Prioritizing management of invasive plants is important for large land management entities, such as federal and state public land stewards, because management resources are limited and multiple land uses and management objectives are differentially impacted. Management decisions also have important consequences for the likelihood of success and ultimate cost of control efforts. We applied multi-criteria decision analysis methods in a geographic information system using natural resource and land use data from Fort Bragg, North Carolina. Landscape-scale prioritization was based on a hierarchical model designed to increase invasive plant management efficiencies and reduce the risk of impacts to key installation management goals, such as training-land management and protected species conservation. We also applied spatial sensitivity analyses to evaluate the robustness of the prioritization to perturbations of the model weights, which were used to describe the relative importance of different elements of the hierarchical model. Based on stakeholders' need for confidence in making management investments, we incorporated the results of the sensitivity analysis into the decision-making process. We identified high-priority sites that were minimally affected by the weight perturbations as being suitable for up-front management and evaluated how adopting this strategy affected management area, locations, and costs. We found that incorporating the results of the sensitivity analysis led to a reduced management area, different target locations, and lower costs for an equal area managed. Finally, we confirmed the distinctiveness of the approach by comparing this same subset of prioritized sites with locations representing species-centric strategies for three invasive plants and their aggregate distribution. By supplying pragmatic information about the localized effects of weighting uncertainty, spatial sensitivity analyses enhanced the invasive plant management decision-making process and increased stakeholder confidence.
Management Implications: Limited resources force land managers to make choices about where and when to implement invasive plant management actions. Ideally these choices will satisfy the multiple land management objectives, legal requirements, and stakeholders pertinent to most invasive plant management campaigns. Multi-criteria decision analysis (MCDA) provides a proven approach for solving complex decision problems, but has not been widely used for invasive plant management. We applied one MCDA method, the Analytic Hierarchy Process (AHP), to a landscape-scale prioritization of invasive plant management at Fort Bragg, North Carolina. Cognizant of the potential impact of weight uncertainty on AHP outputs, we additionally used spatial sensitivity analyses to reveal high-priority locations where investments in invasive plant management could be made with a degree of confidence deemed acceptable by installation stakeholders.
Our results showed that AHP can be easily implemented in a geographic information system to match local invasive plant management concerns and that incorporating spatial sensitivity analysis into the decision-making process affected the area, locations, and costs associated with management implementation. Results of the integrated prioritization also differed from ad hoc species-centric strategies in terms of the locations identified for management and the priority values associated with these locations.
The AHP can be applied to diverse invasive plant management prioritization problems using available data, expert opinion, and science-based heuristics, but can also be expanded to include new insights provided by additional data, stakeholder input, or models of relevant system processes as they become available. Additionally, spatial sensitivity analyses of AHP weights, decision criteria, or both are recommended in or
