Climate change and habitat loss are changing the distributions and population size of many bird species. Many species require urgent conservation actions. The trouble is, how do we know what species are in decline and where they are currently located? In North America, this need is met partly by volunteer projects like the Christmas Bird Count and Breeding Bird Survey. Even with large-scale projects such as these, however, areas with high (human) population density are going to be covered much more thoroughly than low-density areas. Other volunteer projects such as eBird suffer from the same problem.
Some German computer scientists are exploring a possible technical solution for covering the gaps: a recording device with software that can identify bird songs. Microphones would be left in the field for some period of time, and then the many hours of recordings would be analyzed by computer back at a laboratory.
In his project Daniel Wolff of the Institute of Computer Science at the University of Bonn initially concentrated on the bio-acoustic recognition of the Savi’s warbler and the chaffinch. He listened carefully to the various types of birdsong, scrutinised them in a spectrogram and transferred the characteristics to algorithms. As soon as specific parameters are met, the programme kicks in. ‘For example, the signal of the Savi’s warbler has a mean frequency of 4 kHz, which is very typical. If, in addition, individual elements of the signal are repeated at a frequency of 50 Hz, this is detected as the call of a Savi’s warbler,’ Daniel explains. The chaffinch detector also analyses periodic repetitions of elements like these. In doing so it reveals more of a typical verse structure than the pitch of the chaffinch’s song.If this works, it could provide an easier way to monitor areas that are not already covered by population surveys. It seems, though, that the project still has some ground to cover before it can do full population monitoring. In the meantime, keep birding and reporting your sightings!
The Savi’s warbler detector, particularly, which was subjected to long-term monitoring at Brandenburg’s Parsteiner Weiher, is characterised by what researchers call ‘robust recognition’, i.e. a high degree of reliability. Despite interference from rain, wind and amphibians the programme recognised, with a 92% detection accuracy, the song of a species of bird which is still found on the shores of the Baltic but which has become rare elsewhere in Europe.
The birdsong detectors are as yet only calibrated for the birdsong of individual species. However, in the near future, Daniel Wulff thinks, it will be possible to link them up to a kind of superdetector which can recognise as many species as possible and, in combination with GPS coordinates, will make the mapping of bird populations simpler and more efficient.