Wednesday, October 21, 2015

Scientists + Communication = ??

An academic is expected to be a jack of many trades – handling research, teaching, mentorship, administration, committee work, reviewing, grant-writing, and editorial duties. Science communication is increasingly being added to that list as well. Outreach, public engagement and science communication are all terms thrown around (e.g. the 'Broader Impacts' section of many NSF grants, for example, includes the possibility "Broaden dissemination to enhance scientific and technological understanding"). Sometimes this can include communication between academics (conferences, seminars, blogs like this one) but often it is meant to include communication with the general public. Statistics about low science literacy at least partially motivate this. For example, “Between 29% and 57% of Americans responded correctly to various questions measuring the concepts of scientific experiment and controlling variables. Only 12% of Americans responded correctly to all the questions on this topic, and nearly 20% did not respond correctly to any of them”. (

Clearly improving scientific communication is a worthy goal. But at times it feels like it is a token addition to an application, one that is outsourced to scientists without providing the necessary resources or training. . This is a problem because if we truly value scientific communication, the focus should be on doing it in a thoughtful manner, rather than as an afterthought. I say this because firstly because communicating complex ideas, some of which may require specialized terms and background knowledge, is difficult. The IPCC summaries, meant to be accessible to lay readers were recently reported to be incredibly inaccessible to the average reader (and getting worse over time!). Their Flesch reading ease scores were lower than those of Einstein’s seminal papers, and certainly far lower than most popular science magazines. Expert academics, already stretched between many skills, may not always be the best communicators of their own work.

Secondly, even when done well, it should be recognized that the audience for much science communication is a minority of all media consumers – the ‘science attentive’ or ‘science enthusiast’ portion of the public. Popular approaches to communication are often preaching to the choir. And even within this group, there are topics that naturally draw more interest or are innately more accessible. Your stochastic models will inherently be more difficult to excite your grandmother about than your research on the extinction of a charismatic furry animal. Not every topic is going to be of interest to a general audience, or even a science-inclined audience, and that should be okay.

So what should our science communication goals be, as scientists and as a society? There is entire literature on this topic (the science of science communication, so to speak), and it provides insight into what works and what is needed. However, “....despite notable new directions, many communication efforts continue to be based on ad-hoc, intuition-driven approaches, paying little attention to several decades of interdisciplinary research on what makes for effective public engagement.”

One approach supported by this literature process follows 4 steps:

1) Identify the science most relevant to the decisions that people face;
2) Determine what people already know;
3) Design communications to fill the critical gaps (between what people know and need to know);
4) Evaluate the adequacy of those communications.

This approach inherently includes human values (what do people want or need to know), rather than a science-centric approach. In addition, to increase the science-enthusiast fraction of the public, focusing on education and communication for youth should be emphasized.

The good news is that science is respected, even when not always understood or communicated well. When asked to evaluate various professions, nearly 70% of Americans said that scientists “contribute a lot” to society (compared to 21% for business executives), and scientists typically are excited about interacting with the public. But it seems like a poor use of time and money to simply expect academics to become experts on science communication, without offering training and interdisciplinary relationships. So, for example, in the broader impacts section of a GRFP, maybe NSF should value taking part in a program (led by science communication experts) on how to communicate with the public; maybe more than giving a one-time talk to 30 high school students. Some institutions provide more resources to this end than others, but the collaborative and interdisciplinary nature of science communication should receive far more emphasis. And the science of science communication should be a focus – data-driven approaches are undeniably more valuable.

None of this is to say that you shouldn't keep perfecting your answer for when the person besides you on an airplane asks you what you do though :-) 

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.