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261.
We studied nine samples of igneous rocks from the inner wall of the Mariana Trench above the Challenger Deep from 4150 to 6100 m depth recovered by manned submersible and ROV. Samples from two regions that bracket the Moho were studied: (i) 7 samples from a N‐S transect a few km to the west of the Shinkai Seep Field; and (ii) 2 samples from the Shinkai Seep Field. Transect samples include olivine‐2 pyroxene hornblendites, amphibole basalts, basaltic andesite, and hornblende andesite. We analyzed three transect samples for 40Ar/39Ar ages; two yielded good plateau ages of 46.5 ±0.5 Ma (hornblendite) and 46.60 ±0.15 Ma (hornblende andesite). These results combined with previously published results, indicate that this crust formed during an intense 46–47 Ma magmatic episode that occurred 5–6 my after subduction initiation. Hornblendites and hornblende basalts formed from primitive magmas, as shown by high MgO (11–21 wt%), Ni (222–885 ppm) and Cr (412–1145 ppm) contents. Electron microprobe analyses indicate that hornblende is Na‐rich (up to 3.0 wt% Na2O) and that many samples have an atypically large range in plagioclase composition (i.e. individual samples have An < 10 to An 90 plagioclase). Two subgroups can be identified: a mostly deeper depleted suite and a mostly shallower enriched suite. These results indicate that (i) the crust–mantle boundary in this region is transitional, occurring over a ~ 1.5 km interval, with interlayered peridotite and hornblendites between 5800 and 4300 m; and (b) extension to form the Challenger Deep forearc segment occurred by combined stretching of old crust and injection of young basaltic magmas. In contrast to the mostly fresh nature of transect samples, the two samples from the Shinaki Seep Field are intensely altered peridotite and basalt.  相似文献   
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263.
With high‐resolution topography and imagery in fluvial environments, the potential to quantify physical fish habitat at the reach scale has never been better. Increased availability of hydraulic, temperature and food availability data and models have given rise to a host of species and life stage specific ecohydraulic fish habitat models ranging from simple, empirical habitat suitability curve driven models, to fuzzy inference systems to fully mechanistic bioenergetic models. However, few examples exist where such information has been upscaled appropriately to evaluate entire fish populations. We present a framework for applying such ecohydraulic models from over 905 sites in 12 sub‐watersheds of the Columbia River Basin (USA), to assess status and trends in anadromous salmon populations. We automated the simulation of computational engines to drive the hydraulics, and subsequent ecohydraulic models using cloud computing for over 2075 visits from 2011 to 2015 at 905 sites. We also characterize each site's geomorphic reach type, habitat condition, geomorphic unit assemblage, primary production potential and thermal regime. We then independently produce drainage network‐scale models to estimate these same parameters from coarser, remotely sensed data available across entire populations within the Columbia River Basin. These variables give us a basis for imputation of reach‐scale capacity estimates across drainage networks. Combining capacity estimates with survival estimates from mark–recapture monitoring allows a more robust quantification of capacity for freshwater life stages (i.e. adult spawning, juvenile rearing) of the anadromous life cycle. We use these data to drive life cycle models of populations, which not only include the freshwater life stages but also the marine and migration life stages through the hydropower system. More fundamentally, we can begin to look at more realistic, spatially explicit, tributary habitat restoration scenarios to examine whether the enormous financial investment on such restoration actions can help recover these populations or prevent their extinction. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   
264.
Aeolian sediment fingerprinting using a Bayesian mixing model   总被引:1,自引:0,他引:1       下载免费PDF全文
Identifying sand provenance in depositional aeolian environments (e.g. dunefields) can elucidate sediment pathways and fluxes, and inform potential land management strategies where windblown sand and dust is a hazard to health and infrastructure. However, the complexity of these pathways typically makes this a challenging proposition, and uncertainties on the composition of mixed‐source sediments are often not reported. This study demonstrates that a quantitative fingerprinting method within the Bayesian Markov Chain Monte Carlo (MCMC) framework offers great potential for exploring the provenance and uncertainties associated with aeolian sands. Eight samples were taken from dunes of the small (~58 km2) Ashkzar erg, central Iran, and 49 from three distinct potential sediment sources in the surrounding area. These were analyzed for 61 tracers including 53 geochemical elements (trace, major and rare earth elements (REE)) and eight REE ratios. Kruskal–Wallis H‐tests and stepwise discriminant function analysis (DFA) allowed the identification of an optimum composite fingerprint based on six tracers (Rb, Sr, 87Sr, (La/Yb)n, Ga and δCe), and a Bayesian mixing model was applied to derive the source apportionment estimates within an uncertainty framework. There is substantial variation in the uncertainties in the fingerprinting results, with some samples yielding clear discrimination of components, and some with less clear fingerprints. Quaternary terraces and fans contribute the largest component to the dunes, but they are also the most extensive surrounding unit; clay flats and marls, however, contribute out of proportion to their small outcrop extent. The successful application of these methods to aeolian sediment deposits demonstrates their potential for providing quantitative estimates of aeolian sediment provenances in other mixed‐source arid settings, and may prove especially beneficial where sediment is derived from multiple sources, or where other methods of provenance (e.g. detrital zircon U–Pb dating) are not possible due to mineralogical constraints. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   
265.
Morphological change in river channels is frequently evaluated in the context of mass balance sediment budgets. In a closed sediment budget, measurements of sediment influx and efflux are coupled with measured changes in channel topography to provide both spatial and temporal resolution, and independent estimates of the mass balance. For sediment budgets constructed over long river segments (~102 channel widths or greater) and long periods (~2 years or longer), spatial and temporal accumulation of measurement uncertainty, compounded by inadequate sampling frequency or spatial coverage, may produce indeterminate results. The degree of indeterminacy may be evaluated in the context of a signal-to-noise ratio (SNR), which is a function of the magnitude of the mass balance and the magnitudes of potential systematic uncertainties associated with measurements and incomplete sampling. We report on a closed sand budget consisting of measurements of flux and two morphological surveys for a 50-km segment of a large river over a 3-year period. Accurate reporting of the magnitude and sign of the change in sand storage was only possible by using state-of-the-art techniques with high temporal frequency and large spatial extent. Together, a sand flux and morphological mass balance revealed that sand evacuation was temporally concentrated (~100% of mass change occurred during 19% of the study period) and highly localized (70% of mass change occurred in 12% of the study segment). A SNR analysis revealed that uncertainty resulting from undersampling may approach or exceed that caused by measurement uncertainty and that daily sampling of suspended-sand concentration or repeat mapping of at least 50% of the river segment was required to determine the sand budget with SNR > 1. The approach used here to analyze sand budget uncertainty is especially applicable to other river systems with large temporal variability in sediment transport and large spatial variability in erosion and deposition. © 2018 John Wiley & Sons, Ltd.  相似文献   
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