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Making sense of multivariate community responses in global change experiments

  • M. Avolio
  • , K. Komatsu
  • , S. Koerner
  • , E. Grman
  • , F. Isbell
  • , D. Johnson
  • , K. Wilcox
  • , J. Alatalo
  • , A. Baldwin
  • , C. Beierkuhnlein
  • , A. Britton
  • , B. Foster
  • , H. Harmens
  • , C. Kern
  • , W. Li
  • , J. McClaren
  • , P. Reich
  • , L. Souza
  • , Q. Yu
  • , Y. Zhang
  • Johns Hopkins University
  • Smithsonian Institute (USA)
  • University of North Carolina
  • Eastern Michigan University
  • University of Minnesota
  • Virginia Institute of Marine Science
  • University of Wyoming
  • Qatar University
  • University of Maryland
  • University of Bayreuth
  • University of Kansas
  • UK Centre for Ecology and Hydrology
  • United States Department of Agriculture. Forest Service
  • Northwest Agriculture and Forestry University
  • University of Texas
  • University of Oklahoma
  • Chinese Academy of Agricultural Sciences
  • Chinese Academy of Sciences

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article numberArt. E4249
JournalEcosphere.
Volume13
Issue number10
DOIs
Publication statusPublished - 10 Oct 2022

Keywords

  • Centroids
  • Data Synthesis
  • Dispersion
  • Dissimilarity Metrics
  • Rank Abundance Curves
  • Richness

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