Collection of processed BGC-Argo float profiles, used to calculate phytoplankton phenology from chlorophyll, phytoplankton carbon and nitrate.

During the RV Investigator Eddy voyage (IN2016_V02), we sampled a mesoscale cyclonic and anticyclonic eddy in the Southern Ocean south to Tasmania. We have collected water samples to analyse concentration of phytoplankton biomass and nutrients.

Biological ocean data collected from ships find reuse in aggregations of historical data. These data are heavily relied upon to document long term change, validate satellite algorithms for ocean biology and are useful in assessing the performance of autonomous platforms and biogeochemical models. There is a need to combine subsurface biological and physical data into one aggregate data product to support reproducible research. Existing aggregate products are dissimilar in source data, have largely been isolated to the surface ocean and most omit physical data. These products cannot easily be used to explore subsurface bio-physical relationships. We present the first version of a biological ocean data reformatting effort (BIO-MATE, https://gitlab.com/KBaldry/BIO-MATE). BIO-MATE uses R software that reformats openly sourced published datasets from oceanographic voyages. These reformatted biological and physical data from underway sensors, profiling sensors and pigments analysis are stored in an interoperable and reproducible BIO-MATE data product for easy access and use.

The effect of ocean alkalinity enhancement on a coastal phytoplankton community was assessed via a microcosm experiment. The effect of alkalinity enhancement in two scenarios (i) when enclosed seawater was in equilibrium with atmospheric CO2 and (ii) when enclosed seawater was not in equilibrium with atmospheric CO2 were explored. Alkalinity was increased by ~497 umol/kg in these two treatments and plankton communities, carbonate chemistry, dissolved inorganic nutrients, particulate matter and chlorophyll a dynamics monitored over a 22 day period where a spring bloom occurred.

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.

These files contain the metadata adopted and MATLAB code edited as well as visual plots generated in the Hongkun Honour's project. The data mainly includes the shipboard ADCP data and vertical cast type of Triaxus data collected from RV Investigator during the voyage IN2016V04 and IN2018T01 and satellite data (chlorophyll, sea level anomaly & sea surface temperature) collected from the IMOS website on the study region. The data was processed in MATLAB and then used to find visualization results, with the ultimate aim of exploring the potential of Triaxus in biogeochemistry.