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Spatio-temporal analysis of compositional data: increased precision and improved workflow using model-based inputs to stock assessment
Thorson, J.T.; Haltuch, M.A. (2019). Spatio-temporal analysis of compositional data: increased precision and improved workflow using model-based inputs to stock assessment. Can. J. Fish. Aquat. Sci. 76(3): 401-414. https://dx.doi.org/10.1139/cjfas-2018-0015
In: Canadian Journal of Fisheries and Aquatic Sciences = Journal canadien des sciences halieutiques et aquatiques. National Research Council Canada: Ottawa. ISSN 0706-652X; e-ISSN 1205-7533
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| Trefwoorden |
Population characteristics > Population structure > Age composition
Marien/Kust |
| Author keywords |
delta-generalized linear model; spatio-temporal model; length composion |
| Auteurs | | Top |
- Thorson, J.T.
- Haltuch, M.A.
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| Abstract |
Stock assessment models are fitted to abundance-index, fishery catch, and age/length/sex composition data that are estimated from survey and fishery records. Research has developed spatio-temporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age/length/sex composition data. We demonstrate a spatio-temporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatio-temporal and design-based methods demonstrates a 32% increase in input sample size for the spatio-temporal estimator. A Stock Synthesis assessment used to manage lingcod in the California Current also shows a 17% increase in sample size and better model fit using the spatio-temporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatio-temporal approaches are feasible for estimating both abundance-index and compositional data, thereby providing a unified approach for generating inputs for stock assessments. We hypothesize that spatio-temporal methods will improve statistical efficiency for composition data in many stock assessments, and recommend that future research explore the impact of including additional habitat or sampling covariates. |
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