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Toward Sustainable Fisheries in the Eternal Ocean

  • Takashi Yamakawa
  • Ichiro Aoki
  • Akinori Takasuka
Chapter
Part of the Fisheries Science Series book series (FISHSS)

Abstract

The contributions of all the chapters in this book are integrated to give a perspective on the requirements for realizing the sustainable fisheries of dynamic resources. A comprehensive overview of the whole process of data gathering, analyzing, and decision-making for fisheries assessment and management is presented in a sequential adaptive way as a plan-do-check-act (PDCA) cycle and illustrated in a schematic diagram. The process is a loop of sequential information updates and adaptive decision-making in the actual world parallel with the corresponding virtual world. Some points along the panoramic diagram are discussed with reference to discussions in previous chapters. Issues discussed are (1) diversity of management objectives and performance measures: multidisciplinary approach; (2) development of harvest control rules (HCRs); (3) revealing dynamics of stocks, communities, and ecosystems: mechanistic approach; (4) value of monitoring for adaptive management: empirical approach; (5) assessment models vs. operating models: to what extent should they be complex?; and (6) social institution and organization for fisheries management. The ocean is eternal in its existence; however, its components are never static but dynamic. Since fish communities dynamically change with climate-induced ocean regime shifts, we humans have no choice but to adapt to the nature of ecosystems. The benefits of the ocean will be eternal for us only if we successfully achieve such an adaptation.

Keywords

Adaptive management Ecosystem approach Eternal ocean Fisheries management Monitoring PDCA cycle Population dynamics Regime shift Stock assessment Sustainability 

References

  1. Andersen KH, Beyer JE (2006) Asymptotic size determines species abundance in the marine size spectrum. Am Nat 168:54–61CrossRefPubMedGoogle Scholar
  2. Andersen KH, Pedersen M (2010) Damped trophic cascades driven by fishing in model marine ecosystems. Proc R Soc B 277:795–802CrossRefPubMedGoogle Scholar
  3. Andersen KH, Farnsworth KD, Pedersen M, Gislason H, Beyer JE (2009) How community ecology links natural mortality, growth, and production of fish populations. ICES J Mar Sci 66:1978–1984CrossRefGoogle Scholar
  4. Aoki I, Nihira A, Yatsu A, Yamakawa T (2005) Postscript. In: Aoki I, Nihira A, Yatsu A, Yamakawa T (eds) Regime shift and fisheries stock management. Kouseisha Kouseikaku, Tokyo, pp 142–143. (in Japanese)Google Scholar
  5. Benoît E, Rochet MJ (2004) A continuous model of biomass size spectra governed by predation and the effects of fishing on them. J Theor Biol 226:9–21CrossRefPubMedGoogle Scholar
  6. Blanchard JL, Jennings S, Law R, Castle MD, McCloghrie P, Rochet MJ, Benoît E (2009) How does abundance scale with body size in coupled sizestructured food webs? J Anim Ecol 78:270–280CrossRefPubMedGoogle Scholar
  7. Blanchard JL, Law R, Castle MD, Jennings S (2011) Coupled energy pathways and the resilience of size-structured food webs. Theor Ecol 4:289–300CrossRefGoogle Scholar
  8. Cury P, Shannon L, Shin YJ (2003) The functioning of marine ecosystems: a fisheries perspective. In: Sinclair M, Valdimarsson G (eds) Responsible fisheries in the marine ecosystems. CABI Publishing/FAO, Wallingford/Rome, pp 103–123CrossRefGoogle Scholar
  9. Deming WE (1986) Out of the crisis. Massachusetts Institute of Technology, Center for Advanced Engineering Study, Cambridge, MAGoogle Scholar
  10. Duplisea DE, Jennings S, Warr KJ, Dinmore TA (2002) A size-based model of the impacts of bottom trawling on benthic community structure. Can J Fish Aquat Sci 59:1785–1795CrossRefGoogle Scholar
  11. Duraiappah AK, Nakamura K, Takeuchi K, Watanabe M, Nishi M (eds) (2012) Satoyama–satoumi ecosystems and human well-being: socio-ecological production landscapes of Japan. United Nations University Press, TokyoGoogle Scholar
  12. Freeman MMR (1992) The nature and utility of traditional ecological knowledge. Northern Perspectives 20:9–12Google Scholar
  13. Garcia SM, Cochrane KL (2005) Ecosystem approach to fisheries: a review of implementation guidelines. ICES J Mar Sci 62:311–318CrossRefGoogle Scholar
  14. Garcia SM, Zerbi A, Aliaume C, Do Chi T, Lasserre G (2003) The ecosystem approach to fisheries. FAO, RomeGoogle Scholar
  15. Garcia SM, Kolding J, Rice J, Rochet MJ, Zhou S, Arimoto T, Beyer JE, Borges L, Bundy A, Dunn D, Fulton EA, Hall M, Heino M, Law R, Makino M, Rijnsdorp AD, Simard F, Smith ADM (2012) Reconsidering the consequences of selective fisheries. Science 335:1045–1047CrossRefPubMedGoogle Scholar
  16. Gislason H, Rice J (1998) Modelling the response of size and diversity spectra of fish assemblages to changes in exploitation. ICES J Mar Sci 55:362–370CrossRefGoogle Scholar
  17. Hardin G (1968) The tragedy of the commons. Science 162:1243–1248CrossRefGoogle Scholar
  18. Hilborn R (2007) Defining success in fisheries and conflicts in objectives. Mar Policy 31:153–158CrossRefGoogle Scholar
  19. Jennings S, Brander K (2010) Predicting the effects of climate change on marine communities and consequences for fisheries. J Mar Sci 79:418–426Google Scholar
  20. Katsukawa T (2002) Switching fishes for non-equilibrium bioresources. Fish Sci 68(sup1):162–165CrossRefGoogle Scholar
  21. Kawasaki T (1983) Why do some pelagic fishes have wide fluctuations in their numbers? Biological basis of fluctuation from the viewpoint of evolutionary ecology. In: Sharp GD, Csirke J (eds) Proceedings of the expert consultation to examine changes in abundance and species composition of neritic fish resources, FAO Fish Rep 291. FAO, Rome, pp 1065–1080Google Scholar
  22. Kawasaki T (2002) Fundamental nature of the living marine resources and their management. Jap J Fish Econ 148:87–109 (in Japanese with English abstract)Google Scholar
  23. Kolding J, Jaconsen NS, Andersen KH, van Zwieten PAM (2016) Maximizing fisheries yields while maintaining community structure. Can J Fish Aquat Sci 73:644–655CrossRefGoogle Scholar
  24. Law R, Plank MJ, James A, Blanchard JL (2009) Size-spectra dynamics from stochastic predation and growth of individuals. Ecology 90:802–811CrossRefPubMedGoogle Scholar
  25. MacCall AD (2002) Fishery-management and stock-rebuilding prospects under conditions of low-frequency environmental variability and species interactions. Bull Mar Sci 70:613–628Google Scholar
  26. Makino M (2011) Fisheries management in Japan: its institutional features and case studies. Springer, DordrechtCrossRefGoogle Scholar
  27. Makino M, Sakurai Y (2014) Towards integrated research in fisheries science. Fish Sci 80:227–236CrossRefGoogle Scholar
  28. Makino M, Kim S, Velikanov A, Criddle K, Funamoto T, Hirota M, Sakurai Y (2014) Introduction: from the birth to the table of walleye pollock Theragra chalcogramma. Fish Sci 80:103–107CrossRefGoogle Scholar
  29. Maury O, Faugeras B, Shin YJ, Poggiale JC, Ari TB, Marsac F (2007) Modeling environmental effects on the size-structured energy flow through marine ecosystems. Part 1: the model. Prog Oceanogr 74:479–499CrossRefGoogle Scholar
  30. McCullough HC (1988) The tale of the Heike. Stanford University Press, StanfordGoogle Scholar
  31. Ostrom E (1990) Governing the commons: the evolution of institutions for collective action. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  32. Pomeroy R (1995) Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia. Ocean Coast Manag 27(3):143–162CrossRefGoogle Scholar
  33. Pope JG, Rice JC, Daan N, Jennings S, Gislason H (2006) Modelling an exploited marine fish community with 15 parameters – results from a simple size-based model. ICES J Mar Sci 63:1029–1044Google Scholar
  34. Rochet MJ, Benoît E (2012) Fishing destabilizes the biomass flow in the marine size spectrum. Proc R Soc B 279:284–292CrossRefPubMedGoogle Scholar
  35. Sen S, Nielsen JR (1996) Fisheries co-management: a comparative analysis. Mar Policy 20(5):405–418CrossRefGoogle Scholar
  36. Shewhart WA, Deming WE (1939) Statistical method from the viewpoint of quality control. Courier Corporation, New YorkGoogle Scholar
  37. Tetko IV, Livingstone DJ, Luik AI (1995) Neural network studies. 1. Comparison of overfitting and overtraining. J Chem Inf Comput Sci 35:826–833CrossRefGoogle Scholar
  38. United Nations University Institute of Advanced Studies Operating Unit Ishikawa/Kanazawa (2011) Biological and cultural diversity in coastal communities, exploring the potential of satoumi for implementing the ecosystem approach in the Japanese archipelago. In: Technical series 61. Montreal, Secretariat of the Convention on Biological DiversityGoogle Scholar
  39. Walters CJ (1989) Value of short-term forecasts of recruitment variation for harvest management. Can J Fish Aquat Sci 46:1969–1976CrossRefGoogle Scholar
  40. Winemiller KO (2005) Life history strategies, population regulation, and implications for fisheries management. Can J Fish Aquat Sci 62:872–885CrossRefGoogle Scholar
  41. Winemiller KO, Rose KA (1992) Patterns of life-history diversification in north American fishes: implications for population regulation. Can J Fish Aquat Sci 49:2196–2218CrossRefGoogle Scholar
  42. Yvon-Durocher G, Montoya JM, Emmerson MC, Woodward G (2008) Macroecological patterns and niche structure in a new marine food web. Cent Eur J Biol 3(1):91–103Google Scholar

Copyright information

© Springer Japan KK and the Japanese Society of Fisheries Science 2018

Authors and Affiliations

  • Takashi Yamakawa
    • 1
  • Ichiro Aoki
    • 2
  • Akinori Takasuka
    • 3
  1. 1.Graduate School of Agricultural and Life SciencesThe University of TokyoTokyoJapan
  2. 2.The University of TokyoTokyoJapan
  3. 3.Japan Fisheries Research and Education AgencyNational Research Institute of Fisheries ScienceYokohamaJapan

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