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Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures
Although trait choice is crucial to quantify functional diversity appropriately, the quantitative methods for it are rarely compared and discussed. Meanwhile, very little is known about how trait choice affects ecological conclusions drawn from functional diversity measures. We presented the four me...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473860/ https://www.ncbi.nlm.nih.gov/pubmed/28623286 http://dx.doi.org/10.1038/s41598-017-03812-8 |
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author | Zhu, Linhai Fu, Bojie Zhu, Huoxing Wang, Cong Jiao, Lei Zhou, Ji |
author_facet | Zhu, Linhai Fu, Bojie Zhu, Huoxing Wang, Cong Jiao, Lei Zhou, Ji |
author_sort | Zhu, Linhai |
collection | PubMed |
description | Although trait choice is crucial to quantify functional diversity appropriately, the quantitative methods for it are rarely compared and discussed. Meanwhile, very little is known about how trait choice affects ecological conclusions drawn from functional diversity measures. We presented the four methods of trait selection as alternatives to the ordination axis-based method, which directly identify a subset of key traits to represent the main variation of all the traits. To evaluate their performance, we compared the closeness of association obtained by different methods between species richness and functional diversity indices (FAD, FD, Q, FDis) in the six ecosystems. The evaluation was also benchmarked against the results obtained by calculating the possible indices using all the trait combinations (the complete search method). We found that the trait selection methods were potential alternatives to axis-based method to gain a mechanistic understanding of functional responses and effects of traits, while these methods as well as the axis-based method possibly use mismatched information to interpret the investigated ecosystem properties. Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures. The complete search method should be used to assess the rationale of different trait choice methods and the quality of the calculated indices. |
format | Online Article Text |
id | pubmed-5473860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54738602017-06-21 Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures Zhu, Linhai Fu, Bojie Zhu, Huoxing Wang, Cong Jiao, Lei Zhou, Ji Sci Rep Article Although trait choice is crucial to quantify functional diversity appropriately, the quantitative methods for it are rarely compared and discussed. Meanwhile, very little is known about how trait choice affects ecological conclusions drawn from functional diversity measures. We presented the four methods of trait selection as alternatives to the ordination axis-based method, which directly identify a subset of key traits to represent the main variation of all the traits. To evaluate their performance, we compared the closeness of association obtained by different methods between species richness and functional diversity indices (FAD, FD, Q, FDis) in the six ecosystems. The evaluation was also benchmarked against the results obtained by calculating the possible indices using all the trait combinations (the complete search method). We found that the trait selection methods were potential alternatives to axis-based method to gain a mechanistic understanding of functional responses and effects of traits, while these methods as well as the axis-based method possibly use mismatched information to interpret the investigated ecosystem properties. Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures. The complete search method should be used to assess the rationale of different trait choice methods and the quality of the calculated indices. Nature Publishing Group UK 2017-06-16 /pmc/articles/PMC5473860/ /pubmed/28623286 http://dx.doi.org/10.1038/s41598-017-03812-8 Text en © The Author(s) 2017 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 Zhu, Linhai Fu, Bojie Zhu, Huoxing Wang, Cong Jiao, Lei Zhou, Ji Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title | Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title_full | Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title_fullStr | Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title_full_unstemmed | Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title_short | Trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
title_sort | trait choice profoundly affected the ecological conclusions drawn from functional diversity measures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473860/ https://www.ncbi.nlm.nih.gov/pubmed/28623286 http://dx.doi.org/10.1038/s41598-017-03812-8 |
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