2017 ESA Annual Meeting (August 6 -- 11)

COS 20-7 - Plant water content is the best predictor of drought-induced mortality 

Monday, August 7, 2017: 3:40 PM
D138, Oregon Convention Center
Gerard Sapes, Beth Roskilly and Anna Sala, Division of Biological Sciences, University of Montana, Missoula, MT
Background/Question/Methods

Predicting drought-induced forest mortality remains extremely challenging. Recent research has shown that both plant hydraulics and stored non-structural carbohydrates (NSC) interact during drought-induced mortality. The strong interaction between these two variables and the fact that they are both difficult to measure render drought-induced plant mortality extremely difficult to monitor and predict. A variable that is easier to measure and that integrates hydraulic transport and carbohydrate dynamics may, therefore, improve our ability to monitor and predict mortality. Here, we tested whether plant water content is such an integrator variable and, therefore, a better predictor of mortality under drought.

We subjected 250 two-year-old ponderosa pine seedlings planted in pots to drought until they died in a greenhouse experiment. Periodically during the dry down, we measured percent loss of hydraulic conductivity (PLC), NSC concentrations (starch and soluble sugars), and tissue volumetric water content (VWC) in roots, stems and leaves. We estimated the probability of mortality at the population level by re-watering a set of seedlings each time. Linear models were used to explore whether PLC and NSC were linked to VWC and to determine which of the three variables predicted mortality the best.

Results/Conclusions

As expected, plants lost hydraulic conductivity in stems and roots as soil water potential decreased during the dry down. Starch concentrations also decreased in all organs as the drought proceeded. In contrast, soluble sugars increased in stems and roots, consistent with the conversion of stored NSCs into osmotically active compounds. Models containing both PLC and NSC concentrations as predictors of VWC were highly significant in all organs and at the whole plant level, indicating that water content is influenced by both PLC and NSCs. PLC, NSC, and VWC explained mortality across organs and at the whole plant level, but VWC was the best predictor (R2 = 0.90). Our results indicate that plant water content integrates plant hydraulics and carbohydrate availability, two factors commonly interacting and difficult to tease apart. An important advantage of water content is that it is very easy to measure across scales, from leaves in the laboratory to entire ecosystems through remote sensing.