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A new approach for representing agent-environment feedbacks: coupled agent-based and state-and-transition simulation models

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Abstract

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 a dynamic linkage and demonstrate the relevance of this advancement for modeling landscape processes and patterns.

Methods

We developed analytical techniques and software tools to couple these modeling approaches using NetLogo, R, and the ST-Sim package for SyncroSim. We demonstrated the capabilities and value of this coupled approach through a proof-of-concept case study of bison-vegetation interactions in Badlands National Park.

Results

The coupled ABM-STSM: (1) streamlined handling of model inputs and outputs; (2) allowed representation of processes at multiple temporal scales; (3) minimized assumptions; and (4) generated spatial and temporal patterns that better reflected agent-environment interactions.

Conclusions

These developments constitute a new approach for representing agent-environment feedbacks; modelers can now use output from an ABM to dictate landscape changes within an STSM that in turn influence agents. This facilitates experimentation across domains (agent and environment) and creation of more realistic and management-relevant projections, and opens new opportunities for communicating models and linking to other methods.

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Data availability

Models, data, and scripts used in this study are publicly available on the U.S. Geological Survey ScienceBase digital catalogue at: https://doi.org/10.5066/P9R98PPB (Miller and Frid. 2021). See Online Resource S1 for details on accessing the case study files and a sample dataset including coupled and standalone simulations and associated code files that are compatible with the latest version of SyncroSim.

Notes

  1. NRCS ecological site descriptions are available from https://edit.jornada.nmsu.edu

  2. NRCS soil maps and data are available from http://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx

  3. The bison range of Badlands National Park was expanded on October 11, 2019, after model development was complete, hence the use of the previous bison range boundary for this work.

  4. For the updated model, cells in the initial state class raster that were classified as thistle or encroached by woody species were reassigned to another state class according to the proportional areas of the remaining landscape.

  5. The updated model assumed static year-round grazing consumption, which was set to match the number of bison initialized in the ABM.

  6. The updated biomass flows removed litter and only included decomposition, grazing, and net primary production (NPP).

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Acknowledgements

We are grateful to Josie Hughes and Alex Embrey for helping develop the coupled model script, Tyler Beeton for sharing an ABM that served as the seed for the one described here, and Shreeram Senthivasan for reviewing the models and updating the models and documentation in the sample dataset. We also thank Catherine Jarnevich and three anonymous reviewers for their thoughtful comments on previous drafts of the paper. This research was funded by the U.S. Geological Survey, North Central Climate Adaptation Science Center. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Authors and Affiliations

  1. U.S. Geological Survey, North Central Climate Adaptation Science Center, 2150 Centre Avenue, Bldg C, Fort Collins, CO, 80526, USA

    Brian W. Miller

  2. Apex Resource Management Solutions Ltd., 937 Kingsmere Avenue, Ottawa, ON, K2A 3K2, Canada

    Leonardo Frid

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  1. Brian W. Miller
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Contributions

Both authors made substantial, direct contributions to the work, and approved it for publication. BWM conceived of the study and overall approach to link ABMs and STSMs using SyncroSim. LF developed the technical specifications and led the development of the STSM and ABM linkages. BWM led the model parameterization, run implementation, post processing of results, and writing of the manuscript.

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Correspondence to Brian W. Miller.

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Miller, B.W., Frid, L. A new approach for representing agent-environment feedbacks: coupled agent-based and state-and-transition simulation models. Landsc Ecol 37, 43–58 (2022). https://doi.org/10.1007/s10980-021-01282-y

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