Data for Boyd et al. (2023) 'Controls on polar Southern Ocean deep chlorophyll maxima: viewpoints from multiple observational platforms'

This record presents data used in the paper 'Controls on polar Southern Ocean deep chlorophyll maxima: viewpoints from multiple observational platforms,' Philip W Boyd 𝘦𝘵. 𝘢𝘭., submitted to Global Biogeochemical Cycles, November 2023. All methods for the following datasets are detailed and cross-referenced in the paper. Data were collected from a range of methods, including: • vertical profiles (from 1 m resolved profiling using sensors on a CTD rosette: temperature, salinity, chlorophyll fluorescence, transmissivity - all calibrated) • vertical profiles (from discrete samples collected from CTD rosette or trace metal clean rosette, for nutrients, chlorophyll, POC, dissolved and particulate iron, active fluorescence, net primary productivity, biological iron uptake) • tow-body sections (undulating tow body (Triaxus) for temperature, salinity, chlorophyll fluorescence, transmissivity (and the ratio of chlorophyll fluorescence, transmissivity) • time-series observations from a robotic profiling float (BGC-ARGO) for temperature, salinity, chlorophyll fluorescence, and transmissivity).

GRACE time series of Antarctic Ice Sheet mass change 2002-2021, and related climate datasets

Data pertain to analysis of GRACE time series of mass change in both gridded and basin format. The GRACE data are based on the COST-G solution obtained from http://gravis.gfz-potsdam.de/home. Both 50km regular gridded data and basin-level time series are included, as well as the SAM and ENSO climate indices on which the regressions were based. The gridded datasets provided here include derived quantities from the regressions such as trends, uncertainties, and regression coefficients in NetCDF format.

Gridded SAM and ENSO coefficients derived from satellite altimeter data over the Antarctic Ice Sheet, 2002-2020

The data result from an analysis of gridded satellite altimetry time series of ice surface elevation for the Antarctic Ice Sheet. Multiple linear regression is performed, including parameters associated with the cumulative sum of each of the Southern Annular Mode (SAM) and El Nino/Southern Oscillation (ENSO). The gridded data include the original data and the derived parameters and statistical values. Four grids are provided. Two grids are from separate regressions performed on data after applying one of two different spatial smoothing filters (10 km and 200 km Gaussian functions). Two further grids are from regressions after subtracting one of two firn densification models from the 10 km-smoothed altimetry data.

East Antarctic Polynyas: Seal's data

This is a collection of data in East Antarctica from Southern Elephant seal's between 2004 and 2009. The monthly data set has been further classified by polynya and year. Additionally, we provide a dataset of the polynyas contours defined following a criteria of 75% of sea-ice concentration for each individual month between 2004 and 2019. Data are provided in .mat format

SR3 2018 Particulate Iron Data

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.

Climate Change Risk Assessment for Marine Predators Data

Globally, terrestrially-breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to assess likely climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. Our results identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes as well as certain eared seal, albatross, and penguin species were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazard criteria, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.