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Commercially available automated bat identification software packages are widely used in environmental studies to identify bat species from recordings of bat echolocation calls. Caution is, however, needed if the results are used without further verification, as the programs do not guarantee that the results are correct, and wrong species identifications often happen. Taking automated species identifications for granted might hence lead to erroneous conclusions in environmental studies. The goal of our study was to objectively assess the performance of four commercially available and commonly used automated identification software programs by processing an identical reference dataset with all four programs. The reference dataset consisted of nine species selected based on their preference for open habitats in Western Europe or because they occur as vagrants at sea and therefore are vulnerable to the development of onshore and offshore wind farms. Offshore areas are being increasingly examined, as recent studies have identified possible conflicts of offshore wind farms and certain bat species. In our test, we included two automated identification programs that have not yet been tested in other studies, and a reference dataset from a different geographical region (Western-Europe) with a different species composition compared to other studies. Our data hence add to the knowledge base needed for an appropriate assessment of the reliability of analytical software. In general, BatIdent (77% correct species identifications) and Kaleidoscope (71%) seem to be relatively reliable while the performance of BatExplorer (31%) is relatively poor. SonoChiro correctly identified 65% of the sequences to species level. While the tested programs may be considered valuable tools to detect bat calls from the recordings, a trained bat expert needs to cross-check the automated species identifications to avoid erroneous conclusions. Our test hence affirms the conclusions of previous studies in Northern Europe and the USA.

Comparing the results of four widely used automated bat identification software programs to identify nine bat species in coastal Western Europe