中国作物物候对气候变化的响应与适应研究进展

以气候变暖为主要特征的气候变化对作物物候产生了重要的影响,通常气温升高会导致作物生长速度加快,生育期缩短,从而造成作物产量下降,不利于农业发展。同时,作物物候变化可以直接或间接反映气候变化情况,对于气候变化具有重要的指示意义。作物物候的研究对于农业气象灾害的预防、农业生产管理水平的进步以及农业产量提高都极为关键。随着全球地表气温的持续升高,作物物候相关研究也越来越引起科学家的关注。论文结合作物物候的主要研究方法,综述了中国近几十年来小麦、玉米、水稻以及棉花、大豆等主要农作物的生育期变化特征以及主要的驱动因子,得到以下主要结论：①在研究方法上,统计分析方法应用最为普遍,其他几种方法都需要与统计分析方法相结合使用。另外,作物机理模型模拟方法易于操作、可行性强,在物候研究中应用也比较多。遥感反演方法对作物生育期的特征规律要求较高,一般主要关注作物返青期。②整体上,小麦全生育期主要呈缩短趋势,而玉米和水稻全生育期以延长趋势为主。③作物物候变化的驱动因子主要是气候变化和农业管理措施改变,其中,气候变化是主导驱动因子,对作物物候变化起决定作用,而调整农业管理措施,在一定程度上抵消气候变化对作物生育期的不利影响。作物物候对气候变化的响应和适应研究可以为农业生产适应气候变化提供重要的理论依据和对策。     

水稻发育期模型研究进展

物候是气候变化的重要指示物.随着全球变化研究的开展,已经有越来越多的研究表明,随着气象条件的变化,植物的物候期发生了明显的变化,因此,对物候的精准模拟可以帮助我们准确理解作物对全球变化的响应机制,强大的物候模型已经逐渐成为提高植物对气候变化响应的模拟精度的一个关键工具.同时作物物候的模拟也是作物模型的一个重要组成部分.水稻是最重要的粮食作物之一,水稻发育期模型研究对水稻生长模型有着重要的意义.本文对国内外水稻发育模型的发展进行了综述,并提出了目前水稻发育期模型研究中存在的问题以及发展的方向,以期后续的水稻发育期模型乃至作物模型的研究提供借鉴.     

农业物候动态对地表生物物理过程及气候的反馈研究进展

地表过程对全球变化的响应和反馈是地球系统科学研究的核心课题之一,目前的研究多关注全球变化对地表过程的影响,而地表动态过程对地表生物物理过程及气候的反馈研究较少。系统认识地表物候动态对生物物理过程及气候的反馈对深化地球系统科学研究有着重要的意义。本文从农业物候动态的事实、农业物候动态在陆面过程模型中的参数化表达、农业物候动态对地表生物物理过程及气候的反馈等方面进行综述,发现在气候变化和管理措施影响下,以种植期和灌浆期为代表的农业物候期发生了显著的规律性变化;耦合农业物候动态,改善了模型对地表动态过程、生物物理过程和大气过程的数字化表达;农业物候变化对地表净辐射、潜热、感热、反照率和气温、降水、环流等过程产生了影响,并表现出以地表能量分配为主的气候反馈机理。针对农业物候动态对地表生物物理过程及气候效应的时空重要性,需要继续开展以下方面的工作：① 加强全球变化对地表物候动态的影响及其反馈的综合研究;② 不同光谱波段地表反射率与农业物候动态的关系研究;③ 农业物候动态引起的作物生理学特征变化在地表生物物理过程中的贡献;④ 重视不同气候区物候动态对气候反馈效应的差异。     

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。     

遥感物候学研究进展

植物物候现象是环境条件季节和年际变化最直观、最敏感的生物指示器,其发生时间可以反映陆地生态系统对气候变化的快速响应.近年来,遥感物候观测因其具有多时相、覆盖范围广、空间连续、时间序列较长等特点,已成为揭示植被动态对全球气候变化响应与反馈的重要手段.文章在介绍植物物候遥感监测的数据集及其预处理方法的基础上.从植物物候生长季节的划分、植物物候与气候变化、植物物候与净初级生产量、植物物候与土地覆盖、植物物候与农作物估产等方面系统阐述了近5年来国内外遥感物候学研究的重要进展,并针对目前研究中存在的问题,提出近期遥感物候研究的主要方向:(1)发展一种更具普适性的物候生长季节划分方法;(2)通过开展植物群落的物候观测和选择合适的尺度转换方法,统一地面与遥感的空间信息;(3)定量分析植物物候变化对人类活动的响应机制;(4)选择适宜的数学方法和模型,实现各种不同分辨率遥感数据的融合;(5)通过动态模拟,预测植物物候对未来气候变化的响应.     

全球气候变化下中国农业的脆弱性与适应对策

全球气候变化问题虽然还存在某些不确定性，但已得到广泛认同，对气候条件颇为敏感的农业将受影响，主要效应可概括为：（１）农业地理限制的变动；（２）作物产量的变化；（３）对农业系统的冲击。中国农业对气候变化与波动尤其敏感，加之人口压力进一步加大和农业资源已有紧缺，粮食自给的能力将受到严重威胁，必须充分重视适应和调整对策的研究，变动性与不确定性是气候的固有特征，在评价全球气候变化对农业的影响时应该认识到这     

近百年我国积温的变化与作物产量

本文在搜集整理我国长序列积温和产量资料的基础上,对各地的积温和主要作物产量的变化作了初步分析,以期从农业气候(热量)和作物气象产量分析方面为气候变化及其与农业生产关系的研究提供一些参考。     

全球气候变化影响下中国农业产量的可持续性

气候变化的区域影响愈益成为具有挑战性的问题,尤其是气候变化对农业产量可持续性的影响已引起广泛的关注。基于全示气候变化对中国的影响和区域气候变率分析,提出了粮食气候产量形成模型,半将其应用于黄淮海地区冬小麦小分条件和产量研究,同时对全球气候变化情形下冬小麦产量的变化做出评价。     

作物水分利用效率对温度和CO2浓度升高的响应研究进展

以大气CO2浓度和温度升高为主要标志的全球气候变化对作物水分利用效率产生重要影响,作物水分利用效率对CO2浓度和温度升高的响应特征与机理研究,对揭示气候变化对作物生长的影响及其机制具有重要作用和意义。本文分别介绍了作物水分利用效率对CO2浓度和温度升高的响应研究进展,CO2浓度和温度升高对作物水分利用效率的协同效应,以及CO2浓度与温度升高对作物水分利用效率影响的实验研究方法,并提出了作物水分利用效率对CO2浓度和温度升高响应研究仍需要解决的几个关键问题:①多因子协同效应;②不同品种的响应差异;③不同尺度水平的响应过程;④作物水分利用效率对气候变化的适应性。     

中国气候变化的植物信号和生态证据

全球平均气温上升、降水格局变化、极端天气事件发生的频率和强度增大等气候变化现象已经对陆地生态系统产生了影响,物种、群落和生态系统响应于气候变化而发生的改变,可以作为气候变化的间接生物学和生态学证据,对未来气候变化的影响评价有重要的价值,尤其是对减缓和适应全球气候变化的"地球系统科学"研究以及可持续生态系统管理与发展对策的制订,具有重要的意义。在国际气候变化的生物学证据研究的大背景下,总结了中国陆地生态系统响应过去气候变化的植物学信号和生态学证据:(1)物种水平:气候变暖导致中国33°N以北大部分地区植物春季物候期包括萌芽、展叶、开花期等显著提前,植被生长季延长;(2)群落水平:群落物种组成和分布发生改变,主要表现在长白山等高山群落交错带物种组成和林线位置的变化以及青藏高原高寒草甸的退化;(3)生态系统水平:全国总体植被盖度增加,植被活动加强,生产力增加;北方和西部地区农业植被的耕作制度、种植结构、耕种面积和产量发生变化,东北地区水稻种植面积和产量增加,但全国大部分地区农作物产量和温度呈负相关,这将威胁到未来的粮食安全。     

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.     

Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed: (1) the interactions between climate change and land surface phenology dynamic; (2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums; (3) the contributions of crop physiology characteristic changes to land surface biophysical process; (4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.     

农业物候动态对地表生物物理过程及气候的反馈研究进展（英文）

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed:(1) the interactions between climate change and land surface phenology dynamic;(2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums;(3) the contributions of crop physiology characteristic changes to land surface biophysical process;(4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.     

基于蒙特卡洛生存分析探究东北森林物候的影响因素

植被是生态环境变化的指示器,分析植被物候的影响因素不仅有助于气候变化分析,提高区域气候模式的模拟精度,而且对于准确评估植被生长趋势、生产力以及全球碳收支均具有重要意义。基于遥感的植物物候监测已取得了长足的发展和进步,但当前利用大范围、长时间序列的遥感数据分析植被物候影响因素的研究尚不多,采用线性回归模型对非线性的植被物候影响因素进行分析可能存在偏误。因此,本文提出一种基于蒙特卡洛模拟的生存分析方法,对东北森林物候的影响因素进行量化分析。首先利用东北森林地区1982-2009年间AVHRR GIMMS NDVI数据,应用双Logistic曲线拟合方法对植被春季返青期（SOS）、秋季落叶期（EOS）及植被生长期（GSL）进行提取;然后基于蒙特卡洛模拟和生存分析构建植被物候影响因素分析模型;最后运用所构建模型探讨了东北森林区春季返青期、秋季落叶期的可能影响因素。结果发现：温度、降水和风力对中国东北森林关键物候期有一定影响,其中温度是春季返青期和秋季落叶期的最主要驱动因素,长期平均温度比短期内的温度突变对物候影响更显著,落叶期前的风速增加有可能使落叶时间提前;除了环境因素,春季返青早的年间秋季落叶倾向于更晚。研究表明,结合蒙特卡洛方法的生存分析可以较好地对物候期的影响因素进行定量分析,可为物候现象的归因分析提供一种新的方法。     

Changes in climatic variability and maize yield inNortheast China

1IntroductionTheconventionalassessmentSonthepossibleimPactsofclilnateAngehaveahrpothesisofkeepingclimaticvariabilityinaccordtviththatofpresentclimateduetolackofavailableinformationchangesinclimaticvariabiiltyFixedtemperaturechangeandfixedprecipitationadjustingfactorsassumedorderivedffomGCMs'shoulahonareaddedtotheobserveddailytemperatUrormulhpliedwithhiStoricaldailypreeipitahonrespechvelyinthesestUdiest11.Alti1oughthereareanUInerofapparentdeficienciesinGCMs,includinglowertemporalandspatia…     

Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province,China

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a^-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a^-1<θ<1.7 d·10a^-1, θ is the change slope of maize phenology). The length of vegetative period (VPL) (from emergence to tasseling) was shortened by 0.9 d·10a^-1, while the length of generative period (GPL) (from tasseling to maturity) was lengthened by 1.7 d·10a^-1. The growing season length (GSL) (from emergence to maturity) was lengthened by 0.4 d·10a^-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days (GDD) (p<0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.