Skip to main content

Comparison of Experimental Designs for Clonal Forestry Using Simulated Data

Buy Article:

$21.50 plus tax (Refund Policy)

Various alternatives for the design of clonal field trials in forestry were studied using simulated data to identify “optimal” or “near-optimal” scenarios for the estimation of genetic parameters. The simulated field site consisted of a rectangular grid on which 256 clones with 8 ramets each were installed. Estimates of genetic parameters were compared for (1) single-tree and four-tree row plots; (2) several experimental designs (completely randomized, randomized complete block, incomplete blocks of various sizes, and row–column); (3) no mortality versus 257% mortality; and (4) different patterns of environmental variability (only patches, only gradients, and both patches and gradients). Use of single-tree plots, on average, increased the correlations between true and predicted clonal values by 57% over four-tree row plots and increased genetic gain from selection. Starting with a parametric broad-sense heritability (H B 2) of 0.25 for a completely randomized design, the experimental designs resulting in the highest H B 2 were row–column designs for single-tree plots and incomplete blocks with 32 blocks per replication when four-tree row plots were used. These designs increased average heritability 107% and 147% over a randomized complete block design, respectively. The only effect of 257% mortality was an increase in the variability of some variance component estimates.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Mixed models; REML; environmental variability; field testing; heritability

Document Type: Research Article

Affiliations: Salvador A. Gezan, School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL 32611—Phone: (352) 846-0894;, Fax: (352) 846-1277, Email: [email protected]

Publication date: 2006-01-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more