Estimating recruitment from capture–recapture data by modelling spatio‐temporal variation in birth and age‐specific survival rates

Abstract

Understanding the factors influencing recruitment in animal populations is an important objective of many research and conservation programmes. However, evaluating hypotheses is challenging because recruitment is the outcome of birth and survival processes that are difficult to directly observe. Capture–recapture is the most general framework for estimating recruitment in the presence of observation error, but existing methods ignore the underlying birth and survival processes, as well as age effects and spatial variation in vital rates. We present an individual‐based, spatio‐temporal model that can be fit to capture–recapture data to draw inferences on the birth and survival processes governing recruitment dynamics. The number, dates, and spatial distribution of births are modelled as outcomes of a point process, and survival is modelled using a failure time approach. Survival parameters can be modelled as functions of individuals traits and time‐varying, spatial covariates. Continuous‐ and discrete‐time formulations are possible. We demonstrate the model using 7 months of camera data collected on white‐tailed deer Odocoileus virginianus fawns in Big Cypress National Preserve. Spot patterns were used to individually identify 28 fawns, detected 1,454 times between December 1, 2015 and July 1, 2016. A total of 37 (95% CI: 30–49) fawns were born, of which 16 (95% CI: 10–23) survived 180 days to the recruitment age. Mean parturition date was February 14 (95% CI: February 6–February 22), much earlier than in more temperate parts of the species’ range, but coinciding with the dry season in southern Florida. We found little evidence that mortality rates decreased with age, but the estimate of the age effect was imprecise. In contrast, we found strong evidence that encounter rates were age‐specific and increased rapidly over the first month of life as fawns became more mobile. Our case study demonstrates the potential of this new model for advancing knowledge of spatial population dynamics by providing insights into the birth and juvenile survival processes that influence recruitment. Because the model can be applied to data from noninvasive survey methods such as camera trapping, it is possible to apply it at broad spatial scales to understand how environmental variables and predator communities influence recruitment.

Chronology of reproductive investment determines predation risk aversion in a felid‐ungulate system

“…Because deer activity is closely linked to reproductive stage, we organized our study in the context of biological seasons of deer in the BCB (Richter & Labisky, ). Camera trap data indicated a broad window of fawning across most of February and March (Chandler et al, ); thus, we designated these months as the fawning season. This timescale (February–March) was chosen to appropriately characterize behaviors leading up to fawning, such as fawning site selection, while including the time period over which the majority of fawns were born.…”

Does the punishment fit the crime? Consequences and diagnosis of misspecified detection functions in Bayesian spatial capture-recapture modelling

“…Although initially developed with the intent to provide spatially referenced estimates of population size (Efford, 2004; Efford et al, 2004; Borchers and Efford, 2008), SCR is increasingly being used for estimating parameters that inform about other ecological aspects (Chandler and Clark, 2014; Bischof et al, 2016; Muneza et al, 2017; Ergon and Gardner, 2014; Chandler et al, 2018). SCR holds particular promise for addressing spatial ecological questions at the population level (Morin et al, 2017; Bischof et al, 2017).…”

Fawn Counts and Adult Female Site Use Are Mismatched Indicators of Habitat Quality in an Endangered Deer

“…While adult male white-tailed deer are uniquely identifiable for a portion of the year based on antler characteristics [5,16]; adult females are less reliably identifiable. However, fawns are born with spot patterns that can be used to uniquely identify individuals with camera traps [17]. Therefore, we predicted that using uniquely identified individual fawns from camera trap surveys could provide robust insights about important habitat requirements for population recruitment beyond using counts of adult deer for inferences.…”