Storage and Transit Time Data and Code

Author: Andrew J. Felton<br> Date: 7/11/2023 This R project contains the primary code and data used for data production, manipulation,<br> and analysis and figure production for the study entitled: "Global estimates of the storage and transit time of water through vegetation" Please note that 'turnover' and 'transit' are used interchangeably in this project. Data information: The data folder contains key data sets used for analysis. In particular: "data/turnover_from_python/annual/annual_turnover.nc" contains a global array<br> summarizing annual transit, storage, canopy transpiration, and number of<br> months of data. This data is also available is separate .csv files for each land<br> cover type. The same can be found for the minimum, monthly, and seasonal transit<br> time found in their respective folders. These data were produced using the python<br> code found in the "supporting_code" folder. The remaining files in the "data" and<br> "data/supporting_data"" folder primarily contain ground-based estimates of<br> storage and transit found in public databases or through a literature search. #Code information Python scripts can be found in the "supporting_code" folder. Each R script in this project has a particular function: 01_start.R: This script loads the R packages used in the analysis, sets the<br> directory, and imports the user-created functions for the project in the 02_functions.R script. This script can also download the annual and minimum <br> transit datasets, which are core to the analyses. 03_generate_data.R This script is not necessary to run and is primarily<br> for documentation. The main role of this code was to import and wrangle<br> the data needed to calculate ground-based estimates of aboveground water storage. 04_annual_turnover_storage_import.R: This script imports the annual turnover and<br> storage data for each landcover type. 05_minimum_turnover_storage_import.R: This script imports the minimum turnover and<br> storage data for each landcover type. Minimum is defined as the lowest monthly<br> estimate. 06_figures_tables.R: This is the main workhouse. This script generates the key <br> figures and summary statistics used in the study that the get saved in the <br> manuscript_figures folder. Maps were produced using Python code found in the<br> "supporting_code"" folder