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Dataset of leaf inclination angles for 71 different Eucalyptus species

The leaf inclination angle distribution is an important parameter in models useful for understanding forest canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many of these models to variability in leaf inc...

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Detalles Bibliográficos
Autores principales: Pisek, Jan, Adamson, Kairi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569295/
https://www.ncbi.nlm.nih.gov/pubmed/33102658
http://dx.doi.org/10.1016/j.dib.2020.106391
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author Pisek, Jan
Adamson, Kairi
author_facet Pisek, Jan
Adamson, Kairi
author_sort Pisek, Jan
collection PubMed
description The leaf inclination angle distribution is an important parameter in models useful for understanding forest canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many of these models to variability in leaf inclination angle distribution, relatively few measurements have been reported for different tree species in literature and databases such as TRY, and various assumptions about leaf inclination angle distribution are often made by modellers. Here we provide a dataset of leaf inclination angles for 71 different Australia-native Eucalyptus species measured in 13 botanical gardens around the world. Leaf inclination angles were measured using a leveled digital camera approach. The leaf angle measurements were used to estimate corresponding Beta distribution parameters and to assign the appropriate classic type of leaf inclination angle distribution. The data can be used to parameterize leaf angle distributions in e.g., physically-based reflectance models, land surface models, and regional carbon cycle models.
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spelling pubmed-75692952020-10-22 Dataset of leaf inclination angles for 71 different Eucalyptus species Pisek, Jan Adamson, Kairi Data Brief Data Article The leaf inclination angle distribution is an important parameter in models useful for understanding forest canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many of these models to variability in leaf inclination angle distribution, relatively few measurements have been reported for different tree species in literature and databases such as TRY, and various assumptions about leaf inclination angle distribution are often made by modellers. Here we provide a dataset of leaf inclination angles for 71 different Australia-native Eucalyptus species measured in 13 botanical gardens around the world. Leaf inclination angles were measured using a leveled digital camera approach. The leaf angle measurements were used to estimate corresponding Beta distribution parameters and to assign the appropriate classic type of leaf inclination angle distribution. The data can be used to parameterize leaf angle distributions in e.g., physically-based reflectance models, land surface models, and regional carbon cycle models. Elsevier 2020-10-09 /pmc/articles/PMC7569295/ /pubmed/33102658 http://dx.doi.org/10.1016/j.dib.2020.106391 Text en © 2020 The Authors http://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
Pisek, Jan
Adamson, Kairi
Dataset of leaf inclination angles for 71 different Eucalyptus species
title Dataset of leaf inclination angles for 71 different Eucalyptus species
title_full Dataset of leaf inclination angles for 71 different Eucalyptus species
title_fullStr Dataset of leaf inclination angles for 71 different Eucalyptus species
title_full_unstemmed Dataset of leaf inclination angles for 71 different Eucalyptus species
title_short Dataset of leaf inclination angles for 71 different Eucalyptus species
title_sort dataset of leaf inclination angles for 71 different eucalyptus species
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569295/
https://www.ncbi.nlm.nih.gov/pubmed/33102658
http://dx.doi.org/10.1016/j.dib.2020.106391
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