Leaf size estimation based on leaf length, width and shape
Leaf size has considerable ecological relevance, making it desirable to obtain leaf size estimations for as many species worldwide as possible. Current global databases, such as TRY, contain leaf size data for ~30 000 species, which is only ~8% of known species worldwide. Yet, taxonomic descriptions...
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Published in | Annals of botany Vol. 128; no. 4; pp. 395 - 406 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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England
Oxford University Press
03.09.2021
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Abstract | Leaf size has considerable ecological relevance, making it desirable to obtain leaf size estimations for as many species worldwide as possible. Current global databases, such as TRY, contain leaf size data for ~30 000 species, which is only ~8% of known species worldwide. Yet, taxonomic descriptions exist for the large majority of the remainder. Here we propose a simple method to exploit information on leaf length, width and shape from species descriptions to robustly estimate leaf areas, thus closing this considerable knowledge gap for this important plant functional trait.
Using a global dataset of all major leaf shapes measured on 3125 leaves from 780 taxa, we quantified scaling functions that estimate leaf size as a product of leaf length, width and a leaf shape-specific correction factor. We validated our method by comparing leaf size estimates with those obtained from image recognition software and compared our approach with the widely used correction factor of 2/3.
Correction factors ranged from 0.39 for highly dissected, lobed leaves to 0.79 for oblate leaves. Leaf size estimation using leaf shape-specific correction factors was more accurate and precise than estimates obtained from the correction factor of 2/3.
Our method presents a tractable solution to accurately estimate leaf size when only information on leaf length, width and shape is available or when labour and time constraints prevent usage of image recognition software. We see promise in applying our method to data from species descriptions (including from fossils), databases, field work and on herbarium vouchers, especially when non-destructive in situ measurements are needed. |
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AbstractList | Leaf size has considerable ecological relevance, making it desirable to obtain leaf size estimations for as many species worldwide as possible. Current global databases, such as TRY, contain leaf size data for ~30 000 species, which is only ~8% of known species worldwide. Yet, taxonomic descriptions exist for the large majority of the remainder. Here we propose a simple method to exploit information on leaf length, width and shape from species descriptions to robustly estimate leaf areas, thus closing this considerable knowledge gap for this important plant functional trait.
Using a global dataset of all major leaf shapes measured on 3125 leaves from 780 taxa, we quantified scaling functions that estimate leaf size as a product of leaf length, width and a leaf shape-specific correction factor. We validated our method by comparing leaf size estimates with those obtained from image recognition software and compared our approach with the widely used correction factor of 2/3.
Correction factors ranged from 0.39 for highly dissected, lobed leaves to 0.79 for oblate leaves. Leaf size estimation using leaf shape-specific correction factors was more accurate and precise than estimates obtained from the correction factor of 2/3.
Our method presents a tractable solution to accurately estimate leaf size when only information on leaf length, width and shape is available or when labour and time constraints prevent usage of image recognition software. We see promise in applying our method to data from species descriptions (including from fossils), databases, field work and on herbarium vouchers, especially when non-destructive in situ measurements are needed. Leaf size has considerable ecological relevance, making it desirable to obtain leaf size estimations for as many species worldwide as possible. Current global databases, such as TRY, contain leaf size data for ~30 000 species, which is only ~8% of known species worldwide. Yet, taxonomic descriptions exist for the large majority of the remainder. Here we propose a simple method to exploit information on leaf length, width and shape from species descriptions to robustly estimate leaf areas, thus closing this considerable knowledge gap for this important plant functional trait.BACKGROUND AND AIMSLeaf size has considerable ecological relevance, making it desirable to obtain leaf size estimations for as many species worldwide as possible. Current global databases, such as TRY, contain leaf size data for ~30 000 species, which is only ~8% of known species worldwide. Yet, taxonomic descriptions exist for the large majority of the remainder. Here we propose a simple method to exploit information on leaf length, width and shape from species descriptions to robustly estimate leaf areas, thus closing this considerable knowledge gap for this important plant functional trait.Using a global dataset of all major leaf shapes measured on 3125 leaves from 780 taxa, we quantified scaling functions that estimate leaf size as a product of leaf length, width and a leaf shape-specific correction factor. We validated our method by comparing leaf size estimates with those obtained from image recognition software and compared our approach with the widely used correction factor of 2/3.METHODSUsing a global dataset of all major leaf shapes measured on 3125 leaves from 780 taxa, we quantified scaling functions that estimate leaf size as a product of leaf length, width and a leaf shape-specific correction factor. We validated our method by comparing leaf size estimates with those obtained from image recognition software and compared our approach with the widely used correction factor of 2/3.Correction factors ranged from 0.39 for highly dissected, lobed leaves to 0.79 for oblate leaves. Leaf size estimation using leaf shape-specific correction factors was more accurate and precise than estimates obtained from the correction factor of 2/3.KEY RESULTSCorrection factors ranged from 0.39 for highly dissected, lobed leaves to 0.79 for oblate leaves. Leaf size estimation using leaf shape-specific correction factors was more accurate and precise than estimates obtained from the correction factor of 2/3.Our method presents a tractable solution to accurately estimate leaf size when only information on leaf length, width and shape is available or when labour and time constraints prevent usage of image recognition software. We see promise in applying our method to data from species descriptions (including from fossils), databases, field work and on herbarium vouchers, especially when non-destructive in situ measurements are needed.CONCLUSIONOur method presents a tractable solution to accurately estimate leaf size when only information on leaf length, width and shape is available or when labour and time constraints prevent usage of image recognition software. We see promise in applying our method to data from species descriptions (including from fossils), databases, field work and on herbarium vouchers, especially when non-destructive in situ measurements are needed. |
Author | Royer, Dana L Peppe, Daniel J Li, Yirong Schrader, Julian Shi, Peijian Wright, Ian J Wang, Rong Gallagher, Rachael V |
AuthorAffiliation | 1 Department of Biological Sciences, Macquarie University , NSW 2109 , Australia 2 Department of Biodiversity, Macroecology and Biogeography, University of Goettingen , Goettingen , Germany 3 Bamboo Research Institute, Nanjing Forestry University , Nanjing 210037 , P.R. China 4 Department of Earth and Environmental Sciences, Wesleyan University , Middletown, CT 06459 , USA 5 Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University , Waco, TX 76706 , USA |
AuthorAffiliation_xml | – name: 2 Department of Biodiversity, Macroecology and Biogeography, University of Goettingen , Goettingen , Germany – name: 4 Department of Earth and Environmental Sciences, Wesleyan University , Middletown, CT 06459 , USA – name: 5 Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University , Waco, TX 76706 , USA – name: 3 Bamboo Research Institute, Nanjing Forestry University , Nanjing 210037 , P.R. China – name: 1 Department of Biological Sciences, Macquarie University , NSW 2109 , Australia |
Author_xml | – sequence: 1 givenname: Julian orcidid: 0000-0002-8392-211X surname: Schrader fullname: Schrader, Julian organization: Department of Biological Sciences, Macquarie University, NSW 2109, Australia, Department of Biodiversity, Macroecology and Biogeography, University of Goettingen, Goettingen, Germany – sequence: 2 givenname: Peijian orcidid: 0000-0003-4696-0130 surname: Shi fullname: Shi, Peijian organization: Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China – sequence: 3 givenname: Dana L orcidid: 0000-0003-0976-953X surname: Royer fullname: Royer, Dana L organization: Department of Earth and Environmental Sciences, Wesleyan University, Middletown, CT 06459, USA – sequence: 4 givenname: Daniel J orcidid: 0000-0003-4263-133X surname: Peppe fullname: Peppe, Daniel J organization: Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, TX 76706, USA – sequence: 5 givenname: Rachael V orcidid: 0000-0002-4680-8115 surname: Gallagher fullname: Gallagher, Rachael V organization: Department of Biological Sciences, Macquarie University, NSW 2109, Australia – sequence: 6 givenname: Yirong orcidid: 0000-0003-4497-0001 surname: Li fullname: Li, Yirong organization: Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China – sequence: 7 givenname: Rong orcidid: 0000-0003-1444-5740 surname: Wang fullname: Wang, Rong organization: Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China – sequence: 8 givenname: Ian J orcidid: 0000-0001-8338-9143 surname: Wright fullname: Wright, Ian J organization: Department of Biological Sciences, Macquarie University, NSW 2109, Australia |
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Keywords | functional trait proportional relationship leaf morphology leaf width leaf length Correction factor leaf size leaf area |
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Title | Leaf size estimation based on leaf length, width and shape |
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