气候变化和物候变动对东北黑土区农业生产的协同作用及未来粮食生产风险

东北黑土区是中国重要的粮食生产基地,也是中国气候变化最敏感的地区之一。然而,气候变化背景下东北黑土区气候及物候变化对农业生产力的综合影响并不清晰,未来农业生产风险评估的定量化程度不够,风险等级制定缺乏依据。本文借助遥感产品、气候资料和模拟数据等资料,综合运用多元线性回归、相关分析及干旱危险性指数等方法,探究东北黑土区作物物候动态及其气候响应特征,辨识气候与物候变化对农业生产的复合效应及未来可能风险。结果表明：① 2000—2017年东北黑土区29.76%的区域作物生长季开始期呈显著延后趋势,16.71%的区域作物生长季结束期呈提前态势,生长季开始期受气温的影响范围广,且滞后时间长;生长季结束期与前期气候变化关系更加密切,且带状差异性响应格局尤其明显。② 气候变化和物候期改变对作物生产的解释能力较生长季同期气候变化的解释能力增加了70.23%,解释面积扩大了85.04%。③ RCP8.5情景下东北黑土区粮食总产量呈现上升趋势,粮食生产风险表现出“南增北减”的演变特征,风险区面积不断扩大,全球温升2.0 ℃时,松嫩黑土亚区南部粮食减产量可能达到10%。研究有助于深入认识气候—物候—作物生产的关联机理及未来粮食生产风险,对制定气候变化应对策略,保障国家粮食安全具有重要意义。     

The effects of climate change and phenological variation on agricultural production and its risk pattern in the black soil area of northeast China

The black soil region of northeast China is a vital food base and is one of the most sensitive regions to climate change in China. However, the characteristics of the crop phenological response and the integrated impact of climate and phenological changes on agricultural productivity in the region under the background of climate change are not clear. The future agricultural risk assessment has been insufficiently quantified and the existing risk level formulation lacks a sound basis. Based on remote sensing products, climate data, and model simulations, this study integrated a logistic function fitting curvature derivation, multiple linear regression, and scenario simulation to investigate crop phenology dynamics and their climate response characteristics in the black soil region. Additionally, the compound effects of climate and phenology changes on agricultural production and possible future risks were identified. The key results were as follows: (1) From 2000 to 2017, 29.76% of the black soil region of northeast China experienced a significant delay in the start of the growing season (SOS) and 16.71% of the total area displayed a trend for the end of the growing season (EOS) to arrive earlier. The time lagged effects of the SOS in terms of the crop response to climatic factors were site and climatic parameter dependent. The influence of temperature was widespread and its effect had a longer lag time in general; (2) Both climatic and phenological changes have had a significant effect on the inter-annual variability of crop production, and the predictive ability of both increased by 70.23%, while the predictive area expanded by 85.04%, as compared to that of climate change in the same period of the growing season; (3) Under the RCP8.5 scenario, there was a risk that the future crop yield would decrease in the north and increase in the south, and the risk area was constantly expanding. With a 2.0℃ rise in global temperature, the crop yield of the southern Songnen black soil sub-region would reduce by almost 10%. This finding will improve our understanding of the mechanisms underlying climate change and vegetation productivity dynamics, and is also helpful in the promotion of the risk management of agrometeorological disasters.     

The CERES‐Rice Model‐Based Estimates of Potential Monsoon Season Rainfed Rice Productivity in Bangladesh*

Agricultural practices in Bangladesh are largely dependent on the monsoonal rainfall. Historically, Bangladesh often experiences severe droughts and floods during the monsoon months, with significant crop losses during both extreme conditions. This article provides a quantitative assessment of potential monsoon‐season aman rice for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A crop‐growth simulation model, the CERES‐Rice, is applied to sixteen locations representing major rice‐growing regions of Bangladesh to determine baseline yield estimates for four transplanting dates. The applications were conducted for 1975 through 1987. Average potential yield in Bangladesh is 6,907, 5,039, 3,637, and 1,762 kg ha^?1 for the above transplanting dates, respectively. In other words, Bangladesh would obtain 27 percent, 48 percent, and 75 percent less yield for 1 July, 15 July, and 15 August transplanting, respectively, than for 1 June transplanting. Potential yield vulnerability is the least for 1 June transplanting (up to 5 percent) and the highest (up to 66 percent) for 15 July transplanting date. The model applications show that regional variations exist for potential yield and yield vulnerability for a particular transplanting date. In addition, response of yield and vulnerability for a region changes with transplanting dates.     

RCP8.5气候变化情景下21世纪印度粮食单产变化的多模式集合模拟

基于跨部门影响模型比较计划（ISI-MIP）中20种气候模式与作物模型组合的模拟结果,预估了RCP 8.5排放情景下21世纪印度小麦和水稻单产变化。研究发现：① 多模式集合模拟结果基本再现了印度小麦和水稻单产的空间差异;同时,再现了小麦和水稻单产对温度和降水变化的响应特征：与温度呈负相关,与降水呈正相关。② RCP 8.5情景下,水稻和小麦生长季温度和降水均呈增加趋势,小麦生长季的温度、降水增加幅度大于水稻。空间上,温度增加幅度自北向南逐渐减小,降水增幅则逐渐增加,并且小麦种植区升温幅度大于非种植区,降水增幅则少于非种植区,水稻种植区升温幅度小于非种植区,降水增幅则多于非种植区。③ RCP 8.5情景下,小麦和水稻单产均呈下降趋势,21世纪后半叶尤为明显。小麦单产的下降速度明显大于水稻,其中21世纪前半叶小麦和水稻单产下降速度约分别为1.3%/10a （P < 0.001）和0.7%/10a （P < 0.05）,后半叶分别增至4.9%/10a （P < 0.001）和4.4%/10a （P < 0.001）。小麦和水稻单产变化存在明显的空间异质性,小麦单产的最大下降幅度出现在德干高原西南部,降幅约60%,水稻单产最大下降幅度出现在印度河平原北部,降幅约50%。这意味着未来气候变化情景下印度粮食供给将面临较大的挑战。     

科尔沁沙地奈曼旗水稻生产潜力与增产途径

根据沙地水稻栽培试验资料，计算了科尔沁沙地奈曼旗的水稻光温生产潜力。沙地水稻的现实生产力与最大光能利用率为４％时的光温生产潜力较接近，进而分析了沙地水稻增产的主要原因，提出了沙地水稻增产的栽培措施。     

Impacts of climate change on winter wheat growth in Panzhuang Irrigation District, Shandong Province

Global climate change has significant impacts on agricultural production. Future climate change will bring important influences to the food security. The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District (PID) during 2011–2040 under B2 climate scenario based on the Special Report on Emissions Scenarios (SRES) assumptions with the result of RCMs (Regional Climate Models) projections by PRECIS (Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research. The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002–2003 and 2007–2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station (YCES), Chinese Academy of Sciences (CAS). The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area. Average temperature at Yucheng Station rose by 0.86℃ for 1961–2008 in general. Under the B2 climate scenario, average temperature rose by 0.55℃ for 2011–2040 compared with the baseline period (1998–2008), which drastically shortened the growth period of winter-wheat. However, as the temperature keep increasing after 2030, the top-weight and yield of the winter wheat will turn to decrease. The simulated evapotranspiration shows an increasing trend, although it is not very significant, during 2011–2040. Water use efficiency will increase during 2011–2031, but decrease during 2031–2040. The results indicate that climate change enhances agricultural production in the short-term, whereas continuous increase in temperature limits crop production in the long-term.     

基于作物生长期的江苏省沿海地区气候生产潜力估算

江苏沿海地区是中国重要的耕地后备资源基地之一,气候生产潜力能够反映该地区粮食安全保障能力大小。考虑作物不同生长期光温水协调程度,对现有气候生产潜力模型基于作物生长期进一步改进,估算江苏沿海地区14个县市三大粮食作物气候生产潜力。结果表明：基于作物生长期的气候生产潜力模型具有可行性。江苏省沿海地区水稻和小麦作物气候生产潜力受太阳有效辐射、温度和降水因素共同影响;玉米气候生产潜力主要受太阳有效辐射和温度影响,不受降水因素限制。从地域分布特征看,江苏沿海地区水稻和玉米气候生产潜力南北方向呈现梯度递增规律;小麦气候生产潜力南北方向差异不大。     

气候变化对山东省潘庄灌区冬小麦生长的影响(英文)

Global climate change has significant impacts on agricultural production.Future climate change will bring important influences to the food security.The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District(PID) during 2011-2040 under B2 climate scenario based on the Special Report on Emissions Scenarios(SRES) assumptions with the result of RCMs(Regional Climate Models) projections by PRECIS(Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research.The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002-2003 and 2007-2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station(YCES),Chinese Academy of Sciences(CAS).The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area.Average temperature at Yucheng Station rose by 0.86℃ for 1961-2008 in general.Under the B2 climate scenario,average temperature rose by 0.55℃ for 2011-2040 compared with the baseline period(1998-2008),which drastically shortened the growth period of winter-wheat.However,as the temperature keep increasing after 2030,the top-weight and yield of the winter wheat will turn to decrease.The simulated evapotranspiration shows an increasing trend,although it is not very significant,during 2011-2040.Water use efficiency will increase during 2011-2031,but decrease during 2031-2040.The results indicate that climate change enhances agricultural production in the short-term,whereas continuous increase in temperature limits crop production in the long-term.     

未来气候变化对我国南方水稻主产区季节性干旱的影响评估

研究我国水稻主产区季节性干旱受未来气候变化的影响, 对调整水稻种植布局、提高水稻生产适应气候变化能力具有重要意义。本文通过对比时间跨度为1981-2030 年水稻生产可用水量和季节性干旱的时空分布和干旱程度, 得出气候变化对未来我国水稻主产区季节性干旱有显著影响。主要结论有:2001-2030 年(对照期) 与1980-2000 年(基准期) 对比, (1) 早稻和晚稻生长季可用水量均值增加了10%以上, 中稻生长季可用水量保持不变。同时, 中稻和晚稻的生长季可用水量的空间分布更加均匀, 表明由于气候变化的影响, 水稻主产区水稻生长季可用水量从整体上会更加充沛、空间分布会更加均匀, 有利于缓解季节性干旱的发生。(2)水稻的季节性干旱均呈下降趋势, 早稻季节性干旱减少1.25 万km², 中稻季节性干旱减少8.00万km², 特别是晚稻季节性干旱减少25 万km², 几乎占晚稻种植面积的20%。表明由于气候变化的影响, 水稻主产区水稻季节性干旱总体趋于缓解, 特别是晚稻季节性干旱问题有明显改善。(3) 通过建立水文循环过程中可用水量与作物生长季需水量之间的关系, 构建的基于分布式水文模型的水分供需指数(WSDI) 适用于评估未来气候对水稻主产区季节性干旱的影响。     

气候变暖对宁夏引黄灌区水稻生产的影响

对宁夏引黄灌区10个测站1961\_2004年水稻生长发育期5～9月的气温进行分析,结果表明,宁夏引黄灌区水稻生长期的气候明显变暖。ｔ检验表明,5～9月日平均气温的突变发生在1993年,突变后的气温比突变前升高了0.8℃。在水稻生长发育各阶段,气温都有所升高,但没有超过水稻生长发育的适宜温度范围。引黄灌区水稻的温度敏感系数在5月、7~9月上旬为正值,尤其在7月下旬至8月中旬最大,此阶段气候变暖对水稻生产有利,6月、9月中下旬为负值,气候变暖对水稻生产有不利影响。气候变暖为高产品种的引进创造了条件,降低了水稻对温度变化的敏感性,使水稻单产变率减小,保证了水稻的高产稳产。就宁夏引黄灌区而言,气候变暖对水稻单产的贡献为2.51％。     

三北防护林工程区植被绿度对温度和降水的响应

探究三北防护林工程区植被绿度对温度和降水的响应可为该区植被建设提供科学依据。基于2000—2015年的MODIS NDVI数据和气象数据,采用通径分析法分析了不同生长阶段气温和降水对三北防护林工程区植被绿度的直接和间接影响。研究发现：生长季多年平均植被绿度整体上呈现东部高西部低的空间格局,且林地>耕地>草地;生长季植被绿度呈现增长趋势,植被覆盖状况得到改善,其中耕地植被增长趋势最大。生长季升温抑制植被生长,降水量增加促进植被生长,降水量是影响三北防护林工程区生长季植被生长的关键气候因子。在不考虑降水变化影响时,升温促进植被生长,但生长季温度升高带来的降水量减少使得升温对植被生长表现为抑制作用。生长季不同时期降水量增加对植被生长均是促进作用,表现为末期>中期>初期;而气温的影响则表现为生长季初期升温促进植被生长,中期和末期升温不利于植被生长。生长季末期升温对植被生长的负效应以直接作用为主,而中期主要通过降水量变化的间接作用体现。识别生长季不同时段气温和降水对植被绿度影响的差异性,有助于全面认识和评估植被对气候变化的响应。     

Observing climate impacts on tea yield in Assam,India

Tea is an important cash crop for the economy in northeast India. It also supports the livelihoods of a large proportion of the population. At the same time, tea growth is sensitive to climatic conditions making it vulnerable to climate change and variability. Identifying the tea yield response to climatic variability in operational plantations, and identifying the most important climatic variables that impact tea yield is critical to assessing the vulnerability of the industry and informing adaptation. Here, we developed a garden level panel dataset and estimated statistical models to identify the causal effect of monthly temperature, monthly precipitation, drought intensity, and precipitation variability on tea yield. We found decreasing tea yield returns to warmer monthly average temperatures, and when monthly temperatures were above 26.6 °C warming had a negative effect. We found that drought intensity did not affect tea yield and that precipitation variability, and in particular precipitation intensity, negatively affect tea yield. An increase in average temperatures as expected with global warming will reduce the productivity of tea plantations, all else held equal. Further, interventions to reduce the sensitivity of tea plantations to warming and precipitation variability will have immediate pay-offs as well as providing climate change adaptation benefits.     

IMPACT OF CLIMATIC CHANGE ON AGRICULTURAL PRODUCTION IN KANSAS: A FOUR-CROP ANALYSIS

Most scenarios of greenhouse-gas climatic change predict a warmer drier Great Plains environment. The goal of this research was to determine the resulting change in soil moisture and to relate this to changes in agricultural productivity. Soil moisture was used in regression-based models to predict yields for the four major grain crops: wheat, corn, soybeans, and grain sorghum. The results indicate that a warmer drier climate would reduce yields for the summer crops throughout the state. The yield for winter wheat also decreased in the western part of the state but actually increased in eastern Kansas. Corn and soybeans could decline in the dry land crop mix in eastern Kansas as wheat becomes a more viable alternative. Thus, the results imply possible geographic shifts in the crop belts in Kansas. [Key words: climatic change, agricultural production, soil moisture.]     

ASSESSING THE SUITABILITY OF THE EPIC CROP MODEL FOR USE IN THE STUDY OF IMPACTS OF CLIMATE VARIABILITY AND CLIMATE CHANGE IN WEST AFRICA

The EPIC (Erosion Productivity Impact Calculator) crop model, developed by scientists of the United States Department of Agriculture (USDA), has been successfully applied to the study of erosion, water pollution, crop growth and production in the US but is yet to be introduced for serious research purposes in other countries or regions. This paper reports on the applicability of the EPIC 8120 crop model for the assessment of the potential impacts of climate variability and climate change on crop productivity in sub‐Saharan West Africa, using Nigeria as the case study. Among the crops whose productivity has been successfully simulated with this model are five of West Africa's staple food crops: maize, millet, sorghum (guinea corn), rice and cassava. Thus, using the model, the sensitivities of maize, sorghum and millet to seasonal rainfall were demonstrated with coefficients of correlation significant at over 98 per cent confidence limits. The validation tests were based on a comparison of the observed and the model‐generated yields of rice and maize. The main problems of validation relate to the multiplicity of crop varieties with contrasting performances under similar field conditions. There are also the difficulties in representing micro‐environments in the model. Thus, some gaps appear between the observed and the simulated yields, arising from data or model deficiencies, or both. Based on the results of the sensitivity and validation tests, the EPIC crop model could be satisfactorily employed in assessing the impacts of and adaptations to climate variability and climate change. Its use for the estimation of production and the assessment of vulnerabilities need to be pursued with further field surveys and field experimentation.     

2000—2017年内蒙古荒漠草原植被物候变化及对净初级生产力的影响

荒漠草原分布于干旱区和半干旱区,对气候变化的响应极为敏感,但目前学术界对于荒漠草原物候与生产力变化的研究仍较为薄弱。有鉴于此,论文采用2000—2017年MODIS NDVI数据和气象数据,利用通用数量化方法提取内蒙古荒漠草原植被的生长季始期(start of season, SOS)和生长季末期(end of season, EOS);基于Carnegie-Ames-Stanford Approach (CASA)模型估算了植被净初级生产力(NPP),并分析了植被物候和净初级生产力之间的关系。研究结果表明：① 2000—2017年内蒙古荒漠草原SOS呈显著提前趋势(0.88 d/a,P<0.05),EOS不显著提前(0.13 d/a,P>0.05),生长季长度(length of season, LOS)呈显著延长趋势(0.76 d/a)。81.53%像元的SOS与2—4月平均气温呈负相关(8.21%显著相关,P<0.05),60.80%像元的SOS与4月降水量呈负相关关系(6.12%显著相关,P<0.05);65.16%像元的EOS与9月平均气温呈负相关(5.03%显著相关,P<0.05),78.61%像元的EOS 与7—9月降水量呈正相关关系(10.12%显著相关,P<0.05)。② 内蒙古荒漠草原多年平均NPP为104.71 gC/(m ²·a),有自东向西逐渐降低的区域差异;在研究时段内,春、夏季和生长季的NPP均呈不显著增加趋势,秋季NPP有不显著减少趋势;生长季降水量增加有利于生长季NPP的积累。③ 春季NPP与SOS呈不显著负相关,秋季NPP与EOS呈显著正相关。LOS的延长促进了NPP的累积,其中生长季NPP与EOS的推迟关系更为密切。研究结果揭示气候变化对内蒙古荒漠草原植被物候和生产力有显著影响,对区域生态系统管理和生态建设具有重要参考意义。     

THE DENDROCLIMATOLOGICAL POTENTIAL OF AN ALPINE SHRUB,CASSIOPE MERTENSIANA,FROM MOUNT RAINIER,WA, USA

The application of dendrochronological techniques to shrubs found in arctic and alpine plant communities is opening previously untapped regions to the exploration of plant‐climate ecological relationships and climate reconstruction. In this pilot study, we present growth (1963–2004), reproduction (1963–2004), and stable carbon isotope ratio (1975–2004) chronologies for Cassiope mertensiana from a subalpine site in Mount Rainier National Park, Washington, USA. Based on simple linear correlation analysis, positive correlations characterize plant growth and previous year mean maximum temperature in April and June, suggesting the influence of temperature on snowpack and, in turn, on growing season length, plant and soil insulation, and nutrient and moisture availability. Plant growth and reproduction are significantly correlated with current year July mean maximum temperature and total precipitation, indicating the importance of a warm and extended growing season for optimal plant development. Using step‐wise multiple linear regression analysis, we developed a preliminary calibration model for July mean maximum temperature (R = 0.63), extending over the 1974–2004 time period. This archive has the potential to elucidate multi‐scale, spatially‐explicit, ecological and climatic information for alpine ecosystems situated along a north‐south transect from the southern Yukon to the Pacific Northwest of the United States.     

中国东北地区植被生产力控制因素分析

植被生长季长度和生长强度是形态上影响植被生产力变化的重要因子。全球变暖情景下,北半球中高纬度大部分地区植被生长季显著延长并对植被生产力产生正向反馈,而植被生长强度变化情形及对生产力的控制作用并不清晰。中国东北地区属于中纬度温带地区,具有较高的植被覆盖度和丰富的植被类型,探索其植被生长季长度和强度的变化及对生产力的控制作用有利于理解和应对该地区的生态系统变化。以中国东北为研究区,基于1982—2015年长时序遥感植被指数数据（NDVI3g）,利用曲率求导法确定植被生长季开始点（SOS）、结束点（EOS）、生长季长度（LOS）和夏季最大生长季强度（GM）等关键物候参数,然后利用相对重要性（RI）方法定量分析了生长季长度和强度对植被生产力长期变化趋势的相对贡献及时空格局。结果表明：① 研究区整体的植被生产力和生长强度呈现增强趋势,而生长季长度呈现缩短趋势,导致生长强度成为控制生产力变化趋势的主要因素（RI = 70%）;② 在不同植被覆盖区域,生长季长度和生长强度对生产力的影响程度具有显著的空间差异。西部草原区植被生产力受生长强度控制最为显著（RI = 93%）,其次为针叶林（RI = 66%）和阔叶林区（RI = 62%）,农作物区生产力受生长强度影响最小（RI = 56%）。生长季长度对植被生产力的控制在农作物区最为显著（RI = 40%）,在其他区域的影响约为27%~35%。各植被覆盖区生长强度与生产力均为正相关,生长季长度与生产力均为负相关;③ 气候因素（降水、温度）和物候变化均对主要贡献因子生长强度产生影响,其中SOS的变化对生长强度的影响程度和空间范围最为显著,主要表现为SOS推迟促进生长强度增强。本研究基于遥感数据发现1982—2015年间中国东北地区植被生长更加旺盛,但是植被生长活动主要受生长强度的影响,该研究可以为植被生产力变化模拟的参数选择提供新的线索。     

Regional dynamics of terrestrial vegetation productivity and climate feedbacks for territory of Ukraine

Climate change has the potential to affect terrestrial ecosystems and, thereby, the carbon cycle. Various vegetation biomes are likely to respond differently to changes in climatic factors. The purpose of this study was to analyse the trends of the terrestrial vegetation productivity and climate drivers on regional levels and relations between ones. The gross primary productivity from the global satellite-based terrestrial production efficiency model (PEM) MOD17 as the vegetation productivity indicator and meteorological data from the weather station network as climatic indicators were used. The analysis covered a period from 2000 to 2012. Correlation analysis was used to quantify the association between the vegetation productivity and climatic indicators for different growing seasons and landscape-climatic zones of Ukraine. The Mann–Kendall trend test was applied to take into account seasonal features. Multiple linear regression models for corresponding seasons and zones have been simulated using the principal component analysis. The results showed no detectable limiting effect of the climatic drivers on plant productivity for forest areas. The limiting effect of the temperature increasing and precipitation amount decreasing for the steppe zone and eastern forest-steppe subzone of Ukraine for summer was observed.