An Introduction to Ecoacoustics

Farina, Almo; P, Li

doi:10.1007/978-3-030-82177-7_1

Cited by 2 publications

(2 citation statements)

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“…Sound frequencies of up to 10 kHz were considered to calculate the ADI; for the BI calculation, frequencies between 501 Hz and 10 kHz were considered; frequencies up to 1 kHz were considered for anthropophony, and frequencies ranging from 1 to 10 kHz for biophony to calculate the NDSI. We used the SonoScape software (Farina & Li, 2022) to calculate ACIf t (temporal signature). We set the time scale for 5 s and the near field parameter high to 0.1.…”

Section: Methodsmentioning

confidence: 99%

“…Using the sf package (Pebesma, 2018), we created a 600 m buffer around each point to summarize the calculated metrics and compare these buffers according to the metrics and their influence on the indices. Therefore, our analytical approach is to interpret the soundscape, one of the components of the sonic domain (Farina & Li, 2022). The buffer sizes used in our study are comparable to those used in similar studies, such as those that assess the effect of landscape structure on acoustic or diversity data.…”

Section: Land Use and Landscape Metricsmentioning

confidence: 99%

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Acoustic communities in an environmental gradient from native to urban areas in Central Brazil

Araujo,

Machado

2023

Austral Ecology

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As urban areas expand due to increasing human populations, natural habitats are diminishing in quantity and quality. We conducted a study to examine the response of diurnal acoustic communities along a gradient of environments, ranging from native to dense urban areas. We hypothesized that acoustic indices would decline with urbanization, transitioning from natural and rural areas to urban environments. We conducted the research in and around Brasília, Central Brazil. We deployed 24 digital recorders in native, rural, low‐density and high‐density urban areas. We employed five commonly used acoustic indices (ADI, ACI, NDSI, H and BI) to characterize the acoustic communities and represent the existing biodiversity numerically. We initially compared the index values across different land use types using a non‐parametric rank sum test. Subsequently, we selected eight landscape metrics and performed a principal component analysis to summarize the surrounding matrix at each sampling point. We then employed generalized linear models to determine if the acoustic indices exhibited the anticipated variations. The results indicated significant variations in all indices among the different land use types, indicating their responsiveness to distinct acoustic communities and environmental characteristics. ADI, H and NDSI exhibited declining values from native to urban areas, while ACI and BI displayed the opposite trend. These findings underscore the influence of landscape structure on acoustic indices. Consequently, we concluded that adopting appropriate landscape planning, mainly through integrating natural and urban areas, could help preserve biodiversity in tropical urban regions.

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Section: Methodsmentioning

confidence: 99%

Section: Land Use and Landscape Metricsmentioning

confidence: 99%