209 resultados para Spatial typology


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Climate models taking part in the coupled model intercomparison project phase 5 (CMIP5) all predict a global mean sea level rise for the 21st century. Yet the sea level change is not spatially uniform and differs among models. Here we evaluate the role of air–sea fluxes of heat, water and momentum (windstress) to find the spatial pattern associated to each of them as well as the spread they can account for. Using one AOGCM to which we apply the surface flux changes from other AOGCMs, we show that the heat flux and windstress changes dominate both the pattern and the spread, but taking the freshwater flux into account as well yields a sea level change pattern in better agreement with the CMIP5 ensemble mean. Differences among the CMIP5 control ocean temperature fields have a smaller impact on the sea level change pattern.

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The increase in incidence and prevalence of neurodegenerative diseases highlights the need for a more comprehensive understanding of how food components may affect neural systems. In particular, flavonoids have been recognized as promising agents capable of influencing different aspects of synaptic plasticity resulting in improvements in memory and learning in both animals and humans. Our previous studies highlight the efficacy of flavonoids in reversing memory impairments in aged rats, yet little is known about the effects of these compounds in healthy animals, particularly with respect to the molecular mechanisms by which flavonoids might alter the underlying synaptic modifications responsible for behavioral changes. We demonstrate that a 3-week intervention with two dietary doses of flavonoids (Dose I: 8.7 mg/day and Dose II: 17.4 mg/day) facilitates spatial memory acquisition and consolidation (24 recall) (p < 0.05) in young healthy rats. We show for the first time that these behavioral improvements are linked to increased levels in the polysialylated form of the neural adhesion molecule (PSA-NCAM) in the dentate gyrus (DG) of the hippocampus, which is known to be required for the establishment of durable memories. We observed parallel increases in hippocampal NMDA receptors containing the NR2B subunit for both 8.7 mg/day (p < 0.05) and 17.4 mg/day (p < 0.001) doses, suggesting an enhancement of glutamate signaling following flavonoid intervention. This is further strengthened by the simultaneous modulation of hippocampal ERK/CREB/BDNF signaling and the activation of the Akt/mTOR/Arc pathway, which are crucial in inducing changes in the strength of hippocampal synaptic connections that underlie learning. Collectively, the present data supports a new role for PSA-NCAM and NMDA-NR2B receptor on flavonoid-induced improvements in learning and memory, contributing further to the growing body of evidence suggesting beneficial effects of flavonoids in cognition and brain health.

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As the fidelity of virtual environments (VE) continues to increase, the possibility of using them as training platforms is becoming increasingly realistic for a variety of application domains, including military and emergency personnel training. In the past, there was much debate on whether the acquisition and subsequent transfer of spatial knowledge from VEs to the real world is possible, or whether the differences in medium during training would essentially be an obstacle to truly learning geometric space. In this paper, the authors present various cognitive and environmental factors that not only contribute to this process, but also interact with each other to a certain degree, leading to a variable exposure time requirement in order for the process of spatial knowledge acquisition (SKA) to occur. The cognitive factors that the authors discuss include a variety of individual user differences such as: knowledge and experience; cognitive gender differences; aptitude and spatial orientation skill; and finally, cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. It may seem obvious that since every individual's brain is unique - not only through experience, but also through genetic predisposition that a one size fits all approach to training would be illogical. Furthermore, considering that various cognitive differences may further emerge when a certain stimulus is present (e.g. complex environmental space), it would make even more sense to understand how these factors can impact spatial memory, and to try to adapt the training session by providing visual/auditory cues as well as by changing the exposure time requirements for each individual. The impact of this research domain is important to VE training in general, however within service and military domains, guaranteeing appropriate spatial training is critical in order to ensure that disorientation does not occur in a life or death scenario.

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The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.

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Ground-based observations of dayside auroral forms and magnetic perturbations in the arctic sectors of Svalbard and Greenland, in combination with the high-resolution measurements of ionospheric ion drift and temperature by the EISCAT radar, are used to study temporal/spatial structures of cusp-type auroral forms in relation to convection. Large-scale patterns of equivalent convection in the dayside polar ionosphere are derived from the magnetic observations in Greenland and Svalbard. This information is used to estimate the ionospheric convection pattern in the vicinity of the cusp/cleft aurora. The reported observations, covering the period 0700-1130 UT, on January 11, 1993, are separated into four intervals according to the observed characteristics of the aurora and ionospheric convection. The morphology and intensity of the aurora are very different in quiet and disturbed intervals. A latitudinally narrow zone of intense and dynamical 630.0 nm emission equatorward of 75 degrees MLAT, was observed during periods of enhanced antisunward convection in the cusp region. This (type 1 cusp aurora) is considered to be the signature of plasma entry via magnetopause reconnection at low magnetopause latitudes, i.e. the low-latitude boundary layer (LLB I,). Another zone of weak 630.0 nm emission (type 2 cusp aurora) was observed to extend up to high latitudes (similar to 79 degrees MLAT) during relatively quiet magnetic conditions, when indications of reverse (sunward) convection was observed in the dayside polar cap. This is postulated to be a signature of merging between a northward directed IMF (B-z > 0) and the geomagnetic field poleward of the cusp. The coexistence of type 1 and 2 auroras was observed under intermediate circumstances. The optical observations from Svalbard and Greenland were also used to determine the temporal and spatial evolution of type 1 auroral forms, i.e. poleward-moving auroral events occurring in the vicinity of a rotational convection reversal in the early post-noon sector. Each event appeared as a local brightening at the equatorward boundary of the pre-existing type 1 cusp aurora, followed by poleward and eastward expansions of luminosity. The auroral events were associated with poleward-moving surges of enhanced ionospheric convection and F-layer ion temperature as observed by the EISCAT radar in Tromso. The EISCAT ion flow data in combination with the auroral observations show strong evidence for plasma flow across the open/closed field line boundary.

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With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member–member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales, spinup times for the model, and upscale growth of errors and forecast differences. The ensemble spread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales.

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In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context.

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This paper analyses the impact of several avoided deforestation policies within a patchy forested landscape. Central is the idea that deforestation choices in one area influence deforestation decisions in nearby patches. We explore the interplay between forest landscapes comprising heterogeneous patches, localised spatial displacement, and avoided deforestation policies. Avoided deforestation policies at a landscape level are respectively: two Payments for Environmental Services (PES) policies, one focused on deforestation hotspots, the second being equally available to all agents; a conservation area; and, an agglomeration bonus. We demonstrate how the "best" policy, in terms of reduced leakage, depends on landscape heterogeneity. Agglomeration bonuses are shown to be more effective where there is less landscape heterogeneity, whilst conservation areas are most effective where there is more spatial heterogeneity.

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Spatial variability of liquid cloud water content and rainwater content is analysed from three different observational platforms: in situ measurements from research aircraft, land-based remote sensing techniques using radar and lidar, and spaceborne remote sensing from CloudSat. The variance is found to increase with spatial scale, but also depends strongly on the cloud or rain fraction regime, with overcast regions containing less variability than broken cloud fields. This variability is shown to lead to large biases, up to a factor of 4, in both the autoconversion and accretion rates estimated at a model grid scale of ≈40 km by a typical microphysical parametrization using in-cloud mean values. A parametrization for the subgrid variability of liquid cloud and rainwater content is developed, based on the observations, which varies with both the grid scale and cloud or rain fraction, and is applicable for all model grid scales. It is then shown that if this parametrization of the variability is analytically incorporated into the autoconversion and accretion rate calculations, the bias is significantly reduced.

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Findings from animal studies suggest that components of fruit and vegetables (F&V) may protect against, and even reverse, age-related decline(1,2) in aspects of cognitive functioning such as spatial working memory (SWM). Human subjects in vivo and in vitro studies indicate that anti-inflammatory, anti-oxidant and cell-signalling properties of flavonoids and carotenoids, non-nutrient components of F&V, may underpin this protective effect(3–5). The Flavonoid University of Reading Study (FLAVURS), designed to explore the dose-response relationship between dietary F&V flavonoids and CVD, enabled the investigation of such an association with SWM. FLAVURS is an 18-week parallel three-arm randomised controlled dietary intervention trial with four time points, measured at 6-weekly intervals from baseline. Low F&V consumers at risk of CVD aged 26–70 years were randomly assigned to high flavonoid (HF), low flavonoid (LF) or control group. F&V intake increased by two daily 80 g portions every 6 weeks, with either HF or LF F&V, in addition to each participant's habitual diet, while controls maintained their habitual diet. At each visit, participants completed a cognitive test battery with SWM as the primary outcome. The HF group showed significantly higher levels of urinary flavonoids than LF or controls at 12 weeks (P<0.001) as expected, but surprisingly only higher levels than LF at 18 weeks (P<0.01). The LF group showed higher levels of plasma carotenoids than the other groups at 18 weeks (P<0.001). No group differences were found for SWM overall, however, age-group sub-analyses (26–50 and 51–70 years of age) showed differences from 0 to 18 weeks for younger adults, with LF improving significantly more than the other two groups on SWM (P<0.05). As nutritional absorption is known to decrease with age, separate stepwise regressions were performed on the two age groups irrespective of dietary group, with urinary flavonoids and plasma carotenoids as predictors. For younger adults, improved SWM performance from 0 to 18 weeks was associated with higher carotenoid levels, β=0.28, t(55)=2.10, P<0.05, accounting for 7.5% of the variance, R2=0.075, F(1,54)=4.41, P=0.040. For older adults, no between-group SWM differences were found. Findings suggest that F&V-based flavonoids and carotenoids may provide benefits for cognitive function, and that carotenoids in particular may improve cognitive performance in SWM. Given that these benefits were restricted to younger adults, future work is needed to test the reliability of this finding, as well as determine the mechanisms by which age-dependent differences in F&V responsiveness occur.

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Arbuscular mycorrhizal fungi (AMF) are crucial to the functioning of the plant–soil system, but little is known about the spatial structuring of AMF communities across landscapes modified by agriculture. AMF community composition was characterized across four sites in the highly cleared south-western Australian wheatbelt that were originally dominated by forb-rich eucalypt woodlands. Environmentally induced spatial structuring in AMF composition was examined at four scales: the regional scale associated with location, the site scale associated with past management (benchmark woodlands with no agricultural management history, livestock grazing, recent revegetation), the patch scale associated with trees and canopy gaps, and the fine scale associated with the herbaceous plant species beneath which soils were sourced. Field-collected soils were cultured in trap pots; then, AMF composition was determined by identifying spores and through ITS1 sequencing. Structuring was strongest at site scales, where composition was strongly related to prior management and associated changes in soil phosphorus. The two fields were dominated by the genera Funneliformis and Paraglomus, with little convergence back to woodland composition after revegetation. The two benchmark woodlands were characterized by Ambispora gerdemannii and taxa from Gigasporaceae. Their AMF communities were strongly structured at patch scales associated with trees and gaps, in turn most strongly related to soil N. By contrast, there were few patterns at fine scales related to different herbaceous plant species, or at regional scales associated with the 175 km distance between benchmark woodlands. Important areas for future investigation are to identify the circumstances in which recolonization by woodland AMF may be limited by fungal propagule availability, reduced plant diversity and/or altered chemistry in agricultural soils.

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Housebuilding firms vary across the world in size and in the scope of their activities. This variety may seem surprising in an industry with open technologies and ease of entry. While market and technological factors may go some way to explain such differences, much of the causes of variation lie in dissimilarities in regulatory and institutional frameworks. These themes are explored through a comparative analysis of the structure of the residential development industry in Australia, the UK and the USA and in analysis of firm size hierarchies. The firm concentration ratio is much higher in the UK than the other two countries and the reasons may lie in the geography of the country but also in the peculiarities of its planning system.

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The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.