One of the biggest problems of using acoustical methods for bat activity acquisition is the discrimination of species by their calls. While some genera (like Pipistrellus) are more or less simple to determine on a secure level, for others this is close to impossible without elaborate methods (like Myotis). Up until now one has to take measurements manually and compare these with numbers from few publications, time-consuming and non-satisfying. Quite often the awarding authority is not willing to pay this sumptuous task completely.

One of the biggest problems of using acoustical methods for bat activity acquisition is the discrimination of species by their calls. While some genera (like Pipistrellus) are more or less simple to determine on a secure level, for others this is close to impossible without elaborate methods (like Myotis). Up until now one has to take measurements manually and compare these with numbers from few publications, time-consuming and non-satisfying. Quite often the awarding authority is not willing to pay this sumptuous task completely.

Identification scheme

The following scheme displays the identification tree and its steps as it is used in batIdent:

Identification confusions

While using about 600 trainings calls per species, nevertheless confusions of species occur. Due to overlapping call repertoires this must be expected. The following graph supplied by NycNoc GmbH displays the out of bag errors, which were recorded with a single call analysis using randomForest:

We have prepared a document describing the underlying mechanisms as well as typical errors of automated call identification ([Download not found]). Please also see our collection of European bat calls ( Variation of the calls of native bat species ).