These data were generated to evaluate the effects of compound hydroclimatic extremes – a deluge during drought – on production and carbon cycling in a semi-arid (shortgrass steppe) grassland in Colorado (USA). The study experimentally imposed an extreme drought and then interrupted this drought with either a single extreme deluge event or the equivalent amount of precipitation provided in several smaller events. This design, focused on how the combined effects of extreme drought and deluge altered productivity and carbon cycling relative to a control treatment receiving ambient rainfall and a drought treatment that received an equal amount of precipitation delivered as events more typical of contemporary rainfall regimes. Research was conducted at the 6,500 ha USDA-Central Plains Experimental Range (CPER), which is part of the Long-Term Agroecosystem Research network (LTAR; 2012-present; https://ltar.ars.usda.gov/), a former Long-Term Ecological Research station (LTER, 1983-2012), and located in the shortgrass steppe of north-central Colorado, USA. Additional information and referenced materials about many of the long-term studies initiated on the CPER can be found: https://dx.doi.org/10.25675/10217/81141. During the 2019 growing season (May-Aug), four precipitation treatments were randomly assigned to forty 1 m^2 plots spaced 2 m apart (n = 10 per precipitation treatment). Precipitation was excluded during the growing season by installing clear plastic roofs (2.2 x 2.2 m) over each plot and then added water to simulate four precipitation treatments: 1. a control treatment (“CON”; based on the exact pattern and amount that occurred at the site in 1989 – a year with an average precipitation regime, see below), 2. a drought treatment (“DRT”; a 77.5% reduction in each event added to the control plots), 3. a drought plus deluge treatment (“DRT+DEL”; the DRT treatment with a 60 mm deluge added mid-July) and 4. a drought plus small events treatment (“DRT+SE”; the DRT treatment, with a total of 60 mm of precipitation added to nine events from mid-July through mid-August). Over the course of the experiment, four response variables were measured: soil moisture, greenness, carbon fluxes, and productivity. Soil moisture was measured weekly from 0-100 cm at 10 cm increments using a Sentek Diviner probe on a subset of plots (n=3 per treatment), using a site-based calibration to calculate volumetric water content. Weekly plot canopy greenness was estimated using repeat digital photography, by calculating the average green chromatic coordinates (GCC) of the pixels in each photograph. Carbon flux measurements were conducted on a subset of plots (n = 5) using a custom portable flux chamber (0.5 x 0.5 x 0.5 m) attached to a LI-6400. During each measurement, data were logged over a 2 min period to collect the light measurement (net ecosystem exchange; NEE), then the chamber was vented for 7 sec and another measurement was taken during a 2 min period of darkness imposed by an opaque chamber cover (ecosystem respiration; ER). After collection, the data were processed, and the last 30 sec of the measurement were averaged to produce a single value for NEE and ER per measurement. Gross primary production (GPP) was calculated as GPP = NEE – ER. Aboveground net primary production (ANPP) was measured in all plots (n = 10 per treatment) at the end of the growing season (mid-September). In each plot, all plant material from two 0.1 m^2 subplots was harvested to ground height. Belowground net primary production (BNPP) was estimated as fine root mass production measured using root ingrowth cores. Net primary production (NPP) was estimated by summing ANPP and BNPP from each plot.
- CSVExperimental precipitation
- CSVData Dictionary for Experimental Precipitation
- CSVExperimental Soil Moisture
- CSVData Dictionary for Experimental Soil Moisture
- CSVExperimental Greenness
- CSVData Dictionary for Experimental Greenness
- CSVExperimental Carbon Fluxes
- CSVData Dictionary for Experimental Carbon Fluxes
- CSVExperimental Productivity
- CSVData Dictionary for Experimental Productivity