The spatial distributions of all plant species are controlled by their tolerances to a range of environmental conditions. However, growth patterns within the range of tolerance can vary considerably depending on the set of abiotic and biotic factors present. Understanding the mechanisms that control distributional limits of trees across environmental gradients remains an important question in biogeography, especially as we try to predict the effects of climate change on forests. However, few studies have examined tree growth patterns at distributional limits to understand how trees are responding to climatic variability across a moisture gradient. A better understanding of growth patterns and growth-climate relationships is essential to understanding drivers of distributional limits and for improving predictions about those distributions under climate change. Here I used dendroecological analysis to quantify the influence of climate and specifically moisture stress on radial growth patterns of ponderosa pine and Douglas fir growing along a moisture gradient in the Santa Fe National Forest of the Southern Rocky Mountains. I also examined growth before, during, and after a severe drought period in the 1950s to assess recovery rates across the moisture gradient. Using tree-ring analysis, I found growth to be slower and more sensitive to climate at the low moisture distributional limit than elsewhere within the spatial distribution. Trees at this site were more impacted by the 1950s drought and showed slower growth recovery in years following. Climate sensitivity declined across the gradient from xeric to mesic sites, while the pattern of growth rate increased from xeric to intermediate sites and then plateaued. Growth and sensitivity at the xeric site indicates that the distribution is limited by the trees' physiological intolerance to low moisture, while patterns at the mesic site suggest that this distributional limit is not related to intolerances to high moisture, but rather that biotic interactions (e.g. competition) may be the controlling factor. Therefore distributional limits at high and low moisture ends of the gradient are likely driven by different environmental factors and as a result will respond differently to future climate change.
