Summary Urban sprawl has resulted in the permanent presence of large mammal species in urban areas, leading to human–wildlife conflicts. Wild boar Sus scrofa are establishing a permanent presence in many cities in Europe, with the largest German urban population occurring in Berlin. Despite their relatively long‐term presence, there is little knowledge of colonization processes, dispersal patterns or connectivity of Berlin's populations, hampering the development of effective management plans. We used 13 microsatellite loci to genotype 387 adult and subadult wild boar from four urban forests, adjacent built‐up areas and the surrounding rural forests. We applied genetic clustering algorithms to analyse the population genetic structure of the urban boar. We used approximate Bayesian computation to infer the boar's colonization history of the city. Finally, we used assignment tests to determine the origin of wild boar hunted in the urban built‐up areas. The animals in three urban forests formed distinct genetic clusters, with the remaining samples all being assigned to one rural population. One urban cluster was founded by individuals from another urban cluster rather than by rural immigrants. The wild boar that had been harvested within urban built‐up areas was predominantly assigned to the rural cluster surrounding the urban area, rather than to one of the urban clusters. Synthesis and applications. Our results are likely to have an immediate impact on management strategies for urban wild board populations in Berlin, because they show that there are not only distinct urban clusters, but also ongoing source–sink dynamics between urban and rural areas. It is therefore essential that the neighbouring Federal States of Berlin and Brandenburg develop common hunting plans to control the wild boar population and reduce conflicts in urban areas.

In urban areas with a high level of human disturbance, wildlife has to adjust its behavior to deal with the so called "landscape of fear." This can be studied in risk perception during movement in relation to specific habitat types, whereby individuals trade-off between foraging and disturbance. Due to its high behavioral plasticity and increasing occurrence in urban environments, wild boar (Sus scrofa) is an excellent model organism to study adjustment to urbanization. With the help of GPS tracking, space use of 11 wild boar from Berlin's metropolitan region was analyzed: we aimed at understanding how animals adjust space use to deal with the landscape of fear in urban areas compared to rural areas. We compared use vs. availability with help of generalized linear mixed models. First, we studied landscape types selected by rural vs. urban wild boar, second, we analyzed distances of wild boar locations to each of the landscape types. Finally, we mapped the resulting habitat selection probability to predict hotspots of human-wildlife conflicts. A higher tolerance to disturbance in urban wild boar was shown by a one third shorter flight distance and by an increased re-use of areas close to the trap. Urban wild boar had a strong preference for natural landscapes such as swamp areas, green areas and deciduous forests, and areas with high primary productivity, as indicated by high NDVI (normalized difference vegetation index) values. The areas selected by urban wild boar were often located closely to roads and houses. The spatial distribution maps show that a large area of Berlin would be suitable for urban wild boar but not their rural conspecifics, with the most likely reason being a different perception of anthropogenic disturbance. Wild boar therefore showed considerable behavioral plasticity suitable to adjust to human-dominated environments in a potentially evolutionarily adaptive manner.

Urbanization affects key aspects of wildlife ecology. Dispersal in urban wildlife species may be impacted by geographical barriers but also by a species’ inherent behavioural variability. There are no functional connectivity analyses using continuous individual‐based sampling across an urban‐rural continuum that would allow a thorough assessment of the relative importance of physical and behavioural dispersal barriers. We used 16 microsatellite loci to genotype 374 red foxes (Vulpes vulpes) from the city of Berlin and surrounding rural regions in Brandenburg in order to study genetic structure and dispersal behaviour of a mobile carnivore across the urban‐rural landscape. We assessed functional connectivity by applying an individual‐based landscape genetic optimization procedure. Three commonly used genetic distance measures yielded different model selection results, with only the results of an eigenvector‐based multivariate analysis reasonably explaining genetic differentiation patterns. Genetic clustering methods and landscape resistance modelling supported the presence of an urban population with reduced dispersal across the city border. Artificial structures (railways, motorways) served as main dispersal corridors within the cityscape, yet urban foxes avoided densely built‐up areas. We show that despite their ubiquitous presence in urban areas, their mobility and behavioural plasticity, foxes were affected in their dispersal by anthropogenic presence. Distinguishing between man‐made structures and sites of human activity, rather than between natural and artificial structures, is thus essential for better understanding urban fox dispersal. This differentiation may also help to understand dispersal of other urban wildlife and to predict how behaviour can shape population genetic structure beyond physical barriers.

To identify native wildlife species possibly susceptible to infection with Schmallenberg virus (SBV), a midge-transmitted orthobunyavirus that predominantly infects domestic ruminants, samples from various free-living ruminants, but also carnivores, small mammals and wild boar were analyzed serologically. Before 2011, no SBV-specific antibodies were detectable in any of the tested species, thereafter, a large proportion of the ruminant population became seropositive, while every sample taken from carnivores or small mammals tested negative. Surprisingly, SBV-specific-antibodies were also present in a large number of blood samples from wild boar during the 2011/2012 and 2012/2013 hunting seasons. Hence, free-ranging artiodactyls may play a role as wildlife host.

Most wildlife species are urban avoiders, but some became urban utilizers and dwellers successfully living in cities. Often, they are assumed to be attracted into urban areas by easily accessible and highly energetic anthropogenic food sources. We macroscopically analysed stomachs of 247 wild boar (Sus scrofa, hereafter WB) from urban areas of Berlin and from the surrounding rural areas. From the stomach contents we determined as predictors of food quality modulus of fineness (MOF,), percentage of acid insoluble ash (AIA) and macronutrients such as amount of energy and percentage of protein, fat, fibre and starch. We run linear mixed models to test: (1) differences in the proportion of landscape variables, (2) differences of nutrients consumed in urban vs. rural WB and (3) the impact of landscape variables on gathered nutrients. We found only few cases of anthropogenic food in the qualitative macroscopic analysis. We categorized the WB into five stomach content categories but found no significant difference in the frequency of those categories between urban and rural WB. The amount of energy was higher in stomachs of urban WB than in rural WB. The analysis of landscape variables revealed that the energy of urban WB increased with increasing percentage of sealing, while an increased human density resulted in poor food quality for urban and rural WB. Although the percentage of protein decreased in areas with a high percentage of coniferous forests, the food quality increased. High percentage of grassland decreased the percentage of consumed fat and starch and increased the percentage of fibre, while a high percentage of agricultural areas increased the percentage of consumed starch. Anthropogenic food such as garbage might serve as fallback food when access to natural resources is limited. We infer that urban WB forage abundant, natural resources in urban areas. Urban WB might use anthropogenic resources (e.g. garbage) if those are easier to exploit and more abundant than natural resources. This study shows that access to natural resources still is mandatory and drives the amount of protein, starch, fat or fibre in wild boar stomachs in urban as well as rural environments.