Details

Autor(en) / Beteiligte

• Halstead, B. J.
• Wylie, G. D.
• Coates, P. S.
• Valcarcel, P.
• Casazza, M. L.
• Altwegg, Res
• Schaub, Michael

Titel

Bayesian shared frailty models for regional inference about wildlife survival

Ist Teil von

• Animal conservation, 2012-04, Vol.15 (2), p.117-124

Ort / Verlag

London: Blackwell Publishing Ltd

Erscheinungsjahr

2012

Quelle

Wiley Online Library

Beschreibungen/Notizen

• Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology The estimation of survival is an essential but difficult task important for developing rigorous conservation programs. Radio telemetry studies of wildlife survival are often characterized by small sample sizes and high rates of censoring. In cases where multiple radio telemetry studies of a species exist, shared frailty models of survival offer the ability to combine data from multiple studies and improve the precision of survival estimates. We used Bayesian analysis of shared frailty models to examine survival of adult females of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California, USA, and to examine the effects of individual and habitat characteristics on daily risk of mortality. Posterior mean annual survival probability of adult females was 0.61 [95% credible interval (CI) = 0.41–0.79]. The daily risk of mortality for adult female giant gartersnakes while in terrestrial habitats was 0.38 (0.09–0.89) times as great as when they inhabited aquatic habitats. Although 95% CIs for hazard ratios of other covariates included one, sites varied substantially in the effect of linear habitats, which appear to have context‐dependent effects on survival. Assessing survival with shared frailty models allows the prediction of survival probabilities at novel sites and identifies regional and context‐specific mortality risks that can be targeted for conservation action.