Evaluation of the estimate bias magnitude of the Rao’s quadratic diversity index

Author:

Chen Youhua1,Wu Yongbin2,Shen Tsung-Jen3ORCID

Affiliation:

1. CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China

2. College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China

3. Institute of Statistics & Department of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan

Abstract

Rao’s quadratic diversity index is one of the most widely applied diversity indices in functional and phylogenetic ecology. The standard way of computing Rao’s quadratic diversity index for an ecological assemblage with a group of species with varying abundances is to sum the functional or phylogenetic distances between a pair of species in the assemblage, weighted by their relative abundances. Here, using both theoretically derived and observed empirical datasets, we show that this standard calculation routine in practical applications will statistically underestimate the true value, and the bias magnitude is derived accordingly. The underestimation will become worse when the studied ecological community contains more species or the pairwise species distance is large. For species abundance data measured using the number of individuals, we suggest calculating the unbiased Rao’s quadratic diversity index.

Funder

Hundred Talents Program of the Chinese Academy of Sciences

Strategic Priority Research Program of the Chinese Academy of Sciences

National Key Programme of Research and Development, Ministry of Science and Technology

Science and Technology Planning Project of Guangdong Province, China

Innovation of Forestry Science and Technology Foundation of Guangdong, China

Taiwan Ministry of Science and Technology under contract MOST

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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