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Abstract Identifying the factors that affect host–parasite interactions is essential for understanding the ecology and dynamics of vector‐borne diseases and may be an important component of predicting human disease risk. Characteristics of hosts themselves (e.g., body condition, host behavior, immune defenses) may affect the likelihood of parasitism. However, despite highly variable rates of parasitism and infection in wild populations, identifying widespread links between individual characteristics and heterogeneity in parasite acquisition has proven challenging because many zoonoses exist over wide geographic extents and exhibit both spatial and temporal heterogeneity in prevalence and individual and population‐level effects. Using seven years of data collected by the National Ecological Observatory Network (NEON), we examined relationships among individual host condition, behavior, and parasitism byIxodidticks in a keystone host species, the white‐footed mouse,Peromyscus leucopus. We found that individual condition, specifically sex, body mass, and reproductive condition, had both direct and indirect effects on parasitism by ticks, but the nature of these effects differed for parasitism by larval versus nymphal ticks. We also found that condition differences influenced rodent behavior, and behavior directly affected the rates of parasitism, with individual mice that moved farther being more likely to carry ticks. This study illustrates how individual‐level data can be examined using large‐scale datasets to draw inference and uncover broad patterns in host–parasite encounters at unprecedented spatial scales. Our results suggest that intraspecific variation in the movement ecology of hosts may affect host–parasite encounter rates and, ultimately, alter zoonotic disease risk through anthropogenic modifications and natural environmental conditions that alter host space use. 

Abstract As a highly successful introduced species, house sparrows (Passer domesticus) respond rapidly to their new habitats, generating phenotypic patterns across their introduced range that resemble variation in native regions. Epigenetic mechanisms likely facilitate the success of introduced house sparrows by aiding particular individuals to adjust their phenotypes plastically to novel conditions. Our objective here was to investigate patterns of DNA methylation among populations of house sparrows at a broad geographic scale that included different introduction histories: invading, established, and native. We defined the invading category as the locations with introductions less than 70 years ago and the established category as the locations with greater than 70 years since introduction. We screened DNA methylation among individuals (n = 45) by epiRADseq, expecting that variation in DNA methylation among individuals from invading populations would be higher when compared with individuals from established and native populations. Invading house sparrows had the highest variance in DNA methylation of all three groups, but established house sparrows also had higher variance than native ones. The highest number of differently methylated regions were detected between invading and native populations of house sparrow. Additionally, DNA methylation was negatively correlated to time-since introduction, which further suggests that DNA methylation had a role in the successful colonization’s of house sparrows. 

Abstract The prevalence and intensity of parasites in wild hosts varies across space and is a key determinant of infection risk in humans, domestic animals and threatened wildlife. Because the immune system serves as the primary barrier to infection, replication and transmission following exposure, we here consider the environmental drivers of immunity. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immunity across spatial scales. Identifying the most important spatial drivers of immunity could help pre‐empt infectious disease risks, especially in the context of how large‐scale factors such as urbanization affect defence by changing environmental conditions.We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e. macroimmunology). We first review spatial factors that could generate spatial variation in defence, highlighting the need for large‐scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favoured over small‐scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods.We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defence.We use these findings to describe tools from geostatistics and spatial modelling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed‐effects models that account for spatial variability while also allowing researchers to account for both individual‐ and habitat‐level covariates.We finally discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions and urbanization as being especially amenable to large‐scale spatial approaches. Methodologically, we highlight critical opportunities posed by assessing spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite pressure, coupling large‐scale field studies with small‐scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta‐analysis to identify generalizable spatial patterns. Such work will facilitate scaling ecoimmunology from individual‐ to habitat‐level insights about the drivers of immune defence and help predict where environmental change may most alter infectious disease risk.