A framework for quantifying the magnitude and variability of community responses to global change drivers. Issue 12 (21st December 2015)

• Record Type: Journal Article
• Authors: Avolio, Meghan L.; Pierre, Kimberly J. La; Houseman, Gregory R.; Koerner, Sally E.; Grman, Emily; Isbell, Forest; Johnson, David Samuel; Wilcox, Kevin R.
• Is Part Of: Ecosphere. Volume 6:Issue 12(2015)
• Page Start: 1
• Page End: 14
• Publication Date: 2015-12-21
• Subjects: beta diversity -- community dissimilarity -- convergence -- divergence -- multivariate analysis -- non-metric multidimensional scaling -- rank abundance curve -- species composition; Ecology -- Periodicals; Ecology; Periodicals; 577.05
• DOI: 10.1890/ES15-00317.1
• Languages: English
• ISSNs: 2150-8925

Abstract

Abstract : A major challenge in global change ecology is to predict the trajectory and magnitude of community change in response to global change drivers (GCDs). Here, we present a new framework that not only increases the predictive power of individual studies, but also allows for synthesis across GCD studies and ecosystems. First, we suggest that by quantifying community dissimilarity of replicates both among and within treatments, we can infer both the magnitude and predictability of community change, respectively. Second, we demonstrate the utility of integrating rank abundance curves with measures of community dissimilarity to understand the species‐level dynamics driving community changes and propose a series of testable hypotheses linking changes in rank abundance curves with shifts in community dissimilarity. Finally, we review six case studies that demonstrate how our new conceptual framework can be applied. Overall, we present a new framework for holistically predicting community responses to GCDs that has broad applicability in this era of unprecedented global change and novel environmental conditions.