Population Genetics of Fragmented Wolf Populations

Abstract

Grey wolf (Canis lupus) populations in Europe have recovered substantially from near-extinction over the past three decades, recolonising large parts of their former range through natural dispersal and passive range expansion -- yet this recovery is occurring in a highly fragmented landscape in which roads, agricultural intensification, and human population centres subdivide suitable habitat into semi-isolated patches that constrain dispersal and generate genetic differentiation among subpopulations. Understanding the population genetic structure of recovering wolf populations -- and identifying which subpopulations are currently connected by gene flow versus isolated by landscape barriers -- is essential for management decisions about translocation, harvest limits, and connectivity corridor priority. This study presents the most comprehensive single-study European wolf population genetics dataset yet assembled, genotyping 1,247 wolves from 24 subpopulations across 18 countries at 20 microsatellite loci and 5,847 SNPs (reduced representation genome sequencing), integrated with landscape resistance modelling to identify the functional barriers and corridors determining gene flow. STRUCTURE analysis identified K = 7 genetic clusters (Scandinavian; Northern Central European; Alpine-Western; Italian; Dinaric-Balkan; Carpathian; Iberian) with FST ranging from 0.084 (adjacent connected clusters) to 0.347 (Scandinavian vs. Iberian). Landscape resistance modelling identified 184 priority connectivity corridors, of which 47.4% are currently partially or fully blocked by major road infrastructure. Gene flow was significantly predicted by landscape resistance (r = -0.74; p < 0.001) but not by geographic distance alone (r = -0.38; p = 0.018), confirming isolation-by-resistance rather than isolation-by-distance as the primary structuring mechanism.