Development of State-and-Transition Models (STM): Integrating Ecosystem Function, Structure and Energy to STM
محورهای موضوعی : Relationship between Animal and Rangeland
Gholam Ali Heshmati
1
(Faculty of Rangeland and Watershed Management, Gorgan Agricultural and Natural Resource
Sciences University, Gorgan)
Zahra Mohebbi
2
(Rangeland Sciences, Faculty of Rangeland and Watershed Management, Gorgan University of
Agricultural Sciences & Natural Resources, Gorgan)
کلید واژه: energy, STMs, Ecosystem function, Structure and disturbances,
چکیده مقاله :
The main objective of an ecosystem sustainable management is to preserve itscapacity to respond and adapt to current disturbances and/or future changes, and maintain theprovision of environmental goods and services. Two very important properties linked to thisobjective are the ecosystem resilience and resistance to disturbance factors. The objective ofthis paper is to recommend conceptual modifications to the integration of key ecologicalconcepts such as dynamic equilibrium, resistance and resilience to the ‘State and TransitionModel’ (STM) in order to apply them in a more feasible way for rangeland management.Ecological resilience describes the amount of change or disruption required to transform asystem from being maintained by one set of mutually reinforcing processes and structures to adifferent set of processes and structures. STMs integrated to concepts of structure, functionand energy provides greater opportunities to incorporate adaptive management, more accurateforecasts and a better and easier comparison between rangeland ecosystem types thantraditional STMs. We propose to enhance the STM considering four principal axes (ecosystemfunctions and/or processes, natural disturbances and/or negative management activities,required energy to return to the previous state, and structural ecosystem changes and transitiontime) also simultaneously, to compare the “robust” ecosystem to “fragile” ecosystem. Therecommended modifications enable STMs to identify a broader range of variables to anticipateand identify conditions which determine state resilience to better inform ecosystem managersof risk and restoration options.
