Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction, i.e., the reproduction of short-term(several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5) dataset for the period of 1850–2000, the Climatic Research Unit(CRU) dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR) of China during the period of 1961–2011, we calibrated and validated monthly average temperature(MAT) and monthly accumulated precipitation(MAP) in the TMR using the delta, physical scaling(SP) and artificial neural network(ANN) methods. Performance and uncertainty during the calibration(1971–1999) and verification(1961–1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty(negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term(several decades) regional climate reconstruction and longer-term(100 a or more) assessments of regional climate change.     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.     

夏玉米产量时空变化及气候年型分析

定量分析夏玉米同一品种产量及产量构成要素时空变化,探讨造成产量时空差异的气候年型组合变化特征。基于2004～2013年夏玉米种植区郑单958多点田间试验数据分析表明,夏玉米区域平均产量为9 055 kg/hm~2,年际差为1 635 kg/hm~2,变幅为18.1%;地点差4 258 kg/hm~2,变幅为47.1%。夏玉米区域平均千粒重为313 g,年际变幅为13.1%;地点变幅为27.8%。夏玉米区域平均穗粒数为479,年际变幅为18.0%,地点变幅为38.7%。千粒重的增加导致夏玉米产量显著增加。穗粒数显著降低和时空差异大是造成产量波动和时空差异变幅大的主要原因。夏玉米产量和产量构成要素,低产点受各气候要素变化的影响显著;平产点受温度和日最高温度大于33℃的天数影响显著;高产点受降水影响显著。     

Impact of waterlogging and temperature on autumn growth,hardening and freezing tolerance of timothy (Phleum pratense)

Precipitation has generally increased in Norway during the last century, and climate projections indicate a further increase. The growing season has also become longer with higher temperatures, particularly in autumn. Previous studies have shown negative effects of high temperatures and, depending upon temperature conditions, contrasting effects of waterlogging on hardening capacity of timothy. We studied effects of waterlogging on seedlings of timothy (Phleum pratense, cv. Noreng) under three pre-acclimation temperatures: 3°C, 7°C, 12°C, and in autumn natural light in a phytotron at Holt, Tromsø (69°N). After temperature treatments, all plants were cold acclimated at 2°C for three weeks under continued waterlogging treatments. Freezing tolerance was determined by intact plants being frozen in pots at incremental temperature decreases in a programmable freezer. Waterlogging resulted in a higher probability of death after freezing, and a significantly reduced regrowth after three weeks at 18°C, 24 hrs light in a greenhouse. Increasing pre-acclimation temperatures also had a clear negative effect on freezing tolerance, but there was no interaction between temperatures and waterlogging. The results indicate that waterlogging may have negative implications for hardening of timothy and may contribute to reduced winter survival under the projected increase in autumn temperatures and precipitation.     

气候变化对椰心叶甲在中国适生区的影响

为明确椰心叶甲在中国的潜在适生区,降低椰心叶甲入侵造成经济和生态损失,本研究以CLIMEX软件和椰心叶甲的生物学资料为依据,结合ArcGIS反距离加权插值分析功能,利用历史气候数据（1981—2010年）和模拟未来气候数据（2071—2100年）,分析气候变化对椰心叶甲在中国的潜在适生区的影响。结果表明：在历史气候条件下,椰心叶甲主要分布于中国的南部地区,高度适生区分布面积最大。在未来气候条件下,椰心叶甲在国内适生区总面积增加,适生区具有北移的趋势。本研究可为椰心叶甲的管理防控提供一定的理论依据。     

四川冬春季参考作物蒸散量时空变化及其成因

为深入认识四川冬春季参考作物蒸散量(ET₀)的变化特征,利用1980—2016年四川35个气象站的逐日气象观测资料,采用泰森多边形、气候倾向率和克里金空间插值等方法对其冬春季ET₀的时空变化特征进行分析,并通过敏感性和贡献率分析了ET₀的变化成因。结果表明:ET₀的年代际变化呈先降后增的趋势,空间上呈明显的西南高东部低的分布特征,且高值区范围持续扩大,低值区范围波动缩小。ET₀的年际变化呈上升趋势,春季ET₀气候倾向率和空间差异明显大于冬季,且ET₀高值区与低值区空间分布受海拔高度影响明显。ET₀的同一日多年平均值自初冬至初春逐渐上升,1月22日—5月2日仅有8 d的ET₀值低于多年日平均值,具有明显连续的高值时段。ET₀对日照时数的变化最敏感,其次是对相对湿度与平均气温,对三者均呈高敏感性。平均气温的正贡献率是引起ET₀变化的主导因子,其次是相对湿度。研究时段内平均气温的升高对ET₀的正效应和相对湿度的降低对ET₀的负效应,超过了日照时数减少对ET₀的减少效应,导致四川地区冬春季ET₀呈上升趋势。     

北方草地及农牧交错区草地植被碳储量及其影响因素

【目的】 草地生态系统在全球碳平衡中有重要的意义,草地植被碳库及其变化机制研究是植被生态学的重要命题。本文研究北方草地和农牧交错区草地植被碳密度及其空间格局,解析不同区域草地植被碳密度的关键影响因素,分析了气候、土壤、放牧等因素对地上地下植被碳库的相对贡献。【方法】 基于2002—2009年北方草地及农牧交错带草地植被调查数据,结合同期MODIS/NDVI遥感影像和1﹕100万草地类型图,建立了我国主要草地类型的生物量估算模型;整合野外考察数据和前人研究结果,探讨了研究区地上地下生物碳库及其空间格局;基于研究区255个县级行政单元,分析了不同类型草地植被碳库与气候要素、土壤要素及家畜承载量的关系,应用一般线性模型（GLM）解析了不同影响因素对草地碳密度的相对贡献。【结果】 （1）北方草地与农牧交错区草地地上平均生物碳密度为36.9 g C·m^-2,地下生物碳密度为362.9 g C·m^-2,地下生物碳密度高于地上10倍,均呈从东到西递减的趋势,频率分布图基本服从对数正态分布,不同草地类型的生物碳密度存在明显差异;（2）整个研究区及草原亚区、荒漠亚区、农牧交错亚区内,地上生物量与年降水量（MAP）呈极显著正相关、与年均气温（MAT）均呈极显著负相关,与土壤黏粒含量（Clay%）呈显著正相关、与土壤砂粒含量（Sand%）呈显著负相关,整个研究区家畜承载量与草地地上生物量之间呈极显著正相关;（3）一般线性模型（GLM）分析结果表明,年平均降水量（MAP）、年均气温（MAT）、土壤黏粒含量（Clay%）、放牧强度对地上生物量空间变异的解释率分别达到29.6%（P<0.001）、5.8%（P<0.001）、0.8%（P<0.05）、1.3%（P<0.001）;地下生物量的空间变异主要来自于年降水量（MAP）、年均气温（MAT）、土壤砂粒含量（Sand%）,对方差的解释率分别达到12.1%（P<0.001）、6.8%（P<0.001）、1.9%（P<0.005）,放牧强度没有明显贡献。【结论】 气候条件尤其是年降水量是草地生物量碳库的主要影响因素,但对地上生物量影响更为明显;土壤质地对植被生物碳库也有显著贡献,尤其对地下生物量的影响更加显著;放牧强度只能解释地上生物量变化的1.3%、对地下生物量没有显著贡献,这一发现意味着气候对生物量碳库的贡献远大于放牧影响。     

半干旱牧区天然打草场生产力时空变化及对气候响应分析

【目的】 定量评估半干旱牧区天然打草场的生产能力,分析天然打草场的退化程度,明确气候因子对打草场生长过程的影响。【方法】 利用Miami和Tharnthwaite Memorial模型计算2000—2017年半干旱牧区天然打草场气候生产潜力,并结合近18年的中分辨率成像光谱仪（MODIS）净初级生产力（NPP）产品（MOD17A2H）进行分析。【结果】 2000—2017年半干旱牧区天然打草场实际生产力与潜在生产力均随降水增加呈上升趋势,天然打草场18年平均实际生产力和潜在生产力分别为295.24和557.79 g C·m^-2·a^-1。按不同草地类型分析,气候生产潜力与实际生产潜力均以草甸草原最高,分别为589.68 g C·m^-2·a^-1和349.78 g C·m^-2·a^-1,山地草甸的气候生产潜力最低,为518.72 g C·m^-2·a^-1,而实际生产潜力以典型草原最低,仅为269.52 g C·m^-2·a^-1。从变异系数来分析,气候生产潜力与实际生产力均以草甸草原最稳定。从年际变化率分析,草甸草原的气候生产潜力的上升速率最高,为6.30 g C·m^-2·a^-1,实际生产力以山地草甸上升速率最高,为4.44 g C·m^-2·a^-1。实际生产力对降水的响应高于温度,其中95.88%的打草场与降水呈显著正相关关系,与温度呈负相关的区域仅占总面积的5.70%,且不同草地类型的实际生产力均与降水在P<0.001水平呈显著正相关关系。【结论】 天然打草场气候生产潜力呈由西向东递增的地带性规律,而实际生产力受水热条件的影响,以大兴安岭为中心向东西两麓逐渐递减,其对降水的响应高于温度,水分条件是该区植被生长的限制因子;年均气候资源利用率的分布规律与实际生产力相同,平均气候资源利用率为55.09%;以草甸草原打草场的气候资源利用率最高,高达60.34%,同时也是退化速度最高的草地类型。     

水稻拔节期和抽穗期低温对稻米品质影响

【目的】为了探讨低温冷害对水稻品质的影响,以便为气候变化背景下辽宁地区水稻的高效栽培和品质认证提供理论依据。【方法】以水稻90-35为供试品种,分别于拔节期和抽穗期通过TRP-1000D型人工智能气候箱进行不同低温处理(比外界低5℃和低3℃,均持续5 d),以正常栽培管理作对照,5个处理,分别记为CK、A1、A2、B1、B2,分析拔节期和抽穗期不同等级低温胁迫处理对水稻的营养品质、研磨品质和外观品质的影响。【结果】低温胁迫下90-35水稻的蛋白质含量、直链淀粉含量较CK显著增加,处理A1、A2、B1、B2的蛋白质含量分别比CK增加3.45%、1.15%、6.90%、8.05%,除处理B1外直链淀粉含量分别比CK增加1.75%、0.44%、0.44%;脂肪酸含量和精米率较CK显著减少,处理A1、A2、B1、B2的脂肪酸含量分别比CK减少17.75%、7.5%、25%、11%,精米率分别比CK减少2.1%、6.95%、0.22%、7.5%。拔节期低温胁迫下糙米率和垩白粒率显著减少,处理A1、A2的糙米率分别比CK减少0.73%、1.09%,垩白粒率分别比CK减少33.3%、22.2%;抽雄期低温胁迫下糙米率和垩白粒率显著增加,处理B1、B2的的糙米率分别比CK增加0.6%、3.02%,垩白粒率分别比CK增加255.6%、133.3%,即低温胁迫使其营养品质和研磨品质中的精米率受到负面影响,而拔节期适当低温胁迫处理对其研磨品质中的糙米率和外观品质有益。【结论】水稻90-35在不同生育时期经受不同低温胁迫处理后,水稻的营养品质、研磨品质和外观品质均受到不同程度的影响。     

未来气温和降水变化对山西冬小麦产量的影响

【目的】冬小麦是山西省重要的粮食作物,气候变化对冬小麦产量影响显著。利用模型模拟评估气候变化对山西省冬小麦产量的影响,为山西省冬小麦种植规划提供重要科学依据。【方法】利用山西省 2017—2018 年气象资料和 2018 年县级冬小麦产量数据,采用 DNDC 区域模拟方法,对山西省冬小麦种植区单产进行模拟和验证;模拟未来 8 种气候变化情景（温度上升 1、2℃,降水减少 20%、10% 以及温度和降水耦合）对冬小麦产量产生的影响。【结果】DNDC 模型可以较好模拟出山西省冬小麦产量整体水平（4 335.6 kg/hm2）,总体平均误差为 4.63%,空间上的模拟误差主要由于山西省地形和气候差异导致。【结论】未来气候变化背景下,不同程度的增温对产量的影响不一,在温度平均升高 1℃情况下,山西省冬小麦单产下降 4.60%,而气温上升 2℃情景下,单产增加 16.44%;降水减少 10% 和 20% 情景下,产量均降低,说明水分依然是制约冬小麦产量的重要因子;但在增温和降水减少的耦合作用下产量增加 7.41%~15.84%。未来还需根据山西省种植特点,从轮作角度评估气候变化对农业的影响。