Quantifying and estimating ecological network diversity based on incomplete sampling data

Author:

Chiu Chun-Huo1ORCID,Chao Anne2ORCID,Vogel Sebastian3,Kriegel Peter4,Thorn Simon5ORCID

Affiliation:

1. Department of Agronomy, National Taiwan University, Taipei 10617, Taiwan

2. Institute of Statistics, National Tsing Hua University, Hsin-Chu 30043, Taiwan

3. Bavarian Environment Agency, Biodiversitätszentrum Rhön, Marktplatz 11, 97653 Bischofsheim i.d.R., Germany

4. Field Station Fabrikschleichach, Biocenter, University of Würzburg, Glashüttenstr. 5, 96181 Rauhenebrach, Germany

5. Hessian Agency for Nature Conservation, Environment and Geology, Biodiversity Center, Europastraße 10, 35394 Gießen, Germany

Abstract

An ecological network refers to the ecological interactions among sets of species. Quantification of ecological network diversity and related sampling/estimation challenges have explicit analogues in species diversity research. A unified framework based on Hill numbers and their generalizations was developed to quantify taxonomic, phylogenetic and functional diversity. Drawing on this unified framework, we propose three dimensions of network diversity that incorporate the frequency (or strength) of interactions, species phylogenies and traits. As with surveys in species inventories, nearly all network studies are based on sampling data and thus also suffer from under-sampling effects. Adapting the sampling/estimation theory and the iNEXT (interpolation/extrapolation) standardization developed for species diversity research, we propose the iNEXT.link method to analyse network sampling data. The proposed method integrates the following four inference procedures: (i) assessment of sample completeness of networks; (ii) asymptotic analysis via estimating the true network diversity; (iii) non-asymptotic analysis based on standardizing sample completeness via rarefaction and extrapolation with network diversity; and (iv) estimation of the degree of unevenness or specialization in networks based on standardized diversity. Interaction data between European trees and saproxylic beetles are used to illustrate the proposed procedures. The software iNEXT.link has been developed to facilitate all computations and graphics. This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.

Funder

German Federal Environmental Foundation

Bauer- und Stemmler Stiftung

Taiwan Ministry of Science and Technology

DFG Project

Publisher

The Royal Society

Subject

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

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quantifying and estimating ecological network diversity based on incomplete sampling data;Philosophical Transactions of the Royal Society B: Biological Sciences;2023-05-29

2. Theory and application of an improved species richness estimator;Philosophical Transactions of the Royal Society B: Biological Sciences;2023-05-29

3. Detecting and attributing the causes of biodiversity change: needs, gaps and solutions;Philosophical Transactions of the Royal Society B: Biological Sciences;2023-05-29

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