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Activity Number: 165 - SPEED: Environmetrics: Spatio-Temporal and Other Models
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #330941 Presentation
Title: Nonstationarity in Spatiotemporal Fisheries Models
Author(s): John Best*
Companies: School of Aquatic and Fishery Sciences, University of Washington
Keywords: fisheries science; spatio-temporal model; stock assessment; nonstationarity

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.

Authors who are presenting talks have a * after their name.

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