In among all the open-access discussion and ostrich-herding, we at SV-POW! Towers do still try to get some actual science done.  As we all know all too well, the unit of scientific communication is the published paper, and getting a submission ready involves a lot more than just the research itself.  One of the most important aspects is preparing the illustrations — indeed Matt once told me that he thinks one of the best ways to put a paper together is to start with the illustrations, then write the text around them.

[Illustrations are often referred to as “figures”.  I don’t know how the tradition got started, but since that term also means numbers, I will try to avoid it.  If I tell you “I am working on the figures for my diversity paper”, you don’t know if I am accumulating statistics or preparing illustrations.]

Done well, illustrations can be things of beauty as well as scientifically informative.

Taylor et al. 2011b:fig. 1 -- Sauropod neck gallery

Taylor et al. (2011b: figure 1). Sauropod necks, showing relationships for a selection of species, and the range of necks lengths and morphologies that they encompass. Phylogeny based on that of Upchurch et al. (2004: fig. 13.18). Mamenchisaurus hochuanensis (neck 9.5 m long) modified from Young & Zhao (1972: fig. 4); Dicraeosaurus hansemanni (2.7 m) modified from Janensch (1936: plate XVI); Diplodocus carnegii (6.5 m) modified from Hatcher (1903: plate VI); Apatosaurus louisae (6 m) modified from Lovelace, Hartman & Wahl (2008: fig. 7); Camarasaurus supremus (5.25 m) modified from Osborn & Mook (1921: plate 84); Giraffatitan brancai (8.75 m) modified from Janensch (1950: plate VIII); giraffe (1.8 m) modified from Lydekker (1894:332). Alternating grey and white vertical bars mark 1 m increments.

There are a few things to be said about preparing good illustrations, so we’re kicking off a short series on the subject.  This is the first.

But the zeroth was published here a couple of years ago.  Since the most important illustrations in many palaeontology papers are those of the specimens, the base you’re working from is your specimen photographs.  So you might want to refresh your memory by reading Tutorial 8: how to photograph big bones before we proceed.

There are various steps in getting from a photo to a finished, publishable figure, and we’ll look at those along the way.  But somewhere along the line, if you’re publishing in a conventional journal such as the Journal of Vertebrate Paleontology, you’re going to flatten your colour images down to greyscale. Postpone that step till the last possible moment.

That should be too obvious to need saying, but I’ve got it wrong myself.  When I was preparing the specimen photographs for the Xenoposeidon paper, destined for Palaeontology, I flattened the images too early in the process, with the result that the greyscale versions of the figures that were included in the paper are the only versions in existence.  The upshot is that if you look at the full-resolution illustrations in the unofficial supplementary information, you’ll see that the version of Figure 3 available there is greyscale, just like the one in the paper.

By the time the three of us did our neck-posture paper in Acta Palaeontologica Polonica, we weren’t quite so dumb.  So although the illustrations in the published paper are all greyscale, the two that are based on specimen photographs, rather than assembled from previously published greyscale components, were prepared in full colour, then flattened as the very last process before submission.  As a result, the full-resolution illustrations in the unofficial supplementary information have figures 1 and 2 in colour:

Taylor et al. (2009: Figure 1). Cape hare Lepus capensis RAM R2 in right lateral view, illustrating maximally extended pose and ONP: skull, cervical vertebrae 1-7 and dorsal vertebrae 1-2. Note the very weak dorsal deflection of the base of the neck in ONP, contrasting with the much stronger deflection illustrated in a live rabbit by Vidal et al. (1986: fig. 4). Scale bar 5 cm.

So we were pretty happy with that.  But by the time we came to submit the Brontomerus description a couple of years later, we’d had a rather obvious (in retrospect) thought: just because we can’t have colour in the printed journal, does that mean we can’t have it in the PDF?  We asked the good people at Acta Pal. Pol., and they agreed that we could submit colour illustrations, they’d use them in the PDF, and then flatten them to greyscale themselves for the printed edition.

Since about fifty times as many people see the PDF as see the printed journal [yes, I just made than number up out of my head], that solution suited us very well.  The outcome was the the PDF has gorgeous figures like this one:

Taylor er al. 2011a: fig. 4 -- Brontomerus caudal vertebra

Taylor et al. (2011a: figure 4). Mid-caudal vertebra of the camarasauromorph sauropod Brontomerus mcintoshi from the Lower Cretaceous Cedar Mountain Formation of Utah, OMNH 61248 in dorsal (A), anterior (B), left lateral (C), posterior (D) and ventral (E) views.

(I’m slightly sorry to be displaying all our own illustrations here, but they do make the point and frankly I like looking at them.  Especially that beautiful caudal vertebra.)

Why am I making such a big deal about colour?  Because colour is information, and as scientists we love information.  When you flatten a colour image to greyscale, you lose information, and that should never be done without regret.  It’s perfectly possible that adjacent regions of a fossil will be a different hue but the same brightness: flatten the image and the two colours look the same, but in the original you can see a distinction.  That’s valuable.

So in this day and age, The Right Thing is:

  • Prepare your figures in colour
  • Submit them in colour
  • If the journal has a printed edition (and charges extra for colour printing, as most do), tell them to flatten to greyscale.

On the other hand, if you’re submitting to an open-access journal — and you should be, if you want to be widely read — there’s a good chance that it’s online-only (as with PLoS ONE and Palaeontologia Electronica), in which case the use of colour is a complete non-issue.  The only reason to prepare monochrome figures then is (as with the Taylor et al. 2011b sauropod-neck bestiary above) when you’re constructing them from pre-existing greyscale images.


Taylor, Michael P., Mathew J. Wedel and Darren Naish. 2009. Head and neck posture in sauropod dinosaurs inferred from extant animals. Acta Palaeontologica Polonica 54(2):213-230.

Taylor, Michael P., Mathew J. Wedel and Richard L. Cifelli. 2011a. A new sauropod dinosaur from the Lower Cretaceous Cedar Mountain Formation, Utah, USA. Acta Palaeontologica Polonica 56(1):75-98. doi: 10.4202/app.2010.0073

Taylor, Michael P., David W. E. Hone, Mathew J. Wedel and Darren Naish. 2011b. The long necks of sauropods did not evolve primarily through sexual selection. Journal of Zoology 285:150-161. doi: 10.1111/j.1469-7998.2011.00824.x

If you’re a scientist, then one of the things you need to do is prepare high-quality images for your papers.  And, especially if you’re a palaeontologist, or in some other science that involves specimens, that’s often going to mean manipulating photographs.  So image editing has become one of those “grey skills”, like word processing and phylogenetic analysis, that you need to have a little of, even if you’re not specialising in that direction.

Here at SV-POW!, none of us is anything remotely approaching wizardly when it comes to image-editing.  But we’ve done enough of it that we have a few tips to pass on, so this is the first in an occasional series that will offer some random but relevant hints.  (Matt and I both use GIMP, a free image-editing program, but I’m sure PhotoShop has the all the same facilities and more.)

Today: thirty-second colour-balancing.  It’s a technique that comes in handy every now and then, especially if you take a lot of specimen photographs in poorly lit basements that make everything look greenish.  It came up because in the previous post Matt included this photo of a partially dissected turkey neck:

All the orange made my eyeballs hurt.

So you can spend hours on colour-balancing a photo carefully, and that can be appropriate if you’re preparing a figure for publication.  But to fix a photo like this one in thirty seconds, here’s what I do.

Load the image.

Bring up the Layers window and use it to duplicate the layer:

With the top layer selected, choose Colours -> Auto -> Equalize. (There is also a Colours -> Auto -> White Balance option, but I never find that it gives good results.)

Equalize will make the top layer look truly horrible:

Now go back to the Layers window, and play with the top layer’s opacity, so that you get a blend of the original and equalised images:

In this case, I found that 50% opacity looked about the best:

(While it’s still no oil-painting, it’s much better than the all-orange-all-the-time original.)

With the top layer still selected, choose Layers -> Merge Down to make the layers into one, and save the result.

It really does take about thirty seconds total, including the time to start up and shut down the image editor.  (Yes, GIMP starts up more quickly than PhotoShop!)

Update (11 April 2012)

If you’re wondering why this is “part 0”, it’s because it was originally posted as a stand-alone article, and we only realised much later that it fits into the tutorial sequence — in particular, the planned multi-part tutorial on preparing illustrations.


Preparing a talk is a time-consuming process, and there’s no question that getting the slides ready is where the bulk of that time goes.  But unless you understand exactly what it is that you’re going to talk about, even the best slides won’t rescue your talk from mediocrity, so before you fire up PowerPoint, go and read part 1 of this tutorial, on finding the narrative.  Seriously.  The slides are how you convey your message, and they’re important.  But not as important as what your message is.

Assuming you know what story you’re trying to tell, here is the overriding principle of slide design: make yourself understood.  Remember again that you have something less than twenty minutes in which to make your rich, complex research project understood to a hall full of strangers who have just sat through five or ten or fifteen other presentations.  They will be mentally tired.  Help them out.  Make every slide tell a clear story.

The slides for a conference talk are science, not art.  That doesn’t mean they have to be ugly — of course it doesn’t.  But it does mean that whenever you find yourself facing a choice between clarity and beauty, go with clarity.

That means you do not want your slides to look like this:

OK, that is not even beautiful.  But it does illustrate some horrible mistakes, and we’ll touch on all of them  in what follows.  For now, just remember that the purpose of a Results slide is to help the audience know what your results were.

So how do you make yourself understood?

1. Use the full size of the screen

Most importantly, don’t “frame” your content.  You have a specific amount of space in which to present your work.  Don’t throw any of it away.  Although the super-bad slide above may look extreme, I have seen plenty to slides that present, say, specimen photos in about the same amount of space as the graph above occupies.  So, then:

  • No picturesque borders.
  • We don’t need the talk title, or your name or address on every slide.  You can tell us once at the start of the talk and then, if you like, once more at the end.  If we truly forget who you are in the middle, we can always look at the programme.  If we forget what you’re talking about, then your talk has more profound problems.
  • That goes double for logos.  We do not need to see the following more than once (or indeed once):
    • Your institution’s crest
    • The conference logo
    • Logos of funding bodies

We don’t need any of that stuff, and all of it wastes precious real-estate.  Space that you could be using to tell your story.

Most important of all: use as much space as you can for your images.  Specimen photographs, interpretive drawings, reproduced figures from the literature, graphs, cladograms, strat sections — whatever you’re showing us, let us see it.

In my own talks, I like to make the picture fill the whole slide.  You can usually find a light area to put a dark text on, or vice versa.  I often find it’s useful to give the text a drop-shadow, so that it stands out against both light and dark background.  (You can find that option in Format -> Character… -> Font Effects if you use OpenOffice, and no doubt somewhere similar in PowerPoint.)

If the aspect ratio of an image that I want to use is not the 4:3 that projectors give you, then I will often crop it down to that aspect ratio, if some of the edges of the image are dispensable, so that the cropped version is properly shaped to fill the screen.

(On image resolution: most projectors seem to be 1024 x 768, maybe some these days are 1280 x 960.  There’s no point using images at a higher resolution than that: your audience won’t see the additional information.)

2. Legibility

Hopefully you won’t need too many words on your slides, since you’ll be talking to us about what we can see.  But what words you use, we need to see.  Specifically, this means:

  • Use big fonts.  There is absolutely no point in showing us an eighty-taxon phylogenetic tree: we just won’t be able to read the taxon names.  I tend to make my fonts really big — 32-point and up, which actually is probably bigger than you really need.  But you don’t want to be smaller than 20-point at the absolute minimum.
  • Use high contrast between the text and background.  That usually means black on white, or (if you must) white on black.  Well, OK — it doesn’t literally have to be black, but it needs to be a very dark colour (I often use very dark blue).  And it doesn’t literally have to be white, but it needs to be a very light colour.  (I occasionally use a very pale yellow “parchment”-type colour, but less often.)  Do not use grey text or a grey background.  Especially do not use grey text on a grey background, even if they are fairly different greys and the muted effect looks classy.  You’re not shooting for “classy”, you’re shooting for “legible”.  Because you remember the prime directive that you’re trying to make yourself understood.
  • If for some reason you must use a non-black, non-white text or background, don’t make it a highly saturated colour.  Some combinations, such as a red on blue, and virtually impossible to read.
  • No vertical writing (with the possible exception of short y-axis labels on graphs).  If your cladogram’s taxon names are vertical, turn your cladogram around.  Redraw it if necessary.  If the audience have their heads on one side, you’re doing it wrong.

3. Font Choice

Apart from size, what else matters about fonts?

  • Avoid elaborate fonts, such as the URW Chancery L Medium Italic that I used for my name and affiliation in the Bad Slide at the top.  They’re hard to read, and at best they draw attention away from the message to the medium.
  • Pick a single font and stick with it for consistency.  Or if you wish, one serifed font (for body text) and one sans-serif (for headings).  But you should have little enough text on your slides that it’s practically all headings.
  • Stick to standard fonts which you know will be on the computer that will be displaying your presentation.  In practice, the safest approach is it stick to Microsoft’s “core fonts for the web” — which is plenty enough choice.
  • You might want to avoid Arial, which is widely considered particularly ugly.  Other ubiquitous sans-serif fonts include Trebuchet and Verdana, which are both rather nicer than Arial (though Verdana’s glyphs are too widely spaced to my eye).
  • Do not use MS Comic Sans Serif, or no-one will take anything you say seriously.  I don’t just mean your talk, I mean ever, for the rest of your life.

Why is it important to stick to standard fonts?  Because of size, spacing and positioning.  Your computer may have the super-beautiful Font Of Awesomeness and it might make your slides look beautiful; but when you run your PowerPoint file on the conference computer, it won’t have Font Of Awesomeness, so it will substitute whatever it thinks is closest — Arial or Times or something.  Not only will you not get the visual effect you wanted, but the glyphs will be different sizes, so that your text will run off the edge of the page, or fall right off the bottom.

(Handy household hint for users of Debian GNU/Linux and variants such as Ubuntu.  Make sure that you have the MS core fonts installed on your computer, so that OpenOffice can properly display your slides as you’re designing them, rather than substituting.  sudo apt-get install ttf-mscorefonts-installer, restart OpenOffice, and you’re good to go.)

4. How many slides?

I need to mention this issue, if only to say that there’s no right answer.  I don’t say that lightly: for most slide-design issues, there is a right answer.  (Example: should you use MS Comic Sans Serif?  Answer: no.)  But number of slides has to vary between people to fit in with presentation styles.

I tend to use a large number of slides and whiz through them very quickly — my SVPCA 2011 talk had 80 slides, and in 2010 I had 92 slides.  Lots of them are parenthetical, sometimes just a silly joke to make in passing a point that I am already making.  If you miss such a slide, it doesn’t really matter: it’s just light relief and reinforcement, not an integral part of the narrative.


But that many-slides-slipping-quickly-past style doesn’t suit everybody. In the eighteen minutes or so that you get to give a talk (allowing a minute for messing about getting set up and a minute for questions), getting through 80 slides in those 1080 seconds gives you an average of 13.5 seconds per slide.

Lots of people prefer to use fewer slides and talk about them for longer. You can give an excellent talk with very few slides if that approach comes naturally to you: step slowly through nine slides, talk about each one for two minutes.

Once you’ve given a few talks you’ll know which approach works best for you, and you can design accordingly. For your first talk, you’re probably best off aiming initially somewhere in the middle — thirty or so slides — and then seeing what happens when you dry-run the talk. (We’ll discuss that next time around.)

5. Miscellaneous

I’ve touched on this one already, but it’s best to use as little text as possible. That’s because you want your audience listening to your story, not reading your slides. I used to put a lot of text in my slides, because I wanted the PowerPoint file to stand alone as a sort of a record of the talk. But I don’t do that now, because a talk involves talking (clue’s in the question). I include enough text to remind myself what I want to say about each slide (sometimes just one or two words; often none at all). And I try to make sure there’s enough to let the audience know what they’re looking at if I zoom straight past it. For example:


I used this slide to briefly tell a typical taphonomic story of a sauropod neck.  But I didn’t need to say that I was using diagrams of the neck of Sauroposeidon taken from Wedel et al. 2000, so I just shoved that information on the slide for anyone who was interested.  That way I didn’t have to break the flow of my narrative to impart this information.

Use a consistent colour palette.  If you’ve used dark blue text on white for half of your slides, don’t switch to black on pale yellow for the other half.  It’s not a hugely important point, but it all contributes to helping the talk go down smoothly.  You’re getting rid of mental speed-bumps that could stop your audience from giving their full attention to the story you’re telling.

Where possible, avoid putting important information at the bottom — in, say, the lower 10-15% of the slide.  That’s because the lower part of the screen can sometimes be obscured by the heads of the people in the front rows.

Avoid hatching, which can look terrible on a screen, in a way that’s very hard to predict.  In the Sauroposeidon taphonomy slide above, for example, the lost bones are “greyed out” using a flat grey colour rather the close diagonal lines of the original.  I knew it would look right on the screen.

Skip the fancy slide transitions, animated flying arrows, and suchlike. It’s just distracting nonsense that no one in the audience (or anywhere else, for that matter) needs to be exposed to. It’s just gross. Also, as with fonts, you may end up giving your talk from a machine with an older version of PowerPoint that doesn’t support the turning of animated pages and the bouncing arrival of arrows and clipart, and then your presentation will either look stupid or fail to run entirely.

You might want to draw highlighting marks on your slides, e.g. circles around the relevant parts of a specimen photos.  That will save you having to mess about with the laser pointer later.  (I will have much to say about the laser pointer in part 4).  I like to show two consecutive slides: one of the unadorned photo, then one that’s identical apart from the addition of the highlight, like this:

Then as I am talking about the first slide, “in order to mount the vertebrae in something approaching a straight line, they had to leave a huge gap between consecutive centra”, I’ll step on to the next one, which highlights what I’m saying.  Slick, no?  (This is part of why I end up with such high slide counts.)

A pet hate: don’t write “monophyletic clade”.  If it’s a clade, it’s monophyletic by definition.  “Monophyletic clade” is like “round circle”, “square square” or “boring ornithopod”.

And finally …

Show us specimens.  We are vertebrate palaeontologists, and we love vertebrate fossils.  No-one goes into the field because of a deep and abiding passion for graphs or for tables of numbers.  We understand that from time to time you’ll need to show us those things in order to tell the story, but nothing makes an audience happier than big, clean photos of beautiful specimens.

Well, that’s it — how to make good slides.  Next time we’ll look at rehearsing the talk.  (It’ll be a much shorter post than this one.)

This tutorial is based on all the things that I stupidly forgot to do along the way of tearing down the juvenile giraffe neck that Darren, John Conway and I recently got to take to pieces.  At half a dozen different points in that process, I found myself thinking “Oh, we should have done X earlier on!”  So it’s not a tutorial founded on the idea that I know how this should be done; it’s about how I am only now realising how it should be done, off the back of my dumb mistakes.

Cervical vertebra 5 of two-week-old giraffe: left column, anterior; middle column, top to bottom, dorsal, left lateral, posterior, all with anterior to the left; right column, posterior

What you want is to get the maximum possible information out of your specimen.  At each stage of preparation, information is lost — a necessary evil, because of course at the same time new information becomes available.  So don’t miss anything early on.

The whole neck

If you’re lucky, you’ll get the complete, intact neck to work with.  (Ours was not quite intact, having been skinned, and lost an indeteminate amount of superficial muscle and ligament in the process.)  So before you start cutting, photograph the neck in dorsal, ventral, lateral, anterior and posterior aspects.

Next, you want to measure the neck:

  • total mass
  • total length, front of atlas to back of last centrum.
  • maximum flexion (i.e. downwards bend)
  • maximum extension (i.e. upwards bend)
  • maximum deflection (i.e. lateral bend)

These last three are hard to do, because “maximum” flexion, extension and deflection are not exact things.  You can always push or squeeze or bend a bit harder.  These are the unpleasantly messy aspects of working with animals rather than robots — most kinds of tissue are flexible and resilient.  You just have to do the best you can, and supplement your measurements with photographs of the neck bent in each direction.


Now you’re ready to start taking that baby apart.  Get the skin off, then redo all your photos and redo all your measurements — yes, even total length, even though you “know” removing the skin can’t affect that.  Because you don’t know what you don’t know.  Does removing the skin affect the maximum range of movement?  How much of the neck’s total mass was due to the skin?  Weigh the skin as well: does its mass added to that of the deskinned neck add up to that of the intact neck?  If not, is the discrepancy due to blood loss?

Stripping muscle

Once the skin is off, you can start removing muscles.  Ideally, you want to identify each muscle as you go, and remove them one by one, so that you leave the major ligaments behind.  In practice this is harder than it sounds, because the muscles in real necks are, inconveniently, not clearly delineated and labelled like the ones in books.  Still, going slowly and carefully, it’s often possible to avoid cutting actual muscles but just the fascia between them, which allows you remove complete muscles.  Done well, this can leave in place not only the nuchal ligament running along the top of all the neural spines, but the shorter ventral ligaments joining adjacent vertebrae.

John (left) and Darren (right) removing muscle from the giraffe neck (in right lateral aspect), while keeping ligaments intact

As you’re doing this, you want to avoid damaging the intercentral joints and the zygapophyseal capsules, so far as possible.  You’ll probably find it easy to preserve the former, which are tough, but harder not to accidentally damage at least some of the latter.  You want to keep them intact as far as possible, so you can see how the react when you manipulate the neck.  (Do these manipulations gently, or you’ll tear those capsules.)

Now that the skin and muscles are both off — at least, so far as you can remove the muscles, which will not be completely — you can redo all your photos and redo all your measurements again.  Yes, all of them.  Because you just can’t tell what you’re going to be interested in later, and curse yourself for missing.

Stripping ligament

Go right ahead.  Remove the short ligaments, and do your best to get the nuchal ligament off all in one chunk — not quite as easy as it sounds, because it doesn’t just sit on top of the neural spines, but sort of encloses them.  Measure the nuchal ligament at rest, then stretch it out as far as you can and measure it extended.  Calculate how far it stretched as a proportion of the rest length.  Compare this with what you learned from Alexander (1989:64-65).  Hmm.  Interesting, no?

You can guess what’s coming now: redo all your photos and redo all your measurements yet again.  You should find that the total length is the same, but who knows what you might find about changing flexibility?  Also, your progressive sequence of mass measurements will tell you what proportion of the whole neck was skin, muscle, ligament, etc.

Separating the vertebrae

This sounds like it should be easy, but it’s not.  The zygapophyses will come apart very easily, but the centra will be held firmly together with very dense connective tissue which has be cut carefully away, piece by piece, with the blade of a scalpel worked between the condyle of one vertebra and the cotyle of the next.  (I’m writing here about a giraffe neck, but I’m confident the same will be true of other artiodactyls and maybe most mammals; bird necks are different.)

Once you’ve got the vertebrae separate, photograph each vertebra separately, from each of the cardinal directions. Also, measure each vertebra separately — especially for centrum length, but you may as well get all the major measurements.  These measurements will include the cartilage caps at the front and back of each centrum.  (This is the step that I most regret missing out.)

Articulate the vertebrae in “neutral pose” by keeping the centra in full contact and rotating each intercentral joint about its midpoint until the corresponding zygapophyses are maximally overlapped.  What does this pose look like?  How does it compare to the animal’s habitual pose in life?  (If possible, compare with the pose shown by an X-ray of the live animal, since necks lie.)

Articulate the vertebrae in positions of “maximal” flexion, extension and deflection by keeping the centra in full contact and rotating each intercentral joint about its midpoint until the corresponding zygapophyses are displaced to a degree of your choosing.  Try it with the zygs allowed to slide until they are 50% disarticulated, then with 75% disarticulation, then displacing until they are just past the point of contacting each other.  Photograph all these poses and measure their deflection.  Compare these variant poses with those obtained when the vertebrae were still joined together, and when the ligaments, muscles and skin were still in place.  What degree of zygapophyseal disarticulation best matches the whole-neck bending ability?  How does this vary along the neck?  How does that this compare with what you may have been led to expect in the literature.  Hmm.

Using your earlier photos of the whole neck’s bending profile, arrange the vertebrae in the exact same pose.  How much do the zygapophyses disarticulate in these poses?  As you rotate the joints about the articulation of their centra, do the zygs just slide neatly past each other, or do they move far apart from each other as the neck bends?  Interesting, yes?

Cleaning the vertebrae

Have you recorded all the information you need from the intact vertebrae with their cartilage in place?  If you’re sure, then …

Lightly simmer the vertebrae for an hour or so, then remove the excess flesh by hand and using a toothbrush.  Repeat as needed to get them clean.  If you can do this really carefully — I couldn’t — you may be able to keep the cartilage firm, and firmly articulated with the bone.  (Bugging the vertebrae is probably a better approach for this purpose, but I find it hard to be that patient.)

Once the vertebrae have dried out — and especially, once their cartilage is dry — re-measure each vertebra.  Does the drying of the cartilage affect the centrum length?

Simmer the vertebrae again and gently peel off the cartilage caps at the front and back of each centrum.  Re-measure the centra: how long are they now?  What proportion of each centrum’s length was cartilage?

Articulate all the centra in a straight line, and measure the total length.  How does this compare with the whole-neck length you started with?  [Crib-sheet answer for our baby giraffe: 41 cm vs. a whole-neck length of 51 cm.  Expect a closer match if you’re dealing with an adult animal,which will have proportionally less cartilage.]

Articulate the vertebrae in “neutral pose” as you did back when the individual vertebrae were complete.  How does the new “neutral pose” compare with the old one?  With habitual life posture?  Huh.  Makes you think, doesn’t it?

Nearly done …

Articulate the vertebrae in positions of “maximal” flexion, extension and deflection as you did before, and compare your results with those from when the vertebrae were complete with their cartilage caps.  Well!  Who’d have thought?

Now remember that the fossils we have of, say, sauropod cervicals are those of the dry bone only, with no cartilage.  Think about how different the “neutral pose” and range of movement would be if we had the intact vertebrae with their cartilage.

Dammit all, I’ve given the game away

As I wrote this article, I found myself giving away more and more of a paper I’ve been planning to write, in which I go through essentially this process with a couple of necks, ideally from very different clades, and write up the results.  Say, a giraffe, an ostrich and  a croc.  The extent to which the dry-bone postures and flexibility vary from those of the live animals would give us a reasonable starting point for thinking about how life postures and flexibility of sauropods might have varied from what we’d deduce from the dry bones alone.

Wouldn’t that be a great little paper?

Well, I might still write it when I find the time, but I won’t stand in the way of anyone else who wants to plough straight in and just get it done.  (You might mention me in the acknowledgements if you do.)

Why we do mass estimates

Mass estimates are a big deal in paleobiology. If you want to know how much an animal needed in terms of food, water, and oxygen, or how fast it could move, or how many offspring it could produce in a season, or something about its heat balance, or its population density, or the size of its brain relative to its body, then at some point you are going to need a mass estimate.

All that is true, but it’s also a bit bogus. The fact is, people like to know how big things are, and paleontologists are not immune to this desire. We have loads of ways to rationalize our basic curiosity about the bigness of extinct critters. And the figuring out part is both very cool and strangely satisfying. So let’s get on with it.

Two roads diverged

There are two basic modes for determining the mass of an extinct animal: allometric, and volumetric. Allometric methods rely on predictable mathematical relationships between body measurements and body mass. You measure a bunch of living critters, plot the results, find your regression line, and use that to estimate the masses of extinct things based on their measurements. Allometric methods have a couple of problems. One is that they are absolutely horrible for extrapolating to animals outside the size range of the modern sample, which ain’t so great for us sauropod workers. The other is that they’re pretty imprecise even within the size range of the modern sample, because real data are messy and there is often substantial scatter around the regression line, which if faithfully carried through the calculations produces large uncertainties in the output. The obvious conclusion is that anyone calculating extinct-animal masses by extrapolating an allometric regression ought to calculate the 95% confidence intervals (e.g. “Argentinosaurus massed 70000 kg, with a 95% confidence interval of 25000-140000 kg), but, oddly, no-one seems to do this.

Volumetric methods rely on creating a physical, digital, or mathematical model of an extinct animal, determining the volume of the model, multiplying by a scale factor to get the volume of the animal in life, and multiplying that by the presumed density of the living animal to get its mass. Volumetric methods have three problems: (1) many extinct vertebrates are known from insufficient material to make a good 3D model of the skeleton; (2) even if you have a complete skeleton, the method is very sensitive to how you articulate the bones–especially the ribcage–and the amount of flesh you decide to pack on, and there are few good guidelines for doing this correctly; and (3) relatively small changes in the scale factor of the model can produce big changes in the output, because mass goes with the cube of the linear measurement. If your scale factor is off by 10%, you mass will be off by 33% (1.1^3=1.33).

On the plus side, volumetric mass estimates are cheap and easy. You don’t need hundreds or thousands of measurements and body masses taken from living animals; you can do the whole thing in your kitchen or on your laptop in the space of an afternoon, or even less. In the old days you’d build a physical model, or buy a toy dinosaur, and use a sandbox or a dunk tank to measure the volume of sand or water that the model displaced, and go from there. Then in the 90s people started building digital 3D models of extinct animals and measuring the volumes of those.

But you don’t need a physical model or a dunk tank or even a laptop to do volumetric modeling. Thanks to a method called graphic double integration or GDI, which is explained in detail in the next section, you can go through the whole process with nothing more than pen and paper, although a computer helps.

Volumetric methods in general, and GDI in particular, have one more huge advantage over allometric methods: they’re more precise and more accurate. In the only published study that compares the accuracy of various methods on extant animals of known mass, Hurlburt (1999) found that GDI estimates were sometimes off by as much as 20%, but that allometric estimates were much worse, with several off by 90-100% and one off by more than 800%. GDI estimates were not only closer to the right answers, they also varied much less than allometric methods. On one hand, this is good news for GDI afficionados, since it is the cheapest and easiest of all the mass estimation methods out there. On the other hand, it should give us pause that on samples of known mass, the best available method can still be off by as much as a fifth even when working with complete bodies, including the flesh. We should account for every source of error that we can, and still treat our results with appropriate skepticism.

Graphic Double Integration

GDI was invented by Jerison (1973) to estimate the volumes of cranial endocasts. Hurlburt (1999) was the first to apply it to whole animals, and since then it has been used by Murray and Vickers-Rich (2004) for mihirungs and other extinct flightless birds, yours truly for small basal saurischians (Wedel 2007), Mike for Brachiosaurus and Giraffatitan (Taylor 2009), and probably many others that I’ve missed.

GDI is conceptually simple, and easy to do. Using orthogonal views of a life restoration of an extinct animal, you divide the body into slices, treat each slice as an ellipse whose dimensions are determined from two perspectives, compute the average cross-sectional area of each body part, multiply that by the length of the body part in question, and add up the results. Here’s a figure from Murray and Vickers-Rich (2004) that should clarify things:

One of the cool things about GDI is that it is not just easy to separate out the relative contributions of each body region (i.e., head, neck, torso, limbs) to the total body volume, it’s usually unavoidable. This not only lets you compare body volume distributions among animals, it also lets you tinker with assigning different densities to different body parts.

An Example: Plateosaurus

Naturally I’m not going to introduce GDI without taking it for a test drive, and given my proclivities, that test drive is naturally going to be on a sauropodomorph. All we need is an accurate reconstruction of the test subject from at least two directions, and preferably three. You could get these images in several ways. You could take photographs of physical models (or toy dinosaurs) from the front, side, and top–that could be a cool science fair project for the dino-obsessed youngster in your life. You could use the white-bones-on-black-silhouette skeletal reconstructions that have become the unofficial industry standard. You could also use orthogonal photographs of mounted skeletons, although you’d have to make sure that they were taken from far enough away to avoid introducing perspective effects.

For this example, I’m going to use the digital skeletal reconstruction of the GPIT1 individual of Plateosaurus published by virtual dino-wrangler and frequent SV-POW! commenter Heinrich Mallison (Mallison et al 2009, fig. 14). I’m using this skeleton for several reasons: it’s almost complete, very little distorted, and I trust that Heinrich has all the bits in the right places. I don’t know if the ribcage articulation is perfect but it looks reasonable, and as we saw last time that is a major consideration. Since Heinrich built the digital skeleton in digital space, he knows precisely how big each piece actually is, so for once we have scale bars we can trust. Finally, this skeleton is well known and has been used in other mass estimate studies, so when I’m done we’ll have some other values to compare with and some grist for discussion. (To avoid accidental bias, I’m not looking at those other estimates until I’ve done mine.)

Of course, this is just a skeleton, and for GDI I need the body outline with the flesh on. So I opened the image in GIMP (still free, still awesome) and drew on some flesh. Here we necessarily enter the realm of speculation and opinion. I stuck pretty close to the skeletal outline, with the only major departures being for the soft tissues ventral to the vertebrae in the neck and for the bulk of the hip muscles. As movie Boromir said, there are other paths we might take, and we’ll get to a couple of alternatives at the end of the post.

This third image is the one I used for actually taking measurements. You need to lop off the arms and legs and tote them up separately from the body axis. I also filled in the body outlines and got rid of the background so I wouldn’t have any distracting visual clutter when I was taking measurements. I took the measurements using the measuring tool in GIMP (compass icon in the toolbar), in orthogonal directions (i.e., straight up/down and left/right), at regular intervals–every 20 pixels in this case.

One thing you’ll have to decide is how many slices to make. Ideally you’d do one slice per pixel, and then your mathematical model would be fairly smooth. There are programs out there that will do this for you; if you have a 3D digital model you can just measure the voxels (= pixels cubed) directly, and even if all you have is 2D images there are programs that will crank the GDI math for you and measure every pixel-width slice (Motani 2001). But if you’re just rolling with GIMP and OpenOffice Calc (or Photoshop and Excel, or calipers and a calculator), you need to have enough slices to capture most of the information in the model without becoming unwieldy to measure and calculate. I usually go with 40-50 slices through the body axis and 9 or 10 per limb.

The area of a circle is pi*r^2, and the area of an ellipse is pi*r*R, where r and R are the radii of the minor and major axes. So enter the widths and heights of the body segments in pixels in two columns (we’ll call them A and B) in your spreadsheet, and create a third column with the function 3.14*A1*B1/4. Divide by four because the pixel counts you measured on the image are diameters and the formula requires radii. If you forget to do that, you are going to get some wacky numbers.

One obvious departure from reality is that the method assumes that all of the body segments of an animal have elliptical cross-sections, when that is often not exactly true. But it’s usually close enough for the coarse level of detail that any mass estimation method is going to provide, and if it’s really eating you, there are ways to deal with it without assuming elliptical cross-sections (Motani 2001).

For each body region, average the resulting areas of the individual slices and multiply the resulting average areas by the lengths of the body regions to get volumes. Remember to measure the lengths at right angles to your diameter measurements, even when the body part in question is curved, as is the tail of Heinrich’s Plateosaurus.

For sauropods you can usually treat the limbs as cylinders and just enter the lateral view diameter twice, unless you are fortunate enough to have fore and aft views. It’s not a perfect solution but it’s probably better than agonizing over the exact cross sectional shape of each limb segment, since that will be highly dependent on how much flesh you (or some other artist) put on the model, and the limbs contribute so little to the final result. For Plateosaurus I made the arm circular, the forearm and hand half as wide as tall, the thigh twice as long as wide, and the leg and foot round. Don’t forget to double the volumes of the limbs since they’re paired!

We’re not done, because so far all our measurements are in pixels (and pixels cubed). But already we know something cool, which is what proportion each part of the body contributes to the total volume. In my model based on Heinrich’s digital skeleton, segmented as shown above, the relative contributions are as follows:

  • Head: 1%
  • Neck: 3%
  • Trunk: 70%
  • Tail: 11%
  • Forelimbs (pair): 3%
  • Hindlimbs (pair): 12%

Already one of the great truths of volumetric mass estimates is revealed: we tend to notice the extremities first, but really it is the dimensions of the trunk that drive everything. You could double the size of any given extremity and the impact on the result would be noticeable, but small. Consequently, modeling the torso accurately is crucial, which is why we get worried about the preservation of ribs and the slop inherent in complex joints.

Scale factor

The 170 cm scale bar in Heinrich’s figure measures 292 pixels, or 0.582 cm per pixel. The volume of each body segment must be multiplied by 0.582 cubed to convert to cubic cm, and then divided by 1000 to convert to liters, which are the lingua franca of volumetric measurement. If you’re a math n00b, your function should look like this: volume in liters = volume in pixels*SF*SF*SF/1000, where SF is the scale factor in units of cm/pixel. Don’t screw up and use pixels/cm, or if you do, remember to divide by the scale factor instead of multiplying. Just keep track of your units and everything will come out right.

If you’re not working from an example as perfect as Heinrich’s digital (and digitally measured) skeleton, you’ll have to find something else to use for a scale bar. Something big and reasonably impervious to error is good. I like the femur, if nothing else is available. Any sort of multi-segment dimension like shoulder height or trunk length is going to be very sensitive to how much gloop someone thought should go between the bones. Total length is especially bad because it depends not only on the intervertebral spacing but also on the number of vertebrae, and even most well-known dinos do not have complete vertebral series.


Finally, multiply the volume in liters by the assumed density to get the mass of each body segment. Lots of people just go with the density of water, 1.0 kg/L, which is the same as saying a specific gravity (SG) of 1. Depending on what kind of animal you’re talking about, that may be a little bit off or it may be fairly calamitous. Colbert (1962) found SGs of 0.81 and 0.89 for an extant lizard and croc, which means an SG of 1.0 is off by between 11% and 19%. Nineteen percent–almost a fifth! For birds, it’s even worse; Hazlehurst and Rayner (1992) found an SG of 0.73.

Now, scroll back up to the diagram of the giant moa, which had a mass of 257.5 kg “assuming a specific gravity of 1”. If the moa was as light as an extant bird–and its skeleton is highly pneumatic–then it might have had a mass of only 188 kg (257.5*0.73). Or perhaps its density was higher, like that of a lizard or a croc. Without a living moa to play with, we may never know. Two points here: first, the common assumption of whole-body densities of 1.0 is demonstrably incorrect* for many animals, and second, since it’s hard to be certain about the densities of extinct animals, maybe the best thing is to try the calculation with several densities and see what results we get. (My thoughts on the plausible densities of sauropods are here.)

* Does anyone know of actual published data indicating a density of 1.0 for a terrestrial vertebrate? Or is the oft-quoted “bodies have the same density as water” basically bunk? (Note: I’m not disputing that flesh has a density close to that of water, but bones are denser and lungs and air spaces are lighter, and I want to know the mean density of the whole organism.)

Back to Plateosaurus. Using the measurements and calculations presented above, the total volume of the restored animal is 636 liters. Here are the whole body masses (in kg) we get using several different densities:

  • SG=1.0 (water), 636 kg
  • SG=0.89 (reptile high), 566 kg
  • SG=0.81 (reptile low), 515 kg
  • SG=0.73 (bird), 464 kg

I got numbers. Now what?

I’m going to describe three possible things you could do with the results once you have them. In my opinion, two of them are the wrong the thing to do and one is the right thing to do.

DON’T mistake the result of your calculation for The Right Answer. You haven’t stumbled on any universal truth. Assuming you measured enough slices and didn’t screw up the math, you know the volume of a mathematical model of an organism. If you crank all the way through the method you will always get a result, but that result is only an estimate of the volume of the real animal the model was based on. There are numerous sources of error that could plague your results, including: incomplete skeletal material, poorly articulated bones, wrong scale factor, wrong density, wrong amount of soft tissue on the skeleton. I saved density and gloop for last because you can’t do much about them; here the strength of your estimate relies on educated guesses that could themselves be wrong. In short, you don’t even know how wrong your estimate might be.

Pretty dismal, eh?

DON’T assume that the results are meaningless because you don’t know the actual fatness or the density of the animal, or because your results don’t match what you expected or what someone else got. I see this a LOT in people that have just run their first phylogenetic analysis. “Why, I could get any result I wanted just by tinkering with the input!” Well, duh! Like I said, the method will always give you an answer, and it won’t tell you whether the answer is right or not. The greatest advantage of explicit methods like cladistics and GDI is that you know what the input is, and so does everyone else if you are honest about reporting it. So if someone disagrees with your character coding or with how much the belly sags on your model sauropod, you can have a constructive discussion and hopefully science as a whole gets closer to the right answer (even if we have no way of knowing if or when we arrive, and even if your pet hypothesis gets trampled along the way).

DO be appropriately skeptical of your own results without either accepting them as gospel or throwing them out as worthless. The fact that the answer changes as you vary the parameters is a feature, not a bug. Investigate a range of possibilities, report all of those results, and feel free to argue why you think some of the results are better than others. Give people enough information to replicate your results, and compare your results to those of other workers. Figure out where yours differ and why.

Try to think of more interesting things you could do with your results. Don Henderson went from digitally slicing critters (Henderson 1999) to investigating floating sauropods (Henderson 2004) to literally putting sauropods through their paces (Henderson 2006)–not to mention working on pterosaur flight and swimming giraffes and other cool stuff. I’m not saying you should run out and do those exact things, but rather that you’re more likely to come up with something interesting if you think about what you could do with your GDI results instead of treating them as an end in themselves.

How massive was GPIT1, really?

Beats me. I’m not the only one who has done a mass estimate based on that skeleton. Gunga et al. (2007) did not one but two volumetric mass estimates based on GPIT1, and Mallison (2010) did a whole series, and they published their models so we can see how they got there. (In fact, many of you have probably been reading this post in slack-jawed horror, wondering why I was ignoring those papers and redoing the mass estimate the hard way. Now you know!) I’m going to discuss the results of Gunga et al. (2007) first, and come back to Mallison (2010) at the end.

Here’s the “slender” model of Gunga et al. 2007 (their fig. 3):

and here’s their “robust” model (Gunga et al. 2007:fig. 4):

(These look a bit…inelegant, let’s say…because they are based on the way the physical skeleton is currently mounted; Heinrich’s model looks much nicer because of his virtual remount.)

For both mass estimates they used a density of 0.8, which I think is probably on the low end of the range for prosauropods but not beyond the bounds of possibility. They got a mass of 630 kg for the slender model and 912 kg for the robust one.

Their 630-kg estimate for the slender model is deceptively close to the upper end of my range; deceptive because their 630-kg estimate assumes a density of 0.8 and my 636-kg one assumes a density of 1.0. The volumes are more directly comparable: 636 L for mine, 790 L for their slender one, and 1140 L for their robust one. I think that’s pretty good correspondence, and the differences are easily explained. My version is even more skinnier than their slender version; I made it about as svelte as it could possibly have been. I did that deliberately, because it’s always possible to pack on more soft tissue but at some point the dimensions of the skeleton establish a lower bound for how voluminous a healthy (i.e., non-starving) animal could have been. The slender model of Gunga et al. (2007) looks healthier than mine, whereas their robust version looks, to my eye, downright corpulent. But not unrealistically so; fat animals are less common than skinny ones but they are out there to be found, at least in some times and places. It pays to remember that the mass of a single individual can fluctuate wildly depending on seasonal food availability and exercise level.

For GPIT1, I think something like 500 kg is probably a realistic lower bound and 900 kg is a realistic upper bound, and the actual mass of an average individual Plateosaurus of that size was somewhere in the middle. That’s a big range–900 kg is almost twice 500 kg. It’s hard to narrow down because I really don’t know how fleshy Plateosaurus was or what it’s density might have been, and I feel less comfortable making guesses because I’ve spent much less time working on prosauropods than on sauropods. If someone put a gun to my head, I’d say that in my opinion, a bulk somewhere between that of my model and the slender model of Gunga et al. is most believable, and a density of perhaps 0.85, for a result in the neighborhood of 600 kg. But those are opinions, not hypotheses, certainly not facts.

I’m happy to see that my results are pretty close to those of Mallison (2010), who got 740 L, which is also not far off from the slender model of Gunga et al. (2007). So we’ve had at least three independent attempts at this and gotten comparable results, which hopefully means we’re at least in the right ballpark (and pessimistically means we’re all making mistakes of equal magnitude!). Heinrich’s paper is a goldmine, with loads of interesting stuff on how the skeleton articulates, what poses the animal might have been capable of, and how varying the density of different body segments affects the estimated mass and center of mass. It’s a model study and I’d happily tell you all about it but you should really read it for yourself. Since it’s freely available (yay open access!), there’s no barrier to you doing so.


So: use GDI with caution, but do use it. It’s easy, it’s cool, it’s explicit, it will give you lots to think about and give us lots to talk about. Stay tuned for related posts in the not-too-distant future.



February 18, 2009

Start here if you’d like to know more about sauropod vertebrae, photographing specimens, or becoming a paleontologist.

Matt is staying here at Taylor Towers for a couple of weeks while his wife spends some quality time with some leprous human remains in Bradford (yes, really). Since both Matt and I are big fans of sushi, I took a stab at making some at home on Sunday night:

Fig. 1. Sushi plate, poorly preserved due to predation

Fig. 1. Sushi plate, poorly preserved due to predation

We noticed that the spring onion in one of the rolls had held its shape sufficiently well to preserve an air-space running along the length of the roll:

av, avocado; cs, crab-stick; pf, pneumatic foramen; pr, prawn.

Fig. 2. Spring-onion california roll, cross-section in anterior view. A, photograph; B, interpretive drawing. Anatomical abbreviations: av, avocado; cs, crab-stick; pf, pneumatic foramen; pr, prawn.

Using the technique of Wedel (2005:212-213), we can calculate the air-space proportion of this roll (ASP) by dividing the area of the enclosed pneumatic space by total cross-section.

fig. 7.5)

The simplest way to do this is to reduce the image to simple black-and-white with a grey background and count the pixels:

Fig. 4. Spring-onion California roll depicted in figure 2, with solid material drawn in black and pneumatic space in white.

Fig. 4. Sushi roll depicted in figure 2, with solid material drawn in black and pneumatic space in white.

According to image-processing program, the full-sized version of this images has 21961 white pixels and 302993 black pixels, yielding an ASP of W/(W+B) = 21961/(21961+302993) = 0.067, or 6.7%. This is a very low value compared to most sauropod vertebrae: according to Wedel (2005:table 7.2), values are mostly in the range 50-70% — nearly ten times as pneumatic as this sushi roll — with Sauroposeidon reaching 89% in a cervical prezygapophyseal ramus.


At the risk of turning this blog into Brachiosaurus brancai 8th Cervical Picture of the Day, here’s a quick tutorial on your basic sauropod vertebral anatomy, using everyone’s favourite cervical vertebra.

Brachiosaurus brancai, 8th cervical, various views

This picture shows the same vertebra as was photographed in the very first SV-POW! entry.  I’ve composited the figures of this element from Janensch (1950), an exhaustive and lavishly illustrated monograph on the vertebrae and ribs of B. brancai. Parts of this vertebra’s right-hand side are missing, as is apparent in the anterior and posterior views, but most of it is excellently preserved.

First things first: directions. In standard anatomical descriptions of dinosaurs, the direction towards the front is called anterior, and towards the back is posterior — so an anterior view (such as the top left part of this picture) is looking at the front of the vertebra. Upwards is dorsal, downwards is ventral. Sticking out sideways is lateral, and towards the midline is medial. These directions can be combined into single words that describe oblique directions such as anteroventral, posterolateral and anteroventromedial. (Some poor misguided souls use “cranial” and “caudal” in place of “anterior” and “posterior”, but we’ll have none of that here.)

The main body of the vertebra, the roughly cylindrical part, is called the centrum. At the front of the centrum in sauropod cervicals and most dorsals is a ball which fits into a corresponding socket at the back of the preceding one. The ball is called a condyle, the socket is called a cotyle.

Dorsal to the centrum is the neural arch, which is surmounted by the neural spine. A hollow passageway runs through the neural arch from front to back: this houses the spinal cord, and is called the neural canal. (You can’t really see it in the pictures above; you can make it out much more clearly in the BMNH R2523 photos, anterior and posterior.)

Two processes (which just means pointy bits) project laterally from each side of the vertebra: in cervicals they mostly hang downwards a bit, i.e. they project ventrolaterally. (It is a bit of a mystery to me why we say “project ventrolaterally” in scientific writing instead of “hang down”, but there it is.) The dorsal pair of processes are the diapophyses (singular diapophysis, pronounced dye-a-POFF-a-siss). The ventral pair are the parapophyses. They are the articulation points for the ribs. In cervical vertebrae, the ribs are often fused to the processes that support them; in dorsal vertebrae they are free, attached only by soft tissue. (In the pictured specimen, the ribs are broken off very close to their point of origin. In life, they would have projected backwards as thin cylinders a couple of meters long.)

As you see, the diapophysis, parapophysis and fused cervical rib form a loop lateral to the centrum. This loop doesn’t really have a name — it’s called the ansa costro-transversaria in birds, but very few palaeontologists use avian anatomical nomenclature for sauropods. So we three just call it the “cervical rib loop”.

Finally (for now), we have the zygapophyses. There are two pairs of these: prezygapophyses at the front, and postzygapophyses at a location that I will not insult your intelligence by stating. When vertebrae are strung together in a line, their zygs articulate, but they can slide past each other to a limited degree, allowing some flexibility. How much flexibility is a matter of some debate which we may revisit in another post.  The facets of the prezygs always face anteromedially (that’s upwards and inwards, remember?) and the postzygs ventrolaterally, although their precise orientation varies along the spinal column.

That it for now. Coming soon in subsequent tutorials: fossae and foramina; laminae; variation along the column; and much, much more. Remember to tell all your friends that this is where the party is.

Accidental anaglyphs

October 16, 2020

Everyone knows that the very first thing you should do to improve your specimen photography is to use a tripod: it eliminates hand-shake and gives you much crisper photos. In most respects, my photographs have got much, much better since I’ve been habitually using a tripod.

But it has meant I’ve not been able to benefit from happy accidents like the one that gave me this 3D anaglyph of the Archbishop‘s Cervical S in dorsal view:

(Do you have red-cyan glasses? Yes? Good! You will be able to appreciate all the delicious morphological information in this photo. No? Go and order some right now — they cost literally a dollar.)

The reason I was able to make this very useful image is because back in the old pre-tripod days I would sometimes accidentally move a little bit between taking two more-or-less identical photographs. Here are the two images that I was able to composite into the anaglyph above:

Each of them is pretty uninformative alone: who can tell one nondescript area of brown bone from another? But when combined, they are extraordinarily more informative. If you don’t have 3D glasses then (A) get some! and (B) you can get some idea of how helpful the 3D information is from the crude wigglegram below, which simply switches back and forth between the two images.

And I can’t overstate how enormously helpful I have found these accidentally sourced anaglyphs as I write the descriptive part of the Archbishop manuscript. Even at this level of crudity, they have shown me several important points of morphology that I would certainly have missed if I’d been working only from my orthogonal-view photos, and saved me from more than one misinterpretation.

The moral is twofold:

  1. When taking specimen photographs, use a tripod — but deliberately get some pairs of shots where the camera is moved to the side by about 7 cm (the distance between the pupils in an average human).
  2. If you don’t have any red-cyan glasses, get some!

I can’t even count how many sauropod vertebra pictures we’ve posted here across the last ten years, but I am confident that the total comes to at least a lot. Here’s a picture from each year of the blog’s existence so far — let’s vote on which is the best!

November 15, 2007: Xenoposeidon week, day 1: Introducing Xeno

The stark beauty of the Xenoposeidon proneneukos holotype NHMUK R2095, a mid-to-posterior partial dorsal vertebra in left and right lateral views.

February 1, 2008: Your neck is pathetic

Sauroposeidon proteles holotype OMNH 53062, 8th cervical vertebra in left lateral view (1400 mm total length). Entire human neck for scale.

January 7, 2009: The sauropods of Star Wars: Special Edition

Our old friend Giraffatitan brancai MB.R.2181 once more, this time with Matt for scale.

February 12, 2010: Tutorial 8: how to photograph big bones

The Archbishop in all its glory. The much-loved dorsals 8 and 9, in right lateral view, of the Tendaguru brachiosaurid NHMUK R5937.

May 16, 2011: Why the long necks? Probably not sexual selection

Taylor et al. (2011), fig. 1: Sauropod necks, showing relationships for a selection of species, and the range of necks lengths and morphologies that they encompass. Phylogeny based on that of Upchurch et al. (2004: fig. 13.18). Mamenchisaurus hochuanensis (neck 9.5 m long) modified from Young & Zhao (1972: fig. 4); Dicraeosaurus hansemanni (2.7 m) modified from Janensch (1936: plate XVI); Diplodocus carnegii (6.5 m) modified from Hatcher (1903: plate VI); Apatosaurus louisae (6 m) modified from Lovelace, Hartman & Wahl (2008: fig. 7); Camarasaurus supremus (5.25 m) modified from Osborn & Mook (1921: plate 84); Giraffatitan brancai (8.75 m) modified from Janensch (1950: plate VIII); giraffe (1.8 m) modified from Lydekker (1894:332). Alternating grey and white vertical bars mark 1 m increments.

April 15, 2012: Neural spine bifurcation in sauropods, Part 6: more reasons why Haplocanthosaurus is not a juvenile of a known diplodocid

Wedel 2009: Fig. 6. Pneumatization of the presacral vertebrae in Haplocanthosaurus. (A) X-ray image of a posterior cervical vertebra of CM 879 in right lateral view. (B) A CT slice through the same vertebra. (C) X-ray image of an anterior dorsal vertebra of CM 572 in left lateral view. (D) X-ray image of the same vertebra in anterior view.

January 16, 2013: Plateosaurus is pathetic

Our old friend C8 of the Giraffatitan brancai paralectotype MB.R.2181 in left dorsolateral view, with a comparable cervical of the prosauropod Plateosaurus for scale.

February 12, 2014: Can PeerJ really be only a year old?

Barosaurus lentus holotype YPM 429, Vertebra Q (C?13). Top row: left ventrolateral view. Middle row, from left to right: anterior view, with ventral to the right; ventral view; posterior view, with ventral to the left. Bottom row: right lateral view, inverted. Inset shows diapophyseal facet on right side of vertebra, indicating that the cervical ribs were unfused in this individual despite its great size. Note the broad, flat prezygapophyseal facet visible in anterior view. (Taylor and Wedel 2013b: figure 6)

September 14, 2015: So what were apatosaurs doing with their crazy necks?

A slide from our 295 SVPCA talk, illustrating key points in apatosaurine neck morphology that led us to the BRONTOSMASH hypothesis.

May 18, 2016: Thank you to all our Sauropocalypse hosts!

Mike compares Jensen’s sculpture of the big Supersaurus cervical BYU 9024 with the actual fossil.

August 15, 2017: “Biconcavoposeidon”

AMNH FARB 291, five consecutive posterior dorsal vertebrae of a probably brachiosaurid sauropod which we informally designate “Biconcavoposeidon”, in right lateral view.

(Yes, there are eleven pictures: we’ve been running for ten years, but that includes both the end of 2007 and the start of 2017.)

So, which is the picture of the decade? Vote here (and let us know in the comments if we missed your favourite).