The extent to which host biology, ecology and phylogeny determine the diversity of macroparasite assemblages has been investigated in recent years in several taxa, including fish. However, consensus has not been reached probably as a result of data being collected from different sources, different temporal scales or host and parasite biogeography and phylogeny having greater influence than expected. The present study evaluates the relative importance of 27 biological, ecological and phylogenetic characteristics of 14 flatfish species on the diversity of their ecto- and endoparasite assemblages, comprising a total of 53 taxa. Redundancy analyses were applied to the mean abundance of each parasite taxa infecting each host and to the richness, taxonomic distinctness and variance in taxonomic distinctness calculated for each assemblage within each host. Only a few host characteristics contributed significantly to the observed patterns: host distribution was more important in determining the type and mean abundance of ectoparasites present in an assemblage, whereas diversity of these assemblages were mainly related to the host's maximum size. Endoparasite mean abundance and diversity were mostly influenced by the number of food items ingested and by the presence of Crustacea and Polychaeta in the diet. However, the sympatric occurrence of related hosts also played an important role in the diversity values found in macroparasite assemblages. Results showed that a host characteristic has different importance according to the host-parasite relationship being examined, suggesting an important role for host-parasite co-evolution on the diversity of extant macroparasite assemblages.

Macroparasites almost invariably exhibit overdispersed distributions of parasites/host, yet the specific causes of such aggregations remain poorly understood. The present study focused on the distribution of the parasitic nematode Howardula aoronymphium among its hosts, several species of mycophagous Drosophila. The distribution of parasites/host is close to random for cohorts of flies of a given host species emerging from single mushrooms. At the level of Howardula populations, overdispersion of parasites among hosts results primarily from variation among subgroups of hosts in their exposure to infective-stage nematodes. The sources of variation identified in this study include Drosophila host species, the site where flies bred, mushroom species within sites, and, most importantly, individual mushrooms within mushroom species at a site. For the mean intensity of parasitism observed in this study, the degree of aggregation is typical of macroparasites in general. Combinations of random distributions with different means, resulting from variation among groups in exposure to parasites, may be a common cause of the overdispersion of macroparasites among hosts.

In this paper the dynamics and control of nematode parasites of farmed ruminants are discussed via a qualitative analysis of a differential equation model. To achieve this a quantity, ‘the basic reproduction quotient’ (Q0), whose definition coincides with previous definitions of R0 for macroparasites, but extends to models with periodic time-varying transition rates between parasite stages or management interventions, is introduced. This quantity has the usual threshold property: if Q0 is less than one the parasite population cannot maintain itself in the host population, and in the long term becomes extinct; but if Q0 is greater than one the parasite can invade the host population. An alternative quantity, R(E), that is often easier to calculate is also introduced, and shown to have the same threshold property. The use of these two quantities in analysing models for the dynamics of nematodes in complex situations is then demonstrated, with reference to the dynamics of mixed parasite species in one host; the effects of breeding host animals for resistance to parasitism; and the development of parasite strains that are resistant to chemotherapy. Five examples are discussed using parameters for the dynamics of nematode infections in sheep, and some statements on control policies are derived.

In this paper we review the published literature on patterns of abundance and aggregation of macroparasites in wildlife host populations. We base this survey on quantitative analyses of mean burden and a number of measures of the degree of aggregation of parasite burdens between hosts. All major parasite and vertebrate host taxa were represented in the database. Mean parasite burden was found to be log-normally distributed, indicating that all parasite burdens are regulated to some degree. In addition, all but one of the parasitic infections were aggregated with respect to their hosts, and the relationship between log mean parasite burden and log variance was found to be very strong (R2 = 0·87). That is, for a given mean parasite burden there are constraints on the degree of variation in individual host burdens. The aggregated nature of the parasitic infections is also apparent from other measures of the degree of aggregation: prevalence – mean relationships, and the negative binomial parameter, k. Using a relatively new technique for parasitological infection data – tree-based models, as well as traditional linear models – a number of the parasitic infections was found to be associated with systematically lower or higher parasite burdens. Possible biological explanations for these and other patterns are proposed.

The dynamics of host-macroparasite infections pose considerable challenges for stochastic modelling because of the need to take into account a large number of relevant factors and many nonlinear interactions between them. This paper focuses attention on the infection transmission process and the effects of specific modelling assumptions about the mechanisms involved. Some dramatically simplified linear models are considered; they are based on multidimensional linear birth and death processes, and are designed to illuminate qualitative effects of interest. Both single and compound infections are allowed. It is shown that such simple models can generate and increase dispersion of parasite counts, even among homogeneous hosts.

Frequency distributions from 49 published wildlife host–macroparasite systems were analysed by maximum likelihood for goodness of fit to the negative binomial distribution. In 45 of the 49 (90%) data-sets, the negative binomial distribution provided a statistically satisfactory fit. In the other 4 data-sets the negative binomial distribution still provided a better fit than the Poisson distribution, and only 1 of the data-sets fitted the Poisson distribution. The degree of aggregation was large, with 43 of the 49 data-sets having an estimated k of less than 1. From these 49 data-sets, 22 subsets of host data were available (i.e. host data could be divided by either host sex, age, where or when hosts were sampled). In 11 of these 22 subsets there was significant variation in the degree of aggregation between host subsets of the same host–parasite system. A common k estimate was always larger than that obtained with all the host data considered together. These results indicate that lumping host data can hide important variations in aggregation between hosts and can exaggerate the true degree of aggregation. Wherever possible common k estimates should be used to estimate the degree of aggregation. In addition, significant differences in the degree of aggregation between subgroups of host data, were generally associated with significant differences in both mean parasite burdens and the prevalence of infection.