1. Booms and Busts in Europe’s Earliest Farming Societies: Review
Originally posted online on 21 February 2012 at rmchapple.blogspot.com
(http://rmchapple.blogspot.co.uk/2012/02/booms-and-busts-in-europes-earliest.html)
The PCC Lunchtime Seminar Series is run by the School of Geography, Archaeology and
Palaeoecology at QUB in Belfast. I believe that they have been going for some time now
and, although I’ve regularly been told about them and how I really should get along
there, I’ve somehow not managed to make it. However, I promised myself that the next
opportunity I got I would definitely attend – come hell or high water. I spoke to a friend
of mine who told me that the next one coming up (Tuesday 21st February 2012) was on
Early Neolithic Farming. I liked the sound of that and I promised faithfully that I would
be there. It only occurred to me the day before the lecture to enquire who the speaker
was. When I was told that the speaker would be Prof. Stephen Shennan my heart just
fell. I have nothing against the man, I truly don’t. Prof. Shennan is Director of the UCL
Institute of Archaeology. He is also Professor of Theoretical Archaeology, and Fellow of
the British Academy. As I found out when I spoke to him after the lecture, he is a truly
affable person with a ready smile and keen sense of humour. Nonetheless, for me his
name is eternally associated with that part of my life, during the mid to late 90s, when I
was embroiled in writing my MA thesis [also available: here]. I was working on a
statistical and morphological approach to the ringforts of the Loop Head Peninsula in
Co. Clare and Shennan’s book, Quantifying Archaeology, was my constant companion.
There were certain sections of my thesis that relied so much on his work that I was
afraid of being dismissed for plagiarism. I even had dreams about repeatedly typing
‘Shennan (1988) says/states/argues’ etc. By the time I completed my thesis, my copy
of Quantifying Archaeology was in such a poor state it had to be held together with
rubber bands. Yes, I was slightly terrified at being in the room with this man.

2. As it turned out there was no need to be. He began by outlining some concepts of
Evolutionary Demography Theory. The concept is that for people in past societies,
producing children were not so much a means to an end, but a good in their own right.
There are also a number of trade-offs implicit in having children, not least of which is
the number of children it is possible to bear, but how many of one’s offspring can
feasibly survive to sexual maturity and become parents themselves. Changing
environmental and technological conditions can thus alter the balance of these trade-
offs, resulting in increased or decreased fertility. To illustrate this, Shennan showed a
graph comparing the ages of women giving birth for the first time in a modern Mayan
community and how the demographics changed after the introduction of electric pumps
to supply water. In the pre-electric pump society around 50% of the women had given
birth to their first child by the age of 21. However, the addition of the electric pumps
allowed women to be freed from the drudgery of water carrying and resulted in an
increased carrying-capacity for the society. In the latter situation almost 75% of women
had had their first child by the age of 21. Shennan was quick to point out that the
decisions to have children, what numbers, and at what time, are carried out a household
level, but have large-scale population-level results. Thus, there are demographic
consequences in acquitting a new adaptations and technologies, such as cereal- and
pulse-based agriculture. Where we find evidence for population stability, it may be
taken as evidence that a local carrying-capacity ceiling had been reached. Shennan sees
the spread of farming in the Neolithic as a classic example of a dispersal opportunity
acquired through greater technological achievement. There is also the fact that this form
of agriculture is extremely portable – seed and livestock may be moved with relative
ease. Shennan argues that this all leads to a significant increase in environmental
carrying capacity that results in both increased fertility and eventual population growth.
He argues that, contrary to some theories of the spread of agriculture, this is not a
population ‘push’ process but a biological ‘pull’ process. This means that it is not a
situation where an increased population is forced to develop more effective means of
feeding itself (thus adopting agriculture). Instead, this model is one where the
population acquires agricultural skills and then discovers that it can support more and
larger families, leading to a population growth.
Shennan noted that while there is much in the published literature about the earliest
beginnings of agriculture, many researchers appear to assume that once it is in place,

3. there is little to be interested in. However, in examining the evidence from eastern
France, the data shows a sequence of population expansions, interspersed with well
defined gaps where the population contracts (Peterquin et al. 1996).[1] For example,
Zimmerman’s (2009) analysis of Neolithic Bandkeramik sites in the lower Rhine basin.
Here there is evidence for population growth at the beginning of the Neolithic, around
5300 cal BC. There then appears to be continued growth for over a century, followed by
severe population contractions by around 4900 cal BC. To test these hypotheses,
Shennan and his team (Sean Downey, Adrian Thompson, Kevan Edinborough & Mark
Thomas) used summed radiocarbon date distributions as a proxy for the relative
amount of population activity. This approach was then used to compare data from the
pollen record with radiocarbon dates from across the UK. The methodology involved
converting the pollen spectrum into ‘Land Clearance Category Reconstructions’ plotted
against the summed and normalised, geo-referenced, radiocarbon dates. This was all
then divided up into bins of 250 years. The available data runs from 9000 cal BP to
around 3600 cal BP. The UK evidence shows an inferred population growth (what
Shennan terms an ‘upward blip’) around 7600 cal BP. This is paralleled with a
‘downward blip’ in the amount of deciduous woodland. Essentially, the arrival of
farming is shown to result in an increase in the population, coupled with a decrease in
woodland. At around 5300/5200 cal BP there is an observable drop in population that
continues to after c. 4500 cal BP. After this point there is an increase in deciduous
woodland and (unexpectedly) an increase in semi-open pasture. Again, around 4400 cal
BP there is a decrease in woodland and a corresponding increase in semi-open pasture
that is taken to suggest an increase in population. One of the interesting conclusions to
be drawn from this analysis is that it suggests that what we are witnessing is
anthropogenic change to the environment – as opposed to climate change being the
primary determining factor. To test the robustness of these dates and this methodology
the dates were segregated by type. In this way dates from cereal grains could be
separated from dates associated with upstanding monuments. In theory, if there is a
genuine underlying trend in population growth, it should be mirrored by both sets of
data independently. Certainly, this has been demonstrated to be the case during the
earlier Neolithic, but there is a marked divergence in the patterns during the Late
Neolithic, from around 4000 cal BP.
This model was then recreated for ten different regions in Western Europe. Within each
of these regional studies, Shennan and his team took 1000 dates as a ‘bootstrap sample’
to model variation. For example, in the Scottish study there were 305 dated site phases.
Here there is an observable population boom around 5500 cal BP. In Ireland, with 1031
dated site phases, there is a similar population boom at around 5500 cal BP, followed by
a trough around 5000 cal BP. A further rise in population may be noted around the
period 5000-4000 cal BP. In Germany, where farming was introduced approximately
1500 years before it reached Ireland, the Bavaria-Baden-Wurttemberg study area shows
peaks at 7000 cal BP, 5500 cal BP and 4600 cal BP. There are also intervening troughs
in population centred on 6200 cal BP and from 5200 cal BP to 5000 cal BP. Similar
regional studies were carried out for the Low Countries (347 dated site phases), the
Paris Basin (188 dated site phases), and the Rhone-Languedoc (340 dated site phases)
areas (among others). In all of theses the general pattern of population booms and busts
is repeated over and over.

4. Shennan then posed the question: are these patterns real? The fact that the radiocarbon
data largely mirrors the pollen data suggests that, yes, they are real. However, there is
still the possibility that these patterns are spurious and are merely the result of
anomalies within the calibration curve or have appeared as the results of sampling
errors etc. To counter such arguments, the team devised a set of statistical tests. As
Shennan said, these are quite technical and difficult to take in. If I have understood him
correctly, the test centred on simulating 50,000 randomly generated radiocarbon dates,
spread across the time-period under discussion and broken up into 10 year bins. These
were then assigned error ranges that mimicked the real distribution of the calibration
curve and the standard deviations of genuine radiocarbon dates. Essentially, they
recreated 50,000 simulated radiocarbon dates with the same level of
precision/imprecision (or ‘fuzziness’) as one would expect from real dates. Added to this
they factored in the known levels of population growth and taphonomic decay (that
there is less probability of materials surviving from earlier vs. later contexts). Together,
this model predicts an exponential growth of data (and population) over time. When the
simulated data is compared to the real evidence some clear patterns of higher and lower
than predicted activity are revealed. This means that the results may be interpreted as
being a true reflection of genuine population trends within the data and not merely
artefacts of the data itself. In the Wessex-Sussex and Irish regional studies the same
patterns as before are noted, with rising population booms being followed by busts. The
results are less marked for other regions, such as central Germany and southern France,
though this appears to be due to their smaller sample sizes available for study. Shennan
and his colleagues have been able to conclude that the pattern of boom and bust are
clear and genuine occurrences.
A further question was asked – could there be any correlations between these results
and climate patterns? The idea was that the results may still have been spurious and
that the data was not indicating parallels between demography and climate, but merely
reflecting the level of 14C in the atmosphere. The team used two climate proxies:
the NGRIP and the Crag Cave, Co. Kerry, δ18O data. Again, a series of statistical tests
were devised to eliminate all possible bias within the data. With the exception of the
regional study of the Low Countries, no statistically significant correlation was found
between the two sources. This again demonstrates the robustness of the data and the
population expansion and contraction patterns already observed.
Finally, Shennan examined a number of other studies to compare their results with his
own. Similarities were noted with dates from flint mining in Britain (Kerig et al. in
press) which shows a marked rise in dates around 4000 cal BC with a major fall-off and
minor peaks after that time. Parallels were also found in the dates associated with
causewayed enclosures (this comparison was carried out before the publication
of Gathering Time). In his concluding remarks, Shennan admitted that, in many
respects, it is predictable that people would take reproductive advantage of the
introduction of new technology that improved their lifestyles. However, there are, as yet,
no firm reasons as to what caused these cycles of boom and bust. He argues that future
research must take into account the demographic history of populations both as a cause
and as an effect of the process. Even with all these ideas in mind, it is still likely that the

5. socio-economic processes that drove these cycles were different for the growth and
decline phases. Essentially, the appearance of agriculture may be associated with the
initial population booms observed in the various study areas, but the probable reasons
for the declines are much more obscure.
Note:
I hope that I have done justice to Prof. Shennan’s lecture and managed to convey at least
the gist of his ideas and results. Nonetheless, I do sincerely apologise if, in the rush to
write notes and keep up with the pace of delivery, I have misrepresented or misquoted
the speaker. If so, please feel free to contact me, and I will endeavour to set the record
straight.
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[1] I have not been able to give the full references to any of the literature referenced in
the lecture – sorry.