Genome-wide technologies open up new possibilities to clarify questions on genetic structure and phylogeographic history of taxa previously studied with microsatellite loci and mitochondrial sequences. Here, we used 736 individual red deer (Cervus elaphus) samples genotyped at 35,701 single nucleotide polymorphism loci (SNPs) to assess the population structure of the species throughout Europe. The results identified 28 populations, with higher degrees of genetic distinction in peripheral compared to mainland populations. Iberian red deer show high genetic differentiation, with lineages in Western and Central Iberia maintaining their distinctiveness, which supports separate refugial ranges within Iberia along with little recent connection between Iberian and the remaining Western European populations. The Norwegian population exhibited the lowest variability and the largest allele frequency differences from mainland European populations, compatible with a history of bottlenecks and drift during post-glacial colonization from southern refugia. Scottish populations showed high genetic distance from the mainland but high levels of diversity. Hybrid zones were found between Eastern and Western European lineages in Central Europe as well as in the Pyrenees, where red deer from France are in close contact with Iberian red deer. Anthropogenic restocking has promoted the Pyrenean contact zone, admixture events in populations on the Isle of Rum and in the Netherlands, and at least partly the admixture of the two main lineages in central-eastern Europe. Our analysis enabled detailed resolution of population structure of a large mammal widely distributed throughout Europe and contributes to resolving the evolutionary history, which can also inform conservation and management policies.

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.

Rewilding seeks to address biodiversity loss by restoring trophic interactions and fostering self-regulating ecosystems. Although gaining traction in Europe and North America, the extent to which rewilding can meet post-2020 protected-area targets remains uncertain. We formulated criteria to map suitable areas for rewilding by identifying large tracts of land with minimal human disturbances and the presence of key mammal species. We find that one-quarter of Europe, approximately 117 million hectares (ha), is compatible with our rewilding criteria. Of these, 70% are in cooler climates. Passive rewilding opportunities, focused on managing existing wilderness, are predominant in Scandinavia, Scotland, the Iberian Peninsula, and notably in the Baltic states, Ireland, and southeastern Europe. Active rewilding opportunities, marked by reintroduction of absent trophic guilds, are identified in Corsica, Sardinia, southern France, and parts of the Netherlands, Denmark, Sweden, and Norway. Our mapping supports European nations in leveraging land abandonment to expand areas for nature conservation, aligning with the European Biodiversity Strategy for 2030. Nevertheless, countries with limited potential for rewilding should consider alternative conservation strategies.

The American black bear, Ursus americanus, is a widespread and ecologically important species in North America. In California, the black bear plays an important role in a variety of ecosystems and serves as an important species for recreational hunting. While research suggests that the populations in California are currently healthy, continued monitoring is critical, with genomic analyses providing an important surveillance tool. Here we report a high-quality, near chromosome-level genome assembly from a U. americanus sample from California. The primary assembly has a total length of 2.5 Gb contained in 316 scaffolds, a contig N50 of 58.9 Mb, a scaffold N50 of 67.6 Mb, and a BUSCO completeness score of 96%. This U. americanus genome assembly will provide an important resource for the targeted management of black bear populations in California, with the goal of achieving an appropriate balance between the recreational value of black bears and the maintenance of viable populations. The high quality of this genome assembly will also make it a valuable resource for comparative genomic analyses among black bear populations and among bear species.

Human-wildlife conflicts (HWC) are increasing and are potentially harmful to both people and wildlife. Understanding the current and potential distribution of wildlife species involved in HWC, such as carnivores, is essential for implementing management and conservation measures for such species. In this study, we assessed both the current distribution and potential distribution (forecast) of the Egyptian mongoose (Herpestes ichneumon) in the central part of the Iberian Peninsula. We acquired data concerning mongoose occurrences through an online questionnaire sent to environmental rangers. We used the municipality level as the sampling unit because all municipalities within the study area were covered at least by one ranger. Using the information provided by rangers (i.e. occurrences in their municipalities), we constructed environmental favourability distribution models to assess current and potential mongoose distribution through current distribution models (CDM) and ecological models (EM), respectively. >300 rangers participated in the survey and mongooses were reported in a total of 181 of 921 municipalities studied. The CDM model showed a current distribution mainly concentrated on the western part of the study area, where intermediate-high favourability values predominated. The EM model revealed a wider potential distribution, including the south-east part of the study area, which was also characterised by intermediate-high favourability values. Our predictions were verified using independent data, including confirmation of mongoose reproduction by rangers, reports by other experts, and field sampling in some areas. Our innovative approach based on an online survey to rangers coupled with environmental favourability models is shown to be a useful methodology for assessing the current distribution of cryptic but expanding wildlife species, while also enabling estimations of future steps in their expansion. The approach proposed may help policy decision-makers seeking to ensure the conservation of expanding wildlife species, for example, by designing awareness campaigns in areas where the target species is expected to arrive.

Porcine Reproductive and Respiratory Syndrome (PRRS) significantly impacts the pig farming industry globally, leading to economic losses due to reduced productivity. This study focuses on assessing the presence and impact of PRRS within Hungarian wild boar populations amidst efforts to eradicate the virus from domestic pig herds. We used a combination of serological and virological tests on samples collected from wild boars across Hungary to evaluate the prevalence of PRRS virus and its potential transmission risks to domestic pigs. Our findings reveal a low seropositivity rate in wild boars, suggesting a minimal role of wild boars in the transmission of PRRS to domestic pig populations. Moreover, no relationship was found between domestic pig and wild boar densities, emphasizing the limited interaction and consequent risk of disease spread between these populations. We confirm the effectiveness of Hungary\'s PRRS eradication measures among domestic herds and highlight the negligible risk posed by wild boars in re-introducing the PRRS virus.

Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens (Tympanuchus pallidicinctus) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations\' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual\'s health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species\' adaptive potential and persistence on ecologically relevant timescales.

Wild ungulates are expanding in range and number worldwide leading to an urgent need to manage their populations to minimize conflicts and promote coexistence with humans. In the metropolitan area of Barcelona (MAB), wild boar is the main wildlife species causing a nuisance, from traffic accidents to health risks. Selective harvesting of specific sex and age classes and reducing anthropogenic food resources would be the most efficient approach to dealing with overpopulation. Nonetheless, there is a gap in knowledge regarding the age and sex selectivity of the capture methods currently applied in the MAB for wild boar population control. Thus, this study aimed to evaluate the performance and age and sex bias of different hunting and capture methods and the seasonal patterns in their performance (number of captured individuals per event). From February 2014 to August 2022, 1454 wild boars were captured in the MAB using drop net, teleanaesthesia, cage traps, night stalks, and drive hunting. We applied generalized linear models (GLM) to compare the performance of these methods for the total number of wild boars, the wild boars belonging to each age category (i.e., adult, yearling, and juvenile), and for each season. The studied capture methods showed age-class bias and sex bias in adults (>2 years). Drive hunting and drop net removed mainly adult females and yearlings (1-2 years), with drive hunting having the highest performance for adult males. Instead, cage traps and drop net were the best methods to capture juveniles (<1 year). Overall, global performance was higher in summer, decreasingly followed by autumn and spring, winter being the worst performing season. Wildlife managers and researchers should consider the different performance and sex and age bias of each hunting and capture method, as well as the associated public cost, to improve efficiency and achieve the best results in wild boar population management.

Urbanization is an ongoing global environmental change. Wildlife may respond using anthropized environments and resources, which is known as synurbization, creating human-wildlife interactions. Wild boar (Sus scrofa) populations have become common in urban areas, including the metropolitan area of Barcelona. Humans respond to wild boars in urban environments either habituating, with lower conflict perception and higher wild boar acceptance, or sensitizing, with reduced tolerance towards wild boars. Since citizen response influences conflict management, this study analysed the drivers of human responses, which should allow adopting socially-accepted measures to manage synurbic wild boar populations. Interviews to 1956 Barcelona citizens were performed, grouping the response variables to score citizen and urban characteristics, as well as citizen lay-knowledge, emotions, experiences, and perception of wild boar. Five citizen clusters were identified: cluster 1 (3.3 %), highly habituated and active wild boar feeder; cluster 2 (11.3 %), habituated to wild boars with positive feelings; cluster 3 (19.8 %), not habituated nor sensitized, willing to maintain urban wild boar populations; cluster 4 (29.1 %), sensitized and concerned, defending to reduce wild boar; and cluster 5 (40.1 %), highly sensitized and proposing to reduce or even eliminate wild boar. Positive attitudes associated wild boar to aesthetic value, closeness to nature and sympathy, and were more frequent in young citizens with urban background and high education, animal lovers habituated to wild boar through contact without negative experiences. Conversely, negative attitudes were concerned about city fouling, safety or health, accepted lethal management measures, and were more frequent in older citizens with rural background, lower education, low contact with wild boar or sensitized through negative experiences. We document for the first time the sensitization and reciprocal habituation of humans to wild boar in urban areas. The identification of the drivers of citizen attitudes towards urban wildlife should be useful to design socially-accepted management measures.