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paleoanthropology, genetics and evolution

Photo Credit: Pre-Clovis Gault Assemblage artifacts. Thomas Williams et al. (2018) CC-BY-NC

Is there a trade-off between publication impact and open approaches?

Two Dutch biomedical researchers discuss how they are trying to move their institution away from mere quantity of research and citations, and toward real clinical impact: “Do our measures of academic success hurt science?”. They begin their essay with a scenario that reminds me of human evolution research:

A Ph.D. student wants to submit his research to a journal that requires sharing the raw data for each paper with readers. His supervisors, however, hope to extract more articles from the dataset before making it public. The researcher is forced to postpone the publication of his findings, withholding potentially valuable knowledge from peers and clinicians and keeping useful data from other researchers.

I agree with much of what they say in this essay. But I think their opening scenario doesn’t really express a trade-off they are trying to illustrate between an artificial measure of “impact” and real impact.

What we keep finding in human evolution research is that sharing the data leads to higher impact. Papers are published faster, they are cited more widely, and they lead to career advancement for the authors.

It is true that some scientists try to keep datasets private so that other researchers cannot replicate their work. But that is counterproductive to their own research, not only to the field. Researchers who are publishing slowly, not distributing data in a way that can be inspected and used, are not achieving publications, citations, or “impact” even in the artificial, publication-oriented sense.

Using open approaches is not just the way to advance science and its impact on the public, it is also the way to advance careers. There is no trade-off here, not that I’ve experienced at least.

Link: DNA conspiracy theories

In a post this week on the Anthropology News site of the American Anthropological Association, the sociologist Joan Donovan describes her work on DNA identity and self-described white nationalists: “Written in Blood”.

As social scientists, we wanted to know more about how white people, particularly white nationalists, interpret DNA ancestry tests to justify racial purity. It was an important question for us because we were also witnessing the early growth of a white nationalist movement, rebranded as “the Alt-Right” in 2015. Fast forward to December 2017 and the satirical website Cracked.com reported that an anonymous employee from a DNA ancestry company said that they were purposefully messing with some customers’ data in order to anger racists. How and why does a conspiracy theory like this emerge and spread?

This piece is worth reading as a contribution to the conversation on DNA and race.

I have a slightly different perspective than Donovan on this issue.

Cracked.com is in fact a satire site, and many “conspiracies” today get started as satire. But I don’t think there’s anything ridiculous about the idea of DNA genealogy companies “tipping the scales” on ancestry results. For one thing, during just the last few months, we’ve seen a number of stories in which DNA genealogy testing companies gave “Native American” ancestry to samples that (without the companies’ knowledge) had been taken from dogs.

Here’s a story describing one of these cases: “Another DNA Testing Company Reportedly Gets Fooled by Dog DNA”.

Such cases point to the real problem that some companies doing business in this area are not maintaining best practices, to say the least. Without commenting on these particular cases, consumers should make themselves aware that some DNA ancestry tests may be unscrupulous or fraudulent. Indeed, even companies recognized as legitimate businesses may have been reporting results to customers that diverge substantially from the best scientific knowledge about human genetics.

And it is well-known that even the most responsible companies base their reports of “geographic ancestry” upon samples that are very large in Europe but tiny in Africa and the Americas.

All this makes it hard even for experts to tell genuine from fraudulent results in this area, without having access to the algorithms and DNA results. For the public, such “ancestry” tests are simply a black box.

With this “Wild West” atmosphere, it is hardly a stretch to think that a company might report DNA results more skewed to political or commercial interests than to reality.

Genomes of straight-tusked elephants

Earlier this month in eLife, Matthias Meyer and colleagues published a cool paper: “Palaeogenomes of Eurasian straight-tusked elephants challenge the current view of elephant evolution”.

The straight-tusked elephants lived in Europe and western Eurasia as far east as India during the Pleistocene. Most people are familiar with other extinct elephant relatives, such as mammoths or mastodons. The straight-tusked elephants were not mammoths, and they are assumed to be much more like living elephants because they seem to have entered more northerly parts of Europe mainly during interglacial times. Paleontologists have noted that the straight-tusked elephants share some morphological features with Asian elephants, as mammoths do also. For some paleontologists, these similarities are so compelling that they have classified Palaeoloxodon as part of the Asian elephant genus, Elephas.

Ancient DNA evidence is breaking open the study of how the extinct relatives of living elephants moved, interacted, and evolved. First mitochondrial, and more recently nuclear gene sequences have revealed different populations that lasted more than a million years, yet hybridized and mixed where they met.

During the last ten years, it has become clear that populations of elephants in the central African forest have a long history as an evolving lineage distinct from savanna elephants across most of Africa. Forest and savanna elephants have increasingly been recognized as two species, Loxodonta cyclotis in the forest, and L. africana across the rest of Africa. No fossils have been attributed to L. cyclotis, and the L. africana fossil record is quite sparse up until 20,000 years ago.

Before that time, Africa itself was rich in elephants attributed to Palaeoloxodon, especially P. recki, which many sources identify as Elephas recki. P. recki has been identified from fossils as early as 4 million years ago, and as late as 300,000 years ago. Other African species of Palaeoloxodon (again, often classified as Elephas) have been interpreted as part of a single P. recki lineage, including the earlier P. ekorensis and the later P. iolensis. P. iolensis survived until around 30,000 years ago. With so many species identified as Elephas or closely related to Elephas, and with mammoths sharing so many features with living Asian elephants, the basic idea has been the Asian elephant branch of the elephant phylogeny was once global, with mammoths spread across the northern tier of Eurasia and across the Americas, extinct P. antiquus in western Eurasia, extinct P. namascus further east in Asia, and extinct P. recki in Africa. Paleontologists have speculated that P. namascus may itself be the immediate ancestor of living Asian elephants, Elephas maximus. Living African elephants, Loxodonta, were the odd elephants out.

Meyer and colleagues obtained mitochondrial genomes from four individuals of P. antiquus, three of them from Neumark-Nord, Germany, and one from Weimar-Ehringsdorf, Germany. They find that the Neumark-Nord elephants probably date to the last interglacial, around 120,000 years ago, while the Weimar-Ehringsdorf elephant dates to the previous interglacial, around 230,000 years ago. This is a pretty small section of the overall geographic range covered by P. antiquus:

Palaeoloxodon sites across western Eurasia, from Meyer et al. 2017
Figure 1 from Meyer et al. 2017, original caption: "Palaeoloxodon antiquus, geographic range based on fossil finds (after Pushkina, 2007). White dots indicate the locations of Weimar-Ehringsdorf and Neumark-Nord."

What they found was that P. antiquus mitochondrial genomes are not related to Elephas at all; they’re related to forest elephants:

Surprisingly, P. antiquus did not cluster with E. maximus, as hypothesized from morphological analyses. Instead, it fell within the mito-genetic diversity of extant L. cyclotis, with very high statistical support (Figure 2). The four straight-tusked elephants did not cluster together within this mitochondrial clade, but formed two separate lineages that share a common ancestor with an extant L. cyclotis lineage 0.7–1.6 Ma (NN) and 1.5–3.0 Ma (WE) ago, respectively.

That’s not a small difference. Living Asian and African elephants came from a common ancestral population more than 6 million years ago, during the Late Miocene. They are about as different from each other genetically as humans and chimpanzees. The fossil story was just wrong–and it’s as big a difference as misidentifying a Neanderthal as a fossil chimpanzee.

Elephant phylogeny from Meyer et al. 2017
Elephant mtDNA and nuclear DNA phylogeny from Meyer et al. 2017. The Neumark-Nord (NN) and Weimar-Ehringsdorf (WE) straight-tusked elephants are indicated. The mtDNA tree has a time scale (bottom) but the nuclear DNA tree has no time scale associated with it.

All four of the P. antiquus mitochondrial lineages are on the same branch as living forest elephants, and in fact some forest elephants have mtDNA genomes that are closer to P. antiquus than to some other forest elephants. In other words, the mitochondrial genomes of P. antiquus fall within the variation of L. cyclotis. Within this variation, the mitochondrial lineage of the earlier Weimar-Ehringsdorf elephant is part of a different clade than the three Neumark-Nord elephants, so the P. antiquus mitochondrial genomes are not a monophyletic group.

Now, we might well expect the story with the nuclear genome would be different for elephants. We know that the story for Neandertals is different considering the mitochondrial and nuclear genomes: the Sima de los Huesos nuclear genome groups clearly with later Neandertals even though the mtDNA of later Neandertals is more similar to that of living humans.

There is another reason why elephant nuclear and mtDNA genomes might be discordant. In humans, mtDNA is markedly less diverse than most parts of the nuclear genome, and mtDNA types occur across wide geographic areas. Elephants are the opposite. Their mitochondrial DNA exhibits substantially greater variation among populations than the average for the nuclear genome, because female elephants very rarely transfer between groups. Most gene flow in elephants is male-mediated, and male elephants sometimes disperse over very long distances. These contrasting patterns of nuclear and mitochondrial diversity in elephants are consistent enough to provide a way to “triangulate” the region that ivory samples originated (Ishida et al. 2013).

Meyer and colleagues cannot assess yet whether the Weimar-Ehringsdorf elephant would yield a divergent nuclear genome, because they didn’t get nuclear evidence from it. But two of the Neumark-Nord P. antiquus specimens yielded nuclear genome data and they are a close sister group compared to all the forest elephants. That is, the African forest elephants were much broader in their mtDNA phylogeny, and tighter together in their nuclear genome, just as one would expect from the mass of evidence about them.

Palaeoloxodon antiquus tooth, by Khruner (Wikimedia)
P. antiquus tooth. Photo credit: Khruner, CC-BY.

So, that’s an interesting data point about elephant evolution. A widespread extinct species of elephant, which on morphological grounds was interpreted as an Asian elephant relative, is actually related to forest elephants within Africa. Forest elephants today are a relative island species in central Africa, surrounded by savanna elephants. So from today’s standpoint, forest elephants look like a geographic and phylogenetic relict of a much more diverse lineage that once existed.

We already know that today’s situation did not exist earlier in the Pleistocene. In the past, many parts of Africa were inhabited not by today’s savanna elephants but instead by other extinct species, for much of the Early and Middle Pleistocene, P. recki. Savanna elephants are found in the fossil record as early as 500,000 years ago, but they are a relatively rare component of the elephant diversity in comparison to the extinct Palaeoloxodon species.

Of course, without ancient DNA evidence, it’s not certain that these other extinct Palaeoloxodon species are closely related to the forest elephants and P. antiquus.

Furthermore, the nuclear genome evidence presented by Meyer and colleagues does not establish whether the P. antiquus population may have exchanged genes with Asian elephants, thereby accounting for some of its anatomical resemblance to them. Hybridization has already been found to be widespread among the varieties of mammoths, and it continues to occur between savanna and forest elephants despite what appears to be a multi-million year separation. We might expect the same of other extinct elephant species.

When Eleftheria Palkopoulou presented on some of these data at a conference in 2016, she did talk about hybridization. Ewen Callaway reported on that conference presentation at the time: “Elephant history rewritten by ancient genomes”.

Palkopoulou and her colleagues also revealed the genomes of other animals, including four woolly mammoths (Mammuthus primigenius) and, for the first time, the whole-genome sequences of a Columbian mammoth (Mammuthus columbi) from North America and two North American mastodons (Mammut americanum). The researchers found evidence that many of the different elephant and mammoth species had interbred. Straight-tusked elephants mated with both Asian elephants and woolly mammoths. And African savannah and forest elephants, who are known to interbreed today — hybrids of the two species live in some parts of the Democratic Republic of Congo and elsewhere — also seem to have interbred in the distant past. Palkopoulou hopes to work out when these interbreeding episodes happened.

None of these scientific results concerning interbreeding and hybridization are in the new paper by Meyer and colleagues. So I expect we will see much more from these new genome sequences.

W. W. Howells, in the conclusion of the 1980 review, Homo erectus–Who, When and Where: A Survey”:

So we might be wise to be continually careful in writing about Homo erectus, making clear whether one is referring to a population or taxon with a workable definition (such as might embrace all the Chou-k'ou-tien and Javanese fossils), or to a grade taken broadly, or to a time zone (Campbell, 1972). The history of argument about the "Neanderthal phase" should show what the problems may be. As to subspecies of H. erectus, there [sic] are of course legitimate and what we should look for; we should expect their development and their survival over considerable periods. There is no reason to suppose that H. erectus as a species did not include all hominids for a long interval. But the bestowing of names, like having a child, carries responsibilities. To be too liberal with subspecific names, even awarding them to single specimens (e.g., H. e. leakeyi), rather than to recognizable populations, is both to injure their use and to confuse the search for real lineages.

I’m quoting Howells not to endorse this view but because he expresses clearly one opinion about the goals of naming species and subspecies.

A short piece “On the evolution of the science blogosphere” by the Andy Extance of the ScienceSeeker team has some interesting notes on current statistics in blogs.

A quote from late in the article:

It’s notable that despite this exorcism of sci-comm ghosts, the overall number of blogs aggregated by ScienceSeeker has fallen by less than 5%. Our new blogs are frequently soon featured in our weekly picks. Often, new additions are young scientists motivated by the issues of our times. They emphasise the powerful tools science has for illuminating the truth, and argue for national policies to adopt them.

As they point out, the lives of science bloggers change, and things become more or less active as they fit into other parts of life.

For myself, I’ve been very busy with the Homo naledi work and that has reduced the effort I can put into cleaning up my notes about the other parts of science for public consumption. Also, I have a book out, and that took some time to write and edit!

Should scientists refuse to review papers that do not make data available?

What should happen when scientists publish work that cannot be replicated?

That’s an important question that people are asking more and more. So often, the basic results of research are hidden inside of figures that display results but don’t allow other scientists to inspect them or combine them together with other work in their own research. So the results sit there, published but essentially useless for building anything new from them.

Early in 2016, Pete Etchells wrote in The Guardian about a modest proposal for peer review: Scientists should refuse to review papers that do not make their data and methods openly available: “How peer reviewers might hold the key to making science more transparent”.

On Wednesday, a new paper published in Royal Society Open Science argued for a new, grassroots approach to this problem, by putting the power back into the hands of scientists at the coalface of research, by changing the way that we think about the peer review process (full disclosure: both myself and fellow Head Quarters blogger Chris Chambers are co-authors on the paper). The Peer Reviewers’ Openness (PRO) Initiative is, at its core, a simple pledge: scientists who sign up to the initiative agree that, from January 1 2017, will not offer to comprehensively review, or recommend the publication of, any scientific research papers for which the data, materials and analysis code are not publicly available, or for which there is no clear reason as to why these things are not available. To date, over 200 scientists have signed the pledge.

The paper in Royal Society Open Science which came out last year was written by Richard Morey and colleagues; Etchells was one of the coauthors. The subsequent year has allowed some time to see results of this initiative. The opinion paper has been cited 37 times according to Google Scholar, which is a strong result for a paper a year out from publication. People are paying attention to the argument. The paper has been strongly cited within the field of psychology, where the “replication crisis” has resulted in many calls for more responsible publication of data and methods.

But on the other hand, the more than 200 scientists who had signed the pledge by early 2016 have increased now up to only 400 or so scientists, according to the Openness Initiative website. The call for direct action hasn’t had quite the level of participation that proponents of the initiative might have hoped.

I have been a very strong proponent of data access, particularly within the field of human evolution. Here are a few of my articles for background:

So why haven’t I signed the pledge?

I find in many of my conversations with paleoanthropologists that most of them just don’t understand what it means to provide data. When I raise the topic of data access, some of them assume that I am expecting scientists to distribute casts for free, or open the doors of fossil vaults to anybody on demand.

In other words, they view data accessibility as some kind of invasion of scientific privacy, or worse, an abrogation of national heritage.

I also see that the conversation about data access in human evolution is having two kinds of effects.

One of these effects is very positive. New papers are being published that include the data necessary for replication. What’s more, referees are demanding more data be included. I’m seeing this in the work on Homo naledi, I think it’s fair to say that my collaborators have done more than any other team in history to provide the data behind the analyses. We’ve included extensive data tables, full details for the multivariate analyses, and high-resolution surface models of the specimens. Even with all this, we are still challenging ourselves within the team to find new ways to do better, to provide more data in a more useful way. Meanwhile, peer referees are encouraging us to continue to raise the bar higher, providing more and more data—including data we have collected on fossils from other field sites.

The second effect is less encouraging. Some researchers who were failing to report basic measurements as recently as seven or eight years ago seem to have simply stopped publishing any new research on fossil material. This is surely not a coincidence. I think we’re finding that some researchers are having trouble bringing their field methods and analytical standards up to a level where they feel comfortable reporting the underlying data.

Genetics went through such a stage, way back in the 1990s. Every lab had its own distinctive protocols for validating basic sequence data or genotypes. The methods were finicky, and in a high-stakes funding environment, labs competed with each other on whether you could “trust” their data. I remember a conversation with a geneticist about one of his scientific rivals, and he said, “Sure, he has good ideas, but you can’t trust his A’s, C’s, G’s, and T’s.”

Opening up the doors and the records in genetics during the late 1990s and 2000s was not invasive, it helped to clear the air. Many genetics labs were working with outmoded processes that needed to be revised or fixed, and by adopting more open protocols, they were able to take advantage of the methodological advances made in other (often much bigger) labs. Meanwhile, sharing data openly before publication allowed people to leverage the common investment being made in sequencing across institutions.

Anthropologists participated in the debates that came from non-transparent methods in genetics. In the early 1990s, it was common to hear anthropologists say, “Sure, the geneticists say this today, but tomorrow the results will be different.” Consider the example of the original 1987 paper by Cann, Stoneking, and Wilson on “mitochondrial Eve”. The results from that paper were subjected to published challenges for the next eight years, including papers reanalyzing the original data by Alan Templeton in 1993 and Christopher Wills in 1995. It took those scientists a long time, with cooperation from the original researchers, to figure out what had originally been done in the analysis, and even longer to go through the subsequent process of review and publication of their reanalyses.

Today, things have changed. New results in genetics are more transparent, they have been seen by a broader range of scientists before publication, and there is often a robust conversation among different labs as a study is being conducted. Published studies may still have weaknesses, but these are more openly discussed than in the past and replication studies are carried out quickly, sometimes while the original research paper is still a preprint.

Paleoanthropology today is like genetics in the late 1990s. I say that as a very positive thing. We are moving as a field toward higher standards in data reporting and transparency. Data access is a process of continual improvement in record keeping, archiving, and communication. This is really the basic lesson of science from high schools onward—if you want to see where you might go wrong, where errors might creep into your analyses, you need to show your work.

What we must do is continue to insist that scientists use the data that have been published. Providing data is one thing, but the true value of providing data is when other scientists reuse it to make their own work better. We need data that we can trust, not data that cannot be replicated by anyone else. If our observations cannot meet that standard, we need to work on our methodology until they can.


Morey RD, Chambers CD, Etchells PJ, Harris CR, Hoekstra R, Lakens D, Lewandowsky S, Morey CC, Newman DP, Schönbrodt FD, Vanpaemel W, Wagenmakers E-J, Zwaan RA. 2016. The Peer Reviewers' Openness Initiative: incentivizing open research practices through peer review. Royal Society Open Science doi:10.1098/rsos.150547

This is a neat feature from NPR’s Science Friday giving resources for teachers who want to include the SciFri episode on Homo naledi as part of their classroom exercises: “Where does Homo naledi fit into our family tree?”.

It includes alignments with science standards for U.S. K-12 teachers.

Have students compare and contrast different hominid skulls using these drawings and timeline. Where does Homo naledi fit in? How does it compare to other hominid skulls? Using the diagrams and figures in this article about the Homo naledi discovery, relate your skull observations to how Homo naledi alters our view of the human evolutionary tree.

We’ve sure come a long way in a few years!

Homo naledi was chipping its teeth amazingly often

I’d like to point everyone to this new article that may give some insight into the diet or behavior of Homo naledi: “Behavioral inferences from the high levels of dental chipping in Homo naledi. Ian Towle from Liverpool John Moores University examined the H. naledi dental sample last year and, with his colleagues Joel Irish and Isabelle De Groote, he has shown something very interesting about Homo naledi in comparison to other primates: They chipped their teeth a lot.

Figure 1 from the paper tells the story:

Dental chipping frequency in H. naledi compared to other hominoid samples
Figure 1 from Towle et al. 2017, showing the dental chipping rates per tooth class in H. naledi and other samples

Compared to chimpanzees and gorillas, extinct hominins like Au. africanus and Paranthropus robustus crunched on things that chipped their teeth a lot more — for mandibular molars, 25% in Au. africanus, versus only 10% for gorillas. For maxillary molars, gorillas crunched a bit more, and P. robustus surprisingly little. So there seems to be a good bit of noise in the data. But H. naledi puts the apes and other hominins to shame, with 50% chipping in maxillary molars and premolars, 60% in mandibular molars, and 40% in mandibular premolars.

Whatever it was eating or doing with its postcanine teeth, H. naledi was chipping them a lot. And those chips are not microscopic things, they are obvious on visual inspection of the teeth:

Figure 2 from Towle et al showing dental chips
From Figure 2 of Towle et al., 2017, showing dental chips on H. naledi specimens.

In other words, these are macroscopic aspects of tooth wear. We have seen on the teeth of H. naledi that there is a very high wear differential between teeth, and they seem to really have distinctive patterns of wear. Towle and colleagues point out that it is not just anything that yields this kind of chipping, it is seen predominantly in populations that incorporate high amounts of grit into their normal diet. For example, baboons:

The extant primate samples may offer more useful comparisons for H. naledi. For example, in a microwear study by Nystrom et al. (2004), baboons in dry environments were reported to consume large amounts of grit. In the present, combined sample of hamadryas and olive baboons, we found similarities to H. naledi, with frequent small chips and a higher rate of chipping among posterior teeth relative to anterior teeth.

And humans that eat things that sometimes contain shell fragments:

A Late Woodland sample from Cape Cod in the U.S.A. has a pattern like H. naledi in terms of frequency and position (McManamon, Bradley, & Magennis, 1986). The overall frequency is 43% and molars are reported as the tooth type most prone to chipping, with interproximal surfaces most affected. Unfortunately, frequencies for tooth types and positions in that study are not reported. McManamon et al. (1986) suggest that the cause of this patterning was the incorporation of sand, gravel, and/or shell fragment contaminants into the food.

Towle and colleagues note also that the Taforalt sample from the Epipaleolithic of Morocco also has high rates of dental chipping, again thought to relate to the incorporation of shells and fruit stones into the diet. These are high quality food sources that have small, hard objects within them.

The fact that there are human samples with frequencies of chipping comparable to that in H. naledi makes this a bit less puzzling. I would suggest we are looking at dietary adaptability within a population that has a relatively high energy density in its foods. That idea is consistent with the fact that H. naledi has relatively small tooth sizes, despite having substantial chipping rates.

What will be interesting is to see what the microwear texture is like in H. naledi. The sampling for microwear has been done, and our team is now working on assessing it. Thus far, microwear studies have given counterintuitive results as applied to robust australopithecines like P. robustus and others like Au. africanus. “Nutcracker man” evidently wasn’t cracking nuts. That result is holding in this study according to chipping—when you look at the most robust dentitions here, in P. robustus, they have among the lowest rates of dental chipping.

Anyway, it is exciting to see these clues emerge. The picture from dental chipping is remarkably consistent across the H. naledi sample, and it is telling us something very interesting about the diet or other uses of the teeth in this species.

Features of the Grecian ape raise questions about early hominins

Today, Jochen Fuss and colleagues have published a new description of the morphology of a mandible of Graecopithecus freybergi, from Pyrgos Vassilissis Amalia, Greece: “Potential hominin affinities of Graecopithecus from the Late Miocene of Europe”. They carried out microCT imaging of the mandible and another fourth premolar attributed to Graecopithecus from Bulgaria.

Fuss and colleagues show that the fourth premolar root configuration has some similarities with Ardipithecus, Sahelanthropus and Australopithecus. On this basis, they argue that Graecopithecus should be accepted as a member of the human clade, a hominin, closer to humans than chimpanzees and bonobos.

They go further. These Graecopithecus specimens are both older than 7 million years, making them earlier than any known hominin in Africa. So Fuss and colleagues claim that the origin of the hominin clade may itself have been in Europe.

More fossils are needed but at this point it seems likely that the Eastern Mediterranean needs to be considered as just as likely a place of hominine diversification and hominin origins as tropical Africa.

Is it going too far to say that this fossil jaw is the earliest hominin?

Here’s what I think: Paleoanthropology must move past the point where a mandibular fragment is accepted as sufficient evidence.

As blog readers are my witnesses, if I ever describe an unassociated mandibular fragment, I will never claim it is the earliest hominin, the earliest Homo, or the earliest modern human. Again and again, discoveries of relatively complete skeletal evidence have shown that different hominin (and ape) lineages had mosaic morphological patterns across the skeleton. Parallelism and convergence among lineages have been widespread in our evolutionary tree, and no single feature or fragment can accurately indicate relationships.

What’s worse, when we look at the earliest hominins, very few scientists have actually examined the evidence. Ann Gibbons wrote in 2006 that only one scientist at that time had seen all the key fossils, and for all anyone knows that may still be the case – since one of the most important specimens remains unpublished fifteen years after its discovery. Most scientists have been mere spectators, forced to look at cartoon images of skull and pelvis reconstructions that have never to my knowledge been examined by any independent scientist.

I don’t want to take away from the value of the study of Graecopithecus here. It’s pretty cool that Fuss and colleagues were able to find some hidden morphological clues in these very fragmentary specimens. That mandible has only one good tooth in it!

Graecopithecus mandible from Fuss et al. 2017
Figure 1a and 1b from Fuss et al. 2017, showing Graecopithecus specimens. Original caption: a, Type mandible of G. freybergi from Pyrgos, Greece. b, RIM 438/387 –Left P4 of cf. Graecopithecus sp. from Azmaka, Bulgaria. From left to right: distal, mesial, lingual, buccal, occlusal and apical.

With very little to go on, they have done an admirable job of focusing on some interesting dental features that have been seen as important in the early evolution of hominins. I think the study is valuable and I do not question any of the morphological findings.

But consider the example of Ardipithecus. It has a partial skeleton with impressive cranial, dental, and postcranial morphology, and reasonable scientists still cannot decide if it is a hominin. If anyone actually thought we could trust the premolar roots, we wouldn’t be arguing over Ardi.

I think we should take seriously that Graecopithecus premolar root morphology may be yet another demonstration that supposed “hominin” characters actually evolved in other branches of apes during the Miocene. This feature is far from alone. Many other features that supposedly link Ardipithecus or Sahelanthropus with hominins are also found in other Miocene fossils. My colleagues and I documented some of these Miocene ape-like features in Sahelanthropus in 2006.

We need to look with a more critical eye at the fossil evidence for the earliest hominins. They really share very few features with later hominins like Australopithecus. I think we should consider that they might instead be part of a diversity of apes that are continuous across parts of Africa and Europe. Our real ancestry during this earliest phase of our evolution may still be undiscovered.


Fuss J, Spassov N, Begun DR, Böhme M (2017) Potential hominin affinities of Graecopithecus from the Late Miocene of Europe. PLoS ONE 12(5): e0177127. doi:10.1371/journal.pone.0177127

Wolpoff, M. H., Hawks, J., Senut, B., Pickford, M., & Ahern, J. (2006). An ape or the ape: is the Toumaï cranium TM 266 a hominid. PaleoAnthropology, 2006, 36-50.

Doing some reading on supraorbital torus anatomy today, ran across this snarky passage from Mary Doria Russell’s (1985) paper, “The Supraorbital Torus: A Most Remarkable Peculiarity”.

Browridges have often been interpreted as selectively important eye protection, serving as anatomical sun visors (Boule and Vallois 1957, von Haartman 1974, Kurtén 1979) or bony unbrellas (Davies 1972). It has also been suggested that the Australian Aborigines' well-developed browridges protected their eyes from the venom of Australian spitting snakes (Davies 1972). While the selective advantage of some protection against being blinded by venom is obvious, the fact that the snakes in question are ground-dwelling decreases the usefulness of a barrier above the eyes.

William. W. Howells (1980), writing on the way that new discoveries have affected the interpretation of Homo erectus:

The pattern of discovery to a degree continues that of the past. Java has gone on producing material at a familiar pace, while in Europe fossils have been sparse and fragmentary, with two spectacular exceptions (Petralona, Arago), India continues a blank; China has just begun to produce significant finds again. Africa has taken more of its rightful place. However, if one were to take Weidenreich or Boule as a standard, description has been rather slow, and even preparation, especially in the case of delicate specimens, has delayed up full appreciation of some finds.


Howells, W. W. (1980). Homo erectus—who, when and where: a survey. American Journal of Physical Anthropology, 23(S1), 1-23.

Funding must make room for exploration

Scientists often say that you already need to have a result in hand to have a chance at being funded for research. Applications where the results are truly unknown are almost never funded.

Instead, applications succeed when they include slick “pilot data” showing the likely outcome, frame the research in terms of well-known earlier results, and seem certain to lead to a positive result. Failure to reject a null hypothesis is not an option. Replication of other research is almost never funded.

This system is wonderful if the goal is to add one brick at a time to the foundation of what we already think we know. But in many areas of science, what we think we know is wrong. And as many others have noted, the bias against negative results and replication has led some fields to a crisis of false published results.

If we want to get at the nature of things, we need scientists who explore new ideas, even if they don’t come pre-packaged with pilot data.

Times Higher Education has a conversation with Nobel Prize-winning scientist Saul Perlmutter, who “Nobel laureate says scientific breakthrough ‘would not be possible’ today”.

“People forget that what you’re looking for is gigantic surprises and transformations that allow us to do things that we never thought were possible,” he said.
“The only thing we know of that seems to work is to create an environment where people are thoughtful, they’re hopeful and they’re trying many ideas.”
He said that this approach can even be seen among venture capitalists, who only expect a “small fraction” of their investments to be successful.
“You’re looking for those rare, special investments and you have to spread the resources in order to get them,” he said.
Saul Perlmutter. Photo: Wikimedia Commons

Over Twitter in the last few weeks, I’ve seen disappointment from several professional colleagues after the rejections of their latest grant applications. The most heartbreaking had reviewers who wrote that their labs “did not have the necessary expertise to carry out the research.” Of course, I know the people, and I know that in each of these cases, these researchers have already published previous work close to their new proposals. They not only have the expertise, I would consider them among the world’s experts.

Think about this kind of comment. I’ve gotten the same thing on my own applications for funding in the past. This is why researchers are driven to include pilot data in their applications, to show that they have already produced results. It’s why researchers apply for funding to do nearly-completed research, so that they can redirect a fraction of the funds to the next project.

Maybe in an environment where the probability of funding were higher, these kinds of comments would be ignored. But take that idea seriously for a moment. Doesn’t it mean that with less funding, we are being even more conservative in what we fund? Doesn’t that make us even less likely to learn something new?

I don’t want to look at the same questions, the same experimental models, again and again. I want to work on new ideas, with a great team of people who have a wide range of backgrounds. It’s what Perlmutter is saying, “create an environment where people are thoughtful, they’re hopeful, and they’re trying many ideas.”

Exploration may not always lead to discovery, but it’s the only thing that does.

Essential reading on the effects of sexual harassment and assault in field paleoanthropology: “In case this helps you: This happened to me while I was trying to become a paleoanthropologist.”

UPDATE (2017-05-28): This post was removed from the linked website by its author, so the link is dead.

Notable: O’Malley, R. C., Stanton, M. A., Gilby, I. C., Lonsdorf, E. V., Pusey, A., Markham, A. C., & Murray, C. M. (2016). Reproductive state and rank influence patterns of meat consumption in wild female chimpanzees (Pan troglodytes schweinfurthii). Journal of human evolution, 90, 16-28. doi:10.1016/j.jhevol.2015.09.009

Synopsis: Looking at long-term data on diet and reproductive status in wild chimpanzees at Gombe, Tanzania, O’Malley and colleagues found that pregnant females ate more meat than lactating or non-pregnant, non-lactating females. This effect was concentrated in low-ranking females, who have less access to meat than high-ranking females, so social rank and pregnancy both interact as factors influencing female meat consumption.

Interesting because: Pregnancy and lactation have high energy costs and protein costs for females. Meat is a relatively high-energy and high-protein food source. A supply of meat in the diet of pregnant or lactating females would seem to be useful or adaptive, even though meat makes up a fairly small fraction of the chimpanzee diet and can easily be dominated by high-ranking females and males. These data show that female chimpanzees do compete effectively for meat despite low social rank, when they are pregnant.

Useful insight: Females did not significantly change insect consumption, even though it is another significant source of protein and energy, more reliable than meat. They seem to be eating insects at near a maximum, limited by the high time involved in foraging insects and insect defenses. Meat has a higher degree of variability.

Should we move to a system where every scientist gives grant money away?

Worth a read: “With this new system, scientists never have to write a grant application again”.

In Bollen’s system, scientists no longer have to apply; instead, they all receive an equal share of the funding budget annually—some €30,000 in the Netherlands, and $100,000 in the United States—but they have to donate a fixed percentage to other scientists whose work they respect and find important. “Our system is not based on committees’ judgments, but on the wisdom of the crowd,” Scheffer told the meeting.
Bollen and his colleagues have tested their idea in computer simulations. If scientists allocated 50% of their money to colleagues they cite in their papers, research funds would roughly be distributed the way funding agencies currently do, they showed in a paper last year—but at much lower overhead costs.

The incredible costs in time and money just to apply for grants and allocate grant funding are approaching insanity levels. With success rates spiraling down below 15%, researchers are spending more and more of their time writing grant applications and less and less doing research, teaching students, or sharing with the public. The average successful grant applicant sinks months of work into grant applications each year that could have been spent doing science, in a fairer system.

I’ve thought a lot about the kind of “self-organized fund allocation” described in the linked article. Allocating money on the condition that some must be given to other researchers would create several downstream benefits. Scientists who maximize the ability of other scientists to produce their own new and useful results would have a big advantage in this system. Jerks would be punished appropriately. Once they have a role in the system, scientists could make rational decisions about how to collaborate with other researchers to build a larger program, instead of trying to centralize into their own little kingdoms.

The article mentions that Bollen’s scheme includes a condition that you can’t just give money to coauthors. The supposed problem is that people will choose to allocate funding to their friends.

Personally, I think that kind of condition decreases the appeal. Maybe there should be a barrier to allocating within an individual’s institution, to prevent administrators from pressuring researchers to keep the money at home. But I think the ability to allocate money to friends will encourage the development of stable research collaborations across institutions (and internationally). Besides, giving other scientists the means to reward friendly behavior will create a lot more friendly environments for science in the future. I think people allocating money within “friend” networks is a feature of a system, not a bug.

But one thing that I think this model wouldn’t address is the risk-averseness of today’s scientists. Today’s funding model disincentivizes taking true intellectual risks. The funded applications are those for which outcomes can be predicted. As a result, some of the most talented researchers are aiming low, instead of trying to swing for the fences. But giving people money to allocate to others is not likely to address what I see as a big problem. To be sure, having a more stable funding, at a low level, will enable some people to try radical new ideas. But any system where a winner-take-all effects kick in is one where it’s hard to fund contrarian or risky research.

Of course, as applied to human evolution research, or even biological anthropology more broadly, this kind of system wouldn’t have quite the impact as biomedical science. If we divided all the NSF funding for Biological Anthropology among the bona fide researchers in this field working in the U.S., it would average less than $3000 per scientist. Still, I’m pretty sure that amount would generate a lot more research distributed across hundreds of working scientists instead of clumped into the overhead budgets of a few big winners.