In the analysis of forestry experiments, there may be a need to adjust for competition between plots before predicting deployment performance in the field but there have been few attempts to investigate this. Our analysis looked at diameter data from a 19-year old Sitka spruce clonal trial growing in Scotland. Using a sequence of nested models, a likelihood ratio test indicated that fitting competition at both the genetic and residual level provided a significantly better fit than models which either ignored competition or fitted it at just the genetic or just the residual level. A strong negative genetic correlation of -0.93 +/- 0.05 was found between the direct genetic effects and competition effects. This was not significantly different from -1, indicating that competition is almost exactly proportional to the direct genetic effect and that a tree will exert a competitive effect which is closely related to its own genetic merit for size. At the residual level, the correlation between direct and competition effect was estimated as -0.17 +/- 0.03. We conclude that competition exists at both the genetic and environmental levels and including it in genetic evaluation systems gives a better prediction of future performance. Results also demonstrate that it is possible to obtain useful information about competition effects from a single-tree plot experiment.
|Number of pages||7|
|Publication status||Published - 2011|