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A new methodology to infer the singing activity of an avian community: The Acoustic Complexity Index (ACI)
Abstract
The animal soundscape is a field of growing interest because of the implications it has for
human–landscape interactions. Yet, it continues to be a difficult subject to investigate, due to the huge
amount of information which it contains. In this contribution, the suitability of the Acoustic Complexity
Index (ACI) is examined. It is an algorithm created to produce a direct quantification of the complex
biotic songs by computing the variability of the intensities registered in audio-recordings, despite the
presence of constant human-generated-noise. Twenty audio-recordings were made at equally spaced
locations in a beech mountain forest in the Tuscan-Emilian Apennine National Park (Italy) between June
and July 2008. The study area is characterized by the absence of recent human disturbance to forest
assets but the presence of airplane routes does bring engine noise that overlaps and mixes with the natural
soundscape, which resulted entirely composed by bird songs. The intensity values and frequency bin
occurrences of soundscapes, the total number of bird vocalizations and the ACI were processed by using
the Songscope v2.1 and Avisoft v4.40 software. The Spearman’s rho calculation highlighted a significant
correlation between the ACI values and the number of bird vocalizations, while the frequency bin occurrence
and acoustic intensity were weaker correlated to bird singing activity because of the inclusion of
all of the other geo/anthro-phonies composing the soundscape. The ACI tends to be efficient in filtering
out anthrophonies (such as airplane engine noise), and demonstrates the capacity to synthetically and
efficiently describe the complexity of bird soundscapes. Finally, this index offers new opportunities for
the monitoring of songbird communities faced with the challenge of human-induced disturbances and
other proxies like climate and land use changes.
... The aggregation of all these signatures results in an acoustic community signature. Acoustic indices aggregate the amplitude and frequencies of sounds, summarizing the acoustic complexity and dynamics of soundscapes and acting as proxies of biodiversity (Boelman, Asner, Hart, & Martin, 2007;Depraetere et al., 2012;Fuller, Axel, Tucker, & Gage, 2015;Pieretti, Farina, & Morri, 2011;Sueur et al., 2008;Villanueva-Rivera, Pijanowski, Doucette, & Pekin, 2011). Sounds from biota are called biophony, sounds from humans are called anthrophony, and nature sounds from abiotic origin are called geophony. ...
... My first objective is to assess the relationship between acoustic indices and descriptors of habitat structure and composition (including core habitat quality, connectivity, live cover, and percent tree cover) and the relationship between acoustic indices and descriptors of anthropogenic pressure (including road traffic, nighttime lights, and human edges). Given that acoustic indices are related to biodiversity (Boelman et al., 2007;Depraetere et al., 2012;Fuller et al., 2015;Pieretti et al., 2011;Sueur et al., 2008;Villanueva-Rivera et al., 2011), this study tests the hypothesis that acoustics indices can act as indicators of habitat intactness. Given the background literature presented above, I predicted that more intact forest landscapes, described as those with higher connectivity, high live cover, high percent tree cover, and low anthropogenic pressure, would have higher biophony than less intact ones. ...
... For each of the recordings, the Acoustic Complexity Index (ACI, Pieretti et al., 2011), the Normalized Difference Soundscape index (NDSI), and its components: Biophony (B), and Anthrophony (A), were calculated. Biophony and anthrophony can vary considerably depending on the day and weather conditions. ...
Understanding how human-dominated landscapes affect biodiversity and ecosystems is essential for effective conservation planning. This work aims to understand the relationship between the acoustic diversity of forested landscapes, and descriptors of habitat structure, composition, and anthropogenic pressure, as well as to identify the characteristic scale at which acoustic community diversity relates to those metrics in central Massachusetts.
Ten passive acoustic recorders were placed within forest areas in central Massachusetts, during the breeding season. Mono audio recordings were collected during the dawn chorus. The relationship between acoustic indices (AI), and core habitat quality, connectivity, vegetation productivity, percent tree cover, human edge, artificial illumination, and traffic noise were assessed.
Significant relationships were found between AI and variables related to habitat structure and human pressure. Sounds related to biota (biophony) and acoustic complexity were positively correlated with core habitat quality, connectivity, and vegetation while negatively correlated with human pressure variables, including nighttime lights, traffic noise, and human edge. AI can therefore act as successful indicators of habitat quality in highly modified landscapes The highest correlations were found at buffers between 1.5 and 3 Km. This response of AI to the broad spatial context and not to the local site characteristics indicate that they can act as robust landscape-scale indicators.
The large characteristic scale indicates that urban planning should consider potential impacts acting at scales beyond site planning. Moreover, conservation planning can benefit from managing the context matrix to support biodiversity, particularly traffic noise and artificial illumination reduction initiatives.
... With the help of PAM, there is growing interest in soundscape ecology: a recently developed research field that focuses on the study of the temporal and spatial distribution of sound through a landscape, reflecting important ecosystem processes and human activities [12][13][14][15]; soundscape changes can affect animal population and community status [16]. Soundscape ecology uses the acoustic index, a statistic metric summarizing some aspects of the distribution of acoustic energy and information in a recording [17], to rapidly quantify the typical complexity of the biotic songs of a soundscape despite the presence of various noise [18]. In recent years, multiple sound indices have been developed to evaluate the intensity, relative abundance, richness, heterogeneity, and anthropogenic interference on acoustic communities, including the Bioacoustic Index (BI) [19], Acoustic Entropy Index (H) [20], Acoustic Evenness Index (AEI), Acoustic Diversity Index (ADI) [21], Acoustic Complexity Index (ACI) [18], Acoustic Richness Index (AR) [22], Normalized Difference Soundscape Index (NDSI) [14], etc. Acoustic indices have been used for monitoring ecosystem conditions and dynamics [18,[23][24][25], and interpretation of environment change [26][27][28][29][30][31]. ...
... Soundscape ecology uses the acoustic index, a statistic metric summarizing some aspects of the distribution of acoustic energy and information in a recording [17], to rapidly quantify the typical complexity of the biotic songs of a soundscape despite the presence of various noise [18]. In recent years, multiple sound indices have been developed to evaluate the intensity, relative abundance, richness, heterogeneity, and anthropogenic interference on acoustic communities, including the Bioacoustic Index (BI) [19], Acoustic Entropy Index (H) [20], Acoustic Evenness Index (AEI), Acoustic Diversity Index (ADI) [21], Acoustic Complexity Index (ACI) [18], Acoustic Richness Index (AR) [22], Normalized Difference Soundscape Index (NDSI) [14], etc. Acoustic indices have been used for monitoring ecosystem conditions and dynamics [18,[23][24][25], and interpretation of environment change [26][27][28][29][30][31]. The acoustic index-based method has become a feasible and promising method to evaluate the status and change in bird population [24,[32][33][34]. ...
... Soundscape ecology uses the acoustic index, a statistic metric summarizing some aspects of the distribution of acoustic energy and information in a recording [17], to rapidly quantify the typical complexity of the biotic songs of a soundscape despite the presence of various noise [18]. In recent years, multiple sound indices have been developed to evaluate the intensity, relative abundance, richness, heterogeneity, and anthropogenic interference on acoustic communities, including the Bioacoustic Index (BI) [19], Acoustic Entropy Index (H) [20], Acoustic Evenness Index (AEI), Acoustic Diversity Index (ADI) [21], Acoustic Complexity Index (ACI) [18], Acoustic Richness Index (AR) [22], Normalized Difference Soundscape Index (NDSI) [14], etc. Acoustic indices have been used for monitoring ecosystem conditions and dynamics [18,[23][24][25], and interpretation of environment change [26][27][28][29][30][31]. The acoustic index-based method has become a feasible and promising method to evaluate the status and change in bird population [24,[32][33][34]. ...
Passive acoustic sensor-based soundscape analysis has become an increasingly important ecological method for evaluation of ecosystem conditions using acoustic indices. Understanding the soundscape composition and correlations between acoustic indices and species richness of birds, the most important sound source in the ecosystem, are of great importance for measuring biodiversity and the level of anthropogenic disturbance. In this study, based on yearlong sound data obtained from five acoustic sensors deployed in Dalongtan, Shennongjia National Park, we analyzed the soundscape composition by comparing the distributions of the soundscape power in different frequency ranges, and examined the correlations between acoustic indices and bird species richness by means of the Spearman rank correlation coefficient method. The diurnal dynamic characteristics of acoustic indices in different seasons were also described. Results showed that the majority of sounds were in the frequency of 2-8 kHz, in which over 50% sounds were in 2-6 kHz, commonly considered the bioacoustic frequency range. The Acoustics Complexity Index, Bioacoustic Index, and Normalized Difference Soundscape Index were significantly correlated with bird species richness, suggesting that these indices can be used for evaluation of bird species richness; Apparent diurnal dynamic patterns of bird acoustic activities were observed in spring, summer, and autumn; however, the intensity and duration of bird acoustic activities in summer is larger/longer than in spring and autumn.
... Ecoacoustic indices characterise soundscapes with a reduced set of parameters that allow the discrimination of different sound sources in the environment covered [11][12][13][14][15][16][17] and therefore can be used to optimise data generation. These enable the evaluation of soundscape degradation due to human activities and the detection of changes in the soundscape, such that they could be a useful tool to make decisions about conservation in form of macro-indicators. ...
... To overcome the limitation of storage capacity, the recording system could be provided with a processing hardware that enables processing the raw audio signal and only store ecoacoustic indices. The Soundscape Explorer instrument provided by Lunilettronik [30], which computes ACI [13] in real time and is used in [17], is an example of this approach. In [31], a smart low-cost acoustic device for monitoring biodiversity is proposed. ...
... On this first version of the MASE instrument we have implemented three acoustic indicators: Spectral energy, ACI [13], and H f [15]. Each of them is computed for the octave bands of spectra. ...
The study of sound in the natural environment provides interesting information for researchers and policy makers driving conservation policies in our society. The soundscape characterises the biophony, anthrophony and geophony of a particular area. The characterisation of these different sources can lead to changes in ecosystems and we need to identify these parameters in order to make the right decision in relation to the natural environment. These values could be extrapolated and potentially help different areas of ecoacoustic research. Technological advances have enabled the passive acoustic monitoring (PAM) of animal populations in their natural environment. Recordings can be made with little interference, avoiding anthropogenic effects, making it a very effective method for some species such as cetaceans and other marine species in addition to underwater noise studies. Passive acoustic monitoring can be used for population census, but also to understand the effect of human activities on animals. However, recording data over long periods of time requires large storage and processing capacity to handle all the acoustic events generated. In the case of marine environments, the installation of sensors and instruments can be costly in terms of money and maintenance effort. In addition, if they are placed offshore, a data communication problem arises with coverage and bandwidth. In this paper, we propose a low-cost instrument to monitor the soundscape of a marine area using ecoacoustic indices. The instrument is called MASE and provides three echo-acoustic indices at 10 min intervals that are available in real time, which drastically reduces the volume of data generated. It has been operating uninterruptedly for a year and a half since its deployment, except during maintenance periods. MASE has been able to operate uninterruptedly, and maintain an adequate temperature inside while preserving its structural integrity for long periods of time. This has allowed the monitoring and characterisation of the soundscape of the test area in Gando Bay, Gran Canaria Island (Spain) without the need for human intervention to access the data on the instrument itself. Thanks to its integration with an external server, this allows the long-term monitoring of the soundscape, and it is possible to observe changes in the soundscape. In addition, the instrument has made it possible to compare the period of acoustic inactivity during confinement and the return of anthropogenic acoustic activity at sea.
... In the first decade of the 2000s, the practice of soundscape analysis shifted with the introduction of digital recording and analysis tools. The relative ease of spectral analysis with digital tools gave rise to a set of acoustic indices such as the Acoustic Complexity Index (ACI) (Pieretti, Farina, and Morri, 2011) and Acoustic Diversity Index (ADI) (Villanueva-Rivera et al., 2011) that are used to monitor variables like biodiversity and species richness and to identify acoustic events (Abdallah, Frigui, and Gader, 2009;Towsey et al., 2014;. ...
... To calculate ACI in real-time on a microcontroller, it was necessary to translate the ACI algorithm into C++ but also to modify it to work with streaming data instead of a full audio file. Described in detail in Pieretti et al. (2011), the ACI represents the amount of variation of intensity of sound within frequency bands over the course of a recording fragment. It relies on the assumption that anthropogenic noises -for example, the droning of an aeroplane engine or the buzz of a factory -are often spectrally constrained and relatively constant, so it attempts to detect sounds that vary from moment-to-moment. ...
... The transformation of the ACI calculation is somewhat more complex. Described in detail in Pieretti et al. (2011), the ACI represents the amount of variation of intensity of sound within frequency bands over the course of a recording fragment. It relies on the assumption that anthropogenic noises -for example, the droning of an aeroplane engine or the buzz of a factory -are often spectrally constrained and relatively constant, so it attempts to detect sounds that vary from moment-to-moment. ...
Endemic Machines is an interdisciplinary investigation of the question: What is required for a machine to adapt to a local ecosystem? Through the medium of sound, it explores the conceptualization and design of machines that belong in an ecosystem because they evolve within and alongside it. Drawing on research in soundscape ecology, artificial life, and artificial intelligence, it builds an interdisciplinary view of machine engagement with an existing soundscape.
Building on the biosemiotic concept of a sensory world, an umwelt, this work formulates a basis for the machine sensing of the soundscape. In parallel, it presents work — conceptual and based in practice — that constructs a new frame for the production and understanding of machinic vocalizations in the soundscape. The term robophony is devised to describe the sounds of ecologically- engaged machines as they do not fit within the existing ontological framework which characterizes sound as originating from humans (anthrophony), (non-human) biological entities (biophony), or geophysical processes (geophony).
Additionally, the concept of eco-technogenesis is proposed as a way of understanding the cyclical co-evolution of technologies and ecosystems. This extends the concept of technogenesis, which situates technology and humanity as evolutionary partners, to the co-development of ecosystems and machines. The processes of feedback and co-creation inherent in eco-technogenesis provide a framework for understanding how machines can become endemic.
These theoretical contributions are scrutinized in the experimental design of an endemic machine that evolves a vocalization in an existing, real-world soundscape. Through this machine, the Rowdy Krause, adaptation to a local ecosystem is addressed in practice. The work delves into the nuances and complexities of adapting to a local ecosystem and the internal tensions embedded in the concept of an endemic machine.
... From marine wildlife (biophony)? Or from geophysical processes (geophony)?) and to understand the interactions between anthrophony, biophony and geophony (NRC, 2003;Pieretti et al., 2011;Pijanowski et al., 2011;Miksis-Olds et al., 2018). ...
... More than 60 acoustic indices exist (Bradfer-Lawrence et al., 2019). The ACI is one of the most common and used used as a metric for detecting the possible presence of biological sounds, with the aim of isolating the biophony from continuous anthropophonic and geophonic components of the soundscape (Pieretti et al., 2011;Buscaino et al., 2016). It was computed to calculate the difference in amplitude (I) between adjacent temporal steps (k) using the following formula (Pieretti et al., 2011;Buscaino et al., 2016): ...
... The ACI is one of the most common and used used as a metric for detecting the possible presence of biological sounds, with the aim of isolating the biophony from continuous anthropophonic and geophonic components of the soundscape (Pieretti et al., 2011;Buscaino et al., 2016). It was computed to calculate the difference in amplitude (I) between adjacent temporal steps (k) using the following formula (Pieretti et al., 2011;Buscaino et al., 2016): ...
Whales have become an important topic in marine science. One of the best solutions for their protection is a better understanding of their social structure and the way they communicate with each other. To this end, Underwater Passive Acoustics (UPA) offers a unique solution to simultaneously capture both source-specific and more contextual information, thus providing a better understanding of both the behavior of whales and their relationships with the ecosystem around them. As the volume of APSM data to be processed has become very large, the development of automated artificial intelligence (AI) methods to analyze this data is now of prime importance in marine bioacoustics. These rely heavily on the quantity and quality of the annotated data, which is the main limitation in their use. This work explores two approaches in a weakly supervised context, by acting or on the context itself, through the question of where and how one can better extract useful information to supervise AI methods; or by acting on AI methods in this context, through the question of how to develop AI methods to better respond to weak supervision. Our contribution has enabled the development of new tools to aid in the recognition of cetacean sounds through open science with the OsmOSE project, a collaborative and interdisciplinary project following the principles of Findable, Accessible, Interoperable and Reusable data.
... Eco-acoustic indices have shown a rather good accuracy in measuring species diversity in some environments [37,40,53]. Animal species produce a plethora of sounds and this acoustic diversity can be used to extract information on species richness [3,37,40,53]. ...
... Eco-acoustic indices have shown a rather good accuracy in measuring species diversity in some environments [37,40,53]. Animal species produce a plethora of sounds and this acoustic diversity can be used to extract information on species richness [3,37,40,53]. Nonetheless, this relationship is not always straightforward [54]. ...
We applied standard acoustic methods to record, analyze and compare anthropogenic and biological signals belonging to the soundscape of artificial marine habitats. The study was conducted on two tanks located at the Acquario di Genova (Italy), the “Red Sea” and the “Tropical Lagoon” tanks, which represent different living environments hosting a variety of species and background sounds. The use of seven eco-acoustic indices, whose time series spanned the entire period of study, allowed the characterization of the environments. We investigated the extent to which eco-acoustic indices might describe the soundscape in an artificial marine environment surrounded by a background of mechanical noise, overlapping the diurnal/nocturnal fish chorusing produced by soniferous species. Three specific types of sounds emerged: (1) mechanical ones produced by the life-support system of the tanks; (2) anthropic origin ones due to maintenance and introduction of food; and (3) temporal trends associated with day/night cycles, especially impacted by artificial lighting. We searched for selected spectral patterns that were correlated to the time series of the eco-acoustic indices. The observed activity was found to be consistent with the sound emission of three specific fish species hosted in the tanks. The power spectral density (PSD) confirmed the presence of correlated signals (at 95th and 99th percentiles) for the identified frequency intervals. We expect that this method could be useful for studying the behavior of aquatic animals without intruding into their habitats.
... Multiple acoustic indices have been developed to characterize different facets of soundscapes (Pieretti et al., 2011;Villanueva-Rivera et al., 2011;Depraetere et al., 2012;Gasc et al., 2013;Sueur et al., 2014). Species-specific classification approaches that estimate taxonomic diversity require complex model-training techniques. ...
... The Acoustic Complexity Index (ACI) focuses on the intensity variations in the amplitude between succeeding time frames for a specific frequency bin (Pieretti et al., 2011). The Acoustic Diversity Index (ADI) is calculated by dividing the spectral range of the spectrogram into frequency bins and taking the proportion of the signal energy in each bin above a threshold. ...
The soundscape of different habitats can be discriminated by multiple acoustic indices as they have previously been related to vegetation characteristics. However, the relationship between acoustic indices and topography still needs to be thoroughly evaluated, as well as the variance in the relationship at different spatial scales within the same research system. Networks of forest dynamics plots constructed under the same protocol provide an ideal research platform for addressing the above issue. Our study investigated the relationship between acoustic indices, vegetation, and topographic characteristics at two spatial scales. We recorded soundscapes using autonomous recorders across a tropical forest dynamics plot network consisting of 22 plots in Xishuangbanna, Yunnan Province, southwest China. To exclude recordings with geophony and with biotic sounds from non-avian species, especially from cicadas and frogs, the recordings were previewed aurally and visually, with 9110 min of “clear” bird acoustic recordings chosen for final analysis. We assessed the relative importance of tree species richness, six vegetation characteristics, and three topographic characteristics for five acoustic signal complexity indices, and three statistical indices which describe the properties of frequency spectrum, at 25 m and 50 m spatial scales. We found that topographic complexity was the most significant factor influencing acoustic indices. The variation explained by topographic complexity ranged from 13.2 % to 47.2 % for the seven best-fitted models at both spatial scales. Horizontal vegetation characteristics, including tree density and basal area, were also important variables related to acoustic indices. The Acoustic Diversity Index (ADI) and Bioacoustic Index (BIO) were not associated with vegetation or topographic characteristics at either spatial scale. Three out of seven significant relationships between acoustic indices and vegetation or topographic characteristics disappeared as the spatial scale increased from 25 m to 50 m. In contrast, the significant relationship between Acoustic entropy (H), the centroid (CENT) and skewness (SKEW) and topographic complexity remained stable. Our results suggest that both acoustic signal complexity indices and acoustic statistical indices showed a different relationship to vegetation and topographic characteristics in tropical forests, and the strength of these relationship was scale-dependent. This study revealed that topographic complexity might be an effective predictive variable for further ecoacoustic research.
... In many acoustic surveys, vocalizations of sequential focal (target) animals are counted by a trained listener or automated detection by a computer algorithm, preceded or followed by noise reduction techniques to isolate the signal of interest from background noise (Aide et al., 2013;Kvsn et al., 2020;Sainburg and Gentner, 2021). Other methods (Pieretti et al., 2011;Sueur et al., 2008) census groups of vocalizing animals, such as choruses of singing birds or of calling frogs, where instead of identifying a specific focal animal, the entire soundscape is recorded simultaneously. Kloepper et al. (2016) recently introduced a method based on overall acoustic energy to census flying echolocating bats. ...
... Many animals, however, emit vocalizations that fall within the frequency range of interfering noise sources such as vehicles. Isolating these vocalizations from noise can be challenging (Pieretti et al., 2011;Sainburg and Gentner, 2021). Here, we test whether the energy detection algorithm can be used to estimate vocal activity of small groups of chorusing bullfrogs living in a habitat exposed to anthropogenic noise as well as acoustic interference from other vocalizing frog species. ...
Passive acoustics provides a powerful method for localizing vocalizing animals and estimating species abundance. A passive acoustics method previously used to census dense populations of flying bats is applied here to estimate chorusing activity of male bullfrogs vocalizing against anthropogenic noise. There are significant links between manual counts of the numbers of advertisement call notes and automatically detected notes and two measures of acoustic energy. These data provide a foundation for the use of acoustic energy measures to census vocal activity in different habitats.
... The most common α soundscape indices measure the biodiversity of the soundscape and were inspired by traditional biodiversity indices used in ecology (136,137). The acoustic complexity index [ACI; (138)] is a commonly used index comparing the difference in amplitude from one time interval to the next within a narrow frequency band. Therefore, the data required to calculate an ACI can be extracted from a spectrogram divided into temporal and frequency bins [Section 2.4, (138)]. ...
... The acoustic complexity index [ACI; (138)] is a commonly used index comparing the difference in amplitude from one time interval to the next within a narrow frequency band. Therefore, the data required to calculate an ACI can be extracted from a spectrogram divided into temporal and frequency bins [Section 2.4, (138)]. High ACI values are obtained from soundscapes with high biophony (e.g., bird and insect calls), or geophony (e.g., storms), thus it is hard to make a clear distinction between these two sound categories. ...
Sound is a complex feature of all environments, but captive animals' soundscapes (acoustic scenes) have been studied far less than those of wild animals. Furthermore, research across farms, laboratories, pet shelters, and zoos tends to focus on just one aspect of environmental sound measurement: its pressure level or intensity (in decibels). We review the state of the art of captive animal acoustic research and contrast this to the wild, highlighting new opportunities for the former to learn from the latter. We begin with a primer on sound, aimed at captive researchers and animal caregivers with an interest (rather than specific expertise) in acoustics. Then, we summarize animal acoustic research broadly split into measuring sound from animals, or their environment. We guide readers from soundwave to soundscape and through the burgeoning field of conservation technology, which offers new methods to capture multiple features of complex, gestalt soundscapes. Our review ends with suggestions for future research, and a practical guide to sound measurement in captive environments.
... Nuestros hallazgos contradicen dicha hipótesis y es posible que esto esté a su vez relacionado con la actividad vocal de otras especies en diferentes fases lunares. La probabilidad de detección también estuvo relacionada de manera inversa, con el ACI que ha sido considerado como un índice altamente relacionado con la cantidad de sonidos bióticos del entorno (Fuller et al., 2015;Pieretti et al., 2011;Sueur et al., 2014), aunque este índice puede verse alterado por sonidos como el freno de un carro o la voz humana (Fairbrass et al., 2017) y puede llegar a describir la influencia del ruido del tráfico en el paisaje acústico (Pieretti et al., 2011). De cualquier manera, es claro que la probabilidad de detectar a M. durante las horas del anochecer y disminuye con el paso de la noche, estudios que han pretendido entender los patrones de actividad vocal de algunas especies nocturnas (Goyette et al., 2011), han demostrado que diferentes especies de búhos varían su actividad nocturna durante la noche y suelen tener dos picos de actividad vocal, sin embargo, a nuestro conocimiento, este es el primer estudio que da indicios sobre el efecto de la hora en la probabilidad de detección de una especie del género Megascops. ...
... Nuestros hallazgos contradicen dicha hipótesis y es posible que esto esté a su vez relacionado con la actividad vocal de otras especies en diferentes fases lunares. La probabilidad de detección también estuvo relacionada de manera inversa, con el ACI que ha sido considerado como un índice altamente relacionado con la cantidad de sonidos bióticos del entorno (Fuller et al., 2015;Pieretti et al., 2011;Sueur et al., 2014), aunque este índice puede verse alterado por sonidos como el freno de un carro o la voz humana (Fairbrass et al., 2017) y puede llegar a describir la influencia del ruido del tráfico en el paisaje acústico (Pieretti et al., 2011). De cualquier manera, es claro que la probabilidad de detectar a M. durante las horas del anochecer y disminuye con el paso de la noche, estudios que han pretendido entender los patrones de actividad vocal de algunas especies nocturnas (Goyette et al., 2011), han demostrado que diferentes especies de búhos varían su actividad nocturna durante la noche y suelen tener dos picos de actividad vocal, sin embargo, a nuestro conocimiento, este es el primer estudio que da indicios sobre el efecto de la hora en la probabilidad de detección de una especie del género Megascops. ...
Las rapaces nocturnas, búhos y lechuzas, son un grupo de aves con importantes roles en los ecosistemas, como bioindicadores y predadores tope. Entender aspectos de su ecología e historia natural es vital para la conservación puesto que pueden actuar como especies sombrilla. Dada su naturaleza nocturna, su estudio es complicado, sin embargo, las herramientas acústicas han surgido como una opción para monitorear de manera fidedigna a estas especies. En este estudio se evalúa un algoritmo – funcion autodetec del paquete warbleR – que permitiría la automatización del proceso de revisión de los grandes volúmenes de información generados por un muestreo basado en unidades de grabación automática, y se realizan modelos de ocupación de un búho, Megascops centralis, con el fin de establecer patrones en la ocupación de ésta en paisajes fragmentados y determinar si este tipo demonitoreo es viable para este tipo de especies. Encontramos que el algoritmo, a pesar de lograr identificar vocalizaciones de buena calidad, no resulta eficiente en el resto de las grabaciones de calidad intermedia o baja, que pueden ser frecuentes en este tipo de trabajos. Megascops centralis ocupa lugares con alta cobertura arborea y con dosel relativamente alto (promedio de ocupación= 0.6). La actividad vocal de esta especie estuvo relacionada con la fase lunar (mayor actividad hacia la luna llena), la hora de la noche (mayor actividad al atardecer), y la composición acústica del sitio (mayor actividad con menor cantidad de sonidos). Los resultados de este estudio pueden ser utilizados para el diseño de muestreos de poblaciones de búhos, y para identificar zonas de interes para la protección de estas especies. La base de datos generada tambien representa un insumo importante para el entrenamiento de algoritmos de deteccion automatizada. Esperamos que este trabajo promueva el estudio de este fascinante y poco conocido grupo de aves en el neotrópico
... Just as with other indices of biodiversity, the compression of complex data into a single numeric summary to represent a dynamic ecosystem yields useful information only if researchers carefully examine the relationship between the index and the underlying process of interest (Gasc et al., 2013;Fuller et al., 2015). The index used in this study (Acoustic Complexity Index) is particularly apt at detecting patterns in terrestrial avian activity, especially during dawn chorus (Pieretti et al., 2011;Buxton et al., 2016;Eldridge et al., 2016;Lee et al., 2017;Ross et al., 2018). ...
... To represent low-frequency background sound (anthropogenic and weather sounds), we used nominal onethird octave bands between 0.315-1.25 kHz. We ultimately used a single index, ACI, rather than a suite of indices because it has shown to be a suitable index to describe ecological conditions, particularly avian diversity (Pieretti et al., 2011;Farina et al., 2015;Buxton et al., 2016;Ross et al., 2018). At each site, all 10-min ACI values were summarized into a daily mean. ...
Forest management strategies that create spatially diverse fire-caused disturbance outcomes, consistent with historic fire regimes, are a desired condition for fire adapted western United States forests. In this context, the temporal dynamics of forest response to fire can inform the tempo and scale of forest management, including prescribed burning. Here, we investigated the use of ecoacoustic methods to assess ecological condition in a four-year period (2016–2019) after wildfire in a giant sequoia forest landscape within Kings Canyon National Park, California, United States. Audio recorders at nine sites were deployed soon after the 2015 Rough Fire subsided. The monitoring sites were located in regions with different fire histories, representing five fire history categories. We used the Acoustic Complexity Index (ACI) to document biotic chorus complexity. This previously tested ecoacoustic index provided a daily indicator of biotic sound activity in frequencies dominated by avian calls. Patterns in ACI were evaluated using generalized additive mixed models to understand the relationship with time-since-fire and covariates that accounted for season, fire history category, and weather conditions. We showed that time-since fire and fire-history influenced patterns in ACI after accounting for season and air temperature effects. Monitoring sites where prescribed fire preceded the Rough Fire showed the highest predicted ACI and evidence for a relatively consistent seasonal pattern in ecoacoustic activity across subsequent seasons. Sites without prescribed fire and burned by the Rough Fire exhibited the most pronounced successive decreases in ACI in the first and second years after the fire. The daily temporal resolution of the ecoacoustic index also revealed phenological shifts related to time-since-fire and fire history. Sites unburned by the Rough Fire offered some context for how fire changed ecoacoustic activity post-wildfire, however evidence suggested they were also impacted by the presence of the nearby Rough Fire. The patterns in the ecoacoustic index when combined with vegetation surveys offered complementary insights into ecological dynamics of regeneration after fire. Our exploratory analysis showed that using ecoacoustic methods in wildfire monitoring offers a scalable approach to remote sensing of ecological trends. Archived recordings from the monitoring effort afford future opportunities for new or more detailed insights.
... The objective of this study is to take an insight into the influence mechanism of SNR on four most commonly used AIs, i.e., the bioacoustic index (BIO) (Boelman et al., 2007), the acoustic diversity index (ADI) , the acoustic evenness index (AEI) , and the acoustic complexity index (ACI) (Pieretti et al., 2011). Furthermore, we also presented preliminary ideas to improve the robustness of these AIs, which will be explored in the future. ...
In recent years, passive acoustic monitoring (PAM) has become increasingly popular. Many acoustic indices (AIs) have been proposed for rapid biodiversity assessment (RBA), however, most acoustic indices have been reported to be susceptible to abiotic sounds such as wind or rain noise when biotic sound is masked, which greatly limits the application of these acoustic indices. In this work, in order to take an insight into the influence mechanism of signal-to-noise ratio (SNR) on acoustic indices, four most commonly used acoustic indices, i.e., the bioacoustic index (BIO), the acoustic diversity index (ADI), the acoustic evenness index (AEI), and the acoustic complexity index (ACI), were investigated using controlled computational experiments with field recordings collected in a suburban park in Xuzhou, China, in which bird vocalizations were employed as typical biotic sounds. In the experiments, different signal-to-noise ratio conditions were obtained by varying biotic sound intensities while keeping the background noise fixed. Experimental results showed that three indices (acoustic diversity index, acoustic complexity index, and bioacoustic index) decreased while the trend of acoustic evenness index was in the opposite direction as signal-to-noise ratio declined, which was owing to several factors summarized as follows. Firstly, as for acoustic diversity index and acoustic evenness index, the peak value in the spectrogram will no longer correspond to the biotic sounds of interest when signal-to-noise ratio decreases to a certain extent, leading to erroneous results of the proportion of sound occurring in each frequency band. Secondly, in bioacoustic index calculation, the accumulation of the difference between the sound level within each frequency band and the minimum sound level will drop dramatically with reduced biotic sound intensities. Finally, the acoustic complexity index calculation result relies on the ratio between total differences among all adjacent frames and the total sum of all frames within each temporal step and frequency bin in the spectrogram. With signal-to-noise ratio decreasing, the biotic components contribution in both the total differences and the total sum presents a complex impact on the final acoustic complexity index value. This work is helpful to more comprehensively interpret the values of the above acoustic indices in a real-world environment and promote the applications of passive acoustic monitoring in rapid biodiversity assessment.
... Locally, the first step is to reduce the impact of traffic noise on urban parks. The sound of moving cars and honking not only affects the health of residents, but also has a disturbing effect on vocal organisms such as birds [40,41], thus affecting the content of natural sounds such as birdsong in the park, which in turn weakens the health restoration effect of urban parks, and the impact of traffic noise can be mitigated to some extent by matching shrubs and trees in the green belt on both sides of the road and using plants as a barrier [42]. Second, more natural sound should be introduced. ...
Urban public space environments are critical to the health of residents. In previous studies on urban park environments and health, landscape environment questionnaires have been the main method to evaluate the environmental quality and comfort of urban parks. The research on sound perception also focuses on the exploration of evaluation methods and evaluation indicators; there is little objective empirical evidence in these studies. To further explore the nature of the health role of urban parks, this study started with the sound types of urban parks, based on a field survey, combined the electrocardiogram (ECG) index with the sound type of the park through a portable intelligent device, and HR and RMSSD were selected as the ECG indicators to evaluate the stress relief status. The regression model between the type of acoustic environments and the ECG data was established through the analysis of relevant data. This paper tries to improve the physiological recovery benefit and influence mechanism of sound types in urban parks from an objective point of view and puts forward reasonable suggestions to improve the sound environment in urban parks. The preliminary results show that, in a short time frame, natural sound has a strong relieving effect on mental pressure, while mechanical sound has an obvious impediment effect on the recovery of mental pressure. The results also reveal that the human voice has no obvious impediment effect, and changes in wind and broadcast sound have little impact on the recovery of mental pressure.
... Acoustic signalling (often measured as soundscape diversity) have now received much attention in biogeographical research (Lomolino & Pijanowski, 2021;Robert et al., 2019). One important aspect is that studies have demonstrated that acoustic monitoring is a fast and convenient way to monitor biodiversity because soundscape diversity can act as a proxy for inferring some aspects of biodiversity, such as taxonomic diversity (Buxton et al., 2018;Pieretti et al., 2011;Shamon et al., 2021;Sueur, Pavoine, et al., 2008). ...
The equilibrium theory of island biogeography predicts the positive species–area relationship and the negative species–isolation relationship, resulting in higher species richness on large and close islands. Unlike species richness, soundscape diversity integrates sound from various sources (e.g. biophony, geophony and anthrophony). However, how soundscape diversity varies with island area and isolation still needs to be tested. Here, we explored the island biogeography of bird soundscapes and the determinants of island attributes in shaping bird diversity and soundscape diversity. Thousand Island Lake, Zhejiang, China. Birds. We recorded avian soundscapes by audio recorders and censused bird diversity by line transects on 20 land‐bridge islands. We calculated four acoustic indices (acoustic complexity index, bioacoustic index, acoustic evenness index and acoustic entropy index) to assess acoustic richness, evenness and heterogeneity to explore the soundscape diversity of birds. We used multiple linear regressions, spatial autoregressions and piecewise structural equation models to examine the relationships between bird richness and acoustic diversity, and island attributes. We found positive diversity–area relationships for avian soundscapes. Larger islands had more vocal species and higher habitat diversity, which led to an increment in the richness and unevenness of avian soundscapes on large islands. Acoustic evenness decreased with increasing isolation (distance to the mainland). Soundscapes on large islands are more diverse than those on small islands. Rich acoustic assemblages and heterogeneous habitats promote increased soundscape diversity on islands. Conversely, the lack of vocal contributors, resulting in a decrement in the communication of acoustic signals, can create a lower soundscape diversity on small and remote islands. Our study emphasizes the necessity of examining both species and habitat diversity in island biogeography for better understanding the underlying mechanisms determining biological soundscapes on islands.
... Indeed, this workflow can be used to automatically flag the presence of a sound-producing animal (Gervaise et al., 2021;Mac Aodha et al., 2018;Mankin & Benshemesh, 2006), its identity relative to other conspecifics (Favaro et al., 2017), and its behaviour (Ibrahim et al., 2019;Mortimer et al., 2018;Szymański et al., 2021). Acoustic features can also generate estimates of the total number of sound-producing individuals (Pieretti et al., 2011;Wrege et al., 2017) as well as determine their species identity (Acconcjaioco & Ntalampiras, 2020;Caruso et al., 2020;Kawakita & Ichikawa, 2019;Mukundarajan et al., 2017;Roemer et al., 2021). While being essentially limited to sound-producing animals (but see Jung et al., 2018 for sound production in plants), passive acoustic recorders could record cryptic species in low-visibility conditions and over large spatial distances. ...
High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real‐time and automated monitoring of abiotic components has been possible for some time, monitoring biotic components—for example, individual behaviours and traits, and species abundance and distribution—is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high‐throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which can extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological communities via such technologies has primarily been achieved at low spatiotemporal resolutions within limited steps of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify and count multiple species, and record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology: the ability to rapidly generate high‐resolution, multidimensional and standardised data across complex ecologies.
... A quick way to quantify bird vocalizations is the processing of the intensities recorded in an audio file, leading to the extraction of the Acoustic Complexity Index (ACI) [72,78]. The specific acoustic indicator is linked with the ecological complexity concept [79] and is based on the observation that biological sounds present an intrinsic variability of intensities, in contradiction with human-generated noise that presents constant intensity values [72]. ...
Drystone terraces offer a series of ecosystem services including both biological and cultural benefits. The aesthetic contribution towards the landscape and the increase in biodiversity levels, constitute drystone terraces and other similar constructions, as important biocultural assets. The low maintenance and the eventual abandonment of drystone terraces cause a series of drawbacks regarding the sustainability of agricultural environments. The main goal of this research was to assess the effect of drystone terrace maintenance level on biodiversity. For that reason, two closely distant agricultural areas of Lesbos Island (North Aegean, Greece) in which olive grove drystone terraces dominate were compared. The non-intrusive method of ecoacoustics was selected, and the levels of the acoustic complexity and acoustic diversity were statistically analyzed for areas that included highly maintained and poorly maintained olive grove drystone terraces. The results indicated an increase in acoustic biodiversity levels in the poorly maintained drystone terraces area. At this early stage, the results highlighted the fact that the increased resources in the poorly maintained drystone terraces, in terms of nesting and feeding opportunities, increased the biodiversity levels. Nevertheless, the spatiotemporal expansion of this research is undeniably important.
... In the early years, ecoacoustics research was focused on developing pioneer acoustic indices aimed at estimating species richness and abundance from environmental recordings (Table 1). Bioacoustic index (BIO; Boelman et al., 2007), acoustic entropy (H; Sueur et al., 2008), and acoustic complexity index (ACI; Pieretti, Farina & Morri, 2011) were the earliest alpha indices proposed and showed promising results based on both simulations and field surveys. Promptly available in a graphical user interface software (wavesurfer), ACI became a widely used acoustic index Farina, Pieretti & Morganti, 2013). ...
As biodiversity decreases worldwide, the development of effective techniques to track changes in ecological communities becomes an urgent challenge. Together with other emerging methods in ecology, acoustic indices are increasingly being used as novel tools for rapid biodiversity assessment. These indices are based on mathematical formulae that summarise the acoustic features of audio samples, with the aim of extracting meaningful ecological information from soundscapes. However, the application of this automated method has revealed conflicting results across the literature, with conceptual and empirical controversies regarding its primary assumption: a correlation between acoustic and biological diversity. After more than a decade of research, we still lack a statistically informed synthesis of the power of acoustic indices that elucidates whether they effectively function as proxies for biological diversity. Here, we reviewed studies testing the relationship between diversity metrics (species abundance, species richness, species diversity, abundance of sounds, and diversity of sounds) and the 11 most commonly used acoustic indices. From 34 studies, we extracted 364 effect sizes that quantified the magnitude of the direct link between acoustic and biological estimates and conducted a meta‐analysis. Overall, acoustic indices had a moderate positive relationship with the diversity metrics (r = 0.33, CI [0.23, 0.43]), and showed an inconsistent performance, with highly variable effect sizes both within and among studies. Over time, studies have been increasingly disregarding the validation of the acoustic estimates and those examining this link have been progressively reporting smaller effect sizes. Some of the studied indices [acoustic entropy index (H), normalised difference soundscape index (NDSI), and acoustic complexity index (ACI)] performed better in retrieving biological information, with abundance of sounds (number of sounds from identified or unidentified species) being the best estimated diversity facet of local communities. We found no effect of the type of monitored environment (terrestrial versus aquatic) and the procedure for extracting biological information (acoustic versus non‐acoustic) on the performance of acoustic indices, suggesting certain potential to generalise their application across research contexts. We also identified common statistical issues and knowledge gaps that remain to be addressed in future research, such as a high rate of pseudoreplication and multiple unexplored combinations of metrics, taxa, and regions. Our findings confirm the limitations of acoustic indices to efficiently quantify alpha biodiversity and highlight that caution is necessary when using them as surrogates of diversity metrics, especially if employed as single predictors. Although these tools are able partially to capture changes in diversity metrics, endorsing to some extent the rationale behind acoustic indices and suggesting them as promising bases for future developments, they are far from being direct proxies for biodiversity. To guide more efficient use and future research, we review their principal theoretical and practical shortcomings, as well as prospects and challenges of acoustic indices in biodiversity assessment. Altogether, we provide the first comprehensive and statistically based overview on the relation between acoustic indices and biodiversity and pave the way for a more standardised and informed application for biodiversity monitoring.
... Villanueva-Rivera and Pijanowski, 2016). See Pieretti et al. (2011) for the mathematical formula on its calculation. All recording files from the field were pre-processed through a 500 Hz low-stop filter with a roll-off of 48 dB using the open source program Audacity (v.2.3.3; ...
Passive recording technologies have become a valuable tool for ecologists to accumulate large data sets on vocalizing species assemblages and to study the response of biodiversity to regional and global environmental change. However, the process of interpreting these recordings and identifying species can be time-consuming. To automate this process, and to derive diversity metrics directly from the audio files, soundscape ecologists developed and published many bioacoustics indices, which are calculated using computer algorithms that mathematically summarize the acoustic energy in a recording. Of these indices, the acoustic complexity index (ACI) is perhaps the most widely proposed surrogate of bird species richness. Although several studies have shown the ACI to have positive correlations with species richness, it remains unknown how well the ACI will perform over large, habitat-diverse, regions. Our aim, here, was to examine whether site-level bird species richness (alpha diversity) correlated with the ACI across a large heterogenous mountain region. Further, we explored whether the elevational trends for alpha diversity and the ACI exhibited similar unimodal patterns with corresponding maximums and whether any shifts in the elevation of these maximums could be tracked over time in response to climate change. We deployed recording devices along two extensive transects on the Pacific Crest Trail in California, USA; these included a 689-km trail section in northern California and a 531-km section in southern California. Point counts for birds from the field were combined with the interpretation of the recordings to estimate alpha diversity using a Bayesian multispecies occupancy model. We found that alpha diversity exhibited a positive linear relationship with the ACI on both trail sections. However, these relationships were not strong (low R² values). Similar mid-elevation maximums for alpha diversity and the ACI were observed along the northern trail section. Power analysis revealed that with repeated annual surveys using our protocols, we could detect an average shift in the elevation of either maximum species richness or ACI of approximately 100 m over 20 years (i.e., 5 m/yr), which could be improved in precision to 50 m (i.e., 2.5 m/yr) with a 5-fold increase in survey effort. Although there was considerable unexplained variation in our diversity- and ACI-elevation trends, which we suspect was due to microhabitat and microclimate effects, we concluded that the ACI was a useful, albeit coarse, surrogate of alpha diversity across large regions. The ACI warrants consideration by ecologists and land managers for application in large-scale monitoring programs.
... Some common acoustic indices to reduce the complexity of soundscape data, (candidates to provide proxy for ecosystem health and biodiversity), are the Acoustic Complexity Index (Pieretti et al., 2011), Broadband or overall sound pressure levels, Third Octave Levels, and distinguishing characteristic frequencies and spectra of specific marine species (Au and Hastings, 2008). For example, higher sound-pressure levels in low frequencies in coral reef ecosystems have correlated positively with visual measures of fish diversity, coral cover, and invertebrate abundance (Kennedy et al., 2010;Bertucci et al., 2016;Staaterman et al., 2017;Peck et al., 2021). ...
A soundscape is the recording of all sounds present in an area, creating a holistic view of the acoustic profile in an ecosystem. Studying acoustic parameters of marine soundscapes as a whole has been shown to give an indication of the health status of the location, as well as correlate to which species may be present and using the area. With the rapid innovation of technology, especially data storage and declining cost of equipment, marine soundscape research is fast increasing, and these previous limitations have been switched for computing capacity for data analysis. Here, we perform a systematic assessment of literature of marine soundscape studies, from 1978, when the first soundscape study was reported, until 2021. We identified 200 primary research studies that recorded soundscapes and captured their geographical location, depth, habitat, duration of the study, and number of sites in each study. Using this data, we summarize the state of play in marine soundscapes studies, and identify knowledge gaps in the spatial coverage, depth profiles, habitat representation and study duration. Spatially, studies are biased towards the northern hemisphere. They are also more prevalent in more easily accessible ecosystems, in order from most to least studied, in coastal (38%), pelagic (20%), tropical coral reef (17%), rocky reef (7%), polar (5.5%), seagrass meadows, oyster reef and kelp/algal forest (<5% each) areas, with zones of cold-water coral the least studied (0.3%). Continuing the trend of accessibility, studies also tended to focus on shallow ecosystems. Most recordings (68%) were conducted in the upper 50 m, with 13% in 50-200 m depths, and only 0.6% at a depth >4000 m. With anthropogenic noise and other pollution sources increasing globally, these gaps in research should be further addressed, especially as they pertain to vulnerable ecosystems, many of which are affected by global climate change and anthropogenic influences. It is crucial that marine soundscape studies continue to be developed and pursued, to establish baselines for healthy ecosystems and/or document recovery following management actions.
... We measured six standardized acoustic indices that are commonly used to analyze terrestrial soundscapes, following the recommended guidelines from Bradfer-Lawrence et al. (2019). These indices included the Acoustic Complexity Index (ACI; Pieretti et al., 2011), which quantifies the change in power within each frequency band between adjacent time samples; Acoustic entropy (H; Sueur et al., 2008), which represents the information entropy (Shannon, 1948) in the spectrum of an acoustic signal and ranges between 0 for a pure tonal signal and 1 for random noise; Acoustic Evenness (AEven; Villanueva-Rivera et al., 2011), which measures how evenly power is distributed across frequencies; the Acoustic Diversity Index (ADI; Villanueva-Rivera et al., 2011), which uses the Shannon Diversity Index (Shannon, 1948) to assess variation across frequency bands; the Bioacoustic Index (BIO; Boelman et al., 2007), a measure of the number of occupied frequency bands above 2 kHz and the intensity of power in these bands; and lastly, the Normalized Difference Soundscape Index (NDSI, Kasten et al., 2012), which evaluates relative differences in power between 1 and 2 kHz and power above 2 kHz. Because acoustic indices are not influenced by small differences in microphone sensitivity, we calculated all indices from acoustic data that had not been adjusted using correction coefficients. ...
Over the last decade, an increasing number of studies have used soundscapes to address diverse ecological questions. Sound represents one of the few sources of information capable of providing in situ insights into processes occurring within opaque soil matrices. To date, the use of soundscapes for soil macrofauna monitoring has been experimentally tested only in controlled laboratory environments. Here we assess the validity of laboratory predictions and explore the use of soil soundscape proxies for monitoring soil macrofauna (i.e., earthworm) activities in an outdoor context. In a common garden experiment in northern Sweden, we constructed outdoor mesocosm plots (N = 36) containing two different Arctic vegetation types (meadow and heath) and introduced earthworms to half of these plots. Earthworms substantially altered the ambient soil soundscape under both vegetation types, as measured by both traditional soundscape indices and frequency band power levels, although their acoustic impacts were expressed differently in heath versus meadow soils. While these findings support the as-of-yet untapped promise of using belowground soundscape analyses to monitor soil ecosystem health, direct acoustic emissions from earthworm activities appear to be an unlikely proxy for tracking worm activities at daily timescales. Instead, earthworms indirectly altered the soil soundscape by ‘re-engineering’ the soil matrix: an effect that was dependent on vegetation type. Our findings suggest that long-term (i.e., seasonal) earthworm activities in natural soil settings can likely be monitored indirectly via their impacts on soundscape measures and acoustic indices. Analyzing soil soundscapes may enable larger-scale monitoring of high-latitude soils and is directly applicable to the specific case of earthworm invasions within Arctic soils, which has recently been identified as a potential threat to the resilience of high-latitude ecosystems. Soil soundscapes could also offer a novel means to monitor soils and soil-plant-faunal interactions in situ across diverse pedogenic, agronomic, and ecological systems.
... • Acoustic Entropy Index (H), which highlights the evenness of a signal's amplitude over time and across the available range of frequencies [19]; • Acoustic Complexity Index (ACI), which determines the modulation in intensity of a signal over changing frequencies [36]; ...
The-growing influence of urbanisation on green areas can greatly benefit from passive acoustic monitoring (PAM) across spatiotemporal continua to provide biodiversity estimation and useful information for conservation planning and development decisions. The capability of eco-acoustic indices to capture different sound features has been harnessed to identify areas within the Parco Nord of Milan, Italy, characterised by different degrees of anthropic disturbance and biophonic activity. For this purpose, we used a network of very low-cost sensors distributed over an area of approximately 20 hectares to highlight areas with different acoustic properties. The audio files analysed in this study were recorded at 16 sites on four sessions during the period 25–29 May (2015), from 06:30 a.m. to 10:00 a.m. Seven eco-acoustic indices, namely Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-Acoustic Index (BI), Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NSDI), and Dynamic Spectral Centroid (DSC) were computed at 1 s integration time and the resulting time series were described by seven statistical descriptors. A dimensionality reduction of the indices carrying similar sound information was obtained by performing principal component analysis (PCA). Over the retained dimensions, describing a large (∼80%) variance of the original variables, a cluster analysis allowed discriminating among sites characterized by different combination of eco-acoustic indices (dimensions). The results show that the obtained groups are well correlated with the results of an aural survey aimed at determining the sound components at the sixteen sites (biophonies, technophonies, and geophonies). This outcome highlights the capability of this analysis of discriminating sites with different environmental sounds, thus allowing to create a map of the acoustic environment over an extended area.
... For example, external factors (e.g., wind, habitat type, temperature, time of day, diversity of vocalizations) likely influence the ability of BirdNET to correctly identify a species. Wind noise could be evaluated for a given duration of recording by another prebuilt classifier, and a metric of vocal diversity such as the Acoustic Complexity Index (Pieretti et al. 2011) could be tested for its relationship to false-positive rate. Presumably, more acoustically complex communities present more opportunities for BirdNET to incorrectly identify a vocalization. ...
Occupancy modeling is used to evaluate avian distributions and habitat associations, yet it typically requires extensive survey effort because a minimum of 3 repeat samples are required for accurate parameter estimation. Autonomous recording units (ARUs) can reduce the need for surveyors on-site, yet their utility was limited by hardware costs and the time required to manually annotate recordings. Software that identifies bird vocalizations may reduce the expert time needed if classification is sufficiently accurate. We assessed the performance of BirdNET—an automated classifier capable of identifying vocalizations from >900 North American and European bird species—by comparing automated to manual annotations of recordings of 13 breeding bird species collected in northwestern California. We compared the parameter estimates of occupancy models evaluating habitat associations supplied with manually annotated data (9-min recording segments) to output from models supplied with BirdNET detections. We used 3 sets of BirdNET output to evaluate the duration of automatic annotation needed to approach manually annotated model parameter estimates: 9-min, 87-min, and 87-min of high-confidence detections. We incorporated 100 3-s manually validated BirdNET detections per species to estimate true and false positive rates within an occupancy model. BirdNET correctly identified 90% and 65% of the bird species a human detected when data were restricted to detections exceeding a low or high confidence score threshold, respectively. Occupancy estimates, including habitat associations, were similar regardless of method. Precision (proportion of true positives to all detections) was >0.70 for 9 of 13 species, and a low of 0.29. However, processing of longer recordings was needed to rival manually annotated data. We conclude that BirdNET is suitable for annotating multispecies recordings for occupancy modeling when extended recording durations are used. Together, ARUs and BirdNET may benefit monitoring and, ultimately, conservation of bird populations by greatly increasing monitoring opportunities.
... The acoustic signals are very important for reproduction in many anurans and bird species and these mating calls are much affected by the environment and also by the mating calls of the animals of the same species (Tobias et al., 2004). Modern technologies provide many tools to monitor the acoustic signals of the animals clearly and also the changes in their vocalization due to anthropogenic activities, climate change and land use changes (Pieretti et al., 2011). Japanese great tits birds produce alarm calls to inform other group members about the predator and their alarm calls even contain information about the predator i.e., they produce different alarm calls according to the type of predator (Suzuki, 2014). ...
Development in bioacoustic studies have provided new opportunities to understand the information related with different types of vocalization produced by humans and other living organisms in different conditions. Bioacoustics not only help humans to understand the different types of hidden information present in the acoustic signals of living organisms but also assist in understanding how acoustic signals can be used in improving their health and diagnosing severe diseases easily. Bioacoustics benefit both humans and animals by decoding the relation of the acoustic signals with the behaviour of the animal and environment in which they live. Bioacoustic studies also aid in understanding the effects of anthropogenic activities on acoustic signals of other animals. Monitoring through acoustic tools is most convenient and a large number of precision tools are available in the recent times. This paper reviews the findings of bioacoustic studies published between 2000 to 2020 worldwide. Significant researches in the field of sound communication of different animal species have been cited in this review. Varied animal behaviours can be accounted for based on the sound produced by animals under different physiological state, environmental influences and human activities. Study of animal sounds may be of remarkable value from welfare and conservation perspective.
... Indeed, this workflow can be used to automatically flag the presence of a sound-producing animal (Gervaise et al., 2021;Mac Aodha et al., 2018;Mankin & Benshemesh, 2006), its identity relative to other conspecifics (Favaro et al., 2017), and its behaviour (Ibrahim et al., 2019;Mortimer et al., 2018;Szymański et al., 2021). Acoustic features can also generate estimates of the total number of sound-producing individuals (Pieretti et al., 2011;Wrege et al., 2017) as well as determine their species identity (Acconcjaioco & Ntalampiras, 2020;Caruso et al., 2020;Kawakita & Ichikawa, 2019;Mukundarajan et al., 2017;Roemer et al., 2021). While being essentially limited to sound-producing animals (but see Jung et al., 2018 for sound production in plants), passive acoustic recorders could record cryptic species in low-visibility conditions and over large spatial distances. ...
LINK TO THE PEER-REVIEWED & PUBLISHED ARTICLE:
https://www.researchgate.net/publication/364472513_Towards_the_fully_automated_monitoring_of_ecological_communities
High resolution monitoring is fundamental to understand and predict the dynamics of ecological communities in an era of global change and biodiversity declines. While real-time and fully automated monitoring of the abiotic components of ecosystems has been possible for some time, monitoring the biotic components at different organizational scales, e.g. from individual behaviours and traits to the abundance and distribution of species, is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which are able to extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological populations and communities via such technologies is still in its infancy, being primarily achieved at low spatiotemporal resolutions within specific stages of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify, and count multiple species, and even record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology and conservation: the ability to rapidly generate high resolution, multidimensional, and critically, standardized data across complex ecologies.
... Historically, soundscape analysis has often relied on assessing statistical signatures in data to understand ecological dynamics and patterns in biodiversity (Gottesman et al., 2020;Pieretti et al., 2011;Sueur et al., 2008Sueur et al., , 2014. Incorporating detailed information about species composition and signaling rate will inform our interpretation of the patterns seen in ecoacoustic data and will enhance our ability to understanding how the acoustic signatures of environments relate to the underlying biological and ecological dynamics. ...
The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand‐annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated. We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling. To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer‐based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days. Although our analyses used hand‐annotated data, the methods will extend readily to large‐scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer‐based studies of avian ecology. Relationship between total number of bird species detected via passive acoustic monitoring and the number of recorder days that were analyzed, as measured at Hubbard Brook Forest in New Hampshire.
... cohesion and orientation) may be influenced by the structural complexity of the signal (Candolin, 2003), a commonly studied acoustic parameter in animal communication (e.g. avian vocalisations: Pieretti et al., 2011), although seldom considered in studies that quantify impacts of anthropogenic noise. Simple tonal (sinewave) signals also appear in the natural environment, albeit relatively infrequently compared to complex signals. ...
Rising levels of anthropogenic underwater sound may have negative consequences on freshwater ecosystems. Additionally, the biological relevance of sound to fish and observed responses to human-generated noise promote the use of acoustics in behavioural guidance technologies that are deployed to control the movement of fish. For instance, acoustic stimuli may be used to prevent the spread of invasive fishes or facilitate the passage of vulnerable native species at man-made obstructions. However, a strong understanding of fish response to acoustics is needed for it to be effectively deployed as a fisheries management tool, but such information is lacking. Therefore, this thesis investigated the group behavioural responses of cyprinids to acoustic stimuli. A quantitative meta-analysis and experimental studies conducted in a small-tank or large open-channel flume were used to address key knowledge gaps that are necessary to improve the sustainability of acoustic deterrent technologies, and assist in conservation efforts to reduce the negative impacts of anthropogenic noise.
Current understanding on the impact of anthropogenic noise on fishes (marine, freshwater and euryhaline species) was quantified. The impact of man-made sound is greatest for fish experiencing anatomical damage, for adult and juveniles compared to earlier life-stages, and for fish occupying freshwater environments. These findings suggest a review of the current legislation covering aquatic noise mitigation which commonly focus on marine-centric strategies, thereby undervaluing the susceptibility of freshwater fish to the rising levels of anthropogenic sound. Limitations and knowledge gaps within the literature were also identified, including: 1) group behavioural responses to sound, 2) the response of fish to different fundamental acoustic properties of sound, 3) system longevity (e.g. habituation to a repeated sound exposure), and 4) site-specific constraints.
Fish movement and space use were quantified using fine-scale behavioural metrics (e.g. swimming speed, shoal distribution, cohesion, orientation, rate of tolerance and signal detection theory) and their collective response to acoustics assessed using two approaches. First, a still-water small tank set-up allowed for the careful control of confounding factors while investigating cyprinid group response to fundamental acoustic properties of sound (e.g. complexity, pulse repetition rate, signal-to-noise ratio). Second, a large open-channel flume enabled the ability of a shoal to detect and respond to acoustic signals to be quantified under different water velocities.
Shoals of European minnow (Phoxinus phoxinus), common carp (Cyprinus carpio) and roach (Rutilus rutilus) altered their swimming behaviour (e.g. increased group cohesion) in response to a simple low frequency tonal stimulus. The pulse repetition rate of a signal was observed to influence the long-term behavioural recovery of minnow to an acoustic stimulus. Furthermore, signal detection theory was deployed to quantify the impact of background masking noise on the group behavioural response of carp to a tonal stimulus, and investigate how higher water velocities commonly experienced by fish in the wild may influence the response of roach to an acoustic stimulus. Fine-scale behavioural responses were observed the higher the signal-to-noise ratio, and discriminability of an acoustic signal and the efficacy at which fish were deterred from an insonified channel was greatest under higher water velocities.
The information presented in this thesis significantly enhances our understanding of fish group responses to man-made underwater sound, and has direct applications in freshwater conservation, fish passage and invasive species management.<br/
... Also, within this interval, beyond the dominant anthrophony, some creatures like the common cuckoo (Cuculus canorus), large-billed crow (Corvus macrorhynchos) and the Asiatic toad (Bufo gargarizans) could also contribute to relatively high intensity soundscapes at low frequencies. Since the identification of all species was not attempted within the scope of this research, appearance of false positives may possibly exist with the low-frequency PSD calculation procedure, leading to bias to our results (Fairbrass et al., 2017;Pieretti et al., 2011). But the interesting thing is that upon a further investigation, we found that the anthrophony variation pattern of 1-2 kHz in our study strikingly corresponded to the visitors' daily variation features of 157 urban parks case in Shanghai, China (Ullah et al., 2019) (Mann-Whitney U test, p = 0.869) (see Shanghai case in Fig. 7). ...
Urban foresters are addressing the challenge of urban biodiversity loss through management plans in the context of rapid urbanization. Protecting the integrity of the urban ecosystem requires long-term monitoring and planning for resilience as well as effective management. The soundscape assessment has attracted attention in this field, but applying the soundscape assessment in urban ecological monitoring requires a protocol that links soundscapes to the impact of resource management on biodiversity over time. The effective processing and visualization of large-scale data also remains an important challenge. The aim of this study was to better understand the relationship between soundscape and physical environment, and examine the feasibility of this innovative soundscape approach in highly urbanized areas. Soundscape recordings were collected for 20 urban parks twice on 4 consecutive days in Spring. A total of 691,200 min of sound material were automatically obtained. In order to track the spatio-temporal patterns of a soundscape and determine its potential suitability for ecosystem monitoring, our study characterized soundscape information by adopting 4 widely used acoustic indices: acoustic diversity index (ADI), bioacoustic index (BIO), normalized difference vegetation index (NDSI), and power spectral density (PSD). Daily patterns of PSD have provided a potential connection between soundscapes and bird songs, and 1–2 kHz presented a similar pattern that was linked to human activity. Through further modeling, we tested the relationship of soundscapes to physical environment characteristics. The results showed the importance of habitat vegetation structure for acoustic diversity. More vertical heterogeneity, with an uneven canopy height or multilayered vegetation, was associated with more acoustic diversity. This suggests that clearing ground cover may have a significant negative impact on wildlife. Our results suggest that soundscape approaches provide a way to quickly synthesize large-scale recording data into meaningful patterns that can track changes in bird songs and ecosystem conditions. The proposed approach would enable regular assessment of urban parks and forests to inform adaptive planning and management strategies that can maintain or enhance biodiversity.
... We observed non-trivial amounts of Interference (approximately 10% of recordings) and suggest acoustic studies be aware of ARU deployment techniques and instrument sensitivity to these events (e.g., strapping the unit to a tree to prevent banging in the wind). We believe rapid broad frequency interference should be appropriately accounted for and can negatively influence automated methods, for instance, that compare background noise to changes in acoustic energy (e.g., the acoustic complexity index) (Pieretti et al., 2011). ...
Interest in ecoacoustics has resulted in an influx of acoustic data and novel methodologies to classify and relate landscape sound activity to biodiversity and ecosystem health. However, indicators used to summarize sound and quantify the effects of disturbances on biodiversity can be inconsistent when applied across ecological gradients. This study used an acoustic dataset of 487,148 min from 746 sites collected over 4 years across Sonoma County, California, USA, by citizen scientists. We built a custom labeled dataset of soundscape components and applied a deep learning framework to test our ability to predict these soundscape components: human noise (Anthropophony), wildlife vocalizations (Biophony), weather phenomena (Geophony), Quiet periods, and microphone Interference. These soundscape components allowed us to balance predicting variation in environmental recordings and relative time to build a custom labeled dataset. We used these data to quantify soundscape patterns across space and time that could be useful for environmental planning, ecosystem conservation and restoration, and biodiversity monitoring. We describe a pre-trained convolutional neural network, fine-tuned with our sound reference data, with classification achieving an overall F0.75-score of 0.88, precision of 0.94, and recall of 0.80 across the five target soundscape components. We deployed the model to predict soundscape components for all acoustic data and assess their hourly patterns. We noted an increase in Biophony in the early morning and evening, coinciding with peak animal community vocalization (e.g., dawn chorus). Anthropophony increased during morning/daylight hours and was lowest in the evenings, coinciding with diurnal patterns in human activity. Further, we examined soundscape patterns related to geographic properties at recording sites. Anthropophony decreased with increasing distance to major roads, while Quiet increased. Biophony and Quiet were comparable to Anthropophony at more urban/developed and agriculture/barren sites, while Biophony and Quiet were significantly higher than Anthropophony at less-developed shrubland, oak woodland, and conifer forest sites. These results demonstrate that acoustic classification of broad soundscape components is possible with small datasets, and classifications can be applied to a large acoustic dataset to gain ecological knowledge.
... We divided each three-minute file into a one-minute file using the Kaleidoscope software (Wildlife Acoustics). We used five of the most commonly used acoustic diversity indices related to alpha diversity (Sueur et al. 2014;Bradfer-Lawrence et al. 2019) to analyze the data: the Bioacoustic Index (BI) (Boelman et al. 2007), Acoustic Entropy Index (H) (Sueur et al. 2008b), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI) (Villanueva-Rivera, Pijanowski et al. 2011) and Acoustic Complexity Index (ACI) (Pieretti et al. 2011). The BI and H indices are related to the amplitude and evenness of the biophonic sound frequencies, whereas the ADI and AEI are related to evenness among the pre-established frequency bandwidths. ...
Surveying biodiversity using bioacoustics has become increasingly common worldwide, although it is mostly concentrated in temperate regions. The variety of automatic recorders, the development of free analytical tools, and several acoustic indices have increased the number of studies worldwide. The bioacoustic approach is essential for application in poorly surveyed regions with the pressure of human activities, such as the Brazilian cerrado. We tested the association of four bat diversity metrics (taxonomic, phylogenetic, and two functional diversity metrics, being one based on morphological and the other on acoustical traits, with five commonly used acoustic indices. We used a dataset of 608.4 h obtained from 30 sampling points in three protected areas in Central Brazil. Using Flexible Discriminant Analysis, we identified 21 bat species used in our subsequent analysis. The Entropy index was the best predictor of taxonomic and phylogenetic diversity, whereas the Acoustic Complexity Index was the best predictor of functional morphological diversity. We concluded that acoustic indices are suitable for estimating the diversity of insectivorous bats in the cerrado. However, we registered only part of the bat community, and bats can vary seasonally masking the real diversity of the study area; thus, this method should be used parsimoniously.
... These simple formulas contribute to the wide utility of ACI in dealing with acoustically complex environments. We calculated the ACI from the audio files recorded by the acoustic sensors by adapting Pieretti's method [43] to our data and using the function acoustic_complexity in the 'soundecology' package [44]. ...
The observation and assessment of animal biodiversity using acoustic technology has developed considerably in recent years. Current eco-acoustic research focuses on automatic audio recorder arrays and acoustic indices, which may be used to study the spatial and temporal dynamics of local animal communities in high resolution. While such soundscapes have often been studied above ground, their applicability in soils has rarely been tested. For the first time, we applied acoustic and statistical methods to explore the spatial, diurnal, and seasonal dynamics of the soundscape in soils. We studied the dynamics of acoustic complexity in forest soils in the alpine Pfynwald forest in the Swiss canton of Valais and related them to meteorological and microclimatic data. To increase microclimatic variability, we used a long-term irrigation experiment. We also took soil samples close to the sensors on 6 days in different seasons. Daily and seasonal patterns of acoustic complexity were predicted to be associated with abiotic parameters—that is, meteorological and microclimatic conditions—and mediated by the dynamics of the diversity and activity of the soil fauna. Seasonal patterns in acoustic complexity showed the highest acoustic complexity values in spring and summer, decreasing in fall and winter. Diurnal acoustic complexity values were highest in the afternoon and lowest during the night. The measurement of acoustic diversity at the sampling site was significantly associated with soil communities, with relationships between taxa richness or community composition and acoustic complexity being strongest shortly before taking the soil samples. Our results suggest that the temporal and spatial dynamics of the diversity and community composition of soil organisms can be predicted by the acoustic complexity of soil soundscapes. This opens up the possibility of using soil soundscape analysis as a noninvasive and easy-to-use method for soil biodiversity monitoring programs.
... Towsey et al. (2014) developed a method of representing a long sound file in a single spectrogram that can be viewed whole on a standard computer monitor screen. This was achieved by using acoustic indices, which are numerical summaries of the sound signal calculated at coarse time scales, and which can be considered a form of data compression (Sueur et al., 2008;Pieretti et al., 2011). The compressed spectrograms were generated using three different acoustic indices calculated at 1-min resolution and mapping the values to three color channels (red, green, and blue) to form a "false-color" spectrogram. ...
Continuous recording of environmental sounds could allow long-term monitoring of vocal wildlife, and scaling of ecological studies to large temporal and spatial scales. However, such opportunities are currently limited by constraints in the analysis of large acoustic data sets. Computational methods and automation of call detection require specialist expertise and are time consuming to develop, therefore most biological researchers continue to use manual listening and inspection of spectrograms to analyze their sound recordings. False-color spectrograms were recently developed as a tool to allow visualization of long-duration sound recordings, intending to aid ecologists in navigating their audio data and detecting species of interest. This paper explores the efficacy of using this visualization method to identify multiple frog species in a large set of continuous sound recordings and gather data on the chorusing activity of the frog community. We found that, after a phase of training of the observer, frog choruses could be visually identified to species with high accuracy. We present a method to analyze such data, including a simple R routine to interactively select short segments on the false-color spectrogram for rapid manual checking of visually identified sounds. We propose these methods could fruitfully be applied to large acoustic data sets to analyze calling patterns in other chorusing species.
Forest restoration requires monitoring to assess changes in above- and below-ground communities, which is challenging due to practical and resource limitations. With emerging sound recording technologies, ecological acoustic survey methods—also known as ‘ecoacoustics’—are increasingly available. These provide a rapid, effective, and non-intrusive means of monitoring biodiversity. Above-ground ecoacoustics is increasingly widespread, but soil ecoacoustics has yet to be utilised in restoration despite its demonstrable effectiveness at detecting meso- and macrofauna acoustic signals. This study applied ecoacoustic tools and indices (Acoustic Complexity Index, Normalised Difference Soundscape Index, and Bioacoustic Index) to measure above- and below-ground biodiversity in a forest restoration chronosequence. We hypothesised that higher acoustic complexity, diversity and high-frequency to low-frequency ratio would be detected in restored forest plots. We collected n = 198 below-ground samples and n = 180 ambient and controlled samples from three recently degraded (within 10 years) and three restored (30-51 years ago) deciduous forest plots across three monthly visits. We used passive acoustic monitoring to record above-ground biological sounds and a below-ground sampling device and sound-attenuation chamber to record soil communities. We found that restored plot acoustic complexity and diversity were higher in the sound-attenuation chamber soil but not in situ or above-ground samples. Moreover, we found that restored plots had a significantly greater high-frequency to low-frequency ratio for soil, but no such association for above-ground samples. Our results suggest that ecoacoustics has the potential to monitor below-ground biodiversity, adding to the restoration ecologist’s toolkit and supporting global ecosystem recovery.
Implications for Practice
This is the first known study to assess the sounds of soil biodiversity in a forest restoration context, paving the way for more comprehensive studies and practical applications to support global ecosystem recovery.
Soil ecoacoustics has the potential to support restoration ecology/biodiversity assessments, providing a minimally intrusive, cost-effective and rapid surveying tool. The methods are also relatively simple to learn and apply.
Ecoacoustics can contribute toward overcoming the profound challenge of quantifying the effectiveness (i.e., success) of forest restoration interventions in reinstating target species, functions and so-called ‘services’ and reducing disturbance.
Context
Semi-arid landscapes are naturally heterogeneous with several factors influencing this variation. Fauna responses and adaptations vary in xeric environments, and the scale of observation is important. Biodiversity monitoring at several scales can be challenging, and acoustics are an alternative to this issue.
Objectives
We investigated how audible biodiversity is influenced by environmental factors (e.g.: vegetation metrics, climatic variables, etc.) across a fine spatial scale, aiming to provide a better understanding of the variation in audible species across recording locations placed close together. These results will improve the current knowledge on ecoacoustics as a tool for measuring ecological processes in this biome, and better inform conservation plans.
Methods
We collected data in the semi-arid region in Queensland, Australia placing 24 recorders 200 m apart for 48 h. We also sampled environmental attributes (e.g.: temperature and vegetation structure metrics) and used acoustic indices in a time-series algorithm to categorise sound into classes. Bird species and feeding guilds were also identified.
Results
We found significant differences between proximate sensors, demonstrating that soundscape differences occur across fine spatial scales. Birds and insects were the predominant biophonic sound observed and both groups were associated with shrub cover and subcanopy height. Environments with higher shrub and subcanopy cover had a higher percentage of all birds’ feeding guilds and insects. Sixty-three bird species were identified, including a threatened bird species in Queensland.
Conclusion
We show biodiversity is influenced by vegetation heterogeneity across fine spatial scales in semi-arid regions, identifying which attributes sustain higher levels of biodiversity activity. Our study reveals the practicality of acoustic surveys for this biodiversity monitoring by covering a large area in 48 h. However, we caution that scale is an important consideration when designing surveys.
Background & Aims: The animal community is a key element constituting the urban green-space ecosystem. As an important ecological component of wild animal communities, the soundscape is of great significance in guiding urban green-space landscape design and biodiversity conservation measures. This paper examined 353 articles from the core collection of Web of Science from 2005 to 2022 to comprehensively analyze the spatiotemporal patterns of and influences on animal soundscapes in urban green spaces. Findings: The animal soundscape of urban green space was influenced by environmental-spatial gradients and vegetation spatial structure. Animal sound diversity was inversely correlated with altitude, latitude, urbanization degree, and was also related to vegetation type and height. Phenology of the urban soundscape also showed diurnal, seasonal, and annual variation, including characteristics such as dawn and dusk avian choruses, insect and amphibians nocturnal choruses, and other aspects of animals’ seasonal and annual vocalization patterns. The factors that affect the urban animal soundscape thus include mainly vegetation, environment, anthropogenic interference, and self-driving of animals. Prospects: Despite being one of the hotspots of current soundscape ecology research, animal soundscape research faces challenges such as insufficient investigation of large spatiotemporal scales. Promising directions for future research include the quantitative analysis of influential factors and their response mechanisms as well as the establishment of a global animal soundscape database.
Passive acoustic monitoring has developed rapidly as a tool for ecological assessments, and the use of acoustic indices to assess biodiversity in urban forests promises to be a low-cost and efficient analytical approach. However, the accuracy of using acoustic indices to characterize biodiversity may be compromised by excessive human interference. The acoustic complexity index (ACI) and normalized difference soundscape index (NDSI) were chosen to determine their application value, and explore the spatiotemporal patterns of change in the soundscape of a newly established suburban forest park in China. To understand the influence of drivers such as different sound source types, road distance, and vegetation structure on the soundscape, the Eastern Suburb Forest Park was selected as the study area, and 55 recording points (200 m intervals, 5 × 11 grids) were set up using a systematic grid. Passive acoustic monitoring was performed for four consecutive days in each season, and the spatiotemporal variation of the soundscape was visualized based on indices interpolation. The results showed that when using ACI and NDSI to rapidly assess biodiversity in urban forest environments, attention needs to be paid to the implications of seasonal fluctuations on indices. The temporal variation of the soundscape was closely related to the natural rhythms and vocal activity intensity of organisms. Distance to a nearby main road, distance to water, and structural complexity of vegetation were key factors influencing spatial variation. The findings support the use of acoustic methods to assess the characteristics of soundscapes in human-built urban forests. Soundscape mapping visualizes hotspots and moments of ecoacoustic activity, and has great potential for development in the conservation and management of suburban forest soundscapes.
Soundscapes have been likened to acoustic landscapes, encompassing all the acoustic features of an area. The sounds that make up a soundscape can be grouped according to their source into biophony (sounds from animals), geophony (sounds from atmospheric and geophysical events), and anthropophony (sounds from human activities). Natural soundscapes have changed over time because of human activities that generate sound, alter land-use patterns, remove animals from natural settings, and result in climate change. These human activities have direct and indirect effects on animal distribution patterns and (acoustic) behavior. Consequently, current soundscapes may be very different from those a few hundred years ago. This is of concern as natural soundscapes have ecological value. Losing natural soundscapes may, therefore, result in a loss of biodiversity and ecosystem functioning. The study of soundscapes can identify ecosystems undergoing change and potentially document causes (such as noise from human activities). Methods for studying soundscapes range from listening and creating visual (spectrographic) displays to the computation of acoustic indices and advanced statistical modeling. Passive acoustic recording has become an ecological tool for research, monitoring, and ultimately conservation management. This chapter introduces terrestrial and aquatic soundscapes, soundscape analysis tools, and soundscape management.
The Swift Terrestrial Passive Acoustic Recording Unit from The Cornell Lab of Ornithology, running firmware v. STM32 0.18.6.3, produced an initial 4‐sec sound anomaly in each sound (wave file) recording, created by the power‐saving features of the unit as it switches from standby to record mode. The sound anomaly had a statistically significant impact on several soundscape indices calculated from the recordings. Here, as a case study of identifying and solving this problem, I dissected the nature of the anomaly and analyzed the variable effects it has on calculated ecoacoustic soundscape indices. I used a sample of 150, 10‐min sound files, recorded during my ecoacoustics study in central boreal Alaska during 2019 (June‐August) and 2020 (April‐September), stratified by several landscape conditions and by types of sounds representing anthrophony, biophony, and geophony conditions. The sound anomaly statistically significantly biased the calculations of 7 of 13 ecoacoustic indices analyzed from all of these landscape and soundscape conditions. There is no simple correction factor that can be applied to the calculated index values to account for the effects of the anomaly. I suggest several workarounds, notably to automate a procedure to delete a specified segment of each sound file to eliminate the anomaly prior to soundscape analysis, and in general to watch and correct for such anomalies when using Autonomous Recording Units recordings in ecoacoustic analyses. An unexpected anomaly appeared in ARU audio recordings, significantly affecting calculations of ecoacoustic indices of soundscape conditions of central boreal Alaska. An effective solution was to delete the initial 4 sec of each recording and recalculate the indices. The main lesson is to be aware of, and test for, a potential adverse influence of recording devices and their software.
1. Fluctuations in the diel cycle, especially when compared across different land-use types, can reveal key changes in acoustic activity and the biological community. Yet few studies have assessed the effects of land use change on soundscapes across the diel cycle. The emergence of passive acoustic monitoring (PAM) allows us to monitor landscapes over longer and continuous periods, providing data on temporal variability across the diel cycle.
2. Using AudioMoth acoustic recorders we collected data at 120 sites on the Osa Peninsula, Costa Rica, across a gradient of land use intensity. Information was extracted from recordings using a suite of nine acoustic indices. Principal component analysis reduced the indices into two axes, the first reflecting acoustic activity in the mid frequency bands, where the majority of biotic sound is present, and the second, representing acoustic activity in the upper frequency bands and the ratio of activity between the lower and mid-frequency bands.
3. In disturbed land use types we found reduced acoustic activity during the characteristic dawn and dusk peaks in the diel cycle; known as the dawn and dusk chorus. Palm oil plantations showed a complete loss of these peaks, while teak plantations retained evidence of a weaker dawn and dusk chorus. Restricting the analysis to narrower temporal windows masks these differences among habitats.
4. Synthesis and applications. Evaluating acoustic diversity at specific times of the day, which is common practice in bioacoustics studies, may be misleading, as pronounced changes in acoustic activity at dawn and dusk were obscured. By assessing trends across the diel cycle, we can gain a much better representation of the changes in acoustic activity. Our results show that in disturbed ecosystems there is a deviation in acoustic activity from that seen in a healthy native forest ecosystem, suggesting that there are likely changes within the biotic community in these ecosystems.
Praca ma na celu zbadanie, czy współcześnie wykorzystywane wskaźniki akustyczne mogą mieć zastosowanie w monitorowaniu krajobrazu dźwiękowego ze szczególnym zwróceniem uwagi na ochronę enklaw ciszy występujących w środowisku urbanistycznym. Badanymi współczynnikami były: ACI – wskaźnik złożoności akustycznej, NDSI – wskaźnik znormalizowanej różnicy w krajobrazie dźwiękowym, BI – wskaźnik bioakustyczny, ADI – wskaźnik różnorodności akustycznej, AEI – wskaźnik równomierności akustycznej. W ramach pracy została utworzona baza 90 nagrań dźwiękowych, która została subiektywnie podzielona na trzy grupy: miejsca spokojne, miejsca rozrywki oraz miejsca, w których panuje hałas. Na tym etapie wykazano, że najczęściej rozróżnione zostały nagrania z miejsc spokojnych i miejsc rozrywki. W przypadku współczynnika BI nie udało się rozróżnić żadnej grupy.
This is an overview of how one might go about designing a survey using acoustic sensors, including some theoretical and some technical considerations presented at a high level. It was originally developed for an ecoacoustics workshop in Colombia in 2019.
Underwater noise from human activities is recognized as a world-wide problem, with important repercussions on the acoustic communication of aquatic mammals. During the COVID-19 pandemic, the government of Panama went into a nationwide lockdown to limit the spread of the virus. This lockdown resulted in the closing of tourism infrastructure and limited mobility in both land and coastal areas. We used this “natural experiment” as an opportunity to study the impact of tour-boat activities on dolphin communication by using passive acoustic monitoring data collected before and during the lockdown at Dolphin Bay, Bocas del Toro, Panama. During the lockdown, tour-boat activity was absent, but boats transporting people and supplies were allowed to circulate. The shift in type of boat activity within the lockdown resulted in lower ambient noise levels and more frequent detections of dolphin sounds. We also detected a more diverse whistle repertoire during the lockdown than in the pre-lockdown period, even when accounting for variation in sample coverage. A Random Forest Analysis classified whistles between the two periods with high accuracy (92.4% accuracy, κ = 0.85) based primarily on whistle modulation and duration. During the lockdown, whistles were longer in duration and less modulated than pre-lockdown. Our study shows that a shift in boat traffic activity can generate significant changes in dolphin habitat, and in their communicative signals, an important consideration given ongoing unregulated ecotourism in the region.
This report contains the finding of a two year Citizen Science study, that sought to use acoustic information to assess the effectiveness of two contrasting rewilding interventions. The output of the study was a revised version of the Acoustically Enhanced Ecological Richness (AEER) metric, proposed by Agius (2021) within his BSc dissertation. Supplementary information and the raw data from this project is available via the UK Acoustics Network at (https://drive.google.com/drive/folders/1D5pB1SDhibW0SWNZWDudk38UFnsG3Qkx) and is free to download.
Ecological surveys of coral reefs mostly rely on visual data collected by human observers. Although new monitoring tools are emerging, their specific advantages should be identified to optimise their simultaneous use. Based on the goodness-of-fit of linear models, we compared the potential of passive acoustics and environmental data for predicting the structure of coral reef fish assemblages in different environmental and biogeographic settings. Both data types complemented each other. Globally, the acoustic data showed relatively low added value in predicting fish assemblage structures. The predictions were best for the distribution of fish abundance among functional entities (i.e., proxies for fish functional groups, grouping species that share similar eco-morphological traits), for the simplest functional entities (i.e., combining two eco-morphological traits), and when considering diet and the level in the water column of the species. Our study demonstrates that Passive Acoustic Monitoring (PAM) improves fish assemblage assessment when used in tandem with environmental data compared to using environmental data alone. Such combinations can help with responding to the current conservation challenge by improving our surveying capacities at increased spatial and temporal scales, facilitating the identification and monitoring of priority management areas.
Passive acoustic monitoring technology can depict underwater soundscapes, yet phenological and seasonal patterns and shifts in soundscapes are still poorly understood. Here we analyse the seasonal soundscape in the Eastern Taiwan Strait in 2017 using nonlinear dynamical complexity modelling. We find an annual phenology of fish chorusing that begins in spring, and peaks in summer before beginning to subside in autumn and becoming silent in winter. During spring and summer, the soundscape exhibited significantly higher complexity and predictability than in autumn and winter, due to the presence of regular fish chorusing. Soundscape dynamics shifted from being nonlinear in spring and summer to being linear and stochastic in autumn and winter. Our findings suggest that soundscapes could be used to measure phenological patterns and seasonal shifts in marine species behaviour. We propose that monitoring soundscapes could help assess the long-term health of marine ecosystems under environmental and climatic change. Regular fish chorusing during spring and summer makes the underwater soundscape in the Eastern Taiwan Strait more complex and predictable than in autumn and winter, suggesting that acoustic surveys may help monitor ecosystem health.
Documenting the impacts of invasive species on native fauna is challenging and novel remote techniques may contribute to this urgent task. Two primate species, Callithrix jacchus and Callithrixpenicillata, have become invasive in the Brazilian Atlantic Forest, and are considered a threat to native birds, although very few studies have directly addressed their effect on the local communities. Here we used passive acoustic monitoring and acoustic diversity indices to identify (1) the environmental determinants of the occurrence of the marmosets and (2) the potential impact of these invasive species on the bird communities in a large urban forest (Tijuca Forest, Rio de Janeiro, Brazil). We found that invasive marmosets are associated with forest edges and disturbed areas (characterized by fewer woody lianas and presence of jackfruit trees). More importantly, the invasive marmosets occurrence (after removing the effect of their environmental determinants) was negatively related to the acoustic diversity of the bird dawn choruses, as measured by four out of six commonly used acoustic indices (ACI, ADI, H and NDSI). Our results suggest that these primate species impact on bird communities, although the mechanism behind the reduced acoustic diversity remains unclear (e.g., a consequence of direct predation, a shift on bird signaling behavior as an antipredator strategy, or both). This is one of the first studies to document the effect of marmosets Atlantic Forest bird community and to combine the use of passive acoustics and acoustic indices to address invasive species impacts on biodiversity, a promising approach for biological invasions research.
The acoustic complexity indices represent a family of metrics formulated to extract information from sonic matrices. These indices are based on the differences of acoustic energy measured along a temporal interval of a sonic matrix across all the spectral lines (ACIft) and along each individual spectral line (ACItf) obtaining respectively a temporal and a frequential sonic signature. The distribution of information in time and in frequency returns respectively an ACIft evenness and an ACItf evenness that, when combined in a ternary code with ACIft, compose the codes of Ecoacoustic Events (EE). The Ecoacoustic Events are defined as an emergent aggregation of sonic information that assumes a sense for a species or for an ecological process. In order to obtain realistic data, every sonic matrix must be cleaned from low energetic elements, mainly artifacts, by applying adapt energy filters that are also used to delimit near and far acoustic fields contributing to better understand the relationships between sounds and the environment. A clumping procedure can aggregate original data before the application of ACI metrics. The Sonic Signature Dissimilarity (SSD) is used to assess the distance in ACItf between two sonic matrices. The application of the Shannon theory returns the value of entropy of ecoacoustic events. The application of different temporal scales to the ACI computation allows to overpass the uncertainty in the selection of the more adapt temporal resolution obtaining a fractal dimension of ecoacoustic events and of sonic dissimilarity.
Ecoacoustics is a new discipline that aims to investigate the ecological role of sounds of geological, biophonic, and anthropogenic origin. Its development has been favored by new robust theoretical principles associated to efficient metrics for data processing and by the availability of autonomous acoustic recorders to collect a great number of acoustic files at different temporal and geographical scale.The double role of sound as a semiotic tool to communicate and as ecological proxy of environmental conditions to select habitats and to navigate represents the ideal condition for a rapid development of this discipline. The transformation of latent vibrations as generators of any typology of sound, a clear semiosis that recognizes a sonoscape as the component of the original vibroscape sensed by organisms, and a soundscape as the portion of sonoscape interpreted by individual species are three components of the sonic domain. Sonotope and soundtope, respectively, are sensed and interpreted patches with which soniferous species and acoustic communities interact in a spatial sonic mosaic.The Morphological Adaptation Hypothesis, the Acoustic Adaptation Hypothesis, the Acoustic Niche Hypothesis, the Acoustic Community Hypothesis, and the Acoustic Habitat Hypothesis represent the theoretical fundaments of ecoacoustics.An acoustic community is defined as the collection of soniferous species acoustically active in space and time. Such aggregation of soniferous species determines a sonic environment variable in space and time and represented by sonic matrices (on which to apply ecoacoustics metrics) after a process of migration from a temporal domain to a frequential domain via a Fourier Transform. A large portion of ecoacoustic investigations focuses on the role of noise (especially of anthropogenic origin) on behavioral and ecological processes in terrestrial and in aquatic ecosystems.To describe the complex sonic domain where an originator vibroscape evolves into several distinct objects obtained after a latent, sensed, and interpreted semiosis requires the development of a dedicated narrative. Sonoscape is the result of a sensed vibroscape, and a soundscape is obtained from an interpreted sonoscape. Sonotopes represent the “geographical” elements composing a sonoscape, and their detection is obtained by the deployment of sound recorders according to a configuration that enhances the spatial heterogeneity. Sonotopes are the spatial unit of a sonic information system and represent the link with the geographical character of a landscape. Every sonotope is characterized by species-specific sonic and acoustic signatures. The former (species-specific sonic signature) is the result of a sensed vibroscape and the latter (species-specific acoustic signature) of the interpretation of sonic signals.Ecoacoustic events obtained by coding three metrics (ACIft, ACIft evenness, and ACItf evenness) are an attempt to discretize acoustic signals into functional or statistical distinct units.KeywordsEcoacousticsVibroscapeSonoscapeSonotopeSoundscapeSoundtopeMorphological adaptation hypothesisAcoustic adaptation hypothesisAcoustic niche hypothesisAcoustic habitat hypothesisAcoustic community hypothesis
Several human activities in the urban environment pose as a source of pollution including environmental noise. The increasing human population movement towards urban areas has brought a series of environmental pressures that affect the quality of life and the quality of the overall environment. A response towards the problems caused by noise is the creation of quiet areas in agglomerations. The quiet areas of an urban complex, as defined in the Directive 2002/49 / EC, are a societal response in order to deal with environmental noise. However, the concepts of noise and quietness are multidimensional and vague. So far, two approaches have been applied in order to find quiet areas. The first recognizes noise as a sound of increased intensity and the rational that "less" is better than "more", urges the creation of noise maps in order to highlight areas with lower levels of intensity. An important remark about this particular tactic is the homogenization of all sounds in the light of their intensity. However, the emergence of noise as an urban disease and the promotion of quietness as a panacea, offers short-term and one-dimensional benefits. The second way concerns the general conclusion that the quality of the acoustic environment is responsible for declaring an area as quiet and not the intensity of the sounds it contains. This soundscape approach inevitably leads to the search for the concept of the aforementioned quality and its connection with the concept of quietness. The potential risk of using this tactic, which has now been applied in several European countries, is left to the human instrumental rationality towards the environment, the grouping of opinions in order to highlight the preferred one and the practical application of the dominant opinion in a public space without investing in ecological co-benefits. The goals of this dissertation was to create a flexible protocol for urban quiet areas identification, the efforts of ecological connection of quiet areas, the redefining of the concept of urban quietness and the creation of the new Composite Urban Quietness Index (CUQI) that quantifies the state of urban quiet areas, so that possible changes in the quality of the urban environment are observed in a timely manner. The main research tools were noise level measurements and sound recordings. The collected data were used in such a way as to extract noise maps and sound maps that strengthened the efforts of quiet area identification, with the study area being the city of Mytilene. At the same time, altered fixed tactics of evaluating soundscapes such as the soundwalk were used in order to highlight the perception of the acoustic environment. Then, using a special sampling protocol, the Composite Urban Quietness Index was formed. In conclusion, noise emerged as an immaterial barrier to ecological connectivity in an urban environment. Finally, the dysfunctionality of the so far evaluation metrics which concern exclusively to intensity or preference emerged. The introduction of additional aspects of sound in the analysis of urban acoustic environments regarding frequency and acoustic complexity is considered necessary.
We review Seewave, new software for analysing and synthesizing sounds. Seewave is free and works on a wide variety of operating systems as an extension of the R operating environment. Its current 67 functions allow the user to achieve time, amplitude and frequency analyses, to estimate quantitative differences between sounds, and to generate new sounds for playback experiments. Thanks to its implementation in the R environment, Seewave is fully modular. All functions can be combined for complex data acquisition and graphical output, they can be part of important scripts for batch processing and they can be modified ad libitum. New functions can also be written, making Seewave a truly open-source tool.
We used 4-hr tape recordings to assess singing activity of a Least Bell's Vireo (Vireo belli pusillus) on 7 d distributed throughout the breeding season of 2001. We logged 9873 songs, for a mean singing rate of 5.84 min-1, but despite this level of activity, the bird was silent during 33 percent of the 1691 minutes of the study. Availability, the proportion of minutes in which singing activity occurred (and hence the probability of at least one song occurring in any randomly selected minute) varied from 0.36 to 0.96. As availability is a major component of detection probability, we tested several ways of estimating availability from data that can be obtained during a brief point count. Singing rate (songs/min), estimated in 10 or more 1-min samples randomly distributed through the morning provided a good (r 2 = 0.8) estimate of availability for the entire morning. Measures based on a comparison of singing activity (presence/absence) in contiguous 1-min sam- ples yielded poor estimates of availability, regardless of sample size, presumably because of the highly clumped bout structure (i.e., serial auto-correlation of singing and silence).
We review Seewave, new software for analysing and synthesizing sounds. Seewave is free and works on a wide variety of operating systems as an extension of the R operating environment. Its current 67 functions allow the user to achieve time, amplitude and frequency analyses, to estimate quantitative differences between sounds, and to generate new sounds for playback experiments. Thanks to its implementation in the R environment, Seewave is fully modular. All functions can be combined for complex data acquisition and graphical output, they can be part of important scripts for batch processing and they can be modified ad libitum. New functions can also be written, making Seewave a truly open-source tool.
ABSTRACT Point counts are the most frequently used technique for sampling bird populations and communities, but have well-known limitations such as inter- and intraobserver errors and limited availability of expert field observers. The use of acoustic recordings to survey birds offers solutions to these limitations. We designed a Soundscape Recording System (SRS) that combines a four-channel, discrete microphone system with a quadraphonic playback system for surveying bird communities. We compared the effectiveness of SRS and point counts for estimating species abundance, richness, and composition of riparian breeding birds in California by comparing data collected simultaneously using both methods. We used the temporal-removal method to estimate individual bird detection probabilities and species abundances using the program MARK. Akaike's Information Criterion provided strong evidence that detection probabilities differed between the two survey methods and among the 10 most common species. The probability of detecting birds was higher when listening to SRS recordings in the laboratory than during the field survey. Additionally, SRS data demonstrated a better fit to the temporal-removal model assumptions and yielded more reliable estimates of detection probability and abundance than point-count data. Our results demonstrate how the perceptual constraints of observers can affect temporal detection patterns during point counts and thus influence abundance estimates derived from time-of-detection approaches. We used a closed-population capture–recapture approach to calculate jackknife estimates of species richness and average species detection probabilities for SRS and point counts using the program CAPTURE. SRS and point counts had similar species richness and detection probabilities. However, the methods differed in the composition of species detected based on Jaccard's similarity index. Most individuals (83%) detected during point counts vocalized at least once during the survey period and were available for detection using a purely acoustic technique, such as SRS. SRS provides an effective method for surveying bird communities, particularly when most species are detected by sound. SRS can eliminate or minimize observer biases, produce permanent records of surveys, and resolve problems associated with the limited availability of expert field observers.RESUMENLos conteos por punto son la técnica más utilizada para muestrear poblaciones y comunidades de aves, pero tienen limitaciones tales como los errores intra- e inter-observador y la escasa disponibilidad de observadores expertos. Una solución a estas limitaciones es el uso de grabaciones en el campo para censar aves. Diseñamos un sistema de grabación de paisajes sonoros, SRS (por sus siglas en inglés), que combina un sistema de grabación de cuatro canales discretos con un sistema de reproducción cuadrafónica para el censado de comunidades de aves. Comparamos la efectividad del SRS y la de los conteos por punto para estimar la abundancia, riqueza y composición de comunidades de aves en hábitats riparios en California, comparando los datos colectados simultáneamente con ambas técnicas. Utilizamos el método de remoción-temporal para estimar la probabilidad de detección de individuos y abundancia de especies utilizando el programa MARK. El Criterio de Información Akaike proveyó evidencia sustancial de que existen diferencias en la probabilidad de detección entre ambos métodos y entre las 10 especies más comunes de aves. La probabilidad de detección de aves resultó mayor cuando se escucharon las grabaciones del SRS en el laboratorio que durante los conteos por punto en el campo. Además, los datos tomados con la técnica SRS demostraron estar mejor adaptados a los supuestos del modelo de remoción-temporal y ofrecieron estimados más confiables de abundancia y de probabilidad de detección que los datos de conteos por puntos. Nuestros resultados demuestran cómo la percepción de los observadores puede afectar los patrones de detección temporal durante los conteos por punto, influyendo en las estimaciones de abundancia derivadas de procedimientos de tiempo de detección. Utilizamos el método de captura-recaptura de población cerrada para calcular las estimaciones de jackknife de riqueza de especies y la probabilidad de detección de especies para SRS y conteos por punto, utilizando el programa CAPTURE. Ambos tuvieron índices de riqueza de especies y probabilidades de detección similares. Sin embargo, los métodos difirieron en la composición de especies detectadas basados en el índice de similitud de Jaccard. La mayoría de los individuos detectados durante los conteos por punto (83%) vocalizaron al menos una vez durante el periodo de censado, y estuvieron disponibles para ser detectados utilizando una técnica acústica, como SRS. La técnica SRS provee un método efectivo para censar comunidades de aves, particularmente cuando la mayoría de las especies son detectadas por sus sonidos. El SRS puede eliminar o minimizar los sesgos del observador, producir registros permanentes de los censos, y resolver problemas asociados a la limitada disponibilidad de expertos en el campo.
In the speech technology research community there is anincreasing trend to use open source solutions. We present a newtool in that spirit, WaveSurfer, which has been developed at theCentre for Speech Technology at KTH. It has been designed fortasks such as viewing, editing, and labeling of audio data.WaveSurfer is built around a small core to which mostfunctionality is added in the form of plug-ins. The tool has beendesigned to work on most common platforms and with the aimsthat it...
Ecological variation appears to underlie the evolution of mating signals in many taxa, yet understanding of how this process occurs over time is limited. Here, I investigate whether changes over time in a well-studied mating signal-birdsong-are attributable to ecological factors that affect signal production and transmission. Variation in the acoustic properties of songs is thought to be affected by the mechanics of sound production as well as by features of the habitat that affect sound transmission. To determine whether these mechanisms contribute to song variation, I compare patterns of morphological and habitat variation with variation in song structure among populations of white-crowned sparrows (Zonotrichia leucophrys) at two time points separated by 35 years. Among contemporary (2005) populations, vegetation density and bill size explain significant variation in song structure. The direction of change in song structure between 1970 and 2005 is also consistent with the direction of change in vegetation density. These findings suggest that variation in factors that affect signal production and transmission explains significant variation in white-crowned sparrow song.
Biodiversity assessment remains one of the most difficult challenges encountered by ecologists and conservation biologists. This task is becoming even more urgent with the current increase of habitat loss. Many methods-from rapid biodiversity assessments (RBA) to all-taxa biodiversity inventories (ATBI)-have been developed for decades to estimate local species richness. However, these methods are costly and invasive. Several animals-birds, mammals, amphibians, fishes and arthropods-produce sounds when moving, communicating or sensing their environment. Here we propose a new concept and method to describe biodiversity. We suggest to forego species or morphospecies identification used by ATBI and RBA respectively but rather to tackle the problem at another evolutionary unit, the community level. We also propose that a part of diversity can be estimated and compared through a rapid acoustic analysis of the sound produced by animal communities. We produced alpha and beta diversity indexes that we first tested with 540 simulated acoustic communities. The alpha index, which measures acoustic entropy, shows a logarithmic correlation with the number of species within the acoustic community. The beta index, which estimates both temporal and spectral dissimilarities, is linearly linked to the number of unshared species between acoustic communities. We then applied both indexes to two closely spaced Tanzanian dry lowland coastal forests. Indexes reveal for this small sample a lower acoustic diversity for the most disturbed forest and acoustic dissimilarities between the two forests suggest that degradation could have significantly decreased and modified community composition. Our results demonstrate for the first time that an indicator of biological diversity can be reliably obtained in a non-invasive way and with a limited sampling effort. This new approach may facilitate the appraisal of animal diversity at large spatial and temporal scales.
Understanding the environmental triggers for the calling behaviour of fauna is an important element of biological and ecological knowledge necessary for devising better monitoring and management strategies for wildlife. Amphibians calling is seasonal and in Australia, mostly limited to Spring-Summer (October-March). An investigation was instigated following numerous records of the Sphagnum Frog Philoria sphagnicola calling during periods outside (July) of the standard survey season (August-December). In response to this observation, a data logger was designed and programmed to detect only the calls of P. sphagnicola. At hourly intervals, the data logger recorded the number of frog calls, mean ambient temperature, relative humidity, rainfall, water temperature and barometric pressure. This device differs from data loggers used in other anuran studies in its capacity to record only those calls of the species that it is programmed to detect. Furthermore, the data logger simultaneously records vital environmental variables that are important in trying to decipher the single or multiple factors that may stimulate calling behaviour.
This paper describes a technique for the automated detection of leopard seal (Hydrurga leptonyx) vocalizations. Automatic detection of leopard seal calls within the Antarctic underwater soundscape is difficult because (a) the calls are frequently of low amplitude (b) the call duration is highly variable and (c) the frequency band overlaps with those of many other marine mammal vocalizations. However, humans easily distinguish leopard seal vocalizations from those of other marine mammals because of the calls' distinctive sound, which is a result of the pulsed structure of the leopard seal vocalizations. To exploit the unique temporal evolution of the pulse repetition rate (PRR) in high (HDT) and low (LDT) double trills, the Envelope-Spectrogram Technique (tEST) was developed. The extracted PRR feature allows detection of the target vocalizations even against a background of other marine mammal vocalizations. To handle the high variability of the calls' duration, the tEST algorithm was combined with a Hidden Markov Model (HMM) which is particularly well adapted to handle temporal variability. The developed HMM based detection algorithm worked rather reliably. The detection rate over a 4 day test period was high (72 %) although the signal to noise ratio (SNR) was low (< 10 dB). The number of false positive detections (12 %) was tolerable. Most of the false positives occurred during the period when R/V Polarstern was approaching the recording station and the SNR was temporarily < 0 dB. The detector worked 3 times faster than real-time and is therefore suitable for both off line biological research and time critical in-the-field applications, such as the detection of the presence of leopard seals in the context of human diver operations.
We tested the ability of sound recordings relative to that of point counts to estimate species richness in the Tambopata Reserve in southeast Peru. We tested the effect of two environmental factors (estimated richness and presence of noisy species) and two attributes of species (abundance and foraging height) on estimates of species richness made by point counts and sound recordings. Sound recordings are preferred to point counts when richness is high, as during the dawn chorus, because they allow for repeated listenings. Point counts are more effective than sound recordings at detecting rarely heard species. The presence of noisy species at a station had no effect off the relative ability of the two methods to measure species richness. The foraging height of a species had no effect on its relative detectability by either method. Sound recording was found to be a suitable alternative to point counts for estimating species richness and a preferable alternative under some circumstances.
Effective communication requires that the receiver not only detect the presence of a signal but also discriminate significant variations in signals. Consequently, both attenuation and degradation of the structure of acoustic signals during transmission will limit the range of communication. In this study we document two primary sources of degradation of acoustic signals during propagation through natural environments, irregular amplitude fluctuations and reverberations. Amplitude fluctuations arise especially from atmospheric turbulence, while reverberations also result from scattering surfaces, such as vegetation. Both primarily mask information coded in amplitude modulation of the signal and repetitive frequency modulation, like the trills in the songs of many passerine birds. Irregular amplitude fluctuations primarily mask low frequencies of amplitude modulation in signals. Atmospheric turbulence from wind is the primary determinant of the intensity of irregular amplitude fluctuations, although amplitu...
Traffic noise is known to have a negative impact on bird populations in general, but little is known about the mechanisms by which sound pollution affects bird communities. However, a knowledge of these mechanisms is imperative if we want to account for the differences in susceptibility to traffic noise that exist between species, and may thus be critical for conservation action. To address this issue, population assessments were carried out in a contiguous area of oak-beech forest at differing distances from a much frequented motorway to determine the road effect on the whole bird community. As expected, species richness and diversity decreased towards the motorway, and bird abundance was significantly lower along the motorway than in the control area. However, a few species defied the negative impact of the motorway. The songs of the more abundant passerines were analysed with regard to three frequency parameters to determine whether or not a relationship exists between the song pitch of a species and its sensitivity to noise pollution. A significant relationship was found between dominant frequency and decline in abundance towards the motorway, which indicates that having a higher-pitched song with frequencies well above those of traffic noise makes a bird less susceptible to noise pollution. These results suggest that acoustic masking is one of the mechanisms by which traffic noise negatively affects passerine density along roads.
Conventional acoustic surveys of avian communities require expert skills that are rare,
particularly during the relatively short singing periods of most temperate North American
species. We investigated the use of 2 newly developed omnidirectional microphones for
field recordings of forest bird communities. Our study compared richness and abundance
of species recorded by field experts and those inferred from simultaneous recordings
later analyzed by the same observers. The acoustic recording technique worked well
for bird communities associated with the southern boreal mixedwoods of central
Saskatchewan and western Ontario. Similarity measures for both presence-absence and
abundance data ranged from 83 to 97%/. The acoustic recording technique, particularly
in a stereo configuration, could be used to analyze species composition and relative
abundance of forest bird communities. Moreover, this approach had numerous advantages,
including an archived record of point counts, the use of non-expert field staff to
collect recordings, and the standardization of field data through time.
We tested the ability of sound recordings relative to that of point counts to estimate species richness in the Tambopata Reserve in southeast Peru. We tested the effect of two environmental factors (estimated richness and presence of noisy species) and two attributes of species (abundance and foraging height) on estimates of species richness made by point counts and sound recordings. Sound recordings are preferred to point counts when richness is high, as during the dawn chorus, because they allow for repeated listenings. Point counts are more effective than sound recordings at detecting rarely heard species. The presence of noisy species at a station had no effect on the relative ability of the two methods to measure species richness. The foraging height of a species had no effect on its relative detectability by either method. Sound recording was found to be a suitable alternative to point counts for estimating species richness and a preferable alternative under some circumstances.
Omnidirectional bioacoustic recording systems offer the ability to record forest songbirds in the field by technical staff, and then interpret the recordings later in the laboratory by skilled interpreters. Among several advantages to this approach are the ability to estimate variance among interpreters, obtain a permanent archival record of the point count, reduce costs by using regular field crews to collect data vs. those skilled in bird identification, and remove impediments to breeding bird surveys due to lack of available skilled birders. In this study we first evaluated the effects of microphone configuration and digital processing methods on the quality and effectiveness of the recordings, and then evaluated how consistently skilled birders interpreted the same songbird recordings collected under a mix of environmental conditions, and related this to the commonness of the species. At the time of this evaluation, the most cost-effective configuration of the bioacoustic monitoring system included use of a 180/180 microphone combination, a minidisc digital recording system, analog transfer of the sound data via a digital soundcard, post-processing amplification of the signal, and data storage in an .MP3 format. This combination maintains high sound fidelity while minimizing both expense and data storage requirements. As recording device technology improves, the direct storage and digital transfer of .WAV format files will be the preferred and most effective recording option. Despite noisy conditions due to wind and other ambient sounds for many of the recordings, interpreters showed a high level of similarity in species identification and enumeration for the 34 most abundant species. Standardized coefficient of variance increased sharply when species had fewer than 10 occurrences, suggesting that birders are more variable in their identification of rare or uncommon species. Desktop identification systems that include type specimens of spectrographic signature and sound clips to aid interpreters could improve identification accuracy of rarer species. SINOPSIS. Monitoreo bioacústico de aves de bosques: variabilidad en el interpretador y efecto de la configuración del método de procedimiento digital en el laboratorio Los sistemas de grabación bioacústicos omnidireccionales permiten grabar aves de bosque por personal técnico y luego la interpretación de lo grabado por personal versado o con buena experiencia en el laboratorio. Estre las ventajas de este método se encuentran la habilidad para estimar la variación entre interpretadores, obtener y archivar un record permanente en el lugar de grabación, reducir los costos del trabajo utilizando un pequeño grupo para tomar los datos vs. personal experimentado para la identificación de aves y minimizar los impedimentos de censos de aves no-reproductivas debido a la limitación de observadores experimentados. En este estudio evaluamos, en primer lugar, el efecto de la configuración del micrófono y el método de procesamiento digital en la calidad y efectividad de la grabación. También se evaluó la consistencia del personal experimentado en la interpretación de la grabación del canto bajo condiciones ambientales mixtas, y el relacionar esto con el número de individuos de la especie. Al momento de la evaluación, la configuración más costo-efectiva del sistema de monitoreo bioacústico 4 Corresponding author.
Traffic noise is known to have a negative impact on bird populations in general, but little is known about the mechanisms by which sound pollution affects bird communities. However, a knowledge of these mechanisms is imperative if we want to account for the differences in susceptibility to traffic noise that exist between species, and may thus be critical for conservation action. To address this issue, population assessments were carried out in a contiguous area of oak-beech forest at differing distances from a much frequented motorway to determine the road effect on the whole bird community. As expected, species richness and diversity decreased towards the motorway, and bird abundance was significantly lower along the motorway than in the control area. However, a few species defied the negative impact of the motorway. The songs of the more abundant passerines were analysed with regard to three frequency parameters to determine whether or not a relationship exists between the song pitch of a species and its sensitivity to noise pollution. A significant relationship was found between dominant frequency and decline in abundance towards the motorway, which indicates that having a higher-pitched song with frequencies well above those of traffic noise makes a bird less susceptible to noise pollution. These results suggest that acoustic masking is one of the mechanisms by which traffic noise negatively affects passerine density along roads.
When animals colonize cities they often have to adapt their physiology, life history and behaviour to the novel environment. Songbirds rely on acoustic communication for reproduction, and recent studies indicate that songs vary between urban and nonurban habitats. In cities, birds sing louder or use higher frequencies compared to their conspecifics in forests. These habitat-specific differences in song have been interpreted as an adaptation of the city birds to mitigate acoustic masking by low-frequency traffic noise. We compared the songs of blackbirds, Turdus merula, from the city centre of Vienna and the Vienna Woods and found that forest birds sang at lower frequencies and with longer intervals between songs. This difference in song pitch might reflect an adaptation to urban ambient noise. However, the song divergence could also be the result of more intense vocal interaction in the more densely populated city areas or a side-effect of physiological adaptation to urban habitats. We emphasize the need for experimental studies in blackbirds, but also in other species, to clarify a possible causal link between urban acoustics and song characteristics of city birds.
A large scale, systematic, acoustic survey for whales and seals in eastern Antarctic waters was conducted in January-February 2006. During the BROKE-West survey of Southern Ocean waters between 30 and 80° E longitude, an acoustic survey was conducted to complement a traditional visual survey for marine mammal occurrence and distribution. As part of the survey, 145 DIFAR sonobuoys were deployed every 30’ of latitude on north-south transects, and prior to CTD stations on the initial east-west transect. Underwater sound was analyzed for 70 minute samples from each sonobuoy. Blue whales were the most commonly recorded species, identified at 55 of the sonobuoy deployment sites. Other species recorded include: sperm (46 sites), fin (14), humpback (2), and sei (3) whales, and leopard (11) and Ross (17) seals. Large numbers of blue and sperm whales, and all Ross seals were detected on the westernmost two transects, which were the only transects of the survey with relatively extensive sea ice remaining off the continental shelf. Large numbers of blue whales were also detected in the more eastern waters of the survey off the Prydz Bay region, while two detections of pygmy blue whales represent the farthest south these whales have been recorded. Of the relatively few fin whale detections, most occurred in more northerly waters. Fin whale vocalizations from this region were distinctly different than those recorded elsewhere around Antarctica suggesting acoustic recordings may be useful to delineate regional or stock boundaries of this species. Previously undescribed sounds were attributed to Ross seals. Acoustic detections of these and leopard seal sounds indicate these animals venture further from their traditionally described distributions, with vocalizing leopard seals occurring much further north than might be expected. Overall, the results of the sonobuoy survey provide a measure of each species’ relative spatial distribution over the survey area based on acoustic detections, and when combined with the results of the visual survey, will provide a comprehensive view of marine mammal distribution throughout the region during the BROKE-West survey.
Trends in bird population sizes are an important indicator in nature conservation but measuring such sizes is a very difficult, labour intensive process. Enormous progress in audio signal processing and pattern recognition in recent years makes it possible to incorporate automated methods into the detection of bird vocalisations. These methods can be employed to support the census of population sizes. We report about a study testing the feasibility of bird monitoring supported by automatic bird song detection. In particular, we describe novel algorithms for the detection of the vocalisations of two endangered bird species and show how these can be used in automatic habitat mapping. These methods are based on detecting temporal patterns in a given frequency band typical for the species. Special effort is put into the suppression of the noise present in real-world audio scenes. Our results show that even in real-world recording conditions high recognition rates with a tolerable rate of false positive detections are possible.
Great tits hit the high notes to ensure that their mating calls are heard above the city's din.
accepted for publication. Bird soundscape and the cognitive landscape approach: theory, methods and perspectives
- A Farina
- E Lattanzi
- R Malavasi
- L Piccioli
- N Pieretti
Farina, A., Lattanzi, E., Malavasi, R., Piccioli, L., Pieretti, N., accepted for publication.
Bird soundscape and the cognitive landscape approach: theory, methods and
perspectives. Landscape Ecology.
Advantages and Disadvantages of Acoustic Monitoring of Birds. Realistic Scenarios for Automated Bioacoustic Monitoring in a Densely Populated Region
- K H Frommolt
- K H Tauchert
- M Koch
Frommolt, K.H., Tauchert, K.H., Koch, M., 2008. Advantages and Disadvantages of
Acoustic Monitoring of Birds. Realistic Scenarios for Automated Bioacoustic
Monitoring in a Densely Populated Region. In: Computational Bioacoustics for
Assessing Biodiversity. Proceedings of the International Expert Meeting on ITbased Detection of Bioacoustical Patterns, vol. 234. BfN-Skripten, pp. 83-92.
Tuning of the World (in the United States Under the Title: Soundscape) Destiny Books Singing rate and detection probability: an example from the Least Bell's Vireo (Vireo belli pusillus)
- R M Schafer
- T A Scott
- P Lee
- G C Greene
- D A Mccallum
Schafer, R.M., 1977. Tuning of the World (in the United States Under the Title: Soundscape). Destiny Books. Scott, T.A., Lee, P., Greene, G.C., McCallum, D.A., 2005. Singing rate and detection probability: an example from the Least Bell's Vireo (Vireo belli pusillus). In: Ralph, C.J., Rich, T.D. (Eds.), Bird Conservation Implementation and Integration in the Americas. Proceedings of the Third International Partners in Flight Confer-ence. U.S. D.A. Forest Service, General Technical Report PSW-GTR-191, Albany, CA, pp. 845–853.
Loss of Natural Soundscapes Within the Americas. Wildlife Sanctuary Inc., 10pp. (Online) Retrieved 12
- B Krause
Krause, B., 1999. Loss of Natural Soundscapes Within the Americas.
Wildlife Sanctuary Inc., 10pp. (Online) Retrieved 12 July 2009.
www.wildsanctuary.com/bk asa.pdf.
Testing Biophony as an Indicator of Habitat Fitness and Dynamics. Sequoia National Park (SEKI) Natural Soundscape Vital Signs Pilot Program Report
- B Krause
- L Bernard
- S Gage
Krause, B., Bernard, L., Gage, S., 2003. Testing Biophony as an Indicator
of Habitat Fitness and Dynamics. Sequoia National Park (SEKI) Natural Soundscape Vital Signs Pilot Program Report. Wild Sanctuary Inc.,
http://envirosonic.cevl.msu.edu/seki/Document.asp.
Bird song recognition through spectrogram processing and labelling
- K Wolf
Wolf, K., 2009. Bird song recognition through spectrogram processing and
labelling. Available from: http://www.tc.umn.edu/∼wolfx265/DREU/project/
final report/final report.pdf.
Avisoft Sound Analysis and Synthesis Laboratory (Version
- R Specht
Specht, R., 2006. Avisoft Sound Analysis and Synthesis Laboratory (Version
Detecting bird sounds in a complex acoustic environment and applica-tion to bioacoustic monitoring Using soundscape recordings to estimate bird species abundance, richness, and composition
- R Bardeli
- D Wolff
- F Kurth
- M Koch
- K H Tauchert
- K H Frommolt
- A Murillo
- J L Deppe
- M F Allen
Bardeli, R., Wolff, D., Kurth, F., Koch, M., Tauchert, K.H., Frommolt, K.H., 2010. Detecting bird sounds in a complex acoustic environment and applica-tion to bioacoustic monitoring. Pattern Recognition Letters 3, 1524–1534, doi:10.1016/j.patrec.2009.09.014. Celis-Murillo, A., Deppe, J.L., Allen, M.F., 2009. Using soundscape recordings to estimate bird species abundance, richness, and composition. Journal of Field Ornithology 80, 64–78.
- B F Manly
Manly, B.F., 1997. Randomization, Bootstrap, and Monte Carlo Methods in Biology,
2nd ed. Chapman and Hall, London.
Avisoft Sound Analysis and Synthesis Laboratory (Version 4.4) Copyright
- R Specht
Specht, R., 2006. Avisoft Sound Analysis and Synthesis Laboratory (Version
4.4) Copyright 1990-2006 [Computer software].
StatSoft, Statistica Electronic Manual. Version 8
- Statsoft
StatSoft, 2008. StatSoft, Statistica Electronic Manual. Version 8, Statsoft Inc.,. Tulsa,
Oklahoma, USA.
Singing rate and detection probability: an example from the Least Bell's Vireo (Vireo belli pusillus) Bird Conservation Implementation and Integration in the Americas
- T A Scott
- P Lee
- G C Greene
- D A Mccallum
Scott, T.A., Lee, P., Greene, G.C., McCallum, D.A., 2005. Singing rate and detection
probability: an example from the Least Bell's Vireo (Vireo belli pusillus). In:
Ralph, C.J., Rich, T.D. (Eds.), Bird Conservation Implementation and Integration
in the Americas. Proceedings of the Third International Partners in Flight Conference. U.S. D.A. Forest Service, General Technical Report PSW-GTR-191, Albany,
CA, pp. 845–853.
Tuning of the World (in the United States Under the Title: Soundscape)
- R M Schafer
Schafer, R.M., 1977. Tuning of the World (in the United States Under the Title:
Soundscape). Destiny Books.
Cool Edit Pro V.2 User's Manual. Syntrillium Software Corp
- J Sueur
- S Pavoine
- O Hamerlynck
- S Duvail
Sueur, J., Pavoine, S., Hamerlynck, O., Duvail, S., 2008b. Rapid acoustic survey for biodiversity appraisal. PLoS ONE 3 (12), e4065, doi:10.1371/journal.pone.0004065.
Syntrillium Software Corp (Ed.), 2002. Cool Edit Pro V.2 User's Manual. Syntrillium
Software Corp., San Jose, CA.
Bioacoustics Software Version 2.1 Documentation
Wildlife Acoustics, 2007. Songscope. Bioacoustics Software Version 2.1 Documentation. Wildlife Acoustics Inc.