A new family of dissimilarity metrics for discrete character matrices that include inapplicable characters and its importance for disparity studies.

ABSTRACT: The use of discrete character data for disparity analyses has become more popular, partially due to the recognition that character data describe variation at large taxonomic scales, as well as the increasing availability of both character matrices co-opted from phylogenetic analysis and software tools. As taxonomic scope increases, the need to describe variation leads to some characters that may describe traits not found across all the taxa. In such situations, it is common practice to treat inapplicable characters as missing data when calculating dissimilarity matrices for disparity studies. For commonly used dissimilarity metrics like Wills's GED and Gower's coefficient, this can lead to the reranking of pairwise dissimilarities, resulting in taxa that share more primary character states

SUBMITTER: Hopkins MJ 

PROVIDER: S-EPMC6283942 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature