A comprehensive approach to soil‐atmosphere trace‐gas flux estimation with static chambers

Abstract

A new procedure (HMR) for soil‐atmosphere trace‐gas flux estimation with static chambers is presented. It classifies data series into three categories according to criteria based on the application of a particular non‐linear model and provides statistical data analyses for all categories. The two main categories are non‐linear and linear concentration data, for which data are analysed by, respectively, the non‐linear model and linear regression. The third category is represented by concentration data within the range of experimental error, or noise, from sites with no significant flux. Data in this category may be analysed by linear regression or simply classified as no flux. The particular non‐linear model has been selected among alternatives because its exponential curvature generally fits non‐linear static chamber concentration data well, and because it can be proven, mathematically, to be robust against horizontal gas transport through the soil or leaks in the chamber. The application of the HMR procedure is demonstrated on 244 data series of nitrous oxide accumulation over time. On average, 47% of these data were non‐linear, with an average flux increase over linear regression of 52%. The classification and analysis of data with a small signal‐to‐noise ratio requires special attention, and it is demonstrated how diagnostic graphical plots may be used to select the appropriate data analysis. The HMR procedure has been implemented as a free add‐on package for the free software R and is available for download through CRAN ( http://www.r‐project.org ).