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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.more » « lessFree, publicly-accessible full text available April 1, 2025
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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.more » « less
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Abstract As the nutrient‐rich subsurface slope water intruding into the deep basin of the Gulf of Maine (GoM) supports the high biological productivity in the semi‐enclosed gulf, it is important to understand the process and time scale of such slope water intrusion. This study focuses on variations of the GoM deep water on seasonal to interannual time scales and the influences of open ocean processes on the temporal variation of the deep water properties. Based on long‐term monitoring data, it is found that the deep water at Jordan Basin (one of three major basins in the GoM) is persistently warmer in winter than in summer, which is distinctly different from the seasonality of surface water in the basin and the deep water on neighboring shelf seas. The unique seasonality in the deep GoM reflects a time‐lagged response to shoreward intrusion of the subsurface slope water off the GoM. Both observation‐based lag‐correlation analyses and numerical simulations confirm a timescale of approximately 3 months for the intruding subsurface slope water to flow from Northeast Channel to Jordan Basin. Properties of the intruding slope water at the Northeast Channel were significantly correlated with the Gulf Stream position and dramatically impacted by episodic warm‐core rings shed from Gulf Stream. Inside the deep GoM, the intruding slope water was also indirectly affected by the fresher water input from Nova Scotia Current. Spreading of the fresher water inside the gulf strengthens near‐surface stratification, suppresses deep convection, and preserves heat and salt in the deep GoM during the wintertime.
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Abstract Climatic changes have decreased the stability of the Gulf Stream (GS), increasing the frequency at which its meanders interact with the Mid‐Atlantic Bight (MAB) continental shelf and slope region. These intrusions are thought to suppress biological productivity by transporting low‐nutrient water to the otherwise productive shelf edge region. Here we present evidence of widespread, anomalously intense subsurface diatom hotspots in the MAB slope sea that likely resulted from a GS intrusion in July 2019. The hotspots (at ∼50 m) were associated with water mass properties characteristic of GS water (∼100 m); it is probable that the hotspots resulted from the upwelling of GS water during its transport into the slope sea, likely by a GS meander directly intruding onto the continental slope east of where the hotspots were observed. Further work is required to unravel how increasingly frequent direct GS intrusions could influence MAB marine ecosystems.