A conceptual and practical approach to data quality and analysis procedures for high-frequency soil respiration measurements

1. Understanding the mechanisms regulating the efflux of carbon dioxide (CO₂) from the soil to the atmosphere via soil respiration (SR) is a critical component of understanding terrestrial carbon (C) cycle responses to climate change, but requires high-quality measurements of SR fluxes. Thus, measurements of SR have become one of the primary tools used in terrestrial C cycling research. 2. When developing a sampling strategy for SR measurements, researchers must consider the ultimate use of the data set. A weekly or bi-weekly manual sampling strategy is likely sufficient if the desired outcome is an annual estimate of CO₂ efflux. However, if modelling SR on time scales from minutes to days is the purpose of the study, automated SR measurements are advantageous. 3. Automated SR systems produce large volumes of data that present new challenges for quality assurance and quality control. A relatively efficient protocol to analyse large SR data sets is proposed here. 4. Analysis of two large data sets provides information about systematic sampling uncertainties as well as random measurement errors. These must be taken into account when using automated SR measurements in any data-model fusion context.