The genomics of climate adaptation in eucalypts. This project aims to investigate validated, rapid and pragmatic solutions to managing plant and animal maladaptation caused by global environmental change. Using Australia’s iconic blue gum (Eucalyptus globulus), this project will test strategies for identifying the major climatic predictors of, and key genomic regions that underlie, adaptation to climate change. By integrating climate variables and genome sequences with field trial-derived trait ....The genomics of climate adaptation in eucalypts. This project aims to investigate validated, rapid and pragmatic solutions to managing plant and animal maladaptation caused by global environmental change. Using Australia’s iconic blue gum (Eucalyptus globulus), this project will test strategies for identifying the major climatic predictors of, and key genomic regions that underlie, adaptation to climate change. By integrating climate variables and genome sequences with field trial-derived trait and performance data from decades of research and thousands of trees, we will develop validated DNA-based tools for monitoring the rate of adaptation in our native forests and identifying climate-ready seed sources for environmental and industrial plantings.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Working with wind energy and forestry for effective eagle conservation. This project aims to reduce the impacts of wind turbines and disturbance from forestry activity on the Tasmanian wedge-tailed eagle. It will do this by understanding the flight behaviour, movements and mortality of eagles, and the behavioural responses of breeding birds to forestry-related disturbance. The project will build new knowledge and institutional partnerships that will be used to minimise impacts on the Tasmanian e ....Working with wind energy and forestry for effective eagle conservation. This project aims to reduce the impacts of wind turbines and disturbance from forestry activity on the Tasmanian wedge-tailed eagle. It will do this by understanding the flight behaviour, movements and mortality of eagles, and the behavioural responses of breeding birds to forestry-related disturbance. The project will build new knowledge and institutional partnerships that will be used to minimise impacts on the Tasmanian eagle population, and develop models for use in planning. This will safeguard Australia's largest eagle and improve the sustainability of energy and forest industries. This research will also provide a model for the resolution of similar problems elsewhere in the world.Read moreRead less
Will genetic rescue save the Tasmanian devil? This project aims to measure the long-term genetic impacts of the Save the Tasmanian Devil Program’s ‘Wild Devil Recovery’ initiative. The project will determine whether supplementing small populations with individuals that are genetically diverse reduces inbreeding depression. The project will also monitor the impact of supplementation on the evolutionary trajectory of Devil Facial Tumour Disease. The project will train a cohort of conservation scie ....Will genetic rescue save the Tasmanian devil? This project aims to measure the long-term genetic impacts of the Save the Tasmanian Devil Program’s ‘Wild Devil Recovery’ initiative. The project will determine whether supplementing small populations with individuals that are genetically diverse reduces inbreeding depression. The project will also monitor the impact of supplementation on the evolutionary trajectory of Devil Facial Tumour Disease. The project will train a cohort of conservation scientists to translate genetic data into management actions. The outputs will directly inform the management actions of the Tasmanian Department of Primary Industries Parks, Water and the Environment and will help shape other species recovery programs.Read moreRead less
Experimental translocations to understand and combat eastern quoll declines. The project aims to understand the causes of observed declines of the eastern quoll in Tasmania, and develop tools to safeguard this species in their last wild stronghold. The project will test the innovative approach of undertaking a series of experimental translocations at an early stage of a population decline. This approach will provide reliable information on the causes of observed declines, while simultaneously te ....Experimental translocations to understand and combat eastern quoll declines. The project aims to understand the causes of observed declines of the eastern quoll in Tasmania, and develop tools to safeguard this species in their last wild stronghold. The project will test the innovative approach of undertaking a series of experimental translocations at an early stage of a population decline. This approach will provide reliable information on the causes of observed declines, while simultaneously testing the effectiveness of translocations of captive-bred animals as a management tool for the species. It will also develop evidence-based protocols for undertaking captive-bred translocations, to improve the outcomes of eastern quoll recovery efforts as well as promoting early intervention for other declining species. Read moreRead less
Detecting and deciphering extinction dynamics under environmental change. This project aims to improve knowledge of extinction processes and impacts. It will use high-performance computing and museum collections to disentangle the ecological mechanisms that were integral in the initial decline and later extinction of Australia's unique mammals. Its significance is that it will establish the historical ranges and past population trajectories of Australian threatened mammals, pinpointing the combi ....Detecting and deciphering extinction dynamics under environmental change. This project aims to improve knowledge of extinction processes and impacts. It will use high-performance computing and museum collections to disentangle the ecological mechanisms that were integral in the initial decline and later extinction of Australia's unique mammals. Its significance is that it will establish the historical ranges and past population trajectories of Australian threatened mammals, pinpointing the combinations of ecological characteristics and threats that most affect risk of extinction from environmental change. Expected outcomes and benefits are new data and verified models to enrich conservation research and inform evidence-based solutions to better protect and recover some of Australia’s most threatened species.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100002
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes ....ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100992
Funder
Australian Research Council
Funding Amount
$426,216.00
Summary
A novel epigenetic clock tool to conserve Australia’s threatened seabirds. The aim is to develop a novel epigenetic technique for the demographic assessment of long-lived seabirds, including albatrosses and petrels, for application to the conservation of 11 threatened species breeding across Australia. A major innovation will be an affordable and fieldwork-friendly technique to demographically fingerprint any population, ending the large amount of guesswork currently necessary in management. The ....A novel epigenetic clock tool to conserve Australia’s threatened seabirds. The aim is to develop a novel epigenetic technique for the demographic assessment of long-lived seabirds, including albatrosses and petrels, for application to the conservation of 11 threatened species breeding across Australia. A major innovation will be an affordable and fieldwork-friendly technique to demographically fingerprint any population, ending the large amount of guesswork currently necessary in management. The outcome is expected to enable (i) scientists and wildlife managers to impute the impact of threats and management activities on seabird populations, allowing quantitative scenario modelling, and (ii) stakeholders to analyse numerous threats and optimise management responses to these through research-based decision-making.Read moreRead less
ARC Centre of Excellence for Plant Success in Nature and Agriculture. The ARC CoE for Plant Success in Nature and Agriculture will discover the adaptive strategies underpinning productivity and resilience in diverse plants and deepen knowledge of the genetic and physiological networks driving key traits. Using novel quantitative and computational approaches, the Centre will link gene networks with traits across biological levels, giving breeders an unparalleled predictive capacity. The Centre wi ....ARC Centre of Excellence for Plant Success in Nature and Agriculture. The ARC CoE for Plant Success in Nature and Agriculture will discover the adaptive strategies underpinning productivity and resilience in diverse plants and deepen knowledge of the genetic and physiological networks driving key traits. Using novel quantitative and computational approaches, the Centre will link gene networks with traits across biological levels, giving breeders an unparalleled predictive capacity. The Centre will accelerate technologies to transfer successful networks into crops and build legal frameworks to secure this knowledge. With a uniquely multidisciplinary team, the Centre will deliver new strategies to address the problems of food security and climate change, establishing Australia as a global leader in these areas.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