A Critical Evaluation of Network Approaches for Studying Species Interactions

Nico Blüthgen; Michael Staab

doi:10.1146/annurev-ecolsys-102722-021904

A Critical Evaluation of Network Approaches for Studying Species Interactions

Research output: Journal contributions › Scientific review articles › Research

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A Critical Evaluation of Network Approaches for Studying Species Interactions. / Blüthgen, Nico; Staab, Michael.
In: Annual Review of Ecology, Evolution, and Systematics, Vol. 55, No. 1, 26.07.2024, p. 65-88.

Research output: Journal contributions › Scientific review articles › Research

Bibtex

@article{cc4c10abc3e540809a68f70aaeb2a9e3,

title = "A Critical Evaluation of Network Approaches for Studying Species Interactions",

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.",

keywords = "ecosystem function, interaction network, null model, sampling, specialization, trophic interaction, Biology, Ecosystems Research",

author = "Nico Bl{\"u}thgen and Michael Staab",

note = "Publisher Copyright: Copyright {\textcopyright} 2024 by the author(s).",

year = "2024",

month = jul,

day = "26",

doi = "10.1146/annurev-ecolsys-102722-021904",

language = "English",

volume = "55",

pages = "65--88",

journal = "Annual Review of Ecology, Evolution, and Systematics",

issn = "1543-592X",

publisher = "Annual Reviews Inc.",

number = "1",

}

RIS

TY - JOUR

T1 - A Critical Evaluation of Network Approaches for Studying Species Interactions

AU - Blüthgen, Nico

AU - Staab, Michael

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 -

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