fluxfixer: An R package for producing thermal dissipation sap flow data with high quality control

The thermal dissipation method is crucial for estimating tree transpiration, a major component of terrestrial water cycling. However, this method requires careful quality control (QC), and no post-processing software exists for automatic QC that can apply to raw time series with various artifacts. Hence, we developed a novel R package to conduct sophisticated QC combined with statistical methods and machine learning. We further provided selective methods for calibrating the zero-flow conditions. We demonstrate the package’s effectiveness by post-processing raw data observed in a Bornean tropical rainforest. This package will help establish a standardized protocol for processing low-quality sap flow data.