An extreme-value approach to detect clumping and an application to tropical forest gap-mosaic dynamics
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Although forest tree pattern-dynamics has long been a focus for ecological theory, many aspects of basic analysis remain problematic.This paper describes, examines and illustrates an 'extreme-value' approach to clump detection. Simulations demonstrate that the approach, though simple, is sensitive and well suited to identifying aggregation, even in small data sets.Though powerful, the extreme-value tests are slightly conservative.The approach is adaptable to other null distributions and applications. An illustration uses tree data from a Ugandan forest plot with records from 1939 to 1992. One plausible explanation for observed stem increases in this plot is an unusually high incidence of large tree-fall events. Evidence for this is sought through spatial localization of various stem populations. Various technical and ecological aspects of the extreme-value approach and tree spatial analyses are discussed.
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