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Title: Using landscape-level forest monitoring data to draw a representative picture of an iconic subalpine tree species

Author: Goeking, Sara A.; Izlar, Deborah K.;

Date: 2015

Source: In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8–10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 296-301.

Publication Series: General Technical Report (GTR)

   Note: This article is part of a larger document. View the larger document

Description: Whitebark pine (Pinus albicaulis) is an ecologically important species in high-altitude, mid-latitude areas of western North America due to the habitat and food source it provides for many wildlife species. Recent concerns about the long-term viability of whitebark pine stands have arisen in the face of high mortality due to a combination of fire suppression, white pine blister rust, and mountain pine beetle outbreaks. Most previous studies of whitebark pine have focused on pure stands, yet the spatially representative Forest Inventory and Analysis (FIA) dataset shows that whitebark pine is more widespread in other forest types than in pure stands. Because previous studies have focused on iconic, pure whitebark pine stands, managers may not be aware of the potential for ecological restoration of whitebark pine in other forest types. The purpose of this study was to use FIA’s spatially representative sample grid to assess whitebark pine stands in a variety of environments in the Rocky Mountains, and to compare the structure and composition of pure versus mixed-species stands where whitebark pine is present. The results illustrate that metrics of whitebark pine viability, namely regeneration and mortality, may be comparable in the understory of other forest types to those observed within pure stands. Finally, this study demonstrates that the FIA dataset permits spatially representative evaluations of populations that tend to be studied purposively rather than strategically.

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Goeking, Sara A.; Izlar, Deborah K. 2015. Using landscape-level forest monitoring data to draw a representative picture of an iconic subalpine tree species. In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8–10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 296-301.

 


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