Noninvasive genetic sampling for flying foxes: a valuable method for monitoring demographic parameters

Abstract

AbstractEstablishing effective wildlife conservation measures requires accurate demographic information such as population size and survival probability: parameters that can be extremely difficult to obtain. This is especially the case for threatened species, which are often rare and sometimes occupy inaccessible areas. While noninvasive genetic sampling (NIGS) techniques are promising tools for providing demographic data, these methods may be unreliable in certain situations. For instance, fecal samples of frugivorous species in tropical areas degrade rapidly, affecting the usability of the genetic material. In this study, we compared (1) NIGS capture–mark–recapture (NIGS‐CMR) with conventional CMR to determine their potential in estimating demographic parameters of fruit bats, and (2) the precision of these demographic parameters and the associated costs given varying sampling designs through simulations. Using Livingstone’s fruit bats (Pteropus livingstonii) fecal samples, microsatellite markers were tested and genotyping success and error rates were assessed. The average genotyping success rate was 77%, and the total genotyping error rate for all loci was low (allelic dropout rate = 0.089, false alleles rate = 0.018). Our results suggested that five loci were required to identify individuals. Simulations showed that monitoring the species over a 9‐yr period with a recapture rate of 0.20 or over a 6‐yr period with a recapture rate of 0.30 seems appropriate to obtain valuable demographic parameters. Overall, in comparison to conventional CMR, NIGS‐CMR offers a better method for estimating demographic parameters and subsequently for conducting long‐term population monitoring in flying foxes due to the fact that (1) sample collection is easy and the level of genotyping errors in the laboratory is low and (2) it is cheaper, less time‐consuming, and less disturbing to individual animals. We strongly advocate an approach that couples a pilot study with simulations as done in this study in order to choose the most efficient monitoring method for a given species or context.