Ranking factors affecting emissions of GHG from incubated agricultural soils

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...

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Veröffentlicht in:European journal of soil science 2014-07, Vol.65 (4), p.573-583
Hauptverfasser: García‐Marco, S, Ravella, S. R, Chadwick, D, Vallejo, A, Gregory, A. S, Cárdenas, L. M
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Sprache:eng
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Zusammenfassung: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 (NO₃ ⁻) 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 L₁₆ design, comprising 16 experimental units. Within this L₁₆ design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N₂O), methane (CH₄) and carbon dioxide (CO₂) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO₃ ⁻ addition were the main factors affecting N₂O fluxes, whilst glucose, NO₃ ⁻ and soil temperature were the main factors affecting CO₂ and CH₄ 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.
ISSN:1351-0754
1365-2389
DOI:10.1111/ejss.12143