Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography

Journal of Ornithology
By: , and 

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Abstract

Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.
Publication type Article
Publication Subtype Journal Article
Title Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography
Series title Journal of Ornithology
DOI 10.1007/s10336-011-0695-0
Volume 152
Issue Supplement 2
Year Published 2012
Language English
Publisher Springer
Publisher location Amsterdam, Netherlands
Contributing office(s) Patuxent Wildlife Research Center
Description 12 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Journal of Ornithology
First page 561
Last page 572
Country United States
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