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ABSTRACT: There is an international divide between net emissions importers and net emissions exporters, with industrialised nations mainly falling into the former and emerging economies the latter. Integrating emissions transfers into climate policy, so as not to disadvantage export-intensive countries, has been suggested to increase participation in international emissions reduction commitments. Consumption-based scenarios are presented for the UK identifying the geographic and sectorial source of emissions to meet future consumer demands given the current international climate policy landscape. The analysis is applied to the UK yet the discussion is applicable to international climate policy; assigning national responsibility for global emissions reductions; and extending the mitigation potential for net importing countries. Two trajectories for UK consumption emissions are calculated in which (1) international reduction targets are consistent with those pledged today equating to four degrees of temperature rise and (2) international reduction targets achieve a two degree future. By 2050 it is estimated that UK consumption emissions are 40–260% greater than UK territorial emissions depending on the strength of global reduction measures, and assuming the UK meets its 80% reduction in 1990 emissions by 2050 target. Cumulative emissions are presented alongside emissions trajectories, recognising that temperature rise is directly related to every tonne of carbon emitted. Whilst this paper argues that the current UK emissions targets underestimate the UK's contribution to global mitigation for two degrees, it shows how expanding the focus of policy towards consumption introduces new opportunities for reduction strategies at scale. The paper advocates the implementation of consumption-based emissions accounting which reveals underexploited policy interventions and increases the potential to break down barriers that exist between industrialised and emerging economies in international climate policy.Environmental Science & Policy 10/2015; 52. DOI:10.1016/j.envsci.2015.05.016
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ABSTRACT: Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.ISPRS Journal of Photogrammetry and Remote Sensing 10/2015; 109:165. DOI:10.1016/j.isprsjprs.2015.09.007
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ABSTRACT: The human AmphyphisinII/Bin1 N-BAR domain belongs to the BAR domain superfamily, whose members sense and generate membrane curvatures. The N-BAR domain is a 57 kDa homodimeric protein comprising a six helix bundle. Here we report the protein folding mechanism of this protein as a representative of this protein superfamily. The concentration dependent thermodynamic stability was studied by urea equilibrium transition curves followed by fluorescence and far-UV CD spectroscopy. Kinetic unfolding and refolding experiments, including rapid double and triple mixing techniques, allowed to unravel the complex folding behavior of N-BAR. The equilibrium unfolding transition curve can be described by a two-state process, while the folding kinetics show four refolding phases, an additional burst reaction and two unfolding phases. All fast refolding phases show a rollover in the chevron plot but only one of these phases depends on the protein concentration reporting the dimerization step. Secondary structure formation occurs during the three fast refolding phases. The slowest phase can be assigned to a proline isomerization. All kinetic experiments were also followed by fluorescence anisotropy detection to verify the assignment of the dimerization step to the respective folding phase. Based on these experiments we propose for N-BAR two parallel folding pathways towards the homodimeric native state depending on the proline conformation in the unfolded state.PLoS ONE 09/2015; 10(9):e0136922. DOI:10.1371/journal.pone.0136922
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