Multivariate analysis of biogenic constituents in recent sediments off Ras Burka, Gulf of Elat, Red Sea

The shallow shelf area to a water depth of 40 m off Ras Burka, Gulf of Elat, comprises several depositional zones. In order of increasing water depth these include: sand dune (on shore); swash; dead reef platform; sand channel; live coral reef; Cymodoceaslope; reef knolls; and Halophilalawn. The abundance of 64 biogenic constituents, comprising 48 genera of Foraminifera and a variety of other taxa, was recorded in 16 samples representing the sediments presently forming in the various environments. Nodal ordination and association analysis were applied to classify the samples and to examine whether the present day zonation of sedimentary environments can be objectively recognized on the basis of the assemblages of biogenic constituents. The analyses classified the samples consistently into three classes, identified as the shallow near-shore, the upper slope, and the lower slope zones. Association analysis, utilizing only discrete binary presence or absence scores, yielded better results than nodal ordination analysis utilizing continuous metric modal data. In the study area, biogenic grains other than Foraminifera do not contribute to the environmental discrimination. The results suggest that crude presence scores, as contrasted with refined metric data, are informative enough for differentiating sedimentary environments.     

Discrimination of sedimentary facies by association analysis

The ability of association analysis to discriminate sedimentary facies was tested on Purdy's modal analyses of modern sediments of the Great Bahama Bank. Purdy's data set has served in the past as a standard reference for evaluating various multivariate classification algorithms. In order to adapt Purdy's data to association analysis, the percent abundance of the 12 constituents was converted to binary form by dichotomizing each variable on its mean value. The results obtained by association analysis are virtually identical to those obtained by Purdy and other authors. The same four main sedimentary facies were discriminated; 86% of the samples were identically classified (97% when misclassified borderline cases are counted as matches); the total partition variance of the classification is only negligibly greater (4%); and the grouping of the variables yielded the same four groups. The rank order of the three division-attributes responsible for the sample classification is fines, oolites, and corals. Association analysis has been employed by other authors to differentiate meaningful facies groups in studies of ancient reef carbonates, modern reef sediments, and heavy minerals in stream sediments. In all these studies, the results were found to be compatible with those obtained by using the continuous quantitative measurements, indicating that qualitative binary data may often be sufficient for the purpose of facies discrimination in many branches of geology and that association analysis is an effective method for this purpose.     

Asymmetric measures of association, closed data, and multivariate analysis

The association between constant-sum variables X_i and X_j expressed as percentages can be calculated as a product-moment correlation between X_i and X_j/(100 – X_i ) and a correlation between X_j and X_i/(100 – X_j ). An asymmetric, square matrix may be formed from these coefficients, and multivariate analysis performed by two methods: singular value decomposition and canonical decomposition. Either analysis avoids problems in the interpretation of correlation coefficients determined from closed arrays, and provides information about dependencies among the variables beyond that obtained from the usual correlation coefficient between X_i and X_j.Two examples show the canonical decomposition to have the greater usefulness.     

Numerical analysis as applied to the environmental interpretation of carbonate microfacies of some sub-Himalayan carbonates (lower upper precambrian) in northwestern India

Forty-three samples of (1) Sirban Limestone of Riasi, Jammu and Kashmir State, India, based on six mineralogic and petrographic presence-absence variables, and (2) 36 samples of Bilaspur Limestone based on 11 presence-absence mineralogic and petrographic variables, were numerically classified by Q-mode cluster analysis using Sokal and Michner's Simple Matching Coefficient. Sirban Limestone of Riasi yielded 10 clusters or groups indicating four depositional environments: (1) intertidal, (2) intertidal to subtidal, (3) subtidal, and (4) deep-water basinal. Similarly, Bilaspur Limestone yielded nine clusters indicative of the same four environments. A Q-mode ordination of the Riasi samples and of Bilaspur Limestone shows a generalized shelf-to-basin carbonate deposition profile. Results of this study substantiate earlier conclusions of Rao (1979) based on field, mineralogic, and petrographic study of the above-mentioned carbonates.     

A multivariate sedimentary environmental analysis of Great South Bay and South Oyster Bay, New York

A multivariate statistical strategy for classifying paleoenvironments is effective for studying modern sedimentary processes in western Great South Bay and South Oyster Bay, New York. The 13 whole phi weight percent variables were tested for redundancy with R-mode cluster analysis. The samples were partitioned statistically into five environmentally significant facies using Q-mode cluster analysis: (A)sandy gravel, (B)sandy silt, (C)silty sand, (D)slightly gravelly sand, and (E)fine sand. An ordination depicted gradational relationships among the samples and the facies. It was used to evaluate the environmental and textural parameter gradients within the sample space. Interpretations obtained in this manner and by examination of the grain-size curves suggest that these sediments were deposited by waves and currents on beaches and in wave zones (facies C and E),shoal areas (facies B),and tidal channels (facies A and D).Tidal currents, wave action, and eelgrass control the distribution of sediments within the two bays.     

A method for seafloor classification using directional variograms, demonstrated for data from the western flank of the Mid-Atlantic Ridge

Seafloor classification is aimed at quantitatively characterizing seafloor properties such as roughness and anisotropy, and at using such spatial characteristics to distinguish geological provinces automatically. From geostatistical principals, a variogram method is developed for seafloor classification and it is demonstrated for data from the western flank of the Mid-Atlantic Ridge at 25°45N to 26°40N. This study uses HYDROSWEEP bathymetric data which have been ping-edited to flag erroneous data records, and navigation corrected. The classification method can handle the resultant data gaps inside the survey swaths as well as interpret data from several swaths. For a suite of test areas representative of different geological provinces, directional variograms are calculated, and characteristic parameters are extracted for the classification. Examples include a sediment pond, abyssal hill terrain in several segments and of variable spacing, inside and outside corners of ridge discontinuities, and mixed morphological forms. The dependency of the results on random or regular subsampling and on the size of the test area is investigated.     

Microbially mediated carbonates in the Holocene deposits from Sarliève, a small ancient lake of the French Massif Central, testify to the evolution of a restricted environment

Both the mineralogy and facies of lacustrine bio‐induced carbonates are controlled largely by hydrological factors that are highly dependent upon climatic influence. As such they are useful tools in characterizing ancient lake environments. In this way, the study of the sedimentary record from the small ancient Sarliève Lake (Limagne, Massif Central, France) aims to reconstruct the hydrological evolution during the Holocene, using petrographical, mineralogical and geochemical analyses. The fine‐grained marls, mainly calcitic, display numerous layers rich in pristine Ca‐dolomite, with small amounts of aragonite, which are clearly autochthonous. As these minerals are rather unusual in the temperate climatic context of western Europe, the question arises about their forming conditions, and therefore that of the lacustrine environment. Ca‐dolomite prevails at the base of the sequence as a massive dolomicrite layer and, in the middle part, it builds up most of the numerous laminae closely associated with organic matter. Scanning electron microscope observations reveal the abundance of tiny crystals (tens to hundreds of nanometres) mainly organized as microspheres looking like cocci or bacilli. Such a facies is interpreted as resulting from the fossilization of benthic microbial communities by dolomite precipitation following organic matter consumption and extracellular polymeric substance degradation. These microbial dolomites were precipitated in a saline environment, as a consequence of excess evaporation from the system, as is also suggested by their positive ?¹⁸O values. The facies sequence expresses the following evolution: (i) saline pan, i.e. endorheic stage with a perennial lowstand in lake level (Boreal to early Atlantic periods); (ii) large fluctuations in lake level with sporadic freshening of the system (Atlantic); (iii) open lake stage (sub‐boreal); and (iv) anthropogenic drainage (sub‐Atlantic).     

Trend-surface analysis of distribution of some heavy minerals in shelf sediments off Mangalore, India

The mineralogy of the 0.062–0.125 and 0.125–0.25 mm fractions of 58 selected samples from a set of 78 samples collected at a spacing of 1–2 km in the inner shelf of Mangalore were studied. Trend-surface analysis of distribution of the heavy minerals, hornblende, muscovite, garnet, and sillimanite, were made to determine the various factors controlling the mineral-distribution patterns in the area. Parts of the area showing contrasting environments were analyzed separately to determine the relationship of the regional and local trends and the various factors controlling the trends. The linear, quadratic and cubic trends for hornblende, garnet, and sillimanite were controlled by the source, westerly river flow and southerly currents; for mica, the response to processes has been the main factor. The mineral distribution in this area is mainly the result of dynamic interaction of process and response elements and a process-response model is suggested.Published with permission of the Director General, Geological Survey of India.     

陆相断陷盆地低凸起斜坡带层序划分及其沉积充填演化特征:以埕岛东斜坡古近系为例

层序分级不一致和井震层序不统一都会导致沉积充填演化特征反映的不准确,将制约储盖组合与油气分布的预测。文中应用沉积层序的概念,利用岩心、岩性、测井与地震资料,以层序界面与内部构成特征相结合的原则,从坡下到坡上,对东斜坡古近系进行了层序划分。一级层序相当于系地层单元,与构造运动相对应,层序界面为区域性角度不整合;二级层序相当于统或组地层单元,与构造运动幕相对应,层序界面为局部不整合;三级层序相当于段或亚段地层单元,与构造幕内的次级构造作用相对应,层序界面为超覆不整合面、沉积体系转换面及重力流下切面;四级层序即体系域,相当于油组与砂组,与三级层序基准面旋回的阶段性变化相对应,层序界面为初始洪泛面、最大洪泛面,共识别出SQ1、SQ2、SQ3、SQ4、SQ5和SQ6等6个三级层序及15个体系域。井震统一的层序格架结合了钻井资料纵向高分辨率与地震资料横向好连续性的优点,从而高精度、高分辨率地揭示了层序格架充填演化特征,体现出层序旋回性与体系域及平面沉积相分布的差异性。古近纪埕岛凸起夷平,斜坡及凹陷补齐,发育超覆、披覆沉积;古地形由南低北高向南高北低转换;本地物源、邻近物源、区域物源阶段性变迁;多物源的沉积体系交叉、叠置,沉积相发生了扇三角洲-浊积扇-半深湖-滑塌浊积扇-辫状河三角洲-曲流河泛滥平原演变。埕岛低凸起斜坡带层序及沉积充填演化特征具有陆相断陷盆地的代表性,因而,此项研究对于解决层序地层学面临的工业化应用研究不足的问题以及油气储盖组合预测方面的难点可提供有益参考。     

Lithofacies and palaeosol analysis of the Middle and Upper Siwalik Groups (Plio–Pleistocene), Haripur-Kolar section, Himachal Pradesh, India

The Middle–Upper Siwalik Groups (Plio–Pleistocene) are exposed at Haripur-Kolar, Himachal Pradesh, India. The succession is 2800-m thick and has been subdivided into Unit M1 of the Middle Siwalik and four units U1–U4 of the Upper Siwalik Group, on the basis of facies associations, and type and degree of development of palaeosols. The available magnetostratigraphic ages for bases of Units U1, U3 and U4 are 5.5, 2.6 and 1.77 Ma, respectively. The top of the section has been dated as 19 ka.

Lithofacies association and palaeocurrent analysis indicates that the Middle and Upper Siwalik Groups were formed mainly by a basin transverse fluvial system. Two types of river systems, which differ in their size, can be documented in Unit-M1, Unit U1 and Unit-U2: one trunk river system similar to the modern Kosi and the other smaller river system, which formed tributaries to the former. The large rivers were mainly braided in nature. The Unit U3 and lower part of Unit U4 were deposited in the piedmont depositional system mainly by small braided streams and the upper part of the Unit U4 was deposited during a period of arid climate by sediment gravity-flows.

Integration of fluvial lithofacies and pedofacies helps to identify two fluvial depositional systems from the modern Indo-Gangetic Plains. The Lowland System involved deposition on alluvial megafans and interfan areas, which resulted in sand-rich and mud-rich sequences with weekly developed soils. The Upland System allowed large tracts to act as high ground for thousands of years, thereby giving rise to sandstone poor intervals with moderately to strongly developed soils. Occurrence of moderately to strongly developed soils was controlled by uplifting and tilting of large tectonic blocks, without any relation to distance from the main channels. Rate of subsidence apparently controlled the occurrence of Lowland and Upland systems. Deposition of the Unit M1, Unit U1 and Unit U2 took place under Upland and Lowland systems, very similar to those identified from the modern Indo-Gangetic Plains. The warm and humid climate between 5.3 and 2.6 Ma led to the formation of red Alfisols with calcrete nodules at places. Slightly cooler and drier climate starting at about 2.6 Ma and approximately coinciding with the onset of global-scale glaciation, produced poorly developed yellow soil with common development of nodular calcretic horizon and calcitc material disseminated in the groundmass. At ca. 0.9 Ma, a probable significant change to still drier and cooler climate produced typical sediment gravity-flows in the piedmont system, that continued until at least up to 19 ka.     

Climate and environment during the Younger Dryas (GS‐1) as reflected by composite stable isotope records of lacustrine carbonates at Torreberga,southern Sweden

Climatic and environmental changes during the Younger Dryas stadial (GS‐1) and preceding and following transitions are inferred from stable carbon and oxygen isotope records obtained from the sediments of ancient Lake Torreberga, southern Sweden. Event GS‐1 is represented in the sediment sequence by 3.5 m of clay containing lacustrine carbonates of various origins. Comparison of isotopic records obtained on mollusc shells, ostracod valves, and Chara encrustations precipitated during specific seasons of the year supports estimates of relative changes in both lake water and mean annual air temperatures. Variations in soil erosion rates can also be estimated from a simple isotope–mass‐balance model to separate allochthonous and autochthonous carbonate contributions to the bulk carbonate content of the sediments. The well‐known, rapid climatic shifts characterising the Last Termination in the North Atlantic region are clearly reflected in the isotopic data, as well as longer‐term changes within GS‐1. Following maximum cooling shortly after the Allerød–Younger Dryas (GI‐1–GS‐1) transition, a progressive warming and a slight increase in aquatic productivity is indicated. At the Younger Dryas–Preboreal (GS‐1–PB) transition mean annual air temperature rapidly increased by more than 5°C and summer lake‐water temperature increased by ca. 12°C. The subsequent Preboreal oscillation is characterised by an increase in soil erosion and a slight decrease in mean annual air temperature. These results are in harmony with recent findings about large‐scale climate dynamics during the Last Termination. Copyright © 1999 John Wiley & Sons, Ltd.     

Tectonostratigraphy and base-metal mineralization controls, Aravalli province (western India): New interpretations from geophysical data analysis

Analysis and synthesis of multi-disciplinary geoscience information from geological literature/maps and from digitally-processed aeromagnetic and gravity data pertinent to the Aravalli province were carried out to address some hitherto unresolved questions about the tectonostratigraphy of this Archaean–Proterozoic metallogenic province. Based on the magnetic anomalies, several tectonic domains were identified. These domains, bounded by regional-scale geophysical lineaments, have distinct crustal, lithological, metamorphic, and metallogenic characteristics and correlate broadly with lithostratigraphic belts identified by several earlier workers. New interpretations on the tectonostratigraphy and the base-metal mineralization controls in the Aravalli province are as follows. The Hindoli sequences, in the eastern parts of the province, constitute an independent Palaeo–Proterozoic tectonic domain and do not form part of the Archaean basement complex. The base-metal-bearing metasedimentary enclaves in the central parts of the province also constitute an independent Palaeo–Proterozoic tectonic domain, which is quite distinct from the surrounding (basement complex?) rocks. The base-metal-bearing metavolcano-sedimentary sequences in the western parts of the province constitute an independent Neo–Proterozoic tectonic domain. The base-metal deposits in the province are spatially associated with the regional-scale lineaments and with the mafic metavolcanic rocks deduced from the aeromagnetic data. The regional-scale lineaments, which possibly represent Proterozoic crustal-scale faults, are plausible structural controls on the base-metal mineralization in the province. The mafic metavolcanic rocks are plausible heat-source controls on the SEDEX- and/or VMS-type base-metal mineralizations and are possible metal-source controls on the VMS-type base-metal mineralization in the province.     

Spatial and multivariate analysis of geochemical data from metavolcanic rocks in the Ben Nevis area, Ontario

A study of the lithogeochemistry of metavolcanics in the Ben Nevis area of Ontario, Canada has shown that factor analysis methods can distinguish lithogeochemical trends related to different geological processes, most notably, the principal compositional variation related to the volcanic stratigraphy and zones of carbonate alteration associated with the presence of sulphides and gold. Auto- and cross-correlation functions have been estimated for the two-dimensional distribution of various elements in the area. These functions allow computation of spatial factors in which patterns of multivariate relationships are dependent upon the spatial auto- and cross-correlation of the components. Because of the anisotropy of primary compositions of the volcanics, some spatial factor patterns are difficult to interpret. Isotropically distributed variables such as CO ₂ are delineated clearly in spatial factor maps. For anisotropically distributed variables (SiO ₂ ), as the neighborhood becomes smaller, the spacial factor maps becomes better. Interpretation of spatial factors requires computation of the corresponding amplitude vectors from the eigenvalue solution. This vector reflects relative amplitudes by which the variables follow the spatial factors. Instability of some eigenvalue solutions requires that caution be used in interpreting the resulting factor patterns. A measure of the predictive power of the spatial factors can be determined from autocorrelation coefficients and squared multiple correlation coefficients that indicate which variables are significant in any given factor. The spatial factor approach utilizes spatial relationships of variables in conjunction with systematic variation of variables representing geological processes. This approach can yield potential exploration targets based on the spatial continuity of alteration haloes that reflect mineralization.List of symbols c _i Scalar factor that minimizes the discrepancy between andU _i - D Radius of circular neighborhood used for estimating auto- and cross-correlation coefficients - d Distance for which transition matrixU is estimated - d _ij Distance between observed valuesi andj - E Expected value - E _i Row vector of residuals in the standardized model - F(d _ij) Quadratic function of distanced _ij F(d _ij)=a+bd _ij+cd _ij ² - L Diagonal matrix of the eigenvalues ofU - _i Eigenvalue of the matrixU;ith diagonal element ofL - N Number of observations - p Number of variables - Q Total predictive power ofU - R Correlation matrix of the variables - R _0j Variance-covariance signal matrix of the standardized variables at origin;j is the index related tod andD (e.g.,j=1 ford=500 m,D=1000 m) - R _1j Matrix of auto- and cross-correlation coefficients evaluated at a given distance within the neighborhood - R _m ² Multiple correlation coefficient squared for themth variable - S _i Column vectori of the signal values - s _k ² Residual variance for variablek - T _i Amplitude vector corresponding toV _i;ith row ofT=V ^–1 - T Total variation in the system - U Nonsymmetric transition matrix formed by post-multiplyingR ₀₁ ^–1 byR _ij - U _i Componenti of the matrixU, corresponding to theith eigenvectorV _i;U _i= _iV_iT_i - U* _i ComponentU _i multiplied byc _i - U _ij Sum of componentsU _i+U _j - V _i Eigenvector of the matrixU;ith column ofV withUV=VL - w Weighting factor; equal to the ratio of two eigenvalues - X _i Random variable at pointi - x _i Value of random variable at pointi - y _i Residual ofx _i - Z _i Row vectori for the standardized variables - z _i Standardized value of variable     

Effects of detrital carbonate on stable oxygen and carbon isotope data from varved sediments of the interglacial Piànico palaeolake (Southern Alps,Italy)

Contamination with detrital matter is a well‐known bias in δ¹⁸O records from lake carbonates but quantitative information of this effect is yet lacking. Therefore, we developed a new methodological approach combining isotope analyses with microfacies, X‐ray diffraction and micro‐X‐ray fluorescence data and applied this in a case study for the Piànico interglacial lake record in order to provide a quantitative estimate of the effect of detrital carbonate on stable δ¹⁸O and δ¹³C data. The Piànico record contains a long series of distinct and well‐preserved calcite varves and is correlated to Marine Isotope Stage 11. Intercalated in the varve sequence are detrital layers triggered by surface erosion events. These detrital layers are mainly composed of dolomite, thus reflecting the mineralogical signature of the catchment. Microfacies analyses of a 9350 varve year interval allows the identification of detrital layers down to sub‐millimetre scale and a precise selection of three different types of samples for isotope analyses: (1) pure endogenic calcite varves (five varves per sample) without detrital contamination; (2) individual detrital layers; and (3) ‘mixed’ samples including five calcite varves and up to four thin detrital layers. Detrital samples show the isotopic signature of the catchment dolomite and are up to 5.7‰ enriched in δ¹⁸O values with respect to endogenic calcite samples. In mixed samples, the degree of isotopic enrichment is directly related to the amount of detrital contamination; δ¹⁸O of bulk carbonates is significantly biased when the detrital component amounts to more than 5% of the sample. It is also shown that samples containing detrital material have an influence on the calculation of the covariance between δ¹³C and δ¹⁸O. Covariance is high (r = 0.76) when the correlation coefficient is calculated on the base of all samples, but absent (r = ?0.43) when samples containing detrital dolomite are excluded. It has been demonstrated that microfacies analysis is a quick tool to avoid or reduce detrital contamination in bulk carbonate samples during sample selection. Copyright © 2009 John Wiley & Sons, Ltd.     

An improved classification of mineralized zones using particle swarm optimization: A case study from Dagh-Dali ZnPb (±Au) prospect,Northwest Iran

Classification of mineralized areas into different geochemical classes in terms of prospectivity is crucial in the optimal management of exploration risk and costs. Machine learning (ML) algorithms can be served as appropriate alternatives for separating ore-related anomalies due to avoiding the assumptions of statistical distribution and compatibility with the multivariate nature of geochemical features. By hybridizing the ML with a metaheuristic algorithm called particle swarm optimization (PSO), this contribution aims to provide an innovative approach to optimize the classification of geochemical anomalies within the study area. The algorithm, PSO, is inspired by simulating the social behavior of flocks of birds in search of food. The Dagh-Dali ZnPb (±Au) mineral prospect in northwest Iran was subjected as a case study to examine the integrity of the proposed method. Mineralization-related features were extracted by applying principal component analysis (PCA) on metallogenic elements analyzed in soil samples as PC1 and PC2 with elemental assemblages of AgAuPbZn and PbZn, respectively. The silhouette index was employed to estimate the number of underlying geochemical clusters within the adopted feature space. To constitute a comparative analysis, two k-means clustering and PSO-based learning (PSO-L) algorithms were implemented to classify the gridded data of PC1 and PC2 within the study area. The results indicated that the use of PSO has improved the cost function of the clustering problem (up to 4%). Adapting the mineralization classes with the metallogenic evidence demonstrated by boreholes drilled in the study area indicated that PSO-L was superior to the traditional k-means method, improving the accurate estimation of subsurface mineralization classes by 7%. By overcoming the drawbacks of conventional methods for trapping at the local optima, PSO-based learning possesses the potential to highlight weak mineralization signals that are numerically located in boundary conditions. The results show that the proposed approach can serve as an effective medium for optimal modeling of geochemical classes and management of detailed exploration operations.     

Numerical characterization of dispersion coefficients by meshless‐based inverse analysis

This study presents the preliminary development of a meshless‐based indirect inverse analysis. Two goals are desired to be attained: (a) identifying fewer quantities in an indirect inverse analysis and (b) getting the interpolation results of spatial variation of a quantity insensitive to the replacement of one or few interpolation points with other points. This idea is illustrated by modifying a meshless local Petrov‐Galerkin (MLPG) formulation of a two‐dimensional (2D) contaminant transport problem under the concept of boundary control. Thus, dispersion coefficients to be identified are solved from measured or prescribed pollutant concentrations. A field problem is introduced to test the performance of resulting meshless‐based indirect inverse analysis procedure. This test finds a major motive and a minor one for performing a meshless‐based indirect inverse analysis. The major motive is attaining the aforementioned Goal (b), while the above‐mentioned Goal (a) is the minor motive. In conclusion, the development of a meshless‐based indirect inverse analysis procedure can be a valuable application of the MLPG method. Copyright © 2010 John Wiley & Sons, Ltd.     

Internal architecture of a till sheet,Tiskilwa Formation,north‐central Illinois,USA: Application of architectural element analysis

Thick till sheets deposited during the Quaternary form significant aquitards in many areas of North America. However, the detailed sedimentary heterogeneity and architecture and depositional history of till units are not well understood. This study utilizes architectural element analysis to delineate the internal sedimentary architecture of the Tiskilwa Formation exposed at two outcrop sections in north‐central Illinois, USA. Architectural element analysis facilitates systematic delineation of sedimentary architecture based on the nature of facies contacts and change in facies associations, delineation of unit geometries and understanding of depositional processes at different scales of resolution; making architectural element analysis suitable for the sedimentological analysis and palaeoenvironmental reconstruction of subglacial deposits. Eleven facies types are identified in this study, including sand, gravel and diamict facies that record a suite of subglacial depositional processes. Detailed analysis of facies contacts (bounding surface hierarchy) and change in facies associations allows the delineation of five architectural elements, including coarse‐grained lens, coarse‐grained sheet, mixed zone, diamict lens and diamict sheet elements. The spatial arrangement and genetic interpretation of elements, and their spatial relationship with fifth‐order bounding surfaces, allows the delineation of five larger scale architectural units (‘element associations’), which can be mapped in the local study area and record at least three stacked successions of meltwater accumulation and till deposition. The results of this study can be utilized for architectural analysis of till sheets and provide insight to groundwater flow pathways through till in the study area and elsewhere.     

Variation of heavy metals in recent sediments from Piratininga Lagoon (Brazil): interpretation of geochemical data with the aid of multivariate analysis

In the last decade, the Atlantic coast of south-eastern Brazil has been affected by increasing deforestation and anthropogenic effluents. Sediments in the coastal lagoons have recorded the process of such environmental change. Thirty-seven sediment samples from three cores in Piratininga Lagoon, Rio de Janeiro, were analyzed for their major components and minor element concentrations in order to examine geochemical characteristics and the depositional environment and to investigate the variation of heavy metals of environmental concern. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed on the analytical data set to help visualize the sample clusters and the element associations. On the whole, the sediment samples from each core are similar and the sample clusters corresponding to the three cores are clearly separated, as a result of the different conditions of sedimentation. Some changes in the depositional environment are recognized using the results of multivariate analysis. The enrichment of Pb, Cu, and Zn in the upper parts of cores is in agreement with increasing anthropogenic influx (pollution).     

Charcoal signatures defined by multivariate analysis of charcoal records from 10 lakes in northwest Wisconsin (USA)

We show how sedimentary charcoal records from multiple sites within a single landscape can be used to compare fire histories and reveal small scale patterns in fire regimes. Our objective is to develop strategies for classifying and comparing late-Holocene charcoal records in Midwestern oak- and pine-dominated sand plain ecosystems where fire regimes include a mix of surface and crown fires. Using standard techniques for the analysis of charcoal from lake sediments, we compiled 1000- to 4000-yr-long records of charcoal accumulation and charcoal peak frequencies from 10 small lakes across a sand plain in northwestern Wisconsin. We used cluster analysis to identify six types of charcoal signatures that differ in their charcoal influx rates, amount of grass charcoal, and frequency and magnitude of charcoal peaks. The charcoal records demonstrate that while fire histories vary among sites, there are regional patterns in the occurrence of charcoal signature types that are consistent with expected differences in fire regimes based on regional climate and vegetation reconstructions. The fire histories also show periods of regional change in charcoal signatures occurring during times of regional climate changes at ~ 700, 1000, and 3500 cal yr BP.     

An example of cluster analysis applied to a large geologic data set: Aerial radiometric data from Copper Mountain, Wyoming

One objective of the aerial radiometric surveys flown as part of the U.S. Department of Energy's National Uranium Resource Evaluation (NURE) program was to ascertain the spatial distribution of near-surface radioelement abundances on a regional scale. Some method for identifying groups of observations with similar -ray spectral signatures and radioelement concentration values was therefore required. It is shown in this paper that cluster analysis can identify such groups with or without a priori knowledge of the geology of an area. An approach that combines principal components analysis with convergentk-means cluster analysis is used to classify 6991 observations (each observation comprising three radiometric variables) from the Precambrian rocks of the Copper Mountain, Wyoming area. This method is compared with a convergentk-means analysis that utilizes available geologic knowledge. Both methods identify four clusters. Three of the clusters represent background values for the Precambrian rocks of the area, and the fourth represents outliers (anomalously high²¹⁴Bi). A segmentation of the data corresponding to geologic reality as interpreted by other methods has been achieved by perceptive quantitative analysis of aerial radiometric data. The techniques employed are composites of classical clustering methods designed to handle the special problems presented by large data sets.