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, Ne）是种群遗传学、进化生物学与保护生物学领域的核心参数，但其估算工作往往面临诸多挑战。目前学界已开发出多种依托各类推断手段从遗传数据中估算Ne的技术方案，然而现有研究尚未对这些方法准确估算Ne的能力展开全面系统的评估。本研究针对存在迁移与无迁移的模拟种群数据集，选取七种被高频引用的遗传数据Ne估算方法（Colony2、CoNe、Estim、MLNe、ONeSAMP、TMVP以及包含LDNe的NeEstimator）开展对比分析。本次模拟的种群人口统计学场景涵盖三类：无外源迁入的孤立种群、带有接收移民汇种群的岛式模型复合种群，以及存在距离隔离效应的阶梯式种群空间模型。研究结果显示，各类方法在不同种群人口统计学场景下，乃至同一场景内部的表现均存在显著差异，部分方法的估算表现极差。其中，LDNe、MLNe与TMVP可获得精度最高的Ne估算结果，但在不同的种群人口统计学场景中，这三种方法各自存在更具优势的替代方案。若能预先掌握种群大致的人口统计学特征，且有时序遗传数据可供使用，则可显著提升Ne估算的准确性。