Predicting the Water Content of Larrea tridentata Using Spectral Indices

Analyzing leaf optical properties has become a useful method for measuring plant physiological status. The measurements become fast and affordable when coupled with remote sensing, but must first be tested for accuracy on the species of interest. In this study, we examined the correlation between spectral water indices and relative water content of individual leaves for the desert shrub, Larrea tridentata. Leaf-level reflectance measurements were taken periodically as detached Larrea branches desiccated. Four spectral indices were determined from the reflectance data: the water index (WI), the normalized difference vegetation index (NDVI), the normalized water index (nWI) and the structure independent pigment index (SIPI).  Index values were compared to measurements of leaf relative water content (RWC) to determine how well these indices predict plant water status. All indices showed a relatively linear relationship across water contents raging from 7 to 70%. WI had the most predictive capability, however the correlation is relatively weak (R²=0.529). This study shows that there is a correlation between leaf reflectance and the water status of Larrea tridentata, but the indices may only be valuable when looking at large differences in RWC.