Making sense of multivariate community responses in global change experiments Article Swipe
Meghan L. Avolio
,
Kimberly J. Komatsu
,
Sally E. Koerner
,
Emily Grman
,
Forest Isbell
,
David Samuel Johnson
,
Kevin R. Wilcox
,
Juha M. Alatalo
,
Andrew H. Baldwin
,
Carl Beierkuhnlein
,
Andrea J. Britton
,
Bryan L. Foster
,
Harry Harmens
,
Christel C. Kern
,
Wei Li
,
Jennie R. McLaren
,
Peter B. Reich
,
Lara Souza
,
Qiang Yu
,
Yunhai Zhang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1002/ecs2.4249
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1002/ecs2.4249
Ecological communities are being impacted by global change worldwide. Experiments are a powerful tool to understand how global change will impact communities by comparing control and treatment replicates. Communities consist of multiple species, and their associated abundances make multivariate methods an effective approach to study community compositional differences between control and treated replicates. Dissimilarity metrics are a commonly employed multivariate measure of compositional differences; however, while highly informative, dissimilarity metrics do not elucidate the specific ways in which communities differ. Integrating two multivariate methods, dissimilarity metrics and rank abundance curves (RACs), have the potential to detect complex differences based on dissimilarity metrics and detail the how these differences came about through differences in richness, evenness, species ranks, or species identity. Here we use a database of 106 global change experiments located in herbaceous ecosystems and explore how patterns of ordinations based on dissimilarity metrics relate to RAC‐based differences. We find that combining dissimilarity metrics alongside RAC‐based measures clarifies how global change treatments are altering communities. We find that when there is no difference in community composition (no distance between centroids of control and treated replicates), there are rarely differences in species ranks or species identities and more often differences in richness or evenness alone. In contrast, when there are differences between centroids of control and treated replicates, this is most often associated with differences in ranks either alone or co‐occurring with differences in richness, evenness, or species identities. We suggest that integrating these two multivariate measures of community composition results in a deeper understanding of how global change impacts communities.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/ecs2.4249
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ecs2.4249
- OA Status
- gold
- Cited By
- 6
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4303986535
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4303986535Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/ecs2.4249Digital Object Identifier
- Title
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Making sense of multivariate community responses in global change experimentsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-01Full publication date if available
- Authors
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Meghan L. Avolio, Kimberly J. Komatsu, Sally E. Koerner, Emily Grman, Forest Isbell, David Samuel Johnson, Kevin R. Wilcox, Juha M. Alatalo, Andrew H. Baldwin, Carl Beierkuhnlein, Andrea J. Britton, Bryan L. Foster, Harry Harmens, Christel C. Kern, Wei Li, Jennie R. McLaren, Peter B. Reich, Lara Souza, Qiang Yu, Yunhai ZhangList of authors in order
- Landing page
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https://doi.org/10.1002/ecs2.4249Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ecs2.4249Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ecs2.4249Direct OA link when available
- Concepts
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Species evenness, Species richness, Multivariate statistics, Abundance (ecology), Multivariate analysis, Ecology, Rank abundance curve, Ordination, Biology, Statistics, MathematicsTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2025: 2, 2024: 1, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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