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Activity Number: 259 - SPEED: Environmetrics: Spatio-Temporal and Other Models
Type: Contributed
Date/Time: Monday, July 30, 2018 : 3:05 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #333037
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
Abstract:

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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