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A Logistic Model of Mortality in Thinned and Unthinned Mixed Conifer Stands of Northern Idaho

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Published mortality models have not always done an adequate job of predicting the probability of mortality following thinning. This paper describes a mortality model based on a series of thinned and unthinned sample plots located in northern Idaho, some of which have been measured for 70 years. Independent variables are diameter at breast height (dbh), stand basal area, annual diameter growth, relative dbh, and species. Thinning results in changes in three of these variables: the stand basal area, relative dbh, and diameter growth rate. Model performance is evaluated by considering how well the model fits the development data set, how well the model fits an independent data set, and how well the model fits biological reality. In each evaluation the selected model shows a marked improvement over the performance of the mortality model used in previous releases of the Stand Prognosis Model (Wykoff et al. 1982). The model is shown to perform well in both thinned and unthinned stands. Forest Sci. 32:989-1000.

Keywords: Logistic function; mortality prediction

Document Type: Journal Article

Affiliations: Research Forester, Intermountain Research Station, Forest Service, U.S. Department of Agriculture, Moscow, ID 83843

Publication date: 1986-12-01

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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