Homel.indd UDC 598.279.25:591.9(4/5) NEW DATA ON PHYLOGEOGRAPHY OF THE BOREAL OWL, AEGOLIUS FUNEREUS (STRIGIFORMES, STRIGIDAE), IN EURASIA K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty State Scientifi c and Production Association “Scientifi c and Practical Center NAS of Belarus on Bioresources”, Academic st., 27, Minsk, 220072 Republic of Belarus E-mail:homelkv@gmail.com K. V. Homel (https://orcid.org/0000-0002-2396-1387) M. E. Nikiforov (https://orcid.org/0000-0003-1773-1128) E. E. Kheidorova (https://orcid.org/0000-0002-1341-9914) A. A. Valnisty (https://orcid.org/0000-0002-3612-1467) New Data on Phylogeography of the Boreal Owl, Aegolius funereus (Strigiformes, Strigidae), in Eurasia. Homel, K. V., Nikiforov, M. E., Kheidorova, E. E., Valnisty, A. A. — In the article the research’s results of phylogeography, genetic diversity, genetic structure and demographic characteristics of the Boreal Owl population in Eurasia are given. Th e fi rst domain of control region of mtDNA is used as a genetic marker. Th e sample size was 59 specimens. Th e population of Boreal Owl is characteristic of high genetic diversity and it has signs of rapid expansion in the past as revealed by analysis of CR1 mtDNA polymorphism. Genetic diff erentiation between birds from the west and the east part of the species range is shown. Th e level of found population genetic diff erentiation isn’t high that can be explained by gene fl ow in the past and possible at the present time. We didn’t reveal any signs of genetic diff erentiation for Boreal Owl population according to subspecies (between A. f. funereus and A. f. pallens) which are distinguished for the studying area. K e y w o r d s : boreal owl, Aegolius funereus, phylogeography, genetic diversity, genetic structure, Eurasia. Introduction Highly reliable data on the biological diversity of a species provides increased effi ciency of directed conservation eff orts. Defi ning a species’ phylogeographic structure through the genetic diff erentiation of its populations allows for selecting more appropriate and adequate conservation approaches, compared with those based on intraspecifi c taxonomic structure as it is defi ned by morphological criteria for a given species. A solid understanding of intraspecifi c genetic status of a species is vital for determining vulnerable genetic lines, as well as determining fi tting localities for effi cient eff orts towards their conservation (Allendorf et al., 2013). Zoodiversity, 54(6): 523–534, 2020 DOI 10.15407/zoo2020.06.523 Ornithology 524 K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty Phylogeographic studies are also vital for unearthing the history of developing intraspecifi c structure and the infl uences of historical geoclimatic processes on a species and its adaptability (Avise & Walker, 1998; Hewitt, 2001). Establishing the role of climatic and biogeographical processes in determining the genetic makeup of populations serves to make the impact of future environmental transformations on such populations more predictable. Serious contradictions can frequently be seen between classic intraspecifi c taxonomic units and molecular genetic marker data. Examples of such contradictions for mitochondrial markers include Willow Ptarmigan, Lagopus lagopus (Linnaeus, 1758) (Höglund et al., 2013), Northern Goshawk, Accipiter gentilis (Linnaeus, 1758) (Kunz et al., 2019), Golden Eagle, Aquila chrysaetos (Linnaeus, 1758) (Nebel et al., 2015), Eurasian Th ree- toed Woodpecker, Picoides tridactylus (Linnaeus, 1758) (Zink et al., 2002 b), Great Spotted Woodpecker, Dendrocopos major (Linnaeus, 1758) (Zink et al., 2002 a), Western Capercaillie, Tetrao urogallus Linnaeus, 1758 (Duriez et al., 2007), Black Grouse, Lyrurus tetrix (Linnaeus, 1758) (Corrales et al., 2014) and White Wagtail, Motacilla alba Linnaeus, 1758 (Li et al., 2016). Th ese situations of ambiguous intraspecifi c genetic division showcase the complexity and variety of historic phylogeographic structure among birds. Investigating the roots of phylogeographic patters in other species facilitates better understanding of avian microevolution processes and climatic adaptability. What in turn supports the eff orts for biodiversity conservation. In this study we analyze the phylogeographic structure of a polytypic species — the Boreal Owl, Aegolius funereus (Linnaeus, 1758), in the Eurasian part of its range. Th e Boreal Owl inhabits the Holarctic ecozone. In Eurasia this species has a continuous range stretching from boreal forests of Northern and Central Europe across Urals and to Kamchatka and Kuril isles. Th e dispersed populations across Europe stretch south to Pyrenees, Alps and Caucasus mountains, and in Asia along Tarbagatai, Tien Shan and Zervshan mountain ranges (Hayward & Hayward, 2020). Th e species’ habitat includes boreal, subalpine and mixed temperate forests (Hayward & Hayward, 2020). Th e Boreal Owl is characteristic of settled behavior. Males are more site tenacious than females, but both sexes prefer to hold to their home range all year round, undertaking distant migrations only as the numbers of their prey dwindle (Hayward & Hayward, 2020). Th e species is traditionally divided into six subspecies of diff erent localization (Hayward & Hayward, 2020), fi ve subspecies are traditionally counted across its Eurasian part of the range and one subspecies — across its North American part of the range. Present subspecies and wide distribution across Eurasia could suggest signifi cant genetic distancing between subspecies due to separation of subpopulations, as well as intraspecifi c competition. However, the current Boreal Owl subspecies were defi ned according to morphological characteristics, primarily diff erences in body size and plumage coloration. Variability of those traits can have clinal nature. Th is uncertainty could be resolved by employing molecular genetic analysis for determining the intraspecifi c relations between the subspecies on the Eurasian part of the species’ range, which could supply an insight into the species’ development through its phylogeographic history during the Pleistocene glacial periods as well as postglacial events. At the moment there is a series of researches on genetic diff erentiation and diversity of the species existed. Th e preliminary research on the phylogeography of Boreal Owl in Eurasia was already conducted by us in 2013. A 648 bp fragment of mitochondrial COI gene was used as the genetic marker. Th e results of that study did not suggest any noticeable genetic divergence between the Boreal Owl subspecies, or signifi cant genetic distancing between various subspecies specimens from geographically distant subpopulations (Belarus, Russia (Sakhalin, Kirov oblast, Magadan oblast), Norway, Sweden), according to the chosen molecular marker. Th e procured genetic diversity data suggested a recent expansion of the Boreal Owl across Norther Europe and Russia, marking the subspecies divergence as being currently in its early stages. A publication by Koopman et al. from 2005 describes a study of the Boreal Owl subspecies structure using 7 microsatellites as genetic markers. Th e sample size was 275 specimens from North America, 36 from Norway, and 5 from eastern Russia. Microsatellite analysis data did not indicate any signifi cant genetic divergence between Norwegian and Russian Boreal Owl populations, but a certain degree of divergence between Eurasian and North American populations. Authors tied close genetic admixture of populations within the same continent to extensive dispersal ranges of the species, facilitating stable migration rate between subpopulations. In the light of these results, the authors declared the necessity of further genetic research into Boreal Owl populations in order to better determine intraspecifi c structure. Th ey also highlight that North American populations don’t display any signifi cant genetic divergence — Alaskan, Canadian, Idaho, Montana, Wyoming and Colorado were characterized by very low genetic diff erentiation (θ = 0,004) according to chosen microsatellite panel data (Koopman et al., 2005). Another publication reported the study of genetic diff erentiation between the westernmost Boreal Owl population of Pyrenees and the Fennoscandian population (Broggi et al., 2013). A part of mitochondrial DNA’s control region (369 base pairs in length) was utilized as the genetic marker. Th e sample consisted of 19 individual birds from the region of Andorra and Catalonia, and 17 individuals from Finland. A total of 26 marker sequence haplotypes was noted. Th e genetic diversity coeffi cients were similar for both studied populations. Th e hierarchical molecular variance analysis indicated a lack of clear genetic diff erentiation between the studied populations with the ФST = 0.0194 (P  =  0.1711). A presence of genetic fl ow between the sampled groups in the range between 11 and 43 individuals per generation was determined, further highlighting the absence of a clear division between populations. 525New Data on Phylogeography of the Boreal Owl, Aegolius funereus in Eurasia Th is study aims to continue the investigation of boreal owl’s phylogeography and intraspecifi c genetic structure through analysis of mtDNA control region sequences including the easternmost samples. Material and methods Th e study utilized original sequences of boreal owl’s fi rst control region domain of the mtDNA from Belarus (n = 2) and Russia (n = 12), as well as confi rmed and approved publicly available sequences of the same marker obtained from the NCBI database, the latter being sequences from individuals sampled in the Pyrenees (n = 18), Fennoscandia (n = 16), Norway (n = 9), as well as 2 sequences identical to Pyrenees and Fennoscandia (Appendix, table 1). Th e study included a total of 59 mtDNA CR1 sequences of the Boreal Owl (fi g. 1). Th e sampled Boreal Owl sequences source locations correspond to the ranges of two Eurasian subspecies of Boreal Owl out of fi ve, namely A. f. funereus and A. f. pallens (Hayward & Hayward, 2020). DNA for further amplifi cation and sequencing of original samples was extracted from muscle tissues deposited in the genetic collection of SSPA “Scientifi c and Practical Center of the National Academy of Sciences of Belarus on Bioresources” and provided by MSU Zoological Museum. Extraction was carried out using a commercial “Blood, Animal, Plant DNA Preparation Kit” (Jena Bioscience, Germany) utilizing silica membrane spin- columns. Th e concentrations of extracted DNA samples were measured via IMPLEN spectrophotometer P330 (IMPLEN, Germany). Every utilized original DNA sample was deposited into the Wildlife genetic bank of the Scientifi c and Practical Center of the National Academy of Sciences of Belarus on Bioresources for further reference. Th e amplifi cation of the Boreal Owl mtDNA CR1 was conducted using primers Aft RNAglu (5’-GGCCTGAAAAACCACCGTTAA-3’) and AfH535 (5’-AGATTATTTGGTTATGGTGGG-3’) (Broggi et al., 2013). PCR-amplifi cation was performed in 25мl volume reaction mixes, containing 2.5 мl of 10X Taq buff er with (NH4)2SO4, 2.5 мl of 10X dNTPs mix (2mM of each dNTP), 3 мl of Fig. 1. Th e source regions of Boreal Owl mtDNA CR1 sequences used in the present study. Numbered yellow circles indicate sampling regions for utilized Boreal Owl mtDNA CR1 sequences, as well as the number of sequences per each region. Green coloration indicates boreal owl’s range. 526 K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty MgCl2 solution (25 mM), 2мl of forward and reverse primer solution (5 pmol/мl), 1 unit of Taq-polymerase, 2 мl of DNA matrix solution and 10.9 мl of ddH2O. Amplifi cation of the Boreal Owl mtDNA CR1 was done according to the following protocol: initial denaturation at 95 °С for 2 minutes; 35 cycles of — denaturation at 95 °С for 30 seconds, primer annealing at 50 °С for 30 seconds, elongation at 72 °С for 90 seconds; fi nal elongation at 72 °С for 5 minutes. Th e reaction was carried out with a C1000 Touch thermal cycler (Bio-Rad Laboratories, Inc. USA). Th e Boreal Owl mtDNA CR1 amplicons were Sanger-sequenced using a GenomeLab GeXP Genetic Analysis System (Beckman Coulter, Germany) with Dye Terminator Cycle Sequencing Quick Start Kits (Beckman Coulter, Germany) according to manufacturer’s protocols, utilizing the abovementioned mtDNA CR1 primers. Obtained sequence data was manually checked using MEGA 6 soft ware and aligned using Muscle algorithm with the same soft ware (Tamura et al., 2013). Polymorphism sites were detected using MEGA 6 and DnaSP v. 6.10.04 (Rozas et al., 2017). Nucleotide diversity (π), number of haplotypes, average number of nucleotide diff erences (k), haplotype diversity (Hd), number of segregation sites (S) and θ per site from S for the studied sequence set were calculated in DnaSP. Haplotype network of the studied sequences was built using POPART (“PopART,” 2020) with the Median Joining Network algorithm. Demographic indexes were calculated with DnaSP — specifi cally, Fu’s Fs, Tajima’s D, raggedness index (r) and Ramos-Onsin’s and Roza’s R2. Low values of R2 and negative values of Fs and D indicate population expansion in the past (Ramos-Onsins & Rozas, 2002). P-values for the abovementioned indexes were determined via coalescent simulation in DnaSP utilizing theta and segregating sites number both. Additionally, a mismatch distribution graph (the distribution of the number of site diff erences between pairs of sequences) was constructed using DnaSP. Th e last test indicates population expansion in the case if the distribution is a unimodal, raggedness index (quantitative assessment of the smoothness of the mismatch distribution for the demographic scenarios of population expansion and stability in the past) and the sum of squared deviations (SSD) from the sudden expansion model also have low values in this situation (Rogers & Harpending, 1992; Maltagliati et al., 2010). Th e sum of squared deviations (SSD) was calculated in Arlequin 3.5.1.2. (Excoffi er et al., 2007). Divergence rate values of 4 % and 14 % per Myr for mtDNA CR were used to calculate the time of beginning population expansion (Marthinsen et al., 2009). It was calculated as t = τ ÷ 2μ (Shephard et al., 2013; Klinga et al., 2015), τ was taken from mismatch distribution calculation in DnaSP, and μ being [divergence rate/2/106 * sequence length in base pairs (210 bp)* generation time in years] (Marthinsen et al., 2009). Boreal Owl generation was taken as 2 years (Hayward & Hayward, 2020). Th e resulting μ equaled 8,4*10-6 for divergence rate value of 4 % and 2,94*10-5 for 14 % rate. Population diff erentiation within the Boreal Owl population across the Eurasian range was determined using Arlequin. Th e population was divided into three nominal groups: Pyrenees (n = 19), Fennoscandia/Eastern Europe (n = 31) and Russian Far East (n = 9). Genetic divergence of populations was determined through pairwise Fst (Tamura & Nei genetic distance with 10 000 permutations) and an exact test of sample diff erentiation based on haplotype frequencies (default settings). Results and discussion Aligning original mtDNA CR1 sequences and GenBank sequences (with a total of 59) produced a 261 bp alignment. A 210 bp continuous segment of this alignment was fi t for analysis (aft er excluding sites with gaps/missing data). Pyrimidine transitions were more prevalent across the alignment; 31 variable sites were detected, with 22 of them being parsimony-informative ones. Th irty-two distinct haplotypes were identifi ed among 59 aligned sequences (Appendix, table 2). 527New Data on Phylogeography of the Boreal Owl, Aegolius funereus in Eurasia One of the identifi ed haplotypes (Afuner_2) included 11 individuals of the sample; two haplotypes (Afuner_8, Afuner_12) including 4 individuals each; two haplotypes (Afuner_10, Afuner_16) including 3 individuals each and seven haplotypes (Afuner_5, Afuner_11, Afuner_13, Afuner_21, Afuner_27, Afuner_30, Afuner_40) including 2 individuals each. Th e remaining 20 haplotypes all included unique individual sequences. Table 1. Molecular diversity metrics for the Eurasian population of Boreal Owl according to mtDNA CR1 polymorphism Metric Value N 59 h 32 S 22 Hd ± SD 0.953 ± 0.017 π ± SD 0.01337 ± 0.00102 k 2.808 Th eta per site (from S) (Th eta-W) 0.02255 Fu’s Fs –31.39*** Tajima’s D –1.28 NS R2 0.0602 NS SSD 0.00286 NS Raggedness index (r) 0.0438 NS N o t e . N — sample size, SD — standard deviation, Fu’s Fs, Tajima’s D — mutation neutrality indexes, SSD — sum of squared deviations for the sudden expansion model (Rogers & Harpending, 1992 (Maltagliati et al., 2010), raggedness index (r) (Harpending’s (1994) (Maltagliati et al., 2010), NS — statistically not signifi cant, *** p < 0.001. Fig. 2. Mismatch distribution graph for the pairwise comparison of mtDNA CR1 sequences of Eurasian Boreal Owl population. X axis refl ects pairwise diff erence, Y axis refl ects frequency of the diff erence across sequences; Freq. Obs. is the studied sample’s observed mismatch frequency graph, Freq. Exp. is the expected frequency for the sudden expansion model. 528 K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty Th e genetic diversity metrics for the studied Boreal Owl sample are listed in table 1. Th e mtDNA CR1 polymorphism of the studied sample clearly indicates a high genetic diversity level for boreal owl’s Eurasian population, despite modest resolution of the marker. Still, it has proven suffi cient to determine intraspecifi c genetic variety for the studied population. Analysis of demographic metrics of the Eurasian population of the Boreal Owl shows a very likely sudden and rapid population expansion in the species’ distant past, as indicated by statistically signifi cant negative Fu’s Fs value, low (although not statistically signifi cant) R2 value, low and statistically not signifi cant values of SSD for sudden expansion model and raggedness index r (table 1). Th e mismatch distribution graph for the studied sequences, with expected values and the ones obtained from the studied sample’s mtDNA CR1 data is presented in fi g. 2. Th e mismatch distribution graph appears to be unimodal, indicating population expansion in the past. Th e average pairwise distance equaled 2,808, with most diff erences being between 2 and 4 mismatches. Th e mtDNA CR1 divergence data, for μ = 8,4*  10-6 or 2,94 *10-5 and τ = 2,808 indicates the population expansion 167  142,9 or 47  755,10 years ago respectively, this timeframe value being an order of magnitude lesser than the one reported previously (Broggi et al., 2013). Th is shows that Boreal Owl expansion happened before the beginning of the last glacial maximum (about 20 000 years ago (Hewitt, 2001)). Th e high genetic diversity is likely to be tied with the absence of any known major bottleneck events for this species in the late Pleistocene, this possibly being supported by the obtained negative and not signifi cant Tajima’s D value. Th e genetic diversity and demographic history of the Boreal Owl described above is also refl ected in the haplotype network for the studied sample (fi g. 3). Fig. 3. Median joining network of mtDNA CR1 haplotypes for the studied Boreal Owl sample. Each circle refl ects a mtDNA CR1 haplotype. Circle sizes refl ect the number of studied individuals possessing the haplotype; circle colors refl ect geographic origin of individuals possessing the haplotype. Bars connect related haplotypes, with notches on bars refl ecting the number of nucleotide diff erences between them. Black dots indicate implied haplotypes not present in the sample. 529New Data on Phylogeography of the Boreal Owl, Aegolius funereus in Eurasia Th e haplotype network shows a distinct central haplotype Afuner_2, uniting sequences of individuals sampled in Russian Far East (Khabarovsk krai), European Russia (Kirov oblast), Western Europe (Pyrenees) and Northern Europe (Fennoscandia, Norway), marking it as a possible ancestral haplotype. Th e full haplotype network shows a clear picture of species’ expansion in the past with a distinct, interconnected star-like structure with a likely ancestral haplotype in the center, as well as signifi cant genetic diversity though high number of haplotypes including distant and unique ones. Geographic distribution of the studied haplotypes across the Boreal Owl range is shown in fi gure 4. Geographic distribution of Boreal Owl mtDNA CR1 haplotypes shows the presence of common haplotypes between extremely distant regions, such as Fennoscandia and Russian Far East sharing 4 common haplotypes (Afuner_2, Afuner_5, Afuner_10, Afuner_12), the Pyrenees and Russian Far East sharing 2 common haplotypes (Afuner_2, Afuner_13), and Scandinavia and Pyrenees sharing 3 (Afuner_2, Afuner_21, Afuner_30). Unique haplotype distribution possibly shows more active microevolution processes in Pyrenees and Scandinavia (fi g. 4), although this is more likely to be an indication of local genetic diversity refl ected through the local sample size. Th e Fst pairwise comparison unsurprisingly shows the most signifi cant genetic diff erence between Fennoscandia/East Europe group and the Russian Far East group (Fst = 0.099, p = 0.006), with the one between Pyrenees group and Russian Far East group being a close second (Fst  =  0.089, p  = 0.019), the diff erence between the Pyrenees group and the Fennoscandia/East Europe group one being much smaller and statistically not signifi cant (Fst = 0.024, p = 0.077). Exact test of sample diff erentiation based on haplotype frequencies has failed to provide robust diff erences (p  >  0.05), aside from a reliable but very minor diff erence between Pyrenees and Fennoscandia/East Europe groups (p = 0.03). Th ese results lead to the following conclusions: there is a degree of genetic diff erentiation Fig. 4. Boreal Owl mtDNA CR1 haplotype distribution across it’s Eurasian range. Colored dots indicate approximate regions of sampling for individuals possessing the corresponding haplotype. White dots with numbers refl ect the total number of unique haplotypes for this region. 530 K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty between the individuals present in the easternmost and the westernmost parts of the range — which is natural, given the extreme distances. On the other hand, the haplotype frequencies distribution is extremely unlikely to be caused entirely by homoplasy shows a lack of any defi nite line of genetic division of any nature between parts of the range, introducing a degree of gene fl ow across them in the past and, most likely, present. Th e observed minor diff erentiation between the Pyrenees and Fennoscandia/East Europe groups can be attributed to the eff ect of individual unique haplotypes under the limited sample size. Th e Eurasian population of Boreal Owl is characterized by high level of genetic diversity, lack of intraspecifi c diff erentiation and absence of signs of drastic population decline events (bottlenecks) in the observable past. Th e obtained genetic diversity characteristics and absence of intraspecifi c structure in the Eurasian population of Boreal Owl are in agreement with similar earlier publications on the subject (Koopman et al., 2005; Broggi et al., 2013). Broggi et al. (2013) have reported a similar level of diff erentiation between boreal owls from the Pyrenees and Fennoscandia (ФST = 0.0194, p = 0.1711), as well as similar conclusion on demographic dynamics concerning absence of probable bottleneck events in the species’ past (Broggi et al., 2013). Th e most signifi cant diff erence of the present study’s outcomes from the results presented by Broggi et al. (2013) is in the haplotype network structure and the time of population divergence. Th e previous haplotype network lacked any structural diff erentiation between the Pyrenees and Fennoscandian groups. Th is diff erence is most likely tied to the sampling limitations of both studies, rather than any objective eff ect or other diff erences in methodology. Th e signifi cant diff erence in the predicted time of population divergence (between 600 000 and 2 million years ago according to (Broggi et al., 2013)) also most likely stem from diff erent samples, as well as a higher resolution marker used by Broggi et al. (2013) (369 bp sequence against a 210 bp one in the present study), and other minor diff erences in methodology. Th e absence of any clear intraspecifi c structure within the Eurasian Boreal Owl population is supported by earlier studies utilizing microsatellite markers (Koopman et al., 2005). Th at study compared A. f. funereus and A. f. sibiricus (сurrently designated as A. f. pallens (Hayward & Hayward, 2020)) populations, and determined absence of any signifi cant genetic diff erentiation between the subspecies. Th e same conclusions are made for other subspecies of boreal owl, exclusing A. f. caucasicus. Th e basic reason for the lack of intraspecifi c diff erentiation in the Eurasian Boreal Owl population can be the species’ tendency for long-distance migrations, characteristic of the species under the conditions of diminishing prey numbers (Hayward & Hayward, 2020), as well as the species’ exclusion from the historic phenomenon of prolonged isolation in the Mediterranean refugia characteristic of species from temperate and more southern regions (Hewitt, 1996, 2000 quoted in (Broggi et al., 2013)). For example, a related species of tawny owl (Strix aluco Linnaeus, 1758) was determined to possess the genetic diff erentiation within Western Europe populations according to both mitochondrial and nuclear DNA markers data (Brito, 2007). Th is was tied to reason that tawny owl is not prone for making long-range migrations and such behavior prevents constant admixture between partially isolated populations. It is suggested that extended isolation of tawny owl in Mediterranean refugia during the Pleistocene glaciation, which would form a base for the current genetic diff erentiation (Brito, 2005). A fi tting example for a clear role of historic refugia isolation playing a role in the current genetic structure of a species would be the western capercaillie. Most of its subspecies, inhabiting boreal forests of Europe, lack any intraspecifi c structure, while the populations historically tied to the glacial refugia of Balkans and Iberia present clearly defi ned genetic lineages (Bajc et al., 2011; Rodríguez-Muñoz et al., 2007). Th e northern goshawk can serve as an example of another wide-ranging species without any clear intraspecifi c structure akin to the situation of the Boreal Owl (Kunz et al., 2019). Th e cause for this can be tied both to frequent long-range migrations (Squires et al., 2020) and historic expansion from a singular refugium (Kunz et al., 2020). 531New Data on Phylogeography of the Boreal Owl, Aegolius funereus in Eurasia Conclusion Th e obtained results on genetic diff erentiation within the Eurasian population of the Boreal Owl allow us to conclude that this species belongs to the phylogeographic model type with lacking any signifi cant genetic diff erentiation within its continental range, forming a singular expansive population, with any signifi cant genetic diff erences being possible mainly within the global range including the North American population (Koopman et al., 2005). Th e authors would like to thanks to our colleagues from the Zoological Museum of Moscow University (Russia) and Laboratory of ornithology of SSPA “Scientifi c and Practical Center of the National Academy of Sciences of Belarus on Bioresources” for providing and transferring samples of the Boreal Owl from the Russian part of the species range. We also thank the anonymous referees for important comments. A p p e n d i x . T a b l e 1 . A list of Boreal Owl mtDNA CR1 sequences used in the present study N Sequence ID Geographic region of origination Sequences obtained from GenBank 1 KC495114.1 Pyrenees (Spain) 2 KC495113.1 3 KC495112.1 4 KC495111.1 5 KC495110.1 6 KC495109.1 7 KC495107.1 8 KC495106.1 9 KC495105.1 10 KC495104.1 11 KC495103.1 12 KC495102.1 13 KC495101.1 14 KC495100.1 15 KC495099.1 16 KC495098.1 17 KC495097.1 18 KC495096.1 19 KC495095.1 Fennoscandia 20 KC495094.1 21 KC495093.1 22 KC495092.1 23 KC495091.1 24 KC495090.1 25 KC495089.1 26 KC495088.1 27 KC495087.1 28 KC495086.1 29 KC495085.1 30 KC495084.1 31 KC495082.1 32 KC495081.1 33 KC495080.1 34 KC495079.1 532 K. V. Homel, M. E. Nikiforov, E. E. Kheidorova, A. A. Valnisty 35 EU411019.1 Norway (Vest-Agder) 36 EU411018.1 37 EU411017.1 38 EU411016.1 39 EU411015.1 40 EU411014.1 41 EU411013.1 42 EU411012.1 43 EU411011.1 44 KC495108.1 Pyrenees/Fennoscandia 45 KC495083.1 Original sequences from individuals sampled in Russia 46 AV02202 (RYA 2831) Sakhalin island 47 AV02203 (RYA 2839) 48 AV02204 (RYA 2845) 49 AV02205 (RYA 2846) 50 AV02209 (CBH 3372) 51 AV02210 (CBH 3371) 52 AV02206 (CBH 2153) Khabarovsk krai 53 AV02207 (CBH 2154) 54 AV02201 (NIA 458) Tomsk oblast, Seversk city 55 AV02208 (CBH 869) Kirovsk oblast 56 57 AV01751 (RYA 3246) AV01752 (TMA 410) Moscow Original sequences from individuals sampled in Belarus 58 AV00133 Brest oblast., Lyakhovichi district, Tukhovichi village 59 AV02760 State environmental institution«Berezinsky biosphere reserve» A p p e n d i x . T a b l e 2 . Boreal Owl mtDNA CR1 haplotypes identifi ed in the aligned sequences Haplotype Number of individuals Individuals with the haplotype Afuner_1 1 1751_Russia_Moscow Afuner_2 11 2207_Russia_Khabarovsk, 2208_Russia_Kirov_ region, KC495114.1_AF92_Spain, KC495112.1_ AF90_Spain, KC495105.1_AF82_Spain, KC495104.1_AF81_Spain, KC495103.1_AF80_Spain, KC495096.1_AF60_Spain, KC495085.1_AF15_Finland, EU411018.1_perle9_ Norway, EU411012.1_perle2_Norway Afuner_3 1 1752_Russia_Moscow Afuner_5 2 2210_Russia_Sakhalin, KC495090.1_AF33_Finland Afuner_6 1 2760_Belarus_Berezinsky_Reserve Afuner_7 1 2203_Russia_Sakhalin Afuner_8 4 133_Belarus_Lyakhovichi_district, EU411017.1_ perle7_Norway, EU411016.1_perle6_Norway, EU411011.1_perle1_Norway Afuner_9 1 2206_Russia_Khabarovsk Afuner_10 3 2209_Russia_Sakhalin, KC495080.1_AF4_Finland, KC495079.1_AF1_Finland Afuner_11 2 2201_Russia_Tomsk_region, 2205_Russia_Sakhalin Afuner_12 4 2202_Russia_Sakhalin, KC495087.1_AF24_Finland, KC495086.1_AF21_Finland, KC495082.1_AF12_ Finland 533New Data on Phylogeography of the Boreal Owl, Aegolius funereus in Eurasia Afuner_13 2 2204_Russia_Sakhalin, KC495098.1_AF62_Spain Afuner_16 3 KC495113.1_AF91_Spain, KC495109.1_AF86_Spain, KC495097.1_AF61_Spain Afuner_18 1 KC495111.1_AF89_Spain Afuner_19 1 KC495110.1_AF88_Spain Afuner_21 2 KC495108.1_AF85_Spain_Finland, KC495083.1_ AF13_Spain_Finland Afuner_22 1 KC495107.1_AF84_Spain Afuner_23 1 KC495106.1_AF83_Spain Afuner_27 2 KC495102.1_AF66_Spain, KC495100.1_AF64_Spain Afuner_28 1 KC495101.1_AF65_Spain Afuner_30 2 KC495099.1_AF63_Spain, EU411013.1_perle3_ Norway Afuner_34 1 KC495095.1_AF53_Finland Afuner_35 1 KC495094.1_AF50_Finland Afuner_36 1 KC495093.1_AF49_Finland Afuner_37 1 KC495092.1_AF39_Finland Afuner_38 1 KC495091.1_AF34_Finland Afuner_40 2 KC495089.1_AF32_Finland, KC495088.1_AF30_ Finland Afuner_45 1 KC495084.1_AF14_Finland Afuner_48 1 KC495081.1_AF11_Finland Afuner_51 1 EU411019.1_perle10_Norway Afuner_55 1 EU411015.1_perle5_Norway Afuner_56 1 EU411014.1_perle4_Norway References Allendorf, F. 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