Suppr超能文献

从两个世纪的外来物种发现中揭示的昆虫定殖风险隐藏模式。

Hidden patterns of insect establishment risk revealed from two centuries of alien species discoveries.

作者信息

MacLachlan Matthew J, Liebhold Andrew M, Yamanaka Takehiko, Springborn Michael R

机构信息

U.S. Department of Agriculture Economic Research Service, Washington, DC 20024, USA.

U.S. Department of Agriculture Forest Service, Northern Research Station, Morgantown, WV 26505, USA.

出版信息

Sci Adv. 2021 Oct 29;7(44):eabj1012. doi: 10.1126/sciadv.abj1012. Epub 2021 Oct 27.

Abstract

Understanding the socioeconomic drivers of biological invasion informs policy development for curtailing future invasions. While early 20th-century plant trade expansions preceded increased establishments of plant pests in Northern America, increased establishments did not follow accelerating imports later that century. To explore this puzzle, we estimate the historical establishment of plant-feeding Hemiptera in Northern America as a function of historical U.S. imports of live plants from seven world regions. Delays between establishment and discovery are modeled using a previously unused proxy for dynamic discovery effort. By recovering the timing of pest arrivals from their historical discoveries, we disentangle the joint establishment-discovery process. We estimate long delays to discovery, which are partially attributable to the low detectability of less economically important insect species. We estimate that many introduced species remain undiscovered, ranging from around one-fifth for Eurasian regions to two-fifths for Central and South America.

摘要

了解生物入侵的社会经济驱动因素有助于制定减少未来入侵的政策。虽然20世纪初植物贸易扩张先于北美植物害虫定殖数量增加,但该世纪后期进口加速后,定殖数量并未随之增加。为探究这一谜题,我们估计了北美以植物为食的半翅目昆虫的历史定殖数量,将其作为美国历史上从七个世界地区进口活植物数量的函数。定殖与发现之间的延迟通过使用一个此前未使用过的动态发现努力代理变量进行建模。通过从历史发现中推断害虫到达的时间,我们解开了定殖与发现的联合过程。我们估计发现时间存在较长延迟,部分原因是经济重要性较低的昆虫物种难以被发现。我们估计许多引入物种仍未被发现,范围从欧亚地区的约五分之一到中南美的五分之二。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3117/8550319/058333002586/sciadv.abj1012-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验