DOI: 10.5061/dryad.zcrjdfnhc
title: Data from: Acoustic indices estimate breeding bird species richness with daily and seasonally variable effectiveness in lowland temperate Białowieża forest

description: Biodiversity monitoring is important to follow temporal changes of the
 environment. We examined whether acoustic indices can be used as a rapid
 and easy-to-apply tool for bird biodiversity estimation in one of the
 least changed European lowland forests – the Białowieża Forest. We
 collected soundscape recordings in early and late spring at 84 randomly
 chosen recording points. At each recording point, we analysed 72 1-min
 sound samples to evaluate how well acoustic indices predict bird species
 richness from the perspective of a single sound sample, single survey, and
 recording point, and how they follow the daily pattern of singing
 activity. For each 1-min sound sample, we prepared a list of vocalizing
 bird species and calculated three acoustic indices: Bioacoustic Index
 (BI), Acoustic Complexity Index (ACI), and Acoustic Diversity Index (ADI).
 We found that from the perspective of a single 1-min sound sample, BI best
 predicts the bird species richness, independently of time in the season
 but variably across the day, while ACI and ADI showed weaker and
 seasonally and daily variable dependency. The correlation between each
 index and the number of bird species was stronger in the early survey than
 in the late survey.  All acoustic indices followed daily bird
 activity patterns, yet they provided greater values before the peak of the
 species richness estimated by manual spectrogram scanning and listening to
 recordings. We showed that acoustic indices correlate moderately to
 strongly with the bird species richness obtained by manual spectrogram
 scanning and listening to recordings by humans. Therefore, acoustic
 indices can be used as a tool for rapid estimation of bird biodiversity in
 temperate forests. However, daily and seasonal variation in effectiveness
 of acoustic indices should be taken into account in the analysis.
description: 84 recording points were
 randomly selected in Białowieża Forest District. Points were located both
 in protected and unprotected areas. The distance between neighbouring
 recording points ranged from 470 to 1,180m. At each recording point, we
 recorded a soundscape twice in the breeding season: once between April 20
 and May 02, 2021 (early survey) and once between May 18 and May 26, 2021
 (late survey). During each survey, we recorded a soundscape from two hours
 before sunrise to four hours after sunrise. We used 10 Song Meter SM3
 acoustic recorders (Wildlife Acoustics) equipped with one omnidirectional
 microphone SMM-A1 (sensitivity -11 +/- 4 dB; signal-to-noise ratio
 &gt; 68 dB). The recording microphones were checked by using VOLTCRAFT
 SLC-100 sound level calibrator. We recorded mono .wav files (1-hour
 duration, 48kHz/16 bit sampling rate, low and high frequency filters off,
 gain 24 dB).  From the soundscape recordings, we analysed
 1-min every 10 minutes (6 minutes per hour, 36 minutes per survey per
 recording point). 1-min sound samples were analysed by manual scanning and
 listening to recordings, in Raven Pro 1.6.1 software (Cornell Lab of
 Ornithology) with the following settings: Window = Hamming, window size =
 23.1 ms, Overlap = 75%. We compiled a list of bird species recorded in
 each 1-min sound sample. For each 1-min sound sample we calculated
 acoustic indices using Kaleidoscope Pro 5.4.7 software (Wildlife
 Acoustics): Bioacoustic Index (BI) – settings: minimal frequency Fmin=500 Hz,
 Fmax=10 000 Hz, FFT=1,024 samples; 
 Acoustic Complexity Index (ACI)
 – settings: minimal
 frequency Fmin=500 Hz, Fmax=10 000 Hz, J=5s; 
 Acoustic Diversity Index
 (ADI) – settings: minimal
 frequency Fmin=500 Hz, Fmax=10 000 Hz, frequency step=500 Hz,
 threshold=-50 dB.
description: The S1Dataset.xlsx file
 contains:  
 Recording points distribution: ID of recording points,
 coordinates of each recording point, altitude, date of recording (one
 morning at each point during early and late survey);
 List of detected bird
 species: list of bird species detected during the
 study; 1-min sound sample: recording point ID, 1-min
 sound sample corresponding to wav file name, survey (early or late),
 minute in survey (Ordinal variable describing the order of 1-min sound
 sample at point during a day), number of bird species detected in 1-min
 sound sample by manual spectrogram scanning and listening to recordings,
 values of Bioacoustic Index (BI), Acoustic Complexity Index (ACI) and
 Acoustic Diversity Index (ADI) calculated for each 1-min sound
 sample; Survey: recording point ID, survey (early or
 late), total number of bird species detected manually during single survey
 at recording point, average number of bird species detected manually
 during survey at recording point (sum of bird species detected in each
 1-min sound sample divided by the number of 1-min sound samples analysed
 during single survey equal 36); mean BI, ACI, ADI for a single survey
 (average values for 36 1-min sound samples analysed during single survey
 per recording point); Recording point: recording point ID, total
 number of bird species detected manually during early and late survey at
 recording point, average number of bird species detected manually during
 early and late survey at recording point (sum of bird species detected in
 each 1-min sound sample divided by the number of 1-min sound samples
 analysed during early and late survey equal 72); mean BI, ACI, ADI for for
 recording point (average values for 72 1-min sound samples analysed during
 early and late survey at recording point).