Abstract
The relationship between the number of species in a genus in a region and the area of this region is a topic much debated by biologists. Two models, namely the power function model and the exponential model have received most attention in the literature. Parameter estimates for these have been obtained by performing data transformations and applying classical least-squares methods on the transformed data. In this paper, we show how the species-area relationship may be modelled directly as a generalized linear model without data transformation. This method incorporates the above two models and also allows for the modelling of heterogeneity between sampling units. This is achieved by using compound Poisson error distributions for the number of species, in particular the negative binomial and inverse Gaussian-Poisson distributions. Examples of applications, and coding for the computer package GLIM, are given.
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