Testing the influence of habituation on genetic structure of brown bear (Ursus arctos)
DOI:
https://doi.org/10.15287/afr.2015.355Keywords:
genetic structure, brown bear, habituation, management, conservationAbstract
Adult bear individuals live solitary and haveprolonged parent–offspring relationships, therefore the share of learned skills compared to the inherited ones is much larger than in other carnivores. This promotes acquisition of deviated behavior and simultaneously establishment of a kinship structure. However, deviated bear behavior and human food conditioning are the symptoms of habituation. The aim of this paper is to test the genetic structuring of habituated and non-habituated individuals located in the central region of Romania (Braşov and Prahova districts), a hotspot in terms of human-bear conflicts. Seven microsatellites were used to genotype 145 samples (ear clips and tissue), out of which 82 were classified as habituated and 63 as wild individuals, respectively. Our results suggest the presence of kinship structures in habituated bear group and a reduction of genetic diversity (He = 0.75), while the group located in the wild registered a higher genetic diversity (He = 0.78) and more private alleles. The genetic differentiation suggested by the Neighbor joining cluster analysis has been strengthened by the two percent (AMOVA) differences between the two groups and highlights the negative impact of brown bear kinship structure, caused by the human expansion on wilderness. The genetic analyses indicated that the two groups share genetic variants due to the dispersal and breeding patterns of male adult bears. The emergence of genetic differences between the two groups can be avoided by preventing bears to become human-food conditioned; over time, kinship structure can pose a threat to genetic diversity.References
Aumiller, L. D., Matt C. A., 1994. Management of McNeil River State Game Sanctuary for viewing of brown bears. International Conference on Bear Research and Management 9:51-61. Bellemain E., Taberlet P., 2004. Improved noninvasive genotyping method: application to brown bear (Ursus arctos) faeces. Molecular Ecology Notes 4: 519-522. DOI: 10.1111/j.1471-8286.2004.00711.x Breck S.W., Williams C.L., Beckmann J.P., Matthews S.M., Lackey C.W., Beecham J.J, 2008. Using genetic relatedness to investigate the development of conflict behavior in black bears. Journal of Mammalogy 89: 428-434. DOI: 10.1644/07-MAMM-A-028R2.1 Cazacu C., Adamescu M.C., Ionescu O., Ionescu, G., Jurj R., Popa M., Cazacu R., Cotovelea A., 2014. Mapping trends of large and medium size carnivores of conservation interest inRomania. Annals ofForestResearch 57: 97-107. Cotovelea A., 2014a. Assessing the genetic structure of brown bear (Ursus arctos L.) in Romanian Carpathians using molecular markers. Ph.D. Thesis, 138 p. Cotovelea A., 2014b. Predictive models for gene flow "landscape genetics" in Romanian large carnivores populations. Revista de Silvicultura si Cinegetica 34. Cotovelea A., Sofletea N., Ionescu G., Ionescu O., 2013a. Genetic approaches for Romanian brown bear Ursus arctos. conservation. Bulletin of theTransilvaniaUniversityofBrasov6. Cotovelea A., Sofletea N., Ionescu G., Jurj R., Ionescu O., 2013b. Dna isolation and amplification in Romanian species of wild animals. Proceeding of theForestand Sustainable Development. Brașov,Romania, 19-20 October 2012. 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. DOI: 10.1111/j.1365-294X.2005.02553.x Elfström M., Zedrosser A., Jerina K., Støen O.G., Kindberg J., Budic L., Jonozovič M., Swenson J.E., 2014. Does despotic behavior or food search explain the occurrence of problem brown bears in Europe? The Journal of Wildlife Management. DOI: 10.1002/jwmg.727 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. Falush D., Stephens M., Pritchard J.K., 2007. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol Ecol Notes 7: 574-578. DOI: 10.1111/j.1471-8286.2007.01758.x Gilbert, B.K., 1999. Opportunities for social learning in bears. Mammalian social learning: comparative and ecological perspectives H. O. Box an K. R. Gibson, eds. Cambridge University Press,Cambridge,United Kingdom Gittleman J.L., GompperM.E., 2001. The Risk of Extinction--What You Don't Know Will Hurt You. Science 291: 997-999. DOI: 10.1126/science.291.5506.997 Hochberg Y., 1988. Asharper Bonferroni procedure for multiple tests of significance. Biometrika 75: 800-802. DOI: 10.1093/biomet/75.4.800 Gunther K.A., 2004. Management of habituated grizzly bears in North America J. Rahm ed., Trans. of the 69th North American Wildlife and Natural Resources Conference.Washington: Wildlife Management Institute. HopkinsJ.B, 2013. Use of genetics to investigate socially learned foraging behavior in free-ranging black bears. Journal of Mammalogy 94: 1214-1222. DOI: 10.1644/13-MAMM-A-009.1 Huber, D., Dabanovic, V., Kusak, J., Frkovic A., 1994. Reintroduction of hand-reared brown bears into the wild: experiences, problems. In G.M. Dorrestein, M. Kahraman eds. Proceedings of the International Conference on Aspects of Bear Conservation,Bursa,Turkey179-186. Huber D., 1995. Rehabilitation and release of bears. Editors:LydiaKolter, Jiska van Dijk. Zoologischer Garten Köln. 163 p. ISBN: 3-00-017089-8. Hubisz M.J., Falush D., Stephens M., Pritchard J.K., 2009. Inferring weak population structure with the assistance of sample group information. Mol Ecol Resour 9: 1322-1332. DOI: 10. 1111/j.1755-0998.2009.02591.x Ionescu O. 1999. The management of the brown bear inRomania. Bear Conservation Action Plan, IUCN. Jerina K., Jonozovič M., Krofel M., Skrbinšek T. 2013. Range and local population densities of brown bear Ursus arctos in Slovenia. European Journal of Wildlife Research, 59, 459-467. DOI: 10.1007/s10344-013-0690-2 Jerina K., Debeljak M., Džeroski S., Kobler A., Adamič, M., 2003. Modeling the brown bear population in Slovenia. Ecological Modelling 170: 453-469. DOI: 10.1016/S0304-3800(03)00245-X Konovalov D.A., Manning C., Henshaw M.T., 2004. KinGroup: a program for pedigree relationship reconstruction and kin group assignments using genetic markers. Molecular Ecology Notes 4: 779-782. DOI: 10.1111/j.1471-8286.2004.00796.x Langella O., 1999. Populations Version 1.2.30. Distributed by the author, CNRS UPR9034, France. Mace R.D., Waller J.S., 1996. Final report: grizzly bear ecology in theSwanMountains,Montana. Madison, J. S., 2008.YosemiteNational Park: the continuous evolution of human–black bear conflict management. Human-Wildlife Conflicts 2:153–157. Nellemann C., Støen O.G., Kindberg J., Swenson J.E., Vistnes I., Ericsson, G., Katajisto J., Kaltenborn B.P., Martin J., Ordiz A., 2007. Terrain use by an expanding brown bear population in relation to age, recreational resorts and human settlements. Biological Conservation 138: 157-165. DOI: 10.1016/j.biocon.2007.04.011 Paetkau D., Shields G.F., Strobeck, C., 1998. Gene flow between insular, coastal and interior populations of brown bears in Alaska. Mol Ecol 7: 1283-1292. DOI: 10.1046/j.1365-294x.1998.00440.x Paetkau D., Calvert W., StirlingI., Strobeck, C., 1995. Microsatellite analysis of population structure in Canadian polar bears. Mol Ecol 4: 347-354. DOI: 10.1111/j.1365-294X.1995.tb00227.x Peakall R.O.D., Smouse P.E., 2006. genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6, 288-295. DOI: 10.1111/ j.1471-8286.2005.01155.x Pritchard J.K., Stephens M., Donnelly, P., 2000. Inference of Population Structure Using Multilocus Genotype Data. Genetics 155: 945-959. Roderic D. M., 2000. TREEVIEW: An application to display phylogenetic trees on personal computers. Computer Applications in the Biosciences 12: 357-358. RogersL.L., 2011. Does diversionary feeding create nuisance bears and jeopardize public safety? Human Wildlife Interactions 5: 287-295. Røskaft E., Bjerke T., Kaltenborn B., Linnell J.D.C., Andersen R., 2003. Patterns of self-reported fear towards large carnivores among the Norwegian public. Evolution and Human Behavior 24: 184-198. DOI: 10.1016/S1090-5138(03)00011-4 Schwartz C.C., Haroldson M.A., Gunther K.A., Moody D., 2006. Distribution of grizzly bears in the Greater Yellowstone Ecosystem in 2004. Ursus 17: 63-66. DOI: 10.2192/1537-6176(2006)17[63:DOGBIT]2.0.CO;2 Shettleworth S.J., 1988. Foraging as operant behavior and operant behavior as foraging. What have we learned? In The Psychology of Learning and Motivation: Advances in Research and Theory. G. Bower 22: 1-49. Smith, T., Herrero, S. & DeBruyn, T. (2005) Alaskan brown bears, humans and habituation. Ursus, 16, 1-10. DOI: 10.2192/1537-6176(2005)016[0001:ABBHAH]2.0.CO;2 Swenson J.E., Gerstl N., Dahle B., Zedrosser A., 2000. Action Plan for the conservation of the Brown Bear Ursus arctos inEurope. Swenson J.E. Taberlet, P., Bellemain, E. 2011. Genetics and conservation of European brown bears Ursus arctos. Mam Rev 41: 87–98. DOI: 10.1111/j.1365-2907.2010.00179.x Queller D. C., Goodnight K. F., 1989. Estimating relatedness using molecular markers. Evolution 43: 258-275. DOI: 10.2307/2409206 Zachos, F.E., Otto, M., Unici, R., Lorenzini, R., Hartl, G.B., 2008. Evidence of a phylogeographic break in the Romanian brown bear Ursus arctos. population from the Carpathians. Mammalian Biology - Zeitschrift für Säugetierkunde 73: 93-101. Zedrosser A., Dahle B., Swenson J.E., Gerstl N., 2001. Status and management of the brown bear inEurope. Ursus 12: 9-20. Weber W., Rabinowitz A.R., 1996. Aglobal perspective on large carnivore conservation. Conservation Biology 10: 1046-1054. DOI: 10.1046/j.1523-1739.1996.10041046.x Woodroffe R., 2000. Predators and people: using human density to interpret declines of large carnivores. Animal Conservation 3: 165-173. DOI: 10.1111/j.1469-1795.2000.tb00241.x
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