Please use this identifier to cite or link to this item:
http://hdl.handle.net/11667/132
Appears in Collections: | University of Stirling Research Data |
Title: | Guidelines for the use of acoustic indices in environmental research |
Creator(s): | Bradfer-Lawrence, Tom Gardner, Nick Bunnefeld, Lynsey Bunnefeld, Nils Willis, Stephen G Dent, Daisy H |
Contact Email: | tom.bradfer-lawrence@stir.ac.uk |
Keywords: | Acoustic Index Bioacoustics Ecoacoustics Sound recording Soundscape Landscape Biodiversity |
Date Available: | 1-Jul-2019 |
Citation: | Bradfer-Lawrence, T; Gardner, N; Bunnefeld, L; Bunnefeld, N; Willis, SG; Dent, DH (2019): Guidelines for the use of acoustic indices in environmental research. University of Stirling. Faculty of Natural Sciences. Dataset. http://hdl.handle.net/11667/132 |
Publisher: | University of Stirling. Faculty of Natural Sciences |
Dataset Description (Abstract): | Acoustic indices derived from remote audio recordings collected across a human-modified landscape in the Republic of Panama. Data set for "Guidelines for the use of acoustic indices in environmental research" published in the journal Methods in Ecology and Evolution. Abstract; 1. Ecoacoustics, the study of environmental sound, is a growing field with great potential for biodiversity monitoring. Audio recordings could provide a rapid, cost-effective monitoring tool offering novel insights into ecosystem dynamics. More than 60 acoustic indices have been developed to date, which reflect distinct attributes of the soundscape, (i.e. the total acoustic energy at a given location, including noise produced by animals, machinery, wind and rain). However, reported patterns in acoustic indices have been contradictory, possibly because there is no accepted best practice for the collection and analysis of audio recordings. 2. Here, we propose: (1) guidelines for designing studies using audio recordings for the rapid assessment of multiple sites, and (2) a workflow for comparing recordings with seven of the most commonly used indices, permitting discrimination among habitat-specific soundscapes. We collected and analysed over 26,000 hours of recordings from 117 sites across a range of habitats in a human-modified tropical landscape in central Panama; an order of magnitude more recordings than used in previously published studies. 3. We demonstrate that: (1) Standard error variance of indices stabilises within 120 hours of recordings from a single location. (2) Continuous recording should be used rather than sub-sample recording on a schedule; sub sampling is a common practice but delays capture of site variability and maximising total duration of recording should be prioritised. (3) Use of multiple indices to describe soundscape patterns reveals distinct diel and seasonal soundscape patterns among habitats. 4. We advocate collecting at least 120 hours of continuous recordings per site, and using a range of acoustic indices to categorise the soundscape, including the Acoustic Complexity Index, Acoustic Evenness Index, Acoustic Entropy Index and the Normalised Difference Soundscape Index. Differences among habitat types can be captured if multiple indices are used, and magnitude of variance is often more important than mean values. The workflow we provide will enable successful use of ecoacoustic techniques for environmental monitoring. |
Dataset Description (TOC): | Data set for "Guidelines for the use of acoustic indices in environmental research" published in the journal Methods in Ecology and Evolution. Each row holds the acoustic indices values for a 10-minute audio recording. Column headings; "Site" - 3 or 4 character site ID number where recording was collected; "Habitat" - habitat in which recording was collected; "Season" - 1 = Dry Season (Jan - May), 2 = Wet Season (June - Oct), "Deployment" - deployment number (some sites recorded twice); "Month" - calendar month; "Day.Date" - calendar day; "Hour" - hour on 24 hour clock; "Day.Number" - count of day of recording deployment; "Total.Days" - total number of days recording at each site (will be same as "Day.Number" unless this is second deployment); "Day.Rec.No" - 10-minute recording number within each day; Remaining columns are acoustic indices values - "ACImin" = Acoustic Complexity Index (value per minute of recording), "ADI" = Acoustic Diversity Index, "AEve" = Acoustic Evenness Index, "Bio" = Bioacoustic index, "H" = Acoustic Entropy Index, "M" = Median of amplitude envelope, "NDSI" = Normalised Difference Soundscape Index. |
Type: | dataset |
Contract/Grant Title: | Maintenance of tropical forest bird communities in human-modified landscapes |
Funder(s): | NERC - Natural Environment Research Council |
Contract/Grant Number: | 1672519 |
Geographic Location(s): | Republic of Panama |
Time Period: | 01/01/17 - 31/10/17 |
URI: | http://hdl.handle.net/11667/132 |
Rights: | Rights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/ |
Affiliation(s) of Dataset Creator(s): | University of Stirling (Biological and Environmental Sciences) Smithsonian Tropical Research Institute Durham University |
Files in This Item:
File | Description | Size | Format | |
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Bradfer-Lawrence et al 2019 MEE Acoustic indices data.csv | 16.75 MB | Unknown | View/Open |
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