Assessing a model of Pacific Northwest harmful algal bloom transport as a decision-support tool

In the Pacific Northwest, blooms of the diatom Pseudo-nitzschia (PN) sometimes produce domoic acid, a neurotoxin that causes amnesic shellfish poisoning, leading to a Harmful Algal Bloom (HAB) event. The Pacific Northwest (PNW) HAB Bulletin project, a partnership between academic, government, and tribal stakeholders, uses a combination of beach and offshore monitoring data and ocean forecast modeling to better understand the formation, evolution, and transport of HABs in this region. This project produces periodic Bulletins to inform local stakeholders of current and forecasted conditions. The goal of this study was to help improve how the forecast model is used in the Bulletin's preparation through a retrospective particle-tracking experiment. Using past observations of beach PN cell counts, events were identified that likely originated in the Juan de Fuca eddy, a known PN hotspot, and then particle tracks were used in the model to simulate these events. A variety of “beaching definitions” were tested, based on both water depth and distance offshore, to define when a particle in the model was close enough to the coast that it was likely to correspond to cells appearing in the intertidal zone and in shellfish diets, as well as a variety of observed PN cell thresholds to determine what cell count should be used to describe an event that would warrant further action. The skill of these criteria was assessed by determining the fraction of true positives, true negatives, false positives, and false negatives within the model in comparison with observations, as well as a variety of derived model performance metrics. This analysis suggested that for our stakeholders’ purposes, the most useful beaching definition is the 30 m isobath and the most useful PN cell threshold for coincident field-based sample PN density estimates is 10,000 PN cells/L. Lastly, the performance of a medium-resolution (1.5 km horizontal resolution) version of the model was compared with that of a high-resolution (0.5 km horizontal resolution) version, the latter currently used in forecasting for the PNW HAB Bulletin project. This analysis includes a direct comparison of the two model resolutions for one overlapping year (2017). These results suggested that a narrower, more realistic beaching definition is most useful in a high-resolution model, while a wider beaching definition is more appropriate in a lower resolution model like the medium-resolution version used in this analysis. Overall, this analysis demonstrated the importance of incorporating stakeholder needs into the statistical approach in order to generate the most effective decision-support information from oceanographic modeling

Blue carbon potential of eelgrass in the Puget Sound

Coastal ecosystems sequester and store large amounts of carbon making them important contributors to the global carbon budget. There are growing efforts to quantify this coastal marine carbon, referred to as blue carbon, in different regions of the world. Due to the diversity of species and habitats worldwide, and to high spatial variability in carbon storage capacity, local estimates yield the best measures of stored carbon. In this study we estimate the blue carbon potential of eelgrass ecosystems in the Puget Sound, WA, USA. Although direct measures of sediment carbon in seagrass beds are mostly unavailable for the Puget Sound, we used carbon storage values from Padilla Bay, the region with the largest eelgrass extent, and extrapolated carbon storage capacity of Puget Sound eelgrass beds. Our analysis suggests that eelgrass beds in Puget Sound sequester carbon at a rate of 4.2 ± 1.9 ktC yr-1 and store 1819 ± 239 ktC of carbon in the sediment. The uncertainties associated with these estimates can be reduced through location-specific studies of the effects of depth, eutrophication, and sedimentation on carbon burial and storage

Linking Chlorophyll Concentration and Wind Patterns Using Satellite Data in the Central and Northern California Current System

The California Current System (CCS) is a highly productive region because of wind-driven upwelling, which supplies nutrients to the euphotic zone. Numerous studies of the relationship between phytoplankton productivity and wind patterns suggest that an intermediate wind speed yields the most productivity on the shelf. However, few studies have considered the productivity-wind relationship across the entire CCS, including the Northern CCS (north of 42°N), an unusually productive region with highly variable upwelling- and downwelling-favorable winds. Using satellite chlorophyll concentration from GlobColour together with QuikSCAT and ASCAT winds, we examine the relationship between shelf (shallower than the 150 m isobath) chlorophyll concentration and wind patterns in the Central and Northern CCS. Results from this empirical analysis suggest that while there is a dome-shaped relationship between mean chlorophyll concentration and wind stress for the whole system, the Central CCS and Northern CCS have significantly different relationships, which is evident in the separation between their mean chlorophyll concentration-wind stress curves. The Northern CCS also supports high chlorophyll concentration during downwelling-favorable winds. To understand this difference in chlorophyll concentration-wind stress relationships, results from particle tracking experiments using a ROMS model of the Northern CCS are used to map shelf retention times with respect to wind patterns. These results suggest that on the 1°-latitude scale, the effect of wind intermittency on retention is minimal in the Northern CCS; however, this result does not disqualify the influence of more complex controls on retention like wind intermittency on smaller spatial scales. Lastly, we present a revised hypothesis to describe the relationship between chlorophyll concentration and wind stress in the CCS that includes the influence of non-upwelling-derived nutrients in the Northern CCS