Rodney A. Rountree

1. Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Motivation: Fish sounds are integral to a variety of ecological functions, including reproduction, predator–prey interactions and recruitment, with ever‐growing interest in their relationships to anthropogenic impacts and applications for passive acoustic monitoring. Until recently, however, fish sound production data were often not easily accessible, limiting research, management and public awareness. FishSounds.net launched in 2021 to compile and disseminate global fish sound production information and recordings. Here, we describe the subsequent FishSounds version releases 2.0, 2.1, 2.2, 3.0 and 3.1 (cumulatively referred to as Versions 2 and 3). We updated the core dataset to include any fish species studied for sound production up until the year 2023. We added over 1000 new fish sound recordings, collated from FishSounds contributors or Cornell University's Macaulay Library. Connections with FishBase and the World Register of Marine Species were strengthened to improve the species information provided on FishSounds and facilitate data sharing. We also created several interactive visualisation tools, including a dendrogram and map view, to allow users to explore trends in known fish sound production. These updates have made FishSounds now the largest catalogue of fish sound production knowledge, utilised by over 17,000 users annually and featuring 1252 fish species studied across 1013 references as well as 1304 recordings. Main Types of Variables Contained: Fish sound production information compiled from the scientific literature, representative fish sound recordings with associated metadata and supporting images and species data drawn from other repositories. Spatial Location and Grain: Global. Time Period and Grain: 1874–2023. Major Taxa and Level of Measurement: Fishes (Agnatha, Chondrichthyes, Sarcopterygii, Actinopterygii). All sound production information and most recordings have species‐level identification, with any others identified to the lowest possible taxonomic level. Software Format: The complete database is presented on FishSounds.net , with versioned image, audio, tabular and text files in a Borealis data repository.

Extant sirenians are the only aquatic herbivorous mammals and comprise four recognized species: the dugong, the Amazonian manatee, the West Indian manatee, and the African manatee. They inhabit coastal shallow waters in tropical and subtropical areas. All sirenian species produce sounds, many of which are audible to humans. These sounds range from tonal and narrowband to pulsed and broadband. Some of these vocalizations can be frequency-modulated and amplitude-modulated, ranging from 0.5 to at least 22 kHz in frequency and from <0.02 to ~1 s in duration. The variation in sound characteristics has enabled call type categorization into barks, chirps, clicks, quacks, squeaks, squeals, trills, whistles, etc., with gradation between classes. These calls are produced in different contexts, such as mother-calf interactions, territorial assertion, and reproductive behaviors. Sirenian vocalizations are also influenced by the surrounding environment, and their communication can be affected by human-produced noise (e.g., motorized vessels). Understanding the function of sirenian sounds in different social and ecological contexts might enhance the application of passive acoustic monitoring to the conservation and management of these endangered animals.

Aim: The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean).Location: Worldwide, 12,343 sites, all ecosystem types.Time Period: 1991 to present.Major Taxa Studied: All soniferous taxa.Methods: We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms.Results: Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm²) than aquatic sampling (0.3 and 1.8 sites/Mkm² in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds.Main Conclusions: PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.

The acoustic behavior of Amazonian aquatic fauna and the importance of its soundscape are poorly understood. Sounds produced by wild river dolphins (Amazon River dolphin, Inia geoffrensis, and tucuxi, Sotalia fluviatilis) and those of unidentified fishes were recorded from a drifting boat on six different days (8.5 h duration) in July 2012, in the Pacaya-Samiria National Reserve of Peru. Unidentified sounds of fishes were dominated by four broad types: pulsed stridulation, long stridulation, long pulse, and short pulse. Dominant sounds produced by dolphins included echolocation click trains, burst-pulses, whistles, and bubble bursts. Soniferous activity was quantified as total sound duration per 10 s of recording and compared between dolphins and fishes for each sound type and all types combined. Soniferous activity was highly variable among days, with echolocation click trains (7.7 s min-1) and pulsed stridulation (0.33 s min-1) being the dominant components. Soniferous activity of the dolphins and fishes was correlated (Spearman r = 0.49, P < 0.001). However, whether the correlation resulted from predator-prey interactions or other spatial factors could not be determined. Although preliminary in nature, this study is the first examination of the soniferous activity of both river dolphins and fishes in the Amazon and suggests passive acoustic monitoring has the potential to provide unique insight into ecological interactions in the system.