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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. 

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. 

Fast-evolving artificial intelligence (AI) algorithms such as large language models have been driving the ever increasing computing demands in today’s data centers. Heterogeneous computing with domain-specific architectures (DSAs) brings many opportunities when scaling up and scaling out the computing system. In particular, heterogeneous chiplet architecture is favored to keep scaling up and scaling out the system as well as to reduce the design complexity and the cost stemming from the traditional monolithic chip design. However, how to interconnect computing resources and orchestrate heterogeneous chiplets is the key to success. In this paper, we first discuss the diversity and evolving demands of different AI workloads. We discuss how chiplet brings better cost efficiency and shorter time to market. Then we discuss the challenges in establishing chiplet interface standards, packaging, and security issues. We further discuss the software programming challenges in chiplet systems. 

The invasive European green crab (Carcinus maenas) was first detected on the US west coast around 1989 and has expanded its range northward from central California to southern Alaska. The eastern Salish Sea was initially thought to be protected from invasion by the dominant seaward surface current in the Strait of Juan de Fuca (SJdF). However, this “oceanographic barrier” has been breached as established green crab populations have been detected in the eastern Salish Sea in recent years. Here we carried out particle-tracking simulations to understand possible natural pathways of green crab larvae invading the eastern Salish Sea. Both diel vertical migration and temperature-dependent mortality were considered in these simulations. Our results suggest that green crab larvae from the outer coast (outside the Salish Sea) and Sooke Basin (in SJdF) could be carried into the eastern Salish Sea in a narrow time window during the later cold season (esp. in March) when frequent flow reversals in SJdF occur and the seasonally rising water temperature becomes relatively favorable for green crab larvae. The major pathway for larvae to reach the eastern Salish Sea is along the southern coast of SJdF. The probability of live larvae reaching the eastern Salish Sea is highly sensitive to water temperature. Sensitivity simulations indicate that a temperature increase of 0.5–1 °C would double or quadruple the probability of successful arrival in the eastern Salish Sea. This suggests that invading green crabs might have taken advantage of the mild winter conditions in recent warm years. Our results also suggest that the warming climate in the near future may facilitate green crab larval exchange across the Salish Sea. 

Coral reefs, hubs of global biodiversity, are among the world’s most imperilled habitats. Healthy coral reefs are characterized by distinctive soundscapes; these environments are rich with sounds produced by fishes and marine invertebrates. Emerging evidence suggests these sounds can be used as orientation and settlement cues for larvae of reef animals. On degraded reefs, these cues may be reduced or absent, impeding the success of larval settlement, which is an essential process for the maintenance and replenishment of reef populations. Here, in a field-based study, we evaluated the effects of enriching the soundscape of a degraded coral reef to increase coral settlement rates.Porites astreoideslarvae were exposed to reef sounds using a custom solar-powered acoustic playback system.Porites astreoidessettled at significantly higher rates at the acoustically enriched sites, averaging 1.7 times (up to maximum of seven times) more settlement compared with control reef sites without acoustic enrichment. Settlement rates decreased with distance from the speaker but remained higher than control levels at least 30 m from the sound source. These results reveal that acoustic enrichment can facilitate coral larval settlement at reasonable distances, offering a promising new method for scientists, managers and restoration practitioners to rebuild coral reefs. 

Abstract. Because of its temperate location, high dynamic range of environmental conditions, and extensive human activity, the long-term ecological research site in the coastal Northeastern US Shelf (NES) of the northwestern Atlantic Ocean offers an ideal opportunity to understand how productivity shifts in response to changes in planktonic community composition. Ocean production and trophic transfer rates, including net community production (NCP), net primary production (NPP), gross oxygen production (GOP), and microzooplankton grazing rates, are key metrics for understanding marine ecosystem dynamics and associated impacts on biogeochemical cycles. Although small phytoplankton usually dominate phytoplankton community composition and Chl a concentration in the NES waters during the summer, in August 2019, a bloom of the large diatom genus Hemiaulus, with N2-fixing symbionts, was observed in the mid-shelf region. NCP was 2.5 to 9 times higher when Hemiaulus dominated phytoplankton carbon compared to NCP throughout the same geographic area during the summers of 2020–2022. The Hemiaulus bloom in summer 2019 also coincided with higher trophic transfer efficiency from phytoplankton to microzooplankton and higher GOP and NPP than in the summers 2020–2022. This study suggests that the dominance of an atypical phytoplankton community that alters the typical size distribution of primary producers can significantly influence productivity and trophic transfer, highlighting the dynamic nature of the coastal ocean. Notably, summer 2018 NCP levels were also high, although the size distribution of Chl a was typical and an atypical phytoplankton community was not observed. A better understanding of the dynamics of the NES in terms of biological productivity is of primary importance, especially in the context of changing environmental conditions due to climate processes. 

Diatoms are a group of phytoplankton that contribute disproportionately to global primary production. Traditional paradigms that suggest diatoms are consumed primarily by larger zooplankton are challenged by sporadic parasitic “epidemics” within diatom populations. However, our understanding of diatom parasitism is limited by difficulties in quantifying these interactions. Here, we observe the dynamics of Cryothecomonas aestivalis (a protist) infection of an important diatom on the Northeast U.S. Shelf (NES), Guinardia delicatula , with a combination of automated imaging-in-flow cytometry and a convolutional neural network image classifier. Application of the classifier to >1 billion images from a nearshore time series and >20 survey cruises across the broader NES reveals the spatiotemporal gradients and temperature dependence of G. delicatula abundance and infection dynamics. Suppression of parasitoid infection at temperatures <4 °C drives annual cycles in both G. delicatula infection and abundance, with an annual maximum in infection observed in the fall-winter preceding an annual maximum in host abundance in the winter-spring. This annual cycle likely varies spatially across the NES in response to variable annual cycles in water temperature. We show that infection remains suppressed for ~2 mo following cold periods, possibly due to temperature-induced local extinctions of the C. aestivalis strain(s) that infect G. delicatula . These findings have implications for predicting impacts of a warming NES surface ocean on G. delicatula abundance and infection dynamics and demonstrate the potential of automated plankton imaging and classification to quantify phytoplankton parasitism in nature across unprecedented spatiotemporal scales.