Making sense of multivariate community responses in global change experiments
Meghan L. Avolio,
Kimberly J. Komatsu,
Sally E. Koerner,
Emily Grman,
Forest Isbell,
David S. 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
Affiliations
Meghan L. Avolio
Department of Earth and Planetary Sciences Johns Hopkins University Baltimore Maryland USA
Kimberly J. Komatsu
Smithsonian Environmental Research Center Edgewater Maryland USA
Sally E. Koerner
Department of Biology University of North Carolina Greensboro Greensboro North Carolina USA
Emily Grman
Department of Biology Eastern Michigan University Ypsilanti Michigan USA
Forest Isbell
Department of Ecology, Evolution, and Behavior University of Minnesota St. Paul Minnesota USA
David S. Johnson
Virginia Institute of Marine Science William & Mary Gloucester Point Virginia USA
Kevin R. Wilcox
Department of Ecosystem Science and Management University of Wyoming Laramie Wyoming USA
Juha M. Alatalo
Environmental Science Center Qatar University Doha Qatar
Andrew H. Baldwin
Department of Environmental Science and Technology University of Maryland College Park Maryland USA
Carl Beierkuhnlein
Department of Biogeography University of Bayreuth Bayreuth Germany
Andrea J. Britton
Ecological Sciences, The James Hutton Institute Aberdeen UK
Bryan L. Foster
Kansas Biological Survey & Center for Ecological Research, Department of Ecology and Evolutionary Biology University of Kansas Lawrence Kansas USA
Harry Harmens
UK Centre for Ecology & Hydrology, Environment Centre Wales Bangor UK
Christel C. Kern
USDA Forest Service, Northern Research Station Rhinelander Wisconsin USA
Wei Li
Institute of Soil and Water Conservation Northwest A&F University Yangling China
Jennie R. McLaren
Department of Biological Sciences University of Texas at El Paso El Paso Texas USA
Peter B. Reich
Department of Forest Resources, University of Minnestoa and Institute for Global Change Biology University of Michigan St. Paul Minnesota USA
Lara Souza
Oklahoma Biological Survey & Department of Microbiology and Plant Biology University of Oklahoma Norman Oklahoma USA
Qiang Yu
National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China
Yunhai Zhang
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany Chinese Academy of Sciences Beijing China
Abstract 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.
