Leaf 13C data constrain the uncertainty of the carbon dynamics of temperate forest ecosystems

Abstract

Stable carbon isotope discrimination occurred in plant biophysical and biogeochemical processes can help understand plant physiology and soil biogeochemistry with respect to carbon cycling. Here, we incorporated the photosynthetic carbon isotope discrimination into a process-based land surface model (iTEM) to test if stable carbon isotope composition (δ13C) can impose additional constraint on model parameters. Sequential data assimilation was implemented at six eddy covariance flux tower sites using carbon flux observations including gross primary productivity (GPP) and net ecosystem exchange (NEE) with and without considering foliar δ13C (δ13Cf) measurement constraints, respectively. Our model-data fusion showed that δ13Cf can provide useful constraint on photosynthetic (Vcmax25, the maximum rate of carboxylation at 25°C) and stomatal (g1, the slope of stomatal function) parameters as well as the posterior carbon fluxes. When including δ13Cf measurement, g1 spatially varies among the six sites and is significantly correlated with annual precipitation. We incorporated the statistical relationship between g1 and annual precipitation into iTEM, which is then used to quantify the regional carbon dynamic in temperate forest ecosystems of the Northern Hemisphere. Compared with the simulation only conditioned on carbon flux observations, regional carbon flux estimations performed slightly better against the FLUXCOM products and the uncertainties of modeled carbon fluxes were reduced by 27%. Our study demonstrated that δ13Cf data constrains carbon flux uncertainties across space.