© 2012 Marc Anthony Hughes - University of Floridaufdcimages.uflib.ufl.edu/UF/E0/04/53/33/00001/HUGHES_M.pdf · 2013-08-15 · Marc Anthony Hughes May 2013 Chair: Jason A. Smith

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THE EVALUATION OF NATURAL RESISTANCE TO LAUREL WILT DISEASE IN REDBAY (Persea borbonia)

By

MARC ANTHONY HUGHES

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

2013

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© 2012 Marc Anthony Hughes

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To my parents, for all their love and support

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ACKNOWLEDGMENTS

I would like to thank Dr. Jason Smith, my major advisor, for his guidance,

support, and help throughout my doctoral degree program. I am thankful to Drs. Randy

Ploetz, Albert Mayfield III, Ariena van Bruggen, and Pamela Soltis, members of my

advisory committee, for their expertise, counsel, and instruction. For the invaluable help

provided during travel and field expeditions I would sincerely like to acknowledge

Samuel Glucksman, and Adam Black for all greenhouse and nursery assistance. For

their assistance in statistical matters, I would like to thank Hong Ling Er and James

Colee. In regards to molecular and genetics work accomplished during my studies, I

would like to thank Dr. Claire Anderson, Kathy Smith, and Tyler Dreaden. For his

generosity in allowing the use of the quarantine facilities at the Division of Plant

Industry, I would like to acknowledge Dr. Tim Schubert. For the help and support I have

garnered throughout my graduate education, I am thankful to the Forest Pathology lab

members at the University of Florida. To those not mentioned, who have contributed to

my success; I offer my sincere gratitude. Finally, I would like to thank my parents, Ralph

and Cristina Hughes, for their unending support.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES ............................................................................................................ 8

LIST OF FIGURES ........................................................................................................ 10

ABSTRACT ................................................................................................................... 12

CHAPTER

1 AN INTRODUCTION TO THE LAUREL WILT PATHOSYSTEM ............................ 14

The Hosts ............................................................................................................... 15 The Vector .............................................................................................................. 16

The Pathogen ......................................................................................................... 17 The Search for Laurel Wilt Resistance in Redbay .................................................. 18

2 VEGETATIVE PROPAGATION OF PUTATIVELY LAUREL WILT RESISTANT REDBAY (Persea borbonia) ................................................................................... 26

Introduction ............................................................................................................. 26

Methods and Materials............................................................................................ 27 Field Sites ......................................................................................................... 27

Experiment 1 .................................................................................................... 28 Experiment 2 .................................................................................................... 30 Statistical Analysis ............................................................................................ 31

Results .................................................................................................................... 31 Experiment 1 .................................................................................................... 31

Experiment 2 .................................................................................................... 32 Discussion .............................................................................................................. 32

3 RESPONSES OF SWAMP BAY (Persea palustris) TO THE LAUREL WILT PATHOGEN, Raffaelela lauricola ........................................................................... 42

Introduction ............................................................................................................. 42 Methods and Materials............................................................................................ 44

Inoculum Preparation and Quantification.......................................................... 44

Swamp Bay Inoculations .................................................................................. 44 Recovery of R. lauricola from Swamp Bay ....................................................... 45

Statistical Analysis ............................................................................................ 45 Results .................................................................................................................... 46

Inoculum Preparation and Quantification.......................................................... 46 Swamp Bay Inoculations .................................................................................. 46 Comparison between Inoculum Levels and Locations ..................................... 48

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Recovery of R. lauricola from Swamp Bay ....................................................... 48

Discussion .............................................................................................................. 49

4 GENETIC DIVERSITY STUDIES OF THE LAUREL WILT PATHOGEN (Raffaelea lauricola) SUGGEST A CLONAL POPULATION IN THE UNITED STATES, WITH ASIAN ISOLATES ALSO PATHOGENIC TO SWAMP BAY (Persea palustris) AND AVOCADO (Persea americana) ........................................ 62

Introduction ............................................................................................................. 62 Materials and Methods............................................................................................ 64

Fungal Isolates ................................................................................................. 64 DNA Extraction ................................................................................................. 65 Amplified fragment length polymorphism (AFLP) analysis ............................... 66 Microsatellite Analysis ...................................................................................... 67

Sequencing Reactions ..................................................................................... 68 Pathogenicity Tests .......................................................................................... 68

United States isolates ................................................................................ 68 Asian isolates ............................................................................................. 69

Disease severity scale ............................................................................... 69 Results .................................................................................................................... 70

Amplified Fragment Length Polymorphism (AFLP) Analysis ............................ 70

Microsatellite Analysis ...................................................................................... 71 Sequencing Reactions ..................................................................................... 72

Pathogenicity Tests .......................................................................................... 72 United States isolates ................................................................................ 72 Asian isolates ............................................................................................. 73

Discussion .............................................................................................................. 73

5 THE SCREENING OF REDBAY (Persea borbonia) SELECTIONS AGAINST THE LAUREL WILT PATHOGEN, Raffaelea lauricola............................................ 89

Introduction ............................................................................................................. 89

Methods and Materials............................................................................................ 90 Field Sites and Disease Pressure Surveys....................................................... 90 Beetle Trapping Surveys .................................................................................. 91

Inoculation Experiment 1 .................................................................................. 91 Inoculation Experiment 2 .................................................................................. 92 Statistical Analysis ............................................................................................ 93

Results .................................................................................................................... 94

Field Sites and Disease Pressure Surveys....................................................... 94 Beetle Trapping Surveys .................................................................................. 95 Inoculation Experiment 1 .................................................................................. 95 Inoculation Experiment 2 .................................................................................. 96

Discussion .............................................................................................................. 97

LIST OF REFERENCES ............................................................................................. 117

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BIOGRAPHICAL SKETCH .......................................................................................... 126

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LIST OF TABLES

Table page 2-1 Exp 1. Effects of rooting hormone and bottom heat on rootability, number of

roots, and root length on redbay. ........................................................................ 37

2-2 Exp 2. Effects of media mixtures on mean rootability, number of roots, and root length on redbay .......................................................................................... 39

3-1 CFUs for inoculum concentration experiment. .................................................... 52

3-2 Summary of disease development parameters for swamp bays inoculated with R. lauricola. ................................................................................................. 58

3-3 Nonlinear regression analysis of laurel wilt disease progression. ....................... 59

3-4 Contingency table analysis denoting R. lauricola recovery from root and stem tissues ................................................................................................................ 60

3-5 Contingency table analysis denoting R. lauricola recovery from the root tissue with and without the presence of vascular discoloration........................... 61

4-1 Host, collection dates, and origin of Raffaelea lauricola cultures ........................ 77

4-2 Summary of AFLP fragment analysis of R. lauricola isolates ............................. 80

4-3 Pathogenicity of AFLP polymorphic isolates from United States on swamp bay. ..................................................................................................................... 86

4-4 Pathogenicity of Asian isolates of R. lauricola on swamp bay ............................ 87

4-5 Virulence of Asian isolates of R. lauricola on avocado ....................................... 88

5-1 Selected redbay trees and plot characteristics for laurel wilt resistance study. 102

5-2 Experiment 1. Responses of redbay clones to artificial inoculation with R. lauricola (105 conidia). ...................................................................................... 108

5-3 Experiment 1. Summary of analyses of variance for redbays inoculated with R. lauricola (105 conidia)................................................................................... 109

5-4 Experiment 1. Contrast analysis of redbays inoculated with R. lauricola (105 conidia). ............................................................................................................ 110

5-5 Experiment 2. Responses of redbay clones to artificial inoculation with R. lauricola (3.0 x 103 conidia). ............................................................................. 113

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5-6 Experiment 2. Summary of analyses of variance for redbays inoculated with R. lauricola (3.0 x 103 conidia). ......................................................................... 115

5-7 Experiment 2. Contrast analysis for redbay inoculatied with R. lauricola (3.0 x 103 conidia). ................................................................................................... 116

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LIST OF FIGURES

Figure page 1-1 Laurel wilt disease cycle within redbay (P. borbonia). ........................................ 21

1-2 Redbay (P. borbonia) foliage exhibiting initial symptoms of laurel wilt ................ 22

1-3 Redbay (P. borbonia) tree that has completely succumbed to laurel wilt. .......... 23

1-4 Boring dust “tubes” in redbay (P. borbonia) produced during the excavation activity of the redbay ambrosia beetle (X. glabratus). ......................................... 24

1-5 Extensive boring dust production on an exposed portion of a dead redbay (P. borbonia) ............................................................................................................ 25

2-1 The propagation process .................................................................................... 36

2-2. Experiment 1. Comparison of the mean longest root of the propagated cutting per field collection site. ............................................................................ 38

2-3 Experiment 2. Rooted redbay cuttings percentage per rooting medium ............ 40

2-4 Experiment 2. Rooting percentage of live redbay cuttings only ......................... 41

3-1 Development of laurel wilt symptoms on swamp bay after inoculation with 102 conidia of R. lauricola per plant .......................................................................... 53




3-5 Disease development in relation to inoculum concentration (log10) .................... 57

4-1 Map of SE United States indicating location and host species of R. lauricola isolates ............................................................................................................... 81

4-2 United States AFLP fragment analysis dendrogram of R. lauricola.isolates ....... 82

4-3 Aligned microsatellite and flanking region sequence reads for the cpl primer pair ..................................................................................................................... 83

4-4 Aligned microsatellite and flanking region sequence reads for the chk primer pair ..................................................................................................................... 84

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4-5 Microsatellite and flanking region sequence dendrogram of R. lauricola isolates ............................................................................................................... 85

5-1 Beetle trap used for the capture of X. glabratus ............................................... 101

5-2 Redbay plot for laurel wilt resistance experiment 2 .......................................... 107

5-3 Experiment 1. Redbays showing wilt symptoms 35 days post inoculation ...... 111

5-4 Experiment 2. Redbays showing wilt symptoms 40 days post inoculation ...... 112

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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

THE EVALUATION OF NATURAL RESISTANCE TO LAUREL WILT DISEASE IN

REDBAY (Persea borbonia)

By

Marc Anthony Hughes

May 2013

Chair: Jason A. Smith Major: Plant Pathology

Laurel wilt is a vascular disease of the redbay (Persea borbonia) and other

members of the Lauraceae plant family within the United States. The disease is caused

by the introduction of the fungus Raffaelea lauricola into the host’s woody tissue by its

vector, the redbay ambrosia beetle (Xyleborus glabratus). A project was initiated to

develop a method for the location and screening of germplasm that is putatively

resistant to laurel wilt, with a future goal of their re-establishment into previously

affected habitats. Studies were conducted to: 1) Locate and propagate redbay survivors

within stands with high mortality due to laurel wilt, 2) Assess the effects of inoculum

density on disease development, 3) Analyze the genetic and pathogenic diversity of R.

lauricola from populations within the United States and Asia, and 4) Screen redbay

clones for resistance against R. lauricola using artificial inoculation trials.

Propagation studies revealed an average rooting percentages of 19.5% - 37.0%

among all treatments. Results from these experiments indicate the treatment regime of

treating cuttings with 0.3% indole - 3 - butyric acid (IBA) gel, placing cuttings in a 3:1

perlite to vermiculite mixture and treating with bottom heat, to be the optimal protocol

tested. The results from the inoculum density studies showed that as few as 100

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conidia per inoculation were sufficient to incite disease in swamp bay plants, with more

conidia increasing the consistency of disease development. The greenhouse location

was more conducive to disease development than the outside nursery location. The

analysis of the pathogen’s genetic diversity revealed a clonal population of R. lauricola

within the United States, with a close relation to Taiwanese samples found through the

analysis of microsatellite loci. Pathogenicity tests revealed uniform virulence among and

between North American and Asian isolates on swamp bay and avocado. Redbay

resistance screening trials were conducted from propagated material within a field plot.

Three clones (FGC, HIA, and HIL) were disease-tolerant, based on significantly lower

disease parameter scores. Results from the experiments conducted will be used to

further refine a laurel wilt resistance screening program with additional red bay clones to

be tested.

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CHAPTER 1 AN INTRODUCTION TO THE LAUREL WILT PATHOSYSTEM

Laurel wilt is a vascular disease of members of the Lauraceae plant family in the

United States. Discovered during an unprecedented outbreak of redbay (Persea

borbonia L. Spreng) mortality around Savannah, Georgia (GA) in 2003-2004 (17), the

disease is caused by an exotic fungus, Raffaelea lauricola T.C. Harr., Fraedrich &

Aghayeva, which has an exotic vector, the redbay ambrosia beetle Xyleborus glabratus

Eichhoff (17, 33). The hypothesized disease cycle begins when females of X.

glabratus, guided by host volatiles, locate susceptible host trees (Figure 1-1)

(4,30,41,71). Initial tunneling by X. glabratus into the host’s sapwood releases R.

lauricola spores from its mandibular mycangia (pocket-like structures that harbor fungi)

(3, 17, 33), thereby inoculating the tree. However, since ambrosia beetles usually

construct galleries and lay eggs in stressed or recently dead trees, tunnels in healthy

trees are likely aborted without brood production (17,100). Subsequently, as the fungus

colonizes the host, tyloses and gums are produced in vessels, thereby impeding water

and nutrient transport and leading, ultimately, to wilting and death of foliage and the tree

(Figures 1-1 to 1-3) (42,43). During this period of rapid wilt and death, the host

becomes suitable for gallery and brood production, leading to mass attack that is

evidenced by entrance holes, galleries and extensive wood powder that is produced

during tunneling activity (3,17) (Figure 1-1, 1-4 and 1-5). Larvae feed upon R. lauricola

and possibly other ambrosial fungi until development is complete, an estimated 30-60

days, with variation likely dependent on temperature and host (30,72). As mature

females disperse with their pathogenic symbiont and identify new hosts, the laurel wilt

disease cycle is completed (Figure 1-1). To date laurel wilt has spread throughout the

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Atlantic coastal plain into Alabama (AL), Florida (FL), Georgia, South Carolina (SC),

North Carolina (NC), and Mississippi (MS) (96), causing vast mortality in forest and

urban communities.

The Hosts

The only documented hosts for laurel wilt are members of the Lauraceae that

reside within the United States either as natives, agricultural crops, or ornamentals (17,

40,63,75,83). The predominant host during the laurel wilt epidemic has been redbay,

an aromatic evergreen native to the coastal and lowland areas of the southeastern

United States (6,8,11,17). In most cases, the introduction of X. glabratus to new areas

results in the rapid development of laurel wilt, especially where redbay or other hosts

are abundant (17,22,81). Redbay’s closest relatives, swamp bay (Persea palustris

(Raf.) Sarg) and silk bay (Persea humilis Nash) are also highly susceptible (17, 40).

Silk bay, occupying only the scrubland habitats of Florida may be in great peril due to its

limited geographic range and high susceptibility (16, 40). Avocado (Persea americana

Mill.), is also highly susceptible, with the front of the epidemic now extending into

commercial production areas in southern Florida (17,63,74,75). Sassafras (Sassafras

albidum (Nuttall) Nees) was also found susceptible; and with its large geographic range

could presumably enable an expansion of the area that is impacted by the disease

(17,53,83). Northern spicebush (Lindera benzoin (L.) Blume) has also been affected by

laurel wilt, however, a recent study demonstrated that X. glabratus showed very little

attraction to this host, with no evidence of brood development within cut bolts. The

result from the aforementioned study suggests that northern spicebush may have a

minimal role in the spread of laurel wilt (64).

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Additional species of concern are pondspice (Litsea aestivalis (L.) Fern.) and

pondberry (Lindera melissifolia (Walter) Blume). Both species are extremely rare due to

limited habitat, with pondspice threatened in Georgia and South Carolina, and

pondberry listed as federally endangered (18, 39). Camphortree (Cinnamomum

camphora (L.) Sieb.), an Asian native, has been found displaying branch wilt in natural

areas, yet mortality is rare, suggesting tolerance (84). California laurel (Umbellularia

californica (Hook. & Arn.) Nutt.), a native of California, develops dieback symptoms after

artificial inoculation with R. lauricola, with an additional study demonstrating X.

glabratus’ attraction and ability to breed in camphortree (64).

The Vector

The redbay ambrosia beetle is a recent introduction into the United States, being

first detected in 2002 in early monitoring and detection traps at Port Wentworth, GA

(27,79). X. glabratus is a scolytid beetle native to south-east Asia, where it is

associated with Lauraceous and other trees native to the area (79,100). Like many

ambrosia beetles, X. glabratus exhibits inbreeding and a haplo-diploid sex

determination system, in which males are flightless, lack mycangia, haploid, and born

from unfertilized eggs, while females are capable of flight and diploid (52,78).

Emergence ratios are close to 40 females per male (72). As all other ambrosia beetles,

X. glabratus relies solely on ambrosial fungi as a food source. To aid in this symbiotic

relationship, X. glabratus has a pair of specialized pocket-like structures called

mycangia that harbor R. lauricola and other microbes (17,33,34).

The mystery of why this species has become a pest of healthy trees may be

explained by the olfactory mismatch theory, in which volatile profiles of live trees

resemble those of hosts in their original habitat (4,41). Research into the chemical

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ecology of the vector’s selection behavior suggests that the sesquiterpene, α-copaene

is a primary attractant, with others likely involved (31,49,71). The olfactory mismatch

theory may help explain why many ambrosia beetles that are considered pests of live

trees tend to be exotic in origin, including: Xylosandrus compactus Eichhoff,

Megaplatypus mutatus Chapuis, and Euwallacea fornicatus Eichhoff (2,10,15,41).

The Pathogen

Raffaelea lauricola and other members of this anamorphic genus are wood-

inhabiting fungi in the Ophiostomatales, which includes the Dutch elm disease

pathogens Ophiosoma ulmi Buisman C. Nannf and O. novo-ulmi Brasier (1,7,33).

Members of Raffealea form close associations with ambrosia beetles, which carry them

to their hosts in mycangia. The fungi colonize the sapwood and walls of the beetle’s

gallery, forming tightly packed masses of conidiophores (sporodochia) that can be

grazed upon by the developing insects (3,20,34). Once emerged, the next generation

of ambrosia beetles locates new hosts.

R. lauricola was found to be the primary fungal symbiont of X. glabratus; it

probably arrived with the beetle when it was introduced to the USA (35,36). Evaluation

of the vector’s mycangia revealed as many as six Raffaelea species, with hundreds to

thousands of R. lauricola propagules present per beetle (34,35,36). Like most

ambrosial fungi that inhabit stressed or recently dead trees, R. lauricola behave in a

saprophytic manner on extant hosts in its native host range (77). Its method of

pathogenicity within new American hosts remains a mystery. No other Raffaelea

species causes such rapid and systemic death in hosts. Raffaelea quercivora Kubono

et Shin. Ito and Raffaelea quercus-mongolicae K.H. Kim, Y.J. Choi & H.D. Shin,

symbionts of the ambrosia beetles Platypus quercivorus Murayama and Platypus

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koryoensis Murayama, respectively, kill oak species in Japan and Korea (50,54).

However, tree mortality relies on the mass attack of host trees by the vectors. Death of

the affected oaks is a function of mass localized tyloses and necrosis in response to the

symbionts and physical damage caused by numerous vector galleries, rather than

systemic infection (68,89,102). In contrast, only a few X. glabratus beetles or a single

point inoculation with R. lauricola is necessary to induce systemic symptom

development and death in susceptible hosts (17,40,62,75). The contact between these

non-coevolved organisms (fungus and host), which leads to rapid mortality, is proposed

to be the effect of an overly aggressive host response of gum and tylose formation that

walls off the invading fungus but effectively halts vascular function (43). More research

is needed to fully understand the complex interactions between host, pathogen, and

vector in these and similar pathosystems.

The Search for Laurel Wilt Resistance in Redbay

No cost-effective management strategies have been developed for laurel wilt in

forest communities. In general, the great susceptibility of redbay and other host

species, the ability of very few beetles to establish new infection centers, and economic

constraints that face those who manage diseases in natural areas all contribute to this

challenging situation.

In 2006, the Georgia Forestry Commission attempted to eradicate the disease

from Jekyll Island by removing and destroying diseased redbays. Although the effort

was temporarily successful, X. glabratus colonized stumps of the removed trees,

thereby perpetuating the vector and disease on the island (Personal communication-

Bates). Sanitation recommendations include the chipping of infected and infested

material, which physically destroys the vector and renders host material unsuitable for

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brood development (60, Personal communication- Spence). When chipping is

unfeasible, leaving infected trees or cut logs on site may keep infestations localized

(60).

Research into vector control has focused on attractants for improved early

detection and chemical control; further research is needed before specific

recommendations can be made (31,49,71,72). In specific cases where vectors have

not established large populations, sanitation may minimize disease impact. For

example, strategic monitoring and sanitation have helped reduce the effects of Dutch

elm disease in certain cities of the United States (37), and almost completely eradicated

the disease in New Zealand (19). Although prophylactic application of the fungicide

propiconazole via macroinfusion successfully protected avocado and redbay, this

strategy is unfeasible in a forest setting (61,76).

A better option for redbay conservation would be the discovery, development and

utilization of laurel wilt-tolerant germplasm. Although the previously mentioned

management techniques can be effective in some situations, reforestation with this

species might only succeed with tolerant germplasm. Experience with Dutch elm

disease and chestnut blight provides useful information for the present work on redbay.

Four primary methods of genetic tree improvement are commonly employed: 1)

hybridization between susceptible and resistant species, 2) hybridization among

superior selections of susceptible species, 3) selection of wild, naturally occurring

putatively resistant trees, and 4) use of genomic or marker assisted selection and

biotechnology. Each of these techniques has been used in the development of Dutch

elm disease resistant American elms and blight resistant American chestnuts

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(25,80,82,85). In the present work the third approach was explored for redbay, since

resources were not available for the others. Tolerant selections so identified might be

immediately useful, but could also provide germplasm for use in traditional breeding

schemes, as in the first and second approaches above.

The following experiments represent the first steps taken in the development of a

laurel wilt resistance screening program in redbay. This work utilized the practical

knowledge of others when screening for resistance to forest tree diseases. The primary

goal of this research was to identify disease-tolerant redbay germplasm for

reforestation, conservation, and subsequent resistance breeding. Ancillary, secondary

goals were to: 1) develop a method to clonally propagate redbay; 2) assess genetic and

pathogenic diversity in R. lauricola; 3) optimize inoculation protocols; and 4) develop a

method with which redbay germplasm could be rapidly screened for response to this

disease.

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Figure 1-1. Laurel wilt disease cycle within redbay (P. borbonia).

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Figure 1-2. Redbay (P. borbonia) foliage exhibiting initial symptoms of laurel wilt, wilting

and bronze discoloration.

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Figure 1-3. Redbay (P. borbonia) tree that has completely succumbed to laurel wilt.

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Figure 1-4. Boring dust “tubes” in redbay (P. borbonia) produced during the excavation activity of the redbay ambrosia beetle (X. glabratus).

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Figure 1-5. Extensive boring dust production on an exposed portion of a dead redbay (P. borbonia), indicating mass attack and colonization by the vector (X. glabratus).

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CHAPTER 2 VEGETATIVE PROPAGATION OF PUTATIVELY LAUREL WILT RESISTANT

REDBAY (Persea borbonia)

Introduction

Redbay (Persea borbonia) is a common hardwood tree of the coastal lowlands

and plains of the southeastern United States. This attractive medium sized tree is

known for having a dense and often rounded crown of drooping branches packed with

single layers of leathery, evergreen leaves (11). Depending on the site, this aromatic

member of the Lauraceae can grow to a height of around 18 to 21 m with a trunk

diameter from 60 to 90 cm in the forest (8,11,16). Redbay, along with live oak (Quercus

virginiana Mill.), and cabbage palm (Sabal palmetto (Walter) Lodd. ex Schult. & Schult.

F.) forms the canopy of maritime hammock forests in the southeastern USA (16).

Redbay serves as the larval host for the Palamedes Swallowtail (Papilio palamedes

Drury.) and Spicebush Swallowtail (Papilio troilus Linnaeus) butterflies (Figure 2-1a),

and its fruit is a nutritional source for a variety of birds, rodents, and other mammals

(8,11,28,29). In 2002, the exotic redbay ambrosia beetle (Xyleborus glabratus Eichhoff)

was discovered in monitoring traps at Port Wentworth, Georgia (27,79). By 2003, mass

mortality of redbays in and around Savannah, Georgia and the southern South Carolina

area became apparent, and the responsible pathogen was determined to be one of the

beetle’s fungal symbionts, Raffaelea lauricola T.C. Harr., Fraedrich & Aghayeva.

(Ophiostomataceae) (17,33). This newly discovered disease became known as laurel

wilt, which is spread by the deposition of R. lauricola spores during the wood-boring

activities of the redbay ambrosia beetle. Once introduced into a redbay host, the

pathogen rapidly causes complete crown wilt and death. In the years following its

discovery, the coastal forests and their redbay populations have been devastated by

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laurel wilt, with the mortality of large redbays reaching over 90% in some affected sites

(17,22,81). Currently, almost all redbays commercially available are grown from seed,

which is easily available from mature fruiting trees in September to October (6). Due to

the rapid loss of mature redbays from the coastal plain, research has begun to locate

and monitor healthy redbay individuals with putative resistance. Clonal propagation is

essential in order to develop a laurel wilt resistance screening program for redbays,

better understand the possible mechanisms for this putative resistance, establish

breeding populations with potentially resistant individuals, and re-plant affected areas

with resistant germplasm. An established method in the literature for vegetatively

propagated redbay was absent, and based on what is known about their close relatives,

swamp bay (Persea palustris) (12) and avocado (Persea americana) (73), vegetative

propagation may be problematic. The purpose of this study was to investigate factors

influencing the vegetative propagation of putatively laurel wilt-resistant redbays. The

investigation was divided into two experiments. The first experiment evaluated the

effects of rooting hormones and bottom heat on rooting of cuttings, whereas the second

experiment investigated the effects of various potting media on redbay rootability.

Methods and Materials

Field Sites

Six field locations were chosen along the Atlantic coastal plain and barrier islands

of Florida, Georgia, and South Carolina, with two sites selected per state. The sites

were chosen due to their prior abundance of redbays that had been decimated by laurel

wilt disease. By selecting sites that already have tremendous redbay mortality, it allows

for a natural method to select for resistance to this disease (data not presented here).

The sites in Florida were Ft. George Island near the Kingsley Plantation (30°24’35”N

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81°25’50”W) and Fort Clinch State Park (30°40’05”N 81°26’03”W). Georgia sites

included the Cumberland Island National Seashore Park (30°51’53”N 81°26’59”W) and

the maritime forest of St. Catherines Island (31°38’00”N 81°09’34”W). The South

Carolina sites were Hunting Island State Park (32°21’58”N 80°26’40”W) and Edisto

Beach State Park (32°30’41”N 80°18’23”W).

After an initial survey of the field location, 8 to 20 healthy/asymptomatic trees >

7.5 cm dbh were selected for monitoring and propagation per site. The putatively

resistant candidate trees were visually tagged and global positioning system (GPS)

coordinates recorded. Because cuttings were collected at various times of the year as

field locations and research permits became available, collection time was excluded as

an experimental variable; however, special care was taken to collect only semi-

hardwood cuttings. Large branch cuttings were taken using a pole pruner and then

sectioned into smaller segments by hand pruner. Plant material was placed in 13-gallon

kitchen bags, labeled, and placed on ice within coolers. Coolers were placed into the

walk-in cooler at the University of Florida School of Forest Resources and

Conservation. The branch material was trimmed into single-leader ramets about 15 to

25 cm in length, 4 to 8 mm in diameter, and with 2 to 4 remaining leaves.

Experiment 1

Ten redbay trees were selected from six field locations for a total of sixty trees.

Forty cuttings per tree were randomly assigned to four treatments, with 10 ramets per

treatment/pot. All cuttings were placed in 12.5 L black plastic pots filled with a 3:1

perlite/fine vermiculite mixture, with polyester fiber to cover drainage holes. The four

treatments tested were the following: 1.) powdered indole-3-butyric acid (IBA) 0.1% with

bottom heat, 2.) powdered IBA 0.1% without bottom heat, 3.) IBA gel 0.3% with bottom

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heat, and 4.) IBA gel 0.3% without bottom heat. Bottom heat was provided by heavy

rubber propagation heat mats (Pro-Grow Supply Corp., WI) set to approximately 10°C

above ambient (22 ± 4°C). Due to the scarce number of asymptomatic redbays within

the region, the knowledge that severe harvesting for cutting material can increase their

attractiveness to the vector (30), and previous failures to propagate redbay without a

rooting compound; negative (non-hormone) controls, with and without bottom heat were

used only for a random sub-set of 12 trees (6 heat/ 6 no heat) in order to avoid over

sampling from the putatively resistant germplasm. Before the application of IBA, a fresh

cut was made using a hand shears and then the cut end was quickly dipped in a 3%

volume per volume (v/v) sodium hypochlorite solution, followed by a freshwater rinse.

Cuttings were then dipped into the IBA for 5 s and placed into holes dibbled within the

12.5 L pots, with ten cuttings per pot. Pots were then arranged in a completely

randomized design on a mist bench in a climate-controlled greenhouse at the University

of Florida, Gainesville (Figure 2-1b). Mist was applied for 20 s every 16 min. Dead

cuttings were removed and plants were treated for scale insects and mealy bugs as

needed with 3-In-1 Insect, Disease, & Mite Control (Bayer CropScience LP, NC).

After seven months, plants were removed from mist for processing. To free the

cuttings from their rooting medium without damaging the roots, pots were placed in a

water tub until the medium floated, allowing the cuttings to be released (Figure 2-1c).

The following variables were recorded: number of cuttings rooted per pot, average

number of roots per cutting, and average longest root per cutting. Cuttings were then

transplanted into 1 gallon black plastic pots and returned to a shaded bench in the

greenhouse to acclimate for 4 to 6 weeks and later to outside tables (Figure 2-1d).

30

Experiment 2

Twenty-five redbay trees were selected from the Ft. Clinch and the St.

Catherines Island field sites combined. Forty cuttings per each selected tree were

randomly assigned to four treatments, with 10 ramets per treatment/pot. The four

media mixtures tested were the following: 1.) 3:1 perlite-fine vermiculite (3:1 P-V), 2.)

1:1:1 perlite-Canadian peat moss-Cypress sawdust (1:1:1 P-PT-SD), 3.) 1:1 perlite-

Canadian peat moss (1:1 P-PT), and 4.) 2:1:1 perlite-Cypress sawdust-seedling soilless

mix (2:1:1 P-SD-S). All rooting media mixtures were placed in 12.5 L black plastic pots

with polyester fiber to cover drainage holes. Before the application of IBA a fresh cut

was made using hand shears and then the cut ends were quickly dipped in a 3% (v/v)

sodium hypochlorite solution, followed by a freshwater rinse. Cuttings were then dipped

into the powdered IBA 0.1% for 5 s and placed into holes dibbled within 12.5 L pots,

with ten cuttings per pot. Pots were arranged on a bench in a completely randomized

design under an automated mist system in a climate-controlled greenhouse at the

University of Florida, Gainesville. Mist was run for 20 s every 16 min. Dead cuttings

were removed and plants were treated for scale insects and mealy-bugs as needed with

3-In-1 Insect, Disease, & Mite Control (Bayer CropScience LP, NC). After seven

months plants were removed from mist for processing. To free the cuttings from their

rooting media, pots were floated in a water tub and flooded until cuttings were released

(Figure 2-1c). The following variables were recorded: number of cuttings rooted per pot,

average number of roots per cutting for each pot, and average longest root per cutting

for each pot. Cuttings were then transplanted into 1 gallon black plastic pots and

returned to the greenhouse to acclimate for 4 to 6 weeks, and later to outside tables

(Figure 2-1d).

31

Statistical Analysis

For some clones all cuttings died due to disease or showed remarkable disease

symptoms in the mist bench; these were removed and not considered in the dataset.

The experimental units in these experiments were pots, not individual cuttings. Data

were analyzed using SAS 9.3 for Windows (SAS Institute Inc., Cary, NC) using the

GLIMMIX procedure. Percentage variables were analyzed using logistic mixed models.

Mixed models were used to account for correlation to do cuttings arising from the same

tree, and trees originating from the same island. All other models were analyzed using

linear mixed models. Type III tests of fixed effects were used to analyze the effects of

treatments and for the presence of treatment interactions, with a P = 0.05. In

experiment 1 the effects of hormone, heat, and cutting provenance were analyzed, as

well as their interactions. In experiment 2 the effects of rooting media, cutting

provenance, and their interactions were analyzed. Tukey’s Honesty Significant

Difference (HSD) test was used for multiple comparisons in all models with a P = 0.05.

Results

Experiment 1

Cutting rooting percentages between treatments were similar. Cuttings rooted at

a rate of 24.1% to 26.9%, with a heat x location interaction detected (F= 2.8, P= 0.02)

(Table 2-1). If the cuttings stayed green and viable over the seven month time period

on the mist bench, then 60.4% to 68.3% of those cuttings produced roots, without

significant differences between treatments; however; a heat x location interaction was

detected (F = 3.1, P = 0.01) (Table 2-1). The treatments that produced roots (over 0.5

cm) had an average of 2.7 to 3.6 roots per cutting without significant differences

between treatments and without interactions (Table 2-1). The average longest root of

32

the cuttings was between 11.3 and 13.3 cm in length, and the treatments failed to affect

the average longest root (Table 2-1). However, the average longest root per cutting

was significantly different when the location of tree origin was compared (F = 4.4, P =

0.002) (Table 2-1). The average longest root from the Edisto Beach State Park trees

(19.9 cm) was significantly longer than trees from Cumberland Island National Seashore

Park (7.6 cm), St. Catherines Island (10.2 cm), Hunting Island State Park (11.0 cm), and

Fort Clinch State Park (11.3 cm) (Figure 2-2). All non-hormone treated negative control

plants failed to root, regardless of the presence of heat (data not shown).

Experiment 2

Significant differences were observed for some of the different rooting media

used, with no detectable interactions. The highest percentage of rooted cuttings overall

were grown in the 3:1 P-V medium (Table 2-2, Figure 2-3), and this medium also

contained the most cuttings that remained viable over the seven month period that

rooted (Table 2-2, Figure 2-4). In contrast, the 2:1:1 P-SD-S and 1:1:1 P-PT-SD

mixtures contained the lowest number of rooted cuttings (Table 2-2, Figure 2-4).

Cuttings in all mixtures produced between 1.7 to 3.1 roots on average per cutting,

without significant differences or interactions among treatments (Table 2-2). The 1:1 P-

PT mixture produced the longest roots on average, with no significant differences or

interactions between treatments (Table 2-2)

Discussion

The data from experiment 1 alone indicated that the redbay cuttings responded

similarly to the IBA treatments. These results indicated that neither bottom heat nor

form of IBA rooting product contributed significantly to rooting ability. Although the 0.3%

rooting gel with heat treatment did contain the highest scores for: rooting percentage

33

among survivor cuttings, mean number of roots produced, and mean longest roots;

these means were not significantly different from to the other treatments. All non-

treated controls completely failed to root by the end of the experiment, regardless of

heat regime; indicating that rooting compounds are necessary for propagation.

Previous propagation research of other woody species illustrates that use of auxins can

generate more rooted cuttings over non-hormone treated controls; however, the specific

concentration needed for optimal rooting can be species-specific (5,12,69,90,91). The

choice of propagation medium used was very important in overall rooting success, with

3:1 perlite-fine vermiculite mix containing the highest percentage of rooted cuttings

compared to the 1:1:1 perlite-peat-sawdust and 2:1:1 peat-sawdust-seedling soilless

mix. The 1:1 peat-perlite mix was statistically similar to the 3:1 perlite-fine vermiculite

mix. The most significant (and most difficult to quantify) aspect in the success of

vegetative redbay propagation was the difference between clones; (P = 0.0001, data not

shown) which illustrates the importance of each parental trees’ genetic background and

vigor in regards to propagation when compared to other redbay individuals. Previous

propagation research on the closely related avocado showed that the genetic

background of the parent tree was one of the most important factors in relation to

rooting success, with the Mexican races rooting better than both the Guatemalan and

West Indian races. However, even with the general success of rootability being linked

to the avocado’s race, results were inconsistent among cultivars and individual clones

(26,73). This variability of rooting success among clonal propagation of avocado

cultivars accounted for the abandonment of this system for the more efficient and

productive use of grafted containerized trees (73).

34

Interwoven with tree genotype, tree and cutting vigor seemed to be an important

factor in rooting success. Although vigor ratings were absent from the experiments,

visual observations indicated that the more vigorous redbays in the field tended to yield

healthier cutting material, which in turn rooted better in these experiments compared to

cuttings from weak or slowly growing trees. Parent trees grown under higher light levels

appeared to give rise to more robust cuttings, whereas trees grown in heavy shade

tended to produce weak, brittle, and often diseased cuttings. The relative health of the

cuttings was also variable within the tree’s canopy, with top canopy branches appearing

much more robust than shaded stems from the interior and lower canopy. Future

rounds of propagation from our clonal collection will most likely yield better rooting

success simply because of the increased nutrition, vitality, and the high light conditions

of our potted material compared to wild shade grown redbays.

Finding a successful method for vegetative propagation redbays is important for

species preservation, reforestation efforts, and laurel wilt resistance research programs.

The current effort to collect and maintain redbay seed for conservation is an essential

part of securing the diversity of the species; however, long term seed storage is

problematic. Research involving the storage and preservation of seeds has shown that

after 24 months viability decreases rapidly, making long term storage impractical with

current methods (97). The collection and propagation of germplasm from extant

redbays in the forests devastated by laurel wilt allows for the preservation of trees with

genetic backgrounds that may be useful in resistance screening and future reforestation

efforts in affected areas. The ability to generate redbay clones continually and

continued collection of R. lauricola isolates allows for in depth studies of the host-

35

parasite interactions and the possible genetic factors that mediate these relations. With

the ever-decreasing availability of containerized redbay seedlings and the increasing

need of plant material for laurel wilt research and replanting projects, the need for a

practical vegetative propagation method is valid and essential. Our study established a

primary framework for redbay vegetative propagation involving simple and readily

available materials. Although the time of year that the cuttings were taken was

excluded from this experiment, research on the close relative swamp bay indicates that

seasonality may be an important factor in rooting formation (12). Future research will

explore the seasonality and other propagation parameters that may increase the

productivity and efficiency of our system.

36

Figure 2-1. The propagation process A) Spicebush swallowtail larva feeding on redbay leaf, B) Experiment 1 containers on mist bench. Containers in foreground have bottom heat provided by propagation mat, C) Rooted redbay cuttings after removal from propagation media, and D) Stecklings of redbay two months after re-potting in open nursery area

37

Table 2-1. Exp 1. Effects of rooting hormone and bottom heat on rootability, number of roots, and root length on redbay. Powder-

Heat Powder- No Heat

Gel- Heat Gel- No Heat

Location (L)

IBA (I) Heat (H)

H x I H x L L x I H x L x I

% Rooted

24.1 ± 3.0 A

24.4 ± 3.0 A

24.2 ± 3.0 A

26.9 ± 3.1 A

F = 1.6 P = 0.2

F = 0.4 P = 0.5

F = 0.6 P = 0.5

F = 0.4 P = 0.5

F = 2.8 P = 0.02

F = 1.0 P = 0.4

F = 0.8 P = 0.6

Rooting % of Live Cuttings Only

60.4 ± 5.0 A

62.1 ± 5.0 A

68.3 ± 4.8 A

67.3 ± 4.7 A

F = 0.8 P = 0.6

F = 3.0 P = 0.1

F = 0.0 P = 0.9

F = 0.1 P = 0.7

F = 3.1 P = 0.01

F = 1.8 P = 0.1

F = 0.6 P = 0.7

Avg. # Roots per Cutting

2.7 ± 2.0 A

3.0 ± 2.0 A

3.6 ± 2.0 A

3.6 ± 2.0 A

F = 1.5 P = 0.2

F = 3.2 P = 0.1

F = 0.3 P = 0.6

F = 0.2 P = 0.7

F = 1.6 P = 0.2

F = 0.6 P = 0.7

F = 0.4 P = 0.9

Avg. Longest Root per Cutting (cm)

12.2 ± 1.2 A

11.3 ± 1.2 A

13.3 ± 1.2 A

12.8 ± 1.2 A

F = 4.4 P = 0.002

F = 1.8 P = 0.2

F = 0.4 P = 0.5

F = 0.0 P = 0.9

F = 1.5 P = 0.2

F = 0.4 P = 0.9

F = 0.6 P = 0.7

Powder = 0.1% IBA and Gel= 0.3% IBA. Heat was provided via propagation mat to approx. 10°C above ambient. Values denote means ± standard errors. Means in rows followed by different letters are significantly different (P = 0.05) using Tukey’s HSD test. N=54. Number of observations = 216.

38

Figure 2-2. Experiment 1. Comparison of the mean longest root of the propagated cutting per field collection site. Bars represent means ± standard error. Bars labeled with different letters are significantly different (P = 0.05) using Tukeys HSD test. Fort Clinch, FL= 11.3 cm, Fort George Island, FL= 14.4 cm, St. Catherines Island, GA= 10.2 cm, Cumberland Island, GA= 7.6 cm, Hunting Island, SC = 11.0 cm, and Edisto Beach, SC= 19.9 cm.

39

Table 2-2. Exp 2. Effects of media mixtures on mean rootability, number of roots, and root length on redbay

3:1 P-V

1:1:1 P-PT-SD

1:1 P-PT

2:1:1 P-SD-S

Location (L)

Media (M)

L x M

% Rooted

37.0 ± 6.8 A

19.5 ± 4.8 B

28.9 ± 6.1 AB

20.0 ± 4.9 B

F = 0.0 P = 0.9

F = 7.9 P = 0.0001

F = 0.9 P = 0.5

Rooting % of Live Cuttings Only

71.6 ± 8.4 A

48.7 ± 10.6 BC

66.8 ± 9.3 AB

46.4 ± 10.6 C

F = 1.1 P = 0.3

F = 6.0 P = 0.0009

F = 0.5 P = 0.7

Avg. # Roots per Cutting (0.5 cm+)

3.1 ± 0.2 A

2.0 ± 0.2 A

1.7 ± 0.2 A

2.2 ± 0.2 A

F = 0.1 P = 0.7

F = 1.8 P = 0.2

F = 1.1 P = 0.4

Avg. Longest Root per Cutting (cm)

11.8 ± 1.9 A

12.1 ± 1.9 A

15.2 ± 1.9 A

11.7 ± 1.9 A

F = 0.1 P = 0.8

F = 1.3 P = 0.3

F = 0.1 P = 0.9

Values denote means ± standard errors. Means in rows followed by different letters are significantly different (P=0.05) using Tukey’s HSD test. N=25. Number of observations = 100.

40

Figure 2-3. Experiment 2. Rooted redbay cuttings percentage per rooting medium. Bars represent means ± standard error. Bars labeled with different letters are significantly different (P = 0.05) using Tukeys HSD test. 3:1 P-V= 3:1 perlite-fine vermiculite media mix, 1:1:1 P-PT-SD = 1:1:1 perlite-Canadian peat moss-Cypress sawdust media mix, 1:1 P-PT = 1:1 perlite-Canadian peat moss media mix, and 2:1:1 P-SD-S = 2:1:1 perlite-Cypress sawdust-seedling soilless mix.

41

Figure 2-4. Experiment 2. Rooting percentage of live redbay cuttings only. Bars represent means ± standard error. Bars labeled with different letters are significantly different (P = 0.05) using Tukeys HSD test. 3:1 P-V= 3:1 perlite-fine vermiculite media mix, 1:1:1 P-PT-SD = 1:1:1 perlite-Canadian peat moss-Cypress sawdust media mix, 1:1 P-PT = 1:1 perlite-Canadian peat moss media mix, and 2:1:1 P-SD-S = 2:1:1 perlite-Cypress saw dust-seedling soilless mix.

42

CHAPTER 3 RESPONSES OF SWAMP BAY (Persea palustris) TO THE LAUREL WILT

PATHOGEN, Raffaelela lauricola

Introduction

Since its introduction in 2002, laurel wilt, caused by the fungal symbiont

(Raffaelea lauricola) of the exotic redbay ambrosia beetle (Xyleborus glabratus) has

ravaged members of the Lauraceae in the southeastern United States (17,33). Among

the native laurels none have been more affected than the aromatic evergreen redbay

(Persea borbonia) and swamp bay (Persea palustris). Within a few years of stand

infestations, greater than 90% of mature redbays succumb to laurel wilt. This sudden

and substantial mortality of a once abundant tree has changed the species composition

in affected areas, with mature redbays being replaced by other tree species

(17,22,23,81)

In contrast to the situation in the United States, very little is known about this pest

and its symbiont within its native range. X. glabratus is native to south-east Asia (79),

and R. lauricola was detected in individuals of the beetle that were collected in Japan

and Taiwan (Harrington 2011). Although the symbiont is presumed to be as prevalent

in Asian populations of X. glabratus as it is in the USA, laurel wilt has not been reported

in Asia. In typical ambrosia beetle lifestyles, the insects choose stressed and dead

trees for gallery development, egg lying, and the cultivation of their fungal gardens, with

little impact upon healthy forest trees (3). In contrast, X. glabratus interacts with healthy

trees in the USA, causing mortality during its search for a suitable host, which becomes

available during the affected tree’s final stages of life (17). This unusual activity of the

vector may be the function of an introduced pest interacting with and exploiting new

43

naive hosts, with the help of its primary fungal symbiont and incidental pathogen, R.

lauricola.

Currently, the nature of R. lauricola’s interaction with its host at a cellular level is

still unknown. However, in diseased avocados (P. americana) there was a dramatic

reduction in xylem function and hydraulic conductivity (42). Results from inoculations

with live beetles has shown that as few as five female beetles can kill a healthy potted

avocado, and three were sufficient for redbay (62, Hughes unpublished), whereas

artificial inoculations into wounds with a single small agar plug (2 mm) colonized by the

pathogen cause laurel wilt in mature field redbays within weeks (61). These findings

suggest an extremely virulent pathogen capable of infecting and wilting trees in a short

time.

Although the above examinations indicated that single point inoculations can lead

to infection of a tree, specific factors in these interactions are unknown. For example,

no information is available for the amounts of inoculum that occur in naturally affected

trees. Thus, to develop a screening program to identify laurel wilt tolerance, information

would be needed on whether inoculum concentration plays a role in extent and timing of

disease development and, if so, what dosages are needed to incite wilt. Furthermore,

whether trees survive and/or recover after inoculation with lower inoculum

concentrations are needed to adequately evaluate the performance of selections. Data

from studies that are described below guided development of screening protocols with

which laurel wilt tolerance could be identified in cloned redbay trees (see Chapter 2).

44


Inoculum Preparation and Quantification

Inoculum was prepared from the Raffaelea lauricola isolate PL571 (GenBank

accession JQ861956.1), grown on cyclohexamide-streptomycin malt agar (CSMA)

media (32). Spores were gathered by flooding the culture plate with 2 mL of sterile

water, agitation via cell spreader, and collected by pipette. A hemacytometer was used

to quantify the spore suspension as 2.0 x 106 CFU/mL (CFU = Colony Forming Units).

This was repeated three times in order to ensure a consistent spore count. Serial

dilutions were performed in order to obtain the following concentrations: 105, 104, 103,

and 102 conidia. Samples from each spore suspension were spread on plates of CSMA

and ½ strength potato dextrose agar (PDA), and after 3-7 days on a lab bench, fungal

colonies were counted to calculate the numbers of CFUs that were present in each

dilution/inoculum concentration.

Swamp Bay Inoculations

Sixty containerized (12.5 L) swamp bay saplings roughly 1.5 to 2 m in height

were purchased from a local nursery in August 2011. Two experiments were conducted

in September 2011 at the School of Forest Resources and Conservation (SFRC)

nursery area at the University of Florida, Gainesville. The first experiment was under

full sun in a nursery, and the other in a pad and fan greenhouse, with supplemental

lighting (16:16 diurnal light). The mean temperature for the nursery was 16°C and the

greenhouse was set to 21°C day/18°C night temperature regime. Both experiments

were arranged in a completely randomized design with five spore concentration

treatments (0, 102, 103, 104, and 105 conidia) and six replicates per treatment.

45

In September 2011 for each experiment, trees were drill-wounded twice with a

7/64” titanium bit, 15 cm above the soil line and 15 cm above the previous inoculation

point on the opposite side of the stem. Drill wounds were made at a 45° downward

angle with care to stay within the xylem and avoid the pith. All trees received 25 μL of a

spore suspension or water (mock inoculated treatment) per drill wound (50 μL total per

tree), and were then sealed with Parafilm®. Trees were watered as needed, and rated

weekly according to the following disease severity scale.

0 = no wilt symptoms

1 = 1-25% crown wilt




Recovery of R. lauricola from Swamp Bay

At 24 weeks post inoculation (WPI) stems and roots of all trees were checked for

internal vascular streaking, a symptom of laurel wilt. The presence of dark vascular

streaking/discoloration was recorded as present or absent. For the above-ground

examination, a 12-cm stem segment (average diameter =18 mm) was removed at 50

cm above the soil line, and for the below-ground analyses a 10-cm section of a major

root (average diameter =13 mm/avg. depth below soil line =7.5 cm) was randomly

selected and removed per tree. Wood chips were also taken to assay for R. lauricola.

Isolations were performed as previously described (75). Culture plates were incubated

at room temperature under low light, with two replicate plates per sample.


The area under the disease progress curve using the midpoint rule method was

calculated with Microsoft Excel in accordance to Campbell and Madden (1990):

46

AUDPC = i=1n-1 [(ti+1 – ti)(yi + yi+1)/2]

Where: t= time in days, y= proportion of canopy symptomatic (disease severity),

and n= the number of observations.

The NLIN procedure in SAS version 9.3 (SAS Institute Inc., Cary, NC) was used

to fit to the Gompertz model to estimate the rate (r) and asymptote (K) for disease

severity over time. Analysis of variance (ANOVA) was performed using the GLM

procedure followed by a multiple comparison of means according to Fishers’s Least

Squared Difference test (LSD) at P = 0.05. Contingency tables for the fungal isolation

experiments were conducted using JMP, Version 7. (SAS Institute Inc., Cary, NC).

Standard error (SE) was calculated as [std dev/√reps].

Results

Inoculum Preparation and Quantification

CFUs on CSMA and ½ PDA were similar, and total means on both media are

reported in Table 3-1. Conidium viability was good (94%), and there was reasonable

accuracy between the calculated concentrations of conidia that were used to inoculate

plants and the numbers of CFUs that developed on media from a given concentration

(i.e., these data were not significantly different, P= 0.37). Likewise, CFUs that were

used for given inoculum concentrations in the two experiments were similar, as pairwise

comparisons for the experiments were not significantly different (P values between 0.51

and 0.87) (Table 3-1).

Swamp Bay Inoculations

By 3 weeks post inoculation, plants in all inoculated treatments displayed laurel

wilt symptoms (Figure 3-1 to 3-4). At the 102 concentration, disease severity in the

greenhouse increased rapidly from weeks 3-11, with mortality beginning at week 4 and

47

progressing to 100% by week 13 (Figure 3-1, Table 3-2). In contrast, in the outside,

nursery disease incidence and severity were variable at the 102 concentration, with only

two of six plants displaying wilt symptoms. Consequently, these disease progress data

were poorly fit (R2 = 0.1) with a higher standard error when compared to the

greenhouse location (R2 = 0.78) (Figure 3-1, Table 3-3). In addition, mortality

developed slowly in the nursery trees, with some plants dying after 20 WPI (Figure 3-1,

Table 3-2). Disease progression curves at the 103 concentration were similar in both

locations, although all inoculated plants died in the greenhouse by 7 WPI, but trees in

the nursery took an extra 11 weeks to die (Figure 3-2, Table 3-2). There was a good fit

between observed and predicted disease severity in the greenhouse (R2 = 0.94),

whereas the stepwise disease progression that was noted in the nursery was not as

well fit (R2 = 0.59) (Figure 3-2, Table 3-3). At the 104 concentration, Gompertz disease

progression curves were similar in shape and accuracy to the predicted development

curve in the greenhouse (R2 = 0.94) and nursery (R2 = 0.90) (Figure 3-3, Table 3-3).

The main difference between locations at this inoculum level was the rate at which

100% mortality was reached, with 7 WPI in the greenhouse and 17 WPI in the nursery

(Figure 3-3, Table 3-2); however, with one exception all plants in the nursery experiment

died within 6 WPI (data not shown). At the 105 level, similar disease progression

developed at both locations (Figure 3-4); in the greenhouse, a high coefficient of

correlation was noted between observed and predicted disease severity (R2 = 0.94) and

all plants died 6 WPI, whereas in the nursery, R2 = 0.90 and all plants died 8 WPI (Table

3-2).

48

Comparison between Inoculum Levels and Locations

In the nursery experiment, disease progression at 103, 104, and 105 conidia per

plant was similar with rates of 0.73, 1.15, and 1.09, respectively (Table 3-2). However,

the mean rate of 102 conidia (0.17) was significantly lower than of 104 and 105 conidia

(Table 3-2). In the greenhouse, there were no significant differences in rates among

inoculum concentrations (Table 3-2). When the rate of disease progression over log

inoculum concentration was plotted and fitted to a monomolecular growth curve, there

was a clear illustration of the increased speed of disease progress at higher inoculum

dosages (Figure 3-5). The experimental location (P = 0.001) and treatment level (P =

0.001) were important factors in regards to the rate of disease progression, with no

interactions detected (P = 0.08). Although faster rates of symptom development

occurred in the greenhouse (Figure 3-5), final disease severity ratings and time to

mortality were generally unaffected by location. With the exception of the 102 treatment

in the nursery, which had a significantly lower disease asymptote (0.26) due to the

failure of all plants to display symptoms, those for other inoculum concentrations in both

experiments were similar (0.87 - 0.91) (Table 3-2). In the nursery, AUDPCs were

similar at the three highest inoculum levels (82.2 - 99.7), but significantly higher than for

the 102 treatment (21.8), whereas AUDPCs were highly similar (90.4 - 101.1) in the

greenhouse (Table 3-2).

Recovery of R. lauricola from Swamp Bay

Isolations onto CSMA culture media from stem bolts with internal streaking

yielded the pathogen with 100% consistency, while isolation attempts from stem tissue

without internal discoloration were unsuccessful (data not shown). To test for the

presence of an association between fungal isolations from stem and root tissue, as well

49

isolations from discolored and non-discolored root tissue, the Fisher’s Exact Test was

used (Table 3-4 to 3-5). This test showed that there was a consistent relationship

between stem- and root isolation and between root isolation and root discoloration. At

times when R. lauricola was not isolated from the stem tissue, the pathogen was never

found in the underground root tissue (Table 3-4). In trees whose sapwood was positive

for the pathogen, 77.3% (34 of 44 attempts) of root isolations were positive for R.

lauricola (Table 3-4). R. lauricola was successfully isolated from non-discolored root

tissue in 6 of 17 attempts (35.3%) (Table 3-5). Roots with visible dark discoloration

tested positive for the pathogen in 28 of 31 (90.3%) instances (Table 3-5)

Discussion

The present results clearly indicate that R. lauricola is highly virulent in swamp

bay plants, with 102 conidia causing symptoms in many cases. Final disease

asymptotes and AUDPCs were similar among all inoculated treatments, except the 102

treatment in the nursery experiment, which failed to affect all plants. The 102 dosage

may be approaching the minimum threshold necessary to affect plants under the

variable conditions that are present in the field or nursery. In contrast, the 103 – 105

treatments resulted in consistent disease development and final mortality, regardless of

location. Other inoculum concentration studies on Cercospora beticola Sacc. on sugar

beet, and Verticilium dahlia Kleb. on olive and cauliflower also showed that even low-

level inoculations were able to incite disease, with incidence and severity increasing

with dosage (48,57,101).

The differences in inoculation results between locations were similar to those

observed for Dutch elm disease, in which greater disease developed in a controlled

environment vs. the variable conditions present in field experiments (47,82). Sutherland

50

et al. (1997) found ambient temperature and number of sunshine hours to be significant

factors in the defoliation of elms inoculated with O. novo-ulmi, with Green et al. (1985)

also noting internal symptom development being effected by temperature (24,87).

These findings may explain the faster and more uniform disease progression of redbays

within the greenhouse, which had a warmer, more stable temperature, and extended

daylight hours due to supplemental lighting. The biological processes that mediate the

interactions between disease development and environment are still unclear, with

further work needed.

Based on recovery from inoculated plants, R. lauricola colonized swamp bay

rapidly and extensively. This is not routine among diseases with ambrosia beetle

vectors. For example, the oak wilts that are caused by Raffaelea spp. in Japan and

Korea are associated with restricted disease development associated with the Platypus

ambrosia beetle galleries; host mortality would not occur without mass attacks by the

beetle vectors (50,89). In contrast to the Asian oak wilts, few X. glabratus attacks are

needed to successfully infect some susceptible hosts within greenhouse experiments

(17,62,Hughes unpublished). Since as few as 100 conidia caused lethal laurel wilt, it

suggests that mass attack and high fungal titers may not be necessary to cause

mortality under natural conditions; however, more research is needed to decipher the

amount of inoculum released during initial boring attempts.

The fungal isolation experiments revealed the ability of the pathogen to enter the

root system. Pathogen recovery from root tissues was strongly associated to both;

successful stem isolations and root discoloration. Root grafting in street-planted elms

and oaks with shared root systems is a common means by which the DED and

51

Ceratocystis oak wilt pathogens move among those trees (21). Currently, there is a

lack of empirical evidence for root graft transmission of R. lauricola in redbay or swamp

bay; however, observations suggest that pathogen movement via shared root systems

has occurred in sassafras and avocado (Personal communications- Bates and Ploetz).

The possibility of root graft transmission within the avocado groves of south Florida

presents a serious new method of lateral transmission, in which subsequent vector

attacks are not needed.

The observations from this study suggest that few spores/beetle attacks would

be needed to induce wilt naturally in a susceptible host. However, many aspects

confound the understanding of this disease system, including: the great variability of

spore concentrations within the beetle’s mycangia, host vigor, vector behavior, and

environmental conditions. Little has been done to explore the unclear avenue by which

beetles introduce inoculum during their first interactions with a healthy host tree (does

the inoculum that initiates infection come directly from the mycangium or does it

originate in the gardens of the symbiont that are produced in the natal gallery?). These

inoculation studies revealed the general trends in host susceptibility and disease

phenology, which aid in the development of a laurel wilt screening protocol and superior

germplasm.

52

Table 3-1. CFUs for given inoculum concentrations in nursery and greenhouse experiments, as determined on two plates each of CSMA and 1/2 PDA.

CFU/50 µL Nursery Greenhouse P value*

102 93 ± 2.3 A 92 ± 1.8 A 0.80

103 900 ± 15.8 B 905 ± 20.1 B 0.87

104 9,500 ± 334.2 C 9,700 ± 514.8 C 0.76

105 98,250 ± 3705.3 D 94,750 ± 3351.0 D 0.51

P-values are for pair-wise comparisons between mean CFUs for concentrations in the two experiments. Means ± standard errors followed by different letters are significantly different (P < 0.05) according to Fisher’s LSD test.

53

Figure 3-1. Development of laurel wilt symptoms on swamp bay after inoculation with

102 conidia of R. lauricola per plant. Mean disease (severity + standard errors) progress data are fit to a Gompertz growth curve, and dashed lines indicate prediction curves for the nursery and greenhouse experiments.

54

Figure 3-2. Development of laurel wilt symptoms on swamp bay after inoculation with 103 conidia of R. lauricola per plant. Mean disease (severity + standard errors.) progress is fit to a Gompertz growth curve, and dashed lines indicate prediction curves for the nursery and greenhouse experiments.

55

Figure 3-3 Development of laurel wilt symptoms on swamp bay after inoculation with

104 conidia of R. lauricola per plant. Mean disease (severity + standard errors) progress is fit to a Gompertz growth curve, and dashed lines indicate prediction curves for the nursery and greenhouse experiments.

56

Figure 3-4 Development of laurel wilt symptoms on swamp bay after inoculation with 105 conidia of R. lauricola per plant. Mean disease (severity + standard errors) progress is fit to a Gompertz growth curve, and dashed lines indicate prediction curves for the nursery and greenhouse experiments. .

57

Figure 3-5. Disease development (rate + standard errors) in relation to inoculum concentration (log10). Dashed lines indicate predicted rate based on monomolecular growth curves.

58

Table 3-2. Summary of disease development parameters for swamp bays inoculated with R. lauricola.

Inoculum Concentration

Rate of disease progression Asymptote AUDPC

Weeks till death Mortality

Nursery

102 CFU 0.17 ± 0.1 A 0.26 ± 0.2 A 21.84 ± 14.0 A 6-end

2/6

103 CFU 0.73 ± 0.2 AB 0.91 ± 0.03 B 82.19 ± 11.3 B 6-18 6/6

104 CFU 1.15 ± 0.2 BC 0.87 ± 0.02 B 97.08 ± 3.9 B 5-17 6/6 105 CFU 1.09 ± 0.1 BC 0.89 ± 0.002 B 99.71 ± 1.37 B 4-8 6/6

Greenhouse

102 CFU 1.04 ± 0.2 BC 0.89 ± 0.003 B 90.44 ± 6.0 B 4-13 6/6

103 CFU 1.31 ± 0.1 BC 0.88 ± 0.002 B 99.29 ± 1.5 B 4-7 6/6

104 CFU 1.39 ± 0.1 C 0.89 ± 0.003 B 101.06 ± 1.6 B 4-7 6/6

105 CFU 1.33 ± 0.04 C 0.89 ± 0.002 B 99.73 ± 0.9 B 4-6 6/6

Nursery and Greenhouse indicated experimental location. Inoculum concentration = number of conidia inoculated into each plant, rate of disease progression = Gompertz model R value from the NLIN procedure, asymptote = maximum disease severity of disease progress curves, AUDPC = area under the disease progress curve, Weeks till death = time for all replicates to die, with “end” indicating plant survival. Mortality = number of plants that died from 6 replicates. Values denote means ± standard errors. Means in columns followed by different letters are significantly different (P = 0.05) using Fisher’s LSD test.

59

Table 3-3. Nonlinear regression analysis of laurel wilt disease severity over time, and disease development rate over inoculum concentration in swamp bay plants inoculated with R. lauricola at varying inoculum densities, within two locations.

Location:CFU/plant Regression Equation Approx. R2

Disease Severity over Time

Gompertz equation: y= K*(Y0/K)ÊXP(-RX)

Nursery: 102 Y = 0.2575*(1.27E-9/0.2575)ÊXP(-0.444X) 0.1

Nursery: 103 Y = 0.7894*(3.33E-7/0.7894)ÊXP(-0.432X) 0.59

Nursery: 104 Y = 0.8639*(3.01E-15/0.8639)ÊXP(-1.0685X) 0.9

Nursery: 105 Y = 0.8841*(5.58E-12/0.8841)ÊXP(-0.9921X) 0.9

Greenhouse: 102 Y = 0.8697*(8.551E-7/0.8697)ÊXP(-0.6713X) 0.78




Disease Development Rate vs. Inoculum Concentration

Monomolecular equation: y=A*(1-B*EXP(-CX))

Nursery Y = 1.2258*(1-(4.9951*EXP(-0.8755X))) 0.59

Greenhouse Y = 1.3582*(1-(13.2141*EXP(-2.0140X))) 0.18

For the Gompertz model: Y = disease severity, K = asymptote, Y0 = disease severity at time 0, R = rate of disease progression, and X = time. For the Monomolecular model: Y = disease severity, and X = time. R2 = coefficient of determination of the regression line.

60

Table 3-4. Contingency table analysis denoting R. lauricola recovery success (+) and failure (-) from root and stem tissues from combined greenhouse and nursery plants

Stem Isolation

-

Stem Isolation

+

Root Isolation

-

observed = 4 expected =1.17


N = 14

Root

Isolation

+

observed = 0

expected = 2.83

observed = 34

expected =31.17

N = 34

N = 4

N = 44

N = 48

P = 0.005 according to Fisher’s Exact Test (2 - Tail)

61

Table 3-5. Contingency table analysis denoting R. lauricola recovery success (+) and failure (-) from the root tissue of inoculated plants with and without the presence of vascular discoloration from combined greenhouse and nursery plants.

P = 0.001 according to Fisher’s Exact Test (2 - Tail)

Root Discoloration

-

Root Discoloration

+

Root Isolation

-


observed = 3 expected = 9.04

N = 14

Root

Isolation

+

observed = 6

expected = 12.04

observed = 28

expected =21.96

N = 34

N = 17

N = 31

N = 48

62

CHAPTER 4 GENETIC DIVERSITY STUDIES OF THE LAUREL WILT PATHOGEN (Raffaelea lauricola) SUGGEST A CLONAL POPULATION IN THE UNITED STATES, WITH ASIAN ISOLATES ALSO PATHOGENIC TO SWAMP BAY (Persea palustris) AND

AVOCADO (Persea americana)

Introduction

In 2002 the exotic redbay ambrosia beetle (RAB), Xyleborus glabratus, native to

Bangladesh, India, Myanmar, Japan, and Taiwan, was discovered in United States

Department of Agriculture (USDA) Early Detection and Rapid Response program traps

near Port Wentworth, Georgia (27,79). Within 3 years of its detection, significant and

unprecedented mortality of redbay (Persea borbonia) appeared throughout the coastal

maritime hammocks of South Carolina, Georgia, and northeastern Florida (17).

Isolations from discolored vascular stem tissue of P. borbonia and the mandibular

mycangia (pocket-like spore-harboring structure) of X. glabratus revealed the consistent

presence of the new asexual fungus, Raffaelea lauricola, which caused a new disease,

laurel wilt (17,33). Laurel wilt is highly damaging to redbay, swamp bay (P. palustris),

and sassafras (Sassafras albidum), but also affects other members of the Lauraceae

plant family in the southeastern United States, including the economically important

avocado (Persea americana) and two endangered native species, pondspice (Litsea

aestivalis) and pondberry (Lindera melisssifolia) (17,18,39, 63,83).

Since its arrival, the redbay ambrosia beetle and laurel wilt have spread rapidly to

nearby counties at an estimated rate of about 54.8 km/year, with anthropogenic

movement increasing these rates greatly (53). The disease has moved northward and

southward along the coastline, most likely due to the abundance of suitable redbay

hosts. By August 2012, laurel wilt had been reported in over 95 counties in Florida,

Georgia, South Carolina, North Carolina, Alabama, and Mississippi (96).

63

Once laurel wilt spreads to an area with abundant hosts, stands often face

severe and rapid mortality. Recent studies have documented 100% mortality of

redbays > 4” DBH within 2 years (17,81). The unprecedented loss of redbay in affected

ecosystems will impact the future species composition of these areas, as has been

documented on Little Talbot Island, FL (22).

Currently, nothing is known about the genetic structure of R. lauricola in the

United States or its native range. R. lauricola has been recovered from X. glabratus in

Japan and Taiwan, yet there have been no reported cases of laurel wilt in Asia (36).

Knowledge of the genetic structure of R. lauricola could shed light on the possibility of a

clonal population in the USA, its variability within its native range in Asia, and number of

introduction events into the USA. In addition, such information would inform selection

and breeding programs in which laurel wilt tolerance would be developed, with the

variability of the pathogen having direct implications to the inoculation process. A highly

diverse pathogen population within the USA would require the use of multiple strains of

R. lauricola to properly screen for tolerance, with little to no diversity requiring a single

isolate. The purpose of this study was to analyze genetic variation in R. lauricola.

Isolates were collected from symptomatic hosts and X. glabratus (Table 4-1). Amplified

Fragment Length Polymorphisms (AFLPs) were chosen as markers due to their ability

to generate many independent loci across the genome with high reproducibility and

resolution (58,65,66,67,98). An additional type of genetic resolution was provided by

sequences of microsatellite loci and their flanking regions. Due to the highly inbred

nature of the redbay ambrosia beetle, its intimate association with R. lauricola, the

absence of a sexual stage in the fungus, the presumably short length of time that the

64

beetle has been in the USA, and the apparent focal development of the current laurel

wilt epidemic starting around Port Wentworth, it is hypothesized that R. lauricola is

clonal in the USA, and that data from the collected/examined isolates will provide

evidence for a founder event typical of recently introduced invasive pests (14,56).

Materials and Methods

Fungal Isolates

Fifty-seven isolates of Raffaelea lauricola were collected from its known range

along the Atlantic coastal plain of South Carolina, Georgia, Florida, and Mississippi.

Eight isolates were collected from South Carolina, 16 from Georgia, 31 from Florida,

and two from Mississippi (Table 4-1, Figure 4-1). Three Asian isolates were obtained

from The Centraalbureau voor Schimmelcultures (CBS) Fungal Biodiversity Centre in

the Netherlands, two originating from Taiwan and one from Japan (Table 4-1, Figure 4-

1). All United States isolates were collected between 2004 and 2009. Twenty-one of

the 60 isolates were obtained from S.W. Fraedrich, (Southern Research Station, USDA

Forest Service, Athens, GA 30602) by isolation methods described in Fraedrich et al.

(2008). For the other isolates, sapwood samples were collected from symptomatic

hosts. Samples were debarked, and regions with brown to black sapwood discoloration

were removed and cut into approximately 0.5-cm squares, surface disinfested in a 1:1

commercial sodium hypochlorite/ water solution for 30 seconds, and rinsed twice with

deionized water. The samples were then placed on CSMA, a medium used for selective

isolation of Ophiostoma anamorphs (32). Plates were visually inspected for R. lauricola

after 5-7 days using morphological traits described by Harrington et al. (2008), and the

colonies were sub-cultured on CSMA media. To ensure a single spore-derived isolate,

a growing subculture was flooded with 1 mL of deionized water and gently rubbed with a

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sterile plastic spreader in order to release conidia. Ten to 20 µL of the spore solution

was taken from the flooded culture plate and added to a sterile beaker containing 10 mL

of sterile deionized water. A sterile glass rod was dipped into the water/spore solution

and streaked along CSMA plates. Plates were visually inspected after 3-5 days for the

presence of germinated R. lauricola spores with hyphae under a dissection scope. A

single germinated spore was removed from the media with a scalpel and transferred to

fresh a CSMA plate and grown until further analysis. All cultures were transferred to

CSMA slants for long-term storage at the University of Florida, Forest Pathology culture

collection in Gainesville, FL.

DNA Extraction

After 15-30 days of growth, conidia from the single spore isolates were recovered

by flooding cultures with 2 mL of sterile water and gently scraping the surface with a

sterile plastic spreader. The spore suspension was then transferred to a 2 mL micro-

centrifuge tube. Samples were centrifuged for 1 min at 16,000 rpm and the supernatant

was removed. An equal volume of acid-washed sand was added, and samples were

ground at room temperature using a micro-pestle. DNA was extracted using a

modification of the procedure described by Justesen et al. (2002). To each sample, 0.8

mL DNA extraction buffer (25 g/L D-sorbitol, 10 g/L sodium dodecyl sulphate, 10 g/L

polyvinylpolypyrrolidone, 8 g/L hexadecyltrimethylammonium bromide, 0.8 M NaCl, 20

mM EDTA, 0.1 M Tris, pH 8.0) was added, and the sample was mixed thoroughly. Two

µL of DNase-free RNase A (100 mg/mL; Qiagen, Valencia, CA) were added, and the

sample was mixed gently by inversion and then incubated at 65 C for 60 min. Samples

were chilled on ice before addition of 0.8 mL chloroform. Samples were mixed by

66

inversion 30 times and then centrifuged for 5 min at 16,000 rpm. The aqueous phase

was withdrawn, and chloroform extraction was repeated, as before. The aqueous

phase was then recovered, and an equal volume of ice-cold isopropanol was added.

Samples were mixed by inversion before centrifugation for 5 min at 16,000 rpm. The

DNA pellet was washed with 75 % (v/v) ethanol before being air-dried and re-

suspended in 50-100 l TE buffer.

Amplified Fragment Length Polymorphism (AFLP) Analysis

Fifty-seven isolates of Raffaelea lauricola that had been collected throughout the

known range of the pathogen were subjected to Amplified Fragment Length

Polymorphism (AFLP) analysis using fluorescently labeled primers. Six primer pairs

were tested against the panel of fungal isolates (Table 4-1). All EcoRI selective primers

possessed one selective nucleotide, and all MseI selective primers possessed two

selective nucleotides (Table 4-2). AFLP restriction-ligation and pre-selective

amplification reactions were performed using the Ligation and Pre-selective

Amplification Kit for Small Plant Genomes (Applied Biosystems, Inc., Foster City, CA)

according to the manufacturer’s instructions, with the exception that pre-selective

reactions were diluted 1:5 in TE (0.1) buffer (20 mM Tris-HCl, 0.1 mM EDTA, pH 8.0).

Selective amplification reactions were performed in a volume of 10 l that contained 1.5

l of 1:5-diluted pre-selective reaction, 0.5 l of 0.1 M EcoRI selective primer, 0.5 l of

0.5 M MseI selective primer, and 7.5 l of AFLP Amplification Core Mix (Applied

Biosystems, Inc., Foster City, CA). Reactions were amplified according to the

manufacturer’s instructions, and a DNA Engine thermal cycler (Bio-Rad, Hercules, CA)

was used for all amplification steps. EcoRI and MseI selective primers were obtained

67

from Applied Biosystems, Inc. (Foster City, CA) or Eurofins MWG Operon (Huntsville,

AL). All EcoRI selective primers were fluorescently labeled with: FAM, NED, or JOE.

The Interdisciplinary Center for Biotechnology Research Genetic Analysis Laboratory

(University of Florida) provided fragment length analysis services, and samples were

run on an ABI3730 DNA Analyzer (Applied Biosystems Inc., Foster City, CA) using

GeneScan 600 LIZ size standard (Applied Biosystems Inc., Foster City, CA). Data were

analyzed using GeneMarker V1.70 software (SoftGenetics, LLC, State College, PA)

with the following parameters optimized according to Holland et al. (2008); peak height

threshold: 50, minimum fragment length: 50, smoothing enabled, and minimum peak

score set to: fail < 1 check < 1 pass (38). Dendrograms were constructed with the web-

based program DendroUPGMA (http://genomes.urv.cat/UPGMA/) using the Pearson

similarity coefficient, with distance values generated by the transformation d = (1 - r) *

100. One hundred bootstrap replicates were generated. Population genetic descriptive

statistics were generated by the program Popgene (103).

Microsatellite Analysis

Six taxon-specific microsatellite primers (chk, ifw, 2in, cpl, qi5, and 7kc)

developed for R. lauricola by Dreaden et al. (2011) were used to obtain sequences of

the microsatellite loci and their flanking regions. A panel of R. lauricola isolates with

standard AFLP profiles (PL159, PL570, and PL571), three isolates with polymorphic

AFLPs (PL388, PL 692, and PL735), and the three Asian isolates (PL1417, PL1418,

and PL1467) were chosen for analysis. PCR preparations and thermal cycler programs

were used as in Dreaden et al. (2011) for DNA amplification. All sequencing reactions

were performed at the Interdisciplinary Center for Biotechnology Research Genetic

Analysis Laboratory at the University of Florida, Gainesville. Contigs for the forward

68

and reverse sequences were created, aligned and edited with Geneious 5.4.6. Three-

item matrices (3TS) were generated with TAXODIUM version 1.0 (59). Maximum

Parsimony analysis was conducted in PAUP* version 4 (88) with 1000 bootstrap

replicates and an artificial outgroup.

Sequencing Reactions

In order to confirm the identity of the polymorphic isolates as R. lauricola,

sequencing reactions were performed. The small subunit (18S) region of the ribosomal

DNA (rDNA) was PCR-amplified and sequenced using the primers NS1 and NS4 (99).

All sequencing reactions were performed at the Interdisciplinary Center for

Biotechnology Research Genetic Analysis Laboratory at the University of Florida,

Gainesville. Contigs for the forward and reverse sequences were created, aligned, and

edited with DNA baser v3.0.36 (Heracle BioSoft S.R.L., Pitesti, Romania). GenBank

BLASTn searches were then performed to confirm the identity of the isolates.

Pathogenicity Tests

United States isolates

In order to confirm pathogenicity of the three polymorphic isolates, greenhouse

inoculations of seedlings of the susceptible host swamp bay (P. palustris) were

conducted. A spore suspension was made by flooding culture plates with 2 mL of

sterile water, scraping the culture surface with a sterile plastic spreader, collecting by

pipette, and placing into a sterile 50 mL conical tube. The conidia were diluted in sterile

water and quantified by hemacytometer. Spore suspensions of the polymorphic isolates

PL692 (1.13 x 106 spore/mL), PL735 (1.0 x 106 spore/mL), and PL388 (1.2 x 106

spore/mL) were made with the isolate PL571 (1.14 x 106 spore/mL) being used as a

positive control due to its known pathogenicity and normal AFLP genetic profile. Each

69

isolate was inoculated into 4 potted swamp bays, approximately 1.5 meters in height,

with plants inoculated with sterile water serving as a negative control. All inoculations

were made by drill wound into the lower trunk, the addition of 100 µL of spore

suspension via pipette, and covered with Parafilm®. The experiment was arranged in a

randomized block design and conducted twice. All plants were watered as needed and

rated every 3 days according to the scale below. At 52 days post inoculation, a 10 cm

portion of the main stem was removed, 15 cm above ground level. The bark was

removed with a grafting knife, and the percentage of internal tissue discoloration was

visually estimated according to the 0 – 10 scale below. Small sapwood pieces were

used for fungal isolation (as described above).

Asian isolates

The three Asian isolates were tested for pathogenicity in greenhouse inoculations

of swamp bay and avocado cv. ‘Simmonds’ that were conducted under APHIS permit

P526P-12-02677. Inoculum preparation and quantification were performed as above

with concentrations of: PL1417 (1.15 x 106 spore/mL), PL1418 (1.19 x 106 spore/mL),

PL1467 (1.12 x 106 spore/mL) and PL571 (1.06 x 106 spore/mL). Each isolate was

inoculated into four swamp bays and three avocados. PL571 served as a positive

control and sterile water as a negative control. Experiments were divided by host and

arranged in a randomized block design within a quarantine greenhouse at the Division

of Plant Industry (Gainesville, FL). The same inoculation, rating, and isolation

procedure as above was used. The experiment was conducted once.

Disease severity scale:

0= no wilt symptoms

1= 1-10% crown wilt

2= 11-20% crown wilt

70









The area under the disease progress curve using the midpoint rule method was

calculated with Microsoft Excel in accordance to Campbell and Madden (1990):


Where: t= time in days, y= proportion of affected canopy (disease severity), and

n= the number of observations.

Analysis of variance (ANOVA) was performed using the GLM procedure in SAS

version 9.3 (SAS Institute Inc., Cary, NC) followed by a multiple comparison of means

according to Fisher’s LSD at P = 0.05. Standard error was calculated as [std

dev/√reps].

Results

Amplified Fragment Length Polymorphism (AFLP) Analysis

Between 16 and 54 fragments could be reliably scored for each primer pair, with

an average of 36 fragments amplified per primer pair (Table 4-2). To determine the

reproducibility of fragment amplification, duplicate pre-selective reactions were prepared

for ten restriction-ligation reactions, and all ten technical replicates were amplified using

the six selective primer pairs. In addition, duplicate DNA samples were prepared for 28

isolates using independent fungal plate cultures, and AFLP templates prepared from

these biological replicates were amplified using the six selective primer pairs. Identical

71

results were obtained for all technical and biological replicates (data not shown),

indicating that the AFLP procedure is reliable and reproducible.

Of the 57 isolates examined, 54 were genetically identical as determined by

analysis of the 218 AFLP fragments. Only three isolates produced fragment profiles

that differed from the other isolates tested; isolate PL735 lacked a 179-bp fragment

amplified using EcoRI-A/MseI-CG that was present in all other samples, isolate PL692

produced a 494-bp fragment using EcoRI-C/MseI-CT that was absent from all other

samples, and isolate PL388 lacked fragments of 125 bp amplified using EcoRI-A/MseI-

CG and 330-bp amplified using EcoRI-G/MseI-CT that were produced by all other

samples (Table 4-2). The Unweighted Pair Group Method with Arithmetic Mean

(UPGMA) was used to create a dendrogram that depicts the uniformity among most of

the analyzed isolates (Figure 4-2). Descriptive statistics generated by Popgene are as

follows (values are means ± std. dev): Observed number of alleles = 1.0183 ± 0.1345,

effective number of alleles [Kimura and Crow (1964)] = 1.0007 ± 0.0048, Nei's (1973)

gene diversity = 0.0006 ± 0.0046, and Shannon's Information index [Lewontin (1972)] =

0.0016 ± 0.0119 (51,70). All four polymorphisms were confirmed by repeating the AFLP

procedure using DNA samples that had been extracted from independent plate cultures

of each isolate. All three polymorphic isolates were recovered from redbay.

Microsatellite Analysis

Sequence comparisons of the aligned flanking regions and microsatellite loci

revealed 100% nucleotide identity among all United States isolates tested (PL: 159,

388, 570, 571, 692, and 735). Sequence differences were detected among the Asian

isolates PL1418 (Taiwan) and PL1467 (Japan) with the primer cpl, with PL1418

containing a single A to T substitution, and PL1467 having the addition of a single AC

72

microsatellite repeat (Figure 4-3). The chk primer pairs revealed an extra14 TTC

repeats within the microsatellite region of isolate PL1467 from Japan, whereas the

remaining Asian isolates (PL1417 and PL1418) were identical to the United States

isolates (Figure 4-4). In parsimony analyses, all United States isolates and PL1417

from Taiwan formed a single clade with 97% bootstrap support. PL1418, with a single

polymorphism, fell outside the United States clade with 100% bootstrap support, and

the Japanese isolate (PL1467) fell in another clade with 100% bootstrap support (Figure

4-5). Polymorphisms were confirmed by repeating the amplification and sequencing

reactions.

Sequencing Reactions

The sequencing reactions for PL692, PL735, and PL388 produced contigs of

1025-bp, 1028-bp, and 1021-bp respectively. GenBank BLASTn searches of the

isolates PL692, PL735, and PL388 revealed similarity to R. lauricola strain PL159

(GenBank Accession No. EU257806.1). BLASTn searches for the three polymorphic

isolates contained max identity 100%, query coverage 100%, and an e-value of 0.0,

indicating that the polymorphic isolates are probably R. lauricola and not another closely

related species. The isolates PL692, PL735, and PL388 have been deposited in

GenBank and given the accession numbers JF949721.1, JN019754.1, and JF797172.1,

respectively.

Pathogenicity Tests

United States isolates

All trees inoculated with the typical and polymorphic isolates of R. lauricola

displayed characteristic laurel wilt symptoms within 3 weeks, with no visible symptoms

on water-inoculated controls. External disease severity ratings were identical, with all

73

trees eventually dying. No significant differences were detected in regard to internal

disease severity and AUDPC among the isolates tested (Table 4-3). Typical colonies

of R. lauricola were recovered from all inoculated plants, and none were recovered from

water-inoculated controls.

Asian isolates

External and internal disease severity ratings were similar among inoculated

swamp bay and avocado plants (Table 4-5). On swamp bay, AUDPCs for PL1467 and

the United States PL571 were significantly greater than for PL1417 (Table 4-4). On

avocado, AUDPCs for all tested isolates were similar (Table 4-5). The pathogen was

recovered from all inoculated plants (Table 4-5).

Discussion

This is the first investigation of genetic and pathogenic diversity in R. lauricola.

The United States isolates in this study represent a thorough collection of the pathogen

as it moved throughout its current range in the USA, and the majority of the isolates

were from redbay, which is the primary host in the current laurel wilt epidemic (Table 4-

1, Figure 4-1). The 41 isolates from this host span the majority of the trees’ range that

has been affected by laurel wilt; which is also the area of highest redbay mortality

(8,17,22,81) (Figure 4-1). With the exception of isolates from X. glabratus, the

remaining isolates were collected from other naturally infected plants in the Lauraceae

in the United States, including the economically important avocado (63). Except for

redbay and the closely related species swamp bay (P. palustris), other naturally affected

species are far less common and, thus, are considered minor hosts in the laurel wilt

epidemic. Nonetheless, minor genetic variation was detected in the pathogen,

regardless of its host source. The AFLP analyses revealed a clonal population of the

74

pathogen. Ninety-five % (54 of 57) of the examined isolates belonged to the same

AFLP phenotype, whereas minor differences were detected in the remaining three

polymorphic isolates: PL692 and PL735 had a single site polymorphism, and PL388 had

two polymorphisms. The polymorphic isolates had AFLP profiles 99% similar to the rest

of the isolates, with no associated differences in cultural morphology, collection year,

host, collection location, or aggressiveness on swamp bay. Furthermore, the

microsatellite and flanking region sequence data were identical for all United States

isolates, and isolates that were deemed polymorphic by AFLP analysis were

indistinguishable when microsatellite loci were screened. That similar and/or more

genetic variation has been used to propose that populations of other pathogens are

clonal (14,44), supports the assumption that the R. lauricola population in the United

States is clonal.

In order to confirm the identity of the polymorphic AFLP isolates as R. lauricola

and not another Raffaelea species that may also be found in the mycangia of X.

glabratus (34, 35), pathogenicity tests and rDNA sequence analyses were performed.

Inoculations of the Asian isolates were conducted to ascertain if these foreign strains of

R. lauricola were able to incite disease in a comparable manner to their United States

counter-parts. Polymorphic (AFLP) and Asian isolates of R. lauricola caused typical

symptoms of laurel wilt on swamp bay and avocado, and were re-isolated from affected

plants, demonstrating that these isolates were pathogenic. In addition, rDNA SSU

sequences for these isolates were identical to those for R. lauricola accessions in

GenBank.

75

The microsatellite and flanking region sequences revealed a striking similarity

among the Taiwanese and United States isolates, with only a single nucleotide

polymorphism (SNP) between the two groups. The Japanese isolate PL1467 contained

polymorphisms at two of the six loci screened. The primer pair cpl revealed a single AC

addition to the repeat region, and primer chk having a larger insert of 14 TTC repeats.

The above data suggest a close relationship between Taiwanese and United States

populations of the pathogen, although work with more isolates would be needed to

conclude a substantial relationship. Clearly, more isolates from Asia are needed to

understand variation in this pathogen, possible differences in aggressiveness within

host species, and where the United States population may have originated. In addition,

a more global collection of R. lauricola and its vector (X. glabratus) would help explain if

the association between these two occurs only in the select regions that have been

sampled, or if their symbiosis is worldwide.

A screening program has begun to identify redbay individuals that tolerate laurel

wilt. Since laurel wilt is caused by an exotic pathogen and vector, it is unlikely that co-

evolved resistance mechanisms have yet occurred. However, history illustrates that

rare tolerant individuals can exist in populations of susceptible host trees (85). The

search for these rare tolerant individuals forms the basis of our laurel wilt screening

program. Many asymptomatic redbays have been identified in highly affected areas,

collected for clonal propagation, and are now undergoing testing. The knowledge that

the R. lauricola population in the United States is clonal, and that the few polymorphic

isolates detected had no differences in aggressiveness, suggests that the need for

multiple strains of the pathogen is not required for resistance screening. If no changes

76

occur in the pathogen’s genetic structure in the USA, it may also suggest that if tolerant

clones are found, their resistance factors may be durable.

77

Table 4-1. Host, collection dates, and origin of Raffaelea lauricola cultures used in this study.

Isolate Name

Host Collection date

Collection Location Collector GenBank/CBS Accession

PL735 Persea borbonia

2008 Columbia Co. FL J.A. Smith JN019754.1

PL634 P. borbonia 2009 Volusia Co. FL A. E. Mayfield III

PL635 P. borbonia 2009 Volusia Co. FL A. E. Mayfield III

PL638 P. borbonia 2009 Duval Co. FL M. Hughes


PL750 P. borbonia 2009 Clay Co. FL J.A. Smith

PL386 P. borbonia 2008 Alachua Co. FL M. Hughes



PL572 P. borbonia 2009 Clay Co. FL M. Hughes

PL696 P. borbonia 2008 Clay Co. FL M. Hughes

PL570 P .borbonia 2009 Clay Co. FL M. Hughes

PL571 P .borbonia 2009 Clay Co. FL M. Hughes

PL631 P. borbonia 2009 Okeechobee Co. FL

A. E. Mayfield III

PL955 P. borbonia 2010 Orange Co. FL M. Hughes

PL637 P .borbonia 2009 Osceola Co. FL A. E. Mayfield III

PL695 P. borbonia 2009 Marion Co. FL M. Hughes

PL636 P. borbonia 2009 Suwannee Co. FL A. E. Mayfield III


PL627 P .borbonia 2008 Duval Co. FL M. Hughes



PL756 P. borbonia 2006 Appling Co. GA S. W. Fraedrich

PL692 P. borbonia 2006 Appling Co. GA S. W. Fraedrich

JF949721.1

PL734 P. borbonia 2006 Evans Co. GA S. W. Fraedrich

PL629 P. borbonia 2009 McIntosh Co. GA M. Hughes

PL517 P. borbonia 2006 Glynn Co. GA S. W. Fraedrich

PL630 P. borbonia 2006 Wayne Co. GA S. W. Fraedrich

78

Table 4-1. Continued Isolate Name


Collection Location

Collector GenBank/CBS Accession

PL388 P. borbonia 2006 Pierce Co. GA S. W. Fraedrich

JF797172.1

PL736 P. borbonia 2005 Bryan Co. GA S. W. Fraedrich

PL751 P. borbonia 2005 Bryan Co. GA S. W. Fraedrich

PL738 P. borbonia 2005 McIntosh Co. GA S. W. Fraedrich

PL390 P. borbonia 2006 Colleton Co. SC S. W. Fraedrich

PL1532 P. borbonia 2009 Colleton Co. SC M. Hughes

PL1533 P. borbonia 2009 Colleton Co. SC M. Hughes

PL158 P. borbonia 2004 Beaufort Co. SC S. W. Fraedrich


PL382 P. borbonia 2006 Bamberg Co. SC S. W. Fraedrich

JF797171.1


PL716* P. borbonia 2009 Jackson Co. MS J.J. Riggins GQ996063

PL717 P. borbonia 2009 Jackson Co. MS J.J. Riggins

PL640 P. palustris 2009 Duval Co. FL A. E. Mayfield III

PL641 P. palustris 2009 St. Johns Co. FL A. E. Mayfield III

PL159* P. americana 2007 Duval Co. FL A. E. Mayfield III

EU257806

PL632 P. americana 2009 Indian River Co. FL

A. E. Mayfield III

PL642 P. americana 2009 Brevard Co. FL J. Peña

PL633 C. camphora 2009 Baker Co. FL A. E. Mayfield III

PL378 C. camphora 2005 McIntosh Co. GA S. W. Fraedrich

PL392* Litsea aestivalis

2008 St. Johns Co. FL M. Minno FJ514097

PL516 L. aestivalis 2008 St. Johns Co. FL M. Minno

PL393 L. aestivalis 2008 St. Johns Co. FL M. Minno

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Table 4-1. Continued Isolate Name


Collection Location

Collector GenBank/CBS Accession

PL753 L. aestivalis 2006 Effingham Co. GA

S. W. Fraedrich

PL380 L. aestivalis 2006 Effingham Co. GA

S. W. Fraedrich

PL377 Lindera melissifolia

2006 Effingham Co. GA

S. W. Fraedrich

PL379 Sassafras albidum

2005 Liberty Co. GA

S. W. Fraedrich

PL519 S. albidum 2006 Screven Co. GA

S. W. Fraedrich

PL389 Xyleborus glabratus

2007 Beaufort Co. SC

S. W. Fraedrich

PL1417 X. glabratus 2009 N. Taiwan Hye Young HQ688667/ CBS 129001

PL1418 X. glabratus 2009 N. Taiwan Hye Young HQ688666/ CBS 129006

PL1467 X. glabratus 2009 Kyushu, Japan

D. McNew HQ688668/ CBS 129007

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Table 4-2. Summary of AFLP fragment analysis of R. lauricola isolates collected within the United States.

EcoRI primer extension

MseI primer extension

Fragments scored

Fragment size range (bp)

Polymorphic fragments

Polymorphisms

(e9m9)A CG 40 36-520 2

PL388 (-125bp band) PL735 (-179bp band)

(e12m9)G CG 34 44-524 0 (e11m20)C CA 54 32-570 0

(e11m21)C CT 34 34-576 b 1 PL692 (+ 494bp band)

(e12m20)G CA 40 31-541 0

(e12m21)G CT 16 34-332 1 PL388 (-330bp band)

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Figure 4-1. Map of SE United States indicating location and host species of R. lauricola isolates

82

Figure 4-2. United States AFLP fragment analysis based on a Pearson (r) coefficient

with the Dendro-UPGMA program, with artificial outgroup. PL 388, 692, and 735 represent AFLP polymorphic isolates.

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Figure 4-3. Aligned microsatellite and flanking region sequence reads for the cpl primer pair. PL 159, 570, 571 are of

United States origin with standard AFLP profile, PL 388, 692, and 735 are AFLP polymorphic and of United States origin, PL1417 and PL1418 are from Taiwan, and PL1467 is from Japan.

84

Figure 4-4. Aligned microsatellite and flanking region sequence reads for the chk primer pair. PL 159, 570, 571 are of

United States origin with standard AFLP profile, PL 388, 692, and 735 are AFLP polymorphic and of United States origin, PL1417 and PL1418 are from Taiwan, and PL1467 is from Japan.

85

Figure 4-5. Microsatellite and flanking region sequence analysis based on three-item

matrix (3TS) generated by the program TAXODIUM version 1.0. Maximum Parsimony analysis with 1000 bootstrap replicates was conducted on the program PAUP*, with an artificial outgroup. PL1417 and PL1418 are from Taiwan PL1467 is from Japan. All other isolates are from the United States.

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Table 4-3. Pathogenicity of AFLP polymorphic isolates from United States on swamp

bay.

Potted swamp bay seedlings were inoculated with the indicated isolates as described in the text. PL571 served as a positive control and water inoculated plants as negative controls (data not shown). Values denote means ± standard error. Values within columns are not significantly different according to Fisher’s LSD at P = 0.05.

Host

Isolate

External Disease Severity

Internal Disease Severity

AUDPC

Fungal Recovery

PL388 95.0 ± 0.0 A 87.5 ± 0.1 A 19.4 ± 3.3 A 2/2

PL692 95.0 ± 0.0 A 77.5 ± 0.1 A 19.2 ± 2.2 A 2/2

Swamp bay

PL735 95.0 ± 0.0 A 90 ± 0.1 A 20.9 ± 1.8 A 2/2

PL571 95.0 ± 0.0 A 85 ± 0.1 A 21 ± 0.6 A 2/2

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Table 4-4. Pathogenicity of Asian isolates of R. lauricola on swamp bay

Host Isolate

External Disease Severity

Internal Disease Severity

AUDPC Fungal Recovery

PL1417 82.5 ± 0.1 A 57.5 ± 14.9 A 19.5 ± 2.3 A 2/2

PL1418 95.0 ± 0.0 A 73.8 ± 16.6 A 24.3 ± 1.5 AB 2/2

Swamp bay

PL1467 95.0 ± 0.0 A 91.3 ± 8.8 A 27.8 ± 0.5 B 2/2

PL571 95.0 ± 0.0 A 92.3 ± 6.0 A 27.9 ± 0.8 B 2/2

Potted swamp bay seedlings were inoculated with the indicated isolates as noted in the text. PL571 served as a positive control and water inoculated plants as negative controls (data not shown). Values denote means ± standard error. Values within columns followed by different letters are significantly different according to Fisher’s LSD at P = 0.05.

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Table 4-5. Virulence of Asian isolates of R. lauricola on avocado

Host

Isolate

External

Disease Severity

Internal Disease

Severity

AUDPC

Fungal

Recovery

PL1417 48.3 ± 0.2 A 40 ± 16.1 A 13.1 ± 6.2 A 2/2

PL1418 68.3 ± 0.3 A 48.3 ± 21.9 A 18.8 ± 7.3 A 2/2

Avocado PL1467 71.7 ± 0.2 A 54.3 ± 22.3 A 20.7 ± 4.0 A 2/2

PL571 71.7 ± 0.1 A 60 ± 10.4 A 19.6 ± 3.5 A 2/2

Potted, grafted avocado plants, cv. ‘Simmonds’, were inoculated with the indicated isolates as indicated in the text. PL571 served as a positive control and water inoculated plants as negative controls (data not shown). Values denote means ± standard error. Values within columns are not significantly different according to Fisher’s LSD at P = 0.05.

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CHAPTER 5 THE SCREENING OF REDBAY (Persea borbonia) SELECTIONS AGAINST THE

LAUREL WILT PATHOGEN, Raffaelea lauricola

Introduction

Laurel wilt disease, caused by the exotic fungal pathogen Raffaelea lauricola has

been the primary cause of redbay, Persea borbonia, mortality since the introduction of

its vector, the redbay ambrosia beetle Xyleborus glabratus in the USA in 2002

(17,22,33,81). Native to the coastal areas of the southeast United States, redbay is an

attractive evergreen that forms a dominant understory component of many coastal

forest communities and is important in urban landscapes (11,16,104). Laurel wilt has

caused redbay losses of 90% or higher in portions of Florida and Georgia (17,104).

There are limited management strategies for laurel wilt. Vector control is

problematic due to the insect’s secluded lifestyle in host sapwood, complicated by the

possibility of few beetles escaping control treatments and establishing new disease foci.

As in Dutch elm disease and oak wilt in the United States, the fungicide propiconazole

prevented laurel wilt development of redbay and avocado (Persea americana)

(46,61,75,86). Although suitable for high value trees, the high costs and short term

efficacy of treatment makes chemical management impractical for a forest setting.

Host resistance has been a focus of breeding programs for many forest tree

diseases (e.g. Dutch elm disease, white pine blister rust, chestnut blight, and Port-

Orford-cedar root rot) (85). Selection for laurel wilt resistance became possible where

rare individuals of redbay survived recent epidemics. The purpose of this study was to

develop and implement a resistance-screening program for redbay against laurel wilt

disease. Prior results on the propagation of redbay, genetic diversity of the pathogen,

isolate virulence, and inoculum dosage were referenced when selecting putatively

90

resistant germplasm. These trials will help develop a more efficient and effective redbay

screening program.


Field Sites and Disease Pressure Surveys

Based on advice from various collaborators, six field sites were examined in

2007-2009 for laurel wilt-tolerant candidates. Two sites each in Florida, Georgia, and

South Carolina, were chosen due to prior abundance of redbay and high subsequent

mortality due to laurel wilt. The sites in Florida were Ft. George Island near the

Kingsley Plantation (30°24’35”N 81°25’50”W) and Fort Clinch State Park (30°40’05”N

81°26’03”W). Georgia sites included the Cumberland Island National Seashore Park

(30°51’53”N 81°26’59”W) and the maritime forest of St. Catherines Island (31°38’00”N

81°09’34”W). The South Carolina sites were Hunting Island State Park (32°21’58”N

80°26’40”W) and Edisto Beach State Park (32°30’41”N 80°18’23”W).

After initial surveys of each field location, 10 to 22 healthy/asymptomatic trees >

7.5 cm diameter at breast height (DBH) were selected for monitoring and propagation

per site. A total of 84 trees were tagged with permanent metal markers and GPS

coordinates recorded. Ultimately, 10 putatively resistant candidate trees were made the

centers of 1/5 acre circular plots in each field site. The spatial distribution and DBH

were recorded for all live and dead redbays over 2.5 cm stem diameter, and laurel wilt

disease incidence was calculated for each plot.

Periodically the survival of candidate germplasm was assessed. Those that died

where checked for vascular discoloration and evidence of ambrosia beetle activity (both

indicators of laurel wilt), and were no longer considered as resistant in future studies.

Due to the high mortality of chosen candidate trees within the Fort Clinch field location,

91

additional trees were selected in October 2010 (clones FCK – FCV). Additional

resistance candidates were also selected from the St. Catherines Island location (clones

SCIL – SCIV). For these additional resistance candidates selected, beetle trapping and

the establishment of disease plots were omitted.

Beetle Trapping Surveys

With the exception of the new Fort Clinch and St. Catherines selections, beetle

trapping surveys were conducted in each plot to monitor X. glabratus. For each plot, a

single trap was randomly placed, collected after 2 weeks, and examined for numbers of

X. glabratus. Each trap was replaced once, for a total of 2 traps within a period of 4

weeks. Traps were 10 cm x 30 cm sticky-cards + manuka oil lures (Synergy

Semiochemical) attached to 30 cm x 30 cm Plexiglas squares on wooden posts (Figure

5-1) (31). Trapping was conducted for at least 4 weeks between July 2009 and

February 2010.

Inoculation Experiment 1

In July 2010, nine putatively resistant redbay clones and a field susceptible clone

(FCF) were planted at the Plant Science Research and Educational Unit (PSREU) in

Citra, Florida. A total of 44 redbays (20 – 30 mm stem diameter) were arranged in

randomized complete block design, with four replicates per candidate clone (Table 5-2).

For the FCF clone, four additional replicates were planted for use as water-inoculated

controls. Plants were watered daily with a micro-irrigation system.

After 2 months of acclimatization, inoculation experiments were conducted to

assess resistance to R. lauricola. Results from a previous study indicated that all

American R. lauricola isolates analyzed shared over 99% genetic similarity, with no

differences in virulence (Hughes et al. manuscript in preparation). Thus, a single,

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representative fungal isolate representing the dominant genetic profile (PL 571GenBank

accession JQ861956.1) was chosen for inoculum. Conidia were gathered by flooding

the culture plate with 2 mL of sterile water, agitation via cell spreader, and quantified

with a hemacytometer. Conidium viability was assayed on CSMA. Two shallow holes

were drilled in each plant with a 7/64” titanium bit at a 45° downward angle and special

care to stay within the xylem. Trees received 50 μL of a spore suspension (106

conidia/mL) per hole, with 100 μL per tree total (105 conidia), then sealed with Parafilm.

One to two water-inoculated controls per clone received 50 μL of sterile water per drill

hole (100 μL total), and were sealed with Parafilm.

Trees were rated weekly for laurel wilt with the following scale, until 105 days

post inoculation.






In addition to disease severity, records were taken of the area under the disease

progress curve (AUDPC), days until the first appearance of symptoms (incubation

period), rate of disease development, and the percent mortality per clone.


In April 2011, 45 redbay clones were planted at the PSREU in Citra, FL (Figure

5-2). Plants were arranged in a completely randomized design with three to six

replicates per clone, depending on availability.

In September 2012, 18 putatively resistant clones with stem diameters greater

than 15 mm were inoculated with isolate PL571 of R. lauricola, with 1-2 ramets (plants)

93

serving as water inoculated controls. In general, the same protocols were used as in

the prior experiment. However, due to the results of previous inoculum density studies,

3.0 x 103 conidia per tree were used. This change in inoculum concentration reflected

the ability of 103 conidia per tree to consistently induce wilt in redbays, while also

attempting to avoid the effects of over-inoculation and overwhelming possible resistance

mechanisms. Disease ratings were taken every 4th day until 124 days post inoculation,

according to the following scale.











10 = 91-100% crown wilt

In addition to disease severity, records were taken of AUDPC, incubation period,

rate of disease development, and the percent mortality per clone. Stem diameter (mm)

measurements were also taken for use as a covariate in the data analysis.


The area under the disease progress curve (AUDPC) using the midpoint rule

method was calculated with Microsoft Excel in accordance to Campbell and Madden

(1990).


Where: t= time in days, y= proportion of affected canopy (disease severity), and

n= the number of observations.

94

The NLIN procedure in SAS version 9.3 (SAS Institute Inc., Cary, NC) was used

to estimate the rate of disease development using a Gompertz disease progress model.

The GLIMMIX procedure was used to estimate the least squared means and standard

error of the rate of disease development, incubation period, AUDPC, and final disease

severity. The type III test for fixed effects was performed using the GLIMMIX procedure

with candidate tree location as a random effect, followed by a multiple comparison of

means according to Tukeys HSD at P = 0.05. Contrast analysis was conducted using

the ESTIMATE statement to test for the effects of clone provenance. All parameters

were checked for normality by use of the Conditional Pearson Residuals. For

inoculation experiment #2, stem diameter measurements from all redbays were

recorded for use as a covariate for the GLIMMIX procedure with P = 0.05.

Results

Field Sites and Disease Pressure Surveys

Nine of the 10 redbays on Fort George Island (mean dbh = 12.5 cm) survived

(Table 5-1). A mean of 18.5 trees occurred around each candidate tree, which had a

mean incidence of laurel wilt of 65.9%. At Ft. Clinch, only seven (32%) of the 22

selected trees (mean DBH = 16.3cm) survived. For the first 10 trees there was a mean

of 14.6 associated redbays per plot with a mean incidence of laurel wilt of 63.6%. Eight

of the 10 trees on Cumberland Island (mean DBH = 10.4 cm) survived (Table 5-1). A

mean of 8.2 associated trees had a 73% mean incidence of laurel wilt. All 10 monitored

trees on Saint Catherines Island survived, and there was a mean of 12.4 redbay trees

per plot with a mean incidence of laurel wilt of 86.6%. In Edisto Beach State Park 11

candidate trees had a mean DBH of 11.1cm, five of which survived. A mean of 25.8

redbays, with 50% disease incidence, were associated with each tree (Table 5-1). In

95

Hunting Island State Park, an average of 35.2 redbays were associated with each of 10

candidate trees (mean DBH = 11.8cm). Plots averaged, disease incidence of 58%, and

88% candidate redbay survival (Table 5-1). As of July 2012, 70% of a total of 84

putatively resistant redbays survived.

Beetle Trapping Surveys

Highly variable captures of X. glabratus were recorded in different plots and

different sites. The traps from Florida field sites of Ft. George Island and Ft. Clinch

State Park caught 8 and 35 redbay ambrosia beetles, respectively (Table 5-1). Within

Georgia, at Cumberland Island had 8 beetles were captured, while none were found in

the traps at St. Catherines Island. The traps in the field sites of Edisto Beach and

Hunting Island state parks, South Carolina contained 15 and 14 redbay ambrosia

beetles, respectively (Table 5-1).


Differences in incubation period (14 to 19.3 days) (Figure 5-3) and the rate of

disease development (0.04 to 0.31) among the inoculated clones were not significant

(Table 5-2). Although temporal differences in disease development were not detected,

AUDPC and final severity differed among clones. AUDPCs ranged from 39.51 to 73.10,

with clones FGC and EIE performing statistically better than FGD, EIA, EIB, and EIC (P

= 0.04) (Tables 5-2 and 5-3). Based on mean final severity, FGC was the most tolerant

clone with a final severity of 56.8, significantly better than all other clones that were

tested, which reached maximum severity score of 88.5 (midpoint of a 4 severity rating)

(P = 0.02) (Tables 5-2 and 5-3). Only FGC (50%) had any surviving replicates (Table 5-

2). No differences in incubation period, rate of disease development, AUDPC, final

severity and mortality were detected between the field susceptible control (FCF) and

96

selections other than FGC. Water inoculated FCF plants remained asymptomatic

throughout the duration of the experiment.

Contrast analyses were performed to investigate the possible effects of

geographic location and candidate tree provenance on disease development

parameters (Table 5-4). Comparisons of state of origin revealed that the incubation

period of the trees from South Carolina was longer than Florida trees (P = 0.03),

specifically with the clones from Fort George Island, FL developing symptoms faster

than the clones from Edisto Beach State Park, SC (P = 0.04) (Table 5-4). No

differences in contrasts were detected among states or field location for the rate of

disease development, AUDPC, and final severity (Table 5-4).


Incubation periods among clones in experiment 2 ranged from 16 -76 days, with

HIL taking significantly longer to display symptoms than FGI, EIF, EIG, and HIE (Table

5-5) (Figure 5-4). The rate of disease development ranged from 0.06 to 0.23, with that

for HIE being significantly faster than EID (Table 5-5). AUDPCs ranged from 12.65 to

97.1, with HIL having significantly smaller AUDPC than 11 other clones (Table 5-5).

Nine clones, with AUDPCs above 85.0 (FGA, FGD, FGI, EIF, EIG, EIT1, EIT2, HIE, and

HIG) were most susceptible to laurel wilt (Table 5-5). Final severity scores were from

17.5 – 95.0, with scores above 80.0 denoting highly susceptible clones (P = 0.05)

(Table 5-5). HIL, HIA and FGC were most tolerant compared to the other clones tested,

with final severities of 17.5, 35.0, and 38.8, respectively. By 124 days post inoculation,

75% of the replicates of 10 clones had died, two reached 50% mortality, and five had no

plants die (Table 5-5).

97

Stem diameter was significantly related to AUDPC (P = 0.002) and final severity

(P = 0.01), but was not significantly related to incubation period and disease

development rate (Table 5-6). The contrast analysis conducted for experiment 2

compared the performance of the top 3 ranked clones (per disease parameter), and

tested the effects of clone home state and field site. Contrasts among states of origin

and field sites were insignificant for incubation period and disease development rate.

Comparisons among the field sites for Hunting Island State Park vs. Fort George Island

revealed a difference for AUDPC (P = 0.05) and final severity (P = 0.005), with Hunting

Island State Park showing less disease than clones from Fort George Island (Table 5-

7). The comparison of Fort George Island and the Edisto Beach State Park field sites

was statistically significant for AUDPC (P = 0.04) and final severity (P = 0.03), with the

Edisto Beach clones being most susceptible (Table 5-7). Within South Carolina,

differences were detected between the field sites Hunting Island State Park and Edisto

Beach State Park for AUDPC (P = 0.0001) and final severity (P = 0.001) (Table 5-7),

with clones from Edisto Beach State Park more susceptible (Table 5-7). Contrast

analysis of the top three ranked clones (per disease parameter) vs. all other clones was

conducted to confirm superiority of the selected clones. For incubation period, AUDPC

and final severity, the top three clones were FGC, HIA, and HIL. HIA, HIL and EID had

the lowest rates of disease development, while FGC ranked 4th. The top three clones

were significantly better than the others for all disease parameters (P = 0.001 or better).

Water inoculated controls remained asymptomatic throughout the study.

Discussion

This study represents a first attempt to locate and screen putatively laurel wilt

resistant redbay germplasm. In the search for disease resistance in forest trees the first

98

component of a breeding program is the selection of phenotypically superior material

(85). Redbay individuals with putative resistance to laurel wilt were identified in the

present study by first selecting and then propagating large survivors (over 7.5 cm DBH)

in areas with high laurel wilt mortality. Plots were established around candidate trees to

estimate disease pressure (redbay abundance and laurel wilt incidence), and the vector

was trapped to confirm its continued presence on the site. This snapshot of each site’s

infestations may provide future clues about the epidemiology of the disease, allowing for

further fine tuning of the germplasm selection process.

As expected, disease escapes were found in the present work. Even though

candidate trees were exposed to heavy disease pressure, 30% died from laurel wilt

after they were selected. In addition, different epidemiological stages of laurel wilt were

apparent among sites. For example, on Saint Catherines Island the primary wave of the

epidemic may have passed, based on the high level of disease incidence (≈87%),

survival of all candidate trees, and absence of X. glabratus captures there. In contrast,

a lower disease incidence (≈64%), high vector capture, and low survival rate (≈32%) in

Fort Clinch State Park may indicate an active, ongoing epidemic.

Based on AUDPC, final severity and mortality scores, clone FGC was clearly

superior to the others that were tested in inoculation experiment 1. More than 2 years

after this trial, the surviving inoculated clones of FGC have completely recovered.

The expansion of the disease severity scale in the second inoculation

experiment, along with more frequent ratings, enabled refined assessments of disease

progression. According to this study, stem diameter/plant size has an effect on

symptom development, with larger trees appearing more susceptible. This positive

99

correlation between plant size and symptom severity was previously described for

avocado inoculation trials (75). Regarding redbay, the present data correlate well with a

prior survey in which an association was detected between tree size and mortality (17).

In nature, size-associated mortality may result from both vector host preference and the

increased susceptibility of larger plant material. Since this screening program is still in

its infancy, large clonal material is a limiting factor. However, among the tested clones

FGC was one of the largest, suggesting that it might possess true resistance factors.

Analysis of means adjusted by the stem diameter covariate also indicated the

superiority of the best clones in this trial (data not shown).

A major decision in a resistance screening program is the choice of an inoculum

density that is effective in causing realistic disease symptoms. Although using levels

that mimic natural inoculation might be desirable, it is not be clear what these levels are.

In contrast, some screening programs have utilized very high levels of inoculum without

apparent reflection on these “natural” levels. For example, DED-tolerant selections of

American elm (Ulmus americana) have used consistently high concentrations of

Ophiostoma novo-ulmi (55,92,93,94,95).

The goal of the second inoculation experiment was to identify tolerance to laurel

wilt that might be evident under natural conditions. Two things suggest that 3.0 x 103.

conidia per tree, which was used in the second experiment, is a realistic number. First,

in other experiments, consistent wilt and mortality were achieved on redbay with 103

conidia (Hughes et al. manuscript in preparation). Second, X. glabratus harbors

hundreds to thousands of spores in its mycangia (35, 36). Thus, a single beetle is

100

presumably capable of infesting a healthy tree with enough inoculum to cause the lethal

development of this disease.

The second inoculation experiment screened 18 clones, with 13 new additions

and five that were screened in the first experiment. Inclusion of five previously

screened clones served a dual purpose, added replication per clone and validation of

the change in inoculum concentration. Similar results were obtained for clones FGA,

FGB, FGC, FGD, and FGF for final severity in both experiments. FGC was among the

most tolerant in both experiments. In the second experiment HIL ranked among the top

three clones for three of the four disease parameters, while HIA and FGC were among

the top three in three of four parameters. Contrast analysis statistically confirmed the

performance of these clones to be better than the rest at P = 0.001.

These trials establish the groundwork for a functional laurel wilt screening and

breeding program, in which the goal is to identify a variety of resistant redbays to use in

reforestation and the urban landscape. FGC, HIA and HIL represent the first selections

with tolerance to laurel wilt. Additional propagation and testing of these clones and their

progeny will be conducted in order to improve upon the current results achieved. Tree

breeding programs for disease resistance are often long-term projects, with numerous

replications and screenings needed before developed clones are ready for deployment

(25,82,85,95). Future plans for the present program include: testing additional clones in

the current germplasm collection; assessing heritability of tolerance in seed-derived

progeny; histological examinations of clones to assess anatomical features associated

with tolerance; and determining whether volatile profiles of clones differ and influence

beetle attraction.

101

Figure 5-1. Beetle trap used for the capture of X. glabratus. Arrow indicates manuka oil lure.

102

Table 5-1. Selected redbay trees and plot characteristics for laurel wilt resistance study.

Field Location Clone DBH (cm) Total Trees per Plot Disease Incidence Status RAB Capture

Ft. George Island, FL

FGA 14.8 7 71% alive 3

FGB 12.8 14 64% alive 0

FGC 10.3 30 63% alive 0

FGD 15.8 24 42% alive 0

FGF 11.2 27 96% alive 2

FGG 9.4 22 64% alive 1

FGH 14.6 9 78% alive 1

FGI 12.2 4 5% alive 0

FGJ 13.2 2 5% alive 1

FGK 10.5 11 81% dead 0

Mean ± se 12.5 ± 0.7 18.5 ± 3.2 65.9% ± 5.1 90% survival Sum = 8

Fort Clinch State Park, FL

FCA 17.0 17 35% dead 6

FCB 21.9 13 77% dead Stolen Trap

FCC 22.0 6 67% dead 1

FCD 15.3 14 36% dead 0

FCE 24.5 13 69% dead 0

FCF 15.1 15 87% dead 8

103

Table 5-1. Continued


FCG 24.7 12 67% dead 1

FCH 24.3 11 73% dead 1

FCI 10.2 17 65% dead 11

FCJ 16.6 20 60% dead 7

FCK 17.1 * * alive *

FCL 10.1 * * alive *

FCM 10.3 * * alive *

FCN 11.7 * * alive *

FCO 9.9 * * dead *

FCP 9.3 * * dead *

FCQ 12.6 * * dead *

FCR 12.7 * * dead *

FCS 11.0 * * alive *

FCT 19.2 * * dead *

FCU 25.1 * * alive *

FCV 18.1 * * alive *


Cumberland Island, GA

CIA 7.5 8 63% alive 0

CIB 6.7 5 80% alive 1

CID 9.6 8 50% alive 0

104



CIE 9.2 5 60% alive 2

CIG 11.1 15 80% alive 0

CIH 14.0 10 70% alive 1

CII 8.9 11 91% alive 1

CIJ 13.5 10 80% alive 0

CIK 12.7 9 56% dead 1

CIM * 1 100% dead 2


SCIA 7.8 17 88% alive 0

SCIB 9.7 13 92% alive 0

Saint Catherines Island, GA SCIC 11.2 11 91% alive 0

SCID 14.2 21 86% alive 0

SCIE 14.2 8 88% alive 0

SCIF 10.1 19 95% alive 0

SCIG 8.0 11 91% alive 0

SCIH 16.5 6 83% alive 0

SCII 12.3 5 60% alive 0

SCIJ 12.5 13 92% alive 0

SCIL 10.6 * * alive *

SCIM 9.4 * * alive *

105



SCIN 9.1 * * alive *

SCIO 13.8 * * alive *

SCIP 13.3 * * alive *

SCIQ 14.9 * * alive *

SCIR 11.4 * * alive *

SCIS 9.9 * * alive *

SCIT 11.0 * * alive *

SCIU 12.1 * * alive *

SCIV 15.6 * * alive *


EIA 12.7 47 45% dead 5

EIB 9.0 18 50% dead 1

Edisto Beach State Park, SC EIC 10.1 46 76% dead 0

EID 11.0 30 0% alive 0

EIE 15.0 12 50% dead 0

EIF 10.6 23 96% alive 1

EIG 10.2 18 33% alive 1

EIH 10.3 18 61% alive 2

EIT1 10.1 53 64% alive 1

EIT2 12.1 5 40% alive 3

106



EIT3 * 14 36% dead 1


HIA 11.0 20 75% alive 2

HIB 9.4 50 68% dead 3

Hunting Island State Park, SC HIC 7.8 64 52% dead 2

HID 10.5 43 58% alive 0

HIE 12.1 4 5% alive 1

HIF 24.4 30 57% alive 2

HIG 10.8 44 64% alive 0

HIH 10.6 30 47% alive 3

HIK 11.1 32 59% alive 0

HIL 10.7 35 51% alive 1


Plot characteristics include: DBH = diameter at breast height in cm, Total trees per plot = number of redbays per plot, Disease incidence = redbay disease incidence per plot (dead redbay/total redbay), Status = resistance candidate health (live or dead) as of 7-20-12, and X. glabratus (RAB) captures after 4 weeks of trapping. Means are represented ± standard error (se). * indicates measurements were not taken. Last monitoring visit was 7-20-12.

107

Figure 5-2. Redbay plot for laurel wilt resistance experiment 2. Photo taken before inoculations on 9-12-12 at the Plant

Science Research and Education Unit, in Citra FL.

108

Table 5-2. Experiment 1. Responses of redbay clones to artificial inoculation with R. lauricola (105 conidia).

Field Location Clone Incubation (d)

Disease Development Rate AUDPC Final Severity % Mortality %


FGA 14.0 ± 1.2 a 0.31 ± 0.09 a 60.78 ± 7.7 ab 88.5 ± 6.0 a 100

FGB 14.0 ± 1.2 a 0.26 ± 0.09 a 59.95 ± 7.7 ab 88.5 ± 6.0 a 100

FGC 14.0 ± 1.2 a 0.26 ± 0.09 a 39.51 ± 7.7 a 56.8. ± 6.0 b 50

FGD 14.0 ± 1.2 a 0.16 ± 0.09 a 70.42 ± 7.7 b 88.5 ± 6.0 a 100

FGF 14.0 ± 1.2 a 0.11 ± 0.09 a 60.18 ± 7.7 ab 88.5 ± 6.0 a 100

Ft. Clinch State Park, FL

FCF 14.0 ± 1.2 a 0.21 ± 0.09 a 54.35 ± 7.7 ab 88.5 ± 6.0 a 100

Edisto Beach State Park, SC

EIA 14.0 ± 1.2 a 0.15 ± 0.09 a 73.10 ± 7.7 b 88.5 ± 6.0 a 100

EIB 14.0 ± 1.2 a 0.27 ± 0.09 a 71.38 ± 7.7 b 88.5 ± 6.0 a 100

EIC 15.8 ± 1.2 a 0.18 ± 0.09 a 72.79 ± 7.7 b 88.5 ± 6.0 a 100

EIE 19.3 ± 1.2 a 0.04 ± 0.09 a 44.83 ± 7.7 a 88.5 ± 6.0 a 100

Inoculations were performed with the isolate PL571, with water inoculated plants as negative controls (data not shown). Values are the means ± standard error. Values within columns separated by different letters are significantly different based on Tukeys HSD at P = 0.05

109

Table 5-3. Experiment 1. Summary of analyses of variance (Type III Test of Fixed Effects) for redbays inoculated with R. lauricola (105 conidia).

Type III Test of Fixed Effects

Source of variation df Incubation (d)

Disease Development Rate AUDPC Final Severity %

clone 9 F= 2.0 P = 0.07 F = 0.96 P = 0.49

F = 2.36 P = 0.04* F = 2.78 P = 0.02*

residual error 30 Values denote the F estimate and P value. * denotes significance at P = 0.05.

110

Table 5-4. Experiment 1. Contrast analysis of redbays inoculated with R. lauricola (105 conidia).

Contrasts Incubation (d) Disease Development Rate AUDPC Final Severity %

States

FL vs. SC 1.75 (P = 0.03)* -0.06 (P = 0.30) 8.00 (P = 0.12) 0.05 (P = 0.18)

Field Sites

FG vs. FC -13 E-16 (P = 1.00) 0.01 (P = 0.94) 3.81 (P = 0.65) -0.06 (P = 0.34)

FG vs. EB -1.75 (P = 0.04)* 0.06 (P = 0.31) -7.36 (P = 0.16) -0.06 (P = 0.13)

FC vs. EB -1.75 (P = 0.20) 0.05 (P = 0.59) -11.17 (P = 0.20) 6.94 E-18 (P = 1.00)

Classes of comparison: state of origination and field site location. Values denote estimate and (P value). * denotes significance at P = 0.05. States: SC= South Carolina, FL= Florida. Field Sites: FG= Fort George Island FL, FC = Fort Clinch State Park FL, EB = Edisto Beach State Park SC.

111

Figure 5-3. Experiment 1. Redbays showing wilt symptoms 35 days post inoculation. Photo taken 10-29-10 at the Plant Science Research and Education Unit in Citra, FL.

112

Figure 5-4. Experiment 2. Redbays showing wilt symptoms 40 days post inoculation. Photo taken 10-22-12 at the Plant Science Research and Education Unit in Citra, FL.

113

Table 5-5. Experiment 2. Responses of redbay clones to artificial inoculation with R. lauricola (3.0 x 103 conidia).

Field Location Clone

Stem Dia. (mm) Incubation (d)



FGA 55.2 ± 0.6 18 ± 13.5 ab 0.15 ± 0.03 ab 91.0 ± 10.9 c 95.0 ± 11.7 c 75

FGB 46.9 ± 0.5 20 ± 19.1 ab 0.10 ± 0.04 ab 78.8 ± 15.5 bc 90.0 ± 16.5 c 50

FGC 40.9 ± 4.0 52 ± 13.5 ab 0.09 ± 0.03 ab 28.4 ± 10.9 ab 38.8 ± 11.7 ab 0

FGD 41.1 ± 3.2 17.3 ± 15.6 ab 0.18 ± 0.04 ab 91.4 ± 12.6 c 95.0 ± 13.5 c 100

FGF 42.0 ± 7.6 21 ± 13.5 ab 0.20 ±0.03 ab 74.7 ± 10.9 bc 87.5 ± 11.7 c 75

FGG 34.1 ± 2.6 36 ± 19.1 ab 0.12 ± 0.04 ab 62.6 ± 15.5 ab 80.0 ± 16.5 c 50

FGI 47.6 ± 2.6 16 ± 13.5 a 0.12 ± 0.03 ab 86.4 ± 10.9 c 95.0 ± 11.7 c 100

FGJ 40.4 ± 2.1 31 ± 13.5 ab 0.12 ± 0.03 ab 45.7 ± 10.9 ab 62.5 ± 11.7 bc 0

St. Catherines Island, GA SCIJ 25.6 ± 0.0 16 ± 27.1 ab 0.14 ± 0.06 ab 71.3 ± 21.9 ab 75.0 ± 23.3 abc 0

114

Table 5-5. Continued.

Field Location Clone

Stem Dia. (mm)

Incubation (d)


Edisto Beach State Park, SC EID 17.5 ± 0.9 50 ± 13.5 ab 0.06 ± 0.03 a 39.6 ± 11.0 ab

87.5 ± 11.7 c 0

EIF 43.3 ± 4.0 17 ± 13.5 a 0.18 ± 0.03 ab 92.3 ± 11.0 c 95.0 ± 11.7 c 100

EIG 38.0 ± 1.6 17 ± 13.5 a 0.15 ± 0.03 ab 90.9 ± 11.0 c 95.0 ± 11.7 c 100

EIT1 41.2 ± 5.2 16 ± 19.1 ab 0.22 ± 0.04 ab 93.9 ± 15.5 c 95.0 ± 16.5 c 100

EIT2 32.1 ± 0.0 24 ± 27.1 ab 0.19 ± 0.04 ab 91.3 ± 21.9 c 95.0 ± 23.3 bc 100

Hunting Island State Park, SC HIA 32.9 ± 0.0 40 ± 27 ab 0.06 ± 0.06 ab 21.3 ± 21.9 ab

35.0 ± 23.3 abc 0

HIE 31.5 ± 2.8 17 ± 13.5 a 0.23 ± 0.03 b 95.7 ± 10.9 c 95.0 ± 11.7 c 100

HIG 31.4 ± 5.0 12 ± 19.1 ab 0.22 ± 0.04 ab 97.1 ± 15.5 c 95.0 ± 16.5 c 100

HIL 23.9 ± 2.8 76 ± 13.5 b 0.08 ± 0.03 ab 12.65 ± 10.9 a 17.5 ± 11.7 a 0

Inoculations were performed with the isolate PL571, with water inoculated plants as negative controls (data not shown). Values are the means ± standard error. Values within columns separated by different letters are significantly different based on Tukeys HSD at P = 0.05

115

Table 5-6. Experiment 2. Summary of analyses of variance (Type III Test of Fixed Effects) for redbays inoculated with R. lauricola (3.0 x 103 conidia), with data adjusted to the stem diameter covariate.

Type III Test of Fixed Effects

Source of variation

df Incubation (d) Disease Development Rate

AUDPC Final Severity %

stem 1 F = 3.15 P = 0.08 F = 1.63 P = 0.21 F = 10.69 P = 0.002* F = 7.34 P = 0.01*

clone 17 F= 1.49 P = 0.16 F = 2.73 P = 0.006* F = 9.61 P = 0.0001* F = 7.63 P = 0.0001*

residual error 35

Values F estimate and P value. * denotes significance at P = 0.05.

116

Table 5-7. Experiment 2. Contrast analysis for redbay inoculated with R. lauricola (3.0 x 103 conidia).

Contrasts Incubation (d) Disease Development Rate AUDPC Final Severity %

States

SC vs. FL + GA 4.69 (P = 0.51) 0.03 (P = 0.17) 0.81 (P = 0.87) -0.01 (P = 0.85)

FL vs. SC -3.47 (P = 0.61) -0.03 (P = 0.13) -0.97 (P = 0.84) 0.02 (P = 0.75)

GA vs. SC -13.89 (P = 0.55) -0.01 (P = 0.90) 0.46 (P = 0.98) -0.04 (P = 0.82)

GA vs. FL 10.42 (P = 0.65) -0.02 (P = 0.74) -1.43 (P = 0.93) 0.05 (P = 0.74)

Field sites

FG vs. HI -9.83 (P = 0.28) -0.03 (P = 0.24) 13.19 (P = 0.05)* 0.20 (P = 0.005)*

FG vs. EB 1.62 (P = 0.84) -0.03 (P = 0.21) -12.30 (P = 0.04)* -0.13 (P = 0.03)*

FG vs. SCI 10.42 (P = 0.65) -0.02 (P = 0.74) -1.43 (P = 0.93) 0.02 (P = 0.75)

SCI vs. HI 20.25 (P = 0.40) 0.01 (P = 0.89) -14.625 (P = 0.39) -0.14 (P = 0.41)

SCI vs. EB 8.8 (P = 0.71) 0.01 (P = 0.91) 10.87 (P = 0.52) 0.19 (P = 0.28)

HI vs. EB 11.45 (P = 0.27) -0.01 (P = 0.70) -25.50 (P = 0.001) -0.33 (P= 0.0001)*

Top 3 Clones vs. Others 38.11 (P = 0.0001)* -0.11 (P = 0.001)* - 59.60 (P = 0.0001)* -0.59 (P = 0.001)*

Classes of comparison: state of origination, field site location, and top 3 clones per disease parameters category. Values denote estimate and (P value). * denotes significance at P = 0.05. States: SC= South Carolina, FL= Florida, GA= Georgia. Field Sites: FG= Fort George Island FL, HI= Hunting Island State Park SC, EB = Edisto Beach State Park SC.

117

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BIOGRAPHICAL SKETCH

Marc Hughes was born in Orlando, Florida. Soon after Marc’s birth, his parents,

Ralph and Cristina Hughes moved him and his brother to Coral Springs, Florida. While

attending elementary, middle, and high school, Marc’s interests into the natural

environment took hold. Scuba diving, fishing, and hiking became favorite activities of

his during teenage years.

In 2000, Marc began his education at Florida Atlantic University in Boca Raton

Florida. His undergraduate studies focused on biology and the plant sciences, where

he also aided various faculty members with everglades related research. In 2005, Marc

graduated with a Bachelor of the Arts degree in biology, with a certificate of

environmental studies. Subsequent to his graduation, Marc began employment with Dr.

John Volin at Florida Atlantic University in Davie, Florida. During his employment with

Dr. Volin, Marc was a member of a team of field scientists who conducted various

studies in relation to the biology and health of the Florida everglades system. Important

research priorities included the biology and spread of old world climbing fern (Lygodium

microphyllum), monitoring the trends of tree island hydrology, and crayfish monitoring

within the everglades. After his time at FAU, Marc gained employment at EarthWorks

inc., a landscape design company located in Davie, Florida. At EarthWorks, Marc’s

interest in ornamental and native flora developed into a passion for the biology of plants

and their horticultural aspects. Later, Marc gained employment at the City of Coral

Springs as assistant to the city forester. Here, Marc developed his knowledge of

arboriculture and urban forestry, while aiding in a city-wide project to reforest the urban

tree canopy that was lost to hurricane Wilma in 2007.

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Later in 2007, Marc was accepted into the University of Florida, Department of

Plant Pathology, where he studied under his major advisor Dr. Jason Smith. Marc’s

research focused on laurel wilt and the development of a resistance screening

methodology in redbay (Persea borbonia). During his time at the University of Florida,

Marc has worked to understand and describe the biology of the laurel wilt system, the

pathogen’s population structure, and various other aspects of this forest disease. After

his PhD, Marc plans to continue his career in the field of forest pathology.

Documents

© 2012 Marc Anthony Hughes - University of Floridaufdcimages.uflib.ufl.edu/UF/E0/04/53/33/00001/HUGHES_M.pdf · 2013-08-15 · Marc Anthony Hughes May 2013 Chair: Jason A. Smith