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Biological Invasions

, Volume 17, Issue 10, pp 2831–2850 | Cite as

Adaptive invasive species distribution models: a framework for modeling incipient invasions

  • Daniel R. Uden
  • Craig R. Allen
  • David G. Angeler
  • Lucía Corral
  • Kent A. Fricke
Original Paper

Abstract

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Keywords

Adaptive inference Biological invasions Management Niche Scale Uncertainty 

Notes

Acknowledgments

The authors would like to thank Kody Unstad, two anonymous reviewers, and members of the Craig Allen graduate student lab for constructive comments and criticisms of this concept and manuscript. The Nebraska Cooperative Fish and Wildlife Research Unit is jointly supported by a cooperative agreement between the U.S. Geological Survey, the Nebraska Game and Parks Commission, the University of Nebraska–Lincoln, the U.S. Fish and Wildlife Service and the Wildlife Management Institute. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Financial support was provided by the August T. Larsson Foundation (NJ Faculty, Swedish University of Agricultural Sciences). This research was supported in part by an NSF IGERT Grant, DGE-0903469. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Daniel R. Uden
    • 1
  • Craig R. Allen
    • 2
  • David G. Angeler
    • 3
  • Lucía Corral
    • 1
  • Kent A. Fricke
    • 1
  1. 1.Nebraska Cooperative Fish and Wildlife Research Unit, School of Natural ResourcesUniversity of Nebraska–LincolnLincolnUSA
  2. 2.U.S. Geological Survey, Nebraska Cooperative Fish and Wildlife Research Unit, School of Natural ResourcesUniversity of Nebraska–LincolnLincolnUSA
  3. 3.Department of Aquatic Sciences and AssessmentSwedish University of Agricultural SciencesUppsalaSweden

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