PhD Angove Charlotte

127000 €

Unlocking the unique climatic and physiological signal from hydrogen isotopes in trees

Tieteellinen tutkimus / siihen pohjautuva työ | Kaksivuotinen

Boreal forests constitute one of the largest terrestrial biomes on Earth. They are a vital global ecosystem, regulating global climate and locking away vast quantities of carbon dioxide (CO2). They are also highly important social and economic resources. Climate change has implications to the future health of boreal forests, which risks the delivery of ecosystem services which they provide. There is, therefore, an urgent need to improve our understanding of boreal tree response to environmental change, such as changes in atmospheric CO2, temperature and moisture availability. Chemical tracers in tree-rings and needle n-alkanes, known as stable isotope ratios, are rapidly developing tools for understanding tree response to climate change and/or reconstructing past climate. Tree ring stable isotope ratios provide a dateable archive of past tree response to climate change, and they can also be used to predict future tree response to climate change. Meanwhile, tree needle n-alkane stable isotope ratios store climatic information in sediment layers for thousands to millions of years, making them highly valuable proxies for reconstructing past climate. This research project aims to investigate a poorly understood chemical tracer (the stable isotope ratio of hydrogen, d²H) in tree rings and n-alkanes, to unlock the unique and distinct physiological and climatic information which the d²H signal provides. To achieve such an innovation, this project is highly collaborative and interdisciplinary, involving leading experts in multiple research fields. Samples of tree compounds will be prepared and analysed at high temporal resolution using sophisticated laboratory analyses and cutting-edge technologies developed by collaborators. This research is important because it is a necessity to better understand climate trends, and tree response to climate change, to better predict future forest responses.