Annual pattern of zooplankton communities and their environmental response in a subtropical maritime channel system in the northern Bay of Bengal, Bangladesh

Zooplankton plays an important role in aquatic food webs by fluxing of energy from primary producer to subsequent trophic levels in the food chain. The annual pattern of zooplankton communities and potential environmental drivers were studied in the Kohelia channel, Bangladesh from summer 2014 to spring 2015. Samples were collected using net at a depth of 1 m. A total of 32 species belonged to 18 orders, 27 families and 15 taxonomic groups were identified. Of these species, 22 distributed in all four seasons of which 8 were dominant and highly contributing to the total communities. Species number peaked in summer next to winter and fall in spring while maximum abundance was in summer and minimum in spring. Multivariate analyses showed that there was a clear annual pattern in the zooplankton communities. Species diversity and evenness peaked in spring but fall in autumn while the high value of species richness was found in winter. Biological-environmental best matching (BIO-ENV) analyses conformed that community pattern of zooplankton was mainly driven by transparency salinity, and temperature individually or combined with water nutrients. These results demonstrate that annual pattern of the zooplankton community shaped by channel environmental factors in subtropical channel ecosystems, thus might be used for community-based subtropical coastal water bioassessment.     

Estimator Stability in Geological Applications

Classic mathematical statistics recommends maximum likelihood estimators of parameters of a model because they have minimal variance in the model. The theory of robustness showed that these estimators were unstable to small deviations of probability density. The estimator stability is necessary for applications, where reality is always more complex than any model, especially in geology, where objects are unique. Methods of calculus of variations give a measure of the estimator stability, and the maximum likelihood estimators have little stability. Simultaneous maximization of efficiency and stability gives new estimators more suitable for applications. The estimator instability is especially harmful in the estimation of the multivariate normal distribution. To avoid instability, multivariate problems are reduced to sequences of bivariate problems. An example of the solution of a geological problem shows that methods of classic statistics are not good and the reductive method is much better.     

Application of light hydrocarbons (C4–C13) to oil/source rock correlations:: a study of the light hydrocarbon compositions of source rocks and test fluids from offshore Mid-Norway

Relatively little work has been published on the correlation between the light hydrocarbon distributions in reservoir fluids and their proposed source rocks [Philippi, G. T. (1981)]. The aim of our work was to study this relationship in detail for samples from Mid-Norway. The main source rocks offshore Mid-Norway are the marine shales of the Late Jurassic Spekk Formation and the coals and paralic shales of the Early Jurassic Åre Formation. Reliable light hydrocarbon (C₄–C₁₃) data for source rock samples were acquired by thermal extraction-GC of the source rocks. Of these, notably the hydrocarbons in the C₆–C₈ range (routinely measured in test fluids) were used to discriminate between the Spekk and Åre Formation samples. A total of twenty-six samples from the Spekk Formation and twenty-four samples from the Åre Formation at different maturity levels and facies were analyzed. In general, the two source rock types differ in their light hydrocarbon composition by the presence of relatively more aromatics and cyclohexanes in the Åre samples, while the Spekk samples are richer in cyclopentanes and acyclic hydrocarbons. We show that source rock facies is a more important indicator of light hydrocarbon composition than maturity variation. Differences in the chemical composition, which can be used to discriminate between the two source rocks, were supported by differences in the carbon isotope composition of individual components of the same fraction, as determined by GHM-IR-MS analysis of eleven samples. Further, the light hydrocarbon compositions of reservoir fluids (oils and condensates) were compared with those for the source rock(s). Sixty-six gas chromatograms of oils and condensates, representing most of the known petroleum accumulations in Mid-Norway, were collected. Of these, five oil samples were selected for detailed isotopic analysis of individual components (GC-IR-MS). When using a classification scheme based on data from sediment samples, data for the light hydrocarbon fraction of oils and condensates indicate that the Spekk Formation is the dominant source for most of the fields from Mid-Norway, with a significant contribution from the Åre Formation being detected principally in one field. Differences in the chemical composition of the C₆–C₈ fractions were supported by differences in the carbon isotope composition of individual components, which also discriminate between the oils. Although the classification diagrams used in this study are based on source rock data from Mid-Norway, the method can be applied to other areas, providing that the diagrams are calibrated with source rock data from the area of interest.     

多元回归分析方法在火山碎屑岩储层孔隙度计算中应用

火山碎屑岩储层具有岩性复杂、测井数据种类繁多以及区域大、层位多等特点,导致火山碎屑岩储层测井参数难于确定。以海拉尔盆地乌尔逊--贝尔凹陷的火山碎屑岩储层为研究主体,在准确识别岩性的基础上,对测井资料进行预处理,根据岩心分析资料计算其理论骨架参数值。依据孔隙度与中子、密度、声波三者之间的关系,将多元回归方法应用在孔隙度计算中,实现利用多元回归方法计算火山碎屑岩储层孔隙度。其结果与岩心分析孔隙度比较接近,绝对误差仅为1. 6%,能满足储量计算要求。     

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。     

基于Copula函数的联合概率法在海洋工程中的应用

本文介绍了Copula函数的定义、属性和几种特殊的Copula函数.将Copula函数应用到近海工程中,用其建立了最大有效波高和最大风速的联合分布函数并检验,结果表明:Copula函数能够比较好的模拟实际的联合概率分布。通过Copula方法,可以由边缘分布和一个连接它们的Copula函数来得出联合分布函数,发挥其描述相关性尤其是尾部相关性的优势。该方法在近海工程的工程可靠度、设计标准和失效概率的计算中具有广泛的应用前景。     

A statistical approach for determining the environment impact of surface sediments from the Dongting Lake area,central China

The Dongting Lake, the second biggest freshwater lake in China, consists of three wetlands of national importance, namely the East Dongting Lake, the South Dongting Lake, and the West Dongting Lake. Surface sedi-ments were sampled from 57 locations across the lake. Nutrient concentrations [total organic carbon (TOC), total N (TN) and total P (TP)] and 16 element concentrations (Al, As, B, Ca, Cd, Cr, Cu, K, Fe, Hg, Mn, Ni, Pb, Si, Ti and Zn) in the sediments were measured to investigate the impact of industrialization along the lake's coastline and sev-eral tributaries on the profiles of nutrients and heavy metals in the lake's surface sediments. R-mode cluster analysis (CA) was used to integrate geochemical data. The result showed that euthophication of the Dongting Lake resulted mainly from TN and TOC. The main polluting trace metals are Hg, As, Cd, Zn, Pb and Mn, which are largely ad-sorbed on clay minerals or Fe/Mn oxides, or deposited as carbonates. Principal component analysis (PCA) revealed the source of micropollutants. The worst affected district by heavy metals is the East Dongting Lake, the pollution sources may originate mainly from the Xiangjiang drainage area. The results demonstrated that multivariate methods are the potentially great tools for the interpretation of the environmental data on lake sediments.     

湖泊水质预测模型的建立及其应用

根据东湖多年监测数据分析,建立了多元相关预测模型、基于灰色理论灰色系统的预测模型和质量平衡模型。为了提高灰色预测精度,利用残差对模型进行了相应的修正,并利用3种模型对影响东湖水质主要因子——经济、人口、BOD、COD、TN、TP进行了2000年的预测,提出了东湖污染防治对策。     

对应聚类分析

对应聚类分析是一种多元统计分析方法。它吸取了对应分析和聚类分析的主要优点,在充分利用多维空间信息的基础上,该方法将变量类别、样品类别和它们间的对应关系清晰显示于单—图件,即对应聚类谱系图。近年来的许多实例说明该方法在地质和勘查地球化学中的应用是有成效的。本文详细叙述了对应聚类分析的计算方法,通过一些验证性实例介绍了方法效果,并简要讨论了为什么能获得较好效果的原因。     

敦煌绿洲地下水微量元素分布特征及其成因

采用多元统计和水文地球化学分析对中国西北地区敦煌绿洲地下水微量元素分布特征及其成因进行了研究.结果表明:地下水中大多数微量元素含量较低,水质总体良好.地下水微量元素具有明显的地带分布规律,从山前洪积扇扇顶补给地带,到中下游细土平原径流排泄区,多数金属元素含量增加,部分在中游出现极大值.蒸发浓缩作用和水岩相互作用控制了研...