Risk Analysis and Bioeconomics of Invasive Species to Inform Policy and Management


David M. Lodge, Cornell University
Paul W. Simonin, University of Notre Dame
Stanley W. Burgiel, National Invasive Species Council
Reuben P. Keller, Loyola University Chicago
Jonathan M. Bossenbroek, University of Toledo
Christopher L. Jerde, University of Nevada
Andrew M. Kramer, University of Georgia
Edward S. Rutherford, Great Lakes Environmental Research Laboratory
Matthew A. Barnes, Texas Tech University
Marion E. Wittmann, University of Nevada
W. Lindsay Chadderton, Notre Dame Environmental Change Initiative
Jenny L. Apriesnig, Colorado State University
Dmitry Beletsky, University of Michigan
Roger M. Cooke, Resources for the Future
John M. Drake, University of Georgia
Scott P. Egan, Rice University
David C. Finnoff, University of Wyoming
Crysta A. Gantz, University of Notre Dame
Erin K. Grey, Governors State University
Michael H. Hoff, Fish and Aquatic Conservation, US Fish and Wildlife Service
Jennifer G. Howeth, University of Alabama
Richard A. Jensen, University of Notre Dame
Eric R. Larson, University of Illinois
Nicholas E. Mandrak, University of Toronto
Doran M. Mason, National Oceanic and Atmospheric Administration
Felix A. Martinez, National Oceanic and Atmospheric Administration
Tammy J. Newcomb, Michigan Department of Natural Resources
John D. Rothlisberger, US Forest Service
Andrew J. Tucker, Notre Dame Environmental Change Initiative
Travis W. Warziniack, Rocky Mountain Research Station
Hongyan Zhang, Cooperative Institute for Limnology and Ecosystems Research

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forecasting, prevention, early detection, control, eradication, dispersal, surveillance, species distribution modeling, damage

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Risk analysis of species invasions links biology and economics, is increasingly mandated by international and national policies, and enables improved management of invasive species. Biological invasions proceed through a series of transition probabilities (i.e., introduction, establishment, spread, and impact), and each of these presents opportunities for management. Recent research advances have improved estimates of probability and associated uncertainty. Improvements have come from species-specific trait-based risk assessments (of estimates of introduction, establishment, spread, and impact probabilities, especially from pathways of commerce in living organisms), spatially explicit dispersal models (introduction and spread, especially from transportation pathways), and species distribution models (establishment, spread, and impact). Results of these forecasting models combined with improved and cheaper surveillance technologies and practices [e.g., environmental DNA (eDNA), drones, citizen science] enable more efficient management by focusing surveillance, prevention, eradication, and control efforts on the highest-risk species and locations. Bioeconomic models account for the interacting dynamics within and between ecological and economic systems, and allow decision makers to better understand the financial consequences of alternative management strategies. In general, recent research advances demonstrate that prevention is the policy with the greatest long-term net benefit.

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Citation / Publisher Attribution

Annual Review of Environment and Resources, v. 41, p. 453-488