Evidence map›Paper›PMID 42305021›Full record

ArticleAnnals of botany2026

How much cross-sectional area is needed to estimate vessel traits in tropical tree branches?

Robert Muscarella, Julia Valentim Tavares, Carina de Araújo, Silvia Bibbo, Samuel Farrar, Kasia Ziemińska

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Article in Annals of botany, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Robert MuscarellaDepartment of Ecology and Genetics, Uppsala University, Uppsala 752 36, Sweden.ORCID 0000-0003-3039-1076
Julia Valentim TavaresDepartment of Ecology and Genetics, Uppsala University, Uppsala 752 36, Sweden.ORCID 0000-0003-3784-5720
Carina de AraújoDepartment of Ecology and Genetics, Uppsala University, Uppsala 752 36, Sweden.
Silvia BibboDepartment of Ecology and Genetics, Uppsala University, Uppsala 752 36, Sweden.ORCID 0009-0004-7406-811X
Samuel FarrarDepartment of Ecology and Genetics, Uppsala University, Uppsala 752 36, Sweden.
Kasia ZiemińskaTree Anatomy and Function Laboratory, Bielsko-Biała 43-300, Poland.ORCID 0000-0001-7750-4758

Funding

Swedish Phytogeographical SocietySwedish Research Council Formas 2020-00921Swedish Research Council Vetenskapsrådet 2019-03758
6 · The paper itself

Abstract

BACKGROUND AND

aimsWood anatomical traits provide key insights into plant physiology, ecology and evolution but their quantification is time-consuming. As a result, measurements are often based on small sample areas or few features, potentially reducing the accuracy and repeatability of estimates. A better understanding of how sampling intensity influences estimation of anatomical traits would improve the efficiency and reliability of wood anatomical studies.

methodsWe annotated all vessels in 164 branch cross-sections from 19 tree species in Puerto Rico and used these to compute the 'true value' of seven vessel traits. We then applied a subsampling approach to quantify how error of estimated trait values depended on the proportional and absolute area of the sample annotated. We used variance partitioning to assess how the contributions of within-sample, within-species and among-species variation change with area sampled. We also assessed how sampling intensity affected the number of statistically significant comparisons between species. KEY

resultsAt low sampling intensity (i.e. ≤10 % of the total cross-section area), absolute percentage differences of estimates from true values ranged from 6 to 18 %, depending on the trait. Across samples, error declined more strongly as a function of proportional area than absolute area sampled. Nonetheless, among-species and among-individual differences explained the majority of variation in the dataset even at low sampling intensity, while variation among replicate subsamples contributed little to the total variation. Depending on the trait, the proportion of statistically significant differences between species increased by 10-21 % from low to high sampling intensity.

conclusionsOur results suggest that for broad comparisons across species, relatively low sampling intensity can yield robust estimates. However, more sampling may be required for questions demanding greater statistical power, such as within-species or within-individual comparisons. Generally, the design of wood anatomy studies should explicitly consider the accuracy and precision required by the research objectives.

Indexed as

TreesWoodPuerto RicoSpecies SpecificityTropical ClimatePuerto RicoQuantitative wood anatomyvessel densityvessel groupingvessel size

Identifiers

PMID42305021
PMCPMC13595280

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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 Socratic graph.