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Ingram, J. S. I., & Porter, J. R. (2015). Plant science and the food security agenda. Nature Plants, 1(11), 15173.
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Porter, J. R., Durand, J. L., & Elmayan, T. (2016). Edited plants should not be patented. Nature, 530, 33.
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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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Wang, E., Martre, P., Zhao, Z., Ewert, F., Maiorano, A., Rötter, R. P., et al. (2017). The uncertainty of crop yield projections is reduced by improved temperature response functions. Nature Plants, 3, 17102.
Abstract: Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections. Erratum: doi: 10.1038/nplants.2017.125
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