Luikart Gordon, Antao Tiago, Hand Brian K, Muhlfeld Clint C, Boyer Matthew C, Cosart Ted, Trethewey Brian, Al-Chockhachy Robert, Waples Robin S
Flathead Lake Biological Station, Montana Conservation Genomics Laboratory, Division of Biological Sciences, University of Montana, Polson, MT, USA.
The Welcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
Mol Ecol Resour. 2021 Feb;21(2):379-393. doi: 10.1111/1755-0998.13251. Epub 2020 Dec 23.
Estimating the effective population size and effective number of breeders per year (N ) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of N in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. N estimates were biased by ~5%-10% when using SNPs or microsatellites in species ranging from fishes to mosquitoes, frogs, and seaweed. The bias (high or low) was similar for different life history types within a species suggesting that life history variation in populations will not influence N estimation. Precision was higher for 100 SNPs (H ≈ 0.30) than for 15 microsatellites (H ≈ 0.70). Confidence intervals (CIs) were occasionally too narrow, and biased high when N was small (N < 50); however, the magnitude of bias would unlikely influence management decisions. The CIs (from LDNe) were sufficiently narrow to achieve high statistical power (≥0.80) to reject the null hypothesis that N = 50 when the true N = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject N = 500 when the true N = 400 and when sampling 200 individuals and 5,000 loci. Finally, we present a linear regression method that provides high power to detect a decline in N when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate N for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in N and population declines.
估计有效种群大小和每年的有效繁殖个体数（N）有助于早期发现种群数量下降。我们使用计算机模拟，利用一系列已发表的物种生活史类型、样本量和DNA标记，来量化年龄结构种群中N的单样本LDNe估计器的偏差和精度。在从鱼类到蚊子、青蛙和海藻等物种中，使用单核苷酸多态性（SNP）或微卫星时，N的估计偏差约为5%-10%。同一物种内不同生活史类型的偏差（高或低）相似，这表明种群中的生活史变异不会影响N的估计。100个SNP（H≈0.30）的精度高于15个微卫星（H≈0.70）。当N较小时（N<50），置信区间（CI）偶尔会过窄且偏高；然而，偏差的大小不太可能影响管理决策。当真实N = 30且采样50个个体和200个SNP时，来自LDNe的CI足够窄，以实现高统计功效（≥0.80）来拒绝N = 50的零假设。同样，当真实N = 400且采样200个个体和5000个位点时，CI足够窄以拒绝N = 500。最后，我们提出了一种线性回归方法，当对至少五个连续队列进行采样时，该方法具有高功效来检测N的下降。本研究提供了用于模拟和估计年龄结构种群N的指南和工具（https://github.com/popgengui/agestrucnb/），这应该有助于生物学家制定敏感的监测计划，以早期发现N的变化和种群数量下降。
