Synthesizing results from a landscape-scale adaptive management program for non-native Phragmites australis

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Kurt P. Kowalski , Samantha Tank , Erika Jensen

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Non-native Phragmites australis (common reed) can degrade fish and wildlife habitat, reduce property values, and increase fire hazards as it invades wetlands throughout North America. Management of this invasive species is a high priority for resource managers, but landscape-scale collaboration and learning among managers is difficult. In addition, data-driven best management practices are not readily available, and uncertainties exist concerning optimal treatment options. Therefore, the Phragmites Adaptive Management Framework (PAMF; was initiated in 2017 to support land managers and reduce uncertainty surrounding what Phragmites treatments are most effective given site-specific levels of infestation. PAMF participants collect and upload monitoring data about their Phragmites-impacted site to a centralized web hub. These data update the PAMF learning model, which then provides site-specific management guidance that is predicted to maximize the efficacy and efficiency of control efforts. Guidance provided by the data-driven model, therefore, is improved through time and as the number of participants increases. PAMF is evaluating 16 unique combinations of management actions that include applying herbicide, cutting, flooding, and rest. Six states (i.e., levels) of infestation are used to characterize the intensity of Phragmites invasion at each site, both before and after treatment. Optimal management approaches differ by state of invasion, with cost of treatment driving model results at lower invasion states. The PAMF program continues to expand rapidly as managers become aware of the program and recognize the value of participation.

Resource Type:
Conference Presentation, SER2021

Pre-approved for CECs under SER's CERP program