- Email: [email protected]
Sheep blowfly strike: a model approach
Research in Veterinary Science 2000, 69, 1–9 doi:10.1053/rvsc.2000.0383, available online at http://www.idealibrary.com on
REVIEW
Sheep blowfly strike: a model approach R. WALL*, N. P. FRENCH†, A. FENTON‡ School of Biological Sciences, The University of Bristol, Woodland Road, Bristol, BS8 1UG, UK, †Department of Veterinary Clinical Science and Animal Husbandry, University of Liverpool, Leahurst, Neston, L64 7TE, UK and ‡Institute of Biological Sciences, University of Stirling, Stirling, FK9 4LA, UK
OVINE cutaneous myiasis is a familiar and widespread disease of sheep in Britain (French et al 1992) and many other areas of the world (Hall and Wall 1995). The primary agent of sheep strike throughout most of northern Europe is the ‘greenbottle’ blowfly, Lucilia sericata (Meigen) (Diptera: Calliphoridae) (MacLeod 1943a, Wall et al 1992a). The same species is also responsible for myiasis of rabbits and occasionally other, usually debilitated, domestic and wild animals (Hall and Wall 1995). Although blowfly strike has been the subject of extensive investigation over many years, a number of more recent studies have been able to bring new insights into the ecology and epidemiology of this disease, particularly through the use of a theoretical, model-led approach. In this work, a series of models have been developed that simulate the seasonal pattern of fly abundance (Wall et al 1992b, 1993a,b) and sheep myiasis on farms in Britain (French and Morgan 1996a, Fenton and Wall, 1997, Fenton et al 1997, 1998a,b). The models are based on two sub-components. The first simulates the seasonal pattern of abundance of L sericata. The second uses the range of key factors known to influence ewe and lamb susceptibility, to estimate the proportion of a flock at risk from strike. The development and application of these models have allowed the relative importance of the various factors that determine the observed pattern of blowfly abundance and strike incidence to be assessed. They have also allowed deficiencies in the available knowledge to be identified, enabling experimental work to be directed more appropriately. However, perhaps of greatest importance, is the fact that the models developed are beginning to provide a valuable tool through which the potential effects of a range of sheep and strike management options may be explored. The aim of this paper is to review briefly the development of these models, their key findings and highlight their potential value in the future.
properties of particular systems to be made and allow computer-based experiments of control strategies. Simulation models of biological systems may, however, become complex relatively quickly and their construction does require detailed life-history information. The blowfly life-cycle Adult female L sericata lay eggs in the wool of sheep close to the skin surface, selecting areas of high humidity, such as fleece or skin soiled by faeces or bacterial infection (Davies 1948a, Cragg 1955). After hatching, the maggots pass through three stages, feeding on the epidermal tissues and skin secretions (Evans 1936). After about 72 hours, when they have completed feeding, the third stage larvae drop to the ground where they undergo a period of dispersal. The larvae then burrow into the soil before pupariating. Newly emerged adults mate, protein-feed and, after their ovaries have fully matured, females seek-out a suitable oviposition site on a host animal (Fig 1). At each oviposition each female deposits about 200 eggs in a single egg batch (Wall 1993). Cycles of oviposition and emergence can continue throughout the spring and summer but, as the temperature and photoperiod decline in autumn, females produce larvae that cease development mid-way through the wandering phase and burrow into the ground where they overwinter as diapausing larvae (Davies 1929).
Temperature-dependent development and mortality rates
Eggs
Larvae
Pupae
Adults
BLOWFLY MODEL SUB-COMPONENT Oviposition / blowfly strike
In the work reviewed here a simulation approach was adopted; simulations are often of more practical use than analytical models since they allow predictions about the *Corresponding author.
0034-5288/00/040001 + 09 $35.00/0
FIG 1:
Schematic representation of blowfly life-cycle model sub-component.
© 2000 Harcourt Publishers Ltd
R. Wall, N. P. French, A. Fenton
2
Blowfly development and mortality rates The first step in the construction of the blowfly strike simulation models reviewed here was the quantification of the rate at which the life cycle could be completed and the mortality of adults and larvae during its completion. The development rates of insects are determined primarily by the temperature of the environment to which they are exposed (Beck 1983, Wagner et al 1984, Higley et al 1986). As a result, the majority of insect population models attempt quantitatively to extrapolate the population growth rate from available temperature data (Atzeni et al 1994). One of the most commonly used methods involves the calculation of day degrees. This technique assumes that development rate is directly proportional to temperature above a minimum threshold, the base temperature, and that below this threshold no development occurs (Moon 1983, Preuss 1983). The exact nature of the temperature–development rate relationship differs between species and between life-cycle stages within a species. The relationship was determined for L sericata by rearing individuals of different stages under a range of constant temperatures. The rate of development at any temperature was then calculated as the reciprocal of the time taken for 50 per cent of the individuals to complete development at that temperature. A plot of these development rates against temperature showed an approximately linear relationship at the middle temperature range. By linear regression, this portion was extrapolated to where it intercepted the x-axis, giving an estimate of the base threshold temperature for that stage. The base threshold temperatures for development of pre-adult stages and ovary maturation by adult females of L sericata were calculated to be around 9°C and 11°C respectively (Wall et al 1992b; Table 1). The difference between the base temperature and the ambient temperature multiplied by the time taken to complete any life-cycle stage at that temperature, gives the number of day degrees required for complete development of that stage. The number of day degrees required for each stage of the L sericata life-cycle are shown in Table 1. Once the base-temperature and number of day-degrees above this threshold required for development are known, it is possible to calculate the likely development time of a given life-cycle stage at any temperature. Adult mortality rates for L sericata were calculated through examination of the age-structure of populations in the field. The determination of the age of individual flies is problematic, but was achieved using analysis of the known temperature-dependent rate of ovarian development (Wall 1993) in conjunction with either analysis of head-capsule pteridine levels (Wall et al 1991) or analysis of the rate of TABLE 1: Day-degree requirements (±SE) and base threshold temperatures (±SE) for completion of pre-adult life-cycle stages and adult egg batch maturation (from Wall et al 1992b) Life cycle stage
Day-degree requirement (±SE)
Base temperature (°C) (±SE)
Post-diapause larvae Larval wandering stage Pupation First egg batch Subsequent egg batches
29·7 (0·3) 45·6 (5·1) 126·1 (3·7) 62·0 (2·3) 27·7 (0·9)
9·2 (0·1) 9·5 (0·6) 8·8 (0·7) 11·2 (1·3) 11·1 (0·7)
wing-margin damage (Hayes and Wall 1998, 1999). These studies showed that the typical mortality rate is about 2 per cent per day-degree, giving a mean life expectancy of about 50 day-degrees, above a threshold of 11°C. This equates to a mean life expectancy of about 4 or 5 days at average British summer temperatures. Larval mortality rates in the field have proved harder to quantify but, based on trials in which sheep were infested with known numbers of first stage L sericata larvae and third stage larvae then collected and counted (R. Wall, unpublished data), a standard rate of 50 per cent mortality between egg deposition and adult emergence from the puparium is used in the simulation models described here. No allowance has been made in these models for the possibility that L sericata could emerge from carrion. Three lines of evidence support this and indicate that carcasses are unlikely to play an important role in maintaining L sericata populations. The carcasses of small mammals and birds occur largely in hedgerows and woodland. Experimental studies have demonstrated that L sericata on the other hand is almost totally absent from shaded habitats and appears to be strongly confined to open sunny areas (Smith and Wall 1997a). Hence, a carcase lying in woodland is highly unlikely to become infested with L sericata. If it does, however, these L sericata larvae are likely to experience intense competition from the larger, more abundant, shade-loving species of blowflies (Calliphora spp.) (Smith and Wall, 1997b). Small carcasses in open fields could become infested with L sericata, but usually get removed very quickly by scavengers such as foxes, badgers, dogs, cats or birds, before this happens. Large carcasses, such as sheep, could form an important breeding site for L sericata, but leaving dead sheep to decompose in open pasture is not common on lowland farms in the UK. Were lowland sheep farmers to adopt the practice of leaving dead sheep to decay in fields, this would almost certainly lead to a significant increase in L sericata abundance. Finally, it has been shown that if every sheep in an area is treated with a larvicide (cyromazine) early in the year, so that the first blowfly generation of the year is killed, it is possible to largely eliminate the entire L sericata population for an extended period (Wall et al 1995). This would not be possible if significant numbers of L sericata were emerging from carcasses. Domestic pet rabbits are commonly infested by blowfly, however, no routinely infested wild hosts have ever been identified (Hall and Wall 1995). Blowfly model operation In spring, as the temperatures increase, the models assume that a new cohort of L sericata emerges as adults. Daily temperatures are then used to allow the cohort to accumulate day-degrees or day-degree fractions (Fenton et al 1997) and to calculate the mortality schedule. Eventually, when sufficient day-degrees have been accumulated the surviving females of this first cohort oviposit, laying 200 eggs each (Wall et al 1993a,b, Fenton and Wall 1997, Fenton et al 1997), half of which are female and half male. Egg hatch and the larval feeding stages, which occur on the sheep, are allowed 3 days for completion, based on laboratory studies (Wall et al 1992b) and field observations. This period is maintained as a constant since in the protected
Sheep blowfly strike: a model approach
3
1
Ewe and lamb susceptibility
Faecal soiling
Pasture worm burden FIG 2:
Fleece length
Relative humidity
Pasture worm count
Oviposition / blowfly strike
0.8 0.6 0.4 0.2 0
Rainfall
Schematic representation of the sheep strike model sub-component.
microhabitat of the fleece, the rate of development of these stages is relatively independent of ambient temperature. Once the larvae are fully developed and have wandered off the host, once again, daily temperature is used to allow larvae and pupae to accumulate day-degrees and estimate the time required to complete development, prior to emergence of the next generation of adults. This continues on a daily basis throughout the year until, to simulate the effect of induced diapause, the larvae of females ovipositing towards the end of the season are assumed to enter diapause. Deterministic and stochastic forms of this blowfly model have been developed (Fenton et al 1997). The deterministic version assumes that all the individuals are identical, whereas the stochastic version allows for variation between cohorts in day-degree requirements. The stochastic model uses a Monte-Carlo simulation technique to assign random development rates to each life-cycle stage generated from a Weibull distribution fitted to observed variation in development rate for each stage.
SHEEP MODEL SUB-COMPONENT In reality, the incidence of strike will not be related simply to the abundance of flies but will also be associated with a range of factors that promote susceptibility to oviposition and larval survival on the host (French et al 1995). In the second component of the model, therefore, the number of susceptible sheep present each day is calculated by generating patterns of susceptibility throughout the season, based on a combination of the factors known to influence the occurrence of strike (Fig 2). Separate susceptibility patterns are generated in the model for ewes and lambs. Faecal soiling Faecal contamination of the fleece is the major predisposing factor for blowfly strike by L sericata in Britain (French et al 1995, French and Morgan 1996b). Such contamination both attracts oviposition (Ashworth and Wall 1995) and raises and maintains fleece humidity to levels suitable for egg hatch and larval survival (Watts and Perry 1975, Watts and Marchant 1977). In the models reviewed here the pat-
0
30
60 90 Time (day number)
120
150
FIG 3: Hypothetical pattern of relative exposure of sheep endoparasitic nematodes throughout the season used in blowfly strike simulation models (derived from Michel 1976). Day 1 is the 1st May.
terns of faecal contamination used are based on two of the factors which influence wool soiling: the consistency of the faeces and wool length (Fig 2). The model assumes that helminth parasites are the predominant cause of diarrhoea in sheep, particularly in firstseason grazing lambs. Hence, to incorporate the effects of changes in faecal consistency on sheep susceptibility, the models use simple relationships based on recorded patterns of the number of infective larvae of endoparasitic helminths of sheep typically present on pastures over a season (Boag and Thomas 1971, Cornwall 1975, Michel 1976). This is an obvious oversimplification, which it is hoped may be addressed in future versions of the model; addition of the effects of daily ambient temperature and humidity for example on worm abundance and infectivity might be included. The faecal consistency of ewes and lambs each day is assumed to be linearly related to the predicted abundance of infective helminth larvae (Fig 3). A separate weighting factor is given for lambs and ewes to produce a daily index of faecal consistency for each group of sheep. These weighting factors are derived from observed differences in the monthly prevalence of breech strike between lambs and ewes (French et al 1995), which is assumed in the model to reflect the relative likelihood of diarrhoea in response to helminth infections of the two groups of sheep. In addition, observed levels of faecal soiling are considered to be dependent on the length of fleece around the breech area. It is assumed that longer fleeces are associated with higher levels of faecal soiling. The model gives each animal a relative wool length score related to time of year (Fig 4) and may incorporate shearing for ewes. In the standard model, ewes are considered to have been sheared on the 25th of May (Fig 4). Hence, in the model, each day the index of faecal consistency is weighted by the relative wool length score to give the resulting degree of faecal contamination (described as the dag score) expected. Fleece humidity Although the majority of strikes occur in the breech region, strikes are also observed on other areas of the sheep, independent of any influence of faecal soiling (French et al
R. Wall, N. P. French, A. Fenton
4
90
0.8
0.6
Relative humidity (per cent)
Wool length score
Ewes Lambs
0.4
0.2
80 70 60 50 40 30 20 10
0 0
30
60 90 Time (day number)
120
150
FIG 4: Hypothetical seasonal patterns of relative fleece length scores for ewes and lambs used in blowfly strike simulation models. Day 1 is the 1st May and ewes are sheared on the 25th May.
1995). The importance of fleece humidity on the occurrence of these body strikes has been demonstrated in several studies (Davies and Hobson 1935, MacLeod 1940, Davies 1948a,b). Fleece length plays an important role in determining fleece humidity and a reduction in the susceptibility of ewes to attack following shearing has been recorded (Davies and Hobson 1935, MacLeod 1943b). Fleece humidity typically ranges from around 30 to 65 per cent, only rising to over 70 per cent following periods of prolonged wetting (Davies and Hobson 1935, MacLeod 1940, Davies 1948b). To simulate the humidity component of susceptibility, it is assumed that, in the absence of rain, there is a positive linear relationship between fleece length and fleece relative humidity ranging from a base level of 30 per cent for the shortest fleece up to 65 per cent for the longest (Fig 5). Each sheep is assigned a fleece baseline humidity score, determined by the previously calculated relative wool length score. The baseline fleece humidity index is then weighted to account for the effects of rain on any one day, the weighting being dependent on the amount of rain judged to have fallen (Fenton et al 1998a). Immediately following oviposition eggs and first stage larvae are highly susceptible to desiccation due to low fleece humidity levels; relative humidities of at least 60 per cent are required for egg hatch and development at the temperatures experienced in the fleece (Davies and Hobson 1935, Davies 1948a,b). Hence, in the simulation, each day the calculated fleece relative humidity index is used to determine the proportion of egg batches laid the previous day that fail to develop. At fleece humidities of less than 60 per cent all existing unhatched egg batches are assumed to desiccate. Humidities of greater than 80 per cent are considered to be sufficiently moist to allow full development of all egg batches laid (Davies and Hobson 1935, Davies 1948a). For relative humidities between 60 and 80 per cent a linear change in egg/larval mortality between 0 and 100 per cent is assumed (Fenton et al 1998a). Modelling sheep susceptibility In the models, the prevalence of susceptibility of lambs and ewes is related to faecal soiling and fleece humidity by a logistic function. In this function, the odds ratios for the
0
0.2
0.4 0.6 Wool length score
0.8
1
FIG 5: The relationship between the relative fleece length score and the baseline relative humidity of the fleece used in blowfly strike simulation models.
Temperature-dependent development and mortality rates
Larvae
Eggs
Pupae
Adults
Oviposition / blowfly strike Negative binominal aggregation
Temperature dependent oviposition activity
Ewe and lamb susceptibility
Faecal soiling
Pasture worm burden
Fleece length
Relative humidity
Rainfall
FIG 6: Schematic representation of the structure of the complete blowfly and sheep myiasis simulation model.
contribution to susceptibility of faecal soiling and relative humidity are derived from the studies of French et al (1996) and Eismann (1988), respectively. The number of susceptible ewes (NE) and susceptible lambs (NL) present at the start of each day is estimated as the proportion of ewes and lambs that is susceptible, multiplied by the total number of ewes or lambs present in the flock.
THE FULL MODEL In the full model, the blowfly and sheep susceptibility components are brought together (Fig 6). Each day, the fly component of the model calculates the number of gravid females present while the logistic component of the model estimates the number of susceptible ewes and lambs available at the start of each day. The model assumes that each adult female blowfly is able to oviposit on the day it
Sheep blowfly strike: a model approach
5
becomes gravid. Hence, the total number of ovipositions (Ot) on any one day is equal to the number of gravid females present on that day. Individual ovipositions are assigned to ewes (OE) and lambs (OL) proportionately, according to the ratio of the number of susceptible sheep of that category to the total number of sheep in the flock, that is OE=NE/(NE+NL).Ot, and OL= NL/(NE+NL).Ot. Hence, if there are no susceptible lambs, all ovipositions will occur on ewes; if there are no susceptible ewes, all ovipositions will occur on lambs. Two other factors also need to be incorporated into the final model: the distribution of strikes between the susceptible sheep and the effects of temperature of fly oviposition activity.
a season. In an average year three or four generations would be expected (Fig 7). The output of the stochastic model predicts the emergence of generations which are less distinct, with individuals of each generation present both earlier and later than the predictions of the deterministic model (Fig 7). The distinction between generations is further eroded by the addition of temperature-dependent variation in activity. Comparison of the patterns of fly abundance generated by the models with those seen in the field, indicates that the model provides a good description of the changes in fly numbers over time (Wall et al 1993a).
Aggregation
The model indicates that under average spring/summer climatic conditions, when the first female blowflies of the season are ready to oviposit, the majority of the oviposition sites available are present on ewes, due to their full length fleeces (Fig 8). The long fleeces provide areas of high humidity suitable for the development of eggs and larvae. At this time lamb fleeces are still short and faecal soiling is still at a low level. Hence, the first cases of strike are predicted to occur approximately equally on ewes and lambs (Fig 8). Since the blowfly population is in the early stages of development, the incidence of strike is limited by the low number of flies present at the start of the season, and not by the number of susceptible sheep present. In the standard simulation the ewes are sheared on the 25th of May. Towards the end of June, ewe and lamb susceptibility are approximately equal, prior to lamb faecal soiling increasing. Hence, the second generation of blowflies again tends to oviposit equally on lambs and ewes (Fig 8). By late July, however, lamb faecal soiling is at its peak, as is lamb fleece length, while ewe faecal soiling is low although ewe fleece has regrown. Therefore, the third generation of female L sericata oviposit preferentially on lambs rather than ewes. Towards the end of the season, although lamb faecal soiling has declined, it is still greater than that of the ewes. Hence, the final generation of L sericata again tends to oviposit more on lambs than ewes. Comparison of the patterns of strike incidence generated
Fly activity Finally, the number of ovipositions that can occur on any one day is a function of the number of gravid adult females present and the effects of ambient temperature on fly oviposition activity. Trapping and mark-release-recapture studies have shown that adult L sericata are more active and more likely to be caught on warmer days (Wall and Smith 1997). Hence, in the model, each day, the proportion of the female L sericata present that are deemed to be able to oviposit is calculated from a known linear relationship between activity and temperature (Wall and Smith 1997). On days when mean temperature is less than 13°C, none of the flies present are considered to be sufficiently active to oviposit (Fig 6).
MODEL OUTPUT AND VALIDATION Blowfly abundance The output from the model predicts that the adult L sericata emerge in relatively discrete waves, with fly numbers increasing exponentially with each wave over the course of
1000
Number of flies
Blowflies tend to be aggregated in their distribution in the field (Wall et al 1992c) and myiases, like most parasitic infections, tend to be distributed among hosts in a non-random manner affecting some sheep more than others (Wardhaugh and Dalwitz 1984, Fenton et al 1999a,b). In the models reviewed here it has been assumed that strikes occur among the susceptible sheep in the flock according to a negative binomial distribution. Each day, the number of oviposition events occurring on ewes (OE) and lambs (OL), and the number of susceptible ewes (NE) and susceptible lambs (NL) are known. Hence, the mean numbers of ovipositions per susceptible ewe (ME) and lamb (ML) are ME = O E/NE and ML = OL/NL. As a result, the proportion of ewes and lambs with 0,1,2 … strikes can then be calculated according to the negative binomial distribution with parameters x, k and the appropriate mean. The proportion of the susceptible flock uninfected (u) is given as the zero term in the negative binomial, so the proportion of the flock infected (i) is 1 – u. Therefore, the number of ewes or lambs carrying ovipositions at the end of each day is the appropriate value of i multiplied by the total number of susceptible sheep in that group (Fig 6).
Sheep susceptibility and strike incidence
100
10
1 0
40
80 120 Time (day number)
160
FIG 7: The number of Lucilia sericata predicted to be present and available for capture by deterministic (dashed line) and stochastic simulation models (solid line) under representative British temperature and rainfall conditions. Day 1 is the 1st May.
R. Wall, N. P. French, A. Fenton
6
7
Ewes Lambs
6
1.2 Incidence of strike
Monthly incidence
1.5
0.9 0.6 0.3
Ewes Lambs
5 4 3 2 1
0 May
July June
September August October
0 May
June
July
Aug
Sept
Oct
Month of year FIG 8: The expected monthly incidence of strike in ewes and lambs as predicted by a deterministic simulation model under representative British temperature and rainfall conditions.
by the models and described above with those seen in the field (French et al 1995), again indicates that the model provides a good description of the changes in strike incidence over time (Fig 9).
FIG 9: The observed monthly incidence of breech strike per 1000 animals (with 95 per cent confidence intervals) in ewes and lambs in England and Wales in 1991. From French et al (1995).
TABLE 2: Effect of changes in shearing date on the incidences of strike occurring on ewes, lambs and both sheep types, expressed as a percentage change in the incidence from the appropriate standard reference run. In the standard reference run: day –30 = 25th April, –20 = 5th May, –10 = 15th May, ewes are sheared on the 25th of May, day +10 = 4th June, +20 = 14th June and +30 = 24th June Ewe strikes
EFFECTS OF SHEEP MANAGEMENT To explore the effects of different farm management strategies on the incidence of blowfly strike, a number of parameters such as shearing date or worm control may be varied independently in the model, in association with changes in weather conditions. Effects of shearing date To investigate the possibility that the appropriate timing of ewe shearing might lead to a reduction in the seasonal incidence of strike, due to increased egg-batch desiccation, the date of shearing in the model was varied by up to one month either side of the standard reference date used, which is the 25th of May (Table 2). The simulations run under wet spring conditions show that the earliest shearing date examined (26th April), results in a greater incidence of ewe strikes (Table 2). The explanation for this result is that although early shearing coincides with the oviposition by the first generation of flies, the spring rains prevent egg-batch desiccation. Therefore, there is no increase in mortality through egg desiccation. In addition, early shearing allows ewe fleeces to regrow to full length by mid-July, when there is a substantial increase in endoparastic worm burdens. The interaction of these factors leads to a large increase in ewe susceptibility and, consequently, ewe strikes. Conversely, later shearing, although not affecting eggbatch survival in the first generation, does not allow enough time for ewe fleeces to reach maximum length by the time of the peak in worm abundance. Hence, fewer ewes are susceptible and there is a corresponding decrease in ewe strikes each month (Table 2). Furthermore, under the late shearing strategy, the low summer rains, combined with the relatively short ewe fleeces results in many of the second and third
Lamb strikes
Ewes and lambs
Warm, wet spring Shearing –30 –20 –10 +10 +20 +30
13·71 9·92 5·73 –10·22 –22·04 –27·37
–5·07 –3·20 –1·29 0·40 –1·70 –0·15
3·47 2·76 1·90 –4·43 –10·94 –12·52
Warm, dry spring Shearing –30 –20 –10 +10 +20 +30
43·97 –19·23 –44·06 –13·46 –29·98 7·87
19·86 –23·13 –41·74 –1·32 –9·48 34·08
30·55 –23·07 –42·77 –6·71 –18·57 22·45
generation egg batches desiccating. For lambs, in the wet spring, changes in ewe shearing date appear to have relatively little effect on the incidence of strike (Table 2). In general, the effects of shearing date on the incidence of lamb strike is the inverse of the effect on ewe strikes, because lambs make up a greater proportion of the pool of susceptible hosts. Later shearing of ewes causes substantial mortality of the eggs produced by the second generation of flies, leading to low fly populations later in the season. As a result, late shearing reduces the incidence of strike for both ewes and lambs. The effect of shearing date on the monthly incidence of strikes under the dry spring conditions is very different to that observed under wet spring conditions. A reduction in strikes is achieved with shearing between a critical period, from 5th June to 15th July (Table 2). During this time, the monthly incidence of strikes on ewes and lambs is reduced relative to strike incidences for shearing occurring outside this critical period. Shearing early during this period ensures that ewe fleeces are short during the first generation of
Sheep blowfly strike: a model approach
Ewe strikes
Lamb strikes
Ewes and lambs
×2 ×1·5 ×0·5 ×0
–20·93 –11·68 10·97 24·33
52·55 29·12 –28·42 –47·30
19·15 10·58 –10·52 –14·74
ovipositions which, coupled with the dry conditions, results in the desiccation of all egg batches laid on ewes at this time. Likewise, late shearing during this period results in severe desiccation of the second generation of egg batches. All shearing dates during this critical period result in large mortality of the on-sheep egg and larval stages and, consequently, a reduction in the subsequent fly population. In contrast, the earliest shearing date examined, 25th April, provides enough time for ewe fleeces to regrow to sufficient length to prevent desiccation of the egg batches laid by the first generation of flies. Conversely, the latest shearing date examined, 25th June, occurs too late to affect the egg batches laid by the second generation of flies. The effect of shearing on the seasonal incidence of strike under the dry spring conditions is much greater than under the wet spring conditions, due to the increased early-season egg batch mortality during the dry spring. Faecal soiling Faecal soiling is the main contributor to susceptibility to blowfly strike (French et al 1995, 1996). Hence, techniques aimed at reducing the levels of scouring and faecal soiling, especially amongst lambs, such as pasture rotation, worming with anthelmintics or tail docking (amputation) would be expected to produce a significant reduction in the seasonal incidence of strike. In the model, to examine the effect of controlling lamb scouring and faecal soiling on strike incidence, the scouring response of lambs to pasture helminth infection was varied between zero and double the normal value used. In the simulation reported here, the response of ewes to pasture helminth infection was unchanged and the results under warm, wet spring conditions only are presented (Table 3). As the tendency for lambs to scour in response to helminth infection was decreased, the incidence of lamb strikes declined and the incidences of ewe strikes increased (Table 3). This was because as the level of lamb susceptibility declined, susceptible ewes made up an increasing proportion of the overall group of susceptible sheep. Hence, a greater number of gravid female blowflies oviposited on ewes. As the tendency for lambs to scour in response to helminth infection increased so there was a corresponding increase in the incidence of lamb strikes and a corresponding decrease in the incidence of ewe strikes (Table 3).
As demonstrated, the models reviewed here provide a valuable tool with which to explore the effects of a range of control and management techniques for blowfly strike control. This exploration is still in its infancy but even at this early stage, there are two major conclusions that can be drawn. First, it is notable that at the beginning of the season, the model suggests that the incidence of strike is limited by the low number of flies present and not by the number of susceptible sheep (Fig 10). Towards the end of season, however, the blowfly population has grown and the number of strikes is limited by the number of susceptible ewes and lambs, not by fly population density. Hence, an increase in the number of susceptible sheep in the first half of the season is unlikely to increase the incidence of strike, because over this period the number of gravid female L sericata is the limiting factor. In the early part of the season, therefore, control aimed at reducing sheep susceptibility to strike is not likely to be the most cost-effective strategy because most of the sheep treated are unlikely to be struck even though susceptible. Early in the season, efforts aimed at reducing the fly population are likely to be relatively more cost-effective, because for every female fly killed one less oviposition/ strike will occur (Wall et al 1995). In the second half of the season, when susceptible sheep and oviposition sites are limiting, any further increase in the fly population will not increase the incidence of strike. Clearly, therefore, later in the season, attempts to suppress the fly population will be wasteful, because most of the flies killed would not have struck sheep anyway. In contrast, later in the season attempts to reduce sheep susceptibility will be a more cost-effective strike control tactic, because if sheep are treated and made less susceptible, the incidence of strike may be reduced in direct measure (but see later). Clearly the point where the fly abundance and sheep susceptibility lines intersect (Fig 10) is critical to the evaluation of the most appropriate control strategy at any particular time. This intersection point will be influenced by factors such as sheep stocking density, breed, flock size and geographical location (French et al 1992) as well as the factors that directly
Sheep susceptibility
Lamb scouring
CONCLUSIONS: IMPLICATIONS FOR STRIKE CONTROL
Blowfly population density
TABLE 3: Effect of changes in lamb scouring on the incidences of strike occurring on ewes, lambs and both sheep types, expressed as a percentage change in the incidence from the appropriate standard reference run. The simulation was run under warm wet spring conditions only
7
Strike
0
30
60 90 Time (day number)
120
150
FIG 10: Schematic illustration of the seasonal changes in abundance of the blowfly Lucilia sericata (dashed line), the numbers of susceptible sheep (solid line) and below these two lines, the number of struck sheep (hatched area). Day 1 is the 1st May.
R. Wall, N. P. French, A. Fenton
8
affect fly abundance and susceptibility, particularly climate and faecal soiling. These are likely to be different on different farms and would need to be considered explicitly to allow the intersection point to be identified precisely for individual farmers. This could be achieved relatively simply using the existing, or slightly modified, versions of this model. Nevertheless, even at a crude, regional level the general implications of Figure 10, may be sufficient to direct control strategies early or late in the blowfly season, without a precise definition of the intersection point. The second major conclusion from the model simulations reviewed here, is that simply reducing the susceptibility of one age-class of sheep may have unexpected effects in increasing the strike incidence in another age-class. Given that there are a specific number of gravid adult female blowflies ready to lay eggs at any time, they will lay on the most susceptible host. If ewe susceptibility is reduced, the female L sericata lay more frequently on the lambs and the incidence of lamb strike increases. Similarly, reducing lamb susceptibility results in an increase in ewe strike. In theory, therefore, unless all oviposition sites on sheep can be totally eliminated, given that adult female blowflies are likely to lay their eggs on the most susceptible group of animals available, an optimum control strategy would be to reduce the susceptibility of most animals, while artificially increasing the susceptibility of a few ‘sacrificial lambs,’ which would receive almost all strikes protecting the rest of the flock. This is described as a ‘push–pull’ strategy and has been explored in more detail by Fenton et al (1999a). Of course, this is unlikely to be desirable or acceptable in practice, but it may be that the pull could be provided by something other than a highly susceptible sheep, such as a trap or other device baited with the appropriate type and quantity of chemical odours (Ashworth and Wall 1994). The work reviewed in this paper describes an important step in our understanding of the sheep blowfly system. The development of these models, which include a range of key, quantified parameters, allows accurate predictions to be made of the peak incidences of strike and, therefore, allow the effects of a range of possible farm management strategies on the incidence of sheep strike on individual sheep farms in Britain to be assessed, thereby determining more efficient, control strategies for protecting a flock from flystrike. We suggest that this approach is likely to be applicable and useful in a range of other host–disease systems of veterinary importance.
ACKNOWLEDGEMENTS We are indebted to our colleagues Katherine Smith, Eleanor Hayes, Isla Cruickshank, Paul Fisher and Kenton Morgan, for their contributions to the work reviewed here. We are grateful to the Royal Society, BBSRC, the Ministry of Agriculture Fisheries and Food and NERC for their financial support of various components of this work.
REFERENCES ATZENI, M.G., MAYER, D.G., SPRADBERRY, J.P., ANAMAN, K.A. & BUTLER, D.G. (1994) Comparison of the predicted impact of a screwworm fly outbreak in
Australia using a growth index model and a life-cycle model. Medical and Veterinary Entomology 8, 281–291 ASHWORTH, J.R. & WALL, R. (1994) Responses of the sheep blowflies Lucilia sericata and L. cuprina (Diptera: Calliphoridae) to odour and the development of semiochemical baits. Medical and Veterinary Entomology 8, 303–309 BECK, S.D. (1983) Insect thermoperiodism. Annual Review of Entomology 28, 91–108 BOAG, B. & THOMAS, R.J. (1971) Epidemiological studies on gastro-intestinal nematode parasites of sheep: infection patterns on clean and autumn-contaminated pasture. Research in Veterinary Science 12, 132–139 CORNWALL, R.L. (1975) The pattern of infection with gastro-intestinal nematodes in young fattening lambs at pasture. Research in Veterinary Science 18, 1–5 CRAGG, J.B. (1955) The natural history of sheep blowflies. Annals of Applied Biology 42, 197–207 DAVIES, M.W. (1929) Hibernation of Lucilia sericata, Mg. Nature 123, 759–760 DAVIES, L. (1948a) Observations on the development of Lucilia sericata (Mg.) eggs in sheep fleeces. Journal of Experimental Biology 25, 86–102 DAVIES, L. (1948b) Laboratory studies on the egg of the blowfly Lucilia sericata (Mg.). Journal of Experimental Biology 25, 71–85 DAVIES, W.M. & HOBSON, R.P. (1935) Sheep blowfly investigations. I. The relationship of humidity to blowfly attack. Annals of Applied Biology 22, 279–293 EISMANN, C.H. (1988) Upwind flight by gravid Australian sheep blowflies, Lucilia cuprina (Wiedemann) (Diptera: Calliphoridae), in response to stimuli from sheep. Bulletin of Entomological Research 78, 273–279 EVANS, A.C. (1936) The physiology of the sheep blow-fly Lucilia sericata Meig. (Diptera). Transactions of the Royal Entomological Society 85, 363–378 FENTON, A. & WALL, R. (1997). Sensitivity analysis of a stochastic model of the sheep blowfly Lucilia sericata. Journal of Applied Ecology 34, 1023–1031 FENTON, A., WALL, R. & FRENCH, N. (1997) Sensitivity analysis of deterministic and stochastic simulation models of populations of the sheep blowfly, Lucilia sericata. Journal of Theoretical Biology 184, 139–148 FENTON, A., WALL, R. & FRENCH, N.P. (1998a) The incidence of ovine myiasis by the blowfly Lucilia sericata on sheep farms in Britain: a simulation model. Veterinary Parasitology 76, 211–228 FENTON, A., WALL, R. & FRENCH, N.P. (1998b) The effect of farm management strategies on the incidence of sheep strike in Britain: a simulation analysis. Veterinary Parasitology 79, 341–357 FENTON, A., WALL, R. & FRENCH, N.P. (1999a) The effects of oviposition aggregation on the incidence of sheep blowfly strike. Veterinary Parasitology 83, 137–150 FENTON, A., WALL, R. & FRENCH, N.P. (1999b) Oviposition aggregation in the blowfly Lucilia cuprina in Australia. Medical and Veterinary Entomology 13, 453–456 FRENCH, N.P. & MORGAN, K.L. (1996a) A model of ovine cutaneous myosis using the predicted abundance of Lucilia sericata and a pattern of sheep susceptibility. Preventive Veterinary Medicine 26, 143–155 FRENCH, N.P. & MORGAN, K.L. (1996b) Role of neonatal and maternal risk factors in the faecal soiling of lambs. Veterinary Record 134, 460–465 FRENCH, N.P., WALL, R., CRIPPS, P.J. & MORGAN, K.L. (1992) Incidence, regional distribution and control of blowfly strike in England and Wales. Veterinary Record 131, 337–342 FRENCH, N.P., WALL, R. & MORGAN, K.L. (1995) The seasonal pattern of sheep blowfly strike in England and Wales. Medical and Veterinary Entomology 9, 1–8 FRENCH, N.P., PARKIN, T.D.H. & MORGAN, K.L. (1996) A case control study of blowfly strike in lambs. Veterinary Record 139, 384–388 HALL, M.J.R. & WALL, R. (1995) Myiasis in humans and domestic animals. Advances in Parasitology 35, 258–334 HAYES, E. & WALL, R. (1998) Measurement of age and population age structure in the blowfly Lucilia sericata (Meigen) (Diptera: Calliphoridae). Journal of Insect Physiology 44, 895–901 HAYES, E. & WALL, R. (1999) Mortality rate, reproductive output and trap response bias in populations of the blowfly Lucilia sericata. Ecological Entomology 24, 300–307 HIGLEY, L.G., PEDIGO, L.P. & OSTLIE, H.R. (1986) Degday: a program for calculating degree-days and assumptions behind the degree-day approach. Environmental Entomology 15, 999–1016 MacLEOD, J. (1940) The moisture balance of the living fleece in relation to blowfly myiasis, with some remarks on the Australian and British conceptions of susceptibility. Annals of Applied Biology 27, 379–392 MacLEOD, J. (1943a) A survey of British sheep blowflies. Bulletin of Entomological Research 34, 65–88 MacLEOD, J. (1943b) A survey of British sheep blowflies. II. Relation of strike to host and edaphic factors. Bulletin of Entomological Research 84, 95–111 MICHEL, J.F. (1976) The epidemiology and control of some nematode infections in grazing animals. Advances in Parasitology 14, 355–397 MOON, R.D. (1983) Simulating developmental time of preadult face flies (Diptera: Muscidae) from air temperature records. Environmental Entomology 12, 943–948 PREUSS, K.P. (1983). Day-degree methods for pest management. Environmental Entomology 12, 613–619 SMITH, K.E. & WALL, R. (1997a) The use of carrion as breeding sites by the blowfly Lucilia sericata and other Calliphoridae. Medical and Veterinary Entomology 11, 38–44 SMITH, K.E. & WALL, R. (1997b) Asymmetric competition between larvae of the blowflies, Calliphora vicina and Lucilia sericata in carrion. Ecological Entomology 22, 468–474
Sheep blowfly strike: a model approach WAGNER, T.L., WU, H., SHARPE, P.J., SCHOOLFIELD, R.M. & COULSON, R.N. (1984) Modeling insect development rates: a literature review and application of a biophysical model. Annals of the Entomological Society of America 77, 208–225 WALL, R. (1993) The reproductive output of the blowfly Lucilia sericata. Journal of Insect Physiology 9, 743–750 WALL, R. & SMITH, K.E. (1997) The potential for control of the blowfly Lucilia sericata using odour-baited targets. Medical and Veterinary Entomology 11, 335–341 WALL, R., LANGLEY, P.A. & MORGAN, K.L. (1991) Ovarian development and pteridine accumulation for age determination in the blowfly Lucilia sericata. Journal of Insect Physiology 37, 863–868 WALL, R., FRENCH, N.P. & MORGAN, K. (1992a) Blowfly species composition in sheep myiasis in Britain. Medical and Veterinary Entomology 6, 177–178 WALL, R., FRENCH, N. & MORGAN, K. (1992b) Effects of temperature on the development and abundance of the sheep blowfly Lucilia sericata. Bulletin of Entomological Research 82, 125–131 WALL, R., GREEN, C., FRENCH, N. & MORGAN, K. (1992c) Development of an attractive target for the sheep blowfly Lucilia sericata. Medical and Veterinary Entomology 6, 67–74
9
WALL, R., FRENCH, N. & MORGAN, K.L. (1993a) Predicting the abundance of the blowfly Lucilia sericata (Diptera: Calliphoridae). Bulletin of Entomological Research 83, 431–436 WALL, R., FRENCH, N. & MORGAN, K.L. (1993b) Sheep blowfly population control: development of a simulation model and analysis of management strategies. Journal of Applied Ecology 30, 743–751 WALL, R., FRENCH, N.P. & MORGAN, K.L. (1995) Population suppression for control of the blowfly Lucilia sericata and sheep blowfly strike. Ecological Entomology 20, 91–97 WARDHAUGH, K.G. & DALLWITZ, R. (1984) Covert flystrike. Wool Technology and Sheep Breeding 32, 15–19 WATTS, J.E. & MARCHANT, R.S. (1977) The effects of diarrhoea, tail length and sex on the incidence of breech strike in modified mulesed merino sheep. Australian Veterinary Journal 53, 118–123 WATTS, J.E. & PERRY, D.A. (1975) Observations on breech strike in scouring sheep. Australian Veterinary Journal 51, 586–587 Accepted February 11, 2000
REVIEW
Sheep blowfly strike: a model approach R. WALL*, N. P. FRENCH†, A. FENTON‡ School of Biological Sciences, The University of Bristol, Woodland Road, Bristol, BS8 1UG, UK, †Department of Veterinary Clinical Science and Animal Husbandry, University of Liverpool, Leahurst, Neston, L64 7TE, UK and ‡Institute of Biological Sciences, University of Stirling, Stirling, FK9 4LA, UK
OVINE cutaneous myiasis is a familiar and widespread disease of sheep in Britain (French et al 1992) and many other areas of the world (Hall and Wall 1995). The primary agent of sheep strike throughout most of northern Europe is the ‘greenbottle’ blowfly, Lucilia sericata (Meigen) (Diptera: Calliphoridae) (MacLeod 1943a, Wall et al 1992a). The same species is also responsible for myiasis of rabbits and occasionally other, usually debilitated, domestic and wild animals (Hall and Wall 1995). Although blowfly strike has been the subject of extensive investigation over many years, a number of more recent studies have been able to bring new insights into the ecology and epidemiology of this disease, particularly through the use of a theoretical, model-led approach. In this work, a series of models have been developed that simulate the seasonal pattern of fly abundance (Wall et al 1992b, 1993a,b) and sheep myiasis on farms in Britain (French and Morgan 1996a, Fenton and Wall, 1997, Fenton et al 1997, 1998a,b). The models are based on two sub-components. The first simulates the seasonal pattern of abundance of L sericata. The second uses the range of key factors known to influence ewe and lamb susceptibility, to estimate the proportion of a flock at risk from strike. The development and application of these models have allowed the relative importance of the various factors that determine the observed pattern of blowfly abundance and strike incidence to be assessed. They have also allowed deficiencies in the available knowledge to be identified, enabling experimental work to be directed more appropriately. However, perhaps of greatest importance, is the fact that the models developed are beginning to provide a valuable tool through which the potential effects of a range of sheep and strike management options may be explored. The aim of this paper is to review briefly the development of these models, their key findings and highlight their potential value in the future.
properties of particular systems to be made and allow computer-based experiments of control strategies. Simulation models of biological systems may, however, become complex relatively quickly and their construction does require detailed life-history information. The blowfly life-cycle Adult female L sericata lay eggs in the wool of sheep close to the skin surface, selecting areas of high humidity, such as fleece or skin soiled by faeces or bacterial infection (Davies 1948a, Cragg 1955). After hatching, the maggots pass through three stages, feeding on the epidermal tissues and skin secretions (Evans 1936). After about 72 hours, when they have completed feeding, the third stage larvae drop to the ground where they undergo a period of dispersal. The larvae then burrow into the soil before pupariating. Newly emerged adults mate, protein-feed and, after their ovaries have fully matured, females seek-out a suitable oviposition site on a host animal (Fig 1). At each oviposition each female deposits about 200 eggs in a single egg batch (Wall 1993). Cycles of oviposition and emergence can continue throughout the spring and summer but, as the temperature and photoperiod decline in autumn, females produce larvae that cease development mid-way through the wandering phase and burrow into the ground where they overwinter as diapausing larvae (Davies 1929).
Temperature-dependent development and mortality rates
Eggs
Larvae
Pupae
Adults
BLOWFLY MODEL SUB-COMPONENT Oviposition / blowfly strike
In the work reviewed here a simulation approach was adopted; simulations are often of more practical use than analytical models since they allow predictions about the *Corresponding author.
0034-5288/00/040001 + 09 $35.00/0
FIG 1:
Schematic representation of blowfly life-cycle model sub-component.
© 2000 Harcourt Publishers Ltd
R. Wall, N. P. French, A. Fenton
2
Blowfly development and mortality rates The first step in the construction of the blowfly strike simulation models reviewed here was the quantification of the rate at which the life cycle could be completed and the mortality of adults and larvae during its completion. The development rates of insects are determined primarily by the temperature of the environment to which they are exposed (Beck 1983, Wagner et al 1984, Higley et al 1986). As a result, the majority of insect population models attempt quantitatively to extrapolate the population growth rate from available temperature data (Atzeni et al 1994). One of the most commonly used methods involves the calculation of day degrees. This technique assumes that development rate is directly proportional to temperature above a minimum threshold, the base temperature, and that below this threshold no development occurs (Moon 1983, Preuss 1983). The exact nature of the temperature–development rate relationship differs between species and between life-cycle stages within a species. The relationship was determined for L sericata by rearing individuals of different stages under a range of constant temperatures. The rate of development at any temperature was then calculated as the reciprocal of the time taken for 50 per cent of the individuals to complete development at that temperature. A plot of these development rates against temperature showed an approximately linear relationship at the middle temperature range. By linear regression, this portion was extrapolated to where it intercepted the x-axis, giving an estimate of the base threshold temperature for that stage. The base threshold temperatures for development of pre-adult stages and ovary maturation by adult females of L sericata were calculated to be around 9°C and 11°C respectively (Wall et al 1992b; Table 1). The difference between the base temperature and the ambient temperature multiplied by the time taken to complete any life-cycle stage at that temperature, gives the number of day degrees required for complete development of that stage. The number of day degrees required for each stage of the L sericata life-cycle are shown in Table 1. Once the base-temperature and number of day-degrees above this threshold required for development are known, it is possible to calculate the likely development time of a given life-cycle stage at any temperature. Adult mortality rates for L sericata were calculated through examination of the age-structure of populations in the field. The determination of the age of individual flies is problematic, but was achieved using analysis of the known temperature-dependent rate of ovarian development (Wall 1993) in conjunction with either analysis of head-capsule pteridine levels (Wall et al 1991) or analysis of the rate of TABLE 1: Day-degree requirements (±SE) and base threshold temperatures (±SE) for completion of pre-adult life-cycle stages and adult egg batch maturation (from Wall et al 1992b) Life cycle stage
Day-degree requirement (±SE)
Base temperature (°C) (±SE)
Post-diapause larvae Larval wandering stage Pupation First egg batch Subsequent egg batches
29·7 (0·3) 45·6 (5·1) 126·1 (3·7) 62·0 (2·3) 27·7 (0·9)
9·2 (0·1) 9·5 (0·6) 8·8 (0·7) 11·2 (1·3) 11·1 (0·7)
wing-margin damage (Hayes and Wall 1998, 1999). These studies showed that the typical mortality rate is about 2 per cent per day-degree, giving a mean life expectancy of about 50 day-degrees, above a threshold of 11°C. This equates to a mean life expectancy of about 4 or 5 days at average British summer temperatures. Larval mortality rates in the field have proved harder to quantify but, based on trials in which sheep were infested with known numbers of first stage L sericata larvae and third stage larvae then collected and counted (R. Wall, unpublished data), a standard rate of 50 per cent mortality between egg deposition and adult emergence from the puparium is used in the simulation models described here. No allowance has been made in these models for the possibility that L sericata could emerge from carrion. Three lines of evidence support this and indicate that carcasses are unlikely to play an important role in maintaining L sericata populations. The carcasses of small mammals and birds occur largely in hedgerows and woodland. Experimental studies have demonstrated that L sericata on the other hand is almost totally absent from shaded habitats and appears to be strongly confined to open sunny areas (Smith and Wall 1997a). Hence, a carcase lying in woodland is highly unlikely to become infested with L sericata. If it does, however, these L sericata larvae are likely to experience intense competition from the larger, more abundant, shade-loving species of blowflies (Calliphora spp.) (Smith and Wall, 1997b). Small carcasses in open fields could become infested with L sericata, but usually get removed very quickly by scavengers such as foxes, badgers, dogs, cats or birds, before this happens. Large carcasses, such as sheep, could form an important breeding site for L sericata, but leaving dead sheep to decompose in open pasture is not common on lowland farms in the UK. Were lowland sheep farmers to adopt the practice of leaving dead sheep to decay in fields, this would almost certainly lead to a significant increase in L sericata abundance. Finally, it has been shown that if every sheep in an area is treated with a larvicide (cyromazine) early in the year, so that the first blowfly generation of the year is killed, it is possible to largely eliminate the entire L sericata population for an extended period (Wall et al 1995). This would not be possible if significant numbers of L sericata were emerging from carcasses. Domestic pet rabbits are commonly infested by blowfly, however, no routinely infested wild hosts have ever been identified (Hall and Wall 1995). Blowfly model operation In spring, as the temperatures increase, the models assume that a new cohort of L sericata emerges as adults. Daily temperatures are then used to allow the cohort to accumulate day-degrees or day-degree fractions (Fenton et al 1997) and to calculate the mortality schedule. Eventually, when sufficient day-degrees have been accumulated the surviving females of this first cohort oviposit, laying 200 eggs each (Wall et al 1993a,b, Fenton and Wall 1997, Fenton et al 1997), half of which are female and half male. Egg hatch and the larval feeding stages, which occur on the sheep, are allowed 3 days for completion, based on laboratory studies (Wall et al 1992b) and field observations. This period is maintained as a constant since in the protected
Sheep blowfly strike: a model approach
3
1
Ewe and lamb susceptibility
Faecal soiling
Pasture worm burden FIG 2:
Fleece length
Relative humidity
Pasture worm count
Oviposition / blowfly strike
0.8 0.6 0.4 0.2 0
Rainfall
Schematic representation of the sheep strike model sub-component.
microhabitat of the fleece, the rate of development of these stages is relatively independent of ambient temperature. Once the larvae are fully developed and have wandered off the host, once again, daily temperature is used to allow larvae and pupae to accumulate day-degrees and estimate the time required to complete development, prior to emergence of the next generation of adults. This continues on a daily basis throughout the year until, to simulate the effect of induced diapause, the larvae of females ovipositing towards the end of the season are assumed to enter diapause. Deterministic and stochastic forms of this blowfly model have been developed (Fenton et al 1997). The deterministic version assumes that all the individuals are identical, whereas the stochastic version allows for variation between cohorts in day-degree requirements. The stochastic model uses a Monte-Carlo simulation technique to assign random development rates to each life-cycle stage generated from a Weibull distribution fitted to observed variation in development rate for each stage.
SHEEP MODEL SUB-COMPONENT In reality, the incidence of strike will not be related simply to the abundance of flies but will also be associated with a range of factors that promote susceptibility to oviposition and larval survival on the host (French et al 1995). In the second component of the model, therefore, the number of susceptible sheep present each day is calculated by generating patterns of susceptibility throughout the season, based on a combination of the factors known to influence the occurrence of strike (Fig 2). Separate susceptibility patterns are generated in the model for ewes and lambs. Faecal soiling Faecal contamination of the fleece is the major predisposing factor for blowfly strike by L sericata in Britain (French et al 1995, French and Morgan 1996b). Such contamination both attracts oviposition (Ashworth and Wall 1995) and raises and maintains fleece humidity to levels suitable for egg hatch and larval survival (Watts and Perry 1975, Watts and Marchant 1977). In the models reviewed here the pat-
0
30
60 90 Time (day number)
120
150
FIG 3: Hypothetical pattern of relative exposure of sheep endoparasitic nematodes throughout the season used in blowfly strike simulation models (derived from Michel 1976). Day 1 is the 1st May.
terns of faecal contamination used are based on two of the factors which influence wool soiling: the consistency of the faeces and wool length (Fig 2). The model assumes that helminth parasites are the predominant cause of diarrhoea in sheep, particularly in firstseason grazing lambs. Hence, to incorporate the effects of changes in faecal consistency on sheep susceptibility, the models use simple relationships based on recorded patterns of the number of infective larvae of endoparasitic helminths of sheep typically present on pastures over a season (Boag and Thomas 1971, Cornwall 1975, Michel 1976). This is an obvious oversimplification, which it is hoped may be addressed in future versions of the model; addition of the effects of daily ambient temperature and humidity for example on worm abundance and infectivity might be included. The faecal consistency of ewes and lambs each day is assumed to be linearly related to the predicted abundance of infective helminth larvae (Fig 3). A separate weighting factor is given for lambs and ewes to produce a daily index of faecal consistency for each group of sheep. These weighting factors are derived from observed differences in the monthly prevalence of breech strike between lambs and ewes (French et al 1995), which is assumed in the model to reflect the relative likelihood of diarrhoea in response to helminth infections of the two groups of sheep. In addition, observed levels of faecal soiling are considered to be dependent on the length of fleece around the breech area. It is assumed that longer fleeces are associated with higher levels of faecal soiling. The model gives each animal a relative wool length score related to time of year (Fig 4) and may incorporate shearing for ewes. In the standard model, ewes are considered to have been sheared on the 25th of May (Fig 4). Hence, in the model, each day the index of faecal consistency is weighted by the relative wool length score to give the resulting degree of faecal contamination (described as the dag score) expected. Fleece humidity Although the majority of strikes occur in the breech region, strikes are also observed on other areas of the sheep, independent of any influence of faecal soiling (French et al
R. Wall, N. P. French, A. Fenton
4
90
0.8
0.6
Relative humidity (per cent)
Wool length score
Ewes Lambs
0.4
0.2
80 70 60 50 40 30 20 10
0 0
30
60 90 Time (day number)
120
150
FIG 4: Hypothetical seasonal patterns of relative fleece length scores for ewes and lambs used in blowfly strike simulation models. Day 1 is the 1st May and ewes are sheared on the 25th May.
1995). The importance of fleece humidity on the occurrence of these body strikes has been demonstrated in several studies (Davies and Hobson 1935, MacLeod 1940, Davies 1948a,b). Fleece length plays an important role in determining fleece humidity and a reduction in the susceptibility of ewes to attack following shearing has been recorded (Davies and Hobson 1935, MacLeod 1943b). Fleece humidity typically ranges from around 30 to 65 per cent, only rising to over 70 per cent following periods of prolonged wetting (Davies and Hobson 1935, MacLeod 1940, Davies 1948b). To simulate the humidity component of susceptibility, it is assumed that, in the absence of rain, there is a positive linear relationship between fleece length and fleece relative humidity ranging from a base level of 30 per cent for the shortest fleece up to 65 per cent for the longest (Fig 5). Each sheep is assigned a fleece baseline humidity score, determined by the previously calculated relative wool length score. The baseline fleece humidity index is then weighted to account for the effects of rain on any one day, the weighting being dependent on the amount of rain judged to have fallen (Fenton et al 1998a). Immediately following oviposition eggs and first stage larvae are highly susceptible to desiccation due to low fleece humidity levels; relative humidities of at least 60 per cent are required for egg hatch and development at the temperatures experienced in the fleece (Davies and Hobson 1935, Davies 1948a,b). Hence, in the simulation, each day the calculated fleece relative humidity index is used to determine the proportion of egg batches laid the previous day that fail to develop. At fleece humidities of less than 60 per cent all existing unhatched egg batches are assumed to desiccate. Humidities of greater than 80 per cent are considered to be sufficiently moist to allow full development of all egg batches laid (Davies and Hobson 1935, Davies 1948a). For relative humidities between 60 and 80 per cent a linear change in egg/larval mortality between 0 and 100 per cent is assumed (Fenton et al 1998a). Modelling sheep susceptibility In the models, the prevalence of susceptibility of lambs and ewes is related to faecal soiling and fleece humidity by a logistic function. In this function, the odds ratios for the
0
0.2
0.4 0.6 Wool length score
0.8
1
FIG 5: The relationship between the relative fleece length score and the baseline relative humidity of the fleece used in blowfly strike simulation models.
Temperature-dependent development and mortality rates
Larvae
Eggs
Pupae
Adults
Oviposition / blowfly strike Negative binominal aggregation
Temperature dependent oviposition activity
Ewe and lamb susceptibility
Faecal soiling
Pasture worm burden
Fleece length
Relative humidity
Rainfall
FIG 6: Schematic representation of the structure of the complete blowfly and sheep myiasis simulation model.
contribution to susceptibility of faecal soiling and relative humidity are derived from the studies of French et al (1996) and Eismann (1988), respectively. The number of susceptible ewes (NE) and susceptible lambs (NL) present at the start of each day is estimated as the proportion of ewes and lambs that is susceptible, multiplied by the total number of ewes or lambs present in the flock.
THE FULL MODEL In the full model, the blowfly and sheep susceptibility components are brought together (Fig 6). Each day, the fly component of the model calculates the number of gravid females present while the logistic component of the model estimates the number of susceptible ewes and lambs available at the start of each day. The model assumes that each adult female blowfly is able to oviposit on the day it
Sheep blowfly strike: a model approach
5
becomes gravid. Hence, the total number of ovipositions (Ot) on any one day is equal to the number of gravid females present on that day. Individual ovipositions are assigned to ewes (OE) and lambs (OL) proportionately, according to the ratio of the number of susceptible sheep of that category to the total number of sheep in the flock, that is OE=NE/(NE+NL).Ot, and OL= NL/(NE+NL).Ot. Hence, if there are no susceptible lambs, all ovipositions will occur on ewes; if there are no susceptible ewes, all ovipositions will occur on lambs. Two other factors also need to be incorporated into the final model: the distribution of strikes between the susceptible sheep and the effects of temperature of fly oviposition activity.
a season. In an average year three or four generations would be expected (Fig 7). The output of the stochastic model predicts the emergence of generations which are less distinct, with individuals of each generation present both earlier and later than the predictions of the deterministic model (Fig 7). The distinction between generations is further eroded by the addition of temperature-dependent variation in activity. Comparison of the patterns of fly abundance generated by the models with those seen in the field, indicates that the model provides a good description of the changes in fly numbers over time (Wall et al 1993a).
Aggregation
The model indicates that under average spring/summer climatic conditions, when the first female blowflies of the season are ready to oviposit, the majority of the oviposition sites available are present on ewes, due to their full length fleeces (Fig 8). The long fleeces provide areas of high humidity suitable for the development of eggs and larvae. At this time lamb fleeces are still short and faecal soiling is still at a low level. Hence, the first cases of strike are predicted to occur approximately equally on ewes and lambs (Fig 8). Since the blowfly population is in the early stages of development, the incidence of strike is limited by the low number of flies present at the start of the season, and not by the number of susceptible sheep present. In the standard simulation the ewes are sheared on the 25th of May. Towards the end of June, ewe and lamb susceptibility are approximately equal, prior to lamb faecal soiling increasing. Hence, the second generation of blowflies again tends to oviposit equally on lambs and ewes (Fig 8). By late July, however, lamb faecal soiling is at its peak, as is lamb fleece length, while ewe faecal soiling is low although ewe fleece has regrown. Therefore, the third generation of female L sericata oviposit preferentially on lambs rather than ewes. Towards the end of the season, although lamb faecal soiling has declined, it is still greater than that of the ewes. Hence, the final generation of L sericata again tends to oviposit more on lambs than ewes. Comparison of the patterns of strike incidence generated
Fly activity Finally, the number of ovipositions that can occur on any one day is a function of the number of gravid adult females present and the effects of ambient temperature on fly oviposition activity. Trapping and mark-release-recapture studies have shown that adult L sericata are more active and more likely to be caught on warmer days (Wall and Smith 1997). Hence, in the model, each day, the proportion of the female L sericata present that are deemed to be able to oviposit is calculated from a known linear relationship between activity and temperature (Wall and Smith 1997). On days when mean temperature is less than 13°C, none of the flies present are considered to be sufficiently active to oviposit (Fig 6).
MODEL OUTPUT AND VALIDATION Blowfly abundance The output from the model predicts that the adult L sericata emerge in relatively discrete waves, with fly numbers increasing exponentially with each wave over the course of
1000
Number of flies
Blowflies tend to be aggregated in their distribution in the field (Wall et al 1992c) and myiases, like most parasitic infections, tend to be distributed among hosts in a non-random manner affecting some sheep more than others (Wardhaugh and Dalwitz 1984, Fenton et al 1999a,b). In the models reviewed here it has been assumed that strikes occur among the susceptible sheep in the flock according to a negative binomial distribution. Each day, the number of oviposition events occurring on ewes (OE) and lambs (OL), and the number of susceptible ewes (NE) and susceptible lambs (NL) are known. Hence, the mean numbers of ovipositions per susceptible ewe (ME) and lamb (ML) are ME = O E/NE and ML = OL/NL. As a result, the proportion of ewes and lambs with 0,1,2 … strikes can then be calculated according to the negative binomial distribution with parameters x, k and the appropriate mean. The proportion of the susceptible flock uninfected (u) is given as the zero term in the negative binomial, so the proportion of the flock infected (i) is 1 – u. Therefore, the number of ewes or lambs carrying ovipositions at the end of each day is the appropriate value of i multiplied by the total number of susceptible sheep in that group (Fig 6).
Sheep susceptibility and strike incidence
100
10
1 0
40
80 120 Time (day number)
160
FIG 7: The number of Lucilia sericata predicted to be present and available for capture by deterministic (dashed line) and stochastic simulation models (solid line) under representative British temperature and rainfall conditions. Day 1 is the 1st May.
R. Wall, N. P. French, A. Fenton
6
7
Ewes Lambs
6
1.2 Incidence of strike
Monthly incidence
1.5
0.9 0.6 0.3
Ewes Lambs
5 4 3 2 1
0 May
July June
September August October
0 May
June
July
Aug
Sept
Oct
Month of year FIG 8: The expected monthly incidence of strike in ewes and lambs as predicted by a deterministic simulation model under representative British temperature and rainfall conditions.
by the models and described above with those seen in the field (French et al 1995), again indicates that the model provides a good description of the changes in strike incidence over time (Fig 9).
FIG 9: The observed monthly incidence of breech strike per 1000 animals (with 95 per cent confidence intervals) in ewes and lambs in England and Wales in 1991. From French et al (1995).
TABLE 2: Effect of changes in shearing date on the incidences of strike occurring on ewes, lambs and both sheep types, expressed as a percentage change in the incidence from the appropriate standard reference run. In the standard reference run: day –30 = 25th April, –20 = 5th May, –10 = 15th May, ewes are sheared on the 25th of May, day +10 = 4th June, +20 = 14th June and +30 = 24th June Ewe strikes
EFFECTS OF SHEEP MANAGEMENT To explore the effects of different farm management strategies on the incidence of blowfly strike, a number of parameters such as shearing date or worm control may be varied independently in the model, in association with changes in weather conditions. Effects of shearing date To investigate the possibility that the appropriate timing of ewe shearing might lead to a reduction in the seasonal incidence of strike, due to increased egg-batch desiccation, the date of shearing in the model was varied by up to one month either side of the standard reference date used, which is the 25th of May (Table 2). The simulations run under wet spring conditions show that the earliest shearing date examined (26th April), results in a greater incidence of ewe strikes (Table 2). The explanation for this result is that although early shearing coincides with the oviposition by the first generation of flies, the spring rains prevent egg-batch desiccation. Therefore, there is no increase in mortality through egg desiccation. In addition, early shearing allows ewe fleeces to regrow to full length by mid-July, when there is a substantial increase in endoparastic worm burdens. The interaction of these factors leads to a large increase in ewe susceptibility and, consequently, ewe strikes. Conversely, later shearing, although not affecting eggbatch survival in the first generation, does not allow enough time for ewe fleeces to reach maximum length by the time of the peak in worm abundance. Hence, fewer ewes are susceptible and there is a corresponding decrease in ewe strikes each month (Table 2). Furthermore, under the late shearing strategy, the low summer rains, combined with the relatively short ewe fleeces results in many of the second and third
Lamb strikes
Ewes and lambs
Warm, wet spring Shearing –30 –20 –10 +10 +20 +30
13·71 9·92 5·73 –10·22 –22·04 –27·37
–5·07 –3·20 –1·29 0·40 –1·70 –0·15
3·47 2·76 1·90 –4·43 –10·94 –12·52
Warm, dry spring Shearing –30 –20 –10 +10 +20 +30
43·97 –19·23 –44·06 –13·46 –29·98 7·87
19·86 –23·13 –41·74 –1·32 –9·48 34·08
30·55 –23·07 –42·77 –6·71 –18·57 22·45
generation egg batches desiccating. For lambs, in the wet spring, changes in ewe shearing date appear to have relatively little effect on the incidence of strike (Table 2). In general, the effects of shearing date on the incidence of lamb strike is the inverse of the effect on ewe strikes, because lambs make up a greater proportion of the pool of susceptible hosts. Later shearing of ewes causes substantial mortality of the eggs produced by the second generation of flies, leading to low fly populations later in the season. As a result, late shearing reduces the incidence of strike for both ewes and lambs. The effect of shearing date on the monthly incidence of strikes under the dry spring conditions is very different to that observed under wet spring conditions. A reduction in strikes is achieved with shearing between a critical period, from 5th June to 15th July (Table 2). During this time, the monthly incidence of strikes on ewes and lambs is reduced relative to strike incidences for shearing occurring outside this critical period. Shearing early during this period ensures that ewe fleeces are short during the first generation of
Sheep blowfly strike: a model approach
Ewe strikes
Lamb strikes
Ewes and lambs
×2 ×1·5 ×0·5 ×0
–20·93 –11·68 10·97 24·33
52·55 29·12 –28·42 –47·30
19·15 10·58 –10·52 –14·74
ovipositions which, coupled with the dry conditions, results in the desiccation of all egg batches laid on ewes at this time. Likewise, late shearing during this period results in severe desiccation of the second generation of egg batches. All shearing dates during this critical period result in large mortality of the on-sheep egg and larval stages and, consequently, a reduction in the subsequent fly population. In contrast, the earliest shearing date examined, 25th April, provides enough time for ewe fleeces to regrow to sufficient length to prevent desiccation of the egg batches laid by the first generation of flies. Conversely, the latest shearing date examined, 25th June, occurs too late to affect the egg batches laid by the second generation of flies. The effect of shearing on the seasonal incidence of strike under the dry spring conditions is much greater than under the wet spring conditions, due to the increased early-season egg batch mortality during the dry spring. Faecal soiling Faecal soiling is the main contributor to susceptibility to blowfly strike (French et al 1995, 1996). Hence, techniques aimed at reducing the levels of scouring and faecal soiling, especially amongst lambs, such as pasture rotation, worming with anthelmintics or tail docking (amputation) would be expected to produce a significant reduction in the seasonal incidence of strike. In the model, to examine the effect of controlling lamb scouring and faecal soiling on strike incidence, the scouring response of lambs to pasture helminth infection was varied between zero and double the normal value used. In the simulation reported here, the response of ewes to pasture helminth infection was unchanged and the results under warm, wet spring conditions only are presented (Table 3). As the tendency for lambs to scour in response to helminth infection was decreased, the incidence of lamb strikes declined and the incidences of ewe strikes increased (Table 3). This was because as the level of lamb susceptibility declined, susceptible ewes made up an increasing proportion of the overall group of susceptible sheep. Hence, a greater number of gravid female blowflies oviposited on ewes. As the tendency for lambs to scour in response to helminth infection increased so there was a corresponding increase in the incidence of lamb strikes and a corresponding decrease in the incidence of ewe strikes (Table 3).
As demonstrated, the models reviewed here provide a valuable tool with which to explore the effects of a range of control and management techniques for blowfly strike control. This exploration is still in its infancy but even at this early stage, there are two major conclusions that can be drawn. First, it is notable that at the beginning of the season, the model suggests that the incidence of strike is limited by the low number of flies present and not by the number of susceptible sheep (Fig 10). Towards the end of season, however, the blowfly population has grown and the number of strikes is limited by the number of susceptible ewes and lambs, not by fly population density. Hence, an increase in the number of susceptible sheep in the first half of the season is unlikely to increase the incidence of strike, because over this period the number of gravid female L sericata is the limiting factor. In the early part of the season, therefore, control aimed at reducing sheep susceptibility to strike is not likely to be the most cost-effective strategy because most of the sheep treated are unlikely to be struck even though susceptible. Early in the season, efforts aimed at reducing the fly population are likely to be relatively more cost-effective, because for every female fly killed one less oviposition/ strike will occur (Wall et al 1995). In the second half of the season, when susceptible sheep and oviposition sites are limiting, any further increase in the fly population will not increase the incidence of strike. Clearly, therefore, later in the season, attempts to suppress the fly population will be wasteful, because most of the flies killed would not have struck sheep anyway. In contrast, later in the season attempts to reduce sheep susceptibility will be a more cost-effective strike control tactic, because if sheep are treated and made less susceptible, the incidence of strike may be reduced in direct measure (but see later). Clearly the point where the fly abundance and sheep susceptibility lines intersect (Fig 10) is critical to the evaluation of the most appropriate control strategy at any particular time. This intersection point will be influenced by factors such as sheep stocking density, breed, flock size and geographical location (French et al 1992) as well as the factors that directly
Sheep susceptibility
Lamb scouring
CONCLUSIONS: IMPLICATIONS FOR STRIKE CONTROL
Blowfly population density
TABLE 3: Effect of changes in lamb scouring on the incidences of strike occurring on ewes, lambs and both sheep types, expressed as a percentage change in the incidence from the appropriate standard reference run. The simulation was run under warm wet spring conditions only
7
Strike
0
30
60 90 Time (day number)
120
150
FIG 10: Schematic illustration of the seasonal changes in abundance of the blowfly Lucilia sericata (dashed line), the numbers of susceptible sheep (solid line) and below these two lines, the number of struck sheep (hatched area). Day 1 is the 1st May.
R. Wall, N. P. French, A. Fenton
8
affect fly abundance and susceptibility, particularly climate and faecal soiling. These are likely to be different on different farms and would need to be considered explicitly to allow the intersection point to be identified precisely for individual farmers. This could be achieved relatively simply using the existing, or slightly modified, versions of this model. Nevertheless, even at a crude, regional level the general implications of Figure 10, may be sufficient to direct control strategies early or late in the blowfly season, without a precise definition of the intersection point. The second major conclusion from the model simulations reviewed here, is that simply reducing the susceptibility of one age-class of sheep may have unexpected effects in increasing the strike incidence in another age-class. Given that there are a specific number of gravid adult female blowflies ready to lay eggs at any time, they will lay on the most susceptible host. If ewe susceptibility is reduced, the female L sericata lay more frequently on the lambs and the incidence of lamb strike increases. Similarly, reducing lamb susceptibility results in an increase in ewe strike. In theory, therefore, unless all oviposition sites on sheep can be totally eliminated, given that adult female blowflies are likely to lay their eggs on the most susceptible group of animals available, an optimum control strategy would be to reduce the susceptibility of most animals, while artificially increasing the susceptibility of a few ‘sacrificial lambs,’ which would receive almost all strikes protecting the rest of the flock. This is described as a ‘push–pull’ strategy and has been explored in more detail by Fenton et al (1999a). Of course, this is unlikely to be desirable or acceptable in practice, but it may be that the pull could be provided by something other than a highly susceptible sheep, such as a trap or other device baited with the appropriate type and quantity of chemical odours (Ashworth and Wall 1994). The work reviewed in this paper describes an important step in our understanding of the sheep blowfly system. The development of these models, which include a range of key, quantified parameters, allows accurate predictions to be made of the peak incidences of strike and, therefore, allow the effects of a range of possible farm management strategies on the incidence of sheep strike on individual sheep farms in Britain to be assessed, thereby determining more efficient, control strategies for protecting a flock from flystrike. We suggest that this approach is likely to be applicable and useful in a range of other host–disease systems of veterinary importance.
ACKNOWLEDGEMENTS We are indebted to our colleagues Katherine Smith, Eleanor Hayes, Isla Cruickshank, Paul Fisher and Kenton Morgan, for their contributions to the work reviewed here. We are grateful to the Royal Society, BBSRC, the Ministry of Agriculture Fisheries and Food and NERC for their financial support of various components of this work.
REFERENCES ATZENI, M.G., MAYER, D.G., SPRADBERRY, J.P., ANAMAN, K.A. & BUTLER, D.G. (1994) Comparison of the predicted impact of a screwworm fly outbreak in
Australia using a growth index model and a life-cycle model. Medical and Veterinary Entomology 8, 281–291 ASHWORTH, J.R. & WALL, R. (1994) Responses of the sheep blowflies Lucilia sericata and L. cuprina (Diptera: Calliphoridae) to odour and the development of semiochemical baits. Medical and Veterinary Entomology 8, 303–309 BECK, S.D. (1983) Insect thermoperiodism. Annual Review of Entomology 28, 91–108 BOAG, B. & THOMAS, R.J. (1971) Epidemiological studies on gastro-intestinal nematode parasites of sheep: infection patterns on clean and autumn-contaminated pasture. Research in Veterinary Science 12, 132–139 CORNWALL, R.L. (1975) The pattern of infection with gastro-intestinal nematodes in young fattening lambs at pasture. Research in Veterinary Science 18, 1–5 CRAGG, J.B. (1955) The natural history of sheep blowflies. Annals of Applied Biology 42, 197–207 DAVIES, M.W. (1929) Hibernation of Lucilia sericata, Mg. Nature 123, 759–760 DAVIES, L. (1948a) Observations on the development of Lucilia sericata (Mg.) eggs in sheep fleeces. Journal of Experimental Biology 25, 86–102 DAVIES, L. (1948b) Laboratory studies on the egg of the blowfly Lucilia sericata (Mg.). Journal of Experimental Biology 25, 71–85 DAVIES, W.M. & HOBSON, R.P. (1935) Sheep blowfly investigations. I. The relationship of humidity to blowfly attack. Annals of Applied Biology 22, 279–293 EISMANN, C.H. (1988) Upwind flight by gravid Australian sheep blowflies, Lucilia cuprina (Wiedemann) (Diptera: Calliphoridae), in response to stimuli from sheep. Bulletin of Entomological Research 78, 273–279 EVANS, A.C. (1936) The physiology of the sheep blow-fly Lucilia sericata Meig. (Diptera). Transactions of the Royal Entomological Society 85, 363–378 FENTON, A. & WALL, R. (1997). Sensitivity analysis of a stochastic model of the sheep blowfly Lucilia sericata. Journal of Applied Ecology 34, 1023–1031 FENTON, A., WALL, R. & FRENCH, N. (1997) Sensitivity analysis of deterministic and stochastic simulation models of populations of the sheep blowfly, Lucilia sericata. Journal of Theoretical Biology 184, 139–148 FENTON, A., WALL, R. & FRENCH, N.P. (1998a) The incidence of ovine myiasis by the blowfly Lucilia sericata on sheep farms in Britain: a simulation model. Veterinary Parasitology 76, 211–228 FENTON, A., WALL, R. & FRENCH, N.P. (1998b) The effect of farm management strategies on the incidence of sheep strike in Britain: a simulation analysis. Veterinary Parasitology 79, 341–357 FENTON, A., WALL, R. & FRENCH, N.P. (1999a) The effects of oviposition aggregation on the incidence of sheep blowfly strike. Veterinary Parasitology 83, 137–150 FENTON, A., WALL, R. & FRENCH, N.P. (1999b) Oviposition aggregation in the blowfly Lucilia cuprina in Australia. Medical and Veterinary Entomology 13, 453–456 FRENCH, N.P. & MORGAN, K.L. (1996a) A model of ovine cutaneous myosis using the predicted abundance of Lucilia sericata and a pattern of sheep susceptibility. Preventive Veterinary Medicine 26, 143–155 FRENCH, N.P. & MORGAN, K.L. (1996b) Role of neonatal and maternal risk factors in the faecal soiling of lambs. Veterinary Record 134, 460–465 FRENCH, N.P., WALL, R., CRIPPS, P.J. & MORGAN, K.L. (1992) Incidence, regional distribution and control of blowfly strike in England and Wales. Veterinary Record 131, 337–342 FRENCH, N.P., WALL, R. & MORGAN, K.L. (1995) The seasonal pattern of sheep blowfly strike in England and Wales. Medical and Veterinary Entomology 9, 1–8 FRENCH, N.P., PARKIN, T.D.H. & MORGAN, K.L. (1996) A case control study of blowfly strike in lambs. Veterinary Record 139, 384–388 HALL, M.J.R. & WALL, R. (1995) Myiasis in humans and domestic animals. Advances in Parasitology 35, 258–334 HAYES, E. & WALL, R. (1998) Measurement of age and population age structure in the blowfly Lucilia sericata (Meigen) (Diptera: Calliphoridae). Journal of Insect Physiology 44, 895–901 HAYES, E. & WALL, R. (1999) Mortality rate, reproductive output and trap response bias in populations of the blowfly Lucilia sericata. Ecological Entomology 24, 300–307 HIGLEY, L.G., PEDIGO, L.P. & OSTLIE, H.R. (1986) Degday: a program for calculating degree-days and assumptions behind the degree-day approach. Environmental Entomology 15, 999–1016 MacLEOD, J. (1940) The moisture balance of the living fleece in relation to blowfly myiasis, with some remarks on the Australian and British conceptions of susceptibility. Annals of Applied Biology 27, 379–392 MacLEOD, J. (1943a) A survey of British sheep blowflies. Bulletin of Entomological Research 34, 65–88 MacLEOD, J. (1943b) A survey of British sheep blowflies. II. Relation of strike to host and edaphic factors. Bulletin of Entomological Research 84, 95–111 MICHEL, J.F. (1976) The epidemiology and control of some nematode infections in grazing animals. Advances in Parasitology 14, 355–397 MOON, R.D. (1983) Simulating developmental time of preadult face flies (Diptera: Muscidae) from air temperature records. Environmental Entomology 12, 943–948 PREUSS, K.P. (1983). Day-degree methods for pest management. Environmental Entomology 12, 613–619 SMITH, K.E. & WALL, R. (1997a) The use of carrion as breeding sites by the blowfly Lucilia sericata and other Calliphoridae. Medical and Veterinary Entomology 11, 38–44 SMITH, K.E. & WALL, R. (1997b) Asymmetric competition between larvae of the blowflies, Calliphora vicina and Lucilia sericata in carrion. Ecological Entomology 22, 468–474
Sheep blowfly strike: a model approach WAGNER, T.L., WU, H., SHARPE, P.J., SCHOOLFIELD, R.M. & COULSON, R.N. (1984) Modeling insect development rates: a literature review and application of a biophysical model. Annals of the Entomological Society of America 77, 208–225 WALL, R. (1993) The reproductive output of the blowfly Lucilia sericata. Journal of Insect Physiology 9, 743–750 WALL, R. & SMITH, K.E. (1997) The potential for control of the blowfly Lucilia sericata using odour-baited targets. Medical and Veterinary Entomology 11, 335–341 WALL, R., LANGLEY, P.A. & MORGAN, K.L. (1991) Ovarian development and pteridine accumulation for age determination in the blowfly Lucilia sericata. Journal of Insect Physiology 37, 863–868 WALL, R., FRENCH, N.P. & MORGAN, K. (1992a) Blowfly species composition in sheep myiasis in Britain. Medical and Veterinary Entomology 6, 177–178 WALL, R., FRENCH, N. & MORGAN, K. (1992b) Effects of temperature on the development and abundance of the sheep blowfly Lucilia sericata. Bulletin of Entomological Research 82, 125–131 WALL, R., GREEN, C., FRENCH, N. & MORGAN, K. (1992c) Development of an attractive target for the sheep blowfly Lucilia sericata. Medical and Veterinary Entomology 6, 67–74
9
WALL, R., FRENCH, N. & MORGAN, K.L. (1993a) Predicting the abundance of the blowfly Lucilia sericata (Diptera: Calliphoridae). Bulletin of Entomological Research 83, 431–436 WALL, R., FRENCH, N. & MORGAN, K.L. (1993b) Sheep blowfly population control: development of a simulation model and analysis of management strategies. Journal of Applied Ecology 30, 743–751 WALL, R., FRENCH, N.P. & MORGAN, K.L. (1995) Population suppression for control of the blowfly Lucilia sericata and sheep blowfly strike. Ecological Entomology 20, 91–97 WARDHAUGH, K.G. & DALLWITZ, R. (1984) Covert flystrike. Wool Technology and Sheep Breeding 32, 15–19 WATTS, J.E. & MARCHANT, R.S. (1977) The effects of diarrhoea, tail length and sex on the incidence of breech strike in modified mulesed merino sheep. Australian Veterinary Journal 53, 118–123 WATTS, J.E. & PERRY, D.A. (1975) Observations on breech strike in scouring sheep. Australian Veterinary Journal 51, 586–587 Accepted February 11, 2000