Data from: Effects of phylogenetic reconstruction method on the robustness of species delimitation using single-locus data

1. Coalescent-based species delimitation methods combine population genetic and phylogenetic theory to provide an objective means for delineating evolutionarily significant units of diversity. The Generalized Mixed Yule Coalescent (GMYC) and the Poisson Tree Process (PTP) are methods that use ultrametric (GMYC or PTP) or non-ultrametric (PTP) gene trees as input, intended for use mostly with single-locus data such as DNA barcodes. 2. Here we assess how robust the GMYC and PTP are to different phylogenetic reconstruction and branch smoothing methods. We reconstruct over 400 ultrametric trees using up to 30 different combinations of phylogenetic and smoothing methods and perform over 2,000 separate species delimitation analyses across 16 empirical datasets. We then assess how variable diversity estimates are, in terms of richness and identity, with respect to species delimitation, phylogenetic and smoothing methods. 3. The PTP method generally generates diversity estimates that are more robust to different phylogenetic methods. The GMYC is more sensitive, but provides consistent estimates for BEAST trees. The lower consistency of GMYC estimates is likely a result of differences among gene trees introduced by the smoothing step. Unresolved nodes (real anomalies or methodological artefacts) affect both GMYC and PTP estimates, but have a greater effect on GMYC estimates. Branch smoothing is a difficult step and perhaps an underappreciated source of bias that may be widespread among studies of diversity and diversification. 4. Nevertheless, careful choice of phylogenetic method does produce equivalent PTP and GMYC diversity estimates. We recommend simultaneous use of the PTP model with any model-based gene tree (e.g. RAxML) and GMYC approaches with BEAST trees for obtaining species hypotheses.1. 基于溯祖的物种界定方法（Coalescent-based species delimitation methods）整合了群体遗传学与系统发育理论，可为界定演化上具有显著意义的多样性单元提供客观手段。广义混合尤尔溯祖模型（Generalized Mixed Yule Coalescent, GMYC）与泊松树过程模型（Poisson Tree Process, PTP）是两类以超度量树（适用于GMYC或PTP）或非超度量基因树（仅适用于PTP）作为输入的方法，多数情况下适配单基因座数据（如DNA条形码）。2. 本研究旨在评估GMYC与PTP对不同系统发育重建及分支平滑方法的鲁棒性。我们通过组合至多30种系统发育分析与平滑方法，重建了400余棵超度量树，并针对16个实证数据集开展了2000余次独立的物种界定分析。随后，我们从物种丰富度与物种同一性两个维度，评估了不同物种界定方法、系统发育方法及平滑方法所得到的多样性估计值的变异性。3. PTP方法生成的多样性估计值通常对不同系统发育方法的鲁棒性更强。GMYC则更为敏感，但针对BEAST树可得到一致的估计结果。GMYC估计值一致性较低的原因，可能源于分支平滑步骤所引入的基因树差异。未解析节点（包括真实演化异常或方法学人为误差）会同时影响GMYC与PTP的估计结果，但对GMYC的影响更为显著。分支平滑是一个极具挑战性的步骤，或许也是多样性与分化研究中普遍存在但未被充分重视的偏倚来源。4. 尽管如此，谨慎选择系统发育方法仍可使PTP与GMYC得到等价的多样性估计结果。我们建议：将PTP模型与任何基于模型的基因树（如RAxML）结合使用，同时将GMYC方法与BEAST树结合，以获取物种假说。