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Amidst rapidly changing ocean soundscapes, research is still unraveling how marine animals use sound to communicate, detect predators, seek prey, and find suitable habitat. These vital behaviors may also be impacted by anthropogenic noise. Here, we describe a new tool, a Reef Acoustic Playback System, or RAPS, designed to be a cost-effective, extended-duration device that allows researchers to remotely and replay sound cues, manipulate soundscapes, and introduce “noise” into field-based experiments to address key questions regarding sound use or noise impacts within ocean ecology and conservation. The RAPS, outlined herein, has been deployed in the field for days to weeks, powered by renewable solar energy. The tool has been proven to be flexible in applications and robust to a range of ocean conditions. We outline the tool and describe several use cases, including use of the RAPS to replay healthy soundscapes to enhance the settlement of coral larvae, a fundamental ecological process sustaining coral reefs. Fundamentally, the RAPS is a new, potentially scalable means of supporting both healthy and imperiled reefs undergoing restoration, enhancing settlement of reef larvae, and broadening our ability to conduct a range of acoustic behavior studies. 

Acoustic enrichment can facilitate coral and fish larval settlement, offering a promising method to rebuild degraded reefs. Yet it is critical to understand sound propagation in complex shallow-water coral reefs to effectively apply this method over large restoration-scale areas. In this field-based study, we quantified propagation features of multiple sound types emitted through a custom playback system over varying coral reef habitat. Sound levels were computed at different distances from the source in both pressure and particle motion, the latter being detected by marine invertebrates. Detection distances were primarily determined by source levels, and depth-dependent transmission losses. Transmission losses and detection distances were similar for sound pressure and particle acceleration measurements. Importantly, broadband particle acceleration levels could be closely estimated at distances >10 m using a single hydrophone and a plane wave approximation. Using empirically determined coral larvae sound detection thresholds, we found that low frequency sounds (<1 kHz) such as fish calls from healthy coral reef soundscapes may be detectable by larvae hundreds of meters away. These results provide key data to help design standardized methods and protocols for scientists, managers and restoration practitioners aiming to rebuild coral reef ecosystems over reasonably large spatial scales using acoustic enrichment. 

Coastal currents can vary dramatically in space and time, influencing advection and residence time of larvae, nutrients and contaminants in coastal environments. However, spatial and temporal variabilities of the residence time of these materials in coastal environments, such as coastal bays, are rarely quantified in ecological applications. Here, we use a particle tracking model built on top of the high-resolution hydrodynamic model described in Part 1 to simulate the dispersal of particles released in coastal bays around a key and model island study site, St. John, USVI without considering the impact of surface waves. Motivated to provide information for future coral and fish larval dispersal and contaminant spreading studies, this first step of the study toward understanding fine-scale dispersal variability in coastal bays aimed to characterize the cross-bay variability of particle residence time in the bays. Both three-dimensionally distributed (3D) and surface-trapped (surface) particles are considered. Model simulations show pronounced influences of winds, intruding river plumes, and bay orientation on the residence time. The residence times of 3D particles in many of the bays exhibit a clear seasonality, correlating with water column stratification and patterns of the bay-shelf exchange flow. When the water column is well-mixed, the exchange flow is laterally sheared, allowing a significant portion of exported 3D particles to re-enter the bays, resulting in high residence times. During stratified seasons, due to wind forcing or intruding river plumes, the exchange flows are vertically sheared, reducing the chance of 3D particles returning to the bays and their residence time in the bays. For a westward-facing bay with the axis aligned the wind, persistent wind-driven surface flows carry surface particles out of the bays quickly, resulting in a low residence time in the bay; when the bay axis is misaligned with the wind, winds can trap surface particles on the west coast in the bay and dramatically increase their residence time. The strong temporal and inter-bay variation in the duration of particles staying in the bays, and their likely role in larval and contaminant dispersal, highlights the importance of considering fine-scale variability in the coastal circulation when studying coastal ecosystems and managing coastal resources. 

Physical conditions in coastal ecosystems can vary dramatically in space and time, influencing marine habitats and species distribution. However, such physical variability is often overlooked in ecological research, particularly in coral reef research and conservation. This study aims to quantify fine-scale variability in the physical conditions of a coastal environment to provide critical context for coastal ecosystem conservation and coral reef restoration. By developing and analyzing a 50 m-resolution hydrodynamic model, we characterize the physical oceanographic environment around the tropical island of St. John, U.S. Virgin Islands. Model simulations reveal that tides, winds, and the Amazon and Orinoco River plumes, interacting with the complex coastline and seafloor topography, create significant spatial and temporal variability in the coastal environment. Differences in tidal characteristics between the north and south shores generate strong oscillatory tidal flows in the channels surrounding St. John. The mean flow around the island is predominantly westward, driven by prevailing easterly winds. Water temperature and salinity exhibit variability over relatively smalllengthscales, with characteristic alongshore length scales of 3–10 km, depending on the season. Hydrodynamic conditions also vary across multipletimescales. Strong tidal flows interacting with headland geometry produce transient eddies with strong convergent/divergent flows and variability on the scale of hours. Synoptic-scale flow variations are driven by weather events, while seasonal variations are strongly influenced by the Amazon and Orinoco River plumes. During summer and fall, these river plumes freshen the waters on the south shore of St. John, creating significant salinity differences between the north and south shores. These fine-scale physical variabilities can exert a strong influence on the coastal ecosystem and should be considered in the management of coastal resources. By providing a detailed understanding of the physical environment, this study supports efforts to conserve and restore coastal ecosystems, particularly coral reefs, in the face of dynamic and complex oceanographic conditions. 

Large, durophagous (shell-crushing) rays are hypothesized to play a pivotal role in marine food webs, yet information on their fine-scale behavioral ecology is limited due to their elusive nature and challenges with tagging these morphologically unique animals. Here we sought to develop and apply a novel, minimally invasive tagging approach to investigate the movements, behaviors, and ecological interactions of these understudied species. Our custom-adapted multi-sensor device integrated a CATS inertial motion unit (IMU) and camera package equipped with a broadband (0-22050 Hz) hydrophone, an Innovasea V-9 coded acoustic transmitter, and a Wildlife Computers satellite transmitter (363-C). Fully assembled, the package is 24.1 x 7.6 x 5.1 cm, weighs 430 g in air, and is positively buoyant in water. The units are attached to the anterior dorsal region of a ray via two silicone suction cups, and a 24-h or 48-h galvanic timed release is strapped to plastic hooks on the cartilage of each spiracle. Through aquaria-based captive trials (N = 46), and field trials (N = 13) in Bermuda, retention times on whitespotted eagle rays (Aetobatus narinari) ranged from 0.1 to 59.2 h, (mean of 12.1 h ± 11.9 SD), with 7 out of 13 field deployments lasting >18 h, and were significantly increased by the use of the spiracle strap. Data from the Inertial Measurement Unit (IMU) suggest postural and pitching motions related to feeding, while video and audio data can capture shell fracture acoustics (i.e., predation). We expect this tool to provide insight into in situ behaviors of multiple species of benthopelagic rays, although we recommend future researchers incorporate captive testing where possible prior to field experimentation. 

The quantity of passive acoustic data collected in marine environments is rapidly expanding; however, the software developments required to meaningfully process large volumes of soundscape data have lagged behind. A significant bottleneck in the analysis of biological patterns in soundscape datasets is the human effort required to identify and annotate individual acoustic events, such as diverse and abundant fish sounds. This paper addresses this problem by training a YOLOv5 convolutional neural network (CNN) to automate the detection of tonal and pulsed fish calls in spectrogram data from five tropical coral reefs in the U.S. Virgin Islands, building from over 22 h of annotated data with 55 015 fish calls. The network identified fish calls with a mean average precision of up to 0.633, while processing data over 25× faster than it is recorded. We compare the CNN to human annotators on five datasets, including three used for training and two untrained reefs. CNN-detected call rates reflected baseline reef fish and coral cover observations; and both expected biological (e.g., crepuscular choruses) and novel call patterns were identified. Given the importance of reef-fish communities, their bioacoustic patterns, and the impending biodiversity crisis, these results provide a vital and scalable means to assess reef community health. 

Abstract Marine animals equipped with sensors provide vital information for understanding their ecophysiology and collect oceanographic data on climate change and for resource management. Existing methods for attaching sensors to marine animals mostly rely on invasive physical anchors, suction cups, and rigid glues. These methods can suffer from limitations, particularly for adhering to soft fragile marine species such as squid and jellyfish, including slow complex operations, unreliable fixation, tissue trauma, and behavior changes of the animals. However, soft fragile marine species constitute a significant portion of ocean biomass (>38.3 teragrams of carbon) and global commercial fisheries. Here we introduce a soft hydrogel-based bioadhesive interface for marine sensors that can provide rapid (time <22 s), robust (interfacial toughness >160 J m⁻²), and non-invasive adhesion on various marine animals. Reliable and rapid adhesion enables large-scale, multi-animal sensor deployments to study biomechanics, collective behaviors, interspecific interactions, and concurrent multi-species activity. These findings provide a promising method to expand a burgeoning research field of marine bio-sensing from large marine mammals and fishes to small, soft, and fragile marine animals. 

Coral reefs are biodiverse marine ecosystems that are undergoing rapid changes, making monitoring vital as we seek to manage and mitigate stressors. Healthy reef soundscapes are rich with sounds, enabling passive acoustic recording and soundscape analyses to emerge as cost-effective, long-term methods for monitoring reef communities. Yet most biological reef sounds have not been identified or described, limiting the effectiveness of acoustic monitoring for diversity assessments. Machine learning offers a solution to scale such analyses but has yet to be successfully applied to characterize the diversity of reef fish sounds. Here we sought to characterize and categorize coral reef fish sounds using unsupervised machine learning methods. Pulsed fish and invertebrate sounds from 480 min of data sampled across 10 days over a 2-month period on a US Virgin Islands reef were manually identified and extracted, then grouped into acoustically similar clusters using unsupervised clustering based on acoustic features. The defining characteristics of these clusters were described and compared to determine the extent of acoustic diversity detected on these reefs. Approximately 55 distinct calls were identified, ranging in centroid frequency from 50 Hz to 1,300 Hz. Within this range, two main sub-bands containing multiple signal types were identified from 100 Hz to 400 Hz and 300 Hz–700 Hz, with a variety of signals outside these two main bands. These methods may be used to seek out acoustic diversity across additional marine habitats. The signals described here, though taken from a limited dataset, speak to the diversity of sounds produced on coral reefs and suggest that there might be more acoustic niche differentiation within soniferous fish communities than has been previously recognized.