Gao Bei, Hu Ning, Guo Yan Long, Gu Wei, Zou Ji Ye
Jiangsu Key Laboratory of Agricultural Meteorology/College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Remote Sensing Information Center for Agriculture of Shaanxi Province, Xi'an 710015, China.
Ying Yong Sheng Tai Xue Bao. 2017 Oct;28(10):3331-3340. doi: 10.13287/j.1001-9332.201710.015.
Foxtail millet is one of the main food crops in arid and semi-arid areas of China. Due to its strong anti-adversity, wide adaptability and resistance against drought and barren, the foxtail millet is treated as an important strategic crop reserve for the future drought situation. In this study, data from 157 geographical distributions were used to choose 10 climatic indices, 7 soil indices and 3 topographical indices, which were based on the relationship between the foxtail millet production and the environmental factors. Four species distribution models, including maximum entropy model (MaxEnt), ecological niche factor analysis (ENFA), random forest (RF) and generalized additive model (GAM), were applied to analyze the potential geographic distribution of foxtail millet in China. The results showed that all four models did a good job in simulating the potential geographic distribution for foxtail millet and the MaxEnt model was the best one. Precipitation and temperature were most sensitive to the distribution of foxtail millet among all selected environmental factors. The outputs of models, together with the ArcGIS spatial analyst module, displayed that the total potential suitable growing regions for the foxtail millet, including the highly and moderately suitable gro-wing regions, occupied 55.68×10 km, which were much larger than the actual foxtail millet gro-wing area. The potential suitable growing regions were mainly located in northeast China, including the Northeast Plain, south of Changbai Mountain and Mudanjiang River basin, north China, including north of the Huaihe River, central China, including east of Hanjiang River and north of Dabie Mountains, northwest China, including Loess Plateau, the southern Ordos Plateau, the eastern Qilian Mountains, the eastern Tianshan Mountains and the Altai Mountains, and southwest China, including north of Chongqing and the western Guizhou Province.
谷子是中国干旱和半干旱地区的主要粮食作物之一。由于其抗逆性强、适应性广、耐旱耐瘠薄，谷子被视为应对未来干旱形势的重要战略作物储备。本研究基于谷子产量与环境因素的关系，利用157个地理分布数据选取了10个气候指标、7个土壤指标和3个地形指标。应用最大熵模型（MaxEnt）、生态位因子分析（ENFA）、随机森林（RF）和广义相加模型（GAM）四种物种分布模型，分析了谷子在中国的潜在地理分布。结果表明，四种模型在模拟谷子潜在地理分布方面均表现良好，其中MaxEnt模型效果最佳。在所有选定的环境因素中，降水和温度对谷子分布最为敏感。模型输出结果结合ArcGIS空间分析模块显示，谷子潜在适宜种植区总面积，包括高度适宜和中度适宜种植区，为55.68×10平方千米，远大于谷子实际种植面积。潜在适宜种植区主要位于中国东北地区，包括东北平原、长白山以南和牡丹江流域；华北地区，包括淮河以北；华中地区，包括汉江以东和大别山以北；西北地区，包括黄土高原、鄂尔多斯高原南部、祁连山东部、天山东部和阿尔泰山脉；以及西南地区，包括重庆北部和贵州省西部。
