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A Critical Evaluation of Network Approaches for Studying Species Interactions

Research output: Journal contributionsScientific review articlesResearch

28 Citations (Scopus)

Abstract

Ecological networks of species interactions are popular and provide powerful analytical tools for understanding variation in community structure and ecosystem functioning. However, network analyses and commonly used metrics such as nestedness and connectance have also attracted criticism. One major concern is that observed patterns are misinterpreted as niche properties such as specialization, whereas they may instead merely reflect variation in sampling, abundance, and/or diversity. As a result, studies potentially draw flawed conclusions about ecological function, stability, or coextinction risks. We highlight potential biases in analyzing and interpreting species-interaction networks and review the solutions available to overcome them, among which we particularly recommend the use of null models that account for species abundances. We show why considering variation across species and networks is important for understanding species interactions and their consequences. Network analyses can advance knowledge on the principles of species interactions but only when judiciously applied.

Original languageEnglish
JournalAnnual Review of Ecology, Evolution, and Systematics
Volume55
Issue number1
Pages (from-to)65-88
Number of pages24
ISSN1543-592X
DOIs
Publication statusPublished - 26.07.2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2024 by the author(s).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Research areas and keywords

  • ecosystem function
  • interaction network
  • null model
  • sampling
  • specialization
  • trophic interaction
  • Biology
  • Ecosystems Research

ASJC Scopus Subject Areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology

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