(Press-News.org) Everyone knows that if you want to enjoy the full experience of the dawn chorus in the forests of Central Europe, or carry out scientific research on bird species, you have to get up very early in the morning. Until now however, detailed data about daily and seasonal patterns in birdsong have only been available for a few species, as the observations required are time-consuming. A research team from the University of Göttingen and the Northwest German Forest Research Institute has now, for the first time, analysed the song and calls of 53 European forest bird species during a breeding season with the help of artificial intelligence. They were able to show that singing behaviour recorded with automatic audio recorders differs from previous expert knowledge. The findings were published in the Journal of Ornithology.
The researchers collected data at 256 forest locations in Lower Saxony in Germany. They recorded bird calls with small audio recorders around the clock for 30 seconds every 10 minutes from March to May. They then used AI to identify the bird species based on their calls and songs. The researchers checked the AI's suggestions to ensure that only reliable identifications of species were included in the analysis.
High-resolution analysis of a total of 6.4 million recorded sounds revealed that forest bird species have individual patterns of activity. “Our data show that there are far more activity types among forest bird species than just ‘larks’ and ‘owls’,” explains David Singer, lead author of the study and PhD student in Forest Nature Conservation at the University of Göttingen. In addition to a large group of species who are active during the hours of daylight, some species – such as blackbirds and woodcocks – were active around dawn and twilight and could in fact be heard twice a day. Blackbirds were also heard significantly more often in the evening than in the morning, a result that had not shown up in previous bird counts. There were also subgroups within the group of species active in the day. While many species of tit and the black woodpecker were most active in early spring and were heard significantly less from the end of April onwards, species such as the dunnock and the wren became active in April. Nocturnal species were in their own group, as were migratory birds, which do not arrive in Central Europe until May.
The researchers then went on to compare their results with previous recommendations for methods to carry out surveys of breeding birds. They were able to demonstrate that the recommended times to carry out surveys for many species often did not even overlap with their phases of peak song activity. For example, it was previously assumed that the great spotted woodpecker could be easily detected throughout the morning. However, according to the latest data, this species is significantly less likely to be heard around two hours after sunrise than shortly after sunrise. For other typical forest bird species such as the blue tit and the chiffchaff, song activity remained high beyond the recommended recording period in the morning, meaning that these species can still be reliably counted later in the day.
“By combining traditional methods of counting birds with the new AI-supported methods of analysing birdsong, we can significantly improve our knowledge and understanding of bird behaviour,” says Göttingen University forest ecologist Professor Andreas Schuldt, who jointly supervised the work. “In particular, measurements of species with short peaks of activity are improved by this new method.” For example, grey-headed and lesser spotted woodpeckers, which can only be heard during a relatively short time window, can be recorded particularly well with the new method, whereas ornithologists would be very lucky indeed to observe these species.
Working together with the Dachverband Deutscher Avifaunisten (DDA), the results of the study have already been incorporated into the latest edition of the book “Methodenstandards zur Erfassung der Brutvögel Deutschlands” (Methodological Standards for Recording Breeding Birds in Germany), so that strategies for carrying out research on birds can be better planned in future. A comparable evaluation for bird species in agricultural landscapes will be possible in the future thanks to ongoing research projects.
The study is part of the biodiversity monitoring programme of the Nordwestdeutsche Forstliche Versuchsanstalt together with the University of Göttingen’s Forest Nature Conservation, and Conservation Biology research groups. Information on the project (in German): www.nw-fva.de/wir/aktuelles/pm-biodiversitaetsmonitoring.
Original publication: D Singer et al “Diel and seasonal vocal activity patterns revealed by passive acoustic monitoring suggest expert recommendations for breeding bird surveys need adjustment.” Journal of Ornithology (2025). DoI: 10.1007/s10336-025-02307-y
Contact:
David Singer
University of Göttingen
Faculty of Forest Sciences and Forest Ecology – Forest Nature Conservation Research Group
Büsgenweg 3, 37077 Göttingen, Germany
Email: david.singer@nw-fva.de
Professor Andreas Schuldt
University of Göttingen
Faculty of Forest Sciences and Forest Ecology – Forest Nature Conservation Research Group
Email: andreas.schuldt@forst.uni-goettingen.de
www.uni-goettingen.de/en/595615.html
END
More than just larks and owls!
Research team led by Göttingen University use AI to discover when different forest birds sing
2025-07-18
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[Press-News.org] More than just larks and owls!Research team led by Göttingen University use AI to discover when different forest birds sing