Spatial variability of agricultural soil carbon dioxide and nitrous oxide fluxes: Characterization and recommendations from spatially high-resolution, multi-year dataset

Mitigating agricultural soil greenhouse gas (GHG) emissions can contribute to meeting the global climate goals. High spatial and temporal resolution, large-scale, and multi-year data are necessary to characterize and predict spatial patterns of soil GHG fluxes to establish well-informed mitigation strategies, but not many of such datasets are currently available. To address this gap in data we collected two years of in-season soil carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) fluxes at high spatial resolution (7.4 sampling points ha −1 ) from three commercial sites in central Illinois, one conventionally managed continuous corn (2.8 ha in 2021; 5.4 ha in 2022) and two (one site 5.4 ha in 2021 and 2.0 ha in 2022, another site 2.7 ha both years) under conservation practices in corn-soybean rotations. At the field-scale, the spatial variability of CO 2 was comparable across sites, years, and management practices, but N 2 O was on average 77 % more spatially variable in the conventionally managed site. Analysis of N 2 O hotspots revealed that although they represent a similar proportion of the sampling areas across sites (conventional: 12 %; conservation: 13 %), hotspot contribution to field-wide emission was greater in the conventional site than in the conservation sites (conventional: 51 %; conservation: 34 %). Also, the spatial patterns, especially hotspot locations, of both gases were inter-annually inconsistent, with hotspots rarely occurring in the same location. Overall, our result indicated that traditional field-scale monitoring with gas chambers may not be the optimal approach to detect GHG hotspots in row crop systems, due to the unpredictable spatial heterogeneity of management practices. Meanwhile, sensitivity analysis demonstrated that reliable (< 25 % error) field-scale soil GHG flux estimates are attainable when sampled above certain spatial resolutions (1.6 points ha −1 for CO 2 and 5.6 points ha −1 for N 2 O in our dataset). Especially for N 2 O, lower spatial resolutions were prone to underestimating its field-wide flux. • Collected multi-year/site high spatial resolution row-crop soil GHG flux dataset. • N 2 O spatial variability was greater in conventionally managed maize field. • Inter-annually consistent GHG hotspots were rare in our dataset. • GHG hotspots may change due to spatial heterogeneity of management and measurement. • Field-scale GHG flux was reliably estimated at 1.6 (CO 2 ) and 5.6 (N 2 O) points ha −1 .

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Publication Details

Journal
Agriculture Ecosystems & Environment
Published
2025-03-27
DOI
https://doi.org/10.1016/j.agee.2025.109636
Citations
3
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
3.32
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article

Spatial variability of agricultural soil carbon dioxide and nitrous oxide fluxes: Characterization and recommendations from spatially high-resolution, multi-year dataset

Wendy H. Yang, Nakian Kim, Chunhwa Jang, Evan H. DeLucia et al.
3 citations
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Atmospheric and Environmental Gas Dynamics
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article

Spatial variability of agricultural soil carbon dioxide and nitrous oxide fluxes: Characterization and recommendations from spatially high-resolution, multi-year dataset

Wendy H. Yang, Nakian Kim, Chunhwa Jang, Evan H. DeLucia, DoKyoung Lee, Kaiyu Guan
article en
3 citations

Abstract

Mitigating agricultural soil greenhouse gas (GHG) emissions can contribute to meeting the global climate goals. High spatial and temporal resolution, large-scale, and multi-year data are necessary to characterize and predict spatial patterns of soil GHG fluxes to establish well-informed mitigation strategies, but not many of such datasets are currently available. To address this gap in data we collected two years of in-season soil carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) fluxes at high spatial resolution (7.4 sampling points ha −1 ) from three commercial sites in central Illinois, one conventionally managed continuous corn (2.8 ha in 2021; 5.4 ha in 2022) and two (one site 5.4 ha in 2021 and 2.0 ha in 2022, another site 2.7 ha both years) under conservation practices in corn-soybean rotations. At the field-scale, the spatial variability of CO 2 was comparable across sites, years, and management practices, but N 2 O was on average 77 % more spatially variable in the conventionally managed site. Analysis of N 2 O hotspots revealed that although they represent a similar proportion of the sampling areas across sites (conventional: 12 %; conservation: 13 %), hotspot contribution to field-wide emission was greater in the conventional site than in the conservation sites (conventional: 51 %; conservation: 34 %). Also, the spatial patterns, especially hotspot locations, of both gases were inter-annually inconsistent, with hotspots rarely occurring in the same location. Overall, our result indicated that traditional field-scale monitoring with gas chambers may not be the optimal approach to detect GHG hotspots in row crop systems, due to the unpredictable spatial heterogeneity of management practices. Meanwhile, sensitivity analysis demonstrated that reliable (< 25 % error) field-scale soil GHG flux estimates are attainable when sampled above certain spatial resolutions (1.6 points ha −1 for CO 2 and 5.6 points ha −1 for N 2 O in our dataset). Especially for N 2 O, lower spatial resolutions were prone to underestimating its field-wide flux. • Collected multi-year/site high spatial resolution row-crop soil GHG flux dataset. • N 2 O spatial variability was greater in conventionally managed maize field. • Inter-annually consistent GHG hotspots were rare in our dataset. • GHG hotspots may change due to spatial heterogeneity of management and measurement. • Field-scale GHG flux was reliably estimated at 1.6 (CO 2 ) and 5.6 (N 2 O) points ha −1 .

Agriculture Ecosystems & EnvironmentVol. 387
University of Illinois Urbana-Champaign (US)
Zero hunger
Openalex Percentile: Top 9%
Atmospheric and Environmental Gas Dynamics
3.32
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