Data from: Partially incorrect fossil data augment analyses of discrete trait evolution in living species

Ancestral state reconstruction of discrete character traits is often vital when attempting to understand the origins and homology of traits in living species. Recently, the addition of fossils has been shown to alter our understanding of trait evolution in extant taxa, but researchers may avoid using fossils alongside extant species if only few are known, or if the designation of the character state is uncertain. Here, I investigate the impacts of fossils and incorrectly-coded fossils in the ancestral state reconstruction of discrete characters under a likelihood model. Under simulated phylogenies and data, likelihood-based models are generally accurate (~ 70% correct) when estimating ancestral node values. Fossils always out-perform data from extant species alone, and perform to a higher or similar standard even when up to half of fossils values are coded incorrectly. These results are especially pronounced when model assumptions are violated, such as when there is a trend away from the root value. Fossil data are of particular importance when attempting to estimate the root node value. Attempts should be made to include fossils in analysis of discrete traits under likelihood, even if there is uncertainty in the trait data.在探究现存物种性状的起源与同源性时，离散性状（discrete character traits）的祖先状态重建（ancestral state reconstruction）通常至关重要。近年来，已有研究证实，纳入化石类群会改变我们对现存类群（extant taxa）性状演化的认知，但当已知化石数量稀少，或是性状状态的界定存在不确定性时，研究者往往会回避将化石与现存物种结合开展分析。本研究基于似然模型（likelihood model），探讨了化石以及编码有误的化石对离散性状祖先状态重建的影响。在模拟系统发育与数据场景下，基于似然的模型在估算祖先节点值时通常具有较高准确性，正确率约为70%。仅依赖现存物种数据的分析始终不如结合化石的分析方案；即便多达半数的化石性状编码存在错误，结合化石的分析仍能达到更高或相当的表现水平。当模型假设被违背时——例如存在偏离根节点值的演化趋势，上述结果的差异尤为显著。在估算根节点值时，化石数据的作用尤为关键。即便性状数据存在不确定性，基于似然的离散性状分析仍应尽可能纳入化石类群。