Florida Department of Agriculture and Consumer ServicesDivision of Plant Industry, 1911 SW 34th Street, Gainesville, Florida, 32608 USA. .
Zootaxa. 2021 Nov 22;5071(1):131-142. doi: 10.11646/zootaxa.5071.1.7.
A method is presented for correlating phylogenetic characters through cladistic analysis. It extends the use of phylogenetic datasets for diagnostic purposes. It improves matrix-based identification tools by predicting novel character-state combinations that were not observed when the key was constructed. By interpreting homoplasy as analytical error, hypothetical character-state combinations are tested for the homoplasy that they would add to the shortest tree(s). The correlation is equal to the homoplasy summed across all state combinations, divided by a maximum possible value. The results depend on uncertainty about the sequence of state transitions and their overlap among characters. A correlation index r is proposed for sets of non-additive characters; it is a kind of multiple-regression value, and its ensemble value R is a statistic of a whole matrix. This approach can be used to select sets of the best "proxy" characters to substitute for unobservable characters of interest. The concept can be extended to continuous characters. Worked examples are given with datasets of various insect orders.
本文提出了一种通过分支分析进行系统发育特征关联的方法。它扩展了系统发育数据集在诊断目的上的应用。通过将同型现象解释为分析错误，该方法预测了在构建关键时未观察到的新的特征状态组合，从而改进了基于矩阵的识别工具。通过对所有状态组合的同型现象求和，并除以最大可能值，来测试假设的特征状态组合的同型现象。结果取决于对状态转变顺序及其在特征之间的重叠的不确定性。本文还为非加性特征集提出了一个相关指数 r，它是一种多元回归值，其总体值 R 是整个矩阵的一个统计量。这种方法可用于选择最佳“代理”特征集来替代感兴趣的不可观测特征。该概念可以扩展到连续特征。本文提供了不同昆虫目数据集的实例。
