Planning for wolf-livestock coexistence: landscape context predicts livestock depredation risk in agricultural landscapes.

Extensive pastoral livestock systems in Central Europe provide multiple ecosystem services and support biodiversity in agricultural landscapes but their viability is challenged by livestock depredation (LD) associated with the recovery of wolf populations. Variation in the spatial distribution of LD depends on a suite of factors, most of which are unavailable at the appropriate scales. To assess if LD patterns can be predicted sufficiently with land use data alone at the scale of one federal state in Germany, we employed a machine-learning-supported resource selection approach. The model used LD monitoring data, and publicly available land use data to describe the landscape configuration at LD and control sites (resolution 4 km * 4 km). We used SHapley Additive exPlanations to assess the importance and effects of landscape configuration and cross-validation to evaluate the model performance. Our model predicted the spatial distribution of LD events with a mean accuracy of 74%. The most influential land use features included grassland, farmland and forest. The risk of livestock depredation was high if these three landscape features co-occurred with a specific proportion. A high share of grassland, combined with a moderate proportion of forest and farmland, increased LD risk. We then used the model to predict the LD risk in five regions; the resulting risk maps showed high congruence with observed LD events. While of correlative nature and lacking specific information on wolf and livestock distribution and husbandry practices, our pragmatic modelling approach can guide spatial prioritisation of damage prevention or mitigation practices to improve livestock-wolf coexistence in agricultural landscapes.

How the west was won: genetic reconstruction of rapid wolf recolonization into Germany's anthropogenic landscapes.

Following massive persecution and eradication, strict legal protection facilitated a successful reestablishment of wolf packs in Germany, which has been ongoing since 2000. Here, we describe this recolonization process by mitochondrial DNA control-region sequencing, microsatellite genotyping and sex identification based on 1341 mostly non-invasively collected samples. We reconstructed the genealogy of German wolf packs between 2005 and 2015 to provide information on trends in genetic diversity, dispersal patterns and pack dynamics during the early expansion process. Our results indicate signs of a founder effect at the start of the recolonization. Genetic diversity in German wolves is moderate compared to other European wolf populations. Although dispersal among packs is male-biased in the sense that females are more philopatric, dispersal distances are similar between males and females once only dispersers are accounted for. Breeding with close relatives is regular and none of the six male wolves originating from the Italian/Alpine population reproduced. However, moderate genetic diversity and inbreeding levels of the recolonizing population are preserved by high sociality, dispersal among packs and several immigration events. Our results demonstrate an ongoing, rapid and natural wolf population expansion in an intensively used cultural landscape in Central Europe.

Population expansion and individual age affect endoparasite richness and diversity in a recolonising large carnivore population.

The recent recolonisation of the Central European lowland (CEL) by the grey wolf (Canis lupus) provides an excellent opportunity to study the effect of founder events on endoparasite diversity. Which role do prey and predator populations play in the re-establishment of endoparasite life cycles? Which intrinsic and extrinsic factors control individual endoparasite diversity in an expanding host population? In 53 individually known CEL wolves sampled in Germany, we revealed a community of four cestode, eight nematode, one trematode and 12 potential Sarcocystis species through molecular genetic techniques. Infections with zoonotic Echinococcus multilocularis, Trichinella britovi and T. spiralis occurred as single cases. Per capita endoparasite species richness and diversity significantly increased with population size and changed with age, whereas sex, microsatellite heterozygosity, and geographic origin had no effect. Tapeworm abundance (Taenia spp.) was significantly higher in immigrants than natives. Metacestode prevalence was slightly higher in ungulates from wolf territories than from control areas elsewhere. Even though alternative canid definitive hosts might also play a role within the investigated parasite life cycles, our findings indicate that (1) immigrated wolves increase parasite diversity in German packs, and (2) prevalence of wolf-associated parasites had declined during wolf absence and has now risen during recolonisation.

A single-nucleotide polymorphism-based approach for rapid and cost-effective genetic wolf monitoring in Europe based on noninvasively collected samples.

Noninvasive genetics based on microsatellite markers has become an indispensable tool for wildlife monitoring and conservation research over the past decades. However, microsatellites have several drawbacks, such as the lack of standardisation between laboratories and high error rates. Here, we propose an alternative single-nucleotide polymorphism (SNP)-based marker system for noninvasively collected samples, which promises to solve these problems. Using nanofluidic SNP genotyping technology (Fluidigm), we genotyped 158 wolf samples (tissue, scats, hairs, urine) for 192 SNP loci selected from the Affymetrix v2 Canine SNP Array. We carefully selected an optimised final set of 96 SNPs (and discarded the worse half), based on assay performance and reliability. We found rates of missing data in this SNP set of <10% and genotyping error of ~1%, which improves genotyping accuracy by nearly an order of magnitude when compared to published data for other marker types. Our approach provides a tool for rapid and cost-effective genotyping of noninvasively collected wildlife samples. The ability to standardise genotype scoring combined with low error rates promises to constitute a major technological advancement and could establish SNPs as a standard marker for future wildlife monitoring.