Cost-benefit analysis of ecosystem modeling to support fisheries management.

Autor: Holden MH; School of Mathematics and Physics, University of Queensland, St Lucia, Queensland, Australia.; Centre for Biodiversity and Conservation Science, University of Queensland, St Lucia, Queensland, Australia., Plagányi EE; CSIRO Environment, Brisbane, Queensland, Australia.; Centre for Marine Socioecology, University of Tasmania, Hobart, Tasmania, Australia., Fulton EA; Centre for Marine Socioecology, University of Tasmania, Hobart, Tasmania, Australia.; CSIRO Environment, Hobart, Tasmania, Australia., Campbell AB; Fisheries Queensland, Department of Agriculture and Fisheries, Brisbane, Queensland, Australia., Janes R; Fisheries Queensland, Department of Agriculture and Fisheries, Brisbane, Queensland, Australia., Lovett RA; Fisheries Queensland, Department of Agriculture and Fisheries, Brisbane, Queensland, Australia., Wickens M; Fisheries Queensland, Department of Agriculture and Fisheries, Brisbane, Queensland, Australia., Adams MP; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.; Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia.; School of Chemical Engineering, The University of Queensland, St Lucia, Queensland, Australia., Botelho LL; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.; Securing Antarctica's Environmental Future, Queensland University of Technology, Brisbane, Queensland, Australia., Dichmont CM; Cathy Dichmont Consulting, Banksia Beach, Queensland, Australia., Erm P; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, UK., Helmstedt KJ; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.; Securing Antarctica's Environmental Future, Queensland University of Technology, Brisbane, Queensland, Australia., Heneghan RF; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia., Mendiolar M; School of Mathematics and Physics, University of Queensland, St Lucia, Queensland, Australia.; Centre for Biodiversity and Conservation Science, University of Queensland, St Lucia, Queensland, Australia., Richardson AJ; School of Mathematics and Physics, University of Queensland, St Lucia, Queensland, Australia.; Centre for Biodiversity and Conservation Science, University of Queensland, St Lucia, Queensland, Australia.; CSIRO Environment, Brisbane, Queensland, Australia., Rogers JGD; CSIRO Environment, Brisbane, Queensland, Australia., Saunders K; Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia.; Department of Econometrics and Business Statistics, Monash University, Melbourne, Victoria, Australia., Timms L; School of Mathematics and Physics, University of Queensland, St Lucia, Queensland, Australia.; Centre for Biodiversity and Conservation Science, University of Queensland, St Lucia, Queensland, Australia.
Jazyk: angličtina
Zdroj: Journal of fish biology [J Fish Biol] 2024 Jun; Vol. 104 (6), pp. 1667-1674. Date of Electronic Publication: 2024 Mar 30.
DOI: 10.1111/jfb.15741
Abstrakt: Mathematical and statistical models underlie many of the world's most important fisheries management decisions. Since the 19th century, difficulty calibrating and fitting such models has been used to justify the selection of simple, stationary, single-species models to aid tactical fisheries management decisions. Whereas these justifications are reasonable, it is imperative that we quantify the value of different levels of model complexity for supporting fisheries management, especially given a changing climate, where old methodologies may no longer perform as well as in the past. Here we argue that cost-benefit analysis is an ideal lens to assess the value of model complexity in fisheries management. While some studies have reported the benefits of model complexity in fisheries, modeling costs are rarely considered. In the absence of cost data in the literature, we report, as a starting point, relative costs of single-species stock assessment and marine ecosystem models from two Australian organizations. We found that costs varied by two orders of magnitude, and that ecosystem model costs increased with model complexity. Using these costs, we walk through a hypothetical example of cost-benefit analysis. The demonstration is intended to catalyze the reporting of modeling costs and benefits.
(© 2024 Fisheries Society of the British Isles.)
Databáze: MEDLINE
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