Xiongjie Deng

Understanding functional diversity and ecosystem resilience in tropical forests by coupling multi-source remote sensing techniques and trait-based methods

Xiongjie is a DPhil student who focuses on measuring, modelling, monitoring, and forecasting forest spatiotemporal dynamics across tropical ecosystems based on remote sensing data in junction with in-situ measurements. Specifically, he investigates how to map and predict plant functional traits from space and how functional traits help to understand tropical forests' responses to the changing environment. Before joining Oxford, Xiongjie earned a master's degree from Wuhan University with distinction and a bachelor's degree from Chongqing University.

Awards and Funding

• PIF Scholarship by China Oxford Scholarship Fund (2022-2023, 2023-2024)
• Dominique Pire Scholarship (2022-2023), Blackfriars Hall
• New Blackfriars Scholarship (2023-2024), Blackfriars Hall

Journal Articles

• Chen, J., Shao, Z., Deng, A., Huang, X. and Dang, C. (2023) Vegetation as the catalyst for water circulation on global terrestrial ecosystem. Science of The Total Environment, 895: 165071.

Book Chapters

• Malhi, Y., Christmann, T., Deng, X., Zhang-Zheng, H., Moore, S. and Riutta, T. (In press) Forest Carbon Budgets and Climate Change, Part 6: Forest and Climate Change. In, Peh, Kelvin S-H., Richard T. Corlett, and Yves Bergeron (eds.) Routledge Handbook of Forest Ecology. Routledge.

Conference Presentations

• Deng, X. (2022) Pantropical plant functional traits dynamics mapping and predicting by integrating radar and field data on the Google Earth Engine platform. Under Symposium 42: From traits to ecosystems: remote sensing of tropical forest structure and function under environmental change, 58th Annual Meeting of the Association for Tropical Biology and Conservation.
• Deng X., Aguirre-Gutiérrez, J. and Malhi, Y. (2023) Spatiotemporal functional traits mapping and functional diversity assessment from above. ARBOLES: A trait-based Understanding of LATAM Forest Biodiversity and Resilience.
• Huanyuan, Z. and Deng, X. (2023) Indent and comment are critical for readability and reproducibility. Poster presentation at the Institute of Computing for Climate Science at the University of Cambridge.