Algal pigment concentrations, High Arctic, August-September 2018
This project was conducted as a part of a United States-Swedish Joint Arctic Research Initiative. The goal of this initiative involved mooring the Icebreaker (IB) Oden to an ice floe in the inner pack ice in the high Arctic Ocean, and monitoring key oceanic-atmospheric parameters as the ice drifts....
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Arctic Data Center
2019
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Online Access: | https://dx.doi.org/10.18739/a2028pd2h https://arcticdata.io/catalog/view/doi:10.18739/A2028PD2H |
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ftdatacite:10.18739/a2028pd2h |
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openpolar |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
EARTH SCIENCE>OCEANS>OCEAN CHEMISTRY>PIGMENTS Arctic Ocean Phytoplankton Chlorophyll |
spellingShingle |
EARTH SCIENCE>OCEANS>OCEAN CHEMISTRY>PIGMENTS Arctic Ocean Phytoplankton Chlorophyll DiTullio, Giacomo Lee, Peter Algal pigment concentrations, High Arctic, August-September 2018 |
topic_facet |
EARTH SCIENCE>OCEANS>OCEAN CHEMISTRY>PIGMENTS Arctic Ocean Phytoplankton Chlorophyll |
description |
This project was conducted as a part of a United States-Swedish Joint Arctic Research Initiative. The goal of this initiative involved mooring the Icebreaker (IB) Oden to an ice floe in the inner pack ice in the high Arctic Ocean, and monitoring key oceanic-atmospheric parameters as the ice drifts. The cruise timeline (August through September) was chosen to highlight the transitional time period from the summer maximum in microbial biomass to declining stocks as autumn conditions result in lower nutrient and light levels, concomitant with the onset of freezing conditions. Biogenic aerosol production and fluxes are key research parameters in understanding the formation of Cloud Condensation Nuclei (CCN) and their impacts on the radiation budget of the Arctic Ocean. At present, there exists a paucity of data regarding how microbial community composition might change in the high Arctic Ocean, especially with respect to changes in the production of volatile aerosol precursor compounds as pelagic microbial communities replace sympagic communities. Specifically, this project focused on linking microbial community structure with the oceanic-atmosphere fluxes of Volatile Organic Carbon compounds (VOCs) emitted from various oceanic and pack ice ecosystems. The role of diminishing sea ice cover in the Arctic Ocean will significantly impact biogenic aerosol production and fluxes via changes in microbial community structure and the release of VOCs. At present, however, the scarcity of in-situ oceanic VOC measurements available from the high Arctic Ocean prevents the development of robust models correlating phytoplankton biomass with VOCs and their impact on aerosol production. For instance, most current models utilize satellite Chlorophyll a (Chla) imagery for estimating phytoplankton biomass (e.g. Gabric et al. 2014; Becagli et al. 2016). It is also well recognized that high concentrations of sea surface chromophoric dissolved organic matter (CDOM) can significantly bias remotely-sensed Chla concentrations, especially when Chla levels are <0.5 milograms per meter cubed (mg m-3) (Matsuoka et al. 2017). In addition to the bias in estimating in-situ phytoplankton biomass from satellite-derived Chla, the contribution made by oceanic VOC fluxes to the atmospheric aerosol optical depth (e.g. Gabric et al., 2002) is unknown. Moreover, incorrect estimates of the oceanic Mixed Layer Depth (MLD) using climatological datasets and/or subsurface Chla maximum can further compound the errors associated with attempting to correlate phytoplankton integrated water column production with estimates of biomass derived using satellite Chla algorithms (Arrigo et al., 2011). As a result, questions remain regarding the reliability of using Chla estimates as a surrogate to estimate the organic carbon enrichment in submicron marine aerosols (Rinaldi et al. 2013). Hence, models that use satellites over relatively large areal expanses in the Arctic may be biased with regards to estimates of biomass, net primary production and as a result correlations to biogenic aerosol (Arrigo et al., 2011, Becagli et al., 2016). More importantly, however, total Chla biomass is not the only important variable affecting the production of oceanic biogenic VOCs and aerosols. The microbial community composition and physiology will not only affect the cell-specific production rate of precursor biogenic aerosol compounds, but also the secondary transformations of those compounds. Furthermore, determining VOCs or phytoplankton functional groups from space are both fraught with even more difficulty than Chla estimates alone. Consequently, at present, virtually no data exists regarding the suite of VOCs released to the high Arctic atmosphere as a function of the in-situ microbial community composition. The included dataset contains algal pigment concentrations found in samples collected during this expedition. Not only do these data provide estimates of phytoplankton community biomass, they also begin to shed light on the phytoplankton community composition, as taxonomic groups can be identified (or at least estimated) by the presence of a few indicating pigments. Because most of these samples were collected in the same location, but over time, we begin to gain insight into the shift of the phytoplankton community composition from the summer maximal biomass (August) to the declining community as autumn conditions result in lower nutrient and light levels and increased ice cover (September). Over the course of this expedition, CTD casts were made to collect samples from 5-200 meters , to adequately sample the photic zone. Casts were made at the marginal ice zone, as well as on an almost-daily basis at the mooring location in the high Arctic Ocean. |
format |
Dataset |
author |
DiTullio, Giacomo Lee, Peter |
author_facet |
DiTullio, Giacomo Lee, Peter |
author_sort |
DiTullio, Giacomo |
title |
Algal pigment concentrations, High Arctic, August-September 2018 |
title_short |
Algal pigment concentrations, High Arctic, August-September 2018 |
title_full |
Algal pigment concentrations, High Arctic, August-September 2018 |
title_fullStr |
Algal pigment concentrations, High Arctic, August-September 2018 |
title_full_unstemmed |
Algal pigment concentrations, High Arctic, August-September 2018 |
title_sort |
algal pigment concentrations, high arctic, august-september 2018 |
publisher |
Arctic Data Center |
publishDate |
2019 |
url |
https://dx.doi.org/10.18739/a2028pd2h https://arcticdata.io/catalog/view/doi:10.18739/A2028PD2H |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean oden Phytoplankton Sea ice |
genre_facet |
Arctic Arctic Ocean oden Phytoplankton Sea ice |
op_doi |
https://doi.org/10.18739/a2028pd2h |
_version_ |
1766321286854737920 |
spelling |
ftdatacite:10.18739/a2028pd2h 2023-05-15T14:50:15+02:00 Algal pigment concentrations, High Arctic, August-September 2018 DiTullio, Giacomo Lee, Peter 2019 text/xml https://dx.doi.org/10.18739/a2028pd2h https://arcticdata.io/catalog/view/doi:10.18739/A2028PD2H en eng Arctic Data Center EARTH SCIENCE>OCEANS>OCEAN CHEMISTRY>PIGMENTS Arctic Ocean Phytoplankton Chlorophyll dataset Dataset 2019 ftdatacite https://doi.org/10.18739/a2028pd2h 2021-11-05T12:55:41Z This project was conducted as a part of a United States-Swedish Joint Arctic Research Initiative. The goal of this initiative involved mooring the Icebreaker (IB) Oden to an ice floe in the inner pack ice in the high Arctic Ocean, and monitoring key oceanic-atmospheric parameters as the ice drifts. The cruise timeline (August through September) was chosen to highlight the transitional time period from the summer maximum in microbial biomass to declining stocks as autumn conditions result in lower nutrient and light levels, concomitant with the onset of freezing conditions. Biogenic aerosol production and fluxes are key research parameters in understanding the formation of Cloud Condensation Nuclei (CCN) and their impacts on the radiation budget of the Arctic Ocean. At present, there exists a paucity of data regarding how microbial community composition might change in the high Arctic Ocean, especially with respect to changes in the production of volatile aerosol precursor compounds as pelagic microbial communities replace sympagic communities. Specifically, this project focused on linking microbial community structure with the oceanic-atmosphere fluxes of Volatile Organic Carbon compounds (VOCs) emitted from various oceanic and pack ice ecosystems. The role of diminishing sea ice cover in the Arctic Ocean will significantly impact biogenic aerosol production and fluxes via changes in microbial community structure and the release of VOCs. At present, however, the scarcity of in-situ oceanic VOC measurements available from the high Arctic Ocean prevents the development of robust models correlating phytoplankton biomass with VOCs and their impact on aerosol production. For instance, most current models utilize satellite Chlorophyll a (Chla) imagery for estimating phytoplankton biomass (e.g. Gabric et al. 2014; Becagli et al. 2016). It is also well recognized that high concentrations of sea surface chromophoric dissolved organic matter (CDOM) can significantly bias remotely-sensed Chla concentrations, especially when Chla levels are <0.5 milograms per meter cubed (mg m-3) (Matsuoka et al. 2017). In addition to the bias in estimating in-situ phytoplankton biomass from satellite-derived Chla, the contribution made by oceanic VOC fluxes to the atmospheric aerosol optical depth (e.g. Gabric et al., 2002) is unknown. Moreover, incorrect estimates of the oceanic Mixed Layer Depth (MLD) using climatological datasets and/or subsurface Chla maximum can further compound the errors associated with attempting to correlate phytoplankton integrated water column production with estimates of biomass derived using satellite Chla algorithms (Arrigo et al., 2011). As a result, questions remain regarding the reliability of using Chla estimates as a surrogate to estimate the organic carbon enrichment in submicron marine aerosols (Rinaldi et al. 2013). Hence, models that use satellites over relatively large areal expanses in the Arctic may be biased with regards to estimates of biomass, net primary production and as a result correlations to biogenic aerosol (Arrigo et al., 2011, Becagli et al., 2016). More importantly, however, total Chla biomass is not the only important variable affecting the production of oceanic biogenic VOCs and aerosols. The microbial community composition and physiology will not only affect the cell-specific production rate of precursor biogenic aerosol compounds, but also the secondary transformations of those compounds. Furthermore, determining VOCs or phytoplankton functional groups from space are both fraught with even more difficulty than Chla estimates alone. Consequently, at present, virtually no data exists regarding the suite of VOCs released to the high Arctic atmosphere as a function of the in-situ microbial community composition. The included dataset contains algal pigment concentrations found in samples collected during this expedition. Not only do these data provide estimates of phytoplankton community biomass, they also begin to shed light on the phytoplankton community composition, as taxonomic groups can be identified (or at least estimated) by the presence of a few indicating pigments. Because most of these samples were collected in the same location, but over time, we begin to gain insight into the shift of the phytoplankton community composition from the summer maximal biomass (August) to the declining community as autumn conditions result in lower nutrient and light levels and increased ice cover (September). Over the course of this expedition, CTD casts were made to collect samples from 5-200 meters , to adequately sample the photic zone. Casts were made at the marginal ice zone, as well as on an almost-daily basis at the mooring location in the high Arctic Ocean. Dataset Arctic Arctic Ocean oden Phytoplankton Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean |