Mr. Moshe (Vladislav) Dubinin

Dryland forests worldwide are increasingly threatened by drought stress due to climate change. Understanding the relationships between forest structure and function is essential for managing dryland forests to adapt to these changes. We investigated the structure-function relationships in four dryland conifer forests distributed along a semiarid to subhumid climatic aridity gradient. Forest structure was represented by leaf area index (LAI), and function by gross primary productivity (GPP), evapotranspiration (ET), and the derived efficiencies of water use (WUE= GPP/ET) and leaf area (LAE = GPP/LAI). Estimates of GPP and ET were based on the observed relationships between high-resolution vegetation indices from VENμS and Sentinel-2A satellites and flux data from three eddy covariance towers in the study regions. The red-edge-based MERIS Terrestrial Chlorophyll Index (MTCI) from VENμS and Sentinel-2A showed strong correlations to flux tower GPP and ET measurements (R2>0.9) that were higher than the MODIS-GPP and ET products (R2=0.60 and 0.72, respectively). Using our approach, we showed that as LAI decreased with decreasing AI (dryer conditions), estimated GPP and ET decreased (R2>0.8 to LAI), while WUE and LAE increased (R2=0.68 and 0.95, respectively, to LAI). We propose that the higher WUE and LAE reflect an increased proportion of sun vs. shade leaves as LAI decreases. The results demonstrate the importance of high-resolution spectral and spatial data in low-density dry forests and the intricate structure-function interactions in the forests’ response to drying conditions.