Tree species explain only half of explained spatial variability in plant water sensitivity

Spatio-temporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically-driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant wate..., The plant water sensitivity (PWS) data were calculated at 4 km resolution based on remote sensing-derived estimates of live fuel moisture content. The live fuel moisture content data, in turn, were retrieved according to the algorithm developed in the article:
Rao, K., Williams, A. P., Flefil, J. F., & Konings, A. G. (2020). SAR-enhanced mapping of live fuel moisture content. Remote Sensing of Environment, 245, 111797.
The PWS was then calculated based on the lagged relationship between live fuel moisture content and 4 km dead fuel moisture content.
We calculated the locations of all Forest Inventory and Assessment sites where at least 75% of the basal area is from a single species, and sampled the PWS at the 4 km pixel that contained each of these FIA sites. We then built a random forest model to predict PWS based on ten climatic, vegetation density, soil, and topographic predictors and compared the explanatory power of that random forest model to a model that predicts PWS based on..., , # Data for: Tree species explain only half of explained spatial variability in plant water sensitivity

[https://doi.org/10.5061/dryad.g1jwstr05](https://doi.org/10.5061/dryad.g1jwstr05)

This dataset contains the inputs for, and outputs of, an analysis that compares how well an integrated metric of 'plant water sensitivity' can be explained by species type versus biogeographic factors. The plant water sensitivity metric is based on remotely sensed vegetation live fuel moisture content, and a map of this quantity across the Western United States is included. Also included are the maps of the biogeographic factors used to predict plant water sensitivity, as well as the predictions from both the biogeography and species-based models.

## Description of the data and file structure

Two files are included in this dataset. These include:

1\) PWS.tiff: a GeoTIFF file that maps the plant water sensitivity (PWS) across the Western United States at 4 km

2\) PWS_species.nc: This netCDF file con...,