This repository contains the data and code supporting the analyses in the corresponding paper in Global Ecology and Biogeography (GEB). The abstract of the paper is as follows:

Background: In modeling and explaining spatial vegetation patterns, ecologists have increasingly favored the use of climatic water balance variables, including actual evapotranspiration (AET) and climatic water deficit (CWD), for representing the hydrologic and energetic environment experienced by plants. Much of the interest in these variables lies in their hypothesized potential to characterize biologically relevant environmental variation more directly than simple climate variables such as precipitation and temperature. Practically, obtaining AET and CWD values across space requires hydrologic process models that involve assumptions, including assumptions about vegetation transpiration rates. However, transpiration parameter values are rarely known with precision and can vary several-fold within and among vegetation types.

Approach: We evaluate the extent to which assumptions about vegetation physiology in water balance models affect (a) relative spatial variation in modeled water balance values and (b) ecological inferences that are derived from analyses using water balance variables. We demonstrate an approach for identifying inferences that are robust to these assumptions.

Results: Assumptions about vegetation physiology can substantially affect relative spatial variation in modeled water balance values. More importantly, such assumptions can also substantially affect the inferences (e.g., expected vegetation distributions) drawn from ecological analyses that employ water balance variables. Water balance variables are less sensitive to assumptions in environmental settings with abundant water supply, where AET variation is driven primarily by available energy (e.g., temperature and insolation), but they can be highly sensitive to assumptions in drier environments.

Conclusion: Because of their sensitivity to assumptions, water balance variables are not unambiguously superior to simpler climate and topographic variables such as precipitation and temperature. However, they retain some advantages, primarily related to their mechanistic incorporation of interactions between water and energy, which may support their use in applications where sensitivity to hydrological modeling assumptions is low or of minor concern.

The data in this repository consist of environmental variables (e.g., climate, topography, vegetation distribution) extracted and/or computed from publicly available datasets, as cited and described in the corresponding paper in Global Ecology and Biogeography (GEB). The repository also contains all the scripts needed to process the included data to reproduce the water balance modeling and all downstream analyses described in the paper.

This dataset consists of a repository of multiple data and script files, organized into folders, that is provided here as a single zipped folder. The data files in the "data" folder are organized such that they can be located and processed by the R scripts (located in the "scripts" folder) without any modification, assuming the R working directory has been set to the root folder of the repository. The most efficient approach to understanding the data files is to read the headers (and then, if still necessary, the code) of the analysis scripts in this repository. These scripts process the raw data to compute water balance values for grid cells across the study landscape. Other scripts in the repository then analyze the resulting water balance (and other) values to perform the analyses described in the GEB publication. The order in which the scripts should be run to reproduce the analyses in the GEB paper is indicated by the numbering at the beginning of the script filenames. An overview of all the scripts and their purposes can be found in the README.md file in the repository root directory. The repository contains some empty folders (e.g., "figures") because these folders will hold the output of the scripts.

One of the primary data files is "data/wb_input/wb_input_vars2.gri", which is a geospatial grid of climate and other geophysical variables used as inputs to the water balance model. The variables contained in this grid are described in the header of the script "scripts/01_run_water_balance.R".