A system of loblolly pine growth and yield models was developed which used database files as input. Using database files as direct input created a compatible link between the growth and yield models and a Geographic Information System (GIS). Since growth and yield models can be used to update forest inventories and a GIS is a common method for maintaining forest inventory data, this compatibility provided a method to rapidly update past forest inventory records. This system was used to evaluate four different loblolly pine growth and yield models. The growth and yield models examined were: a whole stand, a diameter distribution - parameter prediction, a diameter distribution - parameter prediction, and an individual tree. Three different validation approaches were used to create fitting and validation data sets from permanent plot remeasurement data, and evaluate each of the four growth and yield models at varying projection periods. The periods used were zero, three, six, and nine years. Evaluations were based solely on the capability of each to model to predict merchantable volume. In terms of root mean square error of prediction, the individual tree and whole stand models performed superior than the diameter distribution models. At shorter projection periods the individual tree model performed better than the whole stand model, but the whole stand was superior at the nine year period. The parameter recovery models performed better for shorter periods than the parameter prediction model, but this difference diminished with longer periods. / Master of Science

This study explored the application of compost onto a small loblolly pine tree forest in northeast Texas. Its purpose was to determine if the application of various amounts of compost would provide for accelerated rates of growth for the trees. Soil parameters were also monitored. A total of 270 trees were planted and studied in a northeast Texas forest ecosystem. Compost rates of 5, 25, and 50 tons per acre with either soil or compost backfill were utilized and compared to a control without compost. Nonparametric and parametric ANOVA and Chi-Square tests were utilized. The results indicated that greater application rates retained greater moisture and higher pH levels in the soil. Compost applications also yielded a greater survival rate as well as larger tree height and diameter when compared to the control. The 25 ton/acre application backfilled in native soil achieved the greatest average in height and diameter when compared to the averages for the control plot. Greater growth differences for the 25S application can be attributed to additional nutrients coupled with a stable pH consistent with native soil acidity.

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Gene expression analyses using native populations can provide information on the genetic and molecular mechanisms that determine intraspecific variation and contribute to the understanding of plant development and adaptation in multiple ways. Using quantitative real time – polymerase chain reaction (qRT-PCR), we analyzed the expression of 111 genes with probable roles in wood development in 400 loblolly pine individuals belonging to a population covering much of the natural range. Association mapping techniques are increasingly being used in plants to dissect complex genetic traits and identify genes responsible for the quantitative variation of these traits. We used candidate-gene based association studies to associate single nucleotide polymorphisms (SNPs) in candidate genes with the variation in gene expression. The specific objectives established for this study were to study natural variation in expression of xylem development genes in loblolly pine (Pinus taeda L.) using qRT-PCR, to associate SNPs in candidate genes with the variation in gene expression using candidate-gene based association analyses and to detect loblolly pine promoter polymorphisms and study their effect on gene expression. Out of the 111 genes analyzed using qRT-PCR, there were significant differences in expression among clones for 106 genes. Candidate-gene based association studies were performed between 3937 single nucleotide polymorphisms (SNPs) and gene expression to associate SNPs in candidate genes with the variation in gene expression. To the best of our knowledge, this is the first association genetic study where expression of a large number of genes, analyzed in a natural population, has been the phenotypic trait of interest. We cloned and sequenced promoters of 19 genes, 16 of which are transcription factors involved in wood development and drought response. SNP discovery was done in 13 of these promoters using a panel of 24 loblolly pine clones (unique genotypes). SNP genotyping is underway in the entire association population and association analyses will be done to study the effects of promoter SNPs on gene expression. The results from this project are promising and once these associations have been tested and proved, we believe that they will help in our understanding of the genetics of complex traits.

The molecular mechanisms underlying disease-resistance and drought-resistance in forest trees are not well understood. Linking variation in gene expression with genetic polymorphisms and with variations in disease- and drought-resistance phenotypes can provide information about these complex traits. We used real-time quantitative polymerase chain reaction (PCR) to detect variations in the expression of 88 disease- and drought-responsive genes within an association population of 354 loblolly pine trees (Pinus taeda L.). Using association genetics approaches, we then linked 3,938 single nucleotide polymorphisms (SNPs) in candidate genes with gene expression phenotypes to identify novel disease- and drought-responsive genes. To further examine differences in gene expression induced by drought, Fusarium circinatum (responsible for pitch canker disease), and drought F. circinatum, the expression of 114 genes identified through comparative and association genetics approaches was analyzed on a subset of 24 loblolly pine trees possessing a range of pitch canker- and drought-resistance phenotypes. Significant differences in the uninduced expression of all 88 genes measured on the association population were observed among loblolly pine trees. Principal component analysis showed that some variation within the association population could be accounted for by population substructure of geographic origin. Hierarchical clustering of genes based on uninduced expression did not consistently group together functionally similar genes probably because expression was collected on unstressed stem tissue. This was supported in the smaller expression study as correlations between expression values of genes in the same functional networks were usually stronger when induced by a treatment compared with correlations between the uninduced expression of genes in the control group. Gene expression frequently changed by up to 4-fold in response to one or more treatments, but PtMYB12 was the only gene that exhibited a statistically significant change in response to treatments. ANOVA analyses of gene expression controlling for pitch canker resistance and for water use efficiency phenotypes identified differentially expressed genes suggesting that they may be contributing to these phenotypes. Finally, association genetics approaches detected 101 significant associations between SNPs in 94 candidate genes potentially involved in stress responses and 27 gene expression phenotypes.