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This is to certify that the

dissertation entitled

AEDES TRISERIATUS AND TREEHOLES; TROPHIC
INTERACTIONS AND FACTORS INFLUENCING
LARVAL GROWTH

presented by

Jennifer Ruth Penrod

has been accepted towards fulfillment
of the requirements for

Ph . D . degree in Entomology

 

 

KZM>.%

Major professor

 

Date 24 August, 2000

 

MSU is an Affirmative Action/Equal Opportunity Institution 0-12771

 

 

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6/01 C‘JCIRC/DateDuepssvp. 15

AEDES TRISERIATUS AND TREEHOLES; TROPHIC INTERACTIONS AND
FACTORS INFLUENCING LARVAL GROWTH
BY

Jennifer Ruth Penrod

A DISSERTATION
Submitted to
Michigan State University

in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Natural Science

2000

ABSTRACT
AEDES TRISERIATUS AND TREEHOLES; TROPHIC INTERACTIONS AND
FACTORS INFLUENCING LARVAL GROWTH
By

Jennifer Ruth Penrod

The eastern treehole mosquito, Aedes tn'sen'atus (Say), and the ecosystem it
inhabits provide a valuable model system for studying ecosystem processes and
factors affecting growth and development. Studies reported here were directed
at two aspects of the biology of this mosquito in treeholes: (1) trophic interactions
among larvae and microorganisms in treehole water; and (2) an experimental
analyses of interacting factors affecting growth and metamorphosis of larvae.
With regard to trophic interactions, the trophic cascade hypothesis, and the “top-
down/bottom—up” hypothesis were tested. When a trophic cascade Operates in
an ecosystem, Changes in abundance of organisms in higher trophic levels result
in a cascade of changes in abundance or biomass of organiSms in lower trophic
levels, with alternating directional responses in alternating lower trophic levels.
By contrast, top-down/bottom-up forces operate such that abundance or biomass
of organisms at any given trophic level is dependent upon the input of nutrients
into the lowest trophic level in the ecosystem. Theory predicts that these inputs
should have positive but diminishing effects of the same direction with

succeeding, higher trophic levels. A series of laboratory and field experiments

showed that larvae of A. tn'seriatus are a keystone predator in treehole
ecosystems due to the significant effect of their presence on the abundance of
protists and bacteria. There was no clear evidence for a trophic cascade in
treeholes. Experiments involving nutrient manipulations showed the primary
nutrient affecting higher trophic levels was organic resources (senescent leaf
detritus); anionic nitrogen and sulfur were not stimulatory.

Other experiments were directed at growth and metamorphosis of A.
tn'seriatus larvae when temperature and basal food resources were manipulated.
Theory on the population reaction norm of ectothermic animals predicts that
animals should have decreased development rates and larger body sizes at
metamorphosis at low temperatures compared to the converse at high
temperatures; but that development rates and body sizes should be negatively
correlated when food supply is varied. Experiments showed that these
contrasting predictions held true when cohorts of larvae were subjected to
experimental combinations Of food and temperature; but there were no direct
statistical interactions between food supply and temperature. However, when
larvae were exposed to variable food and temperature individually, these reaction
norm responses differed: body size was similar among larvae reared at different
temperatures. Larval cohort mortality may affect these responses by dynamically
affecting the ration of food supply for larvae as temperature dependent mortality
occurred. Overall, the results indicated that a density-dependent reaction norm

response would be predicted from these findings.

I would like to dedicate this dissertation to my parents for their confidence that I
could and would get this done.

iv

Acknowledgments

I would like to acknowledge the funding of this research from NIH grant Al-
21884. I would like to thank my guidance committee for their help in
accomplishing this dissertation. I would also like to acknowledge the assistance

Of Mike Kaufman and Tracy Smith for their technical knowledge and support.

TABLE OF CONTENTS

LIST OF TABLES ........................................................................... vii

LIST OF FIGURES ........................................................................... viii

CHAPTER 1, Literature Review
Overview ........................................................................... 1
Mosquitoes in Container Habitats ........................................... 5
The Biology of Aedes triseriatds ............................................. 7
Microcosms ...................................................................... 10
Food Webs and Trophic Interactions ....................................... 11
Trophic Cascades .............................................................. 12
Top—down/bottom-up Theory ................................................. 13

Theory of Trophic Interactions and the Treehole Ecosystem. . ......1 5
Growth Pattern Responses of Mosquito Larvae

to Environmental Influences ........................................ 22
Reaction Norms ................................................................. 24
Summary .......................................................................... 27
Literature Cited .................................................................. 29

CHAPTER 2, Trophic interactions in treehole ecosystems; importance Of
top-down and bottom-up forces

Abstract ........................................................................... 41
Introduction ....................................................................... 42
Materials and Methods ........................................................ 44
Results ............................................................................ 49
Discussion ........................................................................ 56
Literature Cited .................................................................. 64

CHAPTER 3, Age and size at maturity in response to variable food and
temperature regimes for larvae of the mosquito, Aedes tn'seratus:
effects Of differential mortality

Abstract ........................................................................... 68
Introduction ....................................................................... 69
Materials and Methods ........................................................ 74
Results ............................................................................ 78
Discussion ........................................................................ 90
Literature Cited .................................................................. 96
CHAPTER 4
Summary and synthesis ..................................................... 100
Literature Cited ................................................................ 109
APPENDIX 1 ................................................................................ 112

vi

LIST OF TABLES

Table 2.1 Summary of ANOVAS testing for effects Of organic and
inorganic nutrients on microbial population densities ........................... 50

Table 2.2 Summary of ANOVAS testing for effects of organic
nutrients and predation on microbial population densities .................... 50

Table 3.1 Estimates of pupation window parameters for results of
experiment 1 (larvae reared in populations Of twenty), plus upper
and lower asymmetric 95% confidence limits are given in
parenthesis ................................................................................ 85

Table 3.2 Survival, development time and adult mass at low and high
leaf rations. Values are given as the mean 1 SEM (N = 6 per
group) ....................................................................................... 85

Table 3.3 Linear regression equations for relationships between
temperature, leaf ration and adult mass. Y = mosquito mass (mg),
X = leaf mass (mg) ...................................................................... 90

Table 3.4 Estimates of pupation window parameters for results of

experiment 3 (larvae reared individually), plus upper and lower
asymmetric 95% confidence limits are given in parenthesis .................. 90

vii

LIST OF FIGURES

Figure 1.1 Descriptive example of a trophic cascade reaction to
disturbance at the top trophic level .................................................. 14

Figure 1.2 Descriptive example of diminishing bottom-up
interactions as outlined by McQueen et al. (1989) .............................. 16

Figure 1.3 Food web diagram depicting relationships of Aedes
tn'seriatus larval feeding habits as determined by gut content
analysis and microbial feeding strategies. (M.G. Kaufman,
unpublished) .............................................................................. 18

Figure 1.4 Pupation window model showing fit of curve
reflecting development time and adult mass of females. The
dashed horizontal line represents the critical (minimum)
mass requirement for pupation and the dashed vertical line
represents the critical length of development time for
pupafion .................................................................................... 23

Figure 2.1 Bacterial and protozoan responses to organic
nutrient input. Density values are represented as log1o values
averaged over microcosms within each treatment group ...................... 51

Figure 2.2 Response of bacterial densities to inorganic nutrient
input in the absence of organic material ............................................ 53

Figure 2.3 Population density of protozoa averaged across three
levels Of organic nutrient input ....................................................... 54

Figure 2.4 Bacterial and protozoan population density response
to predator addition and removal in the absence of any
organic material .......................................................................... 55

Figure 2.5 Bacterial population densities comparing tree holes
either with mosquito larvae present or absent. Those with no
mosquito larvae had larvae removed by exposure to boiling
water. Those with larvae present were treated with boiling
water and then restocked with first instar Aedes trisen'atus
lavae ......................................................................................... 57

viii

Figure 2.6 Relationship of adult emergence and bacterial
population response. Solid line represents bacterial
population densities over time and the dashed line
represents the cumulative emergence of mosquitoes as
adults. This line corresponds to removal of the larval
predator through its natural life cycle. As this keystone
predator exits the natural ecosystem the bacterial population
responds by increasing in numbers .................................................. 58

Figure 2.7 Bacterial population densities comparing tree holes
either with mosquito larvae present or absent in the second
tree hole experiment, where larval mosquitoes were
removed by addition of the bacterial-based liquid larvicide,
Vectobac 12AS ............................................................................ 59

Figure 3.1 Male and female development time for three
temperatures and three food rations. ............................................... 80

Figure 3.2 Male and female mass for three temperatures and
three food rations ......................................................................... 81

Figure 3.3 Male and female survival rates for three
temperatures and three food rations. ............................................... 82

Figure 3.4 Scatter plot Of pupation window data obtained from
larvae reared in populations of twenty ............................................... 84

Figure 3.5 Scatter plot of data for male and female adult mass
against the starting leaf mass available for development ...................... 87

Figure 3.6 Scatter plot of pupation window data obtained from
individually reared larvae .............................................................. 89

ix

CHAPTER 1

Literature Review

Overview

Mosquitoes are responsible for transmitting the causative agents of some of
the most widespread and prevalent infections of humans, including malaria,
lymphatic filariasis, yellow fever, dengue fever, and the encephalitides. These
relationships have been well reviewed elsewhere and will not be repeated here
(e.g. Aultman et al. 2000). Although these diseases remain highly important
causes of morbidity and mortality in tropical regions of the world, such as Africa,
Asia, and South America, they historically occurred in temperate areas as well.
In regions such as North America and Europe, mosquito-bome disease
prevalence has dramatically declined due to indirect effects such as increased
standards of living and improved medical care, and to direct effects such as
vector control, habitat alterations, and intentional barriers blocking mosquito
contact with humans (i.e., window screens, repellents). However, the United
States, the European Economic Community, and other members of the ‘First
World’ continue to be the centers and funders for research on arthropod-bome
diseases, and for the development of anti-vector tools, medicines, and vaccines.
The significance of mosquito-bome disease was dramatically imposed upon
citizens of the United States during the recent outbreak of the West Nile virus in
New York City and surrounding areas in 1999 and continuing into 2000. This

virus, similar to St. Louis encephalitis and known to be vectored by species of

mosquitoes in the genus Culex, could spread beyond this region if measures are
not taken to control the mosquito populations and/or the bird host populations
harboring the virus.

In order to control populations of disease vectors and, in turn, control the
disease agents they transmit, there must exist an extensive and thorough
knowledge of the life cycle and ecology of these arthropods. The contrasting
demands of a well-educated public to control medically-important and pest
mosquitoes, on the one hand; while Simultaneously protecting the environment
from long-term effects of chemical insecticides, on the other hand, only reinforce
the need for biological studies on vectors (Aultman et al. 2000).

There are approximately 2500 species of mosquito worldwide with roughly
150 species in the United States, including many species that participate in
disease transmission cycles. The family Culicidae is biologically diverse, and
indeed there is a rich history of investigations into the biology, ecology,
physiology, biochemistry, molecular biology, systematics, and general life history
of this important insect group (Clements 1992). Despite their diversity, the
biology of mosquitoes can be distilled into basic components. The egg is laid by
the mated female mosquito on top of water either in rafts or singly; or the eggs
are laid in moist or dry soil or Similar environments that will eventually be flooded
with water. Tiny larvae, first instars, hatch from the eggs by bursting the top of
the egg Off using a specialized structure on the head capsule called an egg
burster. These larvae then enter the water, swim about, and feed in the water

column and along submerged surfaces using a highly complex mouth part

arrangement (Merritt et al. 1992). The larvae gain mass, and molt three times
(passing through the second, third, and fourth instars), and then molt again to
enter a motile, aquatic, and non-feeding stage called a pupa. An adult male or
female then emerges from the pupa on top of the water, and after sclerotization,
melanization, and wing stretching, it flies away. Males meet females for mating
in a variety of ways, such as swarming or on substrates. Both males and
females seek nectar for carbohydrate nutrient. Females of many species also
seek vertebrate hosts for blood-feeding. The females utilize the blood
physiologically to develop eggs. A single female mosquito may take many blood
meals in her lifetime. Indeed, it is the serial process Of blood-feeding that permits
acquisition and transmission of disease agents. The above review is a
generalization, and there are variations from it.

A variety Of environmental factors - both biotic and abiotic - contribute to the
growth and development Of larval mosquitoes and to the consequent production
of adults from individual larval habitats. These factors include physical and
chemical water regime in the aquatic habitats, water temperature, quantity and
quality of food available to larvae, and intensity of predation and parasitism
(Clements 1992, Laird 1988). Larvae are thought to compete in a density
dependent manner for food resources in many habitats, particularly in confined
ones (see below). Hawley (1985) has proposed that a linkage exists between
larval performance in habitats, adult production, the variation in adult female size
that results from larval competition, and population dynamics. Physical features

of adult mosquitoes resulting from competition and other factors in the larval

environment, leading to variation in adult body size, may contribute to their
susceptibility to disease agents, their longevity, and consequently to their
capacity as vectors (Hawley 1985, Clements 1992). As Washbum et al. (1988,
1989, 1991) discovered in studies involving protozoan and fungal parasites of
Aedes sierrensis, the western treehole mosquito, the interaction Of the mosquito
with environmental parameters such as food availability, intraspecific competition
for food, and even specific feeding behaviors profoundly influence the
population’s dynamics. Under specific conditions, natural enemies of larval
mosquitoes may actually increase the fitness of certain adults by releasing these
nonparasitized survivors from competition, and thereby increasing their body size
and fecundity.

By examining the biology of mosquitoes from the viewpoint of interactions
between mosquito populations and the ecosystems in which they live, we can
gain a better understanding of the role that environmental factors play in larval
development, adult mosquito production and fitness, and population dynamics.
Examination Of the food web dynamics involving larval mosquitoes and their
microbial prey can provide insight into the relationships between larval
mosquitoes and the natural food resources available to them. Increasing our
knowledge Of how manipulation Of these environmental conditions can influence
biological development will ultimately provide information as to an organism's

ability to carry and transmit disease.

Mosquitoes in Container Habitats

Some 40% of all mosquito Species have as their larval habitat small bodies of
water formed in natural or artificial containers, such as leaf axils, bamboo
intemodes, treeholes, tires, rock holes, cemetery urns, and the like (Frank and
Lounibos 1983). These habitats, called phytotelmata (from the Greek ‘phyto'
meaning plant, and ‘telma’ meaning pond or pool; Frank and Lounibos, 1983),
contain a community of insects and microorganisms. Mosquitoes often figure
prominently in the community living in phytotelmata. Because phytotelmata are
small, discrete, often numerous, and can be sampled fairly easily, they have
been viewed as excellent model systems for a variety of studies including
community ecology, population ecology, and ecosystem modeling (e.g. Kitching
(19833, b, 1987). One of the most common and often investigated types of
phytotelmata is treeholes. A generalized food web model of aquatic treeholes in
temperate regions involves input of organic detritus in the form of senescent
leaves (Kitching 1983a, b). Water enters the treeholes either as throughfall from
the forest canopy or along the sides of the trees in the form of stemflow (Eaton et
al. 1973). Stemflow washes inorganic ions into treeholes that may serve as
nutrient resources for microorganisms associated with decomposing leaf litter
(Kitching 1971, Carpenter 1982, Fish 1983, Fish and Carpenter 1982, Walker et
al. 1988, Walker et al. 1991).

The leaf detritus-based conceptualization of treehole ecosystems has leant
itself to a rigorous series of laboratory and field tests. Those studies conducted

in the laboratory have involved plastic dishes designated as microcosms meant

to simulate natural treeholes, whereas studies in the field have used microcosms
set up as treehole simulations, or have involved manipulations or sampling of
natural treeholes. The bulk of studies have involved mosquitoes. Larval
mosquito growth was found to be primarily a function of leaf litter ration available
per larva across a range of larval densities (Fish and Carpenter 1982, Carpenter
1983), but variation in leaf quality also dramatically affected growth (Walker et al.
1997). Mosquito growth in microcosms with stemflow water was only slightly
greater than that in microcosms with distilled water, suggesting that the
influences of stemflow water on mosquito growth are minor compared to the
influences of leaf detritus (Carpenter 1982). However, Walker et al. (1991) found
that stemflow was stimulatory to growth, perhaps through a physical process Of
adding nutrients while diluting potential toxins such as ammonia and hydrogen
sulfide. Field tests of the leaf detritus-based model showed strong differences in
mosquito productivity between artificial treeholes with leaves compared to
artificial treeholes with no leaves (Walker et al. 1991 ). In contrast, a field test
found no difference in mosquito production between natural treeholes with an
average amount of senescent leaf mass and treeholes from which leaves had
been removed, indicating that other factors besides leaves impinge upon
mosquito growth (Walker and Merritt 1988). More recently, Leonard and Juliano
(1995) refuted these results with an intervention experiment involving caged
mosquitoes that were provided or not provided a leaf substrate in real treeholes.

The realism of caging mosquito larvae is certainly questionable.

Because of the small size of phytotelmata, the high densities of larvae in the
habitats, and the fact that food is often in short supply, populations of mosquitoes
inhabiting phytotelmata are thought to be regulated primarily by biotic factors
such as density-dependent larval competition for food, facilitative density-
dependent interactions among trophic levels in food webs, predation, and
parasitism (lstock et al. 1975, 1976; Siefert 1984; Fish and Carpenter 1982;
Livdahl 1982; Bradshaw and Holzapfel 1983; Chambers 1985; Frank et al. 1985;

Hawley 1985; Lounibos 1985; Kitching 1987; Walker et al. 1987).

The Biology of Aedes triseriatus

Aedes tn'seriatus, the eastern treehole mosquito, is a container-breeding
mosquito of North America. It is the subject of the research reported here.
Because of its role as a vector of La Crosse encephalitis virus and dog
heartworrn, there is extensive literature on the basic biology of this species (Craig
1983), which is reviewed here. The geographic range of A. tn'seriatus extends
from Texas to Manitoba, and eastward to New England, Ontario and Quebec
(Darsie and Ward 1981 ). As with all mosquitoes, the life cycle of A. tn'sen'atus
involves an aquatic larval stage and a terrestrial adult stage. Gravid females lay
eggs on the sides of water-filled containers in clusters at the air/water interface.
Larvae of this species hatch from the eggs beginning in the spring, between
March and April, in response to changes in photoperiod, temperature and a drop
in oxygen concentration experienced when the eggs are flooded (Shroyer 1978,
Gjullin et al. 1941, Borg & Horsfall 1953, Judson 1960). The hatch is

asynchronous due to both a variation in response to the oxygen concentration

(Livdahl & Koenekoop 1985) as well as the influence of variable larval densities
(Livdahl et al. 1984, Livdahl & Edgerly 1987). An asynchronous hatch provides a
population structure with larvae of various developmental stages present at the
same time.

Larvae have four instar developmental periods prior to pupation. The length
of time for development through these stages depends on factors such as
intraspecific competition for food (McCoombs 1979, Fish and Carpenter 1982)
and temperature (Shelton 1973). Upon the fourth molt, the larvae become
pupae. Adults emerge from tree holes in northern states from mid-June through
September (Sinsko and Craig 1979, Scholl and DeFoliart 1978). There can be
either one or two generations per year depending upon environmental conditions,
in particular frequency of rainfall. Eggs of A. tn'sen'atus may enter diapause
beginning in August and delay hatching until the following year in a temperate
climate (Shroyer & Craig 1980). In southern climates the late instar larvae may
also enter diapause to overwinter (Simms 1982).

Male A. tn'sen‘atus adults emerge sooner than females, when eggs of both
sexes are hatched at the same time. Females mate and search for a blood meal
within 3 days post emergence (Walker et al. 1987). Aedes trisen'atus females
prefer mammalian hosts and have the unusual behavior of selecting chipmunk
and squirrel hosts during the daytime. Development of eggs in a female’s body
ranges between 48 and 96 hours dependent on temperature, after which she

deposits her eggs on the container edge above the water line. The number of

eggs laid can vary from less than fifty to more than two hundred depending upon
the fecundity of the insect.

AS mentioned above, treeholes are a type of phytotelmata and form the
primary habitat for A. tn'sen'atus larvae. However, this mosquito has also
Invaded artificial habitats, including discarded cans, buckets, rain barrels and
junked tires. Treeholes Of southern Michigan consist predominantly of rainwater
accumulating in basins formed by living roots of deciduous trees. Aedes
tn'sen‘atus larvae are found in pans or rot holes of deciduous trees in eastern
North America (Jenkins 8 Carpenter 1946, Mitchell & Rockett 1981, and
Bradshaw & Holzapfel 1983). Rot holes are formed at a wound, which
penetrates the bark of the tree, and a pan is a tree hole with a complete bark
lining.

Inhabitants of treehole ecosystems of southern Michigan and other areas
where A. tn'sen'atus occurs include larval mosquitoes, larvae of scirtid beetles,
chironomid midges, ceratopogonids, syrphids (Jenkins and Carpenter 1946,
Snow 1949, Kitching 1971) and a variety of microorganisms including both
bacteria and protozoa (Lackey 1940, Walker and Merritt 1988, Walker et al.
1991). As discussed above, the treehole ecosystem is generally considered to
be a heterotrophic system wherein all life is supported by inputs of senescent leaf
material and other detritus, which decomposes through microbial processing
(Kitching 1983). Episodic rainfall disturbs the water column, and results in inputs
of water as throughfall or stemflow, and may variously increase or decrease

anion and cation concentrations depending upon initial conditions (Walker et al.

1991). Microorganisms are found in treeholes both adhering to solid surfaces,
especially leaves, and in the water column (Kaufman et al. 1999). The microbial
lawn exposed on leaf surfaces can be rapidly grazed to depletion by mosquito
larvae, while leaf surfaces not exposed to larval feeding are teeming with
microbial growth (Fish and Carpenter 1982, Walker and Merritt 1991, Kaufman et
al. 1999). A. tn'sen'atus larvae consume particulate organic matter, including the
biofilm generated by the interaction Of microorganisms and leaf detritus (Walker
et al. 1988).

An understanding of the interactions between these multiple biotic and abiotic
factors influencing larval mosquitoes would greatly benefit the understanding of
A. tn'sen'atus growth and development. As Walker et al. (1991) have Observed
with reference to the biology of A. tn'sen'atus: “Because treeholes are small, are
discrete, contain a tractable community of organisms, and can be manipulated
and simulated, they provide an ideal experimental situation for examining biotic
interactions and processes within an ecosystem, as well as influences of abiotic

and physical factors on an ecosystem.” This theme is adopted here.

Microcosms
Interactions between microbes and their predators have been extensively
studied and revealed using microcosm experiments (Coleman et al. 1983,
Verhoef and Brussaard 1990, Verhoef 1996). The objective of utilizing
microcosms as simplified model systems is to measure processes and

population dynamics accurately in order to test ecological theories (Daehler and

10

Strong 1996, Mikola and Setala 1998). Microcosms are tools for testing
ecological theories because the composition of the community can be strictly

controlled and replicated (Kareiva 1989, Balciunas and Lawler 1995).

Food Webs and Trophic Interactions

A food web is a diagram depicting the complex interactions between all
organisms in a habitat, which create, process, and decompose organic material.
These food web models are useful in applied research by providing an
understanding of community structure and population interactions. The
organisms that create, process, and decompose organic material interact
hierarchically at various trophic levels in what has come to be known as a "food
web”. Each step by which this energy stored in organic material is shuttled
between organisms is a transition between trophic level and the interrelationships
of various trophic levels constitutes such a web. Recently, great attention has
been paid to food web dynamics, with Special interest in aquatic ecosystems
(Carpenter et al. 1985, Matsen & Hunter 1992, Matveev 1995, Armstrong 1994,
Tavares-Comar 1996, Gaedke 1995). In its simplest conceptualization, a food
web consists of top, intermediate and basal trophic species.

Trophic species is a term used by some ecologists (Cohen and Newman
1985, Yodzis 1988, Cohen and Briand 1984, Pimm 1982) to describe a collection
of organisms in an ecosystem which share common prey and predators.
Individuals comprising the top trophic level are not eaten by any other trophic

species in the web, while at the bottom of the food web are basal species,

11

including both primary producers and detritus, which feed on no trophic species.
Individuals occupying the intermediate levels then are utilized as a resource by at
least one other trophic Species while also exploiting an additional trophic species
as a resource. Each trophic level within an ecosystem is influenced both
qualitatively and quantitatively by factors including, but not limited to: 1)
availability of nutrients, 2) competition for resource acquisition, 3) predation by
higher trophic levels, and 4) external disturbances of the system. Although the
concept of trophic level obviously has limitations, it can be utilized broadly as a

means of classifying trophic interactions within the food web concept.

Trophic Cascades

Predictions of biological processes stemming from food web interactions must
be based on the relationships between multiple trophic groups and feedback
responses induced by these relationships. Hairston et al. (1960) first proposed
the idea that regulation of any population is determined by the trophic level to
which it belongs. The ideas presented in a trophic cascade reflect a set of
Interactions rather than a flow of energy. For example, in a terrestrial ecosystem
with three trophic levels (plants, herbivores and carnivores), the plants are limited
by resources such as water and nutrients, the herbivores are limited by the
abundance Of plant biomass, and herbivore prey density limits the carnivores.
The theory of trophic cascades states that these interactions lead to a strong
influence of top-down regulation with the condition of alternating regulatory

processes. This idea of a "cascading” system beginning at the top of the web

12

and flowing down through multiple trophic levels has been further developed to
include the regulation by upper levels on lower level productivity (Carpenter et al.
1985, McNaughton 1985, Carpenter and Kitchell 1988). These ideas can be
graphically represented as outlined in Figure 1.1. These alternating patterns are
reflective of direct feeding relationships of trophic levels following a set of food
chain linkages. These relationships necessarily exclude omnivory, i.e.,
organisms feeding at multiple lower trophic levels. Correspondingly, it is a

Simple, qualitative, and somewhat unrealistic theoretical construct.

Top-downlbottom-up theory

The top-downzbottom-up theory of McQueen et al. (1986) considers the
combined influences of predators and nutrient availability on ecosystem structure
(i.e., food web relationships). It contrasts with the trophic cascade concept,
above, in that it deals with the quantitative nature of trophic interactions and
allows for omnivory. This theory predicts that although the maximum attainable
biomass of a food web is determined by nutrient availability, the actual biomass
is determined by the combined effects of bottom-up and top-down forces. This
theory is concerned more with the magnitude of changes in trophic levels both
above and below a perturbed level. Top-downzbottom-up theory also predicts
that a reduction in resources or nutrients available to the lowest trophic level will
result in decreased abundance, biomass and/or production of organisms in
higher trophic levels, and that this effect will become proportionately weaker with

each higher trophic level (Fig. 1.2). Similarly, the theory predicts that top down

13

 
 
   

 

 

 

Top Level Predator
8
C
N
1:
C
3
.o
<
Intermediate Trophic Level
8
c
(B
'D
C
3
.o
4:
Bottom Trophic Level
3 (Resources)
5
t
c
3
n
<

 

 

Time

Figure 1.1 Descriptive example Of a trophic cascade reaction to disturbance at
the top trophic level.

14

forces will have their greatest effect at the highest trophic level but will dissipate
as they reverberate through lower trophic levels.

The diminishing effect following top level disturbances appears to be
substantiated with field observations in lake ecosystems by McQueen et al.
(1989), as well as by analytical simulation by Herendeen (1995). Several aquatic
studies also support the theory that ”bottom-up" forces of increased productivity
at basal trophic levels will result in increased abundance at all trophic levels
(Abrams 1994, Mills 8 Shiavone 1982, Mittelbach et al. 1988, Leibold 1989).
Although a dissipation of these effects of bottom-up forces to upper levels of the
food chain has been observed by McQueen et al. (1989). Both Matveev (1995)
and Persson et al. (1988) observed food webs in eutrophic lakes in which

bottom-up impacts actually became stronger at higher trophic levels.

Theory of Trophic Interactions and the Tree Hole Ecosystem

The concepts inherent in the trophic cascade and top-downzbottom-up
theories can be applied to a simplified model of Aedes trisen'atus and the tree
hole ecosystem of which it is a part. For the purposes of examination of A.
trisen'atus growth and development, the model food web in treeholes begins with
organic detritus as the basal resource. The first trophic level contains the
bacterial organisms that colonize the detritus, and/or subsist on the nutrients the
detritus provides. The second, or intermediate trophic level is protozoans,
because many protozoan species are predators of bacteria. At the top trophic

level is the mosquito larvae which prey on microorganisms in the lower trophic

15

 

 

 

 

     

Top Level Predator

o

0

c m
N

1:

C

3

.o

<

Intermediate Trophic Level

0

0

C

(B

U

I:

3

a

<

c, Bottom Trophic Level
2

CB

1:

c

3

a

<

 

 

Time

Figure 1.2 Descriptive example of diminishing bottom-up interactions as outlined
by McQueen et al. 1989.

16

levels. This simplified model necessarily removes other invertebrate competitors
or facilitators, but it allows close analysis of the relationship between mosquito
larvae and their food resources. Michael G. Kaufman (unpublished) has
constructed a food web diagram to depict these relationships based on current
information about larval feeding habits, gut content analysis and microbial
feeding strategies (Fig 1.3). The model presented diagrammatically in Fig. 1.3 is
based on the generalized phenomenon of heterotrophic (vs. autotrophic) basis of
ecosystem trophic dynamics. Indeed, many macroinvertebrates in freshwater
ecosystems utilize allochthonous leaf detritus as food. Some invertebrates
consume leaf detritus directly by shredding coarse particulate detritus or by
gathering finer detritus (Berrie 1976, Slansky and Scriber 1985), while other
invertebrates, including mosquito larvae, exploit the leaf detritus indirectly, by
filtering, scraping, or browsing microorganisms in the biofilm on the leaf surface
(Cummins and Klug 1979, Fish and Carpenter 1982, Walker and Merritt 1991,
Merritt et al. 1992). Invertebrate growth on leaf detritus varies with the type of
feeding mode, quantity of leaf detritus, chemical composition of leaf detritus,
decomposition rate of leaves, and microbial conditioning of the leaf material
(Kaushik and Hynes 1971, Berrie 1976, Anderson and Sedell 1979, Cummins
and Klug 1979, Merritt et al. 1984, Walker et al. 1997).

As discussed above, there is some controversy over the exact role of leaf
detritus in tree holes as a basal resource for A. tn'seriatus larvae. To review,
detritus has been shown to be stimulatory to larval A. trisen'atus growth (Walker

et al. 1991, and references therein), but this effect was not repeated in natural

17

Dead plant material Stemflow

\ /

DOC (dissolved organic carbon)
DON (dissolved organic nitrogen)
Inorganic nutrients (e.g. P04, N03, NH4)
FPOM (fine particulate organic matter)

Substrate-associated fungal \ .
biomass Water column bactenal
bIomass

  
   
   
    
    

Substrate-associated bacterial l
biomass
Water column protozoan
I biomass
Substrate-associated
protozoan biomass

\ .

Mosquito larvae and other
invertebrates

I

Adult emergence and outflow

 

 

Figure 1.3 Food web diagram depicting relationships of Aedes trisen'atus larval
feeding habits as determined by gut content analysis and microbial feeding
strategies. (M.G. Kaufman, unpublished)

18

treeholes (Walker & Merritt 1988). Leonard & Juliano (1995) did show that direct
interactions with detritus enhanced larval growth and production of larvae in
treeholes when larvae were confined within mesh cages that did, or did not,
contain senescent leaves. However, those studies, similar to microcosm studies,
eliminate contact with alternative organic surfaces, which could provide
attachment sites and nutrient supplementation to microbial growth such as tree
bark and sediment. The presence of a solid surface influences the number and
activity of bacteria (ZoBell 1943, Sieburth 1976, Paerl 1980, Paerl & Merkel
1982). Nonetheless, microbial decomposition of organic carbon input, such as
detritus, may provide a medium whereby nutrient liberation and microbial
concentration both offer incentive for enhanced larval development.

It has been recognized that bacteria and protozoa are responsible for a large
portion of the biomass, respiration, nutrient cycling, and productivity in aquatic
ecosystems (Azam et al. 1983, Porter et al. 1985, Sherr and Sherr 1991). Thus,
they are of clear importance in the overall trophic dynamics in ecosystems
(Fenchel 1982, Pomeroy and Wiebe 1988, Sherr et al. 1988). Cochran-Stafira
and von Ende (1998) have provided insight into the response of a basal-level
bacterial community to predation in an aquatic microbial food web. Results of
their experiments involving larvae of the pitcher plant mosquito, Wyeomyia
smithii, in artificial pitcher plants, indicated that interactions among higher trophic
levels could cascade down to the microbial level indicating the need to treat

microbes as fully interacting members Of a community.

19

In A. trisen'atus habitats in northern climates, the absence of the predatory
mosquito larvae Toxorhynchites mtilus makes A. trisen'atus the predominant
mosquito species in treeholes (Mitchell and Rockett 1981). In treeholes located
in southern parts of the distribution of A. trisen'atus, the co-occurrence of
Toxorhynchites rutilus might reduce intraspecific competition among A. trisen'atus
larvae as it is becoming increasingly recognized that competition regulates the
number of species in a community only when the members of the community
actually compete, i.e., when they are at or near their carrying capacity (Menge &
Sutherland 1976, Bradshaw & Holzapfel 1983). In northern climates however,
field and laboratory observations have shown that reduced survival and pupal
weight as well as extended development time can be traced to high larval
densities which cause intraspecific competition (Moore 8. Fisher 1969, Mori 1979,
Fish & Carpenter 1982, Broadie & Bradshaw 1991). In this situation, larval
competition may be an important means of population regulation in this
ecosystem. Thus, A. tn'sefiatus larvae can be properly viewed as predators
occupying the top trophic level in tree holes, with microorganisms in lower trophic
levels comprising their prey.

Invertebrate studies have revealed that competitive interactions between
larvae increase with increasing population density because food is a limiting
factor (Lamberti et al. 1987, Wissinger 1988) and because food and density
interact with one another (Hard et al. 1989). Aedes trisen’atus larval densities
specifically exhibit strong competition among larvae in response to manipulation

of larval densities (Edgerly & Livdahl 1992). Presumably, the resource for which

20

these larvae are competing is food in the form of microorganisms. Gut content
analysis of fourth instar larvae of multiple mosquito species revealed a
predominance of bacteria and detritus (Walker et al. 1988, Merritt et al. 1990)

with an estimated mean number of bacteria in the larval food bolus of A.

triseriatus specifically being 2.2 x 105. Bacteria have been considered to be the
most dominant of the microorganisms that comprise the diet of mosquito larvae
(Laird 1988). Rozeboom (1935) showed that mosquito growth was possible on
certain bacterial cultures alone. In addition, feeding by mosquito larvae has been
shown to reduce the abundance of microorganisms in both field studies and
microcosm experiments (Kurihara 1983, Walker et al. 1991). Larval feeding on
microorganisms is not limited to bacteria, as gut content analysis also indicates
the presence of protozoan organisms in the larval diet.

Omnivory is common in decomposer food webs (Polls 1991, Gunn and
Cherrett 1993, Mikola and Setala 1998). When a predator utilizes two prey in the
same ecological habitat, there is generally some interactive effect between these
two prey species. Increases in the population density of one prey species can
decrease a predator's influence on the Opposing prey species, thereby allowing
that population to increase in density (Murdoch 1969, Murdoch & Oaten 1975).
An alternative situation arises when increases in the first prey species allow an
increase in predator numbers which over time would result in decreases in the
second population as well (Holt 1977, Holt & Lawton 1994). The fact that A.

triseriatus larvae feed on both bacteria and protozoans indicates that the

21

relationships between trophic levels are not be clearly defined by these simple

categories.

Growth Pattern Responses of Mosquito Larvae to Environmental
Influences
In several insect species, a minimum weight must be achieved during the

larval stage in order for development to continue (Nijhout & Williams 1974,
Lounibos 1979, Safranek & Williams 1984). The mechanistic model of pupation
presented by Gilpin & McClelland (1979) is based on the Classic Bertalanffy
growth equation (Bertalanffy 1960) and provides a model of an inverse
relationship between pupal mass and development time. A generalized growth
model of mosquito larvae, the pupation window model (Walker et al. 1997),
predicts that larvae must attain both a minimum development time and a
minimum mass prior to pupation according to the equation (T -h1 )(W-h2) = h3,
where T= development time, h1 = minimum development time, W = adult mass,

= h2 minimum adult mass, and h3 indicates the curvature of the function. Faster

growing larvae, not limited by resources, achieve the critical mass within the
minimum development time and continue to grow to a maximum mass
determined by phenotype (Figure 1.4). In the contrary situation, slower growing
larvae pass the minimum development time without accruing sufficient mass to
pupate; they either continue growing to the critical mass before they pupate (at a
mass lower than the maximum possible); or they starve to death. Although the

overall size of mosquito species is based in genetics, individual size can be

22

ADULT MASS

 

critical development time

critical mass

 

 

 

 

DEVELOPMENT TIME

Figure 1.4 Pupation window model showing fit of curve reflecting development
time and adult mass of females. The dashed horizontal line represents the
critical (minimum) mass requirement for pupation and the dashed vertical line
represents the critical length of development for pupation.

23

influenced by a number Of environmental factors including nutrition, temperature,
and larval density. These factors can also affect the Shape and position of the

curve depicting the pupation window model.

Reaction Norms

ln variable environments, organisms will show covarying developmental
responses that represent phenotypic plasticity overlaid on their fixed genotypes
(Steams & Koella 1986). The capability of organisms to adjust their responses to
a variable environment has been termed phenotypic plasticity, while the
expression of the response to any given set of environmental circumstances has
been termed the “reaction norm” or the “norm of reaction.” Schmalhousen (1949)
originally defined the term within an evolutionary context as an expression of
epigenetic effects on ontogenetic processes that allow organisms to adapt to
variable environments. Schlicting & Pigliucci (1998) coined a new but closely
related term, “developmental reaction norm,” and re-defined it in their practical
definition as follows: “The set of (multivariate) ontogenetic trajectories produced
by a genotype (or sibship) in response to naturally occurring (or experimentally
imposed) environmental variation.”

Two of the most common and important environmental factors that affect the
development of ectothermic animals are food supply and varying temperature.
When these factors vary, they strongly affect development time to maturity (i.e.,
age) and Size at maturity (i.e., size). However, they affect these two important

developmental parameters in contrary ways (Sibly and Atkinson 1994). With

24

regard to temperature, age and size at maturity respond similarly, i.e., they both
decrease with increasing temperature, thus the reaction norm (sensu Steams
and Koella 1986) for size-to-age at maturity has a positive slope. With regard to
food supply, by contrast, size and age at maturity respond in opposite ways;
development time decreases whereas size increases with increasing availability
of food; the reaction norm has a negative slope. These contrary responses may
result from the ways that metabolic rate and food acquisition rate respond
differentially to variations in food supply and temperature, thus the latter two
factors ought to interact significantly in affecting the reaction norm (Perrin 1995).
These observations have stimulated a debate about the universality of these
patterns among ectotherrns, the physiological basis for these relationships, and
whether there exists reciprocal selection for development time and body size at
maturity (Bern'gan and Chamov 1994, Perrin 1995).

For mosquito larvae, which are ectothenns, the literature supports the general
observation that limitations in food supply result in an extended larval
development time, smaller adult body size, and higher larval mortality (see
review in Clements 1992). Temperature also affects development time and body
mass of mosquitoes and other ectotherrns during their development, but in ways
contrary to changes in food availability. Decreased temperature results in
increased development time, and also increased body mass (Clements 1992).
Experimentation is necessary in order to predict how food availability and
ambient temperature will interact to affect developmental processes of

mosquitoes. Within the limits of thermal tolerance, the rate at which mosquito

25

larvae develop increases with temperature (Bar-Zeev 1957, Nayar 1968),
whereas the resulting size of the adult varies inversely with temperature (van den
Heuvel 1963, Nayar1969, Hien 1975). Chambers and Klowden (1990) observed
that the larvae of Aedes aegypti mosquito enter the pupal stage at a critical
weight, which was lowered by raising the larval rearing temperatures. This
supports the model for ectothenns which dictates that a decreased temperature
reduces growth rate, and is manifested as extended development and larger size
in 80% of 100 studies (Berrigan and Chamov, 1994).

Why is variation in mosquito body size important? It is now Clear that body
size is an ontogenetic trait that influences fitness through fecundity, and vectorial
capacity, i.e. that combination of biological attributes that permits mosquitoes to
transmit disease agents. Both in nature and in laboratory settings, there is wide
variation in the size of adult mosquitoes within a given species (Fish 1985). In the
laboratory, Aedes aegypti males exhibit 40-fold and females 50-fold variations in
body mass (Christophers 1960). This variation in size is only partly explained by
genetic predisposition, as environmental influences including temperature, food
availability and population density also contribute to determination of adult size at
emergence. Larger adult mosquitoes are more fecund (Briegel, 1999;
Steinwascher, 1982; Washbum et al., 1989; Lyimo & Takken, 1993; Clements,
1992) than their smaller female counterparts which produce fewer eggs per
reproductive cycle (Barlow 1955, Bar-Zeev 1957, Steinwascher 1982, Hawley
1985). As larval densities increase and competition for food correspondingly

increases, adult female size decreases and the number of eggs laid therefore

26

goes down. This relationship has been incorporated into several mosquito
population models with the idea that this kind of exponential dampening
represents a strong control on population density (Hawley 1985). Although
research has been inconclusive regarding the relationship of adult size and
longevity (Haramis, 1985; Nasci, 1987; Landry et al., 1988; Mori, 1979; Walker et
al., 1987), Aedes mosquitoes have shown a direct correlation between large size
and success of blood-feeding (Nasci, 1990). Variation in body Size also affects
parameters contributing to the vectorial capacity of mosquitoes for pathogenic
microorganisms (discussed in Walker et al. 1997), such as the fact that adult
mosquito size can also determine their susceptibility to infection (Baqar et al.,

1980; Grimstad & Haramis, 1984; Kitthawee et al., 1990).

Summary

Because mosquitoes are important ecological organisms as both pest species
and transmitters of disease, it is important to examine their patterns of growth
and development for clues to possible means Of control. Growth and
development ultimately determine important adult features directly related to the
organism’s ability to harbor and transmit pathogens. Female mosquito size is
directly related to vectorial capacity and in return Size is dependent on a variety
of environmental factors. Food resources in microcosms can be Simulated as
leaf detritus, but an understanding Of the relationship between basal resources
and other trophic prey such as microorganisms present in natural treeholes gives

a more accurate picture of the natural food resources contributing to larval

27

development patterns. Temperature, food resource availability and population
density all contribute to the organism’s size and the size contributes to the
organism’s ability to transmit disease. These relationships have encouraged
research to analyze the how these influential parameter Interact to determine

larval growth and development patterns.

28

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39-56. '

40

CHAPTER 2
Trophic interactions in treehole ecosystems; importance of top-down

and bottom-up forces.

Abstract

Larval mosquitoes of the tree hole species, Aedes trisen'atus, are potential
keystone predators on microorganisms in treehole ecosystems. These
ecosystems are detritus-based food webs which can be simplified to three trophic
levels interacting with Aedes triseriatus feeding habits; mosquito larvae as top
predator, protozoa as prey of mosquitoes and predator of bacteria, and
heterotrophic bacteria as transformers of detritus and as prey of protozoans and
mosquitoes. Food web theory suggests that a trophic cascade imposed by
feeding on lower trophic levels should have an alternating effect, where
protozoan density would be reduced, predation pressure on bacteria would be
lessened, and bacterial density would increase. Food web theory alternatively
suggests that both top-down effects of predation, and bottom-up effects of
nutrient inputs, will have effects on the trophic levels as well, and that the effects
should diminish with higher order trophic level. Four experiments, two in
laboratory microcosms and two in treeholes were designed to test these
predictions. Results Showed that the omnivorous feeding habits of the larval
mosquitoes dampened any cascading influence of this keystone predator.
Organic nutrient inputs had strong effects on bacterial and protozoan densities,

but inorganic nutrients did not.

41

Introduction

The interactions of top-down (predation) and bottom-up (nutrient) effects have
been closely examined in a variety of ecosystems in recent years. These studies
have fueled a debate regarding whether the abundance of organisms in a given
trophic level is more likely controlled by predation or by resource availability
(Hunter and Price 1992, Menge 1992, Power 1992, Strong 1992, Hairston and
Hairston 1993, Pace and Cole 1994). In aquatic ecosystems, studies support the
hypothesis that bottom-up forces (i.e., inputs of nutrients into the most basal
trophic level) increased productivity at all trophic levels (Abrams 1994, Mills &
Shiavone 1982, Mittelbach et al. 1988, Leibold 1989) while other studies have
shown bottom-up factors to predominate over the role of predators as regulatory
factors of abundance or biomass (Persson et al. 1988, 1992). Contrasting
research has indicated that predatory influences masked or decreased nutrient
input effects thereby structuring the community (Leibold and Wilbur 1992,
Oksanan 1988, 1991, Hairston and Hairston 1993). And finally, studies by
Carpenter et al. (1991) showed that bottom-up and top-down forces act jointly
and equally in their lake systems. The common determination by many
ecologists is that bottom-up and top-down forces often operate in concert (Hunter
and Price 1992, Power 1992, Rosemond et al. 1993, Balciunas and Lawler
1995). How these forces interact is a major question facing researchers. The

tree hole ecosystem inhabited by Aedes triseriatus, the eastern treehole

42

mosquito in eastern North America , is amenable to imitation and manipulation in
field and laboratory settings, and is an ideal ecosystem to study these processes.
The natural habitat of A. trisen'atus is water-filled treeholes, a type of
phytotelmata (Frank and Lounibos, 1983) consisting predominantly of rainwater
accumulating in basins formed by living roots of deciduous trees The container-
breeding mosquito larvae are found in pans or rot holes of deciduous trees in
eastern North America (Jenkins & Carpenter 1946, Mitchell & Rockett 1981, and
Bradshaw & Holzapfel 1985). Both organic and inorganic nutrients enter this
ecosystem naturally from external sources. Autumn Shed leaves can enter
treeholes to provide a source of particulate organic material; in fact prior studies
have suggested that leaf detritus may be the major contributor of organic carbon
for the growth of treehole invertebrate fauna, particularly mosquito larvae (Fish &
Carpenter 1982, Carpenter 1983, Kitching 1983, Walker et al. 1997). Throughfall
moving down the bark of these trees, referred to as stemflow (Eaton et al. 1973),
carries with it inorganic nutrients into the treeholes. Heavy rainfalls are episodic
and are capable of causing a disturbance to the ecosystem resulting in increases
in nitrate and sulfate levels while concurrently diluting ammonium and phosphate
in the system (Walker et al. 1991). Because treeholes are small, are discrete,
contain a tractable community of organisms, and can be manipulated and
simulated, they provide an ideal experimental Situation for examining biotic
interactions and processes within an ecosystem. Aedes triseriatus larvae can be
viewed as a keystone predator (Paine 1969). upon microorganisms in this

system.

43

The studies that follow were designed to examine trophic interactions using
both microcosm and field studies to explore how the abundance of individuals in
different trophic levels are affected by resources and by predation. Specifically, it
manipulated the top level predator, Aedes triseriatus larvae, and levels of both
organic and inorganic nutrient input in order to determine their effects on bacteria
and protozoa. Our findings Show that nutrient resource availability interacts with
predation pressure in this particular ecosystem. In fact, predation effects may be

diminished visibly in the presence of strong nutrient input.

Materials and Methods

Mosquitoes

Larvae of the mosquito Aedes trisen’atus (Say) occur in pans (tree holes with
a complete bark lining) and rot holes (tree holes formed at a wound penetrating
the bark) in decidous trees of eastern North America (Jenkins and Carpenter
1946, Mitchell and Rockett 1981, Bradshaw and Holzapfel 1985). An
understanding of the basic biology of this mosquito is important medically due to
its ability to vector the La Crosse encephalitis virus (Turell and LeDuc 1983).
Larvae begin hatching in northern treeholes in March and April and grow through
four larval instars prior to pupation. Adults first emerge in late spring or early
summer, mate, and females blood-feed and then lay eggs on the bark along the
water line of treeholes. There are 1-2 generations per year in northern climates.

If the eggs are flooded by rising water levels, the first-instar larvae may hatch the

same season; if not, the eggs enter diapause beginning in mid-August and do not

hatch until the following year (Shroyer and Craig 1980).
Microcosm Preparation

Microcosms were made of PVC (polyvinylchloride) pipe with and inner
diameter of 7.6 cm fitted with a fiberglass disc on the bottom end. Each
microcosm was filled with 600 ml of sterile water (capacity, 700 ml). Senescent
beech leaves [American beech (Fagus grandifolia Ehrh.)] served as a source of
organic nutrient. Leaves were dried 48 hours at 40°C, their petioles removed,
leaf packs were weighed, and then added to the microcosms. Fifty four
microcosms were assembled in the following treatments: 18 with no beech
leaves, 18 with one 9 of leaves and 18 with 3 g of leaves. A mixture of natural
tree hole contents including water, leaves and sediment was collected, combined
in a blender and added to each of the microcosms in 10 ml aliquots. An
incubation period of one week allowed establishment of the microbial community

within the microcosms from this inoculation.

Microcosm Treatments
The effects of predation on the microbial community were studied by either
adding or removing fourth instar larvae. To test the effects of removing a
keystone predator, six microcosms of each leaf ration (0, 1 or 3 g) initially
contained fifty fourth instar A. triseriatus larvae. Following the one week

incubation period and a time zero sampling, these larvae were removed. To test

45

the effects of adding a predator, fifty fourth instar larvae were added to six
microcosms of each leaf ration following the time zero sampling. Due to the
varying leaf rations, this experiment also tested effects of organic nutrient input
simultaneous with the predator treatments.

In order to study solely the influence of organic and inorganic nutrients on the
microbial community, an experiment was conducted where no larvae were used.
Organic nutrients were the beech leaves added to microcosms as described
above. Inorganic nutrients were supplemented as a cocktail containing both
nitrate and sulfate in proportions similar to those found in naturally occurring
stemflow (Walker et al. 1991). Potassium nitrate and potassium sulfate were
added at two different levels, 250 IIM and 300 NM respectively for a low level
addition and 2.5 M and 3 M respectively for a high level addition. Inorganic
additions were made to six microcosms of each leaf ration twice during the
experiment.

Tree Hole Experiments

Field experiments were also conducted in treeholes in mature American
beech trees (Fagus grandifolia) located in Tourney wood lot on the campus of
Michigan State University (East Lansing, Michigan). Predator removal
experiments were conducted in two different years (1995 and 1997), during the
spring and summer, to study predation effects on community densities. Two
different removal methods were utilized: (1) removal of predators (the mosquito

eggs) with a boiling water treatment, and (2) by removal of larvae through

46

selective additions of an asporogenic, liquid formulation of the bacterial-based
mosquito larvicide Vectobac 12AS (Abbott Laboratories, Chicago, IL).

In January 1995, prior to larval hatch, water was removed from each of twenty
seven treeholes and measured to determine their volumetric capacity. The
empty treeholes were subsequently flooded to capacity with boiling water to kill
diapausing eggs of A. triseriatus mosquitoes. Following this treatment, the
original water that had been removed was returned to the treehole pans, along
with detritus and other materials. On April 12 and again on June 9, first instar A.
triseriatus larvae were restocked into twenty one of the prepared treeholes at a
concentration of 1 larva per 5 ml of treehole volume. The remaining six prepared
treeholes were left void of mosquito larvae. All treeholes involved in the study
were enclosed with mesh screen fitted with a plastic neck and cap for sampling
purposes.

During the first field experiment, the effects of basal nutrient supplementation
on the bacterial community were studied with additions of colloidal suspensions
of mixed lipids or proteins. The lipid mixture was prepared with Cholesterol
(Dadd and Kleinjan, 1976) and purified cod liver Oil (a source of polyunsaturated
fatty acids, purified with multiple Bligh and Dyer extractions). Eight restocked
tree holes received additions of this lipid suspension to a final concentration of 10
ppm cholesterol and 10 ppm oil extract. The protein mixture, prepared by
dissolving casein in water by elevating to pH 12 and then precipitated by lowering
to pH 6 was added to final concentration of 50 ppm into five tree holes. AS a

negative control, seven tree hole sites received a corresponding volume of

47

deionized water. Nutrient additions were made on May 18 and 29, June 13, and
July 10 and 20, 1995.

Treeholes in the same wood lots were utilized for the second experiment. In
this series of experiments larvae were removed with exposure to Vectobac 12AS.
A total of twenty-five treeholes were screened off and half were treated with the
larvicide on May 27, 1997. Inspection of the treeholes indicated that larvae died
as a consequence of this treatment. Sampling of treeholes began on June 6 and
water column samples were collected from all treeholes each week for four

weeks. Samples were preserved and processed as described below.

Microbial Enumeration

Samples (2 ml) from the water column of microcosms or treeholes were taken
aseptically using sterile pipettes, and preserved in clean glass tubes by adding 2
ml of cold 8% paraformaldehyde for a final concentration of 4%. All water
column samples were stored at 4°C until enumeration. Direct microbial counts
were conducted using the DNA binding fluorochrome, DAPI, and a slight
modification of the procedures of Hobbie et. al., (1977) and Porter 8. Feig (1980).
DAPI, 4'6-diamidino-2-phenylindole, is a fluorochromatic stain which fluoresces
blue when bound to DNA and exposed to light at 365 nm (Wittekind, 1972). To
determine bacterial densities, 250 pl of water samples were mixed with 75 pl of
DAPI (400 ug/ml) and incubated for 20 minutes in reduced light conditions at 4
°C. The samples were then filtered unto 0.22 pm, black Nuclepore

polycarbonate filters using a hand-pumped vacuum and a 13 mm (internal

48

diameter) glass chimney and filtering apparatus. Protozoan densities were
determined using 1 ml of water sample mixed with 100 pl of DAPI (400 mg/ml)
filtered unto 0.4 pm Nuclepore polycarbonate filters. The Slides were stored in
the dark at 4°C until they could be enumerated. Visualization and enumeration
was done with epiflourescence microscopy using a Jenalumar microscope model

A/D. Counts were converted to densities using a standard formula.

Statistical analysis
Direct count data of bacterial and protozoan densities were compiled into
databases using Microsoft Excel. The data were transformed with the common
logarithmic transformation Iog1o (x + 1). Data were then subjected to repeated-
measures analysis of variance using the PROC GLM procedure of SAS (1985)

and following guidelines presented in Von Ende (1993).

Results

Microcosm experiments
Variation in organic nutrient addition to microcosms resulted in a highly
significant effect on both bacterial and protozoan densities, under conditions
where mosquito larvae were completely absent (Table 2.1). Treatments with 1 or
3 g Of leaf material had higher densities of protozoans and bacteria than did
treatments without leaf material (Figure 2.1). In contrast, there was no effect of

inorganic nutrient additions on either bacterial or protozoan densities,

49

Table 2.1. Summary of ANOVAS testing for effects of organic and
inorganic nutrients on microbial population densities.

 

 

 

Error F statistic

Mean Organic Inorganic Organic x

Response variable square DF Nutrients Nutrients Inorganic
Bacterial densities 0.37 2 27.88*** 0.10 1.55
Over time 0.04 9 3.12““ 0.47 0.81
Protozoan densities 0.96 2 98.44*** 1.27 1.67
Over time 0.57 9 1.06 0.74 0.57

Note: *P < 0.05, **P < 0.01, ***P < 0.001

Table 2.2. Summary of ANOVAS testing for effects of organic nutrients
and predation on microbial population densities.

 

 

Error F statistic
Mean Organic Organic x
Regonse variable square DF Nutrients Predation Predation
Bacterial densities 0.16 2 92.65““ 1 .28 270*
Over time 0.04 8 1343*“ 2.22* 0.96
Protozoan densities 0.82 2 46.14*** 6.68“ 7.57***
Over time 0.62 8 4.29*** 1.56 1.31

 

Note: *P < 0.05, **P < 0.01 , ***P < 0.001

50

+3 9 leaves
-9 -1 9 leaves
+0 9 leaves

3.5

I

I
I
I
I
I

 

U

Protozoan Densities (log 10)
... 1‘;

 

 

 

 

Bacterial Densities (log 10)

 

 

8.4 ~
6.2 M
6 T 1 I I 1
0 50 100 1 50 200 250

Time (hours)
Figure 2.1 Bacterial and protozoan responses to organic nutrient

input. Density values are represented as logIo values averaged
over microcosms within each treatment group.

51

although there was a trend toward increased bacterial numbers in response to
inorganic additions when no organic material was present (Figure 2.2).

Addition and removal of the A. triseriatus larvae in the microcosms resulted in
differential responses of bacterial and protozoan densities. Predation had a
highly significant effect on protozoan densities. Larval removal was followed by
an increase in protozoan density and larval addition was followed by a decrease
in protozoan density (Table 2.2, Figure 2.3). In contrast, there was no significant
influence of larval addition or removal on bacterial density (Table 2.2, Figure 2.3).
The varied levels of senescent beech leaves provisioned into microcosms
Interacted significantly with the predation treatments on protozoan and bacterial
densities (Table 2.2). In order to examine this result further, the data for bacterial
and protozoan densities in the absence of organic nutrients (i.e., 0 g of beech
leaf litter per microcosm) were separated from the other data, and analyzed
using repeated measures analysis of variance. There was a Significant effect of
predation on bacterial densities (F = 4.06, df = 2,11, P < 0.05) as well as on
protozoan densities (F = 8.75, df = 2,11, P < 0.01) (Figure 2.4). In the absence
of nutrient input, the densities of both of these groups were reduced by the
addition of predators. The densities of protozoans and bacteria tended to
increase immediately following physical manipulation of the microcosms,
including the control microcosms, suggesting that movement and mixing
released microorganisms associated with detritus or other substrates into the

water column.

52

7.1 -

 

 

+no inorganids
- O -lowinorganics
’§_ 6'9 ‘ +high inorganics
O)
2
V
In
.2 6.7 -
'2
w ‘ ‘. - I I - - I - - I -
a O "
— 6.5 '
.2 .
L- , '
3 I I.
it . ' ‘. ,
m 6.3 ' .
6.1 I I T I I fl
0 50 100 150 200 250

Time (hours)

Figure 2.2 Response of bacterial densities to inorganic nutrient input in
the absence of organic material.

53

Protozoan Densi ies (log 10)

2.5

.N
s

N
1

1.75

 

. """"""" O. _ . g
I ‘~... '.. -’ I
--
—Cl—control
+ predator added

- -O - predator remand

 

 

I

15

Z; .. .'. 7'.
TIme (hours)

Figure 2.3 Population density of protozoa averaged across three
levels of organic nutrient input.

54

-D-control
+predator added
-0 -predator removed

9"
01

0)

£09 10)

 

 

 

N

Protozoan Densi ies

 

 

5.75 -

 

ies ('09 10)
‘.
\
/

9'
N
01

 

 

Bacterial Densit

 

4.75 . t u t

 

o 15 30 45 60 75
Time (hours)

Figure 2.4 Bacterial and protozoan population density response to
predator addition and removal in the absence of any organic
material.

55

Tree hole experiments

In the first treehole experiment, the presence or absence of A. triseriatus
larvae significantly affected bacterial densities. In treeholes treated with boiling
water and later restocked with larvae, there was a trend for a reduction in
bacterial densities compared to treeholes in which there were no larvae (F =
20.10, df = 1, P < 0.01) (Figure 2.5). Although in both treatment groups, those
with larvae present and with larvae absent, bacterial densities increased over
time as the experiment proceeded, the trend for those treeholes with larvae
present was a steeper line and appeared to change in concert with the timing of
emergence of adult mosquitoes (Figure 2.6).

In the second field experiment, where larvae were removed with Vectobac
12AS, results were similar to the first treehole experiment. Bacterial densities
were significantly lower in treeholes with larvae, and conversely were higher in
treeholes from which larvae had been eliminated (Figure 2.7; repeated measures

ANOVA, F= 6.03, df=1, P<0.05).

Discussion
The results of the microcosm and tree hole experiments reported here
indicated that A. triseriatus larvae function as a "keystone“ predator or “top level
predator” (sensu Paine 1969) in the tree hole ecosystem. Removal or elimination
of larvae resulted in statistically significant Changes in densities of protozoans
and bacteria in the water column. Results were not entirely consistent among

experiments, because in microcosms bacteria responded less dramatically and

56

7.5 -

 

 

 

'0- mosquitoes absent
+ mosqtuitoes present
A 7.25 5
5'3
.2
E 7‘
E 6.75 -
D
E
g; 6.5 -
2'3
53
6.25 a
6 l l l T 1 l l l I
1 2 3 4 5 6 7 8 9 10
Time (weeks)

Figure 2.5 Bacterial population densities comparing treeholes
either with mosquito larvae present or absent. Those with no
mosquito larvae had larvae removed by exposure to boiling water.
Those with larvae present were treated with boiling water and then
restocked with first instar Aedes triseriatus larvae.

57

Bacterial Densities

 

+bacterial response
—O—adult emergence ... 4

- 160
-140
- 120
- 100
I so
- so
- 4o
- 20

.3‘
N
r
l
I

l

r4
5.8-r—O-I—O—I—O’I 2%
12345678910

Time (weeks)

 

 

.1—
‘-
Cli-
-—
O

Figure 2.6 Relationship of adult emergence and bacterial
population response. Solid line represents bacterial population
densities over time and the dashed line represents the cumulative
emergence of mosquitoes as adults. This line corresponds to
removal of the larval predator through its natural life cycle. As this
keystone predator exits the natural ecosystem the bacterial
population responds by increasing in numbers.

58

total adults emerged

7.4 !

 

  

 

 

-l-Mosquito larvae present

7.3 - ....
’5‘: 7 2 . +Mosquito larvae absent
a: .
g 7.1 -
.3 72
’5 6.9 -
g 6 8
D .
I! 6.7 - F
L
,9, 6.6 -
g 6 5
m .

6.4 -

6.3 . . .

 

1 2 3
Time (weeks)

Figure 2.7 Bacterial population densities comparing treeholes
either with mosquito larvae present or absent in the second
treehole experiment, where larval mosquitoes were removed by
addition of the bacterial-based liquid larvicide, Vectobac 12AS.

59

not in a statistically significant manner, to predator manipulations compared to
the treehole experiments. The responses of protozoan densities were much
more pronounced. Although the removal of this top level predator from the
system results in drastic alterations of the remaining trophic levels, the
relationship between the trophic levels of the treehole ecosystem do not follow
the prescribed patterns of food web interactions. Previous studies involving three
or more interacting trophic levels have provided evidence for strong top-down
regulation involving microbes, microbivorous nematodes, and predatory
arthropods (Santos et al. 1981, Parker et al. 1984), but no trophic cascade could
be observed for productivity or biomass in a soil food web (Mikola and Setala,
1998). The same appears to be true for the treehole ecosystem. According to
the trophic cascade theory of Carpenter et al. (1985), a reduction in the
protozoan population density Should be observed following predation by A.
triseriatus larvae. This, in turn, should provide an increase in bacterial population
densities by relieving their predation pressure. This specific interaction was
observed in the pitcher plant ecosystem studied by Cochran-Stafira and von
Ende (1998). There was an increase in bacterial densities in response to grazing
by Wyeomyia smithii larvae. They proposed that the discrepancies between the
pitcher plant studies and treehole studies could be caused by differences in larval
densities found in each ecosystem.

However, Aedes larvae are omnivorous due to their indiscriminate filter
feeding making the responses of lower trophic levels more complex. Omnivores

feed on several trophic levels making the limiting processes in neighboring levels

60

less clear (Leibold 1989, Hunter and Price 1992, Abrams 1993, Osenberg and
Mittelbach 1996, Persson et al. 1996). In addition to omnivory, other factors
have been proposed for the uncoupling of trophic cascades at the microbial level.
Studies have suggested that heterogeneity (Hunter and Price 1992) in prey
edibility may increase the number of inedible organisms at intermediate trophic
levels (Leibold 1989, Abrams 1993, Mikola and Setala 1998). Other studies
(Balciunas and Lawler1995, Hairston and Hairston 1993) suggest that resources
can affect prey vulnerability and thereby limit trophic cascades.

McQueen et al. (1986) proposed the idea of top-down, bottom-up regulation
in plant-based freshwater systems. The theory predicts that top-down forces act
strongest at the top of the food web and weaken as they progress toward lower
levels; in addition to this it also predicts the reverse for forces acting at the
bottom levels of the food web. In other words, nutrient input or bottom-up forces
are strongest acting on the lowest levels of the food web and weaken as they
progress to higher levels. This study clearly showed regulation of upper level
trophic species, protozoa, by predation and regulation of lowest level trophic
species, bacteria, by organic nutrient input. Within a 72 hour time period the
protozoan population was decreased one full log unit by predation by larval
mosquitoes, the majority of this reduction in numbers occurred 48 hours after the
larvae were added to the microcosms. As the protozoan population was
decreasing in numbers the bacterial population was increasing along the same
time frame. The actual numbers of bacteria do not show as large a change in

number as protozoa, but this is most likely due to the turn over rate of bacteria

61

vs. the predation rate of larvae. When the predator is removed from the system
the bacterial density plummets, but apparently not in response to increases in
protozoan densities as is predicted by the trophic cascade model. In relationship
to untreated microcosms neither protozoan populations nor bacterial populations
appear to have any response to removal Of predation pressure within a 72 hour
period. Perhaps the protozoan population requires longer than three days to
recover to a point that it is capable of making an impact on the bacterial
population. The bacterial population in the meantime could be mediated by
factors beyond the scope of this study such as interaction with virus to maintain a
plateau population.

Organic nutrient input appears to be the main driving force influencing the
structure of these small, isolated ecosystems. Hunter and Price (1992) point out
the obvious, which Is too often overlooked, when they observe that removal of
higher trophic levels leaves lower levels present, while removal of primary
producers leaves no system at all. This clearly indicates that nutrient input into
any system ultimately drives the community structure. The effects of predation
are greatly reduced in the presence of high levels of organic nutrient input into
this particular ecosystem. Inorganic nutrients do not alter treehole community
structure indicating that they are not the limiting resources for bottom-up
influences.

Although these laboratory experiments do not indicate that a trophic cascade
takes place in the treehole ecosystem there are other considerations which may

be influencing this result. For example, bacterial turnover time is much faster

62

than that for protozoa so the limited time measured here may not be fully
indicative of the true relationship between these two trophic levels. In addition,
these measurements of bacterial and protozoan densities were made only from
the water column of the microcosms, not directly from leaf surfaces. Many
microbes adhere to this substrate and larval grazing takes place at leaf surfaces
as well as in the water column. The increase in number of microorganisms in all
microcosms following physical manipulation show that the total population
density within the ecosystem is not limited to those in the water column. It is
possible that critical interactions between different trophic levels occur exactly at
the point of interaction of substrate, microorganisms and grazing. Due to the
high impact of nutrient regulation and the apparent relationship between treehole
ecosystems and other microbial systems (Mikola and Setala 1998, McQueen and
Post 1988) it appears that regulation of specific food webs is more accurately
explained by top-down; bottom-up theory as opposed to trophic cascades.
However, we cannot rule out the possibility that changes in the species
comprising the bacterial trophic level influenced the regulatory factors acting on
this ecosystem as they have in others (Hunter and Price 1992, Strong 1992).
These results imply a rebounding of bacterial population numbers in response to

decreased numbers of this top-level predator for the treehole ecosystem.

63

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67

CHAPTER 3
Age and size at maturity In response to variable food and temperature
regimes for larvae of the mosquito, Aedes triseriatus: Effects of differential

mortality

Abstract

The development of larvae of the mosquito Aedes triseriatus, consisting of
both gain of mass to the time of metamorphosis and the duration of this period of
time, is influenced greatly by external environmental factors, in particular food
availability and temperature. Although the interactions of these factors in
affecting development has been studied previously in other invertebrate
(including mosquito) systems, the experiments reported here directly tested their
effects and any interactions between them as well as the influence of
experiment-wise mortality on key growth parameters (namely, development time
to and mass at pupation). Both variations in temperature and food availability
strongly affected growth responses in a series of experiments. In a cohort
experiment, temperature and food availability did not Interact Significantly. This
unexpected result may have been a consequence of differential mortality In
cohorts held at low and high temperatures, as cumulative mortality was
substantially greater at lower temperatures. Alterations in population densities
due to both decreased temperatures and decreased food rations likely
restructured the population such that resources per individual increased, allowing

for increased mass at lower temperatures. Parameter estimates from fits of

68

development time and mass at pupation to a pupation window model showed
differences depending upon whether larvae were reared as cohorts or as
individuals. In the former case, the estimates showed a significantly higher body
mass and extended development time In larvae held at low temperatures. In the
latter case, the estimates showed an extended development time but no change
in body mass. These results suggest that differential mortality during cohort
development indeed influences the growth outcomes of individual larvae. The
general observation that individual mosquitoes, and other ectotherrns, develop
through a long development time to a larger body size at low temperatures
compared to high temperatures, may be a consequence of changing food ration
as larval density decreases and food becomes more readily available to
survivors. This observation challenges the long-standing dogma that
invertebrates experiencing low temperatures are larger at maturity compared to
those reared at higher temperatures, as some direct physiological consequence

of the temperature regime.

Introduction
Variations In food supply and temperature affect development time to maturity
(age) and mass at metamorphosis (size at maturity) in contrary ways in
ectothermic animals (Sibly and Atkinson 1994). With regard to temperature, age
and size at maturity respond Similarly, i.e., they both decrease with increasing
temperature, thus the developmental reaction norm (sensu Steams and Koella

1986, Schlichting and Piggliuci 1998) for size-to-age at maturity has a positive

69

SIOpe. With regard to food supply, by contrast, size and age at maturity respond
in opposite ways. Development time decreases whereas size increases with
increasing availability of food, and the reaction norm has a negative Slope.
These contrary responses may result from the ways that metabolic rate and food
acquisition rate respond differently to the same variations in food supply and
temperature, thus the latter two factors ought to interact significantly in affecting
the reaction norm (Perrin 1995). These observations have stimulated a debate
about the universality of these patterns among ectotherrns, the physiological and
evolutionary bases for these relationships, and whether there exists reciprocal
selection between development time and body Size at maturity (Berrigan and
Chamov 1994, Perrin 1995, Atkinson 1994).

Patterns of mortality during growth may also vary as temperature and food
supply interact, and thus may affect the relationship between development time
and body mass (Sibly and Atkinson 1994, Perrin 1995). For example,
development times are extended at lower temperatures, and body sizes are
predicted to be larger at lower temperatures, but mortality might be greater at
lower temperatures than at higher ones, thus increasing the per capita food
supply of survivors and therefore their growth rate. Interestingly, Sibly and
Atkinson (1994) proposed the opposite model —-that mortality would be higher at
higher temperatures—to explain patterns of body size variation in ectothenns
using a optimality modeling approach within the context of a tradeoff between
development time and optimal body size (and therefore, fecundity, inasmuch as

body size and fecundity are typically positively correlated). Specifically, they

70

noted: “discounted juvenile mortality correlates positively with rearing
temperature” and that “If discounted juvenile mortality rate does not increase at
higher temperatures, some of [our] predictions are difficult to reconcile with the
observed effects of rearing temperature on adult body size because . . . most
ectotherms respond to higher rearing temperature by maturing at a smaller size.”
Although there has been no experimental test of the hypothesis that body size
could be mediated by variation in mortality during development, it could provide a
mechanistic explanation for the patterns observed In laboratory and field
experiments (Perrin 1995).

The food supply of many aquatic macroinvertebrates in freshwater
ecosystems is allochthonous organic detritus, particularly shed, senescent leaves
(Anderson and Sedell 1979, Cummins and Klug 1979). Some of these
Invertebrates shred and consume leaf detritus directly for food (e.g., crane fly
larvae, Lawson et al. 1984), while others browse the microorganisms comprising
the biofilm on the surface Of the detritus and thus utilize the detritus resource
Indirectly (e.g., mosquito larvae, Merritt et al. 1992). For invertebrates with either
feeding mode, their growth and metamorphosis depend upon the quantity and
quality of leaf detritus available to them and the extent of microbial conditioning
of the detritus (Berrie 1976, Ward and Cummins 1979, Fish and Carpenter 1982,
Lawson et al. 1984, Slansky and Scriber 1985, Walker et al. 1997). Larvae of the
treehole mosquito Aedes trisen'atus (Say) utilize Indirectly the leaf detritus that
falls into treeholes (Fish and Carpenter 1982, Carpenter 1983, Walker and Merritt

1988, Lounibos et al. 1993, Leonard and Juliano 1995, Walker et al. 1997).

71

Craig (1983) reviewed the biology of this mosquito. Larval growth of A.
triseriatus is largely dependent upon mass or ration of leaf detritus available per
individual larva (Carpenter 1983, Leonard and Juliano 1995), although variation
in quality of leaves also affects larval growth (Fish and Carpenter 1982, Lounibos
et al. 1993, Walker et al. 1997, Strand and Merritt 1999). A microbial lawn
develops on the leaf surfaces, which the larvae browse intensely (Fish and
Carpenter 1982, Walker and Merritt 1991, Kaufman et al. 1999). The larvae also
actively feed in the water column (Walker and Merritt 1991) and the bacterial and
protozoan populations In the water column respond quantitatively and
qualitatively to this feeding pressure (Walker et al. 1991, Kaufman et al. 1999,
Merritt et al. in preparation). Thus, microorganisms associated with leaf surfaces
and the water column serve as larval food.

The growth of A. triseriatus subsisting on decomposing senescent leaves is
described well by a curvilinear relationship between development time to and
mass at pupation called the “pupation window model’ (Gilpin and McClelland
1979, Carpenter 1984, Walker et al. 1997). The model predicts that larvae will
pupate at or beyond some critical, minimum mass after having passed through a
minimum developmental period. This concept was first proposed as a
generalizable growth model for insects by Nijhout (1975). The pupation model
describes an inverse, nonlinear relationship between development time and
mass at pupation. Larvae develop faster and pupate at a greater mass above
the critical mass when food Is in ready supply, but develop Slower and pupate at

a lower mass (or do not pupate at all, but rather discontinue growth, lose mass,

72

and starve to death) when food is in short supply. The mathematical expression
of growth is derived from fitting the growth trajectories of individual insects’
development time and body mass at maturity, or mean development time and
body mass in the case of cohorts, in mass and time space according to the
following equation:

Wt = W0 exp{(ak/ m - k)(Bo/No)[exp((m - k)t) - 1]}

as described by Gilpin and McClelland (1979), Dye (1982), and Carpenter

(1984), where Wt = the mass of an individual at day t, Wo= the mass of a newly-

hatched larva, a= the efficiency Of conversion of leaf mass into mosquito tissue, k

= decomposition rate of leaves, m = larval mortality rate, Bo = initial mass of leaf

detritus, and N0 = initial number Of mosquito larvae. The endpoint Of a

successful development to adult emergence is then represented by coordinates
(x,y) corresponding to development time and mass. These data are fitted to the

following hyperbolic equation from Carpenter (1984):

h3 = (time — h1)(mass - h2)

where h3 represents the sharpness Of the bend in the hyperbole, m is a
development time minimum, h2 is a body mass minimum, and time and mass are
parameters estimated from experimental data.

Temperature affects rate of growth of larval mosquitoes and body size at
maturity, as it does all ectotherms (Bertalanffy 1960, Clements 1992, Atkinson
1994). Within thermal limits of tolerance, the rate at which mosquito larvae
develop increases with temperature (Bar-Zeev 1958, Nayar 1968), whereas the

resulting size of the pupa or emergent adult varies inversely with temperature

73

(van den Heuvel 1963, Nayar 1969, Hien 1975). Chambers and Klowden (1990)
observed that larvae of the mosquito Aedes aegypti (L.) pupated at a lower mass
when larval rearing temperature was increased, and that mass at pupation
correlated positively with accumulation of nutritional reserves in the last larval
Instar, just prior to pupation, as food supply (a laboratory diet) was Increased.
Thus, temperature influences not only rate of growth, but also the efficiency with
which nutrients are acquired and assimilated.

In the present study, experiments on the growth of an indirect detritivore,
larvae of the mosquito Aedes trisen'atus, were conducted to measure the
interactive effects of variable food availability and temperature on age and size at
maturity. Because mortality of larvae may vary with these factors as well,
experiments were conducted to evaluate the effects of mortality among cohorts
of larvae on the responses of development time and mass The pupation window
model was used as a tool to estimate body mass at and development time to

maturity to compare responses under different experimental conditions.

Materials and Methods

Four laboratory microcosm experiments were conducted in order to examine
the effects of temperature, food resource availability and density on larval A.
triseriatus growth, development and mortality (or conversely, survival to the adult
stage). In all experiments, senescent beech leaves [American beech (Fagus
grandifolia Ehrh.)] served as the source of organic nutrients (cf. Walker et al.

1997). The leaves were dried for 48 hours at 40°C, their petioles were removed

74

to eliminate refractile material, leaf pieces were weighed, and then were added to
the microcosms as individual pieces or in packs. The first experiment was
designed to examine the possibility of interactive effects of temperature and food
availability on larval mosquito growth and development, and to measure mortality
of larval cohorts at different temperatures. Microcosms for this experiment were
plastic dishes, 15.5 cm in diameter x 6.5 cm deep with friction-fitting lids. Each
microcosm was filled with 400 ml of stemflow collected from an American beech
tree in nearby woods as described by Walker et. al. (1991). Twenty newly
hatched first instar A. triseriatus larvae were then added. Leaf packs, prepared
as described previously, were added in amounts of 0.5, 1.0 or 2.0 9, creating leaf
rations of 25, 50 and 100 mg/Iarva. The microcosms were then arranged
randomly with respect to treatment in constant-temperature incubators at 15, 20
or 25°C, resulting in a 3 x 3 factorial design. Each treatment combination was
replicated with six microcosms. It was not possible to replicate at the level of
incubator owing to limitations in availability of equipment, however, incubators
were of the same make and any differences in results were unlikely to have been
affected by them. The microcosms were examined daily and newly emerged,
adult mosquitoes were collected and killed by freezing. Following completion of
the experiment, adults were dried for 48 hours at 40°C and weighed to the
nearest 0.001 mg on a Cahn electrobalance. Male and female emergence (total
number per microcosm), mean development time (days from the beginning of the
experiment until emergence) and mean body mass were calculated. A two-way

analysis of variance (ANOVA) was used to test for significant treatment effects

75

on the responses. Data of mean development time and mean female mass were
fitted to the pupation window model using least squares, nonlinear regression
with the NLIN procedure of SAS (1985), following the methods described in
Walker et al. (1997). Initial estimates used as input for parameters h1 and h;
were derived from plots of development time and mass, whereas initial estimates
for ha ranged between 0.1 and 0.5.

In the second laboratory experiment, a constant temperature was maintained,
but food level and larval density were varied. Thus, this experiment was
designed to examine whether larval density within an experimental cohort per se
will affect survivorship of larvae. Microcosms for this study consisted of
polyvinylchloride pipe fitted with a fiberglass disc on the bottom (inner diameter,
7.6 cm; capacity of 700 ml). Microcosms were filled with 600 ml of sterile water
and then inoculated with 1 ml of a blended slurry created from natural treehole
contents (leaves, water and sediments) collected locally. In addition, leaf packs
were prepared as previously described and distributed into the microcosms in 1.0
and 3.0 g amounts. The microcosms were covered with nylon screen, fitted with
a foam plug, and allowed to incubate for one week prior to the start of the
experiment. The experiment commenced after this time, when either 20 or 90
newly hatched, first instar A. triseriatus larvae were added to microcosms. In
addition to varying food level and larval density, this experiment also examined
the effects of disturbance on these closed systems. Previously, disturbance with
stemflow was found to enhance larval survival to the adult stage (Walker et al.

1991). Because larval survival is hypothesized here to be a factor affecting

76

development time and body size outcomes, this kind of disturbance was
simulated experimentally here. It was done by pouring sterile water or stemflow
water through a funnel containing a mesh filter (to remove large particulate
matter), followed by dripping the water through an 18 gauge needle at a rate of
approximately 15 ml/min. A set of microcosms was not subjected to this
treatment, as an experimental control group. The microcosms were disturbed in
this way once per week for the five weeks. The design of this experiment
resulted in two larval densities, three disturbance factors and two food levels for
a 2 x 3 x 2 factorial design. The experiment was replicated four times for each
treatment combination. Newly emerged, adult mosquitoes were collected and
experimental responses were recorded as described previously. Three way
ANOVA was used to test for significant treatment effects on growth responses
and survival.

The third experiment was similar to the first in that it was designed to test for
effects of variable food resources and varied temperature regime on larval A.
triseriatus development. However, this experiment eliminated within-cohort,
larval mortality and any effects of density because larvae were held singly.
Microcosms were glass, liquid scintillation vials. Each vial was filled with 20 ml of
stemflow, and one newly hatched A. triseriatus larva was added. Leaf packs
were formed in the range of 25 to 100 mg, and were added. There were a total
of 120 microcosms. The same three temperature regimes were utilized as in
experiment 1, i.e., 15, 20 and 25 °C. with forty microcosms containing variable

leaf masses at each temperature. Microcosms were monitored daily for

77

emergence of adults, and adults were treated and data responses recorded as in
previous experiments. The response data were analyzed using analysis of
covariance (ANCOVA) where leaf mass was held as the covariate, and
coefficients from linear regression using leaf mass as the independent variable
were estimated to determine the effect of variation of leaf mass among different
temperatures on growth responses. Data of development time and female mass
were fitted to the pupation window model as with experiment 1.

The fourth experiment combined effects of variation in food resource
availability, temperature regime and larval density on larval growth,
metamorphosis, and mortality of A. triseriatus. Microcosms were scintillation
vials provided with 20 ml of collected stemflow as in experiment 3. The three
temperature regimes utilized in previous experiments were used again, i.e., 15,
20 and 25 °C. Larval densities were 1, 5 or 10 larvae per microcosm. Forty
microcosms were used for each of the combinations of temperature and density,
containing a varying amount of leaf mass created by addition of leaf packs
weighing from 25 to 100 mg each resulting in a total of 360 microcosms. Adults
and adult data were collected as described above. For microcosms with 5 or 10
larvae, mean adult male or female mass and mean development time were
calculated and used as the response variables. An ANCOVA with leaf mass as
covariate and density and temperature as fixed effects was used to test for

effects of these treatments on the response variables.

78

Results
Experiment 1: larvae reared at densities of 20/microcosm

In the first experiment, both temperature and food regime affected the
development time, metamorphosis, and survival of male and female A. triseriatus
larvae. Overall, male and female development times were longest at the lowest
temperature and the lowest food level, and both significantly decreased with
increasing temperature and food level (F = 155.12, df = 2, P < .001 and F =
165.10, df = 2, P < .001 respectively) (Figure 3.1). Body mass was significantly
influenced by food level for both males and females (F = 63.67, df = 2, P < .001
and F = 26.23, df = 2, P < .001), and temperature significantly affected body
mass of females (F = 13.91, df = 2, P < .001) and males (F = 3.80, df = 2, P <
.05). As shown in Figure 3.2, male and female body mass increased with
increasing food level but only female mass increased in a definitive pattern as
temperature decreased. The survival rate of both males and females was
significantly and directly related to food level (F = 13.66, df = 2, P < .001 and F =
8.12, df = 2, P < .001) with the lowest survival rate corresponding to the lowest
food level (Figure 3.3). Male survival was not influenced by temperature, but
female survival was significantly affected (F = 13.741, df = 2, P < .001) and was
lowest at the lowest temperature (15 °C). There were no significant interactions
between food level and temperature for any of the growth responses.

Pupation window model fits to response data, constructed as plots of

development time and adult mass, are shown in Figure 3.4. Estimates of

parameters for the model are shown in Table 3.1. For 20 and 25 °C. the data fit

79

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81

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82

the model well and conformed to the prediction that body mass and development
time would be negatively correlated under conditions of variable food availability.
However, at the lowest temperature, there were fewer females produced per
microcosm, and in some microcosms no females emerged. Under these
conditions, the data fit the pupation window model poorly and the parameter
estimates had high variability (Table 3.1). The estimates of body mass (h2) and
development time (h1) parameters showed that the mass at pupation was lowest
at the highest temperature, highest at the lowest temperature, and intermediate

at the intermediate temperature.

Experiment 2: larvae reared at densities of 20 or 90/microcosm
Disturbance had no significant statistical effect on any growth and

development parameters measured for this experiment and replicates were
therefore pooled for further analysis. Summary data are shown in Table 3.2.
Food level significantly affected both male and female development time as well
as female mass (F = 16.68, df = 1, P < .001 and F = 55.15, df = 1, P < .05
respectively). Male mass was not influenced by food level in this experiment.
For females, body mass increased and development time decreased as food
ration increased (F = 41.38, df = 1, P < .001) (Table 3.2). Survival of larvae also
increased with increasing food levels. The effects of density on larval growth
parameters were also examined in this experiment. Densities of 90 larvae per
microcosm with 1 gram of leaf material resulted in a food ration of approximately

11 mg/larva. Under these conditions, few females pupated, and survival was

83

Adult Mass (mg)

0.8 -

 

 

o 15 degrees

[:1 20 degrees
0'7 ' O A 25 degrees
0.6 - A oo.

o
0.5 . o .
33am ' ' "
0.4 ' A CUB D D . O O
o
0.3 - A A“; 80 A D U
A
A A ‘AAgb o
0.2 '
0.1 -
o ' I I U I
0 20 40 60 80 100

Development Time (days)

Figure 3.4 Scatter plot of pupation window data obtained from
larvae reared in populations of twenty.

84

Table 3.1 Estimates of pupation window parameters for results of experiment 1
(larvae reared in populations of twenty), plus upper and lower asymmetric 95%
confidence limits are given in parenthesis.

 

 

Temperature h1 h2 ha,
15 39 (38.0 - 41.9) 0.44 (0.38 — 0.50) 0.25 (-0.02 — 0.70)
20 22 (21.1 — 23.7) 0.35 (0.32 — 0.38) -0.03 (-0.16 - 0.08)
25 19.5 (19.1 - 19.9) 0.31 (0.27 — 0.34) -0.16 [-0.27 - (-0.060)]

 

Table 3.2 Survival, development time and adult mass at low and high leaf
rations. Values are given as the mean 1 SEM (N = 6 per group)

 

20 larvae 90 larvae
1 g leaves 3 g leaves 1g leaves 3 g leaves
% Survival
Total 8.67 + 2.50 14.33 + 3.34 .250 + 0.45 12.67 + 3.60

Development Time
Males 22.55 + 2.67 20.58 +1.39 30.00 + 5.00 21.57 + 3.31

Females 26.95 + 3.44 23.1 + 2.33 0 24.75 + 5.32

Adult Mass
Males .2013 + .056 .406 + .078 .105 + .015 .132 + .037

Females .350 + .129 .611 + .148 0 .205 + .049

85

significantly affected by density (F = 320.51, df = 1, P < .001). The higher density
also significantly reduced female mass (F = 226.91, df = 1, P < .001) and
resulted in a general trend of decreased size and increased development time for

both males and females in response to increased densities (Table 3.2).

Experiment 3: larvae reared individually

This experiment eliminated any effects of density by rearing larvae
individually. Figure 3.5 shows that there were positive correlations between
starting leaf mass and the resulting adult mass of both males and females. For
females, the relationship tended to be linear to 100 mg of leaf material/larva
continues while for males the relationship appear to plateau at about 75 mg. The
regression equations are shown in Table 3.3. Male and female development
times were significantly influenced by temperature (F = 686.65, df = 2, P < .001
and F = 82.83, df = 2, P < .001 respectively) as evidenced by extended
development times with decreasing temperatures. Development time for females
was significantly slowed by decreasing food levels (F = 14.1, df = 1, P < .001)
while male development time was not effected. Adult masses of males and
females were significantly affected by food level (F= 4.3, df = 1, P< .05 and F=
109.1, df = 1, P < .001 respectively) however, male mass was not affected by
temperature and the female mass was significantly affected to (F = 4.30, df = 2,
P < .05) for this experiment. In addition, the greatest mass for females was at
20°C (mean mass = 0.53 mg) and not at the highest (0.46 mg) or lowest (0.48

mg) temperature. A Least Squares multiple comparisons test based upon the

86

0.9 -
0.8 a
0.7 -
0.6 -
0.5 '1

Male Adult Mass (mg)

MALES

A

A.‘

o 15 degrees
El 20 degrees
A 25 degrees

D D
D A ‘ ’D‘E?‘
b D.
o
mung? o A

A

3;.“

Pm

 

 

Female Adult Mass (m )
P P P P P
N u «h 0! O

P
J
I

 

0.02

FEMALES

0.04 0.06 0.08

 

O
O

0.02

I I I I

0.04 0.06 0.08 0-1
lnltal Leaf Mass (9)

Figure 3.5 Scatter plot of data for male and female adult mass
against the starting leaf mass available for development.

87

Tukey-Kramer adjustment showed that the female mean mass at 20 °C was
significantly greater that the mass at 15 °C, but equal to that at 25 °C.
Examination of the pupation window curves for individually reared larvae (Figure
3.6) indicates that in fact decreasing temperature extends development time
without significantly increasing the mass required for pupation. Estimates of

parameters for the model are shown in Table 3.4.

Experiment 4: variable densities

There was a significant effect of temperature on female mass (F = 3.34, df =
2, P < 0.05) but not male mass under varied larval densities. Although survival
was reduced at high densities and low temperatures, the average mass for
female larvae reared individually was highest at the intermediate temperature (20
°C) but for larvae reared in groups of 5 or 10 the average female mass was
highest for the lowest temperature (15 0C). Similar to previous experiments both
male and female development times were influenced by temperature (F = 55.23,
df = 2, P < .001 and F = 55.56, df = 2, P < .001 respectively). Food levels slightly
influenced male development times (F = 4.219, df = 1, P < .05) but not female
development times while adult masses for both males and females were affected
by food levels (F = 46.10, df = 1, P < .001 and F = 26.16, df = 1, P < .001

respectively).

88

Body Mass (mg)

 

o 15 degrees

 

0-9 - [120 degrees
03 . ‘ DD 0 A 25 degrees
3:: 12%

' C] o
0-5 ' ‘: E 0’. o
0.4 - AA DD .'
0.3 - A D . o
0-2 ‘ ‘ A E] D o
0.1 - 6

0 1 u u

0 10 20 30 40

Development Time (days)

Figure 3.6 Scatter plot of pupation window data obtained from
individually reared larvae.

89

Table 3.3 Linear regression equations for relationships between
temperature, leaf ration and adult mass. Y = mosquito mass (mg). X = leaf
mass (mg).

 

 

SEX TEMPERATURE EQUATION

Male 15 Y = 0.106 + 0.004X, r = 0.90

Male 20 Y = 0.217 + 0.003X, r = 0.74

Male 25 Y = 0.182 + 0.003X, r = 0.84
Female 15 Y = 0.020 + 0.007X, r = 0.92
Female 20 Y = 0.085 + 0.008X, r = 0.90
Female 25 Y = -0.029 + 0.008X, r = 0.97

 

Table 3.4 Estimates of pupation window parameters for results of
experiment 3 (larvae reared individually), plus upper and lower
asymmetric 95% confidence limits are given in parenthesis.

 

 

Temperature h1 h2 h3
15 30 (25.6 - 34.9) 0.46 (0.29 - 0.64) -0.11 (-0.72 — 0.49)
20 20 (17.9 — 22.9) 0.44 (0.26 — 0.62) -0.52 {-1.01 — (-0.05)]

25 14 (9.3 — 18.7) 0.53 (0.13 — 1.24) 0.02 (-0.18 — 1.24)

 

90

Discussion

The effects of temperature and food ration level were similar among all
experiments with regard to development time but these trends were not
consistent for body size. Thus, the results reported here did not always support
the existing models for ectotherm development for body size (Sibly and Atkinson
1994, Perrin 1995). Both male and female mass tended to respond positively to
increases in leaf mass, while female (but not male) development time was
generally shortened in response to increases in leaf mass. Male and female
development time generally decreased with increased temperature. Body mass
varied with temperature, but only when larvae were reared in cohorts as in
experiment 1. This finding is consistent with the generalizations of Atkinson
(1994). However, results from experiment 3, when larvae were held individually,
did not support this generalization. Thus, the most important outcome of the
experimental analyses reported here is that the experimental context can affect
the outcomes regarding the mass and development time relationships that were
under study. The effect was likely mediated through differential larval mortality.

In experiment 1, larvae were held in cohorts at initial densities of 20 per
microcosm, provisioned with low, medium, or high food levels, and were held at
one of three constant temperatures. Although the main treatment effects in this
experiment were marked, the ANOVA showed that temperature and food level
did not interact with each other. Significant interaction terms in ANOVA should

occur if there were different responses to development time and mass for each

91

 

combination of food level and temperature in the first experiment. Further,
feeding rate and assimilation rate respond differently to the same changes in
temperature when food supply varies (Bertalanffy 1960, Perrin 1995), thus
growth rate (an outcome of the combination of these two variables) should have
responded differently to interactions of the main treatments. One possible
explanation for this result relates to the differential larval mortality within
treatment combinations during the course of the experiments. Thus any
interactions between main treatments could have been masked by this
uncontrolled covariate. Another possible explanation is that food supply was not
actually constant for larval cohorts during the course of the experiment, because
there would have been differential development of microorganisms on the
surface of leaves as a function of temperature as well. Thus availability and
acquisition of microbial food were also variables, but they were not measured.
The influence of temperature on mass varied with sex of the larvae, and with
experimental conditions including cohort or individual rearing, and density of
larvae in cohorts. Males and females responded differently to changes in
temperature and food. Females tended to show clear experimental responses to
variations in food and temperature, whereas males did not consistently respond.
These results likely have their explanation in sexual polymorphism in
development time and body size phenotypes among Aedes mosquitoes
(Christophers 1960, Clements 1992). Males may have been selected not to grow
to an optimally large body size but rather to grow rapidly and leave habitats early,

before they dry or before some other catastrophic event occurs. Females, on the

92

other hand, may be selected to optimize body size during larval growth in order
to maximize fitness, inasmuch as body size and fecundity are positively
correlated in female mosquitoes (Clements 1992). Thus, it should not be
surprising that male and female larvae would respond differently to combined
effects of variation in food availability and temperature. influenced by
temperature while females are significantly affected. When larvae were reared in
large microcosms where a small number shared a common food resource,
females reared at the lowest temperature (15 °C) attained the greatest mass but
also had the highest level of mortality. in contrast, when larvae are reared
individually, females in the intermediate temperature (20 °C) were at a greater
mass than those reared at the lowest or highest temperatures (15 °C), but this
difference was not extreme. In addition, when larvae were reared individually the
resulting graphs of development time against adult mass (representing the
pupation window model) showed a stunting effect on the development time axis
of the curve (Figure 3.6).

Mortality, in general, tended to be higher at lower temperatures in all
experiments. When density was controlled as a factor influencing larval
development and the food supply or ration per larvae was also controlled, it
altered the larval response to food supply. Larvae reared among cohorts
resulted in a pupation window model exhibiting a negative correlation between
body mass and development time under various conditions of food availability.
Although this relationship between mass and development time was maintained

within each of the three temperatures, decreasing temperature ultimately resulted

93

in extended development time but greater body masses. This result contradicts
the prediction of the current pupation window model which specifically states that
prolonged development time yields larvae that pupate at a low mass near to a
fixed, critical mass. Results of this first experiment suggest that although body
mass at metamorphosis and development time to metamorphosis covary with
food availability, these growth responses do not covary with temperature.
However, survival rate of larvae in the microcosms could have influenced the
food ration per larvae resulting in the increased body size at the lower
temperatures. In fact, when population density was isolated as an influencing
factor in development, the responses in terms of development time and mass
parameters similarly changed. When larvae were reared individually,
temperature regime appeared to have a reduced influence on adult mass. For
females, it is important to note that although temperature did have a significant
effect on adult mass, the greatest mass was found for larvae reared at the
intermediate temperature (20 °C) and not for larvae reared at the lowest
temperature (15 0C) as was found when larvae were reared together. These
results indicate that interactions between larvae play an important role in female
growth patterns.

The relationship between development time and body mass for Aedes
triseriatus appears to be impacted by patterns of mortality. The predictions of
Sibly and Atkinson (1994) indicate increased mortality with increased
temperature, which they implicate as a possible evolutionary agent directing

reduced adult body size as a tradeoff for fecundity at high temperatures. This

94

prediction is disputed by the findings presented here that A. triseriatus mortality is
highest with the reduction of temperature. This relationship excludes the theory
of a tradeoff between development time and optimal body size. In contrast these
results indicate that the reaction norm as influenced by mortality acts in response
to food supply, creating larger body size at lower temperatures when food
availability was altered through juvenile mortality. Removal of the mortality
variable resulted in elimination of the expected body size reaction norm to
temperature (Atkinson 1994, Perrin 1995).

The pupation window model has been used to describe the relationships
between larval development time and mass at pupation. This model predicts
that pupation will occur at some minimum mass after a minimum developmental
period. The results of this study suggest that the critical point of pupation can be
altered by varying the food supply available, so that increased food allows for
increased mass and decreased food results in increased development time.
Larval Aedes triseriatus do follow the general patterns set forth by the pupation
window model, however, the pupation window model does not allow for variation
in other external environmental factors acting on the developing larvae.
Temperature also is a major influence for invertebrate development parameters
and both food resources and temperature can influence the potential for an
individual to survive. By combining different combinations of various
temperatures, food levels and densities, these experiments help to better explain
the relationships between these factors and their influence on Aedes trisen'atus

growth and development.

95

In conclusion, temperature, food availability and population density all play a
great part in modeling the developmental patterns of larval Aedes trisen'atus.
Although these experiments did not show a direct interaction between the
influencing forces of temperature and food level, they did indicate their
relatedness through the factor of mortality. Larval mortality is significantly
influenced by both reduced food resources and decreased temperatures. When
mortality reduces the population density it redistributes the ration of food
available among the remaining cohorts, this alteration in food availability directly
alters the possibility of maximum mass possible for these larvae. Although the
exact relationship between these three influential growth parameters has yet to
be determined, it is clear that future models of larval mosquito growth and

development must include mortality.

96

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Cummins, K.W., and M.J. Klug. 1979. Feeding ecology of stream invertebrates.
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99

CHAPTER 4

Summary and Synthesis

The intentional control of mosquito populations can be a complex activity. It
must satisfy the demands of diverse groups of people. In order to control
effectively a mosquito population without causing undue environmental harm,
one must consider a range of biological attributes of the target population, and
the community of which it is a part and the ecosystem in which it lives. The need
for this kind of knowledge in order to provide the necessary biological data to
develop and implement new control of management methods of mosquito
populations is the justification for the research reported here. The studies
presented apply not only to Aedes triseriatus per se, but to other species that
dwell in similar types of habitats, i.e., water-filled containers. Aside from these
practical or applied considerations, the research reported here addresses basic
scientific issues: how do trophic interactions affect the structure of biological
communities, and how do variations in environmental factors affect ontogenetic
parameters of organisms.

Currently in the United States, control of mosquito populations is conducted in
an integrated fashion, involving approaches directed at both the aquatic and
terrestrial life stages. Entomopathogenic bacteria have an increasingly important
role in control of larval mosquitoes due to their selectivity, their low environmental
impact, and experimental evidence that evolution of resistance to Cry11A from

Bacillus thun'ngiensis serovariety israelensis and the binary toxin in Bacillus

100

 

sphaen'cus can be averted by simultaneous exposure to the cytolytic toxin Cyt1a
(Wirth et al. 1997, Wirth et al. 2000). This strategy of vector control could be
enhanced by improvement of current strains of these bacteria through
incorporation of combinations of toxins, or by bioengineering new larvicidal
strains selected from resident bacteria in larval mosquito habitats (Thanabalu et
al. 1992, Porter et al. 1993, Thiery et al. 1993, Smith et al. 1998). For any of
these approaches, there must be a thorough knowledge of the dynamics of
microbial communities in larval habitats, coupled with an understanding of the
population dynamics of the larvae themselves. This dissertation addressed
aspects of these interrelated topics. The treehole ecosystem in which A.
triseriatus is a dominant species, given its role (as shown here) as a keystone
predator, appears to be an ideal model system for studying them.

The dynamics of larval feeding and their interaction with the microbial
compartment of the tree hole ecosystem was developed here as a major theme.
Two theoretical constructs central to trophic relationships in ecological systems
were used as a format for design of experiments: the trophic cascade theory, and
the topzdown/bottomzup theory (see Chapter 2). Studies of larval feeding have
previously shown that larvae feed both in the water column as well as on leaf
surfaces, and that the microbial community in the treeholes is affected by feeding
(Fish & Carpenter 1982, Walker & Merritt 1991, Walker et al. 1991, Kaufman et
al. 1999). The studies presented here show that under certain circumstances,
larval feeding reduces the microbial density in the water column, including

bacteria. However, protozoans and bacteria responded differently to feeding, as

101

bacteria remained at high densities even when larval feeding was intense. In
contrast, protozoans were grazed to low levels. Interpretation of these findings
within the context of food web theory suggests the absence of a trophic cascade,
indicating that relationship did not exclusively pass from bacteria to larvae
through the protozoan trophic level. A top-down effect was most apparent, as
the pressure of larval feeding altered the densities of protozoans and to lesser
extent bacteria. These findings reinforce the idea that trophic levels are an
artificial construct when predation can span taxa as different as bacteria and
protozoa. The presence of a clear bottom-up effect with relation to presence of
organic detritus merely reinforces the fact that heterotrophic, organic inputs are
necessary in this ecosystem to support production of microbial and insect
biomass ONalker et al. 1997). More interesting was that there was no detectable
response of the microbial populations under study to supplementation of
inorganic nutrients. Consequently, it cannot be concluded that there were
bottom-up effects of inorganic nutrient additions to the treehole ecosystem.
Apparently, other factors are governing bacterial dynamics, and the data here
suggest that inorganic nutrients (within the confines of the experimental design)
are not limiting.

These findings also have general relevance to the idea that bacteria native to
a larval habitat could be selected and engineered to host combinations of genes
encoding larvicidal toxins. Notably, bacteria remained at high densities even in
the presence of actively feeding larvae. Thus, recombinant bacteria might persist

under conditions when feeding is intense. Further studies involving intentional

102

releases of recombinants into microcosms under experimental conditions of the
type described here and in Kaufman et al. (1999) would help to elucidate the fate
of such organisms when they are mixed with natural populations of bacteria.
Release of any genetically altered microorganisms could impact the ecosystem,
and ultimately mosquito production, in ways that are indirect. For example, the
studies on growth and development reported in Chapter 3 clearly indicated that
increased population densities impacted the population by increasing mortality
rate, and in turn the increased mortality rate produced fewer but larger adult
females. By the same process, reduction of the population through use of
biological control agents could increase the overall size of surviving individuals.
Increasing the size of the females, in turn, could effect dynamics of transmission
of disease agents, and population dynamics. Larger adult female mosquitoes
are more fecund, producing a larger number of eggs per reproductive cycle
(Barlow 1955, Bar-Zeev 1957, Steinwascher1982, Hawley 1985). In some
Aedes mosquito species, there is a positive correlation between body size and
success of blood-feeding (Nasci, 1990). Variation in body size also affects
parameters contributing to the vectorial capacity of mosquitoes for pathogenic
microorganisms (discussed in Walker et al. 1987), such as the fact that adult
mosquito size also can determine their susceptibility to infection (Baqar et al.,
1980; Grimstad 8 Haramis, 1984; Kitthawee et al., 1990). Biological control by
genetically engineered microbes or other entomopathogenic microbes could

cause undesirable effects; research into this possibility is needed.

103

Although the experimental studies on trophic relationships presented here
represent offer certain firm conclusions, there are still open questions. Further
studies could proceed along several lines. For example, the microcosm
approach here simplified the treehole community, when in fact there is
considerable species packing in it. Additional studies could expand the number
of species of insects that occur in natural tree holes, such as beetle larvae,
midge larvae, and so forth, to examine the trophic interactions among them and
Aedes triseriatus larvae. Another line of inquiry would be to examine the
bacterial component of the food web not as an entire trophic level, but as multiple
trophic compartments. Kaufman et al. (1999) have determined that qualitative
shifts in the bacterial community can occur under feeding pressure from
mosquito larvae. These shifts suggest variations in response to predation that
may have to do with variation in digestibility of individual cells, or other factors.
Finally, the plateau of bacterial density observed even in the absence of
predatory pressure indicates some other controlling force is dampening bacterial
growth, perhaps suggesting a carrying capacity. I would propose an
investigation that examines minute resource acquisition and interaction of
bacteria with viruses. Although these studies have generated much information
regarding feeding relationships in container habitats, there are still important
questions that remain unanswered.

Variation in size of adult ectotherms was studied here in regard mainly to
development responses, however there are evolutionary implications. In

Drosophila, multigenerational selection under different thermal regimes resulted

104

in selection for larger body size in populations maintained at lower temperatures
(Partridge & French 1996). This trend, termed “Bergmann’s rule” (Bergmann,
1847), mirrors the generalized trend currently accepted for developmental effects
on size. As pointed out by Atkinson (1996), the temperatures influencing the
evolution of ectothermic organisms may have the same qualitative effects on
physical traits as the temperatures influencing the development of an organism.
The developmental effect of temperature on size is the result of phenotypic
plasticity within the individuals of a single generation reared under different
environmental conditions.

Sibly and Atkinson (1994) observed that, intuitively, the optimal approach for
organisms should be for adult body size to increase with temperature due to
fecundity advantages associated with larger size. However, current reviews of
growth studies by Atkinson (1994) indicate that of the 109 studies examined,
83.5% resulted in size reduction with increased temperature. It is interesting to
note that the largest number of studies involved arthropods and within this
phylum, the number studies indicating that size is reduced with increased
temperature is somewhat lower (78.75%). Atkinson (1996) reviewed some
hypotheses regarding the trend toward decreased size with increased
temperature including von Bertalanffy’s dichotomous explanation of catabolic
versus anabolic processes (von Bertalanffy 1960). Von Bertalanffy (1960)
suggested that the chemical dynamics of catabolic processes are more severely
influenced by temperature than the physical processes of anabolism. Therefore

in his growth equation, the rate of growth is expressed as the difference between

105

anabolism and catabolism: dw/dt = aW" - bVI/’. In the equation, wis weight, tis
time, and a, b, m and n are indices particular to genotype and environment. The
coefficient a affects anabolism and is not influenced by temperature while the
coefficient b relates to catabolism which increases with temperature.

Following these principles, as temperature increases the coefficient b would
increase resulting in increased growth rate and reduced final size. The puzzle
becomes more complex with the consideration of food resources and juvenile
mortality rates on growth reaction norms. Both reduced food and reduced
temperature do in fact slow the growth rate, and predictions indicate that lowered
growth rate should delay maturity and decrease size (Steams and Koella 1986,
Perrin and Rubin 1990), which are the opposite of the predictions discussed
previously (Atksinson 1994). The findings of the experiments involving Aedes
triseriatus, presented here in Chapter 3, indicate that when reared individually,
they do correspond to the simple principles of growth rate reduction with limiting
external influences of temperature and food. The complex interaction of
temperature and food appear to be linked with another critical factor, juvenile
mortality. For certain species, Steams and Koella (1986), found that as the
growth rate decreased juvenile mortality increased rapidly. Sibly and Atkinson
(1994) stated that increased juvenile mortality rate selects for smaller adult body
size under conditions of spatial and temporal heterogeneity. In contrast to
previous studies reviewed by Atkinson (1994) in which he could find no
consistent correlation between temperature and mortality rate, our data indicate

that for Aedes triseriatus there is a positive correlation between reduced

106

temperature and increased larval mortality. The reaction norm for this species
appears to interact with temperature, food resource and juvenile mortality. When
larvae of Aedes triseriatus were reared as cohorts, they followed essentially the
principles set forth by von Bertalanffy (1960), i.e., when temperatures are
reduced the larvae grow to a larger size at a decreased rate. In other words,
when population density factor is held to be constant in the experimental design,
the experiments become less realistic. However, population density is in fact a
variable, because of larval mortality. Consequently, the food ration increases for
those survivors, and adults are consequently larger.

Because there was a strong effect of juvenile mortality on growth rate
(mediated through changes in food ration through time), it was surprising that
temperature and food did not interact on the growth responses. The lack of
these statistically significant interactions may be explained by the dynamics of
the food resources utilized by Aedes trisen'atus larvae. Temperature would not
only have interacted with growth rates of the larvae, but also with microbial
growth rates, recolonization processes on grazed leaf surfaces, and on microbial
conditioning and mineralization of the leaf material itself. If leaf surfaces were
heavily grazed at all temperatures, then the rates of microbial processes on leaf
litter (at different temperatures) might simply have been masked by grazing
intensity.

The growth and development studies also have not ultimately determined the
relationships of external or environmental factors on larval growth and

development. Future studies could examine the relationship of temperature to

107

food resource availability, the effects of decreased temperature on both leaf
decomposition and on bacterial turn-over rate. Additionally, future studies could
examine the genetic basis for the range of growth parameters observed here.
These studies concentrated on environmental influences, but there is little known
about genetic control of adult mosquito size. The ultimate size of any individual
organism is a combined effort of both genetic interactions and environmental

influences.

108

Literature Cited

Atkinson, D. 1994. Temperature and organism size - a biological law for
ectotherms? Adv. Ecol. Res. 25: 1-58.

Atkinson, D. 1996. Ectotherm life-history responses to developmental
temperature. In: Johnston, IA and F. Albert (eds.), Animals and
temperature: phenotypic and evolutionary adaptation. Cambridge University
Press, CA pp. 93-105.

Baqar, W., Hayes, T. and Ahmed, T. 1980. The effect of larval rearing conditions
and adult age on susceptibility of Culex tritaeniorhynchus to infection with
West Nile virus. Mosquito News, 40:165-171.

Barlow, CA 1955. The fecundity of Aedes hexodontus Dyar (Culicidae) in the
laboratory. Can. J. Zool. 33:420-427.

Bar-Zeev, M. 1957. The effect of density on the larvae of a mosquito and its
influence on fecundity. Bull. Res. Council Israel 68:220-228.

Bergmann, C. 1847. Uber die verhaltnisse der Warmeokonomie der Thiere zu
ihrer Grosse. Gottinger Studien 1: 595-708.

Bertalanffy, L. von. 1960. Principles and theory of growth. In: Nowinski, W.W.
(ed), Fundamental aspets of normal and malignant growth. Elsevier,
Amsterdam, pp. 137-259.

Fish, D. and SR. Carpenter. 1982. Leaf Litter and larval mosquito dynamics in
tree-hole ecosystems. Ecol. 632283-288.

Grimstad, PR. and Haramis, L.D. 1984. Aedes triseriatus (Diptera: Culicidae)
and La Crosse virus. Ill. Enhanced oral transmission by nutritionally-deprived
mosquitoes. J. Med. Entomol. 21:249-256.

Hawley, WA 1985. A high-fecundity aedine: factors affecting egg production of
the western treehole mosquito, Aedes sien'ensis (Diptera: Culicidae). J. Med.
Entomol. 22:220-225.

Kaufman, M.G., E.D. Walker, T.W. Smith, R.W. Merritt and M.J. Klug. 1999.

Effects of larval mosquitoes (Aedes triseriatus) and stemflow on microbial
community dynamics in container habitats. App. & Env. Micro. 65:2661-2673.

109

Kitthawee, S., Edman, JD. and Sattabongkot, J. 1990. Evaluation of survival
potential and malaria susceptibility among different size classes of laboratory
reared Anopheles dirus. American Journal of Tropical Medicine and Hygiene,
432328-333.

Nasci, RS. 1990. Relationship of wing length to adult dry weight in several
mosquito species (Diptera: Culicidae). Journal of Medical Entomology,
27:716-719.

Partridge, L. and French, V. 1996. Thermal evolution of ectotherm body size: why
get big in the cold? In: Johnston, IA. and F. Albert (eds), Animals and
temperature: phenotypic and evolutionary adaptation. Cambridge University
Press, CA pp. 126-141.

Perrin, N. and Rubin, J.F. 1990. On dome-shaped reaction norms for size-to-age
at maturity in fishes. Funct. Ecol. 4: 53-57.

Porter, A.G., E.W. Davidson, and J. W. Liu. 1993. Mosquitocidal toxins of bacilli
and their genetic manipulation for effective biological control of mosquitoes.
Microbiol. Rev. 57: 838-861.

Sibly, RM. and Atkinson, D. 1994. How rearing temperature affects optimal adult
size in ectotherms. Funct. Ecol. 8: 486-493.

Smith, T.W., E.D. Walker, & M.G. Kaufman. 1998. Bacterial density and survey
of cultivable heterotrophs in the surface water of a freshwater marsh habitat
of Anopheles quadrimaculatus larvae (Diptera: Culicidae). J. Amer. Mosq.
Control Assoc. 14: 72-77.

Steams, SC. and Koella, J.C. 1986. The evolution of pheotypic plasticity in life
history traits: predictions of reaction norms for age and size at maturity. Evol.
40: 893-91 3.

Steinwasher, K. 1982. Relationship between pupal mass and fecundity for
Aedes aegypti. Envir. Entomol. 24:485-493.

Thanabalu, T., J. Hindley, S. Brenner, C. Oei, and C. Berry. 1992. Expression of
the mosquitocidal toxins of Bacillus sphaen'cus and Bacillus thun'ngiensis
subsp. jsraelensis by recombinant Caulobacter crescentus, a vehicle for
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910.

Thiery, l., G. Sinegre, and N. Tandeau de Marsac. 1993. Occurence and

abundance of cyanobacteria in a brackish marshland and their ingestibility by
mosquito larvae. Bull. Soc. Vector Ecol. 18:164-173.

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Walker, E.D., M.G. Kaufman, M.P. Ayers, M.H. Riedel and R.W. Merritt. 1997.
Effects of variation in qualityof leaf detritus on growth of the eastern tree-hole
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Walker, E.D. Copeland, R.S., Paulson, S.L., and Munstermann, LE. 1987. Adult
survivorship, population density and body size in sympatric populations of
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111

APPENDIX 1

Entomology Voucher Specimens

112

Appendix 1
Record of Deposition of Voucher Specimens"
The specimens listed on the following sheet(s) have been deposited in the named museum(s) as
samples of those species or other taxa, which were used in this research. Voucher recognition
labels bearing the Voucher No. have been attached or included in fluid-preserved specimens.

Voucher No.: 2000-04

Title of thesis or dissertation (or other research projects):

Aedes trisen'atus and treeholes; trophic interactions and factors influencing
larval growth.

Museum(s) where deposited and abbreviations for table on following sheets:

Entomology Museum, Michigan State University (MSU)

Other Museums:

lnvestigator’s Name(s) (typed)

 

Jennie; Ruth Penrod

 

Date M 5. 2000

*Reference: Yoshimoto, C. M. 1978. Voucher Specimens for Entomology in North America.
Bull. Entomol. Soc. Amer. 24: 141-42.

Deposit as follows:
Original: Include as Appendix 1 in ribbon copy of thesis or dissertation.

Copies: Include as Appendix 1 in copies of thesis or dissertation.
Museum(s) files.
Research project files.

This form is available from and the Voucher No. is assigned by the Curator, Michigan State
University Entomology Museum.

113

 

Appendix 1.1

Voucher Specimen Data

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