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Individuals are typically not randomly distributed in space; consequently ecological and evolutionary theory depends heavily on understanding the spatial structure of populations. The central challenge of landscape genetics is therefore to link spatial heterogeneity of environments to population genetic structure. Here, we employ multivariate spatial analyses to identify environmentally induced genetic structures in a single breeding population of 1174 great tits Parus major genotyped at 4701 single-nucleotide polymorphism (SNP) loci. Despite the small spatial scale of the study relative to natal dispersal, we found multiple axes of genetic structure. We built distance-based Moran's eigenvector maps to identify axes of pure spatial variation, which we used for spatial correction of regressions between SNPs and various external traits known to be related to fitness components (avian malaria infection risk, local density of conspecifics, oak tree density, and altitude). We found clear evidence of fine-scale genetic structure, with 21, seven, and nine significant SNPs, respectively, associated with infection risk by two species of avian malaria (Plasmodium circumflexum and P. relictum) and local conspecific density. Such fine-scale genetic structure relative to dispersal capabilities suggests ecological and evolutionary mechanisms maintain within-population genetic diversity in this population with the potential to drive microevolutionary change.

Original publication

DOI

10.1111/evo.12121

Type

Journal article

Journal

Evolution

Publication Date

12/2013

Volume

67

Pages

3488 - 3500

Keywords

Genome-environment association study, Moran's eigenvector maps, Parus major, SNPs, landscape genetics, plasmodium, Animal Migration, Animals, Environment, Evolution, Molecular, Malaria, Avian, Models, Genetic, Passeriformes, Phylogeography, Plasmodium, Polymorphism, Single Nucleotide, Risk Factors, Selection, Genetic