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The key concept in the statistical analysis of any mapped pattern is to regard it as an outcome (“realization”) of a spatial stochastic (“random”), process. Firstand second-order effects describe the two ways by which such a hypothesized process can create an observed spatial pattern that differs from complete spatial randomness (CSR).

First-Order Effects

First-order effects are best understood by reference to a pattern of individual point events making up a dot map. First, variations in the receptiveness of the study area may mean that the assumption of equal probability of each area receiving an event made in defining CSR cannot be sustained. For example, if the “events” are trees of a certain species, then almost certainly they will have a preference for patches of particular soil, with ...

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