Figure 4 - uploaded by Klaus Riede
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Oscillogram and sonagram of the gomphocerine grasshopper Euplectrotettix ferrugineus Bruner 1900 (Acridoidea). Acridid songs have a complex time structure, but their spectral properties can simply be described as wide-band noise.
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Songs of Orthoptera can be used for inventorying and monitoring of individual species and communities. Acoustic parameters such as carrier frequency and pulse rates allow the definition of recognizable taxonomic units (RTUs) which help to overcome the taxonomic impediment due to our scanty knowledge, particularly of tropical faunas. Bioacoustic div...
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We compared pitfall trap sampling; a most commonly used method for surface or ground dwelling insects with the bioacoustics method, the most recent method of orthopteran richness estimation. The primary objective of the study was to estimate species richness of Ensifera (Infraorder: Gryllidea) in Delhi and suburban region using bioacoustics method....
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... Passive acoustic monitoring employs autonomous recording units (ARUs), which record the sounds of soniferous insects and other animals either continuously or intermittently (subsamples of minutes) in both the audible and ultrasonic spectrum [44]. Recorded sounds are usually automatically identified using artificial intelligence (AI) trained on annotated sounds from known species [45]. ...
Insects are the most diverse group of animals on Earth, yet our knowledge of their diversity, ecology and population trends remains abysmally poor. Four major technological approaches are coming to fruition for use in insect monitoring and ecological research—molecular methods, computer vision, autonomous acoustic monitoring and radar-based remote sensing—each of which has seen major advances over the past years. Together, they have the potential to revolutionize insect ecology, and to make all-taxa, fine-grained insect monitoring feasible across the globe. So far, advances within and among technologies have largely taken place in isolation, and parallel efforts among projects have led to redundancy and a methodological sprawl; yet, given the commonalities in their goals and approaches, increased collaboration among projects and integration across technologies could provide unprecedented improvements in taxonomic and spatio-temporal resolution and coverage. This theme issue showcases recent developments and state-of-the-art applications of these technologies, and outlines the way forward regarding data processing, cost-effectiveness, meaningful trend analysis, technological integration and open data requirements. Together, these papers set the stage for the future of automated insect monitoring.
This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.
... Ormiini flies, including Ormia species, are frequently reared from mole crickets (Gryllotalpidae) and katydids (Tettigoniidae), which sing at high frequencies (Lehmann 2003 Saussure, Gryllus Linnaeus, and Teleogryllus Chopard, 1961. All of them are recognized as good singers with sound records used for species descriptions and bioacoustic studies (e.g., Walker 1977, Riede 1998, Gwynne 2001, Otte and Pérez-Gelabert 2009, Redü and Zefa 2017. Anurogryllus species are known for their long and loud trills, whereas the other three genera usually have species with calls characterized by chirps. ...
True crickets (Orthoptera, Grylloidea) are often parasitized by tachinid flies (Diptera, Tachinidae). However, the diversity of these parasitoids and their oviposition strategies remain unclear. Although some flies are specialized in locating crickets by their calling songs, such as the phonotactic fly Ormia ochracea (Bigot, 1889), a large portion of the tachinids that attack true crickets show different host search strategies and are adapted to para-sitize other orthopteroid insects as well. However, these parasitoids have a complex and challenging taxonomy that precludes further improvement in the understanding of Tachinidae-Orthoptera interactions. Here, we described and illustrated seven new host records in Gryllidae and Phalan-gopsidae species from Brazil, including notes on the diagnostic characters of each parasitoid and host. An illustrated identification key to Tachinidae genera recorded in Grylloidea is also provided. Finally, all published records of Tachinidae parasitism in true crickets were revised and are presented in an annotated catalog in order to understand the host range and different oviposition strategies of each parasitoid lineage.
... Such species might be detected much more easily by the sounds they produce. Acoustic monitoring methods focused on Orthoptera have been successfully used for detection of presence and absence of species, determining distribution ranges, detection of otherwise cryptic species [10] and evaluating quality and deterioration of habitats, since they can function as indicator species [11]. Additionally, this method is mostly non-invasive, less elaborate than other common monitoring approaches [8] and could be automated to a high degree [9]. ...
... In the present work, we develop a robust method for acoustic classification of orthopteran and cicada species, using a deep learning method that can adapt to acoustic characteristics of the targeted insects. Some previous attempts of identifying Orthoptera by their sounds have focused on using manual extraction of sound features such as carrier frequency or pulse rates [10,13]. These features must be manually selected and their parameters defined before use for automatic classification. ...
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.
... Insects make up one of the largest shares of the Earth's biodiversity, but recent reports on severe insect declines are alarming (Sánchez-Bayo and Wyckhuys 2019). Because of their short life cycles and, in some species, specialization in habitat, food source, and egg-laying, insects are excellent indicators of climate change (Riede 1998, Jeliazkov et al. 2016, Beckmann 2017. For most insects, we still have too little information about extant biodiversity to understand the causes and consequences of population declines (Saunders et al. 2019). ...
... Because many male orthopterans sing to attract mates, community science studies quantifying species richness, abundance, and emergence times in Orthoptera are relatively simple. Species can be identified by their acoustic profiles, and acoustic survey data can be recorded from trails and roadsides (Fischer et al. 1997, Riede 1998, Penone et al. 2013, Jeliazkov et al. 2016, McNeil and Grozinger 2020, Paiero et al. 2020, Kaláb et al. 2021. This is particularly useful in fragile habitats or for threatened species, where scientists must balance effective monitoring with reducing disruption in conservation spaces (Moran et al. 2014, McNeil andGrozinger 2020). ...
Orthopterans are commonly encountered in rural, suburban, and urban landscapes and have charismatic songs that attract the public’s attention. These are ideal organisms for connecting the public with science and critical concepts in ecology and evolution, such as habitat conservation and climate change. In this review, we provide an overview of community science and review community science in orthopterans. Best practices for orthopteran community science are provided, with a focus on audio recordings and highlighting new ways in which scientists who study orthopterans can engage in community science.
Before the modern era, scientific discovery was commonly made by people who were not scientists by profession (Brenna 2011, Miller-Rushing et al. 2012). This began to change in the middle of the nineteenth century when science became highly academic, with greater “gatekeeping” of knowledge, and data collection became increasingly expensive. As a result, much of the knowledge gained during that time has been effectively withheld from non-scientists in difficult-to-obtain scientific journals, and there were few opportunities for the public to directly engage with scientific research. In recent years, there has been a concerted effort from the scientific community to change the way we engage with the public. These “citizen” or “community” science projects are filling gaps in the modern approach to scientific inquiry (Jordan et al. 2012, Toomey and Domroese 2013, Johnson et al. 2014). Here, we provide an overview of community science and highlight the exciting and unique role that community science can play in orthopteran research. We focus on how acoustic surveys can be used to study orthopteran biodiversity, provide best practices for orthopteran community science, and suggest future avenues for research.
... Such species might be detected much more easily by the sounds they produce. Acoustic monitoring methods focused on Orthoptera have been successfully used for detection of presence and absence of species, determining distribution ranges, evaluating quality and deterioration of habitats and detection of otherwise cryptic species [9], since they can function as indicator species [10]. Additionally, this method is mostly non-invasive, less elaborate than other common monitoring approaches and could be automated to a high degree [8]. ...
... In the present work, we develop a robust method for acoustic classification of orthopteran and cicada species, using a deep learning method that can adapt to acoustic characteristics of the targeted insects. Previous attempts of identifying Orthoptera by their sounds have focused on using manual extraction of sound features such as carrier frequency or pulse rates [9]. ...
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 (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.
... Acoustic monitoring has long been used to monitor the presence of aquatic animals, amphibians, insects, and birds (Acevedo & Villanueva-Rivera, 2006;Parra, 1992;Petrusková et al., 2016;Riede, 1998;Sanders & Mennill, 2014). Like other grey wolf subspecies, Indian grey wolves are known for their long-ranging communication via howls (Theberge & Falls, 1967). ...
The Indian wolf is a Schedule I species in the Wildlife Protection Act 1972. It is now considered an Evolutionary Significant Unit (A adaptive variation significantly important for conservation) (Hennelly et al., 2021). Since they survive predominantly in a human-dominated landscape (Habib et al., 2021; Habib & Kumar, 2007), they face immense survival threats due to habitat degradation and man-animal conflict (Agarwala et al., 2010). Their population status has remained unassessed over the years due to difficulties associated with the population estimation of this visually cryptic long-ranging species (Cozzi et al., 2021). A few studies have suggested that around 1000 to 2000 (Sillero-Zubiri et al., 2004) wolves are left in India, but those are rough estimates without statistical support. Therefore, a non-invasive statistical tool is required to estimate this visually cryptic species. Since the howling survey is considered the most efficient monitoring tool for this visually cryptic species (Harrington & Mech, 1982), my study aimed to standardise a statistical tool to estimate the population of Indian wolves based on their howl. I have started my work with a single point of reference on Indian wolf vocalisation – a comparative study of Indian wolf howls with a few other subspecies (Hennelly et al., 2017). I began the study with howling survey responses and opportunistic recordings from captive and nine free-ranging packs of Indian wolves. Different harmonic call types were characterised using an unsupervised statistical tool and defined to generate baseline information about the vocal characteristics of the Indian wolf. Through unsupervised clustering, I found four distinct vocalisations using 270 recorded calls (Average Silhouette width Si = 0.598), which include howls and howl-barks (N = 238), whimper (N = 2), social squeak (N = 28), and whine (N = 2). Indian wolf howls have an average mean fundamental frequency of 422 Hz (±126), similar to other wolf subspecies. The whimper showed the highest frequency modulation (37.296±4.601) and the highest mean fundamental frequency (1708±524 Hz) compared to other call types. Less information is available on the third vocalisation type, i.e. ‘Social squeak’ or ‘talking’ (Mean fundamental frequency = 461±83 Hz), which is highly variable (coefficient of frequency variation = 18.778±3.587). Lastly, I identified the whine, which had a mean fundamental frequency of 906Hz (±242) and was similar to the Italian wolf (979±109 Hz). The study highlighted how ‘social squeak’ can be misidentified with the howl. They can be differentiated through their frequency modulation and duration. Social squeaks (x̅ = 3.87s) are generally shorter than howl (x̅ = 5.214s). My study on the characterisation of the harmonic vocal repertoire provides a first step in understanding the function and contextual use of vocalisations in the Indian wolf.
Studies over the years found that wolf howls contain individual-specific information (Fentress, 1967; Root-Gutteridge et al., 2014b, 2014a; Tooze et al., 1990). But identifying the unknown individual from their howls had remained challenging over the years, without which howl could not be used in Capture-Mark-Recapture studies (Marques et al., 2013; Stevenson et al., 2015). By understanding the importance of howl identification to an individual in population estimation, I trained a supervised model using known howls to identify howls to individuals. I verified the model with a set of unknown howls (unknown to the model). In this supervised classification, I achieved 97.9% accuracy in identifying known howls (trained dataset) and 75% accuracy in identifying unknown howls (test dataset). For the first time, the unknown wolf howls were classified successfully. Although the achievement is very significant in wolf vocalisation research, further accuracy is required for using them in the population estimation model. Training the model with more howls and verifying them with a different set of test data might increase its reliability. For these, a continuous recording of captive individuals and recordings from free-ranging collared wolves for an extended period is essential.
The howling behaviour of Indian wolves has never been studied. Therefore, understanding the howling behaviour of the Indian wolf was the key to designing a howl survey methodology for population estimation. I studied the howling behaviour of collared and non-collared free-ranging wolves through the response pattern of the active howl survey. I found a disparity in their howl response - based on the distance to villages. In the low disturbed East-Maharashtra (EM), wolves mostly avoid responding to howling surveys (HS) if done within 1200 meters of villages [Response Rate(RR)=0.03±0.021], but they do respond once it is done far from villages (>1200m)[RR=0.226±0.075]. In high human dense West-Maharashtra (WM), wolves showed high RR within 1200 meters from the villages (RR=0.148±0.031). But the RR within 500 meters from villages is less as howling near villages might owe to easy detection. The collared wolf data showed significantly high RR (0.635±0.067) in their home-range core but low RR if the core area is close to a village. Therefore howling too close to the village is disadvantageous, although their tolerance for responding to HS has increased in the human-dominated landscape. The extent of the village may increase further with development, which will leave fewer areas for the wolf to defend territory with a long-range howl. The wolves might behaviourally adapt to a human-modified landscape by reducing their howling intensity. Adaptation in a fragmented habitat may save the wolves from extinction, but the repercussions of the fundamental behavioural alteration might adversely impact wolf behaviour and the ecological cascade. Whereas ecologists are mainly concerned with the extinction of species, the study highlights the vulnerability of fundamental behaviour of a keystone species attributed to human-induced contemporary evolution.
Based on the vocalisation behaviour, I found that a howl survey should be done during their pre-denning season (November-December). Additionally, wind speed is low during this period. The best grid size for a systematic grid howl sampling is 1.7 × 1.7 km2. A 30watt speaker should be used for an active howl survey with 3-5 trials. This study provides the crucial guideline for a howling survey in Indian conditions. Based on these criteria, a howl survey was designed for four districts of Maharashtra. Maximum Entropy Probably Distribution (Maxent) was used for delineating the potential wolf habitats, and 12250 km2 effective wolf habitat was found. A newly triple observer-based howl survey method was introduced, I obtained a relatively high howl response (seven out of twenty-five howl surveys) in randomly selected grids. I used ‘redetection’ in different points in space instead of using individual ‘recapture’ with time. Through my pilot study, I found Indian wolf density is 3.65 individuals/100 km2 with a lower limit of 1.67 to an upper limit of 5.63 (95% CI). Although I do not have data on the population density of Indian wolves to compare, the data and its error range are comparable with the population density of Iberian wolves, i.e., 2.55 wolves/100 km2 (95% CI = 1.87–3.51) estimated by DNA (scat) sampling by López-Bao et al. (2018). The standard error might decrease further with an increase in sampling effort through the active howl survey. This methodology can be a guideline for using the active howling survey in the population estimation of wolves globally.
Since wolf howls also possess individual information, incorporating this information in the future will help reduce the bias and heterogeneity in the population estimation model. Incorporating individual identification in the population estimation model will help generate additional details such as animal survival and home range. Regular population monitoring will help conserve and save this cryptic species before its population falls below a recovery level. Therefore, the study is a stepping stone towards using bioacoustics to estimate animal density and play a significant role in global wolf conservation.
... Many of the loudest and most repetitive sounds are mating signals, which are often speciesspecific, at least within a given habitat (Greenfield 1997, Gerhardt and Huber 2002, Symes 2014. Documenting these sounds can provide a detailed window into the biology and population dynamics of insect species that are central to many food webs (Riede 1998, Hugel 2012, Penone et al. 2013. ...
Insects are an integral part of terrestrial ecosystems, but while they are ubiquitous, they can be difficult to census. Passive acoustic recording can provide detailed information on the spatial and temporal distribution of sound-producing insects. We placed recording devices in the forest canopy on Barro Colorado Island in Panamá and identified katydid calls in recordings to assess what species were present, in which seasons they were signaling, and how often they called. Soundscape recordings were collected at a height of 24 m in two replicate sites, sampled at three time-windows per night across five months, spanning both wet and dry seasons. Katydid calls were commonly detected in recordings, but the call repetition rates of many species were quite low, consistent with data from focal recordings of individual insects where calls were also repeated rarely. The soundscape recordings contained 6,789 calls with visible pulse structure. Of these calls, we identified 4,371 to species with the remainder representing calls that could not be identified to species. The identified calls corresponded to 24 species, with 15 of these species detected at both replicate sites. Katydid calls were detected throughout the night. Most species were detected at all three time points in the night, although some species called more just after dusk and just before dawn. The annotated dataset provided here serves as an archival sample of the species diversity and number of calls present in the forest canopy of Barro Colorado Island, Panama. These hand-annotated data will also be key for evaluating automated approaches to detecting and classifying insect calls. In changing forests and with declining insect populations, consistent approaches to insect sampling will be key for generating interpretable and actionable data.
... Despite the high biodiversity, endemism, and the increasing number of publications of insect bioacoustics in Colombia over the past decade, more efforts are still needed in this field (Kattkan 2004;Martínez-Medina et al. 2021). Acoustic monitoring is a useful tool for conservation strategies and an important indicator of diversity for stridulating insects (Riede 1998, Cadena-Castañeda & Páez 2013. In addition, it is an innovative and cost-effective method that could help us to understand the consequences of human activity in the tropics Deichmann et al. 2018). ...
... In addition, it is an innovative and cost-effective method that could help us to understand the consequences of human activity in the tropics Deichmann et al. 2018). Furthermore, many species from the Orthoptera are valued bioindicators of habitat quality in tropical ecosystems, and monitoring their behavior is a useful tool for developing new strategies for conservation (Riede 1998). with increasingly small and affordable devices, capable of recording with high sample rates, such as the AudioMoth recorders (Hill et al. 2019), we encourage other researchers to conduct more studies like this one. ...
By combining different research disciplines, biologists can understand natural processes in a broader way. Here, we combine both taxonomic and bioacoustic methodologies to provide the first observations of the morphology, geographical distribution, and the acoustic behavior of the monotypic genus Andeophylloides n. gen. This katydid is the second short-winged genus of the tribe Platyphyllini, after Brachyplatyphylloides, both of which are found in the Colombian Andes. This new genus is unique, because it is the first to be collected in a High Andean Forest, in contrast to the other members of the tribe that have been found predominantly at lower elevations. The sound recordings showed males calling with an echeme duration in average of 5.9 ± 3.1 s, a peak frequency of 22.5 kHz, and peak activity starting at 19:00 and decreasing until 05:00. These calls occur mainly in the months of the first rainy season of the year (March to May). Andeophylloides zarauzensis n. sp., is the sixth species of platyphyllines which calling song is known. Additionally, we discuss the taxonomy, bioacoustics, and differentiate the species with Dasyscelidius atrifrons (Pleminiini). This is required as the females are superficially similar and both species share the same geographical distribution.
... In contrast with other methods, such as fogging or traditional taxonomic inventories, the ecoacoustic approach is advantageous as it is noninvasive, easy to implement, allow data collection over large temporal and spatial scales, and in remote places (Sueur & Farina, 2015). An acoustic approach for biodiversity monitoring is meaningful in species-rich ecosystems, such as tropical rainforests (Deichmann et al., 2018), where taxonomic impediments may be overcome by the recognizable taxonomic unit of songs (Riede, 1998(Riede, , 2018. Acoustic monitoring could not, however, be used to characterize the sampled communities by their specific components unless a preliminary taxonomic effort was conducted. ...
Crickets (Ensifera, Grylloidea) are not commonly used as ecological indicators in con-
trary to other Orthoptera (e.g., grasshoppers and katydids). However, they are sensi-
tive to environmental changes and abundant in tropical regions. To evaluate whether
crickets are relevant bioindicators of tropical ecosystems, we investigated cricket as-
semblages along a tropical ecological gradient. We collected crickets during both day
and night in southern New Caledonia for three stages of ecological succession: open
shrubland, preforest, and forest. Simultaneously, we measured several environmental
variables, such as temperature and relative humidity, at each sampling site. Cricket
species assemblages showed a clear response to ecological succession. The highest
and lowest species richness and abundances of individuals were, respectively, found
in forest and shrubland, with species specialized in each ecological stage revealing
the conservation value of each of these stages. Similar results were found when con-
sidering only the part of cricket communities with the ability to acoustically commu-
nicate. This work is part of a larger research program about Neocaledonian crickets
and contributes to support the use of acoustic approaches to monitor tropical en-
vironments. In conclusion, these findings highlight the potential value of crickets as
an environmental indicator in tropical ecosystems. The results also contribute to the
discussion of the intrinsic conservational value of shrublands in New Caledonia and
similar ecotypes.
... Its advantages for biodiversity monitoring including longer term assessment periods, less intrusive monitoring methods, increase of data collection, and increased potential for community bioacoustics research at different scales, when compared to classical monitoring approaches such as specimen collection in the field (Blumstein et al., 2011;Deichmann et al., 2018;Sugai et al., 2020). Furthermore, PAM allows the classification of calling songs into recognizable taxonomic units, also referred to as acoustic morphospecies or sonotypes (Riede, 1998;Aide et al., 2013;Ferreira et al., 2018). Despite that, there are still challenges when applied to high diverse taxonomic groups with lees availability of taxonomic and acoustic descriptions, as insects (Riede, 2018). ...
Passive acoustic monitoring (PAM) is a promising method for biodiversity assessment, which allows for longer and less intrusive sampling when compared to traditional methods ( e.g ., collecting specimens), by using sound recordings as the primary data source. Insects have great potential as models for the study and monitoring of acoustic assemblages due to their sensitivity to environmental changes. Nevertheless, ecoacoustic studies focused on insects are still scarce when compared to more charismatic groups. Insects’ acoustic activity patterns respond to environmental factors, like temperature, moonlight, and precipitation, but community acoustic perspectives have been barely explored. Here, we provide an example of the usefulness of PAM to track temporal patterns of acoustic activity for a nocturnal assemblage of insects (Orthoptera). We integrate satellite remote sensing and astronomically measured environmental factors at a local scale in an Andean Forest of Colombia and evaluate the acoustic response of orthopterans through automated model detections of their songs for nine weeks (March and April of 2020). We describe the acoustic frequency range and diel period for the calling song of each representative species. Three species overlapped in frequency and diel acoustics but inhabit different strata: canopy, understory, and ground surface level. Based on the acoustic frequency and activity, we identified three trends: (i) both sampled cricket species call at lower frequency for shorter periods of time (dusk); (ii) all sampled katydid species call at higher frequency for longer time periods, including later hours at night; and (iii) the diel acoustic activity span window seems to increase proportionally with dominant acoustic frequency, but further research is required. We also identified a dusk chorus in which all the species sing at the same time. To quantify the acoustic response to environmental factors, we calculated a beta regression with the singing activity as a response variable and moon phase, surface temperature and daily precipitation as explanatory variables. The response to the moon phase was significant for the katydids but not for the crickets, possibly due to differences in diel activity periods. Crickets are active during dusk, thus the effects of moonlight on acoustic activity are negligible. The response to precipitation was significant for the two crickets and not for the katydids, possibly because of higher likelihood of rain interrupting crickets’ shorter diel activity period. Our study shows how the local survey of orthopteran acoustic assemblages, with a species taxonomic resolution coupled with remote-sensing environmental measurements can reveal responses to environmental factors. In addition, we demonstrate how satellite data might prove to be a useful alternative source of environmental data for community studies with geographical, financial, or other constraints.
