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1.
In the oldest commercial wine district of Australia, the Hunter Valley, there is the threat of soil salinization because marine sediments underlie the area. To understand the risk requires information about the spatial distribution of soil properties. Electromagnetic (EM) induction instruments have been used to identify and map the spatial variation of average soil salinity to a certain depth. However, soils vary with depth dependent on soil forming factors. We collected data from a single‐frequency and multiple‐coil DUALEM‐421 along a toposequence. We inverted this data using EM4Soil software and evaluated the resultant 2‐dimensional model of true electrical conductivity (σ – mS/m) with depth against electrical conductivity of saturated soil pastes (ECp – dS/m). Using a fitted linear regression (LR) model calibration approach and by varying the forward model (cumulative function‐CF and full solution‐FS), inversion algorithm (S1 and S2), damping factor (λ) and number of arrays, we determined a suitable electromagnetic conductivity image (EMCI), which was optimal (R2 = 0.82) when using the full solution, S2, λ = 3.6 and all six coil arrays. We conducted an uncertainty analysis of the LR model used to estimate the electrical conductivity of the saturated soil‐paste extract (ECe – dS/m). Our interpretation based on estimates of ECe suggests the approach can identify differences in salinity, how these vary with parent material and how topography influences salt distribution. The results provide information leading to insights into how soil forming factors and agricultural practices influence salinity down a toposequence and how this can guide soil management practices.  相似文献   
2.
Cabot's tragopan Tragopan caboti is an endemic and endangered pheasant of the lower montane forests of southeastern China. The typical habitats of the tragopan have been seriously fragmented because of forest management for timber production and farmland reclamation in recent years. The effects of the fragment size and isolation on the distribution of the cabot's tragopan were studied in Wuyanling Natural Reserve. Thirty one habitat fragments (2.5-48.5 ha) surrounded by non-habitat sapling coniferous forests, in an intensively managed forested landscape, were surveyed over four seasons for the occurrence of cabot's tragopan. Five of the 31 fragments were occupied in all four seasons and nine were not occupied. Both landscape and habitat factors affected the occurrence of cabot's tragopan, with landscape factors having the greatest effect. Large and less isolated habitat fragments containing a larger amount of the tree Daphniphyllum macropodum were occupied significantly more often than small, isolated fragments. The appearance of cabot's tragopan in the habitat fragments was best explained by the size of the fragments, the distance to the nearest suitable habitat and the amount of macropdous daphniphyllum trees. Our results could be used to improve the management of the forests where Cabot's tragopan occurs in southeastern China.  相似文献   
3.
在达尔文(1859)看来,新物种只有通过竞争或者自然选择的方式淘汰原有物种才能进入由其他物种占据的生境并成功定居下来。然而,新物种进入生境并成功定居还有另外一个途径,那就是由于超级居群能在全球尺度上改变整个地球环境,从而能在原有环境中创造出一些全新的微环境来,正是这些全新的微环境使新物种避开了和原有定居者的剧烈竞争,很容易地进入了一直由其他物种占据的生境中并成功地定居下来。换句话说,超级居群导致了全球环境的分化,导致了全球尺度上的生境多样性。同时,超级居群通过环境的异质化为新物种准备好了很多全新的微环境,新物种在全新的微环境中的成功定居实现了新物种和原有定居者的长期共存。而这种长期共存导致了整个生物圈的生物多样性的增加。超级居群是地球上很多新环境的创造者,是生境多样性和生物多样性之间的桥梁,据此就能很容易地解释新物种为什么不时能和原有定居者共存甚至依赖于原有定居者,从而导致二者间剧烈竞争缺失的现象。  相似文献   
4.
Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
5.
Lovett-Doust  J.  Biernacki  M.  Page  R.  Chan  M.  Natgunarajah  R.  Timis  G. 《Landscape Ecology》2003,18(6):621-633
Surprisingly few studies have considered the extent to which the nature of the ownership of land is associated with differences in biodiversity. We analysed ownership and other landscape-level effects on rare-species richness for both globally- and regionally-rare biota (including birds, herpetofauna, butterflies, mammals, and plants) in 289 designated natural areas (NAs) in southern Ontario, Canada. Information about each NA −including area, number of plant communities, ownership status and details of species diversity were collected from published sources. Length of perimeter of NA, relative isolation, and an estimate of fragmentation were measured using image analysis and GIS techniques. NAs were in general relatively small, with mean area of 158 ha (median 85 ha, range from 0.9 to 1278 ha) for private NAs; public NAs had mean area of 132 ha (median 16 ha, range from 0.1 to 1481 ha). Mean number of plant communities was 4.6 (median 4, range 1- 13) at private NAs and 3.8 (median 3, range 1-16) at public NAs. Our results show that, of several landscape-level factors, area had the greatest effects on rare-species richness and other biotic indices. Effects of area were followed by effects of plant community diversity, however this was itself significantly affected by area and the extent of perimeter of the NA. Both these factors were followed by effects of ownership of the NA and by effects of isolation of the NA (represented by minimum distance to nearest NA and by number of NAs in 10 km radius). Other landscape- level factors did not appear to have overall significant effects. Variation in area accounted for 0.1% to 29% of variation in number of rare species, with lower values for globally-rare, than for regionally-rare taxa. For all biotic groups, public ownership of NAs was associated with significantly greater rare-species richness compared to private ownership, even after other factors such as area were controlled. For all globally-rare biota except butterflies, area of NA had greater effects on rare-species richness than did ownership. Richness of regionally- rare birds was more affected by plant community diversity than by area of NA. Number of recorded plant communities accounted from 2.1% of variation in number of globally-rare plant species to as high as 31% of variation in regionally-rare butterflies. The diversity of plant communities was itself influenced by total site area (accounting for 45% of variation), extent of elongation of the NA, and both external- and interior- edge perimeters. Public NAs had greatest numbers of rare biota and so should be a significant focus for conservation programs. Smaller, privately-owned patches of natural area dominate (by number and area) in this densely populated region and their significance should not be overlooked. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
6.
In this paper we show how the spatialconfiguration of habitat quality affects the spatial spread of apopulation in a heterogeneous environment. Our main result is thatfor species with limited dispersal ability and a landscape withisolated habitats, stepping stone patches of habitat greatlyincrease the ability of species to disperse. Our results showthat increasing reproductive rate first enables and thenaccelerates spatial spread, whereas increasing the connectivity has aremarkable effect only in case of low reproductive rates. Theimportance of landscape structure varied according to thedemographic characteristics of the population. To show this wepresent a spatially explicit habitat model taking into accountpopulation dynamics and habitat connectivity. The population dynamicsare based on a matrix projection model and are calculated on eachcell of a regular lattice. The parameters of the Leslie matrix dependon habitat suitability as well as density. Dispersal between adjacentcells takes place either unrestricted or with higher probability inthe direction of a higher habitat quality (restricted dispersal).Connectivity is maintained by corridors and stepping stones ofoptimal habitat quality in our fragmented model landscape containinga mosaic of different habitat suitabilities. The cellular automatonmodel serves as a basis for investigating different combinations ofparameter values and spatial arrangements of cells with high and lowquality.This revised version was published online in May 2005 with corrections to the Cover Date.  相似文献   
7.
The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
8.
Johnson  Chris J.  Boyce  Mark S.  Mulders  Robert  Gunn  Anne  Gau  Rob J.  Cluff  H. Dean  Case  Ray L. 《Landscape Ecology》2004,19(8):869-882
Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.  相似文献   
9.
Total weed control within a crop is both difficult and expensive to achieve, so that some weeds will often remain to set seed. The seed production resulting from these weeds will ultimately affect the sustainability of the weed control strategy. If too much is allowed to return each season there could be a gradual, but significant, increase in the potential weed flora over a number of seasons. Field trials were carried out in 2000 and 2001 to quantify the potential magnitude of this weed seed return from Chenopodium album L., grown at two planting densities either in pure stands or in competition with one of two crops (cabbage or onion). Crop and weed weights and weed seed production were notably greater in 2001. Both dry weight and seed production of C. album were suppressed by increasing planting density or by the presence of crop, with cabbage having a more suppressive effect. Despite the plasticity in seed production, a linear relationship was demonstrated between log weed seed production and log weed biomass that was robust over a range of competitive situations with onion and cabbage, at different planting densities and in growing seasons. The study also demonstrated that the relationship could be combined with an existing simple competition model to allow the consequences of incomplete weed control to be assessed in terms of potential weed seed return.  相似文献   
10.
Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R2; 0.29–0.69) outperformed both PTF‐1 (R2; 0.11–0.18) and PTF‐2 (R2; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R2; 0.61–0.86) performed comparably as PTF‐1 (R2; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R2; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).  相似文献   
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