general info about Theriologia Ukrainica

Theriologia Ukrainica

ISSN 2616-7379 (print) • ISSN 2617-1120 (online)

2022 • Vol. 23 • Contents of volume >>>


download pdfValnisty, A. A., K. V. Homel, E. E. Kheidorova, M. E. Nikiforov, V. O. Molchan, P. Y. Lobanovskaya, A. A. Semionova. 2022. Reintroduction shapes the genetic structure of the red deer (Cervus elaphus) population in Belarus. Theriologia Ukrainica, 23: 31–45.


 

title

Reintroduction shapes the genetic structure of the red deer (Cervus elaphus) population in Belarus

author(s)

A. A. Valnisty (orcid: 0000-0002-3612-1467)
K. V. Homel (orcid: 0000-0002-2396-1387)
E. E. Kheidorova (orcid: 0000-0002-1341-9914)
M. E. Nikiforov (orcid: 0000-0002-1341-9914)
V. O. Molchan (orcid: no)
A. A. Siamionava (orcid: 0000-0002-5168-863X)
P. Y. Lobanovskaya (orcid: no)

affiliation

Scientific and Practical Centre for Bioresources, NAS of Belarus (Minsk, Belarus)

bibliography

Theriologia Ukrainica. 2022. Vol. 23: 31–45.

DOI

http://doi.org/10.15407/TU2306

   

language

English, with Ukrainian summary, titles of tables, captures to figs

abstract

The red deer (Cervus elaphus) is considered a valuable and important ungulate species with significant ecological role and high importance as a game species in Europe. Its local population in Belarus had undergone extended periods of decline in the past, followed by multiple reintroduction campaigns and management policy adjustments during the Soviet and post-Soviet periods, which eventually led to a recent spike in estimated population numbers. Along with increasing the numbers, those reintroductions have made the understanding of the structure and origins of the populations for the purpose of proper management and sustainable long-term growth much more complicated. Information on the origin of the reintroduction stock has often been lacking, while control of the red deer population dynamics in Belarus is currently limited to indirect survey of putative population numbers, with no utilization of contemporary genetic analysis. Here we report an estimate and interpretation of the red deer population structure in Belarus based on the analysis of microsatellite genotype data from 118 individuals of the red deer from the most well-known groups across Belarus. These specimens were genotyped using a novel multiplex panel of 14 microsatellite loci with various levels of polymorphism. We describe two red deer subpopulations with overlapping ranges that form the Belarussian metapopulation. We also report estimates of their genetic diversity, gained from the analysis of molecular variance, Bayesian analysis of genetic structure, differentiation indices, genetic bottleneck event analysis, and standard genetic diversity metrics. Based on the geographical distribution of subpopulations, their genetic differentiation and known history of red deer reintroductions in Belarus, we consider that both these subpopulations emerged mostly out of the patterns of animal release during two separate periods of reintroduction. We also suggest appropriate population management adjustments arising from the issue of anthropogenic reintroductions that determine the population structure in this managed species.

keywords

red deer, ungulates, game species, genetic structure, reintroduction, population augmentation, microsatellite analysis, Belarus.

   

references

Abdul-Muneer, P.M., 2014. Application of Microsatellite Markers in Conservation Genetics and Fisheries Management: Recent Advances in Population Structure Analysis and Conservation Strategies. Genetics Research International 2014, 1–11. https://doi.org/10.1155/2014/691759
Andersone-Lilley, Z., Balciauskas, L., Ozolins, J., Randveer, T., 2010. Ungulates and their management in the Baltics (Estonia, Latvia and Lithuania), in: European Ungulates and Their Management in the 21st Century. Cambridge University Press, pp. 103–128.
Apollonio, M., Belkin, V.V., Borkowski, J., Borodin, O.I., Borowik, T., Cagnacci, F., Danilkin, A.A., Danilov, P.I., Faybich, A., Ferretti, F., Gaillard, J.M., Hayward, M., Heshtaut, P., Heurich, M., Hurynovich, A., Kashtalyan, A., Kerley, G.I.H., Kjellander, P., Kowalczyk, R., Kozorez, A., Matveytchuk, S., Milner, J.M., Mysterud, A., Ozolins, J., Panchenko, D.V., Peters, W., Podgorski, T., Pokorny, B., Rolandsen, C.M., Ruusila, V., Schmidt, K., Sipko, T.P., Veeroja, R., Velihurau, P., Yanuta, G., 2017. Challenges and science-based implications for modern management and conservation of European ungulate populations. Mamm Res, 62, 209–217. https://doi.org/10.1007/s13364-017-0321-5
Arif, I.A., Khan, H.A., Bahkali, A.H., Al Homaidan, A.A., Al Farhan, A.H., Al Sadoon, M., Shobrak, M., 2011. DNA marker technology for wildlife conservation. Saudi Journal of Biological Sciences, 18, 219–225. https://doi.org/10.1016/j.sjbs.2011.03.002
Balloux, F., Lugon-Moulin, N., 2002. The estimation of population differentiation with microsatellite markers. Mol Ecol, 11, 155–165. https://doi.org/10.1046/j.0962-1083.2001.01436.x
Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N., Bonhomme, F., 2004. GENETIX4. 05, logiciel sous Windows TM pour la genetiquedes populations. Laboratoire genome, populations, interactions, CNRS UMR 5000, 1996–2004.
Bishop, M.D., Kappes, S.M., Keele, J.W., Stone, R.T., Sunden, S.L., Hawkins, G.A., Toldo, S.S., Fries, R., Grosz, M.D., Yoo, J., 1994. A genetic linkage map for cattle. Genetics, 136, 619–639. https://doi.org/10.1093/genetics/136.2.619
D’Aprile, D., Vacchiano, G., Meloni, F., Garbarino, M., Motta, R., Ducoli, V., Partel, P., 2020. Effects of Twenty Years of Ungulate Browsing on Forest Regeneration at Paneveggio Reserve, Italy. Forests, 11, 612. https://doi.org/10.3390/f11060612
Dellicour, S., Frantz, A.C., Colyn, M., Bertouille, S., Chaumont, F., Flamand, M.C., 2011. Population structure and genetic diversity of red deer (Cervus elaphus) in forest fragments in north-western France. Conserv Genet, 12, 1287–1297. https://doi.org/10.1007/s10592-011-0230-0
DeWoody, J.A., Honeycutt, R.L. and Skow, L.C. (1995) ‘Microsatellite Markers in White-Tailed Deer’, Journal of Heredity, 86, 317–319. https://doi.org/10.1093/oxfordjournals.jhered.a111593
Earl, D.A., vonHoldt, B.M., 2012. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genet Resour, 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7
[Environmental protection in the Republic of Belarus] Охрана окружающей среды в Республике Беларусь, 2021. . National Statistical Committe of the Republic of Belarus.
Evanno, G., Regnaut, S., Goudet, J., 2005. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol, 14, 2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x
Excoffier, L., Lischer, H.E.L., 2010. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources, 10, 564–567. https://doi.org/10.1111/j.1755-0998.2010.02847.x
Falush, D., Stephens, M., Pritchard, J.K., 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics, 164, 1567–1587. https://doi.org/10.1093/genetics/164.4.1567
Feulner, P.G.D., Bielfeldt, W., Zachos, F.E., Bradvarovic, J., Eckert, I., Hartl, G.B., 2004. Mitochondrial DNA and microsatellite analyses of the genetic status of the presumed subspecies Cervus elaphus montanus (Carpathian red deer). Heredity, 93, 299–306. https://doi.org/10.1038/sj.hdy.6800504
Frankham, R., 2005. Genetics and extinction. Biological Conservation, 126, 131–140. https://doi.org/10.1016/j.biocon.2005.05.002
Frantz, A.C., Zachos, F.E., Bertouille, S., Eloy, M.-C., Colyn, M., Flamand, M.-C., 2017. Using genetic tools to estimate the prevalence of non-native red deer ( Cervus elaphus ) in a Western European population. Ecol Evol, 7, 7650–7660. https://doi.org/10.1002/ece3.3282
Galinskaya, T.V., Shchepetov, D.M., Lysenkov, S., 2019. Предубеждения о микросателлитных исследованиях и как им противостоять [Predubezhdeniya o mikrosatellitnykh issledovaniyakh i kak im protivostoyat’]. Genetika, 55, 617–632. https://doi.org/10.1134/S0016675819060043
Hale, M.L., Burg, T.M., Steeves, T.E., 2012. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PLoS One, 7, e45170. https://doi.org/10.1371/journal.pone.0045170
Hammer, O., Harper, D., Ryan, P., 2001. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica, 4, 1–9.
Hedrick, P.W., 2005. A standardized genetic differentiation measure. Evolution 59, 1633–1638. https://doi.org/10.1111/j.0014-3820.2005.tb01814.x
Henegariu, O., Heerema, N.A., Dlouhy, S.R., Vance, G.H., Vogt, P.H., 1997. Multiplex PCR: Critical Parameters and Step-by-Step Protocol. BioTechniques, 23, 504–511. https://doi.org/10.2144/97233rr01
Hoffmann, G.S., Griebeler, E.M., 2013. An improved high yield method to obtain microsatellite genotypes from red deer antlers up to 200 years old. Mol Ecol Resour, 13, 440–446. https://doi.org/10.1111/1755-0998.12068
Holleley, C.E., Geerts, P.G., 2009. Multiplex Manager 1.0: a cross-platform computer program that plans and optimizes multiplex PCR. BioTechniques, 46, 511–517. https://doi.org/10.2144/000113156
Holsinger, K.E., Weir, B.S., 2009. Genetics in geographically structured populations: defining, estimating and interpreting FST. Nat Rev Genet, 10, 639–650. https://doi.org/10.1038/nrg2611
Jones, K.C., Levine, K.F., Banks, J.D., 2002. Characterization of 11 polymorphic tetranucleotide microsatellites for forensic applications in California elk (Cervus elaphus canadensis). Mol Ecol Notes, 2, 425–427. https://doi.org/10.1046/j.1471-8286.2002.00264.x
Jost, L., 2008. G ST and its relatives do not measure differentiation. Molecular Ecology, 17, 4015–4026. https://doi.org/10.1111/j.1365-294X.2008.03887.x
Keenan, K., McGinnity, P., Cross, T.F., Crozier, W.W., Prodohl, P.A., 2013. diveRsity?: An R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol Evol, 4, 782–788. https://doi.org/10.1111/2041-210X.12067
Kopelman, N.M., Mayzel, J., Jakobsson, M., Rosenberg, N.A., Mayrose, I., 2015. CLUMPAK: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour, 15, 1179–1191. https://doi.org/10.1111/1755-0998.12387
Korbie, D.J., Mattick, J.S., 2008. Touchdown PCR for increased specificity and sensitivity in PCR amplification. Nat Protoc, 3, 1452–1456. https://doi.org/10.1038/nprot.2008.133
Kozlo, P.G., 1972. Некоторые итоги реакклиматизации благородного оленя в Березинском заповеднике [Nekotoryye itogi reakklimatizatsii blagorodnogo olenya v Berezinskom zapovednike]. Berezinskiy Zapovednik: Issledovaniya, 2, 120–130.
Krojerova-Prokesova, J., Barancekova, M., Koubek, P., 2015. Admixture of Eastern and Western European Red Deer Lineages as a Result of Postglacial Recolonization of the Czech Republic (Central Europe). JHERED, 106, 375–385. https://doi.org/10.1093/jhered/esv018
Kuhn, R., Anastassiadis, C., Pirchner, F., 2009. Transfer of bovine microsatellites to the cervine (Cervus elaphus). Animal Genetics, 27, 199–201. https://doi.org/10.1111/j.1365-2052.1996.tb00952.x
Lorenz, T.C., 2012. Polymerase Chain Reaction: Basic Protocol Plus Troubleshooting and Optimization Strategies. JoVE, 3998. https://doi.org/10.3791/3998
Ludt, C.J., Schroeder, W., Rottmann, O., Kuehn, R., 2004. Mitochondrial DNA phylogeography of red deer (Cervus elaphus). Molecular Phylogenetics and Evolution, 31, 1064–1083. https://doi.org/10.1016/j.ympev.2003.10.003
Matschiner, M., Salzburger, W., 2009. TANDEM: integrating automated allele binning into genetics and genomics workflows. Bioinformatics, 25, 1982–1983. https://doi.org/10.1093/bioinformatics/btp303
Meirmans, P.G., Hedrick, P.W., 2011. Assessing population structure: F ST and related measures. Molecular Ecology Resources, 11, 5–18. https://doi.org/10.1111/j.1755-0998.2010.02927.x
Mommens, G., Coppieterst, W., Weghe, A., Zeveren, A., Bouquet, Y., 2009. Dinucleotide repeat polymorphism at the bovine MM12E6 and MM8D3 loci. Animal Genetics, 25, 368–368. https://doi.org/10.1111/j.1365-2052.1994.tb00381.x
Moss, R., Piertney, S.B., Palmer, S.C.F., 2003. The use and abuse of microsatellite DNA markers in conservation biology. Wildlife Biology 9, 243–250. https://doi.org/10.2981/wlb.2003.011
Nei, M., 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89, 583–590. https://doi.org/10.1093/genetics/89.3.583
Niedzialkowska, M., Doan, K., Gorny, M., Sykut, M., Stefaniak, K., Piotrowska, N., Jedrzejewska, B., Ridush, B., Pawelczyk, S., Mackiewicz, P., Schmolcke, U., Kosintsev, P., Makowiecki, D., Charniauski, M., Krasnodebski, D., Rannamae, E., Saarma, U., Arakelyan, M., Manaseryan, N., Titov, V.V., Hulva, P., Bala?escu, A., Fyfe, R., Woodbridge, J., Trantalidou, K., Dimitrijevic, V., Kovalchuk, O., Wilczynski, J., Obada, T., Lipecki, G., Arabey, A., Stankovic, A., 2021. Winter temperature and forest cover have shaped red deer distribution in Europe and the Ural Mountains since the Late Pleistocene. J. Biogeogr., 48, 147–159. https://doi.org/10.1111/jbi.13989
Niedzialkowska, M., Jedrzejewska, B., Honnen, A.-C., Otto, T., Sidorovich, V.E., Perzanowski, K., Skog, A., Hartl, G.B., Borowik, T., Bunevich, A.N., Lang, J., Zachos, F.E., 2011. Molecular biogeography of red deer Cervus elaphus from eastern Europe: insights from mitochondrial DNA sequences. Acta Theriol, 56, 1–12. https://doi.org/10.1007/s13364-010-0002-0
Niedzialkowska, M., Jedrzejewska, B., Wojcik, J.M., Goodman, S.J., 2012. Genetic structure of red deer population in northeastern Poland in relation to the history of human interventions: Red Deer in Northeastern Poland. The Journal of Wildlife Management, 76, 1264–1276. https://doi.org/10.1002/jwmg.367
Nussey, D.H., Pemberton, J., Donald, A., Kruuk, L.E.B., 2006. Genetic consequences of human management in an introduced island population of red deer (Cervus elaphus). Heredity, 97, 56–65. https://doi.org/10.1038/sj.hdy.6800838
OpenStreetMap contributors, 2022. Planet dump retrieved from https://planet.osm.org.
Perez-Gonzalez, J., Carranza, J., Torres-Porras, J., Fernandez-Garcia, J.L., 2010. Low Heterozygosity at Microsatellite Markers in Iberian Red Deer with Small Antlers. Journal of Heredity, 101, 553–561. https://doi.org/10.1093/jhered/esq049
Pirozhnik, I.I., Mart?s?inkevich, G.I. (Eds.), 2006. Struktura geograficheskoi sredy i landshaftnoe raznoobrazie Belarusi. BGU, Minsk.
Piry, S., Luikart, G., Cornuet, J.-M., 1999. Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data. Journal of Heredity, 90, 502–503. https://doi.org/10.1093/jhered/90.4.502
Pritchard, J.K., Stephens, M., Donnelly, P., 2000. Inference of Population Structure Using Multilocus Genotype Data. Genetics, 155, 945–959. https://doi.org/10.1093/genetics/155.2.945
QGIS Development Team, 2009. QGIS Geographic Information System. Open Source Geospatial Foundation.
Queiros, J., Acevedo, P., Santos, J.P.V., Barasona, J., Beltran-Beck, B., Gonzalez-Barrio, D., Armenteros, J.A., Diez-Delgado, I., Boadella, M., Fernandez de Mera, I., Ruiz-Fons, J.F., Vicente, J., de la Fuente, J., Gortazar, C., Searle, J.B., Alves, P.C., 2019. Red deer in Iberia: Molecular ecological studies in a southern refugium and inferences on European postglacial colonization history. PLoS ONE, 14, e0210282. https://doi.org/10.1371/journal.pone.0210282
Queiros, J., Godinho, R., Lopes, S., Gortazar, C., de la Fuente, J., Alves, P.C., 2015. Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross-specific and species-specific amplifications. Mol Ecol Resour, 15, 747–760. https://doi.org/10.1111/1755-0998.12349
Queiros, J., Vicente, J., Boadella, M., Gortazar, C., Alves, P.C., 2014. The impact of management practices and past demographic history on the genetic diversity of red deer (Cervus elaphus): an assessment of population and individual fitness: Genetic diversity, of red deer. Biol J Linn Soc Lond, 111, 209–223. https://doi.org/10.1111/bij.12183
Ralls, K., Ballou, J.D., Dudash, M.R., Eldridge, M.D.B., Fenster, C.B., Lacy, R.C., Sunnucks, P., Frankham, R., 2018. Call for a Paradigm Shift in the Genetic Management of Fragmented Populations: Genetic management. Conservation Letters, 11, e12412. https://doi.org/10.1111/conl.12412
Reed, D.H., Frankham, R., 2003. Correlation between Fitness and Genetic Diversity. Conservation Biology, 17, 230–237. https://doi.org/10.1046/j.1523-1739.2003.01236.x
Reiner, G., Lang, M., Willems, H., 2019. Impact of different panels of microsatellite loci, different numbers of loci, sample sizes, and gender ratios on population genetic results in red deer. Eur J Wildl Res, 65, 25. https://doi.org/10.1007/s10344-019-1262-x
Report on the management of the hunting economy for 2020, 2021. Ministry of Forestry of the Republic of Belarus, Minsk.
Report on the management of the hunting economy for 2021, 2022. Ministry of Forestry of the Republic of Belarus, Minsk.
Rodger, J.C., Clulow, J., 2021. Resetting the paradigm of reproductive science and conservation. Anim Reprod Sci, 106911. https://doi.org/10.1016/j.anireprosci.2021.106911
Romanov, V.S., 2000. История охотничьего хозяйства Беларуси [Istoriya okhotnich’yego khozyaystva Belarusi]. Trudy BGTU I, 8, 57–64.
Romanov, V.S., Kozlo, P.G., 2002. Благородный олень (Cervus E. elaphus) в Беларуси и основные принципы программы по его дальнейшей реакклиматизации [Blagorodnyy olen’ (Cervus e. elaphus) v Belarusi i osnovnyye printsipy programmy po yego dal’neyshey reakklimatizatsii]. Trudy BGTU I, 10, 30–42.
Ryman, N., Leimar, O., 2009. G ST is still a useful measure of genetic differentiation - a comment on Jost’s D. Molecular Ecology, 18, 2084–2087. https://doi.org/10.1111/j.1365-294X.2009.04187.x
Shakun, V.V., 2011. Особенности формирования популяций благородного оленя в беларуси и факторы, их обуславливающие [Osobennosti formirovaniya populyatsiy blagorodnogo olenya v belarusi i faktory, ikh obuslavlivayushchiye]. Minsk.
Shakun, V.V., Geshtovt, P.A., Veligurov, P.A., 2021. План управления популяцией оленя благородного в республике Беларусь [Plan upravleniya populyatsiyey olenya blagorodnogo v respublike Belarus]. Minsk.
Shakun, V.V., Veligurov, P.A., 2018. Расселение благородного оленя в Беларуси [Rasseleniye blagorodnogo olenya v Belarusi], in: Tezisy Dokladov 82-y Nauchno-Tekhnicheskoy Konferentsii Professorsko-Prepodavatel’skogo Sostava, Nauchnykh Sotrudnikov i Aspirantov (s Mezhdunarodnym Uchastiyem), Lesnoye Hoziaystvo. Presented at the 82-ya nauchno-tekhnicheskaya konferentsiya professorsko-prepodavatel’skogo sostava, nauchnykh sotrudnikov i aspirantov BGTU, BGTU, Minsk, pp. 160–161.
Shostak, S.V., 1974. Территориальное распределение оленя в Беловежской пуще [Territorial’noye raspredeleniye olenya v Belovezhskoy pushche]. Belovezhskaya Pushcha, 5, 141–145.
Shostak, S.V., Vakula, V.A., Vasilyuk, I.F., 1974. Отлов и расселение оленей Беловежской пущи [Otlov i rasseleniye oleney Belovezhskoy pushchi]. Belovezhskaya Pushcha, 5, 133–141.
Skog, A., Zachos, F.E., Rueness, E.K., Feulner, P.G.D., Mysterud, A., Langvatn, R., Lorenzini, R., Hmwe, S.S., Lehoczky, I., Hartl, G.B., Stenseth, N.C., Jakobsen, K.S., 2009. Phylogeography of red deer ( Cervus elaphus ) in Europe. Journal of Biogeography, 36, 66–77. https://doi.org/10.1111/j.1365-2699.2008.01986.x
Spielman, D., Brook, B.W., Frankham, R., 2004. Most species are not driven to extinction before genetic factors impact them. Proc. Natl. Acad. Sci. U.S.A., 101, 15261–15264. https://doi.org/10.1073/pnas.0403809101
Steffen, P., Eggen, A., Stranzinger, G., Fries, R., Dietz, A.B., Womack, J.E., 2009. Isolation and mapping of polymorphic microsatellites in cattle. Animal Genetics, 24, 121–124. https://doi.org/10.1111/j.1365-2052.1993.tb00252.x
R Core Team, 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Thieven, U., Solinas-Toldo, S., Friedl, R., Masabanda, J., Fries, R., Barendse, W., Simon, D., Harlizius, B., 1997. Polymorphic CA-microsatellites for the integration of the bovine genetic and physical map. Mammalian Genome, 8, 52–55. https://doi.org/10.1007/s003359900348
Vaiman, D., Mercier, D., Moazami-Goudarzi, K., Eggen, A., Ciampolini, R., Lepingle, A., Velmala, R., Kaukinen, J., Varvio, S.L., Martin, P., 1994. A set of 99 cattle microsatellites: characterization, synteny mapping, and polymorphism. Mammalian Genome, 5, 288–297. https://doi.org/10.1007/BF00389543
Valnisty, A.A., 2019. Разработка панели микросателлитных маркеров для мультиплексного генотипирования белорусских популяций благородного оленя (Cervus elaphus L., 1758) [Razrabotka paneli microsatellitnykh markerov dlya multiplexnogo genotipirovaniya belorusskikh populyatsiy blagorodnogo olenya (Cervus elaphus L., 1758)], in: 2019. Struktura i Dinamika Bioraznoobraziya. Presented at the Zaochnaya konferentsiya molodykh uchenyh 23 dec 2019., BSU, Minsk, pp. 260–263.
Van Oosterhout, C., Hutchinson, W.F., Wills, D.P.M., Shipley, P., 2004. Micro-Checker: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes, 4, 535–538. https://doi.org/10.1111/j.1471-8286.2004.00684.x
Wilson, G.A., Nishi, J.S., Elkin, B.T., Strobeck, C., 2006. Effects of a recent founding event and intrinsic population dynamics on genetic diversity in an ungulate population. Conserv Genet, 6, 905–916. https://doi.org/10.1007/s10592-005-9077-6
Zachos, F.E., Frantz, A.C., Kuehn, R., Bertouille, S., Colyn, M., Niedzialkowska, M., Perez-Gonzalez, J., Skog, A., Sprem, N., Flamand, M.-C., 2016. Genetic Structure and Effective Population Sizes in European Red Deer (Cervus elaphus) at a Continental Scale: Insights from Microsatellite DNA. JHERED, 107, 318–326. https://doi.org/10.1093/jhered/esw011


 


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