Iron isotope constraints on particulate iron dynamics in a human-impacted subtropical watershed

Abstract

Riverine particulate iron (Fe) mediates nutrient transport and redox-sensitive biogeochemical processes from watersheds to coastal waters, yet quantitative separation of natural and anthropogenic Fe inputs remains challenging in human-impacted river basins. Here, we combined suspended particulate Fe contents, Fe isotopes (δ⁵⁶Fe), geochemical indicators, land-use information and Bayesian mixing models to constrain the sources and cycling of particulate Fe in the subtropical Jiulong River Basin, southeast China. Particulate Fe concentration (Fe_SPM, g/kg) ranged from 26.27 to 168.79 g/kg, and δ⁵⁶Fe values varied from −0.94‰ to 0.17‰, with basin-wide means of 49.65 g/kg and 0.01‰, respectively. Marked spatial heterogeneity was observed among sub-basins. The tributaries of Beixi River had the highest particulate Fe concentration (mean: 64.48 g/kg) and the most negative δ⁵⁶Fe signatures, indicating intensified inputs of isotopically light Fe. Correlation analysis and Bayesian source apportionment suggested that agricultural land use was a major basin-scale control on Fe_SPM, accounting for approximately 45% of Fe_SPM in the Beixi River under wet-season conditions, whereas mining inputs were locally important in the Beixi headwaters and may have contributed to the depleted δ⁵⁶Fe signatures. Comparison with subtropical and tropical rivers worldwide further implies that agricultural disturbance can enhance riverine particulate Fe mobilization, while mining-derived Fe represents a potentially significant non-point source in mineralized catchments. These results indicate that the coupled isotope–Bayesian framework offers a promising approach for distinguishing overlapping natural weathering and anthropogenic Fe inputs, providing a quantitative basis for assessing particulate Fe transport from human-impacted rivers to coastal waters, pending flux quantification in future work.