Disentangling nonrandom structure from random placement when estimating β‐diversity through space or time

Abstract There is considerable interest in understanding patterns of β‐diversity that measure the amount of change in species composition through space or time. Most hypotheses for β‐diversity evoke nonrandom processes that generate spatial and temporal within‐species aggregation; however, β‐diversity can also be driven by random sampling processes. Here, we describe a framework based on rarefaction curves that quantifies the nonrandom contribution of species compositional differences across samples to β‐diversity. We isolate the effect of within‐species spatial or temporal aggregation on beta‐diversity using a coverage standardized metric of β‐diversity (β C ). We demonstrate the utility of our framework using simulations and an empirical case study examining variation in avian species composition through space and time in engineered versus natural riparian areas. The primary strengths of our approach are that it provides an intuitive visual null model for expected patterns of biodiversity under random sampling that allows integrating analyses across α‐, γ‐, and β‐scales. Importantly, the method can accommodate comparisons between communities with different species pool sizes, and it can be used to examine species turnover both within and between meta‐communities.

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Publication Details

Journal
Ecosphere
Published
2025-03-01
DOI
https://doi.org/10.1002/ecs2.70061
Citations
2
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
1.61

Funders

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article

Disentangling nonrandom structure from random placement when estimating β‐diversity through space or time

Brian J. McGill, María Dornelas, Anne E. Magurran, Thore Engel et al.
2 citations
Ecosphere
Advanced biosensing and bioanalysis techniques
1.61
article

Disentangling nonrandom structure from random placement when estimating β‐diversity through space or time

Brian J. McGill, María Dornelas, Anne E. Magurran, Thore Engel, Inês S. Martins, Jonathan M. Chase, Daniel J. McGlinn, Hideyasu Shimadzu, Shane A. Blowes, Nicholas J. Gotelli
article en
2 citations

Abstract

Abstract There is considerable interest in understanding patterns of β‐diversity that measure the amount of change in species composition through space or time. Most hypotheses for β‐diversity evoke nonrandom processes that generate spatial and temporal within‐species aggregation; however, β‐diversity can also be driven by random sampling processes. Here, we describe a framework based on rarefaction curves that quantifies the nonrandom contribution of species compositional differences across samples to β‐diversity. We isolate the effect of within‐species spatial or temporal aggregation on beta‐diversity using a coverage standardized metric of β‐diversity (β C ). We demonstrate the utility of our framework using simulations and an empirical case study examining variation in avian species composition through space and time in engineered versus natural riparian areas. The primary strengths of our approach are that it provides an intuitive visual null model for expected patterns of biodiversity under random sampling that allows integrating analyses across α‐, γ‐, and β‐scales. Importantly, the method can accommodate comparisons between communities with different species pool sizes, and it can be used to examine species turnover both within and between meta‐communities.

EcosphereVol. 16(3)
University of Vermont (US), Helmholtz Centre for Environmental Research (DE), University of Lisbon (PT), Loughborough University (GB), University of St Andrews (GB), College of Charleston (US), German Centre for Integrative Biodiversity Research (DE), Leverhulme Trust (GB), University of York (GB), Kitasato University (JP), Martin Luther University Halle-Wittenberg (DE), Friedrich Schiller University Jena (DE), University of Maine (US)
National Science Foundation, European Commission, Deutsche Forschungsgemeinschaft, Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig, HORIZON EUROPE Framework Programme, HORIZON EUROPE Marie Sklodowska-Curie Actions
Openalex Percentile: Top 18%
Advanced biosensing and bioanalysis techniques
1.61
DOIOpen Access PDFOpenAlex
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