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EU-Trees4F, a dataset on the future distribution of European tree species
We present “EU-Trees4F”, a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scena...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813948/ https://www.ncbi.nlm.nih.gov/pubmed/35115529 http://dx.doi.org/10.1038/s41597-022-01128-5 |
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author | Mauri, Achille Girardello, Marco Strona, Giovanni Beck, Pieter S. A. Forzieri, Giovanni Caudullo, Giovanni Manca, Federica Cescatti, Alessandro |
author_facet | Mauri, Achille Girardello, Marco Strona, Giovanni Beck, Pieter S. A. Forzieri, Giovanni Caudullo, Giovanni Manca, Federica Cescatti, Alessandro |
author_sort | Mauri, Achille |
collection | PubMed |
description | We present “EU-Trees4F”, a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. “EU-Trees4F”, can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking. |
format | Online Article Text |
id | pubmed-8813948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88139482022-02-10 EU-Trees4F, a dataset on the future distribution of European tree species Mauri, Achille Girardello, Marco Strona, Giovanni Beck, Pieter S. A. Forzieri, Giovanni Caudullo, Giovanni Manca, Federica Cescatti, Alessandro Sci Data Data Descriptor We present “EU-Trees4F”, a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. “EU-Trees4F”, can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking. Nature Publishing Group UK 2022-02-03 /pmc/articles/PMC8813948/ /pubmed/35115529 http://dx.doi.org/10.1038/s41597-022-01128-5 Text en © The Author(s) 2022, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Mauri, Achille Girardello, Marco Strona, Giovanni Beck, Pieter S. A. Forzieri, Giovanni Caudullo, Giovanni Manca, Federica Cescatti, Alessandro EU-Trees4F, a dataset on the future distribution of European tree species |
title | EU-Trees4F, a dataset on the future distribution of European tree species |
title_full | EU-Trees4F, a dataset on the future distribution of European tree species |
title_fullStr | EU-Trees4F, a dataset on the future distribution of European tree species |
title_full_unstemmed | EU-Trees4F, a dataset on the future distribution of European tree species |
title_short | EU-Trees4F, a dataset on the future distribution of European tree species |
title_sort | eu-trees4f, a dataset on the future distribution of european tree species |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813948/ https://www.ncbi.nlm.nih.gov/pubmed/35115529 http://dx.doi.org/10.1038/s41597-022-01128-5 |
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