Longitudinal dynamics of co-infecting gastrointestinal parasites in a wild sheep population

Abstract

Within-year variation in infection is a ubiquitous feature of natural populations, but is determined by a complex interplay of environmental, parasitological and host factors. At the same time, co-infection is the norm in the wild. Longitudinal dynamics of co-infecting parasites may therefore be further complicated by covariation across multiple parasites. Here, we used fecal parasite egg and oocyst counts collected repeatedly from individually marked wild Soay sheep to investigate seasonal dynamics of six gastrointestinal parasite groups. Prevalence and abundance tended to be higher in spring and summer, and abundance was higher in lambs compared to adults. We found that within-year variation in highly prevalent strongyle nematode counts was dependent on adult reproductive status, where reproductive ewes had distinct dynamics compared to males and barren ewes. For similarly prevalent coccidia we found an overall peak in oocyst counts in spring but no differences among males, barren and pregnant ewes. Using multivariate mixed-effects models, we further show that apparent positive correlation between strongyle and coccidia counts was driven by short-term within-individual changes in both counts rather than long-term among-individual covariation. Overall, these results demonstrate that seasonality varies across demographic and parasite groups and highlight the value of investigating co-infection dynamics over time.

Age specific impacts of vegetation functional traits on gastro-intestinal nematode parasite burdens in a large herbivore

“…Soay sheep do show some sex-based social segregation; males tend to form a dominance hierarchy, and male lambs tend to leave their mothers earlier than female lambs (Clutton-Brock et al ., 2004). Additionally, adult males have a different seasonal FEC pattern to lambs or adult females, potentially leading to altered transmission and infection dynamics (Sweeny et al ., 2022). Incorporating social networks and accounting for how different interactions (e.g., mother-offspring relationships) may drive disease transmission could provide further information behind the mechanisms of such transmission.…”

“…We conducted all statistical analyses with August FEC as our response variable in R v.4.0.4 (R Core Team, 2021). Individuals were categorised as adults, yearlings, or lambs due to the pronounced variation in FEC across the age groups (Sweeny et al ., 2022). Spatial autocorrelation, where samples or individuals closer together in time and space are more alike than those further apart, is becoming increasingly important to consider in studies of disease ecology (Albery et al ., 2022).…”

Sex-biased infections scale to population impacts for an emerging wildlife disease

“…Elements of populations that create structure such as classes of individuals of specific ages, sexes, or breeding stages, can have profound effects on disease dynamics (3,(5)(6)(7)(8)(9). Sex is an especially important factor because sex-biases in infections can contribute to differential transmission through populations due to behavior (10)(11)(12)(13)(14)(15), amplify outbreaks due to seasonal changes in susceptibility (16)(17)(18)(19), and modify population impacts through disproportionate mortality (20)(21)(22). Differences in infection and mortality can also modulate virulence evolution through sex-specific immune responses that affect pathogen replication and growth (23,24).…”

Exposure and susceptibility: The Twin Pillars of infection

“…For example, a recent study in Soay sheep found that reproductive females experience a peak of strongyle abundance in spring followed by a decline into summer compared to males who showed later peaks in the summer (Sweeny et al, 2022). Although this spring peak for females is expected due to relaxed immunity (Hayward et al, 2018), due to the observational nature of the data it is unclear whether varied peaks for male and females are due primarily to susceptibility, exposure or a combination of both processes (Sweeny et al, 2022). alongside space use and direct interaction networks (to represent exposure risk).…”

“…Even with a well‐specified model and accurate empirical measurements, it may be very difficult to conclusively state that exposure or susceptibility is responsible for a given change in burden without experimental manipulation; fully observational studies may be able to state that a given pattern ‘conforms to expectations’, but without conclusively identifying the underlying mechanisms. For example, a recent study in Soay sheep found that reproductive females experience a peak of strongyle abundance in spring followed by a decline into summer compared to males who showed later peaks in the summer (Sweeny et al, 2022). Although this spring peak for females is expected due to relaxed immunity (Hayward et al, 2018), due to the observational nature of the data it is unclear whether varied peaks for male and females are due primarily to susceptibility, exposure or a combination of both processes (Sweeny et al, 2022).…”