Freely-associated Earth Day and Outdoor Adventure-related Content

This is being cross-posted to my micro-blog, Tumbld Thoughts.

Here is a recent story on how 70,000 ladybugs have been released in the Mall of America to combat aphid infestations of the interior foliage. At 4.2 million square feet, the Mall of America has developed an incipient ecosystem [1]. The dynamics of this ecosystem will interesting to observe, particularly in light of the work that has been done in the field of biospherics (e.g. Biosphere 2, which is sponsored by the University of Arizona) [2]. Speaking of self-sustaining ecosystems.......

Nice ecosystem animation for Earth Day, courtesy of Google Doodle. Surf the web to find the true meaning of Earth Day, I guess. Speaking of surfing.....

Why it pays to Surf Michigan. No, really! There is a thriving (albeit obscure) surf culture in the US state of Michigan [3]. Lake Michigan surfing (inset on the left, picture from the St. Joseph Pier on Lake Michigan) has been going on for years, usually in the Fall and Spring when gales present waves large enough for surfing on.

When there is significant rainfall (such as during the past few weeks) or Spring snowmelt, the inland rivers (inset on the right, picture from the Red Cedar River in front of the Administration Building at Michigan State University) allow for interesting surf conditions.

Rincon Beach Park, Santa Barbara County, CA. There is also beachfront right across the street from the UCSB campus.

Surfing at Michigan State is a bit like a cold UC Santa Barbara with ducks on a river (odd mental image, I'm sure). Speaking of academically-oriented surfing [4], here is a profile on the "Physics of Surfing" class offered at UC San Diego [5]. Happy outdoor adventuring!

Scenes from the "Physics of Surfing" class, which combines lessons in instrumentation, oceanography, and of course surfing.

NOTES:

[1] this has parallels to ecosystems that emerge due to climatic changes such as the retreat of glaciers.

[2] Allen, J.   People Challenges in Biospheric Systems for Long-Term Habitation in Remote Areas, Space Stations, Moon, and Mars Expeditions. Life Support and Biosphere Science, 8, 67-70 (2002).

[3] Pictures of wetsuit adventurers in interesting conditions courtesy of Matuli Surf Company (Matulis brothers, Midland, MI).

[4] Here is a list of the top 10 surf colleges from Surfer magazine. Michigan State (nor any other Michigan University) is on it. The only odd duck here is NYU, which offers you the opportunity to surf Long Island (and perhaps the sewers). I might add Florida Atlantic University (FAU) to the list, at least during hurricane season.

[5] A few more links about those skeptical of the academic value of studying surfing: 1) a video on the physics of surfing by Kevin Stahl and friends, 2) a white paper called "The Physics of Ocean Waves" by Michael Twardos (courtesy of Snake Gabrielson's Surflibrary.org), 3) a story by John Jeka at the University of Maryland in the "Neuromorphic Engineer" called "Light touch-contact: not just for surfers". The article profiles the role of touch (e.g. somatosensory information) in helping people and other animals keep their balance when moving across a surface.

Replication, Model Organisms, and the Role of Evolutionary Signatures

The following slides and commentary focus on an open problem that involves the difference in perspective between medical researchers and evolutionary biologists. By perspective, I mean the types of explanatory frameworks one uses to understand a set of results.

Notice that I could have used the word "theory", but it actually has more to do with the cultural premises of one's discipline and formal training [1], especially in cases where there is a lack of good theory.

These slides are the second part of a talk of mine called "If your results are unpredictable, does it make them any less true? (posted to Figshare), which is a follow-up on the HTDE 2012 Workshop.

This set of slides was inspired by an in-lab discussion about a news article, that lead me to a recent PNAS paper on sepsis research in mice and humans. While mice are the accepted model organism for studying sepsis [2], it turns out that the physiological response (e.g. microarray studies and gene expression correlations) to sepsis in humans is very different than in mice. 

This result is interesting from an evolutionary standpoint. While there is phylogenetic distance between mice and humans, they are both mammals and certainly share many physiological and genomic characteristics. Furthermore, can these differences be explained using evolutionary theory? Has there been evolution in the sepsis response between mice and humans, or are these differences due to a highly variable response that can vary widely between species (and perhaps even between individuals in the same species)?

The variation in pathway activation and physiological responses seems to be quite common in medical research. When a certain experimental manipulation is done to multiple species [3], there is a range of possible outcomes, from a common response to a widely varying responses. We will return to this later. 

For now, let's consider why such massive differences might exist between humans and mice for a single physiological response. This is where we must return to the issue of premises. Given your background and preferences, you might choose a single explanatory framework. 

I have presented three in the slide below:  black box, complexity, and noise. Each of these may find support depending on the measures used and physiological components assayed. Yet each of them used in isolation may not be particularly satisfying, nor even explain very much of the data by themselves. This is why good, unified theories are of such value.

Another important aspect of understanding this variable response is to rule out alternative hypotheses. In the slide below, I consider three potential artifacts that could unduly influence the animal model results: standardization of environmental conditions, artificial selection on the model organism population due to selective breeding, and the tendency of the experimenter to put more weight on features of the experimental design or analysis that allow for greater experimental replication within a particular species. Particularly in the case of the first and last point, the lesson is that standardization of the experimental setting may actually do more harm than good and introduce ecological validity problems.

Now I present my interpretation of what is going on with the sepsis result. This consists of two hypotheses that can be applied to each species (human and mouse). The first is that the physiological response to sepsis is exact, which utilizes the same pathways and same patterns of gene expression across most conspecifics but only within a single species. This might require mutational distance and other evolutionary changes among the genes that explain the sepsis phenotype. 

The alternate hypothesis says that the physiological response to sepsis is variational, which means that there is potentially great variation is mechanism across most members of the same species. This variation need not be due to heritable mutation, but simply a lack of specificity in the molecular pathways and other associated mechanisms. In this case, there would be differences between human and mouse far greater than a consensus phylogeny might suggest.

What is a variational response? The term "variational" [4] is taken (perhaps loosely) from the mathematics and physics literature, and is generally used to describe a system with many potential solutions. In this context, the goal of the variational method is to approximate potential solutions based on optimizing their properties. 

One example can be shown in the slide below: two alternate routes from Toronto to Vancouver. Each route is the "shortest" route using two pathway criterion. One pathway is tightly restricted to the Trans-Canadian highway, while the other allows for an alternate route along a number of US interstates (e.g. 5, 90, 94). Both routes are about the same number of kilometers in length (e.g. number of steps in a physiological pathway). Yet they might be alternately used due to the in-capacitation of one pathway or the other [5].

The slide below shows these hypotheses in a phylogenetic context. As a contingency table, we consider the exact and variational scenarios for both conserved and divergent mechanisms. In the case of a conserved mechanism, there is very little mutational change to the underlying genes or pathway. For a divergent mechanism, the opposite is true.

To further understand what is meant by evolutionary conservation (and how it affects the consistency of physiological responses across species), I will now discuss two examples from the literature: the regulation of stress and aging, and the use of zebrafish as a human analogue. This will hopefully put my evolutionary speculations in context.

In aging research, phylogenetically-divergent species such as yeast and flatworms are used to understand the substrate of interventions such as caloric restriction and the activity of pathways related to stress resistance. As Longo and Fabrizio [6] demonstrate using aggregated data (see below slide), the associated pathway architectures are quite invariant across yeast, flatworms, and humans. However, this may not involve the same genes form species to species. In cases where conserved genes are known to be involved, it is not clear whether this conservation of mechanism components extends to a conserved mechanism itself.

A recent set of papers [7] focuses on comparing the genomes and proteomes of zebrafish with humans. As zebrafish and humans diverged around 440 million years ago [8], we would expect there to be vast differences in both function and genomics. However, there are occasionally greater differences among zebrafish than between zebrafish and humans. Another puzzle similar to the sepsis story, excpet that now we have extensive characterization of the genome and proteome to work from.

In the slide below (taken from Figure 3 of the Howe et.al paper), we can see how orthologues are shared by zebrafish and human as well as the relationship between so-called ohnologues in the zebrafish genome. Data such as these may provide good future estimates on how and why differences exist when evaluating variation related to basic physiological functions with and between zebrafish and humans.

So what can be learn from the big picture? Particularly when distinguishing between the homogeneity expected from experimental replication and the heterogeneity posed by natural variation? Perhaps we can treat experimental replication as a generative model, where the basic experiment is expected to reveal a range of likely outcomes. Like generative models in machine learning, the goal of analysis is to pick the best model (or in this case, the set of data that provide the closest match to what we know about the underlying natural phenomenon). 

This is a tricky proposition, because both the possible set of experimental and natural outcomes are incompletely known. Nevertheless, as in the case of understanding physiological processes and outcomes as variational processes, we can make good approximations that provide high explanatory power [9] without over-relying on the replication of results.

NOTES: 

[1] cultural premises are also known as "point of view". See this Tumbld Thoughts post for a detailed review.

From two wildly different premises: a painting entitled "Picasso and Dali Paint an Egg" (Artist unknown).

[2] model organisms are used conduct experiments that are either unethical or impossible to engage in with human subjects. Here is the full NIH list of model organisms. The accepted human analogues range from fruit flies (Drosophila) to mice (Mus musculus) and round worms (C. elegans) and zebrafish (Danio rerio). A newer trend is to use domesticated animals (e.g. sheep, cows, goats, pigs) as (non-traditional) model organisms.

Please see the following papers for more information on cross-species comparisons of model organisms with relevance to disease:

Golstein, P., Aubry, L., and Levraud, J.P.   Cell-death alternative model organisms: why and which? Nature Reviews Molecular and Cell Biology, 4(10), 798-807 (2003).

Goldstein, P.   Cell death in unusual but informative and beautiful model organisms. Seminars in Cancer Biology, 17(2), 91–93 (2007).

[3] this effect can be observed (usually understood via anecdotal reporting methods) both in vivo and in vitro (cell culture models). 

[4] the variational principle is widely used in quantum physics and engineering to arrive at solutions in very large, complex systems. Why not a version of this idea for physiological systems analysis?

[5] this suggests a role for mechanisms such as robustness, evolvability, and degeneracy.

[6] Longo, V.D. and Fabrizio, P.   Regulation of longevity and stress resistance: a molecular strategy conserved from yeast to humans? CMLS: Cellular and molecular life sciences, 59(6), 903-908 (2002).

[7] Here are a host of relevant papers (including a recent feature article in Nature):

a. Varshney, G.K. et.al   A large-scale zebrafish gene knockout resource for the genome-wide study of gene function. Genome Research, 23, 727-735 (2013).

b. Kettleborough, R.N.W. et.al   A systematic genome-wide analysis of zebrafish protein-coding gene function. Nature, doi:10.1038/nature11992 (2013).

c. Schier, A.F.   Zebrafish earns its stripes. Nature, doi:10.1038/nature12094 (2013).

d. Howe, K.   The zebrafish reference genome sequence and its relationship to the human genome. Nature, doi:10.1038/nature12111 (2013).

e. Barbazuk, W.B.   The Syntenic Relationship of the Zebrafish and Human Genomes. Genome Research, 10, 1351-1358 (2000).

[8] data derived from multiple consensus phylogenies (a meta-meta analysis) curated by Timetree.org. 

[9] This was cross-posted to my micro-blog, Tumbld Thoughts:

A new paper by Button et.al [a] featured in Wired Science claims that research in the Neurosciences are plagued with low statistical power (e.g. explanatory capacity of significant results), which is based on an 2005 paper by John Ioannidis [b] that applies a measure called positive predictive value (PPV) for determining the reliability of results in a particular scientific field (top image). While Ioannidis originally focused on results in Psychology, in later papers he has extended this line of inquiry to Computational Biology (e.g. microarray analysis) [c].

This reliability can be compromised by something called the proteus phenomenon [d], which deals with drawing a consensus from a series of datasets that exhibit similar biases. Two potential examples of this can be seen in a meta-meta analysis of the Psychological literature (Figure 3) from [a], and the Social Psychology literature. In the case of the latter, a paper from Vul et.al [e] investigates the exceedingly high correlations between brain activity data yielded from neuroimaging data and personality (e.g. self-reported) measures. Does this mean that there truly IS a high correlation, or is a subtle bias at work here?

Whether or not these concerns are overblown is up for debate, and it may be an artifact of the way we test for significance (e.g. NHST) rather than inherent problems with the method of experimental replication [f]. Fortunately, people are trying to address some of these issues (bottom image). Examples include the Equator Network [g] and the reproducibility project [h], both of which advocate open science. And, of course, there are more philosophically-oriented issues that I have started to address with the Hard-to Define Events (HTDE) approach.

For Reference 9, see also:

[a] Button, K.S., Ioannidis, J.P.A., Mokrysz, C., Nosek, B.A., Flint, J., Robinson, E.S.J., and Munafo, M.R.   Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, doi:10.1038/nrn3475 (2013).

[b] Ioannidis, J. P.   Why most published research findings are false. PLoS Medicine, 2, e124 (2005).

[c] Ioannidis, J. P. et.al   Repeatability of published microarray gene expression analyses. Nature Genetics, 41, 149–155 (2009).

[d] Pfeiffer, T., Bertram, L. & Ioannidis, J. P. Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias. PLoS ONE 6, e18362 (2011).

"The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result"

[e] Vul, E., Harris, C., Winkielman, P.,  and Pashler, H.   Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition. Perspectives on Psychological Science, 4, 274 (2009). Also see Ed Vul's site on "voodoo correlations".

[f] for more information on the BEST test (an alternative to tests of the null hypothesis), please see: Kruschke, J.K.   Bayesian estimation supersedes the t test. Journal of Experimental Psychology: (2012).

[g] Simera, I. et.al   Transparent and accurate reporting increases reliability, utility, and impact of your research: reporting guidelines and the EQUATOR Network. BMC Medicine 8, 24 (2010). 

Other (more specialized) consortia geared toward this end include the Consolidated Standards of Reporting Trials (CONSORT), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and the Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Stroke (CAMARADES).

[h] Open-Science-Collaboration. An open, large-scale, collaborative effort to estimate the reproducibility of psychological science. Perspectives in Psychological Science, 7, 657–660 (2012).

Google Doodle -- Leonhard Euler

This has been cross-posted to my micro-blog, Tumbld Thoughts.

Today's Google Doodle (still shot of animation shown here) is in celebration of Leonhard Euler's posthumous 309th birthday. He may be dead in the flesh, but his ideas live on [1]. He had an incredible output of coherent (and long-lived) ideas, some of which are used in technologies as diverse as aircraft design, global positioning systems, the design of virtual (computer) interfaces, and holographic design [2].

NOTES:

[1] For those who are unfamiliar with his work, he's postage stamp worthy (see above image). This used to be a big deal. Perhaps in Europe it still is.

[2] Mathematical and physical tools such as Euler angles and Euler's disks (here is video demo of Euler angles in the context of a phenomenon called gimbal lock and Euler disks in the context of holographs).

Richard Gordon, Transmogrifying from Virtual to Physical, Brought us Bits of Embryogenesis

I was honored to be able to bring Dr. Richard (Dick) Gordon to the Michigan State campus for a seminar on April 9 (see video on Vimeo). Currently at the Gulf Specimen Marine Laboratory (and retired from the University of Manitoba), Dick is a theoretical development biologist of the highest caliber [1]. He gave a talk entitled "Cause and Effect in the Interaction between Embryogenesis and the Genome" [2]. He even brought toys [3] to illustrate his theory of cellular differentiation.

Dick's virtual world avatar (Paleo Darwin) is seated in the middle picture.

Dick Gordon, master collaborator.

The theoretical model he presented suggests that differentiation waves [4] pulse through the embryo during development, which set up spatially-restricted gene expression and differentiation into distinct cellular types. According to this view, each cell's differentiation is a binary and recursive process (e.g. one "decision" point building upon another), and is contingent upon the cell's position and environment. In this sense, higher-level organization (e.g. modules) are not caused by gene expression. Rather, gene expression changes that lead to observable phenotypic modules [5] and other patterns are caused by the extracellular environment of a developing organism.

An example of a Wurfel toy, taken from a slide in his talk. A fine example of Canadian innovation.

There were many profound moments in this lecture. An overarching theme of the talk was how candidate ideas (e.g. hypotheses) are tested, implemented, and critically examined in the course of doing science. One of these was the "organizer" experiments of Hans Spemann [6], in which a piece of tissue transplanted to an embryo can induce the formation of a second animal. Subsequent experiments have shown that while transplanted tissue accomplishes this, other transplanted materials (even some which are non-organic) can induce this response as well. Perhaps the effect is not due to the tissue itself, but the hydrophobicity or hydrophilicity of the materials transplanted. This might be characterized as a special case of Type I error due to incomplete experimental information [7].

Picture of Hans Spemann (inducers).

Another candidate idea presented was Alan Turing's notion of "morphogens". Morphogens are hypothetical molecules proposed by Turing to drive pattern formation in a developing organism [8]. According to the talk, morphogens are not the causal factor for morphogenesis, nor are genetic regulatory cascades. Instead, they are both driven by expansion and contraction waves that course through the embryo. These waves (which have been observed) also trigger the mechanisms of differentiation (e.g. signaling molecules and gene expression changes) in cells. A good example of the problems related to establishing causality in a complex systems.

Picture of Alan Turing (morphogens).

Time-course (and illustration) of differentiation waves moving across an embryo from the talk.

After the talk, Dick and I discussed the possible role of differentiation wave-like activity in the process of in vitro (or perhaps even in vivo) cellular reprogramming (the controlled phenotypic transformation of a cell from one phenotype to another). Interesting stuff, and as always, you are welcome to participate in the Embryo Physics course [9], which is made possible by a fine group of people. Please contact myself or Dick if you are interested in presenting.

The scene of the crime, so to speak. Some quiet moments before my virtual lecture (Scenes from a Graphical, Parallel Biological World) given in April, 2012.

NOTES:

[1] He was originally trained in chemical physics at the University of Oregon (home of the Oregonator). See his Google Scholar profile for more information. According to their records, he has a h-index of 32 (which is quite impressive). He also has an Erdos number of 2i (long story).

Animation of the Oregonator (activator/inhibitor system). COURTESY: Scholarpedia.

[2] Here is a link to the version of this talk (.pdf slides) presented in the Embryo Physics course on March 20, 2012.

[3] One of these was a Wurfel, which is a bunch of wooden blocks joined together with an elastic string. I own one of these, and before this lecture I had no idea as to its name!

The Wurfel was used to demonstrate the configurational constraints and opportunities afforded to the genome due to a cell's biophysical and epigenetic context. For more fun (and combinatorics) with puzzles, please see the following blog post: Puzzle Cube. Paleotechnologist blog, August 31 (2011).

[4] According to his talk, these may either be calcium waves or something functionally similar. For an introduction to embryonic calcium waves (and how to image them), please see:

Gillot, I. and Whittaker, M.   Imaging Calcium Waves in Eggs and Embryos. Journal of Experimental Biology, 184, 213–219 (1993).

[5] Here is a video from Jeff Clune (University of Wyoming) demonstrating how modularity might have evolved using the software platform HyperNEAT (evolutionary neural networks). Based on the following paper:

Clune, J., Mouret, J-B., and Lipson, H.   The evolutionary origins of modularity. Proceedings of the Royal Society B, 280, 2012-2863 (2013).

[5] Here is a YouTube video that explains Spemann's organizer experiments in more detail.

[6] This fits very much within the scope of the Hard-to-define-Events (HTDE) approach. For more information, please see the HTDE 2012 workshop website.

[7] Here are some examples of morphogenesis (sensu Turing) the morphogen concept modeled using the Gro programming language (from the Klavins Lab, University of Washington).

The morphogen concept was some of Turing's later work. Even though Turing was a computing pioneer, his coupled reaction-diffusion model of chemical morphogenesis have become a prevailing view of how developmental morphogenesis proceeds. However, these ideas are also useful in the computational modeling of textures. See Turing's classic paper for more information:

Turing, A.M.   The Chemical Basis of Morphogenesis. Philosophical Transactions of the Royal Society of London, 237 (641), 37–72 (1952).

[8] While not formally a MOOC, the Embryo Physics course is an example of distributed learning. For more information, watch for the forthcoming paper:

Gordon, R.   The Second Life Embryo Physics Course. Systems Biology in Reproductive Medicine, x(x), xxx-xxx (2013).

Games, Noise, and Science-related Obscure References

This is being cross-posted from my micro-blog, Tumbld Thoughts:

First off, here are my notes on "games with noise", a follow-up on a previous Synthetic Daisies post called "Makin' Pha-ses". This approach bears some similarities to the move by nature approach to games and games played with incomplete information.

Next are some art and games inspired by physics and what's on the edge of the unknown. First up is the painting "Black Hole", which is photography by Fabian Oefner. Interesting parallels between the way these images came out and the structure of a Hurricane (see inset for image of Hurricane Isabel). HINT: same physical processes at work -- "Black Hole" was painted by harnessing the power of centripetal force.

By the power of free association, I bring you the Atari video game "Tempest". The game is actually not based on a black hole (of the cosmic variety), but was inspired by a dream about monsters emerging from a hole in the earth. Nevertheless, the Larry Fleinhart character (fictional cosmologist) from the TV show "Numb3rs" seemed to take inspiration from its cosmological resemblance.

Finally, here is some simulated and fictional relativity, courtesy of the Physics arXiv blog (MIT Technology Review) and Wired.

The first article in from the Physics arXiv blog on a new paper that uses in situ visualization (inspired by movie special effects techniques) to compress data in exascale (very large -- 10^18 flops per second) simulations [1].

The second is an article from Wired (Underwire feature) on the Kessel run (of "Star Trek" fame), and how the Millennium Falcon would have to go faster to light speed to achieve it [2].

NOTES:

[1] Specifically, the bullet time scene from "The Matrix". Paper: Kageyama, A. and Yamada, T.    An Approach to Exascale Visualization: Interactive Viewing of In-Situ Visualization. arxiv:1301.4546.

[2] Hill, K.    How the Star Wars Kessel run turns Han Solo into a time-traveler. Wired Underwire blog. February 12 (2013).

This is arcane territory, even for me. Finally, there's a comprehensive explanation for how a "parsec" can be used a unit of time rather than a unit of distance.

Carnival of Evolution, #58 -- Visions of the Evolutionary Future

Welcome to Carnival of Evolution! Now with albedo!

What does the future look like? For some, the future is the place of constant progress and a place where dreams become reality. For others, the future is a scary, dystopian place. When actualized, however, future worlds fall somewhere in between these two visions. Can we make accurate projections about the future? As I pointed out in a Synthetic Daisies post from February [1], futurists and technologists have a pretty dismal track record at projecting future scenarios, and often get things notoriously wrong.

UPPER LEFT: Ad from the 1982 opening of EPCOT Center, Florida. UPPER RIGHT: Dystopic future city from the movie "Idiocracy" (Inset is the cover of "Future Shock" by Alvin Toffler). BOTTOM LEFT: Bank of England Economic Forecast (circa 2011). BOTTOM RIGHT: New New York, circa 3000 (from the TV show "Futurama").

With visions of the future in mind, this month's Carnival of Evolution (#58) theme is the future of evolution. While a significant component of evolutionary biology involves reconstructing the past [2], we are actually (with error, of course) also predicting the future. Yet can we do any better than futurists or technologists? It is hard to say, and if you have opinions on this I would be glad to hear them. However, this month's CoE will address five themes that may (or may not) help us understand where the complexity of life is headed.

A new academic discipline: prospective phylogenetics?

PART I:  The future of evolution is an open book.

Some depictions of future evolution involves both "speculative evolution" and "hyperevolved" creatures [3]. The work of Dougal Dixon [4] is a nice introduction to this point of view. His work ties together science fiction allegory with a functional view of phenotypic evolution to "project" the following future taxa: the engineered pack animal (5 million years from now), the aquatics (50,000 years from now), the tic (1,000 from now with help from engineered soft materials), and the symbiont carrier (10,000 years of coevolution). All of these examples are, of course, based on fictitious forms. And the rate of evolutionary change bears no relationship to known examples of evolution. Nevertheless, these conceptions highlight the role of chance in evolution. One can see parallels (and discrepancies) with this animation of whale evolution.

Here are some posts that provide some scientific fact to inform our speculations about what future evolution might look like:

* Carl Zimmer from the Scientific American blog Phenomena discusses the concept of and hype surrounding "nightmare bacteria". The nightmare in question is the rise of antibiotic-resistant bacteria, about which the post covers in detail.

* Sorting out Science brings us more installments in their "Scientific Tourist" series. Featured this month are the pilot whale and saber-tooth cat. And David Morrison from Genealogical World of Phylogenetic Networks brings us tattooed representations of the scala naturae, or the progressive evolutionary ladder (as opposed to the more realistic branching bush) model of evolution.

A scala naturae conception of future evolution (this time involving robots). COURTESY: Machine Overlords and John Long's "Darwin's Devices".

* Teaching Biology blog features an educational slideshow on Lamarckism, the scala naturae, and its intellectual precedents. In addition, we have two posts this month by Zen Faulkes, who writes at Neurodojo: the first is on the misinterpretation of Charles Darwin's writings as "emotionless" (No, Darwin was not a Robot), and the other is on a new paper that focuses on tail morphology to bring taxonomic clarity to the genus Xenagama.

* Good projections of speculative evolutionary trajectories rely on good estimates of genomic function. Whether the ENCODE project accomplished this for the human genome has been hotly debated since their results were published in Nature late last year. I have posted some slides to Tumbld Thoughts on the debate and scientific reasoning surrounding the latest set of ENCODE results. These slides serve as a new section to my Evolutionary Systems Biology course.

* There are two more in-depth critiques on ENCODE this month. Ken Weiss from Mermaid's Tale focuses on a new paper called "On the immortality of television sets: “function” in the human genome according to the evolution-free gospel of ENCODE" [5]. Both Ken's post and the paper critique the ENCODE projects results on several grounds. And Larry Moran's blog Sandwalk features W. Ford Doolittle's critique of the ENCODE project, which is one of four papers that critically address the claims made by the ENCODE group.

* To put this all in further perspective (Functional Illiteracy and Genetic Background), Anne Buchanan from Mermaid's Tale points us to a new paper in Trends in Genetics [6] on genomic function in the context of genetic backgrounds, which should serve as a nice addition to the ENCODE debate over genomic function. And as a case in point, we have a  post by Jeremy Yoder writing on the blog Denim and Tweed, who critically examines (he calls it a "false discovery") a recent article on how one's genetics may predict whether or not they will attend University. 

Visions of the Neozooic Era (COURTESY: Alexis Rockman). Artnet profile.

Finally, here are a few posts from Mermaid's Tale that might allow us to think about our explorations of future evolution in a more critical manner. Dan Parker brings us "Evolution in a Terrarium", which is an essay about the coevolutionary relationships between human civilization and mosquitos. Anne Buchanan discusses the "Ifs" of natural selection, which involves a critical assessment of what it means for a trait to be naturally selected and what the potential outcomes of natural selection might be. And Holly Dunsworth discusses the caveats and potential for thinking about the outcomes of evolution and other natural processes in an Anthropomorphized manner (a.k.a. the personification of nature).

PART II:  Future possibilities as phenotypic space.

Another depiction involves using a top-down design method to understand forces of natural selection. The video game Spore provides an example of this type of top-down design. While this is an example of "naive evolution" [7], it does provide a conceptual mechanism for future phenotypes.

Above are a collection of "animal: forms from the video game Spore. In Spore, phenotypes are determined in a top-down fashion, but live in a world of "naive" ecology and evolution. They still exhibit a form of (non-Darwinian) descent with modification.

While the creatures in Spore open up the possibilities of phenotypic space, they are not all that plausible as models of biological processes. Perhaps when projecting into the future, plausibility is as much a conceptual roadblock as it is a biological one. In light of this, Jean Flanagan from Sci-Ed discusses the dangers of taking shortcuts during the process of communicating evolution. This includes overcoming the default use of naive models to fill in conceptual gaps.

So perhaps we can construct imaginary phenotypes that are a bit more consistent with molecular mechanisms and formal evolutionary theory. We can use our imagination to build better conceptual models in cases where available data is limited or sparse. In a Synthetic Daisies post from last month (Plausibility and de navitus Models of Complex Systems), I have sketched out the means to solve this problem using something called a de navitus model, which combines naive (e.g. common sense) theories of natural phenomena, machine intelligence, and artificial selection techniques.

* Continuing with the theme of simulated evolution, the BEACON Center blog profiles some work being done by Cory Kohn at Michigan State (Testing Phylogenetic Inference with Experimental Evolution), who uses digital evolution (the AVIDA platform) to better understand the relationship between phylogenetic inference and lineage recombination.

* Carl Zimmer from Phenomena brings us another post (Watching Bodies Evolve), this time on the experimental study of evolutionary transitions. This involves replicating the evolution of multicellularity in a yeast model. The post reports on a recent publication [8] by William Ratcliff and Michael Travisano (among other co-authors), and features a number of nice microscopy images.

Besides the use of virtual worlds and experimental methods, we might also use LEGO kits and other types of physical models to represent possible phenotypes. Below is an entry in the MOCathalon by Sean and Stephanie Mayo, featuring a number of existing invertebrate species. This approach can be leveraged for our purposes by building on the work of Mark Changizi, who observed a scaling law that is shared between LEGOs and the natural world [9].

* The So Much Science Tumblr brings us Phylo: the trading card game, which looks like a potential exhibit at next year's Comic-Con. Build a collection of your favorite species, or create new ones. And Prehistoric Taxonomie (another Tumblr blog) features excellent scientific illustrations of Moschops capensis, a herbivore from the late Permian.

* A consideration of future evolutionary trajectories also requires us to consider potential mechanisms behind such changes. Joachim Dagg from Mousetrap brings us a host of posts on evolutionary maintenance, which mediates the relationship between sexual reproduction and heritable variation. He provides both a short introduction to the set of relevant issues ("A very short history of evolutionary maintenance problems"), and follows up with two specific examples ("DNA repair as a cooperative venture" and "Males and the maintenance of sex"). Blake Stacey from Science after Sunclipse brings us a short reading list on Evolutionary Dynamics. Finally, Tim Eisele from The Backyard Arthropod Project brings us a post on The Origin of Insect Wings.

PART III:  What are the historical contingencies (or time-dependencies)?

Yet another depiction involves projecting future evolutionary constraints. How will existing evolutionary constraints produce diversity into the future, or how will new constraints arise in conjunction with future events? These projections can be made in a number of ways, but here we will focus on biogeography. Specifically, how will the present and future dynamics of plate tectonics and continental drift affect the distribution of species and ecosystems many years from now? Fortunately, it is possible to build projections of future plate tectonics using geophysical data and computational models such as plate motion vectors [10].

An example of future models of tectonic drift. TOP: Earth, as it is projected to look in 100 million years. COURTESY: Ron Blakely at Northern Arizona State (NAU). BOTTOM: The end result of 650 million years of plate tectonics.

This month's evolution blogosphere features a number of loosely-related posts on how the categorical diversity we observe today may or may not be a product of contingencies from the evolutionary past: 

* Rob Graumans at The Young Socrates asks the question and reflects upon of why men and women exist, and why (by contrast) there are many potential genders. I assume his intent here is to engage in Socratic inquiry, which means that you should leave comments.

* Leo van Iersal, posting at Genealogical World of Phylogenetic Networks, brings us a discussion about the topological restrictions posed by how phylogenetic networks are configured. For example, what are the consequences of making a phylogenetic tree in different ways: rooted using a single taxon, acyclic lineages, or time-consistent lineages? And when any given model is consistent with the underlying biology [11], then what is the effect on that particular set of phylogenetic relationships? Another post from the same blog (this one by David Morrison) follows up on this by discussing partially-directed phylogenetic networks that rely on first-degree relationships.

The "escape and radiate" model of coevolution, which describes the coevolution of plant (left phylogeny) and insect (right phylogeny) macroevolution. COURTESY: Figure 1 in [12].

* Jeremy Yoder, this time writing at Nothing in Biology Makes Sense reminds us that there are a lot of potential phylogenetic tree topologies in a single species' genome. This argument is based on the notion of a consensus tree, or what happens when you put many different traits (with different evolutionary histories) together in the same tree. The resulting paper, focusing on genomes from the legume genus Medicago and forthcoming in the journal Systematic Biology, is now available online.

Another way to critically examine historical contingencies is to study macroevolution, or evolution over long periods of time (e.g. millions of years):

* The BEACON Center blog features an interview with Luke Harmon, who reflects upon the macroevolution and its role in producing evolutionary changes. These changes and their contingencies have in large part determined what modern variants (e.g. phenotypes) look like. This has particular relevance to the study of digital evolution, which captures the essence of macroevolutionary trends.

* The BEACON Center blog also features a profile of Zachary Blount's work in the area of E.coli experimental evolution, in which he describes the process of discovering of a new species. In this case, a directly-observed novel physiological adaptation (citrate metabolism) is evaluated in the context of several species concepts (e.g. biological and ecotype).

* PZ Myers from Pharyngula wins the bad joke of the month award (What's Jimmy Walker's favorite arthropod? Tri-lo-bite!). Topic: a mini-review on trilobite anatomy and phylogeny.

* The Molecular Ecologist features a post by Dylan Goldade, Kathryn Theiss, and Chris Smith on new simulation work that demonstrates the role of ecological speciation in the evolution of species [13]. This is accomplished via a review of works by Ernst Mayr and classical population geneticists. 

PART IV:  Behavioral invariants vs. evolution of intelligence.

The final depiction we will discuss here is the future of behavioral change and the evolution of intelligent behavior. Changes in behavior such as migration patterns or foraging behaviors might be observed as a consequence of climate change [14]. However, behavioral repertoires themselves might undergo future evolution, perhaps resulting in evolved intelligence [15]. One way to address this issue is to look to the evolutionary past, and find "invariant" (or recurrent) behaviors that might shape possible evolved behaviors (or their constraints) in the future.

Examples of the using the past to inform the future. Picture at left is adapted from Figure 1 in [16], and picture at lower right is taken from Neanderthal Man (Caroline Chronicles Tumblr post).

There are a number of behavior-related posts this month:

* Matthew Cobb, writing at Why Evolution is True, posts on why animals do not detect radio waves. This sounds like a strange question, unless you realize that plants and animals use the electromagnetic spectrum quite extensively for functions such as energetic inputs and sensation. According to physicists Tommy Ogden and Tim O'Brien, radio waves are too low-energy and have too long a wavelength to be useful for these purposes.

* This Week in Evolution brings us a linkfest entitled "Copying in birds, dolphins, and viruses; evolution and

environmental change; evolution of mutation rate". The reposts featured within include content on learning and alarm call copying in birds, vocal copying and individuality in dolphins, and adaptive immunity in viruses.

* Jason Collins from Evolving Economics presents some quotes from R.A. Fisher's classic "The Genetical Theory of Natural Selection" on the evolution of human exchange and economic markets. The passages are interspersed with critical observations.

* Writing about mixed-species (or heterospecific) social groups, Felipe Dargent from Eco-Evo-Evo-Eco: Eco-Evolutionary Dynamics (Mixed-species groups – everything is about predation... or isn’t it?) presents a hypothesis and evidence as to why they form and what purpose they serve.

* Discussing the recently-published book "Paleofantasy" [17], John Hawks brings us his perspectives on the popular misconceptions and pseudoscience surrounding paleolithic-era human culture, collectively referred to "paleo-advice" (e.g. paleo-diets, paleo-child rearing, etc). And here is a post (Paleo and Woo) from Respectful Insolence which goes into even greater detail about paleo-pseudoscience.

* In keeping with the our past-can-inform-the-future theme, PonerologyNews brings us a feature on possible evolutionary scenarios for the origins of human psychopathy, and how it might be an example of a spandrel (or exaptation) in the human brain.

The right way (top, bottom) and wrong way (inset) to think about how organisms use the electromagnetic spectrum.

PART V: Future Analytical Tools.

A bit beyond the scope of this presentation but nevertheless important is the future of data integration and analysis. Recall that our knowledge of evolution is based in part on reconstruction of the past. Therefore, tools that provide better reconstructions of the past (and present) can inform our projections of the future

A recent post by Jonathan Eisen from Tree of Life blog (The gurus predict the future of evolution) reviews a recent paper called "Evolutionary Biology for the 21rst century" [18]. The authors propose an approach called "BioDiversity Informatics", which leverages computational infrastructure and data aggregation to address issues such as sustaining biological diversity in the face of climate change or the evolutionary origins and trajectory of disease.

In the spirit of BDI, Michael Harvey at Nothing in Biology Makes Sense presents a discussion of natural history in the -omics era, which bridges the worlds of traditional fieldwork and the availability of high-throughput data.

* Taking a slightly different perspective, John Hawks' blog ("The Neandertal Treatment") brings out attention to a recent NatGeo article on the potential use of whole-genome sequence data to clone something called a "neo-Neanderthal". This would be a real (if not far-fetched) opportunity to learn about the future through understanding our common ancestry. But let us suppose that a Neandertal were cloned tomorrow: Brian Switek at Phenomena has a post on "The Promise and Pitfalls of Resurrection Ecology", which is a critical evaluation of bringing extinct species (e.g. ice age megafauna) back to life.

Scenes from science in a possible 31rst century: is the future in 8-bit resolution? COURTESY: "Futurama" episode Reincarnation.

That's all for this month's edition. Hopefully this has provided us with plenty of entertainment and food for thought. So what does the future hold? Subsequent editions of "Carnival of Evolution"? If you administer a blog and are interested in hosting the Carnival of Evolution (happens every first of the month), please contact Bjorn Ostman. And why continue to blog about evolution? Razib Khan has a good post on this topic at Gene Expression (his answer: because you can!).

Finally, I have provided a printable, citable version of this Carnival edition on Figshare (doi:10.6084/ m9.figshare.661698) for those who are interested. I previously hosted CoE #46: The Tree (structures) of Life, which has been published on Figshare as well. Please let me know if you intend to use these for teaching or other purposes.

NOTES:

[1] Alicea, B.  Projective Models: a new explanatory paradigm. Synthetic Daisies blog. February 1. 

[2] For an introduction to phylogenetic construction, please see: Harrison, C.J. and Langdale, J.A.   A step by step guide to phylogeny reconstruction. The Plant Journal, 45, 561-572 (2006).

[3] Ward, P.   Future evolution. Times Books, New York (2001).

For more information, please also see the Discovery TV series "The Future is Wild", and the Speculative Evolution wiki.

[4] for more information, please see Dougal Dixon's website.

[5] Graur, D., Zheng, Y., Price, N., Azevedo, R.B.R., Zufall, R.A., and Elhaik, E.   On the immortality of television sets: “function” in the human genome according to the evolution-free gospel of ENCODE. Genome Biology and Evolution, doi: 10.1093/gbe/evt028.

[6] Chandler, C.H., Chari, S., and  Dworkin, I.   Does  your gene  need a background check? How genetic background impacts the analysis of mutations, genes,  and  evolution. Trends in Genetics (2013).

[7] For information on how this approach can be misused, see this Sandwalk blog post ("Spore and Evolution") from 2008.

[8] Ratcliff, W.C., Pentz, J.T., and Travisano, M. (2013). Tempo and Mode of Multicellular Adaptation in Experimentally-evolved Saccharomyces cerevisiae. Evolution, doi:10.1111/evo.12101.

Example of a yeast proto-colony.

There is also a related paper published in 2012 by the same group: Ratcliff, W.C., Denison, R.F., Borrello, M., and Travisano, M. (2012). Experimental evolution of multicellularity. PNAS, 109(5), 1595-1600.

[9] Changizi, M.A., McDannald, M.A., and Widders, D.   Scaling of differentiation in networks: nervous systems, organisms, ant colonies, ecosystems, businesses, universities, cities, electronic circuits, and LEGOS. Journal of Theoretical Biology, 218(2), 215-237 (2002).

[10] If you are interested in how these animations were produced, here is a link to the calculation of plate motion vectors and estimation of relative plate motions. Overall, the forecast for the (deep) future is for fewer continents, with an 50-100% chance of eventual engulfment by a red giant Sun. Hopefully, this does not ruin your day.

[11] For an example, please see: Lerat, E., Daubin, V., and Moran, N.A.   From Gene Trees to Organismal Phylogeny in Prokaryotes:The Case of the γ-Proteobacteria. PLoS Biology, 1(1), e19 (2003).

[12] This is a nice review on plant-insect macro-coevolution: Futuyma, D.J. and Agrawal, A.A.   Macroevolution and the biological diversity of plants and herbivores. PNAS, 106(43), 18054-18061 (2009).

[13] Flaxman, S.M., Feder, J.L., and Nosil, P.   Genetic Hitchhiking and the Dynamic Buildup of Genomic Divergence During Speciation with Gene Flow. Evolution, doi:10.1111/evo.12055 (2013).

[14] Western, D.   Human-modified ecosystems and future evolution. PNAS, 98(10), 5458-5465 (2001).

[15] For a simple primer on how behavior evolves, please see this short article: McGlynn, T.   How Does Social Behavior Evolve? Nature Education Knowledge, 3(10), 69 (2012).

For a more speculative projection specific to humans, please see this story: Owen, J.   Future Humans: four ways we may, or may not, evolve. National Geographic News, November 24 (2009).

[16] O'Leary, M. et.al   The Placental Mammal Ancestor and the post-K-Pg radiation of placentals. Science, 339, 662 (2013).

[17] Zuk, M.   Paleofantasy: what evolution really tells us about sex, diet, and how we live. W.W. Norton (2013).

[18] Losos, J.B. et.al   Evolutionary Biology for the 21st Century. PLoS Biology, 11(1), e1001466 (2013).