Tuesday, October 6, 2015

Does context alter the dilution effect?

Understanding disease and parasites from a community context is an increasingly popular approach and one that has benefited both disease and ecological research. In communities, disease outbreaks can reduce host populations, which will in turn alter species' interactions and change community composition, for example. Community interactions can also alter disease outcomes - decreases in diversity can incr-
Frogs in California killed by the chytrid fungus
(source: National Geographic News)
ease disease risk for vulnerable hosts, a phenomenon known as the dilution effect. For example, in a high diversity system, a mosquito may bite individuals from multiple resistant species as well as those from a focal host, potentially reducing the frequency of focal host-parasite contact. Hence the dilution effect may be a potential benefit of biodiversity, and multiple recent studies provide evidence for its existence.

Not all recent studies support this diversity-disease risk relationship, however, and it is not clear whether the dilution effect might depend on spatial scale, the definition of disease risk used, or perhaps the system of study. A recent paper in Ecology Letters from Alexander Strauss et al. does an excellent job of deconstructing the assumptions and implicit models behind the dilution effect and exploring whether context dependence might explain some of the variation in published results. The authors develop theoretical models capturing hypothesized mechanisms, and then use these to predict the outcomes of mesocosm experiments.

Suggested mechanisms behind the dilution effect include 1) that diluter species (i.e. not the focal host) reduce parasite encounters for focal hosts, with little or no risk to themselves (resistant); and 2) diluters may compete for resources or space against the focal host and so reduce the host population, which should in turn reduce density dependent disease risk. But, if these are the mechanisms, there are a number of corollaries that should not be ignored. For example, what if the diluter species is the poorer competitor and so competition reduces diluter populations? What if diluter species aren't completely resistant to disease and at large populations are susceptible? The cost/benefit analysis of having additional species present may differ depending on any number of factors in a system.

The authors focus on a relatively simple system - a host species Daphnia dentifera, a virulent fungus Metschnikowia bicuspidata, and a competitor species Ceriodaphnia sp.. Observations suggest that epidemics in the Daphnia species may smaller where the second species occurs - Ceriodaphnia removes spores when filter feeding and also competes for food. By measuring a variety of traits, they could estimate the R* and R0 values - roughly, low R* values indicated strong competitors and high  Rvalues indicated groups that have high disease transmission rates. Context dependence is introduced by considering three different genotypes of the Daphnia: these genotypes varied in R* and Rvalues, allowing them to test whether changing competitive ability and disease transmission in the Daphnia might alter the strength or even presence of a dilution effect. Model predictions were then tested directly against matching mesocosm experiments.

The results show clear evidence of context dependence in the dilution effect (and rather nice matches between model expectations and mesocosm data). Three possible scenarios are compared, which differ in the Daphnia host genotype and its competitive and transmission characteristics. 
  1. Dilution failure: the result of a host genotype that is a strong competitor, and a large epidemic (low R*, high R0). 
  2. Dilution success: the result of a host that is a weak competitor and a moderate epidemic (host has high R*, moderate R0). 
  3. Dilution irrelevance: the outcome of a host that is a weak competitor, and a small epidemic (high R*, low R0). 

From Strauss et al. 2015. The y-axis shows percent host population infected, solid lines show the disease prevalence without the diluter; dashed show host infection when diluter is present.

Of course, all models are simplifications of the real world, and it is possible that in more diverse systems the dilution effect might be more difficult to predict. However, as competition is a component of most natural systems, its inclusion may better inform models of disease risk. Other models for other systems might suggest different outcomes, but this one provides a robust jumping off point for future research into the dilution effect.


Sean Menke said...

Thank you for this write-up. I really appreciate people calling out interesting papers that they have read and the thoughtful summary of the paper. I find it helpful as guide for papers I should check out, spend more time with, or even use for class.

Caroline Tucker said...

Thanks! I'm actually co-teaching a grad seminar and one of the students chose this paper to discuss. Great choice, and the class has proven a good way to keep on top of new papers.