The actual timber yield achieved by a stand depends on many factors. While the SI of the growing site is one important factor, other important factors include species composition, stocking, treatment, and losses to pests, disease, and damage. High SI does not guarantee high yield. For example, high site land with no trees on it, produces no timber volume. Figure 2.11 compares the yield expected from an understocked Pl stand on SI = 20 m with the yield that can be expected with full stocking.
A site may have high growth potential (SI) for conifers, but if deciduous trees establish a thick canopy above the young conifers, the site will produce little conifer volume. A high site may have the potential to grow trees rapidly, but if the trees are killed or repeatedly damaged by pests and disease, little timber volume will accumulate. Figure 2.12 provides a hypothetical example of the different yields that can be achieved by Pl stands on SI = 20 m. Scenario A includes delayed regeneration, inadequate stocking, and heavy brush competition and losses to pests. Scenario B includes patchy but adequate stocking, with some brush competition and moderate losses to pests. Scenario C includes prompt regeneration, full stocking, and no brush competition or losses to pests. To produce an accurate estimate of yield, a stand growth model requires an accurate description of SI, stocking, species composition, and expected losses to pests and disease. The model user must not focus solely on SI.
Compared to a poor site, a site that is better for a given tree species provides the required resources (e.g., light, soil water, soil nutrients, CO2) and environmental conditions (e.g., temperature, soil aeration) at levels that are closer to optimum for more days of the year. Under these favourable conditions, trees achieve more growth; top height growth is greater and stands attain a greater top height at bh age 50 years. Thus, the site has a greater site index. The increased height growth of trees on better sites can be understood as a result of four factors (Figure 2.13):