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Leonardo Frid

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This is a spatially-explicit state-and-transition simulation model of buffelgrass dynamics in Saguaro National Park. Buffelgrass is an invasive grass spreading in the park. The model represents uninvaded and invaded parts of the desert ecosystem including transition pathways related to management activities and includes a connection to a fire behavior model. The model was built using the ST-Sim software platform linked to the FARSITE fire behavior model. The St-SIM file structure includes three components: 1) Buffelgrass.ssim.input folder that houses the input files used by St-SIM, 2) the Buffelgrass.ssim.output folder which houses the scenario outputs used by St-SIM for visualization and export of data, and 3)...
Agent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (i.e., autonomous units, such as wildlife, people, or viruses); agent characteristics, decision-making, adaptive behavior, and mobility; and interactions between agents and their environment. STSMs are flexible and intuitive stochastic models of landscape dynamics that can track scenarios and landscape attributes, and integrate diverse data types. Both can be run spatially and track metrics of management success. Due to the complementarity...
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This is a spatially-explicit state-and-transition simulation model of rangeland vegetation dynamics in southwest South Dakota. It was co-designed with resource management partners to support scenario planning for climate change adaptation. The study site encompasses part of multiple jurisdictions, including Badlands National Park, Buffalo Gap National Grasslands, and Pine Ridge Indian Reservation. The model represents key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition (i.e., distribution of ecological community phases). See Miller et al. (2017) for further details. The model was built using the ST-Sim software platform (www.apexrms.com/stsm)....
Context Agent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (autonomous units, such as wildlife or people); agent characteristics, decision-making, adaptive behavior, and mobility; and agent-environment interactions. STSMs are flexible and intuitive stochastic landscape models that can track scenarios and integrate diverse data. Both can be run spatially and track metrics of management success. Objectives Due to the complementarity of these approaches, we sought to couple them through...
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