Wolverines (Gulo gulo) are one of the rarest carnivores in the contiguous United States. Effective population sizes in Montana, Idaho, and Wyoming, where most of the wolverines in the contiguous United States exist, were calculated to be 35 (credible limits, 28 52) suggesting low abundance. Landscape features that influence wolverine population substructure and gene flow are largely unknown. Recent work has identified strong associations between areas with persistent spring snow and wolverine presence and range. We tested whether a dispersal model in which wolverines prefer to disperse through areas characterized by persistent spring snow cover produced least-cost paths among all individuals that correlated with genetic distance among individuals. Models simulating large preferences for dispersing within areas characterized by persistent spring snow explained the data better than a model based on Euclidean distance. Partial Mantel tests separating Euclidean distance from spring snow-cover-based effects indicated that Euclidean distance was not significant in describing patterns of genetic distance. Because these models indicated that successful dispersal paths followed areas characterized by spring snow cover, we used these understandings to derive empirically based least-cost corridor maps in the U.S. Rocky Mountains. These corridor maps largely explain previously published population subdivision patterns based on mitochondrial DNA and indicate that natural colonization of the southern Rocky Mountains by wolverines will be difficult but not impossible.

We developed two tests for sex identification of felids using y‐chromosome deletions in the zinc‐finger and amelogenin regions. These tests provide positive results for both males and females, while reducing the need to co‐amplify microsatellites to test for DNA quality in hair and scat samples. Furthermore, the y‐chromosome deletions are absent in a wide‐range of prey species; thus, when these tests are used on scat samples, potential contamination caused by prey DNA incidentally extracted, is minimized.

Summary 1.Reliable estimates of population parameters are often necessary for conservation management but these are hard to obtain for elusive, rare and wide-ranging species such as wolves Canis lupus. This species has naturally recolonized parts of its former habitat in Western Europe; however, an accurate and cost-effective method to assess population trend and survival has not been implemented yet. 2.We used open-model capture-recapture (CR) sampling with non-invasive individual identifications derived from faecal genotyping to estimate survival and trend in abundance for wolves in the Western Alps between 1999 and 2006. Our sampling strategy reduced individual heterogeneity in recaptures, thus minimizing bias and increasing the precision of the estimates. 3. Young wolves had lower apparent annual survival rates (0AE24 ± 0AE06) than adult wolves (0AE82 ± 0AE04); survival rates were lower in the summer than in the winter for both young and adults. The wolf population in the study area increased from 21 ± 9AE6 wolves in 1999 to 47 ± 11AE2 wolves in late winter 2005; the population growth rate (k = 1AE04 ± 0AE27) was lower than that recorded for other recolonizing wolf populations. 4. We found a positive trend in wolf abundance, regardless of the method used. However, the abundance estimate based on snow-tracking was on average 36AE2% (SD = 13AE6%) lower than that from CR modelling, because young dispersing wolves are likely to have lower sign detection rates in snow-track surveys, a problem adequately addressed by CR sampling. 5. Synthesis and applications. We successfully implemented a new method to assess large carnivore population trend and survival at large spatial scales. These are the first such estimates for wolves in Italy and in the Alps and have important management implications. Our approach can be widely applied to broader spatial and temporal scales for other elusive and wide-ranging species in Europe and elsewhere.