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Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries.

Biodiversity data journal · 13 Jul 2021 · 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. 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 Tracheophyta ; accessed date December 2020), we identified approximately 10 million images potentially appropriate for our study. From the 10 million images, we selected seven species ( Salix bebbiana Sarg., Alnus incana (L.) Moench, Viola canina L., Salix glauca L., Chenopodium album L., Impatiens capensis Meerb. and Solanum dulcamara L.) , which have a simple leaf shape, are well represented in space and time and have high availability of specimens per species. We downloaded 17,383 images. Out of these, we discarded 5779 images due to quality issues. We used the remaining 11,604 images to measure the area, length, width and perimeter on 32,009 individual leaf blades using the semi-automated tool TraitEx. The resulting dataset contains 128,036 trait records.We demonstrate its comparability to trait data measured in natural environments following standard protocols by comparing trait values from the TRY database. We conclude that the herbarium specimens provide valuable information on leaf sizes. The dataset created in our study, by extracting leaf traits from the digitised herbarium specimen images of seven selected species, is a promising opportunity to improve ecological knowledge about the adaptation of size-related leaf traits to environmental changes in space and time.

Plant phenotyping relevance

デジタル標本画像から葉面積・長さ・幅・周囲長を半自動抽出し、大規模な再利用可能データセットを構築・比較検証しており、植物表現型取得法が中心である。

abstractwe developed a spatio-temporal dataset on intraspecific trait variability containing 128,036 morphological leaf trait measurements for seven selected species.
abstractWe used the remaining 11,604 images to measure the area, length, width and perimeter on 32,009 individual leaf blades using the semi-automated tool TraitEx.
abstractWe demonstrate its comparability to trait data measured in natural environments following standard protocols by comparing trait values from the TRY database.

Code and data availability

The paper's own leaf trait dataset (128,036 records from 11,604 herbarium specimen images) is publicly deposited on Zenodo, and two supplementary CSV files provide image metadata and per-image measurement/exclusion information. No author analysis code with a public URL is provided (Python scripts are mentioned but not)

Supplementpublic

Material 260ECA78-3D27-5F68-AD9E-72A5A181EDBD 10.3897/BDJ.9.e69806.suppl1 Supplementary material 1 Metadata from iDigBio and GBIF Data type comma-separated values Brief description This file contains the metadata of the 17383 digital herbarium specimen images from iDigBio and GBIF for selected seven species. File: oo_548998.csv https://binary.pensoft.net/file/548998 Vamsi Krishna Kommineni, Susanne Tautenhahn, Pramod Baddam, Jitendra Gaikwad, Barbara Wieczorek, Abdelaziz Triki, Jens Kattge F9029DEB-A4B1-50CA-9EC8-3F08DA0A1710 10.3897/BDJ.9.e69806.suppl2 Supplementary material 2 Information of digital herbarium specimen images with different kinds of problems Data type comma-separated value

Open resource ↗lines:213-233
Supplementpublic

ing 'NA', meaning AccessURL of the corresponding record is not responded or not reachable while downloading the images. If 'Number of leaves measured' column is 'NA', then one of the columns 'Image', 'Remarks_1', 'Remarks_2', and 'Ruler' are updated accordingly, meaning the trait measurement is not possible. File: oo_549000.csv https://binary.pensoft.net/file/549000 Vamsi Krishna Kommineni, Susanne Tautenhahn, Pramod Baddam, Jitendra Gaikwad, Barbara Wieczorek, Abdelaziz Triki, Jens Kattge Acknowledgements

Open resource ↗lines:213-233

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