With climate change, many terrestrial ecosystems are experiencing more frequent and intense (hot) droughts. Plant responses to drought reflect the combined effects of soil water limitation and vapour pressure deficit, often compounded by heat. Understanding changes in transpiration, photosynthesis, and recovery after drought requires quantifying water transport and water stress along the soil–plant–atmosphere continuum.
Advances in in-situ measurements and remote sensing provide unprecedented information on plant responses to drought and their drivers. Continuous measurements of plant and soil water status, sap flow, dendrometry, and ecosystem fluxes from eddy-covariance can now be combined with satellite observations of evapotranspiration, canopy temperature, solar-induced fluorescence, soil moisture, vegetation water content and optical depth, linking plant- and ecosystem-level processes.
This wealth of data presents a unique opportunity for mechanistic modellers to improve simulations of water transport across the soil–plant–atmosphere continuum. Models increasingly account for plant hydraulics, plant water storage, detailed root water uptake, and access to subsurface water. Data assimilation, inverse modelling and hybrid or physics-informed machine learning can integrate these new observations to improve our understanding of the processes that control plant responses.
Despite these new opportunities, transferring knowledge across disciplines and scales remains a major challenge. Further work is needed to determine how hydraulic limitations in the rhizosphere and root zone affect stomatal regulation and canopy fluxes, and which hydraulic traits explain responses from individual plants to communities. Other challenges include bridging the gap between field and satellite observations and adequately representing heterogeneity, acclimation, drought legacy effects and recovery in models, together with the combined effects of soil water limitation and atmospheric drought.
This session aims to connect the fields of ecophysiology, ecohydrology, soil science, climate science, remote sensing and modelling. We encourage interdisciplinary contributions based on field experiments, monitoring networks, Earth observation, model development, model-data integration and data assimilation across natural and managed ecosystems. We particularly welcome studies that connect measurements, processes or scales, and contributions led by students and early career researchers.