Assistant Professor
College of Agricultural and Life Sciences | Global Change Research Lab, Department of Forest and Wildlife Ecology
Dr. Min Chen is an assistant professor of the Department of Forest and Wildlife Ecology at the University of Wisconsin-Madison. He is also a faculty member affiliated with the UW Data Science Institute, the Nelson Institute Center of Climatic Research, Department of Geography, and Department of Atmospheric and Oceanic Sciences. Before joining UW-Madison, he was a research scientist at the Joint Global Change Research Institute, Pacific Northwest National Laboratory, and an adjunct professor of the Department of Atmospheric and Oceanic Sciences at the University of Maryland, College Park. He received his Ph.D. from Purdue University majoring in Earth and Atmospheric Sciences, and his M.S. and B.S. degrees in Remote sensing & GIS and Computer Sciences, respectively, both from Beijing Normal University in China. He was a postdoctoral fellow at Harvard University and a Barbara McClintock Fellow at the Carnegie Institution for Sciences at Stanford University.
Areas of expertise, continued: Climate change
Talks:
Measuring Photosynthesis from the Air
Photosynthesis is a crucial biological process underpinning numerous functions within terrestrial ecosystems. Although measuring photosynthesis beyond the leaf scale presents significant challenges, it is essential for understanding implications ranging from agricultural productivity to global climate dynamics. Recent advances in satellite remote sensing technology offer innovative methods for conducting these measurements.
Rising Methane Emission in Boreal-Arctic Wetlands
Methane ranks as the second most significant greenhouse gas following CO2, with wetlands being a primary source of methane emissions. However, our ability to quantify these emissions remains fraught with uncertainty. By employing machine learning techniques alongside a global network of ground-based observations of methane emissions from wetlands, we aim to construct more reliable estimates. This approach also helps us grasp the dynamics of methane emissions from wetlands and the underlying reasons for these changes.