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Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense

Cite this dataset

Becker, Daniel et al. (2019). Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense [Dataset]. Dryad.


1. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immune phenotypes across spatial scales. Identifying the most important spatial drivers of immunity could help preempt infectious disease risks, especially in the context of how large-scale factors such as urbanization affect defense by changing environmental conditions. 2. 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 defense, highlighting the need for large-scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favored 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. 3. 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 defense. 4. We use these findings to describe tools from geostatistics and spatial modeling 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. 5. We lastly discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions, and urbanization as being especially amenable to spatial approaches. We highlight opportunities posed by assessing spatial variation in host tolerance, 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.