Needle samples from 140 Pinus ponderosa were analyzed for trace elements via inductively coupled plasma mass spectrometry (ICP-MS). Samples were collected from eight locations representing five distinct soil types across the Colorado Plateau near Flagstaff, Arizona and Boulder, Colorado. Data includes a full spectral scan between m/z 5-245 which was condensed to 72 dominant atomic masses. Instrument drift, matrix effects, and differing sample mass were corrected for using internal standard ion count intensities and individual sample weight. Further statistical analysis was performed using R executed within the RStudio environment. Classification was performed using three preprocessing techniques and five machine learning algorithms, including hierarchical modeling structures to optimize separation.