Tectonic versus biological processes: What controls the long-term global carbon cycle? A major debate in Earth system analysis concerns two competing hypotheses on the driving forces behind dramatic changes in atmospheric CO2 over geological time. One hypothesis considers tectonic/geological processes to be the major driving force. The other argues that it is the competition between plants and animals that drives the long-term CO2 cycle. We propose to test these hypotheses using a novel set of g ....Tectonic versus biological processes: What controls the long-term global carbon cycle? A major debate in Earth system analysis concerns two competing hypotheses on the driving forces behind dramatic changes in atmospheric CO2 over geological time. One hypothesis considers tectonic/geological processes to be the major driving force. The other argues that it is the competition between plants and animals that drives the long-term CO2 cycle. We propose to test these hypotheses using a novel set of global oceanic palaeo-age grids and subduction models for the last 180 million years. This will allow us to appraise key tectonic carbon cycle components such as mantle degassing, seafloor weathering and sediment subduction.Read moreRead less
Soil inference system for bridging the environmental modelling gap. The Australian environment is confronted with issues of degradation and long-term sustainability. There is a need to predict landscape processes into the future using simulation models. The limited availability of appropriate information on the soil is a fundamental barrier to this crucial modelling. This project will develop an inference system to predict soil properties from the very limited information. The results will be us ....Soil inference system for bridging the environmental modelling gap. The Australian environment is confronted with issues of degradation and long-term sustainability. There is a need to predict landscape processes into the future using simulation models. The limited availability of appropriate information on the soil is a fundamental barrier to this crucial modelling. This project will develop an inference system to predict soil properties from the very limited information. The results will be used to describe soil quality, to monitor the effects of agricultural management, and principally to provide information needed by policy makers concerned with sustainable land use.Read moreRead less