ALBERT

Description: The ability to adapt to social and environmental change is an increasingly critical feature of environmental governance. However, an understanding of how specific features of governance systems influence how they respond to change is still limited. Here we focus on how system features like diversity, heterogeneity, and connectedness impact stability, which indicates a system's capacity to recover from perturbations. Through a framework that combines agent-based modeling with "generalized"dynamical systems modeling, we model the stability of thousands of governance structures consisting of groups of resource users and non-government organizations interacting strategically with the decision centers that mediate their access to a shared resource. Stabilizing factors include greater effort dedicated to venue shopping and a greater fraction of non-government organizations in the system. Destabilizing factors include greater heterogeneity among actors, a greater diversity of decision centers, and greater interdependence between actors. The results suggest that while complexity tends to be destabilizing, there are mitigating factors that may help balance adaptivity and stability in complex governance. This study demonstrates the potential in applying the insights of complex systems theory to managing complex and highly uncertain human-natural systems in the face of rapid social and environmental change.

Description: Marine particles of different nature are found throughout the global ocean. The term "marine particles"describes detritus aggregates and fecal pellets as well as bacterioplankton, phytoplankton, zooplankton and nekton. Here, we present a global particle size distribution dataset obtained with several Underwater Vision Profiler 5 (UVP5) camera systems. Overall, within the 64 μm to about 50 mm size range covered by the UVP5, detrital particles are the most abundant component of all marine particles; thus, measurements of the particle size distribution with the UVP5 can yield important information on detrital particle dynamics. During deployment, which is possible down to 6000 m depth, the UVP5 images a volume of about 1 L at a frequency of 6 to 20 Hz. Each image is segmented in real time, and size measurements of particles are automatically stored. All UVP5 units used to generate the dataset presented here were inter-calibrated using a UVP5 high-definition unit as reference. Our consistent particle size distribution dataset contains 8805 vertical profiles collected between 19 June 2008 and 23 November 2020. All major ocean basins, as well as the Mediterranean Sea and the Baltic Sea, were sampled. A total of 19 % of all profiles had a maximum sampling depth shallower than 200 dbar, 38 % sampled at least the upper 1000 dbar depth range and 11 % went down to at least 3000 dbar depth. First analysis of the particle size distribution dataset shows that particle abundance is found to be high at high latitudes and in coastal areas where surface productivity or continental inputs are elevated. The lowest values are found in the deep ocean and in the oceanic gyres. Our dataset should be valuable for more in-depth studies that focus on the analysis of regional, temporal and global patterns of particle size distribution and flux as well as for the development and adjustment of regional and global biogeochemical models. The marine particle size distribution dataset is available at 10.1594/PANGAEA.924375.

Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: The morphology of a shoreline can provide insight into the processes that have modified the coast. This thesis investigates how coastal processes can leave fingerprints on the morphology of a coast in sandy environments (barrier islands) and detachment-limited environments (rocky coasts of Earth and possibly Titan). Barrier islands are dynamic and ephemeral, facing an uncertain future from climate change and anthropogenic redistribution of sediment. To evaluate barrier resilience to sea-level rise, I propose a novel dimensionless metric called the Washover Ratio which compares cross-shore (overwash) and alongshore transport. Using this ratio, I find that decreases in overwash flux within the narrow middle section—possibly representing the effects of development—lead to a diminished response to sea-level rise across the entire barrier, and therefore a more vulnerable barrier overall. Further investigation of the balance between overwash and alongshore sediment transport allows for an evaluation of barrier island stability to overwash-induced breaching, which is applied to barriers in the Gulf of Mexico. Beyond Earth, Titan, Saturn’s largest moon, is home to the only other active coastlines in our solar system. However, data is sparse for this icy moon. I investigate the signatures of coastal processes found in the planform shape of its coasts using a combination of landscape evolution models and measurements of shoreline shape. Results show that the coastlines of Titan’s seas are consistent with those of both modelled and Earth lakes with flooded river valleys that have been subsequently eroded by waves, particularly when waves saturate (no longer grow in height) at scales up to 10s of km.

Description: Work toward this thesis was funded by the National Science Foundation (NSF) and National Aeronautics and Space Administration (NASA). NSF funding was awarded through the Graduate Research Fellowship Program (#1745302) and the Coupled Natural Hazards program (#CNH-1518503). NASA funding was awarded through the Cassini Data Analysis Program (#80NSSC18K1057) and (#80NSSC20K0484).

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: The search for underwater threats in littoral regions is a problem that has been researched for nearly a century. However, recent developments in autonomy and robotics have made this issue more complex. The advent of capable autonomous underwater vehicles presents a 21st century flare to this traditional problem. These vehicles can be smaller, quieter, and expendable. Therefore, new methods and tactics used to detect and track these vehicles are needed. The use of a swarm of marine robots can increase the likelihood of uncovering these threats. This thesis provides various Voronoi partition-based methods to autonomously control a swarm of identically capable autonomous surface vessels in a limited coverage and tracking problem. These methods increase the probability of interdiction of an adversary vehicle crossing a defined region. The results achieved from Monte Carlo simulations demonstrate how different protocols of swarm movement can improve detection probability as compared to a stationary swarm provided the detection capability does not change. The swarm control algorithms are employed on Clearpath Heron USVs to validate the autonomy algorithms.

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: Acoustic propagation measurements are made in a highly variable and stratified estuary using high frequency transducers (120kHz) on tripods placed across the main channel of the river flow. The measurements are taken in the Connecticut River across several tidal cycles, when the flood tide causes a wedge of seawater to press up the river bed, beneath the fresh water, and then be eroded and pushed back out during the ebb. BELLHOP, implemented via Matlab, is a beam/ray tracing method and is used to model the acoustic propagation in this environment using collected temperature, salinity, and depth data. Multiple modeling comparisons are done over the period of three full tidal cycles, totaling a thousand separate modeling runs and compiled into a time series. Arrival times measurements from the transducer system were able to be accurately modeled, validating BELLHOP as a useful tool in modeling this very dynamic and challenging acoustic environment.

Description: This thesis would not have been possible with the data collected by Dr. Andone Lavery, Jonathan Fincke and others, originally funded by the Office of Naval Research (through ONR Grant #N00014-11-10058).

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science in Chemical Oceanography at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: The environmental effects of both increased urbanization and eutrophication are of growing global concern. Coastal areas, like those found on Cape Cod, Massachusetts, often experience severe impacts associated with the biogeochemical effects accompanying increased nitrogen pollution. Cape Cod is home to roughly 1,000 ponds and lakes which play an important role in local ecosystems, but the cycling of nitrogen in these waters is not well understood. The goal of this research is to identify the major biogeochemical cycling processes responsible for the fate of nitrogen in a nitrogen-rich, coastal, stratified pond. The investigation was carried out through regular high-resolution measurement and monitoring of environmental conditions, nitrogen speciation, and isotopic composition over the course of a summer. Elevated nitrogen concentrations coupled with strong redox gradients make Siders Pond an ideal place for studying dynamics of nitrogen transformations, giving insight into nitrogen retention or removal, which influence water quality. These data demonstrate significant dissolved nitrogen loss from the pond over the course of the summer as well as internal nitrogen cycling that promotes dissolved nitrogen accumulation to extreme levels in the deepest depths. The physical dynamics of mixing promote a coupling of nitrification and denitrification across this redox gradient, driving N loss while also supplying the sunlit waters with nutrient-rich deep water. A simple time-resolved box model suggests that approximately 50% of the upwardly delivered N is removed, while the other portion supports recycling through photosynthetic uptake. While dissolved organic nitrogen (DON) is widely considered refractory material and is rarely measured or reported in environmental studies, here there is evidence for a large and dynamic pool of DON within Siders Pond suggesting important dynamics between organic and inorganic pools in regulating N loss. While nitrate is a commonly used measurement for assessing N contamination, this work highlights the parallel importance of monitoring additional species (including ammonium and DON) for determining eutrophication/contamination. A deeper understanding of Siders Pond can be used to elucidate nitrogen cycling dynamics in analogous redox-stratified systems, including other lakes and ponds, or modern ocean regions such as the Santa Barbara and Cariaco Basins and the Baltic and Black Seas.

Description: National Science Foundation (project number NSF-1924236)

Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: With the rapid decline of coastal ecosystems such as coral reefs and seagrasses, it is crucial to better understand the health of these ecosystem to prevent future loss. Reactive oxygen speices (ROS), such as superoxide and hydrogen peroxide, play an underappreciated role in both organism health and ecosystem biogeochemical cycles. This thesis lays the foundation to measure and identify ROS production by coral in situ and through genomic analysis while also highlighting the important role that ROS can play within biogeochemical cycling within seagrass ecosystems. To measure in situ extracellular superoxide, we develop the first DIver-operated Submersible Chemiluminescent sensOr (DISCO), enabling high resolution, non-invasive measurements in real time. We further refine DISCO by making it more compact, user-friendly, adaptable, and robust, enabling measurements of superoxide across a diversity of environments. Using DISCO, I observe species-specific variation in extracellular superoxide concentrations associated with healthy coral. Despite these variations across species, bioinformatic analysis of coral proteins reveal that nearly all coral species have the extracellular superoxide-producing enzyme NADPH oxidase (NOX), and thus the genetic potential to produce extracellular superoxide. This suggests that coral species likely exhibit differential NOX regulation and expression as a function of physiological responses to external stressors, which may play a role in coral immunity. I then turn to seagrass ecosystems, where I observe rapid hydrogen peroxide production and decay through predominantly reductive pathways. This has implications on the environmental redox state and biogeochemical cycling, impacting the ecosystem services that seagrasses provide to marine environments and coastal communities. Overall, this thesis highlights the potential role that ROS may be playing in organism and ecosystem health and lays the groundwork to further develop ROS as a tool to protect these coastal ecosystems against further degradation.

Description: Funding for this work was provided by the following grants: NSF GRFP (2016230168), Schmidt Marine Technology Partners (G-1801-57385 andG-2010-59878), WHOI Ocean Ventures Fund (2020 and 2021), and the MIT Wellington and Irene Loh Fund Fellowship (4000111995).

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: This thesis presents an Autonomous Underwater Glider (AUG) architecture with improved onboard navigation and acoustics-based sensing intended to enable basin-scale unattended surveys of our Earth’s most remote oceans. Traditional AUGs have long-been an important platform for oceanographic surveys due to their high endurance and autonomy, yet lack the operational flexibility to operate in many regions of scientific interest and the sensing capability to capture scientific data at the air-sea interface. Particularly of interest is the marginal ice zone (MIZ) in the Arctic and the Southern Ocean, as both are vitally important to understanding global climate trends, yet prohibitively expensive to persistently monitor with support vessels. To fill this observational gap, the sensing, navigation, and adaptability of AUGs must be improved. This is possible by employing onboard acoustic sensing for sea state observation and navigation, as well as incorporating vehicle improvements targeting maneuverability and intelligent adaptability to evolving environmental states. To enable persistent monitoring of both the water-column and air-sea interface, this thesis proposes an improved vehicle architecture for a more capable AUG, a real-time DVLaided navigation process that leverages ocean current sensing to limit localization error, and a subsea acoustics-based sea state characterization method capable of analyzing wave spectra under-ice and with zero surface expression. These methods are evaluated with respect to extensive laboratory experiments and field data collected during in-situ implementation.

Description: Support for this research was provided through grants from the National Science Foundation (NSF) Navigating the New Arctic Grant (NNA #1839063) and the National Ocean Partnership Program (NOPP) Enhanced Propulsion Integrated Capability - Deep Autonomous Underwater Glider (EPIC-DAUG) grant (NA19OAR0110408).

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: The goal of this project is to investigate the relationship between paleoceanographic radiocarbon records and the ventilation history of deep oceanic basins during the last 40 kyrs. Deep ocean ventilation changes, especially changes in Atlantic meridional overturning circulation (AMOC), are often invoked to explain the deglacial rise in atmospheric carbon dioxide (CO2) concentration as inferred from ice core records. Much of our current understanding regarding ventilation of the deep ocean during the deglaciation comes from records of the radiocarbon concentration of benthic foraminifera and deep-sea corals (paleo-Δ14C data). Here, we combine a global compilation of paleo-Δ14C data for the past 40 kyrs with a 16-box model of the world ocean (except the Arctic Ocean) to address two key questions: (1) To what extent can the paleo-Δ14C data be explained by atmospheric Δ14C variations when deep ventilation rates are fixed to modern ocean estimates? and (2) To what extent can the paleo- Δ 14C data be explained by atmospheric Δ 14C variations when the ventilation rates are allowed to vary? To address these questions, the box model is fitted to the paleo-Δ14C data using the following sequential methods of optimal estimation theory: the linear Kalman filter, the Extended Kalman Filter, the Rauch-Tung-Striebel (RTS) smoother, and a linearized RTS smoother. We find that 62–76% (depending on the assumptions made about air-sea 14CO2 exchange) of the paleo-Δ 14C data for the past 40 kyrs can be explained by the modern flow rates as represented in the box model, if the model is forced with the IntCal20 reconstruction of atmospheric Δ14C. When the flow rates in the model are allowed to vary with time, 74-89% of the data can be explained by the model. Here, the range in data that can be explained reflects the different assumptions about the errors in the air-sea 14CO2 exchange and in the random walk used to model the temporal evolution of flow rates. It is concluded that changes in deep ocean ventilation may have occurred from 20 and 10 ka, thereby contributing to the deglacial CO2 rise, but that the spatial pattern of ventilation changes may have been complex, with a strengthening of the downwelling branch of the AMOC and a weakening of its deep southward branch during this time.

Description: This project was supported by the United States National Science Foundation, grant number 1903427, which made this work possible.

Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.

Description: Automated information gathering allows exploration of environments where data is limited and gathering observations introduces risk, such as underwater and planetary exploration. Typically, exploration has been performed in service of a query, with a unique algorithm developed for each mission. Yet this approach does not allow scientists to respond to novel questions as they are raised. In this thesis, we develop a single approach for a broad range of adaptive sampling missions with risk and limited prior knowledge. To achieve this, we present contributions in planning adaptive missions in service of queries, and modeling multi-attribute environments. First, we define a query language suitable for specifying diverse goals in adaptive sampling. The language fully encompasses objectives from previous adaptive sampling approaches, and significantly extends the possible range of objectives. We prove that queries expressible in this language are not biased in a way that avoids information. We then describe a Monte Carlo tree search approach to plan for all queries in our language, using sample based objective estimators embedded within tree search. This approach outperforms methods that maximize information about all variables in hydrocarbon seep search and fire escape scenarios. Next, we show how to plan when the policy must bound risk as a function of reward. By solving approximating problems, we guarantee risk bounds on policies with large numbers of actions and continuous observations, ensuring that risks are only taken when justified by reward. Exploration is limited by the quality of the environment model, so we introduce Gaussian process models with directed acyclic structure to improve model accuracy under limited data. The addition of interpretable structure allows qualitative expert knowledge of the environment to be encoded through structure and parameter constraints. Since expert knowledge may be incomplete, we introduce efficient structure learning over structural models using A* search with bounding conflicts. By placing bounds on likelihood of substructures, we limit the number of structures that are trained, significantly accelerating search. Experiments modeling geographic data show that our model produces more accurate predictions than existing Gaussian process methods, and using bounds allows structure to be learned in 50% of the time.

Description: The work in this thesis was supported by the Exxon Mobil Corporation as part of the MIT Energy Initiative under the project ‘Autonomous System for Deep Sea Hydrocarbon Detection and Monitoring’, NASA’s PSTAR program under the project ‘Cooperative Exploration with Under-actuated Autonomous Vehicles in Hazardous Environments’, and the Vulcan Machine Learning Center for Impact under the project ‘Machine Learning Based Persistent Autonomous Underwater Scientific Studies’.