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Managing for resilience: an information theory‐based approach to assessing ecosystems
Author(s) -
Eason Tarsha,
Garmestani Ahjond S.,
Stow Craig A.,
Rojo Carmen,
AlvarezCobelas Miguel,
Cabezas Heriberto
Publication year - 2016
Publication title -
journal of applied ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.503
H-Index - 181
eISSN - 1365-2664
pISSN - 0021-8901
DOI - 10.1111/1365-2664.12597
Subject(s) - univariate , ecosystem , multivariate statistics , resilience (materials science) , computer science , index (typography) , psychological resilience , environmental resource management , environmental science , ecology , machine learning , biology , psychology , physics , world wide web , psychotherapist , thermodynamics
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.