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Plant traits database for climate change adaptation and mitigation in Northwest Portugal
The database presented in this data article is related to the article “Adaptive planting design and management framework for urban climate change adaptation and mitigation” [1]. It includes a list of 287 plant species presently occurring in Porto, Portugal, more precisely in urban green spaces with...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065706/ https://www.ncbi.nlm.nih.gov/pubmed/35515990 http://dx.doi.org/10.1016/j.dib.2022.108193 |
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author | Teixeira, Catarina Patoilo Fernandes, Cláudia Oliveira Ahern, Jack Farinha-Marques, Paulo |
author_facet | Teixeira, Catarina Patoilo Fernandes, Cláudia Oliveira Ahern, Jack Farinha-Marques, Paulo |
author_sort | Teixeira, Catarina Patoilo |
collection | PubMed |
description | The database presented in this data article is related to the article “Adaptive planting design and management framework for urban climate change adaptation and mitigation” [1]. It includes a list of 287 plant species presently occurring in Porto, Portugal, more precisely in urban green spaces with high urban ecological novelty levels. The plant species in this list were classified and organized according to several traits with a particular focus on plant species’ adaptation, mitigation, and ornamental characteristics. Data collection resorted to articles, books, and various open access and online datasets. Data were organized in an Excel file that organizes information on more than 50 plant species traits/variables. |
format | Online Article Text |
id | pubmed-9065706 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90657062022-05-04 Plant traits database for climate change adaptation and mitigation in Northwest Portugal Teixeira, Catarina Patoilo Fernandes, Cláudia Oliveira Ahern, Jack Farinha-Marques, Paulo Data Brief Data Article The database presented in this data article is related to the article “Adaptive planting design and management framework for urban climate change adaptation and mitigation” [1]. It includes a list of 287 plant species presently occurring in Porto, Portugal, more precisely in urban green spaces with high urban ecological novelty levels. The plant species in this list were classified and organized according to several traits with a particular focus on plant species’ adaptation, mitigation, and ornamental characteristics. Data collection resorted to articles, books, and various open access and online datasets. Data were organized in an Excel file that organizes information on more than 50 plant species traits/variables. Elsevier 2022-04-20 /pmc/articles/PMC9065706/ /pubmed/35515990 http://dx.doi.org/10.1016/j.dib.2022.108193 Text en © 2022 Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Teixeira, Catarina Patoilo Fernandes, Cláudia Oliveira Ahern, Jack Farinha-Marques, Paulo Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title | Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title_full | Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title_fullStr | Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title_full_unstemmed | Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title_short | Plant traits database for climate change adaptation and mitigation in Northwest Portugal |
title_sort | plant traits database for climate change adaptation and mitigation in northwest portugal |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065706/ https://www.ncbi.nlm.nih.gov/pubmed/35515990 http://dx.doi.org/10.1016/j.dib.2022.108193 |
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