湖北省日本落叶松栽培区划  

Classification of the cultivation regions of Larix kaempferi in Hubei Province on the basis of maximum entropy ecological niche models

作　　者：杜超群[1] 袁慧 单华平 苏尚敏 侯义梅 许业洲[1] DU Chaoqun;YUAN Hui;SHAN Huaping;SU Shangmin;HOU Yimei;XU Yezhou(Hubei Academy of Forestry, Wuhan, Hubei 430075, China;Institute of Forestry Science in Jianshi, Jianshi, Hubei 445300, China;Jianshi County State-owned Gaoyanzi Forest Farm, Jianshi, Hubei 445300, China)

机构地区：[1]湖北省林业科学研究院,湖北武汉430075 [2]建始县林业局,湖北建始445300 [3]建始县国有高岩子林场,湖北建始445300

出　　处：《森林与环境学报》2019年第3期273-279,共7页Journal of Forest and Environment

基　　金：国家重点研发计划项目子课题"北亚热带日本落叶松高效培育技术"(2017YFD0600401)

摘　　要：根据湖北省温、湿度气象资料及已知日本落叶松造林点的位置信息,利用最大熵(MaxEnt)生态位模型开展日本落叶松栽培气候区划研究,旨在阐明湖北省日本落叶松栽植的气候差异格局,为日本落叶松人工林发展的布局和规划提供支持。结果表明:湖北省日本落叶松气候区划可以分为3个等级:最适宜区、较适宜区和不适宜区,其中最适宜区面积为1.35×10~4km^2,较适宜区面积为1.29×10~4km^2。适宜区域主要为鄂西大巴山东段、巫山和武陵山的部分地区,以及鄂皖交界处的大别山山脉,海拔在800～2 000 m之间;模型受试者工作特征曲线(ROC)下的面积值(AUC)达到0.927,证明预测效果较好。刀切法分析对分布预测的贡献率排名前5位的因子分别为温度季节性变异、最热月最高温度、最热季平均温度、年平均温度和温度年较差,说明影响湖北省日本落叶松适生区划分的气候因子主要为温度因子。To clarify the basic pattern of climate difference distribution and provide references for the layout and planning of Larix kaempferi in Hubei Province, the software MaxEnt was used to classify the cultivation regions of L. kaempferi in Hubei Province with environmental data for temperature and humidity and known distribution. The results showed that the suitability degrees were divided into three categories: the most suitable region (1.35×10 ^4 km ^2), suitable region (1.29×10 ^4 km^2), and not suitable region. The suitable region was mainly in western Hubei, including eastern Dabashan Mountain and parts of Wushan and Wulingshan Mountain and Dabieshan Mountain at the junction of Hubei and Anhui between 800 and 2 000 m altitude. The model constructed using MaxEnt was highly reliable and evaluated using the receiver operating characteristic (AUC=0.927). Response curves created using the jackknife method showed that the temperature factors had an obvious influence on the distribution of L. kaempferi . Temperature seasonality , maximum temperature in the warmest month, mean temperature in the warmest quarter, annual mean temperature, and annual temperature range, which were all related to high temperature and temperature range, were the top five factors that contributed to the prediction.

关 键 词：日本落叶松 最大熵 生态位模型 栽培区划 

分 类 号：S722.8[农业科学—林木遗传育种]