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An Algorithm for Ensuring Compatibility Between Estimated Percentiles of Diameter Distribution and Measured Stand Variables

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It is difficult to formulate a diameter distribution model that is compatible with many stand variables. In previous studies, compatibility of diameter distribution has been ensured with the aid of calibration (adjustment) based on making small changes to the predicted frequencies of diameter classes. In these methods, the minimum and maximum diameters cannot be changed, and the measurement error of the stand variables is not taken into account. In this study, two calibration methods based on minimizing deviations from predicted percentiles were developed. Because minimum and maximum diameters were among the predicted percentiles, there were no problems in changing them in the calibration. In the first method, the measurement error of the stand variables was not taken into account. In the second method, in addition to deviations from predicted percentiles, deviations from the measured stand variables were allowed, and the measurement error was taken into account by weighting each term of the objective function inversely by its error variance. The methods were tested in a dataset of Finnish mixed coniferous forests. Both methods were found to be better than the reference method used because the minimum and maximum diameters could be changed. Even if the measurement error was large, the second method was still advantageous, while the other methods were of no use. FOR. SCI. 50(1):20–32.

Keywords: Diameter distribution; calibration; compatibility; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; measurement error; natural resource management; natural resources; nonlinear optimization; percentile

Document Type: Regular Article

Affiliations: Researcher Finnish Forest Research Institute Joensuu Research Centre P.O. Box 68 Joensuu Finland FIN-80101 Phone: +358-10-2113051;, Fax: +358-10-2113113, Email:

Publication date: February 1, 2004

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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