Automated modeling of ecosystem CO2 fluxes based on periodic closed chamber measurements: A standardized conceptual and practical approach

Closed chamber measurements are widely used for determining the CO2 exchange of different ecosystems. Among the chamber design and operational handling, the data processing procedure is a considerable source of uncertainty of obtained results. We developed a standardized automatic data processing algorithm, based on the language and statistical computing environment R© to (i) calculate measured CO2 flux rates, (ii) parameterize ecosystem respiration (Reco) and gross primary production (GPP) models, (iii) optionally compute an adaptive temperature model, (iv) model Reco, GPP and net ecosystem exchange (NEE), and (v) evaluate model uncertainty. The algorithm was tested in a case study performed at a cultivated fen situated in the northeast of Germany. Our study shows that even minor changes within the modeling approach may result in considerable differences of calculated flux rates, derived photosynthetic active radiation and temperature dependencies. Subsequently modeled Reco, GPP and NEE balance can therefore vary by up to 25%. Thus, automated and standardized data processing procedures, based on clearly defined criteria, such as statistical parameters and thresholds, are a prerequisite and highly desirable to guarantee the reproducibility and traceability of modeling results. Moreover, a standardized and automated data processing procedure also encourage a better comparability between closed chamber-based CO2 measurements.