Evidence of water limited affects in tree density in a subalpine/alpine environment as inferred from hyperspatial image data and climate gradient analysis

We investigated the probability of a tree to establish, grow and survive, independent of species, in a topographically heterogeneous landscape along the eastern side of the Lake Tahoe Basin, NV. The goal was to determine if direct and indirect gradients, all derived from a digital elevation model (DEM), could be used to infer which abiotic variable(s) relate to tree density. We used a relatively new suite of analysis tools and technologies that can identify and describe each tree in a hyperspatial image (ground resolution smaller than the object(s) of interest; in our case, a tree). We generated continuous individual tree maps across the entire eastern side of the Lake Tahoe basin, which completely circumvents ground-based sampling and scaling issues. We found the expected pattern of decreasing tree density with higher elevations. In this region, increasing elevation is correlated with decreasing temperatures, increasing precipitation, and lower soil water holding capacity. This leads to two possible explanations for decreasing stem densities with elevation: temperature limitations or water limitations. To decouple these effects, we examined the effects of yearly potential relative radiation (PRR): low PRR sites ('north facing') showed a significantly higher tree density than high ('south facing') sites at the same elevation. The only explanation for the low and mid-elevation patterns is widespread water limitation, not light or temperature limitation. Increasing temperature with no further input of water, therefore, would only serve to further stress the trees and cause a lower densities and, therefore, a loss of forest habitat.