Abstract
Bioacoustic monitoring and classification of animal communication signals has developed into a powerful tool for measuring and monitoring species diversity within complex communities and habitats. The high number of stridulating species among Orthoptera allows their detection and classification in a non-invasive and economic way, particularly in habitats where visual observations are difficult or even impossible, such as tropical rainforests. Major sound archives were queried for Orthoptera songs, with special emphasis on usability as reference training libraries for computer algorithms. Orthoptera songs are highly stereotyped, reliable taxonomic features. However, exploitation of songs for acoustic profiling is limited by the small number of reference recordings: existing song libraries represent only about 1000 species, mainly from Europe and North America, covering less than 10% of extant stridulating Orthoptera species. Available databases are fragmented and lack tools for song annotation and efficient feature-based searching. Results from recent bioacoustic surveys illustrate the potential of the method, but also the challenges and bottlenecks impeding further progress. A major problem is time-consuming data analysis of recordings. Computer-aided identification software exists for classification and identification of cricket and grasshopper songs, but these tools are still far from practical for field application.A framework for acoustic profiling of Orthoptera should consist of the following components: (1) Protocols for standardized acoustic sampling, at species and community levels, using acoustic data loggers for autonomous long-term recordings; (2) Open access to and efficient management of song data and voucher specimens, involving the Orthoptera Species File (OSF) and Global Biodiversity Information Facility (GBIF); (3) An infrastructure for automatized analysis and song classification; and (4) Complementation and improvement of Orthoptera sound libraries using OSF as the taxonomic backbone and repository for representative song recordings. Taxonomists should be encouraged, or even obliged, to deposit original recordings, particularly if they form part of species descriptions or revisions.
Highlights
A considerable number of animal species produce species-specific sounds for communication, indicating their presence acoustically
Further recordings were made at biodiversity hotspots in New Caledonia and French Guiana. Such overall bioacoustic indices do not provide information about actual Orthoptera species presence and diversity, but informative snippets could be extracted (Riede and Jahn 2013, Lehmann et al 2014). This means that post-hoc analysis for Orthoptera presence/absence at an ever-increasing number of acoustic monitoring sites is possible, if soundscape recordings would be made available for re-analysis
Otte and Alexander (1983) were the first to point out the enormous potential of communicative signal analysis for understanding the systematics and taxonomy of Orthoptera: “It must be clear at this point that those systematists who utilize communicative signals and isolating mechanisms as their principal means of locating and recognizing species are not studying biology as well as morphology, or using a wide variety of characters, as is commonly and justifiably considered desirable in bio-systematic work
Summary
A considerable number of animal species produce species-specific sounds for communication, indicating their presence acoustically. Such overall bioacoustic indices do not provide information about actual Orthoptera species presence and diversity, but informative snippets could be extracted (Riede and Jahn 2013, Lehmann et al 2014) This means that post-hoc analysis for Orthoptera presence/absence at an ever-increasing number of acoustic monitoring sites is possible, if soundscape recordings would be made available for re-analysis. Optional requirements include online visualization of sound files (spectrogram/oscillogram), generation of bioacoustic factsheets, and flexible tools for annotation of song parameters Building on these basic features, a bioacoustics workbench could provide efficient, reciprocal connection to taxonomic (OSF) and specimen-based federated specimen databases (GBIF). Classification of individual recordings.—For individual recordings, song parameters such as pulse rate and carrier frequency can be extracted by basic sound analysis software These parameters might be sufficient to identify species using a traditional taxonomic key (Ragge and Reynolds 1998, p.83) based on acoustic features. Well-curated corpora are not yet available in bioacoustics (cf. Riede and Jahn 2013), which hampers progress of computer-aided analysis
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