Oceanic currents drive all the world’s major climatic, biological, pollutant and sediment transport patterns. Many complex forces interact to produce the intricate movements of the ocean’s waters. Tidal rectification, a phenomenon caused by the spinning reference frame of the Earth acting together with island geometry and friction, is one such process which dictates how water is circulated around islands, seamounts, and other bathymetric shapes when tidal oscillations are present. Tidal rectification has been described mathematically and compared with physical measurements for many islands, but these islands fall into a few distinct categories. Many are either large and restricted to central latitudes, or small in diameter and found in far northern latitudes. Non-Island formations, such as guyots, and smaller bathymetric features in more central latitudes are not rigorously characterized through the lens of tidal rectification. This study expands the practical characterization of tidal rectification by comparing current speed data around a guyot near Namonuito Atoll, south of Guam, to a theoretical scaling of the potential forces acting on the guyot. I hypothesized that friction-based circulation would dominate over Coriolis-based circulation due to the guyot’s low latitude. Current velocity data was collected along a circular transect around the guyot by the R/V Thomas G. Thompson in December 2024. Preliminary findings, based on a scale analysis, suggest that these two cases are difficult to distinguish. Further research is needed to derive the nature of rectified circulation for small low-latitude islands. A rigorous practical analysis of the effects of tidally-rectified circulation is critical for a deeper understanding of biological processes, sediment transport, and pollutant concentrations around island communities.

The El Niño-Southern Oscillation (ENSO) is the most significant year-to-year climate variation, affecting weather and climate systems worldwide. However, current prediction models, both dynamic and statistical, struggle with accuracy due to the complex mechanism of ENSO. This study introduces a regional temperature and salinity prediction method using a Long Short-Term Memory (LSTM) deep learning model, which is well-suited for identifying long-term patterns in sequential data. The model is applied to three specific regions using in-situ data from Argo floats: the central-eastern Pacific, the central tropical Pacific Niño 3.4 region, and the Western Pacific Warm Pool (WPWP). These regions are chosen because they play key roles in ENSO dynamics. Results show that the LSTM model performs best in the WPWP, where the average mean squared error (MSE) is low (0.03), indicating high accuracy and stability. This is likely due to lower noise in the original data. In contrast, the model performs poorly in the central-eastern Pacific, where the average MSE is much higher (7.03), suggesting instability due to high noise in original data. These findings highlight the potential of deep learning for regional climate predictions and suggest that LSTM models could improve local weather forecasting and fisheries management.

We analyzed the effects of marine heatwaves on primary production in the Northern California Current from 1997 to 2023, a productive ecosystem that has been impacted by intense and long-lasting heatwaves, most notably the 'Blob' (2014-2016) and the 'Blob 2.0' (2019). Using Copernicus Marine Service's Global Ocean Colour and NOAA's Optimum Interpolation Sea Surface Temperature (SST) products, we analyzed chlorophyll and temperature bounded by the Columbia River and the Strait of Juan de Fuca. Heatwave metrics were compared to chlorophyll concentrations before and after events, and dynamic linear models (DLMs) were used to determine the changing regression slopes between temperature and primary production for six areas on and off the continental coast. We then used self-organizing maps (SOMs) to analyze spatiotemporal variation in phytoplankton blooms during heatwave years. Chlorophyll decreased during heatwaves for all six locations (p<0.05) and DLMs showed increasingly negative correlations between SST and chlorophyll during heatwaves for the two locations closest to the Strait of Juan de Fuca. Phenological analysis showed that the spring blooms occurred significantly earlier and with lower peaks (p<0.05) during most heatwave years. We conclude that marine heatwaves negatively affect primary production in this region, especially near the Strait of Juan de Fuca. Heatwaves also shifted the timing of spring blooms, indicating possible ecosystem impacts from mismatched phenology. Further analysis is needed to determine the mechanisms of these effects through covariates such as nutrient availability and mixed layer depth.

Eelgrass (Zostera marina) is a foundation species in the Salish Sea, providing essential habitat for several species of waterfowl, finfish and invertebrates, stabilizing sediment, cleaning water, and sequestering carbon. These ecosystem services are under threat in the San Juan Islands, as Washington State’s Submerged Vegetation Monitoring Program reports that “sites with decline outnumber sites with an increase” from 2000 to 2020. One stressor that impacts eelgrass is epiphyte load (species richness and abundance of algae on an eelgrass leaf). The presence of epiphytes can be influenced by leaf age, but associations with depth have not been reported. This case study investigates these relationships between plant depth, leaf age, and epiphyte load for one subtidal eelgrass meadow at Friday Harbor Laboratories, San Juan Island, Washington in April and May 2024. This site featured uniformly sparse eelgrass, allowing for consistent comparisons of plants across depth. I collected eelgrass leaves (n = 29) across a 50 m belt transect directed southeast of shore, including leaves at shallow (-1.1 to -1.2 m MLLW) and deep (-1.5 to -1.8 m MLLW) patches via a snorkel survey at low tide. I identified old leaves as the outermost ranking leaf, and young leaves as the second ranked inner leaf. I identified epiphyte taxa on each leaf via microscope, while visually estimating a ranked relative abundance for each species on both sides of a leaf. Epiphyte species richness and abundance were consistent across depth (p > 0.05). Young leaves exhibited lower species richness (p < 0.001) and abundance (p < 0.001) of epiphytes than old leaves, suggesting that leaves may experience asymmetrical levels of stress from epiphytes. Further developments of this study can be replicated at nearby systems to clarify these relationships between epiphyte load, plant depth, and leaf age to aid subtidal eelgrass conservation and restoration efforts.

 Marine debris, classified as solid, man-made litter and material that has been lost or discarded in the ocean, is a persistent pollution issue in coastal regions around the world, and Puget Sound is not an exception. This research investigates the distribution and abundance of marine debris across various regions of Puget Sound and how they are changing over time. Since 1987, the Washington Department of Fish and Wildlife (WDFW) has conducted annual trawls to assess bottom fish populations in Puget Sound. The contents of these trawls provide valuable representation of the soft-bottom habitat, including the organisms and debris inhabiting the seafloor. The WDFW’s extensive records of these surveys include the location, depth, type, and abundance of debris collected in each trawl. With this dataset, I explore spatial patterns in different types of debris, examine trends in abundance over the last two decades, and identify hotspots for debris accumulation in Puget Sound. The results of this study contribute to a deeper understanding of the dispersal of aluminum, plastic, glass, fishing gear, and other debris that lie at the bottom of Puget Sound. Insights on these patterns are vital to informing effective clean up and guiding prevention efforts to create cleaner and safer waters for both humans and marine life. 

The world’s oceans are witnessing a surge in plastic pollution, a consequence of human activities and the growing urbanization of coastal regions. Urban estuaries are complex habitats that are especially good at trapping sediment, carbon, and pollutants, such as plastics. However, our understanding of the extant of plastic accumulation within estuarine sediments remains limited. We determined the first quantification of the total amount of microplastics (>5 mm) in Main Basin Puget Sound, WA – a heavily urbanized estuary – and identified deposition hotspots related to current hydrodynamics. To measure plastic concentrations, we collected both shoreline and shipboard sediment samples and density extracted microplastics using an NaI solution. Extracted plastics were counted and categorized under a microscope. To complement these plastic analyses, energy of the environment was determined using both grain size analysis and extraction of current velocities from LiveOcean, a hydrodynamic model of Puget Sound. We found that plastic concentrations are the highest near land-water interfaces, which are correlated with human population. A range of 50-716 particles per kilogram of sediment was recorded in bottom samples and as much as 1180 particles/ kg were found in shoreline samples. The dominant source of microplastics came from fibers shed from clothing, giving a well-sorted particle size distribution. Furthermore, using the plastic concentration data we developed a predictive model of plastic distribution that relies on Puget Sound currents and could be adapted for other estuarine systems. Providing a comprehensive analysis of the sources and sinks of microplastics in main basin Puget Sound that can be used to inform preventative management on the negative impacts of urban waste.