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Green Lake Landslide is an ancient giant rock slide in gneiss and granodiorite located in the deeply glaciated Fiordland region of New Zealand. The landslide covers an area of 45 km2 and has a volume of about 27 km3. It is believed to be New Zealand's largest landslide, and possibly the largest landslide of its type on Earth. It is one of 39 known very large (106–107 m3) and giant (≥108 m3) postglacial landslides in Fiordland discussed in the paper. Green Lake Landslide resulted in the collapse of a 9 km segment of the southern Hunter Mountains. Slide debris moved up to 2.5 km laterally and 700 m vertically, and formed a landslide dam about 800 m high, impounding a lake about 11 km long that was eventually infilled with sediments. Geomorphic evidence supported by radiocarbon dating indicates that Green Lake Landslide probably occurred 12 000–13 000 years ago, near the end of the last (Otira) glaciation. The landslide is described, and its geomorphic significance, age, failure mechanism, cause, and relevance in the region are discussed, in relation to other large landslides and recent earthquake-induced landslides in Fiordland. The slope failure occurred on a low-angle fault zone undercut by glacial erosion, and was probably triggered by strong shaking (MM IX–X) associated with a large (≥ M 7.5–8) earthquake, on the Alpine Fault c. 80 km to the northwest. Geology was a major factor that controlled the style and size of Green Lake landslide, and in that respect it is significantly different from most other gigantic landslides. Future large earthquakes on the Alpine Fault in Fiordland are likely to trigger more very large and giant landslides across the region, causing ground damage and devastation on a scale that has not occurred during the last 160 years, with potentially disastrous effects on towns, tourist centres, roads, and infrastructure. The probability of such an event occurring within the next 50 years may be as high as 45%.  相似文献   
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This paper considers the problem of estimatingm, the number of components in a finite mixture of distributions from a parametric family. A step-up procedure using the bootstrap method is proposed. Some properties of the procedure are illustrated with simulation studies. An example of the method, applied to orientation of beach clasts, is given.  相似文献   
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The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   
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Abstract— The osmium isotope ratios and platinum‐group element (PGE) concentrations of impact‐melt rocks in the Chesapeake Bay impact structure were determined. The impact‐melt rocks come from the cored part of a lower‐crater section of suevitic crystalline‐clast breccia in an 823 m scientific test hole over the central uplift at Cape Charles, Virginia. The 187Os/188Os ratios of impact‐melt rocks range from 0.151 to 0.518. The rhenium and platinum‐group element (PGE) concentrations of these rocks are 30–270x higher than concentrations in basement gneiss, and together with the osmium isotopes indicate a substantial meteoritic component in some impact‐melt rocks. Because the PGE abundances in the impact‐melt rocks are dominated by the target materials, interelemental ratios of the impact‐melt rocks are highly variable and nonchondritic. The chemical nature of the projectile for the Chesapeake Bay impact structure cannot be constrained at this time. Model mixing calculations between chondritic and crustal components suggest that most impact‐melt rocks include a bulk meteoritic component of 0.01–0.1% by mass. Several impact‐melt rocks with lowest initial 187Os/188Os ratios and the highest osmium concentrations could have been produced by additions of 0.1%–0.2% of a meteoritic component. In these samples, as much as 70% of the total Os may be of meteoritic origin. At the calculated proportions of a meteoritic component (0.01–0.1% by mass), no mixtures of the investigated target rocks and sediments can reproduce the observed PGE abundances of the impact‐melt rocks, suggesting that other PGE enrichment processes operated along with the meteoritic contamination. Possible explanations are 1) participation of unsampled target materials with high PGE abundances in the impact‐melt rocks, and 2) variable fractionations of PGE during syn‐ to post‐impact events.  相似文献   
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"The paper reports the use of Australian Resources Information System to calculate two proximate populations (people living within (i) 150 and (ii) 500 km) for the centroids of each of 3,000 half by half degree geodetic grid cells covering Australia. The use of proximate population data is exemplified by computing a map of the eighteen regions collectively containing a maximum fraction of the Australian population." The data used are from the 1981 census.  相似文献   
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铁同位素的MC-ICP-MS测定方法与地质标准物质的铁同位素组成   总被引:22,自引:5,他引:17  
详细报道了在低分辨和高分辨模式下运用MC-ICP-MS进行Fe同位素比值高精度测试的方法,对Fe同位素测定过程中谱峰干扰、基质效应、浓度效应、仪器测试的长期重现性等问题进行了评估,并对两种运行模式的测试结果进行了对比.在95%的可信度范围内,所建方法的外部精度优于0.5ε/ainu,达到国际同类实验室的先进水平,并且低分辨和高分辨两种模式下获得的Fe同位素测试结果是一致的.在此基础上对国家地质标准物质GBW07105(玄武岩)和GBW 07111(花岗闪长岩)进行了Fe同位素测定.相对于Fe同位素国际标样IRMM-014,GBW07105的Fe同位素成分为:ε57Fe=1.9±0.3(20),ε56Fe=1.3±0.2(2σ),ε57/56Fe=0.6±0.1(2σ);GBW 07111的Fe同位素成分为:ε57Fe=1.8±0.4(2σ),ε56Fe=1.2±0.2(2σ),ε57/56Fe=0.6±0.1(2σ).  相似文献   
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Artificial reefs are spatially complex habitats and serve as good model systems to study patterns of community succession and the response of epibiota to environmental clines over small spatial scales. Here, we quantified spatial heterogeneity in community composition and diversity of fouling communities across a number of environmental gradients that included water depth, surface orientation of habitats, exposure to currents, and shelter. Assemblage structure was quantified by spatially replicated photo transects on a recently scuttled large navy ship off the East Australian coast, lying in 27 m of water. A rich assemblage of epifauna had colonized the wreck within a year, dominated by barnacles, sponges and bryozoans. Community structure varied significantly over small spatial scales of meters to tens of meters. Depth, surface orientation and exposure were the major environmental drivers. Assemblages were substantially less diverse and abundant on the deepest (23 m near the seafloor) part of the hull with residual antifouling paint, on sheltered surfaces inside the wreck, and on the sediment‐laden horizontal surfaces. Overall, the wrecks’ habitat complexity corresponds with small‐scale heterogeneity in the fouling communities. This study supports the notion that wrecks enhance local diversity and biomass within the habitat mosaic of their location, and habitat complexity may be an important mechanism for this, as demonstrated by the large spatial variability in the assemblages documented here.  相似文献   
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