Agent-based modelling as a tool for elephant poaching mitigation

African elephants (Loxodonta africana) have undergone serious declines in the past century due to poaching for their ivory. Wildlife managers face significant challenges when planning poaching mitigation strategies, bounded by financial and logistical constraints. Quantitative models can provide practical insights for management, and many ‘equation-based’ and game theoretical models have been applied to poaching mitigation to-date. ‘Equation-based’ models are advantageous in many respects, and widely used, but face difficulties when working with complex and dynamic systems like poaching, and often require significant simplifications to be made to the model specification. Game theoretical models can incorporate adaptive responses of poachers and rangers to dynamic systems but abstract the behavioural and ecological information on elephants. Managers and policymakers would benefit from a supplementary modelling technique. Agent-based models (ABMs) can supplement and expand upon the existing work done in this field. These represent the behaviours and objectives of individuals, providing analyses of how bottom-up interactions affect a system on the macro level. ABMs present the opportunity to model the complex interdependencies between law enforcement strategies, adaptive poacher decision-making, and the ecology and behaviour of elephants. To illustrate the utility of ABMs for poaching mitigation, an exploratory ABM was developed that predicts how interactions between elephants, poachers, and law enforcement affect poaching levels within a virtual protected area. Two poacher decision-making strategies are simulated: one in which poachers move randomly throughout the landscape, and one in which poachers adaptively decide where to hunt based on their memories of elephant and ranger whereabouts. Additionally, two law enforcement strategies are tested: one in which rangers patrol according to a prescribed distribution and another in which rangers adaptively follow matriarchal herds. Overall, adaptive poachers and adaptive law enforcement performed significantly better at their relevant goals than randomly moving poachers and the law enforcement strategy in which rangers have a prescribed distribution of effort. This demonstrates how ABMs can allow for more complex formulations and inform new poaching mitigation strategies. The aim is for this model to be developed into a useful management support tool and applied to real-world scenarios to inform decision-making, and several possible refinements and avenues for future research and development are suggested.