About the database
The EuMon consortium, comprising 16 partners from 11 EU-countries, designed databases and carried out online surveys to provide an overview of monitoring approaches and monitoring organisations in Europe. One database, the PMN database, covers characteristics of organisations that involve volunteers in biodiversity monitoring (see Overview graphs& tables and BioMAT background information) and a second one, called DaEuMon, addresses coverage and methodological aspects of biodiversity monitoring. Both databases are automatically updated with each new entry. BioMAT allows extracting information from the databases to generate graphs and tables or to contact monitoring schemes for particular habitats or species groups. On this page we provide information on DaEuMon.
Demands to fill in the questionnaires were communicated to monitoring coordinators by postal mail, email, personally, and by phone. In total, the EuMon consortium has collected over 4000 contact details of potential monitoring organizations (including fish and hunting associations as well as local, regional, and national governmental bodies). The input to the database still continues, making the database the most comprehensive one in Europe. However, not all countries and species groups are covered equally well and this should be considered in any analyses of the data from DaEuMon.
Despite these biases, our survey yielded a wide geographical coverage with at least one scheme from any country in geographical Europe and also adequately covers central and eastern (Poland, Hungary, Lithuania) and western European countries (France, Belgium, Germany).
About 4000 species are covered by the monitoring programs in the database. Schemes monitoring birds and mammals showed small biases (relative to the number of publications listed in the Zoological Record; evaluated in 2008), but some groups, especially fishes, lichens and fungi still seem to be underrepresented.
The usefulness of the EuMon database as a reference to monitoring schemes will further increase with time due to on-going efforts to maintain the database and extend its popularity. In this respect, the recommendations for volunteer involvement and data integration, supporting the work of monitoring coordinators, did already function as powerful incentives for new data entries. We appreciate any further entries to DaEuMon and thank you very much for your support.