Systematic & Applied Acarology Special Publications (2009) 23, 1–30. ISSN 1461-0183

The effect of Macrocheles muscaedomesticae and M. subbadius (Acarina: Mac- rochelidae) phoresy on the dispersal of Stomoxys calcitrans (Diptera: Musci- dae)

D. V. BERESFORD1 & J. F. SUTCLIFFE Trent University Biology Department, 1600 West Bank Drive, Peterborough ON, Canada K9J 7B8. 1Corresponding author. Phone: 705 652-7452; Email: [email protected]

Abstract

In south-central Ontario, the stable flies disperse from their overwintering farms and re-establish populations at neighbouring dairy and beef farms each spring. Two species of phoretic macrochelid mites commonly found on stable flies are Macrocheles muscaedomesticae and M. subbadius. We tested the hypothesis that mite phoresy affects the dispersal of their stable fly phorionts. At a beef farm we found a higher proportion of parous stable flies with mite scars than expected, based on the proportion of nulliparous females carrying mites. These results were consistent with our hypothesis, indicating that stable flies without mites may be emigrating more than flies carrying mites. We further tested our hypothesis by comparing the mite load on dispersing stable flies sampled with a vehicle-mounted truck trap to the mite load on resident stable flies sampled from three dairy farms and one beef farm (May to October, 2001). Significantly, no stable flies caught in the truck trap were carrying mites, compared to the seasonal means of 10% and 5% of female and male stable flies with mites at the four farms. This effect of mite phoresy on stable fly populations is discussed.

Keywords: phoresy, dispersal, Macrocheles, mites, Stomoxys calcitrans, stable fly

Introduction

Dispersal is one of the most important aspects of any organism's success (Andrewartha & Birch 1954). For many mites, dispersal is achieved by phoresy on insect hosts. While it is known that ectoparasites can alter host dispersal (e.g., Wecker 1962), little is known about the effect of phoretic mites on their host's dispersal patterns. This paper examines whether phoresy by two Macrocheles mite species affects the dispersal of one of their muscid phorionts, Stomoxys calcitrans (L.), the stable fly. The stable fly is a costly (Cantigui et al. 1997, Campbell et al. 2001, Mullens et al. 2006) and highly dispersive pest species that annually re-colonizes dairy and beef farms in temperate climates (Beresford & Sutcliffe 2009). Stable flies from farm populations often carry phoretic mites of various species (Axtell 1964, Hunter & Rosario 1988, McGarry & Baker 1997). Both Williams (1976) and Hogsette and Ruff (1985) used the presence of phoretic macrochelid mites on dispersing stable flies to infer an agricultural origin of stable flies found on coastal areas. Many of the Macrochelidae are voracious predators of fly eggs and first instar larvae (Doube et al. 1986), and play an important role in limiting fly populations in agricultural systems (Wallace et al. 1979, Halliday & Holm 1987, Koehler 1997). The most common macrochelid carried by stable flies is Macrocheles muscaedomesticae (Scopoli) (Williams 1976, Halliday 1990, Ho 1990) followed by Macrocheles subbadius (Berlese) (Filipponi 1960, Axtell 1961, 1964, Cicolani 1992). Both of these species are predatory on muscid fly eggs and first instar larvae (Axtell 1961, 1963,

© 2009 Systematic & Applied Acarology Society 1 Mohmood & Al-Dulaimi 1986), and significantly reduce house fly numbers (Wade & Rodriguez 1961, Rodriguez & Wade 1961, Axtell 1963, 1991, Perotti 2001). Mated female mites are the usual dispersants, and prospective phoretic females attach to emergent stable flies, then detach when the flies visit suitable new mite habitat to feed or oviposit (Farish & Axtell 1971). The front leg tarsi of M. muscaedomesticae bear setae that sense water- soluble sugar compounds produced by the pupae and adults of both sexes of house flies and stable flies (Jalil & Rodriguez 1970, Wicht et al. 1971). Mites congregate around the anterior end of stable fly pupae, and attach as they emerge (Greenberg & Carpenter 1960), mainly to the ventral surface of the teneral adult’s abdomen (Ho 1990). Most adult female macrochelids disperse after having mated (Krantz 1998), and a single fertilized female can establish a new colony. Eggs hatch within hours of being laid and M. muscaedomesticae can progress from an egg into an adult in three days in summer (Hunter & Rosario 1988). Fertilized female mites produce an average of four to five eggs per day for about 22 days, and a maximum of 25 eggs per day has been documented (Wade & Rodriguez 1961). Although Rodrigueiro and Prado (2004) did suggest that carrying mites may limit house flies’ ability to colonize new habitat, there is little direct evidence of any effect of phoretic mites on phoriont dispersal. In one reported example, Elzinga and Broce (1988) observed that house flies emerging from silo pits carrying an uncharacteristically large number of Bonomoia mites (Astigmata: Histiostomatidae) were unable to fly more than a few centimeters. What little has been suggested about the potential effect of phoretic macrochelid mites on stable fly populations has been inferred from house fly/macrochelid ecology. High levels (up to 56.3%) of infestation of Macrocheles species on stable flies have been found (Filipponi 1960, Axtell 1964, McGarry & Baker 1997), which suggests that phoresy on individual hosts could have important effects on local stable fly populations associated with behavioural changes induced by the presence of phoretic mites. We tested possible effects of phoretic mites on the dispersal of adult stable flies (App. 1). The main hypothesis of our study is that stable flies carrying M. muscaedomesticae and/or M. subbadius have a lower rate of dispersal than mite-free stable flies. The reasoning behind this is: a) the mites would benefit from keeping their phorionts safe from the risks of emigration or dispersal; b) mites on dispersant flies may be carried to locations where there is no suitable habitat (i.e., off farm); c) macrochelid mites would cause reduced flight activity levels by altering the fly's aerodynamics and impede flight ability. Alternative hypotheses are that stable flies with phoretic mites either have higher dispersal rates than non-infested flies or do not alter their dispersal patterns as the result of mite infestation.

Materials and methods

Evidence of phoresy in parous flies To determine whether mites left permanent identifiable scars on adult stable flies after detachment, stable fly pupae from a colony at Trent University were placed in a colony of M. muscaedomesticae mites over a period of several days while adult flies emerged. Drying conditions were maintained in the mite colony, encouraging mites to attach to emergent adults (Farish & Axtell 1966). Locations of attached mites were noted for each of 10 flies. Mites were removed with forceps from these flies 48 hours after adult emergence, and the adult flies examined with the unaided eye and with the dissecting microscope for scars left by mites. To eliminate the possibility that apparent scars were the result of some other mechanism (e.g., mating, emerging from the pupa, etc.), we also

2 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 examined 92 flies from the Trent University stable fly colony which had not been exposed to mites for similar scarring of the integument.

Sampling resident (non-dispersant) farm stable fly populations To find the phoretic burden and frequency distributions of both macrochelid species on local populations of stable flies in the study area, and to identify any seasonal changes in these phoretic loads, we sampled stable fly populations at one beef farm and three dairy farms. The beef farm is located near Warsaw, Ontario, Canada (60 km north of Lake Ontario near Peterborough). It is used to pasture beef cattle, and stable flies arrive at this site each spring on the cattle that are trucked to the farm. Host-seeking (resident) stable flies were sampled daily each summer at the beef farm from 1997 to 2001, using a CO2-baited cloth Nzi trap (Mihok 2002) (Fig. 1a) following the method outlined in Beresford and Sutcliffe (2008a). This allowed us to sample both nulliparous and parous females (Taylor & Berkebile 2006). Briefly, CO2 was released from the trap opening at a rate of 1 litre per minute throughout each sampling day from 7 am to 7 pm. At the end of each sampling day, stable flies in samples were examined under a dissecting microscope for the presence of mites and/ or scars. Each mite-infested fly was sexed and the number and location of mites and scars, and the species of attached mites were determined. Specimen preparation methods outlined in Krantz (1970) and keys in Hyatt and Emberson (1988) were used to identify the mites to species. During the summer of 2001, five Coroplast sticky traps (Fig. 1b) (Beresford & Sutcliffe 2006, 2008b) were used to sample stable flies weekly at each of the three dairy farms. Since these flies were caught on sticky traps, they could not be age-graded; however, from our earlier analysis of stable fly responses to Coroplast traps (Beresford & Sutcliffe 2006), more than 90% of the females caught can be assumed to have been nulliparous. Thus, the proportion of mite-bearing females caught on the Coroplast sticky traps was used as an estimate (albeit a slight underestimate) of the proportion of mite-bearing nulliparous females in the farm population.

Truck trap collections of dispersant (off-farm) stable flies A net mounted on a truck roof was used to sample dispersing stable flies during the summer of 2000. The truck trap (Fig. 2a) incorporated design details found in Davies and Roberts (1973) and Barnard (1979). The frame (65 cm x 122 cm, constructed from 1 inch electrical conduit) of the net (black fabric netting, 3 mm mesh) was mounted on the top of a small truck. The tapered end of the net was connected to a 90 degree elbow (20 cm diameter) which directed the air into a sheet-metal funnel that was fitted into a slightly larger pipe to act as a slip joint between the net and the collecting apparatus. The collecting apparatus consisted of a horizontal 80 cm x 80 cm x 4 mm aluminum plate, supported by a welded metal frame. The periphery of a round plastic disc (75 cm x 1 cm, suspended 2 mm below the aluminum plate) bore the lids of 25 collecting bottles. A 2.5 cm hole was drilled through each lid, and the disc and the 12 cm by 7 cm collecting bottles were suspended below the plastic disc by screwing them into their lids. Each bottle had a 5 cm hole covered with 2 mm copper screening (attached with silicone adhesive) which caught insects while still allowing air to pass through the bottles. The whole disc assembly made up a carousel with 25 collecting bottles, each of which could be aligned with the net and funnel apparatus (Fig. 2b). The disc was notched at each bottle so that the metal rod extending from the truck cab could hook each notch in turn to bring a new bottle into place beneath the funnel. A mirror in the back of the truck allowed the operator to check collecting bottle alignment. To permit an accurate measurement of the amount of air sampled on each run, an anemometer with a mechanical readout was mounted immediately in front of the net mouth. The anemometer measured the ‘run on wind’ (the length of the air column traveling through the net). By recording the anemometer readout at the beginning and end of a sampling trip and at each bottle change, the

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 3 volume of air sampled for each section of the travel route (i.e., corresponding to each collection bottle) could be determined. From the corresponding truck odometer reading, it was possible to compare the length of the sampled air column to the ground distance covered. Overall, 984 km was traveled in which a total air column 835 km long by 65cm high by 122 cm wide (662,155 cubic meters) was sampled.

FIGURE 1. A, Nzi trap at the Warsaw beef farm showing CO2 canister (a), gas outflow hose (b), collecting region (c), B, three Coroplast sticky traps (d) used at the dairy farms showing a typical setup near a calf hutch.

4 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 FIGURE 2. A, truck trap with net (a) and anemometer (b) mounted on wooden racks (c), and collecting funnel (d) directing aerial catches to the collection bottle assembly, B, collecting apparatus with funnel (e), slip joint (f), and collecting bottles (g), by pulling the cable (h) from inside the cab, a new sample bottle is set in place, the spring returns the cable to the ready position.

Weekly and daily collecting trips were made with the truck-mounted trap. The weekly trip was from the northern extreme of the study region (Warsaw beef farm) to the town of Colbourne on the north shore of Lake Ontario, which represents the southern extreme of the study region (Fig. 3). Weekly trips were made from May 10 to October 11. Each trip started at 11 am and was of

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 5 approximately four hours duration, with sampling done during both legs of the trip. Sampling bottles were changed at the same place in each trip, at 10 to 15 km intervals, corresponding to 15 to 20 minute sampling periods. The daily trips were in the area around Trent University (Fig. 3). Daily sampling was undertaken whenever the truck was in use for other purposes. Typically, daily trips were round trips from the Warsaw farm site through Assumption to Trent University at 9 am and back again through Lakefield at 4 pm (Fig. 3). Driving speed in all runs was maintained at 80 km/ hour as much as possible.

FIGURE 3. Map of weekly and daily sampling routes. The numbers in boxes from 1 to 7 are the section numbers of the weekly route.

To the extent that it was possible, the routes were chosen to pass through agricultural areas supporting dairy and beef farms. The region between Peterborough and Lake Ontario is predominantly agricultural, with a large proportion given over to dairy and beef production. We

6 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 chose the sample route to transect this region in both north/south and east/west directions to minimize the effect of prevailing winds following two-lane roads. The weekly route passed by the three farms where Coroplast sticky traps were deployed to sample non-dispersant populations, and both weekly and daily travel routes incorporated the region around the sampled dairy and beef farms (Warsaw). At the end of each collecting trip, bottles were labeled, removed from the attached lids and capped with a second set of lids. In the laboratory, stable flies were counted, examined for mites, dissected and age-graded according to the criteria of Moobola and Cupp (1978) and Scholl (1980) (length:width ratio and proportion of follicle occupied by oocyte). Based on this method six stages can be distinguished in the first gonotrophic cycle, of these the latter three stages repeat in each subsequent gonotrophic cycle (i.e., nulliparous stages N, I, II, III, IV, V, parous III, IV, V). To differentiate by parous level, we assigned follicles according to an age-grading continuum of from 1 to 12 reproductive age classes (RACs), categorized as: 1 to 6 nulliparous; 7, 8, 9 uniparous; 10, 11, 12 multiparous; stages 6, 9 and 12 being gravid stages. Parity, assessed on the presence or absence of follicular relics (Scholl 1980), was identified as nulliparous (no follicular relics), uniparous (one follicular relic) or multiparous (more than one relic, or relics appearing as yellow bodies).

Analysis of truck trap data Because the expected mite-bearing proportion on neighbouring farms and the likelihood of catching a fly in the truck trap both changed over the summer, we could not use goodness of fit tests (e.g., two-way tables) to compare the proportion of truck trapped flies (dispersant flies) bearing mites to the mite-bearing proportion on dairy farms (non-dispersant flies). To take these changes into consideration, we calculated the probability of obtaining the observed mite-bearing proportion as the product of the probabilities of each individual fly caught bearing a mite. The probability that an individual fly would bear a mite was obtained from the weekly proportion of on-farm flies’ mites: p[proportion flies with mites = pfly1 x pfly2 x pfly3 . . . pflyN (1) in which N is each individual fly caught in the truck trap, and pflyN is determined for each caught fly as the proportion of flies with mites on neighbouring dairy farms on the same week. In this way, we were able to incorporate information on the probability of catching stable flies with mites based on each sampling date. For the expected proportion with mites, we used the proportion of flies with mites at both the Warsaw farm and the weekly mean proportion with mites at the three Coroplast- sampled dairy farms along the weekly sampling route. These calculations were done using separate probabilities for males, and nulliparous and parous females on a weekly basis. As a check on the above, we performed a randomization analysis to compare the proportions of mite-bearing stable flies in truck trap collections to the proportions of mite-bearing stable flies in farm collections. For the randomization we used a Microsoft Office Excel spreadsheet (App. 2). Based on the total number of flies caught in the truck trap, we picked the same number of ‘flies’ in a series, in which each ‘fly’ in the series had a probability of being mited which corresponded to the proportion of mite-bearers observed at the sampled farms in the week the actual fly was caught. Thus, we obtained a possible total number of mited flies that we could have observed in the truck trap over the summer. By repeating this 10,000 times, we were able to obtain 10,000 possible truck trap catch results, based on the date each fly was actually caught, and the likelihood of any fly caught at a particular time having mites. Again, calculations were done using separate probabilities for males, and nulliparous and parous females on a weekly basis. Using the odometer readings and anemometer readings, for each sampling trip we calculated the air/ground ratio (A/G) as: [length of sampled air column (km)]/[ground distance (km)] to determine whether there was any effect of the A/G ratio on whether mites were caught in the truck trap. Such an effect would exist if catches on windy days differed from non-windy days.

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 7

Distribution of mites on flies The frequency distribution of mites on stable flies in farm populations may be described using several indices of dispersion (Ludwig & Reynolds 1988). These are the variance to mean ratio (VMR), the index of clumping (IC), and Green's index. The VMR is calculated as the mean/variance ratio of mites per fly, and has values between 0 and 1 for regular, 1 for Poisson, and >1 for aggregated distributions. IC is the VMR-1, and Green's index is IC/(n-1), where n is the number of sample units, that is, the number of stable flies in the sample (Ludwig & Reynolds 1988). Green's index is the only one of these that is independent of sample size and consequently is considered superior for comparing clumping in data sets of different sizes. The frequency distribution of mites/fly was also compared to the negative binomial distribution, which is commonly used to describe aggregated distributions. The negative binomial (the series resulting from the expansion of (q-p)-k) is described by two parameters, k and p (where p = q-1); the mean = kp and the variance = µ + µ2/k (Krebs 1989). Several methods for calculating k are possible depending on the data. We used the iterative method for aggregated populations with small means described in Ludwig and Reynolds (1988) (also see Southwood 1966 and Krebs 1989). Both k and 1/k can be used as indices of clumping – the smaller k is, the greater the aggregation. An aggregated distribution of phoretic mites would result in a lower proportion of flies bearing mites than if the mites were randomly distributed on their fly hosts. To quantify this, we calculated the expected proportion of flies bearing mites based on a Poisson distribution using the number of mites caught at the farms. We then subtracted this number from the observed proportion of flies with mites. We tested whether the presence of mites of both species on the same fly was more or less common than randomly expected using a chi-square test, and whether there was any difference between male and female stable flies in this regard. We also compared whether both species of mites were more or less common than randomly expected on male and female stable flies using the Jaccard Index (JI) of association (Ludwig & Reynolds 1988). The JI is simply the proportion of mited flies bearing both mite species.

Annual comparisons of proportions of females bearing mites by reproductive age class We used an ANCOVA to compare the proportions of females in each of the 12 RACs (reproductive age class) with and without mites each year, using RAC as the covariate and year (1999 to 2001) as the independent variable. We used an arcsine transformation of the proportional data to satisfy the assumptions of normality (Sokal & Rohlf 1996). We pooled the data from 1999 to 2001 and tested a linear and an exponential regression of RAC against the proportion of mites/RAC. In order to prevent small sample sizes in some RACs from having a disproportionate effect on the regressions, we weighted each arcsine-transformed value by the square root of the number per stage. We also tested the difference in apparent survival (which includes the net migration) between the mited and unmited sections of the stable fly population for each year by determining survival rate using the proportion parous method (Davidson 1954, Service 1976, Scholl 1986). In this method, survival probability is pn = M, where p is the time step-specific survival rate, M is the proportion of parous flies, n is the number of time steps. We used both RAC and parity state as time steps. Therefore, for survival to each parity state, n = 1; for RAC-specific survival from nulliparous to parous, n = 6 (three uninseminated and three inseminated stages), and for uniparous to multiparous survival, n = 3. Note that survival, calculated by the parous proportion method, does not distinguish between mortality and emigration.

8 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 Comparison of mite bearing flies versus non-mite bearing flies We tested whether there was a difference in the fecundity (number of ovarioles per ovary, counted during dissection) between mited and unmited nulliparous females, and scarred or unscarred parous females, using an ANCOVA in which the length of the hind leg (measured with an ocular microscope micrometer) was the covariate. We also compared fly size based on leg length (femur plus tibia length) of mited and unmited, and scarred and unscarred females using a one-way ANOVA. These analyses were done on data obtained at the Warsaw beef farm in 2001.

Results

Mite scars on hosts We removed both M. muscaedomesticae and M. subbadius mites from field caught female stable flies to compare the scars left by these two species. While both left abdominal scars, the M. subbadius scars were sometimes melanized, appearing like raised black dots under a light microscope (Fig. 4a). Flies which had been carrying a large number of mites in one area of the abdomen sometimes had a melanized region that made it difficult to get an accurate scar count (Fig. 4a). Mites located on the thorax or between the head and thorax did not leave identifiable scars. However, in field collections, stable flies with mites on either the head or thorax always also either had mites or mite scars on the ventral surface of the abdomen. Thus, while assessments based on scars will under-estimate individual load somewhat, they should yield accurate estimates of the number of mited flies. Mites removed from colony flies left permanent scars on the integument that were indistinguishable from abdominal marks observed in field-caught stable flies (Fig. 4b). No such scarring was observed in colony flies that had not been exposed to mites.

Occurrence and distribution of mites on non-dispersant stable flies Two species of phoretic mites were regularly found on farm-sampled (non-dispersant) stable flies: Macrocheles muscaedomesticae (Fig. 4c) and M. subbadius. Macrocheles muscaedomesticae was almost exclusively found on the ventral surface of the abdomen (2001 data: 37 out of 40 mites (92.5%)), while M. subbadius, the smaller of the two species, was largely on the abdomen, with about 15% located between the head and thorax or on the lateral surface of the thorax (2001 data: 15 of 100 M. subbadius attached to either the head or thorax). Mites of both species were occasionally found attached to the legs (e.g., in 2001, one incident of each species). Other species of mites were occasionally found, but not identified. One male fly was found carrying a pseudoscorpion. An average of 5.6% (266/4787) of all stable flies caught over the five years of farm sampling carried one or more mites (5.7%, 4.8%, 6.2%, 6.6%, 5.4% in 1997 to 2001respectively) (Table 1a). The mean mite load for all years was 0.14 mites/fly (range 0.10 to 0.19). Excluding flies without mites, the mean mite load was 2.4 mites/fly (range 1.6 to 3.6). The maximum number of M. muscaedomesticae on a single fly was 12 on a female in 2001, and the maximum number of M. subbadius was 35 on a male in 2001. One parous female in 2001 had 42 scars. These scars were melanized suggesting they were made by M. subbadius. Based on 2x2 contingency tables (Table 1b), there was no statistically significant difference in the proportion of mite-bearing males versus the proportion of mite-bearing females from the Warsaw farm population. Nor (except in 2000) was there a significant difference between the proportion of males with mites vs males with scars. There was such a difference among females, however, with a significantly higher proportion of females bearing scars than with mites. There were proportionally more females than males with scars in 2001, but not in the other two years (Table 1b).

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 9

FIGURE 4. A, photograph of single melanized scar to the right of (a) on a field caught female stable fly, note the large melanized region (b) where several M. subbadius mites were removed, B, colony male stable fly with three mite scars (c) typical of M. muscaedomesticae, C, scanning electron micrograph of four M. muscaedomesticae (d) attached to a male stable fly (field caught specimen).

The variance-mean ratios (VMR) for 1997 to 2001 were 3.8, 3.8, 5.2, 7.2, 13.2 respectively, indicating clumped distributions of mites on flies. The negative binomial described the frequency distribution of mites per fly (combined mite species) for all years except 2001 (critical chi-square(.05) = 7.81, 6 categories [0, 1, 2, 3, 4, 5], d.f. = 4: chi-square2001 for all flies, males, females = 17.82, p < 0.001; 16.36, p < 0.001; 8.98, p = 0.03 respectively). The negative binomial provided a good fit to the frequency distribution of M. muscaedomesticae on both male and female stable flies in all years, but not as good a fit to distribution of M. subbadius (Fig. 5, 2001 fit typical) (chi-square all flies combined data 1999 to 2001 = 9.72, p < 0.02; females combined 1999 to 2001 = 12.72, p < 0.005; females 2001 only = 9.06, p < 0.028). The several indices of aggregation (see Myers (1978) for use of these) that were calculated all indicated that the

10 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 frequency distribution of M. subbadius on stable flies was more aggregated than that of M. muscaedomesticae (Table 2). Generally, the number of flies carrying mites each year was half of what would occur if the frequency distribution of mites on flies was random rather than aggregated (Table 3).

TABLE 1. (a) Summary statistics of flies with mites (1997–2001) and with scars (1999-2001). (b) Contingency table analysis of sex [m:f] vs mites [yes:no], sex vs scars [yes:no], and, for each sex, mites with or without scars. Significance was based on a Yates corrected chi-square test.

(a) number % flies (b) test by year year sex flies mites scars mites scars 1997 1998 1999 2000 2001 1997 male 718 36 5 sex (m:f) vs mites (y:n) female 608 39 6.4 chi sq. 0.96 0.38 0.01 0.005 0.79 total 1326 75 5.7 p 0.33 0.54 0.92 0.95 0.37 1998 male 311 17 5.5 female 273 11 4 total 584 28 4.8 sex (m:f) vs scars (y:n) 1999 male 252 14 22 5.6 8.7 chi sq. 1.91 0.34 38.42 female 329 22 42 6.7 12.8 p 0.17 0.56 0.0001 total 581 36 64 6.2 11 2000 male 115 7 23 6.1 20 females mites (y:n) vs scars (y:n) female 156 11 26 7.1 16.7 total 271 18 49 6.6 18.1 chi sq. 7.86 6.01 92.41 2001 male 966 57 75 5.9 7.8 p 0.005 0.01 0.001 female 1056 52 195 4.9 18.5 total 2022 109 270 5.4 13.4 males mites (y:n) vs scars (y:n) all yrs male 2362 131 120 5.6 9* chi sq. 1.47 8.63 2.35 female 2422 135 263 5.6 17.1* p 0.23 0.003 0.13 total 4784 266 383 5.6 13.3* *based on three-year totals

TABLE 2. Indices of aggregation comparing frequency distribution of two macrochelid mites species (M. muscaedomesticae (M.m) and M. subbadius (M.s.)) on stable flies, based on all five years’ data. k is a parameter of the negative binomial distribution. The numbers in brackets give the index value for Poisson and maximum clumping, n = number of individuals in sample (Ludwig & Reynolds, 1988). sex mite species indices VMR ( 1, n) IC ( 0, n-1) Green's (0, 1) k (infinity, 0) 1/k total M.m. 3.68 2.68 0.017 0.029 34.13 M. s. 14.11 13.11 0.033 0.012 86.88 male M.m. 4.1 3.1 0.03 0.034 29.24 M.s. 8.96 7.96 0.053 0.009 110.5 female M.m. 2.85 1.85 0.036 0.024 41.49 M.s. 17.18 16.18 0.065 0.015 68.97

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 11

FIGURE 5. Frequency distributions of phoretic Macrocheles muscaedomesticae and M. subbadius on female stable flies collected at the Warsaw site in 2001, with fitted negative binomial distribution.

TABLE 3. Number of flies, number of mites, and observed and expected frequency distributions, Poisson and negative binomial (obs., Pois. and neg. bin.) of total mites per flies and % flies with mites for each year. SD is standard deviation, CV is coefficient of variation.

year number frequency dist. mites/fly predicted % flies w mites increase flies mites obs. Pois. neg. bin. obs. Pois. neg. bin. (Pois./obs.) 1997 1326 147 75 139.1 75.01 5.7 10.49 5.7 1.84 1998 584 56 28 53.4 28 4.8 9.14 4.8 1.9 1999 581 80 36 74.7 36 6.2 12.9 6.2 2.08 2000 271 51 18 46.5 18 6.6 17.15 6.6 2.6 2001 2025 393 109 357.2 109.4 5.38 17.64 5.4 3.28 mean 957.4 145.4 53.2 134.2 53.3 5.73 13.46 5.74 2.34 SD 636.8 128.4 33.9 116.2 34.1 0.64 3.43 0.64 0.53 CV 66.5 88.3 63.8 86.6 63.9

Overall, phoretic mites from both species were found together more often than randomly expected on female stable flies (combined data all years, Yates corrected chi-square = 15.24, p < 0.0001), but not on males (Yates corrected chi-square = 1.64, p = 0.203) (Table 4). When analyzed by year, this was only seen in 2001, and not 1999 or 2000.

12 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 TABLE 4. Association (Jaccard Index) of M. muscaedomesticae and M. subbadius phoretic on stable flies, 1999 to 2001, at the Warsaw farm site. ‘both’ is the number of flies with both species present, observed and expected.

sex no. flies mites present expected chi sq. p Jaccard Index M.m. M.s. both both all years total 2877 79 75 9 2.57 14.55 0.0001 0.055 female 1544 51 28 6 1.26 15.24 0.0001 0.071 male 1333 28 47 3 1.16 1.64 0.203 0.038 results by year 1999 total 581 28 8 0 0.39 0.04 0.84 0 female 329 19 3 0 0.17 0.66 0.41 0 male 252 9 5 0 0.18 0.61 0.43 0 2000 total 271 12 5 1 0.29 0.17 0.68 0.056 female 156 9 1 1 0.13 1.17 0.28 0.091 male 115 3 4 0 0.1 1.6 0.21 0 2001 total 2025 39 62 8 1.62 22.53 0.0001 0.073 female 1059 23 24 5 0.77 19.2 0.0001 0.096 male 966 16 38 3 0.81 3.79 0.052 0.053 *significant chi-square [0.05] = 3.84, d.f. = 1; p values based on Yates corrected chi-square.

The proportion of female stable flies with either mites or, in the case of parous flies, mite scars, increased with RAC in all three years that mite scar data were collected (1999, 2000 and 2001; logistic regression parameters Table 5, Fig. 6). Based on ANCOVA, there was no difference between the years (1999 to 2001) in the relationship between RAC (covariate) and the proportion of females in that RAC that bore mites (Arcsin transformed, Sokal & Rohlf, 1996) (F(2,30) = 0.39, p = 0.68, untransformed means [adjusted means] and SD: mean1999 = 11.98% [12.03%], SD = 5%; mean2000 = 19.32% [19.02%], SD = 19.2%; mean2001 = 17.72% [17.95%], SD = 7.7%). When the data were weighted by the square root of the number in each RAC, ANCOVA returned a significant difference between years in the ‘RAC vs percent with mites’ lines (F(2,186) = 5.73, p = 0.004); that is, while the slopes of these lines were similar (test of parallelism: F(2,184) = 2.53, p =0.08; beta (overall slope) = 2 2.31, SE = 0.17, R = 0.50, F(1,186) = 186, p < 0.0001), their heights (i.e., intercepts) were different (Table 6).

TABLE 5. Logistic regression parameters y = exp(a+(b)*x)/(1+exp(a+(b)*x)); y = proportion of females with mites or scars, x = reproductive age class. Warsaw farm site data, 1999 to 2001. The bracketed numbers are the standard errors [SE], ‘number of flies’ were those with or without either mites or scars.

year a [SE] tp b [SE] tp number of flies R % variance with without 1999 -2.53 [0.39] 6.6 <0.001 0.17 [0.04] 3.7 <0.001 62 265 0.23 5.09 2000 -3.03 [0.89] 3.4 <0.001 0.24 [0.10] 2.4 0.018 34 123 0.25 6.06 2001 -2.62 [0.22] 11.8 <0.001 0.23 [0.03] 8.4 <0.001 235 823 0.3 8.96 all -2.59 [0.18] 14 <0.001 0.21 [.02] 9.4 <0.001 331 1211 0.27 7.45

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 13

TABLE 6. Linear equations: % flies with mites (arcsine transformed) = a + b*RAC, and backtransformed mean and adjusted mean % flies with mites per RAC. Mean RAC is mean ovarian age class of female stable flies with mites.

year ab backtransformed % w/mites mean RAC N mean adj. mean SD 1999 12.601 1.785 15.9 15.45 2.9 6.05 36 2000 6.989 2.943 18.2 17.55 7.2 6.11 36 2001 13.018 2.497 20.4 21.58 3.7 5.53 95

FIGURE 6. Reproductive age class distribution, plus fitted logistic and exponential lines, of proportion of female stable flies bearing mites or having mite scars caught with an Nzi trap at the Warsaw site in 2001. The numbers in each bar represent the sample size for the corresponding reproductive age class (RAC).

Using the pooled data from 1999 to 2001, we tested a linear and exponential regression model of RAC against the proportion of mites/RAC, with and without the weighted data (weight = square root of the number/RAC). There was a significant exponential regression (Model: y = a*exp(b*x): unweighted a = 0.022, b = 0.269, R = 0.73, R2 = 0.53; weighted a = 0.066, b = 0.465, R = 0.80, R2 = 0.64) (Fig. 6), which provided a slightly better fit to the data than a linear model (Model: y = a + b*x: unweighted a = -0.041, b =0.038, R = 0.63, R2 = 0.40; weighted a = 0.018, b = 0.032, R = 0.72, R2 = 0.52). The proportion of mited or scarred flies increased exponentially with RAC at the same rate each year, in spite of yearly differences in overall proportion of mited flies. Because the exponential regression (above) provided a better fit than the linear regression, we again tested whether there was an RAC-specific difference between the three years in the percent of females with mites or scars using ANCOVA. This time we used a logarithmic transformation of percent mites, ln(1+%mites/ 100)(weighted as above), with RAC as the covariate and year as the independent variable. Again,

14 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 there was a significant effect of year (F(2,186) = 4.52, p = 0.012; test of parallelism: F(2,184) = 0.46, p = 0.63, beta (overall slope) = 0.148, SE = 0.0146, R2 = 0.35, F(1,186) = 102, p < 0.0001; backtransformed mean % mites1999 = 13.4%, SD 1.46, adj mean1999 = 13.03%, covariate = 6.05, N = 59; mean2000 = 13.6%, SD 2.02, adj mean2000 = 13.12%, covariate = 6.11, N = 36; mean2001 = 17.21%, SD 1.2, adj mean2001 = 18.23%, covariate = 5.53, N = 95) (Fig. 7).

FIGURE 7. Proportions (left axis) and ln-transformed proportions (right axis) of stable flies in each age class from Nzi trap samples at Warsaw site in 1999, 2000 and 2001 bearing mites or mite scars. ANCOVA shows that the intercepts (a) of the fitted regression lines differ significantly by year, but the slopes (b) do not.

Fecundity and size Because fecundity is correlated with body size, the number of ovarioles per ovary was tested after being corrected for hind leg length, which was used as an index of body size. There was no difference in the average number of ovarioles per ovary between unmited and mited nulliparous females (F(1, 160) = 0.2, p = 0.66), nor between unscarred and scarred parous females (F(1, 141) = 0.10, p = 0.75) (mean number, [mean adjusted for leg length], SD; nulliparous: unmited 46.8 [44.5] SD = 8.86, n = 147; mited 42.8 [45.1] SD = 9.94, n = 16; parous: unscarred 47.1 [48.2] SD = 9.69, n = 99; scarred 49.75 [48.6] SD = 8.89, n = 46). The size was the same in nulliparous females with and without mites (F(1, 565) = 0.25, p = 0.62) and parous females with and without scars (F(1, 489) = 2.89, p = 0.08), based on the length of the hind legs (mean length mm, SD, nulliparous females: unmited 3.26 mm, SD = 0.72, n = 521; mited 3.20 mm, SD = 0.29, n = 46; parous females: unscarred 3.32 mm, SD = 0.212, n = 327; scarred 3.42 mm, SD = 1.02, n = 164).

Differences in age-specific survival The apparent survival (the sum of actual survival plus flies lost to the population through migration, called ‘survival’ hereafter) of female stable flies bearing mites was greater than the survival of unmited females for 1999, 2000, and 2001 (i.e., years that scar data were collected) (Table 7). The three-year mean survival rates for females from nulliparous to parous were: 0.753 for mited

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 15 and 0.477 for unmited flies, a difference of 0.276. The three-year mean survival rates of females from uniparous to multiparous was 0.644 for mited flies and 0.488 for unmited flies; a difference of 0.155. When these were apportioned into mean RAC-specific survival rates, survival through each of the six nulliparous RACs was 0.954 for mited flies and 0.882 for unmited flies. RAC-specific survival for each of the three uniparous and multiparous RACs was 0.863 for mited flies and 0.786 for unmited flies. The difference between mited and unmited survival rates was 0.072 per nulliparous RAC and 0.077 per uniparous RAC.

TABLE 7. Survival rates determined by proportion of yearly catch that are parous females. The difference in apparent survival between mited and unmited flies is the net difference in dispersal rates between these. Stages are uninseminated, inseminated, uniparous, biparous, nulliparous and parous (un, in, uni, bip, null and par).

stage no mites or scars with mites or scars total stable flies truck 1999 2000 2001 mean 1999 2000 2001 mean 1999 2000 2001 mean survival by RAC un-ins 0.86 0.9 0.82 0.86 0.94 0.95 0.92 0.94 0.87 0.91 0.84 0.87 0.88 ins-uni 0.89 0.94 0.89 0.91 0.97 0.98 0.98 0.97 0.91 0.95 0.92 0.93 0.85 uni-bip 0.83 0.77 0.76 0.79 0.87 0.87 0.85 0.86 0.84 0.8 0.79 0.81 0.79 null-par 0.88 0.92 0.85 0.88 0.95 0.96 0.95 0.95 0.89 0.93 0.88 0.9 0.87 survival by parity state un-ins 0.63 0.72 0.55 0.63 0.82 0.85 0.78 0.82 0.66 0.75 0.6 0.67 0.68 ins-uni 0.72 0.82 0.71 0.75 0.9 0.93 0.93 0.92 0.76 0.85 0.78 0.79 0.62 uni-bip 0.57 0.45 0.44 0.49 0.65 0.67 0.61 0.64 0.59 0.51 0.5 0.53 0.5 null-par 0.45 0.59 0.39 0.48 0.74 0.79 0.72 0.75 0.5 0.64 0.46 0.53 0.42 difference in survival rate by RAC by parity state 1999 2000 2001 mean 1999 2000 2001 mean un-ins 0.08 0.05 0.1 0.08 0.2 0.13 0.23 0.19 ins-uni 0.07 0.04 0.08 0.06 0.19 0.11 0.22 0.17 uni-bip 0.04 0.11 0.09 0.08 0.08 0.21 0.17 0.16 null-par 0.08 0.05 0.09 0.07 0.29 0.2 0.33 0.28

Truck trap samples In the one season it was run (2000), a total of 64 stable flies was caught in the truck trap; 26 males, 22 nulliparous females and 16 parous females. Forty-six of these stable flies (including 27 females) were caught on the weekly sampling route and 18 (11 female) on the daily route (Table 8a). The number of male and female stable flies trapped increased over the summer and the percentage of females became increasingly nulliparous (Table 8b). There was no effect of A/G (length of air column/ground distance) on sampling (ANOVA, F(1,185) = 0.05, p = 0.90). There was however, a significant effect of route section (route divided into three sections, from Fig. 3: north – segments 1 and 2; south – segments 3 and 4; lakeshore – segments 5, 6, and 7; F(2,28) = 6.82, p = 0.004) with more flies caught along Lake Ontario (lakeshore mean = 0.42 flies/km), than the other sections (north mean = 0.10 flies/km; south mean = 0.22 flies/km; north vs south, p = 0.33; south vs lakeshore p = 0.11; north vs lakeshore p = 0.003, Tukey’s HSD).

16 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 TABLE 8. Truck trap catches of stable flies summarized by route (a) and week (b). The data include both the weekly truck run and the week's total of daily sampling. Females are either nulliparous or parous (null and par).

a) results by section section females males null par 1 2 2 0 2 2 2 3 2 0 3 2 4 0 2 4 5 4 3 2 5 8 3 5 3 6 4 2 1 3 7 8 3 6 2 daily 7 5 5 2 b) weekly results week female male % male null par % null 14-Jun 0 0 0 0 0 0 21-Jun 0 0 0 0 0 0 28-Jun 0 0 0 0 0 0 05-Jul 0 0 0 0 0 0 12-Jul 0 0 0 0 0 0 19-Jul 0 0 0 0 0 0 26-Jul 2 2 50 1 1 50 01-Aug 2 0 0 0 2 0 10-Aug 2 2 50 1 1 50 16-Aug 0 2 100 0 0 0 21-Aug 0 2 100 0 0 0 30-Aug 4 3 42.9 1 3 25 05-Sep 7 5 41.7 5 2 71.4 13-Sep 5 1 16.7 4 1 80 20-Sep 4 7 63.6 2 2 50 27-Sep 2 1 33.3 1 1 50 03-Oct 7 1 12.5 5 2 71.4 10-Oct 2 0 0 1 1 50 17-Oct 1 0 0 1 0 100

Mite loads None of the stable flies caught in the truck trap bore mites. One uniparous RAC 7 female had four mite scars. The mean percentages of flies with mites at the four farms (Warsaw, dairy farms 1, 2, and 3) over the truck trapping period were respectively, for nulliparous females, 7.92%, 12.76%, 9.23%, 9.51% (overall mean = 10.5%), and, for males, 5.9%, 3.74%, 5.08%, 6.36% (overall mean = 5.06%) (data per farm, nulliparous females mited flies/total flies: 45/568, 84/723, 72/512, 166/1604; males 57/966, 55/1118, 44/546, 116/2322, respectively). Populations at the four farms increased over the summer, peaking around late summer–early autumn, and dropping with the onset of cold temperatures. At all four farms, the general trend was for the percentage of flies bearing mites to increase to a peak around mid summer dropping back in the fall (Figs. 8, 9). Truck trap numbers increased more slowly than catches at the three dairy farms, but more quickly than at the Warsaw farm (ln weekly farm catches – ln weekly truck trap catches) (Fig. 10).

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 17

FIGURE 8. Weekly means and standard deviations of the sticky trap catches at the three dairy farms, total number caught (above) and the percentage of stable flies with mites (bottom).

FIGURE 9. Weekly total of Warsaw beef farm Nzi trap catches (lines) and percentage (bars) of flies with either mites (nulliparous females and males) or mites and scars (parous females and total catch).

18 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 FIGURE 10. Differences between the number of stable flies caught each week in the truck trap (ln[n+1]) and the number of stable flies caught each week at the 3 dairy farms and 1 Warsaw beef farm. The differences were correlated with date, a positive correlation indicates that the farm populations increased more rapidly relative to the truck trap catches. No correlation was expected if the truck trap catches were simply proportional to the number of flies found in neighbouring populations.

Assuming that the truck trap randomly sampled the farm populations, the calculated probability [eq. (1)] that none of the 48 stable flies caught in the truck trap would carry mites was less than 0.02 (Table 9, using the proportions in App. 2). From the randomization analysis (App. 2), the probability of catching 26 males and 22 nulliparous females with no mites over the course of summer, if the truck trap had been sampling from the same population as the traps on the farms, was 154 in 10,000, or 0.014, based on the Warsaw farm proportions, and 199 in 10,000, or 0.018, based on the mean farm proportions from all three dairy farms.

TABLE 9. Probability of getting stable flies with no mites in the truck trap based on the proportion of flies with mites on neighbouring farms.

source of phoretic fly data number of flies in truck trap 3 dairy farms Warsaw farm mean males 0.266 0.164 0.215 26 females 0.071 0.092 0.082 22 total [m*f] 0.019 0.015 0.017 48

Demographic profile The demographic profile of female stable flies caught in the truck trap and the unmited population of the Warsaw beef farm population showed a declining percentage in each RAC (Figs. 11a, c) whereas in the mited population at the Warsaw farm a higher percentage of flies were caught in some of the later RACs (e.g., RAC 10) (Fig. 11b). Using the frequency distribution of flies per RAC, we compared the mean RAC of the truck trap population to that of the mited and unmited Warsaw farm

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 19 samples for 1999 to 2001. The mean RAC of the truck trapped flies was 5.82, slightly older than the mean 5.47 for flies without mites at the Warsaw site (5.54, 6.15, 4.72 for 1999 to 2001), though not significantly different. The mean RAC of mited flies at the Warsaw site, 7.52 (7.56, 7.91, 7.09 for 1999 to 2001), was significantly greater than either the mean RAC for the truck trapped flies or for unmited farm flies.

FIGURE 11. Frequency distribution of female stable flies per reproductive age class (a) without mites, (b) with mites at the Warsaw beef farm (Nzi trap catch totals 1999 to 2001), and (c) caught in the truck trap.

Survival rate of truck trapped flies The survival of truck trapped female stable flies was 0.421 from nulliparous to parous, and 0.50 from uniparous to multiparous. These translate to RAC-specific survival rates of 0.866 and 0.794 respectively when apportioned to the six nulliparous and three parous RACs (Table 7).

TABLE 10. Aggregation indices recalculated after varying the zero counts (i.e., flies with no mites) to mirror changes in local population due to population level differences in net migration of unmited flies. b is the multiplication factor used to multiply the observed zero counts (1031 unmited flies), where b = 2, 0.1, 0.01, and 0. Data from the 2001 Nzi trap catches at the Warsaw farm site, 1059 female stable flies, of which 58 were carrying M. muscaedomesticae.

flies without mites mites/fly aggregation indices b zeros mean variance VMR IC Green's k 1/k 1 1031 0.054 0.242 4.49 3.49 0.062 0.021 46.73 2 2062 0.028 0.123 4.52 3.52 0.063 0.011 94.34 0.1 103 0.435 1.802 4.14 3.14 0.056 0.22 4.52 0.01 10 1.5 4.689 3.14 2.13 0.04 5.84 0.17 0 0 2.036 5.295 2.60 1.60 0.029

20 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 Discussion

Phoresy and dispersal The evidence of a significantly lower rate of mite phoresy in the truck trap sample supports the hypothesis that phoretic mites inhibit dispersal of female stable flies. The apparent greater survival of mite-bearing female stable flies at the farm site further argues in favour of this hypothesis, since it is consistent with the predictions that mited flies would be less dispersive than mite-free flies. This decrease in dispersal of mite-bearing flies explains the greater average age (measured as RAC) of mite-bearing females on the farm sites based on nulliparous flies without mites being more likely to leave the farm than nulliparous flies with mites. The alternative explanation that mited flies live longer, seems unlikely since carrying mites must have an energetic cost as well as other possibly negative effects (e.g., to flight maneuverability). The simplest explanation is that mited females are underrepresented among dispersing stable flies because they do not disperse. This may be due to either reduced activity levels of mited flies in general, or reduced activity of mited flies in windy conditions due to the mites possibly affecting stable fly flight aerodynamics. To test this, we looked for evidence that stable flies with mites were less likely to be caught on windy days than on still days. In fact, on the Warsaw farm in 2001 there was a negative correlation (r = 0.27, t = 2.23, p = 0.029, n = 66) between mean daily wind speed (ln transformed) and the percentage of mite-carrying nulliparous females (arcsine transformed) (Fig. 12).

FIGURE 12. Correlation of mean hourly wind speed per day (7 am to 7 pm) vs percent of nulliparous stable flies caught carrying mites each day (arcsine transformed) at the Warsaw farm site, 2001.

Based on our hypothesis that mited flies disperse less than unmited flies, for the proportion of mited flies at the Warsaw farm to increase with RAC there must have been a dispersal deficit, with far more emigration than immigration of younger unmited flies. This is likely because the Warsaw farm site is largely isolated from other potential sources of stable flies. It is located in a region that is largely wooded, and is 6 km southwest of the nearest other farm with livestock. Prevailing winds from the west would have carried dispersing stable flies away from the Warsaw site. Most of the region around the Warsaw farm is poor stable fly habitat, and is either uncultivated or overgrown

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 21 with extensive wilderness areas to west, north and south. For less isolated sites, such as the dairy farms, the exchange of stable flies between local populations would mask the difference in survival rates and average age of mited and unmited females. This is the situation over much of the range of stable flies in North America - rural regions with most farms adjacent to one another. To measure the effect of phoresy on dispersal under these conditions would require identifying the natal location of stable flies through physical or genetic markers. Stable flies are commonly found in large numbers on coastal beaches (King & Lenert 1936, Hansens 1951, Jones et al. 1991) and lakeshores (Wang & Gill 1970, Newson 1977, Broce 1993), often after the passage of frontal weather systems (Voegtline et al. 1965, Williams 1973, Jones et al. 1999). Our results suggest that newly arriving stable flies on beaches would be expected to have lower mite loads than those in adjacent rural populations. This could account for Williams' (1976) observation of lower mite loads on stable flies on Florida beaches (1.7%) than on nearby farms (5.6%).

Estimating dispersal rates From the above discussion, because relatively few flies would have immigrated into the Warsaw site, and because truck trap results indicate that few to no mited flies emigrate, any difference in the apparent survival of mited and unmited female stable flies at the Warsaw beef farm site each year should provide a coarse estimate of RAC-specific dispersal rates of unmited flies, i.e., observed mortality in unmited flies represents actual deaths plus emigration, whereas in mited flies mortality represents deaths only. These values were calculated as 7.2% for each of RACs 1 to 6 and 7.7% for each of RACs 7 to 9, and 10 to 12. In other words, an average of 7.2% of female stable flies in RAC's 1 to 6, and 7.7% in RAC's 7 to 12, are estimated to emigrate from their natal sites.

Mite aggregation The aggregation indices all are consistent with an aggregated distribution of mites on stable flies (see App. 3 for a comparison of the indices and dispersal), evidence for a mite dispersal strategy that is characteristic of species living in temporally asynchronous and patchy habitats where density dependent dispersal with bet-hedging should apply. This is consistent with the biology of these mites. The similar size and fecundity of flies with and without mites supports a common habitat for both the mites and stable fly pupae. There appears to be only a slight tendency for both mite species to be present on the same female stable fly, this was only apparent in 2001 when more than 2,000 stable flies were sampled (Table 4). It is not known what selection pressure mites represent to their stable fly phorionts. While M. muscaedomesticae is an efficient predator of muscid fly eggs, which it actively hunts for and can find hidden below the surface (Perotti 2001), it is not known whether the mites leaving their female hosts when flies oviposit causes any net reduction in that female fly's offspring compared to female flies without mites. This may appear to be a reasonable conclusion since the detaching mites prey upon their phoriont's eggs, yet it is not known how many eggs escape predation since female stable flies deposit eggs in several locations. Indeed, the rapid increase in mite populations after detachment might actually benefit the original phoriont by eliminating eggs of other stable flies that are deposited after the mites colonize the oviposition site. Such a relationship exists between Necrophorus beetles and Poecilochirus necrophori mites, in which the latter consume fly eggs, reducing competition with immature beetle larvae (Springett 1968). Consequently, no generalizations can be made about the selective pressure of phoresy on stable flies outside of decreased dispersiveness. We found that mites attach to males at the same rate as they attach to females. This is curious because male stable flies do not return to oviposition sites, and restrict their activities to nectar feeding, mating and blood feeding. Consequently, mites attached to male stable flies are unlikely to

22 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 be carried to suitable new habitat. House flies are another important host species of phoretic Macrochelidae (Filipponi 1960). As is the case for stable flies, there is no difference between phoresy rates of M. muscaedomesticae on male and female house flies (Axtell 1964, Jalil & Rodriguez 1970), and mites were equally attracted to washes obtained from male and female pupae (Wicht et al. 1971). Rodrigueiro and Prado (2004), however, presented some evidence to the contrary in that they found a preference for female flies. The fact that male house flies return to manure to feed may be adequate for mite dispersal. While with stable flies there would seem to be a need for mites to distinguish the sex of their host, it may not be sufficient to enable mites to avoid male stable flies while continuing to disperse on male house flies. There are two important effects of an aggregated versus random mite distribution with respect to stable fly populations: 1) the percent of affected hosts is fewer and 2) variability in the percent of hosts infected in a population is lower. The variation within data sets with different means can be compared using the coefficient of variation (CV) (Sokal & Rohlf 1996). The CV of the number of mites over the five years, 88.3, was similar to the CV of 86.6 of the expected Poisson distribution, whereas the CV of the expected negative binomial was 63.9. The CV of the percent of mite-bearing flies, 11.14, was much lower than the expected Poisson CV of 25.5 (Table 3). Thus, local stable fly populations experience a relatively stable and predictable phoretic load (proportion of mite-bearing flies) in different years in spite of large variability in mite number. Similarly, the clumped distribution of mites means that the proportion of mite-bearing flies should be relatively constant across different populations. The stability of this mite load due to the clumped distribution means a more or less constant pattern of phoresy on stable fly dispersal across populations and in different years, with predictable patterns of seasonal variability in the percent of phorionts within local populations: low in spring, increasing through the summer and dropping again in the fall. See Glida et al. (2003) for an example of seasonally predictable patterns between dung beetles and macrochelid mites. The aggregation of both species of macrochelid mites means that mite phoresy presents a predictable selective pressure on stable flies and stable fly dispersal.

Density independence In temperate regions, stable flies occupy habitats that are both predictable and synchronous, with opportunities for colonization opening up each spring, and populations dramatically reduced each winter by low temperatures (Beresford & Sutcliffe 2009). This suggests that stable flies should adopt either a density-independent dispersal strategy or possibly an inverse density-dependent strategy in order to facilitate spring colonization. The real payoff in offspring in terms of founder effect comes with being a colonist early in the season, whereas mid-season immigrants would enter existing populations. Colonizing dispersal occurs within stable fly populations at low densities in spring and early summer (Beresford & Sutcliffe 2009). The effect of phoretic macrochelid mites on stable fly dispersal means that the increase in the proportion carrying phoretic mites during the summer would result in dispersal that is inversely density-dependent to a minor extent. From our dispersal rate estimate of 7.2 % of nulliparous females (above), if 10% of stable flies in a population were carrying mites by mid season, the dispersal rate would be reduced to 6.5% (0.072 * 0.9). The presence of mites in a habitat is indicative of that habitat's suitability for stable flies because they have partially overlapping habitat requirements. From the mite's perspective, it is advantageous to keep stable flies alive and local, freed from the mortality of dispersing. In temperate climates, the most important times for stable flies to disperse are at the beginning, to establish new populations, and possibly near the end of the summer to find suitable overwintering refuge habitats. Both of these times coincide with periods of low mite loads.

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 23

Acknowledgements

We are grateful to the dairy farmers of Ontario from Peterborough and Northumberland counties for allowing us access to their farms. This research was supported in part by a Natural Sciences and Engineering Research Council of Canada (NSERC) Research Grant to JFS and by an NSERC Graduate Fellowship to DVB.

References

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26 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 APPENDIX 1. Part 1. The following key uses the predictions to identify hypotheses: 1. If the % of truck trap female stable flies with mites < % Warsaw farm population female stable flies with mites, then the decreased dispersal hypothesis is supported 1. If the % of truck trap female stable flies with mites > % Warsaw farm population female stable flies with mites, then the increased dispersal hypothesis is supported 1. If the % of truck trap female stable flies with mites = > % Warsaw farm population female stable flies with mites, then the no effect of phoresy on dispersal hypothesis is supported.

Part 2. If mites reduce the survival of infested flies, the effect will tend to shift the predictions [<<, <, =, >, >>] to the right [<→=, =→> etc.], whereas if mites increase the survival of mited flies, the shift will be to the left [<→<<, =→< etc.]. For example, if mites reduce survival, then (from original → new predictions): net migration E>I EPs Nm>>Ps Nm=Ps Nm>Ps → → → if ii) then Nm>Ps Nm>>Ps NmPs → → → if iii) then Nm=Ps Nm>Ps Nm=Ps Nm>Ps Nm=Ps Nm>Ps

APPENDIX 2. Operationally, the randomization analysis was run by assigning rows in a spreadsheet as the series of weeks in the truck trap sampling program (each row represented one week). Each dispersant fly caught that week was represented by a cell in the row. For each cell, we generated a random number between 0 and 1. To represent the probability of the corresponding fly being mited, if that number was less than or equal to the probability of the non-dispersant farm-trapped sample of the same age and reproductive status having mites that week, the cell was assigned as 1 (a mite-bearing fly’, for example if there was an average of 0.12 females with mites at the dairy and beef farms that week, and the random number in a cell for that week was 0.105, then this ‘fly’ was considered mited). Otherwise, the cell was assigned as 0 (‘fly’ did not bear any mites). In each simulation, we did this for each dispersant fly based on when it was caught and obtained a total of all flies expected to bear mites. The 10,000 simulations were used to produce a distribution of outcomes which were then ordered from lowest to highest totals with mites. The probability of getting the actual truck trap results for the season was obtained as the total number of trials with the same number or fewer mite-bearing female flies than the observed number with mites divided by 10,000. The resulting figure represented the probability that the actual results could be accounted for by the proportions of mite-bearing female stable flies on farms. For example, if only two out of a seasonal total of 100 flies in the truck trap bore mites and 350 randomization trials scored two or less, the probability of getting two mite-bearing flies in 100 in the truck trap would be 350/10,000 = 0.035. This would mean the truck trap is sampling a significantly different stable fly population than that on the farms, one in which flies with mites are underrepresented and thus not dispersing. The randomization analysis was based on the change in the proportion p of flies carrying phoretic mites over the summer season for each sex, pf and pm. The daily farm proportions were smoothed using a 10 day moving average to minimize the effect of small trap catches on any particular day. Thus, at the Warsaw farm for example, on August 1 pf = 0.007 and pm = 0.0215. Each of the 48 flies (26 males and 22 nulliparous females) was assigned a cell in a row of the spreadsheet, fly1, fly2 etc. and a random number, m, between 0 and 1 generated in each cell. Mites were assigned to flies based on these proportions: for example for fly1 on date t, if m <= pf, then fly1 = 1; if m > pf , then fly1 = 0. The sum of the row of 48 cells representing the 26 males and 22 nulliparous females indicated the number of flies carrying mites in that trial (first table). This was repeated to produce 10,000 trials, so that the number of zero scores out of 10,000 was the probability of finding 48 flies with no mites. The proportions used for both randomization and the calculation of probability [from eq. (1)] are in the second table (note that the beef farm is the Warsaw site sampled with the Nzi trap, and dairy farm numbers are based on the mean of three farms sampled with sticky traps).

BERESFORD & SUTCLIFFE: MITE PHORESY AND STABLE FLY DISPERSAL 27

Sex Fly # % flies with % flies with- Probability calculation mites out mites dairy beef dairy beef dairy beef male 1 0.067 0.15 0.933 0.85 0.933 0.850 male 2 0.067 0.15 0.933 0.85 0.870 0.723 male 3 0.067 0.042 0.933 0.958 0.812 0.692 male 4 0.067 0.035 0.933 0.965 0.758 0.668 male 5 0.067 0.02 0.933 0.98 0.707 0.655 male 6 0.067 0.02 0.933 0.98 0.660 0.641 male 7 0.067 0.022 0.933 0.978 0.615 0.627 male 8 0.067 0.033 0.933 0.967 0.574 0.607 male 9 0.012 0.088 0.988 0.912 0.567 0.553 male 10 0.012 0.088 0.988 0.912 0.560 0.505 male 11 0.012 0.088 0.988 0.912 0.554 0.460 male 12 0.032 0.096 0.968 0.904 0.536 0.416 male 13 0.032 0.096 0.968 0.904 0.519 0.376 male 14 0.032 0.096 0.968 0.904 0.502 0.340 male 15 0.032 0.096 0.968 0.904 0.486 0.307 male 16 0.032 0.096 0.968 0.904 0.471 0.278 male 17 0.038 0.047 0.962 0.953 0.453 0.265 male 18 0.058 0.049 0.942 0.951 0.427 0.252 male 19 0.058 0.049 0.942 0.951 0.402 0.239 male 20 0.058 0.049 0.942 0.951 0.378 0.228 male 21 0.058 0.049 0.942 0.951 0.357 0.217 male 22 0.058 0.049 0.942 0.951 0.336 0.206 male 23 0.058 0.049 0.942 0.951 0.316 0.196 male 24 0.058 0.05 0.942 0.95 0.298 0.186 male 25 0.026 0.063 0.974 0.937 0.290 0.174 male 26 0.085 0.059 0.915 0.941 0.266 0.164 female 27 0.014 0 0.986 1 0.986 1.000 female 28 0.014 0.01 0.986 0.99 0.972 0.990 female 29 0.005 0.228 0.995 0.772 0.967 0.764 female 30 0.143 0.137 0.857 0.863 0.829 0.660 female 31 0.143 0.137 0.857 0.863 0.710 0.569 female 32 0.143 0.137 0.857 0.863 0.609 0.491 female 33 0.143 0.137 0.857 0.863 0.522 0.424 female 34 0.143 0.137 0.857 0.863 0.447 0.366 female 35 0.122 0.064 0.878 0.936 0.393 0.342

28 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23 female 36 0.122 0.064 0.878 0.936 0.345 0.321 female 37 0.122 0.064 0.878 0.936 0.303 0.300 female 38 0.122 0.064 0.878 0.936 0.266 0.281 female 39 0.116 0.146 0.884 0.854 0.235 0.240 female 40 0.116 0.146 0.884 0.854 0.208 0.205 female 41 0.116 0.163 0.884 0.837 0.184 0.171 female 42 0.067 0.16 0.933 0.84 0.171 0.144 female 43 0.133 0.073 0.867 0.927 0.148 0.133 female 44 0.133 0.073 0.867 0.927 0.129 0.124 female 45 0.133 0.073 0.867 0.927 0.112 0.115 female 46 0.133 0.073 0.867 0.927 0.097 0.106 female 47 0.133 0.051 0.867 0.949 0.084 0.101 female 48 0.148 0.089 0.852 0.911 0.071 0.092

Truck trap:date Number caught Proportion on farms with mites males nulliparous males nulliparous females females dairy beef dairy beef 26-Jul 2 1 0.067 0.15 0.014 0 03-Aug 1 0.067 0.031 0.014 0.01 06-Aug 1 0.067 0.042 0.014 0.014 10-Aug 1 0.067 0.035 0.014 0.01 16-Aug 2 0.067 0.02 0.014 0.043 18-Aug 1 0.067 0.022 0.014 0.073 21-Aug 1 0.067 0.033 0.014 0.128 30-Aug 3 1 0.012 0.088 0.005 0.228 05-Sep 5 5 0.032 0.096 0.143 0.137 13-Sep 1 4 0.038 0.047 0.122 0.064 20-Sep 6 2 0.058 0.049 0.116 0.146 21-Sep 1 0.058 0.048 0.116 0.163 22-Sep 1 0.058 0.05 0.116 0.188 28-Sep 1 1 0.026 0.063 0.067 0.16 03-Oct 4 0.057 0.1 0.133 0.073 04-Oct 1 0.057 0.109 0.133 0.051 10-Oct 1 0.085 0.059 0.148 0.089 11-Oct 1 0.085 0.046 0.148 0.08

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APPENDIX 3. If we assume no dispersal for mited flies, we wanted to know how changes in the proportion of mite-free flies would affect the various indices used to measure aggregation: i.e., any change in the dispersal of mite-free flies within a population would affect both the frequency distribution and the mean number of mites/fly. Such a change would occur through the immigration of mite free flies which would increase the proportion of zero counts, or through emigration of mite free flies which would lower the proportion of zero counts within a population. To assess this, we changed the frequency of zero counts and recalculated the aggregation indices. This is a different question to whether the aggregation index is independent of sample size (the normal line of inquiry in assessing indices, for example, Myers 1978). The concern here is how well an index performs with changes in the number of non-mited flies (or zero counts) due to immigration and/or emigration. Depending upon the index, any comparison of aggregation across different farms or years would be affected by differences in net migration. In 2001, 1059 females, of which 28 bore M. muscaedomesticae only, were caught at the Warsaw site. Thus, 1031 bore no (zero counts) and 28, or 2.64%, bore M. muscaedomesticae only. The result of changing the zero counts is summarized in Table 10. We found a similar pattern of results with M. subbadius. The largest changes were with the negative binomial statistics k and 1/k, while the indices based on the mean and variance (VMR, IC and Green's) changed the least. More importantly, the VMR indices were stable when the zero frequency ranged from as little as 10% to double the observed number of flies with no mites. While both the VMR and k varied with changes in the mean number of mites per fly, VMR changes were largely at the decimal level whereas k changed in order of magnitude. At very low number of zero counts, the iterative method of calculating k (Krebs 1989) did not converge (the negative binomial distribution approaches the Poisson as k approaches infinity, see Hilborn & Mangel 1997). Therefore, as an indicator of aggregation the VMR and its derivatives appear to be robust and resistant to changes in the frequency of non-mited flies which accompany both immigration and emigration.

30 SYSTEMATIC & APPLIED ACAROLOGY SPECIAL PUBLICATIONS (2009) 23