Aim Our aim was to understand how similarity changes with distance in biological communities, to use the distance decay perspective as quantitative technique to describe biogeographic pattern, and to explore whether growth form, dispersal type, rarity, or support affected the rate of distance decay in similarity.Location North American spruce-fir forests, Appalachian montane spruce-fir forests. MethodsWe estimated rates of distance decay through regression of log-transformed compositional similarity against distance for pairwise comparisons of thirty-four white spruce plots and twenty-six black spruce plots distributed from eastern Canada to Alaska, six regional floras along the crest of the Appalachians, and six regional floras along the east-west extent of the boreal forest.Results Similarity decreased significantly with distance, with the most linear models relating the log of similarity to untransformed distance. The rate of similarity decay was 1.5-1.9 times higher for vascular plants than for bryophytes. The rate of distance decay was highest for berry-fruited and nut-bearing species (1.7 times higher than plumose-seeded species and 1.9 times higher than microseeded/spore species) and 2.1 times higher for herbs than woody plants. There was no distance decay for rare species, while species of intermediate frequency had 2.0 times higher distance decay rates than common species. The rate of distance decay was 2.7 times higher for floras from the fragmented Appalachians than for floras from the contiguous boreal forest. Main conclusionsThe distance decay of similarity can be caused by either a decrease in environmental similarity with distance (e.g. climatic gradients) or by limits to dispersal and niche width differences among taxa. Regardless of cause, the distance decay of similarity provides a simple descriptor of how biological diversity is distributed and therefore has consequences for conservation strategy.

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Gravity models are commonly used by geographers to predict migration and interaction between populations and regions. Even though rarely used by ecologists, gravity models allow estimation of long-distance dispersal between discrete points in heterogeneous landscapes. We developed a production-constrained gravity model to forecast zebra mussel (Dreissena polymorpha) dispersal into inland lakes of Illinois, Indiana, Michigan, and Wisconsin (USA) based on the site and location of lakes and the number and location of boats within 364 counties. A deterministic form of this model was used to estimate bestfit parameters for distance coefficient, Great Lakes boat-ramp attractiveness, and colonization cutoff threshold. A stochastic model thus developed from these parameters allows for random changes in colonization likelihood. The results of our model are highly correlated with the actual pattern of colonized lakes in southern Michigan and southeastern Wisconsin at the end of 1997. Areas of central Wisconsin and western Michigan, where zebra mussel colonies have not been documented, were also predicted to be colonized, suggesting that future invasions may be imminent in these locations. These analyses suggest that gravity models may be useful in predicting long-distance dispersal when dispersal abilities of species and the attractiveness of potential habitats are known.

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