Modelling adaptation strategies to reduce adverse impacts of climate change on maize cropping system in Northeast China

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.

Impact of weather parameters on maize agroecosystem and adaptation strategies under changing climatic conditions: A review: Sustainable and climate-resilient adaptation strategies in maize agroecosystem

“…Accurate weather forecasts and dissemination to the farming community can minimize the impact of extreme events (70). Thus, an integration of modeling adaptation strategies like Noptimization, crop rotations with legumes, planting dates, breeding of cultivars for early maturity, and policy development on the mitigation of the negative impact of climate change can be effective adaptation strategies (71).…”

Simulating the effect of climate change on barley yield in Ethiopia with the DSSAT‐CERES‐Barley model

“…Researchers around the globe have used DSSAT models for simulating climate change's effect on potential future yield (Araya et al., 2012; Endalew, 2019; Iglesias, 2009; Jiang et al., 2021; Paff & Asseng, 2019). Performance of the DSSAT model for simulating barley phenology, yield, soil water, and climate change effects are documented in many studies (Cammarano et al., 2020; Brogan, 2019; Hlavinka et al., 2010; Rötter et al., 2012).…”

Estimation of maize yield incorporating the synergistic effect of climatic and land use change: A case study of Jilin, China

“…The region features a short growing season of maize from May to September (Feng et al, 2021;Jiang et al, 2021;Yang et al, 2007). Over the past 50 years, the average annual temperature has increased significantly by 0.38°C per decade, precipitation has decreased slightly, and droughts and floods have become more frequent (Liu et al, 2009;Yin et al, 2016).…”

“…Future climate data, i.e., precipitation and surface temperatures, were collected from WDCC (https://doi.org/10.1594/WDCC/ETHr2), which were generated using general circulation modelthe Beijing Climate Center Climate System Model version 1.1 m (BCC_CSM1.1 m) (Knutti, 2014). The data are at a T106 horizontal resolution (1.125°×1.125°) (Liu et al, 2021;Wu et al, 2010), and have been widely used to explore maize, wheat and other grain planting systems in northeast China (Gao et al, 2020;He et al, 2018;Jiang et al, 2021).…”