Deep-sea reef fish assemblage patterns on the Blake Plateau(Western North Atlantic Ocean)

Deep‐water coral habitats are scattered throughout slope depths (360–800 m) off the Southeastern United States (SEUS, Cape Lookout, North Carolina, to Cape Canaveral, Florida), contributing substantial structure and diversity to bottom habitats. In some areas (e.g. off North Carolina) deep corals form nearly monotypic (Lophelia pertusa) high profile mounds, and in other areas (e.g. off Florida) many species may colonize hard substrata. Deep coral and hard substrata ecosystems off the SEUS support a unique fish assemblage. Using the Johnson‐Sea‐Link submersible (in 2000–2005, 65 dives), and a remotely operated vehicle (in 2003, five dives), fishes were surveyed in nine deep reef study areas along the SEUS slope. Forty‐two benthic reef fish species occurred in deep reef habitats in these study areas. Species richness was greatest on the two coral banks off Cape Lookout, North Carolina (n = 23 and 27 species) and lowest on the two sites off Cape Canaveral, Florida (n = 7 and 8 species). Fish assemblages exhibited significantly (ANOSIM, Global R = 0.69, P = 0.001) different patterns among sites. Stations sampled off North Carolina (three study areas) formed a distinct group that differed from all dives conducted to the south. Although several species defined the fish assemblages at the North Carolina sites, Laemonema barbatulum, Laemonema melanurum, and Helicolenus dactylopterus generally had the most influence on the definition of the North Carolina group. Fish assemblages at three sites within the central survey area on the Blake Plateau were also similar to each other, and were dominated by Nezumia sclerorhynchus and L. melanurum. Synaphobranchus spp. and Neaumia sclerorhynchus differentiated the two southern sites off Cape Canaveral, Florida, from the other station groups. Combinations of depth and habitat type had the most influence on these station groups; however, explicit mechanisms contributing to the organization of these assemblages remain unclear.     

渤海鱼类复殖吸虫群落结构

根据 1983-1986 年渤海鱼类复殖吸虫调查的结果,对其群落结构进行研究.共发现复殖吸虫 14 科 48 属 84 种.多元分析结果表明:渤海复殖吸虫可以分为内海和外海两个群落:内海的黄姑鱼多睾吸虫(Pleorchis nibeae)-天津褶膜吸虫(Ectenurus tiagjinensis)-多变颈源吸虫(Derogenes varicus)群落(简称PED);外海的球形孔肠吸虫(Opecoelus sphaericus)-褐菖鲉孔肠吸虫(Opecoelus sebastisci)-马面魨拟孟氏吸虫(Paramanteriella cantherini)群落(简称OOP).PED 的种类组成、数量和多样性均高于 OOP,但优势种类和优势度却相对较低.群落结构差异与渤海地理环境、宿主组成、水环境等多因子相关.     

变形预测的逆多元统计模型

测量和预测目标点的空间变形是掌握变形体稳定性的重要手段,本文论证了逆多元统计预测模型用于滑坡的稳定性分析,利用变形点的空间三维移动量模拟时间的变化特征,与正常的时间序列进行对比,检验变形体的稳定性。并结合实例说明了在滑坡变形分析中逆多元统计模型的实用性和可靠性。     

土壤剖面的磁学特征及其对交通污染的指示意义——以北京首都机场高速公路为例

对北京首都机场高速公路旁采集的土壤柱状T01剖面的磁学参数和金属元素分析,探讨了研究区内现代交通导致的土壤磁学性质的变化及其对环境污染的响应.结果表明,磁参数(χ,ARM和SIRM)与重金属含量呈同步垂向变化趋势.来源于交通运输排放的污染物是土壤剖面上部(0～8 cm)磁性和金属含量增强的主要原因,8cm以下,土壤基本未受到污染,磁性矿物和重金属含量较低,磁性颗粒变化稳定,基本代表了该地区土壤的自然背景.尽管土壤岩石磁学分析表明剖面上下部受污染和未受污染样品的磁载体均是粒度较粗的多畴磁铁矿,但是结合磁参数比值曲线,说明底部样品的磁颗粒的粒度较顶部偏细.磁性矿物的含量变化没有影响磁颗粒的粒度特征.指标聚类等相关分析表明,土壤磁参数(χ,ARM和SIRM)与重金属元素(Pb,Zn和Cu)含量显著相关;结合模糊聚类分析,磁参数可用于追踪、识别交通污染物质在土壤剖面中的富集、迁移状态,揭示不同深度土壤的污染程度.     

Modelling bivariate rainfall distribution and generating bivariate correlated rainfall data in neighbouring meteorological subdivisions using copula

The rainfall patterns of neighbouring meteorological subdivisions of India are similar because of similar climatological and geographical characteristics. Analysing the rainfall pattern separately for these meteorological subdivisions may not always capture the correlation and tail dependence. Furthermore, generating the multivariate rainfall data separately may not preserve the correlation. In this study, copula method is used to derive the bivariate distribution of monsoon rainfall in neighbouring meteorological subdivisions. Different Archimedean copulas are used for this purpose and the best copula is selected based on nonparametric test and tail dependence coefficient. The fitted copula is then applied to derive the bivariate distribution, joint return period and conditional distribution. Bivariate rainfall data is generated with the fitted copula and it is observed with the increase of sample size, the generated data is able to capture the correlation as well as tail dependence. The methodology is demonstrated with the case study of two neighbouring meteorological subdivisions of North‐East India: Assam and Meghalaya meteorological subdivision and Nagaland, Manipur, Mizoram and Tripura meteorological subdivision. Copyright © 2010 John Wiley & Sons, Ltd.     

The control of maturity and kerogen type on quantitative analytical pyrolysis data

Quantitative pyrolysis-gas chromatography has been performed on 96 kerogen samples isolated from 17 wells on the Norwegian Continental shelf. Petrographic and bulk geochemical measurements were also performed on the samples, and a combined data set of 117 variables for each sample was analysed using principal components analysis (PCA). This approach provides an objective and reproducible means of kerogen characterisation, which can be easily automated. In addition to objective kerogen characterisation and facile visualisation of facies and maturity related chemical trends, the method has the potential to allow objective prediction of key geochemical parameters such as maturity level from pyrogram data.     

An examination of the use of the logratio transformation for the testing of endmember hypotheses

Given a compositional dataset in the absence of any prior information on any mixing process which may have formed it, a complete analysis of mixtures determines three distinct types of estimates in order. These are: (i) the estimate of the number of endmembers or fixed source compositions, of which all the sample compositions of the dataset must be approximate mixtures; (ii) the estimated compositions for each of these chosen number of endmembers; and (iii) the estimated contributions of each of these endmember estimates to each sample. Traditionally, the estimate for the number of endmembers has been assessed either by mapping or by inspection of the coefficients of determination between the observed and estimated variables. Mapping entails the plotting on a map of the region from which the samples were taken, either the contours of the contributions of each endmember to each sample, or some other portrayal of the distribution of endmember abundances. Because it requires the complete analysis, assessment by this method is too elaborate except for final confirmation and display. Alternatively, choosing a number of endmembers, which result in suitability high coefficients of determination for all or most variables, may account for elements which are not part of the conjectured mixing process or, worse, may result in the identification of endmembers which may never in fact have existed. Such an error is similar to overspecifying a multiple regression model. So, the obvious starting point from which to assess the validity, or otherwise choice of endmember numbers, is to examine the matrix of residuals. The differences between the logratio-transformed observed and estimated data form an array of residual logratios. A linear combination of these may be formed for each sample, which, under a random perturbation assumption, should follow a univariate normal distribution. Whether or not this scalar is normal can be readily tested. It can also be examined graphically for such desirable qualities as symmetry when the test for normality may be too severe. This procedure is employed to assess the decompositions of the U.S.G.S. Mid-Pacific data and the Nazca Plate Surface sediments.This paper was presented at the 18th Geochautauqua, Newark, Delaware, 13–14 October 1989.     

Estimation of a multidimensional covariance function in case of anisotropy

A model of a multivariate covariance function with an ellipsoidal directional correlation scale has been developed. The axes of the ellipsoidal scale are related to the eigenvalues and eigenvectors of a matrix B which characterizes the ellipsoid of the range of influence. The matrix B is found to be related to a matrix T which can be estimated directly from sparse sampling data and can be used to determine estimates of the matrix B. The method has been applied to both two-dimensional and three-dimensional cases. The numerical results show that the satisfactory accuracy is obtained with sparse sampling data from an anisotropic random function.     

矿化富集中心地质因素多元统计分析及应用

本文导出了通过控矿地质因素逻辑信息法的研究来建立矿化富集中心数学模型的公式,使矿化富集中心数学模型与控矿地质因素定量地联系起来。还给出了单个矿化富集中心趋势面分析的数学模型和矿床空间分布模型。在这基础上,以某锡-多金属成矿带中某远景区的研究为例说明怎样应用矿化富集中心地质因素多元统计分析（逻辑信息法、趋势面分析、逐步回归分析和聚类分析）进行矿床统计预测。     

小块体重的多元线性回归方程在锡铁山铅锌矿床储量计算中的应用

从锡铁山铅锌矿床小块体重样品原始测定数据入手，运用数学地质中的回归分析，建立了本矿床的小块体重多元线性回归方程，为矿床储量计算提供了科学参数。利用回归方程法计算小块体重进而可以推广到所有贱金属矿床的储量计算中。