Archives: Evolution

Science isn’t a pizza, so stop slicing it up.

Science isn’t a pizza, so stop slicing it up.


Praj, author of the blog Do I Need Evolution, drives me nuts. Don’t get me wrong, he seems like a nice guy and a well-meaning one at that. Yet as one of the new wave of commentators on the science vs religion battles, he appears to hold a view that basic science is just an indulgence that we should be quiet about in favour of the real science that puts satellites in the air and cures diseases:

You see two images when scientists speak about “science” (something I think we should avoid, but that’s another story). One is science as a useful tool: it helps us cure diseases, win wars, grow the economy, feed the planet, and so on. The other is science as a world-view: it imparts a sense of wonder, conquers fear, and reveals beauty. These images are a spectrum rather than distinct categories. Most scientists have some of both, though applied researchers are usually closer to the science as a tool view and basic researchers tend to be on the other end.

The problem is that the overwhelming majority of non-scientists, and especially the religious, don’t care very much about science as a world-view. They live on the very far end of the spectrum where science has almost zero intrinsic value. To those people science only matters because it helps them do stuff they care about.

Science lobbies appreciate this fact, which is why they focus on the concrete, tangible benefits of research. They know it would be ridiculous to ask for billions of dollars because some people think particle physics is beautiful. Policy experts also appreciate this fact. The standard “explain your thesis to your grandmother” interview question for my DC fellowship is judged on how well you make your research relevant. I suspect many academic scientists don’t appreciate this fact. Or if they do, they don’t weigh it as much as they should. Academics are especially prone to hyperbole about the wonders of science.

Praj would like us to think of science as more or less practical; some science will give us economic benefits, and can be explained in that light, so that’s good. Other science is ‘world-view’ science that only exists to satisfy the whims of a subset of curious people. But I’m going to disagree here and say that Praj doesn’t understand science very well. Despite lip service to a ‘spectrum’, he would like to slice science up into boxes that can be addressed independently. That way, we can focus on ones that are practical, and ignore ones that aren’t 1. But we can’t do that with science. Science is a process and a body of knowledge that is interconnected and historically contingent.

As an example of interconnection, we can look to Darwin himself. Putting aside for the moment the historical antecedents to his work on evolution (including Lamarck and his own grandfather), Darwin had to integrate ideas from all corners of biology with the work of the economist Thomas Malthus to arrive at his insight regarding natural selection. In order for this theory to be sensible, it required a much older earth, ideas that came in part from the volumes of the geologist Charles Lyell that he read while on the Beagle. One of the first serious scientific challenges to evolution came from the physicist Lord Kelvin, who calculated both the age of the earth and the age of the sun before concluding that both were too young for evolution to be valid. This phenomenon has only gotten stronger over time. We carve fields like biology, physics, chemistry, psychology, etc. up into separate fields because we have to have a way to award degrees, and topics can indeed be thought of as clustering together naturally. Most ecologists don’t study quantum field theory, because with our current understanding of science, it’s hard to see how to use it effectively in their work. But that doesn’t mean that we can take those lines in a course catalog as representative of some real and sharp division. What we call biology and chemistry are deeply interrelated, as anyone who’s spent time in a molecular biology lab will tell you. Neuroscientists spend a lot of time on the biology and chemistry (and by extension, biophysics) of the brain and nervous system. One of my favourite evolutionary biologists is John Maynard Smith, who trained as an aeronautical engineer, and we all know that physicists are math fetishists (I kid, I kid). Just look at the new interdisciplinary fields that are cropping up with increasing frequency: biophysics, neurochemistry, behavioural and neuroeconomics, agrophysics, systems biology, computational sociology. And I could do this all day, because science is a heavily connected graph of fields that reflect an underlying continuum in our study of nature. Apparent divisions in scientific fields usually reflect more about our lack of understanding than they do of any real separation.

This brings me to my second point, the historical contingency. Praj and people like him would like to focus on ‘practical’ science that we can make relevant for the public. Things that bring economic benefits now. ‘Applied’ science, new technology, and so on. But people who champion this division between basic and applied research are making a simple mistake of perspective, one that even serious historians of science are prone to making. What is considered applied science now relies directly upon research that used to be considered basic and impractical2. Applied science is simply science for which the next step on path is to an economic benefit that is clear and predictable, but ‘practical’ or ‘applied’ science doesn’t get to walk away and ignore this chain of connections and history. Putting a satellite into orbit relies on centuries of work in physics and mathematics that was once considered deeply impractical. It is the result of thousands of individual steps, some practical, some not, that have given us the ability to put things into orbit. Medical doctors rely on work in anatomy, biochemistry, and biology that has often been considered very impractical (Galen himself wasn’t allowed to work on humans because work on cadavers wasn’t permitted; he inferred from animals because of their anatomical similarities). Astronomy and cosmology are the prototypical basic and useless sciences now, but if we ever become a truly space-facing people, then our descendants will be very happy that we wasted our time on it for the simple pursuit of knowledge. And who knows? Astronomy and cosmology could suddenly become very useful before that; we can’t easily predict what will be applicable, but the history of science tells us that we can expect to be surprised. I’m sure that the Einstein of 1945 would have had some words to say on the topic to the Einstein of 1905.

Praj would like us to believe these things about science, because he wants to believe that Bill Nye is wrong when he says that creationism threatens our ability to understand the world and innovate in science and technology:

I’ve often wondered how people like Bill Nye can maintain this apocalyptic vision. As Saletan notes in the very next paragraph, there are actual, real-life engineers and scientists who reject evolution.

Praj himself relates that his parents were successful doctors and his dad doesn’t understand evolution, so evolution must not be relevant to medicine. He make similar claims several times on his blog, so it’s worth finishing off this post by addressing it. Yes, there are successful doctors and engineers and even other scientists (though few if any biologists) who don’t understand evolution. That is, of course, not the same as saying that they actively reject it and believe in young-earth creationism. There’s a difference here. I don’t understand much about particle physics, but though I consider that a failing it’s one I can live with. There isn’t enough time in the day for me to learn everything I would like to. And yes, doctors who haven’t learned about evolution aren’t necessarily bad doctors. I can even forgive those who ‘reject’ it because they’ve never been exposed to it properly. But doctors who actively reject evolution when taught it, and believe that the earth is 6000 years old? This requires that they actively read and reject the evidence from not just biology but physics, chemistry, geology, and so on. This requires that their critical thinking skills are so deficient that they cannot understand and assimilate anything of such a large and coherent body of evidence upon which there is broad and solid scientific consensus. How can this be a good doctor or engineer? Would you like your satellite designer to be a flat-earther? Would you be worried if your bridge engineer was proficient but convinced that physics and material science works as it does because of the action of ambitious fairies?

When my doctor asked what I did for a living and then launched into a tirade because he was a young-earth creationist, I asked him how he dealt with giving advice to his patients on vaccination or antibiotics. He replied that he didn’t believe in vaccination and that he didn’t think that antibiotic resistance was a problem, because viruses and bacteria don’t evolve. I changed doctors that day. This is a man who may actually kill patients with advice like this, and it stems directly from his religious beliefs. Are all creationist doctors and engineers bad at their jobs? No, but I submit an empirical hypothesis that doctors, engineers, and scientists who are actively creationist (especially YEC) and reject scientific understanding to protect their beliefs are more likely, on average, to be bad at their job and to have crucial deficiencies in their thinking that could prove harmful to their work.

Science isn’t something that can be cleanly chopped up into convenient portions and picked over for economic benefit or religious palatability. It is a method, the best method we have, for discerning the truth about the universe and everything in it. It is a deeply interconnected and historically contingent search for that truth. What we chose to do with that truth afterwards is up to us, but when we ignore those connections and history and our inability to predict the future, we do so to our own detriment.

  1. Like evolution.
  2. Note that I’m not making the same claim about technology, which as McClellan and Dorn persuasively argue, has had a habit of coming before the science that explains it

Who is Andrew Fabich?

tl;dr: Andrew Fabich is a creationist 'microbiologist' at Liberty University who isn't a great scientist.

Who is Andrew Fabich? This question has haunted me since I watched the debate between Ken Ham and Bill Nye. One of Ham's favourite tactics in that debate was to name-drop 'creationist scientists', as though a parade of Ph.Ds would somehow disprove evolution in a blaze of authority. Most of his name-drops were typical creationists: engineers, medical doctors, and the like. But then came Andrew Fabich. In an attempt to discredit the awesome work done by Richard Lenski and his lab on the adaptation of E. coli to use citrate as a novel food source, Ham suddenly trotted out a microbiologist to take a swipe at Lenski et al.

You can watch the video here, or starting at the relevant section here, but I've transcribed it for you (and so has the Lenski blog here):

Ham: There are those that say 'hey, this is against the creationist'. For instance, Jerry Coyne from the University of Chicago says, 'Lenski's experiment is also yet another poke in the eye for anti-evolutionsts,' he says 'The thing I like most is that it says you can get these complex traits evolving by a combination of unlikely events.' But is it a poke in the eye for anti-evolutionists? Is it really seeing complex traits evolving? What does it mean that some of these bacteria are able to grow on citrate? Let me introduce you to another biblical creationist who is a scientist.

Fabich: Hi, my name is Dr. Andrew Fabich. I got my Ph.D. from the University of Oklahoma in microbiology. I teach at Liberty University and I do research on E. coli in the intestine. I have published in secular journals from the American Society for Microbiology including Infection Immunity and Applied Environmental Microbiology as well as several others. My work has been cited, even in the past year in the journals Nature, Science, Translational Medicine, Public Library of Science, Public Library of Science Genetics, it is cited regularly in those journals and while I was taught nothing but evolution, I don't accept that position and I do my research from a creation perspective. When I look at the evidence that people cite of E. coli supposedly evolving over thirty years, over thirty thousand generations in the lab, and people say that is it now able to grow on citrate, I don't deny that it grows on citrate but it's not any kind of new information. It's .. the information's already there and it's just a switch that gets turned on and off, and that's what they reported, and there's nothing new.

Ham: See, students need to be told what's really going on here. Certainly there's change, but it's not change necessary for molecules to man.

I don't need to deal with Fabich's criticism of the E. coli work, for the simple reason that Lenski and his postdoc Zachary Blount have already crushed it over at their blog post. You can see it here, and I encourage you to do so. It's a great read for the biology alone, and it's pretty damning stuff for Fabich. As Zach says at one point:

Fabich went on to state that this “switch” is what we reported. That is emphatically not true. It beggars belief that anyone, much less a trained microbiologist, could actually read our 2012 paper, where we reported the genetic basis of Cit+, and come away thinking this.

So who is this guy? Who is this Ph.D. in microbiology that makes such obvious and simple errors, who presents himself as a creationist biologist and appears with Ham to misinterpret some great work?

Well, let's start with where he works. Fabich is an assistant professor at Liberty University, which is already ringing an alarm bell. Liberty University is a private Christian university located in Virginia, and its biology department openly teaches Young Earth Creationism (YEC). How about Fabich himself? He made a pretty big deal of his publication record during the debate, so I think that we should start by taking a look at it. Fabich has five publications listed on his profile, all dealing with E. coli and the most recent published in 2011 (a Google Scholar search shows the same thing, disregarding a couple of obvious false alarms). These articles have indeed been cited: 6, 56, 82, 16, and 12 in order of date of publication, but these are all large-team papers, with over a dozen authors for several of them and no less than four. This is not suggestive of a creative and robust scientific output on Fabich's part. Finally, the 2011 paper shows his affiliation as being with Oklahoma, which suggests that Fabich hasn't published a single thing since moving to LU. As far as track records go, it wouldn't get you tenure at Harvard (if that mattered to you). Hell, I have more than double the number of publications that he does.

If that was all there was to it, then I probably wouldn't be writing this blog post. But then, I came across this video. It appears to be another attempt to parade a 'creationist scientist' in front of a camera, but it's interesting for its content. In it, Fabich manages to revise the history of scientific thought, bag on the scientific method, quote-mine (incorrectly) a paper on evolution from the 1960s, and from this conclude that evolution is false. A choice highlight from the middle of the video:

The science is not the issue. When you look in the scriptures, even Jesus acknowledges this when he says in Luke 17 that 'the kingdom of God comes not with observation'. Why would you impose that worldview on me? Even Jesus says that you can't do an experiment to prove God or who God is. So, what is the scientific method. Actually, one of the points that I want to make here, right up front, is that modern science had its foundations in the Bible, in Christian Europe. Okay, there are some exceptions, like some people out in India and Turkey, they're isolated and rare exceptions. But the scientific method is based on Biblical presuppositions. I'm not going to go into all of those, but the scientific method, you realise it, you start out with an observation and then you go and you make a hypothesis, collect your data and then there's oh interpretation. You can't get rid of your bias. All scientists are bias [sic]. I'm guilty and so are you.

So, the problem with science that I have is that it never ends. Well, it might not be a problem, it's how I keep my paycheck. Okay, I get it. So one good hypothesis leads to another and so it goes on and on and on and it never stops. If you're not careful, you get trapped into worshipping the internal scientific method rather than the eternal creator of the scientific method who gave it to us so that we could receive it.

What it comes down to here is, our theory has become one which cannot be refuted. You know who said that? It must be a creationist, some big creationist you all recognise and you've got your short list of who it said. Because we're just, we're uncompromising and we're not based on facts and data. You know who said that? It was Paul Ehrlich and L. C. Burch. They, the evolutionists, said 'our theory of evolution has become one which cannot be refuted by any possible observation'. Are you meaning to tell me that it's not based about facts? Whoaaa, so evolution's not based on fact.

There's so much wrong here that I barely know where to start.

  • The history of modern science doesn't begin with the Bible. It is difficult to extricate Christians and their institutions from the matter, but to say that modern science started with the Bible is laughable at best. For instance, such a statement manages to ignore the entire history of scientific thought in Ancient Greece. Aristotle formed a significant, even commanding, aspect of scientific thought until the Scientific Revolution through the 16th to 18th centuries. It also ignores the important role that Byzantine and Islamic influences played, and grossly trivialises the achievements of civilisations in places like India and China. These are all recorded and established facts that Fabich blithely rolls over.
  • The scientific method is a large part of what gives science its power. And far from being a problem, the recursive nature of scientific progress is one of its greatest strengths. The comedian Dara O'Briain said it well when he said 'Science knows it doesn't know everything; otherwise, it'd stop. But just because science doesn't know everything doesn't mean you can fill in the gaps with whatever fairy tale most appeals to you.'
  • Yes, scientists are biased. We're all human. In fact, if Fabich cared to Google it, fields like the philosophy of science and the sociology of science exist to tackle exactly this question. But in general, the power of science is that it is self-correcting (though this is not without challenges, and needs constant work). And Fabich basically admits to paying lip service to the scientific method to keep a paycheck. I'll let you decide on how that reflects on him.
  • And of course, what would a creationist be without a cherry-picked quote? The quote from Ehrlich and Birch comes from a paper published in 1967 and – despite what Fabich has implied by leaving out the following sentences – is not some sort of anti-evolution screed. In fact, the quote in his video goes on to say: 'The cure seems to us not to be a discarding of the modern synthesis of evolutionary biology, but more scepticism about many of its tenets. In population biology, more work is needed in elucidating the general properties of populations, both those made up of one species of organism and those made up of two or more species without reference to dogmas or guesses about how they may have evolved.' So, in reality, the quote that Fabich has chosen is actually about a call for more empirical work to fill in the gaps in the data. And as anyone who's picked up a book in the last 50 will have noticed, they got what they were asking for. (For a longer fisking of this same quote and others, check out Peter Hutcheson from nearly thirty years ago. Way to stay current, Fabich).

So, who is Andrew Fabich? Well, the evidence suggests that he's a poor excuse for a scientist. It suggests that he's not an active member of the scientific community, and that he's interested not in helping the progress of science but in tearing it down to satisfy his worldview. And it suggests that we can safely ignore him.

But Fabich is only the symptom of a larger problem, one that Ken Ham exploited ruthlessly in his side of the debate. The problem is credentialism, or the over-reliance on credentials such as academic degrees. Ham was simply employing a time-honoured technique: parade out a bunch of 'doctors' and 'scientists' who are creationists in an attempt to get a pass simply because they have Ph.Ds. The problem with this is two-fold:

  1. When verified properly, credentials can be a useful tool in situations such as making hiring decisions (a Ph.D. minimum for a research position is probably a defendable, if not foolproof, criterion to use). But academic credentials are no proof of research savvy or even basic competence; anyone with a browser can surf their way to a Ph.D. at a diploma mill. And the problem with Ham listing scientists who happen to be creationists is that it misses the fact that the vast majority of scientists do not share their beliefs. In fact, Project Steve (of which I am a proud member!) was created to mock this very phenomenon of listing creationist scientists.
  2. Ham is essentially making an argument from authority, which is a logical fallacy. The fact that I have a Ph.D. in Biology doesn't mean that I'm automatically right about anything biology-related, even in my own area. What it signifies is that I've spent a long time studying and thinking about biology and related topics, and that my thoughts on the matter are probably more well-informed than the average person's. But if a precocious seven-year child wanders up to me and hands me a verifiable fossil of a Precambrian rabbit, then as a field we would have some serious re-thinking to do1. It doesn't matter that she's still learning to reliably write her own name, or that I have a Ph.D. The evidence is the evidence; we don't make the case for evolution based on our degrees, we make it based on our observations of the world around us.

You can see this at work with Fabich and the debate in general. Fabich shows up in the video, snows the audience under with his credentials, and then declares – based solely on his now-established authority – that Lenski et al don't know what they're talking about. If you watch the video, you'll notice that Bill Nye doesn't do any of that. What does he do instead? He presents evidence. He holds up physical objects, he shows records of observations of trees and ice cores, he discusses what we see in the Grand Canyon.

So why do Ham and crew do this? Because, unfortunately, it works. This is one of the great challenges of science communication: people don't have the time or inclination to become experts, so they rely on others to do it for them (a mental version of the division of labour). How is the average person to know who has a "real" Ph.D. and who doesn't, or which expert is trustworthy and reflects the broad scientific consensus? Creationists, climate-change denialists, anti-vaxxers: they all rely on the same method of inducing doubt. They agitate for 'balance' and 'teaching the other side', because they know that doing so legitimises the debate. In fact, it's one of the reasons that I don't support Nye's decision to debate Ham. I feel that he did a great job in the situation, but I still think that it was a mistake2.

Until we can find a better solution to this problem, though, we're stuck with how I started this post: we need to root out people like Fabich and bring them into the harsh light of good science. Now if you'll excuse me, I have to go do some science of my own.

  1. We might also want to investigate the awarding of a major scientific prize to a pre-teen, but that's another issue
  2. Though this is arguably an empirical question. I could be wrong. Perhaps, on balance, he did more good than harm.

What evolved first, sight or hearing?

While getting tangentially involved in an unrelated conversation about the science behind evolution yesterday, I ended up getting this great question from J. William Runnells yesterday:

Now, I got all excited and gave it some thought and read a bunch of stuff and even went to the library 1 to respond to this, but before I do, a disclaimer is in order:

This is a complex question, and not something I’ve done work on myself.  I welcome additions, corrections, and even complete overhauls from people who work in this field.

That said, let’s give it a whirl.

  1. Yes, I’m a nerd.  I know, I hide it well.

Yes, you could inherit a ‘gene’ for celibacy.

I really enjoy Neil deGrasse Tyson’s work as a science communicator and all-around advocate of rational thought, and I think he’s a really smart guy.  But even really smart people can be fooled when it comes to genetics and evolution, especially if it’s not what they do for a living.  Here’s what Neil tweeted this morning (my time):

Unfortunately, that statement just isn’t true.  There’s a couple of possible explanations, because his statement (despite being ‘simple logic’), is a little vague and open to interpretation.  It’s possible that he was talking about an allele for celibacy, with the other allele probably being the ‘has sex’ allele.  However, as several people pointed out on Twitter, if the ‘celibacy’ allele was recessive it could easily be inherited.  Another plausible scenario that I didn’t see anyone on  Twitter catch is that it could be caused by overdominance (or heterozygote advantage);  just like the case of sickle-cell anemia, where homozygotes have reduced fitness but heterozygotes have an advantage due to their resistance to malaria, if a double dose of ‘celibate’ reduced fitness but a single dose led to greater fitness for some reason then celibacy would be maintained.

More generally, we can ask how a trait like celibacy could arise by evolutionary forces (if indeed it did, and wasn’t simply a cultural artifact).  In order to – hopefully – eliminate the effects of culture, we’ll consider an animal model in which some proportion of the population is celibate.  How could that happen?  Well, if you consider the question in its more general wording as “how could a trait that leads to animals failing to reproduce arise”, the underlying logic is much the same as for same-sex behaviour in animals.  Celibacy would be a more extreme form of this general question, as not many species have members with exclusively homosexual behaviour that have zero chance for reproduction (though apparently there are a few examples, such as sheep), but if an adaptive or non-adaptive explanation works for the persistence of homosexual behaviour then it might work for the persistence of celibacy too.

Helpfully, Nathan Bailey and Marlene Zuk wrote a great review paper a few years ago (here’s a pdf link I found) that rounded up many of the potential explanations for same-sex animal behaviour.  Looking at Table 1 of that paper, where Bailey and Zuk list the explanations in short form, it’s clear that some of them don’t work for celibacy (like the idea that same-sex behaviour is selected for because it provides practice), but several of them do work.  The most obvious potential explanation for persistence of celibacy would, of course, be kin selection.  If a gene for celibacy conferred indirect fitness benefits (i.e. if celibate individuals enhanced the fitness of their sibling), then that gene could be selected for and lead to a polymorphism in the population.  Celibacy could even be a byproduct of the evolution of life history traits, especially in humans where advances in survival and resource provision have led to greatly reduced birth rates as individuals rationally put more and more effort into fewer and fewer offspring to maximize fitness;  if genetic variation for this trait were being maintained and the optimal number of children was low, it  could lead to some individuals ‘overshooting’ the optimum and having zero children.

These are, of course, simply wild speculation dressed up in elements of evolutionary theory, but they are still plausible explanations for how a ‘gene for celibacy’ might arise.  Don’t mistake them for likely explanations, mind you;  even if we do manage to ignore cultural effects which almost certainly play some kind of  role in human celibacy, many of the plausible explanations for celibacy like kin selection have received little support in terms of same sex behaviour (as Bailey and Zuk note).  The reason I bring them up here is to illustrate a specific point, i.e. that seemingly simple statements about evolution can be surprisingly wrong.  Even if you’re as smart as Dr. Tyson.

Science journalism blows it, dolphin rape edition.

A few weeks ago I got into a discussion on Twitter with Ananyo Bhattacharya, online editor of Nature News and writer for The Guardian’s science section, after he put out a call asking for ways to improve science journalism. During that conversation, I argued that one way to do this is to create a culture of journalism that values scientific knowledge and expertise as a core value[1]. Ananyo seemed unimpressed with my viewpoint, and suggested that the main point of science journalism was to pry into the dark corners and root out biases, fraud, and the like in science. He views scientific communication and scientific journalism as two distinct things (and thinks that journalists doing ‘PR for science’ is ‘drippy’). Indeed, when asked directly during a Royal Institute forum on science journalism whether journalists should read the original papers behind the stories that they write, he dismissed the idea:

“If the question is ‘must a good science journalist read the paper in order to be able to write a great article about the work’ then the answer is as I said on Tuesday ‘No’. There are too many good science journalists who started off in the humanities (Mark Henderson) – and some who don’t have any degrees at all (Tim Radford). So reading an academic research paper cannot be a prerequisite to writing a good, accurate story … So I stick to the answer I gave to that question on the night – no, it’s not necessary to read the paper to write a great story on it (and I’ll also keep the caveat I added – it’s desirable to have read it if possible).”

He further suggests, in the same comment (original source), that if journalists had to read original papers than no one could report on particle physics[2].

I’m not going to try and hide my bias here: I don’t like Ananyo’s viewpoint on this. I don’t think that it will lead to good writing, either of the communication or journalistic variety, but more importantly I think that forcing journalists to read the papers before they write an article might have stopped stupid @#$@ like what happened today from happening at all.

The story: I received an e-mail this morning from Dr. Bill Sherwin, a member of the Evolution and Ecology Research Centre (E&ERC) here at my current institution, the University of New South Wales. Bill is one of the authors on a new paper coming out in the Proceedings of The Royal Society (B), entitled ‘A novel mammalian social structure in Indo-Pacific bottlenose dolphins (Tursiops sp.): complex male-male alliances in an open social network’. The paper is a nice little exploration of the characteristics of social networks in dolphins found in Western Australia; in essence, they were testing whether two hypotheses about the nature of these social networks were tenable given the data they’ve observed. In particular, they tested whether dolphins show signs of engaging in ‘community defence’, where higher order alliances of dolphins form to patrol and defend a larger community range, similar to chimpanzees, or if it follows a ‘mating season defence’ model where male groups shift their defence to smaller ranges or sets of females when it’s mating season. The comparison to terrestrial species with complex social cognition (such as primates and elephants) is an interesting one, because it provides yet more insight into the relationship between the development of complex cognitive faculties and social relationships.

So far, so good. Bill gave a simple explanation of the paper in an email that he was sent out to the E&ERC this afternoon:

We put out a paper that said “dolphin male alliances are not as simple as other species”, but it has stirred up quite a lot of interest, because somewhere in it, the paper mentioned “bisexual philopatry”, which when translated out of jargon means  “males stay near where they were born, AND females stay near where they were born” – nothing more or less than that.

‘Quite a lot of interest’ is one way to put it. ‘Idiots crawling out of the woodwork’ is another. Here’s the headlines of four stories that were written about this paper:

Dolphins ‘resort to rape': Dolphins appear to have a darker side, according to scientists who suggest they can resort to ‘rape’ to assert authority. [The Telegraph]

Male dolphins are bisexual, US scientists claim. []. (Note that this is an Australian website, and Bill is Australian).

Male bottlenose dolphins engage in extensive bisexuality. []

And by far the best of the lot (guess who it’s from?):

The dark side of Flipper: He’s sexual predator of the seas who resorts to rape to get his way. [That’s right, The Daily Mail].


Are you kidding me? If the ‘writers’ of these articles had read the paper, they would have noticed that it contains nothing about the sexual behaviour of the dolphins they studied, bisexual or otherwise, aside from brief mentions of the possible consequences of social networks on reproductive success. It certainly didn’t mention anything about bisexual behaviour, homosexual behaviour, or rape. Now, it’s well known that dolphins engage in homosexual behaviours, and I’ve seen papers arguing that they use sexual coercion as well (Rob Brooks confirms this). But these topics have nothing to do with this paper at all. Even a cursory glance through the original source would have killed these headlines – and the first few paragraphs of the Mail story – which aren’t just a miscommunication but border on outright fabrication. The articles themselves are weird mixes of sensationalist headline with a regurgitated paraphrasing of the much better Discovery News piece that they are treating as the primary source. Here’s the problem, though: it’s Discovery News that makes the original mistake about ‘bisexual philopatry’, interpreting it as bisexual behaviour (hot male dolphin-on-dolphin action, as it were). A reporter who had read the original source could have corrected that mistake fairly easily, or could even have been driven to ask further questions. Without that, however, the press cycle grinds mercilessly forward to Flipper the bisexual rapist.

For my part, I was happy to see that James Randerson’s informal survey of science and health writers showed that many of them do read the original papers. And the kind of people who write things about science that I trust, whether they’re professionally trained in science or not, are not the sort of people who do boneheaded things like this. Ananyo might retort that ‘asking questions’ is enough (he suggested as much in his comment above). Matt Shipman said much the same thing in the piece that Ananyo was commenting on. Yet of all people, Ananyo should be wary of this answer, with his focus on investigative science journalism. A scientist writing an email or doing a phone interview can tell you just about anything that you want to hear; a press officer can write a terrible press release; a wire service will probably distort what comes down the line. But a scientific paper is the One, True Source. It is a public record of what was done, and it is the first and best place to start for answers about a study or a scientific topic[3].

Don’t mistake my criticism of Ananyo’s position of reading scientific papers as a general attack on scientific journalism. I think that there’s a lot of great science journalism out there, and that there are even more great science journalists and communicators. Despite the perennial swirl of internet discussion on the topic, I don’t actually think that the whole field is hopelessly broken like some seem to. I just happen to believe that scientific papers, the products of our time and energy as researchers, form an integral part of the process of talking about science (and it’s part of the reason for my support for Open Access publishing). And I think that disgraceful trainwrecks like the reporting on Bill’s paper are a perfect illustration of the need for these papers to be a part of that process.

[Update: Rob Brooks has also discussed this issue over at TheConversation].


[1] Because of Twitter’s space constraints, this was misconstrued to mean that I was agitating for all science journalists to have a Ph.D. in a scientific discipline. Though I wouldn’t be upset if this happened, that’s not what I meant: it is more than possible to have a deep love and knowledge of science without having a degree in a scientific field. Hell, Carl Zimmer probably knows more about viruses and evolutionary biology than I do, and his only training is an undergraduate degree in English. My argument is only that having scientific training increases the probability of a writer or journalist having a good grasp on how science works, not that it’s the only way for that to happen. I will continue to argue, though, that those having a love of science (professional or amateur) will, on average, produce better science writing and science journalism than those who don’t.

[2] He also claimed that most of the people asking journalists to read papers are biologists and medical people, who write easier-to-understand papers. I would have to turn this back on him: if biology and medical papers are so easy to understand, why shouldn’t journalists read them every time?

[3] Yes, there’s no guarantee that what is written in the paper is true. But the chances of detecting fraud are essentially zero if you don’t read the paper to begin with, and if you’re a journalist looking to catch the next Stapel, chances are that you’ll have to wait for the scientific community to find him and tell you about it anyways.

Group selection, again. Yay.

I was amused to see that David Sloan Wilson took a weird poke at Dawkins, got thrashed by Jerry Coyne, and didn’t like it.  In fact, I was going to leave this as a link post, but while searching for a link to Coyne’s piece (Wilson can’t seem to figure out how to embed links to anything but his own blog in his posts) I came across a post by a blogger who calls him/herself “The Verbose Stoic”.  This piece is problematic on several points, but discussing this is going to take some space so I’ll do it here instead of a comment on Verbose Stoic’s blog;   from here on, I’m going to refer to him/her as VS.

VS starts off by questioning “examples”:

 What I want to talk about is the objections that Coyne raises against Wilson’s group selection theory:

Dawkins’s argument against the efficacy of group selection was that this form of selection is usually unsuccessful because groups are vulnerable to subversion from within by those selfish replicators. That is, “cheating” replicators that are “good” for individuals but bad for the group as a whole will tend to propagate themselves. Yes, altruism may help groups propagate, but altruistic groups are susceptible to invasion by cheaters unless the “altruism” is based on kin selection or individual selection via reciprocity.

That’s the main one, but he goes on to fill in more later:

Dawkins’s (and my) beef with group selection as a way to evolve traits that are bad for individuals but good for groups is that this form of selection is inefficient, subject to subversion within groups, and, especially, that there’s virtually no evidence that this form of selection has been important in nature.

Let me deal with the two minor ones before getting back to the main event. Starting with the last one, we can see that it’s a bad argument, because what Coyne is doing here is saying that one of the reasons to reject the examples Wilson’s giving of cases where group selection has been important in nature is … that you haven’t found examples of cases where it has been important in nature. Except, perhaps, for the specific cases Wilson is citing. You can’t in any way reasonably claim that the fact that you haven’t found examples of it yet means that you can dismiss this proposed example.

Look, Wilson isn’t citing any specific cases of group selection occurring in nature, mostly because there aren’t any.  When I say that, I mean that Wilson hasn’t been able to demonstrate that a trait arose because of group selection and not kin selection or natural selection or any other evolutionary force.  Wilson’s argument is that (1) group selection (a.k.a. “new” group selection or multi-level selection) is something different than any other variety of selection, and (2) that it is responsible for the evolution of traits such as altruism.  But (1) group selection reduces mathematically to inclusive fitness (follow the links in my previous post), and so (2) is trivially true.  Sure, it arose by “group selection”, but that’s an empty statement.  Wilson’s ‘proposed example’ is a theoretical model that was dealt with when he proposed it nearly 40 years ago (Wilson, 1975), and though it’s been refuted dozens of times since, he keeps holding on to it and insisting that he’s already won.   I’ll quote at length from West et al. (2007) to drive home the point:

It has since been shown that kin selection and new group selection are just different ways of conceptualizing the same evolutionary process. They are mathematically identical, and hence are both valid (Hamilton, 1975; Grafen, 1984; Wade, 1985; Frank, 1986a, 1998; Taylor, 1990; Queller, 1992; Bourke & Franks, 1995; Gardneret al., 2007). New group selection models show that cooperation is favoured when the response to between group selection outweighs the response to within-group selection, but it is straightforward to recover Hamilton’s rule from this. Both approaches tell us that increasing the group benefits and reducing the individual cost favours cooperation. Similarly, group selection tells us that cooperation is favoured if we increase the proportion of genetic variance that is between-group as opposed to within-group, but that is exactly equivalent to saying that the kin selection coefficient of relatedness is increased (Frank, 1995a). In all cases where both methods have been used to look at the same problem, they give identical results (Frank, 1986a; Bourke & Franks, 1995; Wenseleers et al., 2004; Gardner et al.,2007).

VS also isn’t happy about “efficiency”:

The first one is also a pretty bad argument when you look at evolution. The argument is that Wilson’s proposed solution would be inefficient, but it seems to me that one of the main thrusts of evolution is that it can indeed be — and often is — inefficient but as long as it works, that’s not a problem. When has it become a criteria for evolutionary explanations that it achieve maximal or even reasonable efficiency. To go down that route would risk re-introducing a need for a designer, to ensure that the mechanisms stayed efficient. That can’t be what Coyne wants. But, again, why is efficiency even a factor? Why would you sort evolutionary arguments by efficiency? Being more or less efficient isn’t a hallmark of evolutionary mechanisms, so if two mechanisms are proposed but one is more efficient than the other that says absolutely nothing about which one is more likely to be true.

Efficiency is a perfectly fine criterion to use, though the term is a little vague as used here.  Assuming that group selection is different from inclusive fitness (which it’s not):  if group selection results in an very slow rate of change in gene frequencies or a lower probability of fixation compared to inclusive fitness, then inclusive fitness is more ‘efficient’ and is more likely to be the cause of a trait fixating in a population.  At least, that’s how I would use the term;  I don’t want to put words in Dr. Coyne’s mouth, though I think that my view here is consistent with his usage and with the literature I’ve reviewed.  In other contexts, I’ve also seen ‘efficiency’ used to say that group selection wouldn’t actually the enhance relative fitness of altruism vs ‘cheating’ (which isn’t a great term for this, as I discuss below), which ends up in the same place.
In any case, VS seems to be confusing efficiency (whether Dawkins / Coyne would use it the way I do or not) with design.  Adaptations are often very badly designed, such as the case of the amazing recurrent laryngeal nerve, but that doesn’t say anything about how fast (or with what probability) genes for those adaptations spread through populations as a result of natural selection.  Even if group selection works the way that Wilson thinks it does, reasoning from the published theoretical models it’s easy to see why it would be an extremely inefficient process with its cycles of groups / reproduction as compared to overlapping generations with continual selection pressures.
VS finally goes onto what he thinks is the biggest error that Coyne makes:

That leaves us with the main complaint: cheaters. The main issue here is that there is an issue raised against the individual selection explanations of altruism as well, even kin and reciprocal altruism and it is … cheaters. Cheaters will benefit if they can get away with it, and so those individuals will prosper and those who are altruistic will be outstripped, and so altruism is not self-sustaining at the individual level. To get around this, the proponents of evolutionary explanations for altruism end up appealing to cheater detection mechanisms […]

Additionally, it seems to me that group selection can actually get this without having to apply specific cheater detection mechanisms. After all, group selection would imply that the relevant competing entity is the group. Thus, if a group has a significant percentage of people who are altruistic, then it outperforms groups that don’t. Thus, if you have a group where this happens and where too large a percentage of the group are cheaters, then that group will cease to get those benefits and be outcompeted and presumably eventually exterminated by the groups where that does not happen. Thus, group selection here becomes self-sustaining; if you are above or at the magical percentage that means you benefit from being altruistic, you benefit over other groups as long as it stays there, but if it ever drops below that your group may well collapse and your individuals, then, all lose. Note that we would still see cheater detection mechanisms emerge because they are mechanisms that make the group stable and so less likely to fall below that percentage and collapse.

It seems like VS might be on the verge of confusing old and new school group selection, as the bolded statements (my emphasis) suggest.  West et al.’s paper has a great figure that shows the difference between the two:

In the text of their article, they point out that “[a]nother way of looking at this is that the new group selection approach looks at the evolution of individual characters in a group structured population, whereas the old group selection approach looks at the evolution of group characters”.  VS’s own words make him sound like a disciple of Wynne-Edwards, which would be unfortunate since Wynne-Edwards was decisively crushed by George Williams in the 1960s.  But even if he’s just poorly recapitulating Wilson’s models, VS is still wrong on the evolution of altruism.  There are a number of possible explanations for altruism, including inclusive fitness, but I don’t want to get into a long conversation on how altruism might have evolved because I would have research and then write an inconveniently long book to do so.

Having said that, Coyne’s use of “cheating” (even in quotations) is a little unfortunate, because it overlaps with the literature on Prisoner’s Dilemma  and cooperation.  Cooperation and altruism are not the same concept (again, see West et al. for a good breakdown of the different concepts, or any text on social evolution);  altruism might be a subset of cooperation, depending on how you define the terms, but usually altruism comes at a cost to the altruist while cooperators do not necessarily pay a cost to cooperate.  “Cheating detectors” is more appropriate for a conversation about cooperation than altruism  (see also Figure 2 of this paper), which makes the rest of VS’s argument difficult to respond to.  I think that Coyne is using ‘cheating’ to refer to individuals who receive the benefit of altruistic acts without paying the price of altruism, but that’s not the same as cheating in models of cooperation.  (Honestly, ‘cheating’ isn’t a great word on a lot of grounds, including confusion with other areas such as signalling and an implication of conscious intent where none is necessary).

Returning to the posts that started this digression:  my honest belief is that this group selection debate should have been over years ago, but I will still support Wilson’s right to continue trying to make his case.  If he’s going to attack people like Dawkins and Coyne, though, he’d better learn to be prepared for them to hit back.  And though it’s unlikely that either of them will ever read this post, I’d like to tell them that they’re not alone.

P.S. Can I take this opportunity to point out a further example of Wilson claiming that people agree with him when they don’t?  If you read the end of Wilson’s second piece, he says:

For readers who are up for a challenge and want to learn more about the theoretical basis and empirical evidence for group selection from someone other than myself, I recommend Steven A. Frank’s “Natural Selection. III. Selection vs. Transmission and Levels of Selection (Journal of Evolutionary Biology, 2011). For Frank, it goes without saying that natural selection is a multilevel process and that the group level is often a significant evolutionary force.

I’ve actually read that paper.  In it, Frank once again points out that kin selection and group selection are the same thing:

The equivalence of r and Hamilton’s formal theory of kin selection establishes the exact equivalence of multilevel group selection and kin selection.

And then, after a long analysis, he compares the usage of the two methods in a section entitled (tellingly): Reasons to favour kin selection over group selection.  It contains exactly what the title says.  If you can get it and you like technical discussions of evolutionary biology, I urge you to read the paper yourself.  If you don’t, then just do me a favour and don’t accept Wilson’s claims about this paper at face value.


David Sloan Wilson. A theory of group selection. Proceedings of the National Academy of Sciences, 72 (1):143–146, 1975.

S. A. West, A. S. Griffin, and A. Gardner. Social semantics: altruism, cooperation, mutalism, strong reciprocity and group selection. Journal of Evolutionary Biology, 20(2): 415–432, 2007.

Is it the 1960s again?

Ritual Sacrifice of the Gummulate Tribe!

Ritual Sacrifice of the Gummulate Tribe! by Grizdave, used under a CC license


Found in a textbook today ([1], p. 14-15), immediately following a discussion of Ebola and Lassa fever infections in humans:

While having the death of a host individual occur as the product of an encounter with a pathogen may seem like a dire outcome, this outcome represents a mechanism of defence operating at the leve l of the host population.  If a particular infectious agent is something against which members of the host population could not easily defend themselves, then it may be better to have that particular host individual die (and die very quickly!) to reduce the possible spread of the contagion to other members of the population.

In other words, if it looks like you’ve been infected by something nasty, you sacrifice yourself to stop its spread for the good of the other members of your population.

Look, I’ll be the first to admit that I hold a dim view of multi-level selection, but I’d be really surprised if anyone in the MLS camp were to make an argument as simple-minded as this.  Virulence is a complex topic, certainly, but the above paragraph could have been lifted from a previously-unknown book by Wynne-Edwards in the 1960s and no one would know the difference.  How is it that people are still getting away with stuff like this forty years after it was first shredded by the likes of George Williams and John Maynard Smith?


1. Christon J. Hurst. Defining the ecology of viruses. In Christon J. Hurst, editor, Studies in viral ecology, volume 1, chapter 1, pages 3–40. John Wiley and Sons, Inc., 2011.

What is an animal’s “choice”?

Image by loryresearchgroup

In behavioural ecology, we face a number of limitations in trying to ferret out the relationship between behaviour and evolutionary forces.  These range from the philosophical and theoretical (e.g. what makes a behaviour adaptive or an adaptation?) to the mundane and methodological (is that experimental set up really measuring aggressive behaviour?), and solving these problems is one of the most pressing tasks facing a behavioural ecologist attempting to make useful statements about a behaviour’s evolution.  However, while some of these issues are recurrent and obvious, others are more subtle and can sometimes slip under the radar.  One such problem is the topic of a recent paper by Véronique Martel and Guy Bovin, published recently in the Journal of Insect Behaviour and entitled “Do choice tests really test choice?”  (DOI: 10.1007/s10905-011-9257-9).

The thrust of their argument is that there is a difference between “apparent choice”, and “true choice”, which is driven largely by the fact that we can’t ask animals what they would have done under different circumstances.  As Martel and Bovin point out, animals may make one choice when presented with a particular set of stimuli, or resources as they call it (which may mimic natural conditions!), but express a different preference when presented with a larger set of resources, or when the conditions of the choice are changed.  They distinguish three characteristics of a true choice, only one of which is met by an apparent choice:

  1. The choice must be non-random, i.e. that individuals must choose one resource more often than the others;  testing only this criteria means that researchers are measuring apparent choice, while this is a necessary but not sufficient criteria for true choice.  (I would add to this that the choice probability should be fairly stable if the animal is made to choose under exactly the same conditions).
  2. The choice should be the same even in the “absence of a differential response by the resource” (p. 332). The authors state this to avoid situations in which the resource (e.g. a potential mate) is manipulating the choice of the focal animal, a problem which reminds me very much of the literature on animal signalling.
  3. It should be demonstrated that every resource is perceived, to avoid issues of sensory bias and the like.  It strikes me that this criterion will be hard to meet;  for example, if while testing mate choice the researcher tries to demonstrate a lack of bias by showing responses by the focal individual to each of the potential mates in isolation, how does that prove that one or more of the potential mates aren’t being ignored when the focal individual is given the choice between all of them?
As the authors state, meeting criterion 1 is sufficient for an apparent choice, but 2 and 3 are required for a true choice.  They spend the bulk of the rest of the paper giving examples of both apparent and true choice and elaborating the differences between the two.  It should be noted that they are not claiming that one type of methodology is “better” than the other;  in fact, they take pains to point out the pros and cons of both.  Here’s an example:

The importance of distinguishing between apparent and true choices depends on the objective of a study. If the objective is to establish which resources will be exploited under natural conditions, then the apparent choice is appropriate. If the experimenter wants to know which female will be mated by a male in a natural situation, then the results of this test (the apparent choice) will provide the answer. However, if the objective of the experiment is to establish the mechanisms of this choice, then it becomes important to look more closely at the results. If a male does not perceive a mated female as a resource because she does not produce sex pheromone, the male is thus inseminating virgin females as they are the only resource perceived. In this case, an apparent choice (the virgin female) is expressed, but this choice is the result of the non-perception of the mated female, which prevents this apparent choice from being a true choice. Measuring an apparent rather than a true choice does not remove the relevance of the test, but only modifies its interpretation. Consequently, it is important for the experimenter to state a clear question before identifying the adequate experimental setup to use.

I think that it’s important to mention here that the ideas expressed in this paper aren’t terribly groundbreaking;  a number of people ranging from economics to psychology to behavioural ecology have, at one time or another, made largely the same argument or a variation thereof (one example of a related problem is raised by a really smart guy, Jeffrey Stevens, in this book chapter here).  In fact, I’m a co-author on a paper currently in press at Behavioural Ecology talking about this issue from the opposite direction, wherein we argue that the mechanisms that underlie behaviour may be constrained and that these constraints need to be taken into account when assessing the evolution of behavioural outcomes[1].  I even made an argument very much like the one in this paper during my Ph.D. synthesis exam!

Having said that, I like the paper for its laser-like focus on raising awareness about a very specific part of animal behaviour and cognition that can seriously undercut the conclusions drawn from experimental or field work if the appropriate test isn’t matched to the hypothesis the researcher wishes to explore.  I suspect that their definition of apparent and true choices is incomplete and leaves out issues that will be hashed out in future papers, but if the journey of a thousand steps has to start somewhere, it’s not a terrible first stride.
[1]. I’ll write more about this here when the paper is published.

Got questions about inclusive fitness?

Over at his blog, Andrew Gelman briefly mentions the recent profile of E. O. Wilson in the Atlantic, and along the way mentions the dustup over inclusive fitness that I may have mentioned here before  (did I? It’s hard to remember).   At the end, he makes a throw-away comment which drove me nuts:

The article also discusses Wilson’s recent crusade against selfish-gene-style simplifications of human and animal nature. I’m with Wilson 100% on this one. “Two brothers or eight cousins” is a cute line but it doesn’t seem to come close to describing how species or societies work, and it’s always seemed a bit silly to me when people try to loop everything back to a selfish-gene story.

I’ve been trying to think of a similarly aggravating comment to make about statistics in return;  maybe “lies, damned lies, and statistics”?  “You can prove anything with statistics”?  “Bayesian statistics suck because I don’t understand where priors come from?”  It bugged me enough that I left this comment:

It doesn’t seem like you know much about inclusive fitness, a theory has been massively successful in evolutionary biology. Despite the odd and unsupported comments made by Nowak et al., it stands firm as a well-supported and useful body of theory. Here’s a link to the letter published in response to Nowak et al.’s original article, signed by 137 authors including most of the field’s brightest minds:

The appeal to authority doesn’t mean that they’re right, of course, but extraordinary claims require extraordinary evidence; Nowak et al. have done nothing but ignore the entire published literature on inclusive fitness spanning decades and comprised of hundreds if not thousands of studies, while proposing a mathematical model that adds nothing to our understanding beyond what current theory already provides.

I respect your work on statistics, have always enjoyed reading your blog, and your book (BDA) is sitting on my shelf right now, but your offhand comment above is uninformed and very aggravating; I’d like to deal with that aggravation by offering to assist you in understanding one of the most powerful explanatory mechanisms in evolutionary biology. The letter above provides a succinct summary of the evidence that Nowak et al. ignore, but it might be a bit much for a non-technical audience; I haven’t published directly in this field, but I do work in evolutionary biology and I should be able to answer any specific questions you may have if you would like to pose them. If I can’t answer them myself, I will find people who can.

I’m not going to go into a full blown recapitulation of inclusive fitness theory and then defend it, because I’d have to write several inconveniently long books to do so.  But since I made the offer over there, I’ll make it here too for any interested readers:  if you have questions burning you up about this whole “inclusive fitness” thing, ask them here in the comments and I will do my best to answer them for you.  And if I don’t know what the answer is, I’ll find it.  No question is too small, though I make no promises on how long or short my answers will be!

I’ll leave off with a quotation from a fantastic book by Andrew Bourke that I’m reading right now, Principles of Social Evolution:

Like any large and active field of investigation, the theoretical study of social evolution is not free from disagreements and unresolved issues (e.g. Taylor and Nowak, 2007; West et al. 2007a).  Paradoxically, while the potential richness of inclusive fitness theory as a general theory of social evolution is still underappreciated, the theory is sometimes perceived as an entrenched orthodoxy. A tendency therefore exists for iconoclastically-minded theoreticians to derive models of cooperation in novel ways and then announce them to be fundamental additions to existing theory (e.g. Killingback et al. 2006; Nowak 2006; Ohtsuki et al. 2006; Traulsen and Nowak 2006).  It is healthy for orthodoxies to be continually challenged by new theories and new data.  However, to date, these models have fallen short of true novelty, as other authors have shown that their results are capable of being derived from inclusive fitness theory (e.g. Grafen 2007a, 2007b; Lehmann et al. 2007a, 2007b; West et al. 2007a).  Indeed, inclusive fitness theory has a long history of successfully assimilating apparent challenges and alternatives (Grafen 1974; Queller 1992; Lehmann and Keller 2006a).  This is not surprising when one considers its deep foundations in the theory of natural selection.  Although it is premature to declare a consensus, a substantial body of opinion therefore holds that claims of fundamental extensions to inclusive fitness theory will have to be radically innovative, as well as robust, to be accepted as such (e.g. Lehmann and Keller 2006a; West et al. 2007a).  For all these reasons, Hamilton’s (1964) inclusive fitness theory will underpin the conceptual reasoning employed throughout this book (pp. 22-23).