906 resultados para Site-specific recombination
Resumo:
The summer water balance of a typical Siberian polygonal tundra catchment is investigated in order to identify the spatial and temporal dynamics of its main hydrological processes. The results show that, besides precipitation and evapotranspiration, lateral flow considerably influences the site-specific hydrological conditions. The prominent microtopography of the polygonal tundra strongly controls lateral flow and storage behaviour of the investigated catchment. Intact rims of low-centred polygons build hydrological barriers, which release storage water later in summer than polygons with degraded rims and troughs above degraded ice wedges. The barrier function of rims is strongly controlled by soil thaw, which opens new subsurface flow paths and increases subsurface hydrological connectivity. Therefore, soil thaw dynamics determine the magnitude and timing of subsurface outflow and the redistribution of storage within the catchment. Hydraulic conductivities in the elevated polygonal rims sharply decrease with the transition from organic to mineral layers. This interface causes a rapid shallow subsurface drainage of rainwater towards the depressed polygon centres and troughs. The re-release of storage water from the centres through deeper and less conductive layers helps maintain a high water table in the surface drainage network of troughs throughout the summer.
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Ice-rich permafrost landscapes are sensitive to climate and environmental change due to the melt-out of ground ice during thermokarst development. Thermokarst processes in the northern Yukon Territory are currently not well-documented. Lake sediments from Herschel Island (69°36'N; 139°04'W) in the western Canadian Arctic provide a record of thermokarst lake development since the early Holocene. A 727 cm long lake sediment core was analyzed for radiographic images, magnetic susceptibility, granulometry, and biogeochemical parameters (organic carbon, nitrogen, and stable carbon isotopes). Based on eight calibrated AMS radiocarbon dates, the sediment record covers the last ~ 11,500 years and was divided into four lithostratigraphic units (A to D) reflecting different thermokarst stages. Thermokarst initiation at the study area began ~ 11.5 cal ka BP. From ~ 11.5 to 10.0 cal ka BP, lake sediments of unit A started to accumulate in an initial lake basin created by melt-out of massive ground ice and thaw subsidence. Between 10.0 and 7.0 cal ka BP (unit B) the lake basin expanded in size and depth, attributed to talik formation during the Holocene thermal maximum. Higher-than-modern summer air temperatures led to increased lake productivity and widespread terrain disturbances in the lake's catchment. Thermokarst lake development between 7.0 and 1.8 cal ka BP (unit C) was characterized by a dynamic equilibrium, where lake basin and talik steadily expanded into ambient ice-rich terrain through shoreline erosion. Once lakes become deeper than the maximum winter lake ice thickness, thermokarst lake sediments show a great preservation potential. However, site-specific geomorphic factors such as episodic bank-shore erosion or sudden drainage through thermo-erosional valleys or coastal erosion breaching lake basins can disrupt continuous deposition. A hiatus in the record from 1.8 to 0.9 cal ka BP in Lake Herschel likely resulted from lake drainage or allochthonous slumping due to collapsing shore lines before continuous sedimentation of unit D recommenced during the last 900 years.
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Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub-Arctic tundra are leaf area index (LT) and total foliar nitrogen (NT). LT and NT have been shown to be tightly coupled across PFTs in sub-Arctic tundra vegetation, which simplifies up-scaling by allowing quantification of the main drivers of P from remotely sensed LT. Our objective was to test the LT-NT relationship across multiple Arctic latitudes and to assess LT as a predictor of P for the pan-Arctic. Including PFT-specific parameters in models of LT-NT coupling provided only incremental improvements in model fit, but significant improvements were gained from including site-specific parameters. The degree of curvature in the LT-NT relationship, controlled by a fitted canopy nitrogen extinction co-efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (NM), and we show for the first time that LT-NT coupling is achieved across latitudes via canopy-scale trade-offs between NM and leaf mass per unit leaf area (LM). Site-specific parameters provided small but significant improvements in models of P based on LT and moss cover. Our results suggest that differences in LT-NT coupling between sites could be used to improve pan-Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.
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The ongoing oceanic uptake of anthropogenic carbon dioxide (CO2) is significantly altering the carbonate chemistry of seawater, a phenomenon referred to as ocean acidification. Experimental manipulations have been increasingly used to gauge how continued ocean acidification will potentially impact marine ecosystems and their associated biogeochemical cycles in the future; however, results amongst studies, particularly when performed on natural communities, are highly variable, which may reflect community/environment-specific responses or inconsistencies in experimental approach. To investigate the potential for identification of more generic responses and greater experimentally reproducibility, we devised and implemented a series (n = 8) of short-term (2-4 days) multi-level (>=4 conditions) carbonate chemistry/nutrient manipulation experiments on a range of natural microbial communities sampled in Northwest European shelf seas. Carbonate chemistry manipulations and resulting biological responses were found to be highly reproducible within individual experiments and to a lesser extent between geographically separated experiments. Statistically robust reproducible physiological responses of phytoplankton to increasing pCO2, characterised by a suppression of net growth for small-sized cells (<10 µm), were observed in the majority of the experiments, irrespective of natural or manipulated nutrient status. Remaining between-experiment variability was potentially linked to initial community structure and/or other site-specific environmental factors. Analysis of carbon cycling within the experiments revealed the expected increased sensitivity of carbonate chemistry to biological processes at higher pCO2 and hence lower buffer capacity. The results thus emphasise how biogeochemical feedbacks may be altered in the future ocean.
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The TEX86 paleotemperature proxy is based on archaeal glycerol dibiphytanyl glycerol tetraether (GDGT) lipids preserved in marine sediments, yet both the influence of different physiological factors on the structural distribution of GDGTs, and the mechanism(s) by which GDGTs are exported to marine sediments remain unclear. In particular, TEX86 temperatures derived directly from suspended particulate matter (SPM) in the water column can diverge strongly from corresponding in situ temperatures. Here we investigated the abundance and structural distribution of GDGTs in the South-west and Equatorial Atlantic Ocean by examining SPM collected from four surface 1000 m depth profiles spanning 48 degrees of latitude. The depth distribution of GDGTs was consistent with our current understanding of marine archaeal ecology, and specifically of ammonia-oxidizing Thaumarchaeota. Maximum GDGT concentrations occurred at the base of the primary NO2- maximum. Core GDGTs dominated the structural distribution in surface waters, while intact polar GDGTs - thought to potentially indicate live cells - were more abundant at all depths below the maximum NO2- concentration. When integrated through the upper 1000 m of the water column, > 98% of GDGTs were present in waters at and below the depth of the primary NO2- maximum. TEX86-calculated temperatures showed local minima at the depth of the NO2- maximum, while the ratio of GDGT 2:GDGT 3 [2/3] increased with depth throughout the upper water column. These results were used to model the depth of origin for GDGTs exported to sediments. By comparing our SPM data to published TEX86 values and [2/3] ratios from sediments near our study sites, we conclude that most GDGTs are exported from the depth of maximum GDGT concentrations, near the subsurface NO2- maximum (~80-250 m). This indicates that local ammonia oxidation dynamics are important regional controls on the GDGT ratios preserved in sediments. Predicting the extent to which subsurface variations in archaeal activity may influence the sedimentary TEX86 record will require a better understanding of how site-specific productivity and particle dynamics in the upper water column influence the depth of origin for exported organic matter.
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Because climate can affect xylem cell anatomy, series of intra-annual cell anatomical features have the potential to retrospectively supply seasonal climatic information. In this study, we explored the ability to extract information about water stress conditions from tracheid features of the Mediterranean conifer Juniperus thurifera L. Tracheidograms of four climatic years from two drought-sensitive sites in Spain were compared to evaluate whether it is possible to link intra-annual cell size patterns to seasonal climatic conditions. Results indicated site-specific anatomical adjustment such as smaller and thicker tracheids at the dryer site but also showed a strong climatic imprint on the intra-annual pattern of tracheid size. Site differences in cell size reflected expected structural adjustments against cavitation failures. Differences between intra-annual patterns, however, indicated a response to seasonal changes in water availability whereby cells formed under drought conditions were smaller and thicker, and vice versa. This relationship was more manifest and stable at the dryer site
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Background Energy Policy is one of the main drivers of Transport Policy. A number of strategies to reduce current energy consumption trends in the transport sector have been designed over the last decades. They include fuel taxes, more efficient technologies and changing travel behavior through demand regulation. But energy market has a high degree of uncertainty and the effectiveness of those policy options should be assessed. Methods A scenario based assessment methodology has been developed in the frame of the EU project STEPS. It provides an integrated view of Energy efficiency, environment, social and competitiveness impacts of the different strategies. It has been applied at European level and to five specific Regions. Concluding remarks The results are quite site specific dependent. However they show that regulation measures appear to be more effective than new technology investments. Higher energy prices could produce on their turn a deterioration of competitiveness and a threat for social goals.
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A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An)
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One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing
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Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates
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A total of 92 samples of street dust were collected in Luanda, Angola, were sieved below 100 μm, and analysed by ICP-MS for 35 elements after an aqua-regia digestion. The concentration and spatial heterogeneity of trace elements in the street dust of Luanda are generally lower than in most industrialized cities in the Northern hemisphere. These observations reveal a predominantly “natural” origin for the street dust in Luanda, which is also manifested in that some geochemical processes that occur in natural soils are preserved in street dust: the separation of uranium from thorium, and the retention of the former by carbonate materials, or the high correlation between arsenic and vanadium due to their common mode of adsorption on solid particles in the form of oxyanions. The only distinct anthropogenic fingerprint in the composition of Luanda's street dust is the association Pb–Cd–Sb–Cu (and to a lesser extent, Ba–Cr–Zn). The use of risk assessment strategies has proved helpful in identifying the routes of exposure to street dust and the trace elements therein of most concern in terms of potential adverse health effects. In Luanda the highest levels of risk seem to be associated (a) with the presence of As and Pb in the street dust and (b) with the route of ingestion of dust particles, for all the elements included in the study except Hg, for which inhalation of vapours presents a slightly higher risk than ingestion. However, given the large uncertainties associated with the estimates of toxicity values and exposure factors, and the absence of site-specific biometric factors, these results should be regarded as preliminary and further research should be undertaken before any definite conclusions regarding potential health effects are drawn.
Resumo:
Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak? digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ?373 ?m of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (?1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates.
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So far, the majority of reports on on-line measurement considered soil properties with direct spectral responses in near infrared spectroscopy (NIRS). This work reports on the results of on-line measurement of soil properties with indirect spectral responses, e.g. pH, cation exchange capacity (CEC), exchangeable calcium (Caex) and exchangeable magnesium (Mgex) in one field in Bedfordshire in the UK. The on-line sensor consisted of a subsoiler coupled with an AgroSpec mobile, fibre type, visible and near infrared (vis–NIR) spectrophotometer (tec5 Technology for Spectroscopy, Germany), with a measurement range 305–2200 nm to acquire soil spectra in diffuse reflectance mode. General calibration models for the studied soil properties were developed with a partial least squares regression (PLSR) with one-leave-out cross validation, using spectra measured under non-mobile laboratory conditions of 160 soil samples collected from different fields in four farms in Europe, namely, Czech Republic, Denmark, Netherland and UK. A group of 25 samples independent from the calibration set was used as independent validation set. Higher accuracy was obtained for laboratory scanning as compared to on-line scanning of the 25 independent samples. The prediction accuracy for the laboratory and on-line measurements was classified as excellent/very good for pH (RPD = 2.69 and 2.14 and r2 = 0.86 and 0.78, respectively), and moderately good for CEC (RPD = 1.77 and 1.61 and r2 = 0.68 and 0.62, respectively) and Mgex (RPD = 1.72 and 1.49 and r2 = 0.66 and 0.67, respectively). For Caex, very good accuracy was calculated for laboratory method (RPD = 2.19 and r2 = 0.86), as compared to the poor accuracy reported for the on-line method (RPD = 1.30 and r2 = 0.61). The ability of collecting large number of data points per field area (about 12,800 point per 21 ha) and the simultaneous analysis of several soil properties without direct spectral response in the NIR range at relatively high operational speed and appreciable accuracy, encourage the recommendation of the on-line measurement system for site specific fertilisation.
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This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.
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All crop models, whether site-specific or global-gridded and regardless of crop, simulate daily crop transpiration and soil evaporation during the crop life cycle, resulting in seasonal crop water use. Modelers use several methods for predicting daily potential evapotranspiration (ET), including FAO-56, Penman-Monteith, Priestley-Taylor, Hargreaves, full energy balance, and transpiration water efficiency. They use extinction equations to partition energy to soil evaporation or transpiration, depending on leaf area index. Most models simulate soil water balance and soil-root water supply for transpiration, and limit transpiration if water uptake is insufficient, and thereafter reduce dry matter production. Comparisons among multiple crop and global gridded models in the Agricultural Model Intercomparison and Improvement Project (AgMIP) show surprisingly large differences in simulated ET and crop water use for the same climatic conditions. Model intercomparisons alone are not enough to know which approaches are correct. There is an urgent need to test these models against field-observed data on ET and crop water use. It is important to test various ET modules/equations in a model platform where other aspects such as soil water balance and rooting are held constant, to avoid compensation caused by other parts of models. The CSM-CROPGRO model in DSSAT already has ET equations for Priestley-Taylor, Penman-FAO-24, Penman-Monteith-FAO-56, and an hourly energy balance approach. In this work, we added transpiration-efficiency modules to DSSAT and AgMaize models and tested the various ET equations against available data on ET, soil water balance, and season-long crop water use of soybean, fababean, maize, and other crops where runoff and deep percolation were known or zero. The different ET modules created considerable differences in predicted ET, growth, and yield.