Forest soil chemistry and terrain attributes in a Catskills watershed

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.