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

摘要

Survival probability is a key parameter whose variation may have a substantial in?uence on the population asymptotic and realized growth rate (Caswell, 2001; Nichols & Hines, 2002). Estimation of survival in wild vertebrate populations has long been a challenge and has stimulated collaborations between biologists and statisticians (Williams, Nichols & Conroy, 2002), mostly because of dif?- culties in correcting observed proportions of survivors when not all the individuals alive and present in the study area are detected by investigators (i.e. detection probability is <1; Williams et al., 2002). Halstead et al. (2011) have estimated daily mortality risk in the giant gartersnake (Thamnophis gigas) and addressed spatial variation in survival. In Halstead et al., the dif?culty was not detection probability: individuals were equipped with radio transmitters and detection probability approaches 1 in many telemetry studies (Williams et al., 2002). Halstead et al. used a standard approach in human demography based on hazard models (Hosmer, Lemeshow & May, 2011), where the hazard function accounts for the instantaneous rate of occurrence of the death event. They used a Bayesian approach to estimate a mixed version of their model; that is, a model with ?xed (e.g. habitat type) and random effects (year, site).