AbstractWhere the nonnative annual grass downy brome proliferates, it has changed ecosystem processes, such as nutrient, energy, and water cycles; successional pathways; and fire regimes. The objective of this study was to develop a model that predicts the presence of downy brome in Central Oregon and to test whether high presence correlates with greater cover. Understory data from the U.S. Department of Agriculture (USDA) Forest Service's Current Vegetation Survey (CVS) database for the Deschutes National Forest, the Ochoco National Forest, and the Crooked River National Grassland were compiled, and the presence of downy brome was determined for 1,092 systematically located plots. Logistic regression techniques were used to develop models for predicting downy brome populations. For the landscape including the eastside of the Cascade Mountains to the northwestern edge of the Great Basin, the following were selected as the best predictors of downy brome: low average March precipitation, warm minimum May temperature, few total trees per acre, many western junipers per acre, and a short distance to nearest road. The concordance index = 0.92. Using the equation from logistic regression, a probability for downy brome infestation was calculated for each CVS plot. The plots were assigned to a plant association group (PAG), and the average probability was calculated for the PAGs in which the CVS plots were located. This method could be duplicated in other areas where vegetation inventories take place.
Water primrose invasion changes successional pathways in an estuarine ecosystem
