A Physics-Informed Inverse Modeling Framework for Moose-Wolf Dynamics from Limited and Noisy Data

This paper addresses the inverse problem of recovering governing parameters in ecological predator-prey dynamics from limited and noisy observational data. The study focuses on the Moose-Wolf interaction system in Isle Royale National Park as a canonical benchmark. The proposed physics-informed framework leverages mathematical models of ecosystem interactions combined with data-driven parameter estimation techniques to handle real-world data challenges.