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Michael M Fuller

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Work in progress. Last updated: February 27, 2007.
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We are using spatial analysis to compare alternative hypotheses for biodiversity patterns. Ecologists have long held that the biological traits of species determine their abundance and distribution in local species communities. This view is referred to as niche-based theory. But recently several ecologists have proposed that species traits are less important than inter-community migration rates and the abundance of species in the region. The latter paradigm is referred to as neutral theory. Neutral theory differs from niche-based theory in its assumptions about the intensity and symmetry of competitive interactions between individuals. These assumptions lead to specific predictions that can be used to test each theory. We relied on spatial analysis to detemine which predictions, neutral or niche-based, are best supported by empirical data.

To test the theoretical predictions, we first needed to know what a neutral community would look like. Much of the empirical basis for neutral theory comes from studies of tropical forests. Therefore, we focused on the spatial relationships of tropical forest trees. Neutral theory assumes that the spatial distribution of each tree species within a forest plot is determined its ability to disperse seeds or fruits. The farther away the seeds can travel, the more widespread the species will be. Parent trees act as a point source of seeds. Seed dispersal occurs as seeds are carried on the wind, by animals, or simply by gravity (such as rolling down a hill). From seed dispersal alone we expect the density of seeds, seedlings, and grown trees of a particular species to decrease with increasing distance from parent trees. The spatial gradient in density yields spatial dependence in the abundance of each species, a pattern referred to as spatial autocorrelation. A neutral community will therefore show autocorrelation in the density of each species.

To compare the predictions of the niche-based and neutral theories we used the actual geographic positions of trees recorded for a tropical forest study plot in Costa Rica.

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