Comfort movements as indicators of flies

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Factors affecting biting fly harassment of feral horses (Equus caballus) on a barrier
island
Author names and Institutional affiliation have been deleted
Feral horses in harem bands on Assateague Island National Seashore, Maryland were
observed in June and August 2000 to determine what behavioral and ecological factors
affect the intensity of biting fly harassment. Fly counts and frequencies of comfort
movements were recorded during focal animal samples, as well as data on sex, group
size, habitat type, temperature, humidity, wind speed, and behavior. The number of
biting flies on the horse was affected by horse sex, habitat, temperature, and group
size. The number of comfort movements a horse made could be predicted by habitat,
temperature, wind speed, group size, number of horses within one body length, and
individual identification. Males had more flies on them than females. Fly numbers and
comfort movements were highest in scrub habitat followed by dunes and then marshes.
Fly numbers and comfort movements increased with increasing temperature and
decreased as group size increased. Comfort movements decreased as both wind
speed and the number of horses within one body length increased. The number of
comfort movements made by a horse was found to be a reliable indicator of fly
numbers. Thus the intensity of biting fly harassment is dependent upon a number of
intrinsic and extrinsic physical, social, and ecological factors.
Introduction
Hamilton’s (1971) ‘selfish herd’ model of how spatial relationships among
individuals can reduce predation may also apply to animals subjected to ectoparasitism
by biting flies (Mooring and Hart, 1992). Several studies have found that animals tend
to group together when biting fly density or harassment is high (Bergerund, 1974;
Schmidtmann and Valla, 1982; Rutberg, 1987; Rubenstein and Hohmann, 1989).
Encounter-dilution effects (Mooring and Hart, 1992) assume that in order for an
increase in the number of potential hosts (group size) to dilute the risk of ectoparasitism
on any one of them, the increase in number of hosts cannot result in an equal or larger
increase in parasite numbers. Three studies of feral horse populations have found that
per capita fly numbers decreased with increasing social group size (Duncan and Vigne,
1979; Rutberg, 1987; Rubenstein and Hohmann, 1989).
In addition to aggregating into groups, animals may take other measures to
lessen the degree of biting fly harassment. These measures include body movements
designed to remove or flush flies from the body (Hughes et al., 1981), lying down to
reduce exposed surface area (Espmark and Langvatn, 1979), increasing physical
activity (Breyev, 1964, Khumunen, 1968, and Thomson, 1971, 1973 cited in Espmark
and Langvtan, 1979), and moving to different habitat types (Duncan and Cowtan, 1980).
Biting fly intensity can have serious consequences. A study in New York found
that a dairy cow may receive as many as 4,000 fly bites per day, resulting in a loss of as
much as 0.5 L of blood. Cases of horses being fatally wounded by severe insect
harassment have also been reported (Webb & Wells, 1924, cited in Keiper & Berger,
1982). Reindeer will sometimes refuse to stand still to nurse their young when fly
harassment is intense (Breyev, 1964, Kuhmunen, 1968, and Thomson, 1971, 1973
cited in Espmark & Langvatn, 1979). On Assateague Island, horses that remain on the
southern portion of the island during the summer, where flies are more numerous, have
spend significantly less time foraging during the day (Powell, 2000). Warble flies cause
infections resulting in an estimated 20-70 kg per year growth deficit in growing calves
(Gunderson, 1945; Campbell et al., 1973). Biting flies also transmit a number of
diseases including equine infectious anemia, equine encephalitis, anthrax, swamp
fever, and a variety of trypanosome diseases (Askew, 1971; Chvala et al., 1972).
In this study we sought to determine what behavioral and ecological factors
predict biting fly intensity. We hypothesized that per capita biting fly intensity would be
lower in larger groups of horses and on horses standing in close proximity to one
another. Biting fly intensity was hypothesized to be higher when temperature and
humidity were high and wind speed was low (Tashiro & Schwardt, 1949; Rockel &
Hansens, 1970a). We also expected that biting fly harassment would be more intense
on stationary as opposed to moving animals. Finally, we expected that biting fly
intensity would be highest in marshes, followed by scrub habitats, and finally beaches
and dunes. Our study was conducted on Assateague Island, a 56 km long barrier
island running along the coasts of Maryland and Virginia, U.S.A. Assateague supports
a feral horse population of about 170 individuals. There are five common species of
tabanid flies on Assateague: green-headed horse flies (Tabanus nigrovittatus and T.
lineloa), deer flies (Chrysops fuliginosus and C. atlanticus) and a stable fly, Stomoxys
calcitrans (Rockel & Hansens, 1970b). Females of these species lay eggs in wet areas,
and the larvae develop in the soil. On Assateague, this primarily takes place in the
marshes where the adults emerge and reach maximum numbers in late July through
mid-August (Morgan & Lee, 1977). Female flies seek hosts and engorge themselves
with the host’s blood in order to produce eggs (Hughes et al., 1981).
Methods
We observed feral ponies at Assateague Island National Seashore on a total of
15 days from 8-16 June and 14-28 August, 2000. We conducted the study on an
approximately 18 kilometer portion of the island that had been developed for both a
national and state park. This portion of the island contained beach/dune, bayberryscrub/pine forest, and salt marsh habitats. A more complete description of the flora and
fauna can be found in Higgins et al. (1971). The Maryland portion of the island supports
a population of approximately 170 feral horses, approximately 140 of which inhabited
the study area during the sampling period.
Our study did not concentrate on specific horses, but rather we sampled all
possible individuals in the study area; we made an effort to sample any horse only once
per day. If a horse was sampled multiple times in a day, the samples were taken at
least 3 hours apart. Horses were identified using drawings provided by the National
Parks Service. In most cases, groups of horses could be approached to within 5-10m;
otherwise, binoculars were used to conduct observations. Focal sampling of horses
within a group was done in random order. The horse’s identification, color pattern (bay,
sorrel, or pinto), habitat type, behavior, group size, number of horses within one body
length of the focal, and any important weather data (e.g. wind gusts or rain) were
recorded. On each side of the horse, three counts of flies of any kind on the horse were
taken at 20-second intervals during a one-minute sample. Mosquitoes were not
counted because of the difficulty seeing them. During the next minute, all comfort
movements (snorts, stomps, head sways, bites, muscle twitches) intended to dislodge
flies were counted and totaled. During the third minute, three additional fly counts were
taken as described previously. This procedure was repeated for the other side of the
horse. Data from both sides of the animal were averaged to produce one fly count and
one value for the number of comfort movements per minute per horse sampled. All
samples were collected between 1030 and 1930 hours. Weather data were obtained
for sampling periods from the National Parks Service weather station on Assateague.
Temperature, humidity, and wind speed data were recorded every hour by the station.
Proc Mixed (SAS Stat module, SAS Stat User’s Guide Version 8, SAS Institute
Inc, Cary N.C.) was used to perform a repeated-measures general linear model
predicting mean number of comfort movements and the square root-transformed mean
number of flies on the horse during the sample based on the following. Fixed effects
included wind speed, temperature, humidity, group size, number of horses within one
body length of the focal horse, habitat type (marsh, scrub, or dunes), behavior (play,
graze, or stand), color (pinto, sorrel, or bay), and sex. Horse identification was included
as a repeated measure.
The covariance structure did not display any particular or unique type, although
compound symmetry was considered and tested. The data did not display compound
symmetry; it was not perfectly balanced – typical of data collected without strict control
of experimental units and/or treatments. Small sample size (N=93) in concert with a
relatively large number of experimental subjects (ID, N=55 individual horses) prevented
horse ID from qualifying as a predictor.
The full model (all variables above included) was run using maximum likelihood
estimation on components of variance. Non-significant variables were then excluded
and the remainder put through the same mixed model using REML (restricted maximum
likelihood estimation). No improvement was noted in this secondary model, whether or
not the non-significant variables were omitted from the analysis. The Z-test for the
hypothesis that ID=0 was negated in all cases (p < 0.001). This may imply a non-zero
effect of ID on the significance of the fixed-effect parameters.
Tukey tests were performed when habitat type, behavior, and sex were found to
have significant effects. Tukey tests were not performed when group size and number
of horses within one body length of the focal were found to be significant effects
because the number of tests was too large relative to the number of degrees of
freedom. Means were inspected visually to identify these effects. Means are presented
± SE.
Comfort movements as indicators of flies
To determine whether comfort movements could be used as reliable indicators of
fly numbers, we conducted a simple linear regression analysis of comfort movements
using fly numbers as the independent variable. We also included fly numbers in the
mixed model with the other factors that were found to have significant effects on comfort
movements.
Results
In the majority of the samples (82%, n=93) the focal animal was grazing. The
focal animal was standing (17%) or playing (1%) in the rest of the samples. Since only
one sample included an animal that was playing, only the effects of standing versus
grazing were determined in the behavior analysis. The horses were in the marsh in
37.5% of the samples, the scrub/pine forest in 38.5% of the samples, and in the
dunes/beach area in 24% of the samples. Relative humidity averaged 78.6% (range:
57-100%); the average temperature was 23.9°C (range: 17.2-29.4°C). Wind speed
averaged 15.4 km/hour (6.4-22.5 km/hour).
Fly counts
The mixed model ANOVA found significant effects of sex (F1,53=11.30, p=0.001),
habitat type (F2,13=8.79, p=0.004), behavior (F1,12=5.96, p=0.031), temperature
(F1,33=8.54, p=0.006), and group size (F1,33=15.24, p=<0.001) on mean fly number.
There was also a significant effect of the repeated measure Horse I.D. (z=6.56,
p<0.001). Male horses had more flies on them than female horses (males: 3.880.48,
females: 1.940.25). Grazing horses (3.300.36) had more flies on them than standing
horses (1.760.49). Fly numbers were highest in the scrub habitat followed by the
dunes and marshes (Figure 1). The difference in fly counts between marsh and scrub
habitats was significant (Tukey test t=-3.38, 13 df, p=0.002). There was no significant
difference in fly numbers between marsh and dune habitats (Tukey test t=-0.70, 13 df,
p=0.498). The difference in fly numbers between scrub and dune habitats approached
significance (Tukey test t=1.84, 13 df, p=0.088). Fly numbers increased with increasing
temperature (Figure 2) and decreased with increasing group size (Figure 3). Horse
color was not a significant predictor of fly numbers (p>0.05).
Comfort movements
The mixed model ANOVA found significant effects of habitat type (F 2,13=5.05,
p=0.024), temperature (F1,32=15.80, p<0.001), wind speed (F1,32=14.01, p=<0.001), and
number of horses within one body length of the focal (F1,32=4.69, p=0.038) on mean
number of comfort movements. The effect of group size on comfort movements
approached significance as well (F1,32=2.95, p=0.095). Horse I.D. also had a significant
effect (z=6.63, p<0.001). As with fly numbers, comfort movements were highest in
scrub habitat, followed by marsh and dunes (Figure 1); however, only difference in
comfort movements between scrub and dune habitats was significant (Tukey test
t=2.68, 13 df, p=0.019). Comfort movements increased with increasing temperature
and decreased with increasing wind speed (Figure 4). Comfort movements decreased
with increasing numbers of horses within one body length of the focal animal (Figure 5)
as well as with group size. Horse color was not a significant predictor of comfort
movements (p>0.05).
Comfort movements as indicators of flies
In the linear regression, fly counts were a very significant predictor of comfort
movements (F1,94=25.60, p<0.001, =9.02, adjusted R2=0.206). Fly count also had a
significant effect on comfort movements when included in the mixed model with the
significant factors listed above (F1,31=4.34, p=0.046).
Discussion
Male horses had more flies on them than females. Similar results were found in
a previous study of the Assateague horses (Rutberg, 1987) and in a study of the horses
on Shackleford Banks, North Carolina (Rubenstein & Hohmann, 1989). In general,
metabolic rates of males are higher than those of females (Altmann & Dittmer, 1968),
and metabolic rate may be linked to carbon dioxide (CO2) emission (Smythe & Goody,
1972). Biting flies are drawn to baits with a carbon dioxide source (Wilson et al., 1966;
Knox & Hays, 1972); therefore, more CO2 production by males may lure more flies to
them.
We found support for our hypothesis that per capita fly harassment would
decrease with increasing group size and increasing numbers of close (i.e. within one
body length) neighbors. Similar results have been found in other horse studies (Duncan
& Vigne, 1979; Rutberg, 1987; Rubenstein & Hohmann, 1989). Several studies have
shown that ungulates will clump together when biting fly harassment is severe
(Bergerund, 1974; Schmidtmann & Valla, 1982; Rubenstein & Hohmann, 1989). Since
this study was conducted during the summer when biting flies are generally most
numerous, we are unable to demonstrate that the horses in our sample reduced their
inter-personal distances in response to flies (but see Rutberg, 1987), but we did
observe that the horses would form tightly-clumped groups, often standing with their
flanks touching one another. Very commonly groups of horses would stand side by side
in opposite orientations, such that one horse’s face was flanked by a neighbor’s tail.
Thus the tail movements of one horse would also help to flush flies off the face of its
neighbor. Movement in these groups was fluid, with animals continuously trying to
occupy spots in the middle, where both of their sides would be protected. The horses
would take shelter on the dunes and beaches (where winds and breezes were
strongest), even standing in the surf, or they would migrate long distances to narrower
portions of the island (where perhaps oceanic and bay breezes would sweep the entire
landscape) to escape flies. Habitat shifts and migrations in response to biting insects
like this have also been documented in the Camargue horses (Duncan & Cowtan,
1980).
Fly numbers and comfort movements increased with increasing temperature as
predicted, but we found no significant effect of humidity on either measure. Fly
numbers and comfort movements actually show a slight decrease with increasing
humidity (data not shown); however, this effect may be due in part to the effect of rain.
Samples were not collected during heavy rain, but some were collected during light rain.
It is impossible to distinguish rainy periods from very high humidity periods in the
meteorological data from the weather station, so some of the high humidity readings
might actually reflect rain. If we exclude samples when humidity readings exceeded
80%, then both measures of fly intensity show a general increase with increasing
humidity. Though we did not find a significant effect of wind speed on fly numbers, we
did see that comfort movements decreased with increasing wind speed.
We expected that fly harassment would be greater for animals that were standing
still as opposed to those that were moving. In fact we found that the opposite was true.
Horses that were grazing (and thus moving) had more flies on them than horses that
were standing still resting. We believe that this is due to the fact that as horses were
grazing, they were flushing flies from the substrate through the movements of their
limbs and snouts, whereas resting horses were not disturbing the surrounding
vegetation. Findings from studies of red deer (Cervus elaphus) support this hypothesis
(Espmank & Langvatn, 1979). Similarly, we found that flies and mosquitoes bothered
the observers less when they were sitting or standing still as opposed to walking
through the marshes.
We expected that fly harassment would be greatest in marshes, followed by
scrub and dune habitats since marshes are where the flies lay eggs and where most
adults emerge from the soil. However, fly counts were significantly higher in scrub
habitat, and comfort movements did not differ between marsh and scrub, though
movements were significantly more frequent in these habitats compared to dunes. One
explanation for these results is that the scrub habitats provide more “cover” for flying
insects in the form of vegetation to rest on during periods of high wind or rain. Dunes
and beaches likely have fewer flies because they provide the least amount of cover for
insects because vegetation or other features are very sparse, and wind speed is
generally higher on the beach than inland (see also Rubenstein & Hohmann, 1989). .
Horses likely flush more insects as they move through scrub habitats since the
vegetation is higher and more dense. This could explain why we saw more flies on the
horses here than in other habitats.
We were able to identify a statistically significant effect of individual on fly
numbers and comfort movements; however, it is not clear what the causal factor is
given that other individual characteristics (sex, color) were included in the model.
Numbers of repeated samples from the same individual did not differ greatly across
horses, and the sample is relatively large (55 individuals), so it is unlikely that
observations from a few outstanding individuals are influencing the data. One factor
could be the age of the animal, given that metabolic rate changes with age (Altmann &
Dittmer, 1968),
Finally one of our goals was to assess the validity of using comfort movements
as a proxy measure of fly harassment, given that fly counts are generally more difficult
to do for a number of reasons. Simple regression and mixed model analysis both
indicated that fly numbers were significant predictor of comfort movements. In addition
to reflecting the number of flies on a horse, comfort movements likely also reflect the
number of flies surrounding (and potentially harassing) the horse, which would be
difficult to obtain via visual counts. We therefore suggest the use of comfort movements
to assess biting fly intensity.
In conclusion, biting fly harassment of feral horses is influenced by intrinsic and
extrinsic physical, social, and ecological factors. Harassment by biting insects shapes
feral horse ecology, specifically spatial relationships of individuals and habitat use.
Reduction in biting fly harassment is potentially one factor selecting for group living in
this population.
Acknowledgements
This section has been deleted
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Figure 1: Least-squares mean number of flies/horse (A) and comfort moves/minute (B)
in different habitat types. Bars with different superscripts are significantly different.
Figure 2: Mean number of flies/horse as a function of temperature.
Figure 3: Mean number of flies/horse as a function of group size
Figure 4: Mean number of comfort movements/minute as a function of temperature (A)
and wind speed (B).
Figure 5: Mean number of comfort movements/minute as a function of the number of
horses within one body length of the focal horse.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
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