title: Predictive models for radial sap flux variation in coniferous, diffuse-porous and ring-porous temperate trees.
abstract: Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies.
authors.affiliation: University Program in Ecology, Duke University, Durham, NC 27708, USA Nicholas School of the Environment, Levine Science Research Center A311, Duke University, Durham, NC 27708, USA aaron.berdanier@gmail.com.
authors.forename: Aaron B
authors.initials: AB
authors.lastname: Berdanier
authors.affiliation: Coweeta Hydrologic Lab, USDA Forest Service, Southern Research Station, Otto, NC 28763, USA.
authors.forename: Chelcy F
authors.initials: CF
authors.lastname: Miniat
authors.affiliation: Nicholas School of the Environment, Levine Science Research Center A311, Duke University, Durham, NC 27708, USA Department of Statistical Science, Duke University, Durham, NC 27708, USA.
authors.forename: James S
authors.initials: JS
authors.lastname: Clark
mesh_terms: D008962:Models, Theoretical; D018526:Plant Transpiration / Q000502:physiology; D014197:Trees / Q000378:metabolism*; D014867:Water / Q000378:metabolism
chemical_list: D014867:Water
keywords: hierarchical Bayes; plant hydraulics; radial profile; water use; wood anatomy