The role of host community abundance-richness relationships in pathogen transmission

Background/Question/Methods

A developing idea from the field of disease ecology postulates that declines in host biodiversity lead to elevated disease risk. However, different elements of host community composition and pathogen transmission mode have variable effects on diversity-disease patterns that could influence null expectations. Previous community-level disease models have revealed important and interesting complexities involving the roles of pathogen transmission mode, the variability of pathogen susceptibility among host species, as well as the role of vector diversity. Here, we build upon previous multi-species models to study how an important metric of host community composition – the scaling of total host community abundance with species richness – influences predicted diversity-disease relationships. Specifically, we consider the effects of additive, compensatory and saturating host abundance on pathogen transmission in simulated multi-host communities. We also consider how abundance-richness relationships might influence the detectability of diversity-disease patterns in empirical data, which should help explain the variability observed in natural community disease dynamics.

Results/Conclusions

We find that for pathogens with density-dependent transmission, when host community abundance saturates with increasing richness, non-monotonic trends emerge between pathogen transmission and host richness. Our model also demonstrates that host species identity drives high variability in pathogen transmission in depauparate communities, but this effect declines with richness. Finally, using simulation we show that the non-monotonic relationship observed with host community saturation may obscure patterns in empirical data due to effects of sample size. Our analyses suggest that understanding the patterns of host community ecology and pathogen transmission mode will be crucial for predicting diversity-disease relationships in natural systems and that high variability may hinder the finding of generalizable trends.