稻田甲烷排放模型研究——模型灵敏度分析

模型方法对区域稻田甲烷排放估计的不确定性主要源于模型参数在区域范围内的误差,这种误差导致的估计不确定性由模型灵敏度决定.采用一种动力学分析与统计分析相结合的方法对稻田甲烷模型CH4MOD进行了参数灵敏度分析,结果表明,稻田水管理方式的灵敏度最高,灵敏度指数为O.64,其次为稻田土壤的砂粒含量参数,灵敏度指数0.50,灵敏度最低的参数是水稻移栽期地上生物量.以模型灵敏度指数为基础,建立了模型估计值不确定性与模型参数区域化误差间的数量关系,利用这一量化关系得出我国2000年稻田甲烷排放的不确定性范围为3.09～10.61Tg.此外,模型灵敏度参数的大小也反映了模型要素对稻田甲烷排放影响的大小,因而分析的结果对于采取合理措施减少稻田甲烷排放具有指导意义.     

基于模型和GIS技术的中国稻田甲烷排放估计

将一个比较成熟的稻田甲烷排放模型CH4MOD和GIS空间化数据库结合,模拟估计了中国大陆2000年水稻生长季稻田甲烷的排放。模型的空间输入参数包括:逐日气温、耕层土壤砂粒含量、外源有机质施用量、稻田水分管理模式、水稻移栽期与收获期、水稻种植面积与单产,空间分辨率为10km×10km。模拟结果表明:2000年稻田甲烷排放量为6.02Tg,其中:早稻生长季排放1.63Tg、晚稻1.46Tg、单季稻2.93Tg。提高区域稻田甲烷排放估计精度的进一步目标应放在减小输入参数误差和提高空间数据精度上,在现有数据库基础和模型———GIS技术下探讨我国稻田甲烷排放估计的不确定性范围是必要的。     

稻田甲烷排放模型研究——模型的验证

模型的有效性检验是模型应用于估计区域尺度稻田甲烷排放量的基本前提 ,尤其是针对多种不同的土壤、气候以及农业管理方式等可能影响稻田甲烷排放的环境条件下的模型检验。利用覆盖全国主要水稻产区的 94个甲烷排放观测案例对稻田甲烷排放模型 (CH4 MOD)进行了验证。这些观测区域分布范围北至北京 (4 0°30′N,116°2 5′E) ,南至广州 (2 3°0 8′N,113°2 0′E) ,东起杭州 (30°19′N,12 0°12′E) ,西到四川的土主 (2 9°4 0′N,10 3°5 0′E)。既有双季稻 ,也有单季稻 ,稻田灌溉及施肥方式也多种多样 ,对我国水稻生产具有较广泛的代表性。观测获得的稻田甲烷排放季节总量从 3.1kg C/hm2到 76 1.7kg C/hm2 ,平均值为199.4 (± 187.3) kg C/hm2 ;相应的模拟值分别为 13.9、82 4 .3和 2 2 4 .6 (± 187.0 ) kg C/hm2。模拟值与实测值的线性相关系数(r2 )为 0 .84 (n=94 ,p<0 .0 0 1)。CH4 MOD模型能够通过较少的输入参数有效地模拟我国主要农作方式下的稻田甲烷排放     

东北黑土地区稻田甲烷排放时空演变及排放潜力分析

稻田甲烷排放是农业源甲烷排放的主要来源。东北黑土地区是我国最大的粮食生产基地,农业温室气体减排是实现黑土地永续利用的关键议题之一。运用稻田甲烷排放模型(CH4MOD)核算并分析了2009-2018年东北黑土地区稻田甲烷排放的时空演变特征,结合GOSAT卫星遥感数据探究了水稻生产与区域甲烷排放的时空动态联系,进一步量化了稻田甲烷对区域甲烷排放的贡献程度及不同情景下的排放潜力。结果表明,受水稻生产面积扩张和排放强度提高的影响,东北黑土地区稻田甲烷排放总量从2009年的39.05万t增加到2018年的79.53万t。东北黑土地区区域甲烷排放在季节变化和栅格单元上表现出与稻田甲烷排放较为一致的时空动态,大规模的稻田耕作可能会增加水稻生产与区域甲烷排放直接相关的可能性。随着水稻持续扩种稳产,2018年东北黑土地区水稻生产贡献了区域甲烷排放总量的15.04%,其中黑龙江省的贡献率高达31.06%。在基准发展情景下,预计2035年东北黑土地区稻田CH₄排放量较2018年增加19.5%;在粮食供给保障情景下,维持当前稻田耕作面积,水稻生产集约化程度提高,预计其稻田CH₄排放量较2018年减少0.88%;在此基础上,采取促进秸秆还田、增施有机肥、实施节水间歇灌溉等稻田管理措施将使稻田CH₄排放量增加17.8%-63.6%。以满足膳食需求和供给保障为导向,优化水稻种植结构、控制稻田耕作面积,推动技术进步、品种改良以提升单产水平,采取化肥和有机肥搭配施用、节水间歇灌溉等途径能够缓解稻田甲烷排放。研究综合运用自上而下的遥感数据和自下而上的模型运算,刻画了水稻生产与区域甲烷排放的时空联系,进一步评估了稻田甲烷的排放潜力及减排措施的减排效果,为促进东北黑土地区农业甲烷减排和生产布局优化提供了理论依据和决策参考。     

基于主成分分析水稻植株CH4排放估算模型

估算稻田甲烷（CH4）排放量是开展稻田甲烷排放研究的重要内容之一．通过观测南方红黄壤稻田不同水稻品种甲烷排放通量,测定了16个早稻、20个晚稻品种的植株节间组织的数量特征．选取株高、茎秆长度、茎秆维管束面积／茎壁横切面积、茎壁横切面积／节间横切面积、叶鞘横切面积／节间横切面积、气腔面积／茎壁横切面积、维管束总面积／茎壁横切面积等相关因子进行了主成分分析,建立基于水稻植株的CHa排放估算模型,早、晚稻估算模型相关系数分别为0．827、0．853．同时构造了综合评价函数,得出了水稻品种CH4排放综合分值,与实测结果相比较,吻合度较高．利用估算模型进行模拟,比较模拟值与实测值,相对误差较小,证明模型具有有效性和可行性,为估算水稻CH4排放提供参考依据,为评价水稻品种CH4排放高低提供经验参考．     

奎屯河流域春季融雪期SCS-CN模型参数取值方法

水资源是保障我国西北干旱半干旱地区生态环境安全的关键因素。以新疆奎屯河流域为例,通过修正SCS模型土壤持水量及初损率参数计算方法,寻找适用于干旱半干旱地区山区典型流域春季融雪期径流模拟模型,为流域掌握水资源量及生态用水提供决策依据。与以往研究不同之处在于:首先,引入度-日模型修正降水量参数,以满足流域降雨-融雪混合补给径流特征。其次,利用多期MODIS数据驱动的TS/VI特征空间理论结合土壤水分吸收平衡原理计算土壤持水量参数(S);再运用聚类分析法对初损率(λ)取值方法进行改进。通过参数算法改进后的SCS模型,参数率定期和验证期纳什效率系数和相对误差系数分别为0.92和0.64,0.7%和-1.5%。结果表明:1)参数算法改进后SCS模型能实现奎屯河流域春季融雪期日径流模拟。2)利用遥感大尺度地表信息参数化技术反演SCS模型参数,实现了遥感数据为SCS模型提供大尺度空间数据的同时,间接实现了模型参数由点状数据向面状数据转化的可能;3)初损率(λ)多组取值法可有效提高干旱半干旱地区大尺度流域径流模拟精度。     

基于DNDC模型的稻田温室气体排放通量模拟

理解土地利用方式转变过程影响生态系统生物地球化学循环及温室气体排放的机理,并利用模型模拟土地利用方式转变过程对温室气体通量的影响是一项长期、艰巨的科学任务。本研究基于国际上广泛应用的生物地球化学过程模型(DNDC模型),结合气象、土壤和管理措施等数据,模拟了旱田转水田土地利用方式转变后稻田CH_4、CO_2和N_2O三种温室气体的通量和常年种植水稻的稻田温室气体通量,并将模拟值与观测值进行比较。结果表明:DNDC模型能够较好地模拟新、老稻田温室气体通量的季节变化,但对老稻田温室气体的排放通量模拟效果(R~20. 89,n=40,P0. 01)优于新转稻田(R~20.79,n=265,P0.01),且对CH_4和CO_2的模拟效果优于对N_2O的模拟效果;根据田间观测数据,改变模型模拟土地利用方式转换前后土壤SOC浓度和p H值,并不能完全模拟土地利用变化对温室气体的影响,微生物群落在土地利用方式转变过程中可能发生较大变化,需要在模型中进一步体现。通过模型模拟土地利用方式改变对温室气体排放的影响,可为国家温室气体、碳排放清单的编制及管理政策的制定提供参考依据。     

稻田秸秆还田:土壤固碳与甲烷增排

基于我国农田土壤有机质长期定位试验和稻田甲烷排放试验成果,将全国稻田划分为单季区和双季区.根据土壤有机质试验数据,分析了秸秆还田在我国两个稻田区的单季稻田、水旱轮作稻田和双季稻田的固碳潜力.同时根据我国稻田甲烷排放试验数据,采用取平均排放系数的方法,估算了我国稻田在无秸秆还田情况下的甲烷排放总量;结合IPCC推荐的方法和参数,估算了我国稻田秸秆还田后甲烷排放总量及增排甲烷的全球增温潜势.结果表明:在中国稻田推广秸秆还田的固碳潜力为10.48TgC.a-1,对减缓全球变暖的贡献为38.43TgCO2-eqv.a-1;但秸秆还田后稻田甲烷排放将从无秸秆还田的5.796Tg.a-1增加到9.114Tg.a-1;秸秆还田引起甲烷增排3.318Tg.a-1,其全球增温潜势达82.95TgCO2-eqv.a-1,为土壤固碳减排潜力的2.158倍.可见,推广秸秆还田后,中国稻田增排甲烷的温室效应会大幅抵消土壤固碳的减排效益,是一项重要的温室气体泄漏.     

中国陆地自然植物有氧甲烷排放空间分布模拟及其气候效应

区域尺度陆地植物有氧条件下排放甲烷及其气候效应研究不仅对甲烷收支平衡研究具有重要意义,对于全球变化研究也具有重要推动作用。通过改进Keppler提出的公式,模拟了中国区域植物有氧甲烷排放的时空分布。利用IBIS模拟的NPP数据结合相关文献统计生物量与NPP的比值,计算得到中国区域自然植物叶片生物量,以及叶片甲烷排放。结果显示,2001年至2012年中国植物生物量与植物叶片甲烷排放量在Sres A2和Sres B1两种情景下差异不明显;但是气候变化模式差异的影响会随着时间的推移而扩大。在Sres A2情景下,中国地区年均植物生物量为10803.22Tg C,叶片生物量为1156.15Tg C。如果不考虑天气对光照的影响,植物叶片甲烷排放年均2.69Tg,约是全国年甲烷排放总量7.01%,是中国稻田甲烷排放总量的29.05%。在各植被类型中,草地叶片甲烷排放量最高,达到47.53%,其次是混交林。森林(针叶林、阔叶林、混交林)是主要的植物甲烷排放源,占中国区域植物甲烷排放总量的51.28%,其次是草地,占47.47%。中国区域植物叶片甲烷排放南高北低,东高西低的分布状态主要由地表植被覆盖类型决定,光照和温度也是重要影响因素。对Sres A2和Sres B1两种气候情景下中国植物甲烷排放预测分析,中国区域植物甲烷排放不断增加,在Sres A2情景下不同时期的平均增长率为9.73%,高于Sres B1情景的5.17%,且两种情景下的增长率都在降低。21世纪Sres A2和Sres B1变化情景下,年均植物排放的甲烷CO_2当量分别为83.18Tg和77.34Tg,约占中国年均CO_2排放总量的1.39%和1.29%。     

微生物生物量C、土壤呼吸的季节性变化与黑土稻田甲烷排放

对黑土水稻田一个生长季中土壤微生物生物量C、土壤呼吸和甲烷排放通量进行了监测。结果表明,在水稻生长初期,长效尿素能显著抑制微生物生物量C和土壤呼吸(P<0．05),间歇灌溉措施对二者几乎没有影响,间歇灌溉能减少稻田甲烷的排放,平均排放量比对照减少了32．5％,长效尿素的施用稻田使甲烷的排放略有增加,施用长效尿素的处理,微生物生物量C与甲烷排放量之间呈显著正相关关系。     

A semi-empirical model of methane emission from flooded rice paddy soils

Reliable regional or global estimates of methane emissions from flooded rice paddy soils depend on an examination of methodologies by which the current high variability in the estimates might be reduced. One potential way to do this is the development of predictive models. With an understanding of the processes of methane production, oxidation and emission, a semi-empirical model, focused on the contributions of rice plants to the processes and also the influence of environmental factors, was developed to predict methane emission from flooded rice fields. A simplified version of the model was also derived to predict methane emission in a more practical manner. In this study, it was hypothesized that methanogenic substrates are primarily derived from rice plants and added organic matter. Rates of methane production in flooded rice soils are determined by the availability of methanogenic substrates and the influence of environmental factors. Rice growth and development control the fraction of methane emitted. The amount of methane transported from the soil to the atmosphere is determined by the rates of production and the emitted fraction. Model validation against observations from single rice growing seasons in Texas, USA demonstrated that the seasonal variation of methane emission is regulated by rice growth and development. A further validation of the model against measurements from irrigated rice paddy soils in various regions of the world, including Italy, China, Indonesia, Philippines and the United States, suggests that methane emission can be predicted from rice net productivity, cultivar character, soil texture and temperature, and organic matter amendments.     

Estimates of methane emissions from Chinese rice paddies by linking a model to GIS database

Methane is one of the principal greenhouse gases. Irrigated rice paddies are recognized as contributing to atmospheric methane concentration. Methane emissions from rice paddies are among the most uncertain estimates in rice-growing countries. Efforts have been made over the last decade to estimate CH₄ emissions from Chinese rice paddies via the model method. However, these estimates are very vague due to different models and upscaling methods. A reduction in these uncertainties may be achieved by coupling field-scale models with regional databases. The objective of this article is to develop a methodology of coupling a CH₄ emission model with regional databases by which CH₄ emissions from Chinese rice paddies can then be estimated. CH4MOD, a model for simulating CH₄ emissions from rice paddies with minimal input by using commonly available parameters, is of great potential in terms of upscaling as it has provided a realistic estimate of the observed results from various soils, climates and agricultural practices. By linking spatial databases to CH4MOD, CH₄ emissions from Chinese rice paddies in the 2000 rice-growing season were simulated on a day-by-day basis. The spatial databases were created by GIS with a spatial resolution of 10km10km, including soil sand percentage, amounts of crop straw and roots from the previous season and farm manure, the water management pattern, dates of rice transplanting and harvesting, acreage of rice planted, rice grain yield and daily air temperature. ARCGIS software was used to meet all GIS needs, including data access, projection definition, overlaying of different vector layers, creation of grids (a raster format of ARCGIS software) by converting vector data, and the data conversion between grids and ASCII formats. Methane emissions from rice paddies in mainland China in the 2000 rice-growing season were estimated to be 6.02 Tg (1 Tg = 10⁹ kg). Of the total, approximately 49% (2.93Tg) is emitted during the single rice-growing season, and 27% (1.63Tg) and 24% (1.46Tg) are from the early and late rice-growing seasons respectively. It was concluded that regional CH4 emissions from rice paddies could be estimated by coupling CH4MOD with regional databases with a high spatial resolution. A further effort should be made to improve the quality of the spatial databases, especially in terms of the amount of added organic matter and the water regime. It is also necessary to evaluate the uncertainties of the present estimates in order to improve the overall accuracy.     

Estimates of methane emissions from Chinese rice paddies by linking a model to GIS database

Methane is one of the principal greenhouse gases. Irrigated rice paddies are recognized as contributing to atmospheric methane concentration. Methane emissions from rice paddies are among the most uncertain estimates in rice-growing countries. Efforts have been made over the last decade to estimate CH₄ emissions from Chinese rice paddies via the model method. However, these estimates are very vague due to different models and upscaling methods. A reduction in these uncertainties may be achieved by coupling field-scale models with regional databases. The objective of this article is to develop a methodology of coupling a CH₄ emission model with regional databases by which CH₄ emissions from Chinese rice paddies can then be estimated. CH4MOD, a model for simulating CH₄ emissions from rice paddies with minimal input by using commonly available parameters, is of great potential in terms of upscaling as it has provided a realistic estimate of the observed results from various soils, climates and agricultural practices. By linking spatial databases to CH4MOD, CH₄ emissions from Chinese rice paddies in the 2000 rice-growing season were simulated on a day-by-day basis. The spatial databases were created by GIS with a spatial resolution of 10km×10km, including soil sand percentage, amounts of crop straw and roots from the previous season and farm manure, the water management pattern, dates of rice transplanting and harvesting, acreage of rice planted, rice grain yield and daily air temperature. ARCGIS software was used to meet all GIS needs, including data access, projection definition, overlaying of different vector layers, creation of grids (a raster format of ARCGIS software) by converting vector data, and the data conversion between grids and ASCII formats. Methane emissions from rice paddies in mainland China in the 2000 rice-growing season were estimated to be 6.02 Tg (1 Tg = 10⁹ kg). Of the total, approximately 49% (2.93Tg) is emitted during the single rice-growing season, and 27% (1.63Tg) and 24% (1.46Tg) are from the early and late rice-growing seasons respectively. It was concluded that regional CH4 emissions from rice paddies could be estimated by coupling CH4MOD with regional databases with a high spatial resolution. A further effort should be made to improve the quality of the spatial databases, especially in terms of the amount of added organic matter and the water regime. It is also necessary to evaluate the uncertainties of the present estimates in order to improve the overall accuracy.     

Model estimates of methane emission from irrigated rice cultivation of China

A model developed by the authors ( Huang et al. 1998 ) was further validated against field measurements from various regions of the world and calibrated to estimate methane emission from irrigated rice cultivation of China. On the basis of available information on rice cultivated area, growth duration, grain yield, soil texture and temperature, methane emission from Chinese rice paddies was estimated for 28 rice cultivated provinces in mainland. The calculated daily methane emission rates, on a provincial scale, ranged from 0.15 to 0.86 g m^–2 with an average of 0.32 g m^–2. Five of the top six locations with higher daily methane emissions are located at a latitude between 28° and 31° N. A total amount of 9.66 Tg (1 Tg = 10¹² g) CH₄ per year, ranging from 7.19 to 13.62, was estimated to be released from Chinese rice paddy soils. Of the total, 45% is emitted from the single-rice growing season, and 19% and 36% are from the early-rice and the late-rice growing seasons, respectively. Approximately 70% of the total is emitted in the region located at latitude between 25° and 32° N. The emissions from rice fields in Sichuan and Hunan Province were calculated to be 2.85 Tg y^–1, accounting for ≈ 30% of the total. Comparisons of the estimated and the observed emission rates show that the estimates were, in general, close to the measurements at most locations.     

Effect of ducks on CH4 emission from paddy soils and its mechanism research in the rice-duck ecosystem

The effect of ducks on CH₄ emission from paddy soils and its mechanism were probed in order to decide the optimum number of ducks in the rice-duck ecosystem. Methane emission fluxes from paddy soils were measured by the static box technique. The correlations between methane emission and soil physical and chemical characteristics were also analyzed. The results showed that significant differences (p < 0.01) existed in the dissolved oxygen content of water body in the treatment fields, and the more the ducks, the higher the dissolved oxygen content. Secondly, the soil redox matter content and methanogenic bacteria population of the rice-duck ecosystem reduced more sharply than those of the no-duck rice farming, resulting in a lower methane production. Thirdly, the amount of methane emission differed between the treatments—the more the ducks, the less the methane emission. Other related analyses showed that the negative correlation was significant (p < 0.001) between the methane emission flux and dissolved oxygen content of water body. However, CH4 emission flux had significantly positive correlation (p < 0.01) with the soil redox matter content and rice field methanogenic population.     

Spatial and temporal dynamics of methane emissions from agricultural sources in China

Agricultural activities contribute significantly to the global methane budget. Agricultural sources of methane are influenced by land‐use change, including changes in agricultural area, livestock keeping and agricultural management practices. A spatially explicit inventory of methane emissions from agriculture is made for China taking the interconnections between the different agricultural sources into account. The influence of land‐use change on methane emissions is studied by linking a dynamic land‐use change model with emission calculations. The land‐use change model calculates changes in rice area and livestock numbers for a base‐line scenario. Emissions are calculated for 1991 based on land‐use statistics and for 2010 based on simulated changes in land‐use patterns. Emissions from enteric fermentation and manure management are based on emission factors, while emissions from rice paddies involve the calculation of total organic carbon added to rice paddy soils and assume that a constant fraction is emitted as methane. Spatial patterns of emissions are presented for the different sources. For the land‐use scenario considered it is expected that total methane emissions from agricultural sources in China increase by 11% while the relative contribution of rice fields to the emission decreases. Emissions from manure management are expected to become more important. These results indicate that agencies should anticipate changes in source strengths as a consequence of land‐use changes when proposing mitigation strategies and future national greenhouse gas budgets.     

Agronomic aspects of wetland rice cultivation and associated methane emissions

Wetland rice cultivation is one of the major sources of atmospheric methane (CH₄). Global rice production may increase by 65% between 1990 and 2025, causing an increase of methane emissions from a 92 Tg CH₄ y^–1 now to 131 Tg in 2025.Methane production depends strongly on the ratio oxidizing: reducing capacity of the soil. It can be influenced by e.g. addition of sulphate, which inhibits methanogenesis. The type and application mode of mineral fertilizers may also affect methane emissions. Addition of organic matter in the form of compost or straw causes an increase of methane emissions, but methane production is lower for materials with a low C/N ratio.High percolation rates in wetland rice soils and occasional drying up of the soil during the cultivation period depresses methane release. Water management practices aimed at reducing emissions are only feasible during specific periods in the rice growing season in flat lowland irrigated areas with high security of water availability and good control of the water supply. Intermittent drying of soils may not be possible on terraced rice lands.Assuming a 10 to 30% reduction in emission rates per unit harvested area, the global emission may amount to 93 Tg CH₄ y^– in 2025. A reduction of global emissions seems very difficult. To develop techniques for reducing CH₄ emissions from wetland rice fields, research is required concerning interactions between soil chemical and physical properties, and soil, water and crop management and methanogenesis. Such techniques should not adversely affect rice yields.     

Characterizing spatiotemporal dynamics of methane emissions from rice paddies in Northeast China from 1990 to 2010

Background

Rice paddies have been identified as major methane (CH₄) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH₄ emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels.

Methodology/Principal Findings

Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH₄ emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH₄ fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH₄ emission in the cool paddies.

Conclusions/Significance

The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory.     

Lower‐than‐expected CH4 emissions from rice paddies with rising CO2 concentrations

Elevated atmospheric CO₂ (eCO₂) generally increases carbon input in rice paddy soils and stimulates the growth of methane‐producing microorganisms. Therefore, eCO₂ is widely expected to increase methane (CH₄) emissions from rice agriculture, a major source of anthropogenic CH₄. Agricultural practices strongly affect CH₄ emissions from rice paddies as well, but whether these practices modulate effects of eCO₂ is unclear. Here we show, by combining a series of experiments and meta‐analyses, that whereas eCO₂ strongly increased CH₄ emissions from paddies without straw incorporation, it tended to reduce CH₄ emissions from paddy soils with straw incorporation. Our experiments also identified the microbial processes underlying these results: eCO₂ increased methane‐consuming microorganisms more strongly in soils with straw incorporation than in soils without straw, with the opposite pattern for methane‐producing microorganisms. Accounting for the interaction between CO₂ and straw management, we estimate that eCO₂ increases global CH₄ emissions from rice paddies by 3.7%, an order of magnitude lower than previous estimates. Our results suggest that the effect of eCO₂ on CH₄ emissions from rice paddies is smaller than previously thought and underline the need for judicious agricultural management to curb future CH₄ emissions.