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Modeling Tree Mortality in Low- to Medium-Density Uneven-Aged Hardwood Stands Under a Selection System Using Generalized Estimating Equations

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Tree mortality was modeled through time in uneven-aged northern hardwood stands managed under a selection system using long-term remeasurement data. Two models were fitted and compared: a traditional logistic regression model that predicted the probability of individual tree mortality over discrete time periods and a logistic regression model estimated using generalized estimating equations (GEEs) to account for autocorrelation in the longitudinal data. Model evaluation was based on the mean prediction error, mean absolute prediction error, variance of prediction errors, and mean square error calculated using an independent validation data set. The GEE model produced smaller evaluation statistics, especially for the smaller diameter classes. The predicted probability of mortality from the two models was compared with the observed mortality across 5-cm diameter classes for two time periods. Our results indicate that the GEE model was better able to capture the change in the probability of mortality over time, especially for the smaller diameter classes, than the more traditional logistic model.

Keywords: generalized estimating equations; logistic regression; longitudinal data; tree mortality

Document Type: Research Article

Publication date: 2009-08-01

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  • 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

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

    Also published by SAF:
    Journal of Forestry
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