Context: Anthropogenic structures have considerable effects on ecosystems, disrupting natural population processes and representing a serious risk in terms of vehicle collisions. The golden jackal (Canis aureus) is a mesocarnivore species whose range is expanding in Europe. Roadkills are one of the main human-induced mortalities in Italy to the species.Objectives: Identify road-related characteristics and ecological factors related to golden jackal roadkill risk in Italy.Methods: We used habitat suitability (Maxent) and connectivity (Circuit theory) models to derive 15 metrics potentially affecting roadkill risk. We tested their influence using Bayesian generalized linear models and generalized linear models comparing golden jackal roadkill locations to random locations. Furthermore, we tested if there were significant sex, age-related and seasonal differences among road-killed individuals.Results: We found that roadkill risk was higher in areas characterized by higher values of habitat suitability and connectivity, habitat fragmentation and along highways. It was lower with increasing distance to the source population and in the presence of guardrails. No significant differences were detected in terms of roadkill risk between sexes, age classes and seasonConclusions: The identified factors affecting road mortality of golden jackals in Italy provide insights on how to mitigate wildlife-vehicle collisions. Crossing areas, and visual and acoustic warnings for wildlife, as well as the importance of managing fences along high traffic volume roads could help mitigate further damage. Finally, there is a need to further investigate the effectiveness of mitigation measures in the light of the golden jackal’s ongoing expansion in a human-modified landscape.

Cortisol is the main glucocorticoid hormone commonly measured to assess adrenocortical activity in vertebrates in response to potential stressors. Competition and habitat quality may act as chronic stressors leading to an increase in cortisol accumulation. Moreover, chronic cortisol concentrations may seriously hamper the reproductive potential, health status and body condition of a species. Using hair collected from the rump of 88 adult roadkill roe deer Capreolus capreolus in the north‐eastern Italy, we aimed to assess the effect of both ungulate competitor population densities and habitat suitability on the long‐term physiological stress response of roe deer, using hair cortisol as a reference parameter. Our findings revealed that roe deer showed higher cortisol concentrations in response to higher red deer Cervus elaphus population density, most likely as a consequence of direct interspecific competition. No significant cortisol changes were however recorded in response to both wild boar Sus scrofa and roe deer population densities, probably as a result of reduced competition because of abundant feeding resources, different species population densities and spatial/temporal avoidance among species. Moreover, the absence of a significant effect as far as habitat suitability is concerned, suggest that roe deer are well adapted to live even in poor quality habitats most likely as long as they are close to better quality habitats which provide access to food resources and refuge sites. Our results highlight the importance of hair cortisol as a suitable parameter to assess physiological chronic stress response towards different environmental/ecological conditions.

Biotic interactions are expected to influence species' responses to global changes, but they are rarely considered across broad spatial extents. Abiotic factors are thought to operate at larger spatial scales, while biotic factors, such as species interactions, are considered more important at local scales within communities, in part because of the knowledge gap on species interactions at large spatial scales (i.e., the Eltonian shortfall). We assessed, at a continental scale, (i) the importance of biotic interactions, through food webs, on species distributions, and (ii) how biotic interactions under scenarios of climate and land‐use change may affect the distribution of the brown bear (Ursus arctos). We built a highly detailed, spatially dynamic, and empirically sampled food web based on the energy contribution of 276 brown bear food species from different taxa (plants, vertebrates, and invertebrates) and their ensemble habitat models at high resolution across Europe. Then, combining energy contribution and predicted habitat of food species, we modelled energy contribution across space and included these layers within Bayesian‐based models of the brown bear distribution in Europe. The inclusion of biotic interactions considerably improved our understanding of brown bear distribution at large (continental) scales compared with Bayesian models including only abiotic factors (climate and land use). Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, providing a warning that future indirect climate and land‐use change are likely to have strong but highly uncertain impacts on species biogeography. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future projections of biodiversity change, especially for modelling species distributions and their functional role under climate and land‐use change scenarios, which is key for effective conservation of biodiversity and ecosystem services.

Wildlife abundance estimation is one of the key components in conservation biology. Bayesian frameworks are widely used to adjust the potential biases derived by data collected in the field, as they can increase the precision of model parameter as a consequence of the combination of previous pieces of knowledge (priors) combined with data collected in the field to produce an a-posteriori distribution. Capture-recapture is one of the most common techniques used to assess animal abundance. However, the implementation with camera traps requires that animals present unique phenotypic traits for individual-based recognition. The crested porcupine Hystrix cristata is a semi-fossorial rodent with a continuous, but patchily distribution across Italy. Despite the species does not present evident individual-specific phenotypic traits, the information gathered using presence-only data obtained from camera traps, opportunistic observations, and road-killing events could be used to provide a rough estimate of the species abundance within an area. The main purpose of the present research was hence to provide the first preliminary estimate of the abundance of the crested porcupine in central Italy using presence-only data obtained from the above different monitoring methods. The results obtained estimated an average minimum number of 1803 individuals (SD = 26.89, CI 95% = 1750–1855) within an area covering about 17,111 km². Since the porcupine is considered as “potentially problematic” because of damages to croplands and riverbanks, assessing its abundance is even more important to delineate adequate conservation and management actions to limit the potential trade-off effects over human activities.

‘Agricultural pests’ is a locution used to indicate those wild species considered as dangerous to crops. The crested porcupine Hystrix cristata is a semi–fossorial rodent considered as one of the main agricultural pests by farmers in Italy. Assessing the role of agriculture in shaping the porcupine’s space use is of great importance to develop proper management and conservation strategies. The goal of this study was to quantify the degree of habitat selection by and suitability for porcupines in Central Italy to assess the potential influence of agricultural fields on the ecology of this rodent. The habitat suitability analysis was realized using presence–only data implemented in the MAXENT Software, while the habitat selection analysis was carried out using the Jacobs’ selectivity index. Our research revealed that croplands have an important role in the overall habitat suitability for porcupines. However, during the warm period, all habitats were used according to their availability. Conversely, orchards, vineyards, and olive groves were preferred during the cold period. Our findings suggest that the use of agricultural crops in accordance with their availability during the warm season and the preference shown for orchards, vineyards, and olive groves during the cold one, highlight that porcupine–famer negative interactions may occur in the area. The implementation of proper prevention measures is therefore strongly suggested, especially during the cold period, to reduce the potential impacts on agriculture.

Within ecological communities, larger predators typically limit mesocarnivore populations. On a continental scale, this may be the case for the gray wolf ( Canis lupus ) over the golden jackal ( Canis aureus ) in Europe. North‐eastern Italy represents one of the first areas in Western Europe to experience golden jackal colonization, followed by wolf recolonization. Since few studies have investigated the spatial relationship between these two wild canids, this work aimed to analyze their distribution dynamics and investigate whether the wolf and environmental factors may have influenced golden jackal distribution. We used systematic and opportunistic data collected over 11 years (2013–2023) to assess the presence of both species on a 10 × 10 km square grid system. A multinomial logistic mixed model (MLMM) was applied to test whether the study period and landscape metrics (terrain ruggedness and habitat fragmentation indices) influenced both species' presence at a broad scale (i.e., square grid units). Generalized linear mixed models (GLMMs) were used to test whether the wolf and landscape metrics influenced jackal presence at a finer scale (i.e., jackal howling calling stations). Both species showed an increase in their former distribution, with a small growth in sympatric areas. Models revealed that jackals preferred less rugged and more fragmented areas typical of the lowland, whereas wolves preferred rugged terrain with extensive forested patches in the Alpine range. Furthermore, our results showed that, at a local scale, golden jackal presence was negatively related to wolf presence. This study provides further insights into the coexistence of these two competing wild canids, suggesting a potential top‐down effect of the wolf on golden jackal colonization dynamics. However, the wolf influence may vary in intensity depending on environmental context, with a weaker effect in areas of higher human pressure, such as the lowlands.