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

Abstract

Background and aims 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. Methods 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. Key results 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. Conclusion 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.

Plant phenotyping relevance

葉長・葉幅・葉形から葉面積を推定する植物形質測定法を開発し、画像認識ソフトウェア等と比較検証しているため、方法が研究の中心である。

Code and data availability

The paper's leaf measurement dataset (3125 leaves, 780 taxa) is stated to be fully contained in the paper's supplementary data (Table S1 with family/species data, plus Tables S2–S3 with correction factors), which the authors state are available online at the journal site. No author analysis code or trained models are披露