Environmental and Resource Economics

, Volume 61, Issue 1, pp 71–85 | Cite as

The Behavioral Ecology of Fishing Vessels: Achieving Conservation Objectives Through Understanding the Behavior of Fishing Vessels

  • Marc Mangel
  • Natalie Dowling
  • Juan Lopez Arriaza
Article

Abstract

Colin Clark made seminal contributions in both resource economics and behavioral ecology. In the former, he showed how to link biological and economic factors in a consistent mathematical framework, virtually creating the field of mathematical bioeconomics single-handedly. In the latter, he was a major contributor of the introduction of state variable methods for modeling the behavior and life history of organisms. In this paper, we apply the methods of behavioral ecology to a problem in fisheries management and show that understanding fisher responses to quota decrements according to fishing area (so that the decrement in the quota of effort from fishing in a particular area is larger than the actual effort used there) may be as or more effective for seabird conservation than closing areas. To begin, we explain state variable methods in behavioral ecology, using insect parasitoids—Colin’s choice of after dinner talk at the meeting in his honor—making connections between behavioral ecology and resource economics. We then turn to the pelagic longline fishery off eastern Australia and show how the same kinds of methods used in behavioral ecology can provide new insights about this fishery. We provide a model of sufficient detail to compare the current management practice (closures), no management, and spatial management with effort decrements that vary over space and show that the latter management strategy is both environmentally and economically more effective than closures or no management.

Keywords

Bioeconomics Behavioral ecology State dependence   Stochastic dynamic programming Fisheries 

References

  1. Campbell RA, Hobday AJ (2003) Swordfish-environment-seamount fishery interactions off eastern Australia. Report to the Australian Fisheries Management Authority, CanberraGoogle Scholar
  2. Clark CW (1973) The economics of overexploitation. Science 181:630–634CrossRefGoogle Scholar
  3. Clark CW (1976) Mathematical bioeconomics. Wiley, New YorkGoogle Scholar
  4. Clark CW (2006) The worldwide crisis in fisheries: economic models and human behavior. Cambridge University Press, New YorkGoogle Scholar
  5. Clark CW, Mangel M (1984) Foraging and flocking strategies: information in an uncertain environment. Am Nat 123:626–647CrossRefGoogle Scholar
  6. Clark CW, Mangel M (1986) The evolutionary advantages of group foraging. Theor Popul Biol 30:45–75CrossRefGoogle Scholar
  7. Clark CW, Mangel M (2000) Dynamic state variable models in ecology. Methods and applications. Oxford University Press, OxfordGoogle Scholar
  8. Dixit AK, Pindyck RS (1994) Investment under uncertainty. Princeton University Press, Princeton, NJGoogle Scholar
  9. Dowling NA, Wilcox CW, Mangel M, Pascoe S (2012) Assessing opportunity and relocation costs of marine protected areas using a behavioural model of longline fleet dynamics. Fish Fish 13(2):139–157CrossRefGoogle Scholar
  10. Dowling NA, Wilcox CW, Mangel M (2013) Risk sensitivity and the behaviour of fishing vessels. Fish Fish (in press)Google Scholar
  11. Griffiths SP, Young JW, Lansdell MJ, Campbell RA, Hampton J, Hoyle SD, Langley A, Bromhead D, Hinton MG (2010) Ecological effects of longline fishing and climate change on the pelagic ecosystem off eastern Australia. Rev Fish Biol Fish 20(2):239–272CrossRefGoogle Scholar
  12. Hartog JR, Hobday AJ, Matear R, Feng M (2011) Habitat overlap between southern bluefin tuna and yellowfin tuna in the east coast longline fishery—implications for present and future spatial management. Deep-Sea Res Part II Top Stud Oceanogr 58(5):746–752CrossRefGoogle Scholar
  13. Hannesson R, Kennedy J (2009) Rent-maximization versus competition in the western and central pacific tuna fishery. J Nat Res Policy Res 1:49–65CrossRefGoogle Scholar
  14. Houston AI, McNamara JM (1999) Models of adaptive behavior. Cambridge University Press, CambridgeGoogle Scholar
  15. Jaffry S, Pascoe S, Robinson C (1999) Long run flexibilities for high valued UK fish species: a cointegration systems approach. Appl Econ 31:473–481CrossRefGoogle Scholar
  16. Levi T, Darimont CT, MacDuffee M, Mangel M, Paquet P, Wilmers CC (2012) Using grizzly bears to assess harvest-ecosystem tradeoffs in salmon fisheries. PLoS Biol 10(4):e1001303. doi:10.1371/journal.pbio.1001303 CrossRefGoogle Scholar
  17. Mangel M (1985) Decision and control in uncertain resource systems. Academic Press, NYGoogle Scholar
  18. Mangel M (2006) The theoretical biologist’s toolbox. Quantitative methods for ecology and evolutionary biology. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  19. Mangel M, Clark CW (1983) Uncertainty, search, and information in fisheries. J Int Counc Explor Seas 43:93–103CrossRefGoogle Scholar
  20. Mangel M, Clark CW (1986) Towards a unified foraging theory. Ecology 67:1127–1138CrossRefGoogle Scholar
  21. Mangel M, Clark CW (1988) Dynamic modeling in behavioral ecology. Princeton University Press, Princeton, NJGoogle Scholar
  22. Mangel M, Ludwig D (1992) Definition and evaluation of behavioral and developmental programs. Annu Rev Ecol Syst 23:507–536CrossRefGoogle Scholar
  23. Mangel M, Mullan A, Mulch A, Staub S, Yasukochi E (1998) A generally accessible derivation of the golden rule of bioeconomics. Bull Ecol Soc Am 79:145–148Google Scholar
  24. Richerson K, Levin PS, Mangel M (2010) Accounting for indirect effects and non-commensurate values in ecosystem based fishery management. Mar Policy 34:114–119CrossRefGoogle Scholar
  25. Selten R (1975) Reexamination of the perfectness concept for equilibrium points in extensive games. Int J Game Theory 4:25–55CrossRefGoogle Scholar
  26. Trebilco R, Gales R, Lawrence E, Alderman R, Robertson G, Baker GB (2010) Characterizing seabird by-catch in the eastern Australian tuna and billfish pelagic longline fishery in relation to temporal, spatial and biological influences. Aquat Conserv Mar Freshw Ecosyst 20(5):531–542CrossRefGoogle Scholar
  27. Thompson JN (2013) Relentless evolution. University of Chicago Press, Chicago, ILCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Marc Mangel
    • 1
    • 2
  • Natalie Dowling
    • 3
  • Juan Lopez Arriaza
    • 1
  1. 1.Center for Stock Assessment Research and Department of Applied Mathematics and StatisticsUniversity of CaliforniaSanta CruzUSA
  2. 2.Department of BiologyUniversity of BergenBergenNorway
  3. 3.CSIRO Marine and Atmospheric Research, Castray EsplanadeHobart Tasmania

Personalised recommendations