Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.tree.2019.04.012 |
Using Network Theory to Understand and Predict Biological Invasions | |
Frost, Carol M.1,2; Allen, Warwick J.3; Courchamp, Franck4; Jeschke, Jonathan M.5,6,7; Saul, Wolf-Christian5,6,7,8,9; Wardle, David A.1,10 | |
2019-09-01 | |
发表期刊 | TRENDS IN ECOLOGY & EVOLUTION
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ISSN | 0169-5347 |
EISSN | 1872-8383 |
出版年 | 2019 |
卷号 | 34期号:9页码:831-843 |
文章类型 | Review |
语种 | 英语 |
国家 | Sweden; Canada; New Zealand; France; Germany; South Africa; Singapore |
英文摘要 | Understanding and predicting biological invasions is challenging because of the complexity of many interacting players. A holistic approach is needed with the potential to simultaneously consider all relevant effects and effectors. Using networks to describe the relevant anthropogenic and ecological factors, from community-level to global scales, promises advances in understanding aspects of invasion from propagule pressure, through establishment, spread, and ecological impact of invaders. These insights could lead to development of new tools for prevention and management of invasions that are based on species' network characteristics and use of networks to predict the ecological effects of invaders. Here, we review the findings from network ecology that show the most promise for invasion biology and identify pressing needs for future research. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000482508800010 |
WOS关键词 | PLANT-POLLINATOR NETWORKS ; APPARENT COMPETITION ; ENEMY RELEASE ; TROPHIC INTERACTIONS ; FOOD WEBS ; ECOLOGICAL NETWORKS ; BIOTIC RESISTANCE ; BIODIVERSITY LOSS ; EXOTIC PLANTS ; SPECIES ROLES |
WOS类目 | Ecology ; Evolutionary Biology ; Genetics & Heredity |
WOS研究方向 | Environmental Sciences & Ecology ; Evolutionary Biology ; Genetics & Heredity |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/186902 |
专题 | 资源环境科学 |
作者单位 | 1.Swedish Univ Agr Sci, Dept Forest Ecol & Management, SE-90183 Umea, Sweden; 2.Univ Alberta, Dept Renewable Resources, 230D Earth Sci Bldg, Edmonton, AB T6G 2E3, Canada; 3.Lincoln Univ, Bioprotect Res Ctr, POB 84, Lincoln 7647, New Zealand; 4.Univ Paris Saclay, Univ Paris Sud, CNRS, Ecol Systemat & Evolut,AgroParisTech, F-91400 Orsay, France; 5.Leibniz Inst Freshwater Ecol & Inland Fisheries I, Muggelseedamm 310, D-12587 Berlin, Germany; 6.Free Univ Berlin, Dept Biol, Inst Biol, Chem,Pharm, Konigin Luise Str 1-3, D-14195 Berlin, Germany; 7.Berlin Brandenburg Inst Adv Biodivers Res BBIB, Altensteinstr 34, D-14195 Berlin, Germany; 8.Univ Stellenbosch, CIB, Dept Bot & Zool, Private Bag X1, ZA-7602 Matieland, South Africa; 9.Univ Stellenbosch, Dept Math Sci, Private Bag X1, ZA-7602 Matieland, South Africa; 10.Nanyang Technol Univ, Asian Sch Environm, 50 Nanyang Ave, Singapore, Singapore |
推荐引用方式 GB/T 7714 | Frost, Carol M.,Allen, Warwick J.,Courchamp, Franck,et al. Using Network Theory to Understand and Predict Biological Invasions[J]. TRENDS IN ECOLOGY & EVOLUTION,2019,34(9):831-843. |
APA | Frost, Carol M.,Allen, Warwick J.,Courchamp, Franck,Jeschke, Jonathan M.,Saul, Wolf-Christian,&Wardle, David A..(2019).Using Network Theory to Understand and Predict Biological Invasions.TRENDS IN ECOLOGY & EVOLUTION,34(9),831-843. |
MLA | Frost, Carol M.,et al."Using Network Theory to Understand and Predict Biological Invasions".TRENDS IN ECOLOGY & EVOLUTION 34.9(2019):831-843. |
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