IMAS Metadata Catalogue
PHYTOPLANKTON
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This dataset provides observation-informed latitudinal estimates of apparent grazing parameters used to constrain community-integrated zooplankton grazing dynamics. The products were developed to represent large-scale variation in zooplankton grazing using three independent approaches that draw on observational datasets, empirical grazing relationships and inverse modelling. The first estimate combines latitudinal patterns in zooplankton community composition with empirically derived grazing characteristics. Zooplankton biomass distributions were informed by the MAREDAT database and the statistically interpolated biomass distribution model of Clerc et al. (2024), while grazing parameters were derived from laboratory dilution experiments. Micro- and mesozooplankton contributions were combined according to their relative abundance and empirical grazing characteristics, with temperature-dependent adjustment of grazing parameters. Two additional estimates were derived from inverse-modelling experiments using the WOMBAT biogeochemical model (Rohr et al., 2024). Grazing dynamics were optimised to reproduce satellite-observed phytoplankton phenology while physical transport and bottom-up environmental controls were constrained. Independent optimisations were undertaken using satellite-derived phytoplankton carbon biomass from MODIS backscatter and chlorophyll concentration from VIIRS ocean colour, producing separate carbon-based and chlorophyll-based estimates of community-integrated grazing dynamics. Together, the three products provide alternative observation-informed estimates of the latitudinal structure of apparent zooplankton grazing parameters.
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This archive includes post-processed model out and code for visualisation pertaining the to the evolution of phytoplankton loss rates in CMIP6 model. The core data set is recomputed diagnostic loss terms for grazing and non grazing losses across 11 CMIP6 models as well as a diagnostic deconstruction of the drivers of evolving loss rates.
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This file contains data and associated R code for producing the figures, tables and analysis/models within the manuscript Ferderer et al., Carbonate chemistry fitness landscapes inform diatom resilience to future perturbations. Data was collected at IMAS by Aaron Ferderer.
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Zooplankton samples were collected at inshore coastal waters of south eastern Tasmania, between the years 1971 and 1972. Three stations were selected to cover the D'Entrecasteaux Channel, mouth of the Derwent River and the Storm Bay areas. Surface, midwater and bottom zooplankton samples were collected monthly for a period of twelve months during the day as well as night time, using horizontal tows. Data for temperature and salinity were also obtained from the stations.
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Zooplankton samples were collected at two sites in south eastern Tasmania, between the years 2000 and 2001 using two types of plankton net. Samples were collected using horizontal hauls during the daytime only. All copepods, salps and chaetognaths were identified and enumerated.
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Zooplankton samples were collected at ten stations within the Derwent River estuary, in south eastern Tasmania, between the years 1973 and 1974. Temperature and salinity data was collected at the same time.
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These files contain the data recorded from a mesocosm experiment conducted in Bergen, Norway 2022 which assessed the effect of simualted mineral-based (silicate or calcium) ocean alkalinity enhancement (OAE) on diatom silicification. Ten mesocosms were used in total, divided into two groups either the silicate- or calcium based group and alkalinity was increased by either 0, 150, 300, 450 or 600 µmol L-1 above natrually occuring levels. The PDMPO-fluorescence (an appropriate proxy for silicification) of diatoms was recorded on eight seperate days during the experiment. Accompanying data includes measured; macronutrients (nitrate, nitrite, phophate, silicate), total alkalinity, biogenic silica in the water column and sediment trap.
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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.
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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.
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Ocean alkalinity enhancement (OAE) is an emerging carbon dioxide removal (CDR) strategy that leverages the natural processes of weathering and acid neutralisation to durably store atmospheric CO2 in seawater. OAE can be achieved with a variety of methods, all of which have different environmental implications. One widely considered method utilizes electrochemistry to remove strong acid from seawater, leaving sodium hydroxide (NaOH) behind. This study evaluates the impacts of OAE via NaOH (NaOH-OAE) on a coastal plankton bloom, with particular focus on how macronutrient regeneration in the aftermath of the bloom responds to the perturbation. To investigate this, we enclosed a natural coastal phytoplankton community, including coccolithophores, in nine microcosms. The microcosms were divided into three groups: control, unequilibrated (512.1 ± 2.5 µmol kg-1 alkalinity increase) and equilibrated (499.3 ±5.65 µmol kg-1 alkalinity increase). Light was provided for 11 days to stimulate a bloom (light phase) and lights were turned off thereafter to investigate alkalinity and nutrient changes for 21 days (dark phase). We found no detectable effect of equilibrated NaOH-OAE on phytoplankton community and bacteria abundances determined with flow cytometry but observed a small yet detectable restructuring of phytoplankton communities under unequilibrated conditions. NaOH-OAE had no significant effect on alkalinity, NOx- and phosphate regeneration, but increased silicate regeneration by 64% over 21 days under darkness in the unequilibrated treatments where seawater pH was highest (8.65 relative to 7.92 in the control). Additional dissolution experiments with two diatom species supported this outcome on silicate regeneration for one of the two species, thereby suggesting that the effect is species specific. Our results point towards the potential of NaOH-OAE to influence regeneration of silicate in the surface ocean and thus the growth of diatoms, at least under the very extreme NaOH-OAE conditions simulated here.