140 resultados para V1 intracortical projections


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A form of three-dimensional X-ray imaging, called Object 3-D, is introduced, where the relevant subject material is represented as discrete ‘objects’. The surface of each such object is derived accurately from the projections of its outline, and of its other discontinuities, in about ten conventional X-ray views, distributed in solid angle. This technique is suitable for many applications, and permits dramatic savings in radiation exposure and in data acquisition and manipulation. It is well matched to user-friendly interactive displays.

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We compared output from 3 dynamic process-based models (DMs: ECOSSE, MILLENNIA and the Durham Carbon Model) and 9 bioclimatic envelope models (BCEMs; including BBOG ensemble and PEATSTASH) ranging from simple threshold to semi-process-based models. Model simulations were run at 4 British peatland sites using historical climate data and climate projections under a medium (A1B) emissions scenario from the 11-RCM (regional climate model) ensemble underpinning UKCP09. The models showed that blanket peatlands are vulnerable to projected climate change; however, predictions varied between models as well as between sites. All BCEMs predicted a shift from presence to absence of a climate associated with blanket peat, where the sites with the lowest total annual precipitation were closest to the presence/absence threshold. DMs showed a more variable response. ECOSSE predicted a decline in net C sink and shift to net C source by the end of this century. The Durham Carbon Model predicted a smaller decline in the net C sink strength, but no shift to net C source. MILLENNIA predicted a slight overall increase in the net C sink. In contrast to the BCEM projections, the DMs predicted that the sites with coolest temperatures and greatest total annual precipitation showed the largest change in carbon sinks. In this model inter-comparison, the greatest variation in model output in response to climate change projections was not between the BCEMs and DMs but between the DMs themselves, because of different approaches to modelling soil organic matter pools and decomposition amongst other processes. The difference in the sign of the response has major implications for future climate feedbacks, climate policy and peatland management. Enhanced data collection, in particular monitoring peatland response to current change, would significantly improve model development and projections of future change.

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A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

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We assessed the vulnerability of blanket peat to climate change in Great Britain using an ensemble of 8 bioclimatic envelope models. We used 4 published models that ranged from simple threshold models, based on total annual precipitation, to Generalised Linear Models (GLMs, based on mean annual temperature). In addition, 4 new models were developed which included measures of water deficit as threshold, classification tree, GLM and generalised additive models (GAM). Models that included measures of both hydrological conditions and maximum temperature provided a better fit to the mapped peat area than models based on hydrological variables alone. Under UKCIP02 projections for high (A1F1) and low (B1) greenhouse gas emission scenarios, 7 out of the 8 models showed a decline in the bioclimatic space associated with blanket peat. Eastern regions (Northumbria, North York Moors, Orkney) were shown to be more vulnerable than higher-altitude, western areas (Highlands, Western Isles and Argyle, Bute and The Trossachs). These results suggest a long-term decline in the distribution of actively growing blanket peat, especially under the high emissions scenario, although it is emphasised that existing peatlands may well persist for decades under a changing climate. Observational data from long-term monitoring and manipulation experiments in combination with process-based models are required to explore the nature and magnitude of climate change impacts on these vulnerable areas more fully.

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Climate controls upland habitats, soils and their associated ecosystem services; therefore, understanding possible changes in upland climatic conditions can provide a rapid assessment of climatic vulnerability over the next century. We used 3 different climatic indices that were optimised to fit the upland area classified by the EU as a Severely Disadvantaged Area (SDA) 1961–1990. Upland areas within the SDA covered all altitudinal ranges, whereas the maximum altitude of lowland areas outside of the SDA was ca. 300 m. In general, the climatic index based on the ratio between annual accumulated temperature (as a measure of growing season length) and annual precipitation predicted 96% of the SDA mapped area, which was slightly better than those indices based on annual or seasonal water deficit. Overall, all climatic indices showed that upland environments were exposed to some degree of change by 2071–2100 under UKCIP02 climate projections for high and low emissions scenarios. The projected area declined by 13 to 51% across 3 indices for the low emissions scenario and by 24 to 84% for the high emissions scenario. Mean altitude of the upland area increased by +11 to +86 m for the low scenario and +21 to +178 m for the high scenario. Low altitude areas in eastern and southern Great Britain were most vulnerable to change. These projected climatic changes are likely to affect upland habitat composition, long-term soil carbon storage and wider ecosystem service provision, although it is not yet possible to determine the rate at which this might occur.

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Blanket peatlands are rain-fed mires that cover the landscape almost regardless of topography. The geographical extent of this type of peatland is highly sensitive to climate. We applied a global process-based bioclimatic envelope model, PeatStash, to predict the distribution of British blanket peatlands. The model captures the present areal extent (Kappa = 0.77) and is highly sensitive to both temperature and precipitation changes. When the model is run using the UKCIP02 climate projections for the time periods 2011–2040, 2041–2070 and 2071–2100, the geographical distribution of blanket peatlands gradually retreats towards the north and the west. In the UKCIP02 high emissions scenario for 2071–2100, the blanket peatland bioclimatic space is ~84% smaller than contemporary conditions (1961–1990); only parts of the west of Scotland remain inside this space. Increasing summer temperature is the main driver of the projected changes in areal extent. Simulations using 7 climate model outputs resulted in generally similar patterns of declining aereal extent of the bioclimatic space, although differing in degree. The results presented in this study should be viewed as a first step towards understanding the trends likely to affect the blanket peatland distribution in Great Britain. The eventual fate of existing blanket peatlands left outside their bioclimatic space remains uncertain.

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Sea-level rise is an important aspect of climate change because of its impact on society and ecosystems. Here we present an intercomparison of results from ten coupled atmosphere-ocean general circulation models (AOGCMs) for sea-level changes simulated for the twentieth century and projected to occur during the twenty first century in experiments following scenario IS92a for greenhouse gases and sulphate aerosols. The model results suggest that the rate of sea-level rise due to thermal expansion of sea water has increased during the twentieth century, but the small set of tide gauges with long records might not be adequate to detect this acceleration. The rate of sea-level rise due to thermal expansion continues to increase throughout the twenty first century, and the projected total is consequently larger than in the twentieth century; for 1990-2090 it amounts to 0.20-0.37 in. This wide range results from systematic uncertainty in modelling of climate change and of heat uptake by the ocean. The AOGCMs agree that sea-level rise is expected to be geographically non-uniform, with some regions experiencing as much as twice the global average, and others practically zero, but they do not agree about the geographical pattern. The lack of agreement indicates that we cannot currently have confidence in projections of local sea- level changes, and reveals a need for detailed analysis and intercomparison in order to understand and reduce the disagreements.

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This review assesses the impacts, both direct and indirect, of man-made changes to the composition of the air over a 200 year period on the severity of arable crop disease epidemics. The review focuses on two well-studied UK arable crops,wheat and oilseed rape, relating these examples to worldwide food security. In wheat, impacts of changes in concentrations of SO2 in air on two septoria diseases are discussed using data obtained from historical crop samples and unpublished experimental work. Changes in SO2 seem to alter septoria disease spectra both through direct effects on infection processes and through indirect effects on soil S status. Work on the oilseed rape diseases phoma stem canker and light leaf spot illustrates indirect impacts of increasing concentrations of greenhouse gases, mediated through climate change. It is projected that, by the 2050s, if diseases are not controlled, climate change will increase yields in Scotland but halve yields in southern England. These projections are discussed in relation to strategies for adaptation to environmental change. Since many strategies take10–15 years to implement, it is important to take appropriate decisions soon. Furthermore, it is essential to make appropriate investment in collation of long-term data, modelling and experimental work to guide such decision-making by industry and government, as a contribution to worldwide food security.

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We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

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The Arctic has undergone substantial changes over the last few decades in various cryospheric and derivative systems and processes. Of these, the Arctic sea ice regime has seen some of the most rapid change and is one of the most visible markers of Arctic change outside the scientific community. This has drawn considerable attention not only from the natural sciences, but increasingly, from the political and commercial sectors as they begin to grapple with the problems and opportunities that are being presented. The possible impacts of past and projected changes in Arctic sea ice, especially as it relates to climatic response, are of particular interest and have been the subject of increasing research activity. A review of the current knowledge of the role of sea ice in the climate system is therefore timely. We present a review that examines both the current state of understanding, as regards the impacts of sea-ice loss observed to date, and climate model projections, to highlight hypothesised future changes and impacts on storm tracks and the North Atlantic Oscillation. Within the broad climate-system perspective, the topics of storminess and large-scale variability will be specifically considered. We then consider larger-scale impacts on the climatic system by reviewing studies that have focused on the interaction between sea-ice extent and the North Atlantic Oscillation. Finally, an overview of the representation of these topics in the literature in the context of IPCC climate projections is presented. While most agree on the direction of Arctic sea-ice change, the rates amongst the various projections vary greatly. Similarly, the response of storm tracks and climate variability are uncertain, exacerbated possibly by the influence of other factors. A variety of scientific papers on the relationship between sea-ice changes and atmospheric variability have brought to light important aspects of this complex topic. Examples are an overall reduction in the number of Arctic winter storms, a northward shift of mid-latitude winter storms in the Pacific and a delayed negative NAO-like response in autumn/winter to a reduced Arctic sea-ice cover (at least in some months). This review paper discusses this research and the disagreements, bringing about a fresh perspective on this issue.

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Assessment of changes in precipitation (P) as a function of percentiles of surface temperature (T) and 500 hPa vertical velocity (ω) are presented, considering present-day simulations and observational estimates from the Global Precipitation Climatology Project (GPCP) combined with the European Centre for Medium-range Weather Forecasts Interim reanalysis (ERA Interim). There is a tendency for models to overestimate P in the warm, subsiding regimes compared to GPCP, in some cases by more than 100%, while many models underestimate P in the moderate temperature regimes. Considering climate change projections between 1980–1999 and 2080–2099, responses in P are characterised by dP/dT ≥ 4%/K over the coldest 10–20% of land points and over warm, ascending ocean points while P declines over the warmest, descending regimes (dP/dT ∼ − 4%/K for model ensemble means). The reduced Walker circulation limits this contrasting dP/dT response in the tropical wet and dry regimes only marginally. Around 70% of the global surface area exhibits a consistent sign for dP/dT in at least 6 out of a 7-member model ensemble when considering P composites in terms of dynamic regime.

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Public water supplies in England and Wales are provided by around 25 private-sector companies, regulated by an economic regulator (Ofwat) and and environmental regulator (Environment Agency). As part of the regulatory process, companies are required periodically to review their investment needs to maintain safe and secure supplies, and this involves an assessment of the future balance between water supply and demand. The water industry and regulators have developed an agreed set of procedures for this assessment. Climate change has been incorporated into these procedures since the late 1990s, although has been included increasingly seriously over time and it has been an effective legal requirement to consider climate change since the 2003 Water Act. In the most recent assessment in 2009, companies were required explicitly to plan for a defined amount of climate change, taking into account climate change uncertainty. A “medium” climate change scenario was defined, together with “wet” and “dry” extremes, based on scenarios developed from a number of climate models. The water industry and its regulators are now gearing up to exploit the new UKCP09 probabilistic climate change projections – but these pose significant practical and conceptual challenges. This paper outlines how the procedures for incorporating climate change information into water resources planning have evolved, and explores the issues currently facing the industry in adapting to climate change.

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In this paper we undertake a preliminary assessment of the regional planning and development implications of BAA Stansted Airport’s planning permission to grow to 25 million passengers per annum (mppa) by 2010. Our concern is not simply to consider the overall growth of the airport on the airport site itself but the nature and type of growth both on- and off-site. In this document we focus on the submitted planning permission documents and test them. The methodology we employed was to draw on published and unpublished numerical estimates of the airport’s growth – particularly including estimates produced by the airport owner, BAA, and their economic and planning consultants DTZ Pieda - and critically, and systematically analyse their figures. We adopted this approach because unless the figures which were employed in the initial calculations were correct then all of the subsequent projections which flow from them - and the polices which could then be based on them – could be flawed. The analysis is divided into two parts – firstly, are the growth forecasts correct?; and secondly, what do these forecasts actually mean in developmental terms? In effect, what we have done is to produce a critique of the existing body of evidence by questioning underpinning assumptions and then draw some preliminary conclusions for the region based on this analysis. A major focus of this report has been analyse the figures involved in the planning application to expand Stansted to 25mppa. Ironically, one of our key findings, that the local impact of Stansted’s proposed expansion in employment terms might well be less than was originally thought, might make it easier to gain the acceptance of the relevant local authorities involved to allow the development to take place. Our main overall findings are that the BAA projections over-estimate the local employment impact of the airport’s proposed growth and under-estimate its potential regional ‘transportation’ employment effect. These two findings are, of course, related to each other in important ways, and we also feel that they have potentially significant medium and long-term economic, competitiveness and planning policy implications for the East of England region

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This paper analyses developments in the growth and configuration of the institutional savings markets within the European Union. The paper discusses the changing socio-economic context in which investment services within the EU are being delivered. The is followed by an examination of drivers of market integration such as the growth and consolidation of the fund management industry, the demographic and fiscal pressures for reform of pensions markets and the process and effects of the deregulation of investment services markets. There is a review of outstanding sources of market segmentation. The projections for future growth in pensions are outlined and implications for real estate investment assessed. It is concluded that, although numerous imponderables render reliable quantitative projections problematic, growth and restructuring of the institutional savings market is likely to increase cross-border capital flows to real estate markets.