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Setting reference levels for REDD+

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Tropical deforestation is estimated to contribute 6-17% of all anthropogenic greenhouse gas emissions. One possibility for reducing tropical deforestation is to provide payments to developing countries for reducing emissions from deforestation and forest degradation, a global initiative known as “REDD+”.The effectiveness of REDD is gauged by comparing observed emissions from within a geographical area during a commitment period against ‘reference levels’ of emissions that are predicted to have occurred from the same area if no intervention had taken place. There is no “correct” value for a REDD reference level – it is impossible to know what unplanned events will unfold in the future – so a central question, then, is whether it is possible to develop credible approaches that maximize the use of sound evidence to derive reference levels. Predictive modelling with reported uncertainty is necessary to inform policy decisions and to ensure conservative estimates of emissions are maintained. We must make use of good local datasets to inform a policy which will be implemented at a global scale, and will be worth billions of dollars when functional.

This talk is part of the Plant Sciences Research Seminars series.

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