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Bridging the gaps: Agent-based modelling for elephant poaching mitigation

Bridging the gaps: Agent-based modelling for elephant poaching mitigation (version 1.2.0)

As an illustration of the utility of agent-based models (ABMs) for poaching mitigation, we developed an exploratory ABM that predicts how interactions between elephants, poachers, and law enforcement affect poaching levels within a virtual protected area. The model is theoretical at this stage but is parameterized with realistic ecological and behavioral data on African elephants, as well as representative information on poaching and ranger strategies. The aim of this model is not to provide a realistic depiction of poaching, but instead to demonstrate how ABMs can bridge the gaps present in the other two main modelling techniques applied to this topic to-date (equation-based and game theoretical models) and to provide a framework for future research. The model provides a starting point for further development and application to real-world situations, perhaps incorporating real GPS data of elephant movements and poaching incidents, and GIS satellite imagery. The aim is for this model to be further developed into a useful management support tool, one that can be used as a virtual laboratory to experiment with different scenarios without putting time, funds, resources, personnel, or elephants at risk.

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This is a companion discussion topic for the original entry at