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Modeling Individual-Tree Growth from Data with Highly Irregular Measurement Intervals

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Fitting annual tree growth and survival models to data with irregular measurement intervals requires special consideration to the interpolation of the independent variables. This study presents an iterative method for continuously updating individual-tree and stand attributes, using the hypothesized functional form of a system of forward difference equations. Based on data from permanent sample plots, parameter estimates were obtained for three first-order difference equations of diameter and height growth and mortality for European beech in Denmark. One parameter of the individual-tree diameter and height growth models was estimated locally and expresses apparent site quality. The plot-specific parameters of the individual-tree growth models were highly correlated with site index and plot-specific estimates of rate constants from a dominant height growth model. Parameter estimates of individual-tree models based on either of those indicators of site quality allow for a flexible use of the models. The study failed to establish any relation between plot-specific rate constants and soil texture variables. The resulting system of individual-tree models is consistent with tree growth and mortality expected for beech in Denmark.

Keywords: Fagus sylvatica; diameter; difference equation; height; mortality

Document Type: Research Article

Affiliations: Thomas Nord-Larsen, Royal Veterinary and Agricultural University, Forest & Landscape, Hørsholm Kongevej 11, DK-2970 Hørsholm, Denmark—Phone: (+45) 35281758;, Fax: (+45) 35281517, Email:

Publication date: 2006-04-01

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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:
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