168 resultados para Change Impact


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A regional climate model is used to investigate changes in Israel and Jordan precipitation at the end of the 21st century on daily to monthly timescales. The model predicts that this region will get significantly drier at the peak of the rainy season, reflecting a reduction in both the frequency and duration of rainy events. These changes may be associated with a reduction in the strength of the Mediterranean storm track

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The EU has adopted the European Farmland Bird Index (EFBI) as a Structural and Sustainable Development Indicator and a proxy for wider biodiversity health on farmland. Changes in the EFBI over coming years are likely to reflect how well agri-environment schemes (AES), funded under Pillar 2 (Axis 2) of the Common Agricultural Policy, have been able to offset the detrimental impacts of past agricultural changes and deliver appropriate hazard prevention or risk mitigation strategies alongside current and future agricultural change. The delivery of a stable or positive trend in the EFBI will depend on the provision of sufficient funding to appropriately designed and implemented AES. We present a trait-based framework which can be used to quantify the detrimental impact of land-use change on farmland bird populations across Europe. We use the framework to show that changes in resource availability within the cropped area of agricultural landscapes have been the key driver of current declines in farmland bird populations. We assess the relative contribution of each Member State to the level of the EFBI and explore the relationship between risk contribution and Axis 2 funding allocation. Our results suggest that agricultural changes in each Member State do not have an equal impact on the EFBI, with land-use and management change in Spain having a particularly large influence on its level, and that funding is poorly targeted with respect to biodiversity conservation needs. We also use the framework to predict the EFBI in 2020 for a number of land-use change scenarios. This approach can be used to guide both the development and implementation of targeted AES and the objective distribution of Pillar 2 funds between and within Member States. We hope that this will contribute to the cost-effective and efficient delivery of Rural Development strategy and biodiversity conservation targets.

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An improved stratospheric representation has been included in simulations with the Hadley Centre HadGEM1 coupled ocean atmosphere model with natural and anthropogenic forcings for the period 1979–2003. An improved stratospheric ozone dataset is employed that includes natural variations in ozone as well as the usual anthropogenic trends. In addition, in a second set of simulations the quasi biennial oscillation (QBO) of stratospheric equatorial zonal wind is also imposed using a relaxation towards ERA-40 zonal wind values. The resulting impact on tropospheric variability and trends is described. We show that the modelled cooling rate at the tropopause is enhanced by the improved ozone dataset and this improvement is even more marked when the QBO is also included. The same applies to warming trends in the upper tropical troposphere which are slightly reduced. Our stratospheric improvements produce a significant increase of internal variability but no change in the positive trend of annual mean global mean near-surface temperature. Warming rates are increased significantly over a large portion of the Arctic Ocean. The improved stratospheric representation, especially the QBO relaxation, causes a substantial reduction in near-surface temperature and precipitation response to the El Chichón eruption, especially in the tropical region. The winter increase in the phase of the northern annular mode observed in the aftermath of the two major recent volcanic eruptions is partly captured, especially after the El Chichón eruption. The positive trend in the southern annular mode (SAM) is increased and becomes statistically significant which demonstrates that the observed increase in the SAM is largely subject to internal variability in the stratosphere. The possible inclusion in simulations for future assessments of full ozone chemistry and a gravity wave scheme to internally generate a QBO is discussed.

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Export coefficient modelling was used to model the impact of agriculture on nitrogen and phosphorus loading on the surface waters of two contrasting agricultural catchments. The model was originally developed for the Windrush catchment where the highly reactive Jurassic limestone aquifer underlying the catchment is well connected to the surface drainage network, allowing the system to be modelled using uniform export coefficients for each nutrient source in the catchment, regardless of proximity to the surface drainage network. In the Slapton catchment, the hydrological path-ways are dominated by surface and lateral shallow subsurface flow, requiring modification of the export coefficient model to incorporate a distance-decay component in the export coefficients. The modified model was calibrated against observed total nitrogen and total phosphorus loads delivered to Slapton Ley from inflowing streams in its catchment. Sensitivity analysis was conducted to isolate the key controls on nutrient export in the modified model. The model was validated against long-term records of water quality, and was found to be accurate in its predictions and sensitive to both temporal and spatial changes in agricultural practice in the catchment. The model was then used to forecast the potential reduction in nutrient loading on Slapton Ley associated with a range of catchment management strategies. The best practicable environmental option (BPEO) was found to be spatial redistribution of high nutrient export risk sources to areas of the catchment with the greatest intrinsic nutrient retention capacity.

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A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley

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High spatial resolution environmental data gives us a better understanding of the environmental factors affecting plant distributions at fine spatial scales. However, large environmental datasets dramatically increase compute times and output species model size stimulating the need for an alternative computing solution. Cluster computing offers such a solution, by allowing both multiple plant species Environmental Niche Models (ENMs) and individual tiles of high spatial resolution models to be computed concurrently on the same compute cluster. We apply our methodology to a case study of 4,209 species of Mediterranean flora (around 17% of species believed present in the biome). We demonstrate a 16 times speed-up of ENM computation time when 16 CPUs were used on the compute cluster. Our custom Java ‘Merge’ and ‘Downsize’ programs reduce ENM output files sizes by 94%. The median 0.98 test AUC score of species ENMs is aided by various species occurrence data filtering techniques. Finally, by calculating the percentage change of individual grid cell values, we map the projected percentages of plant species vulnerable to climate change in the Mediterranean region between 1950–2000 and 2020.