I’m attending the Evolution 2009 conference in Moscow, Idaho. Below are some notes from the first day. There are eight separate lecture tracks, so it’s impossible for me to see everything. I’m mostly attending lectures focused on phylogenetics, systematics, and molecular evolution. . .

This morning, I planned to hear Peter Turchin talk about “warfare and the evolution of social complexity.” Unfortunately, I missed his lecture due to an unpublished schedule rearrangement. Instead, I listened to talks on the subject on speciation. Asegul Birand presented simulations which demonstrate species’ range affects speciation rates. Marcus Kronforst characterized hotspots of genetic differentiation in Heliconius butterflies; specifically, Marcus showed that wing coloration patterns are adaptive traits that generate reproductive isolation.

Later, I attended a mid-morning session on phylogenetic methods. . .

Jennifer Riplinger (from Jack Sullivan’s lab) discussed the problem of model selection for maximum likelihood bootstrap replicates. In theory, we should perform model selection for each bootstrap replicate; in practice, most people use the same maximum likelihood model for all replicates. Jennifer examined the role of replicate model selection on CytB, 18S RNA, and COX1 sequences. Her results show that model selection for individual bootstrap replicates is unnecessary and does not yield significantly different bootstrap values. Jennifer makes a good point, but I would like to see her analysis repeated for simulated datasets, where the true phylogenetic partitioning is known. Furthermore, everyone should be careful about placing too much trust in bootstrap values (see Douady 2003).

Randal Linder presented a software tool “*SATe*” to simultaneously align sequence data and estimate phylogeny. Given the short time allowance (only 15 minutes!), I had a difficult time determining how SATe is different from ALIFRITZ or Bali-Phy. Randal used the “SP” metric to show that SATe produces more accurate alignments than ClustalW, MAFFT, MUSCLE, or Prank. I am unfamiliar with the “SP” metric, and I wonder if his analysis would yield different results if he used AMA — instead of SP — to measure accuracy.

Alethea Rea presented the “NeighborNet” method to infer phylogenetic networks (instead of trees). This approach is useful when the true evolutionary history of homologous genes involves recombinant events and/or lateral gene transfer.

Jason Evans (of the Sulllivan Lab) talked about his approach for averaging models during phylogenetic inference. Due to the short time constraint, I didn’t entirely understand his cost-based averaging method. I think integrating uncertainty about the evolutionary model is an appealing phylogenetic problem, but I need to read Jason’s publication before I can say anything critical about his particular method.

Rachel Schwartz talked about error in phylogenetic branch length estimation. Rachel used simulations to show that Bayesian branch lengths (estimated using Mr. Bayes) generally *underestimate* the true branch length, while maximum likelihood branch lengths generally *overestimate* the true length. The underestimation/overestimation bias is magnified for “deep” internal branches. In general — for a rooted tree — Bayesian branch lengths make old nodes older and young nodes younger. On the other hand, maximum likelihood branch lengths make old nodes younger and young nodes older. Overall, the bias is less-pronounced for maximum likelihood estimates, and therefore Bayesian branch lengths should probably be avoided. Rachel’s talk was robust and comprehensive, and I look forward to reading the forthcoming publication.

Finally, I attended an afternoon symposium in which Michael Alfaro discussed a method (named *Medusa*) for integrating fossil information into phylogenetic estimates of birth/death rates. Afterwards, Brian Moore (from John Huelsenbeck’s lab) presented a collection of Bayesian tools for estimating phylogenetic divergence times and diversification rates.

OK, that’s it for now.