Nitrogen (N) fertilizer is a commonly applied silvicultural treatment in intensively managed Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] plantations. When attempting to maximize average growth responses through fertilization, landowners experience difficulty prioritizing stands for treatment based on the likely magnitude of response and return on the operational investment. Field trials were established to better understand Douglas-fir growth response to nitrogen fertilization, in part by empirically quantifying the direct and indirect effects. The trials forming the focus of the study were installed by Stimson Lumber Company (Gaston, Oregon) during the 2009-2010 dormant season. Forty trees were destructively sampled to measure crown attributes and aboveground allometrics. Fertilization resulted in a mean net cubic volume increment response of 11.2% across stands, which was attributed to significant annual responses over the first four years following treatment. Characterizing annual growth responses allowed an examination of the direct effect of fertilization, which implicated a significant shift in diameter inside-bark, seven years following treatment, with the largest increases being observed at or near crown base. The difference in stem form as a result of fertilization suggested volume growth response that is potentially unaccounted for in growth models. Shifts in stem form were hypothesized to be effect of the significant shifts in vertical foliage distribution, and increases in total crown foliage mass. Results presented in this Thesis suggest the potential for successful identification and quantification of mechanisms driving empirical responses. Furthermore, the potential for mechanistic growth model components that incorporate key ecophysiological processes linking stand structure, soil water holding capacity, and site-specific weather inputs. A key motivation for this approach was that successful quantification of direct and indirect growth responses and associated mechanisms will enhance our ability to discriminate between sites with different response potentials. In this way, mechanistic insights coupled with better site characterization should help improve the economic and environmental performance of forest fertilization.