桤木人工林结瘤固氮的时空变化及其对后续植物的效应(Ⅱ)

桤木人工林在山丘区的根瘤固氮活性3～6μmol/(g·h),活性受多种因素影响,变幅相当大,而变化规律仍明显.五年生桤木固氮量1～4mg/(株·h).固氮量取决于结瘤量,pH和质地亦影响显著.壤质的低钙质紫色土固氮能力较高,重壤质的酸性紫色土和黄壤固氮能力较低.十年生桤木林采伐迹地上,桤木固氮改良土壤,并促进后续植物的生长.     

Universal cokriging under intrinsic coregionalization

Under the intrinsic coregionalization model if both primary and secondary measurements are available at all sample locations, the conventional geostatistical wisdom is that cokriging provides exactly the same solution as univariate kriging on the primary process alone. However, recent eamples have been given where nonzero secondary cokriging weights have accurred under this spatial dependence structure. This note identifies the conditions under which secondary information is useful under the assumption of intrinsic coregionalization. An illustration is given using a dataset of plutonium and americium concentrations collected from a region of the Nevada Test Site.     

塔河油田混源油地球化学及多元数理统计学对比研究

       混源油的定量判识是当前石油地质地球化学研究的热点与难点。以塔里木盆地塔河油田奥陶系中聚集的混源油为典型研究实例,通过地质地球化学与数理统计学相结合的方法,探索了定量研究混源油的方法,取得良好效果。原油地球化学研究结果表明,塔河油田原油普遍混源,并表现出多期充注特征,早期充注原油遭受了生物降解,因此目前原油中的轻烃、链状烃、规则甾烷等生物标志物主要反映的是后期充注原油的特征,不能很好地指示早期充注原油。据此,选择受生物降解影响相对较小的三环萜烷和藿烷定量数据,采用多元数理统计学交替最小二乘算法进行了原油成因研究,综合分析后认为现今混源油中可划分出4个端元,其中端元1和2可能主要代表了中上奥陶统烃源岩的贡献,而端元3和4则可能主要代表了寒武系烃源岩的贡献。塔河主体区以寒武系原油聚集为主,而外围地区则以中上奥陶统原油聚集为主,并且在整个塔河油田,总体上以寒武系原油的贡献比例相对最高。这一综合对比研究表明,多元数理统计学方法在混源油的比例计算、端元分析等方面具有重要作用,是对传统地球地球化方法研究的有效补充,值得推广应用,此外,研究认识还为区域油气勘探提供了新的参考信息。     

多元校正分析在水环境地球化学领域中的应用

多元校正分析法应用于水环境地球化学研究,可对复杂的分析数据进行处理和解析,反映水质状况与污染之间的各种关系,建立水质评价和预测模型,从而科学地服务于治理水污染。评述了多元分析方法如主成分分析、偏最小二乘法、人工神经网络等在水环境地球化学研究中的应用、进展和前景。     

缢蛏不同种群数量形态特征的比较分析

本研究采用方差分析、主成分分析、判别分析和聚类分析等多元统计分析方法,对缢蛏(SinonovaculaconstrictaLamarck)5个种群的17个比例性状参数进行分析与比较。方差分析结果显示,山东东营种群与其他4个种群均有15项比例性状存在差异显著(P<0.05)。主成分分析中,4个主成分累计贡献率达85.253%,能够概括5个种群间的形态差异,具有较大负荷值的比例性状主要体现在代表壳高和壳前后端钝圆程度的因子。判别分析结果显示,山东东营种群判别准确率为100%,其他4个种群为53.3%—76.7%。聚类分析显示,福建云霄种群和广东湛江种群聚在一起,浙江乐清种群与广西钦州种群聚在一起,这两支再聚在一起,最后与山东东营聚类。差异系数结果显示,山东东营种群和浙江乐清种群、福建云霄种群、广东湛江种群、广西钦州种群之间分别有13、3、4、10项比例性状的CD值大于1.28;浙江乐清种群、福建云霄种群、广东湛江种群和广西钦州种群两两之间的CD值均小于1.28。综合上述5种统计分析结果,贝体壳高,前后端性状是缢蛏种群形态差异的主要影响因子;缢蛏山东东营种群与其他4个地理种群形态差异较...     

多变量总体最小二乘在点云拼接中的应用

在三维激光扫描仪使用过程中,为了减小点云拼接时的误差问题,本文利用同方差多元变量的EIV(Errors In Variables)模型及总体最小二乘的方法解决三维空间点的相似变换,较传统的迭代算法计算空间坐标转换的方法,具有非迭代性、可靠性和计算过程中的简便性。最后,利用实际工程案例对非迭代算法的有效性进行了验证。     

广西\

基于2012-2016年西南低涡年鉴资料、欧洲中心ERA-Interim再分析资料、湖南省站点降水数据及热带测雨卫星TRMM格点降水产品,对西南涡影响下的湖南省暴雨天气过程进行了普查与分析,并进一步利用多变量EOF法和k均值聚类法对西南涡暴雨天气进行了客观分类。结果表明：（1）西南涡暴雨占湖南总暴雨日数的三分之一,大多由偏东路径的盆地涡和九龙涡造成。（2）湖南省西南涡暴雨天气主要分为暖区类、回流类和锋面类,其中暖区类暴雨强度最强,回流类和锋面类强度相当。（3）西南涡暖区暴雨发生在西南涡槽前深厚的暖湿气流中,落区集中在湘中以北。回流暴雨主要形成于低空高压后部东风回流和西南涡槽前西南气流耦合区,落区集中在湘东南,该类是秋季西南涡暴雨的主要天气形势。锋面暴雨因锋区与西南涡槽前耦合叠加,落区位于锋面附近并沿切变线分布。

     

Identifying sources and hazardous risks of heavy metals in topsoils of rapidly urbanizing East China

With rapid economic and social development, soil contamination arising from heavy metals has become a serious problem in many parts of China. We collected a total of 445 samples (0–20 cm) at the nodes of a 2 km×2 km grid in surface soils of Rizhao city, and analyzed sources and risk pattern of 10 heavy metals (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb and Zn). The combination of Multivariate statistics analysis and Geostatistical methods was applied to identify the sources and hazardous risk of heavy metals in soils. The result indicated that Cr, Ni, Co, Mn, Cu, and As were mainly controlled by parent materials and came from natural sources. Cd and Hg originated from anthropogenic sources. Pb and Zn, belonging to different groups in multivariate analysis, were associated with joint effect of parent materials and human inputs. Ordinary Kriging and Indicator Kriging suggested that single element and elements association from the same principal components had similar spatial distribution. Through comprehensive assessment on all elements, we also found the high risk areas were located in the populated urban areas and western study area, which could be attributed to the higher geological background in the western part and strong human interference in the eastern part.     

中国COVID-19疫情扩散的时空模式及影响因素

在2020年全球暴发新型冠状病毒肺炎（COVID-19）疫情的背景下,揭示中国疫情扩散时空模式及影响因素对于科学制定防疫策略具有重要作用。针对2020年1月24日—3月18日期间中国COVID-19疫情从快速扩散到逐步控制的完整过程,基于累计确诊病例数据,以317个地级市为对象,建立疫情扩散时空模式判别模型,结合峰位置、半峰间距、峰度、偏度等参数,解析时空模式的基本特征;基于交通可达性、城市关联程度和人口流动构建多元Logistic回归模型,揭示时空模式的关键影响因素。结果显示：① 距武汉市直线距离588 km为判别疫情扩散4种空间模式的有效边界,综合同一空间模式下的时间过程类别,得到13类疫情扩散时空模式。② 蛙跳型的疫情扩散相对严重;除近距离蛙跳型以外,其余空间模式的疫情扩散时间过程差异明显;各种时空模式的新增确诊病例峰值大多为2020年2月3日;所有普通类城市的平均半峰间距约为14 d,与COVID-19病毒的潜伏期一致。③ 与武汉市的人口关联度主要影响蔓延型和近距离蛙跳型空间模式,与武汉市的通航状况对远距离蛙跳型空间模式具有正向影响,迁出人口数量对蛙跳型空间模式有显著作用,综合型空间模式受初级和次级疫情暴发地的双重影响。不同城市应根据自身的疫情扩散时空模式,在疫情期间高度重视交通管控,从关键环节遏制疫情扩散。     

Accounting for Parameter Uncertainty in Reservoir Uncertainty Assessment: The Conditional Finite-Domain Approach

An important aim of modern geostatistical modeling is to quantify uncertainty in geological systems. Geostatistical modeling requires many input parameters. The input univariate distribution or histogram is perhaps the most important. A new method for assessing uncertainty in the histogram, particularly uncertainty in the mean, is presented. This method, referred to as the conditional finite-domain (CFD) approach, accounts for the size of the domain and the local conditioning data. It is a stochastic approach based on a multivariate Gaussian distribution. The CFD approach is shown to be convergent, design independent, and parameterization invariant. The performance of the CFD approach is illustrated in a case study focusing on the impact of the number of data and the range of correlation on the limiting uncertainty in the parameters. The spatial bootstrap method and CFD approach are compared. As the number of data increases, uncertainty in the sample mean decreases in both the spatial bootstrap and the CFD. Contrary to spatial bootstrap, uncertainty in the sample mean in the CFD approach decreases as the range of correlation increases. This is a direct result of the conditioning data being more correlated to unsampled locations in the finite domain. The sensitivity of the limiting uncertainty relative to the variogram and the variable limits are also discussed.