This dataset consists of hyperspectral particulate absorption, particulate attenuation, and the first order (calculated) scatter coefficient from a Wetlabs Absorption and Attenuation Sensor (ACS). Data was collected from October 8th to November 1st 2023 aboard the RV Investigator (IN2023_V06). This voyage focused on sampling mesoscale eddies and across frontal features in a strong ecologically significant west boundary current, the East Australian Current (EAC). Throughout the cruise, the sensors continuously measured surface waters through the ships underway system, measuring 87 wavelengths (from 400-735 nm, with ~3 nm spacing) at a rate of 25 times per second. The data was later binned to 30 second intervals and aligned with the ships underway system (data for this can be found here: https://www.marine.csiro.au/data/trawler/survey_details.cfm?survey=IN2023_V06). Further information on the methodology for data acquisition and cleaning of the ACS data can be found in Mears et al., 2026.

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.

Zooplankton are important component of the Southern Ocean ecosystem yet so little is known about the distribution of most species and how this has changes through time. The project used existing data collect from the Southern Ocean Continuous Plankton Recorder Program (https://data.aad.gov.au/aadc/cpr/index.cfm). CPR data from 2000 to 2016 was extracted from the database and paired with environmental data (SST, SST anomaly, IOD, SAM, mixed layer depth). Hierarchical Models of Species Communities (HMSC) was used to model the zooplankton community to make inferences and predictions on the distribution of species and how they have changed through time.