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    Author(s): Zachary Wurtzebach; R. Justin DeRose; Renate R. Bush; Sara A. GoekingSean HealeyJim MenloveKristen A. Pelz; Courtney Schultz; John D. ShawChris Witt
    Date: 2019
    Source: Journal of Forestry. doi: 10.1093/jofore/fvz061.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (256.0 KB)


    In 2012, the US Forest Service promulgated new regulations for land-management planning that emphasize the importance of scientifically credible assessment and monitoring strategies for adaptive forest planning and the maintenance or restoration of ecological integrity. However, in an era of declining budgets, the implementation of robust assessment and monitoring strategies represents a significant challenge for fulfilling the intent of the new planning rule. In this article, we explore opportunities for using data and products produced by the USDA Forest Service’s Forest Inventory and Analysis (FIA) Program to support the implementation of the 2012 Planning Rule. FIA maintains a nationally consistent statistical sample of field plots that covers most national forests with hundreds of plots. We suggest that leveraging FIA data and products can generate efficiencies for assessment, planning, and monitoring requirements detailed in the 2012 Planning Rule, and help fulfill the adaptive intent of the new planning rule. However, strong national leadership and investment in regional-level analytical capacity, FIA liaisons, and decision-support tools are essential for systematically realizing the benefits of FIA data for forest planning across the National Forest System.

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    Wurtzebach, Zachary; DeRose, R. Justin; Bush, Renate R.; Goeking, Sara A.; Healey, Sean; Menlove, Jim; Pelz, Kristen A.; Schultz, Courtney; Shaw, John D.; Witt, Chris. 2019. Supporting National Forest System planning with Forest Inventory and Analysis data. Journal of Forestry. doi: 10.1093/jofore/fvz061.


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    assessment, broader scale, decisionmaking, ecological integrity, monitoring, natural range of variability, planning

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