Biodiversity Data Journal 9: e69806 doi: 10.3897/BDJ.9.e69806 Data Paper Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries Vamsi Krishna Kommineni‡,§, Susanne Tautenhahn‡, Pramod Baddam‡,§, Jitendra Gaikwad|,¶, Barbara Wieczorek§#, Abdelaziz Triki , Jens Kattge‡,| ‡ Max Planck Institute for Biogeochemistry, Jena, Germany § Ernst-Abbe-Hochschule Jena, Jena, Germany | German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany ¶ Friedrich Schiller University Jena, Jena, Germany # University of Sfax, Sfax, Tunisia Corresponding author: Vamsi Krishna Kommineni (
[email protected]), Susanne Tautenhahn (staut@b gc-jena.mpg.de) Academic editor: Alexander Sennikov Received: 07 Jun 2021 | Accepted: 30 Jun 2021 | Published: 13 Jul 2021 Citation: Kommineni VK, Tautenhahn S, Baddam P, Gaikwad J, Wieczorek B, Triki A, Kattge J (2021) Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries . Biodiversity Data Journal 9: e69806. https://doi.org/10.3897/BDJ.9.e69806 Abstract Background Morphological leaf traits are frequently used to quantify, understand and predict plant and vegetation functional diversity and ecology, including environmental and climate change responses. Although morphological leaf traits are easy to measure, their coverage for characterising variation within species and across temporal scales is limited. At the same time, there are about 3100 herbaria worldwide, containing approximately 390 million plant specimens dating from the 16th to 21st century, which can potentially be used to extract morphological leaf traits. Globally, plant specimens are rapidly being digitised and images are made openly available via various biodiversity data platforms, such as iDigBio and GBIF.