Surveys of abundance for Australian sea lions, New Zealand fur seals, little penguins, crested terns, short-tailed and flesh-foot shearwaters conducted from 2003-2012 in the Spencer Gulf, South Australia.

Data from 2003-2012 on the diet of Australian sea lions, New Zealand fur seals, and little penguins in the Spencer Gulf, South Australia.

Albatross and petrel populations have declined globally due to interactions with fishing operations. The survival of four albatross and two giant petrel species breeding on Macquarie Island is threatened and ongoing monitoring is essential to assess their conservation status and mitigate negative influences. Long-term studies are required to obtain reliable information on population size and productivity and age- and sex- related survival parameters. The birds' oceanic movements is also being investigated so that questions regarding temporal and spatial overlap with fisheries can be addressed. Demographic and population data collected for the 2012-13 breeding season on Macquarie Island for 4 species of albatross and 2 species of giant petrel are summarised in the annual report (pdf) and all data contained in tables therein or attached xlxs spreadsheets and access database. Data collected includes breeding census, breeding success, nest location, banding and resight data for the 2012-13 season. The Access database contains data from 1950-2012. 2013-2014 information are held in the 2013-2014 folder, which includes several excel spreadsheets, an updated access database, and a copy of the final report. 2014-2015 information are held in the 2014-2015 folder, which includes several excel spreadsheets, a copy of the report, and updated database tables. 2015-2016 information are held in the 2015-2016 folder, which includes several excel spreadsheets, a copy of the report, and updated database tables. 2016-2017 information are held in the 2016-2017 folder, which includes several excel spreadsheets. 2017-2018 information are held in the 2017-2018 folder, which includes several excel spreadsheets and a pdf document showing the location of nesting sites (waypoints provided in the excel files). 2018-2019 information are held in the 2018-2019 folder, which includes several excel spreadsheets and a pdf document showing the location of nesting sites (waypoints provided in the excel files). This project has replaced project 2569 (which in turn replaced project 751).

This study was carried out by Giulia Roncon as part of her PhD at IMAS. The study employed both archival and contemporary diving data, collected by six species of marine predators (three penguins and three seal species) from the Eastern Antarctic sector of the Southern Ocean, to clarify key questions, such as (i) are there differences and/or commonalities regarding the diving physiology and ecology of marine predators, and (ii) what are the main determinants and constrains that characterise the underwater behaviour of air-breathing vertebrates. This dataset is a compilation of data of several different studies carried out by different research teams in various locations and at various times. All TDRs were archival loggers that had to be retrieved to obtain the data. Thus, the animals had to be captured twice (deployment and retrieval). Details about the types of tags are listed in the dataset. Species used in the study were: Adelie Penguins Emperor Penguins King Penguins Fur Seals Southern Elephant Seals Weddell Seals

The predators of Centrostephanus rodgersii, were identified using remote video monitoring. Experiments were performed in two eastern Tasmanian regions, the Maria Island Marine Reserve (MIMR, 42° 35.26'S, 148° 3.03'E) and the Crayfish Point Research Reserve (CPRR, 42° 57.37'S, 147° 21.30'E). The impact of fishing on these predators, and ultimately on C. rodgersii, was examined by comparing survival of C. rodgersii on reefs inside no-take Marine Protected Areas (MPAs) (high predator biomass) relative to fished reefs (low predator biomass). The size-specific nature of predation interactions was examined in context of size-selective fishing pressures within the sea urchin's extended range.

Raw time series of depth, water temperature, light and swim speed. Stomach temperature and heart rate are available in some instances, but the data is sparse. Data was collected using time/depth recorders and satellite telemetry. Ancillary location was recorded from a separate logger.

Of the ~80 EPBC-listed Threatened and Migratory marine species known to occur in the North Marine Bioregion, 16 were identified as priority species through consultation with research end-users and experts. The priority group consisted of three sawfishes, two river sharks, Dugong, two inshore dolphins, six shorebirds and two turtles. Dwarf and then Green Sawfish had the most data gaps, indicating that these were the most poorly-known of the selected priority species in the North Marine Bioregion, and as such are a priority for research. These were followed (in order of data gaps) by the other river sharks and sawfishes, inshore dolphins, Hawksbill Turtle, Dugong, Olive Ridley Turtle, and shorebirds. Research assessing the relevance and impact of pressures was identified as a gap for all species. New data identified during the project can fill data gaps for all 16 species, and the analysis of these datasets can improve the accuracy of distribution maps, but new data collection is still required for all sharks and sawfishes, Hawksbill Turtle, and inshore dolphins to improve data coverage for distribution modelling and mapping. Phase 1 of the project involved a gap analysis with identified numerous new datasets, both published and unpublished, that are currently not incorporated into SPRAT profiles and distributions (see Table 5). This provided an opportunity to begin compiling and analysing this information to fill current data gaps, as well as identify targeted research needs for the future. Phase 2 of the project built on collaboration with data custodians to develop data sharing agreements for use of these datasets to construct spatial models to refine and update species distributions. Downloadable data and materials are a linked to in the 'online resources' section of this record. GIS online maps of species distributions are available at this WMS endpoint: https://geoserver.imas.utas.edu.au/geoserver/SDM/wms?request=GetCapabilities&service=WMS

Metadata record for data expected from ASAC Project 2940 See the link below for public details on this project. Public: The extent of Antarctic winter sea-ice influences all aspects of the Antarctic marine food-web. We will use natural variations in inter-annual ice extent, to assess how a key component of that ecosystem, the predators, use the sea ice zone. Core foraging areas and dietary signals for a key Antarctic predator (Antarctic fur seal) will be identified. We will use newly developed, technology to track the animals, and stable isotopes to examine tropic linkages. Combined with satellite-derived sea-ice data, this will lead to the development of a model to predict how changing sea-ice patterns will influence Antarctic marine predator communities. Project Objectives: 1. Use large samples of newly-developed (and tested) animal-borne miniature geolocating light level recorders to population level information on the spatial extent of movements of Antarctic fur seals, thereby quantifying the extent of the use of the winter pack-ice and associated waters by these abundant predators. 2. To quantify how changes in winter ice extent influence the location of core foraging areas for this species. 3. To develop models to investigate how changing ice conditions in the future will influence the movements of this species and to examine a range of climate-change scenarios. Taken from the 2007-2008 Progress Report: No field work was conducted at Macquarie Island in the last 12 months. This was due to the decision by the state government to not issue permits for the work. With the help of our colleagues from BAS we did however manage to deploy 20 GLS light loggers on Antarctic fur seals at South Georgia. Taken from the 2008-2009 Progress Report: Objective 1 has been revised to the study of Antarctic fur seals only (see below). Research is progressing well with 78 animals tracked in 2008 and a further 80 expected in 2009. Objectives 2 and 3 will follow once field data is available for both years (May 2010). Isotopic analysis of blood and whisker samples for the 2008 season will commence in May 2009 once samples have been received. Taken from the 2010-2011 Progress Report: Public summary of the season progress: This study has quantified the response of the Antarctic fur seal (Arctocephalus gazella) to inter-annual variation in oceanographic and winter ice conditions. We have measured the winter spatial foraging patterns of 66 adult females from three circum-Antarctic populations over two years (2008, 2009) during 114 trips to sea, while simultaneously recording in situ water temperature. Stable isotope analysis of fur seal blood and whisker samples indicates that adult females feed on a range of lower (krill) to higher (fish and squid) trophic levels across their winter range. Broad-scale habitat preferences across the range of the species indicate the importance of shelf, ice edge, frontal and oceanic and continental upwelling features in determining winter foraging movements.

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.

From the abstract of the referenced paper: Satellite telemetry data are a key source of animal distribution information for marine ecosystem management and conservation activities. We used two decades of telemetry data from the East Antarctic sector of the Southern Ocean. Habitat utilization models for the spring/summer period were developed for six highly abundant, wide-ranging meso- and top-predator species: Adelie, Pygoscelis adeliae and emperor, Aptenodytes forsteri penguins, light-mantled albatross, Phoebetria palpebrata, Antarctic fur seals, Arctocephalus gazella, southern elephant seals, Mirounga leonina, and Weddell seals, Leptonychotes weddellii. The regional predictions from these models were combined to identify areas utilized by multiple species, and therefore likely to be of particular ecological significance. These areas were distributed across the longitudinal breadth of the East Antarctic sector, and were characterized by proximity to breeding colonies, both on the Antarctic continent and on subantarctic islands to the north, and by sea-ice dynamics, particularly locations of winter polynyas. These areas of important habitat were also congruent with many of the areas reported to be showing the strongest regional trends in sea ice seasonality. The results emphasize the importance of on-shore and sea-ice processes to Antarctic marine ecosystems. Our study provides ocean-basin-scale predictions of predator habitat utilization, an assessment of contemporary habitat use against which future changes can be assessed, and is of direct relevance to current conservation planning and spatial management efforts. The data files provided here comprise the model predictions of the preferred habitat for each of the six species listed above, as well as the overlap results obtained by combining these six sets of results. See the paper for methods used to generate the model predictions and to combine the individual species results. File names for individual species are of the form results_SPP_TYPE.asc, where SPP is one of "afs" (Antarctic fur seal), "ap" (Adelie penguin), "ep" (emperor penguin), "lma" (light-mantled albatross), "ses" (southern elephant seal), or "ws" (Weddell seal. TYPE is either "mean" (mean estimate of habitat preference) or "iqr" (inter-quartile range of uncertainty in the estimate; see paper for details). Data values for individual species results are percentiles of the study area, so that values of 90% or higher are pixels corresponding to the most important 10% of habitat for that species, values of 80% or greater are the top 20% of habitat, and so on. The overlap results files are named overlay_results_mean.asc and overlay_results_iqr.asc. Values in these files represent the average of the top four individual species results in a given pixel (see paper for details).