IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v431y2020ics0304380020302507.html
   My bibliography  Save this article

A spatially explicit individual-based model to support management of commercial and recreational fisheries for European sea bass Dicentrarchus labrax

Author

Listed:
  • Walker, Nicola D.
  • Boyd, Robin
  • Watson, Joseph
  • Kotz, Max
  • Radford, Zachary
  • Readdy, Lisa
  • Sibly, Richard
  • Roy, Shovonlal
  • Hyder, Kieran

Abstract

The European sea bass (Dicentrarchus labrax) is a slow growing and late maturing high value fish that is exploited by both commercial and recreational fisheries. In recent years, scientific assessments have shown a rapid decline in spawning stock biomass around the UK attributed to poor recruitment (driven by environmental factors) and high fishing mortality. This resulted in significant reductions in the harvest of sea bass following technical measures implemented by the European Commission to conserve stocks. Individual-based models (IBMs) are simulations of individual ‘agents’ of organisms that interact with each other and their environment locally and have been shown to be effective management tools in many systems. Here, an IBM that simulates the population dynamics and spatial distribution of sea bass was developed to assess how technical management measures applied to subsets of the population impact the overall stock. Conventional stock assessment techniques were used to model the processes affecting population dynamics, while the spatial distribution was simulated using a combination of temperature preferences and information from tagging studies. The IBM was parameterised using existing knowledge from the literature and can mimic key assessment outputs used to inform management and advice on fishing opportunities. Utility of the IBM is demonstrated by simulating the population consequences of several key management scenarios based on those implemented by the European Commission, including short-term bans on pelagic trawling in spawning areas, commercial and recreational catch limits and increasing the minimum conservation reference size. The IBM has potential to complement the annual stock assessment in managing European sea bass because it models individual movement, environmental drivers and emergent spatial distribution, thereby providing enhanced predictions of management strategy outcomes that could inform spatial advice on fishing opportunities and policy.

Suggested Citation

  • Walker, Nicola D. & Boyd, Robin & Watson, Joseph & Kotz, Max & Radford, Zachary & Readdy, Lisa & Sibly, Richard & Roy, Shovonlal & Hyder, Kieran, 2020. "A spatially explicit individual-based model to support management of commercial and recreational fisheries for European sea bass Dicentrarchus labrax," Ecological Modelling, Elsevier, vol. 431(C).
  • Handle: RePEc:eee:ecomod:v:431:y:2020:i:c:s0304380020302507
    DOI: 10.1016/j.ecolmodel.2020.109179
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380020302507
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2020.109179?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. Sambilay, V.C., Jr., 1990. "Interrelationships between swimming speed, caudal fin aspect ratio and body length of fishes," Fishbyte, The WorldFish Center, vol. 8(3), pages 16-20.
    2. Grimm, Volker & Augusiak, Jacqueline & Focks, Andreas & Frank, Béatrice M. & Gabsi, Faten & Johnston, Alice S.A. & Liu, Chun & Martin, Benjamin T. & Meli, Mattia & Radchuk, Viktoriia & Thorbek, Pernil, 2014. "Towards better modelling and decision support: Documenting model development, testing, and analysis using TRACE," Ecological Modelling, Elsevier, vol. 280(C), pages 129-139.
    3. van der Vaart, Elske & Beaumont, Mark A. & Johnston, Alice S.A. & Sibly, Richard M., 2015. "Calibration and evaluation of individual-based models using Approximate Bayesian Computation," Ecological Modelling, Elsevier, vol. 312(C), pages 182-190.
    4. Heinänen, Stefan & Chudzinska, Magda Ewa & Brandi Mortensen, Jonas & Teo, Theophilus Zhi En & Rong Utne, Kjell & Doksæter Sivle, Lise & Thomsen, Frank, 2018. "Integrated modelling of Atlantic mackerel distribution patterns and movements: A template for dynamic impact assessments," Ecological Modelling, Elsevier, vol. 387(C), pages 118-133.
    5. Watkins, Katherine Shepard & Rose, Kenneth A., 2017. "Simulating individual-based movement in dynamic environments," Ecological Modelling, Elsevier, vol. 356(C), pages 59-72.
    6. Woillez, Mathieu & Fablet, Ronan & Ngo, Tran-Thanh & Lalire, Maxime & Lazure, Pascal & de Pontual, Hélène, 2016. "A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study," Ecological Modelling, Elsevier, vol. 321(C), pages 10-22.
    7. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    8. Boyd, Robin & Roy, Shovonlal & Sibly, Richard & Thorpe, Robert & Hyder, Kieran, 2018. "A general approach to incorporating spatial and temporal variation in individual-based models of fish populations with application to Atlantic mackerel," Ecological Modelling, Elsevier, vol. 382(C), pages 9-17.
    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. Watson, Joseph W & Boyd, Robin & Dutta, Ritabrata & Vasdekis, Georgios & Walker, Nicola D. & Roy, Shovonlal & Everitt, Richard & Hyder, Kieran & Sibly, Richard M, 2022. "Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass✰," Ecological Modelling, Elsevier, vol. 466(C).

    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. Watson, Joseph W & Boyd, Robin & Dutta, Ritabrata & Vasdekis, Georgios & Walker, Nicola D. & Roy, Shovonlal & Everitt, Richard & Hyder, Kieran & Sibly, Richard M, 2022. "Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass✰," Ecological Modelling, Elsevier, vol. 466(C).
    2. Boyd, Robin & Roy, Shovonlal & Sibly, Richard & Thorpe, Robert & Hyder, Kieran, 2018. "A general approach to incorporating spatial and temporal variation in individual-based models of fish populations with application to Atlantic mackerel," Ecological Modelling, Elsevier, vol. 382(C), pages 9-17.
    3. Boult, Victoria L. & Quaife, Tristan & Fishlock, Vicki & Moss, Cynthia J. & Lee, Phyllis C. & Sibly, Richard M., 2018. "Individual-based modelling of elephant population dynamics using remote sensing to estimate food availability," Ecological Modelling, Elsevier, vol. 387(C), pages 187-195.
    4. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    5. Cartwright, Samantha J. & Bowgen, Katharine M. & Collop, Catherine & Hyder, Kieran & Nabe-Nielsen, Jacob & Stafford, Richard & Stillman, Richard A. & Thorpe, Robert B. & Sibly, Richard M., 2016. "Communicating complex ecological models to non-scientist end users," Ecological Modelling, Elsevier, vol. 338(C), pages 51-59.
    6. David, Viviane & Joachim, Sandrine & Tebby, Cleo & Porcher, Jean-Marc & Beaudouin, Rémy, 2019. "Modelling population dynamics in mesocosms using an individual-based model coupled to a bioenergetics model," Ecological Modelling, Elsevier, vol. 398(C), pages 55-66.
    7. Lorscheid, Iris & Meyer, Matthias, 2016. "Divide and conquer: Configuring submodels for valid and efficient analyses of complex simulation models," Ecological Modelling, Elsevier, vol. 326(C), pages 152-161.
    8. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    9. Jette Reeg & Simon Heine & Christine Mihan & Sean McGee & Thomas G Preuss & Florian Jeltsch, 2020. "Herbicide risk assessments of non-target terrestrial plant communities: A graphical user interface for the plant community model IBC-grass," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-18, March.
    10. Ayllón, Daniel & Railsback, Steven F. & Vincenzi, Simone & Groeneveld, Jürgen & Almodóvar, Ana & Grimm, Volker, 2016. "InSTREAM-Gen: Modelling eco-evolutionary dynamics of trout populations under anthropogenic environmental change," Ecological Modelling, Elsevier, vol. 326(C), pages 36-53.
    11. Fitts, Lucia A. & Fraser, Jacob S. & Miranda, Brian R. & Domke, Grant M. & Russell, Matthew B. & Sturtevant, Brian R., 2023. "An iterative site-scale approach to calibrate and corroborate successional processes within a forest landscape model," Ecological Modelling, Elsevier, vol. 477(C).
    12. Lamonica, Dominique & Herbach, Ulysse & Orias, Frédéric & Clément, Bernard & Charles, Sandrine & Lopes, Christelle, 2016. "Mechanistic modelling of daphnid-algae dynamics within a laboratory microcosm," Ecological Modelling, Elsevier, vol. 320(C), pages 213-230.
    13. Crouse, Kristin N. & Desai, Nisarg P. & Cassidy, Kira A. & Stahler, Erin E. & Lehman, Clarence L. & Wilson, Michael L., 2022. "Larger territories reduce mortality risk for chimpanzees, wolves, and agents: Multiple lines of evidence in a model validation framework," Ecological Modelling, Elsevier, vol. 471(C).
    14. Chudzinska, Magda & Nabe-Nielsen, Jacob & Smout, Sophie & Aarts, Geert & Brasseur, Sophie & Graham, Isla & Thompson, Paul & McConnell, Bernie, 2021. "AgentSeal: Agent-based model describing movement of marine central-place foragers," Ecological Modelling, Elsevier, vol. 440(C).
    15. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).
    16. King, Elizabeth G. & Franz, Trenton E., 2016. "Combining ecohydrologic and transition probability-based modeling to simulate vegetation dynamics in a semi-arid rangeland," Ecological Modelling, Elsevier, vol. 329(C), pages 41-63.
    17. Courbaud, B. & Lafond, V. & Lagarrigues, G. & Vieilledent, G. & Cordonnier, T. & Jabot, F. & de Coligny, F., 2015. "Applying ecological model evaludation: Lessons learned with the forest dynamics model Samsara2," Ecological Modelling, Elsevier, vol. 314(C), pages 1-14.
    18. Keane, Robert E. & McKenzie, Donald & Falk, Donald A. & Smithwick, Erica A.H. & Miller, Carol & Kellogg, Lara-Karena B., 2015. "Representing climate, disturbance, and vegetation interactions in landscape models," Ecological Modelling, Elsevier, vol. 309, pages 33-47.
    19. Wouter Vermeer & Arthur Hjorth & Samuel M. Jenness & C Hendrick Brown & Uri Wilensky, 2020. "Leveraging Modularity During Replication of High-Fidelity Models: Lessons from Replicating an Agent-Based Model for HIV Prevention," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(4), pages 1-7.
    20. de Jager, Monique & Hengeveld, Geerten M. & Mooij, Wolf M. & Slooten, Elisabeth, 2019. "Modelling the spatial dynamics of Maui dolphins using individual-based models," Ecological Modelling, Elsevier, vol. 402(C), pages 59-65.

    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:431:y:2020:i:c:s0304380020302507. 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.