Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L.) Using Herbarium Data and a Maximum Entropy Model

doi:10.3390/f5112773

	Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L.) Using Herbarium Data and a Maximum Entropy Model
	Li, Guoqing 1,2; Xu, Guanghua 3; Guo, Ke4 ; Du, Sheng 1,2
	2014
发表期刊	FORESTS
卷号	5 期号:11 页码:2773-2792
摘要	Black locust (Robinia pseudoacacia L.) is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt) was used to simulate the potential distribution of this species around the world, and the dominant climatic factors affecting its distribution were selected by using a jackknife test and the regularized gain change during each iteration of the training algorithm. The results show that the MaxEnt model performs better than random, with an average test AUC value of 0.9165 (+/- 0.0088). The coldness index, annual mean temperature and warmth index were the most important climatic factors affecting the species distribution, explaining 65.79% of the variability in the geographical distribution. Species response curves showed unimodal relationships with the annual mean temperature and warmth index, whereas there was a linear relationship with the coldness index. The dominant climatic conditions in the core of the black locust distribution are a coldness index of -9.8 degrees C-0 degrees C, an annual mean temperature of 5.8 degrees C-14.5 degrees C, a warmth index of 66 degrees C-168 degrees C and an annual precipitation of 508-1867 mm. The potential distribution of black locust is located mainly in the United States, the United Kingdom, Germany, France, the Netherlands, Belgium, Italy, Switzerland, Australia, New Zealand, China, Japan, South Korea, South Africa, Chile and Argentina. The predictive map of black locust, climatic thresholds and species response curves can provide globally applicable guidelines and valuable information for policymakers and planners involved in the introduction, planting and invasion control of this species around the world.
关键词	species distribution coldness index warmth index climatic threshold ecological niche
学科领域	Forestry
DOI	10.3390/f5112773
收录类别	SCI
语种	英语
WOS关键词	SPECIES DISTRIBUTIONS ; CLIMATE ; BIODIVERSITY ; PLANT ; PREDICTION ; KNOWLEDGE
WOS研究方向	Forestry
WOS记录号	WOS:000345531000010
出版者	MDPI
文献子类	Article
出版地	BASEL
EISSN	1999-4907
资助机构	National Nature Science Foundation of China [31300407] ; Specialized Research Fund for the Doctoral Program of Higher Education [20130204120028] ; Institute of Soil and Water Conservation, CASMWR [A315021441]
作者邮箱	liguoqing@nwsuaf.edu.cn ; xsplendor@gmail.com ; guoke@ibcas.ac.cn ; shengdu@ms.iswc.ac.cn
作品OA属性	Green Submitted, gold, Green Published
引用统计	被引频次：59[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/27154
专题	植被与环境变化国家重点实验室
作者单位	1.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Peoples R China 2.Chinese Acad Sci, Inst Soil & Water Conservat, Yangling 712100, Peoples R China 3.Minist Water Resources, Yangling 712100, Peoples R China 4.Chinese Acad Sci, Inst Subtrop Agr, Changsha 410125, Hunan, Peoples R China 5.Chinese Acad Sci, State Key Lab Vegetat & Environm Change, Inst Bot, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Li, Guoqing,Xu, Guanghua,Guo, Ke,et al. Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L.) Using Herbarium Data and a Maximum Entropy Model[J]. FORESTS,2014,5(11):2773-2792.
APA	Li, Guoqing,Xu, Guanghua,Guo, Ke,&Du, Sheng.(2014).Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L.) Using Herbarium Data and a Maximum Entropy Model.FORESTS,5(11),2773-2792.
MLA	Li, Guoqing,et al."Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L.) Using Herbarium Data and a Maximum Entropy Model".FORESTS 5.11(2014):2773-2792.

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