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and dynamic population projections to 2100, thus addressing two key science questions: How can geomorphic hazards in dynamic rivers and population exposure to such hazards best be predicted?; How will
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vegetation dynamics in the loop closure signal. The approach will be compared with more traditional methods for crop monitoring based on InSAR coherence, backscatter, and polarimetric SAR data. The Doctoral
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respiration responds to post-wildfire conditions across Amazonia, and how soil properties mediate this response; (2) how pyrogenic carbon (PyC, charcoal) additions affect soil respiration dynamics in southern
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will apply nonlinear and associational (colloquially called “causal”) timeseries analysis techniques to provide a more rigorous, and more statistically significant framework for understanding
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Methods The Southern Ocean plays a disproportionate role in capturing anthropogenic heat and carbon. Its complex dynamics are characterised by interaction between the large-scale and a range of small-scale
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to understand the drivers and dynamics of sediment transport along this highly populated and vulnerable river. Additionally, it will explore the use of prototype water quality sensors (Hydrobeans) to understand
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composition and air quality? What are the spatial and temporal dynamics of wildfire-driven land change? How do these changes translate into population health risks? The Doctoral Researcher will play a central
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to deliver automated, auditable geological models that can be updated dynamically as new data becomes available. The project involves four components to resolve this challenging problem: (1) Inference
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Reproduction will couple satellite-derived ocean temperature data, microclimate forecasts of nesting beaches with behavioural and physiological models derived from biological first principles. This dynamic model
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central question in evolutionary biology and has profound implications for predicting host–pathogen dynamics in changing environments and biodiversity conservation. In this project, you will investigate