10-11am BST, Tuesday, April 12, Zoom
Correct understanding and modeling of terrestrial carbon cycles is an essential first step for accurate prediction of large-scale climate variability and change, which impacts the lives and living quality of all organisms of our planet, including us human beings. However, considerable uncertainties remain, particularly associated with key model parameters and processes that determine the strengths of land plants to interact with current and changing climate. With such uncertainties, there is no doubt that current Earth System Models (ESMs) fail to adequately capture the magnitude, spatial variation and seasonality of terrestrial carbon uptake. Here, with tropical forest ecosystems as an example study system, I show how the integration of multi-scale remote sensing with field observations can help 1) reveal the missing, important ecological mechanisms, 2) improve process understanding and model representations of carbon cycles in current ecosystem models, and 3) harness novel air-/space- borne techniques for large-scale monitoring of the structure, composition and function of terrestrial ecosystems. Collectively, I hope to show that such an integrated approach, which connects multi-scale observations with ecological theories and models, can be an important way towards a more predictive future of terrestrial ecosystems with climate change.
About the speaker: Jin Wu is an Assistant Professor at the School of Biological Sciences, University of Hong Kong (HKU). Prior to his HKU appointment, he held a Goldhaber Distinguished Postdoctoral Fellow at Brookhaven National Laboratory. He received his B.S. in Geoinformatics and Remote Sensing at Wuhan University, and Ph.D. in Ecology and Evolutionary Biology at University of Arizona. He is a broadly trained environmental scientist studying the interaction of forest ecosystems with climate. He shares a very broad research interest in ecology, global change, biodiversity, sustainability science and remote sensing. For more details, please visit https://wu-jin.weebly.com/.