EARTH SCIENCE | OCEANS | OCEAN CHEMISTRY
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This dataset contains temporal and compositional data on the Southern Ocean Time Series (SOTS) 1000 m depth sediment trap between 2010 and 2019. This study has added new data on 40 trace metals and isotopes (TEIs) in addition to the sinking particle flux data available on the Australian Ocean Data Network (AODN portal) and published in Wynn-Edwards et al. (2020; Frontiers in Earth Science). The TEI data was collected by strong acid digestion of archived SOTS 1000 m sinking particle samples collected from sediment trap deployments from 2010 to 2019. Following digestion, sinking particle samples were analysed for TEI concentration at the UTAS Central Science Laboratory using High Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS). The data presented here contains TEI concentration data, elemental fluxes calculated from the sediment trap mass fluxes (Wynn-Edwards et al., 2020) and a range of lithogenic particle fluxes derived from various upper continental crust concentrations reported in the literature. Several iterations of lithogenic flux are included for key lithogenic tracers Al, Fe, Ti and Th, with some mean fluxes of the combination of these tracers included. Here, several multi-tracer lithogenic fluxes are included based on the inclusion of Th concentrations using isotope dilution or linear calibration methods. The final lithogenic fluxes used in the publication are linearly calibrated Al, Ti, Fe and Th flithogenic fluxes and the mean value of these four tracers. Additional V and Pb tracer concentrations were used to assess anthropogenic influences. These results were used to estimate seasonal and interannual lithogenic particle flux in the subantarctic Southern Ocean. Additionally, particle composition, sources and provenance were examined using the attached data. The findings were used to provide an estimate of dust deposition in the subantarctic Southern Ocean south of Australia, contextualised by particle trajectory reanalysis, satellite data products and biogeochemical processes.
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The aim of this project was to estimate the iron recycling and export potential of Antarctic krill faecal pellets. To determine this, we firstly determined the sinking rate of the faecal pellets, characteristics which may influence the sinking rate (e.g., density, length and diameter), and then determined the portion of the total iron in the faecal pellets that is leached over a 12 h period under a continuous flow of seawater. The data sets that can be accessed here are: 1. Faecal pellet characteristics, including the raw and analysed data 2. The dry weight and length of faecal pellets used for total Fe estimation 3. Raw and final iron leachate data
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This dataset contains oceanographic profiles of dissolved iron (DFe) at the Southern Ocean Time Series collected during voyages IN2018_V02 and IN2019_V02 aboard RV Investigator, CSIRO Marine National Facility. Profiles of DFe were collected using a 12-bottle trace metal rosette (TMR; Seabird Scientific) equipped with acid washed, externally sprung Niskin bottles (Ocean Test Equipment). GEOTRACES cleaning, sampling, analytical and intercalibration procedures (Cutter et al., 2017) were followed where possible. Full sampling and analytical details for these profiles can be found in Ellwood et al., (2020a) and Ellwood et al., (2020b)
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The following dataset contains particulate iron data collected during the 2018 occupation of the CLIVAR SR03 (GEOTRACES GS01) transect south of Tasmania, Australia. This data is used ancillary to measurements of dissolved iron in the same transect for a manuscript in preparation by Traill et al. (2023). While modelling efforts have furthered our understanding of marine iron biogeochemistry and its influence on carbon sequestration, observations of dissolved iron (dFe) and its relationship to physical, chemical and biological processes in the ocean are needed to both validate and inform model parameterisation. Where iron comes from, how it is transported and recycled, and where iron removal takes place, are critical mechanisms that need to be understood to assess the relationship between iron availability and primary production. To this end, hydrographic and trace metal observations across the GO-SHIP section SR3, south of Tasmania, Australia, have been analysed in tandem with the novel application of an optimum multiparameter analysis. From the trace-metal distribution south of Australia, key differences in the drivers of dFe between oceanographic zones of the Southern Ocean were identified. In the subtropical zone, the source of dFe was constrained by waters advected off the continental shelf, and by remineralization in recirculated modified mode and intermediate water masses of the Tasman Outflow. In the subantarctic zone, the seasonal replenishment of dFe in Antarctic surface and mode waters appears to be sustained by iron recycling in the underlying mode and intermediate waters. In the southern zone, the dFe distribution is likely driven by dissolution and scavenging by high concentrations of particles along the Antarctic continental shelf and slope, entrained in high salinity shelf water. This approach to trace metal analysis may prove useful in future transects for identifying key mechanisms driving marine dissolved trace metal distributions.
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This dataset contains the input and output data for an extended optimum multiparameter analysis (eOMP). Input data for parameters are given (temperature, salinity, oxygen, nitrate, phosphate and silicate), as obtained from the cited CSIRO open access CTD bottle data for the 2018 SR3 occupation. Output parameters are the proportional contribution of 8 water masses that were defined in the eOMP analysis. The output remineralization estimate, Delta-O, is also given. All data are referenced to depth and geographical position (latitude, longitude) from corresponding CTD bottle data. The eOMP used here was configured following Pardo et al. (2017). Details on the equations, parameterization and end-members that characterize the regional oceanography can also be found in the Supplementary Materials of Traill et al. (2023), including the robustness of the OMP analysis and the uncertainties of both the SWTs’ contributions and the ΔO parameter (Sections S1.2 and S1.3, Table S1, Table S2, Table S3).