Catch per unit effort modelling for stock assessment: A summary of good practices

被引:33
|
作者
Hoyle, Simon D. [1 ,2 ,3 ]
Campbell, Robert A. [4 ]
Ducharme-Barth, Nicholas D. [5 ]
Gruss, Arnaud [6 ]
Moore, Bradley R. [1 ]
Thorson, James T. [7 ]
Tremblay-Boyer, Laura [8 ]
Winker, Henning [9 ]
Zhou, Shijie [10 ]
Maunder, Mark N. [11 ,12 ]
机构
[1] Natl Inst Water & Atmospher Res Ltd NIWA, 217 Akersten St, Port Nelson 7010, Nelson, New Zealand
[2] Indian Ocean Tuna Commiss, POB 1011, Victoria, Seychelles
[3] Univ Auckland, Dept Stat, Private Bag 92019, Auckland, New Zealand
[4] CSIRO Environm, Private Bag 1, Aspendale, Vic 3195, Australia
[5] NOAA, Natl Marine Fisheries Serv, Pacific Isl Fishery Sci Ctr, 1845 Wasp Blvd,Bldg 176, Honolulu, HI 96818 USA
[6] Natl Inst Water & Atmospher Res Ltd NIWA, 301 Evans Bay Parade, Wellington 6021, New Zealand
[7] NOAA, Habitat & Ecol Proc Res Program, Alaska Fisheries Sci Ctr, Natl Marine Fisheries Serv, 7600 Sand Point Way NE, Seattle, WA 98115 USA
[8] CSIRO Environm, GPO Box 1538, Hobart, Tas 7001, Australia
[9] Swedish Univ Agr Sci, Inst Marine Res, Dept Aquat Resources, Uppsala, Sweden
[10] CSIRO Environm, 306 Carmody Rd, Brisbane, Qld 4067, Australia
[11] Interamer Trop Tuna Commiss, 8901 La Jolla Shores Dr, La Jolla, CA 92037 USA
[12] Scripps Inst Oceanog, Ctr Advancement Populat Assessment Methodol, La Jolla, CA USA
关键词
Catch-per-unit-effort (CPUE) standardization; Indices of relative abundance; Good practices; Data preparation; Modelling methods; Stock assessments; SPATIOTEMPORAL DYNAMICS; CPUE STANDARDIZATION; LONGLINE FISHERY; COMMERCIAL CATCH; POPULATION ASSESSMENT; ABUNDANCE INDEXES; ADDITIVE-MODELS; FISHING TACTICS; FLEET DYNAMICS; EFFORT SERIES;
D O I
10.1016/j.fishres.2023.106860
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
Indices of abundance based on fishery catch-per-unit-effort (CPUE) are important components of many stock assessments, particularly when fishery-independent surveys are unavailable. Standardizing CPUE to develop indices that better reflect the relative abundance requires the analyst to make numerous decisions, which are influenced by factors that include the biology of the study species, the structure of the fishery of interest, the nature of the available data, and the objectives of the analysis such as how standardized data will be used in a subsequent assessment model. Alternative choices can substantially change the index, and hence stock assessment outcomes and management decisions. To guide decisions, we provide advice on good practices in 16 areas, focusing on decision points: fishery definitions, exploring and preparing data, misreporting, data aggregation, density and catchability covariates, environmental variables, combining CPUE and survey data, analysis tools, spatial considerations, setting up and predicting from the model, uncertainty estimation, error distributions, model diagnostics, model selection, multispecies targeting, and using CPUE in stock assessments. Often the most influential outcome of exploring and analysing catch and effort data is that analysts better understand the population and the fishery, thereby improving the stock assessment.
引用
收藏
页数:22
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