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Field of Research : Natural Resource Management
Australian State/Territory : VIC
Research Topic : Program evaluation
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  • Researchers (18)
  • Funded Activities (5)
  • Organisations (6)
  • Funded Activity

    Linkage Projects - Grant ID: LP130100311

    Funder
    Australian Research Council
    Funding Amount
    $612,756.00
    Summary
    Adaptive ecotyping of the toxic cyanobacterium Cylindrospermopsis raciborskii to predict its invasive capacity. We change the world while other organisms adapt to these new conditions. Cyanobacteria (blue green algae) increasingly dominate water bodies that were previously free of these harmful blooms. To minimise the spread of these algae, this project will study the genetic basis that determines how rapidly they can evolve and adapt to a changing planet.
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    Funded Activity

    Discovery Projects - Grant ID: DP0666131

    Funder
    Australian Research Council
    Funding Amount
    $160,000.00
    Summary
    Australian transplants: the political ecology of Acacia exchanges across the Indian Ocean. The case studies and conclusions arising out of this project will help environmental practitioners and policymakers make informed decisions about exotic plant introductions, balancing needs to 'safeguard' Australia on the one hand with interests in 'improving' Australia on the other. The project's innovative focus on the comings and goings of a single plant genus also makes a significant contribution to .... Australian transplants: the political ecology of Acacia exchanges across the Indian Ocean. The case studies and conclusions arising out of this project will help environmental practitioners and policymakers make informed decisions about exotic plant introductions, balancing needs to 'safeguard' Australia on the one hand with interests in 'improving' Australia on the other. The project's innovative focus on the comings and goings of a single plant genus also makes a significant contribution to Australian environmental studies, by generating richer public discussion of the question of native versus introduced plants. Finally, it will produce new knowledge about our iconic wattles (made accessible through a book), increase international collaboration across the Indian Ocean, and train two postgraduate students.
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    Funded Activity

    Special Research Initiatives - Grant ID: SR0354677

    Funder
    Australian Research Council
    Funding Amount
    $10,000.00
    Summary
    Sustainable terrestrial and riverine systems through integrated assessment and modelling. Australia must take the lead internationally in sustainability assessment and management; it hosts both the problems and expertise, and is proactive in integrating research and management. This Initiative unites, for the first time, leading researchers from all relevant disciplines to advance our knowledge for achieving sustainable terrestrial and riverine systems (STARS). The intended network can produce a .... Sustainable terrestrial and riverine systems through integrated assessment and modelling. Australia must take the lead internationally in sustainability assessment and management; it hosts both the problems and expertise, and is proactive in integrating research and management. This Initiative unites, for the first time, leading researchers from all relevant disciplines to advance our knowledge for achieving sustainable terrestrial and riverine systems (STARS). The intended network can produce assessments, strategies and policy directions that are objective, adaptive and inclusive. It can evaluate trade-offs between sustainability strategies, integrating research and outcomes, making them accessible to managers. It will build a coordinated research capability that directly supports Australia's goal of ecologically sustainable development.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180101151

    Funder
    Australian Research Council
    Funding Amount
    $484,189.00
    Summary
    Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection .... Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection in water-quality data and generating predictions of sediment and nutrient concentrations throughout river networks in near-real time. This will represent a fundamental increase in scientific knowledge, which will be immediately useful in the domains of aquatic science, environmental monitoring, and statistics.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100495

    Funder
    Australian Research Council
    Funding Amount
    $315,000.00
    Summary
    Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rath .... Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rather than concentrating on individual sites. It intends to underpin a new predictive capacity including response to land use and management changes and climatic variations based on long-term data sets, as well as a water quality prediction capability. It is intended that the models developed will jointly model a range of inter-related water quality parameters.
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