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基于MaxEnt模型预测气候变化下杉木在中国的潜在地理分布
引用本文:陈禹光,乐新贵,陈宇涵,程武学,杜金贵,钟全林,程栋梁.基于MaxEnt模型预测气候变化下杉木在中国的潜在地理分布[J].应用生态学报,2022,33(5):1207-1214.
作者姓名:陈禹光  乐新贵  陈宇涵  程武学  杜金贵  钟全林  程栋梁
作者单位:1.福建师范大学湿润亚热带生态地理过程教育部重点实验室, 福州 350007;2.福建师范大学福建省植物生理生态重点实验室, 福州 350007;3.江西阳际峰国家自然保护区管理局, 江西贵溪 335400;4.福建师范大学地理科学学院, 福州 350007;5.四川师范大学地理与资源科学学院, 成都 610101;6.四川师范大学西南土地资源评价与监测教育部重点实验室, 成都 610068
基金项目:国家自然科学基金项目(32071555, 32001094, 31971643)和福建省科技厅产学合作项目(2019N5009)资助。
摘    要:为研究杉木在中国的分布特征及其对气候变化的响应模式,本研究基于现有分布记录,应用最大熵(MaxEnt)模型和地理信息系统方法,结合气候、地形等环境要素,预测杉木在当前和未来气候变化下的潜在适生区。结果表明: 影响杉木分布的最主要因素是年平均降水量,在当前气候下,杉木适生区合计面积328万km2,占全国陆地总面积的34.5%,低、中和高适生区分别占18.3%、29.7%与52.0%。在未来气候情景下,杉木生长的适宜性在我国总体上呈上升趋势,适生区面积随气候变化增大,且明显向北扩张,南方湿润亚热带地区形成集中连片高适生区。模型经受试者工作特征曲线检验,训练集平均受试者工作特征曲线下面积为0.91,可信度高。

关 键 词:杉木  潜在地理分布  MaxEnt模型  气候情景  
收稿时间:2021-09-06

Identification of the potential distribution area of Cunninghamia lanceolata in China under climate change based on the MaxEnt model
CHEN Yu-guang,LE Xin-gui,CHEN Yu-han,CHENG Wu-xue,DU Jin-gui,ZHONG Quan-lin,CHENG Dong-liang.Identification of the potential distribution area of Cunninghamia lanceolata in China under climate change based on the MaxEnt model[J].Chinese Journal of Applied Ecology,2022,33(5):1207-1214.
Authors:CHEN Yu-guang  LE Xin-gui  CHEN Yu-han  CHENG Wu-xue  DU Jin-gui  ZHONG Quan-lin  CHENG Dong-liang
Abstract:Based on the distribution records of Cunninghamia lanceolata, we used the maximum Entropy (MaxEnt) model and geographic information system (GIS) methods, combined with environmental factors such as climate and terrain, to predict the potential distribution areas suitable for C. lanceolata under current and future climate scenarios. The results showed that annual precipitation was the most important factor driving the distribution of C. lanceolata. Under the current climate scenario, the total area of suitable for C. lanceolata growth was about 3.28 million km2, accounting for about 34.5% of the total land area of China. Among all the suitable areas, the lowly, intermediately, and highly suitable areas accounted for 18.3%, 29.7% and 52.0% of the total, respectively. Under future climate scenarios, the suitable area of C. lanceolata would increase, showing a clear trend of northward expansion in China. A concentrated and contiguous distribution region highly suitable for C. lanceolata would appear in the humid subtropical areas of southern China. The model was tested by the receiver operating characteristic curve (ROC). The average area under the curve of ROC of the training set was 0.91, showing high reliability.
Keywords:Cunninghamia lanceolata  potential geographical distribution  MaxEnt model  climate scenario  
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