1. Pan European Phenological database (PEP725): a single point of access for European data
- Author
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Anita Paul, Kirsten Zimmermann, Elisabeth Koch, Markus Ungersböck, Barbara Templ, Barbara Pietragalla, This Rutishauser, Frank-M. Chmielewski, Anne Tolvanen, Ana Zust, Lenka Hájková, Frank Kaspar, Montserrat Busto, Helfried Scheifinger, Kjell Bolmgren, Sabina Hodzic, Ramiro Romero-Fresneda, and Višnja Vučetič
- Subjects
0106 biological sciences ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,Ecology ,Database ,Databases, Factual ,Phenology ,Health, Toxicology and Mutagenesis ,Climate change ,Vegetation ,computer.software_genre ,010603 evolutionary biology ,01 natural sciences ,Europe ,Data access ,Geography ,Pan european ,Citizen science ,Long-term data ,Plant phenology ,Environmental monitoring ,Seasons ,Single point ,computer ,0105 earth and related environmental sciences - Abstract
The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 “Establishing a European phenological data platform for climatological applications” working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.
- Published
- 2017