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    Author(s): Patrick A. Fekety; Rema B. Sadak; Joel D. Sauder; Andrew T. Hudak; Michael J. Falkowski
    Date: 2019
    Source: Wildlife Society Bulletin. 43(4): 619-629.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (1.0 MB)

    Description

    Canada lynx (Lynx canadensis) is a federally threatened species in the contiguous United States. Within National Forests covered by the Northern Rockies Lynx Management Direction, Federal land managers must consider the effect of management activities on Canada lynx habitat. A common method to assess Canada lynx habitat used by the U.S. Forest Service is to measure horizontal cover using a cover board. We used field measurements and airborne Light Detection and Ranging (LIDAR) metrics to test beta regression models that predict estimates of horizontal cover on the Nez Perce-Clearwater National Forest, Idaho, USA, 2009-2015. We also investigated the effect on model predictions when the cover board was blocked by the main stem of a tree. Model fit statistics for normalized root mean square errors (RMSE%) were 30.8-33.7% and pseudo‐R2 ranged from 0.64 to 0.71. Using independent validation data, model performance statistics for RMSE% were 24.6-33.5% and R2 ranged from 0.51 to 0.69. We found that removing cover board measurements where the main stem of a tree blocked >75% of the cover board produced the best model statistics. These models can be applied across LIDAR extents resulting in maps of horizontal cover estimates, which may be used in assessing effects of management activities on Canada lynx habitat.

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    Citation

    Fekety, Patrick A.; Sadak, Rema B.; Sauder, Joel D.; Hudak, Andrew T.; Falkowski, Michael J. 2019. Predicting forest understory habitat for Canada lynx using LIDAR data. Wildlife Society Bulletin. 43(4): 619-629.

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    Keywords

    beta regression, cover board, horizontal cover, Lynx canadensis, Northern Rocky Mountains

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https://www.fs.usda.gov/treesearch/pubs/60048