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101.
102.
以南京市运粮河沉积物为研究对象,通过磷脂脂肪酸(PLFA)技术分析了不同水期城市纳污河流沉积物微生物群落结构特征。结果表明:在不同的水期运粮河沉积物微生物量出现了显著差异,温度是导致微生物量在丰、平、枯三期出现显著差异的主要因素(P<0.05);在相同水期,营养物质含量高的地方对应着高的微生物量;16:0 iso、17:0 anteiso、15:0 iso这几种PLFA所指示的革兰氏阳性菌(G+)是影响运粮河沉积物微生物群落构成的主要菌落,导致沉积物微生物群落结构出现显著差异的环境因素是水期;单不饱和/支链脂肪酸比值可以作为反映水环境系统整体营养水平的指标,在C/N比值升高时微生物会将单不饱和脂肪酸转变成环丙基或者饱和脂肪酸以适应新的环境;PLFA含量比[c(i15:0)+c(i17:0)]/[c(a15:0)+c(a17:0)]可以作为指示水环境碳素含量的标志。 相似文献
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沼泽湿地垦殖对土壤碳动态的影响 总被引:20,自引:7,他引:13
在中国科学院三江平原湿地生态试验站选取相邻的、土壤类型相同的小叶章沼泽化草甸以及不同开垦殖年限的已垦湿地农田,综合运用多种微生物指标,全面地评价沼泽湿地垦殖后土壤有机碳的动态。结果表明,沼泽湿地垦殖初期(1~3年),土壤微生物量碳(MBC)、微生物商以及基础呼吸(BR)都迅速降低,而代谢商(qCO2)、PR/BR和PR/MBC比值却不断升高。表明湿地垦殖后,有机碳的可利用性下降,微生物对碳源的利用效率降低,造成土壤有机碳的大量损失。各种微生物指标之间有密切的相关关系,综合这些微生物指标能够全面地、准确地评价沼泽湿地垦殖后土壤有机碳的动态。 相似文献
105.
Microbial populations in contaminant plumes 总被引:4,自引:1,他引:3
Received, May 1999/Revised, October 1999/Accepted, October 1999 相似文献
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Levels of bacterial indicators of pollution are related with marine salinity and turbidity at both high tide (HT) and low tide (LT). The salinity varied from values around 26.9 ppm at the LT and 28.6 ppm at the high tide but affected total and faecal coliform (FC) estimates. Salinity readings of 25–30 ppm produced microbial counts below 10−2 MPN/100 ml total coliforms (TCs) whereas salinity of 15–22 ppm produced a TC level of 4.6×10−4 MPN/100 ml. Turbidity peaks in the samples are accompanied by peaks of microbial contamination of the seawater indicating that the contamination is normally deposited at the marine sediment rather than in the water column. In fact, samples collected under heavy stormy weather, in which the water agitation resulted in turbidity values up to 68.3 NTU, produced maximum microbial counts. 相似文献
109.
中国南极长城站室内空气微生物含量七年前后的比较 总被引:3,自引:0,他引:3
中国南极长城站室内空气微生物含量的考察结果表明,七年后,虽然一些室内空气微生物含量有所下降,即空气质量有所改善,但总体来看,略是上升势。与友邻科考站相比,长城站的多少有点偏高。也比非南极的较高纬度的某些室内空气微生物含量高。结果意味着长城站尚有提高空气质量、改善环境状况的余地。 相似文献
110.
An avenue to integrate theoretical, experimental and field research methods to forecast water quality in water bodies for different scenarios of water management is proposed. Exploration of the laws of organization, stability and controllability of laboratory "ideal" water microbial communities (model ecosystems) is the basis to build the following biophysical research chain:to formalize with primary field information a conceptual block-diagram of a water ecosystem →to real chemical and other density-dependent and population-growth-controlling factors → to find our limiting factors for natural ecosystems → to conduct experiments with isolated chemical factors and hydrobionts to derive kinetic dependencies and quantitative parameters→ to transfer regularities of operation and kinetic dependencies to the natural ecosystem→ retrospective verification of the model on the base of available field and derived theoretical-experimental data →prognostic calculations for the scenario. Efficiency of the approach is demonstrated in microalgal "blooming" models for Krasnoyarsk and Kantat reservoirs and in prognostication of radioecological state of great Yenisei river:1) radionuclide distribution in the Yenisei''s bottom sediment is nonuniform-"spotty"; 2) it is theoretically shown, that due to biological interactions and tro-phical radioniclide migration there is "spotive" type of space radionuclide distribution. The research is to make use of the novel methods of ecological biophysics:Monitoring:spectral analysis of surface waters (algal pigments), fluorescent techniques to evaluate productivity and condition of algae; rapid bioassays for water toxicity (bioluminescence, chemotaxis techniques). Kinetic experiments:microcosms on evaluating self-purification rates; special cultivators to evaluate the rates of growth of hydrobionts and radioactive engulfing, nutrition spectra; methods of finding growth limiting factors. Models:application of Bellman Principle to optimizing the river water use; theory and peculiarities of microbiological decomposition of pollutants in the river ecosystem. The composition of Prognostication Simulation Model is the next:1) hydrodynamical unit to calculate 2-dimensional space-time rate of stream on any depth; 2) hydrophysical unit to calculate:water temperature and level of solar radiation inside the water body; 3) ecosystem unit to calculate dynamic of concentration of phytoplankton, zooplankton, bacteria, major chemical matters and pollutants in water, content pollutants inside of hydrobionfs cells and dynamic of bentos; 4) radioe-cological unit to forecast the dynamic of radionuclides in the water body and bottom, their hydro-bont''s concentration; 5) database. Reservoirs and river models are provided by monitoring and kinetic experiments data. 相似文献