Data Sheet 1_Geochemical connectivity among mine tailings, soils, sediments, and waters in a historical mining basin integrating multivariate statistics and exploratory random forest modeling.xlsx

The exploratory Random Forest model (OOB error of 0.12) identified S, Cd, and As the leading predictors of affinity to the predefined reference classes. However, these findings should be considered exploratory because the model was trained on a limited dataset (12 lithological and 13 mine tailings samples). Ecological risk is highest in mine tailings, driven primarily by elevated As, Cd, and Cu.

Water quality and human health risks are restricted to localized groundwater and downstream surface water sites, where quantified As concentrations are the principal contributor to potentially unacceptable carcinogenic risk. Overall, historical mining has amplified and redistributed preexisting hydrothermal geochemical signatures rather than introducing entirely new elemental assemblages. The integrated evaluation of multiple environmental matrices provides a framework for interpreting mining-related impacts in naturally mineralized basins.</p>