349 resultados para Climate change reparation scheme


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Livestock farming is one of the most important sectors in agriculture both economically and socially. In the developing world, livestock is crucial to generating livelihoods and food security for some one billion of the world's poorest people. The demand for livestock products is growing as diets change and the world population increases, mainly in the developing world. Climate change only adds to the challenge facing the world's most disadvantaged people. It impacts on livestock production systems and in turn livestock farming impacts on climate change. This paper reviews the complex interaction between livestock production and climate change and proposes strategies that could be used to help sustain livestock as a key feature of rural livelihoods in the developing world.

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Atmosphere–ocean general circulation models (AOGCMs) predict a weakening of the Atlantic meridional overturning circulation (AMOC) in response to anthropogenic forcing of climate, but there is a large model uncertainty in the magnitude of the predicted change. The weakening of the AMOC is generally understood to be the result of increased buoyancy input to the north Atlantic in a warmer climate, leading to reduced convection and deep water formation. Consistent with this idea, model analyses have shown empirical relationships between the AMOC and the meridional density gradient, but this link is not direct because the large-scale ocean circulation is essentially geostrophic, making currents and pressure gradients orthogonal. Analysis of the budget of kinetic energy (KE) instead of momentum has the advantage of excluding the dominant geostrophic balance. Diagnosis of the KE balance of the HadCM3 AOGCM and its low-resolution version FAMOUS shows that KE is supplied to the ocean by the wind and dissipated by viscous forces in the global mean of the steady-state control climate, and the circulation does work against the pressure-gradient force, mainly in the Southern Ocean. In the Atlantic Ocean, however, the pressure-gradient force does work on the circulation, especially in the high-latitude regions of deep water formation. During CO2-forced climate change, we demonstrate a very good temporal correlation between the AMOC strength and the rate of KE generation by the pressure-gradient force in 50–70°N of the Atlantic Ocean in each of nine contemporary AOGCMs, supporting a buoyancy-driven interpretation of AMOC changes. To account for this, we describe a conceptual model, which offers an explanation of why AOGCMs with stronger overturning in the control climate tend to have a larger weakening under CO2 increase.

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A key reason for pessimism with respect to greenhouse gas emissions reduction relates to the ‘motivation problem’, whereby those who could make the biggest difference prima facie have the least incentive to act because they are most able to adapt: how can we motivate such people (and thereby everyone else) to accept, indeed to initiate, the changes to their lifestyles that are required for effective emissions reductions? This paper offers an account inspired by Rawls of the good of membership of ‘intergenerational cooperative union’ to achieve justice that provides a solution to the motivation problem.

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We summarise the work of an interdisciplinary network set up to explore the impacts of climate change in the British Uplands. In this CR Special, the contributors present the state of knowledge and this introduction synthesises this knowledge and derives implications for decision makers. The Uplands are valued semi-natural habitats, providing ecosystem services that have historically been taken for granted. For example, peat soils, which are mostly found in the Uplands, contain around 50% of the terrestrial carbon in the UK. Land management continues to be a driver of ecosystem service delivery. Degraded and managed peatlands are subject to erosion and carbon loss with negative impacts on biodiversity, carbon storage and water quality. Climate change is already being experienced in British Uplands and is likely to exacerbate these pressures. Climate envelope models suggest as much as 50% of British Uplands and peatlands will be exposed to climate stress by the end of the 21st century under low and high emissions scenarios. However, process-based models of the response of organic soils to this climate stress do not give a consistent indication of what this will mean for soil carbon: results range from a very slight increase in uptake, through a clear decline, to a net carbon loss. Preserving existing peat stocks is an important climate mitigation strategy, even if new peat stops forming. Preserving upland vegetation cover is a key win–win management strategy that will reduce erosion and loss of soil carbon, and protect a variety of services such as the continued delivery of a high quality water resource.

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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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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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Enhanced release of CO2 to the atmosphere from soil organic carbon as a result of increased temperatures may lead to a positive feedback between climate change and the carbon cycle, resulting in much higher CO2 levels and accelerated lobal warming. However, the magnitude of this effect is uncertain and critically dependent on how the decomposition of soil organic C (heterotrophic respiration) responds to changes in climate. Previous studies with the Hadley Centre’s coupled climate–carbon cycle general circulation model (GCM) (HadCM3LC) used a simple, single-pool soil carbon model to simulate the response. Here we present results from numerical simulations that use the more sophisticated ‘RothC’ multipool soil carbon model, driven with the same climate data. The results show strong similarities in the behaviour of the two models, although RothC tends to simulate slightly smaller changes in global soil carbon stocks for the same forcing. RothC simulates global soil carbon stocks decreasing by 54 GtC by 2100 in a climate change simulation compared with an 80 GtC decrease in HadCM3LC. The multipool carbon dynamics of RothC cause it to exhibit a slower magnitude of transient response to both increased organic carbon inputs and changes in climate. We conclude that the projection of a positive feedback between climate and carbon cycle is robust, but the magnitude of the feedback is dependent on the structure of the soil carbon model.

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Geographic distributions of pathogens are the outcome of dynamic processes involving host availability, susceptibility and abundance, suitability of climate conditions, and historical contingency including evolutionary change. Distributions have changed fast and are changing fast in response to many factors, including climatic change. The response time of arable agriculture is intrinsically fast, but perennial crops and especially forests are unlikely to adapt easily. Predictions of many of the variables needed to predict changes in pathogen range are still rather uncertain, and their effects will be profoundly modified by changes elsewhere in the agricultural system, including both economic changes affecting growing systems and hosts and evolutionary changes in pathogens and hosts. Tools to predict changes based on environmental correlations depend on good primary data, which is often absent, and need to be checked against the historical record, which remains very poor for almost all pathogens. We argue that at present the uncertainty in predictions of change is so great that the important adaptive response is to monitor changes and to retain the capacity to innovate, both by access to economic capital with reasonably long-term rates of return and by retaining wide scientific expertise, including currently less fashionable specialisms.

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In response to increasing atmospheric con- centrations of greenhouse gases, the rate of time- dependent climate change is determined jointly by the strength of climate feedbacks and the e�ciency of pro- cesses which remove heat from the surface into the deep ocean. This work examines the vertical heat transport processes in the ocean of the HADCM2 atmosphere± ocean general circulation model (AOGCM) in experi- ments with CO2 held constant (control) and increasing at 1% per year (anomaly). The control experiment shows that global average heat exchanges between the upper and lower ocean are dominated by the Southern Ocean, where heat is pumped downwards by the wind- driven circulation and di�uses upwards along sloping isopycnals. This is the reverse of the low-latitude balance used in upwelling±di�usion ocean models, the global average upward di�usive transport being against the temperature gradient. In the anomaly experiment, weakened convection at high latitudes leads to reduced diffusive and convective heat loss from the deep ocean, and hence to net heat uptake, since the advective heat input is less a�ected. Reduction of deep water produc- tion at high latitudes results in reduced upwelling of cold water at low latitudes, giving a further contribution to net heat uptake. On the global average, high-latitude processes thus have a controlling in¯uence. The impor- tant role of di�usion highlights the need to ensure that the schemes employed in AOGCMs give an accurate representation of the relevant sub-grid-scale processes.