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Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms./
Author:	Payne, Courtney Michelle.
Description:	1 online resource (211 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Contained By:	Dissertations Abstracts International85-05B.
Subject:	Plankton. -
Online resource:	click for full text (PQDT)
ISBN:	9798380714594

Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms.
Payne, Courtney Michelle.

Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms. - 1 online resource (211 pages)

Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

Thesis (Ph.D.)--Stanford University, 2023.

Includes bibliographical references

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 (JanuaryJune) 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 di↵erences 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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380714594Subjects--Topical Terms:

1465264
Plankton.
Index Terms--Genre/Form:

554714
Electronic books.

Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms.
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245 1 0 $a Evaluating the Frequency, Magnitude, and Biogeochemical Consequences of Under-Ice Phytoplankton Blooms.
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500 $a Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
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502 $a Thesis (Ph.D.)--Stanford University, 2023.
504 $a Includes bibliographical references
520 $a 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 (JanuaryJune) 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 di↵erences 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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
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650 4 $a Biogeochemistry. $3 642004
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650 4 $a Ice. $3 1027284
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650 4 $a Microbiology. $3 591510
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