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1.
The present study used two mitochondrial markers (16S rRNA and COI) to assess the genetic diversity of a newly founded Lessepsian migrant mussel, Brachidontes pharaonis, in Tunisian waters. The species appears to be restricted to only one population in Rades Harbour, in the northern part of the country. Phylogenetic analyses revealed the monophyly of B. pharaonis in Tunisia. Both molecular markers revealed high genetic variability of the B. pharaonis population. Haplotype networks and demographic analyses confirmed the recent expansion events within this population. Multiple human-mediated introduction events involving several founder populations and intensive population growth rates are probably the main causes of the high polymorphism observed within this invasive mollusc.  相似文献   
2.
A growing body of evidence implies that the concept of 'treeless tundra' in eastern and northern Europe fails to explain the rapidity of Lateglacial and postglacial tree population dynamics of the region, yet the knowledge of the geographic locations and shifting of tree populations is fragmentary. Pollen, stomata and plant macrofossil stratigraphies from Lake Kurjanovas in the poorly studied eastern Baltic region provide improved knowledge of ranges of north‐eastern European trees during the Lateglacial and subsequent plant population responses to the abrupt climatic changes of the Lateglacial/Holocene transition. The results prove the Lateglacial presence of tree populations (Betula, Pinus and Picea) in the eastern Baltic region. Particularly relevant is the stomatal and plant macrofossil evidence showing the local presence of reproductive Picea populations during the Younger Dryas stadial at 12 900–11 700 cal. a BP, occurring along with Dryas octopetala and arctic herbs, indicating semi‐open vegetation. The spread of PinusBetula forest at ca. 14 400 cal. a BP, the rise of Picea at ca. 12 800 cal. a BP and the re‐establishment of PinusBetula forest at ca. 11 700 cal. a BP within a span of centuries further suggest strikingly rapid, climate‐driven ecosystem changes rather than gradual plant succession on a newly deglaciated land. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   
3.
本文使用交错的与非交错的标号法,证明了一类龙虾树优美。  相似文献   
4.
王赞红  许清海 《地理研究》2006,25(2):262-267
通过20012003年取得的尘暴和非尘暴天气大气花粉的对比研究,发现两类天气条件下大气花粉组合虽都以北京地区木本植物花粉为主,但尘暴天气样品中草本植物花粉数量有较多增加。根据尘暴活动和北京地区物候分析,推测这些草本植物花粉来自尘暴源区和路径区的表土沉积。基于上述认识,进一步对风成黄土古土壤层的花粉进行探讨,认为古土壤中草本植物花粉和木本植物花粉是同期沉积的,其木本植物花粉数量比较少可能是尘暴降尘导致草本植物花粉数增多所致。通过现代尘暴、非尘暴天气大气花粉特征的研究,对正确认识过去风成黄土和古土壤层中以草本植物花粉为主的孢粉组合特征提出了新的思路。  相似文献   
5.
This paper presents a detailed cost accounting of the processes involved in the production of flours from the mesocarps of the fruits of Prosopis alba and P. pallida to be used in human foods. The flours from both species are similar and contain 7–8% protein, 0·8–2% fat, 26–32% total dietary fiber and 48–59% sucrose. The data were based on actual production rates in use at the Universidad de Piura pilot plant using simple machinery. Machinery hourly charges were based on equivalent rental costs in order to avoid interest charge calculations. As opposed to other analyses which only included processing costs delivered to the plant, our analysis ascribed value to the owner of the trees in order to provide incentives to plant and care for the trees. The sensitivity analyses showed that the most economically important factor was the conversion efficiency of pods into flour. When a 40% conversion efficiency, such as that which has been obtained in both Peru and Argentina was obtained, and by-product credits for high fiber containing fraction were assumed, the wholesale selling price with a 5% marketing cost and a 40% profit direct costs was estimated to be $0·66 kg−1 for Peru (using a $0·40 h−1 labor rate ) and $1·76 kg−1 for Argentina (using a $1·5 h−1 labor rate).  相似文献   
6.
7.
Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km2 sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R2. Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R2) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R2 (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R2 scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R2 skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R2. The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
8.
To develop an evidence base to help predict the impacts of land management change on flood generation, four experimental sites were established on improved grassland used for sheep grazing at the Pontbren catchment in upland Wales, UK. At each site, three plots were established where surface runoff was measured, supplemented by measurements of soil infiltration rates and soil and vegetation physical properties. Following baseline monitoring, treatments were applied to two of the plots: exclusion of sheep (ungrazed) and exclusion of sheep and planting with native broadleaf tree species (tree planted), with the third plot acting as a control (grazed pasture). Due to a particularly dry summer that occurred pre‐treatment, the soil hydrological responses were initially impacted by the effects of the climate on soil structure. Nevertheless, treatments did have a clear influence on soil hydrological response. On average, post‐treatment runoff volumes were reduced by 48% and 78% in ungrazed and tree‐planted plots relative to the control, although all results varied greatly over the sites. Five years following treatment application, near‐surface soil bulk density was reduced and median soil infiltration rates were 67 times greater in plots planted with trees compared to grazed pasture. The results illustrate the potential use of upland land management for ameliorating local‐scale flood generation but emphasise the need for long‐term monitoring to more clearly separate the effects of land management from those of climatic variability. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
9.
The recent rise in agricultural commodity prices and the expectation that high price will persist have triggered a wave of farmland expansion in regions where land resources are still available. One such region is the former Soviet Union, where the collapse of socialism caused massive agricultural abandonment and where some of these lands are now being brought back into production. Yet, the extent and spatial patterns of recultivation, and what determines these patterns, remains unclear. We examined the extent of recultivation of abandoned agricultural land in Ukraine since 2007 using a new, satellite-based recultivation map and assessed the effect of biophysical and socioeconomic determinants on recultivation patterns using boosted regression trees. We found key predictors of recultivation to be related to the suitability of land for agriculture (i.e., soil quality, temperature). Accessibility to major cities was also important, with most recultivation happening closer to settlements, but this influence varied across Ukraine. Variables related to agricultural management (fertilizer input, mechanization) and demography were negligible in explaining recultivation in our analyses. These factors suggest that recultivation patterns were primarily driven by factors related to land productivity, with recultivation focusing on the most promising areas. Given the remaining large amount of unused agricultural land in Eastern Europe and the former Soviet Union, and considering that much abandonment occurred in areas only marginally suited to agriculture, our findings provide important insights into where recultivation can be expected to happen and thus for assessing the potential socioeconomic and environmental impacts of recultivation.  相似文献   
10.
The distribution of chemical elements at and near the Earth's surface, the so-called critical zone, is complex and reflects the geochemistry and mineralogy of the original substrate modified by environmental factors that include physical, chemical and biological processes over time.Geochemical data typically is illustrated in the form of plan view maps or vertical cross-sections, where the composition of regolith, soil, bedrock or any other material is represented. These are primarily point observations that frequently are interpolated to produce rasters of element distributions. Here we propose the application of environmental or covariate regression modelling to predict and better understand the controls on major and trace element geochemistry within the regolith. Available environmental covariate datasets (raster or vector) representing factors influencing regolith or soil composition are intersected with the geochemical point data in a spatial statistical correlation model to develop a system of multiple linear correlations. The spatial resolution of the environmental covariates, which typically is much finer (e.g. ∼90 m pixel) than that of geochemical surveys (e.g. 1 sample per 10-10,000 km2), carries over to the predictions. Therefore the derived predictive models of element concentrations take the form of continuous geochemical landscape representations that are potentially much more informative than geostatistical interpolations.Environmental correlation is applied to the Sir Samuel 1:250,000 scale map sheet in Western Australia to produce distribution models of individual elements describing the geochemical composition of the regolith and exposed bedrock. As an example we model the distribution of two elements – chromium and sodium. We show that the environmental correlation approach generates high resolution predictive maps that are statistically more accurate and effective than ordinary kriging and inverse distance weighting interpolation methods. Furthermore, insights can be gained into the landscape processes controlling element concentration, distribution and mobility from analysis of the covariates used in the model. This modelling approach can be extended to groups of elements (indices), element ratios, isotopes or mineralogy over a range of scales and in a variety of environments.  相似文献   
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