Partitioning multiple-site tree-like beta diversity into turnover and nestedness components without pairwise comparisons

摘要

In this letter, I extend a species-level partitioning framework for a multiple-site dissimilarity index established by Ricotta and Pavoine (2015) to account for tree-like information (i.e., evolutionary history, taxonomic classification or functional divergence of species). This novel framework can be applied to evaluate the relative contribution of turnover versus nestedness to total multiple-site tree-like beta diversity in empirical settings. The feature of the framework is to account for expectedly and unexpectedly absence of species in the sites without pairwise comparisons between sites. Simple examples with step-by-step calculation details and corresponding R computing code are provided to better understand and apply the proposed framework. (C) 2015 Elsevier Ltd. All rights reserved.