Accurate estimates of soil mineral weathering are required for regional critical load (CL) modeling to identify ecosystems at risk of the deleterious effects from acidification. Within a correlative modeling framework, we used modeled catchment‐level base cation weathering (BC_w) as the response variable to identify key environmental correlates and predict a continuous map of BC_w within the southern Appalachian Mountain region. More than 50 initial candidate predictor variables were submitted to a variety of conventional and machine learning regression models. Predictors included aspects of the underlying geology, soils, geomorphology, climate, topographic context, and acidic deposition rates. Low BC_w rates were predicted in catchments with low precipitation, siliceous lithology, low soil clay, nitrogen and organic matter contents, and relatively high levels of canopy cover in mixed deciduous and coniferous forest types. Machine learning approaches, particularly random forest modeling, significantly improved model prediction of catchment‐level BC_w rates over traditional linear regression, with higher model accuracy and lower error rates. Our results confirmed findings from other studies, but also identified several influential climatic predictor variables, interactions, and nonlinearities among the predictors. Results reported here will be used to support regional sulfur critical loads modeling to identify areas impacted by industrially derived atmospheric S inputs. These methods are readily adapted to other regions where accurate CL estimates are required over broad spatial extents to inform policy and management decisions.

A century of atmospheric deposition of sulfur and nitrogen has acidified soils and undermined the health and recruitment of foundational tree species in the northeastern US. However, effects of acidic deposition on the forest understory plant communities of this region are poorly documented. We investigated how forest understory plant species composition and richness varied across gradients of acidic deposition and soil acidity in the Adirondack Mountains of New York State.