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Introgression resulting from anthropogenic hybridization may shape phenotypic traits in wild taxa, potentially altering species' ecology and human‐wildlife interactions. This is particularly relevant in large carnivores such as gray wolves (Canis lupus ) that are expanding into human‐dominated landscapes. A notable example is the Italian wolf (C. l. italicus), which, after recovering from near extinction, now faces locally high levels of hybridization with the domestic dog (C. l. familiaris). Although wolf‐dog hybridization is known to affect morphology, its effect on other phenotypic traits remains poorly investigated. We analyzed worldwide‐distributed wolf and dog whole‐genome data to assess the extent and timing of dog ancestry in a sample of 17 Italian wolves, and to explore dog introgression at behavior‐related genes. Five Italian wolves, exhibiting varying levels of genome‐wide dog ancestry (1%–20%), were estimated to result from admixture events that occurred at least 3–7 generations before sampling (2005–2012). No overrepresentation of recent dog introgressions in behavior‐related genes of admixed Italian wolves was detected. However, we identified signals of historical dog introgressions under putative selection, involving genes linked to neuronal plasticity, photoreceptor development, and immune responses. One of such introgressions likely occurred ~4500 years ago during the Bronze Age and the other one ~1000 years ago during the Middle Ages, suggesting that historical admixture might have shaped the Italian wolf evolutionary trajectories. Although preliminary and warranting further analyzes, our results highlight the potential for phenotypic effects of wolf‐dog hybridization to persist across generations, showing that even limited non‐native ancestry can leave significant genomic footprints in wild populations. We analyzed whole‐genome data from Italian wolves and dogs to assess the extent, timing, and functional relevance of dog introgression in the Italian wolf. Five wolves showed recent admixture within the last 3–7 generations, while historical introgressions under selection dated to the Bronze and Middle Ages involved genes linked to neuronal plasticity, vision, and immune response. These findings suggest that even limited dog ancestry may leave lasting genomic and phenotypic imprints on wild wolf populations.

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 (forty-three 5×5-km cells and five 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/1,000 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 expand the bears' range across a larger portion of 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.

Apennine brown bears are a very small, isolated population of central Italy, consisting of about 50 individuals and under a severe risk of extinction. We performed a population viability analysis (PVA) for this population, contrasting a deterministic model and an individual-based stochastic model, using a set of demographic parameters estimated for the same population during the last decade. We also built a set of simulated management scenarios, in which we compared the effectiveness of alternative conservation measures and assessed the susceptibility of the population to catastrophic mortality events. The deterministic model produced an estimate of the asymptotic population growth rate r = 0.001, corresponding to an asymptotically stable population. The stochastic model produced an estimate of r = − 0.013 (standard deviation = 0.103), corresponding to an annual population decrease of 1.3%, a 17% extinction risk in 100 years, an average population of 27 bears for non-extinct populations, and an average time to extinction of 81 years for those gone extinct. Extinction probability increased to more alarming levels (> 0.4) when at least one catastrophic event occurred during a 100-year period. Current vital rates of the population are not compatible with a more than negligible numerical increase, and this bear population is likely to remain small and exposed to a relatively high risk of extinction, if the average survival or reproductive rates do not increase. Management efforts aimed to increase food availability generated minimal to moderate variations in population growth rate and in the associated risk of extinction, whereas interventions meant to reduce adult female mortality were highly effective in increasing persistence probability. We propose that the general objectives of the action plan for the conservation of the Apennine brown bear for the incoming decade should explicitly contemplate quantitative demographic goals, focusing in particular on adult female and cub mortality.

The value of ants to bears is a topic of substantial relevance for the small and highly endangered population of Apennine brown bears (Ursus arctos marsicanus) in central Italy. Following a previous food-habit study (2006-2009) based on scat analysis, we used the same data set to further investigate patterns of ant consumption by Apennine bears at a greater taxonomic and temporal resolution. We observed a great diversity of ant species in bear scats, comprising 15 genera and > 42 species. Bears most frequently consumed ants living in open grassland and forest edges, belonging to five genera: Formica, Lasius, Tetramorium, Camponotus and Myrmica. Specifically, yellow Lasius spp., Serviformica spp., Lasius s. str. spp., and Tetramorium spp. were most represented in the bear diet, followed by Formica pratensis, Camponotus spp., Myrmica spp. and Formica sanguinea. Yellow Lasius spp. yielded the highest number of individuals per bear scat, outnumbering any other ant taxon. During the years of our study, ant consumption by bears peaked between June and July and corresponded to a higher occurrence of brood in the scats. Our results are useful to inform habitat management, especially in light of expected natural and anthropogenic changes. However, further investigation is necessary to unveil behavioural and ecological correlates of myrmecophagy in Apennine brown bears.

The Apennine brown bear (Ursus arctos marsicanus) survives today in a relict population of about 50 bears in the central Apennines, even though they have been long protected and habitat suitability at the landscape scale does not appear to be a limiting factor for population recovery. Multiple uses within the bear range may increase disturbance and chances of human-caused mortality, including wild boar hunting drives with dogs conducted in the fall and coinciding with hyperphagia in bears. Although wild boar hunting drives represent a very popular recreational activity throughout the central Apennines, this is a very invasive practice and is thought to exert both direct and indirect detrimental effects on bears. In order to foster the progressive abandonment of wild boar hunting drives in the bear range in favor of less impacting hunting methods, we developed a species distribution model (SDM) to identify areas of likely bear presence during hyperphagia. This SDM could represent the basis to develop a hunting zoning system useful to modulate wild boar hunting regimes according to the bear occurrence. Starting from a large dataset of bear occurrences collected from September to November (2005–2010) within the core distribution range of the bear (n = 5746 GPS- and VHF-telemetry locations on 25 adult and subadult bears, plus other signs of bear presence), we modeled the distribution of bears during hyperphagia and selected candidate models using second order corrected Akaike information criteria (AIC c). The final model included 16 environmental, topographic, and anthropogenic variables and was evaluated using the continuous Boyce index (0.91). By intersecting the bear occurrence model with a proxy of wild boar hunting intensity, we identified the areas where the banning of wild boar hunting drives represents a priority, and where less impacting hunting regimes are urgently needed. By discussing how such a model can be used to facilitate consensus toward alternative hunting management scenarios, we believe our approach can be extended to other small populations of bears, and of other species as well, that live in multiple-use landscapes and are in need of recovery.

Cimatti, M., Ranc, N., Benítez-López, A., Maiorano, L., Boitani, L., Cagnacci, F., Čengić, M., Ciucci, P., Huijbregts, M.A.J., Krofel, M., López-Bao, J.V., Selva, N., Andren, H., Bautista, C., Ćirović, D., Hemmingmoore, H., Reinhardt, I., Marenče, M., Mertzanis, Y., Pedrotti, L., Trbojević, I., Zetterberg, A., Zwijacz-Kozica, T., Santini, L.

It is often difficult to determine optimal sampling design for non-invasive genetic sampling, especially when dealing with rare or elusive species depleted of genetic diversity. To address this problem, we ran a hair-snag pilot study on the remnant Apennine brown bear population. We used occupancy models to estimate the performance of an improved field protocol, a meta-analysis approach to indirectly model capture probability, and simulations to evaluate the effect of genotyping errors on the accuracy of capture-recapture population estimates. In spring 2007 we collected 70 bear hair samples in 15 5 × 5 km cells, using 5 10-day trapping sessions. Bear detectability was higher in 2007 than in a previous attempt on the same population in 2004, reflecting improved field protocols and sampling design. However, individual capture probability was 0.136 (95% CI = 0.120–0.152), still below the minimum requirements of capture-mark-recapture closed population models. We genotyped hair samples ( n  = 63) at 9 microsatellite loci, obtaining 94% Polymerase Chain Reaction success, and 13 bear genotypes. Estimated P IDsib was 0.00594, and per-genotype error rate was 0.13, corresponding to a 99% probability of correct individual identification. Simulation studies showed that the effect of non-corrected or filtered genetic errors on the accuracy of population estimates was negligible only when individual capture probability was >0.2. Our results underline how the interaction among field protocols, sampling strategies and genotyping errors may affect the accuracy of DNA-based estimates of small and genetically depleted populations, and warned us about the feasibility of a survey using only traditional hair-snag sampling. In this and similar cases, indications from pilot studies can provide cost-effective means to evaluate the efficiency of designed sampling and modelling procedures.

We investigated wolf (Canis lupus)- and dog-livestock conflicts (1992-1995) and costs of compensation (1991-1995) in the Tuscany region of central Italy. The regional indemnity program cost US $345,000 (± 93,000 SD) annually. Most depredations (95.2%) involved sheep, with a mean (± SD) annual loss of 2,550 ± 730 sheep, or 0.35% of the regional stock. Sheep lost to predators by province were correlated with sheep density within areas containing wolves ($r_{s}=0.88,\\ n=9,\\ P=0.0015$), but marked geographical and temporal fluctuations were reported in compensation costs. Highest levels of conflict were observed in the provinces at the border of the regional wolf range, where livestock was left unattended most of the year and sheep density reached its highest regional levels. Based on 527 reports of approved claims during 1992-1995 from the National Health System, depredations were highly seasonal, increasing steadily from spring to early fall, possibly following trends in sheep availability on pastures and density fluctuations of local wolf packs. An average of 3 sheep (range = 1-18) were killed per attack (n = 483), and 42% of the attacks involved killing of ≤2 sheep. Additionally, 21-113 sheep were killed or attacked in mass slaughters which comprised 2.3% of the depredation events and 19% of the sheep lost. Depredations also resulted in 35% (n = 168) of sheep injured and 33% (n = 158) missing. Most sheep depredations occurred during the night, in pastures interspersed with wood or vegetative cover, and involved free-ranging flocks unattended by either the shepherd or guard dogs. High levels of conflict occurred in localized areas of intensive sheep production; 6% of the affected farms and 8% of the affected municipalities accounted for 32% of the sheep lost to both wolves and dogs at the regional level. Compensation programs alone were not effective in reducing the conflict or in preventing illegal, private efforts to control wolf numbers. Improved husbandry should be encouraged and facilitated through financial incentives and public education.

To assess the wolf-habitat relationship on the home range scale (i.e., third order selection), we developed a resource selection probability function (RSPF) through a multiple logistic regression model based on the winter travel routes of a wolf pack in the northern Apennines, Italy (1991-95). Both travel routes (240 km) and habitat variables were mapped at 1:10000 scale, digitised as Geographical Information System (GIS) layers, and overlaid with a 100 × 100 m pixel grid to census all used and unused resource units. Out of 15 covariates, the full model included 10 variables and 4 interaction terms. According to the model, travel routes by wolves were not randomly located within the home range but were clearly associated with selected bio-physical factors, including human-related habitat modifications (i.e., roads), which appeared to affect the wolves' resource selection and, ultimately, habitat quality. Using a jackknife procedure, the model correctly classified 73.1% of used resource units and 63.2% of unused resource units. A Monte Carlo test showed a non-significant effect on the model coefficients of 4 increasing sub-sampling levels of used resource units, suggesting that autocorrelation of snow-tracking data exerted little influence on the point estimates of the coefficients. However, given the increased standard error at higher sub-sampling levels, autocorrelation might have caused an underestimation of the theoretical variance. Although wolves are generally considered habitat generalists, this study shows that patterns of habitat selection are disclosed at finer scales of analysis. In this perspective, resource selection probability functions at finer scales offer different and complementary insight with respect to regional landscape applications, and provide a useful management tool for assessment of habitat quality at the local scale.