Within-field spatial variability of greenhouse gas fluxes from an extensive and intensive sheep-grazed pasture

A - Papers appearing in refereed journals

Charteris, A. F., Harris, P., Marsden, K. A., Harris, I. M., Guo, Z., Beaumont, D. A., Taylor, H., Sanfratello, G., Jones, D. L., Johnson, S. C. M., Whelan, M. J., Howden, N., Sint, H. M., Chadwick, D. R. and Cardenas, L. M. 2021. Within-field spatial variability of greenhouse gas fluxes from an extensive and intensive sheep-grazed pasture. Agriculture, Ecosystems & Environment. 312, p. 107355. https://doi.org/10.1016/j.agee.2021.107355

AuthorsCharteris, A. F., Harris, P., Marsden, K. A., Harris, I. M., Guo, Z., Beaumont, D. A., Taylor, H., Sanfratello, G., Jones, D. L., Johnson, S. C. M., Whelan, M. J., Howden, N., Sint, H. M., Chadwick, D. R. and Cardenas, L. M.
Abstract

Greenhouse gas (GHG) fluxes from livestock grazed pasture soils are highly variable in both space and time but the quantitative importance of the factors regulating this variation remain poorly understood. Our aim was to explore this variability on contrasting extensively (low input) and intensively managed sheep-grazed ‘case-study’ pastures. We quantified (through standard and spatially-informed regressions) the statistical relationships between GHG fluxes (nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4)) and a range of soil, field and management characteristics. Fluxes of these three GHGs at two study sites were highly variable, but spatial structure (i.e. autocorrelation) was only observed in the variability of N2O fluxes across the intensive site and CO2 fluxes across the extensive site. The regression analyses identified significant GHG predictor variables for the extensive site as: NO3- (p < 0.001) and vegetation-type (p < 0.01) for N2O (R2 = 0.57; p = 0.000); NH4+ (p < 0.05), slope (p < 0.05) and elevation (p < 0.01) for CO2 (R2 = 0.34; p = 0.000); and NO3- (p < 0.01), NH4+ (p < 0.05) and soil moisture (p < 0.05) for CH4 (R2 = 0.25; p = 0.005). Significant GHG predictor variables for the intensive site were soil moisture (p < 0.01) and bulk density (p < 0.01) for N2O (R2 = 0.27; p = 0.005); soil moisture (p < 0.001) for CO2 (R2 = 0.31; p = 0.001); while none were found for CH4 (R2 = 0.10; p = 0.655). Key factors driving GHG variation were both site- and GHG-specific, with fluxes controlled by local conditions leading to differences in limiting factors (possibly even at the within-site scale). Our statistical analyses suggest a larger range of driving variables (e.g. air and soil temperature or other soil chemical properties such as total extractable N) may be required to more fully capture the observed variability in the GHG processes considered here, and that it may also be fruitful for future analyses to consider non-linear, non-stationary and interacting relationships across space- and time-scales. Adequacies of each site’s sample design also played a key interpretive role in the GHG processes, requiring further evaluation through additional sampling campaigns.

KeywordsUpland; Lowland; Grassland; Nitrous oxide; Carbon dioxide; Methane
Year of Publication2021
JournalAgriculture, Ecosystems & Environment
Journal citation312, p. 107355
Digital Object Identifier (DOI)https://doi.org/10.1016/j.agee.2021.107355
Web address (URL)https://www.sciencedirect.com/science/article/abs/pii/S0167880921000591
Open accessPublished as green open access
FunderNatural Environment Research Council
Biotechnology and Biological Sciences Research Council
Funder project or codeGrazing behaviour, urine composition and soil properties are key controls of N2O emission factors in the uplands
The North Wyke Farm Platform- National Capability [2017-22]
S2N - Soil to Nutrition - Work package 2 (WP2) - Adaptive management systems for improved efficiency and nutritional quality
S2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales
Accepted author manuscript
Output statusPublished
Publication dates
Online23 Feb 2021
Publication process dates
Accepted06 Feb 2021
PublisherElsevier Science Bv
ISSN0167-8809

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