Habitat fragmentation and loss have contributed significantly to the demographic decline of European wildcat populations and hybridization with domestic cats poses a threat to the loss of genetic purity of the species. In this study we used microsatellite markers to analyse genetic variation and structure of the wildcat populations from the area between the Dinaric Alps and the Scardo-Pindic mountains in Slovenia, Croatia, Serbia and North Macedonia. We also investigated hybridisation between populations of wildcats and domestic cats in the area. One hundred and thirteen samples from free-leaving European wildcats and thirty-two samples from domestic cats were analysed. Allelic richness across populations ranged from 3.61 to 3.98. The observed Ho values ranged between 0.57 and 0.71. The global FST value for the four populations was 0.080 (95% CI 0.056–0.109) and differed significantly from zero (P < 0.001). The highest FST value was observed between the populations North Macedonia and Slovenia and the lowest between Slovenia and Croatia. We also found a signal for the existence of isolation by distance between populations. Our results showed that wildcats are divided in two genetic clusters largely consistent with a geographic division into a genetically diverse northern group (Slovenia, Croatia) and genetically eroded south-eastern group (Serbia, N. Macedonia). Hybridisation rate between wildcats and domestic cats varied between 13% and 52% across the regions.

Disease control and containment in free-ranging populations is one of the greatest challenges in wildlife management. Despite the importance of major histocompatibility complex (MHC) genes for immune response, an assessment of the diversity and occurrence of these genes is still rare in European roe deer, the most abundant and widespread large mammal in Europe. Therefore, we examined immunogenetic variation in roe deer in Slovenia to identify species adaptation by comparing the genetic diversity of the MHC genes with the data on neutral microsatellites. We found ten MHC DRB alleles, three of which are novel. Evidence for historical positive selection on the MHC was found using the maximum likelihood codon method. Patterns of MHC allelic distribution were not congruent with neutral population genetic findings. The lack of population genetic differentiation in MHC genes compared to existing structure in neutral markers suggests that MHC polymorphism was influenced primarily by balancing selection and, to a lesser extent, by neutral processes such as genetic drift, with no clear evidence of local adaptation. Selection analyses indicated that approx. 10% of amino acids encoded under episodic positive selection. This study represents one of the first steps towards establishing an immunogenetic map of roe deer populations across Europe, aiming to better support science-based management of this important game species.

Habitat fragmentation and loss have contributed significantly to the demographic decline of European wildcat populations and hybridization with domestic cats poses a threat to the loss of genetic purity of the species. In this study we used microsatellite markers to analyse genetic variation and structure of the wildcat populations from the area between the Dinaric Alps and the Scardo-Pindic mountains in Slovenia, Croatia, Serbia and North Macedonia. We also investigated hybridisation between populations of wildcats and domestic cats in the area. One hundred and thirteen samples from free-leaving European wildcats and thirty-two samples from domestic cats were analysed. Allelic richness across populations ranged from 3.61 to 3.98. The observed Ho values ranged between 0.57 and 0.71. The global FST value for the four populations was 0.080 (95% CI 0.056–0.109) and differed significantly from zero (P < 0.001). The highest FST value was observed between the populations North Macedonia and Slovenia and the lowest between Slovenia and Croatia. We also found a signal for the existence of isolation by distance between populations. Our results showed that wildcats are divided in two genetic clusters largely consistent with a geographic division into a genetically diverse northern group (Slovenia, Croatia) and genetically eroded south-eastern group (Serbia, N. Macedonia). Hybridisation rate between wildcats and domestic cats varied between 13% and 52% across the regions.

Major histocompatibility complex (MHC) genes are widely recognised as valuable markers for wildlife genetic studies given their extreme polymorphism and functional importance in fitness-related traits. Newly developed genotyping methods, which rely on the use of next-generation sequencing (NGS), are gradually replacing traditional cloning and Sanger sequencing methods in MHC genotyping studies. Allele calling in NGS methods remains challenging due to extreme polymorphism and locus multiplication in the MHC coupled with allele amplification bias and the generation of artificial sequences. In this study, we compared the performance of molecular cloning with Illumina and Ion Torrent NGS sequencing in MHC-DRB genotyping of single-locus species (roe deer) and species with multiple DRB loci (red deer) in an attempt to adopt a reliable and straightforward method that does not require complex bioinformatic analyses. Our results show that all methods work similarly well in roe deer, but we demonstrate non-consistency in results across methods in red deer. With Illumina sequencing, we detected a maximum number of alleles in 10 red deer individuals (42), while other methods were somewhat less accurate as they scored 69–81% of alleles detected with Illumina sequencing.

The European Observatory of Wildlife (EOW) as part of the ENETWILD project, aims to improve the European capacity for monitoring wildlife populations, implementing international standards for data collection, providing guidance on wildlife density estimation, and finally, to promote collaborative, open data networks to develop wildlife monitoring, initially focusing on terrestrial wild mammals. This report presents density estimates for species that are widely distributed (wild boar (Sus scrofa), European roe deer (Capreolus capreolus), red deer (Cervus elaphus)) by following a standardised camera trapping (CT) protocol, in 48 areas from 28 different countries in Europe, during 2022. Density values are provided for 37 areas from 20 countries, while an additional 9 locations from 8 countries are currently completing the data analysis. The EOW involved different stakeholders over most European countries, which resulted for the first time in a number of reliable (known precision) wild ungulate density estimates, from areas representing different European bioregions. These estimates are the result of a collaborative effort from the network to apply practical systematic and rigorous protocols. The results presented from the first pilot campaign of the EOW cannot be used to accurately describe wildlife population gradients and trends at European level but can be used as first baseline data for future trend analyses. Our 1 www.enetwild.com www.efsa.europa.eu/publications 2 EFSA Supporting publication 2023:EN-7892The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.results show data gaps, but also provide relevant insights into some of the main drivers of demographic evolution of wild ungulate populations in Europe. We will expand and improve the EOW in the future to include more representative sites. The Agouti app, including photogrammetry methods to estimate CT detection zone size and animal speed of movement using a computer vision process proved useful to reduce the workload and to improve objectivity of measurements for REM method. We discuss the results obtained by the 2022 campaign in relation to the specific objectives of the EOW and propose the next steps.