Global Cicada Sound Collection I: Recordings from South Africa and Malawi by B. W. Price & M. H. Villet and harvesting of BioAcoustica data by GBIF
- 1. The Natural History Museum, London, United Kingdom
- 2. Rhodes University, Grahamstown, South Africa
Description
Sound collections for singing insects provide important repositories that underpin existing research (e.g. Price et al. 2007 at http://bio.acousti.ca/node/11801; Price et al. 2010) and make bioacoustic collections available for future work, including insect communication (Ordish 1992), systematics (e.g. David et al. 2003), and automated identification (Bennett et al. 2015). The BioAcoustica platform (Baker et al. 2015) is both a repository and analysis platform for bioacoustic collections: allowing collections to be available in perpetuity, and also facilitating complex analyses using the BioVeL cloud infrastructure (Vicario et al. 2011). The Global Cicada Sound Collection is a project to make recordings of the world's cicadas (Hemiptera: Cicadidae) available using open licences to maximise their potential for study and reuse. This first component of the Global Cicada Sound Collection comprises recordings made between 2006 and 2008 of Cicadidae in South Africa and Malawi.
This collection of sounds includes 219 recordings of 133 voucher specimens, comprising 42 taxa (25 identified to species, all identified to genus) from South Africa and Malawi. The recordings have been used to underpin work on the species limits of cicadas in southern Africa, including Price et al. (2007) and Price et al. (2010). The specimens are deposited in the Albany Museum, Grahamstown, South Africa (AMGS).
The harvesting of acoustic data as occurrence records by GBIF has been implemented by the Scratchpads Team at the Natural History Museum, London. This link increases the value of individual recordings and the BioAcoustica platform within the global infrastructure of biodiversity informatics by making specimen/occurence records from BioAcoustica available to a wider audience, and allowing their integration with other occurence datasets that also contribute to GBIF.
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