Dear Colleagues

The major driving force of recent and future anthropogenic climate change is the human perturbation of biogeochemical and energy cycles, including escalation of atmospheric greenhouse gas (GHG) concentrations, especially carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). Among the various sectors, the agricultural sector has large potential for climate mitigation related to land use (cropland, grassland), land management (e.g., manure management; soil management, improved rice cultivation), and intensity of use. In spite of this, given the geographic spread of grasslands and croplands, accompanied by differences in crops, cropping systems and agricultural practices per se, (region-) specific approaches are requested to define sustainable management practices.

Measurements of C fluxes exchanged and GHGs emitted in farming systems have been available in a large body of literature, covering an important number of systems and approaches using either chamber measurements or the eddy covariance method, each with advantages and disadvantages. Chamber measurements are used to characterize the spatial and temporal variability associated with the GHG flux in relatively small areas (from cm^-2 to m^-2), whereas the eddy covariance method is used to characterize temporal variability in relatively large areas (from hundreds of m^-2 to km^-2), allowing to determine system processes. In fact, coupling eddy covariance and ancillary measurements has become the way forward to understand both short- and long-term effects of principal drivers (e.g., management, climate) in in natura measurement and modeling approaches.  

This Special Issue on “Applications of Eddy Covariance in Farming Systems” invites contributions addressing the uses of the eddy covariance technique for i) evaluating different in agroecosystems and/ or agricultural (farm) practices, ii) comparing chamber measurements (CT) and the eddy covariance (EC) method in farming systems, iii) linking climate and management (e.g., cropping systems, rotation, intensification, grazing vs. mowing), and iv) identifying the advantages of modeling and/or remote sensing (e.g., assimilation of satellite vegetation index products at high spatial and temporal resolutions). 

Dr. Abad Chabbi
Dr. Katja Klumpp
Guest Editors

Manuscript Submission Information

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• eddy covariance
• agroecosystems
• soil
• carbon storage
• GHGs
• modeling
• remote sensing
• agricultural management