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

Authors: TERRY, TYSON - Utah State University; Hardegree, Stuart; ADLER, PETER - Utah State University

Submitted to: Ecological Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/27/2024
Publication Date: 9/16/2024
Citation: Terry, T., Hardegree, S.P., Adler, P. 2024. Modeling cheatgrass distribution, abundance, and response to climate change as a function of soil microclimate. Ecological Applications. Article e3028. https://doi.org/10.1002/eap.3028.
DOI: https://doi.org/10.1002/eap.3028

Interpretive Summary: Introduced annual grasses that proliferate after wildfire have degraded resource values over millions of acres of sagebrush steppe rangeland in the Intermountain Western US. Accurate mapping of these grasses, and predictions of their expansion under current and future climate conditions would assist greatly in the prioritization of restoration management. In this study we used soil microclimate and cheatgrass-germination models to develop a seedbed favorability index for cheatgrass germination at 2662 field sites across the Great Basin. This mechanistic modeling approach predicted current cheatgrass distribution with 72% overall accuracy. Our model also suggests that climate change has already affected cheatgrass distribution by expanding the potential range of cheatgrass by 10-17% since 1989. This mapping tool may improve our ability to identify high priority areas for restoration, and to anticipate areas that are becoming more accessible to cheatgrass invasion in the future.

Technical Abstract: Exotic annual grass invasions in water-limited systems cause degradation of native plant and animal communities and increased fire risk. The life history of invasive annual grasses allows for high sensitivity to interannual variability in weather. Current distribution and abundance models derived from remote sensing, however, provide only a coarse understanding of how species respond to weather, making it difficult to anticipate how climate change will affect vulnerability to invasion. Here we derived germination covariates (rate sums) from mechanistic germination and soil microclimate models to quantify favorability of microclimate for cheatgrass (Bromus tectorum L.) establishment and growth across 30 years at 2662 sites across the sagebrush steppe. We then used rate-sum metrics in a generalized additive model to explain field observations of cheatgrass distribution and abundance in this region. Our approach, using four mechanistic climate covariates alone, predicted cheatgrass distribution with accuracy comparable to previous models fit using many years of remotely-sensed imagery. Accuracy metrics from our out-of-sample testing dataset indicate that our model predicted distribution well (72% overall accuracy) but explained patterns of abundance poorly (R2 = 0.22). Cheatgrass distribution depended on both spatial (mean) and temporal (annual anomaly) variation of fall and spring rate sums. Sites that on average have warm and wet fall soils and warm and wet spring soils (high rate sums during these periods) were predicted to have a high abundance of cheatgrass. Interannual variation of fall soil conditions had a greater impact on cheatgrass distribution and abundance than spring conditions. Our model predicts that climate change has already affected cheatgrass distribution, with suitable microclimatic conditions expanding 10-17% from 1989 to 2019 across all aspects at low to mid-elevation sites, while high elevation sites (> 2100m) remain unfavorable for cheatgrass due to cold spring and fall soils.