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A Comparison of Compatible and Annual Growth Models

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Abstract:



Compatible growth and yield models are desirable because they provide the same growth estimates regardless of length of growth periods. However, the compatibility constraints restrict the number of possible models. This restriction might be overcome by using models that predict annual stand growth based on periodic measurements. The advantages of this approach are (1) the flexibility allowed in building annual growth models without constraints, and (2) the step-invariance property maintained by these models. An annual growth model was developed in this study that predicts yield based on information from the previous year. For 162 plots from the Southwide Seed Source Study of loblolly pine (Pinus taeda L.), the annual growth model provided better predictions of stand survival, basal area, and volume than two compatible growth models. FOR. SCI. 49(2):285–290.

Keywords: Compatible growth and yield models; Pinus taeda; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; loblolly pine; natural resource management; natural resources; step-invariant models

Document Type: Miscellaneous

Affiliations: 1: Former Graduate Assistant School of Renewable Natural Resources, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803, 2: Professor School of Renewable Natural Resources, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803, Phone: (225) 578-4218; Fax: (225) 578-4227 qcao@lsu.edu

Publication date: 2003-04-01

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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