Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments

  • Authors: Landsberg, Joe J.; Johnsen, Kurt H.; Albaugh, Timothy J.; Allen, H. Lee; McKeand, Steven E.
  • Publication Year: 2001
  • Publication Series: Miscellaneous Publication
  • Source: Forest Science. 47(1): 43-51.

Abstract

3-PG is a simple process-based model that requires few parameter values and only readily available input data. We tested the structure of the model by calibrating it against loblolly pine data from the control treatment of the SETRES experiment in Scotland County, NC, then altered the fertility rating to simulate the effects of fertilization. There was excellent correspondence between simulated values of stem mass and the values obtained from field measurements, and good correspondence between simulated and measured stem diameters and leaf area index values. Growth efficiency values derived from the model were similar to those obtained from field data. We used the model, without further calibration, to predict tree growth in terms of stem diameter at SETRES 2, a genotype x environment interaction trial in the same locality. Simulated mean stem diameters of two provenances did not differ significantly, over 3 yr, from those observed in the control (unfertilized) treatments, but rates of change were lower than those of fertilized provenances. We then used 3-PG to simulate fertilized stand growth for an entire rotation length, and these results corresponded to those obtained with a traditional growth and yield model. This study showed that the model can simulate accurately the behavior and responses to environmental factors of loblolly pine and that it has considerable potential value as a management tool, for scenario analysis, and as a research tool.

  • Citation: Landsberg, Joe J.; Johnsen, Kurt H.; Albaugh, Timothy J.; Allen, H. Lee; McKeand, Steven E. 2001. Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments. Forest Science. 47(1): 43-51.
  • Posted Date: April 1, 1980
  • Modified Date: September 19, 2008
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