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openother-openOct 2020View details →

Utility of acoustic indices for ecological monitoring in complex sonic environments

Abstract With the continued adoption of passive acoustic monitoring as a tool for rapid and high-resolution ecosystem monitoring, ecologists are increasingly making use of a suite of acoustic indices to summarise the sonic environment. Though these indices are often reported to well represent some aspect of the biology of an ecosystem, the degree to which they are confounded by various extraneous sonic conditions is largely unknown. We conducted an aural inventory across 23 field sites in Okinawa to identify the number of unique animal sounds present in recordings. Using these values of ‘measured richness’, we then examined how the performance of 11 commonly-used acoustic indices varied across a range of sonic conditions (including in the presence and absence of insect stridulations, audible wind or rain, and human-related sounds). Our analysis identified both well- and poor-performing acoustic indices, as well as those that were particularly sensitive to sonic conditions. Only two indices reflected measured richness across the full range of sonic conditions examined. A few indices were relatively insensitive to extraneous sonic conditions, but no index correlated with measured richness when masked by sound from broadband stridulating insects. Our results demonstrate considerable sensitivity of most commonly used acoustic indices to confounding sonic conditions, highlighting the challenges of working with large acoustic datasets collected in the field. We make practical recommendations for acoustic index use based on study design, with the aim of identifying the suite of acoustic indices with greatest utility as indicators for rapid biodiversity monitoring and management of the world’s natural soundscapes. Methods The dataset contains the names of audio files collected across 23 field sites between April 2017 and January 2018 as part of the OKEON-Churamori project on the island of Okinawa, Japan. We conducted an aural inventory, manually counting and recording the number of unique biotic sounds (approximately corresponding to species richness) and noting the presence or absence of three potentially confounding sonic conditions: audible geophony (wind, rain etc.), anthropophony (human-related sounds), and broadband sounds produced by stridulating insect (e.g. cicadas, orthopterans). We then calculated 11 commonly used acoustic indices from the literature and compared their performance (correlation with richness) in the presence vs absence of each sonic condition. Our dataset also contains time and date information for each recording, and the mean site-level richness (i.e. across multiple recordings) for each site and for each unique site-by-season combination. See Table A2 and Methods section in the associated manuscript for details on data processing and the calculation of acoustic indices. Usage notes See readme file for descriptions of data table structure.

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Acoustic indices perform better when applied at ecologically meaningful time and frequency scales

Abstract: 1. Acoustic indices are increasingly employed in the analysis of soundscapes to ascertain biodiversity value. However, conflicting results and lack of consensus on best practices for their usage has hindered their application in conservation and land-use management contexts. Here we propose that the sensitivity of acoustic indices to ecological change and fidelity of acoustic indices to ecological communities are severely impacted by signal masking. Signal masking can occur when acoustic responses sensitive to the effect being monitored are masked by less sensitive acoustic groups, or target taxa sonification is masked by non-target noise. We argue that by calculating acoustic indices at ecologically appropriate time and frequency bins, masking effects can be reduced and the efficacy of indices increased. 2. We test this on a large acoustic dataset collected in Eastern Amazonia spanning a disturbance gradient including undisturbed, logged, burned, logged-and-burned, and secondary forests. We calculated values for two acoustic indices: the Acoustic Complexity Index and the Bioacoustic Index, across the entire frequency spectrum (0-22.1 kHz), and four narrower subsets of the frequency spectrum; at dawn, day, dusk and night. 3. We show that signal masking has a large impact on the sensitivity of acoustic indices to forest disturbance classes. Calculating acoustic indices at a range of narrower time-frequency bins substantially increases the classification accuracy of forest classes by random forest models. Furthermore, signal masking led to highly misleading correlations, including spurious inverse correlations, between biodiversity indicator metrics and acoustic index values compared to correlations derived from manual sampling of the audio data. 4. Consequently, we recommend that acoustic indices are calculated either at a range of time and frequency bins, or at a single narrow bin, predetermined by a priori ecological understanding of the soundscape.

opencc-zeroOct 2020View details →

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Data from: Acoustic identification of Mexican bats based on taxonomic and ecological constraints on call design

Monitoring global biodiversity is critical for understanding responses to anthropogenic change, but biodiversity monitoring is often biased away from tropical, megadiverse areas that are experiencing more rapid environmental change. Acoustic surveys are increasingly used to monitor biodiversity change, especially for bats as they are important indicator species and most use sound to detect, localise and classify objects. However, using bat acoustic surveys for monitoring poses several challenges, particularly in megadiverse regions. Many species lack reference recordings, some species have high call similarity or differ in call detectability, and quantitative classification tools, such as machine learning algorithms, have rarely been applied to data from these areas. Here, we collate a reference call library for bat species that occur in a megadiverse country, Mexico. We use 4685 search-phase calls from 1378 individual sequences of 59 bat species to create automatic species identification tools generated by machine learning algorithms (Random Forest). We evaluate the improvement in species-level classification rates gained by using hierarchical classifications, reflecting either taxonomic or ecological constraints (guilds) on call design, and examine how classification rate accuracy changes at different hierarchical levels (family, genus and guild). Species-level classification of calls had a mean accuracy of 66%, and the use of hierarchies improved mean species-level classification accuracy by up to 6% (species within families 72%, species within genera 71·2% and species within guilds 69·1%). Classification accuracy to family, genus and guild-level was 91·7%, 77·8% and 82·5%, respectively. The bioacoustic identification tools we have developed are accurate for rapid biodiversity assessments in a megadiverse region and can also be used effectively to classify species at broader taxonomic or ecological levels. This flexibility increases their usefulness when there are incomplete species reference recordings and also offers the opportunity to characterise and track changes in bat community structure. Our results show that bat bioacoustic surveys in megadiverse countries have more potential than previously thought to monitor biodiversity changes and can be used to direct further developments of bioacoustic monitoring programs in Mexico.

opencc-zeroDec 2015View details →

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Data from: Scale-dependent foraging ecology of a marine top predator modelled using passive acoustic data

1. Understanding which environmental factors drive foraging preferences is critical for the development of effective management measures, but resource use patterns may emerge from processes that occur at different spatial and temporal scales. Direct observations of foraging are also especially challenging in marine predators, but passive acoustic techniques provide opportunities to study the behavior of echolocating species over a range of scales. 2. We used an extensive passive acoustic dataset to investigate the distribution and temporal dynamics of foraging in bottlenose dolphins using the Moray Firth (Scotland, UK). Echolocation buzzes were identified with a mixture model of detected echolocation inter-click intervals, and used as a proxy of foraging activity. A robust modelling approach accounting for autocorrelation in the data was then used to evaluate which environmental factors were associated with the observed dynamics at two different spatial and temporal scales. 3. At a broad scale, foraging varied seasonally, and was also affected by sea-bed slope and shelf-sea fronts. At a finer scale, we identified variation in seasonal use and local interactions with tidal processes. Foraging was best predicted at a daily scale, accounting for site-specificity in the shape of the estimated relationships. 4. This study demonstrates how passive acoustic data can be used to understand foraging ecology in echolocating species, and provides a robust analytical procedure for describing spatio-temporal patterns. Associations between foraging and environmental characteristics varied according to spatial and temporal scale, highlighting the need for a multi-scale approach. Our results indicate that dolphins respond to coarser-scale temporal dynamics, but have a detailed understanding of finer-scale spatial distribution of resources.

opencc-zeroDec 2012View details →

Fig. 15 in Ecology, acoustics and chromosomes of the East African genus Afroanthracites Hemp & Ingrisch (Orthoptera, Tettigoniidae, Conocephalinae, Agraeciini) with the description of new species

Fig. 15 Power spectra of male calling songs of Afroanthracites species and of Afroagraecia brachyptera. a Species occurring syntopically at Lutindi. b Species occurring syntopically at Mazumbai. c Remaining species

Fig. 14 a in Ecology, acoustics and chromosomes of the East African genus Afroanthracites Hemp & Ingrisch (Orthoptera, Tettigoniidae, Conocephalinae, Agraeciini) with the description of new species

Fig. 14 a Correlation of mirror dimensions and b hind femur length with peak frequency of male calling song. Open symbols Afroagraecia brachyptera

Fig. 11 in Ecology, acoustics and chromosomes of the East African genus Afroanthracites Hemp & Ingrisch (Orthoptera, Tettigoniidae, Conocephalinae, Agraeciini) with the description of new species

Fig. 11 Isolated tegmina of Afroanthracites species and Afroagraecia brachyptera. Upper two lines—left tegmen, lower line—right tegmen. a A. usambaricus, b A. montium, c A. lutindi n. sp., d A. viridis, e A. pseudodiscolor n. sp., f A. discolor, g A. brachyptera. Scale=5 mm

Fig. 4 Male A. lutindi n in Ecology, acoustics and chromosomes of the East African genus Afroanthracites Hemp & Ingrisch (Orthoptera, Tettigoniidae, Conocephalinae, Agraeciini) with the description of new species

Fig. 4 Male A. lutindi n. sp., lateral view, note orange part of tenth abdominal tergite, orange clypeus and coloration of eyes and antennae

Fig. 7 in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 7 Basal part of tegmina in male Eurycorypha punctipennis Chopard, E. varia Brunner von Wattenwyl and E. resonans n. sp. (scale 5 mm)

Fig. 4 in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 4 Oscillograms of calling songs of Eurycorypha species, overview (one echeme in E. punctipennis and E. varia, sequence of two echemes in E. combretoides and E. resonans). In the male–female duet

Fig. 2 in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 2 Oscillograms presenting details of syllable structure in Eurycorypha resonans n. sp. (a part of syllable of disyllabic echeme; b one complete syllable from the polysyllabic echeme) and E. varia Brunner von Wattenwyl (c part of syllable)

Fig. 11 in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 11 Female abdominal apices of Eurycorypha species. a, b Eurycorypha punctipennis Chopard, lateral view on ovipositor (a), ventral view on subgenital plate (b). c, d Eurycorypha resonans n. sp., lateral view on ovipositor (c), ventral view on subgenital plate (d). e, f Eurycorypha conclusa n. sp, lateral view on ovipositor (e), ventral view on subgenital plate (f)

Fig. 13 East African Eurycorypha species. a–c in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 13 East African Eurycorypha species. a–c Eurycorypha meruensis Sjöstedt, southern slopes of Mount Kilimanjaro, Tanzania, 1430 m, banana–coffee plantation, male (a) and female (b), male nymph, fifth instar (c). d–f E. varia Brunner von Wattenwyl, southern slopes of Mount Kilimanjaro, Tanzania, 1710 m, lower border of montane forest, male (d), female (e), female nymph, fifth instar (f)

Fig. 12 in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 12 Nymphs of Eurycorypha species. a Ant-like stage of cf. E. combretoides n. sp. (third instar), savanna bushland, East Kilimanjaro. b Nymph of E. varia Brunner von Wattenwyl (probably fourth instar), southern slopes of Kilimanjaro, forest edge above Kidia, 1700 m

Fig. 9 East African Eurycorypha species. a in Biogeography, ecology, acoustics and chromosomes of East African Eurycorypha Stål species (Orthoptera, Phaneropterinae) with the description of new species

Fig. 9 East African Eurycorypha species. a Eurycorypha punctipennis Chopard, male, Msaranga valley, southern slopes of Mount Kilimanjaro. b Eurycorypha punctipennis Chopard, female, same locality as male. c Eurycorypha resonans n. sp., male, banana–coffee plantation, village Mahoma, southern slopes of Mount Kilimanjaro. d Eurycorypha resonans n. sp., female, same locality as male. e Eurycorypha combretoides n. sp., male, Chala area, savanna, East Kilimanjaro. f Ant- mimiking male nymph of E. combretoides n. sp. (fourth instar), collected on a bush of Maytenus senegalensis at eastern savanna area of Mount Kilimanjaro and reared to adult