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A New Diameter Distribution Model for Unmanaged Loblolly Pine Plantations in East Texas

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A parameter recovery procedure for the Weibull distribution function based on four percentile equations was used to develop a diameter distribution yield prediction model for unmanaged loblolly pine (Pinus taeda L.) plantations in East Texas. This model was compared with the diameter distribution models of Lenhart and Knowe, which have been used in East Texas. All three models were evaluated with independent observed data. The model developed in this study performed better than the other two models in prediction of trees per acre and cubic-foot volume per acre (wood and bark, excluding stump) across diameter classes. Lenhart’s model consistently underestimated the larger-diameter classes because it was developed originally with data mostly collected in young plantations. Knowe’s model overestimated volume in sawtimber-sized trees, which could lead to overestimations of volume in older loblolly pine plantations found in East Texas. An example also is provided to show users how to use this new yield prediction system. These results support the recommendation that forest managers should use growth and yield models designed and/or calibrated for the region in which they are implemented.

Keywords: Pinus taeda; Weibull distribution; growth and yield models; parameter recovery

Document Type: Research Article

Affiliations: 1: Department of Forest Resources, Kongju National University, Yesan, Chungnam, 340-802, South Korea; 2: Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University, Box 6109 SFA Station, Nacogdoches, TX, 75962.

Publication date: February 1, 2006

More about this publication?
  • Each regional journal of applied forestry focuses on research, practice, and techniques targeted to foresters and allied professionals in specific regions of the United States and Canada. The Southern Journal of Applied Forestry covers an area from Virginia and Kentucky south to as far west as Oklahoma and east Texas.
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