Predicting tree-level sap flow from point dendrometer and climate data

Climatic drought and changes in precipitation patterns are key features of the ongoing and predicted climatic changes in northern latitudes such as the boreal forest of Norway. Recent droughts highlight on the possible difficult future of spruce forests in southern Norway. To better understand and monitor these forests under a more extreme climate, it is crucial to gain a better understanding of the water relations of spruce trees across forest stands. Sap flow sensors are typically used for directly measuring the water demands for transpiration in individual trees. There are however limitations to their use in examining the hydraulic and physiological responses to extreme water supply variability: i) manufactured high-resolution sensors such as those following the Heat Ratio Method (HRM) or Heat Field Deformation (HFD) are expensive, limiting their deployment to a few trees in a stand, and ii) the sap flow sensors only measure the movement of water within the active sapwood, not accessing other physiological mechanisms and responses (radial growth, water storage) associated with stress response. Point dendrometers have become increasingly used, monitoring sub-daily stem size fluctuations resulting from both seasonal patterns of radial growth increment and the dynamics of plant tissue water balance. Manufactured point dendrometers are much cheaper to buy and easier to install and maintain than manufactured sap flow sensors. They can therefore be much more extensively deployed across forest stands. We aimed to analyse the relationship between sub-daily stem diameter changes and sap flow using point dendrometers and HRM sap flow sensors installed in a Norway spruce forest located 50 km north of Oslo, Norway. We linked these relationships with individual tree physical attributes, meteorology and soil climate over two growing seasons in 2022 and 2023. Our goal was to assess whether a predictive model of sap flow could be built from measured diameter changes, tree properties and climate, to ultimately reduce the uncertainty of stand level transpiration estimation at the daily resolution across entire forest stands.