温室黄瓜生育期模拟模型的研究

根据黄瓜（Cucumis sativus）发育的光温反应过程,建立了基于生理发育时间的黄瓜生育期模拟模型,并利用不同品种的试验资料对模型进行了检验。结果表明,黄瓜从播种到第一批瓜成熟需积累生理发育时间30d,播种—幼苗、幼苗—伸蔓、伸蔓—开花、开花—结瓜、结瓜—成熟所需的生理发育时间分别为3、11、9、5、2d。发芽期、幼苗期、伸蔓期、开花期、结瓜期等各生育期持续时间的模拟值与实际观测值的回归估计标准误差（root mean squared error;RMSE）分别为0、2．6、1．7、0．8、2．1d,从播种到第一次采收的模拟值与观测值的RMSE为1．4d。而用有效积温法对发芽期、幼苗期、伸蔓期、开花期、结瓜期等各生育期持续时间的模拟值与实际观测值的RMSE分别为0．7、10．0、5．7、2．4、2．5d,从播种到第一次采收的模拟值与观测值的RMSE为22．0d。本模型比用有效积温法能更准确地预测黄瓜各个生育期的起止日期和黄瓜的收获期。     

基于水热因子的玉米物候模拟

对锦州14 a玉米各生育期特征及其与气候因子的关系分析表明：同品种玉米的物候期相近,变化在2 d左右,而吐丝期到成熟期所需天数变化较大,为6 d或以上;玉米各生育期的影响因子不同,气温与湿度对玉米出苗期、三叶期和七叶期的影响显著,播种期到七叶期的积温占整个生育期积温的20%,并与同期的空气湿度累积量显著二次曲线相关（R 2=0.91）。积温与空气湿度累积可较好地模拟玉米播种期至七叶期和玉米的总生育期。     

作物发育期积温计算方法及其稳定性

以山西介休农业气象试验站冬小麦京冬6号从出苗至三叶期为研究对象,比较3种模式的计算方法,分析期间日均温及积温与发育天数的关系,得到冬小麦在此期间发育期天数变化幅度最大。3种模式得到的有效积温变异系数都大于活动积温,活动积温中又以模式2稳定性最大。建议以模式2计算活动积温来模拟冬小麦出苗至三叶期的模拟。从统计角度分析,日均温与发育天数存在显著的线性负相关关系,但以日均温模拟发育进程是不准确的。模式3对温度的订正方法会产生日均温和积温偏离现象,日最高气温或最低气温高于上限温度时,订正结果将低于实际;日最高气温或最低气温低于上限温度时,订正结果将高于实际。作物模型中计算日均温和积温时,不宜采用模式3的订正方法。     

东北春玉米非线性积温模型参数改进

结合我国东北地区春玉米生长发育的实际情况,以观测年份较多、观测地点较广为原则选取4个春玉米品种,分别为东农248、龙单13、四单19和丹玉13,利用生长发育观测资料和同期气象观测资料,判断4个玉米品种的相对熟型并对沈国权非线性积温模型（简称NLM）进行参数拟合,讨论参数的生物学意义及其与品种熟型的关系,对NLM进行有效改进及验证。结果表明:4个春玉米品种NLM均不存在无效参数,参数K与参数Q存在显著的相关性,说明K可能仅是一个统计参数,没有明确的生物学意义;积温在品种间存在显著差异,全生育期模型参数Q与多年站次平均有效积温或活动积温有较好的相关性,由于不同的积温意味着不同的玉米品种熟型,说明Q与玉米品种的熟型有关,将模型参数Q和K用反映玉米品种熟型的参数（有效积温、活动积温）表示,建立了适用于不同品种的通用积温模型,取得较好的应用效果。     

3种光温指标在模拟设施黄瓜生长发育中的应用与比较

2011年9～12月间,以黄瓜“津优1号”（ Cucumis sativus linn. cv. Jingyoul ） 为试材,在南京信息工程大学试验温室进行分批栽培试验,测定温室气象要素和作物数据,分别用活动积温（AAT,Ac-tive accumulated temperature ）、有效积温（ EAT, Effective accumulated temperature） 和辐热积（TEP,Thermal effectiveness and photosynthesis active radiation）3种光温指标模拟温室黄瓜植株叶面积、株高和生育期,并利用独立试验数据对各个模型进行验证。结果表明：用辐热积指标分别模拟黄瓜各生育期（出苗期、开花期、坐果期、果实膨大期、成熟期）距播种日期的天数,其相对标准误差（RMSE）分别为0d,3d,4d,5d,4d,小于活动积温法（1d,6d,8d,11d,11d）和有效积温法（0d,4d,3d,8d,10d）。利用辐热积指标模拟叶面积和株高的相对标准误差（RMSE）分别为43．0cm^2和4．3cm,决定系数（R^2）分别为0．98和0．98,而用活动积温和有效积温指标模拟黄瓜单株叶面积的相对标准误差（RMSE）分别为61．3cm^2和54．6cm^2,模拟株高的相对标准误差（RMSE）分别为9．8cm和7．5cm。比较结果显示利用辐热积指标模拟温室黄瓜生育期、株高和叶面积的精度明显高于活动积温和有效积温,该研究为温室黄瓜生长指标和各生育期的预测以及环境调控提供参考。     

沈阳市近50a10℃活动积温变化特征分析

通过对沈阳近半个世纪10℃活动积温不同尺度的年际间、年代际间、极值等数量变化、升幅变化、降幅变化、形态变化的特征分析,得出了若干具有农业生物学意义的、带有标识性意义的不同级别的气候特征值.首次详细地分析了沈阳不同等级的积温数量、积温振幅、积温极值等,从宏观趋势形态特征到微观数值解析,解释了具有不同农业潜力、不同热量潜势及不同类型、不同气候组合的、多极化的高热量年、低热量年及他们的变化特点.结果表明:在50 a的长时间序列中,1998年为典型的高热量年,当年的积温量值4 010.6℃·d为历史第一,积温正距平值502.6℃;积温垂直升幅635.9℃为历史第一;积温升幅极差598.7℃·d为历史第一;当年创12万hm2水稻平均产量7 935 kg/hm2的大丰收记录.1972年为典型的低温冷害年,其积温量值2 923.8℃·d为历史最低,积温负距平值584.2℃;积温垂直降幅684.9℃·d为历史最低;积温降幅极差647.3℃·d为历史第一.当年全市大面积水稻大歉收,平均只达2 954 425 kg/hm2.     

积温对比法在鸭梨始花期预报中的应用

利用2012—2018年鸭梨花芽发育实景观测照片,精准判定每个鸭梨花芽发育物候期节点发生时间,以此为依据统计鸭梨花芽每个发育物候期的气象要素数据,以物候期为单位分析气象影响因子对花芽发育过程的影响。研究表明:温度在鸭梨花芽发育各阶段起主导作用,筛选出鸭梨花芽萌发到始花、开绽到始花、露蕾到始花3个时段日平均气温≥0℃活动积温和≥3℃有效积温,作为制作鸭梨始花期预报的积温指标计算鸭梨开花日期,得到"积温对比预报法";经2016—2018年应用检验:预报时效10～12d时预报结果与鸭梨开花实况误差在1～2d以内,预报时效7d时预报结果与鸭梨开花实况完全吻合。本研究克服了传统植物花期预报研究因花前物候资料匮乏、不能进行花前发育期分析的缺陷,并把"中长期天气预报产品"引入了花期预报方法的使用,为植物花期预报研究方法提供了新思路。     

沈阳市近50a 10℃活动积温变化特征分析

通过对沈阳近半个世纪10℃ 活动积温不同尺度的年际间、年代际间、极值等数量变化、升幅变化、降幅变化、形态变化的特征分析,得出了若干具有农业生物学意义的、带有标识性意义的不同级别的气候特征值。首次详细地分析了沈阳不同等级的积温数量、积温振幅、积温极值等,从宏观趋势形态特征到微观数值解析,解释了具有不同农业潜力、不同热量潜势及不同类型、不同气候组合的、多极化的高热量年、低热量年及他们的变化特点。结果表明:在50 a的长时间序列中,1998年为典型的高热量年,当年的积温量值4 010.6℃·d为历史第一,积温正距平值502.6℃;积温垂直升幅635.9℃为历史第一;积温升幅极差598.7℃·d为历史第一;当年创12万hm²水稻平均产量7 935 kg/ hm²的大丰收记录。1972年为典型的低温冷害年,其积温量值2 923.8℃·d为历史最低,积温负距平值584.2℃;积温垂直降幅684.9℃·d为历史最低;积温降幅极差647.3℃·d为历史第一。当年全市大面积水稻大歉收,平均只达2 954 425 kg/hm²。     

鲁西南典型植物春季物候期的模拟研究

利用2006~2014年鲁西南地区菏泽、曹县和济宁3个国家级农业气象观测站气象及物候观测资料,采用国际上流行的Forc TT积温模型模拟了当地常见、广泛分布的9种木本植物和4种草本植物展叶始期和开花始期的最佳积温开始日期和基础温度。结果表明:(1)模拟的木本植物展叶始期的最佳积温累积开始日期主要为1月1日,最佳基础温度主要为1℃。开花始期模拟的最佳积温累积开始日期不同木本物种差异较大,开花期较早(3月)的毛白杨、旱柳和榆树的最佳积温累积开始日期为2月1日,最佳基础温度为3℃,开花期集中在4~6月的物种的最佳积温累积开始日期为3月1日,基础温度在3~5℃之间,开花期最晚(7月)的槐树的最佳积温累积开始日期为4月1日,基础温度为4℃;(2)就草本植物而言,展叶期较早(2~3月)的车前、苍耳和芦苇模拟的最佳积温累积开始日期为1月1日,最佳基础温度为1~2℃,展叶较晚(4月)的莲模拟的最佳积温累积开始日期为2月1日,最佳基础温度为3℃。开花期较早(4~6月)的车前和苍耳其开花始期模拟的最佳积温累积开始日期为2月1日,最佳基础温度为3℃,开花较晚(7~9月)的莲和芦苇模拟的最佳积温累积开始日期为4月1日,最佳基础温度分别为-1℃和2℃;(3)展叶始期和开花始期模拟的平均误差在2 d左右。由此可知,无论是木本植物还是草本植物,Forc TT积温模型对展叶和开花始期的模拟效果均较好,预测值和观测值间的相关系数普遍在0.90以上,达高度相关。     

春玉米积温稳定性及在发育期预报中的应用

修正已有积温模型,提高积温稳定性,对积温指标更好地应用于农业生产实践有重要意义。基于东北地区春玉米的生长发育情况,综合分析影响积温稳定性的气象因素,订正常用的活动积温模型。在进行积温稳定性评价基础上,将订正模型应用于春玉米的发育期预报中。结果表明:温度条件是影响积温稳定性的最主要因素,基于温度因子得到的订正模型,在出苗-抽雄阶段和抽雄-成熟阶段较原模型年际间变异系数分别平均减小了0.42%和1.42%,订正模型计算的积温稳定性更好。分别利用1981-2010年及2011-2017年资料进行回代及预报检验,发现订正模型对抽雄期的预报结果改进不明显,对成熟期的预报结果误差较原活动积温模型在回代及预报检验中分别降低了3.78 d和1.1 d。     

气候适宜度在华北冬小麦发育期预报中的应用

利用华北地区39个代表站,1971-2011年逐日最高温度、最低温度、降水量、日照时数、土壤水分、冬小麦发育期和农业气象指标等资料,在考虑_十壤水分和降水对冬小麦不同生长发育阶段的不同影响基础上,建立了冬小麦水分适宜度计算方法,结合温度适宜度和日照适宜度,构建了冀、鲁、豫冬小麦气候适宜度评价模型。以冬小麦气候适宜度为预报因子,建立了冀、鲁、豫3省9个区域冬小麦发育期预报模型。模型回代检验结果表明,不同区域模型的模拟天数与实际天数的平均误差均在1-2天之间,不同发育阶段模型的模拟天数与实际天数的平均误差均在4天以内;模型预报检验表明,各区域不同发育阶段的预报天数与实际天数的误差大多数在3天以下。     

基于水稻生长模型的气象影响评价和产量动态预测

在对国际先进的水稻生长模型ORYZA2000进行模型调试、验证, 实现本地化的基础上, 以双季稻发育速率参数为主, 结合地形、气候、水稻熟性分布和当地生产实际, 将江南双季稻区按发育参数划分为7个区域, 实现了ORYZA2000模式在我国江南双季稻地区的区域应用。利用该模型进行了不同年份气象条件影响定量评估的应用试验, 评价结果与实际符合, 定量客观。探讨了利用机理性作物生长模式动态预测产量的方法。通过建立不同发育期的水稻模拟生物量与相对气象产量的相关统计模型, 结合趋势产量预测, 实现了地区级双季稻不同发育期的产量动态预测。外推检验结果表明, 各地早晚稻不同发育期的产量动态预测模型平均误差为4.8%~6.1%, 可初步用于业务。     

河南省稻麦类作物对气候变化的响应

小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下生育期和产量的变化。结果表明:冬小麦全生育期长度呈缩短趋势,但播种-越冬天数平均每10 a增加1.7 d,开花到乳熟天数平均每10 a增加2-4 d,返青后各生育期均表现出不同程度的提前;水稻各生育期均有不同程度的提前,尤其是拔节期以前,分蘖前的生育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。     

Effects of climate change on the phenology of <Emphasis Type="Italic">Osmia cornifrons</Emphasis>: implications for population management

The phenology of many ecological processes including pollination service is modulated by surface air temperature, making them potentially sensitive to climatic change. The Japanese hornfaced bee, Osmia cornifrons (Hymenoptera: Megachilidae), was introduced into the USA in the 1970s and has been used as a key pollinator of spring blooming fruit crops such as apple and blueberry. This study examined the effects of future climate change on three key phenological events of O. cornifrons: date for adult emergence (female and male) in spring, date for completion of egg and larval development, and duration for the development in the Eastern USA. We used daily temperature data obtained from 21 models in Coupled Model Intercomparison Project Phase 5 for 2006–2100 under the two future climate scenarios of Representative Concentration Pathways (RCPs 4.5 and 8.5). We estimated the Julian dates (JDs) of spring emergence and development of O. cornifrons using the phenological parameters derived from temperature-dependent biophysical models. The JDs for the bee emergence and development are projected to be significantly advanced in the Eastern USA under the RCP 4.5 and 8.5 scenarios. The number of days for bee development is projected to be longer in the southern region (+?0.57 days/decade) and shorter in the central (??0.27 days/decade) and northern (??0.65 days/decade) regions of the Eastern USA (all the p values <?0.01). The significantly longer duration of bee development under future climate change could pose a risk to the bee due to the longer period of being exposed to its pests. Implications for management of O. cornifrons population were discussed in this article.     

Assessment of the impact of climate change on the olive flowering in Calabria (southern Italy)

In phenological studies, plant development and its relationship with meteorological conditions are considered in order to investigate the influence of climatic changes on the characteristics of many crop species. In this work, the impact of climate change on the flowering of the olive tree (Olea europaea L.) in Calabria, southern Italy, has been studied. Olive is one of the most important plant species in the Mediterranean area and, at the same time, Calabria is one of the most representative regions of this area, both geographically and climatically. The work is divided into two main research activities. First, the behaviour of olive tree in Calabria and the influence of temperature on phenological phases of this crop are investigated. An aerobiological method is used to determine the olive flowering dates through the analysis of pollen data collected in three experimental fields for an 11-year study period (1999–2009). Second, the study of climate change in Calabria at high spatial and temporal resolution is performed. A dynamical downscaling procedure is applied for the regionalization of large-scale climate analysis derived from general circulation models for two representative climatic periods (1981–2000 and 2081–2100); the A2 IPCC scenario is used for future climate projections. The final part of this work is the integration of the results of the two research activities to predict the olive flowering variation for the future climatic conditions. In agreement with our previous works, we found a significant correlation between the phenological phases and temperature. For the twenty-first century, an advance of pollen season in Calabria of about 9?days, on average, is expected for each degree of temperature rise. From phenological model results, on the basis of future climate predictions over Calabria, an anticipation of maximum olive flowering between 10 and 34?days is expected, depending on the area. The results of this work are useful for adaptation and mitigation strategies, and for making concrete assessments about biological and environmental changes.     

Climatic conditions and their impact on viticulture in the Upper Moselle region

Climate parameters, especially temperature, sunlight, and precipitation, play a decisive role in growing and maturing processes. The aim of this study is to investigate the relationship between climate variability and variations in phenological events in viticulture. Long time series of daily meteorological observations are used to quantify these relations. The primary aim is to predict the date of phenological events by relationships between plant morphology and environmental conditions. Causal relationships between environment and internal activities of the vine (phytochemistry, cellular interactions, molecular and cell biology) are not our focus. The dates of the phenological events are important for planning treatments in the vineyards like pest management, for predicting the duration of the ripening phase and estimating the quality of the grapes and the vintage. The focus is layed on the region of the Upper Moselle, especially the Luxembourgian viticulture. First the regional climate and the phenological states of different vine varieties during the time period 1951?C2005 are analysed. Significant trends are detected in annual, spring and summer temperatures. Vine phenology is also found to have changed significantly; budburst date and flowering events occur earlier by about two weeks. In a second step, relationships between phenological events and climate parameters are used to develop a prediction model. The parameterisation used in this study is based on a linear multiple regression method with forward and backward steps. The predictors tested are mainly temperature means for different time periods or temperature derived indices. In addition precipitation and sunshine duration for different time periods are evaluated, but only the temperature based predictors showed sufficient skill. For the budburst event, the significant predictors are the accumulated degree days in March, the mean daily maximum temperature in April and the accumulated frost days from January to March. The flowering event is best predicted by the accumulated degree days in May and April, the mean daily maximum temperature in June, and the date of the budburst event. Depending on the vine variety and the phenological event, the model explains 80?C89% of the variance and has a correlation coefficient above 0.90 with the observations.     

河南省稻麦类作物对气候变化的响应

小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES 小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下发育期和产量的变化。结果表明：冬小麦全育期长度呈缩短趋势,但播种-越冬天数平均每10年增加1.7天,开花到乳熟天数平均每10年增加2-4天,返青后各发育期均表现出不同程度的提前;水稻各发育期均有不同程度的提前,尤其是拔节期以前,分蘖前的发育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。     

Plant Phenological Anomalies in Germany and their Relation to Air Temperature and NAO

This paper analyses long-term (1951–2000) phenological observations of20 plant seasonal phases recorded within the phenological network of the German Weather Service in relation to climate data and NAO. Phenological inter-annual variability and temporal trends were determined by using mean anomaly curves for Germany. For all phases, the mean trends derived by this method are similar to German averages of linear trends of single station records. Trend analysis using anomaly curves appears to be effective in relating seasonal phenological trends to climate or satellite data: Spring and summer phenological anomalies, such as leaf unfolding and flowering of different species, strongly correlate with temperature of the preceding months (R² between 0.65 and 0.85, best one-variable model) andtheir onsets have advanced by 2.5 to 6.7 days per ° C warmer spring. Fruit ripening of Sambucus nigra and Aesculus hippocastanum, keyphenophases of early and mid autumn, correlate well with summer temperature (R² 0.74 and 0.84) and also advance by 6.5and 3.8 days per ° C (April–June). But the response of autumn colouringto warmer climate is more complex because two opposing factors influence autumn colouring dates. Higher spring and early summer temperatures advance leaf colouring, whereas warmer autumn temperatures delay leaf colouring. The percentage of variance explained by temperature (R² 0.22 to 0.51,best one-variable model) is less than for spring and summer phases. The length of the growing season is mainly increased by warmer springs (R² 0.48to 0.64, best one-variable model) and lengthened by 2.4 to 3.5 days/° C (February–April). The North Atlantic Oscillation Index (NAO) of January–March correlates with spring phenological anomalies(R² 0.37 to 0.56, best one-variable model), summer to mid autumn phases respond to NAO of February–March (R² 0.23 to 0.36) (both negativecorrelations). Leaf colouring is delayed by higher NAO of (August) September (R² 0.10to 0.18). NAO of January–February explains 0.41 to 0.44% of thevariance of the length of the growing season.     

BP神经网络在油菜花期预报中的应用

建立花期预报模型,发布观赏性植物的精准花期预报,为旅游活动提供重要参考依据,已经成为气象服务领域一个新的发展方向。为了解高淳旅游区油菜花期的变化规律,探索其预报方法,指导高淳油菜花节旅游活动,根据1985—2010年高淳站日最高气温、日最低气温、日平均气温、日降水量、日日照时数、日平均5 cm地温、日平均相对湿度和日小型蒸发量等气象观测数据,利用主成分分析法,得到其与油菜花期相关系数较大的3个主成分,即温度因子、天气因子和辐射因子,以此为输入因子,建立基于BP神经网络的油菜花期预报模型,探讨BP神经网络在花期预报领域的应用。结果表明,传统的有效积温方法预报结果与实际开花期平均相差4.25天,BP神经网络方法预报结果与实际开花期平均相差1.5天,与有效积温预报油菜花期的方法相比,BP神经网络技术具有预测结果准确率高和操作简单等特点,在花期预报领域具有广阔的应用前景。     

Inter-Annual Variability and Decadal Trends in Alpine Spring Phenology: A Multivariate Analysis Approach

Plant phenological observations are of increasing value as indicators of climate change and variability. We developed a robust multispecies estimate for Swiss Alpine spring phenology for the period 1965–2002 by applying empirical orthogonal function (EOF) analysis on a combination of 15 spring phases. The impact of climate parameters such as temperature and precipitation on the phenological development was investigated using a multivariate statistical model. This multispecies estimate proved to be a good approach to assess the pattern of spring appearance during the last 40 years. It revealed an earlier onset of spring in recent years, mainly since 1988 when a clear shift in spring appearance occurred. The mean overall trend of 1.5 days per decade was clearly driven by winter and spring temperatures whereas precipitation showed no significant influence. The dominant EOF patterns suggested a general climate forcing for the observed inter-annual variability independent of single plant phases. A more regional phenology signal was found in the second EOF mode, indicating slightly weaker phenological trends in southern Switzerland as well as in higher altitudes. Both, temperature and precipitation contributed to this pattern significantly. Analysis of single phases confirmed the pattern of the multispecies estimate. All species showed trends towards earlier appearance ranging from −1 to −2.8 days per decade and the appearance dates had a very high covariance with temperature.