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Invasive annual grasses, primarily Bromus tectorum, are a severe risk to native vegetation of the intermountain West. Once established, annual grasses alter natural fire regimes and outcompete natives until, in some places, they become the overwhelming dominant. We developed a regional spatial model encompassing eight ecoregions to indicate the relative abundance of invasive annual grass at five levels of canopy cover. We used field sample data representing invasive annual grass abundance to build and calibrate the model. Explanatory variables, represented as map inputs, included image indices, climate, landform, soil, and human-induced surface disturbance. As a novel modeling approach, we built multiple models based on classes of invasive annual grass cover abundance were developed individually and then combined into a final 90-m pixel resolution model that indicates locations relative to invasive annual grass abundance into classes of 45% cover. Each component model was validated using held-out sample data, and relative accuracy was 86%, 74%, 62%, 62%, and 60%, respectively, with an overall kappa of 0.773. The Columbia Plateau, Northern Basin and Range, and Snake River Plain ecoregions appear to have the greatest overall proportions (48−62%) mapped within at least one of the invasive cover categories. Overlay of the resulting model with major vegetation types indicated > 50 major vegetation types that are affected by current distribution of annual grasses and are at risk of expansion. Among these, Intermountain Basins, Big Sagebrush Steppe, and Columbia Plateau Steppe and Grassland each consistently scored high for invasive risk where they occur. Spatial models of this type should assist with rangeland restoration and for decisions involving placement of infrastructure, vegetation treatments where further surface disturbance could trigger additional cheatgrass expansion. Options exist for extending this model, using climate projections over upcoming decades, to indicate areas of increasing risk for invasion.

Standardized ecological classification units form the foundation for effective data collection, assessment, and reporting on ecosystems. Attempts at regional land cover mapping often falter on this point or struggle along inefficiently. Over the past decade, NatureServe has worked with the Gap Analysis Program and others to map existing vegetation using the US National Vegetation Classification (US-NVC). US-NVC is a system of hierarchical structure and rules that are designed to provide a national classification of existing vegetation. Experience has demonstrated the need to develop map units at conceptual scales intermediate between the narrowly specific alliance (floristic) and the broadly generalized formation (physiognomic) levels of the US-NVC. NatureServe defined over 630 “mesoscale” vegetation-based units that are described across the lower 48 United States. These mesoscale classification units, which we term “terrestrial ecological systems,” are described using multiple plant communities that tend to co-occur based on recurrent similarities in environmental setting and ecological dynamics. By integrating environmental setting and ecological processes with vegetation into the concept of each unit, this classification system lends itself to biophysical modeling and robust characterization of wildlife habitat. These units apply well to land cover mapping and may be augmented with modifiers for specific variants in composition and structure resulting in robust, standardized maps. Regional-scale mapping of “near-natural” land cover was completed by the Southwest Regional Gap Analysis Project using 109 ecological system units, currently the most detailed regional land cover map of its kind. Terrestrial ecological system units provide a direct, systematic link to the US National Vegetation Classification and may also provide a useful framework for integration with ecological site concepts and descriptions.