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Published on: September 25, 2021
Range-weighted branch length difference (RWiBaLD), a new method for distinguishing meso-endemism from neo-endemism
Brent D Mishler1, Nunzio Knerr2, Joseph T Miller3
1Department of Integrative Biology, University and Jepson Herbaria, University of California, Berkeley, California, United States of America.
Abstract:
Our goal is to enhance understanding of phylogenetic endemism (PE), which is studied using a range-weighted phylogenetic tree. We present a new method called Range Weighted Branch Length Difference (RWiBaLD), which is based on the difference between the length of a branch on a range-weighted observed tree and its length on the corresponding range-weighted comparison tree. The latter is a tree with the same topology as the observed tree but with branches adjusted to be of equal length before range-weighting. The goal of this method is to detect the branches of the phylogeny that contribute most to PE, and to distinguish among neo-endemism, paleo-endemism, and a novel category: meso-endemism. The latter is a heretofore missing category in the study of endemism referring to a highly range-restricted lineage that is not particularly short (neo-) or long (paleo-). Application of this approach is illustrated using the plant genus Acacia across the continent of Australia, using previously published spatial data and phylogeny. We show the properties of RWiBaLD, and how to apply it by: (1) mapping the outputs on a phylogeny, thus for the first time enabling PE to be scored for use in existing phylogenetic comparative methods, and (2) dissecting the composition of concentrations of PE on the landscape that are detected by the Categorical Analysis of Neo- And Paleo-Endemism (CANAPE) method. Whereas CANAPE identifies geographic concentrations of high PE, and gives a summary classification of the type of endemism dominating in a location, RWiBaLD identifies the specific branches that contribute the most to PE, and what type of endemism they represent. Thus, RWiBaLD enables novel studies of the evolutionary and ecological causes of endemism, as well as improved conservation assessment.
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