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Neolithic stone axeheads from Britain provide an unusually rich, well-provenanced set of evidence with which to consider patterns of prehistoric production and exchange. It is no surprise then that these objects have often been subject to spatial analysis in terms of the relationship between particular stone source areas and the distribution of axeheads made from those stones. At stake in such analysis are important interpretative issues to do with how we view the role of material value, supply, exchange, and demand in prehistoric societies. This paper returns to some of these well-established debates in the light of accumulating British Neolithic evidence and via the greater analytical power and flexibility afforded by recent computational methods. Our analyses make a case that spatial distributions of prehistoric axeheads cannot be explained merely as the result of uneven resource availability in the landscape, but instead reflect the active favouring of particular sources over known alternatives. Above and beyond these patterns, we also demonstrate that more populated parts of Early Neolithic Britain were an increased pull factor affecting the longer-range distribution of these objects.
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(2020) 27:836859
Journal of Archaeological Method and Theory
British Neolithic Axehead Distributions
and Their Implications
Peter Schauer
&Andrew Bevan
&Stephen Shennan
&Kevan Edinborough
Tim Kerig
&Mike Parker Pearson
#The Author(s) 2019, corrected publication 2020
Neolithic stone axeheads from Britain provide an unusually rich, well-provenanced set
of evidence with which to consider patterns of prehistoric production and exchange. It
is no surprise then that these objects have often been subject to spatial analysis in terms
of the relationship between particular stone source areas and the distribution of
axeheads made from those stones. At stake in such analysis are important interpretative
issues to do with how we view the role of material value, supply, exchange, and
demand in prehistoric societies. This paper returns to some of these well-established
debates in the light of accumulating British Neolithic evidence and via the greater
analytical power and flexibility afforded by recent computational methods. Our anal-
yses make a case that spatial distributions of prehistoric axeheads cannot be explained
merely as the result of uneven resource availability in the landscape, but instead reflect
the active favouring of particular sources over known alternatives. Above and beyond
these patterns, we also demonstrate that more populated parts of Early Neolithic Britain
were an increased pull factor affecting the longer-range distribution of these objects.
Keywords Neolithic .Britain .Radiocarbon .Stone axeheads .Spatial analysis .Cluster
Prehistoric edge-ground stone tools are a key form of human material culture, found
across a vast range of cultural settings and interpreted with more or less regard to their
potential roles as socially charged emblems, proto-currencies, and/or functional tools.
Spatial distributions of stone axeheads have been a particular focus of study, not least as
Electronic supplementary material The online version of this article (
09438-6) contains supplementary material, which is available to authorized users.
*Stephen Shennan
Extended author information available on the last page of the article
Published online: 20 December 2019
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British Neolithic Axehead Distributions and Their Implications
part of intensive efforts to understand prehistoric exchange mechanisms (e.g. Hodder
1974;Renfrew1975,1977; and see discussion below). A striking, early, and large-scale
example of an ultra-long distance spread of stone axeheads from a single source region
is provided by European Neolithic axeheads of Alpine rocks, including jadeitite,
omphacite, and eclogite (Pétrequin and Pétrequin 2012). These visually distinctive,
elaborately produced, onerously accessed, carefully curated axeheads were made from
south-western Alpine sources, but ended up deposited in contexts across large swathes
of western Europe, sometimes over a thousand kilometres away. Indeed, Alpine
axeheads may well have played a culturally foundational role in promoting an ideology
of virtuoso stone extraction and axehead production that led to many more localised but
analogous industries across western Europe that reached their height during the late 5th
and early 4th millennia BC (Schauer et al. 2019).
Within this episode of peak western European production, the stone axeheads of
Early Neolithic Britain constitute perhaps the largest and most systematic published
evidence to hand. Over the last 90 years, British stone axehead studies have been
pushed forward particularly effectively by the Implement Petrology Group (IPG) and
its predecessors, with important ongoing efforts to link specific axeheads to specific
geological sources (especially Clough and Cummins 1979,1988). Careful characteri-
sation by petrological thin-section analysis and optical microscopy has allowed large
numbers of axeheads to be assigned to broadly agreed petrological groups (e.g. group I
greenstones from Cornwall or group VI epidotised tuffs from Cumbria; see Clough and
Cummins 1988: Table 3for a full list). Such work is of course never likely to be
complete(Grimes 1979, p. 3) given the quantity of finds and the diversity of local
geology, and Pitts (1996) has suggested that more general grouping of axeheads by
broad material type might be preferable. Even so, the idea that the IPG groups do
represent real sets of axeheads with a common origin has been strengthened through
isotopic and geochemical studies (e.g. Markham and Floyd 1998; Davis et al. 2009).
The IPGs list remains too useful for addressing large-scale distribution patterns to be
ignored and indeed has already benefited from a range of spatial analytical work (e.g.
Darvill 1989).
A key question for many of the researchers that have so far considered British and
other European stone axehead finds has been to understand what production, consump-
tion, and exchange mechanisms might have led to the spatial distribution of axeheads
that we see in the archaeological record today. Some axeheads clearly were moved long
distances, including crossings by sea in the case of mainland British findspots of
axeheads from Ireland and the Alps (Cooney et al. 2013; Pétrequin and Pétrequin
2012), while it remains clear that many axeheads were local regional products (Darvill
1989;Pitts1996). Cummins (1979) recognised that axeheads of particular materials are
typically found close to their source and decline in frequency with increasing distance,
although occasionally secondary concentrations might appear further away. He sug-
gested a range of mechanisms for their dispersal, from gift exchange to itinerant
Neolithic traders (pedlarsor Neolithic salesmen, 1979, p. 7) and the role of
secondary distribution centres. Darvill (1989) also suggested that a range of exchange
mechanisms might have been responsible for the circulation of axeheads, but in
addition highlighted the possible role of direct visits by axe users to the source regions,
and seasonal migration by axe-using communities. Pitts (1996), however, pointed out
that perhaps the different mechanical properties of different stones (e.g. flint might be
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Schauer et al.
more prone to breakage than igneous stones) might affect how far they travelled from
their source before disposal or final deposition. Bradley and Edmonds (1993)exten-
sively critiqued Cumminstrader and secondary-centre models, while a survey of the
circulation of axeheads in the western Mediterranean (Risch 2011) likewise found no
evidence of specialisation or centralisation in the axehead trade. Earthwork surveys
at flint mines (Barber et al. 1999) have furthermore suggested that, despite the large
number of resulting axehead products, the scale of extraction at such mines was not
large in any modern industrial sense, and that prominent or exotic locations might
sometimes have been favoured over more accessible or even better quality local
sources (Topping 2019; see also Taylor 2017 for the role of topography at the
Langdale source).
A further key question implicit or explicit in past work has been the following: to
what extent was there competition amongst alternative axehead-producing communi-
ties? Indeed, given that ethnographies of twentieth century CE New Guinea (Burton
1989; Pétrequin and Pétrequin 1993) document dedicated axehead-making communi-
ties or tribes whose scale of production sometimes responded to changes in wider
regional demand, to what extent was the presence of a large local pool of potential axe
users in the Neolithic a good explanation for the observable density or diversity of
Neolithic axehead finds? This paper returns to such debates in the light both of
accumulating evidence and the much greater analytical flexibility now offered by
computational methods. We first look to control more formally for research biases in
such find distributions, before addressing what the geographical pattern of axeheads
from known sources can reveal both individually and collectively about exchange
mechanisms, and about the relationship between axeheads and British Early Neolithic
regional population densities. Other things being equal, we would expect larger
numbers of axes to be used and discarded in areas with higher populations. Another
possibility discussed in the literature (e.g. Smith 1971)isthataxeheadsfromlong-
distance sources are more frequent around causewayed enclosures because these were
places where people gathered from a wide area; hence, we go on to examine the
relationship between the numbers of exotic axeheads and the distribution of enclosures.
Finally, in the light of arguments for two if not three distinct streams of Neolithisation
in Britain, an eastern one and one or more in the west (Sheridan 2010), and for the
existence of distinct spatial style zones in the pottery (Pioffet 2014), we can ask
whether these divisions are in any way reflected in the axehead distributions.
Our study uses several sources of information on the spatial distribution of axeheads,
primarily from the IPG (Clough and McK 1988) and Neolithic Axehead Archive (Pitts
1996), but also further relevant finds from England, Wales, and southern Scotland that
have been brought together or recorded in more standardised ways by the Irish Stone
Axe Project (ISAP, Cooney and Mandal 1998) and Projet JADE (Sheridan and Pailler
2012). When combined and de-duplicated, these sources provide a list of some 18,120
axeheads, each of which has a petrological description, a find location, and an object
type (axehead, axe hammer, etc.). The characteristics of individual axeheads, such as
dimensions, weight, and wear patterns, are not uniformly available and have not been
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British Neolithic Axehead Distributions and Their Implications
considered in this study. From this overall set, we have then only kept those that are
clear Neolithic axeheads, thereby by excluding other implement types such as axe-
hammers and objects without a clear type attribution. Our focus in what follows is also
primarily on the Early Neolithic (~ 41003400 BCE), and hence, later styles such as
shaft-hole axeheads (Roe 1968,1979) have also been removed. Similarly, in the case of
materials of known source, we only consider those sources exploited in the Early
Neolithic on the basis of their radiocarbon dates (see Edinborough et al. 2019)orthe
dates of their finds contexts (e.g. Whittle et al. 2011). Finally, we have restricted the
geographical scope of the present study to present-day England, Wales, and southern
Scotland, keeping only those other Scottish, Alpine, French, and Irish axehead types
that have findspots in this chosen study area.
As a result of these restrictions, the final list used in what follows comprises some
5809 axeheads, and Fig. 1presents both the basic distribution of these axeheads and a
kernel density surface which provide a useful spatial statistical summary that we return
to at several stages in what follows. Axeheads are not uniformly distributed, and,
although areas of moderate density occur around sources in Cumbria, Cornwall, and
North Wales, the concentrations of highest intensity are found in a band from the
Yorkshire coast in the northeast to the Welsh borders and in a band in the south across
Wiltshire and Sussex. There is also a dense concentration of axeheads in Norfolk,
which, as will be discussed in detail below, is largely made up of flint axeheads.
Whether or not to include flint and other ungrouped axeheads is an important
consideration. Many previous studies have been based on samples restricted to
axeheads in hard stones (e.g. igneous or metamorphic rocks) and well-defined prove-
nance groups (e.g. Cummins 1979). However, this is to ignore the many thousands of
axeheads which must have been in contemporary production and use alongside the
known hard-stone axehead groups, and whose presence could have influenced the
Fig. 1 The spatial distribution of all axeheads across England, Wales and southern Scotland, with a resulting
model of their spatial intensity (n= 5809, Gaussian kernel (see text) with a one-sigma bandwidth of 30 km),
plus examples of (from left) flint1, greenstone (group I)2, and jadeitite axes2(1CC BY Birmingham Museums
Trust, 2© The Trustees of the British Museum)
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Schauer et al.
eventual distribution of the hard-stone axeheads. A common argument against the
inclusion of flint axeheads is that there is no way to be sure of their date, but previous work
on the radiocarbon dating of both hard-stone quarries and flint mines has shown that, with
the exception of Grimes Graves, their exploitation was particularly a phenomenon of the
Early Neolithic (Edinborough et al. 2019). It is thus reasonable to infer that large numbers of
flint and stone axeheads were produced in this early period, and that they should therefore be
assessed jointly in any analysis. Of course, it is possible that some flint axeheads were not
produced from mined flint but rather from local surface resources, and hence, that the
radiocarbon dating of the mines is insufficient as a guide to chronology, but there is at least
some evidence that axeheads made of surface flint too are likely to be Early Neolithic in date
(Barry Bishop pers.comm., for East Anglia).
Table 1breaks down the sample used in this paper according to different IPG groups
(see Smith 1979) and their attributed sources. It also assigns axeheadsto coarser macro-
groups for those stones that come from the same broad region of Britain. While there
have been attempts to identify even more precise sources within existing source areas
using geochemical fingerprinting, and these have met with some success (Markham
and Floyd 1998;Markham2009; Davis et al. 2009), such techniques have not as yet
been applied consistently across the sample, and for the purposes of the present
analysis, a more approximate source location within ca. 50 km is more than sufficient.
In contrast to the hard-rock axeheads, deciding on one or more assumed points of origin
for flint axeheads is difficult, because flint was clearly sourced from numerous locations
across the south-east (Holgate 1995,Fig1) and only a few of these have been conclusively
identified or indeed dated. In this study, we do not consider the well-known site of Grimes
Graves specifically, as despite a large number of radiocarbon dates, activity at the site has so
far consistently been dated to ~ 26502400 BCE which would place it in the later Neolithic
(Smith 1979; Healy et al. 2018). It remains possible in our view that the large number of
dates from Grimes Graves does not capture the full use-profile through time of the site,
Table 1 The regional groups and their component frequencies (a * means that the location is only a more
general one)
Provenance group NSource Regional macro-group N
Group I 389 Mounts Bay area* A. Cornwall (I, II, IV, XVI, XVII) 546
Group II 11 St Ives area*
Group IV 56 Callington area*
Group XVI 74 Camborne area*
Group XVII 16 St Austell area*
Group VI 1485 Great Langdale and Scafell Pike area B. Cumbria (VI, XI) 1491
Group XI 6 Great Langdale area
Group VII 361 Graig Lwyd C. Wales North (VII, XXI) 383
Group XXI 22 Mynydd Rhiw
Group VIII 111 Southwest Wales* D. Wales South (VIII) 111
Flint/chert 1512 Multiple sources in Norfolk,
West Sussex, and Wiltshire
E. Flint/chert 1512
F. Other 1766
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British Neolithic Axehead Distributions and Their Implications
because only a small, spatially concentrated proportion of the mines at GrimesGraveshave
been excavated and dated, but regardless, it is fair to assume that East Anglian flint was
nevertheless an important Early Neolithic resourcewhether coming from a different part
of Grimes Graves, from another mining site, or from surface material (Frances Healy and
Barry Bishop pers. comms.). This is in keeping with the fact that for all the known hard-rock
sources, there is a decrease in relative quantity with distance from source, as there is for flint
when we assume a source in East Anglia as well as the southern English flint mines (see
below). For what follows, we therefore add a notional approximate point of origin at the
centre of the overall density of East Anglian flint axeheads (some 16.5 km southwest of
Grimes Graves) to the better-defined Early Neolithic sources of mined flint on the English
south coast.
We also consider it worthwhile to retain and treat as an Othercategory all axeheads that
are neither flint nor attributable to a clear petrological group (and that do not belong to clear
later Neolithic shapes or groups). This Othercategory (n= 1766) covers over 330 different
terms for the rock used, the great majority of which (> 310) occur ten times or less; 205 occur
only once. The majority of these axeheads (> 550) are undifferentiated greenstones and tuffs
petrologically similar to Cornish and Lake District groups, which could belong to one of the
groups found there but which are either variants or perhaps have not received the same level of
specialist microscopic analysis. Without examining and sampling each axehead individually,
there is no reliable method for grouping these axeheads, so we have adopted the conservative
position of leaving them in the Othercategory. This also includes some known groups
whose sources are outside the study area, such as porcellanite from Ireland (n= 91, the third
most frequent category), and a small number of axeheads with only-vaguely understood
origins (such as group XXVI, probably in Yorkshire), all groups whose numbers are too small
to justify separate analysis. Furthermore, many axeheads will never be assigned to a group, as
they are made of materials, such as sandstone, so widespread that their sources are extremely
hard to pin down. However, because all these axeheads when taken together are quantitatively
important, their influence on the distribution of grouped axeheads cannot be ignored, hence
our creation of the Othercategory.
A final point to note in this section is that it is almost impossible to assess properly
the factors that might have affected the distance that axeheads travelled from their
source without also considering the likely uneven spatial distribution of the contempo-
rary Early Neolithic human population who used them. As a proxy with which to infer
such patterns of Early Neolithic population, we therefore make use of a database of
spatially referenced radiocarbon dates (see Schauer et al. 2019 for details of sources)
that we restrict both to those falling within our geographic area and within the time
bracket of 4100 to 3400 BCE (n= 1550), when known axehead-producing flint mines
and quarries in Britain were in use on the basis of the available radiocarbon dates from
their sources (see Edinborough et al. 2019). Finally, although forming only a very small
minority, those dates relating to hard-rock quarrying and flint mining have been
removed from these lists to ensure that they offer independent lines of evidence.
Our analysis proceeds below in three stages. First, we explore the varying structures of
axehead distributions in the study area, then we consider the relationship between
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Schauer et al.
axeheads and distance from source, and finally we compare both the observed overall
density of axeheads and the regional diversity of their materials with a proxy for
varying densities in Neolithic human population across the study area. This involves
the following methods:
1D and 2D Kernel-Based Estimates of Raw and Proportional Intensity
Focusing on the largest four IPG groups and flint across England, Wales, and southern
Scotland,weprovideafirst,summary,mappingoftheraw2D spatial intensity of
axeheads in a particular group, in the same manner as conducted for the entire axehead
assemblage in Fig. 1. This summary is constructed by passing a Gaussian kernel (a
smoothing function in the form of a two-dimensional normal curve) with a one-sigma
bandwidth of 30 km across the study area and, for each raster cell, calculating a
distance-weighted density per unit area for the kernel centred on that cell (a standard
spatial statistical and GIS technique, but here using a continuous rather than distance-
clipped kernel: see Baddeley et al. 2015, pp. 168173). The kernel size was chosen as a
compromise between the different values suggested by automatic bandwidth selection
routines and, furthermore, was based on informal assessment of what bandwidth would
minimise erratic behaviour in sparser areas of the dataset. Figure 2shows an example
using group VI axeheads from the Langdale source in Cumbria.
A second complementary form of kernel-based mapping is a relative risksurface
(Kensall and Diggle 1995; Bevan 2012; Baddeley et al. 2015, pp. 581585; Smith et al.
2015), and in particular, we use here a version in which the kernel density of a focal
case (e.g. all stone axeheads from a particular source) is divided by the kernel density of
the total known evidence (e.g. all stone axeheads irrespective of source). Figure 2c
provides an example, again using group VI axeheads from the Langdale source, where
each raster cell expresses the local proportion of Langdale axeheads (i.e. a value
between 0 and 1) which can be compared to the global proportion of identified
Langdale axeheads in the dataset (1485/5809= 0.256). Although such maps of spatially
varying proportions occasionally exhibit misleading artefacts in areas of overall low
data, they offer useful, improved perspectives on spatial variability by controlling, in
some senses, for underling preservation or investigative bias. For example, while the
raw intensity of Langdale axeheads mapped in Fig. 2b retains many of the regional
research biases present in the basic map of all axeheads shown in Fig. 1, by dividing the
former by the latter, a more coherent 2D perspective of fall-off from the Langdale
source is achieved (Fig. 2c).
The above maps are 2D in nature, but traditionally, the fall-off of archaeological
artefacts from a known point source has also been modelled as a 1D curve. Figure 2a,
for example, expresses this fall-off for a series of 50-km zones with increasing distance
from the Langdale source.
Predicted 1D and 2D Relative Intensity
There are various decay models that might be fitted to such a 1D fall-off (e.g. linear or
exponential) and these were extensively discussed in the exchange mechanism litera-
ture of the 1970s. In particular, Renfrews(1975,1977) down-the-line model of
exponential fall-off, in which each link in an exchange chain keeps some material for
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British Neolithic Axehead Distributions and Their Implications
its own use and passes on the rest, has been widely influential. Here, however, we find
that a Gaussian-shaped decay not only proves to be the most consistently useful across
all groups (for example in group VI, AIC Gaussian = 72.289, exponential AIC =
84.028, and power law AIC = 110.601). This is also consistent with a minimal starting
assumption, given we will never know the histories of movement of individual axes,
that any axehead might move from its place of manufacture in steps of random length
and direction, either with its users or when exchanged between them, before reaching a
final resting place in the ground (i.e. a random walk). We have also preferred to use
Euclidean distances from a source rather than a more complicated terrain-weighted
distance model, as there was no initial evidence that a more complicated model would
offer greater explanatory power. The fitted Gaussian decay was then compared with the
Fig. 2 Example of 1D and 2D summaries and simulation of the axehead distribution from Langdale (group
VI). aThe vertical axis indicates the percentage of group VI axes in a series of 50 km distance bands away
from the source; the solid green line corresponds to the actual percentage; the dotted grey line corresponds to
the percentages predicted under a Gaussian random walk model (see text); the grey band around it is the 95%
critical envelope around the percentages created by the model, created by randomly permuting the assignment
of axeheads to sources and generating the corresponding fall-off 1000 times; the dashed line corresponds to the
fitted average fall-off across all stone groups. bThe raw spatial intensity of group VI axeheads. cThe relative
intensity as a proportion of all axeheads. dA simulated model of group VI proportions in 2D given the
Gaussian random walk model fitted in Fig. 2a in 1 dimension
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Schauer et al.
observed decay using a two-sided Kolmogorov-Smirnov test. Model fitting was con-
ducted for the four largest IPG groups (I, VI, VII, VIII, as per Table 1) plus flint, and a
95% critical envelope around the model fit was generated by permuting the member-
ship or not of a known axehead to the source of interest according to the fitted distance
fall-off and repeating this process 1000 times. Finally, we plotted the resulting fit back
onto the map (Fig. 2d) as a point of comparison with the observed 2D proportions (Fig.
Regional Classification Vi a K-Means Clustering
Given a set of several 2D proportion maps such as the one in Fig. 2c, we can stack up
the resulting raster images and group regions of the map together via unsupervised
classification, in the same manner as might be done for a multispectral image. That is to
say, we combine the relative intensity maps for all the stone sources so that each map
cell has its own specific combination of stone types. Raster cells/pixels that exhibit
similar proportion values for axeheads from the different stone sources are thereby
grouped together. It turns out that when pixels are grouped together solely on the basis
of having similar proportions of axeheads from different sources, the resulting clusters
or groups form spatially coherent regions. Amongst a range of alternative clustering
methods, here we use k-means (for the general method amongst a wider set of
numerical classification applied in archaeology, see Shennan 1997, pp. 190240; and
for its use for unsupervised classification of stacked raster surfaces, see Richards 2013,
pp. 319341) and explored a series of different numbers of cluster groups. We opted to
focus our interpretation on the patterning obtained with six groups (see results below).
To address as much regional patterning as possible, this k-means grouping was
conducted on the stone macro-groups (see Table 1) rather than individual IPG groups,
although it is worth noting that this choice does not significantly change the overall
interpretations that we draw below.
Random and Conditional Simulation of Axehead Material Types
One important question is how well different models of distance fall-off fit the observed
diversity of axehead materials found in each of the six classified regions of the UK. We
here express within-region diversity via a Simpson index (Simpson 1949;andforthe
wider family of diversity indices, see also Chao et al. 2014). We then fit a series of three
models to the diversity data, starting with an extremely simple model 1 in which each
observed axehead find is assigned a new stone macro-group completely at random.
Model 2 adds a distance-from source supplyeffect which is the same for all macro-
group sources (i.e. thedashedlineinFig.2a). At a given observed findspot of an
axehead, the simulation selects a stone macro-group for that axehead which is condi-
tioned on how far we are from each macro-group source. For example, if the axehead
findspot is equidistant from source A and source B, then simulation will assign an equal
chance to the axeheads stone type being from one of these sources, but a lesser chance
for source C if the latter is further away. Model 3 further adjusts for variable demand
by imposing a specific distance decay from the observed data for each stone source (i.e.
the dotted rather than the dashed line in Fig. 2a). Hence, at a given observed findspot of
an axehead, the simulation selects a stone macro-group for that axehead conditional on
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British Neolithic Axehead Distributions and Their Implications
the relative distance from each of the sources, but also adjusted for the particular
observed decay profile of that source. This means that if source A has an observed
distance decay which suggests greater popularity and greater geographical reach than
an alternative source B, then at an observed findspot equidistant between these two
sources, source A will be more often chosen as the simulated stone type. All three
models only consider diversity in the counts of groups I, VI, VII, VIII, and flint
(Otheris left out). The goal of these simulations is to produce hypothetical axehead
distributions and expected diversity measures by region.
Comparison with Inferred Population, Monumental Enclosures, and Material
We also compare, both informally and formally, the observed density and diversity of
axehead stone types (in each region of the UK defined by the k-means method above)
to (a) a radiocarbon-based proxy for the possible distribution of Early Neolithic
population, (b) Neolithic causewayed enclosures, and (c) Early Neolithic pottery styles.
The use of radiocarbon dates as a proxy for population has been extensively discussed
in the literature (e.g. Timpson et al. 2014; Timpson et al. 2015;Tallavaaraetal.2014;
Edinborough et al. 2017), responding to criticisms). In the case of Britain, it has been
shown that periods of high population as inferred from the radiocarbon dates coincide
with evidence from pollen diagrams indicating high levels of human impact on the
vegetation in the period 41003400 cal BC on which this paper is focussed
(Woodbridge et al. 2014), strongly suggesting that it is reasonable to use the dates in
this way. Moreover, we find very similar patterns of inferred population in different
parts of the British Isles (Bevan et al. 2017). In addition, comparison of the overall
density of UK radiocarbon dates in Fig. 1in that paper with this papers Fig. 9shows
that the low number of earlier Neolithic dates from East Anglia, for example, contrasts
with the high number of dates for all periods from that region, confirming that such
patterns are not an artefact of differences in fieldwork intensity.
In particular, we compare the densities of axeheads in each k-means region with,
separately, the density of radiocarbon dates and the density of enclosures, which
indicates whether there is significant covariance between these within each region
(for the technique, see Baddeley et al. 2015, pp. 3079). Furthermore, we formally
compare the residuals of the best-fitting simulation model of axehead materials (see the
previous section) against radiocarbon date densities to consider whether higher or lower
inferred population density per region might add further predictive power and thereby
suggest that demandin high population areas drove yet higher levels of axehead
material diversity.
Observed and Simulated 1D and 2D Distributions by Individual Group
Figures 3,4,5,and6use the same method introduced above for Fig. 2, but apply them
to three other IPG groups and to flint axeheads. For example in Fig. 3a,groupI
axeheads are found to represent 18.18% of all axeheads within 50 km of group Is
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Schauer et al.
source (30 out of 165 axeheads found in that 50-km bin). In Fig. 3b, the raw density of
finds primarily shows where most of the group I axeheads have been found, in south-
east and south-central England, while the proportion of group I axeheads versus all
axeheads is mapped in Fig. 3c. Figure 3d shows a prediction surface based on the fitted
1D Gaussian fall-off model and comparison with Fig. 3c emphasises how this
underpredicts the observed proportions of group I axeheads getting to the south-east
and over-predicts those getting to South Wales.
Similar insights are possible from the plots in Figs. 4,5,and6. Groups I, VI, VII,
and VIII differ significantly from the mean fall-off curve (two-sided Kolmogorov-
Smirnov test, p< 0.0001), with the Welsh sources not travelling as far afield as the
Cornish (I) and Langdale (VI) groups. In contrast, the fall-off of flint axeheads, from
several real or inferred sources in the south-east, is indistinguishable from the average
observed pattern (p=1).
Fig. 3 1D and 2D summaries and simulation of the axehead distribution from the Mounts Bay area in
Cornwall (group I): a1D fall-off curve, with a Gaussian fitted model and resulting simulation envelope (and
additionally a dotted line representing the average model across all stone groups); bthe raw spatial intensity of
Group I axeheads, cthe relative intensity as a proportion of all axeheads, and the da simulated model of group
I proportions in 2D given the fitted 1D fall-off
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British Neolithic Axehead Distributions and Their Implications
Regional Classif ication Vi a K-Means Clustering
As described above, to address regionalism in stone axehead finds more broadly, those
IPG petrological groups sourced to similar regions were lumped into five macro-groups
(and a sixth Othercategory, see Table 1) and proportional intensity maps (similar to
Figs. 2c and 3c,etc.) were calculated for each one. These were then stacked up and
classified using an unsupervised k-means classifier for a series of different choices of
the number of clusters (2, 3, 4, 6, and 8) as presented in Fig. 7. At each successive
number of clusters, regions with the highest proportion of a single group of axehead are
split from the remaining axeheads, starting with the Cumbria group, then flint/chert,
then Cornwall, and so on. Selecting six divisions produces a plot in which each cluster
contains one major source, with the exception of clusters 2 and 6, though sources are
not used as an input in this analysis. Cluster 6 effectively surrounds cluster 1, covering
the midlands and north of England, a small area of southern Scotland, and the Isle of
Man, all areas dominated by group VI axeheads but with a greater presence of other
groups than cluster 1. It includes a concentration of axeheads on the Yorkshire coast,
which forms the northeast end of the high-intensity band of axehead frequency seen in
Fig. 4 Group VII. Details as Fig. 3
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Schauer et al.
Fig. 1. Several axehead groups originate in cluster 6, including groups XII, XIV, XVIII,
and XX, but these are not included in this study due to their appearance in the later
Neolithic/early Bronze Age (Smith 1979). Cluster 2 contains both the South Wales
source and several flint sources, which are split between clusters 2 and 4.
The bar plots in Fig. 7show the frequencies of each axehead group in each cluster,
using the 6-cluster solution as an example. Axeheads in the Othergroup make up
between 20.7% (cluster 4) and 49.86% (cluster 5) of each cluster, compared to an
overall proportion of 30.4% (Table 1). The large number of Otheraxeheads in cluster
5 is mostly composed of ungrouped greenstone axeheads, which might be unidentified
members of group I, the most numerous of the Cornish greenstone types.
The relative numbers of the different axehead groups in cluster 2 most closely match
the relative numbers in the overall sample shown in Table 1(p= 0.0358). All other
clusters are very different from this distribution, as would be expected, given that the k-
means process clusters areas of neighbouring raster cells whose axehead findspots
exhibit similar proportions of stone types and that we would expect axeheads to cluster
around their sources. The separation of sources in the k-means regions might indicate
something about the structure of the Neolithic axehead distribution system.
Fig. 5 Group VIII. Details as Fig. 3
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British Neolithic Axehead Distributions and Their Implications
Inferred Population from Radiocarbon Dates and Axehead Intensity
Figure 8compares the summed probability distributions (SPD) for three dated sources
of hard-stone axeheads and ten dated sources of flint, using anthropogenic radiocarbon
dates collected as part of the NEOMINE project (see Edinborough et al. 2019). These
dates are each compared with an SPD made up of dates found within a 1-km hinterland
of each axehead of each type, with hinterlands merged when axeheads were found in
close proximity so that dates are counted only once for each plot. All SPDs are made up
of an envelope of dates created by sampling no more than 5 dates per site, in order to
limit the effects of oversampling of certain sites, such as Grimes Graves. This sampling
was repeated 1000 times for sources and 100 times for axehead hinterlands to produce
95% envelopes around these estimates. The resulting plot suggests that the period of
peak intensity was actually slightly earlier for flint, between 4000 and 3700 BCE, than
for stone, which peaked between 3900 and 3600 BCE.
We can plot the 6-cluster k-means regions onto a density map of radiocarbon dates
from 4100 to 3400 BCE (n= 1550, Fig. 9). There are similarities and differences
Fig. 6 Flint. The source points include mines and quarries with early Neolithic dates, plus a point in East
Anglia which is placedat the centre of the area of overall maximum flint density. This point happens to be only
16.5 km southwest of Grimes Graves
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Schauer et al.
between the date and axehead density plots: the largest area of high date intensity
corresponds with the southern and western parts of cluster 2, an area into which the
distribution for every axehead group extends (Figs. 2b,3b,4b,5b,and6b). However,
the high flint concentrations in Norfolk (see Fig. 6b) correspond with an area of very
low population density during this period (cluster 4). Table 2provides a summary of
modelling the degree to which the density of axehead finds covaries with the density of
Early Neolithic radiocarbon dates (the latter being adopted as a population proxy; see
Fig. 7 K-means plots, with counts of the different stone macro-groups per cluster and alternative divisions
using different cluster counts. As explained in the text, the clusters are created by grouping together all map
cells that have similar proportions of the various stone groups. When mapped, these clusters form spatially
coherent regions. The bar charts show the counts of the different stone groups in each cluster region
Fig. 8 Stone versus flint. Mine SPD formed by sampling, no more than 5 dates per site 1000 times, and
hinterland SPD formed by sampling dates within 1 km of each axehead, no more than 5 dates per site, 100
times. Only axeheads from dated quarries are included in the stone sample
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British Neolithic Axehead Distributions and Their Implications
also the distribution of long barrows: Darvill 2016: Fig.1A). There is a significant
negative relationship in clusters 1 (Cumbria/southern Scotland) and 4 (Norfolk), such
that areas with higher numbers of dates are not those with higher numbers of axehead
finds. This is unsurprising for Cumbria as an agriculturally more marginal zone in an
area of axehead production, but is more surprising for Norfolk, where the low, open
landscape contains few obstacles to settlement. In contrast, there are also significant
positive relationships in all other clusters, where areas with large numbers of dates
generally correspond with many axehead finds.
Fig. 9 aRadiocarbon date density (excluding mine dates) (points) and bEarly Neolithic enclosures (open
circles) (Oswald et al. 2001), with the k-means boundaries added
Table 2 Modelled covariances (within each k-means region and overall) between axehead findspot densities
and kernel density surfaces of (a) radiocarbon dates and (b) Neolithic enclosures. Z-scores suggest the strength
and direction of covariance while asterisks indicate significance at *0.05, **0.01, and ***0.001 levels
K-means region Axehead
date counts
(axeheads ~
Z-score (axeheads
~ enclosures)
1 (Cumbria/southern Scotland) 550 88 6.7519*** 5 9.5602***
2 (Wessex/South Wales) 1727 802 16.4106*** 46 10.3449***
3 (North Wales) 186 59 7.0248*** 1 6.5786***
4 (Norfolk/south-east) 1319 207 6.9884*** 22 1.6324
5 (Cornwall) 347 98 4.5512*** 18 5.7721***
6 (Midlands/Yorkshire/southern
Scotland/Isle of Man)
1624 273 20.1131*** 9 14.3838***
All regions combined 5809 1550 14.767*** 101 12.458***
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Schauer et al.
Table 2also summarises the same kind of comparison between axehead findspot
densities and Neolithic enclosure densities. There is a particular concentration of
enclosures in cluster 2 (Wessex and South Wales have 46 of the 101 mapped examples,
all but a handful of them in Wessex) and very significant positive correlations with
axehead findspot densities in all areas except cluster 5 (Cornwall), where the relation-
ship is strongly negative, and cluster 4 (Norfolk), where it is not significant. Depending
on how we interpret the role of the enclosures themselves, this patterning is interesting
either as another indication of higher populations (where enclosures are common) or as
pointing to a special role for enclosures in exchange systems, such that people closer to
enclosures had a higher probability of obtaining non-local axeheads. The role of
enclosures in long-distance gathering and exchange has, of course, long been
recognised, highlighted by their associations with axeheads, ceramics, and even indi-
viduals derived from distant origins (e.g. Peacock 1969; Evans et al. 1988; Whittle et al.
As noted in the Methodssection, we can also keep observed axehead findspots
constant but simulate a hypothetical macro-group for each axehead, based on a series of
increasingly complex models of likely supply and demand. The observed (Simpson)
diversity of different axehead materials from each cluster region can then be compared
to the simulation for goodness-of-fit. Table 3summaries the results for three such
simulation models: in model 1, each axehead find is assigned a new stone macro-group
completely atrandom. For model 2, the simulation selects a stone macro-group for each
axehead findspot that is conditioned on how far it is from each macro-group source (an
average, constant model of decay as expressed by the dashed line in Fig. 2a). For model
3, the simulation imposes a specific distance decay curve derived from the observed
distance model of each stone source (i.e. the dotted lines in Figs. 2a,3a,4a,5a,and6a).
For all three models, we only consider diversity in the counts of I, VI, VII, VIII, and
flint, excluding both Otherand smaller groups within each region listed in Table 1.
The results show that model 3 is by far the best fit to the data, with simulated diversity
closely matching observed diversity in the majority of cluster regions. For example, the
cluster region with the lowest observed and simulated diversity is Cumbria (cluster 1),
which is dominated by group VI Langdale axeheads (Fig. 7, bar plot 1), while the
greatest diversity is found in Wessex and South Wales (cluster 2). However, there
remain certain discrepancies and Fig. 10 therefore shows the result of regressing the
model 3 residuals against the median radiocarbon date intensity for each cluster region.
There is a good overall correlation (r2=0.56), which implies that, above and beyond
the parameters used in model 3, higher population densities in a region are predictive of
yet higher diversity in axehead materials.
A final possibility that we now consider is whether the distribution of axeheads from
the different sources may be related to other cultural patterns. Pioffet (2014) has argued
persuasively that early pottery styles in southern Britain can be divided into at least two
groups based on differences in technical complexity and variation: style I-1a found in
the east and style I-2a found in the west (Fig. 11). Similarities between these styles and
pottery found in Europe indicate that there were two near simultaneous but separate in-
migrations of people, with one western group arriving primarily from Brittany and
another eastern group arriving from Pas-de-Calais/West Flanders (Sheridan 2010).
These also represent geologically distinct zones on either side of the channel with the
hard-stone resources and landscapes of the Armorican massif (of Hercynian orogeny)
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British Neolithic Axehead Distributions and Their Implications
Table 3 Simpson diversity indices for each cluster, as calculated for the observed data and for each of the three simulation models (see the Methodssection for details of the three
models). Also provided here is a measure of the median radiocarbon intensity within each region
K-means region 1 (Cumbria/southern
2 (Wessex/
South Wales)
3 (North Wales) 4 (Norfolk/south-east) 5 (Cornwall) 6 (Midlands/Yorkshire/southern
Scotland/Isle of Man)
Observed regional
0.0334 0.7041 0.445 0.3632 0.5917 0.5121
Model 1
(uniform supply) diversity
0.798 0.7993 0.7935 0.7992 0.7909 0.7993
Model 2
(supply by distance) diversity
0.387 0.5188 0.6154 0.0484 0.5863 0.6656
Model 3
(uneven supply by distance)
0.1051 0.5868 0.5943 0.3416 0.5499 0.4556
Median 14C intensity 2.53E 09 8.83E 09 3.57E 09 5.77E 09 4.48E 09 4.23E 09
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Schauer et al.
linked to similar ones in the English south-west, while the flint-rich Upper Cretaceous
chalk deposits of south-eastern England are much closer to the landscapes and flint-
Fig. 10 Regression of Simpson diversity index residuals for simulated axehead types against the median
density of dates in each region (r2=0.56)
Fig. 11 Neolithic pottery style zones: pottery style zones and east/west distinctions (a) 39003650 BCE and
(b) 36503200 BCE (after Pioffet 2014:figs.6.14-5)
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British Neolithic Axehead Distributions and Their Implications
mining areas of neighbouring Normandy and southern Belgium (Mortimore 2012;
Collin 2016; Dijkstra and Hatch 2018). Settler communities therefore could have
moved to nearby locations with similar geological and ecological profiles, as well as
similar axehead raw materials, with the western half exploiting hard-stone sources in
Cornwall, Wales, and Cumbria and the eastern half exploiting flint from Sussex and
Norfolk (cf. Edinborough et al. 2019), though it has also been suggested that Langdale
was associated with this tradition. In any case, there is no indication that these different
putative cultural ancestries resulted in a barrier to axehead exchange. On the contrary,
as we have seen, group I axeheads from Cornwall occur far more frequently in
southeast England than we would expect and there are concentrations of group VI
axeheads in east Yorkshire and Lincolnshire.
The application of our updated spatial analysis methods has enabled us to draw new
conclusions concerning the factors affecting the distribution of axeheads from different
sources, and to characterise them with greater rigour through the testing of different
models. In summary, our overall results suggest the impact of both supply and demand
factors affecting the distribution of Neolithic axeheads. The k-means cluster analysis
and comparative inspection of the 2D distributions of the products of the different
sources show that areas adjacent to a major hard-stone source are always dominated by
that source and tend to exclude other materials; for example, there are far fewer group
VI axeheads in North Wales than its distance fall-off would predict.
Yet simple proximity to nearby sources cannot fully explain the pattern of Neolithic
axehead materials that we observe in different parts of southern Britain, since the fitted
fall-offs of different axehead sources exhibit distinctly different curves, suggesting that
certain stone types were far more popular than others and travelled more widely,
especially groups I and VI. In contrast, this is not the case with flint, whose density
further away from its sources is lower than predicted. In fact, the local availability of
flint, and even flint mines, does not exclude the widespread occurrence of group I
axeheads in southern England in the way that group VII excludes group VI in North
Wales. The highest relative density of flint axeheads is greatest in East Anglia, furthest
away from the group I and group VI sources; there is no zone of higher relative flint
density around the southern English flint mines. The reasons why certain types
travelled far more widely are not clear but one reason for the differences may be
variation in the mechanical properties of the rock (cf. Pitts 1996). Thus, a study of the
distribution of greenstone axeheads used by aboriginal groups in Australia showed that
greenstone from the Mt William quarry, average travel distance > 200 km, maximum >
800 km, had greater elasticity and fracture toughness than green stone from the
Berrambool quarry, average travel distance ~ 100 km, maximum < 300 km (Domanski
et al. 1994).
Of course, axehead findspots are places of final deposition for objects that may have
had extended use-lives and multiple owners, so some of the variability we observe may
have been introduced by complex axehead biographies. A flint axehead broken far
from a source of raw materials might be reshaped into other implements and thereby
vanish from the record (Pitts 1996, p. 325). However, it is striking that we can account
for a high degree of the variability in the density and diversity of axehead materials
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Schauer et al.
across different regions of southern Britain by joint modelling of particular fall-off
profiles for each source and of local demand pools provided by particularly dense areas
of Early Neolithic settlement, as in central southern England. This region had the
greatest diversity of axeheads, confirming earlier findings which relate increased
axehead diversity to increased distance from source (Darvill 1989).
The significance of causewayed enclosures as monuments constructed and used by
groups with long-distance exchange links, as supported by evidence of imported
artefacts and materials found within them, is also affirmed by their spatial relationships
with axehead distributions. The relationship between the density of flint and pottery
finds at enclosures and their proximity to flint sources has been previously observed
(e.g. Davis and Sharples 2017, Table 2), but our results emphasise the additional
importance of differences in regional population density. We would therefore expect
not only more enclosures in central southern England, but also for those enclosures to
have a more diverse range of stone artefacts than enclosures in other regions.
Although Early Neolithic immigration seems to have come from two different
regions of continental northwest Europe, this does not seem to have affected the
distribution of hard-stone axeheads.
These conclusions will clearly require further attention with fresh data in the same
study area (as is currently being collected by the IPG, for example) or for analogous
regions elsewhere in Europe, but point to some of the factors influencing supply-and-
demand in the British Early Neolithic.
Acknowledgments We are grateful to The Leverhulme Trust for Grant RPG-2015-199, for the project
Supply and demand in prehistory? Economics of Neolithic mining in NW Europe,that made the project
possible, to Gabriel Cooney for Irish axehead data, and to Frances Healy and Barry Bishop for information
about axeheads and flint sources in East Anglia. We used the R statistical environment for all analysis (R
Development Core Team 2008), especially the spatstat (Baddeley et al. 2015) and rcarbon (Bevan and Crema
2018) packages.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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... The second project directly dated archival material from mining and quarrying sites that were thought to date from the start of the Neolithic in Britain and continental north-west Europe (6500-1500 cal bc: Schauer et al. 2019b;2019a;Edinborough et al. 2020). The goal here was to determine if stone axes (the primary products of mines and quarries) were in increased demand for clearing forest during the economic change to agriculture at this time, and, if so, precisely when this occurred. ...
... 21 Or puzzle. 22 Detailing the premises for the mathematical models that this project relies on is out of the scope of this chapter (but see Schauer et al. 2019a). ...
Narrative Science examines the use of narrative in scientific research over the last two centuries. It brings together an international group of scholars who have engaged in intense collaboration to find and develop crucial cases of narrative in science. Motivated and coordinated by the Narrative Science project, funded by the European Research Council, this volume offers integrated and insightful essays examining cases that run the gamut from geology to psychology, chemistry, physics, botany, mathematics, epidemiology, and biological engineering. Taking in shipwrecks, human evolution, military intelligence, and mass extinctions, this landmark study revises our understanding of what science is, and the roles of narrative in scientists' work. This title is also available as Open Access.
... Chronologies for Neolithic flint mining in Europe were until recently broad and imprecise, relying largely on historic radiocarbon dates with broad standard deviations, or dates obtained from bulk samples of charcoal (Whittle et al. 2011, 257). A recently completed project led by Stephen Shennan (Schauer et al. 2019a;2019b;Edinborough et al. 2020) has attempted to determine the main phases of Neolithic mining in northwest Europe. They have ascertained that there are two such phases of mining at c.4200-3800 cal BC and 3500-2900 cal BC (Schauer et al. 2019a, 158), with the first phase taking place around the same time as the expansion of farming from northern France and Belgium (Crombé et al. 2020, 1). ...
... It has been proposed that the flint extracted from mines was used to manufacture axes for forest clearance during the primary phase of land cultivation at the beginning of the Neolithic, a view which seems to be increasingly supported through new dates on the beginnings of agriculture (Sørensen and Karg 2014;Gron and Sørensen 2018;Schauer et al. 2019a;Edinborough et al. 2020). Therefore, flint mines are likely to correspond with the wider European technological developments associated with the adoption of pastoralism and agriculture (Schauer et al. 2019b). An increasing number of studies indicate that the migration of people prompted this spread of Neolithic subsistence strategies in northern Europe (for an overview, see Shennan 2018;Brace et al. 2019;Gron et al. 2020) and that sea travel may have played an important role in the adoption of ideas such as earthen long barrows (Rassmann 2010) and megalith building (Schulz Paulsson 2019). ...
Neolithic flint mines across northern Europe during the transition between the fifth and fourth millennia BC show similarities in their dating, extraction methods and morphology, as do contemporary forms of monumentality such as causewayed enclosures, earthen long barrows and megalithic tombs during this period. Recent research has identified further similarities in the expressions of art motifs within the mines. While certainly found during different excavations, most of these motifs incised in chalk have not been reported on. Following archival analysis, this paper details these similarities in motifs that extend between sites in the UK, Denmark, Belgium and potentially Poland, and perhaps increasingly over time to other, non-mining, sites. We argue that the practice of flint mining and incising of art motifs may indicate shared specific cultural beliefs at the beginning of the Neolithic in northern Europe that have not been previously recognized.
... En este sentido, la utilización de Sistemas de Información Geográfica (SIG) supone uno de los grandes problemas. Si bien por un lado puede ser utilizados solo con fines ilustrativos o contextuales, por otro lado, el uso de modelización espacial en Arqueología para la construcción de modelos explicativos tiene hoy en día una tradición sólida, tanto en el ámbito peninsular como fuera de él (entre otros, bevan, 2015;isern et al., 2014;sChauer et al., 2020;snitker et al., 2018). Algo similar ocurre con la modelización matemática. ...
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La aplicación de la computación en Humanidades en la última década se ha consolidado como una disciplina clave para el estudio de los procesos históricos desde numerosas vertientes siendo necesaria la utilización de diferentes softwares y lenguajes para la elaboración de dichas aproximaciones y el posterior tratamiento de los resultados. No obstante, son muchos los trabajos que carecen de transparencia (acceso a los datos y código) por lo que se hace imposible su reproducción por otros equipos de investigación. Por ello, en este documento se realiza una revisión de los trabajos publicados en revistas peninsulares para evaluar el grado de transparencia de la comunidad computacional hispano-lusa. The last decade has seen the consolidation of Computational Archaeology and the Digital Humanities as key disciplines in the multifaceted study of historical processes. In this regard, the use of different software packages or programming languages for data analysis has notably increased among archaeologists. However, in many cases open research protocols are not fully observed (when access to data and code are not always granted), which makes reproducibility impossible for other research groups. The present article reviews the transparency of works published in the most important journals of the Iberian Peninsula, to evaluate the degree of openness within the Iberian research community.
... The prevailing view concerning the 'Neolithisation' of Britain involves an influx of migrants from continental Europe towards the end of the 5 th millennium cal BC (Cummings, Morris, 2018;Brace et al. 2019), who brought with them a developed agro-pastoral regime, potting traditions, and an advanced know-how for extracting lithic raw materials and their exchange over great distances (Miles 2016;Sheridan 2010; see also Edinborough et al. 2020;Schauer et al. 2020). While evidence for pre-Neolithic contact between continental farmers and British hunter-gatherers suggested to some that farming spread through the island via processes of acculturation, genetic studies indicate that ultimately the sites made-up of clusters of round or oval pits containing pottery, worked and burnt flint, and charred plant remains inter alia (Garrow 2006). ...
Full-text available
Current models view southeast England as where Neolithic lifeways were first introduced to Britain from continental Europe c. 4000 cal BC, however, there has been little work detailing this process in coastal East Anglia. In 2019, work at the Freston causewayed enclosure provided the first view of a major gathering space associated with semi-mobile farming communities of the Early Neolithic in the county of Suffolk and located on a major estuary close to the North Sea. Excavation produced a rich assemblage of worked flint and Mildenhall Ware pottery (potentially for feasting), plus evidence for the consumption of cereals and hazelnuts.
... While the methodology here is applicable for prehistoric research more broadly, it may be most keenly felt within Mesolithic Studies, where a concerted effort by contemporary researchers is being made to move on from the abstract modelling and generalisation of previous generations, to more nuanced and specific social histories of the period [66][67][68] . For the Neolithic, this increased resolution towards the procurement of flint may perhaps place the distribution, trade, and exchange of objects such as axes 58,59,69,70 in greater context, as well as help towards a more granular understanding of mobility for the period 71 . ...
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It is 50 years since Sieveking et al. published their pioneering research in Nature on the geochemical analysis of artefacts from Neolithic flint mines in southern Britain. In the decades since, geochemical techniques to source stone artefacts have flourished globally, with a renaissance in recent years from new instrumentation, data analysis, and machine learning techniques. Despite the interest over these latter approaches, there has been variation in the quality with which these methods have been applied. Using the case study of flint artefacts and geological samples from England, we present a robust and objective evaluation of three popular techniques, Random Forest, K-Nearest-Neighbour, and Support Vector Machines, and present a pipeline for their appropriate use. When evaluated correctly, the results establish high model classification performance, with Random Forest leading with an average accuracy of 85% (measured through F1 Scores), and with Support Vector Machines following closely. The methodology developed in this paper demonstrates the potential to significantly improve on previous approaches, particularly in removing bias, and providing greater means of evaluation than previously utilised.
... This is a good estimate to describe the intensity of the whole population of points, but when exploring a subset of marked points such as features affected by human activities, a more accurate approach is the ratio-based density estimation known as 'relative risk surface' [29]. This case-control approach is usually adopted in epidemiological studies when investigating areas more at risk of an infectious disease, based on the underlying at risk population [30][31][32][33][34]. In our case, the population at risk is the whole array of archaeological features mapped from the satellite imagery, as they are all potentially at risk of being damaged or affected by the threats considered in this study. ...
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Growing digital documentation of cultural heritage resources yielded from an increasing number of international projects, calls for the development of formal computational approaches to assess the risks that this invaluable material heritage is exposed to. This paper proposes a nuanced case-control approach to the risk assessment developed by the Central Asian Archaeological Landscape (CAAL) project for an area in southern Tajikistan. A number of statistical methods are applied for the spatial modelling of the risk to the cultural heritage across the study area and for the assessment of the local scenarios of potential archaeological features already affected by natural and human threats. The value of this formal approach is in its flexible applicability to diverse regional and national settings, as well as in its capability of being updated and repeated within the same territory. This provides local stakeholders, heritage professionals, and local authorities, with a useful tool to develop a risk management plan that includes quantitative as well as qualitative spatial assessments.
We show that the creation of the first integrated multi-modal pan-European transport network during Roman times influences economic integration over two millennia. Drawing on spatially highly disaggregated data on excavated Roman ceramics, we document that contemporary interregional trade was influenced by connectivity within the network. Today, these connectivity differentials continue to influence integration as approximated by cross-regional firm investment behaviour. Continuity is partly explained by selective infrastructure routing and cultural integration due to bilateral convergence in preferences and values. We show that our results are Roman-connectivity specific and do not reflect pre-existing patterns of exchange using pre-Roman trade data.
The authors of this article consider the relationship in European prehistory between the procurement of high-quality stones (for axeheads, daggers, and other tools) on the one hand, and the early mining, crafting, and deposition of copper on the other. The data consist of radiocarbon dates for the exploitation of stone quarries, flint mines, and copper mines, and of information regarding the frequency through time of jade axeheads and copper artefacts. By adopting a broad perspective, spanning much of central-western Europe from 5500 to 2000 bc , they identify a general pattern in which the circulation of the first copper artefacts was associated with a decline in specialized stone quarrying. The latter re-emerged in certain regions when copper use decreased, before declining more permanently in the Bell Beaker phase, once copper became more generally available. Regional variations reflect the degrees of connectivity among overlapping copper exchange networks. The patterns revealed are in keeping with previous understandings, refine them through quantification and demonstrate their cyclical nature, with additional reference to likely local demographic trajectories.
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New radiocarbon dating and chronological modelling have refined understanding of the character and circumstances of flint mining at Grime's Graves through time. The deepest, most complex galleried shafts were worked probably from the third quarter of the 27th century cal bc and are amongst the earliest on the site. Their use ended in the decades around 2400 cal bc, although the use of simple, shallow pits in the west of the site continued for perhaps another three centuries. The final use of galleried shafts coincides with the first evidence of Beaker pottery and copper metallurgy in Britain. After a gap of around half a millennium, flint mining at Grime's Graves briefly resumed, probably from the middle of the 16th century cal bc to the middle of the 15th. These 'primitive' pits, as they were termed in the inter-war period, were worked using bone tools that can be paralleled in Early Bronze Age copper mines. Finally, the scale and intensity of Middle Bronze Age middening on the site is revealed, as it occurred over a period of probably no more than a few decades in the 14th century cal bc. The possibility of connections between metalworking at Grime's Graves at this time and contemporary deposition of bronzes in the nearby Fens is discussed.
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Lamprophyres represent hydrous alkaline mantle melts that are a unique source of information about the composition of continental lithosphere. Throughout southwest Britain, post-Variscan lamprophyres are (ultra)potassic with strong incompatible element enrichments. Here we show that they form two distinct groups in terms of their Sr and Nd isotopic compositions, occurring on either side of a postulated, hitherto unrecognized terrane boundary. Lamprophyres emplaced north of the boundary fall on the mantle array with εNd -1 to +1.6. Those south of the boundary are enriched in radiogenic Sr, have initial εNd values of -0.3 to -3.5, and are isotopically indistinguishable from similar-aged lamprophyres in Armorican massifs in Europe. We conclude that an Armorican terrane was juxtaposed against Avalonia well before the closure of the Variscan oceans and the formation of Pangea. The giant Cornubian Tin-Tungsten Ore Province and associated batholith can be accounted for by the fertility of Armorican lower crust and mantle lithosphere.
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The nature of landscape use and residence patterns during the British earlier Neolithic has often been debated. Here we use strontium and oxygen isotope analysis of tooth enamel, from individuals buried at the Hambledon Hill causewayed enclosure monument complex in Dorset, England to evaluate patterns of landscape use during the earlier Neolithic. Previous analysis suggests that a significant proportion of the artefacts found at the site may originate from lithology of Eocene and Upper to Middle Jurassic age that the enclosures overlook to the immediate west and south. The excavators therefore argued that the sector of landscape visible from Hambledon Hill provides an approximate index for the catchment occupied by the communities that it served. Most of the burial population exhibit isotope ratios that could be consistent with this argument. Connections between Hambledon Hill and regions much further afield are also hypothesised, based on the presence of artefacts within the assemblage that could have been sourced from lithology in Somerset, Devon, and Cornwall in south-west England. However, few of the sampled individuals have strontium isotope ratios consistent with having obtained the majority of their diet from such areas during childhood. The individuals who exhibit the highest strontium isotope ratios are all adult males, whom the excavators suggest to have died during one or more episodes of conflict, following the burning and destruction of surrounding defensive outworks built during the 36th century bc . At least one of these individuals, who was found with an arrowhead amongst his ribs, did not obtain his childhood diet locally and has ⁸⁷ Sr/ ⁸⁶ Sr values that could be comparable to those bioavailable in the south-west peninsula.
New radiocarbon ( ¹⁴ C) dates suggest a simultaneous appearance of two technologically and geographically distinct axe production practices in Neolithic Britain; igneous open-air quarries in Great Langdale, Cumbria, and from flint mines in southern England at ~4000–3700 cal BC. In light of the recent evidence that farming was introduced at this time by large-scale immigration from northwest Europe, and that expansion within Britain was extremely rapid, we argue that this synchronicity supports this speed of colonization and reflects a knowledge of complex extraction processes and associated exchange networks already possessed by the immigrant groups; long-range connections developed as colonization rapidly expanded. Although we can model the start of these new extraction activities, it remains difficult to estimate how long significant production activity lasted at these key sites given the nature of the record from which samples could be obtained.
The extent to which non-agricultural production in prehistory had cost-benefit motivations has long been a subject of discussion. This paper addresses the topic by looking at the evidence for Neolithic quarrying and mining in Britain and continental northwest Europe and asks whether changing production through time was influenced by changing demand. Radiocarbon dating of mine and quarry sites is used to define periods of use. These are then correlated with a likely first-order source of demand, the size of the regional populations around the mines, inferred from a radiocarbon-based population proxy. There are significant differences between the population and mine-date distributions. Analysis of pollen data using the REVEALS method to reconstruct changing regional land cover patterns shows that in Britain activity at the mines and quarries is strongly correlated with evidence for forest clearance by incoming Neolithic populations, suggesting that mine and quarry production were a response to the demand that this created. The evidence for such a correlation between mining and clearance in continental northwest Europe is much weaker. Here the start of large-scale mining may be a response to the arrival by long-distance exchange of high-quality prestige jade axes from a source in the Italian Alps.
Made from outcrops of fine-grained volcanic tuff, Langdale axes (Group VI) are the most numerous and widely distributed Neolithic axes found in the British Isles. Transported great distances from Cumbria, concentrations have been found in eastern England, the Midlands and along the Thames valley. Many researchers have considered this widespread distribution of axes, with exchange generally favoured as the means by which the artefacts moved. A range of economic, social and political models for exchange have been proposed, with values ascribed to the axes as tools, tokens of individual identity, representations of community cohesion, prestige objects, symbols of power, ceremonial and ritualistic artefacts - the functional and symbolic frequently blurred. However, despite the extensive research, it remains unclear why great numbers of these axes were moved over such long distances. Landscape-scale GIS viewshed modelling and observational work in the field emphasised the unusual visibility of Pike o' Stickle, the Langdale Fell where the bulk of raw material for Group VI axes was extracted. Experiential fieldwork also highlighted the powerful material agency of the mountain and confirmed the physical challenges associated with reaching the quarries. With remoteness, wide visibility and material agency, Pike o' Stickle displays key characteristics of a sacred landscape. Taking account of the evidence for special treatment of Langdale axes at deposition, the concept of pilgrimage is explored.