Ranking factors affecting emissions of GHG from incubated agricultural soils. (18th June 2014)

• Record Type: Journal Article
• Authors: García‐Marco, S.; Ravella, S. R.; Chadwick, D.; Vallejo, A.; Gregory, A. S.; Cárdenas, L. M.
• Is Part Of: European journal of soil science. Volume 65:Number 4(2014:Aug.)
• Page Start: 573
• Page End: 583
• Publication Date: 2014-06-18
• Subjects: Soil science -- Periodicals; 631.4
• DOI: 10.1111/ejss.12143
• Languages: English
• ISSNs: 1351-0754

Abstract

<abstract abstract-type="main" id="ejss12143-abs-0001"> <title>Summary</title> <p id="ejss12143-para-0001">Agriculture significantly contributes to global greenhouse gas (GHG) emissions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO<sub>3</sub><sup>−</sup>) addition, carbon quality (labile and non‐labile C), soil temperature, water‐filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L<sub>16</sub> design, comprising 16 experimental units. Within this L<sub>16</sub> design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N<sub>2</sub>O), methane (CH<sub>4</sub>) and carbon dioxide (CO<sub>2</sub>) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO<sub>3</sub><sup>−</sup> addition were the main factors affecting N<sub>2</sub>O fluxes, whilst glucose, NO<sub>3</sub><sup>−</sup> and soil temperature were the main factors affecting CO<sub>2</sub> and CH<sub>4</sub> fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro‐ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.</p> </abstract>