944 resultados para Geology, Agricultural.


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Although shorebirds spending the winter in temperate areas frequently use estuarine and supratidal (upland) feeding habitats, the relative contribution of each habitat to individual diets has not been directly quantified. We quantified the proportional use that Calidris alpina pacifica (Dunlin) made of estuarine vs. terrestrial farmland resources on the Fraser River Delta, British Columbia, using stable isotope analysis (δ13C, δ15N) of blood from 268 Dunlin over four winters, 1997 through 2000. We tested for individual, age, sex, morphological, seasonal, and weather-related differences in dietary sources. Based on single- (δ13C) and dual-isotope mixing models, the agricultural habitat contributed approximately 38% of Dunlin diet averaged over four winters, with the balance from intertidal flats. However, there was a wide variation among individuals in the extent of agricultural feeding, ranging from about 1% to 95% of diet. Younger birds had a significantly higher terrestrial contribution to diet (43%) than did adults (35%). We estimated that 6% of adults and 13% of juveniles were obtaining at least 75% of their diet from terrestrial sources. The isotope data provided no evidence for sex or overall body size effects on the proportion of diet that is terrestrial in origin. The use of agricultural habitat by Dunlin peaked in early January. Adult Dunlin obtained a greater proportion of their diet terrestrially during periods of lower temperatures and high precipitation, whereas no such relationship existed for juveniles. Seasonal variation in the use of agricultural habitat suggests that it is used more during energetically stressful periods. The terrestrial farmland zone appears to be consistently important as a habitat for juveniles, but for adults it may provide an alternative feeding site used as a buffer against starvation during periods of extreme weather. Loss or reduction of agricultural habitat adjacent to estuaries may negatively impact shorebird fitness, with juveniles disproportionately affected.

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The Prairie Pothole Region of North America has been modified by agriculture during the past 100 yr, resulting in habitat loss, fragmentation, and degradation that have reduced the abundance and productivity of many wildlife species. The 1985 U.S. Farm Bill provided economic incentives to agriculture that are considered by many to be beneficial to nesting waterfowl and other wildlife. Canada has not experienced an equally comprehensive legislative initiative, which would seem to indicate that benefits to waterfowl in Canada should lag behind those in the United States. However, with the removal of some agricultural subsidies in Canada during the 1990s, the amount of perennial cover in the Canadian prairies increased to levels similar to those of the 1970s. Therefore, it is unclear whether and how the U.S. and Canadian prairies might differ with regard to habitat quality for nesting waterfowl. We used historical and contemporary data to compare temporal trends in duck nest success between the United States and Canada and to assess how mean nest success varied with proportion of cropland and wetland density. The data best supported models with nonlinear temporal trends that varied between the two countries and suggested that mean nest success in Canada declined from its high point in 1930s and remained below the long-term value of 0.16 until the end of the time series in 2005. Mean nest success in the United States also declined from its high point in the 1930s, but increased to above the long-term value of 0.25 during the early 2000s. Mean nest success varied negatively with proportion of cropland in both the United States and Canada. Mean nest success was positively correlated with pond density at Canadian sites, but showed only a weak association with pond density at U.S. sites. All models explained the low proportions of the variation in nest success, suggesting that unmeasured factors such as the abundance and identity of nest predators may have strong effects on nest success. Nonetheless, these results support earlier suggestions that agricultural policy that encourages permanent cover positively influences duck reproductive success. We also found that, for reasons that are not entirely clear, nest success for the same intensity of row cropping was generally higher in the United States than in Canada. Further research is required to elucidate the exact nature of the composition, size, and distribution of permanent cover that coincides with greater average nest success by dabbling ducks in the United States. In addition, the data suggest that the benefits that might accrue from increases in the amount of perennial cover in Canada would be better realized if these efforts are accompanied by strong measures to conserve wetlands.

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Many common bird species have declined as a result of agricultural intensification and this could be mitigated by organic farming. We paired sites for habitat and geographical location on organic and nonorganic farms in Ontario, Canada to test a priori predictions of effects on birds overall, 9 guilds and 22 species in relation to candidate models for farming practices (13 variables), local habitat features (12 variables), or habitat features that influence susceptibility to predation. We found that: (1) Overall bird abundance, but not richness, was significantly (p < 0.05) higher on organic sites (mean 43.1 individuals per site) than nonorganic sites (35.8 individuals per site). Significantly more species of birds were observed for five guilds, including primary grassland birds, on organic vs. nonorganic sites. No guild had higher richness or abundance on nonorganic farms; (2) Farming practice models were the best (ΔAIC < 4) for abundance of birds overall, primary grassland bird richness, sallier aerial insectivore richness and abundance, and abundance of ground nesters; (3) Habitat models were the best for overall richness, Neotropical migrant abundance, richness and abundance of Ontario-USA-Mexico (short-distance) migrants and resident richness; (4) Predation models were the best for richness of secondary grassland birds and ground feeders; (5) A combination of variables from the model types were best for richness or abundance overall, 13 of 18 guilds (richness and abundance) and 16 of 22 species analyzed. Five of 10 farming practice variables (including herbicide use, organic farm type) and 9 of 13 habitat variables (including hedgerow length, proportion of hay) were significant in best models. Risk modeling indicated that herbicide use could decrease primary grassland birds by one species (35% decline from 3.4 to 2.3 species) per site. Organic farming could benefit species of conservation concern by 49% (an increase from 7.6 to 11.4 grassland birds). An addition of 63 m of hedgerow could increase abundance and richness of short distance migrants by 50% (3.0 to 4.8 and 1.3 to 2.0, respectively). Increasing the proportion of hay on nonorganic farms to 50% could increase abundance of primary grassland bird by 40% (6.7 to 9.4). Our results provide support for alternative farmland designs and agricultural management systems that could enhance select bird species in farmland.

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Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

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The introduction of the EU Water Framework Directive requires policy to address non-point source pollution as part of an overall integrated strategy to improve the ecological status of water bodies. In this paper, we combine an economic optimisation framework with a dynamic simulation model of N transport in the Kennet Catchment to link decisions taken at the farm level to reductions in nitrate concentrations in the River Kennet. We examine a variety of policies targeted at reducing fertiliser use and changing the way in which farm land is used. We find that a tax on nitrogen emerges as the best policy both in terms of cost- and environmental effectiveness. Such a policy involves a considerable reduction in fertiliser use, as well as, a restructuring of land-use away from arable towards increased use of set-aside. Budgetary implications of such a radical move towards set-aside would be huge and hence unlikely to be politically palatable given the objective of reducing the EU budgetary allocation to agriculture. Additionally, the current rise in world demand for food may also mitigate calls for increasing the proportion of land taken out of agricultural production. Although the study succeeds in establishing a link between actions on the farm and nitrate concentrations in the stream water, further work is required to explore the effect of the retention of nitrates in the unsaturated zone and groundwater on this link.

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The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

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We have examined the contributions sucrose and sawdust make to the net immobilization of inorganic soil N and assimilation of both C and N into microbial biomass when they are used as part of a restoration plan to promote the establishment of indigenous vegetation on abandoned agricultural fields on the Central Hungarian Plain. Both amendments led to net N immobilization. Sucrose addition also led to mobilization of N from the soil organic N pool and its immobilization into microbial biomass, whereas sawdust addition apparently immobilized soil N into a non-biomass compartment or a biomass component that was not detected by the conventional biomass N assay (CHCl3 fumigation and extraction). This suggests that the N was either cycled through the biomass, but not immobilized within it, or that it was immobilized in a protected biomass fraction different to the fraction into which N was immobilized in response to sucrose addition.

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The aim of this study was to examine interrelationships between functional biochemical and microbial indicators of soil quality, and their suitability to differentiate areas under contrasting agricultural management regimes. The study included five 0.8 ha areas on a sandy-loam soil which had received contrasting fertility and cropping regimes over a 5 year period. These were organically managed vegetable, vegetable -cereal and arable rotations, an organically managed grass clover ley, and a conventional cereal rotation. The organic areas had been converted from conventional cereal production 5 years prior to the start of the study. All of the biochemical analyses, including light fraction organic matter (LFOM) C and N, labile organic N (LON), dissolved organic N and water-soluble carbohydrates showed significant differences between the areas, although the nature of the relationships between the areas varied between the different parameters, and were not related to differences in total soil organic matter content. The clearest differences were seen in LFOM C and N and LON, which were higher in the organic arable area relative to the other areas. In the case of the biological parameters, there were differences between the areas for biomass-N, ATP, chitin content, and the ratios of ATP: biomass and basal respiration: biomass. For these parameters, the precise relationships between the areas varied. However, relative to the conventionally managed area, areas under organic management generally had lower biomass-N and higher ATP contents. Arbuscular mycorrhizal fungus colonization potential was extremely low in the conventional area relative to the organic areas. Further, metabolic diversity and microbial community level physiological profiles, determined by analysis of microbial community metabolism using Biolog GN plates and the activities of eight key nutrient cycling enzymes, grouped the organic areas together, but separated them from the conventional area. We conclude that microbial parameters are more effective and consistent indicators of management induced changes to soil quality than biochemical parameters, and that a variety of biochemical and microbial analyses should be used when considering the impact of management on soil quality. (C) 2004 Elsevier Ltd. All rights reserved.

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Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

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The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.