Insect Sounds Research Articles

Towards acoustic monitoring of bees: wingbeat sounds are related to species and individual traits.

Global pollinator decline urgently requires effective methods to assess their trends, distribution and behaviour. Passive acoustics is a non-invasive and cost-efficient monitoring tool increasingly employed for monitoring animal communities. However, insect sounds remain highly unexplored, hindering the application of this technique for pollinators. To overcome this shortfall and support future developments, we recorded and characterized wingbeat sounds of a variety of Iberian domestic and wild bees and tested their relationship with taxonomic, morphological, behavioural and environmental traits at inter- and intra-specific levels. Using directional microphones and machine learning, we shed light on the acoustic signature of bee wingbeat sounds and their potential to be used for species identification and monitoring. Our results revealed that frequency of wingbeat sounds is negatively related with body size and environmental temperature (between-species analysis), while it is positively related with experimentally induced stress conditions (within-individual analysis). We also found a characteristic acoustic signature in the European honeybee that supported automated classification of this bee from a pool of wild bees, paving the way for passive acoustic monitoring of pollinators. Overall, these findings confirm that insect sounds during flight activity can provide insights on individual and species traits, and hence suggest novel and promising applications for this endangered animal group. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Enhancing Insect Sound Classification Using Dual-Tower Network: A Fusion of Temporal and Spectral Feature Perception

In the modern field of biological pest control, especially in the realm of insect population monitoring, deep learning methods have made further advancements. However, due to the small size and elusive nature of insects, visual detection is often impractical. In this context, the recognition of insect sound features becomes crucial. In our study, we introduce a classification module called the “dual-frequency and spectral fusion module (DFSM)”, which enhances the performance of transfer learning models in audio classification tasks. Our approach combines the efficiency of EfficientNet with the hierarchical design of the Dual Towers, drawing inspiration from the way the insect neural system processes sound signals. This enables our model to effectively capture spectral features in insect sounds and form multiscale perceptions through inter-tower skip connections. Through detailed qualitative and quantitative evaluations, as well as comparisons with leading traditional insect sound recognition methods, we demonstrate the advantages of our approach in the field of insect sound classification. Our method achieves an accuracy of 80.26% on InsectSet32, surpassing existing state-of-the-art models by 3 percentage points. Additionally, we conducted generalization experiments using three classic audio datasets. The results indicate that DFSM exhibits strong robustness and wide applicability, with minimal performance variations even when handling different input features.

The incidence of bird sounds, and other categories of non-focal sounds, confound the relationships between acoustic indices and bird species richness in southern China

The analysis of audio recordings through acoustic indices has been proposed as an efficient way to measure and monitor biodiversity, given the assumption that higher levels of biodiversity produce more rapidly-changing and complex sound. However, in previous work in south China, we have found only moderate correlations between the acoustic indices and bird species richness, when analyzing recordings that were made at the same time as conducting point counts of birds. Here, we extended that work in three study regions in Guangxi Province, making observations both inside relatively undisturbed forest reserves and in the surrounding agricultural lands. We found that of 42 correlations between bird species richness and the acoustic indices (seven commonly used acoustic indices [ACI, ADI, AEI, AR, BIO, H, NDSI] each calculated in six habitat/region combinations) only seven had even a moderate relationship (i.e., |r| ≥ 0.20). To understand this paucity of relationships, we listened to a subsample of the recordings, scoring them for various kinds of biophony (incidence of bird and insect sounds), anthropophony (incidence of observer-produced sounds, sounds made by other humans, and sounds made by machines) and geophony (primarily wind, occasionally water). These analyses found that insects were positively related to the acoustic indices, especially in forests. Moreover, anthropophony and geophony, were, in general, negatively correlated to the indices. The incidence of bird vocalizations also had consistent and strong correlations to the residuals of the models relating the acoustic indices to bird species richness, demonstrating that the indices are clearly sensitive to the amount of bird sounds, but that is not necessarily strongly correlated to bird diversity. Multivariate models confirmed that the amounts of different sound categories were more influential on the acoustic indices than bird species richness. Our results demonstrate how competing noises, in both relatively undisturbed environments and heavily modified ones, can confound relationships between the acoustic indices and biodiversity. We discuss possible remedial steps for using acoustic indices in noisy soundscapes, including tailoring the selection of indices and frequency bands for the objectives of the project, or, alternatively, using a big-data approach that combines multiple indices.

Adaptive representations of sound for automatic insect recognition.

Insect population numbers and biodiversity have been rapidly declining with time, and monitoring these trends has become increasingly important for conservation measures to be effectively implemented. But monitoring methods are often invasive, time and resource intense, and prone to various biases. Many insect species produce characteristic sounds that can easily be detected and recorded without large cost or effort. Using deep learning methods, insect sounds from field recordings could be automatically detected and classified to monitor biodiversity and species distribution ranges. We implement this using recently published datasets of insect sounds (up to 66 species of Orthoptera and Cicadidae) and machine learning methods and evaluate their potential for acoustic insect monitoring. We compare the performance of the conventional spectrogram-based audio representation against LEAF, a new adaptive and waveform-based frontend. LEAF achieved better classification performance than the mel-spectrogram frontend by adapting its feature extraction parameters during training. This result is encouraging for future implementations of deep learning technology for automatic insect sound recognition, especially as larger datasets become available.

Cryptic insect soundscapes: Ecological sound art as a prompt for auralization

Much insect sounding is beyond the limits of typical human hearing ability. This sonic separation is exacerbated by a socialized narrative of fear and avoidance of insects in many western societies. With the use of audio technologies to expand our senses, we can embrace opportunities to get to know sensory and communicative insect sound-worlds beyond our own. Ecological sound art – sound art that has an environmentalist intent – is a tangible and accessible means of listening to these sounds. In the series Built Hidden Soundscapes, the primary author (Schonberg) composes imagined soundscapes existing solely of sounds that are beyond the limits of typical human hearing ability. In this article we introduce two compositions in this series, Reserva Florestal Adolpho Ducke and Pipeline Road. These compositions offer a temporary expansion of our aural senses that can increase listeners’ awareness of cryptic insect existences/ecologies. We suggest that this listening practice might prompt future auralization (sounding or hearing in the mind) of insect sound for the listener.

Approximation of Aperiodic Signals Using Non-Integer Harmonic Series: The Generalized NAFASS Approach

In this paper, the non-orthogonal amplitude-frequency analysis of smoothed signals (NAFASS) method) is used to approximate discrete aperiodic signals from various complex systems with the non-integer harmonic series (NIHS). When approximating by the NIHS, there is a problem in determining the dispersion law for harmonic frequencies. In the original version of the NAFASS approach, the frequency dispersion law was determined from a linear-difference equation. However, many complex systems in nature have frequency distributions that differ from the linear law, which is used in the conventional Fourier analysis of periodic signals. This paper proposes a generalization of the NAFASS method for describing aperiodic signals by the NIHS with a frequency distribution that satisfies a recursive formula, which coincides with the local generalized geometric mean (GGM). The methodology of the generalized NAFASS method is demonstrated using descriptions of financial data (prices for metals) and sound data (sounds of insects) as examples. The results show the effectiveness of the generalized NAFASS approach for describing real-world time data. This discovery allows us to propose a new classification scheme for smoothed and aperiodic signals captured as responses and envelopes from various complex systems.

Effects of Soundscapes on Human Physiology and Psychology in Qianjiangyuan National Park System Pilot Area in China

The development of China’s national parks is still in the initial stage, and few scholars have studied the effects of soundscapes on human physiology and psychology from the perspective of the auditory senses in national parks. In this study, the Qianjiangyuan National Park System Pilot Area was taken as the research subject, physiological indicators of subjects were collected through a biopAC-MP150 multi-channel physiological instrument data platform, and the subjective psychological response of soundscapes was measured using a Likert scale. The results showed that the sound of water had the most significant effect on the heart rate and respiratory rate of the subjects. Agricultural sound had the greatest impact on the skin conduction levels, while conversation had the least overall impact on human physiology. There were significant differences in comfort, excitement, and significance among the different soundscapes (p < 0.001). The sounds of insects are more likely to elicit feelings of comfort and excitement, while the sounds of birds are more likely to arouse curiosity. No significant correlation was observed between the physiological indices and psychological indices. The study on the effects of different soundscapes on human physiology and psychology in China’s national parks will provide a basis for the decision makers of national parks to formulate more effective planning, design, and management policies regarding soundscapes.

Hierarchical classification of pollinating flying insects under changing environments

Automatic monitoring of flying insects enables quick and efficient observations and management of ecologically and economically important targets such as pollinators, disease vectors, and agricultural pests. Studies on this topic mainly cover the tasks of detection and identification or classification, the latter often guided by the flight sounds of insects. This paper uses domain knowledge and taxonomy information to classify bee and wasp species based on abiotic variables and wing-beat data that change depending on climatic-environmental conditions. We survey the state-of-the-art in hierarchical classification and evaluate the most popular local and global methods for this task on flight data from nine hymenopteran species. We collected the data in Brazilian fields employing an inexpensive optical sensor. Our results show that it is possible to hierarchically classify groups of specimens per species, species, and groups of species according to their wing-beat data at different temperature and relative humidity levels with at least 91% accuracy. Besides benefiting research aimed at building insect classifiers adaptable to natural variations in the environment, this study is a vital step in a series of efforts to design non-invasive species monitoring techniques.

Project Review: SwampScapes

Project Review: <i>SwampScapes</i>

Classification of singing insect sounds with convolutional neural network

Classification of singing insect sounds with convolutional neural network

Acceptability and appeal: How visitors’ perceptions of sounds can contribute to shared learning and transdisciplinary protected area governance

This paper demonstrates how protected area (PA) acoustic environments , or soundscapes, can provide a boundary object for transdisciplinary conservation governance, informing and facilitating better communication, transdisciplinary learning, and decision making. Through visitor intercepts and on-site listening exercises (N = 899), research examined the appeal and acceptability of perceived sounds, to understand the congruence between visitors’ ratings for the ten open-coded sound categories that emerged. Discussion presents a hypothetical transdisciplinary governance scenario demonstrating how actors can employ similar research to advance collaborative transdisciplinary conservation learning and governance, through collaborative consideration of emergent trends across sound categories and local, national, and international tourist visitor groups. For example, all participants frequently observed Birds, Forest, and Water sounds, as highly appealing and acceptable. This aligns well with core natural PA attributes and conservation objectives. Wind and Insect sounds were less appealing, particularly for international tourists; yet considered acceptable within the PA, for all groups. Perhaps divergence can be addressed through programming and/or infrastructure. Low acceptability for Machine sounds should concern conservation governance; participants seemingly did not connect machine sounds with important PA conservation practices. • Soundscape research can assist collaborative stakeholder ecological governance and learning. • Research employs soundscape acceptability/appeal measures for transdisciplinary governance. • Assessing congruence in acceptability and appeal helps gauge visitor understanding of PA values. • Better visitor understanding/education around human-nature soundscape relationships is needed.

Multiple constraints on urban bird communication: both abiotic and biotic noise shape songs in cities.

Ambient noise can cause birds to adjust their songs to avoid masking. Most studies investigate responses to a single noise source (e.g., low-frequency traffic noise, or high-frequency insect noise). Here, we investigated the effects of both anthropogenic and insect noise on vocalizations of four common bird species in Hong Kong. Common Tailorbirds (Orthotomus sutorius) and Eurasian Tree Sparrows (Passer montanus) both sang at a higher frequency in urban areas compared to peri-urban areas. Red-whiskered Bulbuls (Pycnonotus jocosus) in urban areas shifted the only first note of their song upwards. Swinhoe’s White-eye (Zosterops simplex) vocalization changes were correlated with noise level, but did not differ between the peri-urban and urban populations. Insect noise caused the Eurasian Tree Sparrow to reduce both maximum, peak frequency, and overall bandwidth of vocalizations. Insect noise also led to a reduction in maximum frequency in Red-whiskered bulbuls. The presence of both urban noise and insect noise affected the sound of the Common Tailorbirds and Eurasian Tree Sparrows; in urban areas, they no longer increased their minimum song frequency when insect sounds were also present. These results highlight the complexity of the soundscape in urban areas. The presence of both high- and low-frequency ambient noise may make it difficult for urban birds to avoid signal masking while still maintaining their fitness in noisy cities.

Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management.

Simple SummaryA variety of different acoustic devices has been commercialized for detection of hidden insect infestations in stored products, trees, and soil, including a recently introduced device demonstrated in this report to successfully detect rice weevil immatures and adults in grain. Several of the systems have incorporated digital signal processing and statistical analyses such as neural networks and machine learning to distinguish targeted pests from each other and from background noise, enabling automated monitoring of the abundance and distribution of pest insects in stored products, and potentially reducing the need for chemical control. Current and previously available devices are reviewed in the context of the extensive research in stored product insect acoustic detection since 2011. It is expected that further development of acoustic technology for detection and management of stored product insect pests will continue, facilitating automation and decreasing detection and management costs.Acoustic technology provides information difficult to obtain about stored insect behavior, physiology, abundance, and distribution. For example, acoustic detection of immature insects feeding hidden within grain is helpful for accurate monitoring because they can be more abundant than adults and be present in samples without adults. Modern engineering and acoustics have been incorporated into decision support systems for stored product insect management, but with somewhat limited use due to device costs and the skills needed to interpret the data collected. However, inexpensive modern tools may facilitate further incorporation of acoustic technology into the mainstream of pest management and precision agriculture. One such system was tested herein to describe Sitophilus oryzae (Coleoptera: Curculionidae) adult and larval movement and feeding in stored grain. Development of improved methods to identify sounds of targeted pest insects, distinguishing them from each other and from background noise, is an active area of current research. The most powerful of the new methods may be machine learning. The methods have different strengths and weaknesses depending on the types of background noise and the signal characteristic of target insect sounds. It is likely that they will facilitate automation of detection and decrease costs of managing stored product insects in the future.

Subjective Salience of Birdsong and Insect Song with Equal Sound Pressure Level and Loudness.

Birdsong is used to communicate the position of stairwells to visually impaired people in train stations in Japan. However, more than 40% of visually impaired people reported that such sounds were difficult to identify. Train companies seek to present the sounds at a sound pressure level that is loud enough to be detected, but not so loud as to be annoying. Therefore, salient birdsongs with relatively low sound pressure levels are required. In the current study, we examined the salience of different types of birdsong and insect song, and determined the dominant physical parameters related to salience. We considered insect songs because both birdsongs and insect songs have been found to have positive effects on soundscapes. We evaluated subjective saliences of birdsongs and insect songs using paired comparison methods, and examined the relationships between subjective salience and physical parameters. In total, 62 participants evaluated 18 types of bird songs and 16 types of insect sounds. The results indicated that the following features significantly influenced subjective salience: the maximum peak amplitude of the autocorrelation function, which signifies pitch strength; the interaural cross-correlation coefficient, which signifies apparent source width; the amplitude fluctuation component; and spectral content, such as flux and skewness.

Performance of a Low-Cost Acoustic Insect Detector System with Sitophilus oryzae (Coleoptera: Curculionidae) in Stored Grain and Tribolium castaneum (Coleoptera: Tenebrionidae) in Flour.

Reduction of postharvest losses is gaining increased priority in warm regions where insect infestation may cause rapid deterioration of staple commodities. Acoustic detection can be used to assess the likelihood of insect infestations in bags of grain, flour, and other commodities that are stored in small holdings in developing countries, enabling rapid targeting of treatments. A portable postharvest insect detection system was developed with the goal to provide low-cost capability to acoustically assess infestations in small-scale storage facilities. Electret microphones input pest insect sounds to a 32-bit microcontroller platform that digitized and stored the signals on a digital memory card transferable to a portable laptop computer. The insect sounds then were analyzed by custom-written software that matched their spectra to those of known pests. Infestations of Sitophilus oryzae (L) in 2.6-kg bags could be detected down to densities of 1.9 adults/kg in grain and Tribolium castaneum (Herbst) down to 3.8 adults/kg in flour in laboratory settings. Also, differences in the rates of sounds per insect in treatments with different numbers ranging from 5 to 50 insects suggested that the sound rates of adults of different species at different population densities may be noticeably affected by aggregation pheromones or other behaviorally active semiochemicals. Further testing is needed but previous experience with acoustic detection systems suggests that the prototype has potential for use in small storage facilities where early detection of infestations is difficult to provide.

Dung beetle distress signals may be correlated with sex and male morph: a case study on Copris lunaris (Coleoptera: Scarabaeidae, Coprini)

ABSTRACT Insect sounds are predominantly produced by stridulations, where specialised body parts contact repeatedly to induce acoustic pulse trains. We studied the stridulatory organ and sound emissions in Copris lunaris, by focussing separately on females, and on major and minor males. Results highlighted an isometric growth of pars stridens in response to body size, and identified a wing-pygidium locking structure that assists sound emission. Sex-specific acoustic differences of some degree were detected between major males and females, as sounds emitted by majors showed higher frequencies and shorter pulses with elevated impulse rates. This cannot be immediately explained by size differences in the components of stridulatory apparatus. Rather, divergence might be an indicator of some underlying behavioural difference in response to distressing events. In minor males, acoustic properties overlapped with both females and major males, although incomplete stridulations had a lower ratio in minor than major males. This paper provides the very first perspective of the potential role of sex and male polymorphism on sound production. However, future categorisations of sounds coupled to behavioural observations of specific interactions are needed to reveal the function of sex and morph-specific differences.

Преподавание японского языка через призму зооморфной метафор

In this article, the author proposes a method for the consistent acquaintance of Russian students studying the Japanese language by way of zoonymes and zoomorphic metaphors based on the example of the transcription of Aesop’s fable “The Dragonfly and the Ant”. In the Japanese transcription, instead of the zoonyme “dragonfly”, another zoonyme “grasshopper” is used. In addition, in Japanese linguistic culture, there are two versions of the fable. In one version, the ants refuse to help the grasshopper, and he dies. In another version, the ants help the grasshopper, and he lives through the winter with the ants and plays the violin. A type of entertainment that has existed for a long time in traditional Japanese culture is to listen to the sounds of insects. In modern-day Japan, there is a subculture of kirigirisu, the culture of street musicians, which entertain listeners. Besides, some even choose cosplay costumes in order to dress up as a grasshopper. The teaching method consists of several stages: - Introduction of a zoonyme (its meanings and spelling options); - Explanation of its significance in Japanese linguistic culture; - Descriptions of associations connected with this zoonyme in Japanese linguistic culture; - The use of the zoonyme in its direct meaning; - The use of the zoonyme as a metaphor in phrases, sentences and proverbs. The teaching of zoonymes and zoomorphic metaphors has both an applied and theoretical significance. In applied terms, it will help students who study Japanese learn more about Japanese linguistic culture; to get acquainted with the legends and traditions connected with these insects; to understand the associations that exist in Japanese society in connection with these insects; to learn the use of zoonymes in direct and figurative meanings in phrases and sentences, as well as to understand idioms in which the names of the insects are used. In theoretical terms, learning zoonymes will help students to understand Japanese linguistic culture and the essence of metaphorical meanings on the basis of examples of a non-native language. The proposed method can be used to get acquainted with any zoonymes and zoomorphic metaphors.

A transdisciplinary consideration of sand flies & leishmaniasis

A transdisciplinary consideration of sand flies & leishmaniasis

Intelligent Technology for the Monitoring and Protection of Insect Biodiversity

Monitoring and identification are vitally important to insect biodiversity conservation and protection. As a popular and comparatively well known order, Lepidoptera (moths and butterflies) are good indicators of insect biodiversity. Through much research and testing, a reliable image recognition method and online software were developed. The method includes a color histogram and dual tree complex wavelet transform (DTCWT), local mean color feature based method, sparse coding and scale conjugate gradient (SCG) back propagation neural network (BPNN), and Opponent SIFT (scale invariant feature transform). The result showed that Opponent SIFT was the best choice, reaching 100.00% recognition accuracy, while the first three were 91.98%, 91.96% and 99.43%, respectively. Thus an online consulting system was established, based on Opponent SIFT. After the users load the unknown image of the lepidopteran, the system can output the recognition result and all information about the species. New, but otherwise known species can be added to continuously expand the system. A simple and viable scheme to identify insect sounds automatically was also introduced, using a sound parameterization technique that dominates speaker recognition technology. The acoustic signal is preprocessed and segmented into a series of sound samples. MFCC (Mel-frequency cepstrum coefficient) is extracted from the sound sample, and a feature model is trained using Linde-Buzo-Gray algorithm (Linde et al. 1980) to generate vector quantization (VQ) codebook from the above MFCC. The matching for a test sample is completed by finding the nearest neighbour in all the VQ codebooks. The method is tested in a database with acoustic samples of 70 different insect sounds (data from insect sound library, Mankin et al. 2008). The recognition rate was above 96%, and an ideal time performance was also achieved with the recognition time of 9.13s. Sound recognition software system will also be installed.

Sonic figures of heroism and the 1891 Hehe–German war in Mulokozi’s novel Ngome ya Mianzi

ABSTRACTShortly after the 1884–85 Berlin Conference, Germany invaded and fought a number of wars with Tanganyika’s local chiefdoms in order to subject these territories to its colonial rule. In 1891 the Hehe people, who dwelt in Iringa region in the southern part of today’s Tanzania, fought to resist the invading German troops and succeeded in killing the German commander, Emil von Zelewski. Using both fictional and historical persons, events and locations, a 1991 Kiswahili novel by Tanzanian writer Mugyabuso Mulokozi, Ngome ya Mianzi (Bamboo Fortress), retells the story of the first battle between the German troops and the Hehe, fought at Lugalo. This article examines the ways this novel uses musical figures, including songs, dances, sounds of musical instruments and sounds of birds and insects as semiotic resources to narrate the story, create its characters and shape various events.