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Identifying the areal extent of bedrock outcrops and shallow soils has important implications for understanding spatial patterns in vegetation composition and productivity, stream chemistry gradients, and hydrologic and soil properties of landscapes. Manual methods of delineating bedrock outcrops and associated shallow soils are still commonly employed, but they are expensive to implement over broad areas and often limited by representation of polygon units. Few studies have automated the delineation of bedrock outcrops. These focused on delineation approaches in landscapes with rapidly eroding hillslopes and sparse vegetation. The objectives of this study were to assess the accuracy of visually interpreting high-resolution relief maps for locating bedrock outcrops and associated shallow soil (BOSS) < 50 cm deep in a heavily forested landscape, to use visually interpreted point locations to train predictive models, and to compare predictions with manually delineated polygons in upland glaciated landscapes. Visual interpretation of Lidar-derived 1 m shaded relief maps at Hubbard Brook Experimental Forest (HBEF), USA resulted in a 79% accuracy of interpreting deep soil locations and 84% accuracy in distinguishing BOSS. We explored four probabilistic classifications of BOSS using multiple Lidar-derived topographic metrics as predictive variables. All four methods identified similar predictors for BOSS, including slope and topographic position indices with a 15, 100 and 200 m circular analysis window, respectively. Although all classifiers yielded similar results with little difference in interpretation, a generalized additive model had slightly higher accuracy predicting BOSS presence, yielding 85% overall accuracy using independent validation data across the primary study area, and 86% overall accuracy in a second validation area.

Identifying the areal extent of bedrock outcrops and shallow soils has important implications for understanding spatial patterns in vegetation composition and productivity, stream chemistry gradients, and hydrologic and soil properties of landscapes. Manual methods of delineating bedrock outcrops and associated shallow soils are still commonly employed, but they are expensive to implement over broad areas and often limited by representation of polygon units. Few studies have automated the delineation of bedrock outcrops. These focused on delineation approaches in landscapes with rapidly eroding hillslopes and sparse vegetation. The objectives of this study were to assess the accuracy of visually interpreting high-resolution relief maps for locating bedrock outcrops and associated shallow soil (BOSS) < 50 cm deep in a heavily forested landscape, to use visually interpreted point locations to train predictive models, and to compare predictions with manually delineated polygons in upland glaciated landscapes. Visual interpretation of Lidar-derived 1 m shaded relief maps at Hubbard Brook Experimental Forest (HBEF), USA resulted in a 79% accuracy of interpreting deep soil locations and 84% accuracy in distinguishing BOSS. We explored four probabilistic classifications of BOSS using multiple Lidar-derived topographic metrics as predictive variables. All four methods identified similar predictors for BOSS, including slope and topographic position indices with a 15, 100 and 200 m circular analysis window, respectively. Although all classifiers yielded similar results with little difference in interpretation, a generalized additive model had slightly higher accuracy predicting BOSS presence, yielding 85% overall accuracy using independent validation data across the primary study area, and 86% overall accuracy in a second validation area.

Headwater streams in the White Mountains, NH, United States have been shown to have downstream gradients of increasing pH and concentrations of base cations coupled with decreasing concentrations of aluminum. A two-stage acid neutralization model involving shallow soil exchange processes in headwaters coupled with deeper mineral weathering downstream had been proposed to explain these gradients. We conducted synoptic sampling of three headwater catchments in this region that showed variations in this longitudinal pattern, ranging from streams that remain acidic throughout their length to streams with circumneutral pH beginning at their source. To explain these differences, we mapped soils using a hydropedologic approach that emphasizes the influence of groundwater saturation frequency and water table regime on soil formation processes. Stream segments with lower pH and base cation concentrations, coupled with higher concentrations of dissolved organic carbon (DOC), aluminum, and in one case iron, were in subcatchments mapped with shallow to bedrock soils where eluvial soil forming processes dominated. In contrast, stream segments with higher pH and base cation concentrations coupled with low concentrations of DOC and aluminum were associated with subcatchments with deeper soils where illuvial processes were more dominant. Concentrations of sodium and silicon were relatively uniform across these gradients. Coupled with the higher concentrations of dissolved aluminum and small pools of exchangeable aluminum in the areas of bedrock outcrops and shallow soils, these data suggest that primary mineral dissolution is an important process influencing upper stream reaches, not just along longer, deeper flowpaths in downslope areas. In contrast, some stream reaches with obvious groundwater springs show a more abrupt transition in pH and base cation concentrations higher along the stream, suggesting that neutralization along deeper flowpaths may play a role in upslope areas as