Blood from a stone: Performance of catch-only methods in estimating stock biomass status

被引:64
作者
Free, Christopher M. [1 ,2 ]
Jensen, Olaf P. [1 ]
Anderson, Sean C. [3 ]
Gutierrez, Nicolas L. [4 ]
Kleisner, Kristin M. [5 ]
Longo, Catherine [6 ]
Minto, Coilin [7 ]
Osio, Giacomo Chato [8 ]
Walsh, Jessica C. [9 ,10 ]
机构
[1] Rutgers State Univ, Dept Marine & Coastal Sci, New Brunswick, NJ USA
[2] Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, 2400 Bren Hall, Santa Barbara, CA 93106 USA
[3] Fisheries & Oceans Canada, Pacific Biol Stn, Nanaimo, BC, Canada
[4] Food & Agr Org, Fisheries & Aquaculture Dept, Rome, Italy
[5] Environm Def Fund, Boston, MA USA
[6] Marine Stewardship Council, London, England
[7] Galway Mayo Inst Technol, Marine & Freshwater Res Ctr, Galway, Ireland
[8] Directorate D Sustainable Resources, DG Joint Res Ctr, European Commiss, Ispra, VA, Italy
[9] Monash Univ, Sch Biol Sci, Clayton, Vic, Australia
[10] Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC, Canada
关键词
Stock assessment; Stock status; Data-limited fisheries; Data-poor fisheries; Catch-only methods; Ensemble methods; MARINE FISHERY STATUS; GLOBAL FISHERIES; HARVEST STRATEGIES; REDUCTION ANALYSIS; EVALUATING METHODS; MANAGEMENT; LIMITS; AGREEMENT; FRAMEWORK; PATTERNS;
D O I
10.1016/j.fishres.2019.105452
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
Demand for data-limited stock assessment methods is increasing, and new methods are being developed rapidly. One class of these methods requires only catch time series and, in some cases, information about life history or fishery characteristics, to estimate stock status. These catch-only methods (COMs) range from statistical models trained on data-rich stocks to mechanistic population models that make assumptions about changes in fishing effort. We review 11 COMs, comparing performance through application to data-rich stocks and simulated fisheries. The catch-only methods evaluated here produce imprecise and biased estimates of B/B-msy, especially for stocks that are lightly exploited. They were also generally poor classifiers of stock status. While no method performed best across all stocks, ensembles of multiple COMs generally performed better than individual COMs. We advocate for testing new COMs using this common platform. We also caution that performance in estimating stock status is not sufficient for gauging the usefulness of COMs in managing fisheries. Greater use of management strategy evaluation is needed before COMs can be considered a reliable tool for management.
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页数:10
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