Deconstructing precipitation variability: Rainfall event size and timing uniquely alter ecosystem dynamics (Data)
Cite this dataset
Griffin-Nolan, Robert; Slette, Ingrid; Knapp, Alan (2021). Deconstructing precipitation variability: Rainfall event size and timing uniquely alter ecosystem dynamics (Data) [Dataset]. Dryad. https://doi.org/10.5061/dryad.kkwh70s4q
This dataset contains data from a rainfall manipulation experiment described in the paper: "Griffin-Nolan, R.J., Slette, I.J. and Knapp, A.K. (2021), Deconstructing precipitation variability: rainfall event size and timing uniquely alter ecosystem dynamics. Journal of Ecology. https://doi.org/10.1111/1365-2745.13724"
Water-limited ecosystems are highly sensitive to not only precipitation amount, but also precipitation pattern, particularly variability in the size and timing of growing season rainfall events. Both rainfall event size and timing are expected to be altered by climate change, but the relative responses of dryland ecosystems to changes in rainfall event size vs. timing has not been resolved. In this paper, we disentangle the effects of these different aspects of precipitation pattern on ecosystem dynamics.
We experimentally assessed how these two aspects of rainfall variability impacted a semi-arid grassland ecosystem by altering an ambient precipitation pattern to eliminate variability in (1) rainfall event size (all events were made the same size), (2) rainfall event timing (all events were uniformly spaced in time), and (3) both. Total precipitation amount was constant for all treatments. We measured responses of soil moisture, ecosystem carbon flux (e.g., net primary production and soil CO2 flux), plant community composition, and physiological responses of the dominant C4 grass, Bouteloua gracilis.
Removing variability in rainfall event size altered ecosystem dynamics more than a pattern of uniform event timing, but the largest impact occurred when variability in both were removed. Notably, eliminating variability in both event size and timing increased aboveground net primary productivity by 23%, consistent with reduced water stress in the dominant C4 grass, while also reducing seasonal variability in soil CO2 flux by 35%, reflecting lower seasonal variability in soil moisture.
Synthesis: Unique responses to different aspects of precipitation variability highlight the complexity of predicting how dryland ecosystems will be affected by climate change induced shifts in rainfall patterns. Our results provide novel support for the key roles of rainfall event size and timing, in addition to total precipitation amount, as determinants of ecosystem function.
The dataset was collected during a field study at the Central Plains Experimentla Range (Colorado, USA) and has been processed by a series of linear mixed models (R, lme4 package) to produce a manuscript accepted for publication in Journal of Ecology.
The readme file contains an explanation each datafile and associated units for each variable. Additional descriptions of the data are included in the shared R code, "final_analysis_051721.R".
Information on how the measurements were done can be found in the associated manuscript referenced above.
Division of Environmental Biology, Award: 1137378
Division of Environmental Biology, Award: 1137342
Division of Environmental Biology, Award: 1137363
National Institute of Food and Agriculture, Award: 2018-67019-27849