The Pacific Northwest (PNW) region of the United States has some of the most productive forests in the world. As precipitation regimes may shift with changing climate in this area, droughts are predicted to increase in both frequency and degree of severity, which will have a significant impact on already drought-prone ecosystems. When modeling ecosystem responses to drought, it is important to consider the physiology of individual tree species since the variations in drought sensitivity among species is easily overlooked when plants are characterized using broad plant functional types. Here we explore the use of inherent water-use efficiency as an index of drought sensitivity in semi-arid young and mature ponderosa pine forests and a mesic mature Douglas-fir forest in the PNW. Summer maximum of an evapotranspiration-based WUE (WUEi) was 2.5 times higher in young and mature pines in semi-arid climate than Douglas-fir in mesic climate (12.2 and 11.3 versus 4.7 g C kPa per kg H2O, respectively). In contrast, annually averaged WUEi was similar among the sites (2.8 g C kPa per kg H2O for pines and 2.4 g C kPa per kg H2O for Douglas-fir). The effect of drought stress on WUEi was most pronounced in young pine, followed by mature pine and Douglas-fir (32, 11, and 6% increase in WUEi per % decline in soil water content, respectively) which reflect differences in age-related ecosystem structure (root system, stem capacitance, and soil water holding capacity). Among sites, the responses of WUEi to climate variability were largely driven by changes in evapotranspiration (ET) compared to gross primary productivity (GPP). However, in areas where evaporation is the primary component of ET, such as the open canopy ponderosa forests of the PNW, the contribution of soil processes to ET can overshadow the reaction of vegetation transpiration (T) to changes in water availability. In these cases, utilizing a transpiration-based WUE (WUEi_T) in vegetation models will yield a more accurate representation of plant activity during drought. These results highlight the importance of incorporating differences in species- and age-related WUEi in models in diverse forest types at regional and global scales to improve predictions in ecosystem responses to climate change.