Managing for resilience: an information theory‐based approach to assessing ecosystems. Issue 3 (1st February 2016)

• Record Type: Journal Article
• Authors: Eason, Tarsha; Garmestani, Ahjond S.; Stow, Craig A.; Rojo, Carmen; Alvarez‐Cobelas, Miguel; Cabezas, Heriberto
• Editors: Allen, Craig
• Is Part Of: Journal of applied ecology. Volume 53:Issue 3(2016:Jun.)
• Page Start: 656
• Page End: 665
• Publication Date: 2016-02-01
• Subjects: ecosystems -- Fisher information -- indicators -- indices -- information theory -- leading indicators -- multivariate -- regime shifts -- resilience; Agriculture -- Periodicals; Biology, Economic -- Periodicals; Agricultural ecology -- Periodicals; Applied ecology -- Periodicals; 577
• DOI: 10.1111/1365-2664.12597
• Languages: English
• ISSNs: 0021-8901

Abstract

Summary: Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications . We illustrate the utility of an information theory‐based index for assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abrupt and gradual transitions in ecosystems. Abstract : We illustrate the utility of an information theory‐based index for assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abrupt and gradual transitions in ecosystems.