Habitat difference is an important mechanism for maintenance of tree diversity in tropical forests. The
first step in studies of habitat difference is to statistically analyze whether the spatial distributions of tree
populations are skewed to species-specific habitats; this is called a habitat association test. Wepropose a
novel habitat association test on the basis of the probability of tree occurrence along a continuous habitat
variable. The test uses torus shift simulations to obtain a statistical significance level.We applied this test
to 55 common dipterocarp species in a 52-ha plot of a Bornean forest to assess habitat associations along
an elevation gradient. The results were compared to those of three existing habitat association tests
using the same torus shift simulations. The results were considerably different from one another. In
particular, the results of two existing tests using discrete habitat variables varied with differences in
habitat definitions, specifically, differences in elevation break points, and the number of habitat classes.
Thus, definitions of habitats must be taken into account when habitat association tests with discrete
habitat variables are used. Analyses of artificial populations independent of habitat showed that all of the
tests usedwere robust with respect to spatial autocorrelation in tree distributions, although one existing
test had a higher risk of Type I errors, probably due to the use of multiple tests of significance. Power
analysis of artificial populations in which distributions were skewed to certain elevations showed that
the novel test had comparable statistical power to the most powerful existing test. Statistical power was
affected not by the total number of a given tree but by the number of clumps in a plot, suggesting that >5
clumps were required for a reliable result.