A model represents an event or process in a different and usually simplified form. Modelling, like statistics, can evoke great passions from the uninitiated or strongly prejudiced. To others it's like trying to understand cricket when you have previously played baseball. For readers that find mathematics very trying, a very readable discourse on mathematics and science by Kline (1953) is recommended to help break the ice, and for a similar discourse on modelling see Walters (1986).

Krebs (1988) suggested that population ecologists did not know enough to construct useful models of rodent population dynamics, though Caughley & Krebs (1983) modelled plant-herbivore dynamics of small and large mammals. A good point raised by Krebs (1988) was the need to bridge the apparent gap between modellers and field ecologists by describing the types of data to be measured in the field. Too often, field ecologists collect data not relevant to a model and modellers use parameters in a model that can not be directly estimated in the field. Hairston (1989) correctly cautioned against the blind acceptance of mathematical models because of their inclination to make unrealistic assumptions. Krebs (1988) doubted if models produce new principles in ecology. That is probably true of many models, but the models of disease dynamics have generated the concept of a threshold host abundance. This is described in section 5.6.