Using light to describe the ancient world

#Living the dream

My academic journey so far.

My academic journey so far.

I have recently started a new position at Massey University in Auckland: Lecturer of Vertebrate Zoology (!!!!!). This is an amazing opportunity and I can’t wait to sink my teeth in. I wanted to take this opportunity to give a big thank you to everyone who has helped me along the way, and to name but a tiny fraction:

University of Otago: Professor Ewan Fordyce, Professor Russell Frew, Dr Marc Schallenberg

University of Cape Town: Professor Anusuya Chinsamy-Turan

Smithsonian Institution National Museum of Natural History: Dr Helen James, Dr Matthew Carrano, Dr Gary Graves, Dr Carla Dove, Christopher Milensky, Christina Gebhard, Brian Schmidt, Jacob Saucier

Arizona State University: Professor Kevin McGraw

And a very special thank you to Cushla McGoverin, Joanne Thomas, Murray Thomas, Hollie Steel, Dan Ksepka, Mark Clements and Brandon Gellis


It’s busy times at the moment and there are big plans afoot. Sorry blog, but we might be trains in the night for a little while longer.

Charlotte Doney during her undergraduate internship at the Museum Conservation Institute. Charlotte is shown here sitting in front of an FT-Raman spectrometer in Dr. Odile Madden's Modern Materials lab. Photo source:

Charlotte Doney during her undergraduate internship at the Museum Conservation Institute. Charlotte is sitting in front of an FT-Raman spectrometer in Dr. Odile Madden’s Modern Materials lab. Photo source.

My colleagues at the Smithsonian Institution and I have recently published an article that explores the preservation of old collagen. I think this is a great methods paper that could lead on to some really interesting applications, and I will get to the details of the article in a little bit. First though, I want to highlight one of the most fun aspects of this paper – a good chunk of the work was done by Charlotte Doney, an undergraduate intern from George Washington University.

In 2012, Dr. Christine France successfully attracted funding for undergraduate students to take up research projects in the Museum Conservation Institute. This Institute is housed within the Smithsonian Institution’s Museum Support Center, in Suitland, Maryland. Charlotte Doney was interested in working with Dr. France and Dr. Odile Madden on a project these senior researchers had discussed some years prior – can Raman spectroscopy tell us if collagen in an ancient bone is well preserved? Charlotte was interested in both the challenge and answer.

Raman spectroscopy provides chemical information about a sample, and in the case of an old bone, is useful for studying both the collagen and the bone mineral. Furthermore, the isotopic compositions of carbon and nitrogen in collagen can tell us about the lifestyle of the person or animal the bone is from. Raman spectroscopy doesn’t report on the isotopic composition of collagen – this is the job of a mass spectrometer. Instead, Raman spectroscopy gives us an idea about how much collagen is present in the bone. As collagen degrades, the isotopic composition becomes less meaningful about the original lifestyle of the person or animal. As collagen degrades, there is less and less of it left in the bone, and we can detect this with Raman spectroscopy. Charlotte collected Raman spectra from bones that had known isotopic compositions.

I was working in Dr. Madden’s lab at the time and had the privilege of training Charlotte to collect Raman spectra, and then later I analysed the data and we each cowrote the now published manuscript.

During my time at the University of Otago and the University of Cape Town I hadn’t worked alongside undergraduate interns, so this was one of the new experiences I encountered at the Smithsonian. I had undertaken (and later, worked with) summer studentships at the University of Otago, and looking back there are many similarities. A dedicated research project, a short and fixed time frame, an opportunity to work with professional researchers. I can’t value these experiences highly enough, and if the student is particularly motivated, like Charlotte, then the work can be recognised as a formal publication. How good is that!

France, C. A. M., Thomas, D. B., Doney, C. R. and Madden, O. 2014. FT-Raman spectroscopy as a method for screening collagen diagenesis in bone. Journal of Archaeological Science 42: 346–355

#PCA is your friend, part two

Continued from the post below

The loadings the thing, wherin I’ll catch the essence of the dataset. Principal component analysis (PCA) is an excellent, and often essential, method for analysing a large amount of data. Our research question centers around the differences between two fossil sites, and the large dataset we have at hand is made up of x-ray fluorescence spectra from fossil bones. These data go into the PCA, and out pour our beautiful results in two forms – scores and loadings.

Let’s look at the loadings.

Loadings let us see the major sources of variation in our dataset. By ‘sources of variation’, here I mean the way in which spectra differ from one another, like having peaks in different places. Different sources of variation are teased out for each principal component, and we can visualise these ‘components’ with the loadings. Take the loadings for PC1, for example:

Principal component one loadings for x-ray fluorescence spectra. Data were collected from fossil antelope bone. Modified from Thomas and Chinsamy 2011.

Principal component one loadings for x-ray fluorescence spectra. Data were collected from fossil antelope bone. Modified from Thomas and Chinsamy 2011.

These loadings show us that the peaks attributed to iron and strontium are positively weighted, and the peaks attributed to calcium are negatively weighted. So this means that some samples in our dataset that have a great deal of Fe and Sr, and some samples have extra calcium, over and above the amount typical amount for bone. Now we jump to the next step, and used our PC1 loadings to interpret our PC1 scores, which are below:

Principal component one and two score values. Each score value represents a fossil antelope bone from South Africa. Modified from Thomas and Chinsamy 2011.

Principal component one and two score values. Each score value represents a fossil antelope bone from South Africa. Modified from Thomas and Chinsamy 2011.

We found that our Fe and Sr peaks were positively loaded. In our scores plot, this means that samples with positive PC1 scores should be rich with Fe and Sr. Likewise, our Ca peaks were negatively weighted, and so our samples with negative PC1 scores probably contain an extra calcite mineral. If we take a look at our PC1 scores we find that the positively weighted samples are all from Elandsfontein Main, and all of the Swartklip 1 have negative score values.

So we have found a chemical difference between the bones of these two sites. Elandsfontein bones have been infiltrated with iron and strontium rich minerals, which actually turn out to be clays and sands deposited by groundwater. The Swartklip bones contain abundant calcite. What does that mean for the burial history of these two sites?

The fossil bones at Elandsfontein Main and Swartklip 1 both accumulated in dune environments during the Pleistocene. The Elandsfontein Main site remained inland, and the slightly acidic groundwater that percolated through the fossils partially dissolved the bones and filled them with sediment. In contrast, sea level change periodically brought the coastline close to the Swartklip 1 site, where it is now, actually. The marine influence introduced calcium carbonate into the environment, which buffered the acidic groundwater and laced it with dissolved carbonates. These carbonates precipitated onto the Swartklip 1 fossils.

So, at Elandsfontein Main we have fossils that have been subjected to acidic groundwater for tens of thousands of years, and at Swartklip 1, we have fossils that have been periodically buffered by soil carbonates. If I was to pick one site to start looking for intact and well preserved bone, even down to isotope-level, I would start with the fossils Swartklip 1.

So yeah, this is the type of information we get from spectroscopy and principal components analysis. Pretty cool eh.

Thomas D B, Chinsamy A, 2011. Chemometric analysis of EDXRF measurements from fossil bone. X-ray Spectrometry 40: 441-445

Still to come: R code for pretreating spectra, performing a PCA analysis, and producing informative graphs…

#PCA is your friend

X-ray diffraction spectrum of calcite, the mineral that makes up most fossil shells. Data from The RRUFF™ Project

X-ray diffraction spectrum of calcite, the mineral that makes up most fossil shells. Data from The RRUFF™ Project

Most of the chemical tools we use to study fossils produce a data spectrum, which is just a set of measurements made over a series of observations. For example, think of the output from an x-ray diffraction analysis – the pattern of peak counts for each two-theta value is a spectrum. Other instruments that produce spectra include x-ray fluorescence, isotope ratio mass spectrometry, Fourier transform infrared spectroscopy and so on. We have become adept at reducing these data spectra to a single or few values of interest – calcite has an intense two-theta value at 29.4 under irradiation from a copper source – and we tend to throw away the rest of the spectrum. While there are study questions that can be addressed with point values (“Is there calcite in my fossil clam shell?”), there are other questions that could be better answered while working with the whole spectrum. Is there more than just calcite in my fossil shell? Does the calcite have an unusual chemistry? Is my fossil shell different to your fossil shell? These are questions that we can address by looking at variation between spectra, which we can do with principal component analysis.

I am going to switch study systems and talk about fossil bones and x-ray fluorescence. I will work this up as a practical  tutorial of sorts, and talk about some data from South African fossils that I collected a couple of years ago. There are a couple of advantages in working with these data – one, this is a real world scenario with a tangible result – two, the spectral data are available online so you can perform your own principal component analyses on fossil data.

Principal component analysis (PCA) on spectra from fossil bones.

PremiseStable isotopes in fossils are an incredibly rich source of information about ancient animals. Isotopes in fossil teeth and bones can tell us what an animal ate and how frequently it visited a source of water. Unfortunately, teeth and bones can become altered when they are buried, and the important biological information in the isotopic compositions can be lost. It would be nice to know ahead of time whether or not a fossil bone is altered, and one approach to assessing alteration is to study the burial history of the fossil bone or tooth. In this scenario we are going to examine the burial history of a fossil by studying the elemental composition of the fossil surface – changes in the environment over time will have changed the chemistry of the fossil. We will study fossils from two different Pleistocene locations in the Western Cape of South Africa, and the end goal is to decide which location has the best-preserved fossils.

Samples: Fossil teeth and bones from two localities were analysed. These bones were the horn cores of Pleistocene antelope – springbok (Antidorcas marsupialis), eland (Taurotragus oryx) and a relative of sable (Hippotragus sp.).

Data collection: Fossil teeth and horn cores from each site were analysed with a portable x-ray fluorescence instrument. We will use the energy spectra that the instrument produced, rather than the elemental ratios.

Swartklip fossil location, outside of Cape Town South Africa

Elandsfontein fossil location, outside of Cape Town South Africa


Results and Discussion: A principal component analysis (PCA) identifies the sources of variation in a dataset, which it sees as individual ‘components’. The largest source of variation is principal component one, the second largest source of variation is principal component two, and so on. By separating out sources of variation, PCA provides us with two very important sets of data about the samples we have analysed.

The first set of data are the ‘score values’ (or eigenvalues). The spectrum from each sample is reduced to a single ‘score’ value for each principal component. Samples will have similar score values when they have similar amounts of a particular variable . So, we can look at a distribution of score values and see which samples are more similar to which other samples by how closely positioned they are. Lets take this image here:

Principal component score values, from XRF analyses of fossil bones and teeth.

Principal component score values, from XRF analyses of fossil bones and teeth.

These are the score values from principal component one and principal component two, for our fossil XRF data. The first thing to notice is that all of the Swartklip samples have similar PC1 values. That is, the fossils from the two sites can be separated by the variation that is being pulled out by principal component one. The fossils from both sites have a range of PC2 values, so there is variation at both sites in whatever this component is. So, what is the source of variation along principal component one that is separating these fossil sites?

More soon, including the R code for pre-treating spectral data, performing PCA, and presenting PCA results…

Heard Island emerged from the Indian Ocean millions of years ago and is now savaged by snow and battered by wind. The island is among the most remote places on Earth and our record of its existence only began in the mid 19th century. Victorian-era access to Heard Island was by schooner or barque, from a harbour on the Kerguelen Islands 450 km away. In 1874 a collection of Heard Island wildlife was brought to the Kerguelen Islands and given to the crew of the visiting USS Swatara. The animals from this remote wilderness were passed along to Dr. Jerome Kidder, surgeon and naturalist for Swatara. Kidder prepared and studied the specimens, and 17,000 km away in Washington, DC, he stored the bounty at the Smithsonian Institution.

The specimens from Heard Island included this macaroni penguin:

Crest feathers from a macaroni penguin Eudyptes chrysolophus (USNM 533533). Photo by Daniel Thomas.

Crest feathers from a macaroni penguin Eudyptes chrysolophus (USNM 533533). Photo credit D Thomas.

The penguin that Dr. Kidder brought back from Heard Island has recently helped us with an interesting feather colour puzzle (Thomas et al. 2013). Yellow is a very common feather colour and is achieved in a variety of ways. For example, a canary will eat seeds that contain yellow pigments, and those pigments will be deposited in feathers. A parrot will use biochemical pathways to make yellow pigments while the feather is growing. The yellow pigment in penguin feathers is… a mystery. By studying yellow penguin feathers we could not only learn about the pigment chemistry, but we could also discover when the pigment first evolved and which fossil penguins had yellow feathers.

Raman spectroscopy has given us some new insight into the chemistry of the yellow penguin pigment. As mentioned elsewhere in this blog, Raman spectroscopy describes interactions between atoms in molecules or minerals. A Raman spectrum is a set of bands (or peaks…), and each band describes the energy of a particular atomic interaction. For example, a Raman spectrum of bone contains a band at 960 cm-1, and that band relates to an interaction between phosphorus and oxygen atoms. The Raman spectrum from the penguin pigment was brand new; it is not like anything that we have found in the published literature, and it is completely different from other feather pigments. The spectrum contains important bands at 1578, 1491, 1285 and 683 cm-1, which are hallmarks for a nitrogen-bearing, heterocyclic aromatic ring.

Nitrogen heterocycles in a pterin (left) and a porphyrin (right).

Nitrogen-bearing aromatic heterocyclic rings, highlighted in orange and shown in a pterin (left) and a porphyrin (right). Our best guess at this stage is that the penguin pigment contains something similar. Images adapted from Wikimedia Commons.

We still need more information before we can completely solve the structure, but at this stage we know for certain that the pigment is unlike anything so far observed in nature, and it is not likely to be a pigment that the penguins are eating. This means that penguins have evolved a biochemical pathway for making the pigment themselves. Armed with this new knowledge, we can look at the evolutionary history for the yellow penguin pigment. We do this by lining up the relevant evidence. First, we know that ten species of living penguin make the yellow pigment, including king penguins, yellow-eyed penguins and macaroni penguins. Second, we have a good idea that all living penguins are the descendants of an ancestor that lived more than 13 years ago (Ksepka and Thomas, 2012). Third, only penguins have this yellow pigment, and it is absent from albatrosses, shearwaters or petrels. This means:

1)     Living penguins inherited the yellow pigment from the ancestor that lived 13 years ago.

2)     The yellow pigment evolved after penguins had separated from albatrosses, petrels and shearwaters, at least 62 million years ago (Slack et al. 2006).

So the yellow penguin pigment is ancient, evolving sometime between 62 and 13 million years ago. We can use this information to add colour to an ancient penguin from South America.

Madrynornis mirandus (the ‘wonderful bird of Madryn’) is a 10 million year old penguin from Argentina (Acosta Hospitaleche et al. 2007). Madrynornis is more closely related to crested-penguins, like Kidder’s macaroni penguin, than any other group of penguins that we know of. Yellow-eyed penguins are also close relatives of both Madrynornis and the crested penguins, and all three groups shared a common ancestor that probably lived between 10 and 13 million years ago. We know that two of the groups descended from this common ancestor now have yellow feathers (crested and yellow-eyed penguins), so this means that the common ancestor probably had yellow feathers. And, because Madrynornis is a descendant of a penguin with yellow feathers, it very likely had them as well.

So, using Raman spectroscopy of modern feathers, we can add yellow pigments to Madrynornis mirandus, a 10 million year old penguin.

Image credits: Yellow-eyed penguin photo from Christian Mehlfuhrer, Macaroni penguin photo from Liam Quinn, Madrynornis images from Acosta Hospitaleche et al. 2007.

Image credits: Yellow-eyed penguin photo from Christian Mehlfuhrer, Macaroni penguin photo from Liam Quinn, Madrynornis images from Acosta Hospitaleche et al. 2007.


Acosta Hospitaleche C, Tambussi C,  Donato M, Cozzuol M. 2007. A new Miocene penguin from Patagonia and its phylogenetic relationships. Acta Palaeontologica Polonica 52, 299-314.

Ksepka DT, Thomas DB. 2012 Multiple Cenozoic invasions of Africa by penguins (Aves, Sphenisciformes). Proceedings of the Royal Society B 279, 1027–1032.

Slack K, Jones C, Ando T, Harrison G, Fordyce RE, Arnason U, Penny D. 2006. Early penguin fossils, plus mitochondrial genomes, calibrate avian evolution. Molecular Biology and Evolution 23, 1144–1155.

Thomas, DB, McGoverin CM., McGraw KJ. James HF, Madden O. 2013. Vibrational spectroscopic analyses of unique yellow feather pigments (spheniscins) in penguins. Journal of the Royal Society Interface (doi: 10.1098/​rsif.2012.1065)

Image links: macaroni penguin, Madrynornis mirandus, porphyrin, pterinyellow-eyed penguin


P.S. We called the Raman spectrum ‘spheniscin’, and eventually we adopted this as the name for the pigment. Unfortunately, this was a very embarrassing mistake. A quick google search will show that the name ‘spheniscin’ has already been taken, and I will make sure this mistake is formally corrected in a follow-up publication.

Robert Reisz and colleagues have described dinosaur embryos in a Letter published in Nature. The embryos are from a sauropodomorph dinosaur, “…probably Lufengosaurus…”, and were collected from Early Jurassic sediments (Sinemurian, 190–197 million years old) in the Yunnan Province of China. The tiny embryonic bones are impressive and the microstructural detail (i.e. histology) is astounding. The thing that caught my eye, though, was the evidence for organic molecules.

Thin sections of the tiny dinosaur bones were analysed at the National Synchrotron Radiation Research Center (NSRRC) in Taiwan. The researchers were interested in the wavelengths of infrared light that would be absorbed by the fossils (the synchrotron was their light source). Infrared absorbance is an excellent method for identifying molecules in a sample. Atoms bind together to form molecules – the type of atoms and the way they are bound controls the wavelengths of light that a molecule will absorb. More specifically, a molecule can be identified from the wavelengths of light it absorbs. The researchers presented the results from one bone: infrared wavelengths were directed at 120 points (150 × 180 µm, one spectrum collected every 15 µm), and the spectrum of wavelengths absorbed from each point was mapped.

Organic remnants in a dinosaur bone. Infrared absorption in the amide I and amide II regions provides strong evidence for a peptide bond, the ‘backbone’ of proteins, including collagen. Light microscope images show section of fossil bone that was analysed (left), colored maps show the distribution of apatite, amide I and a carbonate (middle), and spectra were collected from points highlighted with a red cross (right). Reprinted by permission from Macmillan Publishers Ltd: Nature. RR Reisz et al. Nature 496, 210-214 (2013) doi:10.1038/nature11978, copyright (2013).

Organic remnants in a dinosaur bone. Infrared absorption in the amide I and amide II regions provides evidence for a peptide bond, which are found in proteins. Light microscope images show section of fossil bone that was analysed (left), colored maps show the distribution of apatite, amide I and a carbonate (middle), and spectra were collected from points highlighted with a red cross (right). Reprinted by permission from Macmillan Publishers Ltd: Nature. RR Reisz et al. Nature 496, 210-214 (2013) doi:10.1038/nature11978, copyright (2013).

Some of wavelengths absorbed by the dinosaur bones would also be absorbed by the proteins of living animals. The basic structure of a protein involves a set of small molecules (amino acids) linking together to form a long chain (peptide). The ‘linking together’ forms a peptide bond, which has a characteristic infrared absorption. The characteristic absorptions of a peptide bond appear at very specific regions in an infrared absorption spectrum – two of those regions fall between 1500 and 1700 cm-1 and are termed ‘amide I and amide II’. The embryonic dinosaur bones absorb infrared light in the amide I and amide II regions, suggesting the presence of a peptide. Bone is a mixture of mineral (bioapatite) and protein (collagen), so it might be possible that the peptide traces in the fossil are remnants of collagen. The authors state that “…Previous reports of preserved dinosaur organic compounds, or ‘dinosaurian soft tissues’, have been controversial because it was difficult to rule out bacterial biofilms or some other form of contamination as a possible source of the organics. Our results clearly indicate the presence of both apatite and amide peaks within woven embryonic bone tissue, which should not be susceptible to microbial contamination or other post-mortem artefacts….”

Remnant collagen from a 190 million year old dinosaur embryo? Might well be.

Reisz, R R et al. 2013. Embryology of Early Jurassic dinosaur from China with evidence of preserved organic remains. Nature 496, 210-214.

A diverse group of penguins lived in Africa 10-12 million years ago. Dr. Dan Ksepka and I recently co-wrote an article describing these ancient penguins, and Dan has a great summary on his blog. I thought I would take this opportunity to show some of the ‘behind the scenes’ work that helped with the article but was not included in the final cut.

One of the first things we wanted to know was the age of the fossil penguin bones. Eventually we would solve this problem with stratigraphy – one of our first moves, though, was to see if the burial environment of the fossils we had just found was similar to the burial environment of fossil penguins that had previously been described. The burial environment for these already-described penguins is around five million years old.

The chemistry of fossil bones can be useful for describing different burial environments. Water that flows between grains of sediment can have very different chemical compositions in different burial environments, and water can alter the chemistry of a fossil bone in a distinct way. If two fossils have very similar elemental compositions, then you can start thinking about how they might have come from the similar burial environments. Likewise, if fossil bones have distinct chemical compositions, then it might be telling you that the bones also have different ages. Of course, fossils with the same age can be buried in different burial environments, so checking for similarities in burial environment is just a preliminary step.

Analysing the chemistry of a fossil bone is easy to do when you have access to a handheld x-ray fluorescence spectrometer. Two of the penguin bones that I analysed are shown below – most of a humerus from a ~5 million year old Inguza predemersus, and the head of a humerus from one of the newly found penguins (Sphenisciformes B). I collected XRF data from these specimens and found the same proportion of calcium and phosphorus in each fossil. This isn’t surprising – these are the two major ingredients of bone.

Fossil bones from the Western Cape of South Africa.

Fossil bones from the Western Cape of South Africa.

Both of these fossil bones are orange-brown-ish, and both have roughly the same proportion of iron. Iron oxides (rust) can produce orange-brown colours in fossils. So, no great differences in calcium, phosphorus or iron. Strontium, however, was a large component of the newly discovered bone, and represented a smaller proportion of the Inguza bone. Strontium can be fairly mobile, however, and bones from the same locality can have different amounts of strontium.

Energy dispersive x-ray fluorescence spectra from fossil penguin bones.

Energy dispersive x-ray fluorescence spectra from fossil penguin bones.

The most surprising and interesting results were at the higher end of the energy scale. A peak that might represent uranium was very clear in the spectrum from the newly discovered fossil penguin, and comparatively weak in the spectrum from Inguza. Likewise, a peak that might represent yttrium is distinct in the spectrum from Inguza, and weak in Sphenisciformes B. These trace elemental differences, combined with the variation in strontium concentration, are telling us that the two fossil bones have been altered by groundwater in different environments. We took this to mean that the bones were from different burial environments….

….and sure enough, the Inguza fossil was buried around 5 million years ago in a sandy river channel, and Sphenisciformes B was buried between 10 and 12 million years ago in a gravelly estuary. Of course, this conclusion was brought to us by sedimentology and stratigraphy, but it is very nicely supported by spectroscopy.

Thomas DB and Ksepka, DT. 2013. A history of shifting fortunes for African penguins. Zoological Journal of the Linnean Society. DOI: 10.1111/zoj.12024

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