Forest Resources and Conservation

Dr. Salvador Gezan, Associate Professor

Salvador A. Gezan joined the School in 2011 to lead the quantitative genetic analyses for the CFGRP and FBRC breeding programs. He will also works on Forest Modelling and Forest Biometrics in general. He obtained a co-Ph.D. in Statistics and Forestry with emphasis on Quantitative Genetics from the University of Florida. Prior to joining the School, he was a Statistical and Genetics consultant at Rothamsted Research and VSN International, both at United Kingdom. His current research includes topics in mixed models methodology, construction of forest growth and yield models for natural forest and plantations, and optimal design and analysis of plant and genetic experiments.

Research:
Mixed Linear Models, Quantitative Genetics, Design of Experiments, Sampling, Growth and Yield Modelling, Plant Breeding, Forest and Agricultural Statistics.

“My research focuses on the development/understanding of linear mixed models, particularly in applications to genetics and breeding. Some of my current research projects involve the study of multi-trait analysis of clonal breeding pine trials, and un-replicated experiments and its implications in genetic gain and selection. In the near future, some of the relevant topics that I will be studying include developing applications of mixed model to genetics, such as: generation and analysis of un-replicated trials, multiple site spatial analysis, rankings based in single and two-stage analysis of multiple experiments, incorporation of molecular markers into selection and breeding value estimation, including genomic selection, and combine different sources of information in operational rankings.
My other main research area is associated with the construction of growth and yield models for forest species. Some of my current issues of interest include the use of better competition indexes into forest models, particularly for individual distance independent individual growth models. In addition, I will be developing applications with the use of linear (and non-linear) mixed models for different types of responses (e.g. tree diameter), considering the multi-stratum structure of the data and the correlation that exists among observations (individuals, plots, experimental units, etc.).”

Degrees:
PhD, University of Florida, 2005
BS, Universidad de Chile, Chile, 1996