EDaSS - European Database of Successional Seres

The study of succession, the sequential replacement of species following a disturbance, have much to offer to solve contemporary problems concerning biodiversity loss, climate change, invasive species, and ecological restoration. Results of a single particular study can be exploited immediately for local restoration projects, but the systematic comparison of studies across habitats and larger space-temporal scales can enable extrapolation of the results, formulation of new theoretical principles, and inform restoration efforts.

You are kindly invited to contribute your successional data to the European Database of Successional Series (EDaSS). We are compiling existing successional data to do synthesis work of changes in vegetation following disturbance. Synthesis at multiple scales and meta-analysis can allow us to identify overall trends in succession and assess restoration success.

The Restoration Ecology Group has already put together a unique dataset from multiple human-disturbed sites across different latitudes in Europe considering all biomes. We are enlarging this successional database and you are welcome to collaborate and share our effort.


Disturbance types

  • Mining activities

  • Abandoned fields

  • Post-fire succession

  • Clear cutting

  • Road verges

  • Landslides

  • Glacier retreat

  • Dunes

  • Emerged lake-bottoms

  • Others are welcome

Requirements to include the data

  • Vegetation cover data (species) composing successional series of at least 10 years, recording development not later than 5 years after the disturbance
  • Only spontaneous succession is considered, without obvious alterations or additional management (e.g. no grazing, no sowing, planting, topsoiling, etc.).
  • Data from permanent plots or transects (multiple time-points of monitoring) or chronosequences (covering a more or less continuous period), obtained from plots of preferably 5x5 m2 (other sizes could also be included, e.g. 2x2 - 20x20 m2). 


    You will be co-authors of minimum the first paper using your data

    Authorship in following papers is of course welcome and expected

    Will always be cited as data contributors in publications

    Contact details

    Please, do not hesitate to contact us for further information about the project.


    Miguel Ballesteros: miguelballesterosjimenez@gmail.com

    Principal investigators

    Karel Prach, head of the group: prach@prf.jcu.cz

    Klára Řehounková: klara.rehounkova@gmail.com