Data from: Evaluating methods for estimating local effective population size with and without migration

Effective population size is a fundamental parameter in population genetics, evolutionary biology and conservation biology, yet its estimation can be fraught with difficulties. Several methods to estimate Ne from genetic data have been developed which take advantage of various approaches for inferring Ne. The ability of these methods to accurately estimate Ne, however, has not been comprehensively examined. In this study, we employ seven of the most cited methods for estimating Ne from genetic data (Colony2, CoNe, Estim, MLNe, ONeSAMP, TMVP, and NeEstimator including LDNe) across simulated datasets with populations experiencing migration or no migration. The simulated population demographies are an isolated population with no immigration, an island model metapopulation with a sink population receiving immigrants, and an isolation by distance stepping stone model of populations. We find considerable variance in performance of these methods, both within and across demographic scenarios, with some methods performing very poorly. The most accurate estimates of Ne can be obtained by using LDNe, MLNe, or TMVP; however each of these approaches is outperformed by another in a differing demographic scenario. Knowledge of the approximate demography of population as well as the availability of temporal data largely improves Ne estimates.有效种群大小（effective population size，后文简称Ne）是种群遗传学、进化生物学与保护生物学中的核心参数，但其估算往往颇具挑战。学界已开发出多种基于遗传数据估算Ne的方法，这些方法依托多样的推演路径来获取Ne的取值。然而，目前尚未有研究对这些方法精准估算Ne的能力进行全面评估。本研究针对涵盖存在基因流与无基因流种群的模拟数据集，采用了7种被引频次最高的遗传数据Ne估算方法（Colony2、CoNe、Estim、MLNe、ONeSAMP、TMVP以及包含LDNe的NeEstimator）。本次模拟的种群动态场景包括：无外源迁入的孤立种群、包含接收外源个体的汇种群的岛屿模型复合种群，以及距离隔离踏脚石种群模型。研究发现，这些方法的性能在同一动态场景内以及不同场景间均存在显著差异，部分方法的估算表现极差。LDNe、MLNe与TMVP可获得最为精准的Ne估算结果，但在不同的种群动态场景中，这三种方法各自会在特定场景下被其他方法超越。若预先掌握种群大致的动态场景信息，且可获取时序遗传数据，则可显著提升Ne的估算精度。