Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches
The effective population size (Ne) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in na...
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Dryad
2021
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Online Access: | https://doi.org/10.5061/dryad.22rm1728 |
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fttriple:oai:gotriple.eu:50|dedup_wf_001::882778d15b8b9977002fc9d36553752c 2023-05-15T18:42:02+02:00 Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches Skrbinšek, Tomaž Jelenčič, Maja Waits, Lisette Kos, Ivan Jerina, Klemen Trontelj, Peter 2021-06-28 https://doi.org/10.5061/dryad.22rm1728 en eng Dryad http://dx.doi.org/10.5061/dryad.22rm1728 https://dx.doi.org/10.5061/dryad.22rm1728 lic_creative-commons 10.5061/dryad.22rm1728 oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:81521 oai:easy.dans.knaw.nl:easy-dataset:81521 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 re3data_____::r3d100000044 10|openaire____::081b82f96300b6a6e3d282bad31cb6e2 10|opendoar____::8b6dd7db9af49e67306feb59a8bdc52c Ursus arctos genetic monitoring Holocene Wildlife Management effective population size Population Genetics - Empirical Life sciences medicine and health care conservation genetics population dynamics Slovenia 45°29'N - 46°32'N 13°44'E - 15°25'E geo stat Dataset https://vocabularies.coar-repositories.org/resource_types/c_ddb1/ 2021 fttriple https://doi.org/10.5061/dryad.22rm1728 2023-01-22T17:23:37Z The effective population size (Ne) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating Ne from a single sample of genotypes to trace temporal change in Ne for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci, and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both Ne and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (Nb) using Linkage Disequilibrium, Sibship Assignment and Approximate Bayesian Computation methods, and extrapolated these estimates to Ne using the generation interval. The Ne estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of Ne > 50 but short of the long-term minimum viable population goal of Ne > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in Ne probably in the late 1990s and early 2000s. The new single-sample approaches to estimation of Ne provide efficient means for including Ne in monitoring frameworks, and will be of great importance for future management and conservation. Genotypes of bears from SloveniaThe dataset contains genotypes of 510 brown bears genotyped on 22 microsatellite loci. They were obtained by genotyping tissue samples of legally killed bears between 2003 and 2008. Genotype on locus G10H is unrealiable (genotyping problems), and locus Mu26 has null alleles. Both were excluded from analysis, and have some missing data. All genotypes are complete on all other loci. Additional ... Dataset Ursus arctos Unknown |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
Ursus arctos genetic monitoring Holocene Wildlife Management effective population size Population Genetics - Empirical Life sciences medicine and health care conservation genetics population dynamics Slovenia 45°29'N - 46°32'N 13°44'E - 15°25'E geo stat |
spellingShingle |
Ursus arctos genetic monitoring Holocene Wildlife Management effective population size Population Genetics - Empirical Life sciences medicine and health care conservation genetics population dynamics Slovenia 45°29'N - 46°32'N 13°44'E - 15°25'E geo stat Skrbinšek, Tomaž Jelenčič, Maja Waits, Lisette Kos, Ivan Jerina, Klemen Trontelj, Peter Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
topic_facet |
Ursus arctos genetic monitoring Holocene Wildlife Management effective population size Population Genetics - Empirical Life sciences medicine and health care conservation genetics population dynamics Slovenia 45°29'N - 46°32'N 13°44'E - 15°25'E geo stat |
description |
The effective population size (Ne) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating Ne from a single sample of genotypes to trace temporal change in Ne for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci, and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both Ne and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (Nb) using Linkage Disequilibrium, Sibship Assignment and Approximate Bayesian Computation methods, and extrapolated these estimates to Ne using the generation interval. The Ne estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of Ne > 50 but short of the long-term minimum viable population goal of Ne > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in Ne probably in the late 1990s and early 2000s. The new single-sample approaches to estimation of Ne provide efficient means for including Ne in monitoring frameworks, and will be of great importance for future management and conservation. Genotypes of bears from SloveniaThe dataset contains genotypes of 510 brown bears genotyped on 22 microsatellite loci. They were obtained by genotyping tissue samples of legally killed bears between 2003 and 2008. Genotype on locus G10H is unrealiable (genotyping problems), and locus Mu26 has null alleles. Both were excluded from analysis, and have some missing data. All genotypes are complete on all other loci. Additional ... |
format |
Dataset |
author |
Skrbinšek, Tomaž Jelenčič, Maja Waits, Lisette Kos, Ivan Jerina, Klemen Trontelj, Peter |
author_facet |
Skrbinšek, Tomaž Jelenčič, Maja Waits, Lisette Kos, Ivan Jerina, Klemen Trontelj, Peter |
author_sort |
Skrbinšek, Tomaž |
title |
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
title_short |
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
title_full |
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
title_fullStr |
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
title_full_unstemmed |
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches |
title_sort |
data from: monitoring the effective population size of a brown bear (ursus arctos) population using new single-sample approaches |
publisher |
Dryad |
publishDate |
2021 |
url |
https://doi.org/10.5061/dryad.22rm1728 |
genre |
Ursus arctos |
genre_facet |
Ursus arctos |
op_source |
10.5061/dryad.22rm1728 oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:81521 oai:easy.dans.knaw.nl:easy-dataset:81521 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 re3data_____::r3d100000044 10|openaire____::081b82f96300b6a6e3d282bad31cb6e2 10|opendoar____::8b6dd7db9af49e67306feb59a8bdc52c |
op_relation |
http://dx.doi.org/10.5061/dryad.22rm1728 https://dx.doi.org/10.5061/dryad.22rm1728 |
op_rights |
lic_creative-commons |
op_doi |
https://doi.org/10.5061/dryad.22rm1728 |
_version_ |
1766231630495612928 |