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Ecology Letters
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Ecology Letters
Article . 2018 . Peer-reviewed
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Ecology Letters
Article . 2019
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Using food network unfolding to evaluate food–web complexity in terms of biodiversity: theory and applications

Authors: Hiroyuki Togashi; Noboru Okuda; Naoto F. Ishikawa; Naoto F. Ishikawa; Yoshikazu Kato; Yukihiro Kohmatsu; Yukihiro Kohmatsu; +11 Authors

Using food network unfolding to evaluate food–web complexity in terms of biodiversity: theory and applications

Abstract

AbstractFood–web complexity often hinders disentangling functionally relevant aspects of food–web structure and its relationships to biodiversity. Here, we present a theoretical framework to evaluate food–web complexity in terms of biodiversity. Food network unfolding is a theoretical method to transform a complex food web into a linear food chain based on ecosystem processes. Based on this method, we can define three biodiversity indices, horizontal diversity (DH), vertical diversity (DV) and range diversity (DR), which are associated with the species diversity within each trophic level, diversity of trophic levels, and diversity in resource use, respectively. These indices are related to Shannon's diversity index (H′), whereH′ = DH + DV − DR. Application of the framework to three riverine macroinvertebrate communities revealed thatDindices, calculated from biomass and stable isotope features, captured well the anthropogenic, seasonal, or other within‐site changes in food–web structures that could not be captured withH′alone.

Keywords

Food Chain, Biodiversity, Biomass, Ecosystem

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    16
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
hybrid