Genetic admixture between Central European and Alpine wolf populations

The recovery and expansion of formerly isolated wolf populations in Europe raise questions about the nature of their interactions and future consequences for population viability and conservation. Will fragmented populations fuse or maintain a certain level of isolation with migration? Central Europe is suitable for obtaining empirical data in this field as it represents a “crossroad” with the potential for contact among several phylogeographic lineages. In this study, non-invasive genetic samples obtained during population monitoring in the Bohemian and Bavarian Forest (BBF) mountain ranges in the Czech Republic and Germany (Bohemian Massif) were analysed at different neutral markers including mitochondrial sequence, nuclear autosomal microsatellites and gonosomal sex markers. Resultant genetic profiles were compared with reference data to study population ancestry. Both cluster analyses of microsatellite genotypes and syntopic occurrence of haplotypes HW01 and HW22 showed genetic admi..., The studied deme was characterised using genetic markers. Through comparison with neighbouring populations, its origins and status of population admixture were assessed. , QGIS, Microsoft Excell, Rstudio, GeneAlEx, # Genetic admixture between Central European and Alpine wolf populations

We present data on admixture between Central European and Alpine grey wolf populations.

## Description of the data and file structure

This folder contains two files:

1\) Table S1 contains sample information: ID, species determination, population assignment, country of origin, locality (area) of origin, GPS coordinates, date of collection, sample /observation type (camt = camera trap), sex determination (amelogenin), mitochondrial control region haplotype code (classification according to Pilot et al., 2010), identity (ID of samples from the same individual). The symbol \"-\" denotes empty values.

2\) MS Excel sheet \"Microsatellite genotypes\" contains allele scores of all studied individuals. Empty values are marked as \"NA\".