49 resultados para spatial and temporal patterns

em CentAUR: Central Archive University of Reading - UK


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Salmonella is the second most commonly reported human foodborne pathogen in England and Wales, and antimicrobial-resistant strains of Salmonella are an increasing problem in both human and veterinary medicine. In this work we used a generalized linear spatial model to estimate the spatial and temporal patterns of antimicrobial resistance in Salmonella Typhimurium in England and Wales. Of the antimicrobials considered we found a common peak in the probability that an S. Typhimurium incident will show resistance to a given antimicrobial in late spring and in mid to late autumn; however, for one of the antimicrobials (streptomycin) there was a sharp drop, over the last 18 months of the period of investigation, in the probability of resistance. We also found a higher probability of resistance in North Wales which is consistent across the antimicrobials considered. This information contributes to our understanding of the epidemiology of antimicrobial resistance in Salmonella.

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The spatial and temporal effect of distractor related inhibition on stimulus elicited (reflexive) and goal driven (voluntary) saccades, was examined using saccade trajectory deviations as a measure. Subjects made voluntary and reflexive saccades to a target location on the vertical midline, while the distance of a distractor from the target was systematically manipulated. The trajectory curvature of both voluntary and reflexive saccades was found to be subject to individual differences. Saccade curvature was found to decrease monotonically with increasing distractor distance from target for some subjects while for others no reduction in curvature or even an increase was found. These results could not be explained by latency differences or landing position effects. The different patterns of distractor effects on saccade trajectories suggest the additional influence of a non-spatial inhibitory mechanism. (c) 2005 Elsevier Ltd. All rights reserved.

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This paper examines the interaction of spatial and dynamic aspects of resource extraction from forests by local people. Highly cyclical and varied across space and time, the patterns of resource extraction resulting from the spatialtemporal model bear little resemblance to the patterns drawn from focusing either on spatial or temporal aspects of extraction alone. Ignoring this variability inaccurately depicts villagers’ dependence on different parts of the forest and could result in inappropriate policies. Similarly, the spatial links in extraction decisions imply that policies imposed in one area can have unintended consequences in other areas. Combining the spatialtemporal model with a measure of success in community forest management—the ability to avoid open-access resource degradation—characterizes the impact of incomplete property rights on patterns of resource extraction and stocks.

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ATSR-2 active fire data from 1996 to 2000, TRMM VIRS fire counts from 1998 to 2000 and burn scars derived from SPOT VEGETATION ( the Global Burnt Area 2000 product) were mapped for Peru and Bolivia to analyse the spatial distribution of burning and its intra- and inter-annual variability. The fire season in the region mainly occurs between May and October; though some variation was found between the six broad habitat types analysed: desert, grassland, savanna, dry forest, moist forest and yungas (the forested valleys on the eastern slope of the Andes). Increased levels of burning were generally recorded in ATSR-2 and TRMM VIRS fire data in response to the 1997/1998 El Nino, but in some areas the El Nino effect was masked by the more marked influences of socio-economic change on land use and land cover. There were differences between the three global datasets: ATSR-2 under-recorded fires in ecosystems with low net primary productivities. This was because fires are set during the day in this region and, when fuel loads are low, burn out before the ATSR-2 overpass in the region which is between 02.45 h and 03.30 h. TRMM VIRS was able to detect these fires because its overpasses cover the entire diurnal range on a monthly basis. The GBA2000 product has significant errors of commission (particularly areas of shadow in the well-dissected eastern Andes) and omission (in the agricultural zone around Santa Cruz, Bolivia and in north-west Peru). Particular attention was paid to biomass burning in high-altitude grasslands, where fire is an important pastoral management technique. Fires and burn scars from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for a range of years between 1987 and 2000 were mapped for areas around Parque Nacional Rio Abiseo (Peru) and Parque Nacional Carrasco (Bolivia). Burn scars mapped in the grasslands of these two areas indicate far more burning had taken place than either the fires or the burn scars derived from global datasets. Mean scar sizes are smaller and have a smaller range in size between years the in the study area in Peru (6.6-7.1 ha) than Bolivia (16.9-162.5 ha). Trends in biomass burning in the two highland areas can be explained in terms of the changing socio-economic environments and impacts of conservation. The mismatch between the spatial scale of biomass burning in the high-altitude grasslands and the sensors used to derive global fire products means that an entire component of the fire regime in the region studied is omitted, despite its importance in the farming systems on the Andes.

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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

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Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

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Selecting a stimulus as the target for a goal-directed movement involves inhibiting other competing possible responses. Inhibition has generally proved hard to study behaviorally, because it results in no measurable output. The effect of distractors on the shape of oculomotor and manual trajectories provide evidence of such inhibition. Individual saccades may deviate initially either towards, or away from, a competing distractor - the direction and extent of this deviation depends upon saccade latency, target predictability and the target to distractor separation. The experiment reported here used these effects to show how inhibition of distractor locations develops over time. Distractors could be presented at various distances from unpredictable and predictable targets in two separate experiments. The deviation of saccade trajectories was compared between trials with and without distractors. Inhibition was measured by saccade trajectory deviation. Inhibition was found to increase as the distractor distance from target decreased but was found to increase with saccade latency at all distractor distances (albeit to different peaks). Surprisingly, no differences were found between unpredictable and predictable targets perhaps because our saccade latencies were generally long (similar to 260-280 ms.). We conclude that oculomotor inhibition of saccades to possible target objects involves the same mechanisms for all distractor distances and target types. (C) 2009 Elsevier Ltd. All rights reserved.

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Leaf expansion in the fast-growing tree,Populus × euramericana was stimulated by elevated [CO2] in a closed-canopy forest plantation, exposed using a free air CO2 enrichment technique enabling long-term experimentation in field conditions. The effects of elevated [CO2] over time were characterized and related to the leaf plastochron index (LPI), and showed that leaf expansion was stimulated at very early (LPI, 0–3) and late (LPI, 6–8) stages in development. Early and late effects of elevated [CO2] were largely the result of increased cell expansion and increased cell production, respectively. Spatial effects of elevated [CO2] were also marked and increased final leaf size resulted from an effect on leaf area, but not leaf length, demonstrating changed leaf shape in response to [CO2]. Leaves exhibited a basipetal gradient of leaf development, investigated by defining seven interveinal areas, with growth ceasing first at the leaf tip. Interestingly, and in contrast to other reports, no spatial differences in epidermal cell size were apparent across the lamina, whereas a clear basipetal gradient in cell production rate was found. These data suggest that the rate and timing of cell production was more important in determining leaf shape, given the constant cell size across the leaf lamina. The effect of elevated [CO2] imposed on this developmental gradient suggested that leaf cell production continued longer in elevated [CO2] and that basal increases in cell production rate were also more important than altered cell expansion for increased final leaf size and altered leaf shape in elevated [CO2].

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It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques.

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The seasonal sea level variations observed from tide gauges over 1900-2013 and gridded satellite altimeter product AVISO over 1993-2013 in the northwest Pacific have been explored. The seasonal cycle is able to explain 60-90% of monthly sea level variance in the marginal seas, while it explains less than 20% of variance in the eddy-rich regions. The maximum annual and semi-annual sea level cycles (30cm and 6cm) are observed in the north of the East China Sea and the west of the South China Sea respectively. AVISO was found to underestimate the annual amplitude by 25% compared to tide gauge estimates along the coasts of China and Russia. The forcing for the seasonal sea level cycle was identified. The atmospheric pressure and the steric height produce 8-12cm of the annual cycle in the middle continental shelf and in the Kuroshio Current regions separately. The removal of the two attributors from total sea level permits to identify the sea level residuals that still show significant seasonality in the marginal seas. Both nearby wind stress and surface currents can explain well the long-term variability of the seasonal sea level cycle in the marginal seas and the tropics because of their influence on the sea level residuals. Interestingly, the surface currents are a better descriptor in the areas where the ocean currents are known to be strong. Here, they explain 50-90% of inter-annual variability due to the strong links between the steric height and the large-scale ocean currents.

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Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

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Spatial and temporal fluctuations in the concentration field from an ensemble of continuous point-source releases in a regular building array are analyzed from data generated by direct numerical simulations. The release is of a passive scalar under conditions of neutral stability. Results are related to the underlying flow structure by contrasting data for an imposed wind direction of 0 deg and 45 deg relative to the buildings. Furthermore, the effects of distance from the source and vicinity to the plume centreline on the spatial and temporal variability are documented. The general picture that emerges is that this particular geometry splits the flow domain into segments (e.g. “streets” and “intersections”) in each of which the air is, to a first approximation, well mixed. Notable exceptions to this general rule include regions close to the source, near the plume edge, and in unobstructed channels when the flow is aligned. In the oblique (45 deg) case the strongly three-dimensional nature of the flow enhances mixing of a scalar within the canopy leading to reduced temporal and spatial concentration fluctuations within the plume core. These fluctuations are in general larger for the parallel flow (0 deg) case, especially so in the long unobstructed channels. Due to the more complex flow structure in the canyon-type streets behind buildings, fluctuations are lower than in the open channels, though still substantially larger than for oblique flow. These results are relevant to the formulation of simple models for dispersion in urban areas and to the quantification of the uncertainties in their predictions.

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It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.