A framework to integrate innovations in invasion science for proactive management

van Rees, Charles B.; Hand, Brian K.; Carter, Sean C.; Bargeron, Chuck; Cline, Timothy J.; Daniel, Wesley; Ferrante, Jason A.; Gaddis, Keith; Hunter, Margaret E.; Jarnevich, Catherine S.; McGeoch, Melodie A.; Morisette, Jeffrey T.; Neilson, Matthew E.; Roy, Helen E. ORCID: https://orcid.org/0000-0001-6050-679X; Rozance, Mary Ann; Sepulveda, Adam; Wallace, Rebekah D.; Whited, Diane; Wilcox, Taylor; Kimball, John S.; Luikart, Gordon. 2022 A framework to integrate innovations in invasion science for proactive management. Biological Reviews, 97 (4). 1712-1735. https://doi.org/10.1111/brv.12859

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Abstract/Summary

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/brv.12859
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	1464-7931
Additional Keywords:	IAS, invasive species, nuisance species, remote sensing, bioinformatics, infectious disease ecology, big data analytics, species distribution modeling, environmental DNA, genetics
NORA Subject Terms:	Ecology and Environment
Date made live:	05 Jul 2022 16:16 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/532852

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