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Agriculture Ecosystems & Environment
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Agriculture Ecosystems & Environment
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Quantifying and predicting spatio-temporal variability of soil CH 4 and N 2 O fluxes from a seemingly homogeneous Australian agricultural field

Authors: Alex B. McBratney; Marshall D. McDaniel; Marshall D. McDaniel; R. G. Simpson; Budiman Minasny; Mark A. Adams; Brendan P. Malone;

Quantifying and predicting spatio-temporal variability of soil CH 4 and N 2 O fluxes from a seemingly homogeneous Australian agricultural field

Abstract

Abstract Soil methane (CH4) and nitrous oxide (N2O) fluxes are difficult to predict from soil temperature and moisture alone, especially compared to carbon dioxide (CO2) fluxes. That difficulty is reflected in high spatial and temporal (spatiotemporal) variability of these two greenhouse gases (GHGs). We used a 16 ha field, under homogeneous soils and vegetation, to simultaneously explore spatial and temporal variability of soil CH4 and N2O fluxes. We also measured soil physical and chemical properties in order to explain, and predict, spatial variability of these two gases. Gas fluxes were measured using either a dynamic chamber (spatial variability study) or automated chambers using FTIR (temporal variability study). Soil samples were analysed for 30 chemical parameters (including at least two forms of soil carbon and nitrogen), while two proximal soil sensors were used to collect fine-resolution soil electrical conductivity and gamma radiometric concentration across the site. Fluxes of CH4 and N2O showed distinct spatial patterns, and were uniquely related to soil properties. Spatial variability in both CH4 and N2O fluxes was greater than five months of temporal variability (an increase in 112% and 39% in standard deviations for each gas respectively). If we relied solely on the autochambers for mean field fluxes, we would have underestimated fluxes by 59 and 197%, for CH4 and N2O respectively. CH4 fluxes were more spatially-dependent than those of N2O (semivariance analysis), but both showed greater spatial dependence than previously reported. Nearly 40 and 50% of the mean spatial flux of CH4 and N2O were from 1% of the area. Spatial variability in soil CH4 fluxes was predicted best by electrical conductivity measurements at 0–50 cm (r = 0.74) and soil C. Soil N2O fluxes, on the other hand, were predicted best by soil N and the gamma radiometric data (r = 0.48). Overall, our results clearly show that the large spatial variance of both CH4 and N2O fluxes requires great caution when scaling from chamber-based measurements to the field and beyond. Proximal sensors (as used here) can help map “hot spots” of soil CH4 and N2O fluxes at the field scale.

Country
United States
Related Organizations
Keywords

nitrous oxide, 550, methane, Soil Science, Agriculture, electromagnetic induction, Spatial Science, proximal sensors, 630, geospatial statistics, dynamic chambers, greenhouse gas, gamma radiometrics, spatial variability, agriculture

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Top 10%
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
46
Top 10%
Top 10%
Top 10%
hybrid