| DOI: | 10.1111/ele.12741
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| Scopus记录号: | 2-s2.0-85012067031
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| 论文题名: | Predicting the spread of all invasive forest pests in the United States |
| 作者: | Hudgins E.J.; Liebhold A.M.; Leung B.
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| 刊名: | Ecology Letters
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| ISSN: | 1461023X
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| EISSN: | 1461-0248
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| 出版年: | 2017
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| 卷: | 20, 期:4 | | 起始页码: | 426
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| 结束页码: | 435
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| 语种: | 英语
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| 英文关键词: | Dispersal kernel
; habitat invasibility
; macroecology
; propagule pressure
; spatially explicit
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| 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
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| 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 |
| Citation statistics: |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/107643
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| Appears in Collections: | 气候减缓与适应
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作者单位: | Biology Department, McGill University, Montreal, QC, Canada; Northern Research Station, USDA Forest Service, Morgantown, WV, United States
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| Recommended Citation: | |
Hudgins E.J.,Liebhold A.M.,Leung B.. Predicting the spread of all invasive forest pests in the United States[J]. Ecology Letters,2017-01-01,20(4)
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