Rong Jiang1,2, Wentian He3, Liang He4, J Y Yang2, B Qian5, Wei Zhou1, Ping He6. 1. Ministry of Agriculture Key Laboratory of Plant Nutrition and Fertilizer, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China. 2. Harrow Research and Development Centre, Agriculture and Agri-Food Canada, 2585 County Road, Harrow, ON, N0R 1G0, Canada. 3. Institute of Plant Nutrition and Resources, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China. wentian_he@hotmail.com. 4. National Meteorological Centre, Beijing, 100081, China. 5. Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Ave, Ottawa, ON, K1A 0C6, Canada. 6. Ministry of Agriculture Key Laboratory of Plant Nutrition and Fertilizer, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China. heping02@caas.cn.
Abstract
Maize (Zea mays L.) production in Northeast China is vulnerable to climate change. Thus, exploring future adaptation measures for maize is crucial to developing sustainable agriculture to ensure food security. The current study was undertaken to evaluate the impacts of climate change on maize yield and partial factor productivity of nitrogen (PFPN) and explore potential adaptation strategies in Northeast China. The Decision Support System for Agrotechnology Transfer (DSSAT) model was calibrated and validated using the measurements from nine maize experiments. DSSAT performed well in simulating maize yield, biomass and N uptake for both calibration and validation periods (normalized root mean square error (nRMSE) < 10%, -5% < normalized average relative error (nARE) < 5% and index of agreement (d) > 0.8). Compared to the baseline (1980-2010), the average maize yields and PFPN would decrease by 7.6-32.1% and 3.6-14.0 kg N kg-1 respectively under future climate scenarios (2041-2070 and 2071-2100) without adaptation. Optimizing N application rate and timing, establishing rotation system with legumes, adjusting planting dates and breeding long-season cultivars could be effective adaptation strategies to climate change. This study demonstrated that optimizing agronomic crop management practices would assist to make policy development on mitigating the negative impacts of future climate change on maize production.
Maize (n class="Species">Zea mays L.) production in Northeast China is vulnerable to climate change. Thus, exploring future adaptation measures for maize is crucial to developing sustainable agriculture to ensure food security. The current study was undertaken to evaluate the impacts of climate change on maize yield and partial factor productivity of nitrogen (PFPN) and explore potential adaptation strategies in Northeast China. The Decision Support System for Agrotechnology Transfer (DSSAT) model was calibrated and validated using the measurements from nine maize experiments. DSSAT performed well in simulating maize yield, biomass and N uptake for both calibration and validation periods (normalized root mean square error (nRMSE) < 10%, -5% < normalized average relative error (nARE) < 5% and index of agreement (d) > 0.8). Compared to the baseline (1980-2010), the average maize yields and PFPN would decrease by 7.6-32.1% and 3.6-14.0 kg N kg-1 respectively under future climate scenarios (2041-2070 and 2071-2100) without adaptation. Optimizing N application rate and timing, establishing rotation system with legumes, adjusting planting dates and breeding long-season cultivars could be effective adaptation strategies to climate change. This study demonstrated that optimizing agronomic crop management practices would assist to make policy development on mitigating the negative impacts of future climate change on maize production.
Authors: Diego Abalos; Ward N Smith; Brian B Grant; Craig F Drury; Sarah MacKell; Claudia Wagner-Riddle Journal: Sci Total Environ Date: 2016-08-26 Impact factor: 7.963