Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales.

Increased nitrogen (N) deposition rates over the past century have affected both North American and European mountain lake ecosystems. Ecological sensitivity of mountain lakes to N deposition varies, however, because chemical and biological responses are modulated by local watershed and lake properties. We evaluated predictors of mountain lake sensitivity to atmospheric N deposition across North American and European mountain ranges and included as response variables dissolved inorganic N (DIN = NNH + NNO) concentrations and phytoplankton biomass. Predictors of these responses were evaluated at three different spatial scales (hemispheric, regional, subregional) using regression tree, random forest, and generalized additive model (GAM) analysis. Analyses agreed that Northern Hemisphere mountain lake DIN was related to N deposition rates and smaller scale spatial variability (e.g., regional variability between North American and European lakes, and subregional variability between mountain ranges). Analyses suggested that DIN, N deposition, and subregional variability were important for Northern Hemisphere mountain lake phytoplankton biomass. Together, these findings highlight the need for finer-scale, subregional analyses (by mountain range) of lake sensitivity to N deposition. Subregional analyses revealed differences in predictor variables of lake sensitivity. In addition to N deposition rates, lake and watershed features such as land cover, bedrock geology, maximum lake depth (Z), and elevation were common modulators of lake DIN. Subregional phytoplankton biomass was consistently positively related with total phosphorus (TP) in Europe, while North American locations showed variable relationships with N or P. This study reveals scale-dependent watershed and lake characteristics modulate mountain lake ecological responses to atmospheric N deposition and provides important context to inform empirically based management strategies.