Competition effects in a young Sitka spruce (Picea sitchensis, Bong. Carr) clonal trial

A - Papers appearing in refereed journals

Brotherstone, S., White, I. M. S., Sykes, R., Thompson, R., Connolly, T., Lee, S. and Woolliams, J. 2011. Competition effects in a young Sitka spruce (Picea sitchensis, Bong. Carr) clonal trial. Silvae Genetica. 60 (3/4), pp. 149-155. https://doi.org/10.1515/sg-2011-0020

AuthorsBrotherstone, S., White, I. M. S., Sykes, R., Thompson, R., Connolly, T., Lee, S. and Woolliams, J.
Abstract

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.

Keywordsgenetic variance; genetic prediction; single-plot design; local spatial trends
Year of Publication2011
JournalSilvae Genetica
Journal citation60 (3/4), pp. 149-155
Digital Object Identifier (DOI)https://doi.org/10.1515/sg-2011-0020
Web address (URL)https://www.thuenen.de/media/institute/fg/PDF/Silvae_Genetica/2011/Vol._60_Heft_3-4/60_3-4_149.pdf
Open accessPublished as bronze (free) open access
FunderEuropean Union
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Project Noveltree
Application of statistical methods to predictive biology
Publisher's version
Output statusPublished
Publication dates
Online05 Aug 2017
Copyright licenseCC BY-NC-ND
PublisherDE GRUYTER POLAND SP ZOO
ISSN0037-5349

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