Long-term trends in tidal wetland gross primary production observed from satellite
Raymond Najjar, Pennsylvania State University, rgn1@psu.edu (Presenter)
Maria Herrmann, Penn State University, mxh367@psu.edu
Jose D. Fuentes, Pennsylvania State University, jdfuentes@psu.edu
Rusty A Feagin, Texas A&M University, feaginr@tamu.edu
Thomas Huff, Texas A&M University, thomas2013@tamu.edu
Joshua Lerner, Texas A&M University, jlerner@tamu.edu
Tidal wetlands play an important role in coastal carbon cycling by taking up carbon dioxide from the atmosphere, burying organic carbon, and acting as a source of carbon and alkalinity to coastal waters. A key process in tidal wetland carbon cycling is gross primary production (GPP), which is the fixation of carbon dioxide by tidal wetland plants. Long-term tidal wetland GPP data sets are needed in order to understand how tidal wetland carbon cycling is changing as a result of climate and land use. GPP is typically estimated by the eddy covariance method, which is expensive and hence has only been applied at a small number of sites for limited time periods. Here, we analyze long-term trends in a new remote-sensing GPP product, the Blue Carbon (BC) model, which covers the contiguous United States from 2000 to 2019 at a temporal resolution of 16 days. GPP in the BC model is computed from three input variables: the enhanced vegetation index (EVI), air-temperature (T), and photosynthetically active radiation (PAR). We investigate the relative roles of EVI, T, and PAR on long-term trends of GPP by replacing each of the input variables by its mean annual cycle. Results of this preliminary analysis are reported for tidal wetlands in a single estuary.
Poster: Poster_Najjar_2-9_143_35.pdf
Associated Project(s):
Poster Location ID: 2-9
Presentation Type: Poster
Session: Poster Session 2
Session Date: Wed (May 10) 5:15-7:15 PM
CCE Program: OBB