Cost–benefit analysis of ecosystem modeling to support fisheries management

Author:

Holden Matthew H.12ORCID,Plagányi Eva E.34,Fulton Elizabeth A.45,Campbell Alexander B.6,Janes Rachel6,Lovett Robyn A.6,Wickens Montana6,Adams Matthew P.789,Botelho Larissa Lubiana710,Dichmont Catherine M.11,Erm Philip12,Helmstedt Kate J.710,Heneghan Ryan F.7,Mendiolar Manuela12,Richardson Anthony J.123,Rogers Jacob G. D.3,Saunders Kate813,Timms Liam12

Affiliation:

1. School of Mathematics and Physics University of Queensland St Lucia Queensland Australia

2. Centre for Biodiversity and Conservation Science University of Queensland St Lucia Queensland Australia

3. CSIRO Environment Brisbane Queensland Australia

4. Centre for Marine Socioecology University of Tasmania Hobart Tasmania Australia

5. CSIRO Environment Hobart Tasmania Australia

6. Fisheries Queensland, Department of Agriculture and Fisheries Brisbane Queensland Australia

7. School of Mathematical Sciences Queensland University of Technology Brisbane Queensland Australia

8. Centre for Data Science Queensland University of Technology Brisbane Queensland Australia

9. School of Chemical Engineering The University of Queensland St Lucia Queensland Australia

10. Securing Antarctica's Environmental Future Queensland University of Technology Brisbane Queensland Australia

11. Cathy Dichmont Consulting Banksia Beach Queensland Australia

12. Conservation Science Group, Department of Zoology University of Cambridge Cambridge UK

13. Department of Econometrics and Business Statistics Monash University Melbourne Victoria Australia

Abstract

AbstractMathematical 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.

Funder

Australian Research Council

Publisher

Wiley

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