Bestelmeyer, Brandon T.

Briske, David D.

Shaver, P. L.

Stringham, T. K.

English

University of Kentucky

University of Kentucky UKnowledge International Grassland Congress Proceedings 21st International Grassland Congress / 8th International Rangeland Congress Development of Resilience‐Based State‐and‐Transition Models David D. Briske Texas A&M University Brandon T. Bestelmeyer U.S. Department of Agriculture T. K. Stringham Oregon State University P. L. Shaver U.S. Department of Agriculture Follow this and additional works at: https://uknowledge.uky.edu/igc  Part of the Plant Sciences Commons, and the Soil Science Commons This document is available at https://uknowledge.uky.edu/igc/21/4-1/12 The 21st International Grassland Congress / 8th International Rangeland Congress took place in Hohhot, China from June 29 through July 5, 2008. Proceedings edited by Organizing Committee of 2008 IGC/IRC Conference Published by Guangdong People's Publishing House This Event is brought to you for free and open access by the Plant and Soil Sciences at UKnowledge. It has been accepted for inclusion in International Grassland Congress Proceedings by an authorized administrator of UKnowledge. For more information, please contact UKnowledge@lsv.uky.edu. 瞯 ]570　 瞯 　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　Grasslands/Rangelands Resources and Ecology ——— Indicators for Sustainable Use and Conservation of Grasslands/Rangelands ResourcesDevelopment of resilience‐based state‐and‐transition modelsD .D . Briske1 , B .T . Bestelmeyer 2 , T .K . Stringham3 , and P .L . Shaver 41 Texas A &M University , College Station TX , USA 77843 , E‐mail : dbriske ＠ tamu . edu ; 2 USDA‐ARS , JornadaEx perimental Range , L as Cruces , NM , USA 88003 ; 3 Oregon State University , Corvallis OR , USA 97331 ; and 4 USDA‐NRCS , Portland OR , USA 97232 .Key words : alternative stable states , ecological resilience , rangeland monitoring , thresholdsIntroduction The objective of this paper is to recommend the incorporation of additional resilience concepts into the state‐and‐transition model ( STM ) framework . Ecological resilience describes the amount of change or disruption that is required totransform a system from being maintained by one set of mutually reinforcing processes and structures to a different set ofprocesses and structures ( e .g . , an alternative stable state) . In the light of this concept , effective ecosystem management mustfocus on the adoption of management practices and policies that maintain or enhance ecological resilience to prevent stable statesfrom exceeding thresholds . Therefore , resilience‐based management does not exclusively focus on identifying thresholds per se ,but rather on within‐state dynamics that influence state vulnerability or proximity to thresholds .Methods and materials The concepts reported in this paper were partially developed at a State‐and‐T ransition Ecological Theoryworkshop sponsored by USDA‐NRCS on the campus of Oregon State University , August ２００６ . Academics and managersconvened to identify and summarize the most important advances and necessary requirements for STM to more effectivelydescribe ecosystem dynamics .Results and discussion The assessment of state resilience requires the development of recognizable indicators to identify whenstates are approaching thresholds as well as how far states have moved beyond thresholds when they have been crossed( Stringham et al . ２００３ ) . In an effort to incorporate resilience‐based concepts in the STM framework , we recommend thattriggers , at‐risk community phases , feedback mechanisms , and restoration pathways be incorporated for each thresholdseparating individual states , including process‐specific indicators to identify at‐risk plant communities and potential restorationpathways . T riggers describe biotic or abiotic variables or events that initiate threshold‐related processes by contributing to theimmediate loss of ecosystem resilience . Selection of at‐risk communities requires identification of community phases known orassumed to have the least ecological resilience within a state and that immediately precede shif ts to alternative states . Indicatorsof positive and negative feedbacks , contributing to either decreasing or increasing state resilience , respectively , can be inferredfrom altered patterns and processes within individual states . Patterns and processes associated with negative feedbacks inalternative states can be used to develop indicators of the resilience attained by these states af ter thresholds have beensurpassed . Restoration pathways can be assessed with indicators that identify the residual properties of former states thatcontinue to exist within alternative states af ter thresholds have been crossed . Community phases within alternative states thathave developed the least resilience ( e .g . , fewest negative feedbacks) and possess the greatest proportion of residual propertiesof the former state are the most likely candidates from which to initiate restoration pathways (Bestelmeyer ２００６ ; Briske et al .２００６) .Conclusions The incorporation of resilience‐based concepts into the STM framework will promote adaptive management byemphasizing indicators of state resilience in addition to indicators of pending thresholds and it will identify additional variables tobetter inform ecosystem managers of risk and restoration options .ReferencesBestelmeyer , B .T . , (２００６) . Threshold concepts and their use in rangeland management and restoration : the good , the bad ,and the insidious . Restoration Ecology １４ , ３２５‐３２９ .Briske , D .D . , Fuhlendorf , S .D . and Smeins , F .E . , ( ２００６ ) . A unified framework for assessment and application ofecological thresholds . Rangeland Ecology and Management ５９ , ２２５‐２３６ .Stringham , T .K . , Krueger ,W .C . and Shaver , P .L . , ( ２００３) . State and transition modeling : an ecological process approach .Journal o f Range Management ５６ , １０６‐１１３ .

Development of Resilience‐Based State‐and‐Transition Models

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Development of Resilience‐Based State‐and‐Transition Models

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