Combining meteorology, eddy fluxes, isotope measurements, and modeling to understand environmental controls of carbon isotope discrimination at the canopy scale

Estimates of terrestrial carbon isotope discrimination are useful to quantify the terrestrial carbon sink. Carbon isotope discrimination by terrestrial ecosystems may vary on seasonal and interannual time frames, because it is affected by processes (e.g. photosynthesis, stomatal conductance, and respiration) that respond to variable environmental conditions (e.g. air humidity, temperature, light). In this study, we report simulations of the temporal variability of canopy-scale C3 photosynthetic carbon isotope discrimination obtained with an ecophysiologically based model (ISOLSM) designed for inclusion in global models. ISOLSM was driven by half-hourly meteorology, and parameterized with eddy covariance measurements of carbon and energy fluxes and foliar carbon isotope ratios from a pine forest in Metolius (OR). Comparing simulated carbon and energy fluxes with observations provided a range of parameter values that optimized the simulated fluxes. We found that the sensitivity of photosynthetic carbon isotope discrimination to the slope of the stomatal conductance equation (m, Ball–Berry constant) provided an additional constraint to the model, reducing the wide parameter space obtained from the fluxes alone. We selected values of m that resulted in similar simulated long-term discrimination as foliar isotope ratios measured at the site. The model was tested with C measurements of ecosystem (dR) and foliar (df) respiration. The daily variability of simulated C values of assimilated carbon (dA) was similar to that of observed df, and higher than that of observed and simulated dR. We also found similar relationships between environmental factors (i.e. vapor pressure deficit) and simulated dR as measured in ecosystem surveys of dR. Therefore, ISOLSM reasonably simulated the short-term variability of dA controlled by atmospheric conditions at the canopy scale, which can be useful to estimate the variability of terrestrial isotope discrimination. Our study also shows that including the capacity to simulate carbon isotope discrimination, together with simple ecosystem isotope measurements, can provide a useful constraint to land surface and carbon balance models.