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Pair statistics clarify percolation properties of spatially explicit simulations
 

Summary: Pair statistics clarify percolation properties of
spatially explicit simulations
Jeffrey D. Achter , Colleen Webb
Department of Biology, Colorado State University, Fort Collins, CO 80523
Corresponding author.
Email addresses: j.achter@colostate.edu (Jeffrey D. Achter),
ctwebb@lamar.colostate.edu (Colleen Webb).
URL: http://lamar.colostate.edu/jachter (Jeffrey D. Achter).
Preprint submitted to Elsevier Science 15 September 2005
Abstract
Dispersal is a fundamental control on the spatial structure of a population. We inves-
tigate the precise mechanism by which a mixed strategy of short- and long-distance
dispersal affects spatial patterning. Using techniques from pair approximation and
percolation theory, we demonstrate that dispersal controls the extent to which a
population is completely connected by modulating the proportion of neighboring
sites which are simultaneously occupied. We show that near the percolation thresh-
old this pair statistic, rather than other metrics proposed earlier, best explains
clustering, and we suggest more general circumstances under which this may hold.
Key words: dispersal, percolation, pair approximation, aggregation, spatial
models, connectivity

  

Source: Achter, Jeff - Department of Mathematics, Colorado State University

 

Collections: Environmental Sciences and Ecology; Mathematics