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Soil carbon is the largest active terrestrial reservoir in the carbon cycle, and potential feedbacks involving soil carbon play an important role in future climate change. Understanding how combinations of factors, such as vegetation, temperature, and soil moisture, affect soil carbon dioxide (CO 2 ) production in various environments across sub-daily to seasonal timescales is essential to accurately predict climate impacts on the carbon cycle. Here we present a quantitative accounting of factors governing CO 2 production in agricultural and prairie soils, using high-resolution monitoring of below-ground soil CO 2 concentrations and estimates of soil respiration fluxes. We compare Soil CO 2 with Normalized Difference Vegetation Index (NDVI), soil temperature, radiation, and volumetric moisture content using correlations and regressions at a variety of sampling frequencies. We find that NDVI tends to predict soil CO 2 concentration and production more effectively than soil temperature at daily timescales. At the time scale of a rain event, rain frequently leads to rapid drops in CO 2 concentration due to soil CO 2 abiotically equilibrating with rain water followed by prolonged increases in inferred CO 2 production. This pattern was only visible due to the high resolution of the soil CO 2 concentration data. We also found that prairie soils, which host a greater diversity of plant species, have a higher rate of CO 2 production than agricultural soils under comparable climate drivers. Finally, we examine how the temporal resolution of soil CO 2 data affects the magnitude of environmental correlations. These findings highlight that seasonal environmental and vegetation conditions strongly influence local soil CO 2 responses.
Saccardi et al. (Fri,) studied this question.