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Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data

Invasive plants are an ongoing subject of interest in North American forests, owing to their impacts on forest structure and regeneration, biodiversity, and ecosystem services. An important component of studying and managing forest invaders involves knowing where the species are, or could be, geogra...

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Autores principales: Reinhardt, Jason R., Russell, Matthew B., Senay, Senait, Lazarus, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7392769/
https://www.ncbi.nlm.nih.gov/pubmed/32728063
http://dx.doi.org/10.1038/s41598-020-69539-1
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author Reinhardt, Jason R.
Russell, Matthew B.
Senay, Senait
Lazarus, William
author_facet Reinhardt, Jason R.
Russell, Matthew B.
Senay, Senait
Lazarus, William
author_sort Reinhardt, Jason R.
collection PubMed
description Invasive plants are an ongoing subject of interest in North American forests, owing to their impacts on forest structure and regeneration, biodiversity, and ecosystem services. An important component of studying and managing forest invaders involves knowing where the species are, or could be, geographically located. Temporal and environmental context, in conjunction with spatially-explicit species occurrence information, can be used to address this need. Here, we predict the potential current and future distributions of four forest plant invaders in Minnesota: common buckthorn (Rhamnus cathartica), glossy buckthorn (Frangula alnus), garlic mustard (Alliaria petiolata), and multiflora rose (Rosa multiflora). We assessed the impact of two different climate change scenarios (IPCC RCP 6.0 and 8.5) at two future timepoints (2050s and 2070s) as well as the importance of occurrence data sources on the potential distribution of each species. Our results suggest that climate change scenarios considered here could result in a potential loss of suitable habitat in Minnesota for both buckthorn species and a potential gain for R. multiflora and A. petiolata. Differences in predictions as a result of input occurrence data source were most pronounced in future climate projections.
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spelling pubmed-73927692020-07-31 Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data Reinhardt, Jason R. Russell, Matthew B. Senay, Senait Lazarus, William Sci Rep Article Invasive plants are an ongoing subject of interest in North American forests, owing to their impacts on forest structure and regeneration, biodiversity, and ecosystem services. An important component of studying and managing forest invaders involves knowing where the species are, or could be, geographically located. Temporal and environmental context, in conjunction with spatially-explicit species occurrence information, can be used to address this need. Here, we predict the potential current and future distributions of four forest plant invaders in Minnesota: common buckthorn (Rhamnus cathartica), glossy buckthorn (Frangula alnus), garlic mustard (Alliaria petiolata), and multiflora rose (Rosa multiflora). We assessed the impact of two different climate change scenarios (IPCC RCP 6.0 and 8.5) at two future timepoints (2050s and 2070s) as well as the importance of occurrence data sources on the potential distribution of each species. Our results suggest that climate change scenarios considered here could result in a potential loss of suitable habitat in Minnesota for both buckthorn species and a potential gain for R. multiflora and A. petiolata. Differences in predictions as a result of input occurrence data source were most pronounced in future climate projections. Nature Publishing Group UK 2020-07-29 /pmc/articles/PMC7392769/ /pubmed/32728063 http://dx.doi.org/10.1038/s41598-020-69539-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Reinhardt, Jason R.
Russell, Matthew B.
Senay, Senait
Lazarus, William
Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title_full Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title_fullStr Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title_full_unstemmed Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title_short Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data
title_sort assessing the current and potential future distribution of four invasive forest plants in minnesota, u.s.a., using mixed sources of data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7392769/
https://www.ncbi.nlm.nih.gov/pubmed/32728063
http://dx.doi.org/10.1038/s41598-020-69539-1
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