Estimating abundance of the remnant Apennine brown bear (Ursus arctos marsicanus) population using multiple noninvasive genetic data sources

Accurate and precise estimates of population size are critical for effective management, but can be particularly difficult to achieve for small populations of large carnivores. We approached this challenge by integrating multiple noninvasive data sources into a DNA-based, mark–recapture framework to estimate the abundance of the small and endangered Apennine brown bear population. To improve sample size and coverage, we collected hair samples from June to September 2011 by concurrently using 4 noninvasive sampling methods: intensive hair-snagging (43 5x5 km cells and 5 12-day sampling sessions), plus secondary sampling methods (bear rub trees; alpine buckthorn aggregations; and incidental sampling). Following marker selection based on tissue samples from 55 Apennine bears, we used 13 microsatellites (plus gender) and quality assurance protocols to identify multilocus genotypes from hair samples. We used Huggins closed models in program MARK to estimate population size, which allowed us to account for spatial, temporal, and demographic components of heterogeneity in secondary sampling methods. Based on 529 analyzed hair samples, 80.5% of which yielded high-confidence scores for all markers, we achieved a rather precise (CV = 7.9%) population estimate of 51 bears (95% CI = 47–66) including cubs. Compared to a previous survey in 2008, our results provide evidence that the Apennine brown bear population has not been declining in recent years. Additionally, the relatively high (closure corrected) density (39.7 bears/1000 km2; 95%CI = 36.6–51.4) indicates that habitat productivity within the core range is currently adequate for bears, and that effective conservation of this small bear population should aim to the expand the bears' range across a larger scale throughout the central Apennines. We examined if a reduction in sampling effort would affect the precision of our population estimates. Reduced sample coverage, small sample size, and low hair-trap-capture probability preclude the adoption of a single sampling method or a subset of such to survey small bear populations if a comparable level of precision is required.