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Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape?
,This dataset contains growing season precipitation data collected from an extensive rain gauge network with thirty catch cans distributed on the USDA-Central Plains Experimental Range (CPER) in Nunn, Colorado from 1982-2013. The CPER is a site in the USDA Long-term Agroecosystem Research Network. These data provide records of long-term observations, which can be applied to assess responses to naturally occurring deluges across the 62.7 km2 CPER in NE Colorado, a SGS ecosystem with significant spatial variation in precipitation received during the growing season, soils and grazing management, and where several small-scale deluge experiments have been conducted.,,
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Data from: Compound hydroclimatic extremes in a semi-arid grassland: Drought, deluge and the carbon cycle
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,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.,,
Patterns of precipitation and productivity on various topographic positions on the Central Plains Experimental Range, Nunn, Colorado
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,Thirty-six years of aboveground net primary productivity (ANPP) data collected across a topographic sequence in the semiarid shortgrass steppe of North America to examine patterns and drivers of spatiotemporal variability in ANPP. ANPP data were collected from the 6,500 ha USDA-Central Plains Experimental Range (CPER), which is part of the Long-Term Agroecosystem Research (LTAR; 2012-present; https://ltar.ars.usda.gov/) network, 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.,The topography at the CPER is characterized by gently rolling hills, and the topographic positions for data collection were focused along a catena in one of the most common ecological sites on the CPER, Loamy Plains (ID: R067BY002CO; NRCS, 2020). The plant community included four herbaceous plant functional types (PFTs): 1) perennial, warm-season, C4 grasses (primarily Bouteloua gracilis [Willd. ex Kunth] Lag ex Griffiths and B. dactyloides [Nutt.] J.T. Columbus), 2) perennial, cool-season, C3 grasses (primarily Pascopyrum smithii [Rydb] A. Love and Hesperostipa comata [Trin. & Rupr.] Barkworth ssp. comata), 3) cool-season, annual grass (Vulpia octoflora [Walter] Rydb.), and 4) forbs (primarily Sphaeralcea coccinea [Nutt.] Rydb.). Shrubs, subshrubs, and cactus were present but do not represent a large component of total ANPP and were not included in this study.,Daily precipitation data were obtained from a long-term (1979-2018) precipitation gauge associated with the National Atmospheric Deposition program (Site ID: NTN-CO22; http://nadp.slh.wisc.edu/), located on site. Missing precipitation data were gap-filled using CPER headquarters data (1939-2018), or from the Soil Climate Analysis Network (SCAN) rain gauge (1997-2018, Site Number: 2017; https://wcc.sc.egov.usda.gov/), depending on proximity and temporal overlap. Following gap-filling, precipitation data were omitted if >10% of the time series was missing for each focal time period (e.g. fall or spring).,,
Precipitation Frequency for Semiarid Southwest, USA - NOAA Atlas 14 Volume 1
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This GIS grid atlas contains precipitation frequency estimates for the Semiarid Southwest based on precipitation data collected between 1893-2000. This atlas is an updated version of volumes IV (New Mexico), VI (Utah), VII Nevada), VIII (Arizona), published in 1973. The grids provide information for durations from 5 minutes through 60 days, and for return periods of 1 year through 1000 years. All grids are in geographic coordinate system (NAD84 horizontal datum) and units are in 1000th of inches. The grid data also contains estimates for California from NOAA Atlas 14 Volume 6 Version 2. Please see the metadata page for the California portion of the grid.
Assessing the rate and reversibility of large herbivore effects on community composition in a semi-arid grassland ecosystem with GZTX data on the Central Plains Experimental Range, Nunn, Colorado, USA 1992-2017
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,This data package was produced initially by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Then, was continued by the Rangeland Resources and Systems Research Unit of the USDA Agricultural Research Service. Data collection was conducted on the Central Plains Experimental Range in Nunn, Colorado.,When the CPER was established in 1939, researchers constructed a .5-1 ha grazing exclosure in each of the pastures. These areas have remained protected from grazing for the past 70 years. The remaining areas have been grazed for the past 20+ years. This collection of pastures and exclosures provided an extraordinary opportunity to reinitiate grazing and protection, and evaluate the balance between degradation and aggradation. We proposed to rearrange fences and expose areas to grazing that have been protected for 50 years, and protect areas from grazing that had been grazed for 50 years. The combinations of grazing conditions were: 1. Long-term protection 2. Long-term grazing (moderate) 3. 50 years of protection followed by grazing 4. 50 years of grazing followed by protection Net primary production, nitrogen dynamics, cattle utilization, and community dynamics of vegetation were measured. Additional information and referenced materials about many of the long-term studies initiated on the CPER can be found: http://hdl.handle.net/10217/85596.,,
Spreadsheet of normalized Taylor diagram statistics for multi-day extreme precipitation in six regions in the contiguous U.S. (Extreme precipitation statistics.xlsx)
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The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) are collaborating with the U.S. Federal Emergency Management Agency (FEMA) on improving flood-frequency analysis methods to account for mixed populations arising from different flood causal mechanisms. Precipitation data at different timescales are widely used in flood-typing studies. Various gridded precipitation datasets were validated by comparison against station observations to support flood-typing over six pilot regions in the contiguous U.S. (CONUS) where flood-typing approaches will be initially tested. The six pilot regions are (1) the Delaware River, (2) the Iowa River, (3) Puget Sound, (4) the Red River of the North, (5) the Trinity River, and (6) the Upper Colorado River. The datasets were validated by comparison against gage data from the NOAA Global Historical Climatology Network daily (GHCNd) for the periods 1981-2013 and 1998-2013. A Microsoft Excel workbook is provided, which tabulates normalized Taylor diagram statistics for multi-day extreme precipitation in each pilot region for the two periods. Extreme precipitation of 1-, 2-, 3-, 5-, 7-, 10-, and 14-day duration were evaluated. The statistics evaluated include the Pearson correlation coefficient, the standard deviation ratio, the centered root-mean-square difference, the percent bias, and the Kling-Gupta efficiency (KGE) metric. The gridded precipitation datasets include: (1) 20th Century Reanalysis Version 3 (20CRV3) dataset, (2) the Analysis of Record for Calibration (AORC) dataset, (3) the four-kilometer long-term (40-year) regional hydroclimate reanalysis over the conterminous United States dataset (CONUS404), (4) a bias-adjusted version of CONUS404 (CONUS404BA) which uses the Daymet version 3 dataset for bias adjustment, (5) the European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis - Fifth Generation dataset (ERA5), (6) a downscaled version of ERA5 precipitation (ERA5-Land), (7) the gridded precipitation dataset by Livneh et al. (Livneh), (8) a version of the Livneh dataset that does not split reported 24-hour precipitation between subsequent days (Livneh-unsplit), (9) the Parameter-elevation Regression on Independent Slopes Model (PRISM) dataset, and (10) the Stage IV dataset. Stage IV was not included in the 1981–2013 analysis since it is only available since 1997.
Vegetation cover from a precipitation manipulation experiment at the Spruce Gulch Wildlife and Research Preserve, Colorado
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These data consist of plot-level plant species cover measurements from a precipitation manipulation experiment located in the Spruce Gulch Wildlife and Research Reserve near Boulder, Colorado. This data release consists of absolute percent live foliar cover measurements of all plant species within each plot for the years 2011, 2012, 2013, 2020, 2021, 2022, and 2023. From 2011-2013, plots received one of three precipitation manipulations over the winter (October through March) and summer (April-September): 'reduce' = 50 percent reduction in ambient precipitation, 'increase' = 50 percent increase in ambient precipitation, or 'ambient' = no manipulation of precipitation. Precipitation was reduced through the use of rain-out shelters that blocked precipitation from half of each plot. Precipitation was increased by irrigating plots using water from a local well. The 'increase' precipitation treatments were discontinued after 2013, and thus some winter and summer precipitation treatments for plots were reassigned in 2020-2023.
Vegetation cover from a precipitation manipulation experiment at the Spruce Gulch Wildlife and Research Preserve, Colorado
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These data consist of plot-level plant species cover measurements from a precipitation manipulation experiment located in the Spruce Gulch Wildlife and Research Reserve near Boulder, Colorado. This data release consists of absolute percent live foliar cover measurements of all plant species within each plot for the years 2011, 2012, 2013, 2020, 2021, 2022, and 2023. From 2011-2013, plots received one of three precipitation manipulations over the winter (October through March) and summer (April-September): 'reduce' = 50 percent reduction in ambient precipitation, 'increase' = 50 percent increase in ambient precipitation, or 'ambient' = no manipulation of precipitation. Precipitation was reduced through the use of rain-out shelters that blocked precipitation from half of each plot. Precipitation was increased by irrigating plots using water from a local well. The 'increase' precipitation treatments were discontinued after 2013, and thus some winter and summer precipitation treatments for plots were reassigned in 2020-2023.
Standardized Precipitation-Evapotranspiration Index for western United States, 2001-2014, derived from gridMET climate estimates
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These data are 30m by 30 m grids of the mean Standardized Precipitation-Evapotranspiration Index (SPEI) between 2001-2014 in the western United States. The SPEI index was developed by Sergio M. Vicente-Serrano and coauthors (https://spei.csic.es/index.html). Source evapotranspiration and precipitation data were generated by gridMET (http://www.climatologylab.org/gridmet.html).
Standardized Precipitation-Evapotranspiration Index for western United States, 2001-2014, derived from gridMET climate estimates
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These data are 30m by 30 m grids of the mean Standardized Precipitation-Evapotranspiration Index (SPEI) between 2001-2014 in the western United States. The SPEI index was developed by Sergio M. Vicente-Serrano and coauthors (https://spei.csic.es/index.html). Source evapotranspiration and precipitation data were generated by gridMET (http://www.climatologylab.org/gridmet.html).