Spatiotemporal patterns of cheatgrass invasion in Colorado Plateau National Parks

  • Tara B. B. BishopEmail author
  • Seth Munson
  • Richard A. Gill
  • Jayne Belnap
  • Steven L. Petersen
  • Samuel B. St. Clair
Research Article



Exotic annual grasses are transforming native arid and semi-arid ecosystems globally by accelerating fire cycles that drive vegetation state changes. Cheatgrass (Bromus tectorum), a particularly widespread and aggressive exotic annual grass, is a key management target in national parks of the western United States due to its impacts on wildfire and biodiversity loss. Cheatgrass is known for its high interannual variability and can grow in a wide range of conditions.


The objectives were to (1) map the presence and persistence of cheatgrass in national park units across a 11-year period using remote sensing, and (2) identify the biophysical parameters that correlate with cheatgrass persistence.


We used remote sensing and GIS tools to develop a systematic model to characterize the status and environmental correlates of cheatgrass invasions in seven national park units in the western United States.


On average cheatgrass covered 3.8% of park areas, each park ranging from 0.8 to 24.8% coverage. Where cheatgrass was detected, persistent populations across time (hotspots) made up on average 13% of cheatgrass areas. Hotspots were found in areas with deeper plant-available water, lower elevations, colder mean winter temperatures, flatter slopes, higher soil clay content, and lower mean fall precipitation.


Study results identified spatiotemporal patterns of plant invasions and key environmental drivers that influence invasion patterns. GIS tool development and analysis from this study were used to generate invasion maps for each park, which can be used to mitigate wildfire and biodiveristy loss.


Bromus tectorum Cheatgrass Plant invasion Wildfire Remote sensing GIS Spatial modeling 



We gratefully acknowledge the funding provided by the Utah NASA Space Grant Consortium. Thanks to Phil Allen and Bruce Roundy for providing valuable feedback. We also thank Dennis Eggett for guidance on the statistical analysis, Ryan Howell and Catherine McQueen for their time and assistance in GIS data processing, and Kirk Sherrill for his dedication to remote sensing analysis. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Supplementary material

10980_2019_817_MOESM1_ESM.docx (240 kb)
Supplementary material 1 (DOCX 240 kb)


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© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2019

Authors and Affiliations

  1. 1.Department of Plant and Wildlife SciencesBrigham Young UniversityProvoUSA
  2. 2.U.S. Geological Survey, Southwest Biological Science CenterFlagstaffUSA
  3. 3.Department of BiologyBrigham Young UniversityProvoUSA
  4. 4.U.S. Geological Survey, Southwest Biological Science CenterMoabUSA

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