Amy R. Sweeny

Gastrointestinal nematode (GIN) parasites play an important role in the ecological dynamics of many animal populations. Recent studies suggest that fine‐scale spatial variation in GIN infection dynamics is important in wildlife systems, but the environmental drivers underlying this variation remain poorly understood. We used data from over two decades of GIN parasite egg counts, host space use, and spatial vegetation data from a long‐term study of Soay sheep on St Kilda to test how spatial autocorrelation and vegetation in an individual's home range predict parasite burden across three age groups. We developed a novel approach to quantify the plant functional traits present in a home range to describe the quality of vegetation present. Effects of vegetation and space varied between age classes. In immature lambs, strongyle parasite faecal egg counts (FEC) were spatially structured, being highest in the north and south of our study area. Independent of host body weight and spatial autocorrelation, plant functional traits predicted parasite egg counts. Higher egg counts were associated with more digestible and preferred plant functional traits, suggesting the association could be driven by host density and habitat preference. In contrast, we found no evidence that parasite FEC were related to plant functional traits in the host home range in yearlings or adult sheep. Adult FEC were spatially structured, with highest burdens in the north‐east of our study area, while yearling FEC showed no evidence of spatial structuring. Parasite burdens in immature individuals appear more readily influenced by fine‐scale spatial variation in the environment, highlighting the importance of such heterogeneity for our understanding of wildlife epidemiology and health. Our findings support the importance of fine‐scale environmental variation for wildlife disease ecology and provides new evidence that such effects may vary across demographic groups within a population.

Exposure and susceptibility underlie every organism's infection status, and an untold diversity of factors can drive variation in both. Often, both exposure and susceptibility change in response to a given factor, and they can interact, such that their relative contributions to observed disease dynamics are obscured. These independent and interlinked changes often complicate empirical inference in disease ecology and ecoimmunology. Although many disease ecology studies address this problem, it is often implicit rather than explicit and requires a specific set of tools to tackle. Moreover, as yet, there is no established conceptual framework for disentangling susceptibility and exposure processes. Here, we consolidate previous theory and empirical understanding regarding the entwined effects of susceptibility and exposure, which we refer to as ‘the Twin Pillar Problem’. We provide a framework for conceptualising exposure–susceptibility interactions, where they obscure, confound, induce or counteract one another, providing some well‐known examples for each complicating mechanism. We synthesise guidelines for anticipating and controlling for covariance between exposure and susceptibility, and we detail statistical and operational methodology that researchers have employed to deal with them. Finally, we discuss novel emerging frontiers in their study in ecology, and their potential for further integration in the fields of wildlife and human health. Read the free Plain Language Summary for this article on the Journal blog.