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21.
China has long been the world’s most populous nation and faced the double challenge of ensuring its food security without causing catastrophic damage to the environment. Since the early 1960s, Chinese agricultural development has been premised on large domestic increases in nitrogen (N) fertilizer production and consumption. However, current utilization of fertilizer is far beyond optimum, with the fate of excess N largely unknown. Here, we report on N flows, losses, and use efficiency in the production and utilization of three major grain crops using data from 2004. We also use a scenario analysis to explore strategies for improving N use efficiency. Our calculations show that N use efficiency in food production and utilization is much lower than previously published estimates. Mean N surpluses of crop fields were 144 kg/ha for wheat, 184 kg/ha for rice, and 120 kg/ha for maize. We estimate that between 50% and 85% of N harvested as grain is lost for utilization by humans and animals. Fertilizer N use efficiency (FNUE) values in crop–animal system for wheat, rice, and maize were 13.4%, 11.3%, and 3.7%, respectively. This means 7.5, 8.9 and 27.1 kg of N fertilizer were required to produce 1 kg of N in food via fertilization for these three grains. Major room exists for improving the efficiency of N flow in Chinese crop systems. Our scenario analyses shows that increases in N use efficiency of fertilizer applied to cropland (RE), decreasing ratios of grain N headed to plant food processing (GUP), and increasing efficiency in animal production (ANU) would result in a marked decrease in N loss from these three crops amounting to one million ton of N, which accounted for 6% of total chemical fertilizer input. Improved N management in Chinese food production has major ramifications for global estimations of N use efficiency and environmental pollution by reactive N, particularly nitrous oxide emissions, a major anthropogenic contributor to global climate change.  相似文献   
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23.
Landscape Ecology - The Sunda clouded leopard is vulnerable to forest loss and fragmentation. Conservation of this species requires spatially explicit evaluations of the effects of landscape...  相似文献   
24.

Context

The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet.

Objectives

Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the training sample, (4) identify the multiple-scale drivers of recent forest loss and (5) predict future forest loss risk across Borneo.

Methods

We compared random forest machine learning and logistic regression in a multi-scale approach to model forest loss risk between 2000 and 2010 as a function of topographical variables and landscape structure, and applied the highest performing model to predict the spatial pattern of forest loss risk between 2010 and 2020. We utilized a naïve model as a null comparison and used the total operating characteristic AUC to assess model performance.

Results

Our analysis produced five main results. We found that: (1) random forest consistently outperformed logistic regression and the naïve model; (2) including landscape structure variables substantially improved predictions; (3) a ratio of occurrence to non-occurrence points in the training dataset that does not match the actual ratio in the landscape biases the predictions of both random forest and logistic regression; (4) forest loss risk differed between the three nations that comprise Borneo, with patterns in Kalimantan highly related to distance from the edge of the previous frontier of forest loss, while Malaysian Borneo showed a more diffuse pattern related to the structure of the landscape; (5) we predicted continuing very high rates of forest loss in the 2010–2020 period, and produced maps of the expected risk of forest loss across the full extent of Borneo.

Conclusions

These results confirm that multiple-scale modelling using landscape metrics as predictors in a random forest modelling framework is a powerful approach to landscape change modelling. There is immense immanent risk to Borneo’s forests, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo.
  相似文献   
25.
The development of low‐water‐input forages would be useful for improving the water‐use efficiency of livestock production in semi‐arid and arid regions. The desiccation‐tolerant (DT) species Sporobolus stapfianus Gandoger and two desiccation‐sensitive (DS) species, Sporobolus pyramidalis and Sporobolus fimbriatus (Trin.) Nees. (Poaceae), were evaluated for aerial biomass production and seed productivity under three different irrigation regimes. Sporobolus stapfianus displayed the least biomass production, whereas S. pyramidalis and S. fimbriatus produced up to 3.8‐ and 11.2‐fold greater dry biomass, respectively, at the highest irrigation rate of 12 334 l (0.01 acre‐feet). Sporobolus fimbriatus and to a lesser extent S. pyramidalis showed significant increases in biomass production in response to increased irrigation rates, whereas S. stapfianus did not. Sporobolus pyramidalis and S. fimbriatus exhibited 3.2‐ and 6.0‐fold greater seed production, respectively, in response to increased irrigation rates, whereas S. stapfianus showed only a 1.4‐fold increase. All Sporobolus species possessed forage quality traits (e.g. crude protein, fibre content) comparable to those of timothy, a forage grass grown widely in the Great Basin in the western United States. Micronutrient content exceeded the minimum requirements of beef cattle, without surpassing tolerable limits, with the exception of zinc, which appeared low in all three Sporobolus species. The low water requirements displayed by these species, combined with their acceptable forage qualities, indicate that these grasses have the potential to serve farmers and ranchers in semi‐arid and arid regions of the western United States where irrigation resources are limited.  相似文献   
26.
The focus of this review is maternal nutrition during the periconceptual period and offspring developmental outcomes in beef cattle, with an emphasis on the first 50 d of gestation, which represents the embryonic period. Animal agriculture in general, and specifically the beef cattle industry, currently faces immense challenges. The world needs to significantly increase its output of animal food products by 2050 and beyond to meet the food security and agricultural sustainability needs of the rapidly growing human population. Consequently, efficient and sustainable approaches to livestock production are essential. Maternal nutritional status is a major factor that leads to developmental programming of offspring outcomes. Developmental programming refers to the influence of pre-and postnatal factors, such as inappropriate maternal nutrition, that affect growth and development and result in long-term consequences for health and productivity of the offspring. In this review, we discuss recent studies in which we and others have addressed the questions, “Is development programmed periconceptually?” and, if so, “Does it matter practically to the offspring in production settings?” The reviewed studies have demonstrated that the periconceptual period is important not only for pregnancy establishment but also may be a critical period during which fetal, placental, and potentially postnatal development and function are programmed. The evidence for fetal and placental programming during the periconceptual period is strong and implies that research efforts to mitigate the negative and foster the positive benefits of developmental programming need to include robust investigative efforts during the periconceptual period to better understand the implications for life-long health and productivity.  相似文献   
27.
Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.  相似文献   
28.
In mobile animals, movement behavior can maximize fitness by optimizing access to critical resources and minimizing risk of predation. We sought to evaluate several hypotheses regarding the effects of landscape structure on American marten foraging path selection in a landscape experiencing forest perforation by patchcut logging. We hypothesized that in the uncut pre-treatment landscape marten would choose foraging paths to maximize access to cover types that support the highest density of prey. In contrast, in the post-treatment landscapes we hypothesized marten would choose paths primarily to avoid crossing openings, and that this would limit their ability to optimally select paths to maximize foraging success. Our limiting factor analysis shows that different resistant models may be supported under changing landscape conditions due to threshold effects, even when a species’ response to landscape variables is constant. Our results support previous work showing forest harvest strongly affects marten movement behavior. The most important result of our study, however, is that the influence of these features changes dramatically depending on the degree to which timber harvest limits available movement paths. Marten choose foraging paths in uncut landscapes to maximize time spent in cover types providing the highest density of prey species. In contrast, following landscape perforation by patchcuts, marten strongly select paths to avoid crossing unforested areas. This strong response to patch cutting reduces their ability to optimize foraging paths to vegetation type. Marten likely avoid non-forested areas in fragmented landscapes to reduce risk of predation and to benefit thermoregulation in winter, but in doing so they may suffer a secondary cost of decreased foraging efficiency.  相似文献   
29.
Ethanol produced from cellulosic biomass is examined as a large-scale transportation fuel. Desirable features include ethanol's fuel properties as well as benefits with respect to urban air quality, global climate change, balance of trade, and energy security. Energy balance, feedstock supply, and environmental impact considerations are not seen as significant barriers to the widespread use of fuel ethanol derived from cellulosic biomass. Conversion economics is the key obstacle to be overcome. In light of past progress and future prospects for research-driven improvements, a cost-competitive process appears possible in a decade.  相似文献   
30.
Spatial heterogeneity can constrain the movement of individuals and consequently genes across a landscape, influencing demographic and genetic processes. In this study, we linked information on landscape composition, movement behavior, and genetic differentiation to gain a mechanistic understanding of how spatial heterogeneity may influence movement and gene flow of bobcats in the agricultural landscape of Iowa (USA). We analyzed movement paths of 23 animals to parameterize landscape resistance surfaces, applied least cost path analysis to generate measures of effective geographic distance between DNA collection locations of 625 bobcats, and tested the correlation between genetic distance and the different models of geographic distance. We found that bobcats showed a strong preference for forest over any other habitat type, and that incorporating information on habitat composition both along the path and in the surrounding landscape provided the best model of movement. Measures of effective geographic distance were significantly correlated with genetic distance, but not once the effects of Euclidean distance were accounted for. Thus, despite the impact of habitat composition on movement behavior, we did not detect a signature of a landscape effect in genetic structure. Our results are consistent with the issue of limiting factors: the high uniformity of forest fragmentation across southern Iowa, the primary study area, results in a landscape resistance pattern virtually indistinguishable from the isolation-by-distance pattern. The northern portion of the state, however, is predicted to pose a high level of resistance to bobcat movement, which may impede the regional genetic connectivity of populations across the Midwest.  相似文献   
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