962 resultados para Weather types
Resumo:
1. Changes in the frequency of extreme events, such as droughts, may be one of the most significant impacts of climate change for ecosystems. Models predict more frequent summer droughts in much of England: this paper investigates the impact on different types of plants in an ex-arable grassland community. 2. A long-term experiment simulated increased and decreased summer precipitation. Substantial interannual variation allowed the effects of summer drought to be tested in combination with wet and dry weather in other seasons. This is important, as climate models predict increased winter precipitation. 3. Total cover abundance in early summer increased with increasing water supply in the previous summer; there was no effect of winter precipitation. Productivity is therefore likely to decrease with more frequent summer droughts, with no mitigating effect of wetter winters. 4. The percentage cover of perennial grasses declined during a natural drought in 1995-97; this was exacerbated by the experimental drought treatment and reduced by supplemented rainfall. Simultaneously, short-lived ruderal species increased; this was greatest in drought treatments and least with supplemented rainfall. 4. These trends were subsequently reversed during several years of unusually wet weather, with perennial grasses increasing and short-lived forbs decreasing. This occurred even in experimentally droughted plots, and we propose that it resulted from rapid coverage of gaps during wet autumns and winters. 6. Deep-rooted species generally proved to be more drought resistant, but there were exceptions. 7. We conclude that increased frequency of summer droughts could have serious implications for the establishment and successional development of ex-arable grasslands. Increased winter precipitation would moderate the impact on species composition, but not on productivity.
Resumo:
Two models for predicting Septoria tritici on winter wheat (cv. Ri-band) were developed using a program based on an iterative search of correlations between disease severity and weather. Data from four consecutive cropping seasons (1993/94 until 1996/97) at nine sites throughout England were used. A qualitative model predicted the presence or absence of Septoria tritici (at a 5% severity threshold within the top three leaf layers) using winter temperature (January/February) and wind speed to about the first node detectable growth stage. For sites above the disease threshold, a quantitative model predicted severity of Septoria tritici using rainfall during stern elongation. A test statistic was derived to test the validity of the iterative search used to obtain both models. This statistic was used in combination with bootstrap analyses in which the search program was rerun using weather data from previous years, therefore uncorrelated with the disease data, to investigate how likely correlations such as the ones found in our models would have been in the absence of genuine relationships.
Resumo:
A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non-milk producing livestock farms.
Resumo:
The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society
Resumo:
Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.
Resumo:
The area of soil disturbed using a single tine is well documented. However, modern strip tillage implements using a tine and disc design have not been assessed in the UK or in mainland Europe. Using a strip tillage implement has potential benefits for European agriculture where economic returns and sustainability are key issues. Using a strip tillage system a narrow zone is cultivated leaving most of the straw residue on the soil surface. Small field plot experiments were undertaken on three soil types and the operating parameters of forward speed, tine depth and tine design were investigated together with measurements of seedbed tilth and crop emergence. The type of tine used was found to be the primary factor in achieving the required volume of disturbance within a narrow zone whilst maintaining an area of undisturbed soil with straw residue on the surface. The winged tine produced greater disturbance at a given depth compared with the knife tine. Increasing forward speed did not consistently increase the volume of disturbance. In a sandy clay loam the tilth created and emergence of sugar beet by strip tillage and ploughing were similar but on a sandy loam the strip tillage treatments generally gave a finer tilth but poorer emergence particularly at greater working depth.
Resumo:
In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.
Resumo:
1. Dispersal is regarded as critical to the stability of existing populations and the spread of invading species, but empirical data on the effect of travelling conditions during the transfer phase are rare. We present evidence that both timing and distance of ex-natal dispersal in buzzards (Buteo buteo) are strongly affected by weather. 2. Dispersal was recorded more often when the wind changed to a more southerly direction from the more common westerly winds, and when minimum temperatures were lower. The effect of wind direction was greatest in the winter and minimum temperature was most important in the autumn. Poor weather did not appear to initiate dispersal. 3. Dispersal distance was most strongly correlated with maximum temperature during dispersal and wind direction in the following 5-day period. Combined with the sex of the buzzard these three variables accounted for 60% of the variation in dispersal distance. 4. These results are important for conservationists who manage species recovery programs and wildlife managers who model biological invasions.
Resumo:
Termites are an important component of tropical soil communities and have a significant affect on the structure and nutrient content of soil. Digestion in termites is related to gut structure, gut physico-chemical conditions and gut symbiotic microbiota. Here we describe the use of 16S rRNA gene sequencing and Terminal-restriction Fragment Length Polymorphism (T-RFLP) analysis to examine methanogenic Archaea (MA) in the guts and food-soil of the soil-feeder Cubitermes fungifaber Sjostedt across a range of soil types. If they are strictly vertically inherited, then MA in guts should be the same in all individuals even if the soils differ across sites. In contrast, gut MA should reflect what is present in soil if populations are merely a reflection of what is ingested as the insects forage. We show clear differences between the euryarchaeal communities in termite guts and in food-soils from five different sites. Analysis of 16S rRNA gene clones indicated little overlap between the gut and soil communities. Gut clones were related to a termite-derived Methanomicrobiales cluster, to Methanobrevibacter and, surprisingly, to the haloalkaliphile Natronococcus. Soil clones clustered with Methanosarcina, Methanomicrococcus or Rice Cluster I. T-RFLP analysis indicated that the archaeal communities in the soil samples differed from site to site, whereas those in termite guts were similar between sites. There was some overlap between the gut and soil communities but these may represent transient populations in either guts or soil. Our data does not support the hypothesis that termite gut MA are derived from their food soil but also does not support a purely vertical transmission of gut microflora.
Resumo:
Termites are an important component of tropical soil communities and have a significant effect on the structure and nutrient content of soil. Digestion in termites is related to gut structure, gut physicochemical conditions, and gut symbiotic microbiota. Here we describe the use of 16S rRNA gene sequencing and terminal-restriction fragment length polymorphism (T-RFLP) analysis to examine methanogenic archaea (MA) in the guts and food-soil of the soil-feeder Cubitermes fungifaber Sjostedt across a range of soil types. If these MA are strictly vertically inherited, then the MA in guts should be the same in all individuals even if the soils differ across sites. In contrast, gut MA should reflect what is present in soil if populations are merely a reflection of what is ingested as the insects forage. We show clear differences between the euryarchaeal communities in termite guts and in food-soils from five different sites. Analysis of 16S rRNA gene clones indicated little overlap between the gut and soil communities. Gut clones were related to a termite-derived Methanomicrobiales cluster, to Methanobrevibacter and, surprisingly, to the haloalkaliphile Natronococcus. Soil clones clustered with Methanosarcina, Methanomicrococcus, or rice cluster I. T-RFLP analysis indicated that the archaeal communities in the soil samples differed from site to site, whereas those in termite guts were similar between sites. There was some overlap between the gut and soil communities, but these may represent transient populations in either guts or soil. Our data do not support the hypothesis that termite gut MA are derived from their food-soil but also do not support a purely vertical transmission of gut microflora.
Resumo:
This study analyzes the short-term consequences of visitors' use of different types of exhibits (i.e., "exemplars of phenomena" and "analogy based") together with the factors affecting visitors' understanding of and their evaluation of the use of such exhibits. One hundred and twenty five visitors (either alone or in groups) were observed during their interaction and interviewed immediately afterwards. Findings suggest that the type of exhibit constrains the nature of the understanding achieved. The use of analogical reasoning may lead to an intended causal explanation of an exhibit that is an exemplar of a phenomenon, but visitors often express misconceptions as a consequence of using this type of exhibit. Analogy-based exhibits are often not used as intended by the designer. This may be because visitors do not access the source domain intended; are unaware of the use of analogy per se (in particular, when the exhibit is of the subtype "only showing similarities between relationships"); only acquire fragmentary knowledge about the target; or fail to use analogical reasoning of which they were capable. Furthermore, exhibits related to everyday world situations are recognized to have an immediate educative value for visitors. Suggestions for enhancing the educative value of exhibits are proposed.
Resumo:
MPJ Express is our implementation of MPI-like bindings for Java. In this paper we discuss our intermediate buffering layer that makes use of the so-called direct byte buffers introduced in the Java New I/O package. The purpose of this layer is to support the implementation of derived datatypes. MPJ Express is the first Java messaging library that implements this feature using pure Java. In addition, this buffering layer allows efficient implementation of communication devices based on proprietary networks such as Myrinet. In this paper we evaluate the performance of our buffering layer and demonstrate the usefulness of direct byte buffers. Also, we evaluate the performance of MPJ Express against other messaging systems using Myrinet and show that our buffering layer has made it possible to avoid the overheads suffered by other Java systems such as mpiJava that relies on the Java Native Interface.