Abstract
Background The geographic distribution of forest and woodland ecosystems in the Interior West United States is strongly influenced by topographic gradients that, in part, control moisture availability through their effect on insolation, and precipitation capture and retention. Through an empirical approach, we use unique, plot-level data from the Forest Inventory and Analysis Program ( n = 13,437) over eight ecoregions within eight Interior West states to characterize the distribution of the 12 most abundant tree species with respect to the effects of elevation, slope aspect, and slope steepness. Results Across species, elevation, and aspect, most plots occurred on gentle slopes and the number decreased with increasing slope. Species-specific differences to microenvironmental conditions were evident in the variation between observed (plots containing a subject tree) and expected (all forest plots from the systematic sample) numbers of plots across the gradient combinations. Species groups, broadly defined as woodland, montane, and subalpine, generally exhibited similar responses and revealed more generality than hypothesized. Only Douglas-fir, white fir, subalpine fir, and Engelmann spruce exhibited significant patterns of affinity for particular aspects—most often on north and least often on south—with the relative importance of south aspects decreasing with increasing elevation. Limber pine showed unique, unimodal patterns of affinity for moderately steep slopes, with no consistent patterns by aspect or elevation. Although not significant, at high elevations woodland species exhibited a tendency to occur more often on south aspects on gentle to intermediate slopes, and less often on north aspects. Conclusions Unique microenvironments created by interactions between aspect, slope, and elevation create some predictability in patterns of geographic distribution. However, the general lack of species-specific response suggests that patterns of occurrence in relation to physiographic gradients is much broader than in common generalizations.