Saturday, December 25, 2010
First, Rich has been writing regularly for "Anole Annals" (http://anoleannals.wordpress.com/), which is a great new web-log created by Jonathan Losos and devoted entirely to the wonderful adaptive radiation of Anolis lizards, made famous in evolutionary circles by Ernest Williams and Losos himself. If you find it hard to believe that Anolis can single-handedly sustain a regular web-log, then let Losos, Glor, and regular "Anole Annals" contributors Luke Mahler, Manuel Leal, and Yoel Stuart try to prove you wrong.
Second, I recently started blogging about my R phylogenetic development activities in a separate blog on phylogenetic comparative biology (creatively entitled: "Phylogenetic tools for comparative biology", and located at http://phytools.blogspot.com). Since I started programming in R only relatively recently, this might interest both novice users and experienced R junkies alike. It is also designed to complement my newly created beta test version distribution page, which features the R source code for a growing list of R phylogenetics functions and methods that I have been working on.
Please check out these new blogs, but remember to come back to Dechronization because we promise that blogging here will resume here very soon!
Tuesday, November 16, 2010
To most practicing systematists, Goodman was best known as the long-time editor and chief of the journal he founded nearly 20 years ago: Molecular Phylogenetics and Evolution. In a prescient editorial published in the first issue of MPE in 1992, Goodman discussed the rapidly expanding body of molecular phylogenetic data and the need to provide an outlet to "help disseminate the results of these molecular studies." Even though DNA sequence data existed for only a few loci sampled from a small number of taxa in 1992, Goodman recognized that "the genie is out of the bottle." Goodman ended his founding editorial noting "We are at the threshold of a new age of exploration that promises to greatly increase our knowledge of the history and ongoing evolution of the ramifying lines of life. It would be gratifying if Molecular Phylogenetics and Evolution became the journal of this age."
Rest in peace, Morris Goodman, no other journal has published more molecular phylogenetic trees over the past 18 years than MPE.
Wednesday, November 10, 2010
Tuesday, November 9, 2010
Although often viewed with some mixture of confusion and frustration, a well thought-out broader impacts section is critical to any proposal being submitted to NSF. Are you a cynic who views broader impacts as little more than an obstacle standing between you and your research? If yes, get over yourself. The way you and your science interact with the rest of the scientific community and society at large deserves your attention. That said, expectations for the broader impacts of a DDIG are commensurate with the relatively low amount of funds they involve (relative to the much larger amounts your PI is likely to be applying for). Your PI may be starting a high school science program as part of her grant, but you shouldn’t feel compelled to go to such lengths in your DDIG. What then should you include in your broader impacts? Most proposals include some mention of one or more of the following broader impacts, many of which are likely to be coincident with your primary research objectives.
1. Undergraduate research opportunities (i.e., ‘training’ undergraduates by having them slave away on your project). This is a no brainer. Everybody wins when you get undergraduates involved in your research. This will be all the more convincing if you can include some ‘preliminary data’ showing that you already have experience recruiting and mentoring undergraduates.
2. Dissemination of data and results on the interwebs. You’re going to put your data online anyways, so why not take some credit for it?
3. Conservation significance. Conservation is a noble goal, but try to avoid vacuous statements like “The group I’m studying including some species of conservation concern.”
4. Outreach to the broader community. Often in the form of a museum exhibit or public presentations. Be creative here – visit a school, give a “keynote” at a science fair, etc., but make sure reviewers aren’t left feeling like you’re not going to follow through.
Monday, November 8, 2010
Thursday, November 4, 2010
The point of sharing this information is this: to get a DDIG you need to write a proposal that will impress a potentially diverse group of three practicing systematists.
Tuesday, November 2, 2010
This time of year just about every PhD candidate in systematics who doesn’t already have one is working on a proposal for one of the NSF’s lucrative Doctoral Dissertation Improvement Grants. The DDIGs are one of the smartest ideas the good folks at NSF have ever had, and represent a critical source of funding for ambitious and independent young systematists. The sad fact is that there aren’t many other grants available to graduate students that offer the type of $10,000+ windfall that can be essential to making a good thesis a great thesis. Although the program is incredibly popular, some find the application process a bit mysterious. The NSF’s formal guidelines certainly provide you with all the basics, but they’re also somewhat open ended.
How one can best prepare a competitive proposal? Although there aren’t any foolproof answers to this question, I’d like to share a few suggestions I’ve developed for my own graduate students. These suggestions, which undoubtedly reflect my own personal biases, are being made on the basis of having read previously successful (and unsuccessful) proposals and discussions with NSF reviewers who have been involved in evaluating these proposals. I’m going to kick things off in this first post with some basic advice on organizing your proposal, followed by subsequent posts on how proposals are reviewed, how best to incorporate preliminary data, how much methodological detail to include, and how to effectively discuss broader impacts.
A good proposal begins with good organization. There are lots of ways to organize a successful proposal, so how you choose to organize yours is a personal decision that requires lots of careful thought. That said, one general organizational feature that tends to characterize successful proposals is the use of a strong hypothesis testing framework. Think of this as getting back to basics: remember how your freshman biology lab reports started by outlining the specific hypotheses you tested? Doing the same here is going to help your reviewers understand exactly what you are trying to accomplish with your work, while at the same time helping you organize the remainder of your proposal.
Instead of making vague claims like “I will investigate the biogeographic history of midges”, try to make a more specific statement like “I will test the hypothesis that the distribution of midge diversity is a consequence of a vicariant event associated with the uplift of the Andean plateau.” Distilling your work into a few explicit hypotheses can feel a bit constraining when your real goal is to understand why midges are so darned diverse, but being explicit about specific hypotheses does not preclude you from following up on other interesting results that might be somewhat peripheral. You need to provide some context for your hypotheses before introducing them, but try to get to them as soon as possible; your reviewers shouldn’t be able to get past the first page of your proposal without being provided with a concise statement of the questions you intend to address. Try to restrict yourself to a manageable number of hypotheses (things get a bit out of hand when proposals try to juggle a half dozen or more hypotheses, for example). Organize the remainder of your proposal (e.g., methods, discussion, preliminary data) around the hypotheses presented on the first page of your proposal. Make sure that your work can feasibly address each of your hypotheses.
Thursday, October 28, 2010
One concern raised and discussed by the authors is that the domestication and utilization of cattle (a proposed disease vector for TB) roughly coincides with the progress of urbanization in the region. They argue that we can reject this model because correlation is weaker than in the urbanization model; however, in my mind this argument falls short of persuasiveness because (as they admit) the history of cattle domestication for many of their populations is poorly known. This type of error would obviously also have the effect of depressing our perceived correlation between cattle domestication and genetic TB resistance.
Nonetheless, this is a very interesting study. If the result holds up to future scrutiny, then this will no doubt have many relevant human health implications and the study should be broadly cited.
Tuesday, October 26, 2010
Friday, October 22, 2010
According to this method, the authors first obtain an ultrametric phylogenetic tree for the species in their study. They then generate a set of stochastic character histories (Nielsen, 2002; Huelsenbeck et al., 2003) for the discrete character of interest. Example discrete characters might be a "life history trait, morphological feature, or habitat association" - in their empirical test they examine halophilic and freshwater Daphnia species.
Now armed with a distribution of possible character histories on their estimated phylogeny, the authors simultaneously maximize the likelihood of their sequence evolution model and a scaling factor r, a parameter that increases or suppresses the rate of molecular evolution along stochastically mapped branches in the tree. Then they average across character maps.
In an extremely clear analysis of their method, the authors show it capable of producing remarkably good estimates of r for trees with even a modest number of tips (e.g., 20-60) when the true underlying phylogeny is known without error (Figure panel A). Under these idealized circumstances, estimation of r is only slightly biased for small numbers of species - as is common for maximum likelihood methods.
The situation is slightly more complicated when an estimated phylogeny (rather than the true underlying tree and branch lengths) is used. Here, they show that estimation of r can be quite severely downwardly biased, particularly for large values of r (Figure panel B). They think that this is actually due to error in the ultrametricization of their phylogenies - since in their study they used the same data for phylogenetic inference as they do for the estimation of r. This problem is not at all ameliorated for ultrametric phylogenies obtained by Bayesian relaxed clock methods. In the end, this issue argues strongly for the simultaneous estimation of the phylogeny, the character history, and the concomitant variation in nucleotide substitution rates - something that the authors also recommend.
Monday, October 18, 2010
Wednesday, October 13, 2010
Especially given Rabosky's (2010) main result - that is, the high sensitivity of extinction rate estimates to certain model assumptions - the new study by Wertheim & Sanderson is particularly intriguing. Although these methods typically assume that the tree and branch lengths are known without error, Werheim & Sanderson demonstrate in their study that diversification rate estimates are not particularly sensitive to phylogenetic errors either in branch length or topology. In fact, they note in the abstract that even a "crude estimate" of the tree provides substantially more power (e.g., 1.6 x more for the conditions of their study) than, for instance, a comparable non-phylogenetic method, the widely used Slowinski-Guyer test (Slowinski & Guyer 1993; Am. Nat.).
Considered together, these two studies remind us that the robustness of a given statistical method cannot be illustrated by a broad brush. Rabosky's study shows that the estimation of extinction rates from phylogenies of extant species is quite sensitive to the underlying assumption that speciation rates are constant throughout the tree. Conversely, Werheim & Sanderson show that the estimation of speciation rate is not sensitive to the underlying assumption that the phylogenetic tree and branch lengths are known without error - and, furthermore, that even a "crude" tree will do.
Note that the figure above is from neither study - but from my 2005 paper (with Dechronization bloggers Harmon & Glor) about the sensitivity of diversification rate estimates to model parameterization. (We found it to be high.)
Friday, October 8, 2010
The author awards SEK 10,000 to the first who provides an analytical form of φ.
Friday, October 1, 2010
Friday, September 17, 2010
This month's "Evolution" is a good one (even aside from the great choice of cover art), with a number of blog-worthy articles. Look for more Dechronization posts soon.
Tuesday, August 31, 2010
Thursday, July 29, 2010
Tuesday, July 6, 2010
This has been the scene on my front lawn for the past few evenings. Basically, every day in the late afternoon a large swath of ants - not going anywhere in particular or consuming any resource that I can detect - seems to form in the same general region of my front yard in Durham, North Carolina. When I get up to run in the morning and the yard is shaded, they are still there; but as soon as the hot summer sun hits the front lawn they have disappeared. In the evening, when the lawn is again shaded, sure enough - they reappear. Any comments on this peculiar phenomenon are welcome!
Tuesday, June 29, 2010
Monday, June 28, 2010
I also saw a fantastic talk by Jeanne Robertson about courtship and aggressive behavior in dark and white sand dwelling lizards. White sand dwelling lizards have evidently evolved light colored dorsal coloration, obviously for crypsis. However, perhaps even more interestingly, in staged encounters white sand males nearly as often tried to court dark sand males as they tried to fight them. The confusion was one way, however, and Jeanne provided some excellent video of a dark sand male attacking a confused, and simultaneously courting, white sands individual. This unusual tendency is apparently due to a pleiotropic effect that dark dorsal coloration appears to have on ventral patch size - an effect that makes their ventral patches of dark sand males not much larger than the analogous patch on white sand females. So, as Jeanne so elegantly put it in the title of her talk: in white sand lizards, "Dude looks like a lady!" (For the record, Steven Tyler of Aerosmith is pictured above because that "Dude" really does "look like a lady!")
Sunday, June 27, 2010
Friday, June 25, 2010
Monday, May 24, 2010
The authors speculate that the strong relationship between pace-of-life and longevity has resulted from antagonistic pleiotropy between artificially selected traits and life history; rather than from correlated artificial selection. This certainly makes sense in some cases. For example, it seems unlikely that dog breeders directly selected for high mortality in their lines. The ultimate source of several other among-breed correlations found by the authors is less clear, however. For instance, it is somewhat more plausible that humans may have intentionally or unintentionally selected for the observed among-breed negative correlation between body mass and activity level. In this case, the authors advance the possibility that highly active large dogs may have been selected against, because high activity would become increasingly undesirable (and destructive) in large dogs.
Whatever else we might learn from this article, it should dispel any doubt that the classic Billy Joel mantra of "only the good die young" evidently does not apply to our canine friends.
Friday, April 23, 2010
One hypothesis for the evolution of protogyny is that in many species size provides a significant advantage to the mating success of males, but has little impact on mating outcome in females. As such, any mechanism allowing individuals to start life in female form (when they are typically small), but then "mature" into males once they have achieved large size, should be favored by natural selection. This evolutionary scenario is not nearly as implausible as it sounds because teleost fish (unlike most other vertebrates whose gonadal tissues differentiate early in development) develop their sex organs from a single, protogynous tissue type. This hypothesis for the evolution of protogyny has been dubbed the "size-advantage hypothesis."
A recent study by Erem Kazancιoǧlu and Suzanne Alonzo [2010; Evolution Accepted] uses phylogenetic comparative methods to examine the evolution of size-advantage and sequential hermaphroditism in labrid fishes: also known as the wrasses. What they find is that, indeed, the evolution of dioecy (separate sexes) from sequential hermaphroditism is relatively unlikely when the size-advantage of large males is high. However, their evidence for the evolution of protogyny from dioecious species with male size-advantage was somewhat ambiguous.
Although I enjoyed this paper quite a bit, and it seemed perfect fodder for some clever fun in photoshop (actually by E. Lu, see above), I also felt that that the study had some methodologically weak areas. For instance, the authors failed to take advantage of a new phylogenetic logistic regression procedure by Ives & Garland , which seems ideally suited to their data. (In their defense, the method is brand new.) Consequently, however, the authors found themselves of the unfortunate position of using an arbitrary scoring system to estimate size-related reproductive skew: adding 1 point for the presence of "pronounced sexual dichromatism," for example, and subtracting 1 point for "alternative reproductive tactics" (which might decrease the advantage of large male size) . With a phylogenetic multivariable logistic regression, the authors could have tested for an association between the log-odds of protogyny and each of their proxies for size-based reproductive skew (which also included sexual size dimorphism, resource defense, and mate defense), while simultaneously controlling for the phylogenetic non-independence of the species in their sample.
In spite of its limitations, I found this study to be a tremendously interesting read. Due in no small part to its unusual and "sexy" subject matter, I'm sure it is destined to attract the authors considerable attention - among evolutionary biologists and lay people alike.
Wednesday, April 14, 2010
Monday, April 12, 2010
In both plants and animals, simple population genetics theory predicts that for a neutrally evolving locus the rate of substitution should be equal to the per generation neutral mutation rate, μ. Since germline cells are sequestered from somatic cells in animals, and germline cells undergo a fixed number of replications that is independent of generation time, theory thus predicts that, in animals, the rate of nucleotide substitution per unit time at a neutrally evolving locus will be μ/t, for generations of length t. However, for plants the prediction is less simple. This is because in plants, germline cells are not sequestered, but are instead derived from somatic tissue. As such, germ cells in older plants should in theory have more opportunity for somatic (and thus gametic) mutation.
This means that the concomitant increase in generation time that characterizes arborescent plants is insufficient in theory to explain the decreased nucleotide substitution rates estimated empirically. The authors suggest a number of possible alternative underlying causes for this pattern. For instance, they note that both arborescent seed trees and tree ferns might share a lower rate of somatic cell replications (as suggested by Soria-Hernanz et al. 2008). This represents a fully testable hypothesis which might (in part or in whole) account for the pattern found by the authors. Alternatively, Korall et al. (2010) propose that the duration of sporophyte/gametophyte life history stages in arborescent and herbaceous plants should also be considered. This is a difficult hypothesis to test comparatively, since all arborescent species have a relatively long sporophyte phase. It might be possible to study mutation accumulation in sporophyte and gametophyte life history stages in a rapidly reproducing species under laboratory conditions.
In spite of the numerous open questions that it leaves, this article extends the relationship between arborescence and slow rates of molecular evolution beyond the seed plants, and thus into a broader group of diverse organisms. This finding will surely stimulate considerable future research.
Saturday, April 10, 2010
On Monday, I will begin a rotating program officer position at the National Science Foundation in the Systematic Biology and Biotic Inventories Cluster. Thus, this is going to be my last post on Dechronization until my rotation is over. It has been a really great experience being part of this blog and I've met some great people because of it. Keep up the good work Dechron'ers. I'll be reading!
P.S. The photo is of a shovel-snouted lizard (Meroles anchietae), that I got to see on a recent trip to Namibia.
Friday, March 26, 2010
An increasingly popular approach in recent years has been to first estimate the γ-matrix, which contains the coefficients of stabilizing and disruptive selection on its diagonal and the coefficients of correlational selection in off-diagonal positions, and then to diagonalize γ by solving MγM'=Λ for matrices containing the orthonormal eigenvectors (M) and eigenvalues (Λ) of γ. The widely perceived advantage of this approach is one of increased power: diagonalization identifies (in its first and/or last ranked eigenvectors) the dimensions of strongest nonlinear selection; and, furthermore, it allows for more modest multiple test correction, since the number of coefficients to be tested scales linearly with the number of traits in our analysis (rather than as the square). True to form, some studies (e.g., Blows et al. 2003) have found significant nonlinear selection on the canonical axes where none was found on the original traits.
However, a recent paper by Richard Reynolds and colleagues (2010) has revealed that some of this increased power may be illusory. In particular, the standard double-regression approach for hypothesis testing of the canonical nonlinear coefficients has type I error that goes to 1.0 (i.e., very bad type I error) under pretty realistic conditions. The lower panel of the figure above, copied from Reynolds et al. (2010), shows the type I error for hypothesis tests on the canonical axes for a nonlinear selection analysis of 10 traits. In this study no selection was simulated! The authors also prove analytically that the expected eigenvalues of the estimated γ-matrix for data without nonlinear selection only go to zero as the number of samples used to estimate γ goes to infinite (obviously sample sizes in empirical studies are usually finite. . . unless, of course, you take a really, really long field season).
The implications of this result are quite significant. In particular, it means that some recently published examples of significant nonlinear selection on canonical trait axes could be type I errors. However, the authors also provide a solution. They find that type I errors contract to their nominal levels when a permutation-based hypothesis testing approach is used. (In a self-serving addendum, I'd also like to note that I independently devised and applied the exact simulation test recommended by the authors in a recently published paper - detailed here in a supplement - even though I must admit I was not at all aware of this problem at the time!)
I think this paper also reflects the fact that methods are never static, and that when new ones are devised they must be tested thoroughly - and furthermore that these tests should be conducted with both empirical and simulated data. The rise of canonical rotation in the analysis of nonlinear selection had previously not been accompanied by this level of scrutiny. Reynolds et al. (2010) provides not only a definitive critique, but also a suitable way forward.
Friday, March 12, 2010
One-tailed hypothesis tests are popular in large part because they provide increased power to reject the null hypothesis if it is false. The lower panel of the figure, right, shows the expected mean absolute value of t for a real (but small) mean difference between populations A and B, for various equal sample sizes of A and B. What it reveals is that the sample required to reject a two-tailed (rather than a one-tailed) null on average is about 50% larger, which could be expensive and time consuming if data are difficult to obtain.
However, there have been repeated articles questioning the general appropriateness of one-tailed tests. For instance, Lombardi & Hurlbert (2009) conclude that "all uses of one-tailed tests in the journals surveyed seemed invalid." Ruxton & Neuhäuser (2010) were a little more generous, but they concluded that in 17 papers using a one-tailed test, only one had appropriate justification to do so.
The problem arises from an apparently widespread belief among ecologists and evolutionary biologists that any a priori hypothesis regarding the direction of the outcome in our statistical test is sufficient grounds to justify a one-tailed null hypothesis. This is not true, but Lombardi & Hurlbert (2009) conclude that the reason for this misperception is fairly well founded, documenting bad or confusing advice regarding the application of one-tailed hypothesis tests in 40 of 52 popular statistical texts (Lombardi & Hurlbert 2009, Supplement).
In fact, a one-tailed hypothesis test is only appropriate if a large effect in the opposite direction of our a priori prediction is exactly as interesting and will result in the same action as a small, non-significant result in the predicted direction. Both articles point out some very restrictive circumstances in which this might be true. (For instance, in the example of an FDA test on a new headache drug - no positive effect and a large negative effect on the pain of test subjects will result in the same action: no approval for the drug.) However, in ecology and evolution it is quite hard to imagine circumstances in which a large, significant result in the opposite direction of that predicted by theory could easily be ignored.
Of course, there are many statistical tests (lots of them common among evolutionary biologists) to which the concept of "tailedness" doesn't really apply. For instance, we are not usually interested in whether our data fit our a priori model better than expected in a goodness-of-fit test (although perhaps we should be).
For statistical tests in which the concept of tailedness does apply, one-tailed tests generally ill-advised. Thus, their use should require substantial justification. Ruxton & Neuhäuser (2010) give two very simple grounds on which they feel a one-tailed need be justified. First, an author using a one-tailed test should clearly explain why the result in a particular direction is expected, and why it is fundamentally more interesting than a result in the opposite direction. Second, importantly the author should also explain why a large result in the unexpected direction should be treated no differently from a non-significant result in the expected direction (Ruxton & Neuhäuser ). These conditions may be rare (or, in fact, nonexistent: Lombardi & Hurlbert ) in our field.
Wednesday, March 10, 2010
Bob has made their data available via a google motion chart, which allows for easy exploration of the studies' results (embedded below):
Tuesday, March 9, 2010
A recent study in the pages of 'Evolution' has demonstrated a very high toll of reproduction, indeed. By stymieing reproduction in female Brown Anoles (Anolis sagrei, pictured right) through surgical removal of the ovaries, Bob Cox and Ryan Calsbeek at Dartmouth University have found that female interannual survival increases nearly threefold (relative to females manipulated only with a control "sham" surgery; solid bars, right). In addition to the survival advantage of non-reproduction, ovariectomized females also exhibited higher growth than control females.
Although the result is consistent with abundant life-history theory predicting a trade-off between reproduction and survival, the proximate mechanism of increased growth and survival of non-reproductive adult female anoles remains unclear. In performance trials, females whose egg burden has been surgically relieved improved dramatically in both stamina and sprint speed, suggesting that ovariectomized females might be better equipped to avoid predatory attack. However, in results presented in this year's Society for Integrative and Compative Biology meeting (and discussed in a previous blog post), Bob found that experimental manipulation of predation regime had little effect on the survival probability of sham and ovariectomized females. Perhaps ovariectomized lizards are simply better able to allocate sparse resources to fat reserves, and thus exhibit improved survival during food scarcity. Furthermore, Cox and Calsbeek acknowledge that ovariectomy removes not only the physical burden of reproductive investment, but also the source of steroid hormones - which could also affect growth and survival in lizards.
No doubt these important questions regarding proximate causes for the relationship between reproduction and survival in female anoles will be the subject of future studies.
Monday, March 8, 2010
Tuesday, March 2, 2010
Saturday, February 27, 2010
Wednesday, February 17, 2010
For years, the NSF has received many more worthy proposals than it was able to fund, resulting in a logjam of high quality proposals and stifling progress in many important disciplines. Indeed, nearly 80% of the NSF's ARRA funds went to clearing the NSF's backlog, being used to fund highly rated, but unfunded, awards that were submitted the previous year. Although those who didn't submit proposals eligible for ARRA support might feel like they've been left out, the clearing of NSF's backlog is sure to result in higher funding for proposals submitted more recently.
Short-sighted politicians are likely to find fault with the fact that the NSF ranks second to last among federal agencies in spending their stimulus funds (only $136 million of the NSF's ARRA award has been spent). The reason for this are clear - most grants from NSF are multi-year awards and are going to sit in the bank accounts of awardee's institutions as they are allocated over the years to come. This does not mean, of course, that these awards are not having an immediate impact. The bulk of the money associated with my award is going directly to salaries of PhD students and undergraduate employees. My collaborator is using his share of the funds to hire two post-doctoral scholars. Our award, therefore, will directly fund three-four full time positions and a number of additional part-time positions for the next two and half years. Perhaps more importantly than providing jobs today, our award is also contributing tremendously to training the next generation of scientists. While it may not have the same immediate impact as other worthy investments like hiring jobless construction workers to build bridges and roads, the ARRA's gift to the NSF is likely to be a gift that keeps on giving both to the academic community and the country at large for many years to come.
Monday, February 15, 2010
The photo came from this website, which has a nice interview with John about his work.
You may also see John in action in the Amazon in this National Geographic clip.
Friday, February 12, 2010
I'm spending Darwin day at Case Western Reserve University as one of several folks speaking on the topic of phylogenetics and evolution. The event's two headliners just wrapped up their talks. University of Michigan paleontologist Philip Gingerich gave an enlightening talk about evolutionary rates. Discussing a result that dates back to his famous debate with Stephen Jay Gould over punctuated equilibrium in early 1980s, Dr. Gingerich showed why the dramatic inverse correlation between rates of evolution and the interval of time over which they are measured is a simple mathematical artifact. For those interested in more on this work, Dr. Gingerich published a nice review in the Annual Review of Ecology, Evolution and Systematics. Gingerich also provided an interesting anecdote about Gould. Early in his talk today, Gingerich asked the audience how many figures were in the Origin. As any phylogeneticist knows, the answer is one: Darwin's classic illustration of the branching tree of life. Apparently when Gingerich asked this same question when Gould was in the audience Gould quickly, and incorrectly, blurted out "two!"
The other headliner today was the godfather of phylogeography, John Avise. This is the first time I've seen him speak, so it was nice that he provided a 22 point retrospective on the lessons learned from phylogeography. It's amazing to think that his first papers on this topic were published over 30 years ago now!
Thanks to Case Western's Institute for the Science of Origins for sponsoring today's event!