The Stochastic Ferrous Wheel and its Implications for the Carbon Cycle

Abstract

The soil iron cycle has a multi-faceted role in the soil carbon cycle affecting carbon emissions across the globe. The drivers of the iron cycle or "ferrous wheel" are fluctuating redox conditions caused by changes in soil moisture. Soil moisture may change due to stochastic inputs (rainfall) or deterministic events (irrigation) over hours or over months. Various aspects of the soil iron cycle have been studied from a microbiological or geochemical perspective, but modeling the macroscopic effects of the cycle remains a challenge. Two of the most critical mechanisms in which iron affects soil carbon storage are (I) the protection of carbon by iron oxides and (II) the oxidation of carbon with iron as an electron acceptor. These two effects have not yet been explicitly modeled together. Furthermore, many studies are limited to the effect of constant length redox cycles, and the effect of stochastic fluctuations of soil moisture has not been thoroughly explored. The objective of this thesis is to investigate how the coupled water-iron-carbon cycles behave under different conditions and how these interactions affect carbon emissions. To tackle this open ended question, this thesis develops a first pass model at capturing these dynamics. The model is divided into two components: (I) a numerical model that includes carbon protection and carbon oxidation by iron reduction, and (II) a simplified model of the iron cycle driven by stochastic soil moisture fluctuations. Through simulations, the numerical model demonstrates that different initial conditions and rates of reduction can alter the net effect (positive or negative) of iron on carbon emissions. From the stochastic model a probability density function was derived of the fraction of iron that is reduced in a fluctuating redox environment. This function has broad applicability to both carbon dynamics and iron properties of the soil. Overall the models progress the current state of modeling the iron and carbon cycles and connect existing conceptions to a mathematical modeling framework, an important step for predicting soil carbon dynamics under climate change.