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Frequent alteration in land cover often leads to decreased stability of ecosystems which can also increase the vulnerability of rural communities to externalities of environmental change. This study carried out in parts of the coast of southwestern Nigeria utilized topographic base maps and two-time Landsat TM imageries to assess the trend in land cover changes and ecosystems degradation for the three time periods 1965, 1986 and 2001. Remote sensing, geographic information systems and landscape pattern analysis were employed for data processing and analysis. The focus of the analysis was on land cover change, land degradation, and changes in landscape pattern resulting from interplay of natural and anthropogenic drivers.
The results show increased trend in human-induced land cover change with concomitant severe negative impacts on ecosystems and livelihoods. About 98,000ha (30% of the area) was seriously degraded as at 2001. About 33,000ha (10%) was under permanent saline water inundation with about 21 communities already dislocated. Loss of fragile ecosystems including marshland (from 7.7% in 1965 to 1% in 2001) and mangrove (from 14.6% in 1965 to 3.1% in 2001) was intense, while over 300 ponds/small lakes which are important for the local fishing economy have disappeared. About eighteen communities were also dislocated by erosion in a section around the southeastern parts of the coastline. Landscape metrics generated, suggested increased ecosystems perturbation and landscape fragmentation. The paper also discussed the implications of these rapid changes for ecosystems stability, food security and sustainable rural livelihoods in the area.  相似文献   
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In this paper we show how new technologies can be incorporated from the gathering of field data on wildlife distribution to the final stage of producing distribution maps. We describe an integrated framework for conducting wildlife censuses to obtain data to build predictive models of species distribution that when integrated in a GIS will produce a distribution map. Field data can be obtained with greater accuracy and at lower costs using a combination of Global Positioning System, Personal Digital Assistant, and specific wildlife recording software. Sampling design benefits from previous knowledge of environmental variability that can be obtained from free remote sensing data. Environmental predictors derived from this remote sensing information alone, combined with automatic procedures for predictor selection and model fitting, can render cost-effective predictive distribution models for wildlife. We show an example with guanaco distribution in the Patagonian steppes of Santa Cruz province, Argentina.  相似文献   
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In 2006–2007, an unusually high number of harbor porpoises (Phocoena phocoena) stranded along the Washington and Oregon coastlines. Spatiotemporal analyses were used to examine their ability to detect clusters of porpoise strandings during an unusual mortality event (UME) in the Pacific Northwest using stranding location data. Strandings were evaluated as two separate populations, outer coast and inland waters. The presence of global clustering was evaluated using the Knox spatiotemporal test, and the presence of local clusters was investigated using a spatiotemporal scan statistic (space–time permutation). There was evidence of global clustering, but no local clustering, supporting the hypothesis that strandings were due to more varied etiologies instead of localized causes. Further analyses at subregional levels, and concurrently assessing environmental factors, might reveal additional geographic distribution patterns. This article describes the spatial analytical tools applied in this study and how they can help elucidate the spatiotemporal epidemiology of other UMEs and assist in determining their causes. More than one spatial analytical technique should be used if the study objective is to detect and describe clustering in time and space and to generate hypotheses regarding causation of marine mammal disease and stranding events.  相似文献   
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关帝山森林景观异质性及其动态的研究   总被引:22,自引:4,他引:22  
以4期航片为基础资料,在ARC/INFO支持下,应用地理信息系统(GIS)技术,通过景观要素优势度指数、景观多样性指数、景观斑块密度、景观边缘密度、景观镶嵌度指数和景观聚集度指数5类指标,对关帝山林区50年代末以来的景观异质性及其动态特征进行了全面分析,并介绍了各指标的数据来源和计算方法,分析了各指标的实用性.在GIS支持下,上述各指标可以从不同侧面描述和反映景观异质结构特征,用于景观异质性动态变化规律的研究.研究表明,自50年代末以来,关帝山森林景观受环境异质性、植被自然演替和人为活动的共同控制,总体异质性发生了很大变化,3个时期表现出不同的动态特征.对人为活动频繁的次生林区的森林景观异质性动态变化的基本规律和控制因素进行了讨论  相似文献   
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Reliable estimates of feedstock resources are a prerequisite to the establishment of a biomass based-industry for energy and non food products. Field trials in the European Union (EU) show that Miscanthus spp. can produce high yields. Here we use a model (MISCANMOD) coupled with a GIS environment to estimate the contribution that Miscanthus could make to projected national electricity consumption. We describe the integration of different data sets, transformation procedures, and spatial analyses using GIS to produce energy statistics for the EU-25. Overall, Miscanthus grown on the 10% of arable land which is currently in set-aside could generate 282 TWh yr−1 electricity. This would meet 39% of the EU-25 target of 723 TWh yr−1 of electricity from renewable energy sources (RES) by 2010. As RES targets rise, land available for energy crops is also expected to increase. We consider three additional scenarios where Miscanthus could be grown on 10%, 20% and 35% of all agricultural land and we estimate it could generate respectively 345, 691 and 1209 TWh yr−1 of electrical energy. At a national scale France, Poland and Germany have the highest potentials for Miscanthus production based on agricultural land area (respectively 83, 52, 49 TWh yr−1 when 10% agricultural land is used). Finally, we reduced the scale to the EU NUTS2 (Nomenclature of Territorial Units for Statistics) regions to examine regional generation capacities. Key regions have been identified where national RES targets are exceeded. These regions could become net exporters of renewable energy.  相似文献   
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Abstract: Wildlife researchers often test whether animals use resources disproportionately relative to availability (i.e., selectively). However, the traditional estimate of availability at the landscape scale (resource proportions on the landscape) may be inaccurate and lead to false conclusions. We calculated the chance of falsely finding selection (type I error rate) when the traditional estimate of availability is used. True availability was estimated by Monte Carlo simulations with randomly located home ranges and compared to the traditional estimate to calculate type I error rates. Tests were conducted with α = 0.05 for different home-range sizes (1 to 1,000 km2) and 4 habitat patterns. Landscape proportions did not equal proportions of habitats in random home ranges (traditional estimate ≠ true availability). Type I error rates were ≥0.24 and increased with number of animals tested and decreased with home-range size and number of habitats. Therefore, researchers should use randomly located home ranges instead of landscape proportions to estimate availability at the landscape scale. We evaluated a goodness-of-fit test for comparing habitat proportions between randomly located home ranges and observed home ranges. Type I error rates for this method were ≤0.08, regardless of number of animals, home-range size, and number of habitats tested. We evaluated this method for 2 species with different home-range sizes and predicted habitat selection patterns: mountain lions (Puma concolor, ∼ 700 km2, relatively nonselective) and mule deer (Odocoileus hemionus, ∼ 16 km2, relatively selective). This method yielded results consistent with predictions, whereas the traditional method using landscape proportions to estimate availability did not. Randomly located, simulated home ranges are superior to landscape proportions for estimating availability.  相似文献   
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Skin coloration in indigenous peoples is strongly related to levels of ultraviolet radiation (UVR). In this study, the relationships of skin reflectance to seasonal UVR levels and other environmental variables were investigated, with the aim of determining which variables contributed most significantly to skin reflectance. The UVR data recorded by satellite were combined with environmental variables and data on human skin reflectance in a geographic information system (GIS). These were then analyzed visually and statistically through exploratory data analysis, correlation analysis, principal components analysis, least-squares regression analysis, and nonlinear techniques. The main finding of this study was that the evolution of skin reflectance could be almost fully modeled as a linear effect of UVR in the autumn alone. This linear model needs only minor modification, by the introduction of terms for the maximum amount of UVR, and for summer precipitation and winter precipitation, to account for almost all the variation in skin reflectance. A further significant finding was that the effect of summer UVR seems to reach a threshold beyond which further adaptation is difficult.  相似文献   
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