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المؤلفAvolio, Meghan L.
المؤلفKomatsu, Kimberly J.
المؤلفKoerner, Sally E.
المؤلفGrman, Emily
المؤلفIsbell, Forest
المؤلفJohnson, David S.
المؤلفWilcox, Kevin R.
المؤلفAlatalo, Juha M.
المؤلفBaldwin, Andrew H.
المؤلفBeierkuhnlein, Carl
المؤلفBritton, Andrea J.
المؤلفFoster, Bryan L.
المؤلفHarmens, Harry
المؤلفKern, Christel C.
المؤلفLi, Wei
المؤلفMcLaren, Jennie R.
المؤلفReich, Peter B.
المؤلفSouza, Lara
المؤلفYu, Qiang
المؤلفZhang, Yunhai
تاريخ الإتاحة2023-02-15T05:33:42Z
تاريخ النشر2022-10-01
اسم المنشورEcosphere
المعرّفhttp://dx.doi.org/10.1002/ecs2.4249
الاقتباسAvolio, Meghan L., Komatsu, Kimberly J., Koerner, Sally E., Grman, Emily, Isbell, Forest, Johnson, David S., Wilcox, Kevin R., et al. 2022. “ Making Sense of Multivariate Community Responses in Global Change Experiments.” Ecosphere 13( 10): e4249. https://doi.org/10.1002/ecs2.4249
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85141812988&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/40047
الملخصEcological 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.
راعي المشروعWe thank the LTER Network for funding our synthesis working groups in 2012 (NSF EF 1545288 to Meghan L. Avolio and Kimberly J. Komatsu) and 2016 (NSF EF 0553768 to Kimberly J. Komatsu, Meghan L. Avolio, and Kevin R. Wilcox). Importantly, we are immensely grateful to the researchers who provided data for this manuscript and their research teams who assured that the long-term integrity of these global change experiments are/were maintained.
اللغةen
الموضوعcentroids
data synthesis
dispersion
dissimilarity metrics
rank abundance curves
richness
العنوانMaking sense of multivariate community responses in global change experiments
النوعArticle
رقم العدد10
رقم المجلد13
dc.accessType Open Access


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