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Article

Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

1
FAO Viale Del Terme de Caracella, 00153 Rome, Italy
2
Joint Research Centre, European Commission, 21027 Ispra, Italy
3
Centre for Environmental Policy, Imperial College London, London SW7 2BX, UK
4
SAFS, University of Washington, Seattle, WA 98195, USA
5
Sea Around Us, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Vincenzo Torretta, Eun-Sung Chung, António Dinis Ferreira, Peter Goethals and Jose Navarro Pedreño
Sustainability 2021, 13(11), 6101; https://0-doi-org.brum.beds.ac.uk/10.3390/su13116101
Received: 8 April 2021 / Revised: 20 May 2021 / Accepted: 24 May 2021 / Published: 28 May 2021
(This article belongs to the Special Issue Reviews, Advances and Applications in Environmental Sustainability)
Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus), one of the latest developments in the field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments. View Full-Text
Keywords: SDG 14.4.1; SOFIA; overfishing; sustainable; stock reduction; SRA+, CMSY+ SDG 14.4.1; SOFIA; overfishing; sustainable; stock reduction; SRA+, CMSY+
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MDPI and ACS Style

Sharma, R.; Winker, H.; Levontin, P.; Kell, L.; Ovando, D.; Palomares, M.L.D.; Pinto, C.; Ye, Y. Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs. Sustainability 2021, 13, 6101. https://0-doi-org.brum.beds.ac.uk/10.3390/su13116101

AMA Style

Sharma R, Winker H, Levontin P, Kell L, Ovando D, Palomares MLD, Pinto C, Ye Y. Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs. Sustainability. 2021; 13(11):6101. https://0-doi-org.brum.beds.ac.uk/10.3390/su13116101

Chicago/Turabian Style

Sharma, Rishi, Henning Winker, Polina Levontin, Laurence Kell, Dan Ovando, Maria L.D. Palomares, Cecilia Pinto, and Yimin Ye. 2021. "Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs" Sustainability 13, no. 11: 6101. https://0-doi-org.brum.beds.ac.uk/10.3390/su13116101

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