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Journal Articles Philosophical Transactions of the Royal Society B: Biological Sciences Year : 2020

Shifting levels of ecological network’s analysis reveals different system properties

Abstract

Network analyses applied to models of complex systems generally contain at least three levels of analyses. Whole-network metrics summarize general organizational features (properties or relationships) of the entire network, while node-level metrics summarize similar organization features but consider individual nodes. The network- and node-level metrics build upon the primary pairwise relationships in the model. As with many analyses, sometimes there are interesting differences at one level that disappear in the summary at another level of analysis. We illustrate this phenomenon with ecosystem network models, where nodes are trophic compartments and pairwise relationships are flows of organic carbon, such as when a predator eats a prey. For this demonstration, we analysed a time-series of 16 models of a lake planktonic food web that describes carbon exchanges within an autumn cyanobacteria bloom and compared the ecological conclusions drawn from the three levels of analysis based on inter-time-step comparisons. A general pattern in our analyses was that the closer the levels are in hierarchy (node versus network, or flow versus node level), the more they tend to align in their conclusions. Our analyses suggest that selecting the appropriate level of analysis, and above all regularly using multiple levels, may be a critical analytical decision. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’. © 2020 The Author(s) Published by the Royal Society. All rights reserved.

Dates and versions

hal-02890380 , version 1 (10-09-2020)

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Cite

N. Niquil, M. Haraldsson, T. Sime-Ngando, P. Huneman, S.R. Borrett. Shifting levels of ecological network’s analysis reveals different system properties. Philosophical Transactions of the Royal Society B: Biological Sciences, 2020, 375 (1796), ⟨10.1098/rstb.2019.0326⟩. ⟨hal-02890380⟩
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