For many years, the forest silvicultural practices have depended on technical orders (TO) prepared by the Kenya Forestry Research Institute (KEFRl). The TOs had taken account of the practical plantation management experiences gained over time by the forest operation staff but were not sensitive to the changing economic scenarios.
Some of the TOs issued have become inappropriate to plantation management needs.• The deficiencies in the prescriptions and practices have been widely recognised by operational staff as well as by other participants and stakeholders in the forest industry.
The World Bank mid term review team of the Kenya Forestry Development Project (KFDP) which completed its work in February 1996 highlighted areas of silviculture which needed re-examination. The areas highly questioned were pruning and thinning regimes of the current silvicultural practice which have contributed to the existing huge backlogs in the management of Cupressus lusitanica and Pinus patula. These two species occupy about 7S percent of industrial plantations in the country.
As stated above the need for change emerges when one realises that there has been no alterations in some of the prescriptions since 1969 though there are new research findings. Also today the Forest Department utilises genetically improved seed for it planting programme and there is new commercial focus for industrial development which has called for the shortening of the rotations.
This paper provide attempts made to develop alternative prescriptions for silvicultural practice as relates to spacing, thinning and pruning specifically for the two species mentioned above. This paper is basically reliant on a simulation model which allow a quick view of the situation under various hypothetical but possible scenarios. The model was used as it had been validated with data from the existing forest plantations. The outcome of these studies should form the basis for preparation of revised technical orders for silvicultural practices or assist in setting up research trials in the field to validate the model.