Individual-based modeling has been increasingly used to analyze ecological processes, to develop and to evaluate theories, as well as to the management of wild life and conservation. The individual-based models (IBM) are quite flexible, allowing a detailed inclusion of parameters with greater biological meaning, therefore being more realistic than classical population models, which are too constrained inside mathematical formalisms. The present paper discuss seven reasons for IBM to be adopted in simulation studies inside Ecology: (1) ecological systems are inherently complex, being not open to a complete formal mathematical analysis; (2) population processes are emergent outputs from the interactions among individuals and the environment; (3) predictive power; (4) the evolutive view as a definitive guide for ecological studies; (5) individuals are discrete entities; (6) interactions are localized in space and (7) individuals present differences among them.
Individual-based modeling; Ecology; Population dynamics
