MIL-OSI USA: Predicting when the grass is greener: new phenological forecasts for invasive annual grasses

Source: US Geological Survey

Non-native, annual grass species like cheatgrass (Bromus tectorum) and red brome (Bromus rubens) were introduced to the United States in the late 1800s and have since invaded and critically transformed ecosystems like the sagebrush steppe and southwestern deserts. Where present, both grasses increase wildfire risk, reduce native wildlife habitat, and alter soil properties like erosion potential, nutrient availability, and water retention.

Their ability to invade so effectively is directly related to their phenology; both cheatgrass and red brome grow faster and flower earlier in the Spring than neighboring native plants. In disturbed habitats, like a burned grassland, these growth patterns give invasive grasses an advantage over native species, allowing them to dominate a habitat after disturbance.

Background photo: cheatgrass invasion of a post-fire landscape.

Invasive plant managers can exploit the phenological differences between native and invasive grasses by concentrating management actions like grazing or herbicide application on the window of time in early Spring when invasive grasses are growing and native grasses are not. However, it can be difficult to determine exactly when cheatgrass and red brome will begin different phases of their annual life cycle, given the myriad environmental variables, such as precipitation, elevation, and temperature, that can potentially affect plant growth.

In 2022, researchers set up a timelapse camera to take daily photographs of cheatgrass growth in Wyoming. In this slideshow, photos from every few weeks show how much faster cheatgrass completes its annual life cycle, compared to its native counterparts. The cheatgrass shoots up and flowers much earlier than the native grasses and dries out much sooner, turning red by the end of June while native grasses are still green.
Estimated dates of (A) flowering and (B) senescence of cheatgrass, and (C) flowering and (D) senescence of red brome for 2019 calculated using the top performing model from this study. Figure 4 from Prevéy and others (2024).

The phenology forecast models developed in this study can be adapted to:

  • Time management activities, such as intensive short-duration grazing, to reduce undesirable invasive grasses
  • Promote forage production and biodiversity in grasslands
  • Forecast when and where invasive annual grasses have dried out and fire danger may be greatest 
  • Aid remote sensing specialists in selecting imagery that captures distinctive phenological phases to accurately map invasive grasses

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