IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v221y2010i2p362-369.html
   My bibliography  Save this article

Effect of variable fishing strategy on fisheries under changing effort and pressure: An agent-based model application

Author

Listed:
  • Cabral, Reniel B.
  • Geronimo, Rollan C.
  • Lim, May T.
  • Aliño, Porfirio M.

Abstract

An agent-based model was used to evaluate the response of a two-species fish community to fishing boat exploration strategies, namely: boats following high-yield boats (Cartesian); boats fishing at random sites (stochast-random); and boats fishing at least exploited sites (stochast-pressure). At low fishing pressure, the stochast-random mode yielded a high average catch per boat while sustaining fish biomass. At high fishing pressure, the Cartesian mode was more effective. For the Cartesian strategy, fish biomass exhibited four distinct behaviors with increasing number of boats. In the first phase, the fish biomass dropped with increasing number of boats due to a corresponding rise in biomass extraction. Rapid exploitation occurred in the second phase, when two or more boats occupied the same initial area, that led to the faster abandonment of those sites which then underwent biomass recovery. In the third phase, adding more boats resulted in a fluctuating stock biomass, where the combined effects of initial spatial distribution of boats and rapid localization led to either full stock recovery when boats were eventually confined to a single location due to spillovers, or stock extirpation when the entire area became fully occupied. Beyond the third phase, stock extirpation was assured. In order to break the pattern of localization (bandwagon effect), we introduced stochast-random intruders in a Cartesian-dominated fishery. Adding a single intruder changed the patchy-structured stock biomass pattern of a purely Cartesian fishery to a uniformly explored stock biomass pattern because of the additional spatial information provided by the intruder. Consequently, the average catch per boat increased but at the expense of a disproportionate decline in equilibrium biomass.

Suggested Citation

  • Cabral, Reniel B. & Geronimo, Rollan C. & Lim, May T. & Aliño, Porfirio M., 2010. "Effect of variable fishing strategy on fisheries under changing effort and pressure: An agent-based model application," Ecological Modelling, Elsevier, vol. 221(2), pages 362-369.
  • Handle: RePEc:eee:ecomod:v:221:y:2010:i:2:p:362-369
    DOI: 10.1016/j.ecolmodel.2009.09.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380009006425
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2009.09.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sanchirico, James N. & Wilen, James E., 1999. "Bioeconomics of Spatial Exploitation in a Patchy Environment," Journal of Environmental Economics and Management, Elsevier, vol. 37(2), pages 129-150, March.
    2. Youen Vermard & Paul Marchal & Stéphanie Mahévas & Olivier Thébaud, 2008. "A dynamic model of the Bay of Biscay pelagic fleet simulating fishing trip choice: the response to the closure of the European anchovy (Engraulis encrasicolus) fishery in 2005," Post-Print hal-00368317, HAL.
    3. Volker Grimm & Steven F. Railsback, 2006. "Agent-Based Models in Ecology: Patterns and Alternative Theories of Adaptive Behaviour," Contributions to Economics, in: Francesco C. Billari & Thomas Fent & Alexia Prskawetz & Jürgen Scheffran (ed.), Agent-Based Computational Modelling, pages 139-152, Springer.
    4. Fath, Brian D. & Halnes, Geir, 2007. "Cyclic energy pathways in ecological food webs," Ecological Modelling, Elsevier, vol. 208(1), pages 17-24.
    5. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cabral, Reniel B. & Aliño, Porfirio M. & Lim, May T., 2013. "A coupled stock-recruitment-age-structured model of the North Sea cod under the influence of depensation," Ecological Modelling, Elsevier, vol. 253(C), pages 1-8.
    2. Thanassekos, Stéphane & Scheld, Andrew M., 2020. "Simulating the effects of environmental and market variability on fishing industry structure," Ecological Economics, Elsevier, vol. 174(C).
    3. Burgess, Matthew G. & Carrella, Ernesto & Drexler, Michael & Axtell, Robert L. & Bailey, Richard M. & Watson, James R. & Cabral, Reniel B. & Clemence, Michaela & Costello, Christopher & Dorsett, Chris, 2018. "Opportunities for agent-based modeling in human dimensions of fisheries," SocArXiv gzhm5, Center for Open Science.
    4. Chion, Clément & Lamontagne, P. & Turgeon, S. & Parrott, L. & Landry, J.-A. & Marceau, D.J. & Martins, C.C.A. & Michaud, R. & Ménard, N. & Cantin, G. & Dionne, S., 2011. "Eliciting cognitive processes underlying patterns of human–wildlife interactions for agent-based modelling," Ecological Modelling, Elsevier, vol. 222(14), pages 2213-2226.
    5. Stelzenmüller, V. & Letschert, J. & Gimpel, A. & Kraan, C. & Probst, W.N. & Degraer, S. & Döring, R., 2022. "From plate to plug: The impact of offshore renewables on European fisheries and the role of marine spatial planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    6. Cooper, Rachel & Jarre, Astrid, 2017. "An Agent-based Model of the South African Offshore Hake Trawl Industry: Part I Model Description and Validation," Ecological Economics, Elsevier, vol. 142(C), pages 268-281.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luís de Sousa & Alberto Rodrigues da Silva, 2015. "Showcasing a Domain Specific Language for Spatial Simulation Scenarios with case studies," ERSA conference papers ersa15p1044, European Regional Science Association.
    2. Eugenio Caverzasi & Antoine Godin, 2013. "Stock-flow Consistent Modeling through the Ages," Economics Working Paper Archive wp_745, Levy Economics Institute.
    3. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    4. Michael J. Radzicki, 2003. "Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics," Journal of Economic Issues, Taylor & Francis Journals, vol. 37(1), pages 133-173, March.
    5. Kazuya Yamamoto, 2015. "Mobilization, Flexibility of Identity, and Ethnic Cleavage," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-8.
    6. Dirk Helbing & Thomas U. Grund, 2013. "Editorial: Agent-Based Modeling And Techno-Social Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-3.
    7. Ross Richardson & Matteo G. Richiardi & Michael Wolfson, 2015. "We ran one billion agents. Scaling in simulation models," LABORatorio R. Revelli Working Papers Series 142, LABORatorio R. Revelli, Centre for Employment Studies.
    8. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    9. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    10. Khalil, Elias L., 2010. "The Bayesian fallacy: Distinguishing internal motivations and religious beliefs from other beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 268-280, August.
    11. Jakub Bijak & Jason D. Hilton & Eric Silverman & Viet Dung Cao, 2013. "Reforging the Wedding Ring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(27), pages 729-766.
    12. Sterner, Thomas, 2007. "Unobserved diversity, depletion and irreversibility The importance of subpopulations for management of cod stocks," Ecological Economics, Elsevier, vol. 61(2-3), pages 566-574, March.
    13. Colton Brehm & Astrid Layton, 2021. "Nestedness of eco‐industrial networks: Exploring linkage distribution to promote sustainable industrial growth," Journal of Industrial Ecology, Yale University, vol. 25(1), pages 205-218, February.
    14. Christopher Costello & Daniel T. Kaffine, 2010. "Marine protected areas in spatial property-rights fisheries ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(3), pages 321-341, July.
    15. Costello, Christopher & Molina, Renato, 2021. "Transboundary marine protected areas," Resource and Energy Economics, Elsevier, vol. 65(C).
    16. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    17. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    18. Rich, Karl M. & Ross, R. Brent & Baker, A. Derek & Negassa, Asfaw, 2011. "Quantifying value chain analysis in the context of livestock systems in developing countries," Food Policy, Elsevier, vol. 36(2), pages 214-222, April.
    19. Ugo Merlone & Daren Sandbank & Ferenc Szidarovszky, 2013. "Equilibria analysis in social dilemma games with Skinnerian agents," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 12(2), pages 219-233, November.
    20. Hawkins, John & Beard, Rodney & McDonald, Stuart, 2006. "A multi-agent simulation model of fishery fleet dynamics for the Queensland coral reef line fishery," 2006 Conference (50th), February 8-10, 2006, Sydney, Australia 139788, Australian Agricultural and Resource Economics Society.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:221:y:2010:i:2:p:362-369. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.