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饶氏二次多样性指数估计偏差幅度的评估。

Evaluation of the estimate bias magnitude of the Rao's quadratic diversity index.

作者信息

Chen Youhua, Wu Yongbin, Shen Tsung-Jen

机构信息

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.

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

出版信息

PeerJ. 2018 Jul 6;6:e5211. doi: 10.7717/peerj.5211. eCollection 2018.

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.

摘要

饶氏二次多样性指数是功能生态学和系统发育生态学中应用最广泛的多样性指数之一。对于一个由具有不同丰度的一组物种组成的生态群落,计算饶氏二次多样性指数的标准方法是对群落中一对物种之间的功能或系统发育距离求和,并以它们的相对丰度作为权重。在这里,我们使用理论推导和观测到的经验数据集表明,这种标准计算程序在实际应用中会在统计上低估真实值,并据此得出偏差幅度。当所研究的生态群落包含更多物种或成对物种距离较大时,低估情况会变得更糟。对于使用个体数量测量的物种丰度数据,我们建议计算无偏的饶氏二次多样性指数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f523/6037161/cafae5719477/peerj-06-5211-g001.jpg

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