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

Peder Engelstad, Catherine S Jarnevich, Terri Hogan, Helen R Sofaer, Ian S Pearse, Jennifer L Sieracki, Neil Frakes, Julia Sullivan, Nicholas E Young, Janet S Prevéy, Pairsa Belamaric and Jillian LaRoe

PLOS ONE, 2022, vol. 17, issue 2, 1-15

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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0263056

DOI: 10.1371/journal.pone.0263056

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