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Current Selection
Status : Active
Research Topic : Population Isolate
Field of Research : Freshwater Ecology
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Freshwater Ecology (4)
Ecology (3)
Population, Ecological and Evolutionary Genetics (3)
Community Ecology (1)
Conservation and Biodiversity (1)
Environmental Science and Management (1)
Invertebrate Biology (1)
Population Ecology (1)
Water Quality Engineering (1)
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Fresh, Ground and Surface Water Flora, Fauna and Biodiversity (3)
Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments (2)
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Documentation of Undescribed Flora and Fauna (1)
Ecosystem Adaptation to Climate Change (1)
Expanding Knowledge in the Biological Sciences (1)
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Water Allocation and Quantification (1)
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  • Researchers (34)
  • Funded Activities (4)
  • Organisations (27)
  • Active Funded Activity

    Discovery Projects - Grant ID: DP220102040

    Funder
    Australian Research Council
    Funding Amount
    $417,875.00
    Summary
    Rapid evolution, and the dynamics and stability of ecological communities. Population sizes of species go up and down and often we do not know why. This is a problem because changes in population size underpin more complex ecological change, and understanding why population sizes change affects our ability to manage environmental impacts, and threatened, harvested and pest species. The aim of this project is to discover how rapid evolution – evolution occurring over just a few generations – driv .... Rapid evolution, and the dynamics and stability of ecological communities. Population sizes of species go up and down and often we do not know why. This is a problem because changes in population size underpin more complex ecological change, and understanding why population sizes change affects our ability to manage environmental impacts, and threatened, harvested and pest species. The aim of this project is to discover how rapid evolution – evolution occurring over just a few generations – drives changes in population sizes of plants in Australian freshwater ecosystems. By focusing on this fundamental yet poorly understood process, our results promise to rewrite our understanding of the causes of change in ecological communities, while highlighting a unique and little studied component of Australia’s biota.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE190100636

    Funder
    Australian Research Council
    Funding Amount
    $401,202.00
    Summary
    Integrating genomics into native fish management to promote persistence. This project aims to improve predictions of the effects of environmental change on the long-term survival of wildlife, using native fish as a case study. By integrating genomics into biodiversity models, this project expects to generate fundamental knowledge of processes underpinning long-term survival and is a big advance on traditional biodiversity models that consider only occurrence or abundance. Expected outcomes inclu .... Integrating genomics into native fish management to promote persistence. This project aims to improve predictions of the effects of environmental change on the long-term survival of wildlife, using native fish as a case study. By integrating genomics into biodiversity models, this project expects to generate fundamental knowledge of processes underpinning long-term survival and is a big advance on traditional biodiversity models that consider only occurrence or abundance. Expected outcomes include insights into fish responses to environmental conditions and new tools to predict long-term survival of wildlife. These tools will guide cost-effective delivery of environmental water in the Murray-Darling Basin, and wider uptake should promote the long-term effectiveness of conservation efforts for many species.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190101848

    Funder
    Australian Research Council
    Funding Amount
    $475,000.00
    Summary
    Next-generation models to predict cyanobacteria harmful algal blooms. This project aims to address the need for improved predictions of cyanobacteria (blue-green algae) harmful algal blooms. Accurate predictions of blooms with computer models are important to support management strategies to prevent their occurrence. This project is expected to generate new knowledge of strain-level variation in cyanobacteria that leads to toxic blooms. This project will lead to new knowledge of the significance .... Next-generation models to predict cyanobacteria harmful algal blooms. This project aims to address the need for improved predictions of cyanobacteria (blue-green algae) harmful algal blooms. Accurate predictions of blooms with computer models are important to support management strategies to prevent their occurrence. This project is expected to generate new knowledge of strain-level variation in cyanobacteria that leads to toxic blooms. This project will lead to new knowledge of the significance of strain-level variation in cyanobacteria harmful algal blooms, how strains influence toxin production and models for prediction of bloom and toxins. The project will generate significant benefits for water security for the purposes human consumption and recreation, and ecosystem health.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200100381

    Funder
    Australian Research Council
    Funding Amount
    $495,820.00
    Summary
    Improving stream management using ecological modelling and DNA barcodes. Rivers and streams provide invaluable ecosystem services, yet are commonly degraded by human activities: a problem likely to be exacerbated by thermal and flow regimes being altered by climate change. Stream biodiversity is both a value and an indicator of ecological health: effective stream management requires prediction of biodiversity responses to natural environmental and human-impact gradients. By compiling a dataset o .... Improving stream management using ecological modelling and DNA barcodes. Rivers and streams provide invaluable ecosystem services, yet are commonly degraded by human activities: a problem likely to be exacerbated by thermal and flow regimes being altered by climate change. Stream biodiversity is both a value and an indicator of ecological health: effective stream management requires prediction of biodiversity responses to natural environmental and human-impact gradients. By compiling a dataset of macroinvertebrate species using new DNA metabarcoding, modelling their distributions, and ranking biodiversity by reach, we will develop molecular and quantitative spatial tools to provide data-driven, landscape-scale decision support for protecting and restoring streams: an urgent need for stream managers globally.
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