Aridity and drought events are expected to increase in many regions due to global climate change. Predicting their impact on forest productivity and tree mortality remains a challenge. A recently developed stomatal control model, based on an optimization criterion between photosynthesis gain and hydraulic risk, enables predicting stomatal responses under different environmental conditions (light, CO2, temperature, soil moisture, relative humidity). Its parameterization requires plant traits such as xylem vulnerability curves (VCs), leaf to basal area ratio (LA/BA), leaf specific conductivity (LSC), and maximum rate of carboxylation (Vmax). In order to evaluate the impact of plant trait variability on model predictions and the applicability of this model to large distribution areas we: (i) analyzed trait variability in ten aspen (Populus tremuloides Michx.) stands located across Utah; (ii) compared observed midday water potentials, Ψmidday, and native stem conductance, ks, and conductivity, Ks, to predicted values obtained running the model with individual tree traits vs. mean stand traits vs. mean species traits; and (iii) used the model to infer the combinations of predawn xylem pressure (Ψpredawn) and vapor pressure deficit (VPD) that would threaten these stands by reducing net carbon assimilation (Anet) or increasing whole plant PLC relative to unstressed maxima.
Results/Conclusions
Root VCs were similar among stands and their mean 50% loss in hydraulic conductivity (P50) ranged from -0.5 to -1.4 MPa. Stem VCs differed among stands and the mean P50 of stems for stands ranged between -1.2 and -3.9 MPa. LA/BA and LSC were significantly different among stands; stand means ranged 1,851–2,815 cm2/cm2 and 1.2–8.4 mmol s-1 m-2 MPa-1, respectively. Vmax estimations varied from 38 to 240 µmol m-2 s-1. The mean deviation between the observed and predicted Ψmidday was 0.44 MPa running the model with individual tree values (n=59), 0.29 MPa running it with stand means (n=10), and 0.18 MPa running it with species mean for each stand (n=10). This suggests that running the model with mean species values provides better Ψmidday predictions. Observed native Ks correlated with modeled ks values for individual trees (r=0.44, p<0.001) but not for stand and species means (p>0.05). The model showed that Anet is negative at Ψpredawn ≤-0.7 MPa for high VPD (4.25 Pa) and ≤-1.7 MPa for low VPD (1 Pa). 60-70 whole plant PLC increases mortality risk, and these values were reached at -1.1 and -1.5 MPa Ψpredawn, respectively. Only one stand reached this threshold.