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Modeling is a common tool in studies of forest landscape disturbances. After several decades of development and use, these tools could be now examined for their foundations, intentions, scope, advancements, and limitations. We contend that, when applied to forest landscape disturbances, modeling techniques must address many concepts such as stochasticity, heterogeneity, scale dependence, non linearity and parsimony as well as be explicit with the intended degree of abstraction and assumptions. Also we assert that simulating forest landscape disturbances needs to evolve towards mechanistic and process-driven models, from an exclusive reliance on empirical and statistical models.