干旱区生态环境知识资源中心(Arid): Vegetation classification enables inferring mesoscale spatial variation in plant invasibility

Arid

DOI	10.1017/inp.2019.23
	Vegetation classification enables inferring mesoscale spatial variation in plant invasibility
	Li, Yue M.; Stauffer, Brett; Malusa, Jim
通讯作者	Li, YM (corresponding author), Univ Arizona, Sch Nat Resources & Environm, 1064 East Lowell St, Tucson, AZ 85721 USA.
来源期刊	INVASIVE PLANT SCIENCE AND MANAGEMENT
ISSN	1929-7291
EISSN	1939-747X
出版年	2019
卷号	12 期号:3 页码:161-168
英文摘要	Large-scale control of invasive plants can benefit strongly from reliable assessment of spatial variation in plant invasibility. With this knowledge, limited management resources can be concentrated in areas of high invasion risk. We assessed the influence of spatial environments and proximity to roads on the invasibility of African mustard (Brassica tournefortii Gouan) over the 280,000-ha Barry M. Goldwater Range West in southwestern Arizona, USA. We used presence/absence data of B. tournefortii acquired from a vegetation classification project, in which lands were mapped to the level of vegetation subassociations. Logistic regression models suggested that spatial environments represented by the subassociations, not proximity to roads, represented the only factor significantly explaining B. tournefortii presence. We then used the best model to predict B. tournefortii invasibility in each subassociation. This prediction indicates management strategy should differ between the western part and the central to eastern part of the range. The western range is a large spatial continuum with intermediate to high invasion risk, vulnerable to an untethered spread of B. tournefortii. Controlling efforts should focus on preventing existing local populations from further expansion. The central and eastern ranges are a mosaic varying strongly in invasion risk. Control efforts can take advantage of natural invasion barriers and further reduce connectivity through removal of source populations connected with other high-risk locations via roads and other dispersal corridors. We suggest our approach as one effective way to combine vegetation classification and plant invasion assessment to manage complex landscapes over large ranges, especially when this approach is used through an iterative prediction-validation process to achieve adaptive management of invasive plants.
英文关键词	Songlin Fei Purdue University Brassica tournefortii large scale plant invasion Sahara mustard spatial heterogeneity U S National Vegetation Classification weed management
类型	Article
语种	英语
开放获取类型	Green Accepted
收录类别	SCI-E
WOS记录号	WOS:000517845200002
WOS关键词	BRASSICA-TOURNEFORTII ; MOJAVE DESERT ; INVASION ; COMMUNITY ; MANAGEMENT ; DIVERSITY ; STANDARDS ; MODELS ; SPACE
WOS类目	Plant Sciences
WOS研究方向	Plant Sciences
来源机构	University of Arizona
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369416
作者单位	[Li, Yue M.; Malusa, Jim] Univ Arizona, Sch Nat Resources & Environm, 1064 East Lowell St, Tucson, AZ 85721 USA; [Li, Yue M.] Arizona Sonora Desert Museum, Tucson, AZ USA
推荐引用方式 GB/T 7714	Li, Yue M.,Stauffer, Brett,Malusa, Jim. Vegetation classification enables inferring mesoscale spatial variation in plant invasibility[J]. University of Arizona,2019,12(3):161-168.
APA	Li, Yue M.,Stauffer, Brett,&Malusa, Jim.(2019).Vegetation classification enables inferring mesoscale spatial variation in plant invasibility.INVASIVE PLANT SCIENCE AND MANAGEMENT,12(3),161-168.
MLA	Li, Yue M.,et al."Vegetation classification enables inferring mesoscale spatial variation in plant invasibility".INVASIVE PLANT SCIENCE AND MANAGEMENT 12.3(2019):161-168.