Applying 3-PG, a Simple Process-Based Model Designed to Produce Practical Results, to Data from Loblolly Pine Experiments

By J. Landsberg, K. Johnsen, T. Albaugh, H. L. Allen, S. McKeand. Forestry sciences, 2001

137 citations recorded by the source corpus.

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 × 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. FOR. Sci. 47(1):43–51.

Subfields: Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/a14bf74e0462a738ecfdb8c9be8ddab29e9a2737

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Citations in the corpus

Variance-based sensitivity analysis of a forest growth model (2012, methodology): “The model has been calibrated for a few specific tree species, such as Eucalyptus species (Almeida et al., 2004b, 2010; Paul et al., 2007; Sands and Landsberg, 2002), loblolly pine (Pinus taeda L.) (Landsberg et al., 2001) and Douglas-Fir (Pseudotsuga menziesii (Mirb.)”
Forest Growth and Yield Modeling (2011, background): “Regardless, 3-PG has been used for a wide variety of purposes ranging from simulating long-term influences of a range of silvicultural treatments (Landsberg et al., 2001) to predicting regional variation in productivity (Swenson et al., 2005).”
Calibration and testing of a generalized process-based model for use in Portuguese eucalyptus plantations (2006, unknown): “(Landsberg et al. 2001a), Pinus ponderosa Dougl.”
Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model (2008, background): “) and lodgepole pine (Pinus contorta Douglas ex Loudon) (Coops et al., 1998; Law et al., 2000; Waring, 2000; White et al., 2000; Dye, 2001; Landsberg et al., 2001; Tickle et al., 2001; Sands and Landsberg, 2002; Whitehead et al., 2002; Hirsch et al., 2004; Stape et al., 2004; Landsberg et al., 2005;”
Estimating forest productivity in the eastern Siskiyou Mountains of southwestern Oregon using a satellite driven process model, 3-PGS (2001, methodology): “In general, these models have proved useful for integrating different pro cesses and scales of knowledge (Landsberg and Gower 1997), for honing research hypotheses, and for making broad predictions of relative productivity regionally or under different environmental change scenarios (Landsberg et al”