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2017 - Scientific Reports, 7:14858 |
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Hasegawa, T., Li, T., Yin, X., Zhu, Y., Boote, K., Baker, J. ... Confalonieri, R. ... Wallach, D., Wang, Y., Wilson, L.T., Yang, L., Yang, Y., Yoshida, H., Zhang, Z., Zhu, J. |
Abstract:
The CO2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO2] (E-[CO2]) by comparison to free-air CO2 enrichment (FACE) and chamber experiments. The model ensemble
reproduced the experimental results well. However, yield prediction in response to E-[CO2] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO2] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO2] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative
nature of the morphological response to E-[CO2] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO2] × N interactions is necessary to better evaluate management practices under climate change.
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Keywords: - |
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DOI: 10.1038/s41598-017-13582-y |
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AbioticDamage A software component for the impact of abiotic damages on crop productions |
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CropML CropML is a framework-independent component implementing a variety of approaches for crop growth |
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SoilW A software library implementing different approaches for soil hydrology simulation |
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