Abrupt temperature change and a warming hiatus from 1951 to 2014 in Inner Mongolia,China

An abrupt temperature change and a warming hiatus have strongly influenced the global climate.This study focused on these changes in Inner Mongolia, China. This study used the central clustering method, Mann-Kendall mutation test and other methods to explore the abrupt temperature change and warming hiatus in three different temperature zones of the study region based on average annual data series.Among the temperature metrics investigated, average minimum temperature(Tnav) shifted the earliest,followed by average temperature(Tnv) and average maximum temperature(Txav). The latest change was observed in summer(1990 s), whereas the earliest was observed in winter(1970 s). Before and after the abrupt temperature change, Tnav fluctuated considerably, whereas there was only a slight change in Txav.Before and after the abrupt temperature change, the winter temperature changed more dramatically than the summer temperature. Before the abrupt temperature change, Tnav in the central region(0.322°C/10 a)and west region(0.48°C/10 a) contributed the most to the increasing temperatures. After the abrupt temperature change, Tnav in winter in the central region(0.519°C/10 a) and in autumn in the west region(0.729°C/10 a) contributed the most to the temperature increases. Overall, in the years in which temperature shifts occurred early, a warming hiatus also appeared early. The three temperature metrics in spring(1991)in the east region were the first to exhibit a warming hiatus. In the east region, Txav displayed the lowest rate of increase(0.412°C/a) in the period after the abrupt temperature change and before the warming hiatus,and the highest rate of increase after the warming hiatus.     

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。     

石灰岩山地4种林分空气细菌动态变化及其影响因素分析

为探索石灰岩山地不同林分类型中空气细菌的动态变化规律及其影响因素,筛选出抑菌效果较好的林分,选取徐州石灰岩山地4种典型林分为试验材料,采用自然沉降法研究林分中细菌含量的季节变化和日变化,同步监测温湿度、风速、PM2.5和空气负离子浓度,分析空气细菌含量及其之间的关系。试验结果表明:(1)细菌含量季节性变化表现为春季秋季夏季冬季,除冬季日变化呈现"早晚低,中午高"的变化趋势,其他季节表现为"早晚高,中午低";(2)不同林分类型空气细菌含量存在显著差异(P0.05),总体来看,苦楝林对细菌的抑制效果最好;(3)细菌含量与空气湿度和PM2.5呈极显著正相关关系,与空气负离子呈极显著的负相关关系。综上,苦楝林的抑菌效果最好,湿度、PM2.5和负离子是影响空气细菌含量的主要因素。本研究可为此地城市保健林的营建以及生态旅游规划提供科学依据。     

基于无人机多光谱遥感的冬小麦叶绿素含量反演及监测

旨在实现冬小麦各生育期叶绿素含量的准确估测,探究其时空变化规律。利用无人机获取冬小麦越冬期、返青期、拔节期、孕穗期和灌浆期的高分辨率多光谱图像,同时采集地面SPAD数据。选取三类光谱参数建立反演模型,优选出各生育期的最佳预测模型,并定量监测试验区冬小麦叶绿素含量时间变化和空间分布。结果表明：原始波段模型和波段倒数对数模型分别为越冬期及其他生育期叶绿素含量预测的最佳模型,拟合精度R²>0.59;时空分布上,灌浆期前试验区冬小麦叶绿素含量呈南北高、中部低特点,灌浆期则呈北高南低的趋势,叶绿素含量从越冬期到拔节期逐步增加,拔节期到孕穗期开始降低,孕穗期到灌浆期则大幅度降低。本研究建立的倒数对数预测模型,精度较高,且适用于返青到灌浆的4个生育期,对于试验区冬小麦叶绿素含量有较好的时空监测效果。     

气候变暖背景下河南省夏玉米花期高温灾害风险预估

为预估未来气候变暖背景下夏玉米花期高温灾害风险,根据河南省19个农业气象观测站夏玉米抽雄期常年观测资料和未来RCPs(representativeconcentrationpathways)气候变化情景数据,构建夏玉米花期高温风险评价指标,开展河南省夏玉米花期高温灾害时空特征及风险演变分析。其中RCPs气候情景数据包括基准气候条件(1951—2005年, RCP-rf)和未来(2006—2050年)RCP 4.5(中)、RCP 8.5(高)两种浓度路径数据。以抽雄普遍期及之后7d确定为夏玉米花期,并内插匹配气候情景格点数据。以花期最高气温≥32℃和≥35℃作为轻度和重度高温灾害发生阈值,根据轻、重度夏玉米花期高温发生频率和高温积害,建立风险评价指标并分级。结果表明, RCP-rf情景下全省夏玉米花期高温发生频率在20.5%～81.0%(≥32℃)和3.9%～51.9%(≥35℃)。与基准条件相比,≥32℃高温发生频率增加9.1%(RCP4.5)和11.0%(RCP8.5),≥35℃高温发生频率增加8.7%(RCP4.5)和8.3%(RCP8.5)。RCP-rf情景下全省夏玉米花期高温积害在48.5～200.9℃·d(≥32℃)和9.8～138.5℃·d(≥35℃)。与基准条件相比,≥32℃高温积害增加25.4℃·d (RCP 4.5)和25.6℃·d (RCP 8.5),≥35℃高温积害增加25.8℃·d (RCP 4.5)和31.4℃·d (RCP 8.5)。由综合风险分析可知, RCP-rf情景下夏玉米花期高温灾害高值风险区主要分布在新乡、郑州、许昌、漯河、周口及其以东以北的地区(商丘除外),约占夏玉米主栽区面积的30.1%;RCP4.5情景下高值风险区扩大至洛阳和南阳以东的大部分地区,约占夏玉米主栽区面积的63.4%; RCP 8.5情景下高值风险区面积进一步向西扩大,约占夏玉米主栽区面积的占76.3%。     

海南水稻生育期的时空变化特征及对气候变暖的响应

基于海南6个农业气象观测站点的水稻生育期资料和1961~2014年历史气象数据,分析了海南不同地区水稻生育期的时空分布特征,以及气候变暖对海南水稻生育期的影响。结果表明,近54 a海南水稻生长季内平均气温呈上升趋势,早稻气候倾向率为0.21~0.3℃/10 a,以苗期最为明显,晚稻为0.18~0.24℃/10 a,以成熟期最为明显。不同地区水稻生育期差异较大,东部地区早于西部地区,早稻播种时间最大相差55 d,早稻收获和晚稻播种最大间隔42 d,降水和高温可能是造成这一差异的主要原因。随着气候变暖,海南大部分地区早稻生育期提前,晚稻生育期延迟,苗期和成熟期持续时间缩短,与该阶段平均气温呈负相关,但全生育期持续时间变异较大,部分站点略有延长。在未来气候变暖背景下,海南早稻播期可适当提前,晚稻播期可适当延迟,并选用耐高温和抗干旱品种,以减轻高温的不利影响。     

The role of green roofs in mitigating Urban Heat Island effects in the metropolitan area of Adelaide,South Australia

Changing an urban environment and replacing vegetated surfaces with low albedo materials is one of the reasons for increasing temperatures in an urban environment and consequently also one of the key causes of urban heat island effects. In this study, an experimental investigation at the micro-scale and also a numerical simulation at the macro-scale of a typical urban environment in Adelaide were conducted to estimate the potential for mitigating the UHI effect. The results showed that existing low albedo materials such as asphalt, metal roofs and brick pavements contribute to the heat island potential. Also, urban development and a lack of natural vegetation contribute to increased temperatures in cities. The ability of two types of extensive and intensive green roofs to reduce the surrounding micro-climate temperature were monitored. The results showed that they have significant cooling effects in summer time and could behave as an insulation layer to keep buildings warmer in the winter. Furthermore, different scenarios of adding green roofs to the Adelaide urban environment were investigated using the Envi–MET model. The scenario modelling of adding green roofs in a typical urban area in Adelaide, Australia, supported the hypothesis that this can lead to reductions in energy consumption in the Adelaide urban environment. Also an increased use of other water sensitive urban design technologies such as green walls and street trees together with the adoption of high albedo materials is recommended for achieving the optimum efficiency in terms of reducing urban temperatures and mitigating urban heat island effects.