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Forestry

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Browsing Forestry by Author "Dye, Peter."

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    Parameterisation of the 3-PG process-based model in predicting the growth and water use of Pinus elliottii in South Africa.
    (2011) Sithole, Zola.; Dye, Peter.; Zwolinski, Janusz.
    A simplified process-based model simulating growth and water use in forest plantations was utilised to predict the growth of Pinus elliottii in South African forest plantations. The model is called 3-PG (Physiological Principles in Predicting Growth) and predicted the growth of trees by simulating physiological processes that determine growth and water use, and the way trees are affected by the physical conditions to which they are subjected, and with which they react. Pinus elliottii growth data recorded in 301 sample stands around South Africa were sourced from forestry companies. A selection procedure reduced the number of stands to 44, where 32 were used to parameterise 3-PG and 12 were reserved for testing the final model parameters. This was accomplished by matching model output to observed data. All stand simulations were initialised at age four years and continued to the maximum age of recorded growth. A provisional set of parameter values provided a good fit to most stands and minor adjustments of the specific leaf area (σ), which was assigned a value of 5 m2.kg-1, were made, bringing about an improved fit. The predictions of mean DBH, Height, and TPH were relatively good, achieving R2 of 0.8036, 0.8975, and 0.661 respectively, while predictions of stem volumes were worse (R2 =0.5922, n=32). The 3-PG model over-predicted DBH in 20 stands, while modelled volume predictions improved substantially in thinned stands (R2 =0.8582, n=14) compared to unthinned stands (R2 =0.3456, n=18). The height predictions were generally good producing an R2 =0.8975. The final set of 3-PG parameter values was then validated against growth data from the 12 independent stands. The predictions of mean DBH, Height, and TPH were relatively good, achieving R2 of 0.8467, 0.7649, and 0.9916 respectively, while predictions of stem volumes were worse (R2 =0.5766, n=12). The results of this study demonstrated the potential for 3-PG to respond to many growth factors and to predict growth and water use by trees with encouraging realism. Patterns of changing leaf area index (L) over time, responses to drought, and annual evaporation patterns all look realistic. Consequently, 3-PG is judged to have potential as a strategic forestry tool.