MOnitorIng water Status beyond the Tree scale: new tools for forest health assessment

Increasing droughts reduce the water stored in trees leading to widespread forest mortality and higher fire risk. To know where and when forests are endangered, it is crucial to regularly monitor their water status at large (plot to regional) scales. However, there is a large information scale gap between the current measures of water status at the tree level and the target larger scales. Remote sensing retrievals of vegetation optical depth (VOD) can bridge this gap. The VOD is a parameter retrieved using global navigation satellite systems transmissometry (at plot scale) and satellite radiometry (at up to global scale). Recent research shows how water information can be isolated from VOD, and points to the application of different microwave frequencies to sense water in different tree tissues. In MOIST, VOD at plot and regional scales will be compared to in situ leaf and stem ecophysiological data. The VOD will be used to estimate water content in leaves and stems. Then, ecosystem-scale pressure volume curves, a novel concept in plant ecophysiology, will be applied to retrieve water potential estimates at plot and regional scales for the first time. Results will be provided to fire and forestry administrations to enhance their assessment of drought risks on forests. MOIST will combine remote sensing and ecophysiology, involve an international network of researchers, and work with a supervisor and a research center who are world-leading experts in forest ecophysiology. MOIST will reach international publics and engage young generations in taking care of forests. The applicant, Dr. David Chaparro, has the ideal remote sensing skills and dissemination experience to undertake this project, which is also perfectly designed to expand his skills, leveraging his career. With novel approaches to monitor the forests’ water status at large scales, MOIST will bridge the water information scale gap and provide unprecedented tools to assess forest conditions and risks.