Kamath Pauline L, Haroldson Mark A, Luikart Gordon, Paetkau David, Whitman Craig, van Manen Frank T
U.S. Geological Survey, Northern Rocky Mountain Science Center, 2327 University Way, Suite 2, Bozeman, MT, 59715, USA.
Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Missoula, MT, 59812, USA.
Mol Ecol. 2015 Nov;24(22):5507-21. doi: 10.1111/mec.13398. Epub 2015 Oct 28.
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.
有效种群大小(N(e))是监测受威胁种群遗传健康状况的关键参数,因为它反映了种群的进化潜力以及因遗传随机性导致的灭绝风险。然而,其在野生动物监测中的应用一直受到限制,因为在自然种群中难以测量。大黄石生态系统中隔离且经过充分研究的灰熊(棕熊,学名:Ursus arctos)种群提供了一个难得的机会,可用于检验不同N(e)估计方法在监测中的实用性。我们使用20个微卫星对729只黄石灰熊进行了基因分型,并应用三种单样本估计方法来研究1982 - 2007年间世代间隔(GI)、有效繁殖个体数量(N(b))和N(e)的当代趋势。我们还使用多样本方法来估计方差有效种群大小(N(eV))和近交有效种群大小(N(eI))。单样本估计显示出积极的变化趋势,从20世纪80年代到21世纪初,N(e)增加了四倍多(约从100增至450),GI几乎翻倍(约从8增至14)。在这段时间内,N(eV)(240 - 319)和N(eI)(256)与调和平均单样本N(e)(213)相当。重新分析历史数据时,我们发现N(eV)从20世纪10年代至60年代的约80增加到当代种群的约280。与之前对棕熊的研究相比,估计的有效种群大小与总普查种群大小的比率(N(e) /N(c))稳定且较高(0.42 - 0.66)。这些结果支持了自20世纪80年代以来黄石灰熊种群增长的独立种群统计学证据。它们进一步证明了对N(e)的遗传监测如何能够补充基于种群统计学的N(c)和生命率监测,为野生动物管理者提供了一个有价值的工具。