Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities
Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methano...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Yuanyuan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Nutrient cycling in agroecosystems - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980, 127(2023), 2 vom: 25. Juli, Seite 247-263 |
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| Übergeordnetes Werk: |
volume:127 ; year:2023 ; number:2 ; day:25 ; month:07 ; pages:247-263 |
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| DOI / URN: |
10.1007/s10705-023-10299-5 |
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| 245 | 1 | 0 | |a Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities |
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| 520 | |a Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. | ||
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| 700 | 1 | |a Rong, Anqi |4 aut | |
| 700 | 1 | |a Xia, Xuqin |4 aut | |
| 700 | 1 | |a Sun, Ye |4 aut | |
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10.1007/s10705-023-10299-5 doi (DE-627)SPR053409825 (SPR)s10705-023-10299-5-e DE-627 ger DE-627 rakwb eng Wang, Yuanyuan verfasserin aut Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 Hu, Zhenghua aut He, Shuqi aut Jing, Qiang aut Shen, Lidong aut Liu, Chao aut Wu, Zhurong aut Huang, Wei aut Lu, Guihua aut Cao, Rui aut Zheng, Kezhi aut Dong, Ning aut Jiang, Lu aut Ye, Jiayao aut Rong, Anqi aut Xia, Xuqin aut Sun, Ye aut Enthalten in Nutrient cycling in agroecosystems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980 127(2023), 2 vom: 25. Juli, Seite 247-263 (DE-627)270932712 (DE-600)1478384-8 1573-0867 nnns volume:127 year:2023 number:2 day:25 month:07 pages:247-263 https://dx.doi.org/10.1007/s10705-023-10299-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 127 2023 2 25 07 247-263 |
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10.1007/s10705-023-10299-5 doi (DE-627)SPR053409825 (SPR)s10705-023-10299-5-e DE-627 ger DE-627 rakwb eng Wang, Yuanyuan verfasserin aut Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 Hu, Zhenghua aut He, Shuqi aut Jing, Qiang aut Shen, Lidong aut Liu, Chao aut Wu, Zhurong aut Huang, Wei aut Lu, Guihua aut Cao, Rui aut Zheng, Kezhi aut Dong, Ning aut Jiang, Lu aut Ye, Jiayao aut Rong, Anqi aut Xia, Xuqin aut Sun, Ye aut Enthalten in Nutrient cycling in agroecosystems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980 127(2023), 2 vom: 25. Juli, Seite 247-263 (DE-627)270932712 (DE-600)1478384-8 1573-0867 nnns volume:127 year:2023 number:2 day:25 month:07 pages:247-263 https://dx.doi.org/10.1007/s10705-023-10299-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 127 2023 2 25 07 247-263 |
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10.1007/s10705-023-10299-5 doi (DE-627)SPR053409825 (SPR)s10705-023-10299-5-e DE-627 ger DE-627 rakwb eng Wang, Yuanyuan verfasserin aut Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 Hu, Zhenghua aut He, Shuqi aut Jing, Qiang aut Shen, Lidong aut Liu, Chao aut Wu, Zhurong aut Huang, Wei aut Lu, Guihua aut Cao, Rui aut Zheng, Kezhi aut Dong, Ning aut Jiang, Lu aut Ye, Jiayao aut Rong, Anqi aut Xia, Xuqin aut Sun, Ye aut Enthalten in Nutrient cycling in agroecosystems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980 127(2023), 2 vom: 25. Juli, Seite 247-263 (DE-627)270932712 (DE-600)1478384-8 1573-0867 nnns volume:127 year:2023 number:2 day:25 month:07 pages:247-263 https://dx.doi.org/10.1007/s10705-023-10299-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 127 2023 2 25 07 247-263 |
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10.1007/s10705-023-10299-5 doi (DE-627)SPR053409825 (SPR)s10705-023-10299-5-e DE-627 ger DE-627 rakwb eng Wang, Yuanyuan verfasserin aut Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 Hu, Zhenghua aut He, Shuqi aut Jing, Qiang aut Shen, Lidong aut Liu, Chao aut Wu, Zhurong aut Huang, Wei aut Lu, Guihua aut Cao, Rui aut Zheng, Kezhi aut Dong, Ning aut Jiang, Lu aut Ye, Jiayao aut Rong, Anqi aut Xia, Xuqin aut Sun, Ye aut Enthalten in Nutrient cycling in agroecosystems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980 127(2023), 2 vom: 25. Juli, Seite 247-263 (DE-627)270932712 (DE-600)1478384-8 1573-0867 nnns volume:127 year:2023 number:2 day:25 month:07 pages:247-263 https://dx.doi.org/10.1007/s10705-023-10299-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 127 2023 2 25 07 247-263 |
| allfieldsSound |
10.1007/s10705-023-10299-5 doi (DE-627)SPR053409825 (SPR)s10705-023-10299-5-e DE-627 ger DE-627 rakwb eng Wang, Yuanyuan verfasserin aut Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 Hu, Zhenghua aut He, Shuqi aut Jing, Qiang aut Shen, Lidong aut Liu, Chao aut Wu, Zhurong aut Huang, Wei aut Lu, Guihua aut Cao, Rui aut Zheng, Kezhi aut Dong, Ning aut Jiang, Lu aut Ye, Jiayao aut Rong, Anqi aut Xia, Xuqin aut Sun, Ye aut Enthalten in Nutrient cycling in agroecosystems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1980 127(2023), 2 vom: 25. Juli, Seite 247-263 (DE-627)270932712 (DE-600)1478384-8 1573-0867 nnns volume:127 year:2023 number:2 day:25 month:07 pages:247-263 https://dx.doi.org/10.1007/s10705-023-10299-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 127 2023 2 25 07 247-263 |
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Nutrient cycling in agroecosystems |
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Wang, Yuanyuan @@aut@@ Hu, Zhenghua @@aut@@ He, Shuqi @@aut@@ Jing, Qiang @@aut@@ Shen, Lidong @@aut@@ Liu, Chao @@aut@@ Wu, Zhurong @@aut@@ Huang, Wei @@aut@@ Lu, Guihua @@aut@@ Cao, Rui @@aut@@ Zheng, Kezhi @@aut@@ Dong, Ning @@aut@@ Jiang, Lu @@aut@@ Ye, Jiayao @@aut@@ Rong, Anqi @@aut@@ Xia, Xuqin @@aut@@ Sun, Ye @@aut@@ |
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2023-07-25T00:00:00Z |
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270932712 |
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SPR053409825 |
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englisch |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. 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Wang, Yuanyuan |
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Wang, Yuanyuan misc Climate change misc CH misc flux misc Biomass misc Methane production potential Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities |
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Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities Climate change (dpeaa)DE-He213 CH (dpeaa)DE-He213 flux (dpeaa)DE-He213 Biomass (dpeaa)DE-He213 Methane production potential (dpeaa)DE-He213 |
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Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities |
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Wang, Yuanyuan Hu, Zhenghua He, Shuqi Jing, Qiang Shen, Lidong Liu, Chao Wu, Zhurong Huang, Wei Lu, Guihua Cao, Rui Zheng, Kezhi Dong, Ning Jiang, Lu Ye, Jiayao Rong, Anqi Xia, Xuqin Sun, Ye |
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linear relationship between $ ch_{4} $ fluxes and atmospheric $ co_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities |
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Linear relationship between $ CH_{4} $ fluxes and atmospheric $ CO_{2} $ concentration levels controlled by rice biomass and soil methanogenic communities |
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Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract The contribution of $ CH_{4} $ emissions from paddy soils to greenhouse gas emissions is key in the evaluation of future climate change scenarios. Most studies in this field have investigated the effects of elevated $ CO_{2} $ concentrations (e[$ CO_{2} $]s) on $ CH_{4} $ fluxes and methanogenic communities in paddy soils under constant $ CO_{2} $ concentrations ([$ CO_{2} $]s). However, atmospheric [$ CO_{2} $] is gradually increasing and the relationship between future climate change and $ CH_{4} $ emissions from paddy fields is poorly understood. This study explored the responses of $ CH_{4} $ fluxes and methanogenic communities in paddy soils to different e[$ CO_{2} $]s using open-top chambers. The rice biomass, $ CH_{4} $ fluxes, methane production potential, and methanogenic characteristics were analyzed under CK (ambient [$ CO_{2} $]), $ C_{1} $ (e[$ CO_{2} $] by 120 µmol $ mol^{–1} $), and $ C_{2} $ (e[$ CO_{2} $] by 200 µmol $ mol^{–1} $) treatments. The results indicated that the $ C_{1} $ and $ C_{2} $ treatments insignificantly increased the $ CH_{4} $ flux in paddy fields. However, the $ C_{1} $ treatment significantly increased the $ CH_{4} $ flux/biomass at the elongation stage, while the $ C_{2} $ treatment significantly increased the $ CH_{4} $ flux/biomass at all of the growth stages. The $ C_{1} $ and $ C_{2} $ treatments had a positive effect on both methane production potential and methanogenic abundance at all of the growth stages, but this effect was not always significant. In addition, the $ C_{1} $ and $ C_{2} $ treatments significantly altered the methanogenic community structure at the elongation stage. Notably, there was a significant linear relationship between the $ CH_{4} $ flux/biomass and [$ CO_{2} $] at all of the growth stages; between the methane production potential and [$ CO_{2} $] at the tillering, elongation, and milk-ripening stages; and between the mcrA gene abundance and [$ CO_{2} $] at the milk-ripening stage. A linear model based on rice biomass, methane production potential, and soil DOC concentration explained 72.7% of the variation in the $ CH_{4} $ fluxes. Overall, the linear relationship between $ CH_{4} $ fluxes and atmospheric [$ CO_{2} $] levels was controlled by the rice biomass, soil carbon substrate, and methanogenic communities. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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7.4020653 |