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Diagnosing adaptive comanagement across multiple cases

Bibliographic Data

ID4891457
AuthorsRyan Plummer (0000-0001-5749-6201, Stockholm Resilience Centre), Julia Baird (0000-0002-2580-5361, Brock University), Derek Armitage (0000-0002-8921-1693, University of Waterloo), Örjan Bodin (0000-0002-8218-1153, Stockholm Resilience Centre), L Schultz (0000-0003-4763-8872, Stockholm Resilience Centre)
Year2017
Volume22
Issue3
Pagesart19
Publication date2017-01-01
Open AccessYes
TypeARTICLE
VenueConservation Ecology (JOURNAL)
Journal identifiersISSN: 1195-5449 • E-ISSN: 1708-3087
PublisherResilience Alliance (PUBLISHER • CA)
DOI10.5751/es-09436-220319
OpenAlexW2751078006
LanguageEN
Citations received8
References cited26

Adaptive comanagement is at an important cross-road: different research paths forward are possible, and a diagnostic approach has been identified as a promising one. Accordingly, we operationalize a diagnostic approach, using a framework, to set a new direction for adaptive comanagement research. We set out three main first-tier variables: antecedents, process, and outcomes, and these main variables are situated within a fourth: the setting. Within each of these variables, significant depth of study may be achieved by investigating second-and third-tier variables. Causal relationships among variables, and particularly related to the outcomes of adaptive comanagement, may also be investigated at varying depths using the diagnostic framework and associated nomenclature. We believe that the diagnostic approach we describe offers a unifying methodological approach to advancing adaptive comanagement research as well as similar approaches. There are significant benefits to be gained, including building a database of case studies using this common framework, advancing theory, and ultimately, improving social and ecological outcomes

Adaptive Management · Biology · Business · Climate change · Climate change adaptation · Environmental planning · Environmental resource management · Geography · Emergency and Acute Care Studies · Environmental Science · Health, Environment, Cognitive Aging · Machine Learning in Healthcare · Ecology

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Citations per year1
Citation span2018 - 2025 (8)
Highly citedNo

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