Landscape connectivity and seed dispersal characteristics inform the best management strategy for exotic plants.

Exotic plant invasions have triggered environmental and economic problems throughout the world. Our ability to manage these invasions is hindered by the difficulty of predicting spread in fragmented landscapes. Because the spatial pattern of invasions depends on the dispersal characteristics of the invasive species and the configuration of suitable habitat within the landscape, a universal management strategy is unlikely to succeed for any particular species. We suggest that the most effective management strategy may be an adaptive one that shifts from local control to landscape management depending on the specific invader and landscape. In particular, we addressed the question of where management activities should be focused to minimize spread of the invading species. By simulating an invasion across a real landscape (Antietam National Battlefield in Maryland, USA), we examined the importance of patch size and connectivity to management success. We found that the best management strategy depended on the dispersal characteristics of the exotic species. Species with a high probability of random long-distance dispersal were best managed by focusing on the largest patches, while species with a lower probability of random long-distance dispersal were best managed by considering landscape configuration and connectivity of the patches. Connectivity metrics from network analysis were useful for identifying the most effective places to focus management efforts. These results provide insight into invasion patterns of various species and suggest a general rule for managers in National Parks and other places where invasive species are a concern.

Combining a dispersal model with network theory to assess habitat connectivity.

Assessing the potential for threatened species to persist and spread within fragmented landscapes requires the identification of core areas that can sustain resident populations and dispersal corridors that can link these core areas with isolated patches of remnant habitat. We developed a set of GIS tools, simulation methods, and network analysis procedures to assess potential landscape connectivity for the Delmarva fox squirrel (DFS; Sciurus niger cinereus), an endangered species inhabiting forested areas on the Delmarva Peninsula, USA. Information on the DFS's life history and dispersal characteristics, together with data on the composition and configuration of land cover on the peninsula, were used as input data for an individual-based model to simulate dispersal patterns of millions of squirrels. Simulation results were then assessed using methods from graph theory, which quantifies habitat attributes associated with local and global connectivity. Several bottlenecks to dispersal were identified that were not apparent from simple distance-based metrics, highlighting specific locations for landscape conservation, restoration, and/or squirrel translocations. Our approach links simulation models, network analysis, and available field data in an efficient and general manner, making these methods useful and appropriate for assessing the movement dynamics of threatened species within landscapes being altered by human and natural disturbances.

Conceptual models as hypotheses in monitoring urban landscapes.

Many problems and challenges of ecosystem management currently are driven by the rapid pace and spatial extent of landscape change. Parks and reserves within areas of high human population density are especially challenged to meet the recreational needs of local populations and to preserve valued environmental resources. The complex problem of managing multiple objectives and multiple resources requires an enormous quantity of information, and conceptual models have been proposed as tools for organizing and interpreting this information. Academics generally prefer a bottom-up approach to model construction that emphasizes ecologic theory and process, whereas managers often use a top-down approach that takes advantage of existing information to address more pragmatic objectives. The authors propose a formal process for developing, applying, and testing conceptual models to be used in landscape monitoring that reconciles these seemingly opposing perspectives. The four-step process embraces the role of hypothesis testing in the development of models and evaluation of their utility. An example application of the process to a network of national parks in and around Washington, DC illustrates the ability of the approach to systematically identify monitoring data that would both advance ecologic theory and inform management decisions.