Comparing survival among species with imperfect detection using multilevel analysis of mark—recapture data: a case study on bats

Abstract

For comparative demography studies, 2 prerequisites are usually needed: 1) using typical parameter values for species, 2) correctly accounting for the uncertainty in the species specific estimates. However, although within‐species variability may be essential, it is typically not considered in analytical procedures, resulting in parameter estimates that may not be representative of the species. Further, data are analysed in 2 steps, first separately for each species, then estimates are compared among species. Accounting for the uncertainty in the species specific estimates is then difficult. Here we propose the application of multilevel Bayesian models on mark—recapture (MR) data for comparative studies on survival probabilities that solves these problems. Our models account for within‐species variability in space and time in the form of random effects. Models reflecting different biological predictions related to the species’ ecology and life‐history traits may further be contrasted. To illustrate our approach, we used long‐term data from 5 temperate tree‐roosting bat species and compared their survival probabilities. Results suggest that species foraging in open space, high reproductive output and short longevity records have lower survival than species foraging at short distances, with low reproductive output and high longevity records. Multilevel models provided relatively precise estimates, away from the edges of the parameter space, even for species with low encounter rates and short study duration. This is particularly valuable for less studied taxa such as bats for which available data are often more sparse. Our approach can be easily extended to include additional groups or levels of interest and effects at the individual level (e.g. sex or age). Different hypotheses regarding differences or similarities in parameters among species can be tested through the application of different models. Overall, it offers a flexible tool to ecologists, and population and evolutionary biologists for comparative studies, explicitly accounting for multilevel structures often encountered in MR data.

Estimating Survival for Elusive Juvenile Pond‐Breeding Salamanders

“…), particularly if the juvenile stage lasts for multiple years (Table S2). Thus, our study reinforces the need for large individual ( n = 174) and temporal ( n > 21) sample sizes when empirically estimating survival probabilities for cryptic species and life stages using the capture‐mark‐recapture methodology (Papadatou et al ).…”

Integrating growth and capture–mark–recapture models reveals size‐dependent survival in an elusive species

“…Giant gartersnake growth is also positively related to precipitation (Rose et al 2018b). Our analysis of environmental covariate effects on survival was centered on a period of extreme drought (2012Robeson 2015). The annual survival of giant gartersnakes is thus most influenced by the amount of precipitation that falls from 1 October through 30 April.…”

“…Low capture probabilities lead to high uncertainty in estimates of survival (Pike et al 2008, Papadatou et al 2012. Low capture probabilities lead to high uncertainty in estimates of survival (Pike et al 2008, Papadatou et al 2012.…”

“…Hierarchical capture-mark-recapture (CMR) models that share information about the capture and survival process among populations and years can improve precision of parameter estimates while simultaneously obtaining site-and year-specific estimates (K ery and Schaub 2012, Papadatou et al 2012). For example, if a species is sampled using the same methods year after year at several sites, we might expect the capture process to be similar among sites and over time.…”

Age effects on survival of Amazon forest birds and the latitudinal gradient in bird survival

“…To simultaneously model age-specific survival for all species, we adopted a multispecies CJS model (LahozMonfort et al 2011, Papadatou et al 2012, Lloyd et al 2014. This is a hierarchical extension to the classical CJS model with age-specific survival for a single species, described above.…”