Previously, Daniel Streicker and colleagues argued that vampire bat control methods (targeted poisoning) might actually increase rabies rates in vampire bats. I wrote about that here. The team has since published a new model to examine hypotheses regarding why culling vampire bats does not reduce, and worse may even increase, rabies rates in vampire bats. Here’s the article and a press release.
Surprisingly, most of the vampire bats that are exposed to rabies develop resistance. This doesn’t mean that they are lifelong carriers, but rather that they have fought the infection and have been, in effect, immunized. Previous lab studies have found that most of the bats (50 to 90%) exposed to the rabies virus in a lab setting will die, but the authors estimate that only 10% of wild bats bitten by rabid conspecific actually develop a lethal infection. From an evolutionary standpoint, this outcome probably helps the virus from going extinct by wiping out a whole bat colony before the virus can be transmitted. From the virus point of view, it has to get into from one bat to another bats it kills the host, and it has to get from one colony to another. Therefore, the maintenance of the rabies virus over time at high levels relies heavily on dispersal of bats between roosting sites. This is key to why killing as many vampire bats as possible at a site doesn’t effectively get rid of rabies.
But why might culling vampire bats actually lead to higher rates of rabies? One explanation was that the poisoning (which is spread by social grooming) disproportionately targeted adults more often than young, and the adults had developed more resistance than younger bats. I became dubious about whether this made any sense. The authors explicitly based this explanation on the assumption that juveniles are less likely to groom adults, and thus less likely to expose themselves to poison-treated adults. However, in contrast to this claim, juveniles and subadults lick the fur of adults more than adults lick each other. In a roost, young vampire bats should therefore be exposed to vampiricide more, not less, which removes a key assumption for this “selective adult culling hypothesis”. I suggested that either a different mechanism explains the negative relationship between culling and rabies, or that this correlation was spurious.
But there’s another explanation that makes more sense to me. Male bats guard roosts like territories to get access to females. If culling removes these male bats, than males from other areas are more likely to move in. Likewise, killing a group of females could open up a roost for new residents. In other words, culling could increase dispersal, which could increase rabies transmissions.
Culling could also increase dispersal if bats are more likely to leave an area after many of their conspecifics have died. Either scenario seems plausible to me.
Overall, the study highlights the complexity of host-pathogen dynamics and makes the important suggestion that killing vampire bats– even using targeted methods such as poison spread by social grooming– is probably not a good way of fighting rabies in Latin America. This reveals why the task of rabies control is so daunting. It’s also good news for me, because having seen these vampire bat control methods, I am not a fan. I would very happy to see them retired.
But I don’t see vampire bat control disappearing completely anytime soon. Even without rabies, vampires would still be considered an agricultural pest. Farmers and ranchers in Latin America still see 20-30 bites on a single cow. They are like wolves and coyotes to a sheep rancher or deer and groundhogs to a vegetable farmer. Except they can fly right over your fences.
This blogpost grows out of a number of recent conversations about “science”– what it is, how to do it, and why. Whenever my research involves truly boring, tedious things (like scoring hours of video footage), my mind starts to wander off to all kinds of such philosophical things.
Y’know, big picture stuff.
(Not that big picture. Not like, why are we spending our short time on the planet earth running from failure and chasing after success when the main thing we treasure in life is to love and be loved and to make the world a better place? Not that. I mean “big picture” compared to my typical, extremely specific topic: why do unrelated female common vampire bats regurgitate into each others’ mouths?. Hope that’s clear. Now onwards.)
Last year I came across the book, Ignorance: How it Drives Science, by neuroscientist Stuart Firestein. According to Firestein, science is about ignorance, not knowledge.
At first glance, this idea seems like pseudo-profundity, like when bad philosophers simply play around with words and their meanings. But I read into it more and I experienced that lovely sensation when, finally, someone clearly expresses some truth that’s been imprisoned vaguely in the back of your mind for so long. To get the central thesis in 20 min, see his TED talk:
Ignorance, when considered as “what we don’t know” is not such a bad thing. Indeed, for most scientists, it’s really a great pleasure to sit around and wonder about all the things that currently make no sense whatsoever. But this is not just a game for working scientists. In today’s world, where the internet and wikipedia is only an arm’s reach away, one can pretty quickly get close to the limits of collective knowledge (at least compared to when I was in middle school and had to pull out the ole Encyclopedia Brittanica and search for that single paragraph). Even if the answer to your question is not easy to find in the peer-reviewed literature (say because it’s behind paywalls), you can get the email address of the world expert, or anyone with the right technical knowledge, and just ask them (and pray for an answer like this). By the way, you should click on that link.
Obviously, a lot of stuff has been figured out over the last few hundred years of scientific investigation. But a curious person also quickly finds that, for some of the questions, nobody knows the answer. For newer fields like biology or the social sciences, some of the basic questions that kids will ask (Why do cats meow? Why do dogs bark?) don’t really have complete, satisfying answers. And a surprising number of the known “facts” (the starting points of many questions) are themselves not true or are based on very bad evidence.
Older fields, like physics and chemistry, are less open to questions and participation by the naive masses (ironically, much to the envy of the rest of academia) because what is known in physics is so deep, rich, and vast, and the active research questions are so technical. As a college freshman, I went rock climbing with a graduate student in physics. I asked him, “Is a flame just gas that’s glowing?” and which led to “What the heck is plasma?” which led to “Ok, but what is matter, really?” which sparked a 20 min question and answer session. Interestingly, he started answering most of my questions by saying “Well, nobody really knows for sure what that is, but here’s what we do know…”. I remember that well because it changed something fundamental about how I think about science. The guy didn’t seem to care or be shocked that I knew absolutely nothing, but he kept saying things like “that’s a really good question.” That’s not what my high school physics teacher ever told me. And that’s maybe how I decided that I liked science afterall.
So with a little effort, almost anyone can find real, legitimate scientific mysteries and enjoy wondering about stuff nobody understands yet. Here are some questions people (mostly young people) asked me at the Great Lakes Bat Festival: “Do vampire bats really like cow blood more than human blood? Do vampire bats make a special sound to say they are hungry? Do they feel bad if they are rejected? Do they get in fights about being rejected?” It’s fun to think about how one would answer these questions. But you have to start by admitting you don’t really know the answer.
I’m no expert on educational psychology, but it’s long been my opinion that one problem with science education is that we don’t teach science students to say “I don’t know.” Science classes often emphasize facts, and this gives the false impression that science is about memorizing lots of these facts. Scientists are people who have collected so many facts that they have eventually run out and need to do experiments to gather more facts.
But that’s not quite how it works. Instead, as Firestein explains, the more you know, the more questions and less certainty you have. The Dunning-Kruger effect tells us that real competence can weaken self-confidence, and that incompetence leads to overestimation of one’s own competence (so when I don’t know something, I probably don’t even know that I don’t know it). But I believe this cognitive bias is further exacerbated by a tendency for teachers to implicitly punish the “I don’t know” answer, in favor of the “here’s a bunch of related information” answer.
You will recognize what I’m talking about if you have ever been a graduate teaching assistant and spent hours sitting and reading essays on college science exams, where some answers are written by students having no idea of the answer to the question. Sometimes it takes awhile to realize this. It is painful. From the perspective of the test-grader, the easiest thing to grade would be a blank answer. But nobody encourages that. From the perspective of a test-taker, the rational thing to do when you don’t know the answer is to give it your best shot. That is, you make up an answer. Perhaps throw in some words that you remember hearing from the lecture.
For example, take the following science question: What exactly is happening inside a leaf when it becomes red or yellow in the Autumn?
Now, here are 2 imaginary student answers.
Student 1: Leaves are green because they contain chlorophyll, which is a pigment. Chlorophyll is necessary for photosynthesis, which is how a plant generates energy. Chlorophyll is green because it absorbs other wavelengths of light such as red and blue. Red light has a wavelength of 620-750 nm. Chlorophyll is contained within chloroplasts within plants cells. When leaves change color, they are losing their chlorophyll. This is because the plant is losing the leaf during the fall. Plants lose their leaves during the fall to conserve resources. This is important for the plant’s survival and reproduction (its biological fitness) and for the evolution of leaves more generally. Both angiosperms and gymnosperms have leaves. Leaves have multiple types of cells, such as guard cells, which function in photosynthesis. During photosynthesis, plants produce sugars using CO2, water, and sunlight. Photosynthesis consists of both light and dark reactions. [This could go on further but you get the point.]
Student 2: I don’t know. Chlorophyll must somehow be lost from the leaf. Maybe yellow and red pigments have been there already and were hidden before but then are revealed by the loss of the green, or perhaps the reds and yellows are created within the leaf. Maybe the red and yellow pigments are actually brought in from elsewhere when the leaf is ready to fall? I don’t know if the yellow and red pigments even serve a function. Maybe they are just byproducts.
So… neither student actually knows the answer to the question. But in my opinion, student 2 is thinking more like a scientist, because she knows that she doesn’t know the answer, while it’s not clear if student 1 is just desperately listing facts that seem relevant or if she thinks she has actually explained the answer. The sad thing is that student 1 would probably get more points on an exam, if the grader is skimming for technical and salient words and phrases such as “photosynthesis”, “chlorophyll”, “chloroplasts”, “pigment” or “absorbs wavelengths of light”. Often, the main thing that matters in a science class is what you can recall from the lectures and reading, not whether you are thinking critically or scientifically.
Most of the time, scientists do not ask questions and get answers. They ask questions and get more and better questions. Look up the literature on red and yellow pigments in leaves and that’s what you’ll find: some answers, but mostly, better and more precise questions. Yet we are often training students to regurgitate facts, without ever admitting the central importance of ignorance in science or “better ignorance” or even asking questions of their own. And we rarely teach students to say that they don’t know.
Is this really a problem? I don’t know.
A related problem is the myth and allure of the single driving explanation when describing scientific research, especially in biology. If you want to make a good story out of research, it helps to have a clear question and a clear answer. In biology, some questions have clear answers, but the most interesting ones actually have a staggering number of correct explanations, which are all confusingly entangled. Take my question: Why do common vampire bats regurgitate food to non-relatives?
Is it because they usually regurgitate food to relatives and offspring? Is it because feeding non-relatives increases their chances of receiving a food donation later? Or is it because their blood diet and metabolism make them so susceptible to starvation? Is it to honestly signal their ability and intention to help, or perhaps to manipulate other bats? Or is it because they are vampire bats and all 3 species of vampire bat share food with non-relatives? Or is it because vampire bat stomachs can hold so much blood, and they have more extra to give the more they have? In other words, is it simply because of diminishing returns? Is it because vampire bats have special stomachs that facilitate regurgitation, or because blood can’t be easily carried back to young like a prey item? Is it because each vampire bat is more likely to help another bat when any individual helps them regardless of whom?
My answers would be yes, probably, probably, probably, probably, yes, yes, yes, probably yes, and maybe.
It sometimes seems like no question in biology has a single, simple explanation. In a nutshell, biology is complex. (To a biologist, even a nutshell is very complex. I just yesterday listened to an hour-long talk by visiting researcher Dr. Amy Litt on the evolution of the molecular mechanisms underlying the development of dry fruit walls, like nutshells).
So how do we deal with the confusing chaos that every question in biology has so many multiple correct and entangled answers? How can we know when two questions are alternatives rather than complements?
In 1961, Ernst Mayr clarified our thinking in biology in an essay about cause and effect in biology. He popularized the clear distinction between two very different kinds of questions and their corresponding answers. He labeled these, proximate and ultimate. Proximate explanations are answers to mechanistic “how” questions. Like, how does a bat produce sounds that are ultrasonic? Ultimate explanations are evolutionary “why” questions. Why does a bat make calls that are ultrasonic? Hence, proximate explanations and ultimate explanations can never be alternative hypotheses.
In discussing animal behavior, Niko Tinbergen later split these 2 categories into 4 levels of explanation. All organismal biologists know this framework, and this was the first lesson I learned in Intro to Animal Behavior as an undergraduate. Proximate causes include both developmental answers (how does the behavior emerge during the animal’s lifetime?) and mechanistic answers (how does it actually work in real time?). Ultimate causes can relate to phylogeny (when did the behavior first evolve in evolutionary time? and where in the evolutionary tree?). Or they can relate to function (what is the evolutionary advantage of performing the behavior?).
But it doesn’t stop there. Questions at the single level of evolutionary function, for example, can relate to its origin, why the trait first evolved, or alternatively, function can ask what maintains it now. These are also clearly different questions, not competing hypotheses.
Even when considering the more specific question, “what is currently maintaining an evolved trait X?” — one has to consider that there might be several selective pressures acting across different species or situations, or perhaps in all situations simultaneously, perhaps even interactively, such that the presence of one factor determines the importance of the others. In a statistical model, there can be the interesting 2-way interaction (e.g., the ability of X to predict A depends itself on factor Y), the slightly yucky 3-way interaction (e.g., the ability of X to predict A depends on Y to some variable degree based on Z), and the dreadful 4-way interaction (e.g., the ability of X to predict A depends on Y to some degree based on Z…oh, and forgot to mention– that whole thing I just said is true to some degree based on factor Q. Got that?). There are even 5-way interactions and beyond, but to hell with trying to understand those.
To make matters even more complex, proximate mechanisms are not isolated from ultimate mechanisms. Indeed, they often help determine the dynamics of selection that give traits their function. Proximate explanations (mechanisms and development) also put constraints on the directions in which evolution can possibly go (and hence what kinds of ultimate explanations are possible). This leads to so-called reciprocal causation, where proximate mechanisms help drive ultimate ones.
So attempts to cleave a clear framework in biology are soon muddled by trying to interweave more and more reality, and hence more complexity, and hence more potential confusion. Below is a recent attempt to illustrate cause and effect in biology in an easily grasp-able framework. The authors were arguing that the red arrows were not previously recognized enough by previous generations of biologists (whose blue-only frameworks were too simple):
See, we added some new arrows, and it’s still simple, right?
The practical solution to complexity is reductionism. I know that reductionism is normally used as a dirty word. But reductionism to me is actually quite beautiful and under-appreciated in how it allows us to move beyond utter stupefying awe when looking upon something that is holistically complex. By reductionism, I mean breaking big concepts down into components in a hierarchy of levels, which allows each level to be understood in terms of black boxes, which themselves are reducible to other black boxes, and so on. The complex interactions between parts at one level or even different levels can give rise to the emergent properties that seem to just magically appear at the next higher level.
The whole of science is organized in this pleasant way. A community ecologists can tell you about populations of different bats interacting, a population biologist can tell you what a population of vampire bats is doing, and an organismal biologist can tell you something about what an individual vampire bat is doing, and a neuroscientist can tell you what its brain is doing, and a cell biologist can tell you what the neuron is doing, and a biochemist can tell you what the cell membrane is doing, and a chemist can tell you what the molecules are doing, and a physicist can maybe tell you what the carbon atom is doing. And a particle physicist can tell you what the heck a Higgs boson is, because apparently they found one, whatever it is, and how that gives particles mass…or something [?]. My point is that somebody out there understands each part, even though nobody understands the whole big thing. So science is collectively wiser than any one scientist.
In this way, science is both a form and product of collective intelligence. Matt Ridley gave a pretty insightful talk on this principle as applied to cultural and technological innovation, which he illustrated so well by the simple observation that no single person knows how to make a pencil:
I just returned from a 4-day NIMBioS workshop on computational analysis of animal vocal sequences. The workshop was led and organized by NIMBios PostDoc Fellow Arik Kershenbaum, prolific animal behaviorist Dan Blumstein, and bioacoustics-specialist and computer scientist Marie Roch, and included about 40 other researchers from diverse fields such as cognitive science, human speech processing, animal communication, and even philosophy. One goal of the workshop was to write an overview paper on the opportunities and challenges in studying the sequential structure of animal vocalizations in a comparative context.
Studying animal communication is both fascinating and difficult because we humans use language, which is a unique form of communication that greatly biases how we think about communication in other systems. In animal communication research, there are predictable controversies about topics such as information, meaning, and syntax. To what extent, do animal signals have “meaning”? To what extent are concepts from human language, such as phonemes, a suitable framework for studying say bird song, or the sequences of sounds produced by dolphins and bats? How analogous are various vocal sequences to human language? Similar controversies surround the evolution of language itself.
Researchers have described many situations where animals encode information in their calls which have meaning for recipients. For example, dolphins recognize each other using certain syllables in their calls that are highly stereotyped and individually distinct, and also address other individuals using learned labels. Similar vocal labeling behaviors are observed in social birds. Various primates and birds also use referential alarm calls that convey the particular type of predator that is approaching. But one of the main questions here is exactly how information is encoded: Is the information encoded in the shape of how the syllable changes pitch? Or in the harmonic structure? Or is information encoded by the order of the syllables in the sequence? This last question was the major topic of the workshop.
The most obvious and well-studied example of complex vocal sequences is bird song. But there is an increasing appreciation of sequences with different kinds of functions. Some of the best work is being done by lab of Klaus Zuberbuehler. For example, in the calls of putty-nosed monkeys, his group found that the order of the calls is what matters, rather than the calls themselves. They produce two kinds of alarm calls. Call them A and B. Series of As (AAAAA) means leopard, whereas BBBBB conveys crowned eagle (and As can be tagged unto the end). In contrast, if a monkey makes a call where As are followed by Bs (AAAABBB), this reliably means the group will be moving forwards. An even more complex system is used by Campbell’s monkeys. In this study, the research team ”found stereotyped sequences that were strongly associated with cohesion and travel, falling trees, neighboring groups, nonpredatory animals, unspecific predatory threat, and specific predator classes.” The group has described the alarm call systems of several primates species around the world.
Similarly interesting sequences have been found in social mongooses by Marta Manser. For example, Banded mongooses close calls combine two syllables; the first is stereotyped for each individual, while the second is graded, more variable, and can be linked to the current behavior such as foraging or moving. Predictable orders of syllables, often called “syntax” in animal communication has also been found in bats, first described by Jagmeet Kanwal and later linked to song and social behavior by Kisi Bohn and Mirjam Knoernschild.
I’m not even close to looking for things like syllable order in vampire bats. All I really know at this point is that vampire bats can use calls to discriminate and locate individuals vocally. Most of the calls are single syllables, but some are multi-syllabic, and I’m not sure if the syllables can be classified into discrete types (or what’s the optimal way to do that using automated techniques). Unsurprisingly, I have found individual variation in single syllables and found unambiguous perception of those differences in the double-note contact calls of white-winged vampire bats. But whereas white-winged vampire bats make fairly stereotypical double-note calls when isolated, common vampires in the same situation seem to make all kinds of calls that vary from very simple to complex.
Overall, the variation in calls is very large, even for a single individual isolated in a single situation. So when restricting my analysis to the most common syllable “type” (simple downward frequency-modulated sweeps) in a single group of bats, I’m only able to explain a pretty small proportion of the call variation using individual identity. Based on preliminary analyses, factors like group membership and kinship seem to weakly correlate with vocal similarity between any two individuals, but there is still too much unexplained variation, because I’m probably pooling syllables that are actually of different types (even though the context is the same).
Right now, I would like to use some kind of cluster analysis to see if isolated vampires are actually producing types (either within or between individuals) that we can categorize. We could then see how variables like age, identity, and familiarity predict structure of each call type separately. But since my main focus at the moment has been on testing the effects of oxytocin administration on food sharing, I’m trying to find collaborators to help me with the call analysis work, especially people who have more experience on automated methods of call classification.
More and more science is becoming freely available to the public, or open access (OA). I love the movement towards OA, mainly because I like to be able to find and read papers online, even when I’m not on campus. I like being able to use the internet as my interconnected library of science articles, rather than having to store them as isolated PDFs on a hard drive.
OA is clearly a good thing for readers, but there are dangers as well. The first problem is that, like all new and useful media technologies, scammers quickly find ways to exploit it. The first purchases by mail quickly led to new kinds of business fraud, credit cards led to identity theft, email led to all variety of strange messages from wealthy Nigerian investors, informational websites quickly led to ad-filled pseudo-informational sites. The authority of scientific organizations can also be hijacked. The Intergovernmental Panel on Climate Change (IPCC) led to the similarly-sounding Nongovernmental International Panel on Climate Change (NIPCC; i.e. the scientific source that Fox News can cite for their information on climate change).
Similarly, the rise of open access publishing (sparked mostly by the Public Library of Science, PLoS) has led to all kinds of copycat predatory OA journals that charge authors large amounts of money to publish crap science. These unvetted science articles might be read by people who don’t know what journals are legit vs fake.
There’s also a second more subtle problem. Even for legitimate publishers that are not trying to scam anyone, the OA model changes the incentives for publishing and rejecting. If OA journals make more money by publishing more papers, then they have every incentive to accept papers rather than reject them. So they have every reason to have lower standards and publish flawed work.
Science Magazine performed a “sting operation” to reveal a world of corruption and predatory OA publishing. A science writer created a sham paper about a new cancer drug (extracted from lichen) littered with scientific, statistical, and even ethical problems. Then they sent it to about 300 open-access online journals. Many of these targets were already listed on published lists of predatory journals. The project verified what everyone already knew: there are a lot of scammers and crappy peer-review systems out there in the open access publishing world. Of the targeted journals, 157 took the bait and published the crap article, with 60% not even doing peer review (these are the obvious scammers). Of the 106 journals that did conduct peer review, 70% still accepted the paper (these are a mix of the truly dishonest and the self-deceived).
Take home message: you shouldn’t believe everything you read on the internet, even if it comes from a journal with a scientificky-sounding name.
But here’s the problem I see. Let’s talk about incentives. Traditional publishers are losing a lot of money to open-access in all its forms, not to mention it just makes them look bad for charging readers money. The open access movement is to traditional publishers, as climate change activism is to gas and oil companies. At best, it’s something the industry has to adapt to; at worst, it’s a threat. Unsurprisingly then, traditional publishing magazines like Nature and Science usually seem to discuss open access as something potentially full of peril, both to readers and scientists. The message is often “Watch out readers, OA journals publish bad science” and “Watch out scientists, OA journals will take your money and exploit you.” These are both valid concerns, but the issue of predatory science journals is not the same as the issue of open access, and it’s dishonest to draw a simple connection between them. There’s a lot of bait-and-switch going on here: “predatory” becomes “open access”.
Unfortunately, some readers will get the impression that there’s something unreliable or corrupt about the notion of *open-access*. Here are some example headlines:
A “sting” operation found that open-access journals will accept anything — for a price [Salon]
Open-Access Journals Hit By Journalist’s Sting [NPR]
The Wild West world of open-access journals [LA Times]
Hundreds of open access journals accept fake science paper [The Guardian]
First of all, “open access” does not = crappy scam online journals. If I take any paper and post it on my website so that anyone can read it, I’ve just made it “open access”. Some of the best journals like PLoS Biology and PLoS Genetics are open-access journals. PLoS ONE (the largest OA journal in the world by a large margin) pointed out both the scientific and ethical issues in the hoax paper and rejected it in under 2 weeks (that’s fast).
Second, I think it’s a bit hypocritical for mainstream journalists to talk about the lack of rigorous peer-review and reliability of science journals. Yes, predatory journals are absolutely terrible. Why? Because at worst they have the same terrible standards of accuracy as the mainstream media. They’ll publish almost anything without peer review, regardless of the quality of the evidence, just because someone out there reports it. But yeah, that’s another issue.
The most glaring problem is that this “experiment” did not compare open access with non-OA journals. It only targeted OA journals, so it cannot possibly show any effect of being open-access on peer-review quality. We may all agree that OA publishing is where the problem is probably worst, but this study doesn’t even show that. What would have happened if the sham paper was sent to a bunch of small journals that were not OA? What would be the acceptance rate? My guess is that it would be much much lower but still shocking in how many times it would get through peer-review. I once accidentally took a large knife in my knapsack on 2 planes through 3 international airports (post 9-11). No screening procedure is perfect.
Peer-review is a system that ensures that at least 2 other people in your field think your paper is not fundamentally flawed. It doesn’t ensure quality; it just helps. As a reviewer, I’ve seen the other reviewer completely miss giant flaws in a paper, and I’ve also seen the other reviewer catch obvious flaws that I didn’t notice (shame on me). You also read papers that make you think, “How did this get through peer review?”
Ultimately, as a consumer of science, you can’t keep outsourcing skepticism and judgement. If you always have others do the assessments, then who will assess those assessors when there’s a reason for them to be biased? Sometimes you just have to look at the evidence directly, and make up your own mind without resorting to the authority of the journal brand or website or author. That’s why all science papers have methods sections. There’s only one real solution: every individual should develop a healthy skepticism and an intellectual self-defense, rather than a reliance on authority– scientific or otherwise. Crap science published in some sketchy journal should not fool anyone. And if it does, why should “open access” receive any of the blame?
If someone makes a claim, like say, cell phones cause brain tumors (cite: Smith 2013 Journal of Brain Tumors), I personally think the most important service of publishing is that I can go and read that Smith 2013 paper myself to see if I actually agree with the evidence. That’s what open access allows and facilitates.
The problem of bad information does not stem from open access. Flawed science gets published all the time, even when good peer-review is in place, and even in prestigious journals such as Nature and Science. The fact that there’s more bullshit in open-access journals is predictable given the incentive structure. But there are many other examples of poor incentive structures in publishing. For instance, Nature and Science benefit when they publish overly-ambitious or very controversial ideas, because these will attract more citations (even if the majority are citing the paper to say it’s wrong); the effect for the journal is a higher impact factor. Another problem that nobody wants to publish negative results. Another is that scientists can be rewarded by making their papers so technical and hard to read, that peer-review is difficult or only possible by a small group of close associates. Yet another problem is that drug companies pay scientists to publish results they like (e.g. 21% of medical papers published in 6 leading medical journals in 2008 were likely written by honorary authors or ghost writers).
To summarize the larger problem– there’s just a lot of bullshit. In science. In academia. On the internet. In journalism. In blogposts, like this one. Maybe in this very paragraph. Indeed, there are entire fields or subfields of academia that are built entirely out of bullshit. That’s what the Sokal Affair attempted to demonstrated with their original sting operation.
An important difference between a paper published in some small subpar open access journal and some small subpar traditional journal, is that open access allows anyone to read the paper and decide for themselves. Predatory journals will eventually gain bad reputations and won’t do well. That’s why all of them are tiny and have names you’ve never heard of. But there are also new, good progressive OA journals that are just as honest and reliable as any traditional journal. And many new OA journals are doing cool and interesting things. One example is PLoS ONE and another is PeerJ. These are not the end of scientific integrity, I personally think they are the future.
I do think this study is terrific because it will spark a lively discussion. All scientists need to discuss this issue more, and also be more aware of predatory science publishing. But I hope that people stop talking about this finding as if it says something directly about the “dangers” of open access.
People talk about the dangers of the internet, blogging, and social media. Ok, great, interesting. But when people who work in publishing (and make money by charging access to science papers) want to talk about the danger of… open access to scientific information, you have to wonder…
Recently I was talking to someone about vampire bats and described them as “super-bats” as in, super-strong, super-fast, super-smart. In this blogpost, I’m going to give just one example of this– a vampire bat’s extraordinary ability to feed on difficult and dangerous prey. Thanks to Ed Hurme for suggesting I write a blogpost about this after a brief discussion we had earlier.
What kinds of animals will a vampire bat feed on? Vampire bats routinely feed on livestock such as cows, horses, goats, pigs, and chicken. And there are many reports of vampires parasitizing more interesting hosts such as humans, sea lions, penguins, tapirs, peccaries, or even raptors. But just how exotic can the prey of vampire bats be?
In the 1970s, researchers placed a surprising variety of animals in large cages with vampire bats to find out. Many of these observations have not been published in papers but they appear in the out-of-print book, Natural History of Vampire Bats (1988) edited by Arthur Greenhall and Uw Schmidt. Greenhall explains that common vampire bats were able to feed on an armadillo, porcupine, cave rat, vole, cottontail rabbit, (larger) fruit-eating bat, crocodile, turtle, ground iguana, boa constrictor, coral snake, and even a tropical rattlesnake.
Several of the encounters in this book sound like a ridiculous (and somewhat sadistic) ”vampire vs [species X] cage match” that you might expect to see on some pseudo-educational TV show or youtube. For example, consider Greenhall’s description of a bat placed with a Neotoma sp. cave rat (which is much larger than a vampire bat) and is sometimes found in the same caves:
The rat stoutly defended itself and on one occasion rat and bat engaged in a fist fight, both animals rising on their hindlegs and exchanging blows (Figure 7). Joint attack by vampires against one rat presented an uneven fight, and the rat was bitten on its tail, hindleg, nose, and ear, and finally killed.
In a captive encounter with a slender vine snake, Leptophis sp, Greenhall explains that “the bat dodged several more strikes until the snake stopped, seemingly tired. The bat bit its back and fled...” One of the most intriguing accounts describes a vampire bat facing a snake that would simply eat most bats:
A rat snake, Elaphe sp., a bat predator often found near caves with Desmodus, repeatedly struck at the vampire which skillfully avoided the strikes (Figure 8). After some maneuvering, the bat positioned itself facing the snake’s head, nose to nose. The vampire bat repeatedly licked the rostral scale until wound was made and blood flowed… The snake remained motionless, but flicking its tongue.
These images are stills from video recordings. I would be very interested to see that footage someday.
A few other updates:
- Our work on food sharing was discussed in a “quick guide” on reciprocal altruism in Current Biology.
- I’m giving a talk this Saturday Sept 28 at the Great Lakes Bat Festival in Southfield Michigan.
- By placing guano-stained rags in different locations, I found that we could influence where a lone vampire bat chooses to roost (they prefer roosts tainted with guano). This makes me wonder if the pungent smell of vampire guano helps the bats find roosts.
- I will soon know if my bats have been responding to the intranasal oxytocin I’ve been giving them.
Some interesting recent and relevant papers:
- “Social amoeba farmers carry defensive symbionts to protect and privatize their crops” Nature Communications [so cool it's hilarious]
- “Wolf Howling Is Mediated by Relationship Quality Rather Than Underlying Emotional Stress” in Current Biology
- “Female Bechstein’s Bats Adjust Their Group Decisions about Communal Roosts to the Level of Conflict of Interests” in Current Biology [I really like this stuff, but I'm still not sure what the term "group decision" means in a group with unstable membership.]
- “Reciprocity explains food sharing in humans and other primates independent of kin selection and tolerated scrounging: a phylogenetic meta-analysis” in Proceedings B [ In my opinion, this author thinks clearly about reciprocity (as occurring within a long-term social bond rather than as a calculated tit-for-tat strategy that requires planning and self-control to avoid defection).]
- “The excuse principle can maintain cooperation through forgivable defection in the Prisoner’s Dilemma game” in Proceedings B [This result was surprisingly clear. Fantastic system they have here.]
- Finally, I somehow came across this funny gem from an article online entitled ”What vampire bats can tell you about bond yields“
the more the bats cooperate with one another, the less a single bat gains from cooperating. Quick-witted dear readers will see parallels in the bond market. When you lend money (buying a bond, for example), you have to trust the person you lend to. As your level of trust goes up, you accept lower interest rates, because your risk of loss goes down. This is equivalent to the cooperation in a bat colony.
And I thought I related everything to vampire bat cooperation…