Sauropod Vertebra Picture of the Week

THIS POST IS RETRACTED. The reasons are explained in the next post. I wish I had never posted this, but you can’t undo what is done, especially on the Internet, so I am not deleting it but marking it as retracted. I suggest you don’t bother reading on, but it’s here if you want to.

There were some surprises in the the contents of the SVPCA programme this year. Sauropods were woefully under-represented with only two talks (mine on apatosaur neck combat and Daniel Vidal’s on the range of movement of the tail of Spinophorosaurus). In fact non-avian dinosaurs as a whole got short shrift, with two theropod talks, three ornithischian talks and one on dinosaur diversity. This is partly, of course, because so many dinosaur workers among the SVPCA mainstays were absent for one reason or another: Matt Wedel, Paul Upchurch, Paul Barrett, Richard Butler, Roger Benson, Steve Brusatte, David Norman, the list goes on.

But that’s OK. I’ve often found, to my surprise, that the dinosaur talks aren’t always my favourites anyway. (Oddly enough, fish talks can quite often catch my imagination; and pterosaurs are always good for a laugh.)

A more surprising development was the complete absence of any finite element analysis this year — a technique that was crazy trendy a couple of years ago, but seems to have come to the end of its fashion cycle.

Instead, I felt that the talks were strongly dominated by one technique: principal component analysis (PCA). As a technique, I have mixed feelings about it: I don’t go as far as John Conway, who as far as I can tell thinks it’s almost literally meaningless. But I have strong reservations about the plug-and-play way it seems to get used for pretty much everything at the moment, and how very tenuous some of the inferences are that people derive from their morphospace plots. It’s difficult to be specific without criticising individuals, which I’d like to avoid doing. But I do think think that when we draw sweeping and heterodox conclusions about an animal’s lifestyle from a PCA of a single facet of a single bone, the validity of that conclusion is, to put it politely, open to question.

In fact an awful lot of the projects presented in this year’s talks seemed to follow the same template. In an idle (and, yes, unnecessarily snide) moment, I sketched an Automatic Masters Project Generator for lazy supervisors. You just throw four dice, then pick your technique name, body-part, period and taxon from these tables:

Table 1: roll 1d6 for a technique

1. 2d landmark analysis
2. principal component analysis
3. geometric morphometrics
4. morphospace analysis
5. finite element analysis
6. ecomorphological diversity analysis

Table 2: roll 1d6 for a body part

1. quadrate
2. mandible
3. sacrum
4. pelvis
5. ulna
6. astragalus

Table 3: roll 1d6 for a period

1. Permian
2. Mesozoic
3. Jurassic
4. Late Cretaceous
5. Eocene
6. Miocene

Table 4: roll 1d6 for a taxon

1. lamnid sharks
2. sauropterygians
3. ornithopods
4. corvids
5. mustelids
6. golden moles

Try it yourself! Morphospace analysis of the ulna in Miocene mustelids! Ready, steady, go! Your Masters degree will be ready as soon as you can talk reasonably coherently about this combination for fifteen minutes and leap to an obvious but weakly supported conclusion based on vague shapes drawn on a PC1-vs.-PC2 plot that captures only 32.6% of the variation!

(To be clear: I am not saying that PCA is intrinsically worthless. As I found myself repeatedly arguing in pubs with John and others, it’s evidently a very powerful tool for discovering correlations. For me, it goes wrong when very weak results pop out, but are given a veneer of respectability and objectivity because a computer was involved in the process.)

As the week went on, I found myself worrying increasingly about these projects. It’s not just that they are (with a few creditable exceptions) samey to listen to and uninteresting in their results. I worry more that these projects kill the interest of the people who take them on. I may be reading my own biases back into my observations here, but it seemed to me that I detected a distinct lack of enthusiasm in several of the speakers, and my hunch is that for a lot of them this will be their first and last SVPCA. They presumably went into palaeo because they loved some specific extinct taxon; instead, they found themselves spending a year staring at a hundred almost identical photographs of moodily lit tubes of toothpaste. And really, if anything is going to kill the passion of a pterosaur lover stone dead, it’s taking measurements of the distal articular facets of the ulnae of a 154 Miocene mustelids.

So I found myself longing for more talks about taxa, and about ideas, rather than techniques. Most obviously, there was very little pure descriptive palaeontology to be seen this year. But also, our own talk aside, very little of what I would think of as exploratory work — thinking about structures, chewing through their implications, considering alternatives. In short: the fun stuff. I would hate palaeontology to be reduced to a process of harvesting data from specimens (looking only at the aspects needed to fill in the matrix), pouring that data into a sausage machine, and turning the handle until something statistically significant comes out.

We have to be able to offer grad-students more than that. We are, and I say this with all due objectivity, in the most exciting science in the world. People go into palaeo because they love it. I wouldn’t like to think they go straight back out of it, as soon as they have their higher degree, hating it. We need to get students looking at and thinking about and discussing actual specimens — proposing ideas, arguing about them, running into reasons why they might be wrong, figuring out why they might be right after all, putting together an argument. Not sitting in front of computers full time running T-tests.

Of course there is a role, and an important one, for numerical methods. But they have to be the means, not the end. We have to have a more interesting goal than finding a statistically significant correlation. Otherwise we’re going to lose people.