GENETIC DIVERSITY AND STRUCTURE OF THE BLACK GROUSE LYRURUS TETRIX LINNAEUS, 1758 POPULATION IN BELARUS

It is known that black grouse is a valuable resource species of the wild fauna of Belarus. The Belarusian population went through the stages of population decline and redistribution into new agrarian landscape territories – extensive anthropogenic involvement transformed significant parts of the species’ habitat in the course of large-scale land reclamation campaigns, which originated in 1950s. In order to rationally use the preserved black grouse subpopulations, an assessment of the level of their genetic diversity and degree of differentiation was made. For the latter purpose, microsatellite analysis was utilized. It was found that at the present stage the black grouse population has a sufficient level of adaptability (based on indicators of genetic diversity and effective population size) necessary to maintain viability in the foreseeable future.

One of the preferred habitats of this species in Belarus -swampland -suffered a significant reduction in its total area in the course of large-scale drainage reclamation efforts, starting in 1950s. About 700 thousand hectares of bogs were drained for agricultural needs in Belarusian Polesie alone, of which more than 80 % were in the Pripyat basin [15]. The density of black grouse in the country almost halved in 1970s as compared to 1950s as a result of intensive land reclamation and agricultural development of natural lands with structural indicators optimal for black grouse (a combination of open spaces with a certain type of tree and shrub vegetation) [16][17][18].
In that twenty-year period, due to the reduction in the area of natural habitats, the black grouse began to inhabit local agrolandscape. The black grouse is well suited to live in conditions of extensive farming. In this connection, by the middle, and especially towards the end of 1980s, stabilization of the number and increase in the density of the black grouse population was noted in Belarus. The number of black grouse in that period counted in the range of 45-54 thousand individuals [19]. The local population maintained those approximate numbers until the late 1990s.
A steady downward trend in population numbers for black grouse emerged in Belarus in 2000s. 2008 saw a reduction of Belarussian black grouse population numbers from their 2001 values by 21 %, and 2014 -a reduction of 30.4 % [20][21][22].
The decline in the number of black grouse that began in the last decade is generally tied to farming intensification. A statistically significant negative correlation was found between the density of black grouse and the area of arable land in the Grodno region (r = -0.70; p < 0.05). An increase in the predators' numbers such as the fox and the northern goshawk is an additional factor contributing to the decline in the numbers of black grouse. Until recently, the increased number of wild boar, which is dangerous for all land-nesting birds, was a very significant threat factor, but in recent years, due to mass shooting (the fight against ASF, since 2013), this factor's role has decreased. The number of wild boars in Belarus fell from 80.4 thousand in 2013 to 7.8 thousand in April 2014. At the end of 2014, the number of wild boar counted approximately 8.6 thousand individuals, and in 2015 -8.0 thousand [23]. In 2016-2018 the number of wild boars ranged between 2.6 thousand and 2.8 thousand individuals [24]. Thus, at present, the number of wild boars has decreased approximately by a factor of 30 compared to 2013, and by now it should not pose a significant threat to the black grouse. The latter is considered one of the major reasons of the increasing number of black grouse in 2014-2018. According to the Ministry of Forestry of The Republic of Belarus for 2012-2014 years, the numbers of the species' population counted approximately 34.6-39.9 thousand individuals according to spring surveys. The current population in 2018 reached 43.2 thousand individuals [24].
By the end of 2018, the fox population was also 1.8 times lower than in 2006. However, the local numbers of predatory invasive alien species such as a raccoon dog continues to grow. By 2015, the raccoon dog count in Belarus doubled compared to 2005.
A decrease in the number of black grouse in a short period of time were also noted in the regions neighboring Belarus. In the 1970s in Poland the number of black grouse counted approximately about 40-45 thousand individuals, and in the next 7 years, it decreased by 68 % [25].
An inventory of black grouse leks in Belarus showed that over the past decades there has been a significant change in their biotopic distribution. The decrease in the area of natural habitats of black grouse that occurred over the past 40-50 years as a result of large-scale drainage reclamation led to a redistribution of black grouse populations towards extensively exploited anthropogenically transformed lands. However, in the case of land-use change towards further intensification of agriculture a rapid decline in the black grouse number can be predicted. Considering the changes in land use that have occurred in the country and the trends of a drastic decline in the numbers of black grouse in the past, it is necessary to assess the stability of the species' population at the current stage. The importance of studying the genetic diversity and the genetic structure of animal populations is that these indicators have a direct impact on the continued success of their existence. This has been shown by an example of some black grouse populations in Europe [26]. The authors demonstrated that genetic diversity (observed heterozygosity, gene diversity (Hs)) is lower and inbreeding is higher in isolated populations (populations from southeastern Austria, England and Germany) compared with extended populations (from Scandinavia) and populations that are classified as adjacent (from the Alps and the Scottish highlands). The role of fragmentation in the genetic differentiation of populations has been shown for the capercaillie when studying the metapopulation structure in the Alps [27]. The significant differentiation between all populations by allele frequency was demonstrated. The total differentiation based on all loci was 0.046 (p < 0.001). Similar results were obtained in the study of capercaillie in the Bavarian Alps. The authors found a reliable genetic differentiation between pairs of populations separated by a distance of less than 10 km [28]. In another work, the genetic consequences of fragmentation on the capercaillie population were also studied using microsatellite markers in the European part of the range at various levels along the spatial gradient from high population connectedness in the forests of the boreal zone (Russia (Arkhangelsk, Yaroslavl, Karelia), Norway) to the metapopulation system in the Alps, as well as in the context of recent (Central Europe) and historical (Pyrenees) isolation [29]. As it could be expected, the genetic differentiation was the least pronounced within the continuous range of boreal forests. Based on the data received, the authors conclude that anthropogenic disturbance of habitats and fragmentation can lead to significant genetic and evolutionary consequences for the survival of the species.
Taking into account the significant fluctuations of the black grouse population in Belarus, we considered it relevant to assess the level of genetic diversity of the species in order to clarify the possible negative consequences of a decrease in numbers as a result of landscape transformation.
Materials and methods. A panel of microsatellite markers, originally developed for black grouse and capercaillie [30, 31], was selected for studying the intraspecific genetic diversity and structure of the black grouse populations (Tab. 1). The distribution of black grouse samples are presented in Fig. 1. PCR products were genotyped using commercial protocols, reagents and software for the GenomeLab GeXP genetic analysis system (Beckman Coulter, USA). Software Tandem  Analysis of the genetic structure of black grouse was carried out for 4 subpopulations (Fig. 1, 1-4) and two groups of subpopulations (Fig. 1, A, B).
Analysis of the genotypes matching was done using GenAlEx v. 6.501 [37-39]. Samples with absolute genotype similarity were excluded from further analysis.
Linkage disequilibrium between loci was carried out in the Arlequin version 3.5.2.2 [40]. Parameters used: 10,000 permutations, confidence level at p < 0.05. The deviation of the studied loci from the Hardy-Weinberg equilibrium (HWE) was also evaluated in the Arlequin with default settings.
A test for the past decline of black grouse population was carried out in the Bottleneck 1.2.02 [41]. In this analysis, the TPM (two phase model) was used with the following parameters: proportion of SMM (stepwise mutational model) in TPM = 95 %, variance = 12 % (in accordance with [42]). In addition, I.A.M. (infinite allele model) and S.M.M. models were used. Significance of heterozygote excess was assessed using the sign test, standardized differences test and Wilcoxon's sign-rank test.
Bayesian inference of population structure was performed using the software STRUCTURE [44,45]. STRUCTURE runs were performed under admixture model, correlated allele frequencies among populations and using sampling locations as prior information to assist the clustering (only for 4 subpopulations), length of burning period = 50 000, number of MCMC (Markov chain Monte Carlo) = 100 000. STRUCTURE analyses were conducted for 1-6 putative genetic clusters (K) with 15 runs for each value of K for 4 subpopulations and for 1-5 putative genetic clusters (K) with 20 runs for each value of K for 2 groups of black grouse subpopulations. To visualize the STRUCTURE results we used STRUCTURE HARVESTER [46]. An alternative way to find genetic structure was Principal Coordinates Analysis (PCoA) in GenAlEx. Visualization of PCoA data was carried out in the PAST [47]. The population genetic structure was checked by pairwise comparing the fixation index (Fst) between the selected subpopulations of black grouse in diveRsity and conducting a hierarchical analyses of molecular variance (AMOVA) in Arlequin. Additional calculating index of the population differentiation D est (Jost, 2008) was performed in diveRsity. The index D est was carried out due to the fact that Fst can be unreliable when the genetic diversity of the studied populations is very high (Jost, 2008 cited from [48]).
The calculation of the effective population size of the black grouse, as a measure to estimate the rate of loss of genetic variation due to genetic drift and inbreeding, was made according to the formulas given in Braude, 2010 [49].
The effective population size was calculated taking into account inbreeding (inbreeding effective size, Nef ) -this is the size of an ideal population that would allow the same accumulation of pedigree inbreeding as the actual population of interest; this effective population size indicates the loss of heterozygosity across all alleles in population of interest; calculated as a harmonic average population size over time from the founding generation to the penultimate generation.
Additionally, variance effective size (Nev) was calculated (2). The variance effective population size is the size of an ideal population that would accumulate the same amount of variance in allele frequencies as the population of interest; this effective population size indicates how rapidly allele frequencies are likely to change.
Results and discussion. Testing in Micro-Cheсker indicated the presence of null alleles among the microsatellite results only for the singular locus TUT1. This was consistent with analysis for null alleles in Genepop. Therefore, TUT1 was excluded from further analysis. Concerning the rest of the loci, there was no indication of additional genotyping errors. Two pairs of samples -AV00677/AV00673 and AV00671/AV00672 had similar genotypes. The samples AV00673 and AV00672 were excluded from analysis.
Linkage disequilibrium analysis did not show any stable linkage between loci as it was seen from tests for 4 subpopulations and 2 groups of subpopulations of black grouse. This can be explained by the characteristic of the analyzed sample and is unlikely to have any connection with real linkage. All loci except TUT1 were in accordance with the HWE. We didn't find any convincing signs of rapid black grouse population decline in the past.
The indicators of genetic diversity (allelic richness, mean number of alleles) of black grouse subpopulations (Tab. 5) show nearly the same mid-level of diversity. This outcome remains unchanged whether the sample is considered are 4 subpopulations or 2 groups of subpopulations in the analysis. The lowest value of allelic richness is found in Pop2 (the northern region of Belarus) and corresponds to its low sample size. The level of both observed and expected heterozygosity is consistent with the inbreeding coefficient value -there are no signs of significant close related mating or genetic drift.  We didn't observe significant genetic differentiation among most but for one pair of the investigated subpopulations neither through Fst nor through D est (Tab. 6). The pair Pop3-Pop4 had low significant genetic differentiation for Fst (0.0487), but not for D est . The last results are also consistent with AMOVA. The only one fixation index -Fsc (differentiation among subpopulations within groups) was significant (0.03, p < 0.05), which most likely connected with genetic differentiation between Pop3 vs Pop4. Whereas there was no apparent genetic structure for pairwise black grouse subpopulations groups (A and B) comparison (Fct = -0.002, p > 0.05). Results from STRUCTURE indicated that there is no apparent population genetic partitioning (Fig. 2). Despite K = 2 having the highest ΔK value this estimation isn't distinctly different from other K values. Individuals from all putative populations have nearly equal membership proportions to each of the genetic clusters. Moreover, K = 1 has the highest logarithmic probability among the K values. Principal coordinate analysis also did not indicate any significant genetic differentiation for either the 4 subpopulations of black grouse (Fig. 3) or for the 2 groups of black grouse subpopulations. The first 2 axes explained 31.14 % of the total variation.
The microsatellite analysis is consistent with the estimates of the effective population size of the black grouse in Belarus based on long-term census (Tab. 7).
The both inbreeding effective size (Nef) and variance effective population size (Nev) had very high values ≈ 42 669 and 41 940 respectively. Conclusion. Taking into account the data obtained on the genetic diversity and population genetic differentiation of black grouse subpopulations in Belarus, the following conclusions can be drawn: -the black grouse population has sufficient connectivity, which is expressed in the absence of a pronounced subpopulation subdivision (data from Bayesian analysis, Principal coordinate analysis, analysis of molecular variance and values of the indices of population separation Fst and D est ); -the black grouse population can be characterized as stable and viable on the basis of genetic diversity estimation -the rates of both observed and expected heterozygosity are moderate, the population has not experienced a significant decline in numbers and there is no sign of inbreeding.
Thus, despite the strong change in the main black grouse habitat (swampland area reduction), the species has a good adaptive potential. In addition, the maintenance of high abundance of black grouse popula tion in Belarus, as one of the main source of genetic variation, was facilitated by the ecological flexibility of the species, that is the ability to move into the new habitat -agricultural landscape. Of course, this situation will not be observed ubiquitously and will be determined by the quality of the habitat.