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基于MaxEnt模型的新疆红枣生态适宜性与区划分析
引用本文:李曦光,王蕾,刘平,罗磊,侯晓臣,邱琴.基于MaxEnt模型的新疆红枣生态适宜性与区划分析[J].新疆农业科学,2020,57(10):1785-1791.
作者姓名:李曦光  王蕾  刘平  罗磊  侯晓臣  邱琴
作者单位:1.新疆林业科学院现代林业研究所,乌鲁木齐 830000;2.新疆农业大学计算机与信息工程学院,乌鲁木齐 830052
基金项目:自治区公益性科研院所基本科研业务经费(ky2018060)
摘    要:【目的】 结合种植区资源分布现状,利用最大熵模型(MaxEnt)预测新疆红枣潜在适生区,为新疆红枣区域布局和种植结构调整提供有效的理论指导和依据。【方法】 以年降水量、花期降水量(5~6月)、成熟期降水量(9~10月)、年有效积温(≥10℃)、年极端最低气温和平均气温6个气候因子和绿洲灌溉区、沙漠敏感区2个土地因子及高程因子为环境变量,利用GIS空间分析技术获取新疆红枣地理分布数据,采用MaxEnt模型进行建模并预测新疆红枣潜在适生区,使用百分比贡献率分析其主要环境因子及生态位参数。【结果】 (1)ROC评价(Receiver Operating Characteristic,ROC)显示MaxEnt模型预测新疆红枣潜在适生区的训练数据集和测试数据集的AUC值分别为0.921和0.904,模拟效果优秀。(2)新疆红枣潜在适生区总面积2 365.939 7×104 hm2,其中最适生区429.350 1×104 hm2,主要分布于新疆南疆的喀什地区、阿克苏地区、和田地区、克孜勒苏柯尔克孜自治州和巴音郭楞蒙古自治州,东疆的吐鲁番市、哈密市。(3)影响新疆红枣生长的主要环境因子是年极端最低气温(35.15%)、绿洲灌溉区(20.77%)、年有效积温(19%)和成熟期降水量(13.27%)。新疆红枣适宜生长在年极端最低气温≥-24.65℃,年有效积温≥3 595℃,成熟期降水量为0.54~7.64 mm,且绿洲灌溉区有助于提高其适生程度。【结论】 新疆红枣潜在适生区呈现环塔里木盆地聚集,低温是其最主要的影响因子。

关 键 词::红枣  最大熵模型  潜在适生区  环境因子  
收稿时间:2020-01-20

Study on Ecological Suitability and Regionalization of Xinjiang Jujube Based on MaxEnt Model
LI Xiguang,WANG Lei,LIU Ping,LUO Lei,HOU Xiaochen,QIU Qin.Study on Ecological Suitability and Regionalization of Xinjiang Jujube Based on MaxEnt Model[J].Xinjiang Agricultural Sciences,2020,57(10):1785-1791.
Authors:LI Xiguang  WANG Lei  LIU Ping  LUO Lei  HOU Xiaochen  QIU Qin
Institution:1. Institute of Modern Forestry, Xinjiang Academy of Forestry Sciences, Urumqi 830000, China;2. College of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China
Abstract:【Objective】 Combined with the current situation of resource allocation in the planting area, the maximum entropy (MaxEnt) model was used to predict the potential suitable area of Xinjiang jujube in the hope of providing effective theoretical guidance and basis for the regional layout and planting structure adjustment of Xinjiang jujube. 【Methods】 Six climatic factors, including annual precipitation, flowering precipitation (May-June), mature precipitation (September-October), annual effective accumulated temperature (≥10℃), annual extreme minimum temperature and average temperature, and two land factors, including oasis irrigation areas and desert sensitive areas, and elevation, had been taken as environmental variables. Geographical distribution data of Xinjiang jujube had been acquired by GIS spatial analysis technology. MaxEnt model was used to model and predict the potential suitable areas for Xinjiang jujube. The main environmental factors and niche parameters were analyzed by percentage contribution rate. The main environmental factors and niche parameters were analyzed by percentage contribution rate. 【Results】 (1) ROC evaluation showed that the AUC values of training data set and testing data set for predicting the potential suitable areas of Xinjiang jujube by MaxEnt model were 0.921 and 0.904 respectively, indicating that the simulation effect was excellent. (2) The total potential suitable areas of jujube in Xinjiang were 23.659 3 million hm2. Among them, the most suitable areas were 4.293 5 million hm2, which were mainly distributed in Kashgar Prefecture, Aksu Prefecture, Hetian Prefecture, Kizilsu Kirghiz Autonomous Prefecture and Bayingolong Mongolian Autonomous Prefecture of Southern Xinjiang, Turpan City and Hami City of East Xinjiang. (3) The main environmental factors affecting the growth of jujube in Xinjiang were annual minimum temperature (35.15%), oasis irrigation areas (20.77%), annual effective accumulated temperature (19%) and mature precipitation (13.27%). Xinjiang jujube was suitable to grow in the extreme minimum annual temperature which was greater than or equal to -24.65℃, annual effective accumulated temperature was greater than or equal to 35.95℃, mature precipitation was 0.54 -7.64 mm, and oasis irrigation areas could help to improve its suitability. 【Conclusion】 The potential suitable areas of jujube in Xinjiang shows accumulation around Tarim Basin, and the low temperature was the main influencing factor.
Keywords:jujube  maximum entropy model  potential suitable areas  environmental factors  
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