Plant Diversity ›› 2020, Vol. 42 ›› Issue (02): 67-73.DOI: 10.1016/j.pld.2019.12.003

• Articles •     Next Articles

Dramatic impact of metric choice on biogeographical regionalization

Jian-Fei Yea,b,c, Yun Liua,b, Zhi-Duan Chena   

  1. a State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;
    b University of Chinese Academy of Sciences, Beijing 100049, China;
    c Beijing Botanical Garden, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
  • Received:2019-10-04 Revised:2019-12-07 Online:2020-04-25 Published:2020-04-30
  • Supported by:
    This work was supported by grants from the National Natural Science Foundation of China (NNSF 31800178, 31590822, 31500179 and 31461123001), the Strategic Priority Research Program of Chinese Academy of Sciences (XDA19050103 and XDB31000000), the National Key Basic Research Program of China (2014CB954101).

Abstract: For a quantitative biogeographical regionalization, the choice of an appropriate dissimilarity index to measure pairwise distances is crucial. Several different metrics have been used, but there is no specific study to test the impact of metric choice on biogeographical regionalization. We herein applied a hierarchical cluster analysis on the mean nearest taxon distance (MNTD) and the phylogenetic turnover component of the Sørensen dissimilarity index (pβsim) pairwise distances to generate two schemes of phylogenetic regionalization of the Chinese flora, and then evaluated the effect of metric choice. Floristic regionalization based on MNTD was influenced by richness differences, but regionalization based on pβsim can clearly reflect the evolutionary history of the Chinese flora. We provided a brief description of the five regions identified by pβsim, and the regionalization can help develop strategies to effectively conserve the taxa and floristic regions with different origins and evolutionary histories.

Key words: Angiosperms, Chinese flora, Dissimilarity index, Distance metrics, Spatial turnover