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An Approach for Predicting Snow Damage to Ponderosa Pine Plantations

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Snow damage to ponderosa pine plantations is common at many locations in the mountains of central Idaho. A procedure was developed using discriminant analysis techniques to predict snow damage hazards. Two approaches were used: one based on computed values of 20-year average annual maximum snow pressures; and the other based on elevation and the average slope gradient on the sample plantations. Snow pressures were computed from plantation site properties including elevation, slope gradient, aspect, and a classification of surface roughness. Prediction success was best with the snow pressure approach and amounted to 74% for damaged plantations and 91% for undamaged plantations for an overall prediction success of 82%. A sensitivity analysis of the snow pressure equations showed that snow depth was the most important variable influencing snow pressure. Evaluations of annual variability in maximum snow pressures suggest that the 20-year average is a reasonable figure for prediction purposes. Ponderosa pine in the study area has a window of vulnerability of about 13 years. The probability of trees surviving this period without damage in high hazard snow pressure sites is very small. An evaluation of the potential benefits of predicting snow pressure damage along with suggestions for use of the procedures are provided. For. Sci. 33(2):485-503.
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Keywords: Tree survival; discriminant analysis; site factors; snow depth; snow pressure

Document Type: Journal Article

Affiliations: Research Forester, Intermountain Research Station, Forest Service, U.S. Department of Agriculture, Ogden, UT 84401

Publication date: 1987-06-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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