Biology and Marine Biology Program, University of Alaska Southeast, 11120 Glacier Highway, Juneau, AK 99801, USA.
Mol Ecol Resour. 2010 Jul;10(4):684-92. doi: 10.1111/j.1755-0998.2010.02831.x. Epub 2010 Feb 12.
The utility of microsatellite markers for inferring population size and trend has not been rigorously examined, even though these markers are commonly used to monitor the demography of natural populations. We assessed the ability of a linkage disequilibrium estimator of effective population size (N(e) ) and a simple capture-recapture estimator of abundance (N) to quantify the size and trend of stable or declining populations (true N = 100-10,000), using simulated Wright-Fisher populations. Neither method accurately or precisely estimated abundance at sample sizes of S = 30 individuals, regardless of true N. However, if larger samples of S = 60 or 120 individuals were collected, these methods provided useful insights into abundance and trends for populations of N = 100-500. At small population sizes (N = 100 or 250), precision of the N(e) estimates was improved slightly more by a doubling of loci sampled than by a doubling of individuals sampled. In general, monitoring N(e) proved a more robust means of identifying stable and declining populations than monitoring N over most of the parameter space we explored, and performance of the N(e) estimator is further enhanced if the N(e) /N ratio is low. However, at the largest population size (N = 10,000), N estimation outperformed N(e) . Both methods generally required ≥ 5 generations to pass between sampling events to correctly identify population trend.
微卫星标记在推断种群大小和趋势方面的效用尚未经过严格检验,尽管这些标记常用于监测自然种群的动态。我们评估了连锁不平衡有效种群大小估计器(Ne)和简单的捕获-再捕获丰度估计器(N)的能力,以量化稳定或下降种群(真实 N = 100-10,000)的大小和趋势,使用模拟的 Wright-Fisher 种群。这两种方法都不能准确或精确地估计样本大小为 S = 30 个个体的丰度,无论真实 N 如何。然而,如果收集到更大的样本量 S = 60 或 120 个个体,这些方法可以为 N = 100-500 的种群提供有用的丰度和趋势信息。在小种群大小(N = 100 或 250)下,通过加倍采样的位点而不是加倍采样的个体,Ne 估计的精度略有提高。一般来说,在我们探索的大多数参数空间中,监测 Ne 比监测 N 更能有效地识别稳定和下降的种群,并且如果 Ne/N 比率较低,则 Ne 估计器的性能进一步提高。然而,在最大种群大小(N = 10,000)下,N 估计值优于 Ne。这两种方法通常需要在采样事件之间至少经过 5 代才能正确识别种群趋势。