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Porter, J. R., & Wratten, S. (2014). National carbon stocks: Move on to a carbon currency standard. Nature, 506, 295.
Abstract: Alongside Robert Costanza and colleagues’ plea to abandon gross domestic product as a measure of national success (see Nature 505, 283–285; 2014), we believe that there is an urgent need to change the way currencies are valued — by using a new ‘carbon standard’ that links economy to ecology. This would work in a similar way to the old gold-exchange standard, except that a country’s currency value would instead be determined by its saved and standing stocks of fossil and non-fossil carbon. Governments would need to decide whether to risk devaluing their currency by depleting carbon stocks — while still honouring a commitment to keep fossil-carbon stocks at 80% as a safeguard against extreme climate change. After the Second World War, huge investments radically altered the economies of the United States, the Soviet Union and the United Kingdom. In the face of climate change, it is now the global energy system that needs reinvention.
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Comadira, G., Rasool, B., Karpinska, B., Morris, J., Verrall, S. R., Hedley, P. E., et al. (2015). Nitrogen deficiency in barley (Hordeum vulgare) seedlings induces molecular and metabolic adjustments that trigger aphid resistance. J. Experim. Bot., 66(12), 3639–3655.
Abstract: Agricultural nitrous oxide (N2O) pollution resulting from the use of synthetic fertilizers represents a significant contribution to anthropogenic greenhouse gas emissions, providing a rationale for reduced use of nitrogen (N) fertilizers. Nitrogen limitation results in extensive systems rebalancing that remodels metabolism and defence processes. To analyse the regulation underpinning these responses, barley (Horedeum vulgare) seedlings were grown for 7 d under N-deficient conditions until net photosynthesis was 50% lower than in N-replete controls. Although shoot growth was decreased there was no evidence for the induction of oxidative stress despite lower total concentrations of N-containing antioxidants. Nitrogen-deficient barley leaves were rich in amino acids, sugars and tricarboxylic acid cycle intermediates. In contrast to N-replete leaves one-day-old nymphs of the green peach aphid (Myzus persicae) failed to reach adulthood when transferred to N-deficient barley leaves. Transcripts encoding cell, sugar and nutrient signalling, protein degradation and secondary metabolism were over-represented in N-deficient leaves while those associated with hormone metabolism were similar under both nutrient regimes with the exception of mRNAs encoding proteins involved in auxin metabolism and responses. Significant similarities were observed between the N-limited barley leaf transcriptome and that of aphid-infested Arabidopsis leaves. These findings not only highlight significant similarities between biotic and abiotic stress signalling cascades but also identify potential targets for increasing aphid resistance with implications for the development of sustainable agriculture.
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Brouwer, F. (2013). Objectives of MACSUR project and TradeM theme..
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Köchy, M., Jorgenson, J., & Braunmiller, K. (2015). Overview of case studies (Vol. 6).
Abstract: MACSUR comprises 18 regional case studies for analysing the effects of climate change on agriculture with integrated inter-disciplinary models. Three case studies in Finland, Austria, and Italy have been selected as pilot studies because of their advancement in integration and representation of European farming systems and regions. No Label
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Wallach, D., Thorburn, P., Asseng, S., Challinor, A. J., Ewert, F., Jones, J. W., et al. (2016). Overview paper on comprehensive framework for assessment of error and uncertainty in crop model predictions (Vol. 8).
Abstract: Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. Several ways of quantifying prediction uncertainty have been explored in the literature, but there have been no studies of how the different approaches are related to one another, and how they are related to some overall measure of prediction uncertainty. Here we show that all the different approaches can be related to two different viewpoints about the model; either the model is treated as a fixed predictor with some average error, or the model can be treated as a random variable with uncertainty in one or more of model structure, model inputs and model parameters. We discuss the differences, and show how mean squared error of prediction can be estimated in both cases. The results can be used to put uncertainty estimates into a more general framework and to relate different uncertainty estimates to one another and to overall prediction uncertainty. This should lead to a better understanding of crop model prediction uncertainty and the underlying causes of that uncertainty. This study was published as (Wallach et al. 2016)
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