The importance of crop growth modeling to interpret the Δ14CO2 signature of annual plants

Abstract

The 14C/C abundance in CO2(Δ14CO2) promises to provide useful constraints on regional fossil fuel emissions and atmospheric transport through the large gradients introduced by anthropogenic activity. The currently sparse atmospheric Δ14CO2 monitoring network can potentially be augmented by using plant biomass as an integrated sample of the atmospheric Δ14CO2. But the interpretation of such an integrated sample requires knowledge about the day‒to‒day CO2 uptake of the sampled plants. We investigate here the required detail in daily plant growth variations needed to accurately interpret regional fossil fuel emissions from annual plant samples. We use a crop growth model driven by daily meteorology to reproduce daily fixation of Δ14CO2 in maize and wheat plants in the Netherlands in 2008. When comparing the integrated Δ14CO2 simulated with this detailed model to the values obtained when using simpler proxies for daily plant growth (such as radiation and temperature), we find differences that can exceed the reported measurement precision of Δ14CO2(∼2‰). Furthermore, we show that even in the absence of any spatial differences in fossil fuel emissions, differences in regional weather can induce plant growth variations that result in spatial gradients of up to 3.5‰ in plant samples. These gradients are even larger when interpreting separate plant organs (leaves, stems, roots, or fruits), as they each develop during different time periods. Not accounting for these growth‒induced differences in Δ14CO2 in plant samples would introduce a substantial bias (1.5–2 ppm) when estimating the fraction of atmospheric CO2 variations resulting from nearby fossil fuel emissions.