Long-range gene flow and the effects of climatic and ecological factors on genetic structuring in a large, solitary carnivore: The Eurasian lynx

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Abstract

Due to their high mobility, large terrestrial predators are potentially capable of maintaining high connectivity, and therefore low genetic differentiation among populations. However, previous molecular studies have provided contradictory findings in relation to this. To elucidate patterns of genetic structure in large carnivores, we studied the genetic variability of the Eurasian lynx, Lynx lynx throughout north-eastern Europe using microsatellite, mitochondrial DNA control region and Y chromosome-linked markers. Using SAMOVA we found analogous patterns of genetic structure based on both mtDNA and microsatellites, which coincided with a relatively little evidence for male-biased dispersal. No polymorphism for the cytochrome b and ATP6 mtDNA genes and Y chromosome-linked markers were found. Lynx inhabiting a large area encompassing Finland, the Baltic countries and western Russia formed a single genetic unit, while some marginal populations were clearly divergent from others. The existence of a migration corridor was suggested to correspond with distribution of continuous forest cover. The lowest variability (in both markers) was found in lynx from Norway and Białowieża Primeval Forest (BPF), which coincided with a recent demographic bottleneck (Norway) or high habitat fragmentation (BPF). The Carpathian population, being monomorphic for the control region, showed relatively high microsatellite diversity, suggesting the effect of a past bottleneck (e.g. during Last Glacial Maximum) on its present genetic composition. Genetic structuring for the mtDNA control region was best explained by latitude and snow cover depth. Microsatellite structuring correlated with the lynx's main prey, especially the proportion of red deer (Cervus elaphus) in its diet. Eurasian lynx are capable of maintaining panmictic populations across eastern Europe unless they are severely limited by habitat continuity or a reduction in numbers. Different correlations of mtDNA and microsatellite population divergence patterns with climatic and ecological factors may suggest separate selective pressures acting on males and females in this solitary carnivore.

Figures

  • Table 1. Mitochondrial DNA- control region diversity indices for the Eurasian lynx samples studied.
  • Fig. 1. Distribution of Eurasian lynx sampling locations and mtDNA haplotypes. Map showing distribution of sampling locations of the Eurasian lynx in north-eastern and central Europe. The color of each sampled individual denotes the haplotype of cr mtDNA and corresponds to the haplotype network in Fig. 2. Points are clustered into four groups as assigned by SAMOVA (both based on mtDNA and microsatellites) and shaded with different colors: Norway (yellow), BPF (green), Carpathians (blue) and remaining samples (pink). Names of arbitrarily assigned populations are given. Intensity of grey shading refers to the terrain ruggedness indicating mountainous areas. The background map was extracted from open access database available through USGS: http://srtm.usgs.gov/index.php). It is similar but not identical to the original image,
  • Fig. 2. mtDNA haplotype network of Eurasian lynx. Haplotype network illustrating the relationship among 16 haplotypes of Eurasian lynx. Small black circles indicate missing haplotypes. Numbers denote the haplotypes. The size of the circles (except the haplotypes not found in this study) refers to the relative frequencies of a given haplotype in the whole sample. Colors of haplotypes correspond to Fig. 1.
  • Table 2. Microsatellite DNA diversity indices for the Eurasian lynx in Europe.
  • Table 3. Pairwise differentiation between Eurasian lynx populations.
  • Fig. 3. Results of the spatial autocorrelation analysis. Correlograms of the average autocorrelation coefficient (r) for 20 distance classes of 100 km each for male (A) and female (B) Eurasian lynx. The dashed lines represent the 95% upper and lower bounds of the null distribution assuming no spatial structure. The error bars represent the 95% confidence intervals about r. Significant spatial structure is observed when r exceeds the null distribution and the error bars do not overlap zero.
  • Fig. 5. Migration routes and rates of Eurasian lynx across north-eastern Europe. Recent migration rates within the Eurasian lynx population in north-eastern and central Europe between arbitrarily assigned sampling populations, estimated using BayesAss. Directions and rates of migrations are shown with arrows and associated numbers. The numbers within the circles denote proportions of non-immigrants within the sampled populations (denoted with small digits which refer to the population numbers and names in Table 1). Grey shading represents the forest cover. It is prepared based on an open access GlobCOVER database (http:// due.esrin.esa.int/globcover/) by extracting a range of data indicating forested and non forested areas (limited
  • Fig. 6. Results of spatial analysis of genetic differentiation in the Eurasian lynx.Maps showing contour lines of the first axis of the PCA performed on a sample-wise matrix of genetic distance for microsatellite (A) and mtDNA (B) data interpolated with the use of the kriging algorithm (Surfer12 software) and superimposed onto a geographic map of the study area. Black and white arrows show possible migration barriers or migratory corridors respectively. See Fig. 5 for other explanations.

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CITATION STYLE

APA

Ratkiewicz, M., Matosiuk, M., Saveljev, A. P., Sidorovich, V., Ozolins, J., Männil, P., … Schmidt, K. (2014). Long-range gene flow and the effects of climatic and ecological factors on genetic structuring in a large, solitary carnivore: The Eurasian lynx. PLoS ONE, 9(12). https://doi.org/10.1371/journal.pone.0115160

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