Abstract
A neutral model is a minimum set of rules required to generate pattern in the absence of a particular process (or set of processes) being studied. The results of the neutral model provide a means of testing the effect of the measured process on patterns that are actually observed (Caswell 1976). If observed patterns do not differ from the neutral model, then the measured process has not significantly affected the observed pattern. Conversely, when results differ from model predictions in a way that is consistent with a particular process, then strong evidence for the importance of this process has been obtained. Several authors have argued that formulation of a proper neutral model is necessary for hypothesis testing, because data often exhibit nonrandom patterns in the absence of the causal mechanisms of interest (Quinn and Dunham 1983). This approach has been discussed extensively in the field of community ecology (e.g. Conner and Simberloff 1984 1986; Haefner 1988) as well as other areas of biology (Nitecki and Hoffman 1987).
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Pearson, S.M., Gardner, R.H. (1997). Neutral Models: Useful Tools for Understanding Landscape Patterns. In: Bissonette, J.A. (eds) Wildlife and Landscape Ecology. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1918-7_8
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