Does vapor pressure deficit drive the seasonality of δ 13 C of the net land-atmosphere CO 2 exchange across the United States?: The Influence of VPD on δ 13 C of NEE
The seasonal pattern of the carbon isotope content (δ 13 C) of atmospheric CO 2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO 2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δ source at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ 13 C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δ source at the forest sites (0.5‰variation). We did not find a consistent seasonal relationship between VPD and δ source across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δ sourc e (5‰) dominated by seasonal transitions in C 3 /C 4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ 13 C of land-atmosphere CO 2 exchange (δ source ) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C 3 /C 4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δs ource when background atmospheric observations are remote and/or prone to anthropogenic influence.