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- W2077165783 abstract "Crop growth models can be used to address the mode-of-action of the global change impacts on crop yield as well as to predict the extent of the yield change. Presented in this paper are the framework to analyze the simulated yield change caused by the variations of many influencing factors and some methods to visualize the yield change. In the framework, the simulated yield change is mapped into an n-dimensional vector space, where n is the number of the simulated cases, e.g. years or locations. Yield changes owing to the individual impacts as well as the impact of simultaneous changes in all the factors are represented by vectors in the n-dimensional space. Contributions of the individual impacts to the simulated yield change and the interrelations between the impacts can be represented by the magnitude and orientation of the vectors. To visualize the vectors, however, the dimension n must be three or less. This is not the case, in general, and hence some methods are needed to reduce the dimension. By combining the influencing factors into three or less groups, the vectors for each group can be visualized in a subspace of dimension three or less. Impacts within each group may be further visualized in the same way. Taking an average is another way to reduce the dimension of the vector space. With it, the n-dimensional space is partitioned into a one-dimensional space for the mean and an (n - I)-dimensional space for the deviation of the yield change. These methods were applied to an example of the simulated yield changes in soybean and maize owing to climate change (precipitation increase and temperature rise) and elevated CO2 (increases in the radiation use efficiency and the water use efficiency). The analyses revealed the differences between soybean and maize with respect to their responses to the simulated impacts of the climate change and the elevated CO2. These inter-specific differences were related to the differential changes in growth processes. The difference between the two impacts, i.e. the climate change and the CO2 increase, was also addressed. Utilities of the above approach were discussed and compared with the sensitivity analysis. Limitation of this approach was also discussed." @default.
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- W2077165783 date "1994-03-01" @default.
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- W2077165783 title "Mapping results of crop growth simulation in a vector space" @default.
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- W2077165783 doi "https://doi.org/10.1016/0168-1923(94)90068-x" @default.
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