Abstract
Spatial genetics is a relatively new field in wildlife and conservation biology that is becoming an essential tool for unravelling the complexities of animal population processes, and for designing effective strategies for conservation and management. Conceptual and methodological developments in this field are therefore critical. Here we present two novel methodological approaches that further the analytical possibilities of STRUCTURE and DResD. Using these approaches we analyse structure and migrations in a grey wolf ( Canis lupus ) population in north-eastern Europe. We genotyped 16 microsatellite loci in 166 individuals sampled from the wolf population in Estonia and Latvia that has been under strong and continuous hunting pressure for decades. Our analysis demonstrated that this relatively small wolf population is represented by four genetic groups. We also used a novel methodological approach that uses linear interpolation to statistically test the spatial separation of genetic groups. The new method, which is capable of using program STRUCTURE output, can be applied widely in population genetics to reveal both core areas and areas of low significance for genetic groups. We also used a recently developed spatially explicit individual-based method DResD, and applied it for the first time to microsatellite data, revealing a migration corridor and barriers, and several contact zones.
Highlights
Anthropogenic activities are among the key factors affecting wildlife populations, and perhaps most important among them are overexploitation and habitat destruction/fragmentation, which cause a considerable range of problems for wildlife, but for sustainable development in general (e.g. [1,2,3])
In the sign test conducted on all 16 microsatellite loci, the signatures of bottleneck were detected with stepwise mutation model (SMM) and two phase model (TPM) models: wolf populations were not at mutation-drift equilibrium under SMM (P < 0.0001), with 16 loci out of 16 exhibiting heterozygosity deficiency; mutation-drift equilibrium was not identified under TPM (P = 0.006; 12 loci with heterozygosity deficiency)
Population bottlenecks and sub-structuring The Estonian-Latvian wolf population is characterised by relatively high genetic diversity despite past population bottlenecks and severe hunting pressure
Summary
Anthropogenic activities are among the key factors affecting wildlife populations, and perhaps most important among them are overexploitation and habitat destruction/fragmentation, which cause a considerable range of problems for wildlife, but for sustainable development in general (e.g. [1,2,3]). [4], uses population genetic and spatial data to study interactions between the spatial patterns of populations and ecological factors, the latter inevitably including anthropogenic factors. Mobile species such as wolf, brown (Ursus arctos) and black bear (U. americanus) make suitable study species for investigating large-scale spatial and temporal population processes in large carnivores. Spatial genetic analyses have demonstrated, for example, how results from population viability analyses of Mexican wolf (Canis lupus baileyi) can be combined with habitat data to develop quantitative recovery criteria for population connectivity [5]; they have revealed important geographic mixing areas for different brown bear subpopulations [6], cryptic brown bear phylogeographical patterns [7], and have demonstrated the impacts of anthropogenic forces on the spatial genetic structure of black bear populations [8]. A set of methodological approaches have been developed in spatial genetics over the last decade (reviewed in 9), the field would benefit from further conceptual and methodological advancement
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