IMAS Metadata Catalogue
Institute for Marine and Antarctic Studies
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Time series dataset of depth and activity recorded by miniPAT (Wildlife computers) popup satellite archival tags deployed on Kerguelen sandpaper skates (Bathyraja irrasa, n=24) caught in the Patagonian toothfish longline fishery in Heard Island and McDonald Islands. Tags were deployed to assess the post-release survival of skates in the fishery.
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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.
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Climate change is already influencing the worlds oceans. The Kerguelen Plateau as been identified as a climate change hotspot. This study aimed to predict and map how climate change will impact the distribution of demersal fishes. This study uses the published modeled (see https://doi.org/10.25959/4GVK-RM21) to take in predicted oceanographic variables under various IPCC climate change predictions. The oceanographic variables are provided by the FESOM model. Hierarchical models of species communities (HMSC) were used to make predictions in the demersal fish distribution for the 2020s, 2030s, 2040s, and 2050s. Predictions were mapped to explore the regions of change. This record contains all the environmental data, R code, and outputs from this project. Raw RSTS data needs to be requested from the AAD under the authorization of AFMA.
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This record provides an overview of the NESP Marine and Coastal Hub bridging study - "Future-proofing restoration & thermal physiology of kelp". For specific data outputs from this project, please see child records associated with this metadata. -------------------- Kelp forests create complex habitats that support a diverse and productive community of marine life. They underpin coastal food-webs, fisheries, and a suite of other ecosystem services including nutrient and blue carbon cycling. Across much of the world, kelp forests are in decline and under threat from stressors including urbanisation, overgrazing, ocean warming, and marine heatwaves driven by climate change. Australia’s giant kelp (Macrocystis pyrifera) forests are listed as a Threatened Ecological Community under the Environment Protection and Biodiversity Conservation Act 1999. Habitat restoration is a potential tool for the conservation and management of giant kelp ecosystems. Given the direct impacts of climate change and ocean warming, there is growing recognition of the need for habitat restoration to be ‘future proofed’. For restoration to be effective, the cause of habitat decline must be understood and overcome. This is problematic when climate change is driving habitat loss since it cannot be reversed or ameliorated prior to restoration. A previous NESP project led by this team (Project E7, Marine Biodiversity Hub) identified warm-tolerant strains of giant kelp from remnant patches in eastern Tasmania, where the species has experienced precipitous declines due to ocean-warming. These strains have high potential to assist with ‘future-proofing’ kelp forest restoration, however it is still unclear what the physiological mechanisms are that provide their improved thermal tolerance. It is also unknown whether cross-breeding the identified warm-tolerant giant kelp strains will affect and potentially improve their thermal tolerance capacity. This project explored the physiology of kelp thermal performance, specifically the mechanisms potentially responsible for the warm water tolerance identified in particular giant kelp strains. It confirmed the improved ability of the warm-tolerant strains to develop at stressful warm temperatures relative to normal giant kelp, and demonstrated for the first time that their improved thermal performance may extend to the development and fertilisation. The outcomes progress toward the identification of populations of Australian kelp that may be resilient to (or especially threatened by) ocean warming and climate change. Outputs • Ecophysiological measurements from laboratory experiments of warm-tolerant vs average giant kelp genotypes [dataset] • Final Project Report including a short summary of recommendations for policy makers of key findings [written]
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The demersal fish assemblages on the Kerguelen Plateau has changed through time. This study aimed to detect, quantify, and map these changes. This study uses existing data collected from the Random Stratified Trawl Survey (RSTS) program administered through the Australian Antarctic Divisions (AAD). Raw RSTS data between 2000 and 2016 was extracted from the AAD database. The RSTS data contains information on the abundance (catch per unit effort, CPUE) on fish. RSTS data were paired with environmental data to be modelled. Hierarchical models of species communities (HMSC) were used to make inferences and predictions in the changes of demersal fish distribution. This record contains all the environmental data, R code, and outputs from this project. Raw RSTS data needs to be requested from the AAD under the authorization of AFMA.
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The data is quantitative abundance of fish, megafaunal invertebrates and percent algal cover derived from underwater visual census methods involving transect counts at rocky reef sites around Tasmania. This dataset allows examination of changes in Tasmanian shallow reef faunal and floral communities over a decadal scale, with initial surveys conducted in 1992-1995, and again in 2006-2007. There are plans for ongoing surveys. An additional component was added in the latter study - a boat ramp study looking at the proximity of boat ramps and their effects of fishing. We analysed underwater visual census data on fishes and macroinvertebrates (abalone and rock lobsters) at 133 shallow rocky reef sites around Tasmania that ranged from 0.6 - 131 km from the nearest boat ramp. These sites were not all the same as those used for the comparison of 1994 and 2006 reef communities. The subset of 133 sites examined in this component consisted of only those sites that were characterized by the two major algal (kelp) types (laminarian or fucoid dominated). Sites with atypical algal assemblages were omitted from the 196 sites surveyed in 2006. This study aimed to examine reef community data for changes at the community level, changes in species richness and introduced species populations, and changes that may have resulted from ocean warming and fishing. The methods are described in detail in Edgar and Barrett (1997). Primarily the data are derived from transects at 5 m depth and/or 10 m depth at each site surveyed. The underwater visual census (UVC) methodology used to survey rocky reef communities was designed to maximise detection of (i) changes in population numbers and size-structure (ii) cascading ecosystem effects associated with disturbances such as fishing, (iii) long term change and variability in reef assemblages.
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The data is the quantitative abundance of megafaunal invertebrates derived from underwater visual census methods involving transect counts at rocky reef sites around Tasmania. This data forms part of a larger dataset that also surveyed fish abundance and algal cover for the area. The aggregated dataset allows examination of changes in Tasmanian shallow reef floral and faunal communities over a decadal scale - initial surveys were conducted in 1992-1995, and again at the same sites in 2006-2007. There are plans for ongoing surveys. An additional component was added in the latter study - a boat ramp study looking at the proximity of boat ramps and their effects of fishing. We analysed underwater visual census data on fishes and macroinvertebrates (abalone and rock lobsters) at 133 shallow rocky reef sites around Tasmania that ranged from 0.6 - 131 km from the nearest boat ramp. These sites were not all the same as those used for the comparison of 1994 and 2006 reef communities. The subset of 133 sites examined in this component consisted of only those sites that were characterized by the two major algal (kelp) types (laminarian or fucoid dominated). Sites with atypical algal assemblages were omitted from the 196 sites surveyed in 2006. This study aimed to examine reef community data for changes at the community level, changes in species richness and introduced species populations, and changes that may have resulted from ocean warming and fishing. The methods are described in detail in Edgar and Barrett (1997). Primarily the data are derived from transects at 5 m depth and/or 10 m depth at each site surveyed. The underwater visual census (UVC) methodology used to survey rocky reef communities was designed to maximise detection of (i) changes in population numbers and size-structure (ii) cascading ecosystem effects associated with disturbances such as fishing, (iii) long term change and variability in reef assemblages.
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Dataset collected during two field campaigns in the same Antarctic fast ice site (Cape Evans, November/December 2018-19) as part of the AGP and NZARI collaboration over the grant "On Thin Ice: An in situ surveillance system for sea-ice microbial communities". The fieldwork was designed to test the scientific potentials of the IMAS/AGP developed under-ice HI system for mapping temporally dynamic and spatially varying under-ice habitats. The dataset consists of 3 terabytes of HI data acquired both in-situ under a wide range of natural and manipulated light conditions, as well as ex-situ with data acquired using a newly developed ice core scanning approach. The in-situ data are in the form of scanned transects acquired with a HI system capturing transmitted natural sunlight while being deployed beneath sea-ice. The ex-situ data was collected using external light sources illuminating horizontal and vertical sections of extracted ice cores. The dataset includes auxiliary data such as RGB imagery, TriOS RAMSES under-ice irradiance, sky irradiance, and any other measurements or information required to process the data. Other auxiliary data collected include filtered samples of ice core sections for fluorometric Chlorophyll-a (Chl-a) extraction, pigment composition via HPLC (to be processed), and particulate absorption spectra. Media footage (e.g., under-ice ROV videography, under-ice 360 videos, campaign photography of the systems and science) is also included. The dataset includes pre-processed high-resolution under-ice imagery collected from the fast-ice zone using a Sony a6300 camera mounted on a custom under-ice sled system. The imagery was acquired to document the sea-ice underside and analyse spatial patterns associated with amphipod communities from a near-horizontal, grazer-level perspective (publications pending).
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The Maugean Skate Zearaja maugeana is a micro-endemic species known from only two isolated estuaries, Bathurst and Macquarie Harbours in southwestern/western Tasmania. This constitutes one of the most limited distributions of any known extant elasmobranch. As a result, the species is listed as ‘Endangered’ under the Threatened Species Protection Act (Tasmania) and the Environmental Protection and Biodiversity Conservation Act (Commonwealth). Even though it was first discovered in Bathurst Harbour, most of what is known about the species comes from the Macquarie Harbour population. Only four individuals have ever been reported in Bathurst Harbour, with the last known sighting occurring in 1992. This study used environmental DNA (eDNA) to determine the presence/absence of the Maugean skate in Bathurst Harbour on the southwest coast of Tasmania. Water samples were collected from the seafloor in Bathurst Harbour in November 2021 and February 2022, and in Macquarie Harbour (control samples) in December 2021. Samples were filtered using a self-preserving eDNA sampling system. Following each survey DNA from the samples was extracted and analysed through qPCR amplification. Mitochondrial primer pairs from two gene regions were used to detect the presence of Maugean skate DNA in the samples. Where possible, positive detections were sequenced, and their identity verified.
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Dataset collected at Cape Evans, Antarctica, November 2023 as part of a long-term NIWA benthic monitoring program under the Antarctica New Zealand event number K882A. The dataset includes multiple sea-ice and seafloor hyperspectral imaging transects (10-40 meters long) coupled with normal red, green, and blue (RGB) imagery from a dual camera machine vision system. The data were acquired using the remotely operated vehicle (ROV) HIcyBot system, funded by the Australian Centre for Excellence in Antarctic Research (ACEAS). A GNSS-integrated USBL transponder equipped onto the ROV allowed every frame of the high frequency hyperspectral imager to be timestamped via GPS clock to acoustically provided underwater position and attitude. The dataset also includes hyperspectral imaging scans of sampled/retrieved organisms found at the seafloor, to support habitat mapping algorithm development (e.g., algae, urchins, sea-stars, etc.). The ROV was tested as part of an ACEAS Program 2 subcomponent that involved the design of the new under-ice hyperspectral imaging and photogrammetric payload mounted onto the HIcyBot ROV. The overarching goal of the systems was to be able to acquire information of under the sea-ice sympagic and benthic communities (e.g., biomass and photophysiology) and deliver a multi-scale array of biophysical data that can be assimilated with known information in the region and monitor fine-scale change. Through the analysis of new and existing bio-optical under-ice data, the dataset aims to ultimately envisions the delivery of new monitoring tools and algorithms that can provide support for modelling efforts and reveal complex biophysical processes under a changing Antarctic Sea ice. ***NOTE: Data processing is still underway (April 2025). Please contact Emiliano.Cimoli@utas.edu.au for access to data.***