Advanced Tree Physiological Data Processing in R

The increasing availability of tree physiological data provides unique opportunities for exploring tree and forest function, health, and resilience to ongoing environmental changes. However, processing and homogenizing such datasets is challenging. Within this workshop we offer comprehensive workflows on tree physiological time series data processing in R. We provide participants hands-on training on free software tools and their synergies for tree physiological data processing, spanning from interactive visual inspection and cleaning of raw data to advanced data analyses and uncertainty quantification.

Three main topics are covered: (1) Interactive and reproducible data cleaning with datacleanr (https://the-hull.github.io/datacleanr/), an R package designed to ensure best data-handling practices of spatiotemporal tree ecophysiological data. (2) Thermal dissipation sap flow data processing with the TREX (https://the-hull.github.io/TREX/ ), including converting heat metrics to sap flow, and estimating data-processing uncertainties. (3) Dendrometer data processing with treenetproc (https://github.com/treenet/treenetproc/), an R package with advanced functionalities on partitioning stem growth and hydraulic signals from dendrometer data and on detecting growing season dynamics.

Guided by example datasets, this workshop presents a toolbox for interactive and reproducible tree physiological data processing in R. Participants should bring their own laptops with pre-installed R/RStudio (https://rstudio.com/).

The presentation for the course can be found here.