Prediction of reducible soil iron content from iron extraction data

Soils contain various iron compounds that differ in solubility, reducibility and extractability. Moreover, the contribution of the various iron compounds to total iron (Fe) and total Fe concentrations differs highly among soils. As a result, the total reducible Fe content can also differ among soils, and so does the dynamics of iron reduction. These factors complicate the prediction of reducible Fe based on Fe extraction data and hamper the application of process-based models for reduced or waterlogged soils where redox processes play a key-role. This paper presents a theoretical analysis relating reducible to extractable Fe reported in the literature. Predictions made from this theoretical analysis were evaluated in soil incubations using 18 rice paddy soils from all over the world. The incubation studies and the literature study both show that reducible Fe can be related to Fe from some selected, but not all, iron extractions. The combination of measurements for labile Fe(III) oxides (derived from oxalate-extractable Fe) and stabile Fe(III) oxides (derived from dithionite-citrate-extractable Fe) shows highly significant correlations with reducible Fe with high coefficients of determination (r(2) = 0.92-0.95 depending on the definition of stabile Fe(III) oxides). Given the high diversity in rice soils used for the incubations, these regression equations will have general applicability. Application of these regression equations in combination with soil database information may improve the predictive ability of process-based models where soil redox processes are important, such as CH4 emission models derived for rice paddies or wetlands.