Data
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/ff2e9ab&rft.title=Nocturnal soundscapes&rft.identifier=RDM ID: 30914434-fbd0-484d-aa98-170076294e97&rft.publisher=The University of Queensland&rft.description=Passive acoustic monitoring was conducted at twelve forest sites in southeast Queensland across two seasons (winter and summer) using BAR-LT recorders with omnidirectional microphones. Recorders captured nightly soundscapes over 30 consecutive days per season, from 7:00 PM to 3:00 AM. From these recordings, 210 one-minute audio files per season were randomly selected and manually analysed to identify distinct sonotypes through auditory inspection and spectrogram analysis. Five acoustic indices (ACI, AEI, BI, H, and SPL) were calculated to quantify soundscape variation. Statistical analyses included Mann–Whitney U tests for seasonal differences, Spearman’s rank correlations, and GLMMs with a negative binomial distribution to assess relationships between acoustic indices and sonotype richness. This dataset includes two folders, “summer” and “winter,” each containing the 210 one-minute files used for sonotype identification and index calculation, along with a CSV file of sonotype counts, the final dataset used in the analysis, and the R script used to run all analyses. Further details are provided in the accompanying README.txt file.&rft.creator=Dr Berndt Janse Van Rensburg&rft.creator=Dr Berndt Janse Van Rensburg&rft.date=2025&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Ecology&rft_subject=BIOLOGICAL SCIENCES&rft.type=dataset&rft.language=English Access the data

Contact Information

s4613633@student.uq.edu.au
School of the Environment

Full description

Passive acoustic monitoring was conducted at twelve forest sites in southeast Queensland across two seasons (winter and summer) using BAR-LT recorders with omnidirectional microphones. Recorders captured nightly soundscapes over 30 consecutive days per season, from 7:00 PM to 3:00 AM. From these recordings, 210 one-minute audio files per season were randomly selected and manually analysed to identify distinct sonotypes through auditory inspection and spectrogram analysis. Five acoustic indices (ACI, AEI, BI, H, and SPL) were calculated to quantify soundscape variation. Statistical analyses included Mann–Whitney U tests for seasonal differences, Spearman’s rank correlations, and GLMMs with a negative binomial distribution to assess relationships between acoustic indices and sonotype richness. This dataset includes two folders, “summer” and “winter,” each containing the 210 one-minute files used for sonotype identification and index calculation, along with a CSV file of sonotype counts, the final dataset used in the analysis, and the R script used to run all analyses. Further details are provided in the accompanying README.txt file.

Issued: 2025

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local : UQ:289097

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