RSI Research Seminar

Join us every other Monday at noon for lunch and a 30-minute research talk, presented by Resnick Sustainability Institute Graduate Fellows and Caltech researchers funded by the Resnick Sustainability Institute. To see the full schedule of speakers, visit the RSI Research Seminar web page. Seminars currently take place in a hybrid format, both in-person (Jorgensen building first-floor conference room) and via Zoom. For more information and to get the Zoom login info, please reach out to ramonae@caltech.edu

INTERANNUAL VARIATION OF PRODUCTIVITY IN THE HIGH-LATITUDE NORTHERN FORESTS: THE ROLE OF PLANT FUNCTIONAL TYPES AND CLIMATE

The High-Latitude Northern Forest (HLNF) is composed of Gymnosperms trees (both evergreen and deciduous needleleaf), Angiosperm (deciduous broadleaf trees), and shrubland, contributing around 20% to global total gross primary productivity (GPP). These forests have been experiencing dramatic changes under elevated atmospheric CO2and amplified increases in temperature over the high latitudes. These changes, including greening, phenological shifts, plant functional type transition, etc., result in significant variations in carbon cycling. Assessing the variations in productivity of HLNF and their drivers is crucial for understanding the current ecosystem responses and projecting future vegetation and climate changes. We exploit the solar-induced chlorophyll fluorescence (SIF) observations from the TROPOspheric Monitoring Instrument (TROPOMI) to track the interannual variations of forest GPP in the HLNF region and investigate its relationship with the climate drivers. Compared to reflectance-based vegetation indexes (VIs, such as NDVI and EVI), SIF provides a more promising proxy for vegetation productivity, especially in boreal evergreen forests, which undergo seasonal shifts of productivity with retained leaves and chlorophyll content year-round. We also explore how the interannual responses of productivity to climate drivers vary across different plant functional types (PFT) spatially and, to improve our understanding of ongoing and future carbon cycle changes in HLNF.