Developing feasible in situ control of mange disease in wombats. Our goal is the development of feasible in situ control of sarcoptic mange in wombat populations. Globally important, the Sarcoptes scabiei mite infects >100 mammal species and is among the 50 most common human diseases, causing health, welfare and population impacts. This infection is treatable, and we will test a new treatment (fluralaner), develop new models to guide management, and conduct replicated field trials. This will ena ....Developing feasible in situ control of mange disease in wombats. Our goal is the development of feasible in situ control of sarcoptic mange in wombat populations. Globally important, the Sarcoptes scabiei mite infects >100 mammal species and is among the 50 most common human diseases, causing health, welfare and population impacts. This infection is treatable, and we will test a new treatment (fluralaner), develop new models to guide management, and conduct replicated field trials. This will enable science-based guidelines, advancing disease control, local eradication, and regulatory approval for wombats. Our research framework is adaptable to other mange-impacted species, and advance methods and theory for control of treatable disease in wildlife.Read moreRead less
Using animal-borne sensors to unravel East Antarctic coastal productivity. This project will examine the mechanisms underpinning the high productivity in Antarctic coastal polynyas, which are ice-free oases within the sea ice supporting abundant marine life. The study expects to generate essential new biochemical and biological observations using autonomous platforms to understand phytoplankton dynamics in these inaccessible habitats along Australia’s Antarctic Territory. Expected outcomes inclu ....Using animal-borne sensors to unravel East Antarctic coastal productivity. This project will examine the mechanisms underpinning the high productivity in Antarctic coastal polynyas, which are ice-free oases within the sea ice supporting abundant marine life. The study expects to generate essential new biochemical and biological observations using autonomous platforms to understand phytoplankton dynamics in these inaccessible habitats along Australia’s Antarctic Territory. Expected outcomes include novel insight into the role of iron supply from melting glaciers in supporting marine production. This should reduce the high uncertainty in prognoses for polynya activity under anthropogenic climate change, and support Australia’s international leadership in conservation and management of important Antarctic ecosystems.Read moreRead less
Are coastal wetlands vulnerable to bushfires? The ‘Black Summer’ fires burned extensive areas of coastal wetland not typically associated with fire impact. These wetlands rely upon plant growth and sediment delivery to respond to sea-level rise, processes which may be impacted by fire. This project aims to quantify the distribution and severity of fire impact, and establish post-fire vegetation and surface elevation trajectories. By integrating fire ecology and wetland science approaches, this p ....Are coastal wetlands vulnerable to bushfires? The ‘Black Summer’ fires burned extensive areas of coastal wetland not typically associated with fire impact. These wetlands rely upon plant growth and sediment delivery to respond to sea-level rise, processes which may be impacted by fire. This project aims to quantify the distribution and severity of fire impact, and establish post-fire vegetation and surface elevation trajectories. By integrating fire ecology and wetland science approaches, this project will ascertain the resilience of coastal wetlands to the cumulative impacts of fire and sea-level rise. Expected outcomes of this project include new, spatially-explicit fire management tools which will aid the sustainable, long-term management of coastal wetlands in a changing climate.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. Read moreRead less