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Dataset of pollination traits in Fabales

The data presented in this paper is supporting the research article “Reconstructing an historical pollination syndrome: keel flowers” (Aygören Uluer et al., 2022). We present a dataset containing information on number of species, geographic distribution, floral type (keeled or not), presence or abse...

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Detalles Bibliográficos
Autores principales: Aygören Uluer, Deniz, Forest, Félix, Hawkins, Julie A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352444/
https://www.ncbi.nlm.nih.gov/pubmed/35935709
http://dx.doi.org/10.1016/j.dib.2022.108480
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author Aygören Uluer, Deniz
Forest, Félix
Hawkins, Julie A.
author_facet Aygören Uluer, Deniz
Forest, Félix
Hawkins, Julie A.
author_sort Aygören Uluer, Deniz
collection PubMed
description The data presented in this paper is supporting the research article “Reconstructing an historical pollination syndrome: keel flowers” (Aygören Uluer et al., 2022). We present a dataset containing information on number of species, geographic distribution, floral type (keeled or not), presence or absence of fused petals, floral symmetry, presence or absence of a pentamerous corolla (petals+petaloid sepals in Polygalaceae), androecium type, presence or absence of enclosed reproductive organs, presence or absence of three distinct petal types (petals+ petaloid sepals in Polygalaceae), flower size, corolla size (i.e., in open flower) and/or filament size (i.e., entire filament size particularly in subfamily Caesalpinioideae), flower colour, UV reflectance, habit, height, inflorescence type and inflorescence size for 758 Fabales genera. The information was obtained from hundreds of appropriate, previously published sources. This the largest morphological dataset constructed for Fabales to date, and the data presented in this article can be used for morphology, biogeography, ancestral state, ancestral area analyses of any Fabales clades.
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spelling pubmed-93524442022-08-05 Dataset of pollination traits in Fabales Aygören Uluer, Deniz Forest, Félix Hawkins, Julie A. Data Brief Data Article The data presented in this paper is supporting the research article “Reconstructing an historical pollination syndrome: keel flowers” (Aygören Uluer et al., 2022). We present a dataset containing information on number of species, geographic distribution, floral type (keeled or not), presence or absence of fused petals, floral symmetry, presence or absence of a pentamerous corolla (petals+petaloid sepals in Polygalaceae), androecium type, presence or absence of enclosed reproductive organs, presence or absence of three distinct petal types (petals+ petaloid sepals in Polygalaceae), flower size, corolla size (i.e., in open flower) and/or filament size (i.e., entire filament size particularly in subfamily Caesalpinioideae), flower colour, UV reflectance, habit, height, inflorescence type and inflorescence size for 758 Fabales genera. The information was obtained from hundreds of appropriate, previously published sources. This the largest morphological dataset constructed for Fabales to date, and the data presented in this article can be used for morphology, biogeography, ancestral state, ancestral area analyses of any Fabales clades. Elsevier 2022-07-22 /pmc/articles/PMC9352444/ /pubmed/35935709 http://dx.doi.org/10.1016/j.dib.2022.108480 Text en © 2022 The Authors. 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
Aygören Uluer, Deniz
Forest, Félix
Hawkins, Julie A.
Dataset of pollination traits in Fabales
title Dataset of pollination traits in Fabales
title_full Dataset of pollination traits in Fabales
title_fullStr Dataset of pollination traits in Fabales
title_full_unstemmed Dataset of pollination traits in Fabales
title_short Dataset of pollination traits in Fabales
title_sort dataset of pollination traits in fabales
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352444/
https://www.ncbi.nlm.nih.gov/pubmed/35935709
http://dx.doi.org/10.1016/j.dib.2022.108480
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