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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...
Tags: Botany,
Canyonlands,
Colorado Plateau,
Ecology,
Geography, All tags...
Grand County,
Indian Creek,
Information Sciences,
Moab,
Salsola,
San Juan County,
Soil Sciences,
USGS Science Data Catalog (SDC),
Utah,
biogeography,
biological soil crust,
biota,
bromus,
cheatgrass,
climate change,
control plot,
deep soils,
experimental plot data,
geology,
graminoids,
grass,
grassland ecosystem,
parent material,
perennial,
plant populations,
plant species,
plot sampling,
sandstone,
shale,
shallow soils,
shelter plots,
shrubland ecosystem,
shrubs,
shrubs,
soil sciences,
species cover,
vegetation, Fewer tags
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Grasslands in the Great Plains are of ecological, economic, and cultural importance in the United States. In response to a need to understand how climate change and variability will impact grassland ecosystems and their management in the 21st century, the U.S. Geological Survey North Central Climate Adaptation Science Center led a synthesis of peer-reviewed climate and ecology literature relevant to grassland management in the North Central Region (including Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, and Kansas). This synthesis was done to begin to address grassland managers’ information needs and identify research gaps. This open-file report summarizes the impacts of climate change and variability...
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