Database Species-Area Relationships in Palaearctic Grasslands

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Abstract

The Database Species-Area Relationships in Palaearctic Grasslands (GIVD ID EU-00-003) is an initiative of the European Dry Grassland Group (EDGG) and primarily functions as repository for all data sampled during the EDGG Research Expeditions. During these expeditions two types of highly standardised sampling of dry grassland vegetation in the Palaearctic realm are carried out: (i) nested-plot sampling on squares of 0.0001, 0.001, 0.01, 0.1, 1, 10, and 100 m; (ii) additional normal relevs of 10-m plots. For all plot sizes, the terricolous vascular plants, bryophytes, and lichens are recorded that are superficially present (shoot presence). Additionally, for all 10-m plots species cover is estimated directly in percent and a wide range of topographic, soil, and land use parameters is determined. Five such expeditions have been carried out so far (2009: Transylvania, Romania; 2010: Central Podolia, Ukraine; 2011: NW Bulgaria; 2012a: Sicily, Italy; 2012b: N Greece). Additionally, the database contains similar nested-plot data from published and unpublished sources covering dry grasslands in Czech Republic, Estonia, Germany, the Netherlands, Russia, Sweden, Switzerland, and the United Kingdom. The vegetation classes Festuco-Brometea and Koelerio-Corynephoretea prevail, but there are also some data from Mediterranean grasslands. Presently, the database contains data from 402 nested-plot series plus 325 separate 10-m plots. Data from future EDGG Expeditions will be added and we are open to add other nested-plot data from any type of grassland in the Palaearctic. This huge collection of nested-plot data is very valuable for the study of species-area relationships (SARs) in grasslands and how their function types and parameters (e.g. the z-values of the power-law SARs) depend on grassland type, region, and taxon considered. The 10-m plots from the EDGG Expeditions (from inside and outside the nested plots) are an important contribution to consistent large-scale classifications as they were sampled by using a uniform plot size, recording also non-vascular plants, and consistently determining a set of plot-based plot-based environmental variables. The dataset will be available to the scientific public based on individual arrangements.

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