Integrated Farm Modelling to Improve Resilience and Sustainable Prosperity. This project aims to improve farm resilience, farm management, and economic decision-making in Australia and internationally. It expects to generate new interdisciplinary knowledge to integrate our understanding of agro-ecosystems and innovative tools to assess their status and manage their operations more effectively. Expected outcomes include the ability to inform farmers, bankers, and land managers about the trade-off ....Integrated Farm Modelling to Improve Resilience and Sustainable Prosperity. This project aims to improve farm resilience, farm management, and economic decision-making in Australia and internationally. It expects to generate new interdisciplinary knowledge to integrate our understanding of agro-ecosystems and innovative tools to assess their status and manage their operations more effectively. Expected outcomes include the ability to inform farmers, bankers, and land managers about the trade-offs between resilience and efficiency on farms. This should provide significant benefits, including the ability to minimize financial risks to farmers and banks, allow better investment decisions, and achieve sustainable long-term outcomes for both private and public well-being.Read moreRead less
Modern statistical methods for clustering community ecology data. This project will develop statistical methods and software for clustering community ecology data, and use them to analyse systematic survey and citizen science program data collected along the Great Barrier Reef. By doing so, the project will address the dearth of statistical classification techniques for high-dimensional, multi-response data with complex relationships. When the resultant clustering methods are used to construct b ....Modern statistical methods for clustering community ecology data. This project will develop statistical methods and software for clustering community ecology data, and use them to analyse systematic survey and citizen science program data collected along the Great Barrier Reef. By doing so, the project will address the dearth of statistical classification techniques for high-dimensional, multi-response data with complex relationships. When the resultant clustering methods are used to construct bioregions and characterise species’ environmental responses, they should significantly enhance evaluations of the impact of human activity and environmental change on coral diversity. Ultimately, these evaluations can underpin future decisions in the conservation and management of the Great Barrier Reef.Read moreRead less