Abstract:
The need to develop instruments to capture the realistic stumpage volume and infl uence loggers to improve on their logging effi ciency has
been a topic of interest in recent times. This study assessed the logging effi ciency in Ghana and developed allometric models to predict
stumpage volume. A total of 135 trees from nine timber species were sampled from three logging sites during commercial logging operations.
The average logging recovery for all sampled trees was about 75 %. The small-end diameter of the merchantable residues averaged between
31 cm and 60 cm while their length values varied from 3.0 m to 8.5 m. In general, species-specifi c models exhibited better predictive power
than mixed-species models. Models that predicted total merchantable volume from the volume of the extracted logs had the best fi ts, with
Furnival index values ranging from 0.590 to 1.727. Results of the models’ validation indicated that mixed species models could predict
merchantable volume better for relatively small trees than for big trees with merchantable volume greater than 20 m3.
Keywords: sustainable forest management, logging effi ciency, stumpage, allometric models
