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Multiple estimates of effective population size for monitoring a long-lived vertebrate: an application to Yellowstone grizzly bears.
- Source :
-
Molecular ecology [Mol Ecol] 2015 Nov; Vol. 24 (22), pp. 5507-21. Date of Electronic Publication: 2015 Oct 28. - Publication Year :
- 2015
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Abstract
- Effective population size (N(e)) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well-studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different N(e) estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single-sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (N(b)) and N(e) during 1982-2007. We also used multisample methods to estimate variance (N(eV)) and inbreeding N(e) (N(eI)). Single-sample estimates revealed positive trajectories, with over a fourfold increase in N(e) (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. N(eV) (240-319) and N(eI) (256) were comparable with the harmonic mean single-sample N(e) (213) over the time period. Reanalysing historical data, we found N(eV) increased from ≈80 in the 1910s-1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (N(e) /N(c)) was stable and high (0.42-0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of N(e) can complement demographic-based monitoring of N(c) and vital rates, providing a valuable tool for wildlife managers.<br /> (© 2015 John Wiley & Sons Ltd.)
Details
- Language :
- English
- ISSN :
- 1365-294X
- Volume :
- 24
- Issue :
- 22
- Database :
- MEDLINE
- Journal :
- Molecular ecology
- Publication Type :
- Academic Journal
- Accession number :
- 26510936
- Full Text :
- https://doi.org/10.1111/mec.13398