Author
Listed:
- Zhiluo Zhou
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China
School of Ecology, Hainan University, Haikou 570228, China)
- Xiaohuang Liu
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Run Liu
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Jiufen Liu
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Wenjie Liu
(School of Ecology, Hainan University, Haikou 570228, China)
- Qiu Yang
(School of Ecology, Hainan University, Haikou 570228, China)
- Xinping Luo
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Ran Wang
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Liyuan Xing
(Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Beijing 100055, China
Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Honghui Zhao
(Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
- Chao Wang
(Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China)
Abstract
Sugarcane is an important economic crop in China, and its yield is significantly affected by climate change. With climate change leading to significant shifts in environmental conditions, the suitable cultivation zones for the crop are expected to change, impacting China’s sugarcane production and industry layout. This study aims to analyze potential distribution areas for sugarcane under different climate change scenarios, providing scientific guidance for optimizing future cultivation zones and resource allocation. Data on sugarcane distribution in China and 38 related environmental factors were collected. After excluding variables with high correlations, the MaxEnt model and ArcGIS 10.2 software were used to analyze the main environmental factors affecting crop survival based on contribution rates and the Jackknife method. The study simulated the suitable areas in China during the historical period and predicted future suitable areas under three greenhouse gas emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results showed that the Area Under the Receiver Operating Characteristic Curve (AUC) was 0.921, indicating high accuracy in the model’s analysis of suitability zones. The three dominant environmental variables influencing sugarcane distribution in China were identified as annual precipitation, min temperature of the coldest month and elevation. The primary suitable zones are concentrated in southern China, forming a “V” shape, including regions such as Guangxi, Sichuan, Guizhou, Yunnan, Hainan, and Fujian. In the future, the area of unsuitable zones is expected to decrease. The overall suitable zones for sugarcane are projected to shift towards the central and northern parts of China. This research can assist China’s sugarcane industry in addressing the challenges of climate change and provide references for its cultivation, industry layout optimization, and the selection of new planting sites.
Suggested Citation
Zhiluo Zhou & Xiaohuang Liu & Run Liu & Jiufen Liu & Wenjie Liu & Qiu Yang & Xinping Luo & Ran Wang & Liyuan Xing & Honghui Zhao & Chao Wang, 2025.
"Sugarcane Distribution Simulation and Climate Change Impact Analysis in China,"
Agriculture, MDPI, vol. 15(5), pages 1-14, February.
Handle:
RePEc:gam:jagris:v:15:y:2025:i:5:p:491-:d:1599108
Download full text from publisher
References listed on IDEAS
- Yibo Xu & Xiaohuang Liu & Lianrong Zhao & Jiufen Liu & Xiaofeng Zhao & Hongyu Li & Chao Wang & Honghui Zhao & Ran Wang & Xinping Luo & Liyuan Xing, 2024.
"Prediction of Potential Suitability Areas for Ephedra sinica in the Five Northwestern Provinces of China Under Climate Change,"
Agriculture, MDPI, vol. 14(10), pages 1-18, October.
- Sutton, G.F. & Martin, G.D., 2022.
"Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect,"
Ecological Modelling, Elsevier, vol. 473(C).
- van Steenderen, Clarke J.M. & Sutton, Guy F., 2024.
"Climate covariate selection influences MaxEnt model predictions and predictive accuracy under current and future climates,"
Ecological Modelling, Elsevier, vol. 498(C).
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