Predicting High-Dimensional Isotope Relationships from Diagnostic Fractionation Factors in Systems with Diffusional Mass Transfer

High Resolution Image Download MS PowerPoint Slide A dual or multiple stable isotope relationship, for example, a trajectory in a δ？δ (or δ′？δ′) space, can be used to deduce the relationship of underlying diagnostic isotope fractionation factors (α) and therefore reveal the mechanism of a reaction process. While temporal data sampled from a closed-system can be treated by a Rayleigh distillation model, spatial data should be treated by a reaction-transport model. Owing to an apparent similarity between the temporal and spatial trajectories, the research community has often ignored this distinction and applied a Rayleigh distillation model to cases where a reaction-transport model should be applied. To examine the potential error of this practice, here we compare the results of a Rayleigh distillation model to a diffusional reaction-transport model by simulating the trajectories in nitrate’s δ′18O？δ′15N space during a simple denitrification process. We found that an incorrect application of a Rayleigh distillation model can underestimate the degree of a diagnostic fractionation to 50% but results in an insignificant difference in the regression slope of a δ′？δ′ trajectory when α ≈ 1.0. The regression slope predicted by a Rayleigh distillation model can, however, be 0.03–0.3 greater than predicted by a reaction-transport model when NO3– is involved in complex nitrogen cycling. Our reaction-transport model rarely predicts a δ′18O？δ′15N regression slope > 1 for reasonable Earth surface conditions. We found that for those published cases of regression slopes > 1, many can be attributed to the grouping of multiple NO3– sources from independent origins. Our results highlight the importance of linking the underlying physical model to the plotted data points before interpreting their high-dimensional isotope relationships