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The China plant trait database version 2
Plant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of...
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/PMC9755148/ https://www.ncbi.nlm.nih.gov/pubmed/36522346 http://dx.doi.org/10.1038/s41597-022-01884-4 |
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author | Wang, Han Harrison, Sandy P. Li, Meng Prentice, I. Colin Qiao, Shengchao Wang, Runxi Xu, Huiying Mengoli, Giulia Peng, Yunke Yang, Yanzheng |
author_facet | Wang, Han Harrison, Sandy P. Li, Meng Prentice, I. Colin Qiao, Shengchao Wang, Runxi Xu, Huiying Mengoli, Giulia Peng, Yunke Yang, Yanzheng |
author_sort | Wang, Han |
collection | PubMed |
description | Plant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of the China Plant Trait Database, which contains information on morphometric, physical, chemical, photosynthetic and hydraulic traits from 1529 unique species in 140 sites spanning a diversity of vegetation types. Version 2 has five improvements compared to the previous version: (1) new data from a 4-km elevation transect on the edge of Tibetan Plateau, including alpine vegetation types not sampled previously; (2) inclusion of traits related to hydraulic processes, including specific sapwood conductance, the area ratio of sapwood to leaf, wood density and turgor loss point; (3) inclusion of information on soil properties to complement the existing data on climate and vegetation (4) assessments and flagging the reliability of individual trait measurements; and (5) inclusion of standardized templates for systematical field sampling and measurements. |
format | Online Article Text |
id | pubmed-9755148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97551482022-12-17 The China plant trait database version 2 Wang, Han Harrison, Sandy P. Li, Meng Prentice, I. Colin Qiao, Shengchao Wang, Runxi Xu, Huiying Mengoli, Giulia Peng, Yunke Yang, Yanzheng Sci Data Data Descriptor Plant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of the China Plant Trait Database, which contains information on morphometric, physical, chemical, photosynthetic and hydraulic traits from 1529 unique species in 140 sites spanning a diversity of vegetation types. Version 2 has five improvements compared to the previous version: (1) new data from a 4-km elevation transect on the edge of Tibetan Plateau, including alpine vegetation types not sampled previously; (2) inclusion of traits related to hydraulic processes, including specific sapwood conductance, the area ratio of sapwood to leaf, wood density and turgor loss point; (3) inclusion of information on soil properties to complement the existing data on climate and vegetation (4) assessments and flagging the reliability of individual trait measurements; and (5) inclusion of standardized templates for systematical field sampling and measurements. Nature Publishing Group UK 2022-12-15 /pmc/articles/PMC9755148/ /pubmed/36522346 http://dx.doi.org/10.1038/s41597-022-01884-4 Text en © The Author(s) 2022 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/) . |
spellingShingle | Data Descriptor Wang, Han Harrison, Sandy P. Li, Meng Prentice, I. Colin Qiao, Shengchao Wang, Runxi Xu, Huiying Mengoli, Giulia Peng, Yunke Yang, Yanzheng The China plant trait database version 2 |
title | The China plant trait database version 2 |
title_full | The China plant trait database version 2 |
title_fullStr | The China plant trait database version 2 |
title_full_unstemmed | The China plant trait database version 2 |
title_short | The China plant trait database version 2 |
title_sort | china plant trait database version 2 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755148/ https://www.ncbi.nlm.nih.gov/pubmed/36522346 http://dx.doi.org/10.1038/s41597-022-01884-4 |
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