INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States

PLoS One. 2022 Feb 8;17(2):e0263056. doi: 10.1371/journal.pone.0263056. eCollection 2022.

Abstract

Narrowing the communication and knowledge gap between producers and users of scientific data is a longstanding problem in ecological conservation and land management. Decision support tools (DSTs), including websites or interactive web applications, provide platforms that can help bridge this gap. DSTs can most effectively disseminate and translate research results when producers and users collaboratively and iteratively design content and features. One data resource seldom incorporated into DSTs are species distribution models (SDMs), which can produce spatial predictions of habitat suitability. Outputs from SDMs can inform management decisions, but their complexity and inaccessibility can limit their use by resource managers or policy makers. To overcome these limitations, we present the Invasive Species Habitat Tool (INHABIT), a novel, web-based DST built with R Shiny to display spatial predictions and tabular summaries of habitat suitability from SDMs for invasive plants across the contiguous United States. INHABIT provides actionable science to support the prevention and management of invasive species. Two case studies demonstrate the important role of end user feedback in confirming INHABIT's credibility, utility, and relevance.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Conservation of Natural Resources / methods*
  • Decision Making
  • Decision Support Techniques
  • Ecosystem
  • Internet
  • Introduced Species / statistics & numerical data*
  • Plant Dispersal / physiology*
  • Plants / classification
  • Software
  • United States

Grants and funding

Funding for this project was provided by the U.S. Geological Survey Invasive Species Program (https://www.usgs.gov/ecosystems/invasive-species-program), the U.S. Geological Survey Core Science Systems (CSS): Science Analytics and Synthesis (https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/about), and the U.S. Fish and Wildlife Service (http://www.fws.gov). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.