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Identifying influential parameters of a multi-species fish size spectrum model for a northern temperate lake through sensitivity analyses

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  • Benoit, David M.
  • Giacomini, Henrique C.
  • Chu, Cindy
  • Jackson, Donald A.

Abstract

Ecosystem-based approaches that take species interactions into account have shifted to the forefront of fisheries modelling and management in recent years. As a result, multispecies size spectrum models have been increasingly used to explore impacts of fishing on marine community dynamics. The use of these models, which has been facilitated by the development of the R package mizer, requires the estimation of species-specific parameters related to growth, reproduction, and feeding. These parameters, which may be estimated from imperfect information, may contribute to model uncertainty and thus reduce the value of information available for management purposes. In this study of a freshwater fishery, we conduct a comprehensive global sensitivity analysis pairing the Morris and Sobol methods to identify life-history parameters having the largest influence on model outputs. Here, we focus on (i) the size spectrum slope, (ii) the scatter around the linear relationship of the size spectrum, (iii) total biomass, and (iv) species diversity. We found that parameters relating to growth, namely the von Bertalanffy growth coefficient and asymptotic mass, had the greatest influence on our size spectrum model results. This was particularly true for top predators and the most abundant species. Our results suggest that estimation of growth parameters of top predators be given priority to reduce uncertainty in model output, and ultimately, fisheries management.

Suggested Citation

  • Benoit, David M. & Giacomini, Henrique C. & Chu, Cindy & Jackson, Donald A., 2021. "Identifying influential parameters of a multi-species fish size spectrum model for a northern temperate lake through sensitivity analyses," Ecological Modelling, Elsevier, vol. 460(C).
    • Handle: RePEc:eee:ecomod:v:460:y:2021:i:c:s0304380021002908
    DOI: 10.1016/j.ecolmodel.2021.109740
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    References listed on IDEAS

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    1. DeJonge, Kendall C. & Ascough, James C. & Ahmadi, Mehdi & Andales, Allan A. & Arabi, Mazdak, 2012. "Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments," Ecological Modelling, Elsevier, vol. 231(C), pages 113-125.
    2. 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.
    3. Axel G. Rossberg & Ursula Gaedke & Pavel Kratina, 2019. "Dome patterns in pelagic size spectra reveal strong trophic cascades," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    4. Geoffrey B. West & James H. Brown & Brian J. Enquist, 2001. "A general model for ontogenetic growth," Nature, Nature, vol. 413(6856), pages 628-631, October.
    5. Ciric, C. & Ciffroy, P. & Charles, S., 2012. "Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model," Ecological Modelling, Elsevier, vol. 246(C), pages 119-130.
    6. Mesnil, Benoit, 2012. "The hesitant emergence of maximum sustainable yield (MSY) in fisheries policies in Europe," Marine Policy, Elsevier, vol. 36(2), pages 473-480.
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