Predicting the yield of Douglas fir from site factors on better quality sites in Scotland

Abstract

In Scotland, as a result of recent changes in agricultural policy and grant schemes, there is now greater potential for planting a wider range of more productive forestry species on better quality land. In order to permit accurate production forecasting and financial appraisals for any such afforestation, it is necessary to develop predictive yield models. This article describes the development of a multiple linear regression model for the prediction of General Yield Class (GYC) of Douglas fir using readily assessed, or derived, site factors. Climate surfaces developed by spatial analysis of weather data were used to predict temperature and rainfall for 87 sample sites to a resolution of 1 km2. Estimates of wind climate were derived from a regression model using geographic location, elevation and topographic exposure. Multivariate analysis of these and other soil and topographic variables indicate that temperature and exposure are most important in determining the productivity of Douglas fir on better quality sites in Scotland. As crop age increases, GYC declines and the possible reasons for this effect are discussed. Other factors are also discussed, such as the genetic variability of Douglas fir, and problems associated with establishment and form. © 1995 Elsevier/INRA.