Modeling cheatgrass distribution, abundance, and response to climate change as a function of soil microclimate

Area of Science:

• Ecology
• Invasive Species Management
• Climate Change Impact

Background:

• Exotic annual grasses degrade native ecosystems and increase fire risk, especially in water-limited regions.
• Invasive species' sensitivity to weather variability complicates accurate distribution and abundance modeling.
• Current remote sensing models offer a coarse understanding of species-weather interactions, hindering climate change vulnerability assessments.

Purpose of the Study:

• To quantify soil microclimate favorability for cheatgrass (Bromus tectorum L.) establishment and growth.
• To develop a model predicting cheatgrass distribution and abundance using mechanistic germination and soil microclimate data.
• To assess the impact of climate change on cheatgrass distribution in the western United States sagebrush steppe.

Main Methods:

• Derived germination covariates (rate sums) from mechanistic models of germination and soil microclimate.
• Utilized 2662 sites across the sagebrush steppe over 30 years.
• Employed four bioclimatic covariates to predict cheatgrass distribution and abundance.

Main Results:

• The model accurately predicted cheatgrass distribution (72% overall accuracy), comparable to remote sensing models.
• Model explained patterns of abundance poorly (R² = 0.22).
• Climatic suitability depends on spatial and temporal variations in fall and spring soil moisture and temperature; fall conditions were more influential.
• Suitable microclimatic conditions for cheatgrass expanded by 10–17% from 1989 to 2019 at low- to mid-elevations.

Conclusions:

• Mechanistic soil microclimate covariates provide accurate predictions of cheatgrass distribution.
• Fall soil conditions are critical drivers of cheatgrass presence and abundance.
• Climate change has already facilitated cheatgrass expansion into new areas, particularly at lower elevations.