©2017. American Geophysical Union. All Rights Reserved. The seasonal pattern of the carbon isotope content (δ13C) of atmospheric CO2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δsource 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 δ13C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δsource at the forest sites (0.5‰ variation). We did not find a consistent seasonal relationship between VPD and δsource 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 δsource (5‰) dominated by seasonal transitions in C3/C4 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 δ13C of land-atmosphere CO2 exchange (δsource) 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 C3/C4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δsource when background atmospheric observations are remote and/or prone to anthropogenic influence.