文献类型：期刊文献

中文题名：基于MaxEnt生态软件划分澳洲坚果的潜在地理适生区

英文题名：Predicting Potential Geographic Suitable Regions of Macadamia integrifolia Based on MaxEnt

作者：王伟[1] 田荣荣[2] 那立妍[1,2] 杨颖[3] 许新桥[1]

第一作者：王伟

机构：[1]林木遗传育种国家重点实验室国家林业局林木培育重点实验室中国林业科学研究院林业研究所;[2]北京城市学院生物医药学部;[3]山东省食品药品检验研究院

年份：2017

卷号：30

期号：3

起止页码：444-449

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2017_2018】；

基金：国家自然科学基金(41501059);中央级公益性科研院所基本科研业务费专项资金(CAFYBB2016QB004)

语种：中文

中文关键词：澳洲坚果;潜在适生区;MaxEnt;ArcGIS

外文关键词：Macadamia integrifolia ; potential geographical distribution ; MaxEnt ; ArcGIS

分类号：S727.3

摘要：[目的]对澳洲坚果在中国的潜在分布区进行预测,并对其适生区进行分析和划分。[方法]通过收集澳洲坚果的地理信息数据,利用最大熵模型(MaxEnt)与地理信息系统(ArcGIS),综合相关19项气候因子,预测划定澳洲坚果在世界以及我国的潜在地理分布区。[结果]该物种生长区域狭窄,对环境要求苛刻。世界范围内,澳洲坚果的较适宜生长区在澳洲东部、南美洲东南部和马达加斯加岛东部以及亚洲地区23°26'~30°N,73°~122°E范围内。在我国,澳洲坚果适宜分布区主要集中在西藏、台湾、广西、广东和云南等地,其高适宜区面积依次为西藏(15 359km^2),台湾(14 054 km^2),广西(7 372 km^2),广东(6 147 km^2)和云南(3 776 km^2)。刀切法(Jackknife)分析显示,澳洲坚果分布主要受到极端最高温、年均气温变化范围、最干月降雨量、温度季节性变化和等温性等气象因子的影响。[结论]本研究用MaxEnt模拟澳洲坚果的潜在地理分布有一定的准确性,划分出了澳洲坚果基本的地理分布格局和潜在分布区域,并阐明了主导其地理分布的生物气候因子,为澳洲坚果尤其是在我国的引种和推广应用提供了参考。
[ Objective] To predict the potential distribution area of Macadamia integrifolia in China and analyze its suitability. [ Method]The distribution of M. integrifolia and 19 related environmental factors were collected. The potential suitable distribution range of M. integrifolia in the world was analyzed by the softwares MaxEnt and Arc- GIS. E Result] The results showed that the growth areas is very narrow, and this species is demanding on the growth environment. In the world, macadamia nuts is suitable to growth in eastern Australia, southeast of South America and the eastern part of Madagascar Island, but the suitable area are mainly located in the range of latitude 23°26＇ 30° N and longitude 73°- 122°E in Asia. In China, the suitable distribution areas for M. integrifblia are mainly concentrated in Xizang, Taiwan, Guangdong, Guangxi and Yunnan. The highly suitable area in the province men-tioned above are： Xizang （15 359 km^2）, Taiwan （14 054 km^2）, Guangdong （7 372 km^2） , Guangxi （6 147 km^2） and Yunnan （3 776 km^2）. Jackknife analysis showed that five environmental factors （maximum temperature of the warmest month, mean annual temperature range, preeipitation of the driest month, temperature seasonality, Isother- reality） have obvious influence on M. integrifolia distributions. [ Conclusion] In general, MaxEnt accurately simu- lated the geographical distribution of M. integrifolia. It showed the basic pattern of geographic distribution and the potential distribution areas, and clarified the dominant bioelimatie factors to geographic distribution of M. integrifo- lia. The results provide references for M. integrifolia introduction and extension in China.