Dispersal and population dynamics of Frankliniella thrips and progress of tomato spotted wilt virus in tomatoes

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Dispersal and population dynamics of Frankliniella thrips and progress of tomato spotted wilt virus in tomatoes
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Tomato wilts   ( lcsh )
Plant diseases -- Florida   ( lcsh )
Plant viruses   ( lcsh )
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Thesis (Ph. D.)--University of Florida, 1991.
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Includes bibliographical references (leaves 60-73).
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by Helena Puche Erlich.
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Typescript.
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Vita.

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DISPERSAL AND POPULATION DYNAMICS OF FRANKLINIELLA THRIPS
AND PROGRESS OF TOMATO SPOTTED WILT VIRUS IN TOMATOES








By
HELENA PUCHE ERLICH


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


1991













ACKNOWLEDGEMENTS


I wish to express my sincere gratitude to Dr. Joseph E.
Funderburk, Dr. Donald C. Herzog, Dr. J. Howard Frank, Dr. Richard D.
Berger, and Dr. Steve M. Olson for serving on the advisory committee
and for giving their time and experience to improve my professional
development in entomology and plant pathology. Their constructive
criticisms were invaluable in the course of this research and in the
preparation of this manuscript.
Special thanks go to Myrna Litchfield, Sheila Eldrige, Tracey
Austin, Jan Smith, Connie Rudd, Elizabeth Lewis, Andrew Brown,
Leslie Smith from the Department of Entomology and Nematology in
Gainesville and the North Florida Research and Education Center in
Quincy for their assistance during the development of this study.
Their patience and willingness to help and suggestions of ideas are
greatly appreciated.
Thanks are extended to Wayne Williams for all his help in
managing properly the meteorological field Station in Quincy,; to
David W. Hall for identification of the wild plant hosts, to Ann
Foster for suggestions in statistics, and to Dr. Larry Brown for
developing the ELISA tests.
Special thanks go to my husband, Alejandro, for his patience,
friendship, support, and love in times of hard work, and for his
comments on early drafts of this manuscript.











TABLE OF CONTENTS


ACKNOWLEDGEMENTS .............. .................. ii

LIST OF TABLES .............. ....................... v

LIST OF FIGURES .............................. ............. v i

ABSTRACT .............. .. ......................... vii

CHAPTERS

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

Virus Characteristics ..................... .. 2
Virus Infectivity .............................. 2
Thrips and the epidemiology and control of TSWV. 4

2 CAPTURES OF Frankliniella spp. (THYSANOPTERA:
THRIPIDAE) IN TOMATOES BASED ON WEATHER,
SURROUNDING VEGETATION, AND ORIENTATION OF
STICKY-CARDS .............................. 6

Introduction ............................... 6
Materials and Methods .................... .... 8
Results .................................... 11
Discussion ............ ................... 1 4

3 AN ANALYSIS OF DISPERSAL OF FRANKLINIELLA SPP.
(THYSANOPTERA:THRIPIDAE) IN GREENHOUSE
TOMATOES .............................. 21

Introduction .................. ............ 21
Materials and Methods ................... .... 23
Results ................................. 28
Discussion ............. .................. 31








4 POPULATION DYNAMICS OF THRIPS AND
PROGRESS OF TOMATO SPOTTED WILT
IN FIELD TOMATOES ........... ............. 40

Introduction ............................. .. 40
Materials and Methods .......................... 42
Results .................................... 46
Discussion ................................. 48

5 CONCLUSIONS ........................... 54

REFERENCES ............ ......................... 60

BIOGRAPHICAL SKETCH ................................. 74






























iv












LIST OF TABLES
Table Pag

2.1. Mean No. ( S. E. M.) of thrips captured per
trap per week on sticky cards located at the
north, south, east, west, and center of tomato
fields in 1989 and 1990. Gadsden County, FL.
............................................................................................. 1 9

2.2. Mean No. (. S.E.M) of thrips captured per trap
per week on sticky cards in tomato fields
according to surrounding vegetation habitat,
in 1989 and 1990, Gadsden County,
F la .................................................................................... 2 0

3.1. Characteristics of the dispersal and
movement of adults of Frankliniella spp.
marked with a fluorescent dye and released
on greenhouse tomatoes in 1989 and 1990.
Diffusion coefficient in one dimension (D);
diffusion coefficient between rows (Di),
diffusion coefficient within rows (D2), and
disappearance rate (p.) determinedby the
equation of Dempster (1957). ............................. 36

3.2. Kurtosis of the spatial distribution (Ku) at
four times of the day of adults of
Frankliniella spp. marked with fluorescent
dye and released in greenhouse tomatoes in
1989 and 1990. Heterogeneity of movement
indicated by a significant (P < 0.05 (*))
departure from the normal distribution with
respect to the distancefrom the point of
release according to a t-test.
............................................................................................. 3 7












LIST OF FIGURES


2.1. Weekly captures of thrips on sticky cards in
three tomato fields in 1989 and two tomato
fields in 1990, Gadsden County, FL. ................. 1 8

3.1. Diagrammatic representation of the four 3x3
lattice squares evaluated to determine the
coefficients of diffusion (D) in two
directions and the disappearance rate (pg) of
Frankliniella thrips, in greenhouse tomatoes.
............................................................................................. 3 8

3.2. Time variations of the variance of dispersal
of Frankliniella thrips; the total number of
individuals released ranged between 700 to
1300. Variability of the data was explained
by a logarithmic model: y -7729.4 + 0.0002
Log (x), R2 -
0.905........................................................... ................... 3 9

4.1. Mean weekly captures of thrips on sticky
cards, TSWV disease incidence averaged over
two tomato fields, and the corresponding
daily rainfall in 1989 (A) and 1990 (B),
Gadsden County, FL. Note that scales are
different between years.......................................... 53











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

DISPERSAL AND POPULATION DYNAMICS OF Frankliniella THRIPS AND
PROGRESS OF TOMATO SPOTTED WILT VIRUS IN TOMATOES

By

Helena Puche Erlich

August 1991

Chairman: D. C. Herzog
Cochairman: J. E. Funderburk
Major Department: Entomology and Nematology

Thrips of Frankliniella spp. can cause injury to tomato fruits,
and vector the tomato spotted wilt virus (TSWV). Population
dynamics of thrips and epidemics of TSWV were monitored in two
commercial tomato fields during 1989 and 1990. Time and direction
of movement of thrips were examined using blue and yellow sticky
traps at different orientations. More thrips were captured on blue
cards. Captures of thrips were not different on either card side,
indicating similar immigration and emigration. More thrips were
captured on traps at the center and east positions. Fewer thrips
were captured on traps along roads.
Population dynamics of thrips were fitted to the Weibull
model. Thrips rates of increase were similar in both years, and a
small population of thrips was already in the field when trapping








had begun. The Weibull function was fitted to the cumulative
numbers of thrips captured over time and this increase was
sigmoidal. An asymptote of 1850 and 4000 thrips was projected in
1989 and 1990 with the. Weibull function.
Disease incidence was less than 10% in both years, and
attributed to low transmission efficiency or low proportion of
viruliferous thrips in the field. Polynomial and linear models
described progress of TSWV in 1989 and 1990, with low epidemic
rates. Diseased plants were distributed at random, although 40% of
the rows had an aggregated distribution. Spread of TSWV originated
from populations of thrips both within and outside tomato fields.
Secondary infection occurred late in the season.
Movement rates of thrips between and within rows were
estimated in tomato plots in the greenhouse. Rate of thrips
recapture was 12%. Mean rates of movement between and within
rows were 0.501 and 0.403 cm2/h, respectively. Movement rate
within rows was greater at dawn and dusk, accounting for swarming
behavior of thrips. The kurtosis and variance of displacement of
thrips revealed an homogeneous and nonrandom thrips movement.
The speed and movement of Frankliniella thrips may help to
understand TSWV disease spatial transmission. Therefore,
monitoring TSWV and its thrips vectors may help to forecast an
impending epidemic and to provide an early alert of TSWV in
tomatoes.











CHAPTER 1


INTRODUCTION


Epidemics of tomato spotted wilt virus (TSWV) have been
observed since 1986 in major vegetable production areas in north
Florida including tomatoes, peanuts, and other crops (Kucharek
1986). Tomato spotted wilt virus also has been reported on many
plants including cultivated malvaceous plants (Halliwell 1988);
watermelon (Iwaki atal. 1984), papaya (Gonsalves & Trujillo 1986),
peppers (Zitter 1989), flowers and vegetables (Haliwell & Barnes
1987, Schuster & Price 1987, Wilson & Moran 1983), artichokes
(Gracia & Feldman 1978), peanuts (Costa metal. 1977, Culbreath Ital.
1990 a, Todd etal. 1990), and tobacco (Bertrand ftal. 1990,
Culbreath tall. 1990 b). Six species of thrips (Thysanoptera:
Thripidae) have been reported as vectors of the TSWV (Amin et al.
1981, Ghanekar lali. 1979, Rao t al. 1980, Sakimura 1969).
In tomatoes, diseased fruits show yellow concentric rings and
chlorotic spots that greatly diminish its value for the profitable
fresh market. Tomato is a very important vegetable crop in Florida
representing almost 42.7% of Florida's fresh market sales
(Pohronezky ital. 1986). The rapid increase of TSWV among tomato
and other crops is threatening the $603 million revenue that the
tomato crop generates in Florida.










Virus Characteristics
The tomato spotted wilt virus is a spherical ssRNA virus.
Particles fixed with glutaraldehyde have a corrected diameter of 85
nm, a sedimentation coefficient of 530 and an electrophoretic
mobility at pH 7 of -19.8 x 10-5 cm2 V-1 (Joubert atal. 1974). One
minor protein (of MW 220,000 d), and three major structural
proteins (of MW 84,000, 50,000, and 29,000 d) have been found as
part of the TSWV. These three major proteins are glycoproteins and
constitute about 98% of the total viral protein. One of the major
proteins and the minor protein are associated with subviral
particles (Mohamed i al. 1973).
Virus Infectivity
TSWV infection produces diffuse masses containing denser
striated spots of about 5 nm. These masses are intimately
surrounded by ribosomes and occur freely in the cytoplasm of plant
cells. The cisternae of the endoplasmic reticulum system also
present diffuse masses alone or in combination with characteristic
clusters of virus particles (le 1971). As a result, symptoms of the
disease are characterized by marginal wilting, yellowing, brown
spotting, and general stunting of the vegetative portions of the
infected plant (Cho taal. 1987 a, 1989, Paliwal 1974). The
incubation period of the virus in tomato plants under field
conditions has been reported between 8 to 10 days (Bald 1937).
TSWV is a persistent virus and may replicate in the salivary
glands of thrips. Later, the virus is transmitted during salivation at
the feeding site (Sakimura 1962). Thrips feed by piercing leaf cells








with the mandible and ingesting cell contents through the feeding
tube formed by the maxillary stylets. The resulting sucking rate has
been estimated as 8.5 x 10-5 ~l/min (Chisholm & Lewis 1984,
Hunter & Ullman 1989).
The transmission efficiency of TSWV is very low. Only 18% of
thrips could transmit TSWV to tomato plants when caged on tomato
plants (Allen & Broadbent 1986, Ullman ital. 1989). As a result, the
percentage of plants becoming infected can range from 20 to 30%.
Thrips can only acquire the TSWV during the larval stage. A
minimum of 15 min feeding time is required for the acquisition of
the virus from the plant (Lewis 1973). However, the efficient
transmission of the virus to healthy plant hosts requires longer
acquisition times (Paliwal 1976, Sakimura 1962). The incubation
period of the virus in the thrips is about 10 days. However, only
adults are responsible for the transmission and dispersion of the
virus, which is retained over the whole life of the thrips (Sakimura
1963, 1969). Differences between the midgut permeability of the
larval and adult stages may explain the inability of adult thrips to
acquire the virus (Day & Irzykiewicz 1954).
In north Florida, Frankliniella occidentalis (Pergande) and E.
fusca (Hinds) have been reported as efficient vectors of TSWV
(Funderburk fial. 1990). These thrips species also can produce fruit
damage as a result of oviposition (Jensen 1973, Salguero 1990,
Terry & De Gransi-Hoffman 1988). F. occidentalis infests a variety
of host plants, including crops, weeds, and ornamentals. In tomato
fields, several common species of weeds harbor F. occidentalis and
F. fusca (Broadbent el a. 1987, Cho rt al. 1986, Yudin et al. 1986,








1988). These weeds are usually abundant near field crops and are
likely to provide sources of thrips to infest crops to be inoculum
source for TSWV (Da Graga ital. 1985, Greenough & Black 1985,
Stewart flal. 1989).
The acquisition and transmission of TSWV by thrips is
influenced by environmental conditions, such as rainfall, and
temperature (Cho etal. 1987 c, Lublinkhof & Foster 1977, Paliwal
1976). In particular, high rates of viral infection in tomato fields
appear to be related to high temperatures 12 days earlier (Bald
1937).
Thrips and the Epidemiology and Control of TSWV
Presently, growers spray insecticides to control partially
thrips vectors and consequently to control the disease (Caner fial.
1984, Costa fltal. 1977, Culbreath etal. 1990 c, Fazio atal. 1980,
Fazio & Kudamatsu 1983), but no dependable control measures are
available. One of the reasons for this lack of information is that
little is known about the epidemiology of the TSWV in tomatoes and
the interactions of TSWV and Frankliniella thrips (Bald 1937). Some
epidemiological studies have been conducted in lettuce, peanuts, and
tobacco (Cho dtal. 1987 b, 1989, Culbreath etal. 1991).
Infection of tomatoes with TSWV in the field has been
attributed to thrips coming from outside sources (Bald 1937,
Culbreath & Csinos 1991). However, new thrips were not sampled in
either of these studies, hence the role of external sources of thrips
on virus infection was inferred.
The source of the inoculum affects the spatial distribution of
diseased plants in field plots. Depending on whether the inoculum








comes from distant outside sources or from inside the field, the
resultant spatial distribution of diseased plants will be random or
clustered, respectively (Madden ital. 1982). In tomatoes and
tobacco, the spatial distribution of diseased plants by TSWV
appeared in a random pattern. However, TSWV-diseased peanuts
appeared in clustered patterns in the field, which is indicative that
secondary infection occurred (Culbreath tlal. 1990 a).
Given the importance of the disease and the lack of reliable
control programs, further knowledge of migration and dispersal of
Frankliniella thrips as vectors is essential to understand the
epidemiology of TSWV, and to develop feasible recommendations for
control.
Therefore, the goals of this study were to
1. determine the times and directions of movement of adults of
Franklinialla spp. entering and leaving tomato fields and to evaluate
the effects of weather parameters on thrips captures in north
Florida;
2. describe the pattern of movement of Frankliniella thrips and to
estimate the speed of thrips movement in tomatoes;
3. examine the spatial and temporal pattern of local spread of TSWV
disease in relation to the ecology of thrips in tomatoes.











CHAPTER 2


CAPTURES OF Frankliniella spp. (THYSANOPTERA: THRIPIDAE) IN
TOMATOES BASED ON WEATHER, SURROUNDING VEGETATION, AND
ORIENTATION OF STICKY-CARDS

Introduction
Frankliniella occidentalis (Pergande) and E. fusca (Hinds) are
important pests of tomato and other crops. Feeding injury from both
species is economically damaging to numerous crops (e.g., Cho ital.
1989, Tappan 1986). Additionally, cosmetic damage referred to as
"halo spotting" results from oviposition by F. occidentalis into small
developing grapes (Jensen 1973), apples (Terry & DeGransi-Hoffman
1988), and tomatoes (Funderburk unpublished data). These species of
thrips are also vectors of the tomato spotted wilt virus (Sakimura
1962, 1963). Tomato spotted wilt virus has a wide host range and is
world wide in distribution, but the disease it causes has only
recently been found in the southern U. S. (Cho ei al. 1989). Epidemics
of the disease were first noted in Florida during 1989 on tomatoes
and other crops (Kucharek et al. 1986).
Sticky cards have been used to study the color preferences and
population dynamics of thrips in numerous crops (Beavers atal.
1971, Gillespie & Vernon 1990, Gaines 1934, Harding 1961,
Hightower & Martin 1956, Irwin & Yeargan 1980, Lewis 1959, 1973,
Moffit 1964, Shirck 1951, Yudin etal. 1987). Several species of
thrips were consistently attracted to white, blue, and yellow traps
and these traps apparently are suitable to monitor the population








dynamics of thrips. The height of the sticky-card traps affects the
number of captures of thrips. The greatest numbers of E.
occdentalis were captured at a trap height of 2.4 m (Gillespie &
Vernon 1990). The numbers of thrips captured were intermediate on
traps at heights of 1.8 and 3 m and least at 1.2 and 0.6 m.
Environmental factors are known to affect the activity of
thrips. Both temperature and rain influence the movement of Thrips
imaginis Bagnall into roses (Davisdson & Andrewartha 1948).
Activity of L tabaci Lindeman was reduced at temperatures less
than 10 C and in driving rains (Harding 1961, Shirk 1951). The
activity of Isoneuthrips australis Bagnall was greatest when
temperatures were between 10-15 C (Laughlin 1977).
Davidson and Andrewartha (1948) found that the numbers of I.
imaginis in rose flowers depended on the density of the total
population in the vicinity of the rose plantings and on the activity of
the adult thrips seeking out the flowers. The densities of thrips
were greatest in the flowers during the spring months when
environmental conditions favored the development and survival of
the thrips. Funderburk tal. (1990) also determined that seasonal
abundance of E. occidentalis, fusca and F. rilitci (Fitch) were
greater in tomato flowers during the spring. These species are
highly polyphagous (Palmer etal. 1989), and the numerous plant
species that grew in and around the tomato fields served as hosts
for the thrips (Funderburk, unpublished data).
Chemical control has proved effective to reduce the halo
spotting in tomatoes caused by western flower thrips, but attempts
to reduce the incidence of tomato spotted wilt by chemical control








of the vectors in the fields usually was ineffective (Funderburk at
al. 1990). Tomato spotted wilt virus has been managed most
effectively in Hawaii by the development of cultural management
strategies developed from knowledge of certain aspects of disease
epidemiology and vector biology (Cho altal. 1989). Additional
information is required to understand the seasonal dynamics of
populations of thrips in crop and noncrop habitats to develop
efficacious management strategies for thrips and tomato spotted
wilt virus in the southern U. S. Knowledge of migration and dispersal
of thrips in tomatoes and factors that affect their activity also are
needed. Consequently, we conducted studies to determine the times
and directions of movement of adult thrips of Frankliniella spp. that
entered and left tomato fields by using sticky traps. Another
objective was to evaluate the effects of weather parameters on the
number of thrips captured on the traps.


Materials and Methods


Studies were conducted in two fields of tomatoes
(LycoDersicum esculentum (L.) Merrill) during the springs of 1989
and 1990 and in one, 12 x 4 m field of tomatoes during the spring of
1989. Row orientation was east-west in each commercial field and
north-south in the small field. In each field, in-row spacing was 50
cm and between-row spacing was 180 cm. A 60-cm-wide band of
black polyethylene mulch was laid down the center of each row. Six-
week-old 'Sunny' tomato plants were transplanted in mid-March.
Typical production practices were used for fertility, irrigation, and








pest control. Wind direction, wind speed, rainfall, and temperature
were recorded at a nearby meteorological field station.
In each field, yellow and blue 12 x 25 cm plastic cards were
stapled side by side in contiguous rows to wooden stakes, 79 cm
from the ground surface to the bottom of the sticky card, at the
north, south, east, west, and center of the border of the fields. Both
blue and yellow cards were used to assure that at least one of the
colors might be highly attractive for Frankliniella spp. in tomatoes.
Each card was sprayed front and back with a clear insect trapping
adhesive (Insect trap coating; Tanglefoot, Grand Rapids, MI 49504),
by positioning the spray can at 15 cm from the card for 3 sec. These
colored plastic cards were submitted to Hale Color Consultants (3
Starlight Farm Drive/ Phoenix, MD.21131) for analysis using a
Gardner Labs SpectraGard spectrophotometer. Lightness values for
the blue and yellow cards were 46.7 and 78.5, respectively, where a
value 0 is ideal black and 100 is ideal white, in steps visually equal
in magnitude. The hue angles at a* and b* for the blue cards were -
14.4 and -36.0, respectively, and for the yellow cards were 5.5 and
74.5, respectively. The hue angle is the angular position of a color
when plotted on an a*, b* graph, with the color being defined as the
end-point of a vector plotted from the 0,0 point to the color locus. In
degrees, a* when positive indicates redness and when negative
indicates greenness; b* when positive indicates yellowness and
when negative, indicates blueness.
At weekly intervals, sticky cards were collected and new
cards established between 0600 and 1200 hr EDT. Collected cards
were covered with transparent plastic wrap and frozen until








processed. The number of thrips on both sides of the cards was
determined by using 6.5 magnification. Microscope slides were
prepared to identify adult thrips to species, by using CMC-10
(Masters Chemical Co., Inc., 520 Bonnie Lane, Elk Grove Village, IL
60007) as the clearing and preserving medium. After at least 24 hr,
adults were examined at 100 to 1000X magnification, using a key to
the genus Frankliniella (R. Beshear, unpublished data). To determine
the effect of border vegetation on the weekly abundance of the
numbers of thrips captured, the habitats for sticky-card traps
located within 6 m of the borders at the north, south, east, and west
of each field were categorized as weedy hedgerow, wooded, or dirt
road. Efforts also were made to identify the wild plants in weedy
hedgerow and wooded habitats that have served as hosts for the
Frankliniella spp. captured on the sticky cards. Ten flowers from
each of 38 flowering plants were collected weekly from the weedy-
hedgerow and wooded habitats around each field. All collected thrips
in the flowers were prepared and identified as described above. Each
wild plant was identified to species.
All captures of thrips on individual sticky-traps within a field
were averaged to obtain the numbers of adult thrips per field per
week. The effects of each year, field, trap side, trap orientation, and
color were evaluated by using factorial analysis of variance.
Treatment means were separated when the main treatment effect
was significant (PE < 0.05) by using a Scheffe (1959) multiple range
test. The effect of trap side was a test to evaluate patterns of
immigration or emigration. The effect of trap orientation was used
to determine possible directions of movement. A multivariate








analysis was used to evaluate the relationships between weather
parameters and number of thrips captured on the sticky cards (Gauch
1984). For this analysis, weekly mean temperature, mean wind
speed, mean precipitation were regressed on the respective weekly
mean number of thrips per trap. A separate regression analysis
including only significant (P < 0.05) variables then was conducted to
describe the relationship (Southwood 1978).
Results
Population Dynamics
Thrips were captured on all sample dates in 1989 and 1990
(Fig. 2.1). In each large field, the number of captured thrips
increased early in May and were great until early or mid-June, with
two peaks in captures occurring during this period of time. In
contrast, few thrips were captured in the small 12 x 4 m field in
1989 with little change in the number of thrips captured weekly.
Over 97% of the captured thrips were Frankliniella spp., but
deterioration of the insects due to weather and the sticky condition
of the collected thrips prevented accurate estimates of the
frequency of individual species. The numbers of captured E. fusca
were always low. Nearly all of the remaining thrips were E.
occidentalis and E. tritidi in 1989 and E. occidentalis, E. titici, and
E. bispinosa (Morgan) in 1990.

Effect of Side. Color. Orientation of Traps and Surrounding
Vegetation on Number of Thrips Captured
Many thrips were collected on both blue and yellow sticky
cards, but the number of thrips captured on blue cards was greater








than those caught on yellow cards in 1989 (C 93.6; df 1,12; E <
0.001) and 1990 (F 39.7; df = 1,6, E < 0.001). The average number of
thrips per week (mean SEM) captured on blue cards in 1989 and
1990 was 204 12 and 236 16, respectively, compared with the
captures on yellow cards of 120 6 and 121 10, respectively. The
mean number of thrips per card per week captured on the side of the
plastic cards facing outside toward field borders was not
significantly different from the mean number of thrips per card per
week captured on the side of the plastic card facing inside toward
the field in 1989 (E 1.1; df 1, 12; P > 0.05) or 1990 (F 0.1; df = 1,
6; E > 0.05)
The orientation of the trap significantly affected the mean
number of thrips captured per trap per week in 1989 (E = 2.3; df = 1,
12; P 0.05) and 1990 (E = 3.0; df = 1, 6; P < 0.05). Captures on the
traps positioned in the center and east locations were numerically
greater in both years, but not always significantly so than captures
on the north, south, and west sticky cards (Table 2.1). Captures were
similar both years on the center and east sticky cards. The number
of thrips captured on the north, south, and west sticky cards were
similar.
The plant species in the wooded border vegetation areas were
primarily oak (Quercus spp.) and pine (Pinus spp.). Frankliniella spp.
were collected primarily from plant species other than oak and pine
within this habitat. These hosts included crab apple (Malus
angustiflora (Ait.) Michx.), flowering dogwood (gCorus florida L.),
wild cherry (Prunus serotina Ehrh.), chickasaw plum (Prunus
angustifolia Marsh.), and tung-oil tree (Aleurites fordii Hemsl.).








Many plant species were found as hosts for Frankliniella spp. in
weedy-hedgerow border areas; these were wild radish (Raphanus
raphanistrum L.), Japanese honeysuckle (Lon jaa.nica Thunb.),
yellow jessamine (Gelsemium sempervirens (L.) Ait. f.), lady's wood-
sorrel (Oxalis cornculata L.), sand blackberry (Rubus cuneifolius
Pursh), sparkleberry (Vaccinium arboreum Marsh.), false dandelion
(Pyrrhopap us carolinianus (Walt.) DC), common vetch (Yicia sativa
L.), hedge privet (Ligustrum sinense Lour.), lantana (Lantana camera
L.), low hop clover (Trifolium campestre Schreber), and multiflora
rose (Rosa multiflora Thunb. ex Murr.).
Comparisons of mean numbers of thrips per trap per week by
the surrounding vegetation habitats were highly significant in 1989
(F 18.9; df = 3, 6; P < 0.0001) and 1990 (E = 4.7; df= 3, 3; P <
0.005). The numbers of thrips captured on traps located along
roadways were fewer than those captured on traps located by
wooded areas and tomatoes (Table 2.2). The numbers of thrips
captured in wooded areas, weedy-hedgerow areas, or tomatoes were
significantly different each year, but differences were inconsistent
between years.

Effect of Wind Speed. Rainfall. and Temperature on the Numbers of
Captured Thrips
The mean number of thrips captured per trap each week was
related to daily mean temperature, but the relationship was very
weak (y = -457.64 + 23.41x, R2 = 0.112). Mean temperatures
increased weekly until May or early June (ranged from 21.1 to 35.80
C), when mean temperatures remained relatively constant. The mean








number of thrips was not related to mean wind speed or mean
precipitation.




Discussion


Frankliniella spp. occurred in large numbers for a relatively
short period during the year and this period occurred earlier in the
southern U.S. than in the northern U.S. (Webb ital. 1970).
Frankliniella spp. were present in our geographical region between
late April and early June (Salguero-Navas etal. 1991), which
corresponded well with the greatest number of thrips captured on
the sticky cards in each large field sampled in each year in our study
(Fig. 2.1). The numbers of thrips captured in the small 12 x 4 m field
were very low, possibly because of the small size of the tomato
field and the lack of thrips captured on nearby weedy-hedgerow or
wooded habitats.
The color of the sticky card greatly influenced the number of
thrips captured in our study. The yellow cards were
spectrophotometrically near white. White has been reported as the
most attractive color for Frankliniella spp., although blue also was
noted as a highly attractive color (Beavers ial. 1971, Moffit 1964,
Yudin etal. 1987). Frankliniella spp. in our study seemed to
discriminate between hues and to prefer blue over yellow. This field
result is consistent with that found by Brodsgaard (1989) for E.
occidentalis in glasshouse experiments. Weed flowers with higher
reflectance in blue were reported to be visited frequently by other








insects in Canada (Mulligan & Kevan 1973). Researchers have
reported that Frankliniella spp. exhibited thigmotactic behavior and
searched for shaded, dark habitats, apparently to avoid desiccation
and predation (Laughlin 1977, Lewis 1973). It is possible that
Frankliniella spp. preferred the blue cards in our study, because they
were darker than the yellow cards.
The side of the trap toward or away from the field did not
affect the number of thrips captured in our study. We concluded that
multiple habitats were sources of the adult thrips and that these
thrips originated both from within and outside the tomato fields.
Immigration and emigration of thrips in tomato fields was about the
same. Little information has been published concerning patterns of
immigration and emigration of thrips in relation to crop fields. Shirk
(1951) reported that I. tabaci reproduced and overwintered directly
within crop fields. In our fields, Frankliniella spp. undoubtedly
developed on crop and weedy hosts present within the field, but it is
not known whether the thrips were from overwintering populations
or from populations of early spring generations.
The vegetation surrounding the traps greatly influenced the
number of thrips captured (Table 2. 2). Yudin t&al. (1986, 1988) and
Cho etal. (1986) reported F. occidentalis inhabited numerous wild
plant species in and around lettuce fields in Hawaii. Adults of E.
occidentalis, E. titici, E. bispinosa, and F. fusca were common on
numerous plant species located in weedy-hedgerows and wooded
areas in our study. These wild plant hosts undoubtedly served as a
source for some of the adults in tomato fields as thrips were
captured in greater densities on sticky cards adjacent to weedy-








hedgerows and wooded areas. Conversely, few suitable wild plant
hosts were located in or along roadways because of mowing and
frequent soil disturbance. This latter habitat was not a good source
for thrips to move into tomato fields, and few adult thrips were
captured on sticky cards adjacent to roadways.
Compass orientation of the sticky cards influenced captures of
thrips (Table 2.1). The observed differences of captured thrips in
different compass orientation of the cards could be related to the
wind direction which usually was from the east or southeast in both
years. If movement of thrips into fields was affected by wind
direction, then, the greatest numbers of captured thrips would be
expected at the east or south positions. The greatest numbers of
thrips captured were on the east sticky-cards in 1989 and 1990, but
the least for the south sticky cards. Thus, the relationship of wind
direction to the capture of thrips was inconclusive. Observed
differences between trapsat different orientations coincidentally
may be related in both years to the highly significant effect of
border vegetation habitats. Additional research to study this effect
is warranted. Trap orientation was not found to affect sticky-card
captures of E. occidentalis in onion fields in Texas (Harding 1961).
The number of thrips captured increased as temperatures
increased. This general result is consistent with previous studies in
which mass flight of Thysanoptera occurred when temperatures rose
above a threshold (Dintenfas etal. 1987, Lewis 1964, MacGill 1931).
Other weather parameters did not affect the numbers of
Frankliniella spp. captured on sticky cards.





17


The most likely hypothesis to explain our findings is that adult
Frankliniella spp. in tomatoes were mostly local populations
originating from numerous habitats. Some thrips apparently
developed on previous crop or weed hosts within the field and
emerged from the soil during the crop production season. Additional
thrips originated from nearby wild plant habitats, especially weedy
hedgerows and wooded areas. Future research is needed to determine
whether Frankliniella spp. have overwintering populations or early
spring generations. It is also important to know the sources of adult
viruliferous thrips and the host plants upon which they develop and
acquire tomato spotted wilt virus.









600
--0-- 5-ha FIELD 1 1989
500 -- 5-ha FIELD 2

400---- 12 x 4m FIELD

300-

I"
> 200

M 100-

o-
1990
I--
1000-

< 800-

600-

400-

200 -

0-
MARCH APRIL MAY JUNE




Figure 2.1. Weekly captures of thrips on sticky cards in three tomato
fields in 1989 and two tomato fields in 1990, Gadsden County,
FL, average of 10 cards (for 1989 and 1990).

















Table 2.1. Mean no. ( S.E.M) of thrips captured per trap per week on
sticky cards located at the north, south, east, west, and center of
tomato fields in 1989 and 1990, Gadsden County, FL.


Mean no. / trap /week ( S.E.M)


1989


1990


center 172.3 (16.7) a
east 167.2 (18.2) a
west 136.8 (13.4) ab
north 128.0 (17.9) ab
south 91.9 (11.7) b


215.6 (22.3)
189.1 (22.0)
118.3 (15.0)
185.9 (24.9)
184.5 (21.4)


Means in the same column followed by the same letter are
significantly different (P < 0.05) according to Scheffe (1959)
multiple range test (N = 44 for 1989, and N = 72 for 1990).















Table 2.2. Mean no. ( S.E.M) of thrips captured per trap per week on
sticky cards in tomato fields according to surrounding vegetation
habitat, in 1989 and 1990, Gadsden County, Florida.


Mean no./ trap /week ( S.E.M)
1989 1990


Weedy-hedgerow
Wooded
Tomatoes
Roadway


195.9
180.3
118.7
70.6


Means in the same column
significantly different (P <
multiple range test.


(13.5) a
(26.5) ab
(11.8) bc
(8.7) c


182.1 (12.8)
228.5 (43.3)
215.6 (22.3)
118.3 (15.0)


followed by the same letter are
0.05) according to Scheffe (1959)











CHAPTER 3


AN ANALYSIS OF DISPERSAL OF FRANKLINIELLA SPP.
(THYSANOPTERA:THRIPIDAE) IN GREENHOUSE TOMATOES


Introduction
Insect movement is an essential feature in the dynamics of
insect-vectored pathogens and the spread of disease in plant
communities (Power 1987). Tomato spotted wilt is a disease of
many crops that is transmitted by certain species of thrips
(Sakimura, 1962, 1963). The disease recently has been found in the
southern U. S. and has became a serious economic problem in
tomatoes (Funderburk a tal. 1990). Vector species that commonly
inhabit and reproduce in tomatoes include the western flower thrips
Frankliniella occidentalis (Pergande) and the tobacco thrips E. fusca
(Hinds). In addition, infestations of F. occidentalis on tomatoes
cause fruit injury that result in large losses in yield and quality.
Tomato plants infected with the tomato spotted wilt virus are
potential sources of the virus to populations of immature thrips.
After maturing to adults, these thrips can transmit the virus to
healthy plants. It is believed that secondary spread of the disease
can occur within a field (Culbreath etal. 1990a, Harding 1961,
Lewis 1973, Sakimura 1962). The patterns of movement of the adult
thrips obviously are important in the spread of the virus and the
pattern of spread of disease within the field.








Trivial movement or dispersal is one category of flight
activity associated with the search for food, oviposition site, or a
mate, or with the escape from potential enemies. Trivial movements
are restricted to the animal's habitat, and these movements can lead
to a limited increase in the mean distance between individuals and a
characteristic spatial distribution of the population (Chapman
1982).
The spatial distribution of an insect population is the result of
several factors including homogeneity of movement, variability of
that movement through time, and the speed of movement. If insects
are released in an experimental arena, the kurtosis of the spatial
distribution of the released insects can be used to determine
whether movement was heterogeneous or homogeneous and whether
the initial dispersal was due to population pressure associated with
crowding. The variability of insect displacement through time can be
estimated and used to determine whether the speed of insect
movement was constant during that trivial movement. Among the
descriptive characteristics of any dispersal pattern is the
determination of randomness of insect movement. If the data can be
fit to a passive diffusion model, then dispersal of that insect is
considered to be random. Otherwise, movement is nonrandom and
some kind of attractant or repellent may be responsible for the
spatial distribution of those insects in certain areas.
Harding (1961) reported migration of Frankliniella spp. in
cotton and tomato crops, respectively. We found no published
information however, concerning patterns of dispersal of
Frankliniella spp. Information on migration and dispersal of thrips is








essential to understand the temporal and spatial dynamics of spread
of tomato spotted wilt in crop fields, and this information will be
helpful to develop strategies to manage the problem.
Therefore, the objective of this study was to describe the
pattern of trivial movement of Frankliniella spp. Wild adults of
Frankliniella spp. (primarily E. occidentalis) were captured, marked
with a fluorescent dust, and released on tomatoes in a greenhouse.
The coefficient of diffusion (D) (or the speed of movement of the
thrips (cm2/h)), the disappearance rate (g.), and the kurtosis and
variance of their displacement were determined from the recapture
data. The hypothesis for these experiments was that Frankliniella
thrips move at random when released into an experimental arena,
therefore diffusion coefficients should be constant. A passive
diffusion model was used to determine whether the movement of
thrips was random.


Materials and Methods


Adults of Frankliniella spp. for this study were collected
during May in 1989 and 1990 from flowers of wild radish (Raphanus
raphanistrum L.), because this plant species was known to be
inhabited primarily by E. occidentalis. Other species of adults
present that could not be separated visibly from E. occidentalis were
E. tritici (Fitch) in 1989 and E. titici and E. bispinosa (Morgan) in
1990. The flowers containing thrips were brought to the laboratory
and the thrips were sedated by spraying CO02 into the container for 5
sec. The container was shaken gently to separate the thrips from the








flowers. Thrips then were collected by using a mouth aspirator, and
counted. These adults were placed into a 30 ml plastic vial with 0.4
mg of micronized fluorescent dust (DAY-GLO Daylight fluorescent
pigment, Fire orange A-14, Switzer Brothers, Inc., Cleveland, OH;
Lillie at al., 1985) and the vial was shaken gently four times. The
marking procedure was performed a few seconds before releasing
700 to 1300 marked thrips on the tomato plot in the greenhouse.
Micronized fluorescent dusts have been used previously to
study pollen dispersal by pollination vectors (Stockhouse 1976,
Waser & Price 1982), and to study mating patterns in Euphydras
editha Boisduval (Wheye & Ehrlich 1985). Tomato plants for this
experiment were grown in a greenhouse at about 27 C at the North
Florida Research and Education Center, Quincy, FL, from March to May
during 1989 and 1990. Six-week-old 'Sunny' tomato plants, were
transplanted into 3-liter plastic containers containing a peat-like
medium soil, in mid-March.
The marked thrips were released into the greenhouse with
tomato plants on 3 May 1989 and on 1 May, 2 May, and 16 May in
1990. On each date, a total of 32 tomato plants was arranged into
four rows. These plants were the only ones present in the greenhouse
at the time of the experiment. The distance between rows was 1 m,
and plants within rows were spaced 50 cm apart. The plants were
divided into 16 subplots of 2 plants within a subplot (Fig. 3.1) to
determine the coefficient of diffusion (D) in a single dimension and
in two dimensions (Di, the coefficient of diffusion between rows
and D2, the coefficient of diffusion within rows). Marked thrips were
released at 1600 h EDT in a corner of the experimental plot. These








thrips primarily are flower-inhabiting (Salguero-Navas 1990);
consequently, four flowers were selected randomly from each
subplot every 4 h, beginning 15 h after initial release at 0700 h and
ending at 1900 h EDT. The position of recaptured thrips was recorded
within the experimental plot. Flower samples were placed
immediately in vials and frozen for later examination. A microscope
slide was prepared of each collected thrips, with CMC-10 (Masters
Chemicals Co. Inc, 520 Bonnie Lane, Elk Grove Village, IL 60007)
used as the clearing and preserving medium. These prepared thrips
were examined immediately under 6.5 to 40x magnification for
presence of fluorescent dust.
The experiment also was conducted on four sample dates under
open field conditions but only 12 of 24,000 thrips marked and
released were recaptured. Therefore, data from the field were not
presented and not used to describe patterns of movement of
Frankliniella spp.
Four cohorts (10 thrips each) of marked and unmarked thrips
were enclosed in plastic cages for 3 days to verify the reliability of
the fluorescent-dye marking procedures. These thrips were prepared
as described previously and examined for the presence of
fluorescent dye. Longevity, mortality, and observed behavior of these
cohorts of thrips also were noted.
The method of Dempster (1957) was used to calculate D (the
coefficient of diffusion) in one dimension. This method is based on
random diffusion theory and assumes that insects are distributed
along a density gradient. Diffusion is the tendency for a group of
individuals initially concentrated near a point in space to spread out








in time, gradually occupying an even larger area around the initial
point (Okubo 1980). The model assumes that random movement will
tend to homogenize differences in insect densities between the two
areas. The number of individuals that move from one area to another
depends on the difference in insect densities and the rate of
movement of the insects. Overall changes in insect numbers are
determined by emigration, birth, or death. The model of Dempster
(1957) was modified to allow separate estimates of D in two
dimensions, such that


aN(x. y. t) = D1 (2i) + D2 (2fi N (1)
at ox2 ay2
where D1 is the coefficient of diffusion between rows, D2 is the
coefficient of diffusion within rows, and p is the disappearance
rate of insects (combined migration and death minus birth). The
terms (a2N/ax2) and (a2N/ay2) measure the change in the spatial

gradient of insect density at point (x, y). The net change in insect
numbers due to random movement is proportional to these last
terms, according to Fick's law of diffusion (Okubo 1980). The aN/at
term expresses the change in number of thrips in a period of time,
and N is equivalent to the initial number of thrips found in the
center square of a 3 x 3 lattice square (Fig. 1) described by
Dempster (1957). The rate of random movement (D1 or D2), is
defined as the number of insects moving between two equal areas
with a density gradient of one insect between them in unit time t.
This method yields the following estimate of the terms above, for a








central square surrounded by squares of equal area, arranged as a 3 x
3 lattice:
(2N/ax2) 1/3 (Nl 2N12 + N13 + N21 2N22 + N23 + N31 2N32
+ N33), and
(a2N/ay2) = 1/3 (N11 + N12 + N13 2[N21 + N22 + N23] + N31 + N32 +

N33).


In these terms, N22 denotes the number of insects (N) in the central
square (x, y) of the 3 x 3 lattice square (Fig. 3. 1). A series of
simultaneous equations was developed for the central square of each
3 x 3 lattice square in the 16-subplot plot. Using the densities of
thrips in each subplot, the equations were then solved by
mathematical procedures and the values DI, D2 and g, were obtained
(Southwood, 1978, Steel & Torrie 1960). These values were
calculated for the time intervals 0700-1100 h, 1100-1500 h, and
1500-1900 h. A paired t-test was used to compare for significant
differences (P < 0.05) between D1 and D2.
Mean diffusion times for D1 (tmdi) and D2 (tmd2) were
calculated according to the equation:
tm I Di ti / I Di
where Di was the diffusion coefficient (Di or D2) found at the ith
time interval ti (Warner 1981). The same equation was used to
calculate mean disappearance time (tmp). The mean diffusion
coefficients (Mdi or Md2), and mean disappearance rate (Mgi) were
calculated by substituting tmdl, tmd2, and tmu into second degree








polynomial regression models which were the models that explained
variability of D1, D2, and p. over time.
Heterogeneity of movement of thrips with respect to distance
traveled was determined as the kurtosis of their spatial distribution
in greenhouse tomato plots using the equation:
Ku = (N 7 dp4 np) / (, dp2 np)2
where N is the total number of recaptured thrips in all flowers, dp is
the distance of the recapture point from the point of release, and np
is the total number of thrips caught in flowers at recapture points
that are at the same distance from the point of release (Southwood
1978). A t-test was used to test departure from the normal
distribution of numbers of thrips with distance from the point of
release on a given day (P < 0.05, Southwood 1978).
The variance of displacement of thrips was calculated by
measuring the distance (d) from the release point to the point where
recaptured thrips were found and multiplying d by the number of
thrips found at that distance. Average distances traveled were
calculated for each sampling-time and for each date tested and
plotted against time to determine whether the speed of thrips
movement was constant. Regression models were used to fit the
variance of displacement of thrips over time.
A Kolmogorov-Smirnov goodness-of fit test (P. < 0.05) was
used to detect differences between distributions of recaptured
thrips and those predicted by the passive diffusion model by
substituting the appropriate mean diffusion coefficient into
Equation 1.










Results
Marked adults of Frankliniella spp. retained the fluorescent dye
on several body areas for about 3 d, including the bases of the
antennae and legs and the posterior end of the abdomen. Mortality of
the adult thrips was very low, with no obvious difference between
marked and unmarked thrips. For several minutes following the
marking procedure, marked thrips fluttered their wings and used
their legs to remove dye from accessible body areas. Otherwise,
there were no visual behavioral differences between marked and
unmarked thrips. Recapture of thrips from tomato flowers was 12 %
+ 7.38 (mean S.E.M, n=4 dates).
Dispersal characteristics of the adults of Frankliniella spp.
released on greenhouse tomatoes in our experiments at three time
intervals during the day are given in Table 3.1. Diffusion
coefficients were very low at all time intervals. Negative values of
D, Di, and D2 are the result of estimation errors (Southwood 1978).
Dispersal within rows (D2) was greater early in the morning (0900
h) and near dusk (1700 h) than at all other times of the day, possibly
due to the known swarming or aggregation behavior of thrips in the
morning and near dusk (Kirk 1985).
Dispersal between rows (Di) increased from 0900 h to 1300 h
(Table 3.1). Because diffusion coefficients were always low, there
were no significant differences between Di and D2 at any time
interval measured, although there were apparent differences in
dispersal behavior between and within rows. When dispersal in only








one dimension (D), was considered movement was greater at 1300 h
than at other times.
Diffusion of thrips was not a linear process, and D1 and D2
versus the time interval were described by second degree polynomial
regression models (Table 3.1). Mean diffusion times (tmd) for Di, D2
were tmdl 12.479 h, and tmd2 14.703 h, respectively. Mean
diffusion coefficients (Md) were 0.501 and 0.403 cm2/h for Mdi and
Md2, respectively. The estimates of dispersal between and within
rows were not significantly different.
Three days were insufficient for the released thrips to
reproduce; consequently, the disappearance rates (g) represent adult
mortality and migration from the tomato plot (Table 3.1). Values of
la increased from 0900 h to 1300 h. Temperatures over this time
period increased from about 17 C to 29 C in the greenhouse and the
increases in la may be related to the increase in temperatures. The
mean disappearance time (tmg) was 13.928 h and the mean
disappearance rate (Mg) was 0.951 cm2/h.
The kurtosis of the spatial distribution of the released
Frankliniella spp. departed from a normal distribution early in the
morning (Table 3. 2). Kurtosis was not significantly different from
the normal distribution at any of the other time intervals.
Consequently, the movement of thrips was heterogeneous early in
the day, but was homogeneous with respect to the distance they
traveled for the remainder of the day. The variance of displacement
of thrips over time increased rapidly at the beginning of the
dispersal process, slowed its rate of increase as time progressed
and approached a fixed value at the end of the experiment (Fig. 3. 2).








Non-significant differences were found between polynomial and
logarithmic models fitted to the data. Therefore, the simpler
logarithmic model was chosen (R2 = 0.905, Sokal & Rohlf 1981).
The hypothesis of passive diffusion was accepted in two cases
and rejected (at the P. < 0.05 level) in one case (Table 3.1). Therefor,
a simple diffusion model only was able to explain thrips movement
at dusk. Non-random movement of thrips occurred during the day.
Discussion
The fluorescent-dye marking technique used was suitable to
study the trivial movement of the Frankliniella spp. over a 24-hr
time interval. After 3 days, the fluorescent dust was lost from all
body parts. Consequently, other marking techniques would be needed
to study movement of thrips for more then 3 days. Rubidium,
strontium, and iodine 131 have been used to mark egg and adult
Heliothis virescens (F.) (Hayes & Reed 1989), to mark adult
Dendroctonus frontalis Zimmerman (Bridges etal. 1988), and to
study dispersal by insects (Gaudreau & Hardin 1974). Neutron
activation analysis has been used to study dispersal of pollen
(Schlising & Turpin 1971) and to mark BemJ.sa tabaci (Gennadius)
(Costa & Byrne 1988). These techniques should prove useful to study
insect movement over longer periods of time and longer distances.
Mark-recapture techniques have been used to determine the
diffusion coefficient of insects in other studies. The diffusion
coefficients in other studies were based on one or two recaptures
following initial release. Therefore, diffusivity was found to be
constant over time (Okubo 1980). In our experiments, the use of four
recapture times allowed for a more accurate determination of the








diffusivity of thrips than two recaptures after initial release used
in previous studies (Dobzhansky & Wright 1943, Kareiva 1986, Power
1987). The diffusivity of thrips was not constant over time in 'our
experiments. Polynomial equations best described the movement of
thrips and the change in variance of dispersal between successive
recaptures. Nonrandom movement of mobile pest species was
observed by Kareiva (1986). Changes in diffusivity noted for
Frankliniella spp. probably were because of changes in dispersal
related to time of day and possibly other factors.
The increase in dispersal of thrips within rows early in the
morning probably was caused by the disturbance of being marked and
handled and to the escape from the disturbance point immediately
after release (Aikman & Hewitt 1972, Banks tial. 1985, Clark 1962,
Power 1987). Initial dispersal also may have been the result of
interindividual pressure associated with crowding. Movement would
be expected to increase in the overcrowded conditions following
initial release. When thrips dispersed and the overcrowding
diminished, movement would be expected to decrease because of the
disappearance of thrips from the experimental arena. Higher values
of gi have been attributed to higher emigration rates rather than to
higher mortality rates (Bach 1984, Kareiva 1985 a, b, Risch 1981).
A similar decreasing rate of dispersal during the day was
observed previously in locusts (Clark 1962). Indeed, once the value
of D had ceased to increase, migration ceased and was entirely
trivial (Kareiva 1986)
Greater values of D2 in the early morning and late afternoon
also may be the result of swarming behavior of thrips. Kirk (1985)








reported aggregation and mating of Thrias maj.r Uzel and I.
fuscipennis Haliday in flowers, with rapid increases in numbers of
thrips per flower at dawn. Swarming or aggregation behavior has
been reported as a result of hibernation (Eisner & Kafutos 1962) or
mating (Butler 1964). The swarming activity is diurnal with peak
activity at dusk and dawn (Downes 1969, Haddow & Corbet 1961,
Syrjamaki 1964). Swarming of thrips early in the morning also may
explain the heterogeneous movement of thrips at this time; i.e., the
individuals were dispersing at different speeds.
Higher movement between rows of Frankliniella spp. at mid-
day suggests a pattern of colonization of new habitats from the
release point at this time. The movement of thrips is known to
increase as a function of increasing temperature (Davidson &
Andrewartha 1948, Harding 1961, Laughlin 1977). Our experiments
were conducted under similar environmental conditions. The marked
thrips were always released at dusk in a greenhouse and recaptured
during the following day. Therefore, a higher value of Di at mid-day
probably was related in part to increasing temperature, and small
declines of D later in the day probably was related to small declines
in temperature.
The decrease of D1 late in the day for Frankliniella spp. also is
explained by the kurtosis of the spatial distribution of thrips, and
the variance of thrips dispersal over time (Morisita 1971, Okubo &
Chiang 1974, Okubo atal. 1977, Shishegada & Teramoto 1978).
Except at dawn, the dispersal of thrips was homogeneous; i.e., all
individuals were dispersing at the same speed, but this speed was
not constant. Since the variance of thrips dispersal decreased over









time, a decrease in the dispersal coefficient Di was expected
(Dobzhansky & Wright 1943). Early in the day, dispersal between
rows was lower probably due to a higher movement within rows.
Pathogen transmission and disease incidence are influenced by
rates of movement and abundance of the vectors (Kareiva 1982). The
smaller the rate of movement, the greater the time the vector
spends on each plant and, therefore the greater is the pathogen
transmission rate (Power 1987). The transmission of tomato spotted
wilt virus would be greater when the flight of the thrips decreases
and the thrips are feeding on susceptible plants. In our tests such
times were greatest in the early morning and in the late afternoon.
Such information concerning movement patterns and flight activity
of thrips is of potential importance to management programs. With
more complete knowledge of movement, it may prove possible to
plan control measures to reduce pathogen transmission, and thereby
reduce incidence of tomato spotted wilt virus in crop fields.
Our studies contribute toward a better understanding of trivial
movement of Frankliniella spp. adults. We found that movement
under controlled greenhouse conditions was not explained by a
passive diffusion model. The variability of this nonrandom movement
over time was described. Such detailed analyses of vector movement
are essential to interpret disease incidence of tomato spotted wilt
virus in the field.
In general, little progress has been made toward understanding
how to manage pest dispersal to influence patterns of attack and to
reduce crop losses (Kareiva 1986). Conventional control tactics,
especially insecticidal control, are not reliably effective to manage





35


tomato spotted wilt virus, and alternative approaches to involve
manipulation of the cropping systems may be the most promising
tactic for effective management (Cho t al. 1987 b). To develop such
an approach to manage tomato spotted wilt virus, it is important to
know the sources of adult thrips, the host plants upon which they
develop and acquire the virus, and the distance and speed of
movement of the vectors.


















Table 3. 1: Characteristics of the dispersal movement of adults of
Frankliniella spp. marked with a fluorescent dye, released on
greenhouse tomatoes and recaptured in tomato flowers in 1989 and
1990. Diffusion coefficient in one dimension (D); diffusion
coefficient between rows (Dl), diffusion coefficient within rows
(D2), and disappearance rate ()i) determined by the equation of
Dempster (1957).

Time interval Mid point D D1 D2 p.
(h) time (h) (cm2/h) (cm2/h) (cm2/h) (h-1)

0700-1100 0900 -0.283 0.067 0.278 0.352 *
1100-1500 1300 0.267 0.482 0.292 0.873 *
1500-1900 1700 -0.332 -0.004 0.793 0.876

* : indicates a significant departure from the null hypothesis of
passive diffusion (P < 0.05; Kolmogorov-Smirnov goodness of fit
test). The variation on the diffusion coefficients with time was
explained by second degree polynomials:
for D1, y = -4.161 + 0.723x 0.028x2 ; for D2, y = 2.027 0.331x +
0.015x2. For both polynomials R2 0.999.

















Table 3. 2: Kurtosis of the spatial distribution (Ku) at three times of
the day of adults of Frankliniella spp. marked with fluorescent dye
and released in greenhouse tomatoes in 1989 and 1990.
Heterogeneity of movement indicated by a significant (E < 0.05 (*))
departure from the normal distribution with respect to the distance
from the point of release according to a t-test.

Time interval Mid point Ku P
(h) time (h)

0700-1100 0900 1.959 0.0224 *
1100-1500 1300 3.577 0.5546
1500-1900 1700 6.242 0.6091
















*.N2]- :N22' "N23. i .: ...B:.--.
.. .. :: 3 :::i:i i: : i :i:i. .:.:.. .
4 .. ;-. :, ,

A l2:: : N2: NH31':::: : :::.::.:




::: :: :::: W :: ::: N 33::: : ::;:: ;::: :::::::::: :::: :::: ;
.- .,- .. .. .-, ., .. .; ..





: : :: ;: : : :::: :: : :: : :: : : ; : : : ::: : : :: : :: :: : : : :: : ::
,.,-,., ; ,. ..*..



-. ., ., .. .
D.. '. .







Figure 3. 1: Diagrammatic representation of the four 3x3 lattice
squares evaluated to determine the coefficients of diffusion
(D) in two directions and the disappearance rate (ji) of
Franklinie~la thrips in greenhouse tomatoes (*: release point).



















14000 -


12000 -


W 10000-
z

5 8000


6000
5 10 15 20
TIME (h)


Fig 3. 2: Change in the variance of dispersal of Frankliniella spp.; the
total number of individuals released ranged between 700 to
1300. Variability of the data was explained by a logarithmic
model: y = -7729.4 + 0.0002*LOG(x), R2 = 0.905.











CHAPTER 4


POPULATION DYNAMICS OF THRIPS AND PROGRESS OF TOMATO
SPOTTED WILT IN FIELD TOMATOES
Introduction
Tomato spotted wilt (TSWV) was first observed in North
Florida in 1986 (Sprenkel 1987). The disease has become
economically important since it causes serious problems in tomato
and other crops worldwide (Best 1968; Cho tat. 1989). In addition,
epidemics of spotted wilt in North Florida are spreading among
peanut cultivars (Sprenkel 1989). The incidence of the disease in
tomato crops was less than 2%. However, in Georgia, an average
incidence of more than 20% of spotted wilt was found in tobacco
representing a potentially new disease problem in southeastern U.S.
(Culbreath al al. 1991). The symptoms of the disease include brown
ring-spotting of leaves and fruits, yellowing, and general wilting
(Cho et a. 1987 a). More than 200 species of plants are known to be
hosts of the TSWV (Cho 1tal. 1986, Yudin &tal. 1986). In north
Florida, the virus is transmitted exclusively by two species of
thrips, Frankliniella occidentalis (Pergande) and E. fusca (Hinds)
(Thysanoptera: Thripidae).
The location of the source of vectors affects the distribution
of diseased plants in the field. Insect vectors coming from distant
outside sources can produce a random distribution of diseased plants
while in-field population of viruliferous vectors can produce a
disease incidence in a clumped pattern. Vectors coming from weed








hosts at margins of the fields would lead to a gradient from the
field edge into the field. The spatial pattern of spread of TSWV has
been studied on peanut, tobacco, and tomatoes. The distribution of
diseased plants appeared to be clumped or at random depending on
the host plant studied (Bald 1937, Culbreath etal. 1990 a, b). The
random distribution of diseased plants was attributed to
viruliferous thrips coming from distant outside sources, even though
no counts of the thrips were made in those studies. Secondary
infection did not seem to occur in tomatoes (Bald 1937). However, in
tobacco, inoculum from inside the field was responsible for
secondary infections and the resulting clumped distribution of
diseased plants (Tsakiridis 1980).
In these studies, the spatial distribution of diseased plants
was estimated by runs analysis. A run is defined as a succession of
one or more diseased or healthy plants within a row. The
distribution of diseased plants can be used to determine if the
pathogen was moving from plant to plant or from distant or nearby
outside sources (Campbell & Madden 1990, Madden tala. 1982).
The disease progress of TSWV on tomatoes has been assumed
to be monocyclic since its spread does not increase within the crop
during the course of a single growing season (Tresh 1974,
Vanderplank 1982, Zadoks & Schein 1979). However, some secondary
infection of TSWV occurs in other crops and the lack of information
on the dynamics of thrips as vectors in the field suggests that the
progress of the disease may not be exclusively monocyclic.
In this study, temporal and spatial patterns of local spread of
TSWV among tomato plants were examined. Information on the








dispersion of TSWV incidence was obtained in relation to in-field
movement and population trends of thrips in commercial tomato
fields. If virus spread resulted from movements of viruliferous
thrips between adjoining plants along rows, maps of the resulting
diseased plants should show a clumping pattern instead of a pattern
of random spread.


Materials and Methods
Studies were conducted in two commercial fields of tomatoes,
during the springs of 1989 and 1990, in Gadsden County, FL. The
rows were oriented east-west in both fields, in-row spacing was 50
cm, and between-row spacing was 180 cm. Six-week-old tomato
plants, cv 'Sunny', were transplanted into the fields in mid-March.
The plant population in 1989 and 1990 was about 67,454 in field 1
and 45,860 in field 2. A 60-cm-wide band of black polyethylene
mulch was laid down the center of each row. Typical production
practices were used for fertility, irrigation, and pest control.
Movement of adult thrips of the genus Frankliniella was
monitored in each field with yellow and blue 12 x 25 cm plastic
sticky cards set at the same place in contiguous rows. The cards
were stapled to wooden stakes, 79 cm from the ground surface to
the lower border of the sticky card, and the cards were placed at the
north, south, east, west, and center of the fields (ten cards / week /
field). Both blue and yellow cards were used to assure that at least
one of the two colors was highly attractive for Frankliniella spp. in
tomatoes. Each card was sprayed front and back with a clear insect








trapping adhesive (Insect trap coating; Tanglefoot, Grand Rapids,
Mich USA 49504).
Sticky cards were collected at weekly intervals, and new
cards were established between 0600 and 1200 hr EST. Collected
cards were covered with transparent plastic wrap and frozen until
processed. The number of thrips on both sides of the cards was
determined by using 6.5x magnification.
The numbers of thrips captured in both years were represented
as the proportion of cumulative numbers of thrips found per field
over time. This procedure has been used to analyze the number of
fungal spores (inocula) trapped over time (e.g., Politowski &
Browning 1978). The curves of thrips captured over time were fit to
the Weibull model which was chosen because of its flexibility to fit
various curve shapes. The Weibull model can be expressed as
y 1 exp { [ (t a) k] c}) in which y. -proportion of thrips in the
range 0 < y < 1, k = growth rate of the thrips, I = time, a = a location
parameter, and a a shape parameter (Jowett ei al. 1974, Stauffer
1979). The location parameter a, represents the earliest occurrence
of y. (with units of time) or the time of onset of the population
(Campbell & Madden 1990, Weibull 1951). The shape parameter
controls the shape of the rate curve and the inflection point. The
time at which 50% of the population of total thrips was captured
after trapping begun was interpolated from the fitted curves to the
Weibull function.
Records on incidence of TSWV were determined from 30 April
to 30 June in both 1989 and 1990 in both fields. Naturally occurring








sources of infection were responsible for initiation of the
epidemics.
In 1989, a stratified systematic sampling was used to assess
diseased tomato plants at weekly intervals. Disease incidence was
estimated on 11 plants spaced 11 steps from each other within a
row, in three rows of tomatoes randomly chosen in each of the two
fields. In 1990, TSWV-diseased plants were determined in each field
by direct counts at biweekly intervals. The exact locations by row
and plant, of diseased and nondiseased tomato plants were
determined within one subplot of 300 plants in each field studied. In
field 1, the subplot was 6 rows wide and 29 m long; in field 2, the
subplot was 4 rows wide and 44 m long. When a tomato plant was
found with symptoms, it was marked with a flag. Confirmatory tests
of the presence of the virus were made with ELISA by using
symptomatic leaves from randomly selected diseased plants, but not
all plants with symptoms were tested.
Data on the 1989 experiment were analyzed by dividing the
cumulative number of diseased plants by the total number of plants
during the weeks of sampling. In 1990, the proportion of diseased
plants per week was found by averaging the number of diseased
plants per 300 plants assessed in each field. Disease progress
curves were fit to linear models or to third degree polynomials. In
this later case, a separate fit of the data to linear models was done
to determine the disease rate in the increasing part of the curve and
in the decreasing part. The slope of the linear disease progress
model represented the disease rate.








The spatial aspects of the incidence of TSWV-affected tomato
plants was analyzed by runs analysis (Madden It al. 1982). Random
spread vs nonrandom plant-to-plant spread of disease (by in-field
vectors) was determined from field maps of diseased plants using
the formula E(U) [1 + 2m (N m)]/N, where E(U) is the total number
of runs expected under the null hypothesis of randomness, Ni is the
total number of plants in a row, and m. is the total number of
diseased plants. A Z test was performed to detect clustering
(Campbell & Madden 1990). The same analysis was performed
separately for each row to detect clustering of diseased plants per
row of tomatoes assessed in each of the two fields surveyed in
1990. Runs analysis also was performed for the whole field over
time to determine whether contiguous diseased plants were
detected progressively over time due to secondary infection or were
detected at the same time due to primary infection.
A polynomial model of the weekly observed proportion of
diseased plants (y) over time (t) was used to obtain the daily
cumulative proportion of diseased plants over time. To determine
the relationship between disease incidence and thrips captured in
the tomato field, a correlation analysis was performed between the
cumulative proportion of thrips (N cum.) captured on the sticky cards
and the respective proportion of cumulative diseased plants (y) one
week later. Correlation analysis also was performed between the
cumulative number of thrips captured and daily rainfall (Gauch
1984).








Results
Temporal Analysis of Populations of Frankliniella Thrips and the
Increase of TSWV-Diseased Plants in Tomato Fields in Relation to
Weather.
Thrips were captured on all sample dates in 1989 and 1990
(Fig 4.1 A, B). In both years, and in each of the two fields, the
numbers of captured thrips increased early in May and remained high
until early or mid-June.
The shape parameter of the Weibull model for the 1989 curve
was a_= 2.19. Such an a value occurs when the Weibull function is fit
to curves of the Gompertz type (i.e., asymmetrically sigmoidal
curves). In 1990 the shape parameter was c = 3.49 which is close to
the value 3.65, which is characteristic of symmetrically sigmoidal
curves of the logistic type. The position parameter a was -0.411 in
1989, and considerable greater in 1990 (a = -6.76).
The rate parameter k for the increase of the population of
captured thrips over time was very similar and slow for both years;
k= 0.019 in 1989 and k 0.017 in 1990.
The time at which 50% of the population of total thrips
captured after the trapping had begun was similar for both years.
The estimated values were tso 45 in 1989 and t50 47 in 1990.
The greatest difference between the two years was in the estimated
maximum numbers of captured thrips, which were 1850 for 1989 and
4000 for 1990.
Initial symptoms of TSWV started as concentric necrotic rings
and leaf spots about 40 days after tomato seedlings were
transplanted into the field. TSWV infection was confirmed by ELISA








in all symptomatic leaves from those tomato plants collected at
random.
The greatest incidence of disease in both years was during the
periods from mid-May to mid-June although this incidence was less
than 10% (Fig. 4.1A,B). As the season progressed, no more new
TSWV-diseased plants were found.
The disease progress curve for the TSWV in tomatoes was
explained by a third degree polynomial model in 1989 [y 0.75500 -
(0.02147)x + (0.00019)x2- (5.054 10-7)x3; R2 0.75]. The rate at
which disease increased during mid-April to mid-May in 1989 was
0.02 per day. Then, the rate was negligible and slightly negative
until the end of the season. In 1990, the increase of TSWV disease
over time was explained by a linear model [y -0.208 + (0.00186)x;
R2 0.97]. The rate of increase of TSWV was r = 0.002 / unit / day.
In both years, the fluctuation of the cumulative diseased
plants followed the fluctuations in thrips captured one week later
(Fig 4.1A). The correlation coefficients were 0.93 for 1989 and 0.99
for 1990.
The volume of rain on a given day always was below 4 cm / day
in both years but twice as much in 1990 than in 1989 (Fig 1A, B).
During late-April and mid-May of both years, rainy days were
followed by periods of relatively low rainfall in which increased
numbers of thrips were captured. Correlation coefficients between
rainfall and the number of thrips captured one week later were not
significant for 1989 or 1990.








Spatial Analysis of Spread of Spotted Wilt
Overall, the spread of TSWV in tomato fields in 1990 was
considered to be random (Z = 2.6; df = 1, P < 0.05) based on the runs
analysis. However, 40% of the rows had clusters of diseased tomato
plants as detected by the Z test based on runs analysis. The
appearance of diseased plants contiguous to each other progressed
over time and was detected between late May to early June.


Discussion
The population of thrips and the incidence of TSWV were
variable over the two years of this study. The thrips were found
during the second week of the tomato growing season in 1990.
Therefore, they were available for potential spread of the TSWV.
Indeed, we found a strong correlation between abundance of
Frankliniella spp. and TSWV incidence one week later, which could
imply that the thrips were responsible for the transmission and
spread of the TSWV disease in tomatoes.
The curves of cumulative numbers of thrips over time,
described by the Weibull function, differed between years. In 1989, a
position parameter near zero suggested that the trapping had begun
when the population of thrips was beginning to enter in the field or
that trapping had begun when a low population of immigrant thrips
was beginning reproductive cycles in the field. A more negative
position parameter in 1990 indicated that immigrant thrips had
already arrived or that in-field populations of thrips were already
reproducing in the field when the trapping had begun.








The slow rates of increase (k) of the population of thrips in
both years may have been due to environmental pressures that
inhibited population growth to its maximum potential. Under
controlled conditions, cohorts of F. fusca increased at higher rates
than in our studies (Puche & Funderburk 1991). Negative forces
apparently affected the growth of populations of thrips in the field.
The identification of such forces would allow control and
management of thrips and TSWV.
The resultant shape parameter c, for the cumulative numbers of
captured thrips was fit to sigmoidal curves (Weibull 1951). Based on
these analyses, the population of thrips might have been reproducing
in the field or in the immediate vicinity. In plant epidemics, when
the number of trapped airborne spores (inocula) from a known source
of diseased plants over time is sigmoidal, the resulting progress of
disease is also sigmoidal. However, in our studies the disease
progress was not sigmoidal even though the number of arriving
thrips (potential vectors) over time was increasing sigmoidally.
This result, in addition to the slow epidemic rates found both years
could imply that from the total numbers of thrips that were
reproducing in the locality, only a few were viruliferous and that the
transmission efficiency of TSWV by the thrips was very low. Since
hundreds of thrips repeatedly visit tomato flowers during the bloom
period (Salguero-Navas tlal. 1991), and only an average of 2% of the
plants become infected in each field each season, the rate of
transmission of TSWV must indeed be very low. Evidence of low
rates of transmission of TSWV by thrips has been reported (Paliwal
1974). Lower rates of disease transmission may occur if thrips are








spending more time traveling and are not remaining on plants long
enough to transmit the virus. This is the case in aphids, where
higher movement rates lead to lower disease incidence of barley
yellow dwarf virus (BYDV) on oats (Power 1991). The transmission
efficiency of the virus also can be affected by the virus titer and the
age of the leaves where the virus was located (Gray ital. 1991,
Power Ital. 1991).
Characterization of the progress of TSWV with time was
impossible because the incidence of the disease in both years did not
reach severe levels. Tresh (1983) reported that TSWV was a simple
interest type disease. Even though the population of thrips was not
sampled in that study, the distribution of diseased plants was
attributed to the influx of viruliferous thrips from outside sources.
Bald (1937) also found congregation of diseased plants in small
patches in tomato fields. However, this result was overlooked in his
conclusions.
In our studies, the overall random distribution of diseased
plants found in the tomato fields and clustering of diseased plants
over time and in some rows may imply that TSWV spread by
Frankliniella thrips was the result of thrips moving both from
sources outside and within the field. Consequently, a slight
secondary spread of the virus may have occurred late in the season
as a result of thrips moving between contiguous plants. The
sampling was insufficient to determine if gradients away from field
edges existed.
The inefficient transmission of TSWV by Frankliniella spp. or a
low level of viruliferous thrips in the field may be the possible





51


factors that contributed to the low incidence of the virus in
tomatoes.
The curve of the cumulative numbers of thrips captured over
time can be used to predict future abundance of thrips in tomato
fields. Therefore, good knowledge of the numbers of thrips present
early in the season is required to make these predictions.
Estimations of future abundance of thrips should allow advanced
forecasts of TSWV incidence and a better understanding of the
epidemiology of TSWV in tomatoes.



















FIGURE 4. 1: Mean weekly captures of thrips on ten sticky cards, TSWV disease incidence averaged
over two tomato fields, and the corresponding daily rainfall in 1989 (A) and 1990 (B), Gadsden
County, FL. Note that scales are different between years. (--'-- Proportion diseased plants;
-- Thrips/trap/week)











06 1990


< 04












I-
a 02 A
-2 \










S002- 00
2 00-

















SAPRIL MAY JUNE JULY APRI20L AY JUNE
E-











APR IL MAY JUNE JULY APRIL MAY JUNE












CHAPTER 5


CONCLUSIONS


Tomato is an economically important vegetable crop grown in
Florida. The total value of this crop has increased up to $603 million
in 1989. However, the spotted wilt disease is threatening the high
revenues from fresh market tomatoes. The causal agent of this
disease is the tomato spotted wilt virus (TSWV), which has been
reported to infect over 200 plant species. Many herbaceous weeds
are also susceptible to TSWV and may serve as sources of inoculum
for cultivated plants.
The TSWV is transmitted by thrips (Thysanoptera). In Florida,
Frankliniella occidentalis and F. fusca are the two main species of
thrips involved in TSWV transmission. One of these species, E.
occidentalis was considered restricted to the western parts of north
America but in 1986 this species was reported in Georgia and north
Florida causing crop losses in field peanuts and tomatoes. Recently,
the thrips also was found in southern Florida.
The development of an epidemic is governed basically by the
movement and abundance of the vectors in relation to sources of
infection. Therefore, information concerning movement patterns and
flight activity of thrips were needed to develop management
strategies to control TSWV.








These studies were conducted with these objectives: 1. to
determine times and directions of movement of Frankliniella spp.
thrips adults entering and leaving tomato fields and to evaluate the
effects of weather parameters on thrips captured in north Florida. 2.
to describe the pattern of movement of Frankliniella thrips and to
estimate the speed of movement ofthrips in tomatoes, and 3. to
examine the spatial and temporal pattern of local spread of TSWV
disease in relation to the ecology of thrips vectors in tomatoes.
The results of these studies provided new insights on some
ecological relationships between Frankliniella thrips, the TSWV, and
the tomato fields. The seasonal distribution of thrips in the spring
season for tomato was between late April and early June.
Immigration and emigration of adult thrips in tomato fields was
found to be the same during the two years of these studies. More
thrips were captured on blue sticky traps which proved to be a good
method to monitor thrips for management purposes. Furthermore, the
tomato fields were already infested by immigrant Frankliniella spp.
adults by early spring. These thrips probably were coming from local
populations originating from multiple habitats such as weeds and
wooded areas both within and outside tomato fields. The mild
winters in Florida probably allowed weed hosts to grow prolifically
and maintain thrips populations. Therefore, these insects may be
found at any time of the year in the area. Those alternative hosts for
the thrips might harbor the TSWV as well. If this assumption is
correct, Frankliniella thrips and TSWV have developed the required
mobility and ability for rapidly invading the relatively short-lived
hosts and ephemeral habitats provided by the tomato plant and the








vegetation at field edges. This would also explain the natural
sources and overseasoning of Frankliniella populations and virus
inoculum.
Oviposition of migrant thrips must have occurred on alternate
host plants at least ten days before tomatoes were planted as
populations of thrips were captured at approximately the second
week after planting. This period of time was enough for the infected
immature thrips to become adults. The migrant thrips appeared
responsible for the spread of the TSWV within the crop, as virus
incidence increased soon after thrips were captured. Spread of TSWV
progressed to give an almost linear increase in disease incidence,
with only minor fluctuations probably associated with weather
conditions that influenced development, dispersal, and feeding
habits of thrips. However, transmission of TSWV by thrips must be
very low since spread of the virus was limited, and only a few
plants became diseased.
Diseased plants were distributed at random and it seemed that
there was little opportunity for secondary spread to occur. However,
the new generation of adult viruliferous thrips that resulted from
populations of thrips present early in the season, must have emerged
by the time the tomato crop was mature, passed freely to and from
tomato plants, and secondary spread of the virus occurred within the
crop.
It is generally found with virus diseases that diseased plants
are aggregated near the source of infection, i.e., there is a gradient
from the focus of infection. The steepness of the gradient depends
on the association of virus with vector, virus with host, and abiotic








environmental factors, such as weather, influencing the three
elements- vector, virus, and host plant. Persistent viruses, such as
TSWV, are retained in its insect vector for long periods and thus
have a greater chance of spread over long distances. As a result, a
shallow gradient of the virus is formed. In the system thrips-
TSWV- tomato plant, gradients must occur along field edges and the
tomato fields. No assessment of the disease was performed on these
plants to determine if gradients away from field edges existed. This
assumption may explain the overall random pattern of disease
incidence in tomato fields. Furthermore, dispersal of the new
generation of thrips vectors perhaps was restricted by weather
conditions or by mating and reproduction. Therefore, thrips only
dispersed by short flights within the crop, and secondary spread
likely occurred within some rows late in the season.
The analysis of dispersal of Frankliniella thrips provided
important information to understand the way TSWV is spatially
transmitted. The speed of movement was calculated using partial
differential equations generated from the displacement of thrips in
space and represented by coefficients of diffusion of thrips
movement. Movement of thrips was not at random. Greater movement
between rows was found at mid-day and seemed to increase when
temperatures increased. Movement within rows was higher at dawn
and dusk and was attributed to the swarming behavior of thrips.
Consequently, field monitoring of populations of thrips early in the
season and by using sticky traps is necessary to forecast and give an
early alert of the possible spread of the TSWV. Incidence of TSWV in
tomato plantings, evidently is conditioned by a number of








interrelated factors. The higher the population of Frankliniella
thrips, the higher the potential incidence of the virus. However, for
the disease to reach economic losses, the factors governing
dispersal of thrips must be operating positively and the tomato
plants must be susceptible at the same time. The movement of
thrips at low rates also can explain the scattering and low incidence
of diseased plants in the tomato fields. The production of new
generations of thrips by the end of the season and the existence of
movement within rows may explain the pattern of aggregated
diseased plants in some rows.
The results of these studies provided information on the
relationship between the pattern of thrips movement and disease
incidence of the TSWV. The factors that influenced the timing and
abundance of spring thrips migrants have not been identified.
Weather conditions, principally temperature seemed to play an
important role on triggering this movement and the spread of the
TSWV.
Chemical control is one of several measures that should be
used to prevent virus spread. However, reduction of TSWV incidence
in the fields has proved to be ineffective by this method. The
removal of sources, and the inspection of crops are practices also
valid.
The most effective way to control TSWV would be to adopt
cultural practices that will lead to a reduction in disease incidence,
and to grow cultivars that can tolerate the disease. However,
attempts to locate sources of high resistance have been
unsuccessful, and cultural practices such as adjustment of planting






59


dates have to be worked out for each region and crop because the
multiplication and migration of the vector are dependent on climatic
factors. Induction of thrips flights by mechanical methods could be
useful to reduce disease incidence since it has been found that the
more the vector moves, the lower the probability of transmitting the
virus to the host plant.
The efficiency of transmission by different thrips species,
susceptibility of plants to infection, and differences in infectivity
and behavior of virus strains are some aspects of virus infection
which usefully could be explored to expand our knowledge of TSWV
epidemiology and hence improve control of virus spread.












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BIOGRAPHICAL SKETCH


Helena Puche Erlich was born in Caracas, Venezuela in 1959.
She received a high school degree in science in 1976. Upon
graduation, she attended the Universidad Sim6n Bolivar and received
the Licence in Biology in 1982. Her thesis work was focused on the
agonistic behavior of Solenopsis geminata (Formicidae: Myrmicinae)
and its relation to graminaceous plants, under the supervision of Dr.
Klaus Jaffe. This investigation was supported by the Consejo
Nacional de Investigaciones Cientificas (CONICIT).
In 1983, she began her studies in entomology in the
Universidad Central de Venezuela in Maracay, Venezuela. A
fellowship from the Fundaci6n Gran Mariscal de Ayacucho supported
her studies. Her thesis research was related to the population
dynamics of Hediyepta indc~ata (Lepidoptera: Pyralidae) and its
natural enemies in soybean (Glycine max (L.)). This investigation was
supervised by Dr. Aquiles Montagne and supported by a grant from the
Universidad Central de Venezuela. Helena was elected representative
graduate student of the Department of Entomology between 1983 to
1984. She received her master's degree in entomology in 1986.
During 1986, she also worked as a field assistant in a project
of the New York Zoological Society in the Venezuelan Llanos. The
project was related to the behavior, ecology and nutrition of the








hoatzin (Opisthocomus hoatzin. Aves: Opisthocomidae) and was
supervised by Alejandro Grajal.
She enrolled in the Department of Entomology and Nematology
at the University of Florida in 1987, pursuing a Ph.D. degree under
the supervision of Dr. Joe Funderburk. During 1987 and 1988, she
participated as a field assistant in a project related to improving
the biocontrol of waterhyacinth (Eichornia crassies) using weevils
(Curculionidae: Neochetina eichornia and h. bruchi) under the
supervision of Dr. Kim Haag. As a laboratory assistant, she
participated in the following projects:1) spatial distribution,
dispersion and binomial sampling of the southern red mite
(Oligonichus ilici Mc Gregor) in azalea (Rhododendron spp.), under
the supervision of Dr. Kevin Monkman; 2) vectorial role of the green
lynx spider on the dissemination of the Anticarsia gemmatalis
nuclear polyhedrosis virus (NPV) using the ELISA technique, under
the supervision of Dr. Drion Boucias; and 3) identification of a
potyvirus from passion fruit (Passiflora edulis ) and a tobamovirus
from P. incarnata, under the supervision of Dr. F. William Zettler
from the Plant Pathology Department, University of Florida.
Her Ph.D. research was conducted in north Florida on the
movement of Frankliniella spp. (Thysanoptera: Thripidae) and the
epidemiology of the tomato spotted wilt virus (TSWV) in tomato
fields. Her major scientific interests are related to insect ecology,
biocontrol and epidemiology of diseases transmitted by insect
vectors. Specifically, she is interested on the interactions insect-
insect and insect vector-plant pathogen-plant host.








I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the degree
of Doctor of Philosophy. 1 (I


Donald C. Herzokt al I
Professor of Entomdt
Nematology


I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the degree
of Doctor of Philosophy.


Jbseph E. Funderburk,
Cochairman
Associate Professor of
Entomology and Nematology


I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the degree
of Doctor of Philosophy.


J. Howard Frank
Professor of Entomology and
Nematology


I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the degree
of Doctor of Philosophy.


Richard D. Berger 0
Professor of Plant Pathology









I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the degree
of Doctor of Philosophy.

Steven M. Olson
Associate Professor of
Horticultural Science



This dissertation was submitted to the Graduate Faculty of the
College of Agriculture and to the Graduate School and was accepted
as partial fulfillment of the requirements for the degree of Doctor
of Philosophy.


August, 1991
Dean, college of Ag -ulture



Dean, Graduate School






















































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