Some deer species are of conservation concern; others are officially managed as a food source or for their trophies, whereas in many regions, deer are regarded as overabundant or even as a nuisance causing damages. Regardless of local management issues, in most cases, reliable data on deer population sizes and sex ratios are lacking. Non-invasive genetic approaches are promising tools for the estimation of population size and structure. We developed and tested a non-invasive genetic approach for red deer (Cervus elaphus) population size and density estimation based on faeces collected from three free-ranging red deer populations in south-western Germany. Altogether, we genotyped 2762 faecal samples, representing 1431 different individuals. We estimated population density for both sexes separately using two different approaches: spatially explicit capture-recapture (SECR) approach and a single-session urn model (CAPWIRE). The estimated densities of both approaches were similar for all three study areas, ranging between total densities of 3.3 (2.5–4.4) and 8.5 (6.4–11.3) red deer/km2. The estimated sex ratios differed significantly between the studied populations (ranging between 1:1.1 and 1:1.7), resulting in considerable consequences for management. In further research, the issues of population closure and approximation of the effectively sampled area for density estimation should be addressed. The presented approach can serve as a valuable tool for the management of deer populations, and to our knowledge, it represents the only sex-specific approach for estimation of red deer population size and density.
Estimating population size is particularly difficult for animal species living in concealing habitats with dense vegetation. This is the case for roe deer as for many other ungulates. Our objective was to develop a non–invasive genetic capture–mark–recapture approach based on roe deer faeces collected along transects. In a pilot study, we collected 1,790 roe deer faeces during five sampling days in a forested study area in south western Germany. We extracted DNA from 410 of these samples and carried out microsatellite analysis using seven dinucleotide markers. The analyses resulted in 328 useable consensus genotypes which were assigned to 174 individuals. The population size estimated using a Bayesian approach was 94 (82–111) male and 136 (121–156) female roe deer. Our study shows that non–invasive genetic methods are a valuable management tool for roe deer.
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