4.5 Article

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

Journal

ECOLOGICAL MODELLING
Volume 460, Issue -, Pages -

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ELSEVIER
DOI: 10.1016/j.ecolmodel.2021.109740

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Funding

  1. NSERC
  2. University of Toronto

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Ecosystem-based approaches, especially multispecies size spectrum models, have become crucial in fisheries management to study the impacts of fishing on marine community dynamics. Growth-related parameters, particularly those of top predators and abundant species, have the greatest influence on model outcomes, emphasizing the importance of estimating growth parameters for effective fisheries management.
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 miter, 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.

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