ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2023
Quantifying and estimating ecological network diversity based on incomplete sampling data.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Understanding Basic Concepts of Viral Quasispecies: From Evolutionary Dynamics to Clinical Relevance.Pathogens (Basel, Switzerland) · 2026Review
- A comprehensive, multi-method dataset of plant-frugivore interactions in a Mediterranean hotspot.Scientific data · 2026Article
- Untangling Sampling Bias From Lemur Dietary Specialization.Ecology and evolution · 2026Article
- Specialization of bat-fly interactions at different elevations in a montane forest of northern Peru.Parasitology · 2025Article
- Effects of the timing of grazing on insect diversity and insect-plant interactions in mountain grasslands.Ecological applications : a publication of the Ecological Society of America · 2025Article
- Network theory predicts ecosystem robustness across environmental conditions.Proceedings. Biological sciences · 2025Article
- Detecting and attributing the causes of biodiversity change: needs, gaps and solutions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Theory and application of an improved species richness estimator.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Quantifying and estimating ecological network diversity based on incomplete sampling data.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
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5 authors.
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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'.
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