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2026 ARDC Annual Survey is now open!

The Australian Research Data Commons (ARDC) invites you to participate in a short survey about your interaction with the ARDC and use of our national research infrastructure and services. The survey will take approximately 5 minutes and is anonymous. It’s open to anyone who uses our digital research infrastructure services including Reasearch Link Australia.

We will use the information you provide to improve the national research infrastructure and services we deliver and to report on user satisfaction to the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS) program.

Please take a few minutes to provide your input. The survey closes COB Friday 29 May 2026.

Complete the 5 min survey now by clicking on the link below.

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Socio-Economic Objective : Land and water management
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Research Topic : CELL BIOLOGY
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  • Funded Activity

    Special Research Initiatives - Grant ID: SR0354740

    Funder
    Australian Research Council
    Funding Amount
    $10,000.00
    Summary
    CaGaWaLo: regulation of carbon gain and water loss by woody vegetation. Trees and shrubs are widely perceived as central to solving problems of national and international significance. Seed funding is sought to facilitate establishment of a research network focused on their ability to sequester carbon and transmit water to the atmosphere. The proposed network is broadly based in plant physiology and ecology and contains a strong cross-section of leading international expertise in relevant sub- .... CaGaWaLo: regulation of carbon gain and water loss by woody vegetation. Trees and shrubs are widely perceived as central to solving problems of national and international significance. Seed funding is sought to facilitate establishment of a research network focused on their ability to sequester carbon and transmit water to the atmosphere. The proposed network is broadly based in plant physiology and ecology and contains a strong cross-section of leading international expertise in relevant sub-disciplines. By leveraging the huge pool of international expertise and focusing on a range of scales (from molecular to biosphere scales), this network will yield new ideas and approaches that will produce outputs and outcomes of national significance.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559246

    Funder
    Australian Research Council
    Funding Amount
    $260,000.00
    Summary
    Community-level selection: Empirical tests in a microbial system. Given the profile of the question of community-level selection as a long-running controversy, the main benefit of the proposed work, which will critically test the idea in an empirical system, will be to increase recognition of Australia's position as a research nation in evolutionary biology. In exploring mechanisms of floc formation, a key component of wastewater treatment, the work will establish important foundations for impro .... Community-level selection: Empirical tests in a microbial system. Given the profile of the question of community-level selection as a long-running controversy, the main benefit of the proposed work, which will critically test the idea in an empirical system, will be to increase recognition of Australia's position as a research nation in evolutionary biology. In exploring mechanisms of floc formation, a key component of wastewater treatment, the work will establish important foundations for improving the efficiency of wastewater treatment. Improvement in performance of only a few percent will bring important economic savings. This is evidenced by recent commitment of >$US 230 billion to improving the efficiency of wastewater treatment in Germany, Italy and Spain over 5 years.
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    Funded Activity

    Linkage Projects - Grant ID: LP0454287

    Funder
    Australian Research Council
    Funding Amount
    $323,654.00
    Summary
    Cellular automata model of forest stands to predict size-class distribution and survival. Existing forest growth models predict well stand level processes such as growth. However, they provide little information on forest structure and how this affects commercial forest products, risks of growing plantations and stand dynamics that determine carbon sequestration and water-use and result in age-related decline in productivity and self-thinning. By using newly developed technology to quantify in .... Cellular automata model of forest stands to predict size-class distribution and survival. Existing forest growth models predict well stand level processes such as growth. However, they provide little information on forest structure and how this affects commercial forest products, risks of growing plantations and stand dynamics that determine carbon sequestration and water-use and result in age-related decline in productivity and self-thinning. By using newly developed technology to quantify inter-tree competition, tree level resource supply, between tree genetic differences and the importance of chance events this project will draw on complexity theory to develop an innovative model that partitions stand level production to forecast the growth and size of individual trees.
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