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Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland

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Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland. / Barneze, Arlete S.; Abdalla, Mohamed; Whitaker, Jeanette et al.
In: Agronomy, Vol. 12, No. 12, 3055, 02.12.2022.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Barneze, AS, Abdalla, M, Whitaker, J, McNamara, NP, Ostle, NJ & Bellocchi, G (ed.) 2022, 'Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland', Agronomy, vol. 12, no. 12, 3055. https://doi.org/10.3390/agronomy12123055

APA

Barneze, A. S., Abdalla, M., Whitaker, J., McNamara, N. P., Ostle, N. J., & Bellocchi, G. (Ed.) (2022). Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland. Agronomy, 12(12), Article 3055. https://doi.org/10.3390/agronomy12123055

Vancouver

Barneze AS, Abdalla M, Whitaker J, McNamara NP, Ostle NJ, Bellocchi G, (ed.). Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland. Agronomy. 2022 Dec 2;12(12):3055. doi: 10.3390/agronomy12123055

Author

Barneze, Arlete S. ; Abdalla, Mohamed ; Whitaker, Jeanette et al. / Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland. In: Agronomy. 2022 ; Vol. 12, No. 12.

Bibtex

@article{c848dca9859f4469a5119e482abfa152,
title = "Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland",
abstract = "Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.",
keywords = "Article, DNDC model, GHG fluxes, temperate grassland, climate change, management",
author = "Barneze, {Arlete S.} and Mohamed Abdalla and Jeanette Whitaker and McNamara, {Niall P.} and Ostle, {Nicholas J.} and Gianni Bellocchi",
year = "2022",
month = dec,
day = "2",
doi = "10.3390/agronomy12123055",
language = "English",
volume = "12",
journal = "Agronomy",
issn = "2073-4395",
publisher = "MDPI",
number = "12",

}

RIS

TY - JOUR

T1 - Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland

AU - Barneze, Arlete S.

AU - Abdalla, Mohamed

AU - Whitaker, Jeanette

AU - McNamara, Niall P.

AU - Ostle, Nicholas J.

A2 - Bellocchi, Gianni

PY - 2022/12/2

Y1 - 2022/12/2

N2 - Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.

AB - Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.

KW - Article

KW - DNDC model

KW - GHG fluxes

KW - temperate grassland

KW - climate change

KW - management

U2 - 10.3390/agronomy12123055

DO - 10.3390/agronomy12123055

M3 - Journal article

VL - 12

JO - Agronomy

JF - Agronomy

SN - 2073-4395

IS - 12

M1 - 3055

ER -