Geographic Variation of Rice Yield Response to Past Climate Change in China

Previous studies demonstrated climate change had reduced rice yield in China, but the magnitude of the reduction and the spatial variations of the impact have remained in controversy to date. Based on a gridded daily weather dataset, we found there were obvious changes in temperatures, diurnal temperature range, and radiation during the rice-growing season from 1961 to 2010 in China. These changes resulted in a signiifcant decline of simulated national rice yield （simulated with CERES-Rice）, with a magnitude of 11.5%. However, changes in growing-season radiation and diurnal temperature range, not growing-season temperatures, contributed most to the simulated yield reduction, which conifrmed previous estimates by empirical studies. Yield responses to changes of the climatic variables varied across different rice production areas. In rice production areas with the mean growing-season temperature at 12-14＆#176;C and above 20＆#176;C, a 1＆#176;C growing-season warming decreased rice yield by roughly 4%. This decrease was partly attributed to increased heat stresses and shorter growth period under the warmer climate. In some rice areas of the southern China and the Yangtze River Basin where the rice growing-season temperature was greater than 20＆#176;C, decrease in the growing-season radiation partly interpreted the widespread yield decline of the simulation, suggesting the signiifcant negative contribution of recent global dimming on rice production in China＇s main rice areas. Whereas in the northern rice production areas with relatively low growing-season temperature, decrease of the diurnal temperature range was identiifed as the main climatic contributor for the decline of simulated rice yield, with larger decreasing magnitude under cooler areas.     

气候变化对中国南方水稻生产的阶段性影响及适应性对策

根据GISSGCMTransientBRun的输出结果 ,结合中国南方稻区 15个样点近 4 0年的逐日气候资料 ,生成了每个样点在 2 0 10年、2 0 30年和 2 0 5 0年的气候变化情景 ;利用CERES Rice模型在基准气候 (196 0～ 1997年 )以及上述不同年份的气候变化情景下运行的结果 ,结合中国若干农业气候指标 ,分区评述了未来 10年、30年和 5 0年全球气候变化对不同稻作类型水稻生育期、产量、稻田蒸散量的阶段性影响 ,并分析了中国稻作制度可能发生的演进趋势。最后 ,在模拟试验的基础上 ,提出了若干适应气候变化的农业对策 ,包括调整品种布局、有条件地扩种双季稻、改善灌溉条件及培育和引进新品种等。该研究结果对国家及各级农业行政部门制定中远期农业规划和农业发展战略具有重要的参考价值     

河南省商丘市气候变化对玉米产量的影响

为探明气候变化对豫东玉米(Zea mays L.)产量的影响,以河南省商丘市为研究区域,根据1991～2010年河南省商丘市气候变化和玉米产量资料,利用数学统计与Thomthwaite memoriae模型,结合未来气候预测结果定量分析了气候变化对玉米产量的影响.结果表明,在全球气候变暖的背景下,玉米产量整体上呈波动上升趋势;主成分分析表明,气温、降水量与极端温度为影响玉米产量的主要气候因子,降水过多及低温对玉米生产不利.河南省商丘市“暖温型”气候有利于玉米生产力的提高,“冷干型”气候对玉米生产最为不利.     

气候变暖对早稻产量与生育进程的影响

利用OTCs系统模拟了气温升高2℃和CO2浓度升高60 mg/kg等气候变化条件,研究了气候变暖对早稻两优287产量和生育进程的变化特点,统计了主要农业气象灾害发生特点。结果表明,增加CO2浓度处理经济产量最高,增温处理次之,大田对照(无增温,无CO2浓度增加)产量最低;秸秆产量变化也有类似特点。模拟气候变暖条件下的农业气象灾害特点为,增温条件下,高温热害频发,基本避开了低温冷害;不增温条件下,高温热害与低温冷害均有发生。气候变暖对早稻发育期的影响特点为,生育前期差异不大,间隔均在1 d以内。进入拔节期开始,增温处理与增加CO2浓度处理生育进程逐渐加快,其中,增CO2增温+增CO2增温OTCs对照大田对照。增温2℃与CO2浓度升高60 mg/kg的气候变暖条件下,荆州市早稻露地育秧播期可提前至3月14日;如果是温室育秧,育秧的日期可安排在3月10日左右,比当前气候条件下早稻播种期提前了13 d左右。     

The Effects of Climate Change on the Planting Boundary and Potential Yield for Different Rice Cropping Systems in Southern China

Based on climate data from 254 meteorological stations, this study estimated the effects of climate change on rice planting boundaries and potential yields in the southern China during 1951-2010. The results indicated a signiifcant northward shift and westward expansion of northern boundaries for rice planting in the southern China. Compared with the period of 1951-1980, the average temperature during rice growing season in the period of 1981-2010 increased by 0.4＆#176;C, and the northern planting boundaries for single rice cropping system （SRCS）, early triple cropping rice system （ETCRS）, medium triple cropping rice system （MTCRS）, and late triple cropping rice system （LTCRS） moved northward by 10, 30, 52 and 66 km, respectively. In addition, compared with the period of 1951-1980, the suitable planting area for SRCS was reduced by 11%during the period of 1981-2010. However, the suitable planting areas for other rice cropping systems increased, with the increasing amplitude of 3, 8, and 10%for ETCRS, MTCRS and LTCRS, respectively. In general, the light and temperature potential productivity of rice decreased by 2.5%. Without considering the change of rice cultivars, the northern planting boundaries for different rice cropping systems showed a northward shift tendency. Climate change resulted in decrease of per unit area yield for SRCS and the annual average yields of ETCRS and LTCRS. Nevertheless, the overall rice production in the entire research area showed a decreasing trend even with the increasing trend of annual average yield for MTCRS.     

Climate Change Modelling and Its Roles to Chinese Crops Yield

Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation.Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability.Understanding the interactions between climate change and agricultural production is essential for society stable development of China.The first mission is to fully understand how to predict future climate and link it with agriculture production system.In this paper,recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches.The methods for climate change scenarios construction are introduced.The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized.The study found that simulated productions of grain crop inherit uncertainty from using different climate models,emission scenarios and the crops simulation models.Moreover,studies have different spatial resolutions,and methods for general circulation model(GCM) downscaling which increase the uncertainty for regional impacts assessment.However,the magnitude of change in crop production due to climate change(at 700 ppm CO2 eq correct) appears within ±10% for China in these assessments.In most literatures,the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase.Finally,the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops.The uncertainty for crop yield projection is associated with climate change scenarios,CO2 fertilization effects and adaptation options.Therefore,more studies on the fields such as free air CO 2 enrichment experiment and practical adaptations implemented need to be carried out.     

气候变化对中国农业生产的影响

未来气候变化下中国农业的稳定事关中国的长远持续发展,国内外气候变化研究界和农业气象研究界对气候变化对中国农业生产的影响的评估未有一致的认识。本文从农业科学角度讨论了气候变化对中国农业生产涉及的气象资源、土地资源、农业生物环境和生态系统的影响,并从作物生长和经济产量形成的角度讨论和分析了气候变化对中国种植业、养殖业不同产业行业的影响,气候变化中一些趋势性变化因不同作物和不同区域而异,例如温度和CO_2浓度变化对农业生产的影响因不同作物和不同时相而异,反之,极端性气候/天气事件对农业不同行业的生产都显得危害很大,而气候变化中区域性干旱将成为我国未来农业生产愈来愈严重的挑战。气候变化对中国农业生产的影响甚为复杂,一些气候变化因子的实际影响还存在很大不确定性。当前,定量评价气候变化对中国农业生产的影响还存在困难。     

Impacts of Climate Change on Agriculture and Adaptive Strategies in China

China is the world’s most populous country and a major emitter of greenhouse gases. Consequently, China’s role in climate change has received a great deal of attention, whereas the impact of climate change on China has been largely ignored. Studies on the impacts of climate change on agriculture and adaptation strategies are increasingly becoming major areas of scientific concern. However, the clear warming that has been sounded in China in recent decades has not been matched with a clear assessment of the impact of climate change on China’s water resources and agriculture. In the present study, we review observations on climate change, hydrology, and agriculture in China and relate these observations to likely future changes. We also analyse the adaptive strategies in China’s agriculture.     

利用CMIP5多模式集合模拟气候变化对中国小麦产量的影响

【目的】利用最新的国际耦合模式比较计划第五阶段（CMIP5）中30个全球大气-海洋耦合模式（AOGCMs）在典型浓度路径（RCPs）情景下的气候预估结果,基于集合模拟的方法评估气候变化对中国未来小麦产量的影响。【方法】气候变化对农业的影响评估通常基于未来逐日的气象资料,然而AOGCMs模拟的逐日数据存在较大的不确定性。利用“虚拟气候变暖”（PGW）的方法,将CMIP5模式预估的未来气候变化的信号与当前气候的逐日站点观测资料相结合,得到未来气候预估的逐日数据集合。结合作物过程模型CERES-Wheat,利用集合模拟的方法,以概率的形式量化表述气候变化对中国小麦产量影响的不确定性。【结果】未来中国冬春小麦代表站在其小麦生育期内的平均气温均有升高。预估21世纪末期,冬小麦代表站平均增温2.7-2.9℃,春小麦代表站平均增温3.0-3.3℃。RCP8.5情景比RCP2.6情景增温显著。预估未来冬、春小麦在其生育期内的降水量普遍增加,并随着排放量的增长,降水量表现出逐渐增多的趋势。在仅改变未来气候变化的条件下,冬、春小麦的灌溉小麦单产相对于1996-2005年普遍减产,并且随着气候变化,灌溉小麦的减产概率上升。春小麦代表站在灌溉条件下小麦减产的程度比冬小麦代表站更显著。预估到21世纪末期,冬小麦代表站在RCP2.6情景下减产2%左右,在RCP4.5情景下减产6%左右,在RCP8.5情景下减产9%左右,减产概率超过85%。预估春小麦代表站在RCP2.6情景下减产5%,在RCP4.5情景下减产8%以上,在RCP8.5情景下减产15%以上,减产概率超过90%。在雨养条件下,冬小麦代表站的小麦单产相较于1996-2005年显著增产。预估到21世纪末期,冬小麦代表站在RCP2.6情景下增产21%以上,在RCP4.5情景下增产22%以上,在RCP8.5情景下增产25%以上,增产概率超过90%。【结论】利用PGW方法获得未来气候预估的逐日数据集合有效的保留了当前气候的天气信息,尤其是极端天气事件的信息。利用集合模拟的方法评估未来气候在RCP2.6、RCP4.5和RCP8.5情景下对中国小麦单产的影响,表明在灌溉条件下,随着排放量的增加,气候变化导致中国小麦单产减产的概率逐渐上升。雨养小麦单产集合的不确定性较灌溉条件大。     

Climate Change, Risk and Grain Yields in China

Adopting Just and Pope (1978, 1979) style yield functions, this paper proposes a method to analyze the impacts of regional climate change on grain production in China. We find that changes in climate will affect grain production in North and South China differently. Specifically, it emerges that a 1℃ increase in annual average temperature could reduce national grain output by 1.45% (1.74% reduction in North China and 1.19% reduction in South China), while an increase in total annual precipitation of around 100 mm could increase national grain output by 1.31% (3.0% increase in North China and 0.59% reduction in South China).     

Spatio-Temporal Changes in the Rice Planting Area and Their Relationship to Climate Change in Northeast China: A Model-Based Analysis

Rice is one of the most important grain crops in Northeast China (NEC) and its cultivation is sensitive to climate change. This study aimed to explore the spatio-temporal changes in the NEC rice planting area over the period of 1980–2010 and to analyze their relationship to climate change. To do so, the CLUE-S (conversion of land use and its effects at small region extent) model was first updated and used to simulate dynamic changes in the rice planting area in NEC to understand spatio-temporal change trends during three periods: 1980–1990, 1990–2000 and 2000–2010. The changing results in individual periods were then linked to climatic variables to investigate the climatic drivers of these changes. Results showed that the NEC rice planting area expanded quickly and increased by nearly 4.5 times during 1980–2010. The concentration of newly planted rice areas in NEC constantly moved northward and the changes were strongly dependent on latitude. This confirmed that climate change, increases in temperature in particular, greatly influenced the shift in the rice planting area. The shift in the north limit of the NEC rice planting area generally followed a 1°C isoline migration pattern, but with an obvious time-lag effect. These findings can help policy makers and crop producers take proper adaptation measures even when exposed to the global warming situation in NEC.     

一种用于评价全球气候变化对中国南方水稻生产影响的效应模型--RCCMOD

将自主研制的水稻栽培计算机模拟优化决策系统(RCSODS)改造为适于全球气候变化影响评价的水稻效应模型(RCCMOD);利用中国南方9个有代表性样点的水稻区域试验资料与同期同地的天气资料,对RCCMOD进行可靠性检验;将RCCMOD分别在研究区域基准气候(Baseline)和3种基于大气环流模型(GCMs)的(2×CO2)气候变化情景下运行,并将模拟结果与同样条件下CERES Rice模型的模拟结果进行了比较,两者基本一致。     

Climate Change Impact and Its Contribution Share to Paddy Rice Production in Jiangxi,China

In the study, an improved approach was proposed to identify the contribution shares of three group factors that are climate, technology and input, social economic factors by which the grain production is shaped. In order to calibrate the method, Jiangxi Province, one of the main paddy rice producers in China was taken as an example. Based on 50 years （1961-2010） meteorological and statistic data, using GIS and statistical analysis tools, the three group factors that in certain extent impact China＇s paddy rice production have been analyzed quantitatively. The individual and interactive contribution shares of each factor group have been identiifed via eta square （η2）. In the paper, two group ordinary leasr square （OLS） models, paddy models and climate models, have been constructed for further analysis. Each model group consists of seven models, one full model and six partial models. The results of paddy models show that climate factors individually and interactively contribute 11.42-15.25%explanatory power to the variation of paddy rice production in the studied province. Technology and input factors contribute 16.17%individually and another 8.46%interactively together with climate factors, totally contributing about 25%. Social economic factors contribute about 7%of which 4.65%is individual contribution and 2.49%is interactive contribution together with climate factors. The three factor groups individually contribute about 23%and interactively contribute additional 41%to paddy rice production. In addition every two of the three factor groups also function interactively and contribute about 22%. Among the three factor groups, technology and input are the most important factors to paddy rice production. The results of climate models support the results of paddy models, and display that solar radiation （indicated by sunshine hour variable） is the dominate climate factor for paddy rice production.     

Climate Change Impact and Its Contribution Share to Paddy Rice Production in Jiangxi,China

In the study, an improved approach was proposed to identify the contribution shares of three group factors that are climate, technology and input, social economic factors by which the grain production is shaped. In order to calibrate the method, Jiangxi Province, one of the main paddy rice producers in China was taken as an example. Based on 50 years (1961–2010) meteorological and statistic data, using GIS and statistical analysis tools, the three group factors that in certain extent impact China's paddy rice production have been analyzed quantitatively. The individual and interactive contribution shares of each factor group have been identified via eta square (η²). In the paper, two group ordinary leasr square (OLS) models, paddy models and climate models, have been constructed for further analysis. Each model group consists of seven models, one full model and six partial models. The results of paddy models show that climate factors individually and interactively contribute 11.42–15.25% explanatory power to the variation of paddy rice production in the studied province. Technology and input factors contribute 16.17% individually and another 8.46% interactively together with climate factors, totally contributing about 25%. Social economic factors contribute about 7% of which 4.65% is individual contribution and 2.49% is interactive contribution together with climate factors. The three factor groups individually contribute about 23% and interactively contribute additional 41% to paddy rice production. In addition every two of the three factor groups also function interactively and contribute about 22%. Among the three factor groups, technology and input are the most important factors to paddy rice production. The results of climate models support the results of paddy models, and display that solar radiation (indicated by sunshine hour variable) is the dominate climate factor for paddy rice production.     

气候变化对黑龙江省水稻生产可能带来的影响

通过对全球及黑龙江省气候趋势的分析,说明黑龙江省气候至少在未来的几十年内仍处于持续增温的时期。气温升高对黑龙江省水稻生产是有利的,使水稻的北界继续向北扩展,水稻适宜区扩大,同时,原水稻种植区积温增加,可以种植更晚熟品种,单产提高。积温增加、CO2浓度提高和育苗条件的改善,实际生产可用品种熟期可比原积温划分区的可用品种晚1~2个熟级。     

近20年东北气候变暖对春玉米生长发育及产量的影响

【目的】探求东北三省近20 年气候变暖对春玉米生长发育进程及产量的影响,为东北地区气候变暖下粮食安全问题提供理论依据。【方法】选取东北黑龙江、吉林和辽宁省三省进行区域研究,利用东北地区近20 年气候观察数据和春玉米长期观测数据,通过相关和回归等数理统计方法系统分析东北三省春玉米生长季的气候因子（温度和降水量）与春玉米生育进程数据和历史产量数据之间的关系。【结果】东北地区1989-2009 年春玉米生长季日最高温度、最低温度以及平均温度均呈明显上升趋势,气候倾向率每年分别为0.050、0.045和0.044℃,表现为春玉米生育期间白天增温幅度较夜间增温幅度大,降水量变化不显著。近20 年黑龙江省各试验站平均播种日期变化趋势是每年提前0.10 d,而吉林省、辽宁省各试验站每年分别推迟0.18和0.21 d。黑龙江省、吉林省以及辽宁省各试验站春玉米平均成熟日期变化趋势分别每年推迟0.39、0.35和0.55 d,平均生育期天数变化趋势分别每年增加0.49、0.17和0.34 d,成熟日期推迟的幅度大于播种日期的推迟幅度导致三省试验站春玉米生育天数增加。对1991-2006 年东北地区审定品种生育期数据与气候数据关系进行相关性分析表明,黑龙江省最高温度（Tmax）上升会延长审定品种生育期,而吉林和辽宁省春玉米的审定品种生育期与平均温度（Tavg）、最高温度（Tmax）和最低温度（Tmin）均呈现为正相关。采用T检验法分析春玉米审定品种生育期和试验站春玉米生育期关系表明,黑龙江和辽宁省的审定品种和试验站春玉米生育天数呈一致的增加趋势,且无显著性差异。采用线性偏回归测验法分析品种和气候因子对春玉米生育期影响重要性的结果表明,品种生育期的延长是导致春玉米生育期不断延长的主要原因。三省春玉米近20 年平均产量表现为增加趋势,其趋势由小到大的次序是辽宁省、吉林省以及黑龙江省,越往北其产量增加趋势越大,产量增加越明显。东北各省地级市1989-2009年面板数据分析表明,东北地区平均温度（Tavg）、最高温度（Tmax）和最低温度（Tmin）的变化均会影响春玉米的产量。温度上升,东北部产量增加明显,尤其是黑龙江省东部的三江平原地区,而东北地区西南部减产。【结论】受气候变暖的影响,东北春玉米品种对气候变暖是逐步适应,可以利用其适应潜力,通过春玉米品种改良和调整播期等措施来适应气候变暖,从而提高春玉米产量。     

气候变化对忻州玉米气象产量的影响

利用河曲、五寨、五台、繁峙、忻府区5个气候代表站1981—2009年玉米生长期间日照时数、平均气温、降水量、≥10℃积温等农业气象资料及玉米产量资料,应用滑动平均、线性倾向估计和多元回归等统计方法,建立了气象要素与玉米气象产量的多元回归模型。结果表明,近29 a,5个县(区)的降水量与玉米气象产量呈正相关关系;日照时数、平均气温与玉米气象产量五寨、五台和河曲呈正相关关系,繁峙和忻府区呈负相关关系;≥10℃积温河曲、五台和忻府区与玉米气象产量呈正相关关系,五寨和繁峙呈负相关关系。不同县(区)各气象要素影响的程度不同,5个县(区)对玉米气象产量影响最大的均为平均气温;五寨、河曲和繁峙对玉米气象产量影响排第2位的为年降水量;五台对玉米气象产量影响排第2位的为日照时数,忻府区对玉米气象影响排第2位的为≥10℃积温。     

季节性变暖对中国农作物病虫害的影响

基于已有研究成果,采用农作物病虫害发生危害时空变化对季节性变暖时空变化响应事实检测的方法,系统分析和汇总季节性变暖对农作物病虫害影响的已有观测事实及其变化规律性,提出其影响的最新认知,并对今后的发展方向进行展望。已有影响事实检测表明：暖冬可使病虫进入越冬阶段推迟,延长病菌冬前侵染、冬中繁殖时间,降低害虫越冬死亡率,增加冬后菌源和虫源基数;病虫害发生期、迁入期、危害期提前;越冬北界北移、海拔上限高度升高;持续暖冬可使冬后虫源基数显著增加。与常年相比,全国性暖冬年冬中病菌繁殖侵染率可比冬前增加50%以上、冬中害虫存活率可达常年的1-2倍,冬后菌源、虫源基数增加1倍以上;持续暖冬冬后虫源基数可达常年的5倍以上;病害始见期、虫害发生期提前5 d以上,最早可分别提前20、30 d以上;稻飞虱越冬北界北移2-4个纬度,小麦条锈病越冬海拔上限高度升高100-300 m。暖春有利于病虫害危害期提前、扩展速度加快、发生程度加重。炎夏可使一些病菌越夏的海拔下限高度增加、面积和菌量减少,一些害虫发育历期延长、死亡率增加。暖秋有利于害虫滞留危害,发生代数可比常年增加1个代次。季节性变暖对农作物病虫害影响的时空变化及其规律性、发生与灾变的影响预估、风险评估及适应对策将是未来需要重点解决的关键问题。     

中国稻作与旱作生产的气象减产风险评价

本研究利用直线滑动平均模型对中国各省区1950—2006年旱作和稻作的趋势产量进行了模拟,计算出历年的气象产量,并采用减产率指标、减产率浮动性指标、高风险概率指标3个评价指标以及综合性指标进行了气象产量的气候变化减产风险评价,同时采用变异系数对我国各省产量波动状况进行了分析,并将各指标与年平均降水变率、年平均气温变率进行耦合分析。结果表明,旱作高减产风险和波动风险主要分布在华东和华南地区,而稻作则体现为由南向北风险逐渐增加。年平均降水变率和年平均气温变率高的地区,其水稻气象减产风险较大。由于人口增长和经济发展的压力,中国农业面临着应对气象减产和保证粮食增产的双重压力。