【目的】基于不同复杂度的DNDC和RothC模型,模拟旱地不同秸秆还田量下土壤有机碳(SOC)的动态变化,对比模型结果差异及其成因,为耕地SOC动态模拟的模型选择提供参考。【方法】试验数据(气候、土壤、作物等)来自北京昌平土壤质量国家野外...【目的】基于不同复杂度的DNDC和RothC模型,模拟旱地不同秸秆还田量下土壤有机碳(SOC)的动态变化,对比模型结果差异及其成因,为耕地SOC动态模拟的模型选择提供参考。【方法】试验数据(气候、土壤、作物等)来自北京昌平土壤质量国家野外科学观测研究站长期定位试验,试验始于2008年。包括单施化肥(NPK)、化肥加作物秸秆(NPKS)和化肥加有机肥(NPKM)3个处理。采用DNDC和RothC模型,模拟旱地农田SOC动态变化,应用实测的耕层0—20 cm SOC密度对模型进行校准与验证。基于所验证的模型对比分析不同秸秆还田量(0、2250、4500 kg/hm^(2))情景下的农田SOC动态变化模拟结果。【结果】总体上,两个模型对耕层SOC的模拟均取得了良好的效果,nRMSE均小于20%,nARE绝对值均小于15%,r在0.69至0.91之间,表明这两个模型均适用于该研究区旱地农田SOC动态模拟研究。随着模拟年限的增加,不同秸秆还田量情景下的SOC密度均表现为逐渐增加,但增速逐渐减缓,并且秸秆还田量越多,SOC密度增加越明显。由于两个模型在根系碳输入量计算方式上的不同,其预测的SOC变化幅度有所差异,在预测的第190年,DNDC模型预测结果显示,秸秆不还田、半量还田和全量还田情景下,SOC密度分别比预测的第1年增加了39%、95%和147%。RothC模型的预测结果显示,在相同情景下,SOC密度分别增加了104%、206%和307%。【结论】DNDC与RothC模型在模拟旱地SOC动态方面均表现良好,对不同秸秆还田水平下SOC的变化趋势预测较为一致。RothC模型结构简单、所需输入参数少,适用于SOC快速模拟评估,可在旱地秸秆还田情境下替代DNDC模型用于预测SOC动态。而DNDC模型模拟了复杂的作物生长与土壤生物地球化学循环过程,更适用于综合模拟评估。展开更多
Crop straw incorporation is widely recommended to maintain crop yields and improve soil organic carbon(SOC)stocks as well as soil quality.However,the long-term effects of different straw incorporation practices on the...Crop straw incorporation is widely recommended to maintain crop yields and improve soil organic carbon(SOC)stocks as well as soil quality.However,the long-term effects of different straw incorporation practices on the SOC stock remain uncertain.In this study,a long-term experiment(2007 to 2018)with four treatments(MW_0:maize–wheat rotation with no straw incorporation,MW_(50):maize–wheat rotation with 50%chopped straw incorporation,MW_(b50):maize–wheat rotation with 50%in situ burned harvested straw,and MF_(50):maize–fallow rotation with 50%harvested maize straw incorporation)was set up to evaluate the response of the SOC stock to different straw incorporation methods.The results showed that the SOC stock significantly increased by 32.4,12.2 and 17.4%under the MW_(50),MW_(b50)and MF_(50)treatments,respectively,after continuous straw incorporation over a decade,while the SOC stock under MW0 was significantly reduced by 22.9%after the 11 year long-term experiment.Compared to MW_0,straw incorporation significantly increased organic carbon input,and improved the soil aggregate structure and the ratio of dissolved organic carbon(DOC)to particulate organic carbon(POC),but it did not significantly stimulate soil heterotrophic respiration,resulting in the increased SOC accumulation rate and SOC stocks of bulk soil.The increased ratio of DOC to microbial biomass carbon(MBC)enhanced the relative abundances of Acidobacteria and Proteobacteria but inhibited Bacteroidetes and Chloroflexi,and the bacterial relative abundances were the main reasons for the non-significant increase or even decrease in soil heterotrophic respiration with straw incorporation.The SOC stock would reach an equilibrium based on the results of Rothamsted carbon(RothC)model simulations,with a long-term equilibrium value of 18.85 Mg ha^(–1)under MW_(50).Overall,the results of the long-term field experiment(2007–2018)and RothC model simulation suggested that maize–wheat rotation with 50%chopped straw incorporation delivered the largest benefits for the SOC stock in calcareous soils of subtropical mountain landscapes over the long term.展开更多
Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate c...Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.展开更多
Land use change can have a strong impact on soil carbon dynamics and carbon stocks in urban areas. Due to rapid urbanization, large areas of land have been paved, and other areas have undergone rapid land use change. ...Land use change can have a strong impact on soil carbon dynamics and carbon stocks in urban areas. Due to rapid urbanization, large areas of land have been paved, and other areas have undergone rapid land use change. Evaluation of the impact of urbanization on carbon dynamics and carbon stock （30 cm） has become an issue of urgent concern. The soil carbon dynamics, due to rapid land use change in Tianjin Binhai New Area of China, have been simulated in this paper using the RothC model. Because this area is saline, a modified version of RothC that includes a salt rate modifier provided more accurate simulations than the original model. The conversion to urban green land was not accurately simulated by either of the models because of the undefined changes in soil and plant conditions. According to the model, changes of arable to grassland resulted in a decline in soil carbon stocks, and changes of grassland to forest and grassland to arable resulted in increased soil carbon stocks in this area. Across the whole area simulated, the total carbon stocks in 2010 had decreased due to land use change by 6.5% from the 1979 value. By 2050, a further decrease of 21.9% is expected according to the 2050 plan for land use and the continuing losses from the soils due to previous land use changes.展开更多
文摘【目的】基于不同复杂度的DNDC和RothC模型,模拟旱地不同秸秆还田量下土壤有机碳(SOC)的动态变化,对比模型结果差异及其成因,为耕地SOC动态模拟的模型选择提供参考。【方法】试验数据(气候、土壤、作物等)来自北京昌平土壤质量国家野外科学观测研究站长期定位试验,试验始于2008年。包括单施化肥(NPK)、化肥加作物秸秆(NPKS)和化肥加有机肥(NPKM)3个处理。采用DNDC和RothC模型,模拟旱地农田SOC动态变化,应用实测的耕层0—20 cm SOC密度对模型进行校准与验证。基于所验证的模型对比分析不同秸秆还田量(0、2250、4500 kg/hm^(2))情景下的农田SOC动态变化模拟结果。【结果】总体上,两个模型对耕层SOC的模拟均取得了良好的效果,nRMSE均小于20%,nARE绝对值均小于15%,r在0.69至0.91之间,表明这两个模型均适用于该研究区旱地农田SOC动态模拟研究。随着模拟年限的增加,不同秸秆还田量情景下的SOC密度均表现为逐渐增加,但增速逐渐减缓,并且秸秆还田量越多,SOC密度增加越明显。由于两个模型在根系碳输入量计算方式上的不同,其预测的SOC变化幅度有所差异,在预测的第190年,DNDC模型预测结果显示,秸秆不还田、半量还田和全量还田情景下,SOC密度分别比预测的第1年增加了39%、95%和147%。RothC模型的预测结果显示,在相同情景下,SOC密度分别增加了104%、206%和307%。【结论】DNDC与RothC模型在模拟旱地SOC动态方面均表现良好,对不同秸秆还田水平下SOC的变化趋势预测较为一致。RothC模型结构简单、所需输入参数少,适用于SOC快速模拟评估,可在旱地秸秆还田情境下替代DNDC模型用于预测SOC动态。而DNDC模型模拟了复杂的作物生长与土壤生物地球化学循环过程,更适用于综合模拟评估。
基金financially supported by the National Key Research and Development Program of China(2023YFD1901200)the National Natural Science Foundation of China(U22A20562)+4 种基金the Sichuan Science and Technology Program,China(2022YFS0500)the Project of Special Research Assistant of the Chinese Academy of Sciences(Jing Zheng)the China Postdoctoral Science Foundation(2022M723079)the Sichuan Provincial Postdoctoral Research Foundation,China(TB2022042)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(IMHEZYTS-08)。
文摘Crop straw incorporation is widely recommended to maintain crop yields and improve soil organic carbon(SOC)stocks as well as soil quality.However,the long-term effects of different straw incorporation practices on the SOC stock remain uncertain.In this study,a long-term experiment(2007 to 2018)with four treatments(MW_0:maize–wheat rotation with no straw incorporation,MW_(50):maize–wheat rotation with 50%chopped straw incorporation,MW_(b50):maize–wheat rotation with 50%in situ burned harvested straw,and MF_(50):maize–fallow rotation with 50%harvested maize straw incorporation)was set up to evaluate the response of the SOC stock to different straw incorporation methods.The results showed that the SOC stock significantly increased by 32.4,12.2 and 17.4%under the MW_(50),MW_(b50)and MF_(50)treatments,respectively,after continuous straw incorporation over a decade,while the SOC stock under MW0 was significantly reduced by 22.9%after the 11 year long-term experiment.Compared to MW_0,straw incorporation significantly increased organic carbon input,and improved the soil aggregate structure and the ratio of dissolved organic carbon(DOC)to particulate organic carbon(POC),but it did not significantly stimulate soil heterotrophic respiration,resulting in the increased SOC accumulation rate and SOC stocks of bulk soil.The increased ratio of DOC to microbial biomass carbon(MBC)enhanced the relative abundances of Acidobacteria and Proteobacteria but inhibited Bacteroidetes and Chloroflexi,and the bacterial relative abundances were the main reasons for the non-significant increase or even decrease in soil heterotrophic respiration with straw incorporation.The SOC stock would reach an equilibrium based on the results of Rothamsted carbon(RothC)model simulations,with a long-term equilibrium value of 18.85 Mg ha^(–1)under MW_(50).Overall,the results of the long-term field experiment(2007–2018)and RothC model simulation suggested that maize–wheat rotation with 50%chopped straw incorporation delivered the largest benefits for the SOC stock in calcareous soils of subtropical mountain landscapes over the long term.
基金Supported by the Soil Scientific Interest Group (GIS Sol) of Francefinanced by the "Groupement d'Intrêt Scientifique Sol". Jeroen Meersmans' postdoctoral position was funded by the French Environment and Energy Management Agency (ADEME)funded by the EU projects "Greenhouse gas management in European land use systems (GHG-Europe)" (FP7-ENV-2009-1-244122) and "CARBO-Extreme" (FP7-ENV-2008-1-226701)
文摘Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.
文摘Land use change can have a strong impact on soil carbon dynamics and carbon stocks in urban areas. Due to rapid urbanization, large areas of land have been paved, and other areas have undergone rapid land use change. Evaluation of the impact of urbanization on carbon dynamics and carbon stock （30 cm） has become an issue of urgent concern. The soil carbon dynamics, due to rapid land use change in Tianjin Binhai New Area of China, have been simulated in this paper using the RothC model. Because this area is saline, a modified version of RothC that includes a salt rate modifier provided more accurate simulations than the original model. The conversion to urban green land was not accurately simulated by either of the models because of the undefined changes in soil and plant conditions. According to the model, changes of arable to grassland resulted in a decline in soil carbon stocks, and changes of grassland to forest and grassland to arable resulted in increased soil carbon stocks in this area. Across the whole area simulated, the total carbon stocks in 2010 had decreased due to land use change by 6.5% from the 1979 value. By 2050, a further decrease of 21.9% is expected according to the 2050 plan for land use and the continuing losses from the soils due to previous land use changes.
