Abstract

Sap flow measurements are a crucial tool for studies of plant water relations, but upscaling to tree or stand transpiration requires accounting for the radial distribution of sap flow across the stem. Because radial sap flow profiles cannot be measured with single-point measuring methods, predicting their shape based on easier to measure structural or functional traits is a potential route to cost-efficiently improve water-use estimates.We used heat field deformation (HFD) sensors to measure sap flux density at different sapwood depths on 38 trees of eight tropical tree species in secondary dry forest patches in north-west Costa Rica. Based on a Bayesian hierarchical modeling framework, we developed a flexible model for radial profiles that expresses the average profile depth and the spread of the profile around this depth as functions of tree height, wood density and stem growth rate, while allowing for random tree and species effects. From the model output, we scale up to approximate whole-tree daily water use (DWU).Our model revealed pronounced tree height effects, with taller trees having narrower sap flow profiles peaking closer to the cambium. While it explained 96% of the variance in the dataset, large fractions were attributed to random species and tree individual effects. Including functional traits as predictors improved the accuracy of predictions considerably both for new trees and new species. DWU responded positively to tree height, but not to annual stem increment and wood density. Extrapolating the average sap flux in the outermost 2 cm over the entire sapwood area overestimated DWU on average by 26% compared to estimates based on radial profiles.Our model provides a starting point for future studies aiming to improve landscape-scale water-use estimates integrating single-point sap flow measurements and radial profiles from a subset of trees.

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