Diurnal temperature range drives understory plant community composition in micro-climatically complex temperate montane forests

Cold air drainage is common in mountains, and leads to large, fine-scale differences in diurnal temperature range (DTR). DTR is hypothesized to drive plant community assembly, because areas with high DTR can be exposed to both extreme high and extreme low temperatures in the same day. We established networks of temperature and relative humidity sensors along DTR gradients in two montane forest basins, and conducted plant surveys around each sensor (n=45). We studied the seasonal stability of DTR and its effects on fine-scale variation in plant community composition; and used topographic metrics to create spatial models of DTR. We found that mean DTR was stable throughout the year, although it was more variable around the mean (i.e., the standard deviation was higher) in winter months. It achieved both time series stability and distinguishability in less than 100 days, and was most strongly associated with daily minimum vapor pressure deficit. DTR measured in situ was the only variable that explained more than 50% of the within-basin variation in species composition for both basins, but among basins coarser-scale climatic variables (actual evapotranspiration, topographic wetness index, and climatic water deficit) performed better. DTR had a small, negative effect on species richness. Our simple model of DTR explained 64% of the variation, using only topographic wetness index and elevation as predictors. These findings illustrate how at broad scales, average temperature and moisture conditions drive the regional species pool, but fine scales distribution of plant species within a basin is driven by microclimate. Accounting for fine-scale topoclimatic processes will lead to better models that capture topoclimate gradients, allowing for improved representation of complex ecological processes in earth systems models. Future studies should account for microclimate, especially DTR, when designing experiments as sampling across microclimates will introduce bias into community observations.