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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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The USGS assessment and methodology reports cited within this software release require extensive processing using computational methods and modeling. The most demanding aspects of the modeling were performed using publicly available software: SGeMS and GSLIB (See the 'Related External Resources' section on this webpage to learn more about this software). This publication releases the FORTRAN source code of 15 supplementary computer programs that are required to perform the more specific aspects of the modeling. Upon downloading a program, the user needs to use a FORTRAN compiler for generating the executable code. The tasks performed by these FORTRAN programs are: • blankgridsis, for blanking of several realizations...
    map background search result map search result map Coupled Agent-Based and State-and-Transition Simulation Model Coupled Agent-Based and State-and-Transition Simulation Model