It is a widespread misconception that, as we developed the technology to reshape our environment to our preferences, human beings neutralized the power of natural selection. Quite the opposite is true: some of the best-known examples of recent evolutionary change in humans are attributable to technology. People who colonized high-altitude environments were selected for tolerance of low-oxygen conditions in the high Himalayas and Andes; populations that have historically raised cattle for milk evolved the ability to digest milk sugars as adults.
A recent study of population genetics in Native American groups suggests that another example is ripening in the experimental fields just a few blocks away from my office at the University of Minnesota: Corn, or maize, may have exerted natural selection on the human populations that first cultivated it.
One of the biggest dietary changes in the history of Native American humans was the domestication of corn, which provided a staple crop to support settlements across North and South America long before Europeans arrived. However, a staple crop is something of a double-edged sword: it can provide a more predictable food source than hunting and gathering—but if the crop fails, it means famine. It’s been proposed that the 230Cys variant makes people who carry it better at storing food as fat, which might come in handy for ancient farmers who had to weather bad harvests every few years.
Corn on display at the 2011 Minnesota State Fair. (Flickr: jby)
So the new study looks for an association between frequencies of 230Cys and corn-based agriculture in Native populations from Central and South America. The study’s authors—a big international team from universities in Brazil, Argentina, Mexico, Chile, Costa Rica, France, and Great Britain—first show that there’s a strong correlation between the frequency of Cys230 in Native populations and the length of time that domestic corn has been grown by those populations, as determined by the radiocarbon date of maize pollen found in archeological sites. That is, 230Cys is more common in Native populations that have a longer history of growing corn.
The team also used genetic data from the vicinity of Cys230 to estimate the age of the allele, and found that it probably originated between 19,000 and 7,000 years ago—which is to say, all the copies of Cys230 in the population genetic sample are descended from a single mutation that occurred after humans colonized the Americas. The lower age estimate is also pretty close to how long ago native populations are thought to have first begun farming maize.
That data makes a pretty good case for 230Cys having arisen as an adaptation to the diet created by Native American corn-based agriculture. But it’s not the whole story, by a long shot. Although 230Cys is strongly associated with metabolic disease in today’s modern, mostly famine-free, lifestyle, it only explains about four percent of variation in blood cholesterol levels. Moreover, it’s not clear to me that agriculture based on maize should be more prone to famine than agriculture based on wheat or rice—so why didn’t European and Asian populations evolve their own versions of 230Cys? It seems much more probable that there are a lot of other genes involved in determining how human bodies respond to modern-day feasting or prehistoric famine.
And, in fact, a 2010 study of world-wide human population genetics found evidence of selection associated with both climate and with diet type across the genome. That study found genetic markers with strong associations to climate and diet in close proximity to genes connected to blood glucose levels, diabetes risk, cancer risk, and, yes, blood cholesterol levels. The climate and dietary categories examined in that study are very broad, however, so it’s hard to know what, specifically, helped create the natural selection suggested by the observed associations between gene variants and evironments.
Corn and 230Cys may be the most recently described specific case of recent human evolution in response to agricultural technology—but we can expect to find a lot more stories like this one as we dig deeper into human population genetics.◼
Acuña-Alonzo, V., T. Flores-Dorantes, J. K. Kruit, T. Villarreal-Molina, O. Arellano-Campos, T. Hünemeier, A. Moreno-Estrada, M. G. Ortiz-López, H. Villamil-Ramírez, P. León-Mimila, & et al. (2010). A functional ABCA1 gene variant is associated with low HDL-cholesterol levels and shows evidence of positive selection in Native Americans. Human Molecular Genetics, 19, 2877-85 : 10.1093/hmg/ddq173
Hancock, A. M., D. B. Witonsky, E. Ehler, G. Alkorta-Aranburu, C. Beall, A. Gebremedhin, R. Sukernik, G. Utermann, J. Pritchard, & G. Coop (2010). Human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency. Proc. Nat. Acad. Sci. USA., 107, 8924-8930 : 10.1073/pnas.0914625107
Hünemeier, T., C. E. G. Amorim, S. Azevedo, V. Contini, V. Acuña-Alonzo, F. Rothhammer, J.-M. Dugoujon, S. Mazières, R. Barrantes, M. T. Villarreal-Molina, & et al. (2012). Evolutionary responses to a constructed niche: Ancient Mesoamericans as a model of gene-culture coevolution. PLoS ONE, 7 : 10.1371/journal.pone.0038862
The Asian Harlequin ladybug, Harmonia axyridis, eats aphids like they’re Popplers, and it’s been repeatedly introduced into the U.S. and Europe to do exactly that. But since it was first introduced, H. axyridis has spread of its own accord, and displaced native ladybugs. This isn’t just because the Harlequin ladybug eats more aphids, or breeds faster, than the locals; it looks like part of the Harlequin’s success is due to the fact that it eats its native competition.
Although they’re known for eating aphids, most ladybugs are perfectly willing to engage in intraguild predation—that is, to eat other insects that are themselves primarily predators. Including other ladybugs. So a team at Wageningen University in the Netherlands set out to see whether H. axyridis might engage in a different kind of intraguild predation than its native competitors—do the Harlequins preferentially attack ladybugs of different species, and, when they do, are they more likely to win?
The team tested this in what they call a “semi-field” experiment, by creating encounters between ladybug larvae on individual leaves of small potted lime trees. They chose two other ladybug species, Coccinella septempunctata and Adalia bipunctata, for comparison to, and competition with, H. axyridis. Then, on the leaves of small potted lime trees, the researchers set up larval ladybug death matches.
Death matches for science, mind you.
The experiment was, basically, this: put two ladybug larvae on the same leaf, and watch what happens. The team paired up every possible combination of pairs of larvae from the three different ladybug species, so they ended with observations of each species interacting with (1) another member of its own species and (2 and 3) members of each of the other species.
In a majority of these larval ladybug death matches, the paired larvae didn’t actually interact; either they failed to come into contact before the experiment timed out (the researchers gave the larvae 1000 seconds to start rumbling) or one or both larvae jumped off the leaf or crawled back onto the nearest branch. Across all the different possible species pairings, the larve actually interacted in between 23 and 43 percent of the trials.
However, when the larvae did manage to make contact … they also didn’t attack each other that frequently. Out of hundreds of trials, some of the larval pairings only resulted in one or two aggressive interactions. Most of the time the larvae failed to react, or just turned around and departed the leaf. So, okay, “Larval Ladybug Deathmatch” is probably not coming to next year’s reality TV lineup.
However however, out of the small fraction of trials in which the larvae did interact, and did interact aggressively, Harlequin ladybug larvae were clearly the meanest ladybugs on the leaf: when they attacked the larvae of the other species, they went for the ladybug jugular, and ate what they killed a little more than half the time. (The study’s authors use the word “predate” to describe this kind of interaction, a usage for which I do not care.) Harlequin ladybug larvae would sometimes attack members of their own species, but they never ended up eating them.
In comparison, the other two species hardly engaged in any aggression, and the team recorded only two instances of ladybug-on-ladybug predation in which Harlequin larvae weren’t the predators.
So the authors conclude that Harlequin ladybugs successfully invaded Europe and North American, in part, by eating the larvae of species that would otherwise stand in their way. Based on this data set, though, it’s a bit hard for me to believe this could be a major contributor.
Even on the experimental leaves, the larvae either failed to make contact or didn’t interact aggressively most of the time. Then, there’s some reason to think that the larvae don’t come into such close contact on a regular basis when left to their own devices: the research team also tried to set up death matches by placing the larvae on different leaves of the same tree, and then never saw the larvae wander onto the same leaf. So unless ladybug larvae hang out in groups in nature—and maybe they can, if they happen onto the same aphid-ridden tree—Harlequin ladybugs are probably not chowing down on the competition very often.◼
Raak-van den Berg, C. L., H. J. De Lange, & J. C. Van Lenteren (2012). Intraguild predation behaviour of ladybirds in semi-field experiments explains invasion success of Harmonia axyridis. PLoS ONE, 7 : 10.1371/journal.pone.0040681
Ever since Charles Darwin and Alfred Russell Wallace first described the workings of natural selection, one popular way to summarize about selective change has gone something like this: A population of critters is well-adapted to its environment until that environment changes—maybe the critters move to a new climate, maybe the climate changes on them, maybe some new competitors or predators move in. Life gets harder for our critters, until one of them is born … different. That lucky mutant has a never-before-seen trait that lets it cope in the new conditions, and in a few generations, every critter in the population is a descendent of that original mutant.
That narrative isn’t wrong. But it does miss one of the key insights that led to the discovery of natural selection—natural populations are variable.
That population of critters encountering new conditions of life may very well not need to wait around for the lucky mutant before it can begin adapting to new conditions. Mutations happen at random, and continuously—and, particularly if they don’t leave the mutant much less fit, can hang around in a population for generations. And this “standing” variation is raw material waiting for natural selection to act.
High-octane fuel for adaptation
There’s good reason to think that natural selection is more efficient when it has standing variation to work with. Joachim Hermisson and Pleuni Pennings demonstrated this principle rather neatly in a 2005 theory paper, in which they modeled the fate of new genetic mutations that had a weak negative effect when they first appeared in a population, but then became beneficial after the population’s environment changed.
Normally, when a new mutation appears in a population, it’s almost immediately lost to the random effects of genetic drift, even if it confers a benefit. This means that a new mutation needs to be quite strongly favored by selection to have a high probability of “fixing,” or spreading through an entire population.
However, under Hermisson and Pennings’s model, the mutations considered are only those that survive the initial effects of drift. The flip-side of the randomness that can make a weakly beneficial mutation disappear can also help a weakly deleterious mutation spread, achieving an equilibrium between drift, selection, and new mutation events that create new copies of the same variant to replace the ones lost to selection or drift. So, when conditions changed, and the mutation became even weakly beneficial, it was ready to start spreading.
This graph, the key figure from Hermisson and Pennings’s paper, shows the probability that a mutation will “fix,” or spread to dominate the population over the course of several generations, given the power of natural selection (alpha, the term on the horizontal axis). The dotted line tracks the probability of fixation for a brand-new mutation; the solid line tracks probability of fixation for a mutation that existed before selection began to act, and had achieved mutation-selection-drift equilibrium. No matter how strong selection is, the pre-existing mutation is more likely to “fix” than the new mutation—and that difference is most pronounced when selection favoring the mutation is weakest.
In other words, if mutations provide the variation that fuels evolution by natural selection, standing variation is fuel with a substantially higher octane rating.
Harder to spot
But the same features that make adaptation from standing variation so much more efficient also act as a sort of population genetic stealthing. This is because adaptation from standing variation has very different effects on the genetics of an adapting population than the spread of a single new mutation.
The key to this difference is that gene variants, or alleles, aren’t transmitted from one generation to another one at a time. Instead, they come as part of chromosome regions, physically linked to genetic code that may have nothing to do with the function of the focal gene. And population geneticists use that fact to zero in on genetic regions that might have been recently affected by selection.
It’s a little bit like buying LEGO bricks—or, at least, how it used to be when I was still buying a lot of LEGOs, back before you could custom-build your own sets online. Say you want a hundred copies of a particularly special type of LEGO brick, one that’s only available in a single kit. To get those hundred bricks, you need to buy a hundred copies of that one kit. So you end up with a selection of bricks—the ones you wanted, and the ones that came with the ones you wanted—that probably doesn’t have a very wide diversity of brick types.
But suppose you want a hundred copies of a more common LEGO brick, one that’s included in dozens of different kits—kits for pirate ships and castles, race cars and railroads. You might still need to buy a hundred kits, but you can buy many different kinds of kits, and so in addition to the hundred copies of the brick you want, you also have bricks to build anything from a starship to a dragon.
Selection on a single beneficial mutation is like that first LEGO shopping case, where there’s only one kit containing the brick you want. The one lucky mutation exists with only one “genetic background” of other, associated genetic code, and so when the mutation spreads through the population, a chunk of that background code spreads with it. (At least, until recombination can separate the favored mutation from its background; that takes time, sometimes a lot of time.)
Just as purchasing a hundred copies of the same LEGO kit would leave an obvious mark on the makeup of your brick collection, a selective sweep that starts with a single mutation—what’s called a “hard sweep”—results in a region of genetic code with noticeably lower variation across the population, because everyone is carrying the original lucky mutation plus its associated background.
Figure 4 from Linnen et al. (2009), demonstrates the reduced diversity in a gene region associated with fur color in deer mice. Image from Linnen et al. (2009).
In practice, biologists use this principle in two major ways. First, if a biologist has a particular gene in mind that might have recently experienced selection, she can collect DNA sequence data in the vicinity of that gene for many individuals in a popualtion, and see whether it’s less diverse than it ought to be. This is how Catherine Linnen and her collaborators demonstrated that a population of deer mice living on light-colored soils in the Sand Hills of Nebraska had experienced natural selection for lighter color. In a study [PDF] I’ve discussed previously, the team identified a genetic region that was associated with coat color in the mice, then collected sequence data from that region in mice collected from the light-soil population. Compared to the same genetic region in mice from nearby sites with dark soil, the light-soil mice had markedly less variation in the coat-color region.
Alternatively, biologists who don’t know which genes might have been targeted by natural selection can collect sequence data from a whole lot of gene regions—or even “scan” the whole genome—and compare the diversity at each region. Any region that has lower diversity than most of the other sampled regions may have experienced selection recently, and is probably a good candidate for follow-up study.
But selection froms standing variation doesn’t leave such a clear mark on the genome. It’s more like that second LEGO shopping spree, for a brick found in many different kits. If a useful variant is located on many different genetic backgrounds, than selection can make the variant more common in the population without necessarily reducing the diversity of gene regions near the focal variant. This is called a “soft sweep.” Soft sweeps present a problem for those of us who want to find genes that have recently been affected by natural selection—without the loss of diversity, genetic regions that have undergone soft sweeps may not stand out in the genome as a whole.
But the absence of hard sweeps doesn’t mean that soft sweeps are going on all over the place instead. For instance, in an (ongoing) analysis I presented [PDF] at the recent Evolution meetings in Ottawa, I examined patterns of diversity in genetic regions close to genetic markers that are very strongly associated with differing climate conditions in the small but awesome wildflower Medicago truncatula—and I found little evidence of recent hard sweeps. Does that mean all those strongly associated gene variants are strongly associated as a result of adaptation from standing variation? Maybe; but some portion of the associations could also be due to population genetic processes like drift and isolation-by-distance—I’m still thinking about ways to kill the soft sweep hypothesis.
Pennings and Hermisson followed up their original theory paper with a study comparing the power of several different statistical tests to detect soft sweeps, and they found some promising results with an approach based on linkage between genetic variants in the vicinity of a favored variant. More recently, Pennings has approached the question of adaptation from standing variation from a somewhat different angle, by studying selective sweeps in human immunodeficiency virus, HIV. The evolution of HIV after it infects a patient, and as it adapts to antiviral drugs, is quite well understood—to the point that virologists know to expect particular mutations to sweep the viral population within a patient who starts taking a particular drug.
In an analysis recently published in PLoS Computational Biology, Pennings found that the virus’s evolution of drug resistance could be based on standing variation in about 6% of patients on a standard anti-viral drug cocktail—which is to say, about 6% of all patients carry viral populations that are primed to evolve drug resistance the moment therapy begins. (Pennings’s lab website has a good explanation of the clinical implications of this result, with video, even.)
Then, at the Ottawa Evolution meetings, Pennings presented [PDF] an examination of HIV genetic samples taken from multiple patients undergoing antiviral treatment. She identified cases when the virus’s adaptation to the drugs was fueled by standing variation or based on a mutation that occurred after the drug treatment started; one resistance mutation evolved to fixation via a soft sweep in eight out of 23 patients. [Correction, 6 Aug 2012: See Pennings’s comment below for a correction on this point; it’s not known whether this particular soft sweep started from standing variation, or whether it’s simply the case that two different mutations with the same effect managed to sweep the population together.]
If evolutionary biologists want to understand how natural selection helped make the living world we see around us today, it looks like we’re going to have to learn to love soft sweeps. We’re still learning how to differentiate the aftermath of soft sweeps from the results of other, non-selective processes. But fortunately, we live in an era when the genome-scale data that may let us untangle this question are increasingly easy to collect.◼
I started working on this post quite a while before the Ottawa Evolution meetings, when I was pleased to meet Pleuni Pennings for the first time. If there are mistakes in what I’ve written above, they’re my own; but I hope she’ll let me know if I’ve made any!
Flintoft, L. (2011). Human evolution: Sweep model is swept away. Nature Reviews Genetics, 12, 228-9 DOI: 10.1038/nrg2978
Hermisson, J., & Pennings, P.S. (2005). Soft sweeps: Molecular population genetics of adaptation from standing genetic variation. Genetics, 169 (4), 2335-52 DOI: 10.1534/genetics.104.036947
Hernandez, R. D., J. L. Kelley, E. Elyashiv, S. Melton, A. Auton, G. McVean, G. Sella, & M. Przeworski (2011). Classic selective sweeps were rare in recent human evolution. Science, 331, 920-4 DOI: 10.1126/science.1198878
Linnen, C. R., E. P. Kingsley, J. D. Jensen, & H. E. Hoekstra (2009). On the origin and spread of an adaptive allele in deer mice. Science, 325, 1095-8 DOI: 10.1126/science.1175826
Oleksyk, T. K., M. W. Smith, & S. J. O’Brien (2010). Genome-wide scans for footprints of natural selection. Phil. Trans. Royal Soc. B, 365, 185-205 DOI: 10.1098/rstb.2009.0219
Pennings, P.S. (2012). Standing genetic variation and the evolution of drug resistance in HIV. PLoS Computational Biology, 8 : 10.1371/journal.pcbi.1002527
Pennings, P.S., & J. Hermisson (2006). Soft sweeps III: The signature of positive selection from recurrent mutation. PLoS Genetics, 2 DOI: 10.1371/journal.pgen.0020186.eor
Pritchard, J. K., & A. Di Rienzo (2010). Adaptation—not by sweeps alone Nature Reviews Genetics, 11, 665-7 DOI: 10.1038/nrg2880
I mean, I don’t want to be making an ad-hominem argument here, but I tend to think that the point of popular science writing is for the audience to benefit from a writer’s perspective and expert judgement. And Jesse Bering’s judgement is in pretty serious question. (Don’t justtakemywordforit!) He might very well be a great psychologist—that field is beyond my expertise to assess—but it’s pretty clear that Bering’s knowledge of evolution begins and ends with an exceptionally superficial understanding of natural selection, and, more often than not, he rallies that superficial understanding (but not much actual scientific evidence) for the defense of some pretty damn’ regressive ideas.
Plus which, “plunger penis” isn’t exactly news: the paper Bering seems to be citing is from 2003, and Jared Diamond discussed the ways in which the human penis stands out (heh) in comparison to those of other apes in The Third Chimpanzee, which was first published in 1992. Wasn’t this covered in Sex at Dawn?
All I’m saying is, read that new book with a saltshaker handy.◼
Gallup, G. G., R. L. Burch, M. L. Zappieri, R. A. Parvez, M. L. Stockwell, & J. A. Davis (2003). The human penis as a semen displacement device. Evolution and Human Behavior, 24, 277-89 DOI: 10.1016/S1090-5138(03)00016-3
A key component of classical sexual selection theory is the idea that males maximize their evolutionary fitness—the number of children they ultimately have—by mating with lots of females, while females maximize their fitness by selecting only one or a few high-quality partners. It’s pretty clear that this model works well for some species (like ducks), but also that there are many it doesn’t fit so well. Now it looks like one of the “classic” experimental examples of sexual selection may actually fall into the latter category.
Sexual selection was first proposed by Charles Darwin, in his 1871 follow-up to The Origin of Species, The Descent of Man, and Selection in Relation to Sex; but one of the earliest experimental tests of the model wasn’t published until 1948 [PDF]. The biologist A.J. Bateman allowed small groups of fruit flies—good old Drosophila melanogaster—containing equal numbers of males and females to mate at random, then reared the resulting eggs and reconstructed the parentage of the offspring to determine (1) the number of offspring each of the male and female parent flies had produced and (2) how many parters each parent fly had had.
How did Bateman reconstruct parentage decades before the advent of modern genetic testing? He used mutations with known, visible phenotypic effects as “markers”:
The fertility of individual flies of both sexes was measured by means of dominant marker genes. Several flies of each sex were mated together in one bottle, each fly carrying a different dominant marker gene. In this way, assuming the complete viability of all the marker genes, half the progeny of each fly could be identified.
That’s a pretty clever design given the technological limitations of the time. But it also turns out to be the fatal flaw in Bateman’s experiment.
There’s some more new evidence for one of the theories as to how gene variants that make men more likely to be gay could persist in human populations in the face of their obvious selective disadvantages: the same genes could, when carried by women, lead to greater fertility.
The authors interviewed women who were the biological mothers or aunts of gay men, and compared them to women who were mothers or aunts of straight men. They gave each participant a questionaire covering the key question—how many children they’d had. It also covered a sort of focused medical history, covering a slew of conditions that might have affected their fertility—anything from chlamydia infections to ovarian cysts to complicated pregnancies—and asked about their sexual behavior and history. Finally, the team gave the women in their sample a standardized personality test.
Even this relatively small sample showed the previously documented effect of shared genetics with gay men—women who had gay sons or nephews had more children than those who didn’t. Mothers and aunts of gay men also reported lower rates of medical conditions that could reduce their ability to have children. They said they’d had more partners than mothers and aunts of straight men (but this difference wasn’t statistically significant) and were also less concerned about family issues, and more likely to have been divorced. Finally, the personality test revealed that mothers and aunts of gay men were more extraverted.
That’s a big pile of factors tested, which makes me wonder about multiple testing issues with a small sample size. The study’s authors build a somewhat complicated narrative out of it all: They speculate that the same genes that make men gay make women less likely to have fertility-reducing conditions, but also more extraverted and more “relaxed” about building a family—which apparently also helps them have more children. So, okay, I guess that’s plausible given the results.
Here’s what the study doesn’t do, however: it doesn’t identify any specific genes involved in making gay men gay. It can’t actually test the hypothesis that there’s a genetic basis to same-sex attraction at all, much less the hypothesis that genes promoting same-sex attraction in men are located on the maternally-inherited X-chromosome. For those questions, you really need full pedigree data—or, better yet, lots and lots of genetic data; interviewing only female relatives isn’t remotely enough.
The text of the article doesn’t necessarily make that point as clearly as it could. The authors spend a great deal of time talking about the X-chromosome hypothesis, and though they make the requisite disclaimer in the Conclusions section—
With this type of limited data, we cannot directly derive a causal connection between the hypothetical sexually antagonistic autosomal or X-chromosome-linked genetic factors and health, behavior, and personality.
—that disclaimer elides the point that their data set can’t really test anything to do with genetics indirectly either.
The authors repeatedly describe their sample as a “pilot study,” however, so maybe something bigger, and more rigorous, is in the works.◼
Camperio Ciani, A., Fontanesi, L., Iemmola, F., Giannella, E., Ferron, C., & Lombardi, L. (2012). Factors associated with higher fecundity in female maternal relatives of homosexual men. The Journal of Sexual Medicine DOI: 10.1111/j.1743-6109.2012.02785.x
The central idea of sexual selection theory is pretty simple: Females, who invest relatively more in making and raising offspring, have an incentive to be choosy about mating. Males, on the other hand, may be able to get away with no more investment that a squirt of semen—so they have an incentive to mate with any female who’ll have them. How widely that model applies in the animal kingdom is very much an open question, but it does make some specific predictions that can be tested in an evolutionary context.
One of those predictions is that, when relatively more resources are at stake in the process of making babies, sexual selection should be stronger. Austin Hughes, a biologist at the University of South Carolina, recently set out to test for that pattern in waterfowl [$a].
Ducks and their relatives already look like a good fit for classic sexual selection. In many duck species mating is coercive, so females have evolved maze-like reproductive tracts to slow down unwelcome penises—and males have, in turn, evolved corkscrewing penises to navigate those mazes. And in many species, the sexes have strikingly different coloration—generally thought to mean that males are vying for female attention with brightly colored plumage, while females are more concerned with staying hidden while sitting on a nest.
However, there are also plenty of waterfowl species where males and females are almost indistinguishable—think of swans or geese, especially. If sexual plumage differences are related to the strength of sexual selection, maybe that reflects differences in the sexual “stakes” at play in each species. Hughes tested this hypothesis by comparing closely related pairs of waterfowl species or subspecies.
As an index of the reproductive effort made by females of each species, he used the mass of the average clutch of eggs laid, as a fraction of the mass of the average female. He then tested whether the species in each pair whose females made the larger “investment” in reproducing was also the species in the pair with more pronounced sexual differences in plumage coloration. And this was, indeed, what he found.
So that looks like a neat confirmation for one predicted effect of sexual selection. A worthwhile follow-up might be to add male parental care—which may be, admittedly, harder to measure—into the mix. If males help feed and protect the brood (which is often the case for waterfowl), that should offset the cost of reproduction from a female’s perspective, which might also reduce the strength of sexual selection.◼
Hughes, A. (2012). Female reproductive effort and sexual selection on males of waterfowl. Evolutionary Biology DOI: 10.1007/s11692-012-9188-1
A Biologist went down to the coffee shop one day, because the walk out to the edge of the University campus provided some brief respite from the laboratory. Along the way the Biologist encountered an Evolutionary Psychologist, who was also going to the coffee shop, and they fell to walking together.
As they entered the coffee shop, they found it crowded with undergraduates, for it was almost Finals Week. Accordingly, they joined the long queue of prospective customers waiting to place an order. Said the Evolutionary Psychologist to the Biologist, “My dear colleague, do you not see this crowd of fertile young people as I do, engaged in a dance of mate selection and competiton that predates our ancestors’ descent from the trees?”
And the Biologist replied, “I don’t believe that our ancestors had access to steamed milk and espresso. Or free wi-fi.”
“You are being amusingly obtuse!” chortled the Evolutionary Psychologist. “The environment may have changed somewhat since the days of our Darwinian origins, I will allow, but ova remain much dearer than sperm cells.”
“That much is certainly true,” said the Biologist. “But I am not sure how much it matters to the coffee-shop flirtations of undergraduates, almost none of which will result in procreative intercourse.”
“Ah,” said the Evolutionary Psychologist, “Perhaps this is a subject wherein my own field has surpassed the expertise of yours, my dear colleague. For instance, we have recently discovered [PDF] that men are more attracted to unintelligent, inattentive women—precisely what one would expect if men have been naturally selected to seek out easy opportunities for impregnation. And this search is doubtless underway all around us at this very moment.”
“That is a remarkable and possibly misogynistic hypothesis,” said the Biologist. “I am most curious to know how it was tested.”
“O! It was most elegantly done,” said the Evolutionary Psychologist. “Some of my colleagues simply asked a small class of undergraduate psychology students—males, of course—to examine photographs of women which were previously selected for their various appearances of vulnerability, and tell whether the photographs indicated vulnerability to sexual exploitation, suitability for a one-night stand, and suitability for a long-term relationship.”
“I see,” said the Biologist.
“Most surprisingly,” continued the Evolutionary Psychologist, “My colleagues discovered that the young collegiate males felt that women who looked drunk, or were standing in compromising postures, or indicating vulnerability in any of a dozen different ways, were both more vulnerable to sexual assault and more suitable for a brief sexual dalliance—but not more suitable for matrimony.
“So you see, my dear Biologist, it is not we Evolutionary Psychologists, who proposed the hypothesis of sexual exploitability, that are misogynists—the only misogynist here is Natural Selection itself, which confirmed our hypothesis.”
“I must beg your pardon, dear colleague,” said the Biologist, “but I am afraid I do not understand the basis for your conclusion. In order for this discovery to have any bearing on reproductive success, is it not the case that most human reproduction would need to occur via coerced intercourse?”
“I must confess that this seems to be what the data indicate,” replied the Evolutionary Psychologist. “But we must not conclude therefrom that all men are rapists! By no means, dear colleague. I think it is quite plain that this result demonstrates no more then that all men are potential rapists.”
“But I remain perplexed!” said the Biologist. “Surely rape is an inefficient way to reproduce, since babies traditionally require a good deal of care after impregnation, and women have long known how to un-plant unwanted seeds.”
“That,” said the Evolutionary Psychologist, “is an important question to be resolved by additional study! But of course it need only be the case that the occasional coercive impregnation could increase a man’s reproductive success, however slightly, for Natural Selection to grab hold.”
“I suspect,” said the Biologist, “that you attribute greater efficiency to Natural Selection than this evolutionary force truly possesses, my dear colleague. But even if drunken collegiate hook-ups were a viable avenue for procreation, you must concede that there would needs be some genetic basis for the tendency to reproduce in this fashion, if Natural Selection is to act upon it. Do you truly believe this to be the case?”
“What a peculiar question!” exclaimed the Evolutionary Psychologist. “I thought that you Biologists were well aware that, in the absence of evidence to the contrary, it is quite safe to assume that any and all aspects of human nature have a heritable genetic basis. Would you truly require the demonstration of heritability in order to conclude that an observed trait or behavior is adapted by Natural Selection?”
“Indeed we would,” said the Biologist. “Such a demonstration, in the case of a tendency to sexual coercion, would be considered most remarkable in its own right, in the scholarly journals of my discipline.”
“What a boring and backward discipline you practice!” said the Evolutionary Psychologist. “Truly, it is no wonder that your field has seen no great advance this last half-century, even as we Evolutionary Psychologists dissect the very nature of humanity.”
“Your ambitions,” said the Biologist, “are indeed remarkable.”
At this juncture, the two colleagues found that they had reached the front of the queue, placed their orders, and went their separate ways.◼
Goetz, C., Easton, J., Lewis, D., & Buss, D. (2012). Sexual exploitability: Observable cues and their link to sexual attraction. Evolution and Human Behavior DOI: 10.1016/j.evolhumbehav.2011.12.004
It is a truth universally acknowledged in evolutionary biology, that one species interacting with another species, must be having some effect on that other species’ evolution.
Actually, that’s not really true. Biologists generally agree that predators, prey, parasites, and competitors can exert natural selection on the other species they encounter, but we’re still not sure how much those interactions matter over millions of years of evolutionary history.
On the one hand, groups of species that are engaged in tight coevolutionary relationships are also very diverse, which could mean that coevolution causes diversity. But it could be that the other way around: diversity could create coevolutionary specificity, if larger groups of closely-related species are forced into narower interactions to avoid competing with each other.
Part of the problem is that it’s hard to study a species evolving over time without interacting with any other species—how can we identify the effect of coevolution if we can’t see what happens in its absence? If only we could force some critters to evolve with and without other critters, and compare the results after many generations …
A team of evolutionary microbiologists has performed exactly the experiment I outlined above. The study’s lead author is Diane Lawrence, a Ph.D. student in the lab of Timothy Barraclough, who is listed as senior author.
For the experiment, the team isolated five bacterial species, of very different lineages, from pools of water at the bases of beech trees—ephemeral pockets of habitat for all sorts of microbes that break down woody debris, dead leaves, and other detritus. They cultured the bacteria on tea made from beech leaves, in vials containing either a single species, or all five species, and let them evolve for eight weeks—several dozens of bacterial generations. In a particularly clever twist on standard experimental evolution methods, they also used nuclear magnetic resonance (NMR) to identify the carbon compounds in sterilized tea that had been “used up” by the bacterial cultures, and compared the compounds in fresh beech tea to determine what the bacteria were eating.
And, maybe not surprisingly, the bacterial species’ evolution with company turned out to be quite a bit from their evolution alone. Left alone, most of the species evolved a faster growth rate. This is a common result in experimental evolution, because the process of transferring evolving bacteria to fresh growth medium—”serial transfers” that were performed fifteen times over the course of the experimetn—can create natural selection that favors fast-growing mutants. But, grown all together in the same tube, species that had evolved faster growth rates in the solo experiment evolved slower growth instead.
To find out what had evolved in the multi-species tubes, the team tested the growth of the bacterial species on beech tea that had been used to grow one of the other species, then sterilized. The original, ancestral strains of bacteria generally had negative effects on each others’ growth—they lived on similar compounds in the beech tea, and so their used tea wasn’t very nourishing for the other species. The same thing occurred with the strains that had evolved alone, only stronger, which makes sense in light of the increased growth rates, which would’ve depleted the growth medium faster.
But the interactions among the strains of the different bacterial species that had evolved together was strikingly different. Many of them actually made the tea more nutritious for other species in the evolved community. That is, some of the bacteria had evolved the capacity to eat the waste products of another species that was evolving with them. Using the NMR method to track changes in the presence of different carbon compounds in the tea before and after use provided confirmation that the co-evolved species were using, and producing, complementary sets of resources.
In short, the evolving community didn’t simply become more diverse—it evolved new kinds of mutually beneficial relationships between species that began as competitors.
That evolutionary shift toward mutual benefit had a significant impact on the bacterial community as a whole, too. Lawrence et al. assembled new communities of bacteria extracted from the end-point of the group evolution experiment, and compared their carbon dioxide production, a proxy for overall metabolic activity, to that of a community assembled from bacteria extracted from the end point of the solo-evolution experiments. The community of co-evolved bacteria produced significantly more carbon dioxide, suggesting they were collectively able to make more use out of the growth medium.
So that’s a pretty nifty set of results, I have to say. But I’m also left wondering what it tells us more generally. In both Lawrence et al.‘s paper, and in accompanying commentary by Martin Tucotte, Michael Corrin, and Marc Johnson, there’s a fair bit of emphasis on the unpredictability of the result. Lawrence et al. write, in their Discussion section,
The way in which species adapted to new conditions in the laboratory when in monoculture—the setting assumed for many evolutionary theories and experiments—provided little information on the outcome of evolution in the diverse community.
And, as Corrin et al. note,
These results imply that predictions constructed from single-species experiments might be of limited use given that most species interact with many others in nature.
So … evolution went differently under different conditions? That isn’t exactly a shocking revelation. The fact that this is one of the study’s major conclusions is a symptom of how little experimental work has actually tested the effects of multiple species on evolution. One experiment I’ve discussed here previously, focused on the joint effects of predators and competitors on microbes that live in pitcher plant pitfalls, similarly emphasized the fact that it wasn’t possible to predict the evolutionary effects of predators and competitors together based solely on their individual effects. Work in this line of inquiry is hanging at the point of establishing that complex conditions lead to complex results.
What I’d really like to know—and I think all the authors of both the paper and the commentary would agree with me on this—is how we can begin to make general predictions about community evolution beyond, “it depends what we put in at the start.” It may be that we’ll need a lot more studies like this current one before we can start to identify common processes, and more interesting trends.◼
Turcotte, M., Corrin, M., & Johnson, M. (2012). Adaptive evolution in ecological communities. PLoS Biology, 10 (5) DOI: 10.1371/journal.pbio.1001332
Lawrence, D., Fiegna, F., Behrends, V., Bundy, J., Phillimore, A., Bell, T., & Barraclough, T. (2012). Species interactions alter evolutionary responses to a novel environment. PLoS Biology, 10 (5) DOI: 10.1371/journal.pbio.1001330
When people exercise aerobically, their bodies can actually make drugs—cannabinoids, the same kind of chemicals in marijuana. [University of Ariona anthropologist David] Raichlen wondered if other distance-running animals also produced those drugs. If so, maybe runner’s high is not some peculiar thing with humans. Maybe it’s an evolutionary payoff for doing something hard and painful, that also helps them survive better, be healthier, hunt better or have more offspring.
So, in a study [$a] pubished in The Journal of Experimental Biology, Raichlen tested this adaptive hypothesis by comparing the levels of these “endogenous cannabinoids” in the blood of humans, dogs, and ferrets after running on a treadmill. The idea being that the ancestors of dogs, like ours, made a living by running—chasing down prey—while ferrets don’t.
So it’s kind of nice to see that Raichlen and his coauthors did, indeed, find that humans and dogs both had higher levels of endogenous cannabinoids in their blood after a run, and the ferrets didn’t. That’s a useful evolutionary data point: it suggests that whatever physiological system prompts endogenous cannabinoid production in connection with exercise dates to (at least) the common ancestor of dogs and humans, and that its preservation in both species may be linked to our shared ability to run long distances.
But it really doesn’t show that this cannabinoid response is an adaptation to reward us for putting in our daily miles.
To really show that the runner’s high is an adaptation, of course, we’d need data that showed (1) observed variation in the runner’s high response has a genetic basis, and (2) people who had get stronger runner’s highs have more babies. But even apart from that, the understanding of what is good for us today—getting off our butts and going for a run—isn’t particularly that well connencted to the lives of our proto-human ancestors. Does Raichlen really think that early humans (or dogs, or any other animal that chases down prey) would just sit around and go hungry if we didn’t have a cannabinoid payoff at the end of the hunt?
And then, in the text of the very same NPR article, an orthopedic surgeon is quoted saying that the “runner’s high” can actually be a problem:
[Dr. Christina] Morganti treats runners for injuries and she says they’re the worst patients. “The treatment is to stop running,” she says. “They won’t. They don’t want to. A lot of the behavior is not unlike the patients we have who are seeking drugs. It’s really similar. It’s an addiction.”
So … a physiological response that prompts some of us to run even when running is likely to exacerbate injury is a good thing? How, exactly, would giving yourself shin splints lead to greater reproductive fitness if you’re making a living hunting gazelles on the savannah? I’m going to go out on a limb and say it wouldn’t.
Here’s an alternative hypothesis, which I freely admit is no better supported by the available data: the endogenous cannabinoid response isn’t a “reward” for running. Instead, it helped our ancestors tolerate the stress of running when they needed to, by letting them ignore minor pains and press on after that one elusive, tasty antelope. For our ancestors, dinner was the reward for running, not the cannabinoids. In the modern world, where we don’t run for our dinners, we’ve re-purposed the pleasant persistance of those cannabinoids as a motivation to replace that original life-or-death need.
Whatever the actual evolutionary origins of the “runner’s high,” the idea that it’s an adaptive reward for exercise is nothing more than adaptive storytelling filtered through the lens of our modern, very unnatural, lives. Don’t get me wrong—I love to run, and in fact I’m a month away from my fourth marathon. But I’m not going to pretend that I’ll be running those 26.2 miles because natural selection wants me to.◼
Raichlen, D., Foster, A., Gerdeman, G., Seillier, A., & Giuffrida, A. (2012). Wired to run: exercise-induced endocannabinoid signaling in humans and cursorial mammals with implications for the ‘runner’s high’ Journal of Experimental Biology, 215 (8), 1331-6 DOI: 10.1242/jeb.063677