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.
Highlights
Exploring effective adaptation measures in Northeast China is crucial to improving maize production and maintaining environmental health under future climate change
The model performance was “good” to “excellent” for maize yield, biomass and N uptake simulation under the farmers’ practice (FP) treatment at all sites based on the average statistical value of normalized root mean square error (nRMSE) ≤ 6.4%, −1.4% ≤ normalized average relative error (nARE) ≤ 3.3% and d ≥ 0.76 (Table 1 and Supplementary Fig. S1, 2)
The well calibrated Decision Support System for Agrotechnology Transfer (DSSAT) model was proven a capable tool for assessing climate change impacts on maize yield and NUE and exploring adaptation strategies under Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 scenarios in Northeast China
Summary
Exploring effective adaptation measures in Northeast China is crucial to improving maize production and maintaining environmental health under future climate change. Fertilizer application rate and timing should be adjusted to meet the nutrient demands of crop growth and avoid nutrient loss when crop biomass decreases due to water and temperature stress over time under climate change[14,15] He et al.[14] explored the response of maize yields to fertilizer application rate under future climate scenarios, which suggested that the nitrogen (N) rate of 150 kg N ha−1 would be suitable for high maize yields in Canada based on the Decision Support System for Agrotechnology Transfer (DSSAT) model. The DSSAT model has been used to simulate the impacts of climate change on maize yield, no detailed adaptation strategies were assessed in simulations by considering comprehensive management practices for improving maize production and N use efficiency in Northeast China. The objectives of this study were (1) to calibrate and evaluate the DSSAT model using the measured maize yield, biomass and N uptake from nine field experiments in Northeast China; (2) to simulate the climate change impacts on maize yield and partial factor productivity of N (PFPN) during two future periods of 2041–2070 and 2071–2100, relative to the baseline (1981–2010) under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios; and (3) to explore potential adaptation strategies to reduce the negative impacts of future climate change on maize yield and N use efficiency
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