172 resultados para soil moisture content
Resumo:
Global controls on month-by-month fractional burnt area (2000–2005) were investigated by fitting a generalised linear model (GLM) to Global Fire Emissions Database (GFED) data, with 11 predictor variables representing vegetation, climate, land use and potential ignition sources. Burnt area is shown to increase with annual net primary production (NPP), number of dry days, maximum temperature, grazing-land area, grass/shrub cover and diurnal temperature range, and to decrease with soil moisture, cropland area and population density. Lightning showed an apparent (weak) negative influence, but this disappeared when pure seasonal-cycle effects were taken into account. The model predicts observed geographic and seasonal patterns, as well as the emergent relationships seen when burnt area is plotted against each variable separately. Unimodal relationships with mean annual temperature and precipitation, population density and gross domestic product (GDP) are reproduced too, and are thus shown to be secondary consequences of correlations between different controls (e.g. high NPP with high precipitation; low NPP with low population density and GDP). These findings have major implications for the design of global fire models, as several assumptions in current models – most notably, the widely assumed dependence of fire frequency on ignition rates – are evidently incorrect.
Resumo:
The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.
Resumo:
Aims Potatoes are a globally important source of food whose production requires large inputs of fertiliser and water. Recent research has highlighted the importance of the root system in acquiring resources. Here measurements, previously generated by field phenotyping, tested the effect of root size on maintenance of yield under drought (drought tolerance). Methods Twelve potato genotypes, including genotypes with extremes of root size, were grown to maturity in the field under a rain shelter and either irrigated or subjected to drought. Soil moisture, canopy growth, carbon isotope discrimination and final yields were measured. Destructively harvested field phenotype data were used as explanatory variables in a general linear model (GLM) to investigate yield under conditions of drought or irrigation. Results Drought severely affected the small rooted genotype Pentland Dell but not the large rooted genotype Cara. More plantlets, longer and more numerous stolons and stolon roots were associated with drought tolerance. Previously measured carbon isotope discrimination did not correlate with the effect of drought. Conclusions These data suggest that in-field phenotyping can be used to identify useful characteristics when known genotypes are subjected to an environmental stress. Stolon root traits were associated with drought tolerance in potato and could be used to select genotypes with resilience to drought.
Resumo:
Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.
Resumo:
Aims: This experiment aimed to determine whether the soil application of organic fertilizers can help the establishment of cacao and whether shade alters its response to fertilizers. Study Design: The 1.6 ha experiment was conducted over a period of one crop year (between April 2007 and March 2008) at the Cocoa Research Institute of Ghana. It involved four cacao genotypes (T 79/501, PA 150, P 30 [POS] and SCA 6), three shade levels (‘light’, ‘medium’ and ‘heavy’) and two fertilizer treatments (‘no fertilizer’, and ‘140 kg/ha of cacao pod husk ash (CPHA) plus poultry manure at 1,800 kg/ha). The experiment was designed as a split-plot with the cacao genotypes as the main plot factor and shade x fertilizer combinations as the sub-plots. Methodology: Gliricidia sepium and plantains (Musa sapientum) were planted in different arrangements to create the three temporary shade regimes for the cacao. Data were collected on temperature and relative humidity of the shade environments, initial soil nutrients, soil moisture, leaf N, P and K+ contents, survival, photo synthesis and growth of test plants. Results: The genotypes P 30 [POS] and SCA 6 showed lower stomatal conductance under non-limiting conditions. In the rainy seasons, plants under light shade had the highest CO2 assimilation rates. However, in the dry season, plants under increased shade recorded greater photosynthetic rates (P = .03). A significant shade x fertilizer interaction (P = .001) on photosynthesis in the dry season showed that heavier shade increases the benefits that young cacao gets from fertilizer application in that season. Conversely, shade should be reduced during the wet seasons to minimize light limitation to assimilation. Conclusion: Under ideal weather conditions young cacao exhibits genetic variability on stomatal conductance. Also, to optimize plant response to fertilizer application shade must be adjusted taking the prevailing weather condition into account.
The effects of dairy management and processing on quality characteristics of milk and dairy products
Resumo:
Studies within the QLIF project reviewed in this article suggest that organic or low-input management is more likely to result in milk with fatty acid profiles that are higher in α-linolenic acid and/or beneficial isomers of conjugated linoleic acid and antioxidants with up to a 2.5-fold increase in some cases, relative to milk from conventional production. These advantages are preserved during processing, resulting in elevated contents or concentrations of these constituents in processed dairy products of organic or low input origin. Much of the literature suggests that these benefits are very likely to be a result of a greater reliance on forages in the dairy diets (especially grazed grass). Since the adoption of alternative breeds or crosses is often an integral part sustaining these low-input systems, it is not possible to rule out an interaction with genotype in these monitored herds. The results suggest that milk fat composition with respect to human health can be optimized by exploiting grazing in the diet of dairy cows. However, in many European regions this may not be possible due to extremes in temperature, soil moisture levels or both. In such cases milk quality can be maintained by the inclusion of oil seeds in the dairy diets.
Resumo:
We investigated the potential of soil moisture and nutrient amendments to enhance the biodegradation of oil in the soils from an ecologically unique semi-arid island. This was achieved using a series of controlled laboratory incubations where moisture or nutrient levels were experimentally manipulated. Respired CO2 increased sharply with moisture amendment reflecting the severe moisture limitation of these porous and semi-arid soils. The greatest levels of CO2 respiration were generally obtained with a soil pore water saturation of 50–70%. Biodegradation in these nutrient poor soils was also promoted by the moderate addition of a nitrogen fertiliser. Increased biodegradation was greater at the lowest amendment rate (100 mg N kg−1 soil) than the higher levels (500 or 1,000 mg N kg−1 soil), suggesting the higher application rates may introduce N toxicity. Addition of phosphorous alone had little effect, but a combined 500 mg N and 200 mg P kg−1 soil amendment led to a synergistic increase in CO2 respiration (3.0×), suggesting P can limit the biodegradation of hydrocarbons following exogenous N amendment.
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We investigated commensalism of water use among annual shallow-rooted and perennial deep-rooted pasture legumes by examining the effect of hydraulic lift by Cullen pallidum (N.T.Burb.) J.W.Grimes and Medicago sativa on growth, survival and nutrient uptake of Trifolium subterraneum L. A vertically split-root design allowed separate control of soil water in top and bottom soil. Thirty-five days after watering ceased in the top tube, but soil remained at field capacity in the bottom tube, an increase in shallow soil water content by hydraulic lift was 5.6 and 5.9 g kg−1 soil overnight for C. pallidum and M. sativa, respectively. Trifolium subterraneum in this treatment maintained higher leaf water potentials (with M. sativa) or exhibited a slower decline (with C. pallidum) than without companion perennial plants; and shoot biomass of T. subterraneum was 56% (with C. pallidum) and 67% (with M. sativa) of that when both top and bottom tubes were at field capacity. Uptake of rubidium (a potassium analog) and phosphorus by T. subterraneum was not facilitated by hydraulic lift. Interestingly, phosphorus content was threefold greater, and shoot biomass 1.5–3.3-fold greater when T. subterraneum was interplanted with C. pallidum compared with M. sativa, although dry weight of C. pallidum was much greater than that of M. sativa. This study showed that interplanting with deep-rooted perennial legumes has benefited the survival of T. subterraneum.
Resumo:
Fried products impose a health concerns due to considerable amount of oil they contain. Production of snack foods with minimal oil content and good management of oil during frying to minimise the production of toxic compounds continue to be challenging aims. This paper aims to investigate the possibility of producing a fat-free food snack by replacing frying oil with a non-fat medium. Glucose was melted and its temperature was then brought to 185°C and used to fry potato strips, to obtain a product referred here as glucose fries. The resulting product was compared with French fries prepared conventionally under conditions that resulted in similar final moisture content. The resulting products were also examined for crust formation, texture parameters, colour development and glucose content. Stereo microscope images showed that similar crusts were formed in the glucose fries and French fries. Texture parameters were found to be similar for both products at 5mm and 2 mm penetration depth. The maximum hardness at 2mm penetration depth was also similar for both products, but different from cooked potato. The colour development which characterised French fries was also observed in glucose fries. The glucose content in glucose fries was found to be twice the content of French fries, which is to be expected since glucose absorbed or adhered to the surface. In conclusion, glucose fries, with similar texture and colour characteristics to that of French fries, can be prepared by using a non-fat frying medium.
Resumo:
Poor wheat seed quality in temperate regions is often ascribed to wet production environments. We investigated the possible effect of simulated rain during seed development and maturation on seed longevity in wheat (Triticum aestivum L.) cv. Tybalt grown in the field (2008, 2009) or a polythene tunnel house (2010). To mimic rain, the seed crops were wetted from above with the equivalent of 30mm (2008, 2009) or 25mm rainfall (2010) at different stages of seed development and maturation (17 to 58 DAA, days after 50% anthesis), samples harvested serially, and subsequent air-dry seed longevity estimated. No pre-harvest sprouting occurred. Seed longevity (p50, 50% survival period in experimental hermetic storage at 40°C with c. 15% moisture content) in field-grown controls increased during seed development and maturation attaining maxima at 37 (2008) or 44 DAA (2009); it declined thereafter. Immediate effects of simulated rain at 17-58 DAA in field studies (2008, 2009) on subsequent seed longevity were negative but small, e.g. a 1-4 d delay in seed quality improvement for treatments early in development but with no damage detected at final harvests. In rainfall-protected conditions (2010), simulated rain close to harvest maturity (55-56 DAA) reduced longevity immediately and substantially, with greater damage from two sequential days of wetting than one; again, later harvests provided evidence of recovery in subsequent longevity. In the absence of pre-harvest sprouting, the potentially deleterious effects of rainfall to wheat seed crops on subsequent seed longevity may be reversible in full or in part.
Resumo:
Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.
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This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.
Resumo:
During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from seasonal forecast models to give a more detailed monthly outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of a monthly outlook column. This monthly outlook is an indication of the average likely conditions for that month and region and is not a definite prediction of weather impacts.
Resumo:
During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g. droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g. health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015 and SON 2015, a detailed monthly outlook from 5 modeling centres for Dec 2015 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of JF 2016 and MAM 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.
Resumo:
During the summer and autumn of 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and Dec 2015, a detailed monthly outlook from 4 modeling centres for Jan 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of Feb 2016, MAM 2016 and Jun 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.