Ecoacoustics Audio Analysis Software V18.03.0.41

Towsey, Michael; Truskinger, Anthony; Cottman-Fields, Mark; Roe, Paul

doi:10.5281/zenodo.1188744

Cited by 1 publication

(2 citation statements)

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“…In total we calculated different acoustic features using "Analysis Program" (Towsey et al, 2018) and the Bioacoustic Index (Boelman et al, 2007). Data preprocessing involved the package "stringr" (Wickham, 2019).…”

Section: Calculation and Selection Of Acoustic Indicesmentioning

confidence: 99%

“…We used "High Amplitude" and "Clipping Index" to identify recordings with very loud wind and rain noises and excluded all recordings with values > 0 from further analysis. False-Color-Spectrograms (Towsey et al, 2014(Towsey et al, , 2018 were produced to identify periods with strong rain and wind, which were additionally excluded from further analysis. We assumed that strong rain and strong wind events were identical for all plots.…”

Section: Calculation and Selection Of Acoustic Indicesmentioning

confidence: 99%

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Temporal Soundscape Patterns in a Panamanian Tree Diversity Experiment: Polycultures Show an Increase in High Frequency Cover

et al. 2022

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In this ecoacoustic study we used the setting of a tropical tree diversity planted forest to analyze temporal patterns in the composition of soundscapes and to test the effects of tree species richness on associated biodiversity measured as acoustic diversity. The analysis of soundscapes offers easy, rapid and sustainable methods when assessing biodiversity. During the last years the quantification of regional or global acoustic variability in sounds and the analysis of different soundscapes has been evolving into an important tool for biodiversity conservation, especially since case studies confirmed a relationship between land-use management, forest structure and acoustic diversity. Here we analyzed soundscapes from two seasons (dry and rainy season) and aurally inspected a subset of audio recordings to describe temporal patterns in soundscape composition. Several acoustic indices were calculated and we performed a correlation analysis and a non-metric multidimensional scaling analysis to identify acoustic indices that: (i) were complementary to each other and such represented different aspects of the local soundscapes and (ii) related most strongly to differences in acoustic composition among tree species richness, season and day phase. Thus, we chose “High Frequency Cover,” “Bioacoustic Index,” and “Events Per Second” to test the hypothesis that acoustic diversity increases with increasing tree species richness. Monocultures differed significantly from polycultures during night recordings, with respect to High Frequency Cover. This index covers sounds above 8 kHz and thus represents part of the orthopteran community. We conclude that increasing tree species richness in a young tropical forest plantation had positive effects on the vocalizing communities. The strongest effects were found for acoustic activity of the orthopteran community. In contrast to birds, orthopterans have smaller home ranges, and are therefore important indicator species for small scale environmental conditions.

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Section: Calculation and Selection Of Acoustic Indicesmentioning

confidence: 99%

Section: Calculation and Selection Of Acoustic Indicesmentioning

confidence: 99%