Resilience-based application of state-and-transition models

TitleResilience-based application of state-and-transition models
Publication TypeConference Paper
Year of Publication2008
AuthorsBriske D.D., Bestelmeyer BT, Stringham T.K., Shaver P.L.
Conference NameSociety for Range Management Annual Meeting
Date PublishedJanuary 26-31, 2
Conference LocationLouisville, KY
ARIS Log Number223396
Keywordsresilience-based, state-and-transition, STM
AbstractWe recommend that several conceptual modifications be incorporated 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.