NDLI: Allocation of varietal testing efforts for implementing conifer multi-varietal forestry using white spruce as a model species

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Annals of Forest Science : Volume 67

Annals of Forest Science : Volume 66

Annals of Forest Science : Volume 65

Annals of Forest Science : Volume 64

Allocation of varietal testing efforts for implementing conifer multi-varietal forestry using white spruce as a model species

Content Provider	Springer Nature Link
Author	Weng, Yuhui Park, Yill Sung Krasowski, Marek J. Mullin, T. J.
Copyright Year	2011
Abstract	Multi-varietal forestry (MVF) is the deployment of tested tree varieties in plantation forestry. Computer simulation using POPSIM Simulator identified optimal combination of numbers of families, varieties per family and ramets per variety (nf, nc and nr, respectively) yielding the largest genetic gain for a specific status number (NS) in a varietal test (VT) intended for MVF of conifers.Testing 40 to 80 full-sib families and 20 to 30 varieties per family would be optimal for a VT. This nf interval was insensitive to the number of candidate varieties planted, ratio of genetic variances and selection restriction. It was influenced somewhat by individual narrow-sense heritability (h2), required NS and mating design. Lower h2, lower NS and designs with fewer matings per parent tree favoured the lower range of the nf interval. The optimal nr was 6. It was not markedly affected by the required NS, family size or selection restriction but was strongly influenced by h2 and the ratio of genetic variances. Larger h2 or an introduction of non-additive genetic variance allowed planting fewer ramets per variety.
Starting Page	129
Ending Page	138
Page Count	10
File Format	PDF
ISSN	12864560
Journal	Annals of Forest Science
Volume Number	68
Issue Number	1
e-ISSN	1297966X
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-02-19
Publisher Institution	Institut National de la Recherche Agronomique (INRA)
Publisher Place	Paris
Access Restriction	Subscribed
Subject Keyword	POPSIM Simulator Genetic gain Status number Optimization Wood Science & Technology Environment Forestry Management Forestry Tree Biology
Content Type	Text
Resource Type	Article
Subject	Ecology Forestry

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