Tracing the flow of carbon through ecosystems using automated chamber and stable isotope techniques

The stable isotope ¹³C has become a popular tool for tracing carbon exchange between atmospheric and terrestrial reservoirs. Stable isotope techniques have been applied in a variety of ecosystems to partition the component fluxes of net CO₂ exchange (F_N) and have been incorporated into several atmospheric inversion models that estimate the terrestrial carbon sink on the regional and global scales. While the use of stable isotope theory has helped provide valuable insight into the temporal and spatial variability of carbon exchange, there has been some concern about the theory's dependence on several key assumptions that have gone unverified due to limiting sampling techniques. Specific concerns regard the temporal variability of the isotopic composition of ecosystem respiration (δ_R) and its potential influence on ecosystem flux partitioning. In this poster, an automated chamber system was combined with stable isotope techniques (chamber-TDL method) to evaluate and apply isotopic partitioning theory both in an agricultural ecosystem and in a climate controlled experiment using corn and soybean plants. Further, this new automated sampling technique was combined with isotopic flux-gradient measurements to examine the main factors controlling variability in ecosystem respiration and its isotopic composition. The findings from this poster research may benefit land surface schemes that simulate isotopic fluxes for input to atmospheric inversion models.

Isotopic soil flux data suggested root respiration linearly increased from early to peak growth of a corn growing season, accounting for up to 55% of the total soil respiration (F_Rs) during peak growth. In addition, nightly averages of the isotopic composition of F_Rs (δ_Rs) were consistently 2 to 4‰ more depleted than isotopic flux-gradient measurements of gross ecosystem respiration during the same time period. The relatively depleted δ_Rs signal indicates the strong influence of above ground respiration on the total isotopic composition of ecosystem respiration. The chamber-TDL method also revealed strong diurnal patterns in δ_Rs in the agricultural soil plots before crop emergence, consisting of a sharp enrichment of up to 6‰ from 0700 to 1200 hr followed by a gradual depletion throughout the afternoon and evening. The diurnal δ_Rs signal showed poor overall correlations with soil F_R and 5 cm soil temperature but strong correlations with friction velocity and wind speed, suggesting diurnal variation in δ_Rs before crop emergence was caused by turbulence and wind gusts at the surface. During peak corn growth, diurnal variation in δ_Rs was strongly influenced by the isotopic composition of corn root respiration, which enriched nighttime δ_Rs by as much as 7‰ and daytime δ_Rs by as much as 3‰. In addition, microbial consumption of root exudates may have also affected diurnal variability in δ_Rs during peak growth. Partitioning of F_N into photosynthesis (F_P) and respiration (F_R) using the chamber-TDL method in a climate controlled greenhouse produced realistic diurnal values for both the corn and soybean treatments. Chamber data indicated the isotopic composition of F_N (δ_N) and the stomatal conductance for CO₂ (g_c) had the largest influences on estimated F_P values. Despite relatively high noise, the stable isotope partitioning method yielded results that were more realistic physiologically on the diurnal time scale than a common temperature-regression partitioning method, which lacked sensitivity to plant-derived processes that affected the component fluxes of F_N.