A Critical Evaluation of Network Approaches for Studying Species Interactions
Publikation: Beiträge in Zeitschriften › Übersichtsarbeiten › Forschung
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in: Annual Review of Ecology, Evolution, and Systematics, Jahrgang 55, Nr. 1, 26.07.2024, S. 65-88.
Publikation: Beiträge in Zeitschriften › Übersichtsarbeiten › Forschung
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TY - JOUR
T1 - A Critical Evaluation of Network Approaches for Studying Species Interactions
AU - Blüthgen, Nico
AU - Staab, Michael
N1 - Publisher Copyright: Copyright © 2024 by the author(s).
PY - 2024/7/26
Y1 - 2024/7/26
N2 - 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.
AB - 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.
KW - ecosystem function
KW - interaction network
KW - null model
KW - sampling
KW - specialization
KW - trophic interaction
KW - Biology
KW - Ecosystems Research
UR - http://www.scopus.com/inward/record.url?scp=85206248263&partnerID=8YFLogxK
U2 - 10.1146/annurev-ecolsys-102722-021904
DO - 10.1146/annurev-ecolsys-102722-021904
M3 - Scientific review articles
AN - SCOPUS:85206248263
VL - 55
SP - 65
EP - 88
JO - Annual Review of Ecology, Evolution, and Systematics
JF - Annual Review of Ecology, Evolution, and Systematics
SN - 1543-592X
IS - 1
ER -