气候变化领域集成服务门户(CCPortal): Predicting the spread of all invasive forest pests in the United States

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DOI	10.1111/ele.12741
	Predicting the spread of all invasive forest pests in the United States
	Hudgins E.J.; Liebhold A.M.; Leung B.
发表日期	2017
ISSN	1461-023X
EISSN	1461-0248
卷号	20 期号:4
英文摘要	We tested whether a general spread model could capture macroecological patterns across all damaging invasive forest pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility – well-studied predictors of establishment – should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread. © 2017 John Wiley & Sons Ltd/CNRS
英文关键词	Dispersal kernel; habitat invasibility; macroecology; propagule pressure; spatially explicit
学科领域	animal; animal dispersal; biological model; computer simulation; environmental protection; forest; fungus; insect; introduced species; mite; physiology; population dynamics; United States; Animal Distribution; Animals; Computer Simulation; Conservation of Natural Resources; Forests; Fungi; Insects; Introduced Species; Mites; Models, Biological; Population Dynamics; United States
语种	英语
scopus关键词	animal; animal dispersal; biological model; computer simulation; environmental protection; forest; fungus; insect; introduced species; mite; physiology; population dynamics; United States; Animal Distribution; Animals; Computer Simulation; Conservation of Natural Resources; Forests; Fungi; Insects; Introduced Species; Mites; Models, Biological; Population Dynamics; United States
来源期刊	Ecology Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/118414
作者单位	Biology Department, McGill University, Montreal, QC, Canada; Northern Research Station, USDA Forest Service, Morgantown, WV, United States
推荐引用方式 GB/T 7714	Hudgins E.J.,Liebhold A.M.,Leung B.. Predicting the spread of all invasive forest pests in the United States[J],2017,20(4).
APA	Hudgins E.J.,Liebhold A.M.,&Leung B..(2017).Predicting the spread of all invasive forest pests in the United States.Ecology Letters,20(4).
MLA	Hudgins E.J.,et al."Predicting the spread of all invasive forest pests in the United States".Ecology Letters 20.4(2017).