Linking between Water Use Efficiency and Leaf Area Index Along an Aridity Gradient in Dryland Forests

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 along an aridity index (AI) gradient in Israel and California, where 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. Using the red-edge-based index MTCI (MERIS Terrestrial Chlorophyll Index) in these analyses showed correlations (R 2 >0.9) that were much higher than for the MODIS-GPP and ET products vs. flux tower data (R 2 =0.60 and 0.72, respectively). Using our approach, we show that as LAI decreased with decreasing AI (dryer conditions), estimated GPP and ET decreased (R 2 >0.8 with respect to LAI), while WUE and LAE increased (R 2 =0.68 and 0.95, respectively, with respect to LAI). Increasing WUE may indicate leaf-scale stomatal closure and reduced water loss. Increasing LAE, in contrast, likely reflects the increased proportion of sun vs. shade leaves as LAI decreases. The results demonstrate the importance of high-resolution data (spectrally and spatially) in low-density dry forests and the intricate structure-function interactions in the forests’ response to drying conditions.