Advances In Marine Biology, Volume 56

V O LU M E F I F T Y ADVANCES S I X IN MARINE BIOLOGY Advances in MARINE BIOLOGY Series Editor DAVID W. SIMS Ma...

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V O LU M E

F I F T Y

ADVANCES

S I X

IN

MARINE BIOLOGY

Advances in MARINE BIOLOGY Series Editor

DAVID W. SIMS Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth, United Kingdom and Marine Biology and Ecology Research Centre School of Biological Sciences University of Plymouth, Drake Circus Plymouth, United Kingdom Editors Emeritus

LEE A. FUIMAN University of Texas at Austin

CRAIG M. YOUNG Oregon Institute of Marine Biology Advisory Editorial Board

ANDREW J. GOODAY Southampton Oceanography Centre

GRAEME C. HAYS University of Wales Swansea

SANDRA E. SHUMWAY University of Connecticut

ROBERT B. WHITLATCH University of Connecticut

V O LU M E

F I F T Y

ADVANCES

S I X

IN

MARINE BIOLOGY Edited by

DAVID W. SIMS Marine Biological Association of the United Kingdom The Laboratory, Citadel Hill Plymouth, United Kingdom and Marine Biology and Ecology Research Centre School of Biological Sciences University of Plymouth, Drake Circus Plymouth, United Kingdom

AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier

Academic Press is an imprint of Elsevier 32 Jamestown Road, London NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands Linacre House, Jordan Hill, Oxford OX2 8DP, UK 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA First edition 2009 Copyright # 2009 Elsevier Ltd. 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. Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://www.elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made. ISBN: 978-0-12-374960-4 ISSN: 0065-2881 For information on all Academic Press publications visit our website at elsevierdirect.com Printed and bound in UK 09 10 11 12

10 9 8 7 6 5 4 3 2 1

CONTRIBUTORS TO VOLUME 56

Andreas J. Andersson Bermuda Institute of Ocean Sciences, St. George’s GE 01, Bermuda Avan Antia Christian-Albrechts-University of Kiel, 24119 Kiel, Germany Nicholas R. Bates Christian-Albrechts-University of Kiel, 24119 Kiel, Germany Ulrich Bathmann Alfred Wegener Institute, D-27570 Bremerhaven, Germany Gregory Beaugrand Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom and Centre National de la Recherche Scientifique, Laboratoire d’Oce´anologie et de Ge´osciences, Station Marine, Universite´ des Sciences et Technologies de Lille, 62930 Wimereux, France Juan Bellas Departamento de Ecoloxı´a e Bioloxı´a Animal, Facultade de Ciencias do Mar, Universidade de Vigo, 36310 Vigo, Spain Corey J. A. Bradshaw The Environment Institute and School of Earth and Environmental Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia and South Australian Research and Development Institute, Henley Beach, South Australia 5022, Australia Holger Brix Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, California 90095-1567, USA Rik C. Buckworth Fisheries, Northern Territory Department of Primary Industries, Fisheries and Mines, Darwin, Northern Territory 0801, Australia Stephen Dye Centre for Environment, Fisheries and Aquaculture Science (Cefas), Lowestoft, Suffolk NR33 OHT, United Kingdom

v

vi

Contributors

Martin Edwards Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom Iain C. Field School for Environmental Research, Institute of Advanced Studies, Charles Darwin University, Darwin, Northern Territory 0909, Australia and Australian Institute of Marine Science, Casuarina MC, Northern Territory 0811, Australia Astrid C. Fischer Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom Tore Furevik Geophysical Institute, N-5007 Bergen, Norway Reidun Gangstø University of Bern, 3012 Bern, Switzerland Martin J. Genner Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom and School of Biological Sciences, University of Bristol, Bristol BS8 1UG, United Kingdom Hja´lmar Ha´tu´n Faroese Fisheries Laboratory, FO-110 To´rshavn, Faroe Islands Stephen J. Hawkins Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom and College of Natural Sciences, Memorial Building, Bangor University, Gwynedd LL57 2UW, United Kingdom Graeme C. Hays Institute of Environmental Sustainability, Swansea University, Swansea SA2 8PP, United Kingdom Russell R. Hopcroft Institute of Marine Science, University of Alaska Fairbanks, Fairbanks, Alaska 99775-7220, USA Sabine Kasten Alfred Wegener Institute, D-27570 Bremerhaven, Germany Ralph Keeling Scripps CO2 Program, La Jolla, California 92093-0244, USA Mike Kendall Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, United Kingdom

Contributors

vii

Emily Lewis-Brown WWF-UK, Panda House, Weyside Park, Godalming, Surrey GU7 1XR, United Kingdom Colin J. Limpus Environmental Sciences, Environmental Protection Agency, Brisbane, Queensland 4002, Australia Fred T. Mackenzie Department of Oceanography, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA Gill Malin School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom Cecilie Mauritzen Norwegian Meteorological Institute, Blindern, 0313 Oslo, Norway Mark G. Meekan Australian Institute of Marine Science, Casuarina MC, Northern Territory 0811, Australia Michael P. Meredith British Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom Nova Mieszkowska Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom Jo´n O´lafsson University of Iceland and Marine Research Institute, IS-121 Reykjavik, Iceland Charlie Paull Monterey Bay Aquarium Research Institute, Moss Landing, California 95039, USA Milagros Penela-Arenaz Departamento de Ecoloxı´a e Bioloxı´a Animal, Facultade de Ciencias do Mar, Universidade de Vigo, 36310 Vigo, Spain Elvira S. Poloczanska Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Cleveland, Queensland 4163, Australia Corinne Le Que´re´ British Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom and School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom

viii

Contributors

Philip C. Reid Sir Alister Hardy Foundation for Ocean Science, and Marine Biological Association of the UK, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom; Marine Institute, University of Plymouth, Plymouth PL4 8AA, United Kingdom Eric Rignot University of California - Irvine, Croul Hall, Irvine, California 92697, USA; and Jet Propulsion Laboratory, Pasadena, California 91214, USA Koji Shimada Faculty of Marine Science, Department of Ocean Sciences, Tokyo University of Marine Science and Technology, 4-5-7, Konan, Minato-ku, Tokyo 108-8477, Japan David W. Sims Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom and Marine Biology and Ecology Research Centre, School of Biological Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, United Kingdom Mike Sparrow SCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United Kingdom Elsa Va´zquez Departamento de Ecoloxı´a e Bioloxı´a Animal, Facultade de Ciencias do Mar, Universidade de Vigo, 36310 Vigo, Spain Meike Vogt School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom Craig Wallace SCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United Kingdom Zhaomin Wang British Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom Richard Washington School of Geography and the Environment, Oxford University Centre for the Environment (Dyson Perrins Building), University of Oxford, Oxford OX1 3QY, United Kingdom

CONTENTS

Contributors to Volume 56 Series Contents for Last Fifteen Years

v xi

1. Impacts of the Oceans on Climate Change

1

Philip C. Reid, Astrid C. Fischer, Emily Lewis-Brown, Michael P. Meredith, Mike Sparrow, Andreas J. Andersson, Avan Antia, Nicholas R. Bates, Ulrich Bathmann, Gregory Beaugrand, Holger Brix, Stephen Dye, Martin Edwards, Tore Furevik, Reidun Gangstø, Hja´lmar Ha´tu´n, Russell R. Hopcroft, Mike Kendall, Sabine Kasten, Ralph Keeling, Corinne Le Que´re´, ´ lafsson, Charlie Paull, Fred T. Mackenzie, Gill Malin, Cecilie Mauritzen, Jo´n O Eric Rignot, Koji Shimada, Meike Vogt, Craig Wallace, Zhaomin Wang, and Richard Washington 1. Introduction 2. Ocean Physics, Temperature, Circulation, Sea-Level Rise and the Hydrological Cycle 3. Primary Production: Plankton, Light and Nutrients 4. The Solubility, Biological and Continental Shelf Carbon Pumps 5. Ocean Acidification and the Carbonate Pump 6. A Special Case: The Arctic and Seas Adjacent to Greenland 7. The Southern Ocean and Climate 8. Climate Models 9. Conclusions and Recommendations Appendix: Workshop Participants Acknowledgements References

2. Vulnerability of Marine Turtles to Climate Change

5 12 27 51 62 80 93 106 115 126 127 127

151

Elvira S. Poloczanska, Colin J. Limpus, and Graeme C. Hays 1. 2. 3. 4. 5. 6. 7.

Introduction Marine Turtle Biology and Life History Observed and Projected Changes in Oceans and Atmosphere Climate Change Impacts on Marine Turtles Responses to Past Climate Change Adaptation and Resilience Global Trends

152 154 159 163 185 187 189 ix

x

Contents

8. Recommendations Acknowledgements References

3. Effects of Climate Change and Commercial Fishing on Atlantic Cod Gadus morhua

189 191 191

213

Nova Mieszkowska, Martin J. Genner, Stephen J. Hawkins, and David W. Sims 1. Introduction 2. Impacts of Climate Change 3. Impacts of Fishing 4. Population-Level Impacts of Fishing and Climate Change 5. Monitoring Status and Recovery of North Sea Cod: A Case Study 6. Concluding Remarks Acknowledgements References

4. Susceptibility of Sharks, Rays and Chimaeras to Global Extinction

214 222 238 245 249 250 252 252

275

Iain C. Field, Mark G. Meekan, Rik C. Buckworth, and Corey J. A. Bradshaw 1. 2. 3. 4. 5.

Introduction Chondrichthyan Life History Past and Present Threats Chondrichthyan Extinction Risk Implications of Chondrichthyan Species Loss on Ecosystem Structure, Function and Stability 6. Synthesis and Knowledge Gaps 7. Concluding Remarks Acknowledgements References

5. Effects of the Prestige Oil Spill on the Biota of NW Spain: 5 Years of Learning

277 281 284 308 328 335 341 343 343

365

Milagros Penela-Arenaz, Juan Bellas, and Elsa Va´zquez 1. Introduction 2. Effects of the Prestige Oil Spill on the Marine Biota 3. Conclusion References Taxonomic Index Subject Index

366 373 386 390 397 401

SERIES CONTENTS

FOR

LAST FIFTEEN YEARS*

Volume 30, 1994. Vincx, M., Bett, B. J., Dinet, A., Ferrero, T., Gooday, A. J., Lambshead, P. J. D., Pfannku¨che, O., Soltweddel, T. and Vanreusel, A. Meiobenthos of the deep Northeast Atlantic. pp. 1–88. Brown, A. C. and Odendaal, F. J. The biology of oniscid isopoda of the genus Tylos. pp. 89–153. Ritz, D. A. Social aggregation in pelagic invertebrates. pp. 155–216. Ferron, A. and Legget, W. C. An appraisal of condition measures for marine fish larvae. pp. 217–303. Rogers, A. D. The biology of seamounts. pp. 305–350. Volume 31, 1997. Gardner, J. P. A. Hybridization in the sea. pp. 1–78. Egloff, D. A., Fofonoff, P. W. and Onbe´, T. Reproductive behaviour of marine cladocerans. pp. 79–167. Dower, J. F., Miller, T. J. and Leggett, W. C. The role of microscale turbulence in the feeding ecology of larval fish. pp. 169–220. Brown, B. E. Adaptations of reef corals to physical environmental stress. pp. 221–299. Richardson, K. Harmful or exceptional phytoplankton blooms in the marine ecosystem. pp. 301–385. Volume 32, 1997. Vinogradov, M. E. Some problems of vertical distribution of mesoand macroplankton in the ocean. pp. 1–92. Gebruk, A. K., Galkin, S. V., Vereshchaka, A. J., Moskalev, L. I. and Southward, A. J. Ecology and biogeography of the hydrothermal vent fauna of the Mid-Atlantic Ridge. pp. 93–144. Parin, N. V., Mironov, A. N. and Nesis, K. N. Biology of the Nazca and Sala y Gomez submarine ridges, an outpost of the Indo-West Pacific fauna in the eastern Pacific Ocean: composition and distribution of the fauna, its communities and history. pp. 145–242. Nesis, K. N. Goniatid squids in the subarctic North Pacific: ecology, biogeography, niche diversity, and role in the ecosystem. pp. 243–324. Vinogradova, N. G. Zoogeography of the abyssal and hadal zones. pp. 325–387. Zezina, O. N. Biogeography of the bathyal zone. pp. 389–426. *The full list of contents for volumes 1–37 can be found in volume 38.

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Series Contents for Last Fifteen Years

Sokolova, M. N. Trophic structure of abyssal macrobenthos. pp. 427–525. Semina, H. J. An outline of the geographical distribution of oceanic phytoplankton. pp. 527–563. Volume 33, 1998. Mauchline, J. The biology of calanoid copepods. pp. 1–660. Volume 34, 1998. Davies, M. S. and Hawkins, S. J. Mucus from marine molluscs. pp. 1–71. Joyeux, J. C. and Ward, A. B. Constraints on coastal lagoon fisheries. pp. 73–199. Jennings, S. and Kaiser, M. J. The effects of fishing on marine ecosystems. pp. 201–352. Tunnicliffe, V., McArthur, A. G. and McHugh, D. A biogeographical perspective of the deep-sea hydrothermal vent fauna. pp. 353–442. Volume 35, 1999. Creasey, S. S. and Rogers, A. D. Population genetics of bathyal and abyssal organisms. pp. 1–151. Brey, T. Growth performance and mortality in aquatic macrobenthic invertebrates. pp. 153–223. Volume 36, 1999. Shulman, G. E. and Love, R. M. The biochemical ecology of marine fishes. pp. 1–325. Volume 37, 1999. His, E., Beiras, R. and Seaman, M. N. L. The assessment of marine pollution—bioassays with bivalve embryos and larvae. pp. 1–178. Bailey, K. M., Quinn, T. J., Bentzen, P. and Grant, W. S. Population structure and dynamics of walleye pollock, Theragra chalcogramma. pp. 179–255. Volume 38, 2000. Blaxter, J. H. S. The enhancement of marine fish stocks. pp. 1–54. Bergstro¨m, B. I. The biology of Pandalus. pp. 55–245. Volume 39, 2001. Peterson, C. H. The ‘‘Exxon Valdez’’ oil spill in Alaska: acute indirect and chronic effects on the ecosystem. pp. 1–103. Johnson, W. S., Stevens, M. and Watling, L. Reproduction and development of marine peracaridans. pp. 105–260.

Series Contents for Last Fifteen Years

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Rodhouse, P. G., Elvidge, C. D. and Trathan, P. N. Remote sensing of the global light-fishing fleet: an analysis of interactions with oceanography, other fisheries and predators. pp. 261–303. Volume 40, 2001. Hemmingsen, W. and MacKenzie, K. The parasite fauna of the Atlantic cod, Gadus morhua L. pp. 1–80. Kathiresan, K. and Bingham, B. L. Biology of mangroves and mangrove ecosystems. pp. 81–251. Zaccone, G., Kapoor, B. G., Fasulo, S. and Ainis, L. Structural, histochemical and functional aspects of the epidermis of fishes. pp. 253–348. Volume 41, 2001. Whitfield, M. Interactions between phytoplankton and trace metals in the ocean. pp. 1–128. Hamel, J.-F., Conand, C., Pawson, D. L. and Mercier, A. The sea cucumber Holothuria scabra (Holothuroidea: Echinodermata): its biology and exploitation as beche-de-Mer. pp. 129–223. Volume 42, 2002. Zardus, J. D. Protobranch bivalves. pp. 1–65. Mikkelsen, P. M. Shelled opisthobranchs. pp. 67–136. Reynolds, P. D. The Scaphopoda. pp. 137–236. Harasewych, M. G. Pleurotomarioidean gastropods. pp. 237–294. Volume 43, 2002. Rohde, K. Ecology and biogeography of marine parasites. pp. 1–86. Ramirez Llodra, E. Fecundity and life-history strategies in marine invertebrates. pp. 87–170. Brierley, A. S. and Thomas, D. N. Ecology of southern ocean pack ice. pp. 171–276. Hedley, J. D. and Mumby, P. J. Biological and remote sensing perspectives of pigmentation in coral reef organisms. pp. 277–317. Volume 44, 2003. Hirst, A. G., Roff, J. C. and Lampitt, R. S. A synthesis of growth rates in epipelagic invertebrate zooplankton. pp. 3–142. Boletzky, S. von. Biology of early life stages in cephalopod molluscs. pp. 143–203. Pittman, S. J. and McAlpine, C. A. Movements of marine fish and decapod crustaceans: process, theory and application. pp. 205–294. Cutts, C. J. Culture of harpacticoid copepods: potential as live feed for rearing marine fish. pp. 295–315.

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Volume 45, 2003. Cumulative Taxonomic and Subject Index. Volume 46, 2003. Gooday, A. J. Benthic foraminifera (Protista) as tools in deep-water palaeoceanography: environmental influences on faunal characteristics. pp. 1–90. Subramoniam, T. and Gunamalai, V. Breeding biology of the intertidal sand crab, Emerita (Decapoda: Anomura). pp. 91–182 Coles, S. L. and Brown, B. E. Coral bleaching—capacity for acclimatization and adaptation. pp. 183–223. Dalsgaard J., St. John M., Kattner G., Mu¨ller-Navarra D. and Hagen W. Fatty acid trophic markers in the pelagic marine environment. pp. 225–340. Volume 47, 2004. Southward, A. J., Langmead, O., Hardman-Mountford, N. J., Aiken, J., Boalch, G. T., Dando, P. R., Genner, M. J., Joint, I., Kendall, M. A., Halliday, N. C., Harris, R. P., Leaper, R., Mieszkowska, N., Pingree, R. D., Richardson, A. J., Sims, D.W., Smith, T., Walne, A. W. and Hawkins, S. J. Long-term oceanographic and ecological research in the western English Channel. pp. 1–105. Queiroga, H. and Blanton, J. Interactions between behaviour and physical forcing in the control of horizontal transport of decapod crustacean larvae. pp. 107–214. Braithwaite, R. A. and McEvoy, L. A. Marine biofouling on fish farms and its remediation. pp. 215–252. Frangoulis, C., Christou, E. D. and Hecq, J. H. Comparison of marine copepod outfluxes: nature, rate, fate and role in the carbon and nitrogen cycles. pp. 253–309. Volume 48, 2005. Canfield, D. E., Kristensen, E. and Thamdrup, B. Aquatic Geomicrobiology. pp. 1–599. Volume 49, 2005. Bell, J. D., Rothlisberg, P. C., Munro, J. L., Loneragan, N. R., Nash, W. J., Ward, R. D. and Andrew, N. L. Restocking and stock enhancement of marine invertebrate fisheries. pp. 1–358. Volume 50, 2006. Lewis, J. B. Biology and ecology of the hydrocoral Millepora on coral reefs. pp. 1–55.

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Harborne, A. R., Mumby, P. J., Micheli, F., Perry, C. T., Dahlgren, C. P., Holmes, K. E., and Brumbaugh, D. R. The functional value of Caribbean coral reef, seagrass and mangrove habitats to ecosystem processes. pp. 57–189. Collins, M. A. and Rodhouse, P. G. K. Southern ocean cephalopods. pp. 191–265. Tarasov, V. G. EVects of shallow-water hydrothermal venting on biological communities of coastal marine ecosystems of the western Pacific. pp. 267–410. Volume 51, 2006. Elena Guijarro Garcia. The fishery for Iceland scallop (Chlamys islandica) in the Northeast Atlantic. pp. 1–55. JeVrey, M. Leis. Are larvae of demersal fishes plankton or nekton? pp. 57–141. John C. Montgomery, Andrew Jeffs, Stephen D. Simpson, Mark Meekan and Chris Tindle. Sound as an orientation cue for the pelagic larvae of reef fishes and decapod crustaceans. pp. 143–196. Carolin E. Arndt and Kerrie M. Swadling. Crustacea in Arctic and Antarctic sea ice: Distribution, diet and life history strategies. pp. 197–315. Volume 52, 2007. Leys, S. P., Mackie, G. O. and Reiswig, H. M. The Biology of Glass Sponges. pp. 1–145. Garcia E. G. The Northern Shrimp (Pandalus borealis) Offshore Fishery in the Northeast Atlantic. pp. 147–266. Fraser K. P. P. and Rogers A. D. Protein Metabolism in Marine Animals: The underlying Mechanism of Growth. pp. 267–362. Volume 53, 2008. Dustin J. Marshall and Michael J. Keough. The Evolutionary Ecology of Offspring Size in Marine Invertebrates. pp. 1–60. Kerry A. Naish, Joseph E. Taylor III, Phillip S. Levin, Thomas P. Quinn, James R. Winton, Daniel Huppert, and Ray Hilborn. An Evaluation of the Effects of Conservation and Fishery Enhancement Hatcheries on Wild Populations of Salmon. pp. 61–194. Shannon Gowans, Bernd Wu¨rsig, and Leszek Karczmarski. The Social Structure and Strategies of Delphinids: Predictions Based on an Ecological Framework. pp. 195–294.

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Volume 54, 2008. Bridget S. Green. Maternal Effects in Fish Populations. pp. 1–105. Victoria J. Wearmouth and David W. Sims. Sexual Segregation in Marine Fish, Reptiles, Birds and Mammals: Behaviour Patterns, Mechanisms and Conservation Implications. pp. 107–170. David W. Sims. Sieving a Living: A Review of the Biology, Ecology and Conservation Status of the Plankton-Feeding Basking Shark Cetorhinus Maximus. pp. 171–220. Charles H. Peterson, Kenneth W. Able, Christin Frieswyk DeJong, Michael F. Piehler, Charles A. Simenstad, and Joy B. Zedler. Practical Proxies for Tidal Marsh Ecosystem Services: Application to Injury and Restoration. pp. 221–266. Volume 55, 2008. Annie Mercier and Jean-Franc¸ois Hamel. Introduction. pp. 1–6. Annie Mercier and Jean-Franc¸ois Hamel. Gametogenesis. pp. 7–72. Annie Mercier and Jean-Franc¸ois Hamel. Spawning. pp. 73–168. Annie Mercier and Jean-Franc¸ois Hamel. Discussion. pp. 169–194.

C H A P T E R

O N E

Impacts of the Oceans on Climate Change Philip C. Reid,*,†,‡ Astrid C. Fischer,* Emily Lewis-Brown,§ Michael P. Meredith,} Mike Sparrow,** Andreas J. Andersson,†† Avan Antia,‡‡ Nicholas R. Bates,‡‡ Ulrich Bathmann,§§ Gregory Beaugrand,*,}} Holger Brix,*** Stephen Dye,††† Martin Edwards,* Tore Furevik,‡‡‡ Reidun Gangstø,§§§ Hja´lmar Ha´tu´n,}}} Russell R. Hopcroft,**** Mike Kendall,†††† Sabine Kasten,§§ Ralph Keeling,‡‡‡‡ Corinne Le Que´re´,},§§§§ Fred T. Mackenzie,}}}} Gill Malin,§§§§ Cecilie Mauritzen,***** Jo´n O´lafsson,††††† Charlie Paull,‡‡‡‡‡ Eric Rignot,§§§§§ Koji Shimada,}}}}} Meike Vogt,§§§§ Craig Wallace,** Zhaomin Wang,} and Richard Washington****** Contents 5 6 6 7 7 7

1. Introduction 1.1. Heat budget 1.2. Ocean circulation 1.3. Tropical storms 1.4. Storage and transfer of CO2 1.5. Acidification *

Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom Marine Institute, University of Plymouth, Plymouth PL4 8AA, United Kingdom { Marine Biological Association of the UK, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom } WWF-UK, Panda House, Weyside Park, Godalming, Surrey GU7 1XR, United Kingdom } British Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom ** SCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United Kingdom {{ Bermuda Institute of Ocean Sciences, St. George’s GE 01, Bermuda {{ Christian-Albrechts-University of Kiel, 24119 Kiel, Germany }} Alfred Wegener Institute, D-27570 Bremerhaven, Germany }} Centre National de la Recherche Scientifique, Laboratoire d’Oce´anologie et de Ge´osciences, Station Marine, Universite´ des Sciences et Technologies de Lille, 62930 Wimereux, France *** Department of Atmospheric and Oceanic Sciences, University of California - Los Angeles, Los Angeles, California 90095-1567, USA {{{ Centre for Environment, Fisheries and Aquaculture Science (Cefas), Lowestoft, Suffolk NR33 OHT, United Kingdom {{{ Geophysical Institute, N-5007 Bergen, Norway {

Advances in Marine Biology, Volume 56 ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56001-4

#

2009 Elsevier Ltd. All rights reserved.

1

2

Philip C. Reid et al.

1.6. Polar regions 1.7. Plankton productivity, oxygen content and upwelling 1.8. Microbes 1.9. Nutrients 1.10. Sea-level rise 1.11. Structure of the chapter 1.12. Summary conclusions and recommendations 2. Ocean Physics, Temperature, Circulation, Sea-Level Rise and the Hydrological Cycle 2.1. Changes in ocean temperature 2.2. Changes in salinity 2.3. Global circulation 2.4. Upwelling 2.5. Changing physics of tropical seas in a warming ocean 2.6. Sea-level rise 2.7. Destabilisation of ice sheets/glaciers 2.8. Concluding comments 3. Primary Production: Plankton, Light and Nutrients 3.1. Oceanic primary production 3.2. Microbial plankton 3.3. Phyto- and zooplankton 3.4. Chlorophyll and primary production 3.5. Plankton biodiversity functional groups and ocean biomes 3.6. Benthos 3.7. Migration of plankton, fish and benthos towards the poles 3.8. Oxygen 3.9. Nutrients in general 3.10. Other gases and aerosols 3.11. Concluding comments 4. The Solubility, Biological and Continental Shelf Carbon Pumps 4.1. The ocean carbon cycle 4.2. Ocean carbon pumps }}}

8 9 9 9 10 10 12 12 13 16 17 22 23 24 25 26 27 28 30 31 33 34 36 37 38 40 47 51 51 51 54

University of Bern, 3012 Bern, Switzerland Faroese Fisheries Laboratory. FO-110 To´rshavn, Faroe Islands **** Institute of Marine Science, University of Alaska Fairbanks, Fairbanks, Alaska 99775-7220, USA {{{{ Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, United Kingdom {{{{ Scripps CO2 Program, La Jolla, California 92093-0244, USA }}}} School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom }}}} Department of Oceanography, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA ***** Norwegian Meteorological Institute, Blindern, 0313 Oslo, Norway {{{{{ University of Iceland and Marine Research Institute, IS-121 Reykjavik, Iceland {{{{{ Monterey Bay Aquarium Research Institute, Moss Landing, California 95039, USA }}}}} University of California - Irvine, Croul Hall, Irvine, California 92697, USA; and Jet Propulsion Laboratory, Pasadena, California 91214, USA }}}}} Faculty of Marine Science, Department of Ocean Sciences, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, Tokyo 108-8477, Japan ****** School of Geography and the Environment, Oxford University Centre for the Environment (Dyson Perrins Building), University of Oxford, Oxford OX1 3QY, United Kingdom }}}

Impacts of the Oceans on Climate Change

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6.

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8.

9.

4.3. Role of the four ocean carbon pumps 4.4. Species biodiversity and functional groups 4.5. Global and regional information 4.6. Ocean fertilisation 4.7. Concluding comments Ocean Acidification and the Carbonate Pump 5.1. The buffering of climate change by the oceans 5.2. Carbonate formation 5.3. Carbonate dissolution 5.4. Uptake of CO2 by the ocean 5.5. Projected future levels of acidification 5.6. Regional variation in acidification 5.7. Carbonate pump 5.8. Nutrients 5.9. Palaeo-comparisons 5.10. Concluding comments A Special Case: The Arctic and Seas Adjacent to Greenland 6.1. Climate change in the Arctic Ocean and Subarctic seas 6.2. The circulation of the Arctic Ocean and sub-polar seas 6.3. Runoff from Arctic rivers 6.4. Ice formation in the Arctic 6.5. Observed changes in Arctic sea-ice cover 6.6. Trigger factors for initial sea-ice reductions 6.7. Projected changes in Arctic sea-ice cover 6.8. The Greenland ice sheet 6.9. Methane and feedbacks to climate change 6.10. Arctic ocean ecosystems 6.11. Modelling 6.12. Concluding comments The Southern Ocean and Climate 7.1. Role of the Southern Ocean in climate 7.2. Observed changes in the Southern Ocean region 7.3. The future 7.4. Concluding comments Climate Models 8.1. Ocean–climate feedbacks 8.2. Heat uptake 8.3. Heat transport 8.4. Water cycle 8.5. Sea-ice 8.6. Gas exchange/carbon uptake (CO2, N2O, DMS) 8.7. Retro-modelling of past climate change 8.8. Final comments Conclusions and Recommendations 9.1. A decade ago

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9.2. Warming waters 9.3. Freshening waters 9.4. Changing ocean circulation and sea-level 9.5. The MOC and cooling of NW Europe 9.6. Tropical storms 9.7. Primary production, biodiversity and non-native species 9.8. Oxygen 9.9. Nutrients 9.10. Ocean uptake of carbon dioxide 9.11. Acidification 9.12. A special case: The Arctic 9.13. Methane 9.14. Greenland ice sheet 9.15. The Southern Ocean 9.16. Modelling 9.17. Final concluding comments Appendix: Workshop Participants Acknowledgements References

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Abstract The oceans play a key role in climate regulation especially in part buffering (neutralising) the effects of increasing levels of greenhouse gases in the atmosphere and rising global temperatures. This chapter examines how the regulatory processes performed by the oceans alter as a response to climate change and assesses the extent to which positive feedbacks from the ocean may exacerbate climate change. There is clear evidence for rapid change in the oceans. As the main heat store for the world there has been an accelerating change in sea temperatures over the last few decades, which has contributed to rising sea-level. The oceans are also the main store of carbon dioxide (CO2), and are estimated to have taken up 40% of anthropogenic-sourced CO2 from the atmosphere since the beginning of the industrial revolution. A proportion of the carbon uptake is exported via the four ocean ‘carbon pumps’ (Solubility, Biological, Continental Shelf and Carbonate Counter) to the deep ocean reservoir. Increases in sea temperature and changing planktonic systems and ocean currents may lead to a reduction in the uptake of CO2 by the ocean; some evidence suggests a suppression of parts of the marine carbon sink is already underway. While the oceans have buffered climate change through the uptake of CO2 produced by fossil fuel burning this has already had an impact on ocean chemistry through ocean acidification and will continue to do so. Feedbacks to climate change from acidification may result from expected impacts on marine organisms (especially corals and calcareous plankton), ecosystems and biogeochemical cycles. The polar regions of the world are showing the most rapid responses to climate change. As a result of a strong ice–ocean influence, small changes in temperature, salinity and ice cover may trigger large and sudden

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changes in regional climate with potential downstream feedbacks to the climate of the rest of the world. A warming Arctic Ocean may lead to further releases of the potent greenhouse gas methane from hydrates and permafrost. The Southern Ocean plays a critical role in driving, modifying and regulating global climate change via the carbon cycle and through its impact on adjacent Antarctica. The Antarctic Peninsula has shown some of the most rapid rises in atmospheric and oceanic temperature in the world, with an associated retreat of the majority of glaciers. Parts of the West Antarctic ice sheet are deflating rapidly, very likely due to a change in the flux of oceanic heat to the undersides of the floating ice shelves. The final section on modelling feedbacks from the ocean to climate change identifies limitations and priorities for model development and associated observations. Considering the importance of the oceans to climate change and our limited understanding of climate-related ocean processes, our ability to measure the changes that are taking place are conspicuously inadequate. The chapter highlights the need for a comprehensive, adequately funded and globally extensive ocean observing system to be implemented and sustained as a high priority. Unless feedbacks from the oceans to climate change are adequately included in climate change models, it is possible that the mitigation actions needed to stabilise CO2 and limit temperature rise over the next century will be underestimated.

1. Introduction Through many natural processes and feedback mechanisms, the oceans1 regulate climate on a range of timescales, from geological and millennial to decadal, interannual and shorter. Over the last two centuries, because of the ability of the oceans to take up heat and absorb greenhouse gases such as carbon dioxide (CO2), they have partially buffered (neutralised) the effects of increasing levels of human-sourced greenhouse gases in the atmosphere. There is, however, clear evidence that many of the processes that contribute to this buffering role have been changing, in some cases almost certainly as a response to climate change. These processes provide a number of feedbacks that may be positive (reinforcing) or negative (ameliorating) to climate change. There has been insufficient attention paid in the past to the key role that the oceans play in regulating climate and particularly to the feedback mechanisms that have the potential to and, in some cases, may already be intensifying climate change. For example, the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in 2007 included as much information as was possible at that time on the ocean carbon cycle, 1

All the oceans are interconnected and are often referred to in the singular. In this chapter, the plural version is generally used.

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but recognised that many feedback mechanisms were incompletely included. This chapter explores the role of the oceans in regulating the climate and especially those changes that can accelerate climate change and have important implications for achieving stabilisation targets to mitigate climate change. Some of the key issues that are addressed are summarised below, followed by an outline of the structure of the chapter and a brief summary of conclusions and recommendations.

1.1. Heat budget Comprising 97% of the Earth’s water and covering 71% of the surface, the oceans are the main heat store for the world. Over the last few decades there has been a rapid and accelerating change in ocean temperatures and an increase in heat storage affecting seasonal and decadal variability in climate, heat transport, ocean circulation, stratification, biology and biogeochemistry. All of these ocean factors can lead to feedbacks to climate change. The main positive feedbacks derive from rising temperatures and changing salinities. Higher temperatures are causing a loss of Arctic sea-ice, which feeds back to warming and climate change through many processes, including the potential release of the potent greenhouse gas methane. Changes in the oceans have led to an expansion of tropical/subtropical stratified (layered) waters, changing patterns of wind and altered ocean currents. Together these changes are likely to have led to a net reduction in the drawdown of CO2 from the air into the ocean. However, expansion of the suboxic layers in the tropics and Atlantic Ocean (but not in the Indian Ocean) may, on the contrary, increase the preservation of organic matter and thus provide a sink for CO2. A rising sea-level has also resulted from increasing temperatures through thermal expansion of the oceans, as well as shrinking polar ice sheets and glaciers. Some of these feedbacks may be compounded by the impacts of ocean acidification from CO2.

1.2. Ocean circulation Marked changes in salinity have been observed, reflecting an alteration in the hydrological cycle of the world through changes in precipitation, evaporation, river runoff and ice melt, with especially clear reductions in the North Atlantic, and in deeper waters and some upper layers of the Southern Ocean. Changes in ocean temperature have also been observed, with some regions warming very rapidly. Changes in buoyancy forcing (heat and salinity) and mechanical forcing (e.g. winds and tides) have the potential to change the large-scale circulation of the global ocean, including its overturning circulation and horizontal flows [Thermohaline Circulation (THC)/Meridional Overturning Circulation (MOC), commonly known as the ‘global conveyor belt’]. The general consensus from modelling

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projections for the twenty-first century is that there is likely to be a reduction in the strength of the Atlantic MOC by up to 50% of its current strength. This will not necessarily lead to a cooling of Europe, but more likely to a slower rate of warming, because the general atmospheric warming tends to dominate over the cooling expected from a reduced MOC. Recent increases in the poleward ocean heat flux are likely to have played a central role in the decline of Arctic sea-ice. The signal from the changes in the Arctic has, and is expected to continue to, propagate south through subarctic seas on either side of Greenland, to modulate the Atlantic thermohaline overturning.

1.3. Tropical storms The intensity of tropical storms has increased by 75% from 1970 to 2004 in the North Atlantic and western North Pacific and a global increase in their destructiveness is documented. The possible feedback role to climate change is still unclear, but it is expected that as global temperatures rise, storm intensity and possibly their frequency may increase.

1.4. Storage and transfer of CO2 The oceans are the main store for the greenhouse gas CO2, each year taking in about 40% of anthropogenic CO2 from the atmosphere and exporting carbon via physical and biological processes to the deep ocean reservoir. Emissions of CO2 from human sources have already grown to over 7 GtC (gigatonnes carbon) per year. The sensitivity of atmosphere/ocean fluxes of the carbon cycle is particularly evident. Increases in sea surface temperature (SST) and changing biological systems and ocean currents may lead to a reduction in the uptake of CO2 by the oceans. Measurements taken over the last few decades of atmospheric greenhouse gases and ocean observations are indicating that a reduction in the buffering capacity of the oceans is underway in some regions. A slowing down of the ocean sink and any large change to the different ocean carbon pumps could lead to an acceleration of levels of atmospheric CO2 and thus to intensified climate change.

1.5. Acidification Through the uptake of nearly 50% of CO2 produced by burning fossil fuel over time, the oceans have buffered the cause and effects of climate change. This large addition of CO2 to the oceans has also had a profound effect on ocean chemistry. As CO2 dissolves into the ocean, it reacts with seawater, forming carbonic acid which causes a reduction in pH (lower alkalinity), a process that has been termed ‘ocean acidification’. Since the beginning of the industrial revolution, pH has reduced by 0.1 units (representing a 30%

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increase in Hþ ions), a substantial amount considering that the units are logarithmic. Rapid acidification is expected to continue to the extent that in 50 years time the oceans are predicted to be less alkaline than at any time in the past 20, and likely 55, million years. Feedbacks to climate change from ocean acidification may result from expected impacts on marine organisms, ecosystems and biogeochemical cycles. Planktonic plants (phytoplankton) comprise 50% of global primary production and play a crucial role in the uptake of CO2 from the atmosphere. There is concern that oceanic organisms will not be able to adapt to the rate and scale of change now underway. These organisms are vital to the way the oceans draw down CO2 from the atmosphere and play a profound role in the biological pump and the way it transfers CO2 to the deep ocean store. In addition, the effects of projected changes in the pH of the oceans on corals and plankton community structure are likely to have profound implications for biodiversity, marine living resources and again with likely feedback to the carbon cycle.

1.6. Polar regions The polar regions are thought to be especially susceptible to planetary-scale climate change, and a number of indicators of this have been observed. For example, there have been considerable reductions in Arctic sea-ice, rapidly rising temperatures at the Antarctic Peninsula, and a break-up of a number of Antarctic ice shelves. Arctic sea-ice has retreated rapidly in recent years, whereas Antarctic sea-ice has shown a more regional pattern of change— decreasing in some sectors, but increasing in others, and with an overall small increase. Much of the old multi-year ice in the Arctic has been discharged so that the ice now found there is thinner and younger. Sea-ice loss is acting as a trigger for further regional warming, potentially contributing to melting of the Greenland ice sheet and release of methane, a potent greenhouse gas. In the Arctic, release of methane from marine and terrestrial sources is particularly likely to contribute to positive feedback effects to climate change. In the Southern Ocean, the regional sea-ice changes have the potential to modulate the formation of dense waters, with implications for the uptake of CO2 from the atmosphere, as well as oceanic fluxes of heat and freshwater. The carbon storage capability of the circumpolar Southern Ocean is reported to have decreased in recent decades, leaving more CO2 in the atmosphere, although investigations are ongoing into this phenomenon. If the regional average temperature rise above Greenland increases above some threshold, estimated as 3 C above pre-industrial values (which equates to a global average temperature of 1–2 C), it is projected that the ongoing contraction of the Greenland ice sheet would be irreversible. Without effective mitigation of carbon emissions, global warming could exceed this value during the twenty-first century, leading to a total melting

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of the ice sheet and a rise of several metres in sea-level over a timescale that is estimated to take centuries to thousands of years. The rate of loss of Arctic sea-ice was underestimated in the IPCC report in 2007, which, along with omission of some feedbacks, may have led to an underestimate of the cuts in emissions of greenhouse gases necessary to stabilise climate change at given atmospheric levels. The current rate of change in the Arctic, and its active feedbacks, have been triggered by a relatively small increase in global average temperature rise.

1.7. Plankton productivity, oxygen content and upwelling Evidence is accumulating for increases in the intensity of upwelling in the major upwelling regions of the world, leading to a rise in phytoplankton production, anoxia and release of greenhouse gases. Anoxia is the lack of oxygen (O2), an element that plays a direct and important role in the biogeochemical cycling of carbon and nitrogen. It is fundamental to all aerobic organisms, including those living in the dark deep sea. Areas of the ocean that stagnate can become anoxic due to the continual consumption of O2 by living organisms. The main feedbacks to climate from plankton are via potential reductions in CO2 drawdown and in the efficiency of the biological pump.

1.8. Microbes The role of microbes in climate and climate change is crucially important, but little understood and poorly quantified, especially in terms of their contribution to biogeochemical and nutrient cycling, microbial diversity and feedbacks. A considerable increase in research effort is required to improve understanding of the impacts that microbes have on the planetary-scale climate system.

1.9. Nutrients The contrast between biological and nutrient interactions within oceanic and terrestrial systems means that the oceans respond much more rapidly to climate change and feedbacks from oceanic biology. Therefore, biogeochemical interactions are likely to take effect more quickly. Strong regional changes in nutrients are expected in the future, dependent on variability in wet precipitation, evaporation, wave storminess, mixing and the depth of stratification. Precipitation is expected to increase especially in tropical regions. At present, it is not possible to predict future trends because of the localisation of the changes and our lack of knowledge of complex ecosystem interactions. It is also not clear how all the regional responses will add up to a global mean. The subtropical gyres play a large role in

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carbonate production and export to depth (carbonate and biological pumps) and are predicted to expand in area, but not in productivity, in a warming world.

1.10. Sea-level rise Sea-level has been rising at the upper end of the IPCC AR4 projections and can contribute to coastal erosion, inundation and salinification of aquifers. Sea-level rise will affect humans in many ways, including the potential displacement of millions of people. Migration of populations and loss of coastal lands will likely lead to changes in land and resource use that have the potential to establish further positive feedbacks to climate change.

1.11. Structure of the chapter The chapter has been organised into sections that reflect the main ocean drivers of climate change and the variables that contribute to them, as shown schematically in Fig. 1.1. Note that this figure focuses on factors interacting with nutrients; the real situation is more complex as the drivers may also directly impact other processes independently of nutrients. Denitrification may also act independently and be linked to atmospheric concentrations of CO2. The physics starts the process with recycling feedbacks at all levels. The other sections examine key elements of ocean–climate interactions covering: Ocean Physics, Circulation and the Hydrological Cycle, Primary Production: Plankton, Light and Nutrients, the Oceanic Carbon Cycle, Ocean Acidification and Modelling. An additional special focus has been placed on the critically important, but still under-studied polar regions, with separate sections on the Arctic and Southern Oceans. Throughout the chapter, our aim has been to provide an assessment of the key processes and feedbacks from the oceans to climate and climate change and, where possible, prioritise their importance. Gaps in knowledge are identified in modelling and research programmes, with a particular reference to observing systems that are needed to adequately assess the scale and speed of change. Some of the positive feedback mechanisms from the oceans to climate change have been insufficiently included in climate modelling and calculations for stabilisation targets. Without these, it is possible that the stabilisation targets for climate mitigation underestimate the action needed to limit global temperature rise within any given limit. The chapter also includes in places a discussion of tipping points (sudden, possibly irreversible changes that might lead to rapid climate change) and a brief discussion on iron fertilisation. The work to produce this chapter was initiated by a Worldwide Fund for Nature (WWF) sponsored workshop in London during March 2008 that was attended by 30 international researchers who are experts in aspects

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Climate change

Atmospheric CO2, other greenhouse gases

Optical properties (light adsorption and albedo)

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(de)nitrifiers

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River input Ocean circulation

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Figure 1.1 Schematic of potential relationship and links between key nutrient drivers and climate change (produced by Carol Turley, Plymouth Marine Laboratory).

of the field. A list of the participants and the themes addressed at the workshop are appended as an Appendix. The science of the chapter has built on the workshop outcomes, recent reports of the IPCC plus new information from the literature, as well as correspondence with experts selected to cover (where possible) all aspects of ocean science. While other activities, such as fishing, whaling, pollution and habitat destruction, also impact the oceans, here we focus only on the interaction between the oceans and climate, without detailed account of these additional impacts. The extent to which positive feedbacks may lead to a potential acceleration of climate change is assessed. Where possible an update and expansion on ocean information covered by IPCC is included. The chapter aims to stimulate and inform debate, provide a useful complement to the work of IPCC and contribute to the preparations for the next

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IPCC review. It is hoped that it will also be of value to other international and national organisations working on climate change and to the research and modelling community in helping to prioritise improvements that need to be included in future research, modelling and observing programmes.

1.12. Summary conclusions and recommendations This chapter demonstrates that the oceans are vital in regulating our climate. They have buffered climate change substantially since the beginning of the industrial revolution, acting as a sponge to carbon dioxide and heat from global warming. While it was assumed this would continue, our chapter gives a warning—even at current warming levels to date, changes underway in our oceans may accelerate warming and its consequences to organisms, and have the potential to intensify climate change itself. In some examples, such as sea-ice loss, this process may already be underway. A concerted effort to better understand the implications of the role of the oceans in regulating the climate is essential to better predict climate change. Where complete understanding is not possible, feedbacks from the oceans to climate change need to be taken account of when planning responses to climate change. It is necessary to apply the precautionary principle in both marine and climate management until a fuller understanding is achieved. Most ocean observing programmes are still funded from research budgets and, other than for some aspects of the physics, have a poor global coverage, especially for deeper waters and for biological and biogeochemical processes. Implementation of an improved ocean observing system is urgently needed to monitor changes in the interactions between the oceans and climate change.

2. Ocean Physics, Temperature, Circulation, Sea-Level Rise and the Hydrological Cycle This section describes how the large changes that have taken place in SST, ocean heat content and salinity over the last century are altering ocean density, with effects on stability (stratification), circulation, mixing and feedbacks to the atmosphere. The consequences of these changes for sealevel, polar ice, the frequency and intensity of tropical storms (hurricanes, cyclones and typhoons) are then examined as are connections to the monsoons and modes of variability such as the El Nin˜o/Southern Oscillation (ENSO). The physical changes in the oceans were well covered in the IPCC AR4 reports as much more is known about the physics of the oceans than other subjects and more data have been collected on temperature and salinity than any other variable.

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Historically, the climate has undergone large natural change, independently of man’s influence, at global and regional scales through geological time, at alternating time intervals ranging from millions to decadal to annual periodicity (Crowley, 1996; CLIVAR brochure: http://www.clivar.org/ publications/other_pubs/latest_clivar_brochure.pdf ). Natural climate variability can be forced by many factors including changes outside the Earth in the Sun and in the orbit of the Earth in relation to the Sun, and by natural events such as volcanic eruptions and oscillatory regional modes of variability such as El Nin˜o, the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) and the MOC (e.g. Chen et al., 2008a,b; Keenlyside et al., 2008; Shindell et al., 2003). Natural changes may also occur very rapidly, as evident in the ice core record of Greenland where the return to cold glacial temperatures in the Younger Dryas abruptly changed around 12,000 years ago with a rapid rise in temperature of approximately 8 C in less than a decade (Brauer et al., 2008). Against this background, the rise in temperature over the last 50 years cannot be explained without including human forcing. Most of the warming since the mid-twentieth century was considered by IPCC AR4 to be very likely due to the observed increase in anthropogenic greenhouse gas concentrations (Alley et al., 2007).

2.1. Changes in ocean temperature 2.1.1. Sea surface temperature On a global scale, SST (the temperature of the upper few metres of the ocean) observations have shown a progressive warming trend of 0.64 C over the last 50 years. A steady increase has been recorded since 1910 other than an apparent peak centred on 1940 (Trenberth et al., 2007). Thompson et al. (2008) have shown recently that this peak is an artefact due to sampling biases. Their results alter the variability, but not the long-term trend. Modelling studies predict that the trend in SST is likely to continue in the twenty-first century, with regional variability. The regional differences include enhanced warming in the Arctic, in the Indian Ocean and along the equator in the eastern Pacific, with a lower rate of warming in the Northwest Atlantic and in the Southern Ocean (Meehl et al., 2007). Warming has been more pronounced in the Southern Ocean over the last 50–70 years (Gille, 2002, 2008) and has changed locally around the Antarctic Peninsula where the very rapid atmospheric warming has been paralleled by an increase in surface ocean temperature of >1 C in summer months since the 1950s (Meredith and King, 2005). Superimposed on the global trend are natural interannual and decadal variability. This is associated in the Atlantic, for example, with the NAO and the Atlantic Multi-decadal Oscillation (AMO), and in the Pacific with the PDO/ENSO. Regional variability may also be marked. In the North

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Atlantic there is asymmetry across the basin with cooling in the Northwest and warming in the Northeast, until recently when the Northwest region also showed strong warming (Hughes et al., 2008). In the tropical Pacific, there is a general warming trend, with reduced zonal patterns and more El Nin˜o type east to west patterns of change. 2.1.2. Ocean heat content The ocean’s main role in climate variability and change is its huge capacity for the transport and storage of heat. On a global scale, ocean warming accounts for more than 90% of the increase in the Earth’s heat content between 1961 and 2003 (Bindoff et al., 2007). For the upper 700 m of the ocean (the water column from the surface to a depth of 700 m inclusive), the latter study estimates an average increase in temperature of 0.1 C, equivalent to a flux of heat into the ocean of 0.2 0.06 W m2. This large increase in heat storage has implications for seasonal and decadal variability in climate, transport and circulation by ocean currents, stratification, biology and biogeochemistry. All of these factors can lead to feedbacks to climate change. Because of its fundamental importance, there have been many studies of changes in ocean heat content. These have revealed deficiencies in both historical and recent global ocean datasets. Analyses have demonstrated significant time-dependent biases in the expendable bathythermograph (XBT) data that dominates the historical archive since the early 1970s until the recent advent of Argo profiling floats. Wijffels et al. (2008) have shown that biases in the fall rate of XBTs are the dominant source of error and that they can be reduced substantially. In addition, the recent cooling of the ocean (Lyman et al., 2006), reported following the introduction of the new Argo observing system, has now been shown to be incorrect and was a result of inadequate quality control in some of the new Argo floats as well as biases in XBTs (Willis et al., 2007). In addition to instrumental biases, there are also significant sampling problems associated with an inadequate ocean database. Palmer et al. (2007) demonstrated that the accuracy of heat content estimates can be improved by determining changes in heat content relative to an isotherm rather than a fixed depth level. They estimate a warming trend of 0.12 0.04 W m2 relative to the 14 C isotherm. Both the XBT instrumental biases and the sampling issues were addressed by Domingues et al. (2008). Compared to the assessment in the most recent IPCC report (Bindoff et al., 2007), their improved estimate of upper-ocean warming is 50% larger for 1961–2003 and 40% smaller for 1993–2003. From 1961 to 2003, their estimate of heat flux into the upper 700 m of the ocean is 0.36 0.06 W m2. The new results for near globally averaged anomalies of ocean heat content (Fig. 1.2) show similar

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Ocean heat content (⫻1022J)

multi-decadal variability to SST. They also reduce the large (but spurious) warming in the early 1970s and the subsequent cooling in the early 1980s that was a feature of previous estimates and which could not be reproduced in climate simulations. Climate models which include the full range of natural and anthropogenic forcing factors reproduce this observed longterm trend and the decadal variability, and demonstrate that violent volcanic eruptions are responsible for significant variability in ocean heat content (Fig. 1.2). However, this new analysis suggests that climate models may slightly underestimate the amount of ocean heat uptake in the upper 700 m for the period 1961–2003 (Domingues et al., 2008). Observations indicate that the deep and abyssal ocean may be absorbing large amounts of heat ( Johnson and Doney, 2006a,b; Johnson et al., 2007, 2008; Ko¨hl et al., 2007). Unfortunately, our historical observations and our current observing systems are inadequate to calculate quantitatively this storage on a global scale (Domingues et al., 2008). There are pronounced regional patterns in ocean warming, including indications of warming of the subtropical ocean gyres in both hemispheres and a poleward expansion of these gyres. For example, Palmer et al. (2007) suggest that the North Atlantic is a region of net heat accumulation over the period 1965–2004. Pronounced decadal variability is evident as a result of wind stress changes with a deepening of the North Atlantic subtropical gyre from 1981 to 2005 following an earlier period from 1959 to 1981 when the thermocline shoaled (Leadbetter et al., 2007). There is also a significant deep warming near the poleward boundary of the subtropical gyre in the South Pacific Ocean (Roemmich et al., 2007). Recent reanalysis of the sparse

15 10 5 0 −5 Chichon

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Figure 1.2 Upper-ocean heat content (grey shading indicates an estimate of one standard deviation error) for the upper 700 m relative to 1961. The straight line is the linear fit for 1961–2003. The global mean stratospheric optical depth (Ammann et al., 2003) (arbitrary scale) at the bottom indicates the timing of major volcanic eruptions. The brown curve is a 3-year running average of these values, included for comparison with the smoothed observations. Figure modified from Domingues et al. (2008).

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Southern Ocean dataset has revealed significant warming (Gille, 2008). However, much remains to be done to identify clearly these regional patterns to understand the dynamics underlying the changes and to evaluate the ability of climate models to simulate the variability.

2.2. Changes in salinity One of the clear statements in the IPCC AR4 report is that while it is impossible to determine the precise origin of recent changes in regional patterns of freshening and salinification of the global ocean they are consistent with an enhanced hydrological cycle (Bindoff et al., 2007). This is largely a consequence of the much smaller volume of observational data available for salinity compared to temperature, especially for the oceans in the Southern Hemisphere, which form two-thirds of the global ocean area. Salinity is, however, still the most measured property in the ocean after temperature and provides important information on the hydrological cycle, including rates of surface freshwater fluxes, transport and ocean mixing, all of which are important components of climate dynamics. Boyer et al. (2005) reinforced at a global scale the basin-wide message of Curry et al. (2003), who showed that a systematic freshening had occurred in high-latitude regions of the Atlantic at all depths in both the southern and northern hemispheres between the periods 1955–1969 and 1985–1999 (Fig. 1.3). The freshening was especially pronounced in the intermediate depth waters of the Labrador Sea and in the deep outflows from the Nordic Seas via the Faroe–Shetland Channel and Denmark Strait. In contrast, higher salinities have been recorded in the intermediate depth (1000–1200 m) waters flowing out of the Mediterranean reflecting the rising deep water salinities recorded from this sea. It is expected that freshening will continue in the Arctic due to ice loss, but the Northwest Atlantic has undergone a rapid change to higher salinities post-1998 due to changes in the circulation of the sub-polar gyre (Ha´tu´n et al., 2005; Holliday et al., 2008) and increases in the salinity of the top 500 m have occurred in the subtropical gyre. Freshening has also occurred in the subtropical gyres of the Indian Ocean (e.g. Bindoff and McDougall, 2000). In general, surface waters in the subtropical gyres of the Indian and Pacific Oceans have a higher salinity although there is evidence of freshening in the tropical Pacific (Delcroix et al., 2007). A large-scale freshening of waters in the Southern Ocean close to Antarctica has been observed, including upper layer waters in the Ross Sea ( Jacobs et al., 2002) and Antarctic Bottom Water, adjacent to a large part of East Antarctica that is derived from the Ross Sea (Rintoul, 2007). Exact causes for the overall freshening are unknown, but glacial ice melt from the West Antarctic ice sheet has been suggested, along with changes in the sea-ice field of the Weddell Sea. Contributing factors to the changes in

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Figure 1.3 South-to-north vertical section of salinity versus depth for the western Atlantic basin, plotted as Salinity difference averaged for the period 1985–1999 minus 1955–1969. Grey colour means that sampling was not sufficient to estimate mean salinity. Acronyms are for the different water masses; see original paper. From Curry et al. (2003).

salinity are alterations in precipitation/evaporation, freshening from melting of ice, reduced ice formation and changes in ocean circulation. The relative contributions of these factors to the large observed changes are still a matter of debate, although changes in evaporation/precipitation are shown to be important by Curry et al. (2003). The increasing differences in the salinity budgets of the Atlantic and Pacific suggest a change in the freshwater budget of the two basins. Bindoff et al. (2007) conclude that pronounced changes in salinity reflect a modification of the Earth’s hydrological cycle with enhanced transport of water in the atmosphere between low and higher latitudes. Combined together, the salinity and temperature changes alter the density distribution and thus stability (stratification) as well as the THC of the ocean, with large potential feedbacks on regional climate and weather conditions such as temperature, storminess and rainfall patterns.

2.3. Global circulation The world’s large-scale ocean circulation is driven by a range of forcing mechanisms (e.g. winds, heating/cooling/salinity-density) and it is technically not possible to separate the currents based on their respective forcing. Nevertheless, there is a strong tradition in oceanography to consider the

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upper-ocean circulation as wind driven and that which reaches the deep oceans as density-driven. Thus, we often speak of the world’s THC as the density-driven circulation that interconnects all the world’s basins and all the ocean depths (see IPCC AR4, 2007 for a definition of the THC). The THC cannot be measured directly in contrast to the sinking and spreading of cold water through the MOC, which is an observable quantity. Even so, the MOC is only observable in principle—in practice, it is prohibitively expensive to observe this circulation in all but a few limited places. This is rather restrictive because the MOC does not circulate in a pipe (in which case it only needs to be observed in one location), rather it recirculates vigorously both in the surface and deep ocean. So most of the inferences about the MOC are from indirect measurements taken from the far more abundant observations of temperature, salinity, pressure, altimetry, etc., rather than from direct current measurements. Changes in heat and freshwater storage can be used to derive changes in transport. Throughout this chapter both concepts (THC and MOC) are used, but what really is meant is the ocean’s large-scale vertical and horizontal overturning circulation. 2.3.1. Meridional overturning circulation in the North Atlantic/Arctic 2.3.1.1. Subtropical measurements Direct measurements of the heat transport associated with the Atlantic MOC indicate a maximum transport at the 26.5 N latitude (e.g. Ganachaud and Wunsch, 2000). At the same latitude, the Gulf Stream component of the MOC is channelled through the Florida Strait, where robust transport measurements have been maintained since 1980 (Baringer and Larsen, 2001). This latitude has been suggested as one of the optimum locations at which to monitor the MOC - to both establish how the system varies naturally, and to seek evidence of any long-term change that may be underway. Based on measurements from ship transects over the past six decades an apparent 30% reduction in the strength of the MOC was calculated by Bryden et al. (2005) (Fig. 1.4). This appears to be driven by an enhanced southwards re-circulation of upper waters by the subtropical gyre, and a compensatory reduction in the deep southwards return leg of the MOC fed by high-latitude, cold, dense waters. The size and rate of this reduction received much attention, exceeding the limits of projected changes for the same time period based on climate model simulations (see Section 8). In response to the ongoing threat of an abrupt MOC change, and the societal implications this could have for Europe, an international collaborative monitoring system was launched to provide a continuous record of Atlantic MOC strength at 26.5 N, as part of the UK-led RAPID Climate Change Programme. Initial results reveal significant short-term (daily) variability in the strength of the MOC implying that the decrease evident in the ship-based

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MOC strength (Sv)

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Figure 1.4 Mean strength of the Atlantic MOC at 26.5 N between 1957 and 2005 and associated error bars. Blue data points are for measurements taken from ships (Bryden et al., 2005). The red data point is an average of observations taken in the first full year of the RAPID monitoring array, plus error bar (Cunningham et al., 2007). Units are Sv (1 Sv ¼ 1 million m3 s1 of water passing the 26.5 N line). Values indicate a northwards net transport for water shallower than 1000 m.

measurements may be, at least in part, an artefact due to high-frequency ‘noise’ (Cunningham et al., 2007). 2.3.1.2. Arctic/subarctic measurements The oceanic exchanges of surface and deep waters ‘that connect the Arctic and Atlantic oceans through Subarctic Seas are of fundamental importance to climate’ (Dickson et al., 2008). In particular, changes that have taken place in the poleward ocean heat flux are likely to have played a central role in the decline of Arctic seaice (see Section 6). The signal from the changes in the Arctic has, and is expected to continue to, propagate south through Subarctic Seas on either side of Greenland, to modulate the Atlantic thermohaline ‘conveyor’ (Dickson et al., 2008). To measure these changes lines of moorings, supplemented in the last decade by ADCPs (Acoustic Doppler Current Profilers) and other measurements between (1) Iceland and Greenland, (2) Iceland and the Faroe Islands, (3) The Faroe Islands and Shetland, (4) Greenland, Spitsbergen and Norway, and more recently (5) in the Canadian Archipelago, have been in place for some years through the Arctic–Subarctic Flux Study (ASOF) (see http://www.asof.npolar.no) and its predecessors (Fig. 1.5). The aim of ASOF was to observe the inflow and outflow of water to and from the Arctic. A successor integrated Arctic/Subarctic Seas international programme (The integrated Arctic Ocean Observing System, iAOOS) is now in place as part of the International Polar Year (Dickson, 2006; Dickson et al., 2008).

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Figure 1.5 Estimates of freshwater flux relative to S ¼ 34.8* in Arctic and Subarctic Seas as determined during the ASOF project. Units are mSv and the base map is a snapshot of modelled sea surface height courtesy W. Maslowski, NPS, Monterey (1 mSv ¼ 31.546 km3 year1; * the numbers for PE, runoff and ice melt are independent of the choice of reference salinity). From Dickson et al. (2007).

The longest current meter records presently just exceed a decade, so it is difficult to determine any evidence for a long-term trend. There has been a pronounced increase in heat transport to the Arctic in the last 10 years (Holliday et al., 2008; Hughes and Holliday, 2007), with the maximum being reached 5 years ago and with another pulse of heat on its way. As the warmer water delivered to the Arctic is leaving already, the total heat content in the Arctic is slightly decreasing, but with high interannual variability (Dickson et al., 2008; Schauer et al., 2008). 2.3.2. Meridional overturning circulation in the Southern Ocean/Antarctica The Southern Ocean is a key region in the THC/MOC where the products of deep convection in the North Atlantic are upwelled and mixed into shallower layers. These waters are then converted into shallow and deep return flows to complete the overturning circulation (see Section 7). Profound physical changes have been observed in the water masses of both the shallow and deep return flows. The shallow limb of the MOC is sourced towards the northern flank of the Antarctic Circumpolar Current (ACC). Here, the water that is upwelled within the ACC is converted into mode waters and intermediate waters that permeate much of the global ocean basin south of the equator with nutrient-rich water. These waters

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show variability in properties on a range of timescales (seasonal to decadal and longer), reflecting global and regional climate variability in their source regions. The formation and subduction of the mode and intermediate waters (Fig. 1.6) is believed to be a critical process that removes anthropogenically produced CO2 from the atmosphere and likely contributes to A

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Figure 1.6 (A) Locationofmode andintermediatewatersin theglobal ocean.Low-density mode waters of the eastern subtropical gyres—pink. The highest density mode waters, which subduct in the subtropical gyres—red. Atlantic Sub-polar Mode Water, North Pacific central mode water and Subantarctic Mode Water (SAMW)—dark red. (B) Covering a large area of the ocean, intermediate waters are found below the mode water, Labrador Sea intermediate water (LSW)—blue, North Pacific intermediate water (NPIW)—pale green, Antarctic intermediate water (AAIW)—green. These waters eventually re-emerge at the surface far from their origin. Primary formation areas for the intermediate waters are indicated with red crosses. From Talley (1999): http://www-pord.ucsd.edu/ltalley/ papers/1990s/agu_heat/talley_agu_heat.html.

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internannual variability in global oceanic uptake. For example, 40% of the global ocean inventory of anthropogenic CO2 is found south of 30 S and most of that is in the intermediate and mode water (Sabine et al., 2004a). Changes have also been observed in the deep return flow of Antarctic Bottom Water (AABW), the deepest water on the Earth (Fahrbach et al., 2006; see Fig. 1.3). This cold water forms via intense air/sea/ice interaction at the surface, sinks and then spreads northwards towards the Arctic. A freshening of the AABW has occurred off a large sector of East Antarctica that may in part reflect melting at depth (700 m) of Antarctic glaciers that extend over the sea (see Section 7). The densest component of the AABW has shown a warming trend until very recently (Fahrbach et al., 2006), while the less dense variety that can escape the Weddell Sea and penetrate north in the Atlantic has shown a marked decadal warming (Meredith et al., 2008). 2.3.3. Slowing down of the MOC and cooling of NW Europe The general consensus from modelling projections for the twenty-first century is that there is likely to be a reduction in the strength of the Atlantic MOC of up to 50% of its current strength. This will not lead to a cooling of Europe, but less warming. This is because the general atmospheric warming ‘wins’ over the cooling expected from a reduced MOC. The impacts associated with a reduced MOC are contained in the projections of global and regional climate change provided by the IPCC AR4 WG report. These include a continuation of already observed changes in precipitation that include droughts in the subtropics and increased rainfall in equatorial and high-latitude regions. The results indicate that it is unlikely that there will be a large abrupt change in the MOC during this period (Meehl et al., 2007), although changes beyond 2100 cannot be confidently assessed.

2.4. Upwelling Wind-driven Ekman pumping with the Coriolis force drives the four major eastern boundary upwelling regions of the world: Peru, Benguela, California and Northwest Africa, supplemented by a region off Northeast Africa in the Arabian Sea that is driven by monsoonal wind forcing. These regions are possibly the most productive locations in the oceans (Thomas et al., 2004) due to the high concentrations of nutrients that are brought to the surface. Poleward divergence of water driven by the trade winds also causes upwelling to either side of the equator. Upwelling has a dual role in climate modulation as regions of strong outgassing of CO2 and other greenhouse gases (Bakun and Weeks, 2004) and as areas where the biological pump is especially strong as a consequence of the high productivity and rapid sedimentation of planktonic material to the ocean floor. A further consequence of this productivity is a reduction in oxygen levels,

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with at times the establishment of extensive areas of bottom anoxia (Bakun and Weeks, 2004; Neretin, 2006; Tyson and Pearson, 1991). It has been postulated, on the basis of palaeo-evidence, that increases in coastal upwelling and an intensified biological pump reduced levels of atmospheric CO2 in the lead up to the Pleistocene glaciations (Berger, 1985). Bakun (1990) reported an intensification of equatorward alongshore winds and an associated upward trend in upwelling from the 1940s to 1988 in all four of the eastern boundary regions. He attributed the changes to rising global temperatures and predicted an increase in upwelling intensity as global warming progresses. A similar substantial increase in upwelling and a >300% increase in chlorophyll has occurred in the Arabian Sea due to intensified summer monsoon winds in recent years due to warming of the Eurasian landmass (Goes et al., 2005). A modelling study by Hsieh and Boer (1992), however, suggests that upwelling may respond in the opposite way to that suggested by Bakun in a warming world. Their model analysis showed that reduced latitudinal gradients would lead to weaker upwelling and less productivity.

2.5. Changing physics of tropical seas in a warming ocean SSTs in the tropics determine where the upward branch of the Hadley Circulation in the atmosphere is located over the oceans and the strength of the circulation is related to the ENSO (IPCC AR4, WG 1, 2007, p. 296). For example, the Asian-Australian (AA) Monsoon (see WCRP/CLIVAR flyer on the AA Monsoons, available from CLIVAR http://www.clivar.org/) is strongly influenced by changes in SST in the Indian Ocean that are modulated by ENSO. The potential effects of tropical seas on climate change have only been discussed briefly in this chapter and should form a follow-up study. 2.5.1. Tropical storms (hurricanes, cyclones, typhoons) Tropical storms play a vital role in climate by pumping a considerable quantity of heat from the ocean into the atmosphere each year, by generating mixing that brings cold deep water to the surface and, through evaporation (Trenberth and Fasullo, 2007). During the storm, precipitation releases latent heat that is rapidly transported high into the atmosphere where it may radiate into space (Emanuel, 2006). These storms act as a release valve for solar heat caught above the sea in the humid, cloudy conditions of the summer tropics and are generated when surface water temperatures reach a threshold of 26 C over a depth of 50–100 m. The contribution that tropical storms may make to climate change through feedbacks related to a possible increase in their frequency and intensity is still unclear. The intensity of tropical storms has increased by 75% from 1970 to 2004 in the North Atlantic and western North Pacific and a global

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increase in their destructiveness is documented by Trenberth et al. (2007). They also note that the first recorded hurricane ever to cross the coast of South America occurred in March 2004. Atlantic hurricane activity is highly correlated with SST and a rise of only 0.5 C can lead to an increase of 40% in hurricane frequency and activity (Saunders and Lea, 2007). Regional variability in the occurrence of tropical storms is closely linked to ENSO and decadal environmental changes so that there is often an alternation between basins in the number of storms. For example in El Nin˜o years hurricane intensity decreases in the North Atlantic, far west Pacific and Australasian regions, but increases in the remainder of the Pacific. As global temperatures rise it is expected that precipitation will be enhanced, as well as the extent of the geographical area suitable for seeding storms so that global storm intensity and possibly frequency will likely increase.

2.6. Sea-level rise Sea-level rise is a major impact of climate change. Ocean thermal expansion was an important component of sea-level rise during the latter half of the twentieth century and models project it is likely to be the largest contributing factor in the twenty-first century. During the Pleistocene sea-level varied from metres above to over 120 m below present-day values as major ice sheets waxed and waned, particularly in the Northern Hemisphere (Berger, 2008). At the time of the last interglacial period about 125,000 years ago, sea-level was likely 4–6 m higher (Overpeck et al., 2006) than it was during the twentieth century, at polar average temperatures 3–5 C higher than present values. The Third IPCC Assessment Report, TAR (Church et al., 2001), reported that during the disintegration of the Northern Hemisphere ice sheets at the end of the last glacial maximum, sea-level rose at an average rate of 1 m per century, with peak rates of about 4 m per century. In the longer term, these ice sheets have the potential to make the largest contributions to sea-level rise and there is increasing concern about the potential instability of the West Antarctic and Greenland ice sheets. The current projections of sea-level rise are based on the SRES emission scenarios. However, global emissions are already above (Canadell et al., 2007; Raupach et al., 2007) the highest of these scenarios and well above stabilisation scenarios of twice pre-industrial values. Since the start of the IPCC projections in 1990, sea-level is actually rising at near the upper end of the highest IPCC Third Assessment Report projections of 2001 (Rahmstorf et al., 2007). There will also be regional changes in sea-level with some areas showing a decrease relative to the global average rise, due to circulation changes, but there is little understanding of such variability. One regional change that is likely to have a substantial impact is that many deltaic regions around the

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world are sinking as a result of reduced sediment supply, compaction of sediments and water (and/or oil or gas) extraction. Sea-level rise will be felt most acutely through extreme events, such as Hurricane Katrina and Cyclone Nargis. Rising sea-level on its own (without any change in the intensity or frequency of extreme weather driving coastal storm surges) will result in extreme sea-level thresholds of a given value being crossed more frequently. This change in frequency can be pronounced. Any change in the frequency or intensity of meteorological conditions will also change the frequency/intensity of extreme sea-level events.

2.7. Destabilisation of ice sheets/glaciers It is possible that rising sea-levels might destabilise buttressing ice shelves and/or increase the proportion of glaciers that float. A retreat of the grounding line of these glaciers may allow ice streams to speed up and potentially contribute to a large discharge of ice from an ice sheet although the mechanisms involved are still little understood. Recent research, however, has documented the production of a wedge of sediment that stabilises the position of the grounding line indicating that sea-level rise may be implicated in recent retreats (Alley et al., 2007; Anandakrishnan et al., 2007). A combination of basal melt and rising sea-level might, however, allow seawater to extend into sub-ice sheet basins that are presently isolated from the sea and lead to accelerated subsurface melting (D. Martinson, personal communication). Enhanced submarine melting causes the grounding line of glaciers to retreat, reduces the buttressing of frontal ice on inland ice, and allows faster rates of ice flow to the sea (Thomas, 2004). The melting of the glaciers in the western Antarctic Peninsula is more influenced by rising temperature than by changes in sea-level. It is unclear if ocean temperature or air temperature is the more important factor, but the ocean has a larger heat capacity and is in subsurface contact with the ice. Half a degree of temperature change in ocean temperature is more significant than half a degree change in air temperature. The recent decadal warming of the ocean adjacent to the western Antarctic Peninsula (>1 C in summer months since the 1950s) is mooted to have played a significant role in the retreat of its tidewater glaciers (Meredith and King, 2005). Surface melt of the Greenland ice sheet has increased and is projected to increase at a faster rate than additions from higher precipitation as temperature rises. If Greenland air temperatures rise an average of 3 C, it is predicted that the ongoing contraction of the ice sheet may be irreversible (ACIA, 2005). Global warming could exceed this value during the twenty-first century without effective mitigation of emissions. If these temperatures were maintained, they would lead to a virtually complete elimination of the Greenland ice sheet and a contribution to sea-level rise of up to about 7 m in the coming centuries to thousands of years.

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Some recent observations suggest a (rapid) dynamic response of the Greenland and West Antarctic ice sheets (WAIS) that could result in an accelerating contribution to sea-level rise. This is only included in an ad hoc fashion in the current IPCC projections. For the Greenland ice sheet, this is hypothesised to involve surface melt water making its way to the base of the ice sheet and lubricating its motion enabling the ice to slide more rapidly into the ocean. Glaciers in Greenland are already retreating. The sea-ice there shows no buttressing in the way that it does in Antarctica. Even so, sea-ice in the Greenland Sea has rapidly decreased over the last two decades and the Oden ice tongue between 70 and 75 N has disappeared. In Antarctica, the WAIS is grounded below sea-level, allowing warmer ocean water to melt the base of the ice sheet and potentially leading to significant instability. Understanding of these processes is limited. As a result, they are not adequately included in current ice sheet models and there is no consensus as to how quickly they could cause sea-level to rise. Note that these uncertainties are essentially one sided. That is, they could lead to a substantially more rapid rate of sea-level rise but they would not lead to a significantly slower rate of sea-level rise. Current projections suggest that the East Antarctic ice sheet will remain too cold for widespread surface melting and that it is expected to gain mass from increased snowfall over the higher central regions. Net loss of mass could occur, however, if there was a more rapid ice discharge into the sea around East Antarctica due to a higher rate of accumulation from snowfall over the interior or due to a warming of the coastal waters in contact with the glaciers. The latter would increase submarine melting, which in turn would release the grounded glaciers from their bed and allow them to flow faster towards the sea.

2.8. Concluding comments

Global SST has shown a progressive increasing trend over the last century with warmer water extending into the Arctic and parts of the Southern Ocean adjacent to Antarctica. There has been a large increase in the heat content of the ocean down to 700 m depth. The deep ocean appears to be absorbing heat at an increasing rate, but the amount of heat stored is inadequately quantified because of poor sampling. Pronounced changes in salinity have occurred in many regions of the world, likely reflecting a modification of the Earth’s hydrological cycle. Combined together, the salinity and temperature changes alter the density distribution, stratification and THC/MOC with large potential feedbacks to climate. There is clear evidence of large changes and pronounced daily to decadal variability in the MOC in different areas of the world.

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It is not possible at present to say if these changes on a global scale are a consequence of a reduction in the strength of the circulation due to climate change. The general consensus from modelling projections for the end of the twenty-first century is that there is likely to be a reduction in the strength of the Atlantic MOC by 0–50% of its current strength. This will not lead to a cooling, but less warming in Europe, with perhaps more warming in the tropics. It is unlikely that there will be a large abrupt change in the MOC during the next century, although changes beyond 2100 cannot be confidently assessed. There is evidence for increases in the intensity of upwelling, leading to large increases in phytoplankton production, anoxia and release of greenhouse gases. The intensity of tropical storms (hurricanes, cyclones, typhoons) has increased by 75% in the North Atlantic and western North Pacific and a global increase in their destructiveness is documented. With rising sea temperature and enhanced precipitation, the area for seeding tropical storms will expand possibly leading to an increase in storm frequency and intensity. Since the start of the IPCC projections in 1990, sea-level is rising at near the upper end of the highest IPCC Third Assessment Report projections of 2001. Historical evidence adds credibility to the possibility of an increase in the rate of sea-level rise at the upper end of and beyond IPCC projections. If global average temperature in Greenland increases by 3 C above preindustrial values, a level that could be reached during the twenty-first century without effective mitigation of emissions, the ongoing contraction of the Greenland ice sheet may not be reversible and could result in several metres of sea-level rise over hundreds or thousands of years. Recent rapid dynamic responses of the Greenland and West Antarctic ice sheets might result in a future accelerating contribution of their ice melt to sea-level rise. Feedbacks to climate change from sea-level rise are uncertain. Feedbacks from sea-level rise can accelerate ice sheet loss at the coast.

3. Primary Production: Plankton, Light and Nutrients Microscopic marine phytoplankton form the base of the marine food web. They use energy from the Sun to fix CO2 and account for around 45% of global primary production. Most of the organic carbon formed is consumed by herbivores or respired by bacteria, the remainder, about 35% (16 Gt, Falkowski et al., 1998; 11 Gt, Denman et al., 2007; Fig. 1.7), sinks

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Figure 1.7 Cartoon of the Biological pump modified from Falkowski and Oliver (2007). Note that CO2 is emitted from all heterotrophic organisms (e.g. zooplankton, fish and squid) and O2 is produced by phytoplankton as well as other gases such as methane and DMS.

below the upper sunlit layer every year. This section addresses the contribution that planktonic and benthic organisms make to carbon cycling in the ocean with a commentary on the biogeochemical and other controls on primary production. An attempt is made to synthesise and prioritise potential feedbacks to climate change from the many complex processes involved. It should be remembered that any feedbacks to climate are now taking place against a background of a very changed biology that has been impacted by eutrophication and hypoxia (Diaz and Rosenberg, 2008), removal of top predators (Pinnegar et al., 2000) and overfishing (Myers and Worm, 2003).

3.1. Oceanic primary production Production of atmospheric oxygen and fixation of carbon during photosynthesis by phytoplankton enables the Earth to support a rich diversity of marine life and has strongly influenced changes in climate through geological time (Diaz and Rosenberg, 2008; Mackenzie and Lerman, 2006). Phytoplankton biomass and primary production is determined by light availability and access to nutrients (nitrogen, phosphate, silicic acid, iron) as well as grazing and viral lysis. Light varies with the angle of solar insolation (latitude), season, cloud cover, level of water clarity and mixing

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and is variably absorbed by different phytoplankton pigments. Superimposed on these growth-limiting factors is a physical regulation by ocean circulation, mixed-layer dynamics and upwelling. Since 1% of light penetrates to 100 m (a very small proportion may reach as far as 1000 m) in the open ocean, and in productive coastal seas may only extend to 30 m or less, photosynthesis is confined to this upper layer.2 The contributors to primary production vary from cyano- and eubacteria [e.g. Synechococcus, Prochlorococcus, SAR 11 (SAR 11: a dominant cluster of marine bacterial phylotypes first described from the Sargasso Sea)] and eukaryotic picoplankton (0.2–2 mm in size), especially in tropical and oligotrophic oceanic waters, to eukaryotic nannoflagellates (2–10 mm) elsewhere with larger eukaryotic phytoplankton (10 to 150 mm) such as diatoms and dinoflagellates forming an important component of the biomass in upwelling regions and in boreal and temperate seas. A new paradigm for primary production now exists (see Fig. 1 in Karl, 2007), which includes the above new microbial contributors as well as photolysis (PL) of dissolved and particulate organic matter by sunlight (Fuhrman et al., 2008; Karl, 2007). This means that total primary production is likely to exceed the traditional view of chlorophyll-based gross primary production. Plankton also plays a key role in the Biological pump (see Section 4) that moves organic and inorganic carbon to the deep ocean. Grazing and recycling of nutrients by zooplankton, bacteria, archaea and viruses including reprocessing and packaging of planktonic detrital material as it sinks through the water column, are key processes in determining the export rate of C fixed by primary production (Steinberg et al., 2008; Yamaguchi et al., 2002). Viruses (also fungi) have an important role as terminators of plankton blooms and because of their role in the mortality of marine organisms are key players in nutrient and energy cycles and in the structuring of microbial communities (Suttle, 2007). It is believed that changes in the relative strengths of the two fluxes (Primary Production and export flux) strongly influence climate and have been responsible for many of the changes in climate in the geological past (Falkowski et al., 1998). The plankton also change surface albedo, increase retention of heat in the upper ocean by absorbance and contribute to the production of other potent greenhouse gases such as methane and nitrous oxide, and to reactive gases, such as dimethylsulphide (DMS) and halocarbons. It is worth noting here some important differences between oceanic and terrestrial ecosystems. Most marine organisms are small, have rapid turnover times, are able to react quickly to changes in temperature, and are easily distributed by changing ocean currents in contrast to their terrestrial equivalents (Sarmiento et al., 2004). In the upper waters of the open ocean, 2

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temperature and nutrients are strongly related (Kamykowski and Zentara, 2005a,b); this is not the case on land. As a consequence, oceanic organisms react more directly to changes in seawater composition resulting from climate change than terrestrial systems, and feedbacks from oceanic biology and biogeochemical interactions are likely to take effect more quickly.

3.2. Microbial plankton A number of major scientific breakthroughs have greatly improved understanding of oceanic microbial diversity and ecology over the last decade (Karl, 2007). Using genetic sequencing, it has been possible for the first time to determine the microbial (bacterial, archaeal and protist) composition of seawater samples (e.g. Fuhrman and Davis, 1997). One litre of seawater may contain as many as 20,000 species of bacteria, but only a very few 20 dominate. The remainder form what is termed the ‘rare biosphere’ (Karl, 2007; Sogin et al., 2006). Archaea are also an important component of the picoplankton in shallow and deep waters (Herndl et al., 2005; Massana et al., 2000). It is estimated that the global oceans contain approximately 1.3 1028 archaeal cells, equivalent to 30–40% of the estimated abundance of bacteria (DeLong, 2007; Quin˜ones et al., 2009). By combining genetic and isotope techniques with membrane lipid research, a range of new ecological roles for microbes in the biogeochemical cycling of C, N, S, Fe and many other trace elements have been demonstrated that are important to climate change. These include anoxic oxidation of methane (AOM) (Boetius et al., 2000; Michaelis et al., 2002; Stadnitskaia et al., 2008), anaerobic ammonium oxidation (Anammox process) that releases nitrogen gas from the oceans (Gala´n et al., 2008; Jensen et al., 2008; Kuypers et al., 2003; Sinninghe Damste et al., 2002), ammonia as an energy source for Crenarcheota so that they function as chemolitho-autotrophic organisms in the nitrogen cycle (Agogue et al., 2008; Konneke et al., 2005; Nicol and Schleper, 2006), the discovery of new nitrogen fixing microbial organisms in the oceans (Montoya, 2004; Zehr et al., 2008), use of light as an energy source enabling massive fixation of CO2 by SAR bacteria (Eiler, 2006), widespread anoxygenic photoheterotrophy in marine bacteria, including bacteria with bacteriochlorophyll and with proteo-rhodopsin (PR) (Beja et al., 2002; Eiler, 2006; Gomez-Consarnau et al., 2007; Moran and Miller, 2007), close syntrophic partnerships of anaerobic methane oxidising archaea and sulphate-reducing bacteria (Boetius et al., 2000; Pernthaler et al., 2008). These new findings demonstrate the crucial importance of microbes in climate and climate change and highlight a virtual complete absence of understanding of how microbial systems will change and impact biogeochemical cycling with climate change. Developing an understanding of the role of microbial diversity and functioning in biogeochemical and nutrient cycling is a major challenge for the future.

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3.3. Phyto- and zooplankton The distribution, abundance, production and biodiversity of different plankton species/groups are likely to be profoundly affected by projected climate-driven changes in the physical and chemical properties of the ocean including circulation, stratification, nutrients, light, trace metals (e.g. iron) and carbonate chemistry (Richardson, 2008). The converse will also occur as changes in plankton ecology and biodiversity can have a large and rapid impact with important feedbacks to climate variability through their role in the Biological, Continental Shelf and Carbonate Counter carbon pumps (see Section 4). Despite this importance, variability of these organisms on a global scale, other than for satellite measurements of chlorophyll, has been poorly studied. Long-term plankton observation programmes, other than the Continuous Plankton Recorder (CPR) survey (see http://www.sahfos. ac.uk/) in the North Atlantic and Southern Ocean, are non-existent in many oceanic regions of the world. At a global scale there is a strong negative relationship between satellitederived primary production and SST (Behrenfeld et al., 2006), but see the qualification of Sarmiento et al. (2004), that reflects the closely coupled relationship between ocean productivity and climate variability. One of the main reasons for this coupling is that the availability of nitrate (the principal nutrient limiting phytoplankton growth in much of the ocean) has been found to be negatively related to temperatures globally (Kamykowski and Zentara, 2005a,b). In the North Atlantic and over multi-decadal periods, changes in phytoplankton species and communities have been associated with Northern Hemisphere temperature trends and variations in the NAO index (Beaugrand and Reid, 2003). While at the interannual timescale correlations between temperature and phytoplankton are weak, due to high variance inherent in phytoplankton populations, at decadal intervals they are well correlated. Over the whole Northeast Atlantic there has been an increase in phytoplankton biomass in cooler and a decrease in warmer regions (Richardson and Schoeman, 2004). This relationship is likely to be a trade-off between increased phytoplankton metabolic rates caused by higher temperatures in cooler regions and a decrease in nutrient supply in warmer regions (Doney, 2006). The floristic shifts associated with this warming move a diatom-based system towards a more flagellate-based one (Leterme et al., 2005). In this scenario, however, it is assumed that the carbon sequestration will be less efficient because, unlike boreal diatombased systems, much of the flagellate and nanoplanktonic production is remineralised near the well-mixed surface. In a warming ocean, microbial activity is also likely to be faster leading to more rapid recycling of carbon and a less efficient Biological pump. However, due to the underlying complexity of biological communities and their quite often non-linear responses

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to environmental variability, this makes predicting both floristic and faunistic changes and their feedbacks to climate fraught with uncertainty. A number of groups in the plankton, including some benthic larval stages, have calcareous body parts (calcite, Mg calcite and aragonite). These organisms, including the algal coccolithophores (photosynthetic) and protist foraminifera (some of which are photosynthetic through symbiosis) are major contributors to pelagic carbonates especially in the subtropical gyres. Calcification (see Section 5) has the opposite effect to primary production, releasing some CO2 to the water that may outgas adding to the CO2 concentration in the atmosphere. The effects of projected changes in the pH of the oceans (acidification), in combination with rising temperature, on plankton community structure and calcification/dissolution processes are likely to have profound implications for biodiversity, living marine resources and again with likely feedback to the carbon cycle (see Sections 4 and 5). At the microbial level, the dominance of different picoplankton taxa may be affected by changes in pH and temperature with impacts on food web structure, especially in oligotrophic waters (Fu et al., 2007). Changes in ecosystem composition, that appear to be driven by climate variability, are already underway: examples include desertification around the Mediterranean Sea (Ke´fi et al., 2007), shifts in North Atlantic plankton biomass (Beaugrand et al., 2002), regime shifts in the North Pacific and North Sea (Chavez et al., 2003; Reid et al., 2001; Roemmich and McGowan, 1995) and observed shifts in phytoplankton pigment distributions as seen from satellite (Alvain et al., 2008). Large productivity crashes are also associated with ENSO events in the Pacific (e.g. Lavaniegos and Ohman, 2007; Peterson et al., 2002). These changes when seen together indicate that marine ecosystems are reacting beyond what might be expected from interannual variability. The changes also indicate that there may be locations in the ocean that act as biological hot spots that interact with climate change. If this is true, the identification and monitoring of such locations might be crucial for biodiversity, the maintenance of marine ecosystem goods and services, and for carbon drawdown. As oceans warm, primary productivity is peaking earlier in the season in some areas, with less distinctiveness between the spring, summer and autumn seasons (Edwards et al., 2001; Reid, 2005). Other parts of the food chain are shifting geographically poleward in response to thermal stimuli, rather than tracking the seasonal shift in primary productivity (Beaugrand et al., 2002; Mackas et al., 2007). These changes are creating a ‘mismatch between trophic levels and functional groups’ with implications for ocean–climate interactions and living marine resources (Edwards and Richardson, 2004).

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3.4. Chlorophyll and primary production Chlorophyll a is the dominant pigment in phytoplankton. As it is relatively easy to determine, it has been widely used in field studies as an in situ measure of phytoplankton biomass. With the advent of satellite instruments such as the Coastal Zone Color Scanner (CZCS; 1978–1986) and Seaviewing Wide Field-of-view Sensor (SeaWiFS; 1997 to the present) and development of algorithms for the estimation of chlorophyll a and primary production, we have a synoptic viewpoint that allows study of phytoplankton at the global scale (McClain et al., 2004; Fig. 1.8). It should be noted that the satellites only measure phytoplankton in the top few metres of the ocean and do not reflect the estimated 10% of marine primary production that takes place in the Deep Chlorophyll Maximum. In addition, it is becoming increasingly clear that chlorophyll a, on the basis of the new microbial evidence cited above, is not a good proxy for primary production. Using SeaWiFS data for 1997–2006, Behrenfeld et al. (2006) showed that global chlorophyll and calculated net primary production (NPP) increased sharply at the beginning of the period and then declined. The dominant signal in the data reflected changes in the 74% of the global ocean that comprises low-latitude permanently stratified tropical and subtropical waters with mean annual SSTs above 15 C. The pattern of change was highly correlated with SST and an index of ENSO climate variability. The link between ocean biology and the physical environment was shown to operate via warmer upper-ocean temperatures enhancing stratification, which reduced the availability of nutrients for phytoplankton growth and vice versa.

SeaWiFS global chlorophyll a (mg/m3) 90 >10.0 Latitude (deg)

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10.0 3.00

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Figure 1.8 Global image of mean surface chlorophyll for the period 1998–2007. Processed from SeaWiFS data by Takafumi Hirata, PML.

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Polovina et al. (2008), using the same SeaWiFS data, for the period January 1998–February 2007 have shown a similar expansion, especially in winter, of the least productive areas of the ocean, the subtropical gyres. In the North and South Atlantic and Pacific Oceans, outside the equatorial zone, approximately 6.6 million km2 of former higher chlorophyll habitat have been replaced by low chlorophyll water. It appears that the subtropical gyres are expanding on their current position, becoming warmer and more oligotrophic and are likely to continue to expand as temperatures rise further. In the Southern Ocean, Le Que´re´ et al. (2002) show in a modelling study that the response of primary production to increased stratification and temperature varies regionally and that light availability is more important than temperature and dust as a forcing factor. The net effect for the whole ocean is not known. If the reductions in NPP seen within the SeaWiFS period are extrapolated on the basis of projected changes in SST and nutrients, it could lead to a substantial reduction in the productivity of the oceans over the next 100 years. If these changes coincided with a reduction in the net input of CO2 and a reduction in export fluxes, there could be a large impact on the biological pump. A decade or more ago (e.g. Falkowski et al., 1998) modelling had already predicted that primary production would reduce as stratification increased in the oceans. From a climate change perspective, it is important to note that the rates of expansion of the subtropical gyres measured by Polovina et al. (2008) already far exceed recent model predictions. As a corollary, Behrenfeld et al. (2006) also note that modelling has shown that changes in ecosystem structure (e.g. taxonomy, physiology and light absorption) due to climate variations may be as or more important than the changes in bulk integrated satellite measures of chlorophyll. The global observing systems needed to measure such variability are rudimentary and concentrated in the Northern Hemisphere at present. A range of mesoscale processes such as eddies, fronts and their interaction with wind are important in mixing and bringing nutrients to the surface and may stimulate blooms (e.g. McGillicuddy et al., 2007). Similar mixing may be induced by the passage of hurricanes (Son et al., 2007). Understanding of mesoscale variability in oceanic waters and its potential impact on NPP, export flux and climate is poor.

3.5. Plankton biodiversity functional groups and ocean biomes There are tens of thousands of different species of viruses, bacteria, archaea, cyanobacteria, phyto- and zooplankton and other organisms in the plankton. Together they play a key role in ecological and biogeochemical processes (Falkowski et al., 2003) that modulate the cycling of CO2.

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These roles include the regulation of the settling flux of organic and inorganic carbon to the deep ocean and determining levels of reactive trace gases and aerosols in the atmosphere as well as proxy tracers for the carbon cycle such as O2, 13CO2 and O18O. The biodiversity also contributes to variability in physical processes in the ocean, including temperature, stratification and mixing (Dewar et al., 2006; Le Que´re´ et al., 2005). To manage the complex variety of these different plankton modes in modelling and other studies, assemblages of species are generally consolidated, for example, into ‘Plankton Functional Groups’ (Boyd and Doney, 2002; Jin et al., 2006; Sarmiento et al., 2004). Changes in the relative importance of different functional groups in the plankton can strongly impact the biological pump. Diatoms, relatively heavy and fast sinking, would be efficient in transporting sinking carbon to the deep ocean (Smetacek, 1998; Tre´guer and Pondaven, 2000; Yool and Tyrrell, 2003), whereas nanoplankton (including the calcareous coccolithophores), being smaller as well as being rapidly ingested by heterotrophs, would be less efficient in the biological pump. Thus, relative fluxes of diatoms versus calcareous plankton have been implicated as one of the causes for the changes in CO2 between glacial and interglacial periods (Harrison, 2000; Tre´guer and Pondaven, 2000). Several feedback effects are conceivable: higher wind speeds, that favour diatom growth, would result in increased export (Le Que´re´ et al., 2007, 2008); on the other hand, increasing temperatures, which favour the growth of smaller phytoplankton, are thought to reduce export flux. New developments in the interpretation of SeaWiFS data (e.g. Aiken et al., 2008; Alvain et al., 2005, 2006, 2008; Raitsos et al., 2008) are making possible the identification of some phytoplankton functional groups on a global scale. The next step in an analysis of biological variability in the ocean and its importance to climate change is to determine change in different ocean provinces (Biomes: Longhurst, 1998). Sarmiento et al. (2004) in a multimodel comparison study have divided the ocean into six different Biomes based on physical characteristics that reflect nutrient supply (Fig. 1.9). It is clear from carbon export studies in the Southern Ocean and elsewhere (Boyd and Trull, 2007) that there is a need to increase the number of Longhurst provinces with more precise/sensitive definitions based on multi-disciplinary information systems including plankton assemblage data (e.g. Beaugrand et al., 2002; Devred et al., 2007). To achieve this aim an improved knowledge is needed of chemistry, mesoscale properties, spatial and temporal variability in plankton composition and production versus recycling and export rates. In a review by Le Que´re´ et al. (2005), plankton functional types (PFTs) were selected among other criteria on the basis of their clear biogeochemical role, quantitative importance in terms of biomass and production, welldefined environmental, physiological and nutrient control and biological

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Biome definitions 80⬚N Eq-D Eq-U

40⬚N

ST-PS ST-SS

0⬚

LL-U 40⬚S

SP Ice

80⬚S 0⬚

90⬚E

180⬚

90⬚W

0⬚

Figure 1.9 The distribution of six different ocean biomes: (1a) equatorial—downwelling (Eq-D), (1b) equatorial—upwelling (Eq-U), (2) subtropical gyre—permanently stratified (ST-PS), (3) subtropical gyre—seasonally stratified (ST-SS), (4) low latitude—upwelling (LL-U), (5) sub-polar (SP) and (6) marginal sea-ice (Ice). From Sarmiento et al. (2004).

interactions. A provisional grouping of 10 different PFTs that need to be simulated in a new generation of linked ocean physics and ecosystem models was selected by Le Que´re´ et al. (2005) to ‘capture important biogeochemical processes in the ocean’. The groups selected are involved in, for example, bacterial remineralisation, N2 fixation, phytoplankton calcification, silicification and DMS production, and include three different size fractions of zooplankton that contribute to export via a range of processes including faecal pellet and mucilaginous packages. The modelling and research strategy outlined by Le Que´re´ et al. (2005) addressed the urgent need to improve understanding of the interactions between the different types of plankton, food web structure and export efficiency of carbon. To successfully progress such a strategy will require a new level of international collaboration between modellers and marine ecologists, which has been historically absent.

3.6. Benthos Benthic ecosystems play an important role in global carbon cycles as they are sites for remineralisation, burial and calcification. They also are places where many of the nutrients that sustain planktonic production are regenerated. While benthic studies have been carried out worldwide, they are largely confined to shelf waters and are spatially and temporally patchy. The inshore biota of Western Europe and parts of the coast of North America is well

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known but that of most of Asia, Africa and South America, especially in the tropics and subtropics, is poorly studied and the deep sea (around 97% of the world ocean) has scarcely been sampled. As a consequence it is difficult to quantify the role of the benthos in the global carbon cycle or to identify the regional areas that are most important. Furthermore, the majority of benthic studies have been focussed on larger bodied animals; sedimentary microbiology is a relatively young science and thus it is equally difficult to partition carbon cycling between the different elements of the benthic biota. While there has been considerable concern about the impacts of ocean acidification on animals with calcareous body parts, some species appear to be able to increase the rate of calcification at a lower pH (Wood et al., 2008b) although this is at some metabolic cost and may not be sustainable. Non-calcareous species are also likely to be affected as their physiology is finely regulated and has evolved to function within relatively narrow pH and CO2 ranges (Michaelidis et al., 2005). The scale of impacts on populations and assemblages resulting from a potential decline in growth and reproductive rates from ocean acidification has yet to be quantified.

3.7. Migration of plankton, fish and benthos towards the poles A pronounced consequence of a warming ocean has been a poleward expansion of the range of many species in both the Southern and Northern Hemispheres. The resulting marked changes in community structure that are reflecting warming oceans and changes in circulation (e.g. Ha´tu´n et al., 2009) have implications for the biological pump and CO2 drawdown. Some of the strongest evidence for large-scale biogeographical changes in the oceans comes from the Continuous Plankton Recorder survey. In the Northeast Atlantic warmer water, zooplanktonic copepods have moved to the north by 10 latitude (1000 km) within 50 years while colder water plankton has retreated in the same direction (Beaugrand et al., 2002). This represents a mean poleward movement of between 200 and 250 km per decade. The speed of this migration, due to advective processes, is more pronounced than any documented terrestrial study. Responses of zooplankton to changing water temperature have also been observed in the North Pacific (Mackas et al., 2007), but it remains unclear if these are systematic responses to climate change or simply related to shifts in climatic state as reflected by major climate indices such as the Pacific Decadal Oscillation. Many species of fish have also shown apparently similar northerly range extensions in the eastern Atlantic and North Sea, at estimated rates that are up to three times faster than terrestrial species (Brander et al., 2003; Perry et al., 2005). One of the largest biogeographical shifts ever observed for fish species is the dramatic increase and subsequent northerly geographical spread of the snake pipefish (Entelurus aequoreus). Prior to 2003 this fish

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was confined to the south and west of the British Isles, but it now extends as far north as the Barents Sea and Spitzbergen (Kirby et al., 2006; Harris et al., 2007). The pelagic environment is of course three-dimensional and recent research has observed a movement of fish species towards deeper cooler waters in response to climate warming (Dulvy et al., 2008). This change can be seen as analogous to the upward altitudinal movement of terrestrial organisms in alpine environments. There is evidence for poleward migration of benthic species in temperate and sub-polar latitudes of both hemispheres; in all areas, changes that have taken place within the last 20 years. Range expansions have been described, for example, from around California (Barry et al., 1995), the British Isles (Mieszkowska et al., 2007), in the Bering Sea (Grebmeier et al., 2006) and off the Antarctic Peninsula (Clarke et al., 2005; Thatje, 2005). There is minimal information to indicate if tropical and subtropical species, other than possibly corals on the eastern margin of Florida, are expanding poleward.

3.8. Oxygen One of the most critical variables in the world’s ocean is the distribution of dissolved O2. Oxygen plays a direct role in the biogeochemical cycling of carbon and nitrogen as well as being fundamental for all aerobic life, including organisms living in the dark ocean interior. If the oceans were to stagnate, many regions of its interior would be devoid of O2 within a few decades as oxygen is continually being consumed by deep-dwelling organisms (Feely et al., 2004; Whitney et al., 2007). A critical threshold is reached when O2 levels reach 60 mmol kg1, below which most macro-organisms become hypoxic, that is, severely O2 stressed (Gray et al., 2002). A second threshold is crossed when O2 drops below 5 mmol and nitrate becomes important in respiration, a condition termed ‘suboxic’. When O2 levels drop to zero, the water is termed ‘anoxic’, and biogeochemical processes are then dominated by sulphatereducing microbes. Ocean anoxic events (OAEs) have occurred episodically throughout the geologic record (Cohen et al., 2007; Jones and Jenkyns, 2001; Wignall and Twitchett, 1996). These episodes are defined by sedimentary evidence of widespread anoxia and are often associated with evidence of warmer climate conditions, rises in sea-level and occasionally with mass extinctions. Although the cause of the events remains a matter of speculation, their existence underscores the potential vulnerability of oceanic O2 supply in warmer climates. Anoxia is rare in the modern open ocean, but is important in enclosed basins such as the Black and Baltic Seas. Hypoxic conditions occur, however, at mid-depths over wide expanses of the North Pacific, in smaller

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regions of the north Indian Ocean, and in the eastern tropical Atlantic and Pacific Oceans. These regions are known as oxygen minimum zones (OMZs), with the low levels of O2 mostly attributable to the sluggish rate at which the subsurface is renewed by mixing with well-aerated surface waters (Karstensen et al., 2008). Suboxic conditions are restricted to more limited regions of the north Indian and eastern Pacific OMZs. Hypoxic and suboxic conditions frequently occur in coastal waters, where low subsurface O2 levels can be generated by natural high biological productivity in the overlying waters or by eutrophication from agricultural runoff or sewage inputs (Diaz and Rosenberg, 1995). Significant reductions in the O2 supply to the ocean interior and expansion of OMZs may result from continued anthropogenic global warming. Under business-as-usual type emission scenarios, climate models suggest that the global ocean O2 inventory will decrease by 4–7% over the next century with continued reductions after that (Matear and Hirst, 2003; Schmittner et al., 2008). The main mechanism is increased stratification of the surface ocean due to warming and freshening of high-latitude surface waters which reduces renewal rates. The details differ between models, with several other processes also being relevant including the direct reduction of O2 solubility in warmer water and changes in rates of photosynthesis influencing the sinking flux of organic detritus into the ocean interior. The models suggest that detectible changes in O2 content due to global warming may already have occurred (Matear et al., 2000; Sarmiento et al., 1998). Marked declines in subsurface O2 concentrations have been noted in 30year records from the western North Pacific (Ono et al., 2001) and 50-year records from the eastern North Pacific (Whitney et al., 2007). The largest long-term declines (of the order 10 mmol kg1 per decade) have been found in layers occupied by North Pacific intermediate water (150–600 m depth), which is renewed by contact with the surface in the Sea of Okhotsk and neighboring regions. The declines have been tied to freshening surface waters in the renewal regions associated with a reduction in renewal rates (Mecking et al., 2006; Nakanowatari et al., 2007) and appear superimposed on decadal variability of natural origin (Andreev and Baturina, 2006; Mecking et al., 2008). As a consequence the oxic/hypoxic boundary has shoaled from 400 to 300 m over the past 50 years (Whitney et al., 2007). Significant O2 declines have been found in 50-year records from the OMZs in the eastern tropical Pacific and Atlantic (Stramma et al., 2008). The declines are of the order 1–3 mmol kg1 per decade and are associated with a vertical expansion of the hypoxic layers. Clear evidence of long-term trends is lacking in other regions, however, and the ability to resolve longterm trends is impaired by sparse coverage of reliable historical O2 measurements and by short-term or decadal variability ( Johnson and Gruber, 2007; Min and Keller, 2005). Climate models suggest that the O2 levels may

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actually increase in some regions despite the decline in the global average due to the complex response of dissolved O2 to circulation changes (Matear and Hirst, 2003; Schmittner et al., 2008). Changes in climate may also contribute to increasing coastal hypoxia (Grantham et al., 2004). The implications of a continuing global decline in global oceanic O2 to climate change are unclear as the science is still at an early stage. Potential impacts of O2 on organisms and ecosystems must be considered in concert with changes in acidity and temperature (Portner and Farrell, 2008). Further expansion of the O2 minimum zones will likely adversely impact the distribution of fish and other commercially valuable species (Gray et al., 2002).

3.9. Nutrients in general In addition to CO2 and light, phytoplankton growth and productivity requires the availability of a range of nutrients. In the 1930s, Redfield found that the bulk elemental composition of particulate organic matter in seawater is constrained and reflects the concentration of the major elements in seawater. This led to the adoption of the Redfield ratio 106C (carbon):16N (nitrogen):1P (phosphorus) (and 16Si for silicic acid that is essential for diatoms) as the average elemental composition. It should be stressed that there is considerable variability around these average ratios in time, space and by species/taxa (Arrigo, 2005; Klausmeier et al., 2008). Spatial and temporal variability in nutrient availability has a profound influence on the composition, biomass, seasonal cycle and spatial variability of phytoplankton. The ocean basins of the world show very variable spatial concentration patterns for different nutrients. There have been observed changes through time, but these show no consistent basin-scale patterns (Bindoff et al., 2007). This lack of coherence in the data has been attributed to poor sampling coverage and limited compatibility between the methods used through time and by different laboratories (Bindoff et al., 2007). Kamykowski and Zentara (2005a,b), in contrast, using a calibrated temperature/nitrate relationship from a range of locations, have produced anomaly charts of the difference between nitrate availability between 1909 and 2002 (Fig. 1.10). The figure shows the clear expansion of a shallower thermocline over much of the ocean (blue) with reduced availability of nitrate. Equatorial nitrate availability linked to El Nin˜o is evident in the Pacific and a pronounced contrast between the two sides of Canada is seen, in the east reflecting increased haline stratification. Three large regions that together cover 20% of the ocean’s surface, the Southern Ocean, eastern equatorial Pacific and subarctic Pacific, are characterised by high levels of nutrients and low chlorophyll (HNLC regions) (Aumont and Bopp, 2006). The stable chlorophyll levels in these regions have been attributed to iron limitation or grazing control by

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50 Oct 1909–Oct 2002 ERSST v2

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Figure 1.10 Map showing modelled difference in nitrate availability based on a temperature nitrate relationship, between October 1909 and 2002. Darker colours represent greater contrasts between the years. From Kamykowski and Zentara (2005a,b). Green, nitrate in 1909 present at the surface >2002; red, nitrate in 2002 present at the surface >1909; blue, stratification in 1909 between nitracline and surface <2002; grey, stratification in 1909 between nitracline and surface >2002.

microzooplankton (see Section 4). It is possible that increased desertification and land use changes in the future may lead to more aerial input of dust, including micro-nutrients such as iron, into the oceans (Mahowald et al., 1999). Other factors than iron limitation may be behind the low chlorophyll levels, however, and so the addition of iron alone may not lead to an increase in production; it is the cumulative effect of the many changes that is important. There has been an enhanced riverine input of N and P to near shore regions over the last century and especially since 1950 that in some cases have caused eutrophication and elsewhere has been buried in organic carbon in sediments (Smith et al., 2003). The latter study derived estimates based on population relationships that are three times higher than those derived in the 1970s. As population levels rise in the future, this pattern is likely to be reinforced as higher global temperatures are expected to lead to an increased mobilisation of N and P from sediment (Mackenzie et al., 2002). Sequestration of carbon in sediments is likely to especially apply in regions subject to anoxia or hypoxia that appear to be increasing in extent (Diaz and Rosenberg, 2008). Atmospheric inputs of fixed nitrogen to the ocean have also increased and have contributed to higher algal production and nitrogen oxide (N2O) emissions from the ocean (Duce et al., 2008). Langlois et al. (2008) have shown that nitrogen fixing cyanobacteria in the North Atlantic were most abundant at higher temperatures (see also Stal, 2009) and with enhanced inputs of atmospheric dust. Strong regional changes in nutrients are expected in the future dependent on variability in wet precipitation, wave storminess, expanding OMZs,

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mixing and the depth of stratification. Precipitation is expected to increase especially in tropical regions. At present, it is not possible to predict future trends in nutrients because of the localisation of the changes. It is also not clear how all the regional responses will add up to a global mean and influence climate change. 3.9.1. The oceanic nitrogen cycle Nitrogen is a fundamental component of all organisms and essential in the chemical forms that are needed for assimilation in primary production. Understanding of the nitrogen cycle (Fig. 1.11), and especially of the role played by microbes in the cycle, has increased substantially in the last decade. The predominant form in the ocean is nitrogen gas (N2); this gas can only be utilised by a few specialist nitrogen fixers that include the

N2 Atmosphere

f e Anammox

Organic sources

NH3

a AMO

NH2OH

b

Denitrification

c

NO−2 Nitrification

Ammonia oxidation Archaea, Bacteria

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d NO−3 Organic assimilation

Nitrite oxidation Bacteria

Figure 1.11 The global nitrogen cycle. Nitrification is a step-wise process by which ammonia (NH3) of organic origin is oxidised to nitrate ions (NO3). The first step (a) involves the ammonia monooxygenase (AMO) enzyme in Crenarchaeota and bacteria that convert ammonia into hydroxylamine (NH2OH). (b) This is then processed by bacteria and possibly archaea into nitrite ions (NO2). (c) Other specialised bacteria complete nitrification by converting nitrite to nitrate. (d) Nitrate is then assimilated into organic matter during primary production or denitrified by other organisms to form nitrogen some of which escapes to the atmosphere. (e) Anammox bacteria can also convert ammonia and nitrite into nitrogen for release to the atmosphere. (f ) Nitrogen is fixed by specialised organisms and converted to ammonia that is converted into organic matter or oxidised as the cycle continues. The organic sources on land also apply to the ocean and additional sources to the ocean are contributed from rivers and the atmosphere. Figure modified from Schleper (2008).

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important tropical/subtropical cyanobacteria, Trichodesmium and a number of groups of unicellular cyanobacteria (Capone et al., 2005; Stal, 2009). In addition, endosymbiotic associations between some diatoms and cyanobacteria (Gomez et al., 2005) and some bacteria ( Johnston et al., 2005) may also fix N2. ‘A new paradigm for nitrogen fixation’ (Arrigo, 2005; Karl, 2007) means that it is now recognised that the oceans contribute at least 50%, and likely more, to global fixation than the minor contribution previously believed (Stal, 2009). This percentage is likely to increase in the future as tropical and subtropical waters expand, with considerable consequences for climate through changes in nutrient ratios (stochiometry), plankton communities and the biological pump. Other phytoplankton groups utilise a range of reduced and oxidised forms of nitrogen (NH4þ, NO2, NO3 plus organic nitrogen). The concentration and spatial and temporal variability of these N forms is a key global determinant of phytoplankton biomass and rates of primary production. In energetic terms, when available, ammonium (NH4þ) is the preferred nitrogen source. Ammonium is also the primary form of N used by phytoplankton in the large regions of the ocean (subject to permanent stratification) where recycling-based communities prevail and the phytoplankton often have higher surface area-to-volume ratios. Other important breakthroughs in understanding the nitrogen cycle (Fig. 1.11) include the recognition that Archaea (Crenarchaeota) as well as bacteria are capable of oxidising ammonia and the role of the Anammox process in delivering nitrogen gas to the atmosphere (see Section 3.2). Conversion of dissolved ammonia, nitrite and nitrate to particulate forms against the reverse process of denitrification appear to be generally in balance within a 3000-year time period. There are, however, opposing views at present on the size and relative balance between biological nitrogen fixation and denitrification in the ocean. Yool et al. (2007), for example, have shown that about half of the global uptake of nitrate by marine phytoplankton is produced by denitrification. On the basis of their results they suggest that the biological pump may be less efficient than previously estimated. Note the additional complication, by reference to Section 3.2 earlier, of the important discovery of the new Anammox denitrification process and the use of NH4 as an energy source by Archaea, especially in the surface ocean. An increased contribution to the nitrogen pool due to utilisation of N by cyanobacteria and bacteria is thought unlikely as iron is also needed in this process (Falkowski et al., 1998). The extent to which the availability of nitrogen will affect the ability of the biosphere to absorb increasing levels of atmospheric CO2 in the future is not clear (Gruber and Galloway, 2008). There has been a large increase in the anthropogenic input of nitrogen to the environment deriving from industrial processes fertilisers, animal husbandry, sewage and fossil fuel emissions. In the marine environment, many of these inputs have caused problems in coastal waters in the form of eutrophication. Anthropogenic

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emissions contribute to the build-up of greenhouse gases such as nitrous oxide, (N2O) and nitrogen trifluoride (NF3) (Forster et al., 2007; Prather and Hsu, 2008) as well as contributing to a loss of ozone in the atmosphere. On a global scale the deposition in the ocean of anthropogenic biologically available nitrogen from atmospheric sources is likely to have stimulated phytoplankton growth (Duce et al., 2008). The total input of these anthropogenic sources at 160 Tg N year1 accounts for more than the natural fixation of nitrogen on land (110 Tg N year1) or in the ocean (Gruber and Galloway, 2008), but not all may be available for marine photosynthesis. An observed parallel development of trends in atmospheric CO2, N2O and temperature over the last 250 years (Fig. 1.12) with good evidence for parallel changes in the Pleistocene (Flu¨ckiger et al., 2004) emphasises the close relationship between these two gases and their links to climate change. A recent study has shown that cell division rate doubled and the Redfield ratios (106C/16N/1P) C/P and N/P (not C/N) of the planktonic cyanobacteria Trichodesmium changed markedly, as a response to increasing levels of CO2 leading to an enhancement of nitrification and potential enhanced CO2 drawdown (Barcelos e Ramos et al., 2007). It is believed unlikely, but if this proved to be a selective response in phytoplankton, in general it would establish a strong negative feedback to climate, provided the produced POC sank below the mixed layer. Concentrations of greenhouse gases from 0 to 2005 AD 400

2000 1800 Methane (CH4)

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3.9.2. The oceanic phosphorus cycle Phosphorus is an essential nutrient in primary production (Froelich et al., 1982) and is used as an energy carrier (in ATP/ADP molecules) in all organisms (Fo¨llmi, 1996). The marine phosphorus cycle involves uptake and assimilation of phosphate by plankton in surface waters, its release back into the water by processes such as cell lysis and bacterial degradation and its subsequent transport to the deep ocean via sinking of released organic material, and return to the upper ocean by slow mixing (diffusion, upand downwelling) and circulation (Tyrrell, 1999; Williams and Follows, 2003). There has been a considerable debate on the influence of P and N on ocean productivity during glacial cycles and consequently on atmospheric concentrations of CO2. Recent results from deep sea cores (Tamburini and Fo¨llmi, 2009) suggest that burial of reactive P in glacial conditions is reduced and that richer P conditions characterise glacial terminations, both with a possible feedback to the carbon cycle. Models of phosphate cycling by Tyrrell (1999) indicate that while in the steady-state nitrate is more deficient than phosphate, external inputs of P control the longer term primary production of the global ocean. Sources of P in the oceans are dominated by river input with circa 90% of all inputs consisting of organic debris. Outside coastal waters, P concentrations in the euphotic zone are dependent on rates of upwelling and diffusion from deep water in the ocean’s interior as well as the concentration of P in the source water (Froelich et al., 1982). In HNLC (high nutrient low chlorophyll) and upwelling regions, PO4 is in plentiful supply, but generally not elsewhere, except during the winter in temperate and sub-polar latitudes. An exception is the eastern Mediterranean where a high nitrate-to-phosphate ratio has been observed resulting in phosphate limitation of the primary production (Krom et al., 2004; Rees et al., 2006). A similar situation has been described from Station ALOHA in the northwest Pacific sub-polar gyre where N2 fixation is possibly increasing over time due to climate-coupled changes, leading to an intensification of P stress in this P-limited ecosystem (Karl, 2007). 3.9.3. The oceanic silicon cycle In the oceans silicon (Si) is primarily in the dissolved inorganic oxidised form silicic acid. When silicic acid is available, diatoms dominate phytoplankton communities and are important because of their high sinking rates, in the export of carbon via the Biological pump. The proportions of silicate versus carbonate sedimentation have been implicated as a factor in the reduction of atmospheric CO2 concentrations by 100 ppm in glacial periods. Work by Kohfeld et al. (2005), however, suggests that increased growth of diatoms and other biological processes could account for no more than 50% of the drawdown. Over the last 40 million years since the Late Oligocene silica-rich upwelling regions have been increasing as the planet

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cooled, a trend that is closely associated with the evolution of whales (Broecker and Kunzig, 2008); implications for whales and climate in a warming planet are unclear. The supply of silicic acid to the upper illuminated layer derives from weathering, riverine fluxes and upwelling from the ocean interior (Falkowski et al., 1998). Concentrations of silicic acid in water are highest in the Northern Hemisphere, off major river basins, in Subarctic Seas and the Arctic Ocean, but also in the Southern Ocean where silica wells up from deeper water and is carried northwards by the ACC. In contrast, in the central ocean gyres levels of silicic acid are very low. This distribution is reflected in the distribution of the production of biogenic silicon (opal) as diatoms and radiolaria (Fig. 1.13). As a contrast to the Northern Hemisphere, more than two-thirds of the global sedimented silica is deposited south of the Polar Front under the ACC (Smith et al., 2003; Wischmeyer et al., 2003). In a modelling study of the silicon cycle, Yool and Tyrrell (2003) show that the ecological success of diatoms varies inversely with the concentration of silicic acid and thus through a negative feedback controls the cycle. However, total primary production is shown to be controlled by phosphate and not silicic acid availability.

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3.9.4. Iron and dust Iron is an essential element for all organisms because it is needed in a wide range of enzyme systems for processes including photosynthesis, respiration and nitrogen fixation. In HNLC regions, iron deficiency reduces growth rates, cellular chlorophyll levels, net CO2 fixation and active uptake of CO2 and HCO3 (Schulz et al., 2007). The late John Martin helped to focus attention on the importance of iron supply to the Southern Ocean by highlighting that this was higher in the past, which could account for a substantial proportion of the 80-ppm drawdown in atmospheric CO2 observed between glacial and interglacial periods (Martin, 1990). In the contemporary ocean, iron limits the growth of phytoplankton over broad areas where macronutrient concentrations remain high (Boyd et al., 2000). These include the so-called HNLC regions of the Southern Ocean, as well as parts of the North and the Equatorial Pacific. Iron is supplied to the oceans with soil alumino-silicates in riverine inputs, upwelling and to the open ocean via aeolian inputs of dust that originate from various deserts, with lesser inputs from volcanic, anthropogenic and meteoric sources. Drought conditions as well as changes in land use and agricultural practice can lead to increased dust emissions. Dust inputs are particularly important for the vast open ocean regions and a key concern is that arid regions are very sensitive to climate change and this has the potential to change ocean productivity and global climate in turn ( Jickells et al., 2005). However, aside from the issue of climate change, a recent study by Wagener et al. (2008) underlines the need for in-depth comparisons of model and in situ data and a re-evaluation of predictions of present and past dust inputs. They examined aerosol deposition of iron to two remote oceanic areas in the Southern Hemisphere and concluded that current dust deposition models overestimated iron inputs and that dust deposition is not the dominant source of iron for this large and important HNLC region.

3.10. Other gases and aerosols 3.10.1. Methane, nitrous oxide and halocarbons Man-made (livestock, arable farming, landfill, industry) and natural emissions from terrestrial environments and the sea contribute to the atmospheric burden of methane (CH4), nitrous oxide (N2O) and a suite of volatile halocarbons (compounds containing chlorine, iodine and/or bromine). Methane and N2O are potent greenhouse gases with global warming potentials about 21 and 310 times that of CO2. Methane oxidises into CO2, and continues to have a long-term global warming effect. The halocarbon gases are key sea-to-air transfer compounds for the global biogeochemical cycles of bromine, chlorine and iodine.

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Global net methane emissions from oceans and freshwaters are estimated at 10 Tg per annum. While this is only about 2% of the total global source, the marine methane cycle is nevertheless considered highly significant because the concomitant anaerobic methane oxidation sink ensures that the net flux of methane to the air is a minor fraction of the total methane produced (Reeburgh, 2007). Methane is produced and consumed in seawater via microbial reactions, and also arises from geological sources including methane clathrates, hydrothermal vents, cold seeps, mud volcanoes and anaerobic methanogenesis. Considerable regional variability is evident over the ocean that has much lower levels than over the land (Fig. 1.14). The Black Sea stands out for having high surface methane concentrations and fluxes. Until recently, methane production was thought to require strictly anaerobic conditions. The origin of the methane distributed in oxygenated surface ocean waters was considered a paradox, and it was assumed that methane production was limited to anoxic environments in digestive tracts and faecal pellets. However, recently Karl et al. (2008) have shown that methane is a by-product of the aerobic microbial breakdown of methylphosphonate (CH5O3P), and they suggest that marine methane production could increase with global warming-induced increases in stratification and nutrient limitation. The oceans, particularly the sediments of continental slope regions, are estimated to harbour 2000 Gt of carbon as methane gas and icy solids known as methane clathrates or hydrates (Buffett and Archer, 2004). It has been suggested that catastrophic release of methane from this store caused abrupt

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climate warming in the past and there are concerns that a warmer future climate could destabilise this reservoir and trigger further warming (see Section 6). N2O production is enhanced in areas where oxygen levels are depleted and nitrate fuels denitrification. These conditions are combined in upwelling areas and it has been suggested that the global expansion of hypoxic/ anoxic zones (Chan et al., 2008) is leading to increased production of N2O and the accumulation of this radiatively active trace gas in the atmosphere (Naqvi et al., 2000). If the mid-water depths of the ocean are shut off from ocean ventilation, CH4 and N2O will be increasingly produced and as a gas will bubble up towards the surface. An increase of even a small amount of N2O entering the atmosphere could have large implications. The possible role that an increase in sea areas subject to hypoxia/anoxia (as in the Black and Baltic seas or in upwelling regions such as the Arabian Sea) might play as a contribution to climate change is not clear. Some halocarbons are man-made, but many are derived from seaweeds, microalgae and/or extracellular photochemical reactions. They break down photochemically in the troposphere to form halogen radicals which destroy ozone and produce halogen oxides. Ozone is a major precursor for hydroxyl (OH) radicals and its removal from the system impairs the atmospheric cleansing of pollutants including methane. It has been suggested that BrO interacts with DMS (see below) reducing its cooling effect on climate via aerosol production (von Glasow et al., 2004) whereas iodine oxides contribute to the formation and growth of marine aerosol (O’Dowd and Leeuw, 2007). The deep ocean may be an important source region for halocarbons and other gases, but little work has been done in this area. 3.10.2. Aerosols The burning of fossil fuels, including in shipping, releases SO2 to the air where it is oxidised to form sulphate aerosol. This acts to cool the climate directly, because the aerosol particles reflect solar radiation back into space, and indirectly as sulphate particles can also act as condensation nuclei influencing cloud formation and the radiative properties of clouds. Natural emissions of sulphur are dominated by marine biological production of dimethylsulphide [DMS; (CH3)2S] with sporadic minor emissions from volcanoes. Other sources of marine aerosol such as sea salt, other biogenic gases (e.g. iodinated gases and isoprene) or organic matter produced in phytoplankton blooms may also serve as cloud concentration nuclei (CCN). The combined response of all marine aerosol sources as a potential feedback to climate change is still unclear. Between 15 and 33 1012 g of the volatile sulphur trace gas DMS are emitted annually from the ocean to the atmosphere. This is equivalent to 27–60% of the estimated flux of sulphur from anthropogenic sources and

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makes DMS a significant compound in the global sulphur cycle (Kettle and Andreae, 2000), especially when set against the evidence that man-made emissions in many areas have declined since 1989 (Andreae et al., 2005). Using a modelling approach, Vallina et al. (2007) estimated that globally the DMS contribution to CCN was 30% of the total CCN numbers determined from satellite data. In the oceans, DMS is derived from dimethylsulphoniopropionate [(CH3)2SþH2CH2COO; DMSP] that is produced by some marine phytoplankton, especially the Prymnesiophyceae and Dinophyceae (Stefels et al., 2007). Release of DMSP and DMS to seawater occurs during phytoplankton cell death, grazing and viral mortality and may be passively and/or actively released. Most is utilised by bacteria or oxidised via photochemical processes and the amount of DMS emitted to the air is a few percent of the total DMSP and DMS pool. Recent work suggests that UV light enhances DMS production by phytoplankton and decreases bacterial turnover of DMSP. Climate change could impact on DMS production and emissions via changes in wind intensity, ocean circulation, light field, the relative abundance of DMSP-rich and DMSP-poor phytoplankton types, levels of marine productivity and food web functioning. It is well accepted that sulphate aerosols arising from volcanic and fossil fuel-derived sulphur emissions influence the climate by reducing radiative forcing by direct reflection of radiation back into space and through CCN (Andreae et al., 2005), but as yet modelling studies have not reached true consensus on whether DMS has a significant influence on the Earth’s climate. Gunson et al. (2006) used a coupled ocean–atmosphere general circulation model with an atmospheric sulphur cycle and tested how climate might respond to altered DMS emissions. They altered DMS emissions to half the control simulation value and this increased radiative forcing by 3 W m2 and surface air temperature by 1.6 C. Using a 2 CO2 scenario, Bopp et al. (2004) estimated a 3% increase in global DMS flux that would give a minor negative feedback of about 0.05 W m2, but the regional variation in the model output was large (15% to 30%) and a substantial radiative forcing of 1.5 W m2 was suggested for 40–50 S in summer. Kloster et al. (2007) also found large regional-scale variability and their models predicted a 10% reduction in the global annual mean DMS sea surface concentration and the DMS flux for 2061–2090 compared to 1861– 1890, but the atmospheric DMS burden was reduced by only 3% because DMS would have a longer lifetime in air with a warmer climate. Again the Southern Ocean was identified as a vulnerable region, with DMS levels reduced by 40% and DMS concentrations were also reduced in the mid- and low-latitude regions because of nutrient limitation associated with increased stratification.

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3.11. Concluding comments

Marine methane production by plankton could increase with global warming-induced increases in stratification and nutrient limitation. There has been a pronounced expansion of the large low productivity regions of the world (subtropical gyres), which already far exceeds the predictions of models. Extrapolation on the basis of projected changes in sea surface temperature and nutrients could lead to a substantial reduction in the productivity of the oceans and the efficiency of the Biological pump over the next 100 years. The role of microbes in climate and climate change is crucially important, but little understood and poorly quantified. Developing an understanding of their contribution to biogeochemical and nutrient cycling and microbial diversity is a major challenge for the future. Shifts from a diatom to a flagellate dominated system in temperate latitudes and increased microbial remineralisation in a warming ocean are expected to lead to a less efficient Biological pump. If these changes caused a reduction in the net input of atmospheric CO2 to the oceans, there would be a strong positive feedback to climate change. Large changes have been observed in marine ecosystems in many different parts of the oceans; when seen together they indicate that they are reacting beyond what might be expected from interannual variability. Modelling has shown that changes in ecosystem structure (e.g. types of plankton, physiology, light absorption, food web structure) and export efficiency may be as or more important to understanding interactions with climate than changes in bulk-integrated satellite measures of chlorophyll. The global observing systems needed to measure such variability are rudimentary and concentrated in the Northern Hemisphere at present. The oceans are a major producer of sulphur particulates which seed cloud formation. Changes in the production of all aerosols as seas warm has implications for global warming, but the net effect is unclear. Mismatch between trophic levels and functional groups has implications for ocean–climate interactions, including CO2 drawdown.

4. The Solubility, Biological and Continental Shelf Carbon Pumps 4.1. The ocean carbon cycle The carbon cycle is crucial to climate because it governs the amount of the important greenhouse gases such as CO2 and CH4 in the atmosphere. Methane provides a continuous, transitory supplement as it is slowly

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converted to CO2 in the atmosphere over approximately a 10-year period. The oceans play a crucial role in this cycle as the main reservoir for carbon (32,000 Pg estimated as stored in the deep ocean), other than the long-term storage of carbon in the Earth’s crust. Feedbacks from the ocean carbon cycle and relevant processes are discussed Denman et al. (2007). To quote from the IPCC report, ‘‘small changes in the large ocean carbon reservoir can induce significant changes in atmospheric CO2 concentration’’ and the oceans can also buffer ‘‘perturbations in atmospheric pCO2’’. In the pre-industrial Holocene there was an approximate time- and space-averaged equilibrium between CO2 in the atmosphere and dissolved in the surface ocean. The regional differences in partial pressure in seawater CO2 are due to interactions between biological, chemical and physical processes. Anthropogenic CO2 release to the atmosphere has resulted in a net flux of CO2 from the atmosphere to the ocean that occurred on top of an already active oceanic carbon cycle (Fig. 1.15). Anthropogenic CO2 is absorbed into the water by direct solubilisation, with the dissolved carbon subsequently distributed to depth by mixing and ocean currents. The contribution that biology makes is still far from understood. For example, it is not known if CO2 drawdown increases if plankton are more productive and/or if functional groups such as diatoms are more dominant. Introduced CO2 reacts with water to produce carbonic acid. Subsequent re-equilibration of the dissolved inorganic carbon (DIC) system results in an increase in the concentration of CO2 and carbonic acid, a smaller proportionate (but greater in absolute terms) increase in bicarbonate ions, and a decrease in carbonate ions and pH. There is a marked difference in the concentration of DIC between the deep ocean and the mixed layer at 500 m (Raven and Falkowski, 1999; Fig. 1.16) reflecting net autotrophy of surface waters and net heterotrophy in deep waters that results in a huge reservoir of DIC in the deep ocean. The DIC is transported, directly or as dissolved organic (DOC), particulate organic (POC) or inorganic (PIC) carbon, to the deep ocean by four processes collectively known as ‘carbon pumps’. In the upwelling regions of the world, cold DIC-rich waters from the deep ocean recirculate to the surface where CO2 outgases to the atmosphere to complete the ocean carbon cycle. The four ‘carbon pumps’ (Solubility, Biological, Continental Shelf and Carbonate Counter) sequester CO2, largely as DIC at the surface of the ocean, with additional transfer through the intermediarie POC, DOC and CaCO3 PIC to the deep ocean reservoir that is mostly comprised of DIC. To some extent the Continental Shelf and Carbonate Counter pumps can be considered as subsidiary versions of the Biological pump. The Carbonate Counter pump will be covered more fully in Section 5.

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4.2. Ocean carbon pumps 4.2.1. Solubility pump This pump operates most efficiently at low temperatures where the uptake of CO2 as DIC is much higher due to increased solubility and at high latitudes where water downwells. This process only occurs in the sub-polar seas of the North Atlantic (not in the North Pacific) and in the Southern Ocean. When ice is formed in these polar regions, the released dense brines sink rapidly carrying with them DIC-rich water. Dense water may also be formed below pancake ice, for example in the Greenland Sea or in Arctic polynyas (a polynya is a large area of open water surrounded by sea-ice). A similar process takes place over the Arctic shelf as new ice is formed each

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year with the carbon-rich brines flowing along the bottom and over the shelf edge into the deep ocean. In such regions of deep water formation, carbon is delivered at high concentrations to the deep ocean where the deep circulation (MOC) carries it around the world and keeps it out of contact with the atmosphere for up to 1000 years. It has been estimated that about 25–50% of the steep vertical gradient in DIC (Fig. 1.16) is contributed by this pump. In regions where subtropical mode and intermediate waters are formed (see Section 2), usually by wintertime convective mixing, uptake of CO2 by the Solubility pump provides an intermediate (up to decades) carbon sink (Bates et al., 2002; Sabine et al., 2004a). Sabine et al. (2004a) show, for example, that 40% of the global ocean inventory of anthropogenic CO2 is found south of 30 S and most of that is stored in intermediate and mode water. The fact that CO2 solubility reduces with higher temperatures and salinity is of key relevance to climate change. It is estimated that the Solubility pump has become less efficient in the northern North Atlantic (Sabine et al., 2004a) due to the warmer temperatures that have occurred over the last decade or more and supported by the observed reduction in the density of the deep water found in the Norwegian Sea. A similar reduction in uptake has recently been described for the shallower Japan Sea (Park et al., 2008). Changes over the last few decades in the large-scale atmospheric circulation of the Southern Hemisphere (Thompson and Solomon, 2002) are reflected in the leading mode of Southern Hemisphere climate variability, the Southern Annular Mode (SAM; Thompson and Wallace, 2000). Interannual variability and trends in the SAM also have been shown to drive substantial variability in ocean circulation with a poleward shift and intensification of westerly winds, in upper-ocean biology, and in the uptake and release of CO2 to and from the Southern Ocean (Lovenduski and Gruber, 2005; Lovenduski et al., 2007, 2008). Model simulations suggest that the trend towards more positive SAM conditions has led to a reduction in the strength of the Southern Ocean CO2 sink (Lenton and Matear, 2007; Lovenduski et al., 2007, 2008) by anomalous outgassing due to an increase in upwelling. This hypothesis has been supported by the inversion of atmospheric CO2 data (Le Que´re´ et al., 2007), but remains a subject of intense discussion. While doubts have been raised about the sensitivity of the inversion method to the choice of stations used (Law et al., 2008), of the ocean model to the forcing used (Law et al., 2008; Lovenduski et al., 2008), and whether the ‘saturation’ of the Southern Ocean sink is likely to continue in the future (Zickfeld et al., 2008), the results, for example, Le Que´re et al. (2008) underscore the potential sensitivity of the global carbon cycle to changes in the circulation of the Southern Ocean. A number of climate change experiments reinforce this message by suggesting that increased greenhouse gases may, in turn, drive long-term changes towards

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a more positive SAM state (e.g. Kushner et al., 2001; Miller et al., 2006). Thus, the Southern Ocean carbon cycle, in connection with Southern Hemisphere atmosphere–ocean circulation, winds and stratification could give rise to a positive feedback that would enhance global warming (Friedlingstein, 2008; Lovenduski and Ito, 2009). 4.2.2. Biological pump Through this pump CO2 fixed by photosynthesis is transferred to the deep ocean primarily as dead organisms (including the organic skeletal), faecal material (POC), and carbonate skeletons (PIC; note that calcification produces CO2). This results in sequestration (storage) of carbon for periods of decades to centuries (depending on the depth of remineralisation) or even more permanently in the sediments. Longer-term sequestration may be in the form of organic matter, such as the type of material that is ultimately the source of oil and natural gas. A small proportion of the total annual production of the plankton ends up in the deep ocean, but there is strong evidence to suggest that this pump contributes importantly to the different levels of atmospheric CO2 found between glacial and interglacial periods (Raven and Falkowski, 1999). Plankton can act as ballast for the export of carbon to the deep ocean with the organisms that have mineralised skeletal parts playing an important role. Siliceous diatoms and calcareous foraminifera, coccolithophores and molluscan pteropods and cephalopods are important ballast organisms. Other forms of settling occur via faecal pellets or aggregates and gelatinous plankton. Exopolysaccharide aggregation can increase sinking POC and PIC at a given overall density by decreasing the surface area per unit volume (Engel et al., 2004) and terrigenous materials such as clay may also contribute (Klaas and Archer, 2002). It has even been suggested that POC fluxes may drive mineral fluxes rather than vice versa (Passow, 2004). Although there is much data on the rate of organic carbon sinking in the Biological pump and its determinants, there is still uncertainty as to the nature of a predictive model (Boyd and Trull, 2007; De La Rocha and Passow, 2007; Passow, 2004). To predict future CO2 concentrations in the atmosphere there is a need for a much improved understanding of the way that the Biological pump varies both geographically and temporally and the effects on the pump of changes in temperature, ocean circulation and ocean chemistry (e.g. acidification due to increased CO2). It is not known, for example, if earlier spring blooms or higher Fe input into HNLC areas (e.g. the Southern Ocean) will affect carbon drawdown, or if CO2 drawdown will reduce during prolonged periods of recycled production due to longer summers, nutrient limitation and expansion of the subtropics (e.g. Bopp et al., 2001). Recent studies, for example, van Hoof et al. (2008) indicate that natural decadal variability in atmospheric concentrations of CO2 as measured from leaf stomata in the pre-industrial period from 1000 to 1500 AD were more

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pronounced and faster than proposed in IPCC AR4. They suggest that the variability is driven by oceanic perturbations in temperature and salinity. The extent to which the oceans may contribute to such ‘short-term’ variability is not known. 4.2.3. Continental Shelf pump Continental shelf seas comprise 7% of the surface ocean but provide a disproportionately large fraction (15–30%) of oceanic primary production (Bozec et al., 2005). Thus these regions have a strong impact on the global carbon cycle and provide a net flux to the deep ocean reservoir calculated at 1 Pg C year1 by Tsunogai et al. (1999). Cold, denser water with lower pCO2 is formed in many coastal shelf seawaters at temperate and sub-polar latitudes during the colder periods of the year. As a consequence these are regions of net uptake of atmospheric CO2 by solubilisation that may be enhanced by higher levels of phytoplankton production. Shelf seas may be totally mixed throughout the year or have a pycnocline/thermocline that separates stratified waters from the mixed waters below that are isolated from the atmosphere. A range of complex processes transfer DIC through the pycnocline via the intermediaries POC, DOC and PIC. DIC is then transferred by isopycnal mixing (advection and diffusion) off the shelf to the deep ocean. The transfer to the deep ocean may continue even while the surface layer is isolated by stratification. Material may also be transferred to the deep ocean as POC, DOC and PIC via nepheloid layers and by transport of organic material as fluff along the bottom. In strongly mixed waters as in the southern North Sea (Bozec et al., 2005), the whole water column is in regular contact with the atmosphere and bacterial regeneration ensures that these regions are generally net sources of CO2, especially if they are enriched with nutrients. During stratified summer conditions, carbon export to the mixed waters below the pycnocline is probably reduced and so higher temperatures and the resultant stronger stratification will likely feedback to a reduced export of CO2. It is also estimated that higher nutrient input to these regions, especially in eutrophicated areas, will contribute to increased CO2 drawdown if more nutrients are available. Major works to improve water and sewage treatment in Europe, for example, will thus reduce CO2 drawdown by the Continental Shelf pump. 4.2.4. Carbonate Counter pump This pump operates in parallel with the (organic carbon) Biological pump and covers the production and dissolution of marine organisms with body parts made up of inorganic CaCO3. The phytoplankton (coccolithophores) and zooplankton (foraminifera, pteropods, planktonic larval stages of benthic organisms) and some benthic algae plus many benthic animals,

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including corals, produce body parts made of calcite, aragonite or Mg carbonates. Production of carbonates leads to CO2 release (see Section 5).

4.3. Role of the four ocean carbon pumps Some idea of the importance of these carbon pumps can be gauged from a comparison of the present estimated transfer of carbon by the Biological pump to the deep ocean (see IPCC AR4 WG 1, 2007, Fig. 7.3). A net reduction of only 10% (1.1 Pg year1) would virtually counterbalance the current estimated net input (1.4 Pg year1) (Takahashi et al., 2009) of atmospheric CO2 to the ocean. The relative contributions and importance of the Solubility, Biological, Continental Shelf and Carbonate Counter pumps and their geographical and temporal variability is poorly constrained and needs to be better defined to facilitate modelling efforts. In particular, the importance of mesoscale variability in the carbon pumps is poorly understood at present.

4.4. Species biodiversity and functional groups The diversity of species present in the plankton – from the viruses, bacteria and archaea to the largest zooplankton and fish – is immense and with modern genetic studies the true diversity is expected to be even larger. In addition to this genetic diversity there is also a diversity of function as pertains to the role a species or group of species plays in the ecosystem, including the contribution to carbon turnover by the biological pump. Over long time scales the relative dominance of functional groups is thought to have modulated carbon cycling between the ocean and atmosphere (Falkowski et al., 2003). Plankton assemblages that characterise particular biogeochemical functions are important: in the production, turnover and release of radiatively active gases and their exchange with the atmosphere (e.g. CO2, DMS), in the relative proportion of organic material that is respired near the surface or is sequestered to the deep ocean, and in the cycles of major elements such as nitrogen and silica (Boyd and Doney, 2002, Jin et al., 2006). The concept of functional groups is particularly applied in models to simulate the present and future role (in a changing environment) of biology and to estimate the contribution of organisms to global-scale element cycles (Le Que´re´ et al., 2005). Changes in the relative importance of different functional groups in the plankton can strongly impact the Biological pump; for example, relative fluxes of diatoms versus calcareous plankton have been implicated as one of the causes for the changes in CO2 between glacial and interglacial periods. The changes are attributed to substantial differences between the periods in nutrient inputs to the ocean from dust and rivers, sourced especially during

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glacial times from loess and coastal erosion (Harrison, 2000; Tre´guer and Pondaven, 2000). 4.4.1. Changes in the benthos and sea bottom sediment Benthic organisms and bottom sediments also contribute to the oceanic carbon cycle. Animals with carbonate skeletal systems live over a huge shelf area. It has been estimated (Andersson et al., 2005) that coastal ocean surface water carbonate saturation state will decrease by 46% by 2100 due to acidification, leading to a decrease of 42% over the same period in the biogenic production of CaCO3. Their modelling results also show that the carbonate saturation state of pore water in sediment will decrease in the future due to a greater deposition of both land derived, recycled and locally produced organic matter. This will lead to an increased dissolution of carbonate minerals in the sediments. The future reintroduction of carbon from sediments on the sea floor to seawater due to global warming will have a considerable impact on the atmosphere. Warming of shelf seas will change the rates of microbial production and thus gas exchange and nutrient supply—but potential impacts are largely unknown. Changes in the composition, biomass and production of the benthos of both shelf seas and the deep oceans are also likely to be important—but again the impacts are unknown.

4.5. Global and regional information For modelling evaluation, validation and other studies of the processes involved in the ocean carbon cycle comprehensive information is needed on the spatial and temporal coverage of key parameters over a long period (Boyd and Trull, 2007; Le Que´re´ et al., 2005). Information is available for mean fluxes of CO2 (Takahashi et al., 2002, 2009) and DMS (Kettle and Andreae, 2000; Kettle et al., 1999), but there is limited temporal information. Global-scale observations of chlorophyll did not begin until 1978 with the operation of satellite measurements by the CZCS. SeaWiFS satellites have provided a global coverage of chlorophyll since 1997, although this is constrained by cloud cover in many parts of the world so that the coverage is piecemeal in places and at certain times of the year. New approaches to processing the multi-spectral characteristics of SeaWiFS data means that some individual plankton groups such as cyanobacteria and diatoms may also be estimated on a global scale (Raitsos et al., 2008). High reflectance from coccoliths released into the water after coccolithophore blooms signifies that these phytoplankton can in part be determined on a global scale from satellites (Brown and Yoder, 1994; Iglesias-Rodriguez et al., 2008). Nonetheless, satellite information is inadequate to clarify how these postbloom events relate to carbon export. Also, the most important calcifying species are restricted to deeper water in the subtropics that cannot be detected from satellites. In situ data to calibrate the satellite measurements

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of phytoplankton are limited, and satellites provide no information on zooplankton. The Continuous Plankton Recorder surveys in the North Atlantic (Richardson et al., 2006) and Southern Oceans (Hosie et al., 2003) provide the only comprehensive coverage of selected phytoplankton classes and zooplankton diversity and abundance at monthly and regional, but not global scales. Global information is available from more than 100 sediment trapping experiments (Francois et al., 2002; Klaas and Archer, 2002, Boyd and Trull, 2007) used to determine downward fluxes, regeneration and detrital composition at single-site moorings throughout the ocean. Trap sampling methodologies have not been standardised, so there are problems of interpretation. Furthermore, trap coverage is very restricted, especially on continental shelves. A comparison between modelled estimates of export flux between the last glacial maximum and the present, with superimposed measurements from satellites is shown in Fig. 1.17. This figure further emphasises the limited spatial information that is available from sediment traps for some regions of the world. It is clear that global coverage of key parameters needed to understand the ocean carbon cycle is limited and in most cases restricted to a short time series. This applies particularly to routine synoptic measurements at a species level of plankton that are needed for validation of satellite measurements. Finally, the modelled results in some locations are at odds with other calculations of palaeo-productivity, for example, estimated high productivity in the central Pacific during the last glacial maximum (LGM) determined 80⬚N

LGM > CTL

LGM = CTL

LGM < CTL

LGM ? CTL

40⬚N

0⬚N

40⬚S

100⬚E

160⬚W

60⬚W

40⬚E

100 90 80 70 60 50 40 30 20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100

Figure 1.17 Observed (superimposed circles) and modelled changes in export at the LGM compared to the late Holocene (Bopp et al., 2003). Model results are in percent. Observations are qualitative only and indicate a higher (red), lower (blue) or similar (white) export in the LGM compared to the present day. From Le Que´re´ et al. (2005).

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from barite measurements (Paytan et al., 1996) and from organic matter deposition (Perks and Keeling, 1998).

4.6. Ocean fertilisation Seeding the oceans with iron as a micro-nutrient, an essential nutrient for healthy growth of most phytoplankton species, has been proposed as a mitigation measure against rising levels of atmospheric CO2. General concerns exist that the science behind large-scale fertilisation of the oceans by nutrients (including iron) to increase the sequestration of atmospheric CO2 by the oceans is still poorly understood. These concerns have been debated worldwide, for example, at the Woods Hole Oceanographic Institution in September 2007 (http://www.whoi.edu/page.do?pid¼14617) and at the 30th meeting of the London Dumping Convention and associated London Protocol in December 2007. The latter meeting endorsed the concerns expressed by scientists, declared an intention to develop international regulations to oversee such activities, and advised that large-scale fertilisation schemes are currently not justified. An example of the latest scientific view is given in a press statement by the Scientific Committee on Oceanic Research (SCOR) and the Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP), which can be found here: http://www.imo.org/includes/blastDataOnly.asp/data_id%3D21214/ INF-2.pdf. However, given the urgency of potential climate change impacts, there is a need to continue smaller scale experiments. Such experiments should have similar controls to those outlined by the SCOR and GESAMP statement to determine if manipulation of the oceans might be an effective means of mitigation to help reduce the effects of rising atmospheric CO2.

4.7. Concluding comments

If the combined efficiency of the ocean carbon pumps showed a marked decrease, there would be a strong positive feedback on atmospheric CO2. It is estimated that the Solubility pump may already have become less efficient due to warmer temperatures. There is strong evidence to suggest that the Biological pump contributed importantly to the marked variation in levels of atmospheric CO2 found between Pleistocene glacial and interglacial periods. There is limited understanding of processes and spatial and temporal variability in the Biological pump at the present day and how it may change in the next century and impact climate change. Drawdown of CO2 by the Continental Shelf pump is likely to reduce over the next century due to warmer seas, compounded by improvements to urban waste water treatment.

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Changes in the relative importance of different functional groups in the plankton may impact the Biological pump. Changes in the composition, biomass and production of the benthos and in associated sediments of shelf seas and the ocean are likely to be important to climate change, but the impacts are difficult to assess due to limited data. Small-scale, well controlled experiments in ocean fertilisation should be continued as long as they adopt the controls outlined by SCOR and GESAMP. Global and regional coverage of many of the key biological measurements needed to determine fluxes to the deep ocean, including spatial and temporal variability of plankton functional groups and sediment trapping is limited. Lack of inclusion of some ocean carbon feedbacks in climate change modelling may lead to underestimates of the action required to stabilise emissions at given targets.

5. Ocean Acidification and the Carbonate Pump The important role that the oceans play in the carbon cycle and in the uptake of atmospheric CO2 is described in the previous section. As levels of CO2 in the atmosphere increase due to anthropogenic emissions there is a larger uptake of CO2 by the oceans across the air/sea interface. This transfer leads to higher levels of carbon in surface waters and by reaction, more acidic seawater, which is reflected in a lower pH (pH is a measure of acidity). This process is known as ‘ocean acidification’ (Denman et al., 2007; IPCC AR4 WG 1, 2007, Box 7.3; Raven et al., 2005) and is an independent consequence of rising levels of anthropogenic CO2 separate from the Greenhouse Effect. Additional acidification in some coastal waters derived from anthropogenic nitrogen and sulphur deposition from fossil fuel combustion and agriculture may also increase in the future to further exacerbate the problem (Doney et al., 2007). Levels of pH have declined at an unprecedented rate in surface seawater over the last century and are predicted to undergo a further substantial fall by the end of this century as anthropogenic inputs of CO2 continue to rise sharply (Caldeira and Wickett, 2003). This is against a background where we know that emissions are already going up even faster than the maximum modelled projections of IPCC (Canadell et al., 2007). There is real concern over the impact that such a large, rapid and unprecedented rise in acidification might have on marine organisms (Guinotte and Fabry, 2008; Hall-Spencer et al., 2008; ICES, 2007), but little emphasis has so far been placed on the potential feedbacks from acidification to climate change. Acidification may cause

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positive or negative feedbacks to climate change through alterations in biogeochemical processes, nutrient speciation, trace metal availability and ecosystem biodiversity (Milliman et al., 1999; Raven et al., 2005), changes that may be accentuated in combination with rising temperatures.

5.1. The buffering of climate change by the oceans The oceans have taken up 40% of the anthropogenic CO2 produced from fossil fuel burning and cement manufacture since the industrial revolution (Sabine et al., 2004a). In doing so, the ocean is essentially buffering the effects of climate change from the even more elevated atmospheric CO2 concentrations that it would be experiencing if it was not carrying out this important role. The costs of uptake of anthropogenic CO2 by the surface of the world’s ocean are higher bicarbonate ions, lower carbonate ions, higher hydrogen ions and reduced pH (i.e. a more acidic surface ocean). It should be noted that the oceans will not become truly acidic as their pH will remain above 7, even with the worst case scenario, due to the intrinsic buffering capacity of the oceans (this is the ability of a fluid to sustain a certain pH; in this particular case while absorbing CO2). Anthropogenic emissions cause an increase in the partial pressure of atmospheric CO2 (pCO2,atm). As pCO2,atm is typically larger than its equivalent over most of the upper mixed layer of the ocean (pCO2,ocean), there is a net flow of CO2 from the atmosphere to the ocean. Note, however, that there is considerable spatial variability in relative net fluxes (see Section 4 and Fig. 1.18). During the dissolution of atmospheric CO2 in seawater, most reacts rapidly with the water (H2O) to produce carbonic acid at the same time as lowering pH. The reaction continues to produce bicarbonate ions and carbonate ions. This chain of reactions forms the carbonate buffer system that enables the ocean to take up much more CO2 than would be possible from solubility alone. Only the remaining unreacted carbon dioxide fraction of DIC in the seawater takes part in ocean–atmosphere interactions (Denman et al., 2007; Zeebe and WolfGladrow, 2001). In typical seawater, the products of the reactions (Fig. 1.18) occur in the approximate proportions and ratios: Bicarbonate (HCO3 ) Carbonate ions (CO32 ) Remaining aqueous carbon dioxide (CO2) Remaining carbonic acid (H2CO3)

90% 10% 1% Negligible

The sum of these various breakdown products of former atmospheric CO2 are termed DIC: DIC ¼ ½CO2 þ ½HCO3 þ ½CO32 þ ½H2 CO3

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[CO32− ] (mmol kg−1)

CO2

CO2 + H2O => HCO3− + H+

800 600 400

H+ + CO32− => HCO3−

200 0

0 200 400 600 800 [CO2]atm (ppm)

CaCO3 => Ca2+ + CO32− (coral)

Figure 1.18 Linkages between the build-up of atmospheric CO2 and the slowing of coral calcification due to ocean acidification. Approximately, 25% of the CO2 emitted by humans in the period 2000–2006 was taken up by the ocean where it combined with water to produce carbonic acid, which releases a proton that combines with a carbonate ion. This decreases the concentration of carbonate, making it unavailable to marine calcifiers such as corals. Figure from Hoegh-Guldberg et al. (2007).

A net result of the chain of chemical reactions is that carbonate ions (CO32 ) are neutralised and reduced as a proportion of the DIC. On a global scale, this process means that the overall buffering capacity is reduced as levels of atmospheric CO2 rise and more hydrogen ions (Hþ) remain in solution. This will increase acidity (reduce pH). A summary explanation of the terms pH, DIC, carbonate buffer, carbonate saturation horizon, and a more detailed outline of the various reactions is given in Appendix 1 of Raven et al. (2005). In equilibrium, the increase in dissolved CO2 in the surface ocean is proportional to the atmospheric pCO2, but the increase in DIC is not proportional to pCO2,atm. This is due to the carbonate buffering capacity of seawater, which results in a smaller pH change, and can be explained by the Revelle factor (Zeebe and Wolf-Gladrow, 2001). The Revelle factor (or, previously buffering capacity factor) ranges between 8 and 15 units, depending on temperature and pCO2. Due to the buffering capacity, an increase in DIC caused by acidification does not correlate with a 1:1 ratio to

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Table 1.1 Changes in surface ocean inorganic carbon chemistry assuming equilibrium with atmosphere

Atmospheric CO2a Surface ocean CO2b Surface ocean HCO3 b Surface ocean CO32 b Surface ocean total dissolved inorganic Cb Surface ocean pH

Preindustrial

280 9 1766 225 2003 8.18

Present

Twice preindustrial

Thrice preindustrial

380 13 1876 185 2065

560 19 1976 141 2136

840 28 2070 103 2201

8.07

7.92

7.77

a

mmol mol1. mmol kg1. Total alkalinity 2324 mmol kg1, 18 C (modified from Table 1 in Raven et al., 2005). b

the increase of atmospheric CO2 but rather 1:10. Thus, the increase to the present day in atmospheric CO2 of 100 ppm from the pre-industrial 280 ppm represents a rise of 36% whereas DIC has only increased by 3.1% (Table 1.1), approximately a 10-fold difference.

5.2. Carbonate formation A second major process within the carbon chemistry of the ocean that has a crucial long-term role (see later section) in modulating levels of atmospheric CO2 is the production of carbonates. Three types of minerals may be formed: calcite (CaCO3), aragonite (CaCO3) and magnesium (Mg) calcites, each with different solubility characteristics defined by their saturation state (symbolised by omega, O). Since calcium (Ca2þ) is extremely abundant in seawater and as a result its concentration difficult to alter, the saturation state 2þ of seawater with respect to calcium carbonate (O ¼ ½CO2 3 ½Ca =Ksp ) is almost always most strongly influenced by changes in the carbonate ion concentration. The formation of the different forms of CaCO3 (see equation below) requires the presence of water that is supersaturated with carbonate ions, as is typically found at present in most of the upper mixed layer of the ocean. Ca2þ þ 2HCO3 ! CaCO3 þ CO2 þ H2 O In the reaction that produces carbonates, DIC is reduced, alkalinity consumed, CO2 released, acidification increased and pH lowered.

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The solubility of calcium carbonate increases with pressure (depth) and with lower temperature. In consequence each of the three minerals has a different depth where O changes from saturation (>1) to undersaturation (<1). Below this depth, known as the saturation horizon, the minerals will dissolve unless they are protected by an organic membrane as part of a living organism or detrital aggregate. The depth horizon at which CaCO3 starts to disappear from the sediments is known as the lysocline, and the depth at which it (almost) completely disappears is known as the ‘compensation depth’ in sediments. The lysocline and compensation depth are shallower for Mg carbonate, aragonite and calcite in that order. As the seawater saturation state of the North Pacific is lower than the North Atlantic, the aragonite saturation horizon almost reaches the surface in the North Pacific while it is at approximately 3000 m in the North Atlantic (Fig. 1.19). For the calcite form of CaCO3 the saturation horizon varies between less than 1000 m in the North Pacific and more than 4500 m in the North Atlantic. While calcification by carbonate minerals may, in favourable conditions, occur by precipitation, the vast majority is secreted by pelagic and benthic organisms to form complex tests and skeletal structures. Important calcifying groups include the microscopic protist foraminifera, algal coccolithophores that utilise calcite, corals and bivalves (including the pelagic pteropods with aragonitic structures and coralline algae supported by Mg calcite). Some of these organisms play a key role in the biological and carbonate pumps and form extensive areas of calcareous ooze on the bottom of the ocean. In polar regions, the lysocline comes much closer to the surface and, as carbonates dissolve more readily in cold water, polar and sub-polar waters are particularly vulnerable to future changes in ocean carbonate chemistry. There is already evidence that the saturation horizons for aragonite and calcite are shoaling (Orr et al., 2005) and organisms such as pteropods are thus especially under threat. This is an additional vulnerability for Antarctic and Arctic waters over the next century (Fig. 1.20) to those caused directly by climate change (Andersson et al., 2008). There have been observations to suggest that some pelagic and benthic marine organisms may increase their calcification rates with increasing acidification (Iglesias-Rodriguez et al., 2008; Wood et al., 2008a). However, the majority of experiments, models and field observations to date show a deleterious impact on calcifiers from acidification. It should be noted that the ‘sudden’ changes in pH in these short-term experiments may not be representative of nature and that to some extent organisms may be able to adapt to the slower longer term projected changes. This is a key area for research as the implications either way are important.

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A

Depth (m)

Aragonite saturation depth

80⬚N

3500 3250 3000 2750

40⬚N

2500 2250 2000

0⬚

1750 1500 1250

40⬚S

1000 750 500 250

80⬚S

0

50⬚E

150⬚E

110⬚W

10⬚W

Model

Depth (m)

B 80⬚N

3500 3250 3000 2750

40⬚N

2500 2250 2000

0⬚

1750 1500 1250

40⬚S

1000 750 500 250

80⬚S

0

50⬚E

150⬚E

110⬚W

10⬚W

GLODAP

Figure 1.19 Depth of aragonite saturation horizon: lower map from measurements recalculated from GLODAP after Key et al. (2004) and upper map modelled calculations. Figure from Gangstø et al. (2008).

5.3. Carbonate dissolution As atmospheric CO2 increases in the long-term and penetrates deeper into the ocean due to the THC and downwelling and via the solubility, Biological, Carbonate and, ultimately, the shelf sea pumps, the lysoclines for calcite, aragonite and Mg calcite will shoal (come closer to the surface). Previously sedimented carbonates will start to dissolve increasing dissolved

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A

B

Mean omega aragonite

4.5 3.5

40⬚N

Global ocean

0⬚

2.5 1.5

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N Equatorial area

40⬚S

High latitudes

80⬚S

0.5 1900

1950 2000

2050

50⬚E

2100

C 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N 40⬚N 0⬚ 40⬚S 80⬚S 50⬚E

150⬚E

110⬚W

E

0⬚ 40⬚S 80⬚S 50⬚E

150⬚E

110⬚W

2075

40⬚N 0⬚ 40⬚S 80⬚S

10⬚W

150⬚E

110⬚W

10⬚W

2050

F

40⬚N

10⬚W

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 50⬚E

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N

110⬚W

80⬚N

10⬚W

2000

150⬚E

1861

D

80⬚N 40⬚N 0⬚ 40⬚S 80⬚S 50⬚E

150⬚E

110⬚W

10⬚W

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

2100

Figure 1.20 Saturation state with respect to aragonite of surface waters (0–100 m): (A) time series of mean O for the global ocean, the equatorial area and for high latitudes, and maps in year (B) 1861, (C) 2000, (D) 2050, (E) 2075 and (F) 2100. Figure from Gangstø et al. (2008).

carbonate alkalinity. Total alkalinity, which in terms of ocean buffer capacity is more important, will also increase. Thus, when the water returns to the surface over a timescale of several centuries, further CO2 can be removed from the atmosphere and acidification of surface waters will be partly reversed. In a world of increasing CO2 the dissolution of calcium carbonate can be expressed as CO2 þ CaCO3 ðsÞ þ H2 O ! 2HCO3 þ Ca2þ Dissolution of CaCO3 minerals in the surface layers of the oceans acts as a further buffer of pH and carbonate saturation state against acidification from an increasing ocean uptake of atmospheric CO2 (Andersson et al., 2006). However, ‘‘CaCO3 dissolution has a negligible impact on atmospheric

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pCO2 or the atmospheric stabilisation of CO2 emissions’’ over the next few centuries (Archer et al., 1998). Even if dissolution of CaCO3 was taking place at a rate equivalent to the estimated total annual production of CaCO3 in surface waters, it would still only be partially buffered (estimated maximum 6%). This is especially so as most CaCO3 production is pelagic and sinks to deeper depths (Andersson et al., 2006). Dissolution from bottom sediments as the lysocline shoals in response to the reduction in pH over the next century and longer will enable the oceans to increase their CO2 sink.

5.4. Uptake of CO2 by the ocean There is evidence that key ocean sinks for CO2 (the North Atlantic and Southern Ocean) may already be reducing their rate of CO2 uptake (Le Que´re´ et al., 2007, 2008; Schuster and Watson, 2007). However, these measurements have not yet been taken over sufficiently long periods to distinguish whether this is from natural variation, changes in buffering or other causes. In the North Atlantic, for example, the reduced uptake has been linked to a decline in mixing and ventilation between surface and subsurface waters. This is due to increasing stratification associated with changes in the NAO, exacerbated by the changing buffer capacity of seawater as the carbon content of surface waters increased (Schuster and Watson, 2007). Sustained backbone observations such as carried out in these studies are important to continue but are under threat. Over time periods of <10,000 years, the ocean is particularly sensitive to increases in pCO2. On a longer term basis, the buffering capacity of the ocean will become greater (as measured by the Revelle factor), as buffering caused by the dissolution of carbonate sediments moderates the effect of pH change. On a 1000–100,000-year timescale, it is estimated that CaCO3 dissolution will absorb 60–70% and the oceanic water column 22–33% of anthropogenic CO2 emissions (Denman et al., 2007). Thus, eventually, the oceans and their sediment CaCO3 will buffer or neutralise the CO2. However, the new concentration level of CO2 in the atmosphere will never return to pre-industrial levels (Andersson et al., 2003, 2005; Archer et al., 1998). High atmospheric CO2 does not automatically correlate with lower pH, because it can vary while pH remains constant if DIC changes. This fact is particularly relevant to the interpretation of palaeo-evidence where acidification and calcification were thought to be high at the same time. If acidification takes place gradually, as appears to have occurred at times in the geological record, then some of the potential change in pH may be absorbed by dissolution of sediments. During the Palaeocene–Eocene thermal maximum (PETM), it is calculated that following the initial acidification there was a widespread dissolution of sea-floor carbonates, a pattern

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that replicates modelled response to the anthropogenic rise in CO2 (Zachos et al., 2005). Changes in temperature may also alter pH, but any feedback to climate is likely to be trivial. Any effect is likely to be in the other direction as warmer waters absorb less CO2. Warmer temperatures will increase stratification and thus reduce the volume of mixed water available for CO2 absorption from the atmosphere (Raven et al., 2005). And as a further consequence the increased stability will lead to a reduction in the return flow of carbon and nutrients from the deep ocean, reduced primary production and thus lower uptake of CO2.

5.5. Projected future levels of acidification Recorded on a logarithmic scale, pH has reduced as a global average in surface seawater since the beginning of the industrial revolution by 0.1 units (current mean level pH 8.08, pre-industrial 8.18, last glacial maximum 8.35). This is equivalent to a 30% increase in the concentration of hydrogen ions (pH is a measure of the free positive hydrogen ion concentration; measured in seawater as the total concentration; see Zeebe and Wolf-Gladrow, 2001). With continued ‘business-as-usual’ use of fossil fuels, pH is estimated to decrease by a further 0.4 by 2100 and 0.77 units by 2300 (Caldeira and Wickett, 2003). The rate of change and degree of change are unprecedented for likely the last 20 million years (Raven et al., 2005; Fig. 1.21) and possibly since the PETM, 55 million years ago (Zachos et al., 2005). The most pronounced changes in acidification are seen in the North Atlantic extending down to 5000 m, a much deeper depth than previously thought, due to the deep water formation that occurs there 8.6 8.4

pH

8.2 8

1800 2000 2050 2100

Oceanic pH

7.8 7.6 7.4 −25

−20

−10 −5 −15 Time (million years before present)

0

5

Figure 1.21 Changes in the level of seawater pH over more than the last 20 million years. Geological estimates (white diamonds) taken from Pearson and Palmer (2000) (method considered by some researchers to be unreliable when older than a few million years). Calculated mean oceanic pH levels for 1800 and 2000 shown on a vertical line against dates with modelled future predictions for 2050 and 2100 based on IPCC mean scenarios (grey diamonds with dates). Figure from Turley et al. (2006).

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(Tanhua et al., 2007). These changes reflect a high input of anthropogenic carbon and possibly indicate that the oceans can take up more carbon than previously thought over the next century.

5.6. Regional variation in acidification Changes in acidity measured in the open ocean appear to be extending to some shelf seas. For example, Feely et al. (2008) have shown a pronounced shoaling and an increase in the extent of upwelled undersaturated water on the western continental shelf of North America. This region of the Northeast Pacific has one of the shallowest aragonite saturation horizons in the globe and it appears to have shoaled by about 50 m as a response to acidification now allowing acidified waters to penetrate extensively onto the shelf. The impact has been pronounced with deoxygenation and mass mortality of benthic organisms. If a similar situation arose in the Arctic it might further exacerbate the vulnerability of calcareous organisms in this ocean to acidification. Within the second half of the last century input of bicarbonate (DIC) by the Mississippi river increased substantially, primarily as a consequence of human agricultural changes. This marked change in one of the major rivers of the world may have provided a localised buffering system for ocean acidification in parts of the Gulf of Mexico (Raymond et al., 2008). It is not clear how such regional variability in acidification might feedback to climate change. 5.6.1. Carbonate biology: Plankton Laboratory and field observations suggest that ocean acidification enhances photosynthetic carbon fixation in the major phytoplankton functional groups of the modern ocean namely cyanobacteria nitrogen fixers (Hutchins et al., 2007), diatoms (Tortell et al., 2000) and coccolithophores (Iglesias-Rodriguez et al., 2008; Riebesell et al., 2000, 2007). Unlike in corals, the effect of ocean acidification on calcium carbonate-producing phytoplankton is, however, unclear, and shows a non-uniform response across species in laboratory experiments (Iglesias-Rodriguez et al., 2008; Langer et al., 2006; Riebesell et al., 2000) although most experiments, including recent ones (Feng et al., 2008), have shown a decline in the ratio of inorganic/organic carbon in coccolithophores at higher CO2. These laboratory experiments may, however, not reflect natural oceanic conditions. In the open ocean, the effect of ocean acidification on calcification remains an open question. It is the balance between calcification and photosynthetic carbon fixation that controls whether calcifying phytoplankton represent a sink or a source of CO2 to their surrounding environment (see Frankignoulle et al., 1994), and this information is crucial to elucidate changes in the contribution of taxa to changes in the magnitude and direction of CO2 fluxes. Assessing the variability of responses across taxa

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is a challenge, particularly in the light of evidence of variability in other calcifying groups within marine invertebrates (Ries et al., 2008; Wood et al., 2008b). Whether intraspecific physiological variability adds to the complexity of these responses or whether natural populations respond uniformly to changes in carbonate chemistry is the next step in assessing the reciprocal interactions between changing pCO2 and the carbon signature associated with biotic responses to ocean acidification. Higher ocean pCO2 will lead to increased acidity, a lower pH and lower relative calcium carbonate saturation (omega). A temperature rise will, however, increase the relative calcium carbonate solubility, omega. Any effects from a combination of a reduction in pH and rise in temperature will depend on the relative rates of change of the two variables. 5.6.2. Carbonate biology: Coral reefs While only covering 2% of the area of continental shelves, corals through their calcification account for 33–50% of the global production and accumulation of inorganic CaCO3 (PIC) (Borges, 2005). There is now, however, considerable evidence that these levels of coral calcification will be severely impacted by future projected ocean acidification (Tyrrell, 2008). A linear relation has been demonstrated between saturation state and calcification for coral reefs, but these experiments were performed in biospheres and tanks where the corals were stressed and growing at a slower rate. Recent research has shown, however, that in combination with rising temperatures calcification rates have already declined (De’ath et al., 2009). It is estimated that lower rates of calcification will lead to a reduction in coral CaCO3 on a global scale of between 9% and 30% over the next 50–100 years (Gattuso et al., 1999; Kleypas et al., 1999). A range of experimental results show that coral calcification, structure and growth will be reduced by up to 40% for a doubling of pre-industrial atmospheric CO2 to 560 ppm (Hoegh-Guldberg et al., 2007; Wood et al., 2008b). These authors also showed, both experimentally and by comparison with present distributions, that aragonite formation ceases at saturation values of 3.3. Acidification, however, is not the only process impacting coral reefs; other phenomena such as extreme temperatures (coral bleaching), viral attacks, starfish predation, dust and precipitation as well as over fishing, pollution and physical damage also need to be taken into account. The prognosis for reef corals is dire with serious consequences for the many millions of people who depend on them for their homes and livelihoods, as biodiversity hot spots, for shore protection, local fisheries and tourism (Carpenter et al., 2008; Hoegh-Guldberg et al., 2007; Pandolfi et al., 2003). Because of shoaling of the aragonite lysocline, cold water corals are also seriously threatened by acidification. However, the ability of coral species to adapt to change, and especially to the rapid rate of change in pH is not yet clear.

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While corals only cover a small area of the global ocean, they are expected to continue to be major players in the carbon cycle over the next 100–1000 years because the formation and deposition of CaCO3 during their growth is so intense and because rather little of it dissolves. The breakdown of coral reefs in glacial periods due to lower sea-levels is considered. (Coral reef hypothesis of Berger (1982) as one of the possible causes of the alternation of CO2 levels between glacial and interglacial times Kleypas et al., 2006.) 5.6.3. Carbonate biology: Benthos In attempting to identify the impact of ocean acidification on the marine benthos, it would be unrealistic to focus excessively on the impacts of lowered pH on animals with calcareous body parts. The physiology of the marine biota is finely regulated and has evolved to function within relatively narrow pH and CO2 ranges (Michaelidis et al., 2005). In a more acid ocean, animals operate under sub-optimal conditions and hence energy apportionment between respiration, repair, growth and reproduction will change. The latter two processes will suffer as more energy is consumed by repair and respiration. While there has been considerable concern about the impacts of ocean acidification on animals with calcareous body parts, some species appear to be able to increase the rate of calcification at a lower pH (Wood et al., 2008b) although this is at some metabolic cost and may not be sustainable. There are therefore large uncertainties in the adaptation capabilities of marine species and functional groups and, in consequence, any feedback effects to marine climate. The scale of impacts on populations and assemblages resulting from a decline in growth and reproductive rates has yet to be quantified, but it is believed that coralline algae are particularly vulnerable as they utilise Mg calcite. Experimental studies by Albright et al. (2008), Jokiel et al. (2008) and Kuffner et al. (2008), for example, have shown a marked reduction in the growth and recruitment of both coralline algae and corals at elevated levels of pCO2 comparable to those likely to be experienced near the end of the century. Hall-Spencer et al. (2008) have demonstrated the effects of acidification by studying shallow benthic ecosystems adjacent to volcanic CO2 vents along pH gradients. Rocky shore communities with abundant calcareous organisms showed significant reductions in sea urchins, coralline algae and the absence of scleractinian corals at the extreme of the gradient with evidence of dissolution of gastropod shells.

5.7. Carbonate pump This pump involves the production and dissolution of the three calcium carbonate minerals (primarily calcite and aragonite), their transport to the deep ocean by sedimentation and a contribution to increased levels of pCO2

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in the surface ocean. Some of the pCO2 will escape out of the ocean to contribute in a small way to increased levels of atmospheric CO2. This pump is termed the CaCO3 counter pump in Denman et al. (2007). Sedimenting coccolithophores, calcareous resting cysts of dinoflagellates, foraminifera and pteropods form most of the settling material. The mineral component may, because of its higher density, provide an important ballast that ensures that detrital material from the dead organisms settles rapidly within aggregates, mucus nets and faecal pellets. Measurements from sediment traps have shown that the net deposition rate in the carbonate pump is comparable to the organic matter that is deposited by the biological pump. The highest production of carbonate minerals is in coastal upwelling areas and within subtropical gyres. Any reduction in calcification due to acidification of planktonic organisms could have a serious impact on the rates of settling out of both organic and calcareous material from the plankton with important feedback implications. The subtropical gyres play a large role in carbonate production (Carbonate pump) and are predicted to expand in area, but not in productivity, in a warming world (Behrenfeld et al., 2006). They are sensitive areas, but not the focus for much research or monitoring. There is limited understanding of the different regions where both the biological and carbonate pumps are most active, but some indication can be seen from bottom sediment distribution (Fig. 1.22). 90

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Based on the global carbonate budget calculated by Milliman et al. (1999), about 20% of the pelagic carbonate production accumulates in deep sea sediments (Fig. 1.23). These authors also estimate that 60–80% of the planktonic calcium carbonate formed is dissolved in the upper 500– 1000 m of the ocean by reprocessing and packaging in the guts of zooplankton and settling aggregates. Previous to this study it was thought that dissolution did not take place until particles settled below the carbonate lysocline. This dissolution buffers acidification and if it is within the penetration layer for anthropogenic CO2 would allow the oceans to take up more CO2 (Milliman et al., 1999). Shallow-water benthic production of carbonate minerals is also important both within and above the sediment, but little of this material will end up in the deep ocean. Potential dissolution of carbonate minerals on the shelves in the future as pH levels fall further may have important implications for shelf ecosystems with unknown feedbacks to the carbon cycle. The Biological pump is also likely to be seriously affected by acidification through change in plankton ecology and in the physiological processes involved in organic and carbonate production.

5.8. Nutrients It is known that there are interactions between nutrients (including DIC), and photosynthetically active radiation (PAR) in the way that algae take up and assimilate DIC. Most algae, as well as corals and seagrasses, have concentrating mechanisms which can increase the rate of CO2 assimilation, especially at low DIC concentrations (Giordano et al., 2005). The discovery of the widespread and abundant occurrence of PR genes in the oceans

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opens up the possibility of ‘a previously unrecognised pathway of energy capture on Earth’ by heterotrophic bacteria (Karl, 2007); the consequences for biogeochemical cycles are as yet unknown. Changes in the availability of ammonium or nitrate as the nitrogen sources and of the supply of phosphorus and iron can also affect uptake rate and growth. It is expected that these effects will modulate the way in which growth by photosynthetically different primary producers respond to increased CO2, but much more research is needed before confident predictions can be made. In considering the effects of increased CO2 on growth above it was pointed out that CO2 assimilation continues to increase with rising CO2 even after growth (cell division rate) has saturated. This will alter the food quality to the next, and perhaps higher, trophic levels. It is not clear if there are biologically important effects of the changes in ionisation state with decreasing pH of, for example, ammonium and phosphate. Finally, pronounced changes in N2 and CO2 fixation rates have been described from experiments on the cyanobacteria Trichodesmium at atmospheric levels of CO2 up to 1500 ppm, implying potentially large impacts on the N and C cycles and on phosphate availability (Hutchins et al., 2007).

5.9. Palaeo-comparisons By measuring CO2 in bubbles of air (Fig. 1.24) in layered ice cores from both Antarctica and Greenland, the cyclic alternation of CO2 and temperature between Pleistocene glacial and interglacial periods has been documented and recently extended back to 800,000 years before present (Luthi et al., 2008). From the last glacial maximum to prior to the industrial

Water H2O H218O HDO

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Figure 1.24 Bubbles of air in polar ice observed in a thin section under polarised light. Text redrawn from Raynaud D. EPICA lecture (2008 Ocean Sciences Meeting, Orlando, USA). Image: Copyright Michel Creseveur, CNRS/LGGE.

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revolution CO2 levels in the atmosphere increased by 40%, likely representing a release from the ocean reservoir. It should be noted, however, that ice core CO2 measurements are ‘smoothed’ by diffusion and dating problems. Higher resolution data from oak leaf stomata reveal more ‘natural’ variation (up to 34 ppmv) of CO2 in the millennium (van Hoof et al., 2008). The authors show that their stomata-based CO2 trends correlate with changes in Atlantic SST trends and suggest that this may indicate that changes in oceanic sources/sinks may be the mechanism behind the recorded CO2 variability. Prior to the Pleistocene, atmospheric concentrations of CO2 have to be determined from proxies or are calculated using geochemical models. At timescales of millions of years during the Phanerozoic atmospheric CO2 was dependent on the balance between volcanic sources (there were major periods of volcanic activity in Earth history) and consumption of CO2 by weathering of silicate minerals in terrestrial rocks (this process is rate dependent on temperature) followed by deposition of carbonate sediments on the sea floor (Franc¸ois et al., 2005) and by changes in photosynthesis. On timescales of tens of thousands of years, weathering does not affect major ocean chemistry to any great degree; such changes take place in the longer term. Rates of organic carbon deposition in rocks are also important. Both the latter rates and weathering are highly dependent on evolution, especially of the angiosperms, as well as extinction events and tectonic activity (Berner and Kothavala, 2001). The geological record provides evidence of major changes in ocean chemistry that are linked to levels of atmospheric CO2 such as fluid inclusion and other evidence that calcium concentrations approximately halved and magnesium concentrations approximately doubled over the last 100 million years (e.g. Tyrrell and Zeebe, 2004). Mackenzie and Pigott (1981) were the first to note that the carbonate oolites and cements in calcareous sediments oscillated between calcite/dolomite and aragonite through geological time (subsequently termed calcite–dolomite or aragonite seas). Later work showed that biological skeletal precipitates show the same alternation. These periods reflect changing environments and climate as well as Mg to Ca ratios in seawater, and atmospheric and seawater CO2 concentrations (Arvidson et al., 2006). Using the MAGic model of Arvidson et al. (2006) and a relatively small number of calculated chemical parameters, Mackenzie et al. (2008) characterised the history of atmosphere and ocean composition during the Phanerozoic Eon (the last 545 million years). The two major oscillatory chemostatic modes (Fig. 1.25) are distinguished by differences in seawater carbonate saturation state, major ion chemistry, especially SO4/Ca and Mg/Ca ratios, degree of ocean acidification, and atmospheric CO2. The computed trends agree with fluid inclusion data for Mg/Ca and SO4/Ca ratios through Phanerozoic time and the mineralogy of the dominant carbonate precipitates. During the earlier part of the Phanerozoic (the Palaeozoic),

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seafloors were covered in carbonates and atmospheric levels of CO2 were very high in contrast to the succeeding Mesozoic and Tertiary when terrigenous silicilastic sediments predominated (Peters, 2008). In the Cretaceous (Fig. 1.25) high levels of atmospheric CO2 coincided with high rates

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of CaCO3 formation, including the proliferation of coccolithophorids. An important element of the high CO2 world at that time was the higher sealevel, which meant that the area covered by shelf seas was much larger allowing the deposition of extensive layers of chalk. The modelling of Arvidson et al. (2006) suggests that pH was low and carbonate saturation state higher in the Cretaceous. There is however, a contrasting view, that the Cretaceous ocean may not necessarily have been acidic and that the modelled saturation states proposed above would have made the calcite compensation depth too deep. Andersson et al. (2008) have proposed the hypothesis that the more modern Earth system, in terms of the mineral composition of biogenic calcifiers and carbonate sediments, and because of rapidly increasing levels of atmospheric CO2 and ocean acidification, may currently be in process of a transition from an aragonite sea to a condition that is more characteristic of a calcite sea. If such an event occurs it will be without a change in the Mg/Ca or SO4/Ca ratios of seawater. It is predicted however, that the Mg content of calcitic hard parts in marine organisms is likely to decrease, the proportion of stable carbonates formed (e.g. calcite) increase and the Mg content of carbonate sediments decrease. Such changes have occurred in geological time and have been accompanied by profound alterations in marine ecosystems and biogeochemical processes.

5.10. Concluding comments

The impact on climate change from ocean acidification is unclear. The structure of marine ecosystems and the physiological responses of marine organisms are expected to be severely impacted by acidification with potential extinctions, primarily because of the speed of change that is taking place. Reduction in carbonate mineralisation due to acidification may have an important impact on ballast in sedimenting particles, likely leading to more recycling in the upper ocean and a lower uptake of atmospheric CO2. Changes in the relative location and intensity of the biological and carbonate pumps may have important feedbacks to climate change. While corals cover only a small part of global shelf systems they are still expected to be major players in the carbon cycle over the next 100–1000 years due to their intense growth and limited dissolution. Acidification is expected to have very serious consequences for the survival and growth of corals. Over a timeframe of thousands of years the oceans will be able to continue to take up much, but not all, anthropogenic CO2 due to carbonate dissolution in the deep sea.

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6. A Special Case: The Arctic and Seas Adjacent to Greenland 6.1. Climate change in the Arctic Ocean and Subarctic seas The Arctic Ocean (Fig. 1.26) has a central role in global climate. Its key attributes are its high latitude, marked seasonality of insolation, unique enclosed nature and high reflectance of sunlight (albedo) from sea-ice, adjacent glaciers and snow cover. Enclosing the ocean is a terrestrial

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environment that is dominated by the cryosphere, either seasonally on the surface, or permanently just below the surface (i.e. permafrost). As a result of a strong ice–ocean influence, small changes in temperature and salinity may trigger large and sudden changes in regional climate with potential downstream feedbacks to the climate of the rest of the world. It is clear from the Arctic Climate Impact Assessment (ACIA, 2005), the IPCC AR4 and more recent publications that the Arctic region as a whole is changing rapidly. While there are few long-term measurements, it is thought likely that Arctic air temperatures have been increasing since the beginning of the last century and certainly since the 1950s, when more observations became available. During the twentieth century, it is estimated that the Arctic warmed at a rate that was 50% faster (0.09 C compared to 0.06 C per decade) than the average for the whole of the Northern Hemisphere (ACIA, 2005; Fig. 1.27). However, Polyakov et al. (2002) consider that the Arctic long-term trend may not have been amplified with respect to the global trend, and instead that the difference is a consequence of poor seasonal sampling coverage in the Arctic that is hiding pronounced interdecadal variability. New research by Kaufman et al. (2009) has shown that the Arctic cooled progressively over the last 2000 years until 1900 since when the trend reversed sharply to give from 1950 four of the warmest decades in two millenia. Precipitation has also increased and, together with the temperature increase, has led to a chain of other rapid changes within the last two decades including rising river flows, changes in ocean salinity, thinning of permafrost, declining snow cover, melting of glaciers and the Greenland ice sheet, rising sea-levels and most markedly rapid retreat of summer sea-ice extent and a reduction in its thickness. 0.08 0.06

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6.2. The circulation of the Arctic Ocean and sub-polar seas Warm input to the Arctic Ocean comes from extensions of the Gulf Stream (Fig. 1.28). The North Atlantic Current and the European Slope current releasing heat and water to the atmosphere en route. These currents continue north into the Arctic via the Norwegian Sea, as an outer meandering and a topographically constrained current at the edge of the shelf. As the warm saline Atlantic water moves into the Arctic Ocean and loses heat it becomes denser and sinks beneath a cold halocline layer (200 m) and circulates throughout the Arctic Ocean. Mixing and diffusion spread both heat and salt upward into the surface waters. The counterbalancing deep outflow from the system is fresher and primarily driven by temperature with sources from the Arctic shelf seas and deep convection sites in the Greenland and Labrador seas. This water forms the southern out-flowing limb of the MOC in the North Atlantic. The exchange of water and heat is delicately balanced and highly dependent on the rate of sea-ice formation that in turn is governed by temperature and salinity. The upper surface of the cold and dense Arctic-sourced bottom water in the Norwegian Sea has lowered markedly over the last two decades (Dickson et al., 1996). This suggests that dense water formation has declined, and implies that the MOC might also have been reduced. At present, however, there is no indication of a slowing of the MOC (see Section 2), but some strong evidence for increased inflow of warm saline Atlantic water into the Barents Sea and Arctic that falls counter to this suggestion. The cold, dense water emanating from the Arctic has a further hurdle to cross before it becomes incorporated into the main circulation of the MOC in the North Atlantic. The relatively shallow sills that extend between

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Schematic of Arctic circulation (ACIA, 2005).

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Greenland, Iceland the Faroes and Scotland with the two main overflow points through the Denmark Strait and the Faroe Shetland Channel mean that there is no direct connection between the Arctic and the global ocean (Hansen et al., 2008). Understanding and measuring the variability of outflow and inflow at these two sites as part of the MOC has and will continue to be a major area of research into the future (Dickson, 2006; Dickson et al., 2008).

6.3. Runoff from Arctic rivers Increased melting of permafrost and higher levels of precipitation in Russia and Canada (ACIA, 2005) has led to a considerable increase in river runoff to the Arctic. This is in turn leading to changes in nutrients and circulation. Ice-free coastal waters are likely to be more turbid and less productive due to light limitation, in addition to showing increased stratification due to riverine inflow. Basin wide, higher river flows will increase the intensity of the Arctic’s haline stratification. Both increased turbidity and enhanced stratification will reinforce the absorption of the Sun’s energy into these coastal waters and put more heat in contact with any remaining ice to hasten melting and warm the region.

6.4. Ice formation in the Arctic The development and seasonal sequence of sea-ice in the Arctic is very different to the Antarctic, because of its enclosed nature. Due to its constrained movement, ice that survives summer melt may continue to thicken from below year after year to form multi-year ice. The relative proportions of young and multi-year ice, and the characteristic double halocline, have a strong influence on the role of the Arctic in climate. The surface halocline layer in the Arctic is maintained by melting seaice. When this ice reforms at about 1.8 C (due to the depressed freezing point of saltwater), seawater fractionates producing brine that sinks rapidly downward, because of its density. This leaves both ice and fresher water behind at the surface, with additional freshening provided by the contributions from Arctic rivers. This effect helps to explain why the Arctic is so different from the Antarctic: a fresher ice-covered Arctic Ocean is insulated from saltier warmer water below by the density differences (analogy of oil and vinegar). Cold, dense water that is formed seasonally on the shelves is also contributed to the deep basins. These processes are important components of the MOC/THC. The multi-layered haline system is still a key element of the Arctic Ocean. As ice retreats and a more open water ocean starts to develop, strong mixing will remove the haline stratification leading to a step change in the whole Arctic system. Wind mixing will increase, biological production will be enhanced, a biological carbon pump will

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develop and the solubility pump may become less important among other changes. However, even in an ice-free Arctic a surface freshwater layer will be maintained in coastal zones due to the riverine input.

6.5. Observed changes in Arctic sea-ice cover The most evident and rapid change that has taken place in the Arctic Ocean is the decline in summer Arctic sea-ice cover. A marked decline has been measured, from both in situ and satellite observations, in summer Arctic sea-ice cover over the last three decades (Fig. 1.29). Since 1995 approximately, the decline has accelerated reaching the lowest recorded area ever in September 2007 (4.13 million km2; Fig. 1.30) (Stroeve et al., 2007). In September 2007 sea-ice extent was nearly 50% lower than during the 1950s and 1960s and the 2008 sea-ice area was also significantly below the long-term average (Fig. 1.31), and similar to but not as low as 2007. The thickness and volume changes were estimated to have been twice as fast as the changes in sea-ice extent (Maslowski et al., 2000). There is now

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Figure 1.30 Sea-ice in September 2007. Total extent ¼ 4.1 million km2. The grey line shows the average position of the ice edge (median). Source: U.S. National Snow and Ice Data Center, Boulder, CO (http://nsidc.org/news/press/2007_seaiceminimum/images/ 20071001_extent.png).

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little of the thick, old ice left, which could make the region increasingly vulnerable to further ice loss (Rigor and Wallace, 2004). In the winter of 2008 measurements taken by Envisat showed that the thickness of winter sea-ice reduced by 0.26 m compared to the previous 6 years, averaged for the whole circumpolar region (Giles et al., 2008). Thinning and less coverage leads to a reduction in the overall volume of sea-ice, determining its disappearance in the future. Inflow of warm salty water from the Atlantic has likely contributed to the overall decline Polyakov et al. (2008) as well as changes in atmospheric circulation (Maslanik et al., 2007) and cloud cover (Francis and Hunter, 2006) plus a marked increase in export of old ice via the Fram Strait (Nghiem et al., 2007). While the major focus of reduction since 1995 has been in the Eurasian Arctic, there has also been an important contribution to the melting from warm water originating from the Pacific and advection into the Chukchi Sea and adjoining deep basins (Shimada et al., 2006). In 2008, the main melt occurred in the Beaufort, Laptev and Greenland Seas.

6.6. Trigger factors for initial sea-ice reductions The North Atlantic Current, the west European shelf edge current and their extension in the Norwegian Sea (the Norwegian Current) have warmed markedly over the last two decades (Holliday et al., 2008). This increased input of heat into the Arctic Ocean may have contributed to the trigger for the start of the decline in ice extent. However, there is still considerable debate on the relative role of oceanic versus atmospheric forcing of the changes. The Atlantic inflow is mainly related to a strong increase in the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO) at the end of the 1980s. However, even after 1996 when the NAO is average, temperatures, and possibly flow have increased, and there has been no return to the sea-ice state of pre-1988. Warming in the North Pacific and Bering Strait in 1995 led to the first major reduction in the extent and thickness of ice in the western basin. Contrary to the North Atlantic side of the Arctic, which is insulated by a deep halocline layer, the North Pacific surface water is close to the ice, affecting it directly in the winter. This warming has been reinforced since 1998 by warmer temperatures in the West Greenland current. The coincidence of warmer conditions in the Canada Basin and in Baffin Bay led in September 1998 to a complete retreat of ice from the north of Alaska and Canada for the first time in recorded history.

6.7. Projected changes in Arctic sea-ice cover Sea-ice loss is 30–50 years ahead of the modelling used in IPCC AR4 (Stroeve et al., 2007). If the present rate of reduction in sea-ice continues, some models project an ice-free ocean in the Arctic summer by 2030

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(Stroeve et al., 2007) or 2040 (Holland et al., 2006) compared to the more conservative estimates of a loss of greater than 40% in the area covered by sea-ice by 2050 as suggested by the majority of IPCC AR4 models (Overland and Wang, 2007). A more recent modelling analysis of trends in ice extent, thickness and volume (Maslowski et al., 2007); Whelan et al. (2007) estimated that the Arctic may be ice free in the summer as early as 2013; however, more recent studies suggest a date of 2037 (Kerr, 2009). Such a rapid reduction will result in changes to many components of the Arctic environment as well as to adjacent seas. This will include a change to the ocean/atmosphere energy balance, affecting weather patterns, an increase in the freshwater budget from melting ice, supplemented by an increase in river runoff. Traditional patterns of salt and freshwater mixing will change with a likely reduction in the strength of the MOC/THC because of reduced deep water convection. A reduction in deep convection will in turn lead to lower fluxes of CO2/DIC to the deep ocean. In the near-term, further sea-ice loss and increases in marine phytoplankton growth rates are expected to increase the uptake of CO2 by Arctic surface waters (Bates et al., 2006), although mitigated somewhat by warming in the Arctic (Bates and Mathis, 2009). Each of these changes has the potential to have a global effect on climate and climate change. 6.7.1. Sea-ice retreat and feedbacks A positive feedback from the ice reduction already appears to be operating and leading to an acceleration of the retreat. Preconditioning of the sea was identified as a contributory factor to further sea-ice loss by Lindsay and Zhang (2005). Historically, the high reflectivity (albedo) of ice has reflected much of the sunlight during the long Arctic summers back into space, but once the ice starts to break up, it exposes large areas of dark open water where sunlight further heats the ocean. The scale of the effect from a change in albedo is very marked. Perovich (2005), for example, has calculated that a 500% increase in solar heat anomaly, due to the extensive area of open water in the summer of 2007, contributed to an increase in basal melting of ice in the Beaufort Sea and its accelerated retreat. The ponding of meltwater on the surface of sea-ice further leads to reduced reflectance and increased absorption of solar heat. The loss of sea-ice accelerates the warming of the dark ocean below, which distributes the heat to the surrounding water, deeper waters, sea bed and atmosphere. Recent modelling has demonstrated that during rapid sea-ice loss episodes, warmth is released back to the air and can penetrate up to 1500 km from the coast (Lawrence et al., 2008). This can destabilise permafrost and lead to the release of methane, thus accelerating climate change. Methane released from shallow shelf seas has recently been reported as reaching the surface and off-gasing to the atmosphere (Westbrook et al., 2009) although most methane released from sediment is converted to CO2 by microbial anaerobic oxygenation of methane (AOM) before it reaches the surface.

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6.8. The Greenland ice sheet Changes in the mass balance (snow accumulation–melting) of the Greenland ice sheet will be strongly impacted by adjacent Arctic and Subarctic seas. The recent acceleration in ice reduction may in part be affected by the higher SST found in adjacent waters since 1998 (Holland et al., 2008). Changes in the circulation of the sub-polar gyre (Ha´tu´n et al., 2005, 2009) are likely to have contributed to the higher sea temperatures. Warmer temperatures are increasing the number of summer days when portions of the surface of the Greenland ice sheet melt. Along the margins of the ice sheet, up to 20 additional days of melting occurred in 2005 compared to the average since 1988 (Fig. 1.32). Because of the high elevation of its central mass, the ice sheet has a major impact on Northern Hemisphere atmospheric circulation and storm track location. Observed changes in the ice sheet as summarised in IPCC AR4 (2007) are:

Inland thickening over the higher elevations Faster thinning around the coastal periphery Recent accelerated shrinkage of the total mass Northerly movement of the main ice zone from 66 to 70 N between 2000 and 2005

Model simulations indicate that the Greenland ice sheet will decrease in volume and area over the next few centuries, if a warmer climate continues. A threshold beyond which the ice sheet will continue to melt over many centuries (3000 years, Ridley et al., 2005) is expected to be crossed if global annual mean temperature exceeds 3.1 0.8 C or the annual mean temperature for Greenland exceeds 4.5 0.9 C (Gregory and Huybrechts, 2006; Lowe et al., 2006), or 3 C (ACIA, 2005). Temperatures of this order are well within the IPCC A1B Scenario estimates for 2100 (IPCC, 2007), and unless global temperatures decline, the threshold for a complete melting of the Greenland ice sheet is likely to be crossed within this century. Once crossed, it is believed that the ice melt will be irreversible, resulting in sea-level rise of several metres over the coming centuries. This is in addition to any contribution from melting of the West Antarctica ice sheet. Lowe et al. (2006) suggested that complete or partial deglaciation of Greenland may be triggered for even quite modest CO2 stabilisation targets.

6.9. Methane and feedbacks to climate change The importance of methane hydrates (methane gas trapped in an ice-like solid) is becoming increasingly recognised. Methane is 25 times more potent as a greenhouse gas than CO2, thus the release of this gas is potentially a large feedback to climate change. While elsewhere on Earth, methane hydrates are maintained in place by the pressure of the overlying water,

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in the Arctic they are mainly stabilised by temperature (and occur at shallower depth). This fact makes them potentially vulnerable to climate change, especially in a warming Arctic Ocean. 6.9.1. Methane hydrates In the Arctic, and on continental shelves and intercontinental rises elsewhere, sediments entrap major deposits of this greenhouse gas. There is considerable variability and uncertainty over the size of reserves of methane with estimates for methane stored in marine hydrates and sediment ranging from 10,000 Gt (GtC) (approximately twice all other carbon fossil fuels; Buffett and Archer, 2004) to 500 GtC and in permafrost from 450 to 7.5 GtC (Brook et al., 2008). The impact of a sizeable release of these reserves into the atmosphere would be large. It is estimated, for example, that a 10% release of global methane stores to the atmosphere over a few years would be equivalent to a factor of 10 increase in atmospheric CO2 (Archer, 2007). Fortunately, release of methane hydrates over the next century is thought to be significant, but not catastrophic (Archer, 2007). Methane hydrates are sensitive to temperature and geostatic/hydrostatic pressure changes, but will be partially stabilised by the increased pressure from a rise in sea-level. There are two main mechanisms that affect methane hydrates: The first is sensitivity to sea-level rise: if a shelf region is flooded with warm water, a large thermal wave propagates into shallow sea bottom sediments and into the soils of flooded low-lying terrestrial regions. Many gigatonnes of methane hydrates are stored on the Arctic shelves of Alaska, Canada and Siberia, which could be reactivated by this type of warming. However, there are many uncertainties: including the level of temperature increase and timescales needed to melt permafrost. Advective inflow of warmer water from the Pacific or Atlantic would lead to a faster release of gas and could be a positive feedback to climate change. It is worth noting, however, that AOM will have converted most methane to CO2 before it enters the atmosphere although this process will be slowed in the cold waters of the Arctic. The anaerobic micro-organisms responsible substantially reduce oceanic emissions of methane and are a key component of the carbon cycle (e.g. Pernthaler et al., 2008). Secondly, methane outcropping at deeper depths can be affected by the temperature structure on the sea floor. If there is a feedback, it could come from a destabilisation of the hydrates in sediments; any loss could lead to a slope failure. If a turbidity flow was generated as a consequence, it might lead to a large pulse release of hydrates that would float to the surface of the ocean and be released to the atmosphere. Such a process has been suggested as one of the possible trigger mechanisms for the huge Støregga Slide on the shelf slope off Norway and its resulting tsunami circa 8000 BP (Beget and Addison, 2007). For the Arctic, hydrate records show that they were released in previous glacial oscillations, but at least the present Canadian gas hydrate reserves

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have probably been recharged since the last ice age. In off-shore regions of the Beaufort Sea, methane can be found bubbling from hydrates which have been destabilising for thousands of years—this is not a recent change, but contributes to climate change. Post 2000, large volumes of methane have been observed bubbling from the sea bed of the Laptev and East Siberian Shelf Seas and were measured in elevated concentrations above the sea surface (Shakhova et al., 2007, 2008) and attributed to warming conditions. Escape of methane has also been measured off Spitzbergen (Westbrook et al., 2009). It is not clear if these new findings are a response to an anthropogenic signal, and it is also unclear if hydrates have been involved in previous changes of climate. For example, it is still unclear whether the PETM (55 million years ago) was brought on solely by a major methane hydrate release (Panchuk et al., 2008). 6.9.2. Permafrost methane release Warming of the Arctic, through direct warming and through heat released by the ocean, can degrade and melt permafrost and potentially lead to the release of any methane stored within it. The rate of increase of this gas into the atmosphere has slowed down over the last 20 years; a rate change that is not well understood. In 2007, however, the concentrations of methane in the air increased, particularly in the Arctic, suggesting a release from Arctic permafrost among other sources (the NOAA annual greenhouse gas index, Hoffman, http://www.esrl.noaa.gov/gmd/aggi/).

6.10. Arctic ocean ecosystems As surface sea-ice continues to be lost, there are likely to be further large changes in the ecosystems and primary production of the Arctic (Carmack and Wassmann, 2006). Temperature, sea-ice cover and light penetration in the enlarged ice-free zones are expected to change, but not the light season, so phytoplankton primary production will increase within the same growing months. Reductions of sea-ice cover in the last decade, particularly in the western Arctic Ocean, have resulted in a longer marine phytoplankton growing season and an 30–60% increase in the rate of primary production (Pabi et al., 2008). Over the last several years, a similar 10–40% increase in phytoplankton primary production has been observed in the Beaufort and Chukchi Seas (Arrigo et al., 2008). In the Bering Sea, reduced sea-ice cover is thought to favour a ‘phytoplankton–zooplankton’ dominated ecosystem over the typical ‘sea-ice algae–marine benthos’ ecosystem (Piepenburg, 2005). The life cycles of most Arctic species are highly adapted and intimately linked to the timing of sea-ice melt. At present, most phytoplankton primary production takes place as the sea-ice is melting and retreating towards the pole, with primary production rates typically lower in the older open waters of the central basin. It is difficult to estimate what the

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balance will be between planktonic production in a summer sea-ice-free ocean and sea-ice margin production. Indications are that a climate-induced reduction of sea-ice cover duration on Arctic shelves will favour the population growth of several key zooplankton species (e.g. Ringuette et al., 2002), notably the predominant calanoid copepods, perhaps with a transition to a ‘phytoplankton–zooplankton’ dominated ecosystem rather than a ‘sea-ice algae–marine benthos’ ecosystem. In the Arctic’s marginal seas, ecosystem changes could be profound if changes in benthic–pelagic coupling lead to increased pelagic production and a reduction of benthic production (e.g. Grebmeier et al., 2006; Wassmann, 2006). Regardless of any changes in benthic–pelagic coupling, an enhanced seasonal penetration of the generally smaller subarctic species is expected, although the degree to which Arctic species may be displaced is uncertain. Such reorganisation in the way the ecosystem operates will ultimately alter the pathways and magnitude of energy that passes into upper trophic levels such as fish, sea birds and marine mammals, and impact the people dependent on those resources. Potential feedbacks from all these biological changes are unclear, as an integrated ocean-wide view on the structure and function of Arctic Ocean food webs is not yet available (Carmack and Wassmann, 2006). The large reduction in sea-ice cover to the north of Alaska and Canada (including the archipelago) for the first time on record in 1998, is likely linked to evidence for an increased inflow to the Atlantic via this route seen in the first record of the Pacific diatom Neodenticula in the Northwest Atlantic in the following year (Reid et al., 2007). Further incursions of Pacific water are likely to impact biological diversity and the carbon pump in the northern North Atlantic.

6.11. Modelling The current range of Arctic ice and climate models are too conservative and do not adequately reproduce current changes taking place in the Arctic Ocean (Stroeve et al., 2007). Some work suggests that a threshold (tipping point) has been passed in the loss of Arctic sea-ice (Lindsay and Zhang, 2005). There are inadequacies in model forcing, parameterisation of sea and ice processes and model structure. An Arctic model intercomparison project is underway jointly between the EU DAMOCLES and US SEARCH projects (Proshutinsky et al., 2008) for a wide range of global and regional models that focus on different aspects of the Arctic environment. The Global Green Ocean model (Le Que´re´ et al., 2005) indicates that there will be an increase in the Biological pump but this model does not consider acidification. The predicted ocean uptake of anthropogenic CO2 using the IPCC (Intergovernmental Panel on Climate Change) scenarios (e.g. Solomons et al., 2007) is expected to lower pH by 0.3–0.5 units over the next century and beyond (Caldeira and Wickett, 2003, 2005), with the

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Arctic Ocean impacted before other regions due to the relatively low pH of polar waters (Bates et al., 2009; Orr et al., 2005; Steinacher et al., 2009). Work within the International Polar Year is currently fostering improvements in many aspects of modelling within the region.

6.12. Concluding comments There are many feedback loops within the Arctic, some of which have serious implications for global climate and climate change. Increasing heat flux of oceanic water to the Arctic as well as higher atmospheric temperatures is contributing to an accelerating retreat of Arctic sea-ice cover. The ice retreat removes the insulation between the ocean from the atmosphere enhancing ocean/atmosphere interaction and influences atmospheric circulation. The ice-albedo effect is large and provides a strong positive feedback from sea-ice loss. Increased warming of the wider Arctic oceanic region is likely to be contributing to Greenland ice sheet reduction. Methane is a potent greenhouse gas; warming of the Arctic Ocean and surrounding tundra may lead to its destabilisation and release from hydrates and permafrost with the capacity to accelerate global warming. Unless the trend in global temperature rise reduces, the temperature threshold for an eventual complete melting of the Greenland ice sheet may be crossed this century. Melting of the Greenland ice sheet alone could lead to 7 m of sea-level rise over the coming centuries. Model predictions for the disappearance of Arctic sea-ice during summers vary between 2013 and the end of the century. Most climate models underestimate the rate of ice loss over recent decades. Some work suggests that a threshold (tipping point) has been passed in the loss of Arctic sea-ice and recent low ice conditions may persist for some time. The impacts of climate change on Arctic biology and the carbon pump, and vice versa (any feedback to Climate Change) was not addressed by IPCC AR4. The scale and rate of any feedback to climate remain unclear. Deep water formation, the westward retraction of the sub-polar gyre (positive feedback to ice) and biological impacts were not adequately covered by IPCC AR4.

7. The Southern Ocean and Climate This section focuses on the key role that the Southern Ocean (Fig. 1.33) plays in global climate, through its role in the MOC and interaction with sea-ice, Antarctic ecosystems and carbon uptake. Major

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changes that have taken place over recent decades in the forcing and response of the Southern Ocean are outlined, along with the impacts of these changes. As an example some of the rapid changes observed at the Antarctic Peninsula are described. Loss of ice shelves is addressed as well as evidence for net reductions of ice in western Antarctica. Finally, some recent modelling prognoses are presented alongside some of the technological and observing challenges that need to be addressed to monitor such a large and extreme environment. Changes in the cryosphere were comprehensively addressed in the IPCC AR4 reports with less coverage of the Southern Ocean. A detailed analysis of the state of the Antarctica and Southern Ocean climate system has recently been completed for the Scientific Committee on Antarctic Research (SCAR; Mayewski et al., 2009).

7.1. Role of the Southern Ocean in climate The Southern Ocean plays a critical role in driving, modifying and regulating global climate change. This is partly due to its unique configuration: it is the only ocean that circles the globe without being blocked by land. As a consequence, it is home to the largest of the world’s ocean currents: the ACC, which is driven by the strong westerly winds and buoyancy fluxes

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over the Southern Ocean. This current transports 150 times more water around Antarctica than the flow of all the world’s rivers combined. The Southern Ocean controls climate in a number of ways. The flow of the ACC from west to east around Antarctica connects the Pacific, Indian and Atlantic Ocean basins (Fig. 1.34). The resulting global ocean circulation redistributes heat, salt, freshwater and other climatically and ecologically important properties. It has a global impact on patterns of temperature, rainfall and ecosystem functioning. The Southern Ocean is a key region in the oceanic MOC/THC, which transports heat and salt around the world. Within the Southern Ocean, the products of deep convection in the North Atlantic are upwelled and mixed upwards into shallower layers, where they can be converted into shallow and deep return flows that complete the overturning circulation (Fig. 1.34). This upwelling brings carbon and nutrient-rich waters to the surface, acting as a source of CO2 for the atmosphere and promoting biological production. The lower limb of the MOC comprises the cold, dense AABW that forms in the Southern Ocean. Close to the coast, the cooling of the ocean and the formation of sea-ice during winter increases the density of the water, which sinks from the sea surface, spills off the continental shelf and travels northwards hugging the sea floor beneath other water masses (Fig. 1.34), travelling Ind

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as far as the North Atlantic and North Pacific. This cold water also absorbs atmospheric gases, including oxygen and carbon dioxide, which enables it both to aerate the bed of the global ocean and to act as a temporary (hundreds of years) sink for natural and anthropogenically produced CO2. The upper limb of the MOC is sourced towards the northern flank of the ACC. Here, the water that is upwelled within the ACC is converted into mode waters and nutrient-rich intermediate waters that permeate much of the global ocean basin south of the equator. Mode waters (like the Subantarctic Mode Water, SAMW, Fig. 1.35) form at the surface in winter via convective processes, and are relatively homogeneous water masses of uniform density. They are undercut by intermediate waters (AAIW in Fig. 1.35) that are renewed by subduction near the Polar Front. The formation and subduction of the mode and intermediate waters is believed to be a critical process that removes anthropogenically produced CO2 from the atmosphere (Fig. 1.36). Closer to the continent, ocean processes are strongly controlled by sea-ice, the formation of which is the largest single seasonal phenomenon on Earth. The freezing of the sea around the continent as sea-ice each year effectively Buoyancy gain

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doubles the size of Antarctica and has a profound effect on climate. Because of its high albedo (whiteness), it reflects the Sun’s heat back into space, cooling the planet. However, the sea-ice also acts as a ‘patchy blanket’, limiting heat loss from the ocean to the atmosphere and restricting air–sea exchange of climatically important gases. The formation of sea-ice, as noted above, plays a key role in the production of AABW and its annual melt supplies a thin layer of freshwater to the surface ocean that stabilises the stratification and can promote phytoplankton blooms. The sea-ice is also home to large algal populations, as well as sheltering the larvae of plankton such as krill. Because of its upwelling nutrients, the Southern Ocean is highly biologically productive, although it is not as productive as it could be. This is because the productivity is limited by the low availability of micro-nutrients such as iron, except in a few areas such as near the isolated islands that are scattered within the ACC. Nevertheless, the Southern Ocean is a key region for the Biological pump with diatoms as ballast playing an important role in the sedimentation of organic material to the deep ocean (see Section 4).

7.2. Observed changes in the Southern Ocean region The Southern Ocean has shown many marked changes in recent decades, highlighting its sensitivity to global processes and illustrating different aspects of its control on regional and global change. The most conspicuous

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of these changes is probably the profound warming within the ACC (Gille, 2002, 2008; Fig. 1.37). In this area, a strong, surface-intensified temperature increase has been noted that exceeds that of the global ocean as a whole. The exact causes of this warming are not yet understood, though most theories seek to relate it to the intensification and southward shift of the band of westerly winds that overlie the circumpolar Southern Ocean. Potential candidate mechanisms include a latitudinal shift in the ACC, greater air– sea heat fluxes, an intensification of the circumpolar eddy field, and possibly other processes also, almost certainly in some combination (Fyfe, 2006; Fyfe and Saenko, 2006; Gille, 2002, 2008; Hogg et al., 2008; Meredith and Hogg, 2006). The large-scale circulation patterns of the Southern Hemisphere atmosphere over the past few decades reveal changes that are reflected in the leading mode of Southern Hemisphere climate variability, the SAM (Thompson and Wallace, 2000). Interannual variability and trends in the SAM have been shown to drive substantial variability in ocean circulation, upper-ocean biology, and the uptake and release of CO2 to and from the Southern Ocean (Lovenduski and Gruber, 2005; Lovenduski et al., 2007, 2008). The intensification and movement of the wind field as expressed in SAM changes is known to be at least partially due to anthropogenic processes (ozone depletion and greenhouse gas emissions; Marshall, 2003; Thompson and Solomon, 2002). This suggests that the activities of mankind are perturbing the ocean around Antarctica on a large scale. Noteworthy also is the observation that the current generation of climate ⬚W

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models can produce a warming in the Southern Ocean comparable to that observed only if anthropogenic gases and sulphate and volcanic aerosols are included (Fyfe, 2006). If the role of volcanic aerosols is neglected, the simulated warming is nearly double, implying that the potential human impact on Southern Ocean warming is only partially realised at present in our sequence of observations. There are countless likely feedback mechanisms from this circumpolar warming on regional and global climate, including impacts on sea-ice formation (and hence albedo; see below), solubility of carbon dioxide and other climatically important gases, and modulations to primary production and associated ‘biological pumping’ of carbon. Each of these are the subject of ongoing investigation; however, it should be noted here that the circumpolar winds are predicted to increase further over the next few decades, hence (if theories relating the warming to strengthening circumpolar winds are indeed correct) the effects are likely to be persistent rather than transient. The strengthening circumpolar westerly winds have been highlighted as the potential root cause of another important observed change in the Southern Ocean region, namely a saturation of the Southern Ocean CO2 sink. Ocean inverse analyses (Gloor et al., 2003; Mikaloff Fletcher et al., 2007) indicate that the pre-industrial Southern Ocean (south of 44 S) was a source of natural CO2 to the atmosphere. But the rise in atmospheric CO2 from pre-industrial levels of about 280–380 ppm at present, has led to a strong perturbation of the air–sea CO2 balance, that is, it induced a flux of anthropogenic CO2 that is directed into the ocean. This sink of anthropogenic CO2 in the Southern Ocean takes up nearly 10% of the CO2 emissions to the atmosphere. However, based on atmosphere and ocean measurements, and the analysis of model output, Le Que´re´ et al. (2007) argued that this sink has not increased since 1981, in spite of a >40% increase in CO2 emissions. A reduction in CO2 uptake would likely lead to an increase in the amount of CO2 in the atmosphere, with clear implications for climate change. The theory proposed to explain this observation was that upwelling in the Southern Ocean, which brings natural carbon from the deep ocean to the surface layers, has been accelerated by the strengthening winds. This has increased surface concentrations of CO2, and precluded further absorption of anthropogenic CO2. Also noteworthy is that the increased upwelling of CO2 will increase the rate of ocean acidification, with consequences for the ecosystem. Although Le Que´re´’s conclusions have been supported by another modelling study (Lovenduski et al., 2008), it should be noted that Bo¨ning et al. (2008) have questioned this saturation of the Southern Ocean CO2 sink, arguing that the effect of increased eddy formation could compensate for the extra energy imparted to the ocean by the winds, with no significant change in the overturning. Much remains to be done on this important subject,

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including improved monitoring of CO2 and better understanding of the physical processes that mediate the vertical motion in the ocean, and it is imperative that the research community tackles these subjects as a matter of priority. On a regional level, the area in the Southern Hemisphere whose atmospheric climate has been changing most rapidly is that of the Antarctic Peninsula (e.g. Turner et al., 2005). On its western side, a wintertime atmospheric warming of 5 C since 1950 has been observed with a smaller (but still significant) warming seen in summer. This warming has been noted to be strongly linked with the reduction of sea-ice extent and duration in the adjacent Bellingshausen Sea since the 1950s, and has also been shown to be connected to a very strong summer warming of the upper ocean (Meredith and King, 2005; Fig. 1.38). These authors used a large compilation of in situ hydrographic profiles collected between the 1950s and 1990s to demonstrate a surface-intensified warming (of >1 C in the shallowest levels), and a coincident strong summer salinification. It is worth emphasising that these oceanographic changes constitute positive feedbacks that act to sustain and enhance the atmospheric warming and further reductions in sea-ice formation—a clear example of ocean processes exerting a strong influence on regional climate, in an area of very rapid

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change. Meredith and King (2005) also noted that the rising temperatures have played an important role in the accelerating retreat of the tidewater glaciers on the Peninsula that have led to an increasing contribution of glacial meltwater to the adjacent ocean. In accord with this, Cook et al. (2005) showed that the majority of glaciers on the western side of the Peninsula are retreating, and that retreat rates are accelerating. Meredith and King (2005) also noted the profound consequences for the ocean ecosystem in this sector, where benthic organisms are generally well adapted to cope with low temperatures, but poorly adapted to cope with changes in temperature. Indeed, based on a study of temperature tolerances, Peck et al. (2004) asserted likely ‘population and species level losses’ of marine organisms at the western Peninsula associated with a proposed 2 C change in ocean temperature. The observed change of >1 C in 50 years illustrates that such changes are very possible within the next few decades. It is also worth noting that a key species in Southern Ocean food webs, namely Antarctic krill, has been undergoing a dramatic decline in numbers in the South Atlantic in recent decades (Atkinson et al., 2004). This population is sourced at least partially from breeding and nursery grounds near the western Peninsula, and it was argued that the loss of sea-ice and warming of the ocean may be the cause of their decline (Atkinson et al., 2004; Meredith and King, 2005). Krill are a critical component of the Southern Ocean marine food web (Hill et al., 2006; Knox, 2007) with most higher trophic levels depending on them and some such as the baleen whales feeding exclusively on these crustaceans. Krill are also now targeted by commercial fishing and so are particularly vulnerable. Establishing the long-term impacts of their removal from regional ecosystems and on climate is a high priority research area. To the south of the retreating glaciers on the Peninsula referred to above and extending as far as the Trans-Antarctic Mountains is the West Antarctic ice sheet. Much of this ice sheet rests on rock that is well below sea-level and parts of its margin are in direct contact with the ocean. Using satellite radar interferometry and regional climate modelling, Rignot et al. (2008) have estimated a widespread net loss of the ice sheet in western Antarctica adjacent to the Bellingshausen and Amundsen seas; with the rate of loss increasing by 59% in the decade to 2007. The current reduction in mass from the Amundsen Sea embayment of the West Antarctic ice sheet is equivalent to that from the entire Greenland ice sheet (Lemke et al., 2007). The process believed responsible for this rapid and large change is a progressive thinning of the fringing ice shelves seaward of the Amundsen Sea outlet glaciers. The likely cause of this melting is a greater penetration onto the shelf, typically at a few hundred metres depth and upwelling of ‘warm’ Circumpolar Deep Water from the ACC. Why this warmer water is now reaching the ice shelves more readily is still not fully understood, but it is believed to be caused by the increase in westerly winds. At a few key locations these warmer waters flow towards the outlet glaciers along deep

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glacially scoured submarine troughs carved by ice in past glacial periods. Once the ‘warmer’ water reaches the base of the floating ice shelves, it causes extremely high melting rates of many tens of metres per year due to the large temperature contrast between the seawater and ice. Ultimately, this sector could contribute 0.75 m to global sea-level if the area of ice lost is limited to that where the bed slopes downward towards the interior of West Antarctica (e.g. Holt et al., 2006), so a contribution from this sector alone of some tens of centimetres to sea-level rise by the end of the twenty-first century cannot be discounted. On the eastern side of the Antarctic Peninsula the greatest warming is during the summer months, and appears to be directly related to the strengthening of the circumpolar westerly winds (Marshall et al., 2006). These have resulted in more relatively warm, maritime air masses crossing the Peninsula from the west and reaching the low-lying ice shelves in the east. The impacts of this change have included the break-up of large parts of the Larsen ice shelf, which has progressively disintegrated from north to south. The remaining part of this shelf (‘Larsen-C’) is being closely watched, and may well disintegrate within the next few years or decades. Again, with the root cause of the change being the strengthening winds, there is a direct connection between anthropogenic processes (greenhouse gas emission and ozone depletion) and a large response in the Antarctic. In IPCC AR4 it was predicted that the Antarctic ice sheet as a whole will increase in mass over the next century due to higher snowfall as a consequence of a warmer climate (see also Krinner et al., 2007). Build-up of snowfall in the interior of Antarctica is balanced by wastage due to melting and calving of ice along the coast and this balance is an important component of sea-level rise. Measurements made by satellite altimetry confirm a growth in ice mass from snowfall in East Antarctica over an 11-year period since 1992 (Davis et al., 2005) and another study has shown a doubling in snowfall in the western Antarctic Peninsula since 1850 (Thomas et al., 2008). In contrast, the long records of Monaghan et al. (2006) and van den Broeke et al. (2006) for the whole of Antarctica reveal large decadal to multi-decadal variability in snowfall and yet no significant trend. The absence of an observed long-term change in snowfall, when averaged for the whole continent, has taken place against a background where significant warming is not just confined to the Antarctic Peninsula, but extends over much of western Antarctica and positive trends in temperature are recorded for the whole of Antarctica since the 1950s (Steig et al., 2009). There is therefore no clear evidence that snowfall has changed in Antarctica as a whole in response to rising temperature, contrary to the predictions of climate models. The only exception is in the Peninsula, but there the increase in mass has been small compared to the loss of mass from the glaciers, so that precipitation plays only a minor role in mitigating the contribution to sea-level change from the Peninsula.

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In terms of ice wastage, a rapid increase in glacier flow and retreat of ice sheets has occurred in both the Antarctic Peninsula and West Antarctica; the speed of the observed changes has demonstrated the important role that ice shelves play in controlling the mass balance of ice sheets (Rignot, 2006). In East Antarctica, glaciers grounded well below sea-level are also thinning (Rignot, 2006). The main driver for the glacier changes in the Antarctic is the ocean. There is clear evidence that the Southern Ocean has warmed (Gille, 2008) and it is likely that the ocean waters along some coastal sectors of the Antarctic are warmer than in the past, for example, the western Peninsula and Amundsen Sea, but unfortunately there are not enough measurements to show the timing of these changes. These warmer waters condition the evolution of ice shelves much more than air temperature; subsurface melting of ice by the ocean is orders of magnitude larger than what is happening on the surface. Rignot (2006) concludes that the mass balance of ice in a warmer climate will be more affected by the evolution of its ice streams and glaciers than on changes in the precipitation of snow in the interior.

7.3. The future The future climate evolution of Antarctica and the Southern Ocean is especially hard to predict, since many of the coupled climate models that are traditionally used for such predictions do not represent well some of the key processes, and there is also a dearth of data with which to validate and challenge the model-based results. Notwithstanding this, it is possible to generate some understanding of likely future change using such models. For example, Bracegirdle et al. (2008) considered the output of the 20 coupled climate models used in the IPCC Fourth Assessment Report, and produced a ‘scaled average’ of their predictions, with the scaling for each individual model being in accord with the skill shown by that model at reproducing previous (observed) climate change. A ‘middle-of-the-road’ scenario for fossil fuel emissions was adopted for this. Using this approach, the models predicted a continuing warming of the circumpolar Southern Ocean in the next 100 years, but with markedly stronger warming in the sub-polar gyres (Weddell Sea and Ross Sea; Fig. 1.39). This stronger regional warming is associated with a 25% decrease in sea-ice extent. Given the locales, this will almost certainly impact on AABW production in these two key formation sites, with possible consequences for the lower limb of the ocean overturning circulation. The circumpolar westerly winds are also predicted to continue strengthening, with likely consequences in line with the discussions above. In practice, the predicted ubiquitous warming over Antarctica and the Southern Ocean is in line with changes predicted and beginning to be observed in the Arctic. The equilibrium response of the two polar regions to planetary-scale climate change is comparable; the differences observed so far

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are concerned with the transient response. Accordingly, the rapid changes observed in the Arctic and at the Antarctic Peninsula can be viewed as potential harbingers of what is to come around Antarctica and the Southern Ocean as a whole. The future evolution of the Southern Ocean CO2 sink is hard to predict. It depends on how the ocean circulation will change as forcing by the atmosphere evolves, in particular its overturning component. However, knowledge of the evolution of Southern Ocean overturning alone is not sufficient to predict the future of the oceanic CO2 sink because under very high CO2 an increase in upwelling could favour more uptake of anthropogenic CO2 and over-compensate the enhanced ventilation of natural carbon coming from the deep ocean. Furthermore, changes in circulation, temperature and acidification will certainly impact the downward transport of organic carbon by biological activity, but we do not know the direction, amplitude or the rate of the potential changes. However, based on the behaviour of the Southern Ocean carbon cycle during glaciations, it appears that its response to a warmer climate would be to permanently outgas some of its natural CO2 to

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the atmosphere while likely reducing the uptake of anthropogenic CO2, which will add to the challenge of stabilising atmospheric CO2. Regarding the future of the Antarctic ice sheet, changes in the Southern Ocean, especially along the coast of Antarctica, are a major control on the evolution of Antarctic glaciers and on the mass balance of the ice sheet as a whole. This is something that glaciologists and modellers have known about for some time, but it has not been included as a factor in the predictions of the future state of the Antarctic ice sheet. The oceans matter even more than anticipated, but it is a domain of study that is currently fundamentally limited by a lack of basic observations, such as the shape of sub-ice-shelf cavities and oceanic conditions (temperature, salinity, currents, etc.) along the coast of Antarctica, near the glacier grounding lines. Only limited progress will be possible in the prediction of the evolution of Antarctica over the next 100 years until an understanding has been developed of how the Southern Ocean is changing now and into the future. This important new theme is emerging strongly from all recent ice studies and needs to be addressed by the scientific community.

7.4. Concluding comments

The Southern Ocean, including the ACC, plays a critical role in driving, modifying and regulating global climate and climate change. An increase in westerly wind speeds due, at least partly, to human influences (increases in greenhouse gases and ozone depletion) has been observed. A continuing warming of the Southern Ocean and strengthening of the westerly winds is predicted. Rapid warming of the ocean west of the Antarctic Peninsula since the 1950s has been measured and associated atmospheric and cryospheric changes observed. Changes in the Southern Ocean are closely connected to the production and melting of sea-ice, the formation of which is the largest seasonal phenomenon on Earth. Sea-ice has a major effect on the Earth’s energy budget and thus climate. A strong decrease in sea-ice extent over the next 100 years is predicted. The evolution of the Southern Ocean along the coast of Antarctica is a major control on the stability of Antarctic glaciers and on the mass balance of the ice sheet as a whole. Deflation of the northern sector of the West Antarctic ice sheet induced by a thinning of the fringing ice shelves is most likely associated with greater subsurface penetration of Circumpolar Deep Water onto the continental shelf. Reduction of glaciers in the Peninsula and in West Antarctica is predicted to accelerate.

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The Southern Ocean is an important sink for both natural and anthropogenic carbon dioxide, a sink that has been reported as possibly saturating, and which urgently requires further investigation. Further modification to the CO2 sink is predicted. Marked changes have occurred in Southern Ocean ecosystems including a substantial decline in krill numbers. Acidification is predicted to increase with likely important modifications to unique Antarctic ecosystems.

8. Climate Models This section provides a brief review of the ‘state of the art’ in modelling the feedbacks of the ocean on climate change. It notes existing limitations and offers some suggestions for important research priorities in model development and associated observations.

8.1. Ocean–climate feedbacks Figure 1.40 summarises the key ocean feedbacks that contribute to climate. This section attempts to identify and summarise the modelling issues and limitations that exist for these feedbacks and in particular how well the models currently used for climate projections simulate the carbon cycle and sea-ice. The following key questions need to be considered against each of the feedbacks: What are the consequences for future climate prognoses if these feedbacks are not adequately understood and how can they be prioritised?

8.2. Heat uptake The oceans are the main heat reservoir for the world, particularly over longer time periods, and strongly influence the rate of climate change as they have a large capacity to absorb heat compared to land. As a consequence, the oceans warm up slowly down to depths of kilometres and act as a delay on anthropogenically forced global temperature rise. A corollary is that ocean warming will continue for a long time into the future, even if greenhouse gas concentrations are stabilised in the atmosphere. While damping the rate of surface climate change, this warming of the ocean also leads to sea-level rise through the thermal expansion of seawater. State-of-the-art coupled atmosphere–ocean global circulation models (AOGCMs) include the primary physics that controls ocean heat uptake, but there are still substantial differences in the results obtained by different models. For example, the efficiency of ocean heat uptake varies by a factor of over 5 among the AOGCMs used in the IPCC AR4, although the majority of the models are more tightly clustered (Randall et al., 2007). Some models are able to reproduce the broad picture of increasing

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heat content that is deduced from historical observations over the past 50 years (e.g. Barnett et al., 2001). Models generally do not reproduce the apparent maximum in global heat content in the 1970s, apparently calling into question whether the models have sufficient amplitude of internal climate variability; however, recent analysis by Domingues et al. (2008) suggests that the heat content maximum in the observations may be partly an artefact of instrumental errors, thus reducing the discrepancy between models and observations. Uncertainty in the observed heat content estimates also arises from the limited sampling, especially in the era before the Argo buoy network (Gregory et al., 2004). Assessment of modelled and observed heat content changes remains an active research area. Modelling of changes in the heat content of the North Atlantic by Banks and Gregory (2006) has shown that regional distributions of heat uptake are crucially dependent on the changes in the large-scale circulation and mixing

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of the oceans and not just along lines of equal density as might be indicated by tracers. In another study, Lozier et al. (2008) showed large regional differences in the heat uptake of the North Atlantic, which has increased on average at a rate equivalent to a surface heat flux of 0.4 0.05 W m2 over the last 50 years. This basin-wide increase disguises a large contrast between the sub-polar gyre which experienced a net loss of heat between the periods 1950–1970 and 1980–2000 against a large heat gain in the tropical and subtropical North Atlantic. The changes were attributed at least in part to recent decadal variations of winds and heat flux linked with the NAO. The present generation of climate models, in general, do not model recent NAO changes well, so that it can be concluded that there is still considerable uncertainty in modelling heat uptake at this level of detail. Recent analyses by Sriver and Huber (2007) have demonstrated that ‘tropical cyclones are responsible for significant cooling and vertical mixing of the surface ocean in tropical regions’. They calculated that 15% of the transport of heat by the ocean may be associated with this downward mixing of heat. Furthermore, the strength of mixing is correlated with SST so that future increases in tropical temperatures may have important consequences for ocean heat transport and circulation. Since tropical cyclones are poorly resolved in models that are in use at present, their effects must be represented in gross form (parameterised). The size of errors in mixing projections associated with possible future changes in tropical cyclones has not been assessed. 8.2.1. Main limiters to heat uptake modelling progress

The wide range in the present generation of model estimates of heat uptake efficiency. A greater understanding of the reasons for inter-model differences at the process level. An improvement in temporal and spatial coverage of observational data needed to evaluate models. Good estimates of historical water mass changes, including complete error estimates. Shortness of time series (and limits to modelling of the main modes of climate variability) makes the distinction of Climate Change from natural variability difficult. Better sampling (from Argo) will over time improve global observational coverage. More sophisticated data assimilation (reanalysis) methods are needed to extract maximum information from limited historical data. Improved estimates of atmospheric aerosol forcing would have a knockon impact by further constraining the calculation of the efficiency of ocean heat uptake.

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8.3. Heat transport The poleward transport of heat from the tropics, by extensions of the Gulf Stream and the North Atlantic Current and the southerly directed deep counter currents as part of the MOC, has major implications for climate. Around 1015 W of heat is moved northwards in the North Atlantic and is dissipated to the atmosphere northwards of about 24 N to represent a substantial heat source for Northern Hemisphere climate. It has been postulated that a slowing down or cessation of the MOC could lead to a sudden and marked reduction in heat transport to the region, leading to a cooling of Europe’s climate. However, total shutdown of the MOC is generally considered to be a high impact, low probability event, especially in the twenty-first century. The present generation of climate models suggests a slowdown ranging between 0% and 50% during the twentyfirst century, under the IPCC A1B scenario, but none of the models suggests a shutdown (Meehl et al., 2007). In the models where the MOC weakens, warming will continue in Europe as any reduction in the MOC will be counterbalanced by warming due to increasing greenhouse gases. At present it is not possible to give precise quantitative advice, especially on longer timescales, due to a large range of uncertainty in the modelling. Density contrasts caused by spatially differing air–sea heat exchange are one of the three driving forces behind the MOC; others are density contrasts due to spatially differing freshwater exchange (haline forcing) (Saenko et al., 2002) and surface flux of momentum (wind stress forcing) (Beena and von Storch, 2009; Chelton et al., 2001; Delworth and Greatbatch, 2000). Using models to help determine the relative importance of these three driving forces is an important research area for Climate Change. Overall, models suggest that the response of the MOC to Climate Change is initially driven by changes in thermal forcing, with fresh water/salinity effects taking on an increasing role at longer timescales. Freshwater supply from melting of the Greenland ice sheet is not properly modelled in the current generation of climate models. Evidence from recent studies with improved ice sheet models (Fichefet et al., 2003; Ridley et al., 2005) is mixed as to whether this extra water source would have a significant impact on the MOC, but still no model suggests an MOC shutdown during the twenty-first century. Since important branches of the MOC pass through narrow straits that are not fully resolved in present climate models, the sensitivity of model projections to model resolution is an important open question. Many changes have been observed in the North Atlantic recently, for example, in salinity and in some elements of the MOC flow. The MOC at the latitude (25 N) of maximum heat transport has been estimated only a few times from direct observations (Bryden et al., 2005) making it difficult

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to know if there have been any long-term trends. However, a programme of continuous monitoring has recently begun (Cunningham et al., 2007), which should considerably improve our knowledge of the MOC and its variability. Overall there is not yet a clear picture of how the North Atlantic has been changing in recent decades so that it is not yet possible to separate out the effects of climate change and natural climate variation. This remains an active and important research area. Because of the circumpolar surface circulation and the presence of major sites of deep water formation, the Southern Ocean is also a key contributor to the overturning of the world’s ocean. Its large surface area and potential for strong mixing make it an important area for heat and carbon uptake. The existing generation of climate models tend to have some biases in their simulations of the Southern Ocean circulation, believed to be partly a consequence of errors in the simulated winds (Randall et al., 2007). Eddies and boundary current processes may also play an important role in the circulation and tracer transports, and it is an open question as to whether their effects can be adequately parameterised in coarse resolution models (e.g. Banks et al., 2007). Lack of available observations to test the models in this remote part of the world remains an important constraint, although the Argo float programme is now helping to fill data gaps. The tropics are another area where improved understanding of modes of heat transport variability and links to ENSO requires further development in global climate models (GCMs). 8.3.1. Main limiters to heat transport modelling progress

Poor historical time series information on the MOC and its components. Complex patterns of variability make the disentangling of natural and anthropogenic influences difficult. A wide range of responses to increasing greenhouse gases in models of the MOC. Detailed process-level understanding of the different responses is required. Important flows through narrow channels are poorly resolved in presentday models although the importance of this for the modelled response is unknown. Some common errors are found in model simulations of the Southern Ocean. In this region, poor resolution of eddies and boundary currents may be a particular modelling issue and observational gaps limit understanding. The limited observational evidence available does not suggest any radical change to the existing picture of the ocean’s role in the climate system. While there are deficiencies in climate models, there is no clear evidence that the models on average would over- or underestimate large-scale climate change.

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8.4. Water cycle Many of the effects of climate change will be seen through the hydrological cycle. The hydrological cycle also feeds back on the ocean circulation through the impacts of fresh water on the THC (see Section 8.3). In modelling there is an increasing focus on the prediction of regional changes in precipitation. Overall, climate models predict a drying of the subtropics and increased precipitation at high latitudes, but beyond these broad indications there is considerable variation among model projections. A key issue from a modelling perspective is a lack of available observations of freshwater fluxes over the oceans. Substantial changes in salinity have been seen, and these have been interpreted as indirect evidence of changes in the hydrological cycle (Bindoff et al., 2007). However, because of the ability of the ocean circulation to transport large amounts of fresh water, the interpretation of the salinity observations remains a matter of debate (e.g. Pardaens et al., 2008; Wu and Wood, 2008). New datasets from satellites suggest a stronger response of the hydrological cycle to temperature changes than is seen in climate models (Wentz et al., 2007), but the datasets are still new and require further scrutiny. 8.4.1. Main limiters to water cycle modelling progress Limited observations of precipitation and evaporation over the ocean, and non-quantified error bars.

Limitations to the use of historical salinity observations, and possibly large natural variability, may restrict the use of salinity to quantify changes in the hydrological cycle.

8.5. Sea-ice In the Arctic, most climate models simulate slower losses of sea-ice in recent decades than have been seen in measurements made from satellites. A few models are able to simulate the observed long-term reducing trend (Stroeve et al., 2007), but it has been suggested that even these models are misrepresenting key processes of ocean heat transport into the Arctic due to limited resolution (Maslowski lecture 2008, http://www.ees.hokudai.ac.jp/coe21/ dc2008/DC/report/Maslowski.pdf; see also Maslowski et al., 2007, 2008). Record low sea-ice extents were observed in summer 2007, but it is important not to read too much into an individual season, since year-toyear variability is large and not all observed trends are necessarily anthropogenically forced. In contrast, in the Antarctic a decrease in ice extent is simulated over recent decades by some models, but other than the Antarctic Peninsula no such decrease has been observed. Clearly there is much research needed

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to understand recent observed changes and to model them adequately. The sea-ice components of climate models have improved considerably over the past decade, but the overall quality of sea-ice simulation depends also on the driving atmospheric and ocean simulations; and these may now be the limiting factors. Nonetheless a number of important thermodynamic and dynamic processes are still absent from most climate models, and this may be playing a role in some of the model-observation discrepancies (see next paragraph; Hegerl et al., 2007; Randall et al., 2007). Pronounced changes take place in the albedo of the ice-covered Arctic and Southern Ocean when sea-ice melts or is covered with snow or water. The physics behind the changes is still not fully understood and in particular interactions with the atmosphere, with surface melt water that can form ponds on top of the ice, with varying thicknesses of surface snow and with the freshwater surface layer on top of seawater once the ice has melted. Observations of these parameters are very limited, especially historically. In addition to the above difficulties, present-day modelling may not be adequately representing the dynamics of sea-ice, despite important developments in recent years. 8.5.1. Main limiters to sea-ice modelling progress

A lack of observations of sea-ice thickness. Poor understanding of processes controlling sea-ice distribution, including important driving variables in the atmosphere and ocean. Potentially large year-to-year variability makes it difficult to distinguish a climate change signal. A lack of understanding of a number of key sea-ice processes.

8.6. Gas exchange/carbon uptake (CO2, N2O, DMS) Understanding the transfer of CO2 from the atmosphere to the oceans and the carbon cycle is critical to the development of accurate future predictions. Eventually carbon from the atmosphere will end up in the oceans; the problem is in determining the quantity, rates of transfer and location of the fluxes. There is a poor (but improving) knowledge of how the oceanic carbon cycle works. This is a key issue in predicting climate change as the amount of carbon dioxide absorbed by the ocean will strongly affect the impacts of particular atmospheric CO2 emission pathways on climate. Carbon cycle processes are not yet routinely included in climate general circulation models; hence feedbacks of climate change on carbon uptake are not explicitly modelled. However, in recent years a number of modelling groups have developed simple models of both the land and ocean carbon cycles that have been coupled into GCMs to estimate these feedbacks (Friedlingstein et al., 2006).

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Unlike physical processes, there is no convergence of scientific opinion on what are the key processes required to model the role of ocean biology and microbial ecology in carbon uptake and the production of radiatively active gases. Part of this debate involves the complexity that is required to adequately model feedbacks between the biology and climate. Processes (and hence parameterisations) of gas exchange and sinking fluxes are poorly understood (see the ‘Science Plan and Implementation Strategy’ of The Surface Ocean—Lower Atmosphere Study: SOLAS, 2004; http://www. uea.ac.uk/env/solas), yet models are very sensitive to these parameters. Coastal processes, which are not explicitly included in global carbon models, are likely to be highly dynamic in terms of gas exchange and carbon flux, although their overall importance for long-term carbon storage is uncertain. The debate extends to the physical part of the models: for example, eddies may play an important role in the carbon cycle through vertical transport of nutrients, and it is not known whether such transports can be adequately modelled with the existing resolution that is feasible in climate models. In summary, process-level understanding is poor so that predictive output differs greatly between models. However, most existing models suggest that the fraction of CO2 emissions absorbed by the ocean will decrease as climate warms (Denman et al., 2007). This is likely partly due to increased stratification and lower solubility of CO2 as the ocean surface warms. Recent observations have suggested reductions in carbon uptake in both the Southern Ocean and the North Atlantic; however, it is not clear whether these changes are global in extent or can be related to climate change (Le Que´re´ et al., 2005; Schuster and Watson, 2007). It therefore remains an open question whether such analyses of recent carbon uptake changes provide a useful constraint on future model predictions. 8.6.1. Main limiters to gas exchange modelling progress

A lack of quantitative and global understanding of driving biogeochemical processes. There is poor understanding of how to incorporate into models the complex biodiversity and functioning of microbial systems and their impact on biogeochemical cycles. Uncertainty over what level of complexity is required to adequately model the global effects of the ocean ecosystem. A potential high sensitivity of model results (especially vertical tracer fluxes) to resolution.

8.7. Retro-modelling of past climate change While palaeoclimate scenarios have been only marginally covered in this chapter, they provide some analogies to the rapid increases in temperature and pCO2 that are currently taking place due to anthropogenic forcing.

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Possibly the closest analogues to the present situation are the changes that took place prior to and during the PETM, 56 million years ago. In this event, global temperatures increased by 5 C within 1000 years and >2000 GtC as CO2 was injected into the atmosphere with profound impacts on, and feedbacks from, the oceans (Nunes and Norris, 2006; Sluijs et al., 2007; Zachos et al., 2008). The source of the CO2 remains controversial, but the most likely candidates are methane hydrates, volcanic emissions and oxidation of sedimentary organic carbon (Sluijs et al., 2007). It should be noted that even this event, considered ‘rapid’ in geological terms, was a significantly slower change than is projected over the twentyfirst century as a result of anthropogenic greenhouse gas emissions. Retromodelling of the PETM has failed as the models show a strong gradient between the equator and poles, whereas palaeodata convincingly indicate a weak gradient with subtropical conditions in the Arctic (Moran et al., 2006; Sluijs et al., 2006). This implies that some key processes/phenomena that were operating in the PETM are not being taken account of in the current generation of models. The PETM provides us with information on the feedbacks that operate in the Earth system on longer (multi-century) timescales. It is not clear how important these feedbacks are for the more rapid twenty-first century response to anthropogenic forcing. A greater use should also be made of palaeodata not only to test models but also to investigate the coupling of carbon cycling and climate, and the role of feedbacks and the sensitivity of climate to extreme changes in greenhouse gases (see Zachos et al., 2008).

8.8. Final comments

There is a need for an improved understanding of the sensitivity of model results to resolution. This will require the development of higher resolution models and/or improved parameterisations of unresolved processes (e.g. vertical mixing, sill through-flows, boundary currents, eddies). Developments of this nature will be highly dependent on the availability of appropriate computer power. An integrated global ocean observing programme needs to be implemented to include continuous time series of key ocean–climate variables. Such time series need to be maintained for a sufficient length of time to enable a climate change signal to be distinguished from internal variability (e.g. Argo, Altimetry, RAPID MOC array, Continuous Plankton Recorder, CPR). Development of improved and integrated observational datasets of sea-ice thickness is needed. A better observational structure is required to measure the large-scale hydrological cycle that includes error estimates.

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Observational constraints on large-scale ocean carbon uptake need to be resolved with an improvement in the understanding of key processes controlling the ocean carbon cycle (leading to development of models at the appropriate level of detail). Model development is a painstaking, lengthy and continuous process. Long-term investment commitments for both model development and observational time series must be maintained if current demands for an increasing level of detail and reliability in climate predictions are to be met. A greater use should be made of palaeodata not only to test models but also to investigate the coupling of carbon cycling and climate, and the role of feedbacks and the sensitivity of climate to extreme changes in greenhouse gases.

9. Conclusions and Recommendations The Earth is a blue planet, with two-thirds of its surface covered by oceans. It is home to many hundreds of thousands of organisms ranging from the important microbial viruses, bacteria and Archaea to the microscopic and beautiful siliceous, frustuled diatoms to magnificent whales. Some indication of this diversity and beauty has been captured by the Census of Marine Life.3 This chapter has been produced to draw attention to the key role that the oceans play in regulating climate as the main heat engine, water reservoir and carbon sink of the planet. It is worth noting as well that the oceans are greatly impacted in turn by climate change with considerable consequences for coastal communities and urban centres from sea-level rise and storms to fisheries and marine transport. The oceans have been buffering (neutralising) climate change over the past two centuries by absorbing carbon dioxide and heat from the atmosphere generated by both natural variability and man’s contribution via increased levels of greenhouse gases in the atmosphere. This key role in climate has helped substantially reduce the rate of climate change. There has not, however, been any reduction in the independent and parallel effects of ocean acidification due to increasing concentrations of CO2. In recent decades changes have occurred that could alter and possibly undermine the buffering role of the oceans via negative and positive feedbacks. There is a need for a better understanding of these feedbacks, not all of which are fully included in modelling. Some studies indicate that incomplete accounting of land and ocean carbon cycle feedbacks may already have led to an underestimate of the measures needed to mitigate climate change.4 The 3 4

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wide range and rates of changes now underway in the seas and the potential for abrupt changes to occur that may be triggered by feedbacks from the oceans, raises concern. It should be noted, however, that it is still impossible, due to a lack of appropriate long-term measurements, to establish the extent to which some of these changes are due to natural variability or directly a consequence of man-made climate change.

9.1. A decade ago In 1998 in a seminal paper in Science, Falkowski et al. noted that their intention was ‘‘not to make quantitative predictions of the feedbacks, but to call attention to the sensitivity of marine ecosystems, on all time scales, to climatic and geophysical processes external to the ocean, and the role marine ecosystems have played in regulating the chemistry of the Earth. Our predictive capabilities will improve only when the need for an international network of coordinated long-term (multidecadal) observations of oceanic biology is addressed, and our ability to incorporate the biological processes and feedbacks in coupled ocean–atmosphere models is dramatically improved’’. These words are as true today as they were then. A decade has passed, climate change has become a much more urgent issue, and yet the resources to develop an understanding and to measure, through oceanscale observing programmes, these key feedbacks for climate change have not been made available. Progress has been made, but not at the scale and rate that is needed.

9.2. Warming waters The main role that the ocean plays in climate variability and change is its huge capacity for the transport and storage of heat that reaches the surface of the planet from the Sun. Some of the heat is transferred to the deep ocean by mixing and some is released back to the air-driving weather systems and warming adjacent coasts (Bindoff et al., 2007). Over recent decades the oceans have warmed rapidly at the surface (0.64 C over the last 50 years) and in the whole water column in terms of heat storage. Some idea of the scale of the change is clear when it is realised that warming of the global oceans accounted for more than 90% of the increase in the Earth’s heat content between 1961 and 2003. Surface warming has been most pronounced in the Arctic and around the western Antarctic Peninsula where winter temperatures have increased by 5 C in winter months since the 1950s. Globally, most of the increase in ocean heat content has very likely been caused by increasing greenhouse gases. Heat is the main driver of change within the oceans and leads to the biggest feedbacks to climate change. It has pronounced effects on global ocean circulation, sea-level rise, the concentrations of a major greenhouse gas, water vapour in the air (through increased evaporation), the

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occurrence of tropical storms, and the melting of polar sea-ice. Increased temperatures and storms could also alter the sea-to-air transfer of sea salt particles and gases that contribute to climate-cooling aerosols and clouds. Warming also affects the water’s ability to absorb carbon dioxide and the amount of this greenhouse gas removed from the atmosphere. Finally, there is evidence for increases in the intensity of upwelling at the major upwelling sites around the world leading to large increases in phytoplankton production, anoxia and release of greenhouse gases.

9.3. Freshening waters Salinity, the second factor that changes the density of seawater besides temperature has shown a remarkable freshening in many regions of the world, including in deep water surrounding Antarctica. The pattern of change is consistent with an enhanced hydrological cycle, a response that has been predicted by climate modellers as a consequence of a warming ocean. In the case of the deep waters around Antarctica the reduced salinities almost certainly reflect the measured deflation of the West Antarctic ice sheet, retreat of glaciers in the Antarctic Peninsula and enhanced basal melt of sea glaciers.

9.4. Changing ocean circulation and sea-level Warmer water is less dense; as it heats up, a warmer upper layer is established and ‘floats’ above cooler, denser water. This ‘stratification’ of seawater is increasing globally, isolating the surface warmer layer from the nutrient-rich deeper waters. As a consequence, the large central tropical/subtropical areas deficient in nutrients are expanding in most oceans. Associated with this change is an expansion of the OMZs in the tropical oceans that has a pronounced effect on the carbon and nitrogen cycles and impacts on marine ecosystems. Combined, all these factors can limit the production of plankton and reduce the amount of carbon dioxide that is removed from the air. Intensified stratification and oxygen depletion may also lead to better preservation of carbon in bottom sediments, thus acting as a sink for carbon dioxide. The net global balance between these opposing processes is likely to leave more carbon dioxide in the air and contribute to increasing rates of global heating. As rainfall patterns change and ice melts, the freshwater inputs into many seas have increased. The saltiness of the sea has declined markedly in deeper waters of the Southern Ocean and in waters at all depths flowing from the Arctic into the Atlantic. Global circulation in the oceans, the ‘conveyor belt’, relies upon the formation of cold and salty water sinking in highlatitude seas, and ultimately drives the transfer of heat, nutrients and dissolved gases around the world’s oceans. Warmer and less saline polar seas are

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less effective at driving this process, thereby affecting the way heat is transported around the world. Current models predict a reduction in the intensity of this global overturning circulation of up to 50% by 2100, but no abrupt shutdown,5 as has been occasionally suggested in the media. Both the expansion of water due to heating and the melting of glaciers and ice caps cause sea-level to rise. Sea-level is currently tracking the rise in global SST. There are major concerns over the likely contribution that the Greenland, and possibly the West Antarctic, ice sheets might make to sealevel over the next few centuries. The processes involved in ice sheet destabilisation are not well understood and have not been adequately taken into account in current ice sheet models. Historical evidence adds credibility to the possibility of rises at the upper end of and beyond the IPCC AR4 projections by 2100 and a rise of several metres within several hundred to thousands of years. Sea-level rise will affect humans in many ways, including the potential displacement of millions of people. Displacement of populations and loss of coastal lands will likely lead to changes in land and resource use that have the potential to further increase climate change.

9.5. The MOC and cooling of NW Europe Combined together, changes in salinity and temperature alter density distribution, stratification and the Meridional overturning circulation with large potential feedbacks to climate. However, there is no evidence as yet that the THC/MOC has been changed by the observed salinity and temperature changes. Modelling projections predict that the MOC will reduce by between 0% and 50% by the end of the century, but that this will not lead to a cooling of Northwest Europe, but a slowing down of the warming associated with a rise in global mean temperature.

9.6. Tropical storms The intensity of tropical storms (hurricanes, cyclones, typhoons) has increased by 75% in the North Atlantic and western North Pacific and a global increase in their destructiveness has been documented. With rising sea temperature and enhanced precipitation the area for seeding tropical storms may expand. These storms may feedback to climate as they have a major impact on the mixing of the ocean. There is, however, at present, no scientific consensus on whether tropical storms will continue to increase in intensity and possibly frequency with rising global temperatures. 5

IPCC AR4 WG 1, Chapter 10.

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9.7. Primary production, biodiversity and non-native species Production of atmospheric oxygen and fixation of carbon during photosynthesis by phytoplankton enables the Earth to support a rich diversity of marine life and has strongly influenced changes in climate through geological time. The many tens of thousands of planktonic species in the oceans play a key role in ecological and biogeochemical processes that are important in the carbon cycle and climate. Within the last decade major advances have been made in understanding oceanic microbial diversity and ecology, but the extent to which these newly discovered microbial systems will change and impact biogeochemical cycles and climate in a warming world is poorly understood. Changes in the composition of different functional groups in the plankton can strongly impact the biological pump that removes carbon from the upper ocean and have been implicated as one of the causes of the large changes in carbon dioxide between glacial and interglacial periods. There is limited knowledge of the spatial and temporal variability of plankton composition and production versus recycling and export rates in most oceanic geographical provinces. Improved understanding of the interactions between different types of plankton food web structure and the export efficiency of carbon is urgently needed. Increased inflow of warmer water from both the North Atlantic and North Pacific into the Arctic Ocean has contributed to reductions in seaice. In 1998/1999, retreat of the ice from the north of Alaska and Canada allowed the first trans-Arctic migration of a Pacific organism (the phytoplankton Neodenticula seminae) into the North Atlantic, for more than 800,000 years. Further introductions of invasive species are expected following the ice reduction in the summer of 2007. Such non-native species could have a large impact on the plankton communities, biodiversity and ecosystems of the North Atlantic and the biological pump—with implications for the amount of CO2 which is absorbed by the ocean from the atmosphere. Warming seawater is also allowing non-native species to extend their distributions polewards.

9.8. Oxygen One of the most critical variables in the world’s ocean is the distribution of dissolved oxygen (O2) which is fundamental for all aerobic life. Significant reductions in the O2 supply to the ocean interior and expansion of low oxygen areas may result from continued anthropogenic global warming, although there may be regional increases in O2 levels. Models suggest that detectible changes in O2 content due to global warming may already have occurred. Expansion of the regions of the ocean interior that are devoid of O2 (anoxic) will adversely affect fish and other species.

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9.9. Nutrients A range of nutrients and micro-nutrients such as iron are essential for phytoplankton growth and production. Strong regional changes in nutrients are expected in the future dependent on variability in wet precipitation, wave storminess, expanding OMZs, increased nitrogen fixation by cyanobacteria in tropical/subtropical waters, mixing and the depth of stratification. It is not possible at present to predict future trends in nutrients because of the localisation of the changes or how these regional responses will add up to a global mean and influence climate change.

9.10. Ocean uptake of carbon dioxide The ocean carbon pumps together are possibly the second most important feedback to climate after rising temperatures. The ocean takes up carbon dioxide (CO2) from the air through three major processes that buffer climate change. Each of these processes has the potential to become less effective as global warming impacts the oceans, leaving more carbon dioxide in the atmosphere, and further increasing climate change. 9.10.1. The Solubility pump The gas CO2 is soluble in water and enters the ocean by air–sea exchange. The solubility pump removes large quantities of CO2 from the atmosphere each year, and stores them in the deep ocean where they cannot immediately contribute to the greenhouse effect. Over 1000 years, these deep waters are mixed back to the surface, allowing some gas to return to the atmosphere. At high latitudes, dense waters sink, transferring carbon to the deep ocean. Warming of the ocean surface inhibits the sinking and so reduces the efficiency of this pump. Furthermore, as waters warm, the solubility of CO2 in seawater declines, so less gas can be held in the seawater and taken up from the atmosphere. 9.10.2. The Biological pump CO2 is used by phytoplankton to grow. While most organic material is recycled within the food chain, a small proportion of the plankton sinks, and carries with it carbon from the ocean’s surface to the deep sea. In the very long term, much of this carbon is stored in sediments and rocks, eventually forming oil and gas deposits. Changes in temperature, acidification, nutrient availability, circulation, and mixing all have the potential to change the plankton productivity of our seas, and are expected to reduce the drawdown of CO2 via the Biological pump.

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9.10.3. The Continental Shelf pump Water and particles containing carbon are transferred from shallow shelf seas to the deep ocean by this pump. Projected warmer water and higher rainfall (causing reduced salinity) will together lead to increased layering of shelf seawaters and are expected to contribute to a decline in the efficiency of this pump. 9.10.4. The Carbonate Counter pump This pump provides a relatively small offset to the above effects. Many marine animals and plants, such as some plankton and corals, use carbon to make calcium carbonate, a building block of their protective walls and shells. By this process, carbon is ‘fossilised’, but the net growth of these organisms typically does not draw down CO2, but releases back a small proportion to the water and potentially to the atmosphere, in this way acting as a reverse pump. Acidification (see Section 9.11) in combination with rising temperatures is expected to have a pronounced effect on the efficiency of this pump and through dissolution of carbonate will allow the oceans, over several centuries, to take up slightly more CO2. For CO2 to be transferred from the air to the sea, the level in air must be higher than in the surface water. There is mounting evidence that concentrations in surface seawater have increased faster than in the air in some regions. If this trend became global in extent and continued into the future, the efficiency of oceanic carbon uptake could be expected to reduce. Given their importance, there is an urgent need to improve understanding of these carbon pumps and better include them in climate model predictions. IPCC AR4, for example, noted that ‘‘There are no global observations on changes in export production or respiration’’. Of great concern is evidence from observations and models that the uptake of carbon dioxide by the oceanic sink may be declining, and that the terrestrial sink may not be keeping pace with increasing emissions.

9.11. Acidification As well as causing climate change through the ‘greenhouse effect’, carbon dioxide is having a profound effect on the ocean by making seawater more acidic (lower alkalinity). As this gas dissolves into the ocean, it reacts, forming carbonic acid and reduces the pH of seawater. The changes in acidity measured in the open ocean also appear to be extending to some shelf seas. Due to the rapid rate of acidification, the ocean is predicted to be less alkaline, within 50 years, than at any time in the past 20 million years and possibly since the PETM, 55 million years ago. There is concern that ocean organisms will not be able to adapt to the speed and scale of change now underway. Among organisms expected to be most affected are some plankton (e.g. small snail-like pteropods; Fig. 1.41) and corals. These

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Figure 1.41 A pteropod. Image from http://pubs.usgs.gov/of/2000/of00-304/ htmldocs/chap11/images/pelag10l.jpg (U.S. Geological Survey).

organisms may be vital to the whole food chain, but also to the way the oceans take carbon dioxide out of the atmosphere and store it in the oceans, thus affecting the Biological pump.

9.12. A special case: The Arctic Covered by ice for much of the year, the Arctic Ocean is strongly influenced by relatively small changes in sea and air temperature. Warming may change Arctic winds, the thickness and extent of sea-ice, and the water’s salinity by melting ice and driving higher precipitation. Alterations in each of these may trigger large changes in regional climate within decades, with downstream consequences for the rest of the world. The Arctic has lost around 30% of its summer sea-ice in recent decades, with the most extreme reductions observed during the last decade. Sea-ice extent in 2007 was at a record low that was 40% below the recent long-term average. Despite being a cooler year than most in the past decade, the seaice extent in 2008 was also well below the long-term average, although it was not as low as the 2007 record. Sea-ice in 2008 was notable in that there is now little of the thick, old ice left, which could make the region increasingly vulnerable to further ice loss. The Arctic has been losing its sea-ice rapidly and it has been suggested that this may lead to a step change in the whole system due to a loss of the capping layer of fresh water in the Arctic Ocean. Ice is highly reflective and returns much of the solar radiation back to space; as it melts and exposes the dark ocean surface, the water rapidly absorbs and accumulates the incoming radiation over the long Arctic summer. This creates a feedback that tends to accelerate ice loss and warming of both sea and air, triggering further ice loss and regional warming.

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Model predictions for the disappearance of Arctic sea-ice during summers vary between 2013 and the end of the century. However, most climate models underestimate the rate of ice loss over recent decades, and even those that simulate recent trends suffer from deficiencies in resolution that may lead to an underestimate of future change. Some model results suggest that a threshold (tipping point) has been passed in the loss of Arctic sea-ice, meaning that recent low ice conditions may persist for some time.

9.13. Methane A warmer Arctic Ocean releases warmth back to the air, which can penetrate into adjacent coastal areas as far as 1500 km. This can melt permafrost, and potentially lead to the release of methane stored within it. Methane is 25 times more potent as a greenhouse gas than CO2, thus the release of methane is potentially a large feedback to climate change. The rate of release of this gas into the atmosphere has slowed down over the last 20 years; a rate change that is not well understood. In 2007 the concentrations of methane in the air increased, particularly in the Arctic, suggesting a release from Arctic permafrost among other sources. Extensive deposits of methane hydrate (methane gas trapped in an icelike solid) are found beneath coastal Arctic seas, and within permafrost on the adjacent land. A large release of methane from warming of marine hydrates is thought to be unlikely, unless warming causes landslides on steep continental slopes which hold hydrates or inflow of warmer water from adjacent oceans intensifies. Recently, large volumes of methane have been observed bubbling from the sea bed of the Laptev and East Siberian shelf seas and off Spitzbergen. It is not clear, however, if these new findings are a response to an anthropogenic warming signal.

9.14. Greenland ice sheet A recent accelerating reduction in the mass balance of the Greenland ice sheet may in part be due to higher temperatures in the adjacent ocean. While the precise threshold is not known, unless the trend in global temperature rise reduces, the temperature threshold for an eventual complete melting of the Greenland ice sheet may be crossed this century. Melting of the Greenland ice sheet alone could lead to 7 m of sea-level rise over thousands of years with implications for all coastal regions around the world.

9.15. The Southern Ocean The Southern Ocean, including the ACC, plays a critical role in driving, modifying and regulating global climate and climate change. An increase in westerly wind speeds due, at least partly, to human influences (increases in greenhouse gases and ozone depletion) has been observed, and a continuing

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warming of the Southern Ocean and strengthening of the westerly winds is predicted. The ocean west of the Antarctic Peninsula has warmed rapidly since the 1950s in parallel with changes in atmospheric climate and the cryosphere. Changes in the Southern Ocean are closely connected to the production and melting of sea-ice, the formation of which is the largest seasonal phenomenon on Earth. Sea-ice has a major affect on the energy budget of the Earth and thus climate. A 25% decrease in sea-ice extent over the next 100 years is predicted. The evolution of the Southern Ocean along the coast of Antarctica is a major control on the stability of Antarctic glaciers and on the mass balance of the ice sheet as a whole. A reduction in the mass balance of the northern sector of the West Antarctic ice sheet induced by a thinning of the fringing ice shelves is most likely associated with greater subsurface penetration of Circumpolar Deep Water onto the continental shelf. The rates of retreat of glaciers in the Peninsula and in West Antarctica are predicted to accelerate. The Southern Ocean is an important sink for carbon dioxide, a sink that has been reported as possibly weakening and approaching saturation, and which urgently requires further investigation. In the future, it is estimated that the CO2 sink in the Southern Ocean will undergo further modification. Marked changes have occurred in Southern Ocean ecosystems including a substantial decline in krill numbers. The changes in biodiversity, combined with the effects of acidification and rising temperature are likely to lead to important modifications to unique Antarctic ecosystems with associated feedbacks to the carbon cycle and climate.

9.16. Modelling Pronounced changes in ocean processes are now being recorded, some of which through complex feedbacks may accelerate global warming. Models are an essential tool to help investigate these feedbacks and their role in future climate change. Global Climate Change models have proved to be especially reliable in predicting future changes in global temperature. Modelling of ocean processes is less advanced, however, and there are a number of general limitations to progress in modelling feedbacks including poor data, a lack of understanding of key processes and inadequate representation of the processes in models (parameterisation). Data are needed for input to and validation of models; a lack of historical measurements and time series of key variables and processes is a major restriction on modelling progress. To address this problem there is an urgent need to implement an integrated global ocean observing programme that includes continuous time series of key ocean–climate variables. Such time series need to be maintained for a sufficient length of time to enable a climate change signal to be distinguished from internal natural variability (e.g. Argo, Altimetry, RAPID MOC array, ADCP arrays, CPR). In a number of cases, models representing key ocean feedbacks that contribute to climate have failed to represent observations or capture

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regional variation between different ocean basins, for example, the heat uptake, models used in IPCC AR4 and sea-ice models in the Arctic. Poor understanding of processes, inadequate representation of ocean/atmosphere drivers, a lack of inclusion of some important processes in models, scaling factors and spatial resolution as well as a lack of measurements are likely contributors to the failures. Some important ocean feedbacks such as the different ocean carbon pumps are not well represented in GCMs to date. Some studies of mitigation options omit feedbacks from the carbon pumps altogether. This omission could lead to an underestimate of the rate of future climate change, the stabilisation targets necessary to limit warming and, thus, the measures needed to achieve mitigation. There is no clear scientific agreement on the key processes required to model the role of ocean biology and microbial ecology on carbon uptake and the production of radiatively active gases. The processes involved in gas exchange and sinking fluxes, and their parameterisation are especially poorly understood and yet models are very sensitive to these parameters. In particular, it is not yet clear how the complex biodiversity and functioning of microbial systems and their impact on biogeochemical cycles should be incorporated into models. In the case of acidification, open ocean models work well, but the models are less effective in upwelling, coastal and shelf sea regions, which could be especially vulnerable to increased acidification. Observed changes in ocean feedbacks have occurred with a global average (land and sea) temperature rise of less than 1 C. Further warming may increase the impacts of the oceans on climate change, and amplify feedbacks. Despite considerable progress in the development of ocean/ climate models the above limitations mean that their output and prognoses need to be viewed with caution. It should be stressed, however, that while the models are not perfect, this does not reflect on their usefulness as they are an essential tool to look into the future.

9.17. Final concluding comments This chapter demonstrates that the oceans are vital in regulating our climate. There is an urgent need to improve understanding of the interaction between the oceans and climate change and better include this in climate model predictions. Greater use should also be made of palaeodata to test and inform climate models. The oceans have buffered climate change substantially since the beginning of the industrial revolution, acting as a sponge to carbon dioxide and heat from global warming. While it was assumed this would continue, this chapter gives a warning—changes underway in our ocean may accelerate warming or its consequences to organisms, and have the potential to increase climate change itself. In some examples, such as sea-ice loss, this process may already be underway. In this sense, and to quote a reviewer: ‘‘The ocean strikes back’’.

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Appendix: Workshop Participants Name

Russel Arthurton Ulrich Bathmann Gregory Beaugrand Diogo De Gusamao Stephen Dye Martin Edwards

Organisation

LOICZ, UK Alfred Wegener Institute, Germany University of Lille, France Hadley Centre, MetOffice, UK Marine Climate Change Impacts Partnership, UK Sir Alister Hardy Foundation for Ocean Science, UK Astrid Fischer Sir Alister Hardy Foundation for Ocean Science, UK Jacqueline Flu¨ckiger Swiss Federal Institute of Technology, Switzerland Tore Furevik University of Bergen, Norway Jean Claude Gascard AOSB, iAOOS, DAMOCLES, France Debora IglesiasNational Oceanography Centre, Rodriguez Southampton, UK Sabine Kasten Alfred Wegener Institute, Germany Mike Kendall Plymouth Marine Laboratory, UK Reto Knutti Swiss Federal Institute of Technology, Switzerland Emily Lewis-Brown World Wide Fund for Nature, UK Cecilie Mauritzen CliC, Norway Gill Malin University of East Anglia, UK Charlie Paull Monterey Bay Aquarium Research Institute, USA Robin Pingree Marine Biological Association, Plymouth/PML/ SAHFOS, UK Philip C. Reid Sir Alister Hardy Foundation for Ocean Science, UK and University of Plymouth Mike Sparrow SCAR, UK Paul Treguer University of Brest, France Alexander Tudhope University of Edinburgh, UK Carol Turley Plymouth Marine Laboratory, UK Meike Vogt University of East Anglia, UK Craig Wallace RAPID, UK Zhaomin Wang British Antarctic Survey, UK Richard University of Oxford, UK Washington Richard Wood Hadley Centre, MetOffice, UK

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ACKNOWLEDGEMENTS Philip C. Reid wishes to thank especially John Raven, John Church and Wolf Berger for their helpful advice and encouragement throughout the production of the chapter. We are also indebted to Richard Wood and Diogo de Gusma˜o for their contribution and advice on the modelling chapter. Especial thanks are given to attendees at the workshop, who are not on the authorship or mentioned above, for their advice and discussions, Russel Arthurton, Jean Claude Gascard, Catia Domingues, Jacqueline Flu¨ckiger, Debora Iglesias-Rodriguez, Reto Knutti, Robin Pingree, Paul Treguer, Alexander Tudhope and Carol Turley and we wish to acknowledge helpful discussions/correspondence with Nathan Bindoff, Philip Boyd, Howard Cattle, Jean-Claude Duplessy, Nick Hardman-Mountford, Graham Hosie, Patrick Hyder, Richard Kirby, Doug Martinson, Steve Rintoul, Daniela Schmidt, Toby Tyrrell, Martin Visbeck, the sources of the figures, and many other unnamed colleagues. We also wish to thank Sylvette Peplowski, Sally Bailey and Deborah Chapman from WWF who acted as rapporteurs at the workshop. The project to produce this chapter was started at the beginning of 2008 and formally initiated in March 2008 by a workshop in London funded by WWF. P. C. R. and A. F. gratefully acknowledge funding support from WWF, SAHFOS, The University of Plymouth and the Marine Biological Association of the United Kingdom and wish especially to acknowledge the backing and encouragement of Peter Burkill, Director of SAHFOS and assistance from Darren Stevens, SAHFOS on computing issues. P. C. R. thanks Charles Pearson, Regional Manager, NIWA Christchurch, New Zealand, for provision of facilities and Josh Bean, NIWA for computing support. The document was improved by the advice and comments of Jan de Leeuw.

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Vulnerability of Marine Turtles to Climate Change Elvira S. Poloczanska,* Colin J. Limpus,† and Graeme C. Hays‡ Contents 152 154 159 159 160 161 161 162 162 163 164 169 176 180 184 185 187 189 189 191 191

1. Introduction 2. Marine Turtle Biology and Life History 3. Observed and Projected Changes in Oceans and Atmosphere 3.1. Air and ocean temperature 3.2. Rainfall, storms and cyclones 3.3. Sea level 3.4. Winds and ocean currents 3.5. Large-scale ocean–atmosphere patterns 3.6. Ocean acidification 4. Climate Change Impacts on Marine Turtles 4.1. Embryos and hatchlings on nesting beaches 4.2. Reproductive turtles on inshore breeding grounds 4.3. Juveniles and adults foraging in oceanic waters 4.4. Juveniles and adults on inshore foraging grounds 4.5. Oceanic migrations 5. Responses to Past Climate Change 6. Adaptation and Resilience 7. Global Trends 8. Recommendations Acknowledgements References

Abstract Marine turtles are generally viewed as vulnerable to climate change because of the role that temperature plays in the sex determination of embryos, their long life history, long age-to-maturity and their highly migratory nature. Extant species

* Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Cleveland, Queensland 4163, Australia { Environmental Sciences, Environmental Protection Agency, Brisbane, Queensland 4002, Australia { Institute of Environmental Sustainability, Swansea University, Swansea SA2 8PP, United Kingdom Advances in Marine Biology, Volume 56 ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56002-6

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2009 Elsevier Ltd. All rights reserved.

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of marine turtles probably arose during the mid–late Jurassic period (180–150 Mya) so have survived past shifts in climate, including glacial periods and warm events and therefore have some capacity for adaptation. The presentday rates of increase of atmospheric greenhouse gas concentrations, and associated temperature changes, are very rapid; the capacity of marine turtles to adapt to this rapid change may be compromised by their relatively long generation times. We consider the evidence and likely consequences of present-day trends of climate change on marine turtles. Impacts are likely to be complex and may be positive as well as negative. For example, rising sea levels and increased storm intensity will negatively impact turtle nesting beaches; however, extreme storms can also lead to coastal accretion. Alteration of wind patterns and ocean currents will have implications for juveniles and adults in the open ocean. Warming temperatures are likely to impact directly all turtle life stages, such as the sex determination of embryos in the nest and growth rates. Warming of 2 C could potentially result in a large shift in sex ratios towards females at many rookeries, although some populations may be resilient to warming if female biases remain within levels where population success is not impaired. Indirectly, climate change is likely to impact turtles through changes in food availability. The highly migratory nature of turtles and their ability to move considerable distances in short periods of time should increase their resilience to climate change. However, any such resilience of marine turtles to climate change is likely to be severely compromised by other anthropogenic influences. Development of coastlines may threaten nesting beaches and reproductive success, and pollution and eutrophication is threatening important coastal foraging habitats for turtles worldwide. Exploitation and bycatch in other fisheries has seriously reduced marine turtle populations. The synergistic effects of other human-induced stressors may seriously reduce the capacity of some turtle populations to adapt to the current rates of climate change. Conservation recommendations to increase the capacity of marine turtle populations to adapt to climate change include increasing population resilience, for example by the use of turtle exclusion devices in fisheries, protection of nesting beaches from the viewpoints of both conservation and coastal management, and increased international conservation efforts to protect turtles in regions where there is high unregulated or illegal fisheries (including turtle harvesting). Increasing research efforts on the critical knowledge gaps of processes influencing population numbers, such as identifying ocean foraging hotspots or the processes that underlie the initiation of nesting migrations and selection of breeding areas, will inform adaptive management in a changing climate.

1. Introduction Climate change is one of the major threats facing our world over the coming century and impacts on biodiversity are already being recorded (Parmesan, 2006; Rosenzweig et al., 2007; Walther et al., 2002). The IUCN

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(International Union for Conservation of Nature) Marine Turtle Specialist Group through its Burning Issues assessment (http://www.iucn-mtsg.org/ hazards/) recently identified global warming as one of the top five major hazards to marine turtles globally; the other threats being fisheries impacts, direct harvesting of adults and eggs, coastal development, and pollution and pathogens. Life-history characteristics of marine turtles such as temperaturedependent sex determination, long age-to-maturity and a highly migratory nature may make marine turtles vulnerable to climate change. In this chapter, we consider the evidence and likely consequences of the potential impacts of climate change on marine turtles. Impacts are likely to be complex and there will be positive as well as negative impacts; however, adverse impacts are likely to be exacerbated by other anthropogenic-induced stressors such as capture by fisheries and coastal pollution. A long history of capture of adult turtles and harvesting of turtle eggs has reduced many populations worldwide to precarious levels. Marine turtles are iconic animals, especially given increases in eco-tourism and overseas travel, which acts to raise conservation awareness. Recent conservation efforts have resulted in a trend of increasing nesting numbers for several populations (e.g. Broderick et al., 2006; Chaloupka et al., 2008a; Hays, 2004; Seminoff and Shanker, 2008), but there are still a number of pressing conservation matters including climate change. For example, increasing temperatures and rising sea levels linked to large-scale climate changes are of particular concern for future nesting success. Shifts towards greater proportion of female hatchlings have been recorded on warming beaches (Chu et al., 2008; Glen and Mrosovsky, 2004; Hays et al., 2003a). However, earlier nesting has also been recorded at loggerhead, Caretta caretta, colonies in Florida and the Mediterranean, which may alleviate the impact of rising temperatures, to some degree, on hatchling sex ratios (Mazaris et al., 2008; Pike, 2009a; Weishampel et al., 2004). Extant turtle species probably arose during the middle–late Jurassic period (180–150 million years ago) when the world was warmer and more humid (Sellwood and Valdes, 2008). They have survived past shifts in climate, including glacial periods and warm events, by probably altering migratory routes, redistributing breeding and foraging sites and adjusting physiological parameters. Evidence of these can be found in contemporary populations. For example, in northern Australia, where temperatures are extremely high during the austral summer, flatback turtle Natator depressus populations breed during the winter. While on the Australian east and west coasts, at higher latitudes and hence cooler temperatures, N. depressus populations from adjacent genetic stocks nest during the summer months (Limpus, 1971). The timing of peak nesting at each location thus coincides with beach temperatures (25–32 C) compatible with high incubation success and suitable male/female hatchling ratios. The time period over

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which reproductive phenology shifted is unknown, but is likely to have been over a time scale of thousands of years. The question is can marine turtles adapt to future climate change given the rapid projected rates of global warming in the coming century? Rapid climate change coupled with high anthropogenic impacts on turtle populations, particularly pollution and high mortality through directed harvest and bycatch in fisheries, may seriously comprise the ability of turtle populations to adapt to our changing climate. On the other hand, climate change may benefit marine turtle populations through expansion of potential nesting and foraging areas and increased food supplies for various life stages. Impacts on trophic resources and key habitats such as open-ocean gelatinous zooplankton, seagrass beds and coral reefs may be critical for marine turtles. In this chapter, we review climate variability and change impacts on the life stages of marine turtles in five different habitats: embryos and hatchlings on nesting beaches, reproductive turtles on inshore breeding grounds, juveniles and adults foraging in oceanic waters, juveniles and adults on inshore foraging grounds, and during oceanic migrations. We also discuss the responses of marine turtle populations to past climatic change and the potential for adaptation to projected climate change by marine turtle populations. Long-term climate-related trends in marine turtle populations are generally obscured by heavy exploitation historically, in addition to the effects of current conservation efforts which are leading to recent increases in targeted populations (Broderick et al., 2006; Chaloupka et al., 2008a; Seminoff and Shanker, 2008). We conclude our chapter by discussing the current status and trends of marine turtle stocks worldwide and with some recommendations for conservation and research.

2. Marine Turtle Biology and Life History There are seven living species of marine turtle: flatback Natator depressus, green Chelonia mydas, loggerhead Caretta caretta, olive ridley Lepidochelys olivacea, Kemp’s ridley Lepidochelys kempii, hawksbill Eretmochelys imbricata and leatherback Dermochelys coriacea (Fig. 2.1). They are classified into two taxonomic families: the Dermochelyidae, which contains only the leatherback turtle, and the Cheloniidae, which contains the other six species. All of these, with the exception of the flatback N. depressus, are classified as ‘vulnerable’, ‘endangered’ or ‘critically endangered’ in the International Union for the Conservation of Nature (IUCN) Red List (IUCN, 2009; Seminoff and Shanker, 2008). The flatback, N. depressus, which occurs only in Indo-Pacific waters, is currently ‘data deficient’ for IUCN Red List assessment purposes but is considered ‘vulnerable’ in Australian waters

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Figure 2.1 Marine turtles: (A) loggerhead (Caretta caretta), (B) hawksbill (Eretmochelys imbricata), (C) flatback (Natator depressus), (D) green (Chelonia mydas), (E) olive ridley (Lepidochelys olivacea), and (F) leatherback (Dermochelys coriacea).

(Environment Protection and Biodiversity Conservation Act, Australian Government 1999) where all known nesting occurs. Cheloniid turtles are distributed throughout the world’s tropical and sub-tropical waters, but may appear seasonally in cooler waters of the northwestern Atlantic (Hawkes et al., 2007a; Morreale and Standora, 2005) or sporadically year round in cool waters of the south-western Pacific (C.J. Limpus, unpublished data). Marine turtles are generally considered ectothermic with their thermoregulatory capacity varying among species and with body size (Hochscheid et al., 2002; Spotila and Standora, 1985; Standora et al., 1982; Still et al., 2005). The largest turtles, adult leatherbacks,

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D. coriacea, display the greatest degree of endothermy (Bostrom and Jones, 2007; Eckert, 2002; Frair et al., 1972; Goff and Lien, 1988; James et al., 2005a, 2007; Mrosovsky and Pritchard, 1971; Southwood et al., 2005; Spotila and Standora, 1985; Wallace and Jones, 2008; Witt et al., 2007a). Mechanisms for heat retention such as counter-current heat exchangers in their flippers, thick body insulation and large body size enable adult leatherbacks (D. coriacea) to penetrate cold, high-latitude waters (Paladino et al., 1990; Wallace and Jones, 2008). Flatbacks, N. depressus, and Kemp’s ridleys, L. kempii, have the most restricted distributions with N. depressus only found in the continental shelf waters of northern Australia, eastern Indonesia and southern Papua New Guinea, while Kemp’s ridleys (L. kempii) occur mainly in the Gulf of Mexico and the eastern seaboard of the USA. Marine turtle species display common life-history traits which include long-distance migrations, natal homing, no parental care of eggs and young, and temperature-dependent sex determination in the nest (Carr et al., 1978; Meylan and Meylan, 1999). Marine turtles are long-lived and may not reach sexual maturity for many decades (e.g. Casale et al., 2003; Chaloupka et al., 2004; Limpus, 1992; Limpus and Chaloupka, 1997; Zug et al., 1997). They show strong fidelity to natal and foraging areas and undertake long breeding migrations between these regions, generally at intervals greater than 1 year (Avens et al., 2003; Bowen et al., 2004; Limpus and Limpus, 2003; Limpus et al., 1992; Luschi et al., 2003). During nesting, females come ashore and lay eggs in nests dug above the high water line on sandy beaches in the tropics and sub-tropics (Fig. 2.2). Typically, a female will make repeated visits to lay multiple clutches within one breeding season (Carr et al., 1978; Hays et al., 2002a; Limpus and Reed, 1985a; Limpus et al., 1983a, 1984, 2001). Sex of the hatchlings is determined by the nest temperature during the middle third of the incubation period, with higher temperatures producing females (see Fig. 2.3; Hewavisenthi and Parmenter, 2002; Merchant Larios et al., 1997; Miller and Limpus, 1981; Yntema and Mrosovsky, 1982). The ‘pivotal’ temperature, at which a 50:50 sex ratio is produced, is around 29 C for most marine turtle populations (Binckley et al., 1998; Broderick et al., 2002; Godfrey and Mrosovsky, 2006; Hewavisenthi and Parmenter, 2000; Limpus et al., 1985; Mrosovsky, 1988; Mrosovsky et al., 1992, 2002; Yntema and Mrosovsky, 1982). Hatchlings (Fig. 2.2) disperse to open-ocean foraging areas where as juveniles they may spend many years foraging in oceanic waters on gelatinous and other plankton, often at ocean fronts and eddies (Bolton et al., 1998; Bowen et al., 1995; Carr, 1987; Casale et al., 2007; Parker et al., 2005; Polovina et al., 2001; Salmon et al., 2004). The exception to this general pattern being the flatback (N. depressus), which remains in the continental shelf waters off northern Australia (Limpus, 2008; Walker and Parmenter, 1990). The juvenile

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Figure 2.2 (A) Green turtle (Chelonia mydas) laying eggs, Mon Repos, Queensland, Australia. (B) Monitoring green turtle (Chelonia mydas) nesting, Mon Repos. (C) Loggerhead (Caretta caretta) hatchlings heading to the ocean. (D) Flatback (Natator depressus) hatchlings. (E) Tourists watch a nesting green (Chelonia mydas) turtle.

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TRT

Male (%)

100

Pivotal temperature

50

0 29 °C Present

Temperature

Future

Figure 2.3 Generalised scheme of temperature-dependent sex determination in sea turtles and the effect of warming temperatures. A 1:1 sex ratio is produced at the pivotal temperature (around 29 C); cooler temperatures produce a male bias and warmer temperatures produce a female bias. TRT is the transitional range of temperatures over which sex ratios shift from 100% male to 100% female. The blue shading marked PRESENT corresponds to the range of temperatures currently experienced by hypothetical turtle nests at a rookery over the breeding season; red shading marked FUTURE indicates nest temperatures following climate warming—the sex ratio has shifted from male biased to female biased.

pelagic period has been termed ‘the lost years’ (Carr et al., 1978) as, until relatively recently, little was known of the distribution and ecology of the young turtles during these years. For some populations, particularly of leatherbacks (D. coriacea), olive ridleys (L. olivacea) and Kemp’s ridleys (L. kempii), this is still the case. Different species, populations and age classes display a wide range of foraging modes. Foraging grounds of adults and large juveniles of hawksbills E. imbricata, loggerheads (C. caretta), Kemp’s ridleys (L. kempii), flatbacks (N. depressus) and green turtles (C. mydas) tend to be in coastal waters, and the larger immature and adult turtles spend most of their time in these foraging habitats. Hawksbills, E. imbricata, are omnivorous and forage around coral reefs and rocky outcrops, eating benthic invertebrates such as sponges and algae, and occasionally jellyfish (Blumenthal et al., 2009; Houghton et al., 2003; Leo´n and Bjorndal, 2002; Meylan, 1988). Loggerheads (C. caretta) and Kemp’s ridleys (L. kempii) are generally carnivorous, taking invertebrates such as crustaceans and molluscs (Godley et al., 1997; Limpus et al., 2001; Plotkin et al., 1993; Seney and Musick, 2007;

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Wallace et al., 2009). Leatherbacks (D. coriacea) and eastern Pacific olive ridleys (L. olivacea) tend to forage in oceanic environments as sub-adults and adults, exploiting gelatinous plankton and planktonic crustaceans (Benson et al., 2007; Houghton et al., 2006; James and Herman, 2001; Salmon et al., 2004; Wallace et al., 2006). In the Australasian region, olive ridleys (L. olivacea) are benthic, foraging on crustaceans and molluscs (Whiting et al., 2007). Flatbacks (N. depressus) also are carnivorous, feeding on soft bodied invertebrates (Limpus, 2008). In contrast, green turtles (C. mydas) are primarily herbivorous feeding on mostly seagrass and algae (Andre et al., 2005; Brand-Gardner et al., 1999; Fuentes et al., 2006; Garnett et al., 1985; Lopez-Mendilaharsu et al., 2005; Mortimer, 1981). However, recent studies reveal C. mydas may continue to consume of gelatinous zooplankton even as adults during foraging periods along benthic coastal habitats (Arthur et al., 2007).

3. Observed and Projected Changes in Oceans and Atmosphere Climate varies over spatial and temporal scales from seasonal changes to decadal or even millennial variations. The geological record reveals a positive relationship between atmospheric CO2 concentrations and global temperatures (Doney and Schimel, 2007). Present-day atmospheric CO2 concentrations were last reached, at a minimum, 650,000 years ago (Denman et al., 2007). The Earth may now be within approximately 1 C of maximum temperatures of the past million years (Hansen et al., 2006). While many patterns are evident in the global climate, what is now, unequivocal, is that global climate has warmed over the past century due to anthropogenic greenhouse gas emissions (IPCC, 2007). Owing to the inertia of the atmosphere–ocean system, temperatures will continue to rise over the next few decades, if not longer, regardless of any attempts at mitigation of greenhouse gas emissions (IPCC, 2007; Matthews and Caldeira, 2008). Evidence for climate change manifests not only through observed warming temperatures but also through associated changes in the ocean– atmosphere system, such as alternation of rainfall and storm patterns, rising sea level and changes in ocean salinity, all of which will impact the various life stages of marine turtles.

3.1. Air and ocean temperature Average global surface temperatures have risen by 0.74 C over the hundred years since 1906, with warming in recent decades being the most rapid (Trenberth et al., 2007). Eleven of the twelve warmest years since records

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began in 1850 (to 2006) occurred from 1995 onwards (Trenberth et al., 2007). Warm days and nights have become more frequent over most land areas over the past few decades and are projected to continue to increase in frequency while the frequencies of cold extremes are declining (IPCC, 2007; Shiogama et al., 2007). The Northern Hemisphere is warming much faster than the Southern Hemisphere and surface air temperatures are rising faster over land than over the ocean (Hansen et al., 2006; IPCC, 2007). Warming air temperatures may impact the hatching success and hatchling sex ratios of marine turtles globally. Ocean temperatures have also been rising, albeit at a slower rate than air temperatures given the large thermal capacity of the oceans. Over the last 50 years, ocean temperature has risen by 0.1 C to depths of 700 m. Ocean warming is projected to evolve with the upper ocean warming first, then penetration of warming to the deep ocean by the end of the twenty-first century, and particularly so in mid-latitude regions (IPCC, 2007).

3.2. Rainfall, storms and cyclones Rainfall is highly variable both temporally and spatially, but long-term observed trends during the past several decades are evident over many regions linked to rising atmospheric CO2 levels (IPCC, 2007; Zhang et al., 2007). The trends show a drying of Northern Hemisphere tropics and sub-tropics and a moistening of Southern Hemisphere tropics (Zhang et al., 2007). Tropical wet seasons are projected to get wetter, particularly over the tropical Pacific, while dry seasons may get dryer or remain unchanged (Chou et al., 2007). As the frequency of intense rainfall increases over many land areas, including tropical areas, so will the risk of flood events (Meehl et al., 2007). There may also be a tendency for more intense midlatitude storms over this century and an associated increase in wave height (Meehl et al., 2007). The intensity of cyclones has increased in some regions such as the tropical North Atlantic, the Indian Ocean and Southwest Pacific Oceans (IPCC, 2007; Saunders and Lea, 2008). A 0.5 C rise in August–September sea surface temperature (SST) over the period 1965–2005 resulted in an approximately 40% increase in cyclone activity during the storm season (August–October) in the tropical Atlantic (Saunders and Lea, 2008). Climate model projections suggest that the strength of intense storms is likely to further increase over the coming century (Bengtsson et al., 2007; Meehl et al., 2007). For example, simulations of a regional climate model for the Cairns coastline, northeast Australia, showed that projected increases in cyclone intensity can result in a storm surge event with a return period of 100 years, becoming a 55-year event by 2050 and a 40-year event when sea-level rise is also considered (McInnes et al., 2003).

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The global areas affected by tropical storms may widen polewards, particularly in the Southern Hemisphere (IPCC, 2007). There is evidence to indicate a polewards shift in storm tracks has already occurred over the second half of the twentieth century (IPCC, 2007; Seidel et al., 2007). The destructive effects of cyclones, such as flooding, may, therefore, impact at higher latitudes as global temperatures warm (Isaac and Turton, 2009).

3.3. Sea level Sea level has risen by an estimated 1.7 mm/year during the twentieth century due to thermal expansion of the oceans and widespread melting in glaciers and ice caps (IPCC, 2007). Sea-level rise is projected to continue but at a greater rate than over the last several decades. The rates of sea-level rise vary between regions with some areas rising much faster than the global mean rise, while in other areas sea level appears to be falling. Sea levels in the western Pacific and eastern Indian Oceans, where a myriad of tropical islands are found, and many of which contain turtle nesting beaches, are rising in accordance with the average global sea-level rise (Church et al., 2006). The differences in sea-level rise among regions depend largely on regional hydrodynamics and geology. Low-lying, small islands, such as coral atolls, are considered ‘especially vulnerable’ to sea-level rise and extreme events, particularly in the Pacific, although studies have indicated some islands may be morphologically resistant (Mimura et al., 2007). Generally, coral atoll islands are low-lying with the majority of land lying less than 2 m above mean sea level, and are thus vulnerable to storms which can redistribute large quantities of sand and rubble so eroding or building shorelines (Woodroffe, 2008). Islands which have lithified sediments and contain high vegetative cover may be more resilient than unconsolidated or unvegetated islands (Woodroffe, 2008). Large storm surges and tidal surges can be extremely destructive to lowlying coastlines and magnify effects of sea-level rise (Zhang et al., 2004). Sandy beaches are dynamic systems, undergoing continual processes of erosion and accretion (Short, 2006; Zhang et al., 2004) as sea levels and ocean climate alter. As long as beaches can evolve naturally, there should be a continuum of nesting beaches of marine turtles on regional scales. However, beaches that are trapped in a ‘coastal squeeze’ between human developments and climate change will be least resilient, especially considering the present-day recessional nature of the majority sandy beaches globally (Fish et al., 2005; Jones et al., 2007; Schlacher et al., 2007; Zhang et al., 2004).

3.4. Winds and ocean currents Rising temperatures will affect atmosphere and ocean circulation. No significant global trends in marine wind speeds have been identified but regional trends are apparent in the tropics and extratropics (regions between

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30 and 60 latitude from the equator) (IPCC, 2007). A polewards shift and strengthening of the westerly wind belts, driven by rising atmospheric CO2 concentration, has resulted in a strengthening of the East Australian Current (EAC), which carries tropical water from the Coral Sea, and an enhancement of warming rates in the Tasman Sea, impacting marine fauna in this region (Cai, 2006; Cai et al., 2005; Hill et al., 2008; Poloczanska et al., 2007). The Kuroshio Extension current in the western North Pacific, an important foraging hotspot for juvenile turtles (Polovina et al., 2004b, 2006) has increased and moved southwards after 1976, this shift being linked to spin-up by the sub-tropical wind in the North Pacific influencing the wind-driven sub-tropical ocean gyre (IPCC, 2007; Sakamoto et al., 2005). There is no evidence to date for a trend in the strength of the Gulf Stream in the North Atlantic, a subject of much public deliberation (IPCC, 2007).

3.5. Large-scale ocean–atmosphere patterns The El Nin˜o-Southern Oscillation (ENSO), a large-scale ocean–atmosphere phenomenon, has profound influence inter-annually on regional seas but with teleconnections to global climatology. Described simply, ENSO events fluctuate irregularly between two phases: El Nin˜o and La Nin˜a although each ENSO event evolves slightly differently. There are well-documented impacts of ENSO on atmospheric and ocean climates and ecosystems. For example, during El Nin˜o years seasonal rainfall increases over the central and easterncentral Pacific Ocean, and decreases in the Western Pacific and Indian Ocean with a weakening of monsoons in Asia. The ENSO signal has been found in marine ecosystems at all trophic levels from phytoplankton and algae (Turk et al., 2001); to tropical corals (Baker et al., 2008; Grottoli and Eakin, 2007), marine turtles (Limpus and Nicholls, 1988; Saba et al., 2007) and predatory fish (Lehodey et al., 1997). Historically, El Nin˜o events occur every 3–7 years but El Nin˜o events appear to have become dominant since the 1976–1977 ‘climate shift’ when global temperatures started to rise rapidly due to anthropogenic forcing by greenhouse gas emissions (IPCC, 2007; Power and Smith, 2007). While climate models project a weak shift towards ‘El-Nin˜o-like’ conditions in future climate there is no consistent indication of changes in amplitude and intensity (IPCC, 2007).

3.6. Ocean acidification Ocean acidification is not a direct effect of climate change but is a consequence of fossil fuel CO2 emissions, which are the main driver of recent climate change (see Denman et al., 2007). The oceans are a major buffer of anthropogenic CO2 emissions absorbing over 40–50% in the past 200 years (Raven et al., 2005). Open-ocean surface waters are slightly alkaline with an

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average pH of around 8.2 (Raven et al., 2005). The average pH of the oceans has lowered by about 0.1 units, representing a 30% increase in hydrogen ion concentration, since 1750 (around the advent of the Industrial Revolution) when anthropogenic emissions of CO2 into the atmosphere started to increase substantially. The ocean surface is projected to acidify by up to 0.5 units over the twenty-first century (Caldeira and Wickett, 2003, 2005). The pH decrease over the coming centuries may be greater than any changes over the past 300 million years as inferred from the geological record (Caldeira and Wickett, 2003). Acidification leads to a decrease in the saturation state of calcium carbonate and a reduction in the depth below which calcium carbonate dissolves, thus impacting biological calcification rates (Orr et al., 2005; Riebesell, 2004). In waters under-saturated with respect to calcium carbonate, biological calcification rates decrease. For example, calcifying plankton shows dissolution, deformation and/or reduced calcification of shells and liths in undersaturated marine waters (Engel et al., 2005; Moy et al., 2009; Riebesell et al., 2000). Reduced calcification with increased acidity has also been shown in molluscs (Gazeau et al., 2007), coralline algae ( Jokiel et al., 2008; Martin and Gattuso, 2009), echinoderms (Clark et al., 2009; Dupont et al., 2008) and reef-building corals ( Jokiel et al., 2008; Silverman et al., 2009). Much concern has been raised over the severity of the threat of ocean acidification to the survival of coral reefs; by the end of this century all coral reef systems globally may display net dissolution of carbonate with deleterious consequences for coral ecosystems and coastal protection (Hoegh-Guldberg et al., 2007; Silverman et al., 2009). Ocean acidification may have far reaching impacts on ocean biodiversity beyond reduced biological calcification rates, depressing metabolisms and impacting physiologies of species ranging from invertebrates (Clark et al., 2009; Ellis et al., 2009; Kurihara, 2008) to fish (Munday et al., 2009). Increased dissolution of CO2 will increase physiological stress on organisms such as dissolved oxygen levels decrease and metabolic rates and physiological pathways are affected (Ishimatsu et al., 2005; Po¨rtner et al., 2005; Raven et al., 2005; Wilson et al., 2009). There is potential for the widespread disruption of marine food chains and ecosystems (Fabry et al., 2008).

4. Climate Change Impacts on Marine Turtles Climate change manifests in biological systems as changes in the distributions and abundance of species, alteration of phenology such as earlier occurrence of spring and other events, and the lengthening of vegetative growing seasons. Polewards distribution shifts consistent with recent warming have been recorded in many marine species ranging from

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plankton to fish (Beaugrand et al., 2002; Edwards, 2004; Mieszkowska et al., 2005; Perry et al., 2005) and phenological shifts are also evident in marine systems (Chambers, 2004; Edwards and Richardson, 2004; Mackas et al., 1998). Climate change will impact all life stages of marine turtles (Table 2.1).

4.1. Embryos and hatchlings on nesting beaches 4.1.1. Air temperature A major concern for marine turtles with respect to the effects of global warming is the impact on hatchling sex ratios, size and quality, and therefore on population dynamics (e.g. Booth and Astill, 2001a; Burgess et al., 2006; Glen et al., 2003; Godley et al., 2002a,b; Hewavisenthi and Parmenter, 2001; Mazaris et al., 2008). The temperature range over which sex ratios shift from 100% male to 100% female varies between marine turtle species and populations, but in general the range lies between 1 and 4 C (Wibbels, 2003). Small changes in temperature close to the pivotal temperature (29 C) can result in large changes in the sex ratio of hatchlings (see Fig. 2.3; Glen and Mrosovsky, 2004; Janzen, 1994; Limpus et al., 1985; Yntema and Mrosovsky, 1982). This suggests that warming of a couple of degrees centigrade, well within the warming expected over the coming century, can potentially result in a large shift in sex ratios. Air temperatures at many turtle nesting beaches worldwide have already warmed to, or are close to, all female-producing temperatures (e.g. Antigua, Caribbean: Glen and Mrosovsky, 2004; Ascension Island, South Atlantic: Hays et al., 2003a; Australasia, Western Pacific: Chu et al., 2008). As global temperatures rise, the ambient surface air temperatures at many turtle nesting sites globally will warm (Fig. 2.4) thus reducing or eliminating the likelihood of males. There is evidence to indicate, however, that turtles may not be as vulnerable to warming temperatures as first anticipated. Some nesting beaches have persisted with strong female biases over a few decades or even longer (Broderick et al., 2000; Godfrey et al., 1999; Hays et al., 2003a; Marcovaldi et al., 1997; Reed, 1980). There is no evidence to date that a low production of male hatchlings has resulted in a low reproductive success within populations (e.g. Broderick et al., 2000; Glen and Mrosovsky, 2004), although it is possible that the long-term population declines due to exploitation and other factors may mask such effects. Population units may also span many rookeries, so although individual nesting beaches may be female-producing, other beaches within the region may produce the necessary males and conservation of these beaches may become increasingly important as temperatures warm (Hawkes et al., 2007b; Hays et al., 2003a). Furthermore, temperatures will fluctuate during the nesting seasons so may be below pivotal temperatures for at least some of the season (Godfrey et al., 1996; Mrosovsky and Provancha, 1992; Reed, 1980).

Table 2.1 Summary of marine turtle life stages, habitat and potential major climate change impacts on the different life stages

Turtle life stage

Habitat (and distribution)

Incubation and hatching Breeding and nesting

Sandy beaches in the tropics and subtropics Coastal waters and sandy beaches in the tropics and sub-tropics Open ocean, tropics to cool-temperate latitudes

Oceanic juvenile and adults Neritic juveniles and adults Migrations

Coastal and shelf waters, tropics to temperate latitudes Shelf seas and open ocean, hundreds of kilometres to across ocean basins

Warming air and ocean temperatures

p

p

p

p

p

Air

Ocean

Alteration of rainfall, storms and cyclones

Rising sea level

p

p

p

p

Ocean

p

Alteration of large-scale ocean– atmosphere patterns

p

Ocean acidification

p

p

Ocean

Ocean

Alteration of winds and ocean currents

p

p

p

p

p

p

p

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Figure 2.4 Mean annual surface air temperature projections for (A) 2001–2010 and (B) 2091–2100 from CSIRO Mk 3.5 General Circulation Model (GCM) under greenhouse gas emission scenario SRES A2. The 20 , 25 and 30 contours drawn. GCM projections downloaded from the IPCC data hosted by PCMDI and processed at CSIRO marine research. Locations of major nesting sites for loggerheads (Caretta caretta), hawksbills (Eretmochelys imbricata) and leatherbacks (Dermochelys coriacea) (white dots) taken from maps printed by SWoT (2005, 2006, 2007). Full citations for each data point are given in SWoT (2005, 2006, 2007).

The propensity for female biases and likelihood of declining male production for some populations raises theoretical questions about the evolutionary significance of temperature-dependent sex determination (Godfrey et al., 1999; Hulin and Guillon, 2007; Hulin et al., 2009; Mrosovsky and Provancha, 1992; Reece et al., 2002; Wibbels, 2003), and as well as the importance for population dynamics of polyandry (multiple paternity) observed in some species to date (Lee and Hays, 2004; Theissinger et al., 2009; Zbinden et al., 2007). However, data series for hatchling production tend to be short or patchy and sample sizes small. Some of the longest data are for marine turtles nesting in the south-western Pacific over the last quarter century. These reveal long-term, highly skewed sex ratios towards females [hawksbill turtles (E. imbricata): Limpus and Miller, 2008; green turtles (C. mydas): Limpus, 2009] or towards males [loggerhead turtles (C. caretta): Limpus and Limpus, 2003]. Resolving such theoretical challenges may become increasingly important as global

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temperatures warm. We suggest concerns should be raised if sex ratios for regional stocks, that is, the sex ratio across all nesting beaches for a particular stock, approach 1:4 (male to female). Urgent work is also needed to establish the breeding periodicity of male and female turtles. There has been the suggestion that males may return to breed (the remigration interval) more frequently than females which generally only breed every 2–5 years depending on the population. Shorter remigration rates by males might help balance the sex ratios on the breeding grounds compared to hatchling sex ratios. To date, there has been little targeted work on males. The likelihood of males being produced is also determined by variations in localised factors such as sand albedo, sand grain size and vegetative cover which produce small-scale differences in thermal properties of nesting areas (Booth and Astill, 2001b; Hays et al., 2001a, 2003a; Hewavisenthi and Parmenter, 2002; Loop et al., 1995; Speakman et al., 1998), in addition to environmental factors such as rainfall (see below). For example, Mon Repos beach on the mainland in south Queensland has brown sand produces predominantly female loggerhead (C. caretta) hatchlings while the white sands of nearby (150 km) coral cay islands, such as Heron Island, produce mostly male hatchlings (see Fig. 2.5A and B; Limpus et al., 1983b). On Heron Island itself, the northern beach is warmer at nest depth than the more shaded southern beach and hence green turtle (C. mydas) hatchlings have a female bias from the northern beach and a male bias from the southern beach (Booth and Freeman, 2006; Limpus et al., 1983b). It will take temperature shifts of several degrees to change these male-producing beaches into beaches producing 100% female hatchlings. Beaches of contrasting sand colour within a population nesting regions are also found in other areas such as on Ascension Island (see Fig. 2.5C; Hays et al., 2001a). 4.1.2. Rainfall, storms and cyclones Turtles tend to nest just above the high water mark but cyclones, storm surges and heavy rainfall can inundate nests or erode sand dunes resulting in significant nest and egg loss (Edminston et al., 2008; Foley et al., 2006; Pike and Stiner, 2007a; Ragotzkie, 1959; Whiting et al., 2007; Xavier et al., 2006). Populations of marine turtles with nesting seasons that overlap with storm seasons will be most vulnerable to projected increases in storm intensity (Pike and Stiner, 2007a,b). The expected polewards expansion of tropical storm regions (Seidel et al., 2007) will increase impacts on populations nesting at higher latitudes. Rising sea levels, increases in wave heights, coastal erosion and increased storm intensities may all act to increase the risk of tidal inundation of nests at higher beach levels. Heavy rainfalls, such as those caused by storms and cyclones, may act to re-dress the balance in sex ratios through a cooling effect on sand temperature (Reed, 1980). Rainfall is accompanied by a drop in sand temperatures

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Figure 2.5 Contrasting sand colours of beaches within nesting regions of marine turtles in (A, B) the southern Great Barrier Reef and (C) Ascension Island. (A) Mon Repos beach, mainland southern Queensland, Australia. (B) Heron Island, southern Queensland, Australia. (C) Sand from Long Beach, Ascension Island (left) and North East Bay beach, Ascension Island (right).

and it has been shown that protracted rainfall can have a marked, although short-term, cooling effect on nests (Booth and Freeman, 2006; Gyuris, 1993; Houghton et al., 2007; Loop et al., 1995), skewing sex ratios towards males if coinciding with critical periods for sex differentiation (Godfrey et al., 1996; Houghton et al., 2007; Reed, 1980). For example, a significant negative relationship between monthly rainfall and sex ratios has been shown for leatherbacks, D. coriacea, and green turtles, C. mydas, nesting in Suriname (Godfrey et al., 1996). In general, a reduction in tropical rainfall globally is projected over the coming century which coupled with rising temperatures may exacerbate female biases in hatchling sex ratios. Regional increases, such as that projected for summer rainfall in north-western Australia (Nicholls, 2006), or short-term extreme increases in rainfall during storm events, may act to cool nests, if nesting coincides with rainfall and hence increase male production from otherwise female-producing beaches (Reed, 1980).

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4.1.3. Sea level Coupled with increases in storm intensity, rising sea levels may results in increased risk of tidal inundation or destruction of turtle nests on lowprofile beaches, thereby reducing population reproductive success (see above). Nesting beaches backed by coastal developments or salt marshes and lagoons that hindered beach evolution may be at most risk from rising sea levels (Fish et al., 2005, 2008). Where the area of beach available for nesting is substantially reduced, turtles may be forced to dig nests in beach zones that are sub-optimal for hatching success, for example in low regions with high salt-water inundation risk. Nesting area reduction may also result on subsequent increases in nesting density, thus increasing the risk of nest destruction during digging of neighbouring nests and the risk of predation (Mazaris et al., 2009). If nest density increases the likelihood of a disturbance impacting a larger proportion of nests on the beach may increase. 4.1.4. Large-scale ocean–atmosphere patterns The large-scale atmospheric patterns such as El Nin˜o influence local and regional climatology, such as the tropical monsoon season in the northern Indian Ocean. Any alteration in the pattern and intensity of El Nin˜o events will impact turtle nests through changes in rainfall, temperature and storm regimes.

4.2. Reproductive turtles on inshore breeding grounds 4.2.1. Air and ocean temperature Air temperatures directly affect nest incubation temperatures and therefore hatchling sex ratios (see above) and hatchling production. Nest temperatures are modified by factors such as the presence of vegetation and nest depth, so the nesting choices of females will influence hatchling sex ratios (e.g. Booth and Astill, 2001b; Foley et al., 2006; Hays et al., 2001a; Kamel and Mrosovsky, 2006; Speakman et al., 1998). Within a breeding year, successive nests may be clustered on the beach, but there is little evidence this represents fidelity to a specific beach area (Hays et al., 1995; Kamel and Mrosovsky, 2004; Limpus et al., 1984; Nordmoe et al., 2004; Xavier et al., 2006). Fidelity to beach zones such as dune areas or forest edges rather than specific beach regions has been shown for some populations but not for others, and it is unknown if such choices are genetically determined (Garmestani et al., 2000; Kamel and Mrosovsky, 2006; Nordmoe et al., 2004; Pfaller et al., 2009). Hawksbills, E. imbricata, have been shown to consistently select the same beach area for each successive nesting (Mrosovsky, 2006) but there is a lack of evidence to suggest some individuals in the population are genetically programmed to consistently nest in ‘poor’ areas (Pike, 2008a). Turtles are likely to use

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multiple environmental cues during the multiple phases of the nesting process which includes emergence, beach crawls and nest site selection (Mazaris et al., 2006). There is little evidence that females will shift nesting locations on beaches in response to the local environment; for example selecting heavily vegetated sites in warmer years (Hays et al., 1995; Loop et al., 1995; Mazaris et al., 2006; Tiwari et al., 2005; Weishampel et al., 2006) although loggerhead (C. caretta) females with nesting experience have been shown to select a higher proportion of successful nest sites on a beach than unexperienced females (Pfaller et al., 2009). Alteration of nesting dates may mitigate effects of warming temperatures on embryos (Kamel and Mrosovsky, 2004; Mazaris et al., 2008; Morjan, 2003). Shifts in nesting dates and other spring/early summer events have been extensively recorded in Northern Hemisphere birds, butterflies, amphibians and fish (Parmesan, 2007; Root et al., 2003; Rosenzweig et al., 2007). Correlations between peak nesting date and spring (April and May) SSTs were found in populations of loggerheads, C. caretta, nesting at two beaches in Florida, USA (Pike et al., 2006; Weishampel et al., 2004) and at a beach in North Carolina (Hawkes et al., 2007a). Median nesting date on the beaches in Florida has advanced by around 8–10 days over 15 years and appears correlated with warming May SSTs, although these warming trends were apparently not significant (Pike et al., 2006; Weishampel et al., 2004). Earlier nesting with significant increasing SST has been shown in loggerheads, C. caretta, in the Mediterranean, with first nesting emergence advancing by 17 days over 19 years (Mazaris et al., 2008). Egg production may be resource limited in C. caretta (Broderick et al., 2003) which may account for the shorter nesting seasons recorded for this species in warmer years when first laying commences earlier (Pike et al., 2006). Turtles aggregate on breeding grounds before nesting commences for a number of weeks or longer (Fossette et al., 2007; Hays et al., 2002b; Myers and Hays, 2006). Feeding while in these breeding aggregations and during the subsequent inter-nesting phase is at least minimal and may even be absent (Limpus et al., 2001; Tucker and Read, 2001). Nevertheless, temperatures on breeding grounds can directly affect female physiology, for example by increasing metabolic rates (Hamann et al., 2003; Kwan, 1994; Sato et al., 1998). The shorter inter-nesting intervals observed during warmer years are suggestive of increased metabolic rates and may result in shorter nesting seasons for some populations with highly seasonal nesting (Hays et al., 2002a; Mrosovsky et al., 1984; Pike et al., 2006; Sato et al., 1998). However, nesting phenologies are most probably influenced by the geographic position of nesting beaches. At present, turtle nesting sites appear to be constrained by an annual mean surface air temperature of around 25 C in the Southern Hemisphere and around 20 C in the Northern Hemisphere (Fig. 2.4). Nesting in the cooler Northern Hemisphere regions, such as the Mediterranean and Japan, is highly seasonal

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taking place during the summer when seasonal mean surface air temperatures are greater than 25 C and air temperatures are likely to be above the pivotal temperature for balanced sex ratios (29 C) for at least some of this period. For example, in Sarawak, Malaysia (latitude 3 N) where monthly average maximum air temperatures are above 29 C all year, green turtles, C. mydas, nest year round with a peak in July–September. In Cyprus (latitude 35 N) C. mydas nesting is concentrated largely within 4 months (May–August) when monthly average maximum air temperatures reach 24–34 C so even at these cooler, higher latitudes, sex ratios can be female-biased. Data loggers deployed in turtle nests on Cypriot beaches have recorded temperatures that range from 25 to 33 C depending on sand albedo and date of egg-laying with a prevalence at higher temperatures (Godley et al., 2001; Hays et al., 2001a). Populations of turtles breeding at northern hemisphere, higher latitude regions have thus adapted to the strong seasonality in temperatures. Adaptation to strongly seasonal temperature regimes is evident on other life-history stages (discussed further below) of turtles in northern hemisphere waters, with feeding migrations to higher latitudes during warmer months and dormancy as a response to low temperatures recorded for turtles in the Atlantic and Mediterranean. Warming temperatures may lengthen nesting seasons, even if nesting seasons of individuals are shortened due to increased metabolic rates, provided other environmental conditions, such as rainfall intensity, remain favourable. Warming temperatures may also expand availability of favourable breeding habitat for marine turtles (see Fig. 2.4), as beaches outside present-day high-latitude nesting boundaries warm (provided suitable nesting habitat is available). Although turtles show natal fidelity this tends to be to wider regions rather individual beaches within the region. Once a female selects an area during first breeding, she will show strong fidelity to that area, though not necessarily to individual beaches within the area. Turtles nesting on highly dynamic coastlines where beaches and sandbars accrete and erode over short time times (years to decades), such as Suriname, French Guiana and deltas in Myanmar, may regularly shift nesting following natural beach modification or colonise newly formed nesting habitat (Fossette et al., 2008; Kelle et al., 2009; Thorbjarnarson et al., 2000). Further, turtle nesting is sporadically reported, in very low numbers, from beaches where nesting has previously been unrecorded (e.g. Alava et al., 2007; Lima et al., 2003; Tomas et al., 2008) although in some cases this may be due to poor reporting rather than colonisations (Petro et al., 2007). Loggerheads (C. caretta), green turtles (C. mydas) and leatherbacks (D. coriacea), in particular, nest sporadically on beaches at higher latitudes outside major rookeries (e.g. Soto et al., 1997). For example, loggerheads (C. caretta) are recorded nesting regularly in low densities on beaches in southern Queensland and northern New South

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Figure 2.6 Potential changes in turtle nesting populations with warming temperatures over generational time at three latitudes: tropics, sub-tropics and warm temperate, showing trends in nesting females (large turtles) and hatchlings (small turtles). The proportion of male hatchlings (blue) declines as temperatures warm. At the lower latitude (warm-temperate) rookeries, pulses of females (in box) are produced during extreme warm years (shown) while cool years will produce pulses of males (not shown).

Wales, Australia that have been too cool to have produced females within the last 100 years (C.J. Limpus, unpublished data). So how will turtle nesting populations shift with warming temperatures? Two mechanisms may come into play (Fig. 2.6): First, a gradual warming of temperatures may result in the warmest areas becoming all female producing (if not already), with an increased probability of females on previously cool beaches. High temperatures could also increase hatchling mortality (so a slow population decline may occur at the warmest beaches). However, given many turtle populations already operate with female-biased sex ratios, populations may persist in these regions and a gradual expansion of breeding success may occur at cooler distributional edges of the nesting range. Secondly, inter-annual variability in warming temperatures may also produce ‘pulses’ of females on cooler beaches during ‘hot’ years or vice versa.

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4.2.2. Rainfall, storms and cyclones Marine turtles nest on tropical beaches where intense rainfall can occur during summer months, particularly in monsoonal regions, and nesting at many colonies overlaps with tropical storm and cyclone seasons. Timing of nesting is probably determined by climatic pattern of the nesting location, for example whether rainfall is seasonal and predictable or seasonal but unpredictable and heavy (monsoonal rainfall in the wet–dry tropics; see Shine and Brown, 2008) coupled with temperature regimes and other environmental cues. Prolonged rainfall can lower nest temperatures (Houghton et al., 2007) but may also submerge or destroy nests (Foley et al., 2006) and can affect sand stability. At Ascension Island, where the sand tends to be very dry and unstable, therefore unsuitable for digging, nesting occurs during the wettest months (Mortimer and Carr, 1987). In addition, turtle eggs require certain levels of moisture in the sand, depending on species, to avoid desiccation (Bustard and Greenham, 1968; Limpus et al., 2001; Mortimer, 1990). Interestingly, the hydric environment appears to have little influence on the hatching success of flatback, N. depressus, eggs which nests on the generally arid, tropical Australian coastline (Hewavisenthi and Parmenter, 2000, 2001). At immediate timescales, rainfall may directly influence female nesting behaviour. Heavy rainfall may render nest sites unsuitable for digging or egg incubation or may mask cues that trigger female emergence. During intense rainfall events, coastal waters are often turbid and salinity is reduced. Some populations of olive ridley turtles, L. olivacea, display mass nesting events known as ‘arribadas’ when females emerge synchronously to lay eggs. L. olivacea arribadas in Costa Rica have been found to postpone mass nesting during periods of heavy rainfall (Plotkin et al., 1997). In contrast, loggerhead turtles (C. caretta) nesting in Florida, USA, were shown to increase nesting activity during periods of heavy rainfall (Pike, 2008b). The actual benefits occurred by nesting during rainfall periods are unclear and it is likely that there are a number of environmental cues that drive nesting emergence. The destructive effects of storms, cyclones and heavy rainfall are mostly likely to be directly on the nests and eggs (see above) and on beach nesting habitat. Storms and cyclones can be highly destructive causing rapid erosion of beaches and dune systems behind the foreshore and loss of aquatic vegetation or coral reef destruction (Edminston et al., 2008; Thom and Hall, 1991; Woodroffe, 2008). New beach can also be formed during these events (Woodroffe, 2008). Projected increases in severe storms and cyclones and increases in significant wave height are expected to impact sandy beaches globally, particularly when coupled with other anthropogenic influences (Nicholls et al., 2007). For example, coastal development, such as sea walls and dune destruction, can reduce the natural resilience of beach systems to disturbance events (Brown and McLachlan, 2002; Jones et al., 2007;

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Nicholls et al., 2007; Schlacher et al., 2007). Turtle nests on beaches with high coastal development and burgeoning human populations (e.g. Central America: Tomillo et al., 2008; India: Mohanty et al., 2008; Indo-Asia: Hamann et al., 2006) are likely to be most at risk. Remote nesting beaches, such as many of the mainland nesting sites throughout Northern Australia or on south Pacific islands, are likely to be more resilient assuming the integrity of associated ecosystems such as coral reefs and seagrass beds are not impaired. 4.2.3. Sea level Sea-level rise may also be a major threat for turtle breeding beaches, particularly on beaches where coastal development acts as a barrier constraining landward movement of beaches or hindering natural accretion of beach material and the evolution of beach morphology (Fish et al., 2005, 2008; Jones et al., 2007; Nicholls et al., 2007). It is suggested that the dynamics of shoreline systems means the horizontal recession of sandy beaches can be much more rapid (50–100 times) than vertical sea-level rise, although evidence is generally lacking in this area (see Jones et al., 2007; Nicholls et al., 2007). However, there may be little change to beaches, especially those with an extensive dune system, other than a landward migration ( Jones et al., 2007). Sandy beaches are highly dynamic systems undergoing periods of accretion and erosion; however, the majority of the world’s beaches have retreated over the past century (Nicholls et al., 2007). Sea-level rise may not be the primary driver of these retreats as alteration of wind patterns, river inflow and offshore bathymetric changes can cause beach erosion (Nicholls et al., 2007). Turtle nesting beaches in regions with high costal development, whether for industry, coastal defence, habitation or tourism, may be most strongly impacted. For example, a 0.5-m rise in sea level could lead to the loss of 32% of total beach area in the Netherlands Antilles, Caribbean, and 26% of beach area in Barbados with the most vulnerable beaches being those that back onto salt lakes and coastal developments (Fish et al., 2005, 2008). Prohibiting construction within 30–50 m of beaches in Barbados could substantially reduce loss of Hawksbill (E. imbricata) nesting beach area although losses on some beaches may still be severe (Fish et al., 2008). Sea-level rise may result in a reduction or loss of small islands, particularly in the Pacific (Mimura et al., 2007). Interactions with adjoining ecosystems may be particularly important in maintaining resilience of these islands to rising sea levels. For example, the integrity of the surrounding coral reefs is important for the shoreline protection of low-lying islands on coral atolls as the reefs dissipate wave energy, thus helping reduce coastal erosion (Sheppard et al., 2005). Declines in reef health through pollution, eutrophication, over-exploitation and fishing, warming temperatures (coral bleaching) and increasing cyclone intensity, may accelerate coastal erosion

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of small tropical islands (Mimura et al., 2007), thereby impacting turtle breeding beaches. 4.2.4. Large-scale ocean–atmosphere patterns The number of nesting turtles can vary considerably year to year with the largest inter-annual variations generally found in the herbivorous green turtle (C. mydas) populations (Broderick et al., 2001; Limpus et al., 2001). There is evidence of large-scale environmental forcing on numbers of nesting turtles at widely separated rookeries. These may be a reflection of wide-scale ocean–atmosphere forcing such as the ENSO, although the exact mechanisms remain to be determined (Balazs and Chaloupka, 2004; Chaloupka, 2001; Chaloupka and Limpus, 2001; Limpus and Nicholls, 1988; Saba et al., 2007; Solow et al., 2002). An example illustrating this idea is that the numbers of nesting green turtles, C. mydas, at rookeries in the western Pacific have been correlated with ENSO with an 18–24 month lag, with the highest numbers following El Nin˜o events (Chaloupka, 2001; Limpus and Nicholls, 1988). The numbers of turtles breeding each year are likely to be driven by environmental conditions on foraging grounds. Turtles are capital breeders—they deposit fat reserves that can be mobilised later for reproduction (Hamann et al., 2003; Kwan, 1994). Vitellogenesis, the process by which egg yolks are formed, commences at least 8–10 months before the breeding season and can partly explain the lag between environmental signals and breeding numbers (Hamann et al., 2003). The cues to initiate vitellogenesis are unknown but could be environmental such as threshold temperatures or genetic factors such as an energy ‘threshold’ where breeding is initiated only when the turtle has acquired a large enough energy store to sustain itself over the breeding period and breeding migration (Hamann et al., 2003; Hatase and Tsukamoto, 2008). ENSO affects temperature, rainfall and storm patterns over wide Pacific regions but there can be considerable variation in these environmental signals within a region. Further, other large-scale climate modes, such as Indian Ocean Dipole, may dominate signals in some regions. These low frequency climate signals can synchronise breeding of turtles across widely distributed foraging grounds. Females in a nesting area may have migrated from widely spaced foraging areas, which raises questions as to which cues are operating to trigger breeding and how are females responding to these cues (Hamann et al., 2003). Certainly, there is some evidence of differing initiation dates for migration for females from different foraging areas that utilise the same nesting region (Miller and Limpus, 1981). Peak nesting of leatherback, D. coriacea, turtles in Costa Rica has been shown to have a strong ENSO signal suggesting oceanographic conditions on offshore foraging grounds are influencing female nesting (Saba et al., 2007, 2008). Peak nestings were associated with the high surface

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productivity of oceanic, foraging regions that develops during La Nin˜a events and following termination of El Nin˜o events. It has been suggested that recent increases in green turtle, C. mydas, nesting populations in the southern Great Barrier Reef may be attributable to concurrent increases in the frequency of ENSO anomalies (Chaloupka and Limpus, 2001). The breeding season of austral summer 1998/1999 was one of the largest on record (Dethmers et al., 2006; Limpus et al., 2003). This record breeding followed the 1997–1998 ‘super El Nin˜o’, which led to 1998 being the warmest year (between 1856 and 2005) for SSTs (Trenberth et al., 2007). Other biological impacts of this super El Nin˜o included the most severe global episode of mass coral bleaching that has occurred to date (Hoegh-Guldberg, 1999).

4.3. Juveniles and adults foraging in oceanic waters 4.3.1. Ocean temperature Adult turtle distribution throughout the global ocean is generally limited by minimum temperatures around 15–20 C (Coles and Musick, 2000; Davenport, 1997; McMahon and Hays, 2006). Optimal temperature ranges can vary between species, age classes and seasonally. For example, juvenile loggerheads, C. caretta, generally occupy waters ranging from 15 to 25 C while juvenile olive ridleys, L. olivacea, are found in much warmer temperatures of 23–28 C (Polovina et al., 2004b). Large leatherbacks, D. coriacea, show the greatest adaptations for metabolic heat production and retention (Davenport et al., 1990; Frair et al., 1972; Paladino et al., 1990; Wallace and Jones, 2008), and can make seasonal transitory forays into waters below 10 C (Eckert, 2002; James et al., 2006; McMahon and Hays, 2006). Warming ocean temperatures are likely to extend the potential global pelagic habitat of marine turtles further polewards (McMahon and Hays, 2006). For example, satellite tracking of leatherback turtles, D. coriacea, in the North Atlantic suggests that the 15 C SST isotherm may encapsulate the northern boundary of distributions, although they are routinely reported from colder waters (McMahon and Hays, 2006). The mean monthly 15 C SST isotherm has moved 330 km north in the last 17 years (McMahon and Hays, 2006). However, this warming is within variability over the past 150 years, and as such may not be due to global warming per se, but such events are occurring with increasing frequency (Hobson et al., 2008). Warming projected over the coming century is expected to move this contour further northwards thus increasing leatherback, D. coriacea, foraging areas, particularly in the northeast Pacific and northeast Atlantic (Fig. 2.7). It is likely that these isotherms integrate oceanographic and trophic processes, such as the availability of gelatinous zooplankton, that influence movements of D. coriacea (Houghton et al., 2006; Witt et al., 2007b).

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Figure 2.7 Mean sea surface temperature projections for 2001–2010 summers in the Northern hemisphere ( June–August) and in the Southern hemisphere (December– February) from CSIRO Mk 3.5 General Circulation Model (GCM). The position of the 15 C isotherm (black solid line) is indicated, which may effectively encompass the distribution of foraging leatherback, Dermochelys coriacea, turtles. The position of the mean 15 C isotherm (black dotted line) for boreal and austral summers, projected for 2091–2100 under greenhouse gas emission scenario SRES A2, is also shown. Black arrows indicate the general pattern of dispersal away from nesting beaches measured with satellite tags in the North Atlantic, Pacific and Southern Africa and inferred from recaptures of flipper tagged for D. coriacea (indicated by black dots) nesting in West Africa. The movement of D. coriacea nesting in the Andaman Islands (Indian Ocean) is not known. GCM projections downloaded from the IPCC data hosted by PCMDI and processed at CSIRO marine research.

Dense jellyfish aggregations are a natural feature in oceanic ecosystems, but severe blooms are being reported with increasing frequency in recent decades (Richardson et al., 2009). Will climate change therefore be good news for foraging turtles in oceanic waters? The factors driving long-term changes in prey fields, such as gelatinous zooplankton, remain too poorly resolved to address this question. Overfishing (fish are major competitors and predators of jellyfish), eutrophication, habitat modification and climate change may all be regulating jellyfish density (Purcell, 2005; Richardson et al., 2009). For example, there have been reported increases in the abundance of jellyfish in the Benguela upwelling system (Lynam et al., 2006)

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that have been attributed to eutrophication and overfishing although the details of mechanisms remain enigmatic. However, in the North Sea, longterm changes in the abundance of various species of jellyfish have been linked to climatic signals (Lynam et al., 2004). Overall, we are left with the impression that prey abundance is closely linked to the fitness of sea turtles inhabiting oceanic waters and the prey abundance is likely to be heavily shaped by climate change although the specific causes remain obscure (Hays et al., 2004). Strong associations between ocean productivity and associated plankton landscapes and turtle distributions have been suggested (Houghton et al., 2006; Polovina et al., 2001; Witt et al., 2007b). Future alterations of open-ocean prey abundance may be a critical issue for marine turtles, but one that has as yet received very little attention. Warming of the sea surface can enhance stratification of the water column, leading to nutrient-poor waters (potentially favouring jellyfish) and a reduction in productivity (Polovina et al., 2008; Richardson et al., 2009). Over the last half century in the western Pacific, a negative correlation between the slowly increasing mean annual SSTs in the core, foraging areas for loggerhead turtles, C. caretta, and the trend in the size of annual nesting populations during the following respective summers in Japan and eastern Australia has been identified (Chaloupka et al., 2008b). The authors suggested a relationship between warming ocean temperatures and reduced ocean productivity, with the resultant reduction in food supply potentially influencing the annual breeding numbers of Pacific loggerheads, C. caretta, unless they adapted by shifting their foraging habitat to cooler regions. The gradual warming of the Pacific Ocean appears to be a major risk factor for these populations. In the western Atlantic, reported sightings of leatherbacks, D. coriacea, in Canadian waters were found to increase by 12.5% for each degree rise in mean weekly SST, although it was acknowledged that turtles may be responding to seasonal availability of gelatinous zooplankton in these waters rather than directly to temperature ( James et al., 2006). Temperature and declines in prey abundance may also play a role in triggering departures from these grounds, but it is also possible that other factors such as a reduction in feeding efficiency or a threshold for body fat deposition may interact to trigger migrations (Sherrill-Mix et al., 2008). In the North Atlantic, water temperatures play a role in the seasonal movements of turtles to high-latitude foraging grounds (Hawkes et al., 2007a; James et al., 2006; Morreale and Standora, 2005; Morreale et al., 1992; Renaud and Williams, 2005). Warming temperatures may therefore result in increased frequency of leatherbacks, D. coriacea, reported from high-latitude North Atlantic waters and a longer seasonal residence in these waters. For example, most sightings of marine turtles in UK waters, taken from records over the past century, have been recorded in the past

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40 years and sightings are increasing, which is suggestive of a possible shift or expansion in distributions (Robinson et al., 2005). A competing explanation is the hypothesis that increases in turtle populations globally have resulted in a proportional increase in the number of young ‘strays’ (Carr, 1987) and summer migrants carried to British waters by the North Atlantic drift (Witt et al., 2007a). However, increased contemporary sightings of turtles in UK waters may also be an artefact of better reporting and improved public education in recent decades (Robinson et al., 2005; Witt et al., 2007a). 4.3.2. Wind and currents Currents play a number of roles in the distribution of juvenile turtles at sea. They may influence turtle movements through advection, offer a thermal refuge from colder waters and will influence to a large degree the availability of planktonic prey. Ocean circulation patterns may thus help define turtle distributions and deflect turtle movements, particularly those of juvenile turtles (Bowen et al., 2007; Polovina et al., 2006; Revelles et al., 2007a). For example, circulation patterns into and within the Mediterranean Sea are thought to retain immature loggerheads, C. caretta, hatched on Mediterranean beaches until they attain sufficient size and strength to swim against currents and are able to exit into the Atlantic (Revelles et al., 2007a,b). A proportion of green turtles, C. mydas, on foraging grounds in the eastern Caribbean have been shown to originate from Ascension Island rookeries and are probably transported there by the North Atlantic gyre (Luke et al., 2004). Evidence for the influence of ocean circulation patterns on juvenile dispersal and possible fidelity to particular water masses has been shown through genetic and tagging studies (Bass et al., 2006; Carreras et al., 2006; Casale et al., 2007; Luke et al., 2004; Naro-Maciel et al., 2007). Clearly then, straying outside ocean gyre and currents systems can be fatal for young turtles if the temperature difference is large (Carr, 1986, 1987; Lohmann and Lohmann, 1996). Loggerheads (C. caretta) in the North Atlantic have been shown to use the warm waters at the edge of the Gulf Stream as a thermal refuge (Hawkes et al., 2007a). At temperate latitudes, the temperature difference within such currents, which originate in tropical latitudes, and surrounding waters may be large. For example, in southeast Australian waters, the temperature difference between the warm-water East Australian Current (EAC) and surrounding waters may be over 5 C (see Zann, 2000). Juvenile and adult marine turtles seasonally appear in New Zealand waters (34–38 S) and off southeast Australia, either carried or assisted by the poleward extension of the EAC (Gill, 1997; Limpus and McLachlan, 1979; Scott and Mollison, 1956). The numbers of records of turtle mortality in this region have increased in recent decades, with high influx years coinciding with a recent strengthening of the EAC as well as rising ocean temperatures (Cai, 2006; Gill, 1997). The EAC has strengthened driven by

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changes in the circumpolar westerly wind belt due to warming temperatures; the EAC is projected to strengthen by 20% by the 2070s (Cai et al., 2005). This has resulted in a warming of waters off Tasmania, southeast Australia, of 2.28 C in 60 years (Hill et al., 2008). With the strengthening of the EAC, observations of juveniles in New Zealand waters are expected to increase. 4.3.3. Large-scale ocean–atmosphere patterns The large-scale atmospheric patterns such as El Nin˜o influence regional oceanography and productivity. Fluctuations in the abundance of gelatinous zooplankton in regions of the world’s oceans are related to large-scale climate indices such as El Nin˜o and the North Pacific Decadal Oscillation (Anderson and Piatt, 1999; Attrill et al., 2007; Dawson et al., 2001; Purcell, 2005; Raskoff, 2001). How these evolve, as global climate changes, will have repercussions for marine turtle populations globally. 4.3.4. Ocean acidification Ocean acidification will affect the acid–base cellular regulation of marine organisms but as air breathers, marine turtle physiology will be less susceptible to changes in ocean chemistry. The indirect effects of ocean acidification on primary and secondary production may have consequences for marine turtles, particularly if coral reefs decline (see above) or ocean productivity decreases.

4.4. Juveniles and adults on inshore foraging grounds 4.4.1. Ocean temperature Water temperatures in coastal waters tend to be more variable than in openocean waters and strongly seasonal. Foraging turtles are frequently reported from high-latitude, coastal and shelf waters during the summer months (Goff and Lien, 1988; James et al., 2006). Cold stunning of turtles at higher latitudes is a frequent occurrence and, if exposures to low temperatures are prolonged, morbidity and death may occur (Morreale et al., 1992; Still et al., 2005). In partially enclosed seas, such as the Mediterranean (40 N), green turtles, C. mydas, can show periods of ‘dormancy’ rather than migration to tropical waters. During dormancy individuals rest in mid-water or on the bottom (although some level of activity is retained) during periods of low water temperatures (Godley et al., 2002c; Hochscheid et al., 2007). This behaviour appears to be an adaptation of the Mediterranean populations since green turtles, C. mydas, in southeast Australia (30–35 S) do not show dormancy at temperatures similar to the low Mediterranean temperatures. The observed trend to warmer temperatures in the Mediterranean (Bindoff et al., 2007) should reduce the occurrence of dormancy in resident

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turtle populations, thus potentially increasing foraging times and improving resultant body condition. Increased temperatures may also expand the availability of potential turtle coastal foraging habitat polewards and influence food resources. However, turtles show some fidelity to foraging areas, depending on species and population, which may constrain invasion of higher latitude areas as temperatures warm although if foraging regions can no longer support turtle populations then turtles will be driven to locate alternative grounds. 4.4.2. Rainfall, storms and cyclones The increase in tropical, cyclone intensities projected with global warming will impact most heavily on turtles that nest during the storm season or on turtles that forage in shallow coastal habitats such as green turtles. Turtles can survive severe storms and cyclones by reducing time spent at the surface and moving to deeper water (Storch et al., 2006). However, cyclones and large storm surges will cause damage, stress, starvation and death of turtles if foraging grounds are in very shallow areas (Carr, 1987; Limpus and Reed, 1985b). For example, Cyclone Kathy which crossed the Gulf of Carpentaria, Northern Australia in 1984, led to large-scale stranding of 500–1000 adult green turtles, C. mydas, on one section of coastline with a large proportion of these subsequently dying (Limpus and Reed, 1985b). Large storm events can have long-lasting impacts on turtle populations. A 1200 km2 of seagrass beds were destroyed off southern Queensland, Australia in 1992 following two cyclones in quick succession and a major river flood event (Preen et al., 1995). The seagrass die-off was followed some 5 months later with a record number of strandings of dead dugongs, Dugong dugon (large marine herbivores) on the adjacent coastal areas (Preen and Marsh, 1995). During the same period there was an increased number of strandings of dead green turtles, C. mydas, on the adjacent Hervey Bay coast (EPA Marine Wildlife Stranding and Mortality Database, Brisbane, Australia). In western Shoalwater Bay, Australia, following Cyclone Joy in early 1990 which caused similar regional loss of seagrass, it was found the proportion of foraging green turtle (C. mydas) adults that prepared for breeding migrations for the 1991 breeding season was severely depleted and remained below average until 1996 (Limpus et al., 2005). Growth rates of immature C. mydas foraging in the same area were depressed during the same period (Chaloupka et al., 2004). Understanding the impact of climate change in marine turtles in coastal areas will require a more detailed examination of storm and rainfall patterns together with local bathymetry and topography. However, the degree of destruction of coastal marine systems by a cyclone will depend on many factors including cyclone track, topography and coastal hydrodynamics. A severe cyclone may not necessarily be a destructive one for coastal marine systems, particularly for submerged fauna and flora. Seagrass beds appear

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remarkably resilient to storm disturbance as long as the plants are not uprooted or heavily smothered (Carruthers et al., 2002; Cruz-Palacios and van Tussenbroek, 2005; Tilman et al., 1994). For example, Hurricanes Ivan (in 2004) and Katrina (in 2005) were found to have resulted in little loss of seagrass beds in Alabama despite extensive damage on land (Byron and Heck, 2006). However, if damage or destruction does occur, then re-vegetation can take 10 years or more and will have implications for marine herbivores. Storms, cyclones and heavy rainfall events can increase turbidity in coastal waters and can cause rapid drops in salinity affecting the stability of coastal waters. They also wash nutrients from the land which can often lead to harmful algal blooms in coastal waters, particularly in waters which are oligotrophic. For example, higher than average rainfall, coupled with warmer temperatures, may have contributed to a toxic cyanobacterium bloom on an important green turtle, C. mydas, foraging ground in Queensland, Australia (Arthur et al., 2007). The turtles were found to be ingesting the cyanobacterium with potential long-term detrimental effects to their health. Red tides, which are also toxic algal blooms, can develop in coastal and shelf waters following heavy intense rainfall (Lee, 2006; Vargo, 2009). Mass mortalities of marine flora and fauna, including turtles, are often reported from the red tides (e.g. Florida, USA: Gannon et al., 2009; Landsberg et al., 2009; Simon and Dauer, 1972; South Africa: Stephen and Hockey, 2007; Korea: Lee et al., 2007a; Japan: Koizumi et al., 1996). The potential consequences of climate change for harmful algal bloom production and severity are unknown, but it must be assumed the rising CO2 levels and temperatures coupled with alteration of rainfall patterns and expanding human populations (hence increasing likelihood of coastal eutrophication) may lead to more frequent or severe outbreaks of toxic algae. 4.4.3. Sea level Nearshore foraging habitats of marine turtles, such as seagrass beds and coral reefs, may be vulnerable to rising sea levels (Duarte, 2002; Short and Neckles, 1999). Although sea levels are presently rising at 1–2 mm a year, the rise is slow compared to the rates of coral growth (20 cm/year; Done, 2003) and hence is not a major challenge to healthy coral populations. However, additional stressors such as warming temperatures, ocean acidification and pollution may slow coral growth considerably (Hoegh-Guldberg et al., 2007). Benthic marine plants and algae may be more at risk. It is estimated a 50-cm rise in sea level will result in a 30–40% reduction in the growth of the widespread Northern Hemisphere seagrass Zostera marina (Short and Neckles, 1999), which is likely to reduce the area of green turtle, C. mydas, foraging grounds.

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4.4.4. Large-scale ocean–atmosphere patterns Evidence of ENSO influences on green turtle, C. mydas, populations on foraging grounds can be seen in the numbers nesting every year (see above). Increase in ‘El Nin˜o-like’ conditions may enhance seagrass and algal growth in the tropics and sub-tropics with positive consequences for feeding C. mydas. 4.4.5. Ocean acidification Ocean acidification is like to impact two key, coastal, turtle-foraging habitats: coral reefs and seagrasses. The threat of ocean acidification is a major concern for coral reefs globally (Hoegh-Guldberg, 2007; Kleypas et al., 2001). Coral reefs are restricted to high-latitude warm waters which have relatively high aragonite saturation states compared to colder lower latitude waters (Hoegh-Guldberg, 2007; Kleypas et al., 2001). Not only may climate change lead to a net dissolution of coral reefs, but also the potential for poleward expansion of coral reefs with rising temperatures may be restricted to a few hundred kilometres at the most by the lower carbonate saturation levels of seawater at higher latitudes (Kleypas et al., 2001). Furthermore, recent warming of the oceans has led to repeated coral bleaching events, not seen anywhere globally before 1979 (Hoegh-Guldberg, 1999). In Australia, for example, temperature thresholds for coral reef bleaching may be exceeded every year by the middle of this century (Hoegh-Guldberg, 1999). The additional stressor of ocean acidification coupled with warming temperatures may lead to a decline in coral density and diversity globally, associated losses of coral-associated fish and invertebrates and an increase in macroalgal cover (Hoegh-Guldberg et al., 2007). Coral reefs form major coastal foraging grounds for turtles, in particular hawksbills, E. imbricata, and these would be vulnerable if reef systems deteriorated, even though the abundance of hawksbill, E. imbricata, turtles foraging on the rocky reefs of sub-tropical Queensland and northern New South Wales suggests that they are not necessarily limited by coral reef distribution (Speirs, 2002). However, a long-term decline in coral reef habitat will have severe repercussions for many tropical marine ecosystems (Hoegh-Guldberg et al., 2007) including the long-term persistence of hawksbill (E. imbricata) populations. Seagrasses primarily rely on dissolved CO2 and so are photosynthetically inefficient in seawater (Invers et al., 1997; Short and Neckles, 1999). Increased CO2 levels could potentially increase seagrass biomass, providing that optimal temperature regimes exist (Invers et al., 2002; Zimmerman et al., 1997); this response may therefore benefit the herbivorous green turtles, C. mydas. However, seagrass beds are declining globally as a result of other anthropogenic stressors, such as reductions in water quality, which may cancel the climate change benefits to seagrasses (Ferwerda et al., 2007; Waycott et al., 2009).

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4.5. Oceanic migrations Turtles can make long migrations between breeding and foraging areas, depending on species and population (Hays et al., 2002c; James et al., 2005b; Limpus et al., 1983c). The actual strategies used by turtles to navigate during these journeys have been subject of much research and debate. While there is some evidence turtles may use the Earth’s magnetic field to orientate and possibly to navigate (Lohmann, 2007; Lohmann and Lohmann, 1996), and may use currents opportunistically (Luschi et al., 2003), it is still largely unknown how they home precisely to natal and foraging regions (Lohmann et al., 2008). While the mechanisms used during migration remain enigmatic, the return migratory abilities of sea turtles are now fairly well established. For example, both tagging and genetic studies have revealed the ability of turtles to return to breed within natal areas (e.g. Lee et al., 2007b). Furthermore, tracking studies have shown that turtles may undertake long-distance movements during the breeding season, sometimes of several hundred kilometres, and yet return directly to nesting regions (e.g. Georges et al., 2007; Fig. 2.8). These tracking results imply turtles have some geospatial knowledge of their environment. Yet turtles artificially displaced tens or hundreds of kilometres from nesting sites often show searching behaviour and are unable to return directly to their starting point (Luschi et al., 2001). This finding illustrates that active searching may be an integral component of turtle migrations, especially across finer spatial scales, and suggests that even with some climate-induced alterations of homing clues, an active search strategy may still help turtles to find nesting sites (Sims et al., 2008). Set against this backdrop it is particularly difficult to make specific predictions about how climate change might impact migrations.

Figure 2.8

Loggerhead (Caretta caretta) turtle with GPS tag.

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4.5.1. Wind and currents There has been considerable debate on the role that the major ocean currents play in turtle migrations: do turtles use currents opportunistically, do currents represent migration corridors for marine turtles, or are currents a challenge to be overcome by swimming turtles if migrating in a different direction to current flow? The answer may be all of these, depending on species and population. Certainly, the major current systems play a role in linking foraging and nesting areas in turtle populations (Bass et al., 2006). Juveniles and adults may use current flows to facilitate transport, for example, juvenile loggerheads, C. caretta, originating from Japanese populations have been identified from feeding grounds off Baja California, representing a journey that crosses the entire Pacific Ocean, most likely aided by the North Pacific Current (Bowen et al., 1995). Adult loggerheads, C. caretta, have also been tracked using satellite tagging, crossing the Indian Ocean (Luschi et al., 2003) and the Pacific Ocean (Nicols et al., 2000) in the direction of prevailing ocean currents. The increasing use of satellite tagging has revealed turtles do make use ocean currents during their long-distance migrations (Bentivegna et al., 2007; Hays et al., 1999, 2001b, 2002c; Luschi et al., 2003). Long-distance migrations may not rely solely on the directions of these currents. Turtles have also been tracked swimming against prevailing currents suggesting the use of currents may be opportunistic or, at least, not obligate (Bentivegna et al., 2007; Cardona et al., 2005; Luschi et al., 2003; Miller et al., 1998; Polovina et al., 2004a, 2006). Migrations across large expanses of oceans are often direct until coastal waters are reached (Hays et al., 2002c; James et al., 2005b), although currents have been found to deflect turtle migratory paths (Gaspar et al., 2006; Girard et al., 2006). There is evidence of persistent migration corridors for adult turtles that do not necessarily coincide with current flow or other oceanographic features (Hays et al., 2001b; Morreale et al., 1995; Shillinger et al., 2008; Troe¨ng et al., 2005). Disruption or displacement of major ocean current systems could therefore have repercussions for turtle stocks by influencing turtle movements and the impacts may be greatest on juveniles. It is more likely that impacts will manifest through associated changes in ocean productivity.

5. Responses to Past Climate Change The first turtles appear in the fossil record at least 200 million years ago and the turtle lineage (Testudines) probably diverged around this time (Hedges and Poling, 1999; Rieppel and Reisz, 1999). Extant turtles may have arisen some 50–100 million years ago. The most recent period with a

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climate warmer than the present-day climate (2–3 C above pre-industrial temperatures), particularly at mid- and high latitudes, was the middle Pliocene (3 million years ago). Tropical sea surface temperatures and air temperatures were probably little different to present day or slightly warmer (1–4 C) and wetter, whereas high latitudes were significantly warmer (Haywood et al., 2000; Jansen et al., 2007). Sea levels were around 15–25 m higher than present day. Since then, climate has cooled, undergoing a cycle of glacial and interglacial periods with the last glacial maxima (LGM) being 21,000 years ago and a mid-Holocene warm period 6000 years ago. During the last glacial maximum, global temperatures were cooler (5 C) particularly at higher latitudes with extensive ice cover and sea levels were up to 120 m lower. Genetic analysis has revealed that over the past 100 million years the tropics acted as a refuge during glacial cycles for many nesting turtles with sub-division and isolation of populations as sea levels and temperatures altered (Formia et al., 2006; Reece et al., 2005). Nesting turtles were likely to have been continually displaced by cooling periods and changes in sea level, particularly loggerheads, C. caretta, which generally nest at higher latitudes on the sub-tropical and warm-temperate beaches (Bowen and Karl, 2007). Sea levels have been rising since the Last Glacial Maximum (LGM), substantially altering coastal areas and displacing turtle nesting sites. A case study for northern Australia green turtles, C. mydas, provides evidence of past adaptation to climate change by marine turtles (Dethmers et al., 2006). Much of the shelf area off northern Australia would have been exposed 21,000 years ago. Most of the present-day nesting beaches were inaccessible, being far inland (Dethmers et al., 2006; Limpus, 2008), The Gulf of Carpentaria would have been an inland lake until it was flooded when sea levels began to rise 6000–10,000 years ago. A land bridge between Australia and Papua New Guinea would have existed until around 10,000 years ago (450 turtle generations) effectively separating turtle stocks breeding in eastern Australia from those breeding in northern and western Australia, as shown by genetic analysis of green turtles C. mydas (Dethmers et al., 2006). Green turtles, C. mydas, nesting in the Gulf of Carpentaria appear to have invaded from western populations, but have since altered the timing of breeding (from austral summer to the austral winter) to adapt to local temperature regimes. Migration routes have also changed as some green turtle populations in the Gulf of Carpentaria, Northern Australia, migrate between nesting and foraging areas contained entirely within the Gulf representing migratory routes in the order of hundreds of kilometres rather than the thousands of kilometres found in other green turtle (C. mydas) populations (Kennett et al., 2004). Evidence of similar phenological shifts and/or colonisation events are also found in other turtle populations. For example, genetic analysis of green, C. mydas, turtles nesting in the Indian Ocean suggests the turtle

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population nesting at rookeries in the South Mozambique Channel (southwest Indian Ocean) have recently colonised from the Atlantic Ocean around the tip of South Africa (Bourjea et al., 2007). Suitable green turtleforaging habitat occurs close to the tip of South Africa due to warm water flows in this region but no analogous habitat is found along cold-upwelling system that dominates the west coast. The cold South African waters are considered a major geographical barrier for C. mydas dispersal and, prior to the discovery of Atlantic haplotypes in the southern Mozambique Channel populations, no evidence has been found of gene flow between the Indian and Atlantic Oceans over the last 1.5 million years. Further, it is unlikely this colonisation is an ongoing process and the genetic differentiation of the southern Mozambique Channel populations is maintained by the oceanographic currents in this region (Bourjea et al., 2007).

6. Adaptation and Resilience Marine turtles are considered vulnerable to climate change given the strong role temperature plays in all life stages (Davenport, 1997). Much discussion with regard to marine turtles and climate change is centred on the temperature-dependent sex determination of embryos in the nest. Warming expected over the coming century may result in shifts to neat to 100% female-producing beaches for some populations. However, the differences in breeding seasons observed at rookeries within the same genetic stock and recent evidence of some relationships between peak nesting and temperature (Pike et al., 2006; Weishampel et al., 2004) suggests some capacity for adaptation to altered climate by breeding marine turtles. Such responses may not occur at a fast enough rate to keep pace with projected rapid warming over the next 100 years. Loss of suitable nesting sites may be countered by colonisation of new sites as has happened over past, much greater, shifts in sea level and climatic alteration. Fidelity to breeding beaches by turtles may not be as strong as generally supposed. A study of 2891 nesting green turtles, C. mydas, along the Australian east coast, all of which have nested in previous years, revealed 6% changed rookeries (nesting beaches) between nesting seasons, with 1.6% having changed rookeries within a nesting season (Dethmers et al., 2006). Turtles may track changing coastal environments by moving to nearby beaches, as may have happened when the Gulf of Carpentaria flooded (Dethmers et al., 2006). Or events may be long-distance, as in a recent (on an evolutionary scale) colonisation of green turtles, C. mydas, from the Atlantic Ocean into the Indian Ocean via the Cape of Good Hope (Bourjea et al., 2007).

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Many turtle populations have operated with a strong female bias over many decades, if not longer. Thus, some populations may be resilient to warming if female biases remain within or at levels where population success is not impaired. At present, there is little information about the biases that populations can sustain (Hamann et al., 2007). Given the projected warming at turtle rookeries globally, it must be assumed that some populations will be under threat. Resilience of marine turtles to climate change is likely to be compromised by other anthropogenic influences. Development of coastlines may threaten nesting beaches and reproductive success and reduce the availability of alternative breeding areas if current regions become unsuitable. Pollution and eutrophication, in addition to coastal development, is threatening important coastal foraging habitats for turtles worldwide. Around 29% of seagrass beds have disappeared in the last 130 years and rates of decline have accelerated since 1990 (Waycott et al., 2009). Losses are attributed to a loss of water quality from changes in land use and eutrophication, coastal development, invasive species and climate change (Abal and Dennison, 1996; Kirkman, 1997; Ruiz and Romero, 2003; Walker et al., 1999; Waycott et al., 2009). The world has also lost 19% of the original area of coral reefs with a further 20% under serious threat over the next 20–40 years from anthropogenicinduced degradation including climate change (Wilkinson, 2008). Major losses of coral reefs are reported from the occurred in the Caribbean and in the heavily populated regions of Asia. Exploitation and bycatch in other fisheries has seriously reduced marine turtle populations; marine turtles may once have been extremely common in coastal ecosystems until hunting associated with the rise of seafaring reduced numbers relatively rapidly ( Jackson, 1997). Turtles themselves have been the target of major fisheries in the past which have drastically reduced turtle numbers; many populations are still reduced from exploitation over a century ago (Aitken et al., 2001; Daley et al., 2008; Jackson, 1997; Tripathy and Choudbury, 2007) and in some areas, particularly IndoChina, are still exploited. Turtles are also exploited, often illegally, for their eggs and their shells (e.g. Barnett et al., 2004; Hope, 2002; Lagueux and Campbell, 2005). Large numbers of turtles die as the result of being caught as bycatch in pelagic longline and trawl fisheries every year (Ferraroli et al., 2004; Hays et al., 2003b; James et al., 2005a; Kaplan, 2005; Kotas et al., 2004; Lewison and Crowder, 2007). The cumulative effects of other human-induced stressors may seriously reduce the capacity of some turtle populations to cope with the additional stressor of climate change. The widespread and global nature of many of the anthropogenic-induced stressors means that many turtle populations may be threatened at every life stage. Conservation efforts targeting critical life stages or highly threaten populations should increase resilience.

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7. Global Trends The IUCN Red List in 2009 included marine turtles as vulnerable, endangered or critically endangered, with the exception of the flatback, N. depressus, which is data deficient (IUCN, 2009; Seminoff and Shanker, 2008). Many marine turtle populations globally are increasing (although still severely depleted) as the result of conservation efforts resulting in the IUCN listings being contested as misleading (Broderick et al., 2006; Hays, 2004; Seminoff and Shanker, 2008). For example, green turtles, C. mydas, nesting at Ascension Island have increased by an estimated 285% since the 1970s (Broderick et al., 2006). Increases are also reported for C. mydas populations elsewhere (Australia: Chaloupka and Limpus, 2001; Hawaii: Balazs and Chaloupka, 2004; Costa Rica: Bjorndal et al., 1999; Troe¨ng and Rankin, 2005). Similar increases have been recorded for other species. For example, a 10-fold increase in 11 years in nesting activity of olive ridley turtles, L. olivacea, in Brazil has been reported (da Silva et al., 2007). Observations from the US Virgin Islands suggest leatherback populations, D. coriacea, nesting there have been increasing at a rate of around 13% per annum since the 1990s (Dutton et al., 2005), while an recent upward trend has been found in hawksbill, E. imbricata, nesting numbers in Antigua (Richardson et al., 2006).

8. Recommendations Management of marine turtle populations in the face of a rapidly changing climate will require a concerted effort globally, both to reduce the direct impacts of climate change and to increase resilience of turtle populations. Clearly, a beneficial approach to many animal species including turtles would be an international effort to mitigate greenhouse gas emissions. However, while that is being achieved, reducing other stressors should be seen as a priority for helping to increase the resilience of turtle populations. Conservation efforts to date have tended to focus on nesting beaches as these are the most accessible of the turtle habitats and therefore the most cost effective to manage. On a local scale, strategies such as increasing shading to cool nest temperatures, for example, by increasing shoreline vegetative or relocation of eggs, has been used as a management tool, although the costs of large-scale programmes may be prohibitive (Dutton et al., 2005; Hamann et al., 2007; Pfaller et al., 2009; Pike, 2008a). It has been argued that survival to reproductive age of individual hatchlings is extremely low so the likelihood of hatchlings from ‘saved’ nests contributing to the future populations are minimal (Pike, 2008c). This also raises questions about whether such

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strategies interfere with the natural ability of populations to respond to climate variability (Mrosovsky, 2006). Concerns have been raised that egg relocation will distort gene pools by imposing artificial selection on ‘poor’ nesters, if individual females consistently select unfavourable sites and if such traits are heritable (Mrosovsky, 2006; Pike, 2008c). Egg relocation would be a viable conservation strategy for populations with low repeatability in individual selection of nest sites (Pfaller et al., 2009). In this case the ‘doomed nests’ may result from a large percentage of the population so would not distort gene pools. Other strategies have involved ‘head-starting’ turtles where juveniles are raised in hatcheries and released in the wild; however, generally such approaches have not been successful. Options for beach re-nourishment and restoration of low-lying beaches to counteract sand loss due to rising sea levels or storm erosion could also be explored. The success of beach nourishment is currently under discussion with both increases and declines in reproductive output reported (Brock et al., 2009; Fuentes and Hamann, 2009; Pike, 2008c, 2009b). Protection of nesting beaches and protection of nests from land-based predators will increase reproductive successes, while protection of cooler (hence male-producing) beaches, may become critical as temperatures warm. In this context, minor, high-latitude rookeries may become increasingly important. In the open ocean, longline fisheries have received attention as a high source of turtle mortality (Ferraroli et al., 2004; Hays et al., 2003b; James et al., 2005a; Kaplan, 2005; Kotas et al., 2004; Lewison and Crowder, 2007) and efforts to reduce turtle catch in these fisheries should improve the health of turtles stocks globally. The introduction of turtle exclusion devices in trawl fisheries, such as the Northern Prawn Fishery in the Gulf of Carpentaria, Australia or prawn fisheries in the Gulf of Mexico, has greatly reduced turtle bycatch (Brewer et al., 2006; Lewison et al., 2003). Many turtle nesting beaches and foraging grounds are in regions of the world where regulated and unregulated fishing and harvesting are high, both of turtles and of turtle eggs. Conservation programmes within these regions will play an important role in conserving turtle stocks. Strong recoveries of seriously depleted green turtle, C. mydas, populations were found in only a few decades following increases in protection of nesting populations (Chaloupka et al., 2008a). There are many knowledge gaps to be filled before a deeper understanding of turtle population dynamics and life histories will be possible. Advances in genetic approaches are revealing phylogeography of turtle populations worldwide and informing on responses to past climate change which, in turn, will inform us about some of the potential responses of marine turtles to future climate change. Advances in satellite tagging are supplying much needed information on key turtle-foraging regions in the open ocean and turtle migrations, but there is still much to be learnt (Hays,

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2008). Long-term monitoring studies, both at major rookeries and at peripheral nesting beaches, as well as modelling studies, are required to understand how sex ratios respond to a fluctuating environment and how these affect long-term turtle population dynamics. Reproductive studies have tended, for obvious reasons, to concentrate on turtle nesting beaches, but channelling efforts solely on the present-day rookeries ignores the processes driving variability in turtle nesting behaviour and distributions. As research on marine turtles expands, so does our insight into the processes that underlie the initiation of nesting migrations and selection of breeding areas. The paradigm that turtles return to their natal beach to nest has been replaced by a view that turtles return to a natal region as evidence arises of variability in beach selection between years and between individuals in the same breeding stock. This view may alter further as our marine turtle data sets lengthen to encompass multi-generational observations. We recommend that investigation of knowledge gaps of the processes driving breeding site selection is critical for adaptive management decisions in the face of a changing climate.

ACKNOWLEDGEMENTS We would like to thank David Sims and an anonymous referee whose comments have helped to improve this manuscript.

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Effects of Climate Change and Commercial Fishing on Atlantic Cod Gadus morhua Nova Mieszkowska,* Martin J. Genner,*,† Stephen J. Hawkins,*,‡ and David W. Sims*,§ Contents 1. Introduction 1.1. Basic biology and global distribution 1.2. Genetic population structure 1.3. Traits in different stocks 1.4. Movement and activity 2. Impacts of Climate Change 2.1. Biogeographic changes 2.2. Physiology 2.3. Metabolic scope for activity 2.4. Maturation and spawning 2.5. Early life stages 2.6. Recruitment 2.7. Growth 3. Impacts of Fishing 3.1. Northwest Atlantic stocks 3.2. Northeast Atlantic stocks 3.3. The fishing versus climate change debate 4. Population-Level Impacts of Fishing and Climate Change 4.1. Stock assessment 4.2. Stock evaluation—An example from the North Sea 4.3. Allee effects and management plans 5. Monitoring Status and Recovery of North Sea Cod: A Case Study

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* Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom { School of Biological Sciences, University of Bristol, Bristol BS8 1UG, United Kingdom { College of Natural Sciences, Memorial Building, Bangor University, Gwynedd LL57 2UW, United Kingdom } Marine Biology and Ecology Research Centre, School of Biological Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, United Kingdom Advances in Marine Biology, Volume 56 ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56003-8

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Abstract During the course of the last century, populations of Atlantic cod Gadus morhua L. have undergone dramatic declines in abundance across their biogeographic range, leading to debate about the relative roles of climatic warming and overfishing in driving these changes. In this chapter, we describe the geographic distributions of this important predator of North Atlantic ecosystems and document extensive evidence for limitations of spatial movement and local adaptation from population genetic markers and electronic tagging. Taken together, this evidence demonstrates that knowledge of spatial population ecology is critical for evaluating the effects of climate change and commercial harvesting. To explore the possible effects of climate change on cod, we first describe thermal influences on individual physiology, growth, activity and maturation. We then evaluate evidence that temperature has influenced population-level processes including direct effects on recruitment through enhanced growth and activity, and indirect effects through changes to larval food resources. Although thermal regimes clearly define the biogeographic range of the species, and strongly influence many aspects of cod biology, the evidence that population declines across the North Atlantic are strongly linked to fishing activity is now overwhelming. Although there is considerable concern about low spawning stock biomasses, high levels of fishing activity continues in many areas. Even with reduced fishing effort, the potential for recovery from low abundance may be compromised by unfavourable climate and Allee effects. Current stock assessment and management approaches are reviewed, alongside newly advocated methods for monitoring stock status and recovery. However, it remains uncertain whether the rebuilding of cod to historic population sizes and demographic structures will be possible in a warmer North Atlantic.

1. Introduction Atlantic cod Gadus morhua Linnaeus, 1758 is one of the most widely studied marine fishes (Fig. 3.1). The species is a major predator in North Atlantic ecosystems as well as being a prey item for larger fishes and piscivorous marine mammals. It has been exploited as a human food resource for over 1000 years and forms a key component of major fisheries throughout the North Atlantic. Its pivotal ecological role, together with its economic importance, has made it a model system for study among marine fishes. Studies range from individual physiology, to population ecology, community interactions and responses to environmental change, including climate change and fishing. Here, we review these studies and discuss how key aspects of cod

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Figure 3.1 Atlantic cod, Gadus morhua Linnaeus 1758. Photograph courtesy of the Marine Biological Association of the UK.

biology are likely to be influenced by changing environments, such as those associated with changes in fishing pressure and climate. We examine the impacts of these drivers on the current status and potential for future recovery of stocks, with a focus on the North Sea and evaluate potential management strategies to reverse the current global decline in Atlantic cod.

1.1. Basic biology and global distribution Atlantic cod is an apex predator of North Atlantic continental shelf waters. It feeds mainly on invertebrates and fish. It grows to a maximum of 2 m in total length, weighs up to 96 kg, matures at between 2 and 4 years of age (O’Brien et al., 1993) and can live for up to 25 years. Females are typically highly fecund, producing an average of 1 million eggs per individual (Cohen et al., 1990). Spawning takes place between December and June depending on geographic location, and eggs hatch 2–3 weeks later. The pelagic larvae feed on zooplankton for approximately 2 months before settling on demersal nursery grounds. The biogeographic range of cod, like many marine fish species, is primarily governed by temperature (Coutant, 1987; Sundby, 2000). In the North Atlantic Ocean, it is found between 40 and 80 N over a temperature gradient of 1 to 20 C. Northern limits occur in Canada and Iceland, and southern limits are reached around New England in the western Atlantic, and in the Celtic Sea–English Channel in the eastern Atlantic (Fig. 3.2). Key areas of population abundance are Labrador, Newfoundland, southern Greenland, Iceland, the North Sea, the Baltic Sea and the Barents Sea (Bigg et al., 2008; Sundby, 2000). Its depth range extends from shallow waters to 200 m, although it has been recorded at depths of over 500 m (Cohen et al., 1990).

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Figure 3.2 The distribution of Atlantic cod in the North Atlantic Ocean (grey shaded area).

1.2. Genetic population structure Cod live in a diverse and complex marine landscape with contrasting water temperatures, depths, salinities, substrates and prey availability. In many marine species, habitat discontinuities can act as barriers to gene flow by restricting movement of adults or larvae (Hauser and Carvalho, 2008). Genetic differences between populations can be further promoted by behavioural traits, such as adult philopatry, population-specific migratory behaviour or kin aggregation (Pardini et al., 2001). The formation of genetic substructure will, however, be counteracted to some extent by the capability that adult fishes have to range over long stretches of coastline and open water, and the pelagic dispersal of eggs and larvae (Hauser and Carvalho, 2008). Identification of geographic and behavioural barriers to gene flow is critical for stock identification and management. Cod are very patchily distributed across their range (7300 km), and molecular markers have helped to reveal the extent of migration among populations. Several studies have revealed a broad spatial trend of isolation-by-distance across the North Atlantic. In mitochondrial DNA, despite an apparent lack of nucleotide diversity (Arnason and Palsson, 1996), there are large differences in the frequency of common haplotypes (Arnason, 2004; Carr and Crutcher, 1998). Similar patterns have been revealed using restriction fragments of nuclear genes (Pogson et al., 1995, 2001), and nuclear microsatellite markers (Hutchinson et al., 2001; O’Leary et al., 2007; Pampoulie et al., 2008; Skarstein et al., 2007). The extent of population differences in microsatellite allele frequencies are such that cod can be reliably assigned to the Baltic Sea, North Sea and the Northeastern Arctic Ocean on the basis of their genotypes alone (Nielsen et al., 2001).

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1.2.1. Cod population persistence Nearly all studies making temporal comparisons of cod population structure using archived genetic material have found remarkable stability (Imsland et al., 2004; Jonsdottir et al., 1999, 2001; Lage et al., 2004; Nielsen et al., 2001; Pampoulie et al., 2008). A major change in genetic diversity was, however, found in the heavily fished Flamborough Head population in the North Sea between 1954 and 1970. After the decline observed over this period, diversity subsequently increased, and this has been linked to the incursion of new genotypes as new colonists had proportionally greater reproductive success (Hutchinson et al., 2003). The general natural stability of cod populations, however, implies that the present distribution of genetic diversity has changed little over recent time. Bigg et al. (2008) concluded the present distribution of cod dates back more than 100,000 years, but by contrast, using more rapidly evolving microsatellite markers, Pampoulie et al. (2008) calculated the time scale of divergence dates more closely to that of the Last Glacial Maximum, approximately 20,000 years ago. Although the accuracy of these time scales will depend on methods used to calibrate evolutionary rates, together these results suggest that the larger scale distribution of genetic diversity pre-dates the last northern hemisphere glacial cycle. 1.2.2. Regional patterns of genetic diversity Using microsatellite DNA markers, patterns of isolation-by-distance have been revealed over spatial scales of approximately 1000–2000 km (Beacham et al., 2002; O’Leary et al., 2007). At smaller scales (<1000 km), however, the extent of stock structure appears closely linked to environmental parameters and behavioural differences. For example, genetic structure within the Northwest Atlantic has been linked to habitat discontinuities, such as channels and trenches. Lage et al. (2004) found cod on the southern Nantucket shoals to be genetically distinct from those on the neighbouring more northerly offshore Browns Bank and Georges Bank, but there were no genetic differences apparent between Browns Bank and Georges Bank, despite these being separated by a stretch of deep water that likely acts as a barrier to movement of adult cod (Lage et al., 2004). Here, it is likely that a gyre system leads to retention of eggs and larvae on the two offshore banks, but those spawned on the Nantucket shoals do not enter this gyre and are either retained locally, or are transported southwest. This evidence is compatible with both larval dispersal and adult habitat fidelity-determining spatial patterns of genetic diversity (Ruzzante et al., 1998, 1999). There are several other examples where substantial genetic differences have been identified within regions. Populations in the Canadian Arctic saltwater lakes at the extreme northwest of the species range are strongly genetically differentiated from Atlantic populations, and show much lower

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genetic diversity (Hardie et al., 2006). This evidence is consistent with a long period of genetic isolation linked to a habitat barrier. Similarly, strong patterns of genetic differences have been found between populations in the North Sea and the Baltic Sea (Nielsen et al., 2003). In this case, a zone of admixture is flanked at each side by non-admixed populations (Nielsen et al., 2003, 2006); this pattern is associated with local adaptation for differing salinity regimes. Such extreme population structuring is not always common within regions, and weak genetic structuring, or genetic homogeneity, are more typical results of studies employing neutral markers at spatial scales around 1000–2000 km (e.g. Beacham et al., 2002). In some cases, genetic differences between populations have been recovered, but they are not always directly correlated with known environmental conditions or geographic distances. On the northern coast of Norway, for example, coastal cod have clear spatial genetic structure, but no evidence of isolation-by-distance ( Jorde et al., 2007). In this case, it would appear that gradual adult or larval dispersal is unlikely, and instead spatial structure has formed through sporadic colonization waves of genetically similar individuals. The existence of co-occurring populations that are genetically segregated has also become apparent. In Norway, there are differences in otolith shapes between the Arctic offshore cod that overwinter in the warmer, deeper waters, and the coastal inshore cod that overwinter in the cooler, shallower water, and early genetic work found that these offshore and inshore cod possessed adaptive differences in their haemoglobin HBI allele frequency (Mller, 1966). In the North Sea–Skagerrak area there is also evidence that the migratory-offshore North Sea stock and the non-migratory-coastal Skagerrak stock are genetically different, but similarly co-occur within inshore waters (Case et al., 2005). Genetically different offshore migratory and inshore overwintering cod are also present in Newfoundland (Ruzzante et al., 1996a,b), and have been found to differ in their blood ‘antifreeze’ protein levels, with the inshore cod that experience the cooler winter temperatures possessing higher antifreeze protein concentrations. These genetic differences appear to exhibit interannual stability (Ruzzante et al., 1997, 2000).

1.3. Traits in different stocks There is an increasing body of evidence suggesting that genetically different cod stocks differ in adaptive life history traits. In the Skagerrak, where population structure is apparent at a scale of less than 100 km, there is apparent spatial variability in traits, such as juvenile growth rate that corresponds with observed genetic variation (Olsen et al., 2008). In support of an evolutionary explanation for the observed pattern, a range of molecular and breeding studies have revealed evidence for selection on functional genes.

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Several genes show variation at the stock level (Hutchinson, 2008), perhaps the most studied gene in this context is pantophysin (PanI) (Pogson et al., 2001), formerly synaptophysin (Syp I) (Fevolden and Pogson, 1997). Particular life history traits have been associated with this gene, for example, differences in mean weight, length and growth rates have been shown to be dependent on the PanI genotype around Iceland ( Jonsdottir et al., 2002, 2003), and temperature and salinity have been shown to influence the PanI genotype frequency in the Northeast Atlantic (Case et al., 2005). These field results have been supported by ‘common garden’ experiments showing PanI-dependent differences in growth rate and condition factor of individuals reared to 10 weeks. Although these results may be due to genes linked to the PanI (Case et al., 2006), the pattern nevertheless suggests that strong local adaptation of stocks is present in the natural environment.

1.4. Movement and activity The movement and activity patterns of predatory fish such as Atlantic cod can be considered a major driver of the spatio-temporal dynamics of populations and communities within ecosystems. Movements such as migration, dispersal and regional philopatry, when played out over longer temporal scales, not only contribute to observed patterns of population sub-structuring and connectivity, but will also determine how population distribution responds to drivers of climatic change or fishing pressure. Monitoring movements of cod in relation to environment is therefore relevant to understanding the effects of these drivers on cod population re-distributions, with a significant role in future adaptive management regimes. 1.4.1. Adult movements Early mark-recapture studies, fishery surveys and fishing reports informed a general picture of mature cod annual movements, with migration to spawning grounds followed by spent cod returning to their feeding grounds after spawning (Harden Jones, 1968). Although this general model is broadly applicable to cod, the emerging paradigm is that their movements by geographic location and by season are complex, with marked differences in behaviour even within a region such as the North Sea, for example (Hobson et al., 2007). The recent advances in remote telemetry technology for tracking fish, particularly the miniaturization of data-loggers, has enabled these insights (Arnold and Dewar 2001; Sims, 2008) with adult cod movements and activity being recorded over long time periods (>1 year) in nearly all the main regions within its geographic range (Clark and Green, 1990; Cote et al., 2003; Metcalfe, 2006; Neat and Righton, 2006; Neat et al., 2006; Rillahan et al., 2009; Robichaud and Rose, 2001, 2002, 2003, 2004; Steinhausen et al., 2006; Wright et al., 2006). Data-logging storage tags have been attached to cod and used to obtain regionally explicit,

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individual-based data on horizontal and vertical movements and thermal habitat. These studies support the contention that there is not a single paradigm of extended movement between spawning and foraging areas, as generally supposed previously (e.g. Harden Jones, 1968), but rather that such movements vary from individual to individual and from sub-stock to sub-stock (Hobson et al., 2009). Behavioural plasticity is evident for cod in the extent and timing of migration, in the persistence of spawning or feeding site fidelity (philopatry), and also in relation to the types of behaviour displayed on feeding grounds and where and when they occur in the water column compared with remaining close to the seabed (Hobson et al., 2007, 2009; Neat et al., 2006; Palsson and Thorsteinsson, 2003; Righton et al., 2001). Residence and homing behaviour have been shown to be important features of Atlantic cod behaviour (Hobson et al., 2009). Cod are known to aggregate seasonally to spawn and to feed at particular geographic locations (Metcalfe, 2006). For example, spawning area fidelity shown by aggregations representing more or less distinct groups of fish is a behavioural trait supported by at least some evidence from genetic and mark-recapture studies (Metcalfe, 2006). However, the degree to which residence and homing applies to different populations and to sub-stocks has been found to vary greatly depending on geographic location. Robichaud and Rose (2004) proposed four categories of populations of Atlantic cod based on the degree of migration and philopatry. The latter authors identified ‘sedentary residents’ that exhibit site fidelity year round, ‘accurate homers’ that return to spawn in a specific area, ‘inaccurate homers’ that home to a much broader area around the original tagging location in the following years, and ‘dispersers’ that move and spawn in a more irregular pattern within large geographical areas (Metcalfe, 2006). It seems coastal areas support resident populations more commonly, such as those in the Norwegian fjords, the Icelandic coast and the Canadian east coast (Metcalfe, 2006), whereas the Northeast Atlantic has large subpopulations that home with accuracy compared with the Northwest Atlantic that has more inaccurate homers and dispersers (Metcalfe, 2006; Robichaud and Rose, 2004). Nested within this larger scale complexity, are the variations in individual patterns observed within a region and which exemplify the problem with broad categorisation of cod behaviour. Comprehensive studies of cod movements in the Northeast Atlantic have deployed over 3000 electronic tags in the Barents Sea, the North Sea, the Baltic Sea and on the Icelandic and Faroe Plateau between 2002 and 2005, with over 850 tags returned by fishermen, giving more than 130,000 days of data (www.codyssey.co.uk). In the North Sea, for example, it is possible to link horizontal with vertical movement patterns. For individual tracks ranging in duration from 40 to 468 days, cod showed horizontal movements up to 455 km, however, individuals did not always show signs

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of migration during winter months, even displaying continuous localised residence for up to 360 days (Hobson et al., 2009). This indicates that cod do not always migrate between feeding and spawning grounds. Vertical movements showed even greater flexibility, with a variety of movement patterns seen within both periods of residence and directed horizontal movement. Close association with the seabed was seen during both directed horizontal movements and residency, while midwater oscillations in swimming depth were also evident during both horizontal movement types. Therefore, vertical patterns in activity alone could not be used to reliably define periods of migration or localised residence (Hobson et al., 2009). Taken together, the results from studies that have tracked large numbers of individual cod for long periods suggest that Atlantic cod behaviour is mediated by complex interactions between biological and ecological factors that result in diverse movements and activities in relation to changing environment (Hobson et al., 2009; Righton et al., 2001). 1.4.2. Cod thermal habits Electronic tagging data show that cod occupy depths from 10 to 860 m, and water temperatures of 1.5 C in polar fronts off Iceland and in the Barents Sea, to 21 C when resting on the seabed in the southern North Sea. In terms of cod distributional responses to thermal habitat, such studies report, for example, that northern North Sea populations above 57 N do not intermix with southern populations below 56 N (Neat and Righton, 2007), thus concurring with previous mark-recapture programmes (Righton et al., 2007; Robichaud and Rose, 2004; Wright et al., 2006) and genetic studies (Hutchinson et al., 2001). Within the northern North Sea, west Shetland is the warmest and least variable region (<3 C variation) and no cod movement from here to cooler waters has been recorded. By contrast, cod released back into the east Shetland and Viking Bank populations moved rapidly into cold fronts and prolonged occupancy of cooler waters was recorded (Neat and Righton, 2007). Within the southern sector of the North Sea, the German Bight population experiences a highly variable thermal environment, with intra-annual variation of 14 C. The greatest acute fluctuations recorded comprised a 7 C decrease over 3 days, and a 7 C increase over a 2-day period. Individuals from this region, and the neighbouring eastern English Channel mostly migrated only short distances, or remained resident, despite experiencing water temperatures up to 19 C during late summer and autumn (Neat et al., 2006; Righton et al., 2001). Notably, adult cod only commenced vertical migration in October–November once surface temperatures began to decline (Righton et al., 2001), and during this period some mature individuals have been recorded migrating to spawning grounds in the eastern English Channel and Southern Bight (Daan, 1978).

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Given the complex behaviour of cod, and in relation to thermal changes and other biological and physical factors operating across the broad range of temperatures in which it is found, predicting how individual cod will respond to climate-driven changes in sea temperature, for example, remains challenging. 1.4.3. Larval dispersal Genetic evidence for reproductively isolated stocks that co-occur on grounds during non-breeding periods, but that often segregate during spawning seasons, demonstrates the importance of knowledge of spawning and nursery habitats for appropriate management. Tests of population genetic differences using adult individuals have informed us about the general patterns of spatial and temporal stock structure, but such studies convey little about the relative importance of spawning grounds within spatial management units. Traditionally, ichthyoplankton surveys and visual identification of larval species identity have been used for identification of spawning grounds. Indeed, this approach has allowed broad-scale mapping across its range of cod spawning areas and the general pattern of egg and larval transport (Brander, 1997). Eggs and larvae, however, can be difficult to separate visually from those co-occurring gadoids such as whiting (Merlangius merlangus) and haddock (Melanogrammus aeglefinus) (Fox et al., 2005). Recent developments in molecular genetic techniques have enabled reliable identification of cod eggs, revealing, for example, considerable overestimation of cod abundance in the Irish Sea (Fox et al., 2005; Taylor et al., 2002). This approach has also allowed the identification of active spawning grounds in the North Sea (Fox et al., 2008). Importantly, these locations, including the Dogger Bank, German Bight and Moray Firth show close corroboration with spawning areas inferred from historical survey data, implying cod have well-defined, active spawning grounds that have been used by multiple generations. However, to date there is very little available information on the extent of larval dispersal or retention in relation to these spawning grounds, or the cues employed for location and settlement on nursery grounds. Hydrodynamic models coupled with in situ ichthyoplankton surveys for model verification offer considerable promise for revealing mechanisms of larval dispersal or retention over large spatial scales (van der Molen et al., 2007).

2. Impacts of Climate Change Global climate has warmed to temperatures unprecedented over the last 1300 years. Anthropogenic inputs into the atmosphere are now recognised as the primary driver (IPCC, 2007). The latest model predictions indicate that global mean surface temperature will increase by a further

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1.1–2.9 C (low emissions B1 scenario), or 2.4–6.4 C (high emissions A1FI scenario) (IPCC, 2007). Climatic warming has been observed in marine environments across the North Atlantic, and appears to be of a greater magnitude and duration than any periods in recent history (Fig. 3.3) (IPCC, 2001, 2007; Southward, 1963; Southward and Boalch, 1994; Southward et al., 1988). Marine ecosystems are already responding to these changes in sea temperature, through polewards shifts in biogeographic ranges (Beaugrand et al., 2002; Berge et al., 2005; Griffiths, 2003; Hellberg et al., 2001; Mieszkowska et al., 2006, 2007; Zacherl et al., 2003), phenological changes (Genner et al., 2009a; Sims et al., 2001, 2004), and through alterations in the relative abundance of ectothermic species and the structuring of the communities they comprise (Barry et al., 1995; Berge et al., 2005; Genner et al., 2004, 2009b; Hellberg et al., 2001; Mieszkowska et al., 2006; Sagarin et al., 1999; Southward, 1995; Southward et al., 1988). Furthermore, there is burgeoning evidence for climate-driven effects on marine fishes (Graham and Harrod, 2009). In this section, we explore the role of climate drivers on the biology and ecology of Atlantic cod and, in addition to description and discussion of the known or potential biological impacts, we identify knowledge gaps where new studies will progress our understanding towards prediction of cod responses to changing environments.

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2.1. Biogeographic changes Distributional limits of marine fish species are governed to a large extent by regional thermal regimes. The observed thermal occupancy or ‘climate envelope’ of species is the basis for many models that attempt to predict future abundance and distributions (Pearson and Dawson, 2003; Walther et al., 2002, 2005). Where environmental conditions change to fall within the physiological tolerance limits of a species, range extensions are predicted as fish are able to colonize new areas of suitable habitat. In practice, however, the range edge may lie some distance inside this fundamental niche envelope. This is because population distributions are often influenced by additional environmental parameters and biological interactions such as competition, predation and prey availability, parasitism and other factors such as habitat availability and dispersal ability (Brett and Groves, 1979; Davis et al., 1997; Kelsch and Neill, 1990). There is still no general model to describe how thermal physiology of ectotherms and climate interact to determine biogeography (Chown and Gaston, 1999; Clarke, 2003). Clearly, development of such models is a significant challenge for understanding and predicting the macroecological responses of fish species. Data from commercial fishing and research vessel surveys have been used to explore how the biogeography of cod has changed (Blanchard et al., 2005; Daan, 1994). However, use of abundance data from trawl surveys can be insensitive to short-term individual variations in distribution (Neat and Righton, 2006) which can make range assessments for spatially structured stocks problematic (Hutchinson et al., 2001; Metcalfe, 2006; Wright et al., 2006). Both migratory behaviour and density-dependent effects linked to prey abundance can affect geographic distributions (Beaugrand et al., 2003; Blanchard et al., 2003; Moyle and Cech, 2004; Roessig et al., 2004; Swain, 1999; Swain et al., 2003). Moreover, other environmental variables such as salinity, storminess, cloud cover and precipitation can strongly influence the distribution and productivity of marine ecosystems (Bakun, 1996; Stenseth et al., 2004) and the phenology of production cycles (Edwards and Richardson, 2004). The stochastic nature of these parameters is reflected in the annual fluctuations in abundance of cod across its range. Despite the large diversity of factors that can influence distributions, there is compelling evidence that populations have shown responses to climate-related thermal changes during the twentieth century. The North Atlantic warmed at the basin-scale during the 1920s and 1930s, and during this warm period the distributional limits of cod were observed to extend some 1200 km further north from southern Greenland to Disko Island (northwest Greenland), while the Barents Sea population apparently shifted eastwards ( Hansen, 1949; Jensen and Hansen, 1931). Similarly, Icelandic cod were restricted to spawning on southern shelf regions until the 1920s, but afterwards spread to the northern shelf (Sæmundsson, 1934;

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Vilhjalmsson, 1997). During a cool period during the 1960 and 1970s, these changes were seen to reverse. Cod evidently retracted further south in the colder conditions and disappeared entirely from coastal waters around Disko Island (Buch and Hansen, 1988). Furthermore, the population spawning on the northern Icelandic shelf declined to minimal levels during this period, presumably due to a shift in abundance centred further south. During the late 1980s and early 1990s, cooler waters were also present in the Northwest Atlantic from the Labrador Shelf to the Grand Banks, leading to a sudden decline in cod abundance (Atkinson et al., 1997; de Young and Rose, 1993; Drinkwater, 2002; Rose et al., 1994, 2000; Taggart et al., 1993). Whilst fishing activity may also have played a role in establishing this pattern (Hutchings, 1996; Hutchings and Myers, 1994b; Myers et al., 1996), analyses of blood chemistry (Rose et al., 2000) and genetics (Ruzzante et al., 2001) also support a biogeographic shift of Northwest Atlantic stocks to lower latitudes at this time. Apparent northward shifts of both the centre of distribution and the southern range limit of cod in the southern North Sea in recent years are possibly a direct response of individuals to increased seawater temperature over the last decade (Hedger et al., 2004; Perry et al., 2005; Rindorf and Lewy, 2006). However, there is no direct evidence to suggest that fish have actively moved to avoid increasing temperatures (Rindorf and Lewy, 2006). Studies supporting a northward shift in cod have based analyses on the assumption that there is single population in the North Sea that is most abundant at the range centre, and has decreasing numbers of individuals towards range limits. For species that are more or less in a steady state, and are not changing in abundance or distribution rapidly, this pattern can be broadly accepted. By contrast, where a single dimension of the niche changes rapidly, and where there is evidence of population subdivision and local adaptation, responses may not be straightforward. This may be the case in the North Sea given some evidence that several discrete stocks are present (Hutchinson et al., 2001; Metcalfe, 2006; Wright et al., 2006), and which appear to have distinct habitat preferences during different life history stages (Righton et al., 2007; Robichaud and Rose, 2004; Wright et al., 2006). An additional consideration is that individual cod can move large distances or remain resident, and behaviour shows great flexibility across multiple spatio-temporal scales, resulting in complex spatial dynamics (see Section 1.4.1). Thus, there may not necessarily be a long-term location for occupation of the most suitable environmental conditions where the highest abundance of fish can be found. The case of the North Sea is further complicated by a seasonal inversion of the latitudinal temperature gradient, with the southern North Sea being colder in the winter but warmer in the summer than the northern North Sea. Furthermore, analysis of North Sea research survey data suggests that cod have responded to a winter bottom temperature increase of 1.6 C over 25 years by moving into deeper water at

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an average rate of about 7 m per decade (Dulvy et al., 2008). Together, this evidence suggests that climate-driven changes to cod distributions may be more complex than predicted using straightforward ‘climate envelope’ approaches. Observed northward shifts of the southern range limits could also be attributed to local population abundance changes due to fishing pressure, variation in migration between populations (Hedger et al., 2004) or spatial differences in the thermal tolerance limits of adult cod leading to local depletion of stocks (Neat and Righton, 2006; Po¨rtner et al., 2008). The lack of concordant responses to thermal regimes shown by individual cod is consistent with temperature being only one of the factors determining habitat choice (Neat and Righton, 2006). Occupancy of space by cod in historical habitats has declined from 90% to lower than 50% over the last 30 years, and spatial distributions have become increasingly characterized by aggregations in areas of optimal thermal habitat (Blanchard et al., 2005; Horwood et al., 2006; Marshall and Frank, 1994; Myers and Stokes, 1989; Rose and Kulka, 1999). These studies support earlier observations of density-dependent habitat selection in cod (Myers and Stokes, 1989; Swain and Sinclair, 1994), and strongly suggest changing distributions may additionally be linked to aggregation behaviour.

2.2. Physiology Most fish are ectotherms with limited capacity for internal heat regulation (Clarke, 1993). To predict how changes in global climate will affect fish distributions, it is important to know how physiological functions are influenced by temperature variation, and to quantify thermal tolerance thresholds (Guderley, 1990; Po¨rtner, 2001, 2002; Po¨rtner and Knust, 2007; Po¨rtner et al., 2001). This individual-level physiological response extrapolates to population, community and ecosystem-level responses (Roessig et al., 2004). Although temperature is recognised as an important controlling factor for biotic processes, from cellular to ecological levels of organisation (Fry, 1971), defining thermal optima is a complex process due to differential effects of temperature on various physiological processes, and on different life history stages. For example, larval fish drifting passively within the plankton may be more vulnerable than juvenile or adult fish that can actively move away from unfavourable conditions. Moreover, different stocks have also been observed to show local adaptation to differing thermal ranges (Coutant, 1977, 1987; Daan, 1994; Scott, 1982). 2.2.1. Tolerance limits and thermal preferences Both adult and larval cod can tolerate salinities from almost 0% to 35%, but exhibit some preference for 30–35%. They also have a wide thermal tolerance, and have been recorded in waters ranging from 1.5 to 21 C,

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although their temperature range is typically between 0 and 12 C (Tremble and Sinclair, 1985; Wise, 1961). Despite this apparent broad tolerance, they are highly sensitive to even slight water temperature variation of 0.3 C, and individuals seemingly alter their position in the water column to maintain themselves near their temperature for optimal performance, Topt (Fig. 3.4) (Herbert and Steffensen, 2005; Rose et al., 1994). Body temperature has a significant effect on fitness of cod (Fry, 1947; Huey and Berrigan, 2001), so Topt is expected to correspond to the temperature of maximum fitness, Trmax (Beamish, 1978; Schurmann and Steffensen, 1997). Temperaturefitness curves are asymmetric, however, and therefore body temperatures greater than Tmax can lead to stress and rapid fitness decline (Martin and Huey, 2008). The proximity of stressful temperatures to Trmax can result in Topt being lower than Trmax in natural, thermally variable environments. This may have important implications for predicting physiological fitness in response to future climate warming scenarios. 2.2.2. Sublethal physiological thresholds It may not always be possible for a fish to occupy a thermal environment matching the temperature of optimal performance, and thermal stress may result from exposure to unfavourable temperatures. The first symptoms of thermal stress are caused by the limited capacity of respiratory systems to provide sufficient oxygen to body tissue above the pejus temperature Tp (pejus, meaning getting worse, deleterious) (Frederich and Po¨rtner, 2000; Po¨rtner, 2001; Po¨rtner et al., 2001). This is the threshold beyond which the cardiorespiratory system cannot increase aerobic metabolism and body 25 Tcrit range adult cod

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Figure 3.4 A schematic diagram of the thermal physiological thresholds of Atlantic cod. See Sections 2.2.1, 2.2.2 and 2.5 for explanations of terms and concepts.

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fluids start to become hypoxic. This has been determined experimentally to be between 13 and 16 C in adult cod (Fig. 3.4) (Sartoris et al., 2003), and beyond this range cardiac arrhythmia, if present, can cause a reduction in blood circulation capacity. As a consequence, this results in lower venous oxygen concentrations, onset of anaerobic mitochondrial metabolism, alteration of enzymatic rates (Clarke, 1993; Coutant, 1987; Fry, 1971) and a sudden decrease in intracellular pH (Van Dijk et al., 1997). This in turn is accompanied by energetic collapse in white muscle (Foster et al., 1993; Sartoris et al., 2003), reduced scope for whole organism aerobic activity and, ultimately, death at the critical temperature threshold, Tcrit (Lannig et al., 2004; Po¨rtner, 2001; Sartoris et al., 2003). Experimental data suggest that Tcrit ranges between 16.0 and 22.2 C in adult cod populations (Gollock et al., 2006; Lannig et al., 2004; McKenzie, 1938; Po¨rtner et al., 2008; Sartoris et al., 2003) and is lower at 15.5–18.0 C in juveniles (Pe´rezCasanova et al., 2008; Yin and Blaxter, 1987), although survival upon acute exposure to 20 C has been demonstrated in controlled laboratory conditions (Pe´rez-Casanova et al., 2008). This variation in response may be due to different experimental methodologies, but it could also reflect stockspecific adaptation of cod (Po¨rtner et al., 2008). The highest partial pressure of venous oxygen in southern North Sea cod held in laboratory conditions occurs at approximately 5 C (Lannig et al., 2004), which relates closely to Topt for adult growth. The frequency of haemoglobin genotypes in the population can be affected by environmental temperature experienced by parental fish, and underlies thermal preferences in cod (Andersen et al., 2009). Warmer water preferences are associated with the Hb-1 genotype (Petersen and Steffensen, 2003), with highest frequencies of the Hb-1–1 allele found in the southern North Sea (Husebo et al., 2004; Sick, 1965), a region of some of the warmest bottom temperatures within the cod biogeographic range (Vaz et al., 2007). Although Topt of all haemoglobin genotypes appears to be centred around 14 C ( Jordan et al., 2006), optimal oxygen extraction rates occur below 12 C (Colosimo et al., 2003), which may explain why many cod populations occur in waters below this temperature. Thermal adaptation generally optimises whole animal aerobic scope to within a thermal range or window (Po¨rtner, 2001, 2002). However, shortterm thermal acclimatisation may also allow occupation of specific thermal regimes, such as the 2–3 C sea surface isotherm characterising the seasonal migration highway used by cod in the Northwest Atlantic (Rose, 2004b). Evidence for seasonal acclimatisation in cod is not widespread, but has been provided by laboratory trials demonstrating that the thermal limit beyond which heart rates begin to decline can be elevated by acclimatisation to warmer temperatures (Lannig et al., 2004). This suggests that cod may be able to buffer the effects of climate-linked sea temperature warming sufficiently well in the short term, however, as sea temperatures continue

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to rise in the region occupied, shifts in distribution may eventually take place that prevent exposure to temperatures beyond the pejus temperature.

2.3. Metabolic scope for activity Metabolic rate is temperature -dependent (Claireaux et al., 2000; Lannig et al., 2004) and cod inhabiting temperate seas need to acclimatize metabolically to seasonal fluctuations in sea temperature. The costs of routine metabolic activity are lower for individuals experimentally exposed to colder water. In homogeneous water conditions, voluntary activity, metabolic rate and oxygen consumption all increase in response to a 2.5 C rise in temperature, leading to a subsequent decrease in scope for activity (Claireaux et al., 1995). When presented with a thermally stratified environment, however, behavioural changes are exhibited by cod, with individuals swimming away from thermally stressful locations (Claireaux et al., 2000). It appears that both swimming speed (Claireaux et al., 1995) and foraging rate (Peck et al., 2003) are also determined by thermal conditions. Between June and August in the southern North Sea, decreased activity and predominantly benthic habitation were recorded from electronically tagged adult cod. When sea temperatures cooled, first nocturnal activity, then almost continuous activity took place during the following months (Righton et al., 2001). This pattern corresponds with expectations about energy conservation (Arnold and Walker, 1992). When higher temperatures are encountered it would be expected that they would either be avoided (O’Brien et al., 2000), and/or activity reduced, since occupation of higher temperatures will increase standard metabolic rate and reduce scope for aerobic activity (Soofani and Hawkins, 1982; Soofiani and Priede, 1985). Growth also decreases under such conditions, with individuals apparently switching to a ‘translucent’ phase where an opaque band is formed during otolith growth (Pilling et al., 2007), indicating exposure to unfavourable temperatures (Hu¨ssy et al., 2004). Earlier onset and increased duration of the translucent zone of growth in recent decades has been attributed to increased spring/summer water temperatures (Beckman and Wilson, 1995), indicating that climate warming may be extending the period of metabolic stress (Pilling et al., 2007). Sea surface temperatures have exceeded Topt for short periods during recent summers in the southern North Sea, for example. The subsequent decrease in aerobic and locomotory performance will theoretically have been sufficient to impair activity such as to prevent optimal feeding in adult individuals (Lannig et al., 2004; Po¨rtner, 2001; Po¨rtner et al., 2001). This may explain the seasonal absence of cod in the southern North Sea region despite apparent prey availability (Lannig et al., 2004). From these results it has been suggested that if the climate continues to warm, seasonal

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disappearance of cod from some areas may increase in frequency and duration. However, these conclusions assume that Topt does not shift as a result of acclimation to regional temperature regimes, which may not be the case of course. Differences in compensatory capacity to specific temperature challenges are generally expected for populations inhabiting different water masses or latitudes as a result of acclimation to local thermal regimes (Clarke, 1993), so it is unlikely that specific thermal thresholds will be the same for all cod populations across the biogeographic range.

2.4. Maturation and spawning Significant correlations between mean annual sea temperatures and age at maturity have been found for many cod stocks ( Jorgensen, 1990, 1992; O’Brien, 1999; Yoneda and Wright, 2004). Together these results indicate a 1-year reduction in maturation age linked to a 2 C increase in temperature (Drinkwater, 2002). Hence, closer to the southern range edge of the species, maturation is predicted to be at a younger age. This pattern has implications for future stock success in warmer climates because smaller, younger fish are less fecund and spawn for shorter periods (Kjesbu et al., 1996), and warmer spring seasons may promote earlier maturation. Climate-linked sea temperature changes may have direct and indirect effects on cod energy provisioning and maturation processes that precede spawning. Cod build up energy reserves during summer and autumn, and mature during the winter months. Mature female fish in better condition prior to spawning tend to be more fecund (Kjesbu et al., 1991), and expend less energy and lose less somatic mass during the spawning season (Lambert and Dutil, 2000; Lloret and Ra¨tz, 2000; Ra¨tz and Lloret, 2003). Hence, these fish are at less risk of subsequent natural mortality (Krivobok and Tokareva, 1972; Love, 1958). When energy reserves are low, investment in reproduction by females may be maintained, but at a somatic cost, and reproduction may also be reduced or delayed in extreme conditions to limit somatic loss. Changes in environmental conditions and subsequent ecological processes that negatively affect food intake will influence the energy budget and ultimately reduce productivity of the stock (Lambert and Dutil, 1997). If fishing pressure and climate change act synergistically to reduce the age and condition of the spawning stock, population fecundity may decline (Ottersen et al., 2006). Faster development of early life stages and subsequent higher survival under warmer climatic regimes may, however, counteract any such decline in fecundity. Peak spawning dates have been found to vary among different Norwegian coastal cod populations kept in identical environmental conditions (Ottera˚ et al., 2006). This indicates that spawning time is under genetic control, and could be an adaptation related to environmental conditions in their source location. Consistent with this evidence, survey data show cod

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do not rapidly alter spawning time to match the timing of life history events in zooplankton prey species (Beaugrand et al., 2003). This suggests that stock adaptation may result in a limited capacity for the stock to respond rapidly to climate-driven changes in peak abundance of prey. Thus, it can be hypothesised that weak year classes following high larval mortality may become more common with warming sea temperatures. Contrary to the assumed random mating strategy of many broadcast spawners, there is evidence for male lekking behaviour in cod (Robichaud and Rose, 2004; Windle and Rose, 2007), and for direct female mate choice (Engen and Folstad, 1999; Rowe and Hutchings, 2003; Rowe et al., 2004; Rudolfsen et al., 2005). In laboratory trials, both males and females displayed higher reproductive success when mating occurred between larger individuals (Rowe et al., 2007). The observed reduction in the size spectra of wild fish is thus likely to be affecting total reproductive output (Bekkevold, 2006; Bekkevold et al., 2002). Although climate will influence fecundity through temperature-related effects on maturation and reproductive success, sizetargeted fishing mortality (of the largest fish) is one of the most likely dominant factors negatively affecting subsequent year class strength and recovery of spawning stock biomass (SSB).

2.5. Early life stages Cod eggs and larvae suffer high mortality (up to 99.9%) via predation (Campana, 1996; Cushing and Horwood, 1994; Houde, 1989; Leggett and Deblois, 1994; Shepherd and Cushing, 1980). The growth-predation hypothesis predicts a direct relationship between mortality rate and growth rate of early life stages of fishes (Anderson, 1988; Hare and Cowen, 1997), with more rapid egg and larval development promoting metamorphosis at an earlier age, thereby decreasing the duration of pre-juvenile stages (Drinkwater, 2005). Support for this theory has come from both experimental and simulation studies on early life stages of cod, and together these show how small changes in early growth rates due to increases in temperature can lead to large increases in numbers surviving to recruitment (Chambers and Leggett, 1987; Houde, 1989; Meekan and Fortier, 1996; Miller et al., 1988; Pepin and Myers, 1991). Cod eggs are found over a wide range of temperatures, from 1.5 C in the Northwest Atlantic, to 9 C in the Celtic Sea (Geffen et al., 2006), and there is evidence of local adaptation in development rates (Houde, 1989). Cod eggs from North Sea stocks cannot develop at temperatures less than 1.5 C, while larvae from the Baltic Sea can survive exposure to 1 C, and eggs from the most northern populations will develop below 0 C (Geffen et al., 2006; Valerio et al., 1992; Wieland and Jarre-Teichmann, 1997). Egg incubation periods can also vary significantly with temperature (Pauly and Pullin, 1988; Pepin et al., 1997). Much of the observed seasonal variance in

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egg and larval development times (Pauly and Pullin, 1988) and hatching size (Miller et al., 1988) can also be attributed to thermal conditions, with size decreasing as temperature increases. Thermal tolerance experiments, together with knowledge of spawning locations, indicate that it is unlikely that wild eggs become exposed to lethally high water temperatures immediately after release. Egg mortality is probably caused by other processes including predation and disease, but egg mortality due to sublethal effects of increasing energetic costs at high temperatures may also take place (Nissling, 2004). Optimal temperature for growth (Toptg) undergoes a clear ontogenetic shift in cod (Fig. 3.4) (McCauley, 1977; Reynolds, 1977). Yolk sac larvae have the lowest Toptg ( Jobling, 1988) while the highest Toptg is for free swimming larvae and juveniles ( Jobling, 1994; McCauley and Huggins, 1979). This ontogenetic difference in Toptg can range from 2 to 11 C depending on the local thermal regime inhabited by the source population (Brander, 1994, 2005; Buckley et al., 2004; Bunn and Fox, 2004; Nissling, 2004), but is centred around 7 C (Buckley et al., 2004). Larval growth rates increase as temperature increases between 4 and 14 C (Caldarone et al., 2003; Laurence, 1978; Otterlei et al., 1999; Steinarsson and Bjo¨rnsson, 1999) with time to metamorphosis decreasing from 56 days at 4 C, to 23 days at 14 C (Otterlei et al., 1999). Laboratory estimates of growth rates may, however, be dictated in part by indirect thermal effects on food limitation, as was observed for Georges Bank cod larvae during an anomalously warm period of 1992–1994 (Buckley et al., 2004). The slowest growing cod larvae are found both in the cold waters of the Northeast Arctic (Otterlei et al., 1999), and in warm water towards the southern end of the range (Buckley et al., 2004) including the southern North Sea (Pilling et al., 2007). Survival of larvae has been recorded at temperatures as high as 12 C in the Irish Sea (Geffen et al., 2006). Early juvenile cod from the Irish Sea (Geffen et al., 2006) and those from the Norwegian coastal population exhibit higher Toptg and are heavier at the same life stage than individuals inhabiting colder waters of the Northeast Arctic (Gdo and Moksness, 1987; Otterlei et al., 1999). This indicates that upper pejus (deleterious) temperatures have not been reached, and that temperature-driven growth relationships seem to be population specific. Investigations to date indicate that slight warming of the marine climate is likely to enhance egg and larval survival by decreasing the time taken to reach metamorphosis that in turn limits the temporal window of greatest predation risk. Even stocks close to southern range limits in the central North Sea are likely to show increased survival of early larval stages due to warming of between 1.5 and 4 C during the twenty-first century (Hulme et al., 2002). If predator–prey relationships remain unchanged it is possible that the survival of young fish may therefore increase. The lagged responses of cod to climate warming may thus be driven by conditions affecting

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survival, growth and food availability during early life stages (O’Brien et al., 2000; Planque and Fredou, 1999; Platt et al., 2003).

2.6. Recruitment Recruitment success of fish can be dictated by extrinsic stochastic events such as changes in temperature, winds, currents, food availability, predation/parasitism, and intrinsic factors such as variation in adult condition, stock reproductive effort and age structure (Cushing, 1996; Heath and Gallego, 1997; Houde, 1989). These factors subsequently affect cod production, egg viability and survival of the early life stages (Kjesbu et al., 1996; Marshall et al., 1998; Nissling et al., 1998), as well as primary and secondary production of the whole ecosystem (Hooper et al., 2005). Recent studies indicate that the dominant pattern of recruitment variation may be related to an effect of climate-driven sea temperature changes (Brunel and Boucher, 2007). Such climate-related changes in recruitment success may occur through one or more of several potential mechanisms, including higher production or survival of pelagic eggs or larvae (Rijnsdorp et al., 2009). Temperature plays a key role in the variation of cod recruitment success through a combination of direct and indirect effects (Cushing, 1996; Hermann et al., 1965; Ottersen and Loeng, 2000; Sætersdal and Loeng, 1987). Fecundity is lower in mature individuals from northern cod stocks inhabiting colder waters, but given there is no evidence for compensation through an increase in egg size (Brander, 1994), it appears that the cold-induced shift in the energy budget is unfavourable for reproductive output (Po¨rtner et al., 2001). This is supported by observations of strong year classes during warmer years in northern cod stocks (de Young and Rose, 1993; Drinkwater, 2005; Malmberg and Blindheim, 1994; O’Brien et al., 2000; Ottersen, 1996; Ottersen and Sundby, 1995; Ottersen et al., 1994; Sundby, 2000). Interannual variation in recruitment success is strongly dependent on seasonal temperatures (Wieland et al., 2000). Temperatures between February and June have most impact on recruitment and subsequent year class strength in the North Sea. A rise of 0.25 C has been linked to a 30% reduction in recruitment (Clark et al., 2003). Simulations using the UK Hadley Centre HadCM3 climate model reveal an inverse relationship between change in abundance of 1-year-old cod and sea surface temperatures the previous spring, implying that climate effects on life stage is key to later population recruitment success (O’Brien et al., 2000; Planque and Fredou, 1999). A broad relationship between temperature regimes and stock success has been proposed by Drinkwater (2005), who suggested that recruitment increases as bottom sea temperatures increase until 5 C, with little subsequent change until 8.5 C, before a continual decline at higher temperatures. Based on these conclusions, a 2 C increase in sea

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temperature could result in significant declines in cod abundance in the North Sea from recent levels, with local extinctions being more likely beyond a rise of 3 C (Drinkwater, 2005). This model assumes that the slope of the temperature–recruitment relationship does not vary between stocks, does not account for seasonal variation in temperature and does not take into account fishing mortality, or water column profile and occupancy. Indeed, such factors may explain why temperature–recruitment relationships are often weak (Brander, 2000). O’Brien et al. (2000) found no statistically significant link between environmental temperature and recruitment in Northwest Atlantic stocks during the 1980s and 1990s, and reanalyses of recruitment data sets tend to confirm this result (Frank, 1997; Myers, 1998; Myers and Cadigan, 1995a,b; Myers et al., 1995a). In contrast, predictions of climate change impacts on recruitment and SSB in the North Sea have been constructed using a model that includes fishing mortality, temperature-dependent growth rates, and a temperature-dependent Ricker stock–recruitment function (Clark et al., 2003). This model indicates that sea temperature affects population dynamics via recruitment rather than adult growth. Moreover, the model supports the hypothesis that February to June sea surface temperatures most strongly influence recruitment (Dickson et al., 1974; O’Brien et al., 2000; Planque and Fredou, 1999). Under an unchanging climate scenario, the Clark et al. (2003) model suggests that both SSB and recruitment should increase over the next 50 years if fishing mortality remains constant. However, even under a small forcing of the climate by þ0.05 C per decade, which is much less than the 1 C warming that has already occurred in UK coastal seas since the mid-1980s (Hawkins et al., 2003), SSB and recruitment are predicted to decrease. Under the A1F high emissions scenario (IPCC, 2001) of þ0.26 C per decade, North Sea stocks are predicted to virtually disappear if fishing mortality is not reduced (Clark et al., 2003). However, the model has caveats. It is based on linear models that do not fully capture the relationship between recruitment and temperature, and it also does not account for potential ratelimited recruitment at higher temperatures. There is also a lack of spatial representation of adult distributions, including potential for changes in spawning locations over time (Brander, 1994, 1997; Daan, 1978). Cod recruitment patterns may also reflect temperature-driven variability in availability of food resources at lower trophic levels (Rothschild, 1994). It has been demonstrated that peak spawning date in low biomass cod populations shows strong associations with temperature (Kjesbu et al., 1994; Wieland et al., 2000). In the Northwest Atlantic, higher temperatures appear to result in earlier annual spawning dates in stocks occupying higher latitudes, due to accelerated gonad development (Hutchings and Myers, 1994a,b). The most northern stock in the Barents Sea also shows a positive relationship between recruitment and temperature. The opposite relationship was observed in stocks located at lower latitudes towards the southern

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limits in the North Sea (Daan, 1994; Dickson et al., 1974; Myers, 1998). These relationships were subsequently re-tested and shown not to hold, emphasizing that studies of recruitment may need to step beyond searching for straightforward spawner–recruit and temperature–recruitment relationships (Myers, 1998). In the North Sea, changes in the plankton community have been a key driver of interannual fluctuations in cod dynamics. Long-term changes in recruitment co-vary with changes in the abundance and body size of zooplankton prey with a 1-year time lag, and show a tighter relationship than that observed between cod recruitment and sea surface temperature (Beaugrand et al., 2003; Horwood et al., 2006). The relationship holds for both anomalously cool and warm periods, such as the gadoid outburst between the mid 1960s and 1980s when cool temperatures were associated with high abundances of the boreal copepod Calanus finmarchicus. This copepod is a major dietary component of the cod early life stage, and these high abundances occurred in parallel with 12 years of high cod recruitment (Fig. 3.5). Conversely, during the warm period of the late 1990s and early 2000s, anomalously low cod recruitment reflected low biomass of C. finmarchicus. Warmer waters appear to have resulted in unfavourable conditions for the overwintering stage of this copepod (Greene et al., 2003; Heath et al., 1999) and forced a distributional shift to higher latitudes in the North Sea (Beaugrand and Ibanez, 2004). Higher confidence can be placed on the assumptions of these shifts in biogeographic distribution due to the extensive spatial and temporal coverage of the data, and the use of direct observational data rather than extrapolations based on putative centres of distribution. Direct effects of thermal regimes on physiology of larval fish, and indirect effects on their prey availability, are both likely to be important drivers of recruitment strength. However, the exact nature of the

5.3

Figure 3.5 Parallel long-term changes in zooplankton fluctuations (with 1-year lag) and cod recruitment in the North Sea. Adapted from Beaugrand et al. (2003).

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relationships remains unclear. The abundance and size structure of a population will depend on a range of factors, including the extent of immigration and emigration from populations with different thermal tolerances (Sims et al., 2001, 2004). In the absence of gene flow, adaptation or local acclimatization may lead to a contraction of the spawning period and spawning area, causing fish such as cod to become more sensitive to changes in environmental conditions (Ottersen et al., 1994). Heavily exploited populations of cod may therefore display amplified responses to climate change (Planque and Fredou, 1999). These complications may lead to difficulties when predicting short-term outcomes of environmental change on populations (Planque et al., 2003; Rothschild, 1994, 1998). Biological responses may show strong relationships with large-scale climate indices such as the North Atlantic oscillation (NAO) (Broitman et al., 2008; Drinkwater et al., 2003; Fromentin and Planque, 1996; Ottersen et al., 2001; Stenseth et al., 2002; Walther et al., 2002). Such climate indices often incorporate multiple variables and the interactions between them, and thus can capture a complex interplay of weather and climate-induced variations in the natural environment. As a consequence, they can provide useful assessments of climate fluctuations with which to explore ecosystem change (Namias and Cayan, 1981; Stenseth et al., 2003). The NAO is the main index of winter atmospheric circulation over the North Atlantic. During positive NAO years, warmer winters occur and seawater temperatures are warmer around Northwest Europe. When the NAO switches to a negative phase, winter temperatures are colder in the region (Hurrell and Van Loon, 1997; Van Loon and Rogers, 1978). Over the last 25 years, the frequency and magnitude of NAO positive-index events have increased and winter sea surface temperatures have become milder in British coastal waters. The NAO is predicted to remain in a largely positive phase in the coming decades. Relationships between the NAO index, the physical environment of the Northeast Atlantic and biological responses within it have been well established (Broitman et al., 2008; Hurrell and Van Loon, 1997; Reid et al., 2001; Sims et al., 2001, 2004). Importantly, the NAO index has been linked to changes in recruitment success of most cod stocks in this region (Ottersen et al., 2001), mainly via the direct effects of environmental temperature on sub-adult growth and survival (Attrill and Power, 2002; Dippner, 1997; Ottersen et al., 1994). When all Northeast Atlantic cod stocks are combined within a single recruitment model, a significant geographic relationship between the strength of the NAO and recruitment emerges, with stockspecific trends also apparent (Stige et al., 2006). Environmental conditions during a positive NAO index have been shown to have a negative influence for southern stocks on both seaboards of the Atlantic, but a positive influence on more northerly stocks (Brander and Mohn, 2004).

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2.7. Growth Experimental studies and analyses of catch statistics show that changes in seawater temperature exert a major influence on growth (Bjornsson and Steinarsson, 2002; Bjornsson et al., 2001; Brander, 1995, 2000; Campana, 1996; Campana and Hurley, 1989; Jobling, 1988; Solberg and Tilseth, 1987; Steinarsson and Bjo¨rnsson, 1999; Taylor, 1958). As such, temperature is considered to be a major determinant of production in cod stocks (Dutil and Brander, 2003). Benthic water temperatures have been shown to account for 90% of observed variation in growth rates between cod stocks (Brander, 1994, 1995) and to drive annual growth fluctuations within them (Brander, 1995; Brander et al., 2003; Campana et al., 1994; Clark et al., 2003; de Ca´rdenas, 1996; Drinkwater, 2005). This temperature-dependent variability in growth rates is mediated by immediate physiological requirements, and trade offs between growth and reproduction (Po¨rtner et al., 2001). Free swimming cod tend to select temperatures in which growth rate is maximised (Claireaux et al., 1995; Magnuson et al., 1979), but it is not always possible for individual fish to maintain themselves within thermally optimal habitats. Low temperatures result in slower growth rates and a reduction in the physical condition via direct impacts on rate of food assimilation, and indirect effects on food supply (Otterlei et al., 1999). The resultant physiological and ecological impacts are manifested as a small size-at-age, reduced cohort size, a decline in stock biomass, and surplus energy redirected into reproductive effort (Brander, 1995; Campana, 1996; Krohn et al., 1996; May et al., 1965; Taylor, 1958). Meta-analyses of cod populations show that body condition exhibits a significant increase with warmer mean sea bottom temperatures (Drinkwater, 2005; Ra¨tz and Lloret, 2003). The temperature for optimal growth, however, decreases with size and age, and ranges between 14.3 and 17.0 C for newly hatched juveniles, to between 5.9 and 10.0 C for adults (Bjornsson and Steinarsson, 2002; Bjornsson et al., 2001; Brander et al., 2003; Buckley et al., 2004; Po¨rtner et al., 2001). Thus, decreasing growth performance in adult cod is observed with increasing latitude (Brander, 2004; Po¨rtner et al., 2001). Genetic differences between stocks are also likely to be at least partly responsible for the observed spatial differences, as population differences in growth rates have been seen under controlled experimental conditions (Po¨rtner et al., 2001). Such population variation in growth rates and body size may also be a consequence of fishing, as sustained removal of larger individuals has resulted in evolutionary selection for individuals maturing at earlier ages and sizes (Gadil and Bossert, 1970; Olsen et al., 2004). Although studies indicate that as seawater temperatures rise, cod in warmer climates may experience increased growth rates, such increases may be counteracted by food availability, which can explain up to 97% of the variance in growth in wild cod (Chabot and Dutil, 1999). Fooddependent growth rates may become particularly apparent because

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exposure to warmer water increases standard metabolic rates. Such negative effects on growth may be intensified in conditions of low prey density, as the temperature of optimal performance can become lowered (Brett and Groves, 1979; Buckley et al., 2004). Since growth and survival of larval fish are implicit to many recruitment hypotheses (Anderson, 1988; Cushing, 1990; Ware, 1975), and are affected by climate-driven sea temperature changes (Rijnsdorp et al., 2009), predictions of growth rates under future climates will clearly require data on prey abundance, and information on prey distribution and sub-adult feeding behaviour (Buckley et al., 2004; Dower et al., 1998; Fiksen and MacKenzie, 2002).

3. Impacts of Fishing Marine fishing activity in the North Atlantic can be traced back over at least 1000 years (Barrett et al., 2004, 2008), and there is compelling evidence that this has severely depleted demersal fish stocks in the region, reflecting global trends. Biomass of commercially valuable demersal fish populations is now estimated to be at only 10% of pre-industrial levels (Worm and Myers, 2003), and there has been a concomitant decrease in mean trophic level of landed fish (Pauly et al., 1998). Atlantic cod abundance in particular has declined dramatically since the onset of commercial fishing. Using historical records of New England cod abundance derived from mid-nineteenth century fishing logs, it was estimated that current population biomass now stands at less than 5% of that in 1852 (Rosenberg et al., 2005). Reconstructions using historical records or proxies have also revealed high levels of fisheries exploitation affecting key biological parameters of cod. For example, by studying cod vertebrae preserved in middens in New England, large declines in population body size distributions have been revealed ( Jackson et al., 2001), changes that have links to the biological effects of commercial fishing (Olsen et al., 2004). In this section, we describe the impacts of fishing on cod populations in each of the main regions across its biogeographic range, and bring together these findings with those on climate impacts to evaluate the relative contribution of each set of drivers to observed trends.

3.1. Northwest Atlantic stocks All cod stocks are now generally considered to be either fished at unsustainable levels, are subject to moratoria following dramatic stock collapses, or have recovery plans that do not meet ‘precautionary approaches’ advised by the International Council for the Exploration of the Seas (ICES) (CEC, 2001; FAO, 2002; Hutchings and Myers, 1994a,b; ICES, 2005, 2006, 2008;

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Kuikka et al., 1999; Myers et al., 1997). Arguably the most dramatic collapse of cod was that seen in the Northwest Atlantic. During 1986 and 1987 recruitment was very strong in all cod stocks in this region. As a consequence, fishing mortality (F) increased from 0.5 to >1.0 between 1989 and 1992 for all stocks, except that of the southern Grand Banks (Bishop et al., 1993; Myers et al., 1996). Landings initially increased as SSB was decreasing, a pattern thought to have been caused by fish at lower population biomass tending to aggregate, perhaps making them easier to capture (Hutchings, 1996; Morgan et al., 1997; Rose and Kulka, 1999). Whatever the mechanism, catches were soon dominated by young and small cod (Hutchings and Myers, 1994a,b; Myers et al., 1996). It has been argued that the main factors responsible for the collapse across many of the cod stocks by 1993 were the ignorance of the relationship between fishing mortality and stock biomass, due to consistent underestimation of the proportion of fish harvested annually (Myers et al., 1996), and an unwillingness to cut fishing effort due to the perceived short-term economic consequences (Rivard and Maguire, 1993; Schiermeier, 2002). Evidence indicates that incorrect calculations of fishing mortality resulted from overestimation of biomass (Steele et al., 1992; Walters and Maguire, 1996), an underestimation of reductions in productivity (Rice and Evans, 1988), overweighting of abundance indices to provide the most optimistic estimates of SSB (Myers et al., 1996, 1997) and an increase in efficiency of the fishing fleet (Hilborn and Walters, 1992; Walters and Maguire, 1996). No evidence was found to link abundance of age classes or distributions with water temperature, and thus climate change was rejected as a primary driver for the collapse of these cod stocks (Hutchings and Myers, 1994a,b). A decade after the moratorium on cod fishing was introduced in 1992, populations were still at historically low abundance (Lilly et al., 2003), and even in 2007 the SSB continued to have weak representation from all year classes (STECF, 2007).

3.2. Northeast Atlantic stocks Atlantic cod have a broad distribution on the European continental shelf. In this section, however, rather than review stocks in all areas, we focus on three areas with contrasting habitats and different fates of stocks. First, we describe how fishing has impacted cod in the North Sea, a region where some of the largest declines have occurred, we then compare this to changes in the Celtic Sea stock, where, in general, cod are found at relatively low abundance. Finally, we discuss the status of cod in Icelandic waters, where management structures are different with respect to these other areas. 3.2.1. North Sea The entire North Sea has been commercially fished since the mid-eighteenth century (Cushing, 1988; Smith, 1994), with periods of cessation during the two World Wars (Beverton and Holt, 1957; Borley, 1923;

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Estimated weight (in thousands of tonnes)

Hardy, 1959; Margetts and Holt, 1948). Catchability of cod was high during the late 1940s and 1950s, but began to decline in the 1960s as increased levels of exploitation caused dense aggregations to be fished out (Gulland, 1964). During the ‘gadoid outburst’ of the 1970s, high recruitment led to massive increases in juvenile cod abundance, with estimated stock sizes of 250,000 tonnes (Brander, 1995; Cushing, 1984; Hislop, 1996; Horwood et al., 2006). This period was associated with cooler waters and increases in the abundance of the cold water copepod C. finmarchicus, a primary food source for pelagic larval cod (Beaugrand et al., 2003). Landings rose until the early 1990s, then declined before levelling out at record low levels after 2003 (Holden, 1978; ICES, 2007; Jennings et al., 1999; Olsen et al., 2004; Rijnsdorp and van Leeuwen, 1996; Rijnsdorp et al., 1996; Fig. 3.6). The year class of 1996 was anomalously strong, but it was removed by fishing before reaching maturity (Bannister, 2004), indicating that fishing impacts on stock dynamics were far outweighing those of climatic variability. Size of individual adults also declined across the twentieth century in response to increased fishing mortality of larger, older cod (Fig. 3.7). North Sea cod has been managed under joint management agreements involving annual assessments by the European Council of Ministers and the Norwegian government since 1974 (Reeves and Pastoors, 2007). The defined limits of the North Sea include the Skaggerak and eastern English Channel, and all cod are treated as one stock for ease of management despite some genetic evidence for multiple populations within the region (Blanchard et al., 2005;

400 350 300 250 Discards 200

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1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Figure 3.6 Total estimated catch (in thousands of tonnes) of cod from the North Sea since 1985 including landings and discards. Data: ICES (2008).

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Figure 3.7 High numbers of large cod being landed on the fish market at Aberdeen, Scotland. Photograph ca. 1920.

Hutchinson, 2008; Hutchinson et al., 2001; STECF, 2007). The assessment and total allowable catch (TAC) advice process is conducted under an ICES umbrella, and primarily reflects the needs of the main customer, the Commission of the European Communities (Holden, 1994). TACs have been restricted for the last two decades to allow an estimated 30% increase in spawning biomass, but also whilst falling within 15% of the previous year’s TAC. Data from both research vessel surveys and fisheries landings data suggest that TACs have been ineffective. By 1992, only 4% of North Sea cod were surviving to maturity at 4 years old due to intensive harvesting across the year classes (Cook et al., 1997), and the most commonly caught age classes over the last two decades were immature 1 and 2 year olds (Myers et al., 1996; O’Brien et al., 2000). By 2000, SSB had fallen to around 40,000 tonnes (ICES, 2000), well below the ICES minimum biomass limit of 70,000 tonnes, at which stock production was considered as being severely impaired (Horwood et al., 2006). Conclusions from cod recovery scenarios suggested that even a reduction in fishing mortality to a precautionary F ¼ 0.65 per year provided a low probability that stocks would recover to a precautionary biomass level within a decade (STECF, 2007). Moreover, these models did not take into account climate change in the projections. A narrow window between ‘potential’ and ‘no’ recovery was highlighted (Horwood et al., 2006), which may explain why reductions in fishing effort close to precautionary levels have failed to increase stock biomass. Repeated recommendations from ICES of either total closure or reductions in fishing mortality of up to 70% during the 2000s have resulted in annual re-calculations of TACs and reductions

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in the number of days at sea for gill-netting vessels and beam trawlers in the 70–99 mm and >100 mm mesh sectors (ICES, 2003, 2004, 2006, 2007, 2008). A recovery plan involving TACs to allow a 30% increase in biomass was finalized in 2004 for the North Sea, Kattegat, West Scotland and Irish Sea stocks. A year later, ICES announced that the recovery plan for cod was not precautionary (ICES, 2004) and by 2006 the North Sea and Northwest Regional Advisory Committees had found little evidence of recovery, with stocks still at or close to historically low levels (NSRAC, 2006). Although there have been some indications of improved recruitment with a relatively strong year class in 2005, no increase in SSB has been observed to date. ICES altered their recommendations from ‘lowest possible catch’ in 2002 to ‘zero catch’ from 2004 to 2008 (ICES, 2003, 2004, 2006, 2007, 2008). Interestingly, North Sea cod were listed as being ‘harvested sustainably’ by ICES in 2008, but these stocks in 2009 have been categorized as ‘overfished’, with fishing mortality ‘above target’ and a recommendation of ‘zero catch’ (ICES, 2008). 3.2.2. Celtic Sea Cod have also been targeted by both single- and mixed-species fisheries in the Celtic Sea for several centuries (Kurlansky, 1997), but intensive commercial fishing began relatively recently in comparison with other North Atlantic regions (Pinnegar et al., 2002). Recent assessments have valued landings made by the combined international fleet to be approximately £10.5 million per year, with maximum landings occurring during winter months (Fisheries Science Services, 2008; ICES, 2006). Dwindling numbers of pelagic and demersal fish, including cod, in the coastal Celtic Sea and elsewhere around the UK were of concern as early as the mid-nineteenth century (Sims and Southward, 2006). During the period of modern data collection and assessments, fishing mortality in the Celtic Sea has remained at very high levels since the mid-1980s (Fisheries Science Services, 2008; Worm and Myers, 2003) albeit with a slight decrease in recent years due to a reduction in the section of the fleet targeting cod since 1999 (ICES, 2006). The stock has been well below safe minimum limits since 2004, and even with the recent reduction in fishing effort, biomass is continually declining (ICES, 2006, 2008). Despite declining stock size and low projected recruitment if present fishing effort is maintained, a successful management strategy has yet to be put into practice in the Celtic Sea region. The Celtic Sea cod stock is located close to the southern biogeographic limit of the species in the Northeast Atlantic. The fish have relatively fast growth rates and mature at 2–3 years of age (Armstrong et al., 2001; ICES, 2003). Recent poor recruitment rates have been purported to be driven in part by warming seas, but there is little evidence for climate-driven changes in the biogeographic range or abundance of this stock, and thus fishing is

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still recognized as a primary factor determining SSB. In addition to specieslevel impacts, it is notable that significant declines in the mean trophic level of catches overall have been observed from the region, consistent with fishing-induced changes to the structure of the whole fish community (Pinnegar et al., 2002). 3.2.3. Iceland The Icelandic cod stock is one of the largest in the North Atlantic, with a maximum sustainable yield (MSY) of 330,000 tonnes providing annual revenue in excess of £400 million. The stock is managed as a single unit, although there are discrete regional spawning components (Begg and Marteinsdottir, 2000). Stock size declined throughout the twentieth century from a peak of 3.3 million tonnes in 1928 to 600,000 tonnes by 1993 (Schopka, 1994), accompanied by a decline in SSB to 120,000 tonnes (Marine Research Institute, 2008). A low stock size was recorded in 2007 as catches have continued to exceed advised levels, although SSB has shown an increase in recent years to approximately 230,000 tonnes (Marine Research Institute, 2008). Mean weight at age has decreased significantly to an alltime low in 2007 and 2008, attributed to the lack of capelin as a food source in recent years. This weight-at-age trend, in combination with recent poor recruitment, has led to very low productivity of the current stock (Marine Research Institute, 2008). Three so-called ‘cod wars’ have taken place in the waters off Iceland during the latter half of the twentieth century, in 1958, 1972 and 1975. These hostilities arose as a result of extensions in the offshore spatial extent of the Icelandic fishery exclusion zone and a lack of recognition of this expanding zone by vessels from European countries already fishing in these waters. The first conflict resulted in an extension of Iceland’s territorial waters to 12 nautical miles from the coast. Further extensions of the Icelandic fishing zone to 50 nautical miles in 1972 and 200 nautical miles in 1975 resulted in more severe international conflicts. The final confrontation was resolved when intervention by the North Atlantic Treaty Organization (NATO) succeeded in brokering an agreement that reduced access to British vessels within the 200 nautical mile limit, including closure of four conservation areas to British fishing activities. Various Icelandic government acts have since been introduced in an attempt to reverse the trend of declining fish stocks within the 200 nautical mile limit, including The Fisheries Act of 1976 (amended in 1983), Individual Effort Restrictions in 1977, The Fisheries Management Act 1990, the Harvest Control Rule in 1995 and the current system of TACs. Despite these measures, stock size has shown no signs of recovery to sustainable levels. In the early decades of the twentieth century, stock size was strongly correlated with environmental changes in the Iceland–Greenland region. The coastal current and Atlantic inflow are thought to exert a strong

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influence on annual success of each spawning component via alterations in the strength of water flow from the main spawning grounds off the northwest coast of Iceland to the main nursery grounds off the north coast (Begg and Marteinsdottir, 2002). Pelagic juveniles are larger and more abundant during years of stronger current flow and Atlantic inflow, due to both increased dispersal and increased abundances of the main prey species of zooplankton, C. finmarchicus that is brought into the region by the Atlantic inflow (Sundby, 2000). As fishing mortality has steadily increased from 0.16 to approximately 1.0 between the 1930s and 2000s, it has exerted an increasingly dominant influence on the annual stock size of Icelandic cod. Stock models that incorporate both environmental and fishing components indicate that substantial reductions in fishing effort are required to permit stock recovery (Baldursson et al., 1996).

3.3. The fishing versus climate change debate Historically high abundances of North Sea cod during the early 1900s (Eckman, 1953), 1960s and 1970s (Cushing, 1984) have been linked to cooler marine climates, while the recent period of rapid climate warming has been suggested to have contributed to the observed declines in SSB (Blanchard et al., 2005; Clark et al., 2003; O’Brien et al., 2000; Ottersen et al., 2006; Schiermeier, 2004). During recent decades it is possible that climate signals have been overridden by fishing impacts, and recent warmer climates have exerted additional pressures on already stressed stocks (Graham and Harrod, 2009). However, separating the interactions between the two drivers has proved difficult. Thus, quantifying strengths of component effects will be challenging, especially between regions that differ in community compositions, thermal regimes and habitat structure, and also in cod abundance, distributions and behaviour (Neat and Righton 2006; Righton et al., 2001). Despite this, there is a need to more fully understand the contributive effects of climate change on cod stocks that are already at historical low abundance due to overexploitation. Biological responses to environmental changes such as fishing and climate, for example, can be divided into two categories. Firstly, proximate ecological responses that depend upon relationships between physical factors and organismal-level processes, population dynamics and community structure (Harley et al., 2006). Secondly, direct impacts on individual performance during various life stages through changes in physiology, morphology and behaviour (Mieszkowska et al., 2006, 2007). These impacts lead to population-level responses, which can be additionally affected by climate-driven changes in hydrographic processes that affect dispersal of the pelagic larval life stages and recruitment. All of these are likely to lead to alterations in cod distributions, biodiversity, productivity and micro-evolutionary processes.

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4. Population-Level Impacts of Fishing and Climate Change Shifts in survival, maturity, fecundity, reproduction, recruitment success and growth all scale up to the population level. If sufficient numbers of individuals display the same response to an external driver, such as climate, then population dynamics are likely to be altered. Such effects of climate are likely to be observed first within populations located close to the distributional limits, where environmental conditions are most likely to be already approaching stressful levels (Lewis, 1986, 1996; Orton, 1920; Southward, 1995). By contrast, effects of fishing mortality may well affect populations across much of their range.

4.1. Stock assessment SSB is the parameter used to define the size of exploited fish stocks. Both short- and long-term variability in SSB may be driven by natural agestructured interactions, including competition between year classes, cannibalism and natural mortality (Bjornstad et al., 1999). The SSB–recruitment relationship may be contextualized with respect to underlying environmental, ecological and biological processes that control growth, reproduction and mortality. Supporting this idea, inclusion of age structure data can help to improve SSB–recruitment models (Marteinsdottir and Thorarinson, 1998). Different age classes may contribute unequally to reproductive output and a spawning stock with a more diverse age structure may exhibit protraction of the spawning period due to size or age-dependent factors (Hutchings and Myers, 1994a,b; Marteinsdottir and Petursdottir, 1995). The most common method of determining the spawner–recruitment relationship is the application of a model such as the Ricker or Beverton–Holt model to a single stock (Myers et al., 2001). Unfortunately, the stock–recruitment curve that is generated can be simplistic, and the effects of biological and environmental factors can strongly affect this relationship leading to large variations in recruitment (God, 2003; Marshall et al., 1998, 2000). The existence of a relationship between abundance of spawners and number of recruits is implicit to SSB calculations (Hilborn and Walters, 1992; Myers and Barrowman, 1996), but within-stocks data provide a poor fit to models (Myers and Cadigan, 1995a,b; Myers et al., 1995a,b; Shepherd and Cushing, 1980). Potential reasons for this are pre-recruit mortality (Cushing, 1988; Goodyear and Christensen, 1984; Walters and Collie, 1988), model skew caused by outliers (Chen and Paloheimo, 1995) and/or errors in variable measurement (Walters and Ludwig, 1981). There is also the possibility of high variance in reproductive output among individuals, that

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may in turn result in large disparities between effective and observed population sizes (Hedgecock, 1994), and even large populations may have few individuals that effectively contribute to spawning (Hauser and Carvalho, 2008). In theory, a minority of individuals that spawn in favourable oceanographic conditions can disproportionately contribute to the next generation (Hedgecock, 1994). Finally, migrations affecting stock connectivity are also not typically considered when assessing these relationships (Myers et al., 2001).

4.2. Stock evaluation—An example from the North Sea The ICES Stock Assessment Working Group uses data from commercial catches, research vessel surveys and time series to evaluate the status of the North Sea stock relative to previous years and defined reference points. Information on catch per unit effort, catch-at-age and natural mortality are compared to an average between 1980 and 1982, and used to calculate SSB (Beare et al., 2005; Sparre, 1991). These parameters are assumed to remain constant between years. Forecasts of stock status for the forthcoming year are made for a range of exploitation rates, and presented as a catch-option table of resultant SSB from specific fishing mortalities (Reeves and Pastoors, 2007). These projections are then peer-reviewed by the ICES Advisory Committee for Fisheries Management before management decisions are made at the political level. The use of stock–recruitment methods in fisheries management has been criticized due to a lack of concordance between the projected model outputs of stock assessments, and the observed annual variation in reproductive potential of stocks. The disparity is likely to be due to interannual stochastic fluctuations, which in turn are likely to be largely driven by natural environmental changes. This highlights the need for stock assessment analyses to include survey-based indices of stock abundance (Marshall et al., 1998). In theory, changes in SSB should be able to provide a clear indication of whether fishing mortality or climate change is the dominant factor causing the continual decline observed during the last two decades. If climatedriven effects are the primary cause of the decrease in population abundance, years with high observed SSB would be expected to be preceded by high survivorship and recruitment of sub-adults (Myers et al., 1996). However, this is not generally observed. In the North Sea, for example, adult stock biomass has declined from the 1960s until recently (2006–2008), despite numbers of recruits-per-spawner being relatively high, indicating that the loss of individuals from populations is occurring from the older age classes. By contrast, if fishing is the driving force, proportional mortality due to harvesting would continue to increase during the decline of the stock (Myers et al., 1996). Figures indicate that such fishing mortality has continued to increase, despite severe reductions in the TACs issued

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(ICES, 2003, 2004, 2006, 2007, 2008). Taken together, this evidence strongly indicates that overexploitation is the dominant factor causing the continuing decline in cod SSB in the North Sea.

4.3. Allee effects and management plans

Per capita birth rate

When population size falls below a critical point, individual fitness may be reduced, causing a decline in population growth rate known as ‘growth depensation’, with an increase in extinction vulnerability of the population as a whole (Drake and Lodge, 2006; Myers and Cadigan, 1995a,b; Post et al., 2002). More generally, the correlation between population size and population growth rate is known as the Allee effect (Allee, 1931), and the Allee threshold is reached when the population size either increases or declines to an unstable density equilibrium, where the birth rate equals the death rate (Berec et al., 2007) (Fig. 3.8). This threshold is unstable, and for cod, any variation in recruitment or SSB can cause a population that is subject to strong Allee effects to expand, stabilize or collapse (Rose, 2004a,b; Shelton and Healey, 1999; van Kooten et al., 2005). Allee effects can be driven by numerous causes. In some species, they may be induced by a decreased probability of finding a mate, failure of schooling behaviour to prevent predation or decreased foraging efficiency in social foragers at lower population densities (Courchamp et al., 1999; Stephens and Sutherland, 1999). Fisheries exploitation can induce an Allee effect if fish population-size reductions lead to aggregation, enabling fishers to more efficiently locate and harvest the remaining fish. Cod may experience Allee effects from low fertilization success and reduced juvenile survival at low population densities (Rowe et al., 2004). As a top predator, Allee effects may also occur if cod feed specifically on small individuals of a size-structured prey population, and this leads to a decline in the prey abundance, enhanced intraspecific competition and

Alternative stable state 2 = carrying capacity

Alternative stable state 1 = extinction Population density

Figure 3.8 A schematic diagram of theoretical Allee effects on a population. See Section 4.3 for explanations of terms and the concept.

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ultimately a decline in the adult cod population (de Roos and Persson, 2002; de Roos et al., 2003). Equally, Allee effects may act on cod through a ‘predator-pit’ scenario. If predators are able to continually maintain cod biomass at low levels, then populations may be unable to produce sufficient recruits to allow population expansion. Harp seals (Phoca groenlandica) have consumed an estimated 88,000 tonnes of cod per annum in the Northwest Atlantic throughout the second half of the 1990s, many of which are prerecruits (Stenson et al., 1997). The grey seal (Halichoerus grypus) is also reported to be responsible for heavy predation on two Northwest Atlantic stocks (Chouinard et al., 2005; Fu et al., 2001; Trzcinski et al., 2006). North Sea cod are pre-dated upon by grey seals, but estimated consumption of cod only amounts to approximately 3.7% of the total stock biomass (Hammond and Grellier, 2005). Harbour porpoises (Phocoena phocoena) also feed on cod, and are four times as abundant as harbour seals in the North Sea. Cod populations are therefore exposed to both natural and fisheriesinduced depensation. The debate continues over the existence of fishing-induced Allee effects in cod. It has been argued that the species does not exhibit any of the mechanisms usually associated with the Allee effect (Myers et al., 1995a,b; van Kooten et al., 2005). Instead, it has been suggested that fishing mortality may actually enhance juvenile survival due to low spawner densities (Myers et al., 1995a,b). Exclusion of depensation in stock assessment predictions for Northwest Atlantic stocks gave rise to predictions of an annual growth rate of 19% with zero F and a threefold increase in stock size after 7 years from the moratorium in 1993 (Myers et al., 1997). Over a decade on, however, only four stocks have showed any signs of increased abundance, with only one experiencing substantial recovery (Shelton et al., 2006). The potential presence of Allee effects operating on cod populations suggests that if insufficient information on the life history of the target species is included in management models, the effects of climate change on fisheries could be vastly underestimated. For populations such as the North Sea cod, for example, which have been reduced to levels far below the carrying capacity of the system, it is vital that this does not occur. The combination of Allee effects and incorrect management could reduce the stock size to a critical level where the population will suddenly crash. Fisheries assessment models generally assume a spawner stock–recruit function whereby recruitment increases with spawner biomass until it reaches either an asymptote (Beverton–Holt model) or declines (Ricker model). Thus, these models assume that individual reproductive output will actually increase at low fish densities. The inclusion of potential Allee effects into management plans could help to optimise risk management strategies, even though Allee thresholds cannot currently be accurately established (Berec et al., 2007). Protection of areas where high densities of cod are present could help to prevent Allee effects from occurring.

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5. Monitoring Status and Recovery of North Sea Cod: A Case Study Monitoring North Sea cod stocks for signs of recovery has proven difficult, not least because catches and bycatches often go unreported making assessment of recovery difficult (ICES, 2004, 2005). The region currently falls within a single ICES management unit, but the existence of multiple distinct stocks within the North Sea may obscure the disproportionate decline of some more vulnerable stocks for which separate management plans may be required (Hutchinson, 2008). Landings may need to be split into relative contributions from different stocks to allow appropriate management strategies, as recommended by the North Sea Regional Advisory Council (NSRAC, 2008). In addition, a range of values of fishing mortality are obtained using multiple research vessel surveys, introducing uncertainty into stock estimations (Blanchard et al., 2005). Prior to 1988, assessment and forecasting techniques showed large interannual variation in performance as the methodology developed, and between 1988 and 1995 relatively high performances were obtained. However, since then, there has been a systematic underestimation of fish mortality and overestimation of the contribution of incoming year classes (Reeves and Pastoors, 2007). Similar problems have been encountered in other cod stocks (Pastoors, 2005). Under-reporting of landings and the absence of discard data creates uncertainties in catch estimation, although errors in the assessment preceded the problems arising from limited catch data and do not appear to explain the change in model performance. Instead, this may be attributable to the reliance on parameters estimated from earlier time periods where the ecosystem may have been in a different state, and/or that may also have been potentially, at least in part, a consequence of the impacts of climate change (Beaugrand et al., 2003; Blanchard et al., 2005; O’Brien et al., 2000). The international aspect and mixed species nature of the North Sea fishery have been highlighted as the main factors contributing to the recent poor state of the North Sea stock (Bannister, 2004), despite efforts to reduce fishing mortality at the European scale. A wider ecosystem-based approach is being developed to attempt to account for the mixed species nature of North Sea demersal fisheries (Vinther et al., 2004). However, the process of determining suitable parameters that distinguish relative impacts of fishing, climate change and natural variance is continuing (Blanchard et al., 2005; Rice, 1995, 2000; Rice and Evans, 1988; Rice and Rochet, 2005; Rochet and Trenkel, 2003; Trenkel and Rochet, 2003). Among these approaches is size spectra analysis, a technique that has proven useful for detecting effects of exploitation on fish stocks, as temporal changes in the index are consistent

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with fishery-mediated changes in community structure (Bianchi et al., 2000; Gislason and Rice, 1998; Jennings and Greenstreet, 1999; Murawski and Idoine, 1992; Rice and Gislason, 1996; Shin et al., 2005; Zwanenburg, 2000). Even this approach has difficulties, however, as warmer waters expected due to climate warming may lead to enhanced recruitment of small species, and concomitant shifts in the size spectra. If such issues can be overcome by allowances for discrimination between forcing factors, then size-based metrics may become useful management tools (Blanchard et al., 2005; Genner et al., 2009b). There has been little research into the application and utility of closed areas for fishing, and it appears most closures have been designated without clear objectives (SGMOS, 2003). At the geographical scale of the ICES rectangle, the lack of high densities of cod suggest that movement of fishing effort would save few fish (Blanchard et al., 2005). A 10-week closure of part of the North Sea in 2001 was deemed ineffective, and data were of insufficient resolution to separate any closure effects from additional factors (Council Regulation (EC) No. 259/2001). It has since been concluded that temporal closures must be used with other management approaches to have a role in the future maintenance of North Sea cod biomass, and would be required over several years and across larger spatial scales (Horwood et al., 2006; STECF, 2007). Emerging management ideas include the introduction of Optimum Restorable Biomass to replace MSY as a target reference point (Ainsworth and Pitcher, 2008). This has been suggested as a suitable cost/benefit approach to restoration of severely depleted fish stocks (Pitcher, 2008) and uses ‘Back To the Future’ simulation models to establish a restoration trajectory from the present depleted system to a target of an historical system after establishing sustainable fishing (Ainsworth and Pitcher, 2008; Pitcher, 2008; Pitcher and Forrest, 2004). Several optimal trajectories can be simulated based on restoration targets and economic profit scenarios. This multidisciplinary approach to restorative ecology suggests that rebuilding stocks to defined targets is the main goal for fisheries management (Pauly et al., 1998). In contrast, however, the North Sea Regional Advisory Council has recently issued advice to the European Commission that the cod recovery plan should be reviewed and targets changed from recovery based on biomass to that based on fishing mortality (NSRAC, 2008).

6. Concluding Remarks Most recovery plans for fish stocks are less than two decades old, and quantifying potential recovery is still proving difficult (Caddy and Agnew, 2004; Caddy and Surette, 2005). Pelagic stocks appear to be responding

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more positively than demersal stocks, and comparatively few stocks have been restored. The World Summit of Sustainable Development set a target date of 2015 for the management of all fish stocks at the level of MSY. No indication was given, however, as to how multi-species fisheries should be managed to attain such a standard, and it is questionable whether proposed targets are realistic in rapidly changing environments. Additionally, there is debate as to whether the focus of management should be sustainability within an already depleted system, or the complete restoration and rebuilding of fish stocks to historic levels (Pitcher and Pauly, 1998). Moreover, reconstruction of past ecosystems may be an impossible policy goal if the past ecosystems existed under different climatic regimes (Pitcher and Forrest, 2004). It is vitally important that the relative contributions of both fishing mortality and climate change on stock biomass, population structure and abundance changes are quantitatively understood to provide accurate and timely advice for effective fisheries management (Horwood et al., 2006; Rose, 2004a,b). Predicting the effects of climate change on fish productivity, as discussed in earlier sections of this chapter, is difficult due to incomplete knowledge of the physiological and ecological mechanisms by which fishes respond to changes in local and regional environmental conditions. Regime shifts also make predictions of future assemblage states problematic as the drivers force the assemblage into a new stable state which may differ greatly from the previous one (Cury et al., 2008; DeYoung et al., 2004; Mantua, 2004). Time series provide a basis for understanding the effects of environmentally driven fluctuations in abundance and production of stocks, and provide the opportunity for deeper insights of the effects of high exploitation pressure (God, 2003). However, investigations into the macroecological responses of wide ranging fishes such as Atlantic cod are problematic due to the lack of uniformity in spatial data collection from commercial fisheries. In recent years, the availability of research vessel trawl data and standardized fisheries statistics has gone some way to address this problem. It is imperative that these data are now combined with detailed physiological knowledge of the various life history stages, and an understanding of interactions between cod and their environment, to allow more accurate predictions of future stock structure and abundance. Only then we will be able to determine to what degree observed changes in cod populations have been due to fishing and warming seas, and have the ability to introduce effective management plans for mitigation of climate change and fisheries impacts. The review of the European Common Fisheries Policy (CFP) in 2008 acknowledges these factors and a Green Paper on the CFP reform sets out a vision for European fisheries by 2020, which includes integration with the new Integrated Maritime Policy and the Marine Strategy Framework Directive (CEC, 2009). The urgent need to review fisheries management

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as part of the wider maritime environment and associated activities is recognized (Greenstreet and Rogers, 2006), as are the additional impacts of climate change on exploited marine stocks. Fleet over-capacity is still identified as the fundamental problem that needs to be addressed. More active stewardship, including appropriate use of the increasing scientific knowledge base, combined with emergent European and international maritime directives is required if we are to redress the decline in Atlantic cod whilst stocks remain to be conserved. In a rapidly changing world a precautionary approach is required. Climate change interacts with overfishing to increase the risk of declining stocks, especially for species of boreal biogeographic origin such as Atlantic cod. Occasional large recruitment events can enable a single annual-breeding boreal species, which is dependent on the spring/summer temperature regime, to persist in the face of climatic change. If longevity and size of spawning fish are reduced, then persistence becomes less likely as the probability of a major recruitment event during the lifespan of an individual is much reduced. As we describe in this chapter, it seems clear that climate can act to exacerbate the deleterious effects of overfishing on marine ecosystems; however, in this context, climate change effects should not excuse overfishing. Moreover, given the mosaic structure of cod populations with complex stochastic responses to climate change, the revolution of management measures must match the scale of these ecological processes. Management strategies with one size and approach, such as the CFP, will not sufficiently well accommodate the complexities of cod interactions with changing environments.

ACKNOWLEDGEMENTS We thank G. Beaugrand for providing Fig. 3.5 and S. Cotterell for providing critical comments on an earlier version of this Chapter. We gratefully acknowledge funding support from the UK Department for Environment, Food and Rural Affairs (DEFRA), the UK Natural Environment Research Council (NERC) Oceans 2025 Strategic Research Programme through Themes 6 (Science for Sustainable Marine Resources) and 10 (Integrating sustained observations for marine environmental monitoring) and The Worshipful Company of Fishmongers. MJG was supported by a Great Western Research Fellowship and DWS by an MBA Senior Research Fellowship.

REFERENCES Ainsworth, C., and Pitcher, T. (2008). Back to the future in Northern British Columbia: Evaluating historic marine ecosystems and optimal restorable biomass as restoration goals for the future. Am. Fish. Soc. Symp. 49, 317–329. Allee, W. C. (1931). ‘‘Animal Aggregations: A Study in General Sociology.’’ The University of Chicago Press, Chicago.

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C H A P T E R

F O U R

Susceptibility of Sharks, Rays and Chimaeras to Global Extinction Iain C. Field,*,†,1 Mark G. Meekan,†,2 Rik C. Buckworth,‡ and Corey J. A. Bradshaw§,} Contents 1. Introduction 1.1. Aims 2. Chondrichthyan Life History 2.1. Niche breadth 2.2. Age and growth 2.3. Reproduction and survival 3. Past and Present Threats 3.1. Fishing 3.2. Beach meshing 3.3. Habitat loss 3.4. Pollution and non-indigenous species 4. Chondrichthyan Extinction Risk 4.1. Drivers of threat risk in chondrichthyans and teleosts 4.2. Global distribution of threatened chondrichthyan taxa 4.3. Ecological, life history and human-relationship attributes 4.4. Threat risk analysis 4.5. Modelling results 4.6. Relative threat risk of chondrichthyans and teleosts 5. Implications of Chondrichthyan Species Loss on Ecosystem Structure, Function and Stability 5.1. Ecosystem roles of predators

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* School for Environmental Research, Institute of Advanced Studies, Charles Darwin University, Darwin, Northern Territory 0909, Australia { Australian Institute of Marine Science, Casuarina MC, Northern Territory 0811, Australia { Fisheries, Northern Territory Department of Primary Industries, Fisheries and Mines, Darwin, Northern Territory 0801, Australia } The Environment Institute and School of Earth and Environmental Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia } South Australian Research and Development Institute, Henley Beach, South Australia 5022, Australia 1 Present address: Graduate School of the Environment, Macquarie University, Sydney, New South Wales 2109, Australia 2 Present address: Australian Institute of Marine Science, University of Western Australia Ocean Sciences Institute (MO96), Crawley, Western Australia 6009, Australia Advances in Marine Biology, Volume 56 ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56004-X

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5.2. Predator loss in the marine realm 5.3. Ecosystem roles of chondrichthyans 6. Synthesis and Knowledge Gaps 6.1. Role of fisheries in future chondrichthyan extinctions 6.2. Climate change 6.3. Extinction synergies 6.4. Research needs 7. Concluding Remarks Acknowledgements References

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Abstract Marine biodiversity worldwide is under increasing threat, primarily as a result of over-harvesting, pollution and climate change. Chondrichthyan fishes (sharks, rays and chimaeras) have a perceived higher intrinsic risk of extinction compared to other fish. Direct fishing mortality has driven many declines, even though some smaller fisheries persist without associated declines. Mixedspecies fisheries are of particular concern, as is illegal, unreported and unregulated (IUU) fishing. The lack of specific management and reporting mechanisms for the latter means that many chondrichthyans might already be susceptible to extinction from stochastic processes entirely unrelated to fishing pressure itself. Chondrichthyans might also suffer relatively more than other marine taxa from the effects of fishing and habitat loss and degradation given coastal habitat use for specific life stages. The effects of invasive species and pollution are as yet too poorly understood to predict their long-term role in affecting chondrichthyan population sizes. The spatial distribution of threatened chondrichthyan species under World Conservation Union (IUCN) Red List criteria are clustered mainly in (1) south-eastern South America; (2) western Europe and the Mediterranean; (3) western Africa; (4) South China Sea and Southeast Asia and (5) south-eastern Australia. To determine which ecological and life history traits predispose chondrichthyans to being IUCN Red-Listed, and to examine the role of particular human activities in exacerbating threat risk, we correlated extant marine species’ Red List categorisation with available ecological (habitat type, temperature preference), life history (body length, range size) and human-relationship (whether commercially or gamefished, considered dangerous to humans) variables. Threat risk correlations were constructed using generalised linear mixed-effect models to account for phylogenetic relatedness. We also contrasted results for chondrichthyans to marine teleosts to test explicitly whether the former group is intrinsically more susceptible to extinction than fishes in general. Around 52% of chondrichthyans have been Red-Listed compared to only 8% of all marine teleosts; however, listed teleosts were in general placed more frequently into the higher-risk categories relative to chondrichthyans. IUCN threat risk in both taxa was

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positively correlated with body size and negatively correlated albeit weakly, with geographic range size. Even after accounting for the positive influence of size, Red-Listed teleosts were still more likely than chondrichthyans to be classified as threatened. We suggest that while sharks might not have necessarily experienced the same magnitude of deterministic decline as Red-Listed teleosts, their larger size and lower fecundity (not included in the analysis) predispose chondrichthyans to a higher risk of extinction overall. Removal of these large predators can elicit trophic cascades and destabilise the relative abundance of smaller species. Predator depletions can lead to permanent shifts in marine communities and alternate equilibrium states. Climate change might influence the phenology and physiology of some species, with the most probable response being changes in the timing of migrations and shifts in distribution. The synergistic effects among harvesting, habitat changes and climate-induced forcings are greatest for coastal chondrichthyans with specific habitat requirements and these are currently the most likely candidates for extinction. Management of shark populations must take into account the rate at which drivers of decline affect specific species. Only through the detailed collection of data describing demographic rates, habitat affinities, trophic linkages and geographic ranges, and how environmental stressors modify these, can extinction risk be more precisely estimated and reduced. The estimation of minimum viable population sizes, below which rapid extinction is more likely due to stochastic processes, is an important component of this endeavour and should accompany many of the current approaches used in shark management worldwide.

1. Introduction Humans have depended on marine resources since prehistory (Walker and Deniro, 1986), with the commonly held belief until even recent times that it was beyond human capability to cause the extinction of marine species. This is summarised by two of the foremost thinkers of the eighteenth and nineteenth centuries, Jean Baptiste de Lamarck and Thomas Huxley, who reflected a widespread belief that the high fecundity and wide distributions of marine fishes made the seas an inexhaustible source of food and wealth, and that people could use but a small fraction of the total resources available using fishing methods employed at the time (Garibaldi and Caddy, 2004; Sims and Southward, 2006). Even only a decade ago, a survey of marine scientists revealed that nearly one-third believe marine extinctions are currently not a serious problem (Roberts and Hawkins, 1999). In the past decade, it has become clear that marine biodiversity worldwide is under increasing threat, primarily as a result of over-harvesting,

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pollution and the direct and indirect impacts of climate change (Gardner et al., 2003; Harley et al., 2006; Harvell et al., 2002, 2004; Hutchings and Reynolds, 2004; Jackson et al., 2001; Jones et al., 2004; Lotze et al., 2006; Pauly et al., 2002; Roberts, 2002). At present, around 40% of the world’s human population lives within 100 km of the coast (Martinez et al., 2007) and this proportion is increasing. With the median global human population predicted to increase to over 9 billion by 2050 (McMichael, 2001) and more people choosing to live along the coastal fringes, marine habitats are likely to suffer increasing degradation and over-exploitation (Worm et al., 2006). As a corollary, anthropogenic stresses and climatic changes have reduced the resilience of ecosystems in many locations around the globe by slowly degrading habitats and directly harvesting species, causing many ecosystems to switch unexpectedly into alternate states (Folke et al., 2004; Hughes et al., 2003; Nystrom et al., 2000; Scheffer et al., 2001; Worm et al., 2006). Stressors can operate singly or synergistically at multiple scales (Brook et al., 2008), resulting at times in large shifts in species composition. Familiar examples include regime or phase shifts on coral reefs (Aronson et al., 2004; Bellwood et al., 2004; Hawkins and Roberts, 2004; McManus and Polsenberg, 2004), in kelp forests following declines in canopy-forming species (Steneck et al., 2002, 2004), and the abandonment of many coastal and oceanic fisheries (Dulvy et al., 2004b, 2006; Jennings and Kaiser, 1998; Pauly et al., 2002; Roberts, 2002, 2003; Worm et al., 2006). Indeed, despite having sometimes wide geographic distributions and unique regional histories, many marine systems have experienced long periods of slow degradation followed by rapid acceleration in collapse of the biological communities they support (Lotze et al., 2006). This has been largely attributed to the global colonisation by European nations and then the subsequent increase in industrial fishing efficiency (Christensen et al., 2003; Mullon et al., 2005; Roberts, 2003). These rapid changes since the 1950s have been scrutinised intensely over the past decade (Essington et al., 2006; Hilborn et al., 2003; Hutchings, 2000; Hutchings and Reynolds, 2004; Jackson et al., 2001; Jennings and Kaiser, 1998; Myers and Worm, 2003, 2005) to the extent that the sustainability of current and future fisheries is now seriously called into question (Pauly et al., 1998, 2002; Roberts, 2002). The total world catch from wild marine stocks has increased from 19.3 million tonnes in 1950, peaking in 2000 at 86.4 million tonnes and then slightly declining to 84.5 million tonnes in 2004 (Food and Agriculture Organization of the United Nations, 2005). The majority of the world’s fish stocks have been as intensively fished as deemed possible, even to the extent that target populations have been severely reduced and many fisheries have been abandoned (Hilborn et al., 2003). One of the most infamous examples of such depletions is that of Atlantic cod (Gadus morhua) (Hutchings, 1996; Myers et al., 1997); and examples of fisheries abandonment include those

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targeting whales (Baker and Clapham, 2004) and herring (Engelhard and Heino, 2004). These have most often been associated with decline in abundance across entire species’ ranges, or a decreased reproductive capacity through the excessive removal of large, mature females (McIntyre and Hutchings, 2003; Scott et al., 1999) or immature stages (Hutchings and Myers, 1994; Myers et al., 1997). Population declines have also had a number of ripple effects including changes to ecosystems and shifts in fishing to other economically lucrative target species. For example, once cod stocks declined around Newfoundland, the shellfish (shrimp, lobster and crab) populations increased substantially due to a reduction of predators (Bundy, 2001; Worm and Myers, 2003). For mixed-species fisheries, it has commonly been seen through time series of harvesting that population reductions occur selectively for larger individuals first, causing a decline in the size of individuals caught (Jackson et al., 2001; Pitcher, 2001) before leading to an overall decline in catches. This results in smaller species being caught, with the fishery remaining economically viable only because there is a shifting focus towards species lower down the food web (Jennings et al., 1999; Pauly and Palomares, 2005; Pauly et al., 2001). Fisheries harvests are linked to the majority of recorded marine extinctions; around 55% of 133 extinctions have been attributed principally to direct and indirect harvesting by industrial fisheries (HiltonTaylor, 2000; Lotze et al., 2006; Roberts, 2002). Of course, a large proportion has been initiated by subsistence, artisanal and recreational fishing, but these have generally been responsible for local and regional, rather than range-wide extinctions (Dulvy et al., 2003). Physical changes that largely degrade fish habitats can result from either natural sources (e.g. severe storms—Cheal et al., 2004; Kaufman, 1983; earthquakes—Noerenberg, 1971; freshwater inputs and disease—Dulvy et al., 2003) or anthropogenic sources (e.g. land reclamation, coastal development, alteration of freshwater flow and other habitat destruction). Such natural changes can compound the severity of population declines arising from fisheries exploitation. The effects of habitat change will usually alter the abundance and distribution of affected species, and can act differently on different age or developmental groups. These effects can also be locationand species-specific, typically affecting critical habitat requirements (e.g. nursery areas), meaning that attributing observed declines to particular sources can be difficult. Furthermore, the amount of habitat change is mostly related to proximity to land and to human population pressures. Therefore, freshwater and estuarine species are predicted to receive the greatest threats (Musick et al., 2000b). The effects of pollution are closely related to, and often found in association with, other habitat changes. Common pollutants include sewage effluent, organic and inorganic compounds, heavy metals and nutrients that potentially affect all trophic levels. Other biological threats include introduced species, parasites and disease.

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Introduced organisms can outcompete or eat native prey, or they can act as vectors for the transmission of diseases and parasites, thus increasing extinction risk (Dulvy et al., 2003). This risk is further heightened as climate change and other habitat degradation provide more suitable habitats for invading non-indigenous species (Harvell et al., 1999; Ruiz et al., 2000). One taxonomic group of marine fishes that has come under increasing scrutiny in terms of extinction risk from these processes is Chondrichthyes (sharks, rays and chimaeras). These species are typically large predators in all major marine systems and have life history strategies that are likely to predispose them to extinction under rapid environmental change. Chondrichthyan fishes are subject to the range of human-derived threats, from targeted and indirect fishing pressure to other impacts (e.g. habitat change and pollution) across their entire range (Cadet et al., 2003; Cheung et al., 2007; Dulvy et al., 2008; Ferriti et al., 2008; Garcı´a et al., 2008; Stevens et al., 2000, 2005; Walker, 1998). But are chondrichthyans any more or less susceptible to rapid environmental change than other marine biota? We explore this complex question by describing the life history strategies adopted by chondrichthyans in relation to the different threats they face today.

1.1. Aims The overall aim of this chapter is to review the available evidence for and against the posited higher susceptibility of marine shark populations to threatening processes, relate this to other fish taxa that are conservationlisted, and identify areas (regional and topical) requiring more knowledge in this regard. We also tackle the question of whether chondrichthyans should be treated as a specific case in fisheries research and management, or whether they respond in much the same way as all other marine taxa challenged with the additional pressure imposed by human activities. It is not our intention to provide an exhaustive review of all chondrichthyan fisheries (target, by-catch or otherwise) (for some reviews, see Camhi et al., 1998; Fowler et al., 2005; Garcia and de Leiva Moreno, 2003; Hilborn et al., 2003; Kroese and Sauer, 1998; Mullon et al., 2005; Rose, 1996; Sims, 2008; Stevens et al., 2000; Walker, 1998); rather, we contextualise the current extinction risk within this taxon with respect to one of its principal sources of mortality by highlighting specific fishery examples. Nor is our goal to provide a complete overview of chondrichthyan life history (see Cailliet et al., 2005; Compagno, 1990; Corte´s, 2000; Dodd, 1983; Frisk et al., 2001; Smith et al., 1998; Wourms, 1977 for more comprehensive compilations and reviews); our coverage of ecological, life history and human-relationship traits is undertaken to examine the relative susceptibility of this taxon to particular extinction drivers. Specifically, our review encompasses five main, inter-related topics: (1) a description and discussion of chondrichthyan life history traits that are thought to predispose species within this taxon

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to population declines and possible extinction; (2) a broadly comprehensive review of the past and present threats faced by sharks and rays; (3) a quantification of threat risks faced by chondrichthyan and teleost species based on correlations of World Conservation Union (IUCN) Red List categories (www.iucnredlist.org) and a series of life history, ecological and human-relationship attributes; (4) an overview of the ecosystem role of chondrichthyans as predators and implications of their loss to marine biological communities and (5) an appraisal of the future of chondrichthyan species richness and abundance, with emphasis on research priorities.

2. Chondrichthyan Life History Chondrichthyes are cartilaginous fish that include sharks and rays (Class Elasmobranchii) and chimaeras (Class Holocephalii) (for a detailed review of current classification, see Compagno et al., 2005). Modern chondrichthyans are derived from over 400 million years of evolution (Compagno, 1990), and there are presently thought to be over 1100 species (Compagno et al., 2005). However, not all species have been described, and there are new species being described regularly. For examples of recent new descriptions, see Last et al. (2008). The taxon has survived and re-radiated after two major mass extinction periods: the Permian–Triassic and Cretaceous–Tertiary transitions (Carroll, 1988). Although chondrichthyans are generally large in size compared to the average teleost (Compagno, 1981), their historically low economic value to fisheries (see Section 3.1) has stymied the impetus to collect information describing their biology, ecology and role in ecosystem dynamics (Cailliet et al., 2005). At present there is a paucity of essential biological parameters required for both conservation and resource management, with the information currently available derived largely from commercially important or bycatch species (Cailliet et al., 2005; Walker, 1998; Wood et al., 2007).

2.1. Niche breadth Chondrichthyans are found throughout all of the world’s oceans (Compagno, 1990), although they essentially adopt a single trophic mode—predation—and have radiated to fill a range of habitat types. Around 50% of extant species live in coastal and shelf waters (to around 200 m), 35% in deeper water (200–2000 m), and the rest are either oceanic (5%), live in freshwater (5%) or occur within several of these habitats (5%) (Compagno, 1990; Compagno et al., 2005). Although some are obligate freshwater species (35 species), we focus on marine species that live either partially or totally in the marine environment. Within these habitats, some have wide distributions, while others are endemic to specific habitats.

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They also have a range of foraging niches including benthic or pelagic specialisation such as whitetip reef sharks Triaenodon obesus (Stevens, 1984) and salmon sharks Lamna ditropis (Kubodera et al., 2007), respectively. Some are opportunistic predators (e.g. tiger sharks Galeocerdo cuvier— Simpfendorfer et al., 2001), and other are the ocean’s largest filter feeders (e.g. basking sharks Cetorhinus maximus—Sims, 2008). During their evolution, chondrichthyans have adopted alternative life histories from that of most other marine fishes (Compagno, 1990; Holden, 1974). The general category into which these life histories fall has been summarised as ‘K-selected’ (Corte´s, 2002; Fowler et al., 2005) where individuals are long-lived, slow-growing and late-maturing, and have low production and low mortality rates (Cailliet et al., 2005; Musick et al., 2000a; Stevens et al., 2000), although there are a few exceptions, such as spot-tail Carcharhinus sorrah and sharpnose Rhizoprionodon taylori sharks (Simpfendorfer, 1999; Stevens and Wiley, 1986). There is now a general consensus in the literature that these traits, in combination with their main role as predators (Camhi et al., 1998), make chondrichthyan populations highly susceptible to over-exploitation (Corte´s, 2002; Fowler et al., 2005).

2.2. Age and growth The measurement of growth, survival and reproductive potential can provide important information on rates of population change (Hilborn and Walters, 2001; Sinclair et al., 2006; Walters and Martell, 2004), and ultimately risk of extinction (Dulvy and Reynolds, 2002; Hutchings, 2002; Reynolds et al., 2005; Smith et al., 1998). Various methods have been used to calculate or estimate age in chondrichthyans, including measurement of growth bands in vertebrae or other hard structures, bomb carbon dating, tag recapture and captive growth experiments (Cailliet and Goldman, 2004). Some species live >50 years (Beamish and McFarlane, 1987; Bradshaw et al., 2007; Pauly, 2002; Wintner, 2000). Age and growth patterns have been validated for around 120 species (Cailliet and Goldman, 2004; Haddon, 2001) and show a wide range of growth coefficients from ‘slow-growing’ species such as Leucoraja ocella [K ¼ 0.06 (von Bertalanffy growth constant); Sulikowski et al., 2003] to relatively rapid-growing species like C. sorrah (K ¼ 1.17; Davenport and Stevens, 1988). Chondrichthyans also vary widely in age at maturity (Cailliet and Goldman, 2004), from 1 year in the brown smoothhound shark (Mustelus henlei) that can live up to 13 years (Yudin and Cailliet, 1990), to bull sharks (Carcharhinus leucas) that can live for >32 years and not reach sexual maturity until 13 years (Wintner et al., 2002). The distribution of the age at maturity among species appears bimodal, with one peak at 5–6 years and second at 15–25 years (Cailliet and Goldman, 2004). Growth rates also vary extensively within species depending on local water temperature and productivity (Barker et al., 2005; Francis, 1997).

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2.3. Reproduction and survival Chondrichthyan reproduction has evolved to be specialised and highly efficient (Carrier et al., 2004). It generally involves considerable parental investment to produce relatively few large, well-developed young that have a high natural probability of survival (Hamlett and Koob, 1999; Holden, 1974). This is in contrast to teleost fishes that typically produce thousands to tens of millions of tiny eggs annually, although only a few young survive to maturity. This is primarily due to density feedback mechanisms that permit increasing fertility and juvenile survival to compensate for adult population decline (Hilborn and Walters, 2001). Chondrichthyan reproductive parameters are still relatively unquantified for most species although there have been a number of detailed reviews (Budker, 1958; Carrier et al., 2004; Dodd, 1983; Wourms, 1977). Chondrichthyan reproductive strategies tend to proceed along a single path, with all species having internal fertilisation. However, there is still a large diversity among chondrichthyans in terms of egg production, ovulation cycle, gestation period and mating systems (Carrier et al., 2004). Once fertilisation has occurred females retain the eggs during the most vulnerable stages of development. Although energy-expensive, the production of welldeveloped embryos with access to energy reserves allows for highly efficient energy transfer from mother to offspring. Depending on how long embryos are retained, chondrichthyan species are divided into oviparous (egg-laying) and viviparous (live-bearing) forms (Carrier et al., 2004). Oviparous species retain their eggs for a short time and then deposit or attach the eggs to benthic structures. The embryos continue to develop by consuming a yolk sac within the egg case and then hatch fully developed. Viviparous species will retain their embryos internally in one of the five uteri. There are various forms of vivipary employed. These include placental vivipary where the embryo is attached by a placenta, ovovivipary where the development of unattached embryos within the uterus is sustained by food supplied by large egg yolks; oophagy where embryos ingest infertile eggs; embryophagy where embryos consume smaller embryos; and hysteritrophy where fluids secreted by the uterus sustain the embryo. Depending on the species, females can bear from one or two young in sand tiger sharks Carcharias taurus and manta rays Manta birostris (Robins and Ray, 1986; Springer, 1948), to 300 young in whale sharks Rhincodon typus ( Joung et al., 1996). Gestation rates are unknown for most species, but measured times range from around 3 months for Dasyatis sp. rays (Hamlett and Koob, 1999) to more than 22 months for the ovoviviparous spiny dogfish which has the longest gestation period known for any living marine vertebrate (Pratt and Casey, 1990). Breeding does not always occur annually in females and some species have one or more ‘resting’ years between pregnancies.

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Following their high initial investment in pup production, many sharks and rays subsequently give birth in sheltered coastal or estuarine nursery areas where predation risk to pups (primarily from other sharks) is presumably reduced (Branstetter, 1990). Other species deposit eggs in locations where they are most likely to survive undamaged until the pups emerge. There is no known post-birth parental care. Nevertheless, it is thought that most chondrichthyans have relatively low natural mortality compared to teleosts (e.g. Bradshaw et al., 2007; Corte´s and Parsons, 1996; Grant et al., 1979; Gruber et al., 2001; Heupel and Simpfendorfer, 2002; Walker and Hislop, 1998; Waring, 1984). Recently, there has been an increase in the development and use of demographic and population models to describe and predict the status of chondrichthyan populations (Corte´s, 2007). Modelling approaches range from empirically derived age-based demographic models to recruitment models used to estimate survival and productivity, or to characterise vulnerability to exploitation (e.g. Au and Smith, 1997; Corte´s, 1995, 2002; Frisk et al., 2001, 2005; Gruber et al., 2001; McAuley et al., 2007; Punt and Walker, 1998; Simpfendorfer, 1999; Sminkey and Musick, 1996; Smith et al., 1998; Walker, 1992; Xiao and Walker, 2000).

3. Past and Present Threats Harvest of shark and ray populations has been proposed as the current greatest threat to their diversity and abundance, with risk from commercial and industrial fisheries far out-weighing that of artisanal and subsistence harvests (Baum et al., 2003; Dulvy, 2006; Dulvy and Reynolds, 2002; Dulvy et al., 2008; Garcı´a et al., 2008; Robbins et al., 2006; Stevens et al., 2005; Worm et al., 2005). In comparison, the effects of habitat change and degradation, pollution and invasive species on this taxon are poorly understood (Stevens et al., 2000). In this section, we provide an overview of current and past fishing effects on shark populations by industrial fishing, within single and mixed-species fisheries, by targeted or indirect harvesting, as by-catch in fisheries directed to other species and other threats including beach meshing, habitat loss and pollution.

3.1. Fishing Chondrichthyans are a diverse taxonomic group that have radiated into specialised and opportunistic top predators. Whether chondrichthyan fisheries are sustainable has been debated and reviewed extensively over the last three decades (Holden, 1973; Stevens et al., 2000; Walker, 1998). Over the last decade or so in particular, there has been much controversy regarding

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the causes of collapsing fisheries (Hutchings and Reynolds, 2004; Myers and Worm, 2005; Reynolds et al., 2005) and the global state of shark populations (Baum et al., 2005; Burgess et al., 2005a; Dulvy et al., 2008; Ferriti et al., 2008; Robbins et al., 2006; Stevens et al., 2000; Walker, 1998). There has also been much discussion and supposition regarding the impact of shark and ray removal on the marine ecosystems that support them (Coll et al., 2006; Jackson et al., 2001; Stevens et al., 2000; Ward and Myers, 2005; Worm et al., 2006). Some have gone so far as to suggest that many of the world’s shark populations are teetering on the brink of extinction, with catastrophic ecosystem change predicted as the logical corollary (Baum et al., 2003; Myers and Worm, 2003; Worm et al., 2006). Although there is some support for this contention (Aires-da-Silva et al., 2008; Simpfendorfer et al., 2002) others strongly disagree with this outlook, and identify problems in data quality and interpretation (Burgess et al., 2005a,b; Hampton et al., 2005; Hilborn, 2007; Polacheck, 2006; Walters, 2003), and the use of other data sources (Sibert et al., 2006) (see also Section 3.1.3.2). The debate thus far has been confined mainly to large pelagic fisheries, but there is increasing concern for deepwater species living in presumably relatively stable environments that have already become subject to new and increasing exploitation as pelagic and coastal fisheries fail to meet the economic demand for fish products (Camhi et al., 1998; Garcı´a et al., 2008; Roberts, 2002). Furthermore, local fishing has also been suggested as the main driver for population reductions in and around conservation areas (Robbins et al., 2006), which highlights a number of management difficulties associated with the design and implementation of marine protected areas. The global catch of chondrichthyans (including sharks, rays and chimaeras—Fig. 4.1) has increased from approximately 270,000 tonnes in the 1950s to around 810,000 tonnes in 2004, with a peak catch of 881,000 tonnes in 2003 (Food and Agriculture Organization of the United Nations, 2005). This accounts for approximately 1% of the current total landings of all marine fish (Food and Agriculture Organization of the United Nations, 2005). The greatest period of increase during that time was between the 1960s and 1970s when catches rose by 40%. More recently, from 1996 to 2004, the annual catch has exceeded 800,000 tonnes. FAO fishery statistics show that in 2004, 20 countries shared over 75% of the total catch, with Indonesia (15%), India (7.5%), Spain (6.5%), Taiwan (5.5%) and Mexico (4%) sharing approximately 40% of the total catch (Food and Agriculture Organization of the United Nations, 2005) (Fig. 4.2). The current status of regional fisheries harvesting chondrichthyans are reviewed in greater detail by Fowler and Cavanagh (2005). However, recent research has indicated large potential errors in FAO reporting based on market estimates of shark fins (Clarke et al., 2006), from which global fin trade is estimated to be up to four times higher.

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Figure 4.1 Examples of legal and illegal harvest of sharks. (A) Blue sharks (Prionace glauca) being landed at a port in Portugal (photo credit: N. Queiroz, CIBIO, Portugal, and the Marine Biological Association of the UK). (B) Dried shark fins (unidentified species) confiscated by the Australian Customs Service from an illegal fishing boat found within the Australian Fishing Zone in the Arafura Sea (photo credit: M. G. Meekan, Australian Institute of Marine Science). (C) Whole shark carcasses (mainly silky sharks Carcharhinus falciformis, blue sharks and dusky sharks Carcharhinus obscurus) (photo credit: W. White, Commonwealth Scientific and Industrial Research Organisation, Australia).

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These catches deliver products to a global and growing market for their meat, fins, cartilage, skin (leather), oil, teeth, gill rakers and jaws (Rose, 1996). Unfortunately, records of how and in what quantities these resources are used are poor, and for most catches they are entirely unquantified. Fresh shark meat is consumed locally near landing ports, but due to the need for expedient processing and cold storage it has little export value relative to most teleost fisheries (Camhi et al., 1998). On the other hand, dried shark meat and fins are easily processed and supply distant markets (Fig. 4.1). This has led to a large demand that has continued to grow since the mid-1980s, especially for dried fin that is the main ingredient in popular Asian soups (Clarke et al., 2006; Marshall and Barnett, 1997; Rose, 1996). The biological and social effects of fishing exploitation are well documented (Dulvy et al., 2000, 2004b; Hawkins and Roberts, 2004; Hutchings and Reynolds, 2004; Jackson et al., 2001; Jennings and Kaiser, 1998; Jennings et al., 1999; Kitchell et al., 2002; Pauly and Palomares, 2005; Robbins et al., 2006; Stevens et al., 2000; Worm et al., 2006). In addition to the obvious reduction in abundance brought about by unsustainable harvesting, chondrichthyan species might also experience changes to their life history traits (e.g. age at maturity and size distribution) and demography following harvest (Frisk et al., 2005; Stevens and Davenport, 1991). Currently, it is thought that sustainable and economically viable shark and ray fisheries can be maintained if carefully managed, especially for species with relatively high productivity rates (Walker, 1998) such as gummy (Mustelus antarcticus) and blue sharks (Prionace glauca) (Fig. 4.1). Presently, both industrial and small-scale commercial operations frequently raise concern regarding their sustainability, and with an increased demand for shark fin products it has been suggested that shark and ray catches are in reality three to four times higher than those reported (Clarke et al., 2006). This highlights the potential threats from illegal, unreported and unmanaged (IUU) fishing (see Section 3.1.4). It is worth noting that most industrial shark fisheries are unmanaged with the exception of those from a few countries such as Australia, New Zealand, Canada and USA (Fowler et al., 2005). 3.1.1. Definitions From the perspective of providing objective insight into the global status of harvested chondrichthyans and to place this deterministic driver of population reduction into the context of extinction biology, we must be clear about what we mean by ‘extinction’. In his classic paper, Caughley (1994) differentiated the two main paradigms in conservation biology that are still relevant today: (1) the declining population paradigm, which refers to factors that depress the demographic rates of a species and cause its population to decline, and (2) the small-population paradigm, which refers to small populations that have already declined due to some (deterministic) perturbation and are thus more susceptible than large populations to extinction via

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chance events. This distinction is important because semantic labelling of a fishery’s status, with similar terms used with different meanings, does not necessarily indicate heightened extinction risk. A large number of individuals are typically required to ensure that a species will persist with high certainty, given the substantial evidence demonstrating that small and isolated populations are most vulnerable to extinction (Berger, 1990; Brook et al., 2002; Spielman et al., 2004). Small populations have a relatively higher extinction risk than large populations for three main reasons. Firstly, due to demographic fluctuations resulting from random variation in survival and fertility. Secondly, through environmental variation in resource or habitat availability and quality, competitive interactions or predation, and catastrophic mortality events (e.g. disease epidemics, severe storms). Finally, with decreasing genetic heterozygosity, inbreeding depression and genetic drift (Gilpin and Soule´, 1986; Shaffer, 1981), the eventual fate of all closed, finite populations is extinction through genetic erosion (Frankham et al., 2004). As populations decline they become more susceptible to demographic variance in vital rates, stochastic variation in environmental conditions, Allee effects, inbreeding depression and loss of genetic diversity (Caughley, 1994; Frankham, 1995; Melbourne and Hastings, 2008; Traill et al., 2009). A minimum viable population (MVP) size is defined as the smallest abundance required for an isolated population to persist at a defined ‘high’ probability (usually set at >95%) for some (mostly arbitrary) set period into the future (Shaffer, 1981; typically 100 years or 40 generations—Traill et al., 2007). Population-specific MVP sizes can be estimated empirically using population viability analyses (PVA) that calculate the probability of an initial population persisting in spite of demographic, environmental and genetic stochasticity and natural catastrophes (Shaffer, 1981). PVA models can be constructed by empirical simulation, experiments or long-term monitoring (Traill et al., 2009); however, such models generally require good demographic and/or census data to provide reliable estimates (Traill et al., 2007). Other MVP methods use genetic data to estimate the minimum population size that will maintain evolutionary potential—the population size required at equilibrium to balance the loss of quantitative genetic variation with the gain from mutation (Franklin and Frankham, 1998). Once a fishery (or some other deterministic driver) reduces a population to below its MVP size (Shaffer, 1981), then the reduced population becomes subject to a host of population-specific threats, most of which are stochastic (Traill et al., 2007). This important concept appears to have had little adoption or tractability in fisheries science, perhaps mainly because so few chondrichthyans have associated good census or demographic data. As an example, the spiny dogfish (Squalus acanthias) has declined by >78% in the north-eastern Atlantic in about three generations, which is sufficient to warrant Endangered

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status under the IUCN’s Category A. Yet the entire population of S. acanthias numbers in the millions (Reynolds et al., 2005), which exceeds all cross-taxonomic estimates of MVP size (Traill et al., 2007, 2009). Therefore, this species, and perhaps many other chondrichthyans that have declined due to fishing harvest (Reynolds et al., 2005) still have a relatively low risk of extinction. Instead, the fisheries literature is replete with subjective terms that are used to refer to a fished population’s status, with little differentiation between local, global, biological and economic ‘extinction’. Terms such as ‘over-exploited’, ‘over-harvested’, ‘depleted’ and ‘collapsed’ are often only arbitrarily or not explicitly defined, so confusion is common (Hilborn, 2007; Jennings, 2007). For example, a fishery has been labelled ‘collapsed’ when its catch in any year falls below 10% of the highest recorded catch (Worm et al., 2006), yet this definition is uncoupled from the concept of distance to a population’s MVP. Likewise, terms adopted by the FAO like ‘depleted’ are reserved to describe the point at which harvest rate exceeds the maximum biological productivity (or maximum sustainable yield, MSY; Fig. 4.3), but this relationship depends on the underlying model chosen to represent the relationship between population rate of change and density (Fig. 4.4), which can vary considerably and is rarely evaluated specifically (Bradshaw, 2008; Brook and Bradshaw, 2006). The term ‘collapse’ has been defined loosely as when high catches continue for some time after ‘depletion’ has occurred, usually followed by low catch rates and abandonment of the particular fishery (Cooke, 1984), with some definitions based again on arbitrarily set magnitudes of decline (e.g. >90% relative to baseline abundance; Worm et al., 2006). This is a result of socio-economic factors related to profitability (Hilborn et al., 2003; Musick, 2005). Even the word ‘extinction’ can have different meanings. ‘Local’ or ‘population’ extinction is often referred to as ‘extirpation’. This differs from ‘global’ extinction in that only a proportion of the total number of individuals of that species is removed, usually, a sub-population that is geographically or genetically distinct from others (Sodhi et al., 2007). This is further complicated because it is nearly impossible to observe local extinctions directly, especially in the marine environment where most species’ behaviours go unnoticed. Thus extinctions can only be truly determined from successive surveys that fail to identify a species’ presence (Fagan and Holmes, 2006; Sodhi et al., 2007). There are also a number of alternative methods can be used to infer extinction including correlative approaches based on life history and ecological information, time-series to estimate changes in abundance; or demographic analyses based on age- or stage-structured models of vital rates (Dulvy et al., 2004a). These approaches all focus on individual species. Extirpations can change the local biological community (see Section 5), or lead to trophic replacements ( Jackson et al., 2001). Local extinctions can

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Figure 4.3 The classic trade-off between recruitment and fishing rate (F) showing the fishing rate where maximum biological productivity (Mb) occurs, also known as maximum sustainable yield (MSY). Also shown is the fishing rate where economic benefit (Me) is maximised, which is inferior to Mb because it takes into consideration the long-term sustainability of the fishery (i.e. sustained fishing at Mb will tend to result in long-term declines in catch rates) (Hilborn and Walters, 2001).

also lead to increased fragmentation and genetic isolation, which are known to increase extinction risk especially for weakly dispersing and specialist species (Brook et al., 2008; Purvis et al., 2000b). Another concern for rangerestricted species is density depensation, or Allee effects, that cause a reduction in the growth rate of small populations as they decline via reduced survival or reproductive success (Courchamp et al., 2008; Mullon et al., 2005). We want to avoid potentially subjective terms ( Jennings, 2007) and focus instead on how deterministic decline due to harvesting can change chondrichthyan susceptibility to extinction. In the following sections, we document several chondrichthyan fisheries with the view to assess the degree of population decline that could lead to higher extinction risk. 3.1.2. Targeted fisheries Commercial fisheries targeting sharks started as early as the late eighteenth century, with basking sharks (C. maximus) being the earliest-known target species (McNally, 1976). Although this fishery started from artisanal operations, it grew quickly in response to increasing consumer demand (McNally, 1976). From the 1920s, commercial fisheries targeting sharks grew steadily (Bonfil, 1994; Gauld, 1989), with overall shark landings

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Figure 4.4 A simple linear relationship between the rate of population change (r ¼ loge(Ntþ1/Nt)), and measure of abundance (logeN or catch-per-unit-effort, CPUE) and fishing rate (F). This particular population dynamical model represents the classic logistic rise to an environmentally determined (temporally averaged) carrying capacity and has formed the basis for fisheries models for the past 50 years (e.g. Beverton and Holt 1957, 1993; Fox, 1970); however, many non-linear forms of the relationship between r and N exist and should also be considered when the true relationship is unknown (Bradshaw, 2008; Brook and Bradshaw, 2006; Turchin, 2003).

increasing by 2% each year since 1985 (Food and Agriculture Organization of the United Nations, 2005). More recently, directed shark fisheries have clearly reduced target population sizes. These fisheries usually focus on one or two primary species and are often managed using conventional single-species modelling approaches. It has been suggested that shark populations can withstand only modest levels of fishing without large reductions in population size (Camhi et al., 1998; Corte´s, 2000; Musick, 1999b; Musick et al., 2000a). Brief periods of high harvest rates are usually followed by severe declines in catch rates in fished shark populations (Camhi et al., 1998), usually associated with a fishery’s closure and a long, slow period of recovery, or continued low catches at a fraction of those obtained during the initial period (Gauld, 1989; Hurley, 1998; Schindler et al., 2002; Sminkey and Musick, 1996). Due to this predominant historical pattern, intensive and careful management is recommended at the inception of any shark fishery (Musick et al., 2000a). However, the majority of shark fisheries (e.g. see Kroese and Sauer, 1998) are unmanaged (Walker, 1998). These are likely to cause rapid population

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declines (Bonfil, 1994), with slow or little recovery, or fishery abandonment due to economic or market constraints (Musick, 2005). Although many shark species and their fisheries have traditionally been of low economic value compared to dedicated teleost fisheries, the economic impact of population reductions can be similar because recovery time and associated economic downturns usually last much longer (Musick and Bonfil, 2005). Often-cited examples of reduced or abandoned shark fisheries are the various basking shark fisheries (Anonymous, 2002; Kunzlik, 1988; Parker and Stott, 1965), the porbeagle shark (Lamna nasus) fishery in the Northeast Atlantic (Department of Fisheries and Oceans, 2001; Gauld, 1989), the tope or ‘soupfin’ shark (Galeorhinus galeus) fisheries off California and Australia (Olsen, 1959, 1984; Ripley, 1946; Walker et al., 1995) and the spiny dogfish (S. acanthias) fisheries in the North Sea and off British Columbia, Canada (Anderson, 1990) (Fig. 4.5). Although the history and status of targeted shark fisheries are reviewed in detail elsewhere (Camhi et al., 1998; Fowler et al., 2005), we have provided a brief overview of examples of both abandoned and apparently sustainable shark fisheries below. 3.1.2.1. Basking shark C. maximus Dedicated fishing for basking sharks has been noted across northern Europe since the mid-1700s (International Council for the Exploration of the Sea, 2007), with the oldest confirmed fishery records available from west Ireland in the late eighteenth century. This was most likely an artisanal net fishery spanning several decades and becoming a commercial enterprise with rising demand for shark liver oil. This led to notably large declines by 1830 and fishery abandonment in the second half of the nineteenth century. Basking sharks were not targeted again until 1947, at which point a new localised fishery started near Achill Island (Ireland), where 900–1800 sharks were taken each year from 1950 to 1956 (Fig. 4.5). Catches started to decline after 1955, from 1067 per year between 1949 and 1958, to 119 per year between 1959 and 1968, and then to 40 per year for the remaining 7 years of the fishery that ended in 1975. Toward the end of the fishery, even increasing shark oil prices and capital investment did not reverse the steady decline in catches. A total of 12,360 individual fish were caught over the life of the fishery, with 75% caught in the first 6 years (McNally, 1976). Today, basking sharks are often sighted around shelf fronts, although total population sizes are unknown (Sims, 2008; Sims and Quayle, 1998; Sims et al., 2005). Over the same period as the Irish fishery and beyond its end, a Norwegian fleet was also fishing for basking sharks over a large area of the northeast Atlantic. Catches were high (>1000 sharks per year, and >4000 in some years) between 1959 and 1980. Since 1981, landings have declined and not exceeded 1000 sharks per year (Kunzlik, 1988). This decline has been attributed to an ageing fleet, a decline in value of basking shark liver oil (Kunzlik, 1988), or possibly a change in the species’ distribution to areas of higher productivity (Sims and

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Figure 4.5 Location of fisheries and target chondrichthyan species mentioned in the text (coverage is not intended to be inclusive of all shark fisheries). (1) Blue shark Prionace glauca high-seas fisheries; (2) tope, school or ‘soupfin’ shark Galeorhinus galeus fisheries off California, southeastern Australia and New Zealand; (3, 4) Gulf of Mexico and south-eastern USA coastal and pelagic shark fisheries (including dusky Carcharhinus obscurus, sandtiger Odontaspis taurus, oceanic whitetip Carcharhinus longimanus, sandbar Carcharhinus plumbeus, silky Carcharhinus falciformis, great white Carcharodon carcharias, hammerhead Sphyrna lewini, S. mokarran and S. zygaena, thresher Alopias vulpinus and A. superciliousus, short-fin mako Isurus oxyrinchus, and tiger sharks Galeocerdo cuvieri); (5) barndoor skate Dipturus laevis off New England and Canada in the western Atlantic ground fishery; (6) basking shark Cetorhinus maximus fisheries in the north-eastern Atlantic; (7) Irish Sea common skate Dipturus batis fishery; (8) porbeagle Lamna nasus fishery in the North Atlantic; (9) angel shark Squatina squatina in United Kingdom waters; (10) blacktip Carcharinus tilstoni and C. limbatus and spot-tail C. sorrah shark fishery in the Arafura-Timor Seas, northern Australia; (11) gummy shark Mustelus antarcticus catches increasing to offset declines in school shark catches in south-eastern Australia; (12) grey nurse shark Carcharias taurus rapid decline in eastern Australia due to spear-fishing, recreational fishing by-catch, commercial by-catch and beach meshing. Bold numbers and zone demarcations refer to Food and Agriculture Organization of the United Nations (FAO) Fishing Areas (www.fao.org).

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Reid, 2002). Overall in the north-eastern Atlantic between 1946 and 1997, including the target fishery in Scottish waters, records indicate 105,730 basking sharks were captured and traded (Sims, 2008). However, due to a large fishing area and location uncertainty, it has been difficult to detect and evaluate temporal trends in the catch data. Since 1978, management of basking shark fishing in European Community waters (UK and Ireland) has been by a total allowable catch quota system initially set at 400 tonnes, but now the quota has been reduced to zero (Sims et al., 2005). There still appears to be incentive to continue the fishery due to the high prices paid for large basking shark fins in Singapore (Camhi et al., 1998) and other Asian markets. 3.1.2.2. Tope, school or soupfin shark G. galeus Although there are numerous fisheries for tope (‘school’ or ‘soupfin’ shark) around the world, the most infamous fishery occurred off the Californian coast in the early to mid-1900s (Holden, 1974; Ripley, 1946; Fig. 4.5). The fishery only lasted 8 years and was abandoned in the mid-1940s (Ripley, 1946). It is still uncertain whether populations have recovered more than 50 years later (Camhi et al., 1998). Shark landings from 1930 to 1936, of which tope comprised a high proportion (around 80%), were relatively low and stable at around 270 tonnes per year. The fishery then expanded enormously following the establishment of a new market for liver oil in 1937, with catches peaking at 4185 tonnes in 1939. This new market demand also pushed prices from some US $50 per tonne in 1937 to US $2000 per tonne in 1941. Tope landings were declared independently of the general take from 1941, with annual declines from 2172 tonnes in 1941 to 287 tonnes in 1944. Catch-per-unit-effort (CPUE) in one region declined from 34.4 fish/1000 m of gillnet fished for 20 h in 1942, to 4.8 fish/1000 m/20 h in 1945 (Roedel and Ripley, 1950). Not all targeted G. galeus fisheries have caused large population declines. In southeast Australia (Fig. 4.5), exploitation of school sharks began in the 1920s, but production increased greatly during the war years. Catches reached 2000 tonnes live weight in 1949 (Walker et al., 1995) due to demand for shark liver oil. Catches remained relatively high between 1949 and 1957 as the fishery spread from inshore to offshore waters (Olsen, 1959; Walker et al., 1995). In 1964, decline of the liver oil market led to development of the shark meat market and a switch to gillnetting. This new market allowed production to increase rapidly, peaking in 1969 at 3158 tonnes, although the proportion of gummy shark (M. antarcticus) in the catch was also increasing. Following a ban on the sale of large G. galeus in 1972 because of reported high mercury concentration in the meat, catches declined for about 10 years and gummy sharks took over as the principal target species in the fishery (Stevens et al., 1997). With relaxation of mercury laws in the early 1980s, catches again increased, reaching

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3060 tonnes in 1986. However, concerns of population reduction prompted by a measured 84% reduction of mature biomass resulted in the implementation of a dedicated fishery management plan in 1988 (Stevens et al., 1997, 2000) and ongoing research initiatives (Punt and Walker, 1998; Punt et al., 2000; Walker, 1992; Walker et al., 1998). In New Zealand, G. galeus have been harvested since the late 1940s and have followed a similar trend to the Australian fishery. With the demise of the liver oil fishery in the 1950s, a market for the flesh developed with a small export market to Australia. Catches peaked at 5000 tonnes live weight in 1984 (Francis, 1998). 3.1.2.3. Northern Territory, Australia shark fishery Many dedicated shark fisheries tend to be small and target highly productive species (Stevens et al., 2000; Walker, 1998). An example of one such fishery is the north Australian shark fishery in the Northern Territory (Fig. 4.5). This is a small tropical shark fishery with only 13 licences and only 7–9 vessels operating currently. Target species are primarily the Australian blacktip (Carcharhinus tilstoni) and spot-tail sharks (C. sorrah), but frequent switches to teleosts such as grey mackerel (Scomberomorus semifasciatus) occur. A variety of secondary shark species are also caught including tiger (G. cuvier), pigeye (Carcharhinus amboinensis) and hammerhead sharks (Sphyrna spp. and Eusphyra blochii) (Field et al., 2008). The fishery has developed slowly from 1984 to its present management system (Australia Department of Environment and Heritage, 2005) with an annual shark catch that peaked in 2004 at 1089 tonnes (Northern Territory Department of Primary Iindustry Fisheries and Mines, 2005). It has remained relatively stable ever since. An increase in CPUE and in proportional catch of non-primary target species from 2000 to 2003 prompted questions regarding the industry’s future sustainability (Australia Department of Environment and Heritage, 2005). Due to market demand, grey mackerel currently dominates the catch in terms of singlespecies catch, and there has been a reduction in fishing effort to prevent rapid changes or growth of new fisheries enabled by technological advantages (Northern Territory Department of Primary Iindustry Fisheries and Mines, 2005). Research projects to address concerns of sustainability were implemented in 2004 to include stock monitoring (Northern Territory Department of Primary Iindustry Fisheries and Mines, 2005), risk assessment (Pillans, 2007) and observation and tagging studies (Field et al., 2008). As with many shark fisheries, the history of shark harvest in northern Australia is more complex than the current industry’s structure might suggest. From the early 1970s until mid-1986, a Taiwanese pelagic gillnet fleet operated in the waters around northern Australia targeting shark, longtail tuna (Thunnus tonggol) and mackerel (Scomberomorus spp.). Since it was largely unmanaged, the fleet’s extent caused concern (Stevens and Davenport, 1991). The areas accessible to the Taiwanese fleet changed over the course of the fishery’s lifetime following the implementation of

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the Australian Fishing Zone in 1979, limiting it to mainly offshore regions ranging from the North West Shelf to north of the Gulf of Carpentaria (Fig. 4.5). The catch was subsequently reduced from around 17,000 tonnes per year to an annual quota of 7000 tonnes. Before 1980, reporting of catch and effort was limited (Walter, 1981), but afterwards basic catch composition and effort data were collected under Taiwanese and independent logbook programmes. These records indicated that total catch composition by weight was approximately 80% shark, with blacktip (primarily C. tilstoni with an unknown proportion of Carcharhinus limbatus) and spot-tail (C. sorrah) sharks accounting for 60% of the total catch (Stevens and Davenport, 1991). During the early 1980s, fishing effort almost doubled, while CPUE decreased from 16 to 7 kg/km/h (Stevens and Davenport, 1991). Data from the Taiwanese fleet showed some signs of population reduction (Stevens and Davenport, 1991). Other data also indicated age structure changes; length-frequency distributions indicated fewer mature C. tilstoni were caught from 1981 to 1986, and there was also a decrease in the abundance of mature female C. sorrah and a decrease in median size of sharks caught for both C. tilstoni and female C. sorrah. Further restrictions were imposed in 1986, eventually leading to the decision by the Taiwanese to abandon the fishery for economic reasons. However, Taiwanese gillnetting continued outside the Australian Fishing Zone. 3.1.3. Mixed fisheries and by-catch Although directed fishing can have severe effects on target species, possibly the greatest potential threat to chondrichthyans worldwide is indirect harvest, or in mixed-species fisheries where they represent ‘by-catch’ (Bonfil, 1994; Camhi et al., 1998; Musick, 1999b; Stevens et al., 2000, 2005; Walker, 1998). Sharks can be caught incidentally in trawl nets, gillnets, purse seines, and longlines, and mortality from these as by-catch might exceed that from directed fisheries (e.g. oceanic fisheries for tuna and billfishes, Bonfil, 1994; Francis and Griggs, 1997; Polacheck, 1989). In such cases, the fisheries can enter regional or international trade with little or no reporting or tracking of produce. This is of particular concern for smallscale commercial and artisanal fisheries, especially for trade in ‘rare’ species with small population sizes such as sawfishes (Camhi et al., 1998) and possibly basking sharks (Magnussen et al., 2007; Sims, 2008). The two main problems with mixed-species fisheries that catch nontarget species are the (1) low priority and economic value of secondary species catches and (2) limited or no reporting of captured and discarded bycatch species. Such fisheries can generally remain economically viable, at least over the medium term, because the primary species tend to be more productive than secondary species that can eventually sustain large population declines or be driven to extinction (Baum et al., 2003; Casey and Myers, 1998; Essington et al., 2006; Musick, 1999b; Myers and Worm,

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2003; Stevens et al., 2000). Poor catch recording of secondary species in fisheries in domestic and international waters severely limits our capacity to understand and manage by-catch (Alverson et al., 1994; Nakano and Clarke, 2006). Even today most countries do not require by-catch data to be collected. The few data that are collected from either logbooks, landing statistics or observer programmes are limited in coverage, especially for high-seas fisheries, and are generally too imprecise even to identify reliably the species composition of the catch (Dulvy et al., 2000; Nakano and Clarke, 2006). Although some shark by-catch is landed and reported officially, the majority is only estimated. As such, some have argued that bycatch might represent up to 50% of the total worldwide shark catch (Bonfil, 1994). These two components mean that large discrepancies and uncertainty in population trends impair management. Mixed-species fisheries occur across a range of marine habitats, from coastal demersal to open-ocean pelagic regions, although historically deepwater habitats have likely escaped much of the exploitation pressure but are considered especially vulnerable in the future (Garcı´a et al., 2008). The constraints of deepwater fishing might have led to these habitats becoming conservation refuges for many shark species, given that up to 35% of all shark species primarily occupy deepwater habitats (Camhi et al., 1998; Garcı´a et al., 2008; Stevens et al., 2005). Many by-catch species are harvested mainly by trawlers across a broad range of life stages (Stevens et al., 2000), and several examples exist of by-catch chondrichthyans showing signs of moderate to severe population decline. 3.1.3.1. Examples of mixed-species fisheries impacting chondrichthyans In the early 1980s, a severe decline in common skates (Dipturus batis) of the Irish Sea was reported, to the extent that the population was thought to be at the ‘brink of extinction’ (Brander, 1981). More recently, the barndoor skate (Dipturus laevis), a species that is taken as by-catch in the New England and Canadian Atlantic ground fish fisheries, has become the first well-documented example of localised extinction (Casey and Myers, 1998; Fig. 4.5), although non-peer-reviewed reports from Canada and USA concluded the populations have not even been severely reduced (Boelke et al., 2005; Kulka et al., 2002). Other large skate species might be potentially threatened with extinction (Dulvy and Reynolds, 2002), and several other studies have documented reduced diversity in demersal chondrichthyans (Aldebert, 1997; Jukic-Peladic et al., 2001; Rogers and Ellis, 2000). In the northwestern Mediterranean, there has been a clear decline of several shark species commercially captured by trawls due to increased fishing intensity and technological advances in fishing gear. This pattern has also been observed in some coastal areas around the United Kingdom (Fig. 4.5) where trawling has changed demersal fish assemblages by reducing the abundance of large sharks, skates and rays such as D. batis and the angel

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shark Squatina squatina (Rogers and Ellis, 2000). A similar decline in species richness and distribution has been reported for several large shark and rays species in the Adriatic between 1948 and 1998 ( JukicPeladic et al., 2001). Pelagic fisheries using longlines, gillnets and driftnets also pose a large potential threat to chondrichthyans, some of which have been the focus of much research and concern over the last decade. In both the Pacific and Atlantic Oceans there have been large declines in many fish stocks caught in tuna and billfish longline fisheries associated with extensive by-catch (Christensen et al., 2003; Schindler et al., 2002). Pelagic longline fisheries worldwide remove up to 8 million sharks per year, or one-third of the world catch of all sharks and rays (Bonfil, 1994); however, the actual rate could be up to four times higher (Clarke et al., 2006). One of the main by-catch species in the Pacific and Atlantic open-ocean fisheries (Fig. 4.5) is the blue shark (P. glauca) which accounts for around 50% of the total worldwide shark bycatch (Bonfil, 1994; Stevens et al., 2000). This species has relatively high growth and fecundity compared to other chondrichthyans, and so is thought to be relatively resilient to current fishing pressure (Aires-da-Silva and Gallucci, 2007). Prior to the 1980s, there was little demand for blue sharks because of their soft muscle tissue and strong ammonia odour (Walker, 1998). As such, most blue shark by-catch was discarded or returned alive, which acted to reduce fishing mortality (He and Laurs, 1998). With the expansion of the Asian fin market in the 1980s, there was a large increase in the demand for blue shark fins. This led to an increase in finning, the practice of removing the fins from a carcass and discarding the trunk overboard, sometimes with the de-finned shark still alive. Since dried fins do not take up much valuable space in freezers on ships or on land, they represent an economically attractive by-product. In the Hawaiian longline fishery where no sharks were reported being harvested solely for fins prior to 1990, up to 61,000 individual blue sharks were caught and finned in 1998 alone (McCoy and Ishihara, 1999). This increase in dedicated harvest caused population declines from the 1980s onward, although fisheries assessment to determine changes in catch rates have provided conflicting results. For example, it has been estimated that blue shark numbers in the Pacific have declined by 20% between 1982 and 1993, but no such trend was observed in Indian Ocean fisheries and only contrasting evidence of a decline in the Atantic Ocean (Aires-da-Silva et al., 2008; Baum et al., 2003; Nakano, 1996; Nakano and Clarke, 2005). Neither was there a decrease in blue shark catch rates observed in Australian longline fisheries (Stevens and Wayte, 1999). Recently however, these trends have been questioned and there now appears to be evidence of declines (Aires-da-Silva et al., 2008; Baum et al., 2003; Simpfendorfer et al., 2002). Based on fisheryindependent data from 1977 to 1994, Simpfendorfer et al. (2002) found evidence for an 80% decrease in the abundance of male, but not female, blue

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sharks, whereas an analysis of the US North Atlantic catch logbook data concluded an overall 60% decline in catches (Fig. 4.5; Baum et al., 2003). Newer techniques have been used to determine the status of blue sharks (Aires-da-Silva and Gallucci, 2007; Clarke et al., 2006; Schindler et al., 2002; Simpfendorfer et al., 2002) that link life history traits and vital rates to harvest scenarios. These modelling approaches use stochastic age-structured population models to assess population dynamics. By estimating the intrinsic rate of population increase, blue shark populations are at risk of declining once 20% of the original biomass is removed, and juveniles are more at risk if heavily harvested (Aires-da-Silva and Gallucci, 2007). Furthermore, sexual segregation gradients have also been reported for this and other shark species that would exacerbate over-exploitation for some populations (Mucientes et al., 2009). Overall, evidence from market surveys (Clarke et al., 2006) suggests that populations are currently at or just over the MSY for this species. Therefore, the strength of evidence at present shows that most blue shark populations are currently stable; however, some have declined and harvest rates require careful management and monitoring, particularly when there is the possibility of sexual segregation of populations and a likelihood of destabilising population structures (Mucientes et al., 2009). 3.1.3.2. Chondrichthyan decline controversies For other harvested chondrichthyan species caught in coastal and oceanic fisheries, there have been population declines (Aires-da-Silva et al., 2008; Cavanagh, 2005; Corte´s et al., 2002; Musick et al., 1993, 2000b; Simpfendorfer et al., 2002; Stevens et al., 2000). Some studies even suggest that several species are close to extinction (Baum et al., 2003, 2005; Myers and Worm, 2005; Worm et al., 2005). In these cases, the conclusion of high, imminent extinction risk has generated extensive debate (Baum et al., 2005; Burgess et al., 2005a,b), especially with respect to the status of species such as tiger (G. cuvier), great white (Carcharodon carcharias), requiem (Carcharhinus spp.), hammerhead (Sphyrna lewini, Sphyrna mokarran, Sphyrna zygaena), shortfin mako (Isurus oxyrinchus), oceanic whitetip (Carcharhinus longimanus), thresher (Alopias vulpinus and Alopias superciliousus), and porbeagle sharks (L. nasus) (Fig. 4.5). Some of the differences in opinion expressed to date might have arisen in part from competing views of fisheries biologists and conservation ecologists (Hilborn, 2007); however, we attempt in the following to provide a neutral summary of the contentious issues around the reported species declines, to which almost all agree are real, even though the magnitude remains under debate. Although some mention of species decline had been made previously (Corte´s et al., 2002; Musick, 1999a; Musick et al., 1993), it was not until Baum et al. (2003) published their report of severe declines of some shark species in the Northwest Atlantic that serious concerns regarding extinction risk in sharks were raised and received broad national and international

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media attention. The logbook data set on which their analyses were based covered the US pelagic longline fishery targeting tuna and billfish from 1986 to 2000, encompassing a total of 214,234 longline sets (mean ¼ 550 hooks/ longline). This data set was proposed to be one of the longest time series for shark harvest ever analysed, with six species or species groups recorded from 1986 onward, and eight species from 1992 onward. Their results presented strong evidence that hammerhead, great white and thresher sharks had suffered the greatest declines, with reductions of over 75% in relative abundance over the past 15 years. Tiger, coastal requiem (carcharhinid), blue and oceanic whitetip sharks were also substantially reduced by 65%, 61%, 60% and 70%, respectively, and shortfin mako sharks declined moderately. These trends were then extrapolated to the entire region of the North Atlantic. Further evidence in support of large shark declines came soon after from the Gulf of Mexico, where longline records showed declines of 99% and 90% for oceanic whitetip and silky sharks (Carcharhinus falciformis), respectively, between 1954–1957 and 1995–1999 (Baum and Myers, 2004). A number of other coastal shark species in the region have apparently declined due to high harvest rates, including sandtiger (Carcharhinus taurus) and dusky (Carcharhinus obscurus) sharks (Fig. 4.5). These populations declined because of catches persisting until the late 1980s, and showed only modest signs of recovery after 10 years (i.e. a few generations) of regulation. The more productive sandbar shark (Carcharhinus plumbeus), although reduced in population size, continues to sustain fisheries (Musick, 1999a; Musick et al., 1993). The above-mentioned studies, among others (Dulvy et al., 2008), have had a large influence on recent conservation decisions to list many shark species under the Convention on International Trade in Endangered Species (CITES) and the World Conservation Union’s (IUCN) Red List. However, the methods on which the conclusions were based have since been called into question (Baum et al., 2005; Burgess et al., 2005a,b; Worm et al., 2006). According to Burgess et al. (2005a), the weaknesses of the Baum et al. studies are related to the nature of logbook reporting, choice and size of data sets used, the temporal and spatial context of the data, and the standardisations made. One of the greatest concerns raised regard coverage and quality of the data set, in addition to assumptions and standardisation of catch data, to provide indices of relative abundance based on small sample sizes (Burgess et al., 2005a; Hilborn and Walters, 2001). Use of the US pelagic longline logbook data set was considered problematic for two main reasons. Firstly, another 25 data sets were available for the region from other sources, including from US observers on US and Japanese boats, Canadian observers on Canadian and Japanese boats, and from other scientific and recreational surveys. Although, Burgess et al. (2005a,b) recognised that the US pelagic longline data set gives the best temporal and spatial resolution, they

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contended that other data sets and studies were not used or cited; for example, stocks assessment of coastal shark populations from the northwest Atlantic and the Gulf of Mexico were not discussed (Corte´s et al., 2002). Apparent oversight of these additional lines of evidence that provide mixed support for and against the conclusion of severe declines in some species were identified as a shortcoming (Burgess et al., 2005a,b). However, some of these additional data sets were not freely available (Baum et al., 2005). Furthermore, other originally unused data sets have been considered by Shepherd and Myers (2005) and in some unreported studies (Baum et al., 2005), and all of these support the initial conclusions. Secondly, the data sets used (Baum et al., 2003) might not adequately represent the large, less common coastal species relative to pelagic species, and catches might not reflect the true status of the coastal sharks (Burgess et al., 2005a). Also less commonly caught species were not considered, despite other studies showing no evidence of decline in species such as sandbar sharks (C. plumbeus) (Burgess et al., 2005a). Baum et al. (2005) conceded that their data set does not allow modelling of individual coastal shark species and that trends can vary among species; however, they made no inferences about individual trends in abundance. The capacity for species misidentification in the logbook data might also have inflated catches reported for some species, if indeed this was systematic. For example, Burgess et al. (2005a) contended that oceanic whitetip and other sharks bearing white skin patches are often reported as ‘white sharks’, which could be mistaken for C. carcharias, the great white shark. Other species misidentifications were thought to be likely with any large ‘brown’ sharks often reported as ‘tiger’ sharks, and shortfin makos as ‘blue’ sharks. However, the degree of potential misreporting was not determined by either grouping. Concerns were also raised over the particular spatial analyses used and interpretation of results for a number of studies reporting severe declines (Baum et al., 2003; Myers and Worm, 2003). Walters (2003) questioned the interpretation of widespread declines due to errors which can lead to overestimated reduction by summing and averaging catch data over broad areas without taking local ‘weighting’ into consideration (Hilborn and Walters, 2001; Walters, 2003). Burgess et al. (2005a) also identified that changes in fishing practices, target species, gear and management policy during the period over which the data were collected invalidated some of the temporal comparisons in catch composition. There were changes in the type of hooks and leaders used over the data set interval, with newer gear possibly reducing shark by-catch, especially for larger species. Finally, there was likely to be high error associated with data standardisation used to control for environmental heterogeneity, including oceanographic conditions and habitat type (Burgess et al., 2005a). Even after debating the data sets and methods used (Baum et al., 2005; Burgess et al., 2005a,b), there remains some contention over the original

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conclusion of near extinction for many large sharks. Regardless of the debate, however, the overarching trends on which there is agreement indicate that there have been general declines in many of the fished shark species in the north-western Atlantic. The debate is instead centred on the magnitude of the declines, and there is new agreement that to resolve the aforementioned problems, more research and monitoring are required. All parties also agree that a precautionary approach is most certainly advisable, given the signs that a problem exists. One view is that this must be based on stock assessments that rely on a range of data sets including catch rates, size and age composition, tagging returns, and other measurements of ecological and life history traits. 3.1.4. Illegal, unreported and unregulated (IUU) fishing Although sharks have historically been of relatively low economic value, IUU fishing is generally seen as a potentially serious threat to chondrichthyan species richness and abundance (Clarke et al., 2006). IUU fishing refers to harvesting that does not comply with national, regional or global fisheries conservation and management obligations (Agnew et al., 2008; Ainsworth and Pitcher, 2005; Gewin, 2004; Sumaila et al., 2006). In the context of chondrichthyans, illegal harvest principally targets species for the highly lucrative trade in fins, for example, sawfishes (Pristis spp.) and blue sharks (Clarke et al., 2006). IUU fishing on the high seas or in distant waters from landing ports can be a highly organised, mobile and elusive activity that undermines the sustainable management efforts of fish resources under the jurisdiction of responsible countries. International cooperation is therefore essential to combat this serious problem effectively, especially considering that conservative estimates place the harvest due to IUU fishing at three times that of managed fishing quotas (Agnew et al., 2008; Gewin, 2004). As an example, IUU fishing continues to thrive in the northern region of Australia’s Fishing Zone (AFZ) and is largely undertaken by traditional or small-scale Indonesian vessels (Field et al., 2009). Indonesian fishermen involved in IUU fishing in this area target specific species such as shark, reef fish, sea cucumber (Holothuria spp.) and trochus (Trochus spp.) that are destined for the Asian market (Field et al., 2009). Since 1974, traditional, non-motorised, Indonesian vessels have been allowed access to a defined area of the AFZ north west of Broome (Fig. 4.5) in which Australia agrees not to enforce its fisheries laws allowing traditional access; this area is known as the Memorandum of Understanding (MoU) 1974 Box (Field et al., 2009). Historically, IUU fishing by Indonesian vessels occurred either in the MoU Box as a result of opportunistic fishing in other areas of the AFZ, or around the MoU Box contrary to the agreed rules. More recently, there has been a noticeable shift away from what could be termed ‘traditional’ fishing. Motorised vessels are being found as far east as the Torres Strait, and are largely targeting sharks for their valuable fins. This has led to marked

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changes in the abundance and species composition of sharks in the region (Field et al., 2009) and is predicted to have ecosystem and economic consequences (Pascoe et al., 2008). 3.1.5. Recreational fishing Recreational fishing is a popular and growing activity in many parts of the world (Stevens et al., 2005). Although chondrichthyans are mainly by-catch species for many recreational fishers, they are also targeted by others as game or sport fishes (Stevens et al., 2005). Recreational fishing catches are typically small relative to commercial catches, although few data are available specifically for chondrichthyans due to a general absence of formal reporting requirements or dedicated surveys. The few data that do exist provide some interesting insight; however, the impact of recreational fishing on chondrichthyans is difficult to predict. In Australia and New Zealand, recreational catches are relatively low. The total commercial shark catch reported to the FAO (Food and Agriculture Organization of the United Nations, 2000) for Australia was approximately 7500 tonnes in the year 2000. At the same time, a national recreational and indigenous fishing survey estimated that the total shark catch was around 1200 tonnes (Henry and Lyle, 2003), representing approximately 16% of the annual commercial catch, although about 81% was reported as ‘released alive’. This is slightly more than the proportional catch reported for recreational fishers in New Zealand targeting rig (Mustelus lenticulatus), spiny dogfish and elephant fish (Callorhinchus milli) (Fig. 4.5), where recreational fishers caught between 6% and 8% of the total reported commercial shark catch (Francis, 1998). The largest recreational catch for sharks on the east coast of the USA and in the Gulf of Mexico is estimated at around 35,000 tonnes per year, of which approximately 30% were reported killed (Musick et al., 1993). Recently, catches have been revised to 11.1 million individual sharks from all species caught by recreational fishers, and 0.448 million of these were harvested (Marine Recreational Fisheries Statistics Survey, 2001). More specifically, catches of large coastal sharks (e.g. great white, sandbar, blacktip, mako sharks) in the region are thought to be greater than that taken by the commercial fishery (Corte´s et al., 2002), such that the two mortality sources together are hypothesised to be the primary drivers of the decline in blacktip (C. limbatus) and sandbar sharks (C. plumbeus) (Baum and Myers, 2004; Corte´s et al., 2002; Musick et al., 1993; Shepherd and Myers, 2005) (Fig. 4.5). Other types of recreational fishing can also reduce chondrichthyan species abundance. For example, the recreational spearfishing of grey nurse sharks (Carcharias taurus) during the 1960s and 1970s on the east coast of Australia (Fig. 4.5) contributed to a large decline in population size, leading to legislation for protection in 1984 (Pollard, 1996). Today, this species is fully protected throughout Australia, although concerns regarding their future still remain (Environment Australia, 2002; Otway and Burke, 2004; Otway et al., 2004).

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Another concern is that recreational fishing usually takes place in inshore waters, close to coasts and in bays, estuaries and rivers. These areas have been identified as important habitats for many chondrichthyans, especially for breeding, pupping or nursery areas (Stevens et al., 2000, 2005). Recreational fishing often affects juveniles more than adults. Indeed, recreational fishers in Tasmania (Fig. 4.5) were responsible for declines in gummy and school sharks in the 1960s and 1970s by gillnetting in nursery areas (Williams and Schaap, 1992). In recent years, however, growing emphasis on catch and live release is hoped to reduce the negative impacts of recreational fishing on many shark species, while also providing important scientific information for effective species management (Stevens et al., 2000).

3.2. Beach meshing Shark attacks worldwide are rare (Stevens et al., 2005). However, at beaches where attacks were historically common, authorities in Australia and South Africa continue to protect swimmers by setting dedicated shark nets and drum-lines (Burgess and Simpfendorfer, 2005). In response to a number of unprovoked shark attacks in Sydney Harbour, beach meshing programmes started in New South Wales, Australia in 1937 using 50–60 cm gillnets. This success led to similar programmes in South Africa in 1952, Hawaii in 1959, Queensland in 1962, New Zealand in 1969 and Hong Kong in 1995 (Burgess and Simpfendorfer, 2005). These programmes have generally been successful in reducing incidences of shark attacks on human swimmers, although this has come at a cost. In Australia and South Africa, around 1500 and 1200 sharks, respectively, are caught each year. In general, catch rates in these programmes show a rapid initial decline, after which they become stable, although there is considerable variation among species and locations (Reid and Krogh, 1992; Simpfendorfer, 1992). It is also thought that beach meshing has the greatest negative impact when deployed along coastlines rather than around single beaches, increasing the overall probability of capture while also serving to fragment habitat and disrupt migratory behaviour. Total catches are relatively small compared to fishery catches, but beach meshing is an important mortality source for small endemic populations. In Australia, a decline in grey nurse sharks is evident from beach meshing figures: in New South Wales grey nurse sharks mesh catches declined from 19 individuals per month in 1937 (Coppleson, 1962), to 0.29 individuals per month between 1972 and 1990 (Krogh, 1994). Beach meshing and spearfishing were considered the main cultprits (Otway et al., 2004). Beach meshing also kills many harmless chondrichthyans; for example, the Queensland (Australia) beach-meshing programme caught 13,765 rays between 1962 and 1988, and in New South Wales, 2074 rays were caught between 1972 and 1990 (Krogh and Reid, 1996).

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3.3. Habitat loss Chondrichthyans have evolved to fill many niches across a broad range of habitats (Compagno, 1990) and it is unlikely that they will be able to adapt quickly to human-induced changes in their environments (Corte´s, 2002; Garcı´a et al., 2008). Therefore, species with highly specialised life histories (e.g. ontogenetic spatial and cephalopod diet specialisation by Hemigaleus australiensis; Taylor and Bennett, 2008) and limited spatial or environmental ranges are predicted to be more at risk from habitat change. Habitat degradation and loss alter the dynamics, distribution and possibly behaviour of its inhabitants. This includes both reduction in spatial extent of habitat (habitat loss) and the composition and interactions of the biological communities that rely on them (habitat degradation). Habitat requirements can vary considerably over the different stages of the life cycle of species, so habitat loss and degradation can operate insidiously to reduce aspects of performance in terms of reproduction, dispersal or foraging ecology (Martinez et al., 2007; McMichael, 2001; Musick et al., 2000a). Most chondrichthyan species use some type of specific habitat for breeding, shelter or feeding that can encompass everything from freshwater rivers and lakes, shallow estuaries and coastal bays, to coral reefs, kelp forests and the deep sea (Stevens et al., 2005). A number of species require shallow coastal areas as nurseries protected from large predators and inclement environmental conditions. Juveniles can remain in these areas during their early development to maximise survival. As such, the loss of estuarine and coastal nursery habitats from the destruction of mangrove forests, aquaculture and other coastal developments can compromise the recruitment in some species. The continuing loss of these important habitats could exacerbate the extinction risk of associated species in addition to direct threats of over-harvest (Kinney and Simpfendorfer, 2009). The effects of fishing itself can be far more wide-reaching than just removal of individuals. Destructive fishing practices such as trawling and dynamite fishing change habitat structures by reducing substratum complexity and diversity. Some of these effects can be most detrimental for deepwater species that tend to be adapted to relatively stable environments. Unfortunately, dedicated research examining effects of habitat loss and degradation on shark populations has generally been lacking, with current predictions based largely on the expectation of chondrichthyans’ roles in ecosystem function (see Section 5).

3.4. Pollution and non-indigenous species Water pollution is a major problem that affects almost all freshwater and marine environment habitats and ecosystems, and it can directly affect chondrichthyans through changes in water quality and habitat degradation.

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There are four main types of pollutants: (1) those that affect the physical properties of the environment, (2) those that cause eutrophication, (3) poisons and (4) pathogens that can affect the health of an individual or influence community or ecosystem structure. Pollutants can even have multiple effects, such as sewage effluent containing harmful toxins that cause eutrophication leading to dissolved oxygen depletion (Pastorok and Bilyard, 1985). Pollutants that alter the physical properties of water and cause eutrophication have greater effects on the ecosystems on which chondrichthyans rely, than on individuals directly. This is because sharks and rays are generally highly mobile animals that can remove themselves from harmful situations if required. However, endemic species or populations restricted to small regions might be at greater risk to broad-scale pollution events. Certain life stages can also be more sensitive to the effects of pollution than others, especially embryos or juveniles with higher metabolic rates than adults. Chondrichthyans can bio-accumulate heavy metals such as mercury (Lyle, 1984; Walker, 1976, 1988; Watling et al., 1982), especially coastal species that live in shallow turbid environments where freshwater outflow meets marine waters (e.g. Fairey et al., 1997). Bio-accumulation of other pollutants can occur also, such as organic chemical compounds (Davis et al., 2002; Fisk et al., 2002; Gelsleichter et al., 2005; Storelli and Marcotrigiano, 2001; Storelli et al., 2005). These metals and organic compounds can have adverse effects on reproductive, immune, endocrine and nervous systems (Betka and Callard, 1999; Clarkson, 1994; Gelsleichter et al., 2005; Koller, 1979; Scheuhammer, 1991). In male sharks, heavy metals such as cadmium (a known spermatotoxicant) have been observed in high concentrations in some species (Betka and Callard, 1999). In female bonnethead sharks (Sphyrna tiburo), exposure to organic compounds such as PCBs can reduce fertility through disruption of the endocrine system (Gelsleichter et al., 2005). Although many chondrichthyans have been exposed to bio-accumulating pollutants, their effects are still relatively unexplored. Other sources of pollution include oil spills and leaks that can contaminate tissues when ingested (Anonymous, 1993), flotsam and jetsam that can compromise digestion or entrap individuals (Sazima et al., 2002), and ghost netting (Stevens et al., 2005). Other types of environmental pollution include increased thermal outflows and discharges, and disruption of natural electro-magnetic fields by generation of artificial fields around undersea cables that can alter chondrichthyan behaviour because of their reliance on electro-magnetic sensory perception for foraging (Filer et al., 2008; Hoisington and Lowe, 2005; Walker, 2001). A final primary source of marine pollution to consider is from ships’ ballast water from large commercial vessels that travel worldwide, and can transport non-indigenous marine species to new habitats (Drake et al., 2007; Elliott, 2003; Ruiz et al., 2000). There is little direct evidence that

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non-indigenous species threaten chondrichthyans; however, increasing invasions might erode the integrity of natural ecosystems upon which chondrichthyans rely.

4. Chondrichthyan Extinction Risk Given acceleration in species loss globally due mainly to humanmediated changes to the biosphere, there has been a growing interest in identifying and ranking the species characteristics and environmental contexts that could predict the proneness of species to extinction (Dulvy et al., 2003; McKinney, 1997; Pimm et al., 2006; Purvis et al., 2000a; Sodhi et al., 2008a,b). A capacity to predict species’ responses to threats based on intrinsic ecological, life history or environmental traits is important to improve management efficiency and prioritise efforts to recover threatened taxa (Pimm et al., 2006; Sodhi et al., 2008b). For example, predictors of the predisposition of species to extinction could be used for selecting potentially sensitive taxa to monitor for early detection of population decline, enabling decision makers to choose how best to allocate finite conservation and management resources (Duncan and Young, 2000). Current evidence supports the notion that particular combinations of life history and ecological characteristics (organism size, dispersal capacity and native geographic range) and other reproductive, dispersal, morphological and physiological attributes can influence a species’ proneness to extinction (Duncan and Young, 2000; Sodhi et al., 2008b), with the strength of effect often depending on environmental context (Brook et al., 2008; Pimm et al., 2006; Sodhi et al., 2008a). Indeed, rare species tend to have lower reproductive effort and dispersal capacity and more restricted geographic ranges than common species (Blackburn and Cassey, 2004; Kunin and Gaston, 1993, 1997; Pocock et al., 2006). A population’s distribution will also affect its probability of extinction, especially over longer timescales. Widespread species are generally more resilient to local environmental disturbances and ecosystem changes because entire range-wide catastrophes become progressively less likely as a distribution increases (Brook et al., 2008). Fragmented populations are also more vulnerable due to the loss of connectivity between subpopulations, reducing geneflow and resilience of the population to change (Caughley and Gunn, 1996; Dulvy et al., 2003; Saunders et al., 1991). Species’ traits such as body size are closely correlated with other life history attributes such as a geographic extent, potential fecundity, dispersal capacity and niche breadth. Thus, the extinction risk of a species can be classified based on the suite of characteristics that permit recovery from over-harvesting or changes in the environment such as habitat loss.

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Specialised life histories that suit narrow ecological niches can increase the risk of extinction by limiting the ability of the species to adapt rapidly to change. Likewise, large body size tends to correlate positively with extinction risk (Cardillo et al., 2005; Johnson, 2002; Olden et al., 2007), and higher reproductive rates can increase capacity to recover from depletion (Purvis et al., 2000b).

4.1. Drivers of threat risk in chondrichthyans and teleosts Marine species were once considered to have a lower risk of extinction than terrestrial taxa due to the their longer presence in the fossil record (Culotta, 1994; Norse, 1993), high relative fecundity and larger geographic ranges (Dulvy et al., 2003). However, this view is now contested (McKinney, 1998). Despite recent debate on the number of marine fish that have become globally extinct (del Monte-Luna et al., 2007; Dulvy et al., 2003), the number is but a small fraction of the extant species. Dulvy et al. (2003) suggested that three species have become extinct within the human timeframe (New Zealand grayling Prototroctes oxyrhynchus, green wrasse Anampses viridis, and Gala´pagos damsel Azurina eupalama), although del MonteLuna et al. (2007) confirmed the loss of P. oxyrhynchus and A. viridis and provided evidence for the debate over the believed loss of A. eupalama. Currently, only four species found in brackish and/or saltwater are listed on the IUCN’s Red List as Extinct: the European sturgeon (Huso huso) and bastard sturgeon (Acipenser nudiventris) due to over-harvest, the New Zealand grayling due to the release of introduced species, and the Madagascan lampeye (Pantanodon madagascariensis) due to habitat loss. There are, however, many species listed as currently experiencing local and regional declines, thus rendering them vulnerable to extinction. Of all the larger marine taxa, chondrichthyans (sharks, rays and chimaeras) are considered the most vulnerable to extinction because of their tendency toward large size, slow growth and late maturation (Corte´s, 2000; Garcı´a et al., 2008). In fact, the number of chondrichthyan species that are listed as either locally, regionally or globally extinct equals the total number of teleost extinctions (Dulvy et al., 2003), but Red-Listed chondrichthyans outnumber the total number of teleost species listed. This raises the questions: are chondrichthyans at greater risk of extinction than teleosts or perhaps other marine taxa? If so, then what are the principal life history traits that drive this difference? Do chondrichthyans simply represent a higher proportion of listed species because of their high profile for protection (Pimm et al., 2006)? Despite the repetition of their apparent greater risk in the literature (e.g. Baum et al., 2003; Camhi et al., 1998; Corte´s, 2000; Myers and Worm, 2005; Robbins et al., 2006), there has been little, if any, direct qualitative or quantitative analysis of the available data to test the assertion.

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With the understanding that there has not yet been a comprehensive overview and formal analysis of chondrichthyan threat risk relative to teleosts, we constructed a detailed analysis of the ecological, life history and human-relationship data relative to the IUCN’s Red List categorisation for extant chondrichthyans and teleosts. This includes classes Elasmobranchii (sharks and rays), Holocephali (chimaeras), Actinopterygii (ray-finned fishes) and Sarcopterygii (lobe-finned fishes) (Table 4.1). We excluded Classes Cephalaspidomorphi (lampreys) and Myxini (hagfishes) from all analyses. Our main aim was to determine the primary drivers of threat risk for each taxon and whether overall susceptibility differed between chondrichthyans and teleosts.

4.2. Global distribution of threatened chondrichthyan taxa To examine the spatial distribution of threatened Chondrichthyan species from marine and estuarine habitats in the IUCN Red List, we examined all populations listed as critically endangered, endangered and vulnerable (International Union for the Conservation of Nature and Natural Resources, 2008) using the websites www.iucnredlist.org and www. fishbase.org. From these, we plotted the approximate centroid of each threatened population’s distribution in latitude and longitude coordinates (0.5 precision). These data provide a map of the relative global distribution of threatened chondrichthyan populations from least (vulnerable) to most (critically endangered) threatened (Figs. 4.6 and 4.7). Generally, the central Table 4.1 Summary of chondrichthyan [including Classes Elasmobranchii (sharks and rays) and Holocephali (chimaeras)] and teleost [including Classes Actinopterygii (ray-finned fishes) and Sarcopterygii (lobe-finned fishes)] species’ taxonomic sample distribution Class

Chondrichthyans Elasmobranchii Holocephali Total Teleosts Actinopterygii Sarcopterygii Total Totals

Orders

Families

Genera

11 1 12

44 3 47

175 6 181

45 3 48 60

468 4 472 519

4592 4 4596 4777

Species (marine)

Analysed n

961 (937) 37 (37) 998 (974)

216–218 3–9 219–227

27,388 (15,397) 11 (2) 27,399 (15,399) 28,397 (16,373)

141–385 1 142–386 367–612

Total number of species is presented for all milieus and marine only. The final number of species analysed depended on the particular set of attributes included in the model sets (see Tables 4.3 and 4.4), so sample size ranges are shown.

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71

Vulnerable 10⬚

30⬚

Endangered Critically Endangered

51 87

47

41

57

81 50⬚

70⬚

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48

58

Figure 4.6 Global distribution of IUCN Red-Listed threatened chondrichthyan species. Each dot represents the approximate centroid coordinate (0.5 precision determined from cross-referencing data from www.iucnredlist.org and www.fishbase.org) for sub-populations of 115 separate chondrichthyan species listed as vulnerable (light grey), endangered (mid-tone grey) or critically endangered (dark grey) according to the IUCN Red List (www.iucnredlist.org).

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Aetzon Aetnic Carbra Rhyaus Urojav Rhitho Hemhal Carbor Rhityp Dasflu Hemstr Mylham Pricla

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Squaca Rhifor Narbre Rhityp

Uroasp Uroukp Pripri

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Galgal Carcar

Cartau Uroora

71

Hetcol Urosuf Urovir Urobuc Galgal

Aulkan

Squmit

Lamnas

Batalb Batgri Dipchi

88

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48

58

Figure 4.7 Global distribution of IUCN Red-Listed threatened chondrichthyan species (see Fig. 4.6 for details) with species labels: aetfla, Aetobatus flagellum; aetmac, Aetomylaeus maculatus; aetnic, Aetomylaeus nichofii; aetves, Aetomylaeus vespertilio; aetzon, Aetoplatea zonura; anocus, Anoxypristis cuspidata; atlcas, Atlantoraja castelnaui; atlcyc, Atlantoraja cyclophora; atlpla, Atlantoraja platana; aulkan, Aulohalaelurus kanakorum; batalb, Bathyraja albomaculata; batgri, Bathyraja griseocauda; benkre, Benthobatis kreffti; carbor, Carcharhinus borneensis; carbra, Carcharhinus brachyurus; carcar, Carcharodon carcharias*; carhem, Carcharhinus hemiodon; carlei, Carcharhinus leiodon; carlim, Carcharhinus limbatus; carlon, Carcharhinus longimanus; carobs, Carcharhinus obscurus; carsig, Carcharhinus signatus; cartau, Carcharias taurus; cengra, Centrophorus granulosus; cenhar, Centrophorus harrissoni; censqu, Centrophorus squamosus; cetmax, Cetorhinus maximus; dasflu, Dasyatis fluviorum; dasgar, Dasyatis garouaensis; daslao, Dasyatis laosensis; dipbat, Dipturus batis; dipchi, Dipturus chilensis; dipcol, Diplobatis colombiensis; dipcro, Dipturus.

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distribution of threatened sharks covered much of the coastal regions in eastern North America, north-western and south-eastern South America, western Africa, Europe (including the Mediterranean), Indian Ocean, south and south-eastern Asia, and eastern Australia (Figs. 4.5 and 4.6). Obvious clusters of threatened species were found in five regions: (1) south-eastern South America along the coasts of southern Brazil, Uruguay and Argentina; (2) western Europe and the Mediterranean; (3) western Africa; (4) South China Sea and Southeast Asia and (5) south-eastern Australia. The highest concentration of critically endangered species was in western Europe, western Africa and Southeast Asia (Figs. 4.5 and 4.6).

4.3. Ecological, life history and human-relationship attributes For each species, we compiled attributes likely to contribute to the propensity to become threatened and by proxy, extinct (Brook et al., 2008; Garcı´a et al., 2008; Olden et al., 2007; Sodhi et al., 2008b; Traill et al., 2007). These included information on size, fecundity, mode of fertilisation, longevity, age at maturity, geographic range, growth rates, natural mortality, migratory behaviour, habitat, general temperature regime, salinity preference, crosnieri; dipgua, Diplobatis guamachensis; diplae, Dipturus laevis; dipmen, Dipturus mennii; distsc, Discopyge tschudii; galgal, Galeorhinus galeus; galmin, Galeus mincaronei; glygan, Glyphis gangeticus; glygly, Glyphis glyphis; gurdor, Gurgesiella dorsalifera; gymalt, Gymnura altavela; hemhal, Hemiscyllium hallstromi; hemleu, Hemitriakis leucoperiptera; hemstr, Hemiscyllium strahani; hetcol, Heteroscyllium colcloughi; himcha, Himantura chaophraya; himflu, Himantura fluviatilis; himoxy, Himantura oxyrhyncha; himsig, Himantura signifer; isooxy, Isogomphodon oxyrhynchus; isupau, Isurus paucus; lamnas, Lamna nasus; leumel, Leucoraja melitensis; mobmob, Mobula mobular; musfas, Mustelus fasciatus; mussch, Mustelus schmitti; muswhi, Mustelus whitneyi; mylham, Myliobatis hamlyni; narban, Narcine bancroftii; narbre, Narcine brevilabiata; nebfer, Nebrius ferrugineus; negacu, Negaprion acutidens; odofer, Odontaspis ferox; oxycen, Oxynotus centrina; pricla, Pristis clavata; primic, Pristis microdon; pripec, Pristis pectinata; priper, Pristis perotteti; pripri, Pristis pristis; prizij, Pristis zijsron; psebre, Pseudoginglymostoma brevicaudatum; rhianc, Rhina ancylostoma; rhibra, Rhinoptera brasiliensis; rhicem, Rhinobatos cemiculus; rhifor, Rhinobatos formosensis; rhigra, Rhinobatos granulatus; rhihor, Rhinobatos horkelii; rhijav, Rhinoptera javanica; rhiobt, Rhinobatos obtusus; rhirhi, Rhinobatos rhinobatos; rhitho, Rhinobatos thouin; rhityp, Rhincodon typus*; rhyaus, Rhynchobatus australiae; rhydji, Rhynchobatus djiddensis; rhylae, Rhynchobatus laevis; rhylue, Rhynchobatus luebberti; rosalb, Rostroraja alba; schsau, Schroederichthys saurisqualus; scyque, Scylliogaleus quecketti; sphmok, Sphyrna mokarran; sphtud, Sphyrna tudes; squaca, Squalus acanthias; squacu, Squatina aculeata; squarg, Squatina argentina; squgug, Squatina guggenheim; squmit, Squalus mitsukurii; squocc, Squatina occulta; squocu, Squatina oculata; squsqu, Squatina squatina; stefas, Stegostoma fasciatum; symacu, Sympterygia acuta; taemey, Taeniura meyeni; triacu, Triakis acutipinna; trimac, Triakis maculata; uroasp, Urogymnus asperrimus; urobuc, Urolophus bucculentus; urojav, Urolophus javanicus; uroora, Urolophus orarius; urosuf, Urolophus sufflavus; uroukp, Urogymnus ukpam; urovir, Urolophus viridis; zapbre, Zapteryx brevirostris; *, global distribution.

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commercial importance, whether the species was a target of recreational fishing, and if it was considered dangerous to humans (Table 4.2). Life history and environmental data for 28,505 species of marine and estuarine fish were extracted from FishBase (Froese and Pauly, 2004). Where there were data available for multiple populations per species, they were grouped by species, with mean, minimum and maximum values calculated for each parameter. Species with aquaculture populations were excluded from the data set. Complete data were missing for most species, so we examined only the most complete data to maximise the number of species considered in the analyses. The final data set for analysis included the following terms: Length (LNG). Extinction risk in many taxa has been linked to organism size (Brook et al., 2008; Cardillo et al., 2005; Johnson, 2002; Olden et al., 2007; Purvis et al., 2000b; Raup, 1994; Sodhi et al., 2008a). Most length measurements were either ‘standard’ or ‘total length’, but we could not standardise length measurements due to a lack of data on species-specific relationships. Range (RGE). Range extent is an important indicator of the propensity of a species to become threatened (Brook et al., 2008; Croci et al., 2007; Oborny et al., 2005; Pimm et al., 2006). This is because widespread species tend to have a higher capacity to tolerate new environments given that they have already encountered a variety of climatic and habitat conditions in their evolutionary history and acquired relatively high phenotypic plasticity (Croci et al., 2007). FishBase provides information on the number of FAO Fisheries Areas occupied by a particular species. We initially considered the variable as an ordinal integer, but due to high skewnesss, we re-classified the variable into a three-level factor ([1] 1 FAO area, [2] 2 FAO areas, and [3] >2 FAO areas). Habitat (HBT). The type of habitat occupied by a species can influence its distribution given the variation in abiotic factors that dictate habitat distributions (Garcı´a et al., 2008). Species were categorised into one of three habitat classes: [1] demersal (including bathydemersal and demersal), [2] pelagic (including bathypelagic, benthopelagic and pelagic), or [3] reefassociated (around reefs from 0 to 200 m; Froese and Pauly, 2004). Environmental temperature class (ETP). As a measure of latitudinal and bathymetric variation in the probability of being classed as threatened (Worm et al., 2005), we also included a three-level factor describing the principal temperature environment occupied by each species. These included [1] tropical (including subtropical and tropical), [2] temperate (including high-latitude or strictly temperate species) or [3] deep-water (see also Garcı´a et al., 2008). Commercial fisheries interest (CMI). We hypothesised that species would be, on average, more likely to be classed as ‘threatened’ if targeted by fisheries (Pauly et al., 1998; Roberts, 2003; Roberts and Hawkins, 1999). We therefore classified each species with respect to its primary interest to fisheries: [1] of commercial interest, [2] of primarily artisanal interest

Table 4.2 Summary of marine fish (chond, chondrichthyan; teleo, teleost) species’ threat status (threatened, critically endangered, endangered or vulnerable; not threatened, least concern, lower risk, or near threatened) and ecological, life history and human-relationship attributes with a list of the species frequency (available data) for the different category levels n Marine species with data (%)

Parameter abbreviation

Description

Levels

Chond

Teleo

TH08

Threatened (IUCN, 2008)

LNG HBT

Length Habitat

ETP

Environmental temperature

RGE

Range (FAO areas)

CMI

Commercial fishing

GME

Game fished?

DGR

Dangerous?

WT LGV FEC

Max. weight Longevity Max. fecundity

[0] No [1] Yes Continuous (cm) [1] Demersal [2] Pelagic [3] Reef-associated [1] Deep water [2] Temperate [3] Tropical [1] 1 [2] 2 [3] > 2 [1] Artisanal [2] Commercial [3] No fishing interest [0] No [1] Yes [0] No [1] Yes Continuous (g) Continuous (years) Continuous (eggs/female)

246 (70) 108 (30) 754 756 (78) 111 (11) 107 (11) 374 (38) 84 (9) 516 (53) 395 (41) 279 (29) 299 (30) 213 (41) 128 (25) 175 (34) 869 (89) 105 (11) 799 (82) 175 (18) 107 33 153

212 (59) 145 (41) 12,408 7729 (50) 3535 (23) 4135 (27) 3263 (21) 1936 (13) 10,198 (66) 6798 (44) 3830 (25) 4751 (31) 1569 (32) 1661 (34) 1636 (34) 14,590 (95) 809 (5) 14,755 (96) 619 (4) 980 510 395 (continued)

Table 4.2

(continued) n Marine species with data (%)

Parameter abbreviation

Description

Levels

Chond

Teleo

MTL MTA

Length maturity Age maturity

3 38

150 165

LVB

Max. asymptotic length

2

94

GRT

Growth

2

94

MNT

Natural mortality

2

94

RMO

Reproduction mode

FTM

Fertilisation method

MGR

Migratory behaviour

Length at min fecundity (cm) Female minimum age at maturity Max. von Bertalanffy length (L1) Max. growth constant (K) Max. natural mortality rate (per year) [1] Dioecism [2] Parthenogenesis [3] Protandry [4] Protogyny [5] Hermaphroditism [1] External [2] Brood pouch [3] In mouth [4] Oviduct [5] Other [1] Amphidromous [2] Anadromous [3] Catadromous [4] Limnodromous [5] Non-migratory [6] Oceanodromous [7] Potamodromous

855 (100) 0 0 0 0 2 (0.2) 0 0 850 (>99) 0 2 (4) 0 0 0 0 45 (96) 0

2029 (83) 2 (0.8) 56 (2) 312 (13) 42 (2) 2007 (85) 46 (2) 6 (0.3) 291 (12) 4 (0.2) 74 (4) 129 (7) 59 (3) 3 (0.2) 1111 (60) 447 (24) 22 (1)

Parameters in boldface were included in the threat risk analysis (see Tables 4.3 and 4.4).

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(including subsistence and minor commercial interest) or [3] no major interest. We hypothesised that species of commercial interest would have a higher threat risk than other categories. Game fish (GME). Much like the justification for the impact of fisheries interest in a species, we had sufficient information to include whether a species was a targeted game fish. We hypothesised that game fishing would increase the threat risk of a species (Robbins et al., 2006). Dangerous (DGR). The perceived or real threat of danger to humans is thought to have been responsible for the depletion of many local populations of sharks prior to the recognition of this taxon’s plight (Burgess and Simpfendorfer, 2005). We therefore classed each species as [1] dangerous (including high predation risk, toxic, venomous) or [0] harmless.

4.4. Threat risk analysis To determine the relationships between the ecological, life history and humanrelationship traits and the threat risk of the compiled species, we fitted generalised linear mixed-effect models (GLMM) to the data using the lmer function implemented in the R Package V2.5 (R Development Core Team, 2009). For each GLMM, we coded species threat probability [i.e. IUCN Red-Listed (critically endangered, endangered or vulnerable) or not] as a binomial response variable and each trait as a linear predictor (fixed factors), assigning each model a binomial error distribution and a logit link function. We accounted for potential spatial bias in listing probability (i.e. some regions of the Earth might receive greater species assessment scrutiny than others) by removing all non-listed species or those listed as data deficient (International Union for the Conservation of Nature and Natural Resources, 2008) (cf. Olden et al., 2007). We also removed all species coded as extinct/extinct in the wild or those listed because of range restrictions (i.e. listed under Criteria B, D2 or both). This latter category was removed to avoid circularity in assessing correlates of threat risk among taxa (e.g. Bradshaw et al., 2008; Sodhi et al., 2008a). Species are phylogenetic units with shared evolutionary histories and are not statistically independent (Felsenstein, 1985). We therefore decomposed the variance across species by coding the GLMM random-effects error structure as a hierarchical taxonomic effect (Blackburn and Duncan, 2001). We had adequate replication to use the nested random effect of Order/ Family, but insufficient replication at finer taxonomic resolution. The amount of variance in threat probability captured by each model considered was assessed as the per cent deviance explained (%DE) in the binomial response, expressed relative to the deviance of a null model with no fixed effects, but retaining the hierarchical random effect (Brook et al., 2006). We constructed the model sets to reflect particular a priori hypotheses to identify the most important drivers of threat risk in the IUCN-listed species

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Table 4.3 Generalised linear mixed-effect models used to examine the correlation between fish threat status (either for chondrichthyan or teleost species groups separately) and a set of ecological, life history and human-relationship attributes Model No. Term combinations

(A) Phase 1 (P1): Ecology and life history 1 LNG 2 RGE 3 LNG þ RGE 4 LNG þ RGE þ HBT 5

LNG þ RGE þ ETP

LNG þ RGE þ HBT þ ETP 7 1 (B) Phase 2: Human relationship 1 ½P1 þ 2 ½P1 þ þ CMI

6

3 4 5 6 7

Analytical theme

Allometry (body size) Range Allometry þ range Allometry þ range þ habitat Allometry þ range þ temperature Saturated Null (intercept)

Supported Phase 1 terms þCommercial fishing interest ½P1 þ þ GME þGame fishing ½P1 þ þ CMI þ GME þGeneral fishing interest ½P1 þ þ DGR þDanger to humans ½P1 þ þ CMI þ GME þ DGR Saturated 1 Null (intercept)

Model combinations, derived a priori, represent particular analytical ‘themes’ grouping related traits. Terms include LNG, length; RGE, geographic range; HBT, habitat; ETP, environmental temperature class; CMI, commercial fishing interest; GME, game-fished; DGR, dangerous to humans (see also Table 4.2).

collated (Tables 4.3 and 4.4). We first split the modelling approach into two phases to examine different aspects of the relationships: (1) Phase 1 examined the relationship between threat risk (species coded as threatened or not threatened) and the four ecological and life history traits length, range, habitat and environmental temperature. Threatened species were those classed as critically endangered, endangered or vulnerable, with near threatened and least concern taken as not threatened. We also considered a second set of models where near threatened species were removed from the not threatened group; results were similar although there was a moderate increase in the % deviance explained and model ranking (results not shown). No interactions were considered in this phase. Combinations of these traits were constructed to produce seven models (Table 4.3A); (2) Phase 2 examined the influence between the threat response variable and the three human-relationship variables commercial fisheries interest, game-fished and dangerous, but also included the principal ecological and life history traits identified in Phase 1 (see Table 4.3B and Section 4.2). We applied the same two-phase approach to all chondrichthyan and teleost species

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Table 4.4 Generalised linear mixed-effect models used to examine the correlation between fish threat status (for chondrichthyan and teleost species combined) and a set of ecological, life history and human-relationship attributes Model No.

Term combinations

(A) Phase 1: Ecology and life history 1 LNG 2 LNG þ GRP 3 LNG þ GRP þ (LNG GRP) 4 RGE 5 RGE þ GRP 6 RGE þ GRP þ (RGE GRP) 7 LNG þ RGE þ GRP 8

LNG þ RGE þ HBT þ GRP

9

LNG þ RGE þ ETPþ GRP

LNG þ RGE þ HBT þ ETP þ GRP þ LNG þ RGE þ HBT þ ETP þ GRP 11 1 (B) Phase 2: Human relationship 1 ½P1 þ 2 ½P1 þ þ CMI

10

3 4 5 6 7

Analytical theme

Allometry Allometry þ group Allometry þ group interaction Range Range þ group Range þ group interaction Allometry þ range þ group Allometry þ range þ habitat þ group Allometry þ range þ temperatureþ group Saturated

Null (intercept)

Supported Phase 1 terms þCommercial fishing interest ½P1 þ þ GME þGame fishing ½P1 þ þ CMI þ GME þGeneral fishing interest ½P1 þ þ DGR þDanger to humans ½P1 þ þ CMI þ GME þ DGR Saturated 1 Null (intercept)

Model combinations, derived a priori, represent particular analytical ‘themes’ grouping related traits. Terms include LNG, length; GRP, taxonomic grouping (chondrichthyan or teleost); RGE, geographic range; HBT, habitat; ETP, environmental temperature class; CMI, commercial fishing interest; GME, game-fished; DGR, dangerous to humans (see also Table 4.3).

separately, and then added the fixed term Group to test for different threat risks between the two taxonomic groups explicitly. We also considered the Group length interaction (Table 4.4) to examine whether the relationship between length and threat risk differs between groups. We only considered species that were restricted to the marine environment. We used an index of Kullback–Leibler (K–L) information loss, Akaike’s Information Criterion corrected for small sample sizes (AICc), to assign

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relative strengths of evidence to the different competing models (Burnham and Anderson, 2002) as well as the dimension-consistent Bayesian information criterion (BIC), an approximation of the Bayes factor given no informative prior information on relative model support (Burnham and Anderson, 2002). These indices of model parsimony identify the relative evidence of model(s) from a set of candidate models. The relative likelihoods of candidate models were calculated using AICc and BIC weights (Burnham and Anderson, 2002), with the weight (wAICc and wBIC) of any particular model varying from 0 (no support) to 1 (complete support) relative to the entire model set. However, the K–L prior used to justify AICc weighting can favour more complex models when sample sizes are large (Burnham and Anderson, 2004; Link and Barker, 2006). We therefore considered both weightings for determining the contribution of the most important major correlates of extinction risk and to identify any weak tapering effects (Burnham and Anderson, 2004; Link and Barker, 2006).

4.5. Modelling results We compiled data for a total of 28,397 fish species (998 chondrichthyans; 27,399 teleosts); however, specific ecological, life history and human-relationship data were missing for most species (see Table 4.1). Of the species in the database, 525 (52%) chondrichthyan and only 2,272 (8%) teleost species were Red-Listed (see also Table 4.1), so subsequent threat-risk analyses were limited in sample size (Tables 4.5–4.7). Of the listed species, 518 were classed as data deficient (175 chondrichthyans; 343 teleosts). Excluded from the analyses were the 99 species that were classed as extinct/extinct in the wild (all teleosts). The distribution of species among the IUCN categories revealed a generally higher threat risk for teleosts than sharks (Fig. 4.8). Ordering the categories from least concern through to extinct/extinct in the wild (i.e. from lowest to highest risk categories) shows a biased distribution for the proportion of teleost species in the higher-risk categories (i.e. to the right of Fig. 4.8) compared to chondrichthyans, but a similar proportion of least concern species in both taxonomic groups. Of the IUCN Red-Listed species, there is a higher proportion of data-deficient species among the chondrichthyans (Fig. 4.8). The principal correlates of threat risk in the Red-Listed species generally support what is known for many other taxa, but the drivers of risk differed between chondrichthyans and teleosts. Our exploration first revealed that marine species for which there was information available on threat risk, there was only evidence for weak correlation (Spearman’s ) among attributes considered. The maximum jrj was 0.445 between length and range for listed chondrichthyans, and 0.500 between game fish and habitat for listed teleosts. We are thus confident that the results of our GLMMs were not

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Table 4.5 Correlates of marine chondrichthyan threat risk Model

(A) Phase 1 LNG LNGþRGE LNGþRGE þETP LNGþRGE þHBT LNGþRGE þHBTþETP (B) Phase 2 LNGþRGE LNGþRGE þDGR LNGþRGE þGME LNGþRGE þCMI LNGþRGE þCMIþGME

DAICc

wAICc

4 112.228 0.000 0.860 0.000 6 111.400 9.094 0.009 2.556 8 110.124 17.292 <0.001 4.297

0.614 0.171 0.072

3.9 4.6 5.7

8 110.126 17.296 <0.001 4.301

0.072

5.7

10 108.306 24.407 <0.001 5.039

0.049

7.3

k

LL

DBIC

wBIC

% DE

6 119.625 7 118.866

2.182 6.067

0.238 0.000 0.034 0.615

0.387 0.284

5.5 6.1

7 119.474

7.283

0.019 1.831

0.155

5.7

8 118.828 11.394

0.002 2.692

0.101

6.2

9 118.742 16.624 <0.001 4.692

0.037

6.2

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecological and life history correlates and (B) Phase 2: human-relationship attributes, after accounting for the effects of length and range (n = 216 species). Models include nested (hierarchical) taxonomic (order/family) random intercepts. Models are ranked according to the small-sample Akaike’s Information Criterion (AICc). Terms shown are LNG = length, RGE = range, HBT = habitat, ETP = environmental temperature, CMI = commercial fisheries interest, GME = status as game fish, DGR = danger to humans. Also shown are number of parameters (k), maximum log-likelihood (LL), difference in the Bayesian Information Criterion (BIC) and AICc for each model from the most parsimonious model (DBIC, DAICc), model weight (wBIC, wAICc), and per cent deviance explained (%DE) in the response variable (threat probability) by the model under consideration.

unduly biased. For chondrichthyans, threat risk was correlated principally with body length (larger species are more threatened), accounting for 0.61 of the AICc weight in the Phase 1 analysis; however, this attribute accounted for only 3.9% of the deviance explained (%DE) after taking taxonomy (phylogeny) into account (Table 4.5A). There was also weak support for a small effect of range on threat risk (decreasing threat with increasing range; Table 4.5A; Fig. 4.9A), so we included these two terms into the Phase 2 model set as ‘control’ variables. Although there was some wAICc support for the models including environmental temperature and habitat (Table 4.5 A and B), model predictions appeared to support the idea that reef-associated and deep-water chondrichthyans had lower threat risk (Fig. 4.9A). The Phase 2 analysis for chondrichthyans examining whether human-relationship attributes further influenced threat risk revealed that the term dangerous

322 Table 4.6

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Correlates of marine teleost threat risk

Model

(A) Phase 1 LNGþRGE þETP LNGþRGE LNGþRGE þHBT LNGþRGE þHBTþETP LNG (B) Phase 2 LNGþRGE þETPþHBT LNGþRGE þETPþHBT þGME LNGþRGE þETPþHBT þDGR LNGþRGE þETPþHBT þCMI LNGþRGE þETPþHBT þCMIþGME

k

LL

DBIC

wBIC

DAICc

wAICc

% DE

8

96.069

6.099

0.033 0.000

0.357 14.0

6 8

98.449 96.483

0.000 6.928

0.692 0.482 0.022 0.829

0.280 11.9 0.236 13.6

94.953 14.727 <0.001 2.125

0.123 15.0

10

4 104.907

2.057

0.247 9.197

0.004

10

94.953

4.471

0.095 0.000

0.447 15.0

11

94.690

9.374

0.008 1.682

0.193 15.2

11

94.916

9.825

0.007 2.134

0.154 15.0

12

94.059 13.540

0.001 2.648

0.119 15.8

13

93.491 17.927 <0.001 3.856

0.065 16.3

6.1

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecological and life history correlates and (B) Phase 2: human-realationship attributes, after accounting for the effects of length and range (n = 228 species). Models include nested (hierarchical) taxonomic (order/family) random intercepts. Models are ranked according to the small-sample Akaike’s information criterion (AICc). Terms shown are LNG = length, RGE = range, HBT = habitat, ETP = environmental temperature, CMI = commercial fisheries interest, GME = status as game fish, DGR = danger to humans. Also shown are number of parameters (k), maximum log-likelihood (LL), difference in the Bayesian Information Criterion (BIC) and AICc for each model from the most parsimonious model (DBIC, DAICc), model weight (wBIC, wAICc), and per cent deviance explained (%DE) in the response variable (threat probability) by the model under consideration.

(whether a species was considered potentially harmful to humans) had some support (Table 4.5B; Fig. 4.10C)—contrary to expectation, potentially harmful sharks had a lower threat risk than harmless species (Fig. 4.10C). For marine teleosts, length again was positively related to threat risk but accounted for only 6.1% of the deviance in the response (Table 4.6A). The addition of range improved model fit, raising %DE to 11.9% (Table 4.6A). Environmental temperature and habitat also received high support (Table 4.6A),

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Table 4.7 Correlates of marine chondrichthyan and teleost threat risk Model

(A) Phase 1 LNGþRGE þETPþGRP LNGþRGE þGRP LNGþRGE þHBTþETP þGRP LNGþRGE þHBTþGRP LNGþGRP (B) Phase 2 LNGþRGE þETPþGRP LNGþRGE þETPþGRP þGME LNGþRGE þETPþGRP þDGR LNGþRGE þETPþGRP þCMI LNGþRGE þETPþGRP þCMIþGME

k

LL

DBIC

wBIC

DAICc

wAICc

% DE

9 210.160

8.870

0.005 0.000

0.456

8.4

7 212.349

1.056

0.246 0.219

0.409

7.4

11 210.000 20.740 <0.001 3.875

0.066

8.5

9 212.336 13.223

0.001 4.352

0.052

7.5

5 217.917

0.000

0.417 7.235

0.012

5.0

9 210.160

0.000

0.654 0.000

0.378

8.4

10 209.509

4.793

0.060 0.791

0.254

8.7

10 209.968

5.711

0.038 1.709

0.161

8.5

11 209.352 10.574

0.003 2.579

0.104

8.8

12 209.624

0.059 2.209

0.117

9.1

5.132

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecological and life history correlates and (B) Phase 2: human-relationship attributes, after accounting for the effects of length and range (n = 444 species). Models include nested (hierarchical) taxonomic (order/family) random intercepts. Models are ranked according to the small-sample Akaike’s information criterion (AICc). Terms shown are GRP = taxonomic group chondrichthyan or teleost), LNG = length, RGE = range, HBT = habitat, ETP = environmental temperature, CMI = commercial fisheries interest, GME = status as game fish, DGR = danger to humans. Also shown are number of parameters (k), maximum log-likelihood (LL), difference in the Bayesian Information Critertion (BIC) and AICc for each model from the most parsimonious model (DBIC, DAICc), model weight (wBIC, wAICc), and per cent deviance explained (%DE) in the response variable (threat probability) by the model under consideration.

with lower risk predicted for pelagic and higher risk for deepwater species (Fig. 4.9B and C). Including length, range, habitat and environmental temperature in the Phase 2 models, teleosts demonstrated little response to any of the human-relationship attributes considered (Table 4.6B; Fig. 4.10). Combining the two taxonomic groups (marine species only) and setting the Group

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800 Chondrichthyans Teleosts

Number of species listed

700 600 500 400 300 200 100 0

DD

LC

/lc

LR

/cd

LR

/nt

LR

NT

VU

EN

CR

/EW

EX

Proportion of total species listed

0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 DD

LC

/lc

LR

/cd

LR

/nt

LR

NT

VU

EN

CR

/EW

EX

IUCN category (2007)

Figure 4.8 Frequency distribution (top panel: number of species; bottom panel: proportion of species listed per taxonomic group) of chondrichthyans (Classes Elasmobranchii and Holocephalii) and teleosts (Classes Actinopterygii and Sarcopterygii) in the 2008 World Conservation Union’s (IUCN) Red List (www.iucnredlist.org). Categories are ordered left to right from least threatened to most threatened. DD, data deficient; LC, least concern; LR/lc, lower risk/least concern; LR/cd, lower risk/ conservation dependent; LR/nt, lower risk/near threatened; NT, near threatened; VU, vulnerable; EN, endangered; CR, critically endangered; EX/EW, extinct/extinct in the wild.

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Pr(threat for IUCN Red-Listed species)

A 0.5

Chondrichthians Teleosts

0.4 0.3 0.2 0.1 0.0 1 FAO area

2 FAO areas Range

>2 FAO areas

Demersal

Pelagic Habitat

Reef

Deep water

Temperate

Tropical

Pr(threat for IUCN Red-Listed species)

B 0.5 0.4 0.3 0.2 0.1 0.0

Pr(threat for IUCN Red-Listed species)

C 0.5 0.4 0.3 0.2 0.1 0.0

Environmental temperature regime

Figure 4.9 Phase 1 predicted threat risk of IUCN Red-Listed marine chondrichthyan (Classes Elasmobranchii and Holocephalii) and teleost (Classes Actinopterygii and Sarcopterygii) based on generalised linear mixed-effect models that account for phylogenetic relatedness among species (nested random effect ¼ order/family). Risks are predicted as a probability between 0 and 1 relative to the different levels of the three

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term as a fixed effect revealed important support for taxonomic group even after accounting for length (Table 4.7A). This demonstrates that teleosts have a generally higher threat risk than chondrichthyans even after accounting for size differences, although the effect is weak (Table 4.7B).

4.6. Relative threat risk of chondrichthyans and teleosts Our quantitative threat risk analysis revealed some important insights into the relative threat risk of the major marine fish taxa, some of which can appear somewhat counter-intuitive. Of particular importance was the finding that listed teleosts are in general placed more frequently into the higher-risk categories of the IUCN Red List relative to chondrichthyans. However, this is not because the relatively few listed teleosts just happen to be larger-species. Indeed, Red-Listed teleosts were in fact smaller on average than the distribution of all teleosts for which length data were available (Fig. 4.11). The relatively higher threat risk of teleosts compared to chondrichthyans could be misleading, however, if not properly contextualised. Of foremost importance is that only a small proportion of all marine teleosts have been described adequately for a reliable Red Listing (8%), whereas >52% of all known chondrichthyan species have been Red Listed, although many admittedly are placed within the data-deficient category. Therefore, extrapolating true threat risk to the entire marine teleost taxon from the small data set described here is potentially unreliable. Another possible bias is that because of their generally larger size, their stigma in the public eye, and the recent attention brought to the conservation literature regarding their apparently high threat risk, there might be a tendency to list chondrichthyan species at least within the lower threat-risk categories following the precautionary principle. We also found reasonable evidence that disparities in relative threat risk between the two groups did not arise solely from the different size distributions; sharks are approximately one order of magnitude larger on average

ecological and life history trait factors considered: range (number of FAO Fishing Areas – www.fao.org), habitat and environmental temperature regime. See text for full details. The observed threat probability 95% confidence intervals (chondrichthyans: dotted horizontal lines; teleosts: solid horizontal lines) were determined by a 10,000iteration bootstrap of the probabilities predicted by the saturated model over 216 (chondrichthyan) and 228 (teleost) species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iterationbootstrapped upper 95% confidence limits.

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327

Pr(threat for IUCN Red-Listed species)

A 0.5

Chondrichthians Teleosts

0.4 0.3 0.2 0.1 0.0 Artisinal

Pr(threat for IUCN Red-Listed species)

B

No fisheries

0.5 0.4 0.3 0.2 0.1 0.0 Yes

C Pr(threat for IUCN Red-Listed species)

Commercial Fisheries interest

Game fishing

No

0.5 0.4 0.3 0.2 0.1 0.0 Yes

No Dangerous species

Figure 4.10 Phase 2 predicted threat risk of IUCN Red-Listed marine chondrichthyan (Classes Elasmobranchii and Holocephalii) and teleost (Classes Actinopterygii and Sarcopterygii) based on generalised linear mixed-effect models that account for phylogenetic relatedness among species (nested random effect ¼ order/family). Risks are predicted as a probability between 0 and 1 relative to the different levels of the three human-relationship factors considered: fisheries interest, whether a species was

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than teleosts (Fig. 4.11). Indeed, even after accounting for the positive influence of size (length) on threat risk, teleosts were still more likely than chondrichthyans to be classified as threatened. However, we found no evidence for an interaction between Group and the allometry of threat risk, suggesting that the reason for an average higher susceptibility ranking among the teleosts is due to inherently different extinction proneness between the two groups. While sharks might not have necessarily experienced the same magnitude of deterministic decline as Red-Listed teleosts (the declining population paradigm), their larger size and lower fecundity (the latter not included in the analysis) could indeed predispose the taxon to a higher risk of extinction overall (the small population paradigm) (Brook et al., 2006, 2008; Caughley, 1994; Traill et al., 2007). Another important consideration is that total chondrichthyan species richness is considerably lower than for teleosts. Indeed, there are nearly 30 times more teleost species listed in FishBase than chondrichthyans (Table 4.1). This implies that the relative effect of extinction on total chondrichthyan species diversity is considerably higher than the loss of a single species on teleost diversity. This alone could be argued as sufficient justification to consider chondrichthyans as a special case for marine fishes, although it does not negate the obvious conclusion that there are insufficient data for teleosts to make strong inference regarding the true threat risk of that taxon.

5. Implications of Chondrichthyan Species Loss on Ecosystem Structure, Function and Stability 5.1. Ecosystem roles of predators The loss of a single species is an evolutionary tragedy in its own right; however, when species loss triggers the degradation of entire biological communities, the importance of their conservation increases. There is now a rich body of evidence and theory demonstrating how predators of all major trophic levels influence the ecosystems in which they live (Baum and game-fished and whether a species was considered dangerous to humans. See text for full details. The observed threat probability 95% confidence intervals (chondrichthyans: dotted horizontal lines; teleosts: solid horizontal lines) were determined by a 10,000iteration bootstrap of the probabilities predicted by the saturated model over 216 (chondrichthyan) and 228 (teleost) species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iterationbootstrapped upper 95% confidence limits.

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All chondrichthyans All teleosts Red-listed chondrichthyans Red-listed teleosts

1.5

3.0

Density

2.0 0.9 1.5 0.6 1.0 0.3

0.5

0.0

Density (IUCN red-listed species)

2.5

1.2

0.0 0.0

0.5

1.0

1.5

2.0

2.5

3.0

5.4

6.4

log10 length (cm) 0.6

0.5

Density

0.4

0.3

0.2

0.1

0.0 0.4

1.4

2.4

3.4

4.4

7.4

log10 weight (g) 1.0

Density

0.8

0.6

0.4

0.2

0.0 0

1

2

3

4

5

6

7

8

log10 maximum fecundity (eggs/female)

Figure 4.11 Distribution of life history traits between chondrichthyans (Classes Elasmobranchii and Holocephalii) and teleosts (Classes Actinopterygii and Sarcopterygii). Top panel: density distribution of log10-transformed body length (cm), showing all species and only the IUCN Red-Listed species for each taxon used in the threat-risk analyses. Middle panel: density distribution of log10-transformed body weight (g). Bottom panel: density distribution of log10-transformed fecundity (eggs/female).

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Worm, 2009). Most pertinent is the suite of processes known as trophic cascades which are defined as ‘reciprocal predator–prey effects that alter the abundance, biomass or productivity of a population, community or trophic level across more than one link in a food web’ (Pace et al., 1999). This concept has been further simplified into two discrete categories known popularly as ‘top-down’ or ‘bottom-up’ control. Top-down control is a trophic cascade where lower food-web component species are regulated by an upper-level predator, whereas, in contrast, ‘bottom-up’ control is the regulation of food-web components by primary producers or the input of limiting resources into a system (Pace et al., 1999). Although a system can demonstrate a predominant type of trophic cascade, many ecosystems demonstrate elements of both bottom-up and top-down control (Pace et al., 1999). There are many examples of terrestrial trophic cascades, although most of the empirical evidence and theory has been garnered from lakes, streams and intertidal zones (Pace et al., 1999). Examples range from killer whales regulating kelp forest growth via predation on otters and the subsequent increase in herbivorous sea urchins (see more detail in Section 5.2), to mosquitoes affecting protozoan abundance that changes bacteria composition in pitcher plants (see Pace et al., 1999 for a review). The main way in which predators tend to propagate indirect effects down trophic webs is by directly altering the numerical abundance of herbivores, but predators can also modify herbivore foraging behaviour in response to variation in perceived predation risk (Schmitz et al., 2004). Indeed, there is evidence that shifting predation risk in the presence of different predator types affects plant community composition, leading to changes in net primary production and nutrient cycling (Schmitz, 2003, 2008; Schmitz et al., 2004). The loss of predators in many ecosystems reduces species richness, leading to reduced community stability, lower productivity and nutrient cycling (Duffy, 2006; Schmitz, 2008; Schmitz et al., 2000; Stachowicz et al., 2007; Worm et al., 2006) (Fig. 4.12). This in turn reduces ecosystem resilience to stochastic perturbations that operate independently of community structure or species abundance (such as severe El Nin˜o events, intense storms and tsunamis) (Hughes et al., 2005). Such changes in community structure are thought to arise through direct reduction in predator abundance that leads to cascading trophic imbalances and re-equilibration to new stable states (see Scheffer et al., 2001). These situations of ‘predator release’ of prey usually change the foraging capacity (such as increased herbivore or meso-predator survival rates) and alter foraging behaviour (O’Connor and Bruno, 2007). The subsequent decline in plant biomass through increased grazing pressure depends on the strength and number of linkages in a particular food web (Halaj and Wise, 2001; Polis and Strong, 1996). Therefore, the strength of top-down effects of predator reduction and loss will vary between ecosystems with the complexity of food webs, and

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Eutrophication

Overfishing

Benthic Habitat Disturbance

• High diversity • High structural complexity • High fish production • High water clarity • High sediment stability • High resilience

• Low diversity • Low structural complexity • Low fish production • Low water clarity • Low sediment stability • Low resilience

Figure 4.12 An example of how predator removal and other human-mediated changes to marine ecosystems reduce species richness, habitat structure and ecosystem function. Here, over-fishing of higher fish predators, eutrophication and benthic habitat disturbance all lead to a depauperate biological community in this seagrass ecosystem (reproduced with permission from Duffy, 2006).

compensation can occur where changes in the upper trophic levels do not necessarily impact lower levels (Pace et al., 1999). Furthermore, ecosystem changes can arise from the different functions of a predator species where there is niche partitioning of age and life-cycle stages (Bolnick et al., 2003; Field et al., 2005; Pace et al., 1999; Polis, 1984; Schmitz et al., 2004; Taylor and Bennett, 2008).

5.2. Predator loss in the marine realm Worldwide, there is much concern regarding changes seen in marine environments through observed shifts in ecosystem composition and the subsequent loss of resources and ecosystem services (Hughes et al., 2005; Shurin et al., 2002; Worm et al., 2006). Although the effects of marine predator loss in marine systems is difficult to quantify given the clandestine lifestyle of many large predators (Bradshaw, 2007), there is growing empirical evidence describing the role of predatory species in modulating trophic cascades and top-down control across a range of marine ecosystems (Bascompte et al., 2005; Bruno and O’Connor, 2005; Byrnes et al., 2006; Duffy, 2006; Dulvy et al., 2004b; Frank et al., 2005, 2007; Hughes et al.,

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2005, 2007; Jennings and Kaiser, 1998; O’Connor and Bruno, 2007; ¨ sterblom et al., 2006). However, the true function of large marine preO dators and the potential implications of their loss is still not clearly understood for most ecosystems (Bruno and O’Connor, 2005). A good example of a marine trophic cascade is the top-down control of kelp (Macrocystis spp.) forests by sea otters (Enhydra lutris) and other predators (Byrnes et al., 2006; Estes et al., 1998). In western Alaska, sea otter populations transformed nearshore reefs from two- to three-trophic level systems by limiting the distribution and abundance of herbivorous sea urchins, thereby promoting kelp forest development (Estes et al., 1998). Many otter populations are now in abrupt decline over large areas due to increased killer whale predation. This has reduced predation rates by otters on sea urchins, leading to higher urchin densities and greater deforestation of kelp beds. Other predators influence these trophic cascades in kelp forests where otters are absent. Byrnes et al. (2006) showed that crabs (Cancer productus and Cancer magister) and starfish (Pycnopodia helianthoides) play a large role in maintaining kelp forest biomass by regulating herbivore numbers including the snails Tegula brunnea and Tegula funebralis, urchins Strongylocentrotus purpuratus and Strongylocentrotus franciscanus, and a crab Pugettia producta. Although no evidence for direct links between predator and prey densities was found, changes in kelp mass were related to changes in herbivore foraging behaviour with relative predation risks. Similar effects have been seen in seagrass communities (Byrnes et al., 2006; Duffy, 2006). Predatorinduced changes have also been described for other coastal ecosystems where carnivorous fishes (such as blennies Hypleurochilus geminatus and Hypsoblennius hentzi, killifish Fundulus heteroclitus and pinfish Lagodon rhomboides) have regulated numbers of herbivores that control algal diversity and biomass (Bruno and O’Connor, 2005; O’Connor and Bruno, 2007). Another example documented in the Caribbean, Indian and western Pacific Oceans is the change of coral reef ecosystems to macroalgal-dominated communities (Dulvy et al., 2004b; Hughes et al., 2003, 2005, 2007; Pinnegar et al., 2000; Rogers and Beets, 2001). These are often complex systems with feedback loops through mechanisms such as nutrient cycling (McClanahan, 1997) and Allee population effects (Dulvy et al., 2004b). In continental-shelf and open-ocean ecosystems, trophic cascades or changes in fish community structure (Frank et al., 2005; Hughes et al., 2005; Levin et al., 2006; Link and Garrison, 2002; Mangel and Levin, ¨ sterblom et al., 2006; Shiomoto et al., 1997) can occur, although 2005; O there is some debate (see Frank et al., 2007; Parsons, 1992; Reid et al., 2000). Trophic changes have been noted in relatively simple systems like the Barents Sea where top-down and size-selective predation by fish have influenced zooplankton composition and abundance (Reid et al., 2000), and in the North Pacific for salmon predation on zooplankton altering the abundance of phytoplankton (Shiomoto et al., 1997). Until recently,

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however, continental-shelf ecosystems were thought to be largely immune to top-down control because of their relatively wide-distribution, high species diversity and food web complexity (Steele, 1998). Currently, it is thought that these can affect elements of the trophic web or the entire ecosystem (Frank et al., 2005) as a combination of top-down and bottom-up processes. This has resulted in predator replacement, increased production at lower trophic levels and/or long-term ecosystem-level change (Frank et al., 2007). Furthermore, these long-term ecosystem changes might be responsible for the slow or failed recovery many previously exploited fish populations (Hutchings, 2000; Shelton et al., 2005; Worm and Myers, 2003).

5.3. Ecosystem roles of chondrichthyans Chondrichthyans are generally apex predators, so predicting the effects of their removal are complex. As with other large species of predatory fishes, not only does their removal release prey populations from a major mortality source, the reduction in predators can sometimes have unexpected second- and thirddegree implications for non-prey species through trophic linkages (Baum and Worm, 2009; Schindler et al., 2002; Stevens et al., 2000) that can in turn affect ecosystem functions (Worm et al., 2006). The role of sharks in maintaining diversity and ecosystem structure are virtually unexplored (Camhi et al., 1998). Although there have been many diet studies (e.g. Bethea et al., 2006; Ellis and Musick, 2007; Estrada et al., 2006; Huveneers et al., 2007; Polo-Silva et al., 2007; Saidi et al., 2007; Simpfendorfer et al., 2001; Stevens and Wiley, 1986), only a few recent studies have explored the role of chondrichthyan predators in ecosystem structuring, and most have focused on species or ecosystems of economic importance (Kitchell et al., 2002; Stevens et al., 2000). Ecosystem modelling using ECOPATH/ECOSIM models (Walters et al., 1997) predicted the effects of top-predator removal on many ecosystems, with varying results (Kitchell et al., 2002; Stevens et al., 2000). Stevens et al. (2000) modelled these effects in three environments: a tropical shelf ecosystem in Venezuela, a Hawaiian coral reef and a North Pacific oceanic ecosystem. This comparison of a broad range of ecosystems, each dominated by a different functional group of sharks, demonstrated different outcomes when predators were reduced or removed, but predictions were imprecise. Each model showed that some relatively minor prey species for the sharks in each system underwent large increases in biomass after shark removal. For example, turtles and reef sharks following reductions of tiger sharks in Hawaii; seals in the North Pacific following the removal of salmon sharks, and croakers (e.g. Plagioscion spp.) in Venezuela following the removal of small triakid sharks, principally the smooth dogfish Mustelus canis. In contrast, some seemingly important prey groups decreased in biomass. In the North Pacific and Venezuelan systems, at least one non-shark prey

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group decreased in abundance, most likely as a result of complex trophic interactions. The main conclusion was that the effects of shark reductions across ecosystems are often difficult to foresee, but might be ecologically and economically important and persist over long periods of time. Another ECOPATH/ECOSIM modelling exercise examined the potential role of sharks and longline fisheries on pelagic ecosystems in the central North Pacific. Kitchell et al. (2002) evaluated changes in trophic interactions for the central Pacific Ocean and showed that the removal of blue sharks produced compensatory responses favouring other shark species and billfishes, and that their removal had only modest effects on the majority of species. However, intra- and inter-specific predation on juvenile elasmobranchs produced strong, non-linear declines in shark populations. Overall, the model revealed that blue sharks in this system are not ‘keystone’ predators, although if more sharks are removed by longline fisheries, food webs were predicted to degrade. One of the first studies to identify predatory release of elasmobranch mesopredators was in the Gulf of Mexico where coastal shrimp fishing caused by-catch population declines of over 95% in bonnethead sharks (S. tiburo), Bancroft’s numbfish (Narcine bancroftii) and smooth butterfly ray (Gymnura micrura) (Shepherd and Myers, 2005). Combined with fishing reductions in other large shark species in the pelagic longline fishery (Baum et al., 2003), increases in deeper water elasmobranchs such as Atlantic angel sharks (Squatina dumeril) and smooth dogfish (M. canis) were observed. Open-ocean ecosystems have been considered more resilent to predator loss (Steele, 1998), although changes in both the size of shark catches and species composition have been described in the Pacific Ocean (Ward and Myers, 2005). Removal of individuals from larger species, for example, blue, silky and thresher sharks, black marlin (Makaira nigricans) and blue marlin (Makaira indica), caused a coincident increase in smaller species such as pelagic stingray (Dasyatis violacea), skipjack tuna (Katsuwonus pelamis) and pomfrets (Bramidae). More recent empirical evidence has demonstrated how changes to chondrichthyan abundance and structure, mainly through harvest, have altered marine communities and caused trophic cascades. The loss of elasmobranch diversity in the coastal northwest Atlantic has had cascading effects down to even invertebrate species (Myers et al., 2007). Over the last 35 years, there has been a large reported decline in 11 of the great shark species (i.e. >85% for bull, dusky, smooth and scalloped hammerhead, tiger, blacktip and sandbar sharks; Fig. 4.5) that hunt other elasmobranch mesopredators. These declines have allowed many mesopredator populations to increase and restructure the ecosystem, with the corollary that large sharks have become functionally eliminated. Higher densities of cownose ray (Rhinoptera bonasus) were linked to large reductions in bivalve biomass (Blaylock, 1993) such as scallops Argopecten irradians (Peterson et al., 1996).

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Indeed, the subsequent reduction and likely depletion of scallop populations can cause rays to switch to soft and hard clams (e.g. Mya arenaria, Mercenaria mercenaria) and oysters (Crassostrea virginica) that themselves have been reduced by harvesting and other anthropogenic impacts. Other species of mesopredators such as skates in the north-eastern Atlantic (Dulvy et al., 2000) and the long-headed eagle ray (Aetobatus flagellum) around Japan (Yamaguchi et al., 2005) might have also been released from predation by larger sharks, although these systems have not yet been examined in sufficient detail. Of course, many chondrichthyans, especially smaller species, are not apex predators. Yet, there is some evidence that many benthic and demersal species can have important functional roles in marine systems. For the cownose ray, foraging behaviour is also destructive to shallow habitats through the uprooting of seagrasses (Smith and Merriner, 1995), thus exacerbating any cascading effects that might arise from apex predator reduction. Skates can play an important functional role in benthic systems. On the Scotian Shelf, the proportional biomass of skates is low, and therefore might not be considered important for demersal fishes (Duplisea et al., 1997). However, skates have a similar ecological role to flatfishes (Pleuronectidae), and together the two groups represent the majority of the benthic fish biomass on the Scotian Shelf. These species provide an important energy-flow pathway from the benthos and at least one component of the demersal fish assemblage by eating and processing benthic invertebrates (Martell and McLelland, 1994). Therefore, changes in abundance or diversity of either of these mesopredator groups are likely to have an effect on both benthic and demersal ecosystems. In support of evidence found in the terrestrial realm (e.g. Schmitz, 2008), the mere presence of shark predators can alter the foraging behaviour of their prey species, leading to altered ecosystem states. An example of non-lethal predator effects is the regulation of green sea turtle (Chelonia mydas) foraging behaviour by tiger sharks (Heithaus et al., 2007). Turtles in poor body condition foraged on higher quality seagrass beds with high risk of predation by sharks, whereas turtles in good condition foraged on lower quality seagrass beds where fewer predators hunted. A reduction or removal of tiger sharks is therefore predicted to result in greater foraging pressure on high-quality seagrass beds leading to potential overgrazing (Rose et al., 1999).

6. Synthesis and Knowledge Gaps 6.1. Role of fisheries in future chondrichthyan extinctions Despite the controversies and general paucity of good data, there is no question that fishing decreases the probability of survival of individual fishes. Relying on the assumption of density compensation, sustainable and

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low-impact harvests are certainly possible for any exploited fish species, especially for those with rapid generation times and fast growth rates (Hilborn and Walters, 2001; Walters and Martell, 2004). It is only when populations are reduced at rates greater than any gains achieved through density compensation that large population decline becomes inevitable. Population decline itself does not necessarily result in heightened extinction risk, especially if initial population size is large. The declining population paradigm on which much of the IUCN’s Red List classification is based does tend to indicate when population decline becomes cause for concern. In other words, decline can become an issue if the current population size is vastly inferior to some original baseline estimate. However, only when population sizes fall below a MVP size does the risk of extinction rise to non-negligible values (Traill et al., 2007, 2009). Of course, a rare species might already have small initial population sizes, in which case the probability of dropping below MVP with fishing harvest is much higher. Do fisheries contribute to higher extinction risk in chondrichthyans? As for all deterministic drivers of population decline, the answer is ‘yes’; however, it depends entirely on the species in question, the magnitude of decline and the population’s relative distance from a species-specific MVP size (Traill et al., 2009). Our review has highlighted and reinforced the understanding that large species with correspondingly slower growth rates, longer generation times and later ages of maturity are more susceptible to possible extinction risks. Importantly, we have determined that although Red-Listed teleosts have a generally higher assessed threat risk than chondrichthyans, the relatively larger chondrichthyans with lower fecundity, in themselves, suggest that high harvest-rate fisheries have a potentially greater capacity to drive certain chondrichthyan populations to sub-MVP size, especially those that already exist at low densities. There is little debate regarding the future of demand for fish products. An ever-increasing human population and greater propensity for coastal living means that chondrichthyans stand to experience some intense harvest as demand for their products continues to rise (Clarke et al., 2006; Food and Agriculture Organization of the United Nations, 2005). Indeed, as coastal resources become more and more heavily harvested, it is likely to be the pelagic mixed-species fisheries that will be called upon to supply the bulk of the demand. As highlighted, these mixed-species fisheries and their associated by-catch represent some of the greatest mortality sources for rare chondrichthyans, and currently there is little to no management or monitoring of any high-seas fisheries (Mucientes et al., 2009). Coupled with more advanced technological capacity (Roberts, 2002), an increasing human population also means that the quest for previously unavailable or difficult-to-access fish resources will expose more and more species to a previously unknown mortality source. In particular, deepwater fishing is growing in reach and expanse. This is potentially problematic given the

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predicted slower life histories of cold water, deep-dwelling species that have likely much lower intrinsic rebound potential than meso-pelagic species. The endeavour to determine a species-specific MVP size and relate estimates of stock size to this should be one of the foremost goals of any management strategy for chondrichthyan harvest. However, ensuring that a population does not fall below MVP should only be regarded as an absolute minimum baseline, for MVP is typically estimated as the population size below which the probability of (quasi)extinction becomes unacceptable, typically greater than 1% (Shaffer, 1981; Traill et al., 2007). True sustainability should therefore regard the harvest in terms of population trends rather than population size. In other words, instead of setting PVA to estimate the probability of falling below a quasi-extinction threshold, the focus should shift to setting a minimum population size above which decline becomes unlikely. If a population does, however, fall below its MVP, then continued fishing pressure might be outweighed by stochastic factors that act synergistically to increase extinction risk (Brook et al., 2008). In summary, sustainable chondrichthyan fisheries are possible, but these must strive for stability rather than attempt to maximise yield (Hilborn et al., 2003). In the words of Hilborn (2007): It is almost universally recognized that the future of sustainable fisheries lies with much less fishing effort, lower exploitation rates, larger fish stocks, dramatic reduction in bycatch, increased concern about ecosystem impacts of exploitation, elimination of destructive fishing practices, and much more spatial management of fisheries, including a significant portion of marine ecosystems protected from exploitation.

6.2. Climate change The current rate of global climate warming is greater now than at any time in the last 1000 years (Walther et al., 2002) and has been of increasing concern and research focus in recent decades (e.g. Graham and Harrod, 2009; Hughes et al., 2003; Munday et al., 2008; Roberts and Hawkins, 1999; Roessig et al., 2004). As a result of climate change, extinction rates over the next century are predicted to be greater than otherwise expected (e.g. Hansen et al., 2006), particularly for endemic and range-restricted species (Ahonen et al., 2009; Brook et al., 2008; Munday et al., 2008). In addition to the predicted effects associated with increases in both maximum and minimum temperatures, daily minimum temperatures are increasing more rapidly than daily maximum temperature (Vose et al., 2005), with high spatial heterogeneity expected in the response of organisms, populations and ecological communities (Genner et al., 2004). Chondrichthyes is therefore one taxon that could be, on average, at relatively high risk to climate change effects due to slow rates of evolution and low phenotypic

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plasticity that might otherwise enable quick adaptation to rapidly changing environmental conditions (Daufresne et al., 2009; Harley et al., 2006; Visser, 2008). Climate change will also probably influence the phenology and physiology of some species (Sims et al., 2001, 2004), with the most probable response including shifts in distribution and changes in the timing of migrations. The resultant changes to top-down control by shifting densities and configuration of the large predator guild, and the corresponding bottom-up changes expected from shifting community structure in lower trophic levels and nutrient cycling pathways (Walther et al., 2002) are complex and presently impossible to predict reliably. Although it is possible that climate changes might benefit some species, the rapid pace of change combined with pressure from other threats might mean that more species will respond negatively (Brook et al., 2008; Daufresne et al., 2009; Visser, 2008). The direct effects of environmental change likely to affect chondrichthyans are the same that will influence all marine life, namely increases in temperature, and changes to water chemistry (Fig. 4.13). Although most species demonstrate some physiological plasticity in their tolerances to environmental conditions, many species are expected to shift their distributions to areas conducive to maintaining physiological optima, thus we might expect a shift toward higher latitudes (McMahon and Hays, 2006; Rose, 2005). Migratory fish species are already showing changes in their ranges. For example, basking shark foraging behaviour is highly correlated with thermal ocean features, and shifted distributions northward might have occurred in the recent past (Sims and Reid, 2002), and would be more likely to occur in the future as more rapid climate warming alters thermal stratification and the strength and persistence of fronts with consequent distribution changes of its plankton prey (Cotton et al., 2005; Sims, 2008). Temperature and salinity changes are also having effects on ocean circulation (Clark et al., 2002). These will enhance changes to local environmental conditions and the distributional response of their biological communities (Harley et al., 2006). Another direct effect might be the increasing prevalence of disease and emergence of novel pathogens with increasing temperatures (Clark et al., 2002; Harvell et al., 1999, 2002, 2004; Ward and Lafferty, 2004). For coastal shark and rays species, sea-level rise will alter shallow water environments, affecting especially those that have specific habitat requirements (e.g. mangroves) for breeding, pupping or feeding (Heupel et al., 2007). Sea-level rise might also lead to large-scale habitat loss for some species and disrupt coastal and estuarine ecosystems. The effects of increasing frequency of extreme weather condition and intense storm events are likely to affect behavioural changes, destroy habitats and change community structure (Heupel et al., 2003; Scheffer et al., 2001). Other effects of climate change that might influence bottom-up processes are ozone depletion and ocean acidification. Ozone depletion affects

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Increased greenhouse gas concentrations

Human activities

Increased air temperature

Increased UV

Intensified atmospheric pressure gradients Increased storm frequency

Sea-level rise Increased Increased water CO2 Intensified temperature upwelling (?) Decreased pH

Figure 4.13 Abiotic changes to oceans predicted from climate change (reproduced with permission from Harley et al., 2006). The burning of fossil fuels and deforestation increase atmospheric greenhouse gas concentrations, which lead to physical and chemical changes to ocean waters. The effect of climate change on upwelling and current processes is most uncertain.

surface phytoplankton (Zepp et al., 2003) and subsequent productivity of other trophic levels. Ocean acidification has also been identified as a major threat to corals and some calciferous organisms through dissolution of their external calcium carbonate skeletons (Orr et al., 2005). Although acidification to this extent will be unlikely to affect chondrichthyans directly, large potential changes are likely to alter habitat, marine community structure and prey availability for shark predators.

6.3. Extinction synergies Recent empirical and theoretical work is beginning to identify how different factors interact synergistically to exacerbate extinction risk (Brook et al., 2008). Even when systematic threats such as intensive harvest via fishing do not result in immediate extinction, a combination of secondary processes can eventually cause a species to become extinct. For example, habitat fragmentation and over-harvesting can be exacerbated by climate change. Co-extinctions represent another synergistic process which precipitates species loss more rapidly than otherwise expected. Examination of interspecific dependencies demonstrated that many thousands of currently nonRed-Listed species could go extinct alongside their listed symbionts due to these dependencies (Koh et al., 2004). Dependencies might also derive from

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community interactions such as the meso-predator release examples provided in Section 5 (e.g. the reduction in large predatory sharks leading to an expansion of medium-sized chondrichthyans that in turn drive a decline in scallops; Myers et al., 2007). From the chondrichthyan perspective specifically, synergies among harvesting, habitat changes and climateinduced changes to marine environments are most likely to occur in the coastal realm.

6.4. Research needs There have been great leaps in our understanding of Chondrichthyes populations since Camhi et al. (1998) identified a series of research needs for this taxon. Our review has expanded and updated this list by highlighting the important remaining knowledge gaps required to assess extinction risk in this taxon. We therefore offer a list of priorities for research that will enable better assessment and reduce the probability of overlooking and underestimating threats within a precautionary management and conservation framework. In order of relative importance, these are (1) estimation of minimum population sizes and the degree of life history specialisation, (2) trophic interactions and cascades, (3) expanded fisheries monitoring, (4) potential and measured effects of climate change, (5) assessing the implications of habitat loss and degradation and (6) the consequences of genetic erosion on population dynamics and resilience. Despite the recommended hierarchy, all recommendations are interlinked, as are their influences and consequences. As with most ecological research, carefully planned and orchestrated multi-disciplinary approaches can provide robust and cost-effective data. In recent years, many chondrichthyan species have been added to the IUCN Red List. However, none of these are based on quantitative assessments of populations relative to estimated MVP size. Instead, most listings understandably rely on sparse data describing possible distribution and relative abundance changes. PVA are sorely needed for most of the species of highest concern, and these all require specific demographic and population data. However, there are limited demographic and population data available at present for most chondrichthyan species. Often surrogate demographic estimates from congeners or family members have been used in place of known information. Therefore, the highest priority for research is to obtain speciesspecific demographic data such as survival rates, fertility patterns and spatial range. Detailed information is also required on the degree of life history specialisation, including studies examining ontogeny, foraging niches, and intra- and inter-specific competition. These data are essential to determine whether particular life stages are relatively more vulnerable to specific threats, which can inflate estimates of extinction risk for entire populations or species. The ecological interactions between chondrichthyans and their capacity to induce trophic cascades require much more focused study, including

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experimental, observational and modelling approaches. Although there have been a few ECOSIM/ECOPATH modelling studies (Kitchell et al., 2002; Stevens et al., 2000) and some quantitative analyses of time series in this regard (e.g. Myers et al., 2007), we currently have only a rudimentary understanding of how ecosystem changes will influence chondrichthyan extinction risk and affect the marine communities to which they belong. With increasing demand for fisheries to provide food for a large, growing human population, we need better, more systematic and wide-coverage monitoring of chondrichthyan catch data and market trends to identify species in decline (e.g. Casey and Myers, 1998; Mucientes et al., 2009). Baseline data, even if they do not represent unexploited biomass, are required for the majority of harvested species. Monitoring designs must also include detailed inventories of species and sex composition and age/size structure from catches so that whole-population status can be assessed more readily. Such monitoring requires an important at-sea component to measure the magnitude of bycatch, especially in mixed-species fisheries, and the proportion of non-morbid individuals returned alive. Market surveys can also provide information to assess the relative contribution of IUU fishing on population trends (e.g. Clarke et al., 2006). Historical and commercial data sets must also be made freely available to the research community for effective cross-examination and interpretation (e.g. Baum et al., 2005; Burgess et al., 2005a). There is a good understanding of the potential effects of temperature change for many individual marine species. However, the simplistic relationships between temperature and biota do not necessarily provide a good predictive platform for understanding climate change effects on future marine community structure and composition (Harley et al., 2006). More dedicated experimental and time series data are required to test specific hypotheses on potential range shifts, adaptation capacity and physiological tolerance envelopes for most species (Graham and Harrod, 2009). Synergies among extinction drivers require greater focus, especially for species living in environments where risks overlap (see Halpern et al., 2008). Chondrichthyans have evolved over many hundreds of millions of years and the taxon has persisted in spite of two mass extinction events. The genetic implications of small, bottlenecked populations must also be of primary focus in molecular studies to determine the relative contribution of potential inbreeding depression on estimates of chondrichthyan extinction risk.

7. Concluding Remarks We are still in the fortunate situation that there are no recorded cases of chondrichthyan extinction in modern times. However, we have identified that the largest, most range-restricted and heavily harvested species

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might be easily pushed below their MVP sizes, which could be much larger than those estimated under stable environmental conditions. Fishing, at all scales, represents one of the largest mortality sources for many chondrichthyan species, but there are some examples of small local fisheries that have operated without clear declines in population size of targeted species. However, mixed-species fisheries that harvest poorly measured, but presumably large quantities of chondrichthyans are of particular concern, as is IUU fishing. The lack of specific management and reporting mechanisms for the latter types means that many species might already be reduced to densities where extinction risk is unacceptably high. It is almost universally recognised now that so-called ‘sustainable’ fisheries will have to be the norm if they are to survive economically, and that they will have to demonstrate negligible or minimal impacts to ecosystems through careful management and stewardship (Hilborn, 2007). IUU fishing can affect shark populations and community structure, and this might be a far greater challenge to control. Recreational fishing and beach meshing can also contribute to local declines. Climate change and habitat degradation will further erode certain populations to the point where extinction risk rises appreciably. The idea that chondrichthyans have life history characteristics that might predispose them to extinction in a rapidly changing world (e.g. relatively low reproductive potential, growth and capacity for population recovery; Pratt and Casey, 1990) is generally upheld by our results. Furthermore, because chondrichthyans tend to occupy the highest trophic levels, it is arguable that degradation of marine communities might limit the prey quality and quantity available to chondrichthyan predators, further exacerbating population reductions. We found no strong evidence, from admittedly simple models with few parameters, that chondrichthyans are intrinsically more susceptible to extinction than other marine fishes in relation to their evolved niches and life history characteristics. However, chondrichthyans tend to be larger than many other marine fish taxa, and large body size generally correlates with slower growth and lower reproductive capacity. As such, it is the rapid pace of environmental change and harvesting that have the greatest potential to impede certain species from maintaining large population sizes. Any species can withstand moderate to even extreme exploitation if it does not outpace intrinsic replacement rates and adaptation potential (Brook et al., 2008). We were unable to examine all plausible correlates of threat risk due to data paucity. Many studies have examined age at maturity and growth rates in terms of vulnerability to extinction, with late-maturing and slow-growing species apparently at greater risk (Reynolds et al., 2005). Therefore, a better compilation of data incorporating these and other possible correlates could reveal further subtleties in the drivers of threat risk in this taxon and other marine fishes. Another caveat is that predictors of threat risk indicate a

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species’ sensitivity to the largely systematic (deterministic) drivers of population decline (declining population paradigm) (Cardillo, 2003; Sodhi et al., 2008a), whereas actual extinction appears to correlate poorly with ecological and life history traits given that the final coup de graˆce tends to result from largely stochastic processes that act independently of a species’ evolutionary history (Brook et al., 2006, 2008; Sodhi et al., 2008b; Traill et al., 2007) There are many examples of how large predators influence communities and ecosystems via top-down (and in some cases, bottom-up) control of species occupying lower trophic levels. Thus, the removal of large predators can elicit trophic cascades and destabilise the relative abundance of smaller prey and non-prey species. However, these effects are still poorly understood, especially for large, complex trophic webs where interactions are largely unquantified. Specifically, chondrichthyans can alter prey diversity and size distributions, and their mere presence can affect the foraging behaviour of prey that alters ecosystem functions such as nutrient recycling and structural habitat complexity. Severe predator depletions can lead to permanent shifts in marine communities and alternate equilibria. Management of shark populations must therefore take into account the rate at which drivers of decline affect specific species. Only through detailed collection of data describing demographic rates, habitat affinities, trophic linkages and geographic ranges, and how environmental stressors modify these, can extinction risk be estimated and reduced. The estimation of MVP sizes is an essential component of this endeavour and should, in our view, eventually accompany the current approaches used to manage sharks worldwide.

ACKNOWLEDGEMENTS We thank V. M. Peddemors and D. Sims for helpful comments to improve the manuscript and K. Mines for assistance compiling the database. This work was supported by an Australian Research Council (ARC) Linkage Project grant LP0667702, the Northern Territory Government (Fisheries Group) and the Northern Territory Seafood Council.

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C H A P T E R

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Effects of the Prestige Oil Spill on the Biota of NW Spain: 5 Years of Learning Milagros Penela-Arenaz, Juan Bellas, and Elsa Va´zquez Contents 366 373 373 373 376 383 384 386 386 390

1. Introduction 2. Effects of the Prestige Oil Spill on the Marine Biota 2.1. Adtidal 2.2. Plankton 2.3. Benthos 2.4. Fishing resources 2.5. Seabirds 2.6. Marine mammals and turtles 3. Conclusion References

Abstract On 19 November 2002, the oil tanker Prestige broke into two and sank in the Atlantic Ocean 260 km off the north-western coast of Spain, releasing about 63,000 tonnes of Bunker C oil. The accident represented one of the largest environmental catastrophes in the history of European navigation. More than 1000 km of coastline and a huge variety of habitats were affected, ranging from supralittoral, intertidal and sublittoral levels to oceanic and bathyal environments. In this chapter, we review published results regarding the impact of the Prestige oil spill on marine organisms, at levels of biological organisation ranging from the molecular to the ecosystem. Although some research is still in progress, all results indicate a strong initial impact during the first year after the spill, mainly on intertidal communities and fishing resources, with recovery by 2004.

Departamento de Ecoloxı´a e Bioloxı´a Animal, Facultade de Ciencias do Mar, Universidade de Vigo, 36310 Vigo, Spain Advances in Marine Biology, Volume 56 ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56005-1

#

2009 Elsevier Ltd. All rights reserved.

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1. Introduction The oil tanker Prestige broke into two and sank in the Atlantic Ocean 260 km off the north-western coast of Spain on 19 November 2002, releasing about 63,000 tonnes of Bunker C oil. The accident represented one of the largest environmental catastrophes in the history of European navigation (CEDRE, 2009). More than 1000 km of coastline were affected, from the northern coast of Portugal to Brittany and the southern coast of the United Kingdom, including protected areas of great ecological and economic value (Rousseau, 2003). A huge variety of habitats were affected by the Prestige oil spill (hereafter, POS), ranging from supralittoral, intertidal and sublittoral levels to oceanic and bathyal environments, which include important fisheries and highly diverse biological communities (Fig. 5.1). The economic losses in Galicia, due to the POS, have been estimated at !566.97 million (lower bound estimate) for the period 2002–2004, including short-term losses in all economic sectors affected, accountable environmental losses, and cleaning and recovery costs (Loureiro et al., 2006). The total costs associated with the POS are therefore rather significant for a small economy such as that of Galicia, since they represent about 1.57% of the total Galician Gross Domestic Product (!36,097 million in 2002). Total losses in the affected area (Galicia, Asturias, Cantabria and the Basque

B

© ESA 2002

A

0

100

200

kilometres Accident 13/11/2002 France

Sinking site 19/11/2002 50 km

Spain Portugal

Figure 5.1 (A) Satellite image (European Space Agency) showing the trail of crude oil left by the tanker Prestige, from the initial spill on 13 November to the final sinking site on 19 November 2002. (B) Map of the shorelines polluted by the Prestige oil spill in northern Spain and south-western France. Source: Oficina Te´cnica de Vertidos Marinos. Ministerio de Educacio´n y Ciencia (http://otvm.uvigo.es/accidentprestige/ litoralafectado.html).

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Country) in 2002–2004 amounted to !770.58 million, according to estimates from Loureiro et al. (2006). Crude oil consists of a complex mixture of compounds predominated by hydrocarbons. The compounds include straight, branched or cyclic chains, including aromatic compounds (with benzene rings) which constitute the most toxic components of oil for marine biota. Non-hydrocarbon compounds containing sulphur, nitrogen or metals may constitute up to 25% of the oil (Clark, 2001). The Prestige oil was classified as fuel oil No. 6, the characteristics of which include low solubility and low capacity for dispersion, slow degradation, and high viscosity, adherence and density. The volatility of the oil is also relatively low (5–10%) because it contains relatively high amounts of high-molecular-weight hydrocarbons, such as polycyclic aromatic hydrocarbons (PAHs) (Table 5.1). After the POS, the oil showed a tendency towards the formation of stable emulsions in water; these emulsions sank due to the strong swell, which favoured their deposition on the sea bottom and movement of the oil toward the coast. Analyses carried out by the Spanish National Research Council (CSIC) showed that the Prestige fuel oil was mainly composed of 22% saturated hydrocarbons, 35% resins and asphaltene and 50% aromatic hydrocarbons (CSIC, 2003a), some of which are known to be carcinogenic and/or mutagenic to aquatic organisms (Albers, 2003). Furthermore, the fuel contained some trace metals such as Ni, V, Cu and Zn (CSIC, 2003b) (Table 5.1). The POS in Galicia was one of the major oil spills to have occurred in the region, however, it was not an isolated disaster, since Galicia has received 8 of the 20 major oil spills to have taken place in Europe during the last 50 years (CEDRE, 2009; Hooke, 1997; ITOPF, 2009). Hence, Galicia is one of the regions with the highest number of oil spills in the world (Table 5.2). An oil spill may cause a serious impact on the marine coastal environment since it does not only affect organisms directly, but also destroys or damages habitats that support aquatic communities (Kennish, 1992). In general, effects caused by an oil spill can be divided into three categories: direct lethal effects, direct sublethal effects and indirect effects. Direct lethal effects refer to physical and chemical effects produced by direct oil contact, even without ingestion of pollutants by organisms. These effects are detected as an increase in mortality rates due to smothering, hypothermia (very common in oiled seabirds), coating (which interferes with an individual’s movement, hindering food capture, and escape from predators), or acute toxicity of fuel (see review by Kennish, 1992; NOAA, 1992). Mass mortalities are usually reported in coastal rather than offshore habitats, where hydrocarbons are usually present at lower concentrations and observations are more difficult. For instance, the benthic macrofauna was almost wiped out at heavily oiled sites 2 days after the Florida oil spill (Kennish, 1992) and after a spill of Bunker C oil in San Francisco Bay, where more than four million intertidal animals, principally acorn barnacles, died (Chan, 1973).

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Physicochemical properties of Prestige fuel oil References

Physical Density properties Viscosity

Chemical Elemental properties composition %C %H %S %N General chemical composition % Saturated hydrocarbons % Aromatic hydrocarbons % Resines and asphalthenes Metal concentrations (ppm) Na Al, Ca, Fe, K, Mg, Ti Br, Ni, V B, Ba, Mn, Mo, Sr, Zn As, Co, Cr, Cu, Li, Se

0.99 g/cm (15 C)

3

615 cSt (50 C) 30,000 cSt (15 C)

Saybolt-Letonia quality certificate (CEDRE, 2009) Saybolt-Letonia quality certificate (CEDRE, 2009) CSIC (2003a)

86.8 11.0 2.28 0.69 CSIC (2003a) 22 50 28 CSIC (2003b)

1000–10,000 100–1000 10–100 1–10 0.1–1

Sublethal effects, which are more difficult to detect than acute effects, are brought about by the permanence of different fuel components in the environment. Such effects may not cause the death of organisms, but may reduce the fitness of the affected species owing to the impact on the physiology, behaviour or reproductive capability of the organisms (NOAA, 1992). These alterations may also alter the distribution, abundance, composition and diversity of impacted communities. By comparison, indirect effects

369

Prestige Oil Spill Effects on Biota

Table 5.2 List of major oil tanker spills (1965–2002) including those occurring on the Galician coast (grey shaded) Amount spilled (mT)

Tanker

Location

Year

Type of oil

Yanxilas

Rı´a de Vigo, Galicia, Spain

1965

Undetermined oil

16,000

Torrey Canyon

Scilly Islands, UK

1967

Kuwait crude oil (no. 3)

40,000

Spyros Lemnos

Fisterra, Galicia, Spain

1968

Venezuelan heavy crude oil

15,000

Polycommander

Rı´a de Vigo, Galicia, Spain

Sea Star Jakob Maersk Argo Merchant

Gulf of Oman Oporto, Portugal Massachusetts, USA

1970

1972 1975 1976

Arabian light crude oil

15,000

Crude oil Iranian crude oil (no. 2) Fuel oil (no. 6), Cutter stock (no. 4)

115,000 88,000 26,000

Monte Urquiola A Corun˜a, Galicia, Spain

1976

Arabian light crude oil (no. 3), Bunker fuel (no. 4)

108,000

Hawaiian Patriot

Off Hawai

1977

Indonesian light crude oil

95,000

Andros Patria

Off Cape Ortegal, Galicia, Spain

1978

Iranian heavy crude oil

60,000

Amoco Cadiz

Brittany, France

1978

Arabian light crude oil (no. 2), Iranian light crude oil (no. 2), Bunker C (no. 4)

223,000

(continued)

370

Table 5.2

Milagros Penela-Arenaz et al.

(continued) Amount spilled (mT)

Tanker

Location

Year

Type of oil

Independenta

Bosphorous, Turkey Off Tobago

1979 1979

Es Sider crude oil (no. 2) Crude oil

287,000

Campeche Bay, Mexico Off Pylos Harbour, Greece

1979

Crude oil (no. 3)

350,000

1980

Iraqi crude oil (Kirkuk blend)

100,000

Scaptrade

Ribadeo, Galicia, Spain

1980

Light crude oil

32,000

Castillo de Bellver

Off Cape Town, South Africa

1983

252,000

Odyssey

Off Nova Scotia, Canada Off Canary Islands, Spain

1988

Exxon Valdez

Prince William Sound, Alaska

1989

Haven

Genoa, Italy

1991

ABT Summer

Off Angola

1991

Katina P.

Off Maputo, Mozambique

1992

Light crude oil (Murban and Upper Zakum) North Sea Brent crude oil Iranian heavy crude oil (no. 4) Alaska North Slope crude oil (no. 3) Iranian heavy crude oil (no. 3) Iranian heavy crude oil Crude oil

Aegean Sea

A Corun˜a, Galicia, Spain

1992

Brent blend light crude

74,000

Braer

Shetland Isles, UK

1993

Norwegian Gullfarks light crude oil, Heavy bunker oil

85,000

Atlantic Empress Ixtoc I oil well Irenes Serenade

Khark 5

1989

95,000

132,000 80,000

38,000

144,000

260,000 72,000

x

371

Prestige Oil Spill Effects on Biota

Table 5.2

(continued) Amount spilled (mT)

Tanker

Location

Year

Type of oil

Sea Empress

Milford Haven, UK

1996

70,000

Erika

Brittany, France

1999

Forties blend North Sea crude oil Heavy fuel oil (no. 6)

Prestige

Off Fisterra, Galicia, Spain

2002

Heavy fuel oil (no. 6)

63,000

30,000

Data sources: CEDRE (2009), Hooke (1997), and ITOPF (2009).

include changes in habitat, predator–prey dynamics, interactions among competitors, productivity levels and food webs, due to the loss of key species (Freire and Labarta, 2003). It has been stated that such effects may slow down the recovery processes to a decade or more (Peterson, 2001). However, we need to be aware of the difficulties involved in the assessment of recovery after a pollution event such an oil spill, which are probably higher than the assessment of the initial damage. Marine ecosystems are complex environments subjected to many causes of ecological change aside from oil pollution (e.g. human disturbance, physical habitat alteration, commercial fishing, climate, other pollutants), and therefore, the recovery processes may be occurring in a different environmental scenario than when the oil spill first occurred (NRC, 2003). Different factors determine the degree of the effects caused by an oil spill. Oceanographic and meteorological conditions will control the drift velocity of the spill, the location on the shoreline where oil may run up, and the rate of the weathering processes. Timing is also critical, since the impact will be greater if the spill coincides with periods of high primary production, spawning, embryonic and larval development, or the presence of migratory species. The intensity of the impact will also differ depending on the habitat, and will be less intense in offshore than in coastal habitats, as communities are more diverse and higher concentrations of hydrocarbons are found in the latter. Furthermore, the degree of shelter will determine residence times, which will be shorter in high-energy environments than in sheltered habitats (NOAA, 1992). Impacts will be more damaging for species with small populations (Pin˜eira et al., 2008) and/or restricted reproductive and breeding habitats such as rı´as, bays, estuaries or coastal marshes, which are

372

Milagros Penela-Arenaz et al.

more susceptible to localised pollution events such as oil spills (Freire and Labarta, 2003). This is because these low-energy environments tend to trap oil and to accumulate hydrocarbon pollutants in the sediments increasing the likelihood of long-term impact (Kennish, 1992). The effects of hydrocarbon pollution also depend on the species impacted. Gastropods and polychaetes are usually the least sensitive species, while corals, bivalves, decapod crustacea and echinoderms are the most sensitive (NRC, 1985). Such differences in responses to oil pollution are considered to be caused by their different behaviour, physiology and morphology (Swedmark et al., 1973). Nevertheless, the same species may display different responses depending on duration of exposure (recovery is more difficult after a long exposure), sex, age (eggs and larvae are often more sensitive), and their history of contamination (animals previously exposed to certain compounds can exhibit a lower or a greater tolerance when tested later) (NOAA, 1992). However, few valid generalisations about ecological effects can be applied to the majority of spills, since the variations among organisms, environmental conditions and types of oil transform each oil spill into a different event (Day et al., 1997). The assessment of oil-spill impacts is normally made on the basis of historical data from the same site, comparison with nearby unimpacted sites, comparison with model predictions, or through expert opinion. However, there are two major difficulties in assessing accidental impacts, one associated with statistical aspects and the other with biological aspects. Randomisation and replication of treatments that characterise an experiment obviously do not take place during an unplanned environmental impact such as an oil spill. Treatments are not randomly located and reference areas are not true controls, since they must be defined after the spill (Wiens and Parker, 1995). As a result, it is usually very difficult to distinguish effects of the contaminant from effects of environmental differences across localities. Natural factors vary and may co-vary with the contamination in different ways depending on the area. Furthermore, if a community has not been monitored prior to a spill, studies carried out after the spill are often unable to conclude that the oil spill was the cause of any presumed change (Forde, 2002). Nevertheless, in evaluating the effects of unplanned environmental impacts, post facto designs, which document both initial effects and subsequent recovery, can provide information about the magnitude of the damage (Page et al., 1995; Wiens and Parker, 1995). With regard to the clean-up procedures used after the POS, beachcleaning operations were mainly focused on the large-scale manual removal of the fuel covering the sand. Additionally, mechanical and manual skimmers were used to remove the oil that had been buried in deep layers. On the other hand, hydro-cleaning machines were chosen as the preferential method to remove oil from exposed rocky shores. However, areas virtually inaccessible to mechanical cleaning methods (over 60,000 m2 of

Prestige Oil Spill Effects on Biota

373

rocky surface area) were treated by bioremediation (Ministerio de Medio Ambiente, 2005). Oil recovery at sea was carried out by different oil response vessels from several European countries (Spain, UK, Belgium, Germany, Italy, The Netherlands, Norway and Denmark). The recovery systems used were weir, belt and oleophilic skimmers as well as nets and surface trawl systems. In addition, it is worth mentioning the direct participation of Spanish fishermen using simple manual collection systems (CEDRE, 2004). In this chapter, we review the results published to date on the effects of the POS on marine organisms, at levels of biological organisation ranging from the molecular to the ecosystem, and use this overview to inform about any longer term effects and the time scales of recovery in this system.

2. Effects of the Prestige Oil Spill on the Marine Biota 2.1. Adtidal Most of the communities of the terrestrial adlittoral system were directly affected, not only by the POS hydrocarbons deposited upshore by strong waves, but also indirectly by cleaning activities (Urgorri et al., 2004). Loss of species diversity (relative to the situation before the black tides) was detected in communities of Crithmo-Armerietum, Cisto-Ulicetum, Euphorbio-Agropyretum, Othanto-Ammophiletum and Iberidetum. Coating particularly affected Armeria pubigera, Crithmum maritimum, Spergularia rupicola and Puccinellia maritima. Crest dunes and fixed dunes communities, composed of Elymus farctus, Ammophila arenaria, Artemisia crithmifolia, Honkenya peploides, Eryngium maritimum, Calystegia soldanella, Festuca rubra and Juncus maritimus, were not directly affected by the spill, although important damage was caused by cleaning activities and the opening up of new trails to reach impacted areas. A reduction in the surface cover of a large number of Bryophytes species (such as Bryum dunense, Trichostomum crispulum, Tortella flavovirens, Tortula ruraliformis, Pleurochaete squarrosa, Homalothecium lutescens, Dicranella heteromalla, Didymodon acutus, Didymodon trifarius and Weissia controversa) was observed in affected localities. With regard to rocky substrates, the abundance of Grimmia trichophylla, Campylopus pilifer, Racomitrium heterostichum and Polytrichum juniperinum decreased in several localities affected by the POS.

2.2. Plankton Planktonic organisms, particularly those living in the top few centimetres of the water column (neuston), are supposed to be especially susceptible to the acute effects of the oil spills due to their proximity to the highest

374

Milagros Penela-Arenaz et al.

concentrations of the water-soluble oil compounds. However, no longterm effects on the planktonic community are expected due to their high regenerative potential (short generation times) and the recruitment from outside the impacted areas. Clark (2001) states that low concentrations of hydrocarbons (<50 ng/g) may enhance photosynthesis, presumably because they have a nutritive effect, whereas inhibition of photosynthesis occurs above this level. Also, an increase in phytoplankton biomass and productivity was reported after the oil spill from the tanker Tsesis in 1977, due to the decline in grazing zooplankton populations ( Johansson et al., 1980). Thus, it has been suggested that typically, phytoplankton recovers quickly from an oil spill, returning to previous population levels, as observed after the wreck of the Amoco Cadiz in 1978 (Cabioch, 1981). In general, it is assumed that zooplankton is more sensitive to oil pollution than phytoplankton, although contradictory results have been reported. For instance, Samain et al. (1980) observed a high zooplankton mortality in affected areas from the north coast of Brittany during the first weeks following the Amoco Cadiz oil spill and identified biochemical succession of population groups over a 1-year period. Guzma´n del Pro´o et al. (1986) also found a high decrease in zooplankton biomass in the southern part of the Gulf of Mexico following the Ixtoc-1 spill. On the other hand, Batten et al. (1998) concluded that plankton communities from the southern Irish Sea were not significantly impacted after the Sea Empress wreck, when compared with long data series from previous years, although a minor shift in species composition was detected after the spill. Plankton community structure was not seriously affected by the POS. Only occasional variations were observed, but were associated with the natural variability of the ecosystem (Varela et al., 2006), probably because of the low solubility of the Prestige oil, with a tendency to sink (Serrano et al., 2006); the movement of the water, which spreads the fuel and cleans the water column; bacterial biodegradation, the activity of which increased significantly 1 year after the spill, particularly during winter and summer (Bode et al., 2006); the biological mechanisms that transfer the fuel from the surface waters to the sea floor; the capability of plankton to metabolise hydrocarbons and, especially, the large and mesoscale hydrographic processes, which introduce high natural variability in the plankton, masking effects of the oil (Varela et al., 2006). Medina-Bellver et al. (2005) demonstrated that natural populations of bacteria capable of degrading components of the Prestige crude oil were present on the Galician shore, which can be explained by the continued exposure of the indigenous populations to oil components. The bacterial community was principally composed of a-Proteobacteria, although representatives of g-Proteobacteria, Bacteroidetes and Actinobacteria groups were also detected ( Jime´nez et al., 2007).

375

Prestige Oil Spill Effects on Biota

Early developmental stages of invertebrates have been shown to be more responsive to toxicants than adults (see review by His et al., 1999). Since Woelke (1972) proposed use of the oyster Crassostrea gigas embryogenesis bioassay to indicate water quality for the protection of marine resources, bivalve and sea-urchin embryos and larvae have been increasingly used for testing the biological quality of seawater and to evaluate marine pollution (e.g. His and Beiras, 1995; His et al., 1997; Kobayashi, 1995; McFadzen, 1992). An evaluation of the exposure of embryos and larvae of bivalves and echinoids to environmental samples (collected in affected areas) indicated that fuel-polluted seawater was more toxic than sediment elutriates collected immediately after the POS. Prestige oiled water clearly inhibited embryogenesis in Venerupis rhomboideus and Paracentrotus lividus, while sediment elutriates only caused moderate toxicity in V. rhomboideus or no toxicity in Venerupis pullastra and C. gigas (Beiras and Saco-A´lvarez, 2006; Marin˜o-Balsa et al., 2003) (Fig. 5.2). Likewise, bioassays carried out with sediment elutriates 9 months after the event did not reveal any differences in the success of embryogenesis in V. pullastra (Franco et al., 2006), which is supported by the concentration of total PAHs, well below the sediment quality criteria of 4022 mg/kg dry weight suggested by Long et al. (1995). In contrast, bioassays carried out with sediment elutriates sampled 18

100

Mussel larvae (WSF)

Cyprinodon larvae (WSF)

% biological response

80

60

Sea-urchin larvae (WSF)

Acartia (WSF)

40 Clam larvae (oil-polluted water)

20

0 0,1

Sea-urchin larvae (oil-polluted water)

1 10 100 Concentration of WSF/oil-polluted water

1000

Figure 5.2 Concentration–response curves of oil-polluted seawater collected on the Galician coast during the first days after the Prestige spill, and the water-soluble fraction (WSF) of the Prestige oil diluted with clean seawater, for mussel larvae (open diamonds), clam larvae (filled-in circles), Acartia tonsa (open squares), sea-urchin larvae (open triangles for oil-polluted water, filled-in squares for WSF), and Cyprinodon ´ lvarez, 2006; Marin˜o-Balsa variegatus larvae (filled-in triangles) (after Beiras and Saco-A ´ lvarez et al., 2008). et al., 2003; Saco-A

376

Milagros Penela-Arenaz et al.

months after the POS showed failure of P. lividus embryogenesis in the stations with the highest concentrations of PAHs (Ferna´ndez et al., 2006a). The water-soluble fraction (WSF) of the Prestige fuel oil did not affect growth of the freshwater alga Chlorella vulgaris and did not have deleterious effects on the cladoceran Daphnia magna (Navas et al., 2006). However, despite differences in methods of obtaining WSF, high toxicity was reported for the copepod Acartia tonsa and for the embryo-larval development of both sea-urchin (P. lividus) and mussel (Mytilus galloprovincialis) (Ferna´ndez et al., 2006b; Saco-A´lvarez et al., 2008). The toxicity of the Prestige fuel WSF obtained in laboratory conditions (Saco-A´lvarez et al., 2008) was also comparable to the toxicity of natural samples of seawater affected by the ´ lvarez, 2006) (Fig. 5.2). POS (Beiras and Saco-A

2.3. Benthos Intertidal benthic organisms are highly prone to coating, smothering and to the acute toxicity of oil components after an oil spill. Macroalgae and invertebrates such as coelenterates, crustaceans, echinoderms and molluscs usually suffer high mortalities (Peterson et al., 2003). The pattern of succession after an oil spill includes the loss of dominant herbivores and colonisation of the substrate by green algae. Such changes in the benthic community were reported to last for 4 or 5 years after the Torrey Canyon or the Exxon Valdez oil spills (Peterson, 2001; Southward and Southward, 1978). Subtidal areas can also be reached by oil which adsorb to particulate matter, or by heavier fractions of weathered oil that may eventually sink. This oil accumulates on the bottom and may affect the benthic community by direct contact or by the generation of anaerobic conditions (Roberts, 1989). Also, the direct toxicity which mainly occurs during the early acute phases of the spill may cause strong differences in diversity and abundance on subtidal communities (Sanders et al., 1980). In addition, when oil is mixed or buried in the sediments, it can remain a continuing source of toxicity for years, and cause delayed ecosystem effects which persist long after the direct toxic effects of the oil have disappeared (Peterson et al., 2003; Roberts, 1989). 2.3.1. Rocky intertidal As was seen after the Torrey Canyon spill on British shores (Southward and Southward, 1978) and the Exxon Valdez oil spill in Alaska (Highsmith et al., 1996), the upper intertidal zone was the most seriously affected by the POS (Urgorri et al., 2004). Six months after the POS, there was more uncolonised substrate—both bare rock and dried oil—in the upper intertidal zone of the most heavily oiled localities than in the lightly or non-oiled areas. In the latter areas, the upper intertidal zone was mainly covered with the cirripede Chthamalus montagui, a characteristic species on Galician-exposed rocky shores, whereas the cover by C. montagui was less than 10% at the

377

Prestige Oil Spill Effects on Biota

A

% cover/abundance

100 y = −43.58x + 150.23 r 2 = 0.347

80 60 40 20 0 1,5

2 2,5 3 log[sum40PAHs] (mg/kg dw)

3,5

% mortality of C. montagui

B 100 80

b MO

60

b,c HO

40 20

c,d MO a MO

a LO

d LO

0 CAI

CAM

CAL

AGU

CIE

OIA

Figure 5.3 (A) Decrease in the cover of Chthamalus montagui (squares) and Mytilus galloprovincialis (triangles), and in the abundance of Patella spp. (circles) with increasing tissue concentrations of PAHs (mg/kg dry weight). (B) Mortality of C. montagui at different localities of the Galician coast after the Prestige oil spill. LO, lightly oiled sites; MO, medium oiled sites; HO, heavily oiled sites. a, b, c, d indicate homogeneous groups obtained with the Games-Howell post hoc test. After Urgorri et al. (2004).

most heavily oiled sites (Fig. 5.3A). Mortality of C. montagui was also greater in highly oiled localities than in medium oiled ones (Fig. 5.3B) (Urgorri et al., 2004). Similar massive mortalities of barnacles caused by an oil spill have been recorded elsewhere (Chan, 1973; North et al., 1964; Southward and Southward, 1978; Straughan and Abbot, 1971). Populations of sea urchins (P. lividus), goose barnacles (Pollicipes pollicipes) and mussels (Mytilus galloprovincialis), which are all commercially exploited in rocky intertidal areas in Galicia, were affected to different degrees and at different shore levels. Sea urchins disappeared completely from areas that were densely populated before the POS (Urgorri et al., 2004) and mussels almost totally disappeared from the upper intertidal areas in the heaviest oiled sites, although they remained in other areas moderately affected by the spill (Fig. 5.3A). It can be speculated that covering of gill filaments by oil

378

Milagros Penela-Arenaz et al.

would have impaired feeding, with the consequent mortality of mussels by starvation. In addition, byssal thread activity may have been impaired, resulting in detachment from the substrate (Swedmark et al., 1973), as occurred with Mytilus trossulus after the Exxon Valdez spill (Highsmith et al., 1996). Recruitment of P. pollicipes was lower than in the same period in the previous year in most of the areas surveyed. However, recruitment fluctuations may be attributable to the characteristically high natural variability of barnacle recruitment, a phenomena widely reported in many different studies (e.g. Caffey, 1985; Hawkins and Hartnoll, 1982; Jenkins et al., 2000; Kendall et al., 1985). Labarta et al. (2005) observed sublethal effects in wild mussel spat collected 3 months after the POS. Lower survival rates and alteration of lipid metabolism—with a higher percentage of triglycerides and a decreasing proportion of phospholipids—were found in mussel spat from sites with higher PAH concentrations. Such differences in lipid composition were also observed in mussel spat from Pindo (a strongly affected area) transplanted to a raft culture in the Ares-Betanzos Rı´a (Peteiro et al., 2007), but only at the onset of the experimental culture. In addition, the growth in weight and the percentage of mussels classified as ‘large’ at harvest was significantly lower in mussels from Pindo spat than in individuals from less impacted areas (Peteiro et al., 2006). A large decrease in the abundance of limpets (Patella spp.) was observed at upper shore levels in heavily oiled localities (Fig. 5.3A) (Urgorri et al., 2004). Mortality of Patella spp. may have been caused by oil toxicity, smothering, lack of available food, or clean-up activities, as occurred with another limpet, Tectura persona, after the Exxon Valdez oil spill (Highsmith et al., 1996; Houghton et al., 1991). After the Torrey Canyon spill, Patella spp. were nearly eradicated and, because of the absence of these dominant herbivores, algae colonised the bare rock and inhibited settlement of Patella and barnacles for 5 years (Southward and Southward, 1978); but, as mentioned above the decrease in the recruitment of the barnacle P. pollicipes after the POS might have been attributable to variability in the natural conditions. It must be noted that the excessive use of dispersants after the Torrey Canyon oil spill caused major damage to marine biota (Smith, 1968) and therefore comparisons with the POS are not straightforward. One and a half years after the POS, no significant reductions in genetic variability were found in populations of Littorina saxatilis, which had suffered drastic reductions in population size following the spill (Pin˜eira et al., 2008). There are different possible reasons why genetic variability did not decrease in this species, which was chosen as a model species because of its low dispersal ability, direct development, high population density and widespread distribution on Galician shores. Firstly, the effects on genetic diversity would be small if the reduction in population size that occurred after the spill occurred over a short time period. Secondly, recolonisation of

Prestige Oil Spill Effects on Biota

379

the affected localities may have taken place from the presence of juveniles hidden in crevices and behind rocks, or to a lesser extent, as a consequence of migration from unaffected locations nearby. Nevertheless, polluted populations have shown some genetic effects, principally on amplified fragment length polymorphism variation and quantitative shell traits, probably as a result of natural selection (Pin˜eira et al., 2008). The effect of the POS on algae resulted in decreases in biomass and species diversity in Chondrus crispus, Gelidium sesquipedale and Gigartina pistillata communities 6 months after the event (Urgorri et al., 2004). The Mastocarpus stellatus community showed the greatest changes in relation to the pre-spill situation. Biomass and size were lower after the spill but specific richness and diversity were much higher. This was explained as a decrease in biomass of the dominant species, which most likely made more space available for another species to colonise. Communities of M. stellatus are characteristic of sheltered coves, which owing to the retention of the fuel in these locations, may have been more strongly affected than areas with a stronger swell and a faster rate of ‘self-cleaning’. Lobo´n et al. (2008) compared abundance data for macroalgal assemblages before (September 2002) and then 10 months after the spill (September 2003) at upper and lower intertidal levels in affected areas along the coasts of Galicia, Asturias and the Basque Country. The latter study concluded that the abundance of the main taxa did not change greatly after the spill and that dilution of fuel due to intense winter mixing and advection following the accident were the most likely causes for the lack of severe effects on macroalgal assemblages. Moreover, the mucilaginous slime layer that covers the outer surface of many benthic macroalgae has been reported to serve as a barrier to the penetration of oil providing a protective covering (GESAMP, 1977). Biomarkers are cellular, biochemical and molecular features that provide powerful means of detecting environmental disturbances since they indicate the existence of pollutants (exposure biomarkers) or the response of exposed organisms (effect biomarkers) (McCarthy and Shugart, 1990), allowing changes at high levels such as population, community, or ecosystem to be anticipated (Cajaraville et al., 1993). Different biomarkers in mussels (M. galloprovincialis) were used to assess the biological effects of the POS. Mussels are commonly used as sentinel organisms in pollution monitoring programmes because of their ability to accumulate contaminants, their resistance to high levels of pollutants, and their widespread distribution (Goldberg, 1975). Thus, the high levels of PAHs in coastal seawater caused by the POS (max. 2.1 103 mg equiv. of chrysene per litre) were reflected in a peak of PAH accumulation in mussel (M. galloprovincialis) tissues (max. 5.9 103 mg/kg dw); this was followed by a depuration period until the following winter, when a slight increase in PAH concentrations (above background levels) was detected as a consequence of the remobilisation due to winter storms (Nieto et al., 2006).

380

Milagros Penela-Arenaz et al.

Biomarkers of exposure (induction of acyl-CoA oxidase) and effect (lysosomal responses and alterations in morphology and composition of cell types in the digestive gland) in mussels sampled along the northern coast of Spain in 2003 and 2004 revealed exposure to toxic chemicals and effects on the health of mussels due to the POS (Orbea et al., 2006), with the degree of disturbance being higher in the most severely impacted areas. Some degree of recovery was observed in 2004 and was associated with a reduction in total PAH concentrations in mussels (Cajaraville et al., 2006). However, a battery of exposure and effect biomarkers did not reveal any clear effect in mussels fed with Tetraselmis spp. pre-exposed to the wateraccommodated fraction of the Prestige oil. Only NADH reductases and lipid peroxidation levels were affected by the exposure, which may have been due to the low PAH levels measured in exposed individuals as a result of the low solubility of the Prestige oil (Sole´ et al., 2007). The composition of free amino acids (FAA), used as an index of stress, was analysed in juvenile specimens of M. galloprovincialis collected from different Galician rocky shore areas in February 2003 (Babarro et al., 2006). Total FAA and derived indices (taurinease/glycine ratio, sum of serine and threonine, alanine) were not affected by pollution. In fact, the changes in the FAA profiles of soft tissues were associated with endogenous factors in juvenile stages, such as protein content and condition index, and are used as indices of the energetic status of growing individuals. DNA damage in mussel gills, assessed by the comet assay, was detected between August 2003 and June 2004 in two areas of the Galician coast intensely affected by the POS, relative to reference areas (Laffon et al., 2006). DNA damage was significantly higher in fuel-exposed mussels than in control mussels, before and after a 7-day period in the laboratory during which they were held in clean, fresh seawater. During this recovery stage, a slight reduction in comet tail length was observed, suggesting a certain degree of DNA repair in exposed animals, which is consistent with the reported reversibility and non-persistence of such damage (e.g. Nacci et al., 1992). Effects on the immune response of M. galloprovincialis were confirmed by Novas et al. (2007), since the mechanisms responsible for nitric oxide (NO) synthesis in haemocytes appeared absent between January 2003 and December 2004. An increase in the proportion of phagocytic SH cells, probably as a result of the depressed immune potential, was also detected during these years. Nevertheless, these cells were more sensitive to apoptosis and necrosis-inducing agents. On the contrary, Orda´s et al. (2007) did not observe any significant effects on the immune system of mussels exposed to Prestige fuel oil for 4 months; no differences in several cellular immune parameters (haemocyte viability, phagocytic activity, NO production and chemiluminescence emission) were found between oil-treated and control individuals.

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2.3.2. Sandy intertidal The areas most affected by the oil spill were the swash zone and dry sand zone. The latter not only received high amounts of oil but was also affected by clean-up activities. These activities involved the removal of sand, affecting mainly those species which occur on the sand surface or those with low mobility, and the elimination of the algal wrack, used by the supratidal macrofauna as food and refuge (de la Huz et al., 2005; Junoy et al., 2005). A similar impact also occurred after the Exxon Valdez oil spill, where cleaned beaches took longer to recover than beaches that were not cleaned (Peterson, 2001). A decrease in the number of species was detected in 16 of the 18 beaches studied along the Galician coast 6 months after the POS, with a negative relation between the degree of pollution and number of species. The heavily oiled beaches lost about 66.7% of the total species richness compared with data from September 1995 and 1996 (de la Huz et al., 2005; Junoy et al., 2005). The latter authors stated that the large difference observed before and after the spill could not be attributed to the seasonal variation of the species. There was a large reduction in the abundance of the isopod Eurydice, nemerteans and Diptera after the spill. The bivalve Donax trunculus disappeared from five of six beaches where it was known to be consistently present before the spill (de la Huz et al., 2005). The isopod Sphaeroma rugicauda decreased in abundance or disappeared from most of the beaches, whereas there was a large increase in cumaceans and mysids in the swash zone. An increase in abundance of oligochaetes and the practical disappearance of the insects was noted in the retention and dry sand levels, where higher concentrations of hydrocarbons were observed. A clear reduction in the abundance of talitrid amphipods and the semi-terrestrial isopod Tylos was also observed after the spill. Furthermore, the abundance of the opportunistic polychaete Scolelepis squamata decreased after the spill when compared to data from June to September 1997, probably due to cleaning operations, since this species usually adapts easily to oil spills (de la Huz et al., 2005). Surprisingly, the abundance of the amphipod Pontocrates arenarius increased after the POS, whereas amphipods disappeared immediately after the Amoco Cadiz and the Aegean Sea spills (Go´mez-Gesteira and Dauvin, 2000). A significant effect was also noted in the meiofaunal composition (Urgorri et al., 2004). The faunistic heterogeneity and density of the interstitial fauna were low in nearly all samples. Ostracods were eliminated from Corrubedo beach and together with Turbellaria from Barran˜a´n beach. Foraminifera almost totally disappeared from the beaches affected by the POS. However, the presence of early benthic stages of bivalves and polychaetes in the most polluted sediments 6 months after the spill suggested that the recovery, at least with temporary meiobenthic fauna, had already started, as reported by Rodriguez et al. (2007). By comparison, after the

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Monte Urquiola oil spill only some Turbellaria survived, whereas nematodes and harpacticoid copepods were completely eliminated. Nevertheless, the recovery of communities had already started 1 year after the spill, even on the most severely affected beaches (Giere, 1979). Several studies have also evaluated the quality of the sediments affected by the POS. The burrowing behaviour of juvenile clams (V. pullastra and Tapes decussatus) in sediments taken from moderately affected beaches a few days after the spill was not significantly different from the behaviour in control clams (Marin˜o-Balsa et al., 2003), which supports the general assumption that laboratory toxicity tests are insufficient for ecotoxicological risk assessment. In contrast, Morales-Caselles et al. (2007a) found toxic effects of sediments from impacted sites after use of the MicrotoxÒ and the amphipod (Corophium volutator) tests, and identified PAHs as the compounds causing the toxic effects. However, the toxicity of Galician sediments affected by the POS was lower than the toxicity of sediments chronically polluted by oil spills in the Bay of Algeciras. Sediments collected 4 years after the POS did not cause acute mortality in the amphipod Ampelisca brevicornis or the polychaete Arenicola marina in 10-day bioassays and no toxicity was detected with the MicrotoxÒ test (Morales-Caselles et al., 2008), which suggests some recovery of sediment quality from affected areas. However, a significant accumulation of PAHs in organisms exposed to sediments collected from impacted sites indicates that there may still be a risk to the biota in the affected areas (Morales-Caselles et al., 2008). 2.3.3. Sublittoral Surveys carried out 6 months after the POS did not show any obvious effects on benthic coastal organisms (Urgorri et al., 2004). Furthermore, pollutionsensitive species, such as amphipods and the sea-urchin Echinocardium cordatum, were even found in sediments containing oil aggregates. Serrano et al. (2006) indicated that the distribution of benthic communities on the bottom of the Galician continental shelf was not affected by the tar aggregates that settled after the POS, as had occurred after the Braer (Kingston et al., 1995) and the Exxon Valdez oil spills (Feder and Blanchard, 1998), when no significant effects on benthic fauna were detected. In fact, the changes in the communities that were detected were attributed to changing sediment characteristics rather than to concentrations of hydrocarbons. The low bioavailability of Prestige tar aggregates may explain the lack of correlation between distributions of macroscopic tar aggregates and shelf-benthic communities. These results and the lack of toxicity detected in bioassays carried out with sublittoral sediment (Franco et al., 2006) strengthen the conclusion that the POS had no important impact on the Galician sublittoral benthic communities, probably because of the spatial dispersion of the fuel when it reached the sea bottom.

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2.4. Fishing resources Sandeel (Gymnammodytes semisquamatus) catches per unit effort were significantly reduced in 2003. High rates of mortality, similar to those registered after the Torrey Canyon oil spill, were detected, although sandeels may also have migrated to avoid polluted sediments (Velando et al., 2005a). Significant reductions in the abundance of Norway lobster (Nephrops norvegicus), fourspot megrim (Lepidorhombus boscii) and Pandalid shrimp (Plesionika heterocarpus) were also observed over the Galician shelf when bottom trawl surveys carried out after the POS were compared with time series data (1983–2004) (Sa´nchez et al., 2006). An important degree of recovery, evident from abundance indices, of four-spot megrim and shrimp was subsequently recorded in 2004. In addition, the feeding patterns of the above-mentioned three species and of European hake (Merluccius merluccius) did not change in relation to the POS. Even though tar aggregates and hake (M. merluccius) recruits were transported by the same oceanographic events, no significant changes in the abundance or distribution of hake juveniles from Galician and Cantabrian Sea shelves were detected (Sa´nchez et al., 2006). Furthermore, a certain degree of recovery in recruitment was observed during the 2 years following the POS. Large increases in abundance and richness of parasite communities, and significant changes in individual and functional group parasite abundance patterns were found in samples of bogue (Boops boops) collected in Malpica and Vigo 2 and 3 years after the POS (Pe´rez-del Olmo et al., 2007). Nematode parasitisation in liver of European anchovy (Engraulis encrasicolus) and European hake (M. merluccius) was registered at several locations in Galicia and the Bay of Biscay between April and September 2003. However, it was not possible to relate this to the POS because of the lack of prespill data (Marigo´mez et al., 2006). Biomarkers were also used to assess the impact of the POS in fishes. An increase in EROD activities and histopathological lesions of the juveniles of Sparus aurata, as a result of the increasing PAH concentrations in sediments collected 2 years after the POS, was detected, with gill tissues more severely damaged than liver tissue (Morales-Caselles et al., 2007b). In L. boscii, glutathione-S-transferase, glutathione reductase and catalase activities were significantly higher in the most severely affected locations in the northern Iberian shelf 5 months after the accident (Martı´nez-Go´mez et al., 2006). The activities were positively correlated with the density of POS tar aggregates. In addition, high levels of 1-naphthol, a marker of recent exposure to petrogenic compounds, were measured in bile from L. boscii and Trisopterus luscus collected in the Galician area 1 year after the POS (Fernandes et al., 2008). Nevertheless, the lack of historical data and the chronic contamination in the studied area meant that the changes could not be directly and/or exclusively attributed to the POS. Similarly, and despite the prominence of hepatocellular nuclear

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polymorphism in liver of E. encrasicolus and M. merluccius registered at several locations in Galicia and the Bay of Biscay between April and September 2003, no relation with the POS could be established, because of the lack of pre-spill data (Marigo´mez et al., 2006). In the case of Solea senegalensis, short-term (24, 48, and 72 h) exposure to environmentally realistic PAH levels from the WSF of the Prestige fuel oil did not cause oxidative stress or neurotoxicity in juveniles (Sole´ et al., 2008). The low PAH levels reached in this study may be one of several possible reasons for the lack of effects. Similarly, Gonza´lez-Doncel et al. (2008) investigated the effects of different oil fractions (WSF, crude oil, and weathered oil) on the embryo-larval development of the medaka (Oryzias latipes). This study revealed a significant incidence of abnormalities in hatching and growth as well as mortality, which suggested that the environmental hazard of the Prestige fuel oil could not be linked exclusively to PAHs but also to other components. Morales-Nin et al. (2007) and Saborido-Rey et al. (2007) also detected significant differences in otolith and somatic growth, both in length and weight, in juvenile turbot Scophthalmus maximus kept in captivity and fed on a prepared food containing 0.25–5% seawateraccommodated fuel oil collected immediately after the POS. Growth of fish was slower in the tanks with food containing a relatively high proportion of fuel oil, probably as consequence of the diminution in feeding activity and a decrease in the food energy conversion. High mortality rates were also registered for fish larvae (Cyprinodon variegatus) exposed to the WSF of ´ lvarez et al., 2008). Lastly, rainbow trout the Prestige fuel oil (Saco-A RTG-2 cells exposed to the WSF of Prestige oil did not show any cytotoxic effects (Navas et al., 2006), although a dose-dependent increase of EROD activity was induced.

2.5. Seabirds Seabirds are probably the animals that suffer the greatest impact following an oil spill (Peterson et al., 2003) owing to their long contact with the sea surface and the oil accumulated on the coast, where they congregate to breed (Irons et al., 2000). A total of 23,181 oiled birds were collected in Spain, France and Portugal, although some estimates suggest that the total number of birds affected by the POS may have been between 115,000 and 230,000 (Garcı´a et al., 2003). The most severely affected species were the common guillemot Uria aalge (50.9% of the birds collected), the razorbill Alca torda (16.7%), the Atlantic puffin Fratercula arctica (16.6%), and the Northern gannet Morus bassanus (3.4%). Dehydration and exhaustion were probably the main cause of death for POS-affected seabirds. Microscopic examination of tissue from birds with accumulations of oil in the intestine revealed haemosiderin deposits, associated with cachexia and/or haemolytic anemia. In birds treated in the Bird Rescue

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Center of Avile´s, severe aspergillosis and ulcers in the ventriculus were discovered, and were probably due to stress related to rehabilitation (Balseiro et al., 2005). Total PAH concentrations measured in 2004 in blood samples from yellow-legged gulls (Larus michahellis) from oiled colonies were two times higher than those from unoiled colonies (Pe´rez et al., 2008), although there was a reduction in PAH levels over time. Measurements of PAHs in blood samples are sensitive to the ingestion of small quantities of oil. Shags (Phalacrocorax aristotelis) were not killed in large numbers after the POS (Velando et al., 2005a). A skew in adult-female shag mortality was detected (85% of dead adults were females), probably because there were more females at sea when the spillage took place, as males were present at breeding sites (Martı´nez-Abraı´n et al., 2006). The number of immature female and male corpses recovered was similar, probably because immature birds were not defending territories in breeding colonies. As a consequence of this female-biased mortality, important decreases in breeding numbers were expected. In fact, Monte Carlo simulations considering sex-biased mortality predicted a decrease of 11% in the number of breeding pairs (Martı´nez-Abraı´n et al., 2006). In 2003, the breeding success was 50% lower in polluted colonies than in unoiled ones (Velando et al., 2005b), and chick condition was poorer than in pre-spill years (Velando et al., 2005a). The reduction in reproductive success was probably due to oil pollution, sublethal effects, or lack of food after the oil spill. Lack of breeding and changes in survival caused the decline in oiled colonies (ca. 10%) compared with population trends before the spill and at unoiled colonies (Velando et al., 2005b). Azkona et al. (2006) studied a colony of European storm petrels (Hydrobates pelagicus) on Aketx Island, in the Bay of Biscay. Although the population numbers varied greatly among years before the spill, in 2003 the number of breeding pairs and fledglings was lower than in any previous year and the body condition of the former was poorer. In 2004, there was another reduction in the number of pairs that began breeding. The body condition of individuals was slightly better, although values registered before the oil spill were not reached, and all clutches were successful. In 2005, there was a recovery in the number of individuals and breeding success. Nevertheless, the minimum age of recaptured birds was lower, which indicates an effect on population structure. The POS had a negative effect on the population of peregrine falcon (Falco peregrinus) in the Bay of Biscay. The effects were first noted as an increase in the population turnover rate (from 21% to 30%) and in the number of deserted nests containing eggs or young chicks (Zuberogoitia et al., 2006). The effects of pollution were detected inland because falcons predated affected seabirds during the migratory flights of the latter. Measurements using biomarkers showed higher levels of aspartate aminotransferase (AST) and lower values of glucose, total protein, and

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inorganic phosphorus in adult yellow-legged gulls (L. michahellis) breeding in oiled colonies 17 months after the POS, which suggests damage to some vital organs (i.e. liver and kidney) (Alonso-Alvarez et al., 2007a). The effects were more evident in adults than in chicks, although total PAH levels in blood were similar in both age groups, probably because of the longer exposure of adults to pollutants just after the spill. The presence of PAHs in chicks suggests that these components were incorporated through contaminated food. Lower levels of glucose and inorganic phosphorus in plasma and a tendency for lower levels of creatinine were also observed in wild yellow-legged gulls fed with Prestige fuel oil, in comparison with control gulls, fed only with vegetable oil (Alonso-Alvarez et al., 2007b). AST activity was also higher, but only in oil-fed males. However, g-glutamyl transferase activity was higher in control females than in oil-fed females, in contrast to the field data obtained in the previous study (Alonso-Alvarez et al., 2007a), revealing possible differences in the adaptive responses of these enzymes to short-term exposure to fuel. Finally, acetylcholinesterase (AChE) activity decreased by 4% in Atlantic puffins, 16% in exposed common guillemots, and 22% in razorbills relative to non-exposed congeners (Oropesa et al., 2007), although the inhibitory effect on AChE activity of the exposure to the Prestige fuel oil was only demonstrated in razorbills.

2.6. Marine mammals and turtles The effects of oil on marine mammals and turtles include short-term and chronic acute toxic effects ranging from coating of the fur (which causes hypothermia, smothering and drowning), ingestion of toxicants during preening, and ingestion of polluted prey, to disruption of vital social functions in socially organised species (Peterson et al., 2003). A total of 27 cetaceans and 16 turtles strandings were recorded 1 month after the POS (Alonso-Farre´ and Lo´pez-Ferna´ndez, 2002); however, it is difficult to find direct evidence indicating fuel oil as the cause of the strandings.

3. Conclusion Even though there is still some research in progress, the results obtained to date indicate a strong initial impact during the first year after the spill, mainly on intertidal communities and fishing resources (summarised in Table 5.3), with a relatively fast recovery by 2004. The time of year when the POS took place meant that damage was minimal. For example, the abundance of phytoplankton and zooplankton after the spill—between November and February—was at the annual minimum. Furthermore, many invertebrate species were not spawning and larvae

Summary of the biological responses, from molecular to community levels, reported after the Prestige oil spill

Adtidal Vascular plants communities Bryophytes species Rocky intertidal Algal communities Mastocarpus stellatus community Mytilus galloprovincialis Patella spp. Paracentrotus lividus

Decrease in biomass

Higher specific richness

Loss of species diversity

Higher adult mortality

Community

Lower recruitment

Reduction in abundance

Increase in abundance

Alteration of parasite communities

Poorer body condition

Population

Lower growth rates

Failures of embryo-larval development

Individual

Alteration of metabolism

Effects on the immune response

Biological responses

Effects on biomarkers

Molecular

High mortalities

Table 5.3

References

Urgorri et al. (2004) X X X X X

X

X

X

X

X

X

Urgorri et al. (2004) Labarta et al. (2005)

X

Cajaraville et al. (2006)

X

Laffon et al. (2006)

X X

Orbea et al. (2006) Peteiro et al. (2006, 2007) (continued)

(continued)

Chthamalus montagui Pollicipes pollicipes Sandy intertidal Meiofaunal communities Ostracods Turbellaria Foraminifera Macrofaunal communities Diptera Nemerteans Oligochaetes Cumaceans Mysids Venerupis rhomboideus Donax trunculus Eurydice Sphaeroma rugicauda Pontocrates arenarius

X X X X X X

X X X X X X X X

Decrease in biomass

References

Novas et al. (2007) Saco-A´lvarez et al. (2008)

X

X X

Higher specific richness

Loss of species diversity

Higher adult mortality

Community

Lower recruitment

Reduction in abundance

Increase in abundance

Alteration of parasite communities

Poorer body condition

Population

Lower growth rates

Failures of embryo-larval development

Individual

Alteration of metabolism

Effects on the immune response

Biological responses

Effects on biomarkers

Molecular

High mortalities

Table 5.3

Urgorri et al. (2004) de la Huz et al. (2005) Junoy et al. (2005)

Fishing resources Gymnammodytes semisquamatus Oryzias latipes

X

Cyprinodon variegatus Boops boops

X X

Sparus aurata

X

Lepidorhombus boscii

X

X

Scophthalmus maximus Nephrops norvegicus Plesionika heterocarpus Seabirds Uria aalge Alca torda Fratercula arctica Morus bassanus Larus michahellis Phalacrocorax aristotelis Hydrobates pelagicus Falco peregrinus

Velando et al. (2005a)

X

X X X

X

X X X X

X X X

X X X

Gonza´lez-Doncel et al. (2008) Saco-A´lvarez et al. (2008) Pe´rez-del Olmo et al. (2007) Morales-Caselles et al. (2007b) Martı´nez-Go´mez et al. (2006) Saborido-Rey et al. (2007) Morales-Nin et al. (2007) Sa´nchez et al. (2006) Garcı´a et al. (2003) Velando et al. (2005a,b) Azkona et al. (2006) Martı´nez-Abraı´n et al. (2006) Zuberogoitia et al. (2006) Alonso-A´lvarez et al. (2007a,b) Oropesa et al. (2007)

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were not present in the water column at that time of year. Winter storms also favoured cleaning in most areas. If the POS had occurred during the spring blooms or summer upwellings, impacts on reproduction of organisms, plankton and, therefore, on food webs, would have been greater. One difficulty in assessing the impact of the POS was the lack of time series or historical data for most of the areas or ecosystems affected by the spill. Without such information on the natural variability of the marine ecosystem it is very difficult to assess the real impact on the environment and to be able to attribute the observed responses to the spill. Furthermore, there was a high degree of disorganisation in the scientific response during the first weeks of the crisis (Freire et al., 2006). In the aftermath of the oil spill, the three administrations responsible for marine research began to monitor the impact of the oil spill, but worked separately and without any coordination. It was not until 3 months after the catastrophe that the Spanish Ministry of Science and Technology took charge of coordinating the different groups. It was evident that coordination among different administrations and the scientific community needed to be improved to enable a faster, more structured assessment of the real impact of the oil spill, an experience which is relevant to scientific responses to any future environmental crises in this region and elsewhere.

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Beiras, R., and Saco-A´lvarez, L. (2006). Toxicity of seawater and sand affected by the Prestige fuel-oil spill using bivalve and sea urchin embryogenesis bioassays. Water Air Soil Pollut. 177, 457–466. Bode, A., Gonza´lez, N., Lorenzo, J., Valencia, J., Varela, M. M., and Varela, M. (2006). Enhanced bacterioplankton activity after the Prestige oil spill off Galicia, NW Spain. Aquat. Microb. Ecol. 43, 33–41. Cabioch, L. (1981). Subtidal and pelagic ecological impact. In ‘‘Amoco Cadiz Fate and Effects of the Oil Spill,’’ pp. 475–480. Proceedings of the International Symposyum. Centre National pour l’Exploitation des Oceans, Paris. Caffey, H. M. (1985). Spatial and temporal variation in settlement and recruitment of intertidal barnacles. Ecol. Monogr. 55, 313–332. Cajaraville, M. P., Marigo´mez, I., and Angulo, E. (1993). Correlation between cellular and organismic responses to oil-induced environmental stress in mussels. Sci. Total Environ. 134, 1353–1371. Cajaraville, M. P., Garmendia, L., Orbea, A., Werding, R., Go´mez-Mendikute, A., Izagirre, U., Soto, M., and Marigo´mez, I. (2006). Signs of recovery of mussels health two years after the Prestige oil spill. Mar. Environ. Res. 62, S337–S341. CEDRE (Centre de documentation, de recherche et d’expe´rimentations sur les pollutions accidentelles des eaux) (2004). Prestige: Response at sea. Oil recovery (http://www.cedre.fr). CEDRE (2009). Spills caused by sea transport around the Iberian Peninsula since 1950 (http://www.cedre.fr). Chan, G. L. (1973). A study of the effects of the San Francisco oil spill on marine organisms. In ‘‘Proceedings of the Joint Conference on Prevention and Control of Oil Spills,’’ pp. 739–781. American Petroleum Institute, Washington, DC. Clark, R. B. (2001). ‘‘Marine Pollution.’’ Oxford University Press, Oxford. CSIC (Centro Superior de Investigaciones Cientı´ficas) (2003a). Characterization of the spill and preliminary evolution in the environment. In ‘‘CSIC Technical Report No. 01 (in Spanish).’’ (http://csicprestige.iim.csic.es/). CSIC (2003b). Heavy metal presence in the shipwreck area of Prestige tanker and metal contents in the emulsioned fuel. In ‘‘CSIC Technical Report No. 2 (in Spanish)’’ (http:// csicprestige.iim.csic.es/). Day, R. H., Murphy, S. M., Wiens, J. A., Hayward, G. D., Harner, E. J., and Smith, L. N. (1997). Effects of the Exxon Valdez oil spill on habitat use by birds in Prince William Sound, Alaska. Ecol. Appl. 7, 593–613. de la Huz, R., Lastra, M., Junoy, J., Castellanos, C., and Vie´itez, J. M. (2005). Biological impacts of oil pollution and cleaning in the intertidal zone of exposed sandy beaches: Preliminary study of the Prestige oil spill. Estuar. Coastal Shelf Sci. 65, 19–29. Feder, H. M., and Blanchard, A. (1998). The deep benthos of Prince William Sound, Alaska, 16 months after Exxon Valdez oil spill. Mar. Pollut. Bull. 36, 118–130. Fernandes, D., Andreu-Sa´nchez, O., Bebianno, M. J., and Porte, C. (2008). Assessment of pollution along the Northern Iberian shelf by the combined use of chemical and biochemical markers in two representative fish species. Environ. Pollut. 155, 327–335. Ferna´ndez, N., Cesar, A., Gonza´lez, M., and DelValls, T. A. (2006a). Level of contamination in sediments affected by the Prestige oil spill and impact on the embryo development of the sea urchin. Cien. Mar. 32, 421–427. Ferna´ndez, N., Cesar, A., Salamanca, M. J., and Del Valls, T. A. (2006b). Toxicological characterisation of the aqueous soluble phase of the Prestige fuel-oil using the sea-urchin embryo bioassay. Ecotoxicology 15, 593–599. Forde, S. E. (2002). Modelling the effects of an oil spill on open populations of intertidal invertebrates. J. Appl. Ecol. 39, 595–604. Franco, M. A., Vin˜as, L., Soriano, J. A., de Armas, D., Gonza´lez, J. J., Beiras, R., Salas, N., Bayona, J. M., and Albaige´s, J. (2006). Spatial distribution and ecotoxicity of petroleum

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TAXONOMIC INDEX

A Acartia tonsa, 375–376 Acipenser nudiventris, 309 Aetobatus flagellum, 312, 335 Aetomylaeus maculates, 312 Aetomylaeus nichofii, 312 Aetomylaeus vespertilio, 312 Aetoplatea zonura, 312 Alca torda, 384, 389 Alopias superciliousus, 294, 300 Alopias vulpinus, 294, 300 Ammophila arenaria, 373 Ampelisca brevicornis, 382 Anampses viridis, 309 Anoxypristis cuspidate, 312 Arenicola marina, 382 Argopecten irradians, 334 Armeria pubigera, 373 Artemisia crithmifolia, 373 Atlantoraja castelnaui, 312 Atlantoraja cyclophora, 312 Atlantoraja platana, 312 Aulohalaelurus kanakorum, 312 Azurina eupalama, 309 B Bathyraja albomaculata, 312 Bathyraja griseocauda, 312 Benthobatis kreffti, 312 Boops boops, 383, 389 Bramidae, 334 Bryum dunense, 373 C Calanus finmarchicus, 235, 240, 244 Callorhinchus milli, 304 Calystegia soldanella, 373 Campylopus pilifer, 373 Cancer magister, 332 Cancer productus, 332 Carcharhinus amboinensis, 296 Carcharhinus borneensis, 312 Carcharhinus brachyurus, 312 Carcharhinus falciformis, 286, 294, 301 Carcharhinus hemiodon, 312 Carcharhinus leiodon, 312 Carcharhinus leucas, 282

Carcharhinus limbatus, 312 Carcharhinus longimanus, 294, 300, 312 Carcharhinus obscurus, 286, 294, 301, 312 Carcharhinus plumbeus, 294, 301–302, 304 Carcharhinus signatus, 312 Carcharhinus sorrah, 282, 294, 296–297 Carcharias taurus, 283, 294, 304, 312 Carcharinus limbatus, 294, 297, 304 Carcharinus spp., 300 Carcharinus tilstoni, 294, 296–297 Carcharodon carcharias, 294, 300, 302, 312 Caretta caretta, 153–155, 157–158, 166–167, 170–171, 173, 176, 178–179, 184–186 Centrophorus granulosus, 312 Centrophorus harrissoni, 312 Centrophorus squamosus, 312 Cetorhinus maximus, 282, 291, 293–295, 312 Chelonia mydas, 154–155, 157–159, 166–168, 171, 175–176, 179–183, 186–187, 189–190, 335 Cheloniidae, 154 Chlorella vulgaris, 376 Chondrus crispus, 379 Chthamalus montagui, 376–377, 388 Corophium volutator, 382 Crassostrea gigas, 375 Crassostrea virginica, 335 Crithmum maritimum, 373 Cyprinodon variegatus, 375, 384, 389 D Daphnia magna, 376 Dasyatis fluviorum, 312 Dasyatis garouaensis, 312 Dasyatis laosensis, 312 Dasyatis spp., 283 Dasyatis violacea, 334 Dermochelyidae, 154 Dermochelys coriacea, 154–156, 158–159, 168, 171, 175–178, 189 Dicranella heteromalla, 373 Didymodon acutus, 373 Didymodon trifarius, 373 Diplobatis colombiensis, 312 Diplobatis guamachensis, 312–313 Dipturus batis, 294, 298, 312 Dipturus chilensis, 312 Dipturus crosnier, 312–313

397

398

Taxonomic Index

Dipturus laevis, 294, 298, 312–313 Dipturus mennii, 312–313 Discopyge tschudii, 312–313 Donax trunculus, 381, 388 Dugong dugon, 181 E Echinocardium cordatum, 382 Elymus farctus, 373 Engraulis encrasicolus, 383–384 Enhydra lutris, 332 Entelurus aequoreus, 37 Eretmochelys imbricata, 154–155, 158, 166, 169, 174, 183, 189 Eryngium maritimum, 373 Eurydice, 388 Eusphyra blochii, 296 F Falco peregrinus, 385, 389 Festuca rubra, 373 Fratercula arctica, 384, 389 Fundulus heteroclitus, 332 G Gadus morhua L., 213–252, 278 Galeocerdo cuvier, 282, 294, 296, 300 Galeorhinus galeus, 293–294, 296, 312–313 Galeus mincaronei, 312–313 Gelidium sesquipedale, 379 Gigartina pistillata, 379 Glyphis gangeticus, 312–313 Glyphis glyphis, 312–313 Grimmia trichophylla, 373 Gurgesiella dorsalifera, 312–313 Gymnammodytes semisquamatus, 383, 389 Gymnura altavela, 312–313 Gymnura micrura, 334 H Halichoerus grypus, 248 Hemigaleus australiensis, 306 Hemiscyllium hallstromi, 312–313 Hemiscyllium strahani, 312–313 Hemitriakis leucoperiptera, 312–313 Heteroscyllium colcloughi, 312–313 Himantura chaophraya, 312–313 Himantura fluviatilis, 312–313 Himantura oxyrhyncha, 312–313 Himantura signifier, 312–313 Holothuria spp., 303 Homalothecium lutescens, 373 Honkenya peploides, 373 Huso huso, 309 Hydrobates pelagicus, 385, 389

Hypleurochilus geminatus, 332 Hypsoblennius hentzi, 332 I Iberidetum, 373 Isogomphodon oxyrhynchus, 312–313 Isurus oxyrinchus, 294, 300 Isurus paucus, 312–313 J Juncus maritimus, 373 K Katsuwonus pelamis, 334 L Lagodon rhomboides, 332 Lamna ditropis, 282 Lamna nasus, 293–294, 300, 312–313 Larus michahellis, 385–386, 389 Lepidochelys kempii, 154, 156, 158 Lepidochelys olivacea, 154–155, 158–159, 173, 176, 189 Lepidorhombus boscii, 383, 389 Leucoraja melitensis, 312–313 Littorina saxatilis, 378 M Macrocystis spp., 332 Makaira indica, 334 Makaira nigricans, 334 Manta birostris, 283 Mastocarpus stellatus, 379, 387 Melanogrammus aeglefinus, 222 Mercenaria mercenaria, 335 Merlangius merlangus, 222 Merluccius merluccius, 383–384 Mobula mobular, 312–313 Morus bassanus, 384, 389 Mustelus antarcticus, 288, 294–295 Mustelus canis, 333–334 Mustelus fasciatus, 312–313 Mustelus henlei, 282 Mustelus lenticulatus, 304 Mustelus schmitti, 312–313 Mustelus whitneyi, 312–313 Mya arenaria, 335 Myliobatis hamlyni, 312–313 Mytilus galloprovincialis, 376–377, 379–380, 387 Mytilus trossulus, 378 N Narcine bancroftii, 312–313, 334 Narcine brevilabiata, 312–313

399

Taxonomic Index Natator depressus, 153–159, 173, 189 Nebrius ferrugineus, 312–313 Negaprion acutidens, 312–313 Neodenticula, 92 Neodenticula seminae, 119 Nephrops norvegicus, 383, 389 O Odontaspis ferox, 312–313 Odontaspis taurus, 294 Oryzias latipes, 384, 389 Oxynotus centrina, 312–313 P Pantanodon madagascariensis, 309 Paracentrotus lividus, 375–377 Patella spp., 378, 387 Phalacrocorax aristotelis, 385, 389 Phoca groenlandica, 248 Phocoena phocoena, 248 Plagioscion spp., 333 Plesionika heterocarpus, 383, 389 Pleurochaete squarrosa, 373 Pleuronectidae, 335 Pollicipes pollicipes, 377–378, 388 Polytrichum juniperinum, 373 Pontocrates arenarius, 381, 388 Prionace glauca, 286, 288, 294, 299 Pristis clavata, 312–313 Pristis microdon, 312–313 Pristis pectinata, 312–313 Pristis perotteti, 312–313 Pristis pristis, 312–313 Pristis zijsron, 312–313 Prochlorococcus, 29 Prototroctes oxyrhynchus, 309 Pseudoginglymostoma brevicaudatum, 312–313 Puccinellia maritime, 373 Pugettia producta, 332 Pycnopodia helianthoides, 332 R Racomitrium heterostichum, 373 Rhina ancylostoma, 312–313 Rhincodon typus, 283, 312–313 Rhinobatos cemiculus, 312–313 Rhinobatos formosensis, 312–313 Rhinobatos granulates, 312–313 Rhinobatos horkelii, 312–313 Rhinobatos obtusus, 312–313 Rhinobatos rhinobatos, 312–313 Rhinobatos thouin, 312–313 Rhinoptera bonasus, 334 Rhinoptera brasiliensis, 312–313 Rhinoptera javanica, 312–313

Rhizoprionodon taylori, 282 Rhynchobatus australiae, 312–313 Rhynchobatus djiddensis, 312–313 Rhynchobatus laevis, 312–313 Rhynchobatus luebberti, 312–313 Rostroraja alba, 312–313 S Schroederichthys saurisqualus, 312–313 Scolelepis squamata, 381 Scomberomorus semifasciatus, 296 Scomberomorus spp., 296 Scophthalmus maximus, 384, 389 Scylliogaleus quecketti, 312–313 Solea senegalensis, 384 Sparus aurata, 383, 389 Spergularia rupicola, 373 Sphaeroma rugicauda, 381, 388 Sphyrna lewini, 294, 300 Sphyrna mokarran, 294, 300, 312–313 Sphyrna spp., 296 Sphyrna tiburo, 307, 334 Sphyrna tudes, 312–313 Sphyrna zygaena, 294, 300 Squalus acanthias, 289–290, 293, 312–313 Squalus mitsukurii, 312–313 Squatina aculeate, 312–313 Squatina argentina, 312–313 Squatina dumeril, 334 Squatina guggenheim, 312–313 Squatina occulta, 312–313 Squatina oculata, 312–313 Squatina squatina, 294, 299, 312–313 Stegostoma fasciatum, 312–313 Strongylocentrotus franciscanus, 332 Strongylocentrotus purpuratus, 332 Sympterygia acuta, 312–313 Synechococcus, 29 T Taeniura meyeni, 312–313 Tapes decussatus, 382 Tectura persona, 378 Tegula brunnea, 332 Tegula funebralis, 332 Tetraselmis spp., 380 Thunnus tonggol, 296 Tortella flavovirens, 373 Tortula ruraliformis, 373 Triaenodon obesus, 282 Triakis acutipinna, 312–313 Triakis maculate, 312–313 Trichodesmium, 43–44, 76 Trichostomum crispulum, 373 Trisopterus luscus, 383

400

Taxonomic Index

Trochus spp., 303 Tylos, 381

V U

Uria aalge, 384, 389 Urogymnus asperrimus, 312–313 Urogymnus ukpam, 312–313 Urolophus bucculentus, 312–313 Urolophus javanicus, 312–313 Urolophus orarius, 312–313 Urolophus sufflavus, 312–313 Urolophus viridis, 312–313

Venerupis pullastra, 375, 382 Venerupis rhomboideus, 375, 388 W Weissia controversa, 373 Z Zapteryx brevirostris, 312–313 Zostera marina, 182

SUBJECT INDEX

A ACC. See Antarctic circumpolar current Allee effects, cod, 247–248 Antarctic bottom water (AABW) production, 97, 103 Southern Ocean, 95 warming trend until, 22 Antarctic circumpolar current (ACC) flow, 94–95 mode and nurient-rich intermediate waters, 95–96 potential candidate mechanisms, 98 profound warming, 98 silicic acid, 46 Southern Ocean, 123–124 upwelled water, 20–22 Arctic and seas adjacent to Greenland Arctic Ocean and Subarctic Seas geographical features and bathymetry, 80–81 surface atmosphere air temperature, 81 warm rate, 81 comments, 93 ecosystems benthic–pelagic coupling, 92 phytoplankton growing season, 91 sea-ice cover reduction, 91–92 Greenland ice sheet IPCC AR4 report, 88, 89 warmer temperature, 88 ice formation, 83 methane hydrates affect mechanisms, 90 permafrost release, 91 modelling, 92–93 river runoff, 83 sea-ice cover extent, 84, 85 projected changes, 86–87 retreat and feedbacks, 87 seasonal and annual mean, Northern Hemisphere, 84 in September 2007, 84, 85 thickness and volume changes, 84, 86 sub-polar circulation, warm input, 82 MOC and dense water formation, 82–83 trigger factors, sea-ice reductions, 86

Atlantic angel sharks, 334 Atlantic cod Gadus morhua, climate and fishing effects activity, metabolic scope, 229–230 biogeographic changes distributional limits, 224 northward shift, 225–226 thermal effect, 224–225 biology and distribution, 215–216 debate, 244 early life stages, 231–233 genetic population structure diversity regional patterns, 217–218 gene flow, 216 growth, 237–238 maturation and spawning, 230–231 movement and activity adult, 219–221 larval dispersal, 222 thermal habits, 221–222 physiology sublethal thresholds, 227–229 tolerance limits and thermal preferences, 226–227 population-level impact Allee effects and management plans, 247–248 North Sea, stock evaluation, 246–247 stock assessment, 245–246 recruitment, 233–236 status and recovery, North Sea, 249–250 stocks Northeast, 239–244 Northwest, 238–239 trait, 218–219 Atlantic multi-decadal oscillation (AMO), 13 Atmosphere–ocean global circulation models (AOGCMs), 106 B Bayesian information criterion (BIC) marine, threat risk correlates chondrichthyan, 321, 323 teleost, 322, 323 on relative model support, 320 Beach meshing, 305, 342 Benthic system bivalves and polychaetes stages, 381

401

402

Subject Index

Benthic system (cont.) demersal species, 335 ecosystem acidification effect, 73 global carbon cycles, 36–37 habitat disturbance, 331 invertebrates, 158 macroalgae, 379 macrofauna, 367 marine plants and algae, 182 organisms and bottom sediments, 59 coastal, obvious effects, 382 coating, smothering, and oil component toxicity, 376 cope, temperature changes, 101 deoxygenation and mortality, 71 marine, calcification rates, 66 oviparous species, 283 pelagic coupling, 92 shallow-water, 75 species poleward migration, 38 water temperatures, 237 Benthos, Prestige oil spill rocky intertidal algae, 379 biomarkers, 379–380 cover decrease, 377 DNA damage, 380 genetic variability, 378–379 limpets, 378 sea-urchins and mussels, 377–378 upper intertidal zone, 376 sandy intertidal degree of pollution and species number, 381 meiofaunal composition, 381–382 sublittoral, 382 subtidal areas, 376 BIC. See Bayesian information criterion Blue shark fins, 299–300, 303 Brown sharks, 302 C Carbon (CO2), climate change acidification, 7–8 biological pump, 56–57 continental shelf pump, 57 counter pump, 57–58 cycle and CH4, 51–52 climatological mean distribution, 52–53 DIC profile, 52, 54 dissolution alkalinity, 68 CaCO3 production, 68–69 formation aragonite saturation horizon depth, 66–67

calcification, 66 mineral types, 65–66 saturation state, surface waters, 66, 68 pump bottom sediment distribution, 74 CaCO3 budget, 75 pCO2, 73 role, 58 solubility pump, 54–56 storage and transfer, 7 uptake, 69–70 Chimaeras. See Chondrichthyes Chondrichthyes extinction risk analysis, 317–320 ecological, life history and human relationship, 313–317 global distribution, 310–313 identification and ranking, 308 modelling results, 320–326 species traits, 308–309 and teleosts, 309–310 and teleosts relative threat, 326–328 life history age and growth, 282 niche breadth, 281–282 reproduction and survival, 283–284 physical changes, habitat, 279–280 population declines, 279 species loss implication ecosystem role, 333–335 marine realm predator loss, 331–333 synthesis and knowledge gaps climate change, 337–339 extinction synergies, 339–340 fisheries role, 335–337 research, 340–341 threats beach meshing, 305 fishing, 284–305 habitat loss, 306 pollution and non-indigenous species, 306–308 Climate change, chondrichthyes extinction rates, 337–338 Ocean acidification, 339 ozone depletion, 338–339 phenology and physiology, 338 Climate change impacts, cod activity metabolic scope sea surface temperature, 229–230 swimming speed and foraging rate, 229 anthropogenic inputs, 222–223 biogeographic distribution, northward shift, 225–226 stock depletion, 226 thermal occupancy, 224–225

403

Subject Index

early life stages eggs, 231–232 larvae and egg survival, 232–233 ontogenetic shift, 232 and fishing population-level, 245–248 growth low temperatures, 237 warmer climate, 237–238 maturation and spawning energy provision and, 230 male lekking behaviour, 231 peak dates, 230–231 North Atlantic sea surface temperatures, 223 physiology sublethal thresholds, 227–229 tolerance limits and thermal preferences, 226–227 recruitment biological responses vs. NAO index, 236 extrinsic stochastic events, 233 interannual variation, 233–234 plankton community, 235 temperature-driven variability, 234–235 thermal effect, direct, 235–236 Climate models CO2, 112–113 comments, 114–115 heat transport density contrasts, 109 MOC flow, 109–110 Southern Ocean circulation and limiters, 110 heat uptake AOGCMs, 106 limiters, 108 regional distributions, 107–108 ocean–climate feedbacks, 106 retro-modelling, past climate change, 113–114 sea ice components and limiters, 112 extents, 111–112 water cycle, 111 Coastal zone color scanner (CZCS), 33, 59 Commercial fisheries interest (CMI), 314, 318 D Destabilisation glaciers, 25 hydrates, 90 ice sheet in current models, 118 Greenland and East Antarctic, 25–26 Dimethylsulphide (DMS) BrO interaction, 49 CO2 fluxes and, 59 emission, 49–50 gas exchange/carbon uptake, 112–113 production, 36

Dimethylsulphoniopropionate (DMSP), 50 Dissolved inorganic carbon (DIC) system bicarbonate input, 71 CO2, high atmospheric, 69 low concentrations, 75–76 in ocean, 54 re-equilibration, 52 Dissolved organic carbon (DOC), 52, 57 DMS. See Dimethylsulphide E Ecosystem, chondrichthyan abundance and structure changes, 334–335 benthic and demersal species, 335 ECOPATH/ECOSIM models, 333–334 elasmobranch mesopredators predatory release, 334 marine predator loss continental shelf and open-ocean, 332–333 effects, 331–332 trophic cascade, 332 predators role influence, evidence and theory, 328–330 loss, 330–331 terrestrial trophic cascades, 330 El Nin˜o/Southern oscillation (ENSO), 12 Embryos and hatchlings air temperature environmental factors, 167 global warming, 164 marine turtle life stages, 165 turtles nesting, 166 rainfall, storms and cyclone, 167–168 sea level and atmospheric patterns, 169 Environmental temperature class (ETP), 314 Expendable bathythermograph (XBT), 14 Extinction risk, chondrichthyan ecological, life history and human-relationship, 313–317 extinction proneness, 308 modelling IUCN category species distribution, 320, 324 marine teleosts, 322, 326 Red-Listed species, 320–322, 325 relative threat, teleosts FishBase species, 328 Red Listing, 326–327 sharks, 327, 328 species traits, 308–309 taxa threatened, global distribution IUCN Red-Listed, 311, 312 species cluster, 313 and teleosts, 309–310 threat analysis Akaike’s information criterion corrected (AICc), 319–320 BIC, 320 GLMM, 317–319

404

Subject Index F

Fisheries, chondrichthyan extinction fishes survival, 335–336 minimum viable population and stock size, 337 mixed-species and by-catch, 336–337 risk, 336 Fishing, chondrichthyes biological and social effects, 288 collapsing, 284–285 conservation biology paradigms, 288–289 demographic variance, 289 extinction, 288 extirpations, 290–291 global distribution, shark, 287 IUU, 303–304 local/population extinction, 290 mixed fisheries and by-catch barndoor skate, 298–299 blue shark fins, 299–300 decline controversies, 300–303 occurrence, 298 pelagic, 299 problem, 297–298 rate vs. recruitment trade-off, 291 recreational Australia and New Zealand, 304 inshore water, 305 sharks, 286 spiny dogfish, 289–290 target fisheries commercial, 291–292 directed shark, 292–293 Northern Territory, Australia shark, 296–297 tope, school/soupfin shark, 295–296 Fishing impacts, North Atlantic vs. climate change debate, 244 Northeast stocks Celtic Sea, 242–243 Iceland, 243–244 North Sea, 239–242 Northwest stocks, 238–239 population-level and climate change Allee effects and, 247–248 North Sea stock evaluation, 246–247 stock assessment, 245–246 G Game fish (GME), 317 Generalised linear mixed-effect models (GLMM), 317, 320 Genetic population structure, cod diversity change, 217 living condition, 216 regional patterns, diversity co-occurring population, 218 microsatellite DNA markers, 217 substantial differences, 217–218

stock traits, 218–219 Global primary production aerosols DMS emission, 49–50 DMSP, 50 benthos, 36–37 biodiversity functional groups diatoms, 35 ocean biomes, 35–36 organisms role, 34–35 PFT, 35–36 biological pump structure, 28 CH4 causes, climate warming, 48–49 net methane emissions, 48 chlorophyll NPP reduction, 34 SeaWiFS data, 33–34 comments, 51 iron and dust, 47 microbial plankton, 30 N2 Anammox denitrification, 43 atmospheric concentration, CO2 and N2O, 44 availability vs. biosphere ability, 43–44 cycle, 42–43 N and P mobilisation, 41 nitrate availability, 40–41 N2O and halocarbons, 49 O2 OAEs, 38 OMZs, 39 reduction and decadal variability, 39–40 oceanic atmospheric oxygen and carbon fixation, 28 light availability, 28–29 plankton, 29 and terrestrial ecosystems, 29–30 phosphorus, 45 phyto-and zooplankton, 31–32 plankton migration, 37–38 silicon, 45–46 Greenland ice sheet IPCC AR4 report, 88, 89 warmer temperature, 88 Grey nurse shark, 304 H Habitat loss, chondrichthyans, 306 I Illegal, unreported and unregulated (IUU) fishing AFZ and Indonesian vessels, 303–304 high seas/distant water, 303 shark population, 342 Inshore breeding ground reproduction

405

Subject Index

air and ocean temperature breeding grounds, 170 hatchling production, 169 life-history stages, 171 mechanisms, 172 ocean–atmosphere patterns, 175–176 rainfall, storms and cyclones, 173–174 sea level, 174–175 Intergovernmental Panel on Climate Change (IPCC), 5, 9–14, 24, 26, 27, 52, 62, 70, 92, 103, 106, 166 IUU fishing. See Illegal, unreported and unregulated fishing J Juveniles and adults foraging, ocean water ocean–atmosphere patterns, 180 ocean temperature, 176–179 wind and currents, 179–180 inshore foraging grounds ocean–atmosphere patterns and acidification, 183 ocean temperature, 180–181 rainfall, storms and cyclones, 181–182 sea level, 182 L Last glacial maximum (LGM) determination, barite measurement, 61 sea levels, 186 Life history traits, chondrichthyans, 329 M Marine turtle vulnerability adaptation and resilience climate change, 188 role, temperature, 187 beach nourishment, 190 biology and life history hatchlings, 156 thermoregulatory capacity, 155 types, 154 climate change, 163–164, 189 embryos and hatchlings air temperature, 164–167 rainfall, storms and cyclone, 167–168 sea level and atmospheric patterns, 169 genetic approaches, 190–191 inshore breeding grounds reproduction air and ocean temperature, 169–172 ocean–atmosphere patterns, 175–176 rainfall, storms and cyclones, 173–174 sea level, 174–175 juveniles and adults foraging ocean water, 176–180 inshore foraging grounds, 180–183

oceanic migration long-distance movements, 184 wind and currents, 185 oceans and atmosphere acidification, 162–163 large-scale patterns, 162 rainfall, storms and cyclones, 160–161 sea level, 161 temperature, 159–160 wind and, 161–162 past climate change foraging habitat, 187 tropical sea surface temperatures, 186 trends, 189 Meridional overturning circulation (MOC) density-driven circulation and THC, 18 forcing mechanisms, 17 North Atlantic/Arctic Arctic/Subarctic measurement, 19–20 subtropical measurement, 18–19 reduction and NW Europe cooling, 21 Southern Ocean/Antarctica, 20–22 upwelling eastern boundary regions, 22 Pleistocene glaciations, 23 role, 22–23 Minimum viable population (MVP) definition, 289 estimation, 337, 343 MOC. See Meridional overturning circulation Movement and activity, Atlantic cod adult migration to spawning, 219–220 Northeast Atlantic, 220–221 residence and homing behaviour, 220 larval dispersal, 222 thermal habits, 221–222 N Net primary production (NPP) and global chlorophyll, 33 reductions, 34 North Atlantic oscillation (NAO) Atlantic inflow, 86 vs. biological response, 236 North Sea cod, status and recovery, 249–250 Nutrients iron and dust, 47 nitrogen, 42–44 phosphorus, 45 silicon, 45–46 O Ocean acidification buffering, climate change atmospheric CO2 concentration, 63–64 DIC increase, 64–65

406 Ocean acidification (cont.) Revelle factor, 64 CO2 dissolution, 67–69 formation, 65–67 pump, 73–75 uptake, 69–70 comments, 79 nutrients, 75–76 palaeo-comparisons air bubbles, polar ice core, 76 Phanerozoic seafloors, 77–78 silicate minerals weathering, 77 projected future levels, 70–71 regional variation benthos, 73 coral reefs, 72–73 plankton, 71–72 Ocean anoxic events (OAEs), 38 Oceans and atmosphere acidification, 162–163 air temperature, 159–160 large-scale patterns, 162 rainfall, storms and cyclones, 160–161 sea level, 161 wind and, 161–162 Oceans impact, climate change acidification buffering, 63–65 CO2, 65–75 comments, 79 nutrients, 75–76 palaeo-comparisons, 76–79 projected future levels, 70–71 regional variation, 71–73 activities, 11 Arctic and seas adjacent Arctic Ocean and Subarctic Seas, 80–81 comments, 93 ecosystems, 91–92 Greenland ice sheet, 88 ice formation, 83–84 methane hydrates, 88, 90–91 modelling, 92–93 river runoff, 83 sea-ice cover, 84–87 sub-polar seas circulation, 82–83 trigger factors, sea-ice reductions, 86 circulation, 6–7 climate models CO2, 112–113 comments, 114–115 heat transport, 109–110 heat uptake, 106–108 ocean–climate feedbacks, 106 retro-modelling, past climate change, 113–114 sea ice, 111–112 water cycle, 111

Subject Index

CO2 biological pump, 56–57 carbonate counter pump, 57–58 continental shelf pump, 57 cycle, 51–54 role, 58 solubility pump, 54–56 storage and transfer, 7 comments, 26–27, 61–62 destabilisation glaciers, 25 ice sheet, Greenland and East Antarctic, 25–26 elements, ocean–climate interactions, 10 fertilisation, 61 global and regional information, 59–60 heat, 6 IPCC AR4 reports, 12–13 microbes role, 9 MOC density-driven circulation and THC, 18 forcing mechanisms, 17 North Atlantic/Arctic, 18–20 reduction and NW Europe cooling, 22 Southern Ocean/Antarctica, 20–22 upwelling, 22–23 natural climate variability, 13 nutrients, 9–10 observation programmes, 12 plankton productivity, oxygen content and upwelling, 9 polar regions, 8–9 primary production, global aerosols, 49–50 benthos, 36–37 biodiversity functional groups, 34–36 biological pump structure, 28 CH4, 47–49 chlorophyll, 33–34 comments, 51 iron and dust, 47 microbial plankton, 30–31 N2, 42–44 N and P mobilisation, 41 nitrate availability, 40–41 N2O and halocarbons, 49 O2, 38–40 oceanic, 28–30 phosphorus, 45 phyto- and zooplankton, 31–32 plankton migration, 37–38 silicon, 45–46 recommendations acidification, 121–122 Arctic Ocean, 122–123 CO2, 120–121 freshening waters, 117 Greenland ice sheet, 123

407

Subject Index

methane, 123 MOC and NW Europe cooling, 118 modelling, 124–125 nutrients, 120 O2, 119 ocean circulation and sea level changes, 117–118 primary production, biodiversity and non-native species, 119 Southern Ocean, 123–124 tropical storms, 118 warming waters, 116–117 relationship, nutrients and climate change, 11 salinification evaporation/precipitation, 16 south-to-north vertical section vs. western Atlantic basin, 15–16 vs. temperature, 16 sea level rise causes, 24 effects, 10 frequency/intensity, weather, 25 regional changes, 24–25 Southern Ocean comments, 105–106 future evolution, 103–105 observed changes, 97–103 role, 94–97 species biodiversity benthos and sea bottom sediment, 59 plankton, 58 temperature heat content, 14–16 SST, 13–14 tropical storms Atlantic hurricane activity, 24 intensity, 7 role, 23 WWF workshop, 10–11 Ocean temperature heat content climate models, 15–16 upper-ocean warming, 14–15 XBT data, 14 SST decadal and regional variability, 13–14 warming, 13 Oxygen minimum zones (OMZs), 39, 41, 117, 120 P Pacific and Atlantic open-ocean fisheries, 294, 299 Pacific decadal oscillation (PDO), 13 Particulate inorganic carbon (PIC), 52, 56, 57, 72 Particulate organic carbon (POC), 44, 52, 56, 57 Plankton functional types (PFTs), 35–36 Pollution and non-indigenous species

oil spills and leaks, 307 ships ballast water, 307–308 water, 306–307 Population viability analyses (PVA), 289, 337, 340 Prestige oil spill effects, marine biota adtidal, 373 benthos rocky intertidal, 376–380 sandy intertidal, 381–382 sublittoral, 382 subtidal areas, 376 biological responses, 387–389 clean-up procedure, 372–373 direct lethal and sublethal, 367–368 effects degree, 371–372 fishing resources biomarker, 383–384 PAH level, 384 sandeel, 383 Galicia, economic loss, 366–367 impacts assessment, 372 indirect, 368, 371 mammals and turtles, 386 oil components, 367 oil tanker spills, 369–371 physicochemical properties, 368 plankton acute effects, 373–374 embryogenesis, 375 WSF, 376 zooplankton, 374 recovery process, 371 seabirds adaptive responses, 386 affected species, 384 breeding, 385 oil accumulation, 384–385 R Rays. See also Chondrichthyes global catch, 285 pelagic longline fisheries, 299 pup production, 284 Queensland beach-meshing programme, 305 and sharks, 307 S Salinification evaporation/precipitation, 16 south-to-north vertical section vs. western Atlantic basin, 15–16 vs. temperature, 16 Sea level rise causes, 24 effects, 10 frequency/intensity, weather, 25 regional changes, 24–25

408 Sea surface temperature (SST) Atlantic hurricane activity, 24 CO2 reduction, 7 decadal and regional variability, 13–14 global, 26 in ice reduction, 88 isotherm, leatherback turtles, 176 tropics and Indian Ocean, 23 warming, 13 Sea-viewing wide field-of-view sensor (SeaWiFS), 33–35, 59 Sharks. See also Chondrichthyes; Fishing, chondrichthyes attacks, 305 blue sharks, 288, 299 commercial catch report, FAO, 304 global distribution, 287 incidental catch, 297 landing 1930–196, 295 legal and illegal harvest, 286 population management, 343 pup production, 284 and rays, 307 role diversity and ecosystem, 333 pelagic ecosystems, 334 targeted fisheries, 291–297 threatening processes, 280 white sharks, 302 Southern annular mode (SAM), 55, 98 Southern ocean and climate comments, 105–106 future evolution Antarctic glaciers, 105 CO2 sink, 104 planetary-scale climate change, 103 observed changes Antarctic krill, 101 circumpolar deep sea water, 101 CO2 emissions, 99 higher snowfall and glacier flow, 102–103 low-lying ice shelves, 102 sea-ice extent, Bellingshausen Sea, 100 temperature differences, 98 tidewater glaciers, Peninsula, 101 wind field, SAM, 98 role ACC currents, 94–95 biological productivity, 97 global ocean circulation, 95–96 lower and upper limb, MOC, 95–96

Subject Index

mode waters, 96 regional geography, 93–94 water column inventories, 96–97 Spawning, Atlantic cod, 215 Spawning stock biomass (SSB) Allee effects, 247 fishing, 242–243 and fish recruitment, 234 fish stock assessment, 245–246 North Sea, 234, 247 Species biodiversity benthos and sea bottom sediment, 59 plankton, 58 SST. See Sea surface temperature T Teleost threat risk, 322 Tiger sharks, 302, 335 Trophic cascades, 330 Tropical storms Atlantic hurricane activity, 24 intensity, 7 role, 23 Turtles, marine adaptation and resilience, 187–188 biology and life history, 154–159 climate change impacts embryos and hatchlings, 164–169 inshore foraging, juveniles and adults, 180–183 juveniles and adults foraging, 176–180 oceanic migrations, 184–185 reproduction, inshore breeding grounds, 169–176 IUCN Red List, 189 oceans and atmosphere changes acidification, 162–163 air and temperature, 159–160 large-scale patterns, 162 rainfall, storms and cyclones, 160–161 sea level, 161 wind and ocean currents, 161–162 past climate change, 185–187 W Water-soluble fraction (WSF), 375–376, 384 West Antarctic ice sheets (WAIS), 26 White sharks, 302 Worldwide Fund for Nature (WWF), 10

Ocean heat content (×1022J)

15 10 5 0 −5 Chichon

Agung −10

1950

1960

1970

1980

Pinatubo

1990

2000

Philip C. Reid et al., Figure 1.2 Upper-ocean heat content (grey shading indicates an estimate of one standard deviation error) for the upper 700 m relative to 1961. The straight line is the linear fit for 1961–2003. The global mean stratospheric optical depth (Ammann et al., 2003) (arbitrary scale) at the bottom indicates the timing of major volcanic eruptions. The brown curve is a 3-year running average of these values, included for comparison with the smoothed observations. Figure modified from Domingues et al. (2008).

SMW 0.5 0.1

AAIW

1000

MOW 0.05

UCDW

LSW

UNADW

2000

0.03

NEADW

0.015

3000 −0.015

W SO

LNADW

4000

−0.03

D

AABW

Salinity difference (psu)

Depth below sea surface (m)

0

−0.05

5000

−0.1 −0.5

6000 0⬚

0⬚

S

−5

0⬚

S

−4

0⬚

S

−3

0⬚

S

−2

S

−1

Eq

⬚N

10

⬚N

20

⬚N

30

⬚N

40

⬚N

50

⬚N

60

Philip C. Reid et al., Figure 1.3 South-to-north vertical section of salinity versus depth for the western Atlantic basin, plotted as Salinity difference averaged for the period 1985–1999 minus 1955–1969. Grey colour means that sampling was not sufficient to estimate mean salinity. Acronyms are for the different water masses; see original paper. From Curry et al. (2003).

MOC strength (Sv)

30

20

10

0 1950

1960

1970

1980

1990

2000

2010

Philip C. Reid et al., Figure 1.4 Mean strength of the Atlantic MOC at 26.5 N between 1957 and 2005 and associated error bars. Blue data points are for measurements taken from ships (Bryden et al., 2005). The red data point is an average of observations taken in the first full year of the RAPID monitoring array, plus error bar (Cunningham et al., 2007). Units are Sv (1 Sv ¼ 1 million m3 s1 of water passing the 26.5 N line). Values indicate a northwards net transport for water shallower than 1000 m.

Philip C. Reid et al., Figure 1.5 Estimates of freshwater flux relative to S ¼ 34.8* in Arctic and Subarctic Seas as determined during the ASOF project. Units are mSv and the base map is a snapshot of modelled sea surface height courtesy W. Maslowski, NPS, Monterey (1 mSv ¼ 31.546 km3 year1; * the numbers for PE, runoff and ice melt are independent of the choice of reference salinity). From Dickson et al. (2007).

A

80⬚N

60⬚W

0⬚

60⬚E

120⬚E

180⬚

120⬚W

120⬚E

180⬚

120⬚W

60⬚ 40⬚ 20⬚ 0⬚ 20⬚ 40⬚ 60⬚ 80⬚S B

80⬚N

60⬚W

0⬚

60⬚E

60⬚ 40⬚ 20⬚ 0⬚ 20⬚ 40⬚ 60⬚ 80⬚S

Philip C. Reid et al., Figure 1.6 (A) Location of mode and intermediate waters in the global ocean. Low-density mode waters of the eastern subtropical gyres—pink. The highest density mode waters, which subduct in the subtropical gyres—red. Atlantic Sub-polar Mode Water, North Pacific central mode water and Subantarctic Mode Water (SAMW)—dark red. (B) Covering a large area of the ocean, intermediate waters are found below the mode water, Labrador Sea intermediate water (LSW)—blue, North Pacific intermediate water (NPIW)—pale green, Antarctic intermediate water (AAIW)—green. These waters eventually re-emerge at the surface far from their origin. Primary formation areas for the intermediate waters are indicated with red crosses. From Talley (1999): http://www-pord.ucsd.edu/ltalley/papers/1990s/ agu_heat/talley_agu_heat.html.

SeaWiFS global chlorophyll a (mg/m3) 90 >10.0 Latitude (deg)

45

10.0 3.00

0

1.00 0.30

−45

0.10 0.03

−90 −180

−90

0.01 0 Longitude (deg)

90

180

Philip C. Reid et al., Figure 1.8 Global image of mean surface chlorophyll for the period 1998–2007. Processed from SeaWiFS data by Takafumi Hirata, PML.

Biome definitions 80⬚N Eq-D Eq-U

40⬚N

ST-PS ST-SS

0⬚

LL-U 40⬚S

SP Ice

80⬚S 0⬚

90⬚E

180⬚

90⬚W

0⬚

Philip C. Reid et al., Figure 1.9 The distribution of six different ocean biomes: (1a) equatorial—downwelling (Eq-D), (1b) equatorial—upwelling (Eq-U), (2) subtropical gyre—permanently stratified (ST-PS), (3) subtropical gyre—seasonally stratified (ST-SS), (4) low latitude—upwelling (LL-U), (5) sub-polar (SP) and (6) marginal sea ice (Ice). From Sarmiento et al. (2004).

50 Oct 1909–Oct 2002 ERSST v2

30 10 −10 −30 −50 −70

0

20

40

60

80 100 120 140 160 180 200 220 240 260 280 300 320 340 360

Philip C. Reid et al., Figure 1.10 Map showing modelled difference in nitrate availability based on a temperature nitrate relationship, between October 1909 and 2002. Darker colours represent greater contrasts between the years. From Kamykowski and Zentara (2005a,b). Green, nitrate in 1909 present at the surface > 2002; red, nitrate in 2002 present at the surface > 1909; blue, stratification in 1909 between nitracline and surface < 2002; grey, stratification in 1909 between nitracline and surface > 2002.

120⬚

240⬚

50

0⬚

0 10 00 2

60⬚

100 200 200

0

20 0 10 50

60⬚

100 50

50

0⬚ 10

50 100

0

50

10

0

200 100

0⬚

0⬚

50

200

60⬚

100

120⬚

0 20 0 20 100

60⬚

240⬚

Philip C. Reid et al., Figure 1.13 Annual production of biogenic silicon in the oceans (g m2 year1). Source www.radiolaria.org

Surface methane (ppmv)

1.6

1.66

1.72

1.78

1.84

Philip C. Reid et al., Figure 1.14 Global map of surface methane concentrations. From NASA: Credit: GMAO Chemical Forecasts and GEOS GHEM NRT Simulations for ICARTT.

February

A

30⬚ 60⬚ 90⬚ 120⬚ 150⬚180⬚150⬚120⬚ 90⬚ 60⬚ 30⬚ 0⬚ 80⬚

80⬚ 70⬚

70⬚

60⬚

60⬚ 50⬚ 40⬚ 30⬚ 20⬚ 10⬚ 0⬚ 10⬚ 20⬚ 30⬚ 40⬚ 50⬚

50⬚ 40⬚ 30⬚ 20⬚ 10⬚ 0⬚ 10⬚ 20⬚ 30⬚ 40⬚ 50⬚ 60⬚

60⬚ 70⬚

70⬚ 80⬚

80⬚ 30⬚ 60⬚ 90⬚ 120⬚ 150⬚ 180⬚150⬚ 120⬚ 90⬚ 60⬚ 30⬚ 0⬚

August

B

30⬚ 60⬚ 90⬚ 120⬚ 150⬚180⬚150⬚120⬚ 90⬚ 60⬚ 30⬚ 0⬚

80⬚

80⬚ 70⬚

70⬚

60⬚

60⬚ 50⬚ 40⬚ 30⬚ 20⬚ 10⬚ 0⬚ 10⬚ 20⬚ 30⬚ 40⬚ 50⬚

50⬚ 40⬚ 30⬚ 20⬚ 10⬚ 0⬚ 10⬚ 20⬚ 30⬚ 40⬚ 50⬚ 60⬚

60⬚ 70⬚

70⬚ 80⬚

80⬚ 30⬚ 60⬚ 90⬚ 120⬚ 150⬚ 180⬚150⬚ 120⬚ 90⬚ 60⬚ 30⬚ 0⬚

GMT 2008 Apr 1 13:54:09

−9

−8

−7

−6

−5

−4

−3

−2

−1

0

1

2

3

4

5

6

7

8

9

Net flux (gC m−2 month−1)

Philip C. Reid et al., Figure 1.15 Climatological mean distribution of CO2 flux (g C m2 month1) between the air and sea or vice versa for February (A) and August (B) in the reference year 2000. The wind speed data are from the 1979–2005 NCEP/DOE AMIP-II Reanalysis, and the gas transfer coefficient is computed using a (wind speed) squared dependence. Positive values (yellow–orange–red) indicate sea-to-air fluxes, and negative values (blue–magenta) indicate air-to-sea fluxes. Ice field data are from NCEP/DOE-2 Reanalysis Data (2005). An annual flux of 1.4 0.7 Pg C year1 is obtained for the global ocean by a summation of 12 monthly maps that were produced from approximately 12 million measurements. Figure from Takahashi et al. (2009).

80⬚N

LGM > CTL

LGM = CTL

LGM < CTL

LGM ? CTL

40⬚N

0⬚N

40⬚S

100⬚E

160⬚W

60⬚W

40⬚E

100 90 80 70 60 50 40 30 20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100

Philip C. Reid et al., Figure 1.17 Observed (superimposed circles) and modelled changes in export at the last glacial maximum (LGM) compared to the late Holocene (Bopp et al., 2003). Model results are in percent. Observations are qualitative only and indicate a higher (red), lower (blue) or similar (white) export in the LGM compared to the present day. From Le Que´re´ et al. (2005).

A

Depth (m)

Aragonite saturation depth

80⬚N

3500 3250 3000 2750

40⬚N

2500 2250 2000

0⬚

1750 1500 1250

40⬚S

1000 750 500 250

80⬚S

0

50⬚E

150⬚E

110⬚W

10⬚W

Model

Depth (m)

B 80⬚N

3500 3250 3000 2750

40⬚N

2500 2250 2000

0⬚

1750 1500 1250

40⬚S

1000 750 500 250

80⬚S

0

50⬚E

150⬚E

110⬚W

10⬚W

GLODAP

Philip C. Reid et al., Figure 1.19 Depth of aragonite saturation horizon: lower map from measurements recalculated from GLODAP after Key et al. (2004) and upper map modelled calculations. Figure from Gangstø et al. (2008).

A

B

Mean omega aragonite

4.5 3.5

40⬚N

Global ocean

0⬚

2.5 1.5

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N Equatorial area

40⬚S

High latitudes

80⬚S

0.5 1900

1950 2000

2050

50⬚E

2100

C

40⬚N 0⬚ 40⬚S 80⬚S 50⬚E

150⬚E

110⬚W

E

0⬚ 40⬚S 80⬚S 150⬚E

110⬚W

2075

40⬚N 0⬚ 40⬚S 80⬚S

10⬚W

150⬚E

110⬚W

10⬚W

2050

F

40⬚N

50⬚E

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 50⬚E

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N

10⬚W

80⬚N

10⬚W

2000

110⬚W

1861

D 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

80⬚N

150⬚E

80⬚N 40⬚N 0⬚ 40⬚S 80⬚S 50⬚E

150⬚E

110⬚W

10⬚W

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

2100

Philip C. Reid et al., Figure 1.20 Saturation state with respect to aragonite of surface waters (0–100 m): (A) time series of mean O for the global ocean, the equatorial area and for high latitudes, and maps in year (B) 1861, (C) 2000, (D) 2050, (E) 2075 and (F) 2100. Figure from Gangstø et al. (2008).

90

180 150 120 90 60

30

0

30 60

90 120 150 180

70 60 50 30 10 0 10 30 50 60 70 90 Neretic

Oceanic Abyssal clay

Calcareous ooze Foraminifera Pteropod

Silicious ooze Diatom Radiolarian

Philip C. Reid et al., Figure 1.22 Global map of the distribution of different sediment types on the bottom of the ocean. Source: www.radiolaria.org.

Water H2O H218O HDO

Air CO2 CH4 d 15N d 40Ar d 18O...

Impurities Dust, sea salt, 10Be trace elem. pollution, volcanism ....

Philip C. Reid et al., Figure 1.24 Bubbles of air in polar ice observed in a thin section under polarised light. Text redrawn from Raynaud D. EPICA lecture (2008 Ocean Sciences Meeting, Orlando, USA). Image: Copyright Michel Creseveur, CNRS/LGGE.

150⬚

180⬚

150⬚

120⬚

120⬚

90⬚

90⬚

60⬚

60⬚

30⬚

0⬚

30⬚

Bathymetric and topographic tints

(M)

0

−5000 −4000 −3000 −2000 −1500 −1000

25

50

75

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400

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500

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Scale : Map projection: Standard parallel: Horizontal datum:

Varies with plot size Polar stereographic 75⬚N WGS 84

200

Glaciers larger than 90 km2 were plotted in white irrespective of elevation using the same shading parameters as in the rest of the map.

0

400

Nautical miles (75⬚N) 200 0

600

Kilometres (75⬚N)

Philip C. Reid et al., Figure 1.26 Map showing the geographical features and bathymetry of the Arctic Ocean and adjacent seas. From Jakobsson et al. (2008).

0.08 0.06

SAT anomalies (⬚C)

⬚C per year

Trend 0.94 ⬚C/100years 0.04 0.02 0.00 −0.02

120

100

80

60

40

20

0

Number of years before 2001

Philip C. Reid et al., Figure 1.27 Surface atmosphere air temperature trends ( C per year) averaged for the Arctic (green) and Northern Hemisphere (red) ( Jones et al., 1999) with 95% significance as dashed lines from Polyakov et al. (2002).

Bering strait

Lomonosov ridge

Fram strait Greenland gyre Iceland sea Denmark strait Atlantic ocean

Canadian basin

Eurasian basin Surface water

Intermediate water Deep water

Philip C. Reid et al., Figure 1.28

Schematic of Arctic circulation (ACIA, 2005).

16

ICE_EXT, NORSEX SSM/I

⫻ 106

14

Unit:million Sq.km

12 10 8 6

2007 2008 2009 Unfiltered 2009 Average of monthly sea-ice 1979−2007 ± 1 STD of monthly sea-ice

4

Jan 11 22 Feb 10 20 Mar 11 22 Apr 11 21 May 11 22 Jun 11 21 Jul 11 22 Aug 11 22 Sep 11 21 Oct 11 22 Nov 11 21 Dec 11 22 Jan

2

The latest date in 2009 is march 31

Philip C. Reid et al., Figure 1.31 Extent of Arctic sea-ice (area of ocean with at least 15% sea-ice) in 2007, 2008 and part of 2009 with the long-term average. Source: Nansen Environmental and Remote Sensing Center, via the Arctic-ROOS web site (http://arctic-roos.org). 60⬚N

60⬚N 80

30⬚N 20

10 EQ

30⬚N EQ

20 30

30

20

30⬚S 10

70 60 40

30⬚S

30

40

40 60⬚S

60⬚S 90⬚E 0

180⬚ 20

90⬚W

40 60 Moles m−2

0⬚ 80

Philip C. Reid et al., Figure 1.36 Water column inventories of anthropogenic CO2 in the ocean. Note in particular the band of high levels flanking the northern side of the ACC, associated with mode and intermediate waters. Dissolved CO2 is lost to the atmosphere south of the Polar Front, where NADW wells up to the surface close to the coast (purplish colours) and gained from the atmosphere north of the Polar Front where mode waters and intermediate waters sink in the subduction process (green colours), making the Southern Ocean both a source and a sink for atmospheric CO2. From Sabine et al. (2004a).

⬚W

30

0⬚W

15

⬚E

30

60

⬚W

⬚E 60

90⬚E

90⬚W 12

0⬚W

0⬚E

12 15

0⬚E

⬚C −1.0

−0.5

0.0

0.5

1.0

Philip C. Reid et al., Figure 1.37 Temperature differences in the Southern Ocean between the 1990s and earlier decades, at approximately 700–1100 m depth. Note in particular the marked warming around the circumpolar band. Figure from Gille (2002).

⬚W

40⬚W

80⬚W

40 12 ⬚S 0⬚ W

20

⬚W

⬚W

0 10

60⬚W

40⬚W

20

⬚W

0⬚

⬚W

0

0⬚

60⬚W

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0 10

20 m

80 ⬚S

60

70 ⬚S

⬚S

50

⬚S

0m

80

70 ⬚S

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S

50

⬚S

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40

⬚S

12

Temperature trend (⬚C per year), 1955−1998 −0.05 −0.04 −0.03 −0.02 −0.01

0⬚W

80⬚W

60⬚W

40⬚W

0

0.01

20

0⬚W

⬚W

10

0.04

0.05

80⬚W

60⬚W

40⬚W

20⬚

W

10 0⬚

W

0.03

0⬚

W

0⬚

0⬚

12

⬚S S

100 m

80 ⬚

70

60

⬚S

⬚S 50 ⬚S

50 m

80

70 ⬚S

⬚S 60

50 ⬚

S

40

40 ⬚S

⬚S

12

0.02

Philip C. Reid et al., Figure 1.38 Trends in temperature during the second half of the twentieth century in the vicinity of the Antarctic Peninsula. Four different depth levels are shown, namely the surface, 20, 50 and 100 m. Note the strong, surface-intensified warming at the western side of the Peninsula. From Meredith and King (2005).

5 0.25 0.03.30

0.35 0.20 0.2

ANN 20

0.

0.2

15

0 0.

0.

15

0.1

15

0.3

0.20

5

0.

0.2 5 0.10.20 5 0.10 0.15

0.10 0.15

0.2 5

20

0.

−0.2 −0.3

0.25 0 0.3 5 0.3

0 −0.1

0

0.30

0.35

0.3 ⬚C per decade

0.1 0.2

Philip C. Reid et al., Figure 1.39 Predicted trends in surface temperatures over the next 100 years from a weighted average of the 20 coupled models used in IPCC AR4. Note the ubiquitous Southern Ocean surface warming, with ocean ‘hotspots’ in the Weddell and Ross Seas. From Bracegirdle et al. (2008).