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paleoanthropology, genetics and evolution

Photo Credit: 3D printing a Homo naledi cranium. John Hawks CC-BY-NC-ND

Skeletal remains from Milner Hall, a new area of Sterkfontein Caves

This month, the Journal of Human Evolution has published a short paper from Dominic Stratford and colleagues describing two hominin fossils from Milner Hall, a new excavation area within Sterkfontein Caves. One of the authors is my UW-Madison colleagues, Travis Pickering. If you know Sterkfontein, Milner Hall stretches from the area near the Silberberg Grotto across toward the underground lake.

The deposits sampled here are near the base of the fossil-bearing strata in Sterkfontein. Stratford, Grab and Pickering in a 2014 paper described the geological context of the excavation in Milner Hall. The excavation area includes at least three talus deposits that have sloped in from different sources, and have ages ranging from some of the oldest at Sterkfontein up to the last half million years. The hominin material comes from nearest the surface, in the T1 talus deposit. This talus was formed as miners early in the 20th century worked on a large stalactite nearby; this mining caused a relocation of a mixture of sediments from Member 5 and Member 2 into the T1 talus. According to the new paper describing the hominin material, the two hominin pieces most probably come from Member 5 sediments, which include some Oldowan flakes and a core. The age is uncertain.

StW 668 and StW 669
Figure 2 from Stratford et al. 2016, showing StW 669 on the left (a) and StW 668 on the right (b).

The proximal hand phalanx StW 668 is within the size range of humans but is more curved than human proximal phalanges. Its curvature is a bit greater than that seen in the proximal phalanges from Malapa or Dinaledi, but within the range of Hadar proximal phalanges. It is a larger phalanx than any seen at any of the South African fossil sites.

The tooth gives a bit more to compare:

StW 669, with its small occlusal area (116.5 mm2), tall vertical sides and widely spaced cusp apices, is grossly more similar to the M1s of Homo than to those of Australopithecus and Paranthropus. In overall shape and size, it compares most favorably to the Olduvai (Tanzania) M1 OH 6 (MD = 12.5 mm; BL = 12.3 mm) which is traditionally assigned to Homo habilis and to UW 101-1688, an M1 of the newly proposed South African species Homo naledi (MD = 12.4 mm; BL = 12.0 mm; Fig. 3a). In addition, like the majority of M1s traditionally assigned to early Homo (and especially to H. habilis, as well as to South African early Homo), StW 669 falls very near to the line of occlusal symmetry; in contrast, the vast majority of M1s of australopith-grade taxa (including Paranthropus) fall farther away and noticeably below this line.

Stratford and colleagues judge it to be a first molar, which is reasonable based on the cusp morphology. But the tooth lacks a distal interproximal facet, and I wonder if it may be a second molar instead. For some of these species (including H. naledi, the first and second molars are hard to tell apart, except based on size.

The tooth is small relative to most Australopithecus first molars, which means it is even smaller for a second molar of most species. But the size of the tooth does not distinguish species easily because are upper first molars attributed to Au. afarensis, Au. africanus, and even Au. robustus that have the same mesiodistal length as StW 669. These australopith species, however, have a broader buccolingual dimension than StW 669, which plots close to Homo first molars. The areas of the cusps are also more like Homo than Australopithecus, although the StW 669 paracone is yet smaller than the H. habilis examples. The two South African species that are most similar to this tooth are H. naledi and Au. sediba.

On the surface, the tooth looks like a very reasonable match for H. naledi first molars, and I think the match is even better for second molars. But it is not a bad match for the MH1 specimen of Au. sediba, either. We haven’t yet finished the analysis of cusp areas of the H. naledi molars, and on the basis of just this one tooth, I’m not sure we would be able to say StW 669 is very different from H. habilis, the KNM-ER 62000 specimen attributed to H. rudolfensis, or Dmanisi H. erectus.

But in the South African context, it seems like another example of a non-africanus specimen at Sterkfontein. And both Au. sediba and H. naledi are so far known from only a single site each, so demonstrating that they were present at a second site might really help us to understand when and how long these species existed.


Stratford D, Heaton JL, Pickering TR, Caruana MV, Shadrach K. 2016. First hominin fossils from Milner Hall, Sterkfontein, South Africa. Journal of Human Evolution 91:167-173. doi:10.1016/j.jhevol.2015.12.005

Stratford D, Grab S, Pickering TR. 2014. The stratigraphy and formation history of fossil- and artefact-bearing sediments in the Milner Hall, Sterkfontein Cave, South Africa: New interpretations and implications for palaeoanthropology and archaeology. Journal of African Earth Sciences 96:155-167. doi:10.1016/j.jafrearsci.2014.04.002

Notable paper: Stefanie Grosser, Nicolas J. Rawlence, Christian N. K. Anderson, Ian W. G. Smith, R. Paul Scofield, Jonathan M. Waters. 2016. Invader or resident? Ancient-DNA reveals rapid species turnover in New Zealand little penguins. Proceedings of the Royal Society B doi:10.1098/rspb.2015.2879

Synopsis: Grosser and colleagues studied mtDNA from ancient remains of two species of little penguins on New Zealand, the New Zealand endemic Eudyptula minor and Eudyptula novaehollandiae, which occurs both in New Zealand and Australia. They found that all of the remains dating to before 1600 represent E. minor, and they conclude that the appearance of E. novaehollandiae happened only after human-mediated decline in the E. minor population, both because of human predation and because of the human introduction of dogs and rats.

Interesting because: Ancient DNA is increasingly useful to determine the causes of population turnover. Prior to this large sample of aDNA, some biologists had speculated (on the basis of comparison of genetic data from living birds) that E. minor and E. novaehollandiae had coexisted in New Zealand for as long as 200,000 years. Retrospective population genetics just isn’t very accurate when it comes to the time of population divergences and demographic parameters. Ancient DNA is vastly better with questions like this one.

Cool figure: I really like the way they have illustrated the haplotype network and changes in frequencies over time:

Figure from Grosser et al showing haplotype network for penguin mtDNA
Figure 2 from Grosser et al. 2016. Original caption: Temporal haplotype network reconstruction of New Zealand (blue) and Australian little penguin (red) mitochondrial control region sequences from southeastern New Zealand (Otago). Each layer represents a particular time period as indicated in the inset. Circle size is proportional to haplotype frequency. Edges between haplotypes represent single mutation steps. Unobserved haplotypes are indicated by small black circles. Grey circles connected by dashed lines represent haplotypes that occur within the population but not the particular temporal layer. The insets show sampling localities in Otago. Circle colour in insets indicates species affiliation of specimens of the particular site. Blue and red borders interpolate Otago-wide distribution of E. minor and E. novaehollandiae, respectively. H, haplotype diversity; n, sample size; NZ, New Zealand (E. minor).

The National Post of Canada has a long article by Sharon Kirkey on the rise of obesity: “The shape of the future: Is obesity a crisis or just the latest stage of evolution?” It’s a nice piece that covers both genetics, the history of how we approach fat, and the changing views of fatness in society. I’ll be assigning it to my introductory students this semester.

This nice quote about the complexity of the relationship of FTO to obesity could have used a bit more explanation:

But many researchers are convinced basic genetics — not how we (or our mothers) behave — is the biggest driver of obesity, accounting for as much as 80 per cent of the risk of carrying excess weight. Their challenge is to tease out which genes among the 21,000 that make up the human body play a major role in “food-seeking behaviour,” satiety, cravings, and how our body stores and distributes fat.
The leader today is the FTO, the fat mass and obesity-associated gene that regulates appetite. People who inherit one copy of the FTO mutations (possibly as many as one in six people of European descent) have a 30 per cent higher risk of obesity; two copies, and the risk increases 7o per cent.
Even more remarkable, that risk appears to have changed over time. In a study published in 2014, researchers found people born before 1942 did not show an association between the risk variant and obesity. Those born later did.

The gene by environment interaction here is one of the most fascinating topics in human genetics.

Yes, there’s also some stuff about the thrifty genotype and caveman diets in there as well.

A laboratory at Kyoto University has been maintaining a long-term evolution experiment on fruit flies that started in 1954. Now the flies are adapted to living in pitch black darkness:

To keep the flies away from light, they are reared in vials kept in a large pot painted black on the inside and covered with a blackout cloth. When the vials and food need to be changed, the researchers tend to the flies in the pitch dark, then use a feeble red light to check on their work. Fruit flies can’t see this light because the species lacks those light receptor proteins that absorb red wavelengths.
When [Syuiti] Mori retired, he passed on the precious fly stocks to his colleagues at Kyoto University, who have maintained them continuously to this day. The stock of flies has now spent more than 1,500 generations without light. In human terms, that would be like sequestering generations of our ancestors in the dark for 30,000 years.

It’s an interesting type of experiment, similar to the Long Term Experimental Evolution project that has kept E. coli cultures under a constant environmental regime for more than 64,000 generations. The populations adapt to their environmental conditions, different from the natural situations in which their ancestors evolved.

Culture, mathematical models, and Neandertal extinction

I am not philosophically opposed to building a mathematical model of Neandertal populations. Some of my best work has involved mathematical model-building. Models have an important place in helping us to understand evolutionary history. But when it comes to understanding Neandertal and modern human interactions, we have had lots and lots and lots of models and few testable predictions.

When you assume that modern human populations grew faster than Neandertal populations, you will conclude that modern human populations could have out-reproduced the Neandertals. This is not a very deep piece of circular logic. and so I get a little frustrated at the number of papers that really say nothing more than this.

Find x meme

Modeling is a start, but cultural systems are complicated. Clever innovations can help a population grow, but a population can co-evolve with its culture, yielding not only more growth but also greater difference in growth between populations. A cultural innovation can be tied to a particular landscape or raw material substrate, making it difficult to apply outside the context where it was invented.

The populations that we call “modern humans” really did out-reproduce the Neandertals. That’s why living people have only a small fraction of Neandertal ancestry today. But is culture a sufficient explanation? Were modern humans just smarter than Neandertals? Or were other factors important to the interactions between these populations?

Differential equations and Neandertals

I’m taking up this subject today in response to a paper by William Gilpin, Marcus Feldman and Kenichi Aoki, who have investigated a differential equation model for population growth with feedbacks from competitive interactions. The abstract summarizes the paper well:

Archaeologists argue that the replacement of Neanderthals by modern humans was driven by interspecific competition due to a difference in culture level. To assess the cogency of this argument, we construct and analyze an interspecific cultural competition model based on the Lotka−Volterra model, which is widely used in ecology, but which incorporates the culture level of a species as a variable interacting with population size. We investigate the conditions under which a difference in culture level between cognitively equivalent species, or alternatively a difference in underlying learning ability, may produce competitive exclusion of a comparatively (although not absolutely) large local Neanderthal population by an initially smaller modern human population. We find, in particular, that this competitive exclusion is more likely to occur when population growth occurs on a shorter timescale than cultural change, or when the competition coefficients of the Lotka−Volterra model depend on the difference in the culture levels of the interacting species.

The Lotka-Volterra system of differential equations is one in which two components of a system change over time, in such a way that the amount of change in one component depends upon the magnitude of the other component. It has been most famously applied as a model for predator and prey populations, where predator population growth is coupled to prey population size. The behavior in this system can be cyclical—for example, if a predator population crashes, the growth of a prey population can resume, driving subsequent growth in the predator population.

This kind of feedback between components of the system is determined by the differential equation coefficients. The utility of this kind of system is that varying the coefficients allows us to investigate the conditions under which the system can exhibit stable, cyclical, or degenerate behavior.

Gilpin and colleagues assume the Neandertal and modern human populations to have been in a competitive interaction, where the rate of growth of the Neandertal population is smaller when the modern human population is larger, and vice-versa. Each population grows logistically up to a carrying capacity, which is determined by a parameter that they refer to as “culture level”. This “culture level” increases with population size, and it increases faster for the modern human population than for Neandertals—in other words, in this model Neandertals are stupid.

In this system, modern human populations grow faster when they wipe out the local Neandertals. They innovate faster when the population gets larger. If the difference in the rate of change of “culture level” is sufficiently large, Neandertals are doomed.

In principle, the model allows the authors to investigate the way that a second parameter, “culture level”, might constitute an advantage if Neandertals had a lower rate of increase. But the paper does not actually deploy this model in a way that would inform us about the importance of this second parameter. As a result, the conclusion is boring. If we assume that Neandertals were stupid, we don’t need a differential equation to tell us what happened to them.

Neandertal in a suit

Is “culture level” relevant?

The problem is not that we lack models to show how culture may have helped modern humans beat the Neandertals. The problem is that the archaeological data suggest that culture alone may be a poor explanation.

For one thing, the Neandertals persisted in Europe and central Asia long beyond the entry of modern humans into Asia. Initial modern humans in Asia exhibited no obvious cultural superiority over other Middle Paleolithic people, who were presumably archaic humans. “No cultural superiority” is maybe an understatement: Archaeologists have trouble finding any consistent material culture differences between people in West Asia before 50,000 years ago.

Tens of thousands of years later, when modern humans did start to enter Europe, they seem to have mixed with Neandertals more extensively. The later Neandertals were making symbolic artifacts, using pigments, feathers and other ornaments. The people who made the earliest Aurignacian, often assumed to be the earliest modern humans in Western Europe, did not have the intensity of symbolic artifacts of later Aurignacian and Gravettian people. Instead they seem to have been sparse and little different in most cultural practices from Neandertals.

In other words, at the critical time when modern humans entered Europe and their population apparently grew, there was little cultural difference between them. There is even less evidence that there was any cultural advantage to modern humans who spread across southern Asia prior to 50,000 years ago.

What gives? If we assume that “culture level” was a continuous variable, and that “modern humans” had a higher rate of increase than Neandertals, we get a very simple pattern. The data are not a simple pattern. So the “culture level” model seems like a bad model to account for the complexity of what actually happened.

Vital forces

“Culture level” is an archaeological version of “vital force”. Plenty of archaeologists think there is something special about “modern human behavior”, and believe that a “spark” entered the human population. After this vital spark entered the modern population, they were able to grow their population, spread around the world, and conquer the earth with their cultural adaptability. Some have written that this “spark” was a key mutation, some believe it was fully human grammar, some believe that it was a special demographic or ecological setting.

They are not thinking like biologists. The evolution of human cognition was not magic, and it was not caused by a “spark”.

I don’t object to the idea that Neandertals may have been cognitively different than modern humans—in fact, I think this is likely. The idea that Neandertals were fixed for stupid and modern humans fixed for smart is biologically incredible. Instead, we need to consider that if many Neandertals had challenges learning to work with some cultural innovations, many modern humans should have had such challenges as well. Key innovations, if rare, must have been stochastic.

To understand human cognitive evolution, we must consider how specific behaviors may have contributed to reproductive success. Useful cultural innovations tend to be transferred readily across groups, and so make unlikely vehicles for a continuous growth of one population at the expense of another. Was the ability to learn some cultural behaviors heritable? If so, it is unlikely that the ability to learn two behaviors was equally heritable; some must have been more influenced by genes than others. To the extent that behaviors are learned by exposure to skilled individuals, this exposure causes the selection in favor of the ability to learn to weaken as the trait becomes more commonly expressed.

Cultural selection to enforce cultural uniformity can be very effective in fixing cultural traits in a population, but is not especially likely to enhance the traits that really matter for adaptation to new environments. Indeed, cultural selection in many recent human groups has been depressingly conservative, preventing innovation and reducing population growth by imposing various handicaps.

In the real world, some archaic people—including the Neandertals—really were more successful than most early modern human groups. Neandertals as a population contributed more DNA to people around the world than their “conquerors”, the Upper Paleolithic people of Europe. Some modern human populations have massively grown during the last 50,000 years at the expense of others, often for cultural reasons. When we look at the diversity of those situations, we can see that culture is not easily broken down into a linear variable.

Non-linear culture

What makes culture more than a simple system of accumulating knowledge?

There are conditions under which a cultural system may be hard to transfer across groups. A cultural system may have co-evolved with some genetic variants, like dairying and lactase persistence. The cultural traits in such a system, even if learned, might not have had the advantage for Neandertals as for the modern humans that developed it. A cultural system may rely upon some elaborate codification of social behavior, like religious rules, that are not readily adopted by new cultural groups. Again, the behaviors that seem tied to reproductive advantage in such a system may not be as advantageous to people who lack the essential cultural background.

What we lack is some empirical demonstration of what cultural factors among Late Pleistocene people actually led to higher reproductive success. Archaeologists have proposed several, but have tested few. Most, like evidence for symbolic behavior, have subsequently been found in the Neandertals themselves, making them poor explanations for Neandertal extinction.

Later modern humans exhibited greater material culture diversity and more symbolic expression than earlier modern humans, thousands of years after the Neandertals were gone. This is true not only in Europe and central Asia, it is also true in other places long after the first modern humans appeared there: in southern Africa, west Asia, and southeast Asia. In every part of the world, the evidence for elaborate symbolic culture occurs long after the earliest evidence of modern humans. And in most of these areas, the first evidence for symbolic culture occurs substantially before the earliest evidence of modern humans.

To me, this means it was not just “culture level” that made a difference. I can imagine that there may have been some specific aspects of culture, which may not have been archaeologically visible, that made a key difference. Archaeologically visible material culture may reflect demographic growth, but not necessarily the key aspects that mattered to the initial dispersal of populations.

But I can also imagine that non-cultural factors were more important. For example, disease has been a key factor underlying the survival or replacement of populations during the past 10,000 years. It is not a stretch to imagine that disease influenced the Neandertals and other archaic peoples differently from each other and from modern humans. The evidence for selection on genes related to immunity from these archaic humans is now strong, and some of these may reflect pathogens or parasites that were important at the time of population contacts among these people.

Exploration needed

This is why we need more data, more exploration, more archaeology. I don’t mind if people continue to think of mathematical models, as they may help us to understand which factors are important. Listing all the possible factors doesn’t necessarily get us closer to a test of which of those factors were crucial to our evolution, and including every factor in a model will make it untestable.

But we are past the point where a simple model is going to tell us something we don’t already know. Neandertals are gone. Their cultures did not persist. Yet they are among our ancestors. What is necessary is to test models against the timeline of modern human dispersal as we currently understand it, and to take note of those predictions that we have not yet observed. It is the novel predictions of a model that make it valuable to the future.


Gilpin W, Feldman MW, Aoki K. 2016. An ecocultural model predicts Neanderthal extinction through competition with modern humans. Proc Nat Acad Sci USA (online) doi:10.1073/pnas.1524861113

Aleš Hrdlička, in the concluding paragraphs of The Most Ancient Skeletal Remains of Man, his 1914 review of the fossil evidence of human evolution:

The gradually accumulating finds which throw light on the physical past of man, have naturally stimulated further exploration in the same lines; and the various failures and uncertainties connected with some of the finds in the past have impressed all investigators in the field with the necessity of the most careful and properly controlled procedure. Besides men of science, the educated public, engineers controlling public works, and even many among the workmen in Europe have been impressed by these remarkable discoveries, and in hundreds of instances are doubtless watching for new treasures. Under these conditions we are justified in hoping that from time to time we shall receive additions to the precious material already in our hands; that these additions will fill the existing vacua, and gradually extend farther back to the more strictly intermediary forms between man and his ancestral stock, and perhaps eventually even to the source of these link-forms themselves, to the peculiar morphologically unstable family of the anthropogenous primates.
While the anthropologist is thus painfully and slowly reconstructing the past physical history of man, he is also with every new fact adding another imperishable block to the foundation upon which will stand not only the knowledge of the future in regard to man himself, but also the laws of his further physical development, and radically even those of his beliefs and his moral behavior. This is a part of the service of anthropology to humanity.

I think I’m going to take that phrase, “another imperishable block”. Seems ripe for mischief-making…

Ed Yong has an article in Atlantic on the mysterious evolution of the human chin: “We’re the Only Animals With Chins, and No One Knows Why”. He builds on a recent review paper by James Pampush.

It’s a nice read about a trait that has occupied more than the usual amount of paleoanthropological mindshare over the last hundred years.

For example, during human evolution, our faces shortened and our posture straightened. These changes made our mouths more cramped. To give our tongues and soft tissues more room, and to avoid constricting our airways, the lower jaw developed a forward slope, of which the chin was a side effect. The problem with this idea is that the chin's outer face doesn't follow the contours of its inner face, and has an exceptionally thick knob of bone. None of that screams “space-saving measure.”

There are some true “chin nerds” out there who will likely think the article doesn’t treat their favorite hypothesis fairly. The fact is, it’s sort of embarrassing that we have not yet come up with a persuasive test of any of these hypotheses.

Christopher Henshilwood has written a short article for The Conversation describing the archaeological importance of the finds from Blombos and elsewhere in southern Africa: “What excavated beads tell us about the when and where of human evolution”.

Modern human behaviour can be defined as behaviour that is brought about by socially constructed patterns of symbolic thinking, actions and communication. This allows for material and information exchange and cultural continuity between and across generations and contemporaneous communities. The capacity for symbolic thought is not the key defining factor for modern human behaviour. It is rather the use of symbolism to organise behaviour that defines us.
In other words, early humans were first behaviourally modern when symbols became an intrinsic part of their daily lives.

The tranformation of archaeology toward understanding the complexity of Middle Stone Age assemblages in southern Africa is impressive. I think it may be premature to write off the behavior of earlier people as non-symbolic. After all, the production of symbolic objects can only be functional within a society in which symbolic communication is near-universal. Language provides such a basis. Even simple forms of vocal communication in other primate species involve arbitrary learned relationships between sounds and concepts, which is the definition of symbolic communication. Auditory symbol use must have been present in the earliest forms of human language as well, and evidence from the vocal and auditory channels place the origin of vocal language much earlier than the Neandertals.

This is not modern human, I would say it is simply human.

I think we should take seriously the hypothesis that the differences between Middle Pleistocene populations were quantitative and not qualitative. Symbolic behavior did not emerge instantaneously; it evolved within a context of complex social interactions of earlier archaic human populations. The use of symbolic artifacts is an important clue to ancient social systems, evidencing one aspect of complexity. The artifacts give us one kind of evidence about the connections among ancient groups and the persistence of symbolic traditions.

I endorse this message from Holly Dunsworth:

Everyone’s likely heard it or seen it written on a protest sign: “I didn’t evolve from a monkey.” It’s a well-worn refrain of those who resist the evolutionary perspective. The pat response we often hear is, “You’re right! We didn’t evolve from monkeys. We share ancestors with them.” However, this talking point isn’t entirely honest.
Yes, we share ancestors with monkeys; we share ancestors with every living thing. But, also, to be clear: We did evolve from monkeys.

That’s from her new blog, “Origins”, from the new website, SAPIENS. It’s a new public communication portal sponsored by the Wenner-Gren Foundation for Anthropological Research, and I’ll look forward to seeing more of what they have in store.

How long does it take to publish new hominin species after discovery?

In an earlier post, I looked at descriptions of new hominin species during the last 25 years, to see how long they took from submission to acceptance in the journal where each was published (“Hominin species and time in peer review”). The data show that these papers have taken a median time of 70 days to review. But as I noted, the time in peer review probably doesn’t tell us very much about the quality of review. What stands out is that the duration of review has not changed appreciably across the 25-year span.

Au. sediba
Australopithecus sediba was 20 months from first discovery to publication. Photo credit: Lee Berger

A more interesting time interval is from discovery to publication. This time includes not only the peer review and other editorial processes, but also the primary scientific work. Technicians prepare and conserve the fossils, specialists in anatomy take systematic measurements and observations, and they carry out comparisons with other samples of fossils and skeletal collections.

Analysis can take a lot of time. Some fossils require considerable reconstruction. Today such reconstruction can be carried out virtually after 3D scanning of the material, which sounds like it should save time but somehow always seems to take longer. If a specimen preserves a rare piece of anatomy, the comparable anatomical areas may not have been well-reported in other fossil samples, and therefore one or more researchers may need to make special research trips to study fossils from other parts of the world.

Considering the diversity of fossil preservation across different field sites, you might expect the process of publishing diagnoses of new fossil species to be equally diverse in how long they take to prepare.

The data show the opposite: the duration of scientific work preceding the diagnosis of new hominin taxa has generally been between one and two years, and has remained pretty much the same over the last 25 years.

Discovery dates

When was a species found? This is not a simple question, because the evidence for a new species is rarely limited to a single specimen. A team may find fragments that suggest the existence of a new species in one field season, and later find additional evidence that enhances the case.

For example, the earliest specimen now attributed to Australopithecus anamensis to have been discovered is a humerus fragment from Kanapoi, KNM-KP 271, which was found by Bryan Patterson’s research team in 1966. This fragment was known to represent a very early hominin, but does not present anatomical features that would have enabled a clear diagnosis relative to other known hominin species. Only much later did Maeve Leakey and colleagues uncover more remains from Kanapoi and Allia Bay that enabled a diagnostic comparison with other species.

Every formal description of a new species designates a single specimen, known as the “holotype”, that will serve as an anatomical reference for future scholars. Under the rules of the International Code of Zoological Nomenclature, the holotype is forever tied to the formal species name; it can never be recycled to serve as the holotype for any other species name. For Au. anamensis, Leakey and colleagues designated the specimen KNM-KP 29281, discovered in 1994, as the holotype of the species. So although the first specimen now attributed to Au. anamensis was found in 1966, the holotype was found 28 years later.

Even the holotype discovery date is not really the time of “species discovery”. Generally, a team of scientists tests the hypothesis that a new fossil assemblage belongs to an existing species. If the evidence rejects this hypothesis, a team may move toward formally defining a new species. “Discovery” of this new species may happen more-or-less gradually during the analysis of fossil remains, as researchers develop evidence in comparison with other fossil samples. In some cases the team may recognize this distinctiveness very rapidly, in others more slowly, depending upon the quality of the evidence and the difficulty of making the comparisons. Sometimes additional field seasons may be necessary to add more fossil specimens and thereby broaden the scope of comparisons. In some cases, it is the holotype that is unearthed during a later field season, well after a field team has other specimens that make them think a new species exists.

Looking at the records available in formal taxonomic diagnoses, the only practical alternative is to consider the time of holotype discovery. Papers usually report this date and do not reliably list the discovery dates of paratype specimens. Even with holotypes, the reporting is uneven. Some papers have reported a single day of discovery, in which case it is simple to calculate the time from discovery to publication. In many cases, however, only a month of discovery (e.g., “March 2014”) is provided. There several reasons why a single date may not be available. A holotype may have taken several days to uncover during excavation, or it may have been reconstructed from fragments found over a range of dates. In extreme cases, parts of a holotype might have been found in successive field seasons.

In a few cases, the paper gives only the year of discovery (for example, the only date given for KNM-KP 29281 is “1994”). For my comparisons here, if the paper gives no indication of the timing of the field season, I have assigned a date of January 1 to these discoveries. The resulting timeline is necessarily longer than the real time taken by a research team to describe its discovery, in theory up to 12 months longer if the specimen was actually discovered in December.

The results

Number of months from holotype discovery to publication for hominin species since 1990
Asterisks (**) indicate species for which the discovery year was supplied but not the date; the point in this graph assumes discovery on January 1 of that year, making this the maximum possible time from discovery to publication. In reality they may be as much as 12 months less than indicated here.

In this chart, H. cepranensis is an outlier, as discussed below. The remainder of the data show no reduction or increase in the time from discovery to publication over the last 25 years. Out of the fifteen formally named taxa here, ten were published within two years after the discovery of the holotype specimen. Only two of those appeared within one year after discovery. The median time from discovery to description is 20 months.

The x-axis of the chart is the discovery date, not the publication date. There may be taxa that have been discovered in the past few years that have not yet been published, and obviously any such species would not be represented in the chart. H. gautengensis, published in 2010 but based on a holotype discovered in 1976, is not included in the chart.

This period of two years or less includes the time spent by the species in peer review and revision, which I discussed in the previous post. In the case of Homo floresiensis, for example, the time from submission to acceptance of the manuscript was more than 6 months, and the publication of the paper was still only 14 months after the discovery. The paper describing Australopithecus ramidus was slightly more than two months from submission to acceptance; the total timeline from discovery of the holotype to publication was only 9 months.

In light of discussion about the publication pace of Homo naledi, these data may surprise people. H. naledi may be remarkable for the quantity of anatomical evidence, but not the time from discovery to publication. It took substantially longer to move from discovery to publication for H. naledi than for Au. ramidus (9 months), S. tchadensis (12 months), or O. tugenensis (3 months), and even longer than H. floresiensis (14 months) and Au. garhi (17 months).

What explains the consistency in time to publication?

A varied array of research teams around the world have composed effective and highly-cited diagnoses on a varied array of fossil assemblages, with all necessary research and editorial handling and peer review within two years or less. Setting aside diagnoses of new taxa based on previously-published fossil assemblages, the timeline of the procedure has been remarkably consistent.

I think this consistency of timeline can in large part be attributed to the consistency of content.

  • Formal diagnoses follow a common recipe, with a stereotypical block giving essential diagnostic information, and a discussion that places the new taxon into a phylogenetic and adaptive context.

  • The addition of a new taxon generally must reiterate the key information of the next most similar taxon.

  • Most diagnoses of hominin taxa are relatively short, with a median of 7 text pages. Only Homo naledi and Homo gautengensis were diagnosed in papers longer than 11 pages.

  • Although scientific papers have undergone a major trend during the past 15 years to add supplementary information in addition to the main text, this has affected very few of the hominin taxa included here. Only Au. deyiremeda, Au. sediba, and H. floresiensis were accompanied by supplementary information of substantial length.

Some of these species are now represented by fossil samples that were difficult to reconstruct and analyze. But in nearly all cases, the reconstruction and analysis was a second phase of work that followed the formal diagnosis of the new taxon. Therefore most of the difficult work of reconstruction could follow formal diagnosis. This was perhaps most famously the situation with Au. ramidus, where the most famous specimen is not the holotype. But to one degree or another, the process of later, deeper description has been a routine part of the study of most of these species.

The exceptions

What about the exceptions, the species that took much longer than two years to diagnose?

Five taxa required more than two years from discovery to publication. The diagnosis of one of those taxa, H. cepranensis, was based on a holotype specimen that had been described in a peer-reviewed publication several years earlier. To this we can add several similar cases of new formal diagnoses of taxa published in the last 25 years based on previously published fossil material.

  • Curnoe (2010) based the diagnosis of H. gautengensis on StW 53, which was found in 1976, with a description published by Hughes and Tobias (1977).

  • White et al. (1995) based their diagnosis of the genus Ardipithecus on the species diagnosis of Au. ramidus published in 1994.

  • Haile-Selassie et al. (2004) based their diagnosis of the species Ar. kadabba upon the diagnosis of the subspecies Ar. ramidus kadabba that Haile-Selassie had previously published in 2001.

I don’t think these cases are directly comparable to the original first assessment of newly excavated material. Such secondary study is also a process of discovery, sometimes undertaken due to the recovery of additional material (as in the case of Ardipithecus), but the timeline of such research is extremely variable.

Two of the taxa that took longer than two years to diagnose were subspecies: Ar. ramidus kadabba and H. sapiens idaltu. Providing such formal diagnoses of subspecies is a relatively new innovation in hominin taxonomic practice. One motivation to name a subspecies is to preclude the use of a holotype specimen for other taxonomic diagnosis in the future. As the case of Ar. kadabba shows, future discoveries may force a reassessment of the variation presented by a sample, sometimes prompting the promotion of such a subspecies to a species-level taxon.

I can think of two hypotheses to explain why the diagnosis of these subspecies has occupied a longer period of time than species or genera. One possibility is that the relatively subtle anatomical variation that distinguished a subspecies may require more time to fully understand and characterize. A second possibility is that researchers may work on new species and genus-level diagnoses with greater intensity than a subspecies diagnosis. These are not mutually exclusive, and probably there are other possibilities as well. But again, it is not clear that researchers treat the formal diagnosis of a subspecies as the same kind of task as the diagnosis of a higher-level taxon.

This leaves only Au. deyiremeda and H. antecessor, which required approximately 4 years and 3 years from holotype discovery to description, respectively. Both of these are instances in which additional field seasons may have added more information from additional specimens, and as I move forward, I’ll consider whether the sample size and anatomical regions preserved in the holotype and paratype specimens help to explain the timeline of either of these taxa.

Is everyone “rushing” their research?

The standards by which I judge the quality of science are replicability and originality, not speed. The formal diagnosis of a taxon is one of the least creative exercises in paleoanthropology, with several highly standardized parts. These essential ingredients have emerged through history as a way of ensuring the replicability of the key observations that contribute to attributing other fossils in the future. Considering that many hominin fossils are practically inaccessible to independent scientists, scientists must insist that the formal description of such fossils will meet a high standard of replicability.

With that in mind, is there a correlation between replicability and speed of publication?

I don’t think so. Among the papers that are published within four years of holotype discovery, I just don’t see any obvious correlation between time to publication and replicability.

Keep in mind that this is a very small sample to try to find such a correlation. Certainly there are papers here that omit crucial data, there are papers that have given rise to years of controversy, and there are papers that have led to relatively little subsequent reassessment of the broader phylogenetic pattern of hominins. Any set of independent scientists would probably have a wide variety of “favorites” or choices as “best hominin description EVAH”.

But even if we take the strongest critics of new species, I don’t think we see any relationship between a person’s preferences about which diagnoses are replicable and the timeline of publication.

As an example, Tim White has been publicly critical of many of these species as examples of “taxonomic inflation”. Such “inflated” species include H. naledi, Au. deyiremeda, Au. sediba, K. platyops, O. tugenensis, S. tchadensis, Au. anamensis, and H. georgicus. I may be missing several. The median time from discovery to publication of these eight taxa is at most 20 months. The median time for the three taxa published by White himself is 17 months. Whatever the standard of quality and replicability applied by White, time is not an explanation.

Production of a taxonomic assessment for newly discovered hominin fossils is a basic responsibility of field research. Assessing whether a fossil or an assemblage belong to a previously-known taxon is relatively straightforward. That assessment may rely upon small anatomical details, but a review of the anatomy of a fossil will not likely miss those details if they are present. So there’s nothing about the procedure that in principle should take many years to accomplish.

In light of the evidence from the last 25 years of formal taxonomic diagnosis in hominins, it is clear that in most cases, this process is very efficient.


  1. As in the previous post, I am missing data for Australopithecus bahrelghazali.


References for this post are the same as listed in “Hominin species and time in peer review”.

From chapter 2 of Sharing Publication-Related Data and Materials: Responsibilities of Authorship in the Life Sciences, a publication of the National Research Council of the National Academy of Sciences, U. S. A., in 2003.

Community standards for sharing publication-related data and materials should flow from the general principle that the publication of scientific information is intended to move science forward. More specifically, the act of publishing is a quid pro quo in which authors receive credit and acknowledgment in exchange for disclosure of their scientific findings. An author’s obligation is not only to release data and materials to enable others to verify or replicate published findings (as journals already implicitly or explicitly require) but also to provide them in a form on which other scientists can build with further research. All members of the scientific community—whether working in academia, government, or a commercial enterprise—have equal responsibility for upholding community standards as participants in the publication system, and all should be equally able to derive benefits from it.

The entire book, reporting on the NRC “Committee on Responsibilities of Authorship in the Biological Sciences” in 2002, is available online for free.

I spent part of the week preparing for the beginning of classes next week here at UW-Madison. When I’m teaching introductory classes, I’m always more attentive to the basic information that’s available for students.

Neil Shubin reminds us that the Howard Hughes Medical Institute has made all three episodes of the Tangled Bank documentary, “Your Inner Fish”, available for streaming:

As a consultant for the production, I’m very enthusiastic about this. I’ll be using the book, Your Inner Fish, in my course on Evolutionary Biology this semester. It’s such a great way to look at how evolution has transformed vertebrates into our own unique body form.

I’m less enthusiastic about the pictures of hominin relationships that teachers have to show students:

My post on the timeline of peer review for hominin species got some attention:

Some tweets about the new archaeological finds on Sulawesi:

On the subject of data access and replicability in science, first another hopeful sign that African countries are moving toward adoption of open access principles:

And my reminder that I do not consider access to data as an optional add-on to good science.

This week, another series of revelations about sexual harassment by professors of astronomy and astrophysics has dominated my tweetstream. So many voices there that need hearing, many sharing their own harrowing personal experiences. One summarizes the problem:

Why do universities cover up high-profile harassment? Look for the money

How can professors get away with years of sexual harassment or abuse of graduate students without their universities taking any action?

I don’t think money is the entire answer, but I do not think it is a coincidence that these professors generated millions in grants for their institutions.

This week, a story of the disciplinary action against Christian Ott at Caltech was told by Azeen Ghorayshi from Buzzfeed (“He Fell In Love With His Grad Student — Then Fired Her For It”). Last fall Ghorayshi also broke the story of long-term sexual harassment by astronomer Geoffrey Marcy at UC-Berkeley. People reading the Ott story are rightly amazed that a department would fail to take action as a professor has a succession of nine graduate advisees leave in a span of a few years. Different fields and institutions have different standards, but this remarkably high attrition is a clear signal that something serious has gone wrong. So how could an entire department ignore the signs?

The story of Timothy Slater at the University of Arizona was made public this week by Congresswoman Jackie Speier, as detailed in a Mashable story: “Congresswoman reveals prominent astronomy professor’s history of sexual harassment”. Speier also expresses frustration and amazement at the failure of universities to take effective action to end instances of harassment, as quoted in a Wired interview (“Rep Jackie Speier on Why She’s Taking on Sexual Harassment in Science”):

In my work on sexual assault in the military and sexual assault on college campuses, the pattern is there. Typically predators are in environments where there is a closed institution, where they have their own code of conduct—whether the military code of justice or the code of conduct at a university. Often times these cases are not handled appropriately. They sweep them under the rug. It allow sexual predators to reoffend. Often times it’s six or seven times before they are actually caught because everyone believes it’s a one off situation.

In the three cases that have been made public, the universities (the University of California-Berkeley, University of Arizona and California Institute of Technology) investigated and took disciplinary action against the professors in question. In response to the public relevations this week (and with Geoffrey Marcy last fall), people have been speaking out to criticize these institutions’ responses, focusing on the weakness of the disciplinary actions, the lack of protection for future students or adequate response to the injustice suffered by past students. In two of the cases, the faculty member successfully moved to another institution in a senior high-salary position despite sexual harassment investigations or disciplinary action at their previous institution.

These cases are outrageous. These are not cases where a department made a bad hire that no one could have anticipated. High-salary scientists do not make mid-career moves into endowed positions without the special involvement of university administrators. Each of these universities has profited handsomely from its association with these scientists. The three cases now public involve more than $17 million in NSF and NASA funding.

I’ve been surprised at how little attention has been given to the financial aspect of these cases. Federal grants are public records, and we are not talking about small amounts of money. When people ask why university administrators have not been forthcoming about sexual harassment and abuse of students, I believe we must look at how those administrators continue to benefit from looking the other way.

A hint about the importance of funding in this issue comes from the Mashable article that discusses Slater’s case.

Slater began his career as a Kansas high school science teacher in 1989 and has since become one of the most renowned names in astronomy education. Slater said that, over the course of his career, he has received more than $30 million in federally funded grants, and in developing the curriculum for a new generation of astronomy teachers, has received several awards and prestigious appointments.
In 1996, he took a job as a physics professor at Montana State University, where he founded the Conceptual Astronomy and Physics Education Research (CAPER) program that his wife Stephanie today runs as an independent nonprofit. In 2001, he was hired as an astronomy professor at the University of Arizona.

I did a public records search for NSF and NASA awards for each of these three scientists. I could not confirm the $30 million claim based on searching for awards at NSF and NASA. My search is only as good as the online systems for federal grant searches, and it is probable that Slater has significant funding from other federal grant sources. I found a total of $5,450,737 in NSF awards credited to Timothy Slater as either Principal Investigator or Co-Principal Investigator. Additionally, $652,637 was awarded to Slater by NASA at the University of Wyoming and $85,977 at the University of Arizona.

NSF records credit Christian Ott at Caltech with $5,106,789 for grants upon which he is listed as Principal Investigator (PI) or Co-Principal Investigator (co-PI). NASA credits him with $150,000 as PI.

The total in NSF awards credited to Marcy as PI or co-PI is $3,636,399. NASA additionally credits $2,612,545.98 to Marcy as PI since 2005. As large as these amounts are, they are small compared to the $100 million in funding from the Breakthrough Prize Foundation (“Internet investor Yuri Milner joins with Berkeley in $100 million search for extraterrestrial intelligence”). Marcy’s work on extrasolar planets was publicly recognized as a factor behind this award, and he was prominent in the public announcement.

These scientists are not merely successful at grant-getting, they are rainmakers for their universities and departments. In times of increasing challenges for state support for these research universities, the funding brought in by such scientists keeps the budget afloat.

Many people who are not familiar with the U.S. federal grant system may not know that much of this money goes directly into university budgets instead of the project for which the funds were granted. Nature News did a nice article on indirect costs in 2014 that explains them well: “Indirect costs: Keeping the lights on”. When a federal agency funds a grant, the agency provides an additional amount of funding directly to the institution, above and beyond the direct costs of the project budget. These “indirect costs” are intended to help fund the institution’s research enterprise—buildings, laboratory space, electricity, personnel to administer the grant accounting and compliance with federal regulations. Each university negotiates an indirect cost rate with the federal government, which is applied to every federal grant awarded to the university.

Negotiated indirect cost rates differ greatly among institutions. At Caltech, the current indirect cost rate for on-campus research is 64.3% of direct costs, meaning that every budgeted dollar of direct costs comes with a supplementary fund of 64.3 cents to the university. At the University of Arizona, the current rate is 53.5% for on-campus research. Off-campus research indirect cost rates are much lower, in the mid-twenties. Indirect cost rates have consistently increased year-over-year, so grants funded 10 years ago may have had indirect costs from 45% to 55%, not the 50%–65% common today.

Indirect costs mean that when we look at the amount of grant funding awarded to the three scientists in these cases, each university has taken in millions of additional dollars of federal funding to its bottom line. That money was not allocated to these scientists’ particular projects, it solved budget problems for administrators.

Each case that becomes public teaches us more about a culture of neglect when it comes to sexual harassment and abuse of students. Harassers are not the majority, they are a tiny handful of scientists. But they are powerful, and too many departments are full of faculty who do nothing to stop them. That culture comes from treating grants and publications as the only important standards of performance assessment.

I am discouraged that every time I hear about one of these cases, the accused faculty member invariably has been a big NSF grantwinner.

Funding and training are strongly connected at universities. Many federal grants of this kind include direct funding for the salaries of graduate student research assistants and postdoctoral scientists. Most applications address graduate student training as part of their intellectual merit and broader impact. Additionally, when a university’s policies are not protecting its graduate students, we should consider other ways that the federal government is funding graduate education at the institution. Among the most pertinent is the IGERT program by which NSF directly funds interdisciplinary graduate work: more than $6 million at UC-Berkeley and $400,000 at the University of Arizona.

What kind of oversight could NSF and NASA implement to change this? Astronomy is not alone. Anthropologists are now discussing our field’s history of sexual harassment in light of the SAFE study, which showed the extraordinarily high fraction of students who are sexually harassed or abused during fieldwork research experiences. A research project should not be a fiefdom in which the PI has droit de seigneur. But this will persist as long as PIs are rewarded for this culture of abusive behavior.

The culture needs to change. The harm to students is irreparable. The harm to science will be a legacy across the next thirty years haunted by the shadows of promising careers that were stopped before they began. Grant reviewers and panels need to take seriously their responsibility to training the next generation of scientists. At a minimum, that means demanding evidence of a project’s demonstrated success in training students, including evidence about a university’s or department’s track record.

Rep. Speier has rightly criticized the universities for keeping the cases quiet. Each university profits from silence. Universities will hide this behavior as long as administrators believe that future funding will keep rolling in. If we want to end the secrecy, we need to stop the money.

We know about the cases only because victims have spoken out, and particularly we owe much to dogged investigative reporting by Buzzfeed and Ghorayshi. Many important voices have yet to be heard, including some who may draw attention to additional cases both inside and outside of astronomy. We need to keep listening.

More reading:

Ed Yong’s new piece in National Geographic on the evolution of eyes across different branches of animal life is a great one: “Inside the Eye: Nature’s Most Exquisite Creation”. Awesome photographic comparisons of eyes from different kinds of creatures and discussion of their evolutionary diversity.

The same can’t be said for other eye components. Take lenses. Almost all of them are made from proteins called crystallins, which improve their owners’ vision by focusing light onto underlying photoreceptors. But unlike opsins, with their single dynasty, crystallins are unified by name only. Yours are unrelated to those of a squid or a fly. Different animal groups have independently evolved their own brand of crystallins by co-opting proteins that had very different jobs, unrelated to vision: Some broke down alcohol; others dealt with stress. But all were stable, easy to pack, and capable of bending light—perfect for making lenses.

The eye is the evolutionary gift that keeps on giving to those of us who teach about homology and convergence.

A few years ago, historian of science and creationism Ronald Numbers did a great interview with Steve Paulson, which is on Salon: “Seeing the light — of science”. Numbers is the foremost academic expert on the history and growth of the creationism movement, both in the U.S. and globally, and he is one of my University of Wisconsin-Madison colleagues.

This interview looks at Numbers’ own history as a Seventh-Day Adventist, his journey from biblical literalism, and his historical perspective on the strategies of recent creationists.

Well, most people who reject evolution do not see themselves as being anti-scientific in any way. They love science. They love what science has produced. It’s allowed the conservative Christians to go on the airwaves, to fly to mission fields. They’re not against science at all. But they don’t believe evolution is real science. So they’re able to criticize one of the primary theories of modern science and yet not adopt an anti-scientific attitude. A lot of critics find that just absolutely amazing. And it’s a rhetorical game that has been played fairly successfully for a long time. In the latter part of the 19th century, when Mary Baker Eddy came up with her system that denied the existence of a material world — denying the existence of sickness and death, which flew in the face of everything that late 19th century science was teaching — what did she call it? “Christian science.” The founder of chiropractic thought that he had found the only true scientific view of healing. The creationists around 1970 took the view that’s most at odds with modern science and called it “creation science.” They love science! And they want to partake in the cultural authority that still comes to science.

Hat tip: Matt Sponheimer via Twitter.