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Variation in selected solid wood properties of young Pinus patula from diverse sites in the Mpumalanga escarpment area in South Africa

Muller, Barry G, Louw, Josua H, Malan, Francois S
Southern forests 2017 v.79 no.4 pp. 317-327
Pinus patula, climatic factors, decision making, forests, models, modulus of elasticity, pith, prediction, regression analysis, shrinkage, soil, trees, wood density, wood quality, South Africa
Regression analyses identified ‘Growth Days’ (an index expressing site moisture availability) as the only site variable contributing significantly to the prediction to wood density (R² = 0.57), whereas the model predicting grain angle included only ‘Altitude’ (R² = 0.60). These results surfaced during an investigative study to quantify various sources of variation in wood properties and to quantify the effect of a number of site factors on wood properties of Pinus patula grown in the Mpumalanga escarpment area of South Africa. For this purpose, 10 trees were sampled from each of 17 diverse sites for wood property analyses. The effects of site, distance from the pith and differences between trees within site on wood density, transverse shrinkage, grain angle and dynamic modulus of elasticity were investigated. The site factors considered included a wide variety of soil and climatic factors. The effect of radial distance from the pith and differences between individual trees within sites were highly significant, accounting for most of the variation in wood properties. Although the effects of a number of site factors were statistically significant, they generally explained relatively small but important variation in wood properties among sites. The study not only quantified the effects of important sources of variation on a few key wood properties, but it also revealed that the extent of differences between sites can be explained in terms of some specific site factors. It is envisaged that the results will contribute significantly towards the refinement of current forest site classification systems for improved decision-making with respect to wood quality in intensively managed plantation systems.