Evidence map›Paper›PMID 34157097›Full record

ArticleAnnals of botany2021

Leaf size estimation based on leaf length, width and shape.

Julian Schrader, Peijian Shi, Dana L Royer, Daniel J Peppe, Rachael V Gallagher, Yirong Li, Rong Wang, Ian J Wright

Abstract read
In one paragraph

Article in Annals of botany, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
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46citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

46 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Julian SchraderDepartment of Biological Sciences, Macquarie University, NSW 2109, Australia.ORCID 0000-0002-8392-211X
Peijian ShiBamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China.ORCID 0000-0003-4696-0130
Dana L RoyerDepartment of Earth and Environmental Sciences, Wesleyan University, Middletown, CT 06459, USA.ORCID 0000-0003-0976-953X
Daniel J PeppeTerrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, TX 76706, USA.ORCID 0000-0003-4263-133X
Rachael V GallagherDepartment of Biological Sciences, Macquarie University, NSW 2109, Australia.ORCID 0000-0002-4680-8115
Yirong LiBamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China.ORCID 0000-0003-4497-0001
Rong WangBamboo Research Institute, Nanjing Forestry University, Nanjing 210037, P.R. China.ORCID 0000-0003-1444-5740
Ian J WrightDepartment of Biological Sciences, Macquarie University, NSW 2109, Australia.ORCID 0000-0001-8338-9143

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

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. 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.

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.

Indexed as

Plant LeavesSoftwarePlantsCorrection factorfunctional traitleaf arealeaf lengthleaf morphologyleaf sizeleaf widthproportional relationship

Identifiers

PMID34157097
PMCPMC8414912

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.