979 resultados para superfici suddivisione catmull-clark interpolazione


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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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The retention of peatland carbon (C) and the ability to continue to draw down and store C from the atmosphere is not only important for the UK terrestrial carbon inventory, but also for a range of ecosystem services, the landscape value and the ecology and hydrology of ~15% of the land area of the UK. Here we review the current state of knowledge on the C balance of UK peatlands using several studies which highlight not only the importance of making good flux measurements, but also the spatial and temporal variability of different flux terms that characterise a landscape affected by a range of natural and anthropogenic processes and threats. Our data emphasise the importance of measuring (or accurately estimating) all components of the peatland C budget. We highlight the role of the aquatic pathway and suggest that fluxes are higher than previously thought. We also compare the contemporary C balance of several UK peatlands with historical rates of C accumulation measured using peat cores, thus providing a long-term context for present-day measurements and their natural year-on-year variability. Contemporary measurements from 2 sites suggest that current accumulation rates (–56 to –72 g C m–2 yr–1) are at the lower end of those seen over the last 150 yr in peat cores (–35 to –209 g C m–2 yr–1). Finally, we highlight significant current gaps in knowledge and identify where levels of uncertainty are high, as well as emphasise the research challenges that need to be addressed if we are to improve the measurement and prediction of change in the peatland C balance over future decades.

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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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We present simulations of London's meteorology using the Met Office Unified Model with a new, sophisticated surface energy-balance scheme to represent the urban surfaces, called MORUSES. Simulations are performed with the urban surfaces represented and with the urban surfaces replaced with grass in order to calculate the urban increment on the local meteorology. The local urban effects were moderated to some extent by the passage of an onshore flow that propagated up the Thames estuary and across the city, cooling London slightly in the afternoon. Validations of screen-level temperature show encouraging agreement to within 1–2 K, when the urban increment is up to 5 K. The model results are then used to examine factors shaping the spatial and temporal structure of London's atmospheric boundary layer. The simulations reconcile the differences in the temporal evolution of the urban heat island (UHI) shown in various studies and demonstrate that the variation of UHI with time depends strongly on the urban fetch. The UHI at a location downwind of the city centre shows a decrease in UHI during the night, while the UHI at the city centre stays constant. Finally, the UHI at a location upwind of the city centre increases continuously. The magnitude of the UHI by the time of the evening transition increases with urban fetch. The urban increments are largest at night, when the boundary layer is shallow. The boundary layer experiences continued warming after sunset, as the heat from the urban fabric is released, and a weakly convective boundary layer develops across the city. The urban land-use fraction is the dominant control on the spatial structure in the sensible heat flux and the resulting urban increment, although even the weak advection present in this case study is sufficient to advect the peak temperature increments downwind of the most built-up areas. Copyright © 2011 Royal Meteorological Society and British Crown Copyright, the Met Office