Nordic-Baltic Grassland Vegetation Database (NBGVD) – current state and future prospects

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  • Nadiia Skobel
  • Łukasz Kozub
  • Iwona Dembicz
  • Steffen Boch
  • Bruun, Hans Henrik
  • Olha Chusova
  • Valentin Golub
  • Aveliina Helm
  • Dmytro Iakushenko
  • Paweł Pawlikowski
  • Piotr Zaniewski
  • Jürgen Dengler
This Long Database Report describes the historical background and current contents of the Nordic-Baltic Grassland Vegetation Database (NBGVD) (GIVD-code EU-00-002). NBGVD is the EDGG-associated collaborative vegetation-plot database that collects vegetation-plot data of grasslands and other open habitats (except segetal and deep aquatic vegetation) from the Nordic-Baltic region excluding Germany, namely Belarus, Denmark, Estonia, Faroe Islands, Finland, Iceland, Latvia, Lithuania, Norway, N Poland, NW Russia, Svalbard and Jan Mayen, and Sweden. Target vegetation types are lowland grasslands and heathlands, arctic-alpine communities, coastal communities, non-forested mires and other wetlands, rocky, tall-herb and ruderal communities. As of March 2024, it included 12,694 relevés recorded between 1910 and 2023. These were mainly digitised from literature sources (84%), while the remainder comes from individual unpublished sources (16%). The data quality is high, with bryophytes and lichens being treated in more than 80% of all plots and measured environmental variables such as topography and soil characteristics often available in standardised form. A peculiarity of the Nordic-Baltic region are the relatively small plot sizes compared to other regions (median: 4 m2). The available data stem from 35 vegetation classes, with Koelerio-Corynephoretea, Festuco-Brometea, Sedo-Scleranthetea, Molinio-Arrhenatheretea and Scheuchzerio-Caricetea being most frequent. We conclude that NBGVD provides valuable data, allowing interesting analyses at the regional scale and fills gaps in continental to global analyses. Still, since there are many more data around, we ask interested readers to contribute their own data or help find and digitise old data from the literature.
OriginalsprogEngelsk
TidsskriftVegetation Classification and Survey
Vol/bind5
Sider (fra-til)75-84
Antal sider10
DOI
StatusUdgivet - 2024

ID: 393839742