Climate sensitivity functions and net primary production: A framework for incorporating climate mean and variability

Abstract

Understanding controls on net primary production (NPP) has been a long-standing goal in ecology. Climate is a well-known control on NPP, although the temporal differences among years within a site are often weaker than the spatial pattern of differences across sites. Climate sensitivity functions describe the relationship between an ecological response (e.g., NPP) and both the mean and variance of its climate driver (e.g., aridity index), providing a novel framework for understanding how climate trends in both mean and variance vary with NPP over time. Nonlinearities in these functions predict whether an increase in climate variance will have a positive effect (convex nonlinearity) or negative effect (concave nonlinearity) on NPP. The influence of climate variance may be particularly intense at ecosystem transition zones, if species reach physiological thresholds that create nonlinearities at these ecotones. Long-term data collected at the confluence of three dryland ecosystems in central New Mexico revealed that each ecosystem exhibited a unique climate sensitivity function that was consistent with long-term vegetation change occurring at their ecotones. Our analysis suggests that rising temperatures in drylands could alter the nonlinearities that determine the relative costs and benefits of variance in precipitation for primary production.