Patterns of underwater human-generated noise events and durations of noise-free intervals (NFIs) are soundscape metrics that can potentially affect animal communication and behavior. Due to the arduous task of manual analysis, these metrics have not been described in Glacier Bay National Park and Preserve (GBNP). To surmount this challenge, we created a machine-learning (ML) model trained on 18 hr of labeled audio samples from a hydrophone operating in GBNP since 2000. The validated convolutional neural net transfer-learning model (GBNP-CNN) was used to classify several categories of sound sources in nearly 9,000 hours of data from the same hydrophone, enabling our study of vessel noise between 2017 and 2020. We focused on the occurrence and duration of NFI and the hourly proportion (HP) of vessel noise. As expected, shorter NFI and higher HP were found during daytime hours. The GBNP-CNN F1 score was 75%, largely due to the model’s confusion of vessel noise with harbor seal roars. Therefore, NFI lengths should be considered minimum estimates, but the errors do not qualitatively affect diurnal or seasonal patterns. In 2018, mean daytime NFI during peak tourism months (June–August) was less than half the duration compared to May and September (1.3 min vs. 2.9 min). In 2020, when large-vessel tourism was substantially reduced but small-craft activity continued, we found that HP decreased in June–August. In conjunction with other soundscape metrics, monitoring NFI trends using ML models such as GBNP-CNN will provide crucial information for management and conservation of acoustic habitats and sensitive species in GBNP.

Cetaceans in the eastern South Atlantic Ocean are poorly studied. We present results from a 2 week ship-based survey from Cape Town to Vema Seamount (980 km to the west) during October–November 2019, including visual and towed-hydrophone observations from the vessel, and 10 days of acoustic monitoring on the seamount. Fifty-two hours of visual surveys resulted in 39 encounters of whale groups including seven of humpback, six of fin and one sei whale, as well as four unidentified baleen whales, 18 unidentified balaenopterid whales and four unidentified odontocetes. Two humpback whales at the seamount were engaged in possible feeding behaviour. A large aggregation of mostly fin whales was observed near the continental shelf edge (22 encounters over a 70 × 50 km2 area, six fin, one sei whale, 15 not confirmed to species), an historic whaling ground for both fin and sei whales. Towed-hydrophone data (78.7 h) detected five groups of sperm whales, 45 of delphinids, one beaked whale and no Kogiids. Acoustic data from the seamount detected calls from several baleen whale species including humpback whale non-song calls, Antarctic minke ‘bioduck’ calls, sei whale down-sweep calls and a likely Bryde's whale call. Two call types could not be assigned to species, including the most detected – a simple frequency-modulated call with peak power around 130 Hz. This study contributes to an improved understanding of cetacean occurrence in the eastern South Atlantic Ocean and highlights the need for more research to improve identification of cetacean vocalizations in the region.

Marine megafauna occurrence was recorded in the deep-sea region bordering the abyssal plain ~400 km north-west of Luanda, Angola. The survey took place during an Environmental Baseline Study (EBS), prior to drilling exploration activities, with the goal of characterizing the habitat and biodiversity of the region. Offshore shipboard surveys were conducted during September 2018 in water depths ranging from 2350–3850 m. We recorded daytime sightings of marine mammals and sea turtles and at night made audio recordings using passive acoustic monitoring (PAM) methods focused on capturing the sounds of vocalizing marine mammals. A variety of species were visually detected, including the humpback whale (Megaptera novaeangliae), sperm whale (Physeter macrocephalus), common dolphin (Delphinus spp.), striped dolphin (Stenella coeruleoalba), Atlantic spotted dolphin (S. frontalis), and olive ridley turtle (Lepidochelys olivacea). Acoustic click bouts similar to those made by several odontocete species, possibly including beaked whales, were recorded within the 25–48 kHz range. The humpback whale was the most frequently sighted species, accounting for 56% of mammal sightings, indicating a potential far offshore migratory habitat in this region. Most notably, right whales (probable Eubalaena australis) were visually observed. This is the first confirmed record of right whales in Angolan waters since the early 1900s. As development expands in this offshore region, these data can usefully inform future monitoring and mitigation strategies focused on minimizing impacts to wildlife.

With the advent of automated recording units, bioacoustic monitoring has become a popular tool for the collection of long-term data across extensive landscapes. Such methods involve two main components: hardware for audio data acquisition and software for analysis. In the acoustic monitoring of threatened species, a species-specific framework is often essential. Jerdon's courser Rhinoptilus bitorquatus is a Critically Endangered nocturnal bird endemic to a small region of the Eastern Ghats of India, last reported in 2008. Here we describe a reproducible and scalable acoustic detection framework for the species, comparing several commonly available hardware and detection methods and using existing software. We tested this protocol by collecting 24,349 h of data during 5 months. We analysed the data with two commercially available sound analysis programmes, following an analysis pipeline created for this species. Although we did not detect vocalizations of Jerdon's courser, this study provides a framework using a combination of hardware and software for future research that other conservation practitioners can implement. Vocal mimicry can aid or confound in detection and we highlight the potential role of mimicry in the detection of such threatened species. This species-specific acoustic detection framework can be scaled and tailored to monitor other species.

The structure of ecological communities is thought to be mainly driven by competition processes between species. One special case of resource shaping community dynamics is the acoustic space. However, the acoustic communities have been rarely described for tropical birds. Here, we aimed at estimating acoustic competition between the iconic species Pharomachrus mocinno and the other bird species occupying the same habitat. An acoustic survey was conducted in a cloud forest in Guatemala for 17 days in six simultaneous recording sites. All species occurring in the same frequency bandwidth were identified, and the acoustic overlapping between P. mocinno and these species was estimated. Eighteen species were identified as acoustic competitors. Ecological traits and phylogenetic distance were defined for all species. The rate of acoustic competition between P. mocinno and other species was related to different ecological traits and competition for resources. The acoustic overlap was high with species competing for similar food resources and phylogenetically close species and low with predator species and phylogenetically distant species. These unique observations provide new behavioural and ecological information that might be useful for the knowledge of this species and the cloud forest.

Passive acoustic monitoring is rapidly gaining recognition as a practical, affordable and robust tool for measuring gun hunting levels within protected areas, and consequently for its potential to evaluate anti-poaching patrols’ effectiveness based on outcome (i.e., change in hunting pressure) rather than effort (e.g., kilometres patrolled) or output (e.g., arrests). However, there has been no report to date of a protected area successfully using an acoustic grid to explore baseline levels of gun hunting activity, adapting its patrols in response to the evidence extracted from the acoustic data and then evaluating the effectiveness of the new patrol strategy. We report here such a case in Cameroon’s Korup National Park, where anti-poaching patrol effort was markedly increased in the 2015–2016 Christmas/New Year holiday season to curb the annual peak in gunshots recorded by a 12-sensor acoustic grid in the same period during the previous 2 years. Despite a three- to five-fold increase in patrol days, distance and area covered, the desired outcome – lower gun hunting activity – was not achieved under the new patrol scheme. The findings emphasize the need for adaptive wildlife law enforcement and how passive acoustic monitoring can help attain this goal, and they warn about the risks of using effort-based metrics of anti-poaching strategies as a surrogate for desired outcomes. We propose ways of increasing protected areas’ capacity to adopt acoustic grids as a law enforcement monitoring tool.

Between 2008 and 2010, 27 acoustic tags were applied to various age and reproductive classes of grey whales in Laguna San Ignacio, Mexico, a part of the Biosphere Reserve ‘El Vizcaino’. Besides previously described S1 and S3 calls, two additional calls were identified: the impulsive S8 call and the slightly frequency-modulated S9 call. These two additional S8 and S9 calls are by far the most common grey whale sounds detected on tags, even though contemporary bottom-mounted acoustic recordings also collected from the lagoon in 2008 yielded no S8 or S9 calls. The new S8 and old S3 calls display similar spectral maxima, even though the S3 is a frequency-modulated harmonic call and the S8 is a broadband impulsive call. This spectral analysis provides evidence that these new call types are not artefacts arising from mechanical vibration or flow noise.

Studies of the feeding behaviour of aquatic species in their natural environment are difficult, since direct observations are rarely possible. In this study, a newly developed animal-borne underwater sound recorder (AUSOMS-mini) was applied to captive Amazonian (Trichechus inunguis) and Antillean (Trichechus manatus manatus) manatees in order to directly record their feeding sounds. Different species of aquatic plants were offered to the manatees separately. Feeding sounds were automatically extracted using a custom program developed with MATLAB. Compared to ground truth data, the program correctly detected 65–79% of the feeding events, with a 7.3% or lower false alarm rate, which suggests that this methodology is a useful recorder of manatee feeding events. All manatees foraged during both the daytime and night-time. However, manatees tended to be less active and masticated slower during the night than during the day. The manatee mastication cycle duration depended on plant species and individual. This animal-borne acoustic monitoring system could greatly increase our knowledge of manatee feeding ecology by providing the exact time, duration and number of feeding events, and potentially the plant species being fed on.

The Istanbul Strait (Bosphorus) is a part of the Turkish Straits System, connecting the Aegean Sea and the Black Sea. There are three cetacean species in the Strait, namely the harbour porpoise (Phocoena phocoena), the common dolphin (Delphinus delphis), and the bottlenose dolphin (Tursiops truncatus). To monitor the presence of the cetaceans, a fixed stereo passive acoustic monitoring system (A-tag) was deployed in the middle of the Strait from July 2009 to September 2010. In total 26,814 click trains were detected. Presence, direction and inter-click intervals of phonating cetaceans were measured. Most click trains were detected during the night time. Diel presence pattern was prominent in March and April. In spring, the cetaceans were concentrated in one specific direction from the fixed monitoring system. In contrast, they were found in all directions for the rest of the year. Short range sonar (inter-click intervals (ICIs) less than 50 ms) was commonly detected in spring. During the rest of the year ICIs could reach up to 150 ms. All these findings suggest that they were feeding or socializing in spring and mostly travelling in the other seasons. It is well known that pelagic fish such as sprat and bluefish start their migration from the Aegean Sea to the Black Sea in spring. This study suggests that the cetaceans use the middle part of the Strait for feeding on the pelagic fish in spring when the fish migration has just started.

Humpback whales (Megaptera novaeangliae) are known to utilize Massachusetts Bay as a feeding ground in the spring and summer, during the annual migration of the Gulf of Maine sub-population. However, there is a limited understanding of the pattern of humpback whale occurrence in this region outside of the feeding period. Passive acoustic monitoring of Massachusetts Bay over a two-year period, revealed an extended presence of acoustically active humpback whales throughout a majority of the study period (87%; 633 days of presence out of 725 days of acoustic monitoring). Humpback whale presence oscillated between lengthy periods of consistent presence (April to December) and relatively shorter periods of variable presence (December to March). Seasonal variation in presence was evident during three distinct phases: (1) maximum-presence from spring to early winter; (2) variable-presence in early winter and early spring; and (3) minimum-presence mid-winter. The variation in seasonal presence was concurrent with coarse migratory patterns of humpback whales, and yearly variations in presence presumably reflect a shift in the influx and efflux of whales between years. The extended presence of humpbacks in this area suggests that Massachusetts Bay is an important, year-round habitat for the Gulf of Maine sub-population, and may warrant revision of management and regulatory practices to reflect this presence.

The T-POD (Timing POrpoise Detector) is a self-contained acoustic data logger used for detecting and monitoring the presence of echolocation clicks of small cetaceans. It has become a standard tool in environmental impact assessments and monitoring programmes. Yet, little is known about the variability in sensitivity and detection range of T-PODs. In this study the field performance of ten v3 T-PODs was compared to detection thresholds measured in a tank. The T-POD thresholds ranged from 123 to 132 dB re 1μPa (pp). The detection thresholds of the ten individual T-PODs were different and the differences increased over time. The more sensitive a T-POD was in the laboratory (i.e. the lower the threshold) the more clicks were recorded by it in the field. Threshold correlated differently to the five analysed T-POD parameters (encounters, encounter duration, waiting time, porpoise positive minutes, clicks per porpoise positive minute). This study demonstrates that individual threshold calibrations of T-PODs are necessary to obtain comparable results when monitoring odontocetes with this tool. Regression equations for relationships between T-POD detection thresholds and study parameters obtained during field trials may allow comparisons of T-PODs with different detection thresholds.