A framework to integrate innovations in invasion science for proactive management

Charles B. van Rees, Brian K. Hand, Sean C. Carter, Chuck Bargeron, Timothy J. Cline, Wesley Daniel, Jason A. Ferrante, Keith Gaddis, Margaret E. Hunter, Catherine S. Jarnevich, Melodie A. McGeoch, Jeffrey T. Morisette, Matthew E. Neilson, Helen E. Roy, Mary Ann Rozance, Adam Sepulveda, Rebekah D. Wallace, Diane Whited, Taylor Wilcox, John S. KimballGordon Luikart

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1712-1735
Number of pages24
JournalBiological Reviews
Volume97
Issue number4
DOIs
StatePublished - Aug 2022

Funding

This research was funded in part by NASA award #80NSSC19K0185 to G.L. and B.K.H. and a USGS Northwest Climate Adaptation Science Center Fellowship G17AC000218 to C.B.v.R., G.L. and B.K.H. were also supported by an NSF-DoB award #1639014. H.E.R. is supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. H.E.R. also acknowledges COST Action CA17122 – Alien CSI supported by COST (European Cooperation in Science and Technology) www.cost.eu. M.A.M. acknowledges support from the Australian Research Council (DP200101680). The views expressed in this paper do not necessarily reflect those of NASA. The findings and conclusions in this paper are those of the authors and should not be construed to represent any official USDA determination or policy. This research was supported in part by the U.S. Department of Agriculture, Forest Service. We thank Daniel Isaak, Katy Klymus, Deborah Stoliker, John Welch, and two anonymous reviewers for valuable comments and suggestions. We thank Kayla Fratt (K9 Conservationists) for helpful discussion on the current state of conservation detection dog work in invasive species management. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This research was funded in part by NASA award #80NSSC19K0185 to G.L. and B.K.H. and a USGS Northwest Climate Adaptation Science Center Fellowship G17AC000218 to C.B.v.R., G.L. and B.K.H. were also supported by an NSF‐DoB award #1639014. H.E.R. is supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK‐SCAPE programme delivering National Capability. H.E.R. also acknowledges COST Action CA17122 – Alien CSI supported by COST (European Cooperation in Science and Technology) www.cost.eu . M.A.M. acknowledges support from the Australian Research Council (DP200101680). The views expressed in this paper do not necessarily reflect those of NASA. The findings and conclusions in this paper are those of the authors and should not be construed to represent any official USDA determination or policy. This research was supported in part by the U.S. Department of Agriculture, Forest Service. We thank Daniel Isaak, Katy Klymus, Deborah Stoliker, John Welch, and two anonymous reviewers for valuable comments and suggestions. We thank Kayla Fratt (K9 Conservationists) for helpful discussion on the current state of conservation detection dog work in invasive species management. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

FundersFunder number
National Aeronautics and Space Administration80NSSC19K0185, 1639014, G17AC000218
U.S. Forest Service-Retired
Natural Environment Research CouncilNE/R016429/1
Australian Research CouncilDP200101680

    Keywords

    • IAS
    • big data analytics
    • bioinformatics
    • environmental DNA
    • genetics
    • infectious disease ecology
    • invasive species
    • nuisance species
    • remote sensing
    • species distribution modeling

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