Date of Award:


Document Type:


Degree Name:

Doctor of Philosophy (PhD)


Watershed Sciences


Dr. Charles P. Hawkins


Catchment geology is known to influence water chemistry, which can significantly affect both species composition and ecosystem processes in streams. However, current predictions of how stream water chemistry varies with geology are limited in both scope and precision, and we have not adequately tested the specific mechanisms by which water chemistry influences stream biota. My dissertation research goals were to (1) develop empirical models to predict natural base-flow water chemistry from catchment geology and other environmental factors, (2) extend these predictions to nutrients to establish more realistic criteria for evaluating water quality, and (3) test the hypothesis that catchment geology significantly influences the composition of stream invertebrate assemblages by restricting weak osmoregulators from streams with low total dissolved solids (TDS). To meet goal 1, I first mapped geologic chemical and physical influences by associating rock properties with geologic map units. I then used these maps and other environmental factors as predictors of electrical conductivity (EC, a measure of TDS), acid neutralization capacity, and calcium, magnesium, and sulfate concentrations. The models explained 58 – 92% of the variance in these five constituents. Rock chemistry was the best predictor of stream water chemistry, followed by temperature, precipitation and other factors. To meet goal 2, I developed empirical models predicting naturally occurring stream total nitrogen and total phosphorus concentrations. These models explained most of the spatial variation among sites in total nitrogen and phosphorus and produced better predictions than previous models. By determining upper prediction limits that incorporated model error, I demonstrated how predictions of nutrient concentrations could be used to set site-specific nutrient criteria and accounted for natural variation among sites better than regional criteria. To meet goal 3, I experimentally manipulated (high and low) EC in both stream-side and laboratory flowthrough microcosms and measured survival, growth, and emergence of 19 invertebrate taxa. Observed variation among taxa in survival between treatments predicted taxon EC optima estimated from field observations (r² = 0.60). Taxa with the greatest differences in survival between treatments also had the highest EC optima, indicating that the inability to persist in low EC likely restricts the distributions of some taxa.


This work made publicly available electronically on September 20, 2012.