Abstrakt
The Pladias (Plant Diversity Analysis and Synthesis) Database of the Czech Flora and Vegetation was developed by the Pladias project team in 2014-2018 and has been continuously updated since then. The flora section of the database contains critically revised information on the Czech vascular flora, including
13.6 million plant occurrence records, which are dynamically displayed in maps, and data on 120 plant characteristics (traits, environmental associations and other information), divided into the sections: (1) Habitus and growth type, (2) Leaf, (3) Flower, (4) Fruit, seed and dispersal, (5) Belowground organs and clonality, (6) Trophic mode, (7) Karyology, (8) Taxon origin, (9) Ecological indicator values, (10) Habitat and sociology, (11) Distribution and frequency, and (12) Threats and protection. The vegetation section of the database contains information on Czech vegetation types extracted from the monograph Vegetation of the Czech Republic. The data are supplemented by national botanical bibliographies, electronic versions of the standard national flora and vegetation monographs, a database of more than 19,000 pictures of plant taxa and vegetation types, and digital maps (shapefiles) with botanical information. The data from the database are available online on a public portal www.pladias.cz, which also provides download options for various datasets and online identification keys to the species and vegetation types of the Czech Republic. In this paper, we describe the general scope, structure and content of the database, and details of the data on plant characteristics. To illustrate the data and describe the main geographic patterns in selected plant characteristics, we provide maps of mean values of numerical characteristics or proportions of categories for categorical characteristics on the map of the country in a grid of 5 longitudinal x 3 latitudinal minutes (approximately
6.0 km x
5.5 km). We also summarize the main variation patterns in the functional traits in the Czech flora using the principal component analysis.