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I regularly read Nature, Science, PNAS, American Antiquity, Antiquity, Applied Energy, Archäologische Informationen, Archäologisches Korrespondenzblatt, Biblical Archaeology Review, Cambridge Archaeological Journal, Current Anthropology, Evolutionary Anthropology, Journal of Ancient Egyptian Interconnections, Journal of Anthropological Archaeology, Journal of Anthropological Research, Journal of Archaeological Science, Journal of Archaeological Science: Reports, Journal of Human Evolution, Oxford Journal of Archaeology, (several of them on paper – my one big indulgence and luxury) and whatever tidbits I’m led to by finding them being mentioned somewhere. For those marked in bold my personal subscription grants me access to content I can’t get through the University of Cologne.
Whoever happens to share my particular interests can find a list here of all the highlights of the current week, together with abstracts and the personal comments I feel compelled to make.
This is again a model, but this time a correctly used one. It is not touted instead of or against measured data and not used to extrapolate outside its area of validity but given to explain the mechanism of how the observed and measured data came about. Modelling at its best.
This week most of the articles are about ancient migrations and mixtures, mostly based on the new results by Posth et al. The best summary is that by Curry.
Johnson et al. offer a new way to quantify if and by how much a new study should induce the reader to adapt his prior assumptions.
When measurements and proxy evaluations tell one story and current modelling efforts another it used to be obvious which of the two was in need of revision. (Modelling that is, not sound theory as in the case of Feynman and Telegdi.) No more. When models and theories become ideologically charged it is the facts that have to yield. Kaufman & Broadman remain sitting on the fence and undecided, which one it is to be.
While Wen et al. do add dating precision to the contemporaneity of sea surface and terrestrial cooling, their claimed causality from carbon dioxide depletion is neither measured nor inferred from proxies but only a modeling outcome. In the carbon dioxide data shown in their figure 1f no driving signal is discernible.
On the positive side Stock et al. show us data thus allowing us to evaluate their conclusions, something most others especially from the social sciences usually avoid. So for example their figure 6 shows most clearly, how one single sample can skew the picture for ten thousand square miles and a thousand years. Even assuming their lines in figures 1–5 to be valid, what does a tiny shift in the average really tell us for an extremely widely distributed population?
If the temperature trend since about 1800 as shown in Hörhold et al. is mainly carbon dioxide driven, then what we see is a strong effect at very low concentrations followed by a massive saturation afterward. How to extrapolate a series like that remains an open question. Anything linear stated in degrees per amount has to be wrong.
In Li et al.’s figure 5 ab the isotopic values for wheat and barley are nearly identical. What differs are the arbitrary cut-off points taken from Wallace et al. 2013. As pointed out last week and earlier for the primary source that boundary is pure phantasy.
Bishop et al. cite and use the result by Wallace 2013. As I’ve already shown in my lists of 2017-01-15 and 2019-01-20 its predictive value is meaningless. Thankfully the authors recognize as much themselves and clearly say so.
