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Wing Beats
"Bits, Bytes and Biological Barriers"
By Jim Nolen
Jurassic Park taught everyone that mosquitoes have been around for
hundreds of millions of years, so it is not surprising that they
diversified into species very different from one another. After all,
they have successfully adapted to climates from the arctic to the
equator, and everywhere they have solved fundamental survival
problems. They must locate carbohydrates to fuel their flight
muscles, blood to supply protein to the egg clutch, and suitable
habitats in which to lay their eggs. It is also not surprising that
indigenous hosts are as varied as the locale; some mosquitoes are
adept at finding frogs, others birds, still others mammals.
Specialized adaptations exist within and between these categories.
Some mosquitoes prefer birds but are adapted to find mammals. Some
are especially well programmed to find small herbivorous mammals but
easily detect humans nearby.
Mosquitoes are physiologically well-equipped. They can sense
electromagnetic radiation from ultra violet to infrared, detect
minute changes in pressure, temperature and humidity, track their
prey's scent like a bloodhound, and they need not stop to smell the
flowers as they can do it in flight. Eons of natural selection have
focused their instinctive programming on that combination of sensory
input that identifies locally abundant hosts, floral nectar and water
for oviposition on which their survival depends. We studied three
clues mosquitoes use to find a host: scent, sight, and heat.
Structures on the antennae and palpae detect the scent of the host's
odor plume at a distance of up to 30 meters. The mosquito follows the
plume upwind and makes visual contact at a distance of approximately
10 meters. Three meters away (farther when it is humid) thermal
receptors on the tips of the antennae help locate warmer areas where
blood is near the surface of the skin. Some species can detect
temperature changes as small as 0.1ºC.
Tsetse Fly
Those who understand how sensory inputs affect instinctively
programmed behaviors can turn the insect's evolutionary success
against them. In the 1980's, British scientists succeeded in
controlling the Tsetse fly in Africa. Tsetse is a serious health
hazard. It feeds on livestock and humans, spreading sleeping
sickness. The scientists analyzed ox breath using gas chromatography,
and then used lectroantennograms to isolate the two most powerful
attractants: carbon dioxide (CO2) and octenol (1-octen-3-ol), a form
of alcohol. Octenol and CO2 are kairomones, chemical components of
host odor which mosquitoes can detect. Fermenting vegetation in the
ox's digestive tract produces octenol, which along with CO2 is
expelled with each breath. Today, baited traps are deployed to
control several species of Tsetse fly. Aerial pesticide applications
stopped in 1991.
Methods the British used in Africa were straightforward, and the
sensory structures of mosquitoes and biting flies are similar, so why
are success stories like this rare? There are many answers to the
question. Tsetse flies are an easy mark compared to mosquitoes. Their
hosts were known, their host-seeking behaviors were easily deciphered
and vulnerable to attack, and they are not prolific breeders. This is
not the case with mosquitoes.
Mosquitoes
There are more than 3,000 species of mosquitoes with many different
host-seeking behaviors. Narrow the scope to include only public
health pests and hundreds of species remain. Attempt to alter their
behavior with attractants, repellents or inhibitors, and the results
are influenced by variables we cannot completely control: season of
the year, time of day, weather and location. Each influences the
behaviors being studied and makes it difficult to isolate
experimental results so they can be accurately measured.
The problems are so difficult that an impossibly large number of
experimental trials are required to achieve a comprehensive
understanding of behavior. Consequently, experimental trials are
limited to those that can be completed within the time and budget
available. The experimental protocol becomes the embodiment of our
priorities; we design it to reveal the knowledge we believe to be
most important and postpone the rest of what we want to know.
Repetition of trials also limits what can be done in a given amount
of time. Repetition is built into the experimental protocol to
average the effect of environmental variables we cannot control over
several trials. Repetition builds our confidence when identical
trials produce similar results. Equally important, repetition tells
us outside influences are at work when identical trials produce
different results. Sometimes we get the results we expected.
Sometimes we are left wondering how to explain the result we got.
As part of a Cooperative Research and Development Agreement (CRADA)
with the United States Department of Agriculture, we demonstrated
that accurate numerical predictions of mosquito collections in
response to several experimental variables could be developed in as
little as 15 days of field trials. Traditional application of the
scientific method might take hundreds of trials and years in the
field to accomplish the same result. Specifically, we generated 90%
accurate models (correlation of predicted vs. actual catch) of each
species' response to any combination of four attractants. The
attractants were CO2, octenol, heat, and visual targets of three
different sizes.
The level of each attractant was tested over a wide range. For
example, CO2 emissions ranged from zero to 1,000 ml/min, which is
approximately equivalent to the respiration of four large men.
Octenol ranged from zero to 28 mg/hr, which is equivalent to the
emission from several cattle. The visual targets and thermal lures
were combined into one device. The visual target consisted of a
closed metal cylinder. Inside the metal cylinder were electrical
connections for incandescent light bulbs. Because the metal cylinder
trapped the light inside it, the energy of the incandescent bulbs
(which radiate 10% of their energy as light and 90% as heat) was
dissipated as heat through the thin, conductive skin of the cylinder.
The outside of the metal cylinder was painted black to radiate energy
most quickly. The inside of the metal cylinder was painted a mottled
pattern of white and black to produce a non-uniform surface
temperature. This effect is intended to simulate the non-uniform
thermal emissions of living things. Previous research indicated
non-uniform surface temperatures are more attractive than a uniform
surface temperature. The size of the smallest visual target was
equivalent to the trunk of the body of a small animal such as a
rabbit or woodchuck. The next larger size was equivalent to the trunk
of an animal such as a deer or goat. The largest size was equivalent
to the trunk of a man. Finally, incandescent bulbs of various
wattages were used in combination to produce three levels of thermal
emissions. The lowest thermal emission was zero (no incandescent
bulbs). The next higher thermal emission was 0.016 Watt/cm2 (0.1
Watt/in.2), characteristic of animals with lower body temperatures.
The highest thermal emission was 0.031 Watt/cm2 (0.2 Watt/in.2),
characteristic of warm-blooded mammals with higher body temperatures.
There are an infinite number of combinations of these four
attractants, so how can 15 trials produce an accurate model over the
whole range of variables for every species collected? The
computer-designed protocol does not test every possible combination
of attractants, but specifically selects the fewest combinations from
which a statistically valid model may be constructed. Taylor Second
Order Expansion Equations are used together with a specially selected
fractional factorial design to do so.
The fractional factorial design cleverly uses results (insect
collections) of midpoint replicates to minimize the number of trials
required to produce a statistically sound model. Just as human
researchers gain confidence from identical trials that produce
similar results, so too does the computer. The midpoint of every
variable is tested repeatedly and the differences in the collections
determine the level of confidence we have with the result. Next, the
experimental design tests each variable at its extremes, both high
and low. Not every combination of high and low extremes is tested.
Only trials sufficient to determine whether the effect of a given
variable (or its squared value, or its interaction with another
variable) is to increase or decrease collections as the variable is
increased or decreased.
To validate the predictions, the trials are repeated and the actual
collections compared to the predicted values. CRADA research will not
be published until later this year, but two examples illustrating
very different behaviors are reproduced here: Culex nigripalpus, a
St. Louis encephalitis vector, and Culicoides furens, a biting midge.
Figure 1 is the model for Culicoides furens, the infamous biting
midge and an aggressive pest in the Southern US and the scourge of
tropical beaches. This tiny creature is particularly difficult to
control. With a wingspan of 1mm, it can easily pass through physical
barriers such as screens or mosquito nets. It deposits its eggs in
the inter-tidal zone between the high and low water mark, minimizing
their exposure to larvicides. This model indicates that Culicoides
furens is strongly attracted to heat and octenol.

The first line of information at the top of the graph contains the
key used to identify the curves on the face of the graph. The face of
the graph contains three curves representing the predicted catch at
three levels of body-heat. Low (L) represents no energy radiated as
heat. The Mid-point represents 0.0155 Watt/cm2 (0.1 Watt/in.2) energy
radiated as heat. High (H) represents 0.031 Watt/cm2 (0.2 Watt/in.c2)
radiated as heat. As mentioned previously, the Mid-point and High
curves simulate the body-heat of living things.
We can graph only two values on a two-dimensional sheet of paper, so
other experimental values must be held constant. The second and third
line of information at the top of the graph lists the variables that
were held constant. In this case, the visual target was held constant
at a surface area of 4,580 cm2 (710 in.2), approximately the size of
the trunk of a man. This size visual target produced the largest
collections of midges. CO2 emissions were held constant at 200
ml/min, equivalent to the respiration of a 90-kg (200 pound) man.
The horizontal axis is the octenol emissions, which range from 0
mg/hr to 28 mg/hr. As mentioned previously, the higher rate is
characteristic of herbivorous mammals.
The vertical axis labeled 'cf' is the total predicted Culicoides
furens collections per night using a CDC trap mounted at the CO2
discharge point 15.25 cm (6 in.) from the visual target/thermal lure.
Collections took place in October 1996 at the University of Florida
Medical Entomology Laboratory at Vero Beach Florida. The coefficient
of correlation between predicted versus actual collections was 0.97
for this model.
Figure 2 is the model for Culex nigripalpus, the St. Louis
encephalitis vector. The left portion of this model indicates that
Culex nigripalpus is strongly attracted to heat and CO2, a profile
characteristic of avian hosts. The right portion of this model
indicates Culex nigripalpus is also strongly attracted to high levels
of octenol, a host profile characteristic of animals such as cattle.

The format of Figure 2 is identical to Figure 1, with the exception
that a different size visual target is used. In this case, the visual
target was held constant at a surface area of 516 cm2 (80 in.2)
simulating a small animal such as rabbit or woodchuck. This size
visual target produced the largest collections of mosquitoes.
The vertical axis labeled 'cn' is the total predicted Culex
nigripalpus collections per night using the CDC trap described
previously. The coefficient of correlation between predicted versus
actual collections was 0.98 for this model. While the scales remain
tipped strongly in favor of the mosquito, the computer speeds up the
pace of progress. When the insect's behavior is understood, a
multidiscipline team of entomologists, chemists, and engineers can
quickly focus on the best opportunities to exploit that behavior. For example:
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Breaths of CO2 five seconds apart collect more mosquitoes than
continuous discharge.
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A very narrow range of temperature, 43ºC ± 8ºC,
increases collections. Temperatures less than 35ºC do not
increase collections. Temperatures greater than 51ºC reduce collections.
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Irregular infrared patterns (mottled patterns of cooler and warmer
areas) produce larger collections than uniform ones.
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The visual image and thermal emission of a small animal produced the
greatest mosquito collections, while the visual image and thermal
emission of a larger animal produced the greatest midge collections.
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An avian host attractant profile produced larger collections than
mammalian host attractant profile for Culex nigripalpus. These
differences profoundly impact the way one designs traps for the
poultry industry's chickens as opposed to the tourist industry's beach-goers.
The efficiency (target insects collected per ml of CO2, for example)
of traps built to the specifications of the target species (as
indicated by the combination of attractants that maximized
collections) is very high. Efficient traps maximize collections,
lower costs and are harmless to non-target species, making them a
viable alternative to insecticides in some cases. For example, Dr.
Jonathan Day of the University of Florida has created a midge-free
zone 275 meters in length at Boynton Beach, Florida. He used CO2 and
octenol-baited traps spaced at 12 m intervals. While the traps were
running they removed flies at distances of at least 6 m in all directions.
Dr. Daniel Kline of the USDA in Gainesville, Florida reports that mud
samples taken from this area contain no larva when test line is on
and trapping sand files. Health officials in the Gold Coast of
Queensland, Australia are that country's midge experts. They continue
to look for alternative control measures because of insecticide
resistance. They occasionally resort to malathion and beach raking to
reach eggs buried 6 to 10 cm below the surface of the inter-tidal
zone. Considering the difficulties of midge control, Day's
accomplishment is no small feat. It is Day's opinion that removal
trapping may serve as an alternative form of midge control at a cost
competitive with present day insecticide strategies. We also are
confident that biological attractants can be effective in limited but
important applications. Moreover, biological inhibitors that cannot
achieve control may, however, reduce pesticide use in important
applications such as residential pest control, commercial pest
control, and livestock protection.
Our CRADA research originally focused on gaining an understanding of
the interaction effects of attractants. As our understanding of the
underlying chemistry improved, we soon found ourselves concocting
substances that bind more strongly to proteins on the insect's
receptors than do kairomones in the host's scent. This approach lead
to better attractants. For example, one new attractant seems to be
particularly effective against Aedes aegypti. In a preliminary trial
in the USDA's 10 by 20 m outdoor cage in Gainesville, Florida, 1,000
Aedes aegypti were released and 750 were recovered. The experimental
control, an efficient trap baited with 500 ml/min CO2, recovered only
half as many. This approach also lead to better inhibitors. Because
troublesome species of mosquito smell your scent long before they can
see you, inhibiting their scent tracking ability seems to be a
worthwhile strategy. One new inhibitor reduced landings on humans by
50% compared to landings in an unprotected control location, although
there were large individual differences between test subjects, and
some species may be less susceptible than others. In preliminary
olfactometer trials with Aedes aegypti, this new inhibitor was almost
twice as effective as DEET in preventing mosquitoes from locating
human scent. Essentially all Aedes aegypti located human scent alone,
which was the experimental control.
The technology's promise has attracted various business partners who
wish to develop applications for their markets. What does the future
hold? It is early and our crystal ball is very foggy, but some of the
possibilities appear below.
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Lower cost alternatives to pyrethrin for animal protection in dairy
barns, chicken coops, and other livestock enclosures.
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New methods of releasing high levels of attractants for outdoor
spatial barriers.
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New methods of releasing tiny amounts of high-purity attractants or
inhibitors for use indoors and in programmable traps.
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Small traps for indoor use in tropical regions.
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Alternatives to pyrethrin for indoor household use in tropical regions.
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Inexpensive devices powered by a 9-Volt battery or solar energy
surrounding breeding sites to trap mosquitoes.
Special thanks go to Dr. Jonathan Day of the University of Florida
Medical Entomology Laboratory, Dr. Scott Ritchie of the Tropical
Public Health Unit, Cairns, Queensland Australia, and Dr. Daniel
Kline of the USDA Center for Medical, Agricultural and Veterinary
Entomology for their help in the preparation of this article.
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