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Over the last few decades, considerable attention has focused on small-scale studies of invasive plants and invaded systems. Unfortunately, small scale studies rarely provide comprehensive insight into the complexities of biological invasions at macroscales. Systematic and repeated monitoring of biological invasions at broad scales are rare. In this report, we highlight a unique invasive plant database from the national Forest Inventory and Analysis (FIA) program of the United States Forest Service. We demonstrate the importance and capability of this subcontinental-wide database by showcasing several critical macroscale invasion patterns that have emerged from its initial analysis: (1) large portion of the forests systems (39%) in the United States are impacted by invasive plants, (2) forests in the eastern United States harbor more invasive species than the western regions, (3) human land-use legacies at regional to national scalesb may drive large-scale invasion patterns. This accumulated dataset, which continues to grow in temporal richness with repeated measurements, will allow the understanding of invasion patterns and processes at multi-spatial and temporal scales. Such insights are not possible from smaller-scale studies, illustrating the benefit that can be gained by investing in the development of regional to continental-wide invasion monitoring programs elsewhere.
The authors inserted an incorrect figure in Oswalt et al. (2015) that was printed as Fig. 2. The mapped species represented in Oswalt et al. (2015) is Triadica sebifera or Chinese tallow. The correct Fig. 2, representing Imperata cylindrica, is reproduced below. The correction does not alter the conclusions of Oswalt et al. (2015).
Decision tools have been advocated to assist the prioritization of management areas for preventing and mitigating exotic invasions into native ecosystems. Currently, most tools have been created for specific invaders/regions and are thus often not sufficient to address the complex range of invasion scenarios that managers encounter. As exotic invasions continue to be a major issue, science-based, information-driven tools are pressingly needed. In this study, we explore the potential of utilizing the Analytic Hierarchy Process (AHP), one of the information-driven tools, to flexibly prioritize various invasion scenarios by incorporating a broad spectrum of management data. We tested the flexibility of the AHP management tool with two distinct invasion-stage-specific prioritizations for Amur honeysuckle (Lonicera maackii). The AHP tool successfully created two management prioritizations from contrasting invasion scenarios of established Amur honeysuckle invasion versus a hypothetical scenario of newly invading populations. The flexibility of AHP allowed users to alter input based on the stage of invasion in each scenario. In the established scenario, management priority was assigned to removing Amur honeysuckle from the most ecologically significant areas. For the new invasion scenario, priority was shifted to removing the invader from areas of most recent invasions. The two contrasting prioritizations demonstrate the flexibility of AHP as a management tool. We conclude that the flexible AHP tool could be useful for prioritizing management of exotic plant invasions.