Accounting for both automated recording unit detection space and signal recognition performance in acoustic surveys: A protocol applied to the cryptic and critically endangered Night Parrot (Pezoporus occidentalis). (3rd December 2021)
- Record Type:
- Journal Article
- Title:
- Accounting for both automated recording unit detection space and signal recognition performance in acoustic surveys: A protocol applied to the cryptic and critically endangered Night Parrot (Pezoporus occidentalis). (3rd December 2021)
- Main Title:
- Accounting for both automated recording unit detection space and signal recognition performance in acoustic surveys: A protocol applied to the cryptic and critically endangered Night Parrot (Pezoporus occidentalis)
- Authors:
- Leseberg, Nicholas P.
Venables, William N.
Murphy, Stephen A.
Jackett, Nigel A.
Watson, James E. M. - Abstract:
- Abstract: Research into the suitability of autonomous recording units (ARUs) when surveying for vocal species is increasing. Simultaneously, there has been extensive research into methods for efficiently extracting signals of interest from the acoustic data sets that accrue from the deployment of ARUs. For some species, bioacoustic monitoring supported by computerised signal detection offers the only effective and efficient method for widespread survey. In these circumstances, the detection space of both the ARU and the performance of the signal detection process must be considered concurrently, but typically, these two elements have been considered separately. Here, using the Night Parrot ( Pezoporus occidentalis ) as a case study, we consider both ARU detection space and the signal detection process to develop a robust and repeatable survey protocol for the species. After developing a call recogniser for the Night Parrot, we test its performance on a data set of Night Parrot calls given at a known distance from an array of ARUs. Having established a relationship between ARU type, recogniser performance and distance, we determine the sampling radius of an ARU for a given recogniser score cut‐off, and the associated probability of detecting a Night Parrot that calls within that sampling radius. Using these data, we outline how to develop a robust and repeatable survey protocol for the Night Parrot, with a defined probability of detection. This protocol could be adapted forAbstract: Research into the suitability of autonomous recording units (ARUs) when surveying for vocal species is increasing. Simultaneously, there has been extensive research into methods for efficiently extracting signals of interest from the acoustic data sets that accrue from the deployment of ARUs. For some species, bioacoustic monitoring supported by computerised signal detection offers the only effective and efficient method for widespread survey. In these circumstances, the detection space of both the ARU and the performance of the signal detection process must be considered concurrently, but typically, these two elements have been considered separately. Here, using the Night Parrot ( Pezoporus occidentalis ) as a case study, we consider both ARU detection space and the signal detection process to develop a robust and repeatable survey protocol for the species. After developing a call recogniser for the Night Parrot, we test its performance on a data set of Night Parrot calls given at a known distance from an array of ARUs. Having established a relationship between ARU type, recogniser performance and distance, we determine the sampling radius of an ARU for a given recogniser score cut‐off, and the associated probability of detecting a Night Parrot that calls within that sampling radius. Using these data, we outline how to develop a robust and repeatable survey protocol for the Night Parrot, with a defined probability of detection. This protocol could be adapted for other scenarios where deployment of ARUs is necessary to determine a species' status and distribution. Abstract : Automated recording unit (ARU) detection radii for different ARU types, specified values of recall and recogniser score cutoff. … (more)
- Is Part Of:
- Austral ecology. Volume 47:Number 2(2022)
- Journal:
- Austral ecology
- Issue:
- Volume 47:Number 2(2022)
- Issue Display:
- Volume 47, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 47
- Issue:
- 2
- Issue Sort Value:
- 2022-0047-0002-0000
- Page Start:
- 440
- Page End:
- 455
- Publication Date:
- 2021-12-03
- Subjects:
- acoustic monitoring -- automated recording unit -- bioacoustics -- call recogniser -- night parrot
Ecology -- Southern Hemisphere -- Periodicals
Ecology -- Australia -- Periodicals
557 - Journal URLs:
- http://www.blackwell-synergy.com/loi/aec ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/aec.13128 ↗
- Languages:
- English
- ISSNs:
- 1442-9985
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1793.105000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21054.xml