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Climate Change and Biomass Dynamics: Novel Methods in Extracting Forest Biophysical Properties.
Terrestrial vegetation carbon turnover has been identified as the biggest source of uncertainty in global vegetation model predictions and as such there is an urgent need for more accurate biomass estimates at a global scale. This project will use novel data collection techniques combined with an array of existing ground forest inventory, airborne LiDAR and space borne Earth Observation data to understand the role of climate, disturbance, topography and species diversity on forest carbon dynamics in a Mediterranean ecosystem. New methods to integrate diverse data will be developed using a Bayesian data assimilation framework in order to spatially and temporally extend high precision estimates to reduce uncertainty in large scale biomass estimates. Not only will this project develop new approaches to monitoring biomass, it will enhance our understanding of tree and forest dynamics and their likely response to changing climatic conditions by analysing data across distinctive abiotic and biotic gradients. The findings from this proposed project will have an impact on global vegetation modelling and conservation whereby new techniques for fusing data are needed for better monitoring and management at large spatial scales.
- Dr Emily Lines, School of Geography, QMUL
- 2014 - MSc (Hons) Environmental Monitoring, Modelling and Management (Merit, 68.4%), King’s College London.
Thesis: “An evaluation of an alternative method for measuring burning peat emissions in the laboratory using FTIR: A study using Irish sphagnum moss peat” (Distinction, 73%).
- 2012 - BSc (Hons) Geography 2nd Class (Upper Division), University of Plymouth.
- NERC DTP