3) structure typically being associated with marine mammal depot fat. These fatt~ acids are greatly reduced or lacking in the heart and brain. However, it cannot be negated that the diet is of importance when considering the fatty acid profile especially in depot fat.

Layering of the blubber In this work we have demonstrated significant differences in the fatty acid composition in a vertical cross-section by separating the blubber into several layers

164

(Fig. 3). The mean values of the fatty acids found in the blubber in this investigation compare well with earlier investigations [6,7,18,19,25-28]. However, all earlier investigations are based on the assumption of a homogenous blubber in seals. This assumption is based on conclusions drawn by Jangaard and Ke [9] after analysing the blubber from one harp seal. We have analysed 20 animals from four species and they all revealed the same pattern. In all animals, a gradient of the relative amount of fatty acids was found. This gradient may have masked or shaded the results from the work of Jangaard and Ke [9]. Layering of the blubber in marine mammals has been demonstrated earlier in fin whale (Balaenoptera physalis) [2,5], sei whale (Balaenoptera borealis) [3-5], and walrus (Odobenus rosmarus divergens) [8]. This layering of the blubber in seals has, as far as we know, never been demonstrated. One characteristic represented in all the species analysed is the increasing amount of short-chained monounsaturated fatty acids from the inner layer to the skin or outer layer (Fig. 4). Investigation of blubber from fin whale [2,5] and walrus [8] revealed the same pattern. In our investigation the amount of short-chained monounsaturated acids constituted more than 46% of the total lipid content in the outer blubber layer, the total amount of monounsaturated acids in the same layer being more than 55%. However, the long-chained monounsaturated acids do not show the same pattern. In fact, they are decreasing in the same direction. In fin whale [2,6], and in sei whale, blue whale (Balaenoptera musculus) and humpback whale (Megaptera novaengliae) [3,4] the highest level of unsaturated fatty acids was found in the inner layer. This was also demonstrated in walrus [8]. In addition to its function as storage of fat reserves, the blubber plays an important role in thermoregulation [38]. Sea mammals are known to be homeothermal animals, and the blubber is thus heterothermal displaying a temperature gradient from skin to muscle with the temperature ranging from environmental temperature, which can be below 0~ to the body temperature, normally 36-38~ [39]. Compared to whales, seals have a larger surface to volume ratio. In addition, seals are also known to have a thinner insulating blubber layer. The seals may therefore have a large heat loss over the body surface, and it is of great relevance to keep the melting point of the fatty acids at a low level [6]. In fish, an inverse relationship has been demonstrated between the proportion of unsaturated fatty acids and the water temperature that the fish encounter [40]. Unsaturated fatty acids have a lower melting point (-11~ for C18) than saturated fatty acids of the same chain length (79~ for C~8), the melting point increasing with increasing chain length [41]. It should therefore be of great value to have high levels of monounsaturated fatty acids in the blubber, especially when living in arctic and high-boreal regions. Ringed seals were found to have the highest level of short-chained monounsatu-

Fig. 5. Classification of blubber samples by PCA based on 20 fatty acids (the importance of the various fatty acids is given by their position in the biplot), from (a) outer blubber layer, (b) middle blubber layer and (c) inner blubber layer from grey seal (Hg), harbour seal (Pv), ringed seal (Ph) and harp seal (Pg).

165

a)

~PCZ(Z6%) 16:1 to7 1

b) kPCZ(Zl~)

20:4 (06

[8: [ ~ 9

18:1 (o5 2~.5 m3

18:I m7

(o3

PC1(33%)

,

~b,

c) kPCZ(ZO~)

16:0

18:0

phPh

Hg

20.5~ ~

20:4 m6

Pv

Pv

Pg

139

Pgg

Hg

22:6 0~3

L

g

16:1 m 7

20:1 (o9

Hg t~g

Hg

Pu ~)~:4~3Hg

noid2

22:51~ (o5 18:1 m7

%

Pv

Hg

14:l co5

18:1(~9

18:2 (o~"l:)id3

H~b

PC1(30%)"~. ,

166 rated acids in the outer layer (Fig. 4), the amount increasing by 20% from the inner layer. In grey seal and harbour seal the increase was found to be 14%, and 10% in harp seal. Ringed seal is known to be the northernmost seal species, observed as far north as the north pole. The high level of monounsaturated fatty acids may therefore be related to the habitat (arctic and sub-arctic region). We expected to find high levels of monounsaturated fatty acids in harp seal, having boreal and arctic distribution and also greater surface to volume ratio. However, we found higher levels of monounsaturated fatty acids in the sub-arctic and boreal coastal-living grey and harbour seals than in harp seal. It should be noticed that the harp seals analysed were generally leaner than the other species, possibly caused by migration, and this may have masked or disguised the gradient.

Species differences By dividing the blubber into three layers we were able to separate the species by PCA analysis and SIMCA classification. However, the separation between all four species was only significant in the outermost layer (Fig. 5). Species differences in fatty acid composition of blubber have been indicated in earlier investigations [6,7,18,19]. These investigations are all based on univariate treatment of data from few animals, often only one, and without replicates. We have analysed 20 animals with replicate samples from each individual in three blubber layers, a total of 120 blubber samples. This work shows the relevance of newer techniques, i.e. multivariate statistics, in fatty acid analysis of different tissues from marine mammals. The assumption of a homogenous blubber must be discarded and the layering in adipose tissue has to be advised in further analysis for dietary fatty acids as well as in analysis of toxic compounds.

Acknowledgements This study was supported by the Norwegian Research Council. We thank T. Oritsland and K.A. Fagerheim, Institute of Marine Research, Bergen, T. Haug and S. Kjelquist, Fisheries Research Institute, Tromsr for the collection of samples.

References 1. Ackman RG, Lamothe F. Marine mammals. In: Ackman RG (ed) Marine Biogenic Lipids, Fats and Oils II. Boca Raton, FL: CRC Press, 1989;179-381. 2. Ackman RG, Eaton CA, Jangaard PM. Lipids of the fin whale (Balaenoptera physalus) from North Atlantic waters. I. Fatty acid composition of whale blubber and blubber sections. Can J Biochem 1965;43:1513-1520. 3. Ackman RG, Hingley JH, Eaton CA, Logan VH, Odense PM. Layering and tissue composition in the blubber of the North-West Atlantic sei whales (BaIaenoptera borealis). Can J Zool 1975;53:1340-1344.

167 4. Ackman RG, Hingley JH, Eaton CA, Sipos JC. Blubber fat deposition in mysticeti whales. Can J Zool 1975;53:1332-1339. 5. Lockyer CH, MacConnell LC, Waters TD. The biochemical composition of fin whale blubber. Can J Zool 1984;62:2553-2562. 6. Ackman RG, Epstein S, Eaton CA. Differences in the fatty acid composition of blubber fats from northwestern Atlantic fin whales (Balanoptera physalus) and harp seals (Phoca groenlandica). Comp Biochem Physiol 1971;40:683-697. 7. West GC, Burns JJ, Modafferi M. Fatty acid composition of blubber from the four species of Bering Sea phocid seals. Can J Zool 1979;57:189-195. 8. West GC, Burns JJ, Modafferi M. Fatty acid composition of Pacific walrus skin and blubber fats. Can J Zool 1979;57:1249-1255. 9. Jangaard PM, Ke PJ. Principal fatty acids of depot fat and milk lipids from Harp seals (Pagophilus groenlandica) and Hooded seals (Cystophora cristata). J Fish Res Bd Can 1968;25:2419-2426. 10. Kvalheim OM, Oygard K, Grahl-Nielsen O. SIMCA multivariate data analysis of blue mussel components in environmental pollution studies. Anal Chim Acta 1983;150:145-152. 11. Grahl-Nielsen O, Barnung T. Variations in the fatty acid profile of marine animals caused by environmental and developmental changes. Mar Environ Res 1985; 17:218-221. 12. Ugland KI, JCdestr KA, Aspholm PE, KrCyer AB, Jacobsen T. Fish consumption by invading harp seals off the Norwegian coast in 1987 and 1988. International Council for the Exploration of the Sea, J Mar Sci 1993;50:27-38. 13. Pearson K. On lines and planes of closest fit to a system of points in space. Philos Mag 1901 ;2:227-572. 14. Kvalheim O, Kvarstang TV. A general-purpose program for multivariate data analysis. Chemom Intel Lab Sys 1987;2:235-237. 15. Wold S, Sj6str6m M. SIMCA a method for analyzing chemical data in terms of similarity and analogy. In: Kowalski BR, Chemometrics: Theory and Applications. American Chemical Society Symposium Series, 1977;243-282. 16. Albano C et al. Pattern recognition by means of disjoint principal component models (SIMCA). Philosophy and methods. Proceeding Symposium on Applied Statistics, Copenhagen, 1981;182217. 17. Wold S. Cross-validatory estimation of the number of components in factor and principal component models. Technometrics 1978;20:397-405. 18. Ackman RG. Marine Biogenic Lipids, Fats, and Oils II. Boca Raton, FL: CRC Press, 1989. 19. Ackman RG, Hooper SN. Long-chain monoethylenic and other fatty acids in heart, liver, and blubber lipids of two harbour seals (Phoca vitulina) and one gray seal (Halichoerus grypus). J Fish Res Bd Can 1974;31:333-341. 20. Grahl-Nielsen O, Mjaavatten O. BestandsundersCkelse av sjCpattedyr ved hjelp av fettsyreprofiler. Sluttrapport sjr 1991. 2i. Ackman RG, Hooper SN, Hingley J. The Harbor Seal Phoca vitulina concolor De Kay: comparative details of fatty acids in lung and heart phospholipids and triglycerides. Can J Biochem 1972;50:833-838. 22. Engelhardt FR, Walker BL. Fatty acid composition of the harp seal, Pagophilus groenlandicus (Phoca groenlandica). Comp Biochem Physiol 1974; 169-179. 23. Morris RJ, Culkin F. Marine lipids: analytical techniques and fatty acid ester analysis. Oceanogr Mar Biol Annu Rev 1976;14:391-433. 24. Stryer L. Biochemistry. New York: W.H. Freeman, 1988. 25. Schweigert FJ, Stobo WT, Zucker H. Vitamin E and fatty acids in gray seal (HaUchoerus grypus). J Comp Physiol Ser B 1990; 159:649-654. 26. Ackman RG, Jangaard PM. The gray (Atlantic) seal; fatty acid composition of the blubber from a lactating female. Can J Biochem 1965;43:251-255. 27. Ackman RG, Eaton CA. n-3 Docosapentaenoic acid in blubber of dam and pup gray seals

168

(Halichoerus grypus): implications in the inuit diet and for human health. Can J Zool 1988;66:2428-2431. 28. Innis SM, Kuhnlein HV. The fatty acid composition of northern Canadian marine and terrestrial mammals. Acta Med Scand 1987;222:105-109. 29. Grahl-Nielsen O, Mjaavatten O. Dietary influence on fatty acid composition of blubber fat of seals as determined by biopsy: a multivariate approach. Mar Biol 1991;110:59-64. 30. Plakk6 T, Berkel J, Beynen AC, Hermus RJJ, Katan MB. Relationship between the fatty acid composition of the diet and that of the subcutaneous adipose tissue in individual human subjects. Hum Nutr Appl Nutr 1983;37A:365-372. 31. Dayton JA, Hashimoto S, Dixon W, Pearce ML. Composition of lipids in human serum and adipose tissue during prolonged feeding of a diet high in unsaturated fat. J Lipid Res 1966;8:508. 32. Beynen AC, Hermus RJJ, Hautvast JGAJ. A mathematical relationship between the fatty acid composition of the diet and that of the adipose tissue in man. Am J Clin Nutr 1980;33:81. 33. Bonner WN. Gray seal Halichoerus grypus Fabricius, 1791. In: Ridgeway SH, Harrison FR (eds) Handbook of Marine Mammals, Vol 2 Seals. London: Academic Press, 1981;11-144. 34. Fedak MA, Anderson SS. The energetics of lactation; accurate measurements from a large wild animal, the gray seal (Halicoerus grypus). J Zool London 1982;198:473-479. 35. NordCy ES, Blix AS. Energetics of Gray seal pups during the post-weaning fast. Acta Physiol Scand 1985;124:542. 36. Sergeant DE. Feeding, growth and productivity of northwest Atlantic harp seals (Phoca groenlandica). J Fish Res Bd Can 1973;17-29. 37. NordCy ES, Ingebretsen OC, Blix AS. Depressed metabolism and low protein catabolism in fasting Gray seal pups. Acta Physiol Scand 1990;139:361-369. 38. Ryg M, Smith TG, ~ritsland NA. Thermal significance of the topographical distribution of blubber in ringed seals (Phoca hispida). Can J Fish Aquat Sci 1988;45:985-992. 39. Irving L. Temperature regulations in marine mammals. In: Andersen HT (ed) The Biology of Marine Mammals. New York: Academic Press, 1969;168-174. 40. Geraci JR. Pinniped nutrition. International Council for the Exploration of the Sea 1975;169:312323. 41. Hart H. Organic Chemistry. Boston, MA: Houghton Mifflin, 1987.

9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. Wall0eand O. Ulltang,editors

Studies of the social ecology of Norwegian

169

killer whales

(Orcinus

orca) Anna Bisther ~ and Dag Vongraven 2 1University of GOteborg, Kristineberg Marine Research Station, Fiskebdckskil, Sweden; and 2University of Trondheim, Department of Zoology, Dragvoll, Norway Abstract. Killer whales along the Norwegian coast have been studied since 1990 with methods based on photo-identification. Preliminary insights of the social characteristics of Norwegian killer whales are presented generally. About 400 killer whales are identified, and 65% of the whales have been resighted. The whales occur in groups of moderate sizes, all containing adult males and breeding females. The groups seem to be social units based at least partly on stable membership. Acoustic analyses revealed both uniqueness and a variable degree of similarity in the vocalization of different groups of whales. The social integrity of groups is further indicated by cooperative feeding on herring, communal care of young, competitive interactions between groups and specialized feeding on marine mammals by one small group of whales. Some adult males have a nomadic occurrence, and might eventually represent a mating strategy. Ritualized interactions between males appear to be affiliation acts. Large males and female-sized whales do not seem to differentiate in diving behaviour during cooperative feeding due to synchrony in respiration patterns. Norwegian killer whales resemble the well-studied Canadian killer whales, but there are also indications of some intraspecific variability.

Key words: mammals, male strategies, acoustic communication, communal care

Introduction This presentation is a brief summary of behavioural studies conducted within the present project on Norwegian killer whales. It introduces methods and approaches that have been utilized during the past few years, and contains a synoptic discussion of some findings. Detailed results are to be published elsewhere. Killer whales occur regularly along the Norwegian coast and are reported to follow the migration of their main prey item, the Atlanto-Scandic herring (Clupea harengus) [1]. The impact of killer whale predation upon the herring stock caused concern in the early 1970s, and resulted in a protective hunt for killer whales in Norwegian coastal waters [2]. Norwegian authorities then issued a provisional ban on killer whale catches in 1982 because of incomplete knowledge of the status of the whale population. The project on Norwegian killer whales was initiated in 1990, and one objective is to contribute with ecological and life history data for assessment of the population. The social life of the whales is also being studied, where different behavioural aspects are combined into themes. These are partly based on results from the compre

Address for correspondence: A. Bisther, University of G6teborg, Kristineberg Marine Research Station, 450 34 Fiskeb~ickskil, Sweden.

170 hensive research on Canadian killer whales [3,4], but also on theoretical work on large mammals in general.

Methods

Field work has been conducted in both of the areas where killer whales concentrate seasonally; the spawning grounds of herring off the coast of Mere (63~ during early spring, and in the fjords off Ofoten (68~ where the herring reside during the winter months [5]. The winter season provides a unique scenario, since about 500 killer whales enter the fjords and stay until the end of January when the herring starts to migrate south towards the spawning grounds. The project is based on photo-identification where individual whales are identified by their natural and permanent markings [6]. The principle of photo-ID is illustrated in Fig. 1. Identified whales are given alphanumeric codes, which are stored on file together with information on time, location and demographic characters. The database is then utilized for several ecological objectives such as migrational pattern and population size. Behavioural studies include the underwater vocalization of the whales, where acoustic recordings have been obtained with a hydrophone system covering frequencies up to 20 kHz. Data on social events and respiration patterns have been sampled from direct observations and logged utilizing a computer-based recorder or dictaphones. Progressive analyses of behavioural and photographic data refer to (i) the social integrity of groups, (ii) male strategies and (iii) social determinants for large carnivores (e.g. cooperative hunting tactics and communal care of young).

Results

Results are described in general terms. Each behavioural aspect is still based on quantitative field work, and includes both the completed and the continuous studies of killer whale behaviour.

Social integrity of groups About 400 killer whales have been identified within the project, and 65% of these whales have been re-sighted during the years. The whales occur in groups of moderate sizes (-15 animals), all containing adult males and breeding females. Long-term associations (years) are present both between and within the two sexes, and the groups seem to be social units based at least partly on stable membership. Competitive interactions between groups of whales are occasionally observed as "feeding patch take-overs", where one feeding group is forced to leave because of the rapid approach of another. The interactions contrast the usual tolerance ex-

171

~.

.,.~

~

' -~. '

t',,~

.,~. ,..

9 ~.4

9

,

~

o

~

,

,

~

Fig. 1. Examples of photographic identification of Norwegian killer whales (photo" Dag Vongraven).

pressed between killer whale groups feeding independently of each other within close range. Analyses of the vocalization of four different groups of whales revealed stereotyped repetitions of a limited repertoire of acoustic signals classified as "discrete

172

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calls" (defined and illustrated in Fig. 2). Each group could be acoustically distinguished even if a variable degree of similarity was present [7].

Male strategies Males are identified as being either permanent companions to females, or nomadic. Male-male pairs are frequently observed as distinct units, where they might spend several hours in homosexual and highly ritualized activities. "Courtship trios", temporary constellations of two adult males and a female, have occasionally been observed to be engaged in sexual activities. Adult males are also observed to act as "baby-sitters", where a calf or a juvenile is closely attached to the male. This "echelon" position gives the smaller whale energetic benefits through assisted locomotion [8]. A few females are identified as alloparents because of the large number of young at their sides. Respiration profiles were obtained on pairs of instantly identifiable whales, a male and a female-sized whale simultaneously, to investigate if the two sexes differentiated in their diving behaviour during cooperative feeding. An example of a set of profiles is given in Fig. 3.

173 I

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Discussion The social system and behavioural ecology of Norwegian killer whales are gradually pieced together with photographic, bioacoustic and behavioural data. As for most studies on free-ranging whales, this project also has a long-term perspective. Considering the preliminary insights that have been obtained so far, the killer whales off the Norwegian coast seem to have social characteristics in common with their Canadian conspecifics. The cooperative nature of Norwegian killer whales is stated both in their coordinated feeding activities [9], and in the communal care of young where small individuals are hydrodynamically carried by adult group members. The genealogy of the whales is unknown, but the photographic data still indicate stability in group com-

174 position. If Norwegian killer whales are socially organized in the same way as Canadian killer whales, the groups would be matrilineal kin units where even the adult males refrain from dispersing from their natal "pod" [3]. However, intraspecific variation might be found among the strategies of the males. Some of the Norwegian killer whale males seem to have a nomadic lifestyle where they repeatedly occur together with different groups of whales. The presence of other males in the groups does not prevent these males entering the group, participating in cooperative feeding or leaving the group together with a female. These nomads are few, compared to males that are consistently identified together with the same females, and they might represent one of two strategies in accordance with the mating system of the brown hyena (Hyaena brunnea) [10]. Among these animals, the males either become nomadic and mate with unrelated females, or stay in their natal clans and gain reproductive success through alloparenting the cubs of their female relatives. Another possibility, if the killer whale males do have a nomadic strategy, might be the importance of age, size and social rank upon dispersal from the natal group. Because of the previous catch of Norwegian killer whales, it is also possible that the nomadic males are not representing any strategy but are merely a consequence of disrupted groups. Male mammals usually compete for access to receptive females [ 11 ]. Among bottlenose dolphins (Tursiops truncatus), male competition takes the form of physical fighting resulting in heavily scarred bodies of the oldest animals [ 12]. Male aggression has not been observed from the surface behaviour of Norwegian killer whales, but the males frequently occur in pairs, detached from other whales in their vicinity. At these instances, the males might spend a considerable amount of time in a ritualized activity descriptively termed "body contact-belly up-beak genital". Due to the quantified reciprocity and symmetry of roles in the display, the behaviour resembles the sexual gestures used as ritualized greetings between adult male baboons (Papio cynocephalus anubis) [13]. These male primates form stable coalitions where they take the oestrus females of a troop away from other males. In that respect, male baboons have a similar strategy to male bottlenose dolphins in Shark Bay, western Australia [ 14]. The behavioural studies of Norwegian killer whales are too preliminary to be conclusive about the formation of alliances or coalitions among males. The sexual activities observed to occur between two males and a female might however indicate some form of cooperative relationship between adult males. The size differences between male and female killer whales were discussed by Bain [15]. He quotes the work of Peters [16], and since the larger sized males are able to swim more efficiently at higher speeds than females, they would also have the ability to feed at greater depths. Bain suggests that the philopatric males in the Canadian killer whale population might "disperse" ecologically rather than geographically. Adult males would thereby reduce the cost of sharing food resources with their maternal groups. In a Norwegian version of the idea of ecological dispersal, respiration profiles were measured for pairs of killer whales while they were cooperatively feeding on

175 herring with their groups. The diving behaviour of males and female-sized whales during feeding was however highly synchronous. No differences were found that could attribute a specific role for the larger males when measuring the respiration patterns. However, these data were sampled in an area where food is superabundant, and only in a final stage of the feeding when the herring has been herded towards the surface. The males might still compensate for their larger size and higher energetic needs. Solitary feeding on fish has only been observed to include males, which is also described to occur among Canadian killer whales [ 17]. The acoustic communication of killer whales consists of high frequency whistles and pulsed signals that can be either variable or discrete [18]. Discrete "calls" are produced by the whales in a stereotyped way, and each Canadian killer whale pod was found to have a limited but unique and stable repertoire of discrete calls [19]. The pod-specific vocalization was termed "dialects", and is suggested to have evolved among Canadian killer whales as a result of the social structure of the population [4]. The primary function of dialects might be to promote group cohesiveness and to coordinate behavioural activities. The acoustic properties of Norwegian killer whale vocalization resemble dialects. Different groups can be acoustically distinguished, repertoire sizes of discrete calls are comparable, there is a variable degree of similarity between groups and the relative use of calls is about the same [7]. The knowledge of the social organization of Norwegian killer whales is however incomplete. It remains to be demonstrated that all groups are stable units with no long-term exchange of individuals or sub-groups, which is the prerequisite of dialects. Many years of field work on Norwegian killer whales are still required before the results can be adequately compared with the insights revealed from the Canadian killer whale population. Knowledge of the Canadian whales is meanwhile being used as a "model" in the Norwegian research, to search for similarities or variations. Sometimes both occur, as in a small group of Norwegian killer whales that seem to have developed specialized feeding on marine mammals. In that respect, they are "transient" as the carnivorous killer whales in the Canadian population are termed [20]. The Norwegian "transients" still seem to diverge from the Canadian definition, since they are not socially isolated from fish-feeding groups of whales. Further aspects on comparative social ecology will clarify differences between characteristic traits for the killer whale and intraspecific variations due to various ecological factors.

Acknowledgements For the enthusiastic assistance on board M/S Bella, we acknowledge Marianne Olsen, Bente Brekke, Elle Lettevall, Tyri Askl6f, Leffe Strandh, brother and sister Bisther. The project was financed in the period 1990-1993 by The Norwegian Fisheries Research Council as part of the national research program on marine mammals.

176

References 1. Christensen I. Distribution, movements and abundance of killer whales (Orcinus orca) in Norwegian coastal waters, 1982-1987, based on questionnaire survey. Rit Fiskideildar 1988;11:7988. 2. ~ien N. The distribution of killer whales (Orcinus orca) in the North Atlantic based on Norwegian catches, 1938-1981, and incidental sightings, 1967-1987. Rit Fiskideildar 1988;11:65-78. 3. Bigg, MA, Olesiuk PF, Ellis GM, Ford JKB, Balcomb KC. Social organization and genealogy of resident killer whales (Orcinus orca) in the coastal waters of British Columbia and Washington State. Rep Int Whal Commn 1990;(Special Issue 12):383-405. 4. Ford JKB. Vocal traditions among killer whales (Orcinus orca) in coastal waters of British Columbia. Can J Zool 1991 ;69:1454-1483. 5. RCttingen I. A review of variability in the distribution and abundance of Norwegian spring spawning herring and Barents Sea capelin. Polar Res 1990;8:33-42. 6. Bigg MA, Ellis G, Balcomb KC. The photographic identification of individual cetaceans. Whalewatcher (J Am Cetacean Soc) 1986;20(2):10-12. 7. Bisther A. The acoustic communication of social groups of photographically identified killer whales (Orcinus orca) at the coast off Norway. Master thesis, University of Gtiteborg, Sweden, 1991. 8. Lang TG. Hydronamic analysis of cetacean performance. In: Norris KE (ed) Whales, Dolphins and Porpoises. Berkley, CA: University of California Press, 1966;410--432. 9. Simil~i T, Ugarte F. Surface and underwater observations of cooperatively feeding killer whales, Orcinus orca, in northern Norway. Can J Zool 1993;71:1494-1499. 10. Mills MGL. The comparative behavioral ecology of hyenas: the importance of diet and food dispersion. In: Gittleman JL (ed) Carnivore Behavior, Ecology and Evolution. London: Chapman and Hall, 1989;125-143. 11. Poole T. Social Behaviour in Mammals. New York: Chapman and Hall, 1985. 12. Scott MD, Irvine AB, Wells RS. A long-term study of bottlenose dolphins on the west coast of Florida. In: Leatherwood S, Reeves RR (eds) The Bottlenose Dolphin. San Diego, CA: Academic Press, 1990;235-243. 13. Smuts BB, Watanabe JM. Social relationships and ritualized greetings in adult male baboons (Papio cynocephalus anubis). Int J Primatol 1990; 11 (2): 147-172. 14. Connor RC, Smolker RA, Richards AF. Two levels of alliance formation among male bottlenose dolphins (Tursiops sp.). Proc Natl Acad Sci USA 1992;89:987-990. 15. Bain DE. An evaluation of evolutionary processes: studies of natural selection, dispersal and cultural evolution in killer whales (Orcinus orca). Ph.D. dissertation, University of California, Santa Cruz, 1989. 16. Peters RH. The Ecological Implications of Body Size. New York: Cambridge University Press, 1983. 17. Hoelzel RA. Foraging behaviour and social group dynamics in Puget Sound killer whales. Anim Behav 1993;45:581-591. 18. Ford JKB. A catalogue of underwater calls produced by killer whales (Orcinus orca) in British Columbia. Can Data Rep Fish Aquat Sci No 633, 1987. 19. Ford JKB, Fisher HD. Group-specific dialects of killer whales (Orcinus orca) in British Colombia. In: Payne R (ed) Communication and Behavior of Whales. AAAS Sel Symp Series 76, Boulder, CO: Westview Press, 1983;129-161. 20. Baird RW. Foraging behaviour and ecology of transient killer whales (Orcinus orca). PhD thesis, Simon Fraser University, Canada, 1994.

9 1995Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang, editors

177

Possible effects of previous catch on the present population of Norwegian killer whales (Orcinus orca) D a g V o n g r a v e n 1 and A n n a Bisther 2 1Department of Zoology, University of Trondheim-A VH, Dragvoll, Norway; and 2Kristineberg Marine Research Station, University of Gothenburg, 45 034 Fiskebiickskil, Sweden A b s t r a c t . Intensive coastal killer whale catches undertaken in the two decades after 1960 (especially in

1969, 1970 and 1979), might have had effects on reproduction and social behaviour in the present Norwegian killer whale community. The catch was both sex- and age-biased, and this might have triggered compensatory mechanisms. Our approach when studying the social ecology of Norwegian killer whales must take into account the possible presence of such mechanisms. Further modelling studies are in progress. K e y w o r d s : killer whales, catch data, reproduction, social ecology

Introduction

The killer whale population off the Norwegian coast has previously been subjected to a hunting pressure with unknown effects upon the present population. Results and insights from an on-going photo-ID study indicate that this population is stationary and has evolved complex social behaviour. Other species of long-lived, slow-reproducing mammals that live in socially structured societies have been shown to respond to hunting with changes in social strategies, either as an effect of a reduced population density (i.e. simakobu monkey Nasalis concolor [1 ]) or as an effect of selective takes of large and old individuals (i.e. elephants Loxodonta africana [2]). Could peaks in the catch of killer whales one generation ago have had any other effects than a reduced size of the present population?

Materials and Results

There are official catch records of 2435 killer whales caught in the North Atlantic in the period from 1938 to 1981. Of these, 64% were caught in the coastal waters off Norway. Twenty-nine percent of the total catch in the whole period occurred in the three seasons 1969 (231), 1970 (246) and 1979 (221), and 91% of these were caught in the coastal fishery zones. Temporal and spatial intensity is especially characteristic of the catch during these years, during which the majority of the whales were caught

Address for correspondence: D. Vongraven, Department of Zoology, University of Trondheim-AVH, 7055 Dragvoll, Norway.

178 a

1969/1970

b

1979 Sex ratio in total catch (F : M)

Sex ratio in total catch (F : M)

1:2.1 20

1.2:1 20

IMMATURE WHALES

~ ~o

"~

IMMATURE WHALES

10

s 0

MALES

FEMALES BOTHSEXES

0

Fig. 1. Characteristics of the Norwegian killer whale catch, depicting the sex- and age-biases in the peak seasons (a) 1969 and 1970; and (b) 1979.

in the space of 1-2 months within a single fishery zone every season. The 1969/1970 catch was concentrated in the MOre region, while the 1979 catch was concentrated in Lofoten. Females are sexually mature at an average length of 15 ft, and males at 18 ft [3]. Seventy-one percent of the total catch was recorded after 1960, and the fraction of immature whales in the same period was 11.9%. The corresponding fraction for the two high intensity years 1969 and 1970 was 6.9%, and for 1979 15.9%. Of all the whales caught after 1960, a fraction of only 4.2% were smaller than 15 ft (Fig. 1). The overall sex ratio for sexually mature whales is close to 1:1.3 (females/males) for all seasons. However, there are large variations between years. The sex ratio for the two seasons 1969/1970 was 1:2.1, whereas the sex ratio for the 1979 season was 1.2:1 (Fig. 1). There was a switch from a female-biased to a male-biased sex ratio at lengths above 19 ft.

Discussion There are two factors that indicate that the catch in the peak seasons could be regarded as high compared to the total size of the killer whale community. First, a total number of identified whales in the range of 5-700 individuals and fractions of resightings of 65% and 90% in the two on-going photo-ID studies off the Norwegian coast indicate that a population size much bigger than this is improbable (Simil~i personal communication; Bisther and Vongraven, unpublished data). Second, the female bias in the catch from 1979 could be considered as a direct effect of the malebiased catch from previous years, and especially the 1969/1970 catch, if population size was in the size range previously suggested.

179 There is an obvious size bias in the catch from these peak seasons. Given that young whales rely on nursing and care-taking from adult whales for survival, the relative absence of calves and juveniles in the latest catch records could have led to an increase in their future mortality as many parents and potential care-giving individuals were removed. In the Pacific Northwest, when comparing two populations of killer whales with different exploitation histories, Bain [4] found a neonate mortality of 63% in the cropped population and 41% in the uncropped population, whereas adult survivorship was similar. A tendency towards a higher juvenile mortality (up to an age of 15 years) in cropped than in uncropped pods has also been shown by Olesiuk et al. [5]. Live-capture fishery for killer whales in the North-American Pacific Northwest removed approx. 25% of the initial population in the period 1964-1975 [6]. If the population size of Norwegian killer whales in the 1960s was in the order of magnitude previously suggested, then the "coastal" fraction of the 477 whales caught in 1969 and 1970 would at least represent a similar fraction of the population at that time. Findings like these point to the fact that killer whale reproduction depends on social as well as on density dependent determinants. It is also easier to comprehend compensatory mechanisms being induced on a group level rather than on an overall reduced density in the whole area inhabited by the population [7]. Destruction of social structures caused by biased removal of individuals from the population could account for some of the loose group structure suggested by our data. Further modelling studies with basis in the catch data will be carried out. 13y means of different scenarios for population status and catch regime, and previously published vital rates, we will try to investigate what possible effects the catch might have had on the social structure of the population. Finally, we wish to place the emphasis on the potential importance of the catch, and on the influence this ought to have on our approach when studying the social system of Norwegian killer whales. References 1. Watanabe K. Variations in group composition and population density of two sympatric mentawaian leaf-monkeys. Primates 1981 ;22:145-160. 2. Eltringham SK. Elephants. Blandford Books, 1982;52-56. 3. Christensen I. 1982. Killer whales in Norwegian coastal waters. Rep Int Whal Commn 1982;32:633--641. 4. Bain DE. An evaluation of evolutionary processes. Ph.D. Thesis, University of California, Santa Cruz, 1988. 5. Olesiuk PF, Bigg MA, Ellis GM. Life history and population dynamics of resident killer whales O r c i n u s o r c a in the coastal waters of British Columbia and Washington State. Rep Int Whal Commn 1990;(Special Issue 12):209-243. 6. Bigg MA, MacAskie IB, Ellis G. Abundance and movements of killer whales off eastern and southern Vancouver Island with comments on management. Preliminary Report, Arctic Biological Station, Ste. Anne de Bellevue, Quebec, 1976. 7. Fowler CW. Density dependence in cetacean populations. Rep Int Whal Commn 1984;(Special Issue 6):373-379.

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Distribution, diet and feeding ecology

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9 1995 ElsevierScience B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand t3. Ulltang,editors

183

New approaches to studying the foraging ecology of small cetaceans A n d r e w J. R e a d Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA Abstract. Dolphins and porpoises spend the majority of their lives underwater, out of the view of human observers. Consequently, scientists have relied on indirect means to study the foraging ecology of these animals. These indirect methods, such as examining the stomach contents of carcasses, provide an incomplete and often biased view of their feeding ecology. Promising new technological developments with data loggers and satellite telemetry are beginning to offer alternative methods to studying the foraging ecology of small cetaceans. Data loggers have long been used with other marine vertebrates but have not been suitable for dolphins or porpoises because the devices must be retrieved to recover stored data. Recent advances in their recovery have overcome some of these difficulties and loggers have now been successfully deployed on several species of small cetaceans. A new generation of small satellitelinked transmitters has allowed researchers to follow the movements and diving behaviour of animals from their offices. Continuing developments in these fields will afford new opportunities to study the lives of dolphins and porpoises and better understand how they find and obtain food at sea.

Key words: foraging, ecology, small cetaceans

Introduction Dolphins and porpoises spend most of their lives underwater, out of the view of human observers. Many species also live in remote habitats where direct observation of their behaviour is difficult and often impossible. Consequently, for most of these animals, our knowledge of their foraging ecology is limited to inferences made from the examination of carcasses obtained as strandings, incidental catches in commercial fisheries, or from directed catches. Even when we are able to observe dolphins and porpoises catch their prey, we are usually limited to events at or near the surface that are unlikely to be representative of the true range of predator-prey interactions. The traditional approach to studying the foraging ecology of small cetaceans has been to examine stomach contents and attempt to reconstruct the diet from samples of hard parts [21,22]. With this dietary information in hand, it is then possible to make some inferences regarding the foraging ecology and behaviour of the marine mammal. A preponderance of benthic and demersal prey items in the diet would indicate that an animal was feeding at or near the sea floor, for example. This is a valuable exercise that provides important information on the diet of small cetaceans. It is also fraught with potential pitfalls and biases that must be taken into account when reconstructing the diet and making inferences about behaviour. Most of these poten-

Address for correspondence: Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.

184 tial biases are well known (see the review of Pierce and Boyle [21] for a full description). A few examples will illustrate some of the problems associated with such dietary analysis. First, the sample may not be representative of the diet of the population because of the manner in which specimens were obtained. For example, observations of the stomach contents of stranded animals may not reflect their true diet, particularly if the animals were sick for some time before their death. The stomach contents of animals killed incidentally in fishing operations may be biased towards the target species of the fishery and not represent the diet of the population when it is not interacting with fishing gear. A second class of biases arises through the differential ingestion, digestion, and retention of hard parts. Some animals may ingest only the bodies of prey, without consuming the heads (and otoliths). The rates at which hard parts digest in the stomachs of small cetaceans are not known, but it is clear that these rates differ among prey taxa. Squid beaks are resistant to digestion, for example, and are believed to be retained in the stomach much longer than otoliths [5]. It is particularly difficult, therefore, to reconstruct the diet of a marine mammal that feeds on both squid and fish with any accuracy. Finally, the presence of a particular item in the diet tells us little of how, when or where the marine mammal came to locate and capture the prey. A mid-water fish that undertakes pronounced vertical migration could be captured at depth during the day, or near the surface between dusk and dawn; its presence in the stomach tells us little about the foraging behaviour of the predator. A considerable amount of research has helped to overcome some of these biases. Indirect means of examining the diet of marine mammals have been developed, such as studying the fatty acid composition [ 11 ] or stable isotope ratios [ 1] of tissues and comparing them to potential prey. The digestion rates of hard parts of various sizes and shapes have been measured in the laboratory to help understand the biases associated with differential digestion times [22]. And biochemical techniques have been developed to identify the presence of different prey species without using hard parts [21 ]. Taken together, these methods offer researchers a powerful array of tools with which to study the diet of small cetaceans. More promising, however, is the development of methods that allow researchers to follow the activities of individual animals at sea and thus make more direct observations of foraging behaviour [7]. Early attempts to use conventional radio telemetry to study the diving behaviour of common dolphins (Delphinus delphis) were promising [9], but the tags available at that time were too cumbersome for widespread application. Recent advances in the miniaturization, attachment and recovery of data Table 1. Deployments of time-depth recorders (TDRs) on small cetaceans

Species

N

Maximum depth (m)

Reference

Harbour porpoises Spotted dolphins Orcas

7 5 7

226 203 173

[27] [24] [3]

185 loggers and satellite-linked tags have allowed researchers to begin to use these tools to study how marine mammals find and obtain their food at sea [6,7]. The basic technology for both these approaches has been available for some time, but only recently have they been suitable for use with dolphins and porpoises. These applications will revolutionize the way that we study the foraging ecology of small cetaceans in the next decade.

Data loggers Data loggers are microprocessor-controlled devices that record information obtained from external sensors. The most common and best known application of this system is the time-depth recorder (TDR), which has been used on a variety of marine vertebrates and developed extensively with pinnipeds [13]. The earliest TDRs mechanically recorded depth profiles on film [6]. The current generation of TDRs sample ambient pressure at pre-set intervals and store this information as hexadecimal code on a microchip [6,7]. The data are downloaded to a computer after the TDR is retrieved and the code converted to depth information. The need to recover the TDR has been one of the major obstacles to the use of these devices on dolphins and porpoises. TDRs can be attached to and recovered from pinnipeds when they haul out, often in a predictable location. Unfortunately, dolphins and porpoises are not inclined to haul out and allow researchers to attach devices to them. Three innovative approaches have overcome this obstacle, however, and TDRs have now been successfully deployed on harbour porpoises (Phocoena phocoena), spotted dolphins (Stenella attenuata) and orcas (Orcinus orca) (Table 1). The first successful deployment of a TDR on a cetacean was made by Westgate et al. [27], who studied the diving behaviour of harbour porpoises in the Bay of Fundy, Canada. These researchers developed a tag that incorporated a TDR and a small VHF radio tag in a buoyant epoxy package. The tags were attached to porpoises released from herring weirs with the help of commercial fishermen. The attachment mechanism incorporated two small magnesium nuts that corroded rapidly in salt water, allowing the package to detach from the porpoise and float to the surface, where it could be located by conventional radio telemetry. Seven of eight tags were recovered, with one tag retrieved 17 days after it was deployed. Scott et al. [24] tagged and tracked spotted dolphins associated with yellowfin tuna (Thunnus albacares) in the Eastern Tropical Pacific. These dolphins were captured with a chartered commercial purse seiner, tagged with a saddle-mounted TDR and VHF radio assembly and followed from a research vessel. After a period of several days the animals were recaptured with the purse seiner and the saddles removed. In addition, these researchers investigated the bond between dolphins and yellowfin tuna by attaching acoustic tags to the tuna and simultaneously tracking the movements of fish and mammals. Another unique approach was taken by Baird and Goodyear [3,4], who attached a buoyant TDR-VHF package to orcas in the waters of Vancouver Island, British Co-

186 lumbia. The tags were attached to the whales with suction cups, using a crossbow or long pole. A magnesium disc was incorporated into the wall of the suction cup; when the magnesium corroded and the suction was broken, the package detached and floated to the surface. These tags were recovered after a deployment period of up to 8.4 h [3]. In each of these three cases, TDRs provided a wealth of new information on the diving behaviour of the species in question. For example, in the study of Westgate et al. [27], one harbour porpoise dove to the deepest part of the Bay of Fundy (226 m) and most of the tagged porpoises routinely made dives to over 100 m. Most dives were flat-bottomed, with rapid descent and ascent rates and prolonged periods of time at a relatively constant depth during the mid-portion of the dive. The authors interpreted this behaviour as foraging, probably at or near the sea floor, although it was not possible to obtain synoptic data on water depth. This supports the observations of Recchia and Read [23], who found a preponderance of Atlantic herring (Clupea harengus) and silver hake (Merluccius bilinearis) in the stomach contents of harbour porpoises killed in bottom-set gill nets. Herring and silver hake are found predominantly at depth during the day, although both are believed to migrate upwards in the water column at night. Surprisingly, however, the tagged porpoises made longer and deeper dives at night, when their prey are thought to be closer to the surface. This diel variation in diving behaviour is not currently understood, but will undoubtedly spur further study of the foraging behaviour of this species. These three studies demonstrate some of the potential for using data loggers, and particularly TDRs, to study the foraging ecology of small cetaceans. We are beginning to gain an appreciation for the diversity of diving behaviour in dolphins, porpoises, and small whales and to consider some of the factors responsible for this variation. The three studies also demonstrate some of the limitations of this approach as it is currently employed. The use of TDRs with small cetaceans requires researchers to both attach and recover the tags. The non-invasive attachment of Baird and Goodyear [3,4] obviates the requirement of capturing an animal to attach a TDR, but their approach does not allow for a long-term deployment that will provide information on diel patterns in behaviour. In addition, we are still limited in our understanding of the foraging ecology of these animals because TDRs give us only an indirect view into their feeding behaviour. We assume that flat-bottomed dives represent foraging excursions, but have no way of testing this assumption. I shall return to this point below.

Satellite telemetry The use of conventional radio tracking techniques, such as VHF telemetry, has greatly increased our ability to track the movements and behaviour of small cetaceans at sea. Limiting this methodology, however, is the need to stay in radio contact with tagged animals. During the last two decades, a new technique has revolutionized the ability of biologists to track the movements of animals in remote

187 areas. This technique, known as satellite telemetry, utilizes radio transmitters that send signals to receivers aboard the US National Oceanographic and Atmospheric Administration (NOAA) Tiros-N weather satellites. The receivers are operated by Service ARGOS, of Toulouse, France, which makes the system available to commercial and scientific users. The system has proven extremely effective in tracking large terrestrial mammals [12] and used with great success to telemeter information about the foraging ecology of pinnipeds [7,20]. The ARGOS system uses the Doppler shift to estimate the position of the transmitter or Platform Transmitting Terminal (PTI'). All PTI's transmit on a stable frequency of 401.650 mHz. The accuracy of the estimated position depends on the number and quality of transmissions received during a satellite pass. The transmission rate is limited both by the ARGOS system and by the surfacing behaviour of the animal. PTFs used with marine mammals typically employ a salt water switch to restrict transmissions to periods when an animal is at the surface and the signal can be received by the satellite. Each transmitter is identified by a unique code that is sent at the beginning of every message. In addition to the ID code, the transmitter can send up to 256 bits of data, which typically includes information from environmental sensors aboard the tag. The most frequent type of recorded data is information on depth and temperature, although velocity sensors are also employed on pinniped PTrs [20]. Until very recently, PTI's were too large for use with small cetaceans. In 1987, Mate [ 17] tagged a rehabilitated stranded pilot whale (Globicephala melaena) with a P T r and followed its movements and diving behaviour for 95 days. The whale made long dives at night, presumably to forage on the squid that is believed to comprise its primary prey. During the daylight hours, the pilot whale made shallow dives, perhaps resting or feeding on near-surface prey. Since this early success, advances in miniaturization have allowed PTrs to be used to study the movements and activities of bottlenose dolphins (Tursiops truncatus), narwhals (Monodon monoceros), belugas (Delphinapterus leucas), white-sided dolphins (Lagenorhynchus acutus), common dolphins (Delphinus sp.), and harbour porpoises (Table 2). The most successful programme has been the study of high Arctic belugas by Martin and colleagues [15,16]. Eighteen belugas were tagged with PTTs between 1988 and 1992, yielding a tremendous amount of information on movement patterns Table 2. Deployments of satellite-linked radio tags (PTTs) on small cetaceans

Species

N

Maximum duration (days)

Reference

Bottlenose dolphins Pilot whales Narwhals Belugas White-sided dolphins Bottlenose dolphins Common dolphins Harbour porpoises

14 1 3 18 1 1 2 3

35 95 19 75 6 25 ? 21

[25] [17] [14] [15] [19] [18] P. Thorson, personal communication A. Read, unpublished data

188 and diving behaviour. These belugas made dives of up to 18 min in duration and to depths of 440 m. As was the case with harbour porpoises, most of the long dives made by belugas were fiat-bottomed, with several minutes spent at a constant depth near the sea bed. These dives were interpreted as foraging excursions, supporting previous observations from stomach contents that belugas feed on benthic and demersal prey. The diving capabilities of these animals were unexpected, however, and the results demonstrate that belugas have access to much more of the Arctic sea floor than previously believed. Once again, this new technology has radically changed the way that we view the foraging ecology of these animals. The use of satellite telemetry has overcome the need to recover tags to obtain data, one of the main problems with the use of data loggers. But satellite tags have some of the same other limitations possessed by data loggers, particularly the need to capture animals to attach tags. And, as with data loggers, satellite telemetry provides only an indirect view of foraging behaviour. In addition, satellite-linked tags have their own limitations imposed by the ARGOS system. The maximum limit of 256 bits of data per transmission is a serious impediment to the collection of fine-scale environmental data from more than a single sensor. Even with data compression algorithms and duty cycling of different sensors, it is difficult or impossible to collect the kind of information that can be obtained with data loggers. The number of successful uplinks is also limited by the difficulty of coordinating transmissions with satellite passes; this is a particular problem in equatorial regions where the number of passes per day is very limited. The ARGOS system is currently limited to the two Tiros satellites which are both in polar orbits. Finally, the recent success of long-term tag attachments used with PTI's means that we are approaching the maximum transmission life of the current generation of batteries. It may be possible to address some of these limitations with new technological developments, as discussed below.

Future directions

Recent developments with both data loggers and satellite telemetry have produced impressive advances in our understanding of the foraging ecology of small cetaceans. Nevertheless, many important questions remain. For example, how important is echolocation in finding food? The prey of many dolphins and porpoises are known to produce sound, and it is likely that passive acoustics and vision are also important senses in the initial detection process. How do deep-diving animals find their prey several hundred metres below them near the sea floor? How important are cooperative feeding strategies in group-living species? These and many other questions will require more direct means of observing the behaviour of dolphins and porpoises. Below I list some avenues of technological research and development that could yield the answers to such questions. As with the development of data loggers and satellite telemetry, it is likely that many of these developments will first be tested on pinnipeds, before the constraints of deployment on small cetaceans are overcome. One area of future work that holds great promise is the development of new sen-

189 sors for use with data loggers and satellite-linked tags. Researchers are already experimenting with sensors that record stomach temperature [28] and heart rate [ 10]. It should soon be possible to determine when prey are ingested by monitoring reductions in stomach temperature and then link this information to diving patterns to test the hypothesis that long, fiat-bottomed dives are foraging excursions. Video may also make a dramatic impact on our ability to document foraging behaviour, at least for shallow water species [8]. Finally, loggers are now available that allow researchers to record the occurrence of echolocation clicks and thus relate acoustic behaviour to feeding events. Preliminary work has been conducted on several species in captivity [2,26] and it should soon be possible to adapt some of these techniques to the study of free-ranging animals. At present, it seems likely that the simultaneous use of several sensors will be best achieved with data loggers rather than PTTs. Data loggers are not as power-hungry as PTI's because they do not have to transmit data, thus the loggers can be considerably smaller than PTI's. The fact that loggers record rather than transmit data allows them to store information on a much finer scale. Such detailed records will be critical when we attempt to integrate information recorded simultaneously from several sensors (depth, stomach temperature and echolocation trains, for example). The possibility of obtaining such rich data records is tremendously exciting and will leave us struggling for analytical tools to cope with a wealth of information. The second type of technical developments that will further our study of foraging ecology lies in the development, attachment and recovery of the tags themselves. As noted above, for the most part we still need to capture animals to attach tags and, for many species, this is not possible. More work on non-invasive, remote attachments, like those of Baird and Goodyear [3,4], is required. We also need to incorporate active release mechanisms into the attachments used with data loggers, so that we can retrieve them when it is convenient to do so. Although this is a relatively straightforward task, at present we are limited by the need either to recapture a tagged animal or to wait for a passive mechanism to trigger before we can recover the data logger. Finally, we will need considerable advances in our ability to transmit large quantities of data rapidly to receiving stations, either aboard satellites or other platforms. Clearly, in all these cases a productive collaboration between engineers and biologists will be essential to progress. The last aspect of development in the study of foraging ecology of small cetaceans rests not in our ability to understand what dolphins and porpoises are doing, but in the fine-scale distribution and behaviour of their prey. As we increase our ability to monitor the activities of marine mammals, we rapidly outstrip the ecological information base required to interpret this behaviour. Those of us who have searched vainly through databases on commercial fisheries and stock assessments know too well that the scale of this information is much too coarse to be of value. Even when small cetaceans feed on commercially valuable prey species, we seldom have distributional data on a scale that is fine enough to interpret movement or diving patterns. In other cases, such as the pelagic dolphins that feed on mid-water squid and fishes of the deep scattering layer, even the taxonomy of prey species may be unresolved.

190 To test the hypotheses that we will formulate about the feeding strategies of these animals, it will be necessary to collect synoptic information about the distribution and movements of their prey. This may involve sophisticated means of detecting the presence of prey aggregations, such as the use of research sonar systems, and tracking the prey themselves to monitor movements and activity patterns.

Conclusions To those of us involved in studying the foraging ecology of small cetaceans, this is a tremendously exciting time to be conducting field research. Each data logger and satellite uplink holds the promise of new insight into the ecology and behaviour of these animals. As our toolbox of research techniques grows, we will be able to piece together the puzzle that describes how dolphins and porpoises make a living at sea. Our experience to date has demonstrated that with increased knowledge comes a myriad of unexpected questions and apparent paradoxes. Our present challenge is to develop new and benign tools to resolve these questions and better understand the role of small cetaceans in their ecosystems.

Acknowledgement I would like to thank my colleagues who work on harbour porpoises in the Bay of Fundy and on bottlenose dolphins in Sarasota, Florida for their dedication and friendship in the field. In particular, Andrew Westgate, Michael Scott, Randy Wells and Forrest Townsend have been instrumental in developing safe and effective tagging systems. Peter Tyack, Kurt Fristrup and Bill Watkins of the Woods Hole Oceanographic Institution have generously shared their insight and experiences. I also thank Tony Martin and Bruce Mate for their encouragement and advice. This paper was substantially improved by comments from Andrew Westgate. My research has been supported by the US National Marine Fisheries Service, US Office of Naval Research and World Wildlife Canada. Finally, thanks to Arne BjCrge for inviting me to Tromsr and to prepare this paper.

References 1. Abend A, Finn J, Smith TD. Diet prediction of the long-finned pilot whale (Globicephala melas) using carbon and nitrogen stable isotope tracers. Abstracts, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993; 19. 2. Akamatsu T, Hatakeyama Y, Kojima T, Soeda H. Echolocation rates of two harbor porpoises (Phocoena phocoena). Mar Mammal Sci 1994;10:401-411. 3. Baird RW. Foraging behaviour and ecology of transient killer whales (Orcinus orca). PhD Dissertation, Simon Fraser University, Vancouver, Canada, 1994. 4. Baird RW, Goodyear JD. An examination of killer whale diving behaviour using a recoverable,

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5.

6. 7. 8.

9. 10.

11. 12. 13. 14. 15. 16. 17. 18.

19.

20. 21. 22. 23. 24.

25. 26. 27. 28.

suction-cup attached TDR/VHF tag. Abstracts, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993;25. Bigg MA, Fawcett I. Two biases in diet determination of northern fur seals (Callorhinus ursus). In Beddington JR, Beverton RJH, Lavigne DM (eds) Marine Mammals and Fisheries. London: George Allen and Unwin, 1985;284--299. Costa DP. Methods for studying the energetics of freely diving animals. Can J Zool 1988;66:4552. Costa DP. The secret life of marine mammals. Oceanography 1993;6:t20-128. Davis RW, LeBoeuf BJ, Marshall G, Crocker D, Williams J. Observing the underwater behavior of elephant seals at sea by attaching a small video camera to their backs. Abstracts, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993;40. Evans WE. Orientation behavior of delphinids: radio telemetric studies. Ann NY Acad Sci 1971;188:142-160. Goodyear JD, Andrews R. The first whale ECG with a self-contained tag and radio and satellitelinked depth and heart-monitoring tags for whales. Abstracts, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993;54. Iverson S. Milk secretion in marine mammals in relation to foraging: can milk fatty acids predict diet? Symp Zool Soc London 1993;66:263-291. Keating KA, Brewster WG, Key CH. Satellite telemetry: performance of animal tracking systems. J Wildlife Manage 1991;55:160-171. Kooyman G. Diverse Divers: Physiology and Behaviour. Berlin: Springer-Verlag, 1989. Martin AR, Kingsley MCS, Ramsay MA. Diving behaviour of narwhals (Monodon monoceros) on their summer grounds. Can J Zool 1994;66:446--458. Martin AR, Smith TG. Deep diving in wild, free-ranging beluga whales, Delphinapterus leucas. Can J Fish Aquat Sci 1992;49:462-466. Martin AR, Smith TG, Cox OP. Studying the behaviour and movements of high Arctic belugas with satellite telemetry. Symp Zool Soc London 1993;66:195-210. Mate BR. Watching habits and habitats from Earth satellites. Oceanus 1989;32:14-18. Mate BR, Rossbach KA, Nieukirk SL, Wells RS, Irvine AB, Scott MD, Read AJ. Satellitemonitored movements and dive-behavior of a bottlenose dolphin (Tursiops truncatus) in Tampa Bay, Florida. Mar Mammal Sci (in press). Mate BR, Stafford KM, Nawojchik R, Dunn JL. Movements and dive behavior of a satellitemonitored Atlantic white-sided dolphin (Lagenorhynchus acutus) in the Gulf of Maine. Mar Mammal Sci 1994;10:116-121. McConnell B J, Chambers C, Fedak MA. Foraging ecology of southern elephant seals in relation to the bathymetry and productivity of the Southern Ocean. Antarctic Sci 1992;4:393-398. Pierce GJ, Boyle PR. A review of methods for diet analysis in piscivirous marine mammals. Oceanogr Mar Biol Annu Rev 1991;29:409-486. Pierce GJ, Boyle PR, Watt J, Grisley M. Recent advances in diet analysis of marine mammals. Symp Zool Soc London 1993;66:241-261. Recchia CA, Read AJ. Stomach contents of the harbour porpoise, Phocoena phocoena (L.), from the Bay of Fundy, Canada. Can J Zool 1989;67:2140-2146. Scott MD, Chivers SJ, Olson RJ, Lindsay RJ. Radiotracking of spotted dolphins associated with tuna in the Eastern Tropical Pacific. Abstracts, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993;97. Tanaka S. Satellite radio tracking of bottlenose dolphins Tursiops truncatus. Bull Jap Soc Sci Fish 1987 ;53:1327-1338. Tyack P. A data logger to identify vocalizing dolphins. J Acoust Soc Arm 1991;90:1668-1671. Westgate AJ, Read AJ, Berggren P, Koopman HN, Gaskin DE. Diving behaviour of harbour porpoises, Phocoena phocoena. Can J Fish Aquat Sci (in press). Wilson RP, Cooper J, Plotz J. Can we determine when marine endotherms feed? A case study with seabirds. J Exp Biol 1992;167:267-275.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand ~. Ulltang,editors

193

Distribution and diving behaviour of hooded seals L.P. Folkow and A.S. Blix Department of Arctic Biology and Institute of Medical Biology, University of Tromsr Tromsr Norway Abstract. Hooded seals, Cystophora cristata, are abundant in the North Atlantic. This paper reviews current knowledge on the distribution and dive behaviour of these seals. The stock which breeds in sea ice near Jan Mayen may count about 250,000 animals, but little is known about where they stay and what they eat outside the pupping season (March/April) and the moult (July). We used satellite tags to monitor movements and/or dive depths and durations of 19 seals, and we obtained data on -12,000 locations and -120,000 dives, between July 1992 and July 1993. After the moult, most of the seals dispersed to travel, once or repeatedly, between the ice off Greenland and the distant waters off the Faeroe Islands, south of Bear Island, or the Irminger Sea. After breeding, all seals again returned to sea to travel to the waters off northern Ireland, the Faeroes or the Norwegian coast. Hooded seals may dive repeatedly to >1,000 m and stay submerged for >52 min, but usually dive to 100-600 m depth. We suggest that the dietary preferences, and even the fish consumption of hooded seals in different areas may be assessed by comparing their dive depths with the distribution of potential prey. Key words: arctic, feeding ecology, fisheries resources, North Atlantic

Introduction

Hooded seals (Cystophora cristata) are abundant in the ice-filled waters of the North Atlantic. Average lengths and weights of adult males and females are about 2.5 and 2.0 m, and 300 and 160 kg, respectively [1 ]. Previous studies of hooded seals have almost exclusively been conducted in connection with breeding, which takes place in the second half of March/early April, and moulting, which occurs between late June and early August. During these events, hooded seals aggregate in the drift ice and are accessible in large numbers for both studies and harvesting. During the remainder of the year, however, the seals disperse and are seldom found in large concentrations. For this reason, studies of the distribution and feeding ecology of the species during these periods have been difficult to carry out. However, modem satellite tracking techniques have recently made it possible to remotely monitor movements of radiotagged seals, via satellite. Moreover, such satellite tags, which are attached to the seal by gluing it to the fur, may also include different types of sensors allowing collection and subsequent transmission of data on for example dive depth and duration, heart rate, etc. This review of the distribution and dive behaviour of hooded seals integrates previous knowledge based on traditional techniques (field studies on breeding and moulting animals, incidental observations, and interviews with sealers and hunters) with recent data obtained by use of satellite telemetry and tracking techniques.

Address for correspondence: L.P. Folkow, Department of Arctic Biology, University of Tromsr N9037 Tromsr Norway.

194 Distribution and Migration Hooded seals aggregate to give birth and mate in relatively heavy pack ice near Jan Mayen (the West Ice), off Newfoundland (the Front) and in the Gulf of St. Lawrence (the Gulf) (Fig. 1). In addition, whelping also takes place in some areas in the Davis Strait [2]. The sizes of the different breeding stocks are not known, but based on current estimates of pup production rates it appears that the Northwest Atlantic stocks count about 400,000 animals [3], while the West Ice stock may count in the order of 250,000 animals. The segregation into different breeding areas has caused speculation as to whether different breeding stocks represent separate populations.

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195 Based on migration patterns, Rasmussen [4] concluded that there is only one stock of hooded seals in the North Atlantic, and this conclusion is supported by Wiig and Lie [5], who in comparing morphometric data from hooded seal skulls from the different breeding stocks, found no significant differences. Still, the two main breeding stocks appear to inhabit different geographical areas during most of the year. From an ecological and managemental point of view, the two stocks should therefore still be looked upon as separate, despite the fact that there is some exchange of genetic material between them. After breeding, hooded seals have been reported to start migrating towards their moulting areas. The main moulting area is located in the Denmark Strait, where animals from both the Northwest Atlantic and the West Ice stocks have been presumed to moult [4,6,7] (Fig. 1). That migration of hooded seals from Newfoundland to the Denmark Strait takes place has been confirmed by mark-recapture data [2,8], as well as in recent satellite tracking studies [9]. All stocks of hooded seals were for long considered to moult in the Denmark Strait. However, Nansen [6] described another lair which was located further north, between 72 and 76~ Folkow, Mhrtensson and Blix (submitted to Polar Biology) observed a lair somewhat further southeast to this (northwest of Jan Mayen), but concluded that this probably corresponded to that described by Nansen [6], and suggested that a large fraction of the West Ice stock is moulting there. Previous reviews of hooded seal migration patterns seem to imply that the seals start their migration towards the moulting lairs as soon as breeding is completed, and that they all travel in one general direction while feeding on their way [4]. However, data obtained by Folkow, Mhrtensson and Blix (submitted to Polar Biology) from eight satellite tagged hooded seals in the period between breeding and moult show that West Ice hooded seals leave the drift ice and distribute widely soon after breeding, to perform long excursions to distant waters (e.g. off the Faeroe Islands, off northern Ireland and in the Norwegian Sea) (Fig. 1), before heading towards the moulting lair northwest of Jan Mayen in the summer. Also in the Northwest Atlantic, satellite tracking studies show that excursions at high sea take place before the moult migration starts [9]. Data on the distribution of hooded seals after the moult off the east coast of Greenland are few, primarily because such studies have remained impossible until the development of satellite tracking techniques. The general opinion has been that the seals then distribute widely, the seals from the Northwest Atlantic either returning to waters off Newfoundland, or following the Greenland coast around Kap Farvel, and north as far as to the Thule district [10], while West Ice hooded seals have been assumed to mainly range north, in the ice between Greenland, Svalbard and Bear Island [4]. However, some seals have been documented to migrate over long distances to other areas, and records exist of observations or catches of hooded seals, from Alaska in the west [11], to the Barents Sea in the east [7], along the coast of Norway [7,12], south of Iceland and off the Faeroe Islands [13]. In fact, stranded specimens have been found on remote locations as far south as the Portuguese coast in the east [14] and the coast of Florida in the west [15], and a stranded female

196 hooded seal has even been found in the Pacific, as far south as the Califomian coast [ 16]. Such seals have usually been considered as "stragglers" and "strays". However, recent satellite tracking data have shown that long travels in the central and eastern North Atlantic are roles rather than exceptions for these mammals. Folkow, MArtensson and Blix (submitted to Polar Biology) have collected data from 15 subadult and adult hooded seals of both sexes which were equipped with satellite transmitters after the moult in lairs at about 71~ 12~ and which were tracked for about 200 days, on average. They found that all but one of the tagged seals on one or several occasions made an excursion which lasted for about 3-7 weeks to distant areas, and then returned to the drift ice edge, somewhere between 65 and 77~ along the east coast of Greenland. The most frequently visited area off the ice edge were the waters off the Faeroe Islands, where altogether eight of the seals stayed at some time during the tracking period. Other areas of importance were the Irminger Sea (southwest of Iceland), the continental shelf break between the Norwegian mainland and Bear Island, and areas in the Norwegian sea and north/northeast of Iceland (Fig. 1). One individual, which was a male, travelled to waters off the west and north coast of Svalbard (up to 81 ~ and remained there throughout the remainder of the tracking period. Apart from this, the study by Folkow, MArtensson and Blix (submitted to Polar Biology) did not reveal any differences in distribution pattems of males and females. Long excursions at high sea were conducted at all times of the year, but the seals always returned to the ice edge and were never recorded to haul out on any coast. In this sense, the hooded seal appears to be a truly pelagic species. At the time of breeding (second half of March), 7 of the 15 tags which were deployed in July were still active. Judging by the size of the animals, which was compared with length-age data presented by Rasmussen [4], one female may have been sexually mature, and this animal retumed to the breeding area southwest of Jan Mayen and spent 6 days hauled-out on the ice before returning to sea. Given the short nursing period of hooded seals [ 17], this animal may well have given birth and nursed a pup in this period.

Diving behaviour It is easier to summarize previous data on the dive behaviour of hooded seals than on their distribution. In 1890, Nansen [6] stated that hooded seals are deep divers, and Oynes [12] reported that hooded seals occasionally were caught in nets off the coast of Norway at depths of several hundred meters. The first actual recording of dive depths of hooded seals was made by Scholander [18] who found that captive young seals could dive down to about 75 m. Data on dive depths of free-swimming hooded seals did not exist until such information could be collected by satellite telemetry. The first confirmation of Nansen's [6] assumption was made by Folkow and Blix [19], who found that their satellite-tagged hooded seals could dive to depths beyond the depth range of the pressure sensor employed, which was 0-1,000 m. Dives as

197

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deep as this were usually not performed on a daily basis, but could account for more than 40% of all dives in some areas (Fig. 2), at some times of the year (Folkow and Blix, submitted to Polar Biology). Data showed that hooded seals regularly dive to depths between 300 and 600 m (Fig. 3), but that the dive depth pattern may vary significantly from area to area, and between seasons. Thus, diving in ice-covered waters east of Greenland (north of 70~ and north/northeast of Iceland, was characterized by high proportions of dives to depths of less than 300 m, while diving in the Denmark Strait (off the east coast of Greenland, south of 70~ included high fractions of dives to more than 300 m depth. In the waters off the Faeroe Islands, dive depths showed seasonal changes, with depths of 100-300 m dominating in

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duration (rain) Fig. 3. Overall dive depths and durations of 16 hooded seals, between July 1992 and July 1993 (from

manuscript by L.P. Folkow and A.S. Blix, submitted to Polar Biology). autumn (August-November), while there was a shift towards deeper dives (300600 m) in winter and spring (December-May). Areas in which particularly deep dives were performed were the waters off Jan Mayen (Fig. 2), and in the Irminger Sea, but even in these areas dives to between 300 and 600 m usually constituted the largest fractions. Comparison of dive depths with water depths in different areas showed that most dives must have been pelagic. Folkow and Blix (submitted to Polar Biology) also found that dive durations generally were well correlated with dive depths and a few dives of more than 52 min duration were recorded in areas where deep dives (>1,000 m) were performed. The average dive duration of hooded seals appears to be between 5 and 15 min (Fig. 3), and Folkow and Blix (submitted to Polar Biology) estimated the aerobic dive limit of

199 hooded seals to be about 15-17 min, which implies that as much as 36% of all dives by hooded seals are in part anaerobic. Dive depth data have also been collected, by use of the same technique, from Northwest Atlantic hooded seals during the period between breeding and moult. These studies showed that the depths of dives were less in this area (<530 m in the Laurentian Channel) [9] which is not surprising since water depth is also less here. The study by Stenson and co-workers [9] also revealed that hooded seals stay submerged for more than 80% of the time, while at sea. The diving rates recorded by Folkow and Blix (submitted to Polar Biology) from West Ice hooded seals were low to intermediate in ice-covered areas, where the seals presumably hauled out at intervals, while the rate at high sea appeared to be inversely proportional to dive depths, with highs of 125-142 dives per day in areas characterized by shallow diving, and lows of 56 dives per day in deep diving areas. The latter dive rate compares well with those recorded in southern elephant seals (Mirounga leonina) [20] and northern elephant seals (Mirounga angustirostris) [21 ], which are both known as record deep divers.

Prey selection and food consumption Data on the food selection of hooded seals are few, primarily because they fast during both breeding and moult [4], which is when they have been available for studies. Hooded seals with stomach contents have nevertheless been collected, although only in small numbers and from a few selected areas and times of the year. Nansen [6] reported that hooded seals feed on redfish (Sebastes sp.), gadoids, halibut and squid (presumably Gonatus fabricii, as reported by Sergeant [22]). Wolleba~k [23] suggested that they may also take Atlantic salmon (Salmo salar), when available. Greenland halibut (Reinhardtius hippoglossoides), herring (Clupea harengus), capelin (Mallotus villosus), redfish and various gadoids (including Atlantic cod (Gadus morhua) and Arctic cod (Boreogadus saida)) were found in stomachs of hooded seals collected in waters northwest, south and southeast of Greenland [24], as well as in Newfoundland waters [25], with substantial variation in frequency of occurrence between areas. Obviously, these records are not sufficiently detailed to allow a general assessment of the dietary preferences of these mammals at different times of the year and in different areas. Dive depth pattems reflect the depths at which hooded seals forage, and this information can presumably therefore be used, together with fisheries resource survey data, to predict which prey items these animals are primarily eating in different areas. The approach can be illustrated by the following two examples, taken from Folkow and Blix (submitted to Polar Biology): 1. Satellite-tagged hooded seals frequently visited waters off the Faeroe Islands, where, in fact, 14.5% or 550, of the total of almost 3800 seal days which were recorded during the tracking period, were spent. In this area, dive depths of 100-300 m dominated in early autumn, while there was a shift towards deeper

200 (300-600 m) dives in late autumn and winter. The spatial and temporal distribution of the seals correlates very well with the known distribution of the blue whiting (Micromesistius poutassou) which is found in large numbers in these waters (Hjalti J~ikupsstovu, Fisheries Laboratory of the Faeroes (personal communication)). Furthermore, the blue whiting spawns in April and May in waters west of the British Isles, at depths of 300-600 m (JLkupsstovu, personal communication). We found that satellite-tagged hooded seals were also present in this area (off northern Ireland) for 57 seal days (or 1.5% of all seal days) at exactly that time of the year (April and May), and that they mainly were diving to depths of 300-600 m. These data strongly suggest that blue whiting was the main prey of hooded seals in both areas. 2. About 3.8% of all seal days were spent in the Irminger Sea, where dives deeper than 300 m accounted for 30-60% of all dives. In this area, hooded seals were most likely feeding mainly on redfish, which are distributed pelagically at depths of 100-500 m and sometimes down to 900 m [26]. In the following, we have attempted to illustrate how the consumption of fish by hooded seals in different areas may be calculated from this type of data. Such calculations require that we also know the size of the relevant seal stock and that we assume that the behaviour of satellite-tagged seals is representative for this stock. Also, we need to know the energy requirements of hooded seals, as well as the energy density of the relevant prey species. The population size of the West Ice stock of hooded seals is unknown, but may count about 250,000 animals, which spend 250,000 x 365 = 91,250,000 seal days in different areas, on an annual basis. Data on energy expenditure of hooded seals are few. However, Elias [27] reports that adult hooded seals maintain basal metabolic rates that are similar to those predicted by Kleiber [28] for mammals of similar size (i.e. 3.4 W kg-~ It is therefore reasonable to assume that free-swimming hooded seals maintain an average field metabolic rate of about 2.3 x B MR [29], which, for an average-sized hooded seal of about 170 kg would correspond to 31,900 kJ per day. Hooded seals which spend 14.5 + 1.5% = 16% of 91,250,000 (i.e. 14,600,000) seal days off the Faeroes and off Ireland would, thus, need to cover energy expenses totalling 31,900,000 x 14,600,000 = 4.65 x 1014 J by feeding on the blue whiting. The energy density of the blue whiting is unknown, but can be assumed to be similar to that of Atlantic cod, being 4.74 kJ/g, on average (M~trtensson, NordCy, Lager and B lix, unpublished), but only about 93% of the energy content of a fish meal is available as metabolizable energy to the seal, due to energy loss as faecal material [30]. Based on these considerations, hooded seals would be expected to consume 105,000 tonnes of blue whiting in these waters. This figure can be compared with the total fishery of blue whiting in the same (spawning) area of about 346,000 tonnes in 1993 (J~ikupsstovu, personal communication). When using the same approach for redfish (having an average energy density of 6.65 kJ/g, as determined in Sebastes marinus specimens (M~rtensson, NordCy, Lager and Blix, unpublished)), a consumption of almost 18,000 tonnes during a total of 3,467,500 seal days in the Irminger Sea is indicated.

201 The satellite-tagged seals spent most (38%) of their time near the sea ice edge (off Greenland). We have not yet completed the analyses of seal dive depth data in relation to data on available prey items in these areas, but it seem highly likely that hooded seals consume large amounts of capelin and polar cod there. Obviously, the approach described above yields fairly rough estimates of the consumption of fish by hooded seals. However, at present there is no alternative to this approach, since the dispersed offshore distribution of this species makes any systematic analysis of food selection based on collected stomach contents virtually impossible. These calculations set the potential impact of this largely overseen pinniped species into perspective, and illustrate the importance of obtaining better data to predict its effect on fisheries resources in the North Atlantic.

Acknowledgements The authors wish to thank cand. real. Hjalti J~ikupsstovu, Fisheries Laboratory of the Faeroes, for supplying data on the biology of the blue whiting, cand. scient. Per-Erik MArtensson and cand. scient. Anne R. Lager for assistance in the field, and the crews of M/V "Polarfangst" and KNM "Senja" for their helpful cooperation. This study was financed by the Norwegian Research Council, grant nos. 408.006 and 104503/ 110.

References 1. Lavigne DM, Kovacs KM. Harps and hoods: ice-breeding seals of the Northwest Atlantic. Waterloo, Canada: University of Waterloo Press, 1988. 2. Sergeant DE. A rediscovered whelping population of hooded seals Cystophora cristata Erxleben and its possible relationship to other populations. Polarforschung 1974;44:1-7. 3. Anonymous. Report of the joint ICES/NAFO working group on harp and hooded seals. International Council for the Exploration of the Sea, Copenhagen, September, 1993. C.M. 1994/Assess: 5. 4. Rasmussen B. Om klappmyssbestanden i det nordlige Atlanterhav. Fisken Havet 1960; 1:1-23. 5. Wiig ~, Lie RW. An analysis of the morphological relationships between the hooded seals (Cystophora cristata) of Newfoundland, the Denmark Strait, and Jan Mayen. J Zool London 1984;203:227-240. 6. Nansen F. Paa ski over Gr6nland. Kristiania, Oslo: Aschehoug and Co, 1890. 7. Oritsland T. Klappmyss. Fauna Oslo 1959;12:70-90. 8. Hammill MO. Seasonal movements of hooded seals tagged in the Gulf of St. Lawrence, Canada. Polar Biol 1993;13:307-310. 9. Stenson GB, Hammill MO, Fedak MA, McConnell BJ. The diving behaviour and seasonal migration of adult hooded seals. Abstract, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993; 103. 10. Kapel FO. Recent research on seals and seal hunting in Greenland. Rapp P-V R6un Cons Int Explor Mer 1975;169:462-478. 11. Burns JJ, Gavin A. Recent records of hooded seals, Cystophora cristata Erxleben, from the western Beaufort Sea. Arctic 1980;33:326-329. 12. Oynes P. Sel p~ norskekysten fra Finnmark til Mere. Fisk Gang 1964;48:694-707.

202 13. Mohr E. Die Klappmtitze. Kosmos Stuttgart 1955;51:546-551. 14. Reiner F. Nota sobre a segunda ocorrencia de una foca de mitra, Cystophora cristata (Erxleben, 1777) nas costas de Portugal. Mus Mar Cascais Mem Ser Zool 1980;1(6). 15. Miller GS. A hooded seal in Florida. Proc Biol Soc Washington 1917;30:121. 16. Dudley M. First Pacific record of a hooded seal, Cystophora cristata Erxleben, 1777. Mar Mammal Sci 1992;8:164-168. 17. Bowen WD, Oftedal OT, Boness DJ. Birth to weaning in 4 days: remarkable growth in the hooded seal, Cystophora cristata. Can J Zool 1985 ;63:2841-2846. 18. Scholander PF. Experimental investigations on the respiratory function in diving mammals and birds. Hvalrhdets Skr 1940;22:1-131. 19. Folkow LP, Blix AS. Satellite tracking of hooded seals (Cystophora cristata) in the Greenland and Norwegian Seas. Abstract, Tenth Biennial Conference on the Biology of Marine Mammals, Galveston, TX, 1993;48. 20. Hindell MA, Slip DJ, Burton HR. The diving behaviour of adult male and female southern elephant seals, Mirounga leonina (Pinnipedia: Phocidae). Aust J Zool 1991 ;39:595-619. 21. LeBoeuf BJ, Naito Y, Huntley AC, Asaga T. Prolonged, continuous, deep diving by northern elephant seals. Can J Zool 1989;67:2514-2519. 22. Sergeant DE. History and present status of populations of harp and hooded seals. Biol Conserv 1976; 10:95-118. 23. Wolleb~ek A. Uber die Biologie der Seehunde und die Seehundjagd im europ~iischen Eismeer haupts~ichlich nach norwegischen Quellen. Rapp Cons Explor Mer 1907;8:5-82. 24. Kapel FO. Studies on the hooded seal, Cystophora cristata, in Greenland, 1970-1980. NAFO Sci Coun Studies 1982;3:67-75. 25. Ross S-A. Food and feeding of the hooded seal (Cystophora cristata) in Newfoundland. M Sc Thesis, Memorial University of Newfoundland, St. John's, Newfoundland, 1993. 26. Muus B. Fisk (Pisces). In: Salomonsen F (ed) GrCnlands fauna. Copenhagen: Gyldendalske Boghandel, 1981 ;23-158. 27. Elias M. Swimming energetics of hooded seals (Cystophora cristata). MSc Thesis, University of Guelph, Guelph, Ontario, 1985. 28. Kleiber M. The Fire of Life. New York: Krieger, 1975. 29. Stewart REA, Lavigne DM. Energy and female condition in nursing harp seals Phoca groenlandica. Holarctic Ecol 1984;7:182-194. 30. MLrtensson P-E, Nordr ES, Blix AS. Digestibility of crustaceans and capelin in harp seals (Phoca groenlandica). Mar Mammal Sci 1994;10:325-331.

9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang, editors

Distribution and a b u n d a n c e of walruses Svalbard

203

(Odobenus rosmarus) in

Ian Gjertz ~ and Oystein Wiig 2 1Norwegian Polar Institute, Majorstuen, Oslo, Norway; and 2Zoological Museum, Sarsgt. 1, Oslo, Norway Abstract. Information on the distribution and abundance of walruses in Svalbard is reviewed. Former

and present haul-out sites were mapped based on skeletal remains, drag marks and/or hauled out animals. Walruses in Svalbard are sexually segregated. Males are found in the more accessible areas in the north and south-east while females are found in the north-east and possibly in Franz Josef Land. The males seem to be site tenacious, but occasionally undertake trips to neighbouring areas within both Svalbard and Franz Josef Land. A conservative estimate of the number of walruses in Svalbard, which also includes parts of Franz Josef Land, exceeds 2,000 animals. Key words: marine mammals, arctic, haul-out sites, migration, sexual segregation

Introduction Walruses (Odobenus rosmarus) were once very common in Svalbard [ 1]. Their preharvest number has never been established, but the size of the original population must have been very large. Walrus hunting in Svalbard started in 1604, and by the late 19th century the stock showed clear signs of decrease [1]. Hunting continued until 1952, when walruses were given total protection in Norwegian waters [2]. They were then believed to be on the verge of extinction [3]. Born [4] concluded, based on opportunistic observations and surveys, that walruses in Svalbard consisted of a summering stock of about 100 animals in the beginning of the 1980s. Walruses are site-tenacious and annually return to the same haul-out sites on land. This was a major cause of their decline. LCnr [1] summarised historical catches of walruses in Svalbard and the adjacent European Arctic waters, and indicated the areas in Svalbard which were considered best for hunting. Other authors have indicated where walrus observations have been most numerous in the latter part of this century [3-5]. This information either indicates the distribution in the present early stages of a recovering stock or possibly reflects the distribution of observational effort. Tsalkin [6] suggested, based on catch statistics, that walruses in Franz Josef Land and Novaya Zemlya were part of a larger general stock inhabiting the European Arctic (Fig. 1). Born [5] supported this view and suggested that walruses summering in Svalbard belonged to a population with its main distribution in Franz Josef Land. In 1989 we started a research project in order to document the present status of wal-

Address for correspondence: I. Gjertz, Norwegian Polar Institute, P.O.B. 5072 Majorstuen, N-0301 Oslo, Norway.

204 -1-1

90

~_

"

t

~hrans

Josef ~

"-"r~f" - "7

"0

GREENLAND~

Fig. 1. Map of the European Arctic [ 10].

ruses at Svalbard. This paper is a review of the major results obtained during that project.

Distribution Based on historical material and observations obtained in recent years, it has been possible to map the most important distribution areas of walruses in Svalbard. The presence of former haul-out sites, as well as haul-out sites now in use were mapped based on skeletal remains, drag marks and/or hauled-out animals. Three main areas were evident, in the north, north-east and south-east [7] (Fig. 2). From the beginning of the walrus harvest in Svalbard we know that walruses were very abundant at the southernmost island, BjCmCya, and along the west coast of Spitsbergen. Walruses have started to recolonize the latter areas, but they have not yet returned to BjCmCya [7]. Several ground surveys were conducted in south-east Svalbard each year from 1989 to 1993 [7]. All the animals observed, with the exception of a few single cows with calves, were males of varying ages. The surveys have also shown that at least some of the walruses are site tenacious. This could indicate that a large part of the walruses either return to the same sites each year or stay there all year. Few observations of large numbers of females and calves are known from Svalbard. Observations from after 1982 indicate that the only area where they are found in significant numbers is in the extreme north-eastem part of the archipelago [7]. The herds of walruses observed in other areas in summer are almost exclusively males, both adults and immatures [5,7].

205

Svalbard "

.

O

O

O

0 ,

i

1

60 9

i

i

120 km #

Fig. 2. Map of Svalbard, excluding BjCrnCya, indicating locations of known walrus haul-out sites [7].

We know that from the turn of the last century sealing vessels caught large numbers of walruses in Franz Josef Land [8]. These were predominantly females and calves. In 1990, 1991 and 1992 the Norwegian Polar Institute undertook field trips to Franz Josef Land and found a large number of females and calves in the southcentral parts of this archipelago [8,9]. Compared with knowledge on walruses in Svalbard [7], this information suggests that there may be a close connection between the animals of these two neighbouring archipelagos, and that the majority of walruses in Svalbard in summer are males from one common Svalbard-Franz Josef Land stock, as suggested by Born [5]. If walruses in Svalbard and Franz Josef Land are from one common stock then they will necessarily have to undertake annual migrations to meet and mate. Some mention of such migration is found in the literature, but it is not well documented. LCnr [1] dismissed the idea of an annual migration, and showed that even though walruses were exterminated in one area in Svalbard they could still be caught in other areas. He therefore suggested that the walrus population in Svalbard consisted of partially stationary groups which, because of close distances had some contact

206 with each other. Born [5] discussed the possibility of walruses wintering in polynias along the north-east coasts of Svalbard. He suggested that since walruses are usually first observed at northern Spitsbergen late in July, they must come from wintering grounds far away, for example from Franz Josef Land.

Telemetry A total of 34 satellite transmitters (PTI's) were deployed on walruses over a 4-year period (Wiig and Gjertz, unpublished data). All were tagged in the period from midJuly to early September and the PTTs lasted at best to mid-winter. Of these, 28 were deployed on males in Svalbard, the rest were deployed in Franz Josef Land on five males and one female. The results of the satellite trackings show that there is a migration of male walruses between Svalbard and Franz Josef Land [8] (Fig. 3). In particular it seems that an autumn migration of walruses from south-east Svalbard to north-east Svalbard, Victoria Island and Franz Josef Land is common [ 10]. Similarly one of the males from Franz Josef Land moved to Victoria Island [8] (Fig. 4). Four walruses in Svalbard were tracked from late summer to January/February and were seen to stay in that area for the winter. The one walrus that was tracked in Franz Josef Land until mid-winter similarly stayed in that area (Wiig and Gjertz, unpublished data). The telemetry results do not indicate a seasonal migration, following the edge of the drift ice, southwards in the autumn and northwards in spring. They are, however,

/

/

/

i

\

\

\

~'\J

\ .

/ /

/

!

"\

\

/

/

Fig. 3. Walrus tracked from south-east Svalbard to Franz Josef Land and back to northern Svalbard [10].

207

Fig. 4. Two separate walrus trackings. One from western Spitsbergen to Hinlopenstretet, the other from eastern Franz Josef Land to Victoria Island [ 10].

partly in accordance with LCnr [1] view that walruses tend to stay in particular areas, but may undertake long migrations to other areas and then return. The telemetry results for the walruses at south-east Svalbard indicate that the migrations are regular or at least common. We assume that these migrations are connected with breeding activity. Based on the results of the satellite telemetry, it is evident that walruses winter in the Svalbard area, both in the southern parts of Svalbard as well as in the winter pack ice. This is possible because there are numerous open leads within the Barents Sea ice during winter. The only walrus at Franz Josef Land that was followed until midwinter stayed in that area and therefore supports Born's [5] view that walruses also winter there. Born and Knutsen [11], using satellite telemetry in Northeast Greenland, have shown that bull walruses from this area disperse far out to sea, but they found no indication of a connection between the walruses in Greenland and Svalbard. Such a connection was, however, proven in July 1992 [12]. This indicates a connection between the walruses in these two geographical areas, and that the walruses from eastern Greenland to eastern Franz Josef Land may belong to one common stock.

Aerial surveys

In September 1992 surveys using fixed wing aircraft covered most of Svalbard's coastline. Attempts were made to cover areas considered of special interest at least

208 twice. In September-October 1993 similar surveys were conducted at the sites shown to be most important in 1992. In 1992 numbers of walruses observed varied from 0 to 288 on a single day while in 1993 they varied from 0 to 245 animals (Gjertz and Wiig, unpublished data). Cows and calves were only observed in the ice in north-eastern-most Svalbard, however, not in large numbers, in accordance with Gjertz and Wiig [7]. When considering the abundance of walrus in Svalbard, it is important to bear in mind that the animals observed seem to be predominantly males. If we assume that the different herds all behave like the ones in the Southeast, i.e. that they are site tenacious, then at least 750 male walruses are found in Svalbard, excluding the northeastern-most areas (Gjertz and Wiig, unpublished data). These latter areas have been the most important area for walruses in Svalbard in this century [7]. We must therefore assume that a considerable number of walruses are found here. If we assume that the sex ratio among walruses in Svalbard is similar to that in other areas, i.e. 1"1 [13] then the population of walruses belonging to the Svalbard area must, in a conservative estimate, be at least 1500 animals plus calves, i.e. exceed 2000 animals.

Acknowledgement This study was supported by the Norwegian Polar Institute, The Governor of Svalbard and the Norwegian Fisheries Research Council grant 4001-735.004.

References 1. LCnO O. The catch of walrus (Odobenus rosmarus) in the areas of Svalbard, Novaja Zemlja, and Franz Josef Land. Nor Polarinst Arbok 1972; 1970:199-212. 2. Anonymous. Fredning av hvalross. Konglig Resolusjon (Royal Decree) 20, Juni 1952. 3. Norderhaug M. Hvalrossens (Odobenus rosmarus) forekomst i Svalbardomr~det 1960-1967. Nor Polarinst Arbok 1969; 1967:146-150. 4. Oritsland T. Walrus in the Svalbard area. IUCN Publ New Ser Suppl 1973;39:59--68. 5. Born EW. Status of the Atlantic walrus Odobenus rosmarus rosmarus in the Svalbard area. Polar Res 1984;2:27-45. 6. Tsalkin, V. Materials on the biology of the walrus of Franz Josef Archipelago. Byull Mosk Ova Ispyt Prir 1937;46:43-51 (in Russian). 7. Gjertz I, Wiig 0. Past and present distribution of walruses in Svalbard. Arctic 1994;47:34--42. 8. Gjertz I, Hansson R, Wiig 0. The historical distribution and catch of walrus in Franz Josef Land. Nor Polarinst Medd 1992;120:67-81. 9. Knutsen LO. Walrus studies in the Franz Josef Land archipelago during August 1992. Nor Polarinst Medd 1993;126:1-16. 10. Gjertz I, Wiig 0. Status of walrus research in Svalbard and Franz Josef Land in 1992. A review. In: Stewart REA, Richard PR, Stewart BE (eds) Report of the 2nd Walrus International Technical and Scientific (WITS) Workshop, Winnipeg, Manitoba, Canada. Can Tech Rep Fish Aquat Sci 1993; 1940:68-84. 11. Born EW, Knutsen LO. Satellite-linked radio tracking of Atlantic walruses (Odobenus rosmarus rosmarus) in northeastern Greenland, 1989-1991. Z S~iugetierkd 1993;57:275-287.

209 12. Born EW, Gjertz I. A link between walruses (Odobenus rosmarus) in northeast Greenland and Svalbard. Polar Rec 1993;29:329. 13. Fay FH. Walrus Odobenus rosmarus (Linnaeus, 1758). In: Ridgeway SH, Harrison RJ (eds) Handbook of Marine Mammals, Vol 1, The Walrus, Sea Lions, Fur Seals and Sea Otter. London: Academic Press, 1981; 1-23.

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9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

211

Habitat use and diving behaviour of harbour seals in a coastal archipelago in Norway Arne BjCrge ~, Dave T h o m p s o n 2, Philip H a m m o n d 2, Michael F e d a k 2, E d m u n d Bryant 2, Hilde Aarefjord 1, Randi Roen 1 and Marianne Olsen ~ 1Norwegian Institute for Nature Research, Blindern, Oslo, Norway; and 2Sea Mammal Research Unit, Cambridge, UK A b s t r a c t . Background: the harbour seal is coastal and non-migratory and suitable for behavioural

studies using short-range telemetry and tracking. Methods: a combination of VHF radio telemetry and underwater ultrasonic telemetry was used to obtain behavioural and physiological data from 13 harbour seals tagged at an archipelago in Norway. VHF signals were used to locate seals, and they were tracked at close proximity by inflatable boats. Results: transit and foraging activity were identified based on differences in dive profiles. When foraging, all tagged seals operated solitarily, and they returned repeatedly to the same or approximately the same foraging sites. The radio tagged seals used different types of foraging habitats, ranging from shallow kelp areas located 20 km offshore to 150-200 m deep basins with muddy sea bed located a few kilometres from the respective haul-out sites. The seals were typically foraging at or close to the sea bed. Display behaviour including underwater vocalization was recorded for sexually mature males in June and July. Conclusion: the combination of VHF and ultrasonic telemetry is useful for studies of resident seals. Tracking free ranging seals at close proximity made it possible to identify and describe their resting, foraging and display areas. Key words: Phoca vitulina, telemetry, display behavior, foraging ecology

Introduction The harbour seal (Phoca vitulina) has typically been regarded as non-migratory and littoral in distribution [1], and exhibiting a diurnal haul-out pattern [2,3]. Recent studies however, e.g. by Thompson and co-workers [4-6], have revealed seasonal and year to year movements between a few haul-out sites and between foraging locations. Thompson [7] nevertheless concluded that harbour seals are resident in the same geographical area throughout the year. The diurnal haul-out patterns and the limited travelling speed deployed indicate that harbour seals forage within a few kilometres of their haul-out sites. This is supported by studies of foraging movements of radio tagged seals where most foraging activity was less than 50 km from haul-out sites [5-8]. A typical harbour seal habitat should provide, therefore, suitable haul-out sites, shelter during the parturition and lactation periods and sufficient food within reach of the haul-out sites to sustain the population throughout the year. In Norway three distinct types of habitats are utilized by harbour seals: coastal archipelagos, deep fjords and fjords with estuarine sandbanks [9]. The population of

Address for correspondence: A. BjCrge, Norwegian Institute for Nature Research, P.O. Box 1037, Blindern, N-0315 Oslo, Norway.

212 harbour seals in Norway is estimated to be at least 4,100 seals; >95% of these occur in coastal archipelagos, hauling out on intertidal rocks or small islands [9]. In the Northeast Atlantic, harbour seal breeding occurs in June and early July [1,10-13] with most pups born in mid-June [11]. Parturition is followed by a 35 week lactation period. The females ovulate towards the end of the lactation period, and copulation takes place in the water [14,15]. Peak moulting occurs between midJuly and mid-September. Females apparently complete their moult about 3 weeks earlier than males and the whole moulting season is completed within 2-3 months after the end of the breeding season [ 16]. Site fidelity and restricted foraging movements make the harbour seal suitable for studies of haul-out and foraging distribution using short range VHF radio telemetry, and such studies have been carried out at several locations since the late 1970s [5,6,17,18]. In this study, we conducted detailed investigations of the habitat use and at-sea behaviour of seals before and during the breeding season, and after the moult in a coastal archipelago typical for harbour seals in Norway. In order to obtain detailed real-time information on the at-sea behaviour of individual seals, VHF telemetry was combined with underwater ultrasonic telemetry to collect data on dive depth and behaviour when seals were at sea. Materials and Methods

The study was carried out in Froan Nature Reserve off the coast of Central Norway at 64~ 9~ Froan is a coastal archipelago with a large number of small islands and islets on a shallow water plateau. It is separated from the mainland coast to the east by a 50 km wide and 500 m deep basin and separated from larger islands to the south by 300 m deep and about 5 km wide channels. To the north and west, Froan is exposed to the North Atlantic. The harbour seals haul-out in the southern and central part of the archipelago and the number of animals in the area at the time of the study probably exceeded 200 animals [9].

Seal capture and handling Seals were captured in nets with mesh size of 17-19 cm (stretched mesh). The nets were set close to haul-out sites and watched continuously to minimize the risk of drowning seals. A total of 13 harbour seals were tagged: 2 males and 2 females in June-July 1990; 3 males in June 1991; 1 female and 5 males in August-September 1993 (not all seals had a complete set of transmitters). When necessary, seals were tranquillized by Zoletil (Laboratories Reading, Z.A.C. 17 Rue des Marronniers, 94240 L'Hay-les-Roses) before further handling. After handling, seals were left on land until they voluntarily entered the water.

Tags and tagging Small VHF radio tags transmitting on frequencies between 142.0 and 142.5 MHz

213 (produced by Marine Radar Ltd, UK) were attached to the head of the seals. This position was chosen to ensure that the aerial was exposed when seals were at the surface. Depth-velocity tags were attached behind and above the fight fore flipper. These tags were composed of a pressure sensor, paddle wheel, alkaline battery and an ultrasonic transmitter. Components were made by VEMCO Ltd, Halifax, Canada, and assembled at SMRU. A temperature tag (produced for this project by SINTEF, Trondheim, Norway) composed of a temperature sensor, alkaline battery and an ultrasonic transmitter was lowered though the oesophagus and placed in the stomach of the seal. Experiments on captive harbour seals at NINA-University of Oslo showed that the temperature tags would remain in the stomach from 2 to about 20 days. Ultrasonic tags transmitted on frequencies between 60 and 99.9 kHz and all external tags were glued to the fur using an epoxy resin as described by Fedak et al. [ 19].

Data recording and tracking An automatic land-based VHF radio receiving station received and stored radio signals from the seals when they were hauled out or at the surface. The VHF radio station is described by Nicholas et al. [20] and was composed of a set of aerials covering 360 ~ a YAESU VHFAJHF Communication Receiver FRG-9600, and a SANYO 16LT portable computer used as data logger. The station could be programmed to switch from one frequency to another and thus record information from more than one animal. Tracking seals at sea was conducted by a directional VHF radio (a purpose built directional aerial and display unit and a YAESU VHF/UHF Communication Receiver FRG-9600) mounted on board an inflatable boat, type Zodiac MK IV with twin 30 hp Johnson outboard engines. The VHF signals were used to locate and close in on seals at sea. Information on dive duration and dive intervals and positions of the tracking boat were automatically logged on a SANYO 16LT portable computer. Position of the tracking boat was obtained by a GARMIN GPS 65 Personal Navigator. When tracking the seal at close proximity, detailed behavioural and physiological data from the ultrasonic transmitters were received by hydrophone and logged on VEMCO VR60 Ultrasonic Receivers (manufactured and marketed by VEMCO Ltd, Halifax, Canada).

Results

Haul-out patterns and haul-out sites We considered that continuous VHF signals for 8 min or more indicated that seals were hauled out. Although haul-out bouts were recorded during both day and night

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and at high and low tide, there was a tendency for seals to haul-out more frequently during the day and at low tide. After a trip to sea, seals regularly returned to the same

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haul-out rock or to adjacent rocks in the same area. The radio tagged seals typically hauled out among other seals on intertidal rocks in clusters of small islands (e.g. at Hestv~er, Sandskj~er and M~sskj~er in Fig. 1). One seal (91M2) tagged at Hestv~er, however, regularly hauled out alone just outside the harbour of S~rbur~y (Fig. 1).

Dive profiles as indicators of transit and foraging activity When the seals were at sea, we used dive profiles to characterize their behaviour. Travelling to and from the foraging grounds, the seals moved in typical V-shaped dives (Fig. 2). Usually we observed several consecutive V-shaped dives in a constant direction, and we defined these dives as transit dives. These dives did not always reach to the sea floor. When seals ceased directed travel at sea, a different type of dives was observed. The dive profile was U-shaped (Fig. 3), the dives usually reached the sea floor and the swimming direction frequently changed during and between dives. We defined these dives as foraging dives. The stomach temperature was used as further support in identification of foraging activity. Significant drops in temperature were interpreted as ingestion of food. An example is given in Fig. 4. On this occasion the stomach temperature of seal 93M3 was lowered stepwise from about 37~ to about 30~ over a period of 30 min during a trip at sea. The temperature gradually returned to about 37~ over a longer period of time. On a few occasions, in particular when seals foraged in areas with complex topography, transit and foraging type dives may be mingled.

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Dive durations of transit and foraging dives were not significantly different, and the average dive duration was 3.3 min (SD 1.9 min). The longest dive recorded was 14.3 min. For both transit and foraging dives the swimming speed was typically between 1.1 and 1.6 m/s.

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217

Examples offoraging trips All recorded foraging activity was at or close to the sea floor. At the sea floor, the seals continued swimming, presumably searching for food, at their usual swim speed. The seals foraged at water depths between 15 and 200 m and in areas with different substrate. Examples of foraging behaviour of typical seals are given below. One male seal tagged June 22, 1991 (91M3) travelled regularly about 20 km from his haul-out site at Sandskj~er to feed at some shallow offshore rocks (Fig. 1). He fed predominantly at depths between 15 and 50 m. Between his haul-out site and foraging grounds he passed through a 200 m deep basin where other radio tagged seals were foraging (see below). Seal 91M3, however, showed no sign of foraging activity until he reached the shallow rocks. His foraging trips were approximately 8-22 h long and most of his foraging activity was during night hours (between 1800 and 0600 h). The seal remained in the water until he was back at his haul-out site. However, during the longer foraging trips, periods of little movement were recorded. We interpreted these periods as periods with resting in water. Another male seal (90M2) tagged July 6, 1990 foraged in a deep basin 3-6 km from his haul-out sites during July (Fig. 1). His foraging trips were 3-8 h long, predominantly during day hours, and he repeatedly returned to his haul-out site or to a site were he remained stationary in water for several hours (see description of display sites below). A male seal tagged June 13, 1991 (91M2) foraged off the east side of the archipelago. This seal often hauled out outside the harbour of SCrburCy and was foraging within distances of 5 km from his haul-out site (Fig. 1). Most of his foraging activity was at depths of about 100 m. This particular seal started or finished his foraging trips in shallow sandy bays (depth of 15-30 m), where he caught flatfish, as verified by visual observation when he brought his catch to the surface. This seal foraged predominantly during night hours, and the swimming speeds and dive profiles of his nocturnal foraging trip from June 17 to June 18 are shown in Fig. 5. One male seal (93M3) tagged at Hestv~er August 28, 1993 foraged on slopes at depths between 30 and 120 m in the waters mainly north of the haul-out site. He foraged predominantly during the day and regularly returned to Hestv~er to haul-out. However, on September 2, when he foraged on the east side of the archipelago about 5-8 km from Hestv~er, he hauled out about 5 km east of his usual haul-out site. On September 4 he foraged about 15 km northeast of Hestv~er and he hauled out about 10 km from his normal haul-out site.

Foraging habitats Using the dive profiles as indicators of foraging activity, we were able to identify the foraging grounds of the individual seals. Foraging was recorded at or close to the sea floor at depths ranging from 15 to 200 m and on different substrates. The complex topography at Froan creates a diversity of habitats and the harbour seals used a variety of these for foraging.

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Fig. 5. Swim speed and dive profiles of an adult male harbour seal (91M2) during a nocturnal foraging trip from June 17 to June 18, 1991. The X-axis is time in minutes from start of tracking. From 0 to 120 min the seal moved at the surface close to the islands. Between 120 and 248 min he foraged at about 100 m depth about 0.5 km from shore. From 248 min he moved into shallow water where he foraged between 362 and 480 min. The pause in tracking between 253 and 260 min was due to echosounding the first foraging grounds which prevented receiving ultrasonic transmitted data from the seal.

The foraging grounds of seal 91M3 can be described as shallow rocks, 15-50 m below surface. At depths of less than 35 m the rocks were covered by kelp forest. The main kelp species was Laminaria hyperborea where adult plants may have a stipes of 2 m and a leaf of 1-1.5 m. The behavioural data did not provide information on whether the seal was foraging within or just above the kelp forest. Echo-surveys showed concentrations of fish surrounding the top of these shallow rocks. The fish were thought to be young saithe Pollachius virens. Seal 93M3 foraged on slopes from the deeper part of the kelp forest to depths of about 120 m. The substrate was characterized by rocks and stones in the kelp zone and stones, gravel, shells, sand and mud as the depth increased. The foraging grounds of seal 93M3 were not echo-surveyed, but concentrations of fish and single fishes were recorded at similar habitat types in 1991. The recorded concentrations of fish were probably young saithe. In shallow bays and narrows between islands, the substrate consisted of shells, crushed shells, sand and clay. In shallow parts, such bays and narrows were often dominated by sea grass Zostera marina. No concentrations of fish were recorded when echo-surveying this habitat type. Seal 91M2 used this habitat type for parts of his foraging activity. However, during most of his foraging, seal 91M2 searched for food at depths of about 100 m on substrate of gravel, sand and mud where the sea floor was gently sloping down into the 500 m deep basin east of the archipelago.

219 Echosurveys showed dense schools of fish at these foraging grounds of seal 91M2, and based on the characteristics of the echogram the fish species was thought to be herring Clupea harengus. Seal 90M2 and several of the tagged seals not described here foraged at the sea bed in 100-200 m deep basins, 2-15 km from their haul-out sites. The substrate in these basins was soft, consisting of mud and ooze. No concentrations of fish were recorded at these sites.

Diet composition In 1991 the diet of harbour seals was examined by identifying fish otoliths in 20 faecal samples collected at the haul-out sites. Seven species of fish were identified. The species are listed below according to their relative importance in the diet. Numbers in parentheses are percent frequency of occurrence: Norway pout Trisopterus esmarkii (25), saithe (20), Norwegian haddock Sebastes viviparus (15), dab Limanda limanda (5), herring (5), greater argentine Argentina silus (5), poor cod Trisopterus minutus (5). More detailed information on diet of harbour seals at Froan is given by Olsen and BjCrge [21 ].

Breeding habitats and display behaviour In June 1991 three adult males were tagged (91M1 on June 6; 91M2 on June 13; 91M3 on June 22). Until about June 27 they alternated between foraging trips and hauling out. From June 28 and July 3, seals 91M1 and 91M2, respectively, changed their activity patterns. Between foraging trips they spent much of their time in water

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220

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I~5 CALLSI MINUTE Fig. 7. Display vocalization made by male harbour seals at southern Froan in late June early July, 1991. The height of the bars indicates the number of calls per minute. Highest calls rates were recorded in the channels between the most frequented haul-out rocks in the southwestern part of Froan.

at particular sites with repetitive dives uniform in both profile and duration (Fig. 6). The mean duration of these dives was 3.34 min (SD 0.34) and mean surface interval was 0.53 min (SD 0.16). The seals vocalized at 45-60 s intervals during each dive giving 3-5 calls per dive. One seal was monitored for periods of 3 h but VHF reception indicated that he performed similar dive patterns for up to 7 h continuously. The characteristics of these calls are described in detail by Thompson et al. [22]. We interpreted this behaviour as sexual display activity. Similar calls were recorded over large areas in Froan. At some sites, we heard calling at rates up to 6 calls/min. Dividing the call detection rates by the calling rate of our tagged seals indicates that between five and nine seals were calling within the audible distance of our hydrophone at some sites. These sites were mainly in the deeper channels penetrating into the shallow water plateau between the haul-out sites which were used by females with pups and other seals (Fig. 7).

Discussion

At Froan, seals haul-out on rocks and apparently suitable rocks are available throughout the tidal cycle. However, the haul-out pattern of harbour seals in this area was influenced by the diel cycle and tidal cycle. The number of hauled out seals peaked at low tide, but according to Roen and BjCrge [3], the peaks were higher during the day than during the night. This may indicate a preference for foraging at night and a tendency to skip one haul-out bout at low tide during the night. The radio tagged seals had different timing to their foraging trips, but at least two seals (91M2 and 91M3) showed preference for foraging at night while other seals were foraging

221 during the day and night. The number of successfully tracked seals was too limited to evaluate the 24 h distribution of foraging activity. In a sample of 17 radio tagged seals in California, 6 seals hauled out most often during day, 7 hauled out most frequently during the night and for the rest of the tagged seals, no preferences were recorded [23]. In most studies, the predominant diurnal pattern indicates that seals are foraging at night. However, Thompson [7] found that harbour seals in the Moray Firth fed more often during the day when feeding on wintering clupeids. He suggested that these seals preferred to forage when the herring were concentrated in tight schools. The radio tagged seals at Froan were foraging close to the sea floor. Several fish species do migrate vertically and are distributed deeper or closer to the sea floor during the day. This indicates that seals may forage during the night if they are feeding on deep water fish, such as the greater argentine, which may be available to the seals only during their nocturnal vertical migrations. Foraging during the day may be advantageous if seals are feeding on species which are more easily caught when they are concentrated on the sea bed and this limits the range of escape routes. During June and July the tracked seals normally returned to their usual haul-out (or display) sites after a foraging trip. The tracking of seal 93M3 after moult in September 1993 indicated that this seal frequently hauled out at alternative sites, e.g. after a period of active foraging and before returning to the usual site. However, the present data provide no basis to conclude whether this was due to individual behaviour, or Jf it reflects a change in behaviour and site fidelity after moult. However, Thompson [7] stated that breeding may influence movement patterns of harbour seals. This is in agreement with the conclusions drawn by Thompson et al. [22] based on tracking of mature males during breeding season in the present study. In June and July the seals showed strong site fidelity towards haul-out sites and also towards display sites in sexually mature males. Seals tracked during this period were solitary when foraging and they regularly returned to the same or approximately the same feeding grounds for several trips during the period of tracking. Most of the foraging activity was within a few kilometres of the haul-out sites. Under such conditions, intraspecific competition for food and feeding grounds may develop. The variety of different types of foraging habitats utilized by the harbour seals and the pattern of returning to the same feeding grounds may be an indication of individual specialization and a means to minimize intraspecific competition and optimize foraging in periods of the year when site fidelity may cause constraints on the foraging movements of these seals.

Acknowledgements This study was made possible by funding from the Norwegian Council for Fisheries Research as part of the Norwegian Marine Mammal Research Programme. Additional funding was available from the Natural Environment Research Council, UK.

222

We would like to thank Sr Kaarstad, Kevin Nicholas, and the fishermen Rolf Heggelund, BjCrn Gaarden and Magne Werkland for assisting at our field work in Froan.

References 1. Bigg MA. Harbour seal Phoca vitulina Linnaeus, 1758 and Phoca largha Pallas, 1811. In: Ridgway SH, Harrison RJ (eds) Handbook of Marine Mammals, Vol 2: Seals. London: Academic Press, 1981; 1-27. 2. Stewart BS. Diurnal hauling patterns of harbor seals at San Miguel Island, California. J Wildlife Manage 1984;48:1459-1461. 3. Roen R, BjCrge A. Haul-out behaviour of the Norwegian harbour seal in summer. In: Blix AS, Walltae L, Ulltang 0 (eds) Whales, Seals, Fish and Man. Amsterdam, The Netherlands: Elsevier, 1995;61-67. 4. Thompson PM. Seasonal changes in the distribution and composition of common seal (Phoca vitulina) haul-out groups. J Zool 1989;217:281-294. 5. Thompson PM, Miller D. Summer foraging activity and movements of radio-tagged common seals (Phoca vitulina L. ) in the Moray Firth, Scotland. J Appl Ecol 1990;27:492-501. 6. Thompson PM, Pierce GJ, Hislop JRG, Miller D, Diack JWS. Winter foraging by common seals (Phoca vitulina) in relation to food availability in inner Moray Firth, N.E. Scotland. J Anim Ecol 1991 ;60:283-294. 7. Thompson PM. Harbour seal movement patterns. In: Boyd IL (ed) Marine Mammals. Advances in Behavioural and Population Biology. Symp Zool Soc London 66. Oxford: Clarendon Press, 1993;225-239. 8. Stewart BS, Leatherwood S, Yochem PK, Heide-Jlargensen MP. Harbor seal tracking and telemetry by satellite. Mar Mammal Sci 1989;5:361-375. 9. Bjtarge A. Status of the harbour seal Phoca vitulina L. in Norway. Biol Conserv 1991;58:229-238. 10. Veneables UM, Veneables LS. Observations on a breeding colony of the seal Phoca vitulina in Shetland. Proc Zool Soc London 1955;128:387-396. 11. Thompson PM. Timing of mating in the common seal (Phoca vitulina). Mammal Rev 1988;18:105-112. 12. H~irk6nen T, Heide-JCrgensen MP. Comparative life histories of East Atlantic and other harbour seal populations. Ophelia 1990;32:211-235. 13. Temte JL, Bigg MA, Wiig 0. Clines revisited: timing of pupping in the Harbour seal (Phoca vitulina). J Zool 1991;224:617-632. 14. Fisher HD. Delayed implantation in the harbour seal (Phoca vitulina). Nature 1954;173:879-880. 15. Boulva J, McLaren IA. Biology of the harbor seal, Phoca vitulina, in eastern Canada. Bull Fish Res Bd Can 1979;200:1-24. 16. Thompson P, Rothery P. Age and sex differences in the timing of moult in the common seal, Phoca vitulina. J Zool 1987;212:597-603. 17. Brown F, Mate BR. Abundance, movements, and feeding habits of harbor seals, Phoca vitulina, at Netarts and Tillamook Bays, Oregon. Fish Bull US Fish Wildl Serv 1983;81:291-301. 18. Pitcher KW, Mcallister DC. Movements and haul out behaviour of radio-tagged harbour seals, Phoca vitulina. Can Field Nat 1981;95:292-297. 19. Fedak MA, Anderson SS, Curry MG. Attachment of a radio tag to the fur of seals. J Zool 1983 ;200:298-300. 20. Nicholas KS, Fedak MA, Hammond PS. An automatic recording station for detecting and storing radio signals from free ranging animals. In: Priede IG, Swift SM (eds) Wildlife Telemetry: Remote Monitoring and Tracking of Animals. Chichester, UK: Ellis Horwood, 1992;76-78.

223 21. Olsen M, BjCrge A. Seasonal and regional variation in the diet of harbour seal Phoca vitulina in Norwegian waters. In: Blix AS, WallCe L, Ulltang 0 (eds) Whales, Seals, Fish and Man. Amsterdam, The Netherlands: Elsevier, 1995 ;271-275. 22. Thompson D, Fedak MA, BjCrge A, Bryant E, Aarefjord H, Hammond PS. Diving and calling behaviour of male harbour seals (Phoca vitulina) during the breeding season. Mar Mammal Sci (submitted). 23. Yochem PK, Stewart BS, DeLong RL, DeMaster DP. Diel haul-out patterns and site fidelity of harbor seals on San Miguel Island, California, in autumn. Mar Mammal Sci 1987;3:323-333.

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9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. Ulltang,editors

225

Spatial and temporal variations in northeast Atlantic minke whale BalaenopCera acur feeding habits Tore Haug ~, Harald Gjcs~eter2, Ulf LindstrCm3, Kjell T. Nilssen ~ and Ingolf RCttingen 2 1Norwegian Institute of Fisheries and Aquaculture, Tromsr Norway; 2Institute of Marine Research, Nordnes, Bergen, Norway; and 3Norwegian College of Fisheries Science, University of Tromsr Tromsr Norway Abstract. Stomach content samples from northeast Atlantic minke whales Balaenoptera acutorostrata, caught in scientific whaling operations in selected subareas during summer in 1992 and during spring, summer and autumn in 1993 revealed a diet where fish played a very prominent role. Considerable heterogeneity in prey species composition occurred both between areas and seasons and from year-toyear. In the 1992 summer survey, capelin dominated the whale diets in the two northmost study areas (Spitsbergen and Bear Island), while the dietary contribution of krill was much more conspicuous in both summer and autumn in 1993. This is consistent with an increase in krill and severe decrease in capelin availability in these areas from 1992 to 1993. The southern coastal areas (Kola, Finnmark, Lofoten/Vester~ilen) were different from the north in that herring was the dominant planktivorous fish. In 1992, this species, 0-group in particular, was documented to be very abundant both in the resource surveys and in the whale stomach analyses. Herring was also the most important food item for the whales in the southern coastal areas in both summer and autumn in 1993. To some extent, the herring was accompanied by gadoid species during summer in both years, and the gadoids fish species dominated the whale diet in spring in 1993. K e y words: scientific whaling, stomach analysis, prey availability

Introduction

In the management of fish stocks in the Barents Sea (and other areas), increased attention has been paid to account for multispecies interactions. Although the state of the art for multispecies assessment is not very advanced, the Multispecies Working Group of the International Council for the Exploration of the Sea (ICES) is actively working in the field. The modelling effort in the Barents Sea multispecies model (MULTSPEC) [ 1] has mainly focussed on the predation on capelin Mallotus villosus by cod Gadus morhua. Recently, however, the model has been expanded to include other top predators such as harp seals Phoca groenlandica and minke whales Balaenoptera acutorostrata. Recent attempts to analyse multispecies interactions and ecosystem functions have, however, highlighted obvious gaps and deficiencies in both data and knowledge, and this applies in particular to marine mammals [2]. For this reason, studies of the feeding ecology of important predators, including harp seals [3-5], are currently

Address for correspondence: T. Haug, Norwegian Institute of Fisheries and Aquaculture, P.O. Box 2511, N-9002 Troms0, Norway.

226 being carried out. The minke whale is a frequent marine mammal in the Northeast Atlantic, the abundance, as estimated by the International Whaling Commission (IWC), being 86,736 (CV =0.1655, 95% CI 61,000-117,000) [6]. Supplementary studies of the role of this species as a top predator are considered important [7]. The minke whale is a boreo-arctic species which, in the North Atlantic, migrates regularly to feeding areas in the high north in spring and early summer, and southwards to breeding areas in the autumn [9]. The Northeast Atlantic stock is known to

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Fig. 2. Food composition, expressed as relative biomass (by calculated fresh weight) of prey organisms, in minke whales sampled in five subareas in the Northeast Atlantic in summer in 1992, and in four subareas in the Northeast Atlantic in spring, summer and autumn in 1993.0-group herring and gadoids are presented separately. "Others" include amphipods of the genus Parathemisto and several fish species: glacier lantern fish Benthosema glaciale, blue whiting Micromesistius poutassou, redfish Sebastes sp., great silver smelt Argentina silus, witch flounder Glyptocephalus cynglossus and unidentifiable remains of gasteroids, trigliids and cottids. N = numbers of stomachs examined.

228 feed on various species of zooplankton and fish, particularly herring Clupea harengus, capelin and cod [9-13]. The collapse of two important stocks of potential prey species (Norwegian spring spawning herring in the early 1970s and Barents Sea capelin in the mid-1980s [14]) is likely to have had an impact on the feeding habits and possibly also the migratory behaviour of Northeast Atlantic minke whales. Reports from stomach inspections made during previous commercial catches are, therefore, difficult to put into present-day perspective because they relate to periods and areas with changing prey availability or with prey abundance much different from today. During a limited Norwegian scientific catch of minke whales in 1988-1990, some pilot studies of the diet of the captured animals were conducted [15]. In order to evaluate the present ecological significance of the Northeast Atlantic minke whale more thoroughly, a scientific whaling program, addressing particularly questions concerning feeding ecology by using stomach analyses and concurrent estimates of prey availability, was initiated in Norway in 1992 [16]. To fulfill the scientific objectives of this program, a scientific catch of whales at different times of the year (spring, summer and autumn) over a period of 3 years was required. The extent of the program and the many activities which have to be coordinated made it necessary to test the methodology on a reduced scale including only the summer period (July 4-August 17) during the first year (1992) of operations. In 1993, however, all three periods were included (spring, April 15-May 15; summer, June 15-July 12; autumn, August 25-September 20). This paper presents results from minke whale stomach analyses and records of potential prey abundance from these 2 years of field work. Minke whales were sampled in different subareas in Norwegian and adjacent waters. The 1992 field work included five subareas (Fig. 1). Unfortunately, Russian authorities refused any scientific whaling in the Russian economic zone in 1993. This left one of the 1992 subareas (the southeastern Barents Sea) unsurveyed and reduced the 1993 field work to incorporate only four subareas (Fig. 2). The substructured design with respect to both sampling area and time of the year enables evaluation of potential geographical and temporal variations in the minke whale diet. Furthermore, samples in the same areas from two different years enable evaluation of potential year-to-year variations.

Materials and Methods

Sampling of whales An important goal of scientific whaling is to obtain samples representative for each area; all whales present in the area should have the same probability of being caught. This calls for procedures of random sampling that ensure geographical scattering within each area and avoids preference for any particular size, sex, behavior or other attribute [16]. To obtain this randomization, sampling procedures of searching for

229 whales along predetermined transects, randomly laid out in each area, were used. In addition, when a whale was observed during a search, an all-out attempt was made at catching the whale, regardless of catchability. The transects were designed in sawtooth patterns, mainly according to the principles used during the previous shipboard sightings surveys NASS-89 [17]. Experience gained during the 1992 operations was used to perform slight modifications in the 1993 transects. In order to make the searching operations as efficient as possible, a certain amount of freedom was given to modify transect lines during the course of operation, depending on factors such as ice-cover, weather conditions and observations of minke whale abundances [18,19]. The minke whales were hunted and killed according to the whaling procedures described by Haug et al. [ 18,19]. Killed whales were immediately taken on board the vessel for dissection and biological sampling. In 1992 stomach contents data were obtained from 92 whales (51 males and 41 females, ranging in size between 485 and 883 cm). The 1993 material included samples from 63 whales (28 males and 35 females, ranging in size between 442 and 880 cm). Difficult weather conditions and low whale abundance (no whales observed at Spitsbergen, very few observed in the other areas [19]) severely hampered the 1993 spring operations when only 4 whales were obtained. During the 1993 summer period, the whale abundance situation appeared similar to the observations made in 1992, and 32 whales were obtained. Changes in relative distribution of the whales appeared to have occurred between summer and autumn, particularly in the northmost areas where the animals seemed to have left both the Spitsbergen and Bear Island subareas in favour of areas further to the east in the Barents Sea [19]. To secure samples from whales in the northern areas also during autumn, the Bear Island subarea was extended in a northeastward direction during the course of operations. A total of 27 whales were sampled in the autumn period.

Analyses of minke whale stomachs The complete digestive tract was taken out of the whale as soon as possible (1-3 h post mortem). Minke whale stomachs consist of a series of four chambers [20]. Experience from pilot studies performed during the scientific whaling in 1988-1990 suggested that sampling from the first chamber (the fore-stomach) would give sufficient data to evaluate the diet of the animals [15]. Therefore, only contents from this stomach chamber were used in the present analyses. The on board and laboratory treatment of the fore-stomach contents were as described in detail by Haug et al. [21]. Otoliths were collected and identified to the lowest possible taxon, preferably to species [22,23]. The total number of each fish species was determined by adding the number of fresh specimens, the number of intact skulls and half the number of free otoliths. Random subsamples of otoliths were measured, and otolith length-fish length/weight correlations were used to estimate the original fish weight. Erosion of

230 otoliths, which is a problem in studies of seal stomachs [24], is probably not a problem in these minke whale diet studies as the analyses were restricted to the contents in the fore-stomach where digestive glands are completely absent and no gastric acids are produced [20]. For crustaceans, the total weight and the number of individuals were recorded for each species in subsamples, and this was used to obtain crude estimates of the numerical contribution of each prey species. Known mean weights of fresh crustaceans were used to obtain crude estimates of the original biomass of the crustaceans eaten by the minke whales. Several feeding indices are commonly used in stomach analyses of top predators [24,25]. In this presentation, only the relative contribution of each prey species to the total diet expressed in terms of calculated fresh weight, was used.

Estimation of relative prey abundance In 1992, the estimation of minke whale prey abundance was performed in a survey especially designed for the purpose. One of the chartered whaling vessels was fitted with trawl equipment (but no scientific acoustic instrumentation) and was used to trawl pelagically in sound scattering layers in the two northmost sampling areas (Spitsbergen and Bear Island, Fig. 1). The remaining three sampling areas (Kola, Finnmark and Lofoten/Vesterhlen) were subjected to more thorough resource surveys using a research vessel (R/V "Johan Ruud") during the period 11-20 July. R/V "Johan Ruud" carried out an acoustic survey using standard methods [26], where a Simrad EK 500 scientific echo sounder [27] and a BEI post-processing system [28] were used. A minimum acoustic threshold o f - 8 8 dB SV was applied in order also to record larger zooplankton acoustically. Partitioning of the acoustic data and allocation of these to species were done on the basis of the acoustic character of each species and on the results from trawling. Both pelagic and demersal trawls were used to sample the observed scatterers. The standard echo integration method used is described in detail by MacLennan and Simmonds [29]. The acoustic parameter measured by the echo integrator is the area backscattering coefficient (SA), an absolute, acoustic linear unit, proportional to fish (and plankton) area density. Rough estimates of relative differences in the density of the scatterers may be made by use of the SA-Values only. This procedure is followed in this presentation, and the recorded SA-Value per nautical mile and 50 m depth channel was averaged over 5 nautical miles, and distributed on the following groups of targets: 0-group fish, plankton, cod + haddock Malanogrammus aeglefinus, herring, capelin, other pelagic fish, and other demersal fish. The 1993 prey abundance estimations were based on data drawn from regular Norwegian resource surveys designed for the mapping of relevant resources, not all of them necessarily of interest as potential whale prey (Table 1). These surveys form part of a time series, and are carried out at a time of the year which is thought to give the most reliable estimates of abundance of each actual species.

231 Table 1. Annual surveys carried out to estimate absolute abundance of fish stocks in 1993 (operating institution: Institute of Marine Research, Bergen, Norway)

Period

Area

Type of survey

Target species

Feb-Mar

Barents Sea

Cod and haddock

Mar-Apr Jun Aug-Sep Sep Dec-Jan

Lofoten-Vesterhlen Barents Sea Bear Island-Spitsbergen Barents Sea Vestfjord area

Combined acoustics and bottom trawl Acoustic survey Acoustic Bottom trawl Acoustics Acoustics, tagging

Cod, haddock and saithe Immature herring Cod Capelin, immature herring Adult herring

The resource surveys were not always fully synoptic with the minke whale sampiing (Table 1). Further, the surveys aimed to survey the entire fish stock in question while the transects applied in the minke whale sampling program surveyed only part of the distributional area of the prey. Absolute abundances of actual species were estimated for areas according to a classification proposed for use in the Barents Sea multispecies modelling (MULTSPEC) [30]. To estimate the abundance for potential minke whale prey, the following MULTSPEC areas were used to represent the minke whale sampling areas: Bear Island and Spitsbergen, MULTSPEC area VI; Finnmark, MULTSPEC areas II and III; Lofoten/Vesterhlen, MULTSPEC area I. Thus, interpolation in time and space was necessary, utilizing all available knowledge of migration and distribution. In addition to the surveys listed in Table 1, an annual international 0-group fish survey is carried out in the Barents Sea in late August and early September [31 ]. Some additional surveys, with aims other than absolute abundance estimation of fish stocks (0-group, immature and adults), were carried out, concomitantly in area and time with the sampling of minke whales. During spring, relative data on prey abundance were collected in the Bear Island and Finnmark subareas during a cruise designed to assess prawn resources, and in the Bear Island and Lofoten/Vester~len subareas during a cruise to study hydrography and the occurrence of planktonic species. During the summer period, the Spitsbergen subarea was surveyed during a prawn assessment cruise, and the Finnmark subarea during plankton surveys. Data collection during the 1993 resource mappings was generally conducted using devices and methodology comparable to those used during the 1992 "Johan Ruud" resource survey. Relevant plankton surveys to observe annual production and year to year variability were generally conducted in late summer [32]. Standard plankton nets were used to sample the whole water column from bottom to surface. Collected samples were filtered (through 2000/tm, 1000/tm and 180/~m meshes) in order to separate the different size fractions of plankton. The biomass determinations were based on dry weights.

232 Results

The 1992 data Whale stomach contents Fourteen different prey species were identified in the stomachs of the minke whales (Fig. 2). Of these, 12 were fish species. In terms of calculated fresh weight, the relative contribution of krill in all areas (except Bear Island) was small compared with fish. In the two northernmost areas (Spitsbergen and Bear Island), the fish component was completely dominated by capelin (70-90%). In the coastal areas of North Norway (Finnmark and Lofoten/Vester~len), herring (0-group, I-group, and older individuals) comprised the main bulk (77-83%) of prey biomass. One-year-old and older herring also made an important contribution to the prey biomass (27%) in the Kola area, where the prey also included considerable weights of sand eels (30%), large cod (30%) and haddock (9%). A component of large cod (9%) was observed also in the Finnmark material, while large saithe Pollachius virens were found to contribute significantly (15%) to the prey biomass in Lofoten/Vesterhlen. Prey abundance West of Spitsbergen. The pelagic amphipod Parathemisto libellula dominated the pelagic trawl hauls north in the Spitsbergen area. Some few individuals of polar cod Boreogadus saida and capelin were also found. Further south, the catches were totally dominated by 0-group cod. Some specimens of capelin were also observed. Bear Island. The area was dominated by 0-group cod. Additionally, some krill and herring were found, together with a few capelin. Simultaneously with the present survey, a cod fishery took place along the bottom in the area. Coast of Kola. The majority of echo recordings were found in the upper 50 m. Trawling revealed a total dominance of young herring in the Kola area, mainly of the 1991 year class (Table 2). Some 0-group fish were found, although in lower concentrations than observed in Norwegian coastal areas further to the west. The only plankton organism found in the pelagic trawl was krill, and only in small amounts. Coast of Finnmark. On the North Cape Bank (approximate position 71-72~ 26~ a few schools of capelin were found at 100-200 m depth. The densest fish concentrations in Finnmark were located east of 28~ and the concentrations decreased with distance from the coast. North of 71 ~ the 0-group layer was totally dominating. The 0-group fish layer in the eastem parts of this area consisted almost exclusively of cod. To the west of North Cape (26~ however, the 0-group fish layer was dominated by herring. Lofoten/Vestertden. The area was totally dominated by echoes in the upper 50 m. The largest concentrations of echoes were found in the northernmost offshore parts of the area. In the more inshore Vestfjorden, relatively small registrations were detected. A dense layer of 0-group fish dominated (Table 2), but the species composition varied. In Vestfjorden, this layer consisted of cod, haddock, saithe, herring and

233 Table 2. Ecological studies of minke whales 1992: resource surveys, mean echo abundance (SA) of prey groups in the three coastal areas Kola, Finnmark and Lofoten/Vesterfilen

Species or group

Bottom fish Pelagic fish Plankton Herring Capelin 0-group fish Cod + haddock Total

Area Kola

Finnmark

Lofoten/Vesterfilen

3.6 45.8 27.3 280.3 6.9 28.9 1.9 395.7

10.1 61.1 31.2 150.5 38.2 314.4 2.2 607.8

60.1 172.8 28.2 0.0 0.0 1700.0 42.8 2003.8

sand eel. In areas with high echo densities the layer was dominated by herring. Outside Vestfjorden this dominance of herring was nearly total.

The 1993 data Whale stomach contents During the summer period a minimum of 10 different prey species were identified in the stomachs of the minke whales, while the corresponding numbers during spring and autumn were 9 and 7, respectively (Fig. 2). Based on calculated fresh biomass, gadoid fish (cod in Bear Island and Finnmark, haddock and saithe in Lofoten/ Vesterhlen) contributed most to the diet of the minke whales taken during the spring period when only fish was found in the stomachs. During the summer, krill was particularly conspicuous (92%) in the Spitsbergen area. In all other areas, fish contributed most to the summer diet biomass: cod and haddock with 63% in Bear Island, herring with nearly 100% in Finnmark, and haddock, herring and saithe with 90% in Lofoten/Vesterhlen. In the autumn, krill contributed most to the whale diet in Spitsbergen (88%) and in Bear Island/Hopen (80%), while herring dominated the diet biomass in the two coastal areas (74% in Finnmark, 96% in Lofoten/Vesterhlen). Prey abundance: fish species Spitsbergen and Bear Island. During the 1993 spring period, winter conditions prevailed in the water masses both in the Spitsbergen and Bear Island subareas where only very small biomasses of zooplankton and pelagic fish species were available [33]. There are no absolute abundance estimates of prey organisms available for the spring and summer periods in the Spitsbergen and Bear Island region. The biomass of fish is known, however, to be rather small in both periods. The availability of fish increases in the northmost areas from July on, mainly caused by an increasing amount of 0-group fish (herring and cod in particular) which drift northwards with the warm North Atlantic Current. In August 1993, 0-group herring and cod were distributed over a major part of the two northern minke whale sampling areas

234

Table 3. Ecological studies of minke whales 1993" estimated abundance (in tonnes) of different fish stocks in the minke whale sampling areas (x = estimates not available) Period

Prey Cod

Spitsbergen Spring Summer Autumn Bear Island Spring Summer Autumn Finnmark Spring Summer Autumn

68,210

Haddock Saithe

Capelin Herring Herring (adult) (immat.)

8,453

0

0

335,421 19,784

57,000

0

64,000 34,500 x

0 1,500,000 0 1,930,000

x

Lofoten/Vester~len Spring 767,800 25,700 Summer Autumn

7,000

89,100

500,000 600,000 2,500,000

400,000 700,000 700,000

[ 14,32]. An autumn acoustic survey [31 ] also found some capelin in the eastern parts of the Bear Island area and east of Hopen (Table 3). Finnmark. The most important planktivorous fish in this area in 1993 was young and adolescent Norwegian spring spawning herring. In spring, immature herring started feeding migrations into the Finnmark area from areas further to the east [32]. Furthermore, capelin spawn in March-April along the coasts of the Kola Peninsula and Finnmark. Apparently, there will also be considerable amounts of young cod and haddock available in the area, feeding on the herring and also on some spent capelin (Table 3). In the 1993 summer period, the Finnmark area was dominated by immature herring, and from the end of July the fish biomass was further augmented by influx of 0-group fish species which were transported into the area by currents from the south west. In 1993 these 0-group fish concentrations were dominated by cod and herring [ 14,32]. The autumn period in this area was similar to the summer with a predominance of young herring and 0-group fish. The estimates of immature herring in the summer and autumn periods (Table 3) are from surveys performed in June and September, respectively (Table 1). There are no reliable estimates of cod and haddock in Finnmark for the 1993 summer period. Lofoten/Vester&len. In spring, stocks of adult fish (cod, haddock, saithe and herring) migrate northwards through this area on their way from spawning grounds to summer feeding areas. The spring stocks of cod, haddock and saithe (Table 3) were mapped on a spawning ground survey (Table 1) conducted in Lofoten and Vesterhlen from early March to early April [34]. There are also concentrations of

235 immature herring in the area, usually distributed close to the coast. Adult herring, however, migrate at 200--400 m depth to the west of the continental slope during spring. The herring estimates from the spring and summer period are interpolated from stock size estimates made in the wintering area (Table 3) and data on the relative herring distribution in April and July/August. In summer, some fish species (saithe, cod, immature herring) feed in the Lofoten/Vestergden area, while the amount of fish biomass increases substantially in autumn due to the arrival of adult herring which migrate towards their wintering area in the inner Vestfjord. The biomass data from the autumn period are estimated from acoustic estimates on the wintering areas and from tagging estimates [32].

Prey abundance: zooplankton The overall zooplankton production in 1993 in the areas of interest to the minke whale surveys was probably above average and considerably larger than in 1992 [32]. The yearly production of krill in the Barents Sea has been estimated as 50-70 million tonnes [35]. The main species of krill in this area are Thysanoessa inermis, T. raschii, T. longicaudata and Meganyctiphanes norwegica. However, the exact standing stock biomass t.in tonnes) of krill in the particular areas and times of minke whale sampling cannot be given.

Discussion

Piscivorous whales The diet of minke whales in Norwegian and adjacent waters, as observed in JulyAugust 1992, was almost completely dominated by fish while the contribution of planktonic crustaceans was very small. Fish were the most conspicuous constituents of the diet of minke whales examined also in 1993 when surveys were performed both in spring, summer and autumn. The present investigation, therefore, confirms the euryphagous nature of North Atlantic minke whales [9,10,15,36,37], similar to those in Japanese waters [38], but quite unlike the rather stenophagous krill eating minke whales in the Antarctic [39,40]. Considerable heterogeneity in diet occurred among the geographical areas investigated in both 1992 and 1993. In 1993 variation in diet composition was observed also between the investigation periods.

Restricted spring data The 1993 results may point towards a dominant role of gadoid fish (cod, haddock and saithe) in the spring diet of minke whales in the areas investigated. This seems consistent with previous observations made in Lofoten in the 1940s [9,10]. The very few whale observations made during the spring period in the northmost areas (no whales seen at Spitsbergen, very few seen at Bear Island) [19] seem consistent with observations of a typical winter situation prevailing in these waters during the whole

236 spring period [33]. The present material from the spring period is, however, very restricted, and more firm conclusions must await more data.

Capelin and krill in the north In July-August 1992 capelin dominated the whale diet in the northmost parts of the area investigated (Spitsbergen and Bear Island), while the dietary contribution of krill was much more conspicuous in the north in both summer and autumn in 1993. The prominent role of krill in the Spitsbergen area in 1993 is consistent with previous summer observations made in 1950 [9,10] and in 1989 [15]. Stomach inspections in 1950 in the Bear Island area also revealed pelagic crustaceans to be the main food item, although often mixed with capelin [10]. Interestingly, in 1989 the Barents Sea capelin stock still remained at an extremely low abundance level following a severe collapse in 1985/1986 while in 1992 it had recovered completely to its precollapse levels [14]. Furthermore, from 1992 to 1993 the capelin stock was again subjected to a dramatic decrease which occurred simultaneously with a marked increase in zooplankton production, in particular in these northern areas [32]. These ecosystem changes may have contributed to the observed changes in minke whale diets in the northernmost areas between 1989 and 1993. The large amounts of 0-group cod observed during the 1992 resource surveys in the Spitsbergen and Bear Island areas were further confirmed during the international 0-group fish survey in the area [41]. Interestingly, this vast amount of small cod in the upper water layers does not seem to have attracted the attention of the minke whales. The same was true for the pelagic amphipod P. libellula, which dominated in the northernmost trawl hauls in the Spitsbergen area but were only found in very small amounts in minke whale stomachs. Capelin was only found sporadically in the trawl hauls performed in the Spitsbergen and Bear Island areas. The same was true for krill.

Herring and gadoids in the south The capelin stock is mainly confined to the central and northern parts of the Barents Sea [42], while the dominant planktivorous fish along the Norwegian coast and in the southern Barents Sea is the Norwegian spring spawning herring. Contrasting the now very decreased capelin stock, the stock of Norwegian spring spawning herring has been increasing in recent years [32]. The difference in prey abundance situation in the southern coastal areas compared with the north was also reflected in different whale diets. Herring was clearly the most important minke whale prey species in the coastal subareas of North Norway both during summer in 1992 and during summer and autumn in 1993. Summer and early autumn predation of minke whales upon herring was observed in Lofoten and Vesterhlen both in the 1940s [9,10] and in 1988 [15,43]. In 1992 the whale diets in the southern areas were varied and included a broader spectrum of fish species than those in the north. Correlation seemed to exist between

237 prey availability and minke whale diets: 0-group herring was very abundant in the resource surveys in Lofoten/VesterAlen, less abundant in Finnmark and nearly absent off Kola. A similar west-to-east distribution of 0-group herring was found in the minke whale stomachs from these three areas. Apparently, the Kola diet was least dominated by herring, and included considerable amounts of sand eels and cod. An apparent importance of 0-group herring on the whale diet, as observed during summer in 1992, was not found in the Finnmark and the Lofoten/VesterAlen subareas in any parts of the 1993 surveys. The 1993 autumn diet of minke whales from the Lofoten/Vester~len subarea was completely dominated by adult herring, while during summer the diet was more mixed with particular large representation of haddock, to some extent also saithe. The vast autumn appearance of adult Norwegian spring spawning herring in Lofoten/VesterAlen is a relatively new phenomenon, related to the recent rebuilding of this stock [44]. Prior to the collapse of this stock in the late 1960s, the adults wintered in the open sea northeast of Iceland. In Finnmark, where herring dominated the whale diet in both periods, the whales were also observed to have eaten considerable quantities of 0-group gadoid fish during autumn in 1993. Similar minke whale predation upon 0-group fish was observed in Finnmark in August in 1988 [15]. Krill was very scarce in the diets of minke whales sampled in coastal areas of Russia (1992) and North Norway (1992 and 1993). This contradicts some earlier observations: during summer in 1972-1973, krill was found to be the main minke whale prey on the Kola coast [11,12]. Although few minke whale stomach data are available from the Finnmark coast, there is some recent evidence (from 1988 and 1990) that they may also prey upon krill and possibly also on 0-group specimens of herring, cod and haddock [ 15].

Acknowledgements Sincere thanks are due to field assistants and crews on board the chartered whaling vessels "Ann Brita", "AsbjCm Selsbane", "BrandsholmbCen", "Havliner", "Leif Junior", "Nybraena", "Rango" and "Reinebuen", and on board the research vessels "GO Sars", "Jan Mayen", "Johan Hjort" and "Johan Ruud". Assistance was received also from N. Oien in transect constructions, V. Frivoll and L. Svensson in laboratory treatment of whale stomach contents, P. Grotnes in biomass calculations, and S. Hartvedt, F. Strand and G. Granaas in figure production. R.T. Barrett is acknowledged for comments on the manuscript and improvements to the English. The ecological studies of Northeast Atlantic minke whales are supported economically by the Norwegian Council of Research (dept. NFFR), projects 40012800.084 and 4001-701.421.

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9 1995 ElsevierScienceB.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 121.Ulltang,editors

241

Seasonal distribution, condition and feeding habits of Barents Sea harp seals (Phoca groenlandica) Kjell Tormod Nilssen Norwegian Institute of Fisheries and Aquaculture, Tromsr Norway In early summer (May-June) Barents Sea harp seals (Phoca groenlandica) migrate to northern areas of the Barents Sea. Here they feed in open waters and along the drifting pack-ice during summer and autumn. In late autumn (November) the seals migrate southwards, and in winter and spring the stock is usually concentrated in the southeastern areas of the Barents Sea and in the White Sea. Breeding (late February to early March) and moult (April-May) occur in these southern areas. Seasonal variations in the condition of adults indicate that late summer and autumn are the most intensive feeding periods, and the pelagic amphipod Parathemisto libellula appears to be the dominant prey from September until mid-October. During October, a shift in the diet from pelagic crustaceans to fish seems to occur. Capelin, and to a lesser extent polar cod, are major prey during the autumn. In later winter (February) herring has been found to be the main harp seal prey in the southeastern Barents Sea. The energy reserves stored during summer and autumn are maintained until February. During breeding (March) and moult (April-May) the stores of blubber decrease rapidly, indicating restricted food intake at this time. Abstract.

Key words: migrations, feeding intensity, prey, prey abundance

Introduction

In the management of marine resources, increased attention has recently been directed towards the study of multispecies interactions. This has encouraged studies of the feeding ecology of important top predators within marine ecosystems. The harp seal (Phoca groenlandica) is the most abundant seal species in the Barents Sea. Harp seals are important predators in the Barents Sea, and studies of their role as top predators are considered important within a management context [1 ]. The species is now included in a multispecies model, MULTSPEC, which may provide the basis for future management of marine resources in the area [2]. In addition to the biological input required by multispecies modelling, data on harp seal ecology would contribute to a better understanding of environmental processes that affect feeding opportunities for the species. Furthermore, such information may be able to shed some light on density-dependent changes observed in growth and fecundity in Barents Sea harp seals over the past 30 years [3], and reveal potential causes for the extensive harp seal invasions into coastal waters of North Norway in 1986-1988 [4,5].

Address for correspondence: K.T. Nilssen, Norwegian Institute of Fisheries and Aquaculture, P.O. Box 2511, N-9002 Tromsr Norway.

242 Pilot studies of harp seal feeding along the Barents Sea pack-ice edge were carried out by the Institute of Marine Research, Bergen, in autumn 1981-1983 (unpublished data), and the investigations were continued in 1987 [6]. To provide more data on the ecological significance of harp seals in the Barents Sea, further studies designed to gather information about the feeding habits of the animals throughout the year have been carried out more recently [4,7-11 ]. Field sampling was designed to take account of the migratory pattern of the harp seal in the Barents Sea (see Fig. 1). The purposes of the studies were to determine

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Fig. 1. Map showing the seasonal migration pattern of Barents Sea harp seals, and indicating the sampiing areas in the period 1989-1994. From [16].

243 Table 1. Summary of the Barents Sea harp seals collected for ecological studies in the period 1989-

1994

Year

Season

Area

Sampling type

N u m b e of r seals

1989 1990 1991 1991 1992 1992 1992 1992 1993 1993 1994 Total

Mar Sep Jun Sep Mar-Apr Apr Apr-May Oct Feb Mar May

White Sea (1) East of Svalbard (5) East of Hopen (4) East of Svalbard (6) Varangerfjord(8) East Ice (2) White Sea (1) East of Svalbard (7) Southeastern Barents Sea (3) White Sea (1) White Sea (1)

CS SEa SEa SEa SE/GN CS SE SE SEa CS SE

300 22 239 40 44 438 302 51 110 145 52 1,743

cs, commercial sealing; SE, scientific expedition; GN, gill net by-catches. The numbers in parentheses indicate the sampling areas shown in Fig. 1. aAbundance of potential prey was assessed by trawling in the areas where seals were observed and caught. seasonal variations in condition of the harp seals and their feeding habits throughout the year. Material collected included weight, length, girth and blubber thickness measurements, contents from stomachs and intestines and, in some instances estimates of prey abundances [8-10,12]. The following represents an overview of the studies highlighting the most important results.

S a m p l i n g A r e a s a n d Periods

Harp seals were sampled in the southern Barents Sea and White Sea from February to early May 1989-1994, and along the pack-ice belt in the northern parts of the Barents Sea in June, September and October 1990-1992 (Table 1, Fig. 1). Sampling in the White Sea was carded out during Russian commercial sealing in March 1989 and 1993, and Russian research surveys in April-May 1992 and 1994. In the East Ice, sampling was carried out during Norwegian commercial sealing. In March-April 1992 in Varangerfjord, in February 1993 in the areas east of Cape Kanin and in June 1991 and September-October 1990-1992 in the northern parts of the Barents Sea, sampling of harp seals was carried out during research surveys [8-10]. The capture and on-board treatment of the harp seals, and the laboratory analyses of stomach and intestinal contents were described in detail by Nilssen et al. [8,10].

Seasonal Distribution

The annual migration route of the Barents Sea harp seals is summarized in Fig. 1. In winter and spring (December-May), the entire seal stock seems to be concentrated at

244 the southern end of its range, primarily in the southeastern parts of the Barents Sea and in the White Sea where breeding (February-March) and moult (April-May) occur [13,14]. Whelping in the White Sea is followed by 12 days of intensive lactation after which the females mate and desert the pups. After a lapse of a further 4 weeks the adults and immatures then moult. Adult males and immatures of both sexes are the first to haul out on to the ice to moult [15]. Between breeding and moult the mature females undertake a feeding migration from the White Sea westwards along the Kola coast, and some of the migrating females reach Varangerfjord in North Norway [8]. In May, during and after the moult, the seals start to migrate northwards in the Barents Sea, following the receding ice edge. From June onwards the seals are widely distributed in open and pack-ice waters from Novaja Zemlja in the east, along the pack-ice belt in the north and along the western coast of Spitsbergen [13,16]. The distribution of the harp seals at this time seems to be closely linked to the configuration and location of the drifting pack-ice during summer and autumn (June-October). The exact timing and route of the late autumn migration from the northern parts of the Barents Sea are not known, but recent observations suggest that the migration takes place during November before the main southward advance of the drifting pack-ice [16]. By December almost all harp seals appear to have moved southwards and seals are found between the southwest coast of Novaja Zemlja and Cape Kanin.

Seasonal Variations in Adult Condition

Previous observations suggest that both blubber thickness and condition of adult harp seals vary on a seasonal basis [15,17,18]. Recent analyses of changes in harp seal condition in the Barents and White Seas confirm this seasonality [9]. Harp seals are generally in poor condition in spring and early summer (MayJune), their condition improves during the course of summer, and seals are in good condition in September-October (Fig. 2). The energy stores built up during the summer and autumn are maintained until February, but then the seals become thinner as the stores of blubber decrease rapidly during the breeding period (late February to early March). There may be a slight increase in condition in the short period between lactation and moult (late March to early April), but the stores of blubber decrease during moult, which occurs from late April to June (Fig. 2). The increase in condition between mid-June and September, and a further increase to October, indicate that summer and autumn must be very intensive feeding periods. The apparent stability in condition during late autumn and early winter suggests that the seals are able to consume sufficient prey to meet energy requirements during this period. The very poor condition observed in March and June provides clear indications that feeding by the seals must be restricted during breeding and moult. Seasonal changes in feeding have also been observed in captive harp seals, with Lager et al. [19] reporting that food intake in subadults was generally low during moult (May-June), to be followed by a pronounced increase in feeding in the

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Fig. 2. The condition of adult (standard body length 150 cm or more) Barents Sea harp seals (both sexes pooled). Condition factor, C = (L/M)0"Sd,where L is standard body length in m, M is total body mass in kg and d is dorsal blubber thickness in cm, measured between the front flippers (Ryg et al. 1990). From [12]. period July-October. During the period October-April the food intake of captive seals was observed to be relatively stable.

Feeding Habits Winter-spring in the southern Barents and White Seas Our knowledge about the feeding habits of harp seals in the period N o v e m b e r January is still limited. In February 1993, harp seals were captured in the southeastern Barents Sea (Fig. 1, areas 3) and prey abundance was examined by trawling and acoustic echo-integration survey methods. In the area northeast of Cape Kanin, herring (Clupea harengus) was found to be both the dominant harp seal prey and also the dominant species in the trawl catches (Fig. 3). Herring was also the dominant prey of seals in the Pechora Sea, although polar cod (Boreogadus saida) dominated in the trawl catches [9]. The stock of Norwegian spring spawning herring collapsed in the late 1960s. However, since 1988 the stock size has increased gradually to a level comparable to that in the early 1960s. Stock size was estimated to be about 2.8 million tonnes in

246 CAPE KANIN-KOLGUYEV 100%

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1994 [20]. Thus, increasing quantities of young herring (0-group and recruits up to 4 years old) are recorded in the southern Barents Sea [21 ], and immature herring are, at present, probably the major winter prey for harp seal in this area [9]. The decline in condition in spring and early summer (Fig. 2) suggests that food intake is decreased in this period. However, some feeding does occur among lactating female harp seals. In the White Sea breeding grounds in early March 1989 and 1993, the main food items were found to be crustaceans [8]. Comparable observations were made of lactating harp seals in the White Sea in 1962 [22]. Nocturnal

247

feeding, and subsequent rapid digestion [23], may account for the low frequency of food remains found in stomachs of lactating harp seal females shot during the day [24]. The localisation of breeding grounds is determined by the drift and distribution of ice, and this may vary both seasonally and from year to year. This may result in considerable variations in food availability for the female seals which spend a lot of time on the ice nursing their pups [15,25]. In his 1962 investigations in the White Sea, Timoshenko [22] found that if food was available, lactating harp seals fed quite intensively. In contrast to the situation in early March in the White Sea, seals examined in Varangerfjord in late March to early April 1992 had stomachs well filled with undigested prey, almost exclusively capelin (Fig. 4). These seals were mostly adult females, and some still had milk in their mammary glands. These females were probably on a westward feeding migration following the lactation period. Capelin (Mallotus villosus) has also been found to dominate the diet of harp seals in this area during late winter also in 1991 [8]. The increased dominance of capelin in the seal

100

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Fig. 4. Diet composition from stomach contents analyses of harp seals caught in Varangerfjord (MarchApril) and East Ice (April) 1992. Dietary composition is given, in terms of relative frequency of occurrence of each prey item as numerical frequency and as per cent total biomass. From [8].

248 diet during late winter in eastern Finnmark in recent years differs from observations made during the extensive harp seal invasions in 1986-1988. At that time the seal diet consisted mainly of prawns (Pandalus borealis) and codfish (Gadidae) [4,11]. Earlier, in 1978-1981, harp seals taken as by-catches in winter gill-net fisheries in Finnmark were reported to have eaten mainly capelin [26]. The recovery of the Barents Sea capelin stock in 1990, following the severe collapse in 1985/1986 [20], probably accounts for the increase in importance of capelin as prey for harp seals in Finnmark during the winters of 1991 and 1992. The Barents Sea capelin spawning grounds stretch from the White Sea to the North Norwegian coast (particularly Finnmark) and spawning takes place (March-April) when harp seals are in the Varangerfjord area [27-30]. There was a new collapse in the capelin stock during 1993 [20] and the stock is again at a low level. This, combined with the substantial increase of immature Norwegian spring spawning herring in the southern Barents Sea, has probably resulted in herring becoming the most important harp seal prey in this area during the winter. Restricted feeding by harp seals was observed during the moult. In the East Ice in April 1992 the seals had eaten mainly prawns and capelin (Fig. 4), but codfish, sculpins (Cottidae), snailfish (Liparidae) and flatfish (Pleuronectidae) also occurred in the diet [8]. In April 1993 in this area, harp seal stomachs well-filled with herring were observed (K.A. Fagerheim, Institute of Marine Research, Bergen, Norway, pers. comm.). During moult in the White Sea, the harp seal diet comprised amphipods (Parathemisto spp.), prawns, capelin, herring, eelpout (Zoarces viviparus), sandeels (Ammodytes spp.) and stickleback (Gasterosteus aculeatus) [8]. Results of the Barents and White Seas studies agree with previous observations of harp seals in the western North Atlantic. In late winter and early spring, food intake tends to be reduced [15,18]. The exception seems to be in the brief period between breeding and moult when increased condition of adult seals (Fig. 2) and the occurrence of well-filled stomachs in adult females indicates that feeding is more intense. This observation is supported by previous White Sea data which showed a slight increase in adult female blubber thickness in the time period between whelping and moult [ 17].

Early summer to autumn in the northern Barents Sea The Barents Sea harp seals are found in large numbers along the drifting pack-ice and in open waters in early summer [13,16,31,32]. In the course of a research survey conducted along the ice fringe from Novaja Zemlja to Hopen in June 1991 (Table 1), almost all harp seals were observed to be confined to the pack-ice southeast of Hopen [ 10]. The stomachs of seals captured from ice floes in this area (Fig. 1, area 4) were usually empty, with only a few fragments of prawns and otoliths of long rough dab (Hippoglossoides platessoides), sculpin (Triglops pingelii), capelin and polar cod being found. There was also little sign of harp seal faeces on the ice floes where the seals had hauled out. The seals were in poor condition (Fig. 2), suggesting that little feeding had taken place during the early summer period [ 10].

249 Pelagic and bottom trawling carried out concomitantly with the capture of the seals revealed little or no potential prey in the water column at shallow depths. Prawns, capelin, polar cod and other fish species were, however, abundant in bottom waters at depths of approximately 330 m [10]. These prey items were probably unavailable to the harp seals, due to the great depth of occurrence. The fact that adult harp seals improve in condition from June to September (Fig. 2) indicates that the summer and autumn are periods of intensive feeding. However, no data are available about harp seal feeding habits in the Barent Sea during the summer period (July-August). In autumn the harp seals disperse along almost the entire ice edge, from the east of Spitsbergen to the northeastern parts of the Kara Sea [13,16]. In September 1990 and 1991 harp seals were captured whilst in water close to the pack-ice edge (Fig. 1, area

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250 5 in 1990 and area 6 in 1991). The seals had well-filled stomachs suggesting that this was a period of intensive feeding. In September 1990 the seal stomachs contained large amounts of the pelagic amphipod Parathemisto libellula. This amphipod also dominated the diet in September 1991, but prawns and various fish species were also found to contribute to the diet (Fig. 5). Pelagic and bottom trawling revealed that the amphipod P. libellula was most abundant in surface waters (surface and 20 m depth) in September 1990 (Fig. 6). This amphipod was also taken in considerable quantities in the trawl samples made

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251 10-15 m above the bottom, where krill was also present in large amounts. The volumetric contribution of fish to all pelagic hauls was low, whereas the bottom hauls comprised almost exclusively fish, particularly capelin, polar cod and flatfishes (Fig. 6). P. libellula dominated the biomass in the pelagic trawl catches taken at the surface and at 20 rn depth also in September 1991. This amphipod was also abundant in the hauls made approximately 20 m above the bottom, but krill and capelin tended to dominate these samples. Sculpin, polar cod and snailfish (Liparis spp.) were also taken [ 10]. The results of the present study agree with those of investigations carried out in the same area in September 1987 [6]. The possible importance of P. libellula as a prey species for harp seals in other Arctic areas, e.g. Greenland and Canada, has been indicated previously [ 18,33-35]. During October, the temperature in the Barents Sea region falls, and strong winds from the north result in a rapid extension of pack-ice cover towards the south. This forces the harp seals to move southwards, and the seals also seem to move towards Novaja Zemlja further to the east [13,16]. In the pack-ice areas of the central northern parts of the Barents Sea (Fig. 1, area 7) a shift in the diet of the harp seals was observed in October. Thus, the diet consisted mainly of P. libellula up to midOctober, but changed to fish, mainly capelin and to a lesser extent polar cod, as ice cover forced the seals to move southwards during late October (Fig. 5). The amphipod P. libellula is known to be the dominant species in cold water plankton communities in the upper 50 m of the water column of the northwest Atlantic [36]. The abundance of the amphipod may reach a peak in late August, and start to decline in early September [37-39]. The species is known to have a high energy content in September, and in the northwest Atlantic the lipid content increases from 18% to 35% of the dry weight from early August to mid-September [40]. The amphipod has been suggested to be an important link in the food chain between herbivorous zooplankton and marine fish, birds and mammals [ 18,33,37,38,41-45]. The observed consumption of large quantities of P. libellula by the Barents Sea harp seals would seem to confirm the importance of this amphipod species in Arctic food chains. The polar cod is known to be an important prey species in marine Arctic ecosystems [42,46]. In the Barents Sea polar cod spawn in early winter along the west and south coast of Novaja Zemlja [46]. Harp seals are known to feed on polar cod during winter [9,10,13]. Russian studies conducted during the 1930s [13] provided evidence that polar cod was the most important prey of harp seal in eastern parts of the Barents Sea during late autumn. The present stock size of polar cod in the Barents Sea is unknown, but results of annual acoustic surveys conducted since 1986 suggest that it is probably small [47]. Results of recent studies into the feeding habits of harp seals do not suggest that polar cod is currently an important prey species for the harp seal during late autumn and winter. Following the collapse of the Barents Sea capelin stock in 1985/1986 [48], the stock had recovered by 1990-1992 and stock size was comparable to that observed before 1981 [49]. During late summer and autumn the capelin is distributed throughout the central and northern parts of the Barents Sea [27]. If abundant the capelin

252 may represent a potential prey for the seals, and the results of stomach content analyses conducted in late October 1992 tend to support this (Fig. 5). Apparently, there are several fish species that may serve as prey for harp seals during the late autumn and early winter. Given the variability in abundances of species such as capelin and herring, and the currently low level of the Barents Sea capelin stock [20], the catholic taste of the harp seals for different species of fish prey is probably important in ensuring adequate winter feeding in the southern Barents Sea.

Acknowledgements Thanks are due to the crews and field assistants on board the vessels "Johan Ruud", "Polarfangst", Michael Sars", "Selis", "Meridian", "Melshorn", "Jan Mayen" and "Varzuga". The following field assistants participated during the sampling in Varangerfjord and in the White Sea: A. Orjebu, T.O. Rudi, S.A. Kjellqwist, G. Henriksen, Y. Nazarenko and V. Adrianov. Thanks are also due to B. BergflCdt, K.A. Fagerheim, N.E. Skavberg, L. Lindblom, F. Strand, L. Olsen, G. Granaas, S. Hartvedt, N. Stasenkova and S. Slonova for technical and laboratory assistance, and to T. Haug and M. Jobling who commented upon the manuscript and the latter corrected the English. The ecological studies of harp seals were supported by funding from the Norwegian Council of Research, project no. 4001-701.260.

References 1. Anon. Predation and predatory processes in marine mammals and sea-birds - report of a Nordic seminar, Troms~. Nordiske Seminar- og Arbeidsrapporter 1991 ;512:39 pp. 2. Bogstad B, Tjelmeland S, Tjelta T, Ulltang 0. Description of a multispecies model for the Barents Sea (MULTSPEC) and a study of its sensitivity to assumptions on food preferences and stock sizes of minke whales and harp seals. Int Whal Commn 1992;SC/44/09:47 pp. 3. Kjellqwist SA, Haug T, Oritsland T. Trends in age composition, growth and reproductive parameters of Barents Sea harp seals Phoca groenlandica. ICES J Mar Sci 1995;52 (in press). 4. Haug T, KrCyer AB, Nilssen KT, Ugland KI, Aspholm PE. Harp seal (Phoca groenlandica) invasions in Norwegian coastal waters: age composition and feeding habits. ICES J Mar Sci 1991;48:363-371. 5. Haug T, Nilssen KT. Ecological implications of harp seals Phoca groenlandica invasions in northern Norway. Proceedings of the International Symposium on the Biology of Marine Mammals in the Northeast Atlantic, Troms~, Developments in Marine Biology IV. 1994 (in press). 6. Lydersen C, Angantyr LA, Wiig 0, r T. Feeding habits of northeast Atlantic harp seals Phoca groenlandica along the summer ice edge of the Barents Sea. Can J Fish Aquat Sci 1991 ;48:2180-2183. 7. Nilssen KT, Grotnes P, Haug T. The effect of invading harp seals (Phoca groenlandica) on local coastal fish stocks in North Norway. Fish Res 1992;13:25-37. 8. Nilssen KT, Haug T, Potelov V, Stasenkov VA, Timoshenko YK. Food habits of harp seals (Phoca groenlandica) during lactation and moult in March-May in the southern Barents Sea and White Sea. ICES J Mar Sci 1995;52:33-41. 9. Nilssen KT, Ahlquist I, Eliassen J-E, Haug T, Lindblom L. Studies of food availability and diets of

253

10.

11. 12. 13.

14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26.

27. 28. 29. 30. 31.

32. 33.

harp seals (Phoca groenlandica) in the southeastern Barents Sea in February 1993. ICES CM 1994;N:12:24 pp. Nilssen KT, Haug T, Potelov V, Timoshenko YK. Feeding habits of harp seals (Phoca groenlandica) during early summer and autumn in the northern Barents Sea. Polar Biol 1995;15 (in press). Ugland KI, Jc~destcfl KA, Aspholm PE, Krc~yer AB, Jakobsen T. Fish consumption by invading harp seals off the Norwegian coast in 1987 and 1988. ICES J Mar Sci 1993;50:27-38. Nilssen KT, Grotnes PE, Haug T, Potelov V. Seasonal variation in condition of adult Barents Sea harp seals, Phoca groenlandica. Mar Mammal Sci (submitted). Chapskii KK. Nektoroye ekologicheskie obosnovaniya sezonnoi dynamiki areala belomorskoi populyatsiy grenlandskogo tyulenya (Pagophoca groenlandica) (Some biological factors determining seasonal changes in distribution of the White Sea harp seal population (Pagophoca groenlandica)). Trudy Soveshchanii, Ikhtiol Komissii Akad Nauk SSSR 1961; 12:150-163; translated in: Ser Fish Res Bd Can 1962;380:1-22. Benjaminsen T. Pup production and sustainable yield of White Sea harp seals. Fisk Dir Skr Ser Hav Undsers 1979;16:551-559. Sergeant DE. Harp seals, man and ice. Can Spec Publ Fish Aquat Sci 1991;114:1-153. Haug T, Nilssen KT, Oien N, Potelov V. Seasonal distribution of Barents Sea harp seals (Phoca groenlandica) in the Barent's Sea. Polar Res 1994;13:163-172. Sivertsen E. On the biology of the harp seal Phoca groenlandica Erxl. Investigations carried out in the White Sea 1925-1937. HvalrAdets Skr 1941;26:1-166. Sergeant DE. Feeding, growth and productivity of northwest Atlantic harp seals (Pagophilus groenlandicus). J Fish Res Bd Can 1973;30:17-29. Lager AR, NordCy ES, Blix AS. Seasonal changes in food intake of harp seals (Phoca groenlandica) at 69~ Mar Mammal Sci 1994;10(3):332-341. Anon. Ressursoversikt 1994. Fisk Hav 1994;1:1-104. Anon. Report of the Atlanto-Scandian Herring and Capelin Working Group, Copenhagen, October 1993. ICES CM 1994;Assess 8:78 pp. Timoshenko YK. K voprosu o pitanii grenlandskogo tulenya. Sbornik nauchno-issledovatelskih rabot 1962 g (grenlandsky tulen i hohlach). Arkhangelsk 1963;48-52. Murie DJ. Estimating food consumption of free-living harp seals, Phoca groenlandica (Erxleben 1777). MSc thesis, Department of Zoology, University of Guelph, Guelph, 1984. Stewart REA, Murie DJ. Food habits of lactating harp seals (Phoca groenlandica) in the Gulf of St. Lawrence in March. J Mammol 1986;67:186-188. Lydersen C, Kovacs KM. Diving behaviour of lactating harp seals, Phoca groenlandica, females from the Gulf of St Lawrence, Canada. Anim Behav 1993;46:1213-1221. BjCrge A, Christensen I, Oritsland T. Current problems and research related to interactions between marine mammals and fisheries in Norwegian coastal and adjacent waters. ICES CM 1981;N:18:10 pp. Dragesund O, GjOs~eter J, Monstad T. Estimates of stock size and reproduction of the Barents Sea capelin in 1970-1972. Fisk Dir Skr, Ser Hav Unders 1973;16:105-139. GjCs~eterH, Loeng H. Distribution and growth of the capelin in the Barents Sea in relation to water temperature in the period 1974--1983. ICES CM 1984;Gen.:16(Mini-symp):16 pp. Hamre J. Hva har hendt med lodda? Fiskets Gang 1991;77(2):10. Anon. Ressursoversikt 1992. Fisk Hav 1992;1:1-72. Chapskii KK. Noveishie dennye o raspredelenskii Belmorskoi rasy Grenlandskogo tyulenya vne Belmorskogo. (New data on distribution of the White Sea race of harp seal outside the White Sea basin). Probl Arktiki 1938;4:105-131. Christensen I. UndersCkelser av vAgekval i Barentshavet og ved Ost- og Vest GrCnland i 1973. Fiskets Gang 1974;60:278-286. Davis RA, Finley KJ, Richardson WJ. The present status and future management of arctic marine

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36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48.

49. 50.

mammals in Canada. Science Advisory Boards of the Northwest Territories, Yellowknife. 1980;Rep No. 3:93 pp. Kapel FO, Angantyr LA. Feeding patterns of harp seals (Phoca groenlandica) in coastal waters of West Greenland, with a note on offshore feeding. ICES CM 1989;N:6:28 pp. Finley KJ, Bradstreet MSW, Miller GW. Summer feeding ecology of harp seals (Phoca groenlandica) in relation to Arctic cod (Boreogadus saida) in the Canadian High Arctic. Polar Biol 1990; 10:609-618. Percy JA. Reproduction and growth of the Arctic hyperiid amphipod Themisto libellula Mandt. Polar Biol 1993;13:131-139. Dunbar MJ. On Themisto libellula in Baffin Island coastal waters. J Fish Res Bd Can 1946;6(6):419--434. Dunbar MJ. The determinants of production in northern seas: a study of the biology of Themisto libellula Mandt. Can J Zool 1957;35:397--434. Percy JA, Fife FJ. Summertime abundance and depth distribution of macrozooplankton in Frobisher Bay, NWT, from 1978 to 1983. Can Data Rep Fish Aquat Sci 1985;503:63 pp. Percy JA. Energy consumption and metabolism during starvation in the Arctic hyperiid amphipod Themisto libellula Mandt. Polar Biol 1993;13:549-555. Dunbar MJ. Marine macroplankton from the Canadian eastern Arctic. 1. Amphipoda and Schizopoda. Can J Res 1942;20D:33--46. Bradstreet MSW, Cross WE. Trophic relationships at high Arctic ice edges. Arctic 1982;35(1): 112. LCnne OJ, Gulliksen B. Size, age and diet of polar cod, Boerogadus saida (Lepechin 1973) in ice covered waters. Polar Biol 1989;9(3):187-191. Ajiad AM, Gj~s~eter H. Diet of polar cod, Boreogadus saida, in the Barents Sea related to fish size and geographical distribution. ICES CM 1990;G:48:9 pp. Mehlum F, Gabrielsen GW. The diet of high-arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago. Polar Res 1993;12(1):1-20. Panomarenko VP. Some data on the distribution and migrations of polar cod in the seas of the Soviet Arctic. Rapp P-V Reun Cons Perm Int Explor Mer 1968;158:131-135. GjCs~eterH, Ajiad AM. Growth of polar cod, Boreogadus saida (Lepechin), in the Barents Sea. ICES J Mar Sci 1994;51:115-120. Hopkins CCE, Nilssen EM. The rise and fall of the Barents Sea capelin (Mallotus villosus): a multivariate scenario. In: Sakshaug E, Hopkins CCE, Oritsland NA (eds) Proceedings of the Pro Mare Symposium on Polar Marine Ecology, Trondheim, 1990. Polar Res 1991;10:535-546. Anon. Ressursoversikt 1993. Fisk Hav 1993; 1:1-66. Hamre J. Some aspects of the interrelation between the herring in the Norwegian Sea and the stocks of capelin and cod in the Barents Sea. ICES CM 1988;H:42:15 pp.

9 1995ElsevierScienceB.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand t3. Ulltang,editors

255

Food consumption of the Northeast Atlantic stock of harp seals E.S. Nord~y, P-.E. MS.rtensson, A.R. Lager, L.P. Folkow and A.S. Blix Department of Arctic Biology and Institute of Medical Biology, University of Tromsr Breivika, Tromsr Norway Abstract. The present report estimates the yearly food consumption of the White Sea population

(--600,000 animals) of the Northeast Atlantic stock of harp seals. Daily gross energy intake (GEI) was determined by studies of captive harp seals (Phoca groenlandica) offered capelin (Mallotus villosus) with an energy density of 9.6 kJ/g (wet mass). Daily food intake averaged 3.3 % of body mass, and GEl was 25,600 kJ/day. Using a chemical marker method (Mn 2+) digestible energy (DE) of capelin was found to be 93% of GEl, while the DE of krill (Thysanoessa sp.) or amphipods was 82%. Data on GEI, DE, diet composition (based on analysis of stomach contents from seals mainly caught in the pack ice) and seasonal changes in energy density of prey, were used to arrive at an annual food consumption of this population of 1 million tonnes. Of this, about 700,000 tonnes is likely to consist of various fish species, of which capelin and herring (Clupea harengus) appear to be the most important. Our calculations may underestimate fish consumption, however, since feeding experiments and preliminary data from satellite telemetry indicate that harp seals rely less on crustaceans than hitherto presumed. Key words:

Phoca groenlandica, food cnnsumption, Barent's Sea

Introduction

Harp seals in the Northeast Atlantic are divided into two apparent subpopulations, one which breeds in the Greenland Sea (Jan Mayen area) and one breeding in the White Sea of Russia. After breeding and moulting in the pack ice, the populations disperse and probably spend much of the time in open waters of the Greenland and the Barents Seas, respectively, as well as along the northern pack ice edge. In the following, food consumption estimates will be made for the White Sea population only, since there are no recent data on the diet of the Greenland Sea population. The pup production of the White Sea population has been estimated by visual surveys to be about 140,000 pups during the spring of 1991 [1], which indicates a total population size in the order of 600,000 seals (1 year and older) [2]. The rather high number of animals, combined with a mature body mass of 120-150 kg, makes the harp seal an important top predator in the Northeast Atlantic. At the Department of Arctic Biology we have kept harp seals in captivity for several years and during this period, studied food intake and digestibility of different foods to obtain estimates of food consumption on the individual level. The purpose of the present paper is to use results obtained from experiments on captive harp seals, together with current knowledge on the seasonal changes in diet composition and the

Address for correspondence: E.S. Nord~y, Department of Arctic Biology, Breivika, 9037 Tromsr Norway.

256 energy content of prey, to estimate the yearly consumption of various prey groups by harp seals of the White Sea population.

Gross Energy Intake of Captive Seals Since data on the average field metabolic rate and food consumption of free-living harp seals are difficult and expensive to obtain, we have performed a food intake study of captive harp seals for an entire year under changing light conditions which simulates the light regime which harp seals would normally encounter in the wild at 70~ [3]. The great importance of seasonal changes in photoperiod in body mass regulation, appetite and activity levels has previously been demonstrated for other polar species at our department [4-6]. Using four growing harp seals with an age of 3-4 years and an average body mass of 81.3 kg, Lager and co-workers [3] found that food intake varied seasonally from a high level of 5-6% of body mass in August-September to a low level of 1-2% of body mass in April-June, demonstrating the importance of obtaining such measurements throughout the year. Since the energy density of food (--9.6 kJ/g) was continuously monitored, the food intake data could be translated into the average amount of energy ingested, or gross energy intake (GEI), for harp seals during growth. Thus, the average daily GEI per animal was 25,600 kJ/day. Since these measurements were based on medium-sized harp seals that were in an age class probably representing a rather high proportion of the population [7], GEI of these four seals was assumed to be representative of an average, free-living harp seal. Multiplying the all-year average of 25,600 kJ/day with a total population of 600,000 seals, gives an estimate of the total GEI of the population in the order of 5.6 • 1012 kJ/year, if capelin was the only food source. Moreover, if harp seals eat significant amounts of crustaceans, GEI must be adjusted upwards due to a lower digestibility of this prey (DE--82% of GEI), compared with capelin (DE ~92% of GEI) [8].

Diet Composition and Energy Density of Prey In order to convert our estimated GEI into total food intake, one important premise is that seasonal changes in diet composition are known. The 250 stomachs used in this analysis were collected in February-April in Varanger [10,11], during the period February-April in the pack ice off Cape Kanin and in the Pechora Sea [12] and in the period August-October in the pack ice between Svalbard and Franz Josefs Land [13,14]. Thus, almost all our data so far were obtained from seals which resided in the pack ice. The different data for different subareas and seasons were combined to obtain the approximate average yearly % mass contribution from different prey groups. These data suggest that Parathemisto sp. and other crustaceans contribute about 35% of

257 Table 1. The diet composition (as % mass), the average energy density of the prey (in the period 1 January to 31 December) and the % energy contribution of the various prey to gross energy intake (GEI) Prey

% mass

Energy density (kJ/g) wet mass

% of GEl

Parathemisto sp. Herring Capelin Fish, various Pandalus sp. Crustacea Polar cod Sand eel

27.1 20.7 24.2 15.7 4.8 3.0 1.8 2.6

3.9 7.1 6.9 4.9 5.1a 5.0 5.3 6.0

18.8 26.2 29.8 13.7 4.4 2.7 1.7 2.8

aTaken from Keiver et al. [9]. ingested mass of prey, while fish, in particular capelin (Mallotus villosus) and herring (Clupea harengus), contribute the remaining 65% (Table 1). Another critical factor during this process of conversion from GEI to food intake is the seasonal changes in energy density of prey. Many of the important prey groups of harp seals display substantial seasonal changes in energy density (Mhrtensson PE, et al., submitted to Mar Mamm Sci). For example, capelin varies from 4.8 kJ/g (wet mass) in mid-summer to 9.5 kJ/g in late autumn and mid-winter, with a yearly average of 6.9 kJ/g (Table 1).

Food Consumption By combining data on energy density of prey, diet composition, digestibility of the prey and the assumed GEI (Table 1) of a population of the order of 600,000 animals, the consumption of different prey groups was estimated (Fig. 1). These calculations suggest that in the order of 300,000 tonnes of Parathemisto sp., 200,000 tonnes of herring and 250,000 tonnes of capelin are consumed. The total fish consumption is in the order of 700,000 tonnes, while the total consumption of prey, including crustaceans, most likely exceeds 1 million tonnes. To put these numbers into perspective, the estimated food consumption by harp seals was compared with the estimated stock size and the total commercial catch of herring and capelin in 1993 in the Norwegian and Barents Seas (Fig. 2). These numbers suggest that the consumption of herring by harp seals may be at least of the same order of magnitude as the total commercial harvest of herring which was estimated at 8% of the total spawning stock in 1993 in the Norwegian and Barents Sea [15]. Similarly, the estimated consumption of capelin by harp seals may have been about 50% of the commercial take (--586,000 tonnes) in the same area in 1993, when the spawning population was assumed to be 2.2 million tonnes, based on the estimation of the mature stock of capelin during the autumn of 1992 [15]. These numbers show that harp seals may have considerable impact on fish stocks and that it is of

258

0 0 0 '%'"

500

X 09

ttO cO ...,E

to tO 0

>,, (1) t_

n

400 -

[----] Parathemisto sp. Pandalus borealis Crustaceans

300 -

2o0

-

100

-

Fishes

Crustacea, various Herring Capelin IIT[]T~ Sand eel Polar cod Fish, various

[rl]~

0

Prey groups Fig. 1. The estimated mass (1000 tonnes) of various prey species consumed by 600,000 harp seals of the White Sea population in the Northeast Atlantic. The values are based on gross energy intake of captive harp seals, the energy density of prey and the % mass of different prey groups as found by stomach content analysis.

3000

0 0 0

1----] Spawning stock size Commercial catch Harp seal consumption

2500 -

X o~

2000

C C 0

1500 -

-4,--o

O'J o~ t13

-

1000

-

500

-

E 0

83 9- -

Capelin Herring

Fig. 2. The biomass (1000 tonnes) of the spawning population of capelin (3 years +) and herring (3 years +), compared with the total commercial catch of these species [15] and the estimated harp seal consumption (this paper) in the Northeast Atlantic in 1993. To be noted is an additional consumption of capelin and herring by other marine mammals (minke whales in particular) and cod (Gadus morhua). It is emphasised that the biomass of younger age-classes of fish (pre-recruits), which is probably considerable, is not included in the biomass of fish stocks.

259 importance to consider the harp seal population food consumption in future predictions of stock size developments of different important commercial species, like herring and capelin. However, this analysis may be biased due to the fact that most of the stomach material was collected from harp seals from the pack-ice area in the northern and southeastern Barents Sea. As a consequence, the crustacean species Parathemisto libellula, being particularly abundant in close vicinity to pack ice, may be overrepresented in the final food consumption estimates. This suggestion is based on the following arguments. First, extensive feeding experiments have shown that young harp seals which were fed a mixed diet of P. libellula and krill (Thysanoessa sp.), two apparently important crustaceans in the diet, were not able to obtain a positive energy balance [8,16]. In fact, despite access to food ad libitum and a daily food intake of up to 3.7 kg, body mass was lost. After replacing the krill with a diet of capelin, however, an immediate increase in body mass was observed. This pattern of body mass development may be attributed to the rather low energy density and a lower digestibility of crustaceans (M~trtensson P-E et al., submitted to Mar Mamm Sci), compared with capelin [8], and, perhaps, that more energy was wasted during a more timeconsuming feeding behaviour, when eating crustaceans. Secondly, in July 1992 three harp seals were tagged with satellite transmitters to follow their movements after moulting in the Greenland Sea (Folkow and Blix, unpublished). The tags were attached to the fur on the back of the seals, and since these often swim on their backs, locations could only be obtained while the seals hauled out on ice-floes. Initially, all seals stayed within the pack ice. After a few days, however, contact was lost with all seals, in some cases for several months, before they were again relocated along the northern pack-ice edge. We believe that the seals stayed in open water at high sea when they were "incommunicado". This pattern of alternating haul-outs in the pack-ice and long travels somewhere in the open waters was observed throughout the study period (July-April), suggesting that the search for food was mainly concentrated on open waters where fish is more abundant. Based on these findings we conclude that a future priority research area is to obtain unbiased information about the autumn and winter distribution and dive behaviour of harp seals by use of satellite telemetry, in order to improve our understanding of the diet composition of these seals at a time of the year and in areas where traditional stomach content data are extremely difficult to obtain. Such information, supplemented with improved population estimates, may bring us additional steps ahead in our efforts to understand the impact of harp seals on fish stocks and vice versa.

Acknowledgements This study was supported by the Norwegian Fisheries Research Council, Marine Mammal Research Programme, grants nos. 408.004, 408.008 and 408.016.

260

References 1. Anonymous. Report of the Joint ICES/NAFO working group on harp and hooded seals, Copenhagen, 15-21 September 1993. ICES CM 1994;Assess.5:35 pp. 2. Oien N. Er det nok grCnlandssel til at den kan hCstes? Forvaltning og fangstutsikter. Ottar 1994;3:25-33. 3. Lager AR, Nord~y ES, Blix AS. Seasonal changes in food intake of harp seals (Phoca groenlandica) at 69~ Mar Mammal Sci 1994;10:332-341. 4. Larsen TS, Nilsson NO, Blix AS. Seasonal changes in lipogenesis and lipolysis in isolated adipocytes from Svalbard and Norwegian reindeer. Acta Physiol Scand 1985; 123:97-104. 5. Stokkan K-A, Mortensen A, Blix AS. Food intake, feeding rhythm, and body mass regulation in Svalbard rock ptarmigan. Am J Physiol 1986;251 :R264-R267. 6. NordCy ES, Blix AS. Sources of error in estimating food requirements of seals. Polar Rec 1988;24:62-64. 7. Kjellqwist SA, Haug T, Oritsland T. Trends in age composition, growth and reproductive parameters of Barents Sea harp seals, Phoca groenIandica. ICES J Mar Sci (in press). 8. MArtensson P-E, Nordg~y ES, Blix AS. Digestibility of crustaceans and capelin in harp seals (Phoca groenlandica). Mar Mammal Sci 1994;10:325-331. 9. Keiver KM, Ronald K, Beamish FWH. Metabolizable energy requirements for maintenance and faecal and urinary losses of juvenile harp seals (Phoca groenlandica). Can J Zool 1984;62:769776. 10. Nilssen KT, Haug T, Potelov V, Timoshenko Y. Preliminary data on feeding and condition of Barents Sea harp seals (Phoca greonlandica) throughout the year. ICES CM 1992;N.5:23 pp. 11. Nilssen KT, Haug T, Potelov V, Stasenkov VA, Timoshenko YK. Food habits of harp seals (Phoca groenlandica) during lactation and moult in March-May in the southern Barents Sea and White Sea. ICES J Mar Sci 1995;52:33-41. 12. Nilssen KT, Ahlquist I, Eliassen J-E, Haug T, Lindblom L. Studies of food availability and diet of harp seals (Phoca groenlandica) in the southeastern Barents Sea in February 1993. ICES CM 1994;N.12:24 pp. 13. Lydersen C, Angantyr LA, Wiig 0, Oritsland T. Feeding habits of Northeast Atlantic harp seals (Phoca groenlandica) along the summer ice edge of the Barents Sea. Can J Fish Aquat Sci 1991 ;48:2180-2183. 14. Nilssen KT, Haug T, Potelov V, Tomichenko YK. Feeding habits of harp seals (Phoca groenlandica) during early summer and autumn in the Northern Barent's Sea. Polar Biol (in press). 15. Anonymous. Ressursoversikt. Fisk Havet 1994;1:1-104. 16. M~rtensson PE. Foderintag og energiutnyttjning av kr~iftdjur og risk hos gr6nlands~il (Phoca groenlandica). MSc thesis, University of Troms~, 1992, 39 pp.

9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. Wallr and r Ulltang,editors

Historic variation in the diet of harp seals in the northwest Atlantic

261

(Phoca groenlandica)

John W. Lawson and Garry B. Stenson Science Branch, Department of Fisheries and Oceans, St. John's, Newfoundland, Canada Abstract. Background: traditionally, diets of harp seals in the NW Atlantic have been described using

the prevalence of prey items in stomachs. This paper uses an alternative method, reconstructed wet weight, and prevalence to provide new data about dietary variation in nearshore and offshore areas. Methods: diet was determined by reconstructing the contents of 3,299 stomachs collected in 1982, 1986 and 1990-1993 in nearshore and offshore locations. Wet weights of prey were derived from measurements of otoliths and squid beaks in the stomachs. Results: annual, geographic and seasonal differences were observed in the diets of seals collected near Labrador, NE, W and S Newfoundland, and in offshore areas. In nearshore NE Newfoundland there was a drastic shift in diet from a heavy reliance on capelin (Mallotus villosus) in 1982, to polar cod (Boreogadus saida) from 1986 to 1993. Conclusions: while previous studies concluded that capelin was the major prey, reconstructions of stomach contents have revealed that polar cod has been the most important prey in nearshore areas since 1986. In contrast, capelin is the major component in the offshore diet. Atlantic cod represented only a minor part of prey weight consumed in either area since 1982. K e y words: polar cod,

Boreogadus saida, Atlantic cod, Gradus morhua

Introduction In the northwest Atlantic, harp seals (Phoca groenlandica), the most abundant marine mammal [1], inhabit coastal and offshore waters from the Gulf of St. Lawrence to the southern Arctic [2] where they may be significant predators. To date, our knowledge of the diet of harp seals in eastern Canada has been based primarily on relatively small samples of stomachs from different locations, seasons and years (for a review, see Ref. [3]). Differences observed in the diet may have been due to variability in the diet, or biases associated with data collection, or small sample sizes. The frequencies of prey species in stomachs, a commonly used method of expressing diet [2,4], do not provide information about the biomass of each species in the stomachs or the size of prey consumed [5]. This method also tends to overestimate the importance of numerous small prey in the diet while underestimating the contribution of larger, less common items [5]. Reconstructed wet weight permits assessment of the relative contributions of prey species by estimating the sizes of prey eaten from measurements of otoliths and other hard parts recovered from seals' stomachs [2,6]. At present, when coupled with en-

Address for correspondence: J.W. Lawson, Science Branch, Fisheries and Oceans, P.O. Box 5667, St. John's, Newfoundland, Canada A1C 5X1. E-mail: [email protected].

262 ergy density values for specific prey species, this method provides one of the best means to determine which prey satisfy the energy requirements of the seals, and the size (age) of fish taken. This is the first large-scale study of the annual, geographic and seasonal variability in harp seal diet in waters surrounding Newfoundland and Labrador using both frequency and percent wet weight measures of prey importance.

Methods

Stomach contents were examined from 3299 harp seals collected in nearshore and offshore areas around Newfoundland and Labrador (Fig. 1) in 1982, 1986 and 19901993. Since annual and seasonal effects on diet may be confounded by an un-

84 o

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48 o

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48 o

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.

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52 o

44o

Fig. 1. Distribution of harp seal stomach samples collected in nearshore and offshore waters of New-

foundland and Labrador, Canada during 1982, 1986 and 1990-1993.

263 balanced sample, we used a subsample of the data from older seals in NE Newfoundland to examine these effects. Seals were aged using dental annuli and divided into two age groups: pups less than 1 year old (0-group) and seals aged 1 year and older (1+; diets of older seals were similar and aggregated for analyses). Stomachs collected between April and September were designated as "summer" samples and those taken between October and March as "winter" samples. Harp seals were either shot or caught in nets (by Fisheries and Oceans personnel or licensed sealers). Stomachs were removed soon after death, and either frozen at -20~ or preserved in a 70% ethanol solution. In the laboratory, stomach contents were examined using methods described by Murie and Lavigne [7] and Bowen et al. [8]. Otoliths with minimal or no erosion were measured to the nearest 0.01 mm. If more than 50 uneroded otoliths were present, a random subsample of 25 otoliths was measured, and the mean was applied to the unmeasured otoliths. Lengths and wet weights of fish and squid were estimated from regressions relating these measures to otolith or beak dimensions. To estimate the biomass represented by eroded otoliths, we assumed that eroded otoliths of each species were originally the same size as the average of the uneroded measured otoliths of the same species in that stomach. To estimate total biomass in an individual stomach, we summed the estimated wet weights of all prey items.

Results

Sixty-two prey types were identified from stomachs collected in nearshore areas and 43 from those offshore, however less than a third of these contributed significantly (Table 1). The importance of the various prey species differed when expressed as prevalence or weight; the two estimates were similar for only polar cod, rock cod and Atlantic herring. Prevalence was greater than reconstructed weight for capelin, Gadus sp., sand lance (Ammodytes sp.), sculpin sp. (Cottidae), and most invertebrates. Significant geographic differences were observed in the relative importance of major prey species (Table 1). Polar cod, sculpins, Atlantic cod, Gadus sp. and capelin accounted for the majority of the prey weight consumed by 1+ seals from Labrador. Polar cod provided most of the prey weight eaten by 1+ seals in NE Newfoundland, while Atlantic cod were less important than any other area. Redfish, and to a lesser extent, Atlantic cod, herring (Clupea harengus) and capelin were the major components, by prevalence and weight, in the 1+ stomachs collected in S Newfoundland. Polar cod were not present in any stomachs from this area. Capelin, herring, Atlantic cod, redfish (Sebastes sp.) and rock cod (Gadus ogac) provided most of the weight consumed in W Newfoundland. Capelin were the most important prey in offshore areas (40.8% of biomass) with sand lance, Greenland halibut (Reinhardtius hippoglossoides), Pleuronectids and

-

-

~~-

--

Prey species

Labrador Prev.

I + Seals Polar cod Atlantic cod Atlantic herring Capelin Gadus sp. Greenland halibut Pandalus montagui Redfish Pleuronectidae Rock cod Sand lance Sculpin sp. Teuthoidea Total O-Group seals Polar cod Atlantic cod Atlantic herring Capelin Gadus sp. Hyperiidae Euphausiacea Greenland halibut Mysis mixra Pandalus montagui Sand lance Total

Weight %

Northeast Newfoundland

Southern Newfoundland

Western Newfoundland

Prev.

Prev.

Rev.

Weight %

5.6 50.0

1.9 89.1

Weight %

-

54.8 6.2 0.3 23.2 11.1 0.6 13.2 0.3 0.6 3.1 9.9 21.2 0.6 313 seals 28.6 7.1 46.4 -

10.7 14.3 3.6 7.1 3.6

21.4 29 seals

Weight %

31.1 13.1 41.0 6.6 8.2 41.0 3.3

-

11.5

-

6.6 61 seals

5.7 0.2 -

25.7

-

1.35 3.1

45.3 0.6 0.0 1 10.6 8.3

38.1 3.1 2. I

11.3 1.O 29.9 21.6 -

5.1

3.1 6.2 97 seals

65.6 0.6 2.4 10.4 0.01 8.8 4.2

-

0.5 0.1 0.4 22.3

aAs a percentage of the total number of prey-containing stomachs for each area.

0.8 5.8 3.3

68.3 1.7 23.3 3.3

-

2.5 41.7 120 szals

0.1 2.4 1.5 78.4 0.2 0.3 0.1 0. I 10.1 21.8

-

22.2 -

-

11.1 5.6 iY seals

-

0.2 -

2.0 1.0 1.3

264

Table 1. Prevalencea and estimated wet weight (kg) of prey species accounting for 95% of total, reconstructed wet weight of prey-containing harp seals of known age recovered in inshore areas in 1982, 1986 and 199C1993

A

265 squid accounting for the remaining consumed biomass. Atlantic cod accounted for only 5.1% of the weight of prey eaten. Greenland halibut made up most of the prey weight in pups' stomachs from Labrador, with capelin and sand lance as the other main contributors (Table 1). Like their 1+ conspecifics, 0-group seals in NE Newfoundland relied predominantly on polar cod, and to a lesser extent on capelin. Conversely, capelin was the primary prey of pups on the south and west coasts. A notable shift in the annual diet was observed among samples collected in NE Newfoundland. Capelin accounted for over 80% of the wet weight in 1982 (Table 2). In 1986, polar cod replaced capelin in relative importance and has remained the predominant prey in recent years; capelin accounted for less than 10% of consumed biomass. The total biomass consumed in 1992 was distributed among relatively more prey species than in other years. Prevalence and biomass of Atlantic cod remained low throughout the study period, while species such as shrimp and redfish varied irregularly from year to year. Relative contributions, by weight, of prey consumed during summer and winter differed in NE Newfoundland samples (Table 3). Polar cod was the predominant component in both seasons, but was more important during the winter. In contrast, squid, Thysanoessa sp., capelin and herring were more important during the summer. These patterns held true for each of the 6 years.

Discussion

Our study suggests that there is substantial interannual, geographic and seasonal variation in the diet of harp seals in waters near Newfoundland and Labrador. Although suspected previously, this is the first time sufficient samples have been available to describe the degree of variation in an important feeding area for this population. Harp seals recovered in nearshore areas consumed a broad suite of prey, but as in prior studies of harp seals [6] and other pinnipeds [8-10], the bulk of biomass consumed was derived from relatively few species. Further, these dietary assemblages were similar across areas and years for nearshore (1+ (polar cod, Atlantic cod and capelin) and 0-group seals (capelin and polar cod)) and offshore areas (capelin, sand lance, flatfish, squid and Greenland halibut), although the relative importance of each species varied. The most comprehensive data come from NE Newfoundland. Since 1986, the predominant prey species of harp seals from this area was polar cod, whether expressed as prevalence, weight or energy. While this is similar to studies of harp seals in the NE Canadian Arctic [2], NW Greenland [ 11 ] and the southeast Canadian Arctic [4,12], it is contrary to previous studies in this same area which identified capelin as the most important prey [4,13]. However, this predominance of capelin was observed in stomachs from NE Newfoundland in 1982, and from all offshore areas. In addition, capelin was the dominant prey item, by prevalence and weight, for 1+ seals

266

Table 2. Prevalence and wet weight (kg) of prey accounting for at least 95% of the total weight in prey-containing I+ harp seal prey-containing stomachs recovered in nearshore waters of Northeast Newfoundland during 1982 (n = 218), 1986 (n = #7), 1990 (n = 153), 1991 (n =?GI), 1992 (n = 167) and 1993 (n = 88). Prey species

1982 Prev.

Polar cod Atlantic cod Atlantic Herring Capelin Cadus sp. Greenland Halibut Pandalus sp. Redfish Rock cod Sculpin sp. Teuthoidea Thysawessa sp. Total

1986 Weight %

Prev.

1990 Weight %

Rev.

1991 Weight %

Rev.

1992 Weight %

1993

Prev.

Weight %

Prev.

Weight %

25.8 2.3

2.8 0.4

84.1 9.3

85.6 0.5

65.4 17.0

66.3 3.4

70.6 11.2

64.6 2.6

52.6 14.3

52.6 2.5

57.3 10.1

67.9 1.8

88.9 0.3

81.1 0.01

7.0 25.0 4.2

2.4 2.9 0.2

13.1 34.6 6.5

8.3 8.0 0.7

25.2 26.6 5.6

12.6 2.6 1.2

14.3 28.6 5.3

12.8 7.8 0.1

19.1 22.5 1.1

8.8 3.5 1.4

1.8 0.9 0.5 2.3 26.3

0.9 0.4 0.04 1.4 3.8 494.9

2.3 18.7 0.5 3.7 5.8 1.9

1.2 1.3 0.01

0.6 12.0

0.3 1.3

1.4 12.6 -

0.3 2.6

2.2 18.8 0.7 -

-

-

0.002 0.9 0.1 592.1

-

3.9 3.3 3.9 0.6

-

8.0 0.04 0.1 0.01 160.5

-

16.8 5.6

--

8.9 0.5

151.9

1.5 3.0 27.1

3.7 5.6 0.003 0.02 0.3 6.9 66.7 --

aAs a percentage of the total number of prey-containing stomachs for each year. Values are calculated using all species recovered.

18.0 1.1

1.1 4.5 11.2 25.8

0.4 3.4

0.cQI

0.2 2.1 3.7 101.2

267 Table 3. Prevalencea and estimated total wet weight (kg) of prey accounting for 95% of the total weight in prey-containing 1+ harp seal stomachs recovered in nearshore waters of Northeast Newfoundland in summer (n = 326) and winter (n = 831)

Prey species

Polar cod Atlantic cod Atlantic herring Capelin Gadus sp. Greenland halibut Pandalus sp. Redfish Pleuronectidae Rock cod Teuthoidea (squid) Thysanoessa sp. Totalb

Summer

Winter

Prev.

Weight %

Prev.

Weight %

52.1 11.0 18.1 42.6 4.3 1.8 15.8 0.6 4.3 11.3 13.2

48.8 1.7 13.1 10.9 1.1 1.8 1.3 0.01 2.3 7.7 2.7 242.9

68.4 9.5 7.6 36.7 3.7 1.7 16.9 0.4 3.8 1.4 10.6 3.9

76.4 1.3 3.4 8.6 0.3 0.8 1.6 0.4 0.6 1.6 1.0 0.3 1158.2

aAs a percentage of the total number of prey-containing stomachs for each season. blncludes weights of all prey items. in W Newfoundland. This is similar to studies showing capelin to be the dominant prey item in stomachs from seals taken from the Gulf of St. Lawrence [4,14] and the St. Lawrence Estuary in winter [6]. Seasonal and annual changes in abundance for many fish species in nearshore Newfoundland waters are not well understood; thus we cannot determine if this change in diet reflects a change in prey distribution, prey abundance or both. Until recently, capelin abundance was assumed to be very low in the late 1970s and early 1980s, rose to a peak in 1985 then declined to low levels in 1991-1993. However, this picture is based on offshore acoustic surveys. In contrast, inshore indices indicate a stable population in recent years. Therefore it is not possible to compare the consumption pattem with abundance estimates, although it is worth noting that capelin consumption was low in 1986 when capelin were thought to be numerous. Lilly et al. [15] found an increase in abundance and biomass of polar cod off southern Labrador and eastern Newfoundland from the mid-1980s to the early 1990s. If there was an increased polar cod biomass in the same areas where we collected stomachs, our finding of increased reliance on polar cod may represent a shift in diet in response to this [15]. Atlantic cod was a relatively minor component of the diet of harp seals in nearshore areas in recent years. This dearth of cod is similar to the findings of other studies which also examined seals caught primarily in nearshore areas [4,6,12]. Pups appeared to have a relatively greater reliance on capelin (Labrador, W and S Newfoundland) or sand lance (S Newfoundland) than older seals. This is different from previous studies such as Sergeant [4] and Kapel [16] for young seals in W Greenland, and for a small sample of stomachs taken in NE Newfoundland by

268 Stewart and Lavigne [ 17]. Invertebrate prey were relatively unimportant by weight in pups' diets, but, as with all reconstructions, are probably underestimated as their remains are often too digested to identify. For small prey species, prevalence measures will normally exceed biomass estimates. Prevalence measures generally overestimated the relative contributions in terms of weight and energy for the primary prey species; prevalence and weight estimates were similar for only polar cod, Atlantic herring and rock cod. For example, the preponderance of redfish, by weight, in 1+ seals from S Newfoundland were recovered from a smaller proportion of stomachs. Thus prevalence should be augmented by other measures of diet composition, if possible. The dissimilarity between the two methods of expressing prey contribution makes it a difficult task to convert frequency measures directly to biomass values necessary for consumption estimates, although there may be a relationship between the two. While polar cod was the major prey consumed in both summer and winter, herring, capelin and squid gained importance for harp seals during the summer; perhaps as these prey species aggregated in nearshore waters, and were therefore available particularly for pups in S Newfoundland and 1+ seals in W Newfoundland. This may represent a shift by harp seals to locally abundant, schooling prey or prey which were more energy rich, as is the case for herring. Seasonal variations in diet have been documented in a number of other pinnipeds [8,18-22], and are to be anticipated given the temporal and geographic variation in the distributions of these prey.

Acknowledgements We wish to thank the sealers, fishermen and hunters who provided us with seals; W. Penney and D. Wakeham for collecting the samples; and D. McKinnon and D. Kavanagh for processing the samples.

References 1. Shelton PA, Cadigan NG, Stenson GB. Model estimates of harp seal population trajectories in the Northwest Atlantic. Department of Fisheries and Oceans, CAFSAC Res. Doc. 92/89, 1992. 2. Finley KJ, Bradstreet MSW, Miller GW. Summer feeding ecology of harp seals in relation to Arctic cod in the Canadian high Arctic. Polar Biol 1990; 10:609-618. 3. Wallace SD, Lavigne DM. A review of stomach contents of harp seals (Phoca groenlandica) from the Northwest Atlantic. International Marine Mammal Association, 92-03, 1992. 4. Sergeant DE. Feeding, growth, and productivity of northwest Atlantic harp seals (Pagophilus groenlandicus). J Fish Res Bd Can 1973;30:17-29. 5. Hyslop EJ. Stomach contents analysis - a review of methods and their application. J Fish Biol 1980;17:411--429. 6. Murie DJ, Lavigne DM. Food consumption of wintering harp seals, Phoca groenlandica, in the St. Lawrence estuary, Canada. Can J Zool 1991;69:1289-1296. 7. Murie DJ, Lavigne DM. A technique for the recovery of otoliths from stomach contents of piscivorous pinnipeds. J Wildlife Manage 1985 ;49:910-912.

269 8. Bowen WD, Lawson JW, Beck B. Seasonal and geographic variation in the species composition and size of prey consumed by grey seals (Halichoerus grypus) on the Scotian Shelf. Can J Fish Aquat Sci 1993;50:1768-1778. 9. Murie DJ, Lavigne DM. Growth and feeding habits of grey seals (Halichoerus grypus) in the northwestern Gulf of St. Lawrence, Canada. Can J Zool 1992;70:1604-1613. 10. Perez MA, Mooney EE. Increased food and energy consumption of lactating northern fur seals, Callorhinus ursinus. Fish Bull 1986;84:371-381. 11. Kapel FO, Geisler A. Progress report on research on harp and hooded seals in Greenland, 197879. Northwest Atlantic Fisheries Organization, 79/XI/10 NO21, 1979. 12. Sergeant DE. Harp seals, man and ice. Can Spec Publ Fish Aquat Sci 1991;114:153. 13. Fisher HD, Mackenzie BA. Food habits of seals in the Maritimes. Fish Res Brd Can Prog Rep 1955;61:5-9. 14. Beck GG, Hammill MO, Smith TG. Seasonal variation in the diet of harp seals (Phoca groenlandica) from the Gulf of St. Lawrence and western Hudson Strait. Can J Fish Aquat Sci 1993 ;50:1363-1371. 15. Lilly GR, Hop H, Stansbury DE, Bishop CA. Distribution and abundance of polar cod (Boreogadus saida) off southern Labrador and eastern Newfoundland. International Council for Exploration of the Sea, ICES C.M. 1994/O:6 Theme Session on Non-target Species, 1994. 16. Kapel FO. Some second-hand reports on the food of harp seals in west Greenland waters. ICES 1973;8. 17. Stewart REA, Lavigne DM. Neonatal growth of northwest Atlantic harp seals, Pagophilus groenlandicus. J Mammal 1980;61:670--680. 18. Pierce GJ, Boyle PR, Diack JSW, Clark I. Sandeels in the diets of seals: Application of novel and conventional methods of analysis to faeces from seals in the Moray Firth area of Scotland. J Mar Biol Assoc UK 1990;70:829-840. 19. Pierce GJ, Thompson PM, Miller A, Diack JSW, Miller D, Boyle PR. Seasonal variation in the diet of common seals (Phoca vitulina) in the Moray Firth area of Scotland. J Zool, London 1991 ;223:641-652. 20. Doidge DW, Croxall JP. Diet and energy budget of the Antarctic fur seal, Arctocephalus gazella, at South Georgia. in SCAR Symposium on Antarctic Biology Wilderness, South Africa, 1985. 21. H~irk/Snen TJ. Seasonal and regional variations in the feeding habits of the harbour seal, Phoca vitulina, in the Skagerrak and Kattegat. J Zool London 1987;213:535-543. 22. Benoit D, Bowen WD. Seasonal and geographic variation in the diet of grey seals in Eastern Canada. In: Bowen WD (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Ottawa, Canada: Department of Fisheries and Oceans, Communications Directorate, 1990;215-226.

This Page Intentionally Left Blank

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCe and 13. Ulltang, editors

271

Seasonal and regional variations in the diet of harbour seal in Norwegian waters M a r i a n n e Olsen and Arne Bj~rge Norwegian Institute for Nature Research, University of Oslo, Blindern, Oslo, Norway Abstract. Background: in order to describe the fish prey in the diet of the harbour seal Phoca vitulina, field studies were carried out in the Hvaler area in outer Oslofjord in 1990 and 1991, and in Froan in mid-Norway in 1991. Method: the studies were based on analysis of harbour seal faeces with identification of fish prey otoliths. The studies also included trawling in the Hvaler area to study the availability of prey. Results: analysis of faeces showed that the harbour seal feed mainly on schooling fish, predominantly benthic species. Most of the individual fish in the diet of the harbour seals were estimated not to exceed 30 cm in length. The most important groups of fish in the diet were the Gadidae, Clupeidae and Ammodytidae; Norway pout (Trisopterus esmarkii) was the single most important species both at Hvaler and at Froan. There was a substantial variation in the diet during the year, but to a lesser degree between the years. Regional variation in the diet was shown to occur between Hvaler and Froan. Conclusion: the harbour seals seem to have an opportunistic feeding strategy, but not feeding on all the species of fish found in the area. The variation both seasonally and regionally was probably due to variation in availability of species.

Key words: Phoca vitulina, foraging, feeding-strategy

Introduction The purpose of this study was to investigate the diet composition of the harbour seal, with possible variation in the diet between years, through the year and with possible regional variation in the diet. Investigations were carded out at Hvaler and at Froan in 1990 and 1991. At Hvaler the diet was compared to the composition of species found in trawl-catches. Seasonal and regional variations in the diet of harbour seals (Phoca vitulina Linnaeus, 1758) are described from within the range of the species [1-6]. Seasonal and regional variations are interpreted as an opportunistic strategy in harbour seals feeding on the prey species most readily available at the time [1,4,5,7-10]. Few studies, however, have compared the species composition in the diet with the relative abundance of the prey species at the foraging grounds in order to investigate prey preferences. Studies on the diet of seals have traditionally utilized analysis of stomach contents [1,7,3,11-14]. Outside of Norway, several studies on diet and feeding strategy of seals utilizing analysis of faeces have been carried out for the last 20 years [3,5,6,1520]. This study is the first in Norway using analysis of faeces, a method which repre-

Address for correspondence: A. Bjr

NINA, P.O. Box 1037, Blindern, N-0315 Oslo, Norway.

272 sents an alternative to killing or sampling incidentally dead seals. The method makes possible a relatively large sample size even from small populations.

Study areas The population of the north-east Atlantic harbour seal (P. v. vitulina) in Norway is estimated at more than 4,000 individuals and the seals occur in small groups along the entire coast, situated mainly on rocky substrates [21 ]. The area Hvaler is found in

0

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.

~.

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,

f 59N "1

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1

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0 t

al

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i ,'_sa'sa"

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.--trm'rrrr 10"48"Q

"

59"

50"

52"

Fig. 1. Map of the area at Hvaler where the harbour seals haul out and where faeces were collected in 1990 and 1991. Areas where trawling was carried out are shown.

273

70

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Fig. 2. Map of the area at Froan where the harbour seals haul out and where faeces were collected in 1991.

the outer Oslofjord at 59~ 10~ approximately 15 km offshore of the nearest larger island in the Hvaler archipelago (Fig. 1). It consists of a group of seven small islands and rocks, sited in shallow waters with a tidal amplitude less than 50 cm. The local population of harbour seals at Hvaler was estimated to a minimum of 300 animals early in the 1980s [22], but in 1988 approximately 75% of the seals died due to the PDV epizootic [23]. Froan is found approximately 40 km west of the mainland in south-TrCndelag county at 64~ 9~ and consists of several hundred small islands, skerries and tidal rocks (Fig. 2). The tidal amplitude at Froan is approximately 150 cm and some of the

274 Table 1. Number of faeces of harbour seal and their content of otoliths, found at Hvaler in 1990 and 1991 and at Froan in 1991

Apr

Hvaler 1990 No. of samples No. of otoliths

May

Jun/ Jul

Aug

20 186

Hvaler 1991 No. of samples No. of otoliths

40 620

Froan 1991 No. of samples No. of otoliths

9 93

Sep

Oct

Nov

53 1346

24 187

20 369

17 68

2 9

Total

73 1532

3 112

26 418

121 1507

20 369

skerries and rocks used for haul-out are submerged at high tide. The population of harbour seals at Froan was estimated to be 200 animals in 1986 [24] and in August 1989, 186 animals were observed [21 ].

Method

Collection of harbour seal faeces was carded out at haul-out sites at Hvaler during May and September of 1990, and each month, except June, from April to November in 1991. At Froan the sampling was carded out during June-July of 1991. When processing, the samples were washed through a set of three sieves, with mesh sizes 2.0, 1.0 and 0.25 mm, in order to separate hard and soft remains. Hard remains, mainly otoliths, were stored in 70% ethanol for later identification. The number of faecal samples and their contents of otoliths are shown in Table 1. The sagittal otoliths were identified to the lowest possible taxon, preferably species [25]. The otoliths of the family Ammodytidae and Gobiidae were identified to genus (Ammodytes sp.) and family (Gobiidae), respectively. Every otolith was registered as either a left or a right otolith. The species were classified as benthic or pelagic [26], as given in Table 3. The length of the fish was estimated on the basis of regressions for conversion from otolith-length to fish-length given by H~irktinen [25]. The number of fish were estimated after having subjectively paired the left and right otoliths on the basis of length. The relative importance of each species of fish in the diet was calculated by percentage frequency of occurrence (FO~) and as relative numerical frequency (Ni). F O i = 100

•

pi[Pt

Ni = 100 x ni/nt where Pi is the number of samples with species i, ni is the number of individuals of

275 Table 2. Trawling carried out at Hvaler in 1990 and 1991

May/Jun 1990

No. of hauls Average trawling time (min) Depth (m) 1991

No. of hauls Average trawling time (min) Depth (m)

Sep

Nov/Dec

9 90 50-150 16 60 60-120

7 195 60-120

species i, Pt is the number of samples in total and nt is the number of individuals in total. Variations in relative importance of the species between months, between years and regionally were tested statistically using a chi-square test for homogeneity in a contingency-table [27]. Spearman's rank test was used to test for correlation between ranking of species in the faeces and in the trawl [27]. Ranks were given on the basis of the number of individuals of each species. Trawling was carded out at Hvaler in September of 1990 and in May-June and November-December of 1991. Relative availabilities of species of fish were based on the number of individuals of each species in the trawl. Trawling areas are shown in Fig. 1. Number of hauls, trawling-time and depth are given in Table 2.

Results

The species compositions found in the faeces are given in Table 3 and Fig. 3. In total 18 species of fish were found in the faeces at Hvaler in 1990 and 1991, of which 10 belonged to the Gadidae. The diet of seals at Froan was also dominated by the Gadidae, represented by 3 out of 7 species. Norway pout (Trisopterus esmarkii) was the species most frequently found and also the species found in largest number both at Hvaler in 1990 and in 1991, and at Froan in 1991 (Fig. 3). Also in the trawl, Norway pout was the most numerous species, both in 1990 and in 1991 (Fig. 5). In the trawl, 26 species were found in 1990 and 30 in 1991, with 22 being found both years. At Hvaler pelagic and benthic species made up 39% and 61%, respectively, of the diet. There was no significant difference between the years (chi-square test, P < 0.05, df = 1). At Froan, pelagic and benthic species made up 29% and 71%, respectively, of the species found in the faeces. In 1991 approximately 99% of the fish of species found both at Hvaler and at Froan were estimated to be less than 30 cm in length, and 92% were less than 20 cm. Length was measured for 14 of the species found in the trawl, and the range of

9LE

Table 3. Species of fish found in faeces at Hvaler in 1990 and 1991, at Froan in 1991 and in trawl at Hvaler in 1990 and 1991

Family

Species

Squalidae Rajidae Clupeidae

Spurdog Skate Herring Sprat Greater argentine Lesser argentine Norway pout Poor cod Blue whiting Whiting Silvery pout Haddock Saithe Cod Hake Ling Fourbearded rockling Angler John Dory Noway haddock Redfish

Argentinidae Gadidae

Lophiidae Zeidae Scorpaenidae

blp Squalus acanthias Raja sp. Clupea harengus Sprartus sprattus Argentina silus Argentina sphyraena Trisopterus esmarkii Trisoprerus minutus Micromesistius poutassou Merlangius merlangus Gadiculus argenreus thori Melanogrammus aeglefinus Pollachius virens Gadus morhua Merluccius merluccius MoEva molva Rhinonemus cimbrius Laphius piscatorius Zeus faber Sebastes viviparus Sebasres marinus

Froan

Hvaler-90

Hvaler-9 1

Trawl-90

b b

x x

P P

b b b b

X

x x

x x x

x

x x

P

P

x

x x x

b b b

b

X

x

x

x x

x x

x

x x

x

x

x

x

x

x

x

x

x

P P b b b b b

Trawl-9 1

x

Triglidae Cottidae Carangidae Labridae Stichaeidae Anarhichadidae Amrnodytidae Gobiidae Callionymidae Bothidae Pleuronectidae

Soleidae

Grey gurnard Sculpin Scad Ballan wrasse Snake blenny Catfish Sandeel Goby Dragonet Brill Dab Flounder Plaice Lemon sole Witch Longh rough dab Halibut Sole

Eutrigla gurnardus Myoxocephalus scorpius Trachurus trachurus Labrus bergylta Lumpenus Iampraetaeformis Anarhichas lupus Ammodytes sp.

b b

a

Callionymus lyra Scophtalmus rhombus Limanda Iimanda Platichthys Jesus Pleuronectes platessa Microstomus kitt Glyptocephalus cynoglossus . Hippoglossoides plaressoides b Hippoglossus hippoglossus b Solea vulgaris b

LL~g

The species are classified as either benthic (b) or pelagic (p) following Pethon (1989). aFish belonging to the family Gobiidae were not classified to species. Possible species are Gobius niger, Pomatoschistus minutus, Porntoschistus pictus, Pomatoschistus microps and Gobiusculusflavescens.

278 Relative 6 0

numerical

frequency

....

50 40 % 30

17 Hvaler 90

20

Hvaler 91

'O

I~ Froan 91

0

~

e-

i..

t~

I,..

O t.--

t~

Percentage frequency of occurrence

4( r"l Hvaler 90

3C 2C

t~ Hvaler 91

1C

Im Froan 91

0 o

0

---

~

co

._

-~

~

~-,

~

.--_

X

o

tO C

-~

-~--

~_

C3~

Fig. 3. Relative importance of the most important species of fish in the diet of harbour seals at Hvaler in 1990 and 1991 and at Froan in 1991, given as percentage frequency of occurrence (FO) and relative numerical frequency (N).

length was 5-92 cm. Except for cod (Gadus morhua) and ling (Molva molva) all species found in faeces were less than 50 cm when caught in the trawl. There were large variations in the composition of species in the diet between May and September of 1990. The relative importances of the seven most important species (Norway pout, haddock Melanogrammus aeglefinus, whiting Merlangius merlangus, sandeel, poor cod Trisopterus minutus, cod and herring Clupea harengus)

279

oo%

,,,,,,,,,

90% 80%

i!!!

...........

i

lil] Other species

p

E~ Blue whiting

70%

Whiting

60%

Sandeel

50%

i~ Saithe

40%

Norway pout

30% 20%

1--] Sprat

10%

|

O% r~

~,

C3

co

o

I ! Herring > (3 z

Fig. 4. Variation in the relative importance of the species of fish found in the faeces of harbour seals during the period of sampling at Hvaler in 1991. were significantly different between the two months, when considering both frequency of occurrence and number of each species (chi-square test, P < 0.05, df = 6). Significant positive correlation was found between order of ranking of species in the trawl and in faeces in September 1990 (Spearman's rank test, P < 0.05). Ranking was made on the basis of number of individuals. The four species, Norway pout, blue whiting (Micromesistius poutassou), haddock and whiting, made up 96% of all the individuals in the trawl in 1990 and they represented 93% of the individuals found in faeces the same year (Fig. 5). In 1991 the composition of species varied between the months (Fig. 4). Herring was the only species occurring in all the months of sampling. The results indicate variation in the relative importance of the species, even though Norway pout and herring were dominating throughout the sampling period. Significant positive correlation was not found between order of ranking of species in the trawl and in faeces (Spearman's rank test, P < 0.05). However, Norway pout was the dominating species both in faeces and in the trawl. The five most numerous species found in the trawl (Norway pout, whiting, haddock, hake Merluccius merluccius and poor cod) made up 65% of all fish caught in total in 1990 and they represented 56% of the number of fish in the faeces (Fig. 5). In faeces there was a large representation of especially sandeel, but also herring and sprat (Sprattus sprattus). None of these species were found in the trawl. All the species found in faeces at Hvaler in 1990 were also found in 1991 (Table 3). Of the five most important species occurring in both 1990 and 1991 at Hvaler (Norway pout, saithe, sandeel, herring and cod), significant differences were found in the distribution from one year to another (chi-square test, P < 0.05, df = 4). The

280 Faeccs 1990

Trawl 1990 " 0

240

1,0~, 5,9 2,7 2,5 2,3 1,7

7,0

iiii!iiiiiiiiiiiiii!iiiiiii!iiiiiiiiiiiii!ii!iiiiiiii!i!iiiiii ! ii!iiii

[~

norway pout whiting

8

poor cod

D

haddock

k~ hake Facces 1991

Trawl 1991

8,4

8,0 2

8,0

1

~]

cod

~]

plaice

~1

other species

I~

'11,83

sandeel herring

,::iiiiiiiiiii!iiiiFi!iiiiiii!ii :i,o.o, i:::i:, 5,6 5,6

kg;'d ['~

sprat

[]

blue whiting

saithe

24,0 52,7

11,0

Fig. 5. Relative importance of species of fish found in the faeces of harbour seals and in the trawl at Hvaler in 1990 and in 1991.

same 7-8 species were dominating in the diet both years (Fig. 3). However, the ranking within these species varied between the years. In May 1990 there was a relative dominance of Gadidae, Clupeidae and Ammodytidae, and in September a relative decrease in the number of Clupeidae and Ammodytidae, relative to the Gadidae. In contrast to 1990 the occurrence of Clupeidae did not seem to decrease in the autumn of 1991. However, Ammodytidae seemed to follow the same pattern both years; decreasing in September of 1990 and not occurring after August of 1991. Significant difference was found when comparing the relative importance of species at Hvaler and at Froan in 1991 (chi-square test, P < 0.05, df = 4). Comparison was based on the number of individuals of the species Norway pout, saithe, dab (Limanda limanda), herring and poor cod, common in the seals' diet at both sites (Fig. 3). Differences were found both when comparing all the samples of 1991 and when comparing the samples of July 1991 only.

281 Discussion and Conclusions

Using analysis of faeces is based on the assumption that the samples found are representative for the population of seals studied. It should be noted that in months like September and October of 1991, when the number of samples were only two and three, respectively, the total number of species occurring was lower than in months with larger sample size. On the basis of the observed rate at which number of species increases when sample size increases, two and three samples may not give a representative description of the diet. Several studies have shown that small fragile otoliths, especially of clupeids, are more vulnerable to digestion than otoliths from other species, and may therefore be under-represented in the faeces of seals [4,28-31]. Even though an underrepresentation of clupeids cannot be neglected in this study, especially herring were still considered one of the most important species in the diet of harbour seals, indicating that the bias may not be great enough to influence relative importance of a species, not considering mass. Variation in the diet between months

Analyses of faeces from Hvaler in both 1990 and 1991 indicated significant seasonal changes in the diet of harbour seals. This is also shown in other studies [1,6]. H~irkiSnen [4] also found variation within the year at Koster, Sweden, which is an area close to and similar to Hvaler. The variations in relative importance of the prey species is probably due to the seals' feeding strategy. Abundance of prey may change through the year and cause variation in the diet. Olesiuk [ 10] found a change of dominating species of fish in the diet of harbour seals, correlated to the species spawning migration. H~irktinen [4] found that fluctuations in the diet often were correlated to migrations or changed behaviour during periods of spawning. Also some species were found to occur at high frequency when preferred prey were unavailable [36]. The trawl catches gave an indication that the seals feed among the most available species, but also that there are species that the seals avoid or that avoid being a prey. However, species not found in faeces certain periods of the year were without exception found in the trawl at the same time of the year. For example haddock were not found in faeces at Hvaler later than July in 1991, but did occur in the trawl in November-December. Trawling as a method for mapping the species distribution has its limitations, being a selective way of sampling. The depth and area chosen for trawling may eliminate some, especially pelagic, species. This is shown by the fact that neither herring, sprat nor sandeel were represented in the trawl at any time in this study. In August of 1991 there was a marked change in the diet of the seals at Hvaler. The seals behave differently due to age, sex and time of year. During August the harbour seals at Hvaler terminate their pupping and suckling time, which implies that the pups must start feeding, first together with their mother and then on their own. This could explain the change in the diet of the population seen in August of 1991.

282 The mother and pup may feed in other habitats than single grown up seals. The presence of hake, flounder, plaice, dab and goby may indicate feeding in more shallow waters than earlier in the year, reflecting the newly weaned pups contribution to the samples of faeces. In addition to feeding in more shallow water, the pups may start feeding on more easily accessible species and on a wider range of species than older seals, since they probably have not yet fully developed their feeding strategy. In general the harbour seals were found to feed on fish smaller than 30 cm. This may be energetically beneficial. There is, however, a chance that erosion of otoliths during passage through the stomach and intestines [28,32,35] and/or seals decapitating larger fish before swallowing them [34,35], may lead to underestimation of the size of the fish found in faeces.

Difference between years Variation in sample size and sampling period may be an explanation of the variation seen in both number of species and the species' relative importance in faeces when comparing 1990 and 1991. Differences in availability of species between the two years were difficult to investigate on the basis of the trawl catches because trawling was not carded out at the same time of the year. However, all the most important species in the diet were abundant in the trawl of both years, even though some of them were found in faeces only one of the years. Recruitment of fish larvae may show great variation between years. Due to this, certain year classes, and therefore possibly preferred sizes of a particular species, may be less available one year than another. At Koster, Harktinen [4] found little variation from one year to another, but reported a change from the period 1977-1979 to 1989 [37]. Also Rae [1] reported a change in the diet of harbour seals with time.

Regional variation in the diet Few species were found in the samples from Froan compared to the samples from Hvaler. This is probably due to a lower sample size, and may explain some of the variation in diet found between the two sites. Regional variation in the diet has been found in other studies of the diet of harbour seals [2], especially where the seals feed in different habitats [3,5]. The results of this study give no reason to state that Froan and Hvaler represent two different habitats, but the occurrence of greater argentine (Argentina silus) in the samples from Froan may indicate that the seals at Froan feed deeper than the seals at Hvaler. Greater argentine live mainly in deep waters at 200600 m [26]. Since trawling was not carded out at Froan it was not possible to investigate the abundance of species in the area, or use the abundance as an explanation for why some species widely distributed and of relative importance at Hvaler, such as cod, blue whiting and sandeel, were not present in the faeces at Froan. Another factor not studied but possible as an explanation for minor diet variations is competition with other piscivores. At Froan there is a colony of grey seals (Halichoerus grypus), not found at Hvaler. Their diet has not been investigated and possible competition between the two species is unknown.

283 Conclusion

This study indicates that the harbour seals mainly prey on benthic schooling species of fish. This is consistent with other studies [3,6,7,12,]. Few species per sample and clear dominance of one or two species throughout the year supports this view. Feeding on schooling fish, close to the bottom to limit the escape possibilities of the prey and in relatively shallow waters to minimise the energetic costs of diving, could be an energetically beneficial strategy of feeding. A relatively small range of species common through the year also supports the theory of harbour seals avoiding some species, as suggested by H~irktinen [4]. Being partly selective, however, does not exclude having an opportunistic strategy of feeding. The variation seen between months in the same year, from one year to another and between sites, does indicate an opportunistic strategy of feeding dependent on the abundance of prey. This was to a certain degree supported by the trawl catches, where the ranking of species in 1990 was correlated to the ranking in faeces the same year, and the most important species in faeces were the most important species in the trawl catches, especially in 1990 but also in 1991. In conclusion, the harbour seals seem to feed opportunistically on some families but not on all species of fish, and the relative importance of the preferred prey species seems to be determined by the abundance at the time, and possibly also to a certain degree by the state of the seals at the time.

Acknowledgements This study was supported by the Norwegian Research Council. Special thanks to John Prime and Randi Roen for helping out with the field work and to John Prime for support on identification of otoliths. Also thanks to Karin Andersen, University of Oslo, for sharing the trawl data.

References 1. Rae BB. Further observations on the food of seals. J Zool 1973;169:287-297. 2. Cubbage J, Calambokidis J, Carter S. Fish otoliths recovered from scat of harbour seals in the inland waters of Washington State. Third Biennal Conf of the Biol of Mar Mammal, 1979. 3. Brown RF, Mate BR. Abundance, movements and feeding habits of harbor seals, Phoca vitulina, at Netarts and Tillamook Bays, Oregon. Fish Bull 1983;81(2):291-301. 4. H~irk/Snen T. Seasonal and regional variations in the feeding habits of the harbour seal, Phoca vitulina, in the Skagerrak and the Kattegat. J Zool 1987;213:535-543. 5. Payne PM, Seizer LA. The distribution, abundance and selected prey of the harbour seal, Phoca vitulina concolor, in southern New England. Mar Mammal Sci 1989;5(2):173-192. 6. Pierce GJ, Boyle PR, Thompson PM. Diet selection by seals. In: Barnes M, Gibson RN (eds) Trophic Relationships in the Marine Environment. Proc 24th Eur Mar Biol Symp, 1990. 7. Pitcher KW. Food of the harbour seal, Phoca vitulina, in the Gulf of Alaska. Fish Bull 1980;78(2) :544-549.

284 8. Behrends G. Analysis of stomach and colon contents of 185 common seals from the Waddensea of Schleswig-Holstein. ICES CM 1982/N:11 Mar Mammal Comm. 9. Boulva J, McLaren IA. Biology of the harbor seal, Phoca vitulina, in Eastern Canada. Bull Fish Res Bd Can 1979;200. 10. Olesiuk PF, Bigg MA, Ellis GM, Crockford SJ, Wigen RJ. An assessment of the feeding habits of harbour seals (Phoca vitulina) in the Strait of Georgia, British Columbia, based on scat analysis. Can Tech Rep Fish Aq Sci 1990; 1730. 11. Frost KJ, Lowry LF. Sizes of walleye pollock, Theragra chalcogramma, consumed by marine mammals in the Bering sea. Fish Bull 1986;84:192-197. 12. Gortsev VN. Feeding of the harbour seal. Ekologiya 1971;2:62-70. 13. Havinga B. Der Seehund (Phoca vitulina L.) in den Hollaendischen Gewassern. Tijdschr Ned Diersk Vereen 1933;3:79-111. 14. Spalding DJ. Comparative feeding habits of the fur seal, sea lion and harbour seal on the British Columbia coast. Bull Fish Res Bd Can 1964;146. 15. Everitt RD, Gearin PJ, Skidmore JS, Delong RL. Prey items of harbor seals and California sea lions in Puget Sound, Washington. The Murrelet 1981 ;Winter:83-86. 16. Bailey KM, Ainley DG. The dynamics of california sea lion predation on pacific hake. Fish Res 1982;1:163-176. 17. Prime JH, Hammond PS. Quantitative assessment of grey seal diet from faecal analysis. In: Huntley AC, Costa DP, Worthy GAJ, Castellini MA (eds) Approaches to Marine Mammal Energetics 1987;165-181. 18. Prime JH, Hammond PS. The diet of grey seals from the south-western north sea assessed from analysis of hard parts found in faeces. J Appl Ecol 1990;27:435-447. 19. Hammond PS, Prime JH. The diet of British grey seals, Halicoerus grypus. In Bowen WD (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Can Bull Fish Aquat Sci 1990;222. 20. Daneri GA, Coria NR. The diet of Antarctic fur seal, Arctocephalus gazella, during the summerautumn period at Mossman Peninsula, Laurie Island (South Orkneys). Polar Biol 1992;11:565566. 21. BjCrge A. Status of the harbour seal Phoca vitulina L. in Norway. Biol. Conserv 1991;58:229238. 22. BjCrge A, Fagerheim KA, M~rkved B. Telling av steinkobbe ved Hvaler i 1983. Fisken Hav 1983;3:1-4. 23. Markussen NH. Apparent decline in the harbour seal Phoca vitulina population near Hvaler, Norway, following an epizootic. Ecography 1992;15:111-113. 24. BjCrge A. Status of marine mammal habitat protection in Norway. ICES CM 1986/N:4 Mar Mammal Comm. 25. H~irk6nenT. Guide to the otoliths of the bony fishes of the northeast Atlantic. Hellerup, Denmark: Danbiu Aps, 1986. 26. Pethon P. Aschehougs store fiskebok, Oslo: Aschehoug, 1989. 27. Zar JH. Biostatistical Analysis. Engelwood Cliffs, NJ: Prentice Hall, 1974. 28. DaSilva J, Neilson JD. Limitations of using otoliths recovered in scats to estimate prey consumption in seals. Can J Fish Aquat Sci 1985;42:1439-1442. 29. Murie DJ, Lavigne DM. Digestion and retention of Atlantic herring otoliths in the stomachs of grey seals. In: Beddington JR, Beverton RJH, Lavigne PM (eds) Marine Mammals and Fisheries. London: George Allen and Unwin, 1985;292-299. 30. Jobling M, Breiby A. The use and abuse of fish otoliths in studies of feeding habits of marine piscivores. Sarsia 1986;71:265-274. 31. Jobling M. Marine mammal faeces samples as indicators of prey importance - a source of error in bioenergetic studies. Sarsia 1987;72:255-260.

285 32. Dellinger T, Trillmich F. Estimating diet composition from scat analysis in otariid seals (Otariidae): is it reliable? Can J Zool 1988;66:1865-1870. 33. Harvey JT. Assessment of errors associated with harbour seals (Phoca vitulina) fecal sampling. J Zool 1989;219(1):101-112. 34. Boulva J. The biology of the harbour seal in eastern Canada. Ph.D. Thesis, Dalhousie University, Halifax, 1973;153p. 35. Pitcher KW. Stomach contents and faeces as indicators of harbour seal, Phoca vitulina, foods in the Gulf of Alaska. Fish Bull 1980;78(3):797-798. 36. H~irk/Snen T. Food-habitat relationship of harbour seals and black cormorants in Skagerrak and Kattegat. J Zool (London) 1988;214:673-681. 37. H~irk6nen T, Heide-JCrgensen MP. The harbour seal Phoca vitulina as a predator in the Skagerrak. Ophelia 1991 ;34(3):191-207.

This Page Intentionally Left Blank

9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. UUtang,editors

287

Feeding ecology of harp and hooded seals in the Davis StraitBaffin Bay region Finn O. Kapel Greenland Fisheries Research Institute, Copenhagen, Denmark A b s t r a c t . Results of stomach contents analyses of material collected in West Greenland waters in the

period 1986--1993 are reviewed, and compared with published data and circumstantial information from local hunters. The diet of harp seals feeding in this region is variable but consists mainly of pelagic crustaceans (euphausids and amphipods) and small fish species such as capelin, sandeel, polar cod and Arctic cod. Species of importance for commercial fisheries in Greenland, such as Northern prawn, Atlantic cod, and Greenland halibut play a minor role in the diet of harp seals in this area. Variation in the diet of hooded seals is less well documented, but in addition to the species also taken by harp seals, larger demersal fishes such as Greenland halibut, redfish, cod, and wolffish are apparently important prey items. Published data on harp seal feeding in the Canadian Arctic are briefly reviewed; they indicate a variation in food composition between seasons and areas similar to what was found in Greenland waters. Detailed information on hooded seal diet in the Canadian Arctic was not found. Information on population sizes, distribution and abundance of harp and hooded seals is reviewed. On this basis it is suggested that it is possible to develop density indices by area and season for harp and hooded seal in coastal waters of Greenland, and to use such indices combined with feeding data to estimate food consumption in this region. Similar indices may be developed for the Canadian Arctic, and for offshore areas, to arrive at total consumption by the seal stocks during their migrations and stay in the Davis Strait- Baffin Bay region. Key words: Phoca groenlandica, Cystophora cristata, Greenland, Arctic Canada, food composition, distribution, density indices

Introduction The purpose of this presentation is to review available information on the feeding habits of harp and hooded seals in the Northwest Atlantic during their migrations and stay in northern regions, i.e. outside the whelping and moulting seasons. Information on population sizes, distribution and abundance is reviewed in order to investigate ways of combining data on variation in diet and in abundance with estimates of total food consumption by the seals in these northern regions.

Food Composition Harp seal feeding in Greenland Information from hunters on the food of harp seals in Greenland was collected in the 1970s and presented in two meeting documents [ 1,2]. Address for correspondence: Greenland Fisheries Research Institute, Tagensvej 135 l, DK-2200 Copenhagen N, Denmark.

288

Table I .

Harp seal food composition (W%) in West Greenland

Area and month

N

MALL

MOAC

ARB0

FISH

PRAW

EUPH

PARA

CRUS

CEPH

Southwest (s) M Southwest (s) J Southwest (n) M Southwest (n) J Southwest (n) E Southwest (n) W Central W.(w) J Central W.(w) E Central W.(w) W Central W.(e) A Central W.(e) S Uummannaq A Upernavik (s) J Upernavik (s) S Upernavik (n) A Upv.(n) and Thu S Notes: Food items: MALL, capelin; MOAC, Gadus sp.; ARBO, AtctogaduslBoreogadus; FISH, other fish species; PRAW, prawns; EUPH, euphausids; PARA, Parathemisto; CRUS, other crustaceans; CEPH,cephalopods. Areas: (s) southern, (n) northern, (w) western, (e) eastern part. m =month: M, May; J, June(-July); A, August; S, September-October; E, autumn; W, winter.

289 Between 1985 and 1993, harp seal stomachs were collected, and analyses of the contents of 1,172 stomachs were reported [3-5]. Considerable geographical and seasonal variation was demonstrated, but some general patterns in feeding habits emerged. These are illustrated in Table 1 and Fig. 1, and can be summarized as follows. In the coastal waters of Southwest Greenland two prey items dominate the diet of harp seals: capelin (Mallotus villosus) and "krill" (euphausids). In the early summer, May, krill appears to be the predominant food; later, in June and in the autumn months, capelin constitutes the major part of the food. Codfish (in this region mostly Gadus morhua and G. ogac), other fish species, and prawns (particularly Pandalus borealis) are also taken but altogether they account for less than 20% of the diet. In the winter months, however, these "secondary prey species" appear to contribute to more than one-third of the food biomass, yet still surpassed by capelin and krill. In the western part of Central West Greenland, i.e. the region around the southem entrance to Disko Bay, the pattem resembles that found in Southwest Greenland: in June-July pelagic crustaceans dominate the diet: euphausids as well as amphipods, Parathemisto sp., followed by capelin, and prawns. In the autumn, however, capelin is the completely predominant prey item, whereas the winter diet is composed of a number of other fish species, pelagic crustaceans, and squid (mainly Gonatus fabri-

cii). Few samples were obtained from offshore waters in Southwest and Central West Greenland. They show variation between areas and month, with sandeel (Ammodytes sp.) as a very important food item, supplemented by Parathemisto, Pandalus, redfish (Sebastes sp.), and squid [5]. In the northeastern part of Disko Bay ("Vaigat"), polar cod (Boreogadus saida) was the predominant prey in August, followed by capelin and krill. In SeptemberNovember, capelin took over the "leading role" followed by polar cod, some other fish species and squid, but few crustaceans. In most of the samples from Northwest Greenland, polar cod, and to some extent Arctic cod (Arctogadus glacialis), was a significant or dominant part of the food of harp seals. In the Uummannaq district, however, krill was the predominant prey in August, and in the southern part of Upemavik district, capelin constituted more than half of the calculated biomass of the food in September.

Harp seal feeding in Arctic Canada Published information on the feeding of harp seals during their stay in Arctic Canada, i.e. away from the whelping and moulting regions, is relatively sparse. Foy et al. [6] found that immature and adult harp seal feeding in bays on the north coast of Labrador in late May-June were taking mainly capelin, whereas the diet of juveniles feeding near the offshore archipelago consisted mainly of euphausids. Immatures and adults feeding further offshore had a more varied diet including both fish, euphausids, and bottom-living decapods. In late autumn to early winter (November-January) harp seals feeding in the bays were feeding on a variety of

290

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, UMQA

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NUTS

Fig. 1. Food composition (weight%) of harp seals in Southwest (upper part) and Northwest Greenland (lower part). Food items: M A L L , capelin; M O A C , Atlantic cod or Greenland cod; ARBO, polar cod or Arctic cod; FISH, other fish species; P R A W , prawns; EUPH, euphausids or amphipods; CEPH, squid. Area: SW, Southwest Greenland; CW, Central West Greenland; s, n, w, e, southern, northern, western and eastern part, respectively; UMQ, U u m m a n n a q ; UPR, Upernavik (southern part); NUS, northern part of Upernavik; NUT, same (NUS) and Thule. Month: M, May; J, June(-July); A, August; S, September(-October); E, autumn; W, winter.

291 small Gadidae, polar cod, and capelin, whereas invertebrates were of secondary importance. Smith et al. [7] working in southeastern Baffin Island (63-64~ in JulySeptember found that the diet of four young-of-the-year harp seals consisted of 64% pelagic crustaceans (mysids and the amphipod Parathemisto), and 36% fish (mainly polar cod). One adult female harp seal was feeding on the pelagic shrimp Sergestes

arcticus. In the western Hudson Strait, Bech et al. [8] found that the stomachs of 14 harp seals caught in September-October near the south coast were dominated by capelin, with polar cod, sculpin, Greenland cod, and flatfish as secondary elements. One seal feeding offshore, near Salisbury Island, had taken Parathemisto and polar cod in almost equal amounts Sergeant [9] presented stomach contents data on 16 harp seals caught in the Canadian Arctic (at four different localities). Polar cod (Boreogadus saida) occurred in 6 of these, mysids in 5, Parathemisto in 4, and euphausids in 3 stomachs. In the High Arctic, Finley et al. [10] studied the feeding ecology of harp seals at Pond Inlet (73~ and Grise Fiord (76~ between mid-August and early October. Detailed analysis of 63 stomachs revealed that polar cod (Boreogadus saida) occurred in all of them, and accounted for 84% of all food items found in the stomachs (% frequency). The related species Arctic cod (Arctogadus glacialis) was found in 63% of the stomachs, but the number was much lower (5% frequency). In terms of biomass, however, polar cod and Arctic cod contributed 66% and 33% of the weight, respectively (as the individuals of the latter species were considerably larger). Other fish species or invertebrates were also found, but accounted for only a minor part of the food (altogether 16% frequency, and about 1% by weight).

Hooded seal feeding in Greenland In Greenland much less information is available on the feeding of the hooded seal than for the harp seal. Accounts in the literature and information gathered from hunters were reviewed in a previous paper by the present author [ 11 ]. When sampling harp seal stomachs, a few hooded seal stomachs were also obtained, and preliminary results of examination of the contents are presented here (Table 2, Fig. 2). From spring hunting in South Greenland, hunters provided information on the contents of 1,236 hooded seals stomachs, 386 (31.2%) of which were empty. Of the 850 stomachs with contents, 828 (97.4%) contained fish, whereas crustaceans and squid were only reported in 16 and 6 stomachs, less than 2 and 1%, respectively. For many stomachs, the contents were only given as "fish", but the fish species reported most frequently were redfish (Sebastes sp.), cod or Greenland cod (Gadus morhua, G. ogac), and capelin (Mallotus villosus). Six stomachs of hooded seals caught in Southwest Greenland have been examined in the laboratory. One was empty, and in the remaining five capelin was the predominant food. Four of the seals were taken in the spring, one in June, and one in

292

Table 2. Hooded seal food com~ositionin Greenland: information from hunters (8occurrence)

Species

South Greenland No.

-

Northwest Greenland % Food

NO.

% A11

1.6 0.2

4

0.2

55

1.3

1.9 0.7

% All

Southeast Greenland % Food

No.

59

0.6 9.0 9.6

0.9 11.9 12.8

-

1 46 1 153 614

0.2 75.1 24.9 100

0.2 100

30

% All

% Food

-

Capelin Codfishes Grl. halibut Redfish Wolffish Other fish Unspecified fish Fish total Decapods Other crustaceans Crustaceans totaI Cephalopods Stomachs with food Empty stomachs Total

14 2 16

6 850 386 1236

1.1

0.5 68.8 31.2 100

100

aThe percentages of the various fish species are adjusted for "unspecified fish".

206 236

12.7 87.3 100

-

100

Table 2 (continued).Hooded seal food composition in Greenland: ureliminary analyses of stomach contents (~01%)

Southwest Greenland (n = 6)

Capelin Polar/Arctic cod Grl. halibut Redfish Wolffish Other fish Pandalus Other crustaceans Cephalopods Unidentifiable Stomachs with food Empty stomachs

% All

% Food

82.7 0.2 0.3 0.2 -

99.2

-

83.3 16.7

-

0.2 0.4 -

0.2

-

100

-

CW Grl. SAQ(1)

Northwest Greenland UMQ(3)

UPV(5) % All

57 23 18 1 1

-

100

64.3 22.7 11.3 0.7 -

1.O

Southeast Greenland ( n = 29)

24.1 52.0 3.4

-

-

0.4

-

-

100 -

80.0 20.0

%Food 30.2 65.1 -

4.3 0.5 100

%All

-

1.9 2.4 1.7 15.5 2.1 42.0 3.5 69.0 31.0

% Food

2.8 3.5 2.5 22.4 3.0 60.9 5.0 100

293

294

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Fig. 2. Food composition of hooded seals in Greenland: All stomachs (upper part) and stomachs with contents (lower part), based on hunters' reports (% occurrence, left side columns) and stomach analyses (volume %, right side columns). Food: EMPT, empty; CEPH, squid; CRUS, crustaceans; UNID, unidentified items; UNSP, unspecified fish; FISP, specified fish; MALL, capelin; GADO, codfish; REIN, Greenland halibut; SEBA, redfish; FISH, other fish species; INVE, invertebrates. Area: SEGR, Southeast Greenland; SGRL, South Greenland; SWGR, Southwest Greenland; CWGR, Central West Greenland; NWGR, Northwest Greenland; UMQ, Uummannaq; UPV, Upernavik.

295 November; they were all very young animals (0-1 year old), in contrast to the above mentioned hunters' samples that were dominated by seals of age 2 or older [11]. Hunters' information on stomach contents is available for 236 hooded seals caught in Southeast Greenland (Ammassalik district). Of 215 caught in late July to early August, 201 (93.5%) were empty. This is not surprising because the seals were in the late stage of moulting, during which hooded seals are known to spend little time on feeding. Of the 21 reports from this district later in the year (autumn and winter), only 5 (24%) stomachs were empty. The prey species reported most frequently by the Ammassalik hunters was redfish (in 83% of the stomachs with contents), followed by Greenland halibut (7%); crustaceans or squid were not reported by the hunters. Twenty-nine hooded seal stomachs were collected in Southeast Greenland in early September 1991. Laboratory examination revealed that 9 (31%) were empty, and that the rest contained only small amounts of food remains. The predominant prey item was squid, particularly identified by the eyes found in 80% of these stomachs, and constituting about 61% (estimated volume) of the stomach contents. Prawns (Pandalus sp.) dominated in five stomachs (25% occurrence, 22% volume). The contents of one stomach was dominated by redfish, and fish otoliths (most frequently polar cod, Boreogadus saida) were found in five other stomachs. Most of the seals in this sample were young-of-the-year. From Northwest Greenland, hunters' information is available for 614 hooded seals, of which 153 (25%) had empty stomachs. The highest percent of empty stomachs (42%) was found in July, which probably relates to recent moulting condition, the lowest in late autumn (18%, [11]). In this region, Greenland halibut (Reinhardtius hippoglossoides) was the prey reported most frequently (in 61% of the stomachs with contents), followed by wolffish (Anarhichas sp., 11%), and pelagic crustaceans (euphausids and amphipods, 12%). Laboratory analyses of stomach contents of hooded seals caught in the northern part of West Greenland are few. One stomach from Vaigat (Central West Greenland) contained 57% capelin, 23% polar cod, and 18% other fish remains; the contents of eight stomachs from Uummannaq and Upemavik (one empty) were dominated by Greenland halibut (ca. 65%), followed by redfish (Uummannaq, 23%) or polar cod (Upernavik, 30%). Little information is available on the feeding of hooded seals in offshore areas. A seal taken as by-catch during longline fishing off Central West Greenland (approx. 69~ 59~ at depths exceeding 650 m had two Greenland halibut in the stomach [12].

Hooded seal feeding in Arctic Canada There is no published information on studies of the composition of the diet of hooded seals during their stay in Arctic Canada.

296

Population Size, Distribution and Abundance Population size of Northwest Atlantic harp seals Recent estimates of pup production of the Northwest Atlantic stock of harp seals are about 390,000 for 1983 (aerial surveys, Front only) [13] or 534,000 _+33,000 (markrecapture, Gulf and Front) [ 14], and for 1990, 577,900 _.+38,800 (aerial surveys, Gulf and Front) [15]. Based on these data, a figure of 550,000 for pup production in the late 1980s is suggested, corresponding to a total population size of about 2,750,000 harp seals in the Northwest Atlantic.

Population size of Northwest Atlantic hooded seals Recent estimates of pup production of the Northwest Atlantic hooded seals are: for 1984, 62,400 (43,700-89,400) at the Front and 18,600 (14,000-23,000) in the Davis Strait (aerial surveys) [16], and for 1991, 82,200 (69,600-94,800) at Newfoundland (aerial survey) [ 17]. Based on these data, a figure of 85,000 for pup production in the late 1980s is suggested, corresponding to a total population size of about 340,000 hooded seals in the Northwest Atlantic.

Migration and distribution of harp seal in the Davis Strait- Baffin Bay region Detailed knowledge of the migration and distribution of Northwest Atlantic harp seals comes from observations, catch data, and recoveries of tagged animals. All this information has been summarized by Sergeant [ 18,19]. Northwest Atlantic harp seals whelp between late February and mid-March around Newfoundland, a little earlier in the Gulf of St. Lawrence than at the "Front" (off North Newfoundland and southeastern Labrador). The seals undergo the annual moulting in the same general area between late March and late April. Soon after most harp seals leave the moulting region, heading north to spend the summer and autumn months in the Davis Strait- Baffin Bay region. Some seals pass coastal Labrador in May-June, and are summering (July-August) in small numbers off northern Labrador, but most specimens migrate further north. The bulk of the migration is believed to follow the edge of the pack ice to reach Southwest Greenland waters in mid-May. Evidence from Greenland catch statistics, as reviewed by Rosendahl [20] and Kapel [21], and tag recoveries from Greenland (Fig. 3) can be used to describe the migration and distribution in nearshore waters of the Greenland. Harp seals occur in coastal Southwest Greenland in fairly high numbers in late May, but reach peak abundance in this area in early June. During this month harp seals also become abundant further north in the Disko Bay region, Central West Greenland, and some animals may penetrate through openings in the ice and leads to Northwest Greenland. In July the number of harp seals decreases in Southwest Greenland; some may seek offshore areas of Southwest and Central West Greenland,

297

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I year old; I M M A ,

and region. A g e

immatures (2-4 years); A D U L ,

groups: J U V ,

adults (5 + years).

298 but most of them apparently go to coastal Central West and Northwest Greenland, where harp seals are abundant all through the summer months of July, August and September. It is also possible that some of the seals that have spent the early summer in Greenland cross Baffin Bay and migrate into the High Arctic Canadian Archipelago, but this has so far not been documented. Tag recoveries have demonstrated that some harp seals of the Northwest Atlantic stock pass Kap Farvel to migrate to East Greenland, where harp seals occur from July until November (Fig. 3). Recapture of animals tagged at Jan Mayen has, however, shown that part of the harp seals occurring in East Greenland come from that population. In October or November, when the new ice begins to form, most harp seals leave Northwest Greenland, but catch statistics as well as tag recaptures show that quite a few stay behind for a month or two, and wintering harp seals are often seen in open water areas of Central West and Southwest Greenland. In Arctic Canada the first harp seals arrive at Pond Inlet in mid-June, and occur in large numbers in early July [10]. Aerial surveys have indicated that the majority of harp seals in the eastern Canadian Arctic are found in coastal waters. Sea ice begins to form in late September, and by early October harp seals leave the region, starting to migrate south. On their southward migration large numbers of harp seals pass the Labrador coast from late October to early December, and the major part of the population is believed to winter in the waters around Newfoundland, until they again aggregate on the ice to whelp in late winter.

Migration and distribution of Northwest Atlantic hooded seals Northwest Atlantic hooded seals whelp in late March on the pack ice in two areas: a major concentration around Newfoundland and a small one in the Davis Strait [22,23]. Immediately after the extremely short lactation period [24] both young and adults go to sea and begin the migration. Greenland hunting statistics indicate that hooded seals arrive in coastal waters of Southwest Greenland in April, and that peak abundance in this area occurs in May to mid-June [ 11,20,21 ]. In the hooded seal, moulting takes place between late June and late July, and the best known whelping concentrations are found in the Denmark Strait. In Ammassalik district, just south of the Denmark Strait, the peak hunting period for hooded seal is August, and from this district come most of the recoveries of hooded seals tagged at the Newfoundland and Davis Strait whelping patches (Fig. 4) [24]. The linkage between the Northwest Atlantic whelping stocks, Southeast Greenland and the Denmark Strait moulters is thus clear. The fact that moulting concentrations have been found north of Jan Mayen, and that only one hooded seal tagged in that area has been recaptured in Greenland (Ammassalik), put doubt on the previously accepted theory, that hooded seals from the Jan Mayen stock were as a rule also moulting in the Denmark Strait [22,25,26].

299

5 I recoveries --- ~

9 the

, V m , ,

4 O* v , I. (~l l ~ l l l W ~ | l

Gulf,

from

Newfoundl.

• Front, Newfoundl~ Davis Strait Denmark Strait Jan Mayen , so

o

too

a~o

~o

,.ookm

~#I *

Fig. 4. Distribution of hooded seal recoveries in Greenland. The origin of tags from various tagging areas is indicated by different symbols.

300 Hooded seals are also quite common in the Ammassalik district later in the year (September to January), but some of the seals continue the migration southward to South Greenland, and probably further up along the west coast. In Central West Greenland hooded seals occur in April-May, but are rare from late June-December. In Northwest Greenland some animals are seen in May, but the main occurrence is in August-September. This information, and the catching of late moulters in early August, indicates that some hooded seals may conduct their moulting on the Baffin Bay drift ice. Hunting statistics demonstrate that hooded seals can be found all through the winter in the Disko Bay region, Central West Greenland, and casual information from hunters indicates that this is nowadays also the case in the coastal waters of Southwest Greenland. Most of the seals, however, are thought to leave Greenland waters in late autumn, like the harp seals, to spend the winter in the waters around Newfoundland. Detailed information on the occurrence and abundance of hooded seals in Arctic Canada is apparently not available. A general feature of the hooded seal is that it seems to be feeding at greater depths than the harp seal, and it is likely that, in general, they spend more time in offshore waters. There is, however, not yet sufficient published evidence to substantiate that theory. Distribution or density indices for harp and hooded seals in coastal Greenland

The review of Greenland hunting statistics given by Rosendahl [20] included calculation of the catch per half-month per 100 hunters for individual seal species. These values, presented district by district, can be taken as indices of availability for each species at a given time of the year within the area in question, provided that the basic data are reliable. For the period used by Rosendahl (the early 1950s), seal hunting statistics in Greenland are believed to be rather good [21], which unfortunately is not case with more recent data [27]. However, the more recent (1950-1993) data on harp seal tag recoveries in Greenland (Fig. 3) give a similar general picture of migration and distribution as demonstrated by Rosendahl. Differences in details may partly be explained by the fact that the recovery data are not weighted by hunting intensity, or by possible variation in reporting efficiency between various districts. It is, therefore, considered reasonable to use Rosendahl's availability indices to develop density indices for harp seals in coastal Greenland. This was done by pooling district data into values for the regions used for describing variations in diet composition, and adjusting these values according to the relative size of the coastal zone of the regions (defined as the area from the coastline to approximately 20 nautical miles offshore). The result is illustrated in Fig. 5. It appears that density indices for harp seals in coastal West Greenland are low for May, and reach a maximum in June. This reflects our knowledge that the migrants from Newfoundland have not all left southeastern Canadian waters in May, but most

301

Is . . . . . . . . . .

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F i g . 5. D i s t r i b u t i o n i n d i c e s f o r h a r p s e a l s i n c o a s t a l W e s t G r e e n l a n d .

302

~ot

,~ ~ ~,~,,~,,,,~

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'

70605040302010-

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S

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SC0~_t

IV V VI VII VIII IX X XI XII I II lU ,

,

,

,

,

,

[

Fig. 6. Distribution indices for hooded seals in coastal Greenland.

303 do so in June. In July and August, the indices are still high for coastal Greenland as a whole (but lower than for June) and highest in the northern regions, reflecting that a major part of the migrants have left Southwest Greenland continuing to offshore areas, or higher latitudes in Greenland and possibly Arctic Canada. From September onwards, density indices for coastal Greenland are generally declining, reflecting the gradual onset of the southward migration towards Newfoundland waters, with only a minor part of the population, mostly young individuals (?) (cf. the recovery data in Fig. 3), staying behind to winter in Arctic waters. Development of similar density indices for Arctic Canada, or offshore waters, has not yet been attempted, but might be done, using the general knowledge on occurrence, the indication that abundance in the vast offshore region appears to be low, and by distributing the estimated total number of about 2.75 million harp seals among the regions on a month by month basis. A similar procedure to the one described above was used for developing density indices for hooded seals in coastal Greenland, and the result is shown in Fig. 6. Taking the biology and the migration pattern of the hooded seal into account, information from East Greenland is included in this case, as this is highly relevant for a description of the distribution and abundance of the Northwest Atlantic stocks of hooded seals. For coastal Greenland as a whole, abundance of hooded seals is high in May-June (particularly in Southwest Greenland) and in August-September (Southeast and Northwest Greenland), but considerably lower in July (the moulting period), and from October onwards. Because data on hooded seal abundance in Arctic Canada are few, and a greater affiliation to offshore waters is only postulated not documented, it will be more difficult than in the case of harp seals, and even more speculative, to allocate the estimated total number of about 0.34 million hooded seals among the various regions on a month by month basis.

References 1. Kapel FO. Some second-hand reports on the food of harp seals in West Greenland waters. ICES CM 1973/N:8;7 pp (Mimeo). 2. Kapel FO, Geisler A. Progress report on research on harp and hooded seals in Greenland 19781979. NAFO/SCR Doc. 1979/XI/10 (Mimeo). 3. Kapel FO, Angantyr LA. Feeding patterns of harp seals (Phoca groenlandica) in coastal waters of West Greenland, with a note on offshore feeding. ICES CM 1989/N:6;22 pp (Mimeo). 4. Angantyr LA, Kapel FO. Harp seal feeding habits in Greenland - our present knowledge, April 1990. Techn Report from Greenland Fisheries Research Institute, Copenhagen, November 1990 (rev Feb 1991), 73 pp. 5. Kapel FO. Variation in the feeding of harp seals (Phoca groenlandica) in Southwest Greenland waters. ICES CM 1994/N:4, 21 pp (Mimeo). 6. Foy MG, DeGraaf DA, Buchannon RA. Harp seal feeding along the Labrador coast, 1979-1981. LGL Ltd., St. John's, Newfoundland, Rep to Petro-Canada Exploration Incorporated, Calgary, Alt 1981, 37 pp.

304 7. Smith TG, Hammill MH, Doidge DW, Cartier T, Sleno GA. Marine mammal studies in southeastern Baffin Island. Can MS Rep Fish Aquat Sci 1979;1552:70 pp. 8. Beck GG, Hammill MO, Smith TG. Seasonal variation in the diet of harp seals (Phoca groenlandica) from the Gulf of St Lawrence and western Hudson Strait. J Fish Aquat Sci 1993;50:13631371. 9. Sergeant DE. Feeding, growth and productivity of Northwest Atlantic harp seals (Pagophi lus groenlandicus). J Fish Res Bd Can 1973;30:17-29. 10. Finley KJ, Bradstreet MSW, Miller GW. Summer feeding ecology of harp seals (Phoca groenlandica) in relation to Arctic cod (Boreogadus saida) in the Canadian high Arctic. Polar Biol 1990; 10:609-618. 11. Kapel FO. Studies on the hooded seal, Cystophora cristata, in Greenland, 1970-80. NAFO Sci Coun Studies 1982;3:67-75. 12. Pedersen SA. Incidental catch of hooded seals during experimental longline fishery in West Greenland, August 1993. Working Paper SEA-50 to the Joint ICES/NAFO Working Group on Harp and Hooded Seals, September, 1993, 1 p (Mimeo). 13. Myers RA, Bowen WD. Estimating bias in aerial surveys for harp seal pup production. J Wildlife Manage 1989;53:361-372. 14. Roff DA, Bowen WD. Further analysis of population trends in the northwest Atlantic harp seal (Phoca groenlandica) from 1967 to 1985. Can J Fish Aquat Sci 1986;43:553-564. 15. Stenson GB, Myers RA, Hammill MO, Ni I-H, Warren WG, Kingsley MCS. Pup production of harp seals, Phoca groenlandica, in the Northwest Atlantic. Can J Fish Aquat Sci 1993;50:24292439. 16. Bowen WD, Myers RA, Hay K. Abundance estimation of a dispersed, dynamic population: hooded seals (Cystophora cristata) in the Northwest Atlantic. Can J Fish Aquat Sci 1987;44:282295. 17. Stenson GB, Myers RA, Ni I-H, Warren WG. Pup production and population growth of hooded seals (Cystophora cristata) near Newfoundland, Canada. ICES CM 1994/N:8;19 pp. 18. Sergeant DE. Migrations of harp seals, Pagophilus groenlandicus (Erxleben), in the Northwest Atlantic. J Fish Res Bd Can 1965;22:433--464. 19. Sergeant DE. Harp seals, man and ice. Can Spec PUbl Fish Aquat Sci 1991;114:153 pp. 20. Rosendahl P. GrCnlandsk jagt- og fangststatistik. Geogr Tidsskr 1961 ;60:16-38. 21. Kapel FO. Recent research on seals and seal hunting in Greenland. Rapp P-V R6un Cons Int Explor Mer 1975;169:462-478. 22. Sergeant DE. History and present status of populations of harp and hooded seals. Biol Conserv 1976;10:95-118. 23. Sergeant DE. A rediscovered whelping population of hooded seals Cystophora cristata Erxleben and their possible relation to other populations. Polarforschung 1974;44:1-7. 24. Kapel FO. A note on recaptures of tagged and branded hooded seals in Greenland, 1956-1993. Working Paper WP SEA-41 to the Joint ICES/NAFO Working Group on Harp and Hooded Seals, September 1993, 4 pp (Mimeo). 25. Rasmussen B. Exploitation and protection of the East Greenland seal herds. Norsk Hvalfangst-Tid 1957;2:45-59. 26. Rasmussen B. Om klappmyssbestanden i det nordlige Atlanterhav. Fisk Havet 1960;1:1-23. 27. Kapel FO. Trends in catches of harp and hooded seals in Greenland, 1939-83. NAFO Sci Coun Stud 1986; 10:57-65.

Energetics and other physiological aspects

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. Ulltang,editors

307

Food requirements of Northeast Atlantic minke whales E. S. NordCy, L. P. F o l k o w , P.-E. M~rtensson and A.S. B lix Department of Arctic Biology and Institute of Medical Biology, University of Tromsr Breivika, Tromsr Norway Abstract. The Northeast Atlantic stock of minke whales (Balaenoptera acutorostrata) numbers ~ 87,000 animals. In this report we estimate the food requirements of this stock from the energy requirements of growing and adult animals. The daily energy expenditure of free-swimming whales has been estimated by Blix and Folkow [ 1] to be 80 kJ/kg per day. This value includes the heat increment of fat deposition, growth and gestation. The additional energy costs of fattening and growth, determined from carcass analysis of whales caught in spring and autumn, was 17 and 8% of their total daily energy requirements, respectively. Based on an age-length relationship it was assumed that 73% of the population was growing, and 100% of all females older than 11 years were pregnant. By use of current estimates of the composition of the diet of Northeast Atlantic minke whales along with information on the seasonal changes in energy density of prey, it was calculated that this population consumes of the order of 1.4 million tonnes of various prey, during an assumed average stay of 6 months in the Northeast Atlantic. The deposited energy (blubber, muscle and visceral fat) does not cover more than about 60 days of the assumed energy requirements, when in other waters. Key words: Balaenoptera acutorostrata, gross energy intake, Barents Sea

Introduction The total population size of the Northeast Atlantic stock of minke whales, which seasonally inhabit the Norwegian and Barents Seas, is of the order of 87,000 individuals [2]. Because of its abundance and relatively large body size, the minke whale in these waters has been the subject of commercial whaling for several decades. For similar reasons and the fact that a major part of their diet apparently consists of commercially exploited species of fish [3,4], the minke whale is likely to hold a very important position within the Northeast Atlantic ecosystem and might also be a significant competitor to commercial fisheries in the area. The purpose of this study is, thus, to estimate the food requirements of the Northeast Atlantic minke whale stock, in an effort to determine more precisely its position within its ecosystem, by using presently available information from the Norwegian scientific whaling operations in the period 1988-1994.

Address for correspondence: E.S. Nord0y, Department of Arctic Biology, Breivika, 9037 Troms0, Norway.

308 Materials and Methods

The method used to calculate the food requirements of the minke whales in this report is in principle the same as that outlined by Lavigne et al. [5].

Duration of stay in the Northeast Atlantic waters All calculations of food requirements were limited to the period between 1 April and 1 October and assume that minke whales stay in the Northeast Atlantic waters for an average of 6 months per year, before migrating southwards [6].

Field metabolic rate (FMR) The average FMR used in these calculations was obtained from Blix and Folkow [ 1]. The value used, 80 kJ/kg per day, is based on indirect determination of oxygen consumption from studies of the respiratory rates of a number of similar sized (-7.5 m) free-swimming minke whales performing different activities, such as feeding, cruising and "sleeping". Additional data on lung volumes, oxygen extraction and tidal volumes were also used in these calculations. The metabolic rate calculated by this method includes the energy expenditure due to heat increment of growth, gestation and fat deposition. Thus, when calculating the energy costs of growth, etc., the heat increment factor was not added to the energy budget. In order to convert average body length to average body mass for growing and physically mature whales, the following equation was used: BM = 8.148 x B L 3.163, where BM is body mass in kg and BL is body length in metres [7].

Energy deposited during growth and seasonal fattening The total muscle, intra-abdominal fat and blubber masses of minke whales which were caught during spring and autumn were weighed as part of the Norwegian scientific whaling programme (1992-1994), in order to calculate seasonal growth and fat deposition. Tissue mass deposition was converted to energy deposition by measuring the energy density of samples of muscle, intra-abdominal fat and blubber of 5 whales caught in the spring and 5 caught in the autumn, by bomb calorimetry (Frantz Morat KG, Germany).

Energy deposited in foetus A number of foetuses with a wide range of body mass and length were collected during the Norwegian scientific whaling programme (1992-1994). A total of 15 foetuses were ground, their dry masses determined and their energy density measured by use of bomb calorimetry. A time versus foetus mass relationship was established in order to calculate the average mass of the foetuses at the assumed average time of departure of the females from the Northeast Atlantic waters (1

309 October). The energy content of the average foetus was determined from a relationship between their energy content and mass.

Sex and age composition, growth rate and population size Of the 225 minke whales caught during the Norwegian scientific whaling programme (1992-1994) 45.8% were males and 54.2 % were females. Of the 92 whales caught in 1992, 87 were age-determined by reading growth zones in bullae [8]. The results suggest that both sexes are physically mature at an average length of 8.0 m and at the age of 11 years, and that only 28% of the population is physically mature. Based on a female length-pregnancy rate relationship, it was assumed that close to 100% of the females older than 11 years are pregnant, and 30% of the growing females are pregnant. The total population size of the Northeast Atlantic stock of minke whales was assumed to be 86,700 (61,000-117,000, 95% CI) animals [2,9].

Metabolizable energy (ME) It was assumed that protein constitutes 13-18% of wet mass of the average minke whale diet. When this diet is metabolized, an average of 8% of the digestible energy (energy absorbed) is likely to be lost as urinary end products from protein catabolism [5].

Digestible energy (DE) Not all of the ingested food is absorbed. Measurements indicate that 90-95% of the energy of fish (capelin and herring) and 93% of the energy in krill is absorbed, respectively [ 10,11 ]. For practical purposes an average DE of 92% was used.

Gross energy intake (GEl) The daily energy requirements, or gross energy intake, is the sum of the faecal energy losses and the energy which is absorbed.

Food consumption Food consumption was determined by use of our GEI and the diet composition analysis of Haug et al. in 1992 [4], but in our calculations we have used the diet composition of their minke whales expressed as the relative % mass contribution of different prey species (LindstrCm, unpublished). In addition, values for seasonal changes in the energy density of the most common prey of minke whales (M~trtensson, Lager, NordCy and Blix, unpublished) were used to convert energy requirements into tonnes of prey consumed in the Northeast Atlantic waters.

310 Results

Energy requirements FMR The age-body length relationship of minke whales which were caught during the Norwegian scientific whaling in 1992 suggests that minke whales reach physical maturity at an age of 11 years. The fraction (28%) of physically mature animals has an average body length of approximately 8.0 m, while the fraction (72%) of growing animals has an average body length of 7.0 m. According to the length-mass relationship provided by Folkow and Blix [7] the average mass of adult and growing whales is 5.86 and 3.84 tonnes, respectively. Using these body masses and the value for the average energy expenditure of a minke whale provided by Blix and Folkow [1 ], the field metabolic rate of an adult and growing minke whale is 470,000 kJ/day and 307,000 kJ/day, respectively (Table 1). Blubber deposition An adult whale of 8.0 m with a mid-May blubber mass of 512 kg deposits about 208 kg of blubber between mid-May (average capture date in spring, 19 May) and the first week of October (average capture date in autumn, 6 September) (Fig. l a). The energy density of blubber increased from 27.5 kJ/g to 30.6 kJ/g (wet mass) during this period of 112 days. Thus, it can be calculated that about 71,000 kJ was deposited as blubber per day during this period. If a similar calculation is made for growing minke whales, a value of 53,000 kJ/day is obtained (Table 1). Intra-abdominal fat There were insignificant amounts of intra-abdominal fat in the spring, but a relationship between body length and visceral fat in autumn could be established and was used to calculate the average mass of fat deposited by adult and growing animals: Fat mass = 0.31BL-154, where fat mass is given in kg and body length (BL) in centimetres. Thus, adults deposited 94 kg of visceral fat while growing individuals deposited on average 63 kg, with an energy density of 36.7 kJ/g (wet mass) over a l l2-day period. This deposition amounted to 30,800 kJ/day and 21,000 kJ/day in adults and growing whales, respectively (Table 1). Growth or replacement of muscle mass Linear relationships were established between muscle mass and body length in spring and in autumn (Fig. lb). Animals of 7.0 m were estimated to have an increase in muscle mass of 247 kg, or 18% of initial muscle mass. Also for adults there appeared to be an increase in muscle mass between spring and autumn (Fig. l b), which may be attributed to a seasonal replacement of lost lean body mass due to semistarvation in other waters. This increase in muscle mass amounted to about 350kg for an 8.0m animal. During the same ( l l 2 d a y s ) period there was a significant increase in the energy density of muscle, from 5.4 kJ/g in spring to

Table 1. The daily FMR,and cost of fat deposition, growth and pregnancy, expressed in Mlday for 5 different classes of minke whales (adult males, adult pregnant females, growing pregnant females, growing males and growing females), multiplied by the number of days for which calculations were made

Adult males

Growing males

Adult pregnant females

Growing pregnant females

Growing females

-

FMR

Blubber deposition Growth/muscle replacement Visceral fat deposition Foetus Z = ME n (number of animals) MEXn Total metabolizable energy (kJ) Digestible energy (DE) (M) Gross energy intake (GEI) (M) -

7.3108 x 1012 7.9465 x 1012 8.6375 x 1012

--

The sum (metabolizable energy, ME (M)) was multiplied by n (number of animals within each class). The ME for the different classes was summed to obtain the ME for the total population of minke whales (being 87,000 animals). This value was adjusted for loss of energy in urine and faeces to obtain the gross energy intake.

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Fig. 1. (A) The blubber mass (kg) as a function of body length (cm) in minke whales which were caught in spring (closed symbols, average catch date, 19 May) and minke whales which were caught in autumn (open symbols, average catch date, 9 September). The equations describing the linear regressions were: Spring: BM = 1.22BL- 464 (r 2 = 0.809, n = 22) and autumn: BM = 1.76BL-688 (r 2 = 0.780, n = 41), BM is blubber mass in kg and BL is body length in cm. (B) The muscle mass (kg) as a function of body length (cm) in the same whales. The equations describing the linear regressions were: Spring: M M = 5 . 2 6 B L - 2 2 8 8 (r2=0.894, n = 2 2 ) and autumn: M M = 6 . 2 9 B L - 2 7 6 2 (r2=0.815, n = 4 2 ) , where MM is muscle mass in kg and BL is body length in cm.

Fig. 2. (A) Foetus body mass (kg) as a function of time (months) at which they were collected. (B) Total energy content of the foetuses (kJ x 1000) as a function of foetus mass (kg). The polynomial equation describing the relationship was: TEC = 0.78 + 0.95FM + 0.06FM 2 (r 2 = 0.998, n = 15), where TEC is total energy content of foetus (kJ) and FM is foetus mass (kg).

7.0 kJ/g in a u t u m n . T h e a m o u n t o f e n e r g y d e p o s i t e d as a r e s u l t o f i n c r e a s e d m u s c l e m a s s a n d an i n c r e a s e d e n e r g y d e n s i t y o f m u s c l e m a s s , d u e to fat d e p o s i t i o n , w a s c a l c u l a t e d to b e 4 9 , 0 0 0 k J / d a y a n d 3 5 , 0 0 0 k J / d a y in adults a n d g r o w i n g w h a l e s , r e s p e c t i v e l y ( T a b l e 1).

Growth o f foetus T h e r e l a t i o n s h i p b e t w e e n f o e t u s m a s s a n d t i m e is s h o w n in Fig. 2a. B y e x t r a p o l a tion o f t h e c u r v e , an a v e r a g e f o e t u s m a s s o f 35 k g at 1 O c t o b e r w a s f o u n d . T h i s f o e t u s c o n t a i n s 1 3 3 , 0 0 0 kJ o f e n e r g y (Fig. 2b). B e t w e e n

1 May and

1 October

313 this corresponds to an additional cost for pregnant females of only 900 kJ/day (Table

1). Gross energy intake

The daily energy expenditure, or field metabolic rate, was multiplied by 180 days, being the assumed average stay of a minke whale. Similarly, the average blubber deposition and muscle growth, which were measured over a period of 112 days, were assumed to take place at the same rate over a period of 180 days (Table 1). The deposition of visceral fat was restricted to a period of 135 days (19 May-1 October), since there was no significant amount of visceral fat in the whales caught in midMay (Table 1). The cost of growing a foetus was moreover restricted to a 150-day period (1 May-1 October), since the mass of the foetus was negligible in early May (Table 1). These calculations indicate that the total gross energy intake of the entire stock of minke whales is of the order of 8.6 x 10 ~2 kJ during their 180 days stay in the Northeast Atlantic (Table 1). Food

consumption

The total gross energy intake was converted to tonnes of various prey consumed (Fig. 3) by use of the data on the relative % mass contribution by different prey

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314

Table 2. The diet composition (as relative % mass), the average energy density of the prey (in the period 1 April-1 October) and the % energy contribution of the various prey to gross energy intake (GEI) Prey

Diet composition, Averageenergy relative % of density k J / g total massa (wet mass)b

The % energy contribution to GEI

Herring, adult (Clupea harengus) Herring, brits Capelin (Mallotus villosus) Sandeel (Ammodytestobianus) Cod (Gadusmorhua) Haddock (Melanogrammusaeglefinus) Saithe (Pollachius virens) Krill (Thysanoessa sp.) Fish, various

16.5 16.0 25.6 9.7 5.3 4.9 4.1 17.7 0.2

23.9 14.2 27.2 9.4 4.0 3.7 3.1 14.3 0.2

9.0 5.5 6.6 6.0 4.7 4.7c 4.7e 5.0 6.3

aValues taken from Haug et al. [3] and LindstrcJm (unpublished), based on analysis of stomachs from 92 minke whales caught in June-August 1992. bValues taken from Mhrtensson, Lager, Nord~y and Blix (unpublished). CThe same value as used for cod.

species and the average energy density of prey presented in Table 2. The calculations suggest that the Northeastern Atlantic minke whale population consumes of the order of 450,000 tonnes of herring (Clupea harengus), 355,000 tonnes of capelin (Mallotus villosus), 135,000 tonnes of sandeel (Ammodytes tobianus), 75,000 tonnes of cod (Gadus morhua), 70,000 tonnes of haddock (Melanogrammus aeglefinus), 60,000 tonnes of saithe (Pollachius virens) and 250,000 tonnes of krill (Euphausidae). This amounts to 1.4 million tonnes of various prey during their assumed 180-day stay in northern waters, or an average of about 90 kg (--2% of body mass) per animal per day, during this period.

Discussion

Field metabolic rate One important factor in our calculations of energy requirements is the estimated average estimate of F M R of a minke whale [1]. Pregnant, growing females, for instance, are likely to have a higher F M R than the 80 kJ/kg per day (corresponding to about 2.4 times the basal metabolic rate predicted by the Kleiber equation [14]), due to heat increment of gestation. The F M R of adult males, on the other hand, is likely to be lower than this value, since F M R was estimated for minke whales which were probably still growing (7-7.5 m long) [1 ]. Therefore, potential errors are likely to outweigh each other when it comes to discussing gross energy intake on the population level.

315

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4000

Population size Total commercial catch Cod consumption Minke whale consumption

-

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-

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-

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Fig. 4. The biomass (1,000 tonnes) of the autumn stock of capelin (2 years +); the spring spawning stock of herring (3 years +); and of the spring stock of cod (3 years +), compared with the total commercial catch of these species [12], the estimated minke whale consumption (this paper) and the estimated consumption by cod [13], in the Northeast Atlantic in 1992.

Food consumption Having these considerations in mind our results suggest that minke whales consume a biomass of herring which corresponds to about five times the commercial catch in 1992 [12] in the same area (Fig. 4). The herring consumption, moreover, is of about the same order of magnitude as the estimated consumption of herring by NortheastArctic cod [13]. About half the biomass (-200,000 tonnes) of herring consumed by minke whales appears to be 0-group herring, which indicates that this is an important factor that must be considered in management of herring stocks. The estimate of capelin consumption is less than half the commercial catch in 1992 [12] in the Barents Sea (Fig. 4), and only 14% of the estimated consumption by cod [13]. Since this consumption amounts to only 10% of the estimated autumn population (i.e. not including fish younger than 2 years) of capelin in the Barents Sea in 1992 [ 12], predation by minke whales alone is likely to have only minor effects on the fluctuations of capelin stock sizes. Perhaps more important then is the minke whale consumption of cod, which amounts to about 70,000 tonnes, being one fifth of the total commercial take, or 4% of the estimated cod biomass (3 years and older), in 1992 [12]. Since cod is a long-lived species, such a consumption is likely to have important effects on the dynamics of the cod population. It is emphasised that the biomass of younger age-classes of fish (pre-recruits), which is probably considerable, is not included in the biomass of the fish stocks because of lack of data. Both minke whales and cod are known to feed extensively on these younger age-classes, which explains why the total amount caught in commer-

316 cial fisheries, and consumed by cod and minke whales exceeds the estimated stock size of, for example, capelin. In our estimates we have used data on the diet of minke whales in 1992 [4]. It is quite clear, however, that their diet changes dynamically. In 1993, for instance, capelin appeared to some extent to be replaced by krill and gadoid fishes in the diet of whales in northern waters [15]. This may be explained by a dramatic decrease in the total stock of capelin between these two years [ 16]. An interesting calculation can be made with regard to energy deposited as fat and muscle mass in minke whales in northern waters: this energy corresponds to about 35% of the average FMR, and will only cover 60 days of FMR in the other 6 months of the year, when they supposedly stay in unknown southern temperate waters without eating [17]. This shows that minke whales must supply their endogenous stores of energy with a substantial gross energy intake, in order to survive during the remaining months. It remains to be seen where and how this is done.

Conclusion This paper has reviewed current knowledge on the food consumption of minke whales in the Northeast Atlantic with emphasis on data collected during the last years of scientific whaling. Our data suggest that minke whales hold an important position within the ecosystem of the Norwegian and Barents Sea and should be included in the multispecies modelling for better predictions of stock size developments in the future.

Acknowledgements The crew members and scientific personnel who have participated during the Norwegian scientific whaling programme (1992-1994) are thanked for cooperation and the collection of biological data from minke whales. I. Christensen, Institute of Marine Research, Bergen, kindly supplied information on age determination of the minke whales taken as part of the scientific whaling catch in 1992 and T. Haug gave us access to his data on their stomach contents. This study was supported by the Norwegian Fisheries Research Council, Marine Mammal Research Programme, grants nos. 408.005,408.008 and 408.016.

References 1. Blix AS, Folkow LP. Daily energy expenditure in free living minke whales. Acta Physiol Scand (in press). 2. Schweder T, Oien N, HCst G. Estimates of abundance of the Northeastern Atlantic minke whales in 1989. Rep Int Whal Commn 1993;43:323-331.

317 3. Nord~y ES, Blix AS. Diet of minke whales in the Northeastern Atlantic. Rep Int Whal Commn 1992;42:393-398. 4. Haug T, GjCs~eter H, LindstrCm U, Nilssen KT. Studies of minke whale Balaenoptera acutorostrata ecology in the Northeast Atlantic: preliminary results from studies of diet and food availability during summer 1992. Report to the Scientific Committee, IWC 1992;IWC SC/45/NA3. 5. Lavigne DM, Barchard W, Innes S, Oritsland NA. 1982. Pinniped Bioenergetics. In: Mammals in the Seas. vol IV. Small Cetaceans, Seals, Sirenians and Otters. Rome: Food and Agriculture Organization of the United Nations. FAO Fish Ser No. 5, 1982;191-235. 6. Jonsg~rd/~. Studies on the little piked whale or minke whale (Balaenoptera acuto-rostrata Lac6p~da). Nor Hvalfangst Tid 1951 ;40:209-232. 7. Folkow LP, Blix AS. Metabolic rates of minke whales (Balaenoptera acutorostrata). Acta Physiol Scand 1992;146:141-150. 8. Christensen I. Age determination of minke whale, Balaenoptera acutorostrata, from laminated structures in the tympanic bullae. Rep Int Whal Commn 1981 ;31:245-253. 9. International Whaling Commission. Report of the Scientific Committee. Rep Int Whal Commn 1993;43:55-219. 10. Nord~y ES, SCrmo W, Blix AS. In vitro digestibility of different prey species of minke whales (Balaenoptera acutorostrata). Br J Nutr 1993;70:485-489. 11. MArtensson P-E, NordCy ES, Blix AS. Digestibility of krill (Euphausia superba and Thysanoessa sp.) in minke whales (Balaenoptera acutorostrata) and crabeater seals (Lobodon carcinophagus). Br J Nutr (in press). 12. Anonymous. Ressursoversikt 1993. Fisk Hay 1993; 1:1-66. 13. Anonymous. Report of the ICES Arctic Fisheries Working Group. ICES CM 1995/Assess:3, 1994. 14. Kleiber M. The Fire of Life. New York: Krieger, 1975. 15. Haug T, GjCsaeter, H, LindstrCm U, Nilssen KT, R~ttingen I. Spatial and temporal variations in Northeast Atlantic minke whale Balaenoptera acutorostrata feeding habits. In: Schytte-Blix A, WallCe L, Ulltang 0 (eds) Whales, Seals, Fish and Man. Amsterdam: The Netherlands, 1995;225239. 16. Anonymous. Ressursoversikt 1994. Fisk Hav 1994;1:1-104. 17. Stewart BS, Leatherwood S. Minke whale Balaenoptera acutorostrata Lac6p~de, 1804. In: Ridgeway S, Harrison R (eds) Handbook of Marine Mammals 3. London: Academic Press 1985;91-136.

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9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand ~. Ulltang,editors

319

Energetics of pregnancy, lactation and neonatal development in ringed seals (Phoca hispida) Christian Lydersen Norwegian Polar Institute, Tromsr Norway Abstract. Ringed seal fetuses grow according to the equation: (fetal mass) 1/3 (g) = 0.075 (days) - 1.23 (r = 0.997), for the 241 days of active gestation. The energy content of newborn ringed seals (N = 3, mass =4.55 kg, fat = 4.75%, protein = 21.8%) and placentas (N= 3, mass =0.347 kg, fat = 1.88%, protein = 16.38%) are 26.3 MJ and 1.3 MJ, respectively. Metabolic requirements for the growing fetus for the whole gestation period are estimated to be 113.4 MJ. Ringed seal pups are nursed for approximately 39 days and grow at a daily rate of 0.35 kg. Their average metabolic rate is 3.8 times the predicted basal metabolic rate based on body size. The pups drink an average of 1379 ml of milk daily, with a caloric density of 17.32 kJ/g. Net milk energy output for the average female ringed seal over the whole lactation period is thus 931.5 MJ. Total net costs of pregnancy and lactation are thus 1072.5 MJ. Ringed seal neonates are somewhat more energetically costly to their mothers compared to other phocids (per mass unit) because of their unusual degree of activity. While most young phocids spend the majority of their time immobile, nursing ringed seal pups spend more than 50% of their time in the water. As a result they become skilled divers at an extremely early age, and are able to dive for 12 min and to depths of 90 m. Ringed seal pups keep their fetal whitecoat longer than any other phocid pups, and they occupy a high number of breathing holes compared to other age groups of the same species. All of these factors are considered to be evolutionary adaptations for predator avoidance, mainly from polar bears.

Key words: lactation, reproductive energies, diving, behavior, ringed seal pups

Introduction

The ringed seal (Phoca hispida) is the most numerous seal in the northern hemisphere. It has a circumpolar distribution and its total population size is estimated to be between 5-7 million individuals [1]. During the spring breeding and pupping season, ringed seals show a great affinity for ice, where stable land-fast ice seems to be the preferred habitat. The seals are able to maintain breathing holes in ice that is several metres thick and can thus, in principle, be found throughout the whole Arctic marine environment, including the north pole. Ringed seals are the smallest of the northern phocids. They have evolved under strong predation pressure from surface predators, mainly polar bears (Ursus maritimus), but also arctic foxes (Alopex lagopus) and birds such as ravens (Corvus corax) and glaucous gulls (Larus hyperboreus) [2-6]. The high levels of predation pressure have resulted in antipredator adaptations such as giving birth in snow-covered lairs, use of multiple lairs and breathing holes as possible escape routes in case of attack, and a generally

Address for correspondence: Norwegian Polar Institute, P.O. Box 399, N-9001 Tromsr Norway.

320 "nervous" haul-out behaviour. When hauled out, ringed seals normally raise their heads and scan the area every 10-15 s. Additionally, they position themselves at the breathing hole in such a way that the wind is coming from behind [7]. They are thus able to see predators approaching from the front, and smell predators coming from behind. Because of all these anti-predator adaptations, ringed seals are difficult to capture compared to other seal species, and most of the important events during the spring pupping and breeding season occur under the ice, or in snow-covered lairs. A recent report estimated the ringed seal population to be about 200,000 individuals in the region of Svalbard. This number is thought to represent the carrying capacity for this area [8]. Based on studies of ice conditions, and knowledge of densities of ringed seals in different types of ice [9,10], the annual pup production in Svalbard is estimated to be about 20,000 [11]. Thus, the ringed seal is the most abundant mammal in Svalbard. Energy invested in reproduction represents a major component of the annual energy budget of most mammalian species. During the last decade, a series of studies have documented the various components of energetic investment by female ringed seals, such that a reasonably complete analysis of reproductive energetics by females of this species is now possible. This is the subject of the present paper. The primary emphasis of this review is on information gathered from Svalbard during The Norwegian Marine Mammal Research Programme. In the Svalbard area, female ringed seals reach sexual maturity at 3-5 years of age [12]. Peak pupping for ringed seals in this area is the first week of April. Based on cross-sectional studies of ringed seals from the Canadian western Arctic, where ovaries and uterine cornuas were examined, it was estimated that ringed seal females have a delayed implantation of 89 days and an active gestation period of 241 days [13]. Another cross-sectional study of ringed seals from both Svalbard and the Canadian Arctic, that examined ovaries and mammary glands, concluded that ringed seals have an average lactation period of 39 days [14]. If we define 1 April as the nominal birth date in the Svalbard area, and extrapolate the data reported above to the Svalbard population, the average dates for ovulation, weaning and implantation would be 6 May, 9 May and 3 August, respectively (Fig. 1). Seventeen fetuses have been collected from ringed seals in Svalbard (Lydersen, unpublished data). Using collection date as a measure of age, these fetuses grow according to the equation: (fetal mass) 1/3 (g)= 0.075 ( d a y s ) - 1.23 (r = 0.997). Three newborn pups and placentas have also been collected from the same area. The mean mass of the pups was 4.55 _+0.30 kg, and the mean mass of the placentas was 0.347 _+0.140 kg. The total energy contents of a newborn pup and a placenta of average mass based on slaughter house chemical analyses were 26.3 MJ and 1.3 MJ, respectively (Lydersen, unpublished data). In addition to production of fetal and placental tissues, the cost of pregnancy also includes energy to maintain the metabolic requirements of the growing fetus. This cost can be estimated using a relationship derived for terrestrial mammals: QG = 18.4BM 1.2, where QG is the heat of gestation in MJ and BM is the body mass in kg of the newborn pup [15]. According to this

321

Implantation August 3 Fig. 1. Reproductive events in an annual cycle for adult ringed seal females from Svalbard.

relationship the energy required to cover the metabolic requirements of a growing ringed seal pup would be 113.4 MJ. Ringed seals are normally born in a lair that is dug out by the female in the snow covering a breathing hole [16]. Each female has several lairs and breathing holes, and can thus move between these structures if attacked by predators. It is thought that mothers actively move the pups if they are attacked while the pup is relatively young. Newborns do not have an insulating layer of subcutaneous blubber, but can survive brief immersions in ice-cold water through the use of relatively large stores of brown adipose tissue [17]. As lactation progresses pups deposit blubber and they start entering the water voluntarily. Based on VHF recordings of pup activity, nursing ringed seal pups spend up to 64% of their time in the water [18]. Pups of other phocid species that are born bearing lanugo, such as grey (Halichoeurs grypus) and harp (Phoca groenlandica) seals, usually stay on the ice or on shore until the nursing period is over [ 19,20] before they start to explore the aquatic environment. In order to obtain more detailed information on ringed seal pup diving behaviour, microprocessor controlled time-depth recorders (TDRs) (Mk5- Wildlife Computers) were used to collect more than 1,000 h of activity. This sample includes over 7,500 dives from three nursing ringed seal pups [21 ]. The pups were spending an average of 50.3% of this time in the water and 49.7% hauled out on the ice. When the pups were in the water, 20.5% of the time was spent actively diving, while the remaining 79.5% was spent at the surface. The pups used in this experiment inhabited three different geographical areas, and comparisons with sea maps for the respective areas showed that the pups were diving to the bottom in all three cases. The deepest recorded dive was 89 m. The longest recorded dives for the three pups were 5.8, 7.5 and 12.0 min re-

322 spectively. Based on information on body composition and oxygen stores for adult ringed seals [22], the aerobic dive limit (ADL) for a 20 kg ringed seal would be about 3.3 min. Thus, the aerobic dive limit was exceeded by all three pups. However, dives of duration longer than the ADL were exceptional; only 3.7% of all recorded dives exceeded this limit. Pups tended to spend more time in the water and more time actively diving with increasing age. They also increased the number of long dives as they became more competent in the water [21 ]. Two different longitudinal studies, one using tritiated and one using doubly labelled water, were conducted in order to measure growth, water flux and CO2 production, and to estimate milk intake and change in body composition of nursing ringed seal pups [23,24]. During these studies, pups were captured and their stomachs were evacuated of milk. They were then weighed and injected with a known volume of known concentration of labelled water. Then, after the injected isotopes were thought to be at equilibrium with the animal's body water pool, a blood sample was taken before the animal was released. The general procedure for all such experiments should be a serial blood sampling regime performed on some injected individuals to enable determination of equilibrium time for the size and species of animal involved. One should also know approximately the biological half-life of the oxygen isotope, since the most reliable results are obtained when animals are recaptured between one and two half-lives of the oxygen isotope [25]. For ringed seal pups with body masses of 20 kg or less, the injected tritium was in equilibrium with the rest of the body water pool within 30 min after intramuscular injections of the isotope [23]. This short interval reflects the relatively small size and high metabolism of the animals that were crawling around on the ice for most of the equilibration period. These factors are also reflected in the short biological half-life of tritium, of only 130 _+ 17 h in these pups [23]. For later experiments, generally the equilibration blood sample was taken after a waiting period of 1 h post injection after intravenous administration of isotopes, and recapture for terminating experiment or re-injecting isotopes was attempted about 1 week after initial injection. The average daily mass gains of the pups in the two isotope studies were 0.39 _ 0.10 kg and 0.35 _+0.08 kg, respectively. The daily water fluxes in the pups in the same two experiments were 62.9 +_21.5 ml/kg and 52 __.0 ml/kg. The fact that the former value is somewhat higher (although not significantly, P = 0.58, MannWhitney U-test) is expected since the pups in that study were smaller and if all other conditions were similar should thus have a higher mass specific metabolism. In order to calculate the proportion of the total water flux that results from metabolism versus external sources, a second isotope experiment was conducted using doubly labelled water [24]. CO2 production was measured to be 0.85 _+0.16 ml/g per h, corresponding to a field metabolic rate (FMR) of 0.55 +_0.10 MJ/kg per day or 3.8 _ 0.6 times the predicted basal metabolic rate (BMR) based on body size [26]. Using these measurements, metabolic water production was calculated and subtracted from the total water influx. This gave an estimate of water intake from external sources. It is assumed that all water entering the pups was from the milk. None of the pups in the doubly labelled water experiment was observed drinking water or eating snow. In

323 addition, the very small intraspecific variation in water flux, and the credible values for milk intake produced when using the measured water fluxes, suggest that any other intake of water could be neglected. Only one longitudinal record of ringed seal milk is available [23]. The average water content in the milk over an 18-day period was 48.6 +_5.3%. The average values for protein and fat were 9 . 9 _ 2.4% and 38.1 _+2.9%, respectively. The fat content increased from 36.4 to 41.5% during this period. Using these average values, the pups drank 1,379 ml milk daily of a caloric density of 17.32 kJ/g. During an average lactation period of 39 days, pups would thus drink 53.8 1 of milk or take in 931.5 MJ of energy. The body composition of the pups changed dramatically during the nursing period. New-born tinged seals consisted of 4.75% fat and 70.1% water [23]. As the pups grew, the fat content increased and the water content decreased (Fig. 2). Close to weaning, at a body mass of 21 kg, the fat and water content were 41% and 42%, respectively [24]. Nursing ringed seal pups used in the doubly labelled water study were equipped with Mk5 TDRs. Activity budgets, based on information collected with the TDRs, were constructed and used in conjunction with the FMR measurements in an attempt to calculate FMR for the different activities of the pups (Table 1). The three types of activities that can be separated from the TDR readings are hauled out on the ice (saltwater switch dry), actively diving (saltwater switch wet, and pressure transducer recording depths deeper than 1 m) and staying in the water at the surface (saltwater switch wet, and pressure transducer recording depths shallower than 1 m). When solving three equations with three unknowns, where the fractions of time spent in the three different activities for each pup were matched against the total energy con-

60

r/3

5O

,~

4o

"D'----------. o o

3O

9

Water

D

Fat

r r

9 Protein

r

20 I

10

!

14

16

9

!

9

18 Body

!

20

9

i

22

m a s s (kg)

Fig. 2. Variation in body composition in nursing ringed seal pups of different body masses from Sval-

bard spring 1992. (Water: y=43.60 + 2.39x-0.117x2, fat: y= 38.71 - 3.35x +0.164x2, protein: y = 4.39 + 1.93x - 0.070x2, r = 0.86 in all cases). From Lydersen et al. [24].

324 Table 1. Activity budgets and daily energy consumption for nursing ringed seal pups from Svalbard, spring 1992

Animal no.

Duration of experiment (days)

Mean body mass (kg)

Fraction of day hauled out (%)

Fraction of day at surface (%)

Fraction of day diving (%)

Energy consumption (kJ/day)

E 2034 E 2021 E 2056

10 11 10

19.15 18.60 18.05

46 60 50

38 32 42

16 8 8

10,499 8,727 10,032

sumption for each individual, FMRs for hauling out, actively diving, and staying in the water at the surface are calculated to be 1.34, 5.88 and 6.44 times BMR, respectively [24]. The former value seems very low for a growing pup and could be a sampling artifact. However, based on observations, ringed seal pups are very inactive when hauled out, and if they spend a lot of time sleeping, like nursing pups of other phocid species [ 19,20], this dramatically reduces their metabolic rate [27]. Information on activity of ringed seal mothers during the nursing period is scarce. In one study that employed acoustic telemetry on a single female that had an almost weaned pup (22 kg at first capture), it was found that the mother spent 55% of the recorded time in the water [28]. Another female equipped with a Mk5 TDR that had a younger pup (13 kg at first capture) spent 82% of a 17-day recording period in the water (Lydersen, unpublished data). Longitudinal mass loss data from nursing ringed seal mothers have been recorded from two individuals, one monitored over a 17-day period and one over an l 1-day period (Lydersen, unpublished data). They lost 0.62 kg/day and 0.68 kg/day, respectively. If we assume that all of this mass loss is fat, an average daily mass loss of 0.65 kg corresponds to an energy loss of 25.6 MJ. The daily milk energy output of an average female was calculated to be 23.9 MJ. Thus the mass loss of the mothers barely covers the expenses of the milk production. Assuming an average FMR for the mothers of twice BMR and a body mass of 70 kg, an energy equivalent of 14.2 MJ is needed to cover a mother's metabolism. Combining these figures, a daily deficit of 12.5 MJ is found. This has to be covered through eating. This energy value is a minimum estimate since the mass loss of the mothers probably does not consist of 100% fat, and the FMR of twice BMR is probably conservative. Stomach content analyses from ringed seals in the Svalbard area have shown that ringed seals eat mainly arctic cod (Boreogadus saida) and the amphipod Parathemisto libellula [29-31]. Bomb calorimetric measurements of specimens of these food types collected in August, show a caloric density of 3.8 kJ/g and 5.8 kJ/g for P. libellula and arctic cod, respectively. Using these values, ringed seal females would have to eat 2.2 kg of arctic cod or 3.3 kg of P. libellula daily during the nursing period in order to balance their energy budgets. These values are also minimal since the assimilation of energy from the food is not 100%. If we add up the energetic costs of pregnancy and lactation, the average net energy output for each ringed seal female to produce a weaned pup, is 1072.5 MJ (Table 2). Using the same values

325 Table 2. Minimum estimates of net energy required for a ringed seal female to produce a weaned pup MJ Energy content of newborn Energy content of placenta Heat of gestation Milk energy output Total

26.3 1.3 113.4 931.5 1,072.5

for the main prey items, this corresponds to a minimum of 185 kg of arctic cod or 282 kg of P. libellula. Generally, the most efficient energy transfers during lactation in phocid seals are found in species where the nursing period is short and the pups are inactive. Within phocids, ringed seals have the longest nursing period, and with the growth rate recorded for Svalbard, they use about 14 days to double their newborn mass. The corresponding figures for hooded (Cystophora cristata), harp and grey seals are 4, 6 and 9 days, respectively. In addition, newborns of these three species are 5, 2 and 4 times heavier than ringed seals at birth. However, the pups of these other species are very inactive during the nursing period compared to ringed seal pups. As was shown earlier, ringed seal neonates spend about 50% of their time in the water. Predation pressure is probably the major factor that has led to the observed differences in neonatal development and overall lactation strategies. By being active, and diving at an extreme early age, ringed seal pups develop diving skills that help them escape predators. The lactational strategy observed in the other species, where the pups stay helpless on the ice platform during the whole lactation period and thereafter start to explore the water, would be catastrophic in an area where polar bears are constantly hunting. The behaviour of ringed seal pups is of course in conflict with a maximum efficiency of energy retention, and the metabolic overhead paid by tinged seal mothers is the highest among phocid seals. Ringed seal pups store only about 36% of the energy they receive via milk as body tissue. The corresponding figures for harp and grey seal pups are 66% (Lydersen et al., unpublished data) and 75% [32], respectively. However, reproductive success is not measured as who produces the fattest pup but as the number of surviving offspring, and in an environment with constant threat of predation from the surface, learning to dive as fast as possible is a key to survival. Another feature of ringed seal behaviour during lactation that probably resulted from predation pressure is the relatively high number (8.5 _+3.5) of breathing holes used by the females and their pups, compared to the average of 3.5 found for other ringed seals [33]. In addition, the ringed seal pups keep their white lanugo for a very long time (up to 2 months in some cases) compared to pups of other species. At this stage the insulatory properties of the lanugo are of little value, but since vision is important to hunting polar bears [34], cryptic coloration will reduce the pup's chances of being detected when it is hauled out outside lairs.

326

Acknowledgements This study was funded by the Norwegian Fisheries Research Council (NFFR), Department of Fisheries and Oceans, Canada and the Fritjof Nansen Foundation for the Advancement of Science. I would like to thank K. Kovacs for comments on the manuscript.

References 1. Stirling I, Calvert W. Ringed seal. FAO Fish Ser 1979;5:66-69. 2. Smith TG. Predation of ringed seal pups (Phoca hispida) by the arctic fox (Alopex lagopus). Can J Zool 1976;54:1610-1616. 3. Smith TG. Polar bear predation of ringed and bearded seals in the land-fast sea ice habitat. Can J Zool 1980;58:2001-2009. 4. Gjertz I, Lydersen C. Polar bear predation on ringed seals in the fast-ice of Hornsund, Svalbard. Polar Res 1986;4:65-68. 5. Lydersen C, Gjertz I. Studies of the ringed seal (Phoca hispida) in its breeding habitat in Kongsfjorden, Svalbard. Polar Res 1986;4:57-63. 6. Lydersen C, Smith TG. Avian predation on ringed seal Phoca hispida pups. Polar Biol 1989;9:489--490. 7. Kingsley MCS, Stirling I. Haul-out behavior of ringed and bearded seals in relation to defence against surface predators. Can J Zool 1991 ;69:1857-1861. 8. JCdestr K, Ugland KI. S~barhetsanalyse for ringsel og grCnlandsel i Barentshavet nord. Det Norske Veritas Industrier AS, 1994;Rapport no 93-3740. 9. Lydersen C, Jensen PM, Lydersen E. A survey of the Van Mijen fiord, Svalbard, as a breeding habitat for ringed seals, Phoca hispida. Holarct Ecol 1990;13:130-133. 10. Lydersen C, Ryg M. Evaluating breeding habitat and populations of ringed seals Phoca hispida in Svalbard fjords. Polar Rec 1991;27:223-228. 11. Smith, TG, Lydersen C. Availability of suitable land-fast ice and predation as factors limiting ringed seal populations, Phoca hispida, in Svalbard. Polar Res 1991;10:585-594. 12. Lydersen C, Gjertz I. Population parameters of ringed seals (Phoca hispida Schreber, 1775) in the Svalbard area. Can J Zool 1987;65:1021-1027. 13. Smith TG. The ringed seal, Phoca hispida, of the Canadian western Arctic. Can Bull Fish Aquat Sci 1987;216:1-81. 14. Hammill MO, Lydersen C, Ryg M, Smith TG. Lactation in the ringed seal (Phoca hispida). Can J Fish Aquat Sci 1991;48:2471-2476. 15. Brody S. Bioenergetics and Growth, with Special Reference to the Efficiency Complex in Domestic Animals. New York: Reinhold, 1945. 16. Smith TG, Stifling I. The breeding habitat of the ringed seal (Phoca hispida). The birth lair and associated structures. Can J Zool 1975;53:1297-1305. 17. Taugbr G. Ringed seal thermoregulation, energy balance and development in early life. Thesis, Institute of Zoophysiology, University of Oslo, Norway. 1982. Can Fish Aquat Sci Transl Ser 1984;5090. 18. Lydersen C, Hammill MO, Ryg MS. Differences in haul-out pattern in two nursing ringed seal (Phoca hispida) pups. Fauna Norv Ser A 1993;14:47-49. 19. Kovacs K. Maternal behaviour and early behavioural ontogeny of grey seals (Halichoerus grypus) on the Isle of May, UK. J Zool London 1987;213:697-715. 20. Kovacs K. Maternal behaviour and early behavioural ontogeny of harp seals (Phoca groenlandica). Anim Behav 1987;35:844--855.

327 21. Lydersen C, Hammill MO. Diving in ringed seal (Phoca hispida) pups during the nursing period. Can J Zool 1993;71:991-996. 22. Lydersen C, Ryg MS, Hammill MO, O'Brien PJ. Oxygen stores and aerobic dive limit of ringed seals (Phoca hispida). Can J Zool 1992;70:458--461. 23. Lydersen C, Hammill MO, Ryg MS. Water flux and mass gain during lactation in free-living ringed seal (Phoca hispida) pups. J Zool London 1992;228:361-369. 24. Lydersen C, Hammill MO. Activity, milk intake and energy consumption in free-living ringed seal (Phoca hispida) pups. J Comp Physiol 1993;163:433-438. 25. Nagy, KA. The doubly labeled water (3HH180) method: a guide to its use. Los Angeles, CA: UCLA Publication No 12-1417, 1983. 26. Kleiber M. The Fire of Life: an Introduction to Animal Energetics. Huntington, NY: Robert E. Krieber, 1975. 27. Worthy GAJ. Metabolism and growth of young harp and grey seals. Can J Zool 1987;65:13771382. 28. Lydersen C. Monitoring ringed seal (Phoca hispida) behaviour by means of acoustic telemetry. Can J Zool 1991;69:1178-1182. 29. Gjertz I, Lydersen C. The ringed seal (Phoca hispida) spring diet in northwestern Spitsbergen, Svalbard. Polar Res 1986;4:53-56. 30. Lydersen C, Gjertz I, Weslawski JM. Stomach contents of autumn-feeding marine vertebrates from Hornsund, Svalbard. Polar Rec 1989;153:107-114. 31. Weslawski JM, Ryg M, Smith TG, Oritsland NA. Diet of ringed seals (Phoca hispida) in a fjord of west Svalbard. Arctic 1994;47:109-114. 32. Lydersen C, Hammill MO, Kovacs KM. Milk intake, growth and energy consumption in pups of ice-breeding grey seals (Halichoerus grypus) from the Gulf of St. Lawrence, Canada. J Comp Physiol B (in press). 33. Hammill MO, Smith TG. Application of removal sampling to estimate the density of ringed seals (Phoca hispida) in Barrow Strait, Northwest Territories. Can J Fish Aquat Sci 1990;47:244-250. 34. Stifling I. Midsummer observations on the behaviour of wild polar bears (Ursus maritimus) Can J Zool 1974;52:1191-1198.

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329

Harp and hooded seals - a case study in the determinants of mating systems in pinnipeds Kit M. Kovacs Department of Biology, University of Waterloo, Waterloo, Ontario, Canada Abstract. The similarities and differences that occur in the reproductive behaviour and energetics of harp and hooded seals make these two species an interesting case study for refining our understanding of the determinants of mating systems in pinnipeds. Both species breed in whelping patches that form in pack-ice regions in the North Atlantic. This parturition environment provides virtually unlimited space, but strict temporal limits. The lactation strategies employed by these species are similar in that the nursing period of each species is short, pup growth is fast and energy transfer is efficiently accomplished through the production of fat rich milk. Harp seal pups are born weighing 9.9 _ 1.7 kg and grow at a rate of 2.3 • 0.5 kg/day during the 12.9 _+2.5 day nursing period. Mass loss by lactating female harp seals averages 27% (38 kg) of their total body mass (139.0 _ 17.0 kg). Hooded seal pups are born weighing 24.4 _ 2.6 kg and grow at a rate of 6.9 • 1.2 kg/day during the 3.8 _ 0.5 day nursing period. The concomitant mass loss by their mothers is 16% (38 kg) of their parturition mass (236.5 • 35.5 kg). The duration of lactation, in addition to the degree of synchrony among females in birthing, means that females are only available for male breeding attempts for a short period of time in either species. This places a high premium on the choice of mating strategies for males of both species. However, male harp seals and male hooded seals face quite different regimes with respect to female spacing patterns in relation to water and to other females. Females harp seals give birth near open water with a nearest neighbour distance of 5-10 m. Female hooded seals give birth far from open water with an average of 50 m between females. The differences in female habitat choice and mobility have profound effects in the determination of what defines a successful strategy for males. Male monopolization of females is not possible in harp seals and males must mate opportunistically, possibly with scramble or sperm competition determining success. Male hooded seals are able to mate guard to a greater degree and display a form of polygyny that involves serially attending a number of females during a reproductive season. Key words:

Phoca groenlandica, Cystophora cristata, reproduction, energetics

In the last decade or two, mating systems of animals have come to be viewed as the outcomes of natural selection operating at the level of the individual [ 1-4]. Variation in mating behaviour is thus expected both within and between populations and species as a consequence of the adaptive adjustment of male and female behaviour to differences in the social and ecological environment and to variation in individual capabilities. Sexual selection will have its most pronounced affect among populations where a portion of the population has the ability to control the access of others to potential mates. The greater the potential for multiple mate monopolization, the greater should be the potential intensity of sexual selection and the tendency for

Address for correspondence: Department of Biology, University of Waterloo, Waterloo, Ontario, N2L 3G 1 Canada.

330 polygamy [5]. Among mammals, males of most species have much greater reproductive potential than females in terms of gamete production, and females are biologically predisposed to perform the bulk of parental investment. These basic dichotomies between male and female mammals mean that male mammals are fundamentally polygynous and that females represent a limited resource [6]. Thus males will compete for access to females and females should exhibit some mechanism of mate choice. Pinniped mating systems have received considerable research attention, in part due to the extreme forms of polygyny and marked sexual dimorphism displayed among some seal species. Bartholomew's [7] model for the evolution of pinniped polygyny recognized that the simple dichotomy of offshore marine feeding, in combination with terrestrial parturition, set the stage for positive-feedback loops that enhanced selective pressures. These pressures ultimately resulted in the extremes that we see in some pinnipeds, where males are 8 times the body mass of females and where less than 5% of males are responsible for the insemination of in excess of 90% of females [8]. Bartholomew's simple model eloquently described the mating system of all terrestrially breeding otariid seals and a few phocids. However, it was not all encompassing and did not account for half of the living species of pinnipeds, which do not simultaneously exhibit terrestrial mating, marked sexual dimorphism and harem polygyny. Stirling's 1975 [9] and 1983 [10] reviews of pinniped mating systems were much more comprehensive. In these two studies, Stirling identified six primary factors that influence pinniped social dynamics during the reproductive period: (1) habitat availability, access and stability; (2) synchronized parturition and mating; (3) gregariousness of females and sexual dimorphism; (4) predation; (5) terrestrial versus aquatic mating; and (6) thermal considerations. More than a decade has passed since Stirling's second contribution [10] and a great deal of research has been conducted on the reproductive behaviour of pinnipeds. Two species that have received considerable attention during this time are harp and hooded seals. These two phocids share a number of ecological similarities with respect to their reproductive ecology while displaying quite different mating arrangements. Thus, they constitute an interesting case study which is valuable for refinement of our ideas regarding mating systems among pinnipeds. Both harp seals and hooded seals are pack-ice breeders [11 ]. This substrate is extremely transient in both time and space and is unfavourable for the development of extreme polygyny because space is virtually unlimited and access to water is usually readily available through leads, cracks and holes. However, its unstable nature does favour extremely high birthing synchrony, and hence mating synchrony, which enhances the potential for polygyny. It also favours the development of precocial young and a short period of dependence. Both harp and hooded seals have very short lactation periods, during which pups grow rapidly on the fat rich milk their mothers provide. Females of both species are gregarious and form whelping patches in traditional areas. Densities do not approach those of otariids or some land breeding phocids but herds are readily distinguishable and the locations of their initial formations are reasonably predictable in most years. Both harp and hooded seals are preyed

331 upon by polar bears, Greenland sharks and killer whales, but little is known about the extent to which this takes place. Both species mate in the water and experience similar thermal environments and have quite similar adaptations to cold weather. However, there are fundamental behavioural and physiological differences between these two species that result in marked differences in the environmental potential for polygyny (EPP) and hence the social arrangements for mating. Although both harp and hooded seals whelp on pack-ice, the type of ice chosen for birthing by females of the two species is quite different. Female harp seals form herds on thin ice, along the edges of leads. When the leads freeze females actively maintain holes through habitual use; several females frequently share the use of individual haul-out points. Female harp seals keep their young close to their entry point to the water. Hence, pups are clustered with a modal nearest neighbour distance (NND) of 5-10 m (Kovacs unpublished data). Female harp seals are very mobile during lactation and routinely leave their pups for several hours at a time, between feedings [12,13]. In contrast, hooded seal females actively select thick ice and move away from access to open water. Nearest neighbour distances are highly variable, but the average NND is 50 m [14,15]. Female hooded seals are sedentary during lactation, remaining in constant attendance of their pup. Both harp and hooded seals give birth in a highly synchronous manner over a period of 2-3 weeks. However, this time frame has markedly different implications when the duration of lactation of the two species is considered. Harp seal females nurse their pups for more than three times as long as do hooded seals and in all regards hooded seal pups are more precocial than harp seal neonates (Table 1) [ 16-22]. Hooded seal pups are proportionally larger at birth, they possess a thin blubber layer [23] and have already shed their foetal hair in utero. They are fed milk that is higher in fat and grow proportionally faster than harp seal pups during the nursing period. The larger body size of hooded seals compared to harp seals gives females of the former species an advantage. Hooded seal females are able to produce milk rapidly, solely from blubber stores to achieve the remarkable rate of energy transfer without feeding during lactation. The smaller harp seal females mobilize nutrients more slowly and some individuals feed during lactation [18]. However, body size alone does not explain the difference in the duration of lactation between these two species. Little is known about the impact of non-human predation on harp and hooded seals but it is unlikely that the levels of surface or aquatic predation are profoundly different between these pack-ice breeders. Stirling [ 10] has speculated that the heavier ice used by hooded seals may result in them being subject to more intense polar bear predation than harp seal. Conversely, it could be argued that the paralysis behaviour of harp seals [24] and the amount of time females spend in the water during lactation [13] might suggest that they have been subjected to more intense surface predation than hooded seals. Both harp and hooded seals mate in the water but because of the differences in spacing patterns between females relative to water and the duration of lactation between these two species, the behavioural strategy of males is markedly different.

332 Table 1. Summary of neonatal development and energetic aspects of lactation by female harp and hooded seals

Character

Harps

Birth mass (kg) Growth rate (kg day-1) Duration of lactation (days) Female mass loss (kg) per day Average maternal body mass (kg) Maximum milk fat (%) Lanugo at birth Mass transfer efficiency

9.9 + 2.3 • 12.9 _ 3.1 _ 139.0 _ --60 Present 77% b

Hoods 1.7 0.5 2.5 0.8 17.9

24.4 6.9 3.8 10.0 236.5 --70 Shed 63%

• • • • •

Source 2.6 1.2 0.5 2.6 35.5

17,18 17,18 17,18,19 17,18 17,18 20,21 a 22 17,18

aAnd Kovacs et al. unpublished data. bThis value is inflated because some harp seal females feed during lactation.

Male harp and hooded seals have different display environments; harp seal males display in the water and hooded seal males display predominantly on the ice surface. Male harp seals mate opportunistically with no prior attendance of females while male hooded seals mate guard. The behaviour of males throughout the breeding season emphasizes the different strategies employed by males of these two species. Harp seal males spend the first half of the breeding season loafing in groups that are dispersed throughout the whelping patch. Males in these single-sex assemblages are extremely closely spaced yet there are no signs of competition or aggression. Male groups readily go to the water if disturbed and are mobile from day to day. When the females that were the first to give birth approach the end of lactation, male behaviour changes. Male groups become much smaller or disperse. Individual males are seen popping up briefly among female clusters where they are immediately met with threats or are directly attacked by females. Additionally, males commence snorting and bubble blowing at holes used by females and they emit a wide variety of elaborate sounds beneath the ice. Once these activities commence in the herd, single males are commonly seen asleep near holes that are less frequently used by females. These males often have fresh wounds. Agonistic encounters in the water become increasingly frequent as time goes on during the second half of the breeding season. These encounters are difficult to characterize because visibility is often minimal, but it appears that male-male interactions are usually brief and involve a great deal of splashing; rolling and biting appear to be principal components in these encounters. The behaviour of male hooded seals is very different than that of male harp seals. Male hooded seals are combative throughout the whelping season. As soon as females commence giving birth, males display to one another and fight to establish proximity to a female. Males use both their hood and their septum as agonistic signals in aggressive encounters that frequently involve extensive pushing, slashing and biting. Vocalization in the air and in water are quite simple and basically involve only a variety of growls of differing intensity. Physical size and strength are important determinants of success and most male-male turnovers at the sites of females

333 involve combat between large males, with the largest usually being the victor [15]. Males that are successful in attending a female at the time she weans her pup leave the ice with her, and presumably mate with her. Males that leave the ice with a female return to the whelping patch within 12 h and resume competitive activities to re-establish with another female [15, Kovacs, Lydersen and Hammill, unpublished data]. The whelping habitat used by female harp seals and their mobile behaviour patterns are such that males are unable to restrict access to females by other males. Thus they are unable to mate guard or otherwise monopolize females. Males display in the water using elaborate vocalizations and potentially underwater acrobatics to attract females or to compete with other males. Wounding patterns on males, concentrated around the hind flippers, ankles and penile area, and limited behavioural observations suggest that fighting is accomplished primarily through biting. If this is the case, agility would be a fundamental component to male success in combat. It is likely that female harp seals exhibit mate choice, but the criteria for such choosing is unclear. LeBoeuf [25] has suggested that aquatic mating means that female choice becomes a more important component of sexual selection. Aquatic chases may be involved or mating success may be determined through a first or last male effect or through sperm competition if females mate multiply during a single season. There are insufficient data to assess which of these strategies might be employed. The whelping habitat chosen by female hooded seals and their pattern of continual attendance during lactation enables hooded seal males to mate guard. Additionally, their extraordinarily short lactation period adds to the EPP. Even if a male remains with individual females throughout lactation he still has the opportunity to pair with several females. Males actively display and fight on the surface of the ice in order to serially attend females during the breeding season which puts a selective premium on large body size and secondary sexual display characters. Males have been documented to attend up to 8 females during a single season (Kovacs, unpublished data) and this is probably not the maximum level of attendance as a single male has been sighted with five different females over a 4-day period [15]. Males return to the whelping patch <12 h after leaving the ice surface with a female (Kovacs, Lydersen and Hammill, unpublished data). Hence, it is likely that some male hooded seals experience a considerable degree of polygny. Males certainly exhibit considerable inter-individual variation in their reproductive success. There is no need to suggest that the mating system displayed by hooded seals is a scaled down version of a previously polygynous system or that the behaviour we currently observe in this species is the result of an artificially skewed sex ratio due to past hunting practices [101. Harp and hooded seal males each respond to the EPP to which they are exposed. Harp seal males are opportunistic and promiscuous and are likely to experience a slight degree of polygyny. Successful male hooded seals mate guard a number of females in a serial fashion through a breeding season and hence experience a greater degree of polygyny. Polygyny potential and physical fighting on a solid substrate lead to sexual selection reinforcing large body size in males. Classical models of

334 avian and mammalian mating systems describe adequately how these two pack-ice breeding species have come to have such different mating patterns.

Acknowledgements Thanks are extended to the many colleagues that have shared harp and hooded seal seasons with me over the last dozen years. Their contributions to both logistics and the development of my ideas are gratefully acknowledged. In particular I thank David Lavigne, Christian Lydersen and Mike Hammill for the their support of my pursuit of individual interests during group programs. I also thank Mike Hammill for access to unpublished data on male harp seal morphometrics from the Gulf of St. Lawrence. Funding agents for the body of work that has supported this MS include the Natural Sciences and Engineering Research Council of Canada (NSERC), the International Fund for Animal Welfare (IFAW), the Department of Fisheries and Oceans, Canada (DFO), and the North Atlantic Treaty Organization (NATO).

References 1. Williams GC. Sex and Evolution. Princeton, NJ: Princeton University Press, 1975. 2. Trivers RL. Parental investment and sexual selection. In: Campbell B (ed) Sexual Selection and the Descent of Man 1871-1971. Chicago: Aldine, 1972;136-179. 3. Clutton-Brock TH. Reproductive Success. Chicago: University of Chicago Press, 1988. 4. Clutton-Brock TH. Mammalian mating systems. R Soc 1989;236b:339-372. 5. Emlen ST, Oring LW. Ecology, sexual selection and the evolution of mating systems. Science 1977;197:215-223. 6. Kleiman DG. Monogamy in mammals. Q Rev Biol 1977;53:39-69. 7. Bartholomew GA. A model for the evolution of pinniped polygyny. Evolution 1970;24:546-559. 8. Boness DJ. Determinants of mating systems in the Otariidae (Pinnipedia). In: Renouf D (ed) Behaviour of Pinnipeds. London: Chapman and Hall, 1991; 1-44. 9. Stirling I. Factors affecting the evolution of social behaviour in the pinnipeds. Rapp P-V Reun Cons Int Explor Mer 1975;169:205-212. 10. Stirling I. The evolution of mating systems in pinnipeds. In: Eisenberg JF, Kleiman DG (eds) Recent Advances in the Study of Mammalian Behaviour. Am Soc Mammal 1983; Spec Publ No. 7:478-527. 11. Lavigne DM, Kovacs KM. Harps and Hoods. Waterloo, ON: University of Waterloo Press, 1988. 12. Kovacs KM. Maternal behaviour and early behavioural ontogeny of harp seals, Phoca groenlandica. Anim Behav 1987;35:844-855. 13. Lydersen C, Kovacs KM. Diving behaviour of lactating harp seal, Phoca groenlandica, females from the Gulf of St Lawrence, Canada. Anim Behav 1993;46:1213-1221. 14. Boness DJ, Bowen WD, Oftedal OT. Evidence of polygyny from spatial patterns of hooded seals (Cystophora cristata). Can J Zool 1988;66:703-706. 15. Kovacs KM. Mating strategies in male hooded seals (Cystophora cristata). Can J Zool 1990;68:2499-2502. 16. Kovacs KM, Lavigne DM. Neonatal growth and organ allometry of Northwest Atlantic harp seals (Phoca groenlandica). Can J Zool 1985;63:2793-2799.

335 17. Kovacs KM, Lavigne DM. Mass-transfer efficiency between hooded seal (Cystophora cristata) mothers and their pups in the Gulf of St. Lawrence. Can J Zool 1992;70:1315-1320. 18. Kovacs KM, Lavigne DM, Innes SI. Mass transfer efficiency between harp seal (Phoca groenlandica) mothers and their pups during lactation. J Zool London 1991;223:213-221. 19. Bowen WD, Oftedal OT, Boness DJ. Birth to weaning in 4 days: remarkable growth in the hooded seal, Cystophora cristata. Can J Zool 1985;63:2841-2846. 20. Oftedal OT, Boness DJ, Bowen WD. The composition of hooded seal (Cystophora cristata) milk: an adaptation for postnatal fattening. Can J Zool 1088;66:318-322. 21. Stewart REA, Webb BE, Lavigne DM, Fletcher F. Determining lactose content of harp seal milk. Can J Zool 1983;61:1094-1100. 22. Oftedal OT, Bowen WD, Widdowson EM, Boness DJ. The prenatal molt and its ecological significance in hooded and harbour seals. Can J Zool 1991 ;69:2489-2493. 23. Oftedal OT, Bowen WD, Boness DJ. Energy transfer by lactating hooded seals and nutrient deposition in their pups during the four days from birth to weaning. Physiol Zool 1993;66(3):412436. 24. Lydersen C, Kovacs KM. Paralysis as a defense response to threatening stimuli in harp seals (Phoca groenlandica). Can J Zool 1994 (in press). 25. LeBoeuf BJ. Pinniped mating systems on land, ice and in the water: emphasis on the Phocidae. In: Renouf D (ed) Behaviour of pinnipeds. London: Chapman and Hall, 1991 ;45-65.

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9 1995 ElsevierScienceB.V. All fights reserved Whales, seals, fish and man

A.S. Blix, L. WallCeand 13. Ulltang,editors

337

C o n s u m p t i o n of cod by the N o r t h w e s t Atlantic grey seal in Eastern C a n a d a M.O. Hammill ~, M.S. Ryg 2 and B. Mohn 3 1Maurice Lamontagne Institute, Department of Fisheries and Oceans, Mont Joli, QC, Canada; 2Royal Norwegian Air Force, Institute of Aviation Medicine, Blindern, Oslo, Norway; and 3Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, N.S., Canada A b s t r a c t . The Northwest Atlantic grey seal is perceived by fishermen as having a negative impact on commercial fish stocks, particularly Atlantic cod. Both the Sable Island and Gulf of St. Lawrence components of this population have increased substantially over the past several decades, such that total population size in eastern Canada in 1993 was estimated at about 140,000 animals. Estimated total consumption of cod by grey seals is estimated to have increased from <6,000 tonnes in 1970 to as much as 39,000-43,000 tonnes in 1993, depending on model assumptions. Eighty percent of the cod consumed are pre-recruits to the commercial fishery. K e y w o r d s : seals, competition with fisheries, model calculations

Introduction

The subject of competition between marine mammals and fishermen for fish often generates considerable controversy with fishermen on one side and environmental groups on the other. Historically, this competition was of limited importance because marine mammals were also harvested for food or other commercial purposes. However, during the last 20 years there has been a marked shift in public attitudes towards the harvest of marine mammals, resulting in a dramatic decline in the demand for their products. As a result of reduced harvests, many populations appear to be on the increase. Also, since marine mammals are often present in areas occupied by commercial fishermen, they are perceived as having a negative affect on a commercial fishery. This negative impact can occur in several ways. First, they damage fishing gear or the quality of fish through the destruction of fish in nets, through the transmission of parasites, which must be removed during processing, and by consuming commercially important species, reducing their availability to the commercial fishery or by consuming important prey species reducing the availability of food resources for commercially harvested species [ 1]. In Canada, the debate surrounding the potential impact of marine mammals on fisheries has focussed on seals. However, seals are not the only consumers and in the debate perhaps consumption by other groups should also be considered, for example many species of seabirds consume species such as capelin and herring, which are important commercially and as prey for other species of fish such as cod. Also, the various species of whales all consume species such as capelin, and herring, which Address for correspondence." M.O. Hammill, Maurice Lamontagne Institute, Department of Fisheries and Oceans, P.O. Box 1000, Mont Joli, QC, Canada, G5H 3Z4.

338 are either fished commercially or are important prey for commercially fished species. The question of prey consumption by seabirds has been examined to some extent [2] but the question of fish consumption by whales has not been addressed in Canada and may not be a trivial one. It is estimated that total fish consumption by the Northeast Atlantic minke whale is similar to that of the Northeast Atlantic harp seal population [3]. If we wish to evaluate the level of competition between seals and commercial fisheries for fish then we need information on the distribution and abundance in time and space of the predators, their energy requirements, and diet. In many ways, the problem can be considered as a new, undocumented fishery. To assess its impact on existing fisheries, we need information on fleet size, target species for the fleet, gear selectivity and discards, total catch of the fleet and distribution of fishing effort and the stocks exploited [4]. Here we examine the consumption of cod (Gadus morhua) by the Northwest Atlantic grey seal (Halichoerus grypus). The Northwest Atlantic grey seal is distributed along the eastern Canadian coast extending as far north as Labrador [5,6]. Although considered to be abundant prior to the 19th century, extensive hunting for oil led to a sharp decline in numbers such that by the beginning of the 20th century [6] grey seals were considered rare and were thought to number in the low thousands [7]. In the Northwest Atlantic, population pupping occurs during late December to early February. Two major whelping colonies are recognized, located on the pack ice in the southern Gulf of St. Lawrence and on Sable Island 160 km off the coast of Nova Scotia (Fig. 1) [7]. During much of the year, there is considerable mixing between animals from the two groups. However, during the whelping period little interchange between the two groups occurs [5,6].

Seal Population Model Zwanenburg and Bowen [8] used a Leslie matrix to model both the Gulf and Sable Island grey seal populations in eastern Canada. They assumed that grey seals lived to a maximum age of 34 years and that males and females had the same natural mortality rates. Mohn and Bowen [9] built on the approach used by Zwanenburg and Bowen [8] by constructing a deterministic, age-structured model similar to a Leslie matrix model that assumes different rates of natural mortality in males and females after age 5 and different rates for the Gulf and Sable Island components of the population. In the model, all seals are assumed to die at 40 years of age. A two parameter model for each herd was then fit to pup production estimates from the Gulf of St. Lawrence based on results from a series of mark recapture experiments conducted during 1984-1990 [10] and complete enumerations of pups born on Sable Island during 1977-1990 [8,9,11]. The two populations have undergone two very different population trajectories since 1970, with the Gulf population increasing at a rate of approximately 9%, while the Sable Island component is increasing at a rate of

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almost 13% (Fig. 2). At the beginning of this period, 69% of the population was of Gulf origin. However, by 1993, less than 40% of the total population of approximately 143,000 animals was of Gulf origin. Differences in the trajectories of the two groups result from the effects of a government sponsored cull of Gulf animals on the whelping patch between 1967 and 1983 [8] and probable higher pup mortality rates of animals born on the less stable pack-ice in the Gulf of St. Lawrence.

S e a s o n a l D i s t r i b u t i o n of A n i m a l s

Seasonal distributions of each of the herds have been inferred from tagging studies, and aerial observations [5-7,12]. For the most part, outside of the distribution of adults on the whelping grounds, quantitative information on the distribution of animals is not available. For the Sable Island herd, 90% of the animals were assumed to be on the Scotian shelf during the first quarter (January-March). April-June is considered to be a dispersal period [5], consequently 50% of the animals were assumed to remain on the Scotian shelf, 25% moved into the Gulf, and the remaining 25% were dispersed throughout other areas in Atlantic Canada. During the third quarter, animals were still assumed to be widely dispersed with 50% of the Sable herd still found on the Scotian shelf, 15% in the Gulf of St. Lawrence and the

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remaining 35% in the other zones. During the final quarter (October-December), 80% of the herd was located on the Scotian shelf, 5% in the Gulf and 15% in other regions. For the Gulf grey seal herd, during the first quarter 70% of the animals were assumed to be in the southern Gulf, and the remaining 30% were assumed to be distributed evenly between the Northern Gulf, the Scotian shelf, and other zones. For the remainder of the year, tag returns and aerial observations [5,6,12] suggested two quite different distribution patterns. Consequently, consumption was estimated assuming two different distributions for the Gulf herd during the remainder of the year. In the first scenario, the tagging data suggested that the seals were evenly distributed between the northern and southern Gulf during the second and third quarters. For these two quarters, 20% of the herd was located on the Scotian shelf, 35% in the Northern Gulf, 35% in the southern Gulf, and 10% were located in other zones. For the fourth quarter, 70% of the animals were assumed to be in the southern Gulf, and the remaining 30% distributed evenly between the northern Gulf, Scotian shelf, and other zones. The aerial survey data [12] suggested that more animals were located in the northern Gulf than in the southern Gulf, consequently for the second scenario, 60% of the animals were assumed to be in the Northern Gulf, 10% in the southern Gulf, 10% in other zones and 20% on the Scotian shelf. During the fourth

341 quarter, 50% were assumed to be the Northem Gulf, 30% in the Southem Gulf, 10% on the Scotian shelf and 10% in other zones.

Energy Requirements Several models have been developed to estimate energy requirements of seals [1315]. We modelled individual energy requirements taking into account seasonal changes in energy expenditure including moult and reproduction. The model is implemented as a spreadsheet using Microsoft Excel, where energy requirements are calculated on a daily basis and summed over quarterly periods. The basic inputs are sex (male, pregnant females and nonpregnant females) and age. For each day, the metabolizable energy requirements for basal metabolic rate, growth, reproduction and activity are calculated. The sum of BMR and activity is compared with the minimum heat production required for thermal stability and the largest of the two values is set as the maintenance requirement. To this net energy is added an "apparent" heat increment of feeding (HIF). This apparent heat increment of feeding is the heat increment of feeding minus the difference between the minimum heat production for thermal stability and the sum of B MR and activity. This ensures that the heat increment of feeding can be used by the animal to maintain thermal stability. The model is driven by body mass and fat content. Body mass is calculated from a Gompertz growth equation (Hammill, unpublished data). Seasonal changes are implemented by splitting the year into periods of breeding, fat buildup, moulting, fat buildup and next breeding season. Age at first birth for females and age at sexual maturity in males were set at 5 and 6 years, respectively (Hammill and Gosselin, unpublished data). Total growth rates and changes in lean mass and sculp weights are adjusted to fit observed seasonal changes from biological data. Basal metabolic rates (BMR) were calculated using: BMR (joules)= 3.4 Mass (kg) ~ [16]. Energy requirements for activity were calculated as a multiple of BMR, multiplied by the fractions of the day spent in each activity. Minimal heat loss was calculated as a function of body length, body and blubber mass, blubber conductivity and skin temperatures [17]. For an animal in the water the skin temperature was set to equal the water temperature, since this difference will be small [17]. Energy requirements for growth and fattening were calculated as the sum of the gain in core mass multiplied by energy content of protein (23 MJ kg -~) and protein content of core mass (27%) and the gain in blubber mass multiplied by energy content of fat (39.5 MJ kg -1) and the fat content of the blubber (90%). Information on pup mass at birth, growth and mass at weaning, female mass loss and changes in body composition during lactation were taken from [17-20]. The duration of male mass loss during the breeding season was set assuming that male grey seals lose 25% of their mass The rate of mass loss followed the regression of Fedak and Anderson [21] which is similar to the rates of mass loss observed in males on the whelping patch [22]. During the breeding season, adults are assumed to spend 80% of their time on the ice, with a Kleiber factor of 2 and 4 for females

342 and males, respectively. The remaining time was spent searching in the water with a Kleiber factor of 2.5. During the moult animals are assumed to spend 95% of their time on land with a metabolic rate of 1.62 x Kleiber corresponding to a decrease of 19% from 2 x Kleiber [23]. The remaining 5% of the time was spent searching, or cruising, with a Kleiber factor of 2.5. Outside of the breeding or moult period the activity budget was set as 13% hauled out, 41% resting, 32% cruising, and 14% of the time was spent searching [24]. The Kleiber factors during haul-out and rest outside of the breeding season were set at 1.66.

Diet

Prey size and composition of grey seal diets Information on diet is based largely on the identification of hard parts from stomach or faecal samples. Northwest Atlantic grey seals feed on a wide range of demersal and pelagic species. Considerable variability is seen between seasons, between locations and between years. Based on frequency of occurrence, grey seals in the northern Gulf feed heavily on capelin, followed by species such as cod and lumpfish early in the summer. Later in the summer, there is a shift in diet, as grey seals start to consume more cod, herring and mackerel [25-26] (Proust and Hammill, unpublished data). In the southem Gulf they feed on herring, cod, rays and flatfish [7,27]. In the Atlantic, herring, cod, hake, pollock and sand lance are the major prey species [28,29]. Traditional analyses of diet have expressed prey abundance as frequency of occurrence. However, relative energetic contribution or contribution by weight appears to be a more appropriate approach when addressing the issue of total consumption. This approach requires that diets be reconstructed using otolith-length or weight relationships. Since not all items consumed are identified or can be reconstructed we assumed that 20% of the diet with a caloric value of 0.8 kcal/g was not accounted for and adjusted the reconstructed diets accordingly. Bootstrap samples were drawn from the northern Gulf and Scotian shelf samples [9] to determine a mean diet for these areas. Bootstrapping [30] is a computer intensive technique in which the underlying data are resampled, the analysis repeated and the results compiled. We have 13 estimates of seal diets for the Scotian Shelf [9,2829] and 4 for the Northern Gulf [25,26] (Proust and Hammill, unpublished data). Our bootstrapping procedure resampled with replacement the 13 or the 4 possible diets to produce a mean percent cod and mean energy density of the diet for each quarter of the simulation. This procedure was repeated 100 times and the cod consumptions compiled so their modes and 95% confidence limits were estimated (Fig. 2). Diet information from the southern Gulf is limited to 4 stomachs from the Magdalen Islands and 11 stomachs from Amet Island. No information on diet is available for grey seals from the western Gulf, from parts of the Cape Breton east coast. Similarly, diet information for other areas in Atlantic Canada is not available or is very

343 25000 "~ 0 o

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Fig. 3. Estimated cod consumption in the Gulf of St. Lawrence assuming different distributions of Gulf

grey seals. Distribution 1 (a) and distribution 2 (b).

limited. For these samples we assumed that cod comprised 10% by weight of the diet and the average energy density of the diet was 1.5 kcal/g. Depending on the distribution of animals, cod consumption by grey seals in the Gulf of St. Lawrence has increased from less than 5,000 tonnes in 1970, to almost 20,000 tonnes in 1993 (Fig. 3). Cod consumption on the Scotland shelf and in other regions has increased from around 5,000 tonnes to around 20,000 tonnes in 1993 (Fig. 4). Total consumption of cod by grey seals in Atlantic Canada is estimated to have increased from less than 10,000 in 1970, to as much as around 40,000 in 1993. Looking at the size distribution of fish consumed, we can see that grey seals are feeding heavily on fish 10--40 cm in length [25,27-29]. For cod they are feeding

344

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primarily on pre-recruits to the commercial fishery. Forty-four percent of cod consumed were <30 cm in length, 36% were 31-45 cm and only 20% >45 cm.

Discussion Cod stocks in eastern Canada are currently at low levels with a moratorium on fishing of some stocks such as those in the Gulf of St. Lawrence. Within this context seals in this area consume almost 20,000 tonnes of cod most of which are prerecruits to the fishery. Although this represents a significant potential loss to the commercial fishery it is likely that some compensatory mortality occurs which would reduce this impact. Attempts to assess this impact are hindered by the lack of information on mortality in small cod.

345 In arriving at these estimates we have assumed that: (1) the Northwest Atlantic grey seal population has been increasing at an exponential rate since 1970; (2) the observed diets used accurately reflect the proportion of cod in grey seal diets; (3) the seasonal distribution of grey seals can be described by the distributions outlined above; (4) grey seal energy requirements can be adequately described by either of the energy budget models; (5) the functional form of seal/cod interactions can be described by a demand model. In our preliminary analysis we have not attempted to examine the effects of uncertainties in our assumptions on our model output. However, some discussion of these assumptions and the confidence that can be placed in each assumption is warranted. (1) We have assumed that the grey seal population has increased (and is continuing to increase) at an exponential rate. At some point, density-dependent changes in population parameters will alter population trajectories, but recent information on reproductive parameters do not indicate that such changes are yet occurring (Hammill, unpublished data). For the Sable Island herd current information indicates that the population as indicated by changes in pup production has increased exponentially during the period 1977-1993. In the Gulf, there is much greater uncertainty surrounding population estimates, due to a lack of information on population size over time and the possibility of more variable pup mortality rates associated with this ice breeding herd. Although we have presented changes in the population since 1970 including the effects of a government cull of this herd during the 1970s and 1980s, these estimates are extrapolations using pup production estimates available for 1984-1990. (2) Diet information from stomach and faecal samples accurately reflects the proportion of cod in grey seal diets. Species composition in marine mammal diets is largely determined by identification of hard parts in stomachs or faeces. Some of the difficulties associated with this approach are discussed by Mohn and Bowen [9]. Quantitative information on grey seal diets in eastern Canada has been available for some areas since 1983 (Northern Gulf) and for other areas such as Nova Scotia since 1988. Although these samples suggest that there is some seasonal and interannual variability in the fraction of cod in the diet, sample sizes are too small to provide a more complete analysis throughout the study period. Consequently, we have assumed that cod consumption does not change throughout the year and have attempted to evaluate some of the uncertainty in this assumption by bootstrapping the proportion of cod in the diet and mean energy density to provide confidence intervals for Scotian shelf and Northern cod consumption. Unfortunately, for much of the grey seal's range including the southern Gulf, east coast of Cape Breton Island, the Newfoundland coast, and the Bay of Fundy, quantitative diet information is limited or lacking completely. For some of these areas, there is some qualitative diet (frequency of occurrence) information available, but this index tends to underestimate the importance of cod in the diet relative to percent weight [27]. For the southern Gulf and "other", we have assumed that cod comprises 10% by weight and an average energy density of the diet of 1.5 kcal/g. This assumption lies at the lower end of the range of

346 6%-46% and 1.2-2.1 kcal/g seen in other studies [9] (Hammill, unpublished data). Frequency of occurrence data from the southern Gulf indicate that cod was found in 13.6% of a sample of 89 stomachs [26] suggesting that our assumption of 10% cod in the diet is not unreasonable. (3) The seasonal distribution of grey seals can be described by the distributions outlined above. Our estimates of cod consumption changed markedly with changes in assumed seasonal distribution of animals in the Northern Gulf owing to the higher fraction of cod in grey seals in this area. As outlined earlier, outside of the whelping period when virtually all breeding animals are concentrated around two major whelping areas, quantitative information on the seasonal distribution of grey seals is not available. Current information on distribution has been obtained from tag returns and in the Gulf from aerial surveys. Tag return information is of limited use because hunting effort cannot be quantified throughout Atlantic Canada [5,6]. Although much of the information involved in estimating cod consumption by Atlantic grey seals is likely to be refined as information on reproductive rates, diet, size at age and population size is refined, quantitative information on the seasonal and geographic distribution of grey seals in the different regions will not be available in the near future. Using visual aerial surveys to count hauled out animals may provide some information on relative distribution throughout their range [12]. However, this approach will not provide information on whether a hauled out animal is of Gulf of St. Lawrence or Sable Island origin. Additional information is required on the fraction of animals located in inshore versus offshore regions and the proportion of animals hauled out on land versus animals in the water, before this approach can be developed further. Further advances in this area will require an increased effort in the deployment of satellite and time depth recorder telemetry. Early deployment of satellite tags suggests that much of the adult grey seal population leaves the Gulf at the end of the whelping period, moving onto the Scotian shelf in the Atlantic where they may spend several months [31 ]. (4) Grey seal energy requirements can be adequately described by an energy budget model. Here we attempted to model closely the seasonal changes in energy requirements owing to changes in body mass, the effects of reproduction, and incorporated available information on activity. Although intuitively this approach may appear to be more appropriate, the incorporation of additional factors increases model complexity and may give a false sense of model precision since each additional parameter is also measured with error. For example by including in the model the costs of reproduction, total energy requirements for the population increase by only 5% [15] (this study). In addition, although our model suggested that seasonal changes in energy consumption occur, with 20% and 22% of the energy consumption occurring in the first two quarters and 30% and 28% of the annual energy consumption occurring during the last two quarters, the application of a complex energy budget model may not be appropriate if information on seasonal changes in diet is not available. We do not wish to suggest that complex models are not required, indeed their output is important when cross checking model output and to verify whether factors such as the costs of reproduction or seasonal changes in energy re-

347 quirements should be incorporated as simple correction factors into simplified models. (5) The functional form of seal/cod interactions can be described by a demand model. For this analysis we chose a demand model to describe the functional form of the interaction between seal and cod for the analysis of potential impacts of seals on cod; i.e. we have assumed that on average seals will find a certain amount of cod irrespective of its relative abundance. Because the seal population varied by about a factor of ten over the period of investigation, the cod consumption is dominated by seal abundance. This model is of course less likely as the amount of cod compared to other prey species decreases to very low levels while seal herds increase. Unfortunately for most prey items, there are neither assessments nor in many cases even reliable survey estimates. Until supporting data become available, any model chosen will be rather speculative and sensitivity to assumptions about form would be the most profitable analysis. Despite uncertainties in the data over the period covered by the model, the strength of our study is that extensive data on both population size and diets were collected during the most recent period (1983-1992) and little extrapolation is required to assess the current situation. It is only when we attempt to project backwards prior to 1980 or beyond 1992 that the form of the applied model becomes more important. Within the context of the above assumptions, this analysis suggests that cod consumption has increased to around 40,000 tonnes in Atlantic Canada. Although much of this consumption occurs on the Scotian shelf, the estimates of cod consumption by region must be considered to be preliminary since the seasonal and geographic coverage of diet samples throughout the grey seal's range and quantitative information on the seasonal distribution of animals are limited. Much of the cod consumption by grey seals consists of pre-recruits to the commercial fishery. From the diet reconstructions, grey seals in Atlantic Canada would consume 15,000-20,000 tonnes of <30 cm cod, 13,000-16,000 tonnes of 31-45 cm cod and 7,000--9,000 tonnes of >45 cm cod. Attempts to assess the impact of grey seal cod consumption on cod stocks are beyond the scope of this paper. Although grey seals consume large numbers of small cod (pre-recruits), which represent a significant potential loss to the industry, it is also likely that some compensatory mortality occurs which would reduce this impact. References 1. Malouf A. Seals and sealing in Canada. Report of the Royal Commission on seals and sealing in Canada. Vol 3. Department of Supplies and Services, Ottawa, Canada, 1986, 590 pp. 2. Cairns DK, Chapdelaine G, Montevecchi WA. Prey exploitation by seabirds in the Gulf of St. Lawrence. In: Theriault J-C (ed) The Gulf of St. Lawrence: Small Ocean or Big Estuary. Can Spec Publ Fish Aquat Sci 1991;113:277-291. 3. Markussen NH, Oritsland NA. Food energy requirements of the harp seal (Phoca groenlandica) population in the Barents and White Sea. In: Sakshaug E, Hopkins CCE, Oritsland NA (eds) Proceedings of the Pro Mare Symposium on Polar Marine Ecology, Trondheim, May 1990. Polar Res 1991; 10:603--608.

348 4. Harwood J. Assessing the competitive effects of marine mammal predation on commercial fisheries. In: Payne AIL, Brink L, Mann KH, Hilborn R (eds) S Afr J Mar Sci 1992;12:689--693. 5. Stobo WT, Beck B, Horne JK. Seasonal movements of grey seals (Halichoerus grypus) in the Northwest Atlantic. In: Bowen WD (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Can Bull Fish Aquat Sci 1990;222:171184. 6. Lavigueur L, Hammill MO. Distribution and seasonal movements of grey seals, Halichoerus grypus, born in the Gulf of St. Lawrence and eastern Nova Scotia shore. Can Field Nat 1993; 107:329-340. 7. Mansfield AW, Beck B. The grey seal eastern Canada. Department of Environment, Fisheries and Marine Service, Technical Rep 704, 1977, 81 pp. 8. Zwanenburg KCT, Bowen WD. Population trends of the grey seal (Halichoerus grypus) in eastern Canada. In: Bowen WD (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Can Bull Fish Aquat Sci 1990;222:185-197. 9. Mohn R, Bowen WD. A model of grey seal predation om 4VsW cod and its effects on the dynamics and potential yield of cod. DFO Atlantic Fish Res Doc 1994;94/75:25 pp. 10. Hammill MO, Stenson GB, Myers RA, Stobo WT. Mark-recapture estimates of non-Sable Island grey seal (Halichoerus grypus) pup production. CAFSAC Res Doc 1992;92/91:15 pp. 11. Stobo W, Zwanenburg KCT. Grey seal (Halichoerus grypus) pup production on Sable Island and estimates of recent production in the Northwestern Atlantic. In: Bowen WD (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Can Bull Fish Aquat Sci 1990;No. 222:171-184. 12. Clay D, Nielsen G. Grey seal (Halichoerus grypus) distribution during 1983/84 in the Gulf of St. Lawrence as observed by aerial survey. Can MS Rep Fish Aquat Sci 1985;1836:iii+ 8p. 13. Lavigne DM, Barchard W, Innes S, Oritsland NA. Pinniped bioenergetics. In: Mammals in the Seas. FAO Fish Serv 1982;5(IV):191-235. 14. Oritsland NA, Markussen NH. Outline of a physiologically based model for population energetics. Ecol Model 1990;52:267-288. 15. Olesiuk PF. Annual prey consumption by harbor seals (Phoca vitulina) in the Strait of Georgia, British Columbia. Fish Bull 1993;91:491-515. 16. Kleiber M. The Fire of Life (2nd edn). New York: Wiley, 1975. 17. Ryg M, Lydersen C, Knutsen LO, Bj~rge A, Smith TG, Oritsland NA. Scaling of insulation in seals and whales. J Zool London 1993;230:193-206. 18. Baker SR, Barrette C, Hammill MO. Mass transfer during lactation of an ice-breeding pinniped, the grey seal (Halichoerus grypus), in Nova Scotia, Canada. J Zool London (in press). 19. Lydersen C, Hammill MO, Kovacs K. Milk intake, growth and energy consumption in pups of ice breeding grey seals (Halichoerus grypus) from the Gulf of St. Lawrence, Canada. Can J Zool (in press). 20. Iverson SJ, Bowen WD, Boness JD, Oftedal OT. The effect of maternal size and milk energy output on pup growth in grey seals (Halichoerus grypus). Physiol Zool 1993;66:61-68. 21. Fedak MA, Anderson SS. Estimating the energy requirements of seals from weight changes. In: Huntley AC, Costa DP, Worthy GAJ, Castellini MA (eds) Marine Mammal Energetics. Lawrence KS: Allen Press, 1987;205-226. 22. Tinker MT. The reproductive behaviour and energetics of male grey seals (Halichoerus grypus) breeding on a landfast substrate. M.Sc. thesis. University of Waterloo, Waterloo, Ontario, Canada, 1993. 23. Ashwell-Erickson S, Fay FH, Eisner R. Metabolic and hormonal correlates of molting and regeneration of pelage in Alaskan harbor and spotted (Phoca vitulina and Phoca largha). Can J Zool 1986;64:1086-1094. 24. Thompson D, Hammond PS, Nicholas KS, Fedak MA. Movements, diving and foraging behaviour of grey seals (Halichoerus). J Zool London 1991;224:223-232.

349 25. Murie DJ, Lavigne DM. Growth and feeding habits of grey seals (Halichoerus grypus) in the northwestern Gulf of St. Lawrence, Canada. Can J Zool 1992;70:1604-1613. 26. Benoit D, Bowen WD. Summer diet of grey seals (Halichoerus grypus) at Anticosti Island, Gulf of St. Lawrence, Canada. Can Bull Fish Aquat Sci 1990;222. 27. Benoit D, Bowen WD. Seasonal and geographic variation in the diet of grey seals (Halichoerus grypus) in eastern Canada. In: Bowen Wd (ed) Population Biology of Sealworm (Pseudoterranova decipiens) in Relation to its Intermediate and Seal Hosts. Can Bull Fish Aquat Sci 1990;222:215226. 28. Bowen WD, Lawson JW, Beck B. Seasonal and geographic variation in the species composition and size of prey consumed by grey seals (Halichoerus grypus) on the Scotian Shelf. Can J Fish Aquat Sci 1993;50:1768-1778. 29. Bowen WD, Harrison GD. Offshore diet of grey seals Halichoerus grypus near Sable Island. Mar Ecol Prog Ser 1994;112:1-11. 30. Efron B. The Jackknife, the Bootstrap and Other Resampling Plans. SIAM, PA, USA, 1982, 92 pp. 31. Hammill MO, Kovacs K, Lydersen C. Postbreeding movements of western Atlantic grey seals as revealed by satellite telemetry. Tenth Biennial Conference on the Biology of Marine Mammals. Galveston, TX, USA,1993:p57.

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9 1995ElsevierScienceB.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand ~. Ulltang,editors

351

Digestive physiology of minke whales S.D. Mathiesen, T.H. Aagnes, W. S~rmo, E.S. Nordc~y, A.S. Blix a n d M.A. Olsen Department of Arctic Biology and Institute of Medical Biology, University of Tromsr Tromsr Norway Abstract. The anatomy and principal function of the gastro-intestinal tract of minke whales were investigated. The stomach consists of four compartments, including an initial non-glandular forestomach followed by a glandular fundic chamber, a connecting chamber and a pyloric chamber. The length of the small intestine of minke whales is short, only four times body length, and the colon and caecum are poorly developed. The forestomach is small, containing between 5 and 801 of contents, with as much as 24.8% dry matter (DM). High population densities of anaerobic bacteria were found in the forestomach fluid, and adherent to the food particles, pH in the forestomach fluid ranged between 5.36 and 7.43, and the concentration of volatile fatty acids (VFAs) ranged between 49 and 486 mM. Based on these results we conclude that minke whales primarily utilize the prey they eat by microbial digestion. The contribution from VFAs to the daily energy requirements of minke whales seems to be of less importance than in ruminants. The multi-chambered stomach probably is an adaptation which increases passage time and, hence, microbial and enzymatic digestion. We suggest that the relatively small size of the stomach of minke whales, compared with that of ruminants, reflects their carnivorous diet, but does not necessarily indicate any reduced importance of the forestomach microbial digestion. Key words: baleen whales, gastro-intestinal tract, anatomy, function, stomach compartments

Introduction

The principal function of the gastro-intestinal tract of animals is to provide for digestion and absorption of nutrients. In the terrestrial ecosystem a variety of different adaptations for assimilation of food have been developed. Carnivores have a relatively simple stomach. In such animals the stomach is essentially a pouch-like structure which contains glands which secrete HC1 and pepsinogen. The small intestine, caecum and large intestine are short and uncomplicated. In terrestrial ecosystems, herbivorous animals have been very successful. They have developed stomachs and intestinal modifications which enable them to utilize plant cell wall polysaccharides such as cellulose and hemicellulose. The cellulose (1--4)-fl linked glucoside unit is one of the most abundant organic compounds available to terrestrial animals. For unknown reasons vertebrates have not developed the capacity to produce enzymes capable of hydrolysing plant cell wall polysaccharides, such as cellulose. The basis for the ability to utilize these dietary components is the symbiotic relationship between the host animal and the microbial population in the gastro-intestinal tract. In ruminants, the stomach has evolved into four chambers where the dominant organ, the rumen, provides for extensive pregastric microbial

Address for correspondence: S.D. Mathiesen, Department of Arctic Biology, N-9037 Tromsr Norway. Tel: +47 7 76 44871; Fax: +47 7 76 45770.

352 fermentation of structural polysaccharides [1,2]. The development of a forestomach system allows retention of food particles and growth of anaerobic bacteria. In the marine ecosystem the cellulose analogy is chitin, a major structural component of algae, plankton and crustaceans. Chitin is the (1--4)-r-linked unbranched homopolymer of N-acetyl-D-glucosamine. Gooday [3] estimated both its annual production and standing crop to be in the order of 10-100 billion tons. The energy available from the chitin biomass in the ocean supports most marine ecosystems. However, in fish like rainbow trout (Salmo Gairneri), chitin is poorly digested, even though chitinolytic enzymes have been identified [4]. The only explanation for this finding is that the simple gastro-intestinal system found in most fish, is too simple and does not allow enough retention of food particles for microbial fermentation. According to Gaskin [5], a great increase in the number of mammals took place during the palaeocene and ecocene. The local pressure on terrestrial feeding areas probably was intense, with one population after another reaching a state of overabundance and subsequent collapse. Interactions within riverside communities were undoubtedly very dynamic and always in a state of flux. Exertion of such pressures on ancestral populations of whales may well have stimulated them to go to sea to exploit new vacant niches of food. This implies that ancestral whales were herbivores in contrast to seals, which have developed from camivorous creodonts [5]. Molecular evidence for the inclusion of cetaceans within the order of Artiodactyla has recently been found [6]. Few investigations have focused on the digestive functions of marine mammals, but it appears that the anatomy and function of the gastro-intestinal tract of modem whales and seals reflect their evolutionary origin [715]. Large baleen whales have a multi-chambered stomach system [9,14,15] which resembles that of ruminants [ 1]. The functional organization of the baleen whale stomach, however, is somewhat different from that of ruminants. The first three chambers of the ruminant stomach are nonglandular, followed by a gastric chamber. In whales only the initial chamber is nonglandular, and the multi-chambered arrangement primarily involves compartmentalization of the glandular stomach. The north Atlantic minke whale (Balaenoptera acutorostrata) and the harp seal (Phoca groenlandica) seasonally share the same geographical area where they feed on crustaceans, and fish, such as herring (Clupea harengus), capelin (Mallotus villosus) and cod (Gadus morhua) [ 16-23]. In the Antarctic, however, the minke whale is known to feed exclusively on pelagic crustaceans [24]. Information on the structural and functional features of the digestive systems of these animals obviously is of major importance for the understanding of their ability to utilize the food they eat.

Anatomy The stomach of minke whales consists of four compartments, including an initial nonglandular forestomach followed by a glandular fundic chamber, a connecting

353

Har

I

-

.,

Minke whale

Fig. 1. Gastrointestinal tracts of a harp seal (120 kg) and a minke whale (7000 kg). The minke whale intestine is 4 x body length, while the harp seal intestine is 14 x body length. Bar = 40 cm.

chamber and a pyloric chamber [25] (Fig. 1). The forestomach is lined by a white mucosa, composed of a keratinized stratified squamous epithelium. The epithelial lining resembles that of the rumen of ruminants [26] although it lacks papillary projections. Organization of the stomach in minke whales is therefore similar to that reported for larger baleen whales [9,13,27-29]. The mean tissue wet weight of the forestomach in minke whales contributes 10% of tissue wet weight of the total gastro-intestinal tract, compared to as much as 60% in ruminants, like the reindeer (Rangifer t. tarandus) [25] (Mathiesen, unpublished) (Table 1). The in situ contents of the forestomach of minke whales (body mass 2000-7000 kg) range between 5 and 80 1. The in situ wet weight of the rumen contents in ruminants, such as reindeer (75 kg) eating a grass diet in summer varied between 12 and 18% of body mass (Mathiesen, unpublished). The tissue wet weight of the second stomach compartment, the fundic chamber, is approximately 14% of the total weight of the gastointestinal system (Table 1). The entire inner surface of the fundic chamber is lined with columnar mucous cells. Gastric pits lined with columnar mucous cells provide an entrance into the glands throughout the fundic chamber. The mucosal lining of the main fundic chamber of minke whales possesses gastric glands with parietal cells and chief cells [25]. The orifice connecting the forestomach with the fundic chamber is rather large (average diameter 28 cm), compared to the reticulo-omasal orifice in ruminants where only plant fibers less than 2 mm are allowed to pass [1]. Thus, it seems likely that large volumes of digesta including fish bones of considerable size, may easily enter the

354 Table 1. Mean tissue wet weight of the different compartments of the gastro-intestinal system in percent of the total gastrointestinal tract a Compartment

Reindeer (n = 10)

Minke whale (n = 3)

Harp seal (n = 12)

Forestomach(s) Glandular stomach(s) Small intestine Caecum Large intestine

60.1 5.7 19.8 1.5 10.6

10.4 16.8 63.3 0.8 8.7

27.0 67.6 0.2 5.3

a Data from Mathiesen et al. (unpublished); Olsen et al. [25,30].

fundic chamber to be further digested by acids and enzymes. The fundic chamber, the connecting chamber, and the pyloric chamber correspond to the abomasum in ruminants and to the stomach of monogastric animals, such as the harp seal. In minke whales the glandular stomachs comprise 17% of the tissue wet weight of the GI-tract compared to 6% in ruminants, such as the reindeer, and 27% in the harp seal. The tissue wet weight of the total stomach system relative to body mass in minke whales and seals is similar [30] (Table 1). The narrow orifice of the connecting channel (Fig. 2) probably prevents the passage of large components, such as fish bones from the preceding chamber, until they are acted upon by gastric juices and broken down. The proximal portion of the duodenum consists of a duodenal ampulla, which is a dilated sac with less capacity than the fundic chamber. Histological analysis of the tissue has revealed that the mucosa is similar to that of the pyloric chamber. The duodenal ampullae leads directly into the duodenum proper. The length of the small intestine ranges from 16 to 36 m being on average four times the body length [25]. In harp seals, the length of the small intestine ranges between 20 and 25 m, being on average 14 times the body length [30] (Fig. 2). The lengths of the small and the large intestines measured in minke whales in percent of total length of the intestines were 89 and 11%, respectively, while in harp seals the corresponding values were 97% and 3%, respectively. In ruminants, such as the reindeer, with a forestomach fermen-

r

ps

Fig. 2. Illustration of the minke whale stomach and cranial duodenum, showing the forestomach (FS), the fundic chamber (FU), the connecting channel (cc), the pyloric chamber (PY), the pyloric sphincter (ps) and the duodenal ampulla (DA).

355 tation of plant polysaccharides, the small intestine is 24 m which is approximately 12 times body length (Mathiesen, unpublished). In reindeer the contribution of the small and the large intestine to the total length of the intestines is 71 and 29%, respectively (Mathiesen, unpublished). Although the relative length of the intestines in the minke whale is short compared to that of harp seals [25,30], the mean tissue wet weight in percent of total gastrointestinal tract wet weight is not very different, being 63 and 68%, respectively. The absolute length and tissue wet weight of the caecum in both the minke whale and the harp seal were small, the length being on average only 24 cm and 35 cm, respectively [25,30]. Based on these observations, we conclude that the hindgut of minke whales and harp seals is of minor importance.

Function

The role of the cetacean forestomach in digestion has been disputed. The forestomach may function as a temporary storage chamber for larger quantities of ingested food, and an extensive muscularis externa indicates that it also grinds or chums the contents mechanically [9]. Keratinization may protect the forestomach wall against mechanical damage by the prey, which in mysticetes is filtered from the sea with the baleen plates and swallowed intact. The composition of the forestomach contents of minke whales vary from undigested to extensively dissolved food. This indicates that digestion is initiated in the forestomach, even though digestive glands are absent [25]. The dry matter content in the forestomach varies between 14 and 25% [25]. The chemical composition of the forestomach contents of minke whales is much different from that of herbivorous ruminants. In herring-eating minke whales, the protein and lipid contents as percent of the dry matter contents were as high as 40% and 59%, respectively, compared to 73% protein and 40% lipid in the krill-eating minke whales [31]. High concentrations of anaerobic bacteria in the forestomach fluid of minke whales were found [31,32] (Mathiesen, unpublished). The number of bacteria growing in an anaerobic habitat simulating medium [31] ranged between (7145) • 10s bacterial cells per ml forestomach fluid in herring-eating whales, between (1-12) x 10s bacterial cells per ml in krill eating whales, and 3 x 10s bacterial cells per ml forestomach fluid in one capelin-eating whale. These numbers are comparable to the total number of anaerobic bacteria found in the rumen contents of ruminants [1,33]. Transmission electron microscopic analysis of the forestomach fluid revealed high numbers of bacteria with different morphology (Fig. 3). By use of scanning electron microscopical analysis, Olsen et al. [31 ] were able to show that bacteria with different morphology were attached to food particles obtained from the forestomach of herring-eating whales, which indicates that the bacteria actually attack and digest the prey. In herring-eating whales, bacterial species such as Lactobacillus spp., Streptococcus spp. and Ruminococcus spp. were the most common strains. All bacterial strains isolated from the prey using similar microbiological

356 techniques had phenotypic patterns different from those of the strains isolated from the bacterial population in the forestomach, indicating that the microbiota is indigenous to the forestomach of the whales [31 ]. In krill-eating whales, bacterial strains such as Lactobacillus spp., dominated in one whale, while strains of Bacteroides spp., Clostridium spp. and Streptococcus spp. dominated in another (Mathiesen, unpublished). Of the isolated bacterial strains from the forestomach fluid of one whale, 47% were able to hydrolyze chitobiose, while 5 of 37 strains were chitinolytic. Some of the chitinolytic bacteria were able to produce lactate. By use of a selective medium for proteolytic, lipolytic and N-acetyl glucosamine-using bacteria, bacterial populations as high as 3 x 10 9, 1 x 10 9 and 18 x 10 9 bacterial cells per ml forestomach fluid were isolated from krill-eating minke whales (Mathiesen, unpublished). The pH in the forestomach contents of minke whales as measured immediately after death, varied between 5.95 and 6.69 (n = 18) [25], which is comparable to that found in the fermentation chamber of herbivorous mammals [1]. In herring-eating minke whales, the pH of the forestomach was 5.36-6.87, compared to 6.17-7.34 in krill-eating animals [31] (Mathiesen, unpublished). High concentrations of volatile fatty acids (VFAs), such as acetate, butyrate and propionate, have been found in the forestomach of large baleen whales [10,11]. In minke whales, the concentration ranged between 49 and 486 mM in the forestomach fluid (Table 2). However, Olsen

Fig. 3. Transmission electron micrograph of strained forestomach contents from a herring-eating minke whale, showing bacteria with different morphology, some surrounded by a glycocalyx (arrows). Bar = 1/~m.

357 Table 2. Concentration of volatile fatty acids (VFAs) (n = 8) and anaerobic bacteria (n = 4) in the forestomach fluid of minke whales

VFAs (mM)a

Median Range

Total

Acetate

Propionate Butyrate

94 49-486

65 28-332

12

5-66

21

12-89

Viable bacterial cells (109/ml)b 3.7 0.7-14.5

a Data from Olsen and Mathiesen (unpublished) and Mathiesen et al. (unpublished). bData from Olsen [31].

and Mathiesen (unpublished) were able to show that bacterial fermentation of prey in the forestomach varied depending on the volume and quality of the digesta. In ruminants much of the VFAs diffuse across the rumen wall [34] and some 70% of the ingested metabolizable energy passes through the ruminal VFA pool [35]. The contribution of VFAs to the daily energy requirements in minke whales seems to be of less importance than in ruminants. NordCy et al. [36] developed a three stage in vitro digestibility technique to simulate digestion in minke whales, and found that as much as 70% of the initial dry matter of the substrate disappeared into solution by bacterial degradation in the forestomach. The forestomach microbial digestion therefore seems to be of prime importance for the digestion of the prey, while bacterial fermentation products, such as VFAs, contribute less to the daily energy needs of minke whales (Olsen and Mathiesen, unpublished). This is also reflected in the relatively small size of the forestomach, compared to that of ruminants [25]. The stomach system of minke whales is followed by a short intestine, and the compartmentalization of the stomach is therefore thought to aid in retention of food, and hence to increase the passage time through the gastrointestinal tract. With the different structural and functional approaches to digestion in harp seals and minke whales, their ability to utilize food is different. The % digestible energy of fish (herring and capelin) seems to be equally high in both harp seals and minke whales, while the utilization of crustaceans is significantly lower in harp seals (Table 3) [3638]. It could be argued that the forestomach fermentation of food particles like chitin of the crustacean exoskeleton by indigenous bacteria contributes to an increased utilization of crustaceans in whales compared to seals. We suggest that the multi-

Table 3. Digestible energy (%) of different prey species in minke whale and harp seal

Herring (Clupea harengus) Capelin (Mallotus villosus) Krill (Thysanoessa sp.) a Nordr et al. [36]. bKeiver et al. [38]. CM~rtensson et al. [39]. dMhrtensson et al. [37].

Minke whale

Harp seal

92 (n = 16)a 95 (n = 5)c 93 (n = 5)c

95 (n = 4)b 94 (n = 4)d 82 (n = 4)d

358 chambered stomach of minke whales is an adaptation to increase passage time and consequently to increase the time available for both microbial and enzymatic digestion of food particles. The development of a relatively small forestomach in minke whales, compared to ruminants, may reflect an adaptation to a carnivorous diet and does not necessarily indicate a reduced importance of microbial digestion in these animals.

Acknowledgement This study was supported by the Norwegian Research Council, grant no. 4001408.007.

References 1. Hungate RE. The Rumen and its Microbes. New York: Academic Press, 1966. 2. Hobsen PN. The Rumen Microbial Ecosystem. New York: Elsevier, 1988. 3. Gooday GW. Chitinases. In: Leathman G (ed) Enzymes in Biomass Conversion. American Chemical Society, 1990. 4. Lindsay JGH, Walton MJ, Adron JW, Fletcher TC, Cho CY, Cowey CB. The growth of Rainbow trout (Salmo gairdneri) given diets containing chitin and its relationship to chitinolytic enzymes and chitin digestibility. Aquaculture 1984;37:315-334. 5. Gaskin DE. The Ecology of Whales and Dolphins. London: Heinemann Educational Books, 1982. 6. Graur D, Higgins DG. Molecular evidence for the inclusion of Cetaceans within the order Artiodactyla. Mol Biol Evol 1994;11(3):357-364. 7. Murie J. On Phoca groenlandica, Mtill: its modes of progression and its anatomy. Zool Soc London Comm Sci Corresp Proc 1870;604--608. 8. Helm RC. Intestinal length of three California pinniped species. J Zool London 1983;199:297304. 9. Tarpley RJ. Gross and microscopic anatomy of the tongue and gastrointestinal tract of the bowhead whale (Balaena mysticetus). Ph.D. dissertation. Texas A and M University, USA, 1985. 10. Herwig RP, Staley JT, Nerini MK, Braham HW. Baleen whales: Preliminary evidence for forestomach microbial fermentation. Appl Environ Microbiol 1984;47:421--423. 11. Herwig RP, Staley JT. Anaerobic bacteria from the digestive tract of North Atlantic fin whales (Balaenoptera physalus). FEMS Microbiol Ecol 1986;38:361-371. 12. Yamasaki F, Takahashi K. Digestive tract of Ganges dolphin, Platanista gangetica. Oesophagus and stomach. Okajimas Folia Anat Jpn 1971;48:271-293. 13. Hosokawa H, Kamaiya T . Some observations on the cetacean stomachs, with special considerations on the feeding habits of whales. Sci Rep Whales Res Inst 1971;23:91-101. 14. Jungklaus F. Der Magen der Cetaceen. Jenaische Z J Nat 1898;32:1-94. 15. Schulte H von W. Anatomy of a foetus of Balaenopterus borealis. Mem Am Mus Nat Hist (N Ser) 1916; 1:444-502. 16. JonsgArd A. The food of minke whales (Balaenoptera acutorostrata) in northern north Atlantic waters. Rep Int Whal Commn 1982;32:259-262. 17. Lydersen C, Angantyr LA, Wiig 0, Oritsland T. Feeding habits of northeast Atlantic Harp seals (Phoca groenlandica) along the summer ice edge of the Barents sea. Can J Fish Aquat Sci 1991 ;48:2180--2183. 18. Lydersen C, Weslawski JM, Oritsland NA. Stomach content analysis of minke whales Balaenoptera acutorostrata from the Lofoten and Vester~len areas, Norway. Holarctic Ecol 1991;14:219222.

359 19. NordCy ES, Blix AS. Diet of minke whales in the Northeastern Atlantic. Rep Int Whal Commn 1992;42:393-398. 20. Haug T, KrOyer AB, Nilssen KT, Ugland KI, Aspholm PE. Harp seal (Phoca groenlandica) invasions in Norwegian coastal waters, age composition and feeding habits. ICES J Mar Sci 1991;48:363-371. 21. Nilssen KT, Haug T, Potelov V. Field studies of harp seal Phoca groenlandica distribution and feeding ecology in the Barents Sea in September 1990. ICES CM 1991;N:3:23 pp. 22. Nilssen KT, Grotnes PE, Haug T. The effect of invading harp seals (Phoca groenlandica) on coastal fish stocks of North Norway. Fish Res 1992;13:25-37. 23. Nilssen KT, Haug T, Potelov V, Stasenkov VA, Timoshenko YK. Food habits of harp seals (Phoca groenlandica) during lactation and moult in March-May in the southern Barents Sea and White Sea. ICES J Mar Sci 1995;51 (in press). 24. Ichii T, Kato H. Food and daily food consumption of southern minke whales in the Antarctic. Polar Biol 1991;11:479--487. 25. Olsen MA, NordOy ES, Blix AS, Mathiesen SD. Functional anatomy of the gastrointestinal system of northeastern Atlantic minke whales. J Zool 1994;34:55-74. 26. Banks WJ. Digestive system. In: Applied Veterinary Histology 19. Baltimore, MD: Williams and Wilkins, 1981 ;373-423. 27. Carte A, Macalister A. On the anatomy of Balaenoptera rostrata. Philos Trans R Soc London 1868 ;201-261. 28. Pilliet MM, Boulart R. L'estomach des c6tac6s. J Anat Physiol 1895;31:250-260. 29. Tarpley RJ, Sis RF, Albert TF, Dalton LM, George JC. Observations on the anatomy of the stomach and duodenum of the bowhead whale, Balaena mysticetus. Am J Anat 1987;180:295-322. 30. Olsen MA, Nilssen KT, Mathiesen SD. Gross anatomy of the gastrointestinal system of harp seals (Phoca groenlandica). J Zool (in press). 31. Olsen MA, Aagnes TH, Mathiesen SD. Digestion of herring by indigenous bacteria in the minke whale forestomach. Appl Environ Microbiol 1994;60:4445--4455. 32. Mathiesen SD, Aagnes TH, SCrmo W. Microbial symbiotic digestion in minke whales (Balaenoptera acutorostrata). Paper SC/42/NHMi9 presented to the IWC Scientific Committee, 1990. 33. Orpin CG, Mathiesen SD, Greenwood Y, Blix AS. Seasonal changes in the ruminal microflora of the high-arctic Svalbard reindeer (Rangifer tarandus platyrhynchus). Appl Environ Microbiol 1985;50:144-151. 34. Stevens CE. Transport across rumen epithelium. In: Ussing HH, Thorn NA (eds) Transport Mechanisms in Epithelia. Copenhagen: Munksgaard, 1973;404-426. 35. Annison EF, Armstrong DG. Volatile fatty acid metabolism and energy supply. In: Physiology of Digestion and Metabolism in the Ruminant. UK: Oriel Press, 1970;422-437. 36. NordOy ES, SOrmo W, Blix AS. In vitro digestibility of different prey species in minke whales (Balaenoptera acutorostrata). Br J Nutr 1993;70:485--489. 37. MLrtensson P-E, NordOy ES, Blix AS. Digestibility of crustaceans and capeline in harp seals (Phoca groenlandica). Mar Mammal Sci 1994;10(3):325-331. 38. Keiver KM, Ronald K, Beamish FWH. Metabolizable energy requirements for maintenance and faecal and urinary losses of juvenile harp seals (Phoca groenlandica). Can J Zool 1984;62:769776. 39. M~irtensson P-E, NordOy ES, Blix AS. Digestibility of krill in minke whales and crabeater seals. Br J Nutr 1994;72:713-716.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang, editors

361

Body condition of fin whales during summer off Iceland Gisli A. Vl"kingsson Marine Research Institute, Reykjavfk, Iceland Abstract. Background: this study is a part of a larger research programme on the biology and ecology of fin whales conducted in Icelandic waters in 1986-1989. The objective was to examine energetic strategies, seasonal fattening in particular, in the species using data on weight and chemical composition of different tissues. Methods: carcass analysis was used for estimating the allocation of energy into different tissues. A total of 72 fin whales were weighed and the data used to create a formula for the prediction of weight from simple anatomical measurements. Seasonal increase in weight was calculated from the observed increase in girth dimensions and this, in combination with analysis of energetic densities of different tissues, was used to estimate the total energy deposition within the body throughout the summer and fall. Results: pregnant females had the highest rates of seasonal fattening, increasing their weight by 26% and the total energy content of the body by nearly 80%. The corresponding values for immatures were 15% and less than 30%, respectively. Muscle tissue appears to be an important energy depot in all reproductive classes, and pregnant females store relatively more energy in visceral fat and blubber than other reproductive classes. Conclusions: the results support previous findings that energy deposition is closely linked with reproduction. The deposition rates reported here are, however, slightly lower than those in a previous report. A rough transformation of the calculated energy storage into feeding rates of 2-3% of body weight is in concordance with indications from stomach content analysis. Key words: energetics, weight, seasonal fattening, feeding rates

Introduction

The fin whale (Balaenopteraphysalus) is the most abundant species of large whales in Icelandic waters, numbering over 15,000 animals in the East Greenland-IcelandJan Mayen stock area [ 1,2]. The species is highly migratory and is regularly found in Icelandic waters during May-October with the highest densities in June-August. Fin whales typically have a 2-year reproductive cycle, with conception and calving in mid-winter, a gestation period of approximately 11 months followed by 7 months of lactation [3]. In most mysticetes the summer period is characterized by intense feeding and consequently seasonal fattening, while feeding during the rest of the year is generally considered to be at greatly reduced levels [4]. Examination of the stomach content of fin whales caught during the summer off W and SW Iceland has shown an overwhelming dominance of the euphausid Meganyctiphanes norvegica in the diet [5,6] and pronounced diurnal variations in feeding activity indicating a mean daily food intake of 700-1,400 kg [7].

Address for correspondence: Marine Research Institute, P.O. Box 1390, 121 Reykjav~, Iceland.

362 Previous studies into the energetics of fin whales off Iceland have revealed considerable fattening throughout the summer, as well as large variability with respect to reproductive status and between-year fluctuations in food availability [2,5,8,9]. Few attempts have been made to quantify the energy deposition of large whales during the summer feeding season. In a study based on weighings, anatomical measurements and chemical analysis, Lockyer [8,10] concluded that an average pregnant female fin whale deposits around 74 million kcal in lipid stores during 13 weeks of feeding off Iceland, nearly doubling the energy content of the body. Anoestrous and lactating females had much lower deposition rates. In the present study, the methods of Lockyer were used on a larger sample, collected in 1986-1989, to estimate the amount of seasonal accumulation of energy reserves.

Materials and Methods

The material for this study was collected as a part of a larger programme of research on whale stocks in Icelandic waters conducted in 1986-1989. In this period a total of 290 fin whales were caught off W and SW Iceland and landed at the whaling station in Hvalfji3rSur 12-33 h post mortem, where sampling and measurements were made by MRI staff. In the 1986 season, the catch was stretched over the period 16 June to 29 September, whereas in the latter years no whales were caught after 12 August (1988) or 20 July (1987 and 1989). These short sampling seasons, together with the large between-years variations in energetic condition [5,9], result in the following estimation of seasonal fattening being mostly dependent on data from the 1986 season. Blubber thickness was measured at 18 positions on the body, perpendicularly from the skin to the blubber/muscle interface and half girth dimensions were measured at six sites as the whale lay on its lateral side on the flensing platform (Fig. 1). Reproductive condition was determined after careful examination of the reproductive organs [9]. The whales were weighed in parts using the basic flensing methods of the whaling company although special attention was paid to the correct separation of different organs and tissues. More detailed description of the weighing procedure was given by Vfkingsson [11 ]. A total of 72 fin whales were weighed in parts during the research programme.

,oL___ Yoz

1

GI

i vz

GZ

v03

G3

v~~~/

G4

vO5

G5 GG

Fig. 1. Measuring sites for girth dimensions (G) and blubber thickness (D, M and V) used in the study.

363 Approximately 5 x 5 cm samples of blubber and the underlying muscle were routinely taken dorsally, just posterior to the dorsal fin (D5 in Fig. 1) for chemical analysis. Samples of blubber and muscle were also taken at the other sampling sites (Fig. 1), although not from every landed whale, and samples of various internal organs were similarly taken from the majority of the animals. The samples were frozen at-20~ In the chemical analysis, water content was measured by freeze drying and protein content determined by the Kjeldahl-method with automatic distillation and titration as implemented by Tecator A.B., Sweden. The lipid content of muscle samples was determined by hydrolysis with 8 M HC1 and that of the blubber samples by Soxhlet extraction without prior hydrolysis. A detailed account of the chemical analysis was given by Vfkingsson [9].

Results

As 1986 was the only season in the research period that lasted long enough for meaningful analysis of seasonal fattening, and given the large difference between reproductive classes, the sample size (number of weighings) for each reproductive class is too small (n = 22 for all classes in 1986) for direct analysis of seasonal trends in the weight data. However, weight changes can be estimated indirectly, by examination of the relationship between anatomical measurements (length, girth and blubber thickness) taken from every landed whale, and the weight data. A regression analysis of the log-transformed data yielded a formula that quite precisely predicts the weight of fin whales from data on length and girth dimensions: W = 0.0306Ll8~ 1162, F(2,68) = 520.1,

(1)

P = 0.000

where W is weight in tonnes, L is length (m) and G is girth (m) at position G4 in Fig. 1. Relative girth dimensions were found to increase significantly throughout the season according to the following equations: Pregnant females:

G = 26.79 + 0.047D,

Other reproductive classes:

F(1,20) = 15.35,

G = 25.88 + 0.027D,

P = 0.001

F(1,46) = 11.20,

(2)

P = 0.002

(3) where G is girth (G4) in % of length and D is the number of days elapsed since 16 June. In Fig. 2A, eqs. (2) and (3) have been combined with eq. (1) for the estimation of total weight increase in the period 1 June to 1 October using the mean lengths of the different reproductive classes. According to these calculations pregnant females ap-

B. Immature males

C. Mature males

Mmae

Musde

364

A. Increase in total weight PregMnl lemaks

I'

/-

V"'"

I?

...---.......

rm DOrsaMalerPlblubber .......................................... ..-..-.---..--.----.--..----.-..--.--...-Vsnlral blubber

Vontrd blubber

lntemal organs Interns1o w ----.----------.---..-.-.-..-.-.-.-.----.. ----.-.---------.-----....--...-----.-..-. Membranes8 unews Membranes8 WW*s Bons6lwlesn

Bone6Ween

Days from 1 June

Days from 1 June

Days from 1 June

D. Immature females

E. Anestrous females

F. Pregnant females

Immature males

Musde

Mus&

b.iu..de

...-...-...-. -.-.- -..- - -.- - - - - - - - - Y W @ l DorasMateralblubber 10 -..---..-..--.-----.--..-...-.--.-..--.--. .......................................... Do~Vlaterelblubber .......................................... VenW blubber Ventral blubber Voosral I?&(

*

Vontral blubber

Foet?

Internal organs Intemd organs lnteml organs .......................................... . ----.--.-.-..--.--.-.--.-...---*-.-*.-.-.. ------.-.--.---*--.-.--...----...--..-.... Membranes 8 unews Membrmms 8 m w s Membranes 8 u n e m ,

Bona 8 baleen

Days from 1 June

BoneBbalrn

Bone 8 baleen

1 Days from 1 June

J

Days from 1 June

Fig. 2. Calculated increase in the weight of fin whales throughout the summer and fall (June-September) 1986. (A) Increase in total weight in different reproductive classes. (B-F) Increase in the weight of different tissues shown separately for each reproductive class.

365 pear to increase their weight by around 26% in this 4-month period, whereas the other reproductive classes have considerably lower increase rates of around 15%. To examine the allocation of this weight increase into different tissues, three tissue types were considered most important in relation to energy deposition: blubber, visceral fat and muscle. Significant seasonal increase was found in blubber thickness. Again the rate was highest in pregnant females: Pregnant females:

B = 2.65 + 0.0162D,

Other reproductive classes:

F(1,22) = 10.09,

B = 2.31 + 0.0074D,

P = 0.004

F(1,47) = 10.45,

(4)

P = 0.002

(5) where B is blubber thickness (the mean of sites M3, M4 and M5 in Fig. 1) in %o (promilles) of body length and D as in eq. (3). No significant trend was found in the blubber thickness anterio-ventrally on the body. Earlier studies [9,12] have shown the posterior and dorsal parts of the blubber to be most important in energy storage, and the present data reveal a close relationship between the above index of blubber thickness and the weight of posterior and dorsal blubber: Bw = 406.275 + 54.097Bt,

F(1,70) = 167.7,

P = 0.000

(6)

where Bw is the weight (kg) of posterior and dorsal blubber and Bt is blubber thickness (mm). Despite small sample size a significant increase was found in the weight of visceral fat throughout the season in mature fin whales of both sexes (linear regression, P < 0.05). Pregnant females had higher rate of increase (0.0413% of body weight per day) than anoestrous females and males (0.012%). Figure 2 B - F shows the estimated seasonal increase in the weight of different tissues, separately for the different reproductive classes. In this estimate the part of the total weight increase (Fig. 2A), not accounted for by the calculated increase in dorsal/lateral blubber and visceral fat, is assigned to muscle tissue, as previous studies have shown muscles to be important in energy storage [9,12,13]. According to these calculations, weight increase in muscle mass is between 25 and 30% in all reproductive classes. The pregnant females differ however, from the other classes in greater weight increases in dorsal/lateral blubber (27% compared to 10-14% in the latter) and visceral fat. A significant seasonal increase was found in the energetic content of posterior dorsal muscle in adult females: Pregnant females: Anoestrous females:

E = 2.93 + 0.0155D, E = 1.95 + 0.0205D,

F(1,20) = 7.21, F(1,8) = 7.43,

P = 0.021 P = 0.026

(7) (8)

366 0 o

Pregr~ua~,~~"

0

o

Anestrous lem~es

o_

~~~em~ J

~8 el,,

o,. o.,,. ooo o..

0

0

0

20

40 60 80 100 Days lrom 1 June

120

Fig. 3. Seasonal increase in the total energy content of the body of fin whales of different reproductive status as estimated from carcass analysis.

where E is energy (kcal/g) and D days elapsed since 16 June. No significant trend was observed in the energetic density of muscle in other classes, or in the posterior dorsal blubber of any reproductive class. Factory data suggest considerable seasonal increase in the oil content of bones, but analyses on the energetic content of skeletal tissue were too few for statistical analysis (n = 5; mean = 3.13 kcal/g; range 2.194.06 kcal/g). As none of the available data values originate from early spring or late autumn, the range values (2.19 and 4.06 kcal/g) can be considered the spring/fall endpoints for estimating minimum energy deposition in skeletal tissue. In Fig. 3 the data on weight increase has been coupled with data on energetic density of different tissues for estimating the total energy deposition in the body throughout the 4-month feeding season. In the underlying calculations the observed seasonal increase in energy density of posterior dorsal muscle has been assumed to apply to half of the dorsal and ventral muscle. The rest of the muscle tissue is considered of constant density throughout the season. The special position of pregnant

o

od

[ ~Deposition i . t~:_:t Metabolism ]

o o

o o ,,,.. o

o

._o o o

o

FP

FA

FI

MI

MM

Fig. 4. Energetic requirements of fin whales throughout the summer and fall (4 months) off Iceland. The lower part of the bars represents the energy deposited within the body, while the upper part shows the energy used in metabolism. FP, pregnant females; FA, anoestrous females; FI, immature females; MI, immature males; MM, mature males.

367 Table 1. Energy utilization and food consumption of fin whales during summer off Iceland as calculated from carcass analysis

Females

Energy utilization Tonnes of Euphausids kg/day % of body weight

Males

Pregnant

Immature

Anoestrous

Immature

Mature

119 159.9 1311 2.80

50 67.5 553 1.80

90 89.6 988 2.32

47 47.2 520 1.79

61 62.4 676 1.82

Energy utilization (in millions of kcal) and "Tonnes of Euphausids" refer to the 4 months feeding season, while the rest of the table refers to daily requirement.

females is evident from Fig. 3. The total energy content of their body increases by nearly 80%, whereas the corresponding value for immatures is less than 30%. For estimating total energy requirements, maintenance energy has to be added to the energy deposited within the body. Such an estimate for average sized fin whales of different reproductive classes during summer and fall (4 months) is given in Fig. 4. Kleiber's [ 14] formula was used for calculating resting metabolic rates and an activity coefficient of 1.45 [15] was assumed. The figure clearly demonstrates the great energy requirement of mature females, in particular the pregnant ones, and the relative importance of energy storage in these reproductive classes. In Table 1 the energy requirements given above have been transformed into food requirements given the following assumptions: fin whales off Iceland feed solely on Meganyctiphanes norvegica [6] with energy density of 0.93 kcal/g [10] and the assimilation efficiency is 80% [4].

Discussion

Considering the difficulties in obtaining data on the weight of large whales, and the previous literature, the overall sample size in this study is relatively large. This has enabled rather precise prediction of weight from simple anatomical measurements. The large differences between reproductive classes in energy deposition are in agreement with Lockyer's [10] conclusion that energy deposition is closely linked with reproduction. The calculated rate of seasonal increase in total weight of pregnant females (26% in 4 months) is somewhat lower than that estimated by Lockyer [10] (34% in 13 weeks) on the basis of data collected 2 years earlier. This may reflect the large between-year fluctuations in food availability and energetic condition of fin whales in Icelandic waters [2,8,9]. Thus, in 1984 the animals were relatively leaner in the beginning, and fatter towards the end of the season, than in 1986. A considerably lower, but significant increase in weight was found in the non-pregnant part of the population. Lockyer [8] found an insignificant trend in these reproductive classes except anoestrous females.

368 Although a somewhat different approach was used, the present finding of around 80% increase in the total energy content of the body of pregnant females is in general agreement with Lockyer's [8,10] results of 95% increase in the most important tissues for lipid deposition. Considering these tissues separately, the present data give an increase of 113% during the somewhat longer season assumed in this study. According to this study the weight of muscle tissue increases greatly throughout the season. The increase amounts to almost 6 tonnes (30%) in pregnant females and the relative increase is of similar magnitude in other reproductive classes (25-28%). Pregnant females deposit considerably more energy in blubber than other classes, and visceral fat deposition seems especially important in pregnant females. This tissue increases from less than 100 kg in spring to more than 2.7 tonnes in late fall. The pregnant females thus deposit more energy in visceral fat than in blubber (2 tonnes). When comparing the two classes of mature females the difference in energy deposition is least in the muscle, indicating that this is where the deposition begins after a period of leaning (lactation). The feeding rates calculated from the energetic data (Table 1) are in agreement with the analysis of the stomach content [7] and suggest that the animals fill their stomach more than once daily. The calculated energy deposition presented here is not sufficient for maintenance during the remaining 8 months of the year, assuming the same metabolic rates during winter, and using the gestational costs given by Lockyer [8]. The proportion of the winter energy requirements deposited within the body varies from around 35% in immatures to 73% in anoestrous females. This may be accounted for by a number of explanations including the following: the feeding season may be longer than assumed here, the animals may feed at a reduced rate on the winter grounds, they may have a metabolic depression during starvation, as shown in seals [ 16,17], the energy deposition may be underestimated (in bones, etc.). Also one has to bear in mind the large between-year fluctuations in energetic condition, as most of the indices of seasonal fattening in this study are based on data from one season.

References 1. International Whaling Commission. Report of the Scientific Committee. Rep Int Whal Commn 1992;42:51-270. 2. Sigurj6nsson J. Recent studies on abundance and trends in whalestocks in Icelandic and adjacent waters. Proc R Acad Overs Sci (Brussels) 1992;77-111. 3. Lockyer C. Review of baleen whale (Mysticeti) reproduction and implications for management. Rep Int Whal Commn 1984;19(Special Issue 6):27-50. 4. Lockyer C. Growth and energy budgets of large baleen whales from the Southern Hemisphere. FAO Fish Ser (5) Mammals in the Seas 1981;3:379-487. 5. Lockyer C. Body fat condition in Northeast Atlantic fin whales, Balaenoptera physalus, and its relationship with reproduction and food resource. Can J Fish Aquat Sci 1986;43:142-147. 6. Sigurj6nsson J, Vfkingsson GA. Investigations on the ecological role of cetaceans in Icelandic and adjacent waters. ICES CM 1992;N-24-rev.

369 7. Vfkingsson GA. Feeding of fin whales off Iceland - diurnal variation and feeding rates (abstract). Rep Int Whal Commn 1992;42:769. 8. Lockyer C. The relationship between body fat, food resource and reproductive energy costs in North Atlantic fin whales. Symp Zool Soc London 1987;57:343-361. 9. Vfkingsson GA. Energetic studies on fin and sei whales caught off Iceland. Rep Int Whal Commn 1990;40:365-373. 10. Lockyer C. Evaluation of the role of fat reserves in relation to the ecology of North Atlantic fin and sei whales. In: Huntley AC, Costa DP, Worthy GAJ Castellini MA (eds) Approaches to Marine Mammal Energetics. Special Publication No 1. Lawrence: Society for Marine Mammalogy, 1987;183-203. 11. Vfkingsson G, Sigurj6nsson J, Gunnlaugsson Th. On the relationship between weight, length and girth dimensions in fin and sei whales caught off Iceland. Rep Int Whal Commn 1992;38:323-326. 12. Lockyer C, McConnell LC, Waters TD. Body condition in terms of anatomical and biochemical assessment of body fat in North Atlantic fin and sei whales. Can J Zool 1985;63:2328-2338. 13. Lockyer C, Waters TD. Weights and anatomical measurements of north eastern Atlantic fin (Balaenoptera physalus, Linnaeus) and sei (B. borealis, Lesson) whales. Mar Mammal Sci 1986;3(2): 169-185. 14. Kleiber M. The Fire of Life - an Introduction to Animal Energetics. Huntington, NY: RE Krieger, 1975. 15. Markussen NH, Ryg M, Lydersen C. Food consumption of the NE Atlantic minke whale (Balaenoptera acutorostrata) population estimated with a simulation model. ICES J Mar Sci 1992;49:317-323. 16. NordOy ES, Ingebretsen OC, Blix AS. Depressed metabolism and low protein catabolism in fasting grey seal pups. Acta Physiol Scand 1990;139:361-369. 17. Markussen NH, Ryg M, Oritsland NA. Metabolic rate and body composition of harbour seals, Phoca vitulina during starvation and refeeding. Can J Zool 1992;40:220-224.

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9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

371

Seal adaptations for long dives: recent studies of ischemia and oxygen radicals Robert Eisner ~, Stephanie 0yas~eter 2, Ola Didrik Saugstad 2 and Arnoldus Schytte Blix 3 l lnstitute of Marine Science, University ofAlaska, Fairbanks, Alaska, USA; 2Department of Pediatric Research, University of Oslo, Rikshospitalet, Oslo, Norway; and 3Department of Arctic Biology, University of Tromsr Tromsr Norway Abstract. Some seals species are well adapted to diving asphyxia. These adaptations include prominent cardiovascular responses of bradycardia, reduced cardiac output and selective vasoconstriction in some organs resulting in overall oxygen conservation for the most oxygen-sensitive tissues. Brain perfusion is relatively well maintained, myocardial flow becomes intermittent, while kidney and other visceral circulation ceases entirely or is markedly reduced. The result is an overall conservation of available oxygen and maintenance of essential functions. Ischemia poses a potential threat if circulation is not restored within a critical time. However, another hazard of equal or greater potential may result from the burst of oxygen-derived free radicals and other forms of highly reactive oxygen produced by the post-ischemic re-oxygenation. Seal organs tolerate ischemia and reperfusion better than do those of terrestrial mammals. Studies of isolated arteries reveal some of the controls governing their reactivity. Tissue analyses from harp and ringed seals, Phoca groenlandica and Phoca hispida, show that hypoxanthine, a potential oxygen free radical generator, was produced in ischemic heart and kidney. We suggest that its effects may be blunted in seals by being harmlessly metabolized or recycled. Key words: diving asphyxia, ischemia, reactive oxygen species

Introduction Seals of the Phocidae family, whose members are long divers, are useful experimental models for the study of asphyxia and ischemia. Although most of their natural dives are brief, lasting only a few minutes, they are capable of much longer and more demanding dives. In these the seal's survival depends upon a broad range of adaptations in which the circulatory system plays a prominent role [1,2]. Maximum dive durations vary among species from 20 min to well over 1 h. Progressive asphyxia begins at the onset of diving, and more than simple hypoxia is involved. Asphyxial exposure includes the combinations and interactions among cellular lowering of oxygen levels (hypoxia), increasing carbon dioxide (hypercapnia) and accumulating hydrogen ions (acidosis) - the triad of asphyxia that leads to numerous unfavorable metabolic consequences. As the dive lengthens, there is an inevitable conversion from oxidative to anaerobic metabolism. The primary means by which seals endure such long bouts of breath-holding depend upon both energetic

Address for correspondence: R. Eisner, Institute of Marine Science, University of Alaska, Fairbanks, Alaska 99775, USA.

372 stores and functional adaptations. Copious oxygen reserves are sequestered in blood and muscle in combination with hemoglobin and myoglobin [3]. Glycogen reserves supplying anaerobic metabolism are richer in seals than in other animals [4]. Cardiovascular adaptations for diving include bradycardia, reduced cardiac output and selective ischemia. Intense vasoconstriction occurs in tissues that are most tolerant of hypoxia, while perfusion is relatively well maintained in more sensitive organs, especially heart and brain. Brain perfusion is relatively well maintained, myocardial flow becomes intermittent, while kidney circulation ceases entirely or is markedly reduced [1 ]. Thus these three organs represent three different adaptive responses" maintained perfusion, intermittent blood flow and persisting ischemia. Inevitably, there follows a gradual conversion from oxidative to anaerobic metabolism in ischemic organs, and later in perfused tissues. The seal's brain has modest glycogen reserves, but they are enough to sustain its activity. Ultimately, arterial oxygen partial pressure may decline to about 8-10 mmHg at the end of a simulated maximum endurance dive [5]. The cardiovascular responses and related respiratory events are governed by integrated reflexes and interactions within the central nervous system [6].

Ischemic Heart and Kidney The intermittent character of myocardial perfusion during experimental dives was found to result in frequent periods of ischemia, some lasting up to 45 s [7]. Anaerobic dependence was signalled by the appearance of lactate production [8]. The fluctuations of coronary blood flow suggest that the seal may effectively utilize both oxidative and glycolytic energy reserves by a mechanism of alternately switching from reduced perfusion, in which anaerobic metabolism operates, to subsequent restoration of flow, perhaps produced by accumulated metabolic products, in which oxidative metabolism dominates. Other experimental studies on anesthetized animals have shown an intrinsic superior tolerance to hypoxia in seal hearts compared with similarly treated pig hearts [9]. Acetylcholine produced different responses in isolated large and small seal coronary arteries. Micromolar concentrations of acetylcholine produced constriction of small coronary arteries. This response was blocked by indomethacin, suggesting that a prostaglandin mediation was involved. In contrast to the response of small arteries, large coronary arteries showed vascular smooth muscle relaxation and dilation in response to acetylcholine. Both constrictions and dilations were eliminated or reduced by atropine and by removal of or damage to the endothelium [ 10]. In a study several years ago, isolated kidneys of dogs and harbor seals were subjected to 1 h of warm ischemia. When the perfusion pump was restarted, blood flow in the seal kidneys recovered within a few minutes while the dog kidneys were slower to respond. Oxygen consumption of dog kidneys also recovered more slowly. Furthermore, the dog kidneys failed to produce urine during a recovery period of 1 h, in marked contrast to the relatively copious urine flow of seal kidneys [11 ]. Recent

373 unpublished studies of isolated seal renal arteries revealed a vigorous constrictor response to norepinephrine which was reduced by alpha adrenergic blockade. This effect was also inhibited by indomethacin, thus implicating a prostaglandin mechanism.

Hypoxanthine Production Ischemia is obviously damaging if blood flow is not restored before a critical time limit, depending upon the resistance of individual tissues. However, another hazard of equal or greater potential results from the burst of oxygen-derived free radicals and other forms of highly reactive oxygen that are produced by the post-ischemic reoxygenation accompanying restoration of perfusion [12-14]. The questions here concern what, if any, damage might be induced in seals by reactive oxygen species and what protective mechanisms the seal might employ against this hazard. There are several options for protection against these adverse effects of reactive oxygen forms. Hypoxanthine is the last step in hypoxic ATP degradation from which purine salvage might take place. A substantial fraction of purine base is recycled in mammalian tissue under ordinary non-stressed circumstances. Seals might have an increased capability for recycling salvage of hypoxanthine and thus reduce the metabolic cost of repeated ATP synthesis from primary substrates. Otherwise a further reaction of hypoxanthine, mediated by xanthine oxidase, would lead to production of uric acid and the generation of the oxygen radical, superoxide. Superoxide dismutase further catalyzes the reaction of superoxide to production of hydrogen peroxide, not specifically a free radical but a reactive oxygen species. Combination of superoxide and hydrogen peroxide yields the highly reactive and injurious hydroxyl radical. As a first step in addressing these questions, we undertook to determine the presence or absence of hypoxanthine, a potential generator of oxygen free radicals, in seal heart and kidney tissues and in blood plasma. We report here some recent preliminary observations relating to possible elaboration of oxygen-derived free radicals in seal ischemic tissues. Blood was drawn from the intervertebral vein of two harp seals, Phoca groenlandica, before and after 10 min experimental dives performed at the University of Tromsr After centrifugation, the plasma was frozen and transported to Oslo for analysis. Hearts and kidneys were removed from harp seal and ringed seals, Phoca hispida, immediately after death by shooting. Harp seals were collected from sea ice of the Greenland Sea during a Norwegian scientific expedition. Ringed seal organs were obtained through the cooperation of Alaskan Native Inupiat subsistence hunters near Barrow, Alaska, under terms of a scientific permit issued by the US National Marine Fisheries Service. Approximately 5 g of left ventricle and 5 g of combined kidney cortex and medulla were placed in sample vials and in liquid nitrogen. A similar portion of each tissue was maintained at 35~ in a thermos bottle for 30 min, then placed in liquid nitrogen. This latter is referred to here as the "ischemic" tissue. Tissue samples were

374 placed in long-term storage a t - 7 0 ~ and were stored temporarily a t - 2 0 ~ when ready for analysis. Hypoxanthine levels were determined by high performance liquid chromatography [15]. Frozen tissue was disintegrated in a cold mortar and the resulting powder extracted with cold 0.4 N perchloric acid containing EDTA. After centrifugation the pellet was treated with 0.4 N potassium hydroxide at 50~ and spun down [ 16]. The combined supernatants were brought to neutrality with 0.05 M potassium phosphate buffer (pH 8.5), and deproteinized by ultrafiltration (cut off 10,000 mol. wt.). Hypoxanthine values were determined by ultraviolet absorption after chromatographic separation on a reversed-phase column. Hypoxanthine could not be detected in harp seal plasma before or after 10 min experimental dives. It was found to be present in heart and kidney tissues from harp and ringed seals and its concentration was substantially increased after 30 min of isolation (ischemia) at 35~ (Table 1, Fig. 1). The significance of this finding is to suggest that seal tissues may respond to the sequence of ischemia and subsequent reoxygenation upon circulatory restoration by the production of hypoxanthine. The appearance of hypoxanthine in seal heart and kidney extracts and its increased levels after a period of ischemia indicates that ATP degradation proceeds in a manner not fundamentally different from that of other mammalian tissues similarly treated. However, several questions are consequently raised. Among mammalian species there are probably none other that experience such frequently repeated cycles of perfusion, ischemia and reperfusion as occurs during their frequent dives. At least two untoward circumstances may result: (1) damage directly attributable to the presence of free radicals (for example, membrane lipid peroxidation, protein disruption, rupture of DNA strands) and (2) high metabolic cost through the loss of purine base and the necessity for its de novo synthesis. Possibilities for recycling of hypoxanthine to ATP or for the elaboration of reactive oxygen species are still to be determined.

Table 1. Hypoxanthine concentrations in individual seal heart and kidney tissues

Hypoxanthine (~mol/100 g) Heart Harp seal-1 control Harp seal-1 ischemia Harp seal-2 control Harp seal-2 ischemia Ringed seal control Ringed seal ischemia

2.2, 2.6, 2.6 6.6, 6.6, 6.1 4.4, 4.0 9.1, 8.8 14.1, 15.9 21.6, 21.2

Kidney Harp seal-2 control Harp seal-2 ischemia

2.2, 4.4, 3.6 62.8, 51.8, 29.6

Control values from samples placed directly in liquid nitrogen; ischemic values from samples maintained at 35~ for 30 min before freezing.

375 60

I---TControl

E 5O

O~ 0 0

~7-~-~]30 min ischemio 4O

0

E

::k ~"

30

ID C c-

-,-,

5;;

20

z 0

o-lO

"r-

Hh Hh Hr Kh

Hh

Hr

Kh

Heart, harp seal Heart. ringed seal Kidney, harp seal

Fig. 1. Hypoxanthine in seal heart and kidney. Thirty minutes of warm ischemia results in elevated hypoxanthine concentrations.

An observation of ours several years ago may be relevant to these questions. Hypoxanthine was injected into the venous circulation of a harbor seal and its detection in arterial blood attempted. Removal of the hypoxanthine during the lung circuit was complete, suggesting that the seal's lung has unusually high potential for metabolism of purine degradation products.

Acknowledgements This research has been supported by the Norwegian Marine Mammal Research Programme; Norwegian Women's Public Health Association; Department of Arctic Biology, University of Tromsr American Heart Association, Alaska Affiliate; Alaska College Sea Grant Program and the Alaska North Slope Borough Division of Wildlife Management.

References 1. Elsner R, Franklin DL, Van Citters RL, Kenney DW. Cardiovascular defense against asphyxia. Science 1966;153:941-949. 2. Eisner R, Gooden B. Diving and Asphyxia. Cambridge, UK: Cambridge University Press, 1983. 3. Lenfant C. Physiological properties of blood of marine mammals. In: Andersen HT (ed) The Biology of Marine Mammals. New York: Academic Press, 1969;95-116.

376 4. Kerem D, Hammond DD, Eisner R. Tissue glycogen levels in the Weddell seal: a possible adaptation to asphyxial hypoxia. Comp Biochem Physiol A 1973;45:731-736. 5. Kerem D, Elsner R. Cerebral tolerance to asphyxial hypoxia in the harbor seal. Resp Physiol 1973; 19:188-200. 6. Eisner R, Daly MdeB. Coping with asphyxia: lessons from seals. News Physiol Sci 1988;3:65-69. 7. Eisner R, Millard RW, Kjekshus JK, White FC, Blix AS, Kemper WS. Coronary blood flow and myocardial segment dimensions during simulated dives in seals. Am J Physiol 1985;249:H1119Hl128. 8. Kjekshus JK, Blix AS, Eisner R, Hol R, Amundsen E. Myocardial blood flow and metabolism in the diving seal. Am J Physiol 1982;242:R97-R104. 9. White FC, Elsner R, Willford D, Hill E, Merhoff E. Responses of harbor seal and pig heart to progressive and acute hypoxia. Am J Physiol 1990;259:R849-R856. 10. Eisner R, Starr C, Ebbesson SOE, de la Lande IS. Heterogeneous cholinergic vasodilatation and vasoconstriction in seal coronary arteries. Abstracts, IUPS Congress, Glasgow, 1993. 11. Halasz NA, Elsner R, Garvie RS, Grotke GT. Renal recovery from ischemia: a comparative study of harbor seal and dog kidneys. Am J Physiol 1974;227:1331-1335. 12. Saugstad OD, Aasen AO. Plasma hypoxanthine levels as a prognostic aid of tissue hypoxia. Eur Surg Res 1980;12:123-129. 13. McCord JM. Oxygen derived free radicals in postischemic tissue injury. N Engl J Med 1985;312:159-163. 14. Saugstad OD. Hypoxanthine as an indicator of hypoxia: Its role in health and disease through free radical production. Pediatr Res 1988;23:143-150. 15. Simmonds RJ, Harkness RA. High-performance liquid chromatographic methods for base and nucleotide analysis in extracellular fluids and in cells. J Chromatogr 1981 ;226:369-381. 16. Saugstad OD, Schrader H. The determination of inosine and hypoxanthine in the rat brain during normothermic and hypothermic anoxia. Acta Neurol Scand 1978;57:281-288.

9 1995 ElsevierScienceB.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang,editors

377

Pineal functions in newborn seals Karl-Arne Stokkan Department of Arctic Biology and Institute of Medical Biology, University of Tromsr Norway Abstract. The hormone melatonin produced by the pineal gland transduces information about the animals' photoperiodic environment and may also affect their thermoregulation. Seals have an exceptionally large pineal gland, which is relatively larger and much more active in newborns than in adults, even during daytime. In other mammals the gland is small and nonfunctional at birth and notoriously inhibited by daylight. Adult mammals thus have a conspicuous diel rhythm of plasma melatonin. This fundamental consequence of pineal activity is observed during the first day of life in seals, whereafter the hormone concentration rapidly declines to establish the adult pattern and level in less than 1 week. Compared with nighttime pineal activity in other mammals, the tissue-specific activity of the newborn seal pineal gland is actually low. Therefore, the very high plasma concentrations of melatonin in newborn seals may primarily relate to the size of the gland and to the fact that its activity is only partially inhibited by daylight. The physiological consequences of a large and active pineal gland in newborn seals are still unknown. High levels of melatonin at birth may cause increased heat production, but may also reflect a need for this hormone during the foetal period. K e y w o r d s : melatonin, circadian, thyroid, thermoregulation, oxygen radicals

Introduction

In many animals living at mid and high latitudes, changes in the day length are used to regulate the temporal pattern of daily and seasonal events. One physiological link between the organism and its photoperiodic environment is the hormone melatonin secreted from the pineal gland. The light/dark cycle entrains an endogenous circadian rhythm in the pineal production of melatonin and daylight inhibits the production. The concentration of melatonin in the blood is therefore normally high only during the dark phase of a 24-h period, and the duration of the nocturnal increase in hormone production usually matches closely the duration of each night [1]. In this way the pineal gland may act as both a clock and a calendar [2]. The magnitude of the nocturnal increase in melatonin production varies among species, with the trough to peak ratio usually ranging from 1:2 to 1:10 [3]. This change is caused by a parallel rhythm in the activity of the enzyme serotonin Nacetyltransferase (NAT, EC 2.3.1.5), which may increase 2-100-fold during the night, depending on the species studied [4,5]. NAT is considered to be the ratelimiting enzyme in the pineal conversion of serotonin to melatonin [6]. The large rise in NAT activity during the night is caused by an increase in the interaction of norepinephrine with fl-adrenergic receptors in the pinealocyte membranes [7], and in many animals the density of pineal fl-adrenergic receptors also exhibits a marked 24h rhythmicity with high levels during the night [8].

378 Pineal Gland in Seal Pups It has been known for quite some time that animals of the order Pinnipedia (sea lions, seals and walruses) have an exceptionally large pineal gland [9]. Furthermore, the gland is relatively larger and seemingly more active in newborn than in adult seals, producing extremely high levels of circulating melatonin, even during daytime [ 10]. Newborn mammals generally have a small and nonfunctional pineal gland and light unequivocally inhibits melatonin production in adults [11]. Bryden et al. [10] only recorded midday plasma hormone levels in newborn seals and Barrell and Montgomery [12] thereafter reported a lack of 24-h rhythmicity in Weddell seal (Leptonychotes weddellii) pups which were exposed to continuous daylight in the Antarctic summer. However, the fundamental feature of a circadian rhythmicity appears to be present in the pineal gland of newborn seal pups when they are exposed to a light-dark rhythm [13]. The level of plasma melatonin exhibits a 24-h rhythmicity, with increasing concentrations during the night and a fall during the day. This rhythm is evident during the first day of life and is superimposed on a progressive decline in both nighttime amplitude and daytime nadir. At about the 4th day of age in grey seals (Halichoerus grypus), an adult pattem and level appear to be established [ 13]. One implication of the high daytime melatonin levels is that the newborn seal pineal does not seem to be completely inhibited by light, the mechanism of which is unknown. It has been shown that exposure to cold enhances the daytime pineal activity in Djungarian hamsters (Phodopus sungorus) by preventing the light induced inactivation of pineal NAT activity [14]. The thermal shock which many polar seals experience at birth [15] may therefore contribute to the extreme pineal activity in these animals. The relative pineal size (pineal mass (mg)/body mass (kg)) is 20-25 in newborn harp (Phoca groenlandica) and grey seals [13] and about half that in southem elephant seal pups (Mirounga leonina) [10]. This is about one order of magnitude higher than in the collared lemming (Dicrostonyx groenlandicus; [16]) and in Arctic rodents in general, where the gland is also found to be notoriously large [17]. Since many seals are not typically polar animals, their large pineal gland may not necessarily reflect a general tendency of latitudinal increase in size, which was proposed by Ralph [18] and later confirmed in rodents by Quay [17]. Grey seals pups caught in the Gulf of St. Lawrence at 46~ also had large and very active pineals [13]. The concentration of melatonin in the pineal gland of newborn seals is extremely high [10,13] compared with other mammals [19], but it has not been shown to be rhythmic. Supporting this lack of rhythmic changes in melatonin content is a similar lack of day/night differences in the pineal/~-adrenergic receptor density in newborn harp seals [13]. The pinealocytes of elephant seal pups, furthermore, do not reveal the membraneous whorls and granulated vesicles [20], which are structures normally associated with increased pineal secretory activity [21 ]. At present it is not possible to explain these observations since one should expect to find rhythmic changes in the pineal gland in parallel with the changes in circulating melatonin. However, it may

379 relate to infrequent sampling procedures and the fact that the nighttime peak of pineal activity was not detected. Compared with other newborn mammals, the neonate seal pineal gland is certainly very large and active, but its tissue-specific activity is actually markedly lower than that seen during nighttime in some adult mammals. Pineals of rodents like the Syrian hamster (Mesocricetus auratus) and the cotton rat (Sigmodon hispidus) weigh 0.15-0.25 mg [ 17] and contain 1-2.5 ng of melatonin per gland at night [19]. The pineals of newborn seals weigh 300 mg to 4.7 g and contain 10-90 ng of melatonin. The very high levels of circulating melatonin in newborn seals may, therefore, primarily result from a low sensitivity to daylight inhibition and from the mere fact that the gland is large.

Why Do Seal Pups Have a Large and Active Pineal Gland?

The very large and active pineal gland in newborn seals has been assumed to have a thermoregulatory role, presumably acting via the thyroid gland [10,20]. Plasma levels of thyroid hormones are found to be elevated in newborn seals [ 13,22,23] and confirm the general notion of hyperthyroidism in newborn seals as well as in newborn mammals in general [24]. It has been suggested that this could play an important role in maintaining body temperature after birth by increasing the metabolic rate, which in newborn seals may reach 1.5-3 times that of other (adult) animals of similar size [25,26]. Newborn harp seals depend primarily on non-shivering thermogenesis (NST) in brown adipose tissue (BAT) to maintain thermal balance [27]. This activity is maximal during the first 3 days of life and the BAT has lost most of its thermogenic function about 3 weeks later [28]. At this age, the plasma concentrations of melatonin and of thyroid hormones have declined to adult levels [13,23]. This close temporal association between NST and pineal and thyroid activities in the newborn harp seal may be of causal significance. Thyroid hormones play a prominent role in causing high NST in BAT [29], and melatonin has been shown to accomplish similar actions, by itself or via thyroid hormones [30,31]. In recent years accumulated information shows that melatonin itself plays an important role in thermoregulation [32] and that it may affect the central control of body temperature [33]. Based on reference to their own, unpublished observations, Little and Bryden [20] argued that subcutaneous fat cells of newborn southern elephant seals resemble BAT ultrastructurally, but they were uncertain whether these cells are thermogenic. BAT could not be found in either newborn Weddell or hooded seals [15], but the pups of all these seals need elevated heat production just after birth, and they all have a large and active pineal. Little and Bryden [20] suggested that melatonin could increase the peripheral breakdown of thyroxine (T4) to triiodothyronine (T3), thereby maximizing the thermogenic effect of the thyroid output. However, this was not supported by a recent finding in grey and harp seals [13] where the conversion of T4 to T 3 appeared to be lowest in the youngest seals, where the melatonin levels were highest.

380 Seals are not unique in being born into a cold environment [ 15] and some are not born in particularly cold surroundings. Newborn Arctic ungulates rely heavily on NST in BAT [34,35] but they have a small and apparently nonfunctional pineal gland (Stokkan, unpublished observation). The large pineal gland in seals may thus be involved in other metabolic features which are unique to sea mammals and to newborn sea mammals in particular. Possibly, the very high and rapidly declining pineal activity of the newborn seal may reflect prenatal rather than neonatal phenomena, and one condition which is typical for foetal sea-mammals is the hypoxia which they occasionally experience when their mother is diving. Although the foetus in both diving and nondiving animals shows conspicuous cardiovascular responses to acute maternal asphyxia [36], mechanisms protecting against hypoxia probably have greatest adaptive significance in diving animals. One intriguing possibility, which remains to be investigated, is related to the recently discovered antioxidant capacity of melatonin [37]. It has been found that melatonin is a very potent and efficient scavenger of endogenous radicals [38]. Oxygen free radicals are commonly observed in the ischemic and subsequently reperfused myocardial tissue [39], and Eisner, ~yas~eter, Saugstad and B lix (this volume) report that such compounds are also produced in various tissues of the diving seal. They may also be produced in the foetal skeletal muscles when the mother surfaces after a long dive, and, possibly, high levels of melatonin may protect the highly mitotic foetus against chromosomal damage caused by oxygen free radicals.

References 1. Reiter RJ. Melatonin: the chemical expression of darkness. Mol Cell Endocrinol 1991;79:C153C158. 2. Reiter RJ. The melatonin rhythm: both a clock and a calendar. Experientia 1993;49:654--664. 3. Reiter RJ. Comparative aspects of pineal melatonin rhythms in mammals. ISI Atlas of Science: Anim Plant Sci 1988;1:111-116. 4. Klein DC, Weller JL. Indole metabolism in the pineal gland: a circadian rhythm in Nacetyltransferase. Science 1970; 169:1093-1095. 5. Rudeen PK, Reiter RJ, Vaughan MK. Pineal serotonin-N-acetyltransferase in four mammalian species. Neurosci Lett 1975; 1:225-229. 6. Klein DC. Pineal gland as a model of neuroendocrine control system. In: Reichlin S, Baldessarini RJ, Martin JB (eds) The Hypothalamus. New York: Raven Press, 1978;303-329. 7. Deguchi T, Axelrod J. Control of circadian change of serotonin N-acetyltransferase in the pineal organ by the/3-adrenergic receptor. Proc Natl Acad Sci USA 1972;69:2547-2550. 8. Pangerl B, Pangerl A, Reiter RJ. Circadian variations of adrenergic receptors in the mammalian pineal gland: a review. J Neural Transm 1990;81:17-29. 9. Tilney F, Warren LF. The morphology and evolutional significance of the pineal body. Am Anat Mem 1919;9:257 pp. 10. Bryden MM, Griffiths DJ, Kennaway DJ, Ledingham J. The pineal gland is very large and active in newborn Antarctic seals. Experientia 1986;42:564-566. 11. Reiter RJ. Intrinsic rhythms of the pineal gland and associated hormone cycles in body fluids. Ann Rev Chronopharmacol 1988;4:77-105.

381 12. Barrell GK, Montgomery GW. Absence of circadian patterns of secretion of melatonin or cortisol in Weddell seals under continuous natural daylight. J Endocrinol 1989; 122:445-449. 13. Stokkan KA, Vaughan MK, Reiter RJ, Folkow LP, Mhrtensson PE, Sager G, Lydersen C, Blix AS. Pineal and thyroid functions in newborn seals. Gen Comp Endocrinol 1995 (in press). 14. Stieglitz A, Steinlechner S, Ruf T, Heldmaier G. Cold prevents the light induced inactivation of pineal N-acetyltransferase in the Djungarian hamster, Phodopus sungorus. J Comp Physiol A 1991 ;168:599--603. 15. Blix AS, Steen JB. Temperature regulation in newborn polar homeotherms. Physiol Rev 1979;59:285-304. 16. Quay WB. Quantitative morphology and environmental responses of the pineal gland in the collared lemming (Dicrostonyx groenlandicus). Am J Anat 1978; 153:545-562. 17. Quay WB. Greater pineal volume at higher latitudes in Rodentia: exponential relationship and its biological interpretation. Gen Comp Endocrinol 1980;41:340-348. 18. Ralph CL. The pineal gland and geographical distribution of animals. Int J Biometeorol 1975;19:289-303. 19. Reiter RJ. The mammalian pineal gland: structure and function. Am J Anat 1981; 162:287-313. 20. Little GJ, Bryden MM. The pineal gland in newborn southern elephant seals, Mirounga leonina. J Pineal Res 1990;9:139-148. 21. Karasek M. Ultrastructure of the mammalian pineal gland: its comparative and functional aspects. In: Reiter RJ (ed) Pineal Research Reviews 1. New York: Alan R Liss, 1983;1-48. 22. Leatherland JF, Ronald K. Thyroid activity in adult and neonate harp seals Pagophilus groenlandicus. J Zool London 1979; 189:399-405. 23. Engelhardt FR, Ferguson JM. Adaptive hormone changes in harp seals, Phoca groenlandica, and gray seals, Halichoerus grypus, during the postnatal period. Gen Comp Endocrinol 1980;40:434445. 24. Little GJ. Thyroid morphology and function and its role in thermoregulation in the newborn southern elephant seal (Mirounga leonina) at Macquarie Island. J Anat 1991;176:55-69. 25. Lavigne DM, Innes S, Worthy GAJ, Kovacs KM, Schmitz OJ, Hickie JP. Metabolic rates of seals and whales. Can J Zool 1986;64:279-284. 26. Worthy GAJ. Metabolism and growth of young harp and grey seals. Can J Zool 1987;65:13771382. 27. Grav HJ, Blix AS. Brown adipose tissue - a factor in the survival of harp seal pups. Can J Physiol Pharmacol 1976;54:409-4 12. 28. Blix AS, Grav HJ, Ronald K. Some aspects of temperature regulation in newborn harp seal pups. Am J Physiol 1979;236:R188-R197. 29. Silva JE, Matthews PS. Full expression of uncoupling protein gene requires the concurrence of norepinephrine and triiodothyronine. Mol Endocrinol 1988;2:706-713. 30. Heldmaier G, Steinlechner S, Rafael J, Vsiansky P. Photoperiodic control and effects of melatonin on non-shivering thermogensis and brown adipose tissue. Science 1981;212:917-919. 31. Puig-Domingo M, Guerrero JM, Tannenbaum MG, Menendez-Palaez A, Hurlbut EC, Reiter RJ. Melatonin regulation of thyroid hormone metabolism in brown adipose tissue. In: Reiter RJ, Pang SF (eds) Advances in Pineal Research 3. London: Libbey, 1989;231-234. 32. Heldmaier G, Lynch GR. Pineal involvement in thermoregulation and acclimatization. Pineal Res Rev 1986;4:97-139. 33. Saarela S, Reiter RJ. Function of melatonin in thermoregulatory processes. Life Sci 1993;54:295311. 34. Markussen KA, Rognmo A, Blix AS. Some aspects of thermoregulation in newborn reindeer calves (Rangifer tarandrus tarandrus). Acta Physiol Scand 1985;123:215-220. 35. Blix AS, Grav HJ, Markussen KA, White RG. Modes of thermal protection in newborn muskoxen (Ovibos moschatus). Acta Physiol Scand 1984;122:443-453.

382 36. Eisner R, Hammond DD, Parker HR. Circulatory responses to asphyxia in pregnant and fetal animals: a comparative study of Weddell seals and sheep. Yale J Biol Med 1970;42:202-217. 37. Reiter RJ, Poeggeler B, Tan DX, Chen LD, Manchester LC, Guerrero JM. Antioxidant capacity of melatonin: a novel action not requiring a receptor. Neuroendocrinol Lett 1993; 15:103-116. 38. Poeggeler B, Reiter RJ, Tan DX, Chen LD, Manchester LC. Melatonin, hydroxyl radical-mediated oxidative damage, and aging: a hypothesis. J Pineal Res 1993;14:151-168. 39. Goldhaber JI, Weiss JN. Oxygen free radicals and cardiac reperfusion abnormalities. Hypertension 1992;20:118-127.

9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 13. UUtang,editors

383

Changes in metabolic rate and body composition during starvation and semistarvation in harbour seals Nina Hedlund Markussen Division of General Physiology, University of Oslo, Blindern, Oslo, Norway Abstract. Fasting or reduced food intake is a normal part of the life cycle of many seals and is associated with periods of breeding, lactation, moulting, and migration. During fasting the metabolic rate is reduced to below the resting metabolic rate. The course of this metabolic depression seems to be surprisingly different from that found in terrestrial mammals as the metabolic rate is reduced at an early stage of the starvation period and remains at a stable, lowered level throughout the period. During semistarvation or undernutrition a metabolic depression is observed in terrestrial mammals, but this mechanism does not occur in seals during a period where the seals were given 10% of ad libitum intake. The energy equivalent of mass loss reflects the proportion of fat loss and lean body mass during starvation. It has been assumed that seals rely solely on blubber as their energy source during starvation. In juvenile harbour seals it was found that 50% of the mass loss or 75% of the energy used during a forced starvation period and during restricted feeding was taken from fat.

Key words: metabolic depression, energy equivalent of mass loss, starvation, semistarvation

Introduction

The resting metabolic rate is the central variable in the energy balance of mammals and birds. In older literature it was assumed that marine mammals have elevated metabolic rates compared to terrestrial mammals. However, Lavigne et al. [1] pointed out that the early measurements were made on animals which did not meet Kleiber's [2] preconditions (adult, resting, thermoneutral and postabsorptive), but were instead based on measurements of immature seals [3-7], which indeed have about twice the metabolism of adults. Seals normally undergo periods of the year where food consumption is reduced although food may be available. During lactation and moulting, food intake is negligible and during the post-weaning period pups normally fast. These periods of reduced food intake may result in changes in metabolic rate, body mass and body composition [8-13]. In interspecific comparisons, fat content is correlated with metabolic rate [2,14]. However, intraspecifically, a decrease in body mass with a corresponding change in body composition due to starvation or undernutrition may be followed by a decrease in metabolic rate. This response is called metabolic depression and is found during starvation in both terrestrial and marine mammals [13,15-18] and during undernutrition or restricted feeding in terrestrial mammals

Address for correspondence: Division of General Physiology, University of Oslo, P.O. Box 1051 Blindern, 0316 Oslo, Norway.

384 [ 18,19]. The metabolic depression serves to increase survival time by reducing body mass loss [20]. A large proportion of the body mass of marine mammals is fat, consolidated into a blubber layer that serves as both thermal insulation and energy storage. Fasting therefore presents a problem in that excessive loss of fat might jeopardize thermal stability. Most studies of changes in body composition of seals during fasting have been carried out on pups or young individuals with inconsistent results. Reviewing earlier work on seals, Worthy and Lavigne [12] suggested that the conflicting reports might be due to previously undetected differences in the energy density of core tissues. Because death by starvation is linked to depletion of lean body mass, the contribution of fat tissue catabolism to the total energy expenditure also has a direct and profound effect on survival time [21,22]. In the present study we have examined the body mass loss, change in metabolic rate and body composition during starvation and restricted feeding in juvenile harbour seals.

Materials and Methods

Juvenile harbour seals were held at the University of Oslo with access to two swimming pools, one rectangular (3 x 8 m, 1.5 m deep) and one circular (2.5 m in diameter, 1.5 m deep), connected by dry haul-out platforms. Normally the seals were fed herring (Clupea sp.), ad libitum once or twice a day. During the starvation periods food was withheld for about 2 weeks, and during the restricted feeding periods, the seals were given about 10% of ad libitum intake daily in 2-3 weeks. Body mass was determined at 2 or 3-day intervals to the nearest 0.1 kg using a spring balance (Salter). Postabsorptive metabolic rates were measured before and during the restricted feeding period and during the starvation period by indirect calorimetry. The oxygen concentration of the expired air was analysed and metabolic rates were calculated from the oxygen consumption values assuming a caloric equivalent of 20 kJ/1 oxygen. Body composition of the seals was determined before and after the starvation periods and the restricted feeding periods using computed tomography (CT) (Siemens Somatom 2 scanner) [23]. Four cross-sectional images were made, one in the pelvic region, one in the abdominal region, one in the thoracic region, and one in the scapular region. The fat content in each cross-section was determined as a percentage of the total area and the mean value of the four sections from each seal was used as a measure of the fat content. For more detail, see Markussen et al. [17]. Q is defined as the energy equivalent of mass loss and may be considered an expression for the proportion of mass taken from lean body and fat tissues during starvation and is estimated from computer tomography data and by combining data on mass loss and maintenance energy requirements [24].

385

Results There were no significant differences in body mass loss during the starvation period compared to the period with restricted feeding. The mean body mass loss was 0.01 kg per day per kg body mass. By pooling the data from all seals, relative mass loss during starvation and semistarvation may be described by a linear function: BM% = 99.58 - 1.07T,

r 2 = 0.92

where BM% is the body mass as percentage of initial body mass and T is days of starvation or restricted feeding (Fig. 1). The resting metabolic rate was MR = (547.1 _+ 64.7)BM ~

kJ/24 h

before starvation and reduced to MRs = (442.6 _+ 55.2)BM ~ during starvation. prestarvation level:

kJ/24 h

During

MRr = (571 _ 84.7)BM ~

restricted

feeding,

metabolic

rate

remained

at

a

kJ/24 h

(Fig. 2). Fat content ranged from 26.8% to 34.4% before starvation (Fig. 3a) and decreased to values between 23.1% and 31.1% after starvation (Fig. 3b). Similarly, fat content ranged from 22.9 to 28.1% before the restricted feeding period and decreased to between 20.6 and 26.7%. The corresponding fat mass loss ranged from 1.6 kg to

~11o r~ Z lOO r~ <

8

9O

9 O oo 9 o. o

1] 8O

o!

O

80 0

O O

70

9

0

!

~

10

DAYS

I

20

Fig. 1. The body mass loss during restricted feeding (O) and starvation (O) in harbour seals. The body

mass before both restricted feeding and starvation is 100%.

386 I,.i

t,.,.

700

I

600

500

400

300

I

0

I

'

"

9

5

DAYS Fig. 2. The metabolic rate during restricted feeding (O) and starvation (O) in harbour seals.

4.0 kg in both groups. Assuming energy densities of 9.6 MJ/kg and 39 MJ/kg for lean body and fat mass, respectively, the energy equivalent of the mass loss (Q) for these seals ranged from 19.3 MJ/kg to 26.3 MJ/kg during the starvation periods and the restricted feeding periods. This implies that about 75% of the energy lost during starvation and restricted feeding was derived from fat.

Discussion

The body mass loss appeared to be constant at a rate of about 0.01 kg per day per kg body mass, which is similar to the mass loss observed in fasting grey seal (Halichoerus grypus) pups [13]. The relative body mass loss dropped linearly throughout the periods of both starvation and restricted feeding (Fig. 1). Although the seals were given 10% of ad libitum food intake during the restricted feeding periods, the body mass declined in the same manner as if the seals were starving. Since the body mass loss was similar for both groups, a different metabolic rate or a different energy equivalent of mass loss during starvation and restricted feeding may be the reason. A reduction in the energy required for maintenance is a major form of energy conservation during starvation and food restriction [25]. We found that metabolic rate was about 20% lower in starving seals compared with normal fed seals, and appeared to remain at the same level throughout the 2-week starvation period. The present pattem of metabolic depression is different from pattems described in terrestrial mammals where metabolic rate declines throughout the starvation period and the

387

b

Fig. 3. The body composition in a harbour seal before (a) and after (b) starvation shown by computer

tomography. metabolic depression factor is a function of the mass loss [ 15,19]. In our experiment the decrease occurred on the first day and after the initial drop, metabolic rate seemed to stay at a stable level throughout the fasting period. During restricted

388 feeding, however, the low energy intake seems to neutralize the metabolic depression observed during starvation. This is different from what is observed in terrestrial mammals and the reason for this mechanism is still unclear. This missing metabolic depression during restricted feeding may then be the reason for the similar body mass loss during starvation and semistarvation. The energy intake of about 2000-3000 kJ daily is greater than the energy that would have been saved by a metabolic depression found during starvation. However, this difference in energy may be explained by the heat increment of feeding [26] and different activity level in these groups. Reduction of basal metabolic rate is one of the most consistent results of undernutrition in humans [19], but is rarely expressed quantitatively [15]. Most of the contradictory interpretations, and therefore conclusions, reported for marine mammals [11-13,27-29] may be explained by assuming that thermoregulatory needs for increased heat production will override and thus potentially mask metabolic depression. Although all true basal metabolic rate measurements are made in the thermoneutral zone, the lower critical temperature will change during starvation [15]. Metabolic depression might thus be missed if the measurements are made at low temperatures. Several questions about the dual and conflicting role of seal blubber acting as an energy reservoir to be utilized during starvation and, at the same time, as an insulator against heat loss remain unresolved. The present study indicates that the contribution of fat tissue catabolism to the total energy expenditure of subadult harbour seals is similar (75%) to that of harp seal pups (72-80%) [12], but considerably lower than that of grey seal pups (94-97%) [12,13,27]. The difference may be due to age, but may also indicate that the hypothesis of Worthy and Lavigne [12] should be extended to encompass subadults and adults. The hypothesis states that seal pups which usually spend the postweaning fast on land have a higher rate of utilization of blubber than those fasting in cold water, because it is more expendable [ 12]. Harbour seal pups take to the water almost immediately after birth and subadults and adults do not exhibit extended fasting periods ashore [30]. The fat tissue catabolism appears to be the same during restricted feeding as under starvation. It may be worthwhile to note that the present study differs from most other fasting studies of seals in that this was a "forced" fast and restricted feeding as opposed to a "normal" fast and change in energy intake. Whether the physiology of these kinds of fast would be different is unknown at the present time. The result of the simultaneous energy contributions of fat and lean body tissues is conveniently expressed as a value Q which is a function of starvation time for humans [21 ], a function of the fat content for terrestrial mammals and perhaps a function of blubber thickness for harp seals [22]. Q would range between the values of energy densities of fat and lean body mass. The starvation survival time is related to the Q value [22] and it thus becomes important to obtain more information about the progression of Q during a starvation period. In juvenile harbour seals it was found that 75% of the energy used during a forced starvation period and during restricted feeding was taken from fat, which is similar to values reported for post-weaning harp

389 seal pups [12] and hooded seal pups [31 ], but lower than that observed in grey seal pups [11-13,29]. Stewart and Lavigne [32] showed that the initial mass loss of weaned harp seal pups appeared to occur primarily from the core and that blubber was spared because of its importance as an insulator. George et al. [33] showed that adult harp seal muscle has a low fat content, leading to the suggestion that the prime source of energy in these fasting seals was protein [32,34]. Although it has been assumed that young seals rely solely on blubber as their energy source during the postweaning fast [11,35], there is considerable evidence that several marine mammals species also use core reserves during periods of fasting and undernutrition [12,17,31,36-38]. In harp and hooded seal pups [12,31] and harbour seals, only 50% of the mass loss or 75% of the energy during starvation and restricted feeding is taken from fat. This indicates that the blubber layer is preferentially maintained for insulation throughout several days of undernutrition. This suggests that these seal species may go without food for a longer period than grey seal pups where an increased metabolic rate due to thermoregulatory needs [ 11 ] was observed after a longlasting starvation period [25].

Acknowledgement This study has been financially supported by the Norwegian Research Council (Sea Mammal Program).

References 1. Lavigne DM, Innes S, Worthy GAJ, Kovacs KM, Schmitz OJ, Hickie JP. Metabolic rates of seals and whales. Can J Zool 1986;64:279-284. 2. Kleiber M. The Fire of Life. New York: RE Krieger, 1975. 3. Irving L, Hart JB. The metabolism and insulation of seals as bare skinned mammals in cold water. Can J Zool 1957;35:497-511. 4. Hart JB, Irving L. The energetics of harbour seals in air and water with special considerations of seasonal changes. Can J Zool 1959;37:447-457. 5. Miller K, Irving L. Metabolism and temperature regulation in young harbor seals (Phoca vitulina richardi). Am J Physiol 1975;229:506-511. 6. Eisner R, Hammond DD, Denison DM, Wyburn R. Temperature regulation in the newborn Weddell seal, Leptonychotes weddelli. In: Ilano GA (ed) Adaptations Within Antarctic Ecosystems. Houston, TX: Gulf, 1977. 7. Heath ME, McGinnis SM, Alcorn D. Comparative thermoregulation of suckling and weaned pups of the northern elephant seal, Mirounga angustirostris. Comp Biochem Physiol 1977;57A:203206. 8. McLaren IA, Smith TG. Population ecology of seals: retrospective and prospective views. Mar Mammal Sci 1985; 1:54-83. 9. Mansfield A. Seals of arctic and eastern Canada. Fish Res Bd Can Bull 1967;No 137. 10. Sergeant DE. Feeding, growth, and productivity of northwest Atlantic harp seals (Pagophilus groenlandicus). J Fish Res Bd Can 1973;30:17-29.

390 11. Oritsland NA, PAsche A, Markussen NH, Ronald K. Weight loss and catabolic adaptations to starvation in grey seal pups. Comp Biochem Physiol 1985;82A:931-933. 12. Worthy GAJ, Lavigne DM. Mass loss, metabolic rate, and energy utilization by harp and gray seal pups during the postweaning fast. Physiol Zool 1987;60:352-364. 13. NordCy ES, Ingebretsen OC, Blix AS. Depressed metabolism and low protein catabolism in fasting grey seal pups. Acta Physiol Scand 1990;139:361-369. 14. McNab BK. Body weight and the energetics of temperature regulation. J Exp Biol 1970;53:329348. 15. Markussen NH, Oritsland NA. Metabolic depression and heat balance in starving Wistar rats. Comp Biochem Physiol 1986;84A:771-776. 16. Reilly JJ. Adaptations to prolonged fasting in free-living weaned gray seal pups. Am J Physiol 1991 ;260:R267-R272. 17. Markussen NH, Ryg M, Oritsland NA. Metabolic rate and body composition of harbour seals, Phoca vitulina, during starvation and refeeding. Can J Zool 1992;70:220-224. 18. Munch IC, Markussen NH, Oritsland NA. Resting oxygen consumption in rats during food restriction, starvation and refeeding. Acta Physiol Scand 1993; 148:335-340. 19. Grande F, Anderson JT, Keys A. Changes of basal metabolic rate in man in semistarvation and refeeding. J Appl Physiol 1958;12:230-238. 20. Oritsland NA. Physiological functions pertinent to modelling energy balance at the population level. In: Reimers E, Gaare E, Skjenneberg S (eds) Proc 2nd Int Reindeer/Caribou Symp, Direktoratet for Vilt og Ferskvannsfisk, Trondheim, Norway, 1980;350-354. 21. Oritsland NA. Starvation survival and body composition in mammals with particular reference to Homo sapiens. Bull Math Biol 1990;52:643-655. 22. Oritsland NA, Markussen NH. Outline of a physiological based simulation model. Ecol Model 1990;52:267-288. 23. Skjervold H, GrCnseth K, Vangen O, Evensen E. In vivo estimation of body composition by computerized tomography. Z Tier Zuechtungsbiol 1981;98:77-79. 24. Markussen NH, Ryg M, Oritsland NA. Energy requirements for maintenance and growth of captive harbour seals, Phoca vitulina. Can J Zool 1990;68:423-426. 25. Hill JO, Latiff A, DiGirolamo M. Effects of variable caloric restriction on utilization of ingested energy in rats. Am J Physiol 1985;248:R549-R559. 26. Markussen NH, Ryg M, Oritsland NA. The effect of feeding on the metabolic rate in harbour seals (Phoca vitulina). J Comp Physiol B 1994;164:89-93. 27. Brodie PF, PAsche AJ. Density-dependent condition and energetics of marine mammal population in multispecies fisheries management. In: Mercer MC (ed) Multispecies Approaches to Fisheries Management Advice. Can Spec Publ Fish Aquat Sci 1982;59:35-38. 28. Davydov AF. Heat production in harp seal during physiological fasting. Mar Mammal Inf 1983;Dec. 29. NordCy ES, Blix AS. Energy sources in fasting grey seal pups evaluated with computed tomography. Am J Physiol 1985;249:R471-R476. 30. King JE. Seals of the World. British Museum (Natural History). Ithaca, NY: Comstock/Cornell University Press, 1983. 31. Bowen WD, Boness DJ, Oftedal OT. Mass transfer from mother to pup and subsequent mass loss by the weaned pup in the hooded seal, Cystophora cristata. Can J Zool 1987;65:1-8. 32. Stewart REA, Lavigne DM. Neonatal growth of northwest Atlantic harp seal, Phoca groenlandica. J Mammal 1980;61:670-680. 33. George JC, Vallyathan NV, Ronald K. The harp seal, Pagophilus groenlandicus (Erxleben 1777). VII. A histophysiological study of certain skeletal muscles. Can J Zool 1971 ;49:25-30. 34. Bailey BA, Downer RGH, Lavigne DM. Neonatal changes in tissue levels of carbohydrate and lipids in the harp seal, Phoca groenlandica. Comp Biochem Physiol 1980;67B:179-182.

391 35. Iversen JA, Krog J. Heat production and body surface area in seals and sea otters. Nor J Zool 1973 ;21:51-54. 36. Bryden MM. Relative growth of the major body components of the southern elephant seal, Mirounga leonina (1.). Aust J Zool 1969;17:153-177. 37. Ridgeway SH. Homeostasis in the aquatic environment. In: Ridgeway SH (ed) Mammals of the Sea: Biology and Medicine. Springfield, IL: Thomas, 1972;590--780. 38. Worthy GAJ, Lavigne DM. Energetics of fasting and subsequent growth in weaned harp seal pups, Phoca groenlandica. Can J Zool 1983;61:447-456.

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9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang,editors

393

Variation in the metabolic rates of captive harbour seals David Rosen and Deane Renouf Biopsychology Programme and Ocean Sciences Centre, Memorial University, St. John's, NF, Canada Abstract. Background: harbour seals show distinct circannual rhythms in body mass, energy intake, rectal temperatures, and plasma thyroxine levels. It was predicted that these cycles may be concurrent with seasonal changes in their metabolism. Methods: the resting metabolic rates of six captive harbour seals (Phoca vitulina concolor) were estimated monthly, over 18 months. Metabolism was measured using open-circuit gas (indirect) calorimetry. Results: metabolic rates varied during the year, but all the seals exhibited a similar pattern. Metabolism was highest in April and August, and lowest in June and November. There was a 35% decrease between periods of highest and lowest metabolism. There was also a general decline in the yearly mean metabolic rate with seal age. The yearly mean metabolic rate of the eldest male and the female did not differ from that predicted for terrestrial mammals. Conclusions: as predicted, the periods of high and low metabolism corresponded to observed periods of high energy utilization and conservation, respectively. Although a number of physiological and behavioural factors are controlled for when estimating metabolism, failure to account for possible temporal changes may lead to substantial errors.

Key words: phocids, energetics, Phoca vitulina, circannual rhythm

Introduction Knowledge of metabolic rates is essential for estimating the energy budget of an individual or population [1-3]. While much effort has been devoted to determining metabolic consumption in phocid seals, little attention has been paid to possible circannual rhythms. Studies examining temporal changes in the metabolism of phocid seals have generally been limited to the relatively short periods encompassing lactation, breeding, moulting, and/or seasonal fasts. The possibility of significant changes occurring during other times of the year has largely been left unresearched. Recent studies on captive harp seals (Phoca groenlandica) suggest that significant changes in metabolic demands occur throughout the year [4] (Hedd, unpublished data). Previous studies on harbour seals (Phoca vitulina) have uncovered large changes in metabolic rates between the breeding and moulting periods [2,5]. This study was undertaken to examine metabolic rates in a group of captive harbour seals over an entire year. Indirect evidence for seasonal changes in metabolism arises from past studies on these same captive harbour seals that demonstrated an unusual relationship between mass changes and energy intake [6,7]. These authors noted that, at certain times of the year (primarily the mating season), the seals lost mass despite an increase in en-

Address for correspondence: D. Rosen, Biopsychology Programme, Memorial University, St. John's, NF, Canada A 1B 3X9.

394 ergy intake. Conversely, there were times of the year when they gained mass despite a substantial reduction in energy intake. Concurrent with these changes are shifts in plasma thyroxine levels [5,7] and rectal temperatures (Rosen, unpublished data). Given these observed trends, we predicted that the captive harbour seals would display significant circannual variation in their metabolic rates.

Methods

The study group consisted of six captive Atlantic harbour seals (Phoca vitulina concolor). There were 5 males (males 1-5) who were 20, 14, 7, 6, and 1 years old at the start of the study, and one female aged 14 years. Animals were kept together in an outdoor compound year round at the Ocean Sciences Centre (Memorial University). The three youngest seals were born at the facility and the eldest three were introduced as pups. The female has given birth several times in captivity, including in 1992. The 1992 pup (not included in this study) was weaned before the start of metabolic trials, and the female did not give birth in 1993. The compound consisted of three tanks (80, 5, and 4.5 m 3) containing ambient sea water, surrounded by 100 m 2 of wooden deck for hauling out. Animals were fed thawed herring (Clupea harengus) ad libitum for 30 min, once per day. The seals were not fed for at least 24 h before the metabolic determinations. Prior to metabolic tests, the seals were weighed with either an analog scale (accurate to 500 g) until 20 October 1992, or with a digital scale accurate to 200 g, thereafter. Metabolism was measured using open-circuit gas (indirect) calorimetry. The testing chamber was a circular fibreglass tank (2.5 m high, 1.8 m diameter, 6400 1), which was filled with ambient sea water at the start of each test. The chamber was covered by a lexan and fibreglass respiration hood (volume = 25 1). Air was drawn through the hood at a rate of 129-132 1/min, sufficient to avoid a build up of expired gases within the hood (specifically, average minute fraction 02 < 0.5%, CO2 < 1.0%). Air was drawn by two Deltatrac Metabolic Monitors (Datex Instrument Corp., Helsinki, Finland). The monitors determined 02 and CO2 concentrations by paramagnetic and infrared sensors, respectively. Rates of oxygen consumption (~'o2) and CO2 expiration (~'co2) were calculated and recorded each minute. Before each test the machines were calibrated using a gas of known concentration. In addition, the flow rates of the Deltatracs were periodically verified using an iron burn method [8]. The animals were tested approximately once per month for 20-24 h. The first seal was tested 14 July 1992 (after a series of acclimation trials) and the last on 2 November 1993. At the conclusion of each test the data were downloaded to a personal computer. Hourly averages for rates of 02 consumption and CO2 expiration were calculated, discarding the partial first and last hours from the analysis. Subjects were rarely quiescent for long periods during a test. The seals' natural propensity for activity made it essential to take this metabolic factor into account for

395 comparative purposes. Naturally occurring variation in swimming rates has been used to estimate basal metabolic rates in harbour seals [9] (Hedd, personal communication). In the present study, the seals were videotaped from 2000 to 0800 h through a convex Plexiglas window inset into the side of the tank during each metabolic test. Objective activity scores were obtained for each of the 12 videotaped hours, which were linearly regressed against mean hourly 02 consumption to yield a I)'02 when activity equalled zero. The resulting value was used as the metabolic rate. The large number of behavioural and physiological variables which can affect metabolic rates necessitate a standard measurement criterion for comparative purposes [10]. Basal metabolic rate (BMR), a common comparative measure, is defined as the energy consumption of a post-absorptive, mature (non-growing), nonpregnant, quiescent (not active, but awake) individual, tested within its thermoneutral zone [11]. In this study, there was at least one growing animal (male 5) and, since the animals were being tested under natural climatic conditions, thermoneutrality could not always be guaranteed. Due to these possible infractions upon Kleiber's [ 11 ] original criteria, the term "resting metabolic rate" (RMR) is used in this study. In this paper RMRs are presented as a multiple of Kleiber's prediction for the basal metabolic rate of mature, terrestrial mammals (metabolism = 70 kcal/day x mass(kg)~ Hence, animals with a RMR of twice this predicted value are denoted as "2.00K".

Results

The animals displayed substantial variation in both body mass and RMR over the course of the experiment (Table 1). The yearly mean RMRs showed a general decline with age among the males, from a mean of 2.08K in the yearling to 1.12K in the eldest male. The female' s yearly mean (1.14K) was similar to the latter. Metabolic rates varied during the year, but all the seals exhibited a similar pattern. Metabolism was highest in April and August, and lowest in June and November. Table 1. Data summary (yearly mean +_ standard deviation) of mass and metabolic rates for the captive seals from August 1992 to August 1993 Seal

Age (years)

Mass (kg)

Male 1 Male 2 Male 3 Male 4 Male 5 Female

20 14 7 6 1 14

99.8 83.9 89.2 78.9 49.1 82.8

+_6.98 _ 8.99 +_.4.67 _ 4.97 +_.4.63 _ 7.53

RMR (ml 0 2 kg -1 min -1)

RMR/Kleiber

3.62 4.79 4.95 5.58 7.98 3.83

1.12 1.43 1.50 1.64 2.08 1.14

+_ 1.135 _ 0.631 +_.0.813 _ 1.218 +_. 1.301 _ 0.909

+_0.334 _+0.175 +_0.246 _ 0.338 _ 0.335 _+0.255

Resting metabolic rates are listed both as mass-specific oxygen consumption and as a multiple of Kleiber's prediction for terrestrial mammals (see text for how metabolism was estimated). The ages of the seals at the start of the experiment are also given.

396 Table 2. Selected data (1992-1993) of resting metabolic rates for the six seals to illustrate seasonal variation

Subject

August

November

April

June

August

Male 1

1.73

Male 2

1.70

Male 3

1.64

Male 4

1.94

Male 5

1.98

Female

1.09

Means

1.68

0.72 -58 1.21 -29 1.28 -22 1.31 -32 1.25 -37 0.74 -32 1.09 -35

1.38 +91 1.77 +47 2.22 +74 2.38 +81 2.57 +106 1.51 +104 1.97 +84

0.83 -40 1.27 -28 1.23 -45 1.41 -41 1.57 -39 1.18 -22 1.25 -36

1.15 +38 1.63 +28 1.42 +16 1.88 +33 2.12 +35 1.39 +18 1.63 +30

Top cells are the resting metabolic rates expressed as a multiple of the value predicted by Kleiber for terrestrial mammals (see text). The bold numbers below them are the percent change from the previous period. The results are listed by subject, as well as averaged over all animals.

Overall, there was a 35% decline in RMR from August (1.68K) to November (1.09K) (Table 2). This was followed by an 84% increase from November to April, which brought the average RMR (1.97K) higher than the August estimate. There was another decline of 36% leading to a low point in June (1.25K), followed by a 30% increase between June and August (1.63K). The mean RMR in August at the start of the experiment was slightly higher than the mean obtained the following year.

Discussion

Most metabolic studies of phocid seals have been brief, so have therefore been unable to distinguish temporal changes. The results of this study indicate substantial variation of RMR with age, superimposed upon an underlying circannual rhythm. Across seals there was a general decline in the yearly mean RMR with age, with the mean RMR of the eldest seal (male 1) and the female not significantly different from Kleiber's [11] prediction of B MR for a terrestrial mammal. The RMR of the yearling was 2.083K. It is generally accepted that young animals have elevated metabolic rates [12], but the persistence of these phenomena is unknown. AshwellErickson and Eisner [2], supplementing their own data with that from Miller and Irving [13] and Miller et al. [14], suggested a gradual decline in RMR from 2 months of age onwards. The results from this study support their hypothesis. AshwellErickson and Eisner [2] also suggested that declines in metabolic rates were more closely tied to maturity rather than age per se. As female harbour seals reach sexual and physical maturity faster than males [15,16], it is not surprising that the female had a yearly average RMR equivalent to that of the male 6 years her elder.

397 Seasonal variation in RMRs was also observed and was evident across all the seals. The results are similar to the changes exhibited by harp seals [4], where metabolism was high in the summer and low during the winter. The decreases found between the pre- and post-moult values were even more extreme than previously reported for harbour seals. Ashwell-Erickson and co-workers demonstrated decreases in RMR of 17% [2] and 18.6% [5]. The seals in this study showed an average decline in RMR of 35% between August and November. These changes seem to be hormonally driven, as several studies have demonstrated a relationship between decreasing plasma thyroxine, increasing plasma cortisol, and the moult [2,7,17]. The high metabolic rates in August correspond to the end of the mating and the start of the moult period. There is evidence of the high reproductive effort incurred by male harbour seals during the mating period [ 18-21 ]. Reilly and Fedak [22] found that the daily energy expenditure (DEE) of male adult harbour seals was 6.00K, and 1.5 times the DEE predicted by Nagy [23]. This period of high energy expenditure and negative energy balance [22] may last several weeks [24,25]. It is not surprising, therefore, that these periods of increased energy demands are characterized by high RMRs. The female also showed a large difference in RMR between the reproductive and moult periods. Among phocid seals, the main energy expenditure of females during the reproductive period is assumed to be lactation [26-29]. In this study, the female continued to exhibit an elevated RMR after lactation had ceased in 1992, and in 1993 when she was not pregnant. Clearly, in this study, the female's elevated RMRs were related to other aspects of her reproductive effort. The lower metabolic rates seen in November and June occurred during periods when body mass increased despite a decline in energy intake. Although many studies on phocid energetics were undertaken during the moult period (when most species naturally restrict feeding), the effect of decreased energy intake on metabolism is often difficult to ascertain because of concurrent changes in behaviour (pupping, moulting, mating, lactation). However, evidence indicates that some species (such as northern elephant, Mirounga angustirostris, and harp seals) lower their metabolic demands, and possibly their deep body temperatures, in order to conserve energy stores [30-33]. In a forced starvation experiment, Markussen et al. [9] found that the metabolic rates of harbour seals declined by 20% over 16 days. Metabolism then returned to previous levels about a week after the onset of feeding. The harbour seals in this study also exhibited low RMRs during periods of hypophagia, as well as depressed rectal temperatures during these periods of energy conservation (Rosen, unpublished data). As seen in other species, the seals in this study seem to exhibit bioenergetic adaptations to predictable changes in energy intake and demands.

Acknowledgements The authors would like to thank E. Noseworthy, G. Dalton, T. Dunphy, and A. Hedd

398

for their assistance with the data collection. J. Lawson and E. Miller provided useful criticisms on the original manuscript. This work was supported by grants and scholarships provided by: Canadian Centre for Fisheries Innovation, Canadian Dept. of Fisheries and Oceans, the Natural Sciences and Engineering Council (Canada), and Memorial University. This is O.S.C. Contribution No. 250.

References 1. Markussen N, Ryg M, Lydersen C. Food consumption of the NE Atlantic minke whale (Balaenoptera acutorostrata) population estimated with a simulation model. ICES J Mar Sci 1992;49:317-323. 2. Ashwell-Erickson S, Eisner R. The energy cost of free existence for Bering Sea harbor and spotted seals. In: Hood DW, Calder JA (eds) The eastern Bering Sea Shelf: Oceanography and Resources. Seattle, WA: University of Washington Press, 1981 ;869-899. 3. Oritsland N, Markussen N. Outline of a physiologically-based model for population energetics. Ecol Model 1990;52:267-286. 4. Renouf D, Gales R. Seasonal variation in the metabolic rate of harp seals: unexpected energetic economy in the cold ocean. Can J Zool (in press). 5. Ashwell-Erickson S, Fay FH, Eisner R, Wartzok D. Metabolic and hormonal correlates of molting and regeneration of pelage in Alaskan harbor and spotted seals (Phoca vitulina and Phoca largha). Can J Zool 1986;64:1086-1094. 6. Renouf D, Noseworthy E. Feeding cycles in captive harbour seals (Phoca vitulina): weight gain in spite of reduced food intake and increased thermal demands. Mar Behav Physiol 1990;17:203212. 7. Renouf D, Noseworthy E. Changes in food intake, mass, and fat accumulation in association with variations in thyroid hormone levels of harbour seals (Phoca vitulina). Can J Zool 1991;69:2470-2479. 8. Young B, Fenton T, McLean J. Calibration methods in respiratory calorimetry. J Appl Physiol 1984;56:1120-1125. 9. Markussen NH, Ryg M, Oritsland NA. Metabolic rate and body composition of harbour seals, Phoca vitulina, during starvation and refeeding. Can J Zool 1992;70:220-224. 10. Lavigne DM, Innes S, Worthy GAJ, Kovacs KM, Schmitz OJ, Hickie JP. Metabolic rates of seals and whales. Can J Zool 1986;64:279-284. 11. Kleiber M. The Fire of Life: an Introduction to Animal Energetics. New York: RE Krieger, 1975. 12. Poczopko P. Metabolic rate and body size relationships in adult and growing homeotherms. Acta Theriol 1979;24:125-136. 13. Miller K, Irving L. Metabolism and temperature regulation in young harbor seals Phoca vitulina richardi. Am J Physiol 1975;229:506-511. 14. Miller K, Rosenmann M, Morrison P. Oxygen uptake and temperature regulation of young harbor seals (Phoca vitulina richardi) in water. Comp Biochem Physiol 1976;54A:105-107. 15. Boulva J, McLaren IA. Biology of the harbour seal, Phoca vitulina, in eastern Canada. Bull Fish Res Bd Can 1979;200:24. 16. Markussen NH, Bjr A, Oritsland NA. Growth in harbour seals (Phoca vitulina) on the Norwegian coast. J Zool London 1989;219:433-440. 17. Riviere JE, Engelhardt FR, Solomon J. The relationship of thyroxine and cortisol to the moult of the harbor seal, Phoca vitulina. Gen Comp Endocrinol 1977;31:398-401. 18. Thompson PM, Fedak MA, McConnell BJ, Nicholas KS. Seasonal and sex-related variation in the activity patterns of common seals (Phoca vitulina, L.) in the Moray Firth, Scotland. J Appl Ecol 1989;26:521-535.

399 19. Thompson PM, Miller D. Summer foraging activity and movements of radio-tagged common seals (Phoca vitulina, L.) in the Moray Firth, Scotland. J Appl Ecol 1990;27:492-501. 20. Harkonen T, Heide-JCrgensen M-P. Comparative life histories of east Atlantic and other harbour seal populations. Ophelia 1990;32:211-235. 21. Walker BG, Bowen D. Changes in body mass and feeding behaviour in male harbour seals, Phoca vitulina, in relation to female reproductive status. J Zool London 1993;231:423-436. 22. Reilly JJ, Fedak MA. Rates of water turnover and energy expenditure of free-living male common seals (Phoca vitulina). J Zool London 1991 ;223:461-468. 23. Nagy KA. Field metabolic rate and food requirement scaling in mammals and birds. Ecol Monogr 1987;57:111-128. 24. Pitcher KW. Variation in blubber thickness of harbour seals in southern Alaska. J Wildlife Manage 1986;50:463-466. 25. Thompson P, Rothery P. Age and sex differences in the timing of moult in the common seal, Phoca vitulina. J Zool London 1987;212:597-603. 26. Fedak MA, Anderson SS. The energetics of lactation: accurate measurements from a large wild mammal, the grey seal (Halichoerus grypus). J Zool London 1982;198:473-479. 27. Oftedal OT, Boness DJ, Tedman RA. The behaviour, physiology, and anatomy of lactation in the pinnipedia. Curr Mammal 1987; 1:175-245. 28. Bonner WN. Lactation strategies for pinnipeds: problems for a marine mammal group. Symp Zool Soc London 1984;51:253-272. 29. Costa DP, LeBoeuf BJ, Huntley AC, Ortiz CL. The energetics of lactation in the northern elephant seal, Mirounga angustirostris. J Zool London 1986;209:21-33. 30. Castellini MA, Rea LD. The biochemistry of natural fasting at its limits. Experientia 1992;48:575582. 31. Rea L, Costa D. Changes in standard metabolism during long-term fasting in northern elephant seal pups. Physiol Zool 1992;65:97-111. 32. Nord~y E, Aakvaag A, Larsen T. Metabolic adaptations to fasting in harp seal pups. Physiol Zool 1993;66:926-945. 33. Worthy GAJ, Morris PA, Costa DP, LeBoeuf BJ. Moult energetics of the northern elephant seal (Mirounga angustirostris). J Zool London 1992;227:257-265.

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Population dynamics

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9 1995 ElsevierScience B.V. All rights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

403

Population dynamics" species traits and environmental influence Charles W. Fowler National Marine Mammal Laboratory, Seattle, WA 98115, USA Abstract. The population dynamics of species constitute species level properties that are both genetically and environmentally influenced. General patterns in population dynamics related to life-history strategies result from the expression of genetically based traits. Variability about such patterns is under environmental influence. A correlation between the shape of density-dependence curves and rates of increase per generation is an example of genetically controlled patterns. Deviation from such patterns exemplifies the degree to which the shape of density-dependence curves is related to conditions faced by species interacting with both their biotic and abiotic surroundings. The genetic aspects of both species- and ecosystem-level traits are subject to modification through exploitation. Most resource and ecosystem models fail to account for genetic change produced by harvesting. Key words: life-history strategy, inflection points, genetic influence of harvests, evolution of densitydependence

Introduction

Conventional resource management, especially as applied to fish and other wildlife populations, makes use of quantitative models. To varying degrees, simulation models are assumed to represent populations and serve as their surrogates. Calculations are then made with these models to determine levels for harvest or protection to achieve a variety of management objectives. These objectives include hunting or fishing to satisfy human needs for economically valuable products (e.g. food), while protecting resources and preserving future options. In the case of protected species, one management objective is to prevent extinction of critical populations. The application of quantitative models is based on empirical data since the models are fit to measures of populations such as abundance, growth rates, and production. Resulting models are then used to derive reference points or criteria used for management. For example, the concept of "maximum sustained yield" (MSY) is a familiar biological reference point. Other reference points include (in abbreviated notation) TAC, Fpred, nopt, Ere p, Fo. 1, Fop t, Fmmy, Fma x, Fme d, Flo w, TACo.1, and ABC; n e w ones are suggested regularly [ 1]. During the 1970s and 1980s biologists became increasingly aware of pattems (e.g. shape or parameter values) in the formulation of population models that applied to species with different life-history strategies. Of particular interest was the shape of density-dependent functions in comparison with the well known linear form of the

Address for correspondence: National Marine Mammal Laboratory, 7600 Sand Point Way NE, Bin C15700, Seattle, WA 98115, USA.

404 logistic model. Based on a variety of fisheries models [2,3] and other work [4,5] it became clear that nonlinearity is a prevalent feature in the density dependence of animal populations. In particular it has become clear that most large mammals show the majority of their density-dependent change at population levels close to their carrying capacity [6]. Later, correlations between the shapes of density-dependence curves and life-history strategies began to emerge [4,5,7,8]. Such patterns were considered important because of their implications regarding desirable or legally required population levels, harvest levels [9], and both population- and ecosystemassessment methodology [ 10]. In spite of the progress made in single-species assessment and management, overutilization of resources is still common. For example, about 45% of US, and 59% of European, commercial fisheries have been deemed overfished [11]. Several factors contribute to overfishing; scientific research is not always well-communicated or accepted by resource managers and commercial, economic and political interests often override scientific advice [12]. Lastly, given the complexity of nature, it seems clear that the single-species model provides inadequate, or misleading information for resource managers. In this paper, it is argued that a major flaw in resource management is that species are recognized as discrete genetic entities but are not treated accordingly. This flaw is manifested in the determination of species' characteristics through model fitting while assuming that these characteristics cannot change in the time frames over which management is effected. The species characteristics developed during their evolution in response to the conditions of their environment but harvesting changes these conditions and produces novel selective pressures. These new environmental factors result in genetic modifications which alter the original species characteristics. Following arguments made elsewhere [13,14], I now describe how density dependence, as one feature of population dynamics, is a genetically determined speciesspecific trait. It is argued that the use of single-species models as a basis for establishing harvest levels may lead to genetic changes in population parameters which, in turn, lead to over-exploitation of a resource.

Genetic Basis for Patterns

Species may be considered as populations (or made up of populations) which fluctuate around a mean population level. This population level, over certain time scales, may be viewed as a characteristic species-specific carrying capacity (K). This situation is shown in Fig. 1 as a frequency distribution of population levels for a hypothetical species (e.g. a bell-shaped curve). For illustration, the species envisioned is in the initial stages of developing density-dependent demographic behavior through natural selection. Females in such a fluctuating population may be divided into two groups. The first group would be those that exhibit density-dependent change, however minimal, and the second group would show none. Part of the density to which these females are responding is determined by the abundance of

405

a

b..

~

~

~ >.. 0 r O" L_ 14-

Population size Fig. 1. Rate of increase for a hypothetical population in relation to population size, shown for two groups of females which differ in the degree of density-dependent response to population variation around the carrying capacity (K). Line (a) shows more pronounced density dependence in comparison to line (b) (which has less slope and would be flat for females with no density dependence).

males in the population. Furthermore, the responses are integrated responses involving all direct and indirect reactions to population level, including those from the ecosystem in response to population change. The first group is comprised of females which, when below the mean population level, exhibit on average a rate of increase (r) that is larger than the mean increase for the population as a whole. Thus, although specific individuals are expected to show changes in their contribution to r over time and circumstances, in integrating their responses, females of group one exhibit a higher mean rate of increase when below K. The other group is made up of individuals which, at the same reduced population level, contribute at a rate that is on average less than the mean for the population (i.e. no, or less, density dependence). In Fig. 1 the first group (more density dependence) is represented by line (a) and the second group (less density dependence) is represented by line (b). As the population increases in its return to K, females with the higher realized rates of increase (because of their density dependence) will have contributed more of their genetic material to the population than those with the lower rates. If both the rate of increase and its change in relation to population reduction is even partially genetically determined, this represents a change in the genetic composition of the population. A change in gene frequency has occurred as a genetic change within the population. A similar change will occur if the population is reduced again through any source of mortality independent of the genetic composition of the population or its abundance. With each succeeding iteration of such events, the average rate of increase for a population at a specific fraction of K will more closely approximate that of the more reproductive individuals. Similar dynamics also apply to populations when they exceed the K. But here the lag effect between rate of increase and its effect on a subsequent generation is criti-

406 cal. Because of their less well developed density-dependent reaction to population size (and environmental conditions that change in response to population size), females from the second group devote resources to a higher rate of increase than those from the first group when above K. But females of the second group ultimately contribute less to future generations (i.e. have lower fitness) because the demands of producing offspring when resources are limited results in the production of fewer viable offspring (i.e. that survive to reproduce) and increased risks to their own survival. Meanwhile, females from the first group have a lower rate of increase yet survive to be (or contribute to) a larger part of the next generation. Thus, group one, characterized by more density dependence (line (a) in Fig. 1) will be represented by more females or their offspring (and the respective genetic material) in succeeding generations than will the females with less density dependence and higher rates of increase above K (line (b)). Thus, females of group one are selected for whether the population is above or below K. Through repeated cycles through this process, the rate of increase characteristic of reduced population levels increases, but not without limits. It eventually reaches a point at which the same selective forces at work above K (those with lag effects) counteract further increases for population levels below K. In other words, the slope of the resulting line is not expected to become vertical since females can also suffer reduced fitness through rates of increase that are too high when the population is below K. Thus, over time, successive exposures to population levels above and below the K lead to genetically controlled adaptive rates of increase in relation to population size. An evolutionarily stable strategy is expected and is characteristic of the species. It is measured as the slope of the line depicting the degree of density dependence for population levels near K in Fig. 1. The scenario presented above is a description of the process of evolution expected in the development of density dependence and explains the origin and existence of a negative slope in the relationship between rate of increase and population density at K. Species exhibit varying degrees to which their populations fluctuate about K, a feature that depends on their life-history strategy. Some species, for example, mature late in life, have small litter (clutch) size, and exhibit low population variability under normal circumstances (characteristics of K-selected species [7]). This is represented by the narrow frequency distribution of population sizes shown in Fig. 2a. Such species rarely experience population levels far below K, and there is little selective pressure to elevate the rate of increase beyond those levels achieved when at the low end of the range of normal population levels. Thus, there is an upper limit to density-dependent change in rate of increase. This situation is depicted in Fig. 2a by the curved solid line which reaches an asymptote outside the range of normal population variation. Species that fluctuate more show a different pattern as r-selected species [7]. Such species are more frequently exposed to population levels well below their mean population level (Fig. 2b, shown by the broad frequency distribution). They tend to mature early in their life and have large litter (clutch) size. These species experience

407

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a

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less limits to their rates of increase. The solid curved line in Fig. 2b shows how natural selection allows for greater density-dependent elevation in the rate of increase than is possible for species of the type shown in Fig. 2a. Thus, evolution results in a pattern relating the shape of the density-dependence curve (and the equivalent position of the inflection point in population growth curves) to life-history strategy. The effects of natural selection as described above occur on a time scale linked to generation time. The resulting pattern is one in which the curvature of the lines of Figs. 2a,b is correlated with the rate of increase per generation [7,8]. This curvature is an evolved species-level trait. Figure 3, then, is a representation of the evolutionary pattern achieved by species in evolving various lifehistory traits that are adaptations to their respective environments. Species at the lower right of the relationship in Fig. 3 are r-selected species with high population variability and density-dependent rates of increase shown in Fig. 2b [7]. Species at the upper left are K-selected species with lower population variability and densitydependent rates of increase shown in Fig. 2a. Since the life-histories themselves have

408 1.0

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T h e Effects of H a r v e s t i n g

Human predation, like other forms of predation, presents harvested species with selective pressures to which they respond through genetic change. Documentation of the genetic effects of harvesting has been accumulating since at least 1957 [15] and is now of concern in fisheries management [16]. Of considerable importance in the present context are the effects of harvesting on life-history strategies [17]. Components of life history that have responded to harvesting are age at first reproduction, reproductive rate, and growth rate [ 15,18-22]. Another example of life-history alteration involves the harvest of female northern fur seals between 1956 and 1968 on the Pribilof Islands, Alaska. During that harvest nearly 300,000 females were killed, predominantly from the younger age groups [23]. Early maturing young females may have been more available for harvest than

409 late maturing females of the same age. For example, the early maturing females would be more likely to return to the island to copulate than the immature females of the same age. This harvest may have selectively removed females which matured early [24]. One possible result of this removal is a genetically based increased age at first reproduction [24]. As shown in Ref. [24], there is a negative relationship between age at first reproduction and juvenile survival (estimated for juvenile males). Within this correlation, age at first reproduction declines with increasing survival as would be expected in a density-dependent change [25]. However, this relationship changed following the harvest (Fig. 4), a change in which the slope of the correlation remained the same but the intercept rose. Thus, for a given level of survival, the age at first reproduction increased by about 0.6 years during the years of the harvest. This change was opposite that expected in a density-dependent reaction and inconsistent with other observed density-dependent reactions for northern fur seals during the population decline caused by the harvest [25]. Furthermore, whatever caused this deviation had to be extensive enough to overcome opposing density-dependent change. Thus, to the extent that age of maturity is genetically determined, the increase in age at maturity may reflect an effect of the harvest on the genetic makeup of the population. The direct effects of the harvest may account for part of the observed

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I 0.48

Juvenile survival Fig. 4. Age at first reproduction for female northern fur seals, from the Pribilof Islands, Alaska, and their correlation with juvenile male survival, grouped according to the 1956-1966 year classes (during the female harvest) and the 1952-1955 year classes (before the harvest, modified from [24]).

410 decline between 1956 and 1968 [23], if for no other reason than its contribution to reduced productivity. The production of pups by young females is a significant contribution to population growth (or in the case of a harvested population, the production of harvestable individuals). Thus, genetic changes may explain part, or all, of what cannot be accounted for by the harvest [23]. Changes in the genetic composition (change in gene frequency related to age at first reproduction) of this population may also help explain the lack of recovery following the termination of the harvest in 1984. Of importance here is the fact that the components of life history (e.g. age at maturation) that may be modified by harvesting also influence rates of increase and generation time. Changes in the components of population dynamics thereby alter the rate of increase per generation which, in turn, would change the shapes of productivity and growth curves of the type shown in Fig. 2 in accord with the relationship shown in Fig. 3. With current knowledge, the direction or magnitude of these changes remain unpredictable. In accounting for the uncertainty of these changes the effects of genetic change must be considered, especially in management applications.

Discussion Because of the links between life-history strategies, population dynamics, and harvesting, conventional resource management models may be misleading and using them may lead to mistakes. A population model fit to data at one point in time is likely to become obsolete owing to the effects of harvesting through their impact on population genetics. In some cases the genetic alteration of the population characteristics of a species may result in conservative management advice. In contrast, change in the genetic composition of a population can lead to overharvesting when initial models recommended harvest levels that populations with altered life-history strategies cannot support. Changes in genetic composition may affect more than just the harvested species. Altering target species by harvesting results in an altered biotic environment for other species in the ecosystem. These changes may result in secondary genetic changes among these other species as well. The complexity and nature of ecosystem interactions make the management of renewable resources difficult and are the source of further uncertainty to be accounted for in management. This conclusion is not meant to imply that fitting population models to empirical data is an invalid means of characterizing populations. The point is that the measurements upon which models are based are for properties of species that are vulnerable to environmental influences and particularly those produced by harvesting.

Acknowledgement I wish to thank Jason Baker, Howard Braham, Gary Duker, Jeff Hard, Tom

411

Loughlin, Rolf Ream, and Anne York for reviews of earlier drafts of this paper and the improvements made as a result of their efforts.

References 1. Smith SJ, Hunt JJ, Rivard D (eds). Risk evaluation and biological reference points for fisheries management. Can Spec Publ Fish Aquat Sci 1993;120. 2. Beverton RHH, Holt SJ. On the dynamics of exploited fish populations. Fisheries Investigation Series 2, Number 19. London, UK: United Kingdom Ministry of Agriculture and Fisheries, 1957. 3. Ricker WE. Handbook of computations for biological statistics of fish populations. Bull Fish Res Bd Can 1958;191. 4. Stubbs M. Density dependence in the life-cycles of animals and its importance in K- and rstrategies. J Anim Ecol 1977;46:677-688. 5. Gilpin ME, Case TJ, Ayala FJ. 0-Selection. Math Biosci 1976;32:131-139. 6. Fowler, CW. A review of density dependence in populations of large mammals. In: Genoways H (ed) Current Mammalogy. New York: Plenum, 1987;401-441. 7. Fowler CW. Population dynamics as related to rate of increase per generation. Evol Ecol 1988 ;2:197-204. 8. Charnov EL. Life History Invariants: Some Explorations of Symmetry in Evolutionary Ecology. Oxford, UK: Oxford University Press, 1993. 9. Butterworth DS, Best PB. Implications of the recovery rate of the South African right whale population for baleen whale population dynamics. Rep Int Whal Commn 1990;40:433-447. 10. Fowler CW, Siniff DB. Determining population status and the use of biological indices for the management of marine mammals. In: McCullough DR, Reginald RH (eds) Wildlife 2001: Populations. London, UK: Elsevier, 1992; 1051-1061. 11. Rosenberg AA, Fogarty MJ, Sissenwine MP, Beddington JR, Shephard JG. Achieving sustainable use of renewable resources. Science 1993;262:828-829. 12. Smith TD. Scaling in Fisheries: The Science of Measuring the Effects of Fishing, 1855-1955. Cambridge, UK: Cambridge University Press, 1994. 13. Fowler CW. Non-linearity in population dynamics with special reference to large mammals. In: Fowler CW, Bunderson WT, Cherry MB, Ryel RJ, Steel BB (eds) Comparative Population Dynamics of Large Mammals: A Search for Management Criteria. Report to U.S. Marine Mammal Commission. Contract #MM7AC013. NTIS #PB80-178627. National Technical Information Service, 1980; 175-220. 14. Fowler CW. Density dependence as related to life history strategy. Ecology 1981 ;62:602-6 10. 15. Policansky D. Fishing as a cause of evolution in fishes. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993;2-18. 16. Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993. 17. Grey DR. Evolutionarily stable optimal harvesting strategies. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993; 176-186. 18. Horwood J. Growth and fecundity changes in flatfish. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993;37-43. 19. Kirkpatrick M. The evolution of size and growth in harvested natural populations. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an Inter-

412

20.

21.

22.

23. 24. 25.

national Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993; 145-154. Reznick DN. Norms of reaction in fishes. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993;72-90. Rijnsdorp AD. Selection differentials in male and female North Sea plaice and changes in maturation and fecundity. In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993;19-36. Rowell CA. The effects of fishing on the timing of maturity in North Sea cod (Gadus morhua). In: Law R, McGlade JM, Stokes TK (eds) The Exploitation of Evolving Resources: Proceedings of an International Conference, Julich, Germany, 1991 (Lecture Notes in Biomathematics, 99). Berlin: Springer-Verlag, 1993 ;44-61. York AE, Hartley JR. Pup production following harvest of female northern fur seals. Can J Fish Aquat Sci 1981;38:84-90. York AE. Average age at first reproduction of the northern fur seal (Callorhinus ursinus). Can J Fish Aquat Sci 1983;40:121-127. Fowler CW. Density dependence in northern fur seals. (Callorhinus ursinus). Mar Mammal Sci 1990;6:171-195.

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

413

Interpretation of growth layers in the periosteal zone of tympanic bulla from minke whales Balaenoptera acutorostrata Ivar Christensen Institute of Marine Research, Bergen, Norway A b s t r a c t . Growth layers in the periosteal zone of tympanic bullae from minke whales, Balaenoptera acutorostrata, have been analysed. Different methods for preparation of bulla sections were used to

show the growth layers. A comparison of the number of growth layers identified in thick etched sections and in thin translucent sections using light microscopy and scanning electron microscopy show similar readability in the different preparation techniques. Acid-etched surfaces of thick sections from 297 bullae and thin translucent sections from 399 bullae were then examined by reflected and transmitted light in a binocular light microscope. All the etched and 390 of the thin sections were examined by two readers, and 157 of the thin sections were also read by a third reader. Comparisons of the readability of growth layers in etched and thin sections were tested for each individual reader and between readers. There is some problem in counting growth layers, but there is substantial evidence suggesting that about 80% of the minke whales were correctly aged within _1 year. The deposition of periosteal growth layers is discussed in relation to body length of the animals, accumulation of corpora in the ovaries of females and other biological data. Key words: age, bone, baleen whale

Introduction Different methods for determining the age of baleen whales have been suggested during the last five to six decades, but so far no method has proved to be satisfactory. Jonsg~rd [1] tried to utilize Ruud's [2] aging method based on growth ridges in the baleen plates for fin whales, but concluded that the rapid wear of minke whale baleen made it difficult to decide more than 2-3 age groups in this species. Ear plugs [3] useful for aging other baleen whales are difficult to use for the minke whale. Sergeant [4] reported that of 11 minke whale ear plugs collected in good condition off Canada, only one could be read clearly, and Sigurjonsson [5] reported that only 42% of the plugs sampled off Iceland were readable. Laws [6] described the layered structure in tympanic bullae from elephant seals. Later, Laws [7] suggested that the laminae in bones could be used for age determination of baleen whales in which the ear plug had proved unsatisfactory, as for example the minke whale. By comparing the number of layers observed in the periosteal zone of the tympanic bullae from minke whale with layers in the ear plug, body length and the num-

Address for correspondence: Sea Mammal Section, Institute of Marine Research, Postbox 1870 Nordnes, N-5024 Bergen, Norway.

414 ber of corpora in the ovary, Christensen [8] concluded that the periosteal growth layers are formed annually. Sukhovskaya et al. [9] reported that in stained thin sections of bullae, the growth layers showed good correlations with age. However, for etched sections, the inner layers are lost and the age is therefore underestimated.

Materials and Methods Material and data were collected by observers from the Institute of Marine Research on board small whale catchers hunting minke whales in the Barents S e a - Svalbard area in the period 1977-1992. All whales examined were measured to the nearest centimetre; tympanic bullae, one from each animal, and sexual organs were collected. Bullae were sampled from a total of 516 minke whales. All of them seemed to be relatively young animals. In addition to these, a 380 cm long minke whale calf, found drifting dead near Bergen, was included in the material. In the laboratory, a set of parallel successive thick (4.5-5.0 mm) and thin (200/zm) sections was cut from the medial part of each bulla (Fig. 1). The surfaces of a set of thick sections were first polished and then etched with 10% formic acid for 60 min, dried and stored dry.

B DORSAL

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Fig. 1. Schematic drawing of a tympanic bullae from minke whale: (A) longitudinal section, and (B) the transversal section in the medial part of the bone (dotted line in A). Growth layer area marked black.

415

Methods of Analysis

Light microscopy (LM) The 517 bullae were examined using a binocular microscope with zoom lens and magnification of x 6 to x50. Thick etched sections were examined by reflected light, and thin sections by transmitted light.

Scanning electron microscopy (SEM) Thick polished (9), thick etched (5), thin untreated (6), and thin polished (10) sections were mounted on aluminium stubs using colloidal carbon paint. The section surfaces were made electrically conductive by deposition of a 20 nm thick carbon film using a vacuum evaporator. Micrographs were taken both in the secondary electron imaging (SEI) and in the backscattered electron imaging (BEI) mode. The SEI mode was used to study specimen topography, but a few major fractures were seen in this mode [ 10]. The content of Ca and P in the sections was studied by X-ray micro analysis using the LINK analyzer. This is an energy dispersive X-ray analyzer (EDXA) permitting simultaneous detection of all elements in the Periodic Table from 11 (Na) to 92 (U).

Structure of Tympanic Bullae

Light microscopy The tympanic bullae consist of reticular dense bone with a narrow periosteal zone of varying thickness. The periosteal zone consists of layers of bony plates, separated by parallel adhesion layers appearing as lines in thin transverse sections (Fig. 2). The boundary between the periosteal and mesosteal or reticular bone is sometimes very diffuse but the postnatal periosteal zone is often easily distinguished from the prenatal reticular bone because the former has a more uniform structure and a different (whitish) colour. In an etched transverse section of a bullae, a periodical arrangement of ridges and furrows can be seen in the periosteal zone. One ridge and one furrow, i.e. the distance between the beginning of one ridge and the beginning of the subsequent ridge is defined as one growth layer (Fig. 3). The first growth layer is much wider (thicker) than the following growth layers. There is no neonatal line or resting line between prenatal and postnatal bone. This was also confirmed by the bullae from the very young calf found drifting near Bergen (Fig. 4). The resting lines or furrows are formed during periods of reduced growth, while the broad layers of the periosteal bone, the ridges, are formed in periods of rapid growth of the periosteal zone [8]. The first growth layer ends at the first, innermost resting line; subsequent growth layers are of variable thickness.

416

AD

M Fig. 2. A 200 r

thick section from the lateral area of a tympanic bullae (L in Fig. 1) showing (P) the periosteal zone, (M) mesosteal zone, and (AD) adhesion layers ( x 40).

In a 200 btm untreated thick section, translucent laminae appear clear or light in transmitted light and dark in reflected light. Opaque laminae appear as dark zones in transmitted light and as light zones in reflected light. Opaque laminae correspond

AD

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Fig. 3. Etched segment of a minke whale bullae. P, M, and AD as Fig. 2. Twelve ridges and furrows show up in the periosteal ( x 50).

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4. A 200/zm thick section from bullae of a calf. Same area as in Fig. 2 ( x 12).

probably with the ridge and the translucent laminae with the furrows in the etched sections. Scanning electron microscopy showed alternating dark and bright bands in the periosteal zone. One dark and one bright band together were interpreted as one periosteal growth layer. Figure 5 shows growth layers from thick and thin polished sections. As in LM, the growth layers show a varied appearance, from discrete and well defined to broad and poorly defined layers. Splitting and merging of growth layers were occasionally observed.

X-Ray micro analysis Analysis performed on thick polished sections in spot mode showed that the bullae consist of approximately 47% Ca and 22% P giving a total of 69% inorganic material. Significant variations in the composition were not found either between the mesosteal and the periosteal zones, or between the dark and light constituents of the growth layers.

Growth of Bullae

As mentioned by Christensen [8], the resting lines or furrows are formed in periods with low food consumption or slow growth. All bullae in the sample were collected in the Barents Sea early in the feeding season, in May-June. We therefore mostly found fully developed growth layers in the bullae. Two observers with experience using LM in counting growth layers in bones and teeth studied segments from 250 bullae. The results of their readings are given in Table 1.

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Fig. 5. The surface of a thick (a) and thin (b) polished sections imaged in SEM, BEI/COMPO mode. Periosteal growth layers are clearly resolved (arrowheads) and can be seen split an emerge.

Table 1 shows that in the etched section 39% of two successive readings by observer A are identical, while 36% show a difference of +_1 growth layer. The two observers' readings of growth layers in thin sections give about the same percentage scores for two successive readings, 42% (A), 43% (B) for identical readings, and 32% (A) and 38% (B) for difference of _1 growth layer. When comparing A and B readings of the same section, only 20% were identical in numbers of growth layers, while 39% showed a difference of _+1 growth layers (53 readings). Closer examination of these 53 readings (Table 1, _+1), illustrated that B gave 1 more growth layer than A in 39 cases, and 1 less in 14 cases. For the _+2 layer

419 Table 1. Difference in counts of growth layer group in the periosteal zone in middle part of tympanic bullae by two observers A and B and in two successive readings by the same observer

Section

Difference

Etched A (no.) Etched % Thin A (no.) Thin (%) Thin B (no.) Thin (%) Etched-thin, A (no.) Etched-Thin, % Thin A-B (no) Thin A-B (%)

Total

0

_+ 1

_2

__.3

Other

55 39 81 42 51 43 42 27 27 20

51 36 61 32 45 38 55 35 53 39

28 20 31 16 12 10 29 19 36 26

6 4 10 5 6 5 12 8 9 7

3 2 12 6 5 4 18 12 12 9

143 193 119 156 137

Etched section, reflected light (one observer, A). Thin section (200/~m) in transmitted light (two observers).

difference, B gave 2 layers more than A in 31 cases and 2 layers less in 5 cases. In conclusion, B overestimated the number of growth layers relative to A. The readability of growth layers in thin polished and thick polished segments examined in SEM (22%, 44%, 33% for identical _1, __.2layers) is about the same as in thin and etched sections in LM (Table 1). Thin sections in LM and SEM show similar readability (47%, 33%, 7% for identical -+1, _+2 layers) as for two successive readings of thin sections of LM. This comparison shows that the number of growth layers identified using different preparing techniques; etching and thin sections, polished and unpolished segments, reflected and transmitted light, LM and SEM, give similar result for growth layer count in minke whale bullae.

Readability and interpretation Based on these assumptions, three readers (termed 1, 2, 3) with experience in counting growth layers in bones and teeth using LM, studied the sections from the 517 tympanic bullae. Table 2. Average coefficient of variation for age determinations by reader and preparation method

Reader

Males (N)

Etched sections 1 0.0682 (105) 2 0.1074 (9) _

Thin sections 1 0.0919 (125) 2 0.1005 (121) 3 0.0615 (39)

Females (N)

Sexes combined (N)

0.0743 (192) 0.1231 (23)

0.0721 (297) 0.1187 (32)

_

0.0947 (274) 0.1214 (262) 0.0799 (80)

0.0938 (399) 0.1148 (383) 0.0739 (119)

420 Table 3. Percent agreement in age determinations within indicated differences (readers 1, 2, 3" methods: E, etched section; T, thin section) Difference within (years)

Comparison (reader/method) 1 E - IT

2 E - 2T

1 E - 2E

1 T - 2T

I T - 3T

2 T - 3T

0 _1 _+2 _+3

28.6 64.8 85.7 94.5

21.6 56.1 76.6 88.3

33.4 77.5 93.2 97.3

33.1 78.7 94.6 99.0

33.1 77.1 96.2 97.5

34.4 77.5 90.7 97.4

To compare the precision of age determinations between readings for each reader and between the readers, an average coefficient of variation (cv) was calculated for each reader by preparation method for the sections. These cvs are based on sections for which two or more readings are available. As seen from Table 2, it is not possible to select one of the methods as the best with regard to reproducibility of age readings. The table also indicates that for all readers and both methods, age determinations of samples from males seem to be more reproducible than those from females. Agreements in age assigned with selected deviations are given as a percentage in Table 3. These agreements have been calculated using the means of age determinations from sections, rounded to the nearest integer. The percent agreements are comparable within methods, but decrease between methods. The distributions of differences in age determinations between readers and methods are also illustrated in Figs. 6-11. These distributions may indicate problems relating to interpretation if they are asymmetric around 0. Two readers determined age from both etched and thin sections but these results are not conclusive; both distributions are asymmetric. However, while in the case of reader 1 ages determined from etched sections tend to be higher than those from thin sections (Fig. 6), the situation is just the opposite for reader 2 (Fig. 7). For the two readers of the etched sections, reader 1 tended to estimate higher ages than reader 2 (Fig. 8). Thin sections were read by three readers. The highest ages were given by reader 2, then reader 3, with reader 1 giving the lowest age determinations (Figs. 9-11). The

i

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Fig. 6. Comparison of age determination by reader 1 between etched sections and thin sections (E-T, N = 182).

421

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Fig. 7. Comparison of age determination by reader 2 between etched sections and thin sections (E-T, N = 171).

comparison between reader 1 and reader 2 indicates that there may be a problem with the interpretation of the thin sections (Fig. 9).

Conclusion Growth layer groups are identified in etched thick sections using reflected light, thin sections using transmitted light in light microscope, thick and thin polished and unpolished sections using scanning electron microscope. The growth layers in etched sections are a periodical arrangement of ridge and furrows observed in the periosteal zone. In thin sections using transmitted light, the growth layers are observed as dark and light lamina. These correspond probably to the ridge and furrow in etched sections.

8

9

'

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i

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Fig. 8. Comparison of age determinations from etched sections by reader 1 and reader 2 (El-E2, N = 293).

Fig. 9. Comparison of age determinations from thin sections by reader 1 and reader 2 (T1-T2, N = 390).

422

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Fig. 10. Comparison of age determinations from thin sections by reader 1 and reader 3 (T1-T3, N = 157). Fig. 11. Comparison of age determinations from thin sections by reader 2 and reader 3 (T2-T3, N = 151).

In scanning electron microscopy, alternating dark and bright bands are observed in the periosteal zone which also probably correspond to the ridges and furrows seen in etched sections. No variation in the content of Ca (47%) and P (22%) was found in the bullae, either between mesosteal and periosteal, or between dark and light lamina. The number of growth layers identified using different techniques gave similar resuits for the growth layer count in minke whale bullae. The study did not give conclusive evidence of which of the methods, etched sections in reflected light or thin sections in transmitted light were the most reproducible. However, agreement in layers assigned within _1 layer in 77-79% occasions suggests that the method of counting growth layers in tympanic bullae is a useful approach for studying age-related biological data. The etching methods in this study were the same as used by Christensen [8]. He also correlated available biological data with the growth layer, and concluded that one growth layer group is laid down per year. There are still some problems in counting growth layers, but there is substantial evidence to suggest that a minke whale is correctly aged within _+1 year in about 80% of cases.

Acknowledgement This project has been funded by the Norwegian Fisheries Research Council (NFFR), project number 4001-701.247.

References 1. Jonsg~d A. Studies on the little piked whale or minke whale (Balaenoptera acutorostrata Lac6p~de). Report on Norwegian investigations carried out in the years 1943-1950. Norsk Hvalfangst-tid 1951 ;40:209-232.

423 2. Ruud JT. Further studies on the structure of the baleen plates and their application to age determination. Hvalr~d Skr 1945 ;29:1-69. 3. Purves PE. The wax plug in the external auditory meatus of the Mysticeti. Discovery Rep 1955;27:293-302. 4. Sergeant DE. Minke whales, Balaenoptera acutorostrata of the western north Atlantic. J Fish Res Bd Can 1963;20:1489-1504. 5. Sigurjonsson J. A preliminary note on ear plugs from Icelandic minke whales. Rep Int Whal Commn 1980;30:193-194. 6. Laws RM. The elephant seal (Mirounga leonina Linn.) I. Growth and age. Sci Rep Falkland Isl Depend Surv 1953;8:1-62. 7. Laws RM. Laminated structure of bones from some marine mammals. Nature London 1960;187:338-339. 8. Christensen I. Age determination of minke whales, Balaenoptera acutorostrata, from laminated structures in the tympanic bullae. Rep Int Whal Commn 1981;31:245-253. 9. Sukhovskaya LJ, Klevezal GA, Borisov VJ, Lagerev SJ. Use of bone layers to determine age in minke whale. Acta Theriol 1985;30:275-286. 10. Christensen I, Krekling T, Salbu B. Growth layers in tympanic bullae from minke whales (Balaenoptera acutorostrata), determined by light and electron microscopy. Int Whal Commn Sci Comm Pap, 42 (NHMi3) 1990 R~sum~ Section. In: Rep Int Whal Commn 1991;41.

This Page Intentionally Left Blank

9 1995 ElsevierScience B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand t3. Ulltang,editors

425

On the life history and autecology of North Atlantic rorquals J6hann Sigurj6nsson Marine Research Institute, Reykjavfk, Iceland Abstract. Background and methods: this paper briefly reviews in qualitative terms available information on exploitation, stock development, life history and autecology of North Atlantic rorquals (mainly blue, fin, sei, minke and humpback whales) with special reference to interspecific variations in abundance. Historical catches and information on growth, reproductive rate and food preferences are examined in relation to present stock sizes. Results and conclusions: recent sighting surveys show that the North Atlantic rorquals cannot be regarded as threatened or endangered by exploitation, although some species are depleted locally in some areas. The minke and fin whales are both euryphagic seasonal feeders that prior to exploitation and still today number in the 50,000-100,000 and 100,000-200,000 range, respectively. Their opportunistic feeding habits and choice for vast open ocean breeding areas seem to give rise to relatively large stocks and to their apparent sustenance for high catches. The near stenophagic crustacean feeding blue and sei whales seem on the other hand to have had smaller historical stock levels of well within 20,000 animals. While the sei whale is probably at present in the 10,00015,000 range, the blue whale is still at a low level, although increasing in some areas, such as off Iceland. The humpback whale seems to be the species that historically occurs in smallest numbers, although the northwestern stock seems to be in a healthy state (increasing by ~10% per year). The strong recovery of the species in recent decades may be linked with its euryphagous lifestyle. However, the relatively small population size may also be correlated with its dependence on the rather limited coastal zones for breeding. Key words: balaenopterids, stock size, exploitation, status, feeding, competition

Introduction

The past century has been a dramatic epoch with respect to the development and exploitation of North Atlantic balaenopterid whales or rorquals, since with the introduction of modem whaling in the late 1860s they became the main target of the newly developing industry [ 1,2]. The rorquals are part of the baleen whale group and are all, except the minke whale (Balaenoptera acutorostrata), true large whales. The other rorquals occurring in the North Atlantic comprise the largest animal on earth, the blue whale (B. musculus), in addition to fin (B. physalus), sei (B. borealis), Bryde's (B. edeni) and humpback whales (Megaptera novaeangliae). The minke whale was, however, not subject to large scale exploitation until during the first decades of this century with the introduction of small-type whaling activities in several areas of the North Atlantic Ocean [3-5]. The intense whaling pressure caused significant reduction in many of the rorqual stocks even before the turn of the century. This paper briefly reviews the history of

Address for correspondence: Marine Research Institute, P.O. Box 1390, 121 Reykjav~, Iceland.

426 exploitation and discusses a few qualitative aspects of development of stock sizes and the present situation in light of several life history and ecological characteristics of the different species and stocks.

Main Factors Affecting the Survival of the Stocks There are a number of factors that need to be considered in this context (see e.g. Ref. [6]), some of which one may explore, while others are very difficult to approach. We have mentioned the exploitation that evidently is important here. Biological limits are important, the rate of reproduction, the growth rate, etc., i.e. the life history characteristics of each species and stock; also, the selection of habitat, food preference and feeding strategy that the species have adjusted to, and the availability of preferred habitats and food in time and space. Finally, behavioural aspects such as territorialism that we know so little about, may play a central role in this game of survival and competition. One can say that the optimization of all these factors forms each of the species' competitive strength.

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Migration, Distribution and Stock Units The typical migratory cycle of a large baleen whale is a summer feeding migration to high latitudes and a return migration to wintering/breeding grounds in autumn and winter at low latitudes [2,19]. Although this seems to be the general pattern with respect to the rorquals at high latitudes, there are clear exceptions, e.g. the humpback whales that annually occur during winter at the capelin (Mallotus villosus) grounds north off Iceland and at the turn of the century they occurred during January-March at the northwest coast of Finnmarken, N Norway [20,21]. Detailed accounts on the distribution and movements of the rorquals in the N Atlantic are reviewed, e.g. by Kellogg [22] and Jonsghrd [23] and more specifically for blue and fin whales in Jonsg~d's comprehensive papers [24,25], for sei and minke whales in Horwood's two monographs [3,26] and for humpback whales in Winn and Reichley [27]. The question of stock discreteness of each of the species of rorquals has been dealt with in detail by many authors in conjunction with management of whaling [714]. However, scientists in the mid-1970s made postulations regarding division of the N Atlantic baleen whales into stocks that gave rise to the traditional IWC management units [13]. These were mainly based on the distribution of catch grounds and recent sightings, catch history and whale markings. Accumulating evidence favours the idea of several genetically discrete or near isolated entities for minke, fin and humpback whales [10-12]. Fidelity to site, demonstrated well by traditional whale marking/recoveries in fin, sei and minke whales [9,14] and by repeated sightings of photoidentified blue, fin, humpback and minke whales [15-18], is also an important element in this discussion on reasonable units to manage whales, that accommodates some restricted intermingling, even between distant feeding populations. Figure 1 shows the seven traditional stock areas or management units for fin whales in the N Atlantic. Similarly, some four stock areas have been suggested for minke whales, i.e. two western units, one central and one northeastern stock unit. Three sei whale stock units (Nova Scotia, Iceland-Denmark Strait, and Eastern stock) have been suggested [13]. All these rorquals, except the sei whale, have summer feeding grounds ranging north to the ice edge and as far south as the Gulf of Mexico, the Mediterranean Sea and the coast of NW Africa, and more oceanic offshore winter distribution at lower latitudes. The sei whale on the other hand (Fig. 2a), does not normally reach as far north in summer, is more confined to temperate/boreal waters, and stays also offshore but has more southern distribution in winter than the other species, possibly as far south as the equator [26]. Figure 2b shows the feeding and breeding areas of humpback whales at high and low latitudes, respectively. Due to the humpback's coastal affinity and its often clearly identifiable marks on the ventral fluke that can be photographed, this species has been the subject of intensive investigations since the 1970s. The feeding aggregations seem to form quite discrete matrilineal units, apparently with a panmictic genetic pool [ 12,17]. The whales from the western Atlantic including the grounds off

428 Sei whale

75*

70*

65*

60* 55* 50* 45* 40" 35* 30* 25* 20* 15" 10" 5*

70*

50*

30*

10"

10"

30 ~

10 ~

30"

Humpback whale

75*

70*

8

65*

60* 55* 50* 45* 40* 35* 30* 25* 20* 15" 10" 5*

70 ~

50 ~

30 ~

10 ~

Fig. 2. Summer feeding grounds and winter breeding grounds of N Atlantic sei (a) and humpback (b) whales.

429

I!

3000

Fin

Sei

2500

Blue

2000 O E

15o0

Z 1000 500 0

~-v

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.

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.

.

.

1969

1979

Year Fig. 3. Catches of blue, fin, sci and humpback whales in the N Atlantic 1868-1985 (cf. text).

Iceland, migrate in winter to the breeding grounds in the Caribbean Sea. There are large feeding aggregations off Iceland and Newfoundland, and smaller ones at W Greenland, in the Gulf of St Lawrence and Gulf of Maine. The humpbacks off N Norway may have a relationship with the breeding grounds in the southwest, although we have traditionally assumed that this feeding aggregation migrates to the eastern breeding area off Cape Verde Islands, which at present is evidently sparsely populated [27,59].

Exploitation The catches of the four large rorqual species from the start of modem whaling last century (based on Refs. [28,29]) are shown in Fig. 3. We can see a period of learning and expansion of whaling activities into new areas that gave improved catch results up to the mid-1920s when over 3,000 animals (where unspecified catches have been incorporated) were taken annually. The largest catches were taken off Great Britain and Spain, while whaling first commenced off the coast of N Norway in the 1860s and in the 1880s at Iceland, but both these areas played a major role in the history of modern whaling in the N Atlantic. Note that in the early years, strike and loss rate was quite high [1 ], so here we are only talking about landed animals that may have been well over 100,000 in the last century or so. Examination of the species composition indicates that some 79,000 fin, 12,000 blue whales, less than 10,000 humpbacks and 16,000 sei whales were landed during commercial whaling since the late 1860s. The blue and humpback whales were mainly taken during the first period of modem whaling, while catches of fin whales

430 increased until the mid-1920s and then decreased with the closures of the fisheries in the British Isles and later the commercial operations in the Faroes in the 1960s, in Canada and N Norway after 1972, and Spain and Iceland in the mid-1980s. In contrast to the large whaling industry, minke whaling with cold-harpoons and motor vessels did not commence until well into this century. It was confined to small fishing boats in nearshore waters of Norway [4] and Iceland [5,31 ] at the beginning of this century. After the World War II, Norwegian minke whaling expanded to the west [30] and local whaling commenced on the Canadian [32,33] and Greenland coasts [34,35]. The bulk of the minke whale catches were taken by the Norwegian fishery, which gradually expanded towards the open sea on board well equipped and larger vessels that were able to catch and process the whales at sea. At most the annual take by the Norwegian fishery was over 4,000 whales [28,29], but the minke whaling activities were less widely distributed than whaling for other rorquals.

Present Status

Intensive hunting in the last century, involving mainly the five species of rorquals, has had major impact on the status of the stocks. This applies particularly to blue and humpback whales, which probably were reduced to very low levels throughout the ocean just after the turn of the century [17,24,38]. Now recent sighting surveys and other investigations have given us information on the current stock levels (see Table 1). Although apparently the humpback whale never was in great numbers in the N Atlantic [59], after decades of depleted status the stock has more or less fully recovTable 1. Present status of stocks of North Atlantic rorquals

Species

Blue

Stock size

1,000-2,000

Fin

50,000+

Sei

13,500+

Minke

Humpback

100,000+

5,500+

Status

Sources

Low level, mainly off Iceland and Gulf of St Lawrence, far less in other past whaling grounds, increasing by 5% per year off Iceland Still in good numbers, although depleted off W Norway and UK; lack of recent sightings estimate in NW Atlantic, so tagging estimate from 1970s and CETAP results from the US coast used Recent survey estimate in the central N Atlantic available, NW Atlantic marking estimate (1,800) used, depleted in some earlier whaling grounds, such as off N Norway Stock size reduced but still abundant in NE Atlantic, the smaller NW stock may number several thousands NW Atlantic near pre-exploitation level, increasing by --10% per year, eastern stock depleted

15,24,33,37-39,59

8,33,39,40,46

26,33,38,42,46

7,46

17,36,37,59

431 ered in the western and central distribution area and may still be increasing [ 17,36,37,59]. However, the whaling grounds at the eastern side of the N Atlantic are almost vacant for this species. It seems that, prior to exploitation, both sei and blue whales were in somewhat greater abundance or in the 10,000-15,000 range [38]. The present level of sei whales may be of similar order of size in some areas as prior to exploitation, while its absence from the earlier grounds off N Norway has been noted [26]. On the other hand, the blue whale is evidently still at a low level, while showing some significant signs of recovery (5% per year) off Iceland [37]. Moving to the far more abundant fin whale stock, which evidently was also subject to heavy taxation at the end of the last century and the first half of this century [25,28], the situation is different. Nevertheless, some major past whaling grounds, such as off W Norway and the British Isles, seem still to be sparsely populated [8]. Finally, we have the stock of minke whales, which may originally have numbered in excess of 150,000 animals and still is probably well above 100,000 in the entire N Atlantic Ocean [7].

Life History Parameters One may like to speculate why these rather closely related species exhibit such different historical stock levels and what are the likely factors affecting recent developments of the stocks. Such speculations may be of help in understanding stock development and can be useful in generating models to study the stocks in the future. Let us first take a look at the life history characteristics. As we see from Table 2 the ranges in life history parameters are not very different in the large species, the age at sexual maturity ranging from 6 to 12 years of age in blue, fin and sei whales, while it seems that both humpback and minke have a slightly faster growth potential, with age at maturity being somewhat lower. The pregnancy rates are of the same order of magnitude, i.e. normally a 2-year reproductive cycle in the larger species with possibilities of up to 1.5 calf per 2-year period.

Table 2. Life history parameters for balaenopterid whales

Blue a Length of newborn (m) Length (m) at sex. maturity Males Females Age (years) at sexual maturity Males Females Pregnancy rates Length of gestation (months)

--7 20-21 21-23 ~10 ~10 10-11

Fin b

Sei c

6.4

4.5

17.7 18.3

12.0-12.8 13.1-13.4

8-12 6-10 0.5-0.73 11.2

7-11.7 5.6-11.7 0.36--0.47 10.7

Sources: a[44]" b[44,45,55]" c[26]; d[3,7]" e[27,57].

Minke d

Humpback e

2.4-2.8

4-5

6.8-7.0 7.3-7.4

11.6 12.1

3--6 5-7 0.86-0.99 10

2-5 2-5 0.3-0.43 11-11.5

432

Fin

12

~vhales

: Age

'al Iransilion

phase

+1

IO cq

9

i ....

,

55 1960

.

.

.

.

i

'

65 19'70 75 19'80 '85 19'90 Yearat transition Fig. 4. Changes in age at maturation in fin whales off Iceland.

However, the typical minke whale cyclus is annual, which presumably gives it a plus on the competition record. The ranges of ages at maturity shown in Table 2 are to a large degree a reflection of growth rate in the populations where we have available information of this kind. Evidence for dramatic changes in the growth rate of fin whales off Iceland demonstrate this well, where after years of decline in age at sexual maturity [41 ], a reversed trend in the most recent year classes has followed [43,45] as shown in Fig. 4. This has been related to the available food resources [6,19,46], where great fluctuations in fecundity have also been linked with changing availability of food. In conclusion, changes in growth rate and the corresponding changes in age at maturity are important elements in the survival of these stocks and here all the balaenopterid species may have a similar chance. Likewise, it seems as if minke whales may have greater potential in utilizing favourable conditions, when these are available, than the larger species, if only reproduction would decide who is to win.

Table 3. Prey group preference in North Atlantic fin and sei whales

Species

Area

1st prey

2nd prey

Fina

N Norway W Norway Faroes Icelandc Nova Scotia Newfoundland N Norway W Norway Icelandc Nova Scotia

Krill Krill krill krill krill Capelin Copepods Copepods Krill Copepods

Capelin/herring

Seib

Sources: a[25,47]" b[26,47]; Cunpublished.

Herring Blue whiting, herring, capelin Sandlance/mackerel Sand1ancellantern Krill Krill Copepods Krill

433

Table 4. Main fish species found in N Atlantic minke whales Area

Herring a

Capelin a

Barents Sea Norwegian coast Great Britain Iceland E Greenland W Greenland Newfoundland Eastern US

x x x x

x

Ammod. sp. a

Gadoids b

Mackerel b

x x x x

x x

X

X

Sources: [3,47-50,53,54]. aGreatest in quantity; bless in quantity.

Food and Feeding Table 3 lists the favourite/common food (lst prey/2nd prey) of fin and sei whales. Usually fin whales go for krill as the first choice, but they are also taking fish in considerable amounts in certain areas, seasons or time periods [25,47]. The fish species are then most often capelin (Mallotus villosus), herring (Clupea harengus), sandlance or Ammodyte spp. The humpbacks feed even more on fish, while also taking krill. The sei whales eat nearly exclusively crustaceans [26], most often the smallest of these, the copepods. The blue whales are also solely crustacean feeders [59], and are

10 Blue ~

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Fig. 5. Sightings of blue, fin, sei and humpback whales on board vessels west and southwest of Iceland, June-September 1979-1985.

434 even more specialised, nearly always preying on krill. The minke is perhaps the most extreme opportunistic feeder of the N Atlantic balaenopterid whales, taking mainly fish, but also krill, this all varying greatly between seasons and areas. The main species of fish found in the stomach of minke whales in different areas of the N Atlantic are listed in Table 4. In conclusion, it can be stated that there are generalists/opportunists as Mitchell categorized it [47], the minke, humpback and fin whales forming that group; there are the specialists, the blue and sei whales. No doubt the position in the food web and the degree of specialization counts very much in the whale's ability to cope with variations in the availability of different prey. It is important for us to monitor the status of the principal species of fish stocks as well as crustacean production in order to capture a picture of the situation the whales are in at any given time. Many of the pelagic fish species undergo major natural fluctuations that can greatly influence the livelihood of the whale population in the area, such as the capelin off Newfoundland [51 ] and off Iceland [46], or the herring off Norway and Iceland. Off W Iceland herring comprised up to 30% of the food of fin whales at the turn of the century (unpublished data), while in recent years there is

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Fig.

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437

no herring found in the stomachs of fin whales at Iceland, and in fact only some 3% of stomachs during the summer contained remains of fish [52]. Temporal/Spatial Distribution The migration time and spatial utilization of the different species also needs to be considered, although general conclusions on this point are difficult to make. Figure 5 demonstrates the variations in migration behaviour of the different species off Iceland which relate to temporal utilization of the space. Noteworthy, fin and sei whales tend not to occur concurrently in great numbers and have a different peak migration period in the area. Figure 6 shows the distribution of the two species in the Icelandic NASS-89 survey that confirms this apparent tendency. The baleen whales off Iceland also show considerable areal or depth preferences, the blues, humpbacks and particularly minke whales staying close to the coast (Fig. 7), while fin and sei whales stay offshore, mainly outside the banks beyond 4 0 0 500 m depth and as deep as 2,000 m. Although this may partly be explained by local depletion of fin whales due to the whaling and possibly by invasion of blue and

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438 humpbacks as time has passed since they were protected in the 1950s, fin whales seem not to have inhabited the shallow waters in the postwar years (Fig. 8). Examination of catch data in eastern Iceland at the turn of the century shows whales in both deep and shallow waters (Fig. 9). Off the US and Canadian coasts, however, the bulk of the baleen whales are found within 100 or 200 m depth [56,58]. It seems thus that although species seem to have a preference for certain depth intervals in each area, that may be shared with other species, the topography and more general ecological characteristics of the area are not less important. Baleen whales seem to be rather eurytherm [59] and when for example examining satellite images of temperature distribution and rorqual occurrence during the NASS-89 survey (unpublished data), the distribution of whales appears not to be critical with respect to temperature. More likely, ocean fronts, currents and upwellings, which give support to great prey stocks, are influencing the distribution of the whales.

Conclusions

This brief examination of the status of the N Atlantic rorquals shows that they need not be regarded as threatened or endangered by exploitation, although some species are depleted locally in some areas. The minke and fin whales are both euryphagic seasonal feeders that prior to exploitation and still today number in the 50,000100,000 and 100,000-200,000 range, respectively. Their opportunistic feeding habits and choice for vast open ocean breeding areas seem to give rise to relatively large stocks and to their apparent sustenance for high catches. The near stenophagic crustacean feeding blue and sei whales seem on the other hand to have had smaller historical stock levels of well within 20,000 animals. While the sei whale is probably at present in the 10,000-15,000 range, the blue whale is still at a low level, although increasing in some areas, such as off Iceland. The humpback whale seems to be the species that historically occured in smallest numbers, although the northwestern stock seems to be in a healthy state (increasing by --10% per year). The strong recovery of the species in recent decades may be linked with its euryphagous lifestyle. However, the relatively small population size may also be correlated with its dependence on the rather limited coastal zones for breeding. It is likely that the stronger competitors, particularly fin, minke and humpbacks, which all are to some extent fish feeders, will in the near future come increasingly into conflict with fisheries. Therefore, it is important to intensify investigations that may help us to evaluate the potential conflicts that may arise. In that context we need to monitor the whale stocks and associated resources in order to model the interactions. This also requires some basic information on stock discreteness in order to understand the recovery of depleted stocks or stock units. Here further genetic work may be of help, while new technology, such as satellite tracking of the large whales [60], may in the near future help us better to understand the movements, distribution and behaviour of rorquals.

439

Acknowledgements The

author

wishes

to t h a n k

his c o l l e a g u e s

at the M a r i n e

Research

Institute,

R e y k j a v i k , for h e l p in p r e p a r i n g this p a p e r , p a r t i c u l a r l y S v e r r i r D. H a l l d 6 r s s o n for c o m p i l i n g c a t c h d a t a a n d J 6 h a n n a E r l i n g s d 6 t t i r for h e l p with a n a l y s i s o f c a t c h d a t a a n d g r a p h i c a l support.

References 1. T0nnessen JN, Johnsen AO. The History of Modern Whaling. Berkeley: University of California Press, 1982. 2. Mackintosh NA. The Stocks of Whales. London: Buckland Foundation Fishing News (Books), Ltd., 1966. 3. Horwood JW. Biology and Exploitation of the Minke Whale. Boca Raton, FL: CRC Press, 1990. 4. JonsgArd/~. Studies on the little piked whale or minke whale (Balaenoptera acutorostrata Lac6p~de). Nor Hvalfangst-Tid 1951 ;40:209-232. 5. Sigurj6nsson J. Icelandic minke whaling 1914-1980. Rep Int Whal Commn 1982;32:287-295. 6. Lockyer C. The importance of biological parameters in population assessments with special reference to fin whales from the NE Atlantic. N Atlantic Stud 1990;2:22-31. 7. Anonymous. Report of the Scientific Committee. Annex F: report of the sub-committee on North Atlantic minke whales. Rep Int Whal Commn 1991 ;41:82-129. 8. Anonymous. Report of the Comprehensive Assessment Special Meeting on North Atlantic Fin Whales. Rep Int Whal Commn 1992;42:595-644. 9. Sigurj6nsson J. Whale stocks off Iceland- assessment and methods. N Atlantic Stud 1990;2:6476. 10. ,~rnason A, Danielsd6ttir AK, Spilliaert R, Sigurdsson J, J6nsd6ttir S, P~ilsd6ttir A, Duke EJ, Joyce P, Groves V, Trowsdale J. A brief review of protein and DNA marker studies in relation to stock identity of fin whales (Balaenoptera physalus) from Iceland and Spain. Rep Int Whal Commn 1992;42:701-705. 11. Danfelsd6ttir AK, Halld6rsson SD, GuSlaugsd6ttir S, Arnason A. Genetic variation in northeastern Atlantic minke whales (Balaenoptera acutorostrata). In: Blix AS, Wallr L, Ulltang 0 (eds) Whales Seals, Fish and Man. Amsterdam: Elsevier, 1995:105-118. 12. Clapham PJ, Mattila DK, Palsb011 PJ. High-latitude-area composition of humpback whale competitive groups in Samana Bay: further evidence for panmixis in the North Atlantic population. Can J Zool 1993;72:274-279. 13. Donovan GP. A review of IWC stock boundaries. Rep Int Whal Commn 1991;(Special Issue 13):39-68. 14. Sigurj6nsson J, Mitchell E, Gunnlaugsson Th. Fin whale markings in the North Atlantic with special reference to the stock identity question. Rep Int Whal Commn 1992;42:769 (abstract). 15. Sears R, Williamson RM, Wenzel FW, B6rub6 M, Gendron D, Jones P. Photographic identification of the blue whale (Balaenoptera musculus) in the Gulf of St. Lawrence, Canada. Rep Int Whal Commn 1990;(Special Issue 12):335-342. 16. Agler BA, Beard JA, Bowman RS, Corbett HD, Frohock SE, Hawvermale MP, Katona SK, Sadove SS, Seipt IE. Fin whales (Balaenoptera physalus) photographic identification: methodology and preliminary results from the western North Atlantic. Rep Int Whal Commn 1990;(Special Issue 12):349-356. 17. Katona SK, Beard JA. Population size, migrations and substock structure of the humpback whale (Megaptera novaeangliae) in the western North Atlantic Ocean. Rep Int Whal Commn 1990;(Special Issue 12):295-305.

440 18. Dorsey EM. Exclusive adjoining ranges in individually identified minke whales (Balaenoptera acutorostrata) in Washington state. Can J Zool 1983;61:174-181. 19. Vfkingsson GA. Body condition of fin whales during summer off Iceland. In: Blix AS, WallCe L, Ulltang t2t (eds) Whales Seals, Fish and Man. Amsterdam: Elsevier, 1995:361-369. 20. Collett R. Norges Pattedyr. Kristiania: H Aschehoug and Co (W. Nygaard), 1912. 21. Ingebrigtsen A. Whales caught in the North Atlantic and other seas. Rapp P-V Reun Cons Perm Int Explor Mer 1929;56(2):1-26. 22. Kellogg R. What is known of the migrations of some of the whalebone whales? Smithson Inst Annu Rep 1929:467-494. 23. JonsgArd/~. The distribution of Balaenopteridae in the North Atlantic Ocean. In: Norris KS (ed) Whales, Dolphins and Porpoises. Berkeley, CA: University of California Press, 1966:114-124. 24. Jonsg~rd ~. The stocks of blue whales (Balaenoptera musculus) in the northern Atlantic Ocean and adjacent arctic waters. Nor Hvalfangst-Tid 1955;44:505-519. 25. JonsgArd/~. Biology of the North Atlantic fin whale Balaenoptera physalus L - Taxonomy, distribution, migration and food. HvalrAdets Skr 1966;49:1--62. 26. Horwood JW. The Sei Whale: Population Biology, Ecology and Management. London: Croom Helm, 1987. 27. Winn HE, Reichley NE. Humpback whale Megaptera novaeangliae (Borowski, 1781). In: Ridgway S, Harrison R (eds) Handbook of Marine Mammals. Vol 3: The Sirenians and Baleen Whales. London: Academic Press, 1985:241-273. 28. JonsgArd/~. Tables showing the catch of small whales (including minke whales) caught by Norwegians in the period 1938-75 and large whales caught in different North Atlantic waters in the period 1868-1975. Rep Int Whal Commn 1977;27:413-426. 29. Anonymous. International Whaling Statistics 1988;XCV-XCVI:l--68. 30. Christensen I. Preliminary report on the Norwegian fishery for small whales: expansion of Norwegian whaling to Arctic and Northwest Atlantic waters, and Norwegian investigation of the biology of small whales. J Fish Res Bd Can 1975;32:1083-1094. 31. Saemundsson B. Mammalia. The Zoology of Iceland; IV(76). Copenhagen and Reykjavik: Ejnar Munksgaard, 1939. 32. Sergeant DE. Minke Whales, Balaenoptera acutorostrata Lac6p~de, of the western North Atlantic. J Fish Res Bd Can 1963;20:1489-1504. 33. Mitchell E. Present status of northwest Atlantic fin and other whale stocks. In: Schevill WE (ed) The Whale Problem. A Status Report. Cambridge, MA: Harvard University Press, 1974:108169. 34. Larsen F, Kapel FO. Further biological studies of the West Greenland minke whale. Rep Int Whal Commn 1983;33:329-332. 35. Kapel FO. Catch of minke whales by fishing vessels in West Greenland. Rep Int Whal Commn 1978;28:217-226. 36. Mitchell E, Reeves RR. Catch history, abundance, and present status of Northwest Atlantic humpback whales. Rep Int Whal Commn 1983;(Special Issue 5):153-212. 37. Sigurj6nsson J, Gunnlaugsson, Th. Recent trends in abundance of blue (Balaenoptera musculus) and humpback whales (Megaptera novaeangliae) off West and Southwest Iceland, with a note on occurrence of other cetacean species. Rep Int Whal Commn 1990;40:537-551. 38. R6rvik CJ, Jonsg~rd /~. Review of balaenopterids in the North Atlantic Ocean. FAO Fish Ser 1981;5(3) (Mammals of the Seas):379-387. 39. Gunnlaugsson Th, Sigurj6nsson J. NASS-87: estimation of whale abundance based on observations made onboard Icelandic and Faroese survey vessels. Rep Int Whal Commn 1990;40:571580. 40. Buckland ST, Cattanach KL, Gunnlaugsson, Th. Fin whale abundance in the North Atlantic, estimated from Icelandic and Faroese NASS-87 and NASS-89 data. Rep Int Whal Commn 1992;42:645-651.

441 41. Lockyer C. The age at sexual maturity in fin whales off Iceland. Rep Int Whal Commn 1981;31:389-393. 42. Cattanach KL, Sigurj6nsson J, Buckland ST, Gunnlaugsson, Th. Sei whale abundance in the North Atlantic, estimated from NASS-87 and NASS-89 data. Rep Int Whal Commn 1993;43:315-321. 43. Konr~idsson A, Sigurj6nsson J, Gunnlaugsson Th. Trends in age at sexual maturity in fin whales off Iceland based on transition phase in ear plugs. Paper SC/F91/F19 submitted to the Scientific Committee of the IWC, 1991 (unpublished). 44. Evans PGH. The Natural History of Whales and Dolphins. London: Christopher Helm, 1987. 45. Lockyer C, Sigurj6nsson J. The Icelandic fin whale, (Balaenoptera physalus): biological parameters and their trends over time. Paper SC/F91/F8 submitted to the Scientific Committee of the IWC, 1991 (unpublished). 46. Sigurj6nsson J. Recent studies on abundance and trends in whale stocks in Icelandic and adjacent waters. Proc R Acad Overs Sci (Brussels) 1992:77-111. 47. Mitchell E. Trophic relationships and competition for food in northwest Atlantic whales. Proc Can Soc Zool Annu Meet 1974:123-133. 48. Haug T, Gj6seter H, Lindstr6m U, Nilssen K. Studies of minke whale, Balaenoptera acutorostrata, ecology in the Northeast Atlantic: preliminary results from studies of diet and food availability during summer 1992. Paper SC/45/NA3 submitted to the Scientific Committee of the IWC, 1993 (unpublished). 49. JonsgArd/~. The food of minke whales (Balaenoptera acutorostrata) in northern North Atlantic waters. Rep Int Whal Commn 1982;32:259-262. 50. Sigurj6nsson J, Galan A. Information on stomach contents of minke whales in Icelandic waters. Paper SC/42/NHMi28 submitted to the Scientific Committee of the IWC, 1990 (unpublished). 51. Whitehead H, Carscadden JE. Predicting inshore whale abundance-whales and capelin off the Newfoundland coast. Can J Fish Aquat Sci 1985;42:976-981. 52. Sigurj6nsson J, Vfkingsson GA. Investigations on the ecological role of cetaceans in Icelandic and adjacent waters. Paper C.M./N:24 submitted to ICES Marine Mammals Committee, 1992 (unpublished). 53. Lydersen C, Weslawski JM, Oritsland NA. Stomach content analysis of minke whales Balaenoptera acutorostrata from the Lofoten and Vester~len areas, Norway. Holarct Ecol 1991" 14:219222. 54. NordCy ES, Blix AS. Diet of minke whales in the northeastern Atlantic. Rep Int Whal Commn 1992;42:393-398. 55. Haug T. On some reproductive parameters in fin whales Balaenoptera physalus (L.) caught off Norway. Rep Int Whal Commn 1981 ;31:373-378. 56. Hain JHW, Ratnaswamy MJ, Kenney RD, Winn HE. The fin whale, Balaenoptera physalus, in waters of the northeastern United States continental shelf. Rep Int Whal Commn 1981;31:653669. 57. Clapham PJ, Mayo CA. Reproduction and recruitment of individually identified humpback whales, Megaptera novaeangliae, observed in Massachusetts Bay, 1979-1985. Can J Zool 1985:2853-2863. 58. Sutcliffe WH, Brodie PF. Whale distributions in Nova Scotia Waters. Fisheries and Marine Service, Technical Report no. 722, 1977. 59. Klinowska M. Dolphins, porpoises and whales of the w o r l d - The IUCN Red Data Book. Gland and Cambridge: IUCN, 1991. 60. Watkins WA, Sigurj6nsson J, Wartzok D, Maiefski RR, Howey PW, Daher MA. Tagged fin whale tracked by ARGOS off Iceland. January 1995 (unpublished).

This Page Intentionally Left Blank

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang, editors

443

Aspects of the biology of the harbour porpoise, Phocoena phocoena, from British waters Christina Lockyer NERC, Sea Mammal Research Unit, c/o British Antarctic Survey, Cambridge, UK Abstract. Background: Specimens of harbour porpoises, Phocoena phocoena, from both strandings and by-catch around the British Isles between 1985 and September 1994 have been collected, although it has not been possible to distinguish reliably between by-catch and natural strandings. Methods: more than 300 individuals have been examined. Full autopsies were undertaken on most carcasses, and the following data and samples collected: sex, date of finding, location, total body length, girth, body and organ weights, blubber thickness and blubber tissue for lipid content analysis, reproductive organs, and teeth. Decalcified thin stained sections of teeth were used for determining age. Results and conclusions: the age range of the sample included animals from neonates to age 24 years. The largest individual age group comprised yearlings and neonates, and survival appeared to be low in the first year of life. Birth size was in the range 60-75 cm length and 3-9 kg weight. The maximum length recorded for individuals in the sample was 163 cm in males and 189 cm in females indicating that females grow larger than males. Maximum weights of 54 kg and 81 kg were recorded for males and females, respectively. There is a close correlation between body weight and both length and girth, although mid-girth is a better predictor of body weight than length, and small juvenile animals are both relatively and actually fatter than adults. The latter point may reflect the greater surface/volume ratios of young and their need for insulation and thermoregulation. Length, cm (L) and mid-girth, cm (G) together provide the means of most accurate estimation of body weight, kg (W): W=O.OOOO81Ll'2401Gl'5524. Limited female data indicate that pregnant females were heaviest and fattest, and that lactating females were lighter and leaner than anoestrous females. Blubber lipid content averaged 83-87% wet weight tissue for all classes of animals except neonates which appeared in the samples mainly during June, and had a lower mean of <70% wet weight tissue. The inferred peak calving period is June, with high numbers of neonates and calves found stranded in June to September. Data on testes weight suggest that the likely age at sexual maturation in males may be about 3 years onwards. Peak testes weight was observed in June-August and peak births in June. This suggests a gestation of 1 year or less in porpoise.

Key words: life history, age, fat, growth Introduction

This paper documents findings to date on aspects of life history and biological parameters, as well as growth and body fat condition, in harbour porpoise, using data derived from opportunistically sampled strandings and by-catches around the British Isles. By-catches have not been consistently reported, so that carcasses of this origin also tend to appear on beaches as strandings, as the result of being discarded at sea. Complete autopsies have been undertaken on almost every cetacean carcass

Address for correspondence: NERC, Sea Mammal Research Unit, c/o British Antarctic Survey, High Cross, Cambridge CB3 0ET, UK.

444 retrieved, in collaboration with the Institute of Zoology and the Natural History Museum, both in London.

Materials and Methods

In this study, a total sample of 303 porpoise carcasses, autopsied and sampled between 1985 and September 1994, and including 144 males and 128 females, has been examined, and biological data and materials investigated. The following material/data for this study were collected from most individuals when feasible: total length, mid-girth, sex, date of death, location found, teeth for age determination, gonads, body and tissue weights, lateral blubber thickness at the position of midgirth, and blubber tissue for lipid analysis.

Morphometrics Total body length was measured in a straight line from jaw tip to notch between the tail flukes. Other measurements were made according to Lockyer [1 ], including the mid-girth measurement (G3), and blubber thickness at the mid-girth position laterally

(~).

Body weight was measured for the intact animal, and muscle and blubber were weighed separately as described by Lockyer [1 ]. Testes were weighed to the nearest gram on a digital balance. Various plots, curves and regressions were fitted to the data, using software packages SYSTAT and North West Analytical STATPAK, in an investigation of body weight prediction and correlations between various tissue masses and dimensions. Differences with sex and age were examined.

Body fat condition All blubber tissue samples were taken as a strip from the mid-girth region, through to the underlying muscle, and stored frozen a t - 2 0 ~ until analysed for lipid content using an automatic Soxhlet extraction process with hexane [1]. All lipid contents were expressed as a percentage of wet weight of tissue. The lipid contents were subsequently examined in relation to girth and blubber thickness, and how these factors varied with sex, age and reproductive status.

Age and biological parameters Teeth were used for age determination, following the method of histological preparation described by Lockyer [2]. The sectioned and stained decalcified teeth were examined for growth layer groups (GLG) under a binocular microscope in plain transmitted light with magnification power x 10--x 50.

445 Age data were used in the investigation of age distribution of the sample population, growth in males and females, and in calculating likely ages at sexual maturation. For the last investigation, data on the gonads were required. Testes were weighed, and the ovaries individually serially sectioned to identify each ovarian body. All corpora lutea and c. albicantia were recorded and their presence was taken as evidence of ovulation and thus sexual maturation. Very few foetuses have been recovered, and no information regarding them is reported here.

Results

Morphometrics, body size and condition Total body weight, length and girth relationship Females attain a larger size than males with the maximum weights recorded being 54 kg in males and 81 kg in females. Mean adult weight is probably about 50 kg in males and 55 kg in females. The weight at birth is about 5 kg for both sexes, with a range of 3-9 kg for the 60-80 cm group. The maximum lengths recorded in the sample were 163 cm in males and 189 cm in females. The body weight at length relationship is shown in Fig. 1, with a curve fitted from log linear regression. Lockyer [1] showed that there is a strong correlation between weight and length, and although greater in males than females, the relationship between weight and length is similar in both sexes. Thus the sexes have been combined here. The weight on mid-girth (G3) in Fig. 2 demonstrates a close relationship. Lockyer [1] showed that the actual correlation of weight with girth is higher than weight at length. Table 1 gives formulae for predicting weight from both length and mid-girth from log linear regressions. The correlation between weight and both lin-

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ear measurements is strong in both sexes, and is reportedly greater than weight with either length or mid-girth alone [ 1].

Tissue weight and length Plots of muscle and blubber weights with body length are shown in Fig. 3. Muscle mass clearly increases greatly with increase in body length (Fig. 3a) as a power curve fitted to the data demonstrates, whilst blubber mass does not increase as much as muscle (Fig. 3b). The blubber data appear to be served adequately by a straight line plot, and it is certain that muscle mass becomes an increasingly important component of the body, whilst blubber becomes less dominant with general increase in body size. Blubber thickness Mean blubber thickness +_ SE has been plotted against body length in 1 0 c m increments (Fig. 4), and the variability is evident, particularly in the size ranges 9 1 150 cm. The neonates and first year animals <90 cm, as well as the very large animals >160 cm (mostly females), all have relatively thin blubber. There is a general decrease in mean blubber thickness throughout the size range 9 1 - 1 5 0 cm. The pattern thus appears to be thin blubber in neonates and first year animals,

Table 1. Formulae for calculating body weight (W in kg) from length (L in cm) and mid-body girth (G 3 in cm) of porpoise

Sex

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_SE for b

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Male Female Male and Female

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thickest blubber in yearlings and juveniles 91-130 cm, then thinner and decreasingly less blubber in adults as they become large (and older).

Blubber lipid composition Lipid content has been calculated as a percentage of wet weight of blubber tissue, and represents the total lipid content of mid-lateral blubber (site/-,3) throughout the depth of tissue from under-skin to muscle interface. Lipid content is plotted as the mean +_ SE against blubber thickness in 3 mm increments (Fig. 5a). The lipid content appears to increase consistently with thickness of blubber from a mean of about 70%

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in blubber <6 mm, to a maximum of 93% in blubber >30 mm thick. The plot of mean lipid content against body length in l 0-cm increments (Fig. 5b) demonstrates a similar pattern to that of blubber thickness in Fig. 4, with low lipid levels in 100

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Body fat condition and composition by age, sex and reproductive status The overall sample was classified into the size/age groups defined in Table 2, where the mean _+ SD has been calculated for different measurements: length, weight, blubber mass, muscle mass, mid-girth, blubber thickness, and blubber lipid content. Neonates are slightly over half the adult mean length, and about a sixth to a fifth of adult body weight, whereas juveniles (excluding neonates) are about 58% adult mean body weight. The blubber/muscle ratios change as the animal grows and develops, with a ratio of 3.3:1 in neonates, 1.7:1 in juveniles, and 1:1 in adults >130 cm. Mean blubber mass comprises 43.4%, 33.9% and 28.7% of total body weight, respectively, in neonates, juveniles and adults >130cm. The corresponding values of mean percentage muscle mass are 13.2%, 20.2% and 28.7%. These findings confirm the interpretation of Figs. 5a--c earlier where muscle is observed to become a more dominant tissue in the body with increase in size. Mid-girth as a percentage of total body length remains stable at 59-65% throughout life for all groups except anoestrous (resting) adult females >140 cm where the percentage is only 55%. The only lactating female measured had a girth only 52% of body length. Blubber thickness varied considerably with developmental stage and body size. The juveniles, as a group, had the thickest blubber of all at 17.6 mm, fol-

450

Table 2. Mean values for various measurements on pomoise, by reproductive status

Reproductive class

Mean values + SD Length (cm)

Neonates (M + F) <91 cm Sample size Immature less neonates (M + F) 91-130 cm Sample size Mature and sub-adults less pregnant and lactating (M + F) >I30 cm Sample size Mature less pregnant and lactating (F) >I40 cm Sample size Pregnant females Sample size Lactating females Sample size Pregnant and lactating Sample size

Weight (kg)

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Muscle weight (kg)

Mid-girth (cm)

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Lipid content

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9 14.4 i 2.1 6 10.0

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451 lowed by the pregnant group. Adults generally have thinner blubber than these two groups, but when 0.95 confidence intervals are calculated, there is overlap of values and the differences are therefore not significant between these groups. Neonates, however, have the thinnest blubber. In the adult female group, there are too few data to make conclusions. However, the lactating female appears to have thinner blubber than other females and all other adults. The mean lipid content for all groups excluding neonates, is within the range 8387% wet weight of tissue. The neonate group have less lipid than other groups with 68% wet weight of tissue.

Age and biological parameters Age composition of sample The aged sample comprised 114 males and 96 females. The main difference in age frequency distribution of the sexes is in the numbers of 0-1 year age group. This group comprised 47.5% of males and 35.5% of females. The remaining number of individuals of age >2 years was 60 males and 63 females. The data suggest that longevity is similar for both sexes. The oldest male was 24 years and oldest female was 22 years.

Length at age Calculated mean length _ SE at age for each sex separately (Fig. 8) derive from data where all first year animals actually fall in the size range 60-118 cm for males and 66-118 cm for females. This age class comprises both neonates and animals nearly 1 year old. Examination of the size distribution in this age class and also observations of unhealed and healed umbilicus, indicate that the neonates come within the size range 60-80 cm with a probable birth size of 65-70 cm. The length at age data show that females grow larger than males (Fig. 8). Most animals have reached maximum size by age 8 years and mean adult lengths for males and females will probably be about 145 cm and 160 cm, respectively.

Reproductive data Female reproductive materials and data have not yet been completely analysed. However, male testes weights have been analysed, and combined testes weights have been plotted against age (Fig. 9a), and body length (Fig. 9b). Testes weight increases sharply from age 3 years (Fig. 9a) and from length 130 cm (Fig. 9b). One might assume that puberty commences at about age 3 years and length 130 cm, and sexual maturation follows. Figure 9a,b shows that there is very wide variation in testes weight, independent of age or length. The pattern of the relationships of testes weight with age and body size suggests that maturation of the testes probably occurs only in tissue >200 g (this is marked on Fig. 9b). One can therefore assume that testes <200 g are immature. The wide variation in testes weight can be explained by seasonal development when testes weight is plotted against month (Fig. 10). There is a rapid increase in

452

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AGE IN YEARS Fig. 8. Length (cm) at age for (a) male porpoise; (b) female porpoise, in British waters, with log-fitted

curves.

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454

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testes size in the summer months June-August, with the heaviest testes observed in August. This indicates a strong seasonal reproductive activity in males. This seasonal gonad activity in males implies a highly seasonal parturition period. In the plot of frequency of neonates (<90 cm length), by month (Fig. 7, referred to earlier), there is a rise in June-August, with the peak in June. This is strongly indicative of a June-July birth for most porpoise in British waters.

Discussion

Morphometrics, body size and condition The strong correlation of body weight with both length and mid-girth indicates that body weight can be predicted from formulae derived by log-linear regression of weight on both length and mid-girth. It is clear that mid-girth alone may be helpful in estimating body weight in instances where carcasses are damaged and flukes or head are missing. The proportions of blubber and muscle as a percentage of body mass (averaging 28.7% each) appear to differ from the report from Yasui and Gaskin [3] that for a "standard adult" of 150 cm length, blubber is 33.4% and muscle is 22.6% of body weight. However, their sample sizes were small (N = 18 animals). Muscle becomes a

455 more dominant tissue in adulthood, perhaps reflecting the extra power required by adults, and greater levels of activity associated with reproduction. At the same time, blubber appears to be of less importance in the adult. Blubber thickness appears greater in juveniles and is thinner in adults as reported by Read [4] for Bay of Fundy porpoises. Read found that his calves were fattest amongst all groups, unlike findings here for neonates. However, Read measured blubber ventrally over the sternum, rather than mid-laterally, and the mean length of his immature group was larger by up to 16 cm, and also his calf group was larger than the neonates here by about 31 cm. Read [4] observed a direct linear relationship between blubber mass and body length, as found here (Fig. 3b). The mid-girths reported by Read [4] for each group are similar to those in Table 2, although his immature group is fatter, presumably because of the length incompatibilities of the data sets. Birth during June-July may be a favourable time environmentally for neonates which are thin and have a low blubber mass, because of higher water temperature, resulting in less body heat loss. It is clear that juveniles rapidly acquire thick blubber, and lipid content also increases to adult level. Perhaps this takes place during the suckling phase in preparation for nutritional stresses at the time of weaning. Such a potential energy store coupled with increased thermal insulation may favour juvenile survival at a time when finding food may be a problematic and energetically demanding experience. Although lipid content remains fairly stable in adults at 8387% wet weight of tissue, blubber thickness and mass declines relative to juveniles. There is a suggestion that body fat condition may vary with reproductive state in females [4], with increased fatness in pregnancy and depletion in lactation.

Age and biological parameters Age composition of sample The age data include animals >20 years, demonstrating that there are some old animals in the population of both sexes. This is in sharp contrast to findings of Gaskin et al. [5] and Read [6], who found no animals over the age of 13 years. Indeed few animals exceeded 8 years of age. Read's sample was entirely from incidental take in a gill-net fishery in the Bay of Fundy, eastern Canada. Kinze et al. [7] reported porpoise ages up to 15 years off west Greenland. In contrast, Hohn and Brownell [8] reported harbour porpoises up to the age of 24 years off coastal California. These data indicate that individuals are capable of surviving to ages >20 years, and suggest that the Bay of Fundy data may be biased or that the population is depleted from continual incidental fishery exploitation. The high incidence of neonates and first-year porpoise may be of concern. Mortality is generally highest after birth for all animals. The cause of death in these young animals may be natural or may be the result of incidental catch. Some neonatal deaths may be precipitated by unseasonably cold water in some summers, because blubber is thin and thus provides poor insulation. The fact that there are many more males than females in this group may indicate that female neonates have an advantage in survival [1,2], although nothing is known about foetal sex ratios. Sur-

456 vival from birth to age 1 year is extremely low in the sample, and the impression is that the numbers in this age group are biased. The neonate size of about 70 cm is smaller than recorded by other researchers who give sizes within the range 70-85 cm [5,7,8,10-13]. Some "neonates" may be the result of premature delivery (there is a record of a stillborn animal with uninflated lungs), but most small porpoises (60--75 cm) have healthy lungs and stomach contents, suggesting that they were from normal births. A few small animals had a healed umbilicus. SCrensen and Kinze [ 13] reported harbour porpoise neonates in the size range 63-86 cm off Denmark. Length at age The sizes of the British animals are generally similar to those reported elsewhere in the North Atlantic, North Sea and Baltic [5]. However, the largest male (163 cm) and female (189 cm) appear to be among the largest animals reported anywhere [5]. The length at age for each sex is similar to that for porpoises off California [8]. Reproductive data There are estimates in the range 3-5 years for the age at sexual maturity for female porpoise, depending on the population and time period [5-9,13,14]. It is anticipated that porpoises from British waters will be similar, with a likely age of 3 - 4 years. Likely size at maturity would be 140-145 cm, similar to published reports for elsewhere. Age and size at sexual maturity for males are 3 years and 130 cm off west Greenland [7]; 3 years and 135 cm off Denmark [14]; 3 years and 132 cm in coastal eastern Canada [5]; and about 4 years and > 140 cm off California [8]. Limited data suggest maturation at age >3 years and >130 cm for males in British waters. Certainly, puberty is initiated at this age and size. The British data confirm the seasonal reproductive cycle in males reported by Gaskin et al. [5], Read [15] and SCrensen and Kinze [14], and support the existence of a mid-summer birth (June-July) and summer breeding (July) off Britain.

References 1. Lockyer C. Aspects of the morphology, body fat condition and biology of the harbour porpoise, Phocoena phocoena, in British waters. Rep Int Whal Commn 1995;(Special Issue 15):(in press). 2. Lockyer C. Preliminary investigation of life history of the harbour porpoise, Phocoena phocoena, in British waters. Rep Int Whal Commn 1995;(Special Issue 15):(in press). 3. Yasui WY, Gaskin DE. Energy budget of a small cetacean, the harbour porpoise, Phocoena phocoena (L.). Ophelia 1986;25:183-197. 4. Read AJ. Estimation of body condition in harbour porpoises, Phocoena phocoena. Can J Zool 1990;68:1962-1966. 5. Gaskin DE, Smith GJD, Watson AP, Yasui WY, Yurick D.B. Reproduction in the porpoises (Phocoenidae): implications for management. Rep Int Whal Commn 1984;(Special Issue 6):135148.

457 6. Read AJ. Age at sexual maturity and pregnancy rates of harbour porpoises Phocoena phocoena from the Bay of Fundy. Can J Fish Aquat Sci 1990;47:561-565. 7. Kinze CChr, S~rensen TB, Kremer H. The growth and reproduction of west-Greenlandic harbour porpoises (Phocoena phocoena (L.)) with remarks on sex and age distribution. Doc SC/42/SM48. Document submitted to the International Whaling Commission Scientific Committee 1990. 8. Hohn A.A, Brownell Jr RL. Harbor porpoise in central Californian waters: life history and incidental catches. Doc SC/42/SM47. Document submitted to the International Whaling Commission Scientific Committee 1990. 9. Read AJ, Gaskin DE. Changes in growth and reproduction of harbour porpoises, Phocoena phocoena, from the Bay of Fundy. Can J Fish Aquat Sci 1990;47:2158-2163. 10. van Bree PJH. On the length distribution of harbor porpoises (Phocoena phocoena) from west European and Baltic waters. Mammalia 1973;37:359-360. 11. Fisher HD, Harrison, RJ. Reproduction in the common porpoise (Phocoena phocoena) of the North Atlantic. J Zool 1970; 161:471--486. 12. MChl-Hansen U. Investigations on reproduction and growth of the porpoise (Phocoena phocoena (L.)) from the Baltic. Vidensk Medd Dan Naturhist Foren 1954;116:369-396. 13. van Utrecht WL. Age and growth in Phocoena phocoena Linnaeus, 1758 (Cetacea, Odontoceti) from the North Sea. Bijdr Dierkd 1978;48:16-28. 14. Sr TB, Kinze CChr. Reproduction in Danish harbour porpoises (Phocoena phocoena (L.)). Doc SC/42/SM32. Document submitted to the International Whaling Commission Scientific Committee, 1990. 15. Read AJ. Reproductive seasonality in harbour porpoises, Phocoena phocoena, from the Bay of Fundy. Can J Zool 1990;68:284-288.

This Page Intentionally Left Blank

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCe and 13. Ulltang, editors

459

Aspects of reproduction and seasonality in the harbour porpoise from Dutch waters M.J. Addink 1, T.B. SCrensen 2 and M. Garcfa Hartmannl,3, 4 1National Museum of Natural History, Leiden, The Netherlands; 2Cell Biological-Anatomical Laboratory, Zoological Institute, University of Copenhagen, Copenhagen, Denmark; 3Seal Research and Rehabilitation Centre, Pieterburen, The Netherlands; and 4 Duisburg Zoo, Duisburg, Germany Abstract. Background: since about 1960 the harbour porpoise Phocoena phocoena (L.) in Dutch waters has declined in number. In 1990 a research programme was started to establish the possible causes of this decline as well as to obtain basic information on the species' life history. Methods: a complete postmortem was carried out on most stranded animals and some known by-catches. The reproductive organs were studied. Historical data were investigated for useful reproductive information. Results: near-term foetuses were observed in March and April; neonates from May to the end of August. Spermatogenetic activity was observed in one male in March. In a sample of seven females aged at 3 5 years, five were sexually mature. Within a sample of 15 mature females, four had both ovaries functionally developed. Conclusiens: the reproductive season and birth period in Dutch porpoises appear to be extended in comparison with some other populations. A previous study found an age of sexual maturity (ASM) of 6 years for Dutch female porpoises. In the present, limited study the ASM appears lower. Although Phocoena is known for its ovarian asymmetry, 4 out of 15 (26.6%) of the females showed functional development of both ovaries. Key words: Phocena phocena, The Netherlands, female age at sexual maturity (ASM), ovarian asymmetry

Introduction From about 1960, the number of stranded harbour porpoises Phocoena phocoena (L.) severely declined on the coasts of the southern North Sea [1-4]. Sighting records, even though many of these are anecdotal, show a similar trend [4,5]. In 1990 an intensive research programme was started in the Netherlands, with the aim of gathering information on the possible causes of this decline and to obtain basic information on the harbour porpoise. The programme collects data on life history, pathology, pollutant burden and stomach contents.

Materials and Methods All porpoises Collected by the stranding network of the National Museum of Natural History in Leiden are studied during a thorough postmortem. The dissection protocol

Address for correspondence: M.J. Addink, National Museum of Natural History, P.O. Box 9517, 2300 RA Leiden, The Netherlands.

460 is based on an expanded version of the European Cetacean Society dissection protocol for small cetaceans [6]. During the dissection the uterus and ovaries or the testes and epididymides are examined and fixed in 10% neutral buffered formalin. When a foetus is present, its length and weight are recorded. The ovaries are studied under a binocular microscope, and the numbers of corpora lutea (CL) and corpora albicantia (CA) are counted. A porpoise is considered sexually mature if an ovary contains at least one CL or CA. When a CL is present but no foetus is found, the uterus is examined for signs of recent pregnancy. Histology is used to confirm lactation. So far, the testes and epididymides of two animals have been studied histologically. Each testis sample was dehydrated in acidified 2,2-dimethoxypropane, cleared in toluene, embedded in Paraplast and sectioned at 8 r Sections from each sample were stained with Ehrlich's haematoxylin and eosin and mounted in entellan prior to examination. The remaining samples will be processed later. Teeth were processed using standard techniques [7] and age estimates were obtained from counts of growth layer groups. Since about 1920, Dutch biologists have collected porpoises for anatomical research. For the present study, published records [8-11] as well as archives and other historical records were investigated for useful reproductive information.

Results

As the research is still in progress, only aspects of seasonality in birth period and male reproduction are presented here, as well as certain data concerning female age at sexual maturity (ASM) and ovaries. Data on lactation, male ASM, etc. will be presented elsewhere. These are preliminary results based on various subsamples of the database, which were ready for interpretation. The average length at birth of 27 porpoises which, according to biological and/or pathological records were definitely neonate, is 74.3 cm (SD 7.8 cm; range 6397 cm). Apart from these, there is a much larger dataset giving reliably recorded lengths but no information on whether the animals were newborn. Because no statistical tests have yet been carried out on the data, for this article only the above 27 porpoises definitely neonate, and those (n = 47) from the other dataset measuring <74.3 cm (the average length at birth), were used to determine the months of birth. Dutch porpoises show a prolonged birth period (see Fig. 1) which extends into August. Other evidence suggesting an extended mating and, by inference, birth period is that in two males, testis activity was found outside the reproductive period (JuneSeptember) given for Denmark [12]. Gross pathological examination showed that a male found stranded on 26 March 1992 had the epididymides full of sperm (see Fig. 2), and a male found on 6 November 1990 had some traces of sperm. Histological examination revealed spermatogenetic activity in the male from March, but no sig-

461 45

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Fig. 1. Near-term foetuses and neonates of Phocoena phocoena from Dutch waters, by month of birth. Although there is a clear peak in July, the birth season extends into August.

nificant activity was found in the male from N o v e m b e r (this specimen requires a more thorough study). Seven female porpoises studied for reproduction were aged as b e t w e e n 3 and 5 years old. Table 1 shows that five of these were already sexually mature. The ani-

Fig. 2. Sperm taken from the epididymides of the male stranded on 26 March 1992, photographed during the postmortem (photograph J.C. den Hartog).

462 Table 1. Female Dutch harbour porpoises aged between 3 and 5 years old

Maturity

Date

Place

89.03.15 89.09.01 90.12.05 91.01.02 92.01.09 92.01.18 92.11.22

Bloemendaal Mature Z a n d v o o r t Mature Oosterschelde Immature Texel Mature Texel Immature Camperduin Mature Castricum Mature

Length

Weight (kg)

Age (year)

Pregnant

145 154 132 169 149 147.5 150

59 39 29 51 33.5 48 41

5-5.75 3-4 4.25 5 5 5.25 5

Yes No No No No

(cm)

Five out of seven porpoises are already sexually mature (defined as at least one CL or CA present). mal stranded on 15 March 1989 was pregnant with a 53 cm foetus. It had only one CL of pregnancy and no other scars, so must have become pregnant for the first time when it was between 4 and 5 years old. Although P h o c o e n a is known for its ovarian asymmetry, within a series of 15 sexually mature females with at least one CL or CA, four animals showed functional development of both ovaries (26.6%). One of these, a pregnant animal, had the foetus in the right uterus horn and the CL of pregnancy in the right ovary.

Discussion Although there is a pronounced peak in July, the birth period in Dutch waters appears to be extended (see Fig. 1). SCrensen and Kinze [12] as well as Read [13] report a narrow birth peak, from the middle of June to early July for Denmark and from May to June for Canada. In central Californian waters, however, there appears to be a more extended birth period again, from June into August/early September [ 14]. There are sightings of calves as early as April in British waters (P.G.H. Evans, personal communication) and there is one calf in April among a limited set of sightings in Dutch coastal waters [15]. The causes of these differences between porpoises from different geographic areas are not clear; for a discussion of the topic, see SCrensen and Kinze [ 12]. The studies from Denmark and Canada [12,13] also find a strongly synchronized female reproductive cycle, and this appears to be true for males as well. Because most Dutch porpoises are collected in late autumn/winter, there are almost no females available for studying maturing follicles. So far, based on gross pathological examination, only ten males assumed to be mature have been collected during this study. The two males with aseasonal (as defined by SCrensen and Kinze [12]) sperm activity would be in agreement with an extended female mating period. A previous study found an age of sexual maturity of 6 years for Dutch female porpoises [ 11 ]. In our material, the ASM is lower for five of the seven animals studied (see Table 1). It is suspected that some of the ages published by Van Utrecht [ 11 ] may be too high. Some of the teeth studied by Van Utrecht were cut in a way that

463 could lead to an erroneous age determination (C. Lockyer, personal communication). The animals in question will be aged again. If Van Utrecht's age determinations prove correct, our findings could be evidence of a population under pressure, in which the ASM would have decreased by 1 year or more. A similar reaction was observed in the harbour porpoise population in the Bay of Fundy, Canada [ 16]. Phocoena is known for its ovarian asymmetry, with only the left ovary developing during puberty and all activity confined to this ovary [12]. It is thus very interesting that 4 out of 15 females from Dutch waters have both ovaries functionally developed. Because histological examinations are not completed, we will refrain from speculating about the possible causes of this phenomenon.

Acknowledgements We thank P.J.H. van Bree for giving access to historical reports and archives, T. Olesen for processing the two samples for histology, H. Kremer for processing the teeth, J.C. den Hartog for taking photographs during a postmortem, and C. Smeenk and P. de Wilde for critically reading this manuscript.

References 1. Smeenk C. The harbour porpoise Phocoena phocoena (L., 1758) in The Netherlands: stranding records and decline. Lutra 1987;30:77-90. 2. Verwey J. The cetaceans Phocoena phocoena and Tursiops truncatus in the Marsdiep area (Dutch Waddensea) in the years 1931-1973. Nederlands Instituut voor Onderzoek der Zee, Publikaties en Verslagen, 1975;17a,b:l-153. 3. Evans PGH, Harding S, Tyler G, Hall S. Analysis of cetacean sightings in the British Isles, 19581985. Peterborough, UK: Nature Conservancy Council, 1986. 4. Evans PGH, Scanlan GM. Historical review of cetaceans in British and Irish waters. UK Cetacean Group, Zoology Department, University of Oxford, 1989. 5. Camphuysen C, Leopold MF. The harbour porpoise Phocoena phocoena in the southern North Sea, particularly the Dutch sector. Lutra 1993;36:1-24. 6. Kuiken T, Garcfa Hartmann M (eds). Proceedings of the first European Cetacean Society workshop on cetacean pathology: dissection techniques and tissue sampling, Leiden, The Netherlands, 1991. ECS Newslett 1993;(Special Issue 17):1-39. 7. Perrin WF, Myrick Jr AC (eds). Age determination of toothed whales and sirenians. Cambridge: Rep Int Whal Commn 1980;(Special Issue 3). 8. Deinse AB van. De Fossiele en Recente Cetacea van Nederland. Amsterdam: HJ Paris, 1931. 9. Deinse AB van. De recente Cetacea van Nederland van 1931 tot en met 1944. Zool Med 1946;26:139-210. 10. Slijper EJ. Die Cetaceen Vergleichend-anatomisch und Systematisch. Den Haag: Martinus Nijhoff, 1936. 11. Utrecht WL van. Age and growth in Phocoena phocoena Linnaeus, 1758 (Cetacea, Odontoceti) from the North Sea. Bijdr Dierkunde 1978;48:16-28. 12. SCrensen TB, Kinze CC. Reproduction and reproductive seasonality in Danish harbour porpoises, Phocoena phocoena. Ophelia 1994 ;39:159-176.

464 13. Read AJ. Reproductive seasonality in harbour porpoises, Phocoena phocoena, from the Bay of Fundy. Can J Zool 1990;68:284-288. 14. Hohn AA, Brownell RL. Harbor porpoise in central Californian waters: life history and incidental catches. Doe SCI421SM!47. Int Whal Commn 1990;1-11. 15. Camphuysen C. The harbour porpoise Phocoena phocoena in the southern North Sea. II: a comeback in Dutch coastal waters? Lutra 1994;37:54--61. 16. Read AJ, Gaskin DE. Changes in growth and reproduction of harbour porpoises, Phocoena phocoena, from the Bay of Fundy. Can J Fish Aquat Sci 1990;47:2158-2163.

9 1995 Elsevier Science B.V. All rights reserved Whales, seals, fish and man

A.S. Blix, L. WallCeand t3. Ulltang, editors

465

Migration strategy of southern minke whales to maintain high reproductive rate Hidehiro Kato National Research Institute of Far Seas Fisheries, Orido, Shimizu, Shizuoka, Japan The timing of the southward migration of southern minke whales from their breeding grounds is examined by analyzing length data from 11,953 foetuses recorded in Areas II and IV from 1971/1972 to 1986/1987 by the Japanese whaling expeditions. The few records of lactating females or cows with calves in high latitudes and review of published information suggests that the majority of females conceive while still lactating and that lactating females remain segregated and do not migrate to the Antarctic until after weaning. Although back-calculation of foetal length gives a conception peak in early September, females that conceived in the earlier part of the mating season tended to arrive earlier in the Antarctic than those that conceived later. This appears to be a strategy to maintain a high reproductive rate and may be a density dependent change due to a possible recent increase in carrying capacity. Abstract.

Key words: foetal growth, pregnancy while lactating, conception peak, calving interval, migration pattern

Background While it is reasonable to consider for most balaenopterids that the reproductive cycle is 2 years comprising about a year gestation, a half year lactation and a half year resting period [ 1], minke whales (Balaenoptera acutorostrata) are believed to have a shorter reproductive cycles in both the northern and southern hemispheres [2]. Best [3] considered the mean annual pregnancy rate to be 0.78 or 1.29 years of mean calving interval for southern minke whales; if this is true some specific strategy will be necessary to accommodate a 1 year migration cycle to maintain such a high reproductive rate. Kato and Miyashita [4] examined this feature using data obtained from past Antarctic whaling expeditions; the present study further considers and explores the specific feature of the strategy.

Materials The present study used a total of 11,953 foetal lengths recorded in the Antarctic Areas III and IV by the Japanese commercial whaling expeditions in 1971/1972 to 1986/1987 which took place at high latitudes. Data from both areas were combined

Address for correspondence: National Research Institute of Far Seas Fisheries, 5 - 7 - 1 0 r i d o , Shimizu, Shizuoka 424, Japan

466 without further consideration of the stock boundary. In addition to the body length data, total body weights from Areas III, IV and V in 1978/1979 to 1981/1982 were used to calculate the regression formula for foetal body weight on length. In addition to the standard records collected every year by the technicians, the present study used the condition of the mammary gland of each female which was examined on the deck of the factory ship (Nisshin-maru no. 3) by the author or professional colleagues during the entire period of the operation in 1985/1986. The other data source used was the biological master tape for whales caught between 1971/1972 and 1986/1987 held by the National Research Institute of Far Seas Fisheries, Shimizu. Foetal length was measured to the nearest 1 cm along a straight line from the top of the upper jaw to the notch of the tail flukes (or to the tip of the tail for foetuses smaller than about 12 cm in length). Body weight was measured to the nearest 1 g, 10 g, 100 g and 1 kg for size classes <5 cm, 6-15 cm, 16--49 cm and >50 cm, respectively.

Results

Foetal growth curve Model In order to obtain a reasonable model indicating foetal growth of southern minke whales, the formula of Hugget and Widdas [5] was used: Wlt3 = a ( t - to)

(1)

where W is the body weight in grams, a is a growth velocity constant, t is the time in days since conception and to is the intercept where the linear part of the plot, if extrapolated backwards, cuts the time axis. Because of the limited months for fishing and the range of foetal sizes in the minke whale samples, it was not possible to estimate a and to from monthly changes in foetal size composition as noted by Ivashin and Mikhalev [14]. For this study, we have estimated a for southern minke whales by estimating the interspecific relationship among balaenopterids between a and neonatal length. We have accepted the value of to = 74 days proposed for most balaenopterids by Lockyer [1 ] without further consideration. Growth velocity Since balaenopterids have similar gestation periods of 10-11 months, positive correlation can be assumed between neonatal length (Lb) and growth velocity (a). We use this feature here for estimating a. Lockyer [1,6] examined the published foetal growth formula for mysticetes [5,710], and after reviewing previous estimates of a and to by those authors, obtained

467 revised estimates for the southern blue (B. musculus), fin (B. physalus) and sei (B. borealis) whales. Figure 1 shows the correlation between a and ~ (in cm) among the three species (each parameter value is given in Table 1). The fitted regression of a on Lb is expressed as follows, with a high correlation coefficient (r 2 = 0.998):

(2)

a = 0.048 + 0.00067 Lb

Kato [ 11 ] considered 290 cm to be the most appropriate value for the mean length at birth of southern minke whales from reviewing previous studies [3,12-16] and examining the relationship between female maximum lengths and mean neonatal length among several balaenopterids. From eq. (2), this leads to an estimate of a of 0.24.

Weight-length key Using the 867 foetal weight data (Fig. 2) ranging from 1.6 g (4.0 cm in length) to 250 kg (304 cm), the regression between body weight (W, in g) and length (L, in cm) was calculated as W = 0.059L 2-676

(3)

The correlation coefficient between log W and log L is high (r 2 = 0.992).

,•ue

0.6

t--

t~

0.5

o O

0.4

~ O O ,==..

Sei

0.3

Jr"

O t._

I Minke 0.2

O !

I

2

Foetal

1!

I

4

body

I

l

6

length

I

I

I

8

(L b} in c m

Fig. 1. Relationship between the foetal growth velocity (a) and the neonatal body length (Lb) among balaenopterids in the Southern Hemisphere.

468

Table 1. Length distribution of minke whale foetuses in each 10 days, collected from Areas 111 and IV in 1971J1972 to 1986/1987 of Japanese Antarctic operations Length class (cm)

Ten days of month foetus collected; E=early, M=middle, L=late 11E

11M

1lL

12E

12M

12L

1E

1M

1L

2E

2M

2L

3E

3M

3L

0

0

~

0

~

0

~

0

0

0

~

0

0

0

~

0

0

~

0

0

0

0

~

0

0

0

0

0

0

~

0

0

0

0

~

0

0

0

0

0

0

0

0

0

0

0

0

~

0

0

0

0

0

0

0

0

0

0

0

0

0

0

~

0

0

0

~

0

~

0

0

0

0

0

0

0

~

0

~

0

0

0

~

0

0

0

0

~

0

0

0

0

0

0

~

~

0

0

0

469

470

r

v~ o

w = o.os9 L ~ o

0

3

../

"/

f

",~, -.#

o "0 0

eo~,

rn

it

I

!

10

100

Body

length(L)

200 in cm

Fig. 2. Relationship between foetal body length (L) and body weight (W) of southern minke whales in full-logarithmic scale.

Foetal growth formula Using the value of a of 0.24 from eq. (2) and to = 74 days, the foetal growth formula for southern minke whales is W 1/3 = 0 . 2 4 ( t - 74)

(4)

or

t = W1/3/0.24 + 74

(5)

substituting eq. (3) for W, then t = 1.622L ~

+ 74

(6)

However, eq. (4) is not applicable to foetuses in the slow growth stage of early gestation. Although the length (or weight) of a foetus at which the growth rate

471 changes is not known for any cetacean, Laws [17] suggested that change may take place when the placenta is formed in the uterus. From my observation, this phase appears to occur at around 15 cm in body length in southern minke whales. Therefore, we tentatively consider that the growth rate changes at 15 cm (or 82.8 g), at which t is 92 days from eq. (6). Assuming a linear growth rate in body weight between conception (t, W; 0,0) and the change (92, 82.8), the growth for foetuses less than 15 cm in length can be expressed as t = 1.11W

(7)

or t -- 0 . 0 6 5 5 L 2"676

(8)

The overall foetal growth curve is summarized in Fig. 3.

Timing of conception To estimate the date of conception we converted the foetal lengths into ages using eqs. (6) and (8). In the analyses, foetal length data were grouped by 10-cm intervals for foetuses over 19 cm in length (median values were used for the calculations), whereas actual lengths recorded to the nearest 1 cm were used for smaller foetuses.

---~/

300

250 A

E

o

_.e >, '1o o

4) 0 i.!.

200

150

100

50

I

t = 0.06 Lt2"6~6~

I

___......-.---.--,

50

,

,

,

I

100

,

,

i

i

I

150

i

i

i

~

J

200

*

i

i

i.

I

250

.

.

.

.

l

300

9

.

=

I

350

Days since conception (t) Fig. 3. The overall foetal ~rowth curve of southern minke whales established by the present study.

472

Table 2. Incidence of conception by 10 days estimated from foetus length in relation to the month the foetus was sampled: corrected values (Cor.) are from the correction by monthly changes in CPUE, sex ratio, sexual maturity and pregnancy rate

Ten days

Incidence of conception November Crude

December

Cor.

%

January

Crude

Cor.

%

Crude

February %

Crude

Total

March Cor.

%

Crude Cor.

%

Crude

Cor.

%

In previous season 12M 1 0.2

0.1

0

0.0

0.0

0

0.0

0

0.0

0.0

0

0.0

0.0

1

0.2

0.01

In early season 1E 2 2 1L 1 2E I 2M 1 2L 3E 0 3M 0 3L 0 4M 1 4L 0 5E 0 5M 0 5L 0 6E 0 1 6M 6L 14

0.2 0.2 0.1 0.1 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.1 1.4

4 3 5 7

1.9 1.5 2.4 3.4 0.5 2.4 0.0 0.0 0.0 0.0 0.0 1.0 1.0 2.4 5.8 11.2

0.1 0.1 0.1 0.2 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.5

0 0 0 1 1 1 1 2 1 1 0 0 1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.3 0.8

0 0 0 0 0 I 0 0 2 2 2 2 5 11 21 22

0.0 0.0 0.0 0.0 0.0 0.7 0.0 0.0 1.4 1.4 1.4 1.4 3.4 7.5 14.2 14.9

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.3 0.7 0.7

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0

6 5 6 9 3

2.3 1.0 2.6 4.6 1.7 4.1 1.0 2.0 2.6 2.4 1.4 2.4 5.4 16.9 31.8 54.0

0.03 0.03 0.04 0.06 0.03 0.06 0.02 0.03 0.04 0.03 0.02 0.03 0.07 0.22 0.41 0.69

0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.2 2.9

1

5 0 0 0 0 0 2 2 5 12 23

7

11 25

7

1 2 4 3 2 4 8 23 46 84

7E 7M 7L 8E 8M 8L 9E 9M 9L 1OE 1OM 1OL 11E 11M 11L 12E 12M 12L

12 28 70 120 212 134 14 39 26 46 28 47 51 73 82 0 0 0

In late season 1E 0 0 1M 1L 0 2E 0 2M 0 2L 0 3E 0 Total

1,006

473

474

20

9'..o ~ /',,_ i/ ~ ! I. . i ii ~

15

=,,..A. o.-o o--e ~--zx

November samples December samples January samples Februarysamples

o c o

I

!

., :

10

:.

I

:.o/

".

/i~.1, I

,,o~ '

.~1

9

I

,,"

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a"

i

1

,A,I

I\

\/

i/

_ _..,ii~"2B

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\

%-o-t,-o-,, o../\ Xo.~O-~O "--o-a= f O

~

^. - a ,

!

M

J

J

A

S

0

N

D

J

F

Month

Changes in pattern of conception date by month at which foetuses were collected. Incidence of the conception is expressed in 10-day periods obtained from foetal lengths, after correction for monthly changes in CPUE, sex ratio, maturity rate and pregnancy rate in the catch.

Fig. 4.

Table 1 indicates the length distribution of the 872 foetuses by 10-day periods. Conception dates were pooled by 10-day periods. In order to estimate the peak conception date for the population, using foetus samples collected from different months, we obtained the following correlation factors by multiplying the monthly catch per unit effort indices (CSW [ 19]), and the sex ratio, percent mature and pregnancy rate from Kate [16] for Areas III and IV: November,-0.207; December,-0.486; January,-1.000; February,-0.678; March, 0.609. Figure 4 and Table 2 show the incidence of conception by month of collection. Overall there is long-tailed distribution with apparent peaks from late August to early September. However, the apparent conception peaks appear correlated with sample month; the peak of the November samples is in mid-August, of the December samples in late August, and of the January and February samples in mid-September.

Yearly trends in the timing of conception Table 3 examines yearly changes in peak conception dates. The peak of conception in November is fairly constant among years. No trends are apparent for December,

475

Table 3. The peaks of conception expressed by the 10 days of the month calculated from the foetus length in each season of Antarctic operation by the month the foetus was obtained Season

1971/1972 1972/1973 1973/1974 1974/1975 1975/1976 1976/1977 1977/1978 1978/1979 1979/1980 1980/1981 1981/1982 1982/1983 1983/1984 1984/1985 1985/1986 1986/1987

Month foetus obtained a November

December

January

February

8M 8M 8M 8M 8M 8M 8L 8M 8M -

9E 9E 8L 8L 8L-9E 9M 9M 9M 9E-M

9M 9M 9L- 10E 9L 9M-10M 9E-M 9E 10E 9L 9L -

10L 10L 9M 9M

9L 10E

aE, lst-10th; M, 11-20th; L, 21st-30th/31st. January and February, although some fluctuations exist. Insufficient data were available to examine trends for March.

Occurrence of lactating females at the Antarctic The Japanese Antarctic operation took 27,149 female minke whales in seasons from 1971/1972 to 1986/1987, of which only 61 were recorded as lactating (Table 4). Table 4 reveals that the recorded proportions of lactating females to sexually mature females in 1971/1972 (1.42%) and 1985/1986 (0.94%) were relatively high; in these seasons scientists examined all of the whales caught. This suggested that the n u m b e r of lactating females in the other seasons a m o n g mature females in the Antarctic is about 1-1.5%. In 1985/1986, the author and colleagues examined the m a m m a r y glands, uteri and ovaries of all females caught (1,063 individuals) and found 10 lactating females. O f these, five had normal milk and the other five had "late or terminating milk" indicating that they were in the final stage of lactation. Five lactating females were simultaneously pregnant with foetuses of 5 - 1 7 c m in length (Table 5). According to the information from the catcher boats, one had been accompanied by a calf. In addition eight lactating females were taken under the Japanese research catch in 1988/1989, 1989/1990, 1991/1992 and 1992/1993; of those six were simultaneously lactating and pregnant, one was without foetuses and one unknown; none were a c c o m p a n i e d by a calf. Thus 11 simultaneously pregnant and lactating females were confirmed by scientists, and the mean lengths of their foetuses were 11.22 c m (CV 0.46) and 38.5 cm for lactating females with normal milk, respectively.

476

Table 4. Number of females by reproductive status and proportion of lactating females in 1971/1972 to 1986/1987 season of Japanese Antarctic operations Season

1971/1972 1972/1973 1973/1974 1974/1975 1975/1976 1976/1977 1977/1978 1978/1979 1979/1980 1980/1981 1981/1982 1982/1983 1983/1984 1984/1985 1985/1986 1986/1987 Total

Number of females Total

Mature

Pregnant

Unknown

1,942 975 2,597 2,251 1,553 2,276 1,388 1,635 1,327 1,647 1,999 2,140 1,868 1,061 1,063 1,457 27,149

1,643 615 2,031 1,779 1,102 1,834 1,130 1,348 1,090 1,350 1,678 1,845 1,578 991 967 1,362 22,343

1,526 541 1,751 1,620 972 1,602 969 1,181 1,010 1,236 1,563 1,681 1,471 923 907 1,289 20,242

4 11 15 10 18 20 46 21 30 57 64 74 31 5 17 39 461

Lactating 27 5 5 3 4 1 10 3 61

L. %a 1.42 0.52 0.20 0.14 0.25 0.05 0.94 0.21 0.28

aL.%; % of lactating to mature.

Table 5. Biological information of lactating females of the southern minke whale taken from the Antarctic region Date

Body length (m)

Reproductive status a

Foetus size (cm)

Mammary gland status b

T.B. c (cm)

8 Dec. 1985 8 Dec. 1985 9 Dec. 1985 19 Dec. 1985 23 Dec. 1985 24 Dec. 1985 28 Dec. 1985 10 Jan. 1986 10 Jan. 1986 27 Feb. 1986 14 Jan. 1989 11 Dec. 1989 18 Dec. 1989 3 Feb. 1990 1 Jan. 1992 17 Feb. 1992 23 Feb. 1992 3 Jan. 1993

8.9 8.9 8.9 9.3 8.9 8.7 8.8 9.3 8.5 8.9 8.7 9.2 8.8 9.0 9.2 8.6 9.1 8.4

Ovulating Unknown d Pregnant Ovulating Ovulating Pregnant Pregnant Pregnant Resting Pregnant Pregnant Pregnant Pregnant Pregnant Ovulating Pregnant Pregnant Unknown d

?

3.6 3.5 6.7 3.5 3.2 3.9 4.4 4.9 5.0 5.5 9.1 6.0 3.7 5.0 5.0 6.2 5.2 4.4

2.8 3.3 3.1 3.3 3.5 3.2 3.7 3.5 4.2 4.3 3.4 2.8 4.3 3.6 3.4 2.5 3.1 3.2

5 39 15 16 16 17 10 38 14,13 2.8 5.7 ?

L.milk L.milk N.milk L.milk L.milk L.milk N.milk N.milk N.milk N.milk N.milk N.milk L.milk N.milk N.milk N.milk N.milk N.milk

aOvulating means ovulating while lactating and pregnant is pregnant while lactating. bThickness of the mammary gland and types of milk as late (L) and normal (N) milk. CThickness of blubber at the lateral side of the body below the dorsal fin. dUterine horn was damaged by the harpoon.

477 The maximum depth of the mammary glands (Table 5) of the females with normal milk was 4.9-9.1 cm (mean 5.67, CV 0.23). This is within the range (but towards the lower end) of the mammary glands of active lactating females observed off Durban (4-16 cm [3]). The mean depth for females with late milk was 3.2-3.9 cm (mean 3.5, CV 0.24).

Discussion

The present analysis used the Huggett and Widdas [5] growth formula for foetuses over 14 cm in length but in the absence of empirical data we had to assume a simple linear growth rate for the smaller foetus. This is likely to underestimate the age of the smaller foetuses. However, even allowing for this bias, the overall patterns of conception are still acceptable because the magnitude of any bias will be slight. In the absence of empirical data, the lactation of southern minke whales is thought to last from 4 [18] to 6 months [3]. In either case, starting the overall peak of conception in early September revealed by the present analyses, lactation should last

Month ,

/,

M3

j

A ~b

~ b3

gestation(1)~

9-- lactation (1) 9----

?-- gestation(2) "--'-- .~=/~..~,.. 4-'-'~ conception(2)

WINTERGROUND

c•oncep_tion (1)

,

parturition

(1)

)

SUMMERGROUND

A

O~

~~/U

--Q

ICEEDGE

weaning

-Q-

Fig. 5. Schematic illustration of the possible migration pattern of the southern minke whales in relation to reproductive cycle. The double circles mean females and C1 means pregnant females and calf, respectively.

478 from early January to mid-March for most females. However, the percentage of lactating to sexually mature females in the Antarctic catch is only 1-1.5%. This apparent absence of lactating females in the high latitudes is further supported by the low numbers of cow and calf pairs seen during the Antarctic IDCR cruises [20]. It seems, therefore, that females wean their calves before arriving in Antarctic waters, probably because the prevailing oceanographic conditions in the Antarctic are not advantageous for weaned calves. The present study also suggests that most mature females ovulate and conceive while still lactating. This strategy of simultaneous pregnancy and lactation is the most likely way of allowing a short calving interval of about 1 year without breaking the annual migration cycle. It is also common in the Dali's porpoise (Phocoenoides dalli) which has a short calving interval close to 1 year (Gosho and Jones, personal communication; Kasuya, personal communication). In summary, mature females conceive while still lactating in low latitudes, cows and their calves segregate from the other whales, probably in low and middle latitudes, and the females do not move down to high latitudes for feeding until after weaning (Fig. 5). However, this does not mean that females continue to bear calves every year indefinitely. Accepting the annual pregnancy rate of 0.78 by Best [3] would mean that they would miss a pregnancy every 4 years on average. Another feature of their migration pattern revealed by the present analysis is that the peak of conception for November and December foetuses was earlier than that for January and later foetuses. A similar pattern was found in the eastern stock of grey whales [21]. It is unclear, however, whether the females that conceive earlier also leave the feeding grounds earlier. The foetal length distribution of Table 1 provides information on this. Estimates of the length of gestation obtained by regression of mean or modal lengths of foetuses (except those conceived in the previous season) against progress of the feeding season, are always greater than 1 year (up to 18 months) as shown by Masaki [15]. This suggests that females that conceived earlier also leave the feeding ground earlier than those that conceived later. At least two interpretations of the above strategies can be put forward. One is that the minke whale has evolved a 1-year reproductive cycle, particularly given that an annual cycle is seen in both hemispheres, whereas other balaenopterids have 2-year cycles or longer. Another is that the 1-year cycle is a response to changes in carrying capacity. The calving interval is one of several density dependent parameters seen in both terrestrial and marine mammals, and food resources are a major factor in density dependence [22]. As shown by Lockyer [1,6], the energy cost of lactation is generally greater than that of pregnancy and thus simultaneous lactation and pregnancy is energetically expensive and requires sufficient food availability for minke whale populations in the Antarctic, which have increased due to depletion of stocks of the larger baleen whales [23,24]. We believe that the strategy revealed by the present study is probably a result of density dependent changes attributable to an increased carrying capacity.

479

Conclusions 0

2. 3. 0

.

0

A conception peak of southern minke whales exists in early September. The majority of sexually mature females conceive while still lactating. The lactating females segregate and do not migrate to the Antarctic until after weaning. Females that conceived in the earlier parts of the mating season tended to arrive earlier in the Antarctic. Items 2 and 4 above must be specific strategies to maintain short calving interval or high pregnancy rate. This may be a density dependent change due to a recent increase in carrying capacity.

References 1. Lockyer C. Review of baleen whale reproduction and implications for management. Rep Int Whal Commn 1984;(Special Issue 6):27-50. 2. Horwood JW. Biology and Exploitation of the Minke Whales. Boca Raton, FL: CRC Press, 1990; 238 pp. 3. Best PB. Seasonal abundance, feeding, reproduction age and growth in minke whales off Durban (with incidental observations from the Antarctic). Rep Int Whal Commn 1981 ;32:759-786. 4. Kato H, Miyahita T. Migration strategy of southern minke whales in relation to reproductive cycle estimated from foetal length. Rep Int Whal Commn 1991 ;41:363-369. 5. Huggett AStG, Widdas WF. The relationship between mammalian foetal weight and conception age. J Physiol 1951;114:306-317. 6. Lockyer C. Estimation of the energy costs of growth, maintenance and reproduction in the female minke whale (Balaenoptera acutorostrata), from the Southern Hemisphere. Rep Int Whal Commn 1981;31:337-343. 7. Laws RM. Foetal growth rates of whales with special reference to the fin whale, Balaenoptera physalus (L.). Discovery Rep 1959;29:281-308. 8. Frazer JFD, Huggett AStG. Specific foetal growth rates of cetaceans. J Zool London 1973;169:111-126. 9. Frazer JFD, Huggett AStG. Species variations in the foetal growth rates of eutherian mammal. J Zool London 1974;174:481-509. 10. Rice DW. Gestation period and fetal growth of the gray whale. Rep Int Whal Commn 1983;33:539-544. 11. Kato H. Life history of baleen whales, with particular reference to southern minke whales. In: Miyazaki N, Kasuya T (eds), Biology of Marine Mammals. Tokyo: Scientist Inc, 1990;128-150 (in Japanese). 12. Davies JL, Guiler ER. A newborn piked whale in Tasmania. J Mammal 1958;39:593-594. 13. Ohsumi, S. Allomorphosis between length at sexual maturity and body length at birth in Cetacea. J Mammal Soc Jpn 1969;3:3-7. 14. Ivashin MV, Mikhalev YA. To the problem of the prenatal growth of minke whales, Balaenoptera acutorostrata of the Southern Hemisphere of the biology of their reproduction. Rep Int Whal Commn 1978;28:201-205. 15. Masaki Y. Yearly changes of the biological parameters for the Antarctic minke whale. Rep Int Whal Commn 1979;29:375-396.

480 16. Kato H. Year to year changes in biological parameters and population dynamics of southern minke whales. Doctoral thesis, Hokkaido University, 1986;145 pp. (in Japanese). 17. Laws RM. Southern fin whales. Discovery Rep 1966;31:327-486. 18. Williamson GR. Minke whales off Brazil. Sci Rep Whales Res Inst 1975;27:37-59. 19. Free CA. Southern hemisphere minke whales multiplicative regression analysis of Japanese CSW data. Rep Int Whal Commn 1983;33:111-113. 20. Kasamatsu F, Hembree D, Joyce G, Tsunoda L, Rowlett R, Nakano T. Distribution of cetacean sightings in the Antarctic: results obtained from the IWC/IDCR minke whale assessment cruise, 1978/79 to 1983/84. Rep Int Whal Commn 1988;38:449-487. 21. Rice DW, Wolman AA. The Life History and Ecology of the Gray Whale. Special publ 3, The American Society of Mammalogists, 1971; 142 pp. 22. Fowler CW. A review of density dependence in populations of large mammals. In: Genoways H (ed) Current Mammalogy, vol 1. New York: Plenum, 1987;401-441. 23. Kato H. Density dependent changes in growth parameters of the southern minke whale. Sci Rep Whales Res Inst 1987;38:47-73. 24. Kato H, Sakuramoto K. Age at sexual maturity of southern minke whales: a review and some additional analyses. Paper SC/42/SHMill submitted to 42nd annual meeting of IWC/SC, 1990;16 PP.

9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang, editors

481

Overview of cetacean life histories: an essay in their evolution Toshio Kasuya National Institute of Research on Far Seas Fisheries, Shimizu, Shizuoka, Japan Abstract. Extant cetacean species exhibit wide variety in body size, habitat choice, reproductive pattern and social structure. Augmentation occurred in several taxa supported by abundant food supply in association with polygyny, seasonal starvation or needs for precocious calves. Fetal growth rate, gestation time and breeding seasonality appear to have adapted for better life time reproductive success under a given environment, although full interpretation is often difficult. Mother and calf is the only stable individual association known to many baleen whales and some toothed whales such as phocoenids, which has further evolved as seen among several delphinids towards association of individuals by age and reproductive status including that of lactating females and also to extended maternal care. The last trait has evolved to a matrilineal school structure of killer whales and probably of long-finned pilot whales for lifetime cooperation of kin of both sexes, while males of sperm whales and perhaps short-finned pilot whales have chosen another mating strategy to fully utilize the female association by moving between nursing schools. The apparent polyandry of Baird's beaked whales could also arise from the same original social structure by assuming paternal investment in calf rearing and kin selec-

tion. Key words: growth, parental investment, polyandry, polygyny, reproduction

Introduction

Life history characteristics of mammals reflect both genetic and environmental differences. The major environmental factors of cetaceans include oceanography and food availability, and could have already been variously modified by human activities including whaling and other fisheries. However, our knowledge on their life history and social structure covers only a short historical period, and is limited to a small number of species. We know almost nothing about the social structure of many species of baleen whales, Ziphiidae, Monodontidae, and Kogia. The present study attempts, using such fragmental information on cetacean life histories, to review their variability and consider the evolutionary significance. This will help to understand the need of management to match characteristics of each species, although this review does not look at cetacean responses to short term environmental changes such as density dependence which is also an important factor of the management of whale stocks.

Address for correspondence: National Institute of Research on Far Seas Fisheries, 5 - 7 - 1 0 r i d o , Shimizu, Shizuoka, 424 Japan.

482 Sources of Information Used

Fetal growth and reproductive seasonality

o

11

o

.

.

.

.

.

Common porpoise Phocoena phocoena: fetal growth is given in Fraser and Huggest [ 1,2], and reproductive seasonality in Mohl-Hansen [3]. Finless porpoise Neophocaena phocaenoides: gestation time is available in Furuta et al. [4] with some uncertainty on conception date. This and assumption that to = 0.135tg [5], give the fetal growth rate. Breeding seasonality and neonatal length are in Shirakihara et al. [6]. Dali's porpoise Phocoenoides dalli: fetal growth is given in Kasuya [7], and reproductive seasonality in Kasuya [7] and Newby [8]. Commerson's dolphin Cephalorhynchus commersonii: average gestation of 345 _+20 days (n = 8) in captivity [9], average neonatal length of 100 cm [10] and to = 0.135tg [5] give fetal growth rate. Spotted dolphin Stenella attenuta and spinner dolphin S. longirostris: no reliable estimate of fetal growth available. Barlow [11] gives reproductive seasonality for each of the populations identified by Perrin et al. [ 12,13]. Bottlenose dolphin Tursiops truncatus: average gestation time is 3 7 0 _ 7 days (n = 77, population not stated) in captivity [9]. This mean neonatal length of 128 cm (WN Pacific) [14] and 117 cm (WN Atlantic) [15], and to = 0.135tg [5] give a range of the fetal growth rate. The fetal growth rate and dates of 96 fetuses (>26 cm) off Japan give the parturition season [ 14]. Short-finned pilot whale Globicephala macrorhynchus: information is available for two populations off Japan [ 16,17]. Long-finned pilot whale G. melas: Martin and Rothery [18] fitted conception curves to the fetal length to obtain likely fetal growth rate. The one used here is based on a single breeding season hypothesis, which gave a slightly slower growth rate than another bimodal model. A single breeding peak is apparent at least in Faroese waters in the occurrence of small fetuses, being the most direct indicator of the breeding season. Killer whale Orcinus orca: gestation of 515 +_7 days (n = 7) in captivity [9], mean of the four neonates from the N Pacific (231-241 cm) and three from the N Atlantic (206-238 cm) [19], and an assumption of to = 0.09tg provide the fetal growth rate. The breeding seasonality is given in Olesiuk et al.

[201. 10.

White whale Delphinapterus leucas: if a linear fetal growth is applied to the fetal lengths in Burns and Seaman [21], the extended fetal growth will cut the axis of time on 1-31 July and reach the mean neonatal length on 1-31 August, which gives a range of t~-to of 242-304 days and fetal growth rate 0.51-0.64 cm/day. If to = 0.135t~ is assumed, 9-12 months is calculated as the time from the start of conception to the mean neonatal length of 155 cm. This period will be followed by a period of body weight increase of variable duration [21 ].

483 11.

12.

13. 14.

15.

Sperm whale Physeter catodon: neonatal length and fetal growth rate are from Fraser and Huggett [1,2], which are within the range of Best et al. [22]. Breeding seasonality is given in Ohsumi [23]. Blue and fin whales Balaenoptera musculus and B. physalus: fetal growth rate is given in Fraser and Huggett [1,2], and reproductive seasonality in Mackintosh and Wheeler [24]. Sei whale B. borealis: the fetal growth rate is given in Fraser and Huggett [ 1,2] and breeding seasonality in Matthews [25]. Bryde's whale B. edeni: fetal growth rate is not available. Reproduction is aseasonal in the Indian Ocean [26] and off South Africa [27] in latitudes 1035~ or weakly seasonal in the South Pacific (10-30~ and North Pacific (20--43~ [26,28]. Minke whale B. acutorostrata: fetal growth rate is given in Fraser and Huggett [1,2]. Breeding seasonality of two populations in the WN Pacific is given in [29-31 ], and that of Antarctic minke whales in [32].

Age composition and age dependent change in reproduction

o

,

,

,

6.

Dall's porpoise: from the Aleutian Islands and Bering Sea stocks in JulyAugust, 1978 and 1980 [8], or during calving and early conception seasons. Thus pregnant females with near term fetuses and females in lactation, which lasts less than 1 year, are combined to obtain the annual pregnancy rate. Striped dolphin: from eight drives off Japan in November-December, 19711977 [33]. Short-finned pilot whale: from the 21 drives of southern form stock off Japan in 1975-1984 [ 17]. Sperm whale: female reproductive status by age is from South Africa in 196567 [22], and age compositions from the Japanese coastal whaling in 1960-1965 nearly randomly sampled by biologists [34]. Baird's beaked whale: from the catch of whaling off Japan in 1975-1987 [35]. Fin whale: data are from Japanese Antarctic whaling in two seasons of 1968/1969 and 1969/1970 in possession of the National Institute of Research on Far Seas Fisheries, Japan.

Seasonality of Calving Mating season and gestation time of mammals have probably evolved to place parturition in such a season that may maximize the survival of the offspring [36]. However, timing of breeding also changes according to the annual change in food availability and climate, and mammal stocks transplanted across the equator can adjust their reproduction to local climate (Fig. 1). The breeding season may also respond to density changes [ 11 ]. Thus the difference in breeding season cannot always

484

Table 1. Fetal growth rate at linear pact of the growth (mmlday) and reproductive seasonality

Species and stocks

P. p h o c o e ~ N. phocaenoides P. dalli C. commersonii S. attenuata S. longirostris S. I. orientalis T. truncarus G. macrorhynchus

G. melas 0. orca D. leucas Physeter catodon 3. m. musculus B. m. brevicauda 3. physalus B. borealis B. edeni

B. acutorostrata M. novaeangliae

Gestation

Baltic Sea Inland S./Pacific Off W. Kyushu OkhotsklPacific Bering/Aleutian S . America N. offshore S. offshore N . whitebelly Inshore Offshore W.NA and W.NP Southern Japan Northern Japan Faroe Is. NP and NA W . Greenland Whole Arctic N . Pacific Antarctic Indian Ocean Antarctic Antarctic Ind. 0.1s. Africa N. and S. Pacific NP/Okhotsk YSlSJlOkhot~k Antarctic Antarctic

Months

Method

10.8 c11.0 11.4

Regression Direct

-

11.3 -

-

-

12.2 14.9

-

11.8 16.9 10.8 9-1 2 15.5 9.5? 11.2 L2.0 -

12.0 -

12.0

-

Regression Direct -

82 Direct Regression -

Model fit Direct Regression Regression Regression Regression Regression Regression -

Regression Regression

Neonatal length (cm) 75 78 -

100 c100 82 77 77 77 117-128 140 c185 177 219-235 155 155 395 700 640

450 270 456

Fetal growth rate 2.81 2.70 3.33 -

3.35 3-5 (1 1-12) -

-

3.74.0 3.40 6.65 4.7-5.0 5.1-6.4 9.01 27.1

-

19.9 17.0 -

10.0 -

17.0

Birth month peak and range

Conception peak and range

617 (6-7) 4 (3-8) 11/12 (8-4) 819 (8-9) 718 (6-10)

718 (7-8) 5 (6-9) l2/ l (9-5) 9 (7-9) 8 (6-9)

Vaguely bimodal 24,8-9 5-8 (2-10) 2-4 (1-12) 6 718 1-2 4-6 (3-10) 1Crl2 (6-5) 3-5 6/7 ( 4 7 + ) 819 (3-2) 5 (4-6) c6, 12 5 (4-9) 7 (1-11) Aseasonal Vaguely seasonal 12 (9-2) 516 (3-8) 718 (1-12) 7-10

-

-

(1-10) 6 (1-10) (2-1) 5 (11-10) 10-1 1 5-7 (4-1 1)

-

5 2-4 4 (10-9) 617 ( 6 9 ) 617 (5-10) 7 (1-1 1) 3/4(14) 10 (7-1) 819 (6-1) 8-1 1

485 I

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W.N. Pac.

J

D

Fig. 1. Parturition season (line) and its peak months (box) of cetaceans in equatorial and northern waters (roughly in the order of latitude). Determination of the peak season is arbitrary and may not be strictly comparable between stocks.

be evidence of genetic differentiation, although it may suggest at least some degree of genetic isolation. Baleen whales

With the exception of a few species, e.g. Bryde's and bowhead whales, many baleen whales make long distance seasonal migration. They accumulate nutrition in their body during the feeding season in higher latitudes and consume it in the breeding season in lower latitudes [37]. Baleen whales wean the calves during the feeding season following parturition even though some calves may accompany their mothers for nearly 12 months [37,38]. Thus parturition followed by the feeding season offers a good opportunity for calves to switch their nutrition from milk to solid food. Under

486 such an annual cycle, selection could have favored larger body size because it was beneficial for storage of nutrition for reproduction during starvation [39]. The breeding season of normal blue whales that migrate to 60-75~ lasts only 34 months. Using fetal length frequencies in February-March, bimodal breeding has been suggested for pygmy blue whales (B. m. brevicauda) migrating to 40-55~ [40]. The smaller mode (<50 cm) is composed of six fetuses, and the larger one 260 fetuses of 175-650 cm. Near-term fetuses might be under-represented in the sample due to earlier southward migration of females with such a fetus. The length range of the larger mode corresponds to an 8 month period and the gap between the two modes is 1.5 months (assuming fetal growth of 2.71 cm/day). Thus, if there are two breeding peaks, the smaller one can last only for 2.5 months or less. It is questionable if this represents an independent breeding peak; rather, the smaller fetuses will be interpreted as fore-runners of the single conception season lasting for 1011 months, which is usual for species in lower latitudes. Bryde's whales remain in warm waters between latitudes of 40 ~ and several local populations may occur within an ocean basin [26,41]. It is unknown if they have achieved augmentation through a seasonal long distance migration in the past or whether they have achieved it in the current habitat. Their fetal growth rate, if estimated, may offer an answer to this question (see below). The Bering-Chukchi-Beaufort Sea population of bowhead whales feed mostly during the 4 months of June-October [42] and calves are born mostly during April to early June, although a few may be born in March or as late as August [38]. Thus, they remain in close association with ice in all seasons and their life is under strong constraints of the seasonal cycle of food availability. Two minke whale populations in the western N Pacific have different breeding seasons [29], i.e. a stock migrating between the western N Pacific and Okhotsk Sea has a single calving peak in December, while another inhabiting the Yellow Sea, Sea of Japan and Okhotsk Sea calves in May/July. A similar explanation as for bowhead whales (i.e. calving prior to feeding season) may explain the latter, but it does not explain why the former stock does not use the strategy. Toothed whales

In contrast with most baleen whales, individual toothed whales tend to restrict their habitat to a limited oceanographic environment bounded by gyre or front, e.g. female sperm whales [43], Dali's porpoises [44] and short-finless pilot whales [45] off Japan. Additional environmental factors affecting their distribution include depth of water or thermocline [12,13,46]. These could have contributed to the formation of local populations within a species. Male sperm whales, the only known exception to the above generalization, migrate across ocean fronts. This allows them to utilize food resources in the higher latitudes and avoid competition with nursing schools for food. Toothed whales in higher latitudes tend to calve in summer or spring and in a short parturition peak, which are similar to migratory baleen whales. The cows and

487 calves benefit in the breeding season as assumed for baleen whales. The short breeding season is a reflection of the limitation of time suitable for calving. Delphinids in the tropical waters calve in general during any months of the year, but timing and length of the peak season may vary between populations. If "southern" and "northern" populations of offshore spotted dolphins in the eastern tropical Pacific [11 ] are compared, the former has a distinct calving peak in MarchMay, while the latter has two indistinct peaks centered in April and October. The latter population shares a geographical habitat with both the "offshore population" of eastern spinner dolphins and the "northem population" of whitebelly spinner dolphins, but breeding peaks of these three populations are only partially synchronized. Further studies on their life history and response to the environment are required for the understanding of their reproductive seasonality. More puzzling is the difference in breeding season between nearby pair populations of a temperate species where seasonal constraints may be more rigid. Each pair of the populations of finless porpoises [6] and short-finned pilot whales [17] in Japanese waters calve in different seasons which are several months apart. The direct benefit from such seasonality is unknown, but speculation is made that calves of the northem form short-finned pilot whales born in winter will find benefit in switching their major source of nutrition from milk to solid food during the summer season when food availability is high [ 17].

Fetal Growth Rate and Gestation Time

General patterns

Precise gestation periods of cetaceans are known only for a few species in captivity, where pregnancy has been determined by progesterone analysis [9]. For other species it is usually estimated from the seasonal change in fetal body lengths. Such methods may not result in reliable estimates if data cover only short periods which include breeding and/or calving seasons, e.g. striped dolphins [47] and long-finned pilot whales [48]. Even when the data cover most of the year, such methods may under-estimate the growth rate if the breeding season is long compared with the gestation time, e.g. long-finned pilot whales where the magnitude of the bias is about 10%, but the bias may be decreased using analytical techniques suitable for each data set [ 18]. The fetal growth rate referred to in this study is the rate for the linear phase of fetal growth [49]. The length of the earlier curvilinear phase is approximated, although under-estimated, by the time from conception to the time when the extended linear growth line cut the time axis (to). The proportion of to in tg decreases with increasing tg. This rule can apply to fetal growth expressed by body length or the cube root of the weight with slight modification in to [50]. This fetal growth model is used here for both baleen and toothed whales. Although controversy exists on this assumption [ 1,37,50], the effect on the present study will be minimal.

488 1

5

10

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20

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SF

7

0

I

I

1

2

i

I

3 Neonatal

4 length

I

I

I

5

6

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(m)

Fig. 2. Linear fetal growth rate plotted on mean neonatal length of baleen (open circle) and toothed (closed circles and stars) whales. Stars represent gestation time confirmed in captivity. Solid lines are drawn by eye for these points and dotted line is for 12 months gestation (to = 0.135tg assumed). Scale at the top indicates maximum body length of adult (Y, m) predicted from the mean neonatal length (X, m) using the equation Y = ( X - 0.443)/0.2441 [51 ]. Species keys: BD, bottlenose dolphin; BW, blue whale; CD, Commerson's dolphin; DP, Dali's porpoise; FP, finless porpoise; FW, fin whale; HP, harbor porpoise; HW, humpback whale; KW, killer whale; LF, long-finned pilot whale; MW, Minke whale; SF, short-finned pilot whale; SP, sperm whale; SW, sei whale; WW, white whale.

Plots of fetal growth rate on neonatal body length, which reflect adult body size [51,52], places cetacean species in two groups (Fig. 2). One group is composed of baleen whales and toothed whales of small or medium body size, where fetal growth rate increases accompanied by that of neonatal length in such a way that gestation time is retained at about 1 year or less. Another group is composed of a few toothed whale species of medium or large body size and longer gestation time of 1517 months, and the increase in fetal growth rate is so small that larger species have longer gestation time. The two lines meet at the vicinity of the lower left comer, where small cetaceans such as harbor porpoise and Commerson's dolphins are located.

Factors that influence fetal growth rate Cetacean species having gestation of 1 year or less and neonatal length of 0.7-1 m

489 represent at least two families of toothed whales and presumably other species such as Franciscana Pontoporia blainvillei and Ganges susu Platanista gengetica [53]. They inhabit from tropical to subarctic waters, and coastal to offshore waters. This suggests that such fetal growth is widespread among extant cetaceans and among ancestral cetaceans. Future interpretation of growth layers in tooth enamel will allow estimation of gestation time of extinct cetaceans. Precocious neonates were required for the aquatic life of cetaceans and thus selection probably favored greater neonatal size. Fetal growth rate of about 1 year and neonatal size of less than 1 m seem to be an interim compromise achieved by ancestral cetaceans under the annual seasonal cycle and nutritional/physiological limitation. Selection for greater body size further continued in various taxa of cetaceans. The baleen whales, which were placed under the combination of rigorous selection for greater body size (see above) and seasonal life cycle, achieved the augmentation through a rapid increase in fetal growth rate to retain gestation time at about 1 year. Failure of such fast fetal growth meant that they had to have a gestation between 1 and 2 years, as in some toothed whales living in warm waters, before achieving a gestation time of integer years (e.g. 2 years). Mean calving intervals of extant baleen whales are usually over 2 years [37], and the individual variation is wide with the commonest cycle of 2-4 years in humpback, gray and right whales [54-58]. Thus, if a 2-year gestation is once achieved, it may not be a great disadvantage for baleen whales provided that parturitions are followed by post-partum ovulations and subsequent conception. However, the intermediate gestation time is certainly a disadvantage for species living in a rigid seasonal pattern of food availability [37]. This is assumed also for earlier baleen whales. The seasonal constraint has not been so rigid for some toothed whales such as short-finned pilot whales and sperm whales, which probably evolved in tropical waters and conception and successful calving were possible at most times of the year. Thus they achieved augmentation accompanied by a slower increase of fetal growth rate and extension of gestation time. One of the causal factors of the augmentation was probably the polygynous social system. Although this sexual selection works primarily on males, it can affect also female body size because body size will be controlled by several genetic loci which include those located on autosomes. Feeding in only a limited season and breeding during starvation, as in baleen whales, could have also favored large body size of male sperm whales. The gestation time of long-finned pilot whales is only 80% of that of short-finned pilot whales. Such a difference may be uncommon among mammalian species within a genus, although we find greater diversity in Cephalophus (Bovidae, Artiodactyla) containing species of variable body sizes, where gestation ranged from about 120 days (C. Maxwelli, C. niger and C. ogilbi) to 222-245 days (C. dorsalis and C. rulilatus) with an intermediate figure of 196-220 days (C. monticola) [59]. One possible interpretation for the observed gestation time of the long-finned pilot whale is as follows. Long-finned pilot whales accumulate body fat during summer to mid-winter and consume it during winter to early summer to compensate for low prey availability

490 and energy demand for reproduction [60], which seems to be quite different from toothed whales in the tropical environment. This feature is similar to baleen whales, and gives a reason why they had to achieve fast fetal growth to retain gestation of 1 year during the augmentation. White whales are also under similar seasonal constraints, and have apparently achieved additional adaptation to an unpredictable environment. Their birth season is short in any one region but varies by regions correlating with breakup of ice [61 ]. Their fetal growth in all the Arctic regions is similar and fetuses continue growing only in weight after they reach the average neonatal length of 155 cm in April [21]. This means that they first achieved augmentation while retaining gestation of about 1 year, and then they acquired an ability to wait the arrival of an environment suitable for parturition. The body weight increment during the waiting time benefits the survival of neonates, while the nutritional requirement of the cow may be smaller than during lactation. Testes of white whales are in retrogression phase in April and May when most females have a corpus luteum and very few individual small embryos, which suggests delayed implantation [21 ]. This is the first case of such phenomena among cetaceans supported by some evidence, and further information is desired. A similar case proposed for Dali's porpoises [8] was not supported by accompanying testicular activity data.

Reproductive Longevity and Social Structure In baleen whales stable and long association of individuals is limited to cow/calf pairs, which can be maintained during lactation of a few months or extended at most close to 1 year including the postlactum period [37], and their social structure appears to be less developed. Their longevity extends 60-80 years after sexual maturity in both sexes and females are capable of breeding for life, suggesting a maximum capability of production of over 20 calves. This high production is to compensate a high juvenile mortality which is expected from the short parental investment. A similar strategy is found in Phocoenidae, which are characterized by small school size, fluid association between adults, parental care lasting only for a few months and breeding interval of 1 or 2 years [62,63,74]. Although their absolute length of maximum lifetime is shorter than that of baleen whales, the shorter calving interval suggests high lifetime production. A second type of social structure is seen in typical delphinids, e.g. bottlenose dolphins [64], striped dolphins [65] and spotted dolphins [66]. Their school size is greater than in the above species, individuals are more cohesive but move between schools of the same community in accordance with growth stages and reproductive status, and duration of maternal care is longer. In the striped and spotted dolphins, the average lactation period lasts for 1.5-2 years, and most of the calves, particularly males, leave their natal schools at ages 2-5 years to live in a school of immature individuals until puberty at around 10 years. The cow/calf association of bottlenose

491

Fin whale (n=940)

80

! 7 Laot.+Rest. Preg.

z,O

O3

80

=

40

~

o 20

e._

Sperm whale (n=725) l--IRest. ~)~Laot. ~Preg. Short-fin. p. whale (n=350)

0

~- 0 m 40 Z

20

40

o

Dal I's porpoise (n=266) E~Rest. ~Preg.

o

3'0

Age (year)

20

,~o

6'0

Fig. 3. Reproductive status o f sexually mature females.

dolphins lasts for 3-8 years or longer. Maximum longevities are 40-60 years and the sexual difference is insignificant. Pregnancy rate may decrease only slightly with increasing age in striped dolphins (50-30% [33]) and bottlenose dolphins [ 14]. The third type is represented by the matrilineal and polygynous social structure of some large and medium sized toothed whales, e.g. killer whales [20,67], sperm whales [22], short-finned pilot whales [16,17], long-finned pilot whales [18] and perhaps false killer whales [68,69]. A feature common to these species is the probable lifetime association between mother and her female calves, and the shift of maternal investment from calf bearing to calf rearing with increasing age of the cow [69]. The pregnancy rate declines with increasing age and conception ceases 1827 years before the age of maximum longevity. Females of the short-finned pilot whale cease ovulating soon after the last conception but remain receptive during post-reproductive lifetime, which may contribute to the stability of the school [70]. Females of the sperm whale and probably long-finned pilot whales continue ovulating after the reproductive senescence and are believed to be receptive at least during the peri-ovulatory period, which will function as the non-reproductive matings of short-finned pilot whales. The role of males is variable between these species. They may leave their natal school at puberty to segregate from nursing schools (sperm whales [22]) or to join other nursing schools (presumed from the school composition for short-finned pilot

492

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80

Fig. 4. Catch composition of cetaceans expressed as percentage of the total sample.

whales [16]), or they remain in their natal school for life but mate with females of other schools when they occasionally meet (killer whales [20,67] and long-finned pilot whales [71 ]). Thus nursing schools of the latter three species contain both sexes of all age classes, while those of sperm whales may be visited by males occasionally during the mating season [72]. These males attain sexual maturity 8-15 years later than females, and often live 6-17 years shorter. Sperm whales are the only exception, where both sexes have similar longevity. This has been achieved in association with feeding segregation between sexes and with males possibly not breeding every season. The fourth type is known by Baird's beaked whales, Berardius bairdii, which grow close to the size of female sperm whales (11-12 m) but do not exhibit sexual dimorphism [35]. Males are histologically mature 4 years earlier than females (610 years versus 10-14 years) and live 30 years longer, although the male age at first reproduction is unknown. Sex ratio is even before age 10 years, but mature males are over twice as abundant as the mature females in the population due mainly to the longevity difference. Females are probably reproductive throughout life with a high annual ovulation rate of about 0.47/year and apparent pregnancy rate of about 30%. Tooth marks from contacts with conspecifics are equally common in both sexes, suggesting no inter-male competition for a mate. Kasuya and Brownell [73] speculated a patrilineal school structure and male investment in rearing weaned calves, e.g.

493 guiding calves for feeding in great depths of 1000-3000 m or protecting calves from predators, which would decrease the female burden in rearing calves and thus enable them to calve in a short interval and the kin selection could result in great longevity of males. Females may move between schools at puberty as in chimpanzees [73], or remain with the kin of both sexes in a school as observed among species of the 3rd group. Such social structures can be derived from the 2nd type of social structure.

Discussion

Augmentation in cetacean body size occurred in several taxa in association with various factors such as polygyny, seasonal starvation, and needs for precocious calves. Stable and abundant food supply was possibly an additional requirement for such traits to evolve. Baleen whales successfully utilized crustaceans and schooling fish which are often abundant seasonally, pilot whales and beaked whales used squid resources, and killer whales and false killer whales used locally abundant resources of marine mammals or large fish. Among extant toothed whales the degree of polygyny and matrilineal social structure apparently correlate, and the latter also correlates with maternal investment in calf rearing. The last two can easily co-evolve through cooperation of females in rearing calves in a school. Association between females probably started from a preference of particular calving area as observed among beluga [21 ] and Dali's porpoises [74], and evolved to some degree of cooperation in calf rearing as observed in bottlenose dolphins and striped dolphins where females with calves tend to aggregate in schools [64,65]. This could have been followed by extension of the period of maternal care, and finally by the formation of a matrilineal school structure. Among killer whales and probably long-finned pilot whales, males evolved to remain with the matrilineal kin after sexual maturity. The presence of mature males in these schools may contribute to the survival of their kin (this will apply also to Baird's beaked whales and short-finned pilot whales). Males of sperm and perhaps short-finned pilot whales leave their natal school at puberty. It will not be an easy task for a male to herd females that are not associated with each other, additionally the presence of males is not required to retain association between females (e.g. sperm whales [22] and bottlenose dolphine [64]). These suggest that such male behavior has evolved as an adaptation to the presence of cohesive female association. Kasuya et al. [70] have proposed that the extended receptivity of females decreases inter-male competition for mates and offers unrelated males an important background of the apparent coexistence in a nursing school. Other direct explanations for the behaviour of these males will include two alternative questions, i.e. if cooperation is for their current mutual benefit, or inferior males live with the alpha male for future benefit (e.g. acquaintance with nursing females will increase his future chance of becoming alpha male). If spermatozoa in the female uteri are identified to individual males, key information on these questions will be available.

494

Acknowledgements I am grateful Dr. R.L. Brownell for references and to Ms M. Ikeya for data analyses and drawings.

References 1. Fraser JFD, Huggett AStG. Specific fetal growth rate of cetaceans. J Zool London 1973; 169:111126.

2. Fraser JFD, Huggett AStG. Species variations in the foetal growth rates of eutherian mammals. J Zool London 1974;174:481-509. 3. Mohl-Hansen. Investigation on reproduction and growth of the porpoise from the Baltic. Vidensk Medd fra Dansk naturh Foren Bd 1954;116:24-396+2plates. 4. Furuta M, Tsukada O, Kataoka T. On the birth of finless porpoise Neophocaena phocaenoides in captivity. In: Report of the Rearing and Behavior of Finless Porpoise (Neophocaena phocaenoides) in the Toba Aquarium. Toba: Toba Aquarium, 1977;1-12 (in Japanese). 5. Perrin WF, Coe JM, Zweifel JR. Growth and reproduction of the spotted porpoise, Stenella attenuata, in the offshore eastern tropical Pacific. Fish Bull 1976;74:229-269. 6. Shirakihara M, Takemura A, Shirakihara K. Age, growth and reproduction of the finless porpoise, Neophocaena phocaenoides, in the coastal waters of western Kyushu, Japan. Mar Mammal Sci 1993 ;9:392-406. 7. Kasuya, T. The life history of Dali's porpoise with special reference to the stock off the Pacific coast of Japan. Sci Rep Whales Res Inst 1978;30:1--63. 8. Newby T. Life history of Dali's porpoise (Phocoenoides dalli, True 1885) incidentally taken by the Japanese high seas salmon mothership fishery in the northwestern North Pacific and western Bering Sea, 1978 and 1980. Doctoral thesis, University of Washington, 1982 (unpublished). 9. Asper ED, Andrews BF, Antrim JE, Young WG. Establishing and maintaining successful breeding programs for whales and dolphins in a zoological environment. IBI Reports (Kamogawa, Japan) 1992;3:71-84. 10. Lockyer C, Goodall RNP, Galeazzi AR. Age and body length characteristics of Cephalorhynchus commersonii from incidentally-caught specimens off Tierra del Fuego. Rep Int Whal Commn 1988;(Special Issue 9):103-118. 11. Barlow J. Reproductive seasonality in pelagic dolphins (Stenella spp.): implication for measuring rates. Rep Int Whal Commn 1984;(Special Issue 6):191-198. 12. Perrin WF, Akin PA, Kashiwada JV. Geographic variation in external morphology of the spinner dolphin Stenella longirostris in the eastern Pacific and implications for the conservation. Fish Bull 1991;89:411-428. 13. Perrin WF, Schnell GD, Hough DJ, Gilpatrick Jr JW, Kashiwada JV. Reexamination of geographic variation in cranial morphology of the pantropical spotted dolphin, Stenella attenuata, in the eastern Pacific. Fish Bull 1994;92:324-346. 14. Kasuya T. Life history of bottlenose dolphins in the Japanese coastal waters. 1995 (unpublished). 15. Hohn A. Age determination and age related factors in the teeth of western North Atlantic bottlenose dolphins. Sci Rep Whales Res Inst 1980;32:39-66. 16. Kasuya T, Marsh H. Life history and reproductive biology of the short-finned pilot whale, Globicephala macrorhynchus, off the Pacific coast of Japan. Rep Int Whal Commn 1984;(Special Issue 6):259-310. 17. Kasuya T, Tai S. Life history of short-finned pilot whale stocks off Japan and a description of the fishery. Rep Int Whal Commn 1993;(Special Issue 14):425-473.

495 18. Martin T, Rothery P. Reproductive parameters of female long-finned pilot whale (Globicephala melas) around the Faroe Islands. Rep Int Whal Commn 1993;(Special Issue 14):263-304. 19. Duffield DA, Miller KW. Demographic feature of killer whales in oceanaria in the United States and Canada. Rit Fisk 1988;11:297-306. 20. Olesiuk PK, Bigg MA, Ellis GM. Life history and population dynamics of resident killer whales (Orcinus orca) in the coastal waters of British Columbia and Washington State. Rep Int Whal Commn 1990;Special Issue 12:209-243. 21. Burns JJ, Seaman GA. Investigation of belukha whales in coastal waters of western and northern Alaska. II. Biology and ecology. Fairbanks: Alaska Department of Fish and Game, 1985. 22. Best PB, Canham PAS, Macleod N. Patterns of reproduction in sperm whales, Physeter macrocephalus. Rep Int Whal Commn 1984;Special Issue 6:51-79. 23. Ohsumi S. Reproduction of the sperm whale in the north-west Pacific. Sci Rep Whales Res Inst 1965;19:1-35. 24. Mackintosh NA, Wheeler JFG. Southern blue and fin whales. Discovery Rep 1929;1:257-540. 25. Matthews LH. The sei whale, Balaenoptera borealis. Discovery Rep 1938;17:183-290. 26. Ohsumi, S. Population study of the Bryde's whale in the southern hemisphere under scientific permit in the three season 1976/77-1978/79. Rep Int Whal Commn 1980;30:319-331. 27. Best PB. Further information on Bryde's whale (Balaenoptera edeni Anderson) from Saldanha Bay, South Africa. Nor Hvalfangst-Tid 1960;49:201-215. 28. Ohsumi S. Bryde's whales in the pelagic whaling ground of the North Pacific. Rep Int Whal Commn 1977;(Special issue 1):140-149. 29. Best PB, Kato H. Possible evidence from foetal length distributions of the mixing of different compositions of the Yellow Sea-East China Sea-Sea of Japan-Okhotsk Sea Minke whale population(s). Rep Int Whal Commn 1992;42:166. 30. Omura H, Sakiura H. Studies on the little piked whale from the coast of Japan. Sci Rep Whales Res Inst 1956;11:1-17. 31. Wang, P. Studies of the breeding habit of the minke whale (Balaenoptera acutorostrata) in the Huaughai Sea. Oceanol Limnol Sin 1982;13:339-345. (in Chinese with English summary). 32. Kato H, Miyashita T. Migration strategy of southern minke whales in relation to reproductive cycle estimated from foetal lengths. Rep Int Whal Commn 1991 ;41:363-369. 33. Kasuya T. Effect of exploitation on reproductive parameters of the spotted and striped dolphins off the Pacific coast of Japan. Sci Rep Whales Res Inst 1985;36:107-138. 34. Whales Research Institute. Report of the investigation of whale stocks in the North Pacific. Tokyo: Whales Res Inst, 1961-1967 (in Japanese). 35. Kasuya T, Brownell RL, Balcomb KC. Preliminary analysis of life history of Baird's beaked whales off the Pacific coast of central Japan. 1988;IWC/SC/40/SM7, 22pp. 36. Kiltie RA. Seasonality, gestation time, and large mammal extinctions. In: Martin PS, Klein RG (eds) Quaternary Extinctions. Tucson: University of Arizona Press, 1984;299-314. 37. Lockyer C. Review of baleen whale (Mysticeti) reproduction and implication for management. Rep Int Whal Commn 1984;(Special Issue 6):27-50. 38. Koski WR, Davis RA, Miller GW, Withrow DE. Reproduction. In: Burns JJ, Montague JJ, Cowles CJ (eds) The Bowhead Whale. Soc Mar Mammal 1993;239-274. 39. Norris KS. Aggressive behavior in cetacea. In: Clemente CD, Lindsley DB (eds) Aggression and Defence: Natural Mechanism and Social Patterns, Brain Function, vol 5. Berkeley: University of California Press, 1967;225-241. 40. Ichihara T. The pygmy blue whale, Balaenoptera musculus brevicauda, a new subspecies from the Antarctic. In: Norris KS (ed) Whales, Dolphins and Porpoises. Berkeley and Los Angeles: University of California Press, 1966;79-111. 41. Best PB. Two allopatric forms of Bryde's whales off South Africa. Rep Int Whal Commn 1977;(Special Issue 1):116-121.

496 42. Lowry LF. Food and feeding ecology. In: Burns JJ, Montague JJ, Cowles CJ (eds) The Bowhead Whale. Soc Mar Mammal 1993;201-238. 43. Kasuya T, Miyashita T. Distribution of sperm whale stocks in the North Pacific. Sci Rep Whales Res Inst 1984;39:31-75. 44. Kasuya T, Ogi H. Segregation of mother-calf Dali's porpoise pairs as an indication of calving grounds and stock identity. Sci Rep Whales Res Inst 1987;38:125-140. 45. Kasuya T, Miyashita T, Kasamatsu F. Segregation of two forms of short-finned pilot whales off the Pacific coast of Japan. Sci Rep Whales Res Inst 1988;39:77-90. 46. Perrin WF. Patterns of geographical variation in small cetaceans. Acta Zool Fenn 1984;172:37140. 47. Kasuya, T. Growth and reproduction of Stenella caeruleoalba based on the age determination by means of dentinal growth layers. Sci Rep Whales Res Inst 1972;24:57-79. 48. Sergeant DE. The biology of the pilot or pothead whale Globicephala melaena (Traill) in Newfoundland waters. Bull Fish Res Bd Can 1962;132:i-vii+84pp. 49. Huggett WG, Widdas WF. The relationship between mammalian foetal weight and conception age. J Physiol London 1951;114:306-317. 50. Laws RM. The foetal growth rate of whales with special reference to the fin whale, Balaenoptera physalus Linn. Discovery Rep 1959;29:281-307. 51. Scott EOG. Neonatal length as a linear function of adult length. Pap Proc R Soc Tasmania 1949;1948:75-93. 52. Ohsumi S. Allomorphosis between body length at sexual maturity and body length at birth in cetacea. J Mammal Soc Jpn 1966;3:3-7. 53. Brownell Jr RL. Review of reproduction in platanistid dolphins. Rep Int Whal Commn 1984;(Special Issue 6):149-158. 54. Glockner-Ferrari DA, Ferrari ML. Reproduction in the humpback whale (Megaptera novaeangliae) in Hawaiian waters, 1975-1988: the life history, reproductive rates and behavior of known individuals identified through surface and underwater photography. Rep Int Whal Commn 1990;(Special Issue 12):161-169. 55. Clapham PJ, Mayo CA. Reproduction of humpback whales (Megaptera novaeangliae) observed in the Gulf of Maine. Rep Int Whal Commn 1990;(Special Issue 12):171-175. 56. Jones ML. The reproductive cycle in gray whales based on photographic resightings of females on the breeding grounds from 1977-82. Rep Int Whal Commn 1990;(Special Issue 12):177-182. 57. Hamilton PK, Mayo CA. Population characteristics of right whales (Eubalaena glacialis) observed in Cape Cod and Massachusetts Bays, 1978-1986. Rep Int Whal Commn 1990;(Special Issue 12):203-208. 58. Payne R, Rowntry V, Perkins JS. Population size, trend and reproductive parameters of right whale (Eubalaena australis) off Peninsula Valdes, Argentina. Rep Int Whal Commn 1990;(Special Issue 12):271-278. 59. Hayssen V, van Tienhoven A, van Tienhoven A. Asdell's Pattern of Mammalian Reproduction. Ithaca and London: Cornell University Press, 1993. 60. Lockyer C. Seasonal change in body fat condition of Northeast Atlantic pilot whales, and their biological significance. Rep Int Whal Commn 1993;(Special Issue 14):325-350. 61. Sergeant DE. Biology of white whales (Delpinapterus leucas) in western Hudson Bay. J Fish Res Bd Can 1973 ;30:1065-1090. 62. Gaskin DE, Smith GJD, Watson AP, Yasui WY, Yurick DB. Reproduction in the porpoise (Phocoenidae): implication for management. Rep Int Whal Commn 1984;(Special Issue 6):135148. 63. Kasuya T, Kureha K. The population of finless porpoise in the Inland Sea of Japan. Sci Rep Whales Res Inst 1979;31:1--44. 64. Shane SH, Wells RS, Wursig B. Ecology, behavior and social organization of the bottlenose dolphin: a review. Mar Mammal Sci 1986;2:34-63.

497 65. Miyazaki N, Nishiwaki M. School structure of the striped dolphin off the Pacific coast of Japan. Sci Rep Whales Res Inst 1978;30:65-115. 66. Kasuya T, Miyazaki N, Dawbin WF. Growth and reproduction of Stenella attenuata in the Pacific coast of Japan. Sci Rep Whales Res Inst 1974;26:157-226. 67. Bigg MA, Olesiuk PF, Ellis GM, Ford JKB, Balcomb KC. Social organization and genealogy of resident killer whales (Orcinus orca) in the coastal waters of British columbia and Washington State. Rep Int Whal Commn 1990;(Special Issue 12):383-405. 68. Kasuya T. Life history of false killer whales. In: Tamura T, Ohsumi S, Arai S (eds) Report of Investigation for the Solution of Dolphin-Fishery Conflict in the Iki Island Area. Tokyo: Japan Fish Agency, 1986;178-187 (in Japanese). 69. Marsh H, Kasuya T. Evidence for reproductive senescence in female cetaceans. Rep Int Whal Commn 1986;(Special Issue 8):57-74. 70. Kasuya T, Marsh H, Amino A. Non-reproductive mating in short-finned pilot whales. Rep Int Whal Commn 1993;(Special Issue 14):426--437. 71. Amos B, Bloch D, Desportes G, Majerus TMO, Bancroft DR, Barrett JA, Dover GA, A review of molecular evidence relating to social organization and breeding system in the long-finned pilot whale, off the Faroe Islands. Rep Int Whal Commn 1993;(Special Issue 14):209-217. 72. Whitehead H, Armbom T. Social organization of sperm whales off the Galapagos Islands, February-April 1985. Can J Zool 1987;65:913-914. 73. Kasuya T, Brownell Jr RL. Male parental investment in Baird's beaked whales, an interpretation of the age data. In: Abstracts of the Fifth int Theriol Congress 1989;523-524. 74. Kasuya T, Jones LL. Behavior and segregation of the Dali's porpoise in the northwestern North Pacific Ocean. Sci Rep Whales Res Inst 1984;35:107-128.

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9 1995 Elsevier Science B.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCe and 13. Ulltang, editors

499

Modelling the school structure of pilot whales in the Faroe Islands, 1832-1994 Dorete B l o c h 1 and L e n a Lastein 2 1Museumof Natural History, T6rshavn, Faroe Islands; and 2Fisheries Laboratory, T6rshavn, Faroe Islands Abstract. Background: catch data of the long-finned pilot whale (Globicephala melas) in the Faroe Islands have provided hunting statistics covering a long time period. Besides information of number of whales landed, the data also include biological information, such as their weight valuation in skinn (1 skinn = 72 kg). Methods: from 1709 to 1994, skinn values of 87,008 whales are available from 609 of 1,715 totally landed schools. Skinn and sex have been determined for 10,102 whales, sexual status for 3,020 whales. The attainment of sexual maturity is estimated at 9.4 skinn _ 0.01 (males; N = 629), and 5.4 skinn _ 0.00 (females; N = 1,127) and an average male proportion of 29% (females 71%) was found. These data were used to model the sex and maturity distribution through time. Results and conclusions: years with high number of schools were related with many whales, but connected with a low annual average whale size. In periods with a high number of whales and abundant food, the schools consisted mainly of immature whales and proportionally more males. Local differences appeared in the average annual whale size corresponding with the environmental rhythmic variations. A lower annual whale size was found in the southern district in periods with many whales. Finally, peak periods seem to appear at the same time all over the North Atlantic. Key words: long-time catch series, sex distribution, maturity distribution, annual average whalesize, school splitting

Introduction

The Faroese pilot whaling is a drive fishery where entire schools (sighted in the vicinity of the islands from land or from boat) are driven ashore by small fishing boats and dispatched on the beach [1]. Pilot whaling has always been a well organized social event, and taxes paid to the landowners, the church and to the king have caused the local sheriffs to write detailed reports from the whaling and send them to the govemment [2]. Pilot whaling statistics are available from 1584 (unbroken from 1709), when the Faroese local administration took over the journals of the land and landowners. Different studies have demonstrated that the abundance of marine prey species for the Faroe Islanders (seabird species, pilot and bottlenose whales, cod and herring) have changed through centuries according to the same oscillatory rhythm as the climate [3]. Studies of the long-finned pilot whale have shown that the sex ratio in landed schools was biased against males and significantly different for the periods 1870s and 1950-1980 [4,5], and that intermale fighting seems to be the most reason-

Address for correspondence: D. Bloch, Museum of Natural History, FR-100 T6rshavn, Faroe Islands; Tel: +298 18588; Fax: +298 18589; E-mail: [email protected].

500 able explanation for the biased sex ratio [6]. Moreover, it is known that a change in a biased sex-ratio influences female fecundity [7]. Long-term catch series containing some biological information may illustrate the influence of environmental oscillations on the biology of marine animals. The aim of this study is to test if the many details included in the 300 years pilot whaling statistics could inform about the influence of the environment on marine animals in Faroese waters. A more detailed edition of this paper has been published by Bloch and Lastein [8].

Materials and Methods

The pilot whaling statistics Today all reports on pilot whaling statistics are kept in the Faroese National Archive in T6rshavn and the biological details have been compiled on PC at the Zoological Department of the Faroese Museum of Natural History. The biological details in the official reports used for this study consist of: 1. name of the whaling bay; 2. date of the catch; 3. number of whales in each catch; 4. value of each whale, in skinn (see below); 5. total value of the whole school, in skinn; 6. distribution of the share, in skinn. From 1709 to 1994, the hunting statistics give information about 1,715 schools composed of 242,012 pilot whales, of which 238,946 whales comprise about 1,782,003.34 skinn in total (Table 1). In previous times, some whales drowned in the killing and later floated after the beached whales were distributed. These whales are the cause of the difference between the total number of whales and the number involved in the total number of skinn. Moreover, information also exists about some schools, but the evaluation is lacking in the sources remaining (Table 1). From 609 schools (1821-1994) information exists in the form of skinn values for each single pilot whale containing 87,008 whales and valued at 511,359.125 skinns, i.e. more than a third of all schools landed through nearly three centuries, where all the details of the hunting statistics exist today. From these 87,008 whales, the sex has been determined for 10,102, and the sexual status for 3,020 of them [9-11] is known, determined by a thorough examination of the testes or ovaries [ 12,13]. The valuation method in skinn According to pilot whaling regulations, every whale is assessed by using a simple regressive assessing rod, which converts the length of the edible part of the whale to weight, i.e. the part of the body from the eye to the anus, practically measured as a straight line from eye-to-anus parallel to the backbone. The value is an old Norse

501

Table 1. The Faroese pilot whaling statistics in the period 1584-1994 Period

Schools total

Whales total

Skinn (of whales)

1584-1994

1,758 1,715 453 1,254

247,330 242,012 55,372 183,574

1,782,003.34 (238,946) 1,782,003.34 (238,946) 647,047.75 1,134,955.59

1709-1994

1709-1831 1832-1994

one, named "skinn" (value, 1 skinn = 72 kg) [ 14]. For historical reasons, calculations only include the period 1932-1994 [8,15]. A thorough treatment of the skinn valuation and its biological value is made in B loch and Zachariassen [ 14].

The skinn value at sexual maturity The best estimate of the skinn value at the attainment of sexual maturity should be 9.4 _+0.01 skinn for males (N = 629) and 5.4 _+0.00 skinn for females (N = 1,127)

[8]. Results

Analysis of the primary catch data of pilot whales in the period 1832-1994 The number of skinn-measured pilot whales represents sufficiently the total number of landed whales for statistical analysis (Fig. l a) as performed by a variance analysis of the two time series (range 1-100%; average 56%; R = 0 . 6 4 4 ; F = 363.06; e < 0.001) [81. The annual average whale size (AWS) is the annual total amount of skinn divided with the annual total number of whales (Eskinn/Zwhales/year, Fig. l b), and it is 6.5 +_0.00 skinn, range 4.7-10.1 skinn per year. A high annual number of landed whales results in a high annual number of pilot whale schools (R = 0.82; P < 0.001), while Fig. 1a,b indicates that a high annual number of whales is connected with low annual AWS (R = 0.46; P < 0.001) [8].

Modelling the sex distribution of pilot whales in the period 1832-1994 The skinn measurements of 3,020 pilot whales sexed in 1986-1988 were used to analyse the sex distribution according to the skinn value. The dependency of sex to actual skinn value was estimated [8] for males to be 29% on average, range 23-64% (Fig. l c, grey area), and for females of 71%, range 35-76% (Fig. l c, black area). The model displayed the sex distribution and the estimated time series of sex distribution in percent show a very constant proportion of the sexes to time although a higher male percentage is observed in 1930-1970. The extreme peaks observed around 1875 and 1905 are properly caused by the low number of whales taken and thereby a corresponding small number of skinn-measured whales (Fig. 1a).

502

Modelling the sexed maturity distribution of pilot whales in the period 1832-1994 The data on the maturity of pilot whales were used to evaluate a model to estimate the maturity of whales of both sexes depending on the skinn value distribution [8] and used on the annual averaged skinn value in the period 1832-1994 (Fig. l b). In 4500

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503 the peak period in this century (1930-1970), where the male percent in the schools was high (Fig. l c), the main proportion of both sexes was composed of immature whales. In contrast, the valley period (1870-1930) with a lower male percentage (Fig. 1c) gave a lower number of immature whales (Fig. 1d,e).

Size of the largest and 5th largest whales in schools From the 609 skinn-measured schools, the largest whale of each school was picked out to see if not only the maturity distribution (Fig. 1d,e), but perhaps also the size of the largest whale in the school could explain the observed variations in the AWS (Fig. l b). The 5th largest whale was also picked out to be sure if any tendency was general. Sometimes single or few whales beach, and the smallest schools containing < 10 whales were therefore excluded. The largest whale in schools _>10 whales was on average 17.1 _.+0.18 skinn (range 6-30 skinn), and for the 5th largest whale 13.6_ 0.17 skinn (range 5-25 skinn). It was found that a small school had a significantly smaller largest and 5th largest whale than a larger school (N = 594 schools; largest whale R = 0.986; P < 0.001; 5th largest whale R = 0.984; P < 0.001). The annual average sizes of the largest and 5th largest whales in the schools varies for the largest whale from 10.3 skinn in 1969 to 26.0 in 1915 (8.0 in 1857 to 25.0 in 1920 for the 5th largest whales; Fig. 2) with a clear positive correlation between the largest and 5th largest whales (N = 601; R = 0.84; T = 37.29). A difference of 26.0-10.3 = 15.7 skinn (S) means a difference in weight (W) of 2 tons, when using the formula W = 130 x S for the weight-skinn correlation [14]. The variation in the size of largest whales in the schools fluctuates in the same way as the AWS (Figs. 1b and 2).

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Yoar Fig. 3. The annual AWS in the most northern district, Nor0r (o) and the most southern district, Suc3urr (O) of the Faroe Islands in the period 1832-1994. Full lines represent distance weighted least squares lines fitted to the data.

A WS in different districts in the Faroes in the period 1832-1994 The number of landed schools was sorted according to the different districts in the Faroes to examine if any differences were visible in the AWS. When comparing the districts, differences were visible. The most northern district, Nor6r and the most southern district, Su6urCy, seem to show the largest difference (Fig. 3) with the remaining placed between them. Both districts contain whaling bays of great importance through time and about the same amount of whales have been landed. After the data material was divided into two time periods (one before 1920 and the second after 1920), a T-test performed on the series showed that a significant difference ( T = 9.422, P < 0.001) in the AWS in the two districts Su6urCy and Nor6r could be determined for 1920-1994, while the difference in the AWS was not significant ( T = 2.704, P > 0.01) in 1830-1920, which possibly was caused by the low number of observations in this period.

Discussion and Conclusion Hard exploited whale populations show an increased fecundity by attainment of sexual maturity at an earlier age for the females as observed for spotted and striped dolphins of Japan, sperm whales in the North Pacific and fin whales off Iceland [ 1618]. Further, the male sperm whales in the North Pacific have increased their maximal length caused by better feeding possibilities after depletion of stocks [ 17]. The Faroese pilot whale examination showed that the long-finned pilot whales in the Northeastern Atlantic differed significantly from those in the Northwestern At-

505 lantic [19]. The two populations were proposed to live each in the two gyres of the North Atlantic and separated by the front made by the Mid-Atlantic Ridge in the Irminger Sea. If this is so, the main population for Faroese pilot whaling is distributed in the northeastern part of the North Atlantic and estimated at a size of 778,000 whales (CV =0.295) [20]. This means that the population is exploited with

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The material is sampled by the ICES study group

of

506 a percentage ranging from 0 to 0.6%, and an annual mean take of 0.1% under the condition that the population size on the whole is unchanged. The exploitation of the long-finned pilot whale in the Northeast Atlantic must therefore be considered as negligible for the population and the oscillations observed in the Faroese schools by (a) annual take of whales in the Faroe area, (b) annual AWS, (c) largest whales in the schools, and estimated for (d) the sex ratio over time, and finally, (e) the maturity distribution of the two sexes over time, must be caused by environmental conditions other than the hunting pressure. The peak periods in the number of pilot whales taken in the Faroes (Fig. 1a) occur at the same time as the peaks in abundance of the prey species [3,21 ]. In these peak periods the whales are observed to have a smaller AWS (Fig. l b), especially in the southern part of the Faroes (Fig. 3), a higher male percentage (Fig. lc) [5], and smaller size of the largest whales in the schools (Fig. 2). Moreover, in peak periods there are estimated a larger percentage of immature whales in the schools (Fig. 1d,e). The pilot whales feed mainly on mid-water species of gregarious and luminous squid and feed most commonly at depths between 100 and 500 m and the diet is different according to age, sex and reproductive classes [22]. A difference in composition and occurrence of the main prey species over time could therefore be one possible explanation of the small maximum pilot whale size in peak periods and in the fewer, but larger males in valley periods, which must be considered in future examinations. The smaller AWS observed in the southern part of the Faroes in peak periods (Fig. 3) may be explained by a greater part of immatures in the schools (Fig. l d,e). Differences in school composition can perhaps be explained by variations in the food availability and/or in the migrating pattern according to the current system in the area. Low AWS values are correlated with small school sizes, and this could also indicate the establishment of many smaller schools in peak periods by splitting of the larger schools observed in valley periods. A whale measuring >__14 skinn is a male [5,14], but it should be remarked that for some of the smaller schools in this material the largest whale, measured at 11 skinn, has been a female. This points perhaps to a way of establishing a new school out of an old one and opens the way for further studies of pilot whale statistics [23,24]. The number of catches as well as stranded schools from the whole North Atlantic north of Great Britain show the same occurrence of maximum and minimum numbers as the landed schools in the Faroes, despite the fact that some of the numbers are small (Fig. 4, compiled from Butterworth [25]). A future comparison with oceanographic and biological data may indicate if the long-time oscillations found in the abundance of pilot whales in the Faroese waters as well as the biological parameters in the schools are general for the North Atlantic as a whole.

Acknowledgement Thanks to P.H. Enckell for commenting on this paper.

507

References 1. Bloch D, Desportes G, HCydal K, Jean P. Pilot Whaling in the Faroe Islands. July 1986-July 1988. N Atlantic Stud 1990;2:36-44. 2. Debes HJ. FCroya SCga. T6rshavn: Nort)urlond og FCroyar, 1990. 3. Hr K, Lastein L. Analysis of Faroese catches of pilot whales (1709-1992), in relation to environmental variations. Rep Int Whal Commn 1993;(Special Issue 14):89-106. 4. MUller HC. Whale fishing in the Faroe Isles. Fish and Fisheries. Prize Essays of the Intern. Fisheries Exhibition, Edinburgh, 1882; 1-I 6. 5. Bloch D. Studies on the long-finned pilot whale in the Faroe Islands, 1976-86. Fr6c3skaparrit 1992 (1990);38-39:35-61. 6. Bloch D. Intermale competition in schools of long-finned pilot whales as indicated by abundance of fighting marks. In: Bloch D, Pilot Whales in the North Atlantic. Age, Growth and Social Structure in Faroese Grinds of the Long-Finned Pilot Whale, Globicephala melas. Ph D thesis, the University of Lund, Sweden. 1994;VII:1-16. 7. May RM, Beddington JR. The effect of adult sex ratio and density on the fecundity of sperm whales. Rep Int Whal Commn 1990;(Special Issue 2):213-217. 8. Bloch D, Lastein L. Modeling the school structure of the long-finned pilot whales on the Faroe Islands by use of long-time catch series. In: Bloch D, Pilot Whales in the North Atlantic. Age, Growth and Social Structure in Faroese Grinds of the Long-Finned Pilot Whale, Globicephala melas. Ph D thesis, the University of Lund, Sweden. 1994;VIII:1-21. 9. Bloch D, Desportes G, Mouritsen R, Skaaning S, Stefansson E. An introduction to studies of the ecology and status of the long-finned pilot whale (Globicephala melas) off the Faroe Islands, 1986-1988. Rep Int Whal Commn 1993;(Special Issue 14):1-32. 10. Donovan GP, Lockyer CH, Martin AR (eds). Biology of northern hemisphere pilot whales. Rep Int Whal Commn 1993;(Special Issue 14):1-479. 11. Desportes G, Bloch D, Andersen LW, Mouritsen R. The international research programme on the ecology and status of the long-finned pilot whale off the Faroe Islands: presentation, results and reference. Fr6c3skaparrit 1994 (1992); 40: 9-29. 12. Desportes G, Saboureau M, Lacroix A. Reproductive maturity and seasonality of male long-finned pilot whales, off the Faroe Islands. Rep. int. Whal. Commn 1993;(Special Issue 14):233-262. 13. Martin AR, Rothery P. Reproductive parameters of female long-finned pilot whales (Globicephala melas) around the Faroe Islands. Rep Int Whal Commn 1993;(Special Issue 14):263-304. 14. Bloch D, Zachariassen M. The "skinn" values of pilot whales in the Faroe Islands. An evaluation and a corrective proposal. N Atlantic Stud 1989;1:39-56. 15. Bloch D. Pilot whales in the North Atlantic. Age, growth and social structure in Faroese grinds of the long-finned pilot whale, Globicephala melas. Ph.D. thesis, the University of Lund, Sweden, 1994;1-203. 16. Kasuya T. Effect of exploitation on reproductive parameters of the spotted and striped dolphins off the Pacific coast of Japan. Sci Rep Whales Res Inst, Tokyo. 1985;36:107-138. 17. Kasuya T. Density dependent growth in North Pacific sperm whales. Mar Mammal Sci 1991 ;7:230-257. 18. Lockyer C, Sigurj6nsson J. Rep Int Whal Commn Special meeting on North Atlantic Fin Whales, Reykjavfk 25 February - 1 March 1991. Doc. SC/F9 l/F8, 1991; 1-36 (unpublished). 19. Bloch D, Lastein L. Morphometric segregation of long-finned pilot whales in eastern and western North Atlantic. Ophelia. 1993;38: 55-68. 20. Buckland ST, Bloch D, Cattanach KL, Gunnlaugsson T, HCydal K, Lens S, Sigurj6nsson J. Distribution and abundance of long-finned pilot whales in the North Atlantic, estimated from NASS1987 and NASS-89 data. Rep Int Whal Commn 1993;(Special Issue 14):33-49. 21. Zachariassen P. Pilot whale catches in the Faroe Islands, 1709-1992. Rep Int Whal Commn 1993;(Special Issue 14):69-88.

508 22. Desportes G, Mouritsen R. Preliminary results on the diet of long-finned pilot whales off the Faroe Islands. Rep Int Whal Commn 1993;(Special Issue 14):305-324. 23. Brault S, Smith T. Implications of cohesive pod structures for population studies of cetaceans. Presented to the ICES Study Group Meeting, Copenhagen, August-September 1993. WP-9 1993; 1-4 (unpublished). 24. Smith TD, Read A, Caswell H, Brault S, Barlow J. Puffing pigs and podheads in demographic cyberspace: measuring uncertainty in estimates of rate of increase. Presented to the ICES Study Group Meeting, Copenhagen, August-September 1993. WP- 10 1993; 1-5 (unpublished). 25. Butterworth D (ed). Study Group on Long-Finned Pilot Whales. Report of Meeting, Copenhagen, 30 August-3 September 1993. Int. Counc. Exp. Sea. C.M.1993/N:5. Ref.:A. 1-31.

9 1995 ElsevierScienceB.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand 0. Ulltang,editors

509

Harp seals as indicators of the Barents Sea ecosystem Yu. K. Timoshenko Northern Branch of Polar Research Institute of Marine Fisheries and Oceanography (Sev PINRO), Arkhangelsk, Russian Federation Abstract. In 1960-1994, harp seal (Pagophilus groenlandica) population ecology was studied in the White Sea. In the 1980s, substantial changes were revealed in the population ecology, affecting the distribution, migrations, age composition and breeding of the seals. In 1982-1989, unusual harp seal invasions were observed in the estuaries of the rivers flowing into the White Sea (Severnaja Dvina, Koida), movements of seals to the Murmansk coast in summer, and the presence of harp seals in summer and autumn in the White Sea. A sharp reduction in the abundance of younger animals on moulting grounds was also noted, which may indicate high mortality of animals during their first year of life. This trend also characterized the age composition of breeding females on breeding grounds. In the 1980s, harp seal females attained sexual maturity later than normal, and the rates of follicle maturation in ovaries slowed down. Pup weight also decreased. The changes in the ecology of the White Sea harp seal population occurred at a time of profound changes in the Barents Sea ecosystem in the 1980s under the influence of human economic activities. A sharp reduction in fish stocks, particularly polar cod (Boreogadus saida) and capelin (Mallotus villosus), resulted in deterioration of feeding conditions and subsequent changes in the population ecology. The results of the investigations point out the potential of using harp seals as specific indicators of the state of the ecosystem.

Key words: harp seal, distribution, age composition, sexual maturation

Introduction

Marine mammals are an important element of the White and Barents Seas ecosystem. Their significance is conditioned by their role and place in the ecosystem trophic chains. With this in mind, and also the commercial importance of marine mammals, investigations of their biology are being carried out. Great attention is paid to the White Sea population of harp seals ( P a g o p h i l u s g r o e n l a n d i c a ) - an important object of human hunting. More than 30 years of observations of the distribution, migrations, breeding, age-sex composition and other aspects of the harp seal biology have been conducted in the White Sea during the winter-spring periods. The investigations have yielded possibilities to detect changes in the population ecology in recent years. The results of these studies have rarely been reported and have previously been limited to publications on the distribution and migrations of harp seals in the White Sea in 1987 [ 1] and hunting influence on the age composition of breeding females [2].

Address for correspondence: Northern Branch of Polar Research Institute of Marine Fisheries and Oceanography (Sev PINRO), 17 Uritsky Street, 163002 Arkhangelsk, Russian Federation.

510 The harp seal habitat has also undergone substantial changes as a result of human economic activities. Stocks of many fish species (including species comprising the harp seal diet [3-5]) in the Barents Sea have sharply reduced. This paper, therefore, documents the scale of the White Sea harp seal ecology changes and shows how marine mammals can be potentially used as indicators of the ecosystem state.

Materials and Methods

The paper is based on material collected in the White and Barents Seas, mainly in March-May in 1960-1994 during harp seal hunting and but also during other seasons of the year. The harp seal distribution and migrations were studied using airplanes, helicopters, ships, visits to the coast, and direct questioning of local people. Flights were carried out using IL-14, AN-26, AN-30, L-410 planes and MI-8 helicopters. Observations were made by 2-3 observers on the left and right sides of the aircraft at an altitude of 150-300 m at a speed of 200-300 km/h. Age samples were usually collected during the hunt on breeding grounds in the first 10 days of March using helicopters. On moulting grounds, age samples were collected again during the hunt in the third 10 days of April, first 10 days of May from hunting and research ships, and in 1989-1991 (during hunting) from helicopters. Samples characterizing the age composition of breeding females on breeding grounds were collected mainly in the south of the White Sea Basin. On the moulting grounds, samples were collected in the White Sea Voronka, Gorlo and Basin. Neither the hunting nor the collection of material was selective. Therefore, there are reasons to believe that the samples represent the White Sea population. Age was determined by counting layers of dental tissue in the lower jaw canines [6]. Teeth sections 0.11-0.16 mm thick were made and examined under a transmission microscope. Colouring of the harp seal pelages was also taken into account according to an existing classification, as colouring is approximately related to the age of the animals [7]. In total, the ages of 7,106 females obtained on breeding grounds in 1969-1993 and 26,789 males and females obtained on moulting grounds in 1964-1994 are available. Furthermore, 23,819 animals obtained on moulting grounds were grouped according to colouring in 1960-1994. Reproductive organs of females (ovaries) were collected in the third 10 days of April to the first 10 days of May. They were fixed in 4% formalin solution. In the laboratory, ovaries were cut into thin slices and examined visually in order to discover the corpora lutea and follicles. The diameter of large follicles was measured with a ruler. Normally, the largest follicle of the harp seal ovulates, and this allows us to consider its size as a criterion of maturity. Follicles with diameters 10 mm or more were classified as mature based on the fact that corpora lutea ovulationes at early stages are usually of the same size.

511 Females reaching sexual maturity in the current season and breeding for the first time have corpus luteum ovulationis in their ovaries in April-May. Besides corpora lutea ovulationes, corpora lutea lactationes and corpora albicantia were also found at that time in ovaries of females breeding repeatedly. These formations are classified according to colour, thickness, composition and size. Corpora lutea ovulationes are a pale-flesh colour tinged with pink. Corpora lutea lactationes are dark yellow, thicker, and have connective tissue formations. Corpora albicantia are connective tissue infiltrations with luteal tissue remains. Females which have not reached sex maturity do not have these types of corpora lutea in their ovaries. This enables us to group the females into immature, first time breeding and multi-breeding females. The weight of pups was recorded mainly in the second 10 days of March after weaning when they were moulting.

Distribution and Migrations In the 1980s, some unusual peculiarities were revealed in the Barents Sea harp seal distribution and migrations (Fig. 1). During their stay in the White Sea, harp seals appeared in regions in which they usually do not occur. In December 1982, harp seals were observed in the estuary of the river Koida (the Mezen Bay). Their invasion in the river coincided with the mass approach of the gadoid fish navaga (Eleginus navaga). In late December 1982, harp seals were registered in the south of Dvinsky Bay and in the estuary of the river Severnaja Dvina where they penetrated through a channel in the ice made by ships. The animals lay on the ice in groups of 3-5 individuals. Totally, about 50 animals were counted there. Particularly significant deviations from the normal in the harp seal distribution and migrations were observed in the White Sea in 1987. In summer-autumn 1987, individual harp seals or groups of them were repeatedly registered in the coastal regions of Dvinsky Bay, Onega Bay, Kandalakhsha Bay, White Sea Gorlo and Voronka. The animals were very exhausted and behaved unusually in some cases; they did not show their usual caution and they sometimes came out on land. Moreover, the formation of breeding grounds in the White Sea in 1987 was delayed and the density of animals there was low. More information about this is given by Timoshenko [1]. Single animals were also registered in the White Sea Gorlo and Voronka in summerautumn 1988. On June 22, 1985, groups of harp seals consisting of 4-11 animals were discovered in the north-west of the White Sea Voronka and in the Lumbovsky Bay region and near the Cape Svjatoi Nos. Some peculiarities of the harp seal distribution and migrations were also noted in the Barents Sea. On June 22, 1985, groups of harp seals were registered near the Murmansk coast, not far from the estuaries of the rivers Voronja and Varzina. A total of 35 individuals was counted there. On June 24, 1985, 8 animals were observed to the north-west of the Cape Kanin Nos (south of 69~ and 10 animals were observed to the north of the Cape Svjatoi Nos. In March-April 1987, harp seals were registered in the Kolsky Bay, mainly in its northern part.

512 52*

34 ~

36* !

38* ,

40* ,

42*

44*

w

i

BARENTS SEA 69 ~

Q

68*

KOLA

67 ~

66 ~

WWITE S EA 65"

64 ~ I

I

I

I

l

I

.

I

Fig. 1. Localities in the White Sea and in the south of the Barents Sea where harp seals were registered in summer-autumn 1985, 1987 and 1988 ( 9 and winter 1982 (O).

In the 1980s, harp seals were also registered in the coastal regions of the southeastern part of the Barents Sea. For example, in January 1981, 3 adult males were caught (by net) near the entrance to Kolokolkova Bay at the fast ice edge. One of them had 34 navagas of length 18-26 cm in its stomach. The other had navaga otoliths. Single animals were also caught by net in subsequent years.

Age Composition A characteristic peculiarity distinguishing harp seals from other seal species is their change of colouring with respect to age. This can be used in an approximate differentiation of age categories of animals. Thus, results from studies of harp seal composition according to colouring on the White Sea moulting grounds are of some

513 Table 1. Composition of harp seals on moulting grounds in the White Sea according to colouring

Years

Total number of animals

Pelage types Middlings Number

1960 1961 1962 1963 1964 1970 1983 1984 1986 1987 1988 1989 1990 1991 1992 1994

869 2,058 2,307 847 1,508 644 2,526 2,582 763 2,389 1,618 352 1,343 1,473 1,098 1,442

453 1,142 1,143 341 531 419 689 955 178 160 262 17 106 101 99 311

Saddlers % 52.1 55.5 49.5 40.3 35.2 65.1 27.3 37.0 23.3 6.7 16.2 4.8 7.9 6.9 9.0 21.6

Number

%

416 916 1,164 506 977 225 1,837 1,627 585 2,229 1,356 335 1,237 1,372 999 1,131

47.9 44.5 50.5 59.7 64.8 34.9 72.7 63.0 76.7 93.3 83.8 95.2 92.1 93.1 91.0 78.4

Males and females were pooled and the classification was performed in late April to early May, 19601994 in certain years in the period. Middlings are younger animals, saddlers older mature animals.

interest (Table 1). The data show that considerable changes have occurred during the last three decades. In the 1980s and early 1990s, the abundance of middlings (younger animals with "grey-spotted" colouring) on the grounds has reduced gradually, while that of saddlers (older and mature animals with wing-shaped black spots) has increased. Results from studies of the absolute age composition of harp seals caught on the moulting grounds are of special interest, since they probably give the most representative picture of the age composition in the population. Analyses of age samples obtained in the period 1964-1994 demonstrate essential changes in the composition of animals on the moulting grounds (Table 2). First, a pronounced downward trend in abundance of younger animals should be noted. This concerns particularly animals aged from 1 to 4 years old. The number of harp seals from these particular age groups decreased significantly in the 1980s. Simultaneously, the number of older animals, especially those aged 20 years and older, increased. Changes in the age composition of harp seal females congregating in the breeding period in late February to early March have also been revealed. Analyses of age data from the breeding grounds show a reduction in abundance of animals aged 4-9 years from the middle 1970s. Simultaneously some increase in abundance of older harp seals has occurred (Table 3). The data for 1984 do not, however, fit the trend. A factor contributing to this could be that in 1984, material was collected in the third 10 days of March, when the breeding lairs were about to vanish, compared to the first 10 days in other seasons. Moreover, in 1984, females were caught in the north-

514

Table 2. Dynamics of harp seal age composition on moulting grounds in the White Sea Years

Age, years old 1-4

1964 1970 1971 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1994

5-9

10-19

20 and older

No.

%

No.

%

No.

%

No.

%

671 240 140 477 389 601 286 144 111 84 69 81 197 75 92 48 25 40 127 253

28.7 49.2 32.7 48.7 39.3 59.2 20.0 15.1 5.1 8.7 19.4 14.5 14.6 3.4 6.3 2.5 1.5 2.2 7.6 12.7

882 121 146 312 331 218 573 385 687 336 63 223 309 330 492 397 404 496 248 277

37.8 24.8 34.1 31.9 33.4 21.5 40.0 40.5 31.5 35.0 17.7 40.0 22.9 14.9 33.6 20.8 24.1 27.0 14.9 13.9

727 121 124 149 215 151 406 359 977 461 152 197 638 1,254 672 1,056 973 1,028 929 1,055

31.1 24.8 29.0 15.2 21.7 14.9 28.3 37.7 44.9 48.0 42.8 35.3 47.3 56.6 45.9 55.3 58.0 56.0 55.9 52.7

56 6 18 40 55 46 168 63 403 80 71 57 206 557 207 409 277 272 359 415

2.4 1.2 4.2 4.1 5.5 4.5 11.8 6.6 18.5 8.3 20.0 10.2 15.3 25.1 14.1 21.4 16.5 14.8 21.6 20.7

Total number of animals

2,336 488 428 978 990 1,016 1,433 951 2,178 961 355 558 1,350 2,216 1,463 1,910 1,679 1,836 1,663 2,000

Males and females were pooled, and samples were taken in late April-early May in certain years during the period 1964-1994.

ern V o r o n k a area, not in the Gorlo or Basin as in the other years. H e n c e , the s a m p l e for 1984 is not directly c o m p a r a b l e with samples for the other years. Thus, the results of investigations for the recent 30 years s h o w that the age c o m position o f harp seals on both m o u l t i n g and b r e e d i n g g r o u n d s in the W h i t e Sea has c h a n g e d substantially. T h e p e r c e n t a g e of y o u n g e r animals has d e c r e a s e d to a minim u m while that of seals of older age has increased, especially on the m o u l t i n g grounds.

R a t e s of F e m a l e Sexual M a t u r a t i o n E x a m i n a t i o n s of ovaries show essential differences in the rates of harp seal f e m a l e sexual maturation f r o m 1 9 6 2 - 1 9 6 4 to 1988 (Table 4). In 1 9 6 2 - 1 9 6 4 , the m i n i m u m age at w h i c h a corpus luteum ovulationis was d i s c o v e r e d in f e m a l e o v a r i e s thus indicating their sexual maturity, was 4 years. In this earliest period, practically all f e m a l e s at age 7 bred. In the samples f r o m 1988, corpus luteum ovulationis w e r e f o u n d in ovaries of females aged 5 years and older. H o w e v e r , the n u m b e r of such y o u n g m a t u r e individuals was low, and very few f e m a l e s y o u n g e r than 7 - 8 bred.

515 Table 3. Dynamics of age composition of breeding harp seal females on breeding grounds in the White Sea in certain years during the period 1969-1993

Years

Total number of animals

Age, years old 4-9

1969 1970 1971 1972 1973 1974 1975 1976 1980 1984 1986 1987 1988 1989 1993

10-19

20 and older

No.

%

No.

%

No.

%

144 170 134 119 97 107 156 74 76 333 25 35 53 60 91

30.6 35.9 28.7 25.9 20.3 22.7 32.4 17.1 16.0 35.8 19.5 9.0 11.1 12.7 18.4

280 278 275 274 323 276 246 230 277 462 69 254 329 318 332

59.6 58.6 58.9 59.6 67.4 58.5 51.1 53.0 58.3 49.6 53.9 65.3 68.7 67.4 67.1

46 26 58 67 59 89 79 130 122 136 34 100 97 94 72

9.8 5.5 12.4 14.6 12.3 18.9 16.4 30.0 25.7 14.6 26.6 25.7 20.3 19.9 14.5

T h i s i n d i c a t e s an o b v i o u s t r e n d o f d e l a y in s e x u a l m a t u r a t i o n

470 474 467 460 479 472 481 434 475 931 128 389 479 472 495

of females

in t h e

1980s.

Follicle Maturation in Ovaries O v a r i e s o f l a c t a t i n g f e m a l e s , w h i c h w e r e o b t a i n e d o n b r e e d i n g g r o u n d s in t h e W h i t e S e a in t h e f i r s t 10 d a y s o f M a r c h 1 9 6 2 - 1 9 8 9 , w e r e s t u d i e d . N u m b e r s o f o v a r i e s w i t h

Table 4. Rates of harp seal female sexual maturation based on the results from analysis of ovaries

Age

No. of females 1962-1964 Total

3 4 5 6 7 8 >9

44 62 89 101 95 73 192

1988

Immature

Mature

No.

%

No.

%

44 51 32 9 1 1 5

100.0 82.3 36.0 8.9 1.1 1.4 2.6

-

17.7 64.0 91.1 98.9 98.6 97.4

11 57 92 94 72 187

Total

11 35 52 65 50 29 334

Immature

Mature

No.

%

11 35 51 56 23 8 19

100.0 100.0 98.1 86.2 46.0 27.6 5.7

Material collected in the White Sea, late A p r i l - early May, in 1962-1964 and in 1988.

No. 1 9 27 21 315

%

D

1.9 13.8 54.0 72.4 94.3

516 Table 5. Characteristics of the White Sea harp seal female ovaries based on the availibility of mature follicles (sampling was performed in early March, in several years during the period 1962-1989)

Years

1962 1976 1977 1984 1987 1988 1989

Total number of ovaries (pairs) 312 423 135 121 366 459 442

Ovaries with mature follicles No.

%

190 262 73 59 140 157 364

60.9 61.9 54.1 48.8 38.3 34.2 82.4

mature follicles (>10 m m diameter) were determined. The data (Table 5) indicate that the relative abundance of females with mature follicles in their ovaries in the first 10 days of March fluctuates from year to year. T h e lowest n u m b e r of females with mature follicles in ovaries was registered in 1987-1988.

Weight of Pups Harp seal pups were weighed on the breeding grounds in the White Sea in the second half of March. At that time, the pups have accumulated much h y p o d e r m a l fat and begin to moult. The investigations show that the mean pup weight is not constant from year to year (Table 6). In 1987-1989, the mean weight of the pups was significantly lower than in the other years.

Discussion The distribution area of the White Sea harp seal population covers the W h i t e and Barents Seas. Harp seals do not occur constantly in the White Sea, but the most Table 6. Dynamics of mean body weight (M, in kg) of moulting White Sea harp seal pups by year in the period 1976-1992

Year

Date

No. of animals

M

Weight range

1976 1980 1981 1987 1988 1989 1990 1991 1992

15-20.03 16-21.03 25.03-03.04 19-26.03 19-28.03 23-24.03 17-26.03 17-23.03 12-17.03

78 236 20 151 252 186 731 593 372

36.4 36.3 35.2 32.1 30.6 32.5 34.5 35.6 37.4

20-49 21-52 25-54 18-50 20--44 21-45 20-54 21-58 26-51

517 important stages of their annual life history such as breeding and moulting take place there. The Barents Sea is a feeding area of seals where they feed intensively in autumn and winter. Harp seals spend much time in the open sea and on drifting ice. Another peculiarity of harp seals is their ability to undertake seasonal migrations. They are in the White Sea in December-April, but leave after breeding and moulting in late April to the first half of May. As a rule, they do not occur in the White Sea after the second half of May. Progeny staying in the White Sea after this time in years with anomalous ice and meteorological conditions (extensive ice cover, prevalence of northern winds) is an exception [8]. Seals may appear in the White Sea long before pupping; in December, seal grounds were repeatedly surveyed from airplanes along the edge of the drifting ice in the White Sea Voronka near the Kanin coast. In some years, harp seals may appear in the White Sea even earlier. The invasion of harp seals in the rivers Koida and Severnaja Dvina in winter 1982, and their stay in the White Sea in the summers and autumns of 1985, 1987 and 1988 are probably anomalous phenomena emphasizing substantial disturbance in the migration character of the population. This is confirmed both by the results of our investigations and previous observations of fishermen and hunters living on the coast. It is noteworthy that the movement of harp seals to the river Koida coincided in time with a mass approach of navaga to Koida. This may indicate that harp seals came to the river in search for food. Following navaga, individual harp seals also approached the edge of the fast ice in the south-eastern part of the Barents Sea in the 1980s. Navagas were discovered in the stomachs of some seals obtained there. Why the harp seals appeared in the White Sea in the summer and autumn of 1985, 1987 and 1988 is not completely understood. It has been suggested, that due to unfavourable feeding conditions some seals were not energetically prepared for the long migrations from the White Sea to the northern part of the Barents Sea. This is supported by the registration of individuals in poor condition (skin and fat weight only 31-33% of total weight) on the moulting grounds in late April 1987. Our observations of harp seals near the Murmansk coast in June 1985 agree with other data. Several observations of marine mammals have been conducted near the Murmansk coast, in particular on the Aynov Isles in the period 1963-1989. Harp seals, sick or dead individuals, were found in July 1978 and in May 1985 and 1987 [9]. Similar observations were carried out near the Murmansk coast and the Kharlov Island where harp seals were found in June in 1979 and 1987 (Yury Krasnov, the Kandalakhsha Reserve, personal communication). In other years, harp seals were not observed there. Particularly noteworthy are the deviations in the harp seal migrations in the Barents Sea manifested in their mass invasions to the northern Norwegian coast in 1979-1989 accompanied by mass mortality of animals in fishing gear [1012]. These facts show that there were significant deviations in the harp seal distribution and migration routes in the 1980s in the White and Barents Seas. The results of the harp seal age composition studies on the breeding and moulting grounds are of special interest, with respect to the status and dynamics of the population. Harp seals start to moult in the White Sea in April. In this period seals form

518 dense concentrations on the ice, on the so-called moulting grounds. The age-sex composition of seals on the grounds varies with time. Mature males start to form the moulting grounds. Subsequently, the animal composition on the grounds changes gradually following the appearance of immature animals of both sexes and mature females. In the third 10 days of April and the first 10 days of May males and females of all ages (excluding their young) moult. The overwhelming majority of seals stay on the ice in the White Sea in this period. It is reasonable, therefore, to assume that samples from these grounds obtained in the third 10 days of April to early May may give a representative view of the population composition and its changes. Judging from the investigation results from the moulting and breeding grounds, it seems reasonable to suggest that the White Sea harp seal population age composition underwent considerable changes in the 1980s. However, the data on age composition need correction, taking into account the complicated nature of the moulting ground formation process and possible peculiarities in the distribution of young animals in this period. Thus the data should not be considered as absolute. However, the trend revealed in the population composition should be beyond doubt since it is registered over many years. The sharp reduction in abundance of young animals on the moulting grounds should be considered as a negative symptom, indicating a high mortality of animals during their first year of life. This raises the question as to what caused this high mortality of young animals. Sealing based on the taking of pups during the recent 30 years may have had a certain effect on the state and composition of the population. The intensity of harp seal hunting was high in the 1980s, with a mean annual catch of 68,400 (range 42,900-82,100) in 1980-1989, while in 1970-1979, it was estimated at 40,800 (range 36,300--48,500). However, the present harvest of animals can hardly be considered as the main and only reason for the sharp reduction in the number of young animals in the population. This is supported by several facts. Aerial visual observations, conducted over the White Sea after hunting, have shown the presence of young over a large area. For instance, during a flight on 30 March, 1991, pups were found over practically the whole area of the White Sea Gorlo. Although visual observations can hardly produce an accurate estimate of pup numbers after hunting, it can be considered to give a significant picture of the area of their distribution. Since 1989, the harvest of harp seals in the White and Barents Seas has twice been reduced and now amounts to 40,000 animals per season. But this did not influence the age composition of the population and did not result in any appreciable increase in abundance of young animals on the grounds. The mass tagging of young being carried out in the White Sea since 1989 has revealed long-distance migrations of young animals. The tagged animals were registered in several far-distant regions: on the northern coast of Norway, Spitsbergen and the south-west of Greenland. It is difficult to assess the consequences of such distribution due to the lack of data on tagging from previous years. However, we believe that long migrations contribute to an exchange of animals between the White Sea and the Jan-Mayen populations which may be one of the reasons for the low representation of young animals in some years.

519 Considering the changes in the age composition of females on the breeding grounds, it is necessary to take into account the delay in sexual maturation of females in the 1980s. Along with other reasons, this caused a noticeable reduction in the abundance of females aged 4--9 years in the 1980s compared to the previous 10 years. The changes in rates of follicle maturation in harp seal female ovaries are also worthy of attention. Harp seals copulate in the White Sea in mid-late March [ 13]. By that time, mature follicles able to ovulate (graaphian follicles) should appear in the ovaries. This is an indispensable condition predetermining successful breeding. The reduction in abundance of females with mature follicles in their ovaries by early March in the 1980s should be regarded as a result of the delay in the rate of follicle maturation. The negative consequences of this process are not difficult to foresee; ovulation will occur too late. The study of ovaries collected in the White Sea in late March 1984 support this trend: Most of the females had not ovulated by the end of March in 1984 [14]. Such females have less chance of successful breeding, as it can result in the lack of simultaneous mating and ovulation. As a result, the population's reproductive abilities will be reduced. Animal weight is an important morphophysiological indicator corresponding to animal life conditions and development [15]. Therefore, the decrease in the total body weight of harp seal pups in the 1980s should be regarded as a negative symptom. The changes in the White Sea harp seal population ecology occurred during a period of profound changes in the Barents Sea ecosystem including large reductions in stocks of many fish species on which harp seals feed intensively [3-5]. Particularly, this refers to polar cod (Boreogadus saida) and capelin (Mallotus villosus) which play important roles in harp seal feeding ecology [ 16-19]. The polar cod catch in the Barents Sea in 1966 was estimated at less than 1,000 tonnes but already in 1971 it reached a maximum of 348,000 tonnes [20]. However, the catch was subsequently reduced, and by the late 1970s, polar cod had lost its commercial value. The special role of the polar cod is conditioned by the fact that this frigostable fish is distributed near the ice edge along with harp seals. Moreover, it is widely spread in the Barents Sea where it may form significantly dense concentrations [21,22]. It is therefore not surprising that the harp seal migrations are in many respects correlated with polar cod migrations. The dates and regions of the harp seal autumn-winter migrations to the White Sea coincide in many cases with the pre-spawning migrations of polar cod along the western coast of Novaja Zemlja to the south-east of the Barents Sea [23,24]. Chapsky [25] pointed out that both the migrations and dates of harp seal appearance on the breeding grounds in the White Sea are predetermined by the peculiarities of the polar cod distribution. The fact that polar cod forms pre-spawning concentrations and spawns in the south-eastern part of the Barents Sea in autumnwinter may have made this region particularly important for harp seals. Investigations carried out in the south-eastern part of the Barents Sea in December-February in 1966, 1967 and 1971 from the hunting ship "Chistopol" showed mass occurrence of harp seals in regions near the south-western coast of Novaja Zemlja, the Kolgujev

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Island and the Kanin peninsula [26,27; unpublished data]. These are the very areas where the most dense pre-spawning and spawning concentrations of polar cod occur [24]. Harp seals were also registered in the south-east of the Barents Sea in subsequent years. Flights carded out in December 1985, 1987, 1989 and 1990 revealed harp seals on the ice in the Cheshskaja Bay, near the northern coast of the Kanin peninsula, and along the southern coast of Kolgujev Island (Fig. 2). Stocks of capelin, another basic fish in the trophic chains of the Barents Sea, have been catastrophically reduced. Large catches of capelin in the 1970s and early 1980s reduced its stock so much that fishing was provisionally stopped in 1987. Record quantities of capelin, 2.5 million tonnes and 2.9 million tonnes, were taken in 1976 and 1977, respectively [28]. Of course, such wide-scale disturbances in the Barents Sea ecosystem could not occur without consequences for the harp seal population. This is indirectly proved by the fact that harp seal invasions to the coast of Norway have been registered since 1978 [11] when the polar cod stocks were significantly reduced. It is therefore possible that the changes in the White Sea harp seal population

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ecology (migrations, age composition and breeding) in the 1980s occurred as a result of the changes in the Barents Sea ecosystem, primarily the changes in the feeding conditions of the species. This may contribute to an explanation of the deviations in the migration routes, the high mortality of young animals, the progeny weight decrease, the delayed sexual maturation of females and the delay in rates of follicle maturation in ovaries. The deterioration of the habitat conditions showed that young animals were the most vulnerable to unfavourable influences of the environment. This study points out the potential of using harp seals as indicators of the Barents Sea ecosystem.

Acknowledgements We are thankful to Yu.I. Nazarenko, V.V. Andrianov, Yu.M. Silinsky, V.V.

522

Sobolev, V.N. Mankov, G.N. Ognotov for their help in the collection and treatment of the material.

References 1. Timoshenko YuK. Osobennosti rasprostranenija I migratsii grenlandskogo tjulenja v Belom more v 1987 g. Ekologia 1992;1:26-33. 2. Yablokov AV, Nazarenko JuI. Poddezhanije optimalnoi vozrastno-polovoi struktury - osnova ratsionalnoi ekspluatatsii populjatsii grenlandskogo tjulenja. Ekologia 1986;2:51-56. 3. Luka GI, Matishov GG, Nizovtsev GP, Orlova EL. K voprosu ob ekologicheskoi osnove postrojenija ratsionalnogo rybolovstva v Barentsevom more. Vsesojuznaja konferentsija po ratsionalnomu ispolzovaniju biologicheskikh resursov okrainnykh I vnutrennikh morei SSSR/Sbalansirovannoje rybolovstvo/. M: 1989;67-73. 4. Glukhov AA. Ekologicheskije problemy Barentseva izuchenija I ratsionalnogo ispolzovanija biologicheskikh resursov okrainnykh I vnutrennikh morei SNG. Materialy vtoroi mezhgosudarstvennoi konferensii. Rostov-na-Donu: 1992;33-35. 5. Drobysheva SS, Matishov GG. Posledstvija antropogennogo narushenija bioticheskogo balansa v Barentsevom more. Problemy izuchenija I ratsionalnogo ispolzovanija biologicheskikh resursov okrainnykh I vnutrennikh morei SNG. Materialy vtoroi mezhgosudarstvennoi Konferentsii. Rostov-na-Donu: 1992;56-57. 6. Yakovenko MI. Opredelenije vozrasta I srokov nastunlenija polovoi zrelosti u Belomorskogo lysuna. Trudy PINRO, Murmansk, 12, 1960;117-118. 7. Chapsky KK. O perekhodnykh tipakh okraski volosjanogo pokrova samtsov grenlandskogo tjulenja. Issledovanija morskikh mlekopitajushchikh. Trudy PINRO, Murmansk, 1967;21:60-79. 8. Timoshenko YuK. Vlijanije ledovykh I meteorologicheskikh uslovii na nekotorykh predstavitelei nastojashchikh tjulenei. Ecologia 1986;3:72-78. 9. Tatarinkova IP, Chemjakin RG. O vstrechakh morskikh mlekopitajushchikh v raione Ainovykh ostrovov (Zapadnyi Murman). Morskije mlekopitajushchije. Tezisy dokladov X vsesojuznogo soveshchanija po izucheniju, okhrane I ratsionalnomu ispolzovaniju morskikh mlekopitajushchikh. M 1990;291-292. 10. Wiig 0. Selinvasjoner til norskekysten. Fiskets Gang 1988;6/7:18-19. 11. Oritsland T. Seals in the northeast Atlantic and Interactions with Fisheries. Comite Arctique International (CAI): Commentary, 2 Feb 1990; 10-13. 12. Haug T, Kroyer AB, Nilssen KT, Ugland KI, Aspholm PE. Harp seal (Phoca groenlandica) invasions in Norwegian coastal waters: age composition and Feeding habits. ICES J mar Sci 1991;48:363-371. 13. Popov LA. O periode sparivanija grenlandskogo tjulenja. Tezisy dokladov pjatogo vsesojuznogo soveshchanija po izucheniju morskikh mlekopitajushchikh. Ch 1, Makhachkala 1972;80-82. 14. Timoshenko YuK. O srokakh ovuljatsii u grenlandskogo tjulenja belomorskoi populatsii. Morskije mlekopitajushchije. Tezisy dokladov IX Vsesojuznogo soveshchanija po izucheniju, okhrane I ratsionalnomu ispolzovaniju morskikh mlekopitajushchikh. Arkhangelsk 1986;381-382. 15. Shvarz SS, Smirnov VC, Dobrinsky LN. Metod morfofiziologicheskikh indikatorov v ekologii nazemnykh pozvonochnykh. Trudy instituta ekologii rastenii I zhivotnykh, AN SSSR, Uralsky Filial, Sverdlovsk 1968;58:387. 16. Smirnov NA. O morskom zverinom promysle na russkikh sudakh. Eksp. dlja nauch.-prom, issl. u beregov Murmana. SPB 1903;157. 17. Sivertsen E. On the biology of the harp seal Phoca groenlandica. Erxl. Investigations carried out in the White Sea 1925-1937. Hvalradets Skr 1941;26:1-166. 18. Lydersen C, Angantyr LA, Wiig O, Oritsland T. Feeding habits of Northeast of Northeast Atlantic

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19. 20.

21. 22. 23. 24. 25.

26. 27.

28.

harp seals (Phoca grornlandica) along the summer ice edge of the Barents Sea. Can J Fish Aquat Sci 1991;48:2180-2183. Kapel FO, Angantyr LA. Feeding patterns of harp seals (Phoca groenlandica) in coastal waters of West Greenland, with a note on offshore feeding. ICES CM 1989;N:6:1 l+tables. Borkin IV, Ponomarenko VP, Trtjak VL, Shleinik VN. Saika Boreagadus saida (Lepeshin) - ryba poljarnykh morei (zapasy i ispolzovanije). Biologicheskije resursy Arktiki I Antarktiki. M 1987;183-207. Manteifel BP. Saika I jejo promysel. Arkhangelsk 1943;32. Ponomarenko VP. Saika Boreagadus saida V kn.: Promyslovyje biologicheskije resursy severnoi Atlantiki (prilegajushchikh morei Severnogo Ledovitogo okeana. Ch 1, M 1977;309-313. Ponomarenko VP. Osenne-zimneje raspredelenije prednerestovykh I nerestovykh skoplenii saiki (Boreagadus saida) v Barentsevom more. Trudy PINRO, Murmansk, 1963;15:177-197. Ponomarenko VP. Migratsii saiki v Sovetskom sektore Arktiki. Trudy PINRO, Murmansk, 1968;23:500-512. Chapsky KK. Nekotoryje ekologicheskije obosnovanija sezonnoi dinamichnosti areala belomorskoi populjatsii grenlandskogo tjulena. Trudy soveshchanija ikhtiologicheskoi komissii AN SSSR, M, 1961;12:150-162. Beloborodov AG. K osenne-zimney migratsii grenlandskogo tjulenja v Beloje more. Materialy rybokhozjaistvennykh issledovanii Severnogo basseina, vyp XVIII. Murmansk 1971 ;101-106. Timoshenko YuK, Lukin LR. K poznaniju ekologii grenlandskogo tjulenja I morzha v zimny period. Tezisy dokladov konferentsii molodykh uchonykh PINRO po resultatam issledovanii 1971. Murmansk 1972;40-41. Zilanov VK, Luka GI, Ushakov NG. O ratsionalnoi ekspluatatsii zapasov moivy Barentseva morja. Rybnoje khozjaistvo 1984;7:34-37.

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Interactions with fisheries

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9 1995 ElsevierScienceB.V. All fights reserved Whales, seals, fish and man A.S. Blix, L. WallCeand O. Ulltang,editors

527

Interactions between marine m a m m a l s and fisheries: an unresolved problem for fisheries research Tim D. Smith Northeast Fisheries Science Center, Woods Hole, Massachusetts, USA Abstract. Food web interactions between marine mammals and commercial fisheries have been subject to relatively little attention in fishery research. Three characteristics of marine mammals, commercial fisheries, and the conduct of fisheries research have contributed to this. These include differences between marine mammals and fishermen in prey size capability and ability to adapt to rapid changes, major undocumented ecological changes which have occurred historically making it difficult to interpret present ecosystem states, and a short term focus which was adopted by fishery research during its development towards the direct effects of harvesting. These characteristics need to be considered in designing and implementing research programs to investigate interactions between marine mammals and fisheries. Key words: ecology, predation, fishery biology

An Early Morning Introduction It is 4:30 in the morning, and still no revelation" why have fishery biologists not addressed the question of the food web interactions between marine mammals and fisheries? From around my upraised mug of morning tea I glimpse the cobweb in the ceiling comer, vowing again to sweep it down. But something moves; emerging cautiously from the shadow is Lepsima saccharina, the silverfish. It is encouraging at this hour that it is not a spider; at least it has the same name as my quandary" "fish". Awake at this hour out of desperation for an idea I call to it encouragingly, hoping for insight: "Bonjour M. petit poisson d'argent, comment s'va?" But unfortunately it speaks only Norwegian, where it is known as sr "poor silver creature." So it is not a fish after all; my hopes for insight fade. The sr moves diagonally down the wall towards my book shelf, irritatingly bold for so poor a creature. I become the predator, poised. It jumps, and lands on a dark blue book, dusty and old; I strike; it disappears into the book's spine; the book falls to my desk. Animal Ecology is the title, written by Charles Elton in 1927 [ 1]. I understand that sr prefer the glue used in older books, and this may be so because I cannot shake him out of the spine. Instead, I start paging through Elton's version of ecology. He has a lot to say about food web interactions, discussing the size of prey and the requirements of predators. The best size prey, he thinks, is one which a predator can capture and ingest efficiently and safely while being able to catch sufficient numbers

Address for correspondence: Northeast Fisheries Science Center, Woods Hole, MA 02543, USA. Tel: +1 508 548 5124; Fax: +1 508 548 5124; E-mail: [email protected]

528 to meet physiological requirements. I continue to read; it is at least a starting point in this morning's dim light.

Sizes of Predators and Prey The killer whale and the blue whale, Elton notes, represent extremes for large predators; one is specialized to the unusual habit of eating prey larger than itself and the other to eating prey far, far smaller than itself. As Tiu Simil~i and Anna Bisther showed in their presentations to this Symposium, however, we have since learned that killer whales along the coast of Norway also feed on much smaller prey, regularly herding and catching Atlantic herring. But killer whales do not appear as efficient at catching small prey as are the more specialized baleen whales, and must resort to stunning the tightly schooled herring and eating them one at a time. One may wonder if killer whales learned to feed on herring after the whale fisheries in the North Atlantic depleted the numbers of baleen whales, and also, if baleen whales were more abundant today, would killer whales chose to compete with or prey on them. Like killer whales and in contrast to most animals, man as a predator is not limited to certain sizes of prey. We harvest the largest animal, the blue whale, its predator, the killer whale, and now even the blue whale's prey, krill. In this respect, Elton argues, man is unique, although this has been so only "in the later part of his history." Were animals other than man not so constrained, Elton muses, there would be much less "variety and specialisation," and food chains as we see them would not exist. But food chains do exist, linking together, as Elton noted, into food webs. Despite our ability to harvest these chains and webs at any and seemingly all levels, man appears to have ignored changes in food chain dynamics in studying the effects of fishing [2]. Fishermen are animals, and as such are subject to the same evolutionary processes as their prey. But fisheries change as the economics, technology, and levels of prey abundance change, and these changes are much more rapid and radical than those due to biological evolution. For example, between 1880 and 1900 the English sailpowered beam trawler was almost completely replaced by the much more efficient and larger steam-powered otter trawler. The increase in efficiency was substantial, as calculated by Garstang in 1900 [3], perhaps of the order of 4--8 times. The fishing fleet changed markedly, and with fewer but more efficient boats, it roughly doubled its predatory power during these 20 years. The fish and their ecological communities also began to change, although at lesser rates. Abundance of target fish species had fallen by 1990 to half of its 1880 level under the greater predation by fishermen, while the abundance of some nontarget species had increased. The rate of change of fisheries has continuously increased, and although some "species" of fisherman have become extinct in the process, the diversity of types of fishing today is enormous. The English language has adapted by generalizing the word fishing to include the harvest of nearly all aquatic and marine organisms. The

529 change that the word has encompassed is illustrated by the variety of harvesters in the Gulf of Maine who have been and are referred to as fishermen: this ranges from the whalemen of a century ago, to those harvesting pelagic species such as Atlantic mackerel and herring, to the Atlantic halibut fishermen of the turn of the century, to the groundfish trawlers of this century, and now even to those who now have learned to harvest sea cucumbers, sea urchins, and seaweed in their quest for survival. Metamorphoses of fisheries over ranges of species such as this have been common around the world, frequently driven by successive overexploitation of one species after another. Such changes as these are facilitated by the increasing diversity of methods of catching fish used on vessels ranging from the size of a man to the size of a playing field, the latter frequently able to reduce prey handling time by on-board processing catches. At least as significant, the sensory capabilities of fishermen, formerly limited to blind groping with nets and hooks, now greatly exceed the capabilities of most of their prey. Fishermen and fisheries are constantly changing to meet continuously changing economic conditions by modifying vessels and equipment, and adopting technological advances. If the abundance of a target species decreases, due to too much fishing or to environmental change, fishermen evolve their methods to become ever more efficient [4]. If changes occur too rapidly, fishermen must radically alter their harvesting strategy and methods to catch different prey, that is they must metamorphose rather than evolve. These changes generally improve overall predatory effectiveness, but because change is the normal course of fisheries, the fishermen must also maintain or increase their capabilities for yet further changes.

The Present State of Ecosystems While Elton did not follow up on the nature of fisheries, he did describe some of their effects. The "doom of the whales" in the Arctic was sealed, he suggested, with the development of Dutch and English whaling in the 16th century. He shows a photograph of the skulls of Atlantic walrus on Moffen Island, just north of Spitsbergen, slaughtered for their ivory. The fate of that fishery, and now more importantly, the prospects for recovery of that population, is reviewed in a poster by Oystein Wiig and Ian Gjertz at this Symposium. Elton also described the rapid recovery of the Alaska fur seal from its fishing-induced near extinction in 1914. He lamented the senselessness that "the capital of animal numbers is destroyed to make the fortune of a few men," and the unfairness "that all possible benefits for any one coming later are lost." But despite his lament, he was more interested in using these and other examples to illustrate the point that: Living as we do in a world which has largely been denuded of all the large and interesting wild animals, we are usually denied the chance of seeing very big animals in very big numbers. Therefore, he continues:

530 the conditions under which the present fauna has evolved are ... rather different from what one might expect from seeing the world in its present state. Elton did not think that all harvesting had grossly distorted the ecosystem. For example, in the summer around Spitsbergen, he noted, Norwegians were then pursuing a simultaneous hunt for the bearded seal, Erignathus barbatus or storkobbe, and its predator, the polar bear. He observed that despite the harvest, the seals were "more abundant than ever", and suggested that this was due to harvesting the predator along with its prey. Although he recognized that such an outcome depended on the numbers of both species harvested, he thought a "balance happens to have been struck" at Spitsbergen. Nonetheless, such a balance entails a change in the ecosystem; in this case a lower abundance of polar bears, and presumably a higher abundance of Norwegians. More generally, the theory of harvesting outlined by Hjort in 1933 [5], drawing on the work of the mathematical ecologists in the 1920s, emphasized that the major effect of harvesting would be a decrease in the abundance of the target species to some lower stable level as the major effect of harvesting. While the theory allowed for sustainable catches, it was apparent to Hjort that a balance had not been struck for the North Atlantic whale fisheries. These fisheries had decreased the abundance of whales to the point that the fleets had to continually move to new grounds. Since the turn of the century, Foyn's fishing vessels had been excluded first from the Barents Sea grounds, then from Icelandic waters, and by 1933 were returning large profits from the Antarctic grounds. In the face of the large and rapid declines in the species targeted by many fisheries, the changes wrought on the rest of the ecosystem by harvesting were not explicitly addressed when biologists began to develop management advice. For example, Hjort focused primarily on developing methods of measuring the biological significance of the repeated pattern of whaling. Similarly, in applying Hjort's approach, Graham in 1935, Schaefer in 1954 [7], and Chapman in 1964 [2] also focused on the direct effects. Thus while harvesting indirectly changes food web relationships, almost always only the often overwhelming direct effect of reducing the target species has been studied; indirect effects have been ignored.

Fishery Biologists Didn't! Elton was not alone in the 1920s in his interest in the nature of the interactions among predators and prey in fisheries. However, this interest was not shared within the field of fishery biology as it developed in the latter 19th century and the first half of the 20th century. Lankester had argued forcefully in 1883 that the effect of fishing can only be understood by considering the effect of the increased predation by fishermen on the equilibrium between natural predators and their prey: the thousands of apparently superfluous young produced by fishes are not really superfluous, but have a perfectly definite place in the complex interactions of the living beings within their area.

531 Lankester's perspective was not taken up in fishery biology, and there was little study of these effects, even though they have been described for centuries. For example, in response to concerns in France about the effect of dolphins on fisheries, a Papal Decree was issued in 1587 "anathematizing this vermin" [2]. Predator control bounties have arisen as a part of fishery management periodically for centuries. An example close to my laboratory was when the town of Wellfleet on Cape Cod in Massachusetts in 1740 began paying a bounty for "porpoise tails" [8]. Between 1740 and 1742 one person was paid the bounty 500 times. In France the government attempted to implement the earlier Papal Decree in the 1880s in the form of bounties for dolphins [9], but apparently with little success. The calls for renewed control of predators were regular by the turn of the century, but with modest scientific bases. For example, in 1887 the German Fishery Association argued for a "premium on seals" based on the observation that their new estimates of the productivity of fishing grounds, which included seals, was less than half that of the protected fish ponds [10]. A similar conclusion was reached in 1889 by the US Fish Commissioner, Spencer Baird, for porpoises and elasmobranchs. He argued from common knowledge, noting that "the extent of destruction to fish caused by the porpoises, skates, and dogfish is well known" and endorsed a plan for a factory in the village of Woods Hole to make agricultural fertilizer from predatory fish [ 11 ]. This, he argued, would have "a marked influence upon the supply of edible fishes." Whether it did so was not measured, although it did have a direct effect on the economy, as well as the smell, of the village of Woods Hole. Despite the wider interest in the effects of predation, most fishery research has focused on the direct and most apparent effects of fishing. For example, the analyses conducted by scientists of the International Council for the Exploration of the Seas on the higher catch rates in the North Sea after the First World War were confined to such single species effects [ 12]. The ICES analyses were criticized [13,14] by some fishery biologists [13,14] for their narrow scope, and additionally the effects of the war years were seen very differently in other fisheries. For example, in the Adriatic Sea, D'Anconna collected landings data which suggested a higher proportion of predatory fish were in the markets when the overall catches were lower during the war years than before or after the war [ 15]. Based on D'Anconna's observation, Volterra, his father-in-law, developed his well-known predator-prey models in 1926 [15]. While this work fueled a minor controversy in the developing field of mathematical ecology [16], it was generally overlooked by fishery biologists despite a translation of Volterra's paper having been published in one of the prominent fishery science journals of the day. One reason predation and other ecological roles have historically not been subject to widespread study in fishery research is, I feel, the commensal relationship between the biologist and the fishermen. Fishery biology is a discipline which continues to evolve to fill a specialized niche defined by the needs of fishermen, and to coevolve with another commensal, the fisheries manager. The needs that the biologists are called on to meet are ever changing as the "bionomic ecosystem" of Gordon [ 17] evolves under the continued and seemingly ever mounting pressure of fishing.

532 Historically, the fishery biologist tended to see the world from the continually changing point of view of the fishermen. This was literally true when fisherydependent data were the primary source of information, with the fishery biologist observing from the bow, or perhaps stem, of the fishing boats. As such, direct observations of predation by marine mammals are more likely to be made during fishing operations than at other times. These observations may not be representative but are often the source of information underlying complaints by fishermen [ 18,19]. The constraints on the biologist's perspective also change over time, with redefinition of what is important occurring as fisheries change their target species and spatial distribution. For example, in New England the demise of the Atlantic halibut fishery around the turn of the century was followed by an expansion of a fishery on haddock, one of its prey. The questions shifted from the dynamics of predators near the top of a food chain to the dynamics of predators which themselves support several predators. That Georges Bank had once been replete with Atlantic halibut has seemingly been forgotten by both fishermen and biologists. Similarly, we are now asking the question if minke whales or other predators have moved into the niche of the Antarctic blue whales. But, with the ending of the blue whale fishery, the emphasis of fishermen and biologists shifted away from the largest of animals to the next most valuable whale species, the fin whale. The data needed to describe the blue whale's niche was not collected, and now may not be collectable. From his niche within the bionomic ecosystem defined by human predation, the fishery biologist has tended to be myopic. One form this short-sightedness takes is that the factors governing the evolution and metamorphoses of the fishermen in response to changing prey availability and economics frequently have not been observed. A second form is that study has often been limited to the immediate area and season of harvesting, an especially constraining practice when considering the food web interactions with marine mammals, with their frequently large annual movements. Thirdly, there has been a tendency to focus on those components of the bionomic system which most affect the short term success of the fishermen, namely the abundance of their prey. Some of this myopia was firmly embedded in fishery research programs by 1955. In his paper to the United Nations' Rome Conference that year Schaefer [20] outlined how he felt fishery research programs should be structured. There he disallowed a place for the economist, and relegated predation to the most remote comer of the third (meaning least needful of attention) level of his diagrammatic prescription. In the 40 years since the Rome conference, the scope of fishery biology has been broadened substantially, frequently at the level of the fishery biologist and at times in the context of fishery management. Fishery biologists have become less dependent on the bow of the fishing vessel as they have developed fishery independent resource surveys, which have been used to monitor target species abundance, and in some places to monitor both abundance and prey abundance in multispecies groundfish assemblages. Long term programs have been developed to monitor other components of the ecosystem, especially zoo-

533 plankton. Fishery biologists have developed and explored multispecies models to help interpret this information, and some perspectives from it have at time affected the fishery managers. In my own region, for example, international management at one time adopted a "two-tiered quota" system in recognition of interactions among the several harvested groundfish species. The historic concerns about the predatory relationships of marine mammals and fishery resources, however, have reemerged in recent years. Questions about the effect of these predators on fishery resources that were not addressed historically still cannot be answered, even with expansion of the scope of the fishery biologist to include multispecies interactions. An important and I feel unresolved problem is how to develop research programs, including both data collection and methods of analysis, which will allow resource management to address these issues on a scientific basis.

"A New but Undocumented Fishery" In this Symposium many of the papers presented have focused on prey consumption, including estimates of rates of consumption for several pinnipeds and for minke whales. David Lavigne argued in his contribution that further improving our understanding of consumption rates is now far less important for management than improving our understanding of the dynamics of food web interactions. However, despite interest among managers and prompting from other disciplines, fishery biology has not addressed this aspect of the effects of fishing, and has not developed needed research methods. Harwood [21 ] suggested that progress might be made "if we were to consider the competing marine mammal as if it were a new, but undocumented, fishery, and to review what information about its operation is required to evaluate the threat it poses to existing fisheries". Under this approach the tools of the fishery biologist might come into play more naturally as fishery biologists become commensal with the marine mammal rather than, or better in addition to, the fishermen. Harwood's relegation of the marine mammal to the role of the "new fishery" reflects the lack of emphasis given to such studies previously, but is jarring given that the niches of marine mammal predators have been defined over much longer time frames than those of the fisheries. How best to organize fisheries research has been debated since at least the 1890s [2]; many forms have been tried and in most places the model adopted has been the government supported fisheries research laboratory. The question of how best to organize research relating to marine mammals, both as a target of and as by-catch in fisheries has also been much discussed. In the United States, the Marine Mammal Protection Act in its several revisions has resulted in an expanded responsibility for scientists in the fisheries laboratories of the National Marine Fisheries Service. While research by scientists outside the government has also been supported, the nature of

534 most research related to marine mammals has been defined by biologists within the government. Norway has taken a different approach to address its interests, and we are seeing the results of their approach in this Symposium culminating the Norwegian Marine Mammal Research Program, begun in 1989. As Lars WallCe indicated, the Norwegian strategy has been to utilize the expertise and methodology of fishery biology, through the Norwegian Marine Research Institute, and to utilize other disciplines through various universities and research agencies. However, in contrast to the US approach, selection of specific projects for funding was determined external to the government fisheries laboratories. The two approaches have resulted in a different mix of research activities. Some of the differences reflect the different objectives and interests within Norway and the US. Others of these differences are due to the disciplinary filter used in the US in deciding the research to be funded. For example, national priorities have focused our research on measuring the direct effects of the by-catch of marine mammals, and have generally given lower emphasis to measuring the effects of rapidly expanding pinniped populations on their fished prey populations. In contrast, in Norway a broader range of research has been supported. The two approaches have different strengths and weaknesses. The US approach may be too narrowly focused, resulting in key gaps in information. The Norway approach may suffer from too limited integration among the broader scope of research projects. This latter was reflected, for example, in the need for additional simultaneous measurement of prey species distribution and availability (i.e. the specialty of the fishery biologist) to complement the studies on the prey consumption of whales and seals (i.e. the specialty of the academic biologist.) Similarly, some Symposium descriptions of now completed research programs included specific reference to the next step being the evaluation of the management significance of the results, again the province of the fishery biologists. Such evaluation would be more effective, however, as an integral part of the overall research program.

Conclusions

The wisdom and utility of the approaches taken in the US and Norway towards understanding the food web interactions between marine mammals and fisheries will ultimately be evaluated by history; this Symposium has established some of the facts for such judgements to be made. In the meantime, some guidelines emerge. The first is that the full complexity of food webs cannot be directly approached; rather, following the lead of the Benguela Ecology Program [ 18], we should strive to determine the minimal complexity required in models of food webs to provide sound, scientifically justifiable management advice. Secondly, improved data collection methods must be developed for measuring predation (for example fatty acid and stable isotope profiles of predators and prey.) Lastly, the nature and timing of shifts in food web relationships need to be determined. In this Symposium, for example,

535 T o r e H a u g suggested that minke whales m a y shift a m o n g prey on an annual basis, whereas J o h a n n Sigurjonsson noted that fin whales may u n d e r g o decadal c h a n g e s , possibly driven by environmental variability. T h e s e time frames m u s t be c o n s i d e r e d in designing and i m p l e m e n t i n g research p r o g r a m s to obtain long t e r m observations necessary to understand the ecological roles of marine m a m m a l s . In i m p l e m e n t i n g these guidelines, robust institutional structures for research are needed, structures far different f r o m those which are now in place. G i v e n rapidly developing c o m m u n i c a t i o n s abilities, these structures m a y usefully be m o r e than just physical buildings and scientists in specific locations. Further, their overall operation will have to account for both regional and country-wide priorities. Strong effective research which will yield increased understanding of these c o m p l e x interactions is dependent on d e v e l o p m e n t of suitable research institutions, and their structure should be discussed as a matter of urgency if the goal of understanding the interactions between m a r i n e m a m m a l s and fisheries is to be met.

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