Reinvigorating Oleoresin Collection in the Southeast Usa: Evaluation of Chemical Inducers, Stand Management, Tree Characteristics, and Genetics

Home , Bark hack, Natural rubber, Oleoresin

REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST USA: EVALUATION OF CHEMICAL INDUCERS, STAND MANAGEMENT, TREE CHARACTERISTICS, AND GENETICS

MARIE JENNIFER LAUTURE

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2017

In memory of Joel Baussan, Sarah Lauture, and Marguerite Marie Yolande Lauture “Mamie”

ACKNOWLEDGMENTS

I would like to thank my very large family for their unconditional love and support throughout this journey. To my mother, Marie Anne, a woman who sacrificed so much for her children and the strongest person I know. I thank her for teaching me to be resilient, humble, kind, patient, and independent. I thank her for her inspiring me to never give up and accompanying me on all my adventures across rural Haiti. To my father, Jean Marie, for always providing me with motivation throughout my studies and all my endeavors. I thank my sisters, Raquel Aïna, Anne Xavière, Stephanie, and Lya, for your unwavering love, support, and encouragement. I feel very blessed to have three older sisters that inspire me with their intelligence, creativity, love, passion, and hard work. I am immensely grateful to my loving partner and adventure buddy, Cody, who always encouraged me to pursue my dreams, always championed my accomplishments and has supported me through the difficult times. I thank you for your patience and dedication.

I would like to share my gratitude with my graduate advisor, Dr. Gary Peter, without whom this research would have been futile. I started working with him as an undergraduate student and without his guidance, support, and dedication, I would have never pursued my graduate studies. I thank Dr. Alan Hodges for his assistance with statistical analysis, expertise and guidance in the field, and for teaching me the borehole tapping technique to collect oleoresin. I would like to acknowledge all other members of my supervisory committee: Dr. Salvador Gezan, Dr. Eric Jokela, and Dr. John Davis, for their advice and expertise. I want to thank Dr. Gezan for his assistance with data analysis and helping me learn ASReml.

Many thanks to the faculty and staff at the School of Forest Resources and

Conservation (SFRC) and the forest genomics lab. I appreciate the funding support from the Florida Department of Agriculture and Consumer Services Office of Energy and the Department of Energy Advanced Research Projects Agency (ARPA-E). I want to thank Rayonier, Weyerhaeuser (formerly Plum Creek Timber Company), and Roberts

Land & Timber Investment Corp. for providing access to the study sites.

I would like to express my gratitude to Chris Dervinis for his help in organizing my field experiments, his ability to always make me laugh with his nerdy dad jokes, and for always being available to answer my questions and provide me with advice. I would also like to sincerely thank Greg Powell for constantly motivating me, providing a sympathetic ear and for his help in completing my field work. This research would not have been possible without the hard work from the field technicians and my colleagues.

I want to thank Emery Hauser, Justice Diamond, Cody Godwin, Hemant Patel, Wilson

Peter, Kari Hurst, Joshua Cucinella, Oliver Fleming, and Tom Pratt for spending hours out in the forest in the Florida heat.

Many thanks go to my friends, especially Fayola Kojo, Jessica Mulvey, Soyini

Kojo, Daniel Durante, Dan Greene, Erick Larsen, and Melissa Carvalho for your love, support, encouragement, and hospitality throughout my studies. Finally, I thank my uncle Joel Baussan, for taking me to visit the University of Florida and for always encouraging my love and appreciation of the outdoors.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 10

LIST OF FIGURES ...... 15

LIST OF ABBREVIATIONS ...... 18

ABSTRACT ...... 19

CHAPTER

1 INTRODUCTION ...... 21

Background ...... 21 Problem ...... 22 Research Objectives ...... 24

2 REVIEW OF LITERATURE ...... 25

Introduction to Oleoresin ...... 25 Historical Production of Oleoresin ...... 25 Species Used Worldwide of Oleoresin Production ...... 26 Oleoresin Composition ...... 28 Oleoresin and Insect Pests ...... 30 Coevolution of Oleoresin and Insect Pests ...... 30 Host Selection and Colonization Behavior of Insect Pests ...... 31 Conifer Defenses Against Insect Pests ...... 34 Climate Change and Pine Beetles ...... 35 Genetic Variation in Oleoresin ...... 37 Variation of Oleoresin Composition Among Species ...... 37 Variation of Oleoresin Canal Occurrence, Size and Density ...... 41 Variation of Oleoresin Yield and Flow Rate Among Species ...... 45 Oleoresin Viscosity and Crystallization Rate Among Species ...... 49 Oleoresin Production in Planted Versus Natural Forests...... 51 Inducing Oleoresin Flow and Yield ...... 52 Chemical Inducers ...... 52 Physical Inducers ...... 57 Morphological Effects ...... 59 Exudation Pressure ...... 60 Environmental Inducers ...... 61 Climate and seasons ...... 61 Water availability ...... 64 6

Stand density management ...... 67 Fertilization...... 68 Fire ...... 70 Oleoresin tapping techniques ...... 73 Application ...... 77 Genetic Control and Breeding for Increased Terpene Production ...... 77 Global Uses for Oleoresin ...... 80 Pine terpenes for commercial products ...... 80 Pine terpenes for biofuels ...... 81 Distillation ...... 84 Economics of Oleoresin Production ...... 84 Non-Timber Forest Products ...... 84 Oleoresin Tapping and Timber Production ...... 86 Global Supply and Demand ...... 87 Market requirements ...... 87 Global production ...... 87 What Drives the Production Cost? ...... 89 Labor ...... 89 Equipment ...... 90 Cost Compared to other Biofuels ...... 91

3 ASSESSING EFFECTS OF STAND MANAGEMENT, TREE CHARACTERISTICS, AND CHEMICAL STIMULANT ON OLEORESIN PRODUCTION ...... 99

Introduction ...... 99 Methods ...... 101 Study Areas ...... 101 Borehole Tapping and In-Tree Injection ...... 103 Chemical Stimulants ...... 105 Data Collection ...... 105 Tapping Area ...... 106 Statistical Analysis ...... 108 Results ...... 110 General Summary of Oleoresin Yield ...... 110 Stand Age ...... 112 Collection Days ...... 113 Chemical Stimulants ...... 113 Tree Size ...... 115 Stand Management ...... 115 Tapping Area ...... 116 Discussion ...... 117 Summary and Conclusions ...... 121

4 CHEMICAL STIMULANT DOSAGE AND CARRIER SOLVENTS IN THE BOREHOLE METHOD TO INCREASE OLEORESIN YIELD IN SLASH PINE .... 144 7

Introduction ...... 144 Methods ...... 146 Study Areas ...... 146 Borehole Tapping ...... 147 Chemical Stimulants ...... 147 Data Collection ...... 148 Statistical Analysis ...... 148 Results ...... 149 Discussion ...... 151 Summary and Conclusions ...... 155

5 GENETIC EFFECTS ON OLEORESIN FLOW OF SLASH PINE CLONES ...... 166

Introduction ...... 166 Methods ...... 167 Study Area ...... 167 Study Design and Genetic Material ...... 168 Oleoresin Collection ...... 169 Statistical Analysis ...... 170 Results ...... 171 Discussion ...... 174 Summary and Conclusions ...... 176

6 CONCLUSION ...... 189

APPENDIX

A COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT FOR INDIVIDUAL SITES DURING THE 2013 TO 2015 TAPPING SEASONS ...... 195

B COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT AND IN TREE INJECTION FOR INDIVIDUAL SITES DURING THE 2014 AND 2015 TAPPING SEASONS ...... 198

C SLASH PINE OLEORESIN TAPPING OPTIMIZATION TRIALS ...... 202

Methods ...... 202 Study Areas ...... 202 Borehole Tapping ...... 203 Chemical Stimulants ...... 204 Data Collection ...... 206 Statistical Analysis ...... 206 Results ...... 210 High Gum Yielding Slash Pine ...... 210 Big-Small ...... 211 Triple Borehole Test ...... 212 Opposing Side ...... 212 8

Automated Drilling ...... 213 Multi-Borehole Tests...... 214 Tapping Intensity ...... 215 Discussion ...... 216

D PSEUDO BACKCROSS HYBRID STUDY ...... 242

Introduction ...... 242 Methods ...... 242 Study Area ...... 242 Study Design and Genetic Material ...... 244 Phenotypic Measurement ...... 245 Statistical Analysis ...... 245 Results ...... 246 Discussion ...... 248

LIST OF REFERENCES ...... 259

BIOGRAPHICAL SKETCH ...... 275

LIST OF TABLES

Table page

2-1 Average annual oleoresin yield in different regions from various pine species using different tapping methods. A minimum of 2 kg per tree annually is necessary to be economically viable for commercial production. Data retrieved from Hodges 1995, Tadesse et al. 2001, Rodrigues et al. 2011, Cunningham 2012, and Rodríguez-García et al. 2014, Hadiyane et al. 2015..... 94

2-2 Average cost of oleoresin tapping operation in various countries based on hourly wage and quantity of oleoresin collected per resin tapper. Cost is based on United States dollar. Data retrieved from Cunningham 2014...... 95

3-1 Summary of treatments for oleoresin tapping during the 2013 to 2015 field study...... 122

3-2 Summary of sites selected for oleoresin tapping during the 2013 to 2015 field study...... 123

3-3 Summary of main and interactive effects on oleoresin yield in sites using the standard borehole tapping method between 2013 to 2015 based on a general linear model with covariates...... 124

3-4 Summary of main effects F-statistic and p-values on oleoresin yield by site using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates...... 125

3-5 Summary of main effects F-statistic and p-values on oleoresin yield by stand using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates...... 126

3-6 Summary of main effects F-statistic and p-values on oleoresin yield by chemical treatment using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates...... 127

3-7 Summary of main effects F-statistic and p-values on oleoresin yields by collection days drilled using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates...... 128

3-8 Summary of oleoresin yields by stand age from tapping slash pine using the borehole tapping method...... 129

3-9 Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method...... 130

3-10 Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015...... 131

3-11 Summary of oleoresin yields by chemical treatment from tapping slash pine using the borehole tapping method...... 132

4-1 Summary of oleoresin tapping dosage and carrier solvent experiments in 2014-2016...... 156

4-2 Effects of methyl jasmonate carrier solvent, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the standard borehole tapping method...... 157

4-3 Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour and applying 400 mM of methyl jasmonate diluted in 90% ethanol...... 158

5-1 Summary of genotypes selected in each replicate of the CCLONES 2 study. .. 177

5-2 Least square means with standard errors for phenotypic traits measured at the CCLONES 2 study...... 178

5-3 Tukey significance group letters of the least square means for phenotypic traits measured at the CCLONES 2 study (alpha < 0.05) recorded in Table 5- 2...... 179

5-4 Broad sense heritability estimates calculated for phenotypic traits measured at the CCLONES 2 study...... 180

5-5 Summary of main and interactive effects on long-term oleoresin yields at the CCLONES 2 site using the borehole tapping method in 2016 based on a general linear clonal model...... 181

5-6 Summary of variance components of genetic correlation between short-term and long-term oleoresin yield in the CCLONES 2 site...... 182

A-1 Summary of oleoresin yields by chemical treatment in Union 1 site during the 2013 tapping season. Stand age is 14 years old...... 195

A-2 Summary of oleoresin yields by chemical treatment in Alachua 1 site during the 2013 tapping season. Stand age is 16 years old...... 195

A-3 Summary of oleoresin yields by chemical treatment in Alachua 2 site during the 2013 tapping season. Stand age is 22 years old...... 195

A-4 Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old...... 195 11

A-5 Summary of oleoresin yields by chemical treatment in Alachua 3 site during the 2014 tapping season. Stand age is 15 years old...... 195

A-6 Summary of oleoresin yields by chemical treatment in Union 1 site during the 2014 tapping season. Stand age is 15 years old...... 196

A-7 Summary of oleoresin yields by chemical treatment in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking...... 196

A-8 Summary of oleoresin yields by chemical treatment in Alachua 4 site during the 2014 tapping season. Stand age is 22 years old...... 196

A-9 Summary of oleoresin yields by chemical treatment in Alachua 5 site during the 2014 tapping season. Stand age is 22 years old...... 196

A-10 Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old...... 196

A-11 Summary of oleoresin yields by chemical treatment in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old...... 197

A-12 Summary of oleoresin yields by chemical treatment in Union 1 site during the 2015 tapping season. Stand age is 16 years old...... 197

A-13 Summary of oleoresin yields by chemical treatment in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking...... 197

A-14 Summary of oleoresin yields by chemical treatment in Alachua 4 site during the 2015 tapping season. Stand age is 23 years old...... 197

A-15 Summary of oleoresin yields by chemical treatment in Alachua 5 site during the 2015 tapping season. Stand age is 23 years old...... 197

B-1 Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old. .... 198

B-2 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2014 tapping season. Stand age is 15 years old...... 198

B-3 Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2014 tapping season. Stand age is 15 years old...... 198

B-4 Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking...... 199

B-5 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 4 site during the 2014 tapping season. Stand age is 22 years old...... 199

B-6 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 5 site during the 2014 tapping season. Stand age is 22 years old...... 199

B-7 Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old. .... 200

B-8 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old...... 200

B-9 Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2015 tapping season. Stand age is 16 years old...... 200

B-10 Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking...... 201

B-11 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 4 site during the 2015 tapping season. Stand age is 23 years old...... 201

B-12 Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 5 site during the 2015 tapping season. Stand age is 23 years old...... 201

C-1 Summary of oleoresin tapping optimization experiments for slash pine in 2014-2016...... 221

C-2 Chemical treatment and improved genetic effects on average oleoresin yield per tree (kg) from slash pine trees using the standard borehole tapping method in 2014...... 222

C-3 Summary of main and interactive effect on oleoresin yields in high gum and non-high gum site based on a general linear model...... 223

C-4 DBH, height, crown volume, and effect of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2015 using the big-small borehole tapping method...... 224

C-5 Summary of main and interactive effect on oleoresin yields in site drilled using the big-small borehole tapping method based on a general linear model...... 225

C-6 Effects of tapping treatment, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the triple borehole (two inner holes) tapping method and stimulated by methyl jasmonate...... 226

C-7 Effects of chemical stimulant and DBH on oleoresin yield (kg) when tapping slash pine trees in 2014 using the opposing side borehole tapping method. .... 227

C-8 Effects of chemical stimulant and number of boreholes on oleoresin yield (kg) when tapping slash pine trees in 2014 using the automated borehole tapping method...... 228

C-9 Effects of chemical stimulant and DBH on total oleoresin yield (kg) and oleoresin yield per borehole (kg) when tapping slash pine trees in 2014 using the 6 borehole and standard borehole tapping method...... 229

C-10 Effects of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2014 using the 8-borehole tapping method...... 230

C-11 Effects of chemical stimulant, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the 8-borehole tapping method...... 231

C-12 Effects of number of boreholes on tapping intensity and oleoresin yield (kg) when tapping slash pine trees using the 6 and 8 borehole taping method...... 232

C-13 Summary of optimization treatments, number of boreholes, collection days, chemical inducers and oleoresin yields...... 233

C-14 Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour for the manual drilling and 61 trees per hour for the automated drilling. ... 234

D-1 Summary of genotypes planted in each replicate of the CFGRP pseudo backcross hybrid study...... 250

D-2. Least square means with standard errors for phenotypic traits measured at the pseudo-backcross hybrid study...... 251

D-3 Tukey significance group letters of the least square means for phenotypic traits (alpha < 0.05) recorded in Table D-2...... 252

D-4 Disease and mortality observed at the end of the 3rd growing season in the two replicate treatments of the pseudo-backcross hybrid...... 253

D-5 Percentage of trees with stem form issues at the end of the 3rd growing season in the pseudo-backcross hybrid study...... 254

D-6 Narrow sense heritability estimates calculated for phenotypic traits measured at the end of the 3rd growing season in the pseudo-backcross hybrid study.... 255

LIST OF FIGURES

Figure page

2-1 Processes of that lead to successful beetle colonization and conifer defenses with interfering processes used by each organism to prevent the other’s success. Adapted from Wood 1982, Raffa et al. 1993, Phillips and Croteau 1999, Raffa et al. 2005, Faccoli and Schlyter 2007...... 96

2-2 Diagrams of borehole tapping designs...... 97

2-3 Oleoresin distillation process adapted from Coppen 1995...... 98

3-1 Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH greater than 10.16 cm...... 133

3-2 Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH less than 10.16 cm...... 134

3-3 Age effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons...... 135

3-4 Chemical effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons ...... 136

3-5 Chemical effects of oleoresin yield (g) per day with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons...... 137

3-6 Nonlinear regression displaying the actual relationship between average oleoresin yield (kg) in slash pine and DBH in cm for all trees tapped in the 2013 to 2015 tapping season...... 138

3-7 Effect of pine straw management and thinning on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons...... 139

3-8 Chemical effect on oleoresin yield (kg) when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons under different management scenarios...... 140

3-9 Bivariate fit of total tree yield of oleoresin (kg) in slash pine by tapping intensity...... 141

3-10 Bivariate fit of sector area yield of oleoresin in slash pine by tapping intensity. 142

3-11 Bivariate fit of hole area yield of oleoresin in slash pine by tapping intensity. ... 143

4-1 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations (50 mM, 100 mM, and 400 mM) and ethephon percentages (1%, 5%, and 10%) ...... 160

4-2 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method...... 161

4-3 Cumulative flow rate of oleoresin (g) since day of tapping treatment by chemical treatment at the 2015 dose response test...... 162

4-4 Cumulative flow of oleoresin (g) and resin flow rate over time since day of tapping treatment in Gainesville at the 2015 methyl jasmonate dose response test...... 163

4-5 Effect of carrier solvent on oleoresin yield (kg) for 100 Mm methyl jasmonate when tapping slash pine trees in North Florida using the standard borehole drilling method...... 163

4-6 Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2016 using the standard tapping method...... 165

5-1 Layout of the University of Florida’s CCLONES 2...... 183

5-2 Least square means with standard errors for oleoresin traits measured at the CCLONES 2 study...... 184

5-3 Bivariate fit of total long-term tree yield of oleoresin (g) in slash pine by DBH (cm)...... 185

5-4 Bivariate fit of total long-term clonal mean oleoresin yield (g) in slash pine by DBH (cm) ...... 186

5-5 Bivariate fit of short-term tree yield of oleoresin (g) in slash pine by DBH (cm)...... 187

5-6 Bivariate fit of short-term and long-term oleoresin yield (g)...... 188

C-1 Diagrams of borehole tapping designs...... 236

C-2 Calculations for the cross-sectional tapping area and individual hole area model for the trees tapped using the 8-borehole method...... 237

C-3 Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard method and the big-small tapping method...... 238

C-4 Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida in 2014 using the automated drilling technique...... 239

C-5 Predicted cumulative flow of oleoresin (g) by chemical treatment since day of tapping treatment at the 2014 8 borehole test...... 240

C-6 Bivariate fit of total tree oleoresin yield (kg) in slash pine by tapping intensity using the 6 and 8 borehole methods...... 241

D-1 Pedigree of the genotypes planted in the pseudo backcross hybrid study using a Latinized row-column design...... 256

D-2 Layout of the pseudo backcross hybrid study using a Latinized row-column design...... 257

D-3 Codes used for the pseudo backcross hybrid study...... 258

LIST OF ABBREVIATIONS

CCLONES Comparing Clonal Lines on Experimental Sites

CFGRP Cooperative Forest Genetics Research Program at the University of Florida

DAP Diammonium phosphate {(NH4)2HPO4}; with the following formulation: 18-46-0 (N-P-K)

DBH Diameter at breast height (1.4 meters)

DI Deionized

FBRC Forest Biology Research Cooperative

FS Full-Sib

H2 Broad-sense heritability h2 Narrow sense heritability

OP Open pollinated

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

REINVIGORATING OLEORESIN COLLECTION IN THE SOUTHEAST USA: EVALUATION OF CHEMICAL INDUCERS, STAND MANAGEMENT, TREE CHARACTERISTICS, AND GENETICS

Marie Jennifer Lauture

December 2017

Chair: Gary Frank Peter Major: Forest Resources and Conservation

In conifers, oleoresin evolved as a defense mechanism against insects and microbes. Upon wounding, oleoresin flows to the wound site. Because oleoresin is pure terpene it has been collected as a non-timber forest product primarily from Pinus species and is used globally for various products. This research evaluated the potential of reinvigorating the oleoresin tapping industry in the southeastern United States to be competitive in the global market. This dissertation analyzed the effects of chemical inducers, stand management, tree characteristics, and genetics on oleoresin flow and yield in slash pine (Pinus elliottii var. elliottii) trees in North Florida, with the goal of determining the optimal and most sustainable oleoresin collection method for stands managed for timber production.

The borehole tapping method, which involves drilling a hole into the stem, was used to collect oleoresin from live trees because of its labor efficiency, oleoresin quality, and no impact of merchantable timber. In trees between 11 and 22 years, oleoresin yields averaged 1 to 1.5 kg per tree. Oleoresin yields were positively correlated to DBH and negatively correlated to tapping intensity; larger diameter trees are preferred. 19

Methyl jasmonate was the best chemical stimulant tested and was most effective diluted in 90% ethanol at a concentration of 400 mM. When 400 mM of methyl jasmonate was used we recovered an average of 3.0 kg of oleoresin per tree with a 95- day collection season. Based on this average yield of oleoresin per tree and automation we conclude that it is possible to have a sustainable and profitable commercial operation for oleoresin tapping in the southeastern U.S.

The potential of increasing oleoresin productivity in pines through breeding programs is high and imperative to meet global demands. The broad-sense heritability estimates of short-term and long-term oleoresin yield in a 15-year-old slash pine clonal test were moderate (H2 = 0.22 and H2 = 0.19, respectively) and showed potential for selecting families with higher oleoresin productivity. Although short-term and long-term yield were uncorrelated phenotypically, the Type A genetic correlation between them was strong (r2=0.78), supporting the use of short-term yield to accelerate breeding for improved oleoresin yields.

CHAPTER 1 INTRODUCTION

Background

In the southern United States, native loblolly pine (Pinus taeda L.) and slash pine

(Pinus elliottii var. elliottii) are planted on about 120,000 km2 and 55,000 km2 of land, respectively (Xiao et al., 2003). These two species are also planted outside of their native range in various countries primarily for timber harvest. Slash pine is planted in

South Africa, China, Brazil, and various Central American countries for the harvest of both timber and non-timber forest products (Aguiar et al., 2012; Burns et al., 1990).

Forestland in the southern U.S. is economically valuable and vital to meeting consumer demands for timber and non-timber forest products both globally and nationally.

Historically, oleoresin was collected for the naval stores industry in the U.S. to maintain and repair the hulls and rigging of wooden sailing ships (Harrington, 1969).

Pine oleoresin is a key non-timber forest product collected and used globally for various renewable chemical products and biofuels. Oleoresin evolved in conifers as a physiochemical defense mechanism against stem boring insects. Oleoresin is found in several genera of the Pinaceae family, but is collected commercially from thirteen Pinus species. Within the Pinus genus, the quality and quantity of oleoresin produced varies by species; however, various external factors, such as climate, water availability, stand density, fertilization, and tree morphology. can affect the yield potential of a tree. In the

U.S., slash pine is the best candidate species for collection of oleoresin. Furthermore, the potential for inducing the higher yields of oleoresin within a tree through chemical and physical treatments is considerable.

The objectives of Chapter 2 are to address the role and importance of oleoresin in conifers, outlines the genetic variation in oleoresin yield and composition, describes and analyzes the current and potential methods of inducing oleoresin in conifers, and finally outlines the applicability and economics of oleoresin production.

Problem

Since the 1950s, the widespread use of silvicultural technologies and planting of improved genotypes of Pinus taeda L. (loblolly pine) and Pinus elliottii var. elliottii (slash pine) has increased growth and wood yields by more than four-fold (Fox, 2007).

Continued increases in yield for renewable and sustainable materials, chemicals and energy source are needed to meet the growing demand from an increasing human population (Omer, 2008). As climate change is increasing pressure on forest trees to resist water stress, pests and disease outbreaks, the importance to increase productivity and resilience of forest stands becomes evident. In conifers, a primary defense against insect pests like the boring beetles and their associated fungi is the terpene based oleoresin. Oleoresin is synthesized and stored within primary and secondary resin canal networks, and is composed of a mixture of monoterpenes and diterpenoids (da Silva Rodrigues-Corrêa et al., 2013). Wounded pine stems exude oleoresin, which has been collected from live trees for millennia. The importance of pine oleoresin in defense against pests and its use as a renewable chemical and potential biofuel have generated strong interest in better understanding what limits production. It is known that both pine wood growth, and oleoresin yield and composition, are under genetic and environmental control (Squillace and Bengtson, 1961; Squillace, 1971;

USDA Forest Service 1971a; Hodges, 1995; Jokela, 2004; Zhang et al., 2006;

Westbrook et al., 2013; Rodriguez-Garcia, 2014).

While oleoresin yield is affected by genetic and environmental components, there is limited knowledge about how they interact to affect yield. Furthermore, the biological, environmental, or silvicultural factors causing the variability observed in the flow rate and yield of oleoresin among trees from operational stands is not well understood. We know there may be some morphological, anatomical and physiochemical characteristics of trees that affect oleoresin production, but we are lacking knowledge of which primary factors are limiting in conifers. The heritability of different traits, such as stem diameter

(DBH), tree height, crown size, and oleoresin yield, can help quantify the importance of genetics and the environment. Additionally, while there is an established market for these forest products, the potential for maximizing production of oleoresin within a stand has yet to be met.

The long-term goal of this research is to understand the factors that affect growth and yield of forest trees, focusing on loblolly and slash pine, and to maximize the potential production of timber and non-timber resources, specifically oleoresin. This project has the potential of reviving the once thriving industry of oleoresin collection in the U.S. While oil prices in the U.S. have decreased significantly over the past couple of years, it is still crucial to find alternatives that are more sustainable. This study will provide an assessment of the feasibility for private landowners to produce oleoresin for renewable chemicals and biofuels. If economically viable, application of this research will provide a way for landowners to increase their annual income from slash pine plantations. By analyzing the genetic influence on oleoresin properties, we gain insight

on how to manipulate tree breeding and selection to increase resin flow and decrease variability within individual trees.

Research Objectives

Several study sites were selected for this research in North Florida, primarily in

Alachua, Union, and Bradford Counties. The main objectives of this research are:

1. Maximize collection and recovery of oleoresin and increase terpene synthesis in slash pine for renewable chemicals and biofuel production by testing different chemical stimulants, stand ages, and stand management practices (Chapter 3);

2. Determine the optimal methyl jasmonate dosage and carrier solvent for oleoresin collection in the southeast United States (Chapter 4);

3. Determine the genotypic and phenotypic correlations between 24-hour resin flow with multi-month resin collection (Chapter 5); and

Application of this research will provide a way for landowners to increase their annual income from slash pine plantations by creating a cost-effective system for tree induction and collection to supply large quantities of oleoresin from existing plantations to the pine chemical industry and advancing the biofuels industry in Florida. Analyzing the phenotypic growth traits and oleoresin production of loblolly and slash pine backcross hybrids will provide insight on the potential to increase oleoresin yield and timber production from southern pines, as well as improving genomic selection techniques that would benefit tree breeding projects.

CHAPTER 2 REVIEW OF LITERATURE

Introduction to Oleoresin

All conifers naturally produce oleoresin as a defense mechanism to protect trees against insect pests, microbes, and physical damage. Oleoresin is extracted from a variety of plant species, however, commercially it is primarily collected from Pinus species. All Pinus species naturally produce oleoresin, though some species produce better quality and higher quantities of oleoresin. While oleoresin is collected from live pine trees in the forest for commercial purposes worldwide, the market is currently dominated by China, which accounts for 74% of global production, while the second largest producers are Brazil and Indonesia, each with about 9% of world production

(Aguiar et al., 2012).

Historical Production of Oleoresin

While no longer as relevant in the market, the southern U.S., especially Georgia and North Florida, historically collected and processed pine terpenes from live trees and harvested wood in chemical pulp mills. The U.S. naval stores industry began in the mid-

19th century in the Southeast, where pine oleoresin was extracted from live longleaf

(Pinus palustris Mill.) and slash pine (Pinus elliottii Engelm. Var. elliottii) trees by streaking the bark along the stem and attaching a collection cup (Harrington, 1969;

Sullivan, 2014). Historically, gum oleoresin was collected for use on ships for repairs, to caulk seams, and protect ropes (Harrington, 1969).

From the early 1900s to around 1970s, the annual production of pine gum turpentine in the U.S. was about 30 million gallons and the production of gum rosin averaged about 1 billion gallons (Harrington, 1969). However, according to Harrington 25

(1969), production from pine gum began to decrease in the 1950s and by 1967 it dropped to 10 percent of total gum production. In 1910, steam distillation led to increases in turpentine recovery from pine stumps and in 1928 the advent of sulfate pulping also led to a decrease in turpentine and rosin collected from living trees

(Harrington, 1969).

In the mid-1930s, the industry began to reform the resin tapping technique by using chemical stimulants to increase production, and modernizing the collection equipment to be more easily removed and reduce negative effects on tree vigor

(Harrington, 1969). Oleoresin tapping stopped in the southeastern U.S. late last century due to high labor costs, reductions in older slash pine stands, rising competition from chemical substitutes, as well as the negative effects of over tapping (Sullivan, 2014).

Furthermore, after World War II, tall oil rosin became more prevalent and collection from live trees decreased (Harrington, 1969). However, similar techniques are currently being used around the world to collect pine resin. Currently, timber harvesting in the southeast

U.S. is highly efficient, productive and sustainable (Eisenbies et al., 2009). Additionally, current research shows that timber harvested for biofuel will not have negative long- term effects on forest growth (Eisenbies et al., 2009). Reinvigorating the oleoresin tapping industry in the southern U.S. has the potential to be profitable due to the increase in productivity of pine plantations, the modernized tapping techniques, as well as the need to find alternative renewable sources of chemicals and fuels.

Species Used Worldwide of Oleoresin Production

The species used for tapping depends on the geographic region in which collection takes place, and the availability of high yielding species currently in the

region, or capable of being grown in the region. In some countries, China in particular, the industry relies mostly on natural stands of Pinus massoniana trees for tapping, while others, such as Brazil, use non-native planted pines like P. elliottii for tapping. According to Aguiar et al. (2012), the Pinus species and varieties that have high resin yielding capabilities include: P. elliottii Engelm. var. elliottii, P. elliottii Engelm. var. densa, P. massoniana Lamb., P. caribaea Morelet var. bahamensis Griseb., P. caribaea Morelet var. hondurensis Sénécl., P. caribaea Morelet var. caribaea, P. yunnanensis Franch., P. merkusii Jungh. Et De Vriese, P. oocarpa Schiede ex Schltdl., P. kesiya Royle ex

Gordon, P. pinaster Aiton, P. sylvestris L., P. palustris Mill., P. nigra J. F. Arnold, P. taeda L., P. roxburghii Sarg., P. wallichiana A. B. Jacks., P. nigra J. F. Arnold subsp. pallasiana (Lamb.) Holmboe, P. sibirica Du Tour, P. pinea L., P. tropicalis

Morelet, and P. halepensis Mill. While all those species can produce large amounts of oleoresin, they may not be ideal candidates for tapping because they may lack some important characteristics to increase the flow of oleoresin, such as low crystallization rate.

The primary species used today for commercial oleoresin production is P. massoniana, which is native to south, central and east China as well as other southeast

Asian countries and grows at elevations ranging from a few meters to 2000 meters

(Farjon, 2013a). Though it is a productive species, P. massoniana is not usually planted outside its native range (Farjon, 2013a); therefore, it would not be suitable for the oleoresin industry in the United States. The other leading species used for commercial tapping outside of China include P. elliottii var. elliottii, P. caribaea, P. pinaster, and P. sylvestris (Aguiar et al., 2012). The overall highest yielding oleoresin species is P.

elliottii var. elliottii which is native to the southeastern U.S., primarily Florida and

Georgia, and is planted outside of its native range in South Africa, China, Brazil, and

Central America, for the harvest of both timber and non-timber forest products (Aguiar et al., 2012; Burns et al., 1990). P. caribaea is a species native to Central America and the Caribbean and is also planted for oleoresin and timber production in South America

(Aguiar et al., 2012; Farjon, 2013b). P. caribaea includes three major varieties

(bahamensis, hondurensis, and caribaea), some of which are more exploited than others (Farjon, 2013b). To build an oleoresin industry P. elliottii var. elliottii is the ideal candidate species because of its ability to be planted in a variety of geographic locations, improved genetics, and high overall productivity. Among the biggest threats to

P. elliottii var. elliottii are bark boring beetles, however, this threat exists only in its native range (Roberds et al. 2003; Strom et al. 2002).

Oleoresin Composition

The turpentine in oleoresin consists of monoterpene, which includes α and β- pinene (Rodrigues et al., 2011; da Silva Rodrigues-Corrêa et al., 2013; Rodrigues and

Fett-Neto, 2009). The rosin in oleoresin consists of diterpenoids, which seal wounds made by boring bark beetles or other predators (Rodrigues and Fett-Neto, 2009;

Rodrigues et al., 2011; da Silva Rodrigues-Corrêa et al., 2013). Oleoresins produced in traumatic resin ducts tend to include other substances such as phenolics (Nagy et al.,

2000). The oleoresin in conifers is synthesized in resin canals, a specialized tissue that forms an interconnected network in needles and wood. In resin canals, live epithelial cells constitutively synthesize oleoresin and secrete it into the luminal space of the canal (Steele et al., 1995).

Normal resin canals occur naturally in conifers; however, when the tree undergoes significant stress, like wounding or an attack from pests, they develop traumatic resin canals (Nagy et al., 2000; Lin et al., 2002). Both types of resin canals are surrounded by epithelial and parenchyma cells (Nagy et al., 2000; Lin et al., 2002).

The structure of normal resin canals is typically a single layer of cells and tubular, while traumatic resin canals are round and come in one or two rows of cells (Nagy et al. 2000;

Lin et al. 2002). These canals, depending on species and genera, may be found in the xylem, phloem, roots, stem, leaves, and seeds (Lin et al., 2002). Within the xylem and phloem of most conifer species, normal resin canals are divided into the vertical (axial) and horizontal (radial) canals (Lin et al., 2002). Generally, axial resin canals are found in the secondary xylem of conifers often formed as traumatic ducts (Nagy et al., 2000).

The axial resin canals in the xylem can be divided into canals with thin walls surrounding the epithelial cells, which only occur in Pinus species, or canals with thick walls surrounding the epithelial cells, which are found in almost all other genera (Lin et al., 2002). Resin canal length can vary greatly between and within species and individual trees (Lapasha and Wheeler, 1990). In Pinus taeda, longitudinal resin canal lengths ranged from an average of 57 mm to 122 mm for 10-year-old trees, and 74 mm to 167 mm for 20-year-old trees (Lapasha and Wheeler, 1990). LaPasha and Wheeler

(1990) also reported resin canal lengths of other conifer species of varying ages and found an average length of 75 mm for 15-year-old P. contorta, 185 mm for 16-year old

P. monticola, 59 mm for 20-year-old P. ponderosa, and 207 mm and 498 mm for 10 and

20-year-old P. elliottii trees, respectively. These differences in lengths of resin canals have a significant impact on the yield and ability to extract oleoresin from the tree. Thus,

noting these differences gives insight on which species is a better candidate for commercial oleoresin production.

Oleoresin and Insect Pests

Coevolution of Oleoresin and Insect Pests

Forest trees are long lived species and coevolved with their pests and pathogens. Bark beetles (Curculionidae: Scolytinae) including mountain pine beetle

(Dendroctonus ponderosae) and southern pine beetle (Dendroctonus frontalis) are responsible for the death of billions of conifer trees worldwide (Ferrenberg et al., 2014).

To defend against insect pests, conifers evolved chemical defenses in oleoresin and resin canals. Oleoresin is released upon wounding and the sticky monoterpene and diterpenoid resin repels, weakens and can kill insects and their associated fungi (Raffa et al., 2005; Ferrenberg et al., 2014). Terpenes are polymers of the five carbon (C) isopentenyl pyrophosphate, and are the largest and most diverse group of secondary products and have important roles in chemical defenses of plants (Rodrigues-Corrêa et al., 2012).

While many insect pests have the ability to kill off entire forest stands, conifers have successfully persisted in part due to their highly evolved chemical defense mechanism (Phillips and Croteau, 1999). Oleoresin is composed of C10 monoterpenes and C15 sesquiterpenes which constitute the turpentine fraction that also contains toxins, like limonene and 3-carene responsible for fighting off insects and other pests, and C20 diterpenoids (Phillips and Croteau, 1999; Bohlmann and Keeling, 2008;

Rodrigues-Corrêa, 2012). Understanding the relationship between oleoresin production in trees for defense and insect infestation is crucial to determine how yield and flow of

oleoresin can be increased. These relationships can give insight as to what factors are most important to control oleoresin flow and what can be manipulated to increase overall production. Furthermore, if changes in global climate change increases or worsens bark beetle infestations, it is important to recognize how to increase terpene production to mitigate the potential negative impacts.

Host Selection and Colonization Behavior of Insect Pests

Conifers have adapted to bark beetle attacks; similarly bark beetles have adapted their strategies for successfully locating, colonizing, and killing host trees

(Wood, 1982). There are many ecological factors that play a role in determining which insect pests colonize living or recently dead trees, what parts of the trees get attacked, as well as physiological characteristics of the host trees that make it easier or more difficult for colonization, such as oleoresin characteristics. According to Wood (1982), certain insect pests strictly colonize healthy trees, while others prey on trees in poorer health due to environmental stressors. Smaller and lateral buds are preferable for selection by bark beetles because they do not produce enough oleoresin to kill the larvae (Harris, 1960).

In turn, bark beetles have adapted to tree defenses, enabling colonization. First, bark beetles work in large numbers, making their joint attacks more exhaustive to the tree (Raffa et al., 2005). Furthermore, bark beetles use pheromones from oxygenated terpenes, which are synthesized from metabolized host compounds to increase their aggression (Raffa et al., 2005). Rhyacionia buoliana (Schiff.) larvae remove small amounts of resin from their bodies with their mouths and their vomitus (Harris, 1960).

On the other hand, when flooded with larger amounts of resin the R. buoliana larvae

either abandon the tree or are drowned in the resin, and thus are incapable of doing too much damage (Harris, 1960).

Pest species have been successful at colonizing conifer host trees by evolving to produce aggregation pheromones, which allow pests to communicate with one another and facilitates mating, host finding and resource utilization (Raffa et al., 1993). Some species also use aggregation pheromones to attract other beetles from the same species to their host tree, which allow the group of beetles to kill the host tree by virtue of strength in numbers (Raffa et al., 1993). Bark beetles may synthesize their aggregation pheromones from compounds taken from the host tree; for example, ipsedienol is synthesized from myrcene and verbenone is derived from α-pinene (Raffa et al., 1993).

Wood (1982) described in detail the process of colonizing a host tree by beetles.

This process begins with dispersal when young beetles emerge from a host tree and either fly out (long or short distance) or stay in the vicinity of the host tree due to attractive pheromones (Wood, 1982). This phase is followed by selection of a new host tree by the pests. Certain beetles may be attracted to volatile compounds that are released by a tree that is stressed, while others are incapable of detecting prime host trees prior to landing (Wood, 1982). The time it takes for the tree to be colonized after this phase depends on how quickly pheromones are produced and how weakened the host tree is already (Wood, 1982) . Once a beetle selects and establishes itself in the host tree they begin feeding and release pheromones in order to attract more beetles, both male and female, which marks the initiation of the concentration phase (Wood,

1982). There is a negative correlation between the time between selection and

pheromone release and the survival and success of the bark beetle population; with shorter elapsed time giving greater success (Wood, 1982). The final phase of colonizing a tree is termination (Wood, 1982). Proper termination is crucial for the survival of the bark beetle population because if not executed properly, the population runs the risk of exceeding its carrying capacity and deteriorating its resources (Wood, 1982). In some cases, the presence of both male and female beetles decreases the attraction of new beetles to come to the host tree, because certain males release chemicals that alters the responses to pheromones, which limits reproduction and keeps the population at a sustainable level (Wood, 1982). Furthermore, during this phase, some beetles may jump to adjacent trees and begin establishing themselves and releasing pheromones

(Wood, 1982).

Once dispersal and selection have occurred, and the concentration phase has begun, the beetles on the host tree begin to bore through the cambial tissue and create galleries within the tree for reproduction (Phillips and Croteau, 1999). Once the adults have laid their eggs, they bore through the tree creating exit holes and disperse elsewhere beginning a new colonization process (Phillips and Croteau, 1999). When bark beetles attack conifers, their associated fungi are also inoculated, providing access to host tree carbohydrates (Phillips and Croteau, 1999). Furthermore, these fungi produce toxins that play a large role in killing the host tree (Phillips and Croteau, 1999).

After the oleoresin reaches the site of wounding, the exposure to the atmosphere causes it to crystallize and harden, which seals the wound (Phillips and Croteau, 1999).

Most destructive conifer pests, such as bark beetles, only attack live trees and work in

groups in order to kill their host tree to successfully reproduce (Phillips and Croteau,

1999).

Conifer Defenses Against Insect Pests

Southern pine beetle (Dendroctonus frontalis) is a destructive native pest that attacks and kills pine stands in the southeastern U.S. during major outbreaks, especially

P. taeda L. stands (Roberds et al., 2003; Strom et al., 2002). These pine forests use oleoresin to defend themselves against southern pine beetles as it entraps the attacking beetles, which prevent them from establishing galleries, and it delivers toxic compounds to the insect (Roberds et al., 2003). The most important toxic chemicals in oleoresin for pine tree resistance to insect pests, such as bark beetles, are α-pinene, which works against the pheromones of D. frontalis, and limonene, which helps increase the tree’s resistance (Hodges et al., 1979; Strom et al., 2002). The abundance of these two chemicals, however, are not correlated to tree size including crown dimensions, DBH and height (Strom et al., 2002).

Individual trees and species differ in their reactions to a pest attack, such as bark beetles; however, in most cases the concentration of monoterpenes in the tissue surrounding the entry site increases by a few hundred-fold within a couple weeks (Raffa et al., 2005; Figure 2-1). Similarly, the percent mortality of pests increases in a logarithmic fashion because of synthesis of terpenes by the tree (Raffa et al., 2005).

Diterpenoids, on the other hand, do not play a significant role in fighting against boring bark beetles, but they do fight against fungi (Raffa et al., 2005). Many factors help increase resistance to insect attacks on conifers; some of which are only successful in certain species. For example, bark beetle resistance in lodgepole and limber pine,

Ferrenberg et al. (2014) found that resistant trees, compared to susceptible trees, had more resin ducts within the recent 5 to 10 years of tissue growth. This likely increased resin production and flow, which helped fight against an attack (Ferrenberg et al., 2014).

The density and size of resin ducts was significantly greater in resistant P. flexilis compared with susceptible trees. In contrast, no significant difference was observed in

P. contorta, between resistant and non-resistant trees (Ferrenberg et al., 2014). In both

P. contorta and P. flexilis, radial tree growth was positively correlated with the quantity of resin ducts (Ferrenberg et al., 2014). Oleoresin flow has identified trees that are resistant to southern pine beetle in P. taeda and P. echinata (Hodges et al., 1979).

Phenolics also play a role in bark beetle resistance in certain conifers, such as,

Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies Karst.) (Faccoli and

Schlyter, 2007). Phenolic compounds increase tree resistance to bark beetles by reducing the host acceptance and feeding of insects (Faccoli and Schylter, 2007; Figure

2-1). Parenchyma cells in the secondary phloem play a vital role in the constitutive and inducible defense responses against invasive insects in Norway spruce (Franceschi et al., 1998; Franceschi et al., 2000). However, due to the coevolution of trees and insects with their associated fungi, some tree phenolic compounds are not as successful as non-host compounds to deter insect tunneling of Ips typographus on P. abies Karst.

(Faccoli and Schylter, 2007).

Climate Change and Pine Beetles

It is evident that climate change is occurring, and increases in the amounts of greenhouse gas emissions by humans are directly and indirectly causing a variety of issues - including sea level rise, increases in atmospheric temperature, and extreme

weather events (IPCC, 2014). These issues can in turn cause a shift in vegetation type, land use changes, and increase in insect infestations (USGCRP, 2009 and USGCRP,

2014). Climate change can impact conifer forests and bark beetle population dynamics both directly and indirectly. Climate change can alter tree defense and tolerance of insect pests, insect physiology, distribution, and abundance, as well as interactions between abiotic and biotic disturbance agents (Weed et al., 2013).

Pine beetle outbreaks are heavily influenced by climate (Gan, 2004; Bentz et al.,

2010; McNulty et al., 2013). Temperature has a strong influence on population dynamics and developmental processes of bark beetles (Bentz et al., 2010). Beetles have become more tolerant to colder temperatures, but there is still significant mortality due to cold (Bentz et al., 2010). However, with climate change, cold-induced mortality would be reduced. Temperature increases during the spring and winter are predicted to promote pine beetle outbreaks, while warmer fall temperatures would reduce beetle outbreaks (Gan, 2004). Furthermore, warmer winters may promote the overwintering of beetles which could lead to more severe outbreaks and infestations the following spring

(Gan, 2004). During the 21st century, average global temperatures are predicted to increase 1.8 to 4.0 degrees Celsius because of an increase in atmospheric CO2 levels

(Bentz et al., 2010). If atmospheric CO2 levels double to about 750 parts per million, southern pine beetle infestation risks in the U.S. is predicted to increase by 2.5 to 5 times (Gan, 2004).

Climate change is a concern, especially to forest landowners, because as the global temperatures continue to increase, there is a high risk that conifer forests, especially planted forest with faster growth rates, will be damaged by increases in pine

beetle outbreaks. In the southern U.S. about $1.5 billion worth of timber from 1970 to

1996 were lost as a result of southern pine beetle infestations (Gan, 2004; USGCRP,

2009). With climate change, beetles in the southern U.S. and Central America will have the potential to move north following increasing temperatures (Bentz et al., 2010; Gillis,

2013). This could be quite detrimental, as the beetles with current ranges limited to the south could infest northern forests and increase the risks of damage. For example, in

New Jersey, the southern pine beetle has already infested and killed thousands of acres of pineland due to the warmer winters (Gillis, 2013). While the case in New Jersey was confined to a small area, and in the northwest U.S. and Canada, tens of millions of acres of forests have already been destroyed by mountain pine beetle outbreaks made possible by the warming of those areas, highlighting the severity of the threat (Bentz et al., 2010; Gillis, 2013). Furthermore, elevated CO2 concentrations in the atmosphere will indirectly affect the interactions of bark beetles and conifers (Bentz et al., 2010).

Increasing CO2 concentrations increases the ratio between carbon and nitrogen, which would decrease the number of nutrients available for bark beetle, causing insects to feed more heavily on conifers (Bentz et al., 2010).

Genetic Variation in Oleoresin

Variation of Oleoresin Composition Among Species

The chemical composition of oleoresin differs among pine species and geographical ranges (Rezzi et al., 2005). The main constituents found in the oleoresin of Pinus nigra at various concentrations include abietic acid, dehydroabietic acid, neoabietic acid, levoprimaric acid, palustric acid, primaric acid, isoprimaric, sandaracopimaric acid, primaral, isoprimaral, primarol, isocembrol, 4-epi-isocembrol,

cembrene, β-pinene and α-pinene (Rezzi et al., 2005). In China, there are over 36 different components found in nine Chinese pine species (Song et al., 1995). The most common components occurring at higher levels include α-pinene, limonene, communic acid, palustric acid, abietic acid, and neoabietic acid (Song et al., 1995). Some Chinese pine species, like P. densata had extremely low levels of α-pinene (4.4%), compared to the other species which had levels ranging from 14.6 to 39.4% (Song et al., 2005). Most

Chinese species had limonene levels below 2%, while P. densata, P. takahasii, and P. sylvestritomis oleoresin was composed of 24.8% β-pinene (Song et al., 2005). This kind of variation was observed with many other components of the oleoresin in Chinese pines (Song et al., 2005).

Strom et al. (2002) reported that stands where a southern pine beetle outbreak occurred, progeny trees selected from a population that successfully survived an outbreak produced 1.65 times the quantity of oleoresin compared to those from the general population. This study also shows that genetics plays a large role in determining the resistance of individuals to insect pests. A tree more resistant to insect infestation and with better defense mechanisms would be a better candidate for oleoresin production because tapping and disease induced mortality would be lower and yield would be higher because of better quality production.

Squillace (1971) surveyed the oleoresin monoterpene composition in slash pine trees and found that the majority of the monoterpenes were composed of β-pinene

(45%), α-pinene (28.7%), myrcene (10.9%), and β-phellandrene (13.4%). Many of these monoterpenes exhibited some sign of bimodality, especially β-pinene with some trees being composed of only 2 to 8%, while 98% of trees measured had about 21 to 74%.

Additionally, myrcene varied from 0 to 5% in some trees to 6 to 45% in others

(Squillace, 1971).

Sukarno et al. 2015 also looked at the composition of the oleoresin collected from the different provenances of P. merkusii in Indonesia and found that it consisted primarily of α-pinene ranging from 73.3 to 87.2% of the total composition. β-pinene, α- pinene, myrcene, and β-phellandrene all have high levels of narrow-sense heritability

(0.49-0.56, 0.79-0.89, 0.63-0.67, and 0.55-0.71, respectively) (Squillace, 1971). This shows that there is a strong evidence for Mendellian inheritance for these traits involving few or multiple genes (Squillace, 1971; Squillace and Fisher, 1966).

While there is a lot of between-species variation in oleoresin composition, there is equally as much variation observed within-species (Squillace and Fisher, 1966;

Squillace, 1971). Squillace and Fisher (1996) looked at the variation in oleoresin composition in P. elliottii in the U.S. and how they were inherited. However, in their study they only analyzed oleoresin samples from 174 trees growing within a 15-mile radius (Squillace and Fisher, 1966). This geographic and sample size limitation may not represent accurately the oleoresin composition of slash pine throughout the southeastern U.S. Compared to Squillace (1971), Squillace and Fisher (1966) found that the P. elliottii monoterpenes were composed of β-pinene (40.3%), α-pinene

(18.8%), myrcene (15.8%), and β-phellandrene (22%). Both found that the oleoresin monoterpenes consisted primarily of those four main compounds. The variation in oleoresin composition among trees within the same species varies not only among trees from different sites, but also between trees from the same stand (Squillace and Fisher,

1966). Furthermore, within individual trees, variation of oleoresin monoterpene composition was observed between cortex and stem gum (Squillace and Fisher, 1966).

Monoterpene composition within and between populations of P. ponderosa varies greatly and affects the tree’s ability to defend itself against insect pests

(Sturgeon, 1979). Sturgeon (1979) found that ponderosa pine trees with higher levels of limonene in the oleoresin, which is toxic to many pests, are more successful at surviving a beetle attack and not being selected as a host by pests. However, in instances where all favorable trees have already been depleted, insects may develop a tolerance to limonene and prey upon trees with higher levels of it (Sturgeon, 1979). Since insect pests and trees have coevolved with one another, directional selection favoring trees with higher limonene concentration in resin occurred in a northern California and southern Oregon population of ponderosa pine because beetle predation occurred more frequently on trees with lower levels of limonene (Sturgeon, 1979). Numerous studies have shown variation in oleoresin composition among and within species and provenances. If establishing a plantation specifically to collect oleoresin commercially, it would be crucial to select individuals from provenances geographically close to where a plantation would be established.

Oleoresin composition can also be impacted by climate and seasons (Conners et al., 1999). During the course of the year, Conners et al. (1999) found that monoterpene concentrations in P. taeda varied by up to 300 to 500%. This could be the effect of temperature, precipitation, or other environmental factors (Conners et al., 1999). This variation was observed in trees planted in both Mississippi and North Carolina (Conner et al., 1999).

Variation of Oleoresin Canal Occurrence, Size and Density

While resin canals can occur in all conifers, their composition, anatomy and distribution differs among species and genera (Lin et al., 2002). To begin, depending on species and genera, resin canals are found in certain tissue or organs (Lin et al., 2002).

Because of among species variation in resin canal characteristics, species and subspecies are able to be distinguished and identified depending on resin canal density

(Lin et al., 2001). Resin canals in the genera Abies, Cedrus, Tsuga, and Pseudolarix occur only in the event of wounding, pressure, auxin exposure, wind damage, or injury due to herbivore attack (Fahn, 1988). Axial and radial resin canals occur in the secondary phloem of Larix and Pinus species, while only radial resin canals occur in the secondary phloem in Cathaya, Hudus, Picea, and Pseudotsuga (Lin et al., 2002). Some literature distinguishes between resin canals and resin cavities, which are considered elongated spherical sacs, though those distinctions are not clear (Lin et al., 2002;

Srivastava, 1963). Species from the genera Abies, Keteleeria, Larix, Nothotsuga, Picea,

Pinus, and Pseudotsuga in addition to resin canals, also have resin cavities (Lin et al.,

2002).

Resin canals are found in the primary xylem of Pseudotsuga species only. In the secondary xylem, however, resin canals are found in nearly all species in the Pinaceae family; they occur in Cathaya, Keteleeria, Larix, Nothotsuga, Picea, Pinus, and

Pseudotsuga and are absent in Abies, Tsuga, Pseudolarix, and Cedrus (Lin et al.,

2002). Larger inner resin canals can be found in the stem cortex of Cathaya, Abies,

Keteleeria, Nothotsuga, Picea, Pinus, Pseudotsuga, and Tsuga species (Lin et al.,

2002). In addition to the inner canals, smaller peripheral canals are also found in Pinus

species (Lin et al., 2002). All Pinaceae genera have inner resin canals, which occur in the inner part of the mesophylls around the vascular cylinder; or peripheral resin canals, which occur near the epidermis (Lin et al., 2002). As in the stems, most Pinaceae genera have the peripheral resin canals in the leaves, apart from Pinus and Tsuga (Lin et al., 2002). Species in Abies, Cedrus, Keteleeria, and Pseudolarix have 1 to 5 resin canals occurring in the sclerenchymatous layer of the seed coat (Lin et al., 2002).

Furthermore, species in the Nothotsuga and Tsuga genera have about 10 to 20 resin canals occurring in the sclerenchymatous layer of the seed coat (Lin et al., 2002). In the bracts of the female cone, there are usually 1 to 2 resin canals, depending on the species, found in all Pinaceae genera (Lin et al., 2002). These resin canals either occur in the abaxial side of the bract (peripheral) or on both sides of the vascular bundle

(inner) (Lin et al., 2002).

Resin canals can also be found in the seed scales of all 11 Pinaceae genera (Lin et al., 2002). In Abies, Larix, Pseudotsuga, and Tsuga these canals occur on the adaxial side of the vascular bundles, while in Cedrus and Pinus they occur in the abaxial side of the vascular bundles, and in Cathaya, Keteleeria, Nothotsuga, Picea, and Pseudolarix they are found both on the abaxial and adaxial side of the vascular bundles (Lin et al.,

2002). Lin et al. (2002) found that in general, the Pinaceae genera can be separated into two groups based on resin canal attributes. The species in Abies, Cedrus,

Keteleeria, Nothotsuga, Pseudolarix, and Tsuga have normal resin canals in the seed coat and do not have radial resin canals in the secondary xylem or secondary phloem

(Lin et al., 2002). On the contrary, the species in Cathaya, Larix, Picea, Pinus, and

Pseudotsuga do not have normal resin canals in the seed coat, but do have radial resin canals in the secondary xylem and secondary phloem (Lin et al., 2002).

There can also be slight variation in resin canal density within species depending on individual tree characteristic, such as tree foliage height, crown, and age (Lin et al.,

2001). Lin et al. (2001) looked at these within species variations in resin canal densities in Pinus sylvestris L. and found that needles collected higher in the tree had a greater density of resin canals compared to the ones in the mid and lower section. When analyzing resin canal densities in needles collected on the exterior of the crown compared to the interior, Lin et al. (2001) found that the ones on the outer portion of the crown had significantly more resin canals. The number of resin canals in needles also increased with age (Lin et al., 2001).

The density of radial resin canals can vary tremendously within and among trees

(Stark, 1965). The resin duct density in Pinus species ranges from 35 to 50 per square cm in P. ponderosa, 35 to 65 per square cm in P. contorta, 50 to 85 per square cm in P. elliottii, 60 to 70 per square cm in P. sylvestris L., and 60+ per square cm in P. glabra

(Stark, 1965). P. ponderosa tends to have higher natural resin canal densities further up in the tree while P. contorta has higher duct densities concentrated at the base (Stark,

1965). Species also vary in the size of the resin canals, which can have an impact on the ability of a tree to produce oleoresin (Stark, 1965). Furthermore, the size and number of resin canals for species tend to decrease with increasing age (Mergen et al.,

1955).

The ability of a pine tree to successfully resist and defend itself from a bark beetle attack is also related to size and density of resin ducts (Hood and Sala, 2015;

Hood et al., 2015). Pine trees that have greater numbers of resin ducts and/or larger size tend to be more successful at surviving an attack (Hood et al., 2015). Furthermore, trees that grow faster tend to be more resistant to pest attack because they produce more resin ducts (Hood et al., 2015).

There is a positive correlation between oleoresin production, size and area of resin ducts with the basal area, with the best predictor of resin production being duct size and stem basal area (Hood and Sala, 2015; Hood et al., 2015). The size and quantity of resin ducts is greater in faster growing trees, though these trees tend to invest less proportionally in resin ducts than in wood growth (Hood and Sala, 2015).

Growing trees in higher densities create conditions for slower growth smaller crown size and limits the amount of potential oleoresin to be produced, which leads to a decrease in protection against bark beetle attacks (Lorio, 1986). Therefore, thinning stands is recommended for increasing oleoresin production and improving protection.

Resin flow and production in pine trees varies depending on genetics, site quality, climate, tree size, disturbance, stand dominance and wounding (Hood and Sala,

2015). Since resin is costly to produce, there are trade-offs between dedicating energy resources to growth versus defense mechanisms such as oleoresin production (Hood and Sala, 2015; Strauss et al., 2002). Therefore, certain species invest more resources on defense while others invest more on growth. Endara and Coley (2011) use the resource availability hypothesis (RAH) to explain the interspecific variation in tree defense against herbivores and pests. In their meta-analysis, they concluded that, compared to slower growing species from resource-poor environments, faster growing species from rich resource environments experience higher herbivory rates.

Furthermore, Endara and Coley (2011) found that fast growing species have higher inducible defenses because they occur in an environment suitable for inducible factors, and have higher cost of creating new tissue, whereas slow growing species have higher constitutive defenses. Tree vigor is also related to the susceptibility of certain pine species to beetle attack (Larsson et al., 1983). Additionally, tree vigor is negatively correlated to both leaf area and basal area in a stand (Larsson et al., 1983). As a result, stand density management practices, such as thinning is beneficial to preventing or minimizing insect pest attacks (Larsson et al., 1983).

Variation of Oleoresin Yield and Flow Rate Among Species

Conifers naturally produce oleoresin and yield is related to numerous genetic and environmental factors. Oleoresin yield is positively correlated to tree diameter at breast height (DBH) and live crown in many different pine species (Hodges, 1995; Hodges,

2000; Strom et al., 2002; Rodrigues et al., 2008; Rodrigues et al., 2013; Rodríguez-

García et al., 2014). The productivity of planted conifers, with respect to DBH, crown width, branch size, etc. increases with improvement in soil quality and adoption of intensive management practices, for example, thinning, fertilization, site preparation, and planting genetically-improved seedlings (Jokela, 2004; Zhang et al., 2006;

Rodríguez-García et al., 2014).

In central Spain, selection intensity for high oleoresin yielding P. pinaster was found to be great and these high yielding trees produced close to double the quantity of oleoresin compared to the average for that region (7.2 kg/tree/year compared to 3.65 kg/tree/year) (Tadesse et al., 2001). This shows that genetics has a strong impact on potential oleoresin yield from a stand and trees could be bred for improved yield.

Furthermore, there was a positive linear correlation observed between selection intensity and mean resin yields in high yielders in Spain (Tadesse et al., 2001).

Stand age has a positive correlation with oleoresin flow; Knebel et al. 2008 observed 1.5 to 4.5 times more resin yield in 12-year-old trees compared to 6-year-old trees. In some cases, resin flow can be impacted by the interaction of certain trees characteristics with environmental factors. When the interaction effect of stand age with fertilizer is tested, Knebel et al. (2008) found that oleoresin collected from younger trees

(6-year-old) had a longer lasting positive response to fertilization compared to older trees (12-year-old).

The flow rate of oleoresin in conifers is affected by many biological factors such as species, genetics, size of resin ducts, length of resin canals, exudation pressure, and viscosity of oleoresin, as well as environmental factors such as temperature and seasons (USDA Forest Service, 1971a; Hodges, 1995). However, some studies found that exudation pressure was not significantly correlated to resin flow, though pressure was not measured properly (Schopmeyer et al., 1954). Flow rate is typically higher during the late spring and summer, and when average temperatures are above 20°C

(Hodges, 1995). Pine species differ in terms of oleoresin viscosity, and the higher the viscosity of resin, the slower the flow rate (USDA Forest Service, 1971a). The viscosity of oleoresin in individual trees was higher right at the beginning of the growing season and subsequently dropped rapidly (USDA Forest Service, 1971a). Also, viscosity was found to have a strong broad-sense heritability, which shows that breeding programs to improve oleoresin flow in slash pine have great potential (Schopmeyer et al., 1954;

USDA Forest Service, 1971a; USDA Forest Service, 1971b). The flow rate is also

affected by the chemical compositions of oleoresin, with higher levels of monoterpenes reducing viscosity and crystallization rate as well as maintaining resin in a fluid state, which in turn increases flow (Hodges, 1995). Methyl jasmonate, a chemical stimulant, was found to increase monoterpenes in the stem when applied to Douglas fir (Huber et al., 2005). During the first 24 hours of collection, flow rate of oleoresin will be greater in individual trees with larger and higher quantity of resin ducts (Schopmeyer et al., 1954).

Pinus merkusii is native to Sumatra and is planted in Indonesia for timber products as well as oleoresin production (Sukarno et al., 2015). Within species, provenances may vary in terms of oleoresin production, which shows that there are some genetic and environmental impacts on the yield of oleoresin. When tapping 13- year-old Pinus merkusii Jungh. Et De Vriese trees in Indonesia, Sukarno et al. (2015) found that the provenances in Jantho yielded 17-73% more oleoresin than the other provenances in the country. This shows that there is potential for selecting individuals or subpopulations to plant stands specifically for oleoresin yield and increase potential yield (Sukarno et al., 2015). In this study, it was also found that oleoresin yield decreased as elevation of the provenances tapped increased, however turpentine yield increased with elevation (Sukarno et al., 2015). Individual trees within each provenance showed high levels of variation in oleoresin yield, but repeatability estimates for all subpopulations in Indonesia were high with values ranging from 0.57 to 0.74 (Sukarno et al., 2015). Similar to repeatability estimates, estimates of heritability for oleoresin were high (0.52), which shows that there is a strong genetic control on yield (Sukarno et al., 2015).

Narrow-sense heritability estimates of oleoresin yield in southern U.S. pine trees were also high, with Pinus elliottii having an estimate of 0.85, and Pinus taeda having an estimate ranging from 0.44 to 0.59 in the summer (Franklin et al., 1970; Roberds et al., 2003). Westbrook et al. (2013) reported a within site narrow-sense heritability estimate of 0.12-0.30 when comparing constitutive oleoresin flow from various P. taeda sites in north Florida. Constitutive oleoresin flow is also affected by the site x genetic interaction; Westbrook et al. (2013) found that additive genetic correlation of yield decreased from 0.8 to 0.37 as the differences in soil and climate increased. Roberds et al. (2003) found that growth traits and oleoresin flow in loblolly pine had a broad-sense heritability value of greater than 0.5, which shows a strong genetic influence on these traits.

Within native southern U.S. pine trees the number of radial resin canals found in slash pine is much higher than P. palustris, P. echinata, or P. taeda (Hodges et al.,

1981). In the southeastern U.S., the diameter of resin ducts in P. taeda, P. palustris, and slash pine did not differ significantly, while the diameter of P. echinata resin canals was significantly smaller (Hodges et al., 1981). Furthermore, the number of resin canals per area was significantly higher in slash pine compared to P. palustris, P. echinata, and

P. taeda (Hodges et al., 1981).

Flow duration can also be affected by species of pine trees. In the southeast

U.S., slash pine and P. palustris pine tend to have longer lasting oleoresin flow, compared to P. echinata and P. taeda (Hodges et al., 1977). Hodges et al. (1977) found that oleoresin flow in all slash pine trees continued after 24 hours, while 95% of P. palustris, 70% of P. echinata, and 50% of P. taeda showed flow 24 hours after

wounding. Thirty-two to 48 hours after wounding, 90% of slash pine yielded oleoresin, while only 60% of P. palustris, 25% of P. echinata, and 15% of P. taeda yielded oleoresin (Hodges et al., 1977).

Species genetics also affects the rate of flow of oleoresin. When comparing four southern pines, Hodges et al. (1977) found that P. elliottii oleoresin flowed at a rate of

0.56 ml/h, which was significantly slower than that of P. echinata (0.78 ml/h), P. taeda

(1.12 ml/h), and P. palustris (1.55 ml/h). This flow rate can also be affected by environmental conditions, as well as the viscosity and crystallization rate of the individual tree, which can in turn differ by species. Furthermore, no chemical stimulant or inducers were used in this study, and the flow rate and duration of flow can differ when applying stimulant.

Within-species tree variation contributes to the variation in oleoresin flow in species within a stand (Roberds and Strom, 2006). Within the major southern U.S. pine species, variation in oleoresin yields for slash pine was lowest (Roberds and Strom,

2006). Loblolly pine stands was found to have a high repeatability for oleoresin yield with about two-thirds of the tree variability accounting for oleoresin variability (Roberds and Strom, 2006). Furthermore, repeatability measurements for oleoresin yield in P. palustris stands varied from low to high (Roberds and Strom, 2006).

Oleoresin Viscosity and Crystallization Rate Among Species

Oleoresin physical characteristics in most southern pines is not greatly affected by tree morphological characteristics; however, P. palustris has a slight negative correlation between crystallization and tree age and height (Hodges et al., 1977).

Schopmeyer et al. (1954) also found that tree morphological characteristics cannot be

used to select slash pine trees that produce higher oleoresin yields. In southern pines, there is a negative correlation between resin flow and oleoresin viscosity (Hodges et al.,

1977). Between 36 to 65 percent variation in oleoresin flow in southern pine can be accounted for by the viscosity, with 65% of the variation in slash pine (Hodges et al.,

1981). In natural conditions, slash and P. palustris are more resistant to a southern pine beetle attack compared to P. echinata and loblolly pine (Hodges et al., 1977). This could be due to the fact that slash and P. palustris tend to produce oleoresin at great quantities which flow for longer times (Hodges et al., 1977).

Oleoresin viscosity of progenies was influenced by both the mother and father, thus progenies had a viscosity level somewhere in between both parents (Mergen et al.,

1955). When comparing the four-major southern U.S. pine species, a study found that the viscosity of P. palustris resin was lower than the viscosity of slash pine resin

(Hodges et al., 1977). Furthermore, the viscosity of P. palustris was greater than both P. echinata and loblolly pine (Hodges et al., 1977). Another study in Florida found that slash pine had lower viscosity than that recorded in Hodges et al. (1977) (Schopmeyer et al. 1954). This shows that the environmental factors also play a role in viscosity of oleoresin. Viscosity within an individual is fairly uniform, though it may vary slightly at different vertical positions in the tree (Stark, 1985). Crystallization rate is also affected by genetics with slash pine having the slowest rate and loblolly and P. echinata having the quickest rate (Hodges et al., 1977). This can affect resin production, since quicker crystallization slows down resin flow by sealing the wound (Hodges, 1995).

Oleoresin Production in Planted Versus Natural Forests

Today, close to three quarters of the pine oleoresin produced is collected from natural pine stands in Asia, while the remaining oleoresin is tapped from planted pine stands (Cunningham, 2012). One of the major differences in areas where natural stands are tapped compared to those where planted stands are tapped is the type of individual in charge of the operation (Cunningham, 2012). The countries that operate in natural stands are usually found in the northern hemisphere, primarily in Asia, and tend to have individuals that are from rural areas and are not associated with a company that harvest the product (Cunningham, 2012). Furthermore, European countries, such as Spain, often work in natural stands that are managed (Cunningham, 2014). This allows the resin tappers to get more oleoresin yield per tree and visit more trees in a tapping season; for example, resin tappers in Spain tapped on average 5500 trees and collected about 2.3 kg per tree compared to workers in China, who only tapped between

1500 to 2000 trees and collected 2.0 kg of oleoresin per tree (Cunningham, 2014). On the other hand, in the southern hemisphere, as in Brazil, oleoresin collection is controlled and managed by a company that hires laborers to harvest from planted pine trees, usually non-native one (Cunningham, 2012). These companies either own processing mills or sell the product directly to the pine chemical industry (Cunningham,

2012).

Operations in natural stands tend to be inefficient and use outdated tapping methods that are not sustainable (Cunningham, 2012). Tapping resin in a planted stand is more advantageous to the resin tappers because the trees are in proximity to one another, therefore more trees can be visited in a day (Coppen and Hone, 1995). In a

planted stand, tappers usually work in stand with 1100 trees per hectare compared to

200 to 400 trees per hectare found in natural stands (Cunningham, 2014). In planted stands, a single resin tapper is able to tap about 7000 to 1000 trees per year, while a tapper in a natural stand can only tap between 1500 to 2000 trees per year

(Cunningham, 2014; Morris, 2015).

Inducing Oleoresin Flow and Yield

Chemical Inducers

Resin yields in a variety of conifers may also be improved with the application of chemical stimulants such as, methyl jasmonate and an ethylene-releasing compound

(Hodges, 1995; Martin et al., 2003; Hudgins et al., 2004; Hudgins and Franceschi, 2004;

Huber et al., 2005; Rodrigues et al., 2008). The two main stimulants used around the world are a mixture of sulfuric acid with an ethylene precursor (2-chloroethylphosphonic acid, CEPA) and methyl jasmonate (Hodges, 1995; Hodges, 2000; Martin et al., 2003;

Hudgins et al., 2004; Hudgins and Franceschi, 2004; Huber et al., 2005; Rodrigues et al., 2008). These two compounds occur naturally in conifers to fight against pests.

Ethylene is an unsaturated hydrocarbon synthesized from S-adenosyl-L- methionine and catalyzed by the enzymes ACC synthase and ACC oxidase (Bleecker and Kende, 2000). Ethylene is used to regulate metabolic and developmental processes in plants, such as stem and petiole growth, as well as facilitating the plants response to abiotic and biotic stress (Bleecker and Kende, 2000). When inoculated with spores of fungi, the rate of both ethylene and monoterpenes produced by pine trees increases

(Popp et al., 1995b). This shows that ethylene plays a key role in the tree’s defense responses to insects and fungi (Popp et al., 1995b). Methyl jasmonate is a volatile

compound found in both angiosperms and gymnosperms and is used as a cellular regular in developmental processes as well as trigger defense mechanisms in response to abiotic and biotic stresses like insect attacks (Cheong and Choi, 2003). Both ethylene and methyl jasmonate play a vital role in fruit ripening (Bleecker and Kende, 2000;

Cheong and Choi, 2003). Methyl jasmonate and its jasmonic acid are synthesized through the octadecanoid pathway and catalyzed through various enzymes including allene oxide synthase and allene oxide cyclase (Cheong and Choi, 2003).

Methyl jasmonate was found to have a 2-fold effect on the monoterpene and sesquiterpene production in the needles of Norway spruce (Martin et al., 2003). It was found that the terpenes released after the application of methyl jasmonate in Norway spruce wood were products of new resin canals, suggesting this organic compound promotes the production of new resin ducts (Franceschi et al., 2002; Martin et al.,

2003). Under normal conditions P. menziesii, P. grandis, T. heterophylla, and C. libani did not have constitutive axial resin canals, however, following treatment with methyl jasmonate, traumatic resin canals were formed within 8 weeks (Hudgins et al., 2004).

Furthermore, the density of axial resin canals affects oleoresin flow (Nagy et al., 2000).

Another experiment with Norway spruce trees being treated with methyl jasmonate topically found that following inoculation of the insect Ceratocystis polonica trees treated with methyl jasmonate had a significantly greater response with oleoresin flow compared to untreated trees (Franceschi et al., 2002). Franceschi et al. (2002) also compared the presence of axial resin canals in 2-year-old saplings and found that the saplings that we not treated had no resin canals, whereas, the trees treated with methyl jasmonate had a ring of induced traumatic resin canals.

Methyl jasmonate application was most successful at promoting the formation of traumatic resin ducts in P. pungens, P. menziesii, and L. occidentalis compared to wounding and the application of Tween 20 (Hudgins et al., 2003). Compared to wounding, methyl jasmonate induced the formation of resin canals that were double the size of traumatic resin ducts from wounding canals in P. menziesii and one-half the size of the canals produced by wounding in P. pungens (Hudgins et al., 2003). This shows that using methyl jasmonate to promote and increase the flow of oleoresin for commercial production may have varying effects depending on the species used for tapping. The mean area of the resin canals in P. menziesii formed from methyl jasmonate application was close to 3500 µm2, compared to about 1100 µm2 for P. pungens resin canals and less than 500 µm2 for L. occidentalis canals (Hudgins et al.,

2003). Furthermore, higher concentrations of methyl jasmonate (at least 100 mm) was more successful at creating more flow in Douglas fir and giant redwood trees (Hudgins and Franceschi, 2004). In that study, methyl jasmonate and ethylene were both better at promoting oleoresin exudation with higher phenolic area, higher resin duct area, and greater numbers of resin ducts compared to Tween 20, methyl salicylate, and water treatments (Hudgins and Franceschi, 2004). Methyl jasmonate was found to not have a negative effect on growth of treated trees in both the sapling stage and older

(Franceschi et al., 2002). The application of jasmonic acid on plants was found to have a negative effect on insect pests, with higher concentrations of jasmonic acid leading to induced plant responses deterring pests (Thaler et al., 2001).

Hudgins and Franceschi (2004) looked at the number of resin duct and average lumen area responses to giant redwoods and Douglas fir trees treated with varying

doses of methyl jasmonate with the greatest concentration being 100 mm. For both species, the study found that as methyl jasmonate concentration increased, so did the lumen area both where the chemical stimulant was applied as well as around it

(Hudgins and Franceschi, 2004). Furthermore, the same general trend occurred with the number of resin canals increasing with the increase in methyl jasmonate concentration though within the treated area 10 mm and 25 mm concentrations yield the greatest number of resin ducts in the giant redwoods and Douglas fir, respectively

(Hudgins and Franceschi, 2004).

Applying chemical stimulants makes commercial oleoresin production more sustainable and feasible as it reduces the overall cost of tapping (Rodrigues et al.,

2011). Paraquat has been used in other countries, like Brazil, to stimulate resin production (Rodrigues and Fett-Neto, 2009). This compound works to increase yield in slash pine by disturbing the cellular structure of parenchyma cells in the xylem, which increase tree response to wounding (Rodrigues and Fett-Neto, 2009). In my research, however, Paraquat was not found to have much of a significant positive effect on yield.

Increasing the concentrations of CEPA positively affected rein yields in slash pine

(Rodrigues et al., 2008). CEPA and NAA was also found to increase the expression of candidate genes that promote enzyme activation, which can indirectly increase oleoresin yield (de Lima et al., 2016). In India, Lekha (2002) also reported an increase in oleoresin yield with increasing concentrations of both ethephon and sulfuric acid.

Similar results were observed in my study with the increase in methyl jasmonate concentration. For a commercial operation, it is necessary to find the most ideal and cost effective chemical concentration that still yields high oleoresin production.

Fahn et al. (1979) applied two hormone treatments to C. libani trees, NAA and

NAA+GA3, at different time periods. The area above the treated area for both NAA and

NAA+GA3 had larger resin canals occurring after application (Fahn et al., 1979).

Furthermore, the ideal time to apply hormone stimulant to give larger and more abundant resin canals after one month of application was between April to August

(Fahn et al., 1979).

Other chemical stimulants used to promote the flow of oleoresin include sulfuric acid, paraquat, salicylic acid, auxin, benzoic acid, yeast extracts, metal cofactors, and fungal elicitors (da Silva Rodrigues-Corrêa et al., 2013). Salicylic acid is a phenolic compound found in plants and important for defense, while paraquat is a photosynthesis inhibiting herbicide (Silverman et al., 2005). When paraquat is applied to the wound, it induces the formation of lightwood, which increases oleoresin production in pine trees

(Stubbs et al., 1984). Popp et al. (1995a) found that applying a bark-beetle-vectored fungus to the wound of conifers induces the production of lesions soaked in monoterpene. This would also increase the flow of oleoresin to the wound. In Brazil, the application of a stimulant paste containing metal cofactors such as ferrous sulfate, potassium sulfate, copper sulfate, and manganese sulfate yields to an equivalent or higher yield of oleoresin compared to the traditionally used more expensive CEPA

(Rodrigues et al., 2011). The paste typically also includes sulfuric acid, which is known to promote oleoresin flow (Rodrigues et al., 2011). Ten and 100 mM of salicylic acid and the synthetic auxin 2,4-dichlorophenoxyacetic acid applied to a wound was found to yield more oleoresin compared to the CEPA paste in P. elliottii (Rodrigues and Fett-

Neto, 2009). Furthermore, in that same study, yeast extract at various concentrations

(5, 50, and 500 mM) was found to promote statistically similar oleoresin yields compared to CEPA paste (Rodrigues and Fett-Neto, 2009). The auxin 2,4-D was found to induce slightly greater yields in slash pine compared to sulfuric acid (Clements,

1970).

Physical Inducers

Wounding conifers at any age can increase oleoresin flow, however a greater increase in resin flow is observed when the trees are subjected to both wounding and fungal inoculation (Christiansen et al., 1999; Knebel et al., 2008). P. abies trees that were pretreated by inoculation with Ceratocystis polonica had significantly more resin canals at breast height compared to control trees (Christiansen et al., 1999). There is a significant increase in resin flow from trees subjected to mass artificial inoculation compared to trees that were only wounded in P. taeda and P. resinosa (Klepzig et al.,

2005; Knebel et al., 2008; Lombardero et al., 2006). Christiansen et al. (1999) reported that wounding and fungal inoculation together can increase the tree’s resistance, particularly P. abies to mass insect inoculation. Previous wounding has been found to have an initial negative effect on oleoresin flow followed by a positive effect, with the side of the tree that has been previously wounded producing significantly less oleoresin than the unwounded side on the first day of tapping, but producing more by day seven after tapping (Lombardero et al., 2000).

In Cedrus species of Pinaceae, resin canals only occur after the tree has been wounded and appear as both vertical and radial ducts in the secondary xylem (Fahn et al., 1979; Fahn, 1988; Lin et al., 2002). Fahn et al. (1979) found a correlation between the size and shape of the wound with the size of the resin canals; with longer and wider

wounds producing larger and more cyst-like resin canals. The location of the wound, in terms of height on the tree, can also have an impact on oleoresin yield (Tisdale and

Nebeker, 1992). Tisdale and Nebeker (1992) found that wounding closer to the base yielded significantly more oleoresin compared to closer to the lowest live branch when wounding occurred in May and June.

There are different techniques to wound pine trees for oleoresin collection which will be discussed below. Most countries now use a method which involves scraping the bark and phloem and attaching a bag or collection bucket to retrieve the oleoresin.

Furthermore, there are several different wound shapes that are used to promote the flow of oleoresin such as v-shaped, horizontal, or round shaped wounds (da Silva

Rodrigues-Corrêa et al., 2013). Drilling further into the tree is another possible method for collecting oleoresin. Wounds can be made both manually using various tools as well as automatically using robots or tractor mounted devices (Hodges, 2000). Hodges

(2000) developed a mechanized system that operated 3 drills which can also intersect within the tree requiring a single collection spout and bag. Hodges (2000) also automated the application of chemical stimulants. This system can rotate and align with boreholes to spray approximately 1.5 ml of chemical inducers into the borehole using a cone-shaped pattern (Hodges, 2000). This entire system is mounted and operated through a tractor, and takes about 25 seconds to drill and apply stimulant (Hodges,

2000). Lastly, this system would cost about $0.80 per tree to operate including labor and equipment (Hodges, 2000).

The size of the wound can also significantly affect the yield of oleoresin, with larger wounds from scraping the bark and drilling into the tree yielding more oleoresin

(Hodges, 1995; Hadiyane et al., 2015). However, the higher yields from larger boreholes are not proportional to the per unit area of the hole; Hodges (1995) found that

3.49 cm boreholes yielded about 28.1 grams per area compared to 2.54 cm boreholes yielding 31.9 grams per area. This same trend was also observed with hole depth, where shallower holes yielded more oleoresin per unit area compared to deeper holes

(Hodges, 1995).

Using the borehole tapping method, Lekha (2002) found that freshening the boreholes monthly during the tapping season by either increasing the size of the wound or re-spraying with a chemical stimulant had a positive impact on yield. Boreholes that were initially tapped at 1.905 cm and 2.54 cm and then re-drilled multiple times to get a

3.175-cm diameter hole yielded significantly more oleoresin (2961 and 2951 g/hole/tree, respectively) compared to borehole initially tapped at 3.175 cm with no freshening (2905 g/hole/tree). (Lekha, 2002).

Morphological Effects

While a larger crown size allows the tree to grow faster and produce more carbohydrates, the excess resources available is allocated to growth and storage, rather than secondary metabolism, such as oleoresin production (Lombardero et al., 2000).

Suppressed trees, though, were found to have significantly lower oleoresin flow compared to dominant canopy trees (Novick et al., 2012). Gansel (1965) did not find any significant differences in crown and stem characteristics between high and low oleoresin yielding trees. In a study in central Spain, Tadesse et al. (2001) found that compared to control trees, high yielding candidate trees had significant larger diameter, crown height, crown diameter, and oleoresin yield per tree. On the other hand, control

trees were significantly taller and planted at a much greater density although with lower oleoresin yields (Tadesse et al., 2001). Hadiyane et al. (2015) also observed a positive correlation with oleoresin yield and tree diameter. However, Lekha (2002) found no correlation between yield and tree diameter, but reported a significant positive correlation between needle length and tree height with oleoresin yield. Needle thickness was also reported to be positively correlated to oleoresin yield (Lekha, 2002; Bhat,

2015).

Exudation Pressure

Oleoresin exudation pressure (OEP) has been found to have some effect on resin flow rate in certain cases, and in others, has not been found to be significant

(Schopmeyer et al., 1954; Hodges, 1995; Mason, 1971; Rodríguez-García et al., 2014).

Rissanen et al. (2016) measured OEP rates in an even-aged 50-year-old Scots pine stand in southern Finland. OEP varies considerably diurnally, with highest pressure rates occurring from 1 to 3 p.m. and lowest rates occurring between 3 and 6 a.m.

(Rissanen et al., 2016). In general, as ambient temperature and precipitation increases, the OEP also increases exponentially, which allows the tree to exude more resin

(Harris, 1960; Rissanen et al., 2016).

There is a slight negative correlation with xylem diameter and OEP as well as a slight positive correlation between OEP and monoterpene emissions (Rissanen et al.,

2016). The results obtained in this study conflict other experiments with OEP, which found that OEP is negatively correlated with temperature and is lowest in the afternoon and highest just before sunrise (Schopmeyer et al., 1954; Vité, 1961; Lorio and Hodges,

1968; Helseth and Brown, 1970; Rissanen et al., 2016). These results may be

contrasting because all the other studies were conducted in warmer climates with significantly higher average temperatures while Rissanen et al. (2016) conducted their experiment in Finland which has much lower high temperatures. Moreover, OEP was positively correlated to relative humidity, and negatively correlated to water stress

(Helseth and Brown, 1970).

Environmental Inducers

Climate and seasons

Resin flow and production differs seasonally depending on climate (Hood and

Sala, 2015). Resin flow increases during drought periods when tree growth is limited due to water stress (Hood and Sala, 2015). This outcome can be explained by the growth-differentiation balance (GDB) hypothesis (Herms and Mattson, 1992). The GDB hypothesis predicts that environmental resource limitations, whether water stress from droughts or poor nutrient availability, results in carbohydrate accumulation and increase secondary metabolism, which will then increase plant defenses against herbivory without compensating growth (Herms and Mattson, 1992). Moreover, in thinned sites, where competition for resources is not as prevalent, higher resin flow was observed since there were enough resources to allocate for growth and plant defenses (Hood and

Sala, 2015).

Oleoresin production is maximized when conifers are tapped during the summer months because of the higher temperatures and higher pest activity, which would require more production for protection (Lorio, 1986; Gaylord et al., 2007; Davis et al.,

2011). Pine stands are more susceptible to attack by pests during warmer summer months. European trees, compared to American pine trees are less susceptible to pest

attack because European trees experience cooler summers (Harris, 1960). While trees are more susceptible to insect attacks during the summer, it is still beneficial to tap trees during that time because of increases in oleoresin flow. The flow rate may be higher during the summer months because the tree must naturally produce higher levels of oleoresin to defend against a seasonal increased in pest abundance.

Depending on the climate, the resin tapping season can range between eight months out of the year to all year round (Coppen and Hone, 1995). In temperate climates, when using the more common bark streaking method, tapping usually occurs eight to nine months out of the year, however in tropical countries, tapping may occur all year round (Coppen and Hone, 1995). If using the borehole tapping method, tapping usually occurs at the beginning of the growing season and the bags are collected at the start of winter.

High levels of prolonged rainfall are not beneficial to the flow of oleoresin

(Coppen and Hone, 1995). Oleoresin flow rate is ideal when the average outside temperatures are above 20°C (Hodges, 1995). Oleoresin canal density is positively correlated to outside temperatures while it is negatively correlated to precipitation rates

(Rigling et al., 2003). Initial oleoresin flow during early summer is significantly higher than that of late summer (Lombardero et al., 2000). Temperature has been found to affect the viscosity of oleoresin (Stark, 1965).

Elevated atmospheric carbon dioxide levels induce an increase in temperatures

(Novick et al., 2012). This elevated CO2 levels have a significant positive impact on oleoresin flow in canopy dominant P. taeda in nutrient poor soils but has no significant effect on resin flow of suppressed P. taeda trees or those dominant trees in nutrient rich

sites (Novick et al., 2012). Elevated CO2 levels can also lead to higher rates of photosynthesis, though that may not necessarily lead to increase productivity (McNulty et al., 2013).

Axial resin canals in the xylem typically form during late spring around the first week of June to early summer around the first week of July, which is about 12 weeks after cambial reactivation (Blanche et al., 1992). Cells in the early wood and late wood had a positive correlation to tree growth, with faster growing trees having more cells

(Blanche et al., 1992). The timing of vertical resin duct formation could be to a certain extent due to the season or year with the longest photoperiod (Blanche et al., 1992).

Resin flow in loblolly pine was positively correlated to axial resin canal density, but not radial resin canal density (Blanche et al., 1992; Hodges et al., 1981).

While the induction of new resin canal formation is caused by wounding, the size and timing of formation of these ducts are heavily influenced by the month of wounding

(Fahn et al., 1979). Larger ducts are typically a result from wounding end of April

(largest ducts) and between May and August (Fahn et al., 1979). These resin canals usually appear one month after wounding (Fahn et al., 1979). In trees sampled one to two months after wounding between December and March, only some resin canals were visible, and they were mostly small, whereas tree wounded between September and November had most samples with small resin canals present after one to two months (Fahn et al., 1979).

Climate change is also predicted to cause land cover changes. Within the next

50-60 years, southeastern U.S. land cover is projected to change from primarily longleaf-slash pine forests in North Florida to oak-gum-cypress forests (USGCRP,

2009). If these projections become a reality, pine forests in the southeast would be reduced and a decrease in pines would lead to a decrease in availability of oleoresin flow from a stand. This also highlights the importance of increasing the value and overall productivity of the forest. If the forest is more productive, less acreage is needed, and if the forest becomes more economically valuable, there is an incentive for protection, investment, and research. Climate change can have numerous negative impacts on forests, but there is still the potential of mitigating those future negative projections.

Water availability

Water availability in a stand is important for proper tree physiological function and growth. The lack of water can be quite problematic for trees as it creates ideal conditions for a successful insect outbreak (Stark, 1965). Plant growth is more limited by water deficiencies than it is by photosynthesis (Lombardero et al., 2000). When tree growth is limited by the lack of a resource, such as water or light, carbohydrates that are available and cannot be used for growth due to resource limitations are used to invest in secondary metabolism, such as oleoresin flow (Lombardero et al., 2000). Slight water stress can limit pine tree growth more than photosynthesis, and causes more carbon to be allocated to secondary metabolism (Reeve et al., 1995). Additionally, more severe water stress limits assimilation of carbon, which causes less to be allocated to secondary metabolism, thus making it easier for insect pests to successfully attack a tree (Reeve et al., 1995). In the southeast U.S., pine stands are typically planted in raised planting beds because the soil is typically poorly drained (Wilhite and Jones,

1981). Trees planted in beds tend to grow better initially compared to trees planted without beds because of the better drainage they receive (Wilhite and Jones, 1981).

Since tree growth is limited more by water deficiencies compared to photosynthesis, when water is deficient, more carbohydrates remain due to lack of growth, and thus the availability of carbohydrates for secondary metabolism is higher

(Lombardero et al., 2000). Lombardero et al. (2000) and Westbrook et al. (2013) found that constitutive resin flow was increased with water deficiencies. Similarly, Gaylord et al. (2007) found that oleoresin flow was highest in early summer when trees are exposed to more water stress. However, over time, as a result of long term water deficit and increased tree stress from extreme drought, oleoresin flow decreased (Lorio and

Hodges, 1968; Lombardero et al., 2000). This shows that though water shortages can push the tree to allocate more resources to resin production, it is only beneficial in the short term and water availability is still crucial to proper tree function and growth.

Furthermore, if oleoresin flow is key to determining susceptibility of pine trees to insect pest attack, trees planted on flat sites during a period of drought would be more susceptible than those planted on mounds (Lorio and Hodges, 1968).

Understanding the impacts of water stress of insect attacks and oleoresin production of conifer forests is important to predicting effects of climate change on oleoresin flow. Predictive models indicate an increase in the severity, duration and frequencies of droughts is likely to occur in certain areas as a result of climate change and the associated increase in surface heating (Seager et al., 2007; Allen et al., 2009;

Seager et al., 2009; Trenberth et al., 2013). Furthermore, the Intergovernmental Panel on Climate Change (IPCC) predicts a decrease in rainfall in subtropical climates during

the 21st century (Seager et al., 2007). While not much information is available it is highly likely that droughts will occur in new areas, and that natural droughts will set in quicker and be more intense (Trenbeth et al., 2013). If these droughts occur as predicted, the viability of an oleoresin industry decreases as severe stress will lead to a reduction of resin production, and beetle infestations will become more severe.

Increases in tree mortality as a result of drought and severe heat linked to climate change has been observed in Africa, Asia, Australasia, Europe and the

Americas (Allen et al., 2009). In North America, most cases of mortality have occurred in the west coast, with millions of acres of Pinus and Populus species dying in Alaska,

British Columbia, and Alberta (Allen et al., 2009). However, mortality among Quercus and Acer species has occurred in Quebec and the eastern U.S. from Missouri to South

Carolina as a result of drought and warmer spring temperatures (Allen et al., 2009).

Moreover, the southeast U.S. is exceptionally vulnerable to extreme heat and a decrease in water availability (USGCRP, 2014). While the Pinus species in the southeastern U.S. have not yet been directly negatively affected by climate change, current predictions are not favorable and any increase in mortality from climate related factors would prevent the success of oleoresin tapping in the southeast U.S. Short term water stress may be beneficial to oleoresin production in Pinus species, but severe drought like those predicted will not only reduce inducible and constitutive resin flow, but it will also increase pest infestations and tree mortality. Increase in atmospheric temperatures may also play a role in forest die-off, though the extent of that role and predictions in mortality is not yet fully understood (Allen et al., 2009).

When comparing P. sylvestris trees that were grown under natural conditions with trees grown under irrigated conditions, Rigling et al. (2003) found that the resin canal density of the control pines was significantly higher. However, once irrigation ceased, the resin canals densities of the trees grown under formerly irrigated conditions increased significantly (Rigling et al., 2003). This shows that water stress can cause an immediate positive impact on resin duct density, and therefore oleoresin flow.

Soil moisture was found to influence oleoresin flow in P. taeda (Mason, 1971).

Thirty-four percent of the variation in oleoresin flow was caused by fluctuations in soil moisture levels (Mason, 1971). If heavy rains occur after a period of drought, soil moisture levels would increase, which would lead to a substantial increase in oleoresin flow in pines (Mason, 1971). In a study on loblolly pine, recharge of a half inch of available water led to a 40% increase in oleoresin yield (Mason, 1971).

Stand density management

Stand density can also effect the yield of oleoresin (Mason, 1971). Stand productivity is heavily influenced by size-density relationships, thus thinning a stand is beneficial (Jokela, 2004). Reineke (1933) first discussed the negative correlation between the maximum number of trees in a stand and the quadratic DBH. Keeping the stand within the stand density index for that species is crucial to maintain maximum productivity (Reineke, 1933). When abiotic resources, such as light, water and nutrients, become limiting in a stand, density limitations as a result of tree-to-tree competition become apparent. As a result, monospecific stands typically follow the self-thinning model proposed by Yoda et al. (1963) which describes the linear relationship between density and plant size using with a -3/2 slope. If the tree measurements go above the -

3/2 slope, the stand will go through self-thinning, and mortality would occur (Yoda et al.,

1963).

Thinning a stand ahead can positively impact crown width, branch diameter, increase photosynthesis rates, water and nitrogen uptake, and stimulates tree growth, as well as gain revenue from the stand prior to harvest (Mason, 1971; Wallin et al.,

2004; Zhang et al., 2006). Furthermore, when the stand is thinned, undesirable, suppressed and intermediate trees are usually removed; and these trees usually have a lower oleoresin exudation flow rate (Mason, 1971). Thinning may also help fight against insect colonization by increasing pheromone distribution (Larsson et al., 1983; Olsen et al., 1996; Wallin, 2004).

Mason (1971) found that the oleoresin yields in the stand that was not thinned was significantly lower compared to the thinned stands, even the stands that experienced drought. This shows that the negative effects of higher stand density are more detrimental to oleoresin productivity than the effects of low water availability.

Thinned stands produced as much as 40% more oleoresin compared to unthinned stands (Mason, 1971).

Fertilization

Knebel et al. (2008) measured oleoresin flow in fertilized and unfertilized trees before and after wounding and fungal inoculation in P. taeda located in North Carolina.

Prior to wounding 6-year-old loblolly pine trees, trees that were fertilized had about two to four times more oleoresin than those trees that were unfertilized (Knebel et al., 2008).

This shows the strong positive effect fertilization can have on oleoresin yield. However, these results were not observed in older stands as the 12-year-old trees that were

tapped did not have a significant fertilizer effect on oleoresin yield (Knebel et al., 2008).

Furthermore, both six and 12-year-old stand did not have the same fertilizer effect in consecutive year (Knebel et al., 2008). These results are contrary to those obtained in other studies where fertilization did not have any significant effects on resin yield

(Lombardero et al., 2000; Klepzig et al., 2005). Other studies have found that fertilizer application did not have any impact on the yield of oleoresin, even in nutrient poor sites

(Wei et al., 2014). The effect on oleoresin yield to fertilization may be impacted by the initial site nutrient deficiencies; if the site already lacks necessary nutrients which negatively impacts the growth of the trees, fertilization may prove to have a positive impact, however, if the site does not lack proper resources, fertilization may be unnecessary. Furthermore, stand age may have a significant effect on whether oleoresin yields in trees responds to fertilizer application. More mature stands do not grow as much and thus do not need as much fertilization as younger trees. This was observed in the Knebel et al. (2008) study, where younger stands had a positive significant effect on oleoresin yield to fertilization, whereas older stands did not. Under potential future elevated atmospheric CO2 levels, fertilization may have a negative or no impact on oleoresin flow (Novick et al., 2012).

If the results obtained in the studies by Lombardero et al. and Klepzig et al., where constitutive resin flow is negatively impacted by fertilization occurs, intensive pine management, like what happens in the southeastern U.S., will lead to more trees becoming more susceptible to insect pest, such as bark beetles (Lombardero et al.,

2000; Klepzig et al., 2005; Knebel et al., 2008). However, in Knebel et al. (2008) constitutive resin flow was positively impacted by fertilization, which would increase the

potential of trees to survive insect attacks. The lack of available nutrients for individual trees caused by overcrowding in a stand can have a negative impact on oleoresin yield

(Lorio, 1986). Therefore, fertilization could counter high density planting by adding more nutrients necessary for better tree growth, which would give the tree more resources to invest in oleoresin production.

Besides nutrient levels, other soil properties, such as acidity, may influence the oleoresin yield from pine trees. Wei et al. (2014) compared the effect of lime application on oleoresin yields in P. elliottii and P. massoniana stands with acidic soils in southern

China. In both species, a significant effect of lime application on the yield of oleoresin was observed (Wei et al., 2014). The effect lime dosage for both species was different, with P. elliottii responding better to higher dosages compared to P. massoniana (Wei et al., 2014). P. elliottii and P. massoniana are both adapted to growing in acidic soils (Wei et al., 2014), so this significant positive effect may be greater for pine species not adapted to acidic soils.

Fire

Oleoresin flow in Ponderosa pine (Pinus ponderosa) as well as Corsican pine

(Pinus nigra subspecies laricio (Poir.) Maire var. corsicana) increased and viscosity decreased after a prescribed burn (Wallin et al., 2003; Cannac et al., 2009; Davis et al.,

2011). This is most likely caused by the additional stress of fire triggering the formation of new traumatic resin canal formation and the preparation against insect pest attack.

Wallin et al. (2003) found that in ponderosa pine, both constitutive and induced resin flow improved in lightly scorched and moderately scorched trees. However, this study did not compare oleoresin yield to trees that were not burned. While oleoresin volume

after burning and thinning a ponderosa pine stand was initially greater than the untreated control pine stands, in August, several months after the prescribed burn, oleoresin yield in the control stand was greater than the thinned and burned stand

(Wallin et al., 2004). Heavy and severe crown scorch negatively affected oleoresin yield in ponderosa pine (Wallin et al., 2003). In stands that are treated with prescribed fire, tree diameter, basal area, and percent live crown affected oleoresin yield (Davis et al.,

2011). As the diameter and percent live crown in a tree increases, the quantity of oleoresin flow increases as well, however, as basal area increases in a stand, oleoresin flow decreases (Davis et al., 2011).

The study on Corsican pine found that yield increased in trees that were burned multiple times up to 14 months after initial burn (Cannac et al., 2009). Lombardero et al.

(2006) observed a short term decrease in resin flow with a long-term increase in flow of

P. resinosa trees that were burned compared to unburned adjacent trees. Hood et al.

(2015) found that low-severity fire acts as an inducer of resin duct production and that ponderosa pine trees exposed to fire had an increase in resin ducts and these defenses decrease with the cessation of fire. Within burned trees, the burn side of an individual tree can yield significantly higher amounts of oleoresin than the unburned side

(Lombardero et al., 2006). This result lasted up to 55 days after treatment and the burned trees on both burned and unburned tapped sites had twice as much oleoresin yield compared to unburned trees, however, initially there was a reduction in oleoresin flow immediately following burning (Lombardero et al., 2006). Santoro et al. (2000) also found that following a fire in Spring 1998, oleoresin flow in trees damaged by the fire

increased significantly and linearly with height of charring compared to those trees that were not damaged.

Fire, however, increases the attractiveness of the pine trees to insect pests by releasing some volatile compounds, which can have a severe negative impact to the burned tree (Santoro et al., 2000; Lombardero et al., 2006). This increased in attractiveness can be caused by the immediate decline in oleoresin flow after a burn, which allows more pests to successfully attack, especially from wildfires (Lombardero et al., 2006). Santoro et al. 2000 found an increased in abundance of Ips pini in the burned site one month after the fire occurred, however, Ips grandicollis and Ips perroti abundance were not significantly different in burned and unburned sites. During mid- summer, a few months after being burned, I. pini abundance was significantly less in the unburned site and by September the pest abundance in the burned and unburned site did not differ (Santoro et al., 2000). The results from Lombardero et al. were contrary to those from a P. larico study that found that fire did not provoke or increase insect pest attack on burned stands (Cannac et al., 2009).

Tree physiological characteristics following a fire event are also important in determining oleoresin yield and can affect viscosity (Davis et al., 2011). After being scorched, trees with more percent live crown were found to produce more oleoresin with a higher viscosity (Davis et al., 2011). This is most likely due to the fact that trees with large amounts of scorched foliage have lower rates of photosynthesis, which in turn means less resources to use as a defense mechanism against pests (Wallin et al.,

2003). Furthermore, trees that are more heavily damaged by a fire become more susceptible to an insect pest attack and colonization (Wallin et al., 2003). Pine species

that have evolved with and are adapted to fire, such as P. palustris and P. resinosa (red pine), yield more oleoresin when subjected to fire (Harper, 1944; Santoro et al., 2000;

Davis et al., 2011).

Oleoresin tapping techniques

Pine trees around the world are being tapped using several techniques to collect oleoresin for various commercial products, such as medicinal products, adhesives, and biofuels. It is possible to successfully tap a pine tree for over 20 years without posing much risk to the health of the tree and stand (Coppen, 1995). The pine chemical industry supplies crude tall oil and crude sulfate turpentine by extracting form pulpwood in the pulp mills, wood rosin pinenes by extracting from stumps processed in rosin mills, and raw oleoresin collected from tapping live trees (American Chemistry Council, 2011).

The raw oleoresin collected from pine trees in the forest is processed and converted into gum rosin and gum turpentine (Cunningham, 2012).

Physical wounding of slash pine automatically triggers defense mechanisms causing the increase in the production of oleoresin in both normal and traumatic resin canals in order to protect the tree from any form of attack. Cunningham (2012) describes four major techniques used for tapping pine trees around the world: the

“Chinese method”, the “American method”, the “French or Hugues method” and the

“Mazek or Rill method”. All of these methods involve scraping the bark and phloem and attaching a bag or container to have the oleoresin flow into. These extraction methods are all open-based and therefore allow for contaminants to enter the collection vessel.

In addition to this, there is the borehole tapping method that is not as common, but is being used in certain places, like the U.S., and has a lot of promise to tap trees in

a sustainable manner in conjunction with timber harvest (Hodges, 1995; Lekha, 2002).

The borehole tapping method involves drilling boreholes into the tree to reach the resin canals in the xylem of the tree and attaching a PVC pipe spout with a collection bag attached to retrieve the oleoresin over a several months period (Hodges, 1995).

Boreholes may be places in a variety of way around the base of the tree, but the most time efficient method is having two boreholes parallel to one another (Figure 2-2). One of the advantages to the borehole tapping method is that the oleoresin is collected in a closed container and thus the final raw product is purer and not filled with contaminants, such as bark. The borehole tapping method was used to tap P. roxburghii trees in India

(Lekha, 2002). It is also possible to repeatedly tap trees for resin using the borehole method to obtain two to three collection seasons in one stand (Hodges, 2000). The technique patented by Barranx et al. (2002) also allows for oleoresin to be collected in a purer state without many contaminants by using a closed collection bag. Another advantage of the borehole tapping method is that it reduces the viscosity of the oleoresin and captures the volatile terpenes thanks to the closed collection container

(Lekha, 2002).

The Chinese method, mostly used in China, involves cutting a v-shaped wound that reaches and exposes the secondary xylem around 1.2 meters from the ground and a bag is attached to collect the resin flowing down (Cunningham, 2012). Workers then re-visit the tree every day to make another similar shaped wound right below that initial wound until the base of the tree is met (Cunningham, 2012). In China, the tapping season is usually only six months long compared to the eight-month season in Spain and Argentina and 10-month season in Brazil (Cunningham, 2014). The American

method, which is used in Brazil, Argentina, Portugal, and Spain involves making a horizontal wound the length of one-third the circumference of the tree and removing the phloem (Cunningham, 2012). Unlike the Chinese method, with the American method the initial wound is made at the base of the tree, about 20 cm above the ground, and each subsequent wound is made above that wound (Cunningham, 2012). Wound shape and type can affect resin yield. However, in Brazil, Rodrigues et al. found no significant difference in yield when streaking the bark in a V-shape compared to a horizontal line, though the line wound was more time effective (Rodrigues et al., 2008). The American method is also less labor intensive because the tree is re-visited every 15 to 18 days, compared to every single day using the Chinese method (Cunningham, 2012;

Rodrigues et al., 2008; Rodrigues et al., 2011). Unlike the Chinese method, the

American method involves the application of a stimulant paste or chemical, usually an ethylene precursor or salicylic acid, to increase resin yields (Cunningham, 2012). When trees are tapped using these methods all sides of the tree can be wounded in order to tap consecutively, for up to two decades (Coppen, 1995). In addition to the Hugues method, a study in Indonesia also tapped P. merkusii using the borehole method by drilling a 16-mm hole 2 cm into the tree at 20 cm from the ground, and found that the drill method was more successful at yielding oleoresin per wound per tree (Hadiyane,

2015). Contrary to all these methods, when using the borehole method, resin tappers only need to visit the tree twice during the season; once to tap the tree and another to collect the bags at the end of the season (Hodges, 1995).

The borehole tapping method allows landowners to collect oleoresin from pine trees while not damaging the quality of the wood for timber harvest because the tree is

taping solely at the base of the tree. Barranx et al. (2002) patented a method for harvesting oleoresin while also not diminishing the quality of the wood. This method also reduces the amount of volatile products that would normally be lost from evaporation, and does not use metal containers that are unfavorable for tree harvest and often used in other techniques (Barranx et al., 2002). Resin tapping has not been found to have a negative impact on overall tree growth, health quality and value at time of harvest for timber and pulpwood (Coppen, 1995). While there is a slight decrease in the growth during time of tapping, the amount of revenue made from collecting oleoresin during that period would make up for the loss, and may be even more profitable

(Coppen, 1995).

Streaking the bark can yield higher quantity of oleoresin during a season compared to the borehole method, although it is not as cost effective and is more labor intensive, thus not viable for a U.S. commercial production (Hodges, 1995; Rodrigues et al., 2008; Rodrigues et al., 2011). Within the borehole method there are many different prospective drilling designs. There is the potential for deeper or shallower holes, wider or narrower holes, or drilling at different angles. These different designs allow for the access of multiple resin canal networks. While borehole depth and width was positively correlated the average resin yield and the yield based on unit hole area were higher for normal width and shallower boreholes (Hodges, 1995).

To be economically viable, oleoresin yields per tree should be around 2 kg or higher (Coppen, 1995). The various collection techniques and pine species used for tapping around the world yield varying amounts of oleoresin annually (Table 2-1).

Application

Genetic Control and Breeding for Increased Terpene Production

Unlike agricultural crops, many trees, like conifers, take around 20-25 years to reach rotation age. Because of this, tree breeders rely on progeny tests to make inferences based on comparative performances of individual families at a younger age

(Squillace and Gansel, 1974). When selecting top performing progenies, it is crucial to select an age in which growth and yield is strongly correlated to that at the end of the rotation age. Squillace and Gansel (1974) found that progeny test results of slash pines at age 10 could be used to predict yields at age 25, which would allow breeders to increase genetic gains within a shorter period of time. There is always the possibility that younger progeny tests are able to accurately predict wood production and oleoresin yield at the rotation age.

Maximizing capacity of oleoresin yields may be possible through tree breeding programs, since traits that affect resin flow rate, as well as overall oleoresin yields have been found to be heritable (Schopmeyer et al., 1954; Mergen et al., 1955; USDA Forest

Service, 1971a; USDA Forest Service, 1971b; Tadesse et al., 2001; Westbrook et al.,

2013). Progeny tests using open-pollinated sources had greater within family variation in oleoresin yields compared to control-pollinated ones (Mergen et al., 1955). Narrow sense heritability of oleoresin yield in southern U.S. pines ranges from 45 to 90 % and broad sense heritability varies from 67 to 90% (Mergen et al., 1955; Squillace and

Doman, 1959; Squillace and Bengtson, 1961; Squillace, 1965). These estimates of heritability were much higher for gum yield compared to DBH, stem volume, height,

crown width and bark thickness, which had weak to moderately strong estimates

(Squillace and Bengtson, 1961).

Schopmeyer et al. (1954) found that when crossing a tree that has a high factor of significantly correlated with resin flow, such as lower viscosity, with a tree with another correlating factor, like high numbers of resin ducts, it is possible to produce a progeny with a potential to yield more oleoresin than either parent. Mergen et al. (1955) also found that oleoresin viscosity was controlled heavily by genetics. Oleoresin yield and tree growth seem to be controlled by pleiotropic gene with a positive correlation; therefore, selecting for better growing trees can simultaneously yield to trees that produce more resin (Squillace, 1965). All in all, the best way to increase oleoresin production in a stand through breeding is to select the high yielding trees (Tadesse,

2001).

A high gum yielding slash pine progeny test was established in June 1946 on the

Olustee Experimental Forest in Baker County, Florida (McReynolds and Gansel, 1985).

This study also found that increase gum content within slash pine trees is heritable, with high gum trees producing about 10% more wood volume and 30% more oleoresin yields (McReynolds and Gansel, 1985). While this study focused on the improvement of trees for resin production, it is possible to breed trees for better growth, straighter stems, smaller branches in addition to higher gum yields (Squillace, 1965). Genetic engineering and genomic selection allows for the enhancement of oleoresin production in conifers while also predicting genetic variation in performance in different environments (Westbrook et al., 2013). Through breeding and selection, oleoresin flow in southern pines was increased 1.4-fold and number of resin canals in trees was

increased by 1.1-fold (Morris, 2015). Furthermore, based on their research, Westbrook et al. 2013 predict it would be possible to increase oleoresin flow 1.5 to 2.4-fold through clonal breeding. Overall, achieving genetic gains with southern pines, especially slash pine, could be beneficial for both timber and oleoresin production. Bhat (2015) analyzed various genetic markers in P. roxburghii and found no association between them and oleoresin yield. However, since many traits strongly associated with oleoresin yield have high heritability and genetic gain, early selection can improve overall oleoresin production in a stand (Bhat, 2015).

The calculation of heritability shows the amount of total variance caused by a difference in breeding values (Klug et al., 2011). There are two main types of heritability; broad sense heritability, which is the phenotypic variation due to genetic causes and is used to compare clones, and narrow sense heritability, which is used to compare the similarities among relatives by showing how much phenotypes are determined by parental genes (Gezan, 2016).

Breeding hybrid species for increased resin production compared to parent species is also feasible (Coppen and Hone, 1995). One such hybrid is P. elliottii x P. caribaea, tested in South Africa and currently being used in for commercial resin production in Brazil (Coppen and Hone, 1995). When considering breeding hybrid or non-hybrid pines for increased terpene and resin production it is important to consider the quality and quantity of the species, which is affected by genetic factors. P. elliottii naturally has good quality resin and produces a good quantity, while P. pinaster produces good quality resin at a poor quantity (Coppen and Hone, 1995). P. massoniana, which is used in China for resin production produces poor quantity and

quality resin (Coppen and Hone, 1995). P. caribaea produces poor quality resin at very good quantities, while the converse is true for P. radiata (Coppen and Hone, 1995).

Given this information it would be possible to use tree breeding to create a hybrid species with P. caribaea and P. elliottii or P. radiata that produces better quantities of resin at higher quality.

When breeding pine trees for terpenes, or any phenotypic trait, repeatability studies are important, as they provide crucial data and insight on the variation between and within individual trees (Roberds and Strom, 2006). Furthermore, in cases where genetic information is unavailable or it is difficult to calculate heritability, repeatability studies can be used to determine the levels of variation (Roberds and Strom, 2006).

Global Uses for Oleoresin

Pine terpenes for commercial products

Presently, turpentine is collected around the world as a source of chemical isolates to be used or various commercial products, such as, cleaning agents, medicine, paints, and pine oil used for fragrance and flavor (Coppen, 1995). The raw oleoresin is cleaned and then steam distilled at a factory to make turpentine and rosin (Coppen,

1995). The main derivative compounds extracted from oleoresin for commercial purposes include anethole, isobornyl acetate, camphor, citral, citrinellal, linalool, and menthol (Coppen, 1995).

Within the international market, the standard used by the chemical industry that converts derivative compounds to pine oil and fragrances considers turpentine with a total pinene content of 90% to be “good”, while a beta-pinene content of 30-40% is

“excellent” (Coppen, 1995). If the collected turpentine consists of less than 70% of pinenes, it would not succeed in the international market (Coppen, 1995).

Rosin is the main product obtained after distilling pine oleoresin (Coppen and

Hone, 1995). The quality of the rosin varies and depends primarily on color, with the lightest yellow shades being the best (Coppen and Hone, 1995). Unlike turpentine, rosin cannot be used in its raw state and is chemically modified in order to make inks, adhesive, detergents, etc. (Coppen and Hone, 1995). Turpentine can be used in its raw form to make paint solvent or act as a cleaning agent, and can be processed chemically to make a variety of derivatives (Coppen and Hone, 1995).

Pine terpenes for biofuels

One of the goals of collecting oleoresin from pine trees is to provide a potential alternative to petroleum at a competitive price (Barranx et al., 2002). The pure and mixed pine monoterpenes can be dimerized efficiently to make a good replacement for petroleum derived jet fuel (Meylemans et al., 2012, Meylemans et al., 2013). Biofuels are energy sources originated from renewable biomass sources, such as agricultural crops or trees, which can be used for fuel and electricity (Jessup, 2011). Currently, the most widely used form of biofuel globally is ethanol, derived primarily from sugar cane

(Goldemberg, 2007, Somerville et al., 2010). Ethanol actively competes with the petroleum industry, with Brazil producing about 16 billion liters every year (Goldemberg,

2007). In Brazil, there is the potential of sugarcane biomass producing the energy equivalent of 14% of the fuel used for transportation (Somerville et al., 2010). Brazil has about 2.9 million hectares of planted sugarcane that is used solely for ethanol production (Goldemberg, 2008). However, if demand for ethanol as a biofuel increases,

more agricultural land in Brazil, such as pastureland, could get converted into sugarcane plantations, which could in turn increase the pressure of the cattle industry on the Amazon (Goldemberg, 2008).

Biofuels can provide the same benefits as fossil fuels without the negative impacts of high net greenhouse gas emissions, and they are also renewable, sustainable resources that promote energy security (Smith et al., 2013). With biofuels, the amount of energy mined and extracted below ground is limited and replaced with energy obtained from above-ground sources (Borak et al., 2013). One of the big controversies with biofuels is that land that could be used to grow food is getting diverted to grow fuel; also, there is the fear that as oil prices increase, so will the price of grain, because it would become more profitable for farmers to grow biomass for fuel

(Kovarik, 2013).

In areas like the southern U.S., where biofuel crops, including P. palustris, P. taeda, and P. elliottii var. elliottii, that are high in gum turpentine grow naturally, biofuel production from oleoresin could reasonably be promoted. Most pine and other biofuel crop plantations are genetically engineered or selected to increase efficiency and production. Over the past few decades, studies have shown that there are no negative environmental impacts on genetically engineered trees (Häggman et al., 2013). If pine trees can be bred and selected to increase terpene content, forests in the southeast

U.S. could provide abundant feedstock for ethanol production (Singh, 2013). There has already been advancement in increasing oleoresin production in pine trees through breeding, inoculation, and the application of chemical stimulants (Squillace, 1965;

McReynolds and Gansel, 1985; Hodges, 1995; Popp et al., 1995b; Hodges, 2000,

Martin et al. 2003 Hudgins et al. 2004, Hudgins and Franceschi 2004, Huber et al.,

2005, Rodrigues et al., 2008; Morris, 2015). On average, P. taeda has about 2.3% terpene content in heartwood, 0.77% in the inner sapwood, and 0.35% in the outer sapwood (Thompson et al., 2006). Furthermore, the quality of terpenes from conifers are superior to ethanol and other biodiesel sources (Zerbe and Bohlmann, 2014).

While biofuels from agricultural crops are fast growing, highly resistant to pests, highly adaptable, and high yielding, pine trees take approximately 20 years to reach rotation age (Smith et al., 2013). Faster growing trees allow for faster genetic selection and gains, which can improve composition of feedstock for bioenergy. Through breeding trials, pine trees have become more and more resistant to pests, but remain severely affected by them in certain areas. As a result of the much longer rotation age, the net energy yield potential of pine terpenes is lower than that of other agricultural and woody biomass sources (Hinchee et al., 2011). There is a potential for these yields to increase with the advancement in breeding strategies.

The net energy balance, which is unit of energy produced for every unit of energy utilized, of slash pine is higher at 5.7 than that of other feedstock, such as corn (1.25), corn stover (1.7) or switch grass (5.4) (Nesbit, 2008). The net energy balance for ethanol production from sugarcane is between 8.2 and 10, which is much higher than all the other feedstocks discussed (Goldemberg 2008). Pine terpenes in their reduced forms, such as myrcene, limonene, farnesene, and bisabolene have properties and energy content similar to that of diesel fuel (Harvey et al., 2010; Zerbe and Bohlmann,

2014). This shows the potential of pine terpenes for biofuel production, with a potential

of 5.5 billion gallons of ethanol capable of being produced in the U.S. from pine plantations (Nesbit, 2008).

Distillation

Oleoresin collected from live trees is converted into rosin and turpentine through steam distillation (Coppen, 1995; Rezzi, 2005; Figure 2-3). Figure 2-3 outlines the distillation process used to obtain gum turpentine and gum rosin. Rosin and turpentine are further processed into a variety of different chemical products (Rezzi, 2005). After the distillation process, 1000 tonnes of raw resin collected in one year will yield about

650 to 700 tonnes of rosin and 150 tonnes of turpentine (Coppen, 1995).

Economics of Oleoresin Production

Non-Timber Forest Products

Non-timber forest products (NTFP) are harvested around the world in both natural and plantation forests, and are an important income source for millions of people, especially indigenous populations (Ticktin, 2004; Stanley et al., 2012). NTFP range from medicinal products to aromatic resins, oleoresin, pine straw, fruit, rubber, etc. The main advantage of NTFP is that if the demand for these products is high, the deforestation and land use changes will decrease. However, in developing countries people may become dependent on forest resources for economic security, which may be problematic in the long run (Stanley et al., 2012). Though presently, out of 71 NTFP studies sampled, over two-thirds of NTFP researched met the threshold for economic sustainability (Stanley et al., 2012). In tropical rainforests, for example the Brazilian

Amazon, Brazil nut and natural rubber were NTFP historically important to people living

in the forest and were promoted as an incentive to protect the native ecosystem

(Belcher and Schreckenberg, 2007).

In industrialized countries, like the U.S., NTFP are collected primarily in plantations. Landowners in the Southeast U.S. actively manage their pine plantations

(loblolly, P. palustris, and slash) for pine straw as well as timber production (Dickens et al., 2011). In intensively managed plantations, landowners can make an income, even if they are absent, for about 5 to 10 years prior to final timber harvest and increase their total net revenue from the stand (Dickens et al., 2011). In Georgia, the economic benefit of pine straw raking was close to $81 million in 2009 (Dickens et al., 2011). Pine straw collection is a wonderful NTFP for both small and large landowners. Management strategies that benefit pine straw collection, such as fertilization and weed control, is also beneficial to timber harvest, as it increases the overall production of the stand, making it more economically profitable (Duryea, 1989; Dickens et al., 2011).

Oleoresin is one of the oldest NTFP, is renewable, and has undergone significant improvement in collection methods (Tadesse et al., 2001). Economically, re-adding

NTFP to the forest management portfolio in the U.S. would be very beneficial and oleoresin production can easily be included. However, excessive resin tapping, especially using the traditional method of streaking or chipping the bark, may cause tree mortality (Stanley et al., 2012; Susaeta et al., 2014). Formerly, the U.S. was the world’s leading producer of oleoresin, with 50% of production, though that title now belongs to

China (Tadesse et al., 2001). With modern techniques of tapping that are less damaging to trees, combined with the increase in tree productivity for resin and timber

due to breeding, selection, and intensive management, the U.S. can get back into the market and potentially return to being the leading producer of oleoresin.

Oleoresin Tapping and Timber Production

Pine oleoresin is an important NTFP collected and used around the world to increase the economic value of the forest. To be more economically viable, it is important to be able to collect oleoresin from live pine trees while still being able to harvest the timber from that same stand. Wang et al. (2006) reported an increase in the optimal rotation age of their Simao pine plantation in China from oleoresin tapping. This occurs because trees produce more oleoresin as they increase in age (Wang et al.,

2006). However, in the U.S., with slash pine, the optimal rotation age did not increase due to tapping (Susaeta et al., 2014).

With all else equal, a plantation that includes resin tapping and timber production in the management portfolio is more profitable than one with only timber production, as long as the site index is greater than 12 (Wang et al., 2006). The net present value of a resin and timber plantation is higher compared to timber plantations, and is also profitable in cases when only timber is not, such as interest rates of 12% (Wang et al.,

2006). Furthermore, adding oleoresin tapping to a timber stand is most beneficial when the discount rate is low (Wang et al., 2006). Including oleoresin with timber production was found to increase the land expectation value (LEV) by 20.5-42.7% (Susaeta et al.,

2014). The intensity of resin tapping must also be considered. If stands are tapped at higher intensity rates there is the potential of negatively affecting growth of trees, which would diminish the profits from timber harvest while increasing those from resin

collection (Wang et al., 2006). However, with management and control of tapping, this added commodity can be lucrative without damaging forest ecosystems.

Global Supply and Demand

Market requirements

A small processing plant that produces 1,000 tonnes annually would need resin tapped from about 330,000 mature pines if annual production is 3 kg per tree (Coppen and Hone, 1995). Oleoresin quality is important when selling in the international market

(Coppen, 1995). In general, higher levels of beta-pinene, at least 30%, are preferable, and total pinene content above 90% is considered good quality (Coppen, 1995). The presence of certain compounds like 3-carene would lower the quality of resin (Coppen,

1995).

Global production

Production of oleoresin globally averages at about 1,100,000 metric tonnes annually, and in 2008 China produced 849,205 tonnes (Rodrigues-Corrêa et al., 2012;

Susaeta et al., 2014; FAO, 2014). Between 2006 and 2007, Brazil produced about

106,000 tonnes of oleoresin primarily from P. elliottii (Rodrigues et al., 2008). Since

2000, Chinese exports of rosin, resin acids and resin derivatives have steadily increased from about 181.68 million U.S. Dollars (USD) in 2000 to about 551.85 million

USD in 2014 (World Trade Atlas, 2016). The quantity of rosin and resin acids and derivatives exported by China has fluctuated from around 335,642 metric tons in 2000, to around 503,273 metric tons in 2007, and then steadily decreased to about 208,744 metric tons in 2014 (World Trade Atlas, 2016). While the quantity of resin being exported by China has decreased over the years, the value of resin has increased. The

average price of rosin and resin in 2000 was about 0.54 USD per kilogram compared to the current average price of 2.64 USD per kg (World Trade Atlas, 2016). Since China uses the bark streak method of tapping with an open collection system, the resin collected by China is of lower quality to the oleoresin that could be produced in the U.S. through the closed system of the borehole tapping method proposed. Therefore, the value of U.S. oleoresin would potentially be higher and thus could be sold at a higher price compared to China.

Over the past 1.5 decades, the U.S. has steadily imported about 30 million USD to 83 million USD, with a peak of 119 million USD, worth of rosin and resin acids and derivatives annually (United States Census Bureau, 2016). This equates to about

30,000 to 57,000 metric tons of rosin and resin acids and derivatives annually (United

States Census Bureau, 2016). Furthermore, the U.S. has also imported between 5 to 11 million USD worth of turpentine and pine oil annually, while importing 21.85 and 20.78 million USD of this commodity in 2011 and 2012, respectively (United States Census

Bureau, 2016). The U.S. imported between 6.5 to 14.5 metric tons annually of turpentine and pine oil between 2000 and 2014; with the recent few years seeing a reduction in imports from over 12 metric tons in 2012 to 6.5 and 8.6 metric tons in 2013 and 2014, respectively (United States Census Bureau, 2016). The average price of turpentine oil has increased over the years from 0.29 USD/kg in 2000 to 1.14 USD/kg in

2014; pine oil prices have also increased from 1.04 USD/kg in 2000 to 1.54 USD/kg in

2006 (United States Census Bureau, 2016). The U.S. spends a significant amount of money on importing these commodities which could be sourced domestically.

Reinvigorating the oleoresin industry in this country to supply the pine chemical

companies, would allow the U.S. to reduce their imports, and also potentially increase their exports, while supplying jobs to many Americans.

What Drives the Production Cost?

Labor

The different methods of oleoresin tapping require different organization and labor (Coppen and Hone, 1995). When using the bark streaking methods such as the

Chinese, American and French, the resin tapper must visit the tree more frequently throughout the season. Under the Chinese method, because no chemical stimulant is used, the resin tapper must visit the tree approximately every one to three days

(Coppen and Hone, 1995). This would mean more working hours and thus more pay for the worker per season. However, the countries that typically use this method have lower labor costs, like China compared to the U.S. The American and French methods require a visit to the tree every 1 to 2 weeks, which lowers the number of total working hours per laborer but can still be costly depending on minimum wage levels (Coppen and

Hone, 1995). The borehole method is the most cost-effective method in terms of labor because the resin tapper only needs to revisit the tree twice in one season, though tapping takes more time per tree (Hodges, 1995). Cunningham presented the average wage per hour for resin tappers in Brazil, Argentina, Spain and China as well as the labor cost per ton based on the quantity of oleoresin collected by each worker

(Cunningham, 2014; Table 2-2). Developing countries have much cheaper labor compared to developed countries, and thus are able to produce more (Cunningham,

2014; Table 2-2). However, the average resin produced per laborer in China compared

to Brazil and Argentina show the importance of investing in better, more sustainable tapping techniques regardless of cost of labor (Cunningham, 2014; Table 2-2).

When using the bark streaking methods, prior to the beginning of the tapping season, additional labor is required to prepare the stand by shaving the trees and installing collection vessels (Coppen and Hone, 1995). Furthermore, at the end of the season, labor is required to clean-up and collect all the vessels (Coppen and Hone,

1995). As an incentive to be more productive and work more efficiently, some companies pay their laborers based on how much resin they collect, or establish systems in order to reward people who collect more with bonuses, and penalize those that do not produce as much (Coppen and Hone, 1995). In some countries, laborers do not work with a company and are allocated a certain number of trees, and can then decide whether or not they want to hire help using their own finances (Coppen and

Hone, 1995). In the U.S., both small landowners and large companies could enter the resin collection business. Since the minimum wage in the U.S. is higher than in many developing countries, resin tappers would have more of an incentive to work even if it requires hard labor. A tapping method requiring an individual to re-visit the tree multiple times within one season would not be cost effective in this country, because of the higher labor cost, which is why borehole tapping appears to be the best method for this country.

Equipment

The following is a list of equipment that is required to complete resin tapping following the bark streaking methods (Coppen and Hone, 1995).

• Tool to shave off the bark • Bark hack to remove bark 90

• Collection vessel • Material to make gutters • Support nail for the gutters • Hammer or mallet • Sharpening tool for bark hack • Chemical stimulant • Bottle or container to hold and apply stimulant • Bucket to empty resin from collection vessel • Barrel or drum to collect and transport resin • Protective equipment for resin tappers

Similarly, the following is a list required to collect oleoresin using the manual borehole tapping method.

• Boring auger drill bit (2.54 cm or bigger) • Gasoline powered drill • Sharpening tool for drill bit • Gasoline tank • Gasoline and 2-cycle engine oil • PVC pipe fitting • Mallet • Polyethylene collection bags • Cable ties to attach bags to fittings • Spray bottle to hold and apply stimulant • Chemical stimulant • Wire hooks to drain oleoresin from bags to barrels • Barrel or drum to collect and transport resin • Protective equipment for resin tappers

Cost Compared to other Biofuels

Feedstock costs of pine terpenes for biofuels compared to other sources including sugarcane, soybeans, and corn, is much lower at around $25 versus around

$200 per barrel of oil equivalent (Peter, 2013). Also, this cost has remained fairly stable over the past 10 years, whereas other feedstock costs have fluctuated tremendously

(Peter, 2013). The lower feedstock costs are advantageous because it increases the profitability of the biofuel. However, the cost of establishing agricultural plantations is

much lower than that of establishing pine plantations. Frederick et al. (2008a) reported that ethanol from lignocellulosic loblolly pine can be produced at about $1.53 per gallon if 75% of the carbohydrates in the wood can be converted to sugars for ethanol. This cost can be reduced if conversion technology is improved and 95% of carbohydrates can be converted (Frederick et al. 2008a). In addition to this, other co-products, such as tall oil and acetic acid can be recovered for additional profits while processing loblolly carbohydrates for ethanol (Frederick et al. 2008b). This particular cost analysis is based on pine terpene collected from dead trees and not the oleoresin collected from live trees.

Another advantage to using pine terpenes as feedstock for biofuels is that production is scalable due to the large available land area and stable $3-billion-dollar market that is already established (Peter, 2013). Pine terpenes consist of many different compounds that can be used to replace or add into petroleum products (Peter, 2013).

However, the ethanol cost of sugarcane feedstock produced in Brazil is about $0.81 versus, $2.89 for European sugar beet, $1.03 for U.S. corn, and $2.12 for U.S. slash pine terpenes (Goldemberg, 2007; Nesbit, 2008). While pine terpenes are more expensive, they are still competitive and with improvements in genetics and technology, they have the potential to become more cost effective. The market for pine terpenes is already established; in 2010 the U.S. spent $940.8 million buying this product internationally and produced $1.92 billion (Peter, 2013). This means using southern pine plantations in the U.S. for pine terpene production could provide products not only for biofuels but also for the pine chemicals industry.

Besides the economic costs of agricultural crops as biofuels, there can be a detrimental environmental cost. While biofuels can work to reduce greenhouse gas emissions by sequestering carbon through growth, it can also increase emissions from land use changes (Searchinger et al., 2008). Increasing biofuel production from agricultural crops such as corn, switchgrass, or sugarcane could promote the conversion of forestland to cropland by farmers (Searchinger et al., 2008). Depending on the types of land-use changes, biofuels from corn can double emissions while biofuels from switchgrass has the potential to increase emissions by 50% (Searchinger et al., 2008). In Brazil, the expansion of agricultural land was reported to lead to deforestation in the amazon and averaged about two times the size of land cleared cattle production (Morton et al., 2006). While the production of agricultural crops for biofuel, animal feed, and human consumption can be improved through more intensive and efficient agricultural practices, as the demand increases, more forestland will be cleared to meet consumption needs. On the other hand, if pine terpenes are used for biofuel production, there will not be as much of a need for land-use changes because of the already established productive pine plantations, but if there are changing land-use from cropland or pastureland to forests would reduce greenhouse gas emissions.

Table 2-1. Average annual oleoresin yield in different regions from various pine species using different tapping methods. A minimum of 2 kg per tree annually is necessary to be economically viable for commercial production. Data retrieved from Hodges 1995, Tadesse et al. 2001, Rodrigues et al. 2011, Cunningham 2012, and Rodríguez-García et al. 2014, Hadiyane et al. 2015. Country Tree Species Tapping Technique Average Oleoresin Yield (kg/tree/yr) Spain P. pinaster American 2.39-3.8 United States P. elliottii Borehole 1.8 Brazil P. elliottii American 2.1-6.0 China P. massoniana Chinese 2.0 Indonesia P. merskusii French 2.32

Table 2-2. Average cost of oleoresin tapping operation in various countries based on hourly wage and quantity of oleoresin collected per resin tapper. Cost is based on United States dollar. Data retrieved from Cunningham 2014. Country Average Wage Average Resin per Average Labor (USD/Hour) Worker (ton) Cost (USD/ton) Spain 10.34 18.2 1170 Argentina 3.34 14.4 477 Brazil 4.52 32.3 288 China 3.70 3.5 2060

Figure 2-1. Processes of that lead to successful beetle colonization and conifer defenses with interfering processes used by each organism to prevent the other’s success. Adapted from Wood 1982, Raffa et al. 1993, Phillips and Croteau 1999, Raffa et al. 2005, Faccoli and Schlyter 2007.

Figure 2-2. Diagrams of borehole tapping designs. A) Standard boreholes drilled manually with a gas-powered drill. B) Standard boreholes drilled manually on opposite sides of the tree. C) Boreholes drilled using a tractor mounted automated system, (d) borehole drilled manually with two shallower wide holes and two longer holes drilled with a 0.9525 cm drill bit. E) Six boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. F) Eight boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. G) Three borehole system drilled manually with one central borehole and two interior boreholes. All boreholes were drilled using a 2.54 cm drill bit; apart from the longer borehole in D which was drilled using a 0.9525 cm drill bit, the central borehole in the automated system (B) which was drilled with a 3.175 cm bit and the boreholes in the triple borehole experiment (G) which had a counterbore drilled with a 3.175 cm bit and a 2.54 cm drill bit.

Figure 2-3. Oleoresin distillation process adapted from Coppen 1995.

CHAPTER 3 ASSESSING EFFECTS OF STAND MANAGEMENT, TREE CHARACTERISTICS, AND CHEMICAL STIMULANT ON OLEORESIN PRODUCTION

Introduction

In the United States, the naval stores industry began in the mid-19th century with the extraction of pine oleoresin from longleaf (Pinus palustris Mill.) and slash pine

(Pinus elliottii Engelm. Var. elliottii) trees (Harrington, 1969; Sullivan, 2014). In the U.S., oleoresin collection from live trees, stopped in the 1980’s and is principally recovered in chemical pulp mills processing pine pulpwood (Harrington, 1969; American Chemistry

Council, 2011). Today, oleoresin is harvested from live pine trees in countries like China and Brazil to supply the pine chemical industry. Natural stands of Pinus massoniana

Lamb. and planted stands of slash pine are primarily used for tapping (Aguiar et al.,

2012). Raw oleoresin is an important pine product as it is processed into various commercial products such as medicine, paint, fragrances, flavoring, and cleaning agents (Coppen, 1995; Coppen and Hone, 1995). In addition, pine terpenes can be used for biofuel, providing an alternative to petroleum (Barranx et al., 2002).

Oleoresin is a naturally produced by all conifers as a defense against pests and any physical damage. Oleoresin production can be induced in various ways; by using chemical inducers, by physical tapping, and by many environmental factors, such as fire, fertilization, water availability, and climate (see Chapter 2). While there are several tapping techniques used to collect oleoresin from live pine trees (see Chapter 2), for a commercial operation, the primary method for increasing the production of and collecting oleoresin from live pine trees is by wounding and applying a chemical stimulant (Hodges, 1995; Martin et al., 2003; Rodrigues et al., 2008). The primary

method of wounding used globally involves streaking the bark several times during a tapping season, as frequent as every day to every two weeks. This method, however, is not suitable for the U.S. because of higher labor costs. This study used the borehole tapping method, which involves drilling holes into the base of the tree (Hodges, 1995;

Hodges, 2000; Hadiyane et al., 2015).

With multiple tapping techniques, chemical inducers are applied to increase yields (Hodges, 1995; Martin et al., 2003; Hudgins et al., 2004; Hudgins and

Franceschi, 2004, Huber et al., 2005; Rodrigues et al., 2008). As discussed in Chapter

2, methyl jasmonate and ethylene releasing compounds are the two most used stimulants for oleoresin production. Here, we compare the oleoresin yield of trees treated with these two chemical stimulants as well as a combination of inducers. The working hypothesis is that when applied to a wound site on the slash pine stem, chemical stimulants promote the flow of oleoresin towards the wound, stimulate the formation of new resin canals, and increase overall capacity of tree to synthesize and release oleoresin.

Tree diameter at breast height (DBH), height and crown size were reported to have a significant positive effect on oleoresin yield in certain studies (Tadesse et al.,

200; Novick et al., 2012), but not all of these factors had significant effects in other studies (Gansel, 1965; Lekha, 2002). The hypothesis is that trees with larger DBH more leaf area have greater xylem tissue growth, which allows for formation of new resin canals and terpene synthesis. In the southeastern U.S., the best way to accelerate planted pine tree growth is to use various silvicultural practices, including thinning, fertilization, and weed control. All the stands sampled in this study were managed using

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conventional silvicultural practices, including fertilization and herbicide application. Here, we compare the oleoresin yields of stands of differing ages and thinning regimes, while also comparing yields of individual trees based on tree size. We hypothesize that slash pine trees grown in more intensely managed stands will produce more oleoresin when tapped then those with less management, because more photosynthate can be allocated to growth and oleoresin production. Since oleoresin production is maximized when trees are tapped during the summer months (Lorio, 1986; Gaylord et al., 2007;

Davis et al., 2011), oleoresin tapping for this study occurred in the summer, except for the 2013 tapping season which began in early fall.

The objectives of this study were 1) to compare oleoresin yield in slash pine under different silvicultural management scenarios and with various chemical stimulants, and 2) to determine the influence of tree characteristics, including age, DBH, height, and crown volume on the yield of oleoresin.

Methods

Study Areas

Planted slash pine (P. elliottii) trees between the ages of 11 and 23 years were selected from privately owned and managed stands in Alachua, Bradford, and Union counties in Florida, U.S. The forestry companies that provided land for this study included: Rayonier, Roberts Land & Timber Investment Corp., and Weyerhaeuser

(formerly Plum Creek Timber Company). Throughout the study, 10 stands were selected, some of which were used for consecutive years. All stands were managed using similar conventional silvicultural practices such as bedding, fertilization, weed control and contained open pollinated seedlings from genetically improved slash pine

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seed orchards. The criteria used to select stands for tapping included: not easily accessed by the public, sufficient number of live trees available to tap, appropriate age, and thinned/unthinned management. Within a stand, trees with prominent physical signs and symptoms of diseases such as fusiform rust (Cronartium fusiforme Hedgcock &

Hunt ex Cummins), pitch canker (Fusarium circinatum Nirenberg & O’Donnell), bark beetles, and pitch moth were not selected. Furthermore, within a stand, dead trees and those damaged from abiotic factors were not selected. Also, trees with a DBH less than

12.7 cm were not selected to prevent tapping a borehole through the tree.

One of the goals of this study was to analyze the production of oleoresin from trees of varying ages and management strategies. Stand ages from 11 to 22 years were selected and within these age classes, unthinned and thinned stands were selected, except for the 11-year-old stand. The selected unthinned stands were not thinned until the completion of the study.

The Union 1 slash pine experimental site is located near Lake Butler in Lake

Butler, Florida (30°04’N latitude and 82°18’W longitude) at an elevation 43 meters from average sea level (Table 3-2). The Alachua 1 experimental site is located just outside of

Gainesville, Florida (29°43’N latitude and 82°17’W longitude) at an elevation 48 meters from average sea level (Table 3-2). The Alachua 2 experimental site is located near

Newnans Lake east of Gainesville, Florida (29°42’N latitude and 82°11’W longitude) at an elevation 32 meters from average sea level (Table 3-2). The Bradford 1 experimental site is in Hampton, Florida (29°53’N latitude and 82°15’W longitude) at an elevation 48 meters from average sea level (Table 3-2). The Union 2 experimental site is in Lake

Butler, Florida (30°03’N latitude and 82°21’W longitude) at an elevation 41 meters from

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average sea level (Table 3-2). The Alachua 3 experimental site is located just outside of

Gainesville, Florida (29°46’N latitude and 82°18’W longitude) at an elevation 51 meters from average sea level (Table 3-2). The Alachua 4 experimental site is located just outside of Gainesville, Florida (29°43’N latitude and 82°11’W longitude) at an elevation

33 meters from average sea level (Table 3-2). The Alachua 5 experimental site is located just outside of Gainesville, Florida (29°42’N latitude and 82°15’W longitude) at an elevation 42 meters from average sea level (Table 3-2).

All study sites share a humid subtropical climate with hot wet summers and mild dry winters, and the topography was primarily flat with a 1-2% slope. The soils in the study sites ranged from poorly drained to moderately well drained. The site indices of the stands selected ranged from 70 to 90 meters (Table 3-1). The understory vegetation varied throughout the different sites but was primarily sparse compared to natural forests in North Florida. Understory vegetation included saw palmetto (Serenoa repens

(B.) Small.), blackberries (Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)), and greenbriers (Smilax L. spp.), among others.

Borehole Tapping and In-Tree Injection

The borehole tapping method was used to collect oleoresin from living slash pine trees (Hodges; 1995). This method involves drilling a hole into the xylem of a tree and attaching a bag for long-term collection. In the standard tapping method, two boreholes are drilled parallel to one another at the base of the tree using a Stihl BT45 gasoline powered drill at about 1000 rpm. The boreholes were drilled to a depth of 10 cm, 2.54 cm in diameter, and approximately 10 cm apart from one another (Figure 2-2). The holes were drilled at a slight upward angle to facilitate the oleoresin flow downward into

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the collection bag. An Irwin auger bit 2.54 cm diameter, 15 cm twist, and 20 cm overall length was used. The drill bit was sharpened using a triangular file sharpener two to three times a day to ensure effective drilling and cutting of the oleoresin canals.

Immediately after the boreholes were drilled, a chemical stimulant was applied to the hole using a handheld pump compression sprayer. Several chemical stimulants were tested in this study. The compression sprayer was equipped with a cone shaped nozzle that allowed for the application of the chemical solution on the entire surface inside the hole. Approximately 2 ml of the chemical solution was sprayed into each borehole. The chemical treatments were assigned randomly to the trees in the experiment prior to visiting the field site. Each treatment had a sample size of 40 trees and 320 trees per site were tapped. These treatments were replicated across three different age groups and across three tapping seasons between 2013 and 2015 (Table

3-1).

Following the chemical application, a 1.905 cm PVC Lasco male adapter fitting was inserted into the borehole using a mallet to seal it securely. A 3-ply polyethylene/nylon laminate bag with a 2-liter capacity was attached to the fitting and secured using a cable tie. The collection bags were left in the field for 60 to 120 days until weighed and collected once.

During the 2014 tapping season, tapped trees were also injected about 30 days after tapping with an additional chemical stimulant above and in between the two boreholes using an Arbojet Quikjet in-tree injector. During the 2015 tapping season, trees were injected two weeks prior to drilling the boreholes at select sites. These treatments were replicated across 6 sites and across all chemical treatments.

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Chemical Stimulants

Several chemical solutions were tested to stimulate the production of oleoresin in slash pine. At each site, 320 trees were selected and four chemical inducers were tested. Each chemical stimulant treatment had 80 replicates per site. In the 2013 field season, a combination of deionized water, sulfuric acid (H2SO4) and Tween 20

(surfactant) was applied as the control treatment. In addition to this solution, methyl jasmonate with a concentration of 100 mM, 10% ethephon (2-chloroethyl-phosphonic acid, an ethylene precursor), and a combination of the two were added as a stimulant treatment.

During the 2014 to 2015 field seasons, sulfuric acid was no longer used in the chemical solutions. The control treatment consisted of deionized water and Tween 20.

For the stimulant treatments, 100 mM methyl jasmonate, 10% ethephon, and a combination of methyl jasmonate and ethephon were used. During the 2014 field season, a stimulant treatment of iron sulfate with methyl jasmonate was used instead of the methyl jasmonate and ethephon combination treatment. These same stimulants were also injected into the appropriate tapped trees using an in-tree injector after borehole drilling in 2014 and prior to borehole drilling in 2015. Each chemical treatment with and without an in-tree injection had 40 replicate trees, conforming a total of eight treatment combinations.

Data Collection

DBH, tree height, crown height, and crown width was measured for each tree selected for tapping within two weeks of tapping. Table 3-2 summarizes the statistics for all sites tapped from 2013 through 2015. The DBH was measured using a standard

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fabric diameter tape. The tree and crown heights were measured using a Haglöf Vertex

IV Hypsometer (Sweden), which was recalibrated daily. Crown width was measured both along and across the bed using a measuring tape and two field assistants. To measure crown, the longest branch on each side of the tree that was part of the crown was selected. If the longest branch was isolated and not part of the main tree crown it was not selected. Crown volume was then calculated based on the crown height, tree height, and crown width measurement using the standard formula for the volume of a cone:

Volume = π * r2 * (h/3); where r is the radius based on the arithmetic average radius of the crown width measurements, and h is the height of the live crown calculated by subtracting lower crown height from total tree height.

Two to three months after tapping the trees, the bags containing oleoresin were collected from the field and weighed. Net oleoresin yield for each borehole was measured using a digital scale with a hook, a 50 kg capacity, and a 5 g or 10 g accuracy at the end of the tapping season. Once all the measurements were taken, the bags were then drained into plastic barrels for collection.

Tapping Area

The oleoresin yields per unit area tapped were calculated from the cross- sectional area of the individual borehole as well as the estimated sector-shaped tapping area of the tree stem. The cross-sectional area of the borehole was estimated as a polygon with sides a-b-c-d (Figure 3-1). The tapping area was considered as the area in which there is access to resin canals from the borehole tapped. The projected area was estimated from the extremities of the borehole and the center of the tapped tree (Figure

3-1; Figure 3-2). The areas were estimated using trigonometric formulas for the area of 106

a triangle. The predicted stump diameter was calculated using the taper equation developed by Bailey (1994) for slash pine trees. To estimate the outer bark stump

137.16 β diameter in cm for slash pine trees the equation used was: Db = D ( ) , where Db is hb the stump diameter, D is the DBH calculated at breast height (1.37 m), hb is the height of the stump which is equal to the height of borehole (assumed to be 15.24 cm for all tapped trees), and β is the constant parameter for slash pine trees (0.094138) based on a fitted equation (Bailey, 1994).

The following are the formulas used to calculate the angles to determine the area in cm2 of the projected triangle (c-x-y) or shaded tapping area in cases where the borehole depth (10.16 cm) was less than the stump radius (Figure 3-1):

3.81 <β = sin-1 [ ] r

6.35 <λ = tan-1 [ ] r-bd

<α = <λ -<β

α Tapped Sector Area (cm2) = × r2× π 360

Where r is the radius in cm calculated from the estimated stump diameter (Db/2), bd is the depth of the borehole (10.16 cm for all tapped trees).

The following formulas were used to calculate the angles to determine the tapping area in cm2 in cases where the borehole depth (10.16 cm) was greater than the stump radius (Figure 3-2):

3.81 <β = sin-1 [ ] r

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bd-r <λ = tan-1 [ ] 3.81

<α = (<λ +<90) − <β

α Tapped Sector Area (cm2) = × r2× π 360

Where r is the radius calculated from the estimated stump diameter (d), bd is the depth of the borehole (10.16 cm for all tapped trees).

The following are the formulas used to calculate the tapping intensity (Figure 3-1;

Figure 3-2):

Tree Basal Area (cm2) = (0.00007854 × d2) × 10000

Tapped Sector Area Tree Tapping Intensity (%) = × 10000 Tree Basal Area

Statistical Analysis

To assess the main effects of chemical treatment, DBH, number of collection days, site, age, and crown volume on oleoresin yield, a general linear model was fitted using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al.,

2015). The data were analyzed by site, by stand, by chemical treatment, and by number of collection days. The following example model, with covariates, was used:

Y = µ + T + Co + D + A + CV + S + St + e where, µ is the overall mean; T is the fixed effect of chemical treatment; Co is the fixed effect of number of collection days; D is the fixed effect of DBH (cm); A is the fixed effect of age (years); CV is the fixed effect of crown volume (m3); S is the fixed effect of site; St is the fixed effect of stand; and e is the random error.

To assess the individual and interactive effects of treatment, number of collection days, DBH, age, and crown volume on oleoresin yield, a general linear model was fitted 108

using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al.,

2015). Since the number of collection days varied by site, it was standardized for this analysis. The following model, with covariates, was used:

Y = µ + T + Co + D + A + CV + T:Co + T:D + T:A

+ T:CV + Co:D + Co:A + Co:CV + D:A + D:CV + A:CV

+ T:Co:D + T:D:CV + S + S:T + e where, µ is the overall mean; T is the fixed effect of chemical treatment; Co is the fixed effect of number of collection days; D is the fixed effect of DBH; A is the fixed effect of age; CV is the fixed effect of crown volume; T:Co is the fixed interaction effect of chemical treatment and number of collection days; T:D is the fixed interaction effect of chemical treatment and DBH; T:A is the fixed interaction effect of chemical treatment and age; T:CV is the fixed interaction effect of chemical treatment and crown volume;

Co:D is the fixed interaction effect of number of collection days and DBH; Co:A is the fixed interaction effect of number of collection days and age; Co:CV is the fixed interaction effect of number of collection days and crown volume; D:A is the fixed interaction effect of DBH and age; D:CV is the fixed interaction effect of DBH and crown volume; A:CV is the fixed interaction effect of age and crown volume; T:Co:D is the fixed interaction effect of chemical treatment, number of collection days, and DBH;

T:D:CV is the fixed interaction effect of chemical treatment, DBH and crown volume;

S is the random effect of site; S:T is the random interaction effect of site and chemical treatment; and e is the random error.

A one-way analysis of variance (ANOVA) was used to compare the mean oleoresin yields across sites, stand ages, chemical inducers, pine straw management,

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and tree size, using the JMP software from SAS (SAS Institute, 2016). Tukey’s studentized range (HSD) test was used to test for significant differences among treatment means at an α-level of 0.05. The non-linear relationship between tree DBH

(cm) and oleoresin yield (kg) was modelled using the JMP software from SAS (SAS

Institute, 2016). A p-value, which calculates the probability of an equal or greater than the actual results when the null hypothesis is true, was also calculated for each model.

Results

General Summary of Oleoresin Yield

The complete general linear model (GLM) analysis with covariates and an error effect by site showed significant main effects for chemical treatment, number of collection days, DBH, and crown volume (p-values <0.0001, <0.0001, <0.0001, 0.02, respectively) (Table 3-3). Age did not significantly affect oleoresin yield. The GLM analysis with covariates also detected significant two-way interactions between chemical treatment and number of collection days, DBH, and crown volume (p-values

<0.0001, 0.049, 0.009, respectively), and between DBH and crown volume on oleoresin yield (p-value <0.0001) (Table 3-3). Significant three-way interactions among chemical treatment, number of collection days, and DBH, as well as among chemical treatment,

DBH, and crown volume were observed (p-values <0.0001, and 0.02, respectively)

(Table 3-3).

The individual effects of chemical treatment, number of collection days, DBH, age, crown volume, and site on total tree oleoresin yield were fitted for each site using a general linear model without covariates. When comparing by sites, chemical treatment and tree size (DBH) were significantly correlated with oleoresin yield (Table 3-4). For all

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sites, chemical treatment significantly affected the yield of oleoresin (p-values all

<0.0001) (Table 3-4). Apart from the Alachua 2 site (p-value 0.13), DBH had a significant effect on yield (p-values all <0.0001) (Table 3-4). Crown volume was significant only at four of the eight sites: Alachua 2, Union 1, Union 2, and Bradford 1 sites (p-values <0.0001, 0.02, <0.0001, and 0.04, respectively) (Table 3-4).

For all stands, chemical treatment had a highly significant effect on yield (p- values all <0.0001) (Table 3-5). Apart from the 2013 Alachua 2 stand and the 2014

Bradford 1 stand (p-values 0.13 and 0.10, respectively), DBH was significant for all stands (Table 3-5). In this analysis, except for two stands, stand was confounded by collection day. This occurred because during the 2013 tapping season at the Alachua 1 and Alachua 2 stands, the collection day for treatments were around 70 days while others were around 85 days. The number collection days was significant in 2013 for the

Alachua 1 stand but not the Alachua 2 stand (p-values <0.0001 and 0.582, respectively)

(Table 3-5). Crown volume was significant at the 2013 Alachua 2, 2013 Union 1, 2014

Union 2, and 2015 Bradford 1 stands (p-values <0.0001, 0.01, <0.0001, and 0.01, respectively) (Table 3-5).

When comparing oleoresin yield by chemical treatment, site and tree size (DBH) had the most significant effect (Table 3-6). For all chemical treatments, DBH significantly affected the yield of oleoresin (p-values all <0.0001) (Table 3-6). Only for the iron sulfate combined with methyl jasmonate chemical treatment was site not significant (p-value 0.11) (Table 3-6). In the control, methyl jasmonate with in-tree injection, and ethephon treatments, number of collection days had a significant effect on yield (p-values al <0.0001) (Table 3-6). Finally, crown volume was only a significant

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effect in the control and ethephon treatments (p-value 0.001 and 0.04, respectively)

(Table 3-6).

Because the length of the tapping season for certain stands varied widely, oleoresin yield normalized to the number of collection days was analyzed. Chemical treatment and DBH were once again the most significant effects (Table 3-7). Chemical treatment was highly significant among all collection days apart from 88 days and 90 days (p-values all <0.0001) (Table 3-7). In this analysis, except for 72 days, stand was confounded with collection days. DBH was highly significant across all collection days, except for 72, 73, 88, 90, 147 days (p-values 0.05, 0.69, 0.63, 0.05, and 0.10, respectively) (Table 3-7). Crown volume was only significant at collection days 69, 72,

73, and 130 (p-values 0.01, <0.0001, 0.004, and <0.0001, respectively) (Table 3-7).

Stand Age

Comparison of oleoresin yield across stand ages during the three tapping seasons indicated an increase in overall tree yield with increasing age (Table 3-8;

Figure 3-3). Oleoresin yield also depended on the number of collection days. The oleoresin yield per collection day was estimated and compared across all ages. The yield per day decreased with age, apart from two age groups that had significantly lower yield (15 years and 22 years) (Table 3-9). Furthermore, the oleoresin yield per day was analyzed by tapping season. In 2013 and 2015, the oleoresin yield per day for trees aged 14/22 and 16/23, respectively, were not significantly different from one another

(Table 3-10). In contrast to years 2013 and 2015, the average oleoresin yield per day during the 2014 tapping season was lower (Table 3-10).

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Collection Days

The number of days oleoresin was collected strongly impacted the final yield

(Table 3-8). Maximum oleoresin yields were not achieved at 60 or 90 days as total yield was significantly higher after more than 110 or more days.

Chemical Stimulants

Chemical stimulants were very effective at increasing the flow of oleoresin in slash pines. Trees treated with chemical stimulants had a significantly greater oleoresin yield compared to those treated with the control solution (Table 3-11; Figure 3-4; Figure

3-5). The trees treated with methyl jasmonate alone or combined with ethephon or iron sulfate, yielded significantly more oleoresin (approximately 200 g more per tree) compared to those treated with ethephon alone (Table 3-11; Figure 3-4).

Across sites of varying ages and tapping seasons, methyl jasmonate was consistently the most effective chemical stimulant. The methyl jasmonate treatment alone generally resulted in significantly higher oleoresin yields compared to the combined methyl jasmonate and ethephon or iron sulfate treatments, except for a few sites (Tables A1-A15). At the Alachua 3 site tapped in 2014, the iron sulfate mixed with methyl jasmonate chemical stimulant treatment produced a significantly greater oleoresin yield compared to methyl jasmonate alone (approximately 902 g versus 642 g per tree) (Tables A1-A15). At the 2014 Alachua 3 site, the methyl jasmonate treated trees produced less oleoresin compared to the ethephon treatment (642 g versus 758 g per tree), though not significantly different (Tables A1-A15). During the 2015 tapping season, the methyl jasmonate treatment combined with ethephon produced significantly more oleoresin compared to the methyl jasmonate alone (959 g versus 490 g) (Tables

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A1-A15). In 2015, the methyl jasmonate treatment did not produce significantly more oleoresin compared to the ethephon treatment, however, it was significantly more effective than the control treatment (Tables A1-A15).

During the 2015 tapping season, methyl jasmonate did not perform well at stimulating oleoresin yield in the Alachua 4 site. Also, during the 2014 tapping season, methyl jasmonate was not an effective chemical stimulant at the Union 1 site. In the

Alachua 4 and Union 1 sites, the methyl jasmonate treatment yielded the least amount of oleoresin (383 g and 643 g, respectively) compared to all treatments, including the control (Tables A1-A15). In these situations, there may have been some level of human error in the field and the chemical stimulant may not have been properly applied.

Effects of in-tree injection. During the 2014 and 2015 tapping seasons, trees were injected with chemical stimulants a second time using an in-tree injector to test for the effect on resin production. In 2014 the injections took place a month after drilling the boreholes, while in 2015 the injections occurred two weeks prior to drilling the boreholes. The in-tree injection method did not significantly increase oleoresin production (Tables B1-B12). In many cases, the in-tree injection was detrimental to production and trees treated with this treatment produced less overall oleoresin than those that were not injected (Tables B1-B12). The Union 1 site during the 2014 tapping season benefitted from the in-tree injection with the ethephon and methyl jasmonate combined with iron sulfate injection treatments producing significantly more oleoresin compared to all other treatments (Tables B1-B12).

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Tree Size

Tree size had a positive impact on total resin yields per tree. The relationship between DBH (cm) and total oleoresin yield (kg) was modeled using a nonlinear regression (Figure 3-6). This nonlinear regression model explained 38.8% of the variation of oleoresin yield with tree size (r2 = 0.388) (Figure 3-6). The equation for the nonlinear regression model is as followed:

Y = 1.120 × (1 - 2.119 × e-0.085 D) where Y equals the estimated yield per tree and D is the DBH (cm) of the tapped tree.

Stand Management

The effects of thinning and pine straw raking as stand management techniques on oleoresin yields were also evaluated. In both the 2014 and 2015 tapping seasons, the stand managed for pine straw, in addition to timber, had significantly greater resin yield compared to comparable stands only managed for timber (Figure 3-7). The total oleoresin yield per tree was analyzed by chemical stimulant in relation to pine straw management. The ethephon stimulant promoted yield in stands managed for pine straw raking and was not significantly different from the control treatment in the stands not managed for pine straw (Figure 3-8A). The methyl jasmonate and methyl jasmonate combination treatments all increased oleoresin yield at both pine straw and non-pine straw sites; increasing the average yield by about 200 to 300 g per tree (Figure 3-8A).

Surprisingly, for this study, thinning was not found to have a positive effect on the overall yield of oleoresin across tapping sites. In the 2013 tapping season, unthinned and thinned sites were not significantly different (Figure 3-7). During both the 2014 and

2015 tapping seasons, thinned sites yielded significantly less oleoresin compared to

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unthinned sites (Figure 3-7). The only chemical stimulant that showed a difference in effectiveness between thinned and not thinned sites was the methyl jasmonate and iron sulfate combination treatment, which was more effective in thinned sites (Figure 3-8B).

Tapping Area

The tapping intensity for each tree was calculated based on the tree basal area and the area of the sector tapped. The linear relationship between the tapping intensity and total tree oleoresin yield (kg) was modeled and has a slope of –0.0163 [Yield =

1.164 – 0.0163 x (Tapping Intensity), r2 = 0.388; p-value = <0.0001] (Figure 3-9).

The tapping sector area was estimated for each tree as described in the methods section and the total oleoresin yield in relation to tapping area was analyzed. The overall yield by sector area decreased as the tapping intensity increased (Figure 3-10).

The linear relationship between the tapping intensity and yield per sector area (g/cm2) modeled has a slope of –0.152 [Yield = 14.306 – 0.152(Tapping Intensity), r2 = 0.222; p- value = <0.0001] (Figure 3-10).

The tapping borehole area was estimated for each tree based on the predicted hole of 10.16 cm in depth and 2.54 cm in diameter. The oleoresin yield in relation to the area of the borehole by tapping intensity was analyzed. Similar to sector area calculations, the overall yield by hole area decreased as the tapping intensity increased

(Figure 3-11). The relationship between the tapping intensity and yield per hole area

(g/cm2) was modeled as a linear function and has a slope of –0.631 [Yield = 45.120 –

0.631 x (Tapping Intensity), r2 = 0.388, p-value = <0.0001] (Figure 3-11). Overall, oleoresin yield per borehole area and per sector area is inversely related to tapping intensities.

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Discussion

Assessing the effects of chemical inducers, tree morphology and site characteristics on the yield of oleoresin in slash pine is important to evaluate the potential for the reinvigoration of the oleoresin tapping industry in the southern U.S. The borehole tapping method used in this study has been used in other studies within the

U.S. (Hodges, 1995; Hodges, 2000), and has also been used in India (Lekha, 2002).

Compared with previous reports, this study collected oleoresin from younger trees (from

11 to 23 years), which would allow oleoresin to be collected prior to typical final stand harvest for timber products in North Florida.

Oleoresin yield using the short-term tapping method (Knebel et al., 2008) and the

Chinese tapping method, described in Chapter 2 (Wang et al., 2006) was positively correlated with stand age. In this study although we observed a general increase in oleoresin yield with tree age, when accounting for the number of collection days, stand age was not a significant variable with oleoresin yield (Table 3-3). One explanation for age not being significant is that the tapped trees were in a narrow age range (15-23 years) and based on cambial age changes in chemical and mechanical wood properties of loblolly pine all trees are making mature wood. Thus, tree size rather than age is correlated with yield.

Tree size, more specifically DBH was positively correlated with oleoresin yield, where the overall trend was increased oleoresin yield in larger diameter trees. The trees in the larger diameter classes yielded about twice the quantity of oleoresin compared to trees in smaller diameter classes. These results are similar to those reported for older trees by Hodges (1995), Tadesse et al. (2001), and Hadiyane et al. (2015).

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In North Florida with the borehole tapping system, chemical stimulants were the most effective method for increasing oleoresin yields in slash pine trees. Across all sites, all ages, and all tapping years, methyl jasmonate was consistently the most effective chemical stimulant, increasing yields on average by 0.3 kg per tree. It has been reported that methyl jasmonate induces new traumatic resin canal formation and increases wood terpene content (Franceschi et al., 2002; Hudgins et al., 2003; Martin et al., 2003; Hudgins et al., 2004). Methyl jasmonate has also been found to increase monoterpene levels in the stem (Huber et al., 2005) which, in turn, reduces viscosity and crystallization rate allowing oleoresin to continue flowing (Hodges, 1995). The yields at all other sites during the three tapping years showed that methyl jasmonate increased oleoresin yields greater than the other chemical stimulants tested; therefore, we believe that the lack of effect at the 2014 Union 1 and Alachua 3 sites and 2015

Alachua 4 and Bradford 1 sites (Table 3-2), is likely due to human error in the application of the chemical. The results show that to sustainably collect oleoresin from pine trees in a commercial operation, it is crucial to apply stimulant to the trees after wounding.

The additional in-tree injection treatment was done to provide more chemical stimulant, both before or after tapping, with the hypothesis that this would promote oleoresin yields. In-tree injection did not significantly affect yield of oleoresin. In some cases, this added treatment was detrimental to yields. The in-tree injection may have a negative effect on oleoresin yields because creating an extra wound site, no matter how small, may draw oleoresin production away from the collection site. To stimulate an

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increase of oleoresin flow from an already tapped collection site, it may be more useful to either increase the size of the wounding site by re-drilling a slightly larger hole or re- applying the chemical stimulant as tested by Lekha (2002). This, however, would be very time-consuming and may not be cost-effective in the long run, especially in the

U.S. where the cost of labor is high.

Stands managed for pine straw raking had significantly greater oleoresin yields compared to stands managed solely for timber. We also found that the stands managed for pine straw raking showed a significant positive effect of ethephon as a stimulant.

These greater yields may be a result of the more intensive management of understory competition and/or the more intensive fertilizer application. Knebel et al. (2008) observed two to four times greater oleoresin flow of young Pinus taeda in North

Carolina, U.S. from trees that were fertilized compared to unfertilized. However, other studies did not find a positive impact on oleoresin yields due to fertilization (Lombardero et al., 2000; Wei et al., 2004; Klepzig et al., 2005). Moreover, the lack of nutrient availability due to overcrowding in a stand can negatively impact the yield of oleoresin

(Lorio, 1986). Thus, the higher yields of oleoresin observed in the pine straw raking site may be due to the decrease in understory competition from more active management.

This also supports the idea that managing stands in the Southern U.S. for both timber and non-timber products by collecting pine straw and oleoresin in live trees prior to harvesting timber could lead to greater value for landowners (Susaeta et al., 2014). The soil nutrient levels were not tested at any of our sites, so we cannot determine whether soil nutrient deficiencies had a negative impact on oleoresin yields.

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With the bark streak method, Mason (1971) found a negative effect of stand density on the yield of oleoresin. Overall stand productivity is improved by managing the stand density using various silvicultural techniques such as thinning (Reineke, 1933;

Mason, 1971; Jokela, 2004; Wallin et al., 2004; Zhang et al., 2006). We hypothesized that trees with larger crown volume should produce more oleoresin. Decreasing stand density reduces competition among trees and promotes growth by increasing tree crown size and leaf area. We measured crown volume and found that in the overall analysis it was significantly correlated with oleoresin yield (Table 3-3). However, crown volume was only significant at three of the 15 stands and only in one year at two of the sites which were tapped for multiple years (Table 3-5). Our results did not show a positive effect of thinning on the overall yield of oleoresin. One explanation for no effect is that thinned and unthinned stands at different locations we compared and the DBH of the trees tapped within each stand were similar. We did not calculate the stand density at each site; future studies evaluating the impacts of stand density on oleoresin yield would be valuable.

Total tree oleoresin yield in a collection season was higher for trees tapped at lower intensities. Furthermore, sector area and hole area yields decreased as the tapping intensity increased. Hodges (1995) also reported similar results with the negative impact of increased tapping intensities on oleoresin yields per unit tree basal area. This suggests that it would be more beneficial to select larger diameter trees for tapping slash pine for oleoresin.

While oleoresin yields from trees using the borehole tapping method vary considerably, it is possible to predict potential yields from a stand. DBH was the

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strongest predictor variable for oleoresin yields across all sites, stands, chemical inducers, and number of collection days. Chemical treatment also had a significant impact on yields and was the most effective method of increasing production within a stand. In the full general linear model analysis, a positive significant effect of chemical treatment, collection days, DBH, and crown volume on oleoresin yields were observed.

This shows that to increase production in slash pine trees chemical stimulants should be applied to the wounding site, the collection season should last for as long as possible, and trees with larger stem diameters and crowns are favorable.

Summary and Conclusions

The objectives of this study were to test the effects of chemical stimulants, tree size, stand age, and stand management on the yield of oleoresin in slash pine trees.

Our results suggest a general positive effect of DBH on the yield of oleoresin. Methyl jasmonate, whether alone or applied with another stimulant, was the most effective at stimulating and increasing the yields of oleoresin within a tree. Our results showed that yields averaged 1.0 to 1.5 kg of oleoresin per tree from young slash pine stands aged between 11 and 22 years using the standard borehole tapping method and applying methyl jasmonate as a stimulant. The number of days between oleoresin tapping and final collection has a significant effect on the final season yields and thus it is recommended to allow oleoresin flow for at least 120 days. Future studies could evaluate the impact of soil nutrient availability on oleoresin yields in North Florida. The soils in southern U.S. tend to be nutrient poor and thus require fertilization, so there may be some inherent limitations to oleoresin production due to lack of site resources.

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Table 3-1. Summary of treatments for oleoresin tapping during the 2013 to 2015 field study. Age Pine Straw Thinning Inducers Inducer Application Total # 11 N N Control MeJ Eth M+E Whole Tree Base 320 15 Y N Control MeJ Eth M+E Whole Tree Base 320 15 N Y Control MeJ Eth M+E Whole Tree Base 320 15 N N Control MeJ Eth M+E Whole Tree Base 320 22 N Y Control MeJ Eth M+E Whole Tree Base 320 22 N N Control MeJ Eth M+E Whole Tree Base 320

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Table 3-2. Summary of sites selected for oleoresin tapping during the 2013 to 2015 field study. Fall 2013 Stand Site Mean Mean Age Thinning Management Site Index Soil Series DBH (cm) Height (m) 14 Not Thinned No Pine Straw Union 1 76 Mascotte Sand 18.6 17.2 16 Thinned No Pine Straw Alachua 1 76 Newnan/Wauchula/Ponoma Sand 19.9 17.8 22 Thinned No Pine Straw Alachua 2 63 Newnan Sand 21.6 18.1 Summer 2014 Stand Site Mean Mean Age Thinning Management Site Index Soil Series DBH (cm) Height (m) 11 Not Thinned No Pine Straw Bradford 1 70 Sapello Sand 17.3 12.2 15 Not Thinned No Pine Straw Union 1 76 Mascotte Sand 19.2 16.3 15 Not Thinned Pine Straw Union 2 NA Mascotte Sand 19.6 17.0 15 Thinned No Pine Straw Alachua 3 84 Ponoma Sand 21.3 17.7 22 Not Thinned No Pine Straw Alachua 4 90 Newnan Sand 20.6 17.0 22 Thinned No Pine Straw Alachua 5 64 Ponoma Sand 22.1 18.7 Summer 2015 Stand Site Mean Mean Age Thinning Management Site Index Soil Series DBH (cm) Height (m) 12 Not Thinned No Pine Straw Bradford 1 70 Sapello Sand 17.4 12.9 16 Not Thinned No Pine Straw Union 1 76 Mascotte Sand 18.0 18.0 16 Not Thinned Pine Straw Union 2 NA Mascotte Sand 19.5 18.0 16 Thinned No Pine Straw Alachua 3 84 Ponoma Sand 21.9 18.1 23 Not Thinned No Pine Straw Alachua 4 90 Newnan Sand 22.1 18.8 23 Thinned No Pine Straw Alachua 5 64 Ponoma Sand 20.1 17.8

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Table 3-3. Summary of main and interactive effects on oleoresin yield in sites using the standard borehole tapping method between 2013 to 2015 based on a general linear model with covariates. Effect DF Den DF p-value Treatment 9 32.8 <0.001** Collection 1 236.9 <0.001** DBH 1 4232.3 <0.001** Age 1 10.0 0.850 Crown 1 3791.9 0.020* Treatment:Collection 9 156.1 <0.001** Treatment:DBH 9 4136.3 0.049* Treatment:Age 9 39.8 0.100 Treatment:Crown 9 3664.7 0.009** Collection:DBH 1 3854.5 0.940 Collection:Age 1 2139.9 0.320 Collection:Crown 1 3792.3 0.140 DBH:Age 1 3061.1 0.800 DBH:Crown 1 2410.6 <0.001** Age:Crown 1 2960.9 0.420 Treatment:Collection:DBH 9 3425.0 <0.001** Treatment:DBH:Crown 9 3384.4 0.020* Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table 3-4. Summary of main effects F-statistic and p-values on oleoresin yield by site using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. Site Chemical Treatment DBH Age Collection Days Crown Volume Alachua 1 75.26 (<0.001**) 44.84 (<0.001**) NA 14.08 (<0.001**) 0.40 (0.530) Alachua 2 61.70 (<0.001**) 26.94 (0.127) NA 0.54 (0.582) 12.15 (<0.001**) Alachua 3 18.68 (<0.001**) 73.15 (<0.001**) 0.64 (0.42) NA 0.28 (0.600) Alachua 4 4.71 (<0.001**) 57.25 (<0.001**) 300.60 (<0.001**) NA 0.56 (0.460) Alachua 5 36.45 (<0.001**) 112.20 (<0.001**) 256.90 (<0.001**) NA 0.00 (0.100) Union 1 18.60 (<0.001**) 121.40 (<0.001**) 18.86 (0.070) 52.44 (<0.001**) 5.81 (0.020*) Union 2 22.74 (<0.001**) 57.72 (<0.001**) 89.69 (<0.001**) NA 15.12 (<0.001**) Bradford 1 25.02 (<0.001**) 13.34 (<0.001**) 103.00 (<0.001**) NA 4.33 (0.040*) Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table 3-5. Summary of main effects F-statistic and p-values on oleoresin yield by stand using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. Stand Chemical Treatment DBH Collection Days Crown Volume 2013 Alachua 1 75.26 (<0.001**) 44.84 (<0.001**) 14.08 (<0.001**) 0.40 (0.530) 2013 Alachua 2 61.70 (<0.001**) 26.94 (0.130) 0.54 (0.582) 12.15 (<0.001**) 2013 Union 1 122.70 (<0.001**) 31.40 (0.040*) NA 6.72 (0.010*) 2014 Alachua 3 16.72 (<0.001**) 47.52 (<0.001**) NA 0.08 (0.780) 2014 Alachua 4 4.26 (<0.001**) 58.39 (<0.001**) NA 0.66 (0.420) 2014 Alachua 5 14.35 (<0.001**) 76.19 (<0.001**) NA 3.40 (0.070) 2014 Union 1 5.38 (<0.001**) 23.76 (0.030*) NA 2.46 (0.120) 2014 Union 2 18.25 (<0.001**) 38.42 (0.007**) NA 11.18 (<0.001**) 2014 Bradford 1 38.79 (<0.001**) 2.95 (0.100) NA 0.17 (0.680) 2015 Alachua 3 28.24 (<0.001**) 51.33 (<0.001**) NA 0.02 (0.890) 2015 Alachua 4 11.78 (<0.001**) 104.90 (<0.001**) NA 0.61 (0.440) 2015 Alachua 5 50.63 (<0.001**) 67.93 (<0.001**) NA 3.29 (0.070) 2015 Union 1 8.22 (<0.001**) 102.20 (<0.001**) NA 1.25 (0.260) 2015 Union 2 15.86 (<0.001**) 25.35 (0.001**) NA 2.26 (0.130) 2015 Bradford 1 33.48 (<0.001**) 28.50 (<0.001**) NA 6.08 (0.010*) Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table 3-6. Summary of main effects F-statistic and p-values on oleoresin yield by chemical treatment using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. Treatment Site DBH Collection Days Crown Volume Control 11.22 (<0.001**) 102.40 (<0.001**) 88.10 (<0.001**) 10.19 (0.001**) Control/Whole 14.71 (<0.001**) 67.17 (<0.001**) 1.69 (0.180) 0.25 (0.610) MeJa 16.46 (<0.001**) 45.05 (<0.001**) 0.88 (0.420) 2.61 (0.110) MeJa/Whole 15.92 (<0.001**) 25.67 (0.001**) 82.86 (<0.001**) 2.14 (0.140) Ethephon 22.32 (<0.001**) 91.23 (<0.001**) 100.90 (<0.001**) 4.23 (0.040*) Ethephon/Whole 14.81 (<0.001**) 52.62 (<0.001**) 0.24 (0.610) 1.20 (0.270) MeJaEthephon 6.02 (<0.001**) 79.10 (<0.001**) 1.56 (0.190) 2.31 (0.130) MeJaEthephon/Whole 4.03 (<0.001**) 44.10 (<0.001**) NA 1.49 (0.220) FeSMeJa 10.60 (0.002**) 26.66 (<0.001**) NA 0.05 (0.830) FeSMeJa/Whole 3.32 (0.110) 30.03 (<0.001**) NA 1.06 (0.300) Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table 3-7. Summary of main effects F-statistic and p-values on oleoresin yields by collection days drilled using the standard borehole tapping method between 2013 to 2015 based on a general linear model without covariates. Collection Days Treatment DBH Stand Crown Volume 57 8.22 (<0.001**) 102.20 (<0.001**) NA 1.25 (0.260) 63 15.86 (<0.001**) 25.35 (0.001**) NA 2.26 (0.130) 68 50.63 (<0.001**) 67.93 (<0.001**) NA 3.29 (0.070) 69 33.48 (<0.001**) 28.50 (<0.001**) NA 6.08 (0.010*) 71 28.24 (<0.001**) 51.33 (<0.001**) NA 0.02 (0.890) 72 52.79 (<0.001**) 43.35 (0.050) 4.59 (0.030*) 18.81 (<0.001**) 73 215.40 (<0.001**) 15.74 (0.690) NA 8.22 (0.004**) 76 11.78 (<0.001**) 104.90 (<0.001**) NA 0.61 (0.440) 85 31.52 (<0.001**) 27.98 (<0.001**) NA 0.01 (0.920) 86 3.73 (<0.008**) 23.39 (<0.001**) NA 1.81 (0.180) 88 0.00 (0.440) 0.85 (0.630) NA 3.47 (0.080) 90 1.12 (0.350) 3.03 (0.050) NA 0.97 (0.330) 128 5.38 (<0.001**) 23.76 (0.030*) NA 2.46 (0.120) 130 18.25 (<0.001**) 38.42 (0.007**) NA 11.18 (<0.001**) 133 16.72 (<0.001**) 47.52 (<0.001**) NA 0.08 (0.780) 140 4.26 (<0.001**) 58.39 (<0.001**) NA 0.66 (0.420) 147 38.79 (<0.001**) 2.95 (0.100) NA 0.17 (0.680) Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table 3-8. Summary of oleoresin yields by stand age from tapping slash pine using the borehole tapping method. Trees were tapped between summer and early fall of 2013-2015. Stand Age Number of Trees Mean Collection Mean DBH Mean Tree SE Tree CV (years) Tapped Days (cm) Yield (kg) Yield (kg) (%) 11 320 147 17.26 0.691b 0.021 55.03 12 304 69 17.40 0.528c 0.023 76.96 14 318 73 18.63 0.660b 0.018 47.54 15 949 130 20.02 0.792a 0.014 54.63 16 1247 69 20.02 0.647b 0.011 59.62 22 909 113 21.49 0.811a 0.015 55.80 23 624 72 21.13 0.699b 0.019 69.30 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table 3-9. Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015. Age (years) Mean Yield Per Day (g/day) SE (g/day) CV (%) 11 4.699d 0.14 55.03 12 7.657b 0.34 76.96 14 9.108a 0.24 47.48 15 6.084c 0.11 54.80 16 9.509a 0.16 59.63 22 7.492b 0.15 61.35 23 9.863a 0.29 72.70 Note: The ages with different letter superscripts were significantly different from Tukey’s HSD test (p-value < 0.05)

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Table 3-10. Summary of oleoresin yields per collection day by age from tapping slash pine trees using the borehole tapping method. The trees were tapped between summer and early fall 2013-2015. Tapping Year Age (years) Mean Yield (g) SE (g) CV (%) 2013 14 9.108a 0.24 47.48 2013 16 8.009b 0.27 59.00 2013 22 8.957ab 0.34 66.84 2014 11 4.699c 0.15 55.03 2014 15 6.084b 0.11 54.80 2014 22 6.711a 0.14 50.69 2015 12 7.657b 0.34 79.96 2015 16 10.01a 0.19 58.64 2015 23 9.863a 0.29 72.70 Note: The ages with different significance level letters within a tapping season were significantly different based on Tukey’s HSD test (p-value < 0.05)

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Table 3-11. Summary of oleoresin yields by chemical treatment from tapping slash pine using the borehole tapping method. Trees were tapped between summer and early fall of 2013-2015. Chemical stimulants tested include ethephon, Methyl jasmonate (MeJa), iron sulfate mixed with methyl jasmonate (FeSMeJa), and Methyl jasmonate mixed with ethephon (MeJaEthephon). Chemical Treatment Number of Trees Tapped Mean Yield (kg) SE (kg) CV (%) Control (no chemical) 1153 0.493d 0.0083 56.86 Ethephon 1173 0.611c 0.0099 55.46 FeSMeJa 467 0.860ab 0.0188 47.30 MeJa 1182 0.896a 0.0148 56.66 MejaEthephon 697 0.830b 0.0158 50.19 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 3-1. Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH greater than 10.16 cm. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, and bw represents the borehole width. The tapping area is the triangle c-y-x

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Figure 3-2. Calculations for the cross-sectional tapping area and individual hole area model for the trees with DBH less than 10.16 cm. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, bw represents the borehole width, and the shaded area is the tapping area.

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11/12 Years 14/15 Years 16 Years 22/23 Years 1 c b 0.8 a a a a c b 0.6 a

0.4 Total Yield (kg) Yield Total

0.2

0 2013 2014 2015 Tapping Year Figure 3-3. Age effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons.

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Figure 3-4. Chemical effect on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 3-5. Chemical effects of oleoresin yield (g) per day with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 3-6. Nonlinear regression displaying the actual relationship between average oleoresin yield (kg) in slash pine and DBH in cm for all trees tapped in the 2013 to 2015 tapping season.

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Figure 3-7. Effect of pine straw management and thinning on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 3-8. Chemical effect on oleoresin yield (kg) when tapping slash pine trees in North Florida during the 2013 to 2015 field seasons under different management scenarios. A) Effect of managing stands for pine straw raking, B) Effect of thinning.

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Figure 3-9. Bivariate fit of total tree yield of oleoresin (kg) in slash pine by tapping intensity. The r2 for the linear relationship between tapping intensity and average total tree yield is 0.388 (p-value <0.0001).

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Figure 3-10. Bivariate fit of sector area yield of oleoresin in slash pine by tapping intensity. The r2 for the linear relationship between tapping intensity and average yield per sector area is 0.22 (p-value <0.0001).

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Figure 3-11. Bivariate fit of hole area yield of oleoresin in slash pine by tapping intensity. The r2 for the linear relationship between tapping intensity and average yield per hole area is 0.39 (p-value <0.0001).

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CHAPTER 4 CHEMICAL STIMULANT DOSAGE AND CARRIER SOLVENTS IN THE BOREHOLE METHOD TO INCREASE OLEORESIN YIELD IN SLASH PINE

Introduction

With the desire for increased energy security and to mitigate global warming, the

U.S. demand for alternatives to petroleum based fuel is high. Using woody biomass as biofuel feedstocks can help increase the value of timber land in the southern U.S.

Chapter 2 reviewed global and U.S. demand for pine terpenes and the established market for pine chemicals. Terpene extraction from slash pine trees can help meet the market demands for biofuel, jet fuel, and strengthen energy security, providing an alternative to petroleum (Barranx et al., 2002). Currently, in the U.S. the pulping processes extract hemicelluloses from conifers which can be fermented to produce cellulosic ethanol (Nesbit et al., 2011). In their study, Nesbit et al. (2011) concluded that the most profitable scenario for non-industrial forest landowners in the southern U.S. was the production of traditional timber products with the collection of harvest residues to produce biofuels. While this form of ethanol production is not yet cost-competitive with traditional corn-based ethanol, it will become more competitive as the technology develops and improves (Nesbit et al. 2011). However, the technique of removing biomass residues on site can lead to diminishing growth yields overtime due to the removal of soil nutrients (Eisenbies et al., 2009; Nesbit et al. 2011). The nutrients in the soil can be replaced by increasing fertilization rates from 45% to 60% in certain sites

(Eisenbies et al., 2009). On the other hand, with the oleoresin tapping technique considered in this study, pine terpenes can be extracted directly from live trees without the removal of residual biomass. This technique also allows for traditional timber harvest in conjunction with oleoresin collection.

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Oleoresin is currently collected from live trees in various countries using primarily a method of tapping involving the removal of streak of bark. Most resin is collected in countries with low cost labor and use methods where laborers visit the tree multiple times during a tapping season. These methods are not economically feasible in the U.S. due to high labor cost, even though the southern U.S. has extensive planted and natural slash pine forests available. The borehole tapping method is the most attractive oleoresin production method for use in the U.S. (Hodges, 1995; Hodges 2000).

However, to commercialize production of oleoresin in the U.S. and be competitive global producers, it is crucial to increase the yield of oleoresin per individual tree.

Terpene production in conifers has been found to increase significantly with the application of chemical stimulants. Martin et al. (2003) studied the effects of spraying methyl jasmonate on the terpene formation in needles of Norway spruce (Picea abies

Karst.) saplings. Without wounding the saplings, Martin et al. (2003) observed a 2-fold increase in terpene accumulation and a 5-fold increase in terpene emission from the foliage. Past studies have determined that the increase in terpene production in the stem after the application of methyl jasmonate was due to the formation of new traumatic axial resin canals (Franceschi et al., 2002; Martin et al., 2003; Hudgins et al.,

2004). However, limited research has explored the dynamic between chemical dosage of methyl jasmonate and oleoresin yields in slash pine (Pinus elliottii Engelm. Var. elliottii) trees.

The primary goal of this research is to develop optimal and sustainable methods for increasing oleoresin yields from live slash pine trees in the southern U.S. In Chapter

3 the yield of oleoresin was compared with various chemical stimulants, stand

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management techniques, and stand age, and assessed relationships between yield and various tree phenotypic characteristics. Here, chemical concentrations and stimulant solvents were investigated to identify methods to improve oleoresin yield per individual tree. Because methyl jasmonate was the most effective chemical at stimulating oleoresin yield and production in slash pine (Chapter 3), we focused on this chemical.

Therefore, the objectives of this study are: 1) to determine which concentration of methyl jasmonate and, 2) to identify which carrier solvent is most effective to increase oleoresin yield.

Methods

Study Areas

The same thinned slash pine stand in Alachua county described in Chapter 3

(Alachua 3) was used for the dosage carrier solvent experiments. This site was 15 years old in 2014 and 17 years old in 2016, is located just outside of Gainesville, Florida

(29°46’N latitude and 82°18’W longitude) at an elevation 51 meters from average sea level. This stand was managed using conventional silvicultural practices including bedding, weed control, and fertilizer treatments. Trees with prominent physical signs and symptoms of diseases such as fusiform rust (Cronartium fusiforme Hedgcock &

Hunt ex Cummins), pitch canker (Fusarium circinatum Nirenberg & O’Donnell), bark beetles, and pitch moth were not selected.

The study site had a humid subtropical climate with hot wet summers and mild dry winters, and the topography was primarily flat with a 1-2% slope. The soils in the study sites ranged from poorly drained to moderately well drained. The understory vegetation was primarily sparse. Understory vegetation included saw palmetto (Serenoa

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repens (B.) Small.), blackberries (Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)), and greenbriers (Smilax L. spp.), among others.

Borehole Tapping

The borehole tapping method, more thoroughly described in Chapter 3, was used to tap living slash pine trees for oleoresin collection. This method involves drilling two boreholes 2.54 cm in diameter 10.16 inches into the stem at a slight upwards angle at the base of the tree using a gas-powered drill. Once the boreholes were drilled, each hole received 2 ml of a chemical treatment using a handheld compression sprayer. The chemical treatments were assigned randomly to the trees in the experiment prior to visiting the field site and each treatment had a sample size of 40 trees. Following the chemical application, a fitting was inserted into the borehole using a mallet to seal it securely and a collection bag was attached and secured using a cable tie. Additional details describing the borehole tapping technique are presented in Chapter 3.

Chemical Stimulants

2015 tapping season

During the 2015 tapping season, a methyl jasmonate dose response experiments was conducted. Methyl jasmonate at 7 concentrations, 0 mM (control), 25 mM, 50 mM,

100 mM, 200 mM, 400 mM, and 600 mM in DI water and Tween 20 was applied. In

2015 a methyl jasmonate and ethephon dose response experiment tested methyl jasmonate and ethephon at 9 concentration combinations: 50 mM methyl jasmonate with 1%, 5% and 10% ethephon; 100 mM methyl jasmonate with 1%, 5% and 10% ethephon, and 400 mM methyl jasmonate with 1%, 5% and 10% ethephon. During the

2015 tapping season, 90% ethanol compared to DI water and Tween 20 as the carrier solvent for methyl jasmonate was tested.

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2016 tapping season

In 2016 another dose response experiment was implemented that tested methyl jasmonate at 5 concentrations, 0 mM (control), 100 mM, 200 mM, 400 mM, and 600 mM diluted with 90% ethanol.

Data Collection

Diameter at breast height (DBH), tree height and crown volume were measured in the carrier solvent experiment. For the 2015 methyl jasmonate dose response test, all the collection bags were weighed every 4 days for the first 40 days prior to final collection. At the end of the tapping season, all bags were weighed using a digital scale.

Additional details explaining data collection techniques used are presented in Chapter

Statistical Analysis

The chemical inducer treatments for each all dose response experimental tests were randomized prior to visiting the field with each treatment was assigned to 40 trees.

A one-way analysis of variance (ANOVA) was used to compare the mean oleoresin yield across treatments for all tests using the JMP software from SAS (SAS Institute,

2016). Tukey’s studentized range (HSD) test was used to test for significant differences among means at an α level of 0.05.

During the 2015 methyl jasmonate dose response experiment, the mass of the oleoresin collection bags was recorded every 4 days for 40 days and once more at day

95. To examine the cumulative flow of oleoresin during a tapping season, a nonlinear regression model was fitted for each chemical stimulant using the JMP software from

SAS (SAS Institute, 2016). The predicted cumulative flow of oleoresin over time during a 95-day tapping season was estimated using the regression model and graphed.

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Lastly, to examine the overall cumulative flow of oleoresin for all 2015 methyl jasmonate dose response treatments, a nonlinear regression model was fitted.

Results

During the 2015 tapping season, a dose response experiment with various ethephon doses (1%, 5%, and 10%) and methyl jasmonate concentrations (50 mM, 100 mM, and 400 mM) was implemented. Results showed that methyl jasmonate was more effective at stimulating oleoresin yields when combined with lower levels of ethephon, except at 100 mM concentration, methyl jasmonate where there were no significant differences between yields (Figure 4-1). Overall, the average oleoresin yields increased as the concentrations of methyl jasmonate increased (Figure 4-1). The 50 mM with 1% ethephon, 100 mM with 1, 5, and 10% ethephon, and the 400 mM with 10% ethephon treatments did not yield significantly different quantities of oleoresin (Figure 4-1). The

400 mM 1% and 5% yielded significantly more oleoresin than all the other treatments, but were not different from one another (Figure 4-1).

As expected, in the 2015 methyl jasmonate dose response test, oleoresin yields increased with methyl jasmonate concentration (Figure 4-2). The final oleoresin yield of the 600 mM methyl jasmonate treatment was close to double the yield (2.3 kg) of 100 mM methyl jasmonate treatment (1.3 kg) (Figure 4-2), which is the standard dose for experiments described earlier in Chapter 3 (Figure 4-2). The 25 mM methyl jasmonate treatment was not effective and did not yield significantly more oleoresin compared to the control treatment (Figure 4-2). The 400 mM and 600 mM methyl jasmonate treatments were not significantly different; however, the 200 mM treatment yielded significantly less oleoresin compared to the 600 mM treatment (Figure 4-2).

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During this study, the weight of the collection bags was measured every 4 days for the initial 40 days and once more at day 95. These data were used to calculate the cumulative flow rate of oleoresin overtime by chemical stimulant. The data was then modeled using a nonlinear function for each chemical stimulant (Figure 4-3). The equations for the nonlinear regression models are listed in Figure 4-3. The nonlinear regression models explained between 97.0% and 99.4% of the variation of oleoresin yield with concentration of methyl jasmonate (control r2 = 0.99; 25 mM r2 = 0.99; 50 mM r2 = 0.99; 100 mM r2 = 0.97; 200 mM r2 = 0.98; 400 mM r2 = 0.97; 600 mM r2 = 0.98)

(Figure 4-3). The cumulative oleoresin flow rate from the control and treatments with 25 mM, 50 mM, and 100 mM methyl jasmonate concentrations slowed at about day 60, yielding between 70 grams and 216 grams during the last 35 days of collection (control

= 70 grams, 25 mM = 149 grams, 50 mM = 140 grams, and 100 mM = 216 grams)

(Figure 4-2; Figure 4-3). The chemical treatments with 200 mM, 400 mM, and 600 mM methyl jasmonate concentrations did not appear to have reached their full oleoresin production capacity at the time of collection, which suggests the tapping season should be greater than 95 days (Figure 4-3).

The data for all chemical treatments in the 2015 methyl jasmonate dose response experiment were used to calculate and plot the cumulative flow of oleoresin and oleoresin flow rate over time since the day of tapping (Figure 4-4). The following nonlinear regression model was obtained:

Y = 1673.058 × (1 - 0.959 × e-0.017 D) where Y is the oleoresin yield (kg) and D corresponds to the collection day. These data were plotted as the percent of full season oleoresin yield and the percent to reach full

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season yield, in this case, the full season yield was based on the 95-day season (Figure

4-4). Based on these calculations, about 50 % of the oleoresin yield was collected by day 30 (Figure 4-4).

Because the previously described methyl jasmonate dose response experiment did not apparently saturate the response, we conducted a second test in 2015 were we compared DI water and Tween 20 and 90% ethanol as a carrier solvent. These results show that methyl jasmonate was significantly more effective when diluted with 90% ethanol as opposed to the combination of DI water and Tween 20 (Table 4-2; Figure 4-

5). The trees treated with the alcohol dilution averaged 1.5 kg, while the trees treated with the DI water and Tween 20 dilution averaged 0.94 kg of oleoresin (Table 4-2;

Figure 4-5). Furthermore, the main effects of tree height and crown volume were not significant (Table 4-2).

During the 2016 tapping season, a methyl jasmonate dose response test diluted in ethanol instead of DI water and Tween 20 was conducted. Similar to the 2015 methyl jasmonate dose response test, we observed a positive effect of increasing chemical concentration on oleoresin yield (Figure 4-6). Trees that received a methyl jasmonate dose of 400 mM yielded close to double the yield of oleoresin (3.0 kg) compared to trees treated with 100 mM (1.65 kg) (Figure 4-6). The 100 mM and 200 mM methyl jasmonate treatments were not significantly different to one another (Figure 4-6). The

400 mM and 600 mM methyl jasmonate treatments were not significantly different to one another; however, the 400 mM treatment yielded more oleoresin (Figure 4-6).

Discussion

The methyl jasmonate and ethephon dose response experiment show a potential negative interaction with the combination of the two chemical stimulants, particularly

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10% ethephon. This negative effect of ethephon when combined with methyl jasmonate was also observed with many of the other experiments discussed in Chapters 3 and 4 where the methyl jasmonate treatment yielded more oleoresin compared to the methyl jasmonate and ethephon combination treatments. Since methyl jasmonate performed well or significantly better when applied alone and ethephon at 1% and 5% did not stimulate oleoresin yield when combined with methyl jasmonate, we conclude that methyl jasmonate is best used alone to stimulate oleoresin flow. This will also lower the cost of tapping as there will be no need to purchase ethephon.

Compared with the DI water and Tween 20, the alcohol and methyl jasmonate solution increased oleoresin yield. In the field, it appeared that methyl jasmonate dissolved more easily in ethanol compared to DI water and Tween 20. The solutions with 100, 200, 400, and 600 mM of methyl jasmonate in DI water had to be mixed throughout the day, while the solutions with all dosages of methyl jasmonate in ethanol did not. This is likely due to increased solubility of the methyl jasmonate in the ethanol compared with the Tween 20/water. Franceschi et al. (2001) and Martin et al. (2003) solubilized methyl jasmonate at concentrations of 100 mM and lower with Tween 20, however, they did not test higher dosages of methyl jasmonate. Ethanol was used to dissolve methyl jasmonate at low concentrations in a study by Mizukami et al. (1993).

Further, methyl jasmonate is freely soluble in 95% ethanol at estimated volumes of 1 to

10 ml of solvent to dissolve 1 g of solute (Bio-World, 2017), while it is very slightly soluble in water at estimated volumes of 1000 ml of solvent to dissolve 0.34 gram of solute (Sigma-Aldrich, 2017).

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Interestingly, the dose response curve with similar concentrations of methyl jasmonate did not saturate with the Tween 20/water (Figure 4-2) whereas it did saturate with the ethanol solvent, suggesting a more uniform response with ethanol (Figure 4-6).

It is also possible that ethanol carries the methyl jasmonate better into the wood itself to stimulate production of new resin canals, and/or slow oleoresin crystallization at the wound site.

Since ethanol was observed to be a better carrier of methyl jasmonate in 2015, we used a solution of ethanol to apply methyl jasmonate to trees in our 2016 methyl jasmonate dose response treatment. In this study, DBH was the only main tree effect that significantly predicted oleoresin yields. This suggests larger trees tend to be more productive and thus have the potential to produce more oleoresin. This result is also consistent with findings from other oleoresin tapping trials discussed in Chapter 2.

The results from the 2015 and 2016 methyl jasmonate dose response experiments showed increasing the concentration of methyl jasmonate increased oleoresin production. In the 2016 dose response test, the 400 mM and 600 mM methyl jasmonate yielded the same oleoresin amount per tree showing that the response was saturated around 400 mM. Therefore, an additional experiment optimizing the dosage between 200 and 400 mM of methyl jasmonate using the borehole tapping method in a commercial operation would be beneficial. The 2016 experiment highlighted the potential of collecting an average of 3 kg of oleoresin in young live slash pine trees in the southeast U.S., using methyl jasmonate diluted in 90% ethanol as a stimulant.

Based on this study, the optimal treatment for oleoresin collection is drilling two 10.16 cm boreholes at the base of the tree and applying 2 ml of 400 mM methyl jasmonate

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diluted in 90% ethanol. Although Coppen (1995) suggested that to be economically viable, oleoresin yields per tree should be at least 2 kg. Cost sensitivity analyses suggest that the borehole method in the southeast U.S. can be cost effective at yields of

2.5 to 3.0 kg per tree.

Our kinetic data show the importance of the first couple weeks after tapping, when fifty percent of the final oleoresin mass was collected within the first month. Lekha

(2002) increased the yield of oleoresin per tree by re-drilling a slightly larger borehole every month. If we wanted to increase the yield of oleoresin per tree, along with increasing methyl jasmonate concentrations, it may be beneficial to re-drill and re-apply chemical stimulants monthly or at least once after the first month of tapping. However, this may not be cost-effective due to the high labor cost in the U.S.

We conducted a cost analysis based on the yield results from the 2016 ethanol- methyl jasmonate results. For commercial production chemical, labor and equipment costs would have to be considered when determining the optimal tapping treatment

(Hodges and Ferguson, 2011; Table 4-3). The labor and equipment cost would be the same for all chemical stimulant treatments. Based on average productivity rates of 26.7 trees per hour from our study and a labor cost of $8.50 per hour per person, the total cost of labor and equipment for an oleoresin tapping operation would be $1.648 per tree

(Table 4-3). Average oleoresin yield of trees treated with 100 mM of methyl jasmonate was 1.65 kg. The estimated cost per tree of 100 mM methyl jasmonate is $0.28, which would make for a total cost of $1.70 per kg of oleoresin (Table 4-3). Average oleoresin yield of trees treated with 400 mM of methyl jasmonate was 3.00 kg. The estimated cost per tree for 400 mM methyl jasmonate is $1.11, and the total cost per kg of oleoresin is

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$1.21 (Table 4-3). Finally, the estimated cost per tree of 600 mM methyl jasmonate is

$1.66, and the total cost per kg of oleoresin is $1.55 based on average tree yield of 2.7 kg (Table 4-3). Because of the significant increase in oleoresin yield with increasing methyl jasmonate dosage, the most cost-effective chemical stimulant is 400 mM of methyl jasmonate diluted in 90% ethanol.

Summary and Conclusions

This study was designed to test the effects of various concentrations of methyl jasmonate and ethephon on the yield of oleoresin. The goal was to determine the optimal and most effective dose. Our results suggest the application of methyl jasmonate alone increased oleoresin production in younger slash pine trees in the southern U.S. Ethanol was a more efficient carrier solvent of methyl jasmonate compared with a combination of Tween 20 and DI water at concentrations above 100 mM. The optimal chemical stimulant treatment for maximizing oleoresin yields in slash pine is 400 mM of methyl jasmonate diluted in 90% ethanol. Furthermore, since it appears that the trees, based on time series data, had not reached their full oleoresin yield potential at 90-100 days, particularly with the higher doses of methyl jasmonate it is beneficial to allow for 140 days for a full collection season. With 400 mM methyl jasmonate giving an average oleoresin yields of 3.0 kg per tree in 16-year-old slash pine stands in North Florida we estimate that oleoresin can be collected at a cost of $1.21 per kg.

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Table 4-1. Summary of oleoresin tapping dosage and carrier solvent experiments in 2014-2016. Year Site Location Experiment Stand Age Number Number Number (Years) Chemical Trees Boreholes Inducers Per Tree 2014 Gainesville, FL Methyl Jasmonate Dose 15 10 400 2 Response 2014 Gainesville, FL Methyl Jasmonate Dose 15 7 280 2 Response 2015 Gainesville, FL Methyl Jasmonate Dose 16 7 280 2 Response 2015 Gainesville, FL Methyl Jasmonate and 16 9 360 2 Ethephon Dose Response 2015 Gainesville, FL Alcohol 16 2 80 2 2016 Gainesville, FL Methyl Jasmonate Dose 17 6 240 2 Response

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Table 4-2. Effects of methyl jasmonate carrier solvent, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the standard borehole tapping method. Chemical Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg) Average SE Average SE Average SE Average SE Alcohol 22.845a 0.54 20.115a 0.22 47.891a 4.17 1.507a 0.12 Tween 21.873a 0.52 19.594a 0.24 44.064a 3.66 0.936b 0.11 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table 4-3. Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour and applying 400 mM of methyl jasmonate diluted in 90% ethanol. Adapted from Hodges and Ferguson (2011). Quantity Cost per Cost Category / Item Units Unit Price per tree Tree Supplies Spouts: 2.54 x 12.7 cm PVC pipe, or custom molded PE 2 Ea. $0.150 $0.300 Collection bags, Nylon/PE laminate, 6x20 in. 2 Ea. $0.090 $0.180 Cable ties for bag closure 2 Ea. $0.010 $0.020 Methyl jasmonate – 400 mM 2 Dose $0.553 $1.105 Distilled water 2 Dose $0.001 $0.002 Ethanol 2 Dose $0.141 $0.281 Diesel fuel for drill machine and utility vehicle 0.050 Gal. $3.00 $0.150 Gasoline and oil for power drill 0.004 Gal. $4.50 $0.019 Subtotal supplies $2.205 Labor Borehole Treatment/Installation (3-man crew, average 0.163 Hr. $8.50 $1.388 productivity rate) Oleoresin harvesting (3-man crew, average productivity) 0.017 Hr. $8.50 $0.143 Subtotal labor $1.530 Quantity Cost per Equipment per Unit Price Total Cost Tree* crew Off-road utility vehicle (Kubota RTV900XT) 1 $10,000 $10,000 $0.040 Power drill (Sthil BT45) 2 $450 $900 $0.004 Drill bits: 2.54 cm 3 $25 $75 $0.000 Chemical sprayer 2 $100 $200 $0.001 Small tools: mallet, machete, pliers, measuring cup 4 $50 $200 $0.001 Rubber gloves (for chemical mixing and resin handling) 100 $3 $300 $0.001 Note: Equipment costs depreciated over useful life of 250,000 trees; does not include transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080. The cost per tree of 100 mM methyl jasmonate is $0.276; the cost per tree of 600 mM methyl jasmonate is $1.658

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Table 4-3. Continued. Quantity Cost per Equipment per Unit Price Total Cost Tree* crew Fuel can: 2 gal. 2 $15 $30 $0.000 Fuel cans: 15 gal. Buckets: 5 gal. 10 $5 $50 $0.000 Barrels: 55 gal. capacity 50 $30 $1,500 $0.006 Subtotal equipment $11,755 $0.054 Total All Costs $3.642 Predicted average yield per tree at 100 days (Kg) 3.000 Total Cost Per Kg Resin $1.214 Note: Equipment costs depreciated over useful life of 250,000 trees; does not include highway transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080. The cost per tree of 100 mM methyl jasmonate is $0.276; the cost per tree of 600 mM methyl jasmonate is $1.658

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1.8 a 1.6 a ab 1.4 ab ab ab ab 1.2 bc 1

0.8 c

0.6 Oleoresin Yield (kg) Yield Oleoresin 0.4

0.2

0 50 mM 100 mM 400 mM Methyl Jasmonate Concentration

Ethephon Concentration 1% 5% 10%

Figure 4-1. Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations (50 mM, 100 mM, and 400 mM) and ethephon percentages (1%, 5%, and 10%). The means within a methyl jasmonate concentration with a different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 4-2. Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard tapping method. The different doses are methyl jasmonate concentrations in DI water and Tween 20. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 4-3. Cumulative flow rate of oleoresin (g) since day of tapping treatment by chemical treatment at the 2015 dose response test. The following equations correspond to the oleoresin flow rate when trees are stimulated by the different methyl jasmonate doses: control: y = 652.107 * (1 – 0.891 e-0.027D ); 25 mM: y = 1004.612 * (1 – 0.928 e-0.019D ); 50 mM: y = 1097.538 * (1 – 0.991 e-0.023D ); 100 mM: y = 1502.460 * (1 – 0.913 e-0.019D ); 200 mM: y = 2509.604 * (1 – 0.944 e-0.012D ); 400 mM: y = 2723.893 * (1 – 0.948 e-0.012D ); 600 mM: y = 5508.152 * (1 – 0.961 e-0.005D ). Where y corresponds to oleoresin yield (g) and D corresponds to number of days since treatment.

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Figure 4-4. Cumulative flow of oleoresin (g) and resin flow rate over time since day of tapping treatment in Gainesville at the 2015 methyl jasmonate dose response test.

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Figure 4-5. Effect of carrier solvent on oleoresin yield (kg) for 100 mM methyl jasmonate when tapping slash pine trees in North Florida using the standard borehole drilling method. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure 4-6. Chemical dose effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2016 using the standard tapping method. The different doses are methyl jasmonate concentrations diluted in 90% ethanol. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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CHAPTER 5 GENETIC EFFECTS ON OLEORESIN FLOW OF SLASH PINE CLONES

Introduction

The individual tree variation in slash pine (Pinus elliottii Engelm. Var. elliottii) oleoresin composition is high and suggests that many components are under genetic control (Squillace and Fisher, 1966). In Chapter 2, the variation of oleoresin flow and yield among conifer species were discussed. The flow rate of oleoresin is influenced by environmental and biological factors. Resin duct size, number, and length, oleoresin viscosity, crystallization rate, and exudation pressure can all affect the rate of flow of resin and potential yield (USDA Forest Service, 1971a; Hodges, 1995). These resin and tree properties are not only different among conifer species, but can be controlled by genetics within species (Schopmeyer et al., 1954; USDA Forest Service, 1971a; USDA

Forest Service, 1971b; Hodges, 1995; Sukarno et al., 2015). The duration of oleoresin flow also varies within and among species and in the southeast U.S.; oleoresin in slash pine trees flows for months, while oleoresin flow in loblolly pine tends to slow dramatically after 2 days (Hodges et al., 1977).

There is a great potential of increasing productivity in an oleoresin tapping operation through breeding programs due to the high broad-sense heritability of growth traits that have a direct influence on yield as well as the heritability of oleoresin flow and yield (Schopmeyer et al., 1954; Franklin et al., 1970; USDA Forest Service, 1971a;

USDA Forest Service, 1971b; Westbrook et al., 2013; Sukarno et al., 2015). Increasing the productivity of southeastern pine species through intensive forest management and selective breeding is crucial to ensure global timber and non-timber forest products demands are met. 166

The first objective of this study was to evaluate the correlation between short term with long term oleoresin yield of slash pine trees by using the CCLONES 2 site established by the University of Florida’s FBRC. A strong genetic correlation between short term and long-term oleoresin yields would allow us to screen trees more cost effectively for making selections. The second objective of this study was to estimate heritability of the oleoresin flow traits among various families to determine the level of genetic control of this trait.

Methods

Study Area

The slash pine CCLONES 2 (Comparing Clonal Lines On Experimental Sites) stand used for this study was established by the University of Florida’s FBRC in

December 2002 (FBRC, 2002). This study was located in a low rust hazard property owned and managed by Rayonier Inc. in northeast Gainesville, Florida (29°43’45.7” N,

82°17’46.0” W). The study was established by the FBRC, Rayonier Inc., and Boise

Corp. to better understand clonal biology and to “characterize elite genotypes of slash pine and to understand their growth dynamics, ecophysiology, nutrition, pest resistance and wood quality across a range of planting sites and management intensities as both cuttings (clones from FS families) and seedlings (FS families)” (FBRC, 2002).

The study area was prepared with chopping, raking and bedding between April and May 2002. In September 2002, the site was treated with 48 ounces Chopper and five quarts Conquer and in November 2002, a second bed was established in the study area. The site was then planted with test, border and filler trees in December 2002. The study area was divided into eight replicate plots; four intensively managed plots

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(replicates 5, 6, 7, and 8) and four non-intensively managed plots (replicates 1, 2, 3, 4).

In November 2002, the intensive treatments received an additional herbicide treatment of 20% Garlon with 80% JLB Oil applied by hand on palmetto stems. In April 2003, the whole study area was treated with three ounces Oust per acre in 20 gallons of water via broadcast application using a tractor to control herbaceous weeds. Between September and October 2003, the whole study area received 200 lbs per acre of diammonium phosphate (DAP) via helicopter and 50 per acre DAP via four-wheeler.

The study area has a humid subtropical climate with hot wet summers and mild dry winters, and the topography was flat with a slope between 0 and 2%. The study was established on a poorly drained site and the dominant soil series was Wauchula. The

Wauchula series is a Spodosol and is classified as a sandy over loamy, siliceous, active, hyperthermic Ultic Alaquods (USDA Natural Resources Conservation Service

1993b). The understory vegetation included saw palmetto (Serenoa repens (B.) Small.), blackberries (Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)), greenbriers (Smilax L. spp.), lopsided Indiangrass (Sorghastrum nutans (L.) Nash) and a variety of other native grasses.

Study Design and Genetic Material

The CCLONES 2 study consisted of genotypes from 22 elite parents of slash pine clones from the same FS families and seedlings from FS families. The genetic materials for this study were provided by Rayonier Inc. and Boise Corp. (FBRC, 2002).

Five of the elite parents were CFGRP families; while 17 of the elite parents were from

WGFTIP selections (Western Gulf Tree Improvement Program) (FBRC, 2002). The study was planted using an incomplete block plot design with 60 incomplete blocks in

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each replicate plot. The 22 elite parents were used to create 19 FS families (FBRC,

2002). In total, 672 clones and 48 seedlings were planted in each replicate plot. Each replicate plot contains 20 beds with 36 trees in each, for a total of 720 trees per replicate. The study area was planted at a density of 725 seedlings per acre with each replicate plot being about 1 acre. The non-intensive and intensive treatments were separated by a ten-row buffer. Within each intensity treatment there were no border rows. Each treatment had a total of 40 beds and 72 trees in each, split into four replicates. For this dissertation research, only four replicate plots, two from each intensity treatments (i.e., replicates 1, 3, 5, and 7) were selected. Figure 5-1 outlines the planting layout for the study. Table 5-1 summarizes the number of trees selected for tapping in each family and replicate plot.

Oleoresin Collection

The trees in the CCLONES 2 site were tapped using a short-term oleoresin collection method described in Strom et al. (2002) and Roberds et al. (2003). This method involved making a 1.27 cm in diameter circular wound using an arch punch, facilitated removal of the bark and phloem at breast height. Immediately after wounding, plastic taps with a 15-ml collection tube were placed over the wound site and mounted with a screw. Oleoresin flowed into the tubes for roughly 24 hours after tapping and was weighed within one week of collection. The empty tubes, with individual barcodes, were weighed prior to tapping to get the final oleoresin mass.

The trees in the CCLONES 2 site were also tapped using the borehole tapping method discussed in Chapter 3. Each tree was tapped with one borehole and treated

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with 100 mM methyl jasmonate stimulant diluted in 90% ethanol as discussed in

Chapter 4.

Statistical Analysis

The diameter at breast height (DBH) in cm and oleoresin yield (g) data from the

CCLONES 2 study were analyzed in R 3.1.1 and ASReml-R v.3 (R Development Core

Team, 2016; Gilmour et al., 2015). To assess the bivariate effects of DBH on short- and long-term oleoresin yield, a linear regression model was fitted using the JMP software from SAS (SAS Institute, 2016). The least squares mean was calculated using lsmeans

R package based on a general linear mixed model with replicate and family as fixed effects. Outliers more than two standard deviations from the mean were omitted in the analysis. Broad-sense heritabilities of individual phenotypic traits were calculated based on the following clonal model with the constructed pedigree and without covariates:

Yij = µ + Ri + Ri:IBj + ped(Cloneid) + Familyid + ide(Cloneid) + eij

th th where Yij corresponds to the phenotypic trait in the i replicate (i = 1, 3, 5, or 7) and i

th replicate by j incomplete block (j = 1 to 60), Ri corresponds to the fixed replicate effect,

Ri:IBj corresponds to the random incomplete block within replicate effect, ped(Cloneid) corresponds to the random additive effect, ide(Cloneid) corresponds to the random non- additive effects of a given clone, and ej corresponds to the random residual effect.

There is a pedigree associated with the term ped(Cloneid) that was used to assign a numerator relationship matrix.

To assess the individual and interactive effects of DBH and short-term oleoresin yield on long-term oleoresin yield, a general linear mixed model was fitted using R 3.1.1

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and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al., 2015). The following clonal model with the constructed pedigree and covariates was used:

Yij = µ + Ri + TM + D + D:TM + Ri:IBj + ped(Cloneid) + Familyid + ide(Cloneid) + eij

th th where Yij corresponds to the phenotypic trait in the i replicate (I = 1, 3, 5, or 7) and i replicate by jth incomplete block (j = 1 to 60), TM corresponds to the fixed short-term oleoresin yield effect, D corresponds to the fixed DBH effect, D:TM corresponds to the fixed interaction effect of DBH and short-term oleoresin yield. All other terms were previously defined.

The type A genetic correlation between short-term and long-term yield was analyzed using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016; Gilmour et al., 2015). The following equation to calculate genetic correlation was used:

Cov(TM,BM) Correlation(TM,BM)= √Var(TM)×Var(BM)

Where TM corresponds to short-term yield, BM corresponds to long-term yield,

Cov(TM,BM) corresponds to the covariance between short- and long-term yield,

Var(TM) corresponds to the variance component of short-term yield, and Var(BM) corresponds to the variance component of long-term yield.

Results

DBH had a very strong positive influence on total oleoresin yields for long-term but not short-term oleoresin collection. The oleoresin was collected long-term for four months by drilling a single borehole into the base of the tree and was collected short- term for 24 hours by wounding the bark at breast height. The relationship between DBH

(cm) and total long-term oleoresin yield (g) was modeled using a linear regression

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(Figure 5-3). This linear regression model explained 78.5% of the variation of oleoresin yield with tree size (r2 = 0.7846 and p-value <0.0001) (Figure 5-3). The equation for the linear regression model is as followed:

Y = 137.30 + (50.12 × D) where Y equals the estimated yield per tree (g) and D is the DBH (cm) of the tapped tree.

The relationship between DBH (cm) and total long-term oleoresin yield (g) by

Family ID was also modeled using a linear regression (Figure 5-4). This linear regression model explained 37.8% of the variation of oleoresin yield with tree size (r2 =

0.3873 and p-value = 0.0147) (Figure 5-4). The equation for the linear regression model is as followed:

Y = 198.61 + (29.00 × D) where Y equals the estimated yield per tree (g) and D is the DBH (cm) of the tapped tree.

In contrast, no relationship was observed between tree size and short-term oleoresin yield (r2 = 0.0023 and p-value = 0.7503) (Figure 5-5).

Table 5-2 summarizes the least squares means for DBH (cm), short-term yield

(g), and long-term oleoresin yield (g) for all replicate plots. While the clones in family

504 were larger than all the other families (average DBH 17.2 cm), the trees had some of the lowest oleoresin short-term yields (0.60 g) and not significantly different from long-term yield (Table 5-2; Table 5-3; Figure 5-2). Family 534 had the smallest trees

(DBH 13.18) and the lowest long-term yield with a mean about 540 g of oleoresin (Table

5-2; Table 5-3; Figure 5-2). Family 521, had average DBH and short-term yields, but the

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highest long-term oleoresin yield (782.3 g) (Table 5-2; Table 5-3; Figure 5-2). Family

539 had the highest short-term oleoresin yields (1.7 g) and had on average larger DBH

(Table 5-2; Table 5-3; Figure 5-2). Short-term oleoresin yields were the same for families 502 and 532; these families had the lowest yields (0.4 g and 0.5 g, respectively)

(Table 5-2; Table 5-3; Figure 5-2).

The estimated broad-sense heritabilities for all three traits, based on a clonal model with fixed replicate effect and random incomplete block within replicate and individual additive and non-additive clonal effects are presented in Table 5-4. Broad- sense heritability estimates ranged from moderate to low (Table 5-4). DBH had the highest heritability estimate (H2 = 0.321) (Table 5-4). The broad-sense heritability estimates for short-term and long-term oleoresin yield were low (H2 = 0.161 and H2 =

0.190, respectively) (Table 5-4).

The individual and interactive effects of DBH and short-term oleoresin yield on long-term yield were fitted using a general linear clonal model. The model showed only significant main effects of replicate plot and DBH (p-values 0.002 and <0.0001, respectively) (Table 5-5). Short-term yield (Tube Mass) was not a significant predictor as a main effect (p-value = 0.619); however, it had a positive significant interaction with

DBH (p-value = 0.041) (Table 5-5). The broad-sense heritability estimate of long-term oleoresin yield with DBH, short-term yield, and the interaction as covariates was moderately low (H2 = 0.194) (Table 5-4).

The relationship between short- and long-term oleoresin yield (g) was modeled using a linear regression (Figure 5-6). This linear regression model did not explain the variation of long-term oleoresin yield with short-term yield (r2 = 0.001 and p-value =

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0.4177) (Figure 5-6). In contrast, the Type-A genetic correlation between short- and long-term yield was analyzed based on the Family ID and accounting for incomplete block effects. This analysis observes the phenotypic correlation among two traits and can be used to examine the biological relationship between traits and make selections for breeding. The Type-A genetic correlation between short- and long-term yield was

0.718 (Table 5-6).

Discussion

Planted loblolly and slash pine grown in the Coastal Plain typically take around

20-25 years to reach rotation age and, as a result, progeny tests are used by tree breeders to make inferences and select better performing families at a younger age

(Squillace and Gansel, 1974). Ten-year-old slash pine progeny tests can be used to make growth and productivity predictions at the age of 25 (Squillace and Gansel, 1974).

Understanding the genetic architecture of short- and long-term oleoresin yields and tree size on long-term oleoresin yield will allow us to increase productivity of tapping operations and overall profitability of slash pine stands. As observed in the studies discussed in Chapters 2 and 3, DBH is correlated positively with long-term oleoresin yield. Hodges (1995), Tadesse et al. (2001), and Hadiyane et al. (2015), all found similar positive correlations between DBH and oleoresin yields. In the size considered from the CCLONES 2 study, the linear regression model showed a very strong correlation between DBH and long-term oleoresin yield (r2 = 0.7846). This suggests that slash pine families selected for larger stem size on average can increase the potential oleoresin yield of a plantation. Tree size was not correlated with short-term

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oleoresin yield. This was not surprising as oleoresin was collected from a small surface wound for only 24-hours.

According to Tadesse (2001), the best method to increase oleoresin yields is by selecting and breeding high yielding trees. McReynolds and Gansel (1985) found that a high gum yielding slash pine progeny test established in 1946 yielded 30% more oleoresin compared to non-high gum stands. In our study, there were families that outperformed others based on DBH, short-term oleoresin yields and long-term oleoresin yields. However, in certain cases, like family 504, the families with larger trees had less short-term oleoresin yield. In terms of long-term oleoresin yield, one family (521) had significantly higher yield, which would make the high yielding clones within this family good selections.

The broad-sense heritability of DBH in the CCLONES 2 site was moderately strong at H2 = 0.32. However, the broad-sense heritability estimates for short- and long- term oleoresin yield in the CCLONES 2 site were moderately low. These results are not comparable to those obtained in other studies which calculated broad-sense heritability estimates between 67 and 90% (Mergen et al., 1955; Squillace and Doman, 1959;

Squillace and Bengtson, 1961; Squillace, 1965). This is likely due to the small number of families studied here. Nevertheless, these heritability estimates are still high enough to be able to make selections and achieve attractive genetic gains. However, heritability estimates for short-term oleoresin flow in slash pine were comparable to the short-term oleoresin flow reported by Westbrook et al. (2013) in loblolly pine tapped in North

Florida, U.S. using the same method. Westbrook et al. (2013) recorded within site broad-sense heritability estimates of 0.25 to 0.38, compared to our estimates of 0.16.

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DBH was again the best phenotypic predictor of long-term oleoresin yield.

Because there was no phenotypic correlation between short- and long-term yield, short- term yield alone is not a good predictor of long-term yield. However, there was a strong positive genetic correlation (0.718) between short- and long-term yields. This positive association suggests the potential of selecting high yielding trees based on short-term oleoresin flow studies for breeding. Selection of trees with higher short-term oleoresin yields will lead to genetic gain for both short- and long-term oleoresin yields.

Planting high yielding clones and families would increase the profitability of slash pine stands and would allow the U.S. to be more competitive in the global pine chemical industry. Future research should focus on examining the age to age correlation of short- and long-term oleoresin yield. A strong correlation between short-term oleoresin flow in young trees aged 5 to 6 and long-term oleoresin yield in trees aged 15 to 20 would allow us to confidently make early selections of high yielding trees.

Summary and Conclusions

This study was designed to examine the genetic effects on oleoresin yield. The goals of this study were to evaluate the correlations between DBH and short-term oleoresin yield on long-term oleoresin yields and the heritability estimates of these traits in a slash pine clonal site. Phenotypically, short-term yield was not correlated to long- term yields. The strong positive genetic correlation between short- and long-term yield support the approach that genetic tests screened with short-term yields can be used to select high yielding trees. One family tested had significantly higher long-term yields.

This family would be a great candidate for a breeding program aimed at increase oleoresin productivity in slash pine.

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Table 5-1. Summary of genotypes selected in each replicate of the CCLONES 2 study. Family ID Replicate 1 Replicate 3 Replicate 5 Replicate 7 501 13 14 14 14 502 13 10 15 15 504 14 15 14 14 505 15 14 15 14 521 16 15 15 15 529 13 14 14 15 530 14 13 14 14 531 15 15 14 14 532 10 11 15 11 533 14 14 14 14 534 10 10 14 15 535 12 13 15 15 537 15 12 14 15 538 13 15 14 15 539 14 15 13 15 540 14 15 11 13 Total 216 215 225 229

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Table 5-2. Least square means with standard errors for phenotypic traits measured at the CCLONES 2 study. Family ID DBH (cm) Short-Term Oleoresin Long-Term Oleoresin Yield (g) Yield (g) 501 16.579 (0.275) 1.002 (0.156) 643.760 (41.486) 502 16.585 (0.285) 0.382 (0.160) 626.718 (42.291) 504 17.169 (0.268) 0.603 (0.156) 645.623 (40.752) 505 15.249 (0.272) 1.141 (0.152) 722.132 (40.399) 521 15.535 (0.272) 0.892 (0.152) 782.266 (39.393) 529 16.772 (0.275) 1.090 (0.152) 735.904 (41.116) 530 15.749 (0.282) 1.308 (0.159) 649.500 (41.486) 531 15.752 (0.272) 0.799 (0.156) 676.961 (40.399) 532 14.488 (0.296) 0.462 (0.167) 608.080 (44.908) 533 16.819 (0.272) 1.111 (0.156) 658.482 (41.113) 534 13.166 (0.298) 0.761 (0.167) 538.959 (43.993) 535 15.341 (0.282) 0.826 (0.160) 638.262 (41.496) 537 15.948 (0.279) 0.859 (0.157) 659.035 (41.123) 538 15.295 (0.272) 1.377 (0.157) 642.213 (40.755) 539 16.756 (0.270) 1.663 (0.152) 745.471 (40.755) 540 15.129 (0.282) 0.966 (0.157) 639.986 (42.276) Note: short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Table 5-3. Tukey significance group letters of the least square means for phenotypic traits measured at the CCLONES 2 study (alpha < 0.05) recorded in Table 5- 2. Family ID DBH (cm) Short-Term Oleoresin Yield Long-Term Oleoresin Yield (g) (g) 501 ABC ABCD AB 502 ABCD D AB 504 A CD AB 505 DEF ABCD AB 521 BCDEF BCD A 529 AB ABCD AB 530 BCDEF ABC AB 531 BCDEF BCD AB 532 FG D AB 533 AB ABCD AB 534 G BCD B 535 CDEF BCD AB 537 ABCDE BCD AB 538 CDEF AB AB 539 AB A AB 540 EF ABCD AB Note: The different Tukey group letters were significantly different based on Tukey’s HSD test (p-value <0.05). Short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Table 5-4. Broad sense heritability estimates calculated for phenotypic traits measured at the CCLONES 2 study. Phenotypic Trait Broad Sense Heritability Standard Error DBH 0.321 0.064 Short Term Oleoresin Yield 0.161 0.050 Long Term Oleoresin Yield 0.190 0.048 Long Term Oleoresin Yield with Covariates 0.194 0.049 Note: short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Table 5-5. Summary of main and interactive effects on long-term oleoresin yields at the CCLONES 2 site using the borehole tapping method in 2016 based on a general linear clonal model. Effect DF Den DF F-statistic p-value Replicate 3 175.7 5.45 0.002** Tube Mass 1 832.8 0.04 0.619 DBH 1 698.9 125.40 <0.000** DBH:Tube Mass 1 820.6 4.17 0.041 Note: P-values with ** superscripts are significant based on a test with p-value <0.01. Tube mass represents short-term 24-hour oleoresin yield.

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Table 5-6. Summary of variance components of genetic correlation between short-term and long-term oleoresin yield in the CCLONES 2 site. Trait Variance Component Standard Error Short-Term Oleoresin Yield 0.053 0.03 Long-Term Oleoresin Yield 1413.780 1068.89 Short- and Long-Term Oleoresin Yield 6.227 4.04 Note: short-term oleoresin was collected in a 24-hour period and long-term oleoresin was collected over four months.

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Figure 5-1. Layout of the University of Florida’s CCLONES 2.

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B Figure 5-2. Least square means with standard errors for oleoresin traits measured at the CCLONES 2 study. A) Average short-term oleoresin yield. B) Average long-term oleoresin yield.

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Figure 5-3. Bivariate fit of total long-term tree yield of oleoresin (g) in slash pine by DBH (cm). The r2 for the linear relationship between DBH and average total tree yield is 0.785 (p-value <0.0001).

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Figure 5-4. Bivariate fit of total long-term clonal mean oleoresin yield (g) in slash pine by DBH (cm). The r2 for the linear relationship between DBH and average total tree yield is 0.378 (p-value 0.0147).

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Figure 5-5. Bivariate fit of short-term tree yield of oleoresin (g) in slash pine by DBH (cm). The r2 for the linear relationship between DBH and average short-term tree yield is 0.002 (p-value 0.7503).

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Figure 5-6. Bivariate fit of short-term and long-term oleoresin yield (g). The r2 for the linear relationship between short-term tree yield and average long-term yield is 0.001 (p-value 0.4177).

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CHAPTER 6 CONCLUSION

To maximize the value of forest plantations in the southeast U.S., the primary focus of this research was to understand the effects of chemical and physical inducers, and environmental and genetic effects on the flow and yield of oleoresin from slash pine trees. The specific objectives of this research were: (1) to maximize collection and recovery of oleoresin and increase terpene synthesis in slash pine for renewable chemicals and biofuel production by testing different chemical stimulants, tapping intensity, stand ages, and stand management practices, (2) to determine the optimal methyl jasmonate dosage and carrier solvent that gives the greatest oleoresin yields in the southeast U.S., and (3) to determine the genotypic and phenotypic correlations between 24-hour resin flow with multi-month resin collection for genetic improvement in oleoresin yields.

The borehole tapping method to collect oleoresin has numerous benefits compared to other methods used around the world. This method only requires laborers to visit the tree two times during a collection season, it yields better quality oleoresin with less impurities and greater amounts of monoterpenes, reducing crystallization, and this method allows landowners to maintain their stands for timber production without damage to merchantable wood (Hodges, 1995).

In Chapter 3, the effects of stand management, tree characteristics, age, and chemical stimulants on the yield of oleoresin in slash pine trees in North Florida were examined. Overall, oleoresin yields increased with tree age; however, this increase was positively correlated with tree size because age was not significant. Larger trees are more productive and thus have a greater potential for producing oleoresin. Tapping 189

intensity was negatively correlated to oleoresin yield, which further supports tapping of larger trees is preferred. Crown volume was not nearly as strong a predictor of oleoresin yield compared to DBH. Hodges (1995) also concluded that canopy was not as good of a predictor and inferred that oleoresin flow capacity from the borehole tapping method is fixed.

Pine straw management had a significantly positive impact on oleoresin yields.

Active management, increased fertilization treatments, and reduced understory competition all potentially play a role in increasing oleoresin yields observed in trees tapped on a site managed for pine straw raking. Numerous questions on the effects of soil nutrient availability on oleoresin productivity remain unanswered. Knebel et al.

(2008) observed an increase in oleoresin production in loblolly pines with fertilization.

Understanding how the soil nutrient limitations impact production in slash pine trees will help frame silvicultural management regimes for plantations established to collect oleoresin.

Across all sites and all ages, chemical stimulant was the most significant predictor of oleoresin yields. Methyl jasmonate was the best inducer of oleoresin yields tested in slash pine trees. The optimal tapping season length with the borehole tapping method is a minimum of 120 days, with tapping occurring in the late spring/early summer. In summary, when tapping young slash pine trees, aged 15 to 22, in the southeastern U.S. using the borehole method, it is possible to collect on average 1 to

1.5 kg of oleoresin per tree.

In Chapter 4, the optimal and most sustainable treatment for increasing oleoresin yields in slash pine trees was examined. As observed in Chapter 3, the application of

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chemical stimulants was the most effective inducer of oleoresin yields. The dilution of chemical inducers in ethanol as opposed to DI water and Tween 20 was beneficial. The alcohol may allow methyl jasmonate to better penetrate the xylem, reduce the crystallization rate within the borehole and help maintain the flow of the oleoresin. The dose response experiments showed the benefit of increasing methyl jasmonate concentration on oleoresin yield. The optimal concentration of methyl jasmonate to induce oleoresin flow was 400 mM. With this increase in concentration it is possible to collect close to 3.0 kg of oleoresin in 15-year-old slash pine trees, which would make the operation economically viable.

Several variations of the borehole tapping method were tested, including six and eight boreholes and smaller boreholes within larger ones (Appendix C). However, it was found that the best tapping method is an automated system with three boreholes drilled at the base of the tree all connecting to one collection borehole.

The automated method is less labor intensive and allows for a much larger oleoresin collection operation. The average productivity for the manual drilling method using the gas-powered drill to drill two boreholes was 26.7 trees per hour. On the other hand, average productivity using the automated tapping method, which drills three connected boreholes was significantly higher at 61 trees per hour. Further, the estimated total cost per kg of oleoresin using the automated drilling technique is $1.29, compared to $3.00 for the manual drilling method. Further, the most cost-effective chemical stimulant treatment was the 400 mM methyl jasmonate diluted in 90% ethanol which costs an estimated $1.21 per kg of oleoresin using the manual drilling technique.

These costs could be further reduced by tapping trees using the automated drilling

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technique as opposed to manually. For commercial production, the most cost-effective treatment in the southern U.S. is tapping slash pine stands using an automated drilling machine and applying 400 mM of methyl jasmonate diluted in 90% ethanol.

Chapter 5 also examined the correlations between DBH and short-term oleoresin yield on long-term production as well as the effects of genetics on short- and long-term oleoresin flow. To do this, a slash pine clonal site (CCLONES 2) was tapped for short- term flow and long-term yield using the borehole tapping method. DBH was found to have a very strong positive correlation to long-term yield but was not correlated to short- term yield. There was no significant bivariate phenotypic correlation between short-term yield and long-term oleoresin yield; however, there was a strong positive genetic correlation between the two phenotypic traits. The interaction between DBH and short- term yield was a significant predictor of long-term yield. Comparing the average long- term oleoresin yield between different slash pine families allows us to make selections for higher gum oleoresin yielding families. In this study one family (521) had significantly higher yields. Unlike other studies that found broad-sense heritability estimates of oleoresin between 67 and 90%, this study calculated moderate to low broad-sense heritabilities of 0.16 for short-term yield, 0.19 for long-term yield, and 0.194 of long-term yield with covariates (Mergen et al., 1955; Squillace and Doman, 1959; Squillace and

Bengtson, 1961; Squillace, 1965). Nevertheless, it is still possible to make important genetic gains from selections.

In conclusion, there is potential to reinvigorate oleoresin tapping and collection in the U.S. Increasing overall productivity of southern pine stands, primarily slash pine, through intensive management and selective breeding programs, will allow forest

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landowners to increase their stand’s potential oleoresin productivity. Larger diameters have a positive correlation to oleoresin yields. Slash pine trees should be stimulated with a chemical inducer, preferably methyl jasmonate diluted in ethanol, to maximize oleoresin yields.

The effect of soil nutrient availability on oleoresin yield in the southeast U.S. remain unanswered. Understanding these impacts is important to maximize the potential oleoresin productivity of a stand to reinvigorate the industry in the U.S. To establish a commercial operation, it is imperative to identify areas for improvement in the collection and processing method. Establishing a system to more efficiently collect, process, and sort through the collection bags will allow for more trees to be sampled and will decrease cost of labor.

Future studies should investigate the short- and long-term oleoresin flow and yield in pseudo backcross loblolly and slash pine hybrids. Loblolly pines tend to be more productive in terms of growth while slash pine is more productive in terms of oleoresin flow. Since the pseudo backcross hybrids were found to be more growth efficient, they may also have more productive oleoresin yields. Unfortunately, in this study the pseudo backcross hybrid site sampled in Appendix 5 fell victim to a wildfire and we were unable to sample short-term oleoresin flow.

While Squillace and Gansel (1974) found it possible to make growth and productivity predictions for 25-year-old trees using 10-year-old progeny tests, questions remain on the age-to-age correlation of oleoresin yield. Understanding age-age correlations for short-term oleoresin yield in 5-year-old progeny tests to long-term yield in 15 to 20-year-old stands will be important when making selections. Since the rotation

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age for slash pine in the southeast U.S. is 20 to 25 years, finding a strong positive age to age correlation for these oleoresin traits will allow tree breeders to make selections for high yielding trees at a younger age, accelerating the rates of genetic gain. This will then allow breeders to make second a third cycle selections to further improve the oleoresin production in slash pine trees and establish plantations for collection and timber.

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APPENDIX A COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT FOR INDIVIDUAL SITES DURING THE 2013 TO 2015 TAPPING SEASONS

Table A-1. Summary of oleoresin yields by chemical treatment in Union 1 site during the 2013 tapping season. Stand age is 14 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 447.25 B Ethephon 431.25 B MeJa 844.49 A MejaEthephon 923.50 A

Table A-2. Summary of oleoresin yields by chemical treatment in Alachua 1 site during the 2013 tapping season. Stand age is 16 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 392.47 B Ethephon 484.69 B MeJa 903.46 A MejaEthephon 954.87 A

Table A-3. Summary of oleoresin yields by chemical treatment in Alachua 2 site during the 2013 tapping season. Stand age is 22 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 394.01 C Ethephon 507.53 C MeJa 1059.01 A MejaEthephon 762.05 B

Table A-4. Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 431.77 C Ethephon 522.35 C MeJa 1104.25 A MejaFeS 703.25 B

Table A-5. Summary of oleoresin yields by chemical treatment in Alachua 3 site during the 2014 tapping season. Stand age is 15 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 495.70 C Ethephon 757.70 B MeJa 641.77 B MejaFeS 902.25 A

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Table A-6. Summary of oleoresin yields by chemical treatment in Union 1 site during the 2014 tapping season. Stand age is 15 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 755.44 AB Ethephon 843.25 A MeJa 643.25 B MejaFeS 779.62 AB

Table A-7. Summary of oleoresin yields by chemical treatment in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking. Chemical Treatment Mean Yield (g) Tukey Group Control 605.44 C Ethephon 919.25 B MeJa 1347.25 A MejaFeS 805.44 B

Table A-8. Summary of oleoresin yields by chemical treatment in Alachua 4 site during the 2014 tapping season. Stand age is 22 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 772.06 C Ethephon 1020.58 AB MeJa 1089.45 A MejaFeS 890.42 BC

Table A-9. Summary of oleoresin yields by chemical treatment in Alachua 5 site during the 2014 tapping season. Stand age is 22 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 598.48 B Ethephon 679.62 B MeJa 915.50 A MejaFeS 1079.75 A

Table A-10. Summary of oleoresin yields by chemical treatment in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 289.13 C Ethephon 411.04 BC MeJa 490.07 B MejaEthephon 959.31 A

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Table A-11. Summary of oleoresin yields by chemical treatment in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 481.71 C Ethephon 377.89 C MeJa 1029.74 A MejaEthephon 773.73 B

Table A-12. Summary of oleoresin yields by chemical treatment in Union 1 site during the 2015 tapping season. Stand age is 16 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 460.00 B Ethephon 468.08 B MeJa 668.61 A MejaEthephon 670.26 A

Table A-13. Summary of oleoresin yields by chemical treatment in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking. Chemical Treatment Mean Yield (g) Tukey Group Control 363.08 C Ethephon 671.75 B MeJa 852.00 A MejaEthephon 788.13 AB

Table A-14. Summary of oleoresin yields by chemical treatment in Alachua 4 site during the 2015 tapping season. Stand age is 23 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 513.56 B Ethephon 563.92 AB MeJa 383.09 C MejaEthephon 662.41 A

Table A-15. Summary of oleoresin yields by chemical treatment in Alachua 5 site during the 2015 tapping season. Stand age is 23 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 451.92 C Ethephon 548.70 C MeJa 1471.77 A MejaEthephon 984.10 B

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APPENDIX B COMPARING OLEORESIN YIELD BY CHEMICAL TREATMENT AND IN TREE INJECTION FOR INDIVIDUAL SITES DURING THE 2014 AND 2015 TAPPING SEASONS

Table B-1. Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2014 tapping season. Stand age is 11 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 452.00 D Control/Injection 411.03 D Ethephon 517.75 CD Ethephon/Injection 526.83 BCD MeJa 1075.25 A Meja/Injection 1133.25 A MejaFeS 717.50 B MejaFeS/Injection 689.00 BC

Table B-2. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2014 tapping season. Stand age is 15 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 500.75 D Control/Injection 490.51 D Ethephon 771.88 B Ethephon/Injection 741.94 BC MeJa 716.41 BC Meja/Injection 569.00 CD MejaFeS 1026.92 A MejaFeS/Injection 783.66 B

Table B-3. Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2014 tapping season. Stand age is 15 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 841.03 ABC Control/Injection 672.00 BC Ethephon 721.75 BC Ethephon/Injection 964.75 A MeJa 623.25 C Meja/Injection 663.25 BC MejaFeS 673.85 BC MejaFeS/Injection 885.38 ABC

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Table B-4. Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2014 tapping season. Stand age is 15 years old. This stand was managed for pine straw raking. Chemical Treatment Mean Yield (g) Tukey Group Control 646.75 C Control/Injection 563.08 C Ethephon 845.75 BC Ethephon/Injection 992.75 B MeJa 1338.75 A Meja/Injection 1355.75 A MejaFeS 839.52 BC MejaFeS/Injection 766.76 BC

Table B-5. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 4 site during the 2014 tapping season. Stand age is 22 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 775.94 B Control/Injection 768.06 B Ethephon 1064.71 AB Ethephon/Injection 977.71 AB MeJa 1143.61 A Meja/Injection 1036.76 AB MejaFeS 941.94 AB MejaFeS/Injection 837.43 AB

Table B-6. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 5 site during the 2014 tapping season. Stand age is 22 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 657.44 DE Control/Injection 541.00 E Ethephon 648.25 DE Ethephon/Injection 711.79 CDE MeJa 977.25 ABC Meja/Injection 853.75 BCD MejaFeS 1169.74 A MejaFeS/Injection 992.00 AB

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Table B-7. Summary of oleoresin yields by chemical treatment and in tree injection in Bradford 1 site during the 2015 tapping season. Stand age is 12 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 282.50 D Control/Injection 295.75 D Ethephon 415.13 CD Ethephon/Injection 406.84 CD MeJa 541.62 C Meja/Injection 439.87 CD MejaEthephon 1093.59 A MejaEthephon/Injection 800.61 B

Table B-8. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 3 site during the 2015 tapping season. Stand age is 16 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 474.36 CD Control/Injection 489.46 CD Ethephon 378.16 D Ethephon/Injection 377.63 D MeJa 1075.90 A Meja/Injection 983.59 A MejaEthephon 860.26 AB MejaEthephon/Injection 680.00 BC

Table B-9. Summary of oleoresin yields by chemical treatment and in tree injection in Union 1 site during the 2015 tapping season. Stand age is 16 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 484.05 BCD Control/Injection 437.75 D Ethephon 456.92 D Ethephon/Injection 479.23 CD MeJa 704.75 A Meja/Injection 631.54 ABCD MejaEthephon 675.75 AB MejaEthephon/Injection 664.47 ABC

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Table B-10. Summary of oleoresin yields by chemical treatment and in tree injection in Union 2 site during the 2015 tapping season. Stand age is 16 years old. This stand was managed for pine straw raking. Chemical Treatment Mean Yield (g) Tukey Group Control 355.79 C Control/Injection 370.00 C Ethephon 699.50 AB Ethephon/Injection 644.00 B MeJa 842.75 AB Meja/Injection 861.25 AB MejaEthephon 878.25 A MejaEthephon/Injection 698.00 AB

Table B-11. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 4 site during the 2015 tapping season. Stand age is 23 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 489.44 BCD Control/Injection 537.03 ABC Ethephon 612.31 AB Ethephon/Injection 516.75 BCD MeJa 355.37 D Meja/Injection 411.50 CD MejaEthephon 691.75 A MejaEthephon/Injection 632.31 AB

Table B-12. Summary of oleoresin yields by chemical treatment and in tree injection in Alachua 5 site during the 2015 tapping season. Stand age is 23 years old. Chemical Treatment Mean Yield (g) Tukey Group Control 462.75 C Control/Injection 440.53 C Ethephon 518.42 C Ethephon/Injection 578.21 C MeJa 1564.75 A Meja/Injection 1376.41 A MejaEthephon 1021.05 B MejaEthephon/Injection 949.00 B

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APPENDIX C SLASH PINE OLEORESIN TAPPING OPTIMIZATION TRIALS

Methods

Study Areas

Planted slash pine (Pinus elliottii Engelm. Var. elliottii) stands between the ages of 15 and 26 were selected from privately owned and managed companies in Alachua and Union counties. Rayonier and Roberts Land & Timber Investment Corp. provided the stands selected for this research. Throughout these experimental studies, four stands were selected. All stands were managed using similar conventional silvicultural practices including bedding, weed control, and fertilizer treatments. The criteria used to select stands for tapping included: not easily accessed by the public, sufficient number of trees available to tap, appropriate age, and appropriate thinning regime. Trees with signs and symptoms of diseases such as fusiform rust (Cronartium fusiforme), pitch canker (Fusarium circinatum), bark beetles, and pitch moth were not selected. Trees with a diameter less than 12.7 cm, dead trees, and those damaged were not selected for tapping.

Trees in these experimental studies were tapped from 2014 to 2015. The same thinned 15-year-old slash pine stand in Alachua county was used for most of the optimization experiments. This slash pine experimental site is located just outside of

Gainesville, Florida (29°46’N latitude and 82°18’W longitude) at an elevation 51 meters from average sea level. An additional thinned 15-year-old slash pine stand in Alachua

County was selected for the 2014 six boreholes and six borehole match experimental study. This site is also located just outside of Gainesville, Florida (29°43’N latitude and

82°17’W longitude) at an elevation 48 meters from average sea level. 202

We compared the yield of oleoresin from a site identified as planted with high gum trees to a non-high gum stand. These two 26-year-old stands were in Union county. The 26-year-old non-high gum experimental site is in Lake Butler, Florida

(30°03’N latitude and 82°22’W longitude) at an elevation 41 meters from average sea level. The stand that did not have the high gum selection was also managed for cattle grazing, was planted at a lower density, and contained very little understory competition.

The stand with the high gum selection contained more woody and non-woody understory vegetation.

The climate at all study sites was humid subtropical with hot wet summers and mild dry winters, and the topography was primarily flat with a 1-2% slope. The soils in the study sites ranged from poorly drained to moderately well drained. The understory vegetation varied throughout the different sites. The 26-year-old high gum stand had a thick understory, while the 26-year-old non-high gum stand had a clear understory. The two sites in Gainesville, Florida had a mild understory. Understory vegetation included saw palmetto (Serenoa repens (B.) Small.), blackberries (Rubus L. spp.), bluestems

(Andropogon spp.), gallberry (Ilex glabra (L.)), and greenbriers (Smilax L. spp.).

Borehole Tapping

An automated tapping system was used for one test at the 15-year-old slash pine experimental site located just outside of Gainesville, Florida. A drilling rig mounted on a tractor was designed to drill three interconnected boreholes. The two outer holes were

2.54 cm in diameter and were drilled at a slight downward angle towards the central hole, which was 3.81 cm in diameter and drilled at a slight upward angle (Figure 4-1).

The two-outer hole were sealed with a plastic fitting and the central hole was fitted with

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a 3.175 cm PVC Lasco male adapter fitting and collection bag. This allowed the oleoresin from the two outer holes to drain into and flow out of the main collection borehole. The collection bags were left in the field for about 90 days until weighed.

Four additional borehole tapping designs that altered the intensity or volume of wood tapped were investigated using the manual drilling (Figure C-1, Table C-1). The big-small design followed the 2-borehole tapping design apart from being drilled only

5.08 cm deep; inside the main tapping hole, a 0.9525 cm drill bit was used to drill a

15.24 cm deep hole. The opposing side design used an identical method to our standard two-holes but instead of parallel holes on the same side of the tree, the holes were placed on opposite sides of the tree. The three-borehole design had one central hole that was 3.81 cm in diameter and two inner holes drilled on each side of the central hole was also tested with the control treatment only having the central hole. The fourth design involved drilling 6 or 8 holes that were each 5.08 cm deep and placed around the tree at two levels (6 borehole test and 8 borehole test). The upper level was 10 cm higher than the lower one which was near the base of the tree as our standard design.

The holes were also placed at an equal distance from each other. In these experiments, the chemical stimulant was applied as described in Chapter 3 and a collection bag was attached.

Chemical Stimulants

2014 tapping season

For the automated drilling test, 2 ml of methyl jasmonate and a combination of methyl jasmonate with ethephon were applied to all three connected boreholes. For the high gum versus non-high gum test, for each site, the 2 ml of chemical stimulants,

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methyl jasmonate, ethephon, methyl jasmonate combined with ethephon, and a control treatment were applied, and the standard two-parallel borehole technique drilled 10.16 cm deep was used. For the opposing side test a different chemical stimulant, paraquat, was tested and applied to the boreholes along with the methyl jasmonate chemical used

+2 previously. As discussed in Chapter 2, paraquat (C12H14N2C ; 1,1’-Dimethyl-4,4’- bipyridinium dichloride) is a photosynthesis inhibiting herbicide which induces the formation of lightwood and in turn stimulates production of oleoresin (Stubbs et al. 1984 and Silverman et al. 2005). In addition to the new stimulant, a new application method was also tested. For a subset of the trees, the stimulant was applied by spraying into the borehole, while for others, the stimulant was applied in the form of a paste. Lanolin was used as the carrier for the chemical stimulants in the pastes. There were five chemical treatments and one control treatment for this test. The chemical treatments are as followed: methyl jasmonate, paraquat, methyl jasmonate paste, methyl jasmonate and paraquat, methyl jasmonate and paraquat paste.

For the test with 8 boreholes per tree, methyl jasmonate and ethephon were used as chemical stimulants, and there was also a control treatment. For the test with 6 boreholes per tree, methyl jasmonate was the only chemical stimulant tested; forty trees were drilled with 6 holes while forty were drilled with 2 boreholes 10.16 cm in depth. The

6 and 8 boreholes test received 1 mL of stimulant per borehole, while the 2 boreholes test received 2 mL per borehole.

2015 tapping season

In 2015 the triple borehole test had one main and two inner side holes, methyl jasmonate was the only chemical stimulant tested and each hole was sprayed with

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approximately 2 ml of stimulant. For the big-small test, methyl jasmonate, ethephon, methyl jasmonate combined with ethephon, and a control treatment were applied. In

2015 an experiment with 8 boreholes per tree, tested methyl jasmonate, ethephon, methyl jasmonate combined with ethephon and a control treatment were applied at 1 mL dose per borehole.

Data Collection

The same data collection methods discussed in Chapter 3 were used for the experiments in Appendix C. In addition, for the 2014 8 borehole test, all the collection bags were weighed every 7 days for the first 32 days prior to final collection.

Statistical Analysis

The chemical inducer treatments for each experimental test were randomized prior to visiting the field and each treatment was assigned to 40 trees. A one-way analysis of variance (ANOVA) was used to compare the mean oleoresin yield across treatments (chemical and borehole number) using the JMP software from SAS (SAS

Institute, 2016). Tukey’s studentized range (HSD) test was used to test for significant differences among means at an alpha level of 0.05.

To assess the individual and interactive effects of site, chemical inducers, DBH, height, and crown volume on oleoresin yield, a general linear model was fitted for each experiment using R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016;

Gilmour et al., 2015). The models differed among experiments depending on significant and measured variables and were fitted with covariates. The general model fitted was:

Y = µ + C + D + H + CV + Interactive Effects + e

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where, µ is the overall mean; C is the fixed effect of chemical inducer; D is the fixed effect of DBH; H is the fixed effect of height; CV is the fixed effect of crown volume; fixed interaction effects; and e is the random error.

The General Linear Model (GLM) approach was used to analyze the main and interactive effects as well as perform analysis of variance for the 26-year old high gum and non-high gum trees tapped. The following model was fitted:

Y = µ + C + D + S + S:C + S:D + C:D + S:C:D + e where, µ is the overall mean; C is the fixed effect of chemical inducer; D is the fixed effect of DBH; S is the fixed effect of site; S:C is the fixed interactive effect of site and chemical; S:D is the fixed interactive effect of site and DBH; C:D is the fixed interactive effect of chemical and DBH; S:C:D is the fixed interactive effect of site, chemical, and

DBH; and e is the random error.

For the big-small test, the General Linear Model (GLM) approach was used to analyze the main effects and their interactions using a 2.54 cm drill bit to bore a 5.08 cm deep hole and a 0.9525 cm drill bit to drill a 15.24 cm deep hole and those taped using the standard method. The following model was fitted:

Y = µ + T + C + D + H + CV + T:C + T:D + T:CV + T:H + C:D + C:CV + C:H

+ D:CV + D:H + H:CV + e where, µ is the overall mean; T is the fixed effect of tapping method; C is the fixed effect of chemical inducer; D is the fixed effect of DBH; H is the fixed effect of tree height; CV is the fixed effect of crown volume; T:C is the fixed interactive effect of tapping method and chemical inducer; T:D is the fixed interactive effect of tapping method and DBH;

T:CV is the fixed interactive effect of tapping method and crown volume; T:H is the fixed

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interactive effect of tapping method and tree height; C:D is the fixed interactive effect of chemical and DBH; C:CV is the fixed interactive effect of chemical and crown volume;

C:H is the fixed interactive effect of chemical and tree height; D:CV is the fixed interactive effect of DBH and crown volume; D:H is the fixed interactive effect of DBH and tree height; H:CV is the fixed interactive effect of tree height and crown volume; and e is the random error.

The oleoresin yields per unit area tapped in the six and eight borehole experiments were calculated from the cross-sectional area of the individual borehole as well as the estimated sector-shaped tapping area of the tree stem. The cross-sectional area of the borehole was estimated as a polygon with sides a-b-c-d (Figure C-2). The tapping area was considered as the area in which there was access to resin canals from the borehole tapped. The projected area was estimated from the extremities of the borehole and the center of the tapped tree (Figure C-2). As in Chapter 3, the areas were estimated using trigonometric formulas for the area of a triangle and the predicted stump diameter was calculated using the taper equation developed by Bailey (1994) for slash pine trees. To estimate the outer bark stump diameter in cm for slash pine trees the equation used was:

137.16 β Db = D ( ) hb

Where Db is the stump diameter, D is the DBH calculated at breast height (1.3716 meters or 137.16 cm), hb is the height of the stump which is equal to the height of

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borehole (assumed to be 15.24 cm for all tapped trees), and β is the constant parameter for slash pine trees (0.094138) based on a fitted equation (Bailey, 1994).

The following are the formulas used to calculate the angles to determine the area in cm2 of the projected triangle (c-x-y) or tapping area in in the six and eight boreholes experiment (Figure C-2):

bw/2 <β = sin-1 r-bd

<α = <β × 2

α Tapped Sector Area cm2 = × r2× π 360

Where r is the radius calculated from the estimated stump diameter, bd is the depth of the borehole (5.08 cm for all tapped trees) and bw is the width of the borehole (2.54 cm for all tapped trees). For the six borehole experiment, tapped sector area was multiplied by six to calculate the total tree tapped area and for the eight borehole experiment it was multiplied by eight. The tapping intensity for the trees tapped with two boreholes in the six borehole experiment was calculated using the tapping area modeled in Chapter

3 for trees greater than 10.16 cm in diameter (Figure 3-1).

The following formulas were used to calculate the tapping intensity (Figure C-2):

Tree Basal Area cm2 = (0.00007854 × d2) × 10000

Tapped Sector Area Tree Tapping Intensity (%) = × 10000 Tree Basal Area

During the 2014 8 borehole experiment, the mass of the oleoresin collection bags was recorded at day 7, 16, 24, 30, and 99. To examine the cumulative flow of oleoresin during a tapping season, a nonlinear regression model was fitted for each chemical stimulant using the JMP software from SAS (SAS Institute, 2016). Furthermore, the 209

predicted cumulative flow of oleoresin over time during a 99-day tapping season was estimated using the regression model and graphed.

Results

High Gum Yielding Slash Pine

The main effect of chemical treatment and DBH were significant. Comparison of oleoresin yield between trees reported to be high gum and non-high gum matched in age were on the threshold of being significantly different (p-value 0.051) (Table C-2;

Table C-3), although the non-high gum yielded more oleoresin. Chemical stimulant was the most effective (p-value <0.000) at predicting the yield of oleoresin (Table C-3). DBH was also a significant predictor of oleoresin yield in these stands (p-value 0.003) (Table

C-3). The site by chemical treatment interaction was the only significant interaction (p- value 0.025) (Table C-3).

Across both sites, the trees treated with methyl jasmonate, whether alone or combined with ethephon, yielded significantly more compared to those treated with ethephon or no chemical stimulant (Table C-2). Methyl jasmonate was more effective alone at stimulating oleoresin yield at both sites, yielding at least 0.24 kg more compared to the combination treatment, though not significantly different (Table C-2). At both sites, control and ethephon treatments were not significantly different (Table C-2).

The control (C) and ethephon (E) treatments performed better in the high gum stand (C:

1.258 kg vs. 1.027 kg; E: 1.262 kg vs. 1.188 kg) (Table C-2). The methyl jasmonate (M) and methyl jasmonate combined with ethephon (ME) treatments performed better at the non-high gum site (M: 2.405 kg vs. 2.087 kg; ME: 2.124 kg vs. 1.847 kg) (Table C-2).

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Big-Small

The methyl jasmonate treatments significantly increased oleoresin yield, almost double, compared to control and ethephon treatments (Table C-4). The trees treated with the methyl jasmonate stimulant yielded about 0.22 kg more oleoresin compared to the methyl jasmonate and ethephon combination treatment (Table C-4). In this experiment, ethephon was not an effective stimulant and did not yield significantly more oleoresin than the control treatment (Table C-4). There were no significant differences among the DBH, height, and crown volume of the trees tapped between the different chemical treatments (Table C-4).

A comparative test was also established at the same site to measure the yield of oleoresin with the control, ethephon, methyl jasmonate, and methyl jasmonate combined with ethephon treatments using the standard borehole tapping method. With the standard borehole method, control and ethephon stimulants gave the same yield

(Figure C-3). The control treatment yielded 0.47 kg with the standard borehole method and 0.54 kg with the big-small method (Figure C-3). The ethephon treatment yielded

0.39 kg with the standard borehole method and 0.55 kg with the big-small method

(Figure C-3). Further, methyl jasmonate treatment yielded about the same as the methyl jasmonate and ethephon combination; with methyl jasmonate yielding 1.08 kg using the standard tapping method, 1.30 kg using the big-small tapping method, and the combination treatment yielding 0.86 kg and 1.08 kg, respectively, for the standard and big-small methods of tapping (Figure C-3). The methyl jasmonate and ethephon combination treatment yielded significantly less oleoresin compared to the methyl jasmonate treatments, though it was more effective of a stimulant compared to

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ethephon alone (Figure C-3). Using the big-small method, methyl jasmonate yielded significantly more oleoresin compared to all other treatments (Figure C-3). Overall, the big-small tapping method was more effective across all chemical treatments compared to the standard method (Figure C-3).

The main effects of tapping method, chemical treatment, DBH, and height were strongly significant (p-value <0.000, <0.000, <0.000 and 0.041, respectively) (Table C-

5). No interactive effects were significant (Table C-5).

Triple Borehole Test

The triple borehole method, using one main exit hole and two smaller inner holes, was a significantly more effective tapping technique when compared to the single borehole method (Table C-6). The trees tapped using the triple borehole method yielded on average 1.341 kg of oleoresin, while the trees tapped using the single borehole method yielded 0.758 kg of oleoresin (Table C-6).

Opposing Side

The trees treated with methyl jasmonate alone or combined with paraquat, diluted in a lanolin paste or diluted in DI water and Tween 20, yielded significantly more compared to those treated with paraquat or no chemical stimulant (Table C-7). Methyl jasmonate, applied as a paste and as a liquid, was also more effective alone at stimulating oleoresin yield, yielding at least 0.113 kg more compared to the other chemical treatments (Table C-7). The methyl jasmonate and paraquat combination stimulant, applied as a paste and as a liquid, yielded the same as the control treatment and the paraquat stimulant (Table C-7). There were no significant differences found in oleoresin yield between chemical stimulants applied as a paste compared to those

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applied as a liquid. The 15-year-old trees treated with methyl jasmonate using the opposing site method yielded on average 0.757 kg, while the 14 and 16-year-old trees treated with methyl jasmonate using the standard method yielded on average 0.894 and

0.903 kg, respectively (Table C-7; Table A-1; Table A-2). Furthermore, oleoresin was collected for 96 days using the opposing side method and 73 and 85 days using the standard method.

Automated Drilling

When tapped using the automated drilling technique which introduces three interconnected holes, methyl jasmonate combined with ethephon (ME) was significantly more effective at stimulating oleoresin yield compared to methyl jasmonate (M) alone

(Table C-8; Figure C-4). These results differ from those for many of the other manually drilled tapping techniques tested and discussed, as methyl jasmonate tended to be more effective as a chemical stimulant when applied alone. In the automated trial, the

ME treatment yielded around 0.4 kg more oleoresin (Figure C-4). When conducting the field experiment, the automated drilling machine malfunctioned and some trees were only tapped with two boreholes instead of three (the central hole and the left hole).

However, this only affected the ME treatments. The number of boreholes, whether 2 or

3, did not have a significant effect on the yield of oleoresin for the ME treatment, with the 3 boreholes yielding only about 0.02 kg more oleoresin (Table C-8). The positive effect of combining ethephon with methyl jasmonate as a stimulant is highlighted by the fact that the trees drilled with 2 boreholes yielded significantly more oleoresin than the trees drilled with 3 boreholes and stimulated by methyl jasmonate only (Table C-8).

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Multi-Borehole Tests

We tested two methods which consisted of drilling 6 and 8 boreholes around the base of the stem, with three or four at two different heights. In 2014, 40 trees at one site were drilled with 6 boreholes and 40 were drilled with two boreholes; all trees were stimulated with methyl jasmonate. Overall, the trees tapped with 6 boreholes yielded significantly more oleoresin compared to those tapped with only 2 boreholes (2 boreholes: 0.946 kg; 6 boreholes: 1.526 kg) (Table C-9). However, when considering the yield per borehole, the two-borehole treatment had a significantly higher, almost double, yield compared to the 6-hole treatment (0.473 kg vs. 0.254 kg) (Table C-9).

In 2014, a similar experiment was tested at the same stand in which trees were drilled with 8 boreholes at the base of the stem and 3 chemical stimulants were tested.

When tapped using this drilling technique, methyl jasmonate was significantly more effective at stimulating oleoresin yields compared to the control and ethephon treatments (Table C-10). The ethephon treatment was not an effective stimulant as it did not result in significantly higher yields compared to the control treatment (Table C-10).

The bags in this experiment were weighed at days 7, 16, 24, 30 and once again at the end of the tapping season on day 99. This information was used to plot the predicted cumulative resin yields throughout the growing season. A nonlinear regression was used to model the average yield per day with the different chemical stimulants and the

8-borehole tapping method (Figure C-5). The non-linear equations for the obtained prediction model are shown in Figure C-5. All three regression models were effective at explaining the observed variations (control and ethephon r2 = 0.98; methyl jasmonate r2

= 0.99) (Figure C-5). The treatments did not appear to have reached their full oleoresin

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capacity at the time of collection, which suggests tapping season should be more than

100 days when 8 holes are used (Figure C-5).

In 2015, another 8-borehole test was established where trees were stimulated with 4 different chemical treatments. Methyl jasmonate was significantly more effective at stimulating the flow and yield of oleoresin compared to the control, ethephon, and methyl jasmonate combined with ethephon treatments (Table C-11). The methyl jasmonate treatments yielded close to double the quantity of oleoresin compared to the control and ethephon treatments (Table C-11). The trees treated with the methyl jasmonate stimulant yielded on average 0.70 kg more oleoresin compared to the methyl jasmonate and ethephon combination treatments (Table C-11). In this experiment, ethephon and the methyl jasmonate/ethephon combination treatment were not effective stimulants and did not yield significantly more oleoresin compared to the control treatment (Table C-11). There were no significant differences among the DBH, height, and crown volume of the trees tapped between the different chemical treatments (Table

C-11).

Tapping Intensity

The tapping intensity for tree treated with methyl jasmonate and tapped using the

2, 6 and 8 borehole methods was calculated based on the tree basal area and the area of the sector tapped. The linear relationship between the tapping intensity and total tree oleoresin yield (kg) for the six and eight boreholes was modeled and has a slope of –

0.0304 [Yield = 2.767 – 0.0304(Tapping Intensity), r2 = 0.148; p-value = 0.0022] (Figure

C-6). The overall oleoresin yield decreased as the tapping intensity increased (Figure C-

6). As expected, the tapping intensity of the trees tapped with eight boreholes was

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significantly higher than the trees tapped with six boreholes (Table C-12). Furthermore, the tapping intensity of trees tapped with two boreholes was significantly less than trees tapped with six and eight boreholes (Table C-12). The oleoresin yields between the six and eight boreholes were the same (1.53 kg and 1.71 kg, respectively), and were significantly higher than yields from the two-borehole method (0.95 kg) (Table C-12).

Since the oleoresin yield for the two borehole tapping method clustered separately, the oleoresin yield by tapping intensity was modeled only for the six and eight borehole methods. As observed in Chapter 3 and in Hodges (1995), the oleoresin yield was higher as tapping intensity increased. However, with the trees tapped with two boreholes, the yields per tapping area were not as high as the trees tapped with multiple boreholes, even with the lower tapping intensities.

Table C-13 summarizes the average total tree oleoresin yield from each optimization experiment

Discussion

The stand recorded to have high gum yielding slash pine trees did not on average yield more oleoresin compared to the non-high gum match site. When comparing the chemical stimulants at two sites, the control and ethephon treatments yielded more oleoresin in the high gum site, while methyl jasmonate and methyl jasmonate and ethephon combination treatments yielded more in the non-high gum site.

The results may be due to various other factors that were not tested in this study, such as water availability, stand density management, soil resources, understory competition and fertilization. As discussed in Chapter 2, these factors influence the production of oleoresin in conifers. Furthermore, the sites were managed very differently. The non-

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high gum match site is managed by a landowner that also raises cattle on the property, leases the area for pine straw collection and actively maintains a clear understory.

However, the high gum site is not being actively managed for understory competition.

The management of understory competition may lead to overall increases in tree productivity and growth due to the increase availability of nutrients and water. This in turn may have a positive effect on the tree’s ability to produce more oleoresin when wounded and treated with a chemical stimulant. Age also had a positive significant effect on the yield of oleoresin since the average yields of resin from the 26-year-old sites were higher than the average yields of resin from all the other 15-year-old tests.

The opposing sides experiment tested the effects of another type of stimulant

(paraquat) and a different application method (a lanolin paste) as used in other studies

(Rodrigues et al., 2008; Rodrigues and Fett-Neto, 2009; Rodrigues et al., 2011). The lanolin paste stimulants, which were slightly more time consuming to apply, did not yield significantly different yields of oleoresin. This suggests it would be more efficient to continue using a liquid stimulant when tapping pine trees for oleoresin using the borehole tapping method. The methyl jasmonate was once again more effective at stimulating the production of oleoresin. When comparing the oleoresin yields using this tapping method to the yields obtained drilling two parallel holes, this method is not effective.

When a small hole was drilled deeper into the wood in the big-small method, methyl jasmonate stimulation nearly doubled oleoresin yield compared to trees treated with ethephon and yielded more oleoresin compared to the methyl jasmonate and ethephon combination treatment. This once again suggests that methyl jasmonate is a

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more effective chemical stimulant for increasing oleoresin production in younger slash pine trees in the southeast U.S. Across all chemical treatments, the big-small tapping method produced significantly more oleoresin compared to the standard borehole method. This suggests that having a small diameter hole drilled further into the stem allows for better access of stimulant deeper in the xylem and potentially increases the number of radial resin canals and terpene synthesis thus increasing the potential yield of oleoresin.

Drilling two boreholes inside of the single exit hole (triple borehole method) was significantly more effective than drilling simply a single borehole. This may be due to the access of more resin canals from tapping extra boreholes combined with better stimulation. The method of drilling 3 holes within a single exit hole does not take much more time and does not use more supplies and thus is almost as cost effective.

Establishing an automated drilling equipment to tap pine trees for oleoresin should create a more efficient method for commercial operation. Though there were some technical issues when tapping a stand using the automated tractor operated drilling rig, a lot more trees are tapped in a shorter time increasing labor efficiency.

Since the automated system drills the three boreholes into the tree, it decreases the labor intensiveness of the operation and reduces the fatigue of labor workers because they do not have to manually drill each borehole. In this study, the methyl jasmonate and ethephon combination treatment yielded significantly more oleoresin than the methyl jasmonate treatment. It is unclear why the combination was significantly better, when methyl jasmonate alone was better in all the other manually drilled experiments.

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Tapping slash pine trees with numerous (six and eight) but shallower boreholes did not result in oleoresin yields convincingly high enough to justify using this more time- consuming tapping method. When comparing the yields of the standard borehole tapping method that was stimulated by methyl jasmonate diluted in 90% ethanol and collected after 97 days with the yields of the 8-borehole tapping method that was stimulated by methyl jasmonate diluted with Tween 20 and DI water and collected after

103 days, we see that the yields are not that much higher for the multi borehole test. In that case, the chemical stimulant has a greater effect on the yield of oleoresin. With the standard borehole tapping method, we manually drilled two holes into about 300 trees per day, but with the 8-borehole method only about 80 trees per day. Thus, tapping more trees per stand per season with similar number of hours would yield more oleoresin compared to the 8-borehole method because we would be able to tap more trees within a season. Using an automated system with the 8-borehole method would also be more complicated as it would be more difficult for a tractor operated system to navigate around each tree in the pine plantation. When considering the yield per borehole, the two-borehole treatment had almost double the oleoresin yield compared to the 6-hole treatment. This makes sense since each borehole in the 2-borehole treatment were drilled at double the depth of the 6-borehole treatment. Tapping more than two boreholes in a tree can be beneficial and lead to increase oleoresin yield per tree, however, it is important to consider the cost effectiveness of these tapping methods.

The nonlinear regressions from the 2014 8-borehole tapping treatment showed the importance of the first 30 days of tapping as about 75% of the potential oleoresin

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yield was collected during that time. This regression also made the case for a more extended tapping season as the full oleoresin capacity did not appear to have been reached at 100 days.

Table C-14 shows a cost-comparison of the automated drilling method and the manual drilling method. Based on the oleoresin yields obtained from the methyl jasmonate and ethephon combination treatment in the Alachua 3 site manual drilling method (Chapter 3) and the Alachua 3 site automated drilling experiment, the most cost-effective tapping method is the automated technique. Average oleoresin yield of trees treated with 100 mM of methyl jasmonate combined with ethephon tapped with the manual drilling technique was 0.86 kg (Table B-8). The estimated cost per tree of 100 mM methyl jasmonate and ethephon is $0.328, which would make for a total cost of

$3.00 per kg of oleoresin (Table C-14). Average oleoresin yield of trees treated with 100 mM of methyl jasmonate combined with ethephon and tapped with the automated drilling technique was 1.48 kg (Figure C-4). The estimated cost per tree for the automated technique of 100 mM methyl jasmonate and ethephon is $0.493, which would make for a total cost of $1.29 per kg of oleoresin (Table C-14).

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Table C-1. Summary of oleoresin tapping optimization experiments for slash pine in 2014-2016. Year Site Location Soil Series Site Experiment Stand Number Number Number Index Age Chemical Trees Boreholes (Years) Inducers 2014 Gainesville, FL Ponoma Sand 84 Automated Drilling 15 2 542 3 2014 Worthington NA NA High Gum 26 4 160 2 Springs, FL 2014 Lake Butler, FL Sapello Sand NA Non-High Gum 26 4 160 2 2014 Gainesville, FL Ponoma Sand 84 Opposing Side 15 6 240 2 2014 Gainesville, FL Ponoma Sand 84 2014 8 Borehole 15 3 120 8 2014 Gainesville, FL Ponoma Sand 84 2014 6 Borehole 15 1 80 6 2014 Gainesville, FL Ponoma Sand 84 2014 6 Borehole Match 15 1 40 2 2015 Gainesville, FL Ponoma Sand 84 Multiple Borehole 16 1 87 3 2015 Gainesville, FL Ponoma Sand 84 Big-Small 16 4 160 2 2015 Gainesville, FL Ponoma Sand 84 2015 8 Borehole 16 4 160 8

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Table C-2. Chemical treatment and improved genetic effects on average oleoresin yield per tree (kg) from slash pine trees using the standard borehole tapping method in 2014. Chemical Treatment Genetically Improved Not Genetically Improved (High Gum) Control (no chemical) 1.258b 1.027b Ethephon 1.262b 1.188b Methyl Jasmonate 2.087a 2.405a Methyl Jasmonate/Ethephon 1.847a 2.124a Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table C-3. Summary of main and interactive effect on oleoresin yields in high gum and non-high gum site based on a general linear model. Effect DF Den DF F-statistic p-value Chemical 3 296 41.87 <0.000** DBH 1 296 6.43 0.003* Site 1 296 3.61 0.051 Site:Treatment 3 296 2.35 0.025* Site:DBH 1 296 0.62 0.346 Treatment:DBH 3 296 1.18 0.319 Site:Treatment:DBH 3 296 0.34 0.795 Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table C-4. DBH, height, crown volume, and effect of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2015 using the big-small borehole tapping method. Chemical Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg) Average SE Average SE Average SE Average SE Control (no chemcial) 22.66a 0.26 20.32a 0.21 47.77a 3.60 0.530b 0.05 Ethephon 22.44 a 0.21 20.02a 0.20 47.48a 3.40 0.550b 0.04 MeJa 22.52 a 0.23 19.99a 0.22 49.12a 4.06 1.303a 0.08 MeJaE 22.59a 0.27 20.01a 0.23 45.35a 3.43 1.084a 0.08 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). The notations MeJa and MeJaE, respectively represent the chemical treatments methyl jasmonate and methyl jasmonate combined with ethephon.

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Table C-5. Summary of main and interactive effect on oleoresin yields in site drilled using the big-small borehole tapping method based on a general linear model. Effect DF Den DF F-statistic p-value Treatment 1 285 18.94 <0.000** Chemical 3 285 82.56 <0.000** DBH 1 285 30.59 <0.000** Height 1 285 4.83 0.041* Crown Volume 1 285 13.67 0.65 Treatment:DBH 1 285 7.90 0.07 Treatment:Chemical 3 285 1.54 0.15 Treatment:Crown Volume 1 285 0.37 0.36 Treatment:Height 1 285 0.23 0.84 Chemical:DBH 3 285 1.96 0.11 Chemical:Crown Volume 3 285 0.41 0.58 Chemical:Height 3 285 1.57 0.18 DBH:Crown Volume 1 285 0.01 0.59 DBH:Height 1 285 0.39 0.89 Height:Crown Volume 1 285 0.80 0.37 Note: P-values with * superscripts are significant based on a test with p-value <0.05, while p-values with ** superscripts are significant based on a test with p-value <0.01.

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Table C-6. Effects of tapping treatment, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the triple borehole (two inner holes) tapping method and stimulated by methyl jasmonate. Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg) Average SE Average SE Average SE Average SE One Borehole 23.95a 0.46 19.98a 0.22 59.99a 3.97 0.758b 0.05 Triple Borehole 24.19a 0.35 20.00a 0.22 68.96a 5.17 1.341a 0.07 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table C-7. Effects of chemical stimulant and DBH on oleoresin yield (kg) when tapping slash pine trees in 2014 using the opposing side borehole tapping method. The following were the chemical stimulants: control, methyl jasmonate (MeJa). methyl jasmonate and paraquat (MeJaP), methyl jasmonate and paraquat paste (MeJaPPs), methyl jasmonate paste (MeJaPs), and paraquat. Chemical Treatment DBH(cm) Oleoresin Yield (kg) Average SE Average SE Control (no chemical) 21.667a 0.56 0.527b 0.04 MeJa 21.642a 0.61 0.757a 0.06 MeJaP 21.156a 0.51 0.641ab 0.05 MeJaPPs 20.770a 0.48 0.621ab 0.05 MeJaPs 21.899a 0.45 0.754a 0.05 Paraquat 20.723a 0.45 0.519b 0.04 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table C-8. Effects of chemical stimulant and number of boreholes on oleoresin yield (kg) when tapping slash pine trees in 2014 using the automated borehole tapping method. Holes 2 3 Chemical Treatment Average SE Average SE MeJa NA NA 1.061b 0.03 MeJaE 1.475a 0.05 1.493a 0.04 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). The notations MeJa and MeJaE, respectively represent the chemical treatments methyl jasmonate and methyl jasmonate combined with ethephon.

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Table C-9. Effects of chemical stimulant and DBH on total oleoresin yield (kg) and oleoresin yield per borehole (kg) when tapping slash pine trees in 2014 using the 6 borehole and standard borehole tapping method. Treatment DBH(cm) Oleoresin Yield (kg) Oleoresin Yield per Borehole (kg) Average SE Average SE Average SE Two Boreholes 20.619a 0.36 0.946b 0.10 0.473a 0.02 Six Boreholes 19.958a 0.25 1.526a 0.07 0.254b 0.02 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table C-10. Effects of chemical stimulant on oleoresin yield (kg) when tapping slash pine trees in 2014 using the 8-borehole tapping method. Chemical Treatment Oleoresin Yield (kg) Average SE Control (no chemical) 0.770b 0.06 Ethephon 0.808b 0.06 Methyl Jasmonate 1.071a 0.06 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table C-11. Effects of chemical stimulant, DBH, height and crown volume on oleoresin yield (kg) when tapping slash pine trees in 2015 using the 8-borehole tapping method. Treatment DBH(cm) Tree Height (m) Crown Volume (m3) Oleoresin Yield (kg) Average SE Average SE Average SE Average SE Control (no chemcial) 21.520a 0.43 19.318a 0.23 42.981a 4.20 0.906b 0.09 Ethephon 22.332a 0.43 19.503a 0.23 48.653a 4.26 0.848b 0.09 MeJa 21.980a 0.43 19.929a 0.23 44.598a 4.20 1.708a 0.09 MeJaE 21.283a 0.43 19.670a 0.23 41.079a 4.20 1.005b 0.09 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). The notations MeJa and MeJaE, respectively represent the chemical treatments methyl jasmonate and methyl jasmonate combined with ethephon.

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Table C-12. Effects of number of boreholes on tapping intensity and oleoresin yield (kg) when tapping slash pine trees using the 6 and 8 borehole taping method. Number of Boreholes Tapping Intensity Oleoresin Yield (kg) Average SE Average SE Two 11.066c 0.32 0.945b 0.07 Six 35.052b 0.72 1.526a 0.08 Eight 40.152a 1.26 1.708a 0.13 Note: The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05). Tapping intensity is calculated based on the cross- sectional area tapped at the base of the tree. The model for the 6-borehole method is shown in Figure C-2 and the model for the 2-borehole method is shown in Figure 3-1.

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Table C-13. Summary of optimization treatments, number of boreholes, collection days, chemical inducers and oleoresin yields. Stand Number of Collection Mean Oleoresin Experiment Chemical Age Boreholes Days Yield (kg) 15 3 155 MeJa 1.061 Automated 15 3 155 MeJaE 1.493 Drilling 15 2 155 MeJaE 1.475 26 2 176 Control 1.258 26 2 176 Ethephon 1.262 High Gum 26 2 176 MeJa 2.087 26 2 176 MeJaE 1.847 26 2 176 Control 1.027 26 2 176 Ethephon 1.188 Non-High Gum 26 2 176 MeJa 2.405 26 2 176 MeJaE 2.124 15 2 96 Control 0.527 15 2 96 MeJa 0.757 15 2 96 MeJaP 0.641 Opposing Side 15 2 96 MeJaPPs 0.621 15 2 96 MeJaPs 0.754 15 2 96 Paraquat 0.519 15 8 99 Control 0.77 2014 8 Borehole 15 8 99 Ethephon 0.808 15 8 99 MeJa 1.071 15 6 167 MeJa 1.129 15 6 169 MeJa 1.944 2014 6 Borehole 15 6 172 MeJa 1.723 15 6 174 MeJa 1.848 2014 6 15 2 178 MeJa 0.946 Boreholes Match 16 1 120 MeJa 0.758 3 Hole Test 16 3 120 MeJa 1.341 16 2 94 Control 0.529 16 2 94 Ethephon 0.55 Big-Small 16 2 94 MeJa 1.303 16 2 94 MeJaE 1.084 16 8 103 Control 0.906 16 8 103 Ethephon 0.848 2015 8 Borehole 16 8 103 MeJa 1.708 16 8 103 MeJaE 1.005 16 2 97 Alcohol 1.507 Alcohol 16 2 97 Tween 0.936

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Table C-14. Estimated cost per tree of borehole tapping method to collect oleoresin. Calculated costs are based on productivity rates of tapping 26.7 trees per hour for the manual drilling and 61 trees per hour for the automated drilling. Adapted from Hodges and Ferguson (2011). Manual Drilling Automated Drilling Quantity Unit Cost per Quantity Cost per Cost Category / Item Units Units Unit Price per tree Price Tree per tree Tree Supplies Spouts: 1 x 5 in. PVC pipe, or 2 Ea. $0.150 $0.300 1 Ea. $0.150 $0.150 custom molded PE Collection bags, Nylon/PE laminate, 2 Ea. $0.090 $0.180 1 Ea. $0.090 $0.090 6x20 in. Cable ties for bag closure 2 Ea. $0.010 $0.020 1 Ea. $0.010 $0.010 Plugs for machine-drilled boreholes 2 Ea. $0.037 $0.073 Ethephon, 55% active ingredient 2 Dose $0.026 $0.052 3 Dose $0.026 $0.079 Methyl jasmonate – 100 mM 2 Dose $0.138 $0.276 3 Dose $0.138 $0.414 Distilled water 2 Dose $0.001 $0.002 3 Dose $0.001 $0.002 Diesel fuel for drill machine and 0.050 Gal. $3.00 $0.150 0.075 Gal. $3.50 $0.263 utility vehicle Gasoline and oil for power drill 0.004 Gal. $4.50 $0.019 Subtotal supplies $1.00 $1.081 Labor Borehole Treatment/Installation (3- 0.163 Hr. $8.50 $1.388 0.050 Hr. $8.50 $0.422 man crew, average productivity rate) Oleoresin harvesting (3-man crew, 0.017 Hr. $8.50 $0.143 0.017 Hr. $8.50 $0.143 average productivity) Subtotal labor $1.530 $0.565 Note: Equipment costs depreciated over useful life of 250,000 trees; does not include highway transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080.

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Table C-14. Continued. Manual Drilling Automated Drilling Quantity Quantity Unit Total Cost per Unit Cost per Equipment per per Total Cost Price Cost Tree Price Tree crew crew Off-road utility vehicle (Kubota 1 $10,000 $10,000 $0.040 1 $10,000 $10,000 $0.040 RTV900XT) Automated drilling machine and 0 1 $55,000 $55,000 $0.220 prime mover (Volvo L20F) Power drill (Sthil BT45) 2 $450 $900 $0.004 0 Drill bits: 2.54 cm 3 $25 $75 $0.000 6 $25 $150 $0.001 Chemical sprayer 2 $100 $200 $0.001 2 $100 $200 $0.001 Small tools: mallet, machete, pliers, 4 $50 $200 $0.001 4 $50 $200 $0.001 measuring cup Rubber gloves (for chemical mixing 100 $3 $300 $0.001 100 $3 $300 $0.001 and resin handling) Fuel can: 2 gal. 2 $15 $30 $0.000 0 Fuel cans: 15 gal. 2 $40 $80 $0.000 Buckets: 5 gal. 10 $5 $50 $0.000 10 $5 $50 $0.000 Barrels: 55 gal. capacity 50 $30 $1,500 $0.006 50 $30 $1,500 $0.006 Subtotal equipment $11,755 $0.054 $65,980 $0.271 Total All Costs $2.584 $1.917 Predicted average yield per tree at 0.86 1.48 100 days (Kg) Total Cost Per Kg Resin $3.004 $1.295 Note: Equipment costs depreciated over useful life of 250,000 trees; does not include transportation equipment. The cost of 1 kg of methyl jasmonate from Bedoukian Research is $3080.

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Figure C-1. Diagrams of borehole tapping designs. A) Standard boreholes drilled manually with a gas-powered drill. B) Standard boreholes drilled manually on opposite sides of the tree. C) Boreholes drilled using a tractor mounted automated system, (d) borehole drilled manually with two shallower wide holes and two longer holes drilled with a 0.9525 cm drill bit. E) Six boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. F) Eight boreholes drilled manually in two levels, the black-marked holes drilled at the base and the grey-marked holes drilled 10.16 cm higher. G) Three borehole system drilled manually with one central borehole and two interior boreholes. All boreholes were drilled using a 2.54 cm drill bit; apart from the longer borehole in D which was drilled using a 0.9525 cm drill bit, the central borehole in the automated system (B) which was drilled with a 3.175 cm bit and the boreholes in the triple borehole experiment (G) which had a counterbore drilled with a 3.175 cm bit and a 2.54 cm drill bit.

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Figure C-2. Calculations for the cross-sectional tapping area and individual hole area model for the trees tapped using the 8-borehole method. c is the center of the tree, r is the radius calculated using the predicted stump diameter, bd represents the borehole depth, and bw represents the borehole width. The tapping area is the triangle c-y-x. This diagram is also used to calculate tapping area intensity using the 6-borehole method.

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Figure C-3. Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in 2015 using the standard method and the big-small tapping method. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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Figure C-4. Chemical effects on oleoresin yield (kg) with standard errors when tapping slash pine trees in North Florida in 2014 using the automated drilling technique. The means with different letter superscripts were significantly different based on Tukey’s HSD test (p-value <0.05).

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1200

1000

800

600

400 Oleoresin Yield (g) Yield Oleoresin

200

0 0 20 40 60 80 100 120 Day Since Treatment

Control Ethephon Methyl Jasmonate

Figure C-5. Predicted cumulative flow of oleoresin (g) by chemical treatment since day of tapping treatment at the 2014 8 borehole test. The following equations correspond to the oleoresin flow when trees are stimulated by the different treatments: control: y = 802.529 * (1 – 0.911 e-0.032D; r2 = 0.98); ethephon: y = 836.953 * (1 – 0.922 e-0.033D; r2 = 0.98); methyl jasmonate: y = 1108.968 * (1 – 0.991 e-0.035D; r2 = 0.99). Where y corresponds to oleoresin yield (g) and D corresponds to number of days since treatment.

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Figure C-6. Bivariate fit of total tree oleoresin yield (kg) in slash pine by tapping intensity using the 6 and 8 borehole methods. The r2 for the linear relationship between tapping intensity and average total tree yield is 0.148 (p-value 0.0022).

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APPENDIX D PSEUDO BACKCROSS HYBRID STUDY

Introduction

The two primary conifer species planted in the southeast United States for timber production and pulpwood are slash pine (Pinus elliottii Engelm. Var. elliottii) and loblolly pine (Pinus taeda L.). The two species have some distinct phenotypic and growth differences. Forestry companies tend to prefer planting loblolly pine, which accounts for

120,000 km2 of land, as it usually responds better to nutrition management and intensive silvicultural treatments yielding greater total volume at earlier ages (Xiao et al.,

2003). During early developmental stages, loblolly pine is more productive compared to slash pine (Xiao et al., 2003). While loblolly pine outperforms slash pine, slash pine grows better on very poorly drained sites (Borders and Harrison, 1989). Compared to slash pine, loblolly allocates more biomass to crown production, and thus tends to have more primary and secondary branching and larger crown widths (Xiao et al., 2003). As a result, compared to slash pine, loblolly pine tends to have a higher leaf area and poorer stem form caused by the higher number of branches (Xiao et al., 2003; Muñoz Del Valle et al., 2011). The allocation of biomass to crown development in loblolly pine promotes increased tree size (Xiao et al., 2003). Furthermore, slash pine is less resistant to fusiform rust (Cronartium quercuum), a fungal disease that can be fatal to pine trees, but is more resistant to wind damage (Muñoz Del Valle et al., 2011).

Methods

Study Area

In January 2013, the CFGRP and FBRC established the pseudo backcross hybrid study. This study is located at the Murphree Well Field protection area in 242

northeast Gainesville, Florida (29°44’50.0” N, 82°19’44.5”W). The study area is owned and managed by the Weyerhaeuser Company (formerly Plum Creek Timber Company), and was established to evaluate the performance of progeny and identify beneficial backcross hybrids for tree improvement programs.

In September 2012, the site was raked and double bedded, and prior to planting the site received a broadcast application of 48 ounces of Chopper. The site was then planted in January 2013, and following a 6-week survival check, dead trees were replaced with replants in March 2013. Following planting, release herbicide treatment of

13 ounces of Oustar were applied using broadcast application in May 2013 and hand application of 100 gallons of roundup with 6 ounces per gallon in June 2014. The site was fertilized using a hand broadcast at five feet around each tree between late May and early June 2014. Replicate 1 received a low treatment of 200# per acre DAP and replicate 2 received a high treatment of 500# per acre 10-10-10 with micronutrients.

Finally, the site received a herbicide treatment of 48 ounces garlon and 64 ounces glyphosate per acre.

The study location has a humid subtropical climate with hot wet summers and mild dry winters, and the topography was flat with a slope between 0 and 2%. The study was established on a somewhat poorly drained site and the dominant soil series was

Newnan. The Newnan series is a Spodosol and is classified as a sandy, siliceous, hyperthermic Oxyaquic (USDA Natural Resources Conservation Service, 1993a). The understory vegetation included saw palmetto (Serenoa repens (B.) Small.), blackberries

(Rubus L. spp.), bluestems (Andropogon spp.), gallberry (Ilex glabra (L.)), greenbriers

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(Smilax L. spp.), lopsided Indiangrass (Sorghastrum nutans (L.) Nash) and a variety of other native grasses.

Study Design and Genetic Material

The backcross hybrid study consisted of slash pine and loblolly pine hybrid backcrosses and parent material. This study consisted of one open pollinated slash pine parent (E63xMix), one open pollinated loblolly pine (LobxOP) and one loblolly elite family (Filler) (Table D-1; Figure D-1). Furthermore, three pseudo-backcrosses between an elite P. elliottii x an elite P. taeda F1 hybrid (2904), with two P. elliottii and one P. taeda family were planted (Table D-1; Figure D-1). The following are the three pseudo- backcross hybrid species: [(2904 x 22056) (FS loblolly); (2904 x E63) (FS slash); and

(2904 x open pollinated) (half-sib slash)] (Table D-1; Figure D-1). There was a total of

3420 trees planted; 1710 in each replicate (Table D-1; Figure D-1). Half of the trees in this study were managed with high intensity fertilization (replicate 2), while the other half were managed with operational fertilization (replicate 1). The two replicate plots were separated with three border rows.

The genetic materials for this study were provided by Plum Creek and the

CFGRP and the seeds were germinated and grown at the ArborGen nursery in containers. Plum Creek supplied the OP loblolly seeds while the CFGRP supplied the

OP slash pine seeds from a mix of two full sib families (E63xE93 and E63xE82). A

Latinized row-column design with single-tree plots spaced at 2.13ˣ3.66 m, as described by Muñoz Del Valle et al. (2011), was used to plant the trial. Each replicate contained

95 plots; replicate 1 was planted along 11 rows while replicated 2 was planted along 10 rows. Figure D-2 outlines the planting layout for the study.

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Phenotypic Measurement

The backcross site has been measured annually for mortality, disease and height. Between November 2015 and March 2016, age 3 status (mortality and disease), stem form (ramicorn and forking), height (m), DBH (cm), and crown width (m) along and across planting beds were measured for the entire stand. For this study, a ramicorn branch was defined as a branch that was obviously bigger than other branches on the tree and that was growing at less than 45-degree angle from the main stem. A fork was defined as the main stem split into two stems of similar or equal size. Heights of the tree was measured from the base to the tip of the primary bud using a telescoping pole.

DBH was measured using a diameter tape and the crown width along and across the planting bed was measured using a standard tape measure. The number of primary branches and secondary branches at two nodes (3 and 5 from the base of the tree) were counted for all pseudo-backcross trees and for a sample of the parents. If the tree had a dead top or had severe needle dieback, the branch characteristics were not measured. Furthermore, only trees with a height of at least 1.829 meter were measured for their branch characteristics. A code system was used to measure status of the tree and considered if the tree was healthy, had fusiform rust galls on the branch or stem, dead top from rust or unknown causes, and mortality from rust and unknown causes

(Figure D-3).

Statistical Analysis

The DBH, height, crown and branch data from the pseudo backcross hybrid study were analyzed in R 3.1.1 and ASReml-R v.3 (R Development Core Team, 2016;

Gilmour et al., 2015). The data were analyzed for normality and the residual plots were

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examined. The data were analyzed using a general linear mixed model with replicate, family, and replicate by block as fixed effects. The least squares mean was calculated using lsmeans R package based on a general linear mixed model. Narrow-sense heritabilities of individual phenotypic traits were calculated based on the following individual model with the constructed pedigree:

Yij = µ + Ri + Ri:Bj + ped(I) + eij

th th where Yij corresponded to the phenotypic trait in the i replicate (I = 1 or 2) and i

th replicate by j block (j = 1 to 95), Ri corresponded to the fixed replicate effect, Ri:Bj corresponded to the fixed replicate by block effect, ped(I) corresponded to the random individual pedigree effect, and ej corresponded to the random residual effect.

Results

All phenotypic traits were statistically significant with a p-value ≤ 0.01, for differences among families. Furthermore, all phenotypic traits apart from primary and secondary branches at nodes 3 and 5 were statistically different with a p-value of 0.01 when comparing high versus operational fertilization (Table D-2). Pure slash pine had the largest diameters by year 3, though not significantly different to the pseudo backcross loblolly (SLLL) and the second pseudo backcross slash (SSSL) (Table D-2).

For crown traits, the pure slash pine family was unexpectedly significantly larger than all other families measured (Table D-2; Table D-3). The pseudo backcross loblolly pine individuals were significantly taller than the other families and had more primary branches (Table D-2; Table D-3).

The pure loblolly family had more primary branches at node 3 and significantly more primary branches at node 5 compared to all other families (Table D-2; Table D-3).

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As expected, the pure loblolly family and the pseudo backcross loblolly family had significantly more secondary branches compared to all other families at both nodes 3 and 5 (Table D-2; Table D-3). The pure slash pine trees had on average 9.3 secondary branches at node 3 and 5.9 secondary branches at node 5, while the pure loblolly pine trees had on average 27.7 and 28.7 secondary branches at nodes 3 and 5, respectively, which is between 3 and 5 times more branches (Table D-2). On average, the number of secondary branches in the pseudo backcross individuals was somewhere in between the number of secondary branches from the slash and loblolly individuals (Table D-2).

The pseudo backcross slash pine trees had significantly less secondary branching compared to the pseudo backcross loblolly trees (Table D-2). The number of secondary branches at nodes 3 and 5 were the same in pure loblolly and the pseudo backcross loblolly trees (Table D-3).

The pseudo backcross loblolly family was more susceptible to fusiform rust, accounting for about 56% of total rust occurrence in the study (Table D-4). 9.0% of the trees in the pseudo backcross family has either branch or stem galls. Overall mortality in this study at the end of the growing season was 4.5 % (Table D-4), excluding the mortality from the slash pseudo backcross. Stem form of the pseudo backcross loblolly was poorer compared to the other families, with more forking and ramicorn branching

(Table D-5).

The estimated narrow-sense heritabilities for all measured traits, based on an individual pedigree model with fixed replicate and replicate by block effect and random individual pedigree effects are presented in Table D-6. Estimates of narrow-sense heritability for the various phenotypic traits measured were relatively low and ranged

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from 0.046 to 0.195. The number of primary branches and secondary branches at node

5 had the highest heritability estimate (h2 = 0.195) (Table D-6). The heritability estimates for DBH and primary branches at node 3 were low (h2 = 0.046 and h2 = 0.059, respectively) (Table D-6). The heritability estimates for the other traits were slightly higher (height h2 = 0.094, crown h2 = 0.102, primary branch h2 = 0.194, secondary branch node 3 h2 = 0.133, primary branch node 5 h2 = 0.100, secondary branch node 5 h2 = 0.195) (Table D-6).

Discussion

At the FBRC and CFGRP’s backcross hybrid stand, several full-sib families were compared for various growth traits. The pure slash pine trees in this study had wider stem diameters. Compared to loblolly pine trees, slash pine allocates more dry matter to stem wood and stem bark (Colbert et al. 1990). Surprisingly, the average crown size in the pure slash pine trees was significantly larger than all the other families. Although it is well documented that loblolly pine tends to have larger crowns than slash pine (Xiao et al., 2003), it may not be the case for very young trees. Loblolly and pseudo backcross loblolly trees were found to have on average more primary and secondary branches. In their study, Colbert et al. (1990) reported a greater dry matter partitioning to crown foliage and branches in loblolly pine compared to slash pine. These inter-whorl branches allow loblolly pine to more efficiently intercept light and reduces self-shading at higher leaf areas, which would make them more productive at higher densities

(Colbert et al. 1990). However, at lower planting densities with lower leaf areas, slash pine is more productive than loblolly pine (Colbert et al. 1990). The loblolly pine pseudo

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backcross showed signs of hybrid vigor as it had more primary branches and was taller than all other families, including the pure slash and pure loblolly.

Muñoz Del Valle et al. (2011) and Lopez-Upton et al. (1999), reported that loblolly pine tends to be less susceptible to fusiform rust compared to slash pine, although certain families in both species are more resistant. However, in our study, overall rust occurrence was low, but the pseudo backcross loblolly family had 9.0% of trees infected with a branch or stem rust gall. This may be due to the higher rate of these seedlings having nurse rust prior to planting. The narrow-sense heritability estimates for most of the growth traits at age 3 were relatively low as reported in many other studies (Lopez-Upton et al., 1999; Li et al., 2007). The heritability estimates for the number of primary branches and the number of secondary branches at node 5 were the highest.

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Table D-1. Summary of genotypes planted in each replicate of the CFGRP pseudo backcross hybrid study. Family # Individuals Replicate 1 # Individuals Replicate 2 Total # Individuals 2904 x 22056 615 604 1219 2904 x OP 99 99 198 Filler 135 150 285 2904 x E63 407 381 788 E63 x Mix 246 254 500 Lob x OP 208 222 430 Grand Total 1710 1710 3420

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Table D-2. Least square means with standard errors for phenotypic traits measured at the pseudo-backcross hybrid study. Pure slash and loblolly pine families are SSSS and LLLL, respectively, and backcross hybrids with slash and loblolly are (SSSL 1 and 2, and SLLL, respectively. Year 3 Measurements SSSS SSSL (1, 2) SLLL LLLL Height (m) 3.31 (0.04) 3.18 (0.06) 3.58 (0.02) 3.35 (0.04) 3.45 (0.03) DBH (cm) 5.72 (0.08) 5.20 (0.12) 5.63 (0.05) 5.41 (0.08) 5.64 (0.07) Crown (m) 2.08 (0.02) 1.85 (0.03) 1.98 (0.01) 1.92 (0.02) 1.98 (0.02) Primary Branch 27.48 (0.47) 35.72 (0.76) 39.17 (0.29) 36.58 (1.09) 33.82 (0.39) Primary Branch 2.64 (0.08) 3.16 (0.13) 2.97 (0.05) 3.20 (0.18) Node 3 2.77 (0.07) Secondary Branch 9.28 (0.93) 23.71 (1.50) 29.22 (0.58) 27.74 (2.14) Node 3 14.74 (0.77) Primary Branch 2.89 (0.08) 3.18 (0.13) 3.46 (0.05) 3.84 (0.18) Node 5 3.46 (0.07) Secondary Branch 5.85 (0.87) 17.39 (1.40) 25.00 (0.54) 28.67 (1.99) Node 5 10.13 (0.72)

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Table D-3. Tukey significance group letters of the least square means for phenotypic traits (alpha < 0.05) recorded in Table D-2. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively). Year 3 Measurements SSSS SSSL 1 SSSL 2 SLLL LLLL Height (m) BC C B A BC DBH (cm) A B A A AB Crown (m) A C B B BC Primary Branch C B B A B Primary Branch Node 3 C A BC AB AB Secondary Branch Node 3 D B C A AB Primary Branch Node 5 C BC AB AB A Secondary Branch Node 5 D B C A A Note: The different Tukey group letters were significantly different based on Tukey’s HSD test (p-value <0.05).

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Table D-4. Disease and mortality observed at the end of the 3rd growing season in the two replicate treatments of the pseudo-backcross hybrid. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively). Replicate 1 represents the operational fertilization treatment, while replicate 2 represents the higher intensity fertilization. The top line in each family represents disease at mortality in both replicate plots. Disease and Mortality Status by Environment Family Rust Rust Mortality Pitch Moth Mortality SLLL 8.97% 0.06% 1.73% 0.47% Replicate 1 4.06% 0.06% 0.94% 0.18% Replicate 2 4.91% 0% 0.79% 0.29% SSSL1 1.17% 0% 0.32% 0.21% Replicate 1 0.56% 0% 0.12% 0.12% Replicate 2 0.61% 0% 0.20% 0.09% SSSL2 2.96% 0.03% 1.72% 2.08% Replicate 1 1.67% 0.03% 0.73% 0.99% Replicate 2 1.29% 0% 0.99% 1.08% SSSS 2.46% 0.18% 1.17% 0.44% Replicate 1 1.11% 0.12% 0.56% 0.18% Replicate 2 1.35% 0.06% 0.61% 0.26% LLLL 0.56% 0% 0.42% 0.20% Replicate 1 0.15% 0% 0.23% 0.00% Replicate 2 0.41% 0% 0.18% 0.20% Study Means 16.12% 0.27% 5.36% 3.39%

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Table D-5. Percentage of trees with stem form issues at the end of the 3rd growing season in the pseudo-backcross hybrid study. Pure slash and loblolly pine families were measured (SSSS and LLLL, respectively), as well as backcross hybrids with slash and loblolly (SSSL and SLLL, respectively). Replicate 1 represents the operational fertilization treatment, while replicate 2 represents the higher intensity fertilization. The top line in each family represents stem form in both replicate plots. Stem Form by Environment Family None Forking Ramicorn Branching Both SLLL 11.38% 5.55% 15.69% 5.74% Replicate 1 6.12% 2.81% 7.97% 2.52% Replicate 2 5.26% 2.74% 7.72% 3.22% SSSL1 2.63% 0.84% 2.30% 0.42% Replicate 1 1.44% 0.48% 1.02% 0.16% Replicate 2 1.18% 0.35% 1.28% 0.26% SSSL2 13.01% 3.12% 5.96% 0.86% Replicate 1 6.12% 1.53% 3.70% 0.57% Replicate 2 6.89% 1.59% 2.26% 0.29% SSSS 9.57% 1.44% 4.08% 0.26% Replicate 1 4.88% 0.67% 1.88% 0.13% Replicate 2 4.69% 0.77% 2.20% 0.13% LLLL 5.59% 1.59% 5.45% 0.86% Replicate 1 2.78% 0.89% 2.55% 0.41% Replicate 2 2.81% 0.70% 2.90% 0.45% Study Means 42.18% 12.54% 33.48% 8.14%

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Table D-6. Narrow sense heritability estimates calculated for phenotypic traits measured at the end of the 3rd growing season in the pseudo-backcross hybrid study. Year 3 Measurements Phenotypic Trait Narrow Sense Heritability Standard Error Height 0.094 0.058 DBH 0.046 0.043 Crown 0.102 0.065 Primary Branch 0.194 0.071 Primary Branch Node 3 0.059 0.055 Secondary Branch Node 3 0.133 0.050 Primary Branch Node 5 0.100 0.063 Secondary Branch Node 5 0.195 0.070

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Figure D-1. Pedigree of the genotypes planted in the pseudo backcross hybrid study using a Latinized row-column design.

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Figure D-2. Layout of the pseudo backcross hybrid study using a Latinized row-column design.

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Figure D-3. Codes used for the pseudo backcross hybrid study. Part A shows the tree status codes and part B shows the stem form codes.

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BIOGRAPHICAL SKETCH

Marie Jennifer Lauture was born in Port-au-Prince, Haiti in 1992, and moved to

Miami, Florida at age 5. In 2009, after graduating high school, she moved to Gainesville,

Florida to pursue an undergraduate degree at the University of Florida. As an undergraduate student, Jennifer began working with Dr. Gary Peter and his graduate students as a field and laboratory technician. In 2013, Jennifer received her Bachelor of

Science degree in Wildlife Ecology and Conservation. In 2013, she joined the School of

Forest Resources and Conservation at the University of Florida to pursue her graduate study under the supervision of Dr. Gary Peter. She received her PhD from the

University of Florida in the winter of 2017.

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