A new tool for tracking algal toxins is under development. The tool resembles a tea bag filled with sand and, like a tea bag, is soaked in water. The grains in the sac, though, are actually tiny porous resin beads that selectively absorb domoic acid, a naturally occurring neurotoxin that causes amnesic shellfish poisoning in people and brain seizures in marine mammals.

The UC Santa Cruz scientists leading this project envision hanging the “tea bags” off piers and wharfs in California to continuously track algal toxin levels. The idea is similar to what is already being done through the state’s sentinel “mussel watch” program, except that the “tea bags” can detect lower levels of toxins and are unaffected by harmful algal blooms and pollution that can kill living organisms.

Ultimately, scientists would like to use ocean-monitoring data in conjunction with the algal tracking technology to forecast algal blooms based on observed environmental conditions.

The generalized bio-optical transition from oligotrophic blue to mesotrophic green waters has enabled remote measurement of oceanic ecosystems under conditions in which the optically relevant water mass constituents covary with the primary phytoplankton photopigment, chlorophyll a (Chla). This assumption, known as case-1, is generally incorrect within coastal and inland water bodies, where external factors, such as riverine discharge and sediment resuspension, also modify the concentrations of organic and inorganic constituents beyond the ranges anticipated for natural oceanic ecosystems. New approaches to characterize aquatic ecosystems without relying on case-1 criteria are proposed here using measurements of apparent and inherent optical properties. The methods applied in this work include bio-optical modeling and analyses of in situ, airborne, and satellite radiometric measurements of oceanic, coastal, and inland water ecosystems. Key findings are that: satellite phytoplankton datasets underestimate phytoplankton biomass in coastal ocean regions when default atmospheric correction methods are applied (Chapter 1); the expansion of spectral range for above-water radiometric measurements improves the accuracy of colored dissolved organic matter algorithms (Chapter 2); and hyperspectral beam-attenuation meters can accurately predict Chla without relying on empirical relationships between organic and inorganic particle populations (Chapter 3). The bio-optical advances presented here improve measurement capabilities for optically complex waters and are relevant to global (i.e., oceanic, coastal, and inland) water bodies. Finally, this work supports the perspective that bio-optical approaches should be consistent with electromagnetic theory or other fundamental principles - rather than requiring a partition between waters that satisfy versus fail empirical open ocean criteria - to incorporate a greater diversity of global aquatic ecosystems.

Ocean-monitoring satellite and airborne sensors are important for characterizing aquatic ecosystems spatially. These above-water sensors measure light radiating from the sea surface, from which they estimate biogeochemical properties with the help of optical algorithms. To ensure their reliability, radiometric and biogeochemical data products must be validated in-situ across the ecosystems that they characterize. This in-situ validation is typically carried out using ground truth radiometric measurements collected using in-water optical profilers. Our ability to validate above-water sensors using profilers alone, however, is limited, especially in coastal and inland ecosystems. Here we seek to improve the validation of these sensors and their data products in coastal and inland ecosystems. I demonstrate that modeling is an important tool for expanding our capability to reliably validate satellite and airborne sensors, as well as to identify for which ecosystems specific optical algorithms are likely to work. With the advent of next-generation satellites and unmanned aerial vehicles with better spatial and spectral resolution, my research contributes to an improved understanding of coastal and inland ecosystems, as well as their ever-changing dynamics.

Diarrhetic Shellfish Poisoning Toxins (DSTs) are produced by the marine dinoflagellate, Dinophysis. DSTs can bioaccumulate in shellfish and cause gastrointestinal illness when humans consume high levels of this toxin. Although not regulated in the U.S., recent studies in Washington, Texas, and New York suggest DSTs may be widespread throughout U.S. coastal waters. This study describes a four-year time series (2013-2016) of Dinophysis concentration and DST level in California mussels (Mytilus californianus) from Santa Cruz Municipal Wharf (SCMW) in Monterey Bay, California. Results show a maximum Dinophysis concentration of 9,404 cells/L during this study and suggest Dinophysis persists as a member of the background phytoplankton community throughout the year. DSTs in California mussels were found in persistent low levels throughout the course of this study, and exceeded the FDA action level of 160 ng/g 19 out of 192 weeks sampled. Dinophysis concentrations alone are a positive but weak predictor of DST level in California mussels, and basic environmental variables (temperature, salinity, and nutrients) do not sufficiently explain variation in Dinophysis concentration at SCMW. Overall, this study demonstrates that Dinophysis concentrations on the central coast of California, at SCMW, are producing DSTs that accumulate in local shellfish throughout the year, occasionally reaching levels of concern.

Microcystin toxin is a known environmental stressor with implications for ecosystem harm throughout many inland waterways in California. This purported freshwater toxin has recently emerged in the marine environment in Monterey Bay. Microcystin abundance and frequency, as well as environmental variables that drive toxin production in the Monterey Bay area were examined by deploying Solid Phase Adsorption Toxin Tracking (SPATT) samplers and evaluating water samples for 3 years. Microcystin was found in 15 of 21 monitored sites and was shown to be correlated with anthropogenic nutrient loading. Because it is relevant to identify an indicator organism to better monitor this toxin, uptake and release of microcystin toxin in California mussels (Mytilus californianus), and commercial oysters (Crassostrea sp.) were also examined. To provide environmental relevancy Mytilus sp. were also collected at 4 sites in San Francisco Bay for 6 months and analyzed for microcystin toxin. The results indicate that mussels purge microcystin toxin slowly, while oysters released toxin more quickly, however, both have the ability to retain toxin for 8 weeks post-exposure. To investigate potential effects to marine and estuarine birds at upper trophic levels the use of Whatman® FTA® blood sample collection cards were evaluated in tandem with competitive enzyme-linked immunosorbent assay (ELISA), and this method was shown to have utility for postmortem analysis and large die off events. Blood was also collected from birds admitted to rehabilitation in Monterey Bay between 2011-2015 and two groups of waterbirds tested positive for microcystin toxin. The extensive manifestation of microcystin in the Monterey Bay area exhibits the need for better monitoring and management of this toxin. Management decisions made at the terrestrial level, may now impact freshwater, estuarine, and marine ecosystems, particularly given the demonstrated capacity for bio-accumulation in shellfish. The identification of a potential bio-indicator through this study, could be used to inform the current Mussel Watch Program or could aid in establishing an analogous monitoring program specific to this toxin. Because current data on the effects of toxic algae on waterbirds is meager, this study addresses this deficiency by identifying a new technique for detecting microcystin in upper trophic levels.

Canopy forming kelp species (Order: Laminariales), the foundation ofproductive and species-rich ecosystems along rocky coastlines in temperate and Arctic regions, generate a diversity of provisioning, regulating, and supporting ecosystem services. In the northeast Pacific region, giant kelp (Macrocystis pyrifera) and bull kelp (Nereocystis luetkeana) are the dominant canopy forming kelps, which can be detected using remote sensing techniques. Historically, fixed-winged-aircraft-based aerial surveys and spaceborne satellites have been used to study canopy forming kelps via remote sensing, but increasingly unoccupied aircraft systems (UASs) are an emerging tool for kelp mapping. The following dissertation utilizes existing and emerging remote sensing techniques to advance the field of kelp remote sensing and provides insight into kelp monitoring and restoration; notably the implementation of ecosystem-based and adaptive management strategies using long-term in situ and remote sensing datasets.

Dinoflagellates employ a multitude of strategies to competitively assimilate nutrients. These include vertical migration for the assimilation of nutrients at depth and accessing dissolved organic phosphorus (DOP) even when easily accessible inorganic P is available. Identification of these strategies is helpful for characterizing phytoplankton communities and understanding the niche dinoflagellates occupy within that community. Phytoplankton maintain their P status by assimilating dissolved inorganic P (DIP), but when DIP is limiting, or as a preferential utilization, some phytoplankton are able to access dissolve organic P (DOP) by expressing alkaline phosphatase (AP), a metalloenzyme that uses zinc (Zn) as a co-factor.

The first objective of this dissertation was to identify AP activity (APA) in marine phytoplankton as a proxy for determining P-stress amongst communities in the nGoA and coastal Big Sur waters. To this end, a spectrofluorometric method was developed to identify APA in phytoplankton communities with low-cell abundance, like the samples from our study areas. P-stress was identified in dinoflagellates within the communities for both regions, resulting in subtle shifts in phytoplankton composition, even when the entire community was not exhibiting P-stress. In the coastal waters of Big Sur incubation experiments were conducted with the addition of Zn to further investigate the production of AP has on community structure. We found that the addition of Zn had no significant impact on biomass or growth, but may affect subtle changes in community phytoplankton composition. The second objective of this thesis was to investigate another competitive strategy that dinoflagellates employ: the assimilation of nitrate (N) and iron (Fe) from depth. Active vertical migration of Akashiwo sanguinea was observed in laboratory columns under N-replete and N-deplete conditions, as was the significant assimilation of stable isotopes of Fe and N from depth. These observations are the first reported Fe assimilation from depth for any phytoplankton species. Both of these competitive strategies identify tactics dinoflagellates use to access nutrients that are not accessible to other phytoplankton taxon, and the influence this could have on structured phytoplankton communities.

Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. In this study, we 1) quantify spatial variability in Suspended Particulate Matter (SPM) concentrations as a proxy for water quality at different spatial scales to contextualize this assumption and 2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2. Using our ship-based data, we tracked the location of a low-salinity, high-turbidity zone to show that remote sensing of SPM can inform on physical environmental conditions. We found that features exist that are not picked up by current point sampling, which prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23%-80% variability in SPM at the 5km scale (the scale at which point sampling occurs), demonstrating the risk in assuming a single measurement is representative of a 5km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data is collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies.

Earth's climate is intimately associated with biogeochemical processes of the sea. Biological Oceanography explores mechanisms controlling carbon uptake by phytoplankton, carbon transfer through biogeochemical processes, and energy flow through ecosystems. Satellite Oceanography affords a synoptic view of the sea surface and reveals underlying physical, chemical, and biological processes. Since the advent of ocean color satellites in 1978, ocean color algorithms evolved from quantifying phytoplankton biomass to addressing more complex bio-optical and oceanographic problems: characterizing inherent optical properties of the water column, estimating primary productivity, and detecting water masses. Locating a water mass, tracking its changes, and discriminating its constituents using bio-optical algorithms are the three objectives of this dissertation. The first objective identifies the location of the Columbia River Plume (CRP) by using light absorption by chromophoric dissolved organic matter (a _CDOM) as an optical proxy for salinity. It relates in situ measurements of (a _CDOM to salinity using linear regression analysis, then computes "synthetic" salinity using MODIS-Aqua satellite imagery. The algorithm is robust at predicting salinity of the CRP on the Oregon and Washington shelf. The second objective identifies sub-mesoscale features within the CRP and tracks their changes in space and time. It employs k-means clustering and discriminant function analysis to identify water types from bio-optical and environmental input variables using in situ and MODIS-Aqua satellite observations. The algorithm is robust at identifying features in satellite and mooring data, consistent with measured and modeled water masses in previous work. The third objective involves development of an optical model (PHYDOTax) that discriminates phytoplankton taxa contained within an algal bloom. A hyperspectral ocean color signature-library for known phytoplankton (dinoflagellates, diatoms, haptophytes, cryptophytes, chlorophytes, cyanophytes, and phycocyanin-containing eukaryotes) was developed and then PHDYOTax decomposed ocean color spectra for culture mixtures and field samples into constituent taxa. PHYDOTax is robust at discriminating phytoplankton taxa and is one of the first algorithms to distinguish dinoflagellates from diatoms in ocean color data. These algorithms are new tools for the oceanographic community to constrain the location of carbon uptake and transfer through space and time in the CRP, and to partition energy flow through different phytoplankton-taxon dominated ecosystems.