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Acoustic and temporal birdsong measurements

Cite this dataset

Kleyn, Tristan; da Cruz Kaizer, Mariane; Figueiredo Passos, Luiza (2020). Acoustic and temporal birdsong measurements [Dataset]. Dryad.


In tropical birds, survival is dependent on the ability to effectively communicate with others against a background of high ambient noise. The Acoustic Niche Hypothesis proposes that the deterrent selective force of signal masking has caused animals sharing a habitat to partition their calling behaviour amongst the acoustic bandwidths available, so as to minimise interference between one another. Whether and why species share the so-called ‘acoustic space’ remains a gap in our understanding of animal ecosystems. The aim of this study was to investigate differences between the acoustic structure of avian communities in two spatially distinct habitats in the montane tropical forests of the Caparaó National Park in south-eastern Brazil, and to test whether the distribution of birdsong at each conformed to the ANH. Birdsong from nine hours of passive acoustic recordings at each study site were analysed using principal component analyses. The results contradicted the ANH, revealing strikingly similar patterns of synchronised vocal behaviour. No correlation was evident between the acoustic and temporal partitioning behaviour of songbirds. This study provides a novel comparative analysis of the acoustic dynamics in two separate and diverse avian communities and support for theories of synchronized vocal behaviour in such groups.


Sound recordings used for this study were recorded by MCK in January and March of 2017 using four autonomous recording units (ARU) (SongMeter SM3, Wildlife Acoustics Inc., Concord, MA, USA) deployed across a "listening post" in Aleixo Valley and another in Santa Marta Valley(20°28'46.49" S, 41°50'25.00" W and 20°29'25.74"S, 41°44'21.55"W). Each listening post comprised of two SongMeters fixed 1.8 m above ground, each attached to two microphones, facing opposite directions and thus recording in the four cardinal directions (Figure 2). Recordings were sampled at 44.1 kHz and 16 bits per second and recorded in 1-hour segments. A high-pass filter was set at 220 Hz to filter out wind and river noise. Recordings from the two SongMeters at each post were time-synchronized using Garmin GPS’s to triangulate the sound source. Three hours of recording from 0800 to 1100 on three consecutive days were used from each site to investigate the singing avian communities. The nine hours of recording taken from each study site combined for a total of 18 hours of recording for this study. Analysis was carried out in Raven Pro and R Studio. 

Usage notes

Recordings from earlier in the morning during the dawn chorus were orginially intended for use but were omitted to dominant cicada noise. IMPORTANT: pathnames for csv files to be read must be filled in to run analysis R Scripts (see metadata README).