Average, variability, and extremes: A framework to quantify microclimate temperature modulation

Eliah Milan Grooss , Nico Eisenhauer, Georg J. A. Hähn, Francesco Sabatini, Yuanyuan Huang, Julius Quosh, Manfred Wendisch, Rémy Beugnon

Microclimate, the climatic conditions experienced by organisms, can differ substantially from the macroclimate measured by weather stations. Microclimate modulation is the modification of the microclimate by environmental conditions. Despite its ecological importance, there is currently no standardized method for quantifying microclimate modulation, which limits comparability across studies. Commonly used indices can be categorized as targeting microclimate temperature average, variability, or extremes (maxima and minima). The average describes the central tendency of the temperature, variability quantifies its dispersion or fluctuations, and extremes capture rare but potentially important high and low values.
Here, we compiled and compared 12 types of indices used in the literature to quantify microclimate temperature modulation in ecology. Using forest microclimate temperature measurements from 47 sites in Italy, we calculated the microclimate indices and showed in a Principal Component Analysis that they clustered in the categories of average, variability, maxima and minima. In a simulation framework, we modified microclimate average, variability, and extremes, and introduced error. We calculated the microclimate indices on the simulated data, and compared the indices’ responses to the simulated modulation.
We found that both mean and median offset (difference between microclimate and macroclimate) reliably represented average modulation and were robust to simulated error. The offset of amplitudes between the 5th and 95th percentiles best represented variability modulation. For maxima and minima, respectively, the 97.5th and 2.5th percentile best balanced error-proneness and distance from the absolute maximum or minimum.
The proposed indices provide a comprehensive and widely applicable approach to quantifying microclimate temperature modulation in ecology. Since average, variability, and extremes are relevant proxies for how temperature affects ecological processes, we suggest using them in conjunction to characterize microclimate modulation. Widespread application of this framework will enhance comparability between microclimate studies and offer new insights into how microclimate modulation interacts with environmental parameters and ecosystem processes.