Individual identification was assessed for 30 brown bears (Ursus arctos) from the endangered Apennine population in central Italy, mostly through non-invasive sampling. Shed hairs were used as a source of DNA to obtain single genotype profiling at 12 microsatellite loci. Average expected heterozygosity (0.438) and mean number of alleles per locus (2.2) showed that the level of genetic diversity was one of the lowest recorded for brown bear populations across their European and North American ranges. A large portion of the original genetic variation may have been lost through random genetic drift during the recent period of isolation. The level of genetic variability proved sufficient to identify the bears individually by using nine microsatellite loci. The probability that two animals shared by chance the same multilocus genotype was estimated to be 1 in 100. Despite the recent history of small population size, the average relatedness indicated that the majority of individuals are not first-order relatives. Simulated paternity tests showed that a 12-loci genotype may be necessary to assign paternity with an 80–95% confidence level. Lack of genetic diversity, as well as the maintenance of an adequately effective number, may seriously jeopardise the long-term survival of this population. Furthermore, high mortality rates, poaching and encroachment by human activities represent immediate, urgent concerns. A population increase through enforced protection and habitat restoration is recommended. Presently, restocking with bears from other source populations should be discouraged to avoid genetic extinction. Non-invasive sampling provided reliable population and individual genetic data. Microsatellite genotyping proved a valuable genetic tagging method and a feasible alternative to conventional field counts for the brown bear in central Italy.
Lorenzini, R., Posillico, M., Lovari, S., Petrella, A. (2004). Non-invasive genotyping of the endangered Apennine brown bear: a case study not to let one’s hair down. ANIMAL CONSERVATION, 7(2), 199-209 [10.1017/S1367943004001301].
Non-invasive genotyping of the endangered Apennine brown bear: a case study not to let one’s hair down
LOVARI S.;
2004-01-01
Abstract
Individual identification was assessed for 30 brown bears (Ursus arctos) from the endangered Apennine population in central Italy, mostly through non-invasive sampling. Shed hairs were used as a source of DNA to obtain single genotype profiling at 12 microsatellite loci. Average expected heterozygosity (0.438) and mean number of alleles per locus (2.2) showed that the level of genetic diversity was one of the lowest recorded for brown bear populations across their European and North American ranges. A large portion of the original genetic variation may have been lost through random genetic drift during the recent period of isolation. The level of genetic variability proved sufficient to identify the bears individually by using nine microsatellite loci. The probability that two animals shared by chance the same multilocus genotype was estimated to be 1 in 100. Despite the recent history of small population size, the average relatedness indicated that the majority of individuals are not first-order relatives. Simulated paternity tests showed that a 12-loci genotype may be necessary to assign paternity with an 80–95% confidence level. Lack of genetic diversity, as well as the maintenance of an adequately effective number, may seriously jeopardise the long-term survival of this population. Furthermore, high mortality rates, poaching and encroachment by human activities represent immediate, urgent concerns. A population increase through enforced protection and habitat restoration is recommended. Presently, restocking with bears from other source populations should be discouraged to avoid genetic extinction. Non-invasive sampling provided reliable population and individual genetic data. Microsatellite genotyping proved a valuable genetic tagging method and a feasible alternative to conventional field counts for the brown bear in central Italy.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/24587
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