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International audience; Crickets (Ensifera, Grylloidea) are not commonly used as ecological indicators in contrary to other Orthoptera (e.g., grasshoppers and katydids). However, they are sensitive to environmental changes and abundant in tropical regions. To evaluate whether crickets are relevant bioindicators of tropical ecosystems, we investigated cricket assemblages along a tropical ecological gradient. We collected crickets during both day and night in southern New Caledonia for three stages of ecological succession: open shrubland, preforest, and forest. Simultaneously, we measured several environmental variables, such as temperature and relative humidity, at each sampling site. Cricket species assemblages showed a clear response to ecological succession. The highest and lowest species richness and abundances of individuals were, respectively, found in forest and shrubland, with species specialized in each ecological stage revealing the conservation value of each of these stages. Similar results were found when considering only the part of cricket communities with the ability to acoustically communicate. This work is part of a larger research program about Neocaledonian crickets and contributes to support the use of acoustic approaches to monitor tropical environments. In conclusion, these findings highlight the potential value of crickets as an environmental indicator in tropical ecosystems. The results also contribute to the discussion of the intrinsic conservational value of shrublands in New Caledonia and similar ecotypes.; Bien que d’autres groupes d’orthoptères soient largement utilisés comme bioindicateur, les grillons sont peu considérés dans les études écologiques. Pourtant, les grillons sont à la fois sensibles aux changements environnementaux et très abondants dans les régions tropicales. Dans cette étude, nous avons décrit les assemblages de grillons le long d’un gradient écologique en milieu tropical. Nous avons collecté les individus en période nocturne et diurne, sur 12 sites, et dans trois formations végétales du Sud de la Nouvelle Calédonie : le maquis, le paraforestier et le forestier. Des variables environnementales comme la température et l’humidité relative ont été collectées simultanément aux relevés de grillons. Les assemblages de grillons montrent une réponse très claire à la succession environnementale, suivant le gradient écologique, avec une diversité d’espèce et une abondance d’individus plus élevées en milieu forestier qu’en milieu maquis. Chaque stade du gradient écologique montre un assemblage unique d’espèces. Des résultats similaires sont obtenus en ne considérant que la part de la communauté des grillons qui utilisent l’acoustique pour communiquer. Ces résultats, interprétés à la lumière de travaux complémentaires faisant parties du même programme de recherche sur les grillons de Nouvelle-Calédonie, supporte l’analyse de relevés acoustiques pour évaluer l’état des milieux. En conclusion, les résultats soutiennent l’intérêt des grillons comme indicateurs écologiques du milieu tropical. Ces résultats contribuent également à la reconnaissance de la valeur intrinsèque des maquis en terme de conservation de la biodiversité en Nouvelle-Calédonie et dans des écotypes similaires.

Passive acoustic monitoring can be an effective method for monitoring species, allowing the assembly of large audio datasets, removing logistical constraints in data collection and reducing anthropogenic monitoring disturbances. However, the analysis of large acoustic datasets is challenging and fully automated machine learning processes are rarely developed or implemented in ecological field studies. One of the greatest uncertainties hindering the development of these methods is spatial generalisability—can an algorithm trained on data from one place be used elsewhere?We demonstrate that heterogeneity of error across space is a problem that could go undetected using common classification accuracy metrics. Second, we develop a method to assess the extent of heterogeneity of error in a random forest classification model for six Amazonian bird species. Finally, we propose two complementary ways to reduce heterogeneity of error, by (i) accounting for it in the thresholding process and (ii) using a secondary classifier that uses contextual data.We found that using a thresholding approach that accounted for heterogeneity of precision error reduced the coefficient of variation of the precision score from a mean of 0.61 ± 0.17 (SD) to 0.41 ± 0.25 in comparison to the initial classification with threshold selection based on F-score. The use of a secondary, contextual classification with thresholding selection accounting for heterogeneity of precision reduced it further still, to 0.16 ± 0.13, and was significantly lower than the initial classification in all but one species. Mean average precision scores increased, from 0.66 ± 0.4 for the initial classification, to 0.95 ± 0.19, a significant improvement for all species.We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.

Funder: Canon Foundation in Europe; Id: http://dx.doi.org/10.13039/100005286, Passive acoustic monitoring (PAM) has emerged as a transformative tool for applied ecology, conservation and biodiversity monitoring, but its potential contribution to fundamental ecology is less often discussed, and fundamental PAM studies tend to be descriptive, rather than mechanistic. Here, we chart the most promising directions for ecologists wishing to use the suite of currently available acoustic methods to address long‐standing fundamental questions in ecology and explore new avenues of research. In both terrestrial and aquatic habitats, PAM provides an opportunity to ask questions across multiple spatial scales and at fine temporal resolution, and to capture phenomena or species that are difficult to observe. In combination with traditional approaches to data collection, PAM could release ecologists from myriad limitations that have, at times, precluded mechanistic understanding. We discuss several case studies to demonstrate the potential contribution of PAM to biodiversity estimation, population trend analysis, assessing climate change impacts on phenology and distribution, and understanding disturbance and recovery dynamics. We also highlight what is on the horizon for PAM, in terms of near‐future technological and methodological developments that have the potential to provide advances in coming years. Overall, we illustrate how ecologists can harness the power of PAM to address fundamental ecological questions in an era of ecology no longer characterised by data limitation. Read the free Plain Language Summary for this article on the Journal blog.

Sound production represents an integral part of social communication in many teleost fish; however, few studies have investigated the structure, organization and variability of fish sounds at the community level. Fish acoustic community structure was recorded simultaneously in three sites located along the Mediterranean basin within the endemic habitat of Posidonia oceanica seagrass beds. Acoustic diversity and species-specific sound features were expected to differ between locations. We predicted that, in communities characterized by higher acoustic richness, fish species would specialize in their use of acoustic resources (i.e. realized acoustic niche compression), while the overall allocation of resources within the community signal space would expand. The fish acoustic communities inhabiting Posidonia beds were characterized by the same main contributors (the /Kwa/, Ophidion rochei and Sciaena umbra sound types). However, their relative occurrence, abundances and use of acoustic resources were site-specific. Acoustic diversity differed between geographic locations. The range of spectral and temporal resources exploited by the fish acoustic community was wider in sites where acoustic richness was at its highest score. Ophidion rochei was highly specialized in its use of temporal resources where acoustic richness was higher, whilst S. umbra appeared less efficient in specializing the use of spectral and temporal resources. By showing that the same species can exploit different acoustic resources between locations, this study supports the concept of Acoustic Niche plasticity (i.e. plasticity of acoustic resources allocation within a species). The results suggest that the degree of acoustic niche plasticity might be determined by the species-specific degree of sound-producing system plasticity. In turn, different degrees of acoustic niche plasticity might determine different species-specific levels of acoustic adaptability to changing biotic or environmental conditions., Marie Curie COFUND - University of Liege, Grant/Award Number: 600405; University of Liege, Grant/Award Number: contract N° 09/2020.

This ethno-artistic essay proposes to contribute to debates concerning soundscape ecology, ecomusicology and the Anthropocene by investigating the human context and personal dimension of soundscape reception, perception and intervention through varying outputs. It seeks to tie in with this special issue of CfP "A Sonic Anthropocene – Sound Practices in a Changing Environment" via the suggestion of new forms of discursive involvement with the changing environment, such as artistic (re)interpretation or remix of soundscape source material, audio-visual and literary storytelling, and also textual travel logging and field notes. My goal with this essay is three-fold. The first, to conduct a poietic re-signification of various soundscapes recorded in 2018 during a trek between Lukla and Mount Everest, Nepal. The second, to provide a more in-depth ethno-artistic proposal via the presentation of accompanying audiovisual essays in the form of story maps (thus further demonstrating transformational processes between lived and relived experiences), and thirdly, due my own trek playing a part in the ongoing touristification of Everest, to suggest – through my audio-textual-visual work – possible creative, reverential and positive potentialities in alternate methodologies for ethnographers and data-gatherers alike, particularly in documenting the shifting Everest environment and providing a ‘picture in time’ of its changing land and soundscape.

RESUMEN Diferentes iniciativas han permitido conocer los sonidos de los mamíferos neotropicales. Aunque en Colombia hay algunos repositorios de registros bioacústicos, la Colección de Sonidos Ambientales Mauricio Alvarez-Rebolledo del Instituto Humboldt (IAvH-CSA) es la única de acceso público. Nuestro objetivo fue explorar la representatividad de mamíferos en la IAvH-CSA y promover su uso entre la comunidad masto-zoológica colombiana. Encontramos 129 registros, la mayoría de Primates. Los registros incluyen representación de todas las regiones geográficas, excepto el Catatumbo, y 21 de los 32 departamentos del país. Aun así, solo el 3 % de las especies de mamíferos de Colombia están representadas en la colección. Éstas han sido grabadas en su mayoría por ornitólogos. Por tanto, hacemos un llamado a apoyar los repositorios públicos en nuestro país, depositar los registros acústicos para garantizar accesibilidad a estos y abordar futuras preguntas en la bioacústica de mamíferos de Colombia. ABSTRACT Different initiatives have allowed to know the sounds of neotropical mammals. Although in Colombia there have been some repositories of bioacustics records, the Environmental Sound Collection Mauricio Alvarez-Rebolledo of the Humboldt Institute (IAvH-CSA, Spanish acronym) is the only with public access. Our objectives were to explore the representativeness of mammals in the IAvH-CSA, and to promote the use of this collection within Colombian mammalogists. We found 129 recordings in the collection; the majority corresponding to primates. Recordings had representativeness of all geographic regions, except Catatumbo, and 21 out of 32 Colombian departments. Even though, only 3 % of the mammals' species from Colombia are represented in this collection. Most of the recordings have been provided by ornithologists. Therefore, we make a call to support public repositories in our country, to deposit the acoustic recordings to guarantee accessibility, and allowing to approach further questions regarding this group.

A participatory monitoring programme of an exceptional modification of urban soundscapes during Covid-19 containment (Data collection in progress)

Estimation of avian biodiversity is a cornerstone measure of ecosystem condition. Surveys conducted using autonomous recorders are often more efficient at estimating diversity than traditional point‐count surveys. However, there is limited research into the optimal temporal resolution for sampling—the trade‐off between the number of samples and sample duration when sampling a survey window with a fixed survey effort—despite autonomous recorders allowing easy repeat sampling compared to traditional survey methods. We assess whether the additional temporal coverage from high temporal resolution (HTR) sampling, consisting of 240 15‐s samples spread randomly across a survey window detects higher alpha and gamma diversity than low temporal resolution (LTR) sampling of four 15‐min samples at the same locations. We do so using an acoustic dataset collected from 29 locations in a region of very high avian biodiversity—the eastern Brazilian Amazon. We find HTR sampling outperforms LTR sampling in every metric considered, with HTR sampling predicted to detect approximately 50% higher alpha diversity, and 10% higher gamma diversity. This effect is primarily driven by increased coverage of variation in detectability across the morning, with the earliest period containing a distinct community that is often under sampled using LTR sampling. LTR sampling produced almost four times as many false absences for species presence. Additionally, LTR sampling incorrectly found 70 species (34%) at only a single forest type when they were in fact present in multiple forest types, while the use of HTR sampling reduced this to just two species (0.9%). When considering multiple independent detections of species, HTR sampling detected three times more uncommon species than LTR sampling. We conclude that high temporal resolution sampling of passive‐acoustic monitoring‐based surveys should be considered the primary method for estimating the species richness of bird communities in tropical forests.

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, This study was supported by a research project funded by the Comunidad de Madrid and the European Social Fund (PEJ2018-AI/AMB-9957, to D. L.). We thank Camille Desjonquères for her valuable comments on the study design, Alison Cooper for her exhaustive and insightful revision of the manuscript, and anonymous reviewers for their significant contribution. I. A. and L. S. M. S. acknowledge research grants provided by the Comunidad de Madrid (PEJ-2018-AI/ AMB-9957, to D. L.) and the Ministerio de Economía, Industria y Competitividad of Spain (PEJ-2018-004603-A, to D. L.), respectively, together with the support of the European Social Fund. H. L. was supported by the FPI program of the Ministerio de Ciencia e Innovacion of Spain (grant CGL2017-86926-P). D. L. also acknowledges a postdoctoral grant provided by the Comunidad de Madrid (2020-T1/AMB-20636, Atraccion de Talento Investigador, Spain) and a research project funded by the Ministerio de Economía, Industria y Competitividad (CGL2017-88764-R, MINECO/AEI/FEDER, Spain)

Ecoacoustics needs sophisticated acoustic monitoring tools to extract a wide level of features from an observed mixture of sounds. We have developed a portable acoustic monitoring system called ‘HARKBird’ which consists of a laptop PC and an inexpensive commercial microphone array with the robot audition software HARK. HARKBird can extract acoustic events in a recording, and we can obtain the begin and end timings, the spatial information (e.g., position or direction from the microphone array), and the spectrogram of the sound separated from the original recording. In this study, we report how robot audition techniques contribute to monitoring spatio‐spectro‐temporal dynamics of bird behaviors, using an extended and minimal system based on multiple microphone arrays. The dimension reduction of separated sounds is important to integrate the information from multiple microphone arrays. As a dimension reduction algorithm, we use t‐SNE to help manual annotation of each sound and to generate the vocalization distribution automatically. We conduct playback experiments to Spotted Towhee (Pipilo maculatus) to simulate different cases of territorial intrusions (song/call/no playback). Our hypothesis in playback experiments is that playback of conspecific vocalizations would invoke aggressive responses of males against song playbacks and the effects would be more prominent than those of call playbacks. Our primary aim is to test whether our system can extract the necessary information on the aggressiveness of target individuals to examine our hypothesis. We show the system with manual annotation of vocalizations can extract their different spatio‐spectro‐temporal dynamics in different conditions, which supported our hypothesis. We also consider the spectral affinity‐based automatic matching of localized sounds from different microphone arrays. The relative number of localized songs depending on the playback conditions reflected a similar trend to those in the manual approach, implying that we can grasp the long‐term dynamics of vocalizations without costly annotations.

Species distribution models (SDMs) are a key tool for biogeography and climate change research, although current approaches have some significant drawbacks. The use of species occurrence constrains predictions of correlative models, while there is a general lack of eco-physiological data to develop mechanistic models. Passive acoustic monitoring is an emerging technique in ecology that may help to overcome these limitations. By remotely tracking animal behaviour across species geographical ranges, researchers can estimate the climatic breadth of species activity and provide a baseline for refined predictive models. However, such integrative approach still remains to be developed., Here, we propose the following: (a) a general and transferable method to build acoustic SDMs, a novel tool combining acoustic and biogeographical information, (b) a detailed comparison with standard correlative and mechanistic models, (c) a step-by-step guide to develop aSDMs and (d) a study case to assess their effectiveness and illustrate model outputs, using a year-round monitoring of calling behaviour of the Iberian tree frog at the thermal extremes of its distribution range. This method aims at forecasting changes in environmental suitability for acoustic communication, a key and climate-dependent behaviour for a wide variety of animal taxa., SDMs identified strong associations between calling behaviour and local environmental conditions and showed robust and consistent predictive perfor mance using two alternative models (regression and boundary). Furthermore, these models better captured climatic variation than correlative models as they use observations at higher temporal resolution. These results support aSDMs as efficient tools to model calling behaviour under future climate scenarios., The proposed approach offers a promising basis to explore the capacity of vocal species to deal with climate change, supported by an innovative integration of two disciplines: bioacoustics and biogeography. aSMDs are grounded on ecologically realistic conditions and provide spatially and temporally explicit predictions on calling behaviour, with direct implications in reproduction and survival. This enables to precisely forecast shifts in breeding phenology, geographic distribution or species persistence. Our study demonstrates how acoustic monitoring may represent an increasingly valuable tool for climate change., D.L. acknowledges a post-doctoral grant provided by the Comunidad de Madrid (2020-T1/AMB-20636, Atracción de Talento Investigador, Spain), and research projects funded by the European Commission (EAVESTROP–661408, Global Marie S. Curie fellowship, program H2020, EU) and the Ministerio de Ciencia, Innovación y Universidades (CGL2017-88764-R, MINECO/AEI/FEDER, Spain). S.V.-P. acknowledges a post-doctoral grant provided by the Comunidad de Madrid (2017-T2/AMB-6035).

Humans categorize unwanted sounds in the environment as noise. Consequently, noise is associated with negative human and ecological values, especially when it is derived from an anthropogenic source. Although evidence confirms that many machine-generated anthropogenic sounds have negative impacts on animal behavior and communication, natural sources of non-biological sound, such as wind, rain, running water, and sea waves (geophonies) have also been categorized as noise and are frequently dismissed or mischaracterized in acoustic studies as an outside factor of acoustic habitats rather than an integrated sonic component of ecological processes and species adaptations. While the proliferation of machine-generated sound in the Biosphere has become an intrusive phenomenon in recent history, geophony has shaped the Earth’s sonic landscapes for billions of years. Therefore, geophonies have very important sonic implications to the evolution and adaptation of soniferous species, forming essential ecological and semiotical relationships. This creates a need to distinguish geophonies from machine-generated sounds and how species respond to each accordingly, especially given their acoustic similarities in the frequency spectrum. Here, we introduce concepts and terminology that address these differences in the context of ecoacoustics. We also discuss how Acoustic Complexity Indices (ACIs) can offer new possibilities to quantifiably evaluate geophony in relation to their sonic contest.

High rates of biodiversity loss caused by human-induced changes in the environment require new methods for large scale fauna monitoring and data analysis. While ecoacoustic monitoring is increasingly being used and shows promise, analysis and interpretation of the big data produced remains a challenge. Computer-generated acoustic indices potentially provide a biologically meaningful summary of sound, however, temporal autocorrelation, difficulties in statistical analysis of multi-index data and lack of consistency or transferability in different terrestrial environments have hindered the application of those indices in different contexts. To address these issues we investigate the use of time-series motif discovery and random forest classification of multi-indices through two case studies. We use a semi-automated workflow combining time-series motif discovery and random forest classification of multi-index (acoustic complexity, temporal entropy, and events per second) data to categorize sounds in unfiltered recordings according to the main source of sound present (birds, insects, geophony). Our approach showed more than 70% accuracy in label assignment in both datasets. The categories assigned were broad, but we believe this is a great improvement on traditional single index analysis of environmental recordings as we can now give ecological meaning to recordings in a semi-automated way that does not require expert knowledge and manual validation is only necessary for a small subset of the data. Furthermore, temporal autocorrelation, which is largely ignored by researchers, has been effectively eliminated through the time-series motif discovery technique applied here for the first time to ecoacoustic data. We expect that our approach will greatly assist researchers in the future as it will allow large datasets to be rapidly processed and labeled, enabling the screening of recordings for undesired sounds, such as wind, or target biophony (insects and birds) for biodiversity monitoring or bioacoustics research.

International audience; Forests, deserts, rivers, and oceans are filled with animal vocalizations and geological sounds. We postulate that climate change is changing the Earth's natural acoustic fabric. In particular, we identify shifts in acoustic structure that all sound-sensitive organisms, marine and terrestrial, may experience. Only upstream solutions might mitigate these acoustic changes.

Environmental Sonic Translation offers a collection of compositional techniques drawing on detailed analyses of environment-derived soundscapes, which can be found in geological, biological, and anthropogenic sources. It relies on audio technology to collect sounds, analyze their spectra and reassign their features to musical instruments. This research is situated within the fields of Ecoacoustics/Acoustic Ecology, Spectralism, and musique concrète, building a framework that responds to the aesthetic, conceptual and technical principles of environmental sonic translation. The main purpose of this work is to embody the various ways in which sound exists in the world. In this dissertation, I offer a systematic analytic and notational methodology applicable to a wide field of soundscapes, culminating in a compositional body of work generated with the techniques presented. As a background, I discuss influential work that has contributed to the field of environmental sonic translation.

Ecoacoustic approaches have the potential to provide rapid biodiversity assessments and avoid costly fieldwork. Their use in biodiversity studies for improving management and conservation of natural landscapes has grown considerably in recent years. Standardised methods for sampling acoustic information that deliver reliable and consistent results within and between ecosystems are still lacking. Sampling frequency and duration are particularly important considerations because shorter, intermittent recordings mean recorder batteries last longer and data processing is less computationally intensive, but a smaller proportion of the available soundscape is sampled. Here, we compare acoustic indices and processing time for subsamples of increasing duration clipped from 94 one-hour recordings, to test how different acoustic indices behave, in order to identify the minimum sample length required. Our results suggest that short recordings distributed across the survey period accurately represent acoustic patterns, while optimizing data collection and processing. ACI and H are the most stable indices, showing an ideal sampling schedule of ten 1-minute samples in an hour. Although ADI, AEI and NDSI well represent acoustic patterns under the same sampling schedule, these are more robust under continuous recording formats. Such targeted subsampling could greatly reduce data storage and computational power requirements in large-scale and long-term projects.

Anthropogenic noise, which is part of an urban soundscape, can negatively affect the behaviour of wild animals. Here we investigated how biophony (animal sounds) was affected by noise in an urban Brazilian forest fragment. Our hypothesis was that noise and biophony would differ between the border and the centre of the forest fragment (i.e., lower biophony predicted in noisy areas). Two passive acoustic monitoring devices were used to record soundscapes one week per month, 24 hour per day, from May to July 2012. The Acoustic Complexity Index (ACI) was used to quantify biophony and the Power Spectral Density (PSD) to quantify urban noise. PSD and ACI were higher on the border than in the centre of the fragment. PSD was lower in July, while the ACI did not significantly vary between months. Noise levels were also higher on the border. Conversely, potential species richness was higher in the centre of the forest fragment. Higher biophony at noisy sites can be interpreted as behavioural responses of species for communicating in noisy areas. Alternatively, they could be the result of species segregation by degree of vocal plasticity or due to differences in composition of communities.

New technologies like ecoacoustic surveys promise time and cost efficiency for biodiversity assessments, serve as a basis for effective conservation policies, and are particularly appealing for remote and highly diverse tropical areas. Acoustic indices facilitate the analysis of large acoustic datasets but no consensus on their performance has been reached yet. We evaluated the efficacy of four acoustic indices (Acoustic Complexity Index, Acoustic Diversity Index, Acoustic Evenness Index, Acoustic Entropy) for sound data analysis and biodiversity assessments inside a national park and the agricultural mosaic landscape of north-eastern Madagascar, a global biodiversity hotspot. We used self-built sound recorders to continuously record soundscapes on 80 plots across seven land-use types (old-growth forest, forest fragment, forest–derived and fallow-derived vanilla agroforest, herbaceous and woody fallow, rice paddy) and compared index values between land–use types, assessed the correlation with bird species richness as measured by point counts, and related the acoustic indices to plot- and landscape-scale parameters. The Acoustic Diversity Index, Acoustic Evenness Index (inverse) and Acoustic Entropy were highest in old-growth forest and lowest for rice paddies and fallow land. Index values for structurally similar land-use types did not differ significantly from each other. The correlation of the three acoustic indices with bird species richness was strongest during daytime (R²≥0.30). Differences in the index values were best explained by land-use type and vegetation density. Our results showed that all investigated indices except the Acoustic Complexity Index were suitable biodiversity indicators for a tropical, agricultural landscape. Soundscape diversity was positively affected by plot-scale vegetation structure, emphasizing the importance of forests and particularly old-growth forest for conservation. We demonstrated that acoustic indices and sound recordings are a useful tool for assessing biodiversity in tropical agricultural mosaic landscapes. To realize the full potential of ecoacoustics in conservation, sampling guidelines and user-friendly analysis packages will be key to facilitate a wider implementation. ispartof: Ecological Indicators vol:120 issue:2021 status: Published online

This thesis demonstrates an approach to composing with environmental sound that uses spatial concepts and techniques to bridge the aesthetic divide between reductive and relative compositional philosophies. It responds to the complex issues of contextual integration and separation through a detailed compositional approach, which uses the spatial medium of acousmatic music to translate aspects of acoustic ecology, biomimetics, soundscape and ecoacoustics into the domain of contemporary composition. This research makes claims to new knowledge by examining how compositional activities inform the development of novel techniques for environmental sound composition. It takes a practice-based approach to research, which uses the creative practices of field recording, fixed-media composition and software programming to highlight and respond to the issues implicit to the production of environmentally mediated spaces through sound. Furthermore, it provides new theoretical perspectives on the relations between musical form and the external environment. Central to this research is a body of creative work, which presents a portfolio of compositions and the custom software tools integral to its production as research outcomes. As the activities of practice and the insights gained through practice are as crucial to the practice-based research paradigm as its outcomes, this thesis uses a self-reflective approach to document how the knowledge generated during the composition process shaped the outcomes of the creative artefacts. An engagement with spatial concepts characterises the reflective discourse. The non-linear and iterative ways of shaping and applying these ideas in practice underpin the discussion of each composition and the algorithmic realisation of these concepts using the SuperCollider programming language.

Tropical regions host most of the biodiversity found on Earth, but these species-rich areas are constantly threatened by human development and other disturbances that put this diversity of life forms at risk. To avoid extirpations of animal and plant species, scientists and managers rely on accurate monitoring techniques to retrieve information about population trends. This task is not easy, especially in the tropics, where there is often a lack of personnel to conduct surveys, a lack of funding, and the areas are so extensive that many countries need to be involved in monitoring (e.g., Amazon biome). For this reason, scientists are trying to take advantage of technological advancements to develop more cost-effective alternatives for multi-taxa surveys. While satellite imagery provides a richness of information about vegetation, it fails to provide direct measurement of the fauna. In this dissertation conducted in the Brazilian Amazon, I used passive acoustic recorders as a technique to collect reliable and verifiable information about the fauna. I show that the data collected with passive acoustic sensors is able to provide information about how the biodiversity of the Amazon changes with human disturbances, time of the day, and in different environments.

Background Automated sound recorders are a popular sampling tool in ecology. However, the microphones themselves received little attention so far, and specifications that determine the recordings’ sound quality are seldom mentioned. Here, we demonstrate the importance of microphone signal-to-noise ratio for sampling sonant animals. Methods We tested 12 different microphone models in the field and measured their signal-to-noise ratios and detection ranges. We also measured the vocalisation activity of birds and bats that they recorded, the bird species richness, the bat call types richness, as well as the performance of automated detection of bird and bat calls. We tested the relationship of each one of these measures with signal-to-noise ratio in statistical models. Results Microphone signal-to-noise ratio positively affects the sound detection space areas, which increased by a factor of 1.7 for audible sound, and 10 for ultrasound, from the lowest to the highest signal-to-noise ratio microphone. Consequently, the sampled vocalisation activity increased by a factor of 1.6 for birds, and 9.7 for bats. Correspondingly, the species pool of birds and bats could not be completely detected by the microphones with lower signal-to-noise ratio. The performance of automated detection of bird and bat calls, as measured by its precision and recall, increased significantly with microphone signal-to-noise ratio. Discussion Microphone signal-to-noise ratio is a crucial characteristic of a sound recording system, positively affecting the acoustic sampling performance of birds and bats. It should be maximised by choosing appropriate microphones, and be quantified independently, especially in the ultrasound range.

Understanding soundscapes, that is, the totality of sounds within a location, helps to assess nature in a more holistic way, providing a novel approach to investigating ecosystems. To date, very few studies have investigated freshwater soundscapes in their entirety and none across a broad spatial scale.In this study, we recorded 12 freshwater streams in South East Queensland continuously for three days and calculated three acoustic indices for each minute in each stream. We then used principal component analysis of summary statistics for all three acoustic indices to investigate acoustic properties of each stream and spatial variation in their soundscapes.All streams had a unique soundscape with most exhibiting diurnal variation in acoustic patterns. Across these sites, we identified five distinct groups with similar acoustic characteristics. We found that we could use summary statistics of AIs to describe daytimes across streams as well. Most difference in stream soundscapes was observed during the daytime with significant variation in soundscapes both between hours and among sites. Synthesis and Application. We demonstrate how to characterize stream soundscapes by using simple summary statistics of complex acoustic indices. This technique allows simple and rapid investigation of streams with similar acoustic properties and the capacity to characterize them in a holistic and universal way. While we developed this technique for freshwater streams, it is also applicable to terrestrial and marine soundscapes., Understanding soundscapes helps to assess nature in a holistic way and provides a novel approach to investigate ecosystems. In unprecedented spatial and temporal resolution, we recorded 12 freshwater streams in south‐east Queensland for multiple days, calculated three acoustic indices and used a principal component analysis to investigate acoustic properties of each stream. While all streams had a unique soundscape, we could also identified five distinct groups with similar acoustic characteristics across all sites, showing our technique allows a rapid investigation of stream soundscape.

In recent years, a widespread decline has been seen in honey bee population and this is widely attributed to colony collapse disorder. Hence, it is of utmost importance that a system is designed to gather relevant information. This will allow for a deeper understanding of the possible reasons behind the above phenomenon to aid in the design of suitable countermeasures. Electronic Beehive Monitoring is one such way of gathering critical information regarding a colony’s health and behavior without invasive beehive inspections. In this dissertation, we have presented an electronic beehive monitoring system called BeePi that can be placed on top of a super and requires no structural modifications to a standard beehive (Langstroth or Dadant beehive), thereby preserving the sacredness of the bee space without disturbing the natural beehive cycles. The system is capable of capturing videos of forager traffic through a camera placed over the landing pad. Audio of bee buzzing is also recorded through microphones attached outside just above the landing pad. The above sensors are connected to a low-cost raspberry pi computer, and the data is saved on the raspberry pi itself or an external hard drive. In this dissertation, we have developed an algorithm that analyzes those video recordings and returns the number of bees that have moved in each video. The algorithm is also able to distinguish between incoming, outgoing, and lateral bee movements. We believe this would help commercial and amateur beekeepers or even citizen scientists to observe the bee traffic near their respective hives to identify the state of the corresponding bee colonies. This information helps those mentioned above because it is believed that honeybee traffic carries information on colony behavior and phenology. Next, we analyzed the audio recordings and presented a system that can classify those recordings into bee buzzing, cricket chirping, and ambient noise. We later saw how a long–term analysis of the intensity of bee buzzing could help us understand the hive’s development through an entire beekeeping season. We also investigated the effect of local weather conditions using 21 different meteorological variables on the forager traffic. We collected the meteorological data from a weather station located on the campus of Utah State University. Through our study, we were able to show that without the use of additional costly intrusive hardware to count the bees, we can use our bee motion counting algorithm to calculate the bee motions and then use the counts to investigate the relationship between foraging activity and local weather. To ensure that our findings and algorithms can be reproduced, we have made our datasets and source codes public for interested research and citizen science communities.

Knowledge that can be gained from acoustic data collection in tropical ecosystems is low‐hanging fruit. There is every reason to record and with every day, there are fewer excuses not to do it. In recent years, the cost of acoustic recorders has decreased substantially (some can be purchased for under US$50, e.g., Hill et al. 2018) and the technology needed to store and analyze acoustic data is continuously improving (e.g., Corrada Bravo et al. 2017, Xie et al. 2017). Soundscape recordings provide a permanent record of a site at a given time and contain a wealth of invaluable and irreplaceable information. Although challenges remain, failure to collect acoustic data now in tropical ecosystems would represent a failure to future generations of tropical researchers and the citizens that benefit from ecological research. In this commentary, we (1) argue for the need to increase acoustic monitoring in tropical systems; (2) describe the types of research questions and conservation issues that can be addressed with passive acoustic monitoring (PAM) using both short‐ and long‐term data in terrestrial and freshwater habitats; and (3) present an initial plan for establishing a global repository of tropical recordings.

Made available in DSpace on 2022-05-01T05:29:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 Advances in technologies for data acquisition, storage and analysis have boosted Acoustic Ecology studies, but protocols are still lacking. There is a need of more research to understand which methodologies can be applied to answer ecological questions in different environments with varying temporal and spatial dynamics. Tropical forests are generally more complex than temperate ones, both in terms of use of acoustic space and species diversity. The seasonally dry tropical forest (SDTF) in Brazil, known as Caatinga, is a threatened biome, with two marked seasons that shape vegetation and animal activity patterns. In this study, we investigate the applicability of passive acoustics in monitoring SDTF, describing the soundscape and tracking diel patterns and seasonal changes. Combining multiple indices, visualization through false colour spectrograms and clustering, we describe the acoustic activity of the main faunal groups that compose the biophonic orchestra in a SDTF area in the Northeast of Brazil. Distinct patterns were found between day – when birds and wind were the main sound sources – and night – with Orthopterans occupying a large frequency band. Other sound sources in the SDTF soundscape included cicada, rain, and anthropogenic influence such as domestic animals, cars and gunshots. Clustering of eleven acoustic indices was useful to distinguish sound patterns from several sources, especially in the dry season. Further investigation within each cluster showed specific relationships among selected indices and different sound sources. Birds were associated with Entropy of the Spectral Peaks (EPS) and Orthopterans also had a relationship with EPS, as well as with Entropy of Average Spectrum (EAS) and High Frequency Cover (HFC). Variation in diel values of these selected indices, as well as the number of samples included in each cluster category, were successfully used to describe the acoustic activity of Birds and Orthopterans and to track changes between rainy and dry seasons. A better understanding of the soundscape dynamics in a highly seasonal tropical environment was achieved by applying cheap and reliable novel methodologies to study biodiversity in geopolitical regions where funding for conservation initiatives is limited. Laboratório de Bioacústica (LaB) Departamento de Fisiologia e Comportamento Biosciences Center Universidade Federal do Rio Grande do Norte Avenida Senador Salgado Filho, 3000, Bairro Lagoa Nova Science and Engineering Faculty Queensland University of Technology, 2 George St Spatial Ecology and Conservation Lab (LEEC) Department of Biodiversity State University of Sao Paulo (UNESP), Av. 24 A, 1515 Graduate Program in Ecology Biosciences Center Universidade Federal do Rio Grande do Norte Avenida Senador Salgado Filho, 3000, Bairro Lagoa Nova Spatial Ecology and Conservation Lab (LEEC) Department of Biodiversity State University of Sao Paulo (UNESP), Av. 24 A, 1515

Passive acoustic monitoring (PAM) is an increasingly common method for studying populations of vocally active species. However, the detection of individuals not resident to a site may obfuscate inferences about occurrence and population change. Here, we provide a framework for distinguishing resident from non-resident individuals to estimate territory—rather than site—occupancy in PAM programs by leveraging datasets on vocal behavior and acoustic detections for spotted owls (Strix occidentalis) in the Sierra Nevada, California, USA. Based on acoustic/GPS tags, the extent over which individuals typically vocalized (the “vocal home range”) was small relative to space use, such that the likelihood of double counting resident territory-holders across multiple survey sites was low. However, comparing passive acoustic detections to known resident owl locations revealed that detections occurred at PAM survey sites known to be unoccupied, possibly because of the presence of non-territorial individuals. Strict thresholds that required acoustic detections over multiple survey periods successfully removed all detections of non-resident individuals but increased the probability of not detecting resident individuals. Conversely, relatively liberal thresholds that minimized the probability of missing resident individuals increased the probability of detecting non-residents. Thus, a tradeoff exists between error types, with optimal threshold criteria dependent on conservation objectives. Our study highlights the importance of examining patterns in individual vocal behavior and acoustic detections to minimize inferential errors in PAM. It also provides a generalizable framework that can be tailored according to specific conservation objectives to strengthen inferences from PAM as it becomes standard practice in conservation science.

Disturbance regimes and biodiversity—two factors that govern the stability of ecosystems—are changing rapidly due to anthropogenic forces including climate change. Determining whether ecosystems retain their structure and function through intensifying disturbance regimes is an urgent task. However, quantitatively assessing the resilience of natural systems is a complex and challenging endeavor, especially for animal communities, for which datasets around disturbance events are scarce. Here, we apply an emerging remote sensing technology—the recording and analysis of soundscapes—to quantify the resilience of Puerto Rican coral reef and dry forest animal communities in relation to Hurricane Maria, which struck the island in September 2017. Using recordings collected between March 2017 and January 2018 at three terrestrial and three marine sites, we measured three dimensions of resilience—the magnitude of the impacts (resistance), the spatial pattern of the impacts (heterogeneity), and the diversity and timeline of functional responses (recovery)—across eight sound types representing different broad taxonomic groups. While the coral reef communities exhibited high resistance to the storm, all sound types within the dry forest were significantly impacted, with two of the three insect choruses and bird vocalizations at dawn declining approximately 50% in the weeks following Hurricane Maria. The mid-frequency insect sound type returned to pre-storm levels after 56 days, while bird vocalizations returned after 67 days, though seasonal and lunar patterns underscored the importance of long-term data for accurately measuring trajectories of recovery. This study demonstrates that soundscape methodologies can help to quantify elusive dimensions of animal community resilience in order to better understand how biodiversity and ecosystem functioning will change under novel disturbance regimes.

Habitat loss and fragmentation represent two of the most significant threats to biodiversity. In some regions, like the Brazilian Cerrado, the deforestation rate can reach nearly 1 million hectares per year. Ecoacoustics and acoustic indices can be used to promote rapid assessments in threatened regions. We evaluated how two particular indices (the acoustic diversity index − ADI − and normalized difference soundscape index − NDSI) reflect bird species richness and composition in a protected area near Brasilia city. We hypothesised that ADI should reflect the characteristics of birds in the cerrado and in the gallery forest, i.e., with higher values in gallery forest than in the cerrado. Based on habitat structure, we also hypothesised that NDSI should be lower in less complex habitat, and lower in areas close to urbanized areas. We assessed 30 locations by installing automatic recorders to generate 15 min wave files (48 kHz, 16 bits, stereo). Manual inspection of the files revealed the presence of 107 bird species (74 in gallery forest and 47 in cerrado). Our results showed that ADI was significantly associated with species richness, being higher in gallery forest than in the cerrado. We found that NDSI values were lower in areas close to highways, an important source of impact for bird diversity. We argue that acoustic indices are a valid approach for rapid biodiversity assessment, however basic knowledge on species occurrences is essential to interpret the values provided by these indices.

This dataset is the first effort to combine the audio biodiversity of a taxonomic group in a selected location, the Boyaca department in Colombia. We conducted a detailed review of the sound recordings for birds from the Boyaca department within three repositories, the environmental sound collection of the Humboldt Institute, the Macaulay Library of the Cornell Lab of Ornithology, and the xeno-canto platform of the Naturalis Biodiversity Center. We selected recordings that were identified up to species and had complete metadata information. Using latitude and longitude information, we assigned each recording to one of the three regions and one of the 12 biotic units reported for Boyaca. We reported a total of 2321 recordings belonging to the Andean region (1892), Orinoquian region (425), and Carare-Lebrija-Nechi-Sinu (4). The sounds of Boyaca birds have been sampled for approximately three decades, with two peaks of activity in the early 2000's and 2018. We also included a map with the distribution of biotic units and sound recordings of our dataset. This dataset can be used to extract acoustic traits to test hypotheses of turnover in the acoustic space or traits by species, or to compare acoustic traits between species. It can also allow decision-makers to support biodiversity-based economies such as avitourism.

International audience; Three new monorchiid trematodes are reported from fishes of the families Nemipteridae and Pomacanthidae; two species are described from the southern Great Barrier Reef and the third from off Moorea, French Polynesia. Allobacciger polynesiensis sp. nov. is described from Centropyge flavissima (Cuvier), Allobacciger brevicirrus sp. nov. from Scolopsis bilineata (Bloch) and Scolopsis margaritifera (Cuvier), and Allobacciger annulatus sp. nov. from Centropyge tibicen (Cuvier), Centropyge vroliki (Bleeker) and Centropyge bicolor (Bloch). The three species most closely resemble the type-species, Allobacciger macrorchis Hafeezullah & Siddiqi, 1970, as well as Allobacciger centropygis Machida & Uchida, 2001, differing primarily in the morphology of the terminal genitalia and excretory vesicle. With the introduction of these new species, the most recent generic concept does not accurately reflect all species in the genus, and we provide a revised generic diagnosis to accommodate the new taxa. Complete ITS2 rDNA, partial 28S rDNA, partial 18S rDNA and partial cox1 mtDNA sequence data were generated for the three new species; all markers distinguish the three species reported here unambiguously. Phylogenetic analyses of the new sequence data show that the three new species of Allobacciger Hafeezullah & Siddiqi, 1970 form a well-supported clade.

We studied the annual dynamics of the biotic component of the acoustic environment in a lowland monsoon tropical forest. The study was conducted in Nam Cat Tien National Park (southern Vietnam) from January 2013 to January 2014. We placed an autonomous recorder at the Nam Cat Tien ecosystem flux observation station at a height of 35 m. For the analysis, we selected 1–4 5-min recordings per day collected at 5.30 a.m., 12.00 a.m., 4.00 p.m., and 8.00 p.m. For each recording, we calculated four acoustic indices: the acoustic complexity index (ACI), the bioacoustic index (BIO), the acoustic diversity index (ADI) and the acoustic evenness index (AEI). These indices had roughly similar annual dynamics and peaked from May to August (i.e., immediately before the wet season and in the wet season). We then related the four acoustic indices to the daily values of the following meteorological variables: air temperature, air relative humidity, solar radiation, and precipitation sum. The BIO, ADI and AEI were most influenced by daily average humidity. We therefore concluded that humidity rather than precipitation, temperature or radiation was the best predictor of the annual dynamics of acoustic activity in Nam Cat Tien. The increase in humidity was apparent several months before the major rains began in 2013 (i.e., before the wet season). We suggest that future ecoacoustics studies in the tropics should give greater consideration to humidity as a variable determining the acoustic activity of local fauna.

With the continued adoption of passive acoustic monitoring as a tool for rapid and high-resolution ecosystem monitoring, ecologists are increasingly making use of a suite of acoustic indices to summarise the sonic environment. Though these indices are often reported to well represent some aspect of the biology of an ecosystem, the degree to which they are confounded by various extraneous sonic conditions is largely unknown. We conducted an aural inventory across 23 field sites in Okinawa to identify the number of unique animal sounds present in recordings. Using these values of ‘measured richness’, we then examined how the performance of 11 commonly-used acoustic indices varied across a range of sonic conditions (including in the presence and absence of insect stridulations, audible wind or rain, and human-related sounds). Our analysis identified both well- and poor-performing acoustic indices, as well as those that were particularly sensitive to sonic conditions. Only two indices reflected measured richness across the full range of sonic conditions examined. A few indices were relatively insensitive to extraneous sonic conditions, but no index correlated with measured richness when masked by sound from broadband stridulating insects. Our results demonstrate considerable sensitivity of most commonly used acoustic indices to confounding sonic conditions, highlighting the challenges of working with large acoustic datasets collected in the field. We make practical recommendations for acoustic index use based on study design, with the aim of identifying the suite of acoustic indices with greatest utility as indicators for rapid biodiversity monitoring and management of the world’s natural soundscapes.

Protected areas (PAs) monitoring is a technical bottleneck that limits the implementation of decision-making processes for natural resource and wildlife management. Recent methodological advances make passive acoustic monitoring and associated acoustic index analysis an increasingly suitable method for PAs monitoring. Acoustic indices are mathematical filters that can provide standardised comparative information about the acoustic energy, which can be applied to compare communities. In this study we test whether acoustic indices are sufficiently sensitive to detect differences in the soundscape within each of the four seasons between a PA (the Serra do Cipo National Park, Brazil) and a surrounding farmland area. Statistical analysis of results from 12 acoustic indices is used to identify which of 20 acoustic regions, defined by frequency range and time period, present the greatest differences between the two sites. The soundscapes of the two sites differed most in autumn within the acoustic region 6, representing 05:30 – 09:00am and a range of 0.988–3.609 kHz. This acoustic region exhibited significant differences for all the 12 indices tested. Visual examination of 65 long-duration false-colour (LDFC) spectrograms resulted in the selection of 865 (from 1365) sound files with acoustic events within the range of acoustic region 6. Sonotype analysis of the 865 files showed that the soundscape outside the park is strongly influenced by human activity, with domestic animals rare in the park soundscape (1% of the sound files), but very common in the surrounding farmland environment (63% of the sound files). The main goal of monitoring programmes detecting biodiversity trends across space and time, which is here achieved via passive acoustic monitoring and acoustic indices. This confirms the utility of the techniques used here for PA monitoring, especially for detecting trends in anthropogenic disturbance, which is a common threat to natural habitats in parks and reserves in the tropics.

Electronic beehive monitoring extracts critical information on colony behavior and phenology without invasive beehive inspections and transportation costs. As an integral component of electronic beehive monitoring, audio beehive monitoring has the potential to automate the identification of various stressors for honeybee colonies from beehive audio samples. In this investigation, we designed several convolutional neural networks and compared their performance with four standard machine learning methods (logistic regression, k-nearest neighbors, support vector machines, and random forests) in classifying audio samples from microphones deployed above landing pads of Langstroth beehives. On a dataset of 10,260 audio samples where the training and testing samples were separated from the validation samples by beehive and location, a shallower raw audio convolutional neural network with a custom layer outperformed three deeper raw audio convolutional neural networks without custom layers and performed on par with the four machine learning methods trained to classify feature vectors extracted from raw audio samples. On a more challenging dataset of 12,914 audio samples where the training and testing samples were separated from the validation samples by beehive, location, time, and bee race, all raw audio convolutional neural networks performed better than the four machine learning methods and a convolutional neural network trained to classify spectrogram images of audio samples. A trained raw audio convolutional neural network was successfully tested in situ on a low voltage Raspberry Pi computer, which indicates that convolutional neural networks can be added to a repertoire of in situ audio classification algorithms for electronic beehive monitoring. The main trade-off between deep learning and standard machine learning is between feature engineering and training time: while the convolutional neural networks required no feature engineering and generalized better on the second, more challenging dataset, they took considerably more time to train than the machine learning methods. To ensure the replicability of our findings and to provide performance benchmarks for interested research and citizen science communities, we have made public our source code and our curated datasets.

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Recent advances in birdsong detection and classification have approached a limit due to the lack of fully annotated recordings. In this paper, we present NIPS4Bplus, the first richly annotated birdsong audio dataset, that is comprised of recordings containing bird vocalisations along with their active species tags plus the temporal annotations acquired for them. Statistical information about the recordings, their species specific tags and their temporal annotations are presented along with example uses. NIPS4Bplus could be used in various ecoacoustic tasks, such as training models for bird population monitoring, species classification, birdsong vocalisation detection and classification., Comment: 5 pages, 5 figures, submitted to ICASSP 2019

Ecoacoustics is a recent ecological discipline focusing on the ecological role of sounds. Sounds from the geophysical, biological, and anthropic environment represent important cues used by animals to navigate, communicate, and transform unknown environments in well-known habitats. Sounds are utilized to evaluate relevant ecological parameters adopted as proxies for biodiversity, environmental health, and human wellbeing assessment due to the availability of autonomous audio recorders and of quantitative metrics. Ecoacoustics is an important ecological tool to establish an innovative biosemiotic narrative to ensure a strategic connection between nature and humanity, to help in-situ field and remote-sensing surveys, and to develop long-term monitoring programs. Acoustic entropy, acoustic richness, acoustic dissimilarity index, acoustic complexity indices (ACItf and ACIft and their evenness), normalized difference soundscape index, ecoacoustic event detection and identification routine, and their fractal structure are some of the most popular indices successfully applied in ecoacoustics. Ecoacoustics offers great opportunities to investigate ecological complexity across a full range of operational scales (from individual species to landscapes), but requires an implementation of its foundations and of quantitative metrics to ameliorate its competency on physical, biological, and anthropic sonic contexts.

1. Many organisms depend on sound for communication, predator/prey detection and navigation. The acoustic environment can therefore play an important role in ecosystem dynamics and evolution. A growing number of studies are documenting acoustic habitats and their influences on animal development, behaviour, physiology and spatial ecology, which has led to increasing demand for passive acoustic monitoring (PAM) expertise in the life sciences. However, as yet, there has been no synthesis of data processing methods for acoustic habitat monitoring, which presents an unnecessary obstacle to would-be PAM analysts. 2. Here, we review the signal processing techniques needed to produce calibrated measurements of terrestrial and aquatic acoustic habitats. We include a supplemental tutorial and template computer codes in matlab and r, which give detailed guidance on how to produce calibrated spectrograms and statistical analyses of sound levels. Key metrics and terminology for the characterisation of biotic, abiotic and anthropogenic sound are covered, and their application to relevant monitoring scenarios is illustrated through example data sets. To inform study design and hardware selection, we also include an up-to-date overview of terrestrial and aquatic PAM instruments. 3. Monitoring of acoustic habitats at large spatiotemporal scales is becoming possible through recent advances in PAM technology. This will enhance our understanding of the role of sound in the spatial ecology of acoustically sensitive species and inform spatial planning to mitigate the rising influence of anthropogenic noise in these ecosystems. As we demonstrate in this work, progress in these areas will depend upon the application of consistent and appropriate PAM methodologies.

Citizen science projects have demonstrated the advantages of people with limited relevant prior knowledge participating in research. However, there is a difference between engaging the general public in a scientific project and entering an established expert community to conduct research. This paper describes our ongoing acoustic biodiversity monitoring collaborations with the bird watching community. We report on findings gathered over six years from participation in bird walks, observing conservation efforts, and records of personal activities of experienced birders. We offer an empirical study into extending existing protocols through in-context collaborative design involving scientists and domain experts.

The aim of this paper is to propose the use of passive acoustic monitoring (PAM) as a non-invasive method to investigate the state of communities and ecosystems. PAM operates through the study and characterization of the soundscape of an area. One of the three components of the soundscape (beside geophony and biophony) is anthrophony, which is the collection of sounds produced by human activities. This kind of sounds can have effects on natural envi-ronments and natural population. In this study, recording instruments and sampling tech-niques have been used to acquire and collect sound data for long periods (two weeks) in a nat-ural terrestrial ecosystem (Ticino Park) which is affected by road and rail traffic noise. The analysis conducted studied the trends of the eco-acoustic indices belonging to three measure-ment sites to detect the presence of characteristic trends and to evaluate the influence of the two anthropogenic noise sources at different distances.