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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. 

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. 

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. 

Antarctic coastal polynyas are hotspots of biological production with intensive springtime phytoplankton blooms that strongly depend on meltwater‐induced restratification in the upper part of the water column. However, the fundamental physics that determine spatial inhomogeneity of the spring restratification remain unclear. Here, we investigate how different meltwaters affect springtime restratification and thus phytoplankton bloom in Antarctic coastal polynyas. A high‐resolution coupled ice‐shelf/sea‐ice/ocean model is used to simulate an idealized coastal polynya similar to the Terra Nova Bay Polynya, Ross Sea, Antarctica. To evaluate the contribution of various meltwater sources, we conduct sensitivity simulations altering physical factors such as alongshore winds, ice shelf basal melt, and surface freshwater runoff. Our findings indicate that sea ice meltwater from offshore is the primary buoyancy source of polynya near‐surface restratification, particularly in the outer‐polynya region where chlorophyll concentration tends to be high. Downwelling‐favorable alongshore winds can direct offshore sea ice away and prevent sea ice meltwater from entering the polynya region. Although the ice shelf basal meltwater can ascend to the polynya surface, much of it is mixed vertically over the water column and confined horizontally to a narrow coastal region, and thus does not contribute significantly to the polynya near‐surface restratification. Surface runoff from ice shelf surface melt could contribute greatly to the polynya near‐surface restratification. Nearby ice tongues and headlands strongly influence the restratification through modifying polynya circulation and meltwater transport pathways. Results of this study can help explain observed spatiotemporal variability in restratification and associated biological productivity in Antarctic coastal polynyas.

 

This study examines the process of water-column stratification breakdown in Antarctic coastal polynyas adjacent to an ice shelf with a cavity underneath. This first part of a two-part sequence seeks to quantify the influence of offshore katabatic winds, alongshore winds, air temperature, and initial ambient stratification on the time scales of polynya destratification through combining process-oriented numerical simulations and analytical scaling. In particular, the often-neglected influence of wind-driven circulation on the lateral transport of the water formed at the polynya surface—which we call Polynya Source Water (PSW)—is systematically examined here. First, an ice shelf–sea ice–ocean coupled numerical model is adapted to simulate the process of PSW formation in polynyas of various configurations. The simulations highlight that (i) before reaching the bottom, majority of the PSW is actually carried away from the polynya by katabatic wind–induced offshore outflow, diminishing water-column mixing in the polynya and intrusion of the PSW into the neighboring ice shelf cavity, and (ii) alongshore coastal easterly winds, through inducing onshore Ekman transport, reduce offshore loss of the PSW and enhance polynya mixing and PSW intrusion into the cavity. Second, an analytical scaling of the destratification time scale is derived based on fundamental physical principles to quantitatively synthesize the influence of the physical factors, which is then verified by independent numerical sensitivity simulations. This work provides insights into the mechanisms that drive temporal and cross-polynya variations in stratification and PSW formation in Antarctic coastal polynyas, and establishes a framework for studying differences among the polynyas in the ocean.

 

This is Part II of a study examining wintertime destratification in Antarctic coastal polynyas, focusing on providing a qualitative description of the influence of ice tongues and headlands, both common geometric features neighboring the polynyas. The model of a coastal polynya used in Part I is modified to include an ice tongue and a headland to investigate their impacts on the dispersal of water formed at the polynya surface, which is referred to as Polynya Source Water (PSW) here. The model configuration qualitatively represents the settings of some coastal polynyas, such as the Terra Nova Bay Polynya. The simulations highlight that an ice tongue next to a polynya tends to break the alongshore symmetry in the lateral return flows toward the polynya, creating a stagnant region in the corner between the ice tongue and polynya where outflow of the PSW in the water column is suppressed. This enhances sinking of the PSW and accelerates destratification of the polynya water column. Adding a headland to the other side of the polynya tends to restore the alongshore symmetry in the lateral return flows, which increases the offshore PSW transport and slows down destratification in the polynya. This work stresses the importance of resolving small-scale geometric features in simulating vertical mixing in the polynya. It provides a framework to explain spatial and temporal variability in rates of destratification and Dense Shelf Water formation across Antarctic coastal polynyas, and helps understand why some polynyas are sources of Antarctic Bottom Water while others are not.

 

This study examines the generation of warm spiral structures (referred to as spiral streamers here) over Gulf Stream warm-core rings. Satellite sea surface temperature imagery shows spiral streamers forming after warmer water from the Gulf Stream or newly formed warm-core rings impinges onto old warm-core rings and then intrudes into the old rings. Field measurements in April 2018 capture the vertical structure of a warm spiral streamer as a shallow lens of low-density water winding over an old ring. Observations also show subduction on both sides of the spiral streamer, which carries surface waters downward. Idealized numerical model simulations initialized with observed water-mass densities reproduce spiral streamers over warm-core rings and reveal that their formation is a nonlinear submesoscale process forced by mesoscale dynamics. The negative density anomaly of the intruding water causes a density front at the interface between the intruding water and surface ring water, which, through thermal wind balance, drives alocalanticyclonic flow. The pressure gradient and momentum advection of the local interfacial flow push the intruding water toward the ring center. The large-scale anticyclonic flow of the ring and the radial motion of the intruding water together form the spiral streamer. The observed subduction on both sides of the spiral streamer is part of the secondary cross-streamer circulation resulting from frontogenesis on the stretching streamer edges. The surface divergence of the secondary circulation pushes the side edges of the streamer away from each other, widens the warm spiral on the surface, and thus enhances its surface signal.