DOI: 10.25338/b8534k
title: Data from: The utility of climatic water balance for ecological inference depends on vegetation physiology assumptions

description: 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.
description: 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 <em>Global Ecology and
 Biogeography</em> (<em>GEB</em>). 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.
description: 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 <em>GEB</em>
 publication. The order in which the scripts should be run to reproduce the
 analyses in the <em>GEB</em> 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".