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Invasive species information networks: collaboration at multiple scales for prevention, early detection,and rapid response to invasive alien species

机译:外来入侵物种信息网络:在预防,早期发现和对外来入侵物种的快速反应方面的多尺度协作

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Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MidSouth) generate occurrence data at local and regional levels within the United States, which are shared through the US National Institute of Invasive Species Science, The Inter-American Biodiversity Information Network's Invasives Information Network (I3N), facilitates cooperation on sharing invasive species occurrence data throughout the Western Hemisphere. The I3N and other national and regional networks expose their data globally via the Global Invasive Species Information Network (GISIN). International and interdisciplinary cooperation on data sharing strengthens cooperation on strategies and responses to invasions. However, limitations to effective collaboration among invasive species networks leading to successful early detection and rapid response to invasive species include: lack of interoperability: data accessibility; funding; and technical expertise. This paper proposes various solutions to these obstacles at different geographic levels and briefly describes success stories from the invasive species information networks mentioned above. Using biological informatics to facilitate global information sharing is especially critical in invasive species science, as research has shown that one of the best indicators of the invasiveness of a species is whether it has been invasive elsewhere. Data must also be shared across disciplines because natural history information (e.g. diet, predators, habitat requirements, etc.) about a species in its native range is vita! for effective prevention, detection, and rapid response to an invasion. Finally, it has been our experience that sharing information, including invasive species dispersal mechanisms and rates, impacts, and prevention and control strategies, enables resource managers and decision-makers to mount a more effective response to biological invasions.
机译:外来入侵物种(IAS)的当前分布的准确分析和未来分布的有效模型都高度依赖于该物种的发生数据和自然历史信息的可用性和可访问性。外来入侵物种监测和检测网络(例如新英格兰的入侵植物地图集和中南部的入侵植物地图集)在美国本地和区域级别生成发生数据,这些数据通过美国国家入侵物种研究所共享科学,即美洲生物多样性信息网络的入侵信息网络(I3N),促进了在整个西半球共享入侵物种发生数据的合作。 I3N和其他国家和地区网络通过全球入侵物种信息网络(GISIN)在全球范围内公开其数据。关于数据共享的国际和跨学科合作加强了关于入侵的战略和对策的合作。但是,导致成功进行早期发现和对入侵物种的快速反应的入侵物种网络之间有效合作的局限性包括:缺乏互操作性:数据可访问性;资金;和技术专长。本文针对不同地理级别的障碍提出了各种解决方案,并简要介绍了上述入侵物种信息网络的成功案例。利用生物信息学促进全球信息共享在入侵物种科学中尤为关键,因为研究表明,物种入侵的最好指标之一是它是否已在其他地方入侵。还必须在各个学科之间共享数据,因为有关其本地范围内物种的自然历史信息(例如饮食,捕食者,栖息地要求等)是维生素!有效地预防,检测和快速响应入侵。最后,我们的经验是,共享信息,包括入侵物种的扩散机制和速率,影响以及预防和控制策略,可使资源管理者和决策者对生物入侵做出更有效的反应。

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