Evaluating the frequency, magnitude, and biogeochemical consequences of under-ice phytoplankton blooms
Keywords: Sustainability.
Earth System Science.

The Arctic Ocean has changed substantially because of climate change. The loss of sea ice extent and thickness has increased light availability in the surface ocean during the ice-covered portion of the year. Sea ice loss has also been a factor in the observed increases in sea surface temperatures and likely impacts surface ocean nutrient inventories. These changing environmental conditions have substantially altered patterns of phytoplankton net primary production (NPP) across the Arctic Ocean. While NPP in the Arctic Ocean was previously considered insubstantial until the time of sea ice breakup and retreat, the observation of massive under-ice (UI) phytoplankton blooms in many of the Arctic seas reveals that the largest pulse of NPP may be produced prior to sea ice retreat. However, estimating how much NPP is generated during the UI part of the year is challenging, as satellite observations are hampered by sea ice cover and very few field campaigns have targeted UI blooms for study. This thesis uses a combination of laboratory experiments, biogeochemical modeling, and an analysis of satellite remote sensing data to better understand how the magnitude and spatial frequency of UI phytoplankton blooms has changed over time in the Arctic Ocean, as well as to assess the likely biogeochemical consequences of these blooms. In Chapter 2, I present a one-dimensional ecosystem model (CAOS-GO), which I used to evaluate the magnitude of UI phytoplankton blooms in the northern Chukchi Sea (72°N) between 1988 and 2018. UI blooms were produced in all but four years over that period, accounted for half of total annual NPP, and were the primary drivers of interannual variability in NPP. Further, I found that years with large UI blooms had reduced rates of zooplankton grazing, leading to an intensification of the mismatch between phytoplankton and zooplankton populations. In Chapter 3, I used the same model configuration to investigate the role of UI bloom variability in controlling sedimentary processes in the northern Chukchi Sea. I found that, as total annual NPP increased from 1988 to 2018, there were increases in particle export to the benthos, nitrification in the water column and the sediments, and sedimentary denitrification. These increases in particle export to the benthos and denitrification were driven by higher rates of NPP early in the year (January-June) and were highest in years where under-ice blooms dominate, indicating the importance of UI NPP as drivers of these biogeochemical consequences. Additionally, I tested the system's sensitivity to added N, finding that, if N supply in the region increased, 30\% of the added N would subsequently be lost to denitrification. I subsequently deployed this model in the southern Chukchi Sea (68°N) to understand latitudinal differences in UI bloom importance across the region (Chapter 4). I found that UI blooms were far less important contributors to total NPP in the southern Chukchi Sea. Further, I found that their importance was waning over time; NPP generated in the UI period from 2013-2018 was only 34\% of the 1988-1993 mean. This lower rate of UI NPP was driven by a far shorter UI period as sea ice retreated nearly six weeks earlier than in the northern Chukchi Sea. However, low UI NPP was associated with higher rates of both total NPP and sedimentary denitrification in the southern Chukchi Sea than in the north. In Chapter 5, I used satellite remote sensing to determine how UI bloom frequency changed across the Arctic between 2003 and 2021. I found that UI blooms are a widespread feature and can be generated across 40\% of the observable seasonal sea ice zone in the Arctic Ocean. While there was an increase in observable area as sea ice retreated, there was no change in UI area, driving a nearly 10\% decline in the proportion of UI bloom prevalence. The Chukchi Sea was identified as both the region with the highest prevalence of UI blooms and the region most responsible for the decline in UI blooms. Finally, to understand the functional relationship between co-limiting light and nutrient conditions on phytoplankton growth, I conducted a laboratory experiment (Chapter 6). Phytoplankton growth under co-limiting conditions, which is frequently observed in the field, is often modeled using one of two functional relationships, but these relationships produce vastly different predictions of phytoplankton bloom magnitude. Although this laboratory experiment aimed to quantify the functional relationship of light and nutrient limitation on phytoplankton growth, I faced challenges in quantifying the nitrogen (N) concentration and was unable to meaningfully distinguish between these two functional relationships. However, this work also demonstrated that there is little difference between these functional relationships in areas like the Arctic Ocean, where nutrient concentrations can be rapidly depleted, diminishing from non-limiting to scarce over just a few days. Together, the results of this dissertation suggest that UI phytoplankton blooms can substantially contribute to total NPP, drive reductions in food availability, and change the rate of nitrogen loss. However, this work also demonstrates that UI blooms, which have likely been an important source of NPP across the Arctic since at least the 1980s, are likely an ephemeral feature, with their prevalence likely to decline in coming years as sea ice retreat shifts earlier