ArticleBiodiversity data journal2021
Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries.
Article in Biodiversity data journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Mining buried plant trait data from the Global Biodiversity Information Facility (GBIF): Comparison and integration with multiple plant trait databases.Applications in plant sciences · 2026Article
- Manage your image database with computer vision-Lessons learned at Encyclopedia of Life.Bioscience · 2026Article
- Genetic diversity and agro-morphological characterization of cassava varieties provides insight for breeding and crop improvement.Scientific reports · 2025Article
- Effects of Drought Stress on Leaf Functional Traits and Biomass Characteristics ofPlants (Basel, Switzerland) · 2024Article
- Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging.Plants (Basel, Switzerland) · 2023Article
- Envisaging a global infrastructure to exploit the potential of digitised collections.Biodiversity data journal · 2023Article
- Reference bioimaging to assess the phenotypic trait diversity of bryophytes within the family Scapaniaceae.Scientific data · 2022Article
- From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2.Applications in plant sciencesArticle
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMorphological 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. Based on a pilot study to identify the availability and appropriateness of herbarium specimen images for comprehensive trait data extraction, we developed a spatio-temporal dataset on intraspecific trait variability containing 128,036 morphological leaf trait measurements for seven selected species. NEW INFORMATION: After scrutinising the metadata of digitised herbarium specimen images available from iDigBio and GBIF (21.9 million and 31.6 million images for
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