The NOAA reports that “we are currently tied with 1998 as the warmest January–September period on record.”
Having now experienced a near-record-breakingly warm summer and fall, I can now report what the effect of global warming will be in St. Louis, Missouri: the normally irritating plague of backyard mosquitos will become an insatiable horde that renders our backyard thoroughly uninhabitable well into October and possibly November.
This article was originally posted at Science 2.0 on 21 April 2010 as a follow up to my article What Do Ardi, Raptorex, and Komodo Dragons Have in Common?. In light of recent debate* about Raptorex’s identity I thought this was worth a second look.
Normally, being wrong sucks. It’s all -10 points and you don’t get into Harvard. Sadness. But, not in science. One of the best things about scientific method is that it makes being wrong fun. That does not mean that scientists always like to hear they are wrong. We are after all sinful, prideful beasts like the rest of you – just smarter – just kidding.
A while ago, I discussed some relatively recent, amazing contributions of paleontology in order to illustrate that, while DNA may trump fossils for reconstructing evolutionary histories and the relationships between organisms, paleontology provides information on physiology and geographical location that can only be inferred by other disciplines. One of the discoveries discussed was of a 125 million year old, man-sized Tyrannosaurus rex ancestor, Raptorex, reported in Science on 17 September 2009. Continue reading “corREXion?”
This article was originally posted at Science 2.0 on 9 October 2009. It provides some background for the follow-up article corREXion? that has suddenly become relevant again.
Paleontology doesn’t always get the respect it deserves (or desires), in the molecular, genomic, evolutionary, quantitative genetic circles we run in around here. Blame the DNA. Sequence comparisons have proven incomparable in establishing phylogenetic relationships between organisms.
Paleontology can also irritate us by creating false controversy, which irritates the heck out of us. The fossil record is a sparse and biased record of life. Supposed “missing links” are often an artifact of this fact. Supposed discrepancies between sequence divergence times and divergence in form from the fossil record often reflect the fact that sequence divergence necessarily precedes any differences in form significant enough to be noticeable in the fossil record.
This means that biologists tend to relegate paleontology (fairly or not) into the roles of adding colorful detail. Therefore, it is particularly exciting when there are not one, not two, but three recently reported fossils that force the biological community to re-evaluate evolutionary hypotheses. Continue reading “What Do Ardi, Raptorex, and Komodo Dragons Have in Common?”
Sean Carroll at Cosmic Variance recently commented that the recent history of dramatic revolutions in physics, together with the incomprehensible but widely covered debates over string theory and other physical theories at the frontier, tend to make people think that the foundations of everyday physics are much more volatile than they really are.
He makes a fairly basic point, one that I would guess is accepted by the vast majority of scientists, and yet this point is surprisingly controversial in popular science discussions:
Continue reading “The Distorting Effect of Scientific Revolutions”
One physicist’s experience trying to model the EGF signaling pathway with a 48-parameter ODE model
Cerione explained that none of the parameters are known to better than a factor of between two and ten, and that it was so boring to measure them that he couldn’t pay anyone to do so. The model has 48 total parameters!…
We could fit to the data and make predictions, but with 48 free parameters could we trust our answers? To see if an answer was trustworthy, we did statistical mechanics in model space. (Doing a Monte Carlo in parameter space, it turns out, is called stochastic Bayesian analysis.) As I had suspected, the parameters varied over huge ranges. In fact, every parameter varied by over a factor of fifty, and many varied over factors of many thousands. Remember – all of these parameter sets still fit the existing experimental data.
Check out Cornell physicist James Sethna’s page on ‘sloppy models’, where he explains how to deal with biological systems that have dozens of parameters, most of which, thank God, don’t actually matter.
The Finch and Pea 