As these situations are frequently encountered in ecology, simulation models are now widely applied across the discipline. Such an algorithmic model specification is particularly suited for describing systems that are difficult to capture or analyze with differential equations such as: (a) systems that are highly nonlinear or chaotic (b) discrete systems, for example networks or groups of distinct individuals (c) systems that are stochastic and (d) systems that are too complex to be successfully treated with classical calculus. Unlike in a mathematical model, however, this propagation does not employ the methods of calculus but rather a set of rules or formulae that directly prescribe the next state. Broadly speaking, a simulation model is an algorithm, typically implemented as a computer program, which propagates the states of a system forward. With the rise of computers, simulation models have emerged beside the more traditional statistical and mathematical models as a third pillar for ecological analysis.
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