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原文連結
論文資訊
- 類型：已發表論文
- 日期：2012
摘要
A commonly used null model for 物種 association among 森林 trees is a well-mixed community (WMC). A WMC represents a non-spatial, or spatially implicit, model, in which 物種 form nearest-neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the 物種 spatial distributions. Yet, 隨機 dispersal processes often lead to spatial autocorrelation (SAC) in tree 物種 densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially-explicit models, its impact on non-spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non-spatial models, we devel
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