Abstract
Alaska salmon fisheries are a source of commercial revenue, renewable subsistence resource, cultural identity, and recreational destination for Alaskans, native populations, and out of state eco-tourists alike. We constructed a high fidelity, adaptable, data-driven agent based model that generalizes the socio-ecological dynamics of Kenai River, Alaska. Interactions among the model’s agents can be altered to study the impact of fishing regulation changes or salmon run-timing dynamics. Agents are driven by stochastic principles derived from 35 years of integrated data including salmon runs, municipality management reports, and Alaska Department of Fish and Game management reports. Longitudinal and seasonal correlations between the model’s simulation outputs and the reported system measurements are used to validate the model.
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References
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Acknowledgements
This work was funded by Alaska EPSCoR NSF award #OIA-1208927. The authors would also like to thank all project collaborators for their comments and suggestions especially to Dr. Dan Rinella, Molly McCarthy, and ADFG Staff for sharing their incredible wealth of knowledge of Kenai Fisheries.
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Cenek, M., Franklin, M. (2018). Developing High Fidelity, Data Driven, Verified Agent Based Models of Coupled Socio-Ecological Systems of Alaska Fisheries. In: Perez, L., Kim, EK., Sengupta, R. (eds) Agent-Based Models and Complexity Science in the Age of Geospatial Big Data. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-65993-0_1
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DOI: https://doi.org/10.1007/978-3-319-65993-0_1
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