鲚属两种群的形态变异及综合判别

测量了代表刀鲚种群和湖鲚种群形态特征的传统可量性状和框架参数,采用主成分分析法和逐步判别法,对它们进行形态综合分析.结果表明:两种群的形态差异主要是受额部有鳞部最前缘到背鳍起点的距离所影响的;所有25个形态参数数据判别分析,表明两种群形态差异极显著(P<0.01),判别准确率100％;利用挑选后的9项参数判别分析,表明两种群的形态差异极显著(P<0.01),判别准确率P1是95％-100%,P2是95.2％-100％,综合判别率为97.5％.对各形态参数进行单因子方差分析,计算各参数的差异系数,根据Mayr提出的75％规则,认为它们的形态差异仍然是种内不同地理种群的差异,还没有上升到亚种水平.     

鱼类矢耳石形态分析及其在群体识别中的应用实例研究

利用表征性耳石形态变量(大小变量和轮廓变量)分析方法研究了渤海近岸与长江口水域四个刀鲚(Coilia nasus)群体的识别问题,对比分析了协方差(ANCOVA)校正法和异速生长(allometric growth)校正法在耳石形态分析中去除体长效应的应用效果。研究结果表明,两种体长校正法对四个群体的判别分析结果未产生显著影响,总体识别成功率分别为50.3%和56.5%,群体内个体识别成功率分别为39.5%—90.0%和34.0%—65.1%;长江口水域不同体长组刀鲚个体的耳石形态差异显著,表明其耳石形态特质随鱼类个体生长而变化,协方差校正法和异速生长校正方法的体长组别间的总体识别成功率分别为94.8%和98.8%。整体上,耳石轮廓变量(如矩形趋近率、圆度、分形维数、傅立叶系数等)对刀鲚群体间或体长组别间识别的贡献值高于耳石大小变量(如周长、平均直径、重量、面积等),而二者结合能更有效地识别各地理群体或体长组别个体。     

内蒙古地区沙尘和霾自动观测数据的可靠性和修正方法研究*

2014年,中国气象局将地面人工观测业务调整为自动仪器观测的方式,这一改变明显提高了工作效率,但对观测结果,特别是视程障碍类观测产生了一定的影响。为了完善内蒙古地区霾和沙尘天气判别标准,获得准确可信的气象资料,本文选取了2001-2019年内蒙古12个站点逐三小时的气象观测资料,从时空分布特征和判别方法研究了内蒙古地区沙尘和霾自动气象观测数据的可靠性和判别标准的适用性。结合PM2.5和PM10两个空气质量指数,通过修正错误记录,将沙尘中误判的霾和无天气、霾中误判的沙尘、雾和无天气等分离出来。对比结果来看,修正前,霾和沙尘分别占总频次的95%和5%;修正后,霾、沙尘、雾和无天气分别占总频次的55%、17%、1%、27%。对比呼和浩特单站一次沙尘和一次霾天气过程中气象要素和空气质量指数的连续变化可以看出,相对湿度与PM2.5的相关性均达到了0.5以上。沙尘期,能见度与PM10负相关,PM2.5和PM10相关性较差;而霾期,能见度与PM2.5和PM10的相关性较差,PM2.5和PM10相关性达到了0.8以上,即不同相对湿度环境下影响能见度的因素不同。     

Source and distribution of metals in urban soil of Bombay,India, using multivariate statistical techniques

Simplification of a complex system of geochemical variables obtained from the soils of an industrialized area of Bombay is attempted by means of R-mode factor analysis. Prior to factor analysis, discriminant analysis was carried out taking rock and soil chemical data to establish the anthropogenic contribution of metals in soil. Trace elements (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) are expressed in terms of three rotated factors. The factors mostly indicate anthropogenic sources of metals such as atmospheric fallout, emission from different industrial chimneys, crushing operations in quarries, and sewage sludges. Major elements (Na, Mg, Al, Si, P, K, Ca, Ti, Mn, and Fe) are also expressed in terms of three rotated factors indicating natural processes such as chemical weathering, presence of clay minerals, and contribution from sewage sludges and municipal refuse. Summary statistics (mean, standard deviation, skewness, and kurtosis) for the particle size distribution were interpreted as moderate dominance of fine particles. Mineralogical studies revealed the presence of montmorillonite, kaolinite, and illite types of clay minerals. Thus the present study provides information about the metal content entering into the soil and their level, sources, and distribution in the area.     

Discriminant function model as a tool for classification of stratigraphically undefined radiolarian cherts in ophiolite zones

Two discriminant function models are constructed in order to distinguish major- and trace-element geochemical patterns characteristic for radiolarian cherts from the Zagorje–Mid-Transdanubian Zone ophiolite mélange of NW Croatia. The models are subsequently used to assign new samples from the adjacent magmatic–sedimentary complex extending from the Central Dinaridic Ophiolite Belt in NW Bosnia and thereby to test their applicability in similar cases when clear field relations are absent. In both models the first discriminant function explains the most part of the system variability. However, between the two, the trace-element model proves itself as a more helpful predictive tool presenting a straightforward example of correct classification of samples into three pre-defined groups (Triassic-basin, Triassic-slope and Jurassic radiolarian cherts). This result is extended further, with allocation of all samples from the test region into a single group (Jurassic) according to their trace-element geochemistry.     

复合渗透率测井评价方法在砂砾岩稠油油藏的应用——以克拉玛依油田某区八道湾组为例

砂砾岩储层孔隙结构复杂、非均质性强,在渗透率计算方面传统的测井解释方法误差较大,目前还没有经典的计算砂砾岩渗透率的测井解释模型。以克拉玛依油田某区八道湾组砂砾岩稠油油藏为例,首先在微观层面上分析了渗透率的主控因素。其次根据本地区的实际情况建立了3套渗透率测井解释方法:一是在前人研究基础上改进了多元回归模型;二是在岩性识别的基础上分不同岩性建立了渗透率模型;三是利用BP神经网络进行了渗透率的预测。最后对传统的经验公式与文中的3种方法进行检验。结果表明,比起传统的经验公式和多元回归模型,基于不同岩性的渗透率模型与BP神经网络在实际应用中效果更好,较大幅度地提高了测井解释精度,在非均质性强的砂砾岩油藏中具有更好的应用前景。     

Analytical and Chemometric Evaluation of the Situation of Waterbodies in the Polish Tatra Mountains

Chemometric methods are powerful in finding hidden structures and latent information in environmental and other analytical datasets. This work shows the application of cluster analysis, discriminant analysis, and support vector machines for the evaluation of waterbodies in the Polish Tatra Mountains. After the analysis of in situ parameters and the determination of concentrations of cations and anions, cluster analysis shows that the previous separation into Western Tatras and High Tatras should be reconsidered, as the Bystra stream in the border region might have been incorrectly assigned to the Western Tatras up to now. Discriminant analysis not only confirms the geographical separation of waterbodies, but also the fact that the sampling time is a crucial factor in environmental analysis. Samples taken in different months do not result in a homogenous object of investigation. A uniform date should therefore be chosen so that the results will be comparable. The influence of the sampling month on the classification of samples is also approved by support vector machines.     

STEPWISE CANONICAL DISCRIMINANT ANALYSIS OF CONTINUOUS DIGITALIZED SIGNALS:APPLICATION TO CHROMATOGRAMS OF WHEAT PROTEINS

Continuous digitalized signals such as spectra,electrophoregrams or chromatograms generally have alarge number of data points and contain redundant information.It is therefore troublesome performingdiscriminant analysis without any preliminary selection of variables.A procedure for the application ofcanonical discriminant analysis(CDA)on this kind of data is studied.CDA can be presented as asuccession of two principal component analyses(PCAs).The first is performed directly on the raw dataand gives PC scores.The second is applied on the gravity centres of each qualitative group assessed onthe normalized PC scores.A stepwise procedure for selection of the relevant PC scores is presented.Themethod has been tested on an illustrative collection of 165 size-exclusion high-performance(SE-HPLC)chromatograms of proteins of wheat belonging to 55 genotypes and grown in three locations.Thediscrimination of the growing locations was performed using seven to nine PC scores and gave more than86% accurate classifications of the samples both in the training sets and the verification sets.Thegenotypes were also rather well identified,with more than 85% of the samples correctly classified.Thestudied method gives a way of assessing relevant mathematical distances between digitalized signalsaccording to qualitative knowledge of the samples.     

A CLASS-MODELLING TECHNIQUE BASED ON POTENTIAL FUNCTIONS

A probabilistic and distribution-free class-modelling technique is developed from potential functiondiscriminant analysis.In the multidimensional space of variables the class boundary is built either by thesample percentile of the probability density estimated by means of potential functions,or by the estimateof the ‘equivalent’ determinant of the variance-covariance matrix.The equivalent determinant is that ofa hypothetical multivariate normal distribution whose mean probability density was obtained by potentialfunctions.The bases of this modelling rule are evaluated by means of Monte Carlo experiments.Theresults on four datasets are used to measure the performances of this method,which equal and sometimesexceed the performances of parametric class-modelling methods based on linear and quadraticdiscriminant analysis which were used for comparison.     

Geomorphological analysis of paleo drainage systems and their environmental implications in the desert of Kuwait

 A well-developed drainage network is carved in the hard calcretized and gypcretized gravelly sand of the Pleistocene Dibdibba Formation in northern Kuwait. The present-day aridity suggests that these drainages were developed during pluvial episodes that took place in the post-Pleistocene time and, therefore, are considered as paleo-drainage. Detailed morphometrical analysis of the endoeric drainage systems was performed and the degree of correlation among their different morphometric parameters was investigated. Based on these parameters, the studied drainage basins are statistically grouped into three groups. Such grouping was confirmed by discriminant analysis. The categorical data analysis demonstrated the dependence of these groupings on the surface geology, regional topography, and local geomorphological settings. Infiltration measurements revealed that the drainage bedrocks have a low infiltration rate (<20 cm h^–1), whereas the drainage fill deposits have a relatively high infiltration rate (67–30 cm h^–1). The impact of the drainage system pattern and morphometry on the hydrological conditions is discussed and potential near-surface low salinity to freshwater aquifers is delineated. The role of the studied drainage systems in the occurrence of mobile sand and sand dunes, rainwater harvesting, and land capability are discussed. Received: 8 September 1995 · Accepted: 24 October 1995