Interactions of elevation, aspect, and slope in models of forest species composition and productivity


We present a linear model for the interacting effects of elevation, aspect, and slope for use in predicting forest productivity or species composition. The model formulation we propose integrates interactions of these three factors in a mathematical expression representing their combined effect in terms of a cosine function of aspect with a phase shift and amplitude that change with slope and elevation. This model allows the data to determine how the aspect effect changes with elevation and slope. Earlier articles concerning the interactions of slope, aspect, and elevation have been incomplete by either treating elevation as fixed or ignoring the possibility that aspect effect must also involve slope. The proposed set of variables is illustrated in four applications: (1) a hypothetical data set for probability of stocking by ‘species’ having different adaptations to elevation, (2) in a discriminant function for forest/nonforest classification of data from Utah, (3) estimating mean annual increment of Utah forests, and (4) estimating the height asymptote in a mixed-model differential equation predicting Douglas-fir height growth.

Forest Science, 53(4) : 486–492.