Long-term precipitation reduction experiment in the Colorado Plateau - Survival and mortality data from 2010 to 2018

From 2011-2018 USGS biologists recorded vegetation and biological soil crust (BSC) cover by species and tracked survival of tagged individual plants (388 in total) across 40 locations where paired experimental plots had been installed in 2010. Plant cover was visually estimated using four 75 x 100 cm survey frames. Each site contained a two plots measuring 1.5 by 2.0 meteres: a control plot and a plot covered by a shelter that excluded 35% of incoming precipitation. Plots were selected to represent shallow vs. deep soils, sandstone vs. shale parent material, and dominant plant species on the Colorado Plateau around Moab, Utah. We used an information theoretic approach using generalized linear models to determine the combination of factors that best predicted mortality. We included treatment, year, and species as fixed effects in our first order models to test for treatment effects on mortality while accounting for the influence of interannual-climate variability and species-level differences. Models also included individual plant ID nested within site as random effects to account for pseudo-replication across sites and tagged individuals. We continued with a second set of models by adding abiotic variables including elevation (m), soil depth (shallow or deep), and parent material as additional explanatory variables to the best-fit model.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
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identifier USGS:5be0b552e4b0b3fc5cf341bd
metadata_type geospatial
modified 20200827
old-spatial -110.624396804, 37.897065877, -108.576922846, 38.994330927
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash 85f4dab6f855dd310d6714fc8fd44a2efeb34bc9
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spatial {"type": "Polygon", "coordinates": [[[-110.624396804, 37.897065877], [-110.624396804, 38.994330927], [ -108.576922846, 38.994330927], [ -108.576922846, 37.897065877], [-110.624396804, 37.897065877]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • biogeography
  • biological-soil-crust
  • biota
  • bromus
  • canyonlands
  • cheatgrass
  • ckan
  • climate-change
  • colorado-plateau
  • control-plot
  • deep-soils
  • experimental-plot-data
  • geo
  • geology
  • geoss
  • graminoids
  • grand-county
  • grass
  • grassland-ecosystem
  • indian-creek
  • moab
  • national
  • north-america
  • parent-material
  • perennial
  • plant-populations
  • plant-species
  • plot-sampling
  • salsola
  • san-juan-county
  • sandstone
  • shale
  • shallow-soils
  • shelter-plots
  • shrubland-ecosystem
  • shrubs
  • soil-sciences
  • species-cover
  • united-states
  • usgs-5be0b552e4b0b3fc5cf341bd
  • utah
  • vegetation
isopen False
license_id notspecified
license_title License not specified
maintainer Erika L Geiger
maintainer_email egeiger@usgs.gov
metadata_created 2025-11-21T10:09:23.836532
metadata_modified 2025-11-21T10:09:23.836536
notes From 2011-2018 USGS biologists recorded vegetation and biological soil crust (BSC) cover by species and tracked survival of tagged individual plants (388 in total) across 40 locations where paired experimental plots had been installed in 2010. Plant cover was visually estimated using four 75 x 100 cm survey frames. Each site contained a two plots measuring 1.5 by 2.0 meteres: a control plot and a plot covered by a shelter that excluded 35% of incoming precipitation. Plots were selected to represent shallow vs. deep soils, sandstone vs. shale parent material, and dominant plant species on the Colorado Plateau around Moab, Utah. We used an information theoretic approach using generalized linear models to determine the combination of factors that best predicted mortality. We included treatment, year, and species as fixed effects in our first order models to test for treatment effects on mortality while accounting for the influence of interannual-climate variability and species-level differences. Models also included individual plant ID nested within site as random effects to account for pseudo-replication across sites and tagged individuals. We continued with a second set of models by adding abiotic variables including elevation (m), soil depth (shallow or deep), and parent material as additional explanatory variables to the best-fit model.
num_resources 2
num_tags 44
title Long-term precipitation reduction experiment in the Colorado Plateau - Survival and mortality data from 2010 to 2018