Background/Question/Methods The Konza Prairie in northern Kansas, USA contains over 550 vascular plant species, of which, few have been closely studied. Understanding how native tallgrass prairie species respond to changes in water availability and air temperature allows us to predict potential impacts of future climate change. For example, understanding which traits are the best predictors of relative abundance along a continuum of water availability (well watered to water stressed) will aid in the prediction of plant community structure under altered temperature-precipitation regimes. We conducted anatomical and physiological measurements on 122 species of herbaceous tallgrass prairie plants grown from seed in a growth chamber. Gas exchange measurements including transpiration rate, photosynthetic rate, stomatal conductance to water vapor, and intercellular CO2 concentration were taken under optimal light, temperature, and humidity conditions. All plants were exposed to a dry-down period and were monitored daily until conductance fell to zero. At this point, water potentials (Ψ_crit) were measured and the tissues were harvested to measure root length, diameter, volume, and mass, leaf area, leaf tissue density, root tissue density, and root to shoot ratio. Traits were compared using pair-wise bivariate analysis and principal component analysis (PCA).

Results/Conclusions Clear differences were detected between grass and forb functional groups, which were grouped in the dispersion pattern of the plotted PCA axes. The rotated factor pattern suggests a dichotomy between dry-adapted plants with thin, dense leaves and roots, and highly negative Ψ_crit and hydrophiles which have the opposite profile. A second axis offers more separation based on high photosynthetic rate, high conductance rate, and leaf posture, but fails to provide a distinction between C₃ and C₄ species. Matching up these axes with long term abundance data suggests that drought tolerance leads to increased abundance on Konza, especially in grazed, upland habitats. Further investigation will focus on linking plant traits to past climate-driven community changes evident in the long term data.