Research overview: agent-based and individual movement simulation

Movement models can be turned around to simulate animals, generating virtual trajectories from estimated movement rules to predict population-level patterns. This overview describes agent-based and individual-based simulations in which modeled cats make step-by-step decisions about where to move based on habitat, risk, memory, and energetic state. Such simulations test how dispersers might traverse fragmented landscapes, predict colonization of restored habitat, and evaluate where crossing structures would most improve connectivity. They also explore emergent phenomena like territory formation from simple local rules. The overview discusses parameterizing simulations from empirical step-selection models and validating them against real tracks. By extrapolating from observed behavior to scenarios that cannot be directly studied, simulation links mechanistic movement understanding to conservation planning for felids.