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## Category Archives: Evolution

My “Worked Physics Homework Problems” book now stands at 372 pages. If you ever wonder what I do instead of meeting people.
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1996: John Horgan declares THE END OF SCIENCE. 1997: first E. coli genome sequence published. 1998: expansion of Universe found to be accelerating.
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“You’ll get so preoccupied with equations that you forget to eat!” #BadWaysToPromoteScienceToYoungWomen
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The following is a selection of interesting papers on the theory of evolutionary dynamics. One issue addressed is that of “levels of selection” in biological evolution. I have tried to arrange them in an order such that the earlier ones provide a good context for the ones listed later.

I’ve met, corresponded with and in a couple cases collaborated with authors of these papers, but I’ve had no input on writing or peer-reviewing any of them.
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Last October, a paper I co-authored hit the arXivotubes (1110.3845, to be specific). This was, on reflection, one of the better things which happened to me last October. (It was, as the song sez, a lonesome month in a rather immemorial year.) Since then, more relevant work from other people has appeared. I’m collecting pointers here, most of them to freely available articles.

I read this one a while ago in non-arXiv preprint form, but now it’s on the arXiv. M. Raghib et al. (2011), “A Multiscale maximum entropy moment closure for locally regulated space-time point process models of population dynamics”, Journal of Mathematical Biology 62, 5: 605–53. arXiv:1202.6092 [q-bio].

Abstract: The pervasive presence spatial and size structure in biological populations challenges fundamental assumptions at the heart of continuum models of population dynamics based on mean densities (local or global) only. Individual-based models (IBM’s) were introduced over the last decade in an attempt to overcome this limitation by following explicitly each individual in the population. Although the IBM approach has been quite insightful, the capability to follow each individual usually comes at the expense of analytical tractability, which limits the generality of the statements that can be made. For the specific case of spatial structure in populations of sessile (and identical) organisms, space-time point processes with local regulation seem to cover the middle ground between analytical tractability and a higher degree of biological realism. Continuum approximations of these stochastic processes distill their fundamental properties, but they often result in infinite hierarchies of moment equations. We use the principle of constrained maximum entropy to derive a closure relationship for one such hierarchy truncated at second order using normalization and the product densities of first and second orders as constraints. The resulting `maxent’ closure is similar to the Kirkwood superposition approximation, but it is complemented with previously unknown correction terms that depend on on the area for which third order correlations are irreducible. This region also serves as a validation check, since it can only be found if the assumptions of the closure are met. Comparisons between simulations of the point process, alternative heuristic closures, and the maxent closure show significant improvements in the ability of the maxent closure to predict equilibrium values for mildly aggregated spatial patterns.

In network science, one can study the dynamics of a network — nodes being added or removed, edges being rewired — or the dynamics on the network — spins flipping from up to down in an Ising model, traffic flow along subway routes, an infection spreading through a susceptible population, etc. These have often been studied separately, on the rationale that they occur at different timescales. For example, the traffic load on the different lines of the Boston subway network changes on an hourly basis, but the plans to extend the Green Line into Medford have been deliberated since World War II.

In the past few years, increasing attention has been focused on adaptive networks, in which the dynamics of and the dynamics on can occur at comparable timescales and feed back on one another. Useful references:
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Consider the Lagrangian density

$\mathcal{L} (\tilde{\phi},\phi) = \tilde{\phi}\left((\partial_t + D_A(r_A - \nabla^2)\right)\phi - u\tilde{\phi}(\tilde{\phi} - \phi)\phi + \tau \tilde{\phi}^2\phi^2.$

Particle physicists of the 1970s would recognize this as the Lagrangian for a Reggeon field theory with triple- and quadruple-Pomeron interaction vertices. In the modern literature on theoretical ecology, it encodes the behaviour of a spatially distributed predator-prey system near the predator extinction threshold.

Such is the perplexing unity of mathematical science: formula X appears in widely separated fields A and Z. Sometimes, this is a sign that a common effect is at work in the phenomena of A and those of Z; or, it could just mean that scientists couldn’t think of anything new and kept doing whatever worked the first time. Wisdom lies in knowing which is the case on any particular day.

[Reposted from the archives, in the light of John Baez's recent writings.]

For your convenience:

The following is a list of debunkings of Stephen C. Meyer’s Signature in the Cell, arranged more or less in chronological order. I have not included every blog post I’ve seen on the topic; as I did for Behe’s The Edge of Evolution, I’ve focused on the most substantive remarks, rather than keeping track of every time somebody just quoted somebody else. (I’ve also probably overlooked, forgotten, mistakenly thought I’d already included or never been made aware of some worthwhile essays.) In some cases, additional relevant posts can be found by following links within the essays I have listed.
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A discussion elsewhere on the ‘tubes this morning reminded me of this, so I decided to dig it out of my archives. Short version: people complaining that something sounds silly got it coming right back at them because they have no clue what they’re talking about.

I haven’t yet seen the remake of The Day the Earth Stood Still. Generally speaking, I haven’t been terribly speedy about seeing movies as they come out; sometimes, I just wait until they’re available on mplayer. The reviews have not been kind, but on the flipside, not all the reviews have been particularly insightful. To wit, here is Alonso Duralde at msnbc.com:

The new “Day” can’t be bothered to include the thought-provoking dialogue of the original, choosing instead to bury the audience with special effects that are visually impressive but no substitute for an actual script. And what words do remain are so exquisitely awful that they provide some of the season’s biggest laughs.

OK, bring it.

My personal favorite? Astro-biologist Helen Benson (Jennifer Connelly) takes alien Klaatu (Keanu Reeves) to see a Nobel Prize-winning scientist and notes that her colleague was honored “for his work in biological altruism.” What would that entail, exactly? Helping frogs cross the street?

The sound you hear is my palm hitting my forehead, rather emphatically, followed by a howl from deep within my thorax: “Learn to [expletive deleted] Google, you [anatomically uncomplimentary compound noun]!” Just because Chris Tucker of the Daily Mail can’t do a simple web search doesn’t give you an excuse.

Claudia Puig at USA Today is no better:

What, exactly, would that entail? It sounds like something Cleese and his fellow Monty Python wits might have dreamed up.

You ignorant [epithet derived from SF television show]. Why don’t you go [verb unsuitable for a family blog] with Dave White, who apparently thinks that the mere mention of an actual scientific subject makes a movie instant MST3K fodder.

In Scientific American, Michael Shermer gives the movie a mostly positive review, and indicates that “biological altruism” is a real subject. Kenneth Turan of the LA Times is also mostly happy with the film, and he doesn’t crack wise about the “biological altruism” business, though I’m not sure about his grasp of it:

Aside from Klaatu and Gort, the “Day” team claims to have retained the original’s snappy catchphrase, “Klaatu barada nikto,” but it’s so hard to hear that viewers will be forgiven if they miss it. Also still around is the charming blackboard scene, in which Klaatu solves an equation for Professor Barnhardt (John Cleese), a man smart enough to have won the nonexistent but indisputably high-minded Nobel Prize for biological altruism.

Supposing that Barnhardt did work in the field of kin recognition, evolutionary ecology or some such topic which was honoured with a Nobel Prize, it wouldn’t be “the Nobel Prize for biological altruism”, but rather the Nobel Prize in Physiology or Medicine or, possibly, Economics (if Barnhardt’s research focused on, say, evolutionary game theory).

MTV’s Kurt Loder calls the film “boldly mediocre” but says that “biological altruism” is “a very Pythonian name for an actual subject of scientific inquiry”. Stephen D. Greydanus has a similar attitude. The recapper at the Agony Booth was also underwhelmed, by this part and by the rest of the movie:

Helen explains that Karl won the Nobel “for his work in biological altruism.” This sounds like something goofy they made up to make Karl sound noble, but in fact it’s a real field of philosophic study that investigates why, in times of limited resources, individual organisms throughout the animal kingdom occasionally produce fewer offspring (which, in Darwinian terms, is self-abnegation) for the good of the community. Which is great, but since it’s not explained, most of the audience is left to think that it’s something goofy the filmmakers made up.

So, I guess you can still dislike the movie after you’ve looked up the relevant science.

Meanwhile, our long cybernetic nightmare continues. Thoughtlessness abounds. Things fall apart; the ice sheets cannot hold. Bloggers demand their due from a system which is ill-prepared to provide it. Satirists strive mightily to invent new jokes about Twilight.

Some things I’ve enjoyed reading recently:
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I noticed this one when it first hit the arXivotubes a while back; now that it’s been officially published, it caught my eye again.

G. Rozhnova and A. Nunes, “Population dynamics on random networks: simulations and analytical models” Eur. Phys. J. B 74, 2 (2010): 235–42. arXiv:0907.0335.

Abstract: We study the phase diagram of the standard pair approximation equations for two different models in population dynamics, the susceptible-infective-recovered-susceptible model of infection spread and a predator-prey interaction model, on a network of homogeneous degree $$k$$. These models have similar phase diagrams and represent two classes of systems for which noisy oscillations, still largely unexplained, are observed in nature. We show that for a certain range of the parameter $$k$$ both models exhibit an oscillatory phase in a region of parameter space that corresponds to weak driving. This oscillatory phase, however, disappears when $$k$$ is large. For $$k=3, 4$$, we compare the phase diagram of the standard pair approximation equations of both models with the results of simulations on regular random graphs of the same degree. We show that for parameter values in the oscillatory phase, and even for large system sizes, the simulations either die out or exhibit damped oscillations, depending on the initial conditions. We discuss this failure of the standard pair approximation model to capture even the qualitative behavior of the simulations on large regular random graphs and the relevance of the oscillatory phase in the pair approximation diagrams to explain the cycling behavior found in real populations.

Richard Dawkins and PZ Myers had a lengthy, informal chat during the 2008 American Atheists conference in Minneapolis, and a recording of their conversation is now available on DVD and in the video tubes. They discuss the fight against pseudoscience as well as several interesting topics in good science.

I did my best to summarize the kin-vs.-group business in this book review. Among the “glimmerings” which suggest there’s a better way to think about some evolutionary processes (name for that better way still to be defined) are, I think, the epidemiological simulations in which fitness of a genotype is clearly a function of ecology and thus strongly time-dependent, and consequently existing analysis techniques are likely to fail. Assuming this kind of thing happens in the real world, it might be better to speak of “extending the evolutionary stable strategies concept” or “temporally extended phenotypes” than to have yet another largely semantic argument over “group selection.”

Also of note:

When Dawkins spoke at the first artificial life conference in Los Alamos, New Mexico, in 1987, he delivered a paper on “The Evolution of Evolvability.” This essay argues that evolvability is a trait that can be (and has been) selected for in evolution. The ability to be genetically responsive to the environment through such a mechanism as, say, sex, has an enormous impact on one’s evolutionary fitness. Dawkins’s paper has become essential reading in the artificial life community.

Anyway, on with the show.

P-Zed wrote an introduction to allometry a little over a year ago.
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The evilutionary superscientist P-Zed has been trying to drive the riffraff away from his website by writing about biology. First we had “Epigenetics,” and now we’ve got “Snake segmentation.” Meanwhile, Clifford Johnson is telling us about “Atoms and Strings in the Laboratory” (with bonus musical accompaniment). Stick around for stupid questions from me in the comments!

(Everything I know is really just the sum total of answers I’ve received for stupid questions.)

Even buried as I am under a stack of PDFs talking about PDEs, I would be remiss if I didn’t point out some juicy videos describing actual, factual cutting-edge science, namely the talks from Rockefeller’s recent evolution symposium. I’m currently in the middle of Bruce T. Lahn’s (U Chicago) talk, “Probing Human Brain Evolution at the Genetic Level.” Click here and scroll down to find the link. What could be more appropriate for an elitist bastard than an explanation of genes which control brain size?

(Thanks go out to Abbie.)

The most dangerous aspect of being trapped in the digital library’s virtual basement stacks is that you don’t want to come out.

Simon A. Levin (1992), “The Problem of Pattern and Scale in Ecology” Ecology 73, 6: pp. 1943–67. [JSTOR] [PDF].

It is argued that the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology. Applied challenges, such as the prediction of the ecological causes and consequences of global climate change, require the interfacing of phenomena that occur on very different scales of space, time, and ecological organization. Furthermore, there is no single natural scale at which ecological phenomena should be studied; systems generally show characteristic variability on a range of spatial, temporal, and organizational scales. The observer imposes a perceptual bias, a filter through which the system is viewed. This has fundamental evolutionary significance, since every organism is an “observer” of the environment, and life history adaptations such as dispersal and dormancy alter the perceptual scales of the species, and the observed variability. It likewise has fundamental significance for our own study of ecological systems, since the patterns that are unique to any range of scales will have unique causes and biological consequences. The key to prediction and understanding lies in the elucidation of mechanisms underlying observed patterns. Typically, these mechanisms operate at different scales than those on which the patterns are observed; in some cases, the patterns must be understood as emerging form the collective behaviors of large ensembles of smaller scale units. In other cases, the pattern is imposed by larger scale constraints. Examination of such phenomena requires the study of how pattern and variability change with the scale of description, and the development of laws for simplification, aggregation, and scaling. Examples are given from the marine and terrestrial literatures.

Gyorgy Szabo, Gabor Fath (2007), “Evolutionary games on graphs” Physics Reports 446, 4-6: 97–216. [DOI] [arXiv].

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first three sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fourth section surveys the topological complications implied by non-mean-field-type social network structures in general. The last three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner’s Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

SÃ©bastien Lion, Minus van Baalen (2007), “From Infanticide to Parental Care: Why Spatial Structure Can Help Adults Be Good Parents” American Naturalist 170: E26–E46. [HTML] [PDF].
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REVIEW: The Oxford Book of Modern Science Writing, edited by Richard Dawkins. Oxford University Press, 2008. ISBN 978-0-19-921680-2. A PDF copy of this review is available here.

PRELUDE

During the Christmas holidays last year, my mother and I were visiting a bookshop, and we passed by a display of general-audience science books. As a child, I had devoured such things, and propelled by sentiment mixed with curiosity, I looked over the titles, browsing for ones which I’d seen recommended or were written by authors I knew. Momentarily, however, a harsh edge cut through my sentimental reverie. “Look at this,” I said. “This book props up its thesis with phony numbers and citations which point to papers that don’t even discuss what the book says they do! And this one, here, tells a version of 1990s physics history which, to put it mildly, doesn’t match up with what other physicists remember. Oh, and this author, well, everybody is just astonished at how the clarity of his thinking implodes halfway through, when he stops thinking and starts faith-ing. And what’s this — quantum healing?

If the Gentle Reader were to deduce a “moral” from the story, it might be that I am a cantankerous individual with an acerbic disposition, and the reader would not be gravely in error. Beyond that, one could say that a science education nearly killed the general-interest bookshelf for me, and what University did not do, the science-blogging world definitely tried to finish. Caught up in this electronic tangle of opinions, discoveries and arguments, where new findings and reactions to them are all free for the taking, I’d seen the flaws of a great many books exposed. Precisely because online science writing makes irascible iconoclasm a way of life, though, it teaches the joy of discourse and the admiration of written words which, finally, work. Both of these aspects play into the value of The Oxford Book of Modern Science Writing, edited by Richard Dawkins.

This book collects passages written by seventy-nine scientists over the previous hundred years; though Dawkins himself has more than proven his talents as an expositor, his own writings are confined to introductory remarks giving context for each selection. Biology is represented quite strongly, and physics makes a good showing. Astronomy, other than the cosmological variety, makes mostly cameo appearances, and chemistry seems rather the poor stepchild. (Max Perutz, a Nobel Laureate, contributes a bit on X-ray crystallography which is largely an admiring biographical sketch of fellow laureate Dorothy Hodgkin, and the well-known neurologist Oliver Sacks is roped in to give a quirky reminiscence about tungsten! Primo Levi‘s tale of a carbon atom, though, is not to be missed.) Truly commendable is Dawkins’s inclusion of mathematics, a subject which provokes an unnatural fear even in literate readers who appreciate science and enjoy reading about the latest fossil or the most newly discovered extra-solar planet. The selections chosen for The Oxford Book are clear, memorable and not infrequently poetic. Upon occasion, they deliver on that great promise of science education: to provoke the learner into seeing the natural world and the products of the human mind in a new and unforgettable light. After reading what Stephen Jay Gould wrote about Charles Darwin‘s take on the humble earthworm, for example, it is difficult to see in the same way such a simple thing as worms coming out on a pavement after the rain.

The Oxford Book would serve as an excellent smÃ¶rgÃ¥sbord of introductions for the reader who has grown interested in science but doesn’t know where to begin. Likewise, those who catch the biggest headlines and read about the flashiest new breakthroughs will likely benefit from a book about science which has stood the test of time, about discoveries which have kept on inducing breathlessness for several decades. A specialist trained in one scientific field could also enjoy an interlude of lateral thought, poking into a new domain of learning to flex the thought-muscles.

When I’ve heard people talk about a movie or a book being “an unalloyed pleasure,” they mean it to be joy without stopping, all good and nothing bad. Given that an alloy is a mixture of metals, the phrase also carries a trace contamination of the idea that the book or the movie being talked about only offers one kind of goodness — all drama and no comedy, let’s say. Consequently, I find myself describing The Oxford Book of Modern Science Writing as an alloyed pleasure, a mixture of different satisfactions, in unequal amounts. The amazing facts, the flashes of wit, the moments of rapturous wonder are all there to be had, but Dawkins has also provided a series of portals to debate. I’m not talking about a nasty kind of political infighting, with accusations and character assassination, but rather the academic version of the same process: the rolling up of sleeves, the setting down of the teacup and the declaration of intellectual combat.

The book club meetings for this volume can, and should, be. . . volatile places.
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