The latest word on the Gulf of Mexico oil spill, as of the time at which I set the timer for this post to publish (circa 2230, 27 May), seems to be: that BP’s “top kill” maneuver, which would have plugged the gushing wellhead with mud, is not quite working as it ought. Meanwhile, the spill is now officially the worst in U.S. history, and poised to get even messier if it’s not contained by the start of what is projected to be a busier than usual hurricane season. Ugh. In non-oil-related science news:
Migrating bar-tailed godwits can fly 7,100 miles without a break. Photo by jvverde.
The small and squeaky shall inherit the Earth. Fossil evidence from a more gradual episode of warming 12,000 years ago suggests that some rodents, like deer mice, will become more abundant as the globe warms. (Not Exactly Rocket Science)
Got it made in the shade. Coffee farms practicing shade-growing techniques host more bee species, which may mean better pollination of the crop. (Coffee and Conservation)
… and boy are my wings tired! The advent of lightweight GPS and more sophisticated tracking methods has allowed ornithologists to directly monitor migrating birds—revealing nonstop flights of thousands of miles. (NY Times)
One more reason not to stand right behind a mammoth. A new study tracks ancient levels of atmospheric methane, and suggests that human overhunting of North America’s methane-farting megafauna caused the last ice age. (io9)
I know what you’re thinking, punk—only one of those critters is a true bug. Bombardier beetles, cabbage aphids, and velvet worms all employ explosive chemical weaponry as defenses, making them the “ballistics experts of the bug world.” (Ecotone)
No evidence of fossilized tartar sauce. Paleontologists have discovered a fossil frog with a fossil fish in its stomach. (Laelaps)
And finally, there’s a new version of the totally creepy Big Dog walking robot—it’s now cat-sized, and somehow more adorable than creepy. Until a pack of them show up to take me away as a slave to our new robot overlords, anyway. (via Anthony Hecht at Slog, who declares it “still creepy”)
As part of the early promotion for next year’s ScienceOnline conference, science superblogger and chronobiologist Bora Zivkovic asked me to answer a few questions over at A Blog Around the Clock, concerning me, my research, why I write here at D&T, and what a great time I had at ScienceOnline2010. I think this is my first appearance at a blog other than D&T—thanks for having me, Bora!
It’s come to my attention that the polymath blog 3quarksdaily has announced its second annual prize in science blogging, which will be judged this year by none other than Richard Dawkins. Prizes include fame, glory, and actual cash money, apparently. I’ve already self-nominated “Dethroning the Red Queen?”, but other parties who enjoy D&T are (ahem) free to nominate additional posts. Following Nerdy Christie’s lead, allow me to suggest a few other posts with which I’m well pleased:
If your coin is fair, I can guess that it’s come up heads and have a fifty percent chance, or probability equal to 0.5, that I’ve guessed correctly. Now, flip the coin ten times in a row. How many times did heads come up? Again, the best guess is that it came up five times—but it’s not all that unlikely that it came up six times, or four, or even as many as eight.
Now, if you flipped the coin an infinite number of times, then exactly fifty percent of the total flips would be heads. But who has time for that? Similarly, populations of living organisms are not infinite—often far from it—and this means that the frequency of genes in those finite populations can change as a result of the same phenomenon at work on your coin. Biologists call this genetic drift. Evolution at random
The basic principle behind genetic drift is that each generation is a process of sampling from the parental population to create a population of offspring. As most folks know from discussions of opinion polls, smaller samples tend to be less representative of the pool from which they are drawn. Say a population of annual plants begins with equal numbers of plants bearing blue flowers or white flowers. If only ten seeds survive from that population to form the next generation, you would expect them to be five blue-flowered and five white-flowered seeds. However, it’s just like flipping a coin ten times: the probability of drawing six blue seeds is actually a little less than 21%, or one in five. The probability of drawing nine blue seeds is almost one in one hundred—small, but hardly impossible.
Consider, too, that once you draw six blue seeds, it becomes slightly more likely that you’ll draw seven in the next generation, which makes it slightly more likely you’ll draw eight in the next. Repeated selection of small samples means that traits can drift to fixation (or loss, depending on your perspective), so that everyone in the population has the same trait. Rare traits are more likely to be lost to drift, and large populations are less prone to its effects. This is nicely illustrated in this online simulation from the University of Connecticut—over time, a focal gene fixes or disappears from the population as a function of the population size and the initial frequency of the gene.
In general, drift interferes with the efficient operation of natural selection. Even in relatively large populations, the probability that a new beneficial mutation will become fixed is approximately twice the selective benefit of that mutation—typically very small. (This is from a 1927 paper by J.B.S. Haldane that doesn’t seem to be online in any form, but which is discussed by Otto and Whitlock in a 1997 paper extending the classic result.) In a small enough population, a trait can become fixed even if it reduces its carriers’ fitness [PDF].
Evolving differences without selection
As I’ve discussed above, the effect of drift in a single population is to reduce variation as rare traits are lost to chance. This means that, when more than one independently-evolving population is considered, drift actually increases variation among them [$a], as different traits fix or are lost in each. That is, drift can make isolated populations evolve into different species even if they experience identical regimes of natural selection.
Woodland salamanders (genus Plethodon: left, P. vehiculum; right, P. yonahlossee) have diversified not by adapting to different environments, but by being homebodies. Photos by squamatologist.
A flagship example of this sort of non-adaptive diversification are the woodland salamanders of eastern North America, genus Plethodon. Woodland salamanders are quite diverse, having accumulated more than 40 species in the last 27 million years, but all of these species live in more or less the same habitat, under the leaf litter in moist Appalachian forests, and many are “cryptic” species distinguishable only by DNA analysis. How, then, did Plethodon become so diverse?
The answer is simply that woodland salamanders don’t travel very well. Salamanders need moist environments–they breathe through their skin, which doesn’t work well if it dries out—and so have difficulty moving from one stream drainage to another. This means that it doesn’t take much distance to isolate one Plethodon population from another, allowing drift to take them in different directions. Salamanders form new species, in other words, by staying at home.
This effect of drift means that biologists must adjust their “null” expectation when they observe differences in natural populations—the mere fact that some Joshua trees look different from other Joshua trees does not necessarily mean that natural selection has created those differences. Furthermore, the degree to which drift or selection can generate differences among populations depends strongly on the fourth force in the Big Four, which I’ll discuss next week: migration.
Godsoe, W., Yoder, J., Smith, C., & Pellmyr, O. (2008). Coevolution and divergence in the Joshua tree/yucca moth mutualism. The American Naturalist, 171 (6), 816-23 DOI: 10.1086/587757
Kozak, K., Weisrock, D., & Larson, A. (2006). Rapid lineage accumulation in a non-adaptive radiation: phylogenetic analysis of diversification rates in eastern North American woodland salamanders (Plethodontidae: Plethodon) Proc. Royal Soc. B, 273 (1586), 539-46 DOI: 10.1098/rspb.2005.3326
Lande, R. (1992). Neutral theory of quantitative genetic variance in an island model with local extinction and colonization. Evolution, 46 (2), 381-9 DOI: 10.2307/2409859
Otto S.P., & Whitlock M.C. (1997). The probability of fixation in populations of changing size. Genetics, 146 (2), 723-33 PMID: 9178020
Wright S (1931). Evolution in Mendelian populations. Genetics, 16 (2), 97-159 PMID: 17246615
Toxins from the oil spill will likely integrate into the food chain and eventually arrive to the deep in the form of food. Flux of material from the ocean surface is also likely to transport oil and toxins to the deep ocean. Shading by the oil slick might also inhibit phytoplankton production and reduce carbon flux to the deep sea meaning less food for seafloor organisms. An overall reduction of biodiversity both in terms of species and genetic diversity is expected.
Good science doesn’t match the sofa. People tend to prefer colors they associate with things they like. Therefore, natural selection is primarily responsible for humans’ color preferences. Wait, what? (Neurotopia)
I’m pretty sure that’s what “generalist” means. Invasive plants are no better defended than natives against a generalist native herbivore. (Conservation Maven)
Did you mean gesundheit? Google’s method of monitoring flu outbreaks by tracking search terms is almost as accurate as the CDC’s more expensive monitoring program. (Scientific American, but see Virology Blog)
From the folks who brought you octopodes wearing coconut shells: Solving a mystery that puzzled scientists since Aristotle, biologists have shown that the female argonaut octopus uses her paper-thin shell to trap air bubbles and control her buoyancy. (Not Exactly Rocket Science, Wired)
Insert “1up” joke here. Can playing video games improve cognitive skills? Dave Munger weighs the evidence. (SEEDMAGAZINE.com)
There are more than you think. This week’s Radiolab epdisode, “Famous Tumors,” is awesome with a side of neat evolutionary biology. (Radiolab)
A mutation is any change to an individual’s genetic code, whether caused by an external factor like radiation, or an error in the DNA copying that takes place every time an individual cell divides. However, not all mutations are created equal. First and foremost, for a mutation to have any future existence beyond the individual in which it occurs, it must be in a cell that will go towards forming the next generation, a germline cell. In sexually reproducing species, this means sperm or egg cells, or the progenitor cells in the testes or ovaries that form them. Second, for a mutation to be “visible” to natural selection, it must have some effect on fitness, the number of offspring an individual carrying the mutation is likely to have. The genetic code determines how and when individual cells make proteins, and proteins determine phenotypes, the visible characteristics of living things. However, many changes to the genetic code don’t affect their carriers’ fitness. Mutations might be more or less neutral because
They occur in regions of the genome that don’t code for proteins or control protein production—so-called “junk” DNA.
They are synonymous substitutions, which occur in a protein-coding region of DNA, but don’t alter the protein produced.
They alter a protein’s function and an individual’s phenotype, but in a way that doesn’t affect how many offspring that individual has.
Neutral mutations are actually quite important for biological studies—DNA fingerprinting and population genetics studies rely on them. Their frequencies evolve at random, reflecting the history of the populations that carry them rather than the effects of natural selection.
Favorable new mutations sweep the population
TOP: DNA sequences from a population are variable (blue) before a new mutation (red dot) arises; after it “sweeps,” every individual carries the allele as well as identical sequence nearby (red). BOTTOM: a figure from Linnen et al. (2009), demonstrates this pattern in deer mice. Images from Pritchard et al. (2010), fig. 3 and Linnen et al. (2009), fig. 4.
The variation introduced by neutral mutations—or, rather its absence—can help identify regions of the genome where selection is active. When a new gene arises by mutation, and it is strongly favored by selection, it can quickly spread through a population. In species that remix their genomes through sexual selection, the region of the genome containing a useful new gene can recombine into many different genetic backgrounds—but the closer a region of DNA is to the favored mutation, the less likely it is to recombine and separate from it. Thus, a region of the genome rather larger than the gene favored by selection is carried along until everyone in the population has the same DNA sequence.
When a new mutation takes over a population in this manner, it’s called a selective sweep, and the pattern it produces has been used to identify genes recently favored by selection in many different species, including humans. For instance, Linnen et al. documented reduced genetic variation in the neighborhood of gene variant responsible for light-colored fur in deer mice to demonstrate that it spread rapidly through the population after the mice colonized a region with light-colored sand.
Fuel for the engine of natural selection
Selective sweeps highlight how natural selection acts in opposition to mutation: mutation introduces new variation into populations, and natural selection causes the most fit variants to spread—potentially until the whole population carries the same trait. At the same time, selection requires variation in order to operate. If everyone is identical, then everyone has the same expected number of offspring, and the next generation will look just like the current one.
Because of this, natural selection can only operate as rapidly as mutation can introduce new variation from which to select. We know of specific cases in which selection seems to have “stalled” for lack of heritable variation. For instance, the fly Drosophila birchii lives in rainforest habitats along the northeast coast of Australia. Fly populations from the driest locations in this range have greater tolerance for dry conditions, but they also have virtually no heritable variation for drought tolerance [PDF]—and the authors suggest that this could limit the flies’ ability to evolve in response to climate change.
In other cases, though, biologists have found that mutation seems to provide new variation at least as fast as selection can remove it, leading to sustained, long-term evolution of experimental populations [PDF]. One important factor that may determine the outcome of this mutation-selection balancing act is actually the size of the population—more individuals means more opportunities for mutations to occur.
So the rate at which new mutations accumulate in a population depends on many factors, not the least of which are how you choose to measure that rate, and the fitness effects of the counted mutations. (Does a mutation “count” as soon as it occurs in a cell’s nucleus, or only when it has passed on to the next generation, or only when it has spread to everyone in a population?) Ultimately, populations evolve through a constant tension between the effects of mutation, natural selection, and the subject of next week’s Big Four force: genetic drift.
Drake J.W., Charlesworth B., Charlesworth D., & Crow J.F. (1998). Rates of spontaneous mutation. Genetics, 148 (4), 1667-86 PMID: 9560386
García-Dorado, A., Ávila, V., Sánchez-Molano, E., Manrique, A., & López-Fanjul, C. (2007). The build up of mutation-selection-drift balance in laboratory Drosophila populations. Evolution, 61 (3), 653-65 DOI: 10.1111/j.1558-5646.2007.00052.x
Hoffmann, A., Hallas R.J., Dean J.A., & Schiffer M. (2003). Low potential for climatic stress adaptation in a rainforest Drosophila species. Science, 301 (5629), 100-2 DOI: 10.1126/science.1084296
Keightly, PD. (2003). Mutational variation and long-term selection response. Pages 227-48 in Plant Breeding Reviews, Volume 24, part I. J. Janick, ed. John Wiley & Sons. Google Books.
Linnen, C., Kingsley, E., Jensen, J., & Hoekstra, H. (2009). On the origin and spread of an adaptive allele in deer mice. Science, 325 (5944), 1095-8 DOI: 10.1126/science.1175826
Pritchard, J., Pickrell, J., & Coop, G. (2010). The genetics of human adaptation: Hard sweeps, soft sweeps, and polygenic adaptation. Current Biology, 20 (4) DOI: 10.1016/j.cub.2009.11.055
Tokuriki, N., & Tawfik, D. (2009). Protein dynamism and evolvability. Science, 324 (5924), 203-7 DOI: 10.1126/science.1169375