中国海岸风沙沉积的成因与特征

东部和南部沿海是我国风景优美、气候宜人, 工农业与交通事业发达和人口密集的重要经济区。在16, 000多公里的海岸上, 风沙作用的海岸线就有近3, 000公里, 目前它们都在不同程度上处于风沙作用而后退或大大改观的状态。     

南极菲尔德斯半岛湖泊沉积物的稀土地球化学

本文研究了燕鸥湖、西湖和基太湖湖泊沉积物的稀土地球化学。这些湖泊沉积物的稀土分布模式与菲尔德斯半岛第三纪火山岩非常相似，它们的物质来源是菲尔德斯半岛岛弧火山岩。湖泊沉积相与冰碛层稀土模式的差异，反映了它们经历的化学风化程度不同、粘土含量不同。Ｃｅ异常意味着每个湖泊沉积旋回结束的阶段气候是比较干燥的。湖泊沉积物的稀土含量和分布模式变化小，也意味着在中晚更新世时气候是比较干燥的。     

中亚热带网纹红土的稀土元素特征与成因分析

130块样品的稀土元素含量、稀土分布模式、稀土特征值分析以及物源指数的计算表明,中亚热带网纹红土与北方黄土具有相似的稀土特征。网纹红土稀土元素平均含量(179.57μg/g)与地壳平均值(178μg/g)、北京郊区1998年12月大气粉尘稀土总量(177.97μg/g)以及两块中国黄土标样平均值(178.22μg/g)非常接近,稀土分布模式与风成沉积及UCC类同,轻稀土强烈富集,重稀土淋失,轻重稀土比值9.86~15.18,Ce元素正异常,物源指数<0.5。稀土元素特征指示,所研究的网纹红土的母质与黄土具有风尘相似性,而且风尘沉积后经历了较北方黄土更为强列的风化作用,其形成环境与古土壤和上新世红粘土接近。     

Metallic Mineral Resources in the Twenty-First Century: II. Constraints on Future Supply

Supplying worldwide demand of metallic raw materials throughout the rest of this century may require 5–10 times the amount of metals contained in known ore deposits. This demand can be met only if mineral deposits containing the required masses of metals, in excess of present day ore reserves, exist in the Earth’s crust. It is, by definition, not known whether or not such mineral deposits exist. On the basis of the statistical distribution of metal tonnages contained in known ore deposits, however, it is possible to place constraints on the size distribution of the deposits that must be discovered in order to meet the expected demand. A nondimensional analysis of the distribution of metal tonnages in deposits of 20 metals shows that most of them follow distributions that, although not strictly lognormal, share important characteristics with a lognormal distribution. Chief among these is the observation that frequency falls off symmetrically and geometrically with deposit size, relative to a median deposit size that is approximately equal to the geometric mean deposit size. An immediate consequence of this behavior is that most of the metal endowment is concentrated in deposits that are several orders of magnitude larger than the median deposit size, and that are much rarer than the most common deposits that cluster around the median deposit size. The analysis reveals remarkable similarities among the statistical distributions of most of the metals included in this study, in particular, the fact that distribution of most metals can be fully described with essentially the same value (about 2–3) of the scale parameter, σ, which is the only parameter needed to describe the behavior of a normalized lognormal variable. This observation makes it possible to derive the following general conclusions, which are applicable to most metals—both scarce and abundant. First, it is unlikely that undiscovered mineral deposits of sizes comparable to those that contain most of the known metal endowment exist in sufficient quantities to supply the expected worldwide demand throughout the rest of this century. Second, if the expected demand is to be met, one must hope that very large deposits, perhaps up to one order of magnitude larger than the largest known deposits, exist in accessible portions of the Earth’s crust, and that these deposits are discovered.     

Typing Mineral Deposits Using Their Grades and Tonnages in an Artificial Neural Network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further.Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage).Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag.Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.     

贝壳堤的形成与风暴沉积——以广东台山长湾贝壳堤为例

台山市西南部沿海有一条由典型风暴潮沉积堆积形成,出露高度远高于现代风暴潮增水面的贝壳堤.根据贝壳堤出露的横向与纵向剖面以及横剖面上的3个钻孔的形成年代、沉积特征的分析表明风暴潮在贝壳堤发育过程中的不同阶段具有不同的侵蚀与堆积作用;贝壳堤风暴沉积也具有丘状层理、切割充填结构等典型的风暴沉积特征,但贝壳堤风暴沉积与浅海陆架上的风暴沉积在沉积过程、堆积层位、保存条件等方面具有明显的差异.长湾贝壳堤是由多次风暴加积而成,形成贝壳堤的风暴增水高度接近或高于历史最高记录.形成贝壳堤的风暴沉积堆积于平均海面之上,所以增     

天山南麓台兰河口丘状堆积物成因及时代的新见解

研究表明台兰河口的丘状堆积体属古泥石流成因，物质组成显示泥石流形成于中低山带的峡谷段，泥石流可能由谷坡堆积物（主要为钙质胶结的冰碛）滑塌阻塞河床发展而成。其形成时代晚于末次冰期，应在全新世中期或更晚一些。     

Classification of mineral deposits into types using mineralogy with a probabilistic neural network

In order to determine whether it is desirable to quantify mineral-deposit models further, a test of the ability of a probabilistic neural network to classify deposits into types based on mineralogy was conducted. Presence or absence of ore and alteration mineralogy in well-typed deposits were used to train the network. To reduce the number of minerals considered, the analyzed data were restricted to minerals present in at least 20% of at least one deposit type. An advantage of this restriction is that single or rare occurrences of minerals did not dominate the results. Probabilistic neural networks can provide mathematically sound confidence measures based on Bayes theorem and are relatively insensitive to outliers. Founded on Parzen density estimation, they require no assumptions about distributions of random variables used for classification, even handling multimodal distributions. They train quickly and work as well as, or better than, multiple-layer feedforward networks. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class and each variable. The training set was reduced to the presence or absence of 58 reported minerals in eight deposit types. The training set included: 49 Cyprus massive sulfide deposits; 200 kuroko massive sulfide deposits; 59 Comstock epithermal vein gold districts; 17 quartzalunite epithermal gold deposits; 25 Creede epithermal gold deposits; 28 sedimentary-exhalative zinc-lead deposits; 28 Sado epithermal vein gold deposits; and 100 porphyry copper deposits. The most common training problem was the error of classifying about 27% of Cyprus-type deposits in the training set as kuroko. In independent tests with deposits not used in the training set, 88% of 224 kuroko massive sulfide deposits were classed correctly, 92% of 25 porphyry copper deposits, 78% of 9 Comstock epithermal gold-silver districts, and 83% of six quartzalunite epithermal gold deposits were classed correctly. Across all deposit types, 88% of deposits in the validation dataset were correctly classed. Misclassifications were most common if a deposit was characterized by only a few minerals, e.g., pyrite, chalcopyrite,and sphalerite. The success rate jumped to 98% correctly classed deposits when just two rock types were added. Such a high success rate of the probabilistic neural network suggests that not only should this preliminary test be expanded to include other deposit types, but that other deposit features should be added     

Streamflow regulation and multi-level flood plain formation: channel narrowing on the aggrading Green River in the eastern Uinta Mountains, Colorado and Utah

The style and degree of channel narrowing in aggrading reaches downstream from large dams is dependent upon the dominant geomorphic processes of the affected river, the magnitude of streamflow regulation, and the post-dam sediment transport regime. We measured different magnitudes of channel adjustment on the Green River downstream from Flaming Gorge Dam, UT, USA, that are related to these three factors. Bankfull channel width decreased by an average of about 20% in the study area. In reaches with abundant debris fans and eddy deposited sand bars, the amount of channel narrowing was proportional to the decrease in specific stream power. The fan–eddy-dominated reach with the greatest decrease in stream power narrowed by 22% while the reach with the least decrease in stream power narrowed by 11%. In reaches with the same magnitude of peak flow reduction, meandering reaches narrowed by 15% to 22% and fan–eddy-dominated reaches narrowed by 11% to 12%. Specific stream power was not significantly affected by flow regulation in the meandering reaches.In the diverse array of reach characteristics and deposit types found in the study area, all pre- and post-dam deposits are part of a suite of topographic surfaces that includes a terrace that was inundated by rare pre-dam floods, an intermediate bench that was inundated by rare post-dam floods, and a post-dam floodplain that was inundated by the post-dam mean annual flood. Analysis of historical photographs and tree-ring dating of Tamarix sp. shows that the intermediate bench and post-dam floodplain are post-dam landforms in each reach type. Although these two surfaces occur at different levels, they are forming simultaneously during flows of different magnitude. And while the relative elevation and sedimentologic characteristics of the deposits differ between meandering reaches and reaches with abundant debris fans and eddies, both reach types contain deposits at all of these topographic levels.The process of channel narrowing varied between fan–eddy-dominated and meandering reaches. In the meandering reaches, where stream power has not changed, narrowing was accomplished by essentially the same depositional processes that operated prior to regulation. In fan–eddy-dominated reaches, where significant reductions in stream power have occurred, channel narrowing has been accompanied by a change in dominant depositional processes. Mid-channel sand deposits are aggrading on deposits that, in the pre-dam era, were active gravel bars. These deposits are creating new islands and decreasing the presence of open-framework gravel bars. In eddies, bare sand bars are replaced with vegetated bars that have a simpler topography than the pre-dam deposits.     

DIFFERENTIAL ROCK WEATHERING IN THE 'VALLEY OF THE BOULDERS', KÄRKEVAGGE, SWEDISH LAPLAND

Kärkevagge is an alpine valley in the low arctic of Swedish Lapland. It is named after, and famous for, its large deposit of immense (c. 10–15 m) boulders that almost fill the lower valley. Above the boulder deposit, on the flanks of the valley, are more recent and generally much smaller (c. 1–3 m) individual boulders that have fallen from the valley-wall cliff face, presumably from post-glacial valley-side unloading. Some of these smaller boulders are seemingly fresh and unweathered while others have been reduced to no more than mounds in the tundra. These boulders must be younger than the larger, lower giant boulder deposit, but are not particularly recent rockfalls as they are partially buried in colluvium. Comparisons of mineralogy and chemistry indicate that the possibility exists that the incompetent, 'rotten' rocks, if not considerably older than their competent neighbors, are inherently self-destructive. They have evidence of increased sulfur content, which is a proxy for pyrite, a known weathering accelerant in Kärkevagge.     

Basic concepts in three-part quantitative assessments of undiscovered mineral resources

Since 1975, mineral resource assessments have been made for over 27 areas covering 5×10⁶ km² at various scales using what is now called the three-part form of quantitative assessment. In these assessments, (1) areas are delineated according to the types of deposits permitted by the geology,(2) the amount of metal and some ore characteristics are estimated using grade and tonnage models, and (3) the number of undiscovered deposits of each type is estimated.Permissive boundaries are drawn for one or more deposit types such that the probability of a deposit lying outside the boundary is negligible, that is, less than 1 in 100,000 to 1,000,000.     

Probabilistic Estimates of Number of Undiscovered Deposits and Their Total Tonnages in Permissive Tracts Using Deposit Densities

Empirical evidence indicates that processes affecting number and quantity of resources in geologic settings are very general across deposit types. Sizes of permissive tracts that geologically could contain the deposits are excellent predictors of numbers of deposits. In addition, total ore tonnage of mineral deposits of a particular type in a tract is proportional to the type’s median tonnage in a tract. Regressions using size of permissive tracts and median tonnage allow estimation of number of deposits and of total tonnage of mineralization. These powerful estimators, based on 10 different deposit types from 109 permissive worldwide control tracts, generalize across deposit types. Estimates of number of deposits and of total tonnage of mineral deposits are made by regressing permissive area, and mean (in logs) tons in deposits of the type, against number of deposits and total tonnage of deposits in the tract for the 50th percentile estimates. The regression equations (R ² = 0.91 and 0.95) can be used for all deposit types just by inserting logarithmic values of permissive area in square kilometers, and mean tons in deposits in millions of metric tons. The regression equations provide estimates at the 50th percentile, and other equations are provided for 90% confidence limits for lower estimates and 10% confidence limits for upper estimates of number of deposits and total tonnage. Equations for these percentile estimates along with expected value estimates are presented here along with comparisons with independent expert estimates. Also provided are the equations for correcting for the known well-explored deposits in a tract. These deposit-density models require internally consistent grade and tonnage models and delineations for arriving at unbiased estimates.     

Rare earth elements of aeolian deposits in Northern China and their implications for determining the provenance of dust storms in Beijing

This paper contributes to a better understanding of the source of dust storms in northern China and the relationship between these sources and other aeolian sediments in this region. Sediment samples in potential source areas were collected from the Hunshandake Sandy Land, Heaven Desert, the loess deposits of the Bashang area, the mountainous basins and valleys north of Beijing and from the Badain Jaran Desert and Hulunbaier Sandy Land (Fig. 1). Dust samples were collected in Beijing during two dust storms in March 2002 and April 2006. The laboratory methods used in this study included measurements of abundance of trace elements, in particular the rare earth elements (REEs), mineral assemblages and grain size. The REE contents, Eu and Ce anomalies show clear differences between various deposits. Provenance is considered to be the key factor influencing REE patterns in the study areas. The REE abundances and patterns indicate that the aeolian sand north of Beijing, such as in the Heaven Desert, is mainly of local origin rather than from desert encroachment from the north. The mineral grains carried in dust storms, however, are highly mixed, and may come partly from local sources but mainly from distant desert regions in western China.     

Mineral Potential Modelling for the Greater Nahanni Ecosystem Using GIS Based Analytical Methods

Mineral potential within the Greater Nahanni Ecosystem (GNE) was modelled in a Geographic Information System (GIS) for four different deposit types: (1) SEDEX (stratiform shale-hosted sedimentary exhalative Zn–Pb–Ag), (2) ‘Carbonate-Fault’ (carbonate-hosted zinc–lead–silver associated with major faults), (3) ‘Intrusion-Related’ (includes skarn, rare metals and gemstones) and (4) Carlin-Type gold as lode and/or derived placer deposits. This mineral potential modelling study integrates data collected during the Nahanni Mineral and Energy Resource Assessment (MERA) undertaken from 2003 to 2007. The results have contributed to the process of determining the geographic boundaries of the proposed expansion of the Nahanni National Park Reserve. Four mineral potential maps were produced (one for each deposit type) using a knowledge-driven approach. A weighting scheme based on integrated mineral deposit and regional geological knowledge was derived for the various evidence maps for each deposit model using expert opinion. The four potential maps were then combined into a final potential map using a maximum operator. Plots showing the efficiency of the models (mineral potential maps) for predicting the known occurrences of the four deposit types show that partial data sets provide reasonable predictions of the remaining known mineral prospects, occurrences and deposits. Hydrocarbon potential from Nahanni MERA 1 was added to the final potential map to ensure that both mineral and energy potential data were incorporated into the park configuration modelling.     

地表喀斯特沉积中藻类作用的观察研究

本文通过对我国,南斯拉夫及英国的一些典型地表喀斯特沉积样品的微观观察(偏光显微镜及扫描电镜观察),并综合前人成果,讨论了多种陆相淡水碳酸盐沉积物(石灰华、藻微礁、钙壳核、荒漠叠层石及钙结壳等)沉积过程中藻类(蓝藻、硅藻、绿藻、红藻及轮藻的)钙化作用(充填、结壳及代换作用)、捕获和粘结作用、同化作用和分泌作用,并提出了一种地表喀斯特沉积中新的藻类作用的可能类型——构架作用(shoring effect)。     

Map Scale Effects on Estimating the Number of Undiscovered Mineral Deposits

Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale. Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to 50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring detailed and expensive exploration, and land-use planners benefit from reduced areas of concern.     

柴达木盆地灌丛沙丘稀土元素地球化学特征与物源

分析了柴达木盆地灌丛沙丘剖面风沙沉积物中稀土元素及其相关特征参数、分布模式和（La/Yb）_N-REE（稀土元素）物源特征。结果表明：灌丛沙丘剖面风沙沉积物中REE值100.52~163.47 μg·g^-1,接近于新疆灰钙土,而略低于中国黄土;LREE（轻稀土元素）值87.80~144.65 μg·g^-1,占总量86.62%~90.53%,决定了稀土总量的变化。总体表现为LREE相对富集,而HREE（重稀土元素）丰度相对较低,分馏特征基本相似,呈斜"L"型缓右倾斜,Eu大致呈现中度负异常的分配模式,而Ce未表现出明显异常,且更多地反映了其物源特性。其物源主要由东昆仑北麓冲积扇碎屑沉积物质经过风化、搬运、沉积而成,而并非来自于干旱期的湖底剥蚀物。总体而言,灌丛沙丘沉积过程稀土元素分异特征反映了灌丛沙丘发育时期柴达木盆地总体处于干燥的气候环境,化学风化作用弱,植被发育相对较差,成壤作用不明显。     

The study of the undiscovered mineral resources of the Tongass National Forest and adjacent lands,Southeastern Alaska

The quantitative probabilistic assessment of the undiscovered mineral resources of the 17.1-million-acre Tongass National Forest (the largest in the United States) and its adjacent lands is a nonaggregated, mineral-resource-tract-oriented assessment designed for land-planning purposes. As such, it includes the renewed use of gross-in-place values (GIPV's) in dollars of the estimated amounts of metal contained in the undiscovered resources as a measure for land-use planning.Southeastern Alaska is geologically complex and contains a wide variety of known mineral deposits, some of which have produced important amounts of metals during the past 100 years. Regional geological, economic geological, geochemical, geophysical, and mineral exploration history information for the region was integrated to define 124 tracts likely to contain undiscovered mineral resources. Some tracts were judged to contain more than one type of mineral deposit. Each type of deposit may contain one or more metallic elements of economic interest. For tracts where information was sufficient, the minimum number of as-yet-undiscovered deposits of each type was estimated at probability levels of 0.95, 0.90, 0.50, 0.10, and 0.05.The undiscovered mineral resources of the individual tracts were estimated using the U.S. Geological Survey's MARK3 mineral-resource endowment simulator; those estimates were used to calculate GIPV's for the individual tracts. Those GIPV's were aggregated to estimate the value of the undiscovered mineral resources of southeastern Alaska. The aggregated GIPV of the estimates is $40.9 billion.Analysis of this study indicates that (1) there is only a crude positive correlation between the size of individual tracts and their mean GIPV's: and (2) the number of mineral-deposit types in a tract does not dominate the GIPV's of the tracts, but the inferred presence of synorogenic-synvolcanic nickel-copper, porphyry copper skarn-related, iron skarn, and porphyry copper-molybdenum deposits does. The influence of this study on the U.S. Forest Service planning process is yet to be determined.     

Soils and landscape evolution of eolian plains: the Southern High Plains of Texas and New Mexico

Sheets of eolian sediment cover many areas of the earth's surface, sand seas, dune fields, and loess sheets being the best known examples of such features. Less well known are deposits of sandy, eolian sediment forming extensive plains. An excellent example of such a region is the semi-arid Southern High Plains (northwest Texas and eastern New Mexico). The level landscape of the area was created by deposition of multiple, extensive (≈ 80,000 km²) sheets of eolian sediment (Blackwater Draw Formation) over the past 1.4+ Ma. This deposit grades from sandy (southwest) to silty and clayey (northeast) and is up to 27 m thick. Surface soils (at least 30,000 and possibly 120,000 years old) are well developed (5YR hues, agrillic horizons, 1–2m thick with prismatic structure, Stage II–III calcic horizons) and are generally Paleustolls and Paleustalfs, with some Paleargids and Haplargids. Morphologic variation is due mainly to textural variation of the eolian parent material, although locally thickness of the parent material and wind erosion and cumulization are important factors, and locally slight variation in effective precipitation may be significant. The Blackwater Draw Formation contains as many as six well-developed buried soils, each formed in individual layers of eolian sediment, similar to or more strongly expressed (2.5YR hues, higher illuvial clay content) than the regional surface soils. The presence of the buried soils indicates that sedimentation was episodic and separated by long periods of relative landscape stability. Eolian processes also appear to have been important during the periods of stability and pedoenesis by providing clayey, calcareous dust that was added to the soil, promoting formation of the argillic and calcic horizons. The sedimentologic and pedologic uniformity of the deposit suggests that the regional environment has not varied significantly during the Quaternary except for periods of increased sedimentation or wind deflation. Underlying the Blackwater Draw Formation is an Upper Tertiary deposit (up to 36 m thick) of eolian sand, silt, and clay (Ogallala Formation). This deposit contains buried soils very similar to those in the Blackwater Draw Formation, suggesting that the geomorphic processes that created the Quaternary landscape of the Southern High Plains began to operate in the late Tertiary, perhaps as much as 11 million years ago.