https://orcid.org/0000-0003-1268-6620
Figures
Abstract
The introduction and expansion of an invasive non-native species could have important consequences for the genetic patterns and processes of native species, moreover if the new arrival competes strongly for resources and space. This may result in the demographic decline of the native species. Knowing the effects on the levels of genetic diversity and structure in native species is key in terms of their conservation. We analysed temporal (over 50 years) genetic variation of the population of the European polecat (Mustela putorius), a species under threat in several European countries, in the Białowieża Primeval Forest (BPF), Poland, before and after the invasion of the American mink (Neovison vison). Using 11 microsatellite loci and a fragment of the mitochondrial control region we show that levels of diversity changed in the polecat population over 53 generations (over the period 1959–2012) and after the invasion of mink. When compared with other threatened European polecat populations, high levels of diversity are observed in the population in BPF in both periods, as well as in other areas in Poland. Our data shows that genetic structure was not present either before or after the mink invasion in BPF. This would suggest that the polecat population in Poland was not affected by invasive species and other negative factors and would be a potential good source of individuals for captive breeding or genetic rescue conservation management actions in areas where such actions are needed, for example the UK.
Citation: Martínez-Cruz B, Zalewska H, Zalewski A (2022) The genetic diversity and structure in the European polecat were not affected by the introduction of the American mink in Poland. PLoS ONE 17(9): e0266161. https://doi.org/10.1371/journal.pone.0266161
Editor: Mateusz Baca, University of Warsaw, POLAND
Received: August 12, 2021; Accepted: March 15, 2022; Published: September 28, 2022
Copyright: © 2022 Martínez-Cruz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The dataset for the microsatellites are provided as Supplementary Material (S4 Table). All mitochondrial were deposited in GenBank under accession numbers OK644317-OK644331 and OM069433 - OM069566.
Funding: BMC was supported by postdoctoral fellowships under the project BIOCONSUS (Research Potential in Conservation and Sustainable Management of Biodiversity), funded by the European Union 7th Framework Programme (FP7 2010–2013; agreement no. 245737). https://hes32-ctp.trendmicro.com:443/wis/clicktime/v1/query?url=https%3a%2f%2fec.europa.eu&umid=94baad01-67a5-4b37-8bd9-cd17cbee06b6&auth=768f192bba830b801fed4f40fb360f4d1374fa7c-217871f4cbb551ad63bd2c41b1c981cae782ef78 Grant awarded: 19,500 EUR (brut salary). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Invasive non-native species have the potential to cause a decrease in native species number and density in ecosystems mainly by predation or competition [1]. If the introduction of the alien causes a demographic decline in any native species it may result in deleterious consequences for its genetic diversity and structure, which would be difficult to assess. Only the study of the population pre-dating the arrival of the alien provides the baseline to which directly compare the pattern extant in the population at present and infer the actual effect of the perturbation whenever other confounding factors could be discarded [2]. This kind of temporal approach has shed light on the processes and patterns affecting genetic diversity after the occurrence of external perturbations to a population, at both historical (e.g. [3, 4]) and evolutionary scales (e.g. [5, 6]) that would otherwise be difficult to infer.
Native to North America the American mink, Neovison vison, is a small generalist semi-aquatic mustelid that was brought to Europe in the 1920s for commercial fur farming [7]. Escapees from farms colonized wild habitats in many West European countries [7]. Since the 1930s, thousands of American mink were also deliberately released into the wild in the former Soviet Union to form a harvestable population [8]. As a consequence of these two pathways of introduction, the European range of the American mink extended very quickly [9] and at present it inhabits many riparian and mesic habitats in the vast majority of European countries [7, 10, 11]. Although the catastrophic effect of the American mink invasion on the European mink is well documented [12–14], less attention has been paid to its negative effects on other species like the European polecat, Mustela putorius, despite being the carnivore species most affected by it [15].
The European polecat is a medium-sized mustelid widespread in the western Palaearctic [16]. It inhabits a wide range of habitats, including riparian habitat, bog and deciduous forests and grasslands, as well as rural areas including farms and villages [17–19]. In these wild range of habitats polecats feed on a wide spectrum of prey including small mammals, rabbits, birds, reptiles, amphibians and ungulate carcasses [17, 20]. Although classified as a least concern species [21] its populations have been declining over the last few decades in most European countries due to habitat alteration as the drainage of wetlands and changes in the agricultural landscape, direct persecution, prey decline, hybridization with ferrets and the invasion of the American mink [22–26].
The American mink and polecats’ spatial and trophic niches partially overlap [27, 28] potentially resulting in strong competition between both species especially during periods of low food abundance (winter or drought). The spread of the American mink was accompanied by a significant reduction in polecat density in some regions [15, 24, 26] and by the occurrence of a male-biased sex ratio in polecat populations [29–32]. Whether these alterations may have affected the genetic patterns of the polecat populations in terms of diversity and structure, is still to be disentangled. The Białowieża Primeval Forest (BPF) in NE Poland represents an excellent scenario where to investigate such impact.
BPF is one of the last non-altered habitats in Europe, with low hunting or poaching pressure on small mustelids, a high density of polecat preys and with no ferrets or European mink living there (thus free of potential hybridization polecat—related species) [33]. The American mink population was established in BPF in the late 1970s [9, 10, 34] and since then the population has been increasing in size and its density has reached eight individuals per 10 km of river bank on some rivers [28]. After the American mink invasion, the polecat was pushed mainly to small streams and bog ash-alder forest, as the American mink prefers medium-size rivers [28]. However, the increasing American mink populations also colonized some of the small streams from where the polecat density decreased or the species disappeared [30]. Forty years after the American mink invasion however, both species still coexist in BPF, despite the very high food niche overlap between both predators [35].
In this study we used eleven autosomal microsatellite markers and a fragment of the mitochondrial DNA to investigate the effects of the American mink invasion on the neutral genetic diversity of the polecat population in the Białowieża Primeval Forest. We genotyped the historical (pre-American-mink-arrival) and current (post-American-mink-arrival) polecat populations in BPF to analyse: i) potential changes in the levels and distribution of genetic diversity due to the American mink invasion, and ii) changes in the demographic history of the polecat population. Additionally, we genotyped samples from other locations in order to understand the current genetic structure of the polecat population in Poland.
Material and methods
Sample collection, DNA extraction and amplification
A total of 92 individuals were collected during the period between 2000 and 2012 from the areas of Białowieża Primeval Forest (BPF, n = 51, including two samples from Belarussian part of BPF), Biebrza river basin (BIE, n = 20), Narew river basin (NAR, n = 8), Augustów Forest (AUG, n = 3), Drawa and Warta river basins (DRA, n = 5) and Bug river basin (BUG, n = 4) (contemporary samples) and one with unknown location (OTH) (Fig 1). Muscle or ear samples were collected from occasional road casualties or animals found dead in the forest or in the villages (all sites). The hair samples were collected from live-trapped polecats (in BPF) and polecats captured unintentionally during various projects studying American mink biology conduced in all sites (except AUG and BUG). This study did not require permits to approve the field site access. All samples were collected during other projects under permission granted by local and government authorities (Ministry of Environment Protection: DLOPiKog. 4201/143/00 and DLgl-6713-35/09/1399, Poviat Starosty in Hajnówka: RS6121/1/2000).
AUG–Augustów Forest; NAR-BIE–Narew and Biebrza river basins; BPF–Białowieża Primeval Forest; BUG–Bug river basin; DRA–Drawa and Warta river basins. Background map: Natural Earth (public domain).
All tissue and hair samples were stored at -20°C prior to DNA extraction. Additionally, DNA samples were obtained from 116 museum skulls from BPF stored at the zoological collection of Mammal Research Institute PAS collected over the period 1959–1998, and originated from either road kills or animals shot by hunters. Material from historical samples was obtained from the turbinals in the nasal cave. In the case of BPF, both contemporary and museum samples combined represents a time span of 50 years. (See S1 Table for a complete description of the samples). Following the approach described by [36] and under the hypothesis of a strong effect of the harsh weather in the polecat population dynamics, we checked the temporal stability of the genetic frequencies in BPF. With the mean lifespan of the polecat of between 3 to 4 years (maximal life span is 8 years), and the age of maturation one year [37], and being a species with overlapping generations, we could define a cohort in periods of four years. Consequently, samples from BPF were subdivided in different cohorts comprising all individuals sampled within periods of four years. We used a one-year sliding window strategy in order to account for any unexpected variance. Only samples with n ≥ 8 individuals were considered for the analyses. Additionally, we could define a cohort integrated by individuals from NAR-BIE sampled between 2008–2011 (n = 21 in the case of mtDNA; n = 25 in the case of microsatellites) in order to test for spatial fluctuations (S2 Table).
DNA from fresh tissues (mussel, ear, and hair) was extracted using the DNA Tissue Kit (QIAGEN) following the manufacturer’s instructions. Samples of the turbinals were extracted from the nasal cave with the help of a stick. Due to the softness of this bone tissue, each sample could be powdered manually inside the tube used for its digestion by using a plastic stick. DNA was extracted using the QIAamp DNA Investigator Kit (QIAGEN) following the manufacturer’s instructions. Bone extractions were carried out in a separate room specially conditioned for working with non-invasive and ancient material. All the manipulations were made in a laminar-flow hood that was UV irradiated previous to and after any manipulation. Negative extraction controls were performed in every extraction of 23 samples to monitor possible contamination. Among the 150 museum samples, 92 rendered enough DNA for the microsatellite study (77%) and 63 were sequenced for the mtDNA.
Samples were genotyped with twelve microsatellite markers. Six of them were developed for the American mink (Mvi57, Mvi111, Mvi1006, Mvi1341, Mvis002 and Mvis072), five of them were developed for the polecat (MP07, MP22, MP28, Mp3.1 and Mp3.18), and one was developed for the European mink, M. lutreola (MLUT25). Twelve additional microsatellite markers developed for the American mink had also been assayed in an initial set of 18 random samples and discarded due to spurious results (see S3 Table for a complete description of the markers and references).
With the set of twelve microsatellite that rendered good results, three different multiplex were carried out using a Multiplex PCR Kit (QIAGEN) in final reaction volumes of 5 μl for the fresh samples and 8 μl for samples extracted from turbinals, containing a final concentration 1x QIAGEN Multiplex PCR Kit (Qiagen), (0.2 μM) of each primer, 0.25 μg/ μl BSA (Fermentas) and 30 ng of DNA (for museum samples 2 μl of DNA extraction were used) in a (DNA Engine Dyad® BIO-RAD) thermocycler. PCRs consisted of an initial denaturation step at 95°C for 15 minutes, followed by 30 cycles (33 cycles for museum samples) of 94°C for 30 s, 60°C for 90 s, and 72°C for 60 s, and a final extension at 60°C for 30 min. To monitor the possibility of allelic dropout related to low DNA quality and/or quantity in museum and hair samples these were amplified and genotyped three times each and for each multiplex. A high rate of allelic dropout was observed for the Mvis072 marker in samples from the museum so this marker was excluded from all analyses. A final dataset of eleven microsatellite markers was used for further analysis. Fragments were analysed in an ABI3130xl Genetic Anlyser (Applied Biosystems). Allele scoring was performed with the GeneMarker (v 1.85) software (SoftGenetics). Microsatellite genotypes are provided in S4 Table.
A fragment of 640 bp of the mtDNA control region was amplified in forward and reverse orientations using the primers LutF [25] and Mpu1R (5’-tgtgtgatcatgggctgatt-3’–the later designed with the help of Primer3 software. PCRs were performed in a final volume of of 10 μl (fresh samples) or 20 μl (museum samples) and comprised 3 μl (fresh samples) and 6 μl (museum samples) of DNA extract (3–10 ng—about 60 ng per reaction), 5 μl (fresh samples) and 10 μl (museum samples) HotStar Taq Master Mix Kit (Qiagen), 0.5 μM of each primer in final concentration. PCR cycling comprised an initial denaturation at 95°C for 15 min, followed by 35 (fresh samples) and 38 (museum samples) cycles at 94°C for 60 s, 56°C for 60 s, 72°C for 90 s and a final extension at 72°C for 10 min. PCR products were sequenced using the BigDye v 3.1 Terminator Cycle Sequencing Kit (Applied Biosystems) and an automated DNA fragment analyser (ABI-3130xl; Applied Biosystems, Inc.). Sequences were edited, assembled and aligned using the program Sequencher 4.9 (Gene Codes Corporation).
Data analyses
Only the cohorts defined in BPF and NAR-BIE were considered to have adequate sizes to perform population analyses on them. Samples from AUG, DRA and BUG (n ≤ 5 in all cases) were considered only in the analysis of population structure.
Mitochondrial DNA analyses.
Diversity. Haplotype and nucleotide diversity (π) and the number of segregating sites (S) were estimated and mtDNA haplotypes identified for the global polecat populations with DnaSp v5 [38]. Indices of genetic diversity were computed in ARLEQUIN 3.5 [39].
Population differentiation and genetic structure. We calculated ΦST and exact test of differences between the population pre and the population post arrival of the American mink (excluding the individuals from 1974 to 1997, as indicated before) using Arlequin 3.5 [39]. In order to test for fluctuations in the genetic frequencies through time we calculated pairwise ΦST and pairwise differences among all cohorts defined in BPF for every sliding window dataset. The potential effect of the arrival of the American mink on the gene frequencies of the polecat population was tested through an analysis of molecular variance (AMOVA) by pooling cohorts from BPF into pre- or post- American mink arrival for every sliding-window dataset using Arlequin 3.5. Any individual sampled between the years 1974 and 1997 was excluded from the AMOVA analyses as they belonged to the cohorts present during or immediately after the arrival of the American mink. We also included the cohort defined in NAR-BIE to test for contemporary fluctuations in space. All p values were corrected after Bonferroni to account for multiple comparisons. The significances of the observed ΦSTs were tested using 5000 random permutations of the data matrix.
Population demographic history. Past population dynamics of the polecat was investigated with a Bayesian Skyline Plot model using BEAST v1.8.1 [40]. We used a mutation rate of 7.244 x 10−8 substitutions/site/generation as estimated for Mustela erminea in [41] from a combined set of mitochondrial regions. To construct the BSP we assumed an HKY+G model of evolution, and a strict molecular clock which is the more robust method when analysing intraspecific data. Three MCMC chains from different starting points were run, each based on 30,000,000 generations, sampled every 1,000, with the first 3,000,000 discarded as burn-in. Visual inspection of the MCMC autocorrelation plots with Tracer v1.7 [42] showed that runs had converged to the equilibrium distribution. All runs had an effective sample size (ESS) of minimum 500.
Microsatellite markers.
Diversity. Observed and expected heterozygosities (Ho and He respectively) and heterozygote deficits, linkage disequilibrium and Hardy-Weinberg (HW) equilibrium were tested for BPF and NAR-BIE with the probability test of Genepop v3.5 [43] using a Markov chain method to estimate without bias the exact p values of these tests [44]. Significance levels were adjusted with sequential Bonferroni correction in order to correct for the effect of multiple tests [45]. Genetic diversity within groups was estimated as the number of allele per locus (k), and the allelic richness (AR) using FSTAT [46]. Levels of allelic richness and He between groups were compared using a Wilcoxon sign-rank test.
Population differentiation and genetic structure. We calculated FST and exact test of differences between the population pre and the population post arrival of the American mink using Arlequin 3.5. Using the same scheme of sliding windows as for mtDNA, we calculated pairwise FST value [47] among all the cohorts defined in BPF for every sliding window dataset using Arlequin 3.5. We also included the cohort defined in NAR-BIE to test for contemporary fluctuations in space. All p values were corrected after Bonferroni to account for multiple comparisons. Following a similar scheme than for mtDNA, AMOVA were performed using Arlequin 3.5. We preferred FST to RST distances as the latter would underestimate differentiation when populations are not highly structured [48] whereas frequency-based estimates have been shown to be more appropriate when comparing closely related populations [49]. Correlation analysis between genetic and geographical distances (Mantel test) between all pairs of contemporary individuals was calculated with GenePop 3.4 [50].
We further investigated the pattern of spatial genetic structure at present using data from microsatellites. For this we conducted a spatial principal component analysis (sPCA) for BPF (including individuals sampled in the period 2009–2012) and NAR-BIE site (including individuals sampled in the period 2008–2011) using the Adegenet (version) package [51] for R. The sPCA identifies cryptic spatial patterns of genetic structuring across the landscape, and accounts for spatial autocorrelation issues associated with neighbor-mating and sample distribution [52]. It uses Moran’s I index of spatial autocorrelation to compare allele frequencies observed in individuals at given spatial locations with those of individuals at neighbouring sites [51]. Two tests were used to detect global (e.g. clines and patches) and local structure (when spatially close individuals are genetically dissimilar).
We performed a clustering analysis of all the individuals sampled in this study using STRUCTURE v2.3 [53]. This version allows structure to be detected at lower levels of divergence than the original model. Values of K = 1 to K = 7 were tested. In a second step, we also performed the clustering analyses including only all individuals from BPF, testing values from K = 1 to K = 5. To ensure consistency of the results, we performed 10 independent runs per K tested in all cases. Each Markov chain was run for 106 steps after a burn-in period of 105 steps. All chains were run using the F model for correlations of allele frequencies across clusters [54]. Any possible genuine multi-modality of the data was investigated using the Greedy algorithm implemented in CLUMPP [55]. The figure was drawn using the package CLUMPAK [56].
Population demographic history. The occurrence of a genetic bottleneck in the recent past was investigated in the contemporary sample using the program BOTTLENECK [57]. The program was run under the two-phase model that is supposed to fit microsatellite evolution better [58] i.e. with 95% and 78% of the stepwise mutation model with a variance for mutation size set to 12, following what has recently been performed for the same species [22]. Additionally, the method assesses the distribution of allele frequencies, expected to be L-shaped under mutation-drift equilibrium [59]. We estimated the effective population sizes of the populations pre- and post-mink arrival in BPF using the linkage disequilibrium (LD) method [60], as implemented in NeEstimator V2.1 [61]. The demographic history was further investigated using the hierarchical Bayesian model based on Markov Chain Monte Carlo (MCMC) and coalescent theory implemented in MSVAR v1.3 [62, 63]. This method has been proven to precisely estimate the parameters that characterize the demographic history provided that the change in population size was neither too recent nor too weak, and to outperform both the M-ratio test [64] and the BOTTLENECK method [59] in the detection of population declines [65]. It allows the estimation of current and ancestral population sizes (N1 and N0, respectively), the mutation rate (μ) and the time since the population started changing (T). We used wide lognormal priors with large variances to affect posterior distributions as little as possible (as used in [66]). A generation time of 1 year was assumed [25]. Three independent runs from different starting points and combinations of priors and hyper-priors were conducted in order to check the robustness of the results by assessing the convergence of the chains. We ran a total of 5 x 109 iterations thinned by 2 x 105, and the first 10% was eliminated as burn-in. A final amount of 5 x 104 sampling points was used to build the posterior distributions. We assessed convergence with the Gelman-Rubin statistic, we calculated the 95% High Posterior Density (HPD) intervals and plotted the results using the R packages Coda [67] and Locfit [68]. Once convergence was assessed, we combined the three chains to get a final dataset of 15 x 104 sampling points to build a single, definite posterior distribution. We visualized the trace plots of the MCMC chains and calculated the mean values and the 90% high probability density (HPD) of the posterior distribution for each parameter with the program Tracer 1.7 [42].
Results
Diversity
Mitochondrial DNA.
We obtained sequences from the control region in 149 samples from all locations. Among them, 45 were from before (all of them from BPF) and 84 were from after the American mink invasion (48 of them from BPF), 17 corresponded to individuals sampled in between (period 1974–1997), and three were from unknown date and/or origin. All sequences were deposited in GenBank under accession numbers OK644317-OK644331 and OM069433—OM069566. The length of the fragment was 532bp excluding the previously described polypyrimiden CnTn tract in the control region of polecats [22, 69, 70]. Those identified 17 segregating positions and 15 haplotypes, Hp1 to Hp15 (S5A Table). Six of them were found in a single individual (one of them in post-American mink BPF, one in pre-American mink BPF, one in the period in between in BPF, two in NAR, and one in BUG). Eight haplotypes were found in the population before the arrival of the American mink (eleven occurred in post-American mink BPF) whereas twelve where found in the post-American mink population (nine if we take only into account the individuals from BPF). The overall mean haplotype and nucleotide diversities and the average number of nucleotide differences were 0.75, 0.0034 and 1.83, respectively. The most common haplotype, Hp1, was shared by 47% of the individuals (60 out of 129). Apart from the singletons, only haplotypes Hp3 (n = 5), Hp7 (n = 3) and Hp13 (n = 10) were private from a single location, BPF (with H13 happening in pre-American mink BPF, one in the BPF in the period in between, and two in the post-American mink BPF population). Haplotype and nucleotide diversity (HD and ∏) in the polecat population were 0.82 and 0.0043 before, and 0.67 and 0.0028 after the arrival of the American mink (Table 1). This points to a reduction in the levels of mtDNA genetic diversity after the arrival of the American mink. This can be due to a more skewed distribution of haplotypes in the current population (see S5B Table). This difference still appears when considering only the individuals from BPF in the population after the arrival of the American mink (HD = 0.72, ∏ = 0.00278, Table 1).
n stands for the number of samples; N pol. sites, number of polymorphic sites.
Microsatellites.
The genotyping of the whole set of individuals (n = 208) with eleven markers rendered a total of 84 alleles. Number of alleles per locus ranged between five and ten, and global expected heterozygosity He was 0.65. The genotyping of the pre-American mink population (n = 88 individuals, all of them from BPF) with eleven markers rendered a total of 74 alleles. Number of alleles per locus ranged between four and ten and expected heterozygosity He was 0.63. The genotyping of the post-American mink population (n = 92 individuals) with eleven markers rendered a total of 80 alleles. Number of alleles per locus ranged between five and nine and expected heterozygosity He was 0.67. The genotyping of the BPF population after the arrival of the American mink (n = 51 individuals) with eleven markers rendered a total of 73 alleles. Number of alleles per locus ranged between four and nine and expected heterozygosity He was 0.66. Deviation from Hardy-Weinberg equilibrium was not detected in the populations (p > 0.05). When compared to the total post-American mink population, He was lower in historical BPF (Wilcoxon signed rank test, p < 0.001), and AR was similar (Wilcoxon signed rank test, p = 0.083). Expected heterozygosity was similar between the pre- and post-arrival mink population in BPF (Wilcoxon signed rank test, p = 0.067) and AR was lower in the historical population (Wilcoxon signed rank test, p = 0.032) (see Table 2). Finally, both He and AR were similar between contemporary BPF and BIE-NAR populations (He 0.63 and He = 0.66 Wilcoxon signed rank test, p = 1.00; and p = 0.083 for AR comparisons).
Population differentiation and genetic structure.
Mitochondrial DNA. The ΦST value between the pre and post arrival of the American mink populations was low but significant (ΦST = 0.08 p < 0.001). P value for the exact pairwise differences was as well significant (p < 0.001). This pattern was the same when considering only the individuals from BPF in the population post (ΦST = 0.07 p value < 0.001) and a significant p value for the exact pairwise differences (p < 0.001). This difference might be explained by the change in haplotype frequencies. Only nineteen out of 74 pairwise comparisons among cohorts in BPF and NAR-BIE sites were significant after Bonferroni correction for both ΦSTs and pairwise differences (S6 Table). Significant differences seem to particularly affect the cohorts by the end of the 60’s and the beginning of the 70’s. This is an interesting result as polecats and American mink started to coexist in the end of 70’s [9, 34]. AMOVA results indicated that the cohort explains a small although significant amount of the variance, but the group does not (the group being the populations pre- and post-American mink invasion). These analyses showed that the arrival of the American mink did not leave any imprint strong enough to be detected at the mitochondrial level, but for the shift in haplotype frequencies (S5B Table).
Microsatellites. The FST value between the pre and post arrival of the American mink populations was very low but significant (FST = 0.015 p < 0.001). Otherwise, the p value for the exact pairwise differences was not significant (p = 1.00). This pattern was the same when considering only the individuals from BPF in the population post arrival of the American mink (FST = 0.014 p < 0.001), and a very strong non-significant p value for the exact pairwise differences (p = 1.00). The exact test has been shown to be more powerful than the FST test [71], and this together with the very low FST value, suggest that if any differentiation is present it might be subtle. Thirty-five out of 98 pairwise comparisons among cohorts in BPF and NAR-BIE sites were significant after Bonferroni correction (S7 Table). As in the case of the mtDNA, there are some significant differences that mostly imply the cohorts by the end of the 60’s and the beginning of the 70’s, although no clear pattern of differentiation between the polecat populations pre- and post-American mink invasion emerges either with these markers. These slight differences could account for the significant FST p values when comparing the pre and post populations. As with mtDNA, the AMOVA results showed that the cohort explains a small although significant amount of the variance, but the group does as well in two out of the four waves defined by the sliding window. These results, suggest that the American mink could have had a temporal effect on the levels of genetic diversity but they did not leave an imprint strong enough to be detected by all the statistics applied here (Table 3). In addition, the polecat population in Poland does not show an IBD pattern (Mantel test, R = 0.07, p>0.99). As an alternative explanation, the markers used in this study might not be informative enough to unambiguously show the pattern of alterations that the invasion of the American mink produced in the genetic diversity of the polecat population.
Groups indicate pre- or post-American mink invasion populations. Populations in the table refer to the different cohorts.
The sPCA analysis including the contemporary BPF and NAR-BIE sites (Fig 2) showed no pattern of spatial structure at global or local scale (p = 0.27 and p = 0.74, respectively), in agreement with the non-significant FST value between them. The clustering analysis of all the individuals in BPF using the STRUCTURE algorithm did not show any pattern of structure. A similar absence of structure arose when the complete dataset was included in the analysis, comprising also individuals from AUG, DRA, BUG, and one individual from an unknown location (Fig 3).
a) Eigenvalue plot and b) screenplot show that the first axe is the most important explaining the genetic variation that is not statistically significant (p < 0.05). c) Scores in space; grey levels are used for different absolute values with black and white being well differentiated.
Each output represents the matrix of membership coefficients averaged over 40 independent runs with CLUMPP. Acronyms as in Fig 1.
Population demographic history.
Mitochondrial DNA. The analyses with BEAST was not able to detect a bottleneck signal, but suggested that the Ne in the polecat population has been high and mostly stable for the last 17.5 Ky (S1 Fig).
Microsatellites. The analyses with BOTTLENECK showed that the observed proportion of heterozygotes was not significantly different to that expected under equilibrium for the observed number of alleles under the two-phase model (TPM) with a 95% of SMM model (P = 0.97, Wilcoxon test) or with a 78% of stepwise mutation model (SMM) (P = 0.82, Wilcoxon test). The mode shift test showed a normal L-shaped distribution in both cases. The analyses rendered almost identical results for the historical population in BPF. Estimated effective population size for the population pre-dating the arrival of the American mink in BPF (Ne = 74.1, CI 57.8–98.7) was similar than that of the population after (Ne = 75.9, CI 53.4–119.9).
Using the coalescent-based approach implemented in MSVAR 1.3 we found evidence of a historical decline in the polecat population size. An ancestral population with Ne of 15,382 individuals (191–32,359,365 HPD 95%) suffered a reduction that brought the population to a Ne of 2,399 individuals (11.75–223,872 HPD 95%). This demographic process occurred around 7.8 ky ago (0.049–4.9x109 HPD 95%). The convergence among MCMC chains and the ESS values behaved better for the Ne estimated, ancestral and present, than for T. This, along with the wide confidence intervals obtained for T, suggests that the latter parameter could not be properly estimated from our data, and both the median and intervals for T should be taken with caution.
Discussion
The analyses of the polecat population in BPF before and after the arrival of the American mink, and of other additional populations with both microsatellite and mitochondrial markers suggested an almost absence of effects of the arrival of this non-native, invasive competitor on the genetic patterns of the polecat population in terms of both diversity and structure. This would be in agreement with recent data showing weak evidence that the American mink had a negative impact in the demography of the polecat in Poland [30].
Diversity of the polecat population in Poland
Levels of nuclear diversity in the present polecat population in Poland are in the highest values of the range when compared to other polecat populations [25] and considerable higher than levels found in the impoverished British population [22]. This occurs in spite of the fact that half the markers used in our study were not specifically designed for the polecat, while those used in the British population were [22]. This situation was expected, given the critical status of the British population by the beginnings of the 20th century [72]. Mitochondrial diversity in the polecat population from Poland is comparable to other polecat populations [25] although lower than in the British population, probably due to the hybridization with ferrets in the latter [22]. These levels of genetic diversity and the absence of any signal of a recent bottleneck in the Polish polecat population suggest that the population of polecats in Poland is not showing any sign of genetic decline, in contrasts with other populations in Europe (e.g. [25]).
No effect of the arrival of the American mink in BPF on the polecat genetic diversity and an ancient population decline
We were not able to find differences in the levels of diversity between the extant population and the population predating the arrival of the American mink, at any of both nuclear or mitochondrial levels. Although the timeframe considered before and after the arrival of the American mink is not long, it still includes 53 generations, considering one year the generation time of the polecat [25]. Other studies including a smaller number of generations, using a similar number of markers and analysing temporal genetic variation have been able to detect changes in genetic diversity and/or structure patterns (e.g. [3, 35]). It is probable that the American mink affected the sex ratio of the polecat in BPF [30], as in other sites in Europe (e.g. [15, 26, 29]). Otherwise, our results would suggest that they did not erode the levels of genetic diversity of the polecat in BPF, at least in terms of neutral diversity. This is further supported by the fact that Ne has remained similar. Adult sex ratio (ASR) has proven to be heavily shifted towards males in NE Poland (Zalewski et al. in prep.) and in Belarus this shift being up to an increase from 59% to a 95% of males in the population [73]. Analysis of polecat sex ratio shift in Europe suggests that the invasion of American mink was a driver causing these changes [29]. The interaction with external factors causing an important decrease in the female population results in a demographic imbalance that may have negative consequences for the viability of the populations affected (e.g. [74]. Theory indicates that skewed sex ratio reduces effective population size (Ne) and increases the deleterious effects of genetic drift. In the case of the polecat, one male mates with 1–3 females while females usually mate with one male [75]. If a significant reduction in the number of females occurred fewer males will be able to reproduce and thus contribute their genes to the following generation and this could affect levels of genetic diversity. This situation of reduced genetic diversity is not what we have found in the polecat population in BPF. It may be that there has not been enough time for the population to reach the equilibrium situation after the number of females were reduced and that any reduction in the levels of diversity would only be reflected in the future. However, since the arrival of the American mink to Eastern Poland in the late 70’s [34], enough polecat generations have passed (around 30 generations until 2012) to be able to detect changes in levels of diversity. Although our results suggested subtle allelic frequency changes around the 70’s, and that mitochondrial haplotype frequencies might have slightly changed, there is no clear pattern of differentiation between the population before and after the American mink invasion. Although very interesting and meriting further research, these observed changes in allelic frequencies at the end of the 60’s beginning of the 70’s could not be attributed to the arrival of the American mink. Mink arriving in the end of 70’s and its population increasing in the 80’s, the strongest competition between polecat and mink would be happening by the middle or the end of the 80’s [9]. It may also happen that the shift in the ASR in BPF was not strong enough to impact the genetic diversity of the population. On the other hand, even if the trophic niches of polecats and American mink are narrow and considerably overlap, they are able to reduce interspecies competition by using some mechanisms of food segregation [76]. This could act as an additional buffer on the impact of the invasion of the American mink in the polecat population.
On the other hand, the lack of genetic structure observed among populations from diverse areas of Poland, either as a result of a recent common origin of the potential populations or because they are connected by gene flow, would explain why genetic diversity could have been maintained. This lack of structure is remarkable given the geographical distance between the sampling locations (up to 700 km). The sex dispersing in the polecat is the male, while females remain more phylopatric [75]. They disperse mainly to mate in adjacent areas (the dispersal distance are not known), although in some cases they can move up to 35 km [77]. This gene flow may be favoured by the fact that polecats inhabit very different habitats, from riparian areas to forests and even villages [77]. This habitat plasticity would make the species more resilient to human occupation and the modification/fragmentation of the habitat, potentially allowing the connectivity among the different populations.
None of the methods used were able to detect a recent bottleneck in the polecat population. MSVAR was able to detect recent population reductions in otter and in the British polecat populations using a similar number of markers [22, 78], provided these reductions were important. This suggests that we can rule out the occurrence of a significant recent decrease in the polecat population, despite the wide HPD interval. The hunting bag of polecat in Poland increased from 300 in 1991–1992 to 2,400 polecats in 2007–2008, which may suggest an increase of polecat abundance, but this data should be treated with caution [79]. In accordance with our results and although accurate data on the census size of the polecat in Poland do not exist, indirect approaches suggest that the demographic changes suffered by the Polish and BPF polecat population have not been dramatic during the last century [30]. Otherwise, MSVAR detected an ancient bottleneck, a reduction to one sixth of the Polish polecat population occurring several thousand years ago. This coincides in time with the arrival of the Neolithic in Central Europe, which implied an important increase in human population [80]. The planet was already largely transformed by 3,000 years ago by humans [81], and some European mammals suffered range losses and significant declines starting around this time, including mustelids [82] and polecats may have been one of these species affected. Although polecats may adapt to very different habitat, including anthropized ones, they are still affected by human activities at present in some regions [83]. However, this demographic reduction was not detected with the analysis of the mitochondrial fragment. Mitochondrial DNA is expected to be more sensitive to changes in demography due to its ¼ Ne with respect to the nuclear genome. Otherwise, confidence intervals are big enough to infer that the bottleneck happened earlier in time, and the mtDNA fragment analysed is not informative enough to trace it. A bigger battery of nuclear markers as SNPs would be necessary to have a clearer picture on this question.
Conservation implications
A review on the polecat status in 34 countries found that populations were declining or suspected to be declining in 20 of them, including Poland [84]. However, in several cases the information based on expert opinion but not supported by the data, was insufficient to assess the status of the population [85], including status of polecats in Poland. Our results are positive news for the species in this area of Europe. Genetic diversity of the species in Poland seems not to be altered after the arrival of the American mink, probably due to this high level of connectivity among the populations as discussed above, and the partial habitat segregation of both species. This suggests that the Polish population has been genetically stable in the recent history. Additionally, the absence of ferrets in the area [33] make the hybridization with these close relatives impossible, as seen in other populations [22, 72], thus the integrity of the species is not threatened. Both aspects make us suggest the polecat population in Białowieża Primeval Forest and eventually, the Polish population, as a source for captive breeding and/or reintroductions in other areas where the species has been depleted as in the UK, provided the adequate genetic and ecological studies are conducted, including an assessment of potential local adaptations. Otherwise, a thorough study on the intensity of the population skew on the ASR and its potential genetic effects should be conducted before any management action is taken in this sense. Additionally, although our data suggest that the invasion of the American mink has had little genetic effect in the polecat population in Eastern Poland, it would be interesting to develop a significantly larger battery of markers, as thousands of SNPs along the genome, to fully understand the genetic effects of the invasion of the American mink in the patterns of genetic diversity of the European polecat population in Poland.
Supporting information
S1 Fig. Evolution of the effective population size Ne of the polecat population in Poland using the software BEAST.
https://doi.org/10.1371/journal.pone.0266161.s001
(PDF)
S1 Table. Complete list of samples used in this study.
https://doi.org/10.1371/journal.pone.0266161.s002
(XLSX)
S2 Table.
Sliding-window cohorts for A- microsatellites and B- mtDNA sequences. Samples were subdivided in cohorts of four years. n indicates the number of individuals in each cohort. Only cohorts integrated by eight or more individuals are listed and considered for the analyses (and thus included here).
https://doi.org/10.1371/journal.pone.0266161.s003
(XLSX)
S3 Table. Description of the microsatellites tested and used, and tested but not used in this study.
A) Number of alleles, He and Ho values for the eleven microsatellites for all the samples in this study. B) List of microsatellite markers tested but not finally used in this study.
https://doi.org/10.1371/journal.pone.0266161.s004
(XLSX)
S4 Table. Microsatellite genotypes of the individuals used in this study.
https://doi.org/10.1371/journal.pone.0266161.s005
(XLSX)
S5 Table.
A- mtDNA haplotypes found in this study. B- Distribution of the Haplotypes in the populations.
https://doi.org/10.1371/journal.pone.0266161.s006
(XLSX)
S6 Table. FST values among populations estimated with the 11 microsatellite markers.
https://doi.org/10.1371/journal.pone.0266161.s007
(XLSX)
S7 Table. Phist, and Phist and pairwise differences p-values among populations estimated with the fragment of mitochondrial control region sequenced in this study.
https://doi.org/10.1371/journal.pone.0266161.s008
(XLSX)
Acknowledgments
Special thanks to all people for help in sample collection. We would like to thank the two anonymous reviewers for their suggestions and comments and to R. Symonds for proofreading the manuscript.
References
- 1. Vitousek P, D’Antonio C, Loope L, Rejmanek M, Westbrooks R. Introduced Species: A Significant Component of Human-Caused Global Change. New Zealand Journal of Ecology. 1996;21.
- 2.
Lockwood JL, Hoopes MF, Marchetti MP. Invasion ecology: Blackwell Publishing; 2008.
- 3. Martinez-Cruz B, Godoy JA, Negro JJ. Population fragmentation leads to spatial and temporal genetic structure in the endangered Spanish imperial eagle. Molecular Ecology. 2007;16(3):477–86. PubMed PMID: WOS:000243755800002. pmid:17257107
- 4. Poulakakis N, Antoniou A, Mantziou G, Parmakelis A, Skartsi T, Vasilakis D, et al. Population structure, diversity, and phylogeography in the near-threatened Eurasian black vultures Aegypius monachus (Falconiformes; Accipitridae) in Europe: insights from microsatellite and mitochondrial DNA variation. Biological Journal of the Linnean Society. 2008;95(4):859–72. PubMed PMID: WOS:000261133800017.
- 5. Campos PF, Kristensen T, Orlando L, Sher A, Kholodova MV, Gotherstrom A, et al. Ancient DNA sequences point to a large loss of mitochondrial genetic diversity in the saiga antelope (Saiga tatarica) since the Pleistocene. Molecular Ecology. 2010;19(22):4863–75. PubMed PMID: WOS:000283986700005. pmid:20874761
- 6. Naderi S, Rezaei HR, Pompanon F, Blum MGB, Negrini R, Naghash HR, et al. The goat domestication process inferred from large-scale mitochondrial DNA analysis of wild and domestic individuals. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(46):17659–64. PubMed PMID: WOS:000261225600019. pmid:19004765
- 7. Bonesi L, Palazon S. The American mink in Europe: Status, impacts, and control. Biological Conservation. 2007;134(4):470–83. PubMed PMID: WOS:000244769800002.
- 8.
Geptner VG, Naumov NP. Mammals of the Soviet Union. Moskva: 1967.
- 9. Brzeziński M, Żmihorski M, Zarzycka A, Zalewski A. Expansion and population dynamics of a non-native invasive species: the 40-year history of American mink colonisation of Poland. Biological Invasions. 2019;21(2):531–45.
- 10. Brzezinski M, Pyrlik J, Churski M, Komar E, Zalewski A. The influence of American mink odour on the spatial distribution and behaviour of water voles. Ethology. 2019;125(11):791–801. PubMed PMID: WOS:000480193100001.
- 11. Brzeziński M, Żmihorski M, Nieoczym M, Wilniewczyc P, Zalewski A. The expansion wave of an invasive predator leaves declining waterbird populations behind. Diversity and Distributions. 2020;26(1):138–50.
- 12. Maran T, Kruuk H, Macdonald DW, Polma M. Diet of two species of mink in Estonia: displacement of Mustela lutreola by M-vison. Journal of Zoology. 1998;245:218–22. PubMed PMID: WOS:000075199000013.
- 13. Santulli G, Palazon S, Melero Y, Gosalbez J, Lambin X. Multi-season occupancy analysis reveals large scale competitive exclusion of the critically endangered European mink by the invasive non-native American mink in Spain. Biological Conservation. 2014;176:21–9. PubMed PMID: WOS:000340223500003.
- 14. Sidorovich VE, Polozov AG, Zalewski A. Food niche variation of European and American mink during the American mink invasion in north-eastern Belarus. Biological Invasions. 2010;12(7):2207–17. PubMed PMID: WOS:000278897800025.
- 15. Melero Y, Plaza M, Santulli G, Saavedra D, Gosalbez J, Ruiz-Olmo J, et al. Evaluating the effect of American mink, an alien invasive species, on the abundance of a native community: is coexistence possible? Biodiversity and Conservation. 2012;21(7):1795–809. PubMed PMID: WOS:000304171900008.
- 16.
Mitchell-Jones AJ, Amori G, Bogdanovicz W, Krystufek B, Reijnders PJH, Spitzenberger F, et al. The Atlas of European mammals. London: T. & A. D. Poyser Ltd; 1999.
- 17. Brzezinski M, Marzec M, Zmihorski M. Spatial distribution, activity, habitat selection of American mink (Neovison vison) and polecats (Mustela putorius) inhabiting the vicinity of eutrophic lakes in NE Poland. Folia Zoologica. 2010;59(3):183–91. PubMed PMID: WOS:000282860400002.
- 18. Mestre FM, Ferreira JP, Mira A. Modelling the distribution of the European Polecat Mustela putorius in a Mediterranean agricultural landscape. Revue D Ecologie-La Terre Et La Vie. 2007;62(1):35–47. PubMed PMID: WOS:000248324300003.
- 19. Virgos E. Association of the polecat Mustela putorius in eastern Spain with montane pine forests. Oryx. 2003;37(4):484–7. PubMed PMID: WOS:000186977300027.
- 20. Santos MJ, Matos HM, Baltazar C, Grilo C, Santos-Reis M. Is polecat (Mustela putorius) diet affected by "mediterraneity"? Mammalian Biology. 2009;74(6):446–53. PubMed PMID: WOS:000271488600003.
- 21. Skumatov D, Abramov AV, Herrero J, Kitchener A, Maran T, Kranz A, et al. Mustela putorius. The IUCN Red List of Threatened Species 2016: e.T41658A45214384 2016 [updated 29 July 2021]. Available from: https://doi.org/10.2305/IUCN.UK.2016-1.RLTS.T41658A45214384.en.
- 22. Costa M, Fernandes C, Birks JDS, Kitchener AC, Santos-Reis M, Bruford MW. The genetic legacy of the 19th-century decline of the British polecat: evidence for extensive introgression from feral ferrets. Molecular Ecology. 2013;22(20):5130–47. PubMed PMID: WOS:000325550000007. pmid:24050727
- 23. Fernandes CA, Ginja C, Pereira I, Tenreiro R, Bruford MW, Santos-Reis M. Species-specific mitochondrial DNA markers for identification of non-invasive samples from sympatric carnivores in the Iberian Peninsula. Conservation Genetics. 2008;9(3):681–90. PubMed PMID: WOS:000255191000018.
- 24.
MacDonald DW, Thom MD. Alien carnivores: unwelcome experiments in ecological theory. In: Gittleman JL, Funk SM, Macdonald DW, Wayne RK, editors. Carnivore Conservation. Conservation Biology Series. 52001. p. 93–122.
- 25. Pertoldi C, Breyne P, Cabria MT, Halfmaerten D, Jansman HAH, Van Den Berge K, et al. Genetic structure of the European polecat (Mustela putorius) and its implication for conservation strategies. Journal of Zoology. 2006;270(1):102–15. PubMed PMID: WOS:000239778900012.
- 26. Sidorovich V, MacDonald DW. Density dynamics and changes in habitat use by the European mink and other native mustelids in connection with the American mink expansion in Belarus. Netherlands Journal of Zoology. 2001;51(1):107–26. PubMed PMID: WOS:000169673400008.
- 27. Harrington LA, Macdonald DW. Spatial and temporal relationships between invasive American mink and native European polecats in the southern United Kingdom. Journal of Mammalogy. 2008;89(4):991–1000. PubMed PMID: WOS:000258765000020.
- 28. Sidorovich VE, Jedrzejewska B, Jedrzejewski W. Winter distribution and abundance of mustelids and beavers in the river valleys of Bialowieza Primeval Forest. Acta Theriologica. 1996;41(2):155–70. PubMed PMID: WOS:A1996UW16400005.
- 29. Barrientos R. Adult sex-ratio distortion in the native European polecat is related to the expansion of the invasive American mink. Biological Conservation. 2015;186:28–34. PubMed PMID: WOS:000355061300004.
- 30. Brzezinski M, Zarzycka A, Diserens TA, Zalewski A. Does the American mink displace the European polecat? A need for more research on interspecific competition between invasive and native species. European Journal of Wildlife Research. 2021;67(4). PubMed PMID: WOS:000669205700001.
- 31.
Danilov PI, Tumanov IL. Mustelids of north-eastern of SSSR. Leningrad: 1976.
- 32. Sidorovich VE. Seasonal variation in the feeding habits of riparian mustelids in river valleys of NE Belarus. Acta Theriologica. 2000;45(2):233–42. PubMed PMID: WOS:000088104800009.
- 33. Jędrzejewska B, Jędrzejewski W, editors. Predation in Vertebrate Communities1998: Ecological Studies.
- 34. Ruprecht AL, Buchalczyk T, Wojcik JM. The occurrence of minks (Mammalia: Mustelidae) in Poland. Prz zool. 1983;27:87–99.
- 35. Zalewski A, Zalewska H, Lunneryd SG, Andre C, Mikusinski G. Reduced Genetic Diversity and Increased Structure in American Mink on the Swedish Coast following Invasive Species Control. Plos One. 2016;11(6). PubMed PMID: WOS:000378212800062. pmid:27333328
- 36. Balloux F, Lugon-Moulin N. The estimation of population differentiation with microsatellite markers. Molecular Ecology. 2002;11(2):155–65. PubMed PMID: WOS:000173726200001. pmid:11856418
- 37. Weber D. Population—Biological notes on polecats (Mustela putorius L) in Switzerland. Zeitschrift Fur Jagdwissenschaft. 1989;35(2):86–99. PubMed PMID: WOS:A1989AJ23900002.
- 38. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25(11):1451–2. PubMed PMID: WOS:000266109500026. pmid:19346325
- 39. Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evolutionary Bioinformatics. 2005;1:47–50. PubMed PMID: WOS:000207065900004.
- 40. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian Phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution. 2012;29(8):1969–73. PubMed PMID: WOS:000307171300008. pmid:22367748
- 41. Martinkova N, McDonald RA, Searle JB. Stoats (Mustela erminea) provide evidence of natural overland colonization of Ireland. Proceedings of the Royal Society B-Biological Sciences. 2007;274(1616):1387–93. PubMed PMID: WOS:000246478500006. pmid:17412682
- 42. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7. Systematic Biology. 2018;67(5):901–4. PubMed PMID: WOS:000443580600012. pmid:29718447
- 43. Raymond M, Rousset F. GENEPOP (version-1.2)—Population genetics software for exact tests and ecumenicism. Journal of Heredity. 1995;86(3):248–9. PubMed PMID: WOS:A1995RB30200017.
- 44. Guo S-W, Thompson E. Performing the Exact Test of Hardy-Weinberg Proportion for Multiple Alleles. Biometrics. 1992;48:361–72. pmid:1637966
- 45. Rice WR. Analyzing tables of statistical tests. Evolution. 1989;43(1):223–5. PubMed PMID: WOS:A1989R828900018. pmid:28568501
- 46. Goudet J. FSTAT (Version 1.2): A computer program to calculate F-statistics. Journal of Heredity. 1995;86(6):485–6. PubMed PMID: WOS:A1995TL74700013.
- 47. Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38(6):1358–70. PubMed PMID: WOS:A1984TY40400017. pmid:28563791
- 48. Balloux F, Goudet J. Statistical properties of population differentiation estimators under stepwise mutation in a finite island model. Molecular Ecology. 2002;11(4):771–83. PubMed PMID: WOS:000175250300011. pmid:11972763
- 49. Paetkau D, Waits LP, Clarkson PL, Craighead L, Strobeck C. An empirical evaluation of genetic distance statistics using microsatellite data from bear (Ursidae) populations. Genetics. 1997;147(4):1943–57. PubMed PMID: WOS:A1997YK65400035. pmid:9409849
- 50. Rousset F. GENEPOP ’ 007: a complete re-implementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources. 2008;8(1):103–6. PubMed PMID: WOS:000253827100016. pmid:21585727
- 51. Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008;24(11):1403–5. PubMed PMID: WOS:000256169300015. pmid:18397895
- 52. Schwartz MK, McKelvey KS. Why sampling scheme matters: the effect of sampling scheme on landscape genetic results. Conservation Genetics. 2009;10(2):441–52. PubMed PMID: WOS:000263869100016.
- 53. Hubisz MJ, Falush D, Stephens M, Pritchard JK. Inferring weak population structure with the assistance of sample group information. Molecular Ecology Resources. 2009;9(5):1322–32. PubMed PMID: WOS:000268855000004. pmid:21564903
- 54. Falush D, Stephens M, Pritchard JK. Inference of population structure using multilocus genotype data: Linked loci and correlated allele frequencies. Genetics. 2003;164(4):1567–87. PubMed PMID: WOS:000185248000029. pmid:12930761
- 55. Jakobsson M, Rosenberg NA. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics. 2007;23(14):1801–6. PubMed PMID: WOS:000249248300012. pmid:17485429
- 56. Kopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I. Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Molecular Ecology Resources. 2015;15(5):1179–91. PubMed PMID: WOS:000359631600017. pmid:25684545
- 57. Cornuet JM, Luikart G. Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics. 1996;144(4):2001–14. PubMed PMID: WOS:A1996VY93100062. pmid:8978083
- 58. Dirienzo A, Peterson AC, Garza JC, Valdes AM, Slatkin M, Freimer NB. Mutational processes of simple-seqiemce repeat loci in human populations. Proceedings of the National Academy of Sciences of the United States of America. 1994;91(8):3166–70. PubMed PMID: WOS:A1994NF96800063. pmid:8159720
- 59. Luikart G, Allendorf FW, Cornuet JM, Sherwin WB. Distortion of allele frequency distributions provides a test for recent population bottlenecks. Journal of Heredity. 1998;89(3):238–47. PubMed PMID: WOS:000074214900008. pmid:9656466
- 60. Hill WG. Estimation of effective population size from data on linkage disequilibrium. Genetical Research. 1981;38(3):209–16. Epub 2009/04/14.
- 61. Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Molecular Ecology Resources. 2014;14(1):209–14. pmid:23992227
- 62. Beaumont MA. Detecting population expansion and decline using microsatellites. Genetics. 1999;153(4):2013–29. PubMed PMID: WOS:000084079300044. pmid:10581303
- 63. Storz JF, Beaumont MA. Testing for genetic evidence of population expansion and contraction: An empirical analysis of microsatellite DNA variation using a hierarchical Bayesian model. Evolution. 2002;56(1):154–66. PubMed PMID: WOS:000174248200014. pmid:11913661
- 64. Garza JC, Williamson EG. Detection of reduction in population size using data from microsatellite loci. Molecular Ecology. 2001;10(2):305–18. PubMed PMID: WOS:000167779400004. pmid:11298947
- 65. Girod C, Vitalis R, Leblois R, Freville H. Inferring Population Decline and Expansion From Microsatellite Data: A Simulation-Based Evaluation of the Msvar Method. Genetics. 2011;188(1):165–U287. PubMed PMID: WOS:000290276900014. pmid:21385729
- 66. Hu YB, Qi DW, Wang HJ, Wei FW. Genetic evidence of recent population contraction in the southernmost population of giant pandas. Genetica. 2010;138(11–12):1297–306. PubMed PMID: WOS:000285749300020. pmid:21120682
- 67. Plummer M, Best N, Cowles K, Vines K. CODA: convergence diagnosis and output analysis for MCMC. R News. 2006;6(1):7–11.
- 68. Loader CR. Local likelihood density estimation. Ann Statist. 1996;24(4):1602–18.
- 69. Davison A, Birks JDS, Griffiths HI, Kitchener AC, Biggins D, Butlin RK. Hybridization and the phylogenetic relationship between polecats and domestic ferrets in Britain. Biological Conservation. 1999;87(2):155–61. PubMed PMID: WOS:000077491900001.
- 70. Davison A, Griffiths HI, Brookes RC, Maran T, Macdonald DW, Sidorovich VE, et al. Mitochondrial DNA and palaeontological evidence for the origins of endangered European mink, Mustela lutreola. Animal Conservation. 2000;3:345–55. PubMed PMID: WOS:000165205800007.
- 71. Goudet J, Raymond M, de Meeüs T, Rousset F. Testing Differentiation in Diploid Populations. Genetics. 1996;144(4):1933. pmid:8978076
- 72.
Birks JDS, Kitchener AC. The distribution and status status of the polecat Mustela putorious in Britain in the 1990s. London: The Vincent Wildlife Trust, 1999.
- 73. Sidorovich V, Kruuk H, Macdonald DW. Body size, and interactions between European and American mink (Mustela lutreola and M-vison) in Eastern Europe. Journal of Zoology. 1999;248:521–7. PubMed PMID: WOS:000082062700011.
- 74. Grayson KL, Mitchell NJ, Monks JM, Keall SN, Wilson JN, Nelson NJ. Sex Ratio Bias and Extinction Risk in an Isolated Population of Tuatara (Sphenodon punctatus). Plos One. 2014;9(4). PubMed PMID: WOS:000334160900106. pmid:24714691
- 75. Lode T. Mating system and genetic variance in a polygynous mustelid, the European polecat. Genes & Genetic Systems. 2001;76(4):221–7. PubMed PMID: WOS:000171979300002. pmid:11732630
- 76. Zalewski A, Szymura M, Kowalczyk R, Brzeziński M. Low individual diet variation and high trophic niche overlap between the native polecat and invasive American mink. Journal of Zoology. 2021;314(2):151–61.
- 77. Blandford PRS. Biology of the polecat Mustela putorius—A literature review. Mammal Review. 1987;17(4):155–98. PubMed PMID: WOS:A1987L569200001.
- 78. Hajkova P, Pertoldi C, Zemanova B, Roche K, Hajek B, Bryja J, et al. Genetic structure and evidence for recent population decline in Eurasian otter populations in the Czech and Slovak Republics: implications for conservation. Journal of Zoology. 2007;272(1):1–9. PubMed PMID: WOS:000245745300001.
- 79.
Kamieniarz R, Panek M. Zwierzęta łowne w Polsce na przełomie XX i XXI wieku [Game animals in Poland at the turn of the 20th and 21st century]. Czempiń: Stacja Badawcza OHZ PZŁ; 2008.
- 80. Gignoux CR, Henn BM, Mountain JL. Rapid, global demographic expansions after the origins of agriculture. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(15):6044–9. PubMed PMID: WOS:000289413600029. pmid:21444824
- 81. Stephens L, Fuller D, Boivin N, Rick T, Gauthier N, Kay A, et al. Archaeological assessment reveals Earth’s early transformation through land use. Science. 2019;365(6456):897. pmid:31467217
- 82. Crees JJ, Carbone C, Sommer RS, Benecke N, Turvey ST. Millennial-scale faunal record reveals differential resilience of European large mammals to human impacts across the Holocene. Proceedings of the Royal Society B-Biological Sciences. 2016;283(1827). PubMed PMID: WOS:000375732500020. pmid:27009229
- 83.
Costa M, Fernandes C, Santos-Reis M. Ecology and conservation of the polecat Mustela putorius (Linnaeus, 1758) in Portugal: a review. In: RuizGonzalez A, LopezDeLuzuriaga J, Rubines J, editors. Conservation and Management of Semi-Aquatic Mammals of Southwestern Europe. Munibe Monographs-Nature Series. 32014. p. 79–87.
- 84. Croose E, Duckworth JW, Ruette S, Skumatov DV, Kolesnikov VV, Saveljev AP. A review of the status of the Western polecat Mustela putorius: a neglected and declining species? Mammalia. 2018;82(6):550–64. PubMed PMID: WOS:000449147100004.
- 85. Hofmeester TR, Dijkstra V, Dekker JJA, van der Meij T, Broekhuizen S. The status of the Dutch polecat population: correction of a recently published error. Mammalia. 2019;83(5):453–4. PubMed PMID: WOS:000480513300005.