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.
MedGermDB: A seed germination database for characteristic species of Mediterranean habitats
Cruz-Tejada D. M.
;Mo A.;Carta A.Ultimo
Supervision
2024-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.