WHOI Theses

Thesis

Adaptive robotic search and sampling of sparse natural phenomena

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-06) Todd, Jessica Eve ; Yoerger, Dana R.

Autonomous robots are increasingly being used in the field of scientific exploration and data acquisition. Intelligent autonomous robots, capable of online adaptive planning, are seeing wide use in underwater field mapping and agricultural monitoring. The majority of these approaches produce maps of easily observable and widely dispersed phenomena such a temperature, salinity or tree coverage. However underwater and planetary science can often involve phenomena that are ‘expensive’ to observe, discrete, and sparsely distributed. For example, coral disease can only be visually detected by an underwater robot when hovering close to the reef, due to light attenuation underwater, putting the robot at risk of collision with obstacles or organisms. Similarly, subsurface water on Mars can only be detected from a landed system on the surface, due to the short range of the detectors. When the operating conditions are resource-constrained, such as a limited battery life, expensive sensing actions can consume the resource budget, limiting the range of area that can be explored. The tension between needing to act intelligently to find and measure sparse phenomena, and needing to operate within resource constraints, leads to challenges for the robot’s autonomous decision making process in choosing what to sense, where, and when. This thesis aims to address this challenge by combining semantic ‘substrates’ in the environment with hierarchical probabilistic modelling which maps substrate distributions to the underlying phenomena of interest. By using substrates that are detectable over a wide field of view, and correlated with sparser and harder to find phenomena, a robot can be guided to regions known to be associated with the phenomena of interest. This problem can be formulated as a partially-observable Markov decision process (POMDP) referred to as the Discrete Search and Sample problem. This thesis proposes two algorithmic contributions to the field of adaptive path planning to address two scenarios within this framework. In the first scenario, we assume the robot has prior knowledge about the expected density of discrete targets in the various substrates, however is operating without prior knowledge of substrate distributions. We develop a novel multi-altitude planning method, the Sparse Adaptive Search and Sample (SASS) for seeking out targets by mixing low-altitude observations of discrete targets with high-altitude observations of the surrounding substrates. By using the prior information about the distribution of targets across substrate types in combination with belief modelling over these substrates in the environment, high-altitude observations provide information that allows SASS to quickly guide the robot to areas with high target densities. In our second scenario, the a priori assumption of substrate-target correlation models is relaxed and the robot is now operating without strong prior knowledge of target density, or the relationship between target and substrate. Drawing inspiration from the Species Distribution Modelling community, an hierarchical probabilistic model is developed using the Integrated Nested Laplace Approximation framework, that enables online inference about expected target hotspots using predicted substrate distributions. Model parameters are learned online to build a prediction over the discrete targets, and the model is integrated into an anytime online planner to enable adaptive path planning. Both algorithms are extensively evaluated with both synthetic and real-world datasets. Additionally, through the course of addressing these two scenarios, two novel generative species-substrate model were developed that enable rapid simulation of synthetic worlds, with properties derived from real-world data. The development of these simulators allow the testing of path planners that aim to exploit natural correlations in spatial distributions that occur in the real world.

Thesis

Vertical distributions of megafauna on inactive vent sulfide features correspond to their feeding modes

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Meneses, Michael J. ; Mullineaux, Lauren S.

The discovery of inactive hydrothermal vent sulfide features located off the ridge axis in the 9°50'N region of the East Pacific Rise provides an opportunity to investigate knowledge gaps in the distribution and feeding ecology of communities inhabiting this type of deep-sea habitat. Previous seafloor imaging studies indicate that megafaunal taxa on inactive sulfides are not endemic to these features, but their assemblages differ from other deep-sea habitats. I investigated the influence of environmental conditions on megafaunal distributions using highresolution imagery of two inactive sulfide features, Lucky's Mound and Sentry Spire, to determine how taxonomic composition and feeding traits vary with vertical position on the features. A total of 51 morphotypes, each categorized to feeding mode, was identified from three levels of the features (spire, apron, and base) and a section of the surrounding flat oceanic rise. Quantitative image analysis showed that passive suspension feeders were more abundant on the spires of the sulfide features than the base or surrounding rise. Deposit feeders were more abundant on the base of Lucky’s mound and the oceanic rise, than on the spire or apron, but were unexpectedly abundant on the spire of Sentry Spire. These distributions correspond generally to the expected availability of suspended organic particles and detritus on the seafloor that serve, respectively, as food for these two feeding modes, and indicate a potential role for physical attributes of the sulfide feature to influence their faunal assemblages. Distinct differences in community composition between the two inactive sulfide features, however, suggest that other, feature-specific processes, perhaps including local chemoautotrophic production, may also play a role.

Thesis

Modeling sandbar effects on nearshore waves and morphological change using SWAN

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Murman, Charles E. ; Raubenheimer, Britt

Numerical model simulations (Delft3D SWAN) are used to examine the impact of small alongshore variations in the bathymetry of an outer sandbar (in about 5-m water depth) on the nearshore wave field as the shallow (< 3 m) bathymetry changes from near alongshore uniform to strongly spatially variable to understand wave driven morphologic evolution. Waves were observed at Duck, NC with an array of 14 pressure gages between 1- and 3-m water depth spread over 250 meters alongshore. Bathymetry was measured between the dune toe and about 8-m water depth on September 26 and October 2, 2013. The bathymetry evolved from roughly alongshore uniform on September 26 to strongly alongshore variable on October 2. Between these dates incident significant wave heights ranged from 0.5 meters to 2.3 meters, with incident angles from 20 degrees north to 5 degrees south of shore normal. Simulations were run with observed bathymetry for both the outer bar and inner shallow bathymetry, with smoothed outer bar and observed shallow bathymetry, and with digital elevation model bathymetry to determine the effects of outer bar and shallow bathymetry on wave evolution.

Thesis

Movement and energetics of swimming marine mollusks

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Cones, Seth F. ; Mooney, T. Aran

Mollusks constitute a significant proportion of marine animal biomass and fulfill essential ecosystem functions. Yet, our knowledge of their behavior and energy output in natural environments remains elusive. This key knowledge gap stems from our inability to quantify their positions and movements for appreciable time-scales, and thus we know extremely little about how abundant mollusks that are pervasive in all ocean biomes respond to naturally varying and anthropogenically-induced changes. In this thesis, I adapted emerging biologging sensor technology, traditionally designed for large robust vertebrates, for two key mollusk taxonomic groups (squid and scallops) to quantify and characterize movements at fine-temporal scales. In Chapter 2, I collected the first high-resolution (> 1 Hz) in situ movement data for any squid species. These novel data elucidated fundamental swimming behaviors such as swim direction, postures, and environmental extents of ecologically-vital diel vertical migration. In Chapter 3, I linked lab-calibrated bioenergetic models and field observations to map energy output and necessary caloric intake of natural behaviors in the wild. These data revealed dynamic gait use on seconds time scales. Next, in Chapters 4 and 5, I quantified the behavioral disruption and the metabolic cost of a prominent anthropogenic stressor, sound pollution. Squid and scallops elicited drastically different ecophysiological responses to field-simulated offshore windfarm construction. Squid elicited dramatic behavioral responses coinciding with the onset of construction, although animals habituated rapidly. Contrarily, scallops’ behavioral responses were moderate but consistent, and surprisingly there was no evidence of habituation across second, minutes, and daily time scales. Extended behavioral changes manifested as heightened metabolic rates and weakened antipredator responses, suggesting prolonged and potential population-level impacts on a key fishery. This thesis provides new insight in marine invertebrate movement ecology and eco-physiology, demonstrating the utility of coupling biologging and physiological experiments to reveal how key ocean animals behave and expend energy.

Thesis

The origins of the East Greenland Coastal Current on the Northeast Greenland Shelf: a comparison of two reanalysis products

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Vianco, Sara L. ; Foukal, Nicholas P. ; Mahadevan, Amala

The East Greenland Coastal Current (EGCC) carries some of the freshest outflow from the Arctic southward along the East Greenland Shelf and into the Nordic Seas and subpolar North Atlantic. How this fresh water initially flows onto the Northeast Greenland Shelf (NEGS) and feeds the EGCC is not well known due in part to the lack of observations in the region. In this thesis, I use two ocean reanalyses, the Regional Arctic Ocean/sea-ice Reanalysis (RARE) and Global Ocean Physics Reanalysis (GLORYS) to explore the structure and dynamics of the ocean circulation on the NEGS. To validate the use of these products in the region, I compare the reanalysis products to the Fram Strait Arctic Outflow Observatory for the period of 2003-2019. In the mean, RARE is too warm and salty compared to the moorings, while the properties in GLORYS track more closely to the observations. However, the observed velocity field is better represented in RARE than GLORYS. From there, I analyze the cross-shelfbreak flow from 74°N to 81.5°N in the two reanalysis products, and conclude that transport onto the NEGS of waters fresher than 34 salinity is driven by an Ekman circulation that arises from along-shelfbreak winds and a widening shelf south of 81.5°N. The enhanced transport of fresh water also shifts the isohalines across the shelfbreak, directing a geostrophic flow onshelf between 81°N and 79°N. The convergence of fresh water on the NEGS initiates the EGCC as an identifiable and distinct feature around 80°N in RARE, uniting the EGCC along the southwest coast of Greenland and its northern counterpart, the Polar Surface Water (PSW) Jet. In GLORYS, the EGCC is not present throughout the domain, though there is a weak net southward flow on the NEGS. The EGCC in RARE is primarily buoyancy-driven, though the along-coast winds likely play a major role in maintaining the density front that supports the EGCC. Results from this thesis have implications for the transport and fate of Arctic and Greenland-sourced fresh water, and stratification in the high latitude North Atlantic and Nordic Seas.

Thesis

Cross-shelf exchange driven by dense flow down a canyon

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Mier, Christian M. ; Cenedese, Claudia

Laboratory experiments investigated the dynamics controlling the cross-shelf exchange in a prograde sloping canyon induced by dense shelf water descending into the canyon. This thesis is motivated by the dispersal of dense water generated by polynyas on the Arctic and Antarctic continental shelves. Laboratory results corroborate prior numerical results suggesting that canyons are hotspots of cross-shelf exchange. When the dense water descends a canyon, it induces an onshore return flow of offshore water into the canyon. This return flow is initially driven by the dense water eddies descending the canyon and acting like a bucket brigade. At later times, another mechanism may also be at play where large dense cyclonic (anticlockwise) eddies on the northern continental shelf may pull more dense water out of the canyon producing a region of low pressure, near the canyon head, which induces an increase in ambient flow into the canyon. The Burger number (Rossby radius of deformation/canyon width) and the dense water source location with respect to the canyon head affect the offshore ambient water velocity up the canyon. Additionally, as the offshore water reaches the canyon head, the offshore water volume flux becomes larger than the dense water volume flux, possibly due to the low pressure region described above. Understanding these dynamics in the Antarctica region is of global significance for two main reasons: 1. The offshore flowing dense water forms Antarctic Bottom Water and thus affects the global meridional circulation; 2. The onshore heat transport induced by the return flow drives glacial ice melt and therefore contributes to sea level rise.

Thesis

Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Garber, Samantha C. ; Nepf, Heidi M.

Coastal vegetation can provide protection to the coastline through its root structures, which reduce soil erosion, and its stem structures, which dissipate wave energy. The drag a plant induces could be used to quantify the amount of coastal protection that is provided. This study combined field measurements and drone surveys to develop methods for quantifying vegetation drag, focusing on Spartina alterniflora (S. alterniflora), a smooth cordgrass native to the study site: Waquoit Bay National Estuarine Research Reserve. The drag of a single plant is proportional to frontal area. The drag per bed area is proportional to the drag of a single plant and the number of stems per bed area. This study collected plant samples over the growing season to generate allometric relationships between tiller height and individual plant biomass and frontal area, which provides a way to translate remotely-sensed measures of biomass into stem count and frontal area per bed area. The frontal area was measured through digital imaging of individual plants. The elastic modulus of the stem was also measured using an Instron testing machine. For sixteen 1m x 1m test plots, Normalized Difference Vegetation Index (NDVI) extracted from drone multispectral imagery was compared to measured stem count and estimated biomass. The study compared two different years and three time points within a growing season [August 2022; June, August, October 2023). In addition, at three plots the stem count was manually altered by cutting out 50% and 100% of the plants. This study found that while NDVI can be used to determine the abundance of S. alterniflora, there are several limitations that cause the correlations to be case-specific. Limitations to NDVI-S. alterniflora correlations included: (1) saturation, (2) species in-homogeneity of the area tested, (3) shoot density inhomogeneity of the area tested, and (4) environmental conditions.

Thesis

Characterization of microbial primary and secondary metabolism in the marine realm

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Geller-McGrath, David ; Edgcomb, Virginia P.

This thesis applies meta-omics data analysis to elucidate the ecological roles of marine microorganisms in diverse habitats and includes the development of new bioinformatics tools to enhance these analyses. In my second chapter, I applied genome mining tools to analyze the gene content and expression of biosynthetic gene clusters (BGCs). The analysis of BGCs through largescale genome mining efforts has identified diverse natural products with potential applications in medicine and biotechnology. Many marine environments, particularly oxygen-depleted water columns and sediments, however, remain under-represented in these studies. Analysis of BGCs in free-living and particle-associated microbial communities along the oxycline water column of the Cariaco Basin, Venezuela, revealed that differences in water column redox potential were associated with microbial lifestyle and the predicted composition and production of secondary metabolites. This experience set the stage for my third chapter, in which I developed MetaPathPredict, a machine learning-based tool for predicting the metabolic potential of bacterial genomes. This tool addresses the lack of computational pipelines for pathway reconstruction that predict the presence of KEGG modules in highly incomplete prokaryotic genomes. MetaPathPredict made robust predictions in highly incomplete bacterial genomes, enabling more accurate reconstruction of their metabolic potential. In my fourth chapter, I performed metagenomic analysis of microbial communities in the hydrothermally-influenced sediments of Guaymas Basin (Gulf of California, Mexico). Previous studies indicated a decline in microbial abundance and diversity with increasing sediment depth. Analysis revealed a distribution of MAGs dominated by Chloroflexota and Thermoproteota, with diversity decreasing as temperature increased, consistent with a downcore reduction in subsurface biosphere diversity. Specific archaeal MAGs within the Thermoproteota and Hadarchaeota increased in abundance and recruitment of metatranscriptome reads towards deeper, hotter sediments, marking a transition to a specialized deep biosphere. In my fifth chapter, I developed MetaPathPredict-E, a deep learningpowered extension of MetaPathPredict for eukaryotic metabolism predictions. Eukaryotic metabolism is diverse, reflecting varied lifestyles across eukaryotic kingdoms, but the complexity of eukaryotic genomes presents challenges for assembly and annotation. MetaPathPredict-E was trained on diverse eukaryotic genomes and transcriptomes, demonstrating a robust performance on test datasets, thus advancing the study of eukaryotic metabolic potential from environmental samples.

Thesis

Decoding divergence in marine protistan communities: from strain diversity to basin biogeography

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Krinos Quinn, Arianna I. ; Follows, Michael J. ; Alexander, Harriet

Protists (microbial eukaryotes) in the global ocean are critical components of primary productivity and nutrient recycling. Protists are genetically diverse and have distinctive ecological niches based on genetically-driven differences in physiological fitness. A deeper understanding of which dimensions of protistan genetic diversity translate to measurable phenotypic variation is needed to predict the impact of protists on marine biogeochemistry and protists’ environmental change sensitivity. I cultured twelve strains of the coccolithophore Gephyrocapsa huxleyi across temperatures, which revealed strain-specific differences in thermal optima and niche widths. I used traits measured during the experiments to design a Darwin ecosystem model simulation, which demonstrated basin-specific biogeography of thermal optima and niche widths (Chapter 2). For seven of the twelve strains, I sequenced transcriptomes at 3-5 temperatures to assess gene expression variation. Using the RNAseq data, I developed a regression modeling approach to identify proteome allocation model parameters. Combining differential expression analysis, gene abundance normalization, and the regression model to explore the proteome allocation model parameter space, I probed differences in modeled strategies of G. huxleyi strains in response to temperature (Chapter 3). Scalable workflows highlight the challenge and promise of meta-omic data to link community structure to physiology. I developed a pipeline for metatranscriptome analysis and taxonomic annotation to address the lack of tools built specifically for microbial eukaryotes, and created mock communities to assess recovery success in protistan metatranscriptome analysis workflows (Chapters 4 and 5). I applied these tools to a three-year metatranscriptomic dataset from Cape Cod Bay to investigate a recent emergence of a summer occolithophore population in the 20-year time series, tracking shifts in nutrient physiology to identify potential bottom-up controls (Chapter 6). This dissertation advances approaches to constrain the protistan taxonomic diversity that underlies shifts in global primary productivity and nutrient turnover. Specifically, strains of a single phytoplankton species revealed diversity relevant to a global ecosystem model. Future work will clarify variability in protistan gene content and expression that may underpin both protists’ present ecological niches and their future climate change response.

Thesis

Dynamics and implications of ROS in marine systems

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Taenzer, Lina ; Hansel, Colleen M. ; Wankel, Scott

The reactive oxygen species (ROS), superoxide and hydrogen peroxide, play critical roles across diverse marine ecosystems, influencing redox chemistry and organismal health. The distribution and concentration of these compounds in the oceans may serve as important controls for various biogeochemical cycles. The contrasting physiological nature of ROS, serving as both integral compounds for cellular processes such as signaling and growth while inducing oxidative cell damage at elevated concentrations, has made interpretation of their roles in organismal and ecosystem health challenging. Despite the potential for these ROS to provide unique insights into the intricate interactions occurring at the interface between life and its surrounding environment, critical gaps in our understanding of these compounds in marine systems exist. In this thesis I explored two aspects of marine ROS. The first part is focused on advancing our understanding of the distribution of superoxide in the sea. As part of a multidisciplinary team, I developed a submersible chemiluminescent sensor (SOLARIS) capable of measuring ROS in situ to ocean depths greater than 4,000 meters. With the use of SOLARIS, I discovered that a broad diversity of sponges and corals are local hotspots of superoxide at depth. Then, I studied the distribution of superoxide in the stratified water column of the Baltic Sea and found large subsurface maxima in the aphotic zone. In the second part of this thesis, I probed the use of hydrogen peroxide as a monitoring agent of organismal health. I measured hydrogen peroxide and bromoform production by two seaweed species exposed to different stressors. An analysis of these signals suggests that hydrogen peroxide could serve as a non-invasive chemical signature for stress in seaweed meadows and farms. Lastly, I characterized hydrogen peroxide associated with different coral species during a Stony Coral Tissue Loss Disease transmission experiment. I determined that hydrogen peroxide does not predict infection before lesions are visible, thus hindering its utility as an early-stage signature of disease within corals. Altogether, this thesis extends our perspective on the distribution and controls on ROS in various marine systems and provides a baseline for using ROS dynamics to monitor organismal health.

Thesis

Quantifying the effects of sunlight on the fate of oil spilled at sea

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Freeman, Danielle Haas ; Ward, Collin P.

Oil spilled at sea is transformed by sunlight-driven photochemical reactions. The transformed oil has different properties and behavior in the environment compared to the fresh oil, resulting in different fates and effects. My work in this thesis was to put numbers on these changes, with the goal of better predicting where oil goes and how it behaves in diverse spill scenarios. First, I focused on how sunlight generates water-soluble compounds from oil, which can lead to the dissolution of oil-derived compounds in seawater (photo-dissolution; Chapter 2). To find out whether photo-dissolution could be an important fate process during an oil spill, I used a combination of experiments and photochemical rate modeling to calculate photo-dissolution rates for the 2010 Deepwater Horizon spill (DwH) in the Gulf of Mexico (GoM). I found that photodissolution likely converted ~8% of the floating surface oil to dissolved organic carbon during DwH, a fraction similar in magnitude to other well-recognized fate processes. Moving beyond DwH, I evaluated the sensitivity of oil photo-dissolution and photochemically-altered oil physical properties to temperature. I found that if a spill like DwH had occurred in 5°C water rather than the exceptionally warm 30°C water of the GoM, 7x less oil could have dissolved via photodissolution and the viscosity of the remaining insoluble oil could have been 16x higher, resulting in lower entrainment of oil into the water column as small droplets (Chapter 3). The net result is that more oil would stay at the sea surface in a cold-water spill. Finally, I determined photodissolution rates for diverse oil products beyond the light crude that spilled during DwH (Chapter 4). I found that oil photo-reactivity could be predicted from oil chemical composition. I also found that photo-dissolution likely affects oil mass balance in spills of light oils forming thin slicks but not in spills of light or heavy oils forming thick slicks. Overall, this work advances our understanding of how oil changes in the environment upon sunlight exposure. This information can be applied to better predict, evaluate, and mitigate the effects of oil spilled at sea on marine ecosystems, including humans.

Thesis

On the non-microbial sources and sinks of dissolved metabolites in seawater

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Germolus, Noah P. ; Kujawinski, Elizabeth

Dissolved marine metabolites are small (<1000 Da) organic chemicals that remain in seawater when passed through a filter (typically <0.2 μm pore size). Their name implies their biological function: to be produced and consumed by cellular metabolism. These chemicals are the flows of the “microbial loop”—the principle that most of the photosynthesized matter in the ocean is exchanged, respired, and restructured by single-celled organisms. Metabolites have critical biological utility, so they are considered extremely labile; estimates of the time each spends outside cells range from hours to days. Their concentrations are drawn down by their consumers to nanomolar and picomolar levels, making measurement difficult. However, improved techniques to measure metabolites simultaneously and at extremely low concentrations avail the question of what happens to metabolites outside the cell membrane. Conventionally, representations of labile DOM exchange networks avoid that question—metabolites’ short lifetimes imply their flows lead from one organism to the next. This thesis begins to interrogate that assumption, asking if there are other processes that could change the seawater exometabolome on time scales that are relevant to microbial life. In Chapter 1 I discuss the ways ambient metabolite pools could be affected by animals, chemistry, and physics. In Chapter 2 I investigate the photolysis of metabolites and examine metabolomic techniques’ suitability for such experiments. In simulated sunlight, 11 of 57 metabolites decayed to some extent in artificial or natural seawater, and tryptophan and kynurenine may decay rapidly in the mixed layer of an oligotrophic ocean. For Chapter 3, I captured five species of migratory zooplankton and measured metabolites in their dissolved excreta. Four species survived the experiment and produced 43 metabolites, many at a rate that should be measurable in field samples. Chapter 4 harnesses the previous two chapters, plus a model for physical mixing, to probe a field dataset comprising 60 metabolites from Hydrostation S (south of Bermuda). Based on eight profiles over the course of two days, I posit: (1) copepods alone can supply the entire demand of >20 compounds to the mixed layer; (2) mixing is rapid enough to erase input signatures in the mixed layer; and (3) photochemistry is a slow leak of metabolites to forms whose lability is yet unknown. Chapter 5 reflects on how metabolites break the microbial loop—and suture it together with more ecological richness than with elemental fluxes alone.

Thesis

Molecular characterization of microbial interactions with labile dissolved organic matter

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-09) Halloran, Kathryn H. ; Kujawinski, Elizabeth

Marine microbes produce and consume labile dissolved organic matter (DOM), generating a carbon flux with significant implications for global carbon cycling and microbial ecosystems. Intracellular measurements of biological activity cannot fully capture microbial interactions with dissolved carbon. Better understanding this carbon flux thus requires direct and compound-specific characterization of metabolites, the small organic biomolecules that make up labile DOM. However, these measurements are challenging due to low metabolite concentrations, high ambient salt concentrations, and the complexity of labile DOM. More complete characterization of dissolved metabolites is therefore a standing challenge in the field. This in turn leaves many open questions with respect to the specificity of microbe-DOM interactions and the biotic and abiotic drivers of those interactions. This thesis addresses those challenges and questions. In Chapter 2, I explore the compound-specific uptake of metabolites by the copiotrophic gamma-proteobacterium Alteromonas macleodii, with a focus on metabolites derived from the cyanobacteria Prochlorococcus. I find that Alteromonas grows on 3-methyl-2-oxobutanoic acid, a valine intermediate, but not on the other cognate branched chain amino acid intermediates. This substrate selectivity is likely driven by transporter specificity. The distinct fate of these structurally similar molecules emphasizes the importance of compound-specific characterization of labile DOM. To expand our ability to make these compound-specific measurements, in Chapter 3 I develop a method for derivatizing carboxylate-, carbonyl-, and phosphate-containing molecules via aniline derivatization, solid phase extraction, and liquid chromatography-tandem mass spectrometry (LC-MS/MS). This method is able to quantify 51 different metabolites dissolved in seawater, 25 of which could not be detected previously, with pM to nM detection limits. I verify the utility of this method by applying aniline derivatization to phytoplankton culture filtrates and field samples. Additionally, I show that where dissolved metabolites can be quantified by multiple methods, the measurements obtained by aniline derivatization are in good agreement with measurements yielded by other methods. Finally, in Chapter 4 I use aniline derivatization to characterize the diel variability of labile DOM produced by phototrophic microbes. Here, I apply aniline derivatization to filtrate from cultures of Prochlorococcus grown under 24-hour diel light/dark conditions and sampled every two hours. I find that Prochlorococcus cells not only release metabolites into solution, but also take those metabolites up again, with diel rhythmicity. Together, this thesis shows that microbe-DOM interactions can be remarkably subtle and complex; expands our ability to quantify the metabolites that make up labile DOM; and demonstrates the importance of directly quantifying these dissolved metabolites to fully characterize microbial ecology and carbon cycling in the ocean.

Thesis

Assessing the impact of domoic acid exposure on the zebrafish (Danio rerio) brain across life stages

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-06) Hidayat, Alia S. ; Aluru, Neelakanteswar

Domoic acid (DA) is a neurotoxin produced by diatoms in genus Pseudo-nitzschia. DA accumulates in seafood and can affect the health of humans and wildlife. DA is a structural analog of glutamate - an excitatory neurotransmitter - that activates ionotropic glutamate receptors leading to excitotoxicity and ultimately neurobehavioral defects. While current seafood regulations prevent acute toxicity from high-level exposure, low-level exposure can still have effects on brain development and function. Developmental stages are particularly sensitive to low-level exposure. This thesis assesses the impact of DA exposure on brain health in both development and adulthood, and investigates whether developmental exposure to DA has persistent effects. In the first data chapter, I employed microarray analysis to demonstrate that exposure to an asymptomatic dose of DA significantly altered gene expression patterns in the adult zebrafish brain. These changes were distinct from those resulting from symptomatic exposure, suggesting that low levels of DA could affect brain function in unique ways. In the second data chapter, I investigated the effect of developmental exposure to DA on immune cells in the brain (microglia). Microglia have critical roles in brain homeostasis, development, and the response to injury or infection. Using transgenic zebrafish (Tg(mpeg1:mCherry)), I characterized developmental windows of microglial sensitivity to DA exposure. Developmental exposure to DA (0.1 ng/embryo) at 2 days post-fertilization (dpf) resulted in microglial reactivity without permanent gross morphological defects. These findings suggest that microglia may be an understudied target of DA toxicity. My final chapter investigates the effects of developmental exposure on later-life behavior and sensitivity to subsequent exposures. I exposed larval zebrafish to 0.1ng DA at 2 dpf and raised these individuals to adulthood, where they received a second exposure to DA or vehicle. Fish exposed to DA in early life showed no significant changes in survival or sensitivity to a second dose of DA. Furthermore, there was no effect of developmental or adult treatment on behavior in novel tank or Y-maze spatial discrimination assays. This thesis contributes to our understanding of neurodevelopmental effects of DA exposure during developmental and adult life stages, emphasizing the potential for microglia as a target of DA.

Thesis

Processes of stratification breakdown and restratification in Antarctic coastal polynyas

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-05) Xu, Yilang ; Zhang, Weifeng Gordon

Antarctic coastal polynyas are areas of persistent open water surrounded by sea ice. They are characterized by deep winter mixing due to dense water formation from sea ice production and elevated biological productivity after spring restratification. Antarctic coastal polynyas are diverse in terms of their mixing and stratification pattern, as well as the associated biological productivity. Here, we combine satellite and in situ observations, idealized numerical models, and analytical scaling to investigate the three-dimensional polynya circulation and explore the physical factors that control the winter destratification and springtime restratification in coastal polynyas. The highresolution coupled model with ice shelf, sea ice, and ocean components qualitatively reproduces the observed coastal polynyas and sea ice fields, as evidenced by satellite measurements. In winter, strong offshore ocean currents driven by offshore katabatic winds carry some newly-formed dense water away from the polynya, weakening the destratification rate in the polynya water column. In contrast, coastal easterly winds induce onshore Ekman transport, constrain dense water outflows, and intensify vertical mixing. Moreover, an ice tongue and coastline geometry can modify sea ice and ocean circulations, thus influencing the dense water dispersal pathways and destratification in polynyas. In spring, offshore-originating sea ice meltwater primarily drives polynya restratification in the top 100 m of the water column. Even though ice shelf basal meltwater can ascend to the polynya surface, much of it is mixed over the upper 100–200 m and does not have a significant contribution to the near-surface restratification. The surface runoff from the ice shelf surface melt could potentially contribute significantly to the near-surface restratification, but its magnitude is less constrained with high uncertainty. This thesis provides a framework to study mixing and stratification dynamics in Antarctic coastal polynyas. It helps to explain their associated variabilities in dense water formation and biological productivity.

Thesis

Genomic and physiological adaptation to temperature in the invasive golden star runicate (Botryllus schlosseri)

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-06) Tobias, Zachary J. C. ; Tepolt, Carolyn K.

Because non-indigenous species (NIS) often encounter novel environments during colonization and expansion, species invasions present useful opportunities to investigate the mode and pace of adaptive change in natural populations. In this dissertation, I use the range expansion of the invasive golden star tunicate, Botryllus schlosseri, as a natural experiment to study how a pernicious NIS adapts its thermal physiology on contemporary time scales. In Chapter 2, I applied low-coverage whole genome sequencing (lcWGS) to investigate patterns of population genetic structure and signatures of local adaptation to temperature. In addition to illustrating the potential for rapid adaptation of thermal tolerance at the genomic level, this chapter demonstrated that the molecular basis of thermal adaptation on either coast is distinct, providing valuable evidence for parallel adaptation being driven by divergent molecular means. In Chapter 3, I performed a physiological study to investigate differentiation of post-larval heat tolerance across five populations across a major biogeographic break on the east coast of North America. I found that northern populations are more susceptible to heat stress than their southern, warm-exposed counterparts, providing evidence for adaptive shifts of thermal tolerance. Further, by taking advantage of natural temporal variability in temperature, I demonstrated that temperature during development positively affects heat tolerance at later life stages, establishing developmental plasticity of thermal tolerance. In Chapter 4, I extended my physiological investigation to the west coast of North America, comparing post-larval heat tolerance across three populations spanning a 24.3° latitudinal gradient while expanding to include differentiation of cold tolerance in adults. Similar to the east coast, I observed that the two northern populations were more susceptible to heat stress than their southern counterpart. For cold tolerance, I observed a pattern of countergradient variation whereby northern populations were better able to maintain cardiac function in the cold than southern populations. This suggests compensatory genetic adaptation to the colder water temperatures at higher latitudes. Overall, my work furthers our understanding of how NIS are able to rapidly shift their thermal physiology in response to novel environments, shedding light on the potential of species more generally to adapt to environmental change on contemporary timescales.

Thesis

The impact of metals and other stress factors on microbial ammonia oxidation physiology and isotope effects

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-06) Martocello, Donald E., III ; Wankel, Scott

Microbially-mediated cycling processes play central roles in regulating the speciation and availability of nitrogen, a vital nutrient with wide implications for agriculture, water quality, ecosystem health, and climate change. Ammonia (NH3) oxidation, the first and rate-limiting step of nitrification, is carried out by bacteria (AOB) and archaea (AOA). Despite more than a century of research into the physiology of AOB, and only more recently AOA, fundamental questions remain about the ammonia oxidation reaction mechanism and relevant stress factors that regulate environmental rates. Ammonia oxidizing organisms (AOO) require the trace metal micronutrients copper (Cu) and iron (Fe) for growth and metabolic catalysis. Ammonia oxidation is directly affected by pH in regulating the relative availability of ammonium (NH4+) and NH3. Also, photoinhibition of AOO is widely reported. The mechanism is unknown, although links to reactive oxygen species (ROS) cycling seem likely. We present detailed investigations of three environmentally relevant AOO stress factors: metal micronutrient limitation, pH changes, and ROS. Central to these studies were analyses of stable isotope fractionation and how changes in AOO physiology impact expression of these isotope effects. In turn, these tools facilitate probing of the ammonia oxidation reaction mechanism and we propose an initial obligatory coordinated NH4+-NH3 uptake step based on isotope mass balance. In addition, we studied nitrification and related environmental chemistry in the Northern Guaymas hydrothermal vent basin in the Gulf of California. This region hosts a unique juxtaposition of hydrothermal vent emissions enriched in NH4+ underlying an extensive regional oxygen deficient zone (ODZ). Most environmental studies of nitrification have focused on the mesopelagic (high oxygen, comparably warmer temperatures, low NH4+, and low metal micronutrient availability). The Northern Guaymas Basin is functionally the opposite. We suggest ultimate limitation by temperature and, surprisingly, potential proximal limitation by NH4+, Fe, and Cu. In total, this work emphasizes the recently recognized role of Fe and Cu in environmental limitation of nitrification, challenges key axioms of AOO cell culturing and physiology, and proposes revisions to canonical ammonia oxidation reaction mechanisms.

Thesis

Enabling human-multi-robot collaborative visual exploration in underwater environments

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-05) Jamieson, Stewart C. ; Girdhar, Yogesh

This thesis presents novel approaches to vision-based autonomous exploration in underwater environments using human-multi-robot systems, enabling robots to adapt to evolving mission priorities learned via a human supervisor’s responses to images collected in situ. The robots model the spatial distribution of various habitats and terrain types in the environment using semantic classes learned online, and send image queries to the supervisor to learn which of these classes are associated with the highest concentration of targets of interest. The robots do not require prior examples of these targets, and learn these concentration parameters online. This approach is suitable for exploration in unfamiliar environments where unexpected phenomena are frequently discovered, such as coral reefs. A novel risk-based online learning algorithm identifies the concentration parameters using the fewest possible number of queries, enabling the robots to adapt quickly and reducing the operational burden on the supervisor. I introduce four primary contributions to address prevalent challenges in underwater exploration. Firstly, a multi-robot semantic representation matching algorithm enables interrobot sharing of semantic maps, generating consistent global maps with 20-60% higher quality scores than those produced by other methods. Next, we present DeepSeeColor, a novel real-time algorithm for correcting underwater image color distortions, which achieves up to 60 Hz processing speeds, thereby enabling improved semantic mapping and target recognition accuracy online. Thirdly, an efficient risk-based online learning algorithm ensures effective communication between robots and human supervisors, and, while remaining computationally tractable, overcomes the myopia which would cause previous algorithms to underestimate a query’s value. Lastly, we propose a new reward model and planning algorithm tailored for autonomous exploration, together enabling a 25-75% increase in the number of targets of interest located when compared to baseline surveys. These experiments were conducted with simulated robots exploring real coral reef maps and with real, ecologically meaningful targets of interest. Collectively, these contributions overcome key barriers to vision-based autonomous underwater exploration, and enhance the capability of autonomous underwater vehicles to adapt to new and evolving mission objectives in situ. Beyond marine exploration, these contributions have value in broader applications, such as space exploration, ecosystem monitoring, and other online learning problems.

Thesis

Coupled cycling of metals with nitrogen and carbon in marine sediments

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-05) Karolewski, Jennifer S. ; Wankel, Scott

Cross element processes are complex and often understudied components within biogeochemical cycles. In this thesis, I use stable isotopes of carbon, nitrogen, and oxygen as the primary tools to interrogates these complex reactions. First, I report abiotic oxidation of nitrite to nitrate by manganese(III)-pyrophosphate. This reaction can occur even in the absence of oxygen, unlike biological nitrite oxidation. Reaction rates were measured at a range of environmentally relevant pH values (5-8) with the reaction proceeding more quickly at lower pH. Reaction order was second order with respect to manganese(III) and first order with respect to nitrous acid. No reversibility of reaction was observed upon addition of isotopically distinct nitrate. An inverse kinetic isotope effect of +19.9 ± 0.7‰ was calculated, which was comparable in magnitude and direction to that of biological nitrite oxidation. In natural waters, such as estuaries, this reaction could potentially play an important role in the nitrogen cycle. Next, I report an abiotic reaction between hydroxylamine and manganese(III)-pyrophosphate which forms nitrous oxide, nitrite, and likely dinitrogen gas. In artificial seawater (pH = 8), this reaction proceeds rapidly, with the ratio of products highly dependent on the reactant ratio. Nitrous oxide site preference (SP) of +35.5 ± 0.6‰ was observed, consistent with the isotopic signatures of several marine nitrifying organisms. This suggests that “leakage” of intermediate hydroxylamine from nitrifier cells could potentially react with manganese(III) in a mixed biotic-abiotic process without previously being noticed. Finally, I performed experiments using carbon-13 labelling to measure rates of anaerobic oxidation of methane (AOM) in cold seep sediments collected at Cascadia Margin. Four forms of oxidized manganese and four forms of oxidized iron were added to treatments in order to evaluate how these altered rates of AOM. In contrast to previous work, addition of metals did not overall increase rates of AOM above those of an unamended control and some treatments in fact reduced it. However, energy yields from microbes using metal as an electron acceptor are higher per mole of methane reduced than that of using sulfate so even with these lower rates, energy yields would have exceeded those of controls. Additionally, doubling times for the archaea performing AOM are long enough that the microbial community may not have been able to adapt on the timescale of the experiment. Overall, the results of this thesis illuminate the need for further study of abiotic and coupled cycling reactions when considering biogeochemical cycles.

Thesis

Inference and robotic path planning over high dimensional categorical observations

(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024-06) San Soucie, John E. ; Girdhar, Yogesh ; Sosik, Heidi M.

Advances in marine autonomy, deep-learning, and in-situ marine sensing technology have enabled oceanographers to collect vast amounts of spatiotemporally-distributed, sparse, highdimensional categorical data. Statistical models, particularly in streaming and computationally constrained settings, have lagged behind data collection. Recent developments in topic modeling for robotics have highlighted the potential to efficiently extract meaningful relationships from categorical data, and adjust robotic path-planning based on real-time inference. This dissertation seeks to fill the gap in streaming statistical models for sparse, high-dimensional categorical data, in the context of open-ocean phytoplankton community ecology. We begin by exploring the use of existing topic modeling approaches for plankton community characterization. Topic models are compared to standard ecological techniques for dimensionality reduction. The increased fidelity and expressiveness of the topic modeling approach allows for greater resolution of plankton co-occurrence relationships. By analyzing these relationships and ocean physics in and around a retentive eddy, the source of phytoplankton variability is traced to storm-driven advection on the ocean surface. We conclude that topic models offer unique insights into the causal mechanisms underlying plankton community variability. Next, we turn our focus to the development of a streaming belief model for categorical path planning. Such a model must be capable of predicting in regions without data, and it must be able to process streaming data in a computationally efficient manner. We introduce the Gaussian Dirichlet Random Field model, a novel topic model with spatially continuous latent log-probabilities. In addition to producing a more accurate model than the state-ofthe-art in locations with data, the Gaussian Dirichlet Random Field model can interpolate and extrapolate. The model is initially presented with a batch hybrid Markov Chain-Monte Carlo inference procedure. We develop a streaming fully-variational inference approach for inference, called Streaming Gaussian Dirichlet Random Fields, which satisfies both the prediction and efficiency requirements for path planning belief models. In-silico experiments demonstrate the ability of this model to accurately map latent co-occurrence patterns. Comparisons to a standard Gaussian process on both path-planning tasks and observation mapping tasks show how the ability of Streaming Gaussian Dirichlet Random Fields to leverage additional categorical observations enables superior performance.

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