Spatial analysis of ponderosa pine trees infected with dwarf mistletoe

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Abstract
Distance-based multiresponse permutation procedures are presented as an alternative method of characterizing the spatial point pattern of mapped data sets. Methods are described for studying the spatial relationships and patterns in populations consisting of two or more groups. The ability of multiresponse permutation procedures to detect both nonrandom spatial patterns and segregation is compared with Hopkins and Skellam's coefficient of aggregation and Pielou's index of segregation, respectively, using data on the size and severity of dwarf mistletoe (Arceuthobiumvaginatum ssp. cryptopodum (Engelm.) Hawksw. & Wiens) infection of ponderosa pine (Pinusponderosa Laws.) trees. One advantage of multiresponse permutation procedures is that it uses all of the data in the analysis instead of a random sample that is subject to edge effect and sampling errors. Unlike distance sampling, multiresponse permutation procedures are not linked to specific model assumption and hence are more widely applicable as a descriptive measure. However, this method is computationally intensive and has certain limitations, which are highlighted in the discussion.

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