A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals

Biometrics
By: , and 

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Abstract

Understanding drivers of temporal variation in demographic parameters is a central goal of mark‐recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space‐for‐time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time‐varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.
Publication type Article
Publication Subtype Journal Article
Title A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals
Series title Biometrics
DOI 10.1111/biom.13171
Volume 76
Issue 3
Year Published 2020
Language English
Publisher Wiley
Contributing office(s) Western Fisheries Research Center
Description 13 p.
First page 900
Last page 912
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