A multisite analysis of temporal random errors in soil CO₂ efflux

Abstract

Abstract An important component of the terrestrial carbon balance is the efflux of CO 2 from soils to the atmosphere, which is strongly influenced by changes in soil moisture and temperature. Continuous measurements of soil CO 2 efflux are available around the world, and there is a need to develop and improve analyses to better quantify the precision of the measurements. We focused on random errors in measurements, which are caused by unknown and unpredictable changes such as fluctuating environmental conditions. We used the CO 2 gradient flux method with two different algorithms to study the temporal variation of soil CO 2 efflux and associated random errors at four different ecosystems with wide ranges in mean annual temperature, soil moisture, and soil CO 2 efflux. Our results show that random errors were better explained by a double‐exponential distribution, had a mean value close to zero, were nonheteroscedastic, and were independent of soil moisture conditions. Random errors increased with the magnitude of soil CO 2 efflux and scale isometrically (scaling exponent ≈ 1) within and across all sites, with a single relation common to all data. This isometric scaling is unaffected by ecosystem type, soil moisture conditions, and soil CO 2 efflux range (maximum and minimum values within an ecosystem). These results suggest larger uncertainty under extreme events that increase soil CO 2 efflux rates. The accumulated annual uncertainty due to random errors varied between ±0.38 and ±2.39%. These results provide insights on the scalability of the sensitivity of soil CO 2 efflux to changing weather conditions across ecosystems.