This study compares stream nitrate (NO3-) concentrations to spatially distributed snowmelt in two alpine catchments, the Green Lakes Valley, Colorado (GLV4) and Tokopah Basin, California (TOK). A snow water equivalent reconstruction model and Landsat 5 and 7 snow cover data were used to estimate daily snowmelt at 30 m spatial resolution in order to derive indices of new snowmelt areas (NSAs). Estimates of NSA were then used to explain the NO3- flushing behavior for each basin over a 12 year period (1996-2007). To identify the optimal method for defining NSAs and elucidate mechanisms underlying catchment NO3- flushing, we conducted a series of regression analyses using multiple thresholds of snowmelt based on temporal and volumetric metrics. NSA indices defined by volume of snowmelt (e.g., snowmelt ≤ 30 cm) rather than snowmelt duration (e.g., snowmelt ≤ 9 days) were the best predictors of stream NO3- concentrations. The NSA indices were better correlated with stream NO3- concentration in TOK (average R2= 0.68) versus GLV4 (average R2= 0.44). Positive relationships between NSA and stream NO3- concentration were observed in TOK with peak stream NO3- concentration occurring on the rising limb of snowmelt. Positive and negative relationships between NSA and stream NO3- concentration were found in GLV4 with peak stream NO3- concentration occurring as NSA expands. Consistent with previous works, the contrasting NO3- flushing behavior suggests that streamflow in TOK was primarily influenced by overland flow and shallow subsurface flow, whereas GLV4 appeared to be more strongly influenced by deeper subsurface flow paths.

The contribution of savannas to global carbon storage is poorly understood, in part due to lack of knowledge of the amount of belowground biomass. In these ecosystems, the coexistence of woody and herbaceous life forms is often explained on the basis of belowground interactions among roots. However, the distribution of root biomass in savannas has seldom been investigated, and the dependence of root biomass on rainfall regime remains unclear, particularly for woody plants. Here we investigate patterns of belowground woody biomass along a rainfall gradient in the Kalahari of southern Africa, a region with consistent sandy soils. We test the hypotheses that (1) the root depth increases with mean annual precipitation (root optimality and plant hydrotropism hypothesis), and (2) the root-to-shoot ratio increases with decreasing mean annual rainfall (functional equilibrium hypothesis). Both hypotheses have been previously assessed for herbaceous vegetation using global root data sets. Our data do not support these hypotheses for the case of woody plants in savannas. We find that in the Kalahari, the root profiles of woody plants do not become deeper with increasing mean annual precipitation, whereas the root-to-shoot ratios decrease along a gradient of increasing aridity.