Predicting vulnerability of forest patches to invasion by non-native plants for landscape scale management.

As a leading cause of forest health degradation, non-native invasive plant species are a key focus for many forest management and conservation efforts. These efforts come at a high price for resource-limited agencies and organizations making cost-effectiveness an important objective of invasion response plans. In this paper, we present an approach to guide the prioritization of locations for invasion management using species distribution models that account for the non-equilibrium of invasive species distributions and use readily available land use data as the primary explanatory variables. This approach takes advantage of the relatively high spatial resolution, as well as the broad, continuous geographic coverage, of land use data to provide results at a landscape scale relevant to practitioners responsible for invasive species management. In our example from northern Virginia, we simultaneously modeled a suite of invasive plant species to identify common indicators of invasion. We found that the proportions of surrounding non-forested land use types (grasses, crops, and development) were the most common and strongest indicators of invasion risk. These outcomes can guide managers of large protected areas to focus on major divides between forest and non-forest land over linear disturbances. We also found useful species-specific traits that can inform specific management actions. Additionally, we demonstrate through a case study how organizations that manage multiple smaller properties can take advantage of the projected distribution maps when considering acquiring or administering properties.