Management of invasive species is most effective when new colonizers can be detected and eliminated early, and when elimination of existing populations targets patches that have the greatest impact on the spread of the species. Because property managers have limited resources, we need more tools to predict where to search for new patches and to determine which patches are most important for spread dynamics. I am developing a GIS-based model to predict the spread of the invasive grass, Microstegium vimineum, along its invasive front. I have collected three years of data on the distribution and abundance of Microstegium at nine sites, surveying a total of 275 ha. These sites include naturally-disturbed forests, harvested forests, and undisturbed forests, allowing me to compare spread rates across different types of disturbance. Using these field data I have calculated correlations between Microstegium occurrence and environmental factors that determine site suitability and seed production and with landscape features that affect dispersal. I will use a Bayesian framework to combine the most important factors affecting site suitability and dispersal into a predictive model to identify areas susceptible to invasion and which sites when invaded are likely to be most important for population spread.
Results/Conclusions
These results show that slope, aspect, light, and disturbance are the most important determinants of site suitability for Microstegium vimineum. Distance from streams and roads and disturbance were the most important factors for dispersal. On average, spread rate was higher at harvested sites than naturally-disturbed or undisturbed sites, with one harvested site having a 388% increase in cover over two years. However, the highest rate of spread at a single site was at a naturally-disturbed site where Microstegium cover increased by 474% over two years. Naturally-disturbed sites had the most variation in spread rates with one year rates of spread ranging from 71 – 272%. Environmental characters that contributed to Microstegium invasion included north- and east-facing aspects, flat bottomland slopes, and higher levels of canopy openness. I will present predictions of spatial spread patterns of Microstegium from a GIS-based model based on site suitability determined by environmental characteristics and dispersal in relation to distance to roads, trails, and streams. This model should permit property managers to better predict sites that are likely to be invaded and which patches they should target for control.