Assessing the Proliferation, Connectivity, and Consequences of Invasive Fine Fuels on the Sagebrush Biome
Invasive annual grasses can replace native vegetation and alter fire behavior, impacting a range of habitats and species. A team of researchers from the U.S. Geological Survey, Colorado State University, the Bureau of Land Management, and the U.S. Fish and Wildlife Service are working to identify factors that influence changes in the distribution and abundance of invasive annual grasses (IAGs) within the sagebrush ecosystem. They are identifying areas where IAG cover is likely to change and where potential management actions may be most and least effective, to help land managers develop spatial strategies to combat this extensive invasion.
Overview
Invasive annual grasses (IAGs) create an array of management challenges within the sagebrush biome. The continued proliferation of these invasive fine fuels could re-shape ecosystems by diminishing native vegetation and increasing the spread and consequences of wildland fires. Assessments of past patterns and potential future trajectories of invasion could help land managers identify the conditions best suited for resisting, accepting and directing (that is, managing) invasion across the sagebrush biome. We created a series of spatial analyses that can be used to develop management strategies that match treatment actions with suitable places. Analyses of project current and future rates and intensities of invasion will allow managers to consider the durability of treatments and management decisions.
The goals of this project include:
- Understanding potential proliferation of invasive annual grasses in the Great Basin, under current and future disturbance conditions,
- Spatially identifying opportunities to disconnect existing fine fuels at multiple spatial scales within the Great Basin,
- Describing rates of invasion and the stability of rates of invasion over time,
- Identifying the anthropogenic and environmental drivers of rates of IAG proliferation across the sagebrush biome, and
- Predicting rates of invasion under future climate and land use scenarios.
Cheatgrass invasion risk
We developed an empirically based spatial cheatgrass (Bromus tectorum) invasion risk model that linked climate, growing season weather, disturbance, and fire history to potential risk of invasion. We then predicted and mapped the potential for areas to become heavily invaded in three quantiles that can be interpreted as invasion scenarios. These predictions can be used to identify locations that are consistently predicted to have low or high cheatgrass cover and to support management prioritizations by identifying areas at low and at high risk of near-term invasion. See Sofaer and others, 2022.
By altering key disturbance variables (fire, fuel breaks, human disturbance) we were able to identify regions at risk of future invasion as a result of disturbance. In currently uninvaded areas, we identified new areas that were consistently at high or low risk for future cheatgrass invasion under multiple scenarios, as well as those that were moderately or variably vulnerable to invasion. This analysis provides insight into long-term invasion risk and can be used to consider the durability of conservation, restoration, or invasion management investments across the Great Basin.
Configuration and connectivity of fine fuels
To develop a systematic approach that matches different IAG management actions with different invasion situations, we characterized IAG abundance and spatial patterns across the Great Basin. This analysis identified regions of highly connected patches of IAGs, and conversely, areas that are relatively isolated and uninvaded. The multi-scale spatial analysis of IAG cover and configuration provided a way to repeatably quantify the state of invasion across the Great Basin at both local and regional scales. The resulting invasion metrics can be used to match specific management actions with locations that may most benefit from them.
Rates of invasion
We quantified and mapped rates of invasion across the sagebrush ecosystem from 1987 – 2021, highlighting where rates of invasion have remained stable or accelerated over time. To better understand the factors driving slower and faster rates of annual grass invasion, we are also developing multiscale geographically weighted models and examining how environmental and anthropogenic relationships change invasion rates across the sagebrush ecosystem. Potential drivers of rates of invasion include drought, precipitation, wildfire history, cover of perennial grasses, roads, and fuel breaks among others. These models will be used to predict rates of invasion in future climatic and disturbance conditions across the biome. The resulting information on the drivers and rates of change can provide support in designing management strategies that are responsive to the regionally varying conditions that drive invasion. More generally, the results can help identify priority locations for management action and where management actions may be most successful given contemporary and future climatic and disturbance conditions.
Invasive annual grasses can replace native vegetation and alter fire behavior, impacting a range of habitats and species. A team of researchers from the U.S. Geological Survey, Colorado State University, the Bureau of Land Management, and the U.S. Fish and Wildlife Service are working to identify factors that influence changes in the distribution and abundance of invasive annual grasses (IAGs) within the sagebrush ecosystem. They are identifying areas where IAG cover is likely to change and where potential management actions may be most and least effective, to help land managers develop spatial strategies to combat this extensive invasion.
Overview
Invasive annual grasses (IAGs) create an array of management challenges within the sagebrush biome. The continued proliferation of these invasive fine fuels could re-shape ecosystems by diminishing native vegetation and increasing the spread and consequences of wildland fires. Assessments of past patterns and potential future trajectories of invasion could help land managers identify the conditions best suited for resisting, accepting and directing (that is, managing) invasion across the sagebrush biome. We created a series of spatial analyses that can be used to develop management strategies that match treatment actions with suitable places. Analyses of project current and future rates and intensities of invasion will allow managers to consider the durability of treatments and management decisions.
The goals of this project include:
- Understanding potential proliferation of invasive annual grasses in the Great Basin, under current and future disturbance conditions,
- Spatially identifying opportunities to disconnect existing fine fuels at multiple spatial scales within the Great Basin,
- Describing rates of invasion and the stability of rates of invasion over time,
- Identifying the anthropogenic and environmental drivers of rates of IAG proliferation across the sagebrush biome, and
- Predicting rates of invasion under future climate and land use scenarios.
Cheatgrass invasion risk
We developed an empirically based spatial cheatgrass (Bromus tectorum) invasion risk model that linked climate, growing season weather, disturbance, and fire history to potential risk of invasion. We then predicted and mapped the potential for areas to become heavily invaded in three quantiles that can be interpreted as invasion scenarios. These predictions can be used to identify locations that are consistently predicted to have low or high cheatgrass cover and to support management prioritizations by identifying areas at low and at high risk of near-term invasion. See Sofaer and others, 2022.
By altering key disturbance variables (fire, fuel breaks, human disturbance) we were able to identify regions at risk of future invasion as a result of disturbance. In currently uninvaded areas, we identified new areas that were consistently at high or low risk for future cheatgrass invasion under multiple scenarios, as well as those that were moderately or variably vulnerable to invasion. This analysis provides insight into long-term invasion risk and can be used to consider the durability of conservation, restoration, or invasion management investments across the Great Basin.
Configuration and connectivity of fine fuels
To develop a systematic approach that matches different IAG management actions with different invasion situations, we characterized IAG abundance and spatial patterns across the Great Basin. This analysis identified regions of highly connected patches of IAGs, and conversely, areas that are relatively isolated and uninvaded. The multi-scale spatial analysis of IAG cover and configuration provided a way to repeatably quantify the state of invasion across the Great Basin at both local and regional scales. The resulting invasion metrics can be used to match specific management actions with locations that may most benefit from them.
Rates of invasion
We quantified and mapped rates of invasion across the sagebrush ecosystem from 1987 – 2021, highlighting where rates of invasion have remained stable or accelerated over time. To better understand the factors driving slower and faster rates of annual grass invasion, we are also developing multiscale geographically weighted models and examining how environmental and anthropogenic relationships change invasion rates across the sagebrush ecosystem. Potential drivers of rates of invasion include drought, precipitation, wildfire history, cover of perennial grasses, roads, and fuel breaks among others. These models will be used to predict rates of invasion in future climatic and disturbance conditions across the biome. The resulting information on the drivers and rates of change can provide support in designing management strategies that are responsive to the regionally varying conditions that drive invasion. More generally, the results can help identify priority locations for management action and where management actions may be most successful given contemporary and future climatic and disturbance conditions.