Global Research Alliance N2O chamber methodology guidelines: Recommendations for deployment and accounting for sources of variability. Issue 5 (22nd September 2020)

• Record Type: Journal Article
• Authors: Charteris, Alice F.; Chadwick, David R.; Thorman, Rachel E.; Vallejo, Antonio; de Klein, Cecile A.M.; Rochette, Philippe; Cárdenas, Laura M.
• Is Part Of: Journal of Environmental Quality. Volume 49:Issue 5(2020)
• Page Start: 1092
• Page End: 1109
• Publication Date: 2020-09-22
• Subjects: Agricultural ecology -- Periodicals; Environmental engineering -- Periodicals; Pollution -- Periodicals; 630
• DOI: 10.1002/jeq2.20126
• Languages: English
• ISSNs: 0047-2425

Abstract

Abstract: Adequately estimating soil nitrous oxide (N2 O) emissions using static chambers is challenging due to the high spatial variability and episodic nature of these fluxes. We discuss how to design experiments using static chambers to better account for this variability and reduce the uncertainty of N2 O emission estimates. This paper is part of a series, each discussing different facets of N2 O chamber methodology. Aspects of experimental design and sampling affected by spatial variability include site selection and chamber layout, size, and areal coverage. Where used, treatment application adds a further level of spatial variability. Time of day, frequency, and duration of sampling (both individual chamber closure and overall experiment duration) affect the temporal variability captured. We also present best practice recommendations for chamber installation and sampling protocols to reduce further uncertainty. To obtain the best N2 O emission estimates, resources should be allocated to minimize the overall uncertainty in line with experiment objectives. Sometimes this will mean prioritizing individual flux measurements and increasing their accuracy and precision by, for example, collecting four or more headspace samples during each chamber closure. However, where N2 O fluxes are exceptionally spatially variable (e.g., in heterogeneous agricultural landscapes, such as uneven and woody grazed pastures), using available resources to deploy more chambers with fewer headspace samples per chamber may be beneficial. Similarly, for particularly episodic N2 O fluxes, generated for example by irrigation or freeze–thaw cycles, increasing chamber sampling frequency will improve the accuracy and reduce the uncertainty of temporally interpolated N2 O fluxes.