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Variation in Biomass Distribution and Nutrient Content in Loblolly Pine Clones with Contrasting Crown Architecture and G...

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Title:
Variation in Biomass Distribution and Nutrient Content in Loblolly Pine Clones with Contrasting Crown Architecture and Growth Efficiency
Physical Description:
1 online resource (87 p.)
Language:
english
Creator:
Garcia Villacorta, Angelica Milagros
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Forest Resources and Conservation
Committee Chair:
Martin, Timothy A
Committee Members:
Jokela, Eric J
Cropper, Wendell P, Jr

Subjects

Subjects / Keywords:
loblolly -- pine
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre:
Forest Resources and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Loblolly pine (Pinus taeda L.) is well adapted across an extensive range of sites,responds optimally to silvicultural treatments, and has undergone geneticimprovement through traditional tree breeding programs, with selection basedprimarily on growth and disease resistance. However, less research hasaddressed the effects of relationships between stem growth, biomasspartitioning, and component nutrient content in loblolly pine clones withcontrasting crown architecture. We studied four clones which exhibited a rangeof crown sizes from narrow to wide. Based on the ideotype concept, we measuredcrown width, crown volume, and biomass allocated to foliage, branches, stemwoodand bark through destructive harvests. A range of variation in growthefficiency and biomass allocation patterns were observed in a subset of threeclones in the trial.  Clonal variation inbiomass distribution patterns might help to explain variation in growthefficiency between the narrow crown clone (ARB-1) and wide crown clone (ARB-4) inthis study. Clone ARB-1 wasmore efficient at producing stem biomass increment per unit foliar biomass andunit foliar nutrient content than clone ARB-4; this was consistent with theconcept of a crop ideotype. This study provides new information useful forimproving our understanding of the relationships among crown structure, biomassdistribution patterns, growth efficiency, and tree productivity, and may helpto guide management of clonal populations of trees.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Angelica Milagros Garcia Villacorta.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Martin, Timothy A.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046054:00001

MISSING IMAGE

Material Information

Title:
Variation in Biomass Distribution and Nutrient Content in Loblolly Pine Clones with Contrasting Crown Architecture and Growth Efficiency
Physical Description:
1 online resource (87 p.)
Language:
english
Creator:
Garcia Villacorta, Angelica Milagros
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Forest Resources and Conservation
Committee Chair:
Martin, Timothy A
Committee Members:
Jokela, Eric J
Cropper, Wendell P, Jr

Subjects

Subjects / Keywords:
loblolly -- pine
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre:
Forest Resources and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Loblolly pine (Pinus taeda L.) is well adapted across an extensive range of sites,responds optimally to silvicultural treatments, and has undergone geneticimprovement through traditional tree breeding programs, with selection basedprimarily on growth and disease resistance. However, less research hasaddressed the effects of relationships between stem growth, biomasspartitioning, and component nutrient content in loblolly pine clones withcontrasting crown architecture. We studied four clones which exhibited a rangeof crown sizes from narrow to wide. Based on the ideotype concept, we measuredcrown width, crown volume, and biomass allocated to foliage, branches, stemwoodand bark through destructive harvests. A range of variation in growthefficiency and biomass allocation patterns were observed in a subset of threeclones in the trial.  Clonal variation inbiomass distribution patterns might help to explain variation in growthefficiency between the narrow crown clone (ARB-1) and wide crown clone (ARB-4) inthis study. Clone ARB-1 wasmore efficient at producing stem biomass increment per unit foliar biomass andunit foliar nutrient content than clone ARB-4; this was consistent with theconcept of a crop ideotype. This study provides new information useful forimproving our understanding of the relationships among crown structure, biomassdistribution patterns, growth efficiency, and tree productivity, and may helpto guide management of clonal populations of trees.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Angelica Milagros Garcia Villacorta.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Martin, Timothy A.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046054:00001


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1 VARIATION IN BIOMASS DISTRIBUTION AND NUTRIENT CONTENT IN LOBLOLLY PINE CLONES WITH CONTRASTING CROWN ARCHITECTURE AND GROWTH EFFICIENCY By ANGELICA MILAGROS GARCIA VILLACORTA A THESIS PRESENTED TO THE GRADUATE SCHOOL OF T HE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013

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2 2013 Angelica Milagros Garcia Villacorta

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3 To my m other

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4 ACKNOWLEDGMEN TS First of all, I want to thanks my advisor Dr. Timothy Martin who I owe my deepest gratitude because from the beginning to the end of my program he gave me his unconditional support, not only as the best advisor but as a great friend, thanks to him, I ha ve come to the final goal, thanks for giving me this great opportunity and trust me. I am pleased to thank Dr. Eric Jokela and Dr. Wendell Cropper for always being willing to support me and provide me their knowledge and advice at all times. Thanks to my c ommittee for their patience, for their time and for the entire contributions that was undoubtedly very important to finish this document. Distinct thanks to Fulbright LASPAU and the Peruvian Government for the financial support and for made come true one o f my biggest goals that was to become a Master of Science Special thanks to Forest Biology Research Cooperative and School of Forest Resources and Conservation for the financial support to carry out of my research. I owe a special thanks to Mike Ward, Tod d Rockhill, Allen Milligan, Geoff Lokuta, Ben Gottloeb and Bora Imal, who supported me in the field work. I would never forget the help I got from my labmates Maxwell Wightman and Chelsea Drum, who from the beginning gave me their friendship and support. T hanks to Carlos Gonzales, Tania Quezada and Salvador Gezan for their input and help in my study. I am very grateful to Paul Proctor and Cynthia Hight for their help in the logistics. I would like to thank my friends in Gainesville who have been like a fami ly to me during this time especially Sonia Delphin, Leonardo Rada, Ronald Cademus, Michael Baumann and Marco Sinche and many other good friends, thanks for all your support in difficult times and all shared joys, always I will have you all in my heart. I w ould also like to thank my good friends John Terborgh and Tom i Nagai for their wise advices I want to thank Joel Wixson for all the support in many ways, his support

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5 has given me much strength and motivation to keep going. Thanks to my mother and siblings that were by side from distance, especially my mother who has always been my guide, my strength and my best friend on my path. Thanks to my friends in Peru especially Liliana Paulet, Fabiola Barra and Liliana Loayza, who always have sent me their support. I am very much grateful to all the people that I have met in Gainesville during all this time and who in one way or another contributed to the accomplishment of my master program.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 10 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 2 BIOMASS ALLOCATION IN THREE LOBLOLLY PINE CLONES .......................... 18 Methods ................................ ................................ ................................ .................. 20 Study Area ................................ ................................ ................................ ........ 20 Experimental Design ................................ ................................ ........................ 20 Sample Tree S election ................................ ................................ ..................... 21 Biomass Sampling ................................ ................................ ............................ 21 Intercepted Photosynthetically Active Radiation and Canopy Openness ......... 22 Data Analysis ................................ ................................ ................................ ... 23 Results ................................ ................................ ................................ .................... 24 Biomass Distribution ................................ ................................ ......................... 24 Growth Efficiency ................................ ................................ ............................. 25 IPAR and Open Canopy ................................ ................................ ................... 26 Discussion ................................ ................................ ................................ .............. 26 3 VARIATION IN NUTRIENT CONTENT IN THREE LOBLOLLY PINE CLONES WITH CONTRASTING CROWN ARCHITECTURE ................................ ................ 42 Methods ................................ ................................ ................................ .................. 44 Study Area ................................ ................................ ................................ ........ 44 Experimental Design ................................ ................................ ........................ 44 Sample Tree Selection ................................ ................................ ..................... 45 Component Biomass ................................ ................................ ........................ 45 Nutrient Sampling ................................ ................................ ............................. 46 Data Analysis ................................ ................................ ................................ ... 46 R esults ................................ ................................ ................................ .................... 47 Component Biomass ................................ ................................ ........................ 47 Component Nutrient Concentration ................................ ................................ .. 48 Component Nutrient Content ................................ ................................ ............ 49 Discussion ................................ ................................ ................................ .............. 50 Genetic Variation in Biomass Distribution and Nutrient Traits .......................... 51 Ideotypes and Growth Efficiency ................................ ................................ ...... 53

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7 4 SUMMARY AND CONCLUSIONS ................................ ................................ .......... 71 APPENDIX TREE AND PLOT LEVEL DATA ................................ ................................ ................... 73 LIST OF REFERENCES ................................ ................................ ............................... 79 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 87

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8 LIST OF TABLES Table pag e 2 1 Summary of the installation of the FBRC VARIETIES I clonal plot trial at Starke, FL planted in January 2009. ................................ ................................ ... 32 2 2 Treatment history for the VARIETIES I experiment near Starke, FL. .................. 32 2 3 Age 3 year tree level characteristics, stem volume (SV), crown volume (CV), crown width (CW), relative crown width ( CW/H) and stem volume growth efficiency (SV/CV). ................................ ................................ ............................. 33 2 4 Analysis of the log log relationships between age 3 year component biomass and total biomass for three clones in the VARIETIES I experim ent near Starke, FL.. ................................ ................................ ................................ ......... 33 2 5 Parameter estimates for the log log relationships between age 3 year biomass components for three clones in the VARIETIES I experiment near Starke, FL. ................................ ................................ ................................ .......... 34 2 6 Analysis of the log log relationships between age 3 year component biomass and D 2 H for three clones in the VARIETIES I experiment near Starke, FL. ...... 35 2 7 Parameter estimates for the log log relationships between age 3 year biomass components for three clones in the VARIETIES I experiment near Starke, FL.. ................................ ................................ ................................ ......... 36 2 8 Average values of % canopy openness (% CO) foliage biomass (Folbio), stem biomass increment (SBI) and incident photosynthetically active radiation (IPAR).. ................................ ................................ ................................ 37 3 1 Biomass accumulation (kg/ha) patterns of foliage, stemwood, bark, branches, foliated branches (FB) and non foliated branches (NFB). among three different clones of loblolly pine at age 3.. ................................ ............................ 58 3 2 Ratios of component biomass / tot al biomass for foliage, stemwood, bark, foliated branches (FB) and non foliated branches (NFB) for stands of three different clones of loblolly pine at age 3.. ................................ ............................ 58 3 3 Macroelement concentratio ns in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB). Standard Deviations are in parentheses. ................................ ................................ ................................ ....... 59 3 4 Microelement concentrations (mg/kg) in foliage, bark, stem wood, non foliated branches (NFB) and foliated branches (FB). ................................ ...................... 60

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9 3 5 Ratios in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) between nitrogen:phosphorus (N:P) and nitrogen:potasium (N:K) based on component concentrations. ................................ ....................... 61 3 6 Average component macronutrient content (kg/ha) in foliage, bark, stemwood, non foliated branches (NFB) and foliated bran ches (FB) among different clones of loblolly pine at age 3. ................................ ............................. 62 3 7 Average of component micronutrient content (mg/ha) in foliage, bark, stemwood, non foliated branches (NFB) and foliated branc hes (FB) among different clones of loblolly pine at age 3. ................................ ............................. 63 3 8 Average foliage biomass (Folbio), foliar crown nitrogen content (Foliar N), foliar crown phosphorus content (Foliar P), stem b iomass increment from age 2 3 years (SBI) ................................ ................................ ................................ ... 63 A 1 Plot level component macronutrient content (kg/ha) in three different clones of loblolly pine at age 3. ................................ ................................ ...................... 73 A 2 Plot level component micronutrient content (mg/ha) in three different clones of loblolly pine at age 3. ................................ ................................ ...................... 75 A 3 Plot level values of foliage biomass (kg/ha), fol iar N content (kg/ha), foliar P content (kg/ha) and age 2 3 year stem biomass increment (SBI, kg/ha/yr). ....... 77 A 4 Individual tree component biomass harvest data for foliage, bark, stemwood, bran ch, foliated branches (FB) and non foliated branches (NFB) among three different clones of loblolly pine at age 3. ................................ ............................. 78

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10 LIST OF FIGURES Figure page 2 1 FBRC Varieties I. Color pink: ARB 1 (moderate crown), color yellow: ARB 2 (broad crown), color blue: ARB 3 (moderate narrow crown) and color orange: ARB 4 (moderate crown). ................................ ................................ ................... 38 2 2 Log log plot of bark biomass vs. total biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL. ................................ .................... 39 2 3 Log log plot of stem biomass vs. total biomass for three loblolly pi ne clones in the VARIETIES I experiment near Starke, FL. ................................ ................ 39 2 4 Log log plot of branch biomass vs. total biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL. ................................ ................ 40 2 5 Log log plot of foliage biomass vs. total biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL. ................................ ................ 40 2 6 Log log plot of total biomass vs. dbh 2 *height biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL. ................................ .... 41 3 1 Distribution of aboveground biomass (fol iage, stemwood, bark, branches, foliated branches (FBranch) and non foliated branches (NFBranch)) among three different clones of loblolly pine at age 3. ................................ .................... 64 3 2 Distribution of nitrogen (N) co ntent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ................................ ........... 64 3 3 Distribution of phosphorus (P) c ontent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ............................. 65 3 4 Distribution of potassium (K) c ontent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ................................ ........... 65 3 5 Distribution of calcium (Ca) co ntent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ................................ ........... 66 3 6 Distribution of magnesium (Mg) c ontent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ............................. 66

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11 3 7 Distribution of sulfur (S) cont ent in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ................................ ........... 67 3 8 Distribution of boron (B) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. ................................ ................................ ........... 67 3 9 Distribution of copper (Cu) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. ................................ ................................ ...................... 68 3 10 Distribution of iron (Fe) content in folia ge, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. ................................ ................................ ...................... 68 3 11 Distribution of manganese (Mn) content in foliag e, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. ................................ ................................ ........... 69 3 12 Distribution of molybdenum (Mo) content in foliag e, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. ................................ ................................ ........... 69 3 13 Distribution of zinc (Zn) content in foliage, bar k, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. ................................ ................................ ...................... 70

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12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for th e Degree of Master of Science VARIATION IN BIOMASS DISTRIBUTION AND NUTRIENT CONTENT IN LOBLOLLY PINE CLONES WITH CONTRASTING CROWN ARCHITECTURE AND GROWTH EFFICIENCY By Angelica Milagros Garcia Vi llacorta August 2013 Chair: Tim Martin Major: Forest Resources and Conservation Loblolly pine ( Pinus taeda L.) is well adapted across an extensive range of sites, responds optimally to silvicultural treatments, and has undergone genetic improvement thro ugh traditional tree breeding programs, with selection based primarily on growth and disease resistance. However, less research has addressed the effects of relationships between stem growth, biomass partitioning, and component nutrient content in loblolly pine clones with contrasting crown architecture. We studied four clones which exhibited a range of crown sizes from narrow to wide. Based on the ideotype concept, we measured crown width, crown volume, and biomass allocated to foliage, branches, stemwood and bark through destructive harvests. A range of variation in growth efficiency and biomass allocation patterns were observed in a subset of three clones in the trial. Clonal variation in biomass distribution patterns might help to explain variation in g rowth efficiency between the narrow crown clone (ARB 1) and wide crown clone (ARB 4) in this study. C lone ARB 1 was more efficient at producing stem biomass increment per unit foliar biomass and unit foliar nutrient content than clone ARB 4; this was consi stent with the concept of a crop ideotype. This study provides new information

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13 useful for improving our understanding of the relationships among crown structure, biomass distribution patterns, growth efficiency, and tree productivity, and may help to guide management of clonal populations of trees.

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14 CHAPTER 1 INTRODUCTION The development of intensive management practices in forest plantations in the southeastern United States has made the region the woodbasket of the world (Wear and Greis, 2002). Over the last 50 years, management practices in southern pine plantations have been informed by scientific research Many pine plantations in the South, especially loblolly pine ( Pinus taeda L ), are ideal examples of intensively managed forests because this speci es grows fast and, is the most versatile species among the southern pines for forest management (Shultz, 1997). Genetic improvement of loblolly pine has contributed to large increases in plantation productivity, with genetic improvement programs producing a wide variety of highly productive open pollinated (half sib) and full sib families, and more recently, clones (McKeand et al. 2003, 2006). Numerous benefits could be derived for southern pine breeding programs by integrating ideotypes, which are a concep tual models develop by Donald (1968) for agronomic crops, that explicitly define plant phenotypic characteristics that are hypothesized to produce larger yield (Martin et al., 2001). Donald and Hamblin (1976) proposed three types of ideotypes: isolation i deotypes described as free standing trees that perform best in young stands; competition ideotypes that compete aggressively with their neighbors and are hypothesized to be less efficient users of resources (Cannell, 1978); and crop ideotypes that are more effective competitors when resources are limiting (Xiao, 2000). Crop ideotypes should be ideal for intensively managed production systems (Donald and Hamblin 1976; Dickmann 1985). In terms of crown architecture, it has been proposed

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15 that crop ideotypes ma y be likely to have more compact, narrow crowns, while competition ideotypes would have wider crowns (Cannell, 1978; Martin et al., 2005). Few studies have addressed genetic variation in crown structure. Emhart et al. (2007) studied within family clonal variation of growth and crown structural attributes of loblolly pine ( Pinus taeda L.) and slash pine ( Pinus elliottii Engelm. var. elliottii ). Several authors have proposed that ideotypes may offer a valuable model for thinking about crown traits and tree and forest productivity. Some studies have recommended that the development and structure of tree crowns are fundamental factors of resource interception, use, and productivity (Cannell et al. 1978; Martin et al. 2001; Staudhammer et al. 2009). Also, crow n structure is essential in determining the distribution of the photosynthetic surfaces in space. Leaf area distribution influences light interception and is linked with the rate of photosynthesis (McCrady & Jokela, 1998; Chmura et. al., 2009). The spatial distribution of leaf area and biomass contained by a crown could influence net CO 2 exchange rates at the whole tree and stand levels (Wang and Jarvis, 1990). Thus, crown architecture is closely related to forest productivity (Cannell et al. 1987; Dalla Te a and Jokela 1991; McCrady and Jokela 1996). Nutrition of forest trees has been broadly studied in relation to the physiological, ecological and silvicultural characteristics influencing growth (Xiao, 2000). Management practices like forest fertilization increase tree growth (Miller, 1981; Colbert et al., 1990). In many tree species foliar nutrient concentration has been suggested as a good indicator of nutrient stress and as a predictor of responses to soil conditions and fertilization (Prasolova et al., 2005). Previous studies with other tree species have shown that variation in foliar nutrient concentrations had a large genetic component

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16 (Beets and Jokela, 1994; Gonzalez and Fisher, 1997; Xu et al., 2003). Other studies found that genotypic differences in nutrient accumulation and nutrient requirements could allow some genotypes to produce higher yields under nutrient limiting soil conditions. (Li et al., 1991; Schmidtling, 1995; Sun and Payn, 1999; Xu et al., 2003). The relationship between foliar mass and crown size was shown to vary in response to a nutrient availability gradient between two clones of P. taeda in a single site field trial (Tyree et al. 2009b). Typically, genetic experiments comprise single tree plots or row plots which do not represe nt operational environments or ecosystem dynamics (Martin et al., 2001). Physiological variation and stand dynamics in larger, genetic block plot studies may offer useful information for understanding genotype performance under operational conditions (Mart in et al., 2005). This study observed variation in tree level and stand level stem growth, biomass partitioning, and component nutrient content in loblolly pine clones having contrasting crown architecture. We hypothesized that narrow crowned clones would have greater stand level efficiency in terms of stem biomass produced per unit foliage or biomass nutrient content, consistent with predictions for crop ideotypes. The study used a clonal block plot experiment Inve stigations Examining Tree Interactions on Experimental Sites) installed near Starke, Florida (Davis et al., 2010), established by the Forest Biology Research Cooperative at the University of Florida. The goal of this study was to increase our understandin g of the relationship between crown architecture and tree productivity and to explore the causes of growth efficiency variation

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17 Objectives : The principal objective of this study was to examine variation in stem growth, biomass partitioning, and component nutrient content in selected loblolly pine ( Pinus taeda ) clones with contrasting crown architecture. The key questions addressed concern biomass allocation and nutrient content differences among clones. The 2 nd chapter analyzed how the biomass allocation differs between different clones of loblolly pine. The hypothesis and objectives were: Hypothesis: There are significant differences among clones in terms of biomass allocation. Objective 1: To determine if clones will differ in crown characteristics such as crown width and crown volume. Objective 2: To determine if clones will differ in relative proportions of biomass allocated to stemwood, bark, foliage and branches. Objective 3: To determine if clones with smaller crowns will have higher growth efficien cy. The 3rd chapter analyzed the differences in nutrient content among clones. The hypotheses and objectives were: Hypothesis: Clones with narrow crown would have greater stand level efficiency in terms of stem biomass produced per unit foliage or biomass nutrient content Objective 1: To determine the nutrient distribution among clones in different components of the tree. Objective 2: To determine which clone has higher foliar nutrient content.

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18 CHAPTER 2 BIOMASS ALLOCATION IN THREE LOBLOLLY PINE CLONES A variety of pine species grow rapidly in the southern United States. Southern pine trees are very important because of their wood quality and productivity, and are among the most successful species used in the forestry industry (Fox et al., 2007b) Be ginning in the last century there were around 13 million ha o f southern pine plantation s that contained 19 million m 3 of timber (Wear and Greis, 2002) so there is significant interest in improving southern pine plantatio ns. Loblolly pine ( Pinus taeda L ) represents the most important commercial timber tree species in the southern of United States, includes half of the total volume of southern pine growing stock which is around 1.4 billion m 3 (Schultz, 1997). This species is broadly adapted to a wide range of sites, responds well to silvicultural inputs, and has wood properties which make it suitable for a wide range of products, from pulp and paper to lumber and plywood (Schultz, 1997). Loblolly pine has also undergone g enetic improvement through traditional tree breeding programs, with selection based primarily on growth and disease resistance (McKeand et al., 2003). Little work has been done on understanding genetic variation in crown structure (McCrady and Jokela, 199 8; Xiao et al., 2003; Emhart et al., 2007). The concept of ideotypes might provide a useful model for thinking about crown traits and tree and forest productivity. An ideotype is a plant model that is likely to develop the ideal phenotype to enhance produc tivity (Donald, 1968). According to Martin et al. (2001), using ideotypes in different pine plantations has several advantages that may help to understand the mechanisms that control growth. It is also important to improve forest tree species genetically s o that the wood product will be more uniform and more amenable to management (McKeand et al., 2003). Therefore, clonal forestry has the

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19 potential to improve the productivity of southern pine trees in conjunction with silvicultural treatments (Fox et al., 2 007b). Some studies have shown that crown structure is an important influence on pine tree growth (McCrady and Jokela, 1996; Xiao et al., 2003; Chmura and Tjoelker, 2004). Chmura et al. (2007) determined that genetics and silviculture are important determi nants of crown structure. Crown structure is also important in determining the distribution of the photosynthetic surfaces in space. Thus, a good leaf area distribution allows capture of more light and it is potentially associated with an increase in photo synthesis ( McCrady and Jokela, 1998; Chmura et. al., 2009 ). Studies of phenotypic relations between tree growth and crown structure indicate that growth rate is related with light captured by the canopy leaf area (Cannell, 1989; Will et al., 2001). Beside s phenotypic studies, genetic improvements may influence the relations between crown architecture and growth and might be a significant factor that can be selected for in developing tree ideotypes (Dickmann et al., 1994; Emhart et al., 2007). Thus, genetic s and phenotypic studies will be important in understanding growth strategies and o enhancing forest productivity and wood quality traits. Architecture Investigations Examini ng Tree Interactions on Experimental Sites) that was installed near Starke, Florida (Davis et al., 2010). In that experiment, individual genotypes (clones) were planted in pure plots. The experiment contained four different clones, all of which were selec ted for maximum stem growth, but did exhibit a range in crown sizes from narrow to wide. Initial inventory measurements in this experiment indicated variation in crown size and stemwood productivity among clones, and

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20 suggested variation in indices of grow th efficiency among clones (Table 2 3) The objective of this study was to quantify variation in biomass distribution among clones with contrasting crown architecture and growth efficiency, with the goal of better understanding the biological determinants of growth potential. Methods Study A rea The Varietal Architecture Investigations Examining Tree Intera ctions on Experimental Sites (VARIETIES I), is a clonal block plot experiment located near annual temperature of 20C and mean annual precipitation of 1225 mm (NOAA 1999 2012). Soils at the site are somewhat poorly drained Spodosols belonging to the Sapelo fine sands series (sandy, siliceous, thermic Ultic Alaquods). The spodic horizon is approximately 40 cm deep, with a sandy clay loam argillic horizon at 100 120 cm. Do minant understory vegetation at the site included saw palmetto ( Serenoa repens ) and gallberry ( Ilex glabra ). For the period of May and July of 2008 the site was prepared by chopping and bedding. In January 2009, containerized loblolly pines were planted. E xperimental Design The study consists of four clones (ARB 1, ARB 2, ARB 3, ARB 4) and one full sib family (7 56) planted at two densities: wide, 1000 trees/ha (2.7x3.7 m) and narrow, 1802 trees/0.4 ha (1.5x3.7 m), (Table 2 1). The clones were planted in 7 rows x 7 tree plots (0.028 the four clones. Fertilizer was applied in April of 2009 and 2010 and March of 2011.

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21 Subsequent herbicide treatments were conducted to reduce understo ry woody and herbaceous competition. In October of 2010 triclopyr (3%), imazipyr (1%) and metsulfuron methyl (0.625%) were applied with directed spray. A 3.75% solution of glyphosate was applied by directed spray in September of 2009 and 2010 (Table 2 2). Sample Tree Selection An inventory done in December, 2011 included measurements of tree height (H), diameter at breast height (DBH), and crown width (CW) measured in two directions for all genotypes in the study. Stem volume index (SV, DBH 2 H), crown vo lume (CV, calculated as a paraboloid), relative crown width (CW/H) and an index of stem volume growth efficiency (SV/CV) and crown shape ratio (crown length / crown width) were derived fr om the inventory measurements. Based on an analysis of the inventory data, three contrasting clones were chosen for measurement of biomass distribution: ARB 1, ARB 2, and ARB 4. ARB 1 and ARB 4 were chosen because they had the narrowest and widest average CW/H, respectively, and also had a contrasting SV/CV efficiency ind ex. In addition, we chose to measure biomass distribution for ARB 2 because this clone had the highest productivity of all clones in the study (Table 2 3). For each clone, we chose eight trees distributed across the full range of tre e size for destructiv e harvest. Biomass Sampling Biomass harvests were performed on eight trees in each of the clones, with the goal of creating allometric functions describing distributions of stem wood, stem bark, branches, and foliage for each clone. In addition, we calcu lated ratios to quantify efficiency of stem production, including stem biomass / crown volume and stem biomass / leaf biomass.

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22 A destructive harvest was carried out on March 13 and March 16 19, 2012. Each sample tree was cut at the base and separated into stem and branch+foliage components. The total green weight of stem and branch+foliage components was measured in the field; then, appropriate sub sampling was performed to calculate component dry mass of stem wood, stem bark, branches, and foliage. Due t o field and/or data recording errors, data were discarded for two trees from each of clones ARB 1 and ARB 4. As a result, the final sample size for clones ARB 1, ARB 2, and ARB 4 was 6, 8, and 6 trees, respectively. After drying, a small, medium, and lar ge tree was selected from each clone. Subsamples of stemwood, bark, branch, foliated branches, non foliated branches and foliage collected from these trees were chipped and ground in a Wiley Mill to pass through a 1mm stainless steel sieve. The subsamples were stored in plastic tubes, labeled, and sent to an independent laboratory at the Micro Macro International in Athens, Georgia, USA, for a complete nutrient analysis. About 0.5 g of ground tissue samples was first dry ashed in a muffle furnace and then the samples were brought up to volume with aqua regia (3:1 HNO3 : HCl). The extracts were then analyzed using inductively coupled plasma atomic emission spectroscopy (ICP AES; MMI Labs, Athens, GA, USA). Total N was analyzed in a CNS analyzer (LECO Corpo ration, St. Joseph, MI, USA) using the Dumas Method (Campbell, 1992) Intercepted Photosynthetically Active Radiation and Canopy Openness Canopy openness and intercepted photosynthetically active radiation (IPAR) were derived from pictures taken using a he and measurements made with a ceptometer, respectively.

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23 To determine the IPAR in each plot, below canopy radiation was characterized by taking measurements with a ceptometer in a clear day near ground level halfway between each tree w ithin the five internal rows, and spatially averaged along a transect along each of the six inter row spaces, for a total of 36 measurements per plot. At the same time as the ceptometer measurements, measurements of photosynthetically active radiati on were made with a sensor (Li 190, Licor, Lincoln, Nebraska) attached to a datalogger (CR 10X, Campbell Scientific, Logan, Utah) in an adjacent clearing. Percent IPAR was calculated as the difference between above and below canopy PAR, divided by above canopy PAR, multiplied by 100. Ceptometer measurements were taken on October 31 and November 8 of 2012. Hemispherical photographs were taken on January 14 and 16 of 2013, near ground level in the same locations as the ceptometer sampling using a hemisphe rical lens ( FC E8 0.21x fisheye lens, Nikon) and a digital camera (NIKON E995). The photographs were analyzed for % canopy openness with an image analysis program (Gap Light Analyzer, Simon Frazer University, Institute of Ecosystem Studies, Millbrook, Ne w York). Data Analysis Allometric relationships were tested by regressing the natural log transformed age 3 year component biomass (stem, branch, bark and foliage) against the natural log transformed total biomass for three clones. The linear form of the allometric equation used was: L n ( Y ) = B o + B 1 ln ( X ) + error Where ln ( Y ) is the natural logarithm of one component biomass and ln ( X ) is the natural logarithm of the total biomass, and B o and B 1 are the regression coefficients. A

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24 similar equation was used to determine the relationship between component biomass and DBH 2 *H. Analysis of covariance was used to test for differences in component biomass distribution among clones. When there were no significant differences (p=0.05) in a particular equation among cl ones, a single regression was developed. Analyses were performed with SAS software version 9.3. The variables were analyzed with PROC test. Stem Biomass Increment was calcula ted using the allometric equations applied for height and diameter of year 2 and year 3. Results Biomass Distribution All of the clones chosen for this study were highly productive, and this was reflected in the inventory data in Table 2 3: clone ARB 2 had a significantly greater Age 3 stem volume compared to the other three clones however Clones ARB2 and ARB 4 had significantly wider absolute CW than the other two clones. However, when CW was normalized by total tree height, clone ARB 1 had the narrowe st crown, while ARB 4 had the widest. Clone ARB 2 had 50% higher stem volume than the other clones in the study, and significantly greater efficiency index than the other clones (Table 2 3). Clones ARB 4 and ARB 1 had similar stem volume to each other bu t different relative crown width/height, with ARB 4 having the greatest relative crown width of the sampled clones (0.559), and ARB 1 having the narrowest (0.496). Clone ARB 2 had an intermediate CW/H of 0.524.

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25 Log log equations of component biomass versu s total biomass were analyzed to determine if there were differences among clones in the distribution of component biomass (Table 2 4). For stem, there were no differences among clones in either the slope or the intercept of the relationship between stem b iomass and total biomass. In other words, for a given total tree biomass, all clones allocated similar amounts of biomass to the stem. For bark, clone ARB 4 had a significantly higher slope and a significantly more negative intercept than the other two cl ones. Clone ARB 1 had a significantly higher slope and a significantly more negative intercept in the relationship between branch biomass and total biomass compared to the other two clones. For foliage, clone ARB 2 had a significantly greater slope and a more negative intercept than the other two clones. After observing the contrast for slopes and intercepts for all the variables among clones (Table 2 4), we combined data for clones that had no differences to derive appropriate component regression equati ons (Table 2 5). Figures 2 2 to 2 6 show the allometric relationships for the biomass components. Similar analyses were performed for log log plots of component biomass versus D 2 H (Table 2 6). Single component equations were derived for clones with no dif ferences in slope and intercept for a particular component (Table 2 7), and then the final equations were used to estimate component biomass from plot level inventory data. The final equations were also used to calculate stem biomass index between age 2 an d age 3. Growth Efficiency Components of stem biomass increment and foliage biomass were also analyzed. The foliage biomass analysis showed that all the clones were significantly different (Table 2 8) For instance, clone ARB 1 had 1712 kg/ha, clone ARB 2 had 3394

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26 kg/ha and clone ARB 4 had 2608 kg/ha. Then, the stem biomass index showed that clone ARB 2 was significantly different than clones ARB 1 and ARB 4 (2920 kg/ha/yr, 2310 kg/ha/yr and 2066 kg/ha/yr, respectively). In both components clone ARB 2 pres ented the higher values. IPAR and Open Canopy The light factor was also analyzed under log log plots relationships between the components IPAR and canopy openness (CO). The results showed that these components were not significantly different among clones (Table 2 8). For instance, for the component CO, clone ARB 1 had 36.48%, clone ARB 2 had 36.73% and clone ARB 3 had 37.99%. For the component IPAR clone ARB 1, ARB 2 and ARB 4 had 71.77, 79.44 and 77.06, respectively. Discussion The literature on forest tree ideotypes suggests that small crowned crop ideotypes will have higher growth efficiency than wider crowned competition ideotypes (Dickmann, 1985; Martin et al., 2001). Our initial inventory data partially supported this hypothesis, in that the narrow est crowned clone ARB 1 had higher efficiency (measured as SV/CV) than the widest crowned clone ARB 2. These initial measurements motivated the biomass distribution study, to determine whether variation in allocation of biomass could explain differences i n growth efficiency among the clones. The genetic improvement of loblolly pine may play a significant role in mitigating atmospheric CO 2 by carbon (C) sequestration (Aspinwall et al., 2012). Several studies suggest that genetic variation in biomass partit ioning could also have an important effect on C sequestration (Colbert et al., 1990; Chmura et al., 2007); however, some other studies indicate that whole tree biomass partitioning among genotypes are mainly

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27 driven by ontogeny (King et al., 1999; Aspinwall et al., 2013) and perhaps are also a reaction to stand density (Burkes et al., 2003). Aspinwall et al. (2012) propose that genotypic dissimilarities in individual tree biomass partitioning may have some effects on stand level productivity and C sequestrat ion. For example, genotypes which show larger partitioning to long lived woody components could eventually sequester more C. Moreover, increases in C sequestration with genetically improved loblolly pine genotypes will result in increased volume or dry mas s production (Ryan et al., 2010). In various forest plantation species, deployment of clones has been proposed to result in more uniform plantation growth and development (DeBell and Harrington, 1997; Martin et al., 2001; Bettinger et al., 2009). To under stand which traits are related with greater productivity, studying model trees that have phenotypic characteristics correlated with yield will help to develop necessary loblolly pine ideotypes (Martin et al., 2001, 2005; Nelson and Johnsen, 2008). Variatio n in productivity among different loblolly pine is believed to be related to variations in dry mass partitioning patterns and aboveground dry mass production (Bongarten and Teskey 1987; Li et al. 1991; Chmura et al., 2007). According to Aspinwall et al. (2 012) whole tree allometric relationships may provide a better understanding of the primary component traits which regulate phenotypic variability in whole plant growth and productivity. McCrady and Jokela (1996, 1998) found that differences in volume produ ction among different open pollinated loblolly pine families were associated with variation in crown traits, such as foliage and branch biomass production. A number of interpretations can be derived from the age 3 biomass distribution results in the presen t study. Allocation to stemwood biomass appears to be

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28 conservative: all clones allocated the same fraction to stemwood biomass for a given total biomass. The lower allocation of clone ARB 1 to branches compared to the other two clones is consistent with the fact that ARB 1 had the narrowest CW (Table 2 3). This lower allocation to branch biomass may also contribute to the higher efficiency (SV/CV) of this clone. This same clone also tended to have lower total biomass for a given DBH 2 *H (Figure 2 6). ARB 2 had the highest efficiency index of all clones, and this appeared to be associated with a lower allocation to foliage biomass across most of the range of tree size (Figure 2 5); in other words, ARB 2 produced high levels of stem biomass with relatively smaller production of foliage. This may imply a greater photosynthetic rate for this clone; further measurements would be required to confirm this. Some studies have found that stemwood increases and foliage biomass allocation decreases over time (Albaugh et al., 1998; Jokela and Martin, 2000). In our study, clone ARB 2 had lower foliage biomass allocation but had higher efficiency. Blazier et al. (2002) indicated that there was more dry matter allocation to stems and branches, than to foliage, and in th is study clone ARB 2 showed that same pattern. Stovall et al. (2012a) observed clonal variation in biomass partitioning to foliage, branch and stem likewise in our study especially between clones ARB 4 and ARB 1. Stovall et al. (2013) found that the variet y of biomass partitioning patterns observed among clones of loblolly pines indicates an opportunity to choose clones with rapid stem growth rates and a range of other advantageous features, like clone ARB 1 in our study that has a high stem volume and high efficiency. Emhart et al. (2007) indicates that there is a

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29 relationship between clonal variation of growth and crown architecture, in our study we found some evidence of this in clone ARB 1 and clone ARB 4. Growth efficiency has been shown to vary with bo th genetic and environmental factors. Waring (1983) defined stemwood growth efficiency as the slope of the stemwood growth leaf area relationship, and this concept has been used to incorporate the effects of both photosynthetic efficiency and carbon alloca tion on stemwood production (Vose and Allen, 1988). On the other hand, several studies have shown a high linear relationship among aboveground dry matter production intercepted photosynthetically active radiation (IPAR) (Linder, 1985; Cannell et al., 1987; Dalla Tea and Jokela 1991). Martin and Jokela (2004) and Burkes et al. (2003) found that loblolly efficiency. McCrady and Jokela (1998) found significant variation of E among individual loblolly pine trees, which could mean this factor is significant in species genetic variation. While these observations of growth efficiency variation are interesting, fewer studies have demonstrated what mechanisms underlie changes in efficienc y. Colbert et al. (1991) indicated that loblolly pine allocates higher amount of total aboveground dry matter to branches and foliage and had greater leaf area index (LAI) and intercepted radiation than slash pine (Dalla Tea and Jokela, 1991). Dalla Tea an d Jokela (1991) found that in early stand growth, silvicultural methods that accelerate canopy development could have more influence in southern pines yield by enhanced light interception. LAI could change in time and space among and with species (McCrady and Jokela, 1998). According to Vose et al. (1994), these differences happen

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30 for genetic or environmental factors, tolerance to shading, leaf structure, branch and crown shape, and IPAR. Investigations conducted in different environments and species have a ddressed the relationships among forest productivity, light interception and the distribution of foliage and crowns (Linder et al., 1987; Cannell et al. 1987; Leverenz and Hinckley, 1990). We detected considerable differences among clones in biomass alloca tion for each component such as stem, bark, foliage and branches, including non foliated branches and foliated branches. The lower biomass allocation to branches in ARB 1 may have contributed to greater efficiency (SV/CV), and the lower allocation to folia ge in ARB 2, which was associated with very high stem productivity, suggests greater crown photosynthetic efficiency. Despite clone ARB 2 having higher IPAR, the amount of radiation intercepted among clones was similar. The foliage biomass was significantl y different among clones and stem volume increment (SVI) was significantly different in clone ARB 2, while, clones ARB 1 and ARB 4 did not differ. It is important to establish the importance of family variation between the relationship of canopy structure, light interception and stand dry matter productivity to be able to progress in tree breeding programs (Cannell, 1978) and develop the concept of crop ideotype for commercial uses in southern pine species (Dickmann, 1985). In the McCrady and Jokela (1998) study there was no direct measures of photosynthesis and respiration but their results showed that families of loblolly pine had significant differences in radiation use efficiency (E). For instance, differences in E between

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31 families can be less evident if belowground production estimates were measured (Cannell 1989). Ideotypes may be a useful construct for better understanding the mechanisms of tree and forest growth and inter tree competition. An ideotype is a plant model that is likely to develop the i deal phenotype to enhance productivity (Donald, 1968). McCrady and Jokela (1998) point out that reduction in LAI subsequent of canopy closure will be higher for families that are described as isolation ideotypes (grow fast as broad space of individuals) wh ereas competition ideotype (grows fast in progeny mixture and captures in pure closed stands) would undergo these variations to a lesser extent because they can tolerate h igh stand densities or compete for limited resources. Dickmann (1985) stated that trees that have narrow crowned crop ideotypes have been hypothesized to be more efficient than more wide crowned individuals (competition ideotypes). One of the main objecti ves of this study was to define whether clonal variation in biomass distribution patterns could help explain variation in growth efficiency between the narrow crown clones and wide crown clones, like ARB 1 and ARB 4. Subsequently, the results of the initia l inventory data on crown width and growth efficiency were consistent with mentioned hypothesis. At this stage, intriguing differences in allocation to biomass components exist in the three clones examined. Further analysis of nutrient concentration and c ontent of biomass components may allow further interpretation of the mechanisms underlying differences in efficiency of these clones.

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32 Table 2 1. Summary of the installation of the FBRC VARIETIES I clonal plot trial at Starke, FL planted in January 2009. Genetics Entries Treatments / Experimental design ArborG en Varieties ARB 1 ARB 2 ARB 3 ARB 4 Half sib 7 56 Plus mixed plots of 4 varieties Two planting densities: 2.7 x 3.7 m ( 1000 tp ha) 1.5 x 3.7 m (1 802 tp h a) Randomized complete bloc k, 4 reps Plot s ize 0.028 0.049 ha Table 2 2. Treatment history for the VARIETIES I experiment near Starke, FL. Year Month Treatment Type Comments 2008 7 Bedding Double pass with b edding plow 2008 11 Chemical site prep 3.36 kg/ha of imazapyr and 2.8 l /ha of m ethyl ated s eed oil (MSO) 2009 1 Planting Conducted per study plan, surrounding plantation established with improved slash pine 2009 2 Tip moth control 0.67 kg/ha of e sfenvalerate over pine seedlings for immediate tip moth control 2009 2 Tip moth control 1.4 7 kg/ha of fipronil (PTM) was applied via soil injection for extended tip moth control 2009 4 Fertilization 55.8 kg/ha of K (as KCl) and 20.2 kg/ha of N and 22.5 kg/ha of P (as di ammonium phosphate ) 2009 6 Hardwood control 0.21 kg/ha sulfometuron methyl (Oust) 2010 3 Tip moth control 1.05 kg/ha fipronil (PTM) 2010 4 Fertilization 75.65 kg/ha of N (as Urea) 2010 10 Directed spray Triclopyr (3%), Imazipyr (1%), metsulfuron methyl (0.625%) 2011 3 Fertilization 33.6 kg/ha of N, 33.6 kg/ha of P, 33.6 kg/ ha of K + micro nutrient blend 2011 6 Mowing Knock down broom sedge to facilitate spraying 2011 9 Directed spray Glyphosate (3.75%) 2012 9 Directed spray Glyphosate (3.75%)

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33 Table 2 3. Age 3 year tree level characteristics, stem volume (SV), crown vo lume (CV), crown width (CW), relative crown width (CW/H) and stem volume growth efficiency (SV/CV) for four clones in the VARIETIES I experiment near Starke, FL. Within a column and a biomass component, parameter estimates followed by the same lower case l etter were not significantly different at p = 0.05 level. Clone SV (dm 3 ) CV (m 3 ) CW (m) CW/H SV/CV (dm 3 /m 3 ) ARB 4 ARB 3 ARB 1 ARB 2 14.81 b 12.85 b 14.18 b 22.87 a 5.53 b 4.66 b 4.75 b 6.91 a 1.91 a 1.79 b 1.77 b 2.05 a 0.559 c 0.517 b 0.496 a 0.524 b 2.41 c 2.63 ac 2.79 a 3.21 b Values followed by a different letter are statistically different (p < 0.05). Table 2 4. Analysis of the log log relationships between age 3 year component biomass and total biomass for three clones in the VARIETIES I experiment near Starke, FL. Within a column and a biomass component, parameter estimates followed by the same lower case letter were not significantly different at p = 0.05 level. Equation clone slope intercept Stem: lnstem= intercept + slop e*lntotal ARB 1 ARB 2 ARB 4 0.96 a 1.00 a 1.06 a 0.71 a 1.02 a 1.12 a Bark: lnbark= intercept + slope*lntotal ARB 1 ARB 2 ARB 4 0.65 a 0.69 a 1.56 b 1.75 a 1.67 a 3.80 b Branches: lnbranch= intercept + slope*lntotal ARB 1 ARB 2 ARB 4 1.69 a 0.94 b 1.09 b 3.25 a 1.46 b 1.85 b Foliage: lnfoliage= intercept + slope*lntotal ARB 1 ARB 2 ARB 4 0.71 a 1.14 b 0.79 a 0.66 a 1.42 b 0.61 a Total: lntotal= intercept + slope*lnD 2 H ARB 1 ARB 2 ARB 4 1.03 a 0.64 b 0.57 b 8.15 a 4.13 b 3.49 b Folia ge: lnfoliage= intercept + slope*lnbranch ARB 1 ARB 2 ARB 4 0.33 a 1.11 b 0.66 ab 0.71 a 0.40 a 0.79 a

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34 Table 2 5. Parameter estimates for the log log relationships between age 3 year biomass components for three clones in the VARIETIES I experiment nea r Starke, FL. Data were combined for clones when the analysis in Table 2 4 showed no significant difference in the slopes or intercepts for those clones. Equation clones slope Intercept R 2 MSE Stem: lnstem= intercept + slope*lntotal All 0.961 0.846 0.9 46 0.015 Bark: lnbark= intercept + slope*lntotal ARB 1/ARB 2 0.737 1.84 0.938 0.011 ARB 4 1.557 3.803 0.982 0.014 Branches: lnbranch= intercept + slope*lntotal ARB 2/ARB 4 1.004 1.63 0.926 0.026 ARB 1 1.698 3.246 0.886 0.077 Foliage: lnfoliage= intercept + slope*lntotal ARB 1/ARB 4 0.815 0.759 0.867 0.022 ARB 2 1.135 1.424 0.966 0.02 Total: lntotal= intercept + slope*lnD 2 H ARB 2/ARB 4 0.618 3.918 0.967 0.011 ARB 1 1.031 8.152 0.875 0.026

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35 Table 2 6. Analysis of the log log relationships between age 3 year component biomass and D 2 H for three clones in the VARIETIES I experiment near Starke, FL. Within a column and a biomass component, parameter estimate s followed by the same lower case letter were not significantly different from each ot her at the p = 0.05 level. Equation clone slope Intercept Stemwood: lnstem= intercept + slope*lnD 2 H ARB 1 0.99 a 8.61 a ARB 2 0.66 b 5.33 b ARB 4 0.62 b 4.92 b Bark: lnbark= intercept + slope*lnD 2 H ARB 1 0.66 ab 6.92 ab ARB 2 0.45 a 4.61 a ARB 4 0.91 b 9.39 b Branches: lnbranch= intercept + slope*lnD 2 H ARB 1 1.72 a 16.81 a ARB 2 0.59 b 5.21 b ARB 4 0.61 b 5.49 b Foliage: lnfoliage= intercept + slope*lnD 2 H ARB 1 0.76 ab 6.69 ab ARB 2 0.71 a 5.99 a ARB 4 0.45 b 3.35 b Total: lntotal= intercept + slope*lnD 2 H ARB 1 1.03 a 8.15 a ARB 2 0.64 b 4.13 b ARB 4 0.57 b 3.49 b Fbranches: lnfbranch= intercept + slope*lnD 2 H ARB 1 1.36 a 14.17 a ARB 2 0.43 ab 5.09 ab ARB 4 0.75 b 8.25 b NFbranches: lnnfbranch= intercept + sl ope*lnD 2 H ARB 1 1.94 a 19.63 a ARB 2 0.64 b 5.98 b ARB 4 0.55 b 5.26 b

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36 Table 2 7. Parameter estimates for the log log relationships between age 3 year biomass components for three clones in the VARIETIES I experiment near Starke, FL. Data were c ombined for clones when the analysis in Table 2 6 showed no significant difference in the slopes or intercepts for those clones. Equation C lones S lope Intercept R2 MSE Stem: lnstem= intercept + slope*lnD 2 H ARB 1 0.997 8.613 0.881 0.023 ARB 2/ARB 4 0.6 44 5.165 0.989 0.004 Bark: lnbark= intercept + slope*lnD 2 H ARB 1/ARB 2 0.513 5.343 0.829 0.032 ARB 1/ARB 4 0.869 9.014 0.959 0.014 ARB 2 0.452 4.613 0.979 0.004 ARB 4 0.908 9.395 0.99 0.008 Branches: lnbranch= intercept + slope*lnD 2 H ARB 1 1.7 21 16.806 0.75 0.169 ARB 2/ARB 4 0.607 5.426 0.857 0.052 Foliage: lnfoliage= intercept + slope*lnD 2 H ARB 1/ARB 2 0.761 6.573 0.854 0.058 ARB 2/ARB 4 0.507 4.058 0.683 0.053 ARB 2 0.715 5.987 0.903 0.056 ARB 4 0.452 3.347 0.937 0.013 Total: lntotal= intercept + slope*lnD 2 H ARB 1 1.031 8.152 0.875 0.026 ARB 2/ARB 4 0.618 3.918 0.967 0.011 Foliage: lnfbranch= intercept + slope*lnD 2 H ARB 1/ARB 2 0.5 5.793 0.288 0.363 ARB 1/ARB 4 0.84 9.118 0.478 0.341 ARB 2 0.426 5.097 0.481 0.199 ARB 4 0.748 8.25 0.777 0.15 Total: lnnfbranch= intercept + slope*lnD 2 H ARB 1 1.941 19.631 0.501 0.643 ARB 2/ARB 4 0.622 5.859 0.831 0.066

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37 Table 2 8. Average values of % canopy openness (% CO) foliage biomass (Folbio), stem biomass increment (SBI) a nd incident photosynthetically active radiation (IPAR). Within a column, values followed by the same letter were not significantly different (P= 0.05). Clone % CO Folbio (kg/ha) SBI (kg/ha/yr) IPAR ARB 1 36.48 a 1712 a 2310 a 71.77 a ARB 2 36.73 a 3394 b 2920 b 79.44 a ARB 4 37.99 a 2608 c 2066 a 77.06 a

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38 Figure 2 1. FBRC Varieties I. Color pink: ARB 1 (moderate crown), color yellow: ARB 2 (broad crown), color blue: ARB 3 (moderate narrow crown) and color orange: ARB 4 (moderate crown). 2.7x3.7 m Spacing 1.5x3.7 m Spacing

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39 Figure 2 2. Log log plot of bark biomass vs. total biomass for three l oblolly pine clones in the VARIETIES I experiment near Starke, FL. Figure 2 3. Log log plot of stem biomass vs. total biomass for three loblolly pine clones in the VARIETIES I exp eriment near Starke, FL.

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40 Figure 2 4. Log log plot of branch biomass vs. total biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL. Figure 2 5. Log log plot of foliage biomass vs. total biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL.

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41 Figure 2 6. Log log plot of total biomass vs. dbh 2 *height biomass for three loblolly pine clones in the VARIETIES I experiment near Starke, FL.

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42 CHAPTER 3 VARIATION IN NUTRIENT CONTENT IN THREE LOBLOLLY PINE CLONES WITH CONTRASTING CROWN ARCHITECTURE The concept of ideotype developed by Donald (1968) is a theoretical model of plant phenotype proposed to promote better management of a particular desired crop or of crop characteristics. Id eotypes have been proposed as a useful approach for breeding and for understanding the physiological underpinnings of growth (Dickman, 1985). Several ideotypes have been proposed with respect to forest trees managed in plantation systems. The crop ideotyp e does not compete aggressively with its neighbors and uses resources efficiently, and it is more probable to produce improved yield in monoculture (Cannell, 1978). Competition ideotypes, on the other hand, compete aggressively with their neighbors and are hypothesized to be less efficient users of resources (Cannell, 1978). In terms of crown architecture, it has been proposed that crop ideotypes might tend to have more compact, narrow crowns, while competition ideotypes would have wider crowns (Cannell, 1 978; Martin et al., 2005). Martin et al. (2001) pointed out that in traditional single tree progeny trials, crop ideotypes were likely to be overlooked. In young stands before canopy closure, isolation ideotypes (Cannell, 1978) are likely to perform best After canopy closure competition ideotype are likely to perform best Staudhammer et al. (2009) identified loblolly pine ( Pinus taeda L.) and slash pine Pinus elliottii Engelm. var. elliottii ) families with characteristics consistent with both crop and competition ideotypes. In blocks planted with pure families, both narrow crowned and wide crowned families performed well, but in mixed family plots, the wide crowned family performance increased, and the narrow crowned family performance decreased. Stau dhammer et al. (2009) pointed out the possible benefits of planting crop ideotypes

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43 at closer spacing including improved efficiency and possibly increase stand level yield. Several studies have shown that southern pine crown traits are heritable, (Lambeth and Huber, 1997; Emhart et al., 2007), so indirect selection for "efficiency" could be possible if crown traits turn out to be a good surrogate for efficiency or crop vs. competition ideotype traits. In addition, it is important to study crown and branch a rchitecture since they are important determinants of wood product quality (Amateis et al., 2004; Briggs et al., 2007). The major limitation to growth rate of southern pines throughout their natural range is soil nutrient availability, often nitrogen (N) a nd phosphorus (P) (Schulze et al., 1995; Jokela and Martin, 2000; Fox et al., 2007a). Forest fertilization is a common technique used to relieve nutrient deficiencies in southern pine stands (Albaugh et al., 2007; Fox et al., 2007a); however, the costs of fertilizer materials and application have been rising rapidly as fossil fuel costs have risen. Tree genotypes with improved nutrient use efficiency (e.g. greater production of stem wood per unit applied or absorbed nutrient) could potentially reduce manag ement costs and increase the efficiency of wood production. Variation among loblolly pine clones in growth and biomass allocation in a greenhouse test has been shown (Tyree et al. 2009a, 2009b), but studies showing family or clonal variation in nutrient e fficiency in the field are rare. (Prasolova et al., 2005; Stovall et al., 2011). This study examined variation in stand level stem growth, biomass partitioning, and component nutrient content among loblolly pine clones having contrasting crown architecture and growing in pure clonal blocks Clones previously shown to vary in crown size and tree level biomass partitioning (Chapter 2) were compared to determine

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44 whether tree level traits were good indicators of ideotype traits at the stand level. In other wo rds, we hypothesized that narrow crowned clones would have greater stand level efficiency in terms of stem biomass produced per unit foliage or biomass nutrient content, consistent with predictions for crop ideotypes. Methods Study A rea The Varietal Archit ecture Investigations Examining Tree Interactions on Experimental Sites (VARIETIES I), is a clonal block plot experiment located near Starke, Florida ( 29 53' 7.6734" N, 82 3' 24.7458" W ). The climate is humid subtropical, with a mean annual temperature o f 20C and mean annual precipitation of 1225 mm (NOAA 1999 2012). Soils at the site are somewhat poorly drained Spodosols and are mapped as the Sapelo fine sands series (sandy, siliceous, thermic Ultic Alaquods). The spodic horizon is approximately 40 cm deep, with a sandy clay loam argillic horizon at 100 120 cm. Residual understory vegetation at the site includes saw palmetto ( Serenoa repens ) and gallberry ( Ilex glabra ). During May and July of 2008 the site was prepared by chopping and bedding. In Januar y 2009, genetically improved containerized loblolly pine seedlings were planted. Experimental Design The study consists of four clones (ARB 1, ARB 2, ARB 3, ARB 4) and one full sib family (7 56) planted at two densities: wide, 1000 trees/ha (2.7x3.7 m) an d narrow, 1802 trees/ha (1.5x3.7 m), (see Table 2 1 from Chapter 2). The clones were planted in 7 rows x 7 tree plots (0.028 containing mixtures of the four clones. Fertilizer was applied in April of 2009 and 2010

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45 and March of 2011. Herbicide treatments were also applied periodically to control understory competition (see Table 2 2 from Chapter 2). Sample Tree Selection An inventory conducted in December, 2011 included measurements of tree height (H), diameter at breast height (DBH), and crown width (CW) measured in two directions for all genotypes in the study. Stem volume index (SV, DBH 2 H), crown volume (CV, calculated as a paraboloid), relative crown width (CW/H) and an index of stem volume growth efficiency (SV/CV) and crown shape ratio (crown length / crown width) were derived from the inventory measurements. Based on an analysis of the inventory data, three contrasting clones were chosen for measurement of biomass distribution: ARB 1, ARB 2, a nd ARB 4. ARB 1 and ARB 4 were chosen because they had the narrowest and widest average CW/H, respectively and also had contrasting SV/CV efficiency index. In addition, we chose to measure the biomass distribution for ARB 2 because this clone had the hig hest productivity of all clones in the study (see Table 2 3 from Chapter 2). Allometric equations were developed from destructive biomass harvests of individuals from each clone (Chapter 2). Component Biomass Stand level component biomass accumulation w as calculated from clone specific allometric equations (Chapter 2), using age 3 year diameter and height inventory data. Fractional biomass distribution was calculated from the stand level component biomass data.

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46 Nutrient Sampling Prediction equations of total tree and component dry biomass were developed by destructive sampling of 20 trees, 6 trees of clone ARB 1, 8 trees of clone ARB 2 and 6 trees of clone ARB 4, as described in Chapter 2. For a small, medium, and large sampled tree in each clone, subsam ples of dried stemwood, bark, branch, foliated branches, non foliated branches and foliage were chipped and ground in a Wiley Mill to pass a 1mm stainless steel sieve. The subsamples were stored in labeled plastic tubes and sent to an independent laborator y at the Micro Macro International in Athens, Georgia, USA, for a complete nutrient analysis. About 0.5 g of ground tissue samples was first dry ashed in a muffle furnace and then the samples were brought up to volume with aqua regia (3:1 HNO3 : HCl). Th e extracts were then analyzed using inductively coupled plasma atomic emission spectroscopy (ICP AES; MMI Labs, Athens, GA, USA). Total N was analyzed in a CNS analyzer (LECO Corporation, St. Joseph, MI, USA) using the Dumas Method (Campbell, 1992). Data Analysis Allometric equations were developed to calculate component biomass. The linear form of allometric equation was used: Component biomass (kg) = (exp (k1)*(D 2 H)*k2)*CF Where k1 is the intercept and k2 is the slope of the allometric equations develop ed in chapter 2 (see Table 2 7 from Chapter 2). When equations were used to predict biomass, they were corrected for log bias (Baskerville, 1972). Plot level nutrient contents were calculated by multiplying the average clonal nutrient concentration for eac h component by the component biomass derived from allometry. Ratios of N: P and N: K were analyzed to determine foliar nutrient differences.

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47 Analysis of variance was performed with the GLM procedure in SAS software version 9.3. Comparisons among means were tested for significance (p < 0.05) using Results Component B iomass The analysis of component biomass accumulation showed some differences among clones. In all the cases clone ARB 2 ha d higher total aboveground biomass accumulation than the other two clones (Table 3 1). T he total aboveground biomass for clone ARB 1, ARB 2 and ARB 4 were 5664 kg/ha/yr, 9935 kg/ha/yr and 7272 kg/ha/yr, respectively. For the components foliage, branches an d non foliated branches we observed that all the clones were statistically different, but clone ARB 4 had higher values (2607 kg/ha of foliage, 1477 kg/ha of branches and 1116 kg/ha of non foliated branches) than clone ARB 1 (1712 kg/ha of foliage, 923 kg/ ha of branches and 611 kg/ha of non foliated branches). The components stemwood, bark and foliated branches showed that clone ARB 2 was significantly different than the other two clones, but ARB 1 and ARB 4 were similar. The stem and foliage component biom ass was consistently higher than bark or branch biomass among the 3 clones (Figure 3 1). Clone ARB 1 had the lowest total biomass in all the components compared with the other 2 clones. In contrast, the analysis of fraction component biomass presented some different results compared with the analysis of component biomass (Table 3 2). For instance, for the foliage fraction differences among clones were significant, with clone ARB 4 ha ving a higher value (0.36) than clone ARB 1 (0.30). For the stem (0.44), fo liated branches (0.07) and non foliated branches (0.11) components the results showed that clone ARB 1 was significantly greater than the other two clones, but ARB 2 and ARB 4 were

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48 similar. For non foliated branches, clone ARB 4 had a higher value than ARB 1 (0.15 and 0.11, respectively). The bark fraction of clone ARB 4 (0.07) was significantly lower than for clones ARB 1 and ARB 2 (0.09). Component Nutrient Concentration In many cases, clone ARB 4 had higher biomass component nutrient concentrations than the other two clones (Table 3 3). For example, ARB 4 had higher foliar N concentrations (14.9 g/kg) than the other two clones (12.9 g/kg), and also had higher foliar P concentrations (1.1 g/kg for ARB 4, vs. about 0.9 g/kg for ARB 1 and ARB 2). Clone ARB 4 had higher concentrations of P (0.5 g/kg), Ca (1.8 g/kg), Mg (0.6 g/kg) and S (0.5 g/kg) in the bark than clone ARB 1 (0.4 g/kg, 1.3 g/kg, 0.7 g/kg and 0.3 g/kg, respectively). ARB 4 also had higher stem Ca concentrations (0.6 g/kg) than ARB 1 (0.5 g/kg ); the same was true for stem Mg concentrations (0.3 g/kg vs. about 0.2 g/kg for clone ARB 1). Once again, clone ARB 4 had a higher Ca concentration in non foliated branches (1.9 g/kg) than did ARB 1 (1.3 g/kg). Clones ARB 1 and ARB 4 were significantly di fferent, but clone ARB 2 was similar with both. For foliated branches there were no significant differences in nutrient concentrations among clones. Micronutrient concentration patterns were similar to macronutrient concentrations in that clone ARB 4 had h igher values than clone ARB 1 in many cases (Table 3 4). For foliage, clone ARB 4 had higher B (14 mg/kg) concentration than clone ARB 1 (10 mg/kg). Similarly for bark, clone ARB 4 had higher B concentration (10 mg/kg) than clone ARB 1 (9 mg/kg) concentrat ion, but clone ARB 2 was similar with both clones. For stemwood and foliated branches there were no significant differences in B among clones. Boron concentration for non foliated branches was higher in clone ARB 2 than clone ARB 1 (6 mg/kg and 4 mg/kg, r espectively) but clone ARB 4 was similar with

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49 both. In the same way, clone ARB 2 had higher Fe (20 mg/kg) and Mo (0.2 mg/kg) concentrations than clone ARB 1 and clone ARB 2. We did not find any significant differences among the clones in nutrient ratios o f N: P and N: K in any components (Table 3 5). Component Nutrient Content Component nutrient contents at age 3 for clone ARB 4 were generally higher than for clone ARB 1 (Table 3 6). The ARB 4 component foliage contents (N (38.9 kg/ha), P (2.9 kg/ha), K (1 2.7 kg/ha) and Ca (6.5 kg/ha)), were higher than those of clone ARB 1 (22 kg/ha, 2 kg/ha, 8 kg/ha and 4 kg/ha, respectively). For Mg and S contents all the clones were significantly different; however, clone ARB 4 (2.5 kg/ha of Mg and 3.4 kg/ha of S) had h igher contents than clone ARB 1 (1.5 kg/ha of Mg and 1.5 kg/ha of S). For component bark, content of N, K, Mg and S of clone ARB 2 were significantly higher. But for content of Ca clone ARB 4 (0.9 kg/ha) was significantly higher than clone ARB 1 (0.7 kg/ha ). The P content was significantly different among clones, but clone ARB 4 was higher (0.3 kg/ha) than clone ARB 1 (0.2 kg/ha). The content of K, Mg and S was significantly for all the clones of the study in the component stemwood and in these cases clone ARB 4 was higher (2.9 kg/ha, 0.8 kg/ha and 0.5 kg/ha, respectively) than clone ARB 1 (2.2 kg/ha, 0.6 kg/ha and 0.3 kg/ha respectively). However, the content of N, P, and Ca showed that clone ARB 2 is significantly different than clone ARB 1 and ARB 4. In c omponent non foliated branches the content of N, P, K, Ca and Mg were significantly different among clones, but clone ARB 4 had higher content in those nutrients (2.8 kg/ha, 0.2 kg/ha, 1.2 kg/ha, 2.1 kg/ha and 0.4 kg/ha, respectively) than clone ARB 1 (1.5 kg/ha, 0.1 kg/ha, 0.6 kg/ha, 0.8 kg/ha and 0.2 kg/ha, respectively). The content of S was significantly different for clone ARB 2 (0.3

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50 kg/ha). The content of K, Ca, Mg and S showed that clone ARB 2 was significantly different for component foliated branch es. For content of N and P we found that clones ARB 1 and ARB 2 are significantly different but clone ARB 4 is similar with both clones. In addition, it is important to see that the total N, P, Ca and Mg content for all clones was significantly different. However, clone ARB 4 had higher values (52.5 kg/ha, 4 kg/ha, 11.9 kg/ha and 4.3 kg/ha, respectively) than clone ARB 1 (33.5 kg/ha, 2.4 kg/ha, 7.3 kg/ha and 2.9 kg/ha, respectively). The total content of K and S were again higher for clone ARB 4 (19.5 kg/ha and 4.5 kg/ha) than clone ARB 1 (12.8 kg/ha and 2.3 kg/ha). The distribution of the different macronutrients (Figures 3 2 through 3 7) was consistently highest in the foliage component. For the component micronutrient content we did not observe any signif icantly differences in any component among the clones (Table 3 7). However, for the total contents of B, Fe and Mn were significantly different for clone ARB 2, but clone ARB 4 was similar with clone ARB 2 and clone ARB 1. Also, the distribution of the dif ferent micronutrients (Figures 3 8 through 3 12) was consistently highest in the foliage component. Year 2 3 stem biomass increment ( SBI ) for clone ARB 2 (2920 kg/ha/yr) was significantly higher than clone ARB 1 (2310 kg/ha/yr) and clone ARB 4 (2066 m3/ha/ yr) (Table 3 8). The foliar N and foliar P showed that clone ARB 1 was significantly different than the other two clones of the study. Ratios of SBI/Folbio, SBI/Foliar and SBI/Foliar P showed that there were significantly differences among clones, but clon e ARB 1 was significantly higher than the other two clones. Discussion This study examined a number of growth and nutrient traits in a loblolly pine clonal block plot experiment, enabling us to quantify biomass distribution and nutrient

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51 accumulation patter ns at both the tree (in Chapter 2) and stand scale for clones with contrasting crown traits. Our results show interesting patterns of genetic variation, and provide support for variation in growth efficiency associated with variation in crown traits, cons istent with ideotype concepts described in the literature (Cannell, 1989). Genet ic Variation in Biomass Distribution and Nutrient T raits A relatively small number of studies have examined genetic variation in biomass distribution and/or nutrient traits in gymnosperms. Some studies found that, early in forest stand development, most of the biomass is allocated in foliage and fine roots, and stemwood increases over time (Gholz and Fisher, 1982; Miller, 1995; Adegbidi et al., 2002). Improved seedling stock gen etics, site preparation and fertilization have been important factors increasing the productivity of slash and loblolly pine stands in the U.S. South (Adegbidi et al., 2002). It is also important to understand the carbon allocation and nutrient processes e nhance the growth and production of loblolly pine biomass (Adegbidi et al., 2005). Blazier et al. (2002) found that the amount of foliage per branch was considerably influenced by the seed source; also the crown architecture through an efficient intercepti on of light of photosynthesis may influence growth (Chmura et al., 2007). Moreover, it is important to understand the genetic differences in above and belowground dry mass production at stand level because this could influence the productivity and carbon s equestration of southern pines. More research is necessary to evaluate the effects of carbon and nitrogen cycling dynamics of loblolly pine plantations (Aspinwall et al., 2011). In the southeastern United States, nitrogen and phosphorus fertilization of loblolly pine ( P. taeda ) and slash pine ( P. elliottii Engelm.) plantations have been operationally successful (Jokela et al., 1988; Allen et al., 1990). Micronutrient responses (Mn) have

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52 also been documented in rapidly growing stands fertilized with N, P a nd K (Jokela et al., 1991). However, growth dynamics and nutrient demands of fast growing loblolly pine stands are still not well understood (Fox, 2000). To comprehend the mechanisms behind growth performance and nutritional adaptation, physiological studi es under different conditions are necessary (Jansson et al., 2005; Hawkins et al., 2010). Prosalova et al. (2005) indicated that foliar nutrient (especially N) concentration may improve nutrient and water use efficiency. Intensive silvicultural practices, including fertilization, will be necessary to capture the total growth potential of clonal plantations For different species, nutrient use efficiency often increases as nutrient availability decreases (Gray and Schlesinger, 1983; Birk and Vitousek, 1986; L ajtha and Klein, 1988). Stovall et al. (2010) found that clonal differences in nutrient use efficiency could affect growth responses, for instance genotypes that are less responsive to fertilizer application might be fertilized at lower rates, thus reducin g costs without substantially reducing potential growth. Decreasing fertilizer rates in these genotypes may also reduce the occurrence of stem quality deficiencies that have been related with larger nutrient additions (Espinoza, 2009). Hawkins (2007) state d that efficiency of nutrient uptake and utilization contributed to higher growth rates of trees. Therefore, nutrient related traits should be considered in tree breeding programs as evidence of significant genotype nutrient availability relations exists These indications are that assessments for nutrient use efficiency may be made at an early stage (Brown, 1970; Woessner et al., 1975; Jahromi et al., 1976; Bell et al., 1979; Hawkins, 2007). Nutrient related traits tend to be under strong genetic contro l (van den Driessche and El Kassaby, 1991) and are correlated with important traits such as biomass and

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53 height growth (Mari et al., 2003). Some studies have shown important clone by nutrient availability interactions (Beets and Jokela 1994; Tyree et al., 2 009a, 2009b). Hawkins et al. (2010) pointed out that explanations of nutrient uptake based on foliar nutrient concentrations need to be made with great care. High growth rates could cause dilution of nutrients, whereas growth restrictions caused by constra ining environmental or nutritional factors might result in higher foliar concentrations of the nutrient of concern. Plant nutrient content is a better indicator of nutrient uptake; yet, measurement of plant biomass is required. In our study with our biomas s measurements and element concentration we could calculate the nutrient content. There was clonal variation in component nutrient concentration in this study; in most cases clone ARB 4 had higher concentrations of several nutrients among the different bi omass components (Tables 3 3 and 3 4). These elevated nutrient concentrations resulted in in significantly higher nutrient contents for several of the biomass components (Tables 3 6 and 3 7) compared to clone ARB 1. Clone ARB 2 also tended to have relati vely high nutrient content accumulation, primarily due to its high biomass productivity. Ideotypes and Growth E fficiency Ideotypes have long been discussed in the forestry literature as a potential approach for identifying traits for genetic selection, and as a tool for better understanding the mechanisms underlying productivity (Martin et al., 2001). The crop ideotype is an ideal model because it has a narrow crown suitable for growth in dense plantations. Conversely, the competition ideotype will perform better in older or more widely spaced stands (Martin et al., 2005). It is expected that a crop ideotype will be more efficient in terms of biomass productivity. In order to effectively deploy crop

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54 ideotypes, investigation of silvicultural methods and their interactions with biomass partitioning patterns and other traits (Nelson and Johnsen, 2008) will be required. Emhart et al. (2007) mentioned that the variation in crown traits and growth efficiency offers various opportunities for ideotype based clonal se lection. In this study, clone ARB 1 had significantly narrower crowns than the other two clones, and we hypothesized that it might show traits consistent with a crop ideotype. Narrow efficiency t hrough several mechanisms, including altered allocation of biomass to different components, elevated leaf area productivity (perhaps due to increased photosynthesis rates), or increased efficiency of nutrient uptake or utilization. We found evidence of al l three mechanisms in clone ARB 1. Clone ARB 1 had a narrower crown than clone ARB 4, which was in turn manifested at the stand scale as a relative decrease in allocation to branch biomass in that clone. Hence, clone ARB 1 allocated less biomass to branche s and foliage and, therefore, could allocate more biomass to stemwood, which would make this clone ideal as a crop ideotype. Adegbidi et al. (2005) found that stemwood growth efficiency in loblolly pine did not change noticeably between ages 2 and 3 years meaning that biomass allocation did not vary. These results were similar to the stemwood allocation observed at age 3 for the clones examined in this study. T rees with narrow crowns maintain small lateral branches close to the stem, which reduces the non foliated core of the crown (Jack and Long 1992), perhaps providing a better source of assimilates for stemwood production (Stenberg et al.,

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55 1994). The arrangement and the larger branches of loblolly pine may represent an efficient characteristic of foliag e display that enhances light interception through decreases in self shading in closed canopy stands (Dalla Tea and Jokela, 1991). Crown biomass (branch and leaf), total leaf area and their vertical distribution patterns have been related with stand struct ure, forest productivity, and microclimate of the habitat (Maguire and Bennett, 1996). In many species, the positive relationships between leaf area and growth rates or total biomass accumulation have been studied (Gholz et al., 1991; McCrady and Jokela, 1 998). The distribution of leaf area and biomass in a crown may regulates light interception and impact net CO 2 exchange rates at the entire tree and stand levels, leading to an increase in growth (Wang and Jarvis, 1990, Chmura et al., 2007). Moreover, in t his study the decrease in allocation to foliage in clone ARB 1 may reflect an increase in photosynthesis and this could consequently increase stemwood productivity. On the other hand, the genetic differences in partitioning to belowground biomass in loblo lly pine are an important factor of stand carbon sequestration (Ryan et al., 2010, Aspinwall et al., 2011), therefore to decrease the negative effect of CO 2 Also, partitioning of biomass to belowground may contribute to decreasing efficiency (Johnson 1990 Li et al. 1991, Albaugh et al.1998). In this study we did n o t examine belowground biomass allocation, but this will be important for future research to have a better estimation of carbon allocation and growth efficiency. Clone ARB 1 and ARB 4 produced si milar levels of stem wood biomass (Table 3 1), but clone ARB 1 had significantly lower nutrient concentration and content for several elements in most biomass components. When expressed as stem volume increment per unit foliar N or foliar P content, clone ARB 1 was more efficient than

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56 either clone ARB 2 or ARB 4. This difference could point to the possibility of finding or breeding clones with elevated nutrient use efficiency, which could lead to greater stem wood production with fewer costly nutrient input s. Nutrient use efficiency has been most commonly defined in terms of biomass production per unit of nutrient uptake (Gholz et al., 1985; Elliott and White, 1993); this definition could help to evaluate nutrient utilization and production efficiency (Xiao 2000). Nutritional differences among genotype are usually indicated using foliage nutrient concentrations and content (Sari, 1981). Consistently, N use efficiency could be an important selection trait for increasing loblolly pine productivity because mos t pine plantations in Florida are deficient in N and P, but not in Ca and Mg (Jokela et al., 1988). Also, Prosalova et al. (2005) found that P, N, K, and Cu are the important mineral nutrients to be considered for foliar diagnostic analysis and foliar nutr ient concentration, especially N, along with carbon isotope discrimination could be useful to improve nutrient use efficiency. If we observed the total shown in Table 3 4 and the increment shown in Table 3 8, we can see that Clone ARB 1 and clone ARB 4 had similar levels of stem productivity, although clone ARB 1 reached its level of stem growth with less foliar biomass (Table 3 8) and less foliar N, P, K and Ca content (Table 3 6). This suggests that clone ARB 1 was more efficient at producing stem wood bi omass per unit foliar biomass and unit foliar nutrient than clone ARB 4. This is consistent with the hypothesis of ARB 1 being a crop ideotype. The main result of this study is the difference between clones ARB 1 and ARB 4. ARB 1 was narrow crowned, and t hat was evident in the branch biomass and the fraction of biomass allocated to branches at the stand level. Both clones had similar levels of stem productivity, but clone ARB 1 achieved that level of stem growth with less

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57 foliar biomass and less foliar N, P, K and Ca content. This implies that ARB 1 was more efficient at producing stem wood per unit foliar biomass and unit foliar nutrient than clone ARB 4. This result supports our premise that clone ARB 1 was a crop ideotype. As this study only focused o n juvenile growth patterns, further investigations are needed to determine if the concept of ideotype persists into different stand ages and stages of stand development.

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58 Table 3 1. Biomass accumulation (kg/ha) patterns of foliage, stemwood, bark, branche s, foliated branches (FB) and non foliated branches (NFB). among three different clones of loblolly pine at age 3. Within a column, values followed by the same letter were not significantly different (P= 0.05). Clone Foliage Stemwood Bark Branches (Kg/ha) FB NFB Total ARB 1 1712 a 2562 a 513 a 923 a 385 a 611 a 5664 a ARB 2 3394 b 3703 b 924 b 2008 b 510 b 1527 b 9935 b ARB 4 2607 c 2682 a 518 a 1477 c 394 a 1116 c 7272 a Table 3 2. Ratios of component biomass / total biomass for foliage, stemwood, bark, foliated branches (FB) and non foliated branches (NFB) for stands of three different clones of loblolly pine at age 3. Within a column, values followed by the same letter were not significantly different (P= 0.05). Clone Folbio Stemwood Bark FB NFB ARB 1 0.30 a 0.44 b 0.09 a 0.07 b 0.11 b ARB 2 0.34 b 0.37 a 0.09 a 0.05 a 0.15 a ARB 4 0.36 c 0.37 a 0.07 b 0.05 a 0.15 a

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59 Table 3 3. Macroelement concentrations in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB). Stand ard Deviations are in parentheses. Within each element and component combination, values followed by the same lower case letter were not significantly different at p = 0.05 level. Component Clone N P K Ca Mg S g/kg Foliage ARB 1 12.9 a 0.9 a 4.4 a 2.2 a 0.9 a 0.9 a (1.51) (0.02) (0.86) (0.81) (0.11) (0.06) ARB 2 12.9 a 0.9 a 3.4 a 2.2 a 1.1 a 0.8 a (0.21) (0.04) (0.40) (0.25) (0.07) (0.58) ARB 4 14.9 b 1.1 b 4.9 a 2.5 a 1.0 a 1.3 a (0.67) (0.08) (0.42) (0.61) (0.13) (0.40) Bark ARB 1 5.0 a 0.4 a 3.3 a 1.3 a 0.7 a 0.3 a (0.61) (0.05) (0.92) (0.13) (0.03) (0.06) ARB 2 5.3 a 0.5 ab 4.0 a 1.0 a 0.5 b 0.3 a (0.31) (0.03) (0.44) (0.16) (0.06) (0.06) ARB 4 5.8 a 0.5 b 3.7 a 1.8 b 0.6 ab 0.5 b (0.57) (0.07) (0.45) (0.18) (0.12) ( 0.06) Stemwood ARB 1 2.1 a 0.2 a 0.8 a 0.5 a 0.2 a 0.1 a (0.21) (0.02) (0.18) (0.01) (0.02) (0.06) ARB 2 2.3 a 0.2 a 1.0 a 0.6 b 0.2 ab 0.1 a (0.31) (0.04) (0.20) (0.03) (0.02) (0.06) ARB 4 2.1 a 0.2 a 1.1 a 0.6 b 0.3 b 0.2 a (0.12) (0.005) ( 0.07) (0.03) (0.03) (0.06) NFB ARB 1 2.4 a 0.2 a 0.9 a 1.3 a 0.3 a 0.2 a (0.45) (0.03) (0.21) (0.05) (0.03) (0.12) ARB 2 2.9 a 0.2 a 1.1 a 1.7 ab 0.4 a 0.2 a (0.59) (0.03) (0.08) (0.40) (0.06) (0.10) ARB 4 2.5 a 0.2 a 1.0 a 1.9 b 0.4 a 0.1 a (0.29) (0.03) (0.21) (0.26) (0.05) (0.10) FB ARB 1 5.3 a 0.5 a 2.1 a 1.8 a 0.7 a 0.4 a (0.79) (0.03) (0.20) (0.81) (0.11) (0.06) ARB 2 5.1 a 0.5 ab 2.2 a 1.8 a 0.6 a 0.4 a (0.89) (0.07) (0.24) (0.34) (0.10) (0.10) ARB 4 5.9 a 0.5 a 2.2 a 2.0 a 0 .7 a 0.4 a (0.55) (0.06) (0.23) (0.20) (0.04) (0.06)

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60 Table 3 4. Microelement concentrations ( mg/kg ) in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB). Standard Deviations are in parentheses. Within each element and c omponent combination, values followed by the same lower case letter were not significantly different at p = 0.05 level. Component Clone B Cu Fe mg/kg Mn Mo Zn Foliage ARB 1 9.8 a 1.7 a 27.7 a 31.6 a 0.1 a 18.7 a (0.94) (0.52) (1.63) (0.58) (0.20) (3.4 0) ARB 2 12.4 ab 1.9 a 25.8 a 38.2 a 0.02 a 13.4 a (2.55) (0.58) (3.16) (13.97) (0.03) (4.68) ARB 4 13.9 b 1.7 a 31.3 a 43.9 a 0.1 a 12.3 a (0.83) (0.73) (5.16) (28.96) (0.03) (2.01) Bark ARB 1 8.9 a 2.6 a 19.3 a 24.5 a 0.3 a 29.3 a (0.59) (0 .55) (2.50) (5.64) (0.47) (1.14) ARB 2 9.6 ab 2.2 a 30.1 a 25.3 a 0.1 a 27.6 a (0.37) (0.46) (16.43) (5.47) (0.12) (3.46) ARB 4 10.2 b 2.1 a 31.9 a 18.6 a 0.4 a 43.8 a (0.79) (0.90) (287.85) (3.71) (0.57) (37.90) Stemwood ARB 1 2.9 a 2.2 a 11.9 a 10.4 a 0.2 a 8.8 a (0.26) (0.56) (4.12) (2.48) (0.03) (0.67) ARB 2 3.2 a 1.9 a 15.1 a 10.5 a 0.2 a 8.0 ab (0.22) (0.43) (3.91) (0.43) (0.15) (0.46) ARB 4 3.3 a 1.6 a 10.6 a 7.5 a 0.1 a 7.6 b (0.10) (0.37) (1.63) (1.29) (0.09) (0.29) NFB ARB 1 4.4 a 2.3 a 10.0 a 16.2 a 0.0 a 10.7 a (0.37) (0.49) (0.84) (3.24) (0.00) (2.94) ARB 2 5.9 b 1.9 a 19.5 b 22.1 a 0.2 b 10.5 a (0.68) (0.32) (3.52) (8.88) (0.09) (2.89) ARB 4 5.2 ab 1.9 a 14.0 a 13.6 a 0.04 a 7.9 a (0.50) (0.25) (0.96) (3.89 ) (0.06) (1.05) FB ARB 1 7.3 a 3.2 a 19.1 a 27.7 a 0.1 a 16.4 a (0.72) (1.31) (2.95) (1.79) (0.10) (4.59) ARB 2 7.7 a 2.1 a 19.6 a 33.1 a 0.04 a 12.1 a (0.83) (0.74) (3.80) (6.45) (0.06) (2.57) ARB 4 7.9 a 2.1 a 18.0 a 28.7 a 0.1 a 11.8 a (0. 64) (0.86) (3.21) (11.85) (0.06) (2.15)

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61 Table 3 5. Ratios in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) between nitrogen:phosphorus (N:P) and nitrogen:potasium (N:K) based on component concentrations. Within each nut rient ratio and biomass component for the various clones, values followed by the same lower case letter were not significantly different at p = 0.05 level. Component Clone N:P N:K Foliage ARB 1 14.82 a 2.98 a ARB 2 14.76 a 3.31 a ARB 4 13.73 a 3.09 a Bark ARB 1 11.41 a 1.58 a ARB 2 11.09 a 1.33 a ARB 4 10.69 a 1.57 a Stemwood ARB 1 12.50 a 2.51 a ARB 2 12.48 a 2.20 a ARB 4 12.31 a 1.91 a NFB ARB 1 12.77 a 2.62 a ARB 2 12.18 a 2.67 a ARB 4 11.77 a 2.49 a FB ARB 1 11.38 a 2.57 a ARB 2 1 0.70 a 2.28 a ARB 4 10.94 a 2.54 a

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62 Table 3 6 Average component macronutrient content (kg/ha) in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) among different clones of loblolly pine at age 3. Within each element and c omponent combination, values followed by the same lower case letter were not significantly different at p = 0.05 level. Clone Component [N] [P] [K] (kg/ha) [Ca] [Mg] [S] ARB 1 Foliage 22.1 b 1.5 b 7.6 b 3.8 b 1.5 a 1.5 a ARB 2 43.8 a 2.9 a 11.7 a 7.5 a 3.7 b 2.7 b ARB 4 38.9 a 2.9 a 12.7 a 6.5 a 2.5 c 3.4 c ARB 1 Bark 2.6 a 0.2 a 1.7 a 0.7 b 0.4 a 0.15 a ARB 2 4.9 b 0.4 b 3.7 b 0.9 a 0.5 b 0.28 b ARB 4 3.0 a 0. 3 c 1.9 a 0.9 a 0.3 a 0.26 a ARB 1 Stem 5.4 a 0.4 a 2.2 a 1.3 a 0.6 a 0.3 a ARB 2 8 .5 b 0.7 b 3.9 b 2.3 b 0.9 b 0.4 b ARB 4 5.6 a 0.5 a 2.9 c 1.6 a 0.8 c 0.5 c ARB 1 NFB 1.5 a 0.1 a 0.6 a 0.8 a 0.2 a 0.1 a ARB 2 4.4 b 0.4 b 1.7 b 2.5 b 0.6 b 0.3 b ARB 4 2.8 c 0.2 c 1.2 c 2.1 c 0.4 c 0.1 a ARB 1 FB 2.0 a 0.18 a 0.8 a 0.7 a 0.3 a 0 .15 a ARB 2 2.6 b 0.24 b 1.1 b 0.9 b 0.33 b 0.20 b ARB 4 2.3 ab 0.21 ab 0.9 a 0.8 a 0.3 a 0.16 a ARB 1 TOTAL 33.5 a 2.4 a 12.8 b 7.3 a 2.9 a 2.3 b ARB 2 64.3 b 4.7 b 22.0 a 14.2 b 5.9 b 3.9 a ARB 4 52.5 c 4.0 c 19.5 a 11.9 c 4.3 c 4.5 a

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63 Table 3 7. Average of component micronutrient content (mg/ha) in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) among different clones of loblolly pine at age 3. Within each element and component combination, values followed by th e same lower case letter were not significantly different at p = 0.05 level. Clone Component [B] [Cu] [Fe] (mg/ha) [Mn] [Mo] [Zn] ARB 1 Foliage 16.8 a 2.8 a 47.5 a 54.0 a 0.2 a 32.1 a ARB 2 41.9 a 6.3 a 87.5 a 129.7 a 0.1 a 45.5 a ARB 4 36.3 a 4.5 a 81.6 a 114.4 a 0.2 a 32.0 a ARB 1 Bark 4.6 a 1.3 a 9.9 a 12.6 a 0.2 a 15.0 a ARB 2 8.9 a 2.1 a 27.8 a 23.4 a 0.1 a 25.5 a ARB 4 5.30 a 1.1 a 16.5 a 9.6 a 0.2 a 22.7 a ARB 1 Stemwood 7.7 a 5.7 a 30.4 a 26.6 a 0.5 a 22.5 a ARB 2 11.8 a 7.0 a 55.8 a 38.8 a 0.6 a 29.7 a ARB 4 8.9 a 4.3 a 28.3 a 20.1 a 0.2 a 20.5 a ARB 1 NFB 2.7 a 1.4 a 6.1 a 9.9 a 0.00 a 6.6 a ARB 2 9.1 a 3.0 a 29.7 a 33.7 a 0.32 a 16.0 a ARB 4 5.8 a 2.1 a 15.7 a 15.2 a 0.04 a 8.8 a ARB 1 FB 2.8 a 1.2 a 7.3 a 10.7 a 0.05 a 6.3 a ARB 2 3.9 a 1.2 a 9.9 a 16.2 a 0.03 a 6.7 a ARB 4 3.1 a 0.8 a 7.2 a 11.7 a 0.03 a 4.7 a ARB 1 TOTAL 34.6 a 12.5 a 101.2 a 113.7 a 0.9 a 82.5 a ARB 2 75.6 b 19.6 a 210.7 b 241.8 b 1.2 a 123.4 a ARB 4 59.4 ab 12.8 a 149.4 ab 171.0 ab 0.7 a 88.6 a Table 3 8. Average foliage biomass (Folbio), foliar crown nitrogen content (Foliar N), foliar crown phosphorus content (Foliar P), stem biomass increment from age 2 3 years (SBI) and ratios of SBI/Folbio ( (kg/ha/yr stem) / (kg foliage biomass)) SBI/Fol iar N ((kg/ha/yr stem) / (kg foliar N content)) and SBI/Foliar P ((kg/ha/yr stem)/(kg foliar P content)). Within a column, values followed by the same letter were not significantly different (P= 0.05). Clone Folbio Kg/ha Foliar N Kg/ha Foliar P Kg/ha SBI Kg/ha/yr SBI/ Folbio SBI/ Foliar N SBI/ Foliar P ARB 1 1712 a 22.09 b 1.50 b 2310 a 1.35 a 104.59 a 1547.65 a ARB 2 3394 b 43.79 a 2.98 a 2920 b 0.86 b 66.85 b 982.95 b ARB 4 2608 c 38.86 a 2.85 a 2066 a 0.79 c 53.10 c 724.50 c

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64 Figure 3 1. Distribution of aboveground biomass ( foliage stemwood, bark, branches, foliated branches (FBranch) and non foliated branches (NFB ranch)) among three different clones of loblolly pine at age 3. Figure 3 2. Distribution of nitrogen (N) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3.

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65 Figure 3 3. Distribution of p hosphorus (P) content in foliage, bark, stem wood non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. Figure 3 4. Distribution of potassium (K) content in foliage, bark, st emwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3.

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66 Figure 3 5 Distribution of calcium (Ca) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3. Figure 3 6. Distribution of magnesium (Mg) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at age 3.

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67 Figure 3 7. Distribution of s ulfur (S) content in foliage, bark, stem wood non foliated branches (NFB) and foliated branches (FB) biomass among three differe nt clones of loblolly pine at age 3. Figure 3 8. Distribution of boron (B) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass among three different clones of loblolly pine at ag e 3.

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68 Figure 3 9. Distribution of c opper (Cu) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. Figure 3 10. Distribution of i ron (Fe) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3.

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69 Figure 3 11. Distribution of m ang anese (Mn) content in foliage, bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3. Figure 3 12. Distribution of m olybdenum (Mo) content in foliage bark, stemwood, non foliated branches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3.

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70 Figure 3 13. Distribution of z inc (Zn) content in foliage, bark, stemwood, non foliated bran ches (NFB) and foliated branches (FB) biomass in three different clones of loblolly pine at age 3.

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71 CHAPTER 4 SUMMARY AND CONCLUSION S The concept of ideotype developed by Donald (1968) has long been discussed as a potential method for recognizing traits fo r genetic selection, and could lead to understanding the mechanisms that control growth and productivity in different plantations (Martin et al., 2001). Related with the concept of ideotype, the variation in growth efficiency associated with variation in c rown traits (Cannell, 1989) could give several opportunities for clonal selection (Emhart et al. (2007). In the ideotype literature, crop ideotypes are often hypothesized to have narrower crowns than competition ideotypes, and to be more efficient in use o f resources (Martin et al., 2005 ; Cannell, 1978). In our study we analyzed three clones of loblolly pine ( Pinus taeda L.) that have narrow and broad crown and they varied in growth efficiency, biomass distribution and component nutrient content. We found that differences in tree level and stand level biomass allocation existed among the three clones. Also, differences in nutrient accumulation among the components of the three clones were evident, especially between the narrow crowned clone ARB 1 and the wi de crowned clone ARB 4. Results of the initial inventory data on crown width (CW) and growth efficiency were consistent with the concept of a crop ideotype. Clones ARB 1 and ARB 4 have similar levels of stem productivity, but clone ARB 1 reached that level of stem growth with less foliar biomass and nutrient content This suggests that clone ARB 1 was more efficient at producing stem per unit foliar biomass and unit foliar nutrient than clone ARB 4; this, too, was consistent with the concept that clone ARB 1 met the criteria for a crop ideotype. If a clone of P. taeda contains fewer nutrients than another clone but produces

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72 the same amount of biomass or more, it means that the first clone was more efficient. The idea is to find a clone that produces a large amount of biomass without requiring large nutrient additions. In our study, we found that clone ARB 1 presented a pattern consistent with the ideotype concept. However, further investigation of belowground biomass allocation, different stand levels and age s will be necessary, since this study only examined juvenile loblolly pine through age 3 year and aboveground biomass allocation. With this study, we increased and developed better understanding of the relationship between crown structure and tree product ivity and the causes that contributed to variation in growth efficiency. In addition, it is important enhance the knowledge about the genetic variation in allocation and nutrient content in loblolly pine plantation and this research may help in defining m anagement options for clonal populations of trees.

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73 APPENDIX TREE AND PLOT LEVEL DATA Table A 1. Plot level c omponent m acronutrient c ontent (kg/ha) in three different clones of loblolly pine at age 3. Plot Clone Component [N] [P] [K] (kg/ha) [Ca] [Mg] [S] 7 ARB 1 Foliage 20.46 1.38 7.00 3.53 1.41 1.43 14 ARB 1 21.53 1.46 7.37 3.71 1.48 1.50 28 ARB 1 23.34 1.58 7.99 4.02 1.61 1.63 46 ARB 1 23.01 1.55 7.87 3.97 1.59 1.61 12 ARB 2 45.72 3.11 12.17 7.82 3.81 2.84 15 ARB 2 37.76 2.57 10.05 6.46 3 .15 2.34 30 ARB 2 50.76 3.45 13.51 8.69 4.23 3.15 45 ARB 2 40.90 2.78 10.89 7.00 3.41 2.54 10 ARB 4 36.26 2.66 11.82 6.07 2.33 3.16 16 ARB 4 38.82 2.84 12.65 6.49 2.50 3.39 29 ARB 4 43.79 3.21 14.27 7.33 2.82 3.82 44 ARB 4 36.54 2.68 11.91 6.11 2.35 3.19 7 ARB 1 Bark 2.40 0.21 1.57 0.64 0.35 0.14 14 ARB 1 2.50 0.22 1.64 0.67 0.36 0.15 28 ARB 1 2.70 0.24 1.77 0.73 0.39 0.16 46 ARB 1 2.65 0.24 1.74 0.71 0.38 0.16 12 ARB 2 5.06 0.45 3.81 0.99 0.48 0.29 15 ARB 2 4.46 0.40 3.36 0.87 0.42 0 .25 30 ARB 2 5.40 0.48 4.07 1.05 0.51 0.31 45 ARB 2 4.67 0.42 3.51 0.91 0.44 0.26 10 ARB 4 2.64 0.25 1.69 0.80 0.28 0.23 16 ARB 4 2.96 0.28 1.90 0.89 0.32 0.26 29 ARB 4 3.63 0.34 2.33 1.09 0.39 0.31 44 ARB 4 2.78 0.26 1.78 0.84 0.30 0.24 7 ARB 1 Stemwood 4.88 0.39 1.97 1.20 0.54 0.23 14 ARB 1 5.25 0.41 2.12 1.28 0.58 0.25 28 ARB 1 5.69 0.45 2.30 1.39 0.63 0.27 46 ARB 1 5.69 0.45 2.30 1.39 0.63 0.27 12 ARB 2 8.87 0.72 4.02 2.41 0.96 0.39 15 ARB 2 7.45 0.60 3.38 2.02 0.81 0.32 30 ARB 2 9.75 0.79 4.42 2.64 1.06 0.42 45 ARB 2 8.00 0.65 3.62 2.17 0.87 0.35 10 ARB 4 5.12 0.41 2.64 1.45 0.70 0.49 16 ARB 4 5.60 0.45 2.88 1.59 0.76 0.53 29 ARB 4 6.56 0.52 3.37 1.86 0.90 0.62 44 ARB 4 5.25 0.42 2.70 1.49 0.72 0.50

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74 Table A 1. Contin ued Plot Clone Component [N] [P] [K] (kg/ha) [Ca] [Mg] [S] 7 ARB 1 Non Foliated 1.23 0.09 0.48 0.64 0.17 0.10 14 ARB 1 Branches 1.46 0.11 0.56 0.76 0.20 0.12 28 ARB 1 1.51 0.12 0.58 0.78 0.21 0.13 46 ARB 1 1.66 0.13 0.64 0.87 0.23 0.14 12 ARB 2 4.6 1 0.38 1.76 2.63 0.65 0.32 15 ARB 2 3.89 0.32 1.49 2.22 0.55 0.27 30 ARB 2 5.05 0.42 1.93 2.88 0.71 0.35 45 ARB 2 4.17 0.34 1.59 2.38 0.59 0.29 10 ARB 4 2.54 0.22 1.05 1.89 0.38 0.10 16 ARB 4 2.77 0.24 1.14 2.07 0.41 0.11 29 ARB 4 3.24 0.28 1.3 3 2.41 0.48 0.13 44 ARB 4 2.60 0.22 1.07 1.94 0.39 0.10 7 ARB 1 Foliated 1.80 0.16 0.70 0.59 0.23 0.14 14 ARB 1 Branches 2.00 0.18 0.78 0.66 0.26 0.15 28 ARB 1 2.15 0.19 0.84 0.71 0.28 0.16 46 ARB 1 2.22 0.19 0.86 0.73 0.29 0.17 12 ARB 2 2.79 0.2 4 1.09 0.92 0.36 0.21 15 ARB 2 2.38 0.22 1.04 0.85 0.29 0.19 30 ARB 2 2.85 0.27 1.24 1.02 0.35 0.22 45 ARB 2 2.49 0.23 1.08 0.88 0.31 0.19 10 ARB 4 1.80 0.17 0.79 0.64 0.22 0.14 16 ARB 4 2.31 0.21 0.87 0.78 0.28 0.16 29 ARB 4 2.75 0.26 1.04 0.9 3 0.33 0.19 44 ARB 4 2.16 0.20 0.81 0.73 0.26 0.15 7 ARB 1 T otal 30.77 2.23 11.72 6.60 2.70 2.04 14 ARB 1 32.74 2.38 12.47 7.09 2.89 2.18 28 ARB 1 35.40 2.57 13.48 7.64 3.12 2.35 46 ARB 1 35.24 2.56 13.42 7.67 3.12 2.34 12 ARB 2 67.04 4.90 22.85 14.77 6.27 4.04 15 ARB 2 55.95 4.11 19.31 12.43 5.22 3.37 30 ARB 2 73.81 5.41 25.17 16.28 6.87 4.45 45 ARB 2 60.22 4.42 20.71 13.34 5.62 3.63 10 ARB 4 48.37 3.70 17.98 10.85 3.91 4.12 16 ARB 4 52.46 4.03 19.45 11.83 4.27 4.44 29 ARB 4 59.97 4. 61 22.34 13.63 4.91 5.07 44 ARB 4 49.33 3.78 18.28 11.11 4.01 4.18

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75 Table A 2. Plot level c omponent m icronutrient c ontent (mg/ha) in three different clones of loblolly pine at age 3. Plot Clone Component [B] [Cu] [Fe] (mg/ha) [Mn] [Mo] [Zn] 7 ARB 1 Foliage 15.58 2.62 43.97 50.04 0.17 29.71 14 ARB 1 16.39 2.75 46.27 52.66 0.18 31.26 28 ARB 1 17.77 2.99 50.16 57.10 0.20 33.90 46 ARB 1 17.51 2.94 49.44 56.27 0.20 33.40 12 ARB 2 43.81 6.56 91.37 135.43 0.07 47.53 15 ARB 2 36.18 5.41 75.45 111.8 3 0.06 39.25 30 ARB 2 48.64 7.28 101.45 150.36 0.08 52.77 45 ARB 2 39.19 5.87 81.74 121.15 0.06 42.52 10 ARB 4 33.87 4.21 76.19 106.78 0.22 29.88 16 ARB 4 36.26 4.51 81.57 114.31 0.23 31.99 29 ARB 4 40.91 5.08 92.02 128.96 0.26 36.09 44 ARB 4 3 4.13 4.24 76.78 107.60 0.22 30.11 7 ARB 1 Bark 4.28 1.22 9.24 11.73 0.14 14.04 14 ARB 1 4.47 1.28 9.64 12.25 0.15 14.66 28 ARB 1 4.83 1.38 10.42 13.24 0.16 15.84 46 ARB 1 4.74 1.35 10.23 13.00 0.16 15.55 12 ARB 2 9.18 2.12 28.74 24.18 0.12 26.34 15 ARB 2 8.10 1.87 25.36 21.33 0.11 23.24 30 ARB 2 9.81 2.26 30.70 25.83 0.13 28.14 45 ARB 2 8.48 1.96 26.54 22.33 0.11 24.33 10 ARB 4 4.65 0.93 14.52 8.45 0.16 19.92 16 ARB 4 5.23 1.05 16.33 9.51 0.18 22.40 29 ARB 4 6.40 1.28 19.98 11.63 0.23 2 7.41 44 ARB 4 4.91 0.98 15.31 8.91 0.17 21.00 7 ARB 1 Stemwood 6.95 5.16 27.57 24.11 0.44 20.44 14 ARB 1 7.47 5.55 29.63 25.91 0.47 21.96 28 ARB 1 8.11 6.02 32.16 28.12 0.52 23.83 46 ARB 1 8.11 6.02 32.16 28.12 0.52 23.84 12 ARB 2 12.26 7.29 58. 07 40.41 0.66 30.89 15 ARB 2 10.31 6.12 48.80 33.96 0.55 25.96 30 ARB 2 13.47 8.01 63.81 44.41 0.72 33.94 45 ARB 2 11.06 6.57 52.37 36.45 0.59 27.86 10 ARB 4 8.10 3.90 25.73 18.29 0.22 18.61 16 ARB 4 8.85 4.27 28.13 20.00 0.24 20.34 29 ARB 4 10 .37 5.00 32.95 23.42 0.28 23.83 44 ARB 4 8.30 4.00 26.37 18.75 0.22 19.07

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76 Table A 2. Continued Plot Clone Component [B] [Cu] [Fe] (mg/ha) [Mn] [Mo] [Zn] 7 ARB 1 Non Foliated 2.28 1.18 5.15 8.33 0.00 5.50 14 ARB 1 Branches 2.70 1.40 6.11 9.89 0.00 6.53 28 ARB 1 2.79 1.44 6.31 10.20 0.00 6.73 46 ARB 1 3.08 1.59 6.96 11.25 0.00 7.43 12 ARB 2 9.50 3.15 30.90 35.04 0.33 16.65 15 ARB 2 8.03 2.66 26.11 29.61 0.28 14.07 30 ARB 2 10.40 3.45 33.84 38.38 0.37 18.23 45 ARB 2 8.59 2.84 27.93 31.68 0 .30 15.05 10 ARB 4 5.29 1.94 14.28 13.85 0.04 7.99 16 ARB 4 5.77 2.12 15.57 15.10 0.04 8.71 29 ARB 4 6.73 2.47 18.16 17.62 0.05 10.16 44 ARB 4 5.41 1.99 14.60 14.16 0.04 8.17 7 ARB 1 Foliated 2.49 1.09 6.47 9.41 0.04 5.57 14 ARB 1 Branches 2.77 1 .22 7.20 10.48 0.05 6.20 28 ARB 1 2.97 1.31 7.73 11.24 0.05 6.65 46 ARB 1 3.07 1.35 7.98 11.60 0.05 6.86 12 ARB 2 3.85 1.69 10.02 14.57 0.06 8.62 15 ARB 2 3.59 0.97 9.14 15.48 0.02 5.64 30 ARB 2 4.30 1.16 10.95 18.55 0.02 6.76 45 ARB 2 3.75 1.0 1 9.53 16.15 0.02 5.88 10 ARB 4 2.72 0.73 6.92 11.73 0.01 4.27 16 ARB 4 3.07 0.83 7.05 11.21 0.04 4.62 29 ARB 4 3.67 0.98 8.41 13.37 0.04 5.51 44 ARB 4 2.88 0.77 6.60 10.50 0.03 4.33 7 ARB 1 T otal 31.57 11.27 92.40 103.63 0.80 75.25 14 ARB 1 33. 80 12.19 98.86 111.18 0.85 80.60 28 ARB 1 36.47 13.13 106.77 119.89 0.93 86.95 46 ARB 1 36.51 13.26 106.76 120.24 0.92 87.08 12 ARB 2 78.61 20.80 219.10 249.63 1.25 130.03 15 ARB 2 66.20 17.03 184.86 212.22 1.02 108.15 30 ARB 2 86.63 22.16 240.75 277.52 1.32 139.84 45 ARB 2 71.06 18.25 198.12 227.76 1.09 115.64 10 ARB 4 54.64 11.72 137.65 159.11 0.66 80.68 16 ARB 4 59.19 12.77 148.64 170.13 0.74 88.07 29 ARB 4 68.08 14.82 171.51 195.01 0.86 103.00 44 ARB 4 55.63 11.98 139.66 159.93 0.69 82.69

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77 Table A 3 Plot level v alues of foliage biomass (kg/ha), foliar N content (kg/ha), foliar P content (kg/ha) and age 2 3 year stem biomass increment (SBI, kg/ha/yr). Plot Clone Foliage biomass Foliar N Foliar P S B I 7 ARB 1 1586 20.46 1.38 2112 14 ARB 1 1669 21.53 1.46 2262 28 ARB 1 1810 23.34 1.58 242 3 46 ARB 1 1783 23.01 1.55 2433 12 ARB 2 3544 45.72 3.11 307 2 15 ARB 2 2927 37.76 2.57 258 4 30 ARB 2 3935 50.76 3.45 327 3 45 ARB 2 3171 40.90 2.78 275 3 10 ARB 4 2434 36.26 2.66 1886 16 ARB 4 2605 38.82 2.84 204 9 29 ARB 4 2939 43.80 3.21 2405 44 ARB 4 2452 36.54 2.68 192 5

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78 Table A 4. Individual tree component biomass harvest data for foliage, bark, stemwood, branch, foliated branches (FB) and non foliated branches (NFB) among three diff erent clones of loblolly pine at age 3. Clone Tree ID Height (cm) DBH (cm) Foliage Bark Stemwood (kg) Branch FB NFB GE 34 681 363 5.4 1.53 0.47 2.09 0.57 1.72 0.38 GE 34 1368 369 6.7 1.83 0.51 2.66 0.53 2.25 0.11 GE 34 309 355 7.1 1.61 0.55 2.63 1.18 2. 20 0.59 GE 34 2211 449 7.0 2.67 0.83 4.40 1.43 3.14 0.96 GE 34 2219 431 7.7 2.81 0.71 4.02 1.44 3.01 1.25 GE 34 296 506 7.7 3.07 0.91 5.95 3.95 5.15 1.87 NQ 26 2191 245 3.4 0.70 0.37 0.92 0.61 0.89 0.42 NQ 26 721 391 7.7 3.04 0.88 3.74 2.00 3.74 1.30 NQ 26 2199 399 8.4 4.66 0.95 4.29 2.39 5.06 1.99 NQ 26 541 414 8.8 4.49 1.07 4.03 1.66 4.71 1.45 NQ 26 584 409 9.4 5.01 1.24 4.67 3.01 5.55 2.48 NQ 26 553 440 9.5 6.40 1.30 5.46 4.06 6.95 3.51 NQ 26 2157 457 10.0 3.49 1.20 5.68 2.69 4.17 2.00 NQ 26 1 467 457 10.7 5.46 1.34 6.66 3.44 6.40 2.50 PM 51 780 231 4.0 1.49 0.15 1.20 0.69 1.62 0.55 PM 51 781 360 7.0 2.78 0.57 2.93 1.07 3.09 0.76 PM 51 782 399 8.0 2.99 0.87 4.00 1.86 3.51 1.34 PM 51 756 453 8.2 3.84 0.98 4.41 1.99 4.35 1.49 PM 51 483 420 9. 1 4.63 1.23 5.17 2.63 5.09 2.17 PM 51 447 410 9.4 3.95 1.02 4.47 3.12 5.20 1.86

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81 Chmura, D.J., Tjoelker, M.G., Martin, T. A., 2009. Environmental and genetic effects on crown shape in young loblolly pine plantations. Canadian Journal of Forest Research 39, 691 698. C olbert, S.R., Jokela, E.J., Neary, D.G., 1990. Eff ects of annual fertilization and sustained weed control on dry matter partitioning, leaf area, and growth efficiency of juvenile loblolly and slash pine. Forest Science 36, 995 1014. Colbert, S.R., Allen., H.L., 1991. Potential productivity of loblolly pi ne plantations in the southeastern United States. pp 146 147 In: D.L., Mengel, and D. T., Tew, (eds). Ecological Land Classification: Applications to Identify the Productive potential of Southern Forests. USDA Forest Service Southeast. For. Exp. Sta. Gen. Tech. Rep. SE 68. Dalla Tea, F., Jokela, E.J., 1991. Needlefall, canopy light interception, and productivity of young intensively managed slash and loblolly pine stands. Forest Science 37, 1298 1313. Davis, J.M., Jokela, E.J., Martin, T.A., Peter, G.F., 2010. Forest Biology Research Cooperative 14th Annual Report. University of Florida, Gainesville, Florida. p.90. De Bell, D.S., Harrington, C.A., 1997. Productivity of Populus in monoclonal and polyclonal blocks at three spacings. Canadian Journal of Fore st Research 27, 978 985. Dickmann, D.I., 1985. The ideotype concept applied to forest trees. pp. 89 101 in Attributes of trees as crop plants. Cannell, M.G.R., and Jackson, J.E. (eds.). Inst. of Terrestrial Ecol., Huntington, England. Dickmann, D.I., Gol d, M.A., Flore, J.A., 1994. The ideotype concept and the genetic improvement of tree crops. Plant Breeding Reviews 12, 163 193. Donald, C.M., 1968. The breeding of crop ideotypes. Euphytica 17, 385 403. Donald, C.M., Hamblin, J., 1976. The biological y ield and harvest index of cereals as agronomic and plant breeding criteria Advances in Agronomy 28, 361 405 Elliott, K. J., White, A.S., 1993. Effects of competition from young northern hardwoods, on red pine seedling growth, nutrient use efficiency, and leaf morphology. Forest Ecology and Management 57, 233 255. Emhart, V.I., Martin, T.A., White, T.L., Huber, D.A., 2007. Clonal variation in crown structure, absorbed photosynthetically active radiation and growth of loblolly pine and slash pine. Tree Phy siology 27, 421 430. Espinoza, J.A., 2009. Genetic and nutritional effects on stem sinuosity in loblolly pine. In: Forestry. North Carolina St ate University, Raleigh, NC, p. 102.

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82 Fox, T.R., 2000. Sustained productivity in intensively managed forest planta tions. Forest Ecology and Management 138, 187 202. Fox, T.R., Allen, H.L., Albaugh, T.J., Rubilar, R. Carlson, C.A., 2007a. Tree nutrition and forest fertilization of pine plantations in the southern United States. Southern Journal of Applied Forestry 3 1, 5 11. Fox, T.R., Jokela, E.J., Allen, H.L., 2007b. The development of pine plantation silviculture in the southern United States. Journal of Forestry 105, 337 347. Gholz, H.L., Fisher, R.F., 1982. Organic matter production and distribution in slash pin e (Pinus elliottii) plantations. Ecology 63, 1827 1839. Gholz, H.G., Fisher, R.F., Pritchett, W.L., 1985. Nutrient dynamics in slash pine plantation ecosystems. Ecology 66, 647 659. Gholz, H. L., Vogel, S.A., Cropper, Jr., W.P., McKelvey, K., Ewel, K.C., Teskey, R.O., Curran, P.J., 1991. Dynamics of canopy structure and light interception in Pinus elliottii stands, North Florida. Ecological Monographs 61, 33 51. Gonzalez, J., Fisher, R.F., 1997. Variation in foliar elemental composition in mature wild tr ees and among families and provenances of Vochysia guatemalensis in Costa Rica. Silvae Genetica 46, 45 50. Gray, J.T., Schlesinger, W.H., 1983. Nutrient use by evergreen and deciduous shrubs in southern California. Journal of Ecology 71, 43 56. Hawkins, B.J., 2007. Family variation in nutritional and growth traits in Douglas fir seedlings. Tree Physiology 27, 911 919. Hawkins, B.J., Xue, J.M., Bown, H.E., Clinton, P.W., 2010. Relating nutritional and physiological characteristics to growth of Pinus radia ta clones planted on a range of sites in New Zealand. Tree Physiology 30, 1174 1191. Jack, S. B., Long, J. N., 1992. Forest production and the organization of foliage within crowns and canopies. Forest Ecology and Management 49, 233 245. Jahromi, S.T., Goddard, R.E., Smith, W.H., 1976. Genotype x fertilizer interactions in slash pine: growth and nutrient relations. Forest Science 22, 211 219. Jansson, G., Jonsson, A., Eriksson, G., 2005. Use of trait combinations for evaluating juvenile mature relations hips in Picea abies (L.). Tree Genetics and Genome 1, 21 29.

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83 Jokel a, E.J., Harding, B., Troth, J.L., 1988. Decision making criteria for forest fertilization in the Southeast:An industrial perspective. Southern Journal of Applied Forestry, 12, 153 160. Jo kela, E.J., McFee, W.W., Stone, E.L., 1991. Micronutrient deficiency in slash pine: response and persistence of added manganese. Soil Science Society of American Journal 55, 492 496. Jokela, E.J., Martin, T.A., 2000. Effects of ontogeny and soil nutrient supply on production, allocation, and leaf area efficiency in loblolly and slash pine stands. Canadian Journal of Forest Research 30, 1511 1524. King, J.S., Albaugh, T.J., Allen, H.L., Kress, L.W., 1999. Stand level allometry in Pinus taeda as affected b y irrigation and fertilization. Tree Physioliogy 19, 769 778. Lajtha, K., Klein, M., 1988. The effect of varying nitrogen and phosphorus availability on nutrient use by Larrea tridentata, a desert evergreen shrub. Oecologia, 75, 348 353. Lambeth, C.C., H uber, D.A., 1997. Inheritance of branching and crown traits and their relationship to growth rate in loblolly pine. In Proc. 24th Southern Forest Tree Improvement Conference, Orlando, FL, pp 214 223. Leverenz, J. W., Hinckley, T.M., 1990. Shoot structure, leaf area index and productivity of evergreen conifer stands Tree Physiology 6, 135 149. Li B., McKeand S.E., Allen H.L., 1991. Nitrogen and family effects on biomass allocation of loblolly pine seedlings. Forest Science 37(1), 271 283. Linder, S., 1 985. Potential and actual production in Australian forest stands. In: Landsberg, J. J., and W. Parsons, eds. Research for Forest Management. CSIRO, Melbourne, Australia. p. 11 35. Linder, S., Benson, M.L., Myers, B.J., Raison, R.J., 1987. Canopy dynamics an d growth of Pinus radiata. I Effects of irrigation and fertilization during a drought. Canadian Journal of Forest Research 17, 1157 1165. Long, J.N., Smith, F.W., 1992. Volume increment in Pinus contorta var. latifolia: the influence of stand development and crown dynamics. Forest Ecology and Management 53, 53 64. Maguire, D.A., Bennett, W.S., 1996. Patterns in vertical distribution of foliage in young coastal Douglas Canadian Journal of Forest Research 26 1991 2005.

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87 BIOGRAPHICAL SKETCH Angelica Milagros Garcia Villacorta was born in Lima, Peru in 1981 She got a bachelor degree in biology with focus in e cology from Universidad Nacional Agraria La Molina in 2006. After her graduation, she got a scholar ship for the course called (OTS) at Los Amigos Biological Station, Madre de Dios, Peru. Subsequently, she started to work at Cocha Cashu Biological Station (CCBS) located a t Manu National Park in Madre de Dios, Peru where she worked as field manager and research a ssistant She worked there for 3 years. While she was working at CCBS in 2007 she got a grant for conducting field studies for bachelors thesis given by Amazon Conservation Association (ACA) at Los Amigos Biological Stat ion where she also worked as a scientific a ssistant, but after this she continue working at CCBS. Later she got an internship at the Center for Tropical Conservation (CTC) at Duke University where she worked analyzing data of some botany projects of Dr. John Terborgh. After this time she studie d a specialization in audit management and environmental q ua lity in Universidad Nacional Agraria La Molina. At the same time, she joined an environmental consultant firm concentrating her work in the development of biological baselines which include studies of botany and wildlife. Later, she started working as wild life s upervisor for an agency of the Peruvian Government. In 2010, she received a Fulbright Scholarship to study a Master of Science degree. She started her studies in the fall of 2011 at the School of Forest Resources and Conservation at the University of Florida.