Data for: Evaluation of Partitioning Methods to Identify Timescale-Dependent Drivers of Light Use Efficiency in a Wet Tropical Forest

Half Hourly EddyPro processed, EddyPro setting, metadata, and weekly partitioned data (from the daytime afternoon, nighttime, and sundown partitioning methods) accompanying: Bigwood et al., “Evaluation of Partitioning Methods to Identify Timescale-Dependent Drivers of Light Use Efficiency in a Wet Tropical Forest” This repository contains the processed data for the analyses in the manuscript. The data were collected at La Selva Biological Station, Costa Rica, from July 2022 to May 2023. This dataset will be further organized and expanded upon during the peer-review process and upon acceptance of the manuscript. Variables in the EddyPro processed data can be found here. Varibales in the la_selva_partitioning_methods.csv and lue_rfm_cv_predictions.csv are found in GitHub. The Github and associated readme file will be edited to include figure recreation code.