Background/Question/Methods Forests are more than just the sum of the trees that compose them, yet a detailed quantification of tree-level water use facilitates constrained transpiration estimates at larger spatial scales, such as, for example, the forest stand-, catchment-, or ecosystem-level. Stem water movement (sap flow) encompasses critical tree functions that are linked to numerous land-atmosphere interactions triggered by plant transpiration, a substantial green water flux. Moreover, sapwood, apart from being the backbone of sap flow-based transpiration estimates, is also a key structural trait that describes trees’ investments into their water transport tissues. Here, focusing on a diverse range of temperate and boreal tree species from eastern North America and covering species from different taxa (angiosperms and gymnosperms) and xylem porosities (tracheid-bearing, diffuse- or ring-porous species), I provide a cross-scale synthesis of water fluxes from the tissue-, tree-, up to the landscape-level. Tissue-level insights on sapwood characteristics and wood anatomy were combined with sap flow observations to derive tree-level transpiration estimates. This tree-level understanding was then coupled with detailed description of forest structure and composition, based on field surveys and remote sensing products, to derive upscaled transpiration estimates at higher levels of spatial organization.
Results/Conclusions This tree-centered approach provides quantitative insights into the transpiration dynamics across a wide range of spatial scales and pinpoints critical uncertainties in the sap flow upscaling workflow. Moreover, the wealth of compiled observations across a wide species range and environmental conditions, sheds novel light into tree water use dynamics, including inter-specific differences as well as dependences, or lack thereof, of sapwood allometry, radial profiles of axial sap flow, and total tree water use on xylem porosity and tree architecture. Species clustering based on taxa or xylem porosity groups captures a large part of the variability in key parameters in the sap flow upscaling workflow (e.g., sapwood characteristics, radial variability in axial sap flow), facilitating more constrained transpiration estimates across larger spatial scales. When combined with an increasing number of sap flow observations and remote sensing products, these findings can improve tree- and landscape-level transpiration estimates, leading to more robust partitioning of terrestrial water fluxes.