State-and-transition models: recommendations for resilience-based application

TitleState-and-transition models: recommendations for resilience-based application
Publication TypeJournal Article
Year of Publication2008
AuthorsBriske D., Bestelmeyer BT, Stringham T.K., Shaver P.L.
JournalRangeland Ecology and Management
Volume61
Pagination359-367
Date PublishedJuly 2008
ARIS Log Number221086
Keywordsresilience-based, state-and-transition
AbstractThe objective of this paper is to recommend conceptual modifications for incorporation into the state-and-transition model (STM) framework to: 1) explicitly link this framework to the concept of ecological resilience, 2) direct management attention away from thresholds and toward the maintenance of state resilience, and 3) enhance the ability of STMs to capture a broader set of relevant ecological information to support ecosystem management. Ecological resilience describes the amount of change or disruption that is required to transform a system from being maintained by one set of mutually reinforcing processes and structures to a different set of processes and structures (e.g., alternative stable state). Effective ecosystem management must focus on the adoption of management practices and policies that maintain or enhance ecological resilience to prevent stable states from exceeding potential thresholds. In this context, resilience management does not focus on thresholds per se, but rather on within-state dynamics that influence resilience and state proximity and vulnerability to thresholds. Resilience-based ecosystem management provides greater opportunities to incorporate adaptive management than does threshold-based management because thresholds specifically define the limits of state resilience, rather than the conditions that determine the likelihood that these limits will be surpassed. We recommend that the STM framework incorporate triggers, at-risk communities, feedback mechanisms, and restoration pathways and develop process-specific indicators that enable managers to identify at-risk plant communities and potential restoration pathways. Three STMs representing unique ecological conditions and geographic locations are presented to illustrate the incorporation and application of these recommendations. We anticipate that these conceptual modifications will enhance the ability of the STM framework to more efficiently capture and convey ecological information supporting ecosystem management to a broader range of stake holders and special interest groups.
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