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Shoot Elongation Patterns and Genetic Control of Second-Year Height Growth in Pinus taeda L. Using Clonally Replicated Trials

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PAGE 1

SHOOT ELONGATION PATTERNS AND GENETIC CONTROL OF SECOND YEAR HEIGHT GROWTH IN Pinus taeda L. USING CLONALLY REPLICATED TRIALS By LILIANA MARTA PARISI A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Liliana Marta Parisi

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To Elsa and Ruben, my parents Javier, my brother Fabian, my husband Olga, my mother in-law and Luisa. To my friends Laura, Laura, Natalia, Andrea, Tete, Claru and Doa Isabel

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iv ACKNOWLEDGMENTS I would like to thank Drs. Timothy Mart in, Dudley Huber and Timothy White for serving on my advisory committee, sharing with me their time, knowledge and help during this program. In particular, I want to express my enormous gratitude to Dr. Huber for his guidance, support and encouragemen t and also for his immense disposition and patience explaining difficult concepts to me over and over again. I especially thank Dr. Martin, for always providing me with valuab le help for collecting the large amount of data that this project dema nded. Thanks also go to Mr. Greg Powell for his support in several aspects. This research was done with the financ ial support of the Cooperative Forest Genetic Research Program (CFGRP) and th e Forest Biology Research Cooperative (FBRC), and I really hope the results of this study contribute to the continued success of the cooperatives and the better knowledge of loblolly pine height growth. I also would like to acknowledge th e financial support of the FulbrightBunge&Born fellowship for giving me the opport unity to initiate my graduate studies here in the United States and to the CFGRP for additional fundi ng. My thanks also go to INTA (National Institute of Agriculture T echnology), my employer, for maintaining my position and salary all this time. I further acknowledge Blanca Canteros, Sara Caseres and Juan A. Lpez (h.) for their encouragement and support to continue my academic career.

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v Special thanks are extended to all th e people who helped me with the data collection for this project: particularity, Dr. Huber and Mr. Greg Powell for their amazing job at Georgia site; my fellow graduate st udents: Brian Baltunis, Veronica Emhart, Salvador Gezan, and Alex Medina, who also ga ve me valuable tips for classes and other academic issues; my friends Bijay Tamang and Jorge Baldessari, who freely and willingly gave me a helping hand not only with the field work but also with classes; and the help of the FBRC field crew. I want to thank Ms Debra Anderson and my “Fulbright friends” for being such great company on all those special dates that being with family is so important. My special thanks also go to Tirhani Manganyi who cheers my days with her friendship. Finally, and most important, I thank my pare nts and brother for their love, help and support; and, last but not at le ast, I want to thank my hus band, Fabian Hergenreder, who brought me joy and encouragement every day during this master’s program and for bearing stoically my daily supervision duri ng his amazing job of measuring flush length and number of stem units.

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vi TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES...........................................................................................................viii LIST OF FIGURES...........................................................................................................xi ABSTRACT......................................................................................................................x ii CHAPTER 1 INTRODUCTION........................................................................................................1 2 MATERIALS AND METHODS.................................................................................7 Study Area Characteristic.............................................................................................7 Plant Material and Experimental Design......................................................................8 Traits Measured............................................................................................................9 Initiation and Cessation.........................................................................................9 Flush Descriptors.................................................................................................11 Statistical Analyses and Genetic Parameters..............................................................14 Phenological Traits..............................................................................................14 Flush Descriptors.................................................................................................19 3 RESULTS AND DISCUSSION.................................................................................24 Phenological Traits.....................................................................................................24 Least Square Means for Phenologica l Traits by Provenance and Propagule Type.................................................................................................................24 Heritability Estimates..........................................................................................27 Height Growth Increment.............................................................................27 Cumulative and Cumulative Percenta ge Height Growth Increment............28 Phenological Traits and AHI ........................................................................29 Correlations Among Phenological Traits............................................................30 Initiation-Duration Correlation....................................................................31 Cessation-Duration Correlation....................................................................31 InitiationAHI and Initiation-Cess ation Correlations...................................31 InitiationASRG Correlations.......................................................................32 CessationASGR Correlations......................................................................34

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vii Path Analysis.......................................................................................................34 Flush Descriptors........................................................................................................36 Heritability Estimates..........................................................................................36 Type B Correlation..............................................................................................40 Growth and Shoot Components...................................................................43 Flush Descriptors..........................................................................................43 Path Analyses......................................................................................................44 Annual Height Increment with Number of Flushes and Average Flush Length.....................................................................................................44 Flush Length with Number of Stem Units and Mean Stem Unit Length.....47 Least Square Means for Provenance for FLn, PFL, NSU and MSUL .................54 Phyllostatic Patterns............................................................................................58 4 CONCLUSIONS........................................................................................................60 APPENDIX A DIFFERENCES BETWEEN PROPAGULE TYPES................................................63 B SECOND-YEAR PHENOTYPIC, GENETIC and ENVIRONMENTAL CORRELATIONS BETWEEN FLUSH LENGTHS ( FLn ), NUMBER OF STEM UNITS ( NSU ) and MEAN STEM UNIT LENGTH ( MSUL ) by FLUSH..................66 C SECOND-YEAR GROWING SEAS ON PHYLLOSTATIC PATTERNS...............73 LIST OF REFERENCES...................................................................................................74 BIOGRAPHICAL SKETCH.............................................................................................80

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viii LIST OF TABLES Table page 2-1 Phyllostatic series identification...............................................................................14 2-2 Number of trees involved in each of the analyses by site and propagule type.........23 3-1 Least square means for second-year phenological traits and annual height increments by provenances and propagule type for 2004 growing season in Site 1 (North Central Florida) and Site 2 (Southwest Georgia)......................................25 3-2 Incremental height growth: narrow ( h2) and broad-sense ( H2) heritabilities on measurement days during 2004 growing s eason by propagule type at Site 1 (North Central Florida).............................................................................................28 3-3 Cumulative height growth: narrow ( h2) and broad-sense ( H2) heritabilities on measurement days during 2004 growing s eason by propagule type at Site 1 (North Central Florida).............................................................................................29 3-4 Cumulative percentage of height growth: narrow (h2) and broad-sense (H2) heritabilities on measurement days during the 2004 growing season by propagule type in Site 1 (N orth Central Florida).....................................................29 3-5 Individual narrow ( h2) and broad-sense ( H2) heritabilities fo r phenological traits and AHI by propagule type for the 2004 growi ng season in Site 1 (North Central Florida) and 2 (Southwest Georgia).........................................................................30 3-6 Genetic, phenotypic and environmenta l (microsite) correlations between phenological traits and annual height increment ( AHI) by propagule type for 2004 growing season in Site 1 (North Central Florida) and 2 (Southwest Georgia)....................................................................................................................33 3-7 Values of phenotypic and genetic path coefficients, correlation coefficients and degrees of determination for annual height increment ( AHI ) by growth duration ( D ) and average shoot growth rate ( ASRG ) by propagule type for Site 1 (North Central Florida)........................................................................................................35 3-8 Site 1 (North Central Florida): individual-tree narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propagule type for the 2004 growing season.........................................................................................................38

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ix 3-9 Site 2 (Southwest Georgi a): individual tree narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propagule type for 2004 growing season.........................................................................................................39 3-10 Across site individual narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propagule type for 2004 growing season for Site 1(North Central Florida) and Site 2 (Southwest Georgia).......................................41 3-11 Type B correlations for growth a nd shoot components by propagule type for 2004 growing season between Site 1 (Nor th Central Florida) and Site 2 (Southwest Georgia).................................................................................................42 3-12 Phenotypic and genetic values for path coefficients components, correlations coefficients, and degree of determina tions for annual height increment AHIFLn by number of flushes ( NF ) and average flush length ( AvFL ) by propagule type for Site 1 (North Central Florida) and Site 2 (Southwest Georgia)..........................46 3-13 Site 1 (North Central Florida): phenotypi c values of path coefficients and path components, correlations coefficients and degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type..........................................................................48 3-14 Site 2 (Southwest Georgia): phenotypic values of path coefficients and path components, correlations coefficients and degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type..........................................................................49 3-15 Site 1 (North Central Florida): geneti c values for path coefficients and path components, correlation coefficients a nd degrees of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type..........................................................................52 3-16 Site 2 (Southwest Georgia): genetic values for path coefficients and path components, correlation coefficients a nd degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem units ( NSU ) by propagule type........................................................................53 3-17 Frequency of phyllostatic series by pr opagule type in Site 1 (North Central Florida) and 2 (Southwest Georgia).........................................................................59 A-1 Significance levels (p-values) be tween propagule types for annual height increment and phenological traits at Site 1 (North Central Florida) and Site 2 (Southwest Georgia).................................................................................................64 A-2 Significance levels (p-values) betwee n propagule types for height increment, average cumulative height increment and average percentage cumulative increment at Site 1 (North Central Flor ida) and Site 2 (Southwest Georgia)..........64

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x A-3 Significance levels (p-values) betw een propagule types for growth and shoot components at Site 1 (North Central Flor ida) and Site 2 (Southwest Georgia).......65 B-1 Site 1 (North Central Florida): cutti ngs genetic, phenotypic and environmental (microsite) correlations between flush length ( FLn ) by flush for 2004 growing season.......................................................................................................................67 B-2 Site 1 (North Central Florida): cutti ngs genetic, phenotypic and environmental (microsite) correlations between numbers of stem units (NSU) by flush for 2004 growing season.........................................................................................................68 B-3 Site 1 (North Central Florida): cutti ngs genetic, phenotypic and environmental (microsite)correlations between mean stem unit length (MSUL) by flush for 2004 growing season................................................................................................69 B-4 Site 2 (Southwest Georgia): cutti ngs genetic, phenotypic and environmental (microsite)correlations between flush length ( FLn ) by flush for 2004 growing season.......................................................................................................................70 B-5 Site 2 (Southwest Georgia): cutti ngs genetic, phenotypic and environmental (microsite)correlations between numbers of stem units (NSU) by flush for 2004 growing season.........................................................................................................71 B-6 Site 2 (Southwest Georgia): cutti ngs genetic, phenotypic and environmental (microsite) correlations between mean stem unit length (MSUL) by flush for 2004 growing season................................................................................................72 C-1 Individual tree narrow and broad-sense heritabilities for phyllostatic patterns by propagule type for 2004 growing season in Site 1 (North Cent ral Florida) and Site 2 (Southwest Georgia)......................................................................................73

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xi LIST OF FIGURES Figure page 2-1 Loblolly pine parastichy arrangement......................................................................13 3-1 Least square means for average cumulati ve apical height growth increment and apical height growth increment by pr ovenance and propagule type at Site 1 (North Central Florida).............................................................................................26 3-2 Least square means for number of flushes ( NF ) and annual height increment as a summation of flush length ( AHIFL) for the 2004 growing season by propagule type at Site 1 (North Central Flor ida) and Site 2 (Southwest Georgia)...................55 3-3 Least square means for flush length ( FLn ) and flush length contribution (PFL) by propagule type at Site 1 (North Ce ntral Florida) and Site 2 (Southwest Georgia). LG, FL and ACC are Lower Gu lf, Florida and Atlantic Coastal Plain provenances, respectively.........................................................................................56 3-4 Least square means for number of st em units (NSU) and mean stem unit length (MSUL) by propagule type at Site 1 (N orth Central Florida) and Site 2 (Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic Coastal Plain provenances, respectively..................................................................57

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xii Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science SHOOT ELONGATION PATTERNS AND GENETIC CONTROL OF SECOND YEAR HEIGHT GROWTH IN Pinus taeda L. USING CLONALLY REPLICATED TRIALS By Liliana Marta Parisi May 2006 Chair: Timothy A. Martin Cochair: Dudley A. Huber Major Department: Forest Resources and Conservation. Height growth is one of the most commonly measured phenotypic traits for assessing volume production in tree improve ment programs. This study focused on the genetic architecture of the phenological (initiation, cessation, duration and growth rate) and morphological (number of flushes, flush length, number of stem units ( NSU ), mean stem unit length ( MSUL )) aspects of the second-year annual height growth, using approximately 900 clones and 61 seedling fam ilies of loblolly pine from 61 full-sib families and 3 provenances. Rooted cuttings differed from seedlings for all phenological and morphological traits that were analyzed in this study. This difference was due to propagation effects since types were compared for common families. The overall results of this study indicated that the average growth rate per day was the most important variable in determining second-year annual height increment. The

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xiii contribution of growing season duration to second year annual height increment was negligible. Both analogies were used to a ssign relative importance to the components of height growth. The narrow and broad-sense he ritability estimates for the different dates for height growth increment during the gr owing season were moderate and decreased from initiation date to cessation date. For the total population average flush length was the principal contributor to total annual height while number of flushes was a minor contributor. NSU was by far the most important trait for th e length of the first three flushes. For later flushes NSU and MSUL contributed equally to flush length The genetic contribution of MSUL to flush length was relatively larger than the phenotypic contribution, becoming more important than NSU after flush 3, especially for seedlings. Provenances demonstrated differe nt shoot elongation patterns. FL provenance had higher growth at the beginning of the growing season while ACC and LG growth was slightly higher than FL seed source after the second fl ush. Length of the early flushes appeared to confer a significant advantage for FL cutting over the other seed sources. Florida-source loblolly pine also had a longe r growing season and more flushes than the other provenances. With an understanding of the relationshi p among the loblolly pine shoot growth components, their genetic parameters and th eir physiology, we can obtain the structural and functional clues about differences among pr opagule types, seed sources, family and clones for annual height growth performance.

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1 CHAPTER 1 INTRODUCTION Pinus taeda L. (loblolly pine) is the most im portant commercial tree species planted in the southern United States occupying approximately 12 million hectares (Jokela and Long 2000). The material planted over the last 50 year s has been developed from bulk orchards, open-pollinated orchards, full-sib families and more recently clones. In the southern United States, state agencies and forest companies carry out tree improvement programs and some of them are initi ating their third genera tion of breeding. The overall gains in volume per unit area range from 10 to 30 percent over unimproved material; depending the deployment strategies used; but, if just the best full-sib and clones are planted, gains of 35 to 50 percent are possible (McKeand et al 2003). Height growth is one of the most commonly measured phenotypic traits for assessing volume production in tree impr ovement programs (Kremer and Lascoux 1988) and also seems to be the most dependable and simplest trait for early selection in loblolly pine in the southeastern United States (B ridgwater and McKeand 1997). Annual apical growth in conifers is a compound trait and can be divided into multip licative and additive components (Cannell 1978 and Ford 1980). Those components can be grouped into phenological and morphogenical aspects. Know ledge of pine shoot growth components is essential for understa nding height growth. Annual apical growth (annual height increment AHI ) can be considered as the product of shoot growth duration ( D ) and the average shoot growth rate ( ASGR ). For estimation of D and ASGR in addition to height growth, the phenological traits, timing of

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2 initiation and cessation, have to be determine d. Higher growth rate was responsible for the superior height growth of two interprovenance jack pine ( Pinus banksiana ) families (Magnussen and Yeatman 1989). Perry et al. (1966), determined for loblolly pine that growth rate accounted for about 60 percent of the height growth variation. Bollmann and Sweet (1977) suggested that one of the reasons for the high growth rate of Pinus radiata is its extensive growing season. For loblolly pine Jayawickrama et al. (1998), implied that large gains in growth rate can be obtai ned from north Florida material because of their genetically longer growing season. Dougherty et al. (1994) reported an almost 6 week difference in bud break timing in P. taeda from two localities which differ by 6 latitude (Gulf Coast 30.5 and North CarolinaVirginia border 36.5N). Loblolly pine has a broad natural range (14 States in US A, Burns and Honkala 1990) which promotes the occurrence of diverse ecotypes. Loblolly pine has a complex shoot mo rphogenesis, with the annual height increment including many flushes or cycl es (Boyer 1970; Griffing and Elam 1971; Bridgwater et al. 1985; Bridgwater 1990; Harrington 1991) There are commonly 3 to 6 cycles, and two types of growth, predetermi ned and free (Lanner 1976). Height growth initiation is primarily related to temperatur e (Boyer 1970; Ford 1980) and it has been not determined if the overwintering bud goes thr ough a true dormancy or only a chilling period is needed to burst (Carlson 1985). Api cal height growth star ts during the spring with the elongation of the stem units present in the overwin tering bud and this constitutes the first flush. This is predetermined growth because all the stem units that constitute the first flush were formed during the pr evious growing season. Commonly the overwintering bud contains only one flush, but one or two cycles from the preformed bud

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3 were noted by Greenwood (1980) Subsequent flushes ar e called free, summer or indeterminate growth. The main characteristic of this type of growth is that both the bud and the elongation of its components occur in the same growing season, generally during the summer. The number of free cycles vari es from 1 to 7 (Lanner 1976). Griffing and Elam (1971) studied the height growth patterns of loblolly pine saplings and pointed out overlapping flush elongations. Usually two c onsecutive cycles elongate concomitantly. At the time that a succeeding flush is at it s maximum elongation rate the growth rate of the previous flush decelerates. This rep eated pattern occurs until the winter bud is formed, which takes place when a succeeding bud does not elongate even when the preceding flush is fully elongated. Several st udies of shoot growth have assessed the relative contributions of pr edetermined and free growth (Pollard and Longan 1974; Cannell and Johnstone 1978; Ba iley and Feret 1982). Zhang et al (1997), in loblolly pine under nitrogen fertilization, found that on average the first flus h contributed about 69% of the total leaf area. M easuring annual shoot growth Isik et al. (2002) concluded that summer shoot growth can serve as an e xplanatory variable to predict height growth in Pinus brutia populations. Thus, annual shoot length is the result of the summation of predetermined and indeterminate flushes. The number of flushes also has an influence on height growth. Under different levels of vege tation control and site preparation in 3-yearold loblolly pine, the individua ls with superior height grow th had a larger numbers of flushes and a greater length per flush (Allen and Wentworth 1993). The length of each flush is the product of the number of stem units ( NSU ) and the mean stem unit length ( MSUL ). The partitioning of the s hoot growth into its components allows a better understanding of the gene tic variation in height growth through

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4 phenological, morphological and ph ysiological characteristic s associated with shoot growth (Rehfeldt and Lester 1966; Magnussen and Yeatman 1989; Rweyongeza et al. 2003). Theoretically NSU and MSUL are inherited independen tly because the meristems for stem unit initiation and for stem unit elongation are physically different and are activated at different times by independent mechanisms (Cannell et al. 1976; Cannell 1978). The division of conifer shoot growth into its factors has been performed by several authors, providing a method for asse ssing genetic, phenotypic and environmental variation but with very diverse results. NSU has been shown to be more important contributor to shoot leng th in loblolly pine, P. rigida and their hybrids (Bailey and Feret 1982), in P. pinaster (Kremer and Lascoux 1988), in Abies cephalonica (Fady 1990), in P. elliottii under two nitrogen treatments (Smith et al. 1993b) and P. palustris (Allen and Scarbrough 1970). For Kremer and Xu (1989), MSUL was the component with the highest stability and also a better predictor of total height in P. pinaster Kaya (1993) working with Douglas-fir obtai ned moderate correlations among NSU, MSUL and height increment. In P. patula Gmez-Crdenas et al. (1998) found that both MSUL and NSU where influential components in shoot height with a low negative correlation between them. Negative correlation between NSU and MSUL was reported by several authors (Kremer and Larson 1983; Bongarten 1986; Kremer and Lascoux 1988; Magnussen and Yeatman 1989) who suggested that NSU and MSUL are not good selecti on criteria. Some studies show variation between provenan ces and families within provenances for NSU and MSUL. Kremer and Larson (1983) reported that NSU was a better predictor of annual height increment on a provenance level, whereas MSUL was a slightly better predictor on a family-within provenance leve l. Within provenances of Douglas-fir

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5 ( Pseudotsuga menziesii ) and blue spruce ( Picea pungens ) the phenotypic variation in shoot length assigned equally to MSUL and NSU In blue spruce the genetic variation was mostly due to MSUL and the environmental vari ation was caused primarily by NSU (Bongarten 1986). Rweyongeza et al. (2003) working with white spruce found that MSUL would give more expected gain from direct selection at 11 years than NSU for both of the sites in which they were working. Their path coefficien t analysis indicated that branch length was primarily determined by NSU Assessing height growth variation for NSU and MSUL several studies have promoted differential genetic expression of juvenile traits for predicting field performance by creating different environments such as irrigation and/or fertilization with promising results in slash pine (DeWald et al 1992; Smith et al 1993b; Surles 1993) in loblolly pine (Li et al 1992; Williams 1988; Waxler and van Buijtenen 1981). Traits of shoot growth patterns ( NSU MSUL annual height increment ( AHI ), number of cycles) have been evaluated as early selection criteria on genotypic and phenotypic age-age correlations with vary ing results (Williams 1987; Williams 1988; Bridgwater 1990; Li et al 1991; Li et al 1992; Smith et al 1993a; Lu et al 2003). In one study, second-year total annu al height increment was found to be better correlated to 8-year height performance than MSUL or NSU in loblolly pine (Bridgwater 1990) while summer NSU and AHI of treatments with supplementary irrigation and fertilization had equal or better correlation with 8-year height (Li et al 1992). One of the advantages of working with clonal tests derived from full-sib families is the chance to estimate additive and non-a dditive genetic components of variance associated with a specific trait (Isik et al 2003). Isik et al (2003) working with a

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6 clonally replicated trial of loblolly pine de termined that additive variance was the major source of genetic variance in height growth. Dominance va riance for height, diameter and volume was insignificant during the first y ear, but was important at age 6. Epistatic variance was not important for growth traits. Similar results for additive and dominance variance were obtained by Paul et al (1997) for height. The im portance of dominance at age 5 indicates the lik elihood of additional ge netic gains through cl onal testing (Carson 1986; Paul et al 1997). Isik et al (2003) arrived at a sim ilar conclusion and suggested that clonally replicated proge ny tests may provide special ad vantages for loblolly pine tree improvement programs. In clonal tests the efficiency of testing is increased by averaging the microenviromental variance a nd a more precise estimation of genetic parameters can be obtained. This study examined loblolly pine shoot gr owth patterns in clones in two different environments, and provided the opportunity to examine the genetic mechanisms controlling tree growth strategies and to examine the adaptability of Florida material to cooler environments. The present study c ontains large numbers of clones (around 900) from full-sib families derived from a partia l diallel mating design. The objectives were to: (i) Determine whether propagule types, seed sources, families or clones differ in the timing of growth initiation or cessation; (i i) Estimate genetic parameters, genetic architecture, propagule type and seed sour ce effects for phenologi cal and morphological traits; (iii) Determine the relative contributions of the number of flushes to total height growth; and (iv) Determine the relative cont ributions of the different components of the flush to flush length.

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7 CHAPTER 2 MATERIALS AND METHODS Study Area Characteristic Two loblolly pine sites of the Forest Biology Research Cooperative (FBRC) CCLONES (Comparing Clonal Lines On Expe rimental Sites) study were measured during their second growing season. The inte nsive silvicultural treatment portion of those tests was chosen for this study. Site 1 was on Plum Creek land in Putnam County, Florida (approximate latitude 29 38’ 24” N, longitude 81 49’ 27” W; elevation: 7m.) and Site 2 was on MeadWestvaco land in Randolph County, Georgia (approximate latitude 31 47’ 59” N, longitude 84 41’ 32” W; elevation: 137m). The soils at Site 1 belong to Pomona fine sand soil series with slopes from 0 to 2 percent. Their taxonomic classification is sa ndy, siliceous, hyperthermic Ultic Alaquods. These soils are very deep and have a surface la yer of black fine sand of about 18 cm. The subsurface layer is gray and light-gray fine sand with a depth of about 50 cm. The upper part of the subsoil is dark reddish brown loam y fine sand of a depth of 70 cm. Below that layer is dark brown and light brownish gray fine sand at an approximate depth of 105 cm. At around 180 cm the lower layer is gray and light gray fine sandy loam. The substratum as deep as 200 cm is greenish gray fine sandy loam. The water table under natural conditions is within 15 to 45 cm of the surface fo r one to three months and is at a depth of 25 to 100 cm for six months or more during mo st years. The natural fertility of these soils is low (Readle 1990). The average a nnual precipitation for the test area is around

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8 1250 mm. The average high and low temper atures in summer are 33.4C and 24.2C, respectively. The average high and low te mperatures in winter are 16.3C and 6.6C. Soils at Site 2, Randolph County, GA, are cla ssified as the Red Bay soils series. The Red Bay series consists of very deep, well drained, moderately permeable soils that formed in thick beds of unconsolidated, loamy marine sediments on uplands of the Coastal Plain. Slopes range from 0 to 15 per cent. The taxonomic classification is fineloamy, kaolinitc, thermic Rhodic Kandiudults. The typical sequence of horizons of this series is a dark reddish-brown sandy loam Ap horizon of about 15 cm, from approximately 15 to 120 cm this soils has a seri es of Bt horizons (Bt 1, Bt2 and Bt3) dark red sandy loam to sandy clay loam (Monroe 2005). The average a nnual precipitation for the test area is around 1340 mm. The average high and low temperatures in summer are 33.5C and 18.8C, respectively. The average hi gh and low temperatures in winter are 10.6C and 3.5C. Plant Material and Ex perimental Design The study population consisted of 61 genetically-improve d full-sib loblolly pine families. The families were generated from 30 selected parents from the Atlantic Coastal Plain of South Carolina and Ge orgia, the flatwoods of Florid a and the Gulf Coastal Plain of Mississippi and Alabama. Two slow-gro wing parents were incl uded as connectors with other studies (FBRC 2000). The 32 parent s were mated in a pa rtial diallel design creating 70 full-sib families but just 61 full-sib families where in this two test. The material was propagated at the Internati onal Paper Company greenhouse in Jay, Florida (Baltunis et al 2005). The experimental design is an Alpha latt ice with 4 complete replications per treatment. Each replication had 1,120 and 1,100 trees at Site 1 and 2, respectively. Weed

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9 control, pesticides and the a ddition of macro and micro nutrien ts constitute the intensive silvicultural treatment. The tests were planted in 2002 with a chemical site preparation prior to planting. At Site 1 the chemical s ite preparation was done with a combination of triclopyr, glyphosate and imazapyr. Vegetation competition was controlled with directed spray application of glyphosat e during the first and second gr owing season. In May 2003 the test received a broadcas t application of 280 kg ha-1 of diammonium phosphate. During April 2004 560 kg ha-1 of 10-10-10 and micronutrients were applied and in June 2004 the test received 4.17 kg ha-1 of copper supplement. At Site 2, before the bed preparation the area was broadcas t sprayed with glyphosate. Du ring the first year the site was sprayed with sulfometuron methyl and la ter released with gl yphosate applied with backpack sprayers. The fertil izer application was applied before bedding preparation and consisted of 11.2 kg ha-1 micronutrients blend and 902 kg ha-1 of 15-07-13. The total number of clones tested was 941 in Site 1 and 868 in Site 2 (FBRC 2003). This allowed us to compare the genetic pe rformance of 30 elite parents, 61 full-sib families, and about 900 clones within the full-sib families. Traits Measured Initiation and Cessation Height growth increment was assessed to estimate timing of initiation and cessation using repeated measurements during the 2004 gr owing season. Before the trees of Site 1 started their second growing seas on all the trees were marked on their east side with an orange paint as near to the top as possible. The distance from the orange paint mark to the top was measured and used as a referen ce. Consecutive measurements were taken every fifteen to twenty days during the spri ng and fall for growth initiation and cessation and every thirty to forty days during the su mmer for monitoring height increment. The

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10 first and the last measurement were performe d on day of year 44 and 323, respectively. Four replications of each test (4440 trees) we re measured. While the top of the trees could be reached easily, measurements were accomplished using a ta pe graduated in cm (Lufkin Executive thinline 2m W606PM). After May 2004 a T-form graduated pole was used. The T form was used to place the tip of the tree under one of the T’s arms with the objective of having more accurate measur ement knowing that the pole was exactly at the top of tree. Height increment was measured to the nearest 0.1 cm. During 2004 the State of Florida was hit by three major hur ricanes. None of them hit the study sites directly but their proximity affected Site 1, especially with flooding and wind damage. Trees which were leaning greater than 20-25 de grees from the vertical were not included in the determination of cessation. The fina l number of trees measured at Site 1 was 4,038. From late August to early December 2004 (day of year 243 to 348) measurements for determining timing of growth cessation were done at Site 2, initially on 3,252 trees. With the help of a trailer pulled by an All Te rrain Vehicle (ATV) the top of the trees were reached and the painted reference measurement was placed 20 cm from the tip. Site 2 was relatively unaffected by the hurricanes but many trees suffered from tip die-back which reduced the cessation data. The final number of trees measured at Site 2 was 3,049. Percent of cumulative height was calculate d to observe the proportional distribution of the height growth over the growing seas on using total second year increment and periodic summer measurements (Allen and We ntworth 1993). The cumulative height increment was plotted by day of year and the dates of height growth initiation and cessation were estimated by interpolation to de termine the dates of which 5% and 95% of

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11 the total annual height were reached (Mirov et al 1952; Hanover et al 1963; Cannell and Willett 1976; Jayawickrama et al 1998). At Site 1 the second growing season duration ( D ) was determined by subtracting the initia tion date from the cessation date and the average rate of shoot growth ( ASGR ) (cm day-1) was calculated dividing 90% of the AHI by D Flush Descriptors Traits involving flush length ( FLn ), number of flushes ( NF ) and number of stem units ( NSU ) were measured, in 2005 once the shoots were fully elongated. When those traits were measured mean stem unit length ( MSUL ) and annual height increment ( AHIFLn) were calculated. AHIFLn was computed as the sum of the flush lengths of the annual shoot. This height increm ent was slightly different from AHI described above. The number of trees evaluated was 2,132 at Si te 1 and 2,101 at Site 2. Flush length and number of stem units were measured for each flush of the main leader. A 2.4 m ladder was used to reach and measure the flush length and count the number of stem units. Each flush whether predetermined or free growth is characterized by a whorl of branches at the bottom followed by a sterile bract zone, the fertile bract zone (needle-fascicles) and another whorl of branches (or branches buds) at the top. Thus, flush length was measured from the whorl of branches at the bottom to the other whorl of branches at the top with a graduated pole to the nearest 0.1 cm. Annual height increment was obtained by adding the flush length of each cycle fo r each tree. Also the proportion of AHIFLn attributable to each flush ( PFLn ) was calculated by dividing the length of each flush by the AHIFLn and multiplying the result by 100. The term “stem unit” was introduce by Doak in 1935 and has been used by several authors with different meanings since then (C ritchfield 1985). Stem unit in this study is

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12 as defined by Doak (1935): A pine stem unit is comprised of four components 1) a node, 2) the internode below it, 3) a lateral appendage at the node (usually a needle fascicle), and 4) structures in the axia l of the lateral appe ndage. The first three components are always present. NSU are the number of needles and ster ile bracts which are in a spiral disposition along the flush or stem. One of the nondestructive ways to assess the number of stem units is through the le af arrangement (needle-fascicl es and sterile bracts) on the tree stem (phyllotaxis). Pinus species present phyllotactic pa rastichies (spira l or helix). These can be illustrate as imaginary lines that join adjacent stem units (Doak 1935; Kremer and Roussel 1982; Kremer et al 1989, Fredeen et al 2002) (Figure 2-1). Those helical arrangements on each pine flush can be followed in either clockwise (left) or counterclockwise (right ) direction (Zagrska-Marek 1985; Fredeen et al 2002) and are also known as opposed parastichy pairs (Figur e 2-1). The number of stem units was determined by counting the stem units on one of the ascending parastichy ( n ) and multiplying that number by the number of parastichies on each flush ( np ) (Allen and Scarbrough 1970; Fady 1990 and Bridgwater 20 04, personal communication) (Figure 21, Equation [2-1]). np n NSU [2-1] where NSU are the number of stem units n are the number of stem units on a single parastichy and np are the number of parallel parastichies A permanent marker was used to follow the spirals from the bottom to the top of the flush. To avoid systematic errors the same person evaluated the number of the stem units at both sites.

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13 Figure 2-1. Loblolly pine para stichy arrangement. A) The line marked in black shows a clockwise parastichy. B) The lines in color show two opposing parastichies: the clockwise in yellow and the coun terclockwise in red. The numbers illustrate a way to obtain the number of parastichies on each flush. For example: counting the stem units in a clockwise manner (yellow) the number of parastichies on that flush is fi ve. Counting in the counterclockwise direction the number of para stichies is eight, so fo r this flush the number of opposing parastichies is 5:8. (Drawi ng adapted from Kremer and Roussel 1982). Mean stem unit length (MSUL) was obtaine d by dividing the flush length (mm) by number of stem units (NSU) (Equation 2-2). NSU mm length Flush MSUL [2-2] Even though determining helical phyllotactic patterns (PPs) was not one of the objectives of this study, the way that NS U were measured provided a pattern of arrangement in terms of rec ognizable contact parastichies. Different helical phyllotaxis series can be typified by the number of opposing parastichies and the value of the divergence angle (angle betw een successive fascicles on the stem). The helical A B

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14 phyllotactic series classificat ion adopted in this study wa s the one proposed by ZagrskaMarek (1985) (Table 2-1), who followed th e earlier proposal of Richards (1951) and differs little from Jean (1988). PPs were analyzed as an additional trait. Table 2-1. Phyllostatic series identification. Phyllotactic patterns Divergence angle () Sequence of opposed parastichy numbers Monojugate pattern Fibonacci (principal) First accessory Second accessory Third accessory . Seventh accessory 137.5 99.5 77.9 64.08 . 132.2 2:3:5:8 … 3:4:7:11 … 4:5:9:14 … 5:6:11:17 … 3:8:11:19 ... Multijugate patterns Bijugy Trijugy 137.5/2 137.5/3 2:4:6:10 … 3:6:9:15 … Adapted from Zagrska-Marek (1985) Statistical Analyses and Genetic Parameters Phenological Traits The phenological and growth variables were analyzed in ASREML (Gilmour et al. 2002). Analyses were first run for each propa gule type and site separately. A parental model was used to estimate the genetic vari ances components. Equations 2-3 and 2-4 show the linear models for cutti ngs and seedlings respectively. Yijklm = + Ri + incblkj(i) + gcak + gcal + scakl + clonem(kl) + rgcaik + rgcail + rscaikl + ijklm [2-3] Yijklmn is the measured trait of the mth clone within the klth full-sib family in the jt h incomplete block within the ith replication. is an overall mean Ri is the fixed effect of replication, i = 1,2,3,4 incblkj(i) is random incomplete block ~ (0, Diag2 ) (ˆi incblk) gcak and gcal are the random female (k) and male (l) general combining ability respectively ~ N (0, A2ˆGCA) where A is the numerator relationship matrix scakl is the random specific combining ability ~ NID (0, 2ˆSCA)

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15 clonem(kl) is the random clone within full-sib family ~ NID (0, 2ˆCLONE) rgcaik and rgcail are the random replication by female and male general combining ability and replication respectively ~ N [0, Diag (A2ˆREPxGCA)] rscaikl is the random replication by SCA interaction ~ NID (0, 2ˆREPxSCA) ijklm is the random error term ~ NID (0, 2ˆERROR) Yijklm = + Ri + incblkj(i) + gcak + gcal + scakl + rfamikl + ijklm [2-4] Yijklm is the measured trait of the mth seedling within the klth full-sib family in the jth incomplete block within the ith replication. is the seedling population mean Ri is the fixed effect of replication, i = 1,2,3,4 incblkj(i) is the random incomplete block ~ (0, Diag2 ) (ˆi incblk) gcak and gcal are the random female (k) and male (l) general combining ability respectively ~ N (0, A2ˆGCA) scakl is the random specific combining ability ~ NID (0, 2ˆSCA) rfamikl is the random replication by full-sib family ~ NID (0, 2ˆREPxFAM) ijklm is the random error term ~ NID (0, 2ˆERROR) The estimates of additive (AV ˆ ) and total genetic variance for clonal (CGV ˆ ) and seedling (SGV ˆ ) population were calculated by the Equa tions 2-5, 2-6 and 2-7 respectively. 2ˆ 4 ˆGCA AV [2-5] 2 2 2ˆ ˆ ˆ 2 ˆCLONE SCA GCA GCV [2-6] 2 2ˆ 4 ˆ 4 ˆSCA GCA GSV [2-7] Equations 2-8 and 2-9 were used to co mpute the estimates of the phenotypic variance for clonal (CPV ˆ ) and seedling (SPV ˆ ) population. 2 2 2 2 2 2ˆ ˆ ˆ 2 ˆ ˆ ˆ 2 ˆERROR REPxSCA REPxGCA CLONE SCA GCA PCV [2-8] 2 2 2 2ˆ ˆ ˆ ˆ 2 ˆERROR REPxFAM SCA GCA PSV [2-9]

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16 Individual tree-narrow-sense heritability (2h) and broad-sense heritability (2 H ) were calculate using the estimated variance components for the phenological and growth traits for each propagule type. Equations 2-10 and 2-11 were used for assessing clonal heritabilities. CP AV V h ˆ ˆ2 [2-10] C CP GV V H ˆ ˆ2 [2-11] Equation 2-12 and 2-13 were used fo r obtaining seedling heritabilities. SP AV V h ˆ ˆ2 [2-12] S SP GV V H ˆ ˆ2 [2-13] Standard errors for narrow and broad-se nse heritabilities were estimated using ASREML as a Taylor series approximation for the variance of a ratio (Gilmour 2002). Atlantic Coastal Plain ( ACC ), Florida ( FL ), and Lower Gulf ( LG ) were the loblolly pine provenances present in this study. Th e analysis of provenance effect was performed using ASREML (Gilmour 2002). The mean of the population was pa rtitioned into the provenance effect since provenanc es effects were included as fi xed variable in models [23] and [2-4]. Least square means for th e phenological and growth traits of each provenance were calculated adding the estima ted mean, the provenance effects and the average of the replication values. The effect s of the provenance and their standard errors were also computed us ing ASREML (Gilmour 2002).

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17 Genetic correlations among phenol ogical traits and growth rate were calculated for each propagule type and genetic component using Equation 2-14 (Falconer and Mackay 1996): 2 2covy x xy xyr [2-14] where xycovis the genetic component cova riance between two traits, and 2 x and 2 y are the product of the genetic component vari ance for traits x and y, respectively. Standard error for genetic correlations was es timated using ASREML (Gilmour 2002). Differences between propagule types for s hoot length and phenological traits were calculated using ASREML (Gilmour 2002). The propagule types were considered different when their F value was greater than94 6) 4 2 (05 0 F Path coefficient analysis (Wright 1968) was used in order to determine the relative contribution of D and ASGR to the AHI The method has been fully described (Kremer and Larson 1983; Kremer 1985; Bongarten 1986; Magnussen and Yeatman 1989; Rweyongez et al 2003). The following is a short summary of the method The data is standardized by dividing each trait by its mean. With the standardization each trait has a mean of 1 a nd makes it possible for the variances to be compared when the path coefficients are computed (Bongarten 1986; Rweyongeza et al 2003). Shoot elongation ( AHI ) also can be descri bed as the product of D and ASGR ) ( ) (ASRG D AHI [2-15] Applying a logarithmic transformation to equation 2-15 the resultant relationship is:

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18 ASRG D AHI log ) log( ) log( [2-16] In terms of variances ) cov( 22 2 2ASRG DARSG D AHI [2-17] As the correlation of D and ASRG is: ASRG D ASRG DASRG D r ) cov() ( replacing cov( D,ASRG ) by ) ( ASRG D ASRG Dr then equation 2-18 is obtained ) ( 2 2 22ASRG D ASRG D ASRG D AHIr [2-18] Replacing and dividing each term by 2 AHI in equation [2-17], eq uation [2-18] is obtained ) ( 2 2 22ASRG D ASRG D ASRG D AHIr p p p p p [2-19] where 2 AHIp is equal to 1 because it is the path coefficient of ) log( AHI to itself. Dp and ASRGp are the path coefficients for ) log( D and ARSGlog respectively to ) log( AHI. The relative contribution of D to AHI can be determined as ) (D AHI D Dr p c [2-20] where Dc is the degree of determination of D to AHI and ) ( ASRG Dr is the correlation coefficient between AHI and D. The relative contribution of ASGR to AHI can be calculated as ) (ASRG AHI ASRG ASRGr p c [2-21] where ASRGc is the degree of determination of ASGR to AHI and ) (ASRG AHIr is the correlation coefficient between AHI and ASGR. 1 ASRG Dc c [2-22]

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19 Flush Descriptors The flush descriptors, FLn, NSU, MSUL number of flushes of each shoot leader ( NF ), PFLn, AHIFLn and second-year total height ( TH2) traits were analyzed in ASREML (Gilmour et al. 2002). Analyses were run for each pr opagule type and site separately. A parental model was used to estimate the genetic variances com ponents and the linear model used for cuttings and seedlings were detailed in equations [2-3] and [2-4] respectively. NSU and MSUL were analyzed for each flush. The numbers of replications measured for shoot components were 2 for Site 1 and 3 for Site 2. Genetic parameter (AV ˆ ,CGV ˆ ,SGV ˆ ,cPV ˆ ,SPV ˆ ,2h and2 H ) were calculated according equations [2-5] to [2-13] respectively. St andard errors for narrow and broad-sense heritabilities were estimated using ASREML (Gilmour 2002). Provenance differences and genetic corre lations were computed to explain phenological traits. Differences between propagule types were also computed for shoot components and growth traits as for phenological tr aits using ASREML (Gilmour 2002). The propagule types were considered different when their F value was greater than 0 19) 2 2 (05 0F for Site 1 and 55 9) 3 2 (05 0 F for Site 2. Shoot components, PFLn, AHIFLn and TH2 traits were also analyzed across the two sites separately by propagule type. The mixed model is described in equation [2-23] for clones population and equation [2-24] for seed lings respectively. Different residual variances were allowed by site. Yijklmn =+ Si + Rij + incblkk(ij)+ gcal+ gcam+ scalm + clonen(lm)+ sgcail + sgcaim + sscailm+ sclonein(lm) + rgcaijl + rgcaijm + rscaijlm + ijklmn [2-23]

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20 Yijklmn is the measured trait of the nth clone within the lmth full-sib family in the kth incomplete block within the jth replication of the ith site. is the clonal population mean Si is the fixed effect of site i =1,2 Rij is the fixed effect of replication, i = 1,2 j = 1,2,3,4 incblkk(ij) is the random incomplete block ~ (0, Diag 2 ) (ˆi incblk) gcal and gcam are the random female ( l ) and male ( m ) general combining ability respectively ~N (0, A2ˆGCA) scalm is the random specific combining ability ~ NID (0, 2ˆSCA) clonen(lm) is the random clone within full-sib family ~ NID (0, 2ˆCLONE) sgcail and sgcaim are random site by replication by female and male general combining ability and replication respectively ~ NID (0, 2ˆSITExGCA) sscailm is the random site by SCA interaction ~ NID (0, 2ˆSCA) sclonen(lm) is the random site by clone within fu ll-sib family interaction ~ NID (0, 2ˆSITExCLONE) rgcaijl and rgcaijm are the random site by replication by female and male general combining ability and replication interaction respectively ~ N (0, A2ˆGCA) rscaijlm is the random site by replicat ion by SCA interaction ~ NID (0, 2ˆREPxSCA) ijklmn is the random error term ~ [0, Diag (2) (ˆiERROR)] Yijklmn =+ Si + Rij + incblkk(ij)+ gcal+ gcam+ scalm + sgcail + sgcaim + sscailm+ rfamijlm + ijklmn [2-24] Yijklmn is the measured trait of the nth seedling within the lmth full-sib family in the kth incomplete block within the jth replication and the ith site. is the clonal population mean Ti is the fixed effect of site i =1,2 Rij is the fixed effect of replication, i = 1,2 j = 1,2,3,4 incblkk(ij) is the random incomplete block ~ (0, Diag 2 ) (ˆi incblk) gcal and gcam are the random female ( l ) and male ( m ) general combining ability respectively ~NID (0, A2ˆGCA) scalm is the random specific combining ability ~NID (0, 2ˆSCA) sgcail and sgcaim are random site by female and male general combining ability respectively ~ NID (0, 2ˆSITExGCA) sscailm is the random site by SCA interaction ~ NID (0, 2ˆSITExSCA) rfamijlm is the random site by replication by full-sib family interaction ~ NID (0, 2ˆREPxFAM) ijklmn is the random error term ~ [0, Diag (2) (ˆiERROR)]

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21 From the across sites analyses type B correlations for each of the traits were calculated. A type B genetic correlation gives us an indica tion of how consistently the trait is expressed in two diffe rent environments (Yamada 1962). When the correlation is near 1 the trait-by-environment interaction is small and genetic entries rank the same in both environments. When the genetic co rrelation is low the genetic entries rank differently in the two environments. The formulae to calculate the type B correlation were the follow: 2 2 2 2 2 2 2 2 22 2 2SITExCLONE SITExSCA SITExGCA CLONE SCA GCA CLONE SCA GCA BCLONEr [2-25] CLONEBr is the type B genetic correlati on for clonal value across trials 2 2 2 SITExGCA GCA GCA BGCAr [2-26] GCABr is the type B genetic correlati on for parents across the two sites 2 2 2 2 2 22 2 2SITExSCA SITExGCA SCA GCA SCA GCA BFAMILYr [2-27] FAMILYBr is the type B genetic correlation for full-sib families across trials In order to estimated the de gree of determination of the AHI by the number of flushes ( NF) and the average flush length ( AvFLn) as well as the estimate the contribution of the MSUL and the NSU to each flush length FLn, a path coefficient analysis (Wright 1968) was computed for each case (Bongarten 1986; Rweyongeza et al 2003). The FLn of each flush is the result of the product of NSU and MSUL and AHI can be described as the product of NF and AvFLn. With logarithmic transformation those multiplicative relationships became additive. Following the steps described from

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22 equations [2-16] to [2-19] we obtain for FLn and AHIFLn equations [2-28] and [2-29] respectively ) ( 2 2 22NSU MSUL MSUL NSU MSUL NSU FLnr p p p p p [2-28] ) ( 2 2 22AvFLn NF AvFLn NF AvFLn NF AHIr p p p p pFLn [2-29] From [2-28] and [2-29] 2 FLnp and 2FLnAHIp are equal to 1 because they are the path coefficients of ) log( FLn and ) log(FLnAHI with themselves. NSUp and MSULp are the path coefficients for ) log( NSU and ) log( MSUL to ) log( FLn as well as NFp and AvFLnp are the path coefficients for ) log( NF and AvFLn log to ) log(FLnAHI respectively. The relative contribution of NSU and MSUL to FLn and NF and AvFLn to AHIFLn can be determined with the equation [2-30], [2 -31], [2-32] and [2-33] respectively ) ( NSU FLn NSU NSUr p c [2-30] ) ( MSUL FLn MSUL MSULr p c [2-31] ) ( NF AHI NF NFFLnr p c [2-30] ) ( AvFLn AHI AvFLn AvFLnFLnr p c [2-31] where NSUc and MSULc are the degree of determinations of NSU and MSUL to FLn and NFc and AvFLnc are the degree of de terminations of NF and AvFLn to AHIFLn. ) ( NSU FLnr ) ( MSUL FLnr ) ( NF AHIFLnr and ) ( AvFLn AHIFLnr are the correlation coefficients between FLn and NSU FLn and MSUL AHIFLn and NF and AHIFLn and AvFLn respectively Genetic correlations among shoot component s traits were calculated for each propagule type and genetic effect using e quation [2-14] (Falconer and Mackay 1996).

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23 Standard error for genetic correlations was estimated using ASREML (Gilmour 2002). The number of trees involved in each analysis is detailed in Table 2-2. Table 2-2. Number of trees involved in each of the analyses by site and propagule type. Site 1 Site 2 Flush descriptors by flush number Cuttings Seedlings Cuttings Seedlings FLn 1 1730 402 1678 423 2 1729 402 1674 421 3 1727 401 1666 416 4 1702 397 1635 404 5 1493 329 1471 337 6 732 132 746 133 7 134 18 130 21 PFL 1 1727 400 1657 419 2 1727 400 1655 418 3 1727 400 1651 415 4 1702 397 1623 404 5 1493 329 1464 337 6 732 132 746 133 7 134 18 129 21 NSU, MSUL Parastichy 1 1730 402 1674 423 pattern 2 1729 402 1670 421 3 1727 401 1662 416 4 1702 397 1631 404 5 1492 329 1469 337 6 730 131 745 133 7 134 17 130 21 NF 1727 400 1657 419 AHIFLn 1727 400 1657 419 TH2 1769 404 1680 426 Phenological traits 3352 731 2432 618

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24 CHAPTER 3 RESULTS AND DISCUSSION Phenological Traits Least Square Means for Phenological Traits by Provenance and Propagule Type Significant differences (p<0.05) between propagule types were found for all the phenological and growth traits (Appendix A). For Site 1 the average difference for initiation date for seedling and cutting was 4 days In contrast to Site 1, Site 2 seedling material had earlier cessation dates than cutting material. Cuttings provenances were significantly di fferent (p<0.05) for initiation, cessation and duration at Site 1 and for cessation at Site 2, but were not signi ficantly different for ASRG and AHI (Table 3-1). ACC provenance height growth initiation started growing latter than FL and LG which had the same least square mean initiation date. Although LG and FL started together for both propagule types, FL provenance cuttings grew later in the season while ACC and LG had stopped growing by a sim ilar date. There were no significant differences in cessation date for seedlings among provenances. Although there were significant differences in initia tion, cessation and duration for provenance for Site 1, no significant differences were obtained for AHI FL was the provenance with the longest growing season and ACC had the shortest growing periods for both propagule types. LG was the provenance with the smallest AHI, because of its lower ASRG FL and ACC presented similar initiation dates and ASRG In Site 2 again FL is the provenance which the latest cessation date. These results are in partial agreement with Jayawickrama et al (1998) on height growth patte rn of loblolly pine in S outhwest Georgia. They found

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25 significant differences among provenance for he ight growth cessati on but no significant differences for height growth initiation. For Jayawickrama et al (1998) Atlantic Coastal Plain, Lower Gulf and Florida provenan ce grew until day 241, 233 and 248 in 1993 and 244, 240 and 253 in 1994, respectively. Also th eir Florida material (Gulf Hammock) had the longest growing season and greatest hei ght. McCrady and Jokela (1996), in South Carolina, reported a mean bud-break Julian Date of 73 to 84 for their different families and planting spacings. Those dates are in a ccordance with the ones f ound in this report. Also the average shoot rate gr owth reported in this study fo r cuttings was in agreement with McCrady and Jokela (1996) of 0.58-0.65 cmday-1. The duration of the shoot growth in this study in North Ce ntral Florida (Table 3-1) is shorter than th e one reported by McCrady and Jokela (1996) (191 versus 201 days). Table 3-1. Least square means for secondyear phenological traits and annual height increments by provenances and propa gule type for 2004 growing season in Site 1 (North Central Florida) and Site 2 (Southwest Georgia). INITIATION (days) CESSATION (days) DURATION (days) ASRG (cm day-1) AHI (cm) C S C S C S C S C S Site 1 LG 79 84 248 263 170 180 0.56 0.67 108.9 121.3 FL 79 83 252* 266 174* 183* 0.65 0.72 128.7 131.2 ACC 84* 87* 247 261 165 175 0.65 0.72 121.0 125.8 Site 2 LG 269 255 FL 277* 257* ACC 263 248 Note: LG, FL and ACC are Lower Gulf, Florid a and Atlantic Coastal Plain provenances, respectively. C= cuttings; S= seedlings. Initiation and cessation are days after January 1 to complete 5 and 95% of total AHI. (*) indicates significant differences between the provenances (p<0.05) Provenances were also significantly differe nt for shoot growth pattern during the growing season. Least square means were calculated for each of the measurement days (Figure 3-1) for average cumulative apical he ight growth increment and apical height growth increment by propagule type and pr ovenance. Fewer significant points in

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26 seedlings than in cuttings are attributable to lower numbers of seedlings present in the study (Table 2-2). LG FL ACC Day of Year 2004 50100150200250300 Average Cummulative Height Increment (cm) 0 20 40 60 80 100 120 140 Day of Year 2004 50100150200250300Height growth increment (cm) 0 10 20 30 40 50 + CUTTINGS SEEDLINGS + + + + + + + + + + + + + + + Figure 3-1. Least square means for average cumulative apical height growth increment and apical height growth increment by provenance and propagul e type at Site 1 (North Central Florida). (+) indi cates significant differences between provenances (p<0.05). Seedlings and cuttings have a similar general growth pattern for height increment with two peaks, one later in the spring and the other in later summer. Even though no significant difference between provenances were found for the second half of the growing season for cumulative height increment, th e cutting curve shape shows how cumulative growth increment by provenance becomes dis tinct whereas for seedlings provenances differences of cumulative height increment at the end of the growing season are subtle.

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27 Peaks of height increment are larger in seed lings than in cuttings. It seems that the differences in height increment occurred in cu ttings during the second half of the growing season are responsible for the evident (but not significant) differences in cumulative height increment. Heritabilities values for cumulative height increment and height increment are shown in Table 3-2 and 3-3 by day of measure. Heritability Estimates Height Growth Increment Narrow sense heritability for incremental height growth was always greater for cuttings than for seedlings except for dates 141 and 268 (Table 3-2). Seedling values for broad sense heritability were more inconsiste nt than cutting values. Cuttings show a declining trend after day 68 except for day 141 which was smaller than expected. Narrow sense heritabilities also decrease d during the growing s eason after day 68 and cutting heritability values were more inconsistent than seedling values. Larger standard errors are associated with seedlings than with cuttings heritab ilities. After day 268 narrow and broad sense heritabilities for both cuttings and seedling become constant and almost zero. The decreasing and small values of heritabilities are attributable to growth cessation. There was little or no additive variance for day 68 ( h2 was 0.00 and 0.07 for seedlings and cuttings, respectively) but moderate non-additive variance for both propagule types ( H2 was 0.35 and 0.26 for seedlings and cuttings, respectively) for height increment, cumulative height increment and cumulative percentage height increment. The total genetic variance evaluated in H2 is primarily due to clonal variation; 22 GCA is a distant second while the SCA variance contribution is almost negligible (Table 3-2).

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28 These contributions are also consistent for cumulative height growth increment (Table 33) and average cumulative percent height growth (Table 3-4). Table 3-2. Incremental height growth: narrow ( h2) and broad-sense ( H2) heritabilities on measurement days during 2004 growing s eason by propagule type at Site 1 (North Central Florida). Seedlings Cuttings Day No.+ h2 H2 h2 H2 Clone/Vp* 2 GCA/Vp* SCA/Vp* 68 0.00 (0.00) 0.35 (0.16) 0.07 (0 .03) 0.26 (0.02) 0.218 0.035 0.011 88 0.22 (0.11) 0.26 (0.14) 0.25 (0 .08) 0.40 (0.03) 0.259 0.124 0.016 141 0.17 (0.08) 0.17 (0.08) 0.07 (0 .03) 0.11 (0.02) 0.074 0.033 0.002 173 0.15 (0.13) 0.41 (0.17) 0.21 (0 .06) 0.22 (0.03) 0.109 0.104 0.005 236 0.13 (0.09) 0.13 (0.09) 0.23 (0 .06) 0.22 (0.03) 0.103 0.113 0.000 268 0.14 (0.10) 0.20 (0.15) 0.09 (0 .04) 0.11 (0.02) 0.058 0.046 0.010 278 0.00 (0.00) 0.00 (0.00) 0.02 (0 .01) 0.01 (0.01) 0.000 0.008 0.006 299 0.00 (0.00) 0.12 (0.12) 0.01 (0 .01) 0.01 (0.02) 0.000 0.007 0.003 323 0.00 (0.00) 0.00 (0.00) 0.00 (0 .00) 0.02 (0.02) 0.021 0.000 0.003 + Day of the year 2004 when the height increment was recorded. ** Clone/Vp 2 GCA/Vp and SCA/Vp are the relative contribu tion of clonal, GCA and SCA variances to broad-sense heritability ( H2). Standard errors ar e given in parentheses. Cumulative and Cumulative Percen tage Height Growth Increment Cumulative broad sense heritability values (Table 3-3) were generally smaller for cuttings than for seedlings. The decreasi ng pattern during the gr owing season is also present for both narrow and broad-sense heritabi lities for all traits except height growth increment. After day 268 (end of the growing season) heritability values became constant. Non-additive variance seems to be la rger for seedlings than for cuttings, with larger standard errors associated with seedlings than cuttings For cumulative percentage of height grow th the decreasing pattern in both narrow and broad-sense heritability values started at day 88 and becoming close to zero after day 236.

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29 Table 3-3. Cumulative height growth: narrow ( h2) and broad-sense ( H2) heritabilities on measurement days during 2004 growing s eason by propagule type at Site 1 (North Central Florida). Seedlings Cuttings Day No.+ h2 H2 h2 H2 Clone/Vp* 2 GCA/Vp* SCA/Vp* 68 0.00 (0.00) 0.35 (0.16) 0.07 (0.03) 0.26 (0.02) 0.218 0.035 0.011 88 0.22 (0.11) 0.31 (014) 0.24 (0 .07) 0.41 (0.03) 0.274 0.120 0.018 141 0.18 (0.10) 0.28 (0.14) 0.09 (0.03) 0.14 (0.02) 0.096 0.043 0.000 173 0.22 (0.12) 0.31 (0.15) 0.14 (0.05) 0.17 (0.03) 0.101 0.070 0.002 236 0.14 (0.12) 0.24 (0.16) 0.19 (0.06) 0.19 (0.03) 0.087 0.095 0.004 268 0.21 (0.12) 0.23 (0.15) 0.20 (0.06) 0.20 (0.03) 0.087 0.099 0.008 278 0.19 (0.12) 0.22 (0.15) 0.20 (0.06) 0.19 (0.03) 0.083 0.100 0.009 299 0.17 (0.12) 0.21 (0.15) 0.20 (0.06) 0.19 (0.03) 0.082 0.102 0.010 323 0.11 (0.12) 0.23 (0.16) 0.20 (0.06) 0.20 (0.03) 0.084 0.102 0.009 + Day of the year 2004 when the height increment was recorded. Clone/Vp 2 GCA/Vp and SCA/Vp are the relative contributio n of clonal, GCA and SCA variances to broad-sense heritability ( H2). Standard errors are given in parentheses. Table 3-4. Cumulative percenta ge of height growth: narrow (h2) and broad-sense (H2) heritabilities on measurement days during the 2004 growing season by propagule type in Site 1 (N orth Central Florida). Seedlings Cuttings Day No. h2 H2 h2 H2 Clone/Vp* 2 GCA/Vp* SCA/Vp* 68 0.00 (0.00) 0.35 (0.17) 0.05 (0 .02) 0.14 (0.02) 0.115 0.026 0.003 88 0.33 (0.14) 0.43 (0.15) 0.18 (0 .06) 0.27 (0.03) 0.148 0.090 0.030 141 0.31 (0.14) 0.47 (0.17) 0.20 (0 .06) 0.21 (0.03) 0.105 0.100 0.003 173 0.20 (0.11) 0.24 (0.16) 0.15 (0 .05) 0.19 (0,03) 0.117 0.075 0.000 236 0.09 (0.09) 0.17 (0.16) 0.02 (0 .02) 0.08 (0.02) 0.046 0.012 0.017 268 0.01 (0.04) 0.01 (0.04) 0.00 (0 .00) 0.05 (0.02) 0.036 0.000 0.011 278 0.02 (0.05) 0.02 (0.05) 0.00 (0 .00) 0.03 (0.02) 0.025 0.000 0.007 299 0.00 (0.00) 0.00 (0.00) 0.00 (0 .00) 0.02 (0.02) 0.018 0.000 0.005 + Day of the year 2004 when the height increment was recorded. Clone/Vp 2 GCA/Vp and SCA/Vp are the relative contributio n of clonal, GCA and SCA variance to the broad-sense heritability ( H2). Standard errors ar e given in parentheses. Phenological Traits and AHI Little non-additive variance was present for cutting height growth initiation (Table 3-5). Height growth cessation had little geneti c variance in cuttings and seedlings at Site 1. In contrast, for Site 2 seedling height growth cessation was highly controlled by nonadditive variance ( h2 is 0.02; H2 is 0.58). More moderate values for narrow and broadsense heritabilities were present fo r cutting height growth cessation ( h2 is 0.29; H2 is

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30 0.39). This study also reports low narrow and broad-sense heritabilities for seedlings and cuttings for growing season duration. Cutti ng growing season duration seemed to be influenced by non-additive genetic variance. Narrow-sense heritabi lities for initiation, cessation and duration obtained in this study are smaller than those reported by Li and Adams (1993) in 15 year-old pole-size Douglas -fir. They estimated strong narrow-sense heritabilities for bud burst and bud set and low to moderate values for growing season duration ( h2 are 0.73, 0.81 and 0.17, respectively). ASGR was not influenced by nonadditive variance for cuttings. Seedling ASGR heritabilities are higher than cuttings heritabilities. Clonal variati on was the greatest contributor to the total genetic variance; 22GCA made a small contribution while SCA variance contribution was almost negligible (Table 3-5). Table 3-5. Individual narrow ( h2) and broad-sense ( H2) heritabilities for phenological traits and AHI by propagule type for the 2004 growing season in Site 1 (North Central Florida) and 2 (Southwest Georgia) Seedlings Cuttings Variable h2 H2 h2 H2 Clone/Vp 2 GCA/Vp SCA/Vp Site 1 Initiation 0.40 (0.13) 0.40 (0.13) 0.29 (0 .08) 0.39 (0.03) 0.228 0.143 0.018 Cessation 0.07 (0.07) 0.07 (0.07) 0.00 (0 .00) 0.07 (0.02) 0.058 0.000 0.011 AHI 0.11 (0.12) 0.23 (0.16) 0.20 (0 .06) 0.20 (0.03) 0.084 0.102 0.009 Duration 0.10 (0.07) 0.10 (0.07) 0.02 (0 .02) 0.08 (0.02) 0.060 0.008 0.007 ASGR 0.26 (0.14) 0.33 (0.16) 0.18 (0 .06) 0.19 (0.03) 0.090 0.093 0.009 Site 2 Cessation 0.02 (0.11) 0.58 (0.24) 0.22 (0 .07) 0.34 (0.03) 0.216 0.110 0.017 Clone/Vp 2 GCA/Vp and SCA/Vp are the relative contribution of clonal, GCA and SCA variances to broad-sense heritability ( H2). Standard errors are given in parentheses. Correlations Among Phenological Traits. Genetic correlations were not estimat ed for those components whose genetic variance was 0.

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31 Initiation-Duration Correlation Genetic correlations between initiation a nd duration at Site 1 were significantly strong and negative for both propagule types, which indicated that the material which initiated height growth later tended to have a shorter growing season and the material which had early height growth initiation tende d to grow longer (Table 3-6). Phenotypic and microsite initiation-durati on correlations were negatively low and significant. Also initiation-duration correlations for seedlings were in general lower than those for cuttings. GCA initiation-duration correlation was the st rongest negatively and significant correlation. Cessation-Duration Correlation Cessation-duration correlations were signifi cant and strongly positive. Phenotypic and environmental cessation-duration correlation s were positive and even larger than the genetic correlations. The positive correlati on between cessation and duration indicated that the material with the latest cessati on date will have the longest growing season. Phenotypic and environmental correlations between initiation and cessation were significant and low for both cuttings and s eedlings. The clonal initiation-cessation correlation was also low. The significant positive correlation between initiation and cessation implies that the material which star ted growing later also stopped growing later in the season and vice versa. InitiationAHI and Initiation-Cessation Correlations For Site 1 the standard errors associated with initiationAHI and cessationAHI genetic correlations were many times larger than the estimates whereas phenotypic and environmental initiationAHI and cessationAHI correlation were positive low and significant. Lower correlation values were es timated for cuttings than for seedlings and

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32 cessationAHI correlation were lower than initiationAHI correlations. Positive correlation for initiationAHI meant that material which in itiated later in the growing season had larger height increments. At Site 2, standard errors associated with genetic cessationAHI correlation for seedlings were larger than the estimate also microsite standard errors were larger than the estimat ed correlations for both propagule types. The phenotypic and environmental correlations were low and positive, clonal and total genetic correlation for cessationAHI at Site 2 were moderate but with high standard errors. Positive correlation for cessationAHI indicates that material which grew longer in the season had the largest AHI InitiationASRG Correlations Phenotypic, environmental and gene tic correlations for initiationASRG were positive, moderate-to-low and significant for cuttings, except for the SCA correlations where the standard error which was four times larger than the estimate (Table 3-6). Seedling genetic correlations also had high standard errors whereas the phenotypic correlations were positive, significant and moderate. Seedling microsite initiationASRG correlation was also moderate, significant and negative. Positive correlations indicate that materials with later initiation dates w ould have higher growth rate. The negative correlation for microsite initiationASGR meant that a particular microsite promoting early height growth initiation tende d to promote higher growth rate.

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33 Table 3-6. Genetic, phenotypic and envir onmental (microsite) correlations between phenological traits and annual height increment ( AHI) by propagule type for 2004 growing season in Site 1 (North Central Florida) and 2 (Southwest Georgia). Cuttings Seedlings Variables C AHI D ASGR C AHI D ASGR Site 1 rGCA -0.49 (0.50) 0.25 (0.21) -0.91 (0.08) 0.49 (0.17) -0.16 (0.33) 0.31 (0.44) -0.71 (0.18) 0.38 (0.23) rSCA 0.66 (0.46) 0.36 (0.73) *** 0.18 (0.82) *** *** *** *** rClone 0.29 (0.11) 0.06 (0.09) -0.41 (0.10) 0.21 (0.09) --------rGenetic 0.14 (0.10) 0.16 (0.11) -0.60 (0.08) 0.35 (0.10) -0.11 (0.23) 0.19 (0.26) -0.48 (0.20) 0.38 (0.23) rPhenotypic 0.11 (0.02) 0.29 (0.03) -0.29 (0.02) 0.38 (0.03) 0.13 (0.04) 0.89 (0.13) -0.25 (0.05) 0.42 (0.04) I rMicrosite 0.12 (0.02) 0.35 (0.02) -0.21 (0.02) 0.40 (0.02) 0.18 (0.04) 0.37 (0.04) -0.23 (0.04) -0.43 (0.03) rGCA 0.56 (0.31) 0.84 (0.27) 0.26 (0.37) -0.23 (0.41) 0.81 (0.12) -0.45 (0.31) rSCA 0.32 (0.77) 0.97 (0.22) 0.12 (0.86) *** *** *** rClone -0.11 (0.17) 0.77 (0.05) -0.35 (0.14) ------rGenetic 0.11 (0.13) 0.73 (0.05) -0.14 (0.13) -0.23 (0.41) 0.81 (0.12) -0.31 (0.23) rPhenotypic 0.09 (0.02) 0.93 (0.00) -0.24 (0.02) 0.16 (0.04) 0.92 (0.01) -0.23 (0.04) C rMicrosite 0.08 (0.02) 0.95 (0.00) -0.26 (0.02) 0.18 (0.05) 0.93 (0.01) -0.22 (0.04) Site 2 rGCA *** *** rSCA *** 0.36 (0.24) rClone 0.53 (0.24) --rGenetic 0.47 (0.20) 0.36 (0.24) C rPhenotypic 0.12 (0.05) 0.09 (0.04) rMicrosite 0.06 (0.04) 0.06 (0.04) Note: I = Initiation; C =Cessation; D =Duration; ASRG =average shoot growth rate. ***Correlation could not estimated because 2 SCA was 0. (---) was not included in the model. Standard errors are given in parentheses.

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34 CessationASGR Correlations Genetic cessationASGR correlations were associated with large standard errors for both propagule types. Phenotypic and envir onmental correlations for both cuttings and seedlings were negative significant and low, which means that the material which stopped growing early tends to have a highe r growth rate. Phenological and growth correlation results were in agreement with those reported by Li and Adam (1993) for Douglas-fir. They found positive correlati on between bud set and growth. Also they reported negative moderate (-0.30 0.24) a nd negative low (-0.07 0.28) correlations between bud burst and bud set w ith duration for their first ye ar of analyses. For their second year of analysis the dur ation-bud set correlation became a strong correlation (-0.87 0.07). Ekberg et al. (1994) working with Norway spruce ( Picea abies ) seedlings did not find any strong correlati on between total height or shoot elongation with any of the bud phenological traits or shoot elongation period. They also could not strongly associate the shoot elongation pe riod with bud burst and bud set. Path Analysis Table 3-7 presents the phenotypic and ge netic path coefficients, correlation coefficients and degrees of de termination for the second-year AHI from duration and average shoot growth rate for both propagul e types. For both propagule types average shoot growth rate was the principal contributor to AHI The genetic and phenotypic degree of determination of AHI by ASRG was almost 1 for cuttings and 0.86 and 0.72 for seedlings. Both phenotypic and genetic correlations between AHI and ASRG were positive strong and significant, indicating that material which has higher average shoot rate growth has larger AHI

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35 Table 3-7. Values of phenotypic and genetic path coefficients, correlation coefficients and degrees of determination for annual height increment ( AHI ) by growth duration ( D ) and average shoot growth rate ( ASRG ) by propagule type for Site 1 (North Central Florida). Path coefficients components Correlation Coefficient Prop. type AHI Components (Log) Path Coeff. 2 AHIp 2 Dp 2 ASRGp *yz z yr p p 2 ) ( ) ( ASRG AHI D AHIr r ) ( ASRG Dr Degree of determination ASRG Dc c Phenotypic Cuttings D -0.053 -0.016 ASRG 1.004 0.086 1.133 -0.215 0.907 -0.344 0.965 Seedlings D 0.036 0.134 ASRG 0.999 0.139 1.113 -0.253 0.814 -0.322 0.859 Genetic Cuttings D -0.098 -0.033 ASRG 0.986 0.112 1.177 -0.303 0.891 -0.418 0.967 Seedlings D -0.134 -0.045 ASRG 0.998 0.111 1.198 -0.310 0.656 -0.426 0.718 Note: Path coefficient formula: ) ( 2 2 22ASRG D ASRG D ASRG D AHIr p p p p p *) (2ASRG D ASRG Dr p p. ) ( ASRG AHI D Dr p c ; ) ( ASRG AHI ASRG ASRGr p c Numbers in bold are significant (p<0.05) These results were in agreement with those obtained by Magnussen and Yeatman (1989) in jack pine, who found that rate of shoot extension was a better predictor for within-family shoot length than the duration of the shoot elongation. Some reports for loblolly pine were in concordance with our results like: Perry et al. (1966), who through regression analyses reported that growth rate accounted fo r approximately 60 percent of the height growth variation while durati on growth rate accounted for 30 percent. McCrady and Jokela (1996) attributed the differences in AHI between families to the height growth rate, and Boyer (1970) suggested that the flush growth variation in loblolly is attributable to growth rate and not to length of the growth season.

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36 Duration and average growth rate were moderately and negatively correlated meaning that materials with shorter growing period had high growth rates. Phenotypic and genetic correlations were significantly different except for the seedling genetic correlation. Flush Descriptors Heritability Estimates Significant differences (p<0.05) between propagule types were found for all the flush descriptors ( FLn PFL NSU and MSUL ), NF and growth traits ( AHIFLn and TH2) (Appendix A). On Site 1 additive variance was the primar ily genetic variation associated with seedlings and cuttings for most of the flushes for FLn NSU MSUL and PFL (Table 3-8) whereas non-additive genetic variance was the pr incipal genetic variation associated with NF and TH2 for seedlings. Additive genetic varian ce was the main genetic variation for TH2 cuttings and AHIFLn for cuttings and seedlings. Th ere was non-additive variance for seedlings except for FLn flush 1, PFL flush 1 and 4, NSU flush 3 and MSUL flush 2. On Site 2, as well, additive variance was the primarily genetic variation associated with seedlings for mo st of the flushes by FLn NSU MSUL and PFL (Table 3-9) whereas non-additive genetic variance was the princi pal genetic variation associated with NF TH2 and AHIFLn. There was less non-additive variance associated with NF TH2 and AHIFLn in cuttings than in seedlings. Seedlings had no non-additive variance except for flush 2 for FLn, PFL and NSU. Non-additive genetic variance was more freque nt in with cuttings for Site 2 than for Site 1 (Table 3-8 and Table 3-9). On Site 2 for several flushes and different traits, H2 was at least twice as large as h2.

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37 At both sites total genetic variance for cut tings was due primarily to clonal genetic variance. Two times GCA variance was the next highest contributor to the total genetic variance while SCA variance was generally small. Seedling heritabilities were slightly larger and more inconsistent among the flushes than cuttings and also had larger standard erro rs than cuttings, which is attributable to the small seedling population (Table 2-2). Site 2 cutting heritabilitie s in general were slightly larger than in Site 1. There was no clear pattern of decreasing/increasing heritabilities values with the increasing/decreasing flush numb er for either propagule type or site. Heritabilities for flushes 6 and 7 are probably not reliable due to the small number of trees that produced 6 or 7 flushes. NF AHIFLn and TH2 narrow and broad-sense heritabi lities values were larger for Site 2 than for Site 1 for both cuttin gs and seedlings (Table 3-8 and 3-9). For both Site 1 and 2, additive genetic variance was the primary genetic variance for seedlings and cuttings across si te for most of the flushes for FLn PFL NSU and MSUL. Across sites cuttings had little to no nonadditive variance; for a few flushes nonadditive variance was twice as large as the additive variance. Non-additive genetic vari ance was associated with NF and seedlings TH2. Additive genetic variance was the main genetic variance for AHIFLn and cutting TH2. Across-site NF AHIFLn and TH2 cutting heritability values were two to five times larger than seedlings heritabilities values.

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38 Table 3-8. Site 1 (North Centra l Florida): individual-tree narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propagule type for the 2004 growing season. Seedlings Cuttings Variable by flush # h2 H2 h2 H2 PV GCA 2 PV SCA PV Clone 1 0.00 (0.00) 0.21 (0.26) 0.07 (0.03) 0.22 (0.04) 0.03 0.00 0.19 2 0.14 (0.10) 0.14 (0.10) 0.16 (0.06) 0.22 (0.04) 0.08 0.01 0.12 3 0.23 (0.12) 0.23 (0.12) 0.19 (0.06) 0.22 (0.04) 0.10 0.00 0.12 4 0.25 (0.15) 0.27 (0.22) 0.16 (0.05) 0.17 (0.04) 0.08 0.00 0.09 5 0.00 (0.00) 0.00 (0.00) 0.21 (0.07) 0.20 (0.05) 0.11 0.00 0.09 6 0.03 (0.00) 0.03 (0.00) 0.10 (0.08) 0.12 (0.09) 0.05 0.00 0.07 FLn 7 ----0.00 (0.00) 0.00 (0.00) 0.00 0.00 0.00 1 0.12 (0.13) 0.33 (0.23) 0.17 (0.06) 0.27 (0.04) 0.08 0.00 0.18 2 0.08 (0.08) 0.08 (0.08) 0.08 (0.04) 0.13 (0.04) 0.04 0.02 0.08 3 0.19 (0.10) 0.19 (0.10) 0.09 (0.04) 0.16 (0.04) 0.04 0.01 0.11 4 0.09 (0.13) 0.45 (0.30) 0.10 (0.04) 0.13 (0.04) 0.05 0.00 0.09 5 0.07 (0.10) 0.07 (0.10) 0.13 (0.06) 0.15 (0.05) 0.07 0.03 0.05 6 0.73 (0.42) 0.73 (0.42) 0.14 (0.09) 0.21 (0.09) 0.07 0.00 0.14 PFL 7 ----0.00 (0.00) 0.00 (0.00) 0.00 0.00 0.00 1 0.00 (0.00) 0.00 (0.00) 0.12 (0.04) 0.20 (0.04) 0.06 0.00 0.14 2 0.13 (0.09) 0.13 (0.09) 0.13 (0.05) 0.21 (0.04) 0.06 0.01 0.14 3 0.12 (0.11) 0.19 (0.25) 0.22 (0.07) 0.33 (0.04) 0.11 0.00 0.21 4 0.13 (0.10) 0.13 (0.10) 0.17 (0.06) 0.17 (0.04) 0.08 0.01 0.07 5 0.00 (0.00) 0.00 (0.00) 0.15 (0.06) 0.22 (0.04) 0.07 0.00 0.15 6 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.12 (0.09) 0.00 0.00 0.12 NSU 7 ---0.00 (0.00) 0.18 (0.34) 0.00 0.18 0.00 1 0.10 (0.09) 0.10 (0.09) 0.11 (0.05) 0.16 (0.04) 0.06 0.00 0.10 2 0.08 (0.10) 0.11 (0.20) 0.10 (0.06) 0.14 (0.04) 0.05 0.01 0.08 3 0.42 (0.15) 0.42 (0.15) 0.29 (0.08) 0.32 (0.04) 0.14 0.00 0.17 4 0.28 (0.13) 0.28 (0.13) 0.21 (0.06) 0.28 (0.04) 0.11 0.01 0.16 5 0.27 (0.16) 0.27 (0.16) 0.22 (0.08) 0.30 (0.05) 0.11 0.03 0.16 6 0.52 (0.42) 0.52 (0.42) 0.21 (0.08) 0.21 (0.08) 0.11 0.00 0.10 MSUL 7 ---0.00 (0.00) 0.00 (0.00) 0.00 0.00 0.00 NF 0.06 (0.12) 0.24 (0.22) 0.14 (0.07) 0.32 (0.04) 0.07 0.05 0.20 AvFL 0.00 (0.00) 0.00 (0.00) 0.18 (0.08) 0.31 (0.06) 0.09 0.00 0.22 AHIFLn 0.00 (0.00) 0.00 (0.29) 0.26 (0.08) 0.20 (0.05) 0.13 0.00 0.06 TH2 0.01 (0.08) 0.11 (0.26) 0.21 (0.07) 0.22 (0.04) 0.11 0.01 0.109 Note: FLn= flush length; PFL= flush contribution to annual he ight increment in percent; NSU =number of stem units; MSUL =mean stem unit length; NF = number of flushes; AvFL = average flush length; AHIFLn=annual height increment as summation of the flush length; TH2=second year total height. Standard errors are given in parentheses.

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39 Table 3-9. Site 2 (Southwest Georgia): individual tree narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propagule type for 2004 growing season. Seedlings Cuttings Variable by flush # h2 H2 h2 H2 PV GCA 2 PV SCA PV Clone 1 0.10 (0.09) 0.10 (0.09) 0.13 (0 .05) 0.30 (0.04) 0.06 0.01 0.23 2 0.16 (0.14) 0.50 (0.26) 0.20 (0 .06) 0.42 (0.04) 0.10 0.00 0.32 3 0.00 (0.00) 0.00 (0.00) 0.16 (0 .06) 0.26 (0.04) 0.08 0.00 0.18 4 0.16 (0.11) 0.16 (0.11) 0.19 (0.06) 0.28 0.04) 0.10 0.00 0.18 5 0.00 (0.00) 0.23 (0.35) 0.21 (0 .07) 0.28 (0.05) 0.10 0.00 0.17 6 0.10 (0.63) 1.00 (1.21) 0.20 (0 .09) 0.33 (0.09) 0.10 0.00 0.23 FLn 7 ----0.00 (0.00) 0.18 (13.9) 0.00 0.00 0.15 1 0.14 (0.11) 0.14 (0.11) 0.13 (0 .05) 0.30 (0.04) 0.06 0.01 0.23 2 0.19 (0.15) 0.42 (0.25) 0.22 (0 .06) 0.40 (0.04) 0.11 0.00 0.29 3 0.00 (0.00) 0.00 (0.00) 0.10 (0 .05) 0.20 (0.04) 0.05 0.02 0.14 4 0.12 (0.10) 0.12 (0.10) 0.16 (0 .05) 0.28 (0.04) 0.08 0.00 0.20 5 0.06 (0.12) 0.06 (0.12) 0.16 (0 .06) 0.25 (0.05) 0.08 0.00 0.17 6 0.28 (0.47) 0.28 (0.47) 0.11 (0 .08) 0.31 (0.09) 0.06 0.00 0.25 PFL 7 ----0.00 (0.00) 0.59 (27.1) 0.00 0.00 0.59 1 0.09 (0.09) 0.09 (0.09) 0.14 (0.05) 0.32 (0.04) 0.07 0.00 0.24 2 0.16 (0.15) 0.50 (0.26) 0.17 (0.06) 0.39 (0.04) 0.09 0.00 0.30 3 0.03 (0.07) 0.03 (0.07) 0.18 (0.06) 0.26 (0.04) 0.09 0.01 0.16 4 0.08 (0.08) 0.08 (0.08) 0.09 (0.04) 0.21 (0.04) 0.04 0.02 0.15 5 0.08 (0.12) 0.08 (0.12) 0.11 (0.06) 0.28 (0.05) 0.05 0.02 0.21 6 0.00 (0.00) 0.75 (1.29) 0.03 (0.05) 0.21 (0.10) 0.02 0.00 0.19 NSU 7 ----0.00 (0.00) 0.33 (0.33) 0.00 0.08 0.24 1 0.13 (0.11) 0.13 (0.11) 0.18 (0.06) 0.23 (0.04) 0.09 0.00 0.14 2 0.03 (0.08) 0.03 (0.08) 0.20 (0.07) 0.34 (0.04) 0.10 0.02 0.22 3 0.28 (0.13) 0.28 (0.13) 0.29 (0.08) 0.39 (0.04) 0.14 0.00 0.25 4 0.05 (0.09) 0.05 (0.09) 0.26 (0.08) 0.40 (0.04) 0.13 0.00 0.27 5 0.36 (0.18) 0.36 (0.18) 0.22 (0.07) 0.38 (0.04) 0.11 0.01 0.26 6 0.00 (0.00) 1.00 (1.44) 0.16 (0.09) 0.46 (0.07) 0.08 0.00 0.38 MSUL 7 ----0.00 (0.00) 0.00 (0.00) 0.00 0.00 0.00 NF 0.20 (0.15) 0.46 (0.25) 0.29 (0.08) 0.41 (0.04) 0.14 0.01 0.26 AvFL 0.09 (0.09) 0.09 (0.09) 0.10 (0.05) 0.22 (0.05) 0.05 0.00 0.17 AHIFLn 0.07 (0.12) 0.44 (0.27) 0.20 (0.07) 0.33 (0.04) 0.10 0.02 0.21 TH2 0.03 (0.11) 0.53 (0.27) 0.31 (0.09) 0.41 (0.04) 0.15 0.01 0.25 Note: FLn= flush length; PFL= flush contribution to annual he ight increment in percent; NSU =number of stem units; MSUL =mean stem unit length; NF = number of flushes; AvFL = average flush length; AHIFLn=annual height increment as summation of the flush length; TH2=second year total height. Standard errors are given in parentheses.

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40 Narrow and broad-sense heritabilities values were in general lower for across-site analysis than for single-site analyses. Individual-tree narrow and broad-sense heritabilities for cuttings are sl ightly larger than narrow and broad-sense heritabilities for seedlings. These study findings are not in complete agreement with other studies of shoot growth components. Heritability values for second-year total height are in concordance with Paul et al. (1997) from two different factorial loblolly pine clonal tests. The h2values from their two factorial tests were 0.08 and 0.26. H2 values ranged from 0.12 to 0.25 in their factorial tests. In general, cutting heritability estimates in this study for second-year total height were larger than those estimates for the components ( FLn NSU and MSUL ) and almost equal for NF Heritabilities estimates for NSU and MSUL indicated that they are both under similar genetic control. Several other st udies reported greater heritability values than the ones found in this study, with values ranging from 0.1 to nearly 1.0 for growth and growth component traits in loblolly pine and other conifers (Kremer and Larson 1983, Bongarten 1986, Li et al 1991; Li et al 1992, Smith et al. 1993b, Kaya 1993, Rweyongeza et al. 2003). Type B Correlation The stability of families and parents across site were compared for seedlings and cuttings (Table 3-11). Also clonal stabil ity across site was analyzed for cuttings.

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41 Table 3-10. Across site individual narrow ( h2) and broad-sense ( H2) heritabilities for growth and shoot components by propa gule type for 2004 growing season for Site 1(North Central Florida) a nd Site 2 (Southwest Georgia). Seedlings Cuttings Variable by flush # h2 H2 h2 H2 PV GCA 2 PV SCA PV Clone 1 0.03 (0.04) 0.10 (0.07) 0.06 (0.03) 0.12 (0.02) 0.03 0.00 0.09 2 0.08 (0.03) 0.08 (0.03) 0.11 (0.04) 0.14 (0.02) 0.06 0.00 0.08 3 0.05 (0.04) 0.05 (0.04) 0.12 (0.05) 0.13 (0.03) 0.06 0.00 0.07 4 0.10 (0.06) 0.11 (0.08) 0.10 (0.04) 0.14 (0.03) 0.05 0.00 0.09 5 0.00 (0.00) 0.04 (0.09) 0.09 (0.06) 0.17 (0.03) 0.05 0.01 0.11 6 0.00 (0.00) 0.00 (0.00) 0.11 (0.05) 0.06 (0.03) 0.06 0.00 0.00 FLn 7 ----0.18 (0.12) 0.32 (0.12) 0.09 0.00 0.23 1 0.24 (0.10) 0.28 (0.10) 0.17 (0.06) 0.21 (0.03) 0.08 0.01 0.11 2 0.15 (0.06) 0.15 (0.06) 0.11 (0.04) 0.16 (0.03) 0.06 0.00 0.11 3 0.02 (0.04) 0.02 (0.04) 0.06 (0.03) 0.07 (0.02) 0.03 0.01 0.03 4 0.10 (0.07) 0.10 (0.09) 0.06 (0.03) 0.11 (0.03) 0.03 0.00 0.08 5 0.03 (0.07) 0.14 (0.10) 0.05 (0.05) 0.13 (0.03) 0.03 0.03 0.08 6 0.06 (0.02) 0.00 (0.00) 0.11 (0.05) 0.06 (0.03) 0.06 0.00 0.00 PFL 7 ----0.17 (0.11) 0.16 (0.12) 0.08 0.00 0.08 1 0.08 (0.07) 0.27 (0.11) 0.11 (0 .04) 0.17 (0.03) 0.05 0.00 0.12 2 0.05 (0.02) 0.05 (0.02) 0.08 (0 .03) 0.13 (0.02) 0.04 0.00 0.09 3 0.07 (0.03) 0.07 (0.03) 0.15 (0 .02) 0.23 (0.02) 0.08 0.00 0.15 4 0.08 (0.05) 0.08 (0.05) 0.13 (0 .05) 0.19 (0.02) 0.06 0.02 0.11 5 0.05 (0.04) 0.05 (0.04) 0.14 (0 .05) 0.26 (0.03) 0.07 0.00 0.19 6 0.01 (0.14) 0.24 (0.29) 0.05 (0 .03) 0.08 (0.04) 0.02 0.00 0.06 NSU 7 ----0.00 (0.00) 0.10 (0.19) 0.00 0.04 0.06 1 0.16 (0.07) 0.27 (0.09) 0.13 (0 .05) 0.17 (0.03) 0.06 0.00 0.10 2 0.07 (0.07) 0.14 (0.09) 0.15 (0 .05) 0.14 (0.03) 0.08 0.00 0.06 3 0.28 (0.09) 0.28 (0.09) 0.26 (0 .07) 0.26 (0.04) 0.13 0.00 0.14 4 0.14 (0.07) 0.14 (0.07) 0.14 (0 .06) 0.19 (0.03) 0.07 0.00 0.12 5 0.18 (0.07) 0.18 (0.07) 0.17 (0 .07) 0.22 (0.04) 0.09 0.02 0.12 6 0.00 (0.00) 0.00 (0.00) 0.15 (0 .06) 0.08 (0.03) 0.07 0.01 0.00 MSUL 7 ----0.21 (0.15) 0.24 (0.14) 0.11 0.01 0.12 NF 0.05 (0.08) 0.11 (0.12) 0.17 (0 .07) 0.26 (0.03) 0.09 0.02 0.16 AvFL 0.00 (0.01) 0.00 (0.01) 0.05 (0 .03) 0.10 (0.02) 0.03 0.00 0.07 AHIFLn 0.04 (0.05) 0.04 (0.05) 0.21 (0 .07) 0.22 (0.03) 0.10 0.01 0.11 TH2 0.04 (0.05) 0.11 (0.12) 0.22 (0 .07) 0.24 (0.04) 0.11 0.01 0.11 Note: FLn= flush length; PFL= flush contribution to annual he ight increment in percent; NSU =number of stem units; MSUL =mean stem unit length; NF = number of flushes; AvFL = average flush length; AHIFLn=annual height increment as summation of the flush length; TH2=second year total height. Standard errors are given in parentheses.

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42 Table 3-11. Type B correlations for grow th and shoot components by propagule type for 2004 growing season between Site 1 (Nor th Central Florida) and Site 2 (Southwest Georgia). Seedlings Cuttings Variable by flush # ParentsBr FamilyBr CloneBr ParentsBr FamilyBr FLn 1 0.84 (0.88) 0.92 (0.46) 0.68 (0.12) 0.59 (0.20) 0.57 (0.19) 2 1.00 (0.00) 1.00 (0.00) 0.80 (0.08) 0.69 (0.16) 0.61 (0.15) 3 0.83 (0.52) 0.83 (0.52) 0.65 (0.12) 0.79 (0.14) 0.78 (0.13) 4 0.65 (0.31) 0.66 (0.30) 0.72 (0.13) 0.63 (0.17) 0.59 (0.17) 5 0.00 (0.00) 0.28 (0.54) 0.69 (0.12) 0.455 (0.21) 0.52 (0.18) 6 0.00 (0.00) 0.00 (0.00) 0.24 (0.11) 0.72 (0.25) 0.72 (0.25) 7 ----0.98 (0.13) 0.95 (0.44) 0.95 (0.44) PFL 1 0.94 (0.15) 0.94 (0.14) 0.68 (0.08) 0.93 (0.09) 0.91 (0.08) 2 1.00 (0.00) 0.98 (0.22) 0.64 (0.10) 0.70 (0.17) 0.60 (0.16) 3 0.34 (0.68) 0.34 (0.68) 0.43 (0.15) 0.66 (0.21) 0.74 (0.16) 4 0.60 (0.32) 0.60 (0.31) 0.51 (0.13) 0.485 (0.23) 0.42 (0.21) 5 0.27 (0.56) 0.52 (0.35) 0.59 (0.13) 0.37 (0.26) 0.55 (0.17) 6 0.00 (0.00) 0.005 (0.14) 0.23 (0.11) 0.72 (0.26) 0.72 (0.26) 7 ----1.00 (0.00) 1.00 (0.00) 1.00 (0.00) NSU 1 0.94 (0.44) 0.97 (0.22) 0.78 (0.11) 0.82 (0.13) 0.80 (0.13) 2 1.00 (0.00) 1.00 (0.00) 0.81 (0.07) 0.67 (0.18) 0.58 (0.16) 3 1.00 (0.00) 1.00 (0.00) 0.94 (0.09) 0.95 (0.01) 0.95 (0.01) 4 0.78 (0.38) 0.78 (0.38) 0.97 (0.03) 0.92 (0.08) 0.94 (0.07) 5 0.70 (0.67) 0.53 (0.52) 0.96 (0.04) 0.86 (0.12) 0.86 (0.12) 6 1.00 (0.00) 1.00 (0.00) 0.49 (0.27) 1.00 (0.00) 1.00 (0.00) 7 ----0.20 (0.40) 0.23 (0.00) 1.00 (0.00) MSUL 1 0.99 (0.00) 0.99 (0.00) 0.82 (0.12) 0.77 (0.14) 0.77 (0.13) 2 0.47 (0.38) 0.58 (0.30) 0.58 (0.10) 1.00 (0.00) 0.86 (0.11) 3 0.89 (0.14) 0.89 (0.14) 0.73 (0.07) 0.89 (0.07) 0.89 (0.07) 4 0.78 (0.25) 0.78 (0.25) 0.60 (0.08) 0.64 (0.16) 0.61 (0.15) 5 1.00 (0.00) 1.00 (0.00) 0.67 (0.08) 0.76 (0.13) 0.79 (0.11) 6 0.00 (0.00) 0.00 (0.00) 0.25 (0.08) 0.93 (0.18) 0.93 (0.17) 7 ----0.99 (0.18) 0.97 (0.39) 0.97 (0.34) NF 0.36 (0.49) 0.32 (0.29) 0.72 (0.07) 0.76 (0.14) 0.73 (0.11) AvFL 1.00 (0.00) 1.00 (0.00) 0.82 (0.08) 0.59 (0.21) 0.55 (0.20) AHIFLn 0.89 (1.33) 0.40 (0.55) 0.81 (0.09) 0.88 (0.08) 0.89 (0.08) TH2 1.00 (0.00) 0.48 (0.39) 0.74 (0.08) 0.88 (0.10) 0.85 (0.09) Note: FLn= flush length; PFL= flush contribution to annual height increment in decimal equivalents; NSU =number of stem units; MSUL =mean stem unit length; NF = number of flushes; AvFL = average flush length; AHIFLn=annual height increment as summation of the flush length; TH2=second year total height. Standard errors are given in parentheses.

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43 Growth and Shoot Components Cutting NF AHIFLn and TH2 showed consistent clonal, parental and family ranking across site with type B correlations that ra nged from 0.72 to 0.89 whereas seedling family and parental rankings across site were quite inconsistent for NF and for family AHIFLn and TH2 were inconsistent. AvFL family and parental ranking across site was very consistent for seedlings, but not for cuttings. Only clonal ranking was very consistent for cuttings. Flush Descriptors The type B correlations reported in this study vary greatly from flush to flush, trait to trait, and with propagule type. While FLn PFL NSU and MSUL seedling flush 1 and 2 exhibited high strong parent a nd family correlations, cuttings flush 1 and 2 parental and family correlations were moderate, except for MSUL flush 2 for which cutting parental and family correlation are higher than seedlings. Seedling NSU and MSUL exhibited consistent family and parental (ParentsBr=0.70 to 1.00; FamilyBr=0.78 to 1.00) rankings across both sites for most of the flushes except family rankings for MSUL flush 2 and NSU flush 5 which were incons istent with correlated values of 0.47 to 0.58 for either parental and family type B correlations (Table 3-11). Parent type B correlations for seedling FLn were high and ranged from 0.83 to 1.00 for the first three flushes while the fourth flush had a moderated correla tion and the remained flushes where low (0.28) to uncorrelated. PFL showed similar behavior to FLn but just for the first two flushes. Flush 3 was low for both parental and family type B correlation. The other PFL flushes had moderate to nil family and parental correlations.

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44 The majority of the type B correlations fo r cuttings along the flus hes and traits were moderate to high ranging from 0.51 to 1. There were a small number of correlations which were lower than 0.50 and most of th em were clonal type B correlations. Few flushes, flush 6 for example, exhibited consis tent family and parent al ranking across sites and inconsistent clonal ranking across sites for all the traits analyzed. Seedling family type B correlations estimated in this study for loblolly pine second growing season were lower than those reported by Smith et al. (1993b), who reported 0.89 to 0.94 family type B genetic correlati ons for cycle length, number of cycles and NSU per cycle. The moderate correlations (0. 64 to 0.72) for total he ight, total number of NSU and free growth stem unit length were mo re in accord to some of the correlations obtained in this study. Li et al. (1992) reported genetic correlations across their treatments (fertilized and irri gated against nonfe rtilized and non-irri gated) ranging from 0.61 to 0.80. Path Analyses Annual Height Increment with Number of Flushes and Average Flush Length For sites 1 and 2 phenotypic and genetic path coefficients, correlation coefficients and degree of determination for second year AHIFLn by NF and AvFL for both propagule types are show in Table 3-12. For both sites and propagule type average flush length was the pr incipal contributor to AHIFLn. At Site 1, the phenotypic degrees of determination of AHIFLn by AvFL were 0.80 for cuttings and 0.71 for seedlings. Seed ling genetic path analysis could not be assessed due to the very low variance of th e genetic components. Both phenotypic and genetic correla tions between AHIFLn and AvFL were larger than AHIFLn and NF correlations. AHIFLnAvFL correlations were significant positive and moderate to strong

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45 (0.63 to 0.86), indicating that material wh ich has higher average flush length has larger AHIFLn. AHIFLnNF phenotypic correlations were posit ive moderate and significant for both cuttings and seedlings whereas cutting genetic correlation was low and nonsignificant. Cuttings and seedlings NF AvFL phenotypic correlations were negative low (-0.13 to -0.25) but significant, meaning that materials with fewer flushes had longer flushes. Cutting genetic NF AvFL correlation was much highe r (-0.59) than cutting phenotypic correlations. On the other hand Site 2 cuttings and seedlings NF AvFL phenotypic correlation were st rongly negative and signif icant (-0.78 and -0.74). Although the seedling genetic correlation was al so strong negative and significant, Site 2 cuttings genetic NF AvFL correlation was low positive and significant. Site 2 cuttings and seedlings AHIFLnAvFL phenotypic correlation as well as Site 1 were moderate and positive. Genetic AHIFLnAvFL correlations were also moderate and positive but only the cutting correlation was significant. AHIFLn.NF correlation were low (0.003 to 0.26) and nonsignificant for both cuttings and seed lings and for phenotypic and genetic correlations; only the cutting genetic correlation was negative. The relatively larger phenotypic degree of determination for AvFL to AHIFLn at Site 2 indicated a strong contribution of AvFL to AHIFLn and a weak role for NF in that environment. Cutting genetic path analysis was not estimated correctly 2FLnAHIp (the path estimated of AHIFLn with itself has to be 1 and in th is case the number obtained was 4.34). Gmez-Crdenas et al. (1998) found similar average number of flushes (41) in their two year study on P. patula but in the second year their annual he ight increment was quite low (drought) due to shorter flushes. For Gmez-Crdenas et al. (1998) average

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46 flush length and NSU were the most important components in the shoot elongation pattern of P. patula Table 3-12. Phenotypic and gene tic values for path coefficien ts components, correlations coefficients, and degree of determinations for annual height increment AHIFLn by number of flushes ( NF ) and average flush length ( AvFL ) by propagule type for Site 1 (North Central Florida) and Site 2 (Southwest Georgia). Path coeff. components Correlation coefficient Prop. type Flush Components (Log) Path coeff. 2FLnAHIp 2 NFp 2 AvFLp yz z yr p p 2* ) ( ) ( AvFL AHI NF AHIFLn FLnr r r(NF, AvFL) Degree of determination AvFL NFc c Site 1 Phenotypic Cuttings NF 0.46 0.31 AvFL 1.01 0.47 0.86 -0.32 0.86 -0.25 0.79 Seedlings NF 0.56 0.37 AvFL 1.05 0.44 0.77 -0.16 0.81 -0.13 0.71 Genetic Cuttings NF 0.26 0.26 AvFL 1.11 1.02 1.61 -1.52 0.63 -0.59 0.80 Seedlings NF ----AvFL --------------Site 2 Phenotypic Cuttings NF 0.09 0.10 AvFL 0.94 1.26 2.09 -2.41 0.64 -0.74 0.92 Seedlings NF 0.003 0.003 AvFL 0.99 1.52 2.53 -3.04 0.64 -0.78 1.01 Genetic Cuttings NF -0.09 -0.11 AvFL 4.34 1.35 2.56 0.43 0.69 0.12 1.10 Seedlings NF 0.26 0.33 AvFL 1.01 166 2.04 -2.69 0.47 -0.73 0.67 Note: Path coefficient formula: ) ( 2 2 22AvFL NF AvFL NF AvFL NF AHIr p p p p pFLn *) (2AvFL NF AvFL NFr p p. ) ( NF AHI NF NFFLnr p c ; ) ( AvFL AHI AvFL AvFLFLnr p c (---) Could not estimated because at least one of the variances was 0 Numbers in bold are significant (p<0.05).

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47 Flush Length with Number of Stem Units and Mean Stem Unit Length. For site 1 and 2 phenotypic and genetic path coefficients, correlation coefficients and degree of determination for second year height FLn by NSU and MSUL for both propagule types are show in Tabl e 3-13, 3-14, 3-15 and 3-16. At both sites in the phenotypic anal ysis and for both propagule types NSU was by far the principal contributor to FLn for the first and second flush with values of 1 for seedlings and cuttings in Site 2 and with values of 0.72-0. 75 for flush 2 for both cuttings and seedlings in Site 1 (Table 3-13 and 3-14). From flush 4 onward, NSU and MSUL contribute in almost th e same proportion to the FLn In Site 1 for the last flushes evaluated in seedlings (5 and 6) the contribution of MSUL to FLn was slightly superior to NSU (Table 3-13). The phenotypic corre lations between MSUL and NSU at Site 2 (Table 3-14) were low to moderate negative and significant (0.19 to -0.54) for cuttings and seedlings, indicating that material with shorter MSUL had a larger number of NSU The lowest correlations were for flushes 4 and 5 for both propagule types. FLn NSU correlations were positive moderate to high and significant (0.49 to 0.93), indicating that material with longer flushes had greater NSU The results indicate that FLn NSU correlations decreased in value fr om flush 1 to 7 and FLn MSUL correlations increase in value from flush 1 to 7. FLn MSUL correlations were low and negative and not significant for the first two flushes in cuttings and seedlings, except for seedling flush 2 where the correlation was significant.

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48 Table 3-13. Site 1 (North Central Florida): phenotypic values of path coefficients and path components, correlations coeffici ents and degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type. Path coeff. components* Correlation coefficient Prop. type Flush Components (Log) Path coeff. 2 FLnp 2 NSUp 2 MSULp yz z yr p p 2* r(FLn, NSU) r(FLn,MSUL) r(MSUL,NSU) Degree of determination MSUL NSUc c Cuttings Flush NSU 0.88 1.07 1 MSUL 0.95 1.48 0.41 -0.94 -0.07 -0.60 -0.04 NSU 0.88 0.72 2 MSUL 0.99 0.67 0.23 0.085 0.57 0.11 0.28 NSU 0.67 0.60 3 MSUL 0.97 0.79 0.61 -0.43 0.53 -0.31 0.41 NSU 0.70 0.58 4 MSUL 0.99 0.69 0.55 -0.24 0.59 -0.20 0.44 NSU 0.73 0.59 5 MSUL 0.997 0.64 0.49 -0.13 0.62 -0.12 0.43 NSU 0.67 0.45 6 MSUL 0.98 0.45 0.55 -0.02 0.74 -0.02 0.55 NSU 0.64 0.56 7 MSUL 0.99 0.76 0.66 -0.44 0.58 -0.31 0.47 Seedlings Flush NSU 0.85 1.03 1 MSUL 0.94 1.46 0.47 -0.99 -0.04 -0.60 -0.03 NSU 0.88 0.75 2 MSUL 1.00 0.72 0.26 0.02 0.55 0.02 0.28 NSU 0.61 0.53 3 MSUL 0.97 0.76 0.71 -0.50 0.55 -0.34 0.46 NSU 0.71 0.58 4 MSUL 1.08 0.68 0.56 -0.16 0.65 -0.13 0.48 NSU 0.60 0.40 5 MSUL 1.04 0.46 0.68 -0.10 0.76 -0.09 0.63 NSU 0.18 0.11 6 MSUL 0.93 0.365 0.66 -0.09 0.78 -0.09 0.63 Note: Path coefficient formula: ) ( 2 2 22NSU MSUL MSUL NSU MSUL NSU FLnr p p p p p *) (2NSU MSUL MSUL NSUr p p. ) ( NSU FLn NSU NSUr p c ; ) ( MSUL FLn MSUL MSULr p c Numbers in bold are significant (p<0.05).

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49 Table 3-14. Site 2 (Southwest Georgia): phenotypic values of path coefficients and path components, correlations coefficients and degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type. Path coeff. components Correlation coefficient Prop. type Flush Components (Log) Path coeff. 2 FLnp 2 NSUp 2 MSULp yz z yr p p 2* r(FLn, NSU) r(FLn,MSUL) r(MSUL,NSU) Degree of determination MSUL NSUc c Cuttings Flush 1 NSU 0.87 1.03 MSUL 0.98 1.38 0.34 -0.74 -0.05 -0.54 -0.03 2 NSU 0.93 1.02 MSUL 1.00 1.21 0.17 -0.38 -0.04 -0.42 -0.02 3 NSU 0.70 0.74 MSUL 0.98 1.11 0.63 -0.76 0.33 -0.45 0.26 4 NSU 0.67 0.54 MSUL 1.00 0.65 0.58 -0.23 0.61 -0.19 0.47 5 NSU 0.67 0.63 MSUL 1.00 0.85 0.62 -0.47 0.49 -0.33 0.38 6 NSU 0.53 0.52 MSUL 1.03 0.96 0.95 -0.88 0.52 -0.46 0.51 7 NSU 0.49 0.44 MSUL 1.00 0.84 0.99 -0.83 0.56 -0.46 0.56 Seedlings Flush 1 NSU 0.85 1.01 MSUL 0.99 1.29 0.25 -0.55 -0.02 -0.48 -0.01 2 NSU 0.86 1.06 MSUL 1.01 1.30 0.17 -0.46 -0.14 -0.49 -0.06 3 NSU 0.57 0.75 MSUL 1.00 1.02 0.51 -0.53 0.35 -0.37 0.25 4 NSU 0.70 0.49 MSUL 1.00 0.64 0.65 -0.28 0.63 -0.22 0.51 5 NSU 0.62 0.55 MSUL 1.00 0.72 0.62 -0.33 0.57 -0.25 0.45 6 NSU 0.64 0.56 MSUL 0.69 0.69 0.76 -0.75 0.61 -0.52 0.53 Note: Path coefficient formula: ) ( 2 2 22NSU MSUL MSUL NSU MSUL NSU FLnr p p p p p *) (2NSU MSUL MSUL NSUr p p. ) ( NSU FLn NSU NSUr p c ;) ( MSUL FLn MSUL MSULr p c Numbers in bold are significant (p<0.05). The negative correlations between FLn MSUL indicated that flushes with short MSUL had longer flushes. This is in concert with flushes 1 and 2 where the flush length was determined principally by NSU At Site 2 FLn MSUL correlation were no higher

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50 than 0.63. Site 1 phenotypic correlations followed the general pattern indicated for Site 2 but with some particularities. MSUL NSU correlations were in general lower but for flush 2 in both propagule type MSUL NSU correlations were positive low and significant and the contribution of NSU to second flush FLn was lower than for Site 2. FLn MSUL correlations for flush 2 were mode rate positive and significant (0.55 and 0.57) for both seedlings and cuttings. FLn MSUL phenotypic correlations for seedling flushes 5 and 6 and for cutting flush 6 were large (0.74 to 0.78) while their MSUL NSU correlation were low and nonsigni ficant; signifying the increasing contribution of MSUL to the FLn for those flushes. Seedling phenotypic flush 7 path analysis at both sites could not be estimated (Table 2-2). NSU was reported to be the main contributor to total height by several authors like Allen and Scarbrough (1970) in P. palustris Kremer (1985) in P. pinaster Guyon (1986) in P. nigra Kremer and Lascoux (1988) in P. pinaster Magnussen and Yeatman (1989) in P. banksiana Fady (1990) in Abies cephalonica Smith et al. (1993b) in slash pine, Gmez-Crdenas (1998) in P. patula, and Raweyongeza et al (2003) in white spruce. A mixed support for NSU and MSUL as primary contributors to flush length was reported by Kremer and Larson (1983) in jack pine, B ongarten (1986) in blue spruce and Douglas fir, and Kaya (1993) in Douglas fir MSUL NSU negative phenotypic and genetic corre lations were reported in several shoot components studies like Kremer a nd Larson (1983), Kremer (1985), Bongarten (1986), Kremer and Lascoux (1988), Ma gnussen and Yeatman (1989), Fady (1990), Kaya (1993) Smith et al. (1993b) and Gmez-Crdenas (1998) whereas Raweyongeza et al (2003) reported genetic, phenotypic and e nvironmental as very low but positive

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51 correlations between MSUL and NSU Guyon (1986) in P. nigra obtained just one positive non significant MSUL-NSU correlation in the 6 years analyzed. Genetic path analyses by flush for FLn as a product of MSUL and NSU could not be estimated for all the flushes at both sites due to the low variances for some of the traits (Table 3-15 and 3-16). Cutting genetic path analyses for Site 2 followed the general characteristics described for the phenotypic path analyses for cutting for flush 1 and 2 in which NSU were the principal contributors for the FLn but after flush 3 MSUL became equal to or more important than NSU as a determinate of flush length. MSUL degree of determination values ranged from 0.50 to 0.90. Seedlings in Site 2 had the same genetic pattern as cutting but MSUL reached only one extreme value (0.99 in flush 3). Seedling genetic path for flush 5 analysis could not be estimated because at least one of the component variances was almost 0. At Site 1 the cutting genetic path analysis had similar values to the phenotypic path analyses, even the low positive MSUL NSU correlation for flush 2. Seedling genetic path analyses could not be assessed for flushes 1, 2 and 6 because the variance of at least of one of the components was almost 0. For flushes 3, 4 and 5 where the genetic path analyses could be estimated, MSUL was by far the main contributor to FLn with a degree of determination ranged from 0.74 to 1.38. MSUL became more important in its contribution to FLn in the genetic analyses than in the phenotypic to the point that it becam e the primary contributor for many flushes at both sites for cuttings and seedling.

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52 Table 3-15. Site 1 (North Central Florida): ge netic values for path coefficients and path components, correlation coefficients a nd degrees of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem unit ( NSU ) by propagule type. Path coeff. components* Correlation coefficient Prop. type Flush Components (Log) Path coeff. 2 FLnp 2 NSUp 2 MSULp yz z yr p p 2* r(FLn, NSU) r(FLn,MSUL) r(MSUL,NSU) Degree of determination MSUL NSUc c Cuttings Flush NSU 0.76 0.90 1 MSUL 1.03 1.41 0.47 -0.85 0.07 -0.52 -0.05 NSU 0.88 0.73 2 MSUL 0.98 0.70 0.21 0.07 0.55 0.10 0.26 NSU 0.52 0.58 3 MSUL 1.02 1.22 1.08 -1.29 0.41 -0.56 0.55 NSU 0.54 0.51 4 MSUL 1.01 0.96 0.97 -0.92 0.52 -0.48 0.58 NSU 0.62 0.55 5 MSUL 1.03 0.77 0.70 -0.45 0.58 -0.30 0.52 NSU 0.55 0.33 6 MSUL 1.03 0.36 0.74 -0.07 0.80 -0.07 0.64 NSU ----7 MSUL --------------Seedlings Flush NSU ----1 MSUL --------------NSU ----2 MSUL --------------NSU -0.43 -0.37 3 MSUL 0.89 0.67 2.55 -2.34 0.87 -0.82 1.38 NSU 0.31 0.16 4 MSUL 0.55 0.26 0.48 -0.19 0.84 -0.21 0.74 NSU -0.30 -0.14 5 MSUL 0.96 0.18 1.59 -0.81 0.94 -0.66 1.16 NSU ----6 MSUL --------------Note: Path coefficient formula: ) ( 2 2 22NSU MSUL MSUL NSU MSUL NSU FLnr p p p p p *) (2NSU MSUL MSUL NSUr p p. ) ( NSU FLn NSU NSUr p c ; ) ( MSUL FLn MSUL MSULr p c (---) Could not estimated because at least one of the variances was 0 Numbers in bold are significant (p<0.05).

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53 Table 3-16. Site 2 (Southwest Georgia): genetic values for path coefficients and path components, correlation coefficients a nd degree of determination for flush length ( FLn ) as the product of mean stem unit length ( MSUL ) and number of stem units ( NSU ) by propagule type. Path coeff. components Correlation coefficient Prop. type Flush Components (Log) Path coeff. 2 FLnp 2 NSUp 2 MSULp yz z yr p p 2* r(FLn, NSU) r(FLn,MSUL) r(MSUL,NSU) Degree of determination MSUL NSUc c Cuttings Flush 1 NSU 0.92 1.13 MSUL 0.99 1.51 0.24 -0.76 -0.28 -0.63 -0.14 2 NSU 0.94 1.09 MSUL 0.99 1.34 0.16 -0.51 -0.25 -0.55 -0.10 3 NSU 0.51 0.57 MSUL 0.95 1.26 1.12 -1.43 0.40 -0.60 0.42 4 NSU 0.40 0.27 MSUL 1.02 0.46 0.92 -0.36 0.76 -0.28 0.73 5 NSU 0.50 0.50 MSUL 0.99 0.98 0.98 -0.96 0.50 -0.49 0.50 6 NSU 0.12 0.08 MSUL 0.99 0.53 1.36 -0.90 0.77 -0.53 0.90 7 NSU 0.57 0.45 MSUL 1.26 0.62 0.68 -0.04 0.65 -0.03 0.56 Seedlings Flush 1 NSU 0.93 1.30 MSUL 1.06 1.96 0.34 -1.25 -0.47 -0.76 -0.27 2 NSU 0.97 1.18 MSUL 0.99 1.48 0.13 -0.62 -0.51 -0.71 -0.18 3 NSU 0.01 0.01 MSUL 0.98 1.34 2.31 -2.67 0.65 -0.76 0.99 4 NSU 0.82 0.43 MSUL 1.01 0.27 0.43 0.31 0.89 0.46 0.57 5 NSU ----MSUL --------------6 NSU 0.56 0.29 MSUL 0.79 0.27 0.40 0.12 0.82 0.18 0.52 Note: Path coefficient formula: ) ( 2 2 22NSU MSUL MSUL NSU MSUL NSU FLnr p p p p p *) (2NSU MSUL MSUL NSUr p p. ) (NSU FLn NSU NSUr p c ; ) (MSUL FLn MSUL MSULr p c (---) Could not estimated because at least one of the variance was 0 Numbers in bold are significant (p<0.05). Seedling results have to be viewed with some caution due to the small seedling sample size. Therefore, these results are in agreement with those reported by Bongarten (1986), who concluded that th e degree of contribution of MSUL and NSU to FLn depended, among other factors, on the type of th e data considered (phenotypic, genetic or

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54 environmental). His results within Douglas-f ir and blue spruce provenances were that MSUL and NSU contributed equally to flush length phenotypic variation. For genetic variation MSUL was the primarily component for FLn in blue spruce while NSU was for environmental. On the other hand Rweyongeza et al (2003) reported that the NSU degree of determination was larger than MSUL under genetic, phenotypic and environmental analyses. Bridgwater (1990) reported that some loblolly pine families might show superior height increment due to greater number of stem units while other families depend more on the greater elongati on of the stem units. Also Kaya (1993) reported for Douglas-fir seedlings that MSUL explained nearly tw o-third of the free growth in an inland population while NSU explained coastal population free growth. Bailey and Feret (1982) working with loblolly pine and hybrids from P. rigida x taeda result were in agreement to those of this study where MSUL was more important for free growth flush length than NSU and NSU was the dominating factor for fixed growth. Cannell (1978) also reported that MSUL tended to be a larger component free growth (summer flushes) than for the first flush. Least Square Means for Provenance for FLn, PFL, NSU and MSUL Significant differences (p<0.05) between propagule type were found for all the morphological and growth traits ( FLn NSU MSUL NF and AHIFL) (Table A-3 in Appendix A). FL was the only provenance which demons trated significant differences for NF for both propagule types at Site 1. Although, all provenances were signif icantly different for NF at Site 2, LG provenance had the highest NF The Georgia site had higher AHIFL values for all the provenances and propagule types than Site 1. FL cuttings were significantly different for AHIFL at Sites 1 and 2 (Figure 3-2).

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55 Number of flushes 0 1 2 3 4 5 6 7 CUTT SEED PROVENANCE LGFLACCAnnual Height Increment (cm) 0 50 100 150 200 PROVENANCE LGFLACC SITE 2 SITE 1+ + + + Figure 3-2. Least square means for number of flushes ( NF ) and annual height increment as a summation of flush length ( AHIFL) for the 2004 growing season by propagule type at Site 1 (North Cent ral Florida) and Site 2 (Southwest Georgia). (+) indicates significant differences among provenances (p<0.05). Few flushes were coincidently significan tly different for provenances for both cuttings and seedlings for the same trait. Figures 3-3 and 3-4 describe graphically the results from the path analyses for flush length as a product of MSUL and NSU After flush 3 FLn had the tendency for MSUL to be a major contributor while NSU is the major importance. Site 2 seedlings had by fa r the largest values of FLn and NSU for flush 1 than cuttings (Figure 3-3 and 3-4). At both sites seedlings and cuttings had di fferent patterns for all of the traits analyzed except for MSUL at Site 2. Seedli ngs trend to have highe r values for all the traits from 3 and on while cuttings pr esent lower values after flush 3.

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56 Flush length (cm) 10 15 20 25 30 35 40 Flush length (cm) 10 20 30 40 50 60 LG FL ACC Flush number 012345678PFL 5 10 15 20 25 30 PFL 5 10 15 20 25 30 35 40 Flush number 012345678 SITE 1 SITE 2 SITE 1 SITE 2 CUTTINGS SEEDLINGS + + + + + + + + + + + + + + + + + + Figure 3-3. Least square means for flush length ( FLn ) and flush length contribution (PFL) by propagule type at Site 1 (N orth Central Florida) and Site 2 (Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic Coastal Plain provenances, respectively. (+) indicates significant differences between the provenances (p<0.05).

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57 MSUL (mm) 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 Flush number 012345678MSUL (mm) 0.5 1.0 1.5 2.0 2.5 3.0 Flush number 01234567 NSU 50 100 150 200 250 300 NSU 80 100 120 140 160 180 200 220 240 LG FL ACC SITE 1 + + + + ++ + + + + + + + + + + + + + + + + + CUTTINGS SEEDLINGS SITE 2 SITE 1 SITE 2 + Figure 3-4. Least square means for number of stem units (NSU) and mean stem unit length (MSUL) by propagule type at Site 1 (North Central Florida) and Site 2 (Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic Coastal Plain provenances, respectively. (+) indicates significant differences between the provenances (p<0.05).

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58 Provenance demonstrated different shoot elongation patterns. The FL provenance had higher growth at the beginni ng of the growing season while ACC and LG growth was slightly higher than FL seed source after the second flush. Length of the early flushes is what conferred a significant advantage for FL cutting over the ot her seed sources. LG provenance had the lowest values for NSU and the largest values of MSUL at both sites, suggesting that for this provenance MSUL was the most important contributor to flush length. There were no significant di fferences for provenances for flush 1 for any of the morphological traits analyzed except MSUL at Site 2. Values for flush 1 were very similar for the all provenances for all traits. Phyllostatic Patterns Phyllostatic patterns demonstrated little genetic variance. Narrow and broad-sense heritability for single site and across-site analyses were extremely low (Appendix C). Similarly, Kremer et al (1989) di d not find genetic variability among P. pinaster, P. banksiana and P. nigra Arn. ssp. nigrican populations or families for phyllostatic traits. Fibonacci series (3:5:8:13…) were present fo r 82.5 % of the trees at Site 1 and for 87.9 % of the trees at Site 2. The second mo st common series was the principal bijugate (4:6:10…) with 12.0% at in Si te 1 and 8.3 % at Site 2. First accessory of the monojugate series (4:7:11…) occurred at just 5.5 and 3.2 % at Site 1 and 2, respectively. The principal trijugate series (3:6:9:15…) were pres ent in 0.6 % of the trees at Site 2 and 0% at Site 1 (just 2 trees). At Site 2 one “foxtail” tree had th e tetrajugate series (4,8,12…). The phyllostatic pattern survey for propagule type separately gave similar results as the general, except one for the seedli ng population at Site 1 (Table 3-17).

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59 Table 3-17. Frequency of phyllo static series by propagule type in Site 1 (North Central Florida) and 2 (Southwest Georgia) Site 1 Site 2 Pyllostatic series Seedlings (%) Cuttings (%) Seedlings (%) Cuttings (%) Monojugate pattern Fibonacci 65.1 86.1 81.0 89.3 First accessory 22.0 9.7 15.1 6.9 Multijugate patterns Bijugy 12.9 4.2 2.8 3.2 Trijugy 0.0 0.0 1.1 0.5 These frequencies were comparable to the proportions obta ined by Kremer and Roussel (1982); Kremer et al (1989), Zagrska-Marek ( 1985) and Fady (1990) in P. pinaster, P. banksiana, P. nigra Arn. ssp. nigricans, Abies balsamea, and A. cephalonica, respectively

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60 CHAPTER 4 CONCLUSIONS Rooted cuttings differed from seedlings fo r all phenological and morphological traits that were analyzed in this study. This indi cates that regardless of the fact that both propagule types were from the same genetic ma terial the apparent differences in plant architecture and physiological age between th em results in differe nt morphological and phenological behavior. Phenological traits The results of this study indicated that the average growth rate per day was the most important variable in determining second-year annual height increment. The contribution of growing season duration to second-year annual height increment was negligible. Although significant differences were found am ong propagule types a nd seed sources for timing of initiation and cessation these traits were not important contributors to annual height increment. Because average shoot growth rate and growi ng season duration were low negatively and significantly correlated, growing season duration is a trait that has to be considered because at the same growth rate a longer growing season can result in a difference in height increment. A longer growing season may also adversely affect FL material in cooler environment by increasing frost risks. The narrow and broad-sense heritability es timates for the different dates for height growth increment during the growing seas on were moderate and decreased from initiation date to cessation date, becoming c onstant and almost zero for both propagule types after day 268, increment decrease.

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61 Morphological characters Average flush length was the principal c ontributor to total annual height while number of flushes had a minor contributio n. In our results the most important contribution of number of flushes to tota l annual height was at Site 2 for seedling material being responsible for 30% of the annual height increment. NF and AvFL were negatively strongly to moderately and significantly correlated. These results indicate that selecting genetic material for height increm ent would increase average flush length with minor changes in number of flushes. NSU was by far the most important phenotypic trait for the length of the three first flushes, and its contribution decreased in su bsequent flushes with an increase in the MSUL contribution to flush lengt h until reaching to a 1:1 re lationship. The genetic contribution of MSUL to flush length was relatively larger than the phenotypic contribution becoming more important than NSU after flush 3, especially for seedlings. MSUL and NSU were negatively moderately an d significantly correlated. The NSU and MSUL flush length correlations varied greatly depending on the flush and the relationship of NSU and MSUL to flush length. Despite MSUL and NSU being negatively correlated a nd under low genetic control, both were important determinants of flush lengths and flush length is an important determinant of annual height increment. Thus, both are indirectly important for the maximization of annual height increment. Se lection of individuals with high values of NSU and MSUL would improve annual height grow th but comparing heritabilities choosing for height growth direct ly would be more efficient.

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62 Provenances demonstrated differe nt shoot elongation patterns. FL provenance had the highest growth at the beginning of the growing season while ACC and LG growth was slightly greater than FL seed source after the second fl ush. Length of early flushes appeared to confer a significant advantage for FL cutting over the other seed sources. Phyllostatic patterns had low genetic va riability with extremely low narrow and broad-sense heritabilities.

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63 APPENDIX A DIFFERENCES BETWEEN PROPAGULE TYPES

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64 Table A-1. Significance leve ls (p-values) between propa gule types for annual height increment and phenological traits at Site 1 (North Central Florida) and Site 2 (Southwest Georgia). Variable Significant level between propagule type Site 1 Initiation <0.000001 Cessation <0.0000001 Duration <0.0000001 ASGR <0.00001 AHI <0.00001 Site 2 Cessation <0.0000001 AHI <0.000001 ASGR=average shoot growth rate; AHI=annual height increment. Table A-2. Significance levels (p-values) between propagule types for height increment, average cumulative height increment and average percentage cumulative increment at Site 1 (North Central Fl orida) and Site 2 (Southwest Georgia). Variable Height increment Average cumulative height increment Average percentage cumulative height increment Site 1 Day 68 <0.001 <0.001 <0.001 88 <0.001 <0.001 <0.001 141 <0.0001 <0.00001 <0.00001 173 <0.0001 <0.00001 <0.00001 236 <0.00001 <0.00001 <0.0000001 268 <0.001 <0.00001 <0.000000001 278 <0.001 <0.00001 <0.0000000001 299 <0.1 <0.00001 <0.000000001 323 <0.01 <0.00001 Site 2 Day 256 <0.00001 <0.00001 <0.0001 266 <0.0001 <0.0001 <0.0001 273 <0.001 <0.01 <0.000001 294 <0.001 <0.01 <0.00001 321 <0.001 <0.001 <0.00001 349 <0.001 <0.001 <0.00001

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65 Table A-3. Significance levels (p-values) between propagule types for growth and shoot components at Site 1 (North Central Flor ida) and Site 2 (Southwest Georgia). Variable by flush N Site 1 Site 2 FLn 1 <0.001 <0.0001 2 <0.01 <0.00001 3 <0.01 <0.000001 4 <0.001 <0.00001 5 <0.001 <0.00001 6 <0.01 <0.00001 PFL 1 <0.001 <0.0001 2 <0.01 <0.0001 3 <0.001 <0.000001 4 <0.001 <0.00001 5 <0.001 <0.00001 6 <0.01 <0.00001 NSU 1 <0.01 <0.0001 2 <0.01 <0.0001 3 <0.001 <0.00001 4 <0.001 <0.00001 5 <0.001 <0.00001 6 <0.01 <0.000001 MSUL 1 <0.001 <0.00001 2 <0.001 <0.000001 3 <0.01 <0.00001 4 <0.001 <0.00001 5 <0.001 <0.00001 6 <0.001 <0.00001 NF <0.001 <0.000001 AvFL <0.001 <0.00001 AHIFLn <0.001 <0.000001 TH2 <0.001 <0.000001 Note: FLn =flush length; PFL =flush contribution to a nnual height increment in percentage; NSU =number of stem units; MSUL =mean stem unit length; NF = number of flushes; AvFL = average flush length; AHIFLn=annual height increment as summation of the flush length; TH2=second year total height.

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66 APPENDIX B SECOND-YEAR PHENOTYPIC, GE NETIC AND ENVIRONMENTAL CORRELATIONS BETWEEN FLUSH LENGTHS ( FLN ), NUMBER OF STEM UNITS ( NSU ) AND MEAN STEM UNIT LENGTH ( MSUL ) BY FLUSH

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67 Table B-1. Site 1 (North Central Florida): cu ttings genetic, phenotypic and environmental (microsite) correlations between flush length ( FLn ) by flush for 2004 growing season. FLn-FLn correlations Flush 1 2 3 4 5 6 2 rGCA 0.63 (0.19) rSCA --rClone(fam) 0.51 (0.15) rGenetic 0.52 (0.11) rPhenotypic 0.40 (0.02) rMicrosite 0.37 (0.03) 3 rGCA 0.25 (0.26) 0.50 (0.20) rSCA ---0.03 rClone(fam) 0.07 (0.16) 0.88 (0.20) rGenetic 0.12 (0.13) 0.70 (0.12) rPhenotypic 0.13 (0.03) 0.20 (0.03) rMicrosite 0.14 (0.04) 0.05 (0.04) 4 rGCA 0.10 (0.28) 0.17 (0.26) 0.93 (0.05) rSCA ------rClone(fam) -0.06 (0.19) 0.44 (0.20) 0.37 (0.17) rGenetic -0.02 (0.15) 0.31 (0.15) 0.61 (0.10) rPhenotypic 0.17 (0.03) 0.12 (0.03) 0.43 (0.02) rMicrosite 0.21 (0.04) 0.04 (0.04) 0.38 (0.03) 5 rGCA -0.12 (0.29) 0.15 (0.27) 0. 81 (0.11) 0.83 (0.10) rSCA ----------rClone(fam) -0.17 (0.20) -0.15 (0.20) 0.15 (0.19) 0.68 (0.16) rGenetic -0.15 (0.15) -0.02 (0.15) 0.45 (0.13) 0.75 (0.10) rPhenotypic 0.06 (0.03) -0.13 (0.04) 0. 28 (0.03) 0.48 (0.02) rMicrosite 0.12 (0.04) -0.15 (0.04) 0. 24 (0.04) 0.42 (0.03) 6 rGCA -0.84 (0.24) -0.61 (0.24) 0.57 (0 .25) 0.62 (0.28) 1.00 (0.09) rSCA ----------rClone(fam) -0.47 (0.31) -0.56 (0.28) 0.21 (0 .30) 0.90 (0.43) 0.83 (0.48) rGenetic -0.55 (0.23) -0.55 (0.19) 0.35 (0 .20) 0.79 (0.27) 0.91 (0.23) rPhenotypic -0.16 (0.23) -0.40 (0.06) 0.22 (0 .04) 0.16 (0.04) 0.55 (0.03) rMicrosite -0.08 (0.06) -0.39 (0.05) 0. 20 0.04 (0.06) 0.47 (0.04) 7 rGCA ------------rSCA ------------rClone(fam) ------------rGenetic ------------rPhenotypic ------------rMicrosite -0.01 (0.11) -0.29 (0.10) 0.09 (0.10) -0.07 (0.10) 0.18 (0.10) 0.37 (0.09) Note: (---) Correlation could not be estimat ed because of variances which were 0.

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68 Table B-2. Site 1 (North Central Florida): cu ttings genetic, phenotypic and environmental (microsite) correlations between numbers of stem units (NSU) by flush for 2004 growing season. NSU-NSU correlations Flush 1 2 3 4 5 6 2 rGCA 0.30 (0.24) rSCA --rClone(fam) 0.49 (0.17) rGenetic 0.42 (0.13) rPhenotypic 0.39 (0.02) rMicrosite 0.38 (0.03) 3 rGCA 0.49 (0.18) 0.80 (0.12) rSCA --0.73 (0.63) rClone(fam) 0.30 (0.13) 1 (0.14) rGenetic 0.38 (0.11) 0.91 (0.08) rPhenotypic 0.38 (0.03) 0.45 (0.02) rMicrosite 0.38 (0.03) 0.29 (0.03) 4 rGCA 0.55 (019) --0.91 (0.07) rSCA ----0.00 (1) rClone(fam) 0.38 (0.20) 0.83 (0.14) 0.82 (0.12) rGenetic 0.43 (0.13) --0.82 (0.06) rPhenotypic 0.29 (0.03) 0.21 (0.02) 1 (0.08) rMicrosite 0.25 (0.03) 0.06 (0.03) 0.47 (0.03) 5 rGCA 0.66 (0.17) 0.47 (0.23) 0. 84 (0.10) 0.97 (0.04) rSCA --------rClone(fam) 0.38 (0.17) 0.66 (0.19) 0.80 (0.11) 1 (0.17) rGenetic 0.48 (0.12) 0.57 (0.13) 0.80 (0.07) 1 (0.08) rPhenotypic 0.32 (0.03) 0.19 (0.03) 0. 44 (0.03) 0.60 (0.02) rMicrosite 0.28 (0.04) 0.07 (0.04) 0. 30 (0.04) 0.44 (0.03) 6 rGCA 0.65 (0.22) ------rSCA --------rClone(fam) 0.54 (0.27) 0.44 (0.32) 0.49 (0. 18) 0.95 (0.24) 0.87 (0.16) rGenetic 0.57 (0.20) 0.32 (0.10) 0.31 (0. 12) 0.70 (0.18) 0.87 (0.17) rPhenotypic 0.25 (0.04) -0.04 (0.03) 0.24 (0 .03) 0.38 (0.03) 0.50 (0.03) rMicrosite 0.17 (0.06) -0.13 (0.06) 0.22 (0 .06) 0.32 (0.05) 0.44 (0.05) 7 rGCA ------------rSCA --0.38 (0.43) 0.84 (0.50) ------rClone(fam) ------------rGenetic --0.13 (0.15) 0.20 (0.12) ------rPhenotypic ---0.01 (0.10) 0.15 (0.08) ----rMicrosite 0.23 (0.11) -0.04 (0.12) 0.14 (0.11) 0.26 (0.08) 0.28 (0.10) 0.28 (0.09) Note: (---) Correlation could not be estimat ed because of variances which were 0.

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69 Table B-3. Site 1 (North Central Florida): cu ttings genetic, phenotypic and environmental (microsite)correlations between mean stem unit length (MSUL) by flush for 2004 growing season. MSUL-MSUL correlations Flush 1 2 3 4 5 6 2 rGCA 0.64 (0.18) rSCA --rClone(fam) 0.34 (0.23) rGenetic 0.46 (0.15) rPhenotypic 0.24 (0.02) rMicrosite 0.20 (0.03) 3 rGCA 0.50 (0.19) 0.61 (0.16) rSCA ----rClone(fam) 0.11 (0.16) 0.21 (0.20) rGenetic 0.27 (0.13) 0.41 (0.13) rPhenotypic 0.13 (0.03) 0.16 (0.03) rMicrosite 0.89 (0.04) 0.08 (0.04) 4 rGCA 0.58 (0.18) 0.73 (0.16) --rSCA --0.07 (1) --rClone(fam) 0.34 (0.18) 0.45 (0.22) 0.88 (0.12) rGenetic 0.43 (0.13) 0.54 (0.13) 0.55 (0.08) rPhenotypic 0.13 (0.03) 0.24 (0.03) 0.24 (0.02) rMicrosite 0.45 (0.04) 0.17 (0.03) 0.10 (0.04) 5 rGCA 0.63 (0.20) 0.57 (0.22) 0. 74 (0.11) 0.89 (0.07) rSCA --------rClone(fam) -0.02 (0.18) 0.18 (0.20) 0. 79 (0.14) 0.74 (0.14) rGenetic 0.21 (0.14) 0.34 (0.16) 0. 77 (0.09) 0.81 (0.09) rPhenotypic 0.01 (0.03) 0.02 (0.03) 0. 30 (0.03) 0.31 (0.03) rMicrosite -0.05 ( 0.04) -0.06 (0.04) 0.07 (0.03) 0.10 (0.04) 6 rGCA 0.34 (0.25) 0.12 (0.30) 0.69 (0. 14) -0.21 (0.17) 0.91 (0.09) rSCA 0.99 (0.00) ------0.85 (0.38) rClone(fam) -0.23 (0.30) -0.03 (0.32) 0.96 (0.28) 1 (0.40) 0.73 (0.21) rGenetic 0.01 (0.20) 0.03 (0.22) 0.83 (0 .14) 1 (0.08) 0.81 (0.12) rPhenotypic -0.11 (0.04) -0.21 (0.04) 0.35 (0 .04) 0.35 (0.21) 0.53 (0.03) rMicrosite -0.14 (0.06) -0.27 (0.05) 0.17 (0 .05) -0.21 (0.05) 0.43 (0.05) 7 rGCA ------------rSCA ------------rClone(fam) ------------rGenetic ------------rPhenotypic ------rMicrosite -0.13 (0.10) -0.14 (0.10) 0.13 (0.10) 0.08 (0.10) 0.24 (0.10) 0.55 (0.07) Note: (---) Correlation could not be estimat ed because of variances which were 0.

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70 Table B-4. Site 2 (Southwest Georgia): cutt ings genetic, phenotypic and environmental (microsite)correlations between flush length ( FLn ) by flush for 2004 growing season. FLn-FLn correlations Flush 1 2 3 4 5 6 2 rGCA 0.44 (0.22) rSCA --rClone(fam) 0.01 (0.10) rGenetic 0.11 (0.09) rPhenotypic 0.14 (0.03) rMicrosite 0.16 (0.04) 3 rGCA -0.46 (0.22) -0.1 (0.25) rSCA ----rClone(fam) -0.17 (0.12) 0.33 (0.11) rGenetic -0.24 (0.10) 0.21 (0.10) rPhenotypic -0.16 (0.03) -0.03 (0.03) rMicrosite -0.14 (0.04) -0.16 (0.04) 4 rGCA -0.39 (0.26) -0.12 (0.25) 0.83 (0.11) --rSCA 0.61 (1.1) --0.93 (1.4) --rClone(fam) -0.15 (0.12) 0.20 (0.10) 0.41 (0.12 --rGenetic -0.18 (0.10) 0.11 (0.10) 0.55 (0.10) --rPhenotypic -0.12 (0.03) 0.01 (0.03) 0.36 (0.03) --rMicrosite -0.09 (0.04) -0.05 (0.04) 0.28 (0.03) --5 rGCA -0.48 (0..21) -0.08 (0.23) 0.74 (0.14) 0.57 (0.17) rSCA --------rClone(fam) 0.02 (0.13) -0.05 (0.11) 0. 29 (0.14) 0.31 (0.14) --rGenetic -0.13 (0.11) -0.06 (0.10) 0.45 (0.11) 0.40 (0.11) --rPhenotypic -0.12 (0.04) -0.03 (0.04) 0.27 (0.03) 0.26 (0.03) --rMicrosite -0.12 (0.04) -0.02 (0.04) 0.20 (0.04) 0.21 (0.04) --6 rGCA -0.34 (0.27) -0.53 (0.22) 0.34 (0 .27) 0.41 (0.25) 0.40 (0.24) rSCA rClone(fam) 0.24 (0.18) -0.42 (0.11) 0.26 (0. 20) -0.04 (0.18) -0.09 (0.19) rGenetic 0.09 (0.15) -0.45 (0.10) 0.28 (0 .16) 0.09 (0.14) 0.07 (0.15) rPhenotypic -0.08 (0.05) -0.44 (0.04) 0.08 (0 .04) 0.15 (0.04) 0.00 (0.04) rMicrosite -0.15 (0.06) -0.44 (0.05) 0.01 (0 .06) 0.18 (0.06) -0.03 (0.06) 7 rGCA -0.55 (0.44) -0.17 (0.40) 0.67 (0.31) 0.85 (0.39) 0.35 (0.36) 1 (0.27) rSCA ------------rClone(fam) 0.87 (0.35) -0.12 (0.23) 0.32 (0.31) 0.35 (0.31) -0.08 (0.30) 0.13 (0.30) rGenetic 0.57 (0.29) -0.13 (0.20) 0.42 (0.23) 0.45 (0.24) 0.06 (0.23) 0.34 (0.23) rPhenotypic -0.19 (0.10) -0.41 (0.10) 0.18 (0.09) 0.11 (0.08) -0.03 (0.10) 0.19 (0.09) rMicrosite -0.7 (0.11) -0.72 (0.13) 0.03 (0.18) -0.13 (0.18) -0.09 (0.17) 0.10 (0.18) Note: (---) Correlation could not be estimat ed because of variances which were 0.

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71 Table B-5. Site 2 (Southwest Georgia): cutt ings genetic, phenotypic and environmental (microsite)correlations between numbers of stem units (NSU) by flush for 2004 growing season NSU-NSU correlations Flush 1 2 3 4 5 6 2 rGCA 0.28 (0.24) rSCA --rClone(fam) 0.04 (0.10) rGenetic 0.10 (0.09) rPhenotypic 0.23 (0.03) rMicrosite 0.30 (0.03) 3 rGCA 0.32 (0.23) 0.34 (0.22) rSCA ----rClone(fam) 0.11 (0.12) 0.91 (0.11) rGenetic 0.17 (0.11) 0.74 (0.09) rPhenotypic 0.16 (0.03) 0.25 (0.03) rMicrosite 0.16 (0.04) 0.03 (0.04) 4 rGCA 0.09 (0.30) 0.12 (0.28) 0.76 (0.11) rSCA ------rClone(fam) 0.11 (0.13) 0.61 (0.11) 0.68 (0.11) rGenetic 0.10 (0.12) 0.50 (0.10) 0.70 (0.08) rPhenotypic 0.11 (0.03) 0.16 (0.03) 0.43 (0.02) rMicrosite 0.12 (0.04) 0.02 (0.04) 0.34 (0.03) 5 rGCA 0.18 (0.30) 0.46 (0.24) 0. 85 (0.10) 0.64 (0.23) rSCA ------0.85 (0.30) rClone(fam) 0.22 (0.11) 0.68 (0.09) 0. 66 (0.11) 0.57 (0.11) rGenetic 0.20 (0.10) 0.61 (0.08) 0. 75 (0.08) 0.61 (0.09) rPhenotypic 0.18 (0.03) 0.34 (0.03) 0. 43 (0.03) 0.40 (0.02) rMicrosite 0.16 (0.04) 0.16 (0.04) 0. 30 (0.04) 0.33 (0.04) 6 rGCA 0.85 (0.54) 0.74 (0.24) 0.96 (0. 27) 0.78 (0.40) 0.73 (0.24) rSCA ----------rClone(fam) 0.44 (0.19) 0.30 (0.16) 0.46 (0. 10) 0.46 (0.19) 0.46 (0.20) rGenetic 0.48 (0.17) 0.38 (0.14) 0.53 (0. 16) 0.47 (0.16) 0.51 (0.16) rPhenotypic 0.10 (0.04) 0.24 (0.05) 0.28 (0. 04) 0.29 (0.04) 0.41 (0.03) rMicrosite -0.03 (0.06) 0.19 (0.06) 0.20 (0 .06) 0.24 (0.06) 0.38 (0.05) 7 rGCA ------------rSCA ------------rClone(fam) 0.06 (0.20) 0.47 (0.17) 0.26 (0.20) 0.14 (0.18) 0.35 (0.16) 0.44 (0.18) rGenetic 0.05 (0.16) 0.40 (0.14) 0.20 (0.15) 0.12 (0.15) 0.28 (0.13) 0.43 (0.18) rPhenotypic 0.03 (0.09) 0.20 (0.08) 0.09 (0.08) 0.08 (0.07) 0.15 (0.07) 0.22 (0.07) rMicrosite -0.01 (0.24) -0.20 (0.22) -0.08 (0.24) 0.13 (0.26) -0.05 (0.24) 0.13 (0.12) Note: (---) Correlation could not be estimat ed because of variances which were 0.

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72 Table B-6. Site 2 (Southwest Georgia): cutt ings genetic, phenotypic and environmental (microsite) correlations between mean stem unit length (MSUL) by flush for 2004 growing season. MSUL-MSUL correlations Flush 1 2 3 4 5 6 2 rGCA 0.66 (0.14) rSCA --rClone(fam) 0.49 (0.12) rGenetic 0.55 (0.10) rPhenotypic 0.36 (0.03) rMicrosite 0.28 (0.03) 3 rGCA 0.47 (0.18) 0.85 (0.07) rSCA ----rClone(fam) 0.29 (0.12) 0.82 (0.07) rGenetic 0.36 (0.10) 0.83 (0.05) rPhenotypic 0.20 (0.03) 0.47 (0.03) rMicrosite 0.12 (0.04) 0.25 (0.03) 4 rGCA 0.42 (0.20) 0.63 (0.15) 0.85 (0.08) rSCA ------rClone(fam) 0.37 (0.12) 0.43 (0.09) 0.53 (0.07) rGenetic 0.39 (0.10) 0.49 (0.08) 0.63 (0.06) rPhenotypic 0.16 (0.03) 0.22 (0.03) 0.39 (0.03) rMicrosite 0.06 (0.04) 0.05 (0.04) 0.23 (0.03) 5 rGCA 0.34 (0.21) 0.77 (0.11) 0. 84 (0.08) 0.69 (0.13) rSCA --------rClone(fam) 0.21 (0.13) 0.53 (0.10) 0. 70 (0.08) 0.47 (0.09) rGenetic 0.26 (0.11) 0.61 (0.08) 0. 75 (0.06) 0.54 (0.08) rPhenotypic 0.14 (0.03) 0.31 (0.03) 0. 41 (0.03) 0.28 (0.03) rMicrosite 0.09 (0.04) 0.14 (0.04) 0. 19 (0.04) 0.13 (0.04) 6 rGCA 0.14 (0.32) 0.68 (0.21) 0.80 (0. 17) 0.59 (0.25) 0.59 (0.23) rSCA ----------rClone(fam) 0.14 (0.15) 0.32 (0.12) 0.44 (0. 10) 0.30 (0.11) 0.33 (0.11) rGenetic 0.13 (0.13) 0.40 (0.10) 0.51 (0. 09) 0.36 (0.10) 0.39 (0.10) rPhenotypic 0.04 (0.04) 0.15 (0.04) 0.34 (0. 04) 0.20 (0.04) 0.26 (0.04) rMicrosite 0.00 (0.06) 0.00 (0.06) 0.22 (0. 06) 0.11 (0.06) 0.19 (0.06) 7 rGCA ------------rSCA ------------rClone(fam) ------------rGenetic ------------rPhenotypic ------------rMicrosite 0.00 (0.10) -0.10 (0.10) 0.22 (0.09) 0.22 (0.09) 0.26 (0.10) 0.28 (0.10) Note: (---) Correlation could not be estimated because of variances which were 0.

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73 APPENDIX C SECOND-YEAR GROWING SEASON PHYLLOSTATIC PATTERNS. Table C-1. Individual tree narrow and broad-se nse heritabilities for phyllostatic patterns by propagule type for 2004 growing season in Site 1 (North Central Florida) and Site 2 (Southwest Georgia). Seedlings Cuttings Phyllostatic pattern by flush h2 H2 h2 H2 Site 1 1 0.05 (0.09) 0.05 (0.09) 0.00 (0.00) 0.06 (0.02) 2 0.03 (0.08) 0.03 (0.08) 0.00 (0.00) 0.05 (0.02) 3 0.04 (0.08) 0.04 (0.08) 0.00 (0.00) 0.05 (0.02) 4 0.06 (0.09) 0.06 (0.09) 0.00 (0.00) 0.06 (0.02) 5 0.00 (0.00) 0.24 (0.32) 0.00 (0.00) 0.07 (0.03) 6 0.49 (0.58) 1.00 (1.25) 0.00 (0.02) 0.20 (0.06) 7 ----0.27 (0.43) 0.14 (0.21) Site 2 1 0.00 (0.00) 0.19 (0.23) 0.00 (0.01) 0.00 (0.01) 2 0.00 (0.00) 0.18 (0.23) 0.00 (0.01) 0.01 (0.04) 3 0.10 (0.10) 0.10 (0.10) 0.01 (0.01) 0.02 (0.04) 4 0.00 (0.00) 0.12 (0.24) 0.00 (0.01) 0.00 (0.01) 5 0.19 (0.18) 0.19 (0.18) 0.01 (0.02) 0.00 (0.01) 6 0.19 (0.77) 1.00 (1.10) 0.00 (0.00) 0.08 (0.10) 7 ----0.10 (0.42) 0.05 (0.21)

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77 Jokela, E.J., and Long, A.J. 2000. Using soils to guide fertilizer recommendations for southern pines. Florida Cooperative Ex tension Service Circular 1230. 9 p. Kaya, Z. 1993. Genetic variati on in shoot growth component s and their correlations in Pseudotsuga menziesii var. menziesii seedlings. Scand. J. For. Res. 8 (1): 1-7. Kremer, A. 1985. Component analysis of height growth, compensation between components and seasonal stability of s hoot elongation in maritime pine ( Pinus pinaster Ait.). Crop physiology of forest trees: 203-217. Kremer, A., and Larson, P.R. 1983. Genetic control of height growth components in jack pine seedlings. For. Sci. 29 (3): 451-464. Kremer, A., and Lascoux, D.M. 1988. Genetic ar chitecture of height growth in maritime pine ( Pinus pinaster Ait.). Silvae Genet. 37 (1): 1-8. Kremer, A., and Roussel, G. 1982. Composante s de la croissance en hauteur chez le pin maritime ( Pinus pinaster Ait.). Ann. Sci. Forest. 39 (1): 77-97. Kremer, A., and Xu, L. 1989. Relationship be tween first-season free growth components and later field height growth in maritime pine ( Pinus pinaster ). Can. J. For. Res. 19: 690-699. Kremer, A., Xu, L.A., Guyon, J.P., and Rou ssel, G. 1989. Genetic, age and ontogenetic variation of phyllotactic arrangements in pine species. Can. J. Bot. 67 (4): 12541261. Lanner, R.M. 1976. Patterns of shoot devel opment in pinus and their relationship to growth potencial. Tree Physiol. and Yi eld Improvement (Cannell, M.G.R., and Last, F.T., eds): 223-244, Academic Press, New York. 567p. Li, B., Williams, C., Carlson, W.C., Harri ngton, C.A., and Lambeth, C.C. 1992. Gain efficiency in short-term testing: experimental results. Can. J. For. Res. 22 (3): 290297. Li, P., and Adams, W.T. 1993. Genetic c ontrol of bud phenology in pole-size trees and seedlings of coastal Douglas-fir. Can J. Forest Res. 23: 1043-1051. Lu, P., Joyce, D.G., and R.W. Sinclair. 2003. Effect of select ion on shoot elongation rhythm of eastern white pine (Pinus strobus L) and its implications to seed transfer in Ontario. Forest Ec ology and Management. 182: 161-173. Magnussen, S., and Yeatman, C.W. 1989. Hei ght growth components in interand intraprovenance jack pine families. Can. J. For. Res. 19: 962-972. McCrady, R.L., and Jokela, E.J. 1996. Grow th phenology and crown st ructure of selected loblolly pine families planted at two spacings. For. Sci. 42: 46-57.

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78 McKeand, S.E., Mullin, T., Byram, T.D., a nd White, T. 2003. Deployment of genetically improved loblolly and slash pine s in the south. J. Forest. 101 (3): 32-37. Mirov, N.T., Duffield, J.W., and Liddi coet, A.R. 1952. Altitudinal races of Pinus ponderosa a 12-year progress report. J. Forest. 50: 825-831. Monroe, K.W. 2005. Soil Survey of Randol ph County, GA. USDA Natural Resources Conservation Service. 289p. http://www.mo15.nrcs.usda.gov/technical /surveys/georgia/randolph/Randolph.pdf March, 2006. Perry, T.O., Wang, C.W., and Schmitt, D. 1966. Height growth for loblolly pine provenances in relation to photoperiod and growing season. Silvae Genet. 15: 61100. Pollard, D., and Logan, K. 1974. The role of summer shoots in the differentiation of provenances of black spruce. Can. J. For. Res. 4: 308-311. Readle, E.L. 1990. Soil Survey of Putnam County, FL. USDA Natural Resources Conservation Service. 224p. Rehfeldt, G.E., and Lester, D.T. 1966. Variation in shoot elongation of Pinus resinosa (Ait.). Can. J. Bot. 44: 1457-1469. Richards, F.J. 1951. Phyllotaxis: its quantitat ive expression and relati on to growth in the apex. Philo. Trans. R. Soc. London, Ser. B. 235: 509-563. Rweyongeza, D.M., Yeh, F.C., and Dhir, N.K. 2003. Genetic variation in stem growth components in white spruce seedlings and its implications to retrospective early selection. For. Genet. 10: 4299-4308. Smith, C.K., White, T.L., and Hodge, G.R. 1993a Genetic variation in second-year slash pine shoot traits and their re lationship to 5and 15-year volume in the field. Silvae Genet. 42 (4-5): 266-275. Smith, C.K., White, T.L., Hodge, G.R., Duryea, M.L., and Long, A.J. 1993b. Genetic variation in first-year slas h pine shoot components and their relationship to mature field performance. Can. J. For. Res. 23 (8): 1557-1565. Surles, S.E. 1993. Early selecti on for volume growth in slash pine. (Ph. D. dissertation. University of Florida, Gainesville. pp. 81). Waxler, M.S., and Van Buijtenen, J.P. 1981. Ea rly genetic evaluation of loblolly pine. Can. J. For. Res. 11: 351-355. Williams, C.G. 1988. Accelerated short-term ge netic testing for loblolly pine families. Can. J. For. Res. 18: 1085-1089.

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79 Wright, S. 1968. Evolution and the genetics populations. University of Chicago Press, Chicago, IL. Yamada, Y. 1962. Genotype by environment inte raction and genetic correlation of the same trait under different e nvironments. Jpn. J. Genet. 37: 498-509. Zagrska-Marek, B. 1985. Phyllotact ic patterns and transitions in Abies balsamea Can. J. Bot. 63: 1844-1854. Zhang, S.S., Allen, H.L., and Dougherty, P. M. 1997. Shoot and foliage growth phenology of loblolly pine trees as affected by n itrogen fertilization. Can. J. For. Res. 27 (9): 1420-1426

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80 BIOGRAPHICAL SKETCH Liliana Parisi was born in the town of La Plata in Argentina and grew up in the city of Pergamino, Buenos Aires Province, a re gion without many trees but where agriculture and cattle are very popular. In 1996, she gradua ted as an Agricultura l Engineer at the Universidad Nacional de La Plata (UNLP) in La Plata, Argentina. Between 1997 and 2003, she worked as a junior researcher at the forestry division of INTA Bella Vista Experimental Station. She enrolled in the School of Forest Resear ch and Conservation master’s program in August 2003 at the Univer sity of Florida. Afte r her graduation, she will continue her studies at the University of Florida pursuing her PhD degree.


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SHOOT ELONGATION PATTERNS AND GENETIC CONTROL OF SECOND
YEAR HEIGHT GROWTH IN Pinus taeda L. USING CLONALLY REPLICATED
TRIALS















By

LILIANA MARTA PARISI


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2006



























Copyright 2006

by

Liliana Marta Parisi






















To Elsa and Ruben, my parents

Javier, my brother

Fabian, my husband

Olga, my mother in-law

and Luisa.

To my friends

Laura, Laura, Natalia, Andrea, Tete, Claru and Dofia Isabel















ACKNOWLEDGMENTS

I would like to thank Drs. Timothy Martin, Dudley Huber and Timothy White for

serving on my advisory committee, sharing with me their time, knowledge and help

during this program. In particular, I want to express my enormous gratitude to Dr. Huber

for his guidance, support and encouragement and also for his immense disposition and

patience explaining difficult concepts to me over and over again. I especially thank Dr.

Martin, for always providing me with valuable help for collecting the large amount of

data that this project demanded. Thanks also go to Mr. Greg Powell for his support in

several aspects.

This research was done with the financial support of the Cooperative Forest

Genetic Research Program (CFGRP) and the Forest Biology Research Cooperative

(FBRC), and I really hope the results of this study contribute to the continued success of

the cooperatives and the better knowledge of loblolly pine height growth.

I also would like to acknowledge the financial support of the Fulbright-

Bunge&Born fellowship for giving me the opportunity to initiate my graduate studies

here in the United States and to the CFGRP for additional funding. My thanks also go to

INTA (National Institute of Agriculture Technology), my employer, for maintaining my

position and salary all this time.

I further acknowledge Blanca Canteros, Sara Caseres and Juan A. L6pez (h.) for

their encouragement and support to continue my academic career.









Special thanks are extended to all the people who helped me with the data

collection for this project: particularity, Dr. Huber and Mr. Greg Powell for their amazing

job at Georgia site; my fellow graduate students: Brian Baltunis, Veronica Emhart,

Salvador Gezan, and Alex Medina, who also gave me valuable tips for classes and other

academic issues; my friends Bijay Tamang and Jorge Baldessari, who freely and

willingly gave me a helping hand not only with the field work but also with classes; and

the help of the FBRC field crew.

I want to thank Ms Debra Anderson and my "Fulbright friends" for being such

great company on all those special dates that being with family is so important. My

special thanks also go to Tirhani Manganyi who cheers my days with her friendship.

Finally, and most important, I thank my parents and brother for their love, help and

support; and, last but not at least, I want to thank my husband, Fabian Hergenreder, who

brought me joy and encouragement every day during this master's program and for

bearing stoically my daily supervision during his amazing job of measuring flush length

and number of stem units.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ................................................................................................. iv

LIST O F TA BLE S ............. ........... ... .... .... ................. ... .... .... .............. viii

LIST OF FIGURES ......... ......................... ...... ........ ............ xi

ABSTRACT ........ .............. ............. .. ...... .......... .......... xii

CHAPTER

1 INTRODUCTION ............... ................. ........... ................. ... .... 1

2 M ATERIALS AND M ETHOD S ........................................... ........... ............... 7

Study A rea Characteristic ............................................................ ............7
Plant Material and Experimental Design ....................................... ...............8
T raits M easu red ....................................................... ................ .. 9
Initiation and Cessation ............................................................. .. ......... 9
Flush D escriptors ................. ... .................. ............... .... ...... .............. .. 11
Statistical Analyses and Genetic Parameters............... .............................................14
Phenological Traits .................. ........................... .... .... ............... ... 14
Flush D escriptors ....................................................... .... ...............19

3 RESULTS AND DISCU SSION ........................................... .......................... 24

P h en logical T raits ........... ....... ..... ... .. .. .................................................................24
Least Square Means for Phenological Traits by Provenance and Propagule
T y p e ......................................................................... 2 4
H eritability Estim ates .......................................... .......... .... ...... .. ............ 27
Height Growth Increment.................... ...... ..... .............27
Cumulative and Cumulative Percentage Height Growth Increment............28
Phenological Traits and AHI ............................................ .................. 29
Correlations Among Phenological Traits. ................................ .................30
Initiation-D duration Correlation ........................................ ............... 31
Cessation-Duration Correlation................. ....... ...............31
Initiation-AHI and Initiation-Cessation Correlations .............................. 31
Initiation-ASRG Correlations ............................................ ............... 32
Cessation-ASGR Correlations ............................. ..... ...................... 34









Path Analysis .................................... ........ .................. 34
Flush D escriptors .................. ...................................................... .. 36
Heritability Estimates ...... .......... ......... .. ...... ............... 36
Type B Correlation ....... .. ... ....... .... ........... ....................... ..............40
Growth and Shoot Components ....................................... ............... 43
F lu sh D escriptors........ ................................................ ........ .... .......... 43
Path Analyses ....................................... .......... ....... ........ 44
Annual Height Increment with Number of Flushes and Average Flush
L length ............................................................ ... ..... ....................... 44
Flush Length with Number of Stem Units and Mean Stem Unit Length.....47
Least Square Means for Provenance for FLn, PFL, NSU and MSUL.................54
P hyllostatic P patterns ............................ .................. ............ .... ..... ...... 58

4 C O N C L U SIO N S ....................... .. .... ........................ .. ........ ...... ... ...... 60

APPENDIX

A DIFFERENCES BETWEEN PROPAGULE TYPES.................. ...... .............63

B SECOND-YEAR PHENOTYPIC, GENETIC and ENVIRONMENTAL
CORRELATIONS BETWEEN FLUSH LENGTHS (FLn), NUMBER OF STEM
UNITS (NSU) and MEAN STEM UNIT LENGTH (MSUL) by FLUSH..................66

C SECOND-YEAR GROWING SEASON PHYLLOSTATIC PATTERNS ..............73

LIST OF REFEREN CES ............................................................................. 74

BIO GRAPH ICAL SK ETCH .................................................. ............................... 80















LIST OF TABLES


Table page

2-1 Phyllostatic series identification.................................................................. .......14

2-2 Number of trees involved in each of the analyses by site and propagule type.........23

3-1 Least square means for second-year phenological traits and annual height
increments by provenances and propagule type for 2004 growing season in Site
1 (North Central Florida) and Site 2 (Southwest Georgia). ...................................25

3-2 Incremental height growth: narrow (h2) and broad-sense (H2) heritabilities on
measurement days during 2004 growing season by propagule type at Site 1
(N orth C central Florida)................................................. ................................ 28

3-3 Cumulative height growth: narrow (h2) and broad-sense (H2) heritabilities on
measurement days during 2004 growing season by propagule type at Site 1
(N orth C central Florida)................................................. ................................ 29

3-4 Cumulative percentage of height growth: narrow (h2) and broad-sense (H2)
heritabilities on measurement days during the 2004 growing season by
propagule type in Site 1 (North Central Florida). ................................................29

3-5 Individual narrow (h2) and broad-sense (H2) heritabilities for phenological traits
and AHI by propagule type for the 2004 growing season in Site 1 (North Central
Florida) and 2 (Southw est G eorgia) ...................................................................... 30

3-6 Genetic, phenotypic and environmental (microsite) correlations between
phenological traits and annual height increment (AHI) by propagule type for
2004 growing season in Site 1 (North Central Florida) and 2 (Southwest
G eo rg ia) ...................................... .....................................................3 3

3-7 Values of phenotypic and genetic path coefficients, correlation coefficients and
degrees of determination for annual height increment (AHI) by growth duration
(D) and average shoot growth rate (ASRG) by propagule type for Site 1 (North
C central F lorida). ................................................................... ... 35

3-8 Site 1 (North Central Florida): individual-tree narrow (h2) and broad-sense (H2)
heritabilities for growth and shoot components by propagule type for the 2004
grow ing season. ...................................................................... 38









3-9 Site 2 (Southwest Georgia): individual tree narrow (h2) and broad-sense (H2)
heritabilities for growth and shoot components by propagule type for 2004
grow ing season. ........................................................................39

3-10 Across site individual narrow (h2) and broad-sense (H2) heritabilities for growth
and shoot components by propagule type for 2004 growing season for Site
1(North Central Florida) and Site 2 (Southwest Georgia). ...................................41

3-11 Type B correlations for growth and shoot components by propagule type for
2004 growing season between Site 1 (North Central Florida) and Site 2
(Southw est G eorgia) ................................................................. ..................42

3-12 Phenotypic and genetic values for path coefficients components, correlations
coefficients, and degree of determinations for annual height increment AHIFLn
by number of flushes (NF) and average flush length (AvFL) by propagule type
for Site 1 (North Central Florida) and Site 2 (Southwest Georgia)..........................46

3-13 Site 1 (North Central Florida): phenotypic values of path coefficients and path
components, correlations coefficients and degree of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem unit (NSU) by propagule type ......................................................................... 48

3-14 Site 2 (Southwest Georgia): phenotypic values of path coefficients and path
components, correlations coefficients and degree of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem unit (NSU) by propagule type ......................................................................... 49

3-15 Site 1 (North Central Florida): genetic values for path coefficients and path
components, correlation coefficients and degrees of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem unit (NSU) by propagule type .........................................................................52

3-16 Site 2 (Southwest Georgia): genetic values for path coefficients and path
components, correlation coefficients and degree of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem units (NSU) by propagule type. ............................................ ............... 53

3-17 Frequency of phyllostatic series by propagule type in Site 1 (North Central
Florida) and 2 (Southw est Georgia) ...................................... ......... .............. 59

A-1 Significance levels (p-values) between propagule types for annual height
increment and phenological traits at Site 1 (North Central Florida) and Site 2
(Southw est G eorgia) ................................................................. ..................64

A-2 Significance levels (p-values) between propagule types for height increment,
average cumulative height increment and average percentage cumulative
increment at Site 1 (North Central Florida) and Site 2 (Southwest Georgia). .........64









A-3 Significance levels (p-values) between propagule types for growth and shoot
components at Site 1 (North Central Florida) and Site 2 (Southwest Georgia). .....65

B-l Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite) correlations between flush length (FLn) by flush for 2004 growing
season .............................................................................. 67

B-2 Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite) correlations between numbers of stem units (NSU) by flush for 2004
grow ing season. ........................................................................68

B-3 Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite)correlations between mean stem unit length (MSUL) by flush for
2004 grow ing season ........................... .... .................... .... .... ........... 69

B-4 Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite)correlations between flush length (FLn) by flush for 2004 growing
season .............................................................................. 70

B-5 Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite)correlations between numbers of stem units (NSU) by flush for 2004
grow ing season ................................................................................ ............... 7 1

B-6 Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite) correlations between mean stem unit length (MSUL) by flush for
2004 grow ing season ........................... .... .................... .... .... ........... 72

C-l Individual tree narrow and broad-sense heritabilities for phyllostatic patterns by
propagule type for 2004 growing season in Site 1 (North Central Florida) and
Site 2 (Southw est G eorgia). ............................................ ............................. 73















LIST OF FIGURES

Figure page

2-1 Loblolly pine parastichy arrange ent ...................................... ..................... 13

3-1 Least square means for average cumulative apical height growth increment and
apical height growth increment by provenance and propagule type at Site 1
(N orth C central Florida).................................................. ............................... 26

3-2 Least square means for number of flushes (NF) and annual height increment as a
summation of flush length (AHIFL) for the 2004 growing season by propagule
type at Site 1 (North Central Florida) and Site 2 (Southwest Georgia) ...................55

3-3 Least square means for flush length (FLn) and flush length contribution (PFL)
by propagule type at Site 1 (North Central Florida) and Site 2 (Southwest
Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic Coastal Plain
provenances, respectively...................... ....... ............................... 56

3-4 Least square means for number of stem units (NSU) and mean stem unit length
(MSUL) by propagule type at Site 1 (North Central Florida) and Site 2
(Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic
Coastal Plain provenances, respectively. ..................................... ............... 57















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

SHOOT ELONGATION PATTERNS AND GENETIC CONTROL OF SECOND
YEAR HEIGHT GROWTH IN Pinus taeda L. USING CLONALLY REPLICATED
TRIALS

By

Liliana Marta Parisi

May 2006

Chair: Timothy A. Martin
Cochair: Dudley A. Huber
Major Department: Forest Resources and Conservation.

Height growth is one of the most commonly measured phenotypic traits for

assessing volume production in tree improvement programs. This study focused on the

genetic architecture of the phenological (initiation, cessation, duration and growth rate)

and morphological (number of flushes, flush length, number of stem units (NSU), mean

stem unit length (MSUL)) aspects of the second-year annual height growth, using

approximately 900 clones and 61 seedling families of loblolly pine from 61 full-sib

families and 3 provenances.

Rooted cuttings differed from seedlings for all phenological and morphological

traits that were analyzed in this study. This difference was due to propagation effects

since types were compared for common families.

The overall results of this study indicated that the average growth rate per day was

the most important variable in determining second-year annual height increment. The









contribution of growing season duration to second year annual height increment was

negligible. Both analogies were used to assign relative importance to the components of

height growth. The narrow and broad-sense heritability estimates for the different dates

for height growth increment during the growing season were moderate and decreased

from initiation date to cessation date.

For the total population average flush length was the principal contributor to total

annual height while number of flushes was a minor contributor.

NSUwas by far the most important trait for the length of the first three flushes. For

later flushes NSU and MSUL contributed equally to flush length. The genetic

contribution of MSUL to flush length was relatively larger than the phenotypic

contribution, becoming more important than NSU after flush 3, especially for seedlings.

Provenances demonstrated different shoot elongation patterns. FL provenance had

higher growth at the beginning of the growing season while ACC and LG growth was

slightly higher than FL seed source after the second flush. Length of the early flushes

appeared to confer a significant advantage for FL cutting over the other seed sources.

Florida-source loblolly pine also had a longer growing season and more flushes than the

other provenances.

With an understanding of the relationship among the loblolly pine shoot growth

components, their genetic parameters and their physiology, we can obtain the structural

and functional clues about differences among propagule types, seed sources, family and

clones for annual height growth performance.














CHAPTER 1
INTRODUCTION

Pinus taeda L. (loblolly pine) is the most important commercial tree species

planted in the southern United States occupying approximately 12 million hectares

(Jokela and Long 2000). The material planted over the last 50 years has been developed

from bulk orchards, open-pollinated orchards, full-sib families and more recently clones.

In the southern United States, state agencies and forest companies carry out tree

improvement programs and some of them are initiating their third generation of breeding.

The overall gains in volume per unit area range from 10 to 30 percent over unimproved

material; depending the deployment strategies used; but, if just the best full-sib and

clones are planted, gains of 35 to 50 percent are possible (McKeand et al. 2003).

Height growth is one of the most commonly measured phenotypic traits for

assessing volume production in tree improvement programs (Kremer and Lascoux 1988)

and also seems to be the most dependable and simplest trait for early selection in loblolly

pine in the southeastern United States (Bridgwater and McKeand 1997). Annual apical

growth in conifers is a compound trait and can be divided into multiplicative and additive

components (Cannell 1978 and Ford 1980). Those components can be grouped into

phenological and morphogenical aspects. Knowledge of pine shoot growth components

is essential for understanding height growth.

Annual apical growth (annual height increment AHI) can be considered as the

product of shoot growth duration (D) and the average shoot growth rate (ASGR). For

estimation of D and ASGR, in addition to height growth, the phenological traits, timing of









initiation and cessation, have to be determined. Higher growth rate was responsible for

the superior height growth of two interprovenance jack pine (Pinus banksiana) families

(Magnussen and Yeatman 1989). Perry et al. (1966), determined for loblolly pine that

growth rate accounted for about 60 percent of the height growth variation. Bollmann and

Sweet (1977) suggested that one of the reasons for the high growth rate of Pinus radiata

is its extensive growing season. For loblolly pine Jayawickrama et al.(1998), implied

that large gains in growth rate can be obtained from north Florida material because of

their genetically longer growing season. Dougherty et al. (1994) reported an almost 6

week difference in bud break timing in P. taeda from two localities which differ by 60

latitude (Gulf Coast 30.50 and North Carolina-Virginia border 36.50N). Loblolly pine

has a broad natural range (14 States in USA, Burns and Honkala 1990) which promotes

the occurrence of diverse ecotypes.

Loblolly pine has a complex shoot morphogenesis, with the annual height

increment including many flushes or cycles (Boyer 1970; Griffing and Elam 1971;

Bridgwater et al. 1985; Bridgwater 1990; Harrington 1991). There are commonly 3 to 6

cycles, and two types of growth, predetermined and free (Lanner 1976). Height growth

initiation is primarily related to temperature (Boyer 1970; Ford 1980) and it has been not

determined if the overwintering bud goes through a true dormancy or only a chilling

period is needed to burst (Carlson 1985). Apical height growth starts during the spring

with the elongation of the stem units present in the overwintering bud and this constitutes

the first flush. This is predetermined growth because all the stem units that constitute the

first flush were formed during the previous growing season. Commonly the

overwintering bud contains only one flush, but one or two cycles from the preformed bud









were noted by Greenwood (1980). Subsequent flushes are called free, summer or

indeterminate growth. The main characteristic of this type of growth is that both the bud

and the elongation of its components occur in the same growing season, generally during

the summer. The number of free cycles varies from 1 to 7 (Lanner 1976). Griffing and

Elam (1971) studied the height growth patterns of loblolly pine saplings and pointed out

overlapping flush elongations. Usually two consecutive cycles elongate concomitantly.

At the time that a succeeding flush is at its maximum elongation rate the growth rate of

the previous flush decelerates. This repeated pattern occurs until the winter bud is

formed, which takes place when a succeeding bud does not elongate even when the

preceding flush is fully elongated. Several studies of shoot growth have assessed the

relative contributions of predetermined and free growth (Pollard and Longan 1974;

Cannell and Johnstone 1978; Bailey and Feret 1982). Zhang et al. (1997), in loblolly

pine under nitrogen fertilization, found that on average the first flush contributed about

69% of the total leaf area. Measuring annual shoot growth Isik et al. (2002) concluded

that summer shoot growth can serve as an explanatory variable to predict height growth

in Pinus brutia populations. Thus, annual shoot length is the result of the summation of

predetermined and indeterminate flushes. The number of flushes also has an influence on

height growth. Under different levels of vegetation control and site preparation in 3-year-

old loblolly pine, the individuals with superior height growth had a larger numbers of

flushes and a greater length per flush (Allen and Wentworth 1993).

The length of each flush is the product of the number of stem units (NSU) and the

mean stem unit length (MSUL). The partitioning of the shoot growth into its components

allows a better understanding of the genetic variation in height growth through









phenological, morphological and physiological characteristics associated with shoot

growth (Rehfeldt and Lester 1966; Magnussen and Yeatman 1989; Rweyongeza et al.

2003). Theoretically NSU and MSUL are inherited independently because the meristems

for stem unit initiation and for stem unit elongation are physically different and are

activated at different times by independent mechanisms (Cannell et al. 1976; Cannell

1978). The division of conifer shoot growth into its factors has been performed by

several authors, providing a method for assessing genetic, phenotypic and environmental

variation but with very diverse results. NSU has been shown to be more important

contributor to shoot length in loblolly pine, P. rigida and their hybrids (Bailey and Feret

1982), in P. pinaster (Kremer and Lascoux 1988), in Abies cephalonica (Fady 1990), in

P. elliottii under two nitrogen treatments (Smith et al. 1993b) and P. palustris (Allen and

Scarbrough 1970). For Kremer and Xu (1989), MSUL was the component with the

highest stability and also a better predictor of total height in P. pinaster. Kaya (1993)

working with Douglas-fir obtained moderate correlations among NSU, MSUL, and height

increment. In P. patula, G6mez-Cardenas et al. (1998) found that both MSUL and NSU

where influential components in shoot height with a low negative correlation between

them. Negative correlation between NSU and MSUL was reported by several authors

(Kremer and Larson 1983; Bongarten 1986; Kremer and Lascoux 1988; Magnussen and

Yeatman 1989) who suggested that NSU and MSUL are not good selection criteria. Some

studies show variation between provenances and families within provenances for NSU

and MSUL. Kremer and Larson (1983) reported that NSUwas a better predictor of

annual height increment on a provenance level, whereas MSUL was a slightly better

predictor on a family-within provenance level. Within provenances of Douglas-fir









(Pseudotsuga menziesii) and blue spruce (Piceapungens) the phenotypic variation in

shoot length assigned equally to MSUL and NSU. In blue spruce the genetic variation

was mostly due to MSUL and the environmental variation was caused primarily by NSU

(Bongarten 1986). Rweyongeza et al. (2003) working with white spruce found that

MSUL would give more expected gain from direct selection at 11 years than NSU for

both of the sites in which they were working. Their path coefficient analysis indicated

that branch length was primarily determined by NSU.

Assessing height growth variation for NSU and MSUL several studies have

promoted differential genetic expression of juvenile traits for predicting field

performance by creating different environments such as irrigation and/or fertilization

with promising results in slash pine (DeWald et al. 1992; Smith et al. 1993b; Surles

1993) in loblolly pine (Li et al. 1992; Williams 1988; Waxler and van Buijtenen 1981).

Traits of shoot growth patterns (NSU, MSUL, annual height increment (AHI),

number of cycles) have been evaluated as early selection criteria on genotypic and

phenotypic age-age correlations with varying results (Williams 1987; Williams 1988;

Bridgwater 1990; Li etal. 1991; Li etal. 1992; Smith etal. 1993a; Lu etal. 2003). In

one study, second-year total annual height increment was found to be better correlated to

8-year height performance than MSUL or NSUin loblolly pine (Bridgwater 1990) while

summer NSU and AHI of treatments with supplementary irrigation and fertilization had

equal or better correlation with 8-year height (Li et al. 1992).

One of the advantages of working with clonal tests derived from full-sib families is

the chance to estimate additive and non-additive genetic components of variance

associated with a specific trait (Isik et al. 2003). Isik et al. (2003) working with a









clonally replicated trial of loblolly pine determined that additive variance was the major

source of genetic variance in height growth. Dominance variance for height, diameter

and volume was insignificant during the first year, but was important at age 6. Epistatic

variance was not important for growth traits. Similar results for additive and dominance

variance were obtained by Paul et al (1997) for height. The importance of dominance at

age 5 indicates the likelihood of additional genetic gains through clonal testing (Carson

1986; Paul et al 1997). Isik et al (2003) arrived at a similar conclusion and suggested

that clonally replicated progeny tests may provide special advantages for loblolly pine

tree improvement programs. In clonal tests the efficiency of testing is increased by

averaging the microenviromental variance and a more precise estimation of genetic

parameters can be obtained.

This study examined loblolly pine shoot growth patterns in clones in two different

environments, and provided the opportunity to examine the genetic mechanisms

controlling tree growth strategies, and to examine the adaptability of Florida material to

cooler environments. The present study contains large numbers of clones (around 900)

from full-sib families derived from a partial diallel mating design. The objectives were

to: (i) Determine whether propagule types, seed sources, families or clones differ in the

timing of growth initiation or cessation; (ii) Estimate genetic parameters, genetic

architecture, propagule type and seed source effects for phenological and morphological

traits; (iii) Determine the relative contributions of the number of flushes to total height

growth; and (iv) Determine the relative contributions of the different components of the

flush to flush length.














CHAPTER 2
MATERIALS AND METHODS

Study Area Characteristic

Two loblolly pine sites of the Forest Biology Research Cooperative (FBRC)

CCLONES (Comparing Clonal Lines On Experimental Sites) study were measured

during their second growing season. The intensive silvicultural treatment portion of

those tests was chosen for this study. Site 1 was on Plum Creek land in Putnam County,

Florida (approximate latitude 290 38' 24" N, longitude 810 49' 27" W; elevation: 7m.)

and Site 2 was on MeadWestvaco land in Randolph County, Georgia (approximate

latitude 310 47' 59" N, longitude 840 41' 32" W; elevation: 137m).

The soils at Site 1 belong to Pomona fine sand soil series with slopes from 0 to 2

percent. Their taxonomic classification is sandy, siliceous, hyperthermic Ultic Alaquods.

These soils are very deep and have a surface layer of black fine sand of about 18 cm. The

subsurface layer is gray and light-gray fine sand with a depth of about 50 cm. The upper

part of the subsoil is dark reddish brown loamy fine sand of a depth of 70 cm. Below that

layer is dark brown and light brownish gray fine sand at an approximate depth of 105 cm.

At around 180 cm the lower layer is gray and light gray fine sandy loam. The substratum

as deep as 200 cm is greenish gray fine sandy loam. The water table under natural

conditions is within 15 to 45 cm of the surface for one to three months and is at a depth of

25 to 100 cm for six months or more during most years. The natural fertility of these

soils is low (Readle 1990). The average annual precipitation for the test area is around









1250 mm. The average high and low temperatures in summer are 33.40C and 24.20C,

respectively. The average high and low temperatures in winter are 16.30C and 6.60C.

Soils at Site 2, Randolph County, GA, are classified as the Red Bay soils series.

The Red Bay series consists of very deep, well drained, moderately permeable soils that

formed in thick beds of unconsolidated, loamy marine sediments on uplands of the

Coastal Plain. Slopes range from 0 to 15 percent. The taxonomic classification is fine-

loamy, kaolinitc, thermic Rhodic Kandiudults. The typical sequence of horizons of this

series is a dark reddish-brown sandy loam Ap horizon of about 15 cm, from

approximately 15 to 120 cm this soils has a series of Bt horizons (Btl, Bt2 and Bt3) dark

red sandy loam to sandy clay loam (Monroe 2005). The average annual precipitation for

the test area is around 1340 mm. The average high and low temperatures in summer are

33.50C and 18.80C, respectively. The average high and low temperatures in winter are

10.60C and 3.50C.

Plant Material and Experimental Design

The study population consisted of 61 genetically-improved full-sib loblolly pine

families. The families were generated from 30 selected parents from the Atlantic Coastal

Plain of South Carolina and Georgia, the flatwoods of Florida and the Gulf Coastal Plain

of Mississippi and Alabama. Two slow-growing parents were included as connectors

with other studies (FBRC 2000). The 32 parents were mated in a partial diallel design

creating 70 full-sib families but just 61 full-sib families where in this two test. The

material was propagated at the International Paper Company greenhouse in Jay, Florida

(Baltunis et a. 2005).

The experimental design is an Alpha lattice with 4 complete replications per

treatment. Each replication had 1,120 and 1,100 trees at Site 1 and 2, respectively. Weed









control, pesticides and the addition of macro and micro nutrients constitute the intensive

silvicultural treatment. The tests were planted in 2002 with a chemical site preparation

prior to planting. At Site 1 the chemical site preparation was done with a combination of

triclopyr, glyphosate and imazapyr. Vegetation competition was controlled with directed

spray application of glyphosate during the first and second growing season. In May 2003

the test received a broadcast application of 280 kg ha-1 of diammonium phosphate.

During April 2004 560 kg ha-1 of 10-10-10 and micronutrients were applied and in June

2004 the test received 4.17 kg ha-1 of copper supplement. At Site 2, before the bed

preparation the area was broadcast sprayed with glyphosate. During the first year the site

was sprayed with sulfometuron methyl and later released with glyphosate applied with

backpack sprayers. The fertilizer application was applied before bedding preparation and

consisted of 11.2 kg ha-1 micronutrients blend and 902 kg ha-1 of 15-07-13.

The total number of clones tested was 941 in Site 1 and 868 in Site 2 (FBRC 2003).

This allowed us to compare the genetic performance of 30 elite parents, 61 full-sib

families, and about 900 clones within the full-sib families.

Traits Measured

Initiation and Cessation

Height growth increment was assessed to estimate timing of initiation and cessation

using repeated measurements during the 2004 growing season. Before the trees of Site 1

started their second growing season all the trees were marked on their east side with an

orange paint as near to the top as possible. The distance from the orange paint mark to

the top was measured and used as a reference. Consecutive measurements were taken

every fifteen to twenty days during the spring and fall for growth initiation and cessation

and every thirty to forty days during the summer for monitoring height increment. The









first and the last measurement were performed on day of year 44 and 323, respectively.

Four replications of each test (4440 trees) were measured. While the top of the trees

could be reached easily, measurements were accomplished using a tape graduated in cm

(Lufkin Executive thinline 2m W606PM). After May 2004 a T-form graduated pole

was used. The T form was used to place the tip of the tree under one of the T's arms with

the objective of having more accurate measurement knowing that the pole was exactly at

the top of tree. Height increment was measured to the nearest 0.1 cm. During 2004 the

State of Florida was hit by three major hurricanes. None of them hit the study sites

directly but their proximity affected Site 1, especially with flooding and wind damage.

Trees which were leaning greater than 20-25 degrees from the vertical were not included

in the determination of cessation. The final number of trees measured at Site 1 was

4,038. From late August to early December 2004 (day of year 243 to 348) measurements

for determining timing of growth cessation were done at Site 2, initially on 3,252 trees.

With the help of a trailer pulled by an All Terrain Vehicle (ATV) the top of the trees were

reached and the painted reference measurement was placed 20 cm from the tip. Site 2

was relatively unaffected by the hurricanes but many trees suffered from tip die-back

which reduced the cessation data. The final number of trees measured at Site 2 was

3,049.

Percent of cumulative height was calculated to observe the proportional distribution

of the height growth over the growing season using total second year increment and

periodic summer measurements (Allen and Wentworth 1993). The cumulative height

increment was plotted by day of year and the dates of height growth initiation and

cessation were estimated by interpolation to determine the dates of which 5% and 95% of









the total annual height were reached (Mirov et al. 1952; Hanover et al. 1963; Cannell and

Willett 1976; Jayawickrama et al. 1998). At Site 1 the second growing season duration

(D) was determined by subtracting the initiation date from the cessation date and the

average rate of shoot growth (ASGR) (cm day-) was calculated dividing 90% of the AHI

by D.

Flush Descriptors

Traits involving flush length (FLn), number of flushes (NF) and number of stem

units (NSU) were measured, in 2005 once the shoots were fully elongated. When those

traits were measured mean stem unit length (MSUL) and annual height increment

(AHIFLn) were calculated. AHIFLn was computed as the sum of the flush lengths of the

annual shoot. This height increment was slightly different from AHI described above.

The number of trees evaluated was 2,132 at Site 1 and 2,101 at Site 2. Flush length and

number of stem units were measured for each flush of the main leader. A 2.4 m ladder

was used to reach and measure the flush length and count the number of stem units. Each

flush whether predetermined or free growth is characterized by a whorl of branches at the

bottom followed by a sterile bract zone, the fertile bract zone (needle-fascicles) and

another whorl of branches (or branches buds) at the top. Thus, flush length was

measured from the whorl of branches at the bottom to the other whorl of branches at the

top with a graduated pole to the nearest 0.1 cm. Annual height increment was obtained

by adding the flush length of each cycle for each tree. Also the proportion ofAHIFLn

attributable to each flush (PFLn) was calculated by dividing the length of each flush by

the AHIFLn and multiplying the result by 100.

The term "stem unit" was introduce by Doak in 1935 and has been used by several

authors with different meanings since then (Critchfield 1985). Stem unit in this study is









as defined by Doak (1935): A pine stem unit is comprised of four components 1) a node,

2) the internode below it, 3) a lateral appendage at the node (usually a needle fascicle),

and 4) structures in the axial of the lateral appendage. The first three components are

always present. NSU are the number of needles and sterile bracts which are in a spiral

disposition along the flush or stem. One of the nondestructive ways to assess the number

of stem units is through the leaf arrangement (needle-fascicles and sterile bracts) on the

tree stem (phyllotaxis). Pinus species present phyllotactic parastichies (spiral or helix).

These can be illustrate as imaginary lines that join adjacent stem units (Doak 1935;

Kremer and Roussel 1982; Kremer et al. 1989, Fredeen et al. 2002) (Figure 2-1). Those

helical arrangements on each pine flush can be followed in either clockwise (left) or

counterclockwise (right) direction (Zagorska-Marek 1985; Fredeen et al. 2002) and are

also known as opposed parastichy pairs (Figure 2-1). The number of stem units was

determined by counting the stem units on one of the ascending parastichy (n) and

multiplying that number by the number of parastichies on each flush (np) (Allen and

Scarbrough 1970; Fady 1990 and Bridgwater 2004, personal communication) (Figure 2-

1, Equation [2-1]).

NSU =n*np [2-1]

where NSU are the number of stem units n are the number of stem units on a single

parastichy and np are the number of parallel parastichies

A permanent marker was used to follow the spirals from the bottom to the top of

the flush. To avoid systematic errors the same person evaluated the number of the stem

units at both sites.































Figure 2-1. Loblolly pine parastichy arrangement. A) The line marked in black shows a
clockwise parastichy. B) The lines in color show two opposing parastichies:
the clockwise in yellow and the counterclockwise in red. The numbers
illustrate a way to obtain the number of parastichies on each flush. For
example: counting the stem units in a clockwise manner (yellow) the number
of parastichies on that flush is five. Counting in the counterclockwise
direction the number of parastichies is eight, so for this flush the number of
opposing parastichies is 5:8. (Drawing adapted from Kremer and Roussel
1982).

Mean stem unit length (MSUL) was obtained by dividing the flush length (mm) by

number of stem units (NSU) (Equation 2-2).

MSUL = Flush length (mm) [2-2
NSU

Even though determining helical phyllotactic patterns (PPs) was not one of the

objectives of this study, the way that NSU were measured provided a pattern of

arrangement in terms of recognizable contact parastichies. Different helical phyllotaxis

series can be typified by the number of opposing parastichies and the value of the

divergence angle (angle between successive fascicles on the stem). The helical









phyllotactic series classification adopted in this study was the one proposed by Zagorska-

Marek (1985) (Table 2-1), who followed the earlier proposal of Richards (1951) and

differs little from Jean (1988). PPs were analyzed as an additional trait.

Table 2-1. Phyllostatic series identification.
Divergence Sequence of opposed
Phyllotactic patter angle (0) parastichy numbers
Monojugate pattern
Fibonacci (principal) 137.5 2:3:5:8...
First accessory 99.5 3:4:7:11 ..
Second accessory 77.9 4:5:9:14 ...
Third accessory 64.08 5:6:11:17 ..


Seventh accessory 132.2 3:8:11:19...

Multijugate patterns
Bijugy 137.5/2 2:4:6:10 ..
Trijugy 137.5/3 3:6:9:15 ...
Adapted from Zagorska-Marek (1985)

Statistical Analyses and Genetic Parameters


Phenological Traits

The phenological and growth variables were analyzed in ASREML (Gilmour et al.

2002). Analyses were first run for each propagule type and site separately. A parental

model was used to estimate the genetic variances components. Equations 2-3 and 2-4

show the linear models for cuttings and seedlings respectively.

Yijkim =u + R,+ incblkj + gcak + gcal + scakl + clone(k) + rgcak + rgcal + rscakl

+Eijklm [2-3]

Yijklmn is the measured trait of the mth clone within the k/th full-sib family in thejth
incomplete block within the ith replication.
pu is an overall mean
R, is the fixed effect of replication, i = 1,2,3,4
incblkj(,, is random incomplete block (0, Diag -2blk()
gcak and gcal are the random female (k) and male (/) general combining ability
respectively N (0, Adr2cA ) where A is the numerator relationship matrix
scaki is the random specific combining ability ~ NID (0, )C









clonem() is the random clone within full-sib family NID (0, &~oNE )
rgcak and rgca,l are the random replication by female and male general combining ability
and replication respectively N [0, Diag (AjEPxGC )]
rsca,kl is the random replication by SCA interaction ~ NID (0, &~EPxC )
syjklm is the random error term ~ NID (0, :RoR )


Yijkim =,u + R, + incblkj(, + gc g cal + scaki + rfamkl + jklm [2-4]

Yijkim is the measured trait of the mth seedling within the klth full-sib family in thejth
incomplete block within the ith replication.
pu is the seedling population mean
R, is the fixed effect of replication, i = 1,2,3,4
incblk,,,) is the random incomplete block ~ (0, Diag 2 ,cbk(,)
gcak and gcal are the random female (k) and male (1) general combining ability
respectively ~ N (0, AocA )
scaki is the random specific combining ability NID (0, &~ )
rfamnkl is the random replication by full-sib family ~ NID (0, :REPxFAM)
eykklm is the random error term ~ NID (0, :RoR )

The estimates of additive (VA) and total genetic variance for clonal (VG ) and

seedling (VG,) population were calculated by the Equations 2-5, 2-6 and 2-7 respectively.

VA =4 GA [2-5]
1 22 j 2 2 2 [2-6]
G= 2GCA + CA + CLONE[

VG =4 a4 2 +4a2 [2-7]

Equations 2-8 and 2-9 were used to compute the estimates of the phenotypic

variance for clonal (ViP ) and seedling (VPJ) population.

V (j 2 +2 12 j2 G2 +2 2Px [2-8]
P GCA 0SCA CLONE 2 REPxGCA xSCA ERROR


1 P = 2 ^ 2 ^ [2 -2
VPs =2 GCA +SCA + 00REPxFAM +0 ERROR


[2-9]









Individual tree-narrow-sense heritability (h2) and broad-sense heritability (H2)

were calculate using the estimated variance components for the phenological and growth

traits for each propagule type. Equations 2-10 and 2-11 were used for assessing clonal

heritabilities.


h2~A [2-10]
VPC

2= VG
H2 G [2-11]
VPC

Equation 2-12 and 2-13 were used for obtaining seedling heritabilities.


h2 [2-12]
VPS


H2 G~ [2-13]
PS

Standard errors for narrow and broad-sense heritabilities were estimated using

ASREML as a Taylor series approximation for the variance of a ratio (Gilmour 2002).

Atlantic Coastal Plain (ACC), Florida (FL), and Lower Gulf (LG) were the loblolly

pine provenances present in this study. The analysis of provenance effect was performed

using ASREML (Gilmour 2002). The mean of the population was partitioned into the

provenance effect since provenances effects were included as fixed variable in models [2-

3] and [2-4]. Least square means for the phenological and growth traits of each

provenance were calculated adding the estimated mean, the provenance effects and the

average of the replication values. The effects of the provenance and their standard errors

were also computed using ASREML (Gilmour 2002).









Genetic correlations among phenological traits and growth rate were calculated for

each propagule type and genetic component using Equation 2-14 (Falconer and Mackay

1996):

cov
r = v [2-14]
xy22 2


where cov is the genetic component covariance between two traits, and a and o2 are

the product of the genetic component variance for traits x and y, respectively. Standard

error for genetic correlations was estimated using ASREML (Gilmour 2002).

Differences between propagule types for shoot length and phenological traits were

calculated using ASREML (Gilmour 2002). The propagule types were considered

different when their F value was greater than F 00( 4)= 6.94.

Path coefficient analysis (Wright 1968) was used in order to determine the relative

contribution of D and ASGR to the AHI. The method has been fully described (Kremer

and Larson 1983; Kremer 1985; Bongarten 1986; Magnussen and Yeatman 1989;

Rweyongez et al. 2003). The following is a short summary of the method

The data is standardized by dividing each trait by its mean. With the

standardization each trait has a mean of 1 and makes it possible for the variances to be

compared when the path coefficients are computed (Bongarten 1986; Rweyongeza et al.

2003).

Shoot elongation (AHI) also can be described as the product of D and ASGR

AHI= (D)(ASRG) [2-15]

Applying a logarithmic transformation to equation 2-15 the resultant relationship









log(AHI)=log(D)+ log(ASRG) [2-16]

In terms of variances

2A +2 G +2 cov(D, ASRG) [2-17]
OAHI OD ARSG

cov(D, ASRG)
As the correlation of D and ASRG is: r(D,ARG) =co replacing
'D ASRG

cov(D,ASRG) by aDCAsRG(D,ARG) then equation 2-18 is obtained


AHI D 'ASRG + 2cDASRG r(D,ASRG) [2-18]

Replacing and dividing each term by oAHI in equation [2-17], equation [2-18] is obtained

2 2 2
PAHI =PD + PASRG + 2PD PASRG r(D,ASRG) [2-19]

where pAHI is equal to 1 because it is the path coefficient of log(AHI) to itself. pD and


PASRG are the path coefficients for log(D) and log(ARSG) respectively to log(AHI).

The relative contribution of D to AHI can be determined as

cD = PD rAHID) [2-20]

where cD is the degree of determination ofD to AHI and r(D,ARG) is the correlation

coefficient between AHI and D. The relative contribution ofASGR to AHI can be

calculated as

CASRG PASRG r(AHI,ASRG) [2-21]

where CASR is the degree of determination ofASGR to AHI and r(AHI,ARG) is the

correlation coefficient between AHI and ASGR.

D +CARG = 1 [2-22]









Flush Descriptors

The flush descriptors, FLn, NSU, MSUL, number of flushes of each shoot leader

(NF), PFLn, AHIFLn and second-year total height (TH2) traits were analyzed in ASREML

(Gilmour et al. 2002). Analyses were run for each propagule type and site separately. A

parental model was used to estimate the genetic variances components and the linear

model used for cuttings and seedlings were detailed in equations [2-3] and [2-4]

respectively. NSU and MSUL were analyzed for each flush. The numbers of replications

measured for shoot components were 2 for Site 1 and 3 for Site 2.

Genetic parameter (AV V; VG ~, VP ,, h2, andH 2) were calculated according

equations [2-5] to [2-13] respectively. Standard errors for narrow and broad-sense

heritabilities were estimated using ASREML (Gilmour 2002).

Provenance differences and genetic correlations were computed to explain

phenological traits.

Differences between propagule types were also computed for shoot components

and growth traits as for phenological traits using ASREML (Gilmour 2002). The

propagule types were considered different when their F value was greater than

F,0 (2,2) =19.0 for Site 1 and F, 0(2,3) =9.55 for Site 2.

Shoot components, PFLn, AHIFLn and TH2 traits were also analyzed across the two

sites separately by propagule type. The mixed model is described in equation [2-23] for

clones population and equation [2-24] for seedlings respectively. Different residual

variances were allowed by site.

Yijkimn =-u+ S, + Rj + inchk gca g ca,,+ scalm + clonen(im)+ sgca,l + \g/ +

sscailm+ sclonen(lm) + ',t + "it .. + rscalyim + Ejklmn [2-23]









Yijklmn is the measured trait of the nth clone within the Imth full-sib family in the kth
incomplete block within thejth replication of the ith site.
pu is the clonal population mean
S, is the fixed effect of site i=1,2
R, is the fixed effect of replication, i= 1,2j = 1,2,3,4
incblkk(j) is the random incomplete block (0, Diag !2zncblk(i)
gcal and gca,, are the random female (/) and male (m) general combining ability
respectively -N (0, Ao- ~ )
scam is the random specific combining ability ~ NID (0, OSA )
clonen(im) is the random clone within full-sib family ~ NID (0, ~LONE
sgca,l and %" /I are random site by replication by female and male general combining
ability and replication respectively NID (0, ITExGCA )
sscalm is the random site by SCA interaction ~ NID (0, SC^A)
sclonenm) is the random site by clone within full-sib family interaction NID (0,
^2
'SITExCLONE )
t 'iI, and <,'I .. are the random site by replication by female and male general
combining ability and replication interaction respectively N (0, AcA )
rsca,jlm is the random site by replication by SCA interaction NID (0, (R PxSA)
eyklmn is the random error term [0, Diag (-2 )]


Yijklmn =,u+ Si + Rij + incblkk(ij)+ gcal+ gcam+ scalm + sgcail + sgcaim +

sscailm+ rfanijlm + Eijklmn [2-24]

Yijklmn is the measured trait of the nth seedling within the Imth full-sib family in the kth
incomplete block within thejth replication and the ith site.
pu is the clonal population mean
T, is the fixed effect of site i=1,2
R, is the fixed effect of replication, i= 1,2j = 1,2,3,4
incblkk(j) is the random incomplete block (0, Diag mc2blk(i))
gcal and gcat,, are the random female (/) and male (m) general combining ability
respectively -NID (0, A &cA )
scam is the random specific combining ability -NID (0, Ca )
sgcal and g / .. are random site by female and male general combining ability
respectively NID (0, TExGCA
ssca,lm is the random site by SCA interaction NID (0, OTESCA )
rfamyim is the random site by replication by full-sib family interaction ~ NID (0,
2 \
:RKEPxFMI )
Eyklmn is the random error term ~ [0, Diag (60 RROR










From the across sites analyses type B correlations for each of the traits were

calculated. A type B genetic correlation gives us an indication of how consistently the

trait is expressed in two different environments (Yamada 1962). When the correlation is

near 1 the trait-by-environment interaction is small and genetic entries rank the same in

both environments. When the genetic correlation is low the genetic entries rank

differently in the two environments.

The formulae to calculate the type B correlation were the follow:

U2 2 2
r -- 2 GCA +SCA CLONE [2-25]
2 B- 2CA +CA +O2N +20U2 + 2 + 2
GCA SCA CLONE SITExGCA SITExSCA SITExCLONE

rB is the type B genetic correlation for clonal value across trials

2
r GCA [2-26]
rBGCA 2 2
'GCA + 'SITExGCA

rB is the type B genetic correlation for parents across the two sites


( 2 2
rBF,-LY ( GCA 2 SCA 2 [2-27]
2GCA SCA + SITExGCA +SITExSCA

rB y is the type B genetic correlation for full-sib families across trials


In order to estimated the degree of determination of the AHI by the number of

flushes (NF) and the average flush length (AvFLn) as well as the estimate the contribution

of the MSUL and the NSUto each flush length FLn, a path coefficient analysis (Wright

1968) was computed for each case (Bongarten 1986; Rweyongeza et al. 2003).

The FLn of each flush is the result of the product of NSU and MSUL and AHI can

be described as the product ofNF and AvFLn. With logarithmic transformation those

multiplicative relationships became additive. Following the steps described from









equations [2-16] to [2-19] we obtain for FLn and AHIFLn equations [2-28] and [2-29]

respectively

2 2 2
PFLnPNS UPMSuL + 2pNSu PsMSL rMSuL, NSU) [2-28]

PAHI PNF AFL + 2PNFPAvFLn r(NF,AvFLn) [2-29]

From [2-28] and [2-29] pFL and pAHIF are equal to 1 because they are the path

coefficients of log(FLn) and log(AHIJ ) with themselves. PNs and PMsuL are the

path coefficients for log(NSU) and log(MSUL) to log(FLn) as well as pNF and PAvFLn

are the path coefficients for log(NF) and log(AvFLn) to log(AHIL), respectively.

The relative contribution of NSU and MSUL to FLn, and NF and AvFLn to AHIFLn can be

determined with the equation [2-30], [2-31], [2-32] and [2-33] respectively

CNSU PNSU TrFLn,NSU) [2-30]

CMSUL = PMSUL r(FLn,MSUL) [2-31]

CNF = PNF (AHIL,,NF) [2-30]

CAvFLn = PAvFLn r(AHIF,,AvFLn) [2-31]

where CNS and c~sU are the degree of determinations of NSU and MSUL to FLn and

CNF and CAvFLn are the degree of determinations ofNF and AvFLn to AHIFLn. rFLn,NSU),


r MFLn,SUL), rrAHII,,NF), and r(AHIn, AvFLn) are the correlation coefficients between FLn and

NSU, FLn and MSUL, AHIFLn and NF, and AHIFLn and AvFLn, respectively.

Genetic correlations among shoot components traits were calculated for each

propagule type and genetic effect using equation [2-14] (Falconer and Mackay 1996).











Standard error for genetic correlations was estimated using ASREML (Gilmour 2002).

The number of trees involved in each analysis is detailed in Table 2-2.

Table 2-2. Number of trees involved in each of the analyses by site and propagule type.


Site 1 Site 2
Crmin1,- a Seedlings Ciii..- Seedlings


FLn


NSU, MSUL
Parastichy
pattern







NF
AHIFLn
TH2

Phenological
traits


1730
1729
1727
1702
1493
732
134

1727
1727
1727
1702
1493
732
134

1730
1729
1727
1702
1492
730
134

1727
1727
1769


1678
1674
1666
1635
1471
746
130

1657
1655
1651
1623
1464
746
129

1674
1670
1662
1631
1469
745
130

1657
1657
1680


3352 731 2432


Flush descriptors by
flush number














CHAPTER 3
RESULTS AND DISCUSSION

Phenological Traits

Least Square Means for Phenological Traits by Provenance and Propagule Type

Significant differences (p<0.05) between propagule types were found for all the

phenological and growth traits (Appendix A). For Site 1 the average difference for

initiation date for seedling and cutting was 4 days. In contrast to Site 1, Site 2 seedling

material had earlier cessation dates than cutting material.

Cuttings provenances were significantly different (p<0.05) for initiation, cessation

and duration at Site 1 and for cessation at Site 2, but were not significantly different for

ASRG and AHI (Table 3-1). ACC provenance height growth initiation started growing

latter than FL and LG which had the same least square mean initiation date. Although

LG and FL started together for both propagule types, FL provenance cuttings grew later

in the season while ACC and LG had stopped growing by a similar date. There were no

significant differences in cessation date for seedlings among provenances. Although

there were significant differences in initiation, cessation and duration for provenance for

Site 1, no significant differences were obtained for AHI. FL was the provenance with the

longest growing season and ACC had the shortest growing periods for both propagule

types. LG was the provenance with the smallest AHI, because of its lower ASRG. FL and

ACC presented similar initiation dates and ASRG. In Site 2 again FL is the provenance

which the latest cessation date. These results are in partial agreement with Jayawickrama

et al. (1998) on height growth pattern of loblolly pine in Southwest Georgia. They found









significant differences among provenance for height growth cessation but no significant

differences for height growth initiation. For Jayawickrama et al. (1998) Atlantic Coastal

Plain, Lower Gulf and Florida provenance grew until day 241, 233 and 248 in 1993 and

244, 240 and 253 in 1994, respectively. Also their Florida material (Gulf Hammock) had

the longest growing season and greatest height. McCrady and Jokela (1996), in South

Carolina, reported a mean bud-break Julian Date of 73 to 84 for their different families

and planting spacings. Those dates are in accordance with the ones found in this report.

Also the average shoot rate growth reported in this study for cuttings was in agreement

with McCrady and Jokela (1996) of 0.58-0.65 cm-day-1. The duration of the shoot

growth in this study in North Central Florida (Table 3-1) is shorter than the one reported

by McCrady and Jokela (1996) (191 versus 201 days).

Table 3-1. Least square means for second-year phenological traits and annual height
increments by provenances and propagule type for 2004 growing season in
Site 1 (North Central Florida) and Site 2 (Southwest Georgia).
INITIATION CESSATION DURATION ASRG AHI
(days) (days) (days) (cm day'1) (cm)
C S C S C S C S C S
Site 1
LG 79 84 248 263 170 180 0.56 0.67 108.9 121.3
FL 79 83 252* 266 174* 183* 0.65 0.72 128.7 131.2
ACC 84* 87* 247 261 165 175 0.65 0.72 121.0 125.8
Site 2
LG 269 255
FL 277* 257*
ACC 263 248

Note: LG, FL and ACC are Lower Gulf, Florida and Atlantic Coastal Plain provenances,
respectively. C= cuttings; S= seedlings.
Initiation and cessation are days after January 1 to complete 5 and 95% of total AHI.
(*) indicates significant differences between the provenances (p<0.05)

Provenances were also significantly different for shoot growth pattern during the

growing season. Least square means were calculated for each of the measurement days

(Figure 3-1) for average cumulative apical height growth increment and apical height

growth increment by propagule type and provenance. Fewer significant points in











seedlings than in cuttings are attributable to lower numbers of seedlings present in the


study (Table 2-2).


CUTTINGS


c,


>E
-5 -
E a)
EE
o)
0)


SEEDLINGS


50 100 150 200 250 300 50 100 150 200 250 300
Day of Year 2004 Day of Year 2004


Figure 3-1. Least square means for average cumulative apical height growth increment
and apical height growth increment by provenance and propagule type at Site
1 (North Central Florida). (+) indicates significant differences between
provenances (p<0.05).

Seedlings and cuttings have a similar general growth pattern for height increment


with two peaks, one later in the spring and the other in later summer. Even though no


significant difference between provenances were found for the second half of the growing


season for cumulative height increment, the cutting curve shape shows how cumulative


growth increment by provenance becomes distinct whereas for seedlings provenances


differences of cumulative height increment at the end of the growing season are subtle.









Peaks of height increment are larger in seedlings than in cuttings. It seems that the

differences in height increment occurred in cuttings during the second half of the growing

season are responsible for the evident (but not significant) differences in cumulative

height increment. Heritabilities values for cumulative height increment and height

increment are shown in Table 3-2 and 3-3 by day of measure.

Heritability Estimates

Height Growth Increment

Narrow sense heritability for incremental height growth was always greater for

cuttings than for seedlings except for dates 141 and 268 (Table 3-2). Seedling values for

broad sense heritability were more inconsistent than cutting values. Cuttings show a

declining trend after day 68 except for day 141 which was smaller than expected.

Narrow sense heritabilities also decreased during the growing season after day 68 and

cutting heritability values were more inconsistent than seedling values. Larger standard

errors are associated with seedlings than with cuttings heritabilities. After day 268

narrow and broad sense heritabilities for both cuttings and seedling become constant and

almost zero. The decreasing and small values of heritabilities are attributable to growth

cessation. There was little or no additive variance for day 68 (h2 was 0.00 and 0.07 for

seedlings and cuttings, respectively) but moderate non-additive variance for both

propagule types (H was 0.35 and 0.26 for seedlings and cuttings, respectively) for height

increment, cumulative height increment and cumulative percentage height increment.

The total genetic variance evaluated in H2 is primarily due to clonal variation; 2 cr is a

distant second while the SCA variance contribution is almost negligible (Table 3-2).









These contributions are also consistent for cumulative height growth increment (Table 3-

3) and average cumulative percent height growth (Table 3-4).

Table 3-2. Incremental height growth: narrow (h2) and broad-sense (H2) heritabilities on
measurement days during 2004 growing season by propagule type at Site 1
(North Central Florida).
Day Seedlings Cuttings
No.+ h2 H2 h2 H2 Clone/Vp* 2GCA/Vp* SCA/Vp*

68 0.00 (0.00) 0.35 (0.16) 0.07 (0.03) 0.26 (0.02) 0.218 0.035 0.011
88 0.22 (0.11) 0.26 (0.14) 0.25 (0.08) 0.40 (0.03) 0.259 0.124 0.016
141 0.17 (0.08) 0.17(0.08) 0.07 (0.03) 0.11 (0.02) 0.074 0.033 0.002
173 0.15 (0.13) 0.41(0.17) 0.21(0.06) 0.22 (0.03) 0.109 0.104 0.005
236 0.13 (0.09) 0.13 (0.09) 0.23 (0.06) 0.22 (0.03) 0.103 0.113 0.000
268 0.14 (0.10) 0.20 (0.15) 0.09 (0.04) 0.11 (0.02) 0.058 0.046 0.010
278 0.00 (0.00) 0.00 (0.00) 0.02 (0.01) 0.01(0.01) 0.000 0.008 0.006
299 0.00 (0.00) 0.12 (0.12) 0.01(0.01) 0.01(0.02) 0.000 0.007 0.003
323 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.02 (0.02) 0.021 0.000 0.003

+Day of the year 2004 when the height increment was recorded.
** Clone/Vp, 2GCA/Vp and SCA/Vp, are the relative contribution of clonal, GCA and
SCA variances to broad-sense heritability (H2). Standard errors are given in parentheses.

Cumulative and Cumulative Percentage Height Growth Increment

Cumulative broad sense heritability values (Table 3-3) were generally smaller for

cuttings than for seedlings. The decreasing pattern during the growing season is also

present for both narrow and broad-sense heritabilities for all traits except height growth

increment. After day 268 (end of the growing season) heritability values became

constant. Non-additive variance seems to be larger for seedlings than for cuttings, with

larger standard errors associated with seedlings than cuttings

For cumulative percentage of height growth the decreasing pattern in both narrow

and broad-sense heritability values started at day 88 and becoming close to zero after day

236.











Table 3-3. Cumulative height growth: narrow (h2) and broad-sense (H2) heritabilities on
measurement days during 2004 growing season by propagule type at Site 1
(North Central Florida).
Day Seedlings Cuttings


H2 Clone/Vp*


0.00 (0.00)
0.22(0.11)
0.18(0.10)
0.22 (0.12)
0.14(0.12)
0.21 (0.12)
0.19(0.12)
0.17(0.12)
0.11 (0.12)


0.35 (0.16)
0.31 (014)
0.28 (0.14)
0.31 (0.15)
0.24 (0.16)
0.23 (0.15)
0.22 (0.15)
0.21 (0.15)
0.23 (0.16)


0.07 (0.03)
0.24 (0.07)
0.09 (0.03)
0.14 (0.05)
0.19(0.06)
0.20 (0.06)
0.20 (0.06)
0.20 (0.06)
0.20 (0.06)


0.26 (0.02)
0.41 (0.03)
0.14 (0.02)
0.17(0.03)
0.19 (0.03)
0.20 (0.03)
0.19 (0.03)
0.19 (0.03)
0.20 (0.03)


0.218
0.274
0.096
0.101
0.087
0.087
0.083
0.082
0.084


2GCA/Vp* SCA/Vp*


0.035
0.120
0.043
0.070
0.095
0.099
0.100
0.102
0.102


0.011
0.018
0.000
0.002
0.004
0.008
0.009
0.010
0.009


Day of the year 2004 when the height increment was recorded.
* Clone/Vp, 2GCA/Vp and SCA/Vp, are the relative contribution of clonal, GCA and SCA
variances to broad-sense heritability (H2). Standard errors are given in parentheses.



Table 3-4. Cumulative percentage of height growth: narrow (h2) and broad-sense (H2)
heritabilities on measurement days during the 2004 growing season by
propagule type in Site 1 (North Central Florida).
Seedlings Cuttings


aJdy o'U.


H2 Clone/Vp* 2GCA/Vp*


0.00 (0.00)
0.33 (0.14)
0.31 (0.14)
0.20(0.11)
0.09 (0.09)
0.01 (0.04)
0.02 (0.05)
0.00 (0.00)


0.35 (0.17)
0.43 (0.15)
0.47 (0.17)
0.24 (0.16)
0.17(0.16)
0.01 (0.04)
0.02 (0.05)
0.00 (0.00)


0.05 (0.02)
0.18 (0.06)
0.20 (0.06)
0.15 (0.05)
0.02 (0.02)
0.00 (0.00)
0.00 (0.00)
0.00 (0.00)


0.14 (0.02)
0.27 (0.03)
0.21 (0.03)
0.19 (0,03)
0.08 (0.02)
0.05 (0.02)
0.03 (0.02)
0.02 (0.02)


0.115
0.148
0.105
0.117
0.046
0.036
0.025
0.018


0.026
0.090
0.100
0.075
0.012
0.000
0.000
0.000


SCA Vp*


0.003
0.030
0.003
0.000
0.017
0.011
0.007
0.005


Day of the year 2004 when the height increment was recorded.
* Clone/Vp, 2GCA/Vp and SCA/Vp, are the relative contribution of clonal, GCA and SCA
variance to the broad-sense heritability (H2). Standard errors are given in parentheses.


Phenological Traits and AHI

Little non-additive variance was present for cutting height growth initiation (Table


3-5). Height growth cessation had little genetic variance in cuttings and seedlings at Site


1. In contrast, for Site 2 seedling height growth cessation was highly controlled by non-


additive variance (h2is 0.02; H2is 0.58). More moderate values for narrow and broad-


sense heritabilities were present for cutting height growth cessation (h is 0.29; H2 is









0.39). This study also reports low narrow and broad-sense heritabilities for seedlings and

cuttings for growing season duration. Cutting growing season duration seemed to be

influenced by non-additive genetic variance. Narrow-sense heritabilities for initiation,

cessation and duration obtained in this study are smaller than those reported by Li and

Adams (1993) in 15 year-old pole-size Douglas-fir. They estimated strong narrow-sense

heritabilities for bud burst and bud set and low to moderate values for growing season

duration (h2 are 0.73, 0.81 and 0.17, respectively). ASGR was not influenced by non-

additive variance for cuttings. Seedling ASGR heritabilities are higher than cuttings

heritabilities. Clonal variation was the greatest contributor to the total genetic variance;

2crA made a small contribution while SCA variance contribution was almost negligible

(Table 3-5).

Table 3-5. Individual narrow (h2) and broad-sense (H2) heritabilities for phenological
traits and AHI by propagule type for the 2004 growing season in Site 1 (North
Central Florida) and 2 (Southwest Georgia)
Variable Seedlings Cuttings
h2 H2 h2 H2 Clone/Vp 2GCA/Vp SCA/Vp
Site 1
Initiation 0.40 (0.13) 0.40 (0.13) 0.29 (0.08) 0.39 (0.03) 0.228 0.143 0.018
Cessation 0.07 (0.07) 0.07 (0.07) 0.00 (0.00) 0.07 (0.02) 0.058 0.000 0.011
AHI 0.11(0.12) 0.23 (0.16) 0.20 (0.06) 0.20 (0.03) 0.084 0.102 0.009
Duration 0.10(0.07) 0.10(0.07) 0.02 (0.02) 0.08 (0.02) 0.060 0.008 0.007
ASGR 0.26 (0.14) 0.33 (0.16) 0.18 (0.06) 0.19(0.03) 0.090 0.093 0.009
Site 2
Cessation 0.02 (0.11) 0.58 (0.24) 0.22 (0.07) 0.34 (0.03) 0.216 0.110 0.017
Clone/Vp, 2GCA/Vp and SCA/Vp, are the relative contribution of clonal, GCA and SCA
variances to broad-sense heritability (H2). Standard errors are given in parentheses.


Correlations Among Phenological Traits.

Genetic correlations were not estimated for those components whose genetic

variance was 0.









Initiation-Duration Correlation

Genetic correlations between initiation and duration at Site 1 were significantly

strong and negative for both propagule types, which indicated that the material which

initiated height growth later tended to have a shorter growing season and the material

which had early height growth initiation tended to grow longer (Table 3-6). Phenotypic

and microsite initiation-duration correlations were negatively low and significant. Also

initiation-duration correlations for seedlings were in general lower than those for cuttings.

GCA initiation-duration correlation was the strongest negatively and significant

correlation.

Cessation-Duration Correlation

Cessation-duration correlations were significant and strongly positive. Phenotypic

and environmental cessation-duration correlations were positive and even larger than the

genetic correlations. The positive correlation between cessation and duration indicated

that the material with the latest cessation date will have the longest growing season.

Phenotypic and environmental correlations between initiation and cessation were

significant and low for both cuttings and seedlings. The clonal initiation-cessation

correlation was also low. The significant positive correlation between initiation and

cessation implies that the material which started growing later also stopped growing later

in the season and vice versa.

Initiation-AHI and Initiation-Cessation Correlations

For Site 1 the standard errors associated with initiation-AHI and cessation-AHI

genetic correlations were many times larger than the estimates whereas phenotypic and

environmental initiation-AHI and cessation-AHI correlation were positive low and

significant. Lower correlation values were estimated for cuttings than for seedlings and









cessation-AHI correlation were lower than initiation-AHI correlations. Positive

correlation for initiation-AHI meant that material which initiated later in the growing

season had larger height increments. At Site 2, standard errors associated with genetic

cessation-AHI correlation for seedlings were larger than the estimate also microsite

standard errors were larger than the estimated correlations for both propagule types. The

phenotypic and environmental correlations were low and positive, clonal and total genetic

correlation for cessation-AHI at Site 2 were moderate but with high standard errors.

Positive correlation for cessation-AHI indicates that material which grew longer in the

season had the largest AHI.

Initiation-ASRG Correlations

Phenotypic, environmental and genetic correlations for initiation-ASRG were

positive, moderate-to-low and significant for cuttings, except for the SCA correlations

where the standard error which was four times larger than the estimate (Table 3-6).

Seedling genetic correlations also had high standard errors whereas the phenotypic

correlations were positive, significant and moderate. Seedling microsite initiation-ASRG

correlation was also moderate, significant and negative. Positive correlations indicate

that materials with later initiation dates would have higher growth rate. The negative

correlation for microsite initiation-ASGR meant that a particular microsite promoting

early height growth initiation tended to promote higher growth rate.











Table 3-6. Genetic, phenotypic and environmental (microsite) correlations between
phenological traits and annual height increment (AHI) by propagule type for
2004 growing season in Site 1 (North Central Florida) and 2 (Southwest


Georgia).
Variables


Site 1


-0.49
rGCA (0.50)
0.66
rSCA (0.46)
0.29
rclone (0.11)
0.14
(0.10)
0.11
rPhenotypc 11
(0.02)
0.12
rMicrosite (0.02)


rGCA

rSCA

TClone
C
rGenetic

rPhenotypic

rMicrosite
Site 2
rGCA

TSCA

C rClone
rGenetic

rPhenotypic

rMicrosite


Cuttings Seedlings
C AHI D ASGR C AHI D


-0.91
(0.08)


-0.41
(0.10)
-0.60
(0.08)
-0.29
(0.02)
-0.21
(0.02)

0.84
(0.27)
0.97
(0.22)
0.77
(0.05)
0.73
(0.05)
0.93
(0.00)
0.95
(0.00)


0.49
(0.17)
0.18
(0.82)
0.21
(0.09)
0.35
(0.10)
0.38
(0.03)
0.40
(0.02)

0.26
(0.37)
0.12
(0.86)
-0.35
(0.14)
-0.14
(0.13)
-0.24
(0.02)
-0.26
(0.02)


-0.16
(0.33)




-0.11
(0.23)
0.13
(0.04)
0.18
(0.04)


0.25
(0.21)
0.36
(0.73)
0.06
(0.09)
0.16
(0.11)
0.29
(0.03)
0.35
(0.02)

0.56
(0.31)
0.32
(0.77)
-0.11
(0.17)
0.11
(0.13)
0.09
(0.02)
0.08
(0.02)





0.53
(0.24)
0.47
(0.20)
0.12
(0.05)
0.06
(0.04)


-0.71
(0.18)




-0.48
(0.20)
-0.25
(0.05)
-0.23
(0.04)

0.81
(0.12)




0.81
(0.12)
0.92
(0.01)
0.93
(0.01)


Note: I= Initiation; C=Cessation; D=Duration; ASRG=average shoot growth rate.
***Correlation could not estimated because U2 was 0.

(--) was not included in the model.
Standard errors are given in parentheses.


I


ASGR

0.38
(0.23)




0.38
(0.23)
0.42
(0.04)
-0.43
(0.03)


0.31
(0.44)




0.19
(0.26)
0.89
(0.13)
0.37
(0.04)

-0.23
(0.41)




-0.23
(0.41)
0.16
(0.04)
0.18
(0.05)



0.36
(0.24)


0.36
(0.24)
0.09
(0.04)
0.06
(0.04)


-0.45
(0.31)




-0.31
(0.23)
-0.23
(0.04)
-0.22
(0.04)









Cessation-ASGR Correlations

Genetic cessation-ASGR correlations were associated with large standard errors for

both propagule types. Phenotypic and environmental correlations for both cuttings and

seedlings were negative significant and low, which means that the material which

stopped growing early tends to have a higher growth rate. Phenological and growth

correlation results were in agreement with those reported by Li and Adam (1993) for

Douglas-fir. They found positive correlation between bud set and growth. Also they

reported negative moderate (-0.30 + 0.24) and negative low (-0.07 0.28) correlations

between bud burst and bud set with duration for their first year of analyses. For their

second year of analysis the duration-bud set correlation became a strong correlation

(-0.87 0.07). Ekberg et al. (1994) working with Norway spruce (Picea abies) seedlings

did not find any strong correlation between total height or shoot elongation with any of

the bud phenological traits or shoot elongation period. They also could not strongly

associate the shoot elongation period with bud burst and bud set.

Path Analysis

Table 3-7 presents the phenotypic and genetic path coefficients, correlation

coefficients and degrees of determination for the second-year AHI from duration and

average shoot growth rate for both propagule types. For both propagule types average

shoot growth rate was the principal contributor to AHI. The genetic and phenotypic

degree of determination of AHI by ASRG was almost 1 for cuttings and 0.86 and 0.72 for

seedlings. Both phenotypic and genetic correlations between AHI and ASRG were

positive strong and significant, indicating that material which has higher average shoot

rate growth has larger AHI.










Table 3-7. Values of phenotypic and genetic path coefficients, correlation coefficients
and degrees of determination for annual height increment (AHI) by growth
duration (D) and average shoot growth rate (ASRG) by propagule type for Site
1 (North Central Florida).
Path cotk ict' components Correlation Degree
AHI Path Coettk ient of
Prop. Components Coeff. 2 2 determination
type (Log) PD PASRG 2pp ID) r(DASR) CD
r(AHI,ASRG) CASRG
Phenotypic
Cuttings
D -0.053 -0.016
S 1.004 0.086 1.133 -0.215 00 -0.344 0 6
ASRG 0.907 0.965

Seedlings
D 0.036 0.134
S 0.999 0.139 1.113 -0.253 -0.322
ASRG 0.814 0.859

Genetic
Cuttings
D -0.098 -0.033
S 0.986 0.112 1.177 -0.303 --0.418
ASRG 0.891 0.967

Seedlings
D -0.134 -0.045
S 0.998 0.111 1.198 -0.310 4 -0.426
ASRG 0.656 0.718

Note: Path coefficient formula: pH p+ + 2D PASRG DRG)

*2D PASRG (D, ASRG) CD = PD r(AHI,ASRG)' ASRG = PASRG r(AHI,ASRG)
Numbers in bold are significant (p<0.05)

These results were in agreement with those obtained by Magnussen and Yeatman

(1989) in jack pine, who found that rate of shoot extension was a better predictor for

within-family shoot length than the duration of the shoot elongation. Some reports for

loblolly pine were in concordance with our results like: Perry et al. (1966), who through

regression analyses reported that growth rate accounted for approximately 60 percent of

the height growth variation while duration growth rate accounted for 30 percent.

McCrady and Jokela (1996) attributed the differences in AHI between families to the

height growth rate, and Boyer (1970) suggested that the flush growth variation in loblolly

is attributable to growth rate and not to length of the growth season.









Duration and average growth rate were moderately and negatively correlated

meaning that materials with shorter growing period had high growth rates. Phenotypic

and genetic correlations were significantly different except for the seedling genetic

correlation.

Flush Descriptors

Heritability Estimates

Significant differences (p<0.05) between propagule types were found for all the

flush descriptors (FLn, PFL, NSU and MSUL), NF and growth traits (AHIFLn and TH2)

(Appendix A).

On Site 1 additive variance was the primarily genetic variation associated with

seedlings and cuttings for most of the flushes for FLn, NSU, MSUL, and PFL (Table 3-8)

whereas non-additive genetic variance was the principal genetic variation associated with

NF and TH2 for seedlings. Additive genetic variance was the main genetic variation for

TH2 cuttings and AHIFLn for cuttings and seedlings. There was non-additive variance for

seedlings except for FLn flush 1, PFL flush 1 and 4, NSU flush 3 and MSUL flush 2.

On Site 2, as well, additive variance was the primarily genetic variation associated

with seedlings for most of the flushes by FLn, NSU, MSUL, and PFL (Table 3-9) whereas

non-additive genetic variance was the principal genetic variation associated with NF, TH2

and AHIFLn. There was less non-additive variance associated with NF, TH2 and AHIFLn in

cuttings than in seedlings. Seedlings had no non-additive variance except for flush 2 for

FLn, PFL and NSU.

Non-additive genetic variance was more frequent in with cuttings for Site 2 than for

Site 1 (Table 3-8 and Table 3-9). On Site 2 for several flushes and different traits, H2 was

at least twice as large as h2.









At both sites total genetic variance for cuttings was due primarily to clonal genetic

variance. Two times GCA variance was the next highest contributor to the total genetic

variance while SCA variance was generally small.

Seedling heritabilities were slightly larger and more inconsistent among the flushes

than cuttings and also had larger standard errors than cuttings, which is attributable to the

small seedling population (Table 2-2). Site 2 cutting heritabilities in general were

slightly larger than in Site 1. There was no clear pattern of decreasing/increasing

heritabilities values with the increasing/decreasing flush number for either propagule type

or site. Heritabilities for flushes 6 and 7 are probably not reliable due to the small

number of trees that produced 6 or 7 flushes.

NFAHIFLn and TH2 narrow and broad-sense heritabilities values were larger for

Site 2 than for Site 1 for both cuttings and seedlings (Table 3-8 and 3-9).

For both Site 1 and 2, additive genetic variance was the primary genetic variance

for seedlings and cuttings across site for most of the flushes for FLn, PFL, NSU and

MSUL. Across sites cuttings had little to no non-additive variance; for a few flushes non-

additive variance was twice as large as the additive variance.

Non-additive genetic variance was associated with NF, and seedlings TH2.

Additive genetic variance was the main genetic variance for AHIFLn and cutting TH2.

Across-site NF, AHIFLn and TH2 cutting heritability values were two to five times larger

than seedlings heritabilities values.











Table 3-8. Site 1 (North Central Florida): individual-tree narrow (h2) and broad-sense
(H2) heritabilities for growth and shoot components by propagule type for the


004 growing season.
Seedlings


2
Variable
by
flush #
1
2
3
FLn 4
5
6
7

1
2
3
PFL 4
5
6
7

1
2
3
NSU 4
5
6
7

1
2
3
MSUL 4
5
6
7

NF


h2

0.00 (0.00)
0.14 (0.10)
0.23 (0.12)
0.25 (0.15)
0.00 (0.00)
0.03 (0.00)


0.12 (0.13)
0.08 (0.08)
0.19 (0.10)
0.09 (0.13)
0.07(0.10)
0.73 (0.42)


0.00 (0.00)
0.13 (0.09)
0.12 (0.11)
0.13 (0.10)
0.00 (0.00)
0.00 (0.00)


0.10 (0.09)
0.08 (0.10)
0.42 (0.15)
0.28 (0.13)
0.27 (0.16)
0.52 (0.42)


H2

0.21 (0.26)
0.14 (0.10)
0.23 (0.12)
0.27 (0.22)
0.00 (0.00)
0.03 (0.00)


0.33 (0.23)
0.08 (0.08)
0.19 (0.10)
0.45 (0.30)
0.07(0.10)
0.73 (0.42)


0.00 (0.00)
0.13 (0.09)
0.19 (0.25)
0.13 (0.10)
0.00 (0.00)
0.00 (0.00)


0.10 (0.09)
0.11 (0.20)
0.42 (0.15)
0.28 (0.13)
0.27 (0.16)
0.52 (0.42)


Cuttings
2GCA
H2
VP
0.22 (0.04) 0.03
0.22 (0.04) 0.08
0.22(0.04) 0.10
0.17(0.04) 0.08
0.20(0.05) 0.11
0.12 (0.09) 0.05
0.00 (0.00) 0.00


h2

0.07 (0.03)
0.16(0.06)
0.19(0.06)
0.16(0.05)
0.21 (0.07)
0.10 (0.08)
0.00 (0.00)

0.17(0.06)
0.08 (0.04)
0.09 (0.04)
0.10(0.04)
0.13 (0.06)
0.14 (0.09)
0.00 (0.00)

0.12 (0.04)
0.13(0.05)
0.22 (0.07)
0.17(0.06)
0.15 (0.06)
0.00 (0.00)
0.00 (0.00)

0.11 (0.05)
0.10(0.06)
0.29 (0.08)
0.21 (0.06)
0.22 (0.08)
0.21 (0.08)
0.00 (0.00)


0.27 (0.04)
0.13 (0.04)
0.16(0.04)
0.13 (0.04)
0.15 (0.05)
0.21 (0.09)
0.00 (0.00)

0.20 (0.04)
0.21 (0.04)
0.33 (0.04)
0.17(0.04)
0.22 (0.04)
0.12 (0.09)
0.18(0.34)

0.16(0.04)
0.14 (0.04)
0.32 (0.04)
0.28 (0.04)
0.30 (0.05)
0.21 (0.08)
0.00 (0.00)


0.06 (0.12) 0.24 (0.22) 0.14 (0.07) 0.32 (0.04) 0.07

0.00(0.00) 0.00(0.00) 0.18(0.08) 0.31(0.06) 0.09

0.00 (0.00) 0.00 (0.29) 0.26(0.08) 0.20(0.05) 0.13

0.01 (0.08) 0.11 (0.26) 0.21(0.07) 0.22(0.04) 0.11


Note: FLn=flush length; PFL=flush contribution to annual height increment in percent;
NSU=number of stem units; MSUL=mean stem unit length; NF= number of flushes;
AvFL= average flush length; AHIFLn=annual height increment as summation of the flush
length; TH2=second year total height. Standard errors are given in parentheses.


Clone
V,
0.19
0.12
0.12
0.09
0.09
0.07
0.00

0.18
0.08
0.11
0.09
0.05
0.14
0.00

0.14
0.14
0.21
0.07
0.15
0.12
0.00

0.10
0.08
0.17
0.16
0.16
0.10
0.00

0.20


AvFL

AHI,,,


0.01 0.109











Table 3-9. Site 2 (Southwest Georgia): individual tree narrow (h2) and broad-sense (H2)
heritabilities for growth and shoot components by propagule type for 2004


growing season.
Seedlings


Variable
by
flush #
1
2
3
FLn 4
5
6
7

1
2
3
PFL 4
5
6
7

1
2
3
NSU 4
5
6
7

1
2
3
MSUL 4
5
6
7


0.10(0.09)
0.16(0.14)
0.00 (0.00)
0.16(0.11)
0.00 (0.00)
0.10(0.63)


0.14(0.11)
0.19(0.15)
0.00 (0.00)
0.12 (0.10)
0.06 (0.12)
0.28 (0.47)


0.09 (0.09)
0.16(0.15)
0.03 (0.07)
0.08 (0.08)
0.08 (0.12)
0.00 (0.00)


0.13(0.11)
0.03 (0.08)
0.28 (0.13)
0.05 (0.09)
0.36 (0.18)
0.00 (0.00)


0.10(0.09)
0.50 (0.26)
0.00 (0.00)
0.16(0.11)
0.23 (0.35)
1.00 (1.21)


0.14(0.11)
0.42 (0.25)
0.00 (0.00)
0.12 (0.10)
0.06 (0.12)
0.28 (0.47)


0.09 (0.09)
0.50 (0.26)
0.03 (0.07)
0.08 (0.08)
0.08 (0.12)
0.75 (1.29)


0.13(0.11)
0.03 (0.08)
0.28 (0.13)
0.05 (0.09)
0.36 (0.18)
1.00 (1.44)


S 2GCA
H2
VP
0.30 (0.04) 0.06
0.42 (0.04) 0.10
0.26 (0.04) 0.08
0.28 0.04) 0.10
0.28(0.05) 0.10
0.33 (0.09) 0.10
0.18(13.9) 0.00


0.13 (0.05)
0.20 (0.06)
0.16 (0.06)
0.19 (0.06)
0.21 (0.07)
0.20 (0.09)
0.00 (0.00)

0.13 (0.05)
0.22 (0.06)
0.10 (0.05)
0.16 (0.05)
0.16 (0.06)
0.11 (0.08)
0.00 (0.00)

0.14 (0.05)
0.17 (0.06)
0.18 (0.06)
0.09 (0.04)
0.11 (0.06)
0.03 (0.05)
0.00 (0.00)

0.18 (0.06)
0.20 (0.07)
0.29 (0.08)
0.26 (0.08)
0.22 (0.07)
0.16 (0.09)
0.00 (0.00)


NF 0.20 (0.15) 0.46 (0.25) 0.29 (0.08) 0.41 (0.04) 0.14


0.09 (0.09) 0.09 (0.09) 0.10 (0.05) 0.22 (0.05) 0.05


0.07(0.12) 0.44(0.27) 0.20(0.07) 0.33(0.04) 0.10


0.03(0.11) 0.53(0.27) 0.31 (0.09) 0.41 (0.04) 0.15


Note: FLn=flush length; PFL flush
NSU=number of stem units; MSUL
AvFL= average flush length; AHIFLn
length; TH2=second year total height.


contribution to annual height increment in percent;
=mean stem unit length; NF= number of flushes;
annual height increment as summation of the flush
Standard errors are given in parentheses.


0.30 (0.04)
0.40 (0.04)
0.20 (0.04)
0.28 (0.04)
0.25 (0.05)
0.31 (0.09)
0.59 (27.1)

0.32 (0.04)
0.39 (0.04)
0.26 (0.04)
0.21 (0.04)
0.28 (0.05)
0.21 (0.10)
0.33 (0.33)

0.23 (0.04)
0.34 (0.04)
0.39 (0.04)
0.40 (0.04)
0.38 (0.04)
0.46 (0.07)
0.00 (0.00)


Clone
V,
0.23
0.32
0.18
0.18
0.17
0.23
0.15

0.23
0.29
0.14
0.20
0.17
0.25
0.59

0.24
0.30
0.16
0.15
0.21
0.19
0.24

0.14
0.22
0.25
0.27
0.26
0.38
0.00

0.26


AvFL


AHITn


TH2









Narrow and broad-sense heritabilities values were in general lower for across-site

analysis than for single-site analyses. Individual-tree narrow and broad-sense

heritabilities for cuttings are slightly larger than narrow and broad-sense heritabilities for

seedlings.

These study findings are not in complete agreement with other studies of shoot

growth components. Heritability values for second-year total height are in concordance

with Paul et al. (1997) from two different factorial loblolly pine clonal tests. The

h2values from their two factorial tests were 0.08 and 0.26. H2 values ranged from 0.12 to

0.25 in their factorial tests.

In general, cutting heritability estimates in this study for second-year total height

were larger than those estimates for the components (FLn, NSU and MSUL) and almost

equal for NF. Heritabilities estimates for NSU and MSUL indicated that they are both

under similar genetic control. Several other studies reported greater heritability values

than the ones found in this study, with values ranging from 0.1 to nearly 1.0 for growth

and growth component traits in loblolly pine and other conifers (Kremer and Larson

1983, Bongarten 1986, Li etal. 1991; Li etal. 1992, Smith et al. 1993b, Kaya 1993,

Rweyongeza et al. 2003).

Type B Correlation

The stability of families and parents across site were compared for seedlings and

cuttings (Table 3-11). Also clonal stability across site was analyzed for cuttings.











Table 3-10. Across site individual narrow (h2) and broad-sense (H2) heritabilities for
growth and shoot components by propagule type for 2004 growing season for
Site 1(North Central Florida) and Site 2 (Southwest Georgia).


Variable
by
flush #
1
2
3
FLn 4
5
6
7
1
2
3
PFL 4
5
6
7
1
2
3
NSU 4
5
6
7

1
2
3
MSUL 4
5
6
7


Seedlings


S 2GCA
H2
V
0.12 (0.02) 0.03
0.14 (0.02) 0.06
0.13 (0.03) 0.06
0.14 (0.03) 0.05
0.17(0.03) 0.05
0.06 (0.03) 0.06
0.32 (0.12) 0.09
0.21 (0.03) 0.08
0.16 (0.03) 0.06
0.07 (0.02) 0.03
0.11 (0.03) 0.03
0.13 (0.03) 0.03
0.06 (0.03) 0.06
0.16 (0.12) 0.08
0.17(0.03) 0.05
0.13 (0.02) 0.04
0.23 (0.02) 0.08
0.19(0.02) 0.06
0.26 (0.03) 0.07
0.08 (0.04) 0.02
0.10 (0.19) 0.00


0.03 (0.04)
0.08 (0.03)
0.05 (0.04)
0.10(0.06)
0.00 (0.00)
0.00 (0.00)

0.24 (0.10)
0.15 (0.06)
0.02 (0.04)
0.10(0.07)
0.03 (0.07)
0.06 (0.02)

0.08 (0.07)
0.05 (0.02)
0.07 (0.03)
0.08 (0.05)
0.05 (0.04)
0.01 (0.14)


0.16(0.07)
0.07 (0.07)
0.28 (0.09)
0.14 (0.07)
0.18(0.07)
0.00 (0.00)


NF 0.05 (0.08) 0.11(0.12) 0.17(0.07) 0.26 (0.03) 0.09


0.00(0.01) 0.00(0.01) 0.05(0.03) 0.10(0.02) 0.03

0.04 (0.05) 0.04 (0.05) 0.21 (0.07) 0.22 (0.03) 0.10


0.04 (0.05) 0.11(0.12) 0.22 (0.07) 0.24 (0.04) 0.11


contribution to annual height increment in percent;
=mean stem unit length; NF= number of flushes;
annual height increment as summation of the flush
Standard errors are given in parentheses.


Note: FLn=flush length; PFL flush
NSU=number of stem units; MSUL
AvFL= average flush length; AHIFLn
length; TH2=second year total height.


0.10(0.07)
0.08 (0.03)
0.05 (0.04)
0.11 (0.08)
0.04 (0.09)
0.00 (0.00)

0.28 (0.10)
0.15 (0.06)
0.02 (0.04)
0.10(0.09)
0.14 (0.10)
0.00 (0.00)

0.27(0.11)
0.05 (0.02)
0.07 (0.03)
0.08 (0.05)
0.05 (0.04)
0.24 (0.29)


0.27 (0.09)
0.14 (0.09)
0.28 (0.09)
0.14 (0.07)
0.18(0.07)
0.00 (0.00)


0.06 (0.03)
0.11 (0.04)
0.12 (0.05)
0.10 (0.04)
0.09 (0.06)
0.11 (0.05)
0.18 (0.12)
0.17(0.06)
0.11 (0.04)
0.06 (0.03)
0.06 (0.03)
0.05 (0.05)
0.11 (0.05)
0.17(0.11)
0.11 (0.04)
0.08 (0.03)
0.15 (0.02)
0.13 (0.05)
0.14 (0.05)
0.05 (0.03)
0.00 (0.00)

0.13 (0.05)
0.15 (0.05)
0.26 (0.07)
0.14 (0.06)
0.17(0.07)
0.15 (0.06)
0.21 (0.15)


Clone
V,
0.09
0.08
0.07
0.09
0.11
0.00
0.23
0.11
0.11
0.03
0.08
0.08
0.00
0.08
0.12
0.09
0.15
0.11
0.19
0.06
0.06

0.10
0.06
0.14
0.12
0.12
0.00
0.12

0.16


0.07

0.11


0.11


0.17(0.03)
0.14 (0.03)
0.26 (0.04)
0.19 (0.03)
0.22 (0.04)
0.08 (0.03)
0.24 (0.14)


AvFL


AHITn


TH2











Table 3-11. Type B correlations for growth and shoot components by propagule type for
2004 growing season between Site 1 (North Central Florida) and Site 2


Variab
byflush


FLn








PFL








NSU








MSUL








NF


(Southwest Georgia).

le Seedlings
le
# r r
Parents

1 0.84 (0.88) 0.9
2 1.00(0.00) 1.C
3 0.83 (0.52) 0.8
4 0.65(0.31) 0.6
5 0.00 (0.00) 0.2
6 0.00 (0.00) 0.0
7 ---

1 0.94 (0.15) 0.9
2 1.00(0.00) 0.9
3 0.34 (0.68) 0.3
4 0.60 (0.32) 0.6
5 0.27(0.56) 0.5
6 0.00 (0.00) 0.0(
7 ---

1 0.94 (0.44) 0.9
2 1.00(0.00) 1.0
3 1.00(0.00) 1.0
4 0.78(0.38) 0.7
5 0.70 (0.67) 0.5
6 1.00(0.00) 1.0
7 ---

1 0.99(0.00) 0.9
2 0.47(0.38) 0.5
3 0.89(0.14) 0.8
4 0.78 (0.25) 0.7
5 1.00(0.00) 1.0
6 0.00 (0.00) 0.0
7 ---


0.36 (0.49) 0.32 (0.29)

1.00(0.00) 1.00(0.00)

0.89(1.33) 0.40(0.55)

1.00(0.00) 0.48(0.39)


BFamily


12 (0.46)
0o (0.00)
33 (0.52)
66 (0.30)
.8 (0.54)
0o (0.00)


4 (0.14)
I8 (0.22)
44 (0.68)
)0(0.31)
2 (0.35)
05 (0.14)


'7 (0.22)
0o (0.00)
0o (0.00)
'8 (0.38)
33 (0.52)
0o (0.00)


99 (0.00)
8 (0.30)
9 (0.14)
'8 (0.25)
0) (0.00)
0o (0.00)


rB r
Parens BFamily


rB
BClone


0.68 (0.12)
0.80 (0.08)
0.65 (0.12)
0.72 (0.13)
0.69 (0.12)
0.24(0.11)
0.98(0.13)

0.68 (0.08)
0.64(0.10)
0.43 (0.15)
0.51 (0.13)
0.59(0.13)
0.23(0.11)
1.00 (0.00)

0.78(0.11)
0.81(0.07)
0.94 (0.09)
0.97 (0.03)
0.96 (0.04)
0.49 (0.27)
0.20 (0.40)

0.82(0.12)
0.58(0.10)
0.73 (0.07)
0.60 (0.08)
0.67 (0.08)
0.25 (0.08)
0.99 (0.18)


0.59 (0.20)
0.69 (0.16)
0.79 (0.14)
0.63 (0.17)
0.455 (0.21)
0.72 (0.25)
0.95 (0.44)

0.93 (0.09)
0.70 (0.17)
0.66 (0.21)
0.485 (0.23)
0.37 (0.26)
0.72 (0.26)
1.00 (0.00)

0.82(0.13)
0.67 (0.18)
0.95 (0.01)
0.92 (0.08)
0.86 (0.12)
1.00 (0.00)
0.23 (0.00)

0.77 (0.14)
1.00 (0.00)
0.89 (0.07)
0.64 (0.16)
0.76(0.13)
0.93 (0.18)
0.97 (0.39)


0.72 (0.07) 0.76 (0.14) 0.73 (0.11)

0.82 (0.08) 0.59 (0.21) 0.55 (0.20)

0.81(0.09) 0.88 (0.08) 0.89 (0.08)

0.74 (0.08) 0.88 (0.10) 0.85 (0.09)


Note: FLn=flush length; PFL=flush contribution to annual height increment in decimal
equivalents; NSU=number of stem units; MSUL=mean stem unit length; NF= number of
flushes; AvFL= average flush length; AHIFLn=annual height increment as summation of
the flush length; TH2=second year total height. Standard errors are given in parentheses.


0.57(0.19)
0.61 (0.15)
0.78 (0.13)
0.59 (0.17)
0.52 (0.18)
0.72 (0.25)
0.95 (0.44)

0.91 (0.08)
0.60 (0.16)
0.74 (0.16)
0.42 (0.21)
0.55 (0.17)
0.72 (0.26)
1.00 (0.00)

0.80 (0.13)
0.58(0.16)
0.95 (0.01)
0.94 (0.07)
0.86 (0.12)
1.00 (0.00)
1.00 (0.00)

0.77 (0.13)
0.86 (0.11)
0.89 (0.07)
0.61 (0.15)
0.79 (0.11)
0.93 (0.17)
0.97 (0.34)


AvFL

AHJFL,

TH2









Growth and Shoot Components

Cutting NF, AHIFLn and TH2 showed consistent clonal, parental and family ranking

across site with type B correlations that ranged from 0.72 to 0.89 whereas seedling family

and parental rankings across site were quite inconsistent for NF, and for family AHIFLn

and TH2 were inconsistent. AvFL family and parental ranking across site was very

consistent for seedlings, but not for cuttings. Only clonal ranking was very consistent for

cuttings.

Flush Descriptors

The type B correlations reported in this study vary greatly from flush to flush, trait to

trait, and with propagule type. While FLn, PFL, NSU and MSUL seedling flush 1 and 2

exhibited high strong parent and family correlations, cuttings flush 1 and 2 parental and

family correlations were moderate, except for MSUL flush 2 for which cutting parental

and family correlation are higher than seedlings.

Seedling NSU and MSUL exhibited consistent family and parental (rB =0.70 to

1.00; rB, 0.78 to 1.00) rankings across both sites for most of the flushes except family

rankings for MSUL flush 2 and NSU flush 5 which were inconsistent with correlated

values of 0.47 to 0.58 for either parental and family type B correlations (Table 3-11).

Parent type B correlations for seedling FLn were high and ranged from 0.83 to 1.00 for

the first three flushes while the fourth flush had a moderated correlation and the remained

flushes where low (0.28) to uncorrelated. PFL showed similar behavior to FLn, but just

for the first two flushes. Flush 3 was low for both parental and family type B correlation.

The other PFL flushes had moderate to nil family and parental correlations.









The majority of the type B correlations for cuttings along the flushes and traits were

moderate to high ranging from 0.51 to 1. There were a small number of correlations

which were lower than 0.50 and most of them were clonal type B correlations. Few

flushes, flush 6 for example, exhibited consistent family and parental ranking across sites

and inconsistent clonal ranking across sites for all the traits analyzed.

Seedling family type B correlations estimated in this study for loblolly pine second

growing season were lower than those reported by Smith et al. (1993b), who reported

0.89 to 0.94 family type B genetic correlations for cycle length, number of cycles and

NSUper cycle. The moderate correlations (0.64 to 0.72) for total height, total number of

NSU and free growth stem unit length were more in accord to some of the correlations

obtained in this study. Li et al. (1992) reported genetic correlations across their

treatments (fertilized and irrigated against non- fertilized and non-irrigated) ranging from

0.61 to 0.80.

Path Analyses

Annual Height Increment with Number of Flushes and Average Flush Length

For sites 1 and 2 phenotypic and genetic path coefficients, correlation coefficients

and degree of determination for second year AHIFLn by NF and AvFL for both propagule

types are show in Table 3-12.

For both sites and propagule type average flush length was the principal contributor

to AHILn. At Site 1, the phenotypic degrees of determination of AHIJL, by AvFL were

0.80 for cuttings and 0.71 for seedlings. Seedling genetic path analysis could not be

assessed due to the very low variance of the genetic components. Both phenotypic and

genetic correlations between AHIJLn and AvFL were larger than AHIJLn and NF

correlations. AHIFL,-AvFL correlations were significant positive and moderate to strong









(0.63 to 0.86), indicating that material which has higher average flush length has larger

AHIFLn. AHIFLn-NF phenotypic correlations were positive moderate and significant for

both cuttings and seedlings whereas cutting genetic correlation was low and

nonsignificant. Cuttings and seedlings NF-AvFL phenotypic correlations were negative

low (-0.13 to -0.25) but significant, meaning that materials with fewer flushes had longer

flushes.

Cutting genetic NF-AvFL correlation was much higher (-0.59) than cutting

phenotypic correlations. On the other hand Site 2 cuttings and seedlings NF-AvFL

phenotypic correlation were strongly negative and significant (-0.78 and -0.74).

Although the seedling genetic correlation was also strong negative and significant, Site 2

cuttings genetic NF-AvFL correlation was low positive and significant. Site 2 cuttings

and seedlings AHIFLn-AvFL phenotypic correlation as well as Site 1 were moderate and

positive. Genetic AHIFLn-AvFL correlations were also moderate and positive but only the

cutting correlation was significant. AHIFLn.-NF correlation were low (0.003 to 0.26) and

nonsignificant for both cuttings and seedlings and for phenotypic and genetic

correlations; only the cutting genetic correlation was negative. The relatively larger

phenotypic degree of determination for AvFL to AHIFLn at Site 2 indicated a strong

contribution of AvFL to AHIFLn and a weak role for NF in that environment. Cutting

genetic path analysis was not estimated correctly PHIFL, (the path estimated of AHIFLn

with itself has to be 1 and in this case the number obtained was 4.34).

G6mez-Cardenas et al. (1998) found similar average number of flushes (4+1) in their

two year study on P. patula, but in the second year their annual height increment was

quite low (drought) due to shorter flushes. For G6mez-Cardenas et al. (1998) average







46


flush length and NSU were the most important components in the shoot elongation


pattern of P. patula.


Table 3-12. Phenotypic and genetic values for path coefficients components, correlations
coefficients, and degree of determinations for annual height increment AHIFLn
by number of flushes (NF) and average flush length (AvFL) by propagule type
for Site 1 (North Central Florida) and Site 2 (Southwest Georgia).
Path coeff components Correlation c oettic int Deree


Flush
p. Components
(Log)


Site 1
Phenotypic
Cuttings
NF
AF
AvFL
Seedlings
NF
AvFL
Genetic
Cuttings
NF
AvFL
Seedlings
NF
AvFL
Site 2
Phenotypic
Cuttings
NF
AvFL
Seedlings
NF
AvFL
Genetic
Cuttings
NF
AvFL
Seedlings
NF
AvFL


Fath
coeff.
P2
PAHI_


2 2 ppr,
PN PAvFL 2pyp
*


T(AHIJF, NF)

r(AHIJF ,AvFL)


1.01 0.47 0.86 -0.32



1.05 0.44 0.77 -0.16




1.11 1.02 1.61 -1.52


0.94 1.26 2.09 -2.41



0.99 1.52 2.53 -3.04




4.34 1.35 2.56 0.43



1.01 166 2.04 -2.69


0.003
0.64


-0.09
0.69

0.26
0.47


r(NF, AvFL)


of
determination
CNF
CAvFL


-0.25



-0.13


-0.59









-0.74



-0.78




0.12



-0.73


0.003
1.01


-0.11
1.10

0.33
0.67


Note: Path coefficient formula: p2A =p PFL + 2PNF PAvL 2NF.AvFL)

*2pNF PAFL rNF, AvFL) cNF = PNF r(AH FL,,NF) ; CAFL = PAVFL r(AH,, AVFL)

(---) Could not estimated because at least one of the variances was 0
Numbers in bold are significant (p<0.05).









Flush Length with Number of Stem Units and Mean Stem Unit Length.

For site 1 and 2 phenotypic and genetic path coefficients, correlation coefficients and

degree of determination for second year height FLn by NSU and MSUL for both

propagule types are show in Table 3-13, 3-14, 3-15 and 3-16.

At both sites in the phenotypic analysis and for both propagule types NSUwas by far

the principal contributor to FLn for the first and second flush with values of 1 for

seedlings and cuttings in Site 2 and with values of 0.72-0.75 for flush 2 for both cuttings

and seedlings in Site 1 (Table 3-13 and 3-14). From flush 4 onward, NSU and MSUL

contribute in almost the same proportion to the FLn. In Site 1 for the last flushes

evaluated in seedlings (5 and 6) the contribution of MSUL to FLn was slightly superior to

NSU (Table 3-13).

The phenotypic correlations between MSUL and NSU at Site 2 (Table 3-14) were

low to moderate negative and significant (-0.19 to -0.54) for cuttings and seedlings,

indicating that material with shorter MSUL had a larger number of NSU. The lowest

correlations were for flushes 4 and 5 for both propagule types. FLn-NSU correlations

were positive moderate to high and significant (0.49 to 0.93), indicating that material

with longer flushes had greater NSU. The results indicate that FLn-NSU correlations

decreased in value from flush 1 to 7 and FLn-MSUL correlations increase in value from

flush 1 to 7.

FLn-MSUL correlations were low and negative and not significant for the first two

flushes in cuttings and seedlings, except for seedling flush 2 where the correlation was

significant.







48



Table 3-13. Site 1 (North Central Florida): phenotypic values of path coefficients and
path components, correlations coefficients and degree of determination for
flush length (FLn) as the product of mean stem unit length (MSUL) and
number of stem unit (NSU) by propagule type.


Flush
Prop. Flush
tPop. Components
ype (Log)


Path
coeff.
2
PFLn


Path coeff. components*


PNSU PMSUL 2 py ry
*


Correlation coettic ieut


r(FLnf, NSU)
r(FLnMSUI)


r(ISuLNSU)


Cuttings


Flush
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL


0.95 1.48 0.41 -0.94

0.99 0.67 0.23 0.085

0.97 0.79 0.61 -0.43

0.99 0.69 0.55 -0.24

0.997 0.64 0.49 -0.13

0.98 0.45 0.55 -0.02

0.99 0.76 0.66 -0.44


Seedlings


Flush
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL


0.94 1.46 0.47 -0.99

1.00 0.72 0.26 0.02

0.97 0.76 0.71 -0.50

1.08 0.68 0.56 -0.16

1.04 0.46 0.68 -0.10

0.93 0.365 0.66 -0.09


Note: Path coefficient formula: p2 =pNS U pUL + 2PNu PMSUL rMSULNSU)

*2pNsu PMSUL 'rMSUL,NSU) CNSU = PNSU riFLn,NSU) CMSUL = PMSUL r(FLn,MSUL)
Numbers in bold are significant (p<0.05).


Degree
of
determination

CNSU

CMSUL


0.88
-0.07
0.88
0.57
0.67
0.53
0.70
0.59
0.73
0.62
0.67
0.74
0.64
0.58


-0.60

0.11

-0.31

-0.20

-0.12

-0.02

-0.31


1.07
-0.04
0.72
0.28
0.60
0.41
0.58
0.44
0.59
0.43
0.45
0.55
0.56
0.47


0.85
-0.04
0.88
0.55
0.61
0.55
0.71
0.65
0.60
0.76
0.18
0.78


-0.60

0.02

-0.34

-0.13

-0.09

-0.09


1.03
-0.03
0.75
0.28
0.53
0.46
0.58
0.48
0.40
0.63
0.11
0.63











Table 3-14. Site 2 (Southwest Georgia): phenotypic values of path coefficients and path
components, correlations coefficients and degree of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem unit (NSU) by propagule type.


S Flush
tPop. Components
type (Log)


Path
coeff.
2
PFLn


Path coeff. components

2 2
PNSU PMSUL 2 pypry,
*


Correlation c oettic iut


r(FLn, NSU)
r(FLn,MSUL)


r(MsUL,NSU)


Degree
of
determination

CNSU

CMSUL


Cuttings


Flush
1 NSU
MSUL
2 NSU
MSUL
3 NSU
MSUL
4 NSU
MSUL
5 NSU
MSUL
6 NSU
MSUL
7 NSU
MSUL


0.98 1.38 0.34 -0.74

1.00 1.21 0.17 -0.38

0.98 1.11 0.63 -0.76

1.00 0.65 0.58 -0.23

1.00 0.85 0.62 -0.47

1.03 0.96 0.95 -0.88

1.00 0.84 0.99 -0.83


Seedlings


Flush
1 NSU
MSUL
2 NSU
MSUL
3 NSU
MSUL
4 NSU
MSUL
5 NSU
MSUL
6 NSU
MSUL


0.99 1.29 0.25 -0.55

1.01 1.30 0.17 -0.46

1.00 1.02 0.51 -0.53

1.00 0.64 0.65 -0.28

1.00 0.72 0.62 -0.33

0.69 0.69 0.76 -0.75


Note: Path coefficient formula: p =p2S + pMSUL + 2PNSU PMUL rMSUL,NSU)

* 2pNSU PMSUL rMSULNSU) CNSU = PNSU rFLn,NSU); cMSUL = PMSUL r(FLn,MSUL)
Numbers in bold are significant (p<0.05).


The negative correlations between FLn-MSUL indicated that flushes with short


MSUL had longer flushes. This is in concert with flushes 1 and 2 where the flush length


was determined principally by NSU. At Site 2 FLn-MSUL correlation were no higher


-0.54

-0.42

-0.45

-0.19

-0.33

-0.46

-0.46


-0.48

-0.49

-0.37

-0.22

-0.25

-0.52


1.01
-0.01
1.06
-0.06
0.75
0.25
0.49
0.51
0.55
0.45
0.56
0.53









than 0.63. Site 1 phenotypic correlations followed the general pattern indicated for Site 2

but with some particularities. MSUL-NSU correlations were in general lower but for

flush 2 in both propagule type MSUL-NSU correlations were positive low and significant

and the contribution of NSUto second flush FLn was lower than for Site 2.

FLn-MSUL correlations for flush 2 were moderate positive and significant (0.55

and 0.57) for both seedlings and cuttings. FLn-MSUL phenotypic correlations for

seedling flushes 5 and 6 and for cutting flush 6 were large (0.74 to 0.78) while their

MSUL-NSU correlation were low and nonsignificant; signifying the increasing

contribution of MSUL to the FLn for those flushes. Seedling phenotypic flush 7 path

analysis at both sites could not be estimated (Table 2-2).

NSUwas reported to be the main contributor to total height by several authors like

Allen and Scarbrough (1970) in P. palustris, Kremer (1985) in P. pinaster, Guyon (1986)

in P. nigra, Kremer and Lascoux (1988) in P. pinaster, Magnussen and Yeatman (1989)

in P. banksiana, Fady (1990) in Abies cephalonica, Smith et al. (1993b) in slash pine,

G6mez-Cardenas (1998) in P. patula, and Raweyongeza et al (2003) in white spruce. A

mixed support for NSU and MSUL as primary contributors to flush length was reported

by Kremer and Larson (1983) in jack pine, Bongarten (1986) in blue spruce and Douglas

fir, and Kaya (1993) in Douglas fir

MSUL-NSU negative phenotypic and genetic correlations were reported in several

shoot components studies like Kremer and Larson (1983), Kremer (1985), Bongarten

(1986), Kremer and Lascoux (1988), Magnussen and Yeatman (1989), Fady (1990),

Kaya (1993) Smith et al. (1993b) and G6mez-Cardenas (1998) whereas Raweyongeza et

al (2003) reported genetic, phenotypic and environmental as very low but positive









correlations between MSUL and NSU. Guyon (1986) in P. nigra obtained just one

positive non significant MSUL-NSU correlation in the 6 years analyzed.

Genetic path analyses by flush for FLn as a product of MSUL and NSU could not be

estimated for all the flushes at both sites due to the low variances for some of the traits

(Table 3-15 and 3-16).

Cutting genetic path analyses for Site 2 followed the general characteristics

described for the phenotypic path analyses for cutting for flush 1 and 2 in which NSU

were the principal contributors for the FLn but after flush 3 MSUL became equal to or

more important than NSU as a determinate of flush length. MSUL degree of

determination values ranged from 0.50 to 0.90. Seedlings in Site 2 had the same genetic

pattern as cutting but MSUL reached only one extreme value (0.99 in flush 3). Seedling

genetic path for flush 5 analysis could not be estimated because at least one of the

component variances was almost 0.

At Site 1 the cutting genetic path analysis had similar values to the phenotypic path

analyses, even the low positive MSUL-NSU correlation for flush 2. Seedling genetic path

analyses could not be assessed for flushes 1, 2 and 6 because the variance of at least of

one of the components was almost 0. For flushes 3, 4 and 5 where the genetic path

analyses could be estimated, MSUL was by far the main contributor to FLn with a degree

of determination ranged from 0.74 to 1.38.

MSUL became more important in its contribution to FLn in the genetic analyses than

in the phenotypic to the point that it became the primary contributor for many flushes at

both sites for cuttings and seedling.







52



Table 3-15. Site 1 (North Central Florida): genetic values for path coefficients and path
components, correlation coefficients and degrees of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem unit (NSU) by propagule type.


Flush
Prop. Flush
tPop. Components
type (Log)


Path
coeff.
2n
PFLn


Path coeff. components*

2 2 2p r,
PNSU PMSUL 2'pypr
*


Correlation c oetic ieut


r(FLn, NSU)
r(FLn,MSUL)


r(MUL,NSsU)


Cuttings


Flush
NSU
MSUL
NSU
MSUL
NSU
MSUL
S NSU
MSUL
NSU
MSUL
NSU
MSUL
NSU
MSUL
Seedlings

Flush
NSU
MSUL
NSU
MSUL
NSU
MSUL
4 NSU
MSUL
NSU
MSUL
NSU
MSUL
MSUL


1.03 1.41 0.47 -0.85

0.98 0.70 0.21 0.07

1.02 1.22 1.08 -1.29

1.01 0.96 0.97 -0.92

1.03 0.77 0.70 -0.45

1.03 0.36 0.74 -0.07











0.89 0.67 2.55 -2.34

0.55 0.26 0.48 -0.19

0.96 0.18 1.59 -0.81


-0.52

0.10

-0.56

-0.48

-0.30

-0.07











-0.82

-0.21

-0.66


0.90
-0.05
0.73
0.26
0.58
0.55
0.51
0.58
0.55
0.52
0.33
0.64










-0.37
1.38
0.16
0.74
-0.14
1.16


Note: Path coefficient formula: p = u + PMSUL + 2PNs PMSUL rMSULNSU)

*2pNSu PsL r(MSULNSU CNSU = PNSU r(FLnNSU) CMSU = PMSUL rFLn,MSUL)
(---) Could not estimated because at least one of the variances was 0
Numbers in bold are significant (p<0.05).


Degree
of
determination
CNSU

CMSUL







53



Table 3-16. Site 2 (Southwest Georgia): genetic values for path coefficients and path
components, correlation coefficients and degree of determination for flush
length (FLn) as the product of mean stem unit length (MSUL) and number of
stem units (NSU) by propagule type.


S Flush
rop. Components
type (Log)


Path
coeff
P FLn


Path coeff components

2P U PsL pr,
PNSU PMSUL 2'pyP p
*


Correlation c o.tic ieut


r(FLn, NSU)
r(FLn,MSUL)


r(MUL,ANSU)


Degree
of
determination

CNSU

CMSUL


Cuttings


Flush
1 NSU
MSUL
2 NSU
MSUL
3 NSU
MSUL
4 NSU
MSUL
5 NSU
MSUL
6 NSU
MSUL
7 NSU
MSUL

Seedlings
Flush
1 NSU
MSUL
2 NSU
MSUL
3 NSU
MSUL
4 NSU
MSUL
5 NSU
MSUL
6 NSU
MSUL


0.99 1.51 0.24 -0.76

0.99 1.34 0.16 -0.51

0.95 1.26 1.12 -1.43

1.02 0.46 0.92 -0.36

0.99 0.98 0.98 -0.96

0.99 0.53 1.36 -0.90

1.26 0.62 0.68 -0.04


1.06 1.96 0.34 -1.25

0.99 1.48 0.13 -0.62

0.98 1.34 2.31 -2.67

1.01 0.27 0.43 0.31



0.79 0.27 0.40 0.12


Note: Path coefficient formula: p2 =pu + PSUL + 2PNSU PMSUL rMSULNSU)

*2pNsu PMSUL rMSUL,NSU) CNSU PNSU r(FLn,NSU) ; CMSUL =PMSUL r(FLn,MSUL)
(---) Could not estimated because at least one of the variance was 0
Numbers in bold are significant (p<0.05).


Seedling results have to be viewed with some caution due to the small seedling


sample size. Therefore, these results are in agreement with those reported by Bongarten


(1986), who concluded that the degree of contribution of MSUL and NSU to FLn


depended, among other factors, on the type of the data considered (phenotypic, genetic or


-0.63

-0.55

-0.60

-0.28

-0.49

-0.53

-0.03


-0.76

-0.71

-0.76

0.46



0.18









environmental). His results within Douglas-fir and blue spruce provenances were that

MSUL and NSU contributed equally to flush length phenotypic variation. For genetic

variation MSUL was the primarily component for FLn in blue spruce while NSUwas for

environmental. On the other hand Rweyongeza et al. (2003) reported that the NSU

degree of determination was larger than MSUL under genetic, phenotypic and

environmental analyses. Bridgwater (1990) reported that some loblolly pine families

might show superior height increment due to greater number of stem units while other

families depend more on the greater elongation of the stem units. Also Kaya (1993)

reported for Douglas-fir seedlings that MSUL explained nearly two-third of the free

growth in an inland population while NSU explained coastal population free growth.

Bailey and Feret (1982) working with loblolly pine and hybrids from P. rigida x taeda

result were in agreement to those of this study where MSUL was more important for free

growth flush length than NSU and NSUwas the dominating factor for fixed growth.

Cannell (1978) also reported that MSUL tended to be a larger component free growth

(summer flushes) than for the first flush.

Least Square Means for Provenance for FLn, PFL, NSU and MSUL

Significant differences (p<0.05) between propagule type were found for all the

morphological and growth traits (FLn, NSU, MSUL, NF and AHIFL) (Table A-3 in

Appendix A).

FL was the only provenance which demonstrated significant differences for NF for

both propagule types at Site 1. Although, all provenances were significantly different for

NF at Site 2, LG provenance had the highest NF. The Georgia site had higher AHIFL

values for all the provenances and propagule types than Site 1. FL cuttings were

significantly different for AHIFL at Sites 1 and 2 (Figure 3-2).












SITE 1 SITE 2
7-
I CUTT
6 SEED
+ +
m 5-

4
-0
E lo
Z 2


0-
200 -
C)
S150

10 I0

50


LG FL ACC LG FL ACC
PROVENANCE PROVENANCE
Figure 3-2. Least square means for number of flushes (NF) and annual height increment
as a summation of flush length (AHIFL) for the 2004 growing season by
propagule type at Site 1 (North Central Florida) and Site 2 (Southwest
Georgia). (+) indicates significant differences among provenances (p<0.05).

Few flushes were coincidently significantly different for provenances for both

cuttings and seedlings for the same trait.

Figures 3-3 and 3-4 describe graphically the results from the path analyses for flush

length as a product of MSUL and NSU. After flush 3 FLn had the tendency for MSUL to

be a major contributor while NSU is the major importance.

Site 2 seedlings had by far the largest values of FLn and NSU for flush 1 than

cuttings (Figure 3-3 and 3-4).

At both sites seedlings and cuttings had different patterns for all of the traits

analyzed except for MSUL at Site 2. Seedlings trend to have higher values for all the

traits from 3 and on while cuttings present lower values after flush 3.













SEEDLINGS


SITE 1


SITE 2
+ -e LG
-a- FL
+- ACC









SITE 1


SITE 2 Q +


0 1 2 3 4 5 6 7
Flush number


1 2 3 4 5 6 7 8
Flush number


Figure 3-3. Least square means for flush length (FLn) and flush length contribution
(PFL) by propagule type at Site 1 (North Central Florida) and Site 2
(Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic
Coastal Plain provenances, respectively. (+) indicates significant differences
between the provenances (p<0.05).


CUTTINGS















SITE 1
L-- LG
-12 FL
--- ACC



+ + +





SITE 2 3


0 1 2 3 4 5

Flush number


6 7


1 2 3 4 5 6 7

Flush number


Figure 3-4. Least square means for number of stem units (NSU) and mean stem unit
length (MSUL) by propagule type at Site 1 (North Central Florida) and Site 2
(Southwest Georgia). LG, FL and ACC are Lower Gulf, Florida and Atlantic
Coastal Plain provenances, respectively. (+) indicates significant differences
between the provenances (p<0.05).


250

200


CUTTINGS


SEEDLINGS









Provenance demonstrated different shoot elongation patterns. The FL provenance

had higher growth at the beginning of the growing season while ACC and LG growth was

slightly higher than FL seed source after the second flush. Length of the early flushes is

what conferred a significant advantage for FL cutting over the other seed sources. LG

provenance had the lowest values for NSU and the largest values of MSUL at both sites,

suggesting that for this provenance MSUL was the most important contributor to flush

length.

There were no significant differences for provenances for flush 1 for any of the

morphological traits analyzed exceptMSUL at Site 2. Values for flush 1 were very

similar for the all provenances for all traits.

Phyllostatic Patterns

Phyllostatic patterns demonstrated little genetic variance. Narrow and broad-sense

heritability for single site and across-site analyses were extremely low (Appendix C).

Similarly, Kremer et al (1989) did not find genetic variability among P. pinaster, P.

banksiana and, P. nigra Arn. ssp. nigrican populations or families for phyllostatic traits.

Fibonacci series (3:5:8:13...) were present for 82.5 % of the trees at Site 1 and for

87.9 % of the trees at Site 2. The second most common series was the principal bijugate

(4:6:10...) with 12.0% at in Site 1 and 8.3 % at Site 2. First accessory of the monojugate

series (4:7:11...) occurred at just 5.5 and 3.2 % at Site 1 and 2, respectively. The

principal trijugate series (3:6:9:15...) were present in 0.6 % of the trees at Site 2 and 0%

at Site 1 (just 2 trees). At Site 2 one "foxtail" tree had the tetrajugate series (4,8,12...).

The phyllostatic pattern survey for propagule type separately gave similar results as

the general, except one for the seedling population at Site 1 (Table 3-17).










Table 3-17. Frequency of phyllostatic series by propagule type in Site 1 (North Central
Florida) and 2 (Southwest Georgia)
Site 1 Site 2
Pyllostatic series Seedlings C1, I, Seedlings C1,1 ,I,
(%0) (0%) (%0) (0%0)
Monojugate pattern
Fibonacci 65.1 86.1 81.0 89.3
First accessory 22.0 9.7 15.1 6.9
Multijugate patterns
Bijugy 12.9 4.2 2.8 3.2
Trifugy 0.0 0.0 1.1 0.5

These frequencies were comparable to the proportions obtained by Kremer and

Roussel (1982); Kremer et al. (1989), Zagorska-Marek (1985) and Fady (1990) in P.

pinaster, P. banksiana, P. nigra Am. ssp. nigricans, Abies balsamea, and A. cephalonica,

respectively.














CHAPTER 4
CONCLUSIONS

Rooted cuttings differed from seedlings for all phenological and morphological traits

that were analyzed in this study. This indicates that regardless of the fact that both

propagule types were from the same genetic material the apparent differences in plant

architecture and physiological age between them results in different morphological and

phenological behavior.

Phenological traits

The results of this study indicated that the average growth rate per day was the most

important variable in determining second-year annual height increment. The contribution

of growing season duration to second-year annual height increment was negligible.

Although significant differences were found among propagule types and seed sources for

timing of initiation and cessation these traits were not important contributors to annual

height increment. Because average shoot growth rate and growing season duration were

low negatively and significantly correlated, growing season duration is a trait that has to

be considered because at the same growth rate a longer growing season can result in a

difference in height increment. A longer growing season may also adversely affect FL

material in cooler environment by increasing frost risks.

The narrow and broad-sense heritability estimates for the different dates for height

growth increment during the growing season were moderate and decreased from

initiation date to cessation date, becoming constant and almost zero for both propagule

types after day 268, increment decrease.









Morphological characters

Average flush length was the principal contributor to total annual height while

number of flushes had a minor contribution. In our results the most important

contribution of number of flushes to total annual height was at Site 2 for seedling

material being responsible for 30% of the annual height increment. NF and AvFL were

negatively strongly to moderately and significantly correlated. These results indicate that

selecting genetic material for height increment would increase average flush length with

minor changes in number of flushes.

NSU was by far the most important phenotypic trait for the length of the three first

flushes, and its contribution decreased in subsequent flushes with an increase in the

MSUL contribution to flush length until reaching to a 1:1 relationship. The genetic

contribution of MSUL to flush length was relatively larger than the phenotypic

contribution becoming more important than NSU after flush 3, especially for seedlings.

MSUL and NSU were negatively moderately and significantly correlated. The NSU

and MSUL flush length correlations varied greatly depending on the flush and the

relationship of NSU and MSUL to flush length.

Despite MSUL and NSU being negatively correlated and under low genetic control,

both were important determinants of flush lengths and flush length is an important

determinant of annual height increment. Thus, both are indirectly important for the

maximization of annual height increment. Selection of individuals with high values of

NSU and MSUL would improve annual height growth but comparing heritabilities

choosing for height growth directly would be more efficient.






62


Provenances demonstrated different shoot elongation patterns. FL provenance had

the highest growth at the beginning of the growing season while ACC and LG growth was

slightly greater than FL seed source after the second flush. Length of early flushes

appeared to confer a significant advantage for FL cutting over the other seed sources.

Phyllostatic patterns had low genetic variability with extremely low narrow and

broad-sense heritabilities.




























APPENDIX A
DIFFERENCES BETWEEN PROPAGULE TYPES










Table A-1. Significance levels (p-values) between propagule types for annual height
increment and phenological traits at Site 1 (North Central Florida) and Site 2
(Southwest Georgia).
Significant level
Variable between propagule
type
Site 1
Initiation <0.000001
Cessation <0.0000001
Duration <0.0000001
ASGR <0.00001
AHI <0.00001
Site 2
Cessation <0.0000001
AHI <0.000001
ASGR=average shoot growth rate; AHI=annual height increment.

Table A-2. Significance levels (p-values) between propagule types for height increment,
average cumulative height increment and average percentage cumulative
increment at Site 1 (North Central Florida) and Site 2 (Southwest Georgia).
Average Average
Average
Height cumulative percentage
Variable cumulative
increment height
incheight
incrementincrement
increment
Site 1
Day
68 <0.001 <0.001 <0.001
88 <0.001 <0.001 <0.001
141 <0.0001 <0.00001 <0.00001
173 <0.0001 <0.00001 <0.00001
236 <0.00001 <0.00001 <0.0000001
268 <0.001 <0.00001 <0.000000001
278 <0.001 <0.00001 <0.0000000001
299 <0.1 <0.00001 <0.000000001
323 <0.01 <0.00001
Site 2
Day
256 <0.00001 <0.00001 <0.0001
266 <0.0001 <0.0001 <0.0001
273 <0.001 <0.01 <0.000001
294 <0.001 <0.01 <0.00001
321 <0.001 <0.001 <0.00001
349 <0.001 <0.001 <0.00001










Table A-3. Significance levels (p-values) between propagule types for growth and shoot
components at Site 1 (North Central Florida) and Site 2 (Southwest Georgia).
Variable
by Site Site 2
flush No
FLn


PFL


NSU


MSUL
1
2
3
4
5
6

NF

AvFL

AHIFLn


<0.001
<0.01
<0.01
<0.001
<0.001
<0.01

<0.001
<0.01
<0.001
<0.001
<0.001
<0.01

<0.01
<0.01
<0.001
<0.001
<0.001
<0.01

<0.001
<0.001
<0.01
<0.001
<0.001
<0.001

<0.001

<0.001

<0.001


<0.0001
<0.00001
<0.000001
<0.00001
<0.00001
<0.00001

<0.0001
<0.0001
<0.000001
<0.00001
<0.00001
<0.00001

<0.0001
<0.0001
<0.00001
<0.00001
<0.00001
<0.000001

<0.00001
<0.000001
<0.00001
<0.00001
<0.00001
<0.00001

<0.000001

<0.00001

<0.000001


TH2 <0.001 <0.000001
Note: FLn=flush length; PFL=flush contribution to annual height increment in
percentage; NSU=number of stem units; MSUL=mean stem unit length; NF= number of
flushes; AvFL= average flush length; AHIFn=annual height increment as summation of
the flush length; TH2=second year total height.














APPENDIX B
SECOND-YEAR PHENOTYPIC, GENETIC AND ENVIRONMENTAL
CORRELATIONS BETWEEN FLUSH LENGTHS (FLN), NUMBER OF STEM
UNITS (NSU) AND MEAN STEM UNIT LENGTH (MSUL) BY FLUSH











Table B-1. Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite) correlations between flush length (FLn) by flush for 2004 growing
season.


Flush
2 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
3 rGCA


r( I
rGenetie
rPhenotypie
rMicrosite
4 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
5 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite
6 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
7 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite


1
0.63 (0.19)


0.51 (0.15)
0.52(0.11)
0.40 (0.02)
0.37 (0.03)
0.25 (0.26)


0.07 (0.16)
0.12(0.13)
0.13 (0.03)
0.14 (0.04)
0.10(0.28)


-0.06 (0.19)
-0.02 (0.15)
0.17(0.03)
0.21 (0.04)
-0.12 (0.29)


-0.17 (0.20)
-0.15 (0.15)
0.06 (0.03)
0.12 (0.04)
-0.84 (0.24)


-0.47 (0.31)
-0.55 (0.23)
-0.16 (0.23)
-0.08 (0.06)








-0.01 (0.11)


FLn-FLn correlations
2 3


0.50 (0.20)
-0.03
0.88 (0.20)
0.70 (0.12)
0.20 (0.03)
0.05 (0.04)
0.17(0.26)


0.44 (0.20)
0.31 (0.15)
0.12 (0.03)
0.04 (0.04)
0.15 (0.27)


-0.15 (0.20)
-0.02 (0.15)
-0.13 (0.04)
-0.15 (0.04)
-0.61 (0.24)


-0.56 (0.28)
-0.55 (0.19)
-0.40 (0.06)
-0.39 (0.05)


0.93 (0.05)


0.37 (0.17)
0.61 (0.10)
0.43 (0.02)
0.38 (0.03)
0.81 (0.11)


0.15 (0.19)
0.45 (0.13)
0.28 (0.03)
0.24 (0.04)
0.57 (0.25)


0.21 (0.30)
0.35 (0.20)
0.22 (0.04)
0.20


4



























0.83 (0.10)


0.68 (0.16)
0.75 (0.10)
0.48 (0.02)
0.42 (0.03)
0.62 (0.28)


0.90 (0.43)
0.79 (0.27)
0.16 (0.04)
0.04 (0.06)


1.00 (0.09)


0.83 (0.48)
0.91 (0.23)
0.55 (0.03)
0.47 (0.04)


-0.29 (0.10) 0.09 (0.10) -0.07 (0.10) 0.18(0.10) 0.37 (0.09)


Note: (---) Correlation could not be estimated because of variances which were 0.











Table B-2. Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite) correlations between numbers of stem units (NSU) by flush for
2004 growing season.


Flush
2 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
3 rGCA


r( I
rGenetie
rPhenotypie
rMicrosite
4 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
5 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
6 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
7 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite


1
0.30 (0.24)


0.49 (0.17)
0.42 (0.13)
0.39 (0.02)
0.38 (0.03)
0.49 (0.18)


0.30 (0.13)
0.38(0.11)
0.38 (0.03)
0.38 (0.03)
0.55 (019)


0.38 (0.20)
0.43 (0.13)
0.29 (0.03)
0.25 (0.03)
0.66 (0.17)


0.38 (0.17)
0.48 (0.12)
0.32 (0.03)
0.28 (0.04)
0.65 (0.22)


0.54 (0.27)
0.57 (0.20)
0.25 (0.04)
0.17(0.06)








0.23(0.11)


NSU-NSU correlations
2 3


0.80(0.12)
0.73 (0.63)
1(0.14)
0.91 (0.08)
0.45 (0.02)
0.29 (0.03)



0.83 (0.14)


0.21 (0.02)
0.06 (0.03)
0.47 (0.23)


0.66(0.19)
0.57(0.13)
0.19(0.03)
0.07 (0.04)


0.44 (0.32)
0.32(0.10)
-0.04 (0.03)
-0.13 (0.06)


0.38 (0.43)


0.13 (0.15)
-0.01 (0.10)
-0.04 (0.12)


0.91 (0.07)
0.00 (1)
0.82 (0.12)
0.82 (0.06)
1(0.08)
0.47 (0.03)
0.84(0.10)


0.80 (0.11)
0.80 (0.07)
0.44 (0.03)
0.30 (0.04)



0.49 (0.18)
0.31 (0.12)
0.24 (0.03)
0.22 (0.06)


0.84 (0.50)


0.20 (0.12)
0.15 (0.08)
0.14 (0.11)


0.97 (0.04)


1(0.17)
1 (0.08)
0.60 (0.02)
0.44 (0.03)



0.95 (0.24)
0.70(0.18)
0.38 (0.03)
0.32 (0.05)


0.87(0.16)
0.87(0.17)
0.50 (0.03)
0.44 (0.05)


0.26(0.08) 0.28(0.10) 0.28(0.09)


Note: (---) Correlation could not be estimated because of variances which were 0.








69



Table B-3. Site 1 (North Central Florida): cuttings genetic, phenotypic and environmental
(microsite)correlations between mean stem unit length (MSUL) by flush for
2004 growing season.


Flush
2 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
3 rGCA


r( I
rGenetie
rPhenotypie
rMicrosite
4 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
5 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite
6 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
7 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite


1
0.64 (0.18)


0.34 (0.23)
0.46(0.15)
0.24 (0.02)
0.20 (0.03)
0.50(0.19)


0.11 (0.16)
0.27(0.13)
0.13 (0.03)
0.89 (0.04)
0.58(0.18)


0.34(0.18)
0.43 (0.13)
0.13 (0.03)
0.45 (0.04)
0.63 (0.20)


-0.02 (0.18)
0.21 (0.14)
0.01 (0.03)
-0.05 (0.04)
0.34 (0.25)
0.99 (0.00)
-0.23 (0.30)
0.01 (0.20)
-0.11 (0.04)
-0.14 (0.06)


MSUL-MSUL correlations
2 3


0.61 (0.16)


0.21 (0.20)
0.41 (0.13)
0.16(0.03)
0.08 (0.04)
0.73 (0.16)
0.07(1)
0.45 (0.22)
0.54 (0.13)
0.24 (0.03)
0.17(0.03)
0.57 (0.22)


0.18(0.20)
0.34 (0.16)
0.02 (0.03)
-0.06 (0.04)
0.12 (0.30)


-0.03 (0.32)
0.03 (0.22)
-0.21 (0.04)
-0.27 (0.05)


0.88 (0.12)
0.55 (0.08)
0.24 (0.02)
0.10(0.04)
0.74 (0.11)


0.79 (0.14)
0.77 (0.09)
0.30 (0.03)
0.07 (0.03)
0.69 (0.14)


0.96 (0.28)
0.83 (0.14)
0.35 (0.04)
0.17(0.05)


0.89 (0.07)


0.74 (0.14)
0.81 (0.09)
0.31 (0.03)
0.10(0.04)
-0.21 (0.17)


1(0.40)
1(0.08)
0.35 (0.21)
-0.21 (0.05)


0.91 (0.09)
0.85 (0.38)
0.73 (0.21)
0.81 (0.12)
0.53 (0.03)
0.43 (0.05)


-0.13 (0.10) -0.14 (0.10) 0.13 (0.10) 0.08 (0.10) 0.24 (0.10) 0.55 (0.07)


Note: (---) Correlation could not be estimated because of variances which were 0.







70


Table B-4. Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite)correlations between flush length (FLn) by flush for 2004 growing
season.
FLn-FLn correlations
Flush 1 2 3 4 5 6
2 rGCA 0.44 (0.22)
rsCA
r( ,. ., 0.01(0.10)
rGenetic 0.11 (0.09)
rPhenotypic 0.14 (0.03)
rMicrosite 0.16(0.04)
3 rGCA -0.46 (0.22) -0.1 (0.25)
rSCA
r( ,, -0.17 (0.12) 0.33 (0.11)
rGenetic -0.24 (0.10) 0.21 (0.10)
rPhenotypic -0.16 (0.03) -0.03 (0.03)
rMicrosite -0.14 (0.04) -0.16 (0.04)
4 rGCA -0.39 (0.26) -0.12 (0.25) 0.83 (0.11) ---
rsCA 0.61(1.1) --- 0.93 (1.4) ---
r( ,. -0.15 (0.12) 0.20 (0.10) 0.41 (0.12 ---
rGenetic -0.18 (0.10) 0.11 (0.10) 0.55 (0.10) ---
rPhenotypic -0.12 (0.03) 0.01 (0.03) 0.36 (0.03) ---
rMicrosite -0.09 (0.04) -0.05 (0.04) 0.28 (0.03) ---
5 rGCA -0.48 (0..21) -0.08 (0.23) 0.74 (0.14) 0.57 (0.17)
rSCA --
r ,. 0.02 (0.13) -0.05 (0.11) 0.29 (0.14) 0.31 (0.14) ---
rGenetic -0.13 (0.11) -0.06 (0.10) 0.45 (0.11) 0.40 (0.11) ---
rPhenotypic -0.12 (0.04) -0.03 (0.04) 0.27 (0.03) 0.26 (0.03) ---
rMicrosite -0.12 (0.04) -0.02 (0.04) 0.20 (0.04) 0.21(0.04) ---
6 rGCA -0.34 (0.27) -0.53 (0.22) 0.34 (0.27) 0.41 (0.25) 0.40 (0.24)
rSCA
r( ,. ., 0.24 (0.18) -0.42 (0.11) 0.26 (0.20) -0.04 (0.18) -0.09 (0.19)
rGenetic 0.09 (0.15) -0.45 (0.10) 0.28 (0.16) 0.09 (0.14) 0.07 (0.15)
rPhenotypic -0.08 (0.05) -0.44 (0.04) 0.08 (0.04) 0.15 (0.04) 0.00 (0.04)
rMicrosite -0.15 (0.06) -0.44 (0.05) 0.01(0.06) 0.18(0.06) -0.03 (0.06)
7 rGCA -0.55 (0.44) -0.17 (0.40) 0.67 (0.31) 0.85 (0.39) 0.35 (0.36) 1(0.27)
TSCA
r( ,. ., 0.87 (0.35) -0.12 (0.23) 0.32 (0.31) 0.35 (0.31) -0.08 (0.30) 0.13 (0.30)
rGenetic 0.57 (0.29) -0.13 (0.20) 0.42 (0.23) 0.45 (0.24) 0.06 (0.23) 0.34 (0.23)
rPhenotypic -0.19 (0.10) -0.41 (0.10) 0.18(0.09) 0.11(0.08) -0.03 (0.10) 0.19(0.09)
rMicrosite -0.7 (0.11) -0.72 (0.13) 0.03 (0.18) -0.13 (0.18) -0.09 (0.17) 0.10(0.18)
Note: (---) Correlation could not be estimated because of variances which were 0.











Table B-5. Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite)correlations between numbers of stem units (NSU) by flush for
2004 growing season


Flush
2 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
3 rGCA


r( I
rGenetie
rPhenotypie
rMicrosite
4 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
5 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite
6 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite
7 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite


1
0.28 (0.24)


0.04 (0.10)
0.10 (0.09)
0.23 (0.03)
0.30 (0.03)
0.32 (0.23)


0.11 (0.12)
0.17(0.11)
0.16 (0.03)
0.16 (0.04)
0.09 (0.30)


0.11 (0.13)
0.10 (0.12)
0.11 (0.03)
0.12 (0.04)
0.18 (0.30)


0.22 (0.11)
0.20 (0.10)
0.18 (0.03)
0.16 (0.04)
0.85 (0.54)


0.44 (0.19)
0.48 (0.17)
0.10 (0.04)
-0.03 (0.06)



0.06 (0.20)
0.05 (0.16)
0.03 (0.09)
-0.01 (0.24)


NSU-NSU correlations
2 3


0.34 (0.22)


0.91 (0.11)
0.74 (0.09)
0.25 (0.03)
0.03 (0.04)
0.12 (0.28)


0.61 (0.11)
0.50 (0.10)
0.16(0.03)
0.02 (0.04)
0.46 (0.24)


0.68 (0.09)
0.61 (0.08)
0.34 (0.03)
0.16(0.04)
0.74 (0.24)


0.30 (0.16)
0.38 (0.14)
0.24 (0.05)
0.19(0.06)



0.47 (0.17)
0.40 (0.14)
0.20 (0.08)
-0.20 (0.22)


0.76 (0.11)


0.68 (0.11)
0.70 (0.08)
0.43 (0.02)
0.34 (0.03)
0.85 (0.10)


0.66 (0.11)
0.75 (0.08)
0.43 (0.03)
0.30 (0.04)
0.96 (0.27)


0.46 (0.10)
0.53 (0.16)
0.28 (0.04)
0.20 (0.06)



0.26 (0.20)
0.20 (0.15)
0.09 (0.08)
-0.08 (0.24)


0.64 (0.23)
0.85 (0.30)
0.57 (0.11)
0.61 (0.09)
0.40 (0.02)
0.33 (0.04)
0.78 (0.40) 0.73 (0.24)


0.46 (0.19)
0.47 (0.16)
0.29 (0.04)
0.24 (0.06)



0.14 (0.18)
0.12(0.15)
0.08 (0.07)
0.13 (0.26)


0.46 (0.20)
0.51 (0.16)
0.41 (0.03)
0.38 (0.05)



0.35 (0.16)
0.28 (0.13)
0.15 (0.07)
-0.05 (0.24)


Note: (---) Correlation could not be estimated because of variances which were 0.


0.44 (0.18)
0.43 (0.18)
0.22 (0.07)
0.13(0.12)











Table B-6. Site 2 (Southwest Georgia): cuttings genetic, phenotypic and environmental
(microsite) correlations between mean stem unit length (MSUL) by flush for
2004 growing season.


Flush
2 rGCA
rECA
r( I
rGenetie
rPhenotypie
rMicrosite
3 rGCA


r( I
rGenetie
rPhenotypie
rMicrosite
4 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
5 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite
6 rGCA
rsCA
r(
rGenetie
rPhenotypie
rMicrosite
7 rGCA
rsCA
r( '
rGenetie
rPhenotypie
rMicrosite


1
0.66 (0.14)


0.49 (0.12)
0.55 (0.10)
0.36 (0.03)
0.28 (0.03)
0.47 (0.18)


0.29 (0.12)
0.36 (0.10)
0.20 (0.03)
0.12 (0.04)
0.42 (0.20)


0.37 (0.12)
0.39 (0.10)
0.16(0.03)
0.06 (0.04)
0.34 (0.21)


0.21 (0.13)
0.26(0.11)
0.14 (0.03)
0.09 (0.04)
0.14(0.32)


0.14(0.15)
0.13(0.13)
0.04 (0.04)
0.00 (0.06)








0.00 (0.10)


MSUL-MSUL correlations
2 3


0.85 (0.07)


0.82 (0.07)
0.83 (0.05)
0.47 (0.03)
0.25 (0.03)
0.63 (0.15)


0.43 (0.09)
0.49 (0.08)
0.22 (0.03)
0.05 (0.04)
0.77 (0.11)


0.53 (0.10)
0.61 (0.08)
0.31 (0.03)
0.14 (0.04)
0.68 (0.21)


0.32 (0.12)
0.40 (0.10)
0.15 (0.04)
0.00 (0.06)


0.85 (0.08)


0.53 (0.07)
0.63 (0.06)
0.39 (0.03)
0.23 (0.03)
0.84 (0.08)


0.70 (0.08)
0.75 (0.06)
0.41 (0.03)
0.19(0.04)
0.80 (0.17)


0.44 (0.10)
0.51 (0.09)
0.34 (0.04)
0.22 (0.06)


0.69 (0.13)


0.47 (0.09)
0.54 (0.08)
0.28 (0.03)
0.13 (0.04)
0.59 (0.25)


0.30(0.11)
0.36 (0.10)
0.20 (0.04)
0.11 (0.06)


0.59 (0.23)


0.33(0.11)
0.39 (0.10)
0.26 (0.04)
0.19(0.06)


-0.10 (0.10) 0.22 (0.09) 0.22 (0.09) 0.26 (0.10) 0.28 (0.10)


Note: (---) Correlation could not be estimated because of variances which were 0.















APPENDIX C
SECOND-YEAR GROWING SEASON PHYLLOSTATIC PATTERNS.

Table C-1. Individual tree narrow and broad-sense heritabilities for phyllostatic patterns
by propagule type for 2004 growing season in Site 1 (North Central Florida)
and Site 2 (Southwest Georgia).
Phyllostatic Seedlings Cuttings
pattern h2 H2 h2 H2
by flush
Site 1
1 0.05 (0.09) 0.05 (0.09) 0.00 (0.00) 0.06 (0.02)
2 0.03 (0.08) 0.03 (0.08) 0.00 (0.00) 0.05 (0.02)
3 0.04 (0.08) 0.04 (0.08) 0.00 (0.00) 0.05 (0.02)
4 0.06 (0.09) 0.06 (0.09) 0.00 (0.00) 0.06 (0.02)
5 0.00 (0.00) 0.24 (0.32) 0.00 (0.00) 0.07 (0.03)
6 0.49 (0.58) 1.00 (1.25) 0.00 (0.02) 0.20 (0.06)
7 --- --- 0.27 (0.43) 0.14 (0.21)
Site 2
1 0.00 (0.00) 0.19 (0.23) 0.00 (0.01) 0.00 (0.01)
2 0.00 (0.00) 0.18 (0.23) 0.00 (0.01) 0.01(0.04)
3 0.10 (0.10) 0.10 (0.10) 0.01(0.01) 0.02 (0.04)
4 0.00 (0.00) 0.12 (0.24) 0.00 (0.01) 0.00 (0.01)
5 0.19(0.18) 0.19(0.18) 0.01(0.02) 0.00(0.01)
6 0.19 (0.77) 1.00 (1.10) 0.00 (0.00) 0.08 (0.10)
7 --- --- 0.10 (0.42) 0.05 (0.21)
















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pp.15.

Bailey, D.B., and Feret, P.P. 1982. Short note: shoot elongation in Pinus rigida x taeda
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Bollmann, M.P., and Sweet, G.B. 1977. Bud morphogenesis ofPinus radiata in New
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BIOGRAPHICAL SKETCH

Liliana Parisi was born in the town of La Plata in Argentina and grew up in the city

of Pergamino, Buenos Aires Province, a region without many trees but where agriculture

and cattle are very popular. In 1996, she graduated as an Agricultural Engineer at the

Universidad Nacional de La Plata (UNLP) in La Plata, Argentina. Between 1997 and

2003, she worked as a junior researcher at the forestry division of INTA Bella Vista

Experimental Station. She enrolled in the School of Forest Research and Conservation

master's program in August 2003 at the University of Florida. After her graduation, she

will continue her studies at the University of Florida pursuing her PhD degree.