AIS explorer: Prioritization for watercraft inspections-A decision-support tool for aquatic invasive species management

Amy C. Kinsley, Robert G. Haight, Nicholas Snellgrove, Petra Muellner, Ulrich Muellner, Meg Duhr, Nicholas B.D. Phelps

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Invasions of aquatic invasive species have caused significant economic and ecological damage to global aquatic ecosystems. Once an invasive population has established in a new habitat, eradication can be financially and logistically impossible, motivating management strategies to rely heavily upon prevention measures to reduce the introduction and spread. To be productive, on-the-ground management of aquatic invasive species requires effective decision-making surrounding the allocation of limited resources. Watercraft inspections play an important role in managing aquatic invasive species by preventing the overland transport of invasive species between waterbodies and providing education to boaters. In this study, we developed and tested an interactive web-based decision-support tool, AIS Explorer: Prioritization for Watercraft Inspections, to guide AIS managers in developing efficient watercraft inspection plans. The decision-support tool is informed by a network-based algorithm that maximized the number of inspected watercraft that move from AIS infested to uninfested lakes within and between counties in Minnesota, USA. It was iteratively built with stakeholder feedback, including consultations with county managers, beta-testing of the web-based application, and workshops to educate and train end-users. The co-development and implementation of data-driven decision support tools demonstrate how interdisciplinary methods can be used to connect science and management to support decision-making. The AIS Explorer: Prioritization for Watercraft Inspections application makes optimized research outputs accessible in multiple dynamic forms that maintain pace with discovery of new infestations and local needs. In addition, the decision support tool has supported improved and closer communication between AIS managers and researchers on this topic.

Original languageEnglish (US)
Article number115037
JournalJournal of Environmental Management
Volume314
DOIs
StatePublished - Jul 15 2022

Bibliographical note

Funding Information:
Here we developed and implemented a decision support tool informed by a network-based optimization algorithm that maximizes the number of inspections that occur on watercraft that move from AIS infested to uninfested lakes. We tested the algorithm in three counties. Here we present the results of one, Crow Wing County, as a case study, comparing the network-based optimization algorithm to a traditional integer linear optimization approach and AIS managers' decision processes. The network-based optimization algorithm is available through the Prioritization for Watercraft Inspections application accessible on the AIS Explorer dashboard (http://www.aisexplorer.umn.edu). This paper discusses the development and testing the application and end-user training that provides Minnesota's AIS managers with a first-of-its-kind support tool for decision-making. Our quantitative approach, application development, and stakeholder engagement methods apply to other geographic locations, invasive species, and pathways in which surveillance is conducted.There are two key features of the AIS Explorer: Prioritization for Watercraft Inspections application that make it a unique and flexible tool, able to support operational tasks in the dynamic context of AIS infestations. The first is that the application automatically updates on an as-needed basis, incorporating any new infestations listed on the MN DNR Infested Waters list ( Minnesota Department of Natural Resources, 2019a,b,c). This is important because new infestations may change a county's watercraft inspection location plan if the infestation occurs within the county or includes risky movements from an infested lake outside the county to lakes within the county. The second critical feature is the customizability of the networks. By being able to remove or add to the network, end-users can create a completely customized list of lakes. This may be of importance when AIS managers are not responsible for inspections at a particular lake or share responsibility with other agencies/organizations.We would like to thank all of the stakeholders that participated in the development of the application, including Jacob Frie and Nicole Erickson (Crow Wing County), Ariana Richardson (Meeker County), Justin Townsend (Ramsey County), Cole Loewen (Stearns County), Justine Dauphinais (Coon Creek Watershed District), Dave Rush (Douglas County), Kevin Farnum (MN Coalition of Associations/Lake Koronis Association), Jeff Forrester (Minnesota Lakes and Rivers Advocates), James Johnson (DNR Statewide Aquatic Invasive Species Advisory Committee), Daniel Larkin (UMN), Gretchen Hansen (UMN), Jeff Lovgren (Vermillion Association), Adam Doll (MN DNR), Heidi Wolf (MN DNR), Jan Shaw-Wolff (MN DNR), and Kelly Pennington (MN DNR). This research was supported by the Environment and Natural Resources Trust Fund as recommended by the Legislative Citizen Commission of Minnesota Resources and the Minnesota Aquatic Invasive Species Research Center, and the State of Minnesota.

Funding Information:
We would like to thank all of the stakeholders that participated in the development of the application, including Jacob Frie and Nicole Erickson (Crow Wing County), Ariana Richardson (Meeker County), Justin Townsend (Ramsey County), Cole Loewen (Stearns County), Justine Dauphinais (Coon Creek Watershed District), Dave Rush (Douglas County), Kevin Farnum (MN Coalition of Associations/Lake Koronis Association), Jeff Forrester (Minnesota Lakes and Rivers Advocates), James Johnson (DNR Statewide Aquatic Invasive Species Advisory Committee), Daniel Larkin (UMN), Gretchen Hansen (UMN), Jeff Lovgren (Vermillion Association), Adam Doll (MN DNR), Heidi Wolf (MN DNR), Jan Shaw-Wolff (MN DNR), and Kelly Pennington (MN DNR). This research was supported by the Environment and Natural Resources Trust Fund as recommended by the Legislative Citizen Commission of Minnesota Resources and the Minnesota Aquatic Invasive Species Research Center, and the State of Minnesota.

Publisher Copyright:
© 2022 The Authors

Keywords

  • Aquatic invasive species
  • Aquatic resource management
  • Decision-support tool
  • Invasive species management
  • Network algorithm
  • Resource allocation
  • Stakeholder engagement

PubMed: MeSH publication types

  • Journal Article

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