986 resultados para Soil use


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We examined the reproductive consequences of differential nest site use in Fork-tailed Storm-Petrels (Oceanodroma furcata) in the Aleutian Islands, Alaska, where birds on islands where foxes were introduced nest in rocky substrate rather than in typical soil habitat. We investigated how physical and microclimatic nest site characteristics influenced storm-petrel breeding success 20 years after fox removal. We then examined whether those nest site characteristics that affected success were related to the amount of rock that composed the nest. In both years of our study, nest temperature had the strongest influence on chick survival and overall reproductive success, appearing in all the top models and alone explaining 14–35% of the variation in chick survival. The relationship between reproductive success and nest temperature was positive in both years, with higher survival in warmer nests. In turn, the best predictor of nest temperature was the amount of rock that composed the site. Rockier nests had colder average temperatures, which were driven by lower daily minimum temperatures, compared to nests with more soil. Thus, the rockiness of the nest site appeared to affect chick survival and overall reproductive success through its influence on nest temperature. This study suggests that the use of rocky nest sites, presumed to be a result of historic predation from introduced foxes, could decrease breeding success in this recovering population, and thus be a long-lasting effect of introduced predators.

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The Integrated Catchment Model of Nitrogen (INCA-N) was applied to the River Lambourn, a Chalk river-system in southern England. The model's abilities to simulate the long-term trend and seasonal patterns in observed stream water nitrate concentrations from 1920 to 2003 were tested. This is the first time a semi-distributed, daily time-step model has been applied to simulate such a long time period and then used to calculate detailed catchment nutrient budgets which span the conversion of pasture to arable during the late 1930s and 1940s. Thus, this work goes beyond source apportionment and looks to demonstrate how such simulations can be used to assess the state of the catchment and develop an understanding of system behaviour. The mass-balance results from 1921, 1922, 1991, 2001 and 2002 are presented and those for 1991 are compared to other modelled and literature values of loads associated with nitrogen soil processes and export. The variations highlighted the problem of comparing modelled fluxes with point measurements but proved useful for identifying the most poorly understood inputs and processes thereby providing an assessment of input data and model structural uncertainty. The modelled terrestrial and instream mass-balances also highlight the importance of the hydrological conditions in pollutant transport. Between 1922 and 2002, increased inputs of nitrogen from fertiliser, livestock and deposition have altered the nitrogen balance with a shift from possible reduction in soil fertility but little environmental impact in 1922, to a situation of nitrogen accumulation in the soil, groundwater and instream biota in 2002. In 1922 and 2002 it was estimated that approximately 2 and 18 kg N ha(-1) yr(-1) respectively were exported from the land to the stream. The utility of the approach and further considerations for the best use of models are discussed. (C) 2008 Elsevier B.V. All rights reserved.

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The uptake of arsenic (As) by plants from contaminated soils presents a health hazard that may affect the use of agricultural and former industrial land. Methods for limiting the hazard are desirable. A proposed remediation treatment comprises the precipitation of iron (Fe) oxides in the contaminated soil by adding ferrous sulfate and lime. The effects on As bioavailability were assessed using a range of vegetable crops grown in the field. Four UK locations were used, where soil was contaminated by As from different sources. At the most contaminated site, a clay loam containing a mean of 748 mg As kg(-1) soil, beetroot, calabrese, cauliflower, lettuce, potato, radish and spinach were grown. For all crops except spinach, ferrous sulfate treatment caused a significant reduction in the bioavailability of As in some part of the crop. Application of ferrous sulfate in solution, providing 0.2% Fe oxides in the soil (0-10 cm), reduced As uptake by a mean of 22%. Solid ferrous sulfate was applied to give concentrations of 0.5% and 1% Fe oxides: the 0.5% concentration reduced As uptake by a mean of 32% and the 1% concentration gave no significant additional benefit. On a sandy loam containing 65 mg As kg(-1) soil, there was tentative evidence that ferrous sulfate treatment up to 2% Fe oxides caused a significant reduction in lettuce As, but calabrese did not respond. At the other two sites, the effects of ferrous sulfate treatment were not significant, but the uptake of soil As was low in treated and untreated soils. Differences between sites in the bioavailable fraction of soil As may be related to the soil texture or the source of As. The highest bioavailability was found on the soil which had been contaminated by aerial deposition and had a high sand content. (C) 2003 Elsevier Science B.V. All rights reserved.

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Estimates of soil organic carbon (SOC) stocks and changes under different land use systems can help determine vulnerability to land degradation. Such information is important for countries in and areas with high susceptibility to desertification. SOC stocks, and predicted changes between 2000 and 2030, were determined at the national scale for Jordan using The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. For the purpose of this study, Jordan was divided into three natural regions (The Jordan Valley, the Uplands and the Badia) and three developmental regions (North, Middle and South). Based on this division, Jordan was divided into five zones (based on the dominant land use): the Jordan Valley, the North Uplands, the Middle Uplands, the South Uplands and the Badia. This information was merged using GIS, along with a map of rainfall isohyets, to produce a map with 498 polygons. Each of these was given a unique ID, a land management unit identifier and was characterized in terms of its dominant soil type. Historical land use data, current land use and future land use change scenarios were also assembled, forming major inputs of the modelling system. The GEFSOC Modelling System was then run to produce C stocks in Jordan for the years 1990, 2000 and 2030. The results were compared with conventional methods of estimating carbon stocks, such as the mapping based SOTER method. The results of these comparisons showed that the model runs are acceptable, taking into consideration the limited availability of long-term experimental soil data that can be used to validate them. The main findings of this research show that between 2000 and 2030, SOC may increase in heavily used areas under irrigation and will likely decrease in grazed rangelands that cover most of Jordan giving an overall decrease in total SOC over time if the land is indeed used under the estimated forms of land use. (C) 2007 Elsevier B.V. All rights reserved.

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The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.

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The precision farmer wants to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. Ordinary kriging can be used for prediction if the data are spatially dependent and there is a suitable variogram model. However, even if data are spatially correlated, there are often few soil sampling sites in relation to the area to be managed. If intensive ancillary data are available and these are coregionalized with the sparse soil data, they could be used to increase the accuracy of predictions of the soil properties by methods such as cokriging, kriging with external drift and regression kriging. This paper compares the accuracy of predictions of the plant available N properties (mineral N and potentially available N) for two arable fields in Bedfordshire, United Kingdom, from ordinary kriging, cokriging, kriging with external drift and regression kriging. For the last three, intensive elevation data were used with the soil data. The mean squared errors of prediction from these methods of kriging were determined at validation sites where the values were known. Kriging with external drift resulted in the smallest mean squared error for two of the three properties examined, and cokriging for the other. The results suggest that the use of intensive ancillary data can increase the accuracy of predictions of soil properties in arable fields provided that the variables are related spatially. (c) 2005 Elsevier B.V. All rights reserved.

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A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).

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Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

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Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.

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Silchester is the site of a major late Iron Age and Roman town (Calleva Atrebatum), situated in northern Hampshire (England (UK)) and occupied between the late first century BC and the fifth or sixth century AD. Extensive evidence of the nature of the buildings and the plan of the town was obtained from excavations undertaken between 1890 and 1909. The purpose of this study was to use soil geochemical analyses to reinforce the archaeological evidence particularly with reference to potential metal working at the site. Soil analysis has been used previously to distinguish different functions or land use activity over a site and to aid identification and interpretation of settlement features (Entwistle et al., 2000). Samples were taken from two areas of the excavation on a 1-metre grid. Firstly from an area of some 500 square metres from contexts of late first/early second century AD date throughout the entirety of a large 'town house' (House 1) from which there was prima facie evidence of metalworking.

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This investigation examines metal release from freshwater sediment using sequential extraction and single-step cold-acid leaching. The concentrations of Cd, Cr, Cu, Fe, Ni, Pb and Zn released using a standard 3-step sequential extraction (Rauret et al., 1999) are compared to those released using a 0.5 M HCl; leach. The results show that the three sediments behave in very different ways when subject to the same leaching experiments: the cold-acid extraction appears to remove higher relative concentrations of metals from the iron-rich sediment than from the other two sediments. Cold-acid extraction appears to be more effective at removing metals from sediments with crystalline iron oxides than the "reducible" step of the sequential extraction. The results show that a single-step acid leach can be just as effective as sequential extractions at removing metals from sediment and are a great deal less time-consuming.

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Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.

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Ochre is an unwanted waste product that accumulates in wetlands and streams draining abandoned coal and metal mines. A potential commercial use for ochre is to remediate As contaminated soil. Arsenic contaminated soil (605 mg kg(-1)) was mixed with different ochres (A, B and C) in a mass ratio of 1:1 and shaken in 20 mL of deionised water. After 72 h As concentration in solution was ca. 500 mu g kg(-1) in the control and 1-2.5 mu g kg(-1) in the ochre treated experiments. In a second experiment soil:ochre mixtures of 0.05-1:1 were shaken in 20 mL of deionised water for 24 h. For Ochres A and C, as Solution concentration was reduced to ca. 1 mu gkg(-1) by 0.2-1:1 ochre:soil mixtures. For Ochre B, as concentration only reached ca. 1 mu g kg(-1) in the 1:1 ochre:soil inix. Sorption of As was best modelled by a Freundlich isotherm using As sorption per mass of goethite in the ochre (log K= 1.64, n = 0.79, R-2 = 0.76, p <= 0.001). Efficiency of ochre in removing As from solution increased with increasing total Fe, goethite, citrate dithionite extractable Fe and surface area. (c) 2005 Elsevier Ltd. All rights reserved.

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Displacement studies on leaching of potassium (K+) were conducted under unsaturated steady state flow conditions in nine undisturbed soil columns (15.5 cm in diameter and 25 cm long). Pulses of K+ applied to columns of undisturbed soil were leached with distilled water or calcium chloride (CaCl2) at a rate of 18 mm h(-1). The movement of K+ in gypsum treated soil leached with distilled water was at a similar rate to that of the untreated soil leached with 15 mM CaCl2. The Ca2+ concentrations in the leachates were about 15 mM, the expected values for the dissolution of the gypsum. When applied K+ was displaced with the distilled water, K+ was retained in the top 10-12.5 cm depth of soil. In the undisturbed soil cores there is possibility of preferential flow and lack of K+ sorption. The application of gypsum and CaCl2 in the reclamation of sodic soils would be expected to leach K+ from soils. It can also be concluded that the use of sources of water for irrigation which have a high Ca2+ concentration can also lead to leaching of K+ from soil. Average effluent concentration of K+ during leaching period was 30.2 and 28.6 mg l(-1) for the gypsum and CaCl2 treated soils, respectively. These concentrations are greater than the recommended guideline of the World Health Organisation (12 mg K+ l(-1)).

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Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. (C) 2007 Elsevier B.V. All rights reserved.