Rarefaction and extrapolation with beta diversity under a framework of Hill numbers: The iNEXT.beta3D standardization

Author:

Chao Anne1ORCID,Thorn Simon23ORCID,Chiu Chun‐Huo4ORCID,Moyes Faye5ORCID,Hu Kai‐Hsiang1,Chazdon Robin L.67ORCID,Wu Jessie1,Magnago Luiz Fernando S.8ORCID,Dornelas Maria5ORCID,Zelený David9ORCID,Colwell Robert K.71011ORCID,Magurran Anne E.5ORCID

Affiliation:

1. Institute of Statistics National Tsing Hua University Hsinchu Taiwan

2. Hessian Agency for Nature Conservation, Environment and Geology Biodiversity Center Gießen Germany

3. Czech Academy of Sciences, Biology Centre Institute of Entomology České Budějovice Czech Republic

4. Department of Agronomy National Taiwan University Taipei Taiwan

5. Centre for Biological Diversity and Scottish Oceans Institute, School of Biology University of St Andrews St Andrews UK

6. Tropical Forest and People Research Centre University of the Sunshine Coast Sippy Downs Queensland Australia

7. Department of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut USA

8. Centro de Formação em Ciências Agroflorestais, Universidade Federal do Sul da Bahia (UFSB) Ilhéus Brazil

9. Institute of Ecology and Evolutionary Biology National Taiwan University Taipei Taiwan

10. University of Colorado Museum of Natural History Boulder Colorado USA

11. Departamento de Ecologia Universidade Federal de Goiás Goiânia Brazil

Abstract

AbstractBased on sampling data, we propose a rigorous standardization method to measure and compare beta diversity across datasets. Here beta diversity, which quantifies the extent of among‐assemblage differentiation, relies on Whittaker's original multiplicative decomposition scheme, but we use Hill numbers for any diversity order q ≥ 0. Richness‐based beta diversity (q = 0) quantifies the extent of species identity shift, whereas abundance‐based (q > 0) beta diversity also quantifies the extent of difference among assemblages in species abundance. We adopt and define the assumptions of a statistical sampling model as the foundation for our approach, treating sampling data as a representative sample taken from an assemblage. The approach makes a clear distinction between the theoretical assemblage level (unknown properties/parameters of the assemblage) and the sampling data level (empirical/observed statistics computed from data). At the assemblage level, beta diversity for N assemblages reflects the interacting effect of the species abundance distribution and spatial/temporal aggregation of individuals in the assemblage. Under independent sampling, observed beta (= gamma/alpha) diversity depends not only on among‐assemblage differentiation but also on sampling effort/completeness, which in turn induces dependence of beta on alpha and gamma diversity. How to remove the dependence of richness‐based beta diversity on its gamma component (species pool) has been intensely debated. Our approach is to standardize gamma and alpha based on sample coverage (an objective measure of sample completeness). For a single assemblage, the iNEXT method was developed, through interpolation (rarefaction) and extrapolation with Hill numbers, to standardize samples by sampling effort/completeness. Here we adapt the iNEXT standardization to alpha and gamma diversity, that is, alpha and gamma diversity are both assessed at the same level of sample coverage, to formulate standardized, coverage‐based beta diversity. This extension of iNEXT to beta diversity required the development of novel concepts and theories, including a formal proof and simulation‐based demonstration that the resulting standardized beta diversity removes the dependence of beta diversity on both gamma and alpha values, and thus reflects the pure among‐assemblage differentiation. The proposed standardization is illustrated with spatial, temporal, and spatiotemporal datasets, while the freeware iNEXT.beta3D facilitates all computations and graphics.

Funder

Ministry of Science and Technology, Taiwan

Natural Environment Research Council

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3