Activity Number:
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259
- SPEED: Environmetrics: Spatio-Temporal and Other Models
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2018 : 3:05 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #333037
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Title:
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Nonstationarity in Spatiotemporal Fisheries Models
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Author(s):
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John Best*
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Companies:
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School of Aquatic and Fishery Sciences, University of Washington
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Keywords:
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fisheries science;
spatio-temporal model;
stock assessment;
nonstationarity
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Abstract:
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Many fish species occur in areas with complicated geography. Natural barriers such as islands and coastlines mean that the spatial structure of the population is unlikely to be stationary. Here I develop and fit a spatiotemporal model that accounts for nonstationarity. The stochastic partial differential equation approach is used to reduce the computational burden. A simulation study demonstrates improved abundance estimates. This improvement has the potential to improve management decisions by more accurately reflecting a stock's spatial structure. It should also provide more trustworthy estimates of uncertainty. These combined have the potential to improve management decision in many fisheries.
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Authors who are presenting talks have a * after their name.