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.

离散性状的祖先状态重建（Ancestral state reconstruction）在解析现生物种的性状起源与同源性时通常至关重要。近期研究表明，纳入化石可改变我们对现存类群性状演化的认知，但倘若已知化石数量稀少，或性状状态的标注存在不确定性，研究者往往会回避将化石与现生物种结合开展分析。本文基于似然模型（likelihood model），探讨了化石以及性状编码有误的化石在离散性状祖先状态重建中的影响。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整体准确率约为70%。化石始终优于仅使用现生物种的数据，且即便有多达半数的化石性状编码存在错误，其分析表现仍能达到或接近同等水准。当模型假设被违背时，例如存在偏离根节点性状值的演化趋势时，上述结果尤为显著。在估算根节点性状值时，化石数据尤为关键。即便性状数据存在不确定性，基于似然方法的离散性状分析仍应纳入化石样本。