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The Ecospace model applied to the North Sea: Evaluating spatial predictions with fish biomass and fishing effort data

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  • Romagnoni, Giovanni
  • Mackinson, Steven
  • Hong, Jiang
  • Eikeset, Anne Maria

Abstract

The Ecospace model has been developed from the Ecopath with Ecosim food web model to add a spatial dimension for investigating marine ecosystems. In this study, we evaluated the sensitivity of an Ecospace model developed for the North Sea ecosystem to some of its key parameters, and we examined this model's capability to reproduce trends in spatial time-series of fish biomass and fishing effort. We measured the fit between the spatiotemporal model predictions and the corresponding data of biomass for 12 species and effort for three fishing fleets. Our results suggest that the Ecospace model for the North Sea can predict quite successfully the species distribution, but not the distribution of fishing effort. We hypothesise that the reason might be that Ecospace assumes spatial effort distribution to be driven mainly by profit, while other factors might be more important in our system at the spatiotemporal scale explored. The model might thus fail to capture fisher's behaviour accurately for this system. Despite the limitations of our ad hoc approach for sensitivity analysis, these results hint that some problems exist in our model, which might extend to other Ecospace models and perhaps to the framework in general. This study highlights the importance of validating Ecospace models with data if their results are used for management advice. We suggest that, in order to make of Ecospace a more robust tool for management advice, some critical improvements are needed: the development of an algorithm for parameter optimisation through fitting the model predictions to data, and advancement of the effort distribution model.

Suggested Citation

  • Romagnoni, Giovanni & Mackinson, Steven & Hong, Jiang & Eikeset, Anne Maria, 2015. "The Ecospace model applied to the North Sea: Evaluating spatial predictions with fish biomass and fishing effort data," Ecological Modelling, Elsevier, vol. 300(C), pages 50-60.
  • Handle: RePEc:eee:ecomod:v:300:y:2015:i:c:p:50-60
    DOI: 10.1016/j.ecolmodel.2014.12.016
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    References listed on IDEAS

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    1. 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.
    2. Steenbeek, Jeroen & Coll, Marta & Gurney, Leigh & Mélin, Frédéric & Hoepffner, Nicolas & Buszowski, Joe & Christensen, Villy, 2013. "Bridging the gap between ecosystem modeling tools and geographic information systems: Driving a food web model with external spatial–temporal data," Ecological Modelling, Elsevier, vol. 263(C), pages 139-151.
    3. Sanchirico, James N., 2005. "Additivity properties in metapopulation models: implications for the assessment of marine reserves," Journal of Environmental Economics and Management, Elsevier, vol. 49(1), pages 1-25, January.
    4. Espinosa-Romero, Maria J. & Gregr, Edward J. & Walters, Carl & Christensen, Villy & Chan, Kai M.A., 2011. "Representing mediating effects and species reintroductions in Ecopath with Ecosim," Ecological Modelling, Elsevier, vol. 222(9), pages 1569-1579.
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    Cited by:

    1. 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.
    2. Tabeta, Shigeru & Suzuki, Shota & Nakamura, Yoshiharu, 2015. "Combined modeling of fish behavior and fishing operations for conger eel fishery in Ise Bay," Ecological Modelling, Elsevier, vol. 313(C), pages 266-275.
    3. Nascimento, Marcela C. & Husson, Berengere & Guillet, Lilia & Pedersen, Torstein, 2023. "Modelling the spatial shifts of functional groups in the Barents Sea using a climate-driven spatial food web model," Ecological Modelling, Elsevier, vol. 481(C).
    4. 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).
    5. Tabeta, Shigeru & Suzuki, Shota & Nakamura, Kenta, 2017. "Assessment of fishery management by using a fishery simulator for bottom otter trawling in Ise Bay," Ecological Modelling, Elsevier, vol. 358(C), pages 40-49.

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