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Enhancing the Robustness and Trustworthiness of Machine Learning Models in Diverse Domains
Get PDFThesis (Ph.D.)--Michigan State University. Computer Science - Doctor of Philosophy, 2025The rapid advancement of machine learning, particularly over-parameterized deep neural networks (DNNs), has led to significant progress across diverse domains. While the over- parameterization of DNNs gives them the power to capture complex mappings between input data points and target labels, in real-world challenges, they can inevitably be exposed to unseen out-of-distribution (OoD) examples that deviate from the training distribution. This raises critical concerns around robustness, adaptiveness, and trustworthiness of such models when transferring knowledge from the training domains to unseen test domains.In this thesis, we propose three different methods targeting the robustness and adaptiveness of machine learning models. First, to address agnostic data corruption in the source domain, we propose a simple and computationally efficient unsupervised domain adaptation (UDA) approach that enables parallel training of ensemble models. The learning framework we proposed can be flexibly combined with available UDA approaches that are orthogonal to our work to improve their robustness under corrupted data. Second, with the rise of large language models (LLMs) pre-trained on vast, web-sourced datasets spanning multiple domains, which led to a surge of interest in adapting these models to a wide range of downstream tasks. However, the real-world corpora used in the pre-training stage often exhibit a long-tail distribution, where knowledge from less frequent domains is underrepresented. As a result, LLMs failed to give correct answers for queries sampling from the long-tail distributions. To solve this problem, we propose a reinforcement learning-based dynamic uncertainty ranking method for retrieval-augmented ICL with a budget controller. The system adjusts the ranking of retrieved samples based on LLM feedback, promoting informative and stable examples while demoting misleading ones. Third, while the neighborhood community DA aims to ensure model robustness by maintaining high performance on OoD samples from target domains with domain shifts, out-of-distribution (OoD) detection focuses on model reliability by identifying samples that exhibit semantic shifts. To bridge a critical research gap of OoD detection and federated learning (FL), we propose a privacy-preserving federated OoD synthesizer that exploits data heterogeneity to enhance out-of-distribution (OoD) detection across clients. This approach enables each client to benefit from external class knowledge shared among non-IID participants, without compromising data privacy.The model adaptation process can also introduce a new challenge, which is the risk of unauthorized reproduction or intellectual property (IP) theft, especially for high-value models. To enhance the trustworthiness of models, we introduce two methods for model watermarking. The first is an OoD-based watermarking technique that eliminates the need for training data access, making it suitable for scenarios with strict data confidentiality. The method is both sample-efficient and time-efficient while preserving model utility. The second technique targets federated learning, enabling both ownership verification and leakage tracing, transitioning FL model use from anonymity to accountability.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Food Trade System Under Crises in a Metacoupled World
Get PDFThesis (Ph.D.)--Michigan State University. Fisheries and Wildlife - Doctor of Philosophy, 2025In an increasingly interconnected world, food trade systems are increasingly exposed to overlapping crises\u2014including pandemics, geopolitical conflicts, and climate change. These disruptions reveal persistent vulnerabilities in global supply chains and demand a cross-scale understanding of food trade resilience. This dissertation applies the metacoupling framework\u2014which integrates human\u2013nature interactions within (intracoupling), between neighboring (pericoupling), and between distant (telecoupling) systems\u2014to examine food trade dynamics under multiple crises across spatial and temporal scales.Chapter 2 presents a systematic review of 455 peer-reviewed studies and identifies major gaps in existing research. While most studies focus on national-scale trade or intracoupled systems, few consider spillover systems or interactions across multiple coupling types. Based on this gap, the chapter synthesizes fragmented resilience indicators into a unified assessment framework, structured around human- and nature-related drivers. Chapter 3 develops a multi-dimensional evaluation framework to assess food trade resilience before and after the COVID-19 pandemic. By disaggregating five indicators\u2014Bonilla index, centrality, connectivity, trade disruptions, and supply chain diversity\u2014into adjacent and distant trade components, the study reveals stark inequalities in resilience, particularly in low-income countries with limited diversification and infrastructure. Chapter 4 constructs a rapid assessment framework to estimate the impacts of the Russia\u2013Ukraine war on winter cereals trade in 2022. Leveraging remote sensing-based cropland data, trade statistics, and network metrics, the study shows a sharp decline in trade connectivity and the emergence of new trade pathways, exposing the fragility of current supply chains in conflict-affected regions. Chapter 5 extends the analysis to the global wheat trade over three decades (1991\u20132022). Using a combination of network analysis, structural change modeling (SCM), and generalized additive models (GAM), the chapter quantifies long-term trends in trade resilience. The results show widening disparities across income groups, with distant trade growing in dominance and low-income countries remaining disproportionately vulnerable to both acute and chronic crises. Together, these chapters advance theoretical and empirical understanding of food trade resilience under multiple crises. By integrating metacoupling theory with remote sensing, network science, and quantitative modeling, this dissertation provides a cross-scale perspective on the evolving structure of global wheat trade and offers actionable insights for enhancing global food system resilience.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Canine Bladder Cancer as a Model for Targeted Radiotherapeutic Development
Get PDFThesis (M.S.)--Michigan State University. Comparative Medicine and Integrative Biology - Master of Science, 2025The more advanced form of bladder cancer (BC), muscle-invasive bladder cancer (MIBC), remains a significant clinical challenge in both canine and human patients afflicted with the disease. Although non-muscle invasive bladder cancer is the more dominant subtype, cases often reccur or progress, even after treatment. Despite current treatment options like chemotherapy, cystectomy, and external beam radiation, invasive bladder cancers have poor prognosis, with a 50% mortality rate in humans, and dogs are rarely cured. Dogs naturally develop bladder cancer in the presence of a complete immune system, making them an ideal preclinical model for studying human bladder cancer and developing novel targeted therapies as opposed to current available murine models. This study investigated the potential of radiolabeled FDA-approved monoclonal antibodies dual-targeting EGFR1 and EGFR2 biomarkers for treating canine bladder cancer and the possibility of eventually translating these findings into human treatment.This thesis project aimed to characterize EGFR1 and EGFR2 expression in five different canine bladder cancer cell lines using technetium-99m binding assays, and confirming the binding affinities of monoclonal antibodies cetuximab and trastuzumab for these receptors. Colony formation assays were conducted to assess the impact of radiation therapy using beta-particle therapy (Lu-177-[cetuximab/trastuzumab]) and were compared with results from studies performed without radiation. Findings suggested that the antibodies alone do not have an inhibitory or proliferative effect on the canine bladder cancer and that any theraputic effects may be attributed to that of the radiation alone. Additionally, this study supports the use of targeting radiation therapy as a more promising treatment for both canine and human bladder cancer, with the potential for reduced off-target effects when compared to traditional radiation therapies, like external beam radiation therapy. The utilization of pet dogs as a model for MIBC is particularly advantageous, given that canine bladder cancer closely resembles the disease in humans. Overall, this approach could accelerate the development of targeted radiotherapies and improve treatment outcomes for both veterinary and human patients. Leveraging similarities between canine and human bladder cancer should allow for enhanced therapeutic strategies that expedite the translation of novel therapeutics into clinical practice, a win-win scenario for canine and human patients alike.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ENABLING UNDERWATER BIOLOGICAL CONTACT SENSING SYSTEMS FOR SEA LAMPREY DETECTION THROUGH CARBON-BASED INTERDIGITATED ELECTRODES
No full textThesis (Ph.D.)--Michigan State University. Electrical and Computer Engineering - Doctor of Philosophy, 2025Accurate monitoring of sea lamprey populations is critical to enabling the deployment of moretargeted and effective control measures to minimize the impact associated with this species. This dissertation demonstrates the development of an automated sea lamprey detection system and the effects of algal-based biofouling on its voltage response. The system is built around a sensor composed of two exposed carbon-based planar in- terdigitated electrodes (IDE) functioning as an underwater biological contact sensor. A microcontroller-based DC measurement system for the detection of lamprey attachment underwater is presented; measuring voltage instead of impedance reduces cost and signal processing complexity, making the device more attractive for field deployment. The system is calibrated to a baseline output voltage, and deviations from this baseline occur when ob- jects touch the IDE. Validation was done through testing on live adult sea lampreys using video recordings to correlate lamprey attachments to the sensor response. Three response types were identified corresponding to different attachments: sustained, short, and sliding- sustained (video demonstrations are included in this work). The response to sustained and sliding-sustained attachments showed a characteristic exponential decay, whereas the response due to short attachments was indistinguishable from measurement noise. Sea lam- prey size was found to have a weak linear correlation with both response parameters, positive for the voltage drop and negative for the time constant of the voltage drop. A representative circuit for the lamprey-sensor interaction is proposed and simulated using element values calculated from the response parameters. The response of the model shows agreement with experimental data. Characterization of the IDE sensor\u2019s response to sea lamprey attachment allowed for the development of detection algorithms, to automate the process of detecting sea lamprey from the sensor output. Inherent limitations on the computing power of the microcontroller unit used to measure the sensor motivated the exploration of low-complexity models for the task: single-layer artificial neural networks, logistic regression, Gaussian Na \u308\u131ve-Bayes, decision trees, random forest, and Scalable, Efficient, and Fast classifieR (SEFR). Threshold models tuned using a multi-objective optimization formulation were also considered. Mod- els were trained/tuned with a data set generated through live animal testing and presented accuracies between 80-86%. The models were deployed on an Arduino microcontroller plat- form and compared in classification accuracy, detection performance, time complexity, and memory size using real-time detection testing. Classification accuracies between 65-75% were observed during validation. Models demonstrated capture rates of 63-85% for sea lamprey attachments and average detection delays of 9-36 seconds. A video demonstration of a real- time validation test is also presented. Sensor robustness, sensitivity, and detection speed were identified as areas of improvement for the system, so electrodes were updated to more durable, conductive carbon-based 3D-printed electrodes, and an updated measurement sys- tem combining a resistive bridge topology and an instrumentation amplifier was developed to allow for scaling the sensor response. The effects of biofilm accumulation on the baseline sensor response were also studied to simulate field conditions. Sensors were exposed to optimal biofilm growth conditions in a photobioreactor running a culture of Chlorella sorokiniana MSU, a robust algae species native to the Great Lakes region. Two responses to biofilm formation on the sensors were observed: (1) a consistent rise in voltage following the increasing form of the exponential decay function, and (2) a similar rise in baseline but followed by a period of approximately exponential decay. These responses were generally related to changes in sensor resistance, with (1) corresponding to a decrease and (2) to an increase. A study relating these changes in sensor resistance to biomass accumulation was performed, but did not produce a conclusive relationship. The sensors\u2019 ability to pick up biological contact after fouling was observed to be inconsistently affected. The implications of these results for sea lamprey detection and potential ways to address them are discussed. Overall, this research presents the first step toward an electronic sea lamprey monitoring system that can provide a detailed view of sea lamprey activity, enhancing control and conservation efforts across its entire range.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
SANKOFA : RECLAIMING AND RE/POSITIONING INDIGENOUS AFRICAN RHETORICS
Get PDFThesis (Ph.D.)--Michigan State University. Rhetoric and Writing - Doctor of Philosophy, 2025In this dissertation, I examine the situatedness and importance of African rhetorics within the field of rhetoric and writing as well as its related fields. Grounded in a decolonial research orientation and rooted in African thought, I investigate how African worldviews can be analyzed to reveal the profound rhetorical power and significance embedded in Indigenous African knowledge systems. I focus on African rhetoric and then shed light on how the shortcomings of Euro-Western frameworks adopted to examine any phenomena in African contexts tend to often lead some scholars to reduce African worldviews and rhetorical practices to superficial elements such as aesthetics, religious performances, or entertainment. To address these constrained perspectives, I propose and develop the sankofa methodology\u2014a decolonial research framework inspired by the Akan philosophical concept of sankofa, which emphasizes purposeful return to the past in order to reclaim, reinterpret, and reapply valuable cultural knowledge for the present and future. Through this methodology, I investigate the deep-seated knowledge and rhetorical dexterity of kente and kente weaving. Focusing on the rhetorical and technical communication dimensions of kente and kente weaving among the Ewe people of Ghana, I use talking circles and counter-storytelling to engage with weavers to uncover, articulate, and reclaim the epistemic, communal, and meaning-making power of kente weaving practice. By adopting a decolonial perspective, this research offers new insights into how African meaning-making practices foster community-building, inclusivity, and decolonial encounters. This research contributes to decolonial and Indigenous rhetoric, technical communication, and cultural and material rhetorics by foregrounding relationality, cultural specificity, and rhetorical sovereignty. Ultimately, this research calls for a paradigmatic shift that centers African ways of knowing as vital to global knowledge-making practices.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
UNLOCKING OPPORTUNITIES : THREE ESSAYS ON STATE POLICIES SUPPORTING ENGLISH LEARNERS\u2019 SUCCESS
No full textThesis (Ph.D.)--Michigan State University. Educational Policy - Doctor of Philosophy, 2025Our nation's nearly five million English learner-classified (EL) students, comprisingnearly 10 percent of the US K-12 student population, face significant educational disparities resulting from inadequate attention to their needs within current policies and practices, placing them at a distinct educational disadvantage compared to their non-EL peers. While a large body of research highlights inequities ELs face in their schools and classrooms, less has focused on the ways broader education policies exacerbate or ameliorate educational inequities for ELs. Research in this area can offer thoughtful analysis to policymakers and education leaders as they work to expand equity for this growing and diversifying subgroup of students.This three-paper dissertation explores the role of state policy in shaping ELs\u2019 educationalopportunities in Michigan. Michigan offers a useful context for study as it is a new immigrant diaspora state with a fast-growing EL population, similar to many other US states. The first paper employs a difference-in-regression discontinuities design to assess the impact of shifting reclassification responsibility from school districts to the state, highlighting the ability of default policies to standardize EL reclassification processes. The second paper leverages interview data with school district leaders to better understand how school districts interpret and implement state funding policy to provide EL services. The findings highlight areas in which policy can better support districts to provide effective, high-quality English language development services. The third paper couples administrative and interview data to document changes in recent immigrant, or \u201cnewcomer,\u201d student populations, and explores school districts\u2019 responses to suchDescription based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
EVALUATING THE IMPACT OF BIOFERTILIZER ON MAIZE (ZEA MAYS L.) YIELD AND NITROGEN UPTAKE
Get PDFThesis (M.S.)--Michigan State University. Crop and Soil Sciences - Master of Science, 2025Synthetic fertilizers have played a significant role in sustaining the rapidly growing population; however, they have also led to significant environmental pollution. Nitrogen (N)-fixing biofertilizers have emerged as an effective alternative or partial substitute for synthetic N fertilizers without compromising crop productivity. A two-year field experiment was conducted to evaluate the effect of biofertilizer on maize yield, N uptake, and N use efficiency (NUE). We compared maize crop yield, N uptake, and NUE after the application of synthetic fertilizer (SF), a liquid blend of 28% N with a sulfur additive (26-0-0-2: N-P-K-S), and the co-application of Pivot PROVEN\uae 40 as a biofertilizer and SF (SF+Bio). In 2022, fields 1 and 2 for each treatment received the same amount of total N, 205 kg ha 121. In 2023, fields 3 and 4 had total N rates of 229 kg ha 121 for SF and 268 kg ha 121 for SF+Bio. No significant differences were observed (p > 0.05) in maize yield and N uptake across all fields, with NUE being significant only in field 4. Maximum maize yields were 14.0, 13.8, 12.4, and 13.0 Mg ha 121 for fields 1, 2, 3, and 4, respectively. N uptake at R6 was 200, 195, 339, and 360 kg ha 121 for fields 1, 2, 3, and 4, respectively. The NUE values for fields 1, 2, and 3 were 0.99, 0.97, and 1.3, respectively. In field 4, the NUE for SF was 1.61, showing a 24% increase, while SF+Bio had an NUE of 1.3. Overall, substituting a portion of the SF with biofertilizer has positive implications. In the first year, it maintained yield, nitrogen uptake, and NUE, effectively promoting plant growth and development comparable to SF. In the second year, there was no benefit to increasing the N rate, suggesting that the substitution can consistently maintain yield and N uptake while maintaining NUE without the need for higher N inputs.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
FOSTERING KNOWLEDGE CO-PRODUCTION IN NATURAL RESOURCE MANAGEMENT AND INTEGRATION OF TRIBAL NATURAL RESOURCE MANAGEMENT IN FORESTRY CURRICULA
Get PDFThesis (Ph.D.)--Michigan State University. Forestry - Doctor of Philosophy, 2025An estimated 4,000 miles of Indigenous forestland share a border with US Forest Service lands alone, not including other agencies and organizations that border Indigenous lands (Dockry and Hoagland, 2017). These shared borders mean that forest management and stewardship may benefit from cross-boundary collaboration and communication. Without proper training in communicating with, understanding of, and general exposure to tribal entities, future foresters are not only at a disadvantage, but are inadequately prepared to work meaningfully with tribal partners. In addition to this, federal land managers now have a legal requirement to consult with tribes on forest management in these areas where cross-boundary stewardship is essential (Dockry & Hoag, 2017). This requirement is often difficult, because new foresters lack the background knowledge or respect for Indigenous ways of knowing (Verma et al., 2016). Outside of classes and programs specifically designed to teach about Indigenous knowledge and topics, these students and future foresters do not receive the education and training they need to work meaningfully with tribes. Few research studies have examined the prevalence of Indigenous knowledge in forestry curricula and how forestry education can incorporate Indigenous knowledge comprehensively and even fewer have explored the benefits that come with this integration and collaboration in educational settings. This collaboration can then help knowledge co-production between Indigenous and non-Indigenous natural resource managers. Knowledge co-production (KCP) is a process that requires a time investment and open-mindedness among the contributors. KCP combines Indigenous knowledge and Western science to create stronger management outcomes that address current environmental challenges facing the world (Kruijf et. al., 2020). With an increasing emphasis on KCP, particularly with underrepresented and historically marginalized communities, there is a demand placed upon communities to engage in research and knowledge co-production, by researchers and the entities that fund them. In the Great Lakes Watershed, there are 27 federally recognized tribal groups. These tribal communities are facing disproportionate impacts from climate change, such as sea-level rise and increase in intense weather changes (David-Chavez and Gavin, 2018). This work seeks to understand how tribes in the region are affected by and managing their natural resources, understanding their capacity for knowledge co-production, study capacity impacts of knowledge co-production, and if and how this knowledge is used in forestry curricula. From this study we found that the greatest concerns for tribes in the region are climate change and capacity, however there is a strong interest in knowledge co-production with some tribes already implementing some collaborative projects. We found that there are practical limitations to knowledge co-production and capacity is the central barrier. Preparing future forestry professionals to engage in meaningful knowledge co-production will not only require a deeper understanding of tribal resource management and co-stewardship approaches but may also require a fundamental shift in forestry education. A sample of U.S. undergraduate forestry curricula revealed that while there is interest in including more Indigenous knowledge in the future, most courses in forestry majors lack Indigenous knowledge inclusion. These results can help foster new conversations and changes that can encourage the inclusion of more Indigenous knowledge in forestry curricula and natural resource management more broadly.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
TEACHER AUTONOMY SUPPORT FOR YOUNG BEGINNERS\u2019 APP-BASED LANGUAGE LEARNING BEYOND THE CLASSROOM : A SELF-DETERMINATION THEORY PERSPECTIVE
Get PDFThesis (Ph.D.)--Michigan State University. Second Language Studies - Doctor of Philosophy, 2025With the importance of second language (L2) learning beyond the classroom (e.g., Reinders et al., 2022), language learning apps (e.g., Mango Languages, Duolingo) have shown potential for promoting self-directed L2 learning. Despite research indicating a positive relationship between the extent of in-app activities and L2 proficiency gains (e.g., Loewen et al., 2020), high attrition rates pose a significant challenge to this learning method in self-study contexts (Hwang et al., 2024). Thus, teacher support is crucial for developing learners\u2019 agency in their independent use of technology out of class (Godwin-Jones, 2019).In self-determination theory (SDT, Ryan & Deci, 2017; Noels et al. 2019a in L2 contexts), autonomy\u2014a fundamental human psychological need\u2014refers to a sense of volition and self-endorsement in one\u2019s action. When this need is satisfied, learners take ownership of their own learning and engage in activities out of interest and enjoyment. This, in turn, leads to greater learning success and well-being. In this dissertation, I explored how teachers can support L2 learners\u2019 autonomy need for app-based language learning out of class, thereby influencing their app engagement, app usage, and L2 learning. Particularly, the study examined the moderating role of learners\u2019 initial motivation for English learning in this process.Additionally, recognizing the potential influence of socio-ecological structures, I investigated the implementation of app-based language learning in South Korea\u2019s distinctive educational context. In South Korea, the high-stakes nature of English tests often leads learners to rely on hagwons\u2014for-profit, private educational institutions. Within this landscape, language learning apps are one of many resources available for English learning. Building on this, I explored whether learners\u2019 perceived opportunity cost of using language learning apps (i.e., the sense of sacrificing other valued learning activities to use apps) affects their out-of-class app usage, and how teacher autonomy support can help mitigate this perceived opportunity cost.Participants were seventh-grade beginner learners (N = 258) in South Korea. While learners independently used a commercially available language learning app over 13 weeks, their teachers provided Reeve and Cheon\u2019s (2021) autonomy-supportive instructional behaviors to enhance out-of-class app usage. Using questionnaires, I measured learners\u2019 (a) initial L2 motivation, (b) perceived teacher autonomy support, (c) autonomy need satisfaction, (d) app engagement (behavioral, emotional, cognitive, and agentic dimensions), and (e) perceived opportunity cost. Additionally, in-app usage and learning gain data were collected.Using structural equation modeling, I conducted mediation and moderated mediation analyses, revealing three key findings: (1) greater app usage positively predicted vocabulary learning gains; (2) teacher autonomy support indirectly increased app usage by enhancing autonomy need satisfaction and reducing perceived opportunity cost; and (3) teacher autonomy support was effective even for learners with controlled L2 motivation.These findings suggest that classroom-based autonomy support encourages L2 learners to use technology beyond the classroom and builds their resilience against disengagement from it, enabling sustained self-directed L2 learning. Pedagogical implications are discussed regarding the importance of creating a structured learning climate to ensure consistent and reliable teacher autonomy support.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
IODINE CYCLING IN MODERN AND ANCIENT MARINE OXYGEN DEPLETED ZONES : CONSTRAINTS FROM OBSERVATIONS, EARTH SYSTEM MODELING, AND EXPERIMENTS
Get PDFThesis (Ph.D.)--Michigan State University. Earth and Environmental Sciences \u2013 Doctor of Philosophy, 2025Iodine is a redox sensitive element that transforms between its two stable forms\u2014iodate (IO3-) and iodide (I-)\u2014depending on the redox state of the seawater. Because only the oxidized form of iodine, IO3-, in incorporated into the carbonate lattice that is precipitated from seawater, iodine to calcium (I/Ca) ratios in marine carbonates are therefore used as a paleoredox proxy. However, the current understanding towards mechanisms of IO3- redox transformations is limited, hindering redox interpretations based on the I/Ca proxy. The overall goal of this dissertation is to understand the redox cycling of iodine in marine low-O2 settings and hence provide insights for quantitative redox reconstruction based on secular variation of I/Ca records. Chapter 2 focuses on the iodine cycle in modern marine low-O2 settings. Samples were collected from two modern anoxic basins: the Baltic Sea and Siders Pond. Iodine speciation was measured, including IO3-, I-, dissolved organic iodine (DOI) and total dissolved iodine (TI) of these samples. IO3- was depleted in both the anoxic basins, and was even low within the surface layer where dissolved O2 was saturated. In addition, non-conservative features were observed throughout the water column. A significant I- flux from the sediments contributed to excessive iodine observed in the bottom of Siders Pond. In the Baltic Sea, net I- removal from the water column near the chemocline was observed. The causation of such I- removal requires further investigation. The decoupling of IO3- and O2 in relatively small water bodies in the surface anoxic basins indicates IO3- accumulation requires ventilation within the oxygenated open ocean waters. Chapter 3 calibrates the iodine cycle built into an Earth System model (cGENIE). Four processes were simulated: IO3- uptake and release of I- through the biological pump, the reduction in ambient IO3- to IO3- in the water column, and the re-oxidation of I- to IO3-. New I- oxidation and IO3- reduction parameters were incorporated into cGENIE. The model performance was evaluated against both modern and paleo-observations. The iodine cycle parameterizations optimized through model-data comparison replicates the general trends of iodine speciation gradients, including the zonal surface distribution, depth profiles, and oxygen-deficient zones (ODZs). The best-performing parameters were selected to simulate IO3- distribution in a Cretaceous model configuration as a case study. The broad match between the simulated IO3- and the carbonate I/Ca observation emphasizes the potential of using these parameters to interpreting and constraining redox variation in past oceans. Chapter 4 provides insights into the secular variation of marine IO3- through Earth history. Two approaches were conducted targeting understanding IO3- accumulation in seawater: (1) microbial IO3- reduction experiment under low but controlled O2, and (2) Earth System modelling. The model bacterial strain Shewanella oneidensis MR-1 started reducing IO3- when dissolved O2 in its medium decreased to 0.1\u3bcM. This O2 threshold provides the minimum estimate of dissolved O2 in association with the first appearance of IO3- accumulation in seawater during the Great Oxygenation Event (GOE). Earth system modelling indicates that IO3- accumulation in the surface ocean is a function of atmospheric O2 and ocean nutrient levels (PO4). A low I/Ca baseline in the Proterozoic could be best explained as the combined results of low atmospheric O2 (< 3% present atmospheric level, PAL) and low PO4 (< 10% present ocean level, POL). The transition of the low I/Ca baseline from the Proterozoic low levels to the modern-like values observed throughout the Paleozoic may require shifts in both oxygenation and nutrient availability. Together, this chapter demonstrates that changes in IO3- steady-state values through Earth history reflects fundamental changes in the Earth System, including O2 and other non-redox factors that have been previously overlooked.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references