Tyler, A.L. and MacMillan, D.C. and Dutch, J. (1996) Models to predict the General Yield Class of Douglas fir, Japanese larch and Scots pine on better quality land in Scotland. Forestry, 69 (1). pp. 13-24. ISSN 0015-752X .
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Recent changes in forestry incentives mean that there is potential for an increase in afforestation on better quality agricultural land in Scotland. As a result improved information is required about timber yields from a range of species on better quality sites for production forecasting, financial appraisal, and planning at the local, regional and strategic levels. This paper describes the development of models that enable General Yield Class (GYC) to be predicted from site factors for Douglas fir, Japanese larch and Scots pine. Temporary sample plots were established in stands below 350 m on Land Capability for Forestry class I to V sites. At each location GYC was assessed, as well as the soil, climate and topographic factors which had been demonstrated to influence forest productivity in earlier studies in Scotland. The models, based on a step-wise multiple regression procedure, indicate that mean spring temperature, geomorphic shelter (topex), and crop age are most important in determining the productivity of Douglas fir and Japanese larch. For Scots pine, mean spring temperature, mean winter temperature, and crop age are the most important factors. The models accounted for between 34 and 45 per cent of variation in General Yield Class and are sufficiently precise for estimating mean productivity at regional and national levels.
|Additional information:||Pages 22-23 are missing from attached PDF file.|
|Subjects:||S Agriculture > SD Forestry|
|Divisions:||Faculties > Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)|
|Depositing User:||Douglas MacMillan|
|Date Deposited:||23 Oct 2009 10:02|
|Last Modified:||04 Mar 2013 14:26|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/23101 (The current URI for this page, for reference purposes)|
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