Get reliable rangeland science

State-and-transition models (STM) represent a fairly new approach to describe range dynamics with multiple stable states. STMs can be improved by including multiple sources of information, such as ecological data and local knowledge, and by addressing multiple ecosystem services. By including additional services in the models, such as wildlife habitat, land managers could predict how wildlife populations might change in response to vegetation dynamics and drivers of change like fire or grazing. Our objective was to incorporate avifauna abundance data into locally-developed STMs for dominant ecological sites in sagebrush rangelands in northwest Colorado. We stratified our study area by ecological site, or where developed ESDs were lacking, by sagebrush cover and elevation. We surveyed randomly distributed plots for songbirds and greater sage-grouse (Centrocercus�urophasinus) pellets, collected a suite of vegetation and soils data at each plot, and developed STMs based on multivariate analyses and local stakeholder input. To predict avifauna abundance per state, we developed count-based regression models with the vegetation data as predictor variables, and predicted the count of songbirds and sage-grouse pellets based on average predictor values per state. One STM included two shrub states, a native grassland state, and a crested wheatgrass (Agropyron cristatum) dominated state. We predicted higher abundances for sagebrush and shrub-obligate species in either the diverse shrub or crested wheatgrass-dominated state and the least in the native grassland state. Conversely, the native grassland state provided greater abundances of non-shrub-obligate species. Our models can assist local land managers and landowners to gauge impacts of land-use decisions on avifauna populations.