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Silva Fennica 1926-1997
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1960-1969
Acta Forestalia Fennica
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Articles containing the keyword 'genetic component'.

Category: Research article

article id 5662, category Research article
Samuel Egbäck, Urban Nilsson, Kenneth Nyström, Karl-Anders Högberg, Nils Fahlvik. (2017). Modeling early height growth in trials of genetically improved Norway spruce and Scots pine in southern Sweden. Silva Fennica vol. 51 no. 3 article id 5662. https://doi.org/10.14214/sf.5662
Highlights: The developed height growth model based on unimproved material predicted the development relatively well for genetically improved Norway spruce; For genetically improved Scots pine, however, the model needed to be modified; By incorporating a genetic component into the Scots pine model, the prediction errors were reduced.

Genetically improved Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) are used extensively in operational Swedish forestry plantations to increase production. Depending on the genetic status of the plant material, the current estimated genetic gain in growth is in the range 10–20% for these species and this is expected to increase further in the near future. However, growth models derived solely from data relating to genetically improved material in Sweden are still lacking. In this study we investigated whether an individual tree growth model based on data from unimproved material could be used to predict the height increment in young trials of genetically improved Norway spruce and Scots pine. Data from 11 genetic experiments with large genetic variation, ranging from offspring of plus-trees selected in the late 1940s to highly improved clonal materials selected from well performing provenances were used. The data set included initial heights at the age of 7–15 years and 5-year increments for almost 2000 genetic entries and more than 20 000 trees. The evaluation indicated that the model based on unimproved trees predicted height development relatively well for genetically improved Norway spruce and there was no need to incorporate a genetic component. However, for Scots pine, the model needed to be modified. A genetic component was developed based on the genetic difference recorded within each trial, using mixed linear models and methods from quantitative genetics. By incorporating the genetic component, the prediction errors were significantly reduced for Scots pine. This study provides the first step to incorporate genetic gains into Swedish growth models and forest management planning systems.

  • Egbäck, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden ORCID ID:E-mail: samuel.egback@slu.se (email)
  • Nilsson, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden ORCID ID:E-mail: urban.nilsson@slu.se
  • Nyström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, 901 83 Umeå, Sweden ORCID ID:E-mail: kenneth.nystrom@slu.se
  • Högberg, Skogforsk, Ekebo, 268 90 Svalöv, Sweden ORCID ID:E-mail: karl-anders.hogberg@skogforsk.se
  • Fahlvik, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden ORCID ID:E-mail: nils.fahlvik@slu.se

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