Increasing populations of wild boar and feral domestic pigs Sus scrofa have evoked growing concern due to their potential as disease reservoir and as an origin of agricultural damages. Reliable population estimates are needed for effective management measures of this species. As an alternative to traditional methods, non‐invasive genetic population estimation approaches based on hair or faeces sampling have yielded promising results for several species in terms of feasibility and precision. We developed and applied a non‐invasive population estimation approach based on wild boar faeces in a study area situated in the Palatinate Forest, southwestern Germany. We collected 515 faeces samples along transects in January 2008. We carried out genotyping using six microsatellite markers to discriminate between individuals. During the trial, we identified 149 individual wild boar. Using multimodel inference and model averaging, we obtained relatively consistent estimates. Population densities calculated using the estimated population sizes ranged from 4.5 (2.9‐7.8) to 5.0 (4.0‐7.0) wild boar/km2. In the future, to further improve the precision of population estimates based on wild boar faeces, the detection probability should be increased. However, even when comparing a conservative population estimate to the hunting bag, our results show that the present hunting regime in our study area is not effective in regulating the wild boar population. The method which we present here offers a tool to calibrate hunting or other management measures for wild boar.

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.