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

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. D...

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Autores principales: Engelstad, Peder, Jarnevich, Catherine S., Hogan, Terri, Sofaer, Helen R., Pearse, Ian S., Sieracki, Jennifer L., Frakes, Neil, Sullivan, Julia, Young, Nicholas E., Prevéy, Janet S., Belamaric, Pairsa, LaRoe, Jillian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824347/
https://www.ncbi.nlm.nih.gov/pubmed/35134065
http://dx.doi.org/10.1371/journal.pone.0263056
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author Engelstad, Peder
Jarnevich, Catherine S.
Hogan, Terri
Sofaer, Helen R.
Pearse, Ian S.
Sieracki, Jennifer L.
Frakes, Neil
Sullivan, Julia
Young, Nicholas E.
Prevéy, Janet S.
Belamaric, Pairsa
LaRoe, Jillian
author_facet Engelstad, Peder
Jarnevich, Catherine S.
Hogan, Terri
Sofaer, Helen R.
Pearse, Ian S.
Sieracki, Jennifer L.
Frakes, Neil
Sullivan, Julia
Young, Nicholas E.
Prevéy, Janet S.
Belamaric, Pairsa
LaRoe, Jillian
author_sort Engelstad, Peder
collection PubMed
description 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.
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spelling pubmed-88243472022-02-09 INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States Engelstad, Peder Jarnevich, Catherine S. Hogan, Terri Sofaer, Helen R. Pearse, Ian S. Sieracki, Jennifer L. Frakes, Neil Sullivan, Julia Young, Nicholas E. Prevéy, Janet S. Belamaric, Pairsa LaRoe, Jillian PLoS One Research Article 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. Public Library of Science 2022-02-08 /pmc/articles/PMC8824347/ /pubmed/35134065 http://dx.doi.org/10.1371/journal.pone.0263056 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Engelstad, Peder
Jarnevich, Catherine S.
Hogan, Terri
Sofaer, Helen R.
Pearse, Ian S.
Sieracki, Jennifer L.
Frakes, Neil
Sullivan, Julia
Young, Nicholas E.
Prevéy, Janet S.
Belamaric, Pairsa
LaRoe, Jillian
INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title_full INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title_fullStr INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title_full_unstemmed INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title_short INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States
title_sort inhabit: a web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous united states
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824347/
https://www.ncbi.nlm.nih.gov/pubmed/35134065
http://dx.doi.org/10.1371/journal.pone.0263056
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