基于MaxEnt模型预测气候变化下杉木在中国的潜在地理分布

doi:10.13287/j.1001-9332.202205.024

应用生态学报 ›› 2022, Vol. 33 ›› Issue (5): 1207-1214.doi: 10.13287/j.1001-9332.202205.024

基于MaxEnt模型预测气候变化下杉木在中国的潜在地理分布

陈禹光^1,2, 乐新贵³, 陈宇涵⁴, 程武学^5,6, 杜金贵^1,2, 钟全林^1,2, 程栋梁^1,2*

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

收稿日期:2021-09-06 接受日期:2022-02-28 出版日期:2022-05-15 发布日期:2022-11-15
通讯作者: * E-mail: chengdl02@aliyun.com
作者简介:陈禹光, 男, 1996年生, 硕士研究生。主要从事植物地理与植物生态研究。E-mail: ygChen0612@163.com
基金资助:
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。

Identification of the potential distribution area of Cunninghamia lanceolata in China under climate change based on the MaxEnt model

CHEN Yu-guang^1,2, LE Xin-gui³, CHEN Yu-han⁴, CHENG Wu-xue^5,6, DU Jin-gui^1,2, ZHONG Quan-lin^1,2, CHENG Dong-liang^1,2*

¹Key Laboratory for Humid Subtropical Eco-geographical Processes, Fujian Normal University, Fuzhou 350007, China;
²Fujian Provincial Key Laboratory for Plant Eco-Physiology, Fujian Normal University, Fuzhou 350007, China;
³Yangjifeng National Nature Reserve Administration of Jiangxi Province, Guixi 335400, Jiangxi, China;
⁴School of Geographical Science, Fujian Normal University, Fuzhou 350007, China;
⁵Institute Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China;
⁶Key Laboratory of Land Resources Evaluation and Monitoring in Southwest of Ministry of Education, Sichuan Normal University, Chengdu 610068, China

Received:2021-09-06 Accepted:2022-02-28 Online:2022-05-15 Published:2022-11-15

摘要/Abstract

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

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.

Key words: Cunninghamia lanceolata, potential geographical distribution, MaxEnt model, climate scenario

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.

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.

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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

Identification of the potential distribution area of Cunninghamia lanceolata in China under climate change based on the MaxEnt model

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