Automated acoustic monitoring

Acoustic emissions of animals serve communicative purposes and most often contain species-specific and individual information exploitable to listeners, rendering bioacoustics a valuable tool for biodiversity monitoring. Recording bioacoustic signals allows reproducible species identification. There is a great need for increased use and further development of automated animal sound recording and identification to improve monitoring efficiency and accuracy for the benefit of conservation. Greece, with its high number of endemic species, represents a hotspot for European Biodiversity, including Orthopteran insects. Songs of many Orthoptera might be employed for the inventorying and monitoring of individual species and communities. We assessed the regional spatio-temporal composition of Orthoptera species at the Hymettos near Athens, which is a Natura 2000 site under constant threat due to the surrounding megacity. Within the framework of the EU Life Plus funded AmiBio project, we documented the Orthopteran species’ habitat characteristics, their co-occurrence and phenology. We found, in total, 20 species with seven to ten Orthoptera at locations characterised by diverse vegetation patterns of perennial herbs and bushes. For the purposes of implementation of an automated remote monitoring scheme, we identified sampling sites with high Orthopteran diversity, allowing the monitoring of all singing Orthoptera within single localities. By analysing sound depositories and adding recordings from new sample individuals, we established a song library as prerequisites for future automatic song detection. Based on our results, acoustic recording units have been placed at remote sites at the Hymettos. We discuss recommendations for further studies to fully employ the potential of automated acoustic monitoring of Orthoptera. A reliable assessment of singing Orthoptera needs recording units covering ultrasound. Due to high attenuation and absorbance by the vegetation, particularly of the high frequencies characterising Orthopteran songs, positioning of microphones at sites is critical: the microphone sensor network has to be an order of magnitude denser than for monitoring birds.