Optimization of maximum photosynthetic carboxylation rate (Vc,max) in CLASSIC for North America’s boreal forests using eddy covariance data
Bo Qu, Département de géographie, Université de Montréal; Centre d’études Nordiques, geo_qb@163.com (Presenter)
Alexandre Roy, Université du Québec à Trois-Rivières; Centre d’études Nordiques, alexandre.roy@uqtr.ca
Joe Melton, Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, joe.melton@canada.ca
T. Andrew Black, Biometeorology and Soil Physics Group, University of British Columbia, andrew.black@ubc.ca
Brian Amiro, Department of Soil Science, University of Manitoba, brian.amiro@umanitoba.ca
Hank Margolis, Département des sciences du bois et de la forêt, Université Laval, hank.margolis@sbf.ulaval.ca
Eugenie Euskirchen, Institute of Arctic Biology, University of Alaska Fairbanks, seeuskirchen@alaska.edu
Masahito Ueyama, Graduate School of Life and Environmental Sciences, Osaka Prefecture University, miyabi-flux@muh.biglobe.ne.jp
Hideki Kobayashi, Department of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology, hkoba@jamstec.go.jp
Oliver Sonnentag, Département de géographie, Université de Montréal; Centre d’études Nordiques, oliver.sonnentag@gmail.com
The maximum rate of photosynthetic carboxylation (Vc,max) is a key parameter in photosynthesis models for estimating gross primary productivity (GPP) of vegetation. Vc,max varies in space as a consequence of variation in plant traits (e.g., leaf nitrogen) and environmental conditions, posing a challenge to accurately estimate GPP across North America’s boreal biome and its forest ecosystems. Here, we implemented a Bayesian Vc,max optimization scheme for North America’s boreal forests in the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) using eddy covariance observations made at eight forest stands in different climate and permafrost zones. The Tree-structure Parzen Estimators (TPE), a hyper-parameter searching algorithm based on Bayesian optimization, was employed over each forest stand for Vc,max optimization at the dominating overstory and understory plant functional types (PFTs). We compared stand-level optimized Vc,max within and among PFTs and investigated PFT-level GPP estimates obtained by the optimized photosynthesis model. Our findings suggest that Vc,max varies significantly across the climate and permafrost zones of North America’s boreal biome. Carefully characterized stand-level variations in Vc,max provide an opportunity to improve regional GPP estimates across North America’s boreal forests by better constraining overstory and understory vegetation contributions.
Presentation: Talk_Qu_23_27.pdf
Session: 1.3 Modeling Framework & Comparisons