Aggregated Distribution Of Parasites Research Articles

Distribution of Pomphorhynchus laevis s.l. (Acanthocephala) among fish species at a local scale: importance of fish biomass density.

Parasite distribution among hosts is a fundamental aspect of host-parasite interactions. Aggregated parasite distributions within and across host species are commonly reported and potentially influenced by many factors, whether host or parasite specific, or related to host-parasite encounter and compatibility. Yet, the respective role of each in observed parasite distributions are often unclear. Here, we documented the distribution of the acanthocephalan parasite Pomphorhynchus laevis sensu lato (s.l.) in two replicate fish host populations. Aggregated distributions were observed in both populations, within and across fish host species. We found a positive abundance-prevalence relationship across fish species, suggesting that resource availability (fish host biomass density) was the main driver of P. laevis s.l. distribution. This was supported by further positive associations between mean parasite load and fish biomass density. We found little evidence for intensity-dependent regulation within host (i.e. intra-host competition among co-infecting parasites). Furthermore, P. laevis s.l. infection had no detectable effect on fish condition indices, except on the body condition of female barbel (Barbus barbus). Therefore, P. laevis s.l. tended to accumulate with size/age within fish species, and with fish biomass density among fish species, with apparently negligible limitations due to intra-host intensity-dependent regulation of parasite, or to parasite-induced morbidity in fish. The relative availability of final hosts for trophic transmission thus appears to be the main driver of P. laevis s.l. distribution among fish.

Визначення раціонального обсягу вибірки в паразитологічних дослідженнях бутстреп-методом

Sampling of field material in parasitological studies is a highly time consuming procedure, which successful implementation also requires substantial financial and human resources. Therefore it is important to determine the rational sample size as a balance between the informative of the data from the small samples and the excess costs for collecting the unnecessary data. Due to aggregated distribution of parasites in populations of hosts it is difficult to calculate the confidence intervals of the statistical characteristics using the methods of classical statistics. In such situations it is need to use the non-parametric methods and resampling. The study offers practical recommendations to determine the rational sample size for calculation the interval estimates of the statistical parameters and the precision using the Bag of Little Bootstraps. The precision is defined as a confidence interval such that the estimate of the mean should be within some value of the true mean. The approach is illustrated on the example of monogenean parasites of Ligophorus llewellyni and L. pilengas from the so-iuy mullet. The initial data set included 224 elements for each parasite species. The results showed that the level of precision and parameter of aggregation are strongly affected by the sample size. It was found that the width of the confidence interval was equal or less of the empirical mean for samples more than 45 elements. The mean abundance is systematically underestimated for samples with 20–35 individuals. The small samples (n=10) have led to the unreliable estimates. The similar results were obtained in studies of Marques and Cabral. The proposed here approach will relief the sampling plan design and will help researchers to define the rational sample size and the precision level for the estimated mean abundance in parasitological studies.

Parasitic Nematode Abundance Aggregation as a Mechanism of the Adaptive Response of the Host Plant to Temperature Variations

The mathematical model of host–parasite relations suggested previously by the authors was applied to analyze the formation of the aggregated distribution of parasites in the case of the host plant–parasitic nematode system. For nearly the same conditions and empirical infection levels, nematode abundances in the host population followed the gamma distribution. Exposure to temperature stresses modifies the resistance of the plant population to infection. Experiments with prolonged chilling of potato plants prior to nematode infestation revealed no statistically reliable increase in the share of resistant plants compared to the control, although the mean and the range of variation of the infection rate, as well as the aggregation of the parasite distribution, decreased. Short-term chilling of the plants prior to infestation led to a reliable decrease in the mean abundance of parasites and to the lowest aggregation of the parasitic nematode in the host plant population. The results of this study showed that this temperature stress caused potatoes to develop a reliably high and uniform resistance to the nematode.

Explaining variability in parasite aggregation levels among host samples

Aggregated distributions among individual hosts are a defining feature of metazoan parasite populations. Heterogeneity among host individuals in exposure to parasites or in susceptibility to infection is thought to be the main factor generating aggregation, with properties of parasites themselves explaining some of the variability in aggregation levels observed among species. Here, using data from 410 samples of helminth parasites on fish hosts, I tested the contribution of (i) within-sample variation in host body size, taken as a proxy for variability in host susceptibility, and (ii) parasite taxon and developmental stage, to the aggregated distribution of parasites. Log-transformed variance in numbers of parasites per host was regressed against log mean number across all samples; the strong relationship (r²= 0.88) indicated that aggregation levels are tightly constrained by mean infection levels, and that only a small proportion of the observed variability in parasite aggregation levels remains to be accounted for by other factors. Using the residuals of this regression as measures of 'unexplained' aggregation, a mixed effects model revealed no significant effect of within-sample variation in host body size or of parasite taxon or stage (i.e. juvenile versus adult) on parasite aggregation level within a sample. However, much of the remaining variability in parasite aggregation levels among samples was accounted for by the number of individual hosts examined per sample, and species-specific and study-specific effects reflecting idiosyncrasies of particular systems. This suggests that with most differences in aggregation among samples already explained, there may be little point in seeking universal causes for the remaining variation.

Partitioning the Aggregation of Parasites on Hosts into Intrinsic and Extrinsic Components via an Extended Poisson-Gamma Mixture Model

It is well known that parasites are often highly aggregated on their hosts such that relatively few individuals host the large majority of parasites. When the parasites are vectors of infectious disease, a key consequence of this aggregation can be increased disease transmission rates. The cause of this aggregation, however, is much less clear, especially for parasites such as arthropod vectors, which generally spend only a short time on their hosts. Regression-based analyses of ticks on various hosts have focused almost exclusively on identifying the intrinsic host characteristics associated with large burdens, but these efforts have had mixed results; most host traits examined have some small influence, but none are key. An alternative approach, the Poisson-gamma mixture distribution, has often been used to describe aggregated parasite distributions in a range of host/macroparasite systems, but lacks a clear mechanistic basis. Here, we extend this framework by linking it to a general model of parasite accumulation. Then, focusing on blacklegged ticks (Ixodes scapularis) on mice (Peromyscus leucopus), we fit the extended model to the best currently available larval tick burden datasets via hierarchical Bayesian methods, and use it to explore the relative contributions of intrinsic and extrinsic factors on observed tick burdens. Our results suggest that simple bad luck—inhabiting a home range with high vector density—may play a much larger role in determining parasite burdens than is currently appreciated.

Does the early frog catch the worm? Disentangling potential drivers of a parasite age–intensity relationship in tadpoles

The manner in which parasite intensity and aggregation varies with host age can provide insights into parasite dynamics and help identify potential means of controlling infections in humans and wildlife. A significant challenge is to distinguish among competing mechanistic hypotheses for the relationship between age and parasite intensity or aggregation. Because different mechanisms can generate similar relationships, testing among competing hypotheses can be difficult, particularly in wildlife hosts, and often requires a combination of experimental and model fitting approaches. We used field data, experiments, and model fitting to distinguish among ten plausible drivers of a curvilinear age–intensity relationship and increasing aggregation with host age for echinostome trematode infections of green frogs. We found little support for most of these proposed drivers but did find that the parsimonious explanation for the observed age–intensity relationship was seasonal exposure to echinostomes. The parsimonious explanation for the aggregated distribution of parasites in this host population was heterogeneity in exposure. A predictive model incorporating seasonal exposure indicated that tadpoles hatching early or late in the breeding season should have lower trematode burdens at metamorphosis, particularly with simulated warmer climates. Application of this multi-pronged approach (field surveys, lab experiments, and modeling) to additional parasite–host systems could lead to discovery of general patterns in the drivers of parasite age–intensity and age–distribution relationships.Electronic supplementary materialThe online version of this article (doi:10.1007/s00442-010-1776-0) contains supplementary material, which is available to authorized users.

Searching for generality in the patterns of parasite abundance and distribution: Ectoparasites of a South African rodent, Rhabdomys pumilio

We studied abundance and distribution of seven ectoparasite species (fleas Chiastopsylla rossi and Dynopsyllus ellobius, a louse Polyplax arvicanthis, mites Androlaelaps fahrenholzi and Laelaps giganteus and two ticks Haemaphysalis elliptica and Hyalomma truncatum) exploiting the same populations of the rodent host Rhabdomys pumilio in South Africa. We considered three general patterns of abundance and distribution, namely (i) aggregated distribution of parasites amongst individual hosts; (ii) positive relationships between mean parasite abundance and their prevalence; and (iii) applicability of a simple epidemiological model based on mean parasite abundance and its variance to predict the observed patterns of prevalence. Our aims were to evaluate the relative role of host- versus parasite-associated factors by looking at similarity amongst different parasites in these patterns. In general, all parasites demonstrated strong similarity in each of the three patterns of abundance and distribution. However, the strength of these patterns differed amongst parasite species. We conclude that these patterns are driven mainly by hosts, but differences are caused by differences between various life-history traits of parasite species. Our results support the idea that general laws apply to parasite population ecology.

Stochastic and spatial dynamics of nematode parasites in farmed ruminants

Host-parasite systems provide powerful opportunities for the study of spatial and stochastic effects in ecology; this has been particularly so for directly transmitted microparasites. Here, we construct a fully stochastic model of the population dynamics of a macroparasite system: trichostrongylid gastrointestinal nematode parasites of farmed ruminants. The model subsumes two implicit spatial effects: the host population size (the spatial extent of the interaction between hosts) and spatial heterogeneity ('clumping') in the infection process. This enables us to investigate the roles of several different processes in generating aggregated parasite distributions. The necessity for female worms to find a mate in order to reproduce leads to an Allee effect, which interacts nonlinearly with the stochastic population dynamics and leads to the counter-intuitive result that, when rare, epidemics can be more likely and more severe in small host populations. Clumping in the infection process reduces the strength of this Allee effect, but can hamper the spread of an epidemic by making infection events too rare. Heterogeneity in the hosts' response to infection has to be included in the model to generate aggregation at the level observed empirically.

Distribution and repeatability of nematode faecal egg counts in dairy goats: a farm survey and implications for worm control

The aims of this study were to characterise trichostrongyle egg excretion in dairy goat flocks under various epidemiological conditions, and to assess the relative importance of animals in their first lactation and goats with high levels of milk production on the total egg output of the flock. The repeatability of egg excretion was estimated on 4 different dates in 14 dairy goat farms in France. Egg outputs were positively skewed on most farms suggesting an aggregated distribution of parasites. Within-year repeatability coefficients ranged from 0·29 to 0·82 suggesting that, on most farms, animals with high egg excretion on one occasion are likely to show high rates of excretion on other occasions. Comparisons of egg outputs from the selected subgroups showed that the high producing goats contributed prominently to egg excretion, particularly at times of peak parasitism. Results from goats in their first lactation were more equivocal. These results provide a rationale for anthelmintic strategies in dairy goats based on phenotypic characters.

Aggregated parasite distributions on hosts in a homogeneous environment: examining the Poisson null model

Parasites are typically aggregated on their hosts in nature. The null hypothesis is that parasites should follow a Poisson distribution if environment, parasites and hosts are homogeneous. From this starting point, models have shown that factors such as heterogeneity in host susceptibility and spatial aggregations of parasites may cause parasite aggregations on hosts. I used computer simulations to show that parasites typically become aggregated on their hosts even in a homogeneous environment where parasites do not differentially prefer any host, and hosts do not differ in susceptibility, provided that hosts are randomly distributed and spatial distance between host and parasite influences the likelihood of colonisation.

A stochastic model of schistosomiasis immuno-epidemiology.

Schistosomiasis is a helminth (worm) infection with approximately 200 million people infected worldwide. There is still controversy on whether differing worm burdens between individuals is a result of differing contact rates or of acquired immunity. In this paper, we present a stochastic modelling framework to address these issues. By using appropriate approximations for the higher moments of the joint distributions, differential equations for the means, variances and co-variances of infection and immunity can be obtained. Numerical solutions of these equations to obtain age profiles of the above properties were compared with Monte Carlo simulations of the stochastic process. Simulations showed that the results depended on whether between host heterogeneity was generated by differing contact rates or differing immune responses. Heterogeneity in contact rates produced a highly aggregated distribution of parasites with a large variance/mean ratio. Heterogeneity in the immune response had very little effect on the overall dynamics. This agrees with the predominant field evidence which would suggest that infection is mainly determined by ecology with a smaller contribution of immunity.

Schistosoma mansoni infection in a natural population of olive baboons (Papio cynocephalus anubis) in Gombe Stream National Park, Tanzania.

Infection with Schistosoma mansoni was studied in 5 troops of olive baboons (Papio cynocephalus amubis) in Gombe Stream National Park, Tanzania. Three troops were infected with S. mansoni. An aggregated distribution of parasites was observed among hosts. Troop membership was found to be the most significant factor influencing parasite prevalence. Age and reproductive status had no significant effect, but there was a trend for males to acquire higher levels of infection. However, age-prevalence curves showed a high infection in young baboons declining in the older baboons. Behavioural components of exposure--as measured in water-contact pattern--may be related to parasite burden. A 'peak shift' between infection in different age-classes in the different troops was observed: troops with higher schistosome prevalences displayed an earlier peak in prevalence of infection. The baboon troop with the most contact with people showed highest prevalence of infection possibly due to longer exposure to the parasite than the other troops and/or higher host density.

Analysis of Aggregated Parasite Distributions: A Comparison of Methods

1. Empirically, parasite distributions are often best described by the negative binomial distribution; some hosts have many parasites while most have just a few. Thus identifying heterogeneities in parasite burdens using conventional parametric methods is problematical. In an attempt to conform to the assumptions of parametric analyses, parasitologists and ecologists frequently log-transform their overdispersed data prior to analysis. In this paper, we compare this method of analysis with an alternative, generalized linear modelling (GLM), approach. 2. We compare the classical linear model using log-transformed data (Model 1) with two GLMs: one with Poisson errors and an empirical scale parameter (Model 2), and one in which negative binomial errors are explicitly defined (Model 3). We use simulated datasets and empirical data from a long-term study of parasitism in Soay Sheep on St Kilda to test the efficacies of these three statistical models. 3. We conclude that Model 1 is much more likely to produce type I errors than either of the two GLMs, and that it also tends to produce more type II errors. Model 3 is only marginally more successful than Model 2, indicating that the use of an empirical scale parameter is only slightly more likely to generate errors than using an explicitly defined negative binomial distribution. Thus, while we strongly recommend the use of GLMs over conventional parametric analyses, either GLM method will serve equally well.

Mathematical models for the population biology of Ostertagia ostertagi and the significance of aggregated parasite distributions

Parasite frequency distributions are frequently aggregated. Such distributions are conveniently described using the negative binomial frequency distribution. This distribution is completely characterized by two parameters: the mean of the distribution and an exponent, k. The degree of aggregation is inversely proportional to the value of k. Aggregated parasite distributions enhance the ability of regulatory processes to maintain parasite populations at or near their equilibrium level but incorporating parasite frequency distributions in realistic models of parasite population biology is fraught with difficulty (several simplified examples are given). Indeed, it is not always possible to incorporate parasite frequency distributions and the question arises whether this compromises model performance. Trichostrongylid nematodes, including Ostertagia ostertagi, are aggregated but the estimated value of k for such populations is usually greater than 1. This is typical of populations with high population means (tens of thousands). It is shown that when the degree of aggregation is such that k > 1, the results of a model which recognizes parasite frequency distribution is not much different from the results of a model which assumes all hosts contain exactly the same number of parasites.

Parasite-induced parthenogenesis in a freshwater snail: stable, persistent patterns of parasitism.

The role of parasites in the evolution of host reproductive modes has gained renewed interest in evolutionary ecology. It was previously argued that obligate parthenogenesis (all-female reproduction) arose in a freshwater snail, Campeloma decisum, as a consequence of severe sperm limitation caused by an unencysted trematode, Leucochloridiomorpha constantiae. In the present study, certain conditions are examined for parasitic castration to account for the maintenance of parthenogenesis: the spatial patterns of the prevalence and intensity of infection on a broad geographical scale and its relationship to host genotype; the recovery from infection after isolation from sources of infection; age-related patterns of infections; and the effects of L. constantiae on snail fecundity.In contrast to the common pattern of the aggregated distribution of parasites within host populations, many snail populations with high prevalence and intensity of infection have non-aggregated parasite distributions. Clonal genotype of the host explained little of the variation in intensity and prevalence of infection by the parasite. Female snails maintained similar prevalence and intensity of infection after isolation, and individuals accumulated parasites throughout their lifespan, both of which suggest there is no effective immune response to infection by L. constantiae. Snail fecundity is not significantly influenced by the intensity of infection. These results suggest that L. constantiae may have represented a strong selective force against males during the initial introduction of this parasite into sexual snail populations because of the persistent nature of infection.