1. Non-invasive genetic sampling (NGS) of hair and faeces has become an important tool for monitoring wildlife populations, but many managers question the feasibility and cost-effectiveness of these methods for long-term monitoring. To address this question, more studies are needed that simultaneously evaluate the effectiveness and efficiency of multiple NGS designs in the same study area.
2. In 2003–2004, we carried out an experimental study of NGS for a small brown bear Ursus arctos population established by translocation in the Italian Alps. We evaluated and compared the effectiveness and efficiency of three NGS approaches including two systematic designs, baited hair traps and transect sampling of hair and faeces, and opportunistic collection of faecal and hair samples. Effectiveness was evaluated in terms of the number of samples collected, bears identified, genotyping success and error rate, detection frequencies, individual movement and spatial distribution of the species. We also evaluated the suitability of the data collected for population size estimation using single- and multi-session approaches. Efficiency was assessed by calculating total cost/genotyped sample, cost/unique bear identified and cost/bear sample.
3. During 2 years of sampling, 1164 samples and 15 unique genotypes were obtained. From these genotypes, we documented reproduction, an increase in the minimum population size of bears in the study area and important information on specific bears causing damages to property.
4. The optimal sampling strategy combined systematic hair trapping and opportunistic sampling, as the pooled data set efficiently provided large sample quantities, the highest number of identified bears, multiple individual detections, information on bear distribution and suitable data for population size estimation.
5. We provide an example of how the efficiency of NGS monitoring can be improved by integrating sampling into routine duties of existing field personnel.
6.Synthesis and applications. This study provides baseline data for monitoring brown bears in the Italian Alps and has important implications for NGS of other small populations in human-dominated landscapes. Conservation of small populations in such habitats will benefit from multiple strategies that obtain critical demographic, spatial and genetic information in a cost-effective manner.