A ERSF-VIPA framework: scalable wildlife movement modelling for conflict mitigation

Area of Science:

• Ecology
• Conservation Biology
• Wildlife Management

Background:

• Accurate wildlife movement path (WMP) modeling is essential for effective conservation planning and human-wildlife conflict mitigation.
• Current methods are often hindered by limited data and a lack of reliable techniques for modeling elusive species.
• Developing models that utilize minimal data to reproduce WMPs is a critical challenge.

Purpose of the Study:

• To introduce a novel framework, the Enhanced Resource Selection Function-Vector-network Iterative Pathfinding Algorithm (ERSF-VIPA), for simulating WMPs with limited data.
• To demonstrate the model's ability to provide actionable insights for human-wildlife conflict management.
• To assess the accuracy and applicability of ERSF-VIPA for reconstructing movement paths of elusive wildlife.

Main Methods:

• The ERSF-VIPA framework utilizes historical occurrence records, assuming rational, goal-driven decisions by individuals based on local environmental knowledge.
• It employs a random forest on a hexagonal grid to estimate nonlinear resource-selection probabilities.
• VIPA performs an iterative search across a hexagonal vector network, scoring paths by combining selection probability with cubic distance coefficients for ecological validity and energetic efficiency.

Main Results:

• The ERSF-VIPA model demonstrated high accuracy, with 90.3% of simulated paths closely approximating observed paths (average maximum deviation of 418m).
• The model successfully simulated Asian elephant (Elephas maximus) movement paths using coarse, non-continuous historical data.
• The framework proved robust and capable of translating limited tracking data into actionable conservation insights.

Conclusions:

• ERSF-VIPA is a robust and accurate framework for simulating wildlife movement paths, even with minimal and imprecise data.
• Its minimal data requirements enhance its extensibility and broad applicability for various elusive wildlife species.
• The model serves as a powerful decision-support tool for real-time animal monitoring and proactive human-wildlife conflict mitigation.