# AAPA and the March for Science

I am just back from the annual meeting of the American Association of Physical Anthropologists in New Orleans. As always, it was great to catch up with colleagues and friends. I’m never quite sure about how I fit in to AAPA, but I certainly know a lot of people there (and, of course, I’m never quite sure about how I fit in to nearly any academic conference I attend!). I was struck by what seems like a pretty dramatic demographic shift from previous incarnations of AAPA. Overall, the assembled conference-goers seemed quite a bit younger. The image I have in my mind of AAPA is a bunch of stodgy old dudes wearing polyester-mix sport coats. Not so much this year. So much ink! There was even a bit more diversity, which is an encouraging sign for a field dedicated to the study of human diversity. I really appreciate that AAPA is taking an active part in changing its heretofore woeful diversity problem and I’m looking forward to seeing the payoff from the new IDEAS Workshop (thanks on that front to Ripan Malhi and Susan Antón for getting the grant to make the workshop happen).

I have to admit, I didn’t see that many talks. This is kind of my idiom at scientific meetings. There are so many people to meet and talk to that it seems a bit wasteful to spend hour after hour listening to podium talks of, let’s face it, rather mixed quality. However, I did spend a lot of time in the poster hall. I saw a number of really interesting posters. A couple that stand out in my memory: Saige Kelmelis, together with her advisor Jim Wood and my former student Mike Price, had a terrific poster describing the use of multi-state demographic models to infer the effect of leprosy on survival in medieval Denmark (lesioned skeletons had an overall increase in the estimated mortality hazard in excess of a factor of six!). Adam Reynolds at Emory, along with Paul Hooper and a bunch of co-authors, had a poster describing a dynamic-state model for herd management in Mongolia that looked really innovative (and left me with so many questions — a good thing in a scientific conference). Alaina Schneider, a student in Herman Pontzer’s lab, presented awesome work measuring the energetic costs of immune function in a mouse model. Emma Pomeroy of Liverpool John Moores University had a neat poster on the ancient origins of chronic disease risk in South Asian populations. That was one of those great ones where I knew nothing going in and felt like I actually learned something new after our chat.

I presented in one of the human biology sessions organized by Aaron Blackwell on some recent insights we’ve had into the statistical modeling of network data collected in the field using ethnographic methods. Be on the lookout for forthcoming discussion of ethnographic porcupines and how to deal with them. Current post-doc Ashley Hazel presented her great work on the epidemiological effects of isolation and mobility on HSV-2 infection among pastoralists of northern Namibia.  Ashely is also instrumental to the work that I presented and I’m excited about what should be coming out of our work in the (hopefully) not-too-distant future.

AAPA overlapped this year with Earth Day and the March for Science. In a statement of solidarity with this national movement, AAPA president Susan Antón and the conference organizers decided to cancel the standard plenary lecture and instead lend our support to the New Orleans satellite march.

I was an enthusiastic participant in the march, but I ended up having a bit of an adventure that I’ve come to think of as a metaphor for my own scientific career. Alan Rogers and I had gone to lunch at the House of Blues (quite a distance from the start of the march at Duncan Plaza). We got kind of lost in a wide-ranging conversation that included a discussion of fair productivity metrics for anthropologists to numerical calculation of eigenvalues to genetic algorithms to graph theory and Markov chains. At one point, Alan looked down at his watch and realized that we were late for the march. Having missed the  exodus from the conference hotel, we figured that we would just walk straight from the restaurant to the starting point of the march. The problem was, we thought that the march was starting from Jackson Square, not Duncan Plaza. I should have known that this wasn’t right because Jackson Square is more or less ground-zero for New Orleans tourism. It fronts St. Louis Cathedral and is across Decatur Street from the world-famous home of late-night beignets, Café du Monde. Seems hard to imagine Decatur Street being shut down for a political march on a Saturday in April!

When we arrived at Jackson Square, it was obvious that we were in the wrong spot. A quick search on my phone under the shade of the trees in Jackson Square and we realized our mistake. Unfortunately, we were unable to figure out the route of the march, since by this time, it had almost certainly started. We guessed and headed out for Duncan Plaza, figuring we might manage to intercept the march if our guess was right. Well, our guess wasn’t right. We walked the mile-and-a-half, didn’t encounter the march en route, and found ourselves at an empty Duncan Plaza (having acquired a couple other stragglers we encountered on the way) with no evidence of which way the thousands of people had gone!

A bit dejected — and very hot and sweaty — we figured we’d just head back to the conference hotel and get a drink and cool off in the hotel bar. As we approached the Marriott, I said “hey, I think we found it.” Alan , with a note of surprise in his voice over my seemingly terrible spatial cognition, said “yes, we’re nearly at the hotel. Don’t you know where we are?” I replied, “No, we found the march!” Sure enough, there they were, assembled in front of the Marriott, chanting, waving signs, and jamming out to the brass band which had accompanied the march.  Natalia Reagan captured a bit of the atmosphere in this tweet:

While it was a bit frustrating to miss much of the march, it was great to hang out with Alan while we comically tried to find a couple thousand of our closest friends as they marched, chanted, and made a whole lot of noise on the streets of a pretty small city, and I came to think of this as a pretty apt metaphor for my life as a scientist. I bumbled around, not entirely knowing what I was doing or where to look for an answer, mostly failing, but ultimately finding a modicum of success. That sounds like science to me. On this particular day, I enjoyed the great honor of bumbling around with one of my major scientific role models and fellow autodidact, Alan Rogers. We talked about a ridiculous array of technical and theoretical issues as we wandered, which is half the fun of science. Sure, maybe we felt a bit isolated from the field — perhaps even wondering if we actually belonged. This, again, is pretty par for the course of doing interdisciplinary science for me. But in the end, we managed to find our way into the field again, enjoy a sense of connection with the community and the history of our discipline, and let our voices be heard on some of the central issues of our time.

# On the Uses of an Interdisciplinary Ph.D.

Today, I participated in a panel — along with super-smart colleagues Alex Konings and Kabir Peay — for the first-year Ph.D. students in the E-IPER program, an interdisciplinary, graduate interdepartmental program (IDP) at Stanford. As is the idiom for any E-IPER event, we spent a lot of time fretting about interdisciplinarity: what it means, how you achieve it, what costs it entails for jobs, etc.

I expressed the slightly heretical opinion that we should not pursue interdisciplinarity for interdisciplinarity’s sake. What matters — both in terms of the science and more instrumental outcomes such as getting published, getting a job, getting tenure — are questions. Yes, questions. One should ask important questions that people care about. Why are there so many species in the tropics? Where do pandemic diseases come from and how can we best control them? Does democracy and the rule of law provide the best approach to governance? How do people adapt to a changing climate?

Where the interdisciplinary Ph.D. program comes in is it provides students the opportunity to pursue whatever tools and approaches are required to answer the question in the best way possible. You don’t need to use a particular approach because that’s what people in your field do. Sometimes the best thing to do will be totally interdisciplinary; sometimes it will look a bit more like what someone in a disciplinary program would do. Always lead with the question.

Answering important questions using the best tools available is probably the best route to managing the greatest risk of an interdisciplinary degree. This risk, of course, is the difficulty in getting a job when you don’t look like what any given department had in mind when they wrote a job ad. The best way to manage this risk is simply to be excellent. If your work is strong enough, the specific discipline of your Ph.D. doesn’t really matter. Now, there are certainly some disciplines that are more xenophobic than others (anthropology and economics come immediately to mind), but if your work is really outstanding, the excuse that you don’t have the right degree for a given job gets much more tenuous. Two people who come immediately to mind are my colleague David Lobell and my sometime collaborator and former Stanford post-doc Marcel Salathé.

Is David a geographer? Geologist? Economist? Doesn’t really matter because he’s generally recognized as being a smart guy doing important work. Similarly with Marcel: population geneticist? Epidemiologist? Computer scientist? Who cares? He has important things to say and gets recognized for it.

Now, alas, we can’t all be David and Marcel, but we can strive to ask important scientific questions and let these questions lead us to both the skills and the bodies of knowledge we need. These then form the foundation of our research careers. Interdisciplinarity then is about following the question. It is not an end to itself.

# Integrating the Social Sciences with the Environmental and Earth Sciences

Seven years ago, I was invited to participate in a panel at NIH in Bethesda charged with evaluating the joint NSF/NIH interdisciplinary program on the Ecology of Infectious Disease. While there was an explicit call for the participation of social and behavioral sciences in the call for proposals, very few social scientists were getting involved in this remarkable program. Having participated in a wide array of similarly interdisciplinary panels, I knew that this was a common dilemma: the architects of the panel (whether it is a panel evaluating grant proposals, an interdisciplinary symposium, or an edited volume), who are typically natural scientists of some sort, make a good-faith effort to bring social scientists into the fold, but generally have little luck. Through a series of slightly hilarious miscommunications and travel snafus, I was unable to attend the meeting in Bethesda. I holed up for a weekend in a cottage in Santa Fe (where I had been participating in an panel the previous week) and wrote a document on how researchers working on the ecology of infectious disease could engage the social sciences and social scientists. As I contemplate my new role in the School of Earth, Energy, and the Environment at Stanford, it seems like a propitious time to revisit this white paper.

The stakes for involving the social sciences in environmental research – broadly construed – are high. Massive – potentially existential – problems like climate change, emerging pandemic disease, and large-scale extinction have both human drivers and enormous consequences for human welfare. This said, there are precious few social scientists – people charged with understanding human behavior and societies – who are engaged in research on environmental problems. This problem is particularly acute at elite institutions such as leading research universities.

Since human behavior is central to many aspects of most environmental problems, the contributions of social scientists to work on environmental problems is important and, quite possibly, necessary for dealing with the major problems associated with this domain of research. Understanding environmental problems such as climate change is obviously of major significance for state actors (e.g., governments, regulatory bodies)  and, ultimately, people more generally. Why then is it so difficult to engage social scientists in these research questions? This seems all the more puzzling given the amount of money potentially available for this research, particularly when compared to the funding available within the social science disciplines. There is clearly a collective action problem here: the generation of a public good that could come from the cooperation of social scientists and natural scientists is being inhibited somehow. Presumably, there would be benefits for social scientists who chose to collaborate with natural scientists on important environmental problems. Why then are we stuck with the collective action problem?

Sometimes, there is an explicit attempt to get social scientists to do the bidding of natural scientists in promoting social or cultural change for their desired ends. The eminent Stanford ecologist, Paul Ehrlich  has called for research into the mechanisms that change social norms, suggesting that there is an urgency to changing norms because of mounting environmental problems. The irony here, of course, is that in trying to engage social scientists in research on the environment, Ehrlich and other interested natural scientists needs to induce a change in social norms.

In an essay reviewing models for changing social norms,  Ehrlich and the great Princeton ecologist Simon Levin note that they did not even attempt to address how asymmetries of power or social networks affect the spread of social norms. Unfortunately, this is exactly the problem facing natural scientists trying to engage social scientists and models that fail to acknowledge these factors are doomed to failure. Within both the academy and society more broadly, there are distinct power asymmetries across scientific fields and, in general, social science fields are on the losing end of such power asymmetries. The great majority of social scientists can not compete with natural scientists with respect to research funding or the prestige (or volume) of of their publications.

When power/prestige gradients are steep, disciplines are likely to become insularized. An adaptive response to a collective’s inability to compete across disciplines is to, consciously or not, collude in agreeing that the only relevant opinions about the quality/volume of individual scholars’ research are other members of the scholars’ discipline. There are institutional practices that can facilitate this (e.g., the manner in which promotions are managed). I suggest that insularized disciplines will also fetishize theory above all other intellectual outcomes. Theory becomes fetishized at the expense of answering interesting and important questions or developing new methodologies for answering important questions. There are few checks on the degree to which theory can become abstruse and convoluted when its development becomes decoupled from answering questions. There comes a point where only very narrow specialists can ever hope to understand the intricacies of a particular theoretical tradition and be successful. Emphasizing theoretical development above all else within a discipline is thus a path toward disciplinary insularity and is the enemy of both interdisciplinarity and problem-focused research.

Social science disciplines do not gain prestige or other within-field benefits from engaging in the substance of human-environmental interactions. This arises in part because of the dynamics of differentiation from higher-prestige science disciplines engaged in these questions. There is also a positive feedback. Way back when I first came to Stanford, I was at a party where most of the other party-goers were political scientists. At the time, I was struck by the fact that there didn’t seem to be anyone in the department who studied environmental politics. I took the opportunity that this party afforded to ask a fellow assistant professor in that department why this was the case. His answer was simply “because no one could ever get tenure at Stanford studying environmental politics.” This conversation piqued my interest and I have now had a similar conversation with quite a few economists and political scientists. While not everyone is as blunt as my interlocutor in 2003, most have agreed broadly that working on environmental questions is not the route to professional advancement and these topics are therefore avoided by promising junior scholars trying to forge research careers.

I should probably note that economics provides an interesting exception to the power/prestige hierarchy. It’s really a topic that deserves its own post, so I won’t get into it too much here, but I think that economics is an exception that proves the rule. While the discipline is certainly more prestigious than, say, anthropology (!), I think that it’s hard to imagine a more insular discipline that fetishizes theory – and its mathematical accoutrements – more and in which professional incentives are absolutely not aligned with the interests of interdisciplinary, problem-based science.

Another phenomenon that has become a barrier to genuine interdisciplinary engagement for social scientists is the tendency for scientists from high-prestige disciplines to dabble in social science. The hilariously half-assed surveys that some scientists field when they want to get at the “human dimensions” of their problem come immediately to mind.

At a more structural level, I think about network science. When one attends the Sunbelt Social Networks Conference, one can frequently hear grumbling about how a bunch of physicists have swooped in and created what is sometimes known as a “new science” of networksIt is rare to find citations to the substantial social science literature on the topics many physicists write on other than the token citations to Milgram or possibly Simmel. New terms for well-described phenomena are invented and go largely to cultural fixation. Prior work (often 20 years old) is ignored. Papers on social networks get published in Physical Review D rather than established technical journals like Social Networks, Computational and Mathematical Organization Theory, or the Journal of Mathematical Sociology. Within-discipline citations are circular. Concepts having little interest to social scientists (for good reason) go to fixation and demand being addressed despite dubious relevance (e.g., “scale-free” networks).

I am actually of two minds about this phenomenon. On the one hand, it would be nice if this “new science” did a better job acknowledging that smart people have been working on these topics for quite a long time. On the other hand, I think that we need to have more more than the small handful of methodological innovators who work on social network analysis from within social sciences departments. The volume of quality work coming out of the physical sciences is almost certainly greater than that coming out of social science departments. A big part of this is the social organization of science (see below), but surely part of this is about getting smart people to work on important problems. We need to have more social scientists who are willing to engage in the general science literature where the visibility is greater (e.g., compare the citation patterns and general visibility of Science vs. CMOT!). Social scientists need to be willing to take the risk of publishing their strongest results in high-prestige general science journals like Science, Nature, PNAS. Yes, we will usually get rejected, but that’s no different from the experience of natural scientists, and we are certain to never get into these high-impact journals if we never even try.

I do not, in any way, want to decry the engagement of high-prestige natural scientists with the social sciences. Indeed, this is something we desperately need! But it needs to be real engagement rather than either dilettantism or intellectual imperialism. Three examples of physicists who switched disciplines and had enormous positive effects come immediately to mind: Harrison White (Sociology, Columbia), Bob May (Epidemiology, Ecology and Evolutionary Biology, Oxford), and my sometime mentor, Shripad Tuljapurkar (Demography/Population Biology, Stanford). These are all scholars who took the substance and the history of their new disciplines seriously and have made enormous contributions. My amazing Ph.D. student Mike Price is a physicist-turned-anthropologist who is poised to make some truly fundamental contributions to anthropology, evolutionary biology, and economics.

A key issue that has not been sufficiently addressed in the differential funding, productivity, and status within universities is the social organization of science. The natural sciences are generally structured for productivity: organized labs, large groups working toward a common research goal, substantial division of labor. This social organization of science certainly interacts with institutional structures. For example, the allocation of teaching load and the manner in which activities (i.e., lab meetings, co-taught classes) are credited often differs systematically between the natural and social sciences. For the most part, social scientists still follow a more individualist model of scholarly production. Papers may be written with students, but research groups, if they exist, are not necessarily structured for production toward a common research goal. My own situation is instructive on this topic. As an anthropologist, I have always had more of a natural-science culture to my research group. This said, my “lab” has always been more a loose confederation of people more or less interested in similar things, than a group focused on a clearly-articulated research goal.  There was a point not that long ago when I had Ph.D. students simultaneously working on the following topics:  bushmeat in Cameroon, sex workers in China, malaria ecology in the Colombian Amazon, water security in Caribbean Colombia, sago horticulture in West Papua, disease transmission networks in Uganda, rodent population cycling and hantavirus transmission, TB in South Africa, food sharing in Nunavik. Now that I’m based in a natural science department, there is hope for some more coherence.

Really Inviting Social Scientists to the Table: A Power-Inversion Strategy

We have a situation where lower-prestige disciplines effectively opt out of competing with high-prestige ones, where runaway theory fetishism institutionally insulates scholars interested in similar phenomena from each other, and where substantive applications to problems of human-environment interaction are institutionally blocked. How do we get social scientists engaged?

The simple answer is that professional incentives of social-science researchers (particularly junior ones) and the institutional and societal priorities of solving vital problems involving the environment and human well-being need to be aligned. The first step is to get social scientists to the table to foster an environment of collaboration. Being mindful of the power dynamics across fields, collaboration opportunities need to be framed in terms of categories of thought and research questions of intrinsic interest to social scientists.  This may sound trivial, but it is key that this framing be consistent with the autochthonous development of ideas within the social sciences, rather than (even well-intentioned) natural scientists’ conceptions of what social science is. Even though an RFP or other invitation may seem like something in which social scientists should be interested to natural scientists and program officers, it may not obviously address institutionally important or interesting questions, theories, or methodologies from the social scientists’ perspective.

Remember, the system of professional reward works reasonably well from any individual social science researcher’s perspective. We expect agents to be risk-averse and such risk-aversion in this context leads to the collective action problem that we are forgoing a public good of increased understanding – and maybe even the ability to positively intervene in – significant environmental challenges of humanitarian, social, and economic import. By framing questions in terms of existing research themes in the social sciences, we may be able to overcome the risk-aversion because properly framed research opportunities should not be professionally risky.

Some areas within social science of relevance to the environmental sciences include:

• political economy, global-to-local political relationships, the development of power asymmetries – particularly in regard to access to resources, health, etc.
• equity, justice, property rights, and social movements
• trust, governance, conflict
• consumption, social, cultural and symbolic capital
• institutions
• migration, indigeneity, and ethnicity
• markets, commodities, motivations, values and cosmologies, and time horizons

In brief, if we want social scientists to become engaged with research generally seen as beneficial from a societal perspective, we have to let them “do their thing” first and let the natural science do the complementing. Rather than asking how social science can contribute to natural science research agendas, we must sometimes ask how natural science can contribute to social science research agendas. Some examples from infectious disease ecology: How can thinking about the emergence in the western hemisphere of Zika virus help us understand the development of trust or its implications for governance? How do neoliberal economic policies promote the emergence of Nipah virus of Japanese encephalitis? Why does the Indonesian government refuse to provide H5N1 samples to the US CDC or WHO? This certainly doesn’t mean that it always has to work this way, but it must work this way sometimes if progress is to be made.

I do think that natural scientists and social scientists need to be able to sit down and put together intellectually strong, multi-disciplinary research projects together. However, the way to get social scientists engaged in the first place is to frame the research possibilities in terms that are relevant to them. From here, real interdisciplinarity can be achieved.

# What Dinosaurs Teach Us About Approaching Stanford

My wife, Libra Hilde, and I are resident fellows in a freshman dorm at Stanford. The RF residences are, shall we say, not quite as grand as the masters’ residences at Harvard (which have been know to get named in Top Five Lists of Apartments in Boston), but we fill a similar ceremonial role for our students that the masters at Harvard do. This means giving speeches to parents when students arrive and for important occasions like Parents’ Weekend.

Every year, the house staff (RFs and student staff) pick a theme and then decorate the dorm in anticipation of freshman arrivals. The standard Stanford gag is to pick a theme that somehow plays off the name of the house. These themes can be hilariously tenuous — that’s actually part of the gag — and some house names are easier to work with than others. I’m afraid we’re saddled with a particularly difficult name to play off of. We are Arroyo House. Our themes over the past few years have been: “Where the Wild Things Arroyo” (as in the classic Maurice Sendak book), “ATROYO” (an ancient Greek theme), and “Arroyosemite” (as in the National Park). After a long debate at our staff retreat, we finally decided on this year’s theme of “Dinosarroyo.” Lots of great decorating opportunities, as you can see from this picture of our common room.

A little game I play with myself in my ceremonial role of Arroyo House Resident Fellow is to welcome the parents with a brief speech on how our house theme relates to their kids’ careers at Stanford and beyond. Now bear in mind, we choose the theme on the basis of (1) how good a pun it makes with our house name (and we don’t have a lot to work with on that front!) and (2) the decoration possibilities it entails. How that theme fits into our larger vision is, frankly, pretty low on the list. This is what makes the game fun! After giving it a bit of thought, it occurred to me that Dinosarroyo actually has a lot to teach us. There are three big themes:

(1) College is about the spirit of discovery. Romantic tales of the expeditions of paleontologists such as Edward Drinker Cope or Roy Chapman Andrews of the American Museum of Natural History have inspired the early careers of countless scientists. Students’ experience at Stanford should inspire them to explore the boundaries of knowledge, whether they are future scientists, educators, lawyers, entrepreneurs, or whatever. Stanford students excel most when they eschew the easy path. This is a research university. Our students should take advantage of this and make new discoveries about the world. Embrace the spirt of discovery embodied by those romantic vertebrate paleontologists.

(2) The Dinosauria first appeared on Earth during the Triassic period and were the dominant form of animal life for over 135 million years. The age of the dinosaurs came to an abrupt end at the Cretaceous-Paleogene Boundary, about 65 million years ago. This 135 million years that dinosaurs dominated is approximately 100 times longer than anything recognizably human has been on the planet. In fact, what appears to us to be a geological ‘instant’ where the dinosaurs went extinct at the K-Pg boundary was, in fact, probably longer than humans have been in existence. That this mighty and diverse lineage of animals managed to die out in the blink of an evolutionary eye suggests to me that we should have some humility about our own dominion. Crucially, at this moment in human history we are faced with many enormous challenges, some of which are potentially existential. We should use the incredible opportunities that are afforded to us by our association with this incredible institution to address these challenges. Our society has given us so much to allow us to be here at this remarkable point in history. Let’s make the most of it!

(3) Those synapsid ancestors of mammals who managed to survive when all the (non-bird) dinosaurs went extinct give us a clue as to what our comparative advantage in this universe is. We are adaptable. We are opportunistic. Most remarkably of all, our particular lineage is blessed with the capacity for planning and foresight. We need to encourage our students to take advantage of the opportunities given them by this university to become adaptable lifelong learners. I can’t predict what the job market will look like in 10 years (and anyone who tells you they can is either fooling themselves or trying to sell you something). What I can say, is that it will be different than it is today. And the job market ten years beyond that will be even more different. This means that learning to be flexible, adaptable, and to never stop learning is probably the greatest ‘skill’ our students can learn.

# On Genetics and Human Behavioral Biology

Nicholas Wade, former science reporter for the New York Times has written a book, A Troublesome Inheritance, in which he argues that large-scale societal differences (e.g., the existence of capitalist democracies in the West or of paternalistic, authoritarian political systems in Asia) may be attributable to small genetic differences that were fixed at a population level through the action of natural selection since the emergence of anatomically modern humans and their subsequent dispersal from Africa. The fixation of these gene variants happened because the continents of Europe, Asia, and Africa (homes of the major “racial” groups) differed in systematic ways. David Dobbs recently reviewed it in the Sunday Review of Books, which prompted a kind of amicus brief letter-to-the-editor from over 120 population geneticists, affirming that Wade’s writing misrepresents the current science of genetics. A full list of the signatories of this letter can be found here. It is a veritable who’s who of contemporary population genetics.

As you might imagine, A Troublesome Inheritance has been quite controversial. A great deal has already been written on this book, both in formal publications and in the science (and economics) blogging ecosystem. To name just a few, Greg Laden, my old homie and fellow TF for Irv DeVore‘s famous Harvard class, Science B-29, Human Behavioral Biology, wrote a brief review here for American Scientist. Columbia statistician and political scientist, Andrew Gelman, wrote a review for Slate.com. Notre Dame professor and frequent contributor of popular work on human evolution, Agustin Fuentes, wrote a critique for Huffington Post, while UNC-C anthropology professor Jonathan Marks wrote a critique for the American Anthropological Association blog, which also appears in HuffPo.

This state of affairs is extremely problematic since genetics is the material cause (in the Aristotelean sense) or one of the mechanistic causes (in the Tinbergian sense) of much of the diversity of life. If we are going to make a scientific claim that some observed trait is the result of natural selection, we should be able to have a sense for how such a trait could evolve in the first place. The standard excuse for ignoring genetics in the adaptive analysis of a trait of interest is what Alan Grafen termed the “phenotypic gambit.” The basic idea behind the phenotypic gambit is that natural selection is strong enough to overcome whatever constraints may be acting on it. The phenotypic gambit is a powerful idea and it has yielded some productive work in behavioral ecology. I use it. However, a complete evolutionary explanation of a trait’s existence needs to consider all levels of explanation. In modern terms, and as nicely outlined a letter by Randolph Nesse, we need to answer questions about mechanism, ontogeny, phylogeny, and function. Explanations relying on the phenotypic gambit only address the functional question (i.e., fitness, or what Tinbergen called the “survival value” of the trait).

I could go on about this for a long time, so I will limit myself to three points: (1) complex traits will generally not be created by a single gene, (2) heritability and the response to selection are regularly misunderstood and misapplied, (3) we need to think about the strength of selection and the constancy of selective regimes when making statements about the adaptive evolution of specific traits.

First, we need to get over the whole one-gene thing. Among other things, the types of adaptive arguments that are made particularly for recent human behavioral innovations are simply highly implausible for single genes. There are a variety of formulae for calculating the time to fixation of advantageous alleles that depend on the particulars of the system (e.g., details about dominance, initial frequency, mutation rate). Using the approximation that the number of generations that it takes for the fixation of a highly advantageous allele with selection coefficient $s$ is simply twice the natural logarithm of $s$ divided by $s$, we can calculate the expected time to fixation for an advantageous allele. With a (very) substantial average selection coefficient of $s=0.05$ (think of lopping of 5% of the population each generation), the time to fixation of such a highly advantageous allele is about 120 generations generations. That’s over 3,000 years for humans. This is interesting, of course, because it makes the type of recent evolution the John Hawks or Henry Harpending have discussed more than plausible. It makes it hard to imagine how the large changes in presumably complex behavioral complexes in historical time suggested by authors such as Wade or Gregory Clark, author of Farewell to Alms (which I actually find a fascinating book), pretty implausible.

In addition to the population-genetic implausibility of single-locus evolutionary models, complex traits are polygenic, meaning that they are constructed from multiple genes, each of which typically has a small effect. Now, this doesn’t even address the issue of epigenetics, where genotype-environment interactions profoundly shape gene expression and can produce fundamentally different phenotypes in the absence of significant genetic difference, but that’s another post. In many ways, this is good news for people who study whole organisms in a naturalistic context (like human behavioral ecologists!) because it means that we can work with quantitatively-measured trait values and apply regression models to understanding their dynamics. In short, the math is easier though, admittedly, the statistics can be pretty tricky. Further good news: there are lots of people who would probably be happy to collaborate and there are plenty of training opportunities in quantitative genetics through short courses, etc.

The masterful review paper that Marc Feldman and Dick Lewontin wrote for Science in 1975 amid the controversy surrounding Arthur Jensen’s work on the genetics of intelligence, and its implications for racial educational achievement differentials, still applies. Heritability is a systematically misunderstood concept and its misuse seems to surface in policy debates approximately every twenty years. Heritability, in the strict sense, is a ratio of the total phenotypic variance that is attributable to additive genetic variance (i.e., the variance contributed by the mean effect of different alleles). Because total variance of the phenotype is in the denominator of this ratio, heritability is very much a population-specific measure. If a population has low total phenotypic variance because of a uniformly positive environment, for instance, there is more potential for a greater fraction of the total variance to be due to additive genetic variance. Think, for example, about children’s intelligence (as measured through psychometric tests) in a wealthy community with an excellent school district where most parents are college-educated and therefore have the motivation to guide their children to high scholastic achievement, the resources to supplement their children’s school instruction (e.g., hiring tutors or sending kids to enrichment programs), and the study skills and knowledge base to help their children with homework, etc. I have used this example in prior post. Given the relative uniformity of the environment, more of the variation in test scores may be attributable to additive genetic contributions and heritability would be higher than it would be in a more heterogeneous population. This is a hypothetical example, but it illustrates the rather constrained meaning of heritability and the problems associated with its application to cross-population comparisons. It is also suggestive of the problem of effect sizes of different contributions to phenotypic variance. The potential for environmental variance to swamp real additive genetic variance is quite large. What’s a better predictor of life expectancy: having a genetic predisposition to high longevity or living in a neighborhood with a high homicide rate or a endemic cholera in the drinking water supply?

Heritability essentially measures the potential response to selection, everything else being equal. The so-called Breeder’s Equation (Lush 1937) states that the change in a single quantitative phenotype (e.g., height) from one generation to the next is equal to the product of heritability and the force of selection. If there is lots of additive variability in a trait but not much selective advantage to it, the change in the mean phenotype will be small. Similarly, even if selection is very strong, the phenotype will not change much if the amount of additive variance is low. A famous, but frequently misunderstood result, known as Fisher’s Fundamental Theorem shows that the change in fitness is directly proportional to variance in fitness. This is really just a special case of the breeder’s equation, as shown in great detail in Lynch and Walsh’s textbook (and their online draft chapter 6) or in Steve Frank’s terrific book, in which the trait we care about is fitness itself. An important implication of Fisher’s theorem is that selection should deplete variance in fitness — and this makes sense if we think of selection as truncating a distribution. A corollary of Fisher’s theorem is that traits which are highly correlated with fitness should not have high heritability. Oops. Does this mean that intelligence, with its putatively very high heritabilities is not important for fitness?

Everything in the last paragraph applies to the case where we are only considering a single trait. When we consider the joint response of two or more traits to selection, we must account for correlations between traits (technically, additive genetic covariances between the traits). Sometimes these covariances will be positive; sometimes they will be negative. When the additive genetic covariance between two traits is negative, it means that selection to increase the mean of one will reduce the mean of the other. In their fundamental (1983) paper, my Imperial College colleague Russ Lande and Steven Arnold generalized the breeder’s equation to the multivariate case. The response to selection becomes a balancing act between the different force of selection, additive genetic variance, and additive genetic covariance for all the traits. Indeed, this is where constraints come from (or it’s at least one place). Suppose there are two traits (1 and 2) that share a negative covariance. Further suppose that the force of selection is positive for both but is stronger on trait 1 than it is on trait 2. Depending on the amount of genetic variance present, this could mean that the mean of trait 2 will not change or even that the mean could decrease from one generation to the next.

The work of Lande and Arnold (and many others) has spawned a huge literature on evolvability (something that Charles has moved into and that we have some nascent collaborative work on in the area of human life-history evolution). This work is very important for understanding things like the evolution of human psychology. Consider the hypothesis, popular in evolutionary psychology, that the mind is divided into a large number of specific problem-solving “modules,” each of which is the product of natural selection on the outcome of the problem-solving. How do you create so many of these “organs” in a relatively short time frame? Humans last shared a common ancestor with chimpanzees and bonobos around five million years ago and most likely human ancestors until about 1.8 million years ago seem awfully ape-like (and therefore probably not carrying around anything like the human mental toolkit in their heads). One of the key processes responsible for the creation of complex phenotypes is known as modularity (which is a bit confusing since this is also the term that evolutionary psychologists use for these mental organs!) and one of the fundamental mechanisms by which modularity is achieved is through the duplication of sets of genes responsible for existing structures. These duplicated “modules” are less constrained because of their redundancy and can evolve to form new structures. However, the fact that modules are duplicated means that they should experience substantial genetic correlation with their ancestral modules. This makes me skeptical that the diversity of hypothetical structures posited by the massive modularity hypothesis could be constructed by directional selection on each module. There is just bound to be too much correlation in the system to permit it to move in a fine-tuned way toward to phenotypic optimum for each module.

Trade-offs matter for the evolution of phenotypes. While I suspect that very few human evolutionary biologists would argue with that, I think that we generally fall short of considering the impact of trade-offs for adaptive optima. The multivariate breeders’ equation of Lande and Arnold gives us an important (though incomplete) tool for looking at these trade-offs mechanistically. A few authors have done this. The example that comes immediately to mind is Virpi Luumaa and her research group, who have done some outstanding work on the quantitative genetics of human life histories using Finnish historical records.

My third, and last (for now), point addresses the constancy of selection. This is related to the concept of the Environment of Evolutionary Adaptedness (EEA), central to the reasoning of evolutionary psychology. A few years back, I wrote quite a longish piece on this topic and its attendant problems. Note that when we use population-genetic models like the one we discussed above for the expected time to fixation of an advantageous allele, the selection coefficient $s$ is the average value of that coefficient over time. In reality, it will fluctuate, just as the demography of the population selection is working on will vary. Variation in vital rates can have huge impacts on demographic outcomes, as my Stanford colleague Shripad Tuljapurkar has spent a career showing. It can also have enormous effects on population-genetic outcomes, which shouldn’t be too surprising since it’s the population of individuals which is governed by the demography that is passing genetic material from on generation to the next!

When I read accounts of rapid selection that rely heavily on EEA-type environments or the type of generalizations found in the second half of Wade’s book (e.g., Asians live in paternalistic, autocratic societies), my constant-environment alarm bells start to sound. I worry that we are essentializing societies. One of the all-time classic works of British Social Anthropology is Sir Edmund Leach’s groundbreaking Political systems of Highland Burma. Leach found that the social systems of northern Burma were far more fluid than anthropologists of the time typically thought was the case. One of the key results is that there was a great deal of interchange between the two major social systems in northern Burma, the Kachin and and Shan. Interestingly, the Shan, who occupied lowland valleys, practiced wet-rice agriculture, and whose social systems were highly stratified were seen by western observers as being more “civilized” than the Kachin, who occupied the hills, practiced slash-and-burn agriculture, and had much more egalitarian social relations. Leach (1954: 264) writes, “within the general Kachin-Shan complex we have, I claim, a number of unstable sub-systems. Particular communities are capable of changing from one sub-system into another.” Yale anthropologist/political scientist James Scott has extended Leach’s analysis in his recent book, The Art of Not Being Governed, and suggested that the fluid mode of social organization, where people alternate between hierarchical agrarian states, and marginal tribes depending on political, historical, and ecological vicissitudes is, in fact, the norm for the societies of Southeast Asia.

The clear implication of this work for our present discussion is that a single lineage may find some of its members struggling for existence in hierarchical states where the type of docility that Wade suggests should be advantageous would be beneficial, while descendants just a generation or two distant might find themselves in egalitarian societies where physical dominance, initiative, and energy might be more likely to determine evolutionary success. I don’t mean to imply that these generalizations regarding personality-type and evolutionary success are necessarily supported by evidence. The key here is that the social milieux of successive generations could be radically different if the models of Leach and Scott are right (and the evidence brought to bear by Scott is impressive and leads me to think that the models are right). At the very least, this will reduce the average selection differential on the putative genes for personality types that are adapted to particular socio-political environments. More likely, I suspect, it will establish quite different selective regimes — say, for behavioral flexibility through strong genotype-environment interactions!

These are some of the big issues regarding genetics and the evolution of human behavior that have been bothering me recently. I’m not sure how we go about fixing this problem, but a great place to start is by fostering more collaborations between geneticists and behavioral biologists. Of course, this would be predicated on behavioral biologists’ motivation to fully understand the origin and maintenance of phenotypes and I worry that the institutional incentives for this are not in place.

# EEID 2014 Wrap-Up

It’s been a long time since I’ve written in monkey’s uncle. Life has gotten pretty busy and my seeming inability to write brief entries has led me to neglect the blog this year. However, I am freshly back from the Ecology and Evolution of Infectious Disease Conference in Fort Collins, Colorado and feel compelled to give my annual run-down. The conference was hosted by friend and colleague Mike Antolin, Sue Vandewoude, and my erstwhile post-doc, now CSU researcher, Dan Salkeld. Nice job, folks, on a very successful conference.

EEID is pretty much the best meeting. As I noted in last year’s post, I love its future-orientation. EEID is a meeting that foregrounds the work of junior scientists and there was, as ever, a tremendous array of human capital on display at this meeting. This drives home to me the importance of investment in professional training and research programs that specifically develop human capital. This community exists in large measure because of the innovative program jointly offered by NSF and NIH. Thanks as ever to the vision and hard work of Josh Rosenthal, Sam Scheiner, and all the funders (e.g., support from The Gates Foundation can be found all around this conference) for this area. It’s always great to catch up with smart, fun friends. Plenty of time was spent talking science and drinking craft beer (what a beer town Ft. Collins is!) with the likes of Peter Hudson, Jessica Metcalf, Ottar Bjornstad, Aaron King, Mike Antolin, Tony Goldberg, Issa Cattadori, Maciej Boni, Marm Kilpatrick and, of course, Dan Salkeld. It was nice to meet and chat, if only briefly, with my sometime remote collaborator Paul Sharp, who gave what I understand to be an extremely stimulating keynote on the complicated and surprising evolution of malaria (alas, I missed it as I was delayed getting to Ft. Collins). I also spent some quality time learning about acquired immunity in dogs with Colin Parrish. This may come in handy for some ideas that Jess Metcalf and I have been playing around with.

There is a great tradition of the EEID hike and closing banquet/dance. Ft. Collins provided a beautiful and challenging hike out in Lory State Park. The view from the top of Arthur’s Peak was pretty amazing.

At Wednesday’s banquet, I’m afraid to say that Princeton once again dominated the dance floor as we all rocked out to the amazing Denver funk/rock/jam band Kinetix (great choice, Mike). The Stanford showing was disappointing in part because of the early departure of some of our most enthusiastic dancers. Don’t get cocky though, Princeton. We’ll be gunning for you next year.

The entirety of Tuesday morning’s session was given over to communicating science. Dan Salkeld warmed up the crowd with some hilarious examples of the reporting frenzy that ensued following the publication of our paper on plague dynamics in prairie dog towns or, more recently, Hillary Young‘s work showing that excluding large ruminants increases rodent density in Kenya. Wow. Dan also used my Stanford colleague Rebecca Bird‘s work as an example of how an unexpected story can engage readers and listeners. My collaborator Tony Goldberg gave a talk that was also not lacking in ridiculous headlines thanks to his “viral” nose-tick work. David Quammen, author of outstanding popular science books such as The Song of the Dodo and Spillover (which Bill Durham and I use for our class on environmental change and emerging infectious disease), gave a terrific presentation in which he consolidated a lot of nice, practical advice on the craft of writing engaging work into 18 points, amply illustrated by anecdotes of characters from our field. Sonia Altizer from the University of Georgia introduced the crowd to the opportunities (and pitfalls) of citizen science and suggested that it might just be possible to engage the public in disease ecology data collection. Some examples she identified included the granddaddy of citizen-science in the US run by the Laboratory of Ornithology at Cornell, the ZomBee Watch at SFSU, and her own Project MonarchHealth. If I had to summarize this session in one pithy phrase, I think it would have to be “Yay, ecologists!”

Quammen took to Twitter to call us out for being behind the curve with respect to social media.

While there were, in fact, a few of us tweeting the occasional tidbit from the conference, I think his general point is valid. This stuff is intrinsically interesting and we can do a much better job communicating to broad publics.

Some talks that really caught my attention.

Ary Hoffmann gave a great talk about the complexities of using bacteria of the genus Wolbachia to control the Aedes mosquitoes that transmit dengue in Australia (and elsewhere). Wolbachia infects mosquitoes and can have a variety of effects on their biology. The reason artificial infection of mosquitoes wit this bacterium seems so promising as a means of biological control is that the offspring of crosses between infected and uninfected mosquitoes are not viable. This is obviously a very substantial fitness cost to the mosquitoes and this creates serious challenges for getting the infected mosquitoes to persist and take over local populations. Hoffmann presented a cool result about the invasibility of infected mosquitoes wherein in the early phases of introduction there is an unstable point in the mosquito dynamics. At this point, if the infected mosquitoes are above a threshold, they will successfully invade, otherwise, they will die out because of the inherent fitness costs of the Wolbachia infection. One policy challenge that arises is that to get a local population of mosquitoes above the invasibility threshold, researchers and vector-control specialists have to sometimes introduce a lot of mosquitoes. This means that the number of mosquitoes locally can increase substantially and, as you can imagine, this isn’t always popular with communities.

Fellow Anthropologist Aaron Blackwell from UCSB gave a fantastic talk on our “old friends”, the helminths (cue the freaky electron micrograph of a helminth’s mouth!). Aaron participates in the Tsimane Health and Life History Project which was started by colleagues Mike Gurven (also at UCSB) and Hilly Kaplan (New Mexico). Using sophisticated multi-state Markov hazard models (go Anthropology!), Aaron showed that co-infection with helminths and Giardia is less frequent than expected among this population that experiences ubiquitous exposure to both pathogens and that, in fact, infection with the one appears to be protective against infection with the other. One of the most provocative results he presented showed that helminth infection actually lowered systolic blood pressure in men by an amount equivalent to the increase that comes from aging ten years. Chronic helminthic infection may be a reason why Tsimane men’s systolic blood pressure does not rise precipitously with age as it does in the US. This result, which may provide fresh insights into the mechanisms of hypertension, a major source of morbidity in the US, struck me as particularly poignant given the demeaning comments made about NSF funding for work among the Tsimane from none other than Lamar Smith (R–TX), the chair of the House Committee on Science, Space, and Technology.

Anna Savage, a post-doc with the National Zoo in Washington DC, gave an awesome talk on the comparative immunogenetics of of frogs with respect to infection with the devastating fungal infection, chytridiomycosis. Chytridiomycosis has been identified as a major cause of amphibian extinction worldwide and Anna showed surprising heterogeneity in immune response across frog species. This is a subject with which I have only passing familiarity, but her talk demonstrated an amazing sophistication in integrating different levels of biological organization and making sense of a dauntingly complex problem. I would wager that Dr. Savage is one to keep an eye on.

The organizers tried a scheduling format that was a bit different from last year, wherein each session started with two half-hour talks generally given by somewhat more senior people. The second half of each session was then given over to brief ten-minute talks, typically delivered by more junior people. This format is nicely in keeping with the great EEID tradition of promoting the research of junior scientists. A few short talks that I found especially interesting included one by Sarah Hamer, from Texas A&M, on Chagas disease in the United States. She presented sobering data from national blood-bank surveillance showing a surprising number of Chagas-infected samples coming from donors with no history of travel to Latin America. When pushed by a questioner, she suggested that she would consider Chagas to be endemic in the US, at least in dogs and possibly even in people. Carrie Cizauskas, formerly of Wayne Getz‘s shop at Berkeley and now with Andy Dobson and Andrea Graham at Princeton, give a nice talk on the role of both stress and sex hormones in mediating macroparasite infection in wild ungulates in Etosha National Park, Namibia. Romain Garnier from Princeton described a very nifty image-processing approach to scanning large volumes of histological slides for indications of infection.

I perhaps didn’t see as many posters as I should have. The problem with the poster sessions is that one keeps running into various people one wants to talk to. I did manage to check out the poster of my former freshman advisee and current Princeton EEB student Cara Brook. She’s got an awesome PhD project studying the multi-host ecology of infectious disease in Malagasy fruit bats.

I’m looking forward to next year’s meeting at the University of Georgia already. I’m also looking forward to resuscitating the pedagogical workshop that used to be a signature feature of this EEID meeting. More on that later…

# AAA Recap, 2013

I guess it’s that time of the year. You know, when I recap, in my bittersweet way, the annual meeting of the American Anthropological Association? I am an anthropologist, yes, but I am deeply torn in my feelings for my discipline, my department, and my flagship (?) professional organization. The question mark arises because I am also a physical anthropologist and a demographer, so an argument can be made that my flagship professional organization is actually AAPA or PAA, but there is something about the unmarked category that is AAA. It’s supposed to represent anthropologists, broadly construed. I honestly don’t think that it does a very good job at this, but the reasons behind that are complex and I’ve only allocated myself a bit of time to blog since I’m desperately trying to catch up from all the travel I’ve done recently.

The meeting this year was in Chicago, which is a pretty amazing town. I stayed in the the Blackstone Renaissance Hotel, which was recently renovated in a lovely Art Deco theme. We did Chicago stuff. Tube steaks were eaten, the quantity of cheese that can be crammed into a deep-dish pizza was marveled at, beer was drunk.

AAA is a pretty bizarre scene. For starters, it’s at the weirdest time. It seems like the peculiar timing of AAA during November must be disruptive for just about every academic anthropology department, particularly because it is nearly a week-long endeavor. It seems that the life in an American university carries on just fine without the anthropologists around for a week in the middle of the Fall term, thank you very much. A couple innovations this year struck me as particularly incongruous, given the content of much current scholarship in anthropology. First, anyone who registered for the meeting as a non-member was given a yellow badge holder to mark them as outsiders. This seemed a bit gratuitous. I’m not sure what’s gained from such marking — they already pay a substantially higher rate for the privilege of attending, do they also need to be shamed for their lack of faith? Second, in the hall outside the main bunch of conference rooms, there was a television that played a loop of anthropologists talking about how important anthropology is. This struck me as unnecessarily propagandistic and it’s not at all clear to me who the target audience for this performance was. Presumably, those of us who were there already think that anthropology is a worthwhile endeavor. Seems to me that it’s the rest of the world we need to convince. Once again, there appears to be almost nothing considered newsworthy to emerge from this meeting of 6,000+ scholars with the exception of a paper on the similarities in street-scanning behaviors by police and fashion scouts.

Another strange feature of AAAs is that computers, cables, remotes, laser-pointers, etc. were not provided in the conference rooms but needed to be provided by the session chairs. This is the first time I’ve experienced this in years at a major conference and it definitely slowed us down quite a bit at the start of our session. I’m not sure what was going on with that. Maybe the budget to pay for AV services was already spent on the fancy video production that reminded us how important we all are?

This year, I organized and chaired a session, which was sponsored by EAS, on social network analysis in evolutionary anthropology. Unfortunately for the EAS party-goers from the previous night, the session ran at 08:00 on Saturday morning. Despite this challenge, the room was packed and the audience generally seemed into it. We had great talks by Stanford’s own Elly Power and Ashley Hazel. Elly talked about her amazing dissertation research on using social capital to understand costly displays of religious devotion in southern India. Ashley talked about her dissertation work in the School of Natural Resources and the Environment on mobility and the changing landscape of STI risk in Kaokoland, northern Namibia. David Nolin, one of our discipline’s most talented young methodologists, presented a very clever test of generalized reciprocity using dichotomous exchange data from his work in Lamalera in Indonesia. Ben Hannowell, yet another talented methodologist to come out of the WSU/UW IGERT program, discussed his collaborative work with Zack Almquist on inferring dominance structure from tournament graphs. The always marvelous Rebecca Sear talked about her recent synthetic work on the effects of kin on fertility (kinship, of course, is the classic application of networks in anthropology since genealogies are just special cases of graphs). John Ziker presented a network-based approach to understanding food sharing and reciprocity from his terrific ethnographic work in Siberia. I closed out the talks with my own combination history of anthropological (and ethological) contributions to social network analysis and pep talk to encourage anthropologists to be confident about their methods and have the courage to innovate new ones the way people like John Barnes or Clyde Mitchell or Elizabeth Bott or Kim Romney or Russ Bernard did!

After schmoozing for a bit post-session, I headed over to the Saturday EAS session on methodological advances in experimental games. While I didn’t see all the talks, the ones I saw were pretty cool. In general, I have mixed feelings about experimental economic games. There are lots of results and some fairly convincing stories to go along with some of the results. However, absent of context, I really wonder what they are measuring and, if they are indeed measuring something, whether it is actually interesting. This session made some real progress in dealing with this question and I think it really highlighted the comparative advantage of anthropologists in the multi-disciplinary landscape of twenty-first century behavioral science. While economists such as Loewenstein (1999) might lament the fact that there is no way to play context-less games and that this jeopardizes the validity and generality of such experimental games, anthropologists are experts in thinking specifically about context and its effect on behavior. Furthermore, anthropologists are still the go-to researchers for providing contextual diversity. In this session, we heard about experimental games played in Bolivia, Siberia, Fiji, and on the streets of Las Vegas. One talk in this session that particularly impressed me was given by Drew Gerkey, who is currently a post-doc at SESYNC in Annapolis, Maryland (and soon to be an assistant professor at Oregon State University — Go Beavs!). I was at SESYNC earlier in the week and got a chance to talk pretty extensively with him about this work. Drew makes the point that seems obvious now that I’ve heard (a sign of an important idea) that, in the evolution of cooperation literature, the counterfactual scenario to cooperation is frequently untenable. One does not simply go it alone when one is a hunter/fisher in Siberia. Drew also designed a number of very clever experimental games that fit the types of social dilemmas faced by his Siberian interlocutors. Very nice work indeed.

In addition to the sessions I attended, it was nice to see and chat with various smart, fun people I know who sometimes find their way to AAAs. I missed my partner in crime from last year’s AAA, Charles Roseman, who left the day I arrived, probably too bloated from the binge on Chicago’s amazing food he no doubt shared with Fernando Armstron-Fumero to be of much use to anyone. However, I got to see Siobhan Mattison, Brooke Scelza, Brian Wood, Rick Bribiescas, Mary Shenk, Aaron Blackwell, Pete Kirby and, briefly, Shauna Burnsilver and Dan Hruschka. Despite my general misgivings about the conference, it is nice to have an excuse to see so many cool people in one place at one time.

# Ecology and Evolution of Infectious Disease

I am recently back from the 2013 Ecology and Evolution of Infections Disease Conference at Penn State University. This was quite possibly the best meeting I have ever attended, not even for the science (which was nonetheless impeccable), but for the culture. I place the blame for this awesome culture firmly on the shoulders of the leaders of this field and, in particular, the primary motivating force behind the recent emergence of this field, Penn State’s Peter Hudson. Since I had attended the other EEID conference at UGA earlier this Spring (another great conference), I had no intention on attending the Penn State conference this year. Then, one day in late March, Nita Bharti asked me if I was going and mentioned, “You know it’s Pete’s 60th birthday, right?” Well that sealed it; I really had no choice.  I simply had to go if for no other reason than to pay my due respect to this man I admire so greatly. Pete has the most relentless optimism about the future of science and a willingness to make things happen that I have ever encountered and, in this way, has provided me one of my primary role models as a university professor and mentor. He has played a role in developing so many of the brilliant people who make this field so exciting, it’s amazing (just a sample that comes immediately to mind: Ottar Bjornstad, Matt Ferrari, Nita Bharti, Marcel Salathé, Isabella Cattadori, Jamie Lloyd-Smith, Shweta Bansal, Jess Metcalf…). Of course, even as I write this, I realize the joint influence of another major player in the field, Bryan Grenfell, formerly of Penn State but now at Princeton, becomes obvious. A great scientist in his own right, Pete is the master facilitator, providing the support (and institutional interference!) that allows young scholars to thrive. He is a talent-spotter extraordinaire.

The tone set by these great mentors carries through to the whole culture of the conference, where senior people attended the poster sessions, sat with students at lunches and dinners, and schmoozed at the plentiful open-bar mixers. For example, on the first full day of the conference, there was an afternoon poster session that started at 4:30 (we had been in back-to-back sessions since 8:30). This session was preceded by an hour-long poster-teaser session in which grad students and post-docs got up and presented 60-second (and, as Andrew Read noted, not one nanosecond more) teasers of their posters. Bear in mind, this session was entirely comprised of students and post-docs. It was striking that essentially every seat in the house was occupied and all the major players were present. The teasers were great – many were very funny, including a haiku apparently written by a triatomine bug and translated to us by Princeton EEB student Jennifer Peterson.

After the teasers, the conference went en masse to the fancy new Millenium Science Complex (it turns out that Pete Hudson has physical capital projects in addition to human capital ones!). There, participants milled about the 150 posters. After spending quite a bit of time doing this – and dutifully getting pictures of all my lab with their posters – I thought to check the time and realized it was nearly 6:30. The poster session had been going for two hours and nearly everyone was still there, including all the luminaries. It helped that there was free beer. I tweeted my amazement at this realization:

That is, in fact, Princeton‘s Bryan Grenfell moving fast in the middle of the picture, apparently making a bee-line for Michigan’s Aaron King. Andrew Read is in the far background, talking to a poster-presenter (he has that posture).

Scientific highlights for me included Caroline Buckee‘s talk about measuring mobility in the context of malaria transmission in Kenya and Derek Cummings‘s talk on the Fluscape Project to measure spatial heterogeneity in influenza transmission in China. I am a long-time fan of this project and it’s nice to see the great work that has come out of it. These talks were right in my wheelhouse of interest, but there were plenty other cool ones including Britt Koskella‘s talk on the dynamics of bacteria and phage on tree leaves.

Stanford was exceedingly well represented at this conference. My lab had no fewer than five posters. Ashley Hazel presented on her work with Carl Simon on modeling gonorrhea transmission dynamics in Kaokoland, Namibia. Whitney Bagge presented her work on remote-sensing of rodent-borne disease in Kenya. Alejandro Feged presented work on the transmission dynamics of malaria in the Colombian Amazon among the indigenous Nukak people. Laura Bloomfield presented her remote sensing and spatial analysis work from our project on the spillover of primate retroviruses in Western Uganda. I closed things out with a minimalist poster on simple graphical models for multiple attractors in vector-borne disease dynamics in multi-host ecologies. In addition to my lab group, Giulio De Leo (with whom I have been running a weekly disease ecology workshop at Woods since winter quarter) was there, helping to bridge all sorts of structural holes in our collective collaboration graphs.

The other thing that comes out of these meetings, especially more intimate ones like EEID, is some actual work on collaborative projects. I managed to find some time to sit down and discuss plans with collaborators as well as do some shameless recruitment for my planned re-submission of the Stanford Biodemography Workshops. I’m really excited about some of these collaborations, including one that brings together my two major areas of interest: biodemography and life history theory and infectious disease ecology.

Oh, and I’m convinced that there must be an interpretive dance component to the Ph.D. exam in the Grenfell lab. This is certainly the most parsimonious explanation for much of what I saw Wednesday night.

# Ecology and Evolution of Infectious Disease, 2013

I am recently back from the Ecology and Evolution of Infectious Disease (EEID) Principal Investigators’ Meeting hosted by the Odum School of Ecology at the University of Georgia in lovely Athens. This is a remarable event, and a remarkable field, and I can’t remember ever being so energized after returning from a professional conference (which often leave me dismayed or even depressed about my field). EEID  is an innovative, highly interdisciplinary funding program jointly managed by the National Science Foundation and the National Institutes of Health. I have been lucky enough to be involved with this program for the last six years. I’ve served on the scientific review panel a couple times and am now a Co-PI on two projects.

We had a big turn-out for our Uganda team in Athens and team members presented no fewer than four posters. The Stanford social networks/human dimensions team (including Laura Bloomfield, Shannon Randolph and Lucie Clech) presented a poster (“Multiplex Social Relations and Retroviral Transmission Risk in Rural Western Uganda”) on our preliminary analysis of the social network data. Simon Frost’s student at Cambridge, James Lester, presented a poster (“Networks, Disease, and the Kibale Forest”) analyzing our syndromic surveillance data. Sarah Paige from Wisconsin presented a poster on the socio-economic predictors of high-risk animal contact (“Beyond Bushmeat: Animal contact, injury, and zoonotic disease risk in western Uganda”) and Maria Ruiz-López, who works with Nelson Ting at Oregon, presented a poster on their work on developing the resources to do some serious population genetics on the Kibale red colobus monkeys (“Use of RNA-seq and nextRAD for the development of red colobus monkey genomic resource”).

Parviez Hosseini, from the EcoHealth Alliance, also presented a poster for our joint work on comparative spillover dynamics of avian influenza (“Comparative Spillover Dynamics of Avian Influenza in Endemic Countries”). I’m excited to get more work done on this project which is possible now that new post-doc Ashley Hazel has arrived from Michigan. Ashley will oversee the collection of relational data in Bangladesh and help us get this project into high gear.

The EEID conference has a unique take on poster presentations which make it much more enjoyable than the typical professional meeting. In general, I hate poster sessions. Now, don’t get me wrong: I see lots of scientific value in them and they can be a great way for people to have extended conversations about their work. They can be an especially great forum for students to showcase their work and start the long process of forming professional networking. However, there is an awkwardness to poster sessions that can be painful for the hapless conference attender who might want, say, to walk through the room in which a poster session is being held. These rooms tend to be heavy with the smell of desperation and one has to negotiate a gauntlet of suit-clad, doe-eyed graduate students desperate to talk to anyone who will listen about their work. “Please talk to me; I’m so lonely” is what I imagine them all saying as I briskly walk through, trying to look busy and purposeful (while keeping half an eye out for something really interesting!).

The scene at EEID is much different. All posters go up at the same time and the site-fidelity of poster presenters is the lowest I have ever seen. It has to be since, if everyone stuck by their poster, there wouldn’t be anyone to see any of them! What this did was allow far more mixing than I normally see at such sessions and avoid much of the inherent social awkwardness of a poster session. Posters also stayed up long past the official poster session. I continued to read posters for at least a day after the official session ended. Of course, it helps that there was all manner of great work being presented.

There were lots of great podium talks too. I was particularly impressed with the talks by Charlie King of Case Western on polyparasitism in Kenya, Maria Diuk-Wasser of Yale on the emergence of babesiosis in the Northeast, Jean Tsao (Michigan State) and Graham Hickling‘s (Tennessee) joint talk on Lyme disease in the Southeast, and Bethany Krebs’s talk on the role of robin social behavior in West Nile Virus outbreaks. Laura Pomeroy, from Ohio State, represented one of the other few teams with a substantial anthropological component extremely well, talking about the transmission dynamics of foot-and-mouth disease in Cameroon. Probably my favorite talk of the weekend was the last talk by Penn State’s Matt Thomas. They done awesome work elucidating the role of temperature variability on the transmission dynamics of malaria.

It turns out that this was the last EEID PI conference. Next year, the EEID PI conference will be combined with the other EEID conference which was originally organized at Penn State (and is there again this May). This combining of forces is, I’m sure, a good thing as it will reduce confusion and probably make it more likely that all the people I want to see have a better chance of showing up. I just hope that this new, larger conference retains the charms of the EEID PI conference.

EEID is a new, interdisciplinary field that has grown thanks to some disproportionately large contributions of a few, highly energetic people. One of the principals in this realm is definitely Sam Scheiner, the EEID program officer at NSF.  The EEID PI meeting has basically been Sam’s baby for the past 10 years. Sam has done an amazing job creating a community of interdisciplinary scholars and I’m sure I speak for every researcher who has been heavily involved with EEID when I express my gratitude for all his efforts.

# On Global State Shifts

This is a edited version of a post I sent out to the E-ANTH listserv in response to a debate over a recent paper in Nature and the response to it on the website “Clear Science,” written by Todd Meyers. In this debate, it was suggested that the Barnosky paper is the latest iteration of alarmist environmental narratives in the tradition of the master of that genre, Paul Ehrlich. Piqued by this conversation, I read the Barnosky paper and passed along my reading of it.

The Myers’s piece on the “Clear Science” web site is quite rhetorically clever. Climate-change deniers have a difficult task if they want to convincingly buck the overwhelming majority of reputable scientists on this issue. Myers uses ideas about the progress of science developed by the philosopher Thomas Kuhn in his classic book, The Structure of Scientific Revolutions. By framing the Barnosky et al. as mindlessly toeing the Kuhnian normal-science line, he has come up with a shrewd strategy for dealing with the serious scientific consensus around global climate change. Myers suggests that “Like scientists blindly devoted to a failed paradigm, the Nature piece simply tries to force new data to fit a flawed concept.”

I think that a pretty strong argument can be made that the perspective represented in the Barnosky et al. paper is actually paradigm-breaking. For 200 years the reigning paradigm in the historical sciences has been uniformitarianism. Hutton’s notion — that processes that we observe today have always been working — greatly extended the age of the Earth and allowed Lyell and Darwin to make their remarkable contributions to human understanding. This same principle allows us to make sense of the archaeological record and of ethnographic experience. It is a very useful foil for all manner of exceptionalist explanatory logic and I use it frequently.

However, there are plenty of ways that uniformitarianism fails. If we wanted to follow the Kuhnian narrative, we might say that evidence has mounted that leads to increased contradictions arising from the uniformitarian explanatory paradigm. Rates of change show heterogeneities and when we trying to understand connected systems characterized by extensive feedback, our intuitions based on gradual change can fail, sometimes spectacularly. This is actually a pretty revolutionary idea, apocalyptic popular writings aside, in mainstream science.

Barnosky et al. draw heavily on contemporary work in complex systems. The theoretical paper (Scheffer et al. 2009) upon which the Barnosky paper relies heavily represents a real step forward in the theoretical sophistication of this corpus and does so by making unique and testable predictions about systems approaching critical transitions. I have written about it previously here.

The most difficult part of projecting the future state of complex systems is that human element. This leads too many physical and biological scientists to simply ignore social and behavioral inputs. This said, there are far too few social and behavioral scientists willing to step up and do the hard collaborative work necessary to make progress on this extremely difficult problem. The difficulty of projecting human behavior often leads to projections of the business-as-usual variety and, unfortunately, these are often mischaracterized by the media and other readers. Such projections simply assume no change in behavior and look at the consequences some time down the line. A business-as-usual projection actually provides a lot of information, albeit about a very hypothetical future. What if things stayed the way they are? Yes, behavior changes. People adapt. Agricultural production becomes more efficient. Prices increase, reducing demand and allowing sustainable substitutes. Of course, sometimes things get worse too. Despite tremendous global awareness and lots of calls to reduce greenhouse gas emissions, carbon emissions have continued to rise. So, there is nothing inherently flawed about a business-as-usual projection. We just need to be clear about what it means when we use one.

A criticism that emerged on the list is that Barnosky et al. is essentially “an opinion piece.” However, the great majority of the Barnosky et al. paper is, in fact, simply a review. There are numerous facts to be reviewed: biodiversity has declined, fisheries have crashed, massive amounts of forest have been converted and degraded, the atmosphere has warmed. They are facts. And they are facts in which many vested interests would like to sow artificial uncertainty for political purposes. Positive things have happened too (e.g., malaria eradication in temperate climes, increased food security in some places that used to be highly insecure, increased agricultural productivity — though this may be of dubious sustainability), though these are generally on more local scales and, in some cases, may simply reflect exporting the problems to rich countries to the Global South. The fact that they are not reviewed does not mean that the paper belongs in an hysterical chicken-little genre.

A common critique of the doomsday genre is the certainty with which the horrible outcomes are framed. The Barnosky paper is suffused with uncertainty. In fact, this is the main point I take away from it! The first conclusion of the paper is that “it is essential to improve biological forecasting by anticipating critical transitions that can emerge on a planetary scale and understanding how such global forcings cause local changes.” This suggests to me that the authors are acknowledging massive uncertainty about the future, not saying that we are doomed with certainty. Or how about: “the plausibility of a future planetary state shift seems high, even though considerable uncertainty remains about whether it is inevitable and, if so, how far in the future it may be”?

Myers writes “they base their conclusions on the simplest linear mathematical estimate that assumes nothing will change except population over the next 40 years. They then draw a straight line, literally, from today to the environmental tipping point.” This is a profoundly misleading statement. Barnosky et al. are using the fold catastrophe model discussed in Scheffer et al. (2009). The Scheffer et al. analysis of the fold catastrophe model uses some fairly sophisticated ideas from complex systems theory, but the ideas are relatively simple. The straight line that so offends Myers arises because this is the direction of the basin of attraction. In the figure below, I show the fold-catastrophe model. The abcissa represents the forcing conditions of the system (e.g., population size or greenhouse gas emissions). The ordinate represents the state of the system (e.g., land cover or one of many ecosystem services). The sideways N represents an attractor — a more general notion of an equilibrium. The state of the system tends toward this curve whenever it is perturbed away.

The region in the interior of the fold (indicated by the dashed line) is unstable while the upper and lower tails (indicated by solid lines) are stable and tend to draw perturbations from the attractor toward them. The grey arrows indicate the basin of attraction. When the system is perturbed off of the attractor by some random shock, the state tends to move in the direction indicated by the arrow. When the state is forced all the way down the top arc of the fold, it enters a region where a relatively small shock can send the state into a qualitatively different regime of rapid degradation. This is illustrated by the black arrow (a shock) pushing the state away from point F2. The state will settle again on the attractor, but a second shock will send the state rapidly down toward the bottom arm of the fold (point F1). Note that this region of the attractor is stable so it would take a lot of work to get it back up again (e.g., reduce population or drastically reduced total greenhouse gasses). This is what people mean when they colloquially refer to a “global tipping point.”

This is the model. It may not be right, but thanks to Scheffer et al. (2009), it makes testable predictions. By framing global change in terms of this model, Barnosky et al. are making a case for empirical investigation of the types of data that can falsify the model. Maybe because of the restrictions placed on them by Nature (and these are severe!), maybe because of some poor choices of their own, they include an insufficiently explained, fundamentally complex figure that a critic with clear interests in muddying the scientific consensus can sieze on to dismiss the whole paper as just more Ehrlich-style hysteria.

For me — as I suspect for the authors of the Barnosky et al. paper — massive, structural uncertainty about the state of our planet, coupled with a number of increasingly well-supported models of the behavior or nonlinear systems (i.e., not simply normal science) strongly suggests a precautionary principle. This is something that the economist Marty Weitzman suggested in his (highly technical and therefore not widely read) paper in 2009 and that I have written about before here and here. This is not inflammatory fear-mongering, nor is it grubbing for grant money (I wish it were that easy!). It is responsible scientists doing their best to communicate the state of the science within the constraints of society and the primary mode of scientific communication. Let’s not be taken in by writers pretending to present “just the facts” in a cool, detached manner but who actually have every reason to try to foment unnecessary uncertainty about the state of our world and impugn the integrity of people doing their level best to understand a rapidly changing planet.

References

Kuhn, T. 1962. The Structure of Scientific Revolutions. Chicago: University of Chicago Press.

Scheffer, M., J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk, and G. Sugihara. 2009. Early-Warning Signals for Critical Transitions. Nature. 461 (7260):53-59.

Weitzman, M. L. 2009. On Modeling and Interpreting the Economics of Catastrophic Climate Change. The Review of Economics and Statistics. XCI (1):1-19.