Tian, Z., Xu, H., Sun, L., Fan, D., Fischer, G., Zhong, H., Zhang, P., Pope, E., et al. (2020). Using a cross-scale simulation tool to assess future maize production under multiple climate change scenarios: An application to the Northeast Farming Region of China. Climate Services 18 e100150. 10.1016/j.cliser.2020.100150.
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Abstract
The Northeast Farming Region (NFR) is a major maize cropping region in China, which accounts for about 30% of national maize production. Although the regional maize production has an increasing trend in the last decades, it has greater inter-annual fluctuation. The fluctuation is caused by the increased variations of the local temperature and precipitation given the dominance of rainfed maize in the region. To secure high and stable level of maize production in the NFR under the warmer and drier future climate conditions, we employed a cross-scale model-coupling approach to identify the suitable maize cultivars and planting adaptation measures. Our simulation results show that, with proper adaptations of maize cultivars and adjustments of planting/harvest dates, both maize planting area and yield per unit of land will increase in most regions of NFR. This finding indicates that proactive adaptation can help local farmers to reap the benefits of increasing heat resource brought in by global warming, thus avoiding maize production losses as reported in other studies. This research can potentially contribute to the development of agricultural climate services to support climate-smart decisions for agricultural adaptations at the plot, farm and regional scales, in terms of planning the planting structure of multiple crops, breeding suitable maize varieties, and optimizing planting and field management schedules.
Item Type: | Article |
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Uncontrolled Keywords: | Agriculture climate service; Cross-scale model coupling; Climate change; Maize production; Food security; China |
Research Programs: | Water (WAT) Young Scientists Summer Program (YSSP) |
Depositing User: | Luke Kirwan |
Date Deposited: | 03 Feb 2020 06:39 |
Last Modified: | 27 Aug 2021 17:32 |
URI: | https://pure.iiasa.ac.at/16284 |
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