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MedGermDB: A seed germination database for characteristic species of Mediterranean habitats

Applied vegetation science · 1 Jan 2024 · 10.1111/avsc.12771

Abstract

Seed germination is a crucial phase of plant responses in early life to current and future environmental conditions. However, germination data are still scarce or disaggregated for many plant lineages and regions, including global biodiversity hotspots such as the Mediterranean Basin. We present MedGermDB, the first germination database for characteristic species of Mediterranean habitats, as defined by the EUNIS classification. We also present a systematic approach to build germination databases using automatic and semi‐automatic data extraction from the literature. MedGermDB contains germination data for 4680 laboratory tests performed with 236 angiosperm species from 43 families, extracted from 125 literature sources (2837 sources screened). Each test is associated to a seed lot (i.e., a seed collection of a plant species obtained from a specific location at a specific time) and its metadata, recording geographical information and experimental conditions (storage, dormancy‐breaking treatments, incubation temperature, and photoperiod). MedGermDB is available as a csv file, and through a web app: https://dianamariacruztejada.shinyapps.io/medgermdb/. MedGermDB can be used to explore eco‐evolutionary questions and provides a backbone data set for informing effective seed‐based conservation and ecological restoration activities targeting EUNIS habitats. Our methodological approach to data extraction can be extended to other study systems, contributing to global efforts to mobilize germination data.

Plant phenotyping relevance

植物の発芽状態に関する大規模データセットを構築し、文献からの自動・半自動データ抽出手法とWebアプリを提示しており、単なる生物学的実験のルーチン測定ではない。

abstractWe present MedGermDB, the first germination database for characteristic species of Mediterranean habitats
abstractWe also present a systematic approach to build germination databases using automatic and semi‐automatic data extraction from the literature.
abstractMedGermDB is available as a csv file, and through a web app: https://dianamariacruztejada.shinyapps.io/medgermdb/.

Code and data availability

The paper's MedGermDB germination database (supplementary CSVs) and the code/workflow to join database files are publicly available in the authors' GitHub repository, with a Zenodo version of record and a Shiny app for visualization.

Codepublic

ty and Research (MUR) as part of the PON 2014– 2020 “Research and Innovation” resources—Green/Innovation Action—DM MUR 1061/2022, Number: DOT13GFICX-­ 2. CONFLICT OF INTEREST STATEMENT None. DATA AVAILABILITY STATEMENT All data are available as supplementary materials. The data and codes to join the database files are stored at https://github.com/DianaCruzT ejada/ MedGe rmDB and visualized with the shiny app at https://diana mariacruztejada.shinyapps.io/medgermdb/. A version of record of the repository can be found at https:// doi. org/ 10. 5281/ zenodo. 10915154. All people interested in contributing to the growth of this germination database are encouraged to contact the corresp

Open resource ↗MedGermDB · pdf-raw-page:6 lines:1-151

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