Assessing invasive annual grass treatment efficacy across the sagebrush biome
We are using existing datasets that span broad spatial and temporal extents to model the efficacy of invasive annual grass treatments across the sagebrush biome and the influence of environmental factors on their success. The models we develop will be used to generate maps of predicted treatment efficacy across the biome, which will be integrated into the Land Treatment Exploration Tool for land managers, planners and other stakeholders to use to guide efforts to more effectively manage cheatgrass and other invasive annual grasses.
Background
Invasive annual grasses (IAGs) threaten the ecological integrity of the sagebrush biome and the species and communities that depend on it. Cheatgrass (Bromus tectorum) alone occupies more than 200,000 square kilometers across the intermountain west and its footprint is steadily increasing over time. Dominance of IAGs, such as cheatgrass, across this landscape directly impacts ecological integrity in a variety of ways but most dramatically by modifying fire regimes to increase the frequency, extent, and intensity of wildfires. Managing IAG invasion has proven challenging, in part due to the size of the impacted region and diversity of environmental conditions within. Through the Sagebrush Conservation Design, regional stakeholders devised a management strategy focused on 1) Defending the Core (of sagebrush habitat), 2) Growing the Core, and 3) Mitigating Impacts. However, a comprehensive understanding of the efficacy of IAG management across the sagebrush biome is needed to align management efforts with this strategy.
Our project goals and anticipated outcomes
We are leveraging new datasets extending across the sagebrush biome over the course of multiple decades to model efficacy of IAG treatments over space and time. Specifically, we are using estimates of annual herbaceous cover from remote sensing products (for example, RCMAP – Rangeland Condition Monitoring Assessment and Projection, and RAP – Rangeland Analysis Platform; 1986-2021) to evaluate the success of weed control treatments documented in the Land Treatment Digital Library, the Conservation Efforts Database, and Utah’s Watershed Restoration Initiative. We are using these and other data to evaluate the influence of spatial and temporal factors on the outcomes of weed control treatments, including repeated treatments, treatment timings, size of treatments/infestations, perennial grass seedings, wildfire characteristics, and environmental conditions, such as soil moisture. We will also explore validating our results using IAG-specific remote sensing products, such as the USGS Rangeland Exotic Plant Monitoring System, or field data from the BLM’s Assessment, Inventory and Monitoring program. With these modeled relationships, we will generate spatially explicit maps of potential treatment efficacy and explore differences between RAP and RCMAP that can help potential users understand which product may be better suited for their region or goals. These results can directly inform multi-agency, cross-jurisdictional management efforts for controlling IAGs and will be integrated into the Land Treatment Exploration Tool. This additional output will facilitate adaptive management efforts by providing metrics and data layers that could allow users to filter projects by treatment efficacy, see what conditions impact efficacy in their region, and compare accuracy between RAP and RCMAP based analyses.
