Plant communities as microclimate sensors: a new approach to climate downscaling using North American trees as bioindicators

Background/Question/Methods

Microclimate patterns are important in spatial ecology and climate change resilience, but generating ecologically useful microclimate predictions is a challenge. Traditionally, microclimate models have relied either on a “mechanistic approach” based on physical first principles, or on an “empirical approach” based on installing microclimate sensors throughout a landscape. We propose a new “bioindicator approach” that instead infers microclimate from plant species distributions, by leveraging correlations in their observed occurrence patterns across macroclimatic versus micro-topographic gradients. This approach overcomes several limitations of traditional methods: it requires only publicly available data, is scalable to large geographic areas, and generates estimates of ecologically salient aspects of microclimate. We implement the method in a multilevel Bayesian model describing how fine-scale terrain variables (slope, aspect, topographic prominence, and prevailing wind exposure) shape microclimate temperature and moisture regimes across the ranges of 216 tree species in North America.

Results/Conclusions

Our results highlight a number of important topoclimate phenomena. Plant distributions indicate that fine-scale topography drives local microclimate variation up to 5°C and up to twofold variation in moisture, and that the size of these effects is geographically variable, with the strongest effects in cool, dry climates. We find that the hillslope aspects with the warmest and driest biotic signatures are different (which implies multidimensional variation in microclimate with aspect), and we find that southeastern aspects tend to have the warmest, driest biotic signatures (which is surprising given that southwest aspects tend to be hottest and driest). Finally, we demonstrate how the fitted model parameters can be used in conjunction with topographic and macroclimatic data to generate downscaled microclimate maps for use in spatial ecology applications. These methods and results open new lines of insight into microclimate ecology.