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Updated: Jun 4, 2025

The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees
Published on: December 27, 2017
A global dataset of tree hydraulic and structural traits imputed from phylogenetic relationships
James Knighton1, Pablo Sanchez-Martinez2, Leander Anderegg3
1Department of Natural Resources and the Environment, University of Connecticut, Storrs, Connecticut, USA. james.knighton@uconn.edu.
Abstract:
We present a dataset of plant hydraulic and structural traits imputed for 55,779 tree species based on TRY plant trait dataset observations and phylogenetic relationships. We collected plant trait values for maximum stomatal conductance (gsMAX), xylem pressure at 12%, 50%, and 88% conductance loss (P12, P50, P88), maximum observed rooting depth (rdMAX), photosynthetic Water Use Efficiency (WUE), maximum plant height (height), Specific Leaf Area (SLA), and leaf Nitrogen content (LeafN). We demonstrated that each of these traits exhibited remarkably large phylogenetic signals across all land plants. Based on the strength of this signal we then developed random forest (RF) models trained on TRY trait data to impute the traits of previously unstudied tree species using Phylogenetic Eigenvector Maps. We quantified imputed trait uncertainty by fitting RF model test dataset residuals to skew exponential power distributions accounting for heteroscedasticity, demonstrating encouraging lack of biases in the imputed dataset. The resulting dataset of imputed trait values can support global analyses of plant trait variations and species-level parameterization of earth systems models.
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