Optimizing Sowing Date and Planting Density Can Mitigate the Impacts of Future Climate on Maize Yield: A Case Study in the Guanzhong Plain of China

Fang Xu,Ning Yao,Chuan He,Qiang Yu,De Li Liu,Hao Feng,Jiquan Xue,Bin Wang,Jianqiang He,Puyu Feng,Shutu Xu,Renhe Zhang

doi:10.3390/agronomy11081452

Abstract

We used the APSIM-Maize model to simulate maize potential yield (Yp) and rain-fed yield (Yw) when adaptation options of sowing date and planting density were adopted under Representative Concentration Pathway (RCP) 4.5 and 8.5 in the Guanzhong Plain of China. The results showed that Yp would decrease by 10.6–14.9% and 15.0–31.4% under RCP4.5 and RCP8.5 for summer maize, and 13.9–19.7% and 18.5–36.3% for spring maize, respectively. The Yw would decrease by 17.1–19.0% and 23.6–41.1% under RCP4.5 and RCP8.5 for summer maize, and 20.9–24.5% and 27.8–45.5% for spring maize, respectively. The loss of Yp and Yw could be reduced by 2.6–9.7% and 0–9.9%, respectively, under future climate for summer maize through countermeasures. For spring maize, the loss of Yp was mitigated by 14.0–25.0% and 2.0–21.8% for Yw. The contribution of changing sowing date and plant density on spring maize yield was more than summer maize, and the optimal adaptation options were more effective for spring maize. Additionally, the influences of changing sowing date and planting density on yields become weak as climate changes become more severe. Therefore, it is important to investigate the potential of other adaptation measures to cope with climate change in the Guanzhong Plain of China.

Highlights

It has been estimated that the global average surface temperature will increase by 0.3–4.8 ◦C by the end of the 21st century [1]
We found that properly delaying the sowing date and increasing planting density could effectively offset the negative effects of future climate change
We evaluated the possible changes in maize yield simulated by the Agricultural Production Systems sIMulator (APSIM)-Maize model under future climate change based on a total of 36 global climate models (GCMs) under two greenhouse emission scenarios of RCP4.5 and RCP8.5

Summary

Introduction

It has been estimated that the global average surface temperature will increase by 0.3–4.8 ◦C by the end of the 21st century [1]. Climate change has seriously affected agricultural production, especially in developing countries such as China [3,4,5]. It is urgent to develop various agronomic management practices to cope with the negative impacts of climate change on crop production to ensure global food security. Maize is one of the three major food crops in the world. The yield of maize rose by 66.9 kg ha−1 year−1 since 1961 and the total production became the largest among the three main food crops since 2001 in the world [6]. The harvested areas of maize decreased obviously in China This was mainly because of the national policy on optimizing the planting structure and reducing inefficient crop planting areas [8]

Methods

Results

Discussion

Conclusion