Limitations on maximum tree density using hyperspatial remote sensing and environmental gradient analysis

Abstract

We present a novel approach for performing environmental gradient analysis to address the question: is maximum potential tree density in eastern Lake Tahoe Basin, NV limited by water, temperature/energetic constraints, or both? To address this question we fuse continuous tree density estimates derived from hyperspatial remote sensing imagery (pixels smaller than trees) with two topographically derived environmental gradients: elevation and yearly potential relative radiation (PRR). We based our analysis on the maximum tree density found in each of over 200 environmental gradient combinations found with our area of interest, drawing from a dataset consisting of over 300,000 30 m plots and over 3 million individual trees. At a given elevation, sites in which maximum tree density increases as a function of increasing yearly PRR were considered to be temperature or energy limited. Conversely, sites in which maximum tree density decreased as a function of increasing yearly PRR were considered water limited. We found that eastern Lake Tahoe appears to be a landscape which is both water limited (at lower elevation and brighter, south-facing slopes) and temperature/energy limited (at higher elevations and darker, north-facing slopes). We discuss how fusing accurate and ecologically relevant remote sensing outputs with direct and indirect continuous microclimate surfaces can provide a powerful tool for addressing major questions of tree distributions and life history parameters.