EUPHOTIC IODATE PRODUCTION ALONG THE ALTANTIC MERIDIONAL TRANSECT By Kirsten Fentzke A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Geological Sciences – Master of Science 2024 ABSTRACT The oxidized iodine species, iodate, is the most pervasive form of iodine in well- oxygenated marine waters and can be tracked in carbonates as a paleo-redox proxy. Despite known marine spatial concentration variations in iodate and the reduced iodide today and temporal gradients across Earth history, the rates and mechanisms of iodate formation remain poorly understood. To quantify rates and pathways of iodine cycling, we performed ship-board tracer experiments in euphotic waters across a latitudinal transect with known gradients in iodine speciation—the Atlantic Meridional Transect spanning from the Falkland Islands to Southampton in the United Kingdom (UK) (45°S to 37°N) during March 2023. We collected samples for incubations and accompanying iodine speciation depth profiles (5-500 meters) from 11 stations along the transect. All incubation sets were spiked with radioactive 129I (t1/2 ~15.7 My) as iodide and were performed at two depths capturing the 7% and 1% light levels, thus tracking the deep chlorophyl maximum (DCM). Quantified rates varied with depth and location, with northern (spring) locales at 1% light showing the highest activity. Importantly, most locations exhibited no significant iodate production. Iodate formation from iodide is inferred from only one location based on increases in iodate 129I/127I ratios. At other locations, decreases in iodate 129I/127I ratios imply that alternative sources—likely the recycling of intermediates—are an important factor for iodate production. Ultimately, our survey reveals significant variability in iodate formation pathways in Atlantic euphotic waters, which have implications for improving models of iodine cycling and refining the paleo-redox proxy. Future research should focus on further elucidating mechanisms and explore seasonal and regional variations that drive iodine cycling dynamics in marine environments. TABLE OF CONTENTS INTRODUCTION ……………………………………………………………..…………..……..1 BACKGROUND …………………………………………………………………………..……..5 METHODS …………………………………………………………….……………………..…..9 RESULTS ………………………………………………………….…………………………….14 DISCUSSION ……………………………………………………….…………………………..28 CONCLUSION …………………………………………………………………..….…………..42 BIBLIOGRAPHY …...………………………………………………………..………..………..44 APPENDIX ………………………………………………………………………….....………..49 iii INTRODUCTION Iodine is the most abundant trace element in Earth’s oceans, and both influences and tracks the biogeochemical cycling of carbon and oxygen. For example, iodine is redox-sensitive, and partitioning between the reduced and oxidized endmember—iodide (I-) and iodate (IO3 -), respectively—tracks redox dynamics in global oxygen minimum zones. Exploiting this modern redox relationship, the abundance of iodine in carbonate rocks—which incorporate the oxidized iodate—has been used as proxy for reconstructing ancient oxygen availability across geologic time (Lu et al., 2010). In addition, marine phytoplankton both assimilate iodine and reduce iodate to iodide in euphotic waters (Hepach et al., 2020). The resulting assimilated iodine contributes to iodine biogeochemical cycling in sediments and the water column (Hepach et al., 2020). Iodide generated at the sea surface further interacts with and degrades tropospheric ozone and is a major component of atmospheric ozone cycling models (Carpenter et al., 2013; Chance et al., 2014; Luhar et al., 2017). Importantly, the formation and persistence of iodate, the most abundant and ubiquitous marine iodine species today, is an essential component for quantitative integration and application of iodine cycling within each of these fields; yet there are little-to-no observational constraints on iodate formation rates, pathways, and mechanisms, including spatiotemporal controls. This project seeks to address this knowledge gap by quantifying iodate formation rates and pathways in a diversity of marine settings across Atlantic Euphotic waters from the Falkland Islands to the UK (45°S to 37°N). While aspects of the iodine cycle are not well understood, the distribution patterns of marine iodine are well known. Primarily, iodine exists in two main forms: iodide and iodate, which are both dissolved and generally sum to 400-500 nM total iodine (Campos et al., 1996). Iodate comprises nearly 100% of total iodine outside of the ocean surface and marginal upwelling zones. Within these settings, iodine speciation showcases a dynamic distribution influenced by various environmental factors. First, iodate is reduced to iodide, often quantitatively, in oxygen-deficient or reducing conditions (Luther, 2023; Moriyasu et al., 2020; Wong & Brewer, 1977). Second, iodate reduction to iodide occurs in euphotic waters during primary production (Chance et al., 2014; Spokes & Liss, 1996). Importantly, while iodate still predominates in euphotic settings, iodide persists even under fully oxygenated conditions (Chance et al., 2014). This suggests that I- oxidation in marine waters is likely slow and not directly related to O2 (1.5-560 nM/yr) (Campos et al., 1996; Edwards & Truesdale, 1997; Hardisty et al., 2020; He et al., 2013; Hughes, et al., 1 2021; Luther, 2023; Truesdale et al., 2001; Žic & Branica, 2006). Importantly, while a trend of elevated euphotic iodide transitioning to nearly total iodate at depth can be seen globally, this trend is exacerbated in stratified low latitude settings (Chance et al., 2014). This suggests that, in addition to in situ cycling, seasonal mixing trends with underlying iodate-rich waters may also drive trends in euphotic iodine speciation. Iodine cycling thus involves several interrelated biological, chemical, and physical processes. A key iodine cycling process in euphotic waters is the conversion of iodate (IO₃⁻) to iodide (I⁻) by phytoplankton and bacteria (Hepach et al., 2020). In addition to the direct reduction of iodate, phytoplankton also assimilate iodine during their growth. This iodine is eventually released back into the marine environment when the phytoplankton die and decompose. However, some iodine appears to be absent when mass balance calculations are performed in these productive zones. This discrepancy can be partly explained by the temporary storage of iodine within the cells of phytoplankton, which is released upon their senescence and decay. This delayed release of iodine may account for the observed shortfall in these calculations (Hepach et al., 2020). While processes driving iodate reduction are better understood—both in oxic euphotic waters and oxygen deficient zones—there is uncertainty regarding the rates and pathways of iodate formation. Specifically, because iodate comprises nearly 100% of total iodine outside of the ocean surface and terrestrial and seafloor margins—where major internal and external fluxes of iodide are concentrated—the implication is that iodate production in the ocean is likely widespread. However, the redox disequilibria indicated from the long-term accumulation of iodide implies that iodide oxidation may be extremely slow, at least in some or most settings. Beyond potentially slow rates, another key inhibitor for quantifying iodate formation is uncertainty regarding the formation pathways and mechanisms. This knowledge gap limits our ability to replicate iodate production reactions in the lab or to target marine settings most likely to host such reactions. To date, there is some evidence that iodate production may be facilitated by some combination, but not likely exclusive to, reaction with reactive oxygen species (ROS), manganese, and during nitrification. ROS, such as superoxide (O₂⁻) and hydrogen peroxide (H₂O₂), can oxidize iodide (I⁻) to iodate (IO₃⁻) directly or indirectly via intermediate species like hypoiodous acid (HOI) and iodine monoxide (IO)(Luther, 2023). ROS production is often associated with biological activity, especially in surface waters where photosynthesis and respiration occur (Luther, 2023). Nitrification, a microbial process involving the oxidation of 2 ammonia (NH₃) to nitrite (NO₂⁻) and then to nitrate (NO₃⁻), may also indirectly contribute to iodate production (Hughes et al., 2021). Nitrate produced during nitrification can react with iodide, leading to the formation of iodate as a byproduct. While these pathways have been addressed in laboratory settings, they have not been demonstrated under ambient marine conditions. Directly observing these processes across an Atlantic transect will allow for deeper understanding of how and where iodate forms or its interactions within biogeochemical cycles. One implication of slow iodide oxidation rates is that mixing processes may play an important role in the distribution of iodine species in marine settings. Understanding how vertical mixing sources affect iodate/iodide distribution at the sea surface is crucial (Wadley et al., 2020). Horizontal and vertical mixing, driven by factors like wind, tides, and currents, can homogenize iodine concentrations within water masses (Wadley et al., 2020). Horizontal mixing occurs along oceanic currents and eddies, leading to the dispersal of iodine species over large spatial scales (Wadley et al., 2020). Vertical mixing, on the other hand, involves the exchange of water masses between different depths, impacting the vertical distribution of iodine (Chance et al., 2020). Vertical diffusion refers to the movement of substances, including iodine species, across vertical gradients in water properties such as temperature, salinity, and density. This process is driven by molecular diffusion and turbulent mixing, particularly near boundaries like the thermocline and halocline. Vertical diffusion can influence the transfer of iodine between surface and deeper waters, affecting speciation patterns (Qi et al., 2023). The combined effects of mixing and vertical diffusion have several implications for iodine speciation and distribution. Mixing processes can homogenize iodine concentrations horizontally, leading to relatively uniform distributions over large oceanic regions. However, vertical gradients in iodine speciation may still exist, especially near oceanic boundaries and transition zones (Moriyasu et al., 2020). Mixing and diffusion facilitate the transport of iodine species across oceanic regions, including lateral transport along current pathways and vertical transport across water column layers. This transport can influence the spatial variability of iodine concentrations and speciation. Vertical diffusion contributes to the establishment of vertical profiles of iodine species within the water column. For example, in regions with strong vertical gradients in biological activity or redox conditions, vertical diffusion can lead to distinct vertical distributions of iodide and iodate (Miwa et al., 2020). Changes in iodine speciation and distribution due to mixing and diffusion can impact marine ecosystems, including 3 phytoplankton communities that utilize iodine for metabolic processes. Vertical nutrient fluxes driven by mixing can also influence nutrient availability and primary production in surface waters. Recent research has quantified both iodide oxidation and iodate formation rates via novel tracer approaches. Specifically, recent studies have used a 129-iodine tracer approach in shipboard seawater incubations to track iodate formation rates from iodide and intermediates (Hardisty et al., 2020; Schnur et al., 2024; Ştreangă et al., 2023). Each of these studies focused on different regions and conditions, leading to unique findings. Hardisty et al. (2020) investigated the iodate formation rates in Martha’s Vineyard Sound, USA. Their results indicated that biological activity may catalyze iodate formation. In contrast, Schnur et al. (2024), conducted their study in the Sargasso Sea and did not observe iodate formation, which they attributed to lower biological activity and different chemical conditions. This study highlighted how regional variations in environmental factors such as temperature and nutrient availability can significantly influence iodine cycling. Ştreangă et al. (2023) focused on subtropical regions in the North Pacific Ocean, where they determined that intermediate iodine species may be particularly important in driving iodate formation. Importantly, each of these local studies had different observations, pointing to a need for large surveys to determine broader trends in the pathways of iodate production. To investigate large-scale trends in the pathways and rates of iodate production via iodide and intermediates, we performed shipboard 129I- radiotracer incubations under ambient seawater conditions during the Atlantic Meridional Transect (AMT-30) in February to March of 2023. With a half-life of ~15.7 Ma, 129I- is useful as a tracer on timescales of decades or less (Hardisty et al., 2020, 2021). This study aims to fill the knowledge gap in understanding iodine's chemical reactions and rates in seawater, which is crucial for marine science and has implications for the cycling of other essential elements like carbon, dissolved oxygen, and ozone. 4 BACKGROUND AMT-30 (Figure 1) and the broader AMT program offer a unique platform for studying iodine speciation, particularly iodate production, by combining extensive field observations, incubation experiments, tracer techniques, and a comprehensive multi-disciplinary approach. These efforts contribute to advancing our knowledge of marine biogeochemistry and its implications for global nutrient cycles (Aiken et al., 2000; Rees et al., 2015). By conducting sampling along a latitudinal gradient, the AMT-30 enables direct observation of changes in iodine speciation and production over large spatial and temporal scales. This latitudinal approach is crucial for understanding how oceanographic conditions, such as temperature, salinity, and nutrient availability, influence iodine dynamics. The AMT program has a long history of repeated expeditions, providing a valuable dataset with temporal continuity (Rees et al., 2015). Long-term observations allow for the detection of trends, seasonal variations, and a deeper understanding of how this study fits into the broader set of accumulated data. Spanning from high latitudes in the North Atlantic to low latitudes in the South Atlantic, the AMT covers a diverse range of marine environments. One of the significant contributions of the AMT program is the study by Aiken et al. (2009), which offers a decadal assessment of phytoplankton pigments and functional types across the Atlantic Ocean. Utilizing AMT data from 1995 to 2005, this study focused on the distribution and variability of phytoplankton communities, revealing significant spatial and temporal patterns. The research highlighted how different phytoplankton functional types and pigments varied across the Atlantic, with shifts linked to changes in oceanographic conditions and nutrient availability. This comprehensive assessment underscores the AMT’s role in providing long-term, high-resolution data essential for mapping key phytoplankton groups and elucidating their roles in ocean biogeochemical cycles. Picoplankton are dominant in oligotrophic waters, nanoplankton in mesotrophic waters, and microplankton in eutrophic waters. There was low inter-annual variability in total chlorophyll a across provinces, with some evidence of perturbations where cruise track differences were thought to be responsible for those changes (Aiken et al., 2009). This long-term perspective is crucial for understanding how phytoplankton dynamics are influenced by environmental changes and how these dynamics, in turn, affect marine ecosystems. Further advancing our understanding of oceanic processes, Aiken et al. (2017) synthesized data on the environmental responses of the North and South Atlantic Sub-Tropical Gyres over two 5 decades of AMT observations. This synthesis elucidates long-term trends in oceanographic conditions, such as temperature and nutrient concentrations, and their impacts on marine productivity and community structure. The paper reveals several key findings about the North and South Atlantic Sub-Tropical Gyres (NAG, SAG). AMT data define gyre boundaries, with low- velocity flow within the gyres and higher velocities at their edges. The surface layer is nutrient- depleted with low chlorophyll a (Chla) biomass, while the deeper chlorophyll maximum (DCM) is nutrient-replete but light-limited. Seasonal variations show surface Chla peaks in mid-winter due to the "Light Effect," and DCM Chla reaches its maximum in mid-summer but declines as sunlight decreases. Two modeling approaches extend remote sensing (RS) observations to greater depths and simulate seasonal cycles, addressing gaps in AMT sampling. Differences between the NAG and SAG include significant dust input in the NAG and varying trends in sea surface temperature and physical properties (Aiken et al., 2017). The study emphasizes the need for additional data from January and July and suggests that future research could benefit from expanding networks like Argo and bio-Argo for improved 3D visualizations and data coverage. The study underscores the value of continuous, long-term data in detecting subtle changes in oceanic conditions and in understanding the broader implications for marine biogeochemistry and ecosystem health. The efficiency of particulate organic carbon (POC) export and its transfer to the deep ocean has been another focal point of AMT research, as explored by Henson et al. (2012). This study investigates global patterns in the export of POC and its subsequent fate in the ocean interior. High- latitude regions with diatom dominance showed high export efficiency but low transfer efficiency, indicating labile organic matter, while low-latitude regions with effective microbial recycling had low export efficiency but high transfer efficiency, suggesting more refractory organic matter. The study concludes that ecosystem structure, rather than the presence of CaCO3, is the key factor controlling the efficiency of the biological carbon pump (Henson et al., 2012). The findings highlight the variability in carbon export efficiency across different regions of the Atlantic and emphasize the role of POC in the global carbon cycle. Understanding these patterns is critical for assessing the ocean's role in sequestering atmospheric CO2 and for evaluating the potential impacts of climate change on carbon cycling. Additionally, the role of micro-phytoplankton in photosynthesis, primary production, and potential export production has been addressed by Tilstone et al. (2017). Their research provides 6 detailed insights into how micro-phytoplankton contribute to primary production and nutrient cycling in the Atlantic Ocean. They found that micro-phytoplankton contributed about 30% to total primary production (PP) in the top 50 meters of the North Atlantic Drift (NADR) and North Atlantic Tropical (NATL) regions, but this contribution dropped to 15–30% in the West Tropical Atlantic (WTRA) and South Atlantic Tropical (SATL) regions. In the central NATL, the contribution was less than 15%, increasing to around 20% at the boundaries with SATL and WTRA (Tilstone et al., 2017). The study reveals the importance of different phytoplankton size classes in mediating carbon and nutrient fluxes, thereby influencing overall marine productivity and biogeochemical cycles. The AMT program's long-term observational data are invaluable for detecting seasonal variations and understanding the broader implications of marine biogeochemical processes. Henson (2014) emphasizes the significance of these long-term records in advancing our knowledge of ocean biogeochemistry and its interactions with global nutrient cycles. The ability to track trends and changes over extended periods is crucial for assessing the impacts of both natural variability and anthropogenic influences on marine systems. The AMT program provides a unique and comprehensive platform for studying marine biogeochemistry across a wide range of environmental conditions. The program's extensive spatial and temporal coverage enables researchers to investigate complex marine processes and their interactions with global nutrient cycles. Through the integration of field observations, experimental data, and long-term records, the AMT program continues to contribute valuable insights into the dynamics of marine ecosystems and their responses to environmental changes. 7 Figure 1. Surface chlorophyll values with select AMT-30 stations from February and March of 2023. 8 3.1 Sample Collection METHODS Seawater samples were collected via a CTD (Conductivity, Temperature, and Depth) rosette deployed on a cable to a maximum depth of 500 m during the AMT-30 transect cruise (Table 1). Depth profile samples from the solar noon CTD Niskin bottles were taken every three days at 11 of the 54 total stations, with 12 samples per cast (250mL each) ranging from 5m to 500m depth for a total of 132 samples for iodine speciation analysis along the transect. Samples were filtered to remove bacteria and other particles through 0.2μm filters with 0.8μm pre-filters (AcropakTM 1500 Supor Capsule, Pall Corporation) using a Masterflex pump and then placed into opaque 60mL bottles and frozen at -20°C (Campos et al., 1996; Moriyasu et al., 2023). Additionally, larger volume samples (1-3L) were collected from depths corresponding to light levels of 7% and 1% (DCM). The iodine isotope (129I-) spike was added to the larger volume first to homogenize the iodine speciation and respective isotope ratio before aliquoting into replicates. The larger volumes were spiked to a concentration of 70nM 129I- solution (t1/2 = 15.7 My) (Eckert and Ziegler Isotope Products©) (Hardisty et al., 2020, 2021; Schnur et al., 2024). Notably, the isotope spike included a NaI carrier, which included 127I-, so total I- added was approximately 140 nM (129I/127I of I- ~1). Similar to previous analogous applications (Hardisty et al., 2020, 2021; Schnur et al., 2024; Ştreangă et al., 2023), there is also a small amount of 129IO3 -, which allows for isotopic ratio analyses of the t0 timepoints for iodate and then subsequent changes can be interpreted to reflect in situ processes. Each spiked carboy was split into triplicate 250mL incubations (Hardisty et al., 2020b). Incubations occurred within on-deck flow-through incubators with screens replicating the light levels of the sample depths. Samples for t0 were immediately subsampled after adding the spike. All subsamples were filtered at 0.2μm to end interaction with biology, put into amber high-density polyethylene (HDPE) Nalgene bottles, and frozen at -20°C. All (t0, t1, t2) subsamples were ~60 ml. Subsamples of 60mL were taken after 1.5-3 days. Incubation conditions were monitored for pH and taxonomic analysis onboard. All taxonomic analysis were conducted on board by Glen Tarran from Plymouth Marine Laboratory (Rees, 2023; Tarran et al., 2006). All samples were stored frozen (at -20°C) until analysis at Michigan State University. 9 3.2 Spectrophotometry Iodate concentrations from select depth profiles were quantified using a technique for spectrophotometric measurement of iodate adapted from Jickells et al., (1988). This method involves reacting seawater iodate with an excess of potassium iodide (KI) and sulfamic acid, which generates triiodide (I3 -) in a reaction specific to iodate. Potassium iodate is known to degrade quickly over time; therefore, a fresh 10% KI solution was prepared daily for analysis. Sample intensity at specific wavelengths was recorded by a VWR 3100 PC UV-Vis Scanning Spectrophotometer equipped with UV-Vis Analyst software. Reusable Fisherbrand® Semi-Micro Quartz Cuvettes (Cat. No. 14-958-126) with a 10 mm path length were utilized for visible range (200-2500 nm) measurements. The triiodide product that is quantified via this reaction sequence exhibits a characteristic absorption spectrum with a trough around 320 nm, a peak at 350 nm, and a secondary trough at 400 nm. The iodate concentration (nM IO3 -) was calculated from these spectral features using the equation: 𝑛𝑀𝐼𝑂3− = (𝐴(𝐼𝑂3 −)~320 + 𝐴(𝐼𝑂3 −)350 − (𝐴(𝐼𝑂3 2 −)400) × 𝑚𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑐𝑢𝑟𝑣𝑒 The 𝑚𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑐𝑢𝑟𝑣𝑒 variable represents the slope of a calibration curve generated from -) standards that were created using iodate additions to seawater over a potassium iodate (KIO3 range of 0-500nM. This approach, based on the specific reaction of iodate with iodide under acidic conditions to form triiodide, enabled precise quantification of iodate concentrations in these samples. 3.3 ICPMS Concentration Analysis (Column Chromatography) An established ion-exchange chromatography protocol was employed to separate iodide (I- ), iodate (IO3 -), and dissolved organic iodine (DOI) species from natural seawater samples for measurement of their concentration in AMT-30 samples from the 7% and 1% light depths (Hardisty et al., 2020, 2021; Hou et al., 1999, 2001, 2007, 2009; Moriyasu et al., 2023; Wong & Brewer, 1977). The iodide fractions were analyzed via triple-quad inductively coupled mass spectrometry (ICP-MS-TQ) to quantify iodine concentrations, as previous studies have demonstrated near- complete (~100%) recovery yields (Hardisty et al., 2020). Subsequently, these fractions were 10 measured for 129I/127I isotope ratios using multicolletor inductively coupled mass spectrometry (MC-ICP-MS). Iodate recovery yields have been shown to typically range from 90-95% (Hou et al., 1999, 2001, 2007, 2009), which is confirmed in this work as well. While this does not impact our isotope analyses, we recognize that low yields could contribute to uncertainty between triplicates for iodate concentration measurements made from this fraction for our incubations. The iodine speciation was conducted using glass columns packed with PYREX glass wool and 1 mL of AG1-X8 resin, which were pre-cleaned to eliminate residual iodine before sample processing. Cleaning was performed by replacing seawater samples with 18.2 MΩ·cm water within a full ion chromatography separation procedure. Approximately 20 mL of each seawater sample, measured gravimetrically, was used for chromatographic separation. Iodide was eluted from the seawater matrix after iodate and DOI were released from the resin. Iodate and DOI were collected independently, but DOI was not measured. The iodate fraction was then reduced to iodide using concentrated hydrochloric acid (HCl) and 0.3 M sodium bisulfite (NaHSO₃), following the methods outlined by Hardisty et al. (2020), Hou et al. (1999, 2009), Reifenhäuser & Heumann (1990), and Schnur et al. (2024). After an overnight reduction, these fractions underwent a second round of chromatography on cleaned resin for iodide elution using an 18% TMAH/2 M HNO₃ eluent. The masses of the eluent and samples were measured gravimetrically to facilitate concentration calculations. For quality control, a 200 ppb iodide solution (diluted from a 1000 ± 4 μg/mL iodide standard in 1% tetraethylammonium (TEA) for iodide or dissolved solid KIO₃ in 18.2 MΩ·cm water for iodate was processed through the columns alongside the samples to assess elution efficiency and yield. Two 18.2 MΩ·cm water blanks were included for each column set to check for contamination, and at least one replicate sample was processed in each column set to evaluate reproducibility. Iodide concentrations [127I⁻] were measured using a Thermoscientific iCap triple- quad inductively coupled plasma mass spectrometer (ICP-MS-TQ) with Qtegra software version 2.10.3324.131, in both single-quad (SQ) and triple-quad (TQ) modes with O₂ reaction cell gas as outlined in Schnur et al. (2024). A Teledyne ASX 520 autosampler was used for sample introduction. Eluent was diluted with samples at 1:20 or 1:40 for subsequent ICP-MS analysis. The same matrix was used for ICP-MS rinse solutions. Data correction was performed using internal standards (In, Rh, and Cs) from Inorganic Ventures©. Calibration curves and column standards were based on a 1000 ± 4 μg/mL iodide standard in 1% TEA (Schnur et al., 2024). 11 3.4 Multi-Collector ICPMS (Sparge Technique) Iodine isotope ratios (129I/127I) were analyzed at the Woods Hole Oceanographic Institution (WHOI) using a ThermoFinnegan Neptune MC-ICP-MS, following the method outlined in Hardisty et al. (2020) and Schnur et al. (2024). These measurements were performed on splits from the column chromatography used for ICPMS concentration analysis. Each day before sample analyses were performed, the instrument was tuned to maximize beam intensity for accuracy of the instrument. The mass spectrometer was set to monitor specific ion beams with mass/charge ratios (m/z) corresponding to Te (126, 128, 130), Xe (126, 128, 129, 130, 131, 132), 132Ba, and 127I and 129I (Hardisty et al., 2020). The latter isotopes (127I and 129I) were detected by Faraday cups L3-L1 and H1-H3, with m/z 129 centered. Mass bias corrections were applied using a 500 ppb Te solution (Inorganic Ventures©), and potential isobaric interferences were tracked by monitoring 131Xe over the course of sample analysis. Iodine samples were introduced into the instrument using a gas-based "sparge" method with desolvation prior to the samples entering the instrument. A 300 μL/min quartz nebulizer was used to introduce the Ar carrier gas and Te solution, in conjunction with a standard sample cone and x-type skimmer cone (Hardisty et al., 2020, 2021). Samples (≤6 ml) were held in 30 ml Teflon vials fitted with pre-made "sparge caps" to allow for Ar gas flow through the vial. These vials were cleaned with 50% nitric acid at 90°C for >3 hours, rinsed with 18.2 MΩ·cm water, and air-dried in a hood before reuse. To avoid contamination, tubing connecting the sparge caps to the Neptune intake was replaced after each use in between samples. Before connecting a sample vial to the torch, the Ar gas flow rate was reduced to ~0.1 L min-1 and the sample was purged with Ar for 1 minute. The gas flow was then increased to ~1.2 L min-1 after connection. The Te signal was monitored until it stabilized (3-7 V), at which point the sample run was initiated. To induce iodine volatilization, 4 ml of concentrated 70% HNO3 was injected upstream of the sample vial. The total volume of nitric acid and iodine eluent was kept <10 ml to prevent bubbling over and potential sample introduction into the torch. The collected data was corrected according to (Hardisty et al., 2020) to yield a final 129I/127I ratio and paired standard deviation (Schnur et al., 2024). 12 Table 1. Table of samples collected during AMT-30. AMT-30 Station Numbers 54 54 48 48 42 42 41 41 35 35 30 30 24 24 19 19 13 13 7 7 2 2 Light Percentage 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% 7% 1% Depth (m) 20 25 55 112 50 85 40 60 40 65 90 110 100 155 75 105 60 105 30 55 15 30 Longitude -18.766899 -18.766899 -23.666847 -23.666847 -24.983574 -24.983574 -25.283462 -25.283462 -25.366844 -25.366844 -25.150113 -25.150113 -25.05022 -25.05022 -24.516787 -24.516787 -33.333398 -33.333398 -42.750142 -42.750142 -47.816875 -47.816875 Depth Profile Samples Collected Total Samples Collected Latitude 37.783555 37.783555 29.266756 29.266756 20.683592 20.683592 10.416763 10.416763 0.916885 0.916885 -8.733511 -8.733511 -18.01677 -18.01677 -27.300227 -27.300227 -33.26678 -33.26678 -38.45003 -38.45003 -45.500052 -45.500052 13 Samples Collected 6 6 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 132 324 RESULTS Over the course of the six-week cruise transect, variations in temperature (degrees Celsius), oxygen (μmol/kg), and fluorescence (μg/L) were observed via CTD (Figure 2). The fluorescence tracks the concentration of photosynthetic material at the base of the euphotic zone along the transect, known as the Deep Chlorophyll Maximum (DCM), which is defined here as the depth at which light has attenuated to only 1% of surface incidence. The DCM shifted in depth across the transect, being shallower at higher latitudes and deeper near the equator. The temperature plots closely followed the trends of the DCM, with higher temperatures reaching deeper into the water column near the equator and cooler temperatures at higher latitudes. The oxygen plot was homogeneous at higher latitudes in the upper 500 meters, with slightly lower oxygen concentrations near the equator associated with an oxygen deficient zone off the coast of Africa (Figure 2). Iodide depth profile plots followed a similar trend across the transect, with decreased concentrations of iodide at higher latitudes (40-15 degrees S/N) and a shift to lower values near the equator. At lower latitudes, iodide persisted deeper into the water column. These depth profiles resembled previous studies of euphotic waters, with iodide accumulation at the top of the profile decreasing with depth, while iodate increased with depth (Figure 2) (Chance et al., 2020; Moriyasu et al., 2023). The iodate isotope ratios for the incubation are shown in Figures 3 and 4. The solid line shows the average value of the initial (t0) triplicate samples measured. The dashed line shows one standard deviation above and below this average (Tables 2 and 3). For each incubation statistical test (t-test) was performed between each of the initial and final triplicate ratio values to establish statistical significance between t0 and tfinal timepoints. If the value calculated by the t-test was greater than 0.05 the significant difference between the mean of tinitial and tfinal values the timepoints are not statistically different, implying no changes across the incubation. Conversely if the t-test values were less than 0.05 the timepoints are statistically different, implying changes across the incubation. Overall, substantial variability in iodate 129I/127I ratios was observed across the AMT-30 transect, with the northern portion exhibiting the most pronounced fluctuations. This pattern overlaps with the northern hemisphere's spring season, suggesting potential seasonal influences on iodate formation dynamics. Within this context, three types of trends were observed: 1.) a lack of 14 129I/127I of iodate variability between t0 and subsequent samples; 2.) increase in 129I/127I of iodate between t0 and subsequent samples; 3.) decrease in 129I/127I of iodate between t0 and subsequent samples. The majority of the 22 incubations exhibited no statistical significance between time points, 17 incubations show no changes between timepoints. An example of no variability is station 7 at 7% light (Figure 3). The 7% light level at Station 35 is the only example of a statistically significant positive shift. Several incubations exhibit a negative shift between the initial and final timepoints. Station 35, 41, 42, and 48 at the 1% light level show this significant decrease in the 129I/127I iodate between timepoints (Figure 4). The same t-tests approach was used to determine changes in iodate and iodide isotope ratios (Figures 3, 4, 5, and 6) as well as the concentrations of iodate and iodide (Figures 7, 8, 9, and 10) during the incubations. These t-test results of all incubations are summarized in Tables 2 and 3. With the exception of Station 48 at the 1% light level, stations with statistically significant changes in the 129I/127I of iodate also had statistically significant changes in some combination of iodide 129I/127I and iodate and iodide concentration. Iodide 129I/127I ratios across both light depths generally did not change significantly, with only two negative shifts observed between time points at stations 35 (7%) and 7 (1%). Speciation concentrations of iodate and iodide remained consistent overall, although smaller variations were noted between the 1% and 7% light depths. Statistically significant changes in iodate concentrations were observed at the 1% light depth for Stations 30, 35, and 42, based on calculated t-test values (Figure 8). Stations 30 and 35 showed a decrease in iodate concentration between the initial and final timepoints, while Station 42 exhibited an increase (Figure 8). In contrast, only Station 7 at the 1% light depth showed a statistically significant decrease in iodide concentrations between timepoints. At the 7% light level, no statistically significant changes were detected in either iodate or iodide concentrations between the initial and final timepoints (Figures 3, 4, and 6). The taxonomic analyses of the incubation experiments reveal that species counts remained relatively stable across all three timepoints via flow cytometry (Figure 11). While the overall populations did decrease over time, this decline is within the expected range for die-off typically observed during shipboard incubations, where removing seawater from its in-situ environment onto the ship can induce some stress on the organisms (Karl & Dore, 2001; Veldhuis & Timmermans, 2007). Despite this, the consistency in species counts suggests that the community 15 structure did not undergo any significant shifts, indicating a relatively stable taxonomic composition throughout the incubation period. 16 Figure 2. Ocean Data View plots of the AMT-30 transect from top to bottom: fluorescence (ug/L), temperature (degrees Celsius), oxygen (μmol/kg), iodide (nM), and iodate (nM). 17 Table 2. Table summarizing the results of the changes in iodate and iodide isotope ratios as well as iodate and iodide concentrations from the 7% light level between the initial and final timepoints using a t-test. A “0” means no discernable change, “+” is a positive shift, and “n/a” is not available due to insufficient data being available for that station. 7% Light Table Station Number 54 48 42 41 35 30 24 19 13 7 2 Iodate Isotope Ratio 0 0 0 0 + 0 0 0 0 0 0 Iodide Isotope Ratio 0 n/a n/a n/a - n/a n/a n/a 0 0 0 Iodate Concentration (nM) Iodide Concentration (nM) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Table 3. Table summarizing the results of the changes in iodate and iodide isotope ratios as well as iodate and iodide concentrations from the 1% light level between the initial and final timepoints using a t-test. A “0” means no discernable change, “+” is a positive shift, “-” is a negative shift, and “n/a” is not available due to insufficient data being available for that station. 1% Light Table Station Number 54 48 42 41 35 30 24 19 13 7 2 Iodate Isotope Ratio 0 - - - - 0 0 0 0 0 0 Iodide Isotope Ratio 0 0 0 n/a 0 n/a 0 n/a n/a - n/a Iodate Concentration (nM) Iodide Concentration (nM) 0 0 0 + 0 0 0 0 0 - 0 0 0 + 0 - - 0 0 0 0 0 18 Figure 3. Plots of iodate isotope ratios from 11 stations (54 to 2) from the 7% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value placed in the corner of each plot is the calculated p value from the performed t-tests. 19 Figure 4. Plots of iodate isotope ratios from 11 stations (54 to 2) from the 1% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value placed in the corner of each plot is the calculated p value from the performed t-tests. 20 Figure 5. Plots of iodide isotope ratios from 3 stations (35, 13, 7, and 2) from the 7% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value in the upper right corner of each plot is the calculated p value from the performed t-tests. 21 Figure 6. Plots of iodide isotope ratios from 5 stations (54, 48, 42, 35, 24, and 7) from the 1% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value placed in the corner of each plot is the calculated p value from the performed t-tests. 22 Figure 7. Plots of iodate concentrations from 11 stations (54 to 2) from the 7% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value in the upper right corner of each plot is the calculated p value from the performed t-tests. 23 Figure 8. Plots of iodate concentrations from 11 stations (54 to 2) from the 1% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value in the upper right corner of each plot is the calculated p value from the performed t-tests. 24 Figure 9. Plots of iodide concentrations from 11 stations (54 to 2) from the 7% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The decimal in the upper right corner of each plot is the calculated p value from the performed t-tests. 25 Figure 10. Plots of iodide concentrations from 11 stations (54 to 2) from the 1% light depth. Each plot includes every available timepoint as well as the initial average, calculated from the average of the triplicate timepoint collected at t0 (0 hours), marked by the solid black line and one standard deviation above and below the average (dotted blue line). The value in the upper right corner of each plot is the calculated p value from the performed t-tests. 26 Figure 11. Plot A: taxonomic analysis of shipboard incubations over time at the 7% light percentage for station 35, which showed significant iodate isotopic changes between the initial and final timepoints. Plot B: taxonomic analysis of shipboard incubations over time at the 1% light percentage for stations 35 and 42, that showed significant isotopic changes between the initial and final timepoints. Syn is Synechococcus sp. Cyanobacteria, Pro is Prochlorococcus sp. Cyanobacteria, Peuk is Nanoeukaryote phytoplankton (approx. 2-12µm), Cocco is Coccolithophores, Cryp is Cryptophytes, HNA bac is Relatively High Nucleic Acid-containing bacteria, LNA bac is Relatively Low Nucleic Acid- containing bacteria. is Picoeukaryote phytoplankton (<2µm), Nano 27 DISCUSSION The AMT-30 transect provides a unique opportunity to explore the variability and mechanisms of iodate production across different latitudinal and light regimes in the Atlantic Ocean. Our findings indicate that variability in iodine speciation and cycling is pervasive across the transect. This includes some regions with more active iodine cycling. For example, iodate production is notably enhanced at the 1% light level and at locations north of the equator sampled during boreal spring. Further, our observations highlight differences in rates and pathways of iodate production between regions. In the following sections we address these differences in pathways, the broader changes in iodine across the transect, and how this affects calculated rates of iodide oxidation. 5.1 Changes in Iodine Speciation Across the Transect The analysis of iodine concentrations during the six-week transect of the Atlantic Meridional Transect (AMT-30) reveals significant spatial variations, both in depth and across latitude. A clear gradient in iodide concentrations was observed, with lower levels at higher latitudes (40-15° N and S) and a marked increase as the transect approached the equator. Specifically, iodide concentrations at higher latitudes were consistently at least 25% lower compared to those observed near the equator. Iodide concentrations also decreased with depth, ranging from 100 nM at the surface to approximately <10 nM at depths below 500 meters, which is consistent with the findings of Bluhm et al. (2010), who observed similar depth profiles in the Atlantic. The accumulation of iodate in deeper waters reflects its greater overall stability compared to iodide and underscores the influence of physical processes on iodine speciation (Wong et al., 2002). Truesdale et al., (2000) measured surface iodate concentrations from the AMT. They revealed a similar pattern in iodate concentration to what is seen in previous studies with latitude: elevated iodate at high latitudes and lower values at low latitudes. The initial iodate concentrations from our incubations at the 7% and 1% light levels reveal this same pattern (Figures 7 and 8). Our measured latitudinal iodide distribution pattern is antithetical to the iodate pattern, which is consistent with other studies. Notably, however, the iodate concentrations from our depth profiles show much more variability and do not match this pattern. This is likely due to methodological differences. The iodate concentrations from incubations were measured via column 28 chromatography and ICPMS while the iodate from depth profiles were measured via spectrophotometry. The spectrophotometric method is known to have interferences, which can maintain precision but offset accuracy (e.g., Jones et al., 2023). Notably, the iodate concentration measurement via column chromatography and ICPMS can also have low yields (Hou et al., 2009; Wong & Brewer, 1977), which likely accounts for the lower precision in our triplicate time points from the incubations. For these reasons, we suggest that, until further investigation, iodate variations in the depth profiles measured via spectrophotometry may represent an analytical artefact. Alternatively, differences in iodate concentrations may be attributed to the time frames of each study. The AMT-30 collected data from February 2023 through March 2023 while the data examined in Truesdale 2000 was collected between September and October of 1996 (AMT-3) and April through May of 1997 (AMT-4). This shift in time frames could account for seasonal changes in the availability of nutrients at locations along the transect, seasonality changes impacting bioactivity in the observed regions, or physical dynamics such as vertical diffusion and stratification effects (Truesdale et al., 2000). The transect passed by and edged along the oxygen-deficient zone (ODZ) off the coast of Africa (Figure 2). However, despite the proximity to the ODZ, the data indicate no clear trend of iodate reduction to iodide in this region. Therefore, while ODZ’s are known locations of high iodide (Hardisty et al., 2021; Luther, 2023; Moriyasu et al., 2020), the ODZ does not play a meaningful role in the processes examined in this study. The deep chlorophyll maximum (DCM), a key feature in marine ecosystems, was tracked along the transect using fluorescence as a proxy, as fluorescence is strongly correlated with high phytoplankton concentrations and elevated primary productivity in surface waters. The DCM typically occurs at depths where light availability begins to decrease but nutrient concentrations remain sufficient to sustain phytoplankton growth (usually at 1-3% light percentage), resulting in a peak in chlorophyll concentrations (Moriyasu et al., 2023). This zone of heightened primary productivity plays a critical role in biogeochemical cycles, including the marine iodine cycle. Phytoplankton activity within the DCM has been shown to influence iodine speciation, particularly through enhanced reduction of iodate to iodide (Truesdale et al., 2000), which directly affects the spatial distribution of iodine species. 29 As the transect approached the equator, areas of high iodide concentrations were found to correlate with regions of elevated temperature and were positioned just above the DCM. This observation aligns with findings by Truesdale et al. (2000), who reported similar relationships between iodide concentrations and the DCM in the Atlantic. Further supporting this, studies in other parts of the Atlantic have demonstrated that areas with higher chlorophyll concentrations are typically associated with higher iodide levels and more active iodate oxidation (Moriyasu et al., 2023). This relationship between fluorescence, chlorophyll, and iodide concentration becomes particularly pronounced at light levels around 1%, where the iodine cycle appears more dynamic due to elevated biological activity and chlorophyll presence. Tracking the DCM along the transect provided a valuable indicator of primary productivity and allowed for better understanding of iodine speciation patterns in the Atlantic Ocean. The correlation between DCM features, such as high fluorescence and chlorophyll concentrations, and the distribution of iodine species suggests that the biological processes within the DCM significantly impact the cycling of iodine. This reflects the broader influence of biological productivity on marine iodine cycling, highlighting the importance of the DCM as a zone where the iodine cycle is actively shaped by biotic factors. Hughes et al. (2021) demonstrated in lab cultures that ammonia oxidation, which is typically near or coincident with the DCM, can play a significant role in the iodine cycle. Their experimental work showed that ammonia-oxidizing microorganisms can oxidize iodide to iodate under controlled conditions. This finding highlights a direct biochemical pathway for iodine transformations in the presence of ammonia oxidation, suggesting that microbial activity influences iodine speciation at deeper light levels. Our shipboard incubations at the DCM provide a test to this hypothesis under ambient conditions. These observations underscore the complex interplay of physical, chemical, and biological processes that govern iodine cycling in the upper ocean. The variability in iodate and iodide distributions, particularly within the dynamic 1% light level, highlights the intricate mechanisms at work in different marine environments. Understanding these patterns is essential for unraveling the broader implications of iodine's role in ocean biogeochemistry. 5.2 Iodate formation pathways in shipboard incubations In analyzing the changes in iodate isotope ratios across the Atlantic transect during AMT- 30, we categorized the observed patterns into three distinct groups based on the results of t-tests 30 conducted between the initial and final timepoints. To determine statistical significance, we employed a t-test with a threshold p-value of 0.05, where changes were considered statistically insignificant if the p-value exceeded 0.05, and significant if the p-value was below this threshold. Category 1 includes stations where no discernible change in iodate ratios were detected between the initial and final timepoints. This observation aligns with findings from Schnur et al. (2024), who reported similar stability in iodate 129I/127I. In our study, stations 2-30 and 54 at the 1% light level (Figure 4) and stations 2-30 and 41-54 at the 7% light level (Figure 3) displayed no significant differences, suggesting consistent conditions in these regions. Category 2 consists of stations that exhibited a significant positive shift in iodate isotope ratios. Our results show a notable increase at station 35 at the 7% light level (Figure 3). These results are similar to findings from Hardisty et al. (2020), who also observed a positive shift in iodate isotope ratios in their comparable study. Category 3 captures stations where a significant negative shift in iodate isotope ratios was observed. In our study, stations 35, 41, 42, and 48 at the 1% light level (Figure 4) showed a decrease in iodate isotope ratios between the initial and final timepoints. These findings are comparable to those reported by Ştreangă et al. (2023), who also identified negative shifts in iodate isotope ratios in an incubation of surface water in their work. Overall, the most dynamic changes in iodate isotope ratios during AMT-30 were observed at the 1% light level, particularly in the northern portion of the transect, encompassing stations 35-48. The majority of our locations fall within Category 1, with a lack of significant changes in iodate isotope ratios over time at various light levels and stations. A similar finding was observed from similar iodine-129 tracer incubations from (Schnur et al., 2024). In their examination of iodine speciation and isotope ratio changes in incubations from two depths in the Sargasso Sea, Schnur and others (2024) reported no significant variation in [IO3 -] and [I-] concentrations and their isotope ratios over time. This finding is consistent with slow oxidation rates and other studies providing evidence that iodine redox species in surface waters tend to remain stable, at least over short time periods (Hou et al., 2001). This stability is evident in our data, particularly at stations 2-30 and 54 (Figure 3) and stations 2-30 and 41-54 (Figure 4), where iodate isotope ratios at both the 7% and 1% light levels show no significant change. An example from our data that illustrates this stability can be seen at Station 2 (Figure 3). At the 7% light level, the initial timepoint average for the three samples was 0.0069±0.00029, which only slightly increased to 0.0081±0.00068 at the final timepoint. The t-test value of 0.23 further supports the conclusion that this change is not 31 statistically significant. Similarly, at the 1% light level from this same station, the initial timepoint average of 0.0065±0.00035 increased to 0.0071±0.000423, with a t-test value of 0.17, again indicating no significant change. We cannot rule out that iodine cycling is active at these sites, but beyond the temporal, spatial, or analytical resolution of our experiments. Specifically, the lack of significant changes in isotope ratios in incubations from these stations may indicate that the iodine cycling is temporally punctuated (e.g., seasonal) during periods not sampled here. Alternatively, other euphotic depths not evaluated here could be important loci of iodine redox reactions. The importance of specific depths and associated conditions is evident from our comparison of 7% and 1% light levels. Lastly, iodate production may be occurring, but at rates slower than the resolution of our tracer approach. This possibility and our upper constraints on rates are discussed in detail in the next section. Regardless, however, slow or temporally isolated iodate production in the majority of our studied sites and depths is consistent with local and regional mixing processes playing an important role in regulating local iodine speciation (Chance et al., 2010; Luther, 2023; Moriyasu et al., 2020; Truesdale et al., 2000; Wadley et al., 2020). For Category 2, the observed positive shift in iodate isotope ratios—particularly at Station 35 (Figure 3)—specifically implies a role of iodide in the production of iodate. This shift is consistent with trends reported by Hardisty et al. (2020), where similar positive changes in iodate isotope ratios were interpreted as indicative of enhanced oxidative processes. Specifically, at the 7% light level, the average iodate 129I/127I ratio increased from 0.014±0.00059 at the initial timepoint to 0.016±0.00041 at the final timepoint, with a t-test value of 0.017 supporting the statistical significance of this shift. Since iodide is the iodine species from which the tracer is mostly composed of, such a change implies a net oxidation of iodide to iodate, potentially driven by biological or photochemical processes. This same observation was made from unfiltered incubations from surface seawater from Martha’s Vineyard Sound (Hardisty et al., 2020). Importantly, that study and the North Pacific study (Ştreangă et al., 2023) combined the iodate fraction with another fraction which has been interpreted in other studies as hosting dissolved organic iodine (Hughes et al., 2021), which provides some ambiguity as to whether iodate or iodine intermediate formation contributed to changes in iodine isotope ratios in those studies. In our study, we isolated these 2 fractions and focused on the iodate fraction specifically in order to avoid ambiguity regarding the formation of iodate from iodide. As such, our observation of increased 32 iodate 129I/127I ratios provides strong, and among the first, direct observations of iodate production from iodide in a normal marine setting. At this same location (Station 35 at 7%) the iodide 129I/127I decrease between the average initial (0.31±0.00011) and average final (0.31±0.00016) timepoints with a calculated p-value of 0.010. This change in iodide (difference in iodide: 0.0017) is notable but less distinct compared to the iodate 129I/127I ratios (difference in iodate: 0.0020) from this same station and light depth. Together, these suggests that iodate reduction and formation were occurring simultaneously. Another observed increasing trend in the iodate 129I/127I between the initial and final timepoints is Station 7 at the 1% light level. Although the p-value for the performed t-test is 0.06 which is just on the cusp of statistical significance (p≤0.05). At Station 7, sampled at the 1% light level, the iodate isotope ratio (129I/127I) exhibited a notable change over time first decreasing then increasing overall. The initial decrease in the ratio between t0 and t1 was not statistically significant (p = 0.12). However, the comparison between the middle and final timepoints (t1 and tf) yielded a p-value of 0.034, indicating a statistically significant increase. This suggests a potential conversion of iodide to iodate. Conversely, the iodide 129I/127I ratio decreased, with a p-value of 0.041 indicating a statistically significant decrease over the course of the incubation. The observed decrease followed by an increase in iodate isotope ratios at Station 7 (1%) suggests dynamic iodate formation pathways, with intermediates potentially playing a significant role before complete conversion. Similar inferences were made by Ştreangă et al. (2023) based on internal changes in iodate isotope ratios in unfiltered incubations. Additionally, the decrease in iodide isotope ratios points to potential iodate reduction and iodide oxidation during the experiment. The final observed pattern from our data, Category 3, reveals a significant negative shift in iodate isotope ratios over time in 4 out of 22 of the stations/depth evaluated here. The same observation was made in Ştreangă et al. (2023) in their iodine-129 tracer incubation from North Pacific surface water. Our study identified a marked decline in iodate isotope ratios at Stations 35, 41, 42, and 48, all at the 1% light level, (Figure 5). For example, at Station 42, the iodate 129I/127I ratio decreased from an average of 0.016±0.00037 at the initial timepoint to 0.0079±0.00070 at the final timepoint, with a t-test value of 0.0011 indicating a statistically significant change. Importantly, at Station 42 (1% light level) a statistically significant increase in the iodate concentrations was also observed, providing additional evidence of iodate production (Figure 4). 33 Importantly, a decrease in the iodate isotope ratio requires iodate formation rates to be highest from a source other than the iodide-129 tracer (i.e., a source dominated by iodine-127). This implies a likely role of iodine intermediates in the formation of iodate. It is possible that iodide is part of the pathway, but that the rates of iodide oxidation to the required intermediates are slower than the subsequent oxidation of intermediates to iodate, thus diluting any isotopic signal from iodide. Our study did not include controls to isolate specific reaction mechanisms or pathways, but the study of Ştreangă et al. (2023) —which made a similar observation—did include controls. Specifically, Ştreangă et al. (2023) observed a lack of significant changes in iodate isotope ratios in filtered controls, pointing to the possibility that microorganisms excluded during filtering (0.2 µm) catalyzed the reaction. Further, thermodynamic calculations provide evidence that iodine intermediates are required for iodate formation (Luther, 2023). Specifically, Luther (2023) demonstrated that the formation of iodate from iodide involves a complex multi-step process that includes the oxidation of iodide (I⁻) to hypoiodous acid (HOI), followed by the disproportionation of HOI to produce diatomic iodine (I₂) and further oxidation steps leading to the final formation of iodate (IO₃⁻). Each of these intermediate steps involves specific reaction conditions and equilibria that can shift depending on the surrounding chemical environment, such as pH, the presence of catalysts, or microbial activity (Luther, 2023). The involvement of these intermediates is crucial, as they dictate the overall kinetics of the process and ultimately control the isotopic composition of the iodate formed. This aligns with our observations and those of Ştreangă et al. (2023), indicating that iodate production may be largely governed by the dynamics of these intermediate species rather than by the initial oxidation of iodide. 5.3 Rates calculations Understanding the rates at which iodate, iodide, and potential intermediates undergo transformations in the ocean is crucial for elucidating the dynamics of the marine iodine cycle. These rates provide insights into the underlying pathways and mechanisms driving the observed changes in iodate concentrations and ratios over time. This section explores the variability in these rates across different stations and light levels, highlighting the same 3 categories from the previous section: no discernible change in iodate isotope ratios (Scenario 1), a positive shift in iodate isotope ratios (Scenario 2), and a negative shift in iodate isotope ratios (Scenario 3). By examining the calculated rates in conjunction with potential physical, chemical, and biological mechanisms, we 34 aim to shed light on the processes governing iodine speciation in the marine environment. The following analysis is summarized in Tables 4 and 5, as well as Figure 12, and is supported by comparisons with previous studies to contextualize these findings within the broader framework of marine biogeochemistry. Rate calculations of iodate formation were performed for each incubation at 1% and 7% light according to previous approaches (Hardisty et al., 2020; Schnur et al., 2024; Ştreangă et al., 2023). For these calculations, we modeled changes in iodate concentration based on the measured 129I/127I of iodate. These calculations all start with the average measured iodate concentration at t0 as the initial timepoint. We then calculated the 129IO3 - and 127IO3 - concentrations at t0 for each of the triplicates using measured 129I/127I of iodate at t0. Next, we solved for the 129IO3 - and 127IO3 - additions required to achieve the measured isotope ratio of subsequent time points, which are summed to determine total IO3 - for these time points. Importantly, specific considerations were made regarding the isotopic composition of the iodate precursor for each of the generalized three scenarios that we observed. These are outlined in more detail below. Lastly, in each case, rates were calculated according to zeroeth, first, and second order (Hardisty et al., 2020; Schnur et al., 2024; Ştreangă et al., 2023). These were each considered because there is uncertainty regarding the specific reaction mechanism and associated reaction order, but also in an attempt to constrain the reaction order using our experiments. For Scenario 1, where no change in iodate 129I/127I ratios was observed, we constrain the maximum rates possible in which the final time points remain within 1 standard deviation of our initial time points—thus within the uncertainty of our data (e.g., Schnur et al., 2024). These values are shown in Tables 4 and 5, where they are within brackets to denote that they represent maximum constraints. Importantly, we considered the maximum iodate production rates associated with a positive shift in iodate isotope ratios (implying iodate formation from an iodide source matching the 129I/127I measured at t0) as well as the maximum rates associated with a negative shift in iodate isotope ratios (implying a non-specific 127I-only sources to iodate). Notably, given the initially low 129I/127I of iodate, the iodate isotopic changes are more sensitive to additions with the isotopic composition of our measured 129I/127I of iodide, and thus the calculated maximum rates are much lower in this scenario relative to iodine-127 only additions. In scenarios where no significant change in iodate isotope ratios is observed, as seen in the majority of our experiments, the first order rates calculated range from 9 to 37 yr-1 for the 127I- 35 addition at the 7% light level (Table 4) and from 4 to 33 yr-1 for the 127I- addition at the 1% light level (Table 5). The 129I- additions for the 7% light level (Table 4) for the first order rates range from 0.156 to 6.94 yr-1 and for the 1% light level the rates range from 2.25 to 3.16 yr-1. The lack of significant change in iodate isotope ratios indicates that the iodine cycle at these locations is not driven primarily by chemical or biological transformations but rather by physical mixing and advection. The role of physical mixing in controlling iodate levels has been supported by previous studies, which have shown that in regions with strong water column mixing, the distribution of iodine species is often uniform, leading to minimal changes in iodate isotope ratios (Truesdale et al., 2000; Wong & Brewer, 1977). These slow iodine redox transformations also align with the findings of Schnur et al. (2024), who also inferred from similar experimental observations that physical processes dominate in Atlantic surface waters near Bermuda. Scenario 2 only applies to station 35 at the 7% light level, where a positive shift in iodate isotope ratios is observed. This observation specifically implies iodate formation from iodide, so the rate calculation was only performed for an increase in 129I/127I of iodate sourced from the measured 129I/127I of iodide. We do recognize that 127I-only sources to iodate could occur alongside iodide oxidation to iodate, as we suggest for station 7 (1%), but to maintain simplicity and in the absence of direct constraints we ignore this possibility. The zeroth-order rate calculated at station 35 is approximately 1321 nM/yr, which is about ten times as fast as the zeroth-order reaction rates reported by Hardisty et al. (2020), who also documented an increase in iodate isotope ratios in similar experiments, but at rates between 118 and 189 nM/yr. This substantial difference in rates between the 2 studies suggests more active biogeochemical processes such as microbial oxidation of iodide, which can be influenced by environmental factors like light availability, organic matter concentration, and the presence of reactive oxygen species (Campos et al., 1996; Hardisty et al., 2020). Regardless, our survey results and comparison to other studies (Hardisty et al., 2020; Schnur et al., 2024; Ştreangă et al., 2023) clearly suggest that iodate formation from iodide is not widespread, but when active there is potential for large variations in reaction rates. For Scenario 3, where negative shift in iodate isotope ratios is observed, our rate calculations exclusively consider an unspecified 127I source for iodate formation. Analogous to Scenario 2, we recognize that oxidation of the radiolabeled iodide could occur simultaneously with radio-iodine free sources, but to maintain simplicity and in the absence of direct constraints we ignore this possibility. At the relevant stations—i.e., stations 35, 41, 42, and 48 at the 1% light 36 level—the rates of iodate formation are notably high, ranging from 51,112 to 142,944 nM/yr for zeroeth order and 92 to 126 yr-1 for first order rates (Table 5 and Figure 12). These rapid rates suggest that the iodate production is occurring at an accelerated pace, possibly due to a multi-step reaction mechanism involving iodine intermediates. Comparison of reaction order fit to the calculated iodate concentrations suggests that first-order reactions may be most applicable for this scenario (Figure 12). This supports the idea that the process involves complex biochemical pathways (Luther, 2023). This dynamic cycling likely involves the transient accumulation of iodine intermediates, which then rapidly convert back to iodate, resulting in the observed negative shift. Ştreangă et al. (2023) reported similar findings, reporting a first order reaction rate of 157 yr-1 which overlaps with the range observed here. The predicted iodate production rates for stations with decreased iodate isotope ratios are notably higher than any observed changes in iodate concentrations (Figures 3 and 4). For example, at stations 35 through 48 at the 1% light level, the predicted rates of iodate production (as shown in Figure 12 and Table 5) are much higher than the measured iodate concentrations at the final timepoints (Figure 5). When rates far exceed what is directly observed, this indicates a pattern of extensive recycling of iodine between endmember and intermediate pools. This disparity suggests that our calculations constrain a gross rate of iodate formation and that the net rate is offset by back reactions from iodate to iodine intermediates that also occur at a significant rate. Given these observations, we suggest that the isotopic trend and reaction order fit could indicate that isotopic equilibrium between the intermediate pools and the iodate pool is being established during rapid exchange. Thus, changes in 129I/127I of iodate decelerate at the final stages of the incubation as the two isotopic pools become more similar. If so, the rates could be even faster than that calculated here, since we assumed an iodate source that was exclusively 127I. Further, given the relatively large concentration of iodine-127 additions required to detect changes in the 129I/127I of iodate, we suggest similar reactions are perhaps widespread but might be more easily detected in tracer experiments with the 129I added directly as iodate. Regardless, the observed trend for Scenario 3 is still not universal; most stations and depths show no change in either concentration or isotope ratios between incubation timepoints. This comparison to other stations provides confidence that the observed phenomenon of accelerated iodate exchange with intermediates is localized, potentially limited to stations 35 through 48 at the 1% light level. 37 Table 4. Table of calculated iodide oxidation rates for stations at the 7% light level, in nM/year-1. Values are the rates, dashes are where a rate was not calculated due to an observed statistically significant change between timepoints in the other category, and “NC” is where a calculation was unable to be performed due to missing variables. Brackets indicate values calculated using the upper standard deviation value for the highest rate possible. Rates at the 7% Light Percentage Site Number 2 7 13 19 24 30 35 41 42 48 54 Zero Order I- 127 (nM/yr) [4.77E+03] [5.58E+03] [4.53E+03] [5.15E+03] [5.18E+03] [3.51E+03] - [6.49E+03] [1.65E+04] [6.46E+03] [2.00E+04] Zero Order I- 129 (nM/yr) [7.67E+01] [1.32E+02] [9.82E+01] NC NC NC 1.32E+03 NC [3.74E+03] [1.12E+03] [2.35E+02] First Order I- 127 (yr-1) [9.05E+00] [1.40E+01] [9.25] [1.38E+01] [1.45E+01] [1.11E+01] - [1.72E+01] [2.88E+01] [9.49] [3.73E+01] First Order I- 129 ( yr-1) [1.56E-01] [3.69E-01] [2.14E-01] NC NC NC 3.83 NC [6.94] [1.62] [4.83E-01] Second Order I- 127 (nM-1yr-1) [1.72E-02] [3.53E-02] [1.89E-02] [3.70E-02] [4.07E-02] [3.50E-02] - [4.55E-02] [5.08E-02] [1.40E-02] [6.99E-02] Second Order I- 129 ( nM-1yr-1) [3.16E-04] [1.03E-03] [4.68E-04] NC NC NC 1.11E-02 NC [1.29E-02] [2.34E-03] [9.90E-04] 38 Table 5. Table of calculated iodide oxidation rates for stations at the 1% light level, in nM/year-1. Values are the rates, dashes are where a rate was not calculated due to an observed statistically significant change between timepoints in the other category, and “NC” is where a calculation was unable to be performed due to missing variables. Brackets indicate values calculated using the upper standard deviation value for the highest rate possible. Rates at the 1% Light Percentage Site Number 2 7 13 19 24 30 35 41 42 48 54 Zero Order I- 127 (nM/yr) [5.56E+03] [1.58E+04] [7.32E+03] [8.07E+03] [6.47E+03] [2.25E+03] 1.43E+05 5.11E+04 6.08E+04 6.59E+04 [2.66E+04] Zero Order I- 129 (nM/yr) NC [1.72E+03] NC [1.21E+03] [1.21E+03] NC - - - - - First Order I- 127 (yr-1) [1.17E+01] [3.37E+01] [1.55E+01] [1.41E+01] [1.23E+01] [4.29] 1.21E+02 9.23E+01 1.26E+02 1.03E+02 [5.68E+01] First Order I- 129 ( yr-1) NC [3.16] NC [2.25] [2.40] NC - - - - - Second Order I- 127 (nM-1yr-1) [2.45E-02] [7.28E-02] [3.30E-02] [2.47E-02] [2.34E-02] [8.18E-03] 1.21E-01 1.85E-01 3.07E-01 1.88E-01 [1.23E-01] Second Order I- 129 ( nM-1yr-1) NC [5.90E-03] NC [4.20E-03] NC NC - - - - - 39 5.5 Implications Observations of iodate production have remained elusive, but this study demonstrates that iodine cycling processes are actively occurring in the ocean, with both iodine oxidation and reduction contributing to the observed variability. Understanding these mechanisms is essential for accurately modeling cycling in the ocean and its interactions with other elements (Wadley et al., 2020; Lu et al., 2018; Cheng et al., 2024), such as carbon and nitrogen, as well as predicting how marine biogeochemical cycles might respond to environmental changes like ocean acidification or warming. For example, while global-scale modeling approaches assuming generalized reaction rates for iodide oxidation to iodate may be applicable (e.g., Cheng et al., 2024), ours and the combination of other recent tracer studies demonstrate a diversity of rates from location to location. That said, the challenge remains of determining the natural mechanisms and required conditions for driving these rate variations, which is essential for incorporation into global iodine cycling models. This study also sheds light on the potential pathways of iodide oxidation. The observation of enhanced iodate production at the 1% light level overlapping with the DCM provides some support for links between iodate production and ammonia oxidation (Hughes et al., 2021). While ammonia oxidation rates were not measured in this study, previous nitrogen tracer studies from the AMT transect have demonstrated that this process is most active at the DCM (Rees et al., 2015), which is generally true globally. Iodide oxidation to iodate was observed in laboratory cultures of ammonium oxidizing bacteria while our data reinforce this connection in the natural environment. Importantly, however, our results from the DCM do not clearly link iodate production to iodide oxidation, instead suggesting an important role for intermediates, including oxidation and reduction. Future work should consider more directly linking iodate production and ammonia oxidation. For example, this could include controls limiting ammonia oxidation in shipboard experiments similar to that here where iodate production is being traced. Similarly, tracking ammonia oxidation rates and iodate production rates in the same experiments could provide evidence of coupled increases and decreases in rates, thus linking the processes. This research has profound implications for paleoceanography, particularly in the context of redox proxies, as iodine is increasingly used to infer past redox conditions and the oxygenation state of ancient waters. The study’s findings on iodate production and the role of intermediates offer a new framework for interpreting these proxies, as understanding the modern mechanisms of 40 iodate formation and variability allows for better interpretation of historical changes in iodine cycling and redox states preserved in sedimentary records. However, the rates and pathways of iodate production present significant challenges for both modern and ancient iodine cycle models (Cheng et al., 2024; Wadley et al., 2020). The observed variability in iodate production complicates the application of iodine-based proxies for quantitative interpretations of past ocean conditions. Nonetheless, the insights from this study contribute crucial data for improving these models, particularly in simulating the balance between oxidation and reduction reactions in iodine cycling. By identifying the key processes that drive iodine transformations, this research enhances our ability to reconstruct ancient ocean conditions, assess their impact on Earth's climate over geological timescales, and refine models incorporating iodine isotopes as paleo-redox indicators. 41 CONCLUSION This study offers a comprehensive analysis of iodine cycling in the Atlantic Ocean, integrating field observations with a radioactive iodine-129 tracer to uncover the complexity of iodate production mechanisms. The observed iodate production occurred through multiple pathways, revealing three distinct trends: no discernible change, a positive shift, and a negative shift in iodate isotope ratios. The variability in these trends, along with quantified rates that differed by depth and location, underscores the intricate interplay between biological and physical processes in iodine cycling. Notably, recycling of intermediates plays a crucial role in these dynamics, with most locations exhibiting no significant iodate production, while northern (boreal spring) locales at 1% light showed the most activity. These findings have important implications for improving models of iodine cycling and refining the use of iodine as a paleo-redox proxy. Future research should aim to refine experimental methods and explore seasonal and regional variations to further elucidate the mechanisms governing iodine dynamics in marine environments, enhancing our understanding of both modern and historical iodine cycles. 42 Figure 12. Plots showing each station where a statistically significant change occurred between initial and final timepoints and the associated calculated rate. Each rate includes a zeroth, first, and second order variation with a line of best fit in red for each plot and the rate value plotted as a blue “x”. 43 BIBLIOGRAPHY Aiken, J., Brewin, R. J. 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Croatica Chemica Acta, 79(1), 143–153. 48 APPENDIX Figure S13: taxonomic analysis of shipboard incubations over time at the 7% light percentage for all stations. 49 Figure S14: taxonomic analysis of shipboard incubations over time at the 1% light percentage for all stations. 50 Table S6. Isotope and Concentration Incubation Data Table. Sample Number AMT30- 22 AMT30- 23 AMT30- 24 AMT30- 125 AMT30- 126 AMT30- 127 AMT30- 19 AMT30- 20 AMT30- 21 AMT30- 128 AMT30- 129 AMT30- 130 AMT30- 107 Station Number Latitude Longitude Depth (m) Date Collected Light Percent Iodide Concentration (nM) Iodate Concentration (nM) Iodide Ratio Iodate Ratio - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 - 45.30.206 -38 27.109 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 - 47.49.736 -42 45.511 2 2 2 2 2 2 2 2 2 2 2 2 7 15 2/23/2023 7% 260.2447936 510.290974 0.448735 0.007268 15 2/23/2023 7% 264.1765011 471.5412281 0.448763 0.006568 15 2/23/2023 7% 288.6021005 484.5922722 0.447111 0.006985 15 3/1/2023 7% 268.8900081 503.1586409 0.44097 0.007094 15 3/1/2023 7% 294.0608726 607.0395556 0.437424 0.008515 15 3/1/2023 7% 302.4847505 500.841738 0.443926 0.008541 30 2/23/2023 1% 293.0994827 412.890952 30 2/23/2023 1% 270.5157665 519.2421516 30 2/23/2023 1% 204.4339316 366.7338982 30 3/1/2023 1% 225.3930194 451.8544198 30 3/1/2023 1% 210.9211709 371.0518945 30 3/1/2023 1% 282.3740137 378.7822378 - - - - - - 0.006791 0.006034 0.006763 0.006845 0.006695 0.007658 30 2/26/2023 7% 197.2015611 297.4115876 0.398544 0.008533 51 Table S6 (cont’d) AMT30- 108 AMT30- 109 AMT30- 227 AMT30- 228 AMT30- 229 AMT30- 92 AMT30- 93 AMT30- 94 AMT30- 140 AMT30- 141 AMT30- 142 AMT30- 212 AMT30- 213 AMT30- 214 AMT30- 179 7 7 7 7 7 7 7 7 7 7 7 7 7 7 13 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -33 16.405 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -33 20.230 30 2/26/2023 7% 162.3002462 282.8564045 0.396083 0.009248 30 2/26/2023 7% 299.7948955 483.2663869 0.400454 0.007889 30 3/4/2023 7% 295.8774102 415.5059257 0.396092 0.00961 30 3/4/2023 7% 292.415326 496.5351894 0.395662 0.008818 30 3/4/2023 7% 279.19524 406.6429829 0.393519 0.008678 55 2/26/2023 1% 194.7087509 392.5636733 0.407883 0.010858 55 2/26/2023 1% 199.984966 379.2825418 0.409079 0.010342 55 2/26/2023 1% 200.2781964 395.4713953 0.409104 0.011207 55 3/1/2023 1% 187.3618448 416.0195554 0.406068 0.008225 55 3/1/2023 1% 188.0085233 401.2668903 0.408183 0.009928 55 3/1/2023 1% 202.2166579 416.5051495 - 0.008578 55 3/4/2023 1% 181.2209247 417.585739 0.402023 0.011915 55 3/4/2023 1% 177.7150567 442.3518558 0.404187 0.011779 55 3/4/2023 1% 178.6708615 393.3113209 0.399575 0.011748 60 3/1/2023 7% 266.7271455 471.7226661 0.3819 0.006954 52 Table S6 (cont’d) AMT30- 180 AMT30- 181 AMT30- 311 AMT30- 312 AMT30- 313 AMT30- 182 AMT30- 183 AMT30- 184 AMT30- 236 AMT30- 237 AMT30- 238 AMT30- 314 AMT30- 315 AMT30- 316 AMT30- 290 13 13 13 13 13 13 13 13 13 13 13 13 13 13 19 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -27 18.821 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -24 31.421 60 3/1/2023 7% 304.4036475 437.1143962 0.382848 0.006627 60 3/1/2023 7% 472.4012408 453.0971069 0.370536 0.00735 60 3/7/2023 7% 293.5024343 488.7566029 0.378318 0.007137 60 3/7/2023 7% 294.2321685 457.4221336 0.381613 0.006956 60 3/7/2023 7% 276.3529759 450.8738722 0.375867 0.007196 105 3/1/2023 1% 181.5066429 410.802958 105 3/1/2023 1% 176.8512434 412.3119125 105 3/1/2023 1% 176.4694883 420.5575895 105 3/4/2023 1% 145.2098137 356.5716783 105 3/4/2023 1% 108.3098527 416.9477341 105 3/4/2023 1% 168.0720087 255.0942673 105 3/7/2023 1% 178.662573 436.4344637 105 3/7/2023 1% 179.3778515 418.6994922 105 3/7/2023 1% 177.2043492 429.1932547 75 3/4/2023 7% 219.8043346 333.0976498 - - - - - - - - - - 0.011709 0.010034 0.010142 0.010939 0.012062 0.010983 0.009783 0.009276 0.010658 0.007614 53 Table S6 (cont’d) AMT30- 291 AMT30- 292 AMT30- 341 AMT30- 342 AMT30- 343 AMT30- 404 AMT30- 405 AMT30- 406 AMT30- 278 AMT30- 279 AMT30- 280 AMT30- 392 AMT30- 393 AMT30- 394 AMT30- 362 19 19 19 19 19 19 19 19 19 19 19 19 19 19 24 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 75 3/4/2023 7% 223.4817582 317.6105979 75 3/4/2023 7% 226.8743051 348.5816352 75 3/7/2023 7% 222.5167207 317.5888125 75 3/7/2023 7% 158.03536 353.9280675 75 3/7/2023 7% 232.0255691 234.9266021 75 3/10/2023 7% 227.0071005 333.2925576 75 3/10/2023 7% 223.6384934 349.3093398 75 3/10/2023 7% 232.0501975 326.7334223 - - - - - - - - 0.00874 0.00875 - - - 0.007386 0.008976 0.008174 105 3/4/2023 1% 217.8025707 548.0970721 0.296021 0.032082 105 3/4/2023 1% 204.4916929 511.4473072 0.311532 0.032781 105 3/4/2023 1% 165.0449045 468.3220803 0.374194 0.037094 105 3/10/2023 1% 186.3777868 505.9335726 105 3/10/2023 1% 199.4679277 563.8097405 105 3/10/2023 1% 136.5238653 546.2605335 - - - - 0.030644 0.029897 0.040504 0.007752 -18 1.386 -25 3.809 100 3/7/2023 7% 250.643644 326.7767926 54 Table S6 (cont’d) AMT30- 363 AMT30- 364 AMT30- 413 AMT30- 414 AMT30- 415 AMT30- 491 AMT30- 492 AMT30- 493 AMT30- 365 AMT30- 366 AMT30- 367 AMT30- 494 AMT30- 495 AMT30- 496 AMT30- 470 24 24 24 24 24 24 24 24 24 24 24 24 24 24 30 -18 1.386 -25 3.809 100 3/7/2023 7% 262.3485753 319.1896309 -18 1.386 -25 3.809 100 3/7/2023 7% 276.5803411 304.9068303 -18 1.386 -25 3.809 100 3/10/2023 7% 267.9001507 323.6959804 -18 1.386 -25 3.809 100 3/10/2023 7% 267.8175761 319.2334884 -18 1.386 -25 3.809 100 3/10/2023 7% 278.3058331 328.3603633 -18 1.386 -25 3.809 100 3/13/2023 7% 262.1971471 303.1227845 -18 1.386 -25 3.809 100 3/13/2023 7% 274.9247797 312.2251524 -18 1.386 -25 3.809 100 3/13/2023 7% 271.0651038 304.5969572 - - - - - - - - 0.006575 0.007283 - - - 0.007317 0.007965 0.00905 -18 1.386 -25 3.809 155 3/7/2023 1% 204.1617254 479.3239184 0.346091 0.045463 -18 1.386 -25 3.809 155 3/7/2023 1% 219.9865367 432.5807416 0.332578 0.040257 -18 1.386 -25 3.809 155 3/7/2023 1% 216.8592608 512.8884861 0.328483 0.045586 -18 1.386 -25 3.809 155 3/13/2023 1% 244.5644962 501.6719277 0.30216 0.028549 -18 1.386 -25 3.809 155 3/13/2023 1% 253.7960099 485.7912514 0.31422 0.026648 -18 1.386 -25 3.809 155 3/13/2023 1% 207.8367 453.2195797 0.344479 0.090772 -8 44.641 -25 9.408 90 3/10/2023 7% 309.4456343 292.2099688 - 0.010282 55 Table S6 (cont’d) AMT30- 471 AMT30- 472 AMT30- 521 AMT30- 522 AMT30- 523 AMT30- 584 AMT30- 585 AMT30- 586 AMT30- 458 AMT30- 459 AMT30- 460 AMT30- 572 AMT30- 573 AMT30- 574 AMT30- 542 30 30 30 30 30 30 30 30 30 30 30 30 30 30 35 -8 44.641 -25 9.408 90 3/10/2023 7% 322.8031111 291.6109794 -8 44.641 -25 9.408 90 3/10/2023 7% 330.8055461 283.971993 -8 44.641 -25 9.408 90 3/13/2023 7% 315.4916437 280.7693119 -8 44.641 -25 9.408 90 3/13/2023 7% 326.9176749 305.1717479 -8 44.641 -25 9.408 90 3/13/2023 7% 320.4047662 275.2575884 -8 44.641 -25 9.408 90 3/15/2023 7% 339.124471 278.5821862 -8 44.641 -25 9.408 90 3/15/2023 7% 331.5536678 277.5196631 -8 44.641 -25 9.408 90 3/15/2023 7% 333.9197946 280.417484 -8 44.641 -25 9.408 110 3/10/2023 1% 204.7929015 416.5822333 -8 44.641 -25 9.408 110 3/10/2023 1% 228.7554842 532.2490894 -8 44.641 -25 9.408 110 3/10/2023 1% 212.6326222 569.3654745 -8 44.641 -25 9.408 110 3/15/2023 1% 220.479988 280.2733414 -8 44.641 -25 9.408 110 3/15/2023 1% 320.2936336 345.1897108 - - - - - - - - - - - - - - 0.009365 0.009158 - - - 0.008959 0.009681 0.010006 0.009468 0.009078 0.009456 0.008995 0.009519 0.01081 -8 44.641 0 55.755 -25 9.408 -25 22.639 110 3/15/2023 1% 348.0903144 297.2444223 40 3/13/2023 7% 281.2195961 321.4670019 0.3124 0.013156 56 Table S6 (cont’d) AMT30- 543 AMT30- 544 AMT30- 593 AMT30- 594 AMT30- 595 AMT30- 671 AMT30- 672 AMT30- 673 AMT30- 545 AMT30- 546 AMT30- 547 AMT30- 674 AMT30- 675 AMT30- 676 AMT30- 650 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 10 25.350 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 17.460 35 35 35 35 35 35 35 35 35 35 35 35 35 35 41 40 3/13/2023 7% 286.064345 339.0490165 0.312143 0.014571 40 3/13/2023 7% 289.2681293 353.5077996 0.312311 0.013604 40 3/15/2023 7% 291.7820399 353.9635641 40 3/15/2023 7% 282.3028757 340.8273462 40 3/15/2023 7% 292.0091977 344.6774606 - - - - - - 40 3/17/2023 7% 272.1101778 323.4268585 0.310499 0.015704 40 3/17/2023 7% 277.5984909 343.3063652 0.310762 0.016331 40 3/17/2023 7% 290.3817934 333.2289782 0.310382 0.015351 65 3/13/2023 1% 154.7346643 556.3014499 0.318209 0.026094 65 3/13/2023 1% 170.1156429 433.8380253 0.309215 0.023821 65 3/13/2023 1% 173.1920337 673.7860757 0.308056 0.024734 65 3/17/2023 1% 191.3765479 279.3275635 0.313839 0.011992 65 3/17/2023 1% 198.512993 269.2465135 0.288893 0.013767 65 3/17/2023 1% 257.6490219 415.083892 0.324299 0.012895 40 3/16/2023 7% 235.5183531 346.8870366 - 0.015425 57 Table S6 (cont’d) AMT30- 651 AMT30- 652 AMT30- 701 AMT30- 702 AMT30- 703 AMT30- 764 AMT30- 765 AMT30- 766 AMT30- 638 AMT30- 639 AMT30- 640 AMT30- 752 AMT30- 753 AMT30- 754 AMT30- 722 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 20 41.930 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -24 59.866 41 41 41 41 41 41 41 41 41 41 41 41 41 41 42 40 3/16/2023 7% 218.064137 343.9992847 40 3/16/2023 7% 247.7894914 340.4448662 40 3/18/2023 7% 231.4652796 335.1430039 40 3/18/2023 7% 235.7275318 331.5805693 40 3/18/2023 7% 237.8297388 332.5909624 40 3/20/2023 7% 248.2325731 332.803988 40 3/20/2023 7% 249.4557076 345.5251536 40 3/20/2023 7% 242.4297983 351.537048 60 3/16/2023 1% 196.3430516 337.8277636 60 3/16/2023 1% 140.036773 245.9346001 60 3/16/2023 1% 150.235214 350.1686031 - - - - - - - - - - - 0.014113 0.01363 - - - 0.013709 0.015904 0.012204 0.016604 0.023482 0.01807 60 3/20/2023 1% 213.5968069 387.241937 0.462288 0.01141 60 3/20/2023 1% 167.6039221 367.2273527 0.46978 0.012619 60 3/20/2023 1% 192.2654783 241.239261 0.478388 0.012183 50 3/19/2023 7% 239.7037741 467.1950704 0.379517 0.05678 58 Table S6 (cont’d) AMT30- 723 AMT30- 724 AMT30- 773 AMT30- 774 AMT30- 775 AMT30- 851 AMT30- 852 AMT30- 853 AMT30- 725 AMT30- 726 AMT30- 727 AMT30- 776 AMT30- 777 AMT30- 778 AMT30- 854 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 50 3/19/2023 7% 195.1676115 522.4551292 0.37757 0.070849 50 3/19/2023 7% 192.4290154 470.963653 0.377973 0.065271 50 3/21/2023 7% 119.2998448 514.7489662 50 3/21/2023 7% 133.3898873 504.8777816 50 3/21/2023 7% 130.6377417 487.5256973 50 3/23/2023 7% 125.0232037 479.7200742 50 3/23/2023 7% 135.2945405 511.4909122 50 3/23/2023 7% 143.3288601 455.3316909 - - - - - - - - - 0.078938 0.07053 0.064874 85 3/19/2023 1% 244.4537203 245.9724014 0.403975 0.015425 85 3/19/2023 1% 242.9473132 222.1257839 0.404279 0.015607 85 3/19/2023 1% 186.2659418 199.1920202 0.394888 0.016279 85 3/21/2023 1% 240.3378619 394.1953273 85 3/21/2023 1% 273.3463323 388.4246628 85 3/21/2023 1% 182.6037355 352.67773 - - - 0.011158 0.010105 0.010572 85 3/23/2023 1% 267.6987397 311.0921576 0.403307 0.007516 59 Table S6 (cont’d) AMT30- 855 AMT30- 856 AMT30- 830 AMT30- 831 AMT30- 832 AMT30- 881 AMT30- 882 AMT30- 883 AMT30- 944 AMT30- 945 AMT30- 946 AMT30- 818 AMT30- 819 AMT30- 820 AMT30- 869 20 41.930 20 41.930 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 -24 59.866 -24 59.866 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 42 42 48 48 48 48 48 48 48 48 48 48 48 48 48 85 3/23/2023 1% 237.7844436 334.6041763 0.404063 0.007363 85 3/23/2023 1% 261.5239973 333.9615982 0.405788 0.008924 55 3/22/2023 7% 86.24022413 514.6550275 0.442647 0.064838 55 3/22/2023 7% 77.10716772 552.1077919 0.442934 0.06069 55 3/22/2023 7% 84.61408993 870.5789054 0.440339 0.061509 55 3/24/2023 7% 88.17920136 540.2074737 55 3/24/2023 7% 82.98419606 538.8301918 55 3/24/2023 7% 79.70707246 538.7106396 55 3/26/2023 7% 88.94265277 534.9467417 55 3/26/2023 7% 76.82949998 555.7828942 55 3/26/2023 7% 50.67224049 422.9310099 - - - - - - 0.059588 0.063085 0.063577 0.061044 0.064622 0.069335 112 3/22/2023 1% 180.8051346 378.4554336 0.458659 0.010539 112 3/22/2023 1% 186.5830051 342.1936418 0.473565 0.011802 112 3/22/2023 1% 170.1077827 243.9998147 0.473098 0.011552 112 3/24/2023 1% 139.2340648 450.721155 - 0.007429 60 Table S6 (cont’d) AMT30- 870 AMT30- 871 AMT30- 932 AMT30- 933 AMT30- 934 AMT30- 908 AMT30- 909 AMT30- 910 AMT30- 959 AMT30- 960 AMT30- 961 AMT30- 905 AMT30- 906 AMT30- 907 AMT30- 956 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 48 48 48 48 48 54 54 54 54 54 54 54 54 54 54 112 3/24/2023 1% 213.9281681 476.3095109 112 3/24/2023 1% 144.080203 486.9942775 - - 0.007908 0.008897 112 3/26/2023 1% 164.0334907 364.7638548 0.466946 0.007741 112 3/26/2023 1% 184.7383985 507.0105934 0.465219 0.005501 112 3/26/2023 1% 184.8189699 395.9366807 0.467801 0.006641 20 3/25/2023 7% 153.4375867 483.6174437 0.618471 0.008332 20 3/25/2023 7% 168.2273609 501.1740741 0.617349 0.009508 20 3/25/2023 7% 164.0591144 463.7613201 0.615523 0.008582 20 3/27/2023 7% 162.3529269 475.6752262 20 3/27/2023 7% 176.1546889 471.8343468 20 3/27/2023 7% 163.0654348 445.9671566 - - - 0.009363 0.009434 0.009003 25 3/25/2023 1% 148.5746521 371.67223 0.632255 0.007793 25 3/25/2023 1% 152.6004153 399.253768 0.634865 0.007145 25 3/25/2023 1% 149.0842887 396.4624378 0.632517 0.00777 25 3/27/2023 1% 155.8164077 552.1910747 0.58763 0.006941 61 Table S6 (cont’d) AMT30- 957 AMT30- 958 54 54 37 47.807 37 47.807 -18 46.836 -18 46.836 25 3/27/2023 1% 150.3109671 452.1089435 0.626313 0.006734 25 3/27/2023 1% 237.7421996 459.6713339 0.630342 0.006527 62 Table S7. Depth Profile Data Table Sample Number AMT30-27 AMT30-28 AMT30-29 AMT30-30 AMT30-31 AMT30-32 AMT30-33 AMT30-34 AMT30-35 AMT30-36 AMT30-110 AMT30-111 AMT30-112 AMT30-113 AMT30-114 AMT30-115 AMT30-116 AMT30-117 AMT30-118 AMT30-119 AMT30-120 AMT30-121 AMT30-188 AMT30-189 AMT30-190 AMT30-191 AMT30-192 Station Number 2 2 2 2 2 2 2 2 2 2 7 7 7 7 7 7 7 7 7 7 7 7 13 13 13 13 13 Latitude -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -45.30.206 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -38 27.109 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 Longitude Depth (m) -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -47.49.736 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -42 45.511 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 200 150 100 60 40 30 25 20 15 5 5 10 15 25 30 50 55 80 100 150 250 500 5 10 20 60 80 63 Iodide Concentration (nM) 7.8592 11.8598 24.6794 36.8399 33.9740 37.7876 39.8927 46.4915 38.3279 62.8146 34.2836 29.7368 19.6803 28.4812 41.9868 16.7888 23.9124 5.5656 3.6525 2.1657 0.1519 Date Collected 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/23/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 2/26/2023 below detection 3/1/2023 3/1/2023 3/1/2023 3/1/2023 3/1/2023 66.9731 80.4852 83.5826 76.0958 65.8304 Iodate Concentration (nM) 231.3870 205.0724 342.9972 313.0530 132.4804 193.2762 213.2390 227.7574 184.2022 252.2572 248.9618 177.3307 134.5267 199.1694 278.6625 138.0209 193.9281 303.9954 144.1358 172.0894 215.7669 191.3075 121.4460 271.6965 277.1460 281.0385 299.7225 Table S7 (cont’d) AMT30-193 AMT30-194 AMT30-195 AMT30-196 AMT30-197 AMT30-198 AMT30-199 AMT30-296 AMT30-297 AMT30-298 AMT30-299 AMT30-300 AMT30-301 AMT30-302 AMT30-303 AMT30-304 AMT30-305 AMT30-306 AMT30-307 AMT30-371 AMT30-372 AMT30-373 AMT30-374 AMT30-375 AMT30-376 AMT30-377 AMT30-378 AMT30-379 AMT30-380 AMT30-381 AMT30-382 13 13 13 13 13 13 13 19 19 19 19 19 19 19 19 19 19 19 19 24 24 24 24 24 24 24 24 24 24 24 24 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -33 16.405 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -27 18.821 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -18 1.386 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -33 20.230 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -24 31.421 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 -25 3.809 105 120 130 150 250 400 500 5 20 40 75 90 105 115 150 175 250 400 500 5 10 20 40 80 100 155 170 185 250 400 500 64 3/1/2023 3/1/2023 3/1/2023 3/1/2023 3/1/2023 3/1/2023 3/1/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/4/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 3/7/2023 57.0828 33.9546 23.4802 15.3620 3.3039 below detection below detection 97.4748 105.1076 105.0808 63.4394 70.2487 54.9979 43.1197 21.8477 14.1811 below detection below detection below detection 111.9028 114.9350 110.7383 120.3928 100.1160 98.5091 81.4681 70.2235 35.5711 below detection below detection below detection 319.9635 329.3055 349.5465 361.2240 332.4195 375.2370 398.5920 238.2881 285.6497 269.3691 216.8273 278.2494 325.6110 343.3716 371.4926 270.8492 396.6534 276.0293 339.6715 226.3803 168.2347 198.4704 202.3468 206.9984 223.2792 259.7171 218.6276 334.1435 214.7512 262.8182 258.1666 Table S7 (cont’d) AMT30-476 AMT30-477 AMT30-478 AMT30-479 AMT30-480 AMT30-481 AMT30-482 AMT30-483 AMT30-484 AMT30-485 AMT30-486 AMT30-487 AMT30-551 AMT30-552 AMT30-553 AMT30-554 AMT30-555 AMT30-556 AMT30-557 AMT30-558 AMT30-559 AMT30-560 AMT30-561 AMT30-562 AMT30-656 AMT30-657 AMT30-658 AMT30-659 AMT30-660 AMT30-661 AMT30-662 30 30 30 30 30 30 30 30 30 30 30 30 35 35 35 35 35 35 35 35 35 35 35 35 41 41 41 41 41 41 41 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 -8 44.641 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 0 55.755 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 9.408 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 22.639 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 5 10 20 40 80 90 110 140 180 250 400 500 5 10 20 40 65 80 100 120 180 250 400 500 5 10 20 40 60 70 80 65 90.2755 119.0676 123.1580 113.6844 145.2416 129.6400 123.3148 58.7814 3.8708 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 3/10/2023 below detection 3/10/2023 below detection 3/10/2023 below detection 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 3/13/2023 below detection 3/13/2023 below detection 3/16/2023 3/16/2023 3/16/2023 3/16/2023 3/16/2023 3/16/2023 3/16/2023 110.1208 102.7148 115.7234 84.8337 90.5413 18.1852 5.0411 4.4094 2.3908 0.5083 151.6562 121.7976 137.6765 148.1032 76.3756 37.8211 27.0972 209.3520 300.9435 221.3461 221.3461 256.2381 279.1360 248.6055 307.4858 409.9810 558.2720 455.7768 450.3249 259.5560 249.2328 240.3843 184.3438 321.4955 308.2228 296.4248 379.0108 404.0815 389.3340 387.8593 411.4553 187.6500 200.1600 209.8900 254.3700 240.4700 272.4400 283.5600 Table S7 (cont’d) AMT30-663 AMT30-664 AMT30-665 AMT30-666 AMT30-667 AMT30-731 AMT30-732 AMT30-733 AMT30-734 AMT30-735 AMT30-736 AMT30-737 AMT30-738 AMT30-739 AMT30-740 AMT30-741 AMT30-742 AMT30-836 AMT30-837 AMT30-838 AMT30-839 AMT30-840 AMT30-841 AMT30-842 AMT30-843 AMT30-844 AMT30-845 AMT30-846 AMT30-847 AMT30-911 AMT30-912 41 41 41 41 41 42 42 42 42 42 42 42 42 42 42 42 42 48 48 48 48 48 48 48 48 48 48 48 48 54 54 10 25.350 10 25.350 10 25.350 10 25.350 10 25.350 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 20 41.930 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 29 16.323 37 47.807 37 47.807 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -25 17.460 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -24 59.866 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -23 40.649 -18 46.836 -18 46.836 100 150 250 400 500 5 10 20 40 50 85 110 150 200 250 400 500 5 10 25 55 70 112 120 135 175 250 400 500 5 10 66 12.7583 0.5706 3/16/2023 3/16/2023 3/16/2023 below detection 3/16/2023 below detection 3/16/2023 below detection 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/19/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/22/2023 3/25/2023 3/25/2023 112.5670 120.0297 129.7545 142.7934 121.3852 127.7853 24.9442 7.0165 0.7517 -2.7918 -2.4289 -3.6925 60.6759 69.9225 64.9685 66.6261 42.8256 51.0814 99.5556 71.5454 16.3346 4.0095 4.4466 2.5303 32.6585 43.1305 395.4550 305.8000 369.7400 421.1700 317.6150 336.7068 363.2701 341.7323 350.3474 363.2701 338.8606 492.4966 251.2738 482.4456 493.9324 557.1098 580.8013 217.8008 315.7380 236.8035 236.8035 152.0220 217.8008 329.6246 264.5768 340.5878 358.1288 396.1343 384.4403 289.5743 373.0355 Table S7 (cont’d) AMT30-913 AMT30-914 AMT30-915 AMT30-916 AMT30-917 AMT30-918 AMT30-919 AMT30-920 AMT30-921 AMT30-922 54 54 54 54 54 54 54 54 54 54 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 37 47.807 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 -18 46.836 20 25 40 50 90 120 175 250 400 500 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 3/25/2023 37.4799 35.3955 32.0979 44.0385 37.9873 15.0614 -1.7071 -1.0047 -3.0342 -2.6350 375.9385 354.1660 314.9755 373.7613 367.2295 351.2630 444.1590 418.0320 448.5135 431.0955 67