Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland eco ....Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland ecosystems. Under a framework that connects detailed measurements and small-scale processes, with machine-learning, data-model assimilation and large-scale next-generation biogeochemical modelling, it’ll allow more accurate predictions of soil carbon change and better decision-making to guide sustainable rangelands management.Read moreRead less
Modelling network innovation performance capability: a multidisciplinary approach. Innovation is created in complex network interactions.
By combining agent-based and fuzzy logic modelling, this project will identify combinations of resources to generate new ideas/technologies. This will enable managers and policy makers to understand the mechanisms behind innovation and implement policies aimed at enhancing innovation processes.
Real-time signal processing and distributed robotic telescope networking for co-detection of gravitational waves and their optical counterparts. An international collaboration of scientists will employ a global network of telescopes and detectors to search for ripples in space-time. The project will use novel computational tools to study exotic phenomena in the distant Universe.