Rapid determination of comparative drought tolerance traits: using an osmometer to predict turgor loss point

1. Across plant species, drought tolerance and distributions with respect to water availability are strongly correlated with two physiological traits, the leaf water potential at wilting, that is, turgor loss point (ptlp), and the cell solute potential at full hydration, that is, osmotic potential (po). We present methods to determine these parameters 30 times more rapidly than the standard pressurevolume (pv) curve approach, making feasible community-scale studies of plant drought tolerance. 2. We optimized existing methods for measurements of pi o using vapour-pressure osmometry of freeze-thawed leaf discs from 30 species growing in two precipitation regimes, and developed the first regression relationships to accurately estimate pressurevolume curve values of both pi o and pi tlp from osmometer values. 3. The pi o determined with the osmometer (pi osm) was an excellent predictor of the pi o determined from the pv curve (pi pv,r2 = 0.80). Although the correlation of pi osm and pi pv enabled prediction, the relationship departed from the 1 : 1 line. The discrepancy between the methods could be quantitatively accounted for by known sources of error in osmometer measurements, that is, dilution by the apoplastic water, and solute dissolution from destroyed cell walls. An even stronger prediction of pi pv could be made using pi osm, leaf density (rho), and their interaction (r2 = 0.85, all P < 2 x 10-10). 4. The pi osm could also be used to predict pi tlp (r2 = 0.86). Indeed, pi osm was a better predictor of pi tlp than leaf mass per unit area (LMA; r2 = 0.54), leaf thickness (T; r2 = 0.12), rho (r2 = 0.63), and leaf dry matter content (LDMC; r2 = 0.60), which have been previously proposed as drought tolerance indicators. Models combining posm with LMA, T, rho, or LDMC or other pv curve parameters (i.e. elasticity and apoplastic fraction) did not significantly improve prediction of pi tlp. 5. This osmometer method enables accurate measurements of drought tolerance traits across a wide range of leaf types and for plants with diverse habitat preferences, with a fraction of effort of previous methods. We expect it to have wide application for predicting species responses to climate variability and for assessing ecological and evolutionary variation in drought tolerance in natural populations and agricultural cultivars.