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Figure 2 in Variability in blue whale acoustic behavior off southern California

Figure 2. The percent of singular A (orange), singular B (blue), and D (green) call detections, and single (purple) and repetitive (maroon) AB phrase detections that occurred out of the total number of monthly detections at each of the four sites. Monthly detection totals are listed at the top of each bar. Periods shaded in gray indicate times when there was no data at that site.

Figure 3 in Variability in blue whale acoustic behavior off southern California

Figure 3. Residual plots of monthly variability for singular A (diamonds), singular B (squares), and D (circles) call detections (left panels), and single (upright triangles) and repetitive (downward triangles) AB phrase detections (right panels).

Figure 4 in Variability in blue whale acoustic behavior off southern California

Figure 4. Proportion of song consisting of each type per month at the inshore and offshore sites. Only months that contained identifiable song are included. No song was identified at the offshore sites in December 2009. Months when no data were available are marked in dark gray (Table 1).

Figure 1 in Variability in blue whale acoustic behavior off southern California

Figure 1. Percent of all song bouts recorded at the inshore and offshore sites comprised of the two blue whale phrase types between September 2009 and August 2010.

opencc-zeroFeb 2023View details →

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Data from: Acoustic indices estimate breeding bird species richness with daily and seasonally variable effectiveness in lowland temperate Białowieża forest

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.

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Killer whale acoustic patterns respond to prey abundance and environmental variability around the Prince Edward Islands, Southern Ocean

Killer whales are apex predators with temporally and spatially varying distributions throughout the world’s oceans. Their ecology and behaviour are poorly understood in most regions due to limited research, often because of logistical challenges. Here, we use easily deployable year-round passive acoustic monitoring device to investigate the seasonal acoustic occurrence and diel vocalizing behaviour of killer whales around the remote sub-Antarctic Prince Edward Islands (PEIs), Southern Ocean. Killer whales showed diel vocalizing patterns that varied seasonally in relation to their prey abundance and social activities. Killer whale calls were intermittently detected year-round with a high number of hours containing calls in October through December, and a secondary peak in March through May, which corresponded to the abundance of seal prey. Random forest modelling identified wind speed as an important predictor of the occurrence of killer whale calls whilst sea surface height, chlorophyll-a, and sea surface temperature were moderately important. We provide the first acoustic evidence that killer whale occurrence around PEIs coincide with variability in environmental conditions and prey abundance. Our results provide the first indication of diel vocalizing pattern of killer whales in the Southern Ocean. This knowledge is important for understanding killer whale ecology and adaptation to the changing oceans.

opencc-by-4.0Jun 2023View details →

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Data from: Environmental variability and acoustic signals: A multilevel approach in songbirds

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publicAug 2012View details →

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Data from: Acoustic indices estimate breeding bird species richness with daily and seasonally variable effectiveness in lowland temperate Białowieża forest

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publicFeb 2023View details →

FIGURES 40–53 in Review of the genus Taurotettix Haupt, 1929 (Homoptera: Cicadellidae: Deltocephalinae: Cicadulini): morphology, acoustic signals, and geographical variability

FIGURES 40–53. Taurotettix spp., male calling signal oscillograms, general view at low speed. 40–42―T. (T.) beckeri, 43– 48―T. (C.) modesta, 49–53―T. (C.) elegans elegans. Faster oscillograms of the parts of signals indicated as "54–69" are given under the same numbers. Scale mark at the bottom is the same for all oscillograms.

FIGURES 1–15 in Review of the genus Taurotettix Haupt, 1929 (Homoptera: Cicadellidae: Deltocephalinae: Cicadulini): morphology, acoustic signals, and geographical variability

FIGURES 1–15. Taurotettix spp., subgenital plates (1–2) and lateral view (3–15). 1, 3―T. (T.) beckeri, 4–7―T. (C.) modesta, 2, 8–11―T. (C.) elegans elegans, 12–15―T. (C.) elegans subornata. 3–8, 10–12, 14–15―males, 9, 13―females. Localities are given under the figures for taxa distributed in multiple regions.

FIGURES 54–69 in Review of the genus Taurotettix Haupt, 1929 (Homoptera: Cicadellidae: Deltocephalinae: Cicadulini): morphology, acoustic signals, and geographical variability

FIGURES 54–69. Taurotettix spp., male calling signal oscillograms, parts of signals at high speed. 54–57―T. (T.) beckeri, 58–62―T. (C.) modesta, 63–69―T. (C.) elegans elegans. Scale mark at the bottom is the same for all oscillograms.

FIGURES 16–39. Taurotettix spp., male genitalia. 16–17―T in Review of the genus Taurotettix Haupt, 1929 (Homoptera: Cicadellidae: Deltocephalinae: Cicadulini): morphology, acoustic signals, and geographical variability

FIGURES 16–39. Taurotettix spp., male genitalia. 16–17―T. (T.) beckeri, 18–27―T. (C.) modesta, 28–33―T. (C.) elegans elegans, 34–39―T. (C.) elegans subornata. 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38―penis, lateral view, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39―style, dorsal view. Localities are given under the figures for taxa distributed in multiple regions.