5 record(s)
Type of resources
Contact for the resource
Provided by
From 1 - 5 / 5
  • Relevant spatial datasets for mapping pressures were identified and collated. Pressures were categorised as resource extraction and use, pollution, habitat modification, climate, and ‘other’. Pressures included Commonwealth trawl fisheries effort, aquaculture infrastructure, location of oil and gas infrastructure, historical shipping and pollution data, location of historical seismic operations, cyclone intensity, spoil dumping, sewage outfalls, location of ports, and tourism operations. Two main pressure maps were derived i) an additive pressure hotspots map, which gives higher weight to areas with multiple pressures of high risk; and, ii) a multiplicative hotspot pressure map, which gives lower weighting to areas with multiple low risk pressures. Areas of high risk were identified, and thus possibly high benefit for management versus low risk or low associated benefit for mitigation. The information generated needs to be considered alongside robust species distribution data and interaction matrices for effective decision-making.

  • Categories    

    The Southern Ocean has been disproportionately affected by climate change and is therefore an ideal place to study the influence of changing environmental conditions on ecosystems. Changes in the demography of predator populations are indicators of broader shifts in food-web structure, but long-term data are required to study these effects. Southern elephant seals (Mirounga leonina) from Macquarie Island have consistently decreased in population size while all other major populations across the Southern Ocean have recently stabilised or are increasing. Two long-term mark-recapture studies (1956-1967 and 1993-2009) have monitored this population, which provides an opportunity to investigate demographic performance over a range of climatic conditions. This provides insights on individual vital rates of known-age seals from Macquarie Island over extensively long timeseries.

  • Categories  

    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.

  • 'Weather@home ANZ' is a global citizen science distributed computing project being run as part of the Oxford-based 'weather@home' project, which is part of ''. In this experiment, a detailed limited area (regional) climate model is embedded within the less detailed 'driving' global model. This higher-resolution regional model is able to tell us in unprecedented detail about potential changes to patterns of weather as climate changes. In the initial 'weather@home' experiment launched in 2010, the project team released this regional modelling capability for three regions: Europe, Southern Africa and the Western USA. This capability has been extended to other regions around the world and the first such new region to be developed was the Australasian region encompassing Australia, New Zealand and surrounding areas, which was launched to the public in 2014. This particular part of the project - 'weatherathome ANZ' - has received support from the University of Oxford (U.K.), the U.K. Met. Office, the Universities of Melbourne and Tasmania (Australia), the Tasmanian Partnership for Advanced Computing and the New Zealand National Institute for Water and Atmospheric Research (NIWA). 'weather@home' has also been supported by Microsoft Research.

  • Categories    

    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.