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Which forcing factors fit? Using ecosystem models to investigate the relative influence of fishing and changes in primary productivity on the dynamics of marine ecosystems

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Listed:
  • Mackinson, S.
  • Daskalov, G.
  • Heymans, J.J.
  • Neira, S.
  • Arancibia, H.
  • Zetina-Rejón, M.
  • Jiang, H.
  • Cheng, H.Q.
  • Coll, M.
  • Arreguin-Sanchez, F.
  • Keeble, K.
  • Shannon, L.

Abstract

Fishing mortality and primary production (or proxy for) were used to drive the dynamics of fish assemblages in 9 trophodynamic models of contrasting marine ecosystems. Historical trends in abundance were reconstructed by fitting model predictions to observations from stock assessments and fisheries independent survey data. The model fitting exercise derives values for otherwise unknown parameters that specify the relative strength of trophic interactions and, in some instances, a time series anomaly for changes in primary production. We measured how much better or worse were model predictions when bottom-up forcing by primary production were added to top-down forcing by fishing. Searching for cross system patterns, the relative contribution of fishing and changes in primary production, mediated through trophic interactions, are evaluated for the ecosystems as a whole and for selected similar species in different ecosystems. The analysis provides a simple qualitative way to explain which forcing factors have most influence on modeled dynamics. Both fishing and primary production forcing were required to obtain the best model fits to data. Fishing effects more strongly influenced 6 of 9 of the ecosystems, but primary production was more often found to be the main factor influencing the selected pelagic and demersal fish stock trends. Examination of sensitivity to ecological and model parameters suggests that the results are the product of complex food-web interactions rather than simple deterministic responses of the models.

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  • Mackinson, S. & Daskalov, G. & Heymans, J.J. & Neira, S. & Arancibia, H. & Zetina-Rejón, M. & Jiang, H. & Cheng, H.Q. & Coll, M. & Arreguin-Sanchez, F. & Keeble, K. & Shannon, L., 2009. "Which forcing factors fit? Using ecosystem models to investigate the relative influence of fishing and changes in primary productivity on the dynamics of marine ecosystems," Ecological Modelling, Elsevier, vol. 220(21), pages 2972-2987.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:21:p:2972-2987
    DOI: 10.1016/j.ecolmodel.2008.10.021
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    References listed on IDEAS

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    1. Coilín Minto & Ransom A. Myers & Wade Blanchard, 2008. "Survival variability and population density in fish populations," Nature, Nature, vol. 452(7185), pages 344-347, March.
    2. Grégory Beaugrand & Keith M. Brander & J. Alistair Lindley & Sami Souissi & Philip C. Reid, 2003. "Plankton effect on cod recruitment in the North Sea," Nature, Nature, vol. 426(6967), pages 661-664, December.
    3. Jiang, Hong & Cheng, He-Qin & Xu, Hai-Gen & Arreguín-Sánchez, Francisco & Zetina-Rejón, Manuel J. & Del Monte Luna, Pablo & Le Quesne, William J.F., 2008. "Trophic controls of jellyfish blooms and links with fisheries in the East China Sea," Ecological Modelling, Elsevier, vol. 212(3), pages 492-503.
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    1. Evan Howell & Colette Wabnitz & John Dunne & Jeffrey Polovina, 2013. "Climate-induced primary productivity change and fishing impacts on the Central North Pacific ecosystem and Hawaii-based pelagic longline fishery," Climatic Change, Springer, vol. 119(1), pages 79-93, July.
    2. Lercari, Diego & Defeo, Omar & Ortega, Leonardo & Orlando, Luis & Gianelli, Ignacio & Celentano, Eleonora, 2018. "Long-term structural and functional changes driven by climate variability and fishery regimes in a sandy beach ecosystem," Ecological Modelling, Elsevier, vol. 368(C), pages 41-51.
    3. Fu, Caihong & Travers-Trolet, Morgane & Velez, Laure & Grüss, Arnaud & Bundy, Alida & Shannon, Lynne J. & Fulton, Elizabeth A. & Akoglu, Ekin & Houle, Jennifer E. & Coll, Marta & Verley, Philippe & He, 2018. "Risky business: The combined effects of fishing and changes in primary productivity on fish communities," Ecological Modelling, Elsevier, vol. 368(C), pages 265-276.
    4. Zetina-Rejón, Manuel J. & Cabrera-Neri, Erika & López-Ibarra, Gladis A. & Arcos-Huitrón, N. Enrique & Christensen, Villy, 2015. "Trophic modeling of the continental shelf ecosystem outside of Tabasco, Mexico: A network and modularity analysis," Ecological Modelling, Elsevier, vol. 313(C), pages 314-324.
    5. Coll, M. & Pennino, M. Grazia & Steenbeek, J. & Sole, J. & Bellido, J.M., 2019. "Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches," Ecological Modelling, Elsevier, vol. 405(C), pages 86-101.
    6. Tomczak, M.T. & Niiranen, S. & Hjerne, O. & Blenckner, T., 2012. "Ecosystem flow dynamics in the Baltic Proper—Using a multi-trophic dataset as a basis for food–web modelling," Ecological Modelling, Elsevier, vol. 230(C), pages 123-147.
    7. Heymans, Johanna Jacomina & Coll, Marta & Link, Jason S. & Mackinson, Steven & Steenbeek, Jeroen & Walters, Carl & Christensen, Villy, 2016. "Best practice in Ecopath with Ecosim food-web models for ecosystem-based management," Ecological Modelling, Elsevier, vol. 331(C), pages 173-184.
    8. Morris, David J. & Speirs, Douglas C. & Cameron, Angus I. & Heath, Michael R., 2014. "Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos," Ecological Modelling, Elsevier, vol. 273(C), pages 251-263.
    9. Stäbler, Moritz & Kempf, Alexander & Mackinson, Steven & Poos, Jan Jaap & Garcia, Clement & Temming, Axel, 2016. "Combining efforts to make maximum sustainable yields and good environmental status match in a food-web model of the southern North Sea," Ecological Modelling, Elsevier, vol. 331(C), pages 17-30.
    10. Ofir, E. & Heymans, J.J. & Shapiro, J. & Goren, M. & Spanier, E. & Gal, G., 2017. "Predicting the impact of Lake Biomanipulation based on food-web modeling—Lake Kinneret as a case study," Ecological Modelling, Elsevier, vol. 348(C), pages 14-24.
    11. Barros, Mónica E. & Arriagada, Ana & Arancibia, Hugo & Neira, Sergio, 2024. "Using a time-dynamic food web model to compare predation and fishing mortality in Pleuroncodes monodon (Galatheidae: Crustaceae) and other benthic and demersal resource species off central Chile," Ecological Modelling, Elsevier, vol. 487(C).
    12. Püts, Miriam & Taylor, Marc & Núñez-Riboni, Ismael & Steenbeek, Jeroen & Stäbler, Moritz & Möllmann, Christian & Kempf, Alexander, 2020. "Insights on integrating habitat preferences in process-oriented ecological models – a case study of the southern North Sea," Ecological Modelling, Elsevier, vol. 431(C).
    13. Coll, Marta & Steenbeek, Jeroen & Sole, Jordi & Palomera, Isabel & Christensen, Villy, 2016. "Modelling the cumulative spatial–temporal effects of environmental drivers and fishing in a NW Mediterranean marine ecosystem," Ecological Modelling, Elsevier, vol. 331(C), pages 100-114.

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