FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3142480483> ?p ?o ?g. }

• W3142480483 endingPage "1819" @default.
• W3142480483 startingPage "1811" @default.
• W3142480483 abstract "PDF HTML阅读 XML下载 导出引用 引用提醒 稻田温室气体排放与土壤微生物菌群的多元回归分析 DOI: 10.5846/stxb201102260224 作者: 作者单位: 中国农业科学院农业环境与可持续发展研究所,中国农业科学院农业环境与可持续发展研究所,中国科学院大气物理研究所,中国农业科学院农业环境与可持续发展研究所,湖南省土壤肥料研究所,湖南省土壤肥料研究所,Semiarid Prairie Agricultural Research Centre,AAFC,Swift current,Saskatchewan,SH X,中国农业科学院农业环境与可持续发展研究所,中国科学院亚热带农业生态研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 2011年公益性行业(农业)科研专项经费资助(201103039);国家973计划课题(2012CB417106) Multivariate regression analysis of greenhouse gas emissions associated with activities and populations of soil microbes in a double-rice paddy soil Author: Affiliation: Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences,Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences,Institue of Atmospheric Physics, Chinese Academy of Sciences,Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences,Soils and Fertilizer Institute of Hunan Province,Soils and Fertilizer Institute of Hunan Province,,Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences,Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan 410125, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为揭示多种田间管理措施综合影响下双季稻田温室气体平均排放通量与土壤微生物菌群的多元回归关系,利用静态箱-气相色谱法和稀释培养计数法进行了温室气体排放通量和土壤产气微生物菌群数量的连续观测。2a研究结果显示,稻田甲烷排放通量与土壤微生物总活性和产甲烷菌数量关系密切,甲烷排放通量与二者的关系可分别由指数和二次多项式模型拟合。一元回归分析表明,仅产甲烷菌数量就能单独解释96.9%的稻田甲烷排放通量变异(R2=0.969,P<0.001),但考虑两种因素的二元回归拟合优度高于一元回归(R2=0.975,P<0.001)。氧化亚氮排放通量与土壤硝化细菌和反硝化细菌数量也密切相关(P <0.05),氧化亚氮排放通量与二者的二元非线性混合回归模型可以解释至少70.4%的稻田氧化亚氮排放通量(R2≥0.704, P <0.001),其拟合优度也高于一元回归。稻田温室气体排放通量受多种影响因素控制,土壤产气微生物活性和数量是多种因素影响的直接响应,因此二者与温室气体排放存在显著相关,基于田间试验的多元非线性回归分析客观的揭示了温室气体排放通量与环境因子的相关关系。 Abstract:To investigate the regression relationships between greenhouse gas (GHG) emissions and soil microbes in a double-rice paddy soil under various management practices, a two-year study was conducted to observe the seasonal variation of GHG emissions and activities of soil microbes (SMA ) as well as their populations (SMP) using the closed static chamber-GC (gas chromatography) and the most probable number methods. There were seven management practices (or treatments), including CWS (Conventional Tillage + Without Straw Residues + Urea), NWS (No Tillage + Without Straw Residues + Urea), SCU (Conventional Tillage + Without Straw Residues + Controlled-Release Urea), HN (High Stubbles + No Tillage + Urea), HC (High Stubbles + Conventional Tillage + Urea), SN (Straw Cover + No Tillage + Urea) and SNF (Straw Cover + No Tillage + Urea + Continuous Flooding). The average values of seven treatments' daily fluxes of GHGs and SMA as well SMP were used for the analysis in this study. Regression analysis was conducted using the R statistical software. Similar seasonal variations of methane flux and SMA as well as the amount of soil methanogens (MET) were found in the rice growing season of 2008-2009; and same regularity occurred in the temporal distribution of nitrous oxide flux and the amount of soil nitrifiers and denitrifiers. Furthermore, there was a strong correlation between methane flux and SMA as well as the population of MET. The relationships of methane flux vs. SMA and methane flux vs. MET can be represented by using the exponential and quadratic polynomial models, respectively. Simple regression indexed that the quantity of MET could explain individually at least 96.96% of variance of methane flux (R2=0.969, P<0.001), but the fitting precision of multiple nonlinear regression of methane flux with two factors of SMA and MET (R2=0.975, P<0.001) was higher than the univariate regression analysis. Besides, the pronounced positive dependency of nitrous oxide flux with soil nitrifiers and denitrifiers has also been found (P<0.05). The mixed binary nonlinear regression of nitrous oxide flux with the SMP of the two types of microbes can explain at least 70.4% of variance of nitrous oxide flux (R2≥0.704, P<0.001), and of course the fitting precision of multiple nonlinear regression was higher than the simple regression using the SMP of either nitrifiers or denitrifiers. However, as we know, GHG emissions from paddy soils are affected by many factors, of which SMA and SMP are the most direct influential variants. In order to reasonably reveal the interactions between GHG emissions and environmental variables, the multivariate nonlinear regression analysis should be carried out based on data derived from the extensive field experiments rather than few laboratory trials. 参考文献 相似文献 引证文献" @default.
• W3142480483 created "2021-04-13" @default.
• W3142480483 creator A5007634030 @default.
• W3142480483 creator A5014895826 @default.
• W3142480483 creator A5022932039 @default.
• W3142480483 creator A5061648145 @default.
• W3142480483 creator A5061836563 @default.
• W3142480483 creator A5069270310 @default.
• W3142480483 creator A5080510186 @default.
• W3142480483 creator A5081900477 @default.
• W3142480483 creator A5084860744 @default.
• W3142480483 date "2012-01-01" @default.
• W3142480483 modified "2023-10-17" @default.
• W3142480483 title "Multivariate regression analysis of greenhouse gas emissions associated with activities and populations of soil microbes in a double-rice paddy soil" @default.
• W3142480483 doi "https://doi.org/10.5846/stxb201102260224" @default.
• W3142480483 hasPublicationYear "2012" @default.
• W3142480483 type Work @default.
• W3142480483 sameAs 3142480483 @default.
• W3142480483 citedByCount "0" @default.
• W3142480483 crossrefType "journal-article" @default.
• W3142480483 hasAuthorship W3142480483A5007634030 @default.
• W3142480483 hasAuthorship W3142480483A5014895826 @default.
• W3142480483 hasAuthorship W3142480483A5022932039 @default.
• W3142480483 hasAuthorship W3142480483A5061648145 @default.
• W3142480483 hasAuthorship W3142480483A5061836563 @default.
• W3142480483 hasAuthorship W3142480483A5069270310 @default.
• W3142480483 hasAuthorship W3142480483A5080510186 @default.
• W3142480483 hasAuthorship W3142480483A5081900477 @default.
• W3142480483 hasAuthorship W3142480483A5084860744 @default.
• W3142480483 hasConcept C118518473 @default.
• W3142480483 hasConcept C14168384 @default.
• W3142480483 hasConcept C142724271 @default.
• W3142480483 hasConcept C16397148 @default.
• W3142480483 hasConcept C166957645 @default.
• W3142480483 hasConcept C178963451 @default.
• W3142480483 hasConcept C18903297 @default.
• W3142480483 hasConcept C191935318 @default.
• W3142480483 hasConcept C205649164 @default.
• W3142480483 hasConcept C2780560099 @default.
• W3142480483 hasConcept C2984488660 @default.
• W3142480483 hasConcept C39432304 @default.
• W3142480483 hasConcept C47737302 @default.
• W3142480483 hasConcept C54286561 @default.
• W3142480483 hasConcept C54924851 @default.
• W3142480483 hasConcept C6557445 @default.
• W3142480483 hasConcept C71924100 @default.
• W3142480483 hasConcept C86803240 @default.
• W3142480483 hasConceptScore W3142480483C118518473 @default.
• W3142480483 hasConceptScore W3142480483C14168384 @default.
• W3142480483 hasConceptScore W3142480483C142724271 @default.
• W3142480483 hasConceptScore W3142480483C16397148 @default.
• W3142480483 hasConceptScore W3142480483C166957645 @default.
• W3142480483 hasConceptScore W3142480483C178963451 @default.
• W3142480483 hasConceptScore W3142480483C18903297 @default.
• W3142480483 hasConceptScore W3142480483C191935318 @default.
• W3142480483 hasConceptScore W3142480483C205649164 @default.
• W3142480483 hasConceptScore W3142480483C2780560099 @default.
• W3142480483 hasConceptScore W3142480483C2984488660 @default.
• W3142480483 hasConceptScore W3142480483C39432304 @default.
• W3142480483 hasConceptScore W3142480483C47737302 @default.
• W3142480483 hasConceptScore W3142480483C54286561 @default.
• W3142480483 hasConceptScore W3142480483C54924851 @default.
• W3142480483 hasConceptScore W3142480483C6557445 @default.
• W3142480483 hasConceptScore W3142480483C71924100 @default.
• W3142480483 hasConceptScore W3142480483C86803240 @default.
• W3142480483 hasIssue "6" @default.
• W3142480483 hasLocation W31424804831 @default.
• W3142480483 hasOpenAccess W3142480483 @default.
• W3142480483 hasPrimaryLocation W31424804831 @default.
• W3142480483 hasRelatedWork W175460536 @default.
• W3142480483 hasRelatedWork W1852119094 @default.
• W3142480483 hasRelatedWork W1969707431 @default.
• W3142480483 hasRelatedWork W2009269323 @default.
• W3142480483 hasRelatedWork W2036553097 @default.
• W3142480483 hasRelatedWork W2145738095 @default.
• W3142480483 hasRelatedWork W2573867712 @default.
• W3142480483 hasRelatedWork W2999066202 @default.
• W3142480483 hasRelatedWork W3131688536 @default.
• W3142480483 hasRelatedWork W3196632638 @default.
• W3142480483 hasVolume "32" @default.
• W3142480483 isParatext "false" @default.
• W3142480483 isRetracted "false" @default.
• W3142480483 magId "3142480483" @default.
• W3142480483 workType "article" @default.