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Vocal territory defense can vary within a species due to many factors such as sex and breeding status, influencing territory size and thus population density across a landscape. Therefore, understanding what influences variation in territorial vocalizations can help to illuminate trade‐offs between territoriality and other life history demands, which benefits our general understanding of animal ecology as well as helps to inform emerging passive acoustic monitoring approaches. Here, we investigated how sex and breeding status affected territoriality and vocal behavior in the California spotted owl Strix occidentalis occidentalis in the Sierra Nevada, California, USA, using high‐resolution acoustic/GPS tags. We discovered that territorial vocal behavior was related to breeding status and to a lesser extent sex. Breeding owls with fledged young had a less diverse vocal repertoire, produced fewer and quieter territorial calls, and typically called only when close to their nest. Males were also more likely to engage in territorial calling than females. Breeding spotted owls also maintained significantly smaller territories – but utilized larger home ranges – than non‐breeding individuals. Our results suggest that breeding spotted owls may reduce their investment in territorial behaviors to mitigate the demands and risks associated with rearing young. Further, our results have important implications for the passive acoustic monitoring of spotted owls and, more broadly, highlight the utility of using multiple call types to detect species of interest. [ABSTRACT FROM AUTHOR]

The rise in species richness with area is one of the few ironclad ecological relationships. Yet, little is known about the spatial scaling of alternative dimensions of diversity. Here, we provide empirical evidence for a relationship between the richness of acoustic traits emanating from a landscape, or soundscape richness, and island area, which we term the SoundScape-Area Relationship (SSAR). We show a positive relationship between the gamma soundscape richness and island area. This relationship breaks down at the smallest spatial scales, indicating a small-island effect. Moreover, we demonstrate a positive spatial scaling of the plot-scale alpha soundscape richness, but not the beta soundscape turnover, suggesting a direct effect of species on acoustic trait diversity. We conclude that the general scaling of biodiversity can be extended into the realm of ecoacoustics, implying soundscape metrics are sensitive to fundamental ecological patterns and useful in disentangling their complex mechanistic drivers., (© 2024 The Author(s). Ecology Letters published by John Wiley & Sons Ltd.)

Ecosystem restoration interventions often utilize visible elements to restore an ecosystem (e.g. replanting native plant communities and reintroducing lost species). However, using acoustic stimulation to help restore ecosystems and promote plant growth has received little attention. Our study aimed to assess the effect of acoustic stimulation on the growth rate and sporulation of the plant growth-promoting fungus Trichoderma harzianum Rifai, 1969. We played a monotone acoustic stimulus (80 dB sound pressure level (SPL) at a peak frequency of 8 kHz and a bandwidth at -10 dB from the peak of 6819 Hz-parameters determined via review and pilot research) over 5 days to T. harzianum to assess whether acoustic stimulation affected the growth rate and sporulation of this fungus (control samples received only ambient sound stimulation less than 30 dB). We show that the acoustic stimulation treatments resulted in increased fungal biomass and enhanced T. harzianum conidia (spore) activity compared to controls. These results indicate that acoustic stimulation influences plant growth-promoting fungal growth and potentially facilitates their functioning (e.g. stimulating sporulation). The mechanism responsible for this phenomenon may be fungal mechanoreceptor stimulation and/or potentially a piezoelectric effect; however, further research is required to confirm this hypothesis. Our novel study highlights the potential of acoustic stimulation to alter important fungal attributes, which could, with further development, be harnessed to aid ecosystem restoration and sustainable agriculture.

Passive acoustic recorders have been used successfully as automated survey tools to detect terrestrial wildlife. However, few studies have monitored Neotropical migratory bird use of riparian forest habitat using this technology. Within dryland ecosystems, the forests along rivers support high bird diversity. Many bird species of conservation concern require these floodplain forest habitats for foraging, migration stop-overs, and breeding. Few studies have explored the use of acoustic records in riverine systems designated for conservation for their natural resource value via the Wild and Scenic Rivers Act in the USA. Using acoustic recorders, we document vocal activity of four riparian-obligate species (Bell’s Vireo, Vireo bellii; Summer Tanager, Piranga rubra; Yellow Warbler, Setophaga petechial; and Yellow-billed Cuckoo, Coccyzus americanus) to determine species occurrence along a Wild and Scenic River. We established three study reaches along the perennial Lower Verde River, in the Sonoran Desert of central Arizona, USA. Nine acoustic recorders were used over the period of 80–120 days during the summer of 2018. We measured vegetation composition and structure in 100 m2 plots paired with acoustic recorders. Visualizing vocal activity showed that three species were calling and singing at each reach; whereas, one species, the cuckoo, had fewer recordings and occurred later in the summer. We demonstrate the utility of acoustic monitoring even when applied to rare birds in complex riparian habitats. This information is important for land management and conservation efforts concerning these species of interest and identifying important habitat features in Southwestern US riparian woodlands.

Theories across sciences and humanities posit a central role for musicking in the evolution of the social, biological and technical pat- terns that underpin modern humanity. In this talk I suggest that contemporary computer musicking can play a similarly critical role in supporting us through contemporary existential, ecological, technological and social crises, by providing a space for reworking our relationships with each other and the world, including the technologies that we make. Framed by Gregory Bateson’s analysis of the fundamental epistemological error which leads to interrelated existential, social and ecological crises, I will draw upon a range of personal projects to illustrate the value of computer music practices in learning to think better: from cybernetic generative art, through ecosystemic evolutionary art and feedback musicianship to the need for interactive approaches to algorithm interpretation in ma- chine listening to biodiversity. I will illustrate how computer musicking can help in three ways: firstly by developing complexity literacy, helping us to better understand the complex systems of the anthropocene; secondly by providing a space to explore other modes of relation through learning to let others be; and thirdly to clarify the importance of aligning technologies with and not against, the biosphere. As pre-historic musicking made us human, so contemporary computer musicking can help us learn to think through the challenges we face today and be better humans tomorrow.

The ocean’s soundscape is fundamental to marine ecosystems, not only as a source of sensory information critical to many ecological processes but also as an indicator of biodiversity and habitat health. Yet, little is known about how ecoacoustic activity in marine habitats is altered by environmental changes such as temperature. The sounds produced by dense colonies of snapping shrimp dominate temperate and tropical coastal soundscapes worldwide and are a major driver broadband sound pressure level (SPL) patterns. Field recordings of soundscape patterns from the range limit of a snapping shrimp distribution showed that rates of snap production and associated SPL were closely positively correlated to water temperature. Snap rates changed by 15-60% per °C change in regional temperature, accompanied by fluctuations in SPL between 1-2 dB per °C. To test if this relationship was due to a direct effect of temperature, we measured snap rates in controlled experiments using two snapping shrimp species dominant in the Western Atlantic Ocean and Gulf of Mexico (Alpheus heterochaelis and A. angulosus). Snap rates were measured for shrimp held at different temperatures (across 10-30 °C range, with upper limit 2°C above current summer mean temperatures) and under different social groupings. Temperature had a significant effect on shrimp snap rates for all social contexts tested (individuals, pairs, and groups). For individuals and shrimp groups, snap production more than doubled between mid-range (20°C) and high (30°C) temperature treatments. Given that snapping shrimp sounds dominate the soundscapes of diverse habitats, including coral reefs, rocky bottoms, seagrass, and oyster beds, the strong influence of temperature on their activity will potentially alter soundscape patterns broadly. Increases in ambient sound levels driven by elevated water temperatures has ecological implications for signal detection, communication, and navigation in key coastal ecosystems for a wide range of organisms, including humans.

Vocal territory defense can vary within a species due to many factors such as sex and breeding status, influencing territory size and thus population density across a landscape. Therefore, understanding what influences variation in territorial vocalizations can help to illuminate trade‐offs between territoriality and other life history demands, which benefits our general understanding of animal ecology as well as helps to inform emerging passive acoustic monitoring approaches. Here, we investigated how sex and breeding status affected territoriality and vocal behavior in the California spotted owl Strix occidentalis occidentalis in the Sierra Nevada, California, USA, using high‐resolution acoustic/GPS tags. We discovered that territorial vocal behavior was related to breeding status and to a lesser extent sex. Breeding owls with fledged young had a less diverse vocal repertoire, produced fewer and quieter territorial calls, and typically called only when close to their nest. Males were also more likely to engage in territorial calling than females. Breeding spotted owls also maintained significantly smaller territories – but utilized larger home ranges – than non‐breeding individuals. Our results suggest that breeding spotted owls may reduce their investment in territorial behaviors to mitigate the demands and risks associated with rearing young. Further, our results have important implications for the passive acoustic monitoring of spotted owls and, more broadly, highlight the utility of using multiple call types to detect species of interest.

We introduce a new approach—acoustic restoration—focusing on the applied utility of soundscapes for restoration, recognising the rich ecological and social values they encapsulate. Broadcasting soundscapes in disturbed areas can accelerate recolonisation of animals and the microbes and propagules they carry; long duration recordings are also ideal sources of data for benchmarking restoration initiatives and evocative engagement tools. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring (PAM) involves recording the sounds of animals and environments for research and conservation. PAM is used in a range of contexts across terrestrial, marine and freshwater environments. However, financial constraints limit applications within aquatic environments; these costs include the high cost of submersible acoustic recorders. We quantify this financial constraint using a systematic literature review of all ecoacoustic studies published in 2020, demonstrating that commercially available autonomous underwater recording units are, on average, five times more expensive than their terrestrial equivalents. This pattern is more extreme at the low end of the price range; the cheapest available aquatic autonomous units are over 40 times more expensive than their terrestrial counterparts. Following this, we test a prototype low‐cost, low‐specification aquatic recorder called the 'HydroMoth': this device is a modified version of a widely used terrestrial recorder (AudioMoth), altered to include a waterproof case and customisable gain settings suitable for a range of aquatic applications. We test the performance of the HydroMoth in both aquaria and field conditions, recording artificial and natural sounds, and comparing outputs with identical recordings taken with commercially available hydrophones. Although the signal‐to‐noise ratio and the recording quality of HydroMoths are lower than commercially available hydrophones, the recordings with HydroMoths still allow for the identification of different fish and marine mammal species, as well as the calculation of ecoacoustic indices for ecosystem monitoring. Finally, we outline the potential applications of low‐cost, low‐specification underwater sound recorders for bioacoustic studies, discuss their likely limitations, and present important considerations of which users should be aware. Several performance limitations and a lack of professional technical support mean that low‐cost devices cannot meet the requirements of all PAM applications. Despite these limitations, however, HydroMoth facilitates underwater recording at a fraction of the price of existing hydrophones, creating exciting potential for diverse involvement in aquatic bioacoustics worldwide. [ABSTRACT FROM AUTHOR]

Timo Maran has defined "biosemiotic criticism" as the study of human culture with an emphasis on the recognition that all forms of life are organized by sign processes. That approach guides this investigation of the sonic devices and practices that have been used in encounters between birds and humans in agricultural spaces. "Bird-scaring" has been a long-standing component of the semiotic relationship between humans and birds in what I am calling the agricultural semiosphere. The struggle between humans and "pest" species over the control of agricultural resources has spurred technological development, and an examination of the sonic tools that have been involved in bird-scaring practices, from wooden rattles to digital sound recordings, intersects with scholarship on sound technology and media studies. The field of ecoacoustics provides a conceptual framework for the sonic dynamics of the interspecies communication under examination. To the extent that the essay also explores the sign relations between humans and birds it has a place in the growing corpus of biosemiotic criticism. The historical account of bird-scaring practices is presented in three sections, demarcated by changes in technology as well as shifts in the mode of semiotic reference. Across the analysis, a historical approach to bird-scaring is interwoven with a discussion of biosemiotic and ecoacoustic themes and concepts. [ABSTRACT FROM AUTHOR]

Abstract Freshwater conservation is vital to the maintenance of global biodiversity. Ponds are a critical, yet often under‐recognized, part of this, contributing to overall ecosystem functioning and diversity. They provide habitats for a range of aquatic, terrestrial, and amphibious life, often including rare and declining species. Effective, rapid, and accessible survey methods are needed to enable evidence‐based conservation action, but freshwater taxa are often viewed as “difficult”—and few specialist surveyors are available. Datasets on ponds are therefore limited in their spatiotemporal coverage. With the advent of new recording technologies, acoustic survey methods are becoming increasingly available to researchers, citizen scientists, and conservation practitioners. They can be an effective and noninvasive approach for gathering data on target species, assemblages, and environmental variables. However, freshwater applications are lagging behind those in terrestrial and marine spheres, and as an emergent method, research studies have employed a multitude of different sampling protocols. We propose the Pond Acoustic Sampling Scheme (PASS), a simple protocol to allow a standardized minimal sample to be collected rapidly from small waterbodies, alongside environmental and methodological metadata. This sampling scheme can be incorporated into a variety of survey designs and is intended to allow access to a wide range of participants, without requiring complicated or prohibitively expensive equipment. Adoption of this sampling protocol would enable consistent sound recordings to be gathered by researchers and conservation organizations, and allow the development of landscape‐scale surveys, data sharing, and collaboration within an expanding freshwater ecoacoustic community—rather than individual approaches that produce incompatible datasets. The compilation of standardized data would improve the prospects for effective research into the soundscapes of small waterbodies and aid freshwater conservation efforts.

Our planet is facing unprecedented adversity due to the global impacts of climate change and an emerging sixth mass extinction. These impacts are exacerbated by population and industrial growth, where increased resource extraction is required to meet our insatiable demands. Yet, the tangible elements of our lone inhabited planet in the solar system are not the only things disappearing or being modified. The sounds of Earth are being altered in ways that may never be recovered. Indeed, we occupy a noisier world in this age of machines that comes at a great expense in the form of sonic extinctions. It is profoundly apparent, yet not widely recognized, that conservation efforts must consider the importance of the sonic environment (i.e., sonosphere). Although sound has been integral to life for millions of years, our understanding of its ecological role has only just begun. Sounds are one of the most important extensions of the organismic inner world, becoming testimonials of environmental complexity, integration, and relationships between apparently separated parts. From a semiotic perspective, sounds are signals utilized by many organisms to save energy in patrolling, defending, exploring, and navigating their surroundings. Sounds are tools that establish dynamic biological and ecological competencies through refined partitioning in the natural selection process of evolution. Ecoacoustics is a recent scientific discipline that aims to investigate the role of sound in ecological processes. Despite its youth, Ecoacoustics has had rapid theoretical and applied growth, consolidating a diverse array of research on the ecology of sounds across many disciplines. Here, we present how Ecoacoustics plays a significant role in conservation ecology by exploring the discipline's theoretical framework, new descriptors of sonic complexity, and innovative methods for supporting conservation efforts from singular species to entire landscapes across local and global scales. The combination of automated recording units and ecoacoustic indices present a very promising approach to the study of remote areas, rare species, and data rich analyses. While Ecoacoustics scientists continue to explore this new scientific horizon, we encourage others to consider Ecoacoustics in their conservation agendas because of its application to the study and management of terrestrial, marine, and freshwater habitats. [ABSTRACT FROM AUTHOR]

Tropical ecosystems with high levels of endemism are under threat due to climate change and deforestation. The conservation actions are urgent and must rely on a clear understanding of landscape heterogeneity from transformed landscapes. Currently, passive acoustic monitoring uses the soundscape to understand the dynamics of biological communities and physical components of the sites and thus complement the information about the structures of landscape. However, the link between the analysis and quantification of ecosystem transformation based on acoustic methods and acoustic heterogeneity is just beginning to be analyzed. This document proposes a new beta Acoustic Heterogeneity Index (AHI) that quantifies the acoustic heterogeneity related to landscape transformation. AHI estimates the acoustic dissimilarity between sites modeling membership degrees of mixture models in three transformation states: high, medium, and low. We hypothesized that if acoustic recordings of different habitats are analyzed looking for particular patterns, it is possible to quantify the landscape heterogeneity between sites using sound. To calculate the AHI we propose a methodology of five steps: (1) filtering out recordings with high noise levels, (2) estimating acoustics indices, (3) including temporal patterns, (4) using GMM classification models to recognize habitat transformation levels, and (5) calculating the proposed AHI. We tested the proposal with data collected from 2015 to 2017 for 22 tropical dry forests (TDF) sites in two watersheds of Colombian Caribbean region. The sites were labeled by the level of landscape transformation using forest degradation indicators with satellite imagery. We compared these labels with the predicted transformation of our method showing an F1 score of 92% and 90% in regions of La Guajira and Bolívar respectively. To use AHI interactively, we analized the soundscapes similarities on geographic maps in the study regions. We identified that AHI allows estimating the similarity of points with similar transformations, and where the soundscape provides information about the transition states. This proposal allows complementing landscape transformation studies with information on the acoustic heterogeneity between pairs of sites.

Historically, ecological monitoring of marine habitats has primarily relied on labour-intensive, non-automated survey methods. The field of passive acoustic monitoring (PAM) has demonstrated the potential of this practice to automate surveying in marine habitats. This has primarily been through the use of ‘ecoacoustic indices’ to quantify attributes from natural soundscapes. However, investigations using individual indices have had mixed success. Using PAM recordings collected at one of the world’s largest coral reef restoration programmes, we instead apply a machine-learning approach across a suite of ecoacoustic indices to improve predictive power of ecosystem health. Healthy and degraded reef sites were identified through live coral cover surveys, with 90–95% and 0–20% cover respectively. A library of one-minute recordings were extracted from each. Twelve ecoacoustic indices were calculated for each recording, in up to three different frequency bandwidths (low: 0.05–0.8 kHz, medium: 2–7 kHz and broad: 0.05–20 kHz). Twelve of these 33 index-frequency combinations differed significantly between healthy and degraded habitats. However, the best performing single index could only correctly classify 47% of recordings, requiring extensive sampling from each site to be useful. We therefore trained a regularised discriminant analysis machine-learning algorithm to discriminate between healthy and degraded sites using an optimised combination of ecoacoustic indices. This multi-index approach discriminated between these two habitat classes with improved accuracy compared to any single index in isolation. The pooled classification rate of 1000 cross-validated iterations of the model had a 91.7% 0.8, mean SE) success rate at correctly classifying individual recordings. The model was subsequently used to classify recordings from two actively restored sites, established >24 months prior to recordings, with coral cover values of 79.1% (±3.9) and 66.5% (±3.8). Of these recordings, 37/38 and 33/39 received a classification as healthy respectively. The model was also used to classify recordings from a newly restored site established

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.

Bat communities can usually only be comprehensively monitored by combining ultrasound recording and trapping techniques. Here, we propose bat point counts, a novel, single method to sample all flying bats. We designed a sampling rig that combines a thermal scope to detect flying bats and their flight patterns, an ultrasound recorder to identify echolocating bat calls, and a near-infrared camera and LED illuminator to photograph bat morphology. We evaluated the usefulness of the flight pattern information, echolocation call recordings, and near-infrared photographs produced by our sampling rig to determine a workflow to process these heterogenous data types. We present a conservative workflow to enable taxonomic discrimination and identification of bat detections. Our sampling rig and workflow allowed us to detect both echolocating and non-echolocating bats and we could assign 84% of the detections to a guild. Subsequent identification can be carried out with established methods such as taxonomic keys and call libraries, based on the visible morphological features and echolocation calls. Currently, a higher near-infrared picture quality is required to resolve more detailed diagnostic morphology, but there is considerable potential to extract more information with higher-intensity illumination. This is the first proof-of-concept for bat point counts, a method that can passively sample all flying bats in their natural environment.

Abstract 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.

Ecoacoustics is an emerging science that seeks to understand the role of sound in ecological processes. Passive acoustic monitoring is being used to collect vast quantities of soundscape audio recordings to study variations in acoustic community and monitor biodiversity. However, extracting relevant information from soundscape recordings is non-trivial. Recent approaches to machine-learned acoustic features appear promising but are limited by at least three issues: inductive biases, lack of interpretability and crude temporal integration. In this paper we introduce a novel self-supervised representation learning algorithm for ecoacoustics - a convolutional Variational Auto-encoder (VAE) - and directly address these shortcomings. Firstly, we train the network on soundscape recordings from temperate and tropical field sites along a gradient of ecological degradation to provide a more relevant inductive bias than prior approaches. Secondly, we present a new method that allows interpretation of the latent space for the first time, giving insight into the basis of classification. Thirdly, we advance existing methods for temporal aggregation of learned embeddings by encoding latent features as a distribution over time. Under our approach to increase interpretability, we provide insight into how learned features drive habitat classification for the first time: inspection of latent space confirms that varying combinations of biophony, geophony and anthrophony are used to infer sites along a degradation gradient. Our novel temporal encoding method increases sensitivity to periodic signals and improves on previous research that uses time-averaged representations for site classification. This approach also reveals the contribution of hardware-specific frequency response that create a potential bias; we demonstrate how a simple linear transformation can be used to mitigate the effect of hardware variance on the learned representation under our approach. Our novel approach paves the way for development of a new class of deep neural networks that afford more interpretable learned ecoacoustic representations to advance both fundamental and applied science and support global conservation efforts. [Display omitted] • Ecoacoustics needs methods to interpret how soundscapes are embedded in summary descriptors to advance the science. • VAE decoder shows mixed biophony, geophony and anthrophony infer a habitat quality degradation gradient. • Learned differences in recorder hardware normalised using a linear transformation of latent encodings. • Preserving occasional or periodic acoustic signals by binning latent features over time improves site prediction accuracy. [ABSTRACT FROM AUTHOR]

Songbirds are one of the study targets for both bioacoustic and ecoacoustic research. In this paper, we discuss the applicability of robot audition techniques to understand the dynamics of forest bird vocalizations in a soundscape measured in azimuth and elevation angles with a single 16-channel microphone array, using HARK and HARKBird. First, we evaluated the accuracy in estimating the azimuth and elevation angles of bird vocalizations replayed from a loudspeaker on a tree, 6.55 m above the height of the array, from different horizontal distances in a forest. The results showed that the localization error of azimuth and elevation angle was equal to or less than 5 degrees and 15 degrees, respectively, in most of cases when the horizontal distance from the array was equal to or less than 35 m. We then conducted a field observation of vocalizations to monitor birds in a forest. The results showed that the system can successfully detect how birds use the soundscape horizontally and vertically. This can contribute to bioacoustic and ecoacoustic research, including behavioral observations and study of biodiversity.

Pantropical degradation of coral reefs is prompting considerable investment in their active restoration. However, current measures of restoration success are based largely on coral cover, which does not fully reflect ecosystem function or reef health.Soundscapes are an important aspect of reef health; loud and diverse soundscapes guide the recruitment of reef organisms, but this process is compromised when degradation denudes soundscapes. As such, acoustic recovery is a functionally important component of ecosystem recovery.Here, we use acoustic recordings taken at one of the world's largest coral reef restoration projects to test whether successful restoration of benthic and fish communities is accompanied by a restored soundscape. We analyse recordings taken simultaneously on healthy, degraded (extensive historic blast fishing) and restored reefs (restoration carried out for 1–3 years on previously degraded reefs). We compare soundscapes using manual counts of biotic sounds (phonic richness), and two commonly used computational analyses (acoustic complexity index [ACI] and sound‐pressure level [SPL]).Healthy and restored reef soundscapes exhibited a similar diversity of biotic sounds (phonic richness), which was significantly higher than degraded reef soundscapes. This pattern was replicated in some automated analyses but not others; the ACI exhibited the same qualitative result as phonic richness in a low‐frequency, but not a high‐frequency bandwidth, and there was no significant difference between SPL values in either frequency bandwidth. Furthermore, the low‐frequency ACI and phonic richness scores were only weakly correlated despite showing a qualitatively equivalent overall result, suggesting that these metrics are likely to be driven by different aspects of the reef soundscape.Synthesis and applications. These data show that coral restoration can lead to soundscape recovery, demonstrating the return of an important ecosystem function. They also suggest that passive acoustic monitoring (PAM) might provide functionally important measures of ecosystem‐level recovery—but only some PAM metrics reflect ecological status, and those that did are likely to be driven by different communities of soniferous animals. Recording soundscapes represents a potentially valuable tool for evaluating restoration success across ecosystems, but caution must be exercised when choosing metrics and interpreting results. [ABSTRACT FROM AUTHOR]

In soundscape ecology analysis, the use of acoustic features is well established and offers important baselines to ecological analyses. However, in many cases, the problem is difficult due to high-class overlap in terms of time-frequency characteristics, as well as the presence of noise. Deep neural networks have become state-of-the-art for feature learning in many multi-class applications, but they often present issues such as over-fitting or achieve unbalanced performances for different classes, which can hamper the deployment of such models in realistic scenarios. In the context of counting the number of classes in observations, the quantification task is attracting attention and was shown to be effective in other applications. This paper investigates the use of quantification combined with classification loss in order to train a convolutional neural network to classify species of birds and anurans. Results indicate quantification has advantages over both acoustic features alone and the use of regular classification networks, in particular in terms of generalization and class recall making it a suitable choice for segregation tasks related to soundscape ecology. Moreover, we show that a more compact network can outperform a deeper one for fine-grained scenarios of birds and anurans species. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Acoustic signals are one of the most important ways of communication for fauna. The study of acoustic signals constitutes a valuable tool to obtain information on ecology, behavior, taxonomic identification, and the effect of human activities in natural environments and different animal species. Furthermore, it offers the possibility of quantifying and monitoring biodiversity in different Colombian ecosystems. In this work, we present an analysis of the research on bioacoustics that have been developed in Colombia, to establish a baseline, identify gaps in knowledge, strengths, weaknesses and discuss future challenges for bioacoustics research in Colombia. We searched information on scientific publications, degree papers, and electronic database conference presentations, using different keywords. We obtained 321 results;studies using acoustic tools are much more common in birds (36.4%) and amphibians (35%) than in any other taxonomic group, and there is a bias towards studying bioacoustics in the Andean region. However, this is a field with growing interest, and, therefore, there is a need for collaborative and multidisciplinary work, a consensus on methodologies, along with the strengthening and enrichment of the country's sound collections.

We assessed the structural complexity of vegetation, birds and soundscapes in two areas of Braulio Carrillo National Park, Costa Rica, with different road exposure, as baseline information for conservation and management. We measured vegetation structure complexity, surveyed birds and recorded soundscapes in an area adjacent to the National Highway 32 (Quebrada) and another area 20 km away (Ceibo). Quebrada presented a more open forest structure and lower density of trees and shrubs; lower evenness and higher acoustic complexity, higher bioacoustic activity and sound pressure level; higher bird abundance and richness. Ceibo showed a higher density of trees and shrubs, higher complexity of vegetation structure, higher proportion of biophonies than anthrophonies, and an acoustic community with higher diversity and entropy. The study sites differed in characteristics of their bird communities in an unexpected way; these differences appear to be mostly influenced by the structure and complexity of the vegetation surrounding the road. However, the soundscapes seemed to properly reflect the habitat condition, and are promising for evaluating the ecological condition of a site.

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.

Automatically detecting the calls of species of interest in audio recordings is a common but often challenging exercise in ecoacoustics. This challenge is increasingly being tackled with deep neural networks that generally require a rich set of training data. Often, the available training data might not be from the same geographical region as the study area and so may contain important differences. This mismatch in training and deployment datasets can impact the accuracy at deployment, mainly due to confusing sounds absent from the training data generating false positives, as well as some variation in call types. We have developed a multiclass convolutional neural network classifier for seven target bird species to track presence absence of these species over time in cotton growing regions. We started with no training data from cotton regions but we did have an unbalanced library of calls from other locations. Due to the relative scarcity of calls in recordings from cotton regions, manually scanning and labeling the recordings was prohibitively time consuming. In this paper we describe our process of overcoming this data mismatch to develop a recognizer that performs well on the cotton recordings for most classes. The recognizer was trained on recordings from outside the cotton regions and then applied to unlabeled cotton recordings. Based on the resulting outputs a verification set was chosen to be manually tagged and incorporated in the training set. By iterating this process, we were gradually able to build the training set of cotton audio examples. Through this process, we were able to increase the average class F1 score (the harmonic mean of precision and recall) of the recognizer on target recordings from 0.45 in the first iteration to 0.74.

Bat communities can usually only be comprehensively monitored by combining ultrasound recording and trapping techniques. Here, we propose bat point counts, a novel, single method to sample all flying bats. We designed a sampling rig that combines a thermal scope to detect flying bats and their flight patterns, an ultrasound recorder to identify echolocating bat calls, and a near-infrared camera and LED illuminator to photograph bat morphology. We evaluated the usefulness of the flight pattern information, echolocation call recordings, and near-infrared photographs produced by our sampling rig to determine a workflow to process these heterogenous data types. We present a conservative workflow to enable taxonomic discrimination and identification of bat detections. Our sampling rig and workflow allowed us to detect both echolocating and non-echolocating bats and we could assign 84% of the detections to a guild. Subsequent identification can be carried out with established methods such as taxonomic keys and call libraries, based on the visible morphological features and echolocation calls. Currently, a higher near-infrared picture quality is required to resolve more detailed diagnostic morphology, but there is considerable potential to extract more information with higher-intensity illumination. This is the first proof-of-concept for bat point counts, a method that can passively sample all flying bats in their natural environment.

In this ecoacoustic study we used the setting of a tropical tree diversity planted forest to analyze temporal patterns in the composition of soundscapes and to test the effects of tree species richness on associated biodiversity measured as acoustic diversity. The analysis of soundscapes offers easy, rapid and sustainable methods when assessing biodiversity. During the last years the quantification of regional or global acoustic variability in sounds and the analysis of different soundscapes has been evolving into an important tool for biodiversity conservation, especially since case studies confirmed a relationship between land-use management, forest structure and acoustic diversity. Here we analyzed soundscapes from two seasons (dry and rainy season) and aurally inspected a subset of audio recordings to describe temporal patterns in soundscape composition. Several acoustic indices were calculated and we performed a correlation analysis and a non-metric multidimensional scaling analysis to identify acoustic indices that: (i) were complementary to each other and such represented different aspects of the local soundscapes and (ii) related most strongly to differences in acoustic composition among tree species richness, season and day phase. Thus, we chose “High Frequency Cover,” “Bioacoustic Index,” and “Events Per Second” to test the hypothesis that acoustic diversity increases with increasing tree species richness. Monocultures differed significantly from polycultures during night recordings, with respect to High Frequency Cover. This index covers sounds above 8 kHz and thus represents part of the orthopteran community. We conclude that increasing tree species richness in a young tropical forest plantation had positive effects on the vocalizing communities. The strongest effects were found for acoustic activity of the orthopteran community. In contrast to birds, orthopterans have smaller home ranges, and are therefore important indicator species for small scale environmental conditions.

The North American beaver Castor canadensis is an invasive species in the Tierra del Fuego Archipelago. Due to this biological invasion, Argentina and Chile signed an agreement to restore affected ecosystems by eradicating beavers. In southern Patagonia, the beavers' ecological impacts are well studied, but there is a relative lack of information on how their invasion (and potential removal) could affect bird communities.In the southern portion of Tierra del Fuego's 'big island' (Isla Grande), we conducted passive acoustic monitoring and avian point counts in intact riparian forests, beaver ponds and beaver meadows (i.e. drained ponds) to assess spatial and seasonal differences in acoustic activity and avian abundance, species diversity and functional diversity.During spring and summer, acoustic activity was significantly higher in meadows than in forests, with ponds exhibiting intermediate values.Abundance and species diversity exhibited similar patterns, driven largely by resident passerines, while functional diversity tended to be highest in ponds, largely due to ducks and raptors. Effects were weaker in fall and winter.Acoustic metrics exhibited moderate to strong correlations with all point‐count‐derived metrics.Synthesis and applications. At the patch level, the avian community was more abundant and diverse in beaver‐modified habitats than in intact riparian forests, though communities in modified patches may not differ substantially from those in analogous natural open and wetland habitats. Dam breaching and pond drainage did not yield a return to an intact forest bird community, indicating that active reforestation may be necessary to restore avian communities to pre‐beaver conditions in the short to medium term, as sought by the binational agreement. Given the immense challenges of eradication and restoration, its social‐ecological costs and benefits—including those related to avifauna—should be thoroughly considered in establishing goals or indicators of success. [ABSTRACT FROM AUTHOR]

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Abstract In recent years, passive acoustic monitoring has emerged as a reliable method for monitoring soniferous fauna, with numerous studies finding estimates of species richness and community composition are comparable with estimates derived from conventional field surveys. Most of these studies compare point counts of forest bird communities with contemporaneous short‐duration acoustic recordings, but several questions remain. How do these two methods compare in more open, arid ecosystems, how does applying methods optimally influence comparisons, and how do patterns in acoustically detectable species compare with overall patterns? Here we demonstrate techniques for improving sampling of acoustic data and conduct acoustic surveys to estimate species richness from ephemeral creek‐lines in the Australian arid zone using a long‐term passively derived acoustic dataset. We examine these results in the context of long‐term observer‐based transect surveys conducted along the same creek‐lines to define species within the avian assemblage that are acoustically detectable or acoustically undetectable/cryptic. Our data suggest that some species were consistently missed by acoustic surveys, but most belonged to groups that are typically excluded from inventories prior to analysis including rare species, raptors, waterbirds, swallows and nocturnal birds. Further, the relative diversities of sites were well estimated by acoustic surveys, with variations between sites reflecting those estimated by observer‐based field surveys. This suggests that in our study system, acoustically detectable species are reliable indicators of overall species richness. Field‐based surveys will remain an important component of sampling in arid ecosystems and we highlight the value of applying acoustic and conventional field‐based surveys in a complementary manner. This approach allows large, publishable datasets to be generated by exploiting the temporal reach of acoustic sensors, while also maximizing detections of acoustically cryptic species via field‐based surveys. We argue that acoustic monitoring has the potential to facilitate greater research effort in largely research‐deficient arid ecosystems.

Abstract 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.

Many organizations are attempting to scale ecoacoustic monitoring for conservation but are hampered at the stages of data management and analysis. We reviewed current ecoacoustic hardware, software, and standards, and conducted workshops with 23 participants across 10 organizations in Australia to learn about their current practices, and to identify key trends and challenges in their use of ecoacoustics data. We found no existing metadata schemas that contain enough ecoacoustics terms for current practice, and no standard approaches to annotation. There was a strong need for free acoustics data storage, discoverable learning resources, and interoperability with other ecological modeling tools. In parallel, there were tensions regarding intellectual property management, and siloed approaches to studying species within organizations across different regions and between organizations doing similar work. This research contributes directly to the development of an open ecoacoustics platform to enable the sharing of data, analyses, and tools for environmental conservation.

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.

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.

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.

Effective forest restoration requires tools for evaluating and comparing restoration approaches. Nevertheless, measuring restoration progress can be difficult and expensive. Passive acoustic monitoring (PAM) can be an inexpensive assessment strategy to collect large amounts of biodiversity information at scale. Nevertheless, analyzing and interpreting this information remains a difficult challenge. In this study we applied and compared three approaches to assess restoration treatments using recordings collected from PAM. We tested the hypothesis that variation in forest structure translates into differences in the species composition and acoustic signature of sites. For this purpose we used a reforestation experiment on the Osa Peninsula of Costa Rica, where we compared the mature forest to four restoration treatments. The treatments included natural regeneration and three treatments that varied the ratio of balsa, a pioneer tree species, and other native species. Our first approach consisted of visual and acoustic review of recordings to describe taxonomic groups found in each location. Our second approach consisted of measuring the acoustic energy present in the 10–30 kHz frequency band, an acoustic range primarily occupied by the mating signals of katydids and other insects, important elements of the food web and are often less mobile than birds and mammals. In our third approach we created 24-hour spectrograms that represented sites and treatments. Using the 24-hour spectrograms, we calculated a PCA and used a tSNE to evaluate the differences in acoustic signature and visualize clusters of treatments. The first approach revealed that relying on visual and acoustic review would fail to find the diel acoustic patterns that were captured in the other two approaches. The approaches varied substantially in the amount of acoustic data incorporated and the amount of human processing time. Subsampling recordings demonstrated that using only 10 sec instead of 40 sec per recording generated comparable results. The failure to differentiate among restoration treatments could reflect insensitivity in the approaches, but more likely represents the fact that the restoration plots are newly established and that substantial differentiation is more likely to arise during the time course of restoration.

African Penguins Spheniscus demersus are endangered and declining seabirds which make extensive use of vocal signals for intra‐specific vocal communication. Accordingly, passive acoustic monitoring tools could be developed as robust population monitoring methods that cause minimal disturbance to the birds. In this study, we collected soundscape recordings at the Stony Point penguin colony (Betty's Bay, South Africa) during the breeding season in 2019 to document the circadian rhythms of vocal activity of this species and to investigate whether the magnitude of variation of three different ecoacoustic indices correlates with the number of ecstatic and mutual display songs counted in recordings, which might inform on the breeding activity of the colony. Indeed, whereas ecstatic display songs are produced by males during intersexual competition and territorial defence, mutual display songs are given by parents returning to the nest after foraging trips. We found that the vast majority of the display songs (> 80%) occurred between 04:00–08:00 and 17:30–21:30 h. We also found that the Acoustic Entropy Index was a good predictor of the number of penguins' songs within a recording. Overall, our study shows that African Penguins vocalizations have the potential to assist the monitoring of this species while minimizing disturbance. [ABSTRACT FROM AUTHOR]

Passive acoustic recorders have been used successfully as automated survey tools to detect terrestrial wildlife. However, few studies have monitored Neotropical migratory bird use of riparian forest habitat using this technology. Within dryland ecosystems, the forests along rivers support high bird diversity. Many bird species of conservation concern require these floodplain forest habitats for foraging, migration stop-overs, and breeding. Few studies have explored the use of acoustic records in riverine systems designated for conservation for their natural resource value via the Wild and Scenic Rivers Act in the USA. Using acoustic recorders, we document vocal activity of four riparianobligate species (Bell's Vireo, Vireo bellii; Summer Tanager, Piranga rubra; YellowWarbler, Setophaga petechial; and Yellow-billed Cuckoo, Coccyzus americanus) to determine species occurrence along a Wild and Scenic River. We established three study reaches along the perennial Lower Verde River, in the Sonoran Desert of central Arizona, USA. Nine acoustic recorders were used over the period of 80-120 days during the summer of 2018. We measured vegetation composition and structure in 100 m² plots paired with acoustic recorders. Visualizing vocal activity showed that three species were calling and singing at each reach; whereas, one species, the cuckoo, had fewer recordings and occurred later in the summer. We demonstrate the utility of acoustic monitoring even when applied to rare birds in complex riparian habitats. This information is important for land management and conservation efforts concerning these species of interest and identifying important habitat features in Southwestern US riparian woodlands. [ABSTRACT FROM AUTHOR]

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.

Underwater passive acoustic monitoring (PAM) is of growing importance for monitoring the health of aquatic environments. Standard practices use expensive hydrophones to sample soundscapes. They must either be linked to surface recording rigs or use autonomous instrumentation which comes at a premium cost. Although citizen science projects could be of great value to PAM by increasing the number of underwater recordings collected around the world, there is a lack of available low-cost and user-friendly recording hardware. However, consumer-grade action cameras potentially offer an accessible alternative to traditional hydrophones, capable of capturing underwater acoustic recordings.We evaluated the performance of two models of GoPro underwater action cameras deployed as PAM recorders. We tested these cameras against a research-grade hydrophone in a range of shallow tropical sea environments. First, in a sandy area away from reef habitat, we took simultaneous recordings of loudspeaker playbacks of known acoustic signals using all three instruments. We then performed repeated deployments on different coral reef sites in which all three instruments were placed side-by-side to record simultaneously the same natural reef soundscapes. We calculated eight of the most commonly used ecoacoustic indices used in marine soundscape ecology, and assessed the reliability and quantitative accuracy of these compared to the hydrophone.Although not calibrated, GoPros captured recordings from which selected ecoacoustic indices could be calculated reliably, including temporal variability, the acoustic complexity index and acoustic richness. Metrics derived from GoPros can be valuably compared between recordings taken using the same model, but are not directly comparable with hydrophone-derived values. We outline the best settings for collecting soundscape data with GoPros.Underwater action cameras are used frequently by marine scientists, sports enthusiasts and tourists around the world. Their capacity to capture soundscape recordings represents a valuable approach for the global expansion of PAM through citizen science.

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.

Invasive alien species (IAS) are a threat to biodiversity and ecosystem function worldwide. Unfortunately, researchers, agencies, and other management groups face the unresolved challenge of effectively detecting and monitoring IAS at large spatial and temporal scales. To improve the detection of soniferous IAS, we introduced a pipeline for large-scale passive acoustic monitoring (PAM). Our main goal was to illustrate how PAM can be used to rapidly provide baseline information on soniferous IAS. To that aim, we collected acoustic data across Puerto Rico from March to June 2021 and used single-species occupancy models to investigate species distribution of species in the archipelago and to assess the peak of vocal activity. Overall, we detected 16 IAS (10 birds, 3 mammals, and 3 frogs) and 79 native species in an extensive data set with 1,773,287 1-min recordings. Avian activity peaked early in the morning (between 5 a.m. and 7 a.m.), while amphibians peaked between 1 a.m. and 5 a.m. Occupancy probability for IAS in Puerto Rico ranged from 0.002 to 0.67. In general, elevation and forest cover older than 54 years were negatively associated with IAS occupancy, corroborating our expectation that IAS occurrence is related to high levels of human disturbance and present higher occupancy probabilities in places characterized by more intense human activities. The work presented here demonstrates that PAM is a workable solution for monitoring vocally active IAS over a large area and provides a reproducible workflow that can be extended to allow for continued monitoring over longer timeframes.